diff --git a/python/CODING_STANDARD.md b/python/CODING_STANDARD.md index 1b7b2726b8..d5f9d6f150 100644 --- a/python/CODING_STANDARD.md +++ b/python/CODING_STANDARD.md @@ -55,8 +55,8 @@ Prefer attributes over inheritance when parameters are mostly the same: # ✅ Preferred - using attributes from agent_framework import ChatMessage -user_msg = ChatMessage(role="user", content="Hello, world!") -asst_msg = ChatMessage(role="assistant", content="Hello, world!") +user_msg = ChatMessage("user", ["Hello, world!"]) +asst_msg = ChatMessage("assistant", ["Hello, world!"]) # ❌ Not preferred - unnecessary inheritance from agent_framework import UserMessage, AssistantMessage diff --git a/python/README.md b/python/README.md index 06eca19999..74d7052c12 100644 --- a/python/README.md +++ b/python/README.md @@ -113,8 +113,8 @@ async def main(): client = OpenAIChatClient() messages = [ - ChatMessage(role="system", text="You are a helpful assistant."), - ChatMessage(role="user", text="Write a haiku about Agent Framework.") + ChatMessage("system", ["You are a helpful assistant."]), + ChatMessage("user", ["Write a haiku about Agent Framework."]) ] response = await client.get_response(messages) diff --git a/python/packages/a2a/agent_framework_a2a/_agent.py b/python/packages/a2a/agent_framework_a2a/_agent.py index 00e045fba6..4dd89c6f02 100644 --- a/python/packages/a2a/agent_framework_a2a/_agent.py +++ b/python/packages/a2a/agent_framework_a2a/_agent.py @@ -32,7 +32,6 @@ BaseAgent, ChatMessage, Content, - Role, normalize_messages, prepend_agent_framework_to_user_agent, ) @@ -187,7 +186,7 @@ async def __aexit__( async def run( self, - messages: str | ChatMessage | Sequence[str | ChatMessage] | None = None, + messages: str | Content | ChatMessage | Sequence[str | Content | ChatMessage] | None = None, *, thread: AgentThread | None = None, **kwargs: Any, @@ -210,11 +209,11 @@ async def run( """ # Collect all updates and use framework to consolidate updates into response updates = [update async for update in self.run_stream(messages, thread=thread, **kwargs)] - return AgentResponse.from_agent_run_response_updates(updates) + return AgentResponse.from_updates(updates) async def run_stream( self, - messages: str | ChatMessage | Sequence[str | ChatMessage] | None = None, + messages: str | Content | ChatMessage | Sequence[str | Content | ChatMessage] | None = None, *, thread: AgentThread | None = None, **kwargs: Any, @@ -245,7 +244,7 @@ async def run_stream( contents = self._parse_contents_from_a2a(item.parts) yield AgentResponseUpdate( contents=contents, - role=Role.ASSISTANT if item.role == A2ARole.agent else Role.USER, + role="assistant" if item.role == A2ARole.agent else "user", response_id=str(getattr(item, "message_id", uuid.uuid4())), raw_representation=item, ) @@ -269,7 +268,7 @@ async def run_stream( # Empty task yield AgentResponseUpdate( contents=[], - role=Role.ASSISTANT, + role="assistant", response_id=task.id, raw_representation=task, ) @@ -421,7 +420,7 @@ def _parse_messages_from_task(self, task: Task) -> list[ChatMessage]: contents = self._parse_contents_from_a2a(history_item.parts) messages.append( ChatMessage( - role=Role.ASSISTANT if history_item.role == A2ARole.agent else Role.USER, + role="assistant" if history_item.role == A2ARole.agent else "user", contents=contents, raw_representation=history_item, ) @@ -433,7 +432,7 @@ def _parse_message_from_artifact(self, artifact: Artifact) -> ChatMessage: """Parse A2A Artifact into ChatMessage using part contents.""" contents = self._parse_contents_from_a2a(artifact.parts) return ChatMessage( - role=Role.ASSISTANT, + role="assistant", contents=contents, raw_representation=artifact, ) diff --git a/python/packages/a2a/tests/test_a2a_agent.py b/python/packages/a2a/tests/test_a2a_agent.py index eca97b2ac6..cbbb16fd63 100644 --- a/python/packages/a2a/tests/test_a2a_agent.py +++ b/python/packages/a2a/tests/test_a2a_agent.py @@ -25,7 +25,6 @@ AgentResponseUpdate, ChatMessage, Content, - Role, ) from agent_framework.a2a import A2AAgent from pytest import fixture, raises @@ -129,7 +128,7 @@ async def test_run_with_message_response(a2a_agent: A2AAgent, mock_a2a_client: M assert isinstance(response, AgentResponse) assert len(response.messages) == 1 - assert response.messages[0].role == Role.ASSISTANT + assert response.messages[0].role == "assistant" assert response.messages[0].text == "Hello from agent!" assert response.response_id == "msg-123" assert mock_a2a_client.call_count == 1 @@ -144,7 +143,7 @@ async def test_run_with_task_response_single_artifact(a2a_agent: A2AAgent, mock_ assert isinstance(response, AgentResponse) assert len(response.messages) == 1 - assert response.messages[0].role == Role.ASSISTANT + assert response.messages[0].role == "assistant" assert response.messages[0].text == "Generated report content" assert response.response_id == "task-456" assert mock_a2a_client.call_count == 1 @@ -170,7 +169,7 @@ async def test_run_with_task_response_multiple_artifacts(a2a_agent: A2AAgent, mo # All should be assistant messages for message in response.messages: - assert message.role == Role.ASSISTANT + assert message.role == "assistant" assert response.response_id == "task-789" @@ -233,7 +232,7 @@ def test_parse_messages_from_task_with_artifacts(a2a_agent: A2AAgent) -> None: assert len(result) == 2 assert result[0].text == "Content 1" assert result[1].text == "Content 2" - assert all(msg.role == Role.ASSISTANT for msg in result) + assert all(msg.role == "assistant" for msg in result) def test_parse_message_from_artifact(a2a_agent: A2AAgent) -> None: @@ -252,7 +251,7 @@ def test_parse_message_from_artifact(a2a_agent: A2AAgent) -> None: result = a2a_agent._parse_message_from_artifact(artifact) assert isinstance(result, ChatMessage) - assert result.role == Role.ASSISTANT + assert result.role == "assistant" assert result.text == "Artifact content" assert result.raw_representation == artifact @@ -296,7 +295,7 @@ def test_prepare_message_for_a2a_with_error_content(a2a_agent: A2AAgent) -> None # Create ChatMessage with ErrorContent error_content = Content.from_error(message="Test error message") - message = ChatMessage(role=Role.USER, contents=[error_content]) + message = ChatMessage("user", [error_content]) # Convert to A2A message a2a_message = a2a_agent._prepare_message_for_a2a(message) @@ -311,7 +310,7 @@ def test_prepare_message_for_a2a_with_uri_content(a2a_agent: A2AAgent) -> None: # Create ChatMessage with UriContent uri_content = Content.from_uri(uri="http://example.com/file.pdf", media_type="application/pdf") - message = ChatMessage(role=Role.USER, contents=[uri_content]) + message = ChatMessage("user", [uri_content]) # Convert to A2A message a2a_message = a2a_agent._prepare_message_for_a2a(message) @@ -327,7 +326,7 @@ def test_prepare_message_for_a2a_with_data_content(a2a_agent: A2AAgent) -> None: # Create ChatMessage with DataContent (base64 data URI) data_content = Content.from_uri(uri="data:text/plain;base64,SGVsbG8gV29ybGQ=", media_type="text/plain") - message = ChatMessage(role=Role.USER, contents=[data_content]) + message = ChatMessage("user", [data_content]) # Convert to A2A message a2a_message = a2a_agent._prepare_message_for_a2a(message) @@ -341,7 +340,7 @@ def test_prepare_message_for_a2a_with_data_content(a2a_agent: A2AAgent) -> None: def test_prepare_message_for_a2a_empty_contents_raises_error(a2a_agent: A2AAgent) -> None: """Test _prepare_message_for_a2a with empty contents raises ValueError.""" # Create ChatMessage with no contents - message = ChatMessage(role=Role.USER, contents=[]) + message = ChatMessage("user", []) # Should raise ValueError for empty contents with raises(ValueError, match="ChatMessage.contents is empty"): @@ -360,7 +359,7 @@ async def test_run_stream_with_message_response(a2a_agent: A2AAgent, mock_a2a_cl # Verify streaming response assert len(updates) == 1 assert isinstance(updates[0], AgentResponseUpdate) - assert updates[0].role == Role.ASSISTANT + assert updates[0].role == "assistant" assert len(updates[0].contents) == 1 content = updates[0].contents[0] @@ -408,7 +407,7 @@ def test_prepare_message_for_a2a_with_multiple_contents() -> None: # Create message with multiple content types message = ChatMessage( - role=Role.USER, + role="user", contents=[ Content.from_text(text="Here's the analysis:"), Content.from_data(data=b"binary data", media_type="application/octet-stream"), @@ -465,7 +464,7 @@ def test_prepare_message_for_a2a_with_hosted_file() -> None: # Create message with hosted file content message = ChatMessage( - role=Role.USER, + role="user", contents=[Content.from_hosted_file(file_id="hosted://storage/document.pdf")], ) diff --git a/python/packages/ag-ui/agent_framework_ag_ui/_client.py b/python/packages/ag-ui/agent_framework_ag_ui/_client.py index 74bb50e306..340d2c125f 100644 --- a/python/packages/ag-ui/agent_framework_ag_ui/_client.py +++ b/python/packages/ag-ui/agent_framework_ag_ui/_client.py @@ -334,7 +334,7 @@ async def _inner_get_response( Returns: ChatResponse object """ - return await ChatResponse.from_chat_response_generator( + return await ChatResponse.from_update_generator( self._inner_get_streaming_response( messages=messages, options=options, diff --git a/python/packages/ag-ui/agent_framework_ag_ui/_event_converters.py b/python/packages/ag-ui/agent_framework_ag_ui/_event_converters.py index bd2d989f2a..7b7e99e8d4 100644 --- a/python/packages/ag-ui/agent_framework_ag_ui/_event_converters.py +++ b/python/packages/ag-ui/agent_framework_ag_ui/_event_converters.py @@ -7,8 +7,6 @@ from agent_framework import ( ChatResponseUpdate, Content, - FinishReason, - Role, ) @@ -86,7 +84,7 @@ def _handle_run_started(self, event: dict[str, Any]) -> ChatResponseUpdate: self.run_id = event.get("runId") return ChatResponseUpdate( - role=Role.ASSISTANT, + role="assistant", contents=[], additional_properties={ "thread_id": self.thread_id, @@ -98,7 +96,7 @@ def _handle_text_message_start(self, event: dict[str, Any]) -> ChatResponseUpdat """Handle TEXT_MESSAGE_START event.""" self.current_message_id = event.get("messageId") return ChatResponseUpdate( - role=Role.ASSISTANT, + role="assistant", message_id=self.current_message_id, contents=[], ) @@ -112,7 +110,7 @@ def _handle_text_message_content(self, event: dict[str, Any]) -> ChatResponseUpd self.current_message_id = message_id return ChatResponseUpdate( - role=Role.ASSISTANT, + role="assistant", message_id=self.current_message_id, contents=[Content.from_text(text=delta)], ) @@ -128,7 +126,7 @@ def _handle_tool_call_start(self, event: dict[str, Any]) -> ChatResponseUpdate: self.accumulated_tool_args = "" return ChatResponseUpdate( - role=Role.ASSISTANT, + role="assistant", contents=[ Content.from_function_call( call_id=self.current_tool_call_id or "", @@ -144,7 +142,7 @@ def _handle_tool_call_args(self, event: dict[str, Any]) -> ChatResponseUpdate: self.accumulated_tool_args += delta return ChatResponseUpdate( - role=Role.ASSISTANT, + role="assistant", contents=[ Content.from_function_call( call_id=self.current_tool_call_id or "", @@ -165,7 +163,7 @@ def _handle_tool_call_result(self, event: dict[str, Any]) -> ChatResponseUpdate: result = event.get("result") if event.get("result") is not None else event.get("content") return ChatResponseUpdate( - role=Role.TOOL, + role="tool", contents=[ Content.from_function_result( call_id=tool_call_id, @@ -177,8 +175,8 @@ def _handle_tool_call_result(self, event: dict[str, Any]) -> ChatResponseUpdate: def _handle_run_finished(self, event: dict[str, Any]) -> ChatResponseUpdate: """Handle RUN_FINISHED event.""" return ChatResponseUpdate( - role=Role.ASSISTANT, - finish_reason=FinishReason.STOP, + role="assistant", + finish_reason="stop", contents=[], additional_properties={ "thread_id": self.thread_id, @@ -191,8 +189,8 @@ def _handle_run_error(self, event: dict[str, Any]) -> ChatResponseUpdate: error_message = event.get("message", "Unknown error") return ChatResponseUpdate( - role=Role.ASSISTANT, - finish_reason=FinishReason.CONTENT_FILTER, + role="assistant", + finish_reason="content_filter", contents=[ Content.from_error( message=error_message, diff --git a/python/packages/ag-ui/agent_framework_ag_ui/_message_adapters.py b/python/packages/ag-ui/agent_framework_ag_ui/_message_adapters.py index f8f1623a30..dfa64e9bdb 100644 --- a/python/packages/ag-ui/agent_framework_ag_ui/_message_adapters.py +++ b/python/packages/ag-ui/agent_framework_ag_ui/_message_adapters.py @@ -9,7 +9,6 @@ from agent_framework import ( ChatMessage, Content, - Role, prepare_function_call_results, ) @@ -269,7 +268,7 @@ def _update_tool_call_arguments( def _find_matching_func_call(call_id: str) -> Content | None: for prev_msg in result: - role_val = prev_msg.role.value if hasattr(prev_msg.role, "value") else str(prev_msg.role) + role_val = prev_msg.role if hasattr(prev_msg.role, "value") else str(prev_msg.role) if role_val != "assistant": continue for content in prev_msg.contents or []: @@ -287,7 +286,7 @@ def _resolve_approval_call_id(tool_call_id: str, parsed_payload: dict[str, Any] return str(explicit_call_id) for prev_msg in result: - role_val = prev_msg.role.value if hasattr(prev_msg.role, "value") else str(prev_msg.role) + role_val = prev_msg.role if hasattr(prev_msg.role, "value") else str(prev_msg.role) if role_val != "assistant": continue direct_call = None @@ -396,7 +395,7 @@ def _filter_modified_args( m for m in result if not ( - (m.role.value if hasattr(m.role, "value") else str(m.role)) == "tool" + (m.role if hasattr(m.role, "value") else str(m.role)) == "tool" and any( c.type == "function_result" and c.call_id == approval_call_id for c in (m.contents or []) @@ -473,14 +472,14 @@ def _filter_modified_args( additional_properties={"ag_ui_state_args": state_args} if state_args else None, ) chat_msg = ChatMessage( - role=Role.USER, + role="user", contents=[approval_response], ) else: # No matching function call found - this is likely a confirm_changes approval # Keep the old behavior for backwards compatibility chat_msg = ChatMessage( - role=Role.USER, + role="user", contents=[Content.from_text(text=approval_payload_text)], additional_properties={"is_tool_result": True, "tool_call_id": str(tool_call_id or "")}, ) @@ -500,7 +499,7 @@ def _filter_modified_args( else: func_result = str(result_content) chat_msg = ChatMessage( - role=Role.TOOL, + role="tool", contents=[Content.from_function_result(call_id=str(tool_call_id), result=func_result)], ) if "id" in msg: @@ -516,7 +515,7 @@ def _filter_modified_args( result_content = msg.get("result", msg.get("content", "")) chat_msg = ChatMessage( - role=Role.TOOL, + role="tool", contents=[Content.from_function_result(call_id=str(tool_call_id), result=result_content)], ) if "id" in msg: @@ -554,7 +553,7 @@ def _filter_modified_args( arguments=arguments, ) ) - chat_msg = ChatMessage(role=Role.ASSISTANT, contents=contents) + chat_msg = ChatMessage("assistant", contents) if "id" in msg: chat_msg.message_id = msg["id"] result.append(chat_msg) @@ -562,7 +561,7 @@ def _filter_modified_args( # No special handling required for assistant/plain messages here - role = AGUI_TO_FRAMEWORK_ROLE.get(role_str, Role.USER) + role = AGUI_TO_FRAMEWORK_ROLE.get(role_str, "user") # Check if this message contains function approvals if "function_approvals" in msg and msg["function_approvals"]: @@ -584,14 +583,14 @@ def _filter_modified_args( ) approval_contents.append(approval_response) - chat_msg = ChatMessage(role=role, contents=approval_contents) # type: ignore[arg-type] + chat_msg = ChatMessage(role, approval_contents) # type: ignore[arg-type] else: # Regular text message content = msg.get("content", "") if isinstance(content, str): - chat_msg = ChatMessage(role=role, contents=[Content.from_text(text=content)]) + chat_msg = ChatMessage(role, [Content.from_text(text=content)]) else: - chat_msg = ChatMessage(role=role, contents=[Content.from_text(text=str(content))]) + chat_msg = ChatMessage(role, [Content.from_text(text=str(content))]) if "id" in msg: chat_msg.message_id = msg["id"] diff --git a/python/packages/ag-ui/agent_framework_ag_ui/_run.py b/python/packages/ag-ui/agent_framework_ag_ui/_run.py index d1229620a7..7cd9e0c686 100644 --- a/python/packages/ag-ui/agent_framework_ag_ui/_run.py +++ b/python/packages/ag-ui/agent_framework_ag_ui/_run.py @@ -862,7 +862,7 @@ async def run_agent_stream( from pydantic import BaseModel logger.info(f"Processing structured output, update count: {len(all_updates)}") - final_response = AgentResponse.from_agent_run_response_updates(all_updates, output_format_type=response_format) + final_response = AgentResponse.from_updates(all_updates, output_format_type=response_format) if final_response.value and isinstance(final_response.value, BaseModel): response_dict = final_response.value.model_dump(mode="json", exclude_none=True) diff --git a/python/packages/ag-ui/agent_framework_ag_ui/_utils.py b/python/packages/ag-ui/agent_framework_ag_ui/_utils.py index f7f01261f5..bb33c3279e 100644 --- a/python/packages/ag-ui/agent_framework_ag_ui/_utils.py +++ b/python/packages/ag-ui/agent_framework_ag_ui/_utils.py @@ -10,19 +10,19 @@ from datetime import date, datetime from typing import Any -from agent_framework import AgentResponseUpdate, ChatResponseUpdate, FunctionTool, Role, ToolProtocol +from agent_framework import AgentResponseUpdate, ChatResponseUpdate, FunctionTool, ToolProtocol # Role mapping constants -AGUI_TO_FRAMEWORK_ROLE: dict[str, Role] = { - "user": Role.USER, - "assistant": Role.ASSISTANT, - "system": Role.SYSTEM, +AGUI_TO_FRAMEWORK_ROLE: dict[str, str] = { + "user": "user", + "assistant": "assistant", + "system": "system", } -FRAMEWORK_TO_AGUI_ROLE: dict[Role, str] = { - Role.USER: "user", - Role.ASSISTANT: "assistant", - Role.SYSTEM: "system", +FRAMEWORK_TO_AGUI_ROLE: dict[str, str] = { + "user": "user", + "assistant": "assistant", + "system": "system", } ALLOWED_AGUI_ROLES: set[str] = {"user", "assistant", "system", "tool"} diff --git a/python/packages/ag-ui/getting_started/client_with_agent.py b/python/packages/ag-ui/getting_started/client_with_agent.py index be23404583..1a17a8e618 100644 --- a/python/packages/ag-ui/getting_started/client_with_agent.py +++ b/python/packages/ag-ui/getting_started/client_with_agent.py @@ -171,7 +171,7 @@ def _preview_for_message(m) -> str: messages = await thread.message_store.list_messages() print(f"\n[THREAD STATE] {len(messages)} messages in thread's message_store") for i, msg in enumerate(messages[-6:], 1): # Show last 6 - role = msg.role.value if hasattr(msg.role, "value") else str(msg.role) + role = msg.role if hasattr(msg.role, "value") else str(msg.role) text_preview = _preview_for_message(msg) print(f" {i}. [{role}]: {text_preview}") diff --git a/python/packages/ag-ui/tests/test_ag_ui_client.py b/python/packages/ag-ui/tests/test_ag_ui_client.py index af9c7fb916..5f4ad1794b 100644 --- a/python/packages/ag-ui/tests/test_ag_ui_client.py +++ b/python/packages/ag-ui/tests/test_ag_ui_client.py @@ -12,7 +12,6 @@ ChatResponse, ChatResponseUpdate, Content, - Role, tool, ) from pytest import MonkeyPatch @@ -76,8 +75,8 @@ async def test_extract_state_from_messages_no_state(self) -> None: """Test state extraction when no state is present.""" client = TestableAGUIChatClient(endpoint="http://localhost:8888/") messages = [ - ChatMessage(role="user", text="Hello"), - ChatMessage(role="assistant", text="Hi there"), + ChatMessage("user", ["Hello"]), + ChatMessage("assistant", ["Hi there"]), ] result_messages, state = client.extract_state_from_messages(messages) @@ -96,7 +95,7 @@ async def test_extract_state_from_messages_with_state(self) -> None: state_b64 = base64.b64encode(state_json.encode("utf-8")).decode("utf-8") messages = [ - ChatMessage(role="user", text="Hello"), + ChatMessage("user", ["Hello"]), ChatMessage( role="user", contents=[Content.from_uri(uri=f"data:application/json;base64,{state_b64}")], @@ -134,8 +133,8 @@ async def test_convert_messages_to_agui_format(self) -> None: """Test message conversion to AG-UI format.""" client = TestableAGUIChatClient(endpoint="http://localhost:8888/") messages = [ - ChatMessage(role=Role.USER, text="What is the weather?"), - ChatMessage(role=Role.ASSISTANT, text="Let me check.", message_id="msg_123"), + ChatMessage("user", ["What is the weather?"]), + ChatMessage("assistant", ["Let me check."], message_id="msg_123"), ] agui_messages = client.convert_messages_to_agui_format(messages) @@ -182,7 +181,7 @@ async def mock_post_run(*args: object, **kwargs: Any) -> AsyncGenerator[dict[str client = TestableAGUIChatClient(endpoint="http://localhost:8888/") monkeypatch.setattr(client.http_service, "post_run", mock_post_run) - messages = [ChatMessage(role="user", text="Test message")] + messages = [ChatMessage("user", ["Test message"])] chat_options = ChatOptions() updates: list[ChatResponseUpdate] = [] @@ -215,7 +214,7 @@ async def mock_post_run(*args: object, **kwargs: Any) -> AsyncGenerator[dict[str client = TestableAGUIChatClient(endpoint="http://localhost:8888/") monkeypatch.setattr(client.http_service, "post_run", mock_post_run) - messages = [ChatMessage(role="user", text="Test message")] + messages = [ChatMessage("user", ["Test message"])] chat_options = {} response = await client.inner_get_response(messages=messages, options=chat_options) @@ -258,7 +257,7 @@ async def mock_post_run(*args: object, **kwargs: Any) -> AsyncGenerator[dict[str client = TestableAGUIChatClient(endpoint="http://localhost:8888/") monkeypatch.setattr(client.http_service, "post_run", mock_post_run) - messages = [ChatMessage(role="user", text="Test with tools")] + messages = [ChatMessage("user", ["Test with tools"])] chat_options = ChatOptions(tools=[test_tool]) response = await client.inner_get_response(messages=messages, options=chat_options) @@ -282,7 +281,7 @@ async def mock_post_run(*args: object, **kwargs: Any) -> AsyncGenerator[dict[str client = TestableAGUIChatClient(endpoint="http://localhost:8888/") monkeypatch.setattr(client.http_service, "post_run", mock_post_run) - messages = [ChatMessage(role="user", text="Test server tool execution")] + messages = [ChatMessage("user", ["Test server tool execution"])] updates: list[ChatResponseUpdate] = [] async for update in client.get_streaming_response(messages): @@ -324,7 +323,7 @@ async def fake_auto_invoke(*args: object, **kwargs: Any) -> None: client = TestableAGUIChatClient(endpoint="http://localhost:8888/") monkeypatch.setattr(client.http_service, "post_run", mock_post_run) - messages = [ChatMessage(role="user", text="Test server tool execution")] + messages = [ChatMessage("user", ["Test server tool execution"])] async for _ in client.get_streaming_response(messages, options={"tool_choice": "auto", "tools": [client_tool]}): pass @@ -338,7 +337,7 @@ async def test_state_transmission(self, monkeypatch: MonkeyPatch) -> None: state_b64 = base64.b64encode(state_json.encode("utf-8")).decode("utf-8") messages = [ - ChatMessage(role="user", text="Hello"), + ChatMessage("user", ["Hello"]), ChatMessage( role="user", contents=[Content.from_uri(uri=f"data:application/json;base64,{state_b64}")], diff --git a/python/packages/ag-ui/tests/test_event_converters.py b/python/packages/ag-ui/tests/test_event_converters.py index ff4d2ddc91..f26013a3fe 100644 --- a/python/packages/ag-ui/tests/test_event_converters.py +++ b/python/packages/ag-ui/tests/test_event_converters.py @@ -2,8 +2,6 @@ """Tests for AG-UI event converter.""" -from agent_framework import FinishReason, Role - from agent_framework_ag_ui._event_converters import AGUIEventConverter @@ -22,7 +20,7 @@ def test_run_started_event(self) -> None: update = converter.convert_event(event) assert update is not None - assert update.role == Role.ASSISTANT + assert update.role == "assistant" assert update.additional_properties["thread_id"] == "thread_123" assert update.additional_properties["run_id"] == "run_456" assert converter.thread_id == "thread_123" @@ -39,7 +37,7 @@ def test_text_message_start_event(self) -> None: update = converter.convert_event(event) assert update is not None - assert update.role == Role.ASSISTANT + assert update.role == "assistant" assert update.message_id == "msg_789" assert converter.current_message_id == "msg_789" @@ -55,7 +53,7 @@ def test_text_message_content_event(self) -> None: update = converter.convert_event(event) assert update is not None - assert update.role == Role.ASSISTANT + assert update.role == "assistant" assert update.message_id == "msg_1" assert len(update.contents) == 1 assert update.contents[0].text == "Hello" @@ -101,7 +99,7 @@ def test_tool_call_start_event(self) -> None: update = converter.convert_event(event) assert update is not None - assert update.role == Role.ASSISTANT + assert update.role == "assistant" assert len(update.contents) == 1 assert update.contents[0].call_id == "call_123" assert update.contents[0].name == "get_weather" @@ -184,7 +182,7 @@ def test_tool_call_result_event(self) -> None: update = converter.convert_event(event) assert update is not None - assert update.role == Role.TOOL + assert update.role == "tool" assert len(update.contents) == 1 assert update.contents[0].call_id == "call_123" assert update.contents[0].result == {"temperature": 22, "condition": "sunny"} @@ -204,8 +202,8 @@ def test_run_finished_event(self) -> None: update = converter.convert_event(event) assert update is not None - assert update.role == Role.ASSISTANT - assert update.finish_reason == FinishReason.STOP + assert update.role == "assistant" + assert update.finish_reason == "stop" assert update.additional_properties["thread_id"] == "thread_123" assert update.additional_properties["run_id"] == "run_456" @@ -223,8 +221,8 @@ def test_run_error_event(self) -> None: update = converter.convert_event(event) assert update is not None - assert update.role == Role.ASSISTANT - assert update.finish_reason == FinishReason.CONTENT_FILTER + assert update.role == "assistant" + assert update.finish_reason == "content_filter" assert len(update.contents) == 1 assert update.contents[0].message == "Connection timeout" assert update.contents[0].error_code == "RUN_ERROR" diff --git a/python/packages/ag-ui/tests/test_helpers.py b/python/packages/ag-ui/tests/test_helpers.py index b4a7e9f047..2fdd1d6771 100644 --- a/python/packages/ag-ui/tests/test_helpers.py +++ b/python/packages/ag-ui/tests/test_helpers.py @@ -29,8 +29,8 @@ def test_empty_messages(self): def test_no_tool_calls(self): """Returns empty set when no tool calls in messages.""" messages = [ - ChatMessage(role="user", contents=[Content.from_text("Hello")]), - ChatMessage(role="assistant", contents=[Content.from_text("Hi there")]), + ChatMessage("user", [Content.from_text("Hello")]), + ChatMessage("assistant", [Content.from_text("Hi there")]), ] result = pending_tool_call_ids(messages) assert result == set() @@ -114,7 +114,7 @@ def test_system_message_without_state_prefix(self): def test_empty_contents(self): """Returns False for message with empty contents.""" - message = ChatMessage(role="system", contents=[]) + message = ChatMessage("system", []) assert is_state_context_message(message) is False @@ -342,7 +342,7 @@ def test_empty_messages(self): def test_no_approval_response(self): """Returns None when no approval response in last message.""" messages = [ - ChatMessage(role="assistant", contents=[Content.from_text("Hello")]), + ChatMessage("assistant", [Content.from_text("Hello")]), ] result = latest_approval_response(messages) assert result is None @@ -357,7 +357,7 @@ def test_finds_approval_response(self): function_call=fc, ) messages = [ - ChatMessage(role="user", contents=[approval_content]), + ChatMessage("user", [approval_content]), ] result = latest_approval_response(messages) assert result is approval_content diff --git a/python/packages/ag-ui/tests/test_message_adapters.py b/python/packages/ag-ui/tests/test_message_adapters.py index 4f6c3f1d42..85fe778e09 100644 --- a/python/packages/ag-ui/tests/test_message_adapters.py +++ b/python/packages/ag-ui/tests/test_message_adapters.py @@ -5,7 +5,7 @@ import json import pytest -from agent_framework import ChatMessage, Content, Role +from agent_framework import ChatMessage, Content from agent_framework_ag_ui._message_adapters import ( agent_framework_messages_to_agui, @@ -24,7 +24,7 @@ def sample_agui_message(): @pytest.fixture def sample_agent_framework_message(): """Create a sample Agent Framework message.""" - return ChatMessage(role=Role.USER, contents=[Content.from_text(text="Hello")], message_id="msg-123") + return ChatMessage("user", [Content.from_text(text="Hello")], message_id="msg-123") def test_agui_to_agent_framework_basic(sample_agui_message): @@ -32,7 +32,7 @@ def test_agui_to_agent_framework_basic(sample_agui_message): messages = agui_messages_to_agent_framework([sample_agui_message]) assert len(messages) == 1 - assert messages[0].role == Role.USER + assert messages[0].role == "user" assert messages[0].message_id == "msg-123" @@ -86,7 +86,7 @@ def test_agui_tool_result_to_agent_framework(): assert len(messages) == 1 message = messages[0] - assert message.role == Role.USER + assert message.role == "user" assert len(message.contents) == 1 assert message.contents[0].type == "text" @@ -328,9 +328,9 @@ def test_agui_multiple_messages_to_agent_framework(): messages = agui_messages_to_agent_framework(messages_input) assert len(messages) == 3 - assert messages[0].role == Role.USER - assert messages[1].role == Role.ASSISTANT - assert messages[2].role == Role.USER + assert messages[0].role == "user" + assert messages[1].role == "assistant" + assert messages[2].role == "user" def test_agui_empty_messages(): @@ -366,7 +366,7 @@ def test_agui_function_approvals(): assert len(messages) == 1 msg = messages[0] - assert msg.role == Role.USER + assert msg.role == "user" assert len(msg.contents) == 2 assert msg.contents[0].type == "function_approval_response" @@ -385,7 +385,7 @@ def test_agui_system_role(): messages = agui_messages_to_agent_framework([{"role": "system", "content": "System prompt"}]) assert len(messages) == 1 - assert messages[0].role == Role.SYSTEM + assert messages[0].role == "system" def test_agui_non_string_content(): @@ -425,7 +425,7 @@ def test_agui_with_tool_calls_to_agent_framework(): assert len(messages) == 1 msg = messages[0] - assert msg.role == Role.ASSISTANT + assert msg.role == "assistant" assert msg.message_id == "msg-789" # First content is text, second is the function call assert msg.contents[0].type == "text" @@ -439,7 +439,7 @@ def test_agui_with_tool_calls_to_agent_framework(): def test_agent_framework_to_agui_with_tool_calls(): """Test converting Agent Framework message with tool calls to AG-UI.""" msg = ChatMessage( - role=Role.ASSISTANT, + role="assistant", contents=[ Content.from_text(text="Calling tool"), Content.from_function_call(call_id="call-123", name="search", arguments={"query": "test"}), @@ -464,7 +464,7 @@ def test_agent_framework_to_agui_with_tool_calls(): def test_agent_framework_to_agui_multiple_text_contents(): """Test concatenating multiple text contents.""" msg = ChatMessage( - role=Role.ASSISTANT, + role="assistant", contents=[Content.from_text(text="Part 1 "), Content.from_text(text="Part 2")], ) @@ -476,7 +476,7 @@ def test_agent_framework_to_agui_multiple_text_contents(): def test_agent_framework_to_agui_no_message_id(): """Test message without message_id - should auto-generate ID.""" - msg = ChatMessage(role=Role.USER, contents=[Content.from_text(text="Hello")]) + msg = ChatMessage("user", [Content.from_text(text="Hello")]) messages = agent_framework_messages_to_agui([msg]) @@ -488,7 +488,7 @@ def test_agent_framework_to_agui_no_message_id(): def test_agent_framework_to_agui_system_role(): """Test system role conversion.""" - msg = ChatMessage(role=Role.SYSTEM, contents=[Content.from_text(text="System")]) + msg = ChatMessage("system", [Content.from_text(text="System")]) messages = agent_framework_messages_to_agui([msg]) @@ -534,7 +534,7 @@ def test_extract_text_from_custom_contents(): def test_agent_framework_to_agui_function_result_dict(): """Test converting FunctionResultContent with dict result to AG-UI.""" msg = ChatMessage( - role=Role.TOOL, + role="tool", contents=[Content.from_function_result(call_id="call-123", result={"key": "value", "count": 42})], message_id="msg-789", ) @@ -551,7 +551,7 @@ def test_agent_framework_to_agui_function_result_dict(): def test_agent_framework_to_agui_function_result_none(): """Test converting FunctionResultContent with None result to AG-UI.""" msg = ChatMessage( - role=Role.TOOL, + role="tool", contents=[Content.from_function_result(call_id="call-123", result=None)], message_id="msg-789", ) @@ -567,7 +567,7 @@ def test_agent_framework_to_agui_function_result_none(): def test_agent_framework_to_agui_function_result_string(): """Test converting FunctionResultContent with string result to AG-UI.""" msg = ChatMessage( - role=Role.TOOL, + role="tool", contents=[Content.from_function_result(call_id="call-123", result="plain text result")], message_id="msg-789", ) @@ -582,7 +582,7 @@ def test_agent_framework_to_agui_function_result_string(): def test_agent_framework_to_agui_function_result_empty_list(): """Test converting FunctionResultContent with empty list result to AG-UI.""" msg = ChatMessage( - role=Role.TOOL, + role="tool", contents=[Content.from_function_result(call_id="call-123", result=[])], message_id="msg-789", ) @@ -604,7 +604,7 @@ class MockTextContent: text: str msg = ChatMessage( - role=Role.TOOL, + role="tool", contents=[Content.from_function_result(call_id="call-123", result=[MockTextContent("Hello from MCP!")])], message_id="msg-789", ) @@ -626,7 +626,7 @@ class MockTextContent: text: str msg = ChatMessage( - role=Role.TOOL, + role="tool", contents=[ Content.from_function_result( call_id="call-123", @@ -723,7 +723,7 @@ def test_agui_to_agent_framework_tool_result(): assert len(result) == 2 # Second message should be tool result tool_msg = result[1] - assert tool_msg.role == Role.TOOL + assert tool_msg.role == "tool" assert tool_msg.contents[0].type == "function_result" assert tool_msg.contents[0].result == "Sunny" diff --git a/python/packages/ag-ui/tests/test_message_hygiene.py b/python/packages/ag-ui/tests/test_message_hygiene.py index ecc01de3cb..03c8a1b9b3 100644 --- a/python/packages/ag-ui/tests/test_message_hygiene.py +++ b/python/packages/ag-ui/tests/test_message_hygiene.py @@ -25,9 +25,7 @@ def test_sanitize_tool_history_injects_confirm_changes_result() -> None: sanitized = _sanitize_tool_history(messages) - tool_messages = [ - msg for msg in sanitized if (msg.role.value if hasattr(msg.role, "value") else str(msg.role)) == "tool" - ] + tool_messages = [msg for msg in sanitized if (msg.role if hasattr(msg.role, "value") else str(msg.role)) == "tool"] assert len(tool_messages) == 1 assert str(tool_messages[0].contents[0].call_id) == "call_confirm_123" assert tool_messages[0].contents[0].result == "Confirmed" diff --git a/python/packages/ag-ui/tests/test_run.py b/python/packages/ag-ui/tests/test_run.py index a415000692..7fb7055ae0 100644 --- a/python/packages/ag-ui/tests/test_run.py +++ b/python/packages/ag-ui/tests/test_run.py @@ -188,7 +188,6 @@ def test_no_schema(self): def test_creates_message(self): """Creates state context message.""" - from agent_framework import Role state = {"document": "Hello world"} schema = {"properties": {"document": {"type": "string"}}} @@ -196,7 +195,7 @@ def test_creates_message(self): result = _create_state_context_message(state, schema) assert result is not None - assert result.role == Role.SYSTEM + assert result.role == "system" assert len(result.contents) == 1 assert "Hello world" in result.contents[0].text assert "Current state" in result.contents[0].text @@ -207,7 +206,7 @@ class TestInjectStateContext: def test_no_state_message(self): """Returns original messages when no state context needed.""" - messages = [ChatMessage(role="user", contents=[Content.from_text("Hello")])] + messages = [ChatMessage("user", [Content.from_text("Hello")])] result = _inject_state_context(messages, {}, {}) assert result == messages @@ -219,8 +218,8 @@ def test_empty_messages(self): def test_last_message_not_user(self): """Returns original messages when last message is not from user.""" messages = [ - ChatMessage(role="user", contents=[Content.from_text("Hello")]), - ChatMessage(role="assistant", contents=[Content.from_text("Hi")]), + ChatMessage("user", [Content.from_text("Hello")]), + ChatMessage("assistant", [Content.from_text("Hi")]), ] state = {"key": "value"} schema = {"properties": {"key": {"type": "string"}}} @@ -230,11 +229,10 @@ def test_last_message_not_user(self): def test_injects_before_last_user_message(self): """Injects state context before last user message.""" - from agent_framework import Role messages = [ - ChatMessage(role="system", contents=[Content.from_text("You are helpful")]), - ChatMessage(role="user", contents=[Content.from_text("Hello")]), + ChatMessage("system", [Content.from_text("You are helpful")]), + ChatMessage("user", [Content.from_text("Hello")]), ] state = {"document": "content"} schema = {"properties": {"document": {"type": "string"}}} @@ -243,13 +241,13 @@ def test_injects_before_last_user_message(self): assert len(result) == 3 # System message first - assert result[0].role == Role.SYSTEM + assert result[0].role == "system" assert "helpful" in result[0].contents[0].text # State context second - assert result[1].role == Role.SYSTEM + assert result[1].role == "system" assert "Current state" in result[1].contents[0].text # User message last - assert result[2].role == Role.USER + assert result[2].role == "user" assert "Hello" in result[2].contents[0].text @@ -357,7 +355,7 @@ def test_extract_approved_state_updates_no_handler(): """Test _extract_approved_state_updates returns empty with no handler.""" from agent_framework_ag_ui._run import _extract_approved_state_updates - messages = [ChatMessage(role="user", contents=[Content.from_text("Hello")])] + messages = [ChatMessage("user", [Content.from_text("Hello")])] result = _extract_approved_state_updates(messages, None) assert result == {} @@ -368,6 +366,6 @@ def test_extract_approved_state_updates_no_approval(): from agent_framework_ag_ui._run import _extract_approved_state_updates handler = PredictiveStateHandler(predict_state_config={"doc": {"tool": "write", "tool_argument": "content"}}) - messages = [ChatMessage(role="user", contents=[Content.from_text("Hello")])] + messages = [ChatMessage("user", [Content.from_text("Hello")])] result = _extract_approved_state_updates(messages, handler) assert result == {} diff --git a/python/packages/ag-ui/tests/test_utils.py b/python/packages/ag-ui/tests/test_utils.py index 7f1de812c4..41b8e3665b 100644 --- a/python/packages/ag-ui/tests/test_utils.py +++ b/python/packages/ag-ui/tests/test_utils.py @@ -404,11 +404,11 @@ def test_safe_json_parse_with_none(): def test_get_role_value_with_enum(): """Test get_role_value with enum role.""" - from agent_framework import ChatMessage, Content, Role + from agent_framework import ChatMessage, Content from agent_framework_ag_ui._utils import get_role_value - message = ChatMessage(role=Role.USER, contents=[Content.from_text("test")]) + message = ChatMessage("user", [Content.from_text("test")]) result = get_role_value(message) assert result == "user" diff --git a/python/packages/ag-ui/tests/utils_test_ag_ui.py b/python/packages/ag-ui/tests/utils_test_ag_ui.py index 5c2415583c..9ac9b04df4 100644 --- a/python/packages/ag-ui/tests/utils_test_ag_ui.py +++ b/python/packages/ag-ui/tests/utils_test_ag_ui.py @@ -56,7 +56,7 @@ async def _inner_get_response( contents.extend(update.contents) return ChatResponse( - messages=[ChatMessage(role="assistant", contents=contents)], + messages=[ChatMessage("assistant", contents)], response_id="stub-response", ) diff --git a/python/packages/anthropic/agent_framework_anthropic/_chat_client.py b/python/packages/anthropic/agent_framework_anthropic/_chat_client.py index 630b92ca02..901a42122f 100644 --- a/python/packages/anthropic/agent_framework_anthropic/_chat_client.py +++ b/python/packages/anthropic/agent_framework_anthropic/_chat_client.py @@ -13,12 +13,10 @@ ChatResponse, ChatResponseUpdate, Content, - FinishReason, FunctionTool, HostedCodeInterpreterTool, HostedMCPTool, HostedWebSearchTool, - Role, TextSpanRegion, UsageDetails, get_logger, @@ -172,20 +170,20 @@ class AnthropicChatOptions(ChatOptions[TResponseModel], Generic[TResponseModel], # region Role and Finish Reason Maps -ROLE_MAP: dict[Role, str] = { - Role.USER: "user", - Role.ASSISTANT: "assistant", - Role.SYSTEM: "user", - Role.TOOL: "user", +ROLE_MAP: dict[str, str] = { + "user": "user", + "assistant": "assistant", + "system": "user", + "tool": "user", } -FINISH_REASON_MAP: dict[str, FinishReason] = { - "stop_sequence": FinishReason.STOP, - "max_tokens": FinishReason.LENGTH, - "tool_use": FinishReason.TOOL_CALLS, - "end_turn": FinishReason.STOP, - "refusal": FinishReason.CONTENT_FILTER, - "pause_turn": FinishReason.STOP, +FINISH_REASON_MAP: dict[str, str] = { + "stop_sequence": "stop", + "max_tokens": "length", + "tool_use": "tool_calls", + "end_turn": "stop", + "refusal": "content_filter", + "pause_turn": "stop", } @@ -415,7 +413,7 @@ def _prepare_options( run_options["messages"] = self._prepare_messages_for_anthropic(messages) # system message - first system message is passed as instructions - if messages and isinstance(messages[0], ChatMessage) and messages[0].role == Role.SYSTEM: + if messages and isinstance(messages[0], ChatMessage) and messages[0].role == "system": run_options["system"] = messages[0].text # betas @@ -502,7 +500,7 @@ def _prepare_messages_for_anthropic(self, messages: MutableSequence[ChatMessage] as Anthropic expects system instructions as a separate parameter. """ # first system message is passed as instructions - if messages and isinstance(messages[0], ChatMessage) and messages[0].role == Role.SYSTEM: + if messages and isinstance(messages[0], ChatMessage) and messages[0].role == "system": return [self._prepare_message_for_anthropic(msg) for msg in messages[1:]] return [self._prepare_message_for_anthropic(msg) for msg in messages] @@ -673,7 +671,7 @@ def _process_message(self, message: BetaMessage, options: dict[str, Any]) -> Cha response_id=message.id, messages=[ ChatMessage( - role=Role.ASSISTANT, + role="assistant", contents=self._parse_contents_from_anthropic(message.content), raw_representation=message, ) diff --git a/python/packages/anthropic/tests/test_anthropic_client.py b/python/packages/anthropic/tests/test_anthropic_client.py index 6b06843b73..516f644ea7 100644 --- a/python/packages/anthropic/tests/test_anthropic_client.py +++ b/python/packages/anthropic/tests/test_anthropic_client.py @@ -11,11 +11,9 @@ ChatOptions, ChatResponseUpdate, Content, - FinishReason, HostedCodeInterpreterTool, HostedMCPTool, HostedWebSearchTool, - Role, tool, ) from agent_framework.exceptions import ServiceInitializationError @@ -150,7 +148,7 @@ def test_anthropic_client_service_url(mock_anthropic_client: MagicMock) -> None: def test_prepare_message_for_anthropic_text(mock_anthropic_client: MagicMock) -> None: """Test converting text message to Anthropic format.""" chat_client = create_test_anthropic_client(mock_anthropic_client) - message = ChatMessage(role=Role.USER, text="Hello, world!") + message = ChatMessage("user", ["Hello, world!"]) result = chat_client._prepare_message_for_anthropic(message) @@ -164,7 +162,7 @@ def test_prepare_message_for_anthropic_function_call(mock_anthropic_client: Magi """Test converting function call message to Anthropic format.""" chat_client = create_test_anthropic_client(mock_anthropic_client) message = ChatMessage( - role=Role.ASSISTANT, + role="assistant", contents=[ Content.from_function_call( call_id="call_123", @@ -188,7 +186,7 @@ def test_prepare_message_for_anthropic_function_result(mock_anthropic_client: Ma """Test converting function result message to Anthropic format.""" chat_client = create_test_anthropic_client(mock_anthropic_client) message = ChatMessage( - role=Role.TOOL, + role="tool", contents=[ Content.from_function_result( call_id="call_123", @@ -213,7 +211,7 @@ def test_prepare_message_for_anthropic_text_reasoning(mock_anthropic_client: Mag """Test converting text reasoning message to Anthropic format.""" chat_client = create_test_anthropic_client(mock_anthropic_client) message = ChatMessage( - role=Role.ASSISTANT, + role="assistant", contents=[Content.from_text_reasoning(text="Let me think about this...")], ) @@ -229,8 +227,8 @@ def test_prepare_messages_for_anthropic_with_system(mock_anthropic_client: Magic """Test converting messages list with system message.""" chat_client = create_test_anthropic_client(mock_anthropic_client) messages = [ - ChatMessage(role=Role.SYSTEM, text="You are a helpful assistant."), - ChatMessage(role=Role.USER, text="Hello!"), + ChatMessage("system", ["You are a helpful assistant."]), + ChatMessage("user", ["Hello!"]), ] result = chat_client._prepare_messages_for_anthropic(messages) @@ -245,8 +243,8 @@ def test_prepare_messages_for_anthropic_without_system(mock_anthropic_client: Ma """Test converting messages list without system message.""" chat_client = create_test_anthropic_client(mock_anthropic_client) messages = [ - ChatMessage(role=Role.USER, text="Hello!"), - ChatMessage(role=Role.ASSISTANT, text="Hi there!"), + ChatMessage("user", ["Hello!"]), + ChatMessage("assistant", ["Hi there!"]), ] result = chat_client._prepare_messages_for_anthropic(messages) @@ -374,7 +372,7 @@ async def test_prepare_options_basic(mock_anthropic_client: MagicMock) -> None: """Test _prepare_options with basic ChatOptions.""" chat_client = create_test_anthropic_client(mock_anthropic_client) - messages = [ChatMessage(role=Role.USER, text="Hello")] + messages = [ChatMessage("user", ["Hello"])] chat_options = ChatOptions(max_tokens=100, temperature=0.7) run_options = chat_client._prepare_options(messages, chat_options) @@ -390,8 +388,8 @@ async def test_prepare_options_with_system_message(mock_anthropic_client: MagicM chat_client = create_test_anthropic_client(mock_anthropic_client) messages = [ - ChatMessage(role=Role.SYSTEM, text="You are helpful."), - ChatMessage(role=Role.USER, text="Hello"), + ChatMessage("system", ["You are helpful."]), + ChatMessage("user", ["Hello"]), ] chat_options = ChatOptions() @@ -405,7 +403,7 @@ async def test_prepare_options_with_tool_choice_auto(mock_anthropic_client: Magi """Test _prepare_options with auto tool choice.""" chat_client = create_test_anthropic_client(mock_anthropic_client) - messages = [ChatMessage(role=Role.USER, text="Hello")] + messages = [ChatMessage("user", ["Hello"])] chat_options = ChatOptions(tool_choice="auto") run_options = chat_client._prepare_options(messages, chat_options) @@ -417,7 +415,7 @@ async def test_prepare_options_with_tool_choice_required(mock_anthropic_client: """Test _prepare_options with required tool choice.""" chat_client = create_test_anthropic_client(mock_anthropic_client) - messages = [ChatMessage(role=Role.USER, text="Hello")] + messages = [ChatMessage("user", ["Hello"])] # For required with specific function, need to pass as dict chat_options = ChatOptions(tool_choice={"mode": "required", "required_function_name": "get_weather"}) @@ -431,7 +429,7 @@ async def test_prepare_options_with_tool_choice_none(mock_anthropic_client: Magi """Test _prepare_options with none tool choice.""" chat_client = create_test_anthropic_client(mock_anthropic_client) - messages = [ChatMessage(role=Role.USER, text="Hello")] + messages = [ChatMessage("user", ["Hello"])] chat_options = ChatOptions(tool_choice="none") run_options = chat_client._prepare_options(messages, chat_options) @@ -448,7 +446,7 @@ def get_weather(location: str) -> str: """Get weather for a location.""" return f"Weather for {location}" - messages = [ChatMessage(role=Role.USER, text="Hello")] + messages = [ChatMessage("user", ["Hello"])] chat_options = ChatOptions(tools=[get_weather]) run_options = chat_client._prepare_options(messages, chat_options) @@ -461,7 +459,7 @@ async def test_prepare_options_with_stop_sequences(mock_anthropic_client: MagicM """Test _prepare_options with stop sequences.""" chat_client = create_test_anthropic_client(mock_anthropic_client) - messages = [ChatMessage(role=Role.USER, text="Hello")] + messages = [ChatMessage("user", ["Hello"])] chat_options = ChatOptions(stop=["STOP", "END"]) run_options = chat_client._prepare_options(messages, chat_options) @@ -473,7 +471,7 @@ async def test_prepare_options_with_top_p(mock_anthropic_client: MagicMock) -> N """Test _prepare_options with top_p.""" chat_client = create_test_anthropic_client(mock_anthropic_client) - messages = [ChatMessage(role=Role.USER, text="Hello")] + messages = [ChatMessage("user", ["Hello"])] chat_options = ChatOptions(top_p=0.9) run_options = chat_client._prepare_options(messages, chat_options) @@ -500,11 +498,11 @@ def test_process_message_basic(mock_anthropic_client: MagicMock) -> None: assert response.response_id == "msg_123" assert response.model_id == "claude-3-5-sonnet-20241022" assert len(response.messages) == 1 - assert response.messages[0].role == Role.ASSISTANT + assert response.messages[0].role == "assistant" assert len(response.messages[0].contents) == 1 assert response.messages[0].contents[0].type == "text" assert response.messages[0].contents[0].text == "Hello there!" - assert response.finish_reason == FinishReason.STOP + assert response.finish_reason == "stop" assert response.usage_details is not None assert response.usage_details["input_token_count"] == 10 assert response.usage_details["output_token_count"] == 5 @@ -534,7 +532,7 @@ def test_process_message_with_tool_use(mock_anthropic_client: MagicMock) -> None assert response.messages[0].contents[0].type == "function_call" assert response.messages[0].contents[0].call_id == "call_123" assert response.messages[0].contents[0].name == "get_weather" - assert response.finish_reason == FinishReason.TOOL_CALLS + assert response.finish_reason == "tool_calls" def test_parse_usage_from_anthropic_basic(mock_anthropic_client: MagicMock) -> None: @@ -668,7 +666,7 @@ async def test_inner_get_response(mock_anthropic_client: MagicMock) -> None: mock_anthropic_client.beta.messages.create.return_value = mock_message - messages = [ChatMessage(role=Role.USER, text="Hi")] + messages = [ChatMessage("user", ["Hi"])] chat_options = ChatOptions(max_tokens=10) response = await chat_client._inner_get_response( # type: ignore[attr-defined] @@ -692,7 +690,7 @@ async def mock_stream(): mock_anthropic_client.beta.messages.create.return_value = mock_stream() - messages = [ChatMessage(role=Role.USER, text="Hi")] + messages = [ChatMessage("user", ["Hi"])] chat_options = ChatOptions(max_tokens=10) chunks: list[ChatResponseUpdate] = [] @@ -723,13 +721,13 @@ async def test_anthropic_client_integration_basic_chat() -> None: """Integration test for basic chat completion.""" client = AnthropicClient() - messages = [ChatMessage(role=Role.USER, text="Say 'Hello, World!' and nothing else.")] + messages = [ChatMessage("user", ["Say 'Hello, World!' and nothing else."])] response = await client.get_response(messages=messages, options={"max_tokens": 50}) assert response is not None assert len(response.messages) > 0 - assert response.messages[0].role == Role.ASSISTANT + assert response.messages[0].role == "assistant" assert len(response.messages[0].text) > 0 assert response.usage_details is not None @@ -740,7 +738,7 @@ async def test_anthropic_client_integration_streaming_chat() -> None: """Integration test for streaming chat completion.""" client = AnthropicClient() - messages = [ChatMessage(role=Role.USER, text="Count from 1 to 5.")] + messages = [ChatMessage("user", ["Count from 1 to 5."])] chunks = [] async for chunk in client.get_streaming_response(messages=messages, options={"max_tokens": 50}): @@ -756,7 +754,7 @@ async def test_anthropic_client_integration_function_calling() -> None: """Integration test for function calling.""" client = AnthropicClient() - messages = [ChatMessage(role=Role.USER, text="What's the weather in San Francisco?")] + messages = [ChatMessage("user", ["What's the weather in San Francisco?"])] tools = [get_weather] response = await client.get_response( @@ -776,7 +774,7 @@ async def test_anthropic_client_integration_hosted_tools() -> None: """Integration test for hosted tools.""" client = AnthropicClient() - messages = [ChatMessage(role=Role.USER, text="What tools do you have available?")] + messages = [ChatMessage("user", ["What tools do you have available?"])] tools = [ HostedWebSearchTool(), HostedCodeInterpreterTool(), @@ -803,8 +801,8 @@ async def test_anthropic_client_integration_with_system_message() -> None: client = AnthropicClient() messages = [ - ChatMessage(role=Role.SYSTEM, text="You are a pirate. Always respond like a pirate."), - ChatMessage(role=Role.USER, text="Hello!"), + ChatMessage("system", ["You are a pirate. Always respond like a pirate."]), + ChatMessage("user", ["Hello!"]), ] response = await client.get_response(messages=messages, options={"max_tokens": 50}) @@ -819,7 +817,7 @@ async def test_anthropic_client_integration_temperature_control() -> None: """Integration test with temperature control.""" client = AnthropicClient() - messages = [ChatMessage(role=Role.USER, text="Say hello.")] + messages = [ChatMessage("user", ["Say hello."])] response = await client.get_response( messages=messages, @@ -837,11 +835,11 @@ async def test_anthropic_client_integration_ordering() -> None: client = AnthropicClient() messages = [ - ChatMessage(role=Role.USER, text="Say hello."), - ChatMessage(role=Role.USER, text="Then say goodbye."), - ChatMessage(role=Role.ASSISTANT, text="Thank you for chatting!"), - ChatMessage(role=Role.ASSISTANT, text="Let me know if I can help."), - ChatMessage(role=Role.USER, text="Just testing things."), + ChatMessage("user", ["Say hello."]), + ChatMessage("user", ["Then say goodbye."]), + ChatMessage("assistant", ["Thank you for chatting!"]), + ChatMessage("assistant", ["Let me know if I can help."]), + ChatMessage("user", ["Just testing things."]), ] response = await client.get_response(messages=messages) @@ -863,7 +861,7 @@ async def test_anthropic_client_integration_images() -> None: messages = [ ChatMessage( - role=Role.USER, + role="user", contents=[ Content.from_text(text="Describe this image"), Content.from_data(media_type="image/jpeg", data=image_bytes), diff --git a/python/packages/azure-ai-search/agent_framework_azure_ai_search/_search_provider.py b/python/packages/azure-ai-search/agent_framework_azure_ai_search/_search_provider.py index ac81a3c50b..e11d3e8793 100644 --- a/python/packages/azure-ai-search/agent_framework_azure_ai_search/_search_provider.py +++ b/python/packages/azure-ai-search/agent_framework_azure_ai_search/_search_provider.py @@ -5,7 +5,7 @@ from collections.abc import Awaitable, Callable, MutableSequence from typing import TYPE_CHECKING, Any, ClassVar, Literal -from agent_framework import AGENT_FRAMEWORK_USER_AGENT, ChatMessage, Context, ContextProvider, Role +from agent_framework import AGENT_FRAMEWORK_USER_AGENT, ChatMessage, Context, ContextProvider from agent_framework._logging import get_logger from agent_framework._pydantic import AFBaseSettings from agent_framework.exceptions import ServiceInitializationError @@ -525,9 +525,7 @@ async def invoking( messages_list = [messages] if isinstance(messages, ChatMessage) else list(messages) filtered_messages = [ - msg - for msg in messages_list - if msg and msg.text and msg.text.strip() and msg.role in [Role.USER, Role.ASSISTANT] + msg for msg in messages_list if msg and msg.text and msg.text.strip() and msg.role in ["user", "assistant"] ] if not filtered_messages: @@ -548,8 +546,8 @@ async def invoking( return Context() # Create context messages: first message with prompt, then one message per result part - context_messages = [ChatMessage(role=Role.USER, text=self.context_prompt)] - context_messages.extend([ChatMessage(role=Role.USER, text=part) for part in search_result_parts]) + context_messages = [ChatMessage("user", [self.context_prompt])] + context_messages.extend([ChatMessage("user", [part]) for part in search_result_parts]) return Context(messages=context_messages) @@ -921,7 +919,7 @@ async def _agentic_search(self, messages: list[ChatMessage]) -> list[str]: # Medium/low reasoning uses messages with conversation history kb_messages = [ KnowledgeBaseMessage( - role=msg.role.value if hasattr(msg.role, "value") else str(msg.role), + role=msg.role if hasattr(msg.role, "value") else str(msg.role), content=[KnowledgeBaseMessageTextContent(text=msg.text)], ) for msg in messages diff --git a/python/packages/azure-ai-search/tests/test_search_provider.py b/python/packages/azure-ai-search/tests/test_search_provider.py index 66ead79a6b..d348f3ef79 100644 --- a/python/packages/azure-ai-search/tests/test_search_provider.py +++ b/python/packages/azure-ai-search/tests/test_search_provider.py @@ -5,7 +5,7 @@ from unittest.mock import AsyncMock, MagicMock, patch import pytest -from agent_framework import ChatMessage, Context, Role +from agent_framework import ChatMessage, Context from agent_framework.azure import AzureAISearchContextProvider, AzureAISearchSettings from agent_framework.exceptions import ServiceInitializationError from azure.core.credentials import AzureKeyCredential @@ -39,7 +39,7 @@ def mock_index_client() -> AsyncMock: def sample_messages() -> list[ChatMessage]: """Create sample chat messages for testing.""" return [ - ChatMessage(role=Role.USER, text="What is in the documents?"), + ChatMessage("user", ["What is in the documents?"]), ] @@ -318,7 +318,7 @@ async def test_semantic_search_empty_query(self, mock_search_class: MagicMock) - ) # Empty message - context = await provider.invoking([ChatMessage(role=Role.USER, text="")]) + context = await provider.invoking([ChatMessage("user", [""])]) assert isinstance(context, Context) assert len(context.messages) == 0 @@ -520,10 +520,10 @@ async def test_filters_non_user_assistant_messages(self, mock_search_class: Magi # Mix of message types messages = [ - ChatMessage(role=Role.SYSTEM, text="System message"), - ChatMessage(role=Role.USER, text="User message"), - ChatMessage(role=Role.ASSISTANT, text="Assistant message"), - ChatMessage(role=Role.TOOL, text="Tool message"), + ChatMessage("system", ["System message"]), + ChatMessage("user", ["User message"]), + ChatMessage("assistant", ["Assistant message"]), + ChatMessage("tool", ["Tool message"]), ] context = await provider.invoking(messages) @@ -548,9 +548,9 @@ async def test_filters_empty_messages(self, mock_search_class: MagicMock) -> Non # Messages with empty/whitespace text messages = [ - ChatMessage(role=Role.USER, text=""), - ChatMessage(role=Role.USER, text=" "), - ChatMessage(role=Role.USER, text=None), + ChatMessage("user", [""]), + ChatMessage("user", [" "]), + ChatMessage("user", [None]), ] context = await provider.invoking(messages) @@ -581,7 +581,7 @@ async def test_citations_included_in_semantic_search(self, mock_search_class: Ma mode="semantic", ) - context = await provider.invoking([ChatMessage(role=Role.USER, text="test query")]) + context = await provider.invoking([ChatMessage("user", ["test query"])]) # Check that citation is included assert isinstance(context, Context) diff --git a/python/packages/azure-ai/agent_framework_azure_ai/_chat_client.py b/python/packages/azure-ai/agent_framework_azure_ai/_chat_client.py index 540aacbca2..e2c1c79bdb 100644 --- a/python/packages/azure-ai/agent_framework_azure_ai/_chat_client.py +++ b/python/packages/azure-ai/agent_framework_azure_ai/_chat_client.py @@ -26,7 +26,6 @@ HostedMCPTool, HostedWebSearchTool, Middleware, - Role, TextSpanRegion, ToolProtocol, UsageDetails, @@ -353,7 +352,7 @@ async def _inner_get_response( options: dict[str, Any], **kwargs: Any, ) -> ChatResponse: - return await ChatResponse.from_chat_response_generator( + return await ChatResponse.from_update_generator( updates=self._inner_get_streaming_response(messages=messages, options=options, **kwargs), output_format_type=options.get("response_format"), ) @@ -638,7 +637,7 @@ async def _process_stream( match event_data: case MessageDeltaChunk(): # only one event_type: AgentStreamEvent.THREAD_MESSAGE_DELTA - role = Role.USER if event_data.delta.role == MessageRole.USER else Role.ASSISTANT + role = "user" if event_data.delta.role == "user" else "assistant" # Extract URL citations from the delta chunk url_citations = self._extract_url_citations(event_data, azure_search_tool_calls) @@ -688,7 +687,7 @@ async def _process_stream( ) if function_call_contents: yield ChatResponseUpdate( - role=Role.ASSISTANT, + role="assistant", contents=function_call_contents, conversation_id=thread_id, message_id=response_id, @@ -704,7 +703,7 @@ async def _process_stream( message_id=response_id, raw_representation=event_data, response_id=response_id, - role=Role.ASSISTANT, + role="assistant", model_id=event_data.model, ) @@ -733,7 +732,7 @@ async def _process_stream( ) ) yield ChatResponseUpdate( - role=Role.ASSISTANT, + role="assistant", contents=[usage_content], conversation_id=thread_id, message_id=response_id, @@ -747,7 +746,7 @@ async def _process_stream( message_id=response_id, raw_representation=event_data, response_id=response_id, - role=Role.ASSISTANT, + role="assistant", ) case RunStepDeltaChunk(): # type: ignore if ( @@ -776,7 +775,7 @@ async def _process_stream( Content.from_hosted_file(file_id=output.image.file_id) ) yield ChatResponseUpdate( - role=Role.ASSISTANT, + role="assistant", contents=code_contents, conversation_id=thread_id, message_id=response_id, @@ -795,7 +794,7 @@ async def _process_stream( message_id=response_id, raw_representation=event_data, # type: ignore response_id=response_id, - role=Role.ASSISTANT, + role="assistant", ) except Exception as ex: logger.error(f"Error processing stream: {ex}") @@ -1077,7 +1076,7 @@ def _prepare_messages( additional_messages: list[ThreadMessageOptions] | None = None for chat_message in messages: - if chat_message.role.value in ["system", "developer"]: + if chat_message.role in ["system", "developer"]: for text_content in [content for content in chat_message.contents if content.type == "text"]: instructions.append(text_content.text) # type: ignore[arg-type] continue @@ -1107,7 +1106,7 @@ def _prepare_messages( additional_messages = [] additional_messages.append( ThreadMessageOptions( - role=MessageRole.AGENT if chat_message.role == Role.ASSISTANT else MessageRole.USER, + role=MessageRole.AGENT if chat_message.role == "assistant" else MessageRole.USER, content=message_contents, ) ) diff --git a/python/packages/azure-ai/agent_framework_azure_ai/_client.py b/python/packages/azure-ai/agent_framework_azure_ai/_client.py index 202002a45f..15bcd7cfc9 100644 --- a/python/packages/azure-ai/agent_framework_azure_ai/_client.py +++ b/python/packages/azure-ai/agent_framework_azure_ai/_client.py @@ -482,7 +482,7 @@ def _prepare_messages_for_azure_ai( # System/developer messages are turned into instructions, since there is no such message roles in Azure AI. for message in messages: - if message.role.value in ["system", "developer"]: + if message.role in ["system", "developer"]: for text_content in [content for content in message.contents if content.type == "text"]: instructions_list.append(text_content.text) # type: ignore[arg-type] else: diff --git a/python/packages/azure-ai/tests/test_azure_ai_agent_client.py b/python/packages/azure-ai/tests/test_azure_ai_agent_client.py index 4366ea8141..76c1c75252 100644 --- a/python/packages/azure-ai/tests/test_azure_ai_agent_client.py +++ b/python/packages/azure-ai/tests/test_azure_ai_agent_client.py @@ -22,7 +22,6 @@ HostedFileSearchTool, HostedMCPTool, HostedWebSearchTool, - Role, tool, ) from agent_framework._serialization import SerializationMixin @@ -309,7 +308,7 @@ async def empty_async_iter(): mock_stream.__aenter__ = AsyncMock(return_value=empty_async_iter()) mock_stream.__aexit__ = AsyncMock(return_value=None) - messages = [ChatMessage(role=Role.USER, text="Hello")] + messages = [ChatMessage("user", ["Hello"])] # Call without existing thread - should create new one response = chat_client.get_streaming_response(messages) @@ -336,7 +335,7 @@ async def test_azure_ai_chat_client_prepare_options_basic(mock_agents_client: Ma """Test _prepare_options with basic ChatOptions.""" chat_client = create_test_azure_ai_chat_client(mock_agents_client) - messages = [ChatMessage(role=Role.USER, text="Hello")] + messages = [ChatMessage("user", ["Hello"])] chat_options: ChatOptions = {"max_tokens": 100, "temperature": 0.7} run_options, tool_results = await chat_client._prepare_options(messages, chat_options) # type: ignore @@ -349,7 +348,7 @@ async def test_azure_ai_chat_client_prepare_options_no_chat_options(mock_agents_ """Test _prepare_options with default ChatOptions.""" chat_client = create_test_azure_ai_chat_client(mock_agents_client) - messages = [ChatMessage(role=Role.USER, text="Hello")] + messages = [ChatMessage("user", ["Hello"])] run_options, tool_results = await chat_client._prepare_options(messages, {}) # type: ignore @@ -366,7 +365,7 @@ async def test_azure_ai_chat_client_prepare_options_with_image_content(mock_agen mock_agents_client.get_agent = AsyncMock(return_value=None) image_content = Content.from_uri(uri="https://example.com/image.jpg", media_type="image/jpeg") - messages = [ChatMessage(role=Role.USER, contents=[image_content])] + messages = [ChatMessage("user", [image_content])] run_options, _ = await chat_client._prepare_options(messages, {}) # type: ignore @@ -455,8 +454,8 @@ async def test_azure_ai_chat_client_prepare_options_with_messages(mock_agents_cl # Test with system message (becomes instruction) messages = [ - ChatMessage(role=Role.SYSTEM, text="You are a helpful assistant"), - ChatMessage(role=Role.USER, text="Hello"), + ChatMessage("system", ["You are a helpful assistant"]), + ChatMessage("user", ["Hello"]), ] run_options, _ = await chat_client._prepare_options(messages, {}) # type: ignore @@ -478,7 +477,7 @@ async def test_azure_ai_chat_client_prepare_options_with_instructions_from_optio chat_client = create_test_azure_ai_chat_client(mock_agents_client, agent_id="test-agent") mock_agents_client.get_agent = AsyncMock(return_value=None) - messages = [ChatMessage(role=Role.USER, text="Hello")] + messages = [ChatMessage("user", ["Hello"])] chat_options: ChatOptions = { "instructions": "You are a thoughtful reviewer. Give brief feedback.", } @@ -501,8 +500,8 @@ async def test_azure_ai_chat_client_prepare_options_merges_instructions_from_mes mock_agents_client.get_agent = AsyncMock(return_value=None) messages = [ - ChatMessage(role=Role.SYSTEM, text="Context: You are reviewing marketing copy."), - ChatMessage(role=Role.USER, text="Review this tagline"), + ChatMessage("system", ["Context: You are reviewing marketing copy."]), + ChatMessage("user", ["Review this tagline"]), ] chat_options: ChatOptions = { "instructions": "Be concise and constructive in your feedback.", @@ -520,17 +519,17 @@ async def test_azure_ai_chat_client_prepare_options_merges_instructions_from_mes async def test_azure_ai_chat_client_inner_get_response(mock_agents_client: MagicMock) -> None: """Test _inner_get_response method.""" chat_client = create_test_azure_ai_chat_client(mock_agents_client, agent_id="test-agent") - messages = [ChatMessage(role=Role.USER, text="Hello")] + messages = [ChatMessage("user", ["Hello"])] chat_options: ChatOptions = {} async def mock_streaming_response(): - yield ChatResponseUpdate(role=Role.ASSISTANT, text="Hello back") + yield ChatResponseUpdate(role="assistant", text="Hello back") with ( patch.object(chat_client, "_inner_get_streaming_response", return_value=mock_streaming_response()), - patch("agent_framework.ChatResponse.from_chat_response_generator") as mock_from_generator, + patch("agent_framework.ChatResponse.from_update_generator") as mock_from_generator, ): - mock_response = ChatResponse(role=Role.ASSISTANT, text="Hello back") + mock_response = ChatResponse(messages=ChatMessage("assistant", ["Hello back"])) mock_from_generator.return_value = mock_response result = await chat_client._inner_get_response(messages=messages, options=chat_options) # type: ignore @@ -673,7 +672,7 @@ async def test_azure_ai_chat_client_prepare_options_tool_choice_required_specifi dict_tool = {"type": "function", "function": {"name": "test_function"}} chat_options = {"tools": [dict_tool], "tool_choice": required_tool_mode} - messages = [ChatMessage(role=Role.USER, text="Hello")] + messages = [ChatMessage("user", ["Hello"])] run_options, _ = await chat_client._prepare_options(messages, chat_options) # type: ignore @@ -718,7 +717,7 @@ async def test_azure_ai_chat_client_prepare_options_mcp_never_require(mock_agent mcp_tool = HostedMCPTool(name="Test MCP Tool", url="https://example.com/mcp", approval_mode="never_require") - messages = [ChatMessage(role=Role.USER, text="Hello")] + messages = [ChatMessage("user", ["Hello"])] chat_options: ChatOptions = {"tools": [mcp_tool], "tool_choice": "auto"} with patch("agent_framework_azure_ai._shared.McpTool") as mock_mcp_tool_class: @@ -750,7 +749,7 @@ async def test_azure_ai_chat_client_prepare_options_mcp_with_headers(mock_agents name="Test MCP Tool", url="https://example.com/mcp", headers=headers, approval_mode="never_require" ) - messages = [ChatMessage(role=Role.USER, text="Hello")] + messages = [ChatMessage("user", ["Hello"])] chat_options: ChatOptions = {"tools": [mcp_tool], "tool_choice": "auto"} with patch("agent_framework_azure_ai._shared.McpTool") as mock_mcp_tool_class: @@ -1409,7 +1408,7 @@ async def test_azure_ai_chat_client_get_response() -> None: "It's a beautiful day for outdoor activities.", ) ) - messages.append(ChatMessage(role="user", text="What's the weather like today?")) + messages.append(ChatMessage("user", ["What's the weather like today?"])) # Test that the agents_client can be used to get a response response = await azure_ai_chat_client.get_response(messages=messages) @@ -1427,7 +1426,7 @@ async def test_azure_ai_chat_client_get_response_tools() -> None: assert isinstance(azure_ai_chat_client, ChatClientProtocol) messages: list[ChatMessage] = [] - messages.append(ChatMessage(role="user", text="What's the weather like in Seattle?")) + messages.append(ChatMessage("user", ["What's the weather like in Seattle?"])) # Test that the agents_client can be used to get a response response = await azure_ai_chat_client.get_response( @@ -1455,7 +1454,7 @@ async def test_azure_ai_chat_client_streaming() -> None: "It's a beautiful day for outdoor activities.", ) ) - messages.append(ChatMessage(role="user", text="What's the weather like today?")) + messages.append(ChatMessage("user", ["What's the weather like today?"])) # Test that the agents_client can be used to get a response response = azure_ai_chat_client.get_streaming_response(messages=messages) @@ -1479,7 +1478,7 @@ async def test_azure_ai_chat_client_streaming_tools() -> None: assert isinstance(azure_ai_chat_client, ChatClientProtocol) messages: list[ChatMessage] = [] - messages.append(ChatMessage(role="user", text="What's the weather like in Seattle?")) + messages.append(ChatMessage("user", ["What's the weather like in Seattle?"])) # Test that the agents_client can be used to get a response response = azure_ai_chat_client.get_streaming_response( @@ -2098,7 +2097,7 @@ def test_azure_ai_chat_client_prepare_messages_with_function_result( chat_client = create_test_azure_ai_chat_client(mock_agents_client) function_result = Content.from_function_result(call_id='["run_123", "call_456"]', result="test result") - messages = [ChatMessage(role=Role.USER, contents=[function_result])] + messages = [ChatMessage("user", [function_result])] additional_messages, instructions, required_action_results = chat_client._prepare_messages(messages) # type: ignore @@ -2118,7 +2117,7 @@ def test_azure_ai_chat_client_prepare_messages_with_raw_content_block( # Create content with raw_representation that is a MessageInputContentBlock raw_block = MessageInputTextBlock(text="Raw block text") custom_content = Content(type="custom", raw_representation=raw_block) - messages = [ChatMessage(role=Role.USER, contents=[custom_content])] + messages = [ChatMessage("user", [custom_content])] additional_messages, instructions, required_action_results = chat_client._prepare_messages(messages) # type: ignore diff --git a/python/packages/azure-ai/tests/test_azure_ai_client.py b/python/packages/azure-ai/tests/test_azure_ai_client.py index 694bcb6604..8563d78cbf 100644 --- a/python/packages/azure-ai/tests/test_azure_ai_client.py +++ b/python/packages/azure-ai/tests/test_azure_ai_client.py @@ -22,7 +22,6 @@ HostedFileSearchTool, HostedMCPTool, HostedWebSearchTool, - Role, tool, ) from agent_framework.exceptions import ServiceInitializationError @@ -299,16 +298,16 @@ async def test_prepare_messages_for_azure_ai_with_system_messages( client = create_test_azure_ai_client(mock_project_client) messages = [ - ChatMessage(role=Role.SYSTEM, contents=[Content.from_text(text="You are a helpful assistant.")]), - ChatMessage(role=Role.USER, contents=[Content.from_text(text="Hello")]), - ChatMessage(role=Role.ASSISTANT, contents=[Content.from_text(text="System response")]), + ChatMessage("system", [Content.from_text(text="You are a helpful assistant.")]), + ChatMessage("user", [Content.from_text(text="Hello")]), + ChatMessage("assistant", [Content.from_text(text="System response")]), ] result_messages, instructions = client._prepare_messages_for_azure_ai(messages) # type: ignore assert len(result_messages) == 2 - assert result_messages[0].role == Role.USER - assert result_messages[1].role == Role.ASSISTANT + assert result_messages[0].role == "user" + assert result_messages[1].role == "assistant" assert instructions == "You are a helpful assistant." @@ -319,8 +318,8 @@ async def test_prepare_messages_for_azure_ai_no_system_messages( client = create_test_azure_ai_client(mock_project_client) messages = [ - ChatMessage(role=Role.USER, contents=[Content.from_text(text="Hello")]), - ChatMessage(role=Role.ASSISTANT, contents=[Content.from_text(text="Hi there!")]), + ChatMessage("user", [Content.from_text(text="Hello")]), + ChatMessage("assistant", [Content.from_text(text="Hi there!")]), ] result_messages, instructions = client._prepare_messages_for_azure_ai(messages) # type: ignore @@ -420,7 +419,7 @@ async def test_prepare_options_basic(mock_project_client: MagicMock) -> None: """Test prepare_options basic functionality.""" client = create_test_azure_ai_client(mock_project_client, agent_name="test-agent", agent_version="1.0") - messages = [ChatMessage(role=Role.USER, contents=[Content.from_text(text="Hello")])] + messages = [ChatMessage("user", [Content.from_text(text="Hello")])] with ( patch.object(client.__class__.__bases__[0], "_prepare_options", return_value={"model": "test-model"}), @@ -454,7 +453,7 @@ async def test_prepare_options_with_application_endpoint( agent_version="1", ) - messages = [ChatMessage(role=Role.USER, contents=[Content.from_text(text="Hello")])] + messages = [ChatMessage("user", [Content.from_text(text="Hello")])] with ( patch.object(client.__class__.__bases__[0], "_prepare_options", return_value={"model": "test-model"}), @@ -493,7 +492,7 @@ async def test_prepare_options_with_application_project_client( agent_version="1", ) - messages = [ChatMessage(role=Role.USER, contents=[Content.from_text(text="Hello")])] + messages = [ChatMessage("user", [Content.from_text(text="Hello")])] with ( patch.object(client.__class__.__bases__[0], "_prepare_options", return_value={"model": "test-model"}), @@ -969,7 +968,7 @@ async def test_prepare_options_excludes_response_format( """Test that prepare_options excludes response_format, text, and text_format from final run options.""" client = create_test_azure_ai_client(mock_project_client, agent_name="test-agent", agent_version="1.0") - messages = [ChatMessage(role=Role.USER, contents=[Content.from_text(text="Hello")])] + messages = [ChatMessage("user", [Content.from_text(text="Hello")])] chat_options: ChatOptions = {} with ( @@ -1355,10 +1354,10 @@ async def test_integration_options( # Prepare test message if option_name.startswith("tool_choice"): # Use weather-related prompt for tool tests - messages = [ChatMessage(role="user", text="What is the weather in Seattle?")] + messages = [ChatMessage("user", ["What is the weather in Seattle?"])] else: # Generic prompt for simple options - messages = [ChatMessage(role="user", text="Say 'Hello World' briefly.")] + messages = [ChatMessage("user", ["Say 'Hello World' briefly."])] # Build options dict options: dict[str, Any] = {option_name: option_value, "tools": [get_weather]} @@ -1372,7 +1371,7 @@ async def test_integration_options( ) output_format = option_value if option_name == "response_format" else None - response = await ChatResponse.from_chat_response_generator(response_gen, output_format_type=output_format) + response = await ChatResponse.from_update_generator(response_gen, output_format_type=output_format) else: # Test non-streaming mode response = await client.get_response( @@ -1458,11 +1457,11 @@ async def test_integration_agent_options( # Prepare test message if option_name.startswith("response_format"): # Use prompt that works well with structured output - messages = [ChatMessage(role="user", text="The weather in Seattle is sunny")] - messages.append(ChatMessage(role="user", text="What is the weather in Seattle?")) + messages = [ChatMessage("user", ["The weather in Seattle is sunny"])] + messages.append(ChatMessage("user", ["What is the weather in Seattle?"])) else: # Generic prompt for simple options - messages = [ChatMessage(role="user", text="Say 'Hello World' briefly.")] + messages = [ChatMessage("user", ["Say 'Hello World' briefly."])] # Build options dict options = {option_name: option_value} @@ -1475,9 +1474,7 @@ async def test_integration_agent_options( ) output_format = option_value if option_name.startswith("response_format") else None - response = await ChatResponse.from_chat_response_generator( - response_gen, output_format_type=output_format - ) + response = await ChatResponse.from_update_generator(response_gen, output_format_type=output_format) else: # Test non-streaming mode response = await client.get_response( @@ -1519,7 +1516,7 @@ async def test_integration_web_search() -> None: }, } if streaming: - response = await ChatResponse.from_chat_response_generator(client.get_streaming_response(**content)) + response = await ChatResponse.from_update_generator(client.get_streaming_response(**content)) else: response = await client.get_response(**content) @@ -1544,7 +1541,7 @@ async def test_integration_web_search() -> None: }, } if streaming: - response = await ChatResponse.from_chat_response_generator(client.get_streaming_response(**content)) + response = await ChatResponse.from_update_generator(client.get_streaming_response(**content)) else: response = await client.get_response(**content) assert response.text is not None diff --git a/python/packages/azurefunctions/tests/test_app.py b/python/packages/azurefunctions/tests/test_app.py index f8b414fc34..d33ca1f99c 100644 --- a/python/packages/azurefunctions/tests/test_app.py +++ b/python/packages/azurefunctions/tests/test_app.py @@ -355,9 +355,7 @@ class TestAgentEntityOperations: async def test_entity_run_agent_operation(self) -> None: """Test that entity can run agent operation.""" mock_agent = Mock() - mock_agent.run = AsyncMock( - return_value=AgentResponse(messages=[ChatMessage(role="assistant", text="Test response")]) - ) + mock_agent.run = AsyncMock(return_value=AgentResponse(messages=[ChatMessage("assistant", ["Test response"])])) entity = AgentEntity(mock_agent, state_provider=_InMemoryStateProvider(thread_id="test-conv-123")) @@ -373,9 +371,7 @@ async def test_entity_run_agent_operation(self) -> None: async def test_entity_stores_conversation_history(self) -> None: """Test that the entity stores conversation history.""" mock_agent = Mock() - mock_agent.run = AsyncMock( - return_value=AgentResponse(messages=[ChatMessage(role="assistant", text="Response 1")]) - ) + mock_agent.run = AsyncMock(return_value=AgentResponse(messages=[ChatMessage("assistant", ["Response 1"])])) entity = AgentEntity(mock_agent, state_provider=_InMemoryStateProvider(thread_id="conv-1")) @@ -407,9 +403,7 @@ async def test_entity_stores_conversation_history(self) -> None: async def test_entity_increments_message_count(self) -> None: """Test that the entity increments the message count.""" mock_agent = Mock() - mock_agent.run = AsyncMock( - return_value=AgentResponse(messages=[ChatMessage(role="assistant", text="Response")]) - ) + mock_agent.run = AsyncMock(return_value=AgentResponse(messages=[ChatMessage("assistant", ["Response"])])) entity = AgentEntity(mock_agent, state_provider=_InMemoryStateProvider(thread_id="conv-1")) @@ -448,9 +442,7 @@ def test_create_agent_entity_returns_function(self) -> None: def test_entity_function_handles_run_operation(self) -> None: """Test that the entity function handles the run operation.""" mock_agent = Mock() - mock_agent.run = AsyncMock( - return_value=AgentResponse(messages=[ChatMessage(role="assistant", text="Response")]) - ) + mock_agent.run = AsyncMock(return_value=AgentResponse(messages=[ChatMessage("assistant", ["Response"])])) entity_function = create_agent_entity(mock_agent) @@ -475,9 +467,7 @@ def test_entity_function_handles_run_operation(self) -> None: def test_entity_function_handles_run_agent_operation(self) -> None: """Test that the entity function handles the deprecated run_agent operation for backward compatibility.""" mock_agent = Mock() - mock_agent.run = AsyncMock( - return_value=AgentResponse(messages=[ChatMessage(role="assistant", text="Response")]) - ) + mock_agent.run = AsyncMock(return_value=AgentResponse(messages=[ChatMessage("assistant", ["Response"])])) entity_function = create_agent_entity(mock_agent) diff --git a/python/packages/azurefunctions/tests/test_entities.py b/python/packages/azurefunctions/tests/test_entities.py index 555b588887..909dedd6f8 100644 --- a/python/packages/azurefunctions/tests/test_entities.py +++ b/python/packages/azurefunctions/tests/test_entities.py @@ -10,7 +10,7 @@ from unittest.mock import AsyncMock, Mock import pytest -from agent_framework import AgentResponse, ChatMessage, Role +from agent_framework import AgentResponse, ChatMessage from agent_framework_azurefunctions._entities import create_agent_entity @@ -19,11 +19,7 @@ def _agent_response(text: str | None) -> AgentResponse: """Create an AgentResponse with a single assistant message.""" - message = ( - ChatMessage(role=Role.ASSISTANT, text=text) - if text is not None - else ChatMessage(role=Role.ASSISTANT, contents=[]) - ) + message = ChatMessage("assistant", [text]) if text is not None else ChatMessage("assistant", []) return AgentResponse(messages=[message]) diff --git a/python/packages/azurefunctions/tests/test_orchestration.py b/python/packages/azurefunctions/tests/test_orchestration.py index 2b9a4126d4..1f8a029dba 100644 --- a/python/packages/azurefunctions/tests/test_orchestration.py +++ b/python/packages/azurefunctions/tests/test_orchestration.py @@ -6,7 +6,7 @@ from unittest.mock import Mock import pytest -from agent_framework import AgentResponse, ChatMessage, Role +from agent_framework import AgentResponse, ChatMessage from agent_framework_durabletask import DurableAIAgent from azure.durable_functions.models.Task import TaskBase, TaskState @@ -136,7 +136,7 @@ def test_try_set_value_success(self) -> None: # Simulate successful entity task completion entity_task.state = TaskState.SUCCEEDED - entity_task.result = AgentResponse(messages=[ChatMessage(role="assistant", text="Test response")]).to_dict() + entity_task.result = AgentResponse(messages=[ChatMessage("assistant", ["Test response"])]).to_dict() # Clear pending_tasks to simulate that parent has processed the child task.pending_tasks.clear() @@ -178,7 +178,7 @@ class TestSchema(BaseModel): # Simulate successful entity task with JSON response entity_task.state = TaskState.SUCCEEDED - entity_task.result = AgentResponse(messages=[ChatMessage(role="assistant", text='{"answer": "42"}')]).to_dict() + entity_task.result = AgentResponse(messages=[ChatMessage("assistant", ['{"answer": "42"}'])]).to_dict() # Clear pending_tasks to simulate that parent has processed the child task.pending_tasks.clear() @@ -254,7 +254,7 @@ def test_fire_and_forget_returns_acceptance_response(self, executor_with_uuid: t response = result.result assert isinstance(response, AgentResponse) assert len(response.messages) == 1 - assert response.messages[0].role == Role.SYSTEM + assert response.messages[0].role == "system" # Check message contains key information message_text = response.messages[0].text assert "accepted" in message_text.lower() diff --git a/python/packages/bedrock/agent_framework_bedrock/_chat_client.py b/python/packages/bedrock/agent_framework_bedrock/_chat_client.py index d7e0754c2b..bc67bc7908 100644 --- a/python/packages/bedrock/agent_framework_bedrock/_chat_client.py +++ b/python/packages/bedrock/agent_framework_bedrock/_chat_client.py @@ -16,9 +16,7 @@ ChatResponse, ChatResponseUpdate, Content, - FinishReason, FunctionTool, - Role, ToolProtocol, UsageDetails, get_logger, @@ -185,20 +183,20 @@ class BedrockChatOptions(ChatOptions[TResponseModel], Generic[TResponseModel], t # endregion -ROLE_MAP: dict[Role, str] = { - Role.USER: "user", - Role.ASSISTANT: "assistant", - Role.SYSTEM: "user", - Role.TOOL: "user", +ROLE_MAP: dict[str, str] = { + "user": "user", + "assistant": "assistant", + "system": "user", + "tool": "user", } -FINISH_REASON_MAP: dict[str, FinishReason] = { - "end_turn": FinishReason.STOP, - "stop_sequence": FinishReason.STOP, - "max_tokens": FinishReason.LENGTH, - "length": FinishReason.LENGTH, - "content_filtered": FinishReason.CONTENT_FILTER, - "tool_use": FinishReason.TOOL_CALLS, +FINISH_REASON_MAP: dict[str, str] = { + "end_turn": "stop", + "stop_sequence": "stop", + "max_tokens": "length", + "length": "length", + "content_filtered": "content_filter", + "tool_use": "tool_calls", } @@ -397,7 +395,7 @@ def _prepare_bedrock_messages( conversation: list[dict[str, Any]] = [] pending_tool_use_ids: deque[str] = deque() for message in messages: - if message.role == Role.SYSTEM: + if message.role == "system": text_value = message.text if text_value: prompts.append({"text": text_value}) @@ -414,7 +412,7 @@ def _prepare_bedrock_messages( for block in content_blocks if isinstance(block, MutableMapping) and "toolUse" in block ) - elif message.role == Role.TOOL: + elif message.role == "tool": content_blocks = self._align_tool_results_with_pending(content_blocks, pending_tool_use_ids) pending_tool_use_ids.clear() if not content_blocks: @@ -574,7 +572,7 @@ def _process_converse_response(self, response: dict[str, Any]) -> ChatResponse: message = output.get("message", {}) content_blocks = message.get("content", []) or [] contents = self._parse_message_contents(content_blocks) - chat_message = ChatMessage(role=Role.ASSISTANT, contents=contents, raw_representation=message) + chat_message = ChatMessage("assistant", contents, raw_representation=message) usage_details = self._parse_usage(response.get("usage") or output.get("usage")) finish_reason = self._map_finish_reason(output.get("completionReason") or response.get("stopReason")) response_id = response.get("responseId") or message.get("id") @@ -642,7 +640,7 @@ def _parse_message_contents(self, content_blocks: Sequence[MutableMapping[str, A logger.debug("Ignoring unsupported Bedrock content block: %s", block) return contents - def _map_finish_reason(self, reason: str | None) -> FinishReason | None: + def _map_finish_reason(self, reason: str | None) -> str | None: if not reason: return None return FINISH_REASON_MAP.get(reason.lower()) diff --git a/python/packages/bedrock/tests/test_bedrock_client.py b/python/packages/bedrock/tests/test_bedrock_client.py index 704eb2138a..7addad3b73 100644 --- a/python/packages/bedrock/tests/test_bedrock_client.py +++ b/python/packages/bedrock/tests/test_bedrock_client.py @@ -6,7 +6,7 @@ from typing import Any import pytest -from agent_framework import ChatMessage, Content, Role +from agent_framework import ChatMessage, Content from agent_framework.exceptions import ServiceInitializationError from agent_framework_bedrock import BedrockChatClient @@ -42,8 +42,8 @@ def test_get_response_invokes_bedrock_runtime() -> None: ) messages = [ - ChatMessage(role=Role.SYSTEM, contents=[Content.from_text(text="You are concise.")]), - ChatMessage(role=Role.USER, contents=[Content.from_text(text="hello")]), + ChatMessage("system", [Content.from_text(text="You are concise.")]), + ChatMessage("user", [Content.from_text(text="hello")]), ] response = asyncio.run(client.get_response(messages=messages, options={"max_tokens": 32})) @@ -63,7 +63,7 @@ def test_build_request_requires_non_system_messages() -> None: client=_StubBedrockRuntime(), ) - messages = [ChatMessage(role=Role.SYSTEM, contents=[Content.from_text(text="Only system text")])] + messages = [ChatMessage("system", [Content.from_text(text="Only system text")])] with pytest.raises(ServiceInitializationError): client._prepare_options(messages, {}) diff --git a/python/packages/bedrock/tests/test_bedrock_settings.py b/python/packages/bedrock/tests/test_bedrock_settings.py index d98cf00817..124892e51d 100644 --- a/python/packages/bedrock/tests/test_bedrock_settings.py +++ b/python/packages/bedrock/tests/test_bedrock_settings.py @@ -10,7 +10,6 @@ ChatOptions, Content, FunctionTool, - Role, ) from pydantic import BaseModel @@ -47,7 +46,7 @@ def test_build_request_includes_tool_config() -> None: "tools": [tool], "tool_choice": {"mode": "required", "required_function_name": "get_weather"}, } - messages = [ChatMessage(role=Role.USER, contents=[Content.from_text(text="hi")])] + messages = [ChatMessage("user", [Content.from_text(text="hi")])] request = client._prepare_options(messages, options) @@ -59,15 +58,15 @@ def test_build_request_serializes_tool_history() -> None: client = _build_client() options: ChatOptions = {} messages = [ - ChatMessage(role=Role.USER, contents=[Content.from_text(text="how's weather?")]), + ChatMessage("user", [Content.from_text(text="how's weather?")]), ChatMessage( - role=Role.ASSISTANT, + role="assistant", contents=[ Content.from_function_call(call_id="call-1", name="get_weather", arguments='{"location": "SEA"}') ], ), ChatMessage( - role=Role.TOOL, + role="tool", contents=[Content.from_function_result(call_id="call-1", result={"answer": "72F"})], ), ] diff --git a/python/packages/chatkit/agent_framework_chatkit/_converter.py b/python/packages/chatkit/agent_framework_chatkit/_converter.py index 894d54831d..457cfc5e1e 100644 --- a/python/packages/chatkit/agent_framework_chatkit/_converter.py +++ b/python/packages/chatkit/agent_framework_chatkit/_converter.py @@ -9,7 +9,6 @@ from agent_framework import ( ChatMessage, Content, - Role, ) from chatkit.types import ( AssistantMessageItem, @@ -101,21 +100,21 @@ async def user_message_to_input( # If only text and no attachments, use text parameter for simplicity if text_content.strip() and not data_contents: - user_message = ChatMessage(role=Role.USER, text=text_content.strip()) + user_message = ChatMessage("user", [text_content.strip()]) else: # Build contents list with both text and attachments contents: list[Content] = [] if text_content.strip(): contents.append(Content.from_text(text=text_content.strip())) contents.extend(data_contents) - user_message = ChatMessage(role=Role.USER, contents=contents) + user_message = ChatMessage("user", contents) # Handle quoted text if this is the last message messages = [user_message] if item.quoted_text and is_last_message: quoted_context = ChatMessage( - role=Role.USER, - text=f"The user is referring to this in particular:\n{item.quoted_text}", + "user", + [f"The user is referring to this in particular:\n{item.quoted_text}"], ) # Prepend quoted context before the main message messages.insert(0, quoted_context) @@ -214,7 +213,7 @@ def hidden_context_to_input( message = converter.hidden_context_to_input(hidden_item) # Returns: ChatMessage(role=SYSTEM, text="User's email: ...") """ - return ChatMessage(role=Role.SYSTEM, text=f"{item.content}") + return ChatMessage("system", [f"{item.content}"]) def tag_to_message_content(self, tag: UserMessageTagContent) -> Content: """Convert a ChatKit tag (@-mention) to Agent Framework content. @@ -293,7 +292,7 @@ def task_to_input(self, item: TaskItem) -> ChatMessage | list[ChatMessage] | Non f"A message was displayed to the user that the following task was performed:\n\n{task_text}\n" ) - return ChatMessage(role=Role.USER, text=text) + return ChatMessage("user", [text]) def workflow_to_input(self, item: WorkflowItem) -> ChatMessage | list[ChatMessage] | None: """Convert a ChatKit WorkflowItem to Agent Framework ChatMessage(s). @@ -348,7 +347,7 @@ def workflow_to_input(self, item: WorkflowItem) -> ChatMessage | list[ChatMessag f"\n{task_text}\n" ) - messages.append(ChatMessage(role=Role.USER, text=text)) + messages.append(ChatMessage("user", [text])) return messages if messages else None @@ -390,7 +389,7 @@ def widget_to_input(self, item: WidgetItem) -> ChatMessage | list[ChatMessage] | try: widget_json = item.widget.model_dump_json(exclude_unset=True, exclude_none=True) text = f"The following graphical UI widget (id: {item.id}) was displayed to the user:{widget_json}" - return ChatMessage(role=Role.USER, text=text) + return ChatMessage("user", [text]) except Exception: # If JSON serialization fails, skip the widget return None @@ -416,7 +415,7 @@ async def assistant_message_to_input(self, item: AssistantMessageItem) -> ChatMe if not text_parts: return None - return ChatMessage(role=Role.ASSISTANT, text="".join(text_parts)) + return ChatMessage("assistant", ["".join(text_parts)]) async def client_tool_call_to_input(self, item: ClientToolCallItem) -> ChatMessage | list[ChatMessage] | None: """Convert a ChatKit ClientToolCallItem to Agent Framework ChatMessage(s). @@ -442,7 +441,7 @@ async def client_tool_call_to_input(self, item: ClientToolCallItem) -> ChatMessa # Create function call message function_call_msg = ChatMessage( - role=Role.ASSISTANT, + role="assistant", contents=[ Content.from_function_call( call_id=item.call_id, @@ -454,7 +453,7 @@ async def client_tool_call_to_input(self, item: ClientToolCallItem) -> ChatMessa # Create function result message function_result_msg = ChatMessage( - role=Role.TOOL, + role="tool", contents=[ Content.from_function_result( call_id=item.call_id, diff --git a/python/packages/chatkit/tests/test_converter.py b/python/packages/chatkit/tests/test_converter.py index b75139bf58..71400527aa 100644 --- a/python/packages/chatkit/tests/test_converter.py +++ b/python/packages/chatkit/tests/test_converter.py @@ -5,7 +5,7 @@ from unittest.mock import Mock import pytest -from agent_framework import ChatMessage, Role +from agent_framework import ChatMessage from chatkit.types import UserMessageTextContent from agent_framework_chatkit import ThreadItemConverter, simple_to_agent_input @@ -44,7 +44,7 @@ async def test_to_agent_input_with_text(self, converter): assert len(result) == 1 assert isinstance(result[0], ChatMessage) - assert result[0].role == Role.USER + assert result[0].role == "user" assert result[0].text == "Hello, how can you help me?" async def test_to_agent_input_empty_text(self, converter): @@ -117,7 +117,7 @@ def test_hidden_context_to_input(self, converter): result = converter.hidden_context_to_input(hidden_item) assert isinstance(result, ChatMessage) - assert result.role == Role.SYSTEM + assert result.role == "system" assert result.text == "This is hidden context information" def test_tag_to_message_content(self, converter): @@ -234,7 +234,7 @@ async def test_to_agent_input_with_image_attachment(self): assert len(result) == 1 message = result[0] - assert message.role == Role.USER + assert message.role == "user" assert len(message.contents) == 2 # First content should be text @@ -303,7 +303,7 @@ def test_task_to_input(self, converter): result = converter.task_to_input(task_item) assert isinstance(result, ChatMessage) - assert result.role == Role.USER + assert result.role == "user" assert "Analysis: Analyzed the data" in result.text assert "" in result.text @@ -385,7 +385,7 @@ def test_widget_to_input(self, converter): result = converter.widget_to_input(widget_item) assert isinstance(result, ChatMessage) - assert result.role == Role.USER + assert result.role == "user" assert "widget_1" in result.text assert "graphical UI widget" in result.text @@ -418,5 +418,5 @@ async def test_simple_to_agent_input_with_text(self): assert len(result) == 1 assert isinstance(result[0], ChatMessage) - assert result[0].role == Role.USER + assert result[0].role == "user" assert result[0].text == "Test message" diff --git a/python/packages/chatkit/tests/test_streaming.py b/python/packages/chatkit/tests/test_streaming.py index ff552d79e8..c26a9cb7ac 100644 --- a/python/packages/chatkit/tests/test_streaming.py +++ b/python/packages/chatkit/tests/test_streaming.py @@ -4,7 +4,7 @@ from unittest.mock import Mock -from agent_framework import AgentResponseUpdate, Content, Role +from agent_framework import AgentResponseUpdate, Content from chatkit.types import ( ThreadItemAddedEvent, ThreadItemDoneEvent, @@ -34,7 +34,7 @@ async def test_stream_single_text_update(self): """Test streaming single text update.""" async def single_update_stream(): - yield AgentResponseUpdate(role=Role.ASSISTANT, contents=[Content.from_text(text="Hello world")]) + yield AgentResponseUpdate(role="assistant", contents=[Content.from_text(text="Hello world")]) events = [] async for event in stream_agent_response(single_update_stream(), thread_id="test_thread"): @@ -59,8 +59,8 @@ async def test_stream_multiple_text_updates(self): """Test streaming multiple text updates.""" async def multiple_updates_stream(): - yield AgentResponseUpdate(role=Role.ASSISTANT, contents=[Content.from_text(text="Hello ")]) - yield AgentResponseUpdate(role=Role.ASSISTANT, contents=[Content.from_text(text="world!")]) + yield AgentResponseUpdate(role="assistant", contents=[Content.from_text(text="Hello ")]) + yield AgentResponseUpdate(role="assistant", contents=[Content.from_text(text="world!")]) events = [] async for event in stream_agent_response(multiple_updates_stream(), thread_id="test_thread"): @@ -91,7 +91,7 @@ def custom_id_generator(item_type: str) -> str: return f"custom_{item_type}_123" async def single_update_stream(): - yield AgentResponseUpdate(role=Role.ASSISTANT, contents=[Content.from_text(text="Test")]) + yield AgentResponseUpdate(role="assistant", contents=[Content.from_text(text="Test")]) events = [] async for event in stream_agent_response( @@ -107,8 +107,8 @@ async def test_stream_empty_content_updates(self): """Test streaming updates with empty content.""" async def empty_content_stream(): - yield AgentResponseUpdate(role=Role.ASSISTANT, contents=[]) - yield AgentResponseUpdate(role=Role.ASSISTANT, contents=None) + yield AgentResponseUpdate(role="assistant", contents=[]) + yield AgentResponseUpdate(role="assistant", contents=None) events = [] async for event in stream_agent_response(empty_content_stream(), thread_id="test_thread"): @@ -131,7 +131,7 @@ async def test_stream_non_text_content(self): non_text_content.text = None async def non_text_stream(): - yield AgentResponseUpdate(role=Role.ASSISTANT, contents=[non_text_content]) + yield AgentResponseUpdate(role="assistant", contents=[non_text_content]) events = [] async for event in stream_agent_response(non_text_stream(), thread_id="test_thread"): diff --git a/python/packages/claude/agent_framework_claude/_agent.py b/python/packages/claude/agent_framework_claude/_agent.py index f8f3796656..f4439df851 100644 --- a/python/packages/claude/agent_framework_claude/_agent.py +++ b/python/packages/claude/agent_framework_claude/_agent.py @@ -16,7 +16,6 @@ Content, ContextProvider, FunctionTool, - Role, ToolProtocol, get_logger, normalize_messages, @@ -628,7 +627,7 @@ async def run_stream( text = delta.get("text", "") if text: yield AgentResponseUpdate( - role=Role.ASSISTANT, + role="assistant", contents=[Content.from_text(text=text, raw_representation=message)], raw_representation=message, ) @@ -636,7 +635,7 @@ async def run_stream( thinking = delta.get("thinking", "") if thinking: yield AgentResponseUpdate( - role=Role.ASSISTANT, + role="assistant", contents=[Content.from_text_reasoning(text=thinking, raw_representation=message)], raw_representation=message, ) diff --git a/python/packages/claude/tests/test_claude_agent.py b/python/packages/claude/tests/test_claude_agent.py index 15fc0b8090..d54489cd0d 100644 --- a/python/packages/claude/tests/test_claude_agent.py +++ b/python/packages/claude/tests/test_claude_agent.py @@ -4,7 +4,7 @@ from unittest.mock import AsyncMock, MagicMock, patch import pytest -from agent_framework import AgentResponseUpdate, AgentThread, ChatMessage, Content, Role, tool +from agent_framework import AgentResponseUpdate, AgentThread, ChatMessage, Content, tool from agent_framework_claude import ClaudeAgent, ClaudeAgentOptions, ClaudeAgentSettings from agent_framework_claude._agent import TOOLS_MCP_SERVER_NAME @@ -375,7 +375,7 @@ async def test_run_stream_yields_updates(self) -> None: updates.append(update) # StreamEvent yields text deltas assert len(updates) == 2 - assert updates[0].role == Role.ASSISTANT + assert updates[0].role == "assistant" assert updates[0].text == "Streaming " assert updates[1].text == "response" @@ -632,7 +632,7 @@ def test_format_user_message(self) -> None: """Test formatting user message.""" agent = ClaudeAgent() msg = ChatMessage( - role=Role.USER, + role="user", contents=[Content.from_text(text="Hello")], ) result = agent._format_prompt([msg]) # type: ignore[reportPrivateUsage] @@ -642,9 +642,9 @@ def test_format_multiple_messages(self) -> None: """Test formatting multiple messages.""" agent = ClaudeAgent() messages = [ - ChatMessage(role=Role.USER, contents=[Content.from_text(text="Hi")]), - ChatMessage(role=Role.ASSISTANT, contents=[Content.from_text(text="Hello!")]), - ChatMessage(role=Role.USER, contents=[Content.from_text(text="How are you?")]), + ChatMessage("user", [Content.from_text(text="Hi")]), + ChatMessage("assistant", [Content.from_text(text="Hello!")]), + ChatMessage("user", [Content.from_text(text="How are you?")]), ] result = agent._format_prompt(messages) # type: ignore[reportPrivateUsage] assert "Hi" in result diff --git a/python/packages/copilotstudio/agent_framework_copilotstudio/_agent.py b/python/packages/copilotstudio/agent_framework_copilotstudio/_agent.py index 98d5a2b475..6d764bf68a 100644 --- a/python/packages/copilotstudio/agent_framework_copilotstudio/_agent.py +++ b/python/packages/copilotstudio/agent_framework_copilotstudio/_agent.py @@ -12,7 +12,6 @@ ChatMessage, Content, ContextProvider, - Role, normalize_messages, ) from agent_framework._pydantic import AFBaseSettings @@ -331,7 +330,7 @@ async def _process_activities(self, activities: AsyncIterable[Any], streaming: b (activity.type == "message" and not streaming) or (activity.type == "typing" and streaming) ): yield ChatMessage( - role=Role.ASSISTANT, + role="assistant", contents=[Content.from_text(activity.text)], author_name=activity.from_property.name if activity.from_property else None, message_id=activity.id, diff --git a/python/packages/copilotstudio/tests/test_copilot_agent.py b/python/packages/copilotstudio/tests/test_copilot_agent.py index c4e2ff3e08..4f3edbbbfd 100644 --- a/python/packages/copilotstudio/tests/test_copilot_agent.py +++ b/python/packages/copilotstudio/tests/test_copilot_agent.py @@ -4,7 +4,7 @@ from unittest.mock import MagicMock, patch import pytest -from agent_framework import AgentResponse, AgentResponseUpdate, AgentThread, ChatMessage, Content, Role +from agent_framework import AgentResponse, AgentResponseUpdate, AgentThread, ChatMessage, Content from agent_framework.exceptions import ServiceException, ServiceInitializationError from microsoft_agents.copilotstudio.client import CopilotClient @@ -131,7 +131,7 @@ async def test_run_with_string_message(self, mock_copilot_client: MagicMock, moc content = response.messages[0].contents[0] assert content.type == "text" assert content.text == "Test response" - assert response.messages[0].role == Role.ASSISTANT + assert response.messages[0].role == "assistant" async def test_run_with_chat_message(self, mock_copilot_client: MagicMock, mock_activity: MagicMock) -> None: """Test run method with ChatMessage.""" @@ -143,7 +143,7 @@ async def test_run_with_chat_message(self, mock_copilot_client: MagicMock, mock_ mock_copilot_client.start_conversation.return_value = create_async_generator([conversation_activity]) mock_copilot_client.ask_question.return_value = create_async_generator([mock_activity]) - chat_message = ChatMessage(role=Role.USER, contents=[Content.from_text("test message")]) + chat_message = ChatMessage("user", [Content.from_text("test message")]) response = await agent.run(chat_message) assert isinstance(response, AgentResponse) @@ -151,7 +151,7 @@ async def test_run_with_chat_message(self, mock_copilot_client: MagicMock, mock_ content = response.messages[0].contents[0] assert content.type == "text" assert content.text == "Test response" - assert response.messages[0].role == Role.ASSISTANT + assert response.messages[0].role == "assistant" async def test_run_with_thread(self, mock_copilot_client: MagicMock, mock_activity: MagicMock) -> None: """Test run method with existing thread.""" diff --git a/python/packages/core/README.md b/python/packages/core/README.md index 4113eca061..30ff1b7aa4 100644 --- a/python/packages/core/README.md +++ b/python/packages/core/README.md @@ -96,8 +96,8 @@ async def main(): client = OpenAIChatClient() messages = [ - ChatMessage(role=Role.SYSTEM, text="You are a helpful assistant."), - ChatMessage(role=Role.USER, text="Write a haiku about Agent Framework.") + ChatMessage("system", ["You are a helpful assistant."]), + ChatMessage("user", ["Write a haiku about Agent Framework."]) ] response = await client.get_response(messages) diff --git a/python/packages/core/agent_framework/_agents.py b/python/packages/core/agent_framework/_agents.py index 4dc6df2eac..5c36d937fa 100644 --- a/python/packages/core/agent_framework/_agents.py +++ b/python/packages/core/agent_framework/_agents.py @@ -38,6 +38,7 @@ ChatMessage, ChatResponse, ChatResponseUpdate, + Content, normalize_messages, ) from .exceptions import AgentExecutionException, AgentInitializationError @@ -209,7 +210,7 @@ def get_new_thread(self, **kwargs): async def run( self, - messages: str | ChatMessage | Sequence[str | ChatMessage] | None = None, + messages: str | Content | ChatMessage | Sequence[str | Content | ChatMessage] | None = None, *, thread: AgentThread | None = None, **kwargs: Any, @@ -240,7 +241,7 @@ async def run( def run_stream( self, - messages: str | ChatMessage | Sequence[str | ChatMessage] | None = None, + messages: str | Content | ChatMessage | Sequence[str | Content | ChatMessage] | None = None, *, thread: AgentThread | None = None, **kwargs: Any, @@ -490,7 +491,7 @@ async def agent_wrapper(**kwargs: Any) -> str: stream_callback(update) # Create final text from accumulated updates - return AgentResponse.from_agent_run_response_updates(response_updates).text + return AgentResponse.from_updates(response_updates).text agent_tool: FunctionTool[BaseModel, str] = FunctionTool( name=tool_name, @@ -755,7 +756,7 @@ def _update_agent_name_and_description(self) -> None: @overload async def run( self, - messages: str | ChatMessage | Sequence[str | ChatMessage] | None = None, + messages: str | Content | ChatMessage | Sequence[str | Content | ChatMessage] | None = None, *, thread: AgentThread | None = None, tools: ToolProtocol @@ -770,7 +771,7 @@ async def run( @overload async def run( self, - messages: str | ChatMessage | Sequence[str | ChatMessage] | None = None, + messages: str | Content | ChatMessage | Sequence[str | Content | ChatMessage] | None = None, *, thread: AgentThread | None = None, tools: ToolProtocol @@ -784,7 +785,7 @@ async def run( async def run( self, - messages: str | ChatMessage | Sequence[str | ChatMessage] | None = None, + messages: str | Content | ChatMessage | Sequence[str | Content | ChatMessage] | None = None, *, thread: AgentThread | None = None, tools: ToolProtocol @@ -927,7 +928,7 @@ async def run( async def run_stream( self, - messages: str | ChatMessage | Sequence[str | ChatMessage] | None = None, + messages: str | Content | ChatMessage | Sequence[str | Content | ChatMessage] | None = None, *, thread: AgentThread | None = None, tools: ToolProtocol @@ -1043,9 +1044,7 @@ async def run_stream( raw_representation=update, ) - response = ChatResponse.from_chat_response_updates( - response_updates, output_format_type=co.get("response_format") - ) + response = ChatResponse.from_updates(response_updates, output_format_type=co.get("response_format")) await self._update_thread_with_type_and_conversation_id(thread, response.conversation_id) await self._notify_thread_of_new_messages( diff --git a/python/packages/core/agent_framework/_clients.py b/python/packages/core/agent_framework/_clients.py index 68d9d0312f..60fe7698ea 100644 --- a/python/packages/core/agent_framework/_clients.py +++ b/python/packages/core/agent_framework/_clients.py @@ -45,6 +45,7 @@ ChatMessage, ChatResponse, ChatResponseUpdate, + Content, prepare_messages, validate_chat_options, ) @@ -129,7 +130,7 @@ async def _stream(): @overload async def get_response( self, - messages: str | ChatMessage | Sequence[str | ChatMessage], + messages: str | Content | ChatMessage | Sequence[str | Content | ChatMessage], *, options: "ChatOptions[TResponseModelT]", **kwargs: Any, @@ -138,7 +139,7 @@ async def get_response( @overload async def get_response( self, - messages: str | ChatMessage | Sequence[str | ChatMessage], + messages: str | Content | ChatMessage | Sequence[str | Content | ChatMessage], *, options: TOptions_contra | None = None, **kwargs: Any, @@ -160,7 +161,7 @@ async def get_response( def get_streaming_response( self, - messages: str | ChatMessage | Sequence[str | ChatMessage], + messages: str | Content | ChatMessage | Sequence[str | Content | ChatMessage], *, options: TOptions_contra | None = None, **kwargs: Any, @@ -219,9 +220,7 @@ class BaseChatClient(SerializationMixin, ABC, Generic[TOptions_co]): class CustomChatClient(BaseChatClient): async def _inner_get_response(self, *, messages, options, **kwargs): # Your custom implementation - return ChatResponse( - messages=[ChatMessage(role="assistant", text="Hello!")], response_id="custom-response" - ) + return ChatResponse(messages=[ChatMessage("assistant", ["Hello!"])], response_id="custom-response") async def _inner_get_streaming_response(self, *, messages, options, **kwargs): # Your custom streaming implementation @@ -341,7 +340,7 @@ async def _inner_get_streaming_response( @overload async def get_response( self, - messages: str | ChatMessage | Sequence[str | ChatMessage], + messages: str | Content | ChatMessage | Sequence[str | Content | ChatMessage], *, options: "ChatOptions[TResponseModelT]", **kwargs: Any, @@ -350,7 +349,7 @@ async def get_response( @overload async def get_response( self, - messages: str | ChatMessage | Sequence[str | ChatMessage], + messages: str | Content | ChatMessage | Sequence[str | Content | ChatMessage], *, options: TOptions_co | None = None, **kwargs: Any, @@ -358,7 +357,7 @@ async def get_response( async def get_response( self, - messages: str | ChatMessage | Sequence[str | ChatMessage], + messages: str | Content | ChatMessage | Sequence[str | Content | ChatMessage], *, options: TOptions_co | "ChatOptions[Any]" | None = None, **kwargs: Any, @@ -381,7 +380,7 @@ async def get_response( async def get_streaming_response( self, - messages: str | ChatMessage | Sequence[str | ChatMessage], + messages: str | Content | ChatMessage | Sequence[str | Content | ChatMessage], *, options: TOptions_co | None = None, **kwargs: Any, diff --git a/python/packages/core/agent_framework/_mcp.py b/python/packages/core/agent_framework/_mcp.py index 9410a6698b..578fb606e1 100644 --- a/python/packages/core/agent_framework/_mcp.py +++ b/python/packages/core/agent_framework/_mcp.py @@ -32,7 +32,6 @@ from ._types import ( ChatMessage, Content, - Role, ) from .exceptions import ToolException, ToolExecutionException @@ -71,7 +70,7 @@ def _parse_message_from_mcp( ) -> ChatMessage: """Parse an MCP container type into an Agent Framework type.""" return ChatMessage( - role=Role(value=mcp_type.role), + role=mcp_type.role, contents=_parse_content_from_mcp(mcp_type.content), raw_representation=mcp_type, ) diff --git a/python/packages/core/agent_framework/_middleware.py b/python/packages/core/agent_framework/_middleware.py index c41c2e7b5b..4cd136a230 100644 --- a/python/packages/core/agent_framework/_middleware.py +++ b/python/packages/core/agent_framework/_middleware.py @@ -429,7 +429,7 @@ async def process(self, context: ChatContext, next): # Add system prompt to messages from agent_framework import ChatMessage - context.messages.insert(0, ChatMessage(role="system", content=self.system_prompt)) + context.messages.insert(0, ChatMessage("system", [self.system_prompt])) # Continue execution await next(context) diff --git a/python/packages/core/agent_framework/_serialization.py b/python/packages/core/agent_framework/_serialization.py index e4866c12d6..01161435ec 100644 --- a/python/packages/core/agent_framework/_serialization.py +++ b/python/packages/core/agent_framework/_serialization.py @@ -38,7 +38,7 @@ class SerializationProtocol(Protocol): # ChatMessage implements SerializationProtocol via SerializationMixin - user_msg = ChatMessage(role="user", text="What's the weather like today?") + user_msg = ChatMessage("user", ["What's the weather like today?"]) # Serialize to dictionary - automatic type identification and nested serialization msg_dict = user_msg.to_dict() @@ -53,7 +53,7 @@ class SerializationProtocol(Protocol): # Deserialize back to ChatMessage instance - automatic type reconstruction restored_msg = ChatMessage.from_dict(msg_dict) print(restored_msg.text) # "What's the weather like today?" - print(restored_msg.role.value) # "user" + print(restored_msg.role) # "user" # Verify protocol compliance (useful for type checking and validation) assert isinstance(user_msg, SerializationProtocol) @@ -175,8 +175,8 @@ class SerializationMixin: # ChatMessageStoreState handles nested ChatMessage serialization store_state = ChatMessageStoreState( messages=[ - ChatMessage(role="user", text="Hello agent"), - ChatMessage(role="assistant", text="Hi! How can I help?"), + ChatMessage("user", ["Hello agent"]), + ChatMessage("assistant", ["Hi! How can I help?"]), ] ) diff --git a/python/packages/core/agent_framework/_threads.py b/python/packages/core/agent_framework/_threads.py index e44c362324..a9d53c9890 100644 --- a/python/packages/core/agent_framework/_threads.py +++ b/python/packages/core/agent_framework/_threads.py @@ -202,7 +202,7 @@ class ChatMessageStore: store = ChatMessageStore() # Add messages - message = ChatMessage(role="user", content="Hello") + message = ChatMessage("user", ["Hello"]) await store.add_messages([message]) # Retrieve messages diff --git a/python/packages/core/agent_framework/_tools.py b/python/packages/core/agent_framework/_tools.py index d88fa4b54c..56594ecec2 100644 --- a/python/packages/core/agent_framework/_tools.py +++ b/python/packages/core/agent_framework/_tools.py @@ -1831,7 +1831,6 @@ def _replace_approval_contents_with_results( """Replace approval request/response contents with function call/result contents in-place.""" from ._types import ( Content, - Role, ) result_idx = 0 @@ -1861,7 +1860,7 @@ def _replace_approval_contents_with_results( if result_idx < len(approved_function_results): msg.contents[content_idx] = approved_function_results[result_idx] result_idx += 1 - msg.role = Role.TOOL + msg.role = "tool" else: # Create a "not approved" result for rejected calls # Use function_call.call_id (the function's ID), not content.id (approval's ID) @@ -1869,7 +1868,7 @@ def _replace_approval_contents_with_results( call_id=content.function_call.call_id, # type: ignore[union-attr, arg-type] result="Error: Tool call invocation was rejected by user.", ) - msg.role = Role.TOOL + msg.role = "tool" # Remove approval requests that were duplicates (in reverse order to preserve indices) for idx in reversed(contents_to_remove): @@ -1988,13 +1987,12 @@ async def function_invocation_wrapper( if any(fccr.type == "function_approval_request" for fccr in function_call_results): # Add approval requests to the existing assistant message (with tool_calls) # instead of creating a separate tool message - from ._types import Role - if response.messages and response.messages[0].role == Role.ASSISTANT: + if response.messages and response.messages[0].role == "assistant": response.messages[0].contents.extend(function_call_results) else: # Fallback: create new assistant message (shouldn't normally happen) - result_message = ChatMessage(role="assistant", contents=function_call_results) + result_message = ChatMessage("assistant", function_call_results) response.messages.append(result_message) return response if any(fccr.type == "function_call" for fccr in function_call_results): @@ -2005,7 +2003,7 @@ async def function_invocation_wrapper( # This allows middleware to short-circuit the tool loop without another LLM call if should_terminate: # Add tool results to response and return immediately without calling LLM again - result_message = ChatMessage(role="tool", contents=function_call_results) + result_message = ChatMessage("tool", function_call_results) response.messages.append(result_message) if fcc_messages: for msg in reversed(fcc_messages): @@ -2026,7 +2024,7 @@ async def function_invocation_wrapper( errors_in_a_row = 0 # add a single ChatMessage to the response with the results - result_message = ChatMessage(role="tool", contents=function_call_results) + result_message = ChatMessage("tool", function_call_results) response.messages.append(result_message) # response should contain 2 messages after this, # one with function call contents @@ -2162,7 +2160,7 @@ async def streaming_function_invocation_wrapper( # Depending on the prompt, the message may contain both function call # content and others - response: "ChatResponse" = ChatResponse.from_chat_response_updates(all_updates) + response: "ChatResponse" = ChatResponse.from_updates(all_updates) # get the function calls (excluding ones that already have results) function_results = {it.call_id for it in response.messages[0].contents if it.type == "function_result"} function_calls = [ @@ -2206,15 +2204,14 @@ async def streaming_function_invocation_wrapper( if any(fccr.type == "function_approval_request" for fccr in function_call_results): # Add approval requests to the existing assistant message (with tool_calls) # instead of creating a separate tool message - from ._types import Role - if response.messages and response.messages[0].role == Role.ASSISTANT: + if response.messages and response.messages[0].role == "assistant": response.messages[0].contents.extend(function_call_results) # Yield the approval requests as part of the assistant message yield ChatResponseUpdate(contents=function_call_results, role="assistant") else: # Fallback: create new assistant message (shouldn't normally happen) - result_message = ChatMessage(role="assistant", contents=function_call_results) + result_message = ChatMessage("assistant", function_call_results) yield ChatResponseUpdate(contents=function_call_results, role="assistant") response.messages.append(result_message) return @@ -2243,7 +2240,7 @@ async def streaming_function_invocation_wrapper( errors_in_a_row = 0 # add a single ChatMessage to the response with the results - result_message = ChatMessage(role="tool", contents=function_call_results) + result_message = ChatMessage("tool", function_call_results) yield ChatResponseUpdate(contents=function_call_results, role="tool") response.messages.append(result_message) # response should contain 2 messages after this, diff --git a/python/packages/core/agent_framework/_types.py b/python/packages/core/agent_framework/_types.py index 9c49d25845..826394b11c 100644 --- a/python/packages/core/agent_framework/_types.py +++ b/python/packages/core/agent_framework/_types.py @@ -8,13 +8,12 @@ Callable, Mapping, MutableMapping, - MutableSequence, Sequence, ) from copy import deepcopy -from typing import TYPE_CHECKING, Any, ClassVar, Final, Generic, Literal, cast, overload +from typing import TYPE_CHECKING, Any, ClassVar, Final, Generic, Literal, NewType, cast, overload -from pydantic import BaseModel, ValidationError +from pydantic import BaseModel from ._logging import get_logger from ._serialization import SerializationMixin @@ -40,7 +39,9 @@ "ChatResponseUpdate", "Content", "FinishReason", + "FinishReasonLiteral", "Role", + "RoleLiteral", "TextSpanRegion", "ToolMode", "UsageDetails", @@ -62,42 +63,25 @@ # region Content Parsing Utilities -class EnumLike(type): - """Generic metaclass for creating enum-like classes with predefined constants. - - This metaclass automatically creates class-level constants based on a _constants - class attribute. Each constant is defined as a tuple of (name, *args) where - name is the constant name and args are the constructor arguments. - """ - - def __new__(mcs, name: str, bases: tuple[type, ...], namespace: dict[str, Any]) -> "EnumLike": - cls = super().__new__(mcs, name, bases, namespace) - - # Create constants if _constants is defined - if (const := getattr(cls, "_constants", None)) and isinstance(const, dict): - for const_name, const_args in const.items(): - if isinstance(const_args, (list, tuple)): - setattr(cls, const_name, cls(*const_args)) - else: - setattr(cls, const_name, cls(const_args)) - - return cls - - def _parse_content_list(contents_data: Sequence[Any]) -> list["Content"]: - """Parse a list of content data dictionaries into appropriate Content objects. + """Parse a list of content data into appropriate Content objects. Args: - contents_data: List of content data (dicts or already constructed objects) + contents_data: List of content data (strings, dicts, or already constructed objects) Returns: List of Content objects with unknown types logged and ignored """ contents: list["Content"] = [] for content_data in contents_data: + if content_data is None: + continue if isinstance(content_data, Content): contents.append(content_data) continue + if isinstance(content_data, str): + contents.append(Content.from_text(text=content_data)) + continue try: contents.append(Content.from_dict(content_data)) except ContentError as exc: @@ -1420,140 +1404,56 @@ def prepare_function_call_results(content: "Content | Any | list[Content | Any]" # region Chat Response constants +RoleLiteral = Literal["system", "user", "assistant", "tool"] +"""Literal type for known role values. Accepts any string for extensibility.""" -class Role(SerializationMixin, metaclass=EnumLike): - """Describes the intended purpose of a message within a chat interaction. - - Attributes: - value: The string representation of the role. - - Properties: - SYSTEM: The role that instructs or sets the behavior of the AI system. - USER: The role that provides user input for chat interactions. - ASSISTANT: The role that provides responses to system-instructed, user-prompted input. - TOOL: The role that provides additional information and references in response to tool use requests. - - Examples: - .. code-block:: python - - from agent_framework import Role - - # Use predefined role constants - system_role = Role.SYSTEM - user_role = Role.USER - assistant_role = Role.ASSISTANT - tool_role = Role.TOOL - - # Create custom role - custom_role = Role(value="custom") - - # Compare roles - print(system_role == Role.SYSTEM) # True - print(system_role.value) # "system" - """ - - # Constants configuration for EnumLike metaclass - _constants: ClassVar[dict[str, str]] = { - "SYSTEM": "system", - "USER": "user", - "ASSISTANT": "assistant", - "TOOL": "tool", - } - - # Type annotations for constants - SYSTEM: "Role" - USER: "Role" - ASSISTANT: "Role" - TOOL: "Role" - - def __init__(self, value: str) -> None: - """Initialize Role with a value. - - Args: - value: The string representation of the role. - """ - self.value = value - - def __str__(self) -> str: - """Returns the string representation of the role.""" - return self.value - - def __repr__(self) -> str: - """Returns the string representation of the role.""" - return f"Role(value={self.value!r})" - - def __eq__(self, other: object) -> bool: - """Check if two Role instances are equal.""" - if not isinstance(other, Role): - return False - return self.value == other.value - - def __hash__(self) -> int: - """Return hash of the Role for use in sets and dicts.""" - return hash(self.value) - +Role = NewType("Role", str) +"""Type for chat message roles. Use string values directly (e.g., "user", "assistant"). -class FinishReason(SerializationMixin, metaclass=EnumLike): - """Represents the reason a chat response completed. +Known values: "system", "user", "assistant", "tool" - Attributes: - value: The string representation of the finish reason. +Examples: + .. code-block:: python - Examples: - .. code-block:: python + from agent_framework import ChatMessage - from agent_framework import FinishReason + # Use string values directly + user_msg = ChatMessage("user", ["Hello"]) + assistant_msg = ChatMessage("assistant", ["Hi there!"]) - # Use predefined finish reason constants - stop_reason = FinishReason.STOP # Normal completion - length_reason = FinishReason.LENGTH # Max tokens reached - tool_calls_reason = FinishReason.TOOL_CALLS # Tool calls triggered - filter_reason = FinishReason.CONTENT_FILTER # Content filter triggered + # Custom roles are also supported + custom_msg = ChatMessage("custom", ["Custom role message"]) - # Check finish reason - if stop_reason == FinishReason.STOP: - print("Response completed normally") - """ + # Compare roles directly as strings + if user_msg.role == "user": + print("This is a user message") +""" - # Constants configuration for EnumLike metaclass - _constants: ClassVar[dict[str, str]] = { - "CONTENT_FILTER": "content_filter", - "LENGTH": "length", - "STOP": "stop", - "TOOL_CALLS": "tool_calls", - } +FinishReasonLiteral = Literal["stop", "length", "tool_calls", "content_filter"] +"""Literal type for known finish reason values. Accepts any string for extensibility.""" - # Type annotations for constants - CONTENT_FILTER: "FinishReason" - LENGTH: "FinishReason" - STOP: "FinishReason" - TOOL_CALLS: "FinishReason" +FinishReason = NewType("FinishReason", str) +"""Type for chat response finish reasons. Use string values directly. - def __init__(self, value: str) -> None: - """Initialize FinishReason with a value. - - Args: - value: The string representation of the finish reason. - """ - self.value = value +Known values: + - "stop": Normal completion + - "length": Max tokens reached + - "tool_calls": Tool calls triggered + - "content_filter": Content filter triggered - def __eq__(self, other: object) -> bool: - """Check if two FinishReason instances are equal.""" - if not isinstance(other, FinishReason): - return False - return self.value == other.value +Examples: + .. code-block:: python - def __hash__(self) -> int: - """Return hash of the FinishReason for use in sets and dicts.""" - return hash(self.value) + from agent_framework import ChatResponse - def __str__(self) -> str: - """Returns the string representation of the finish reason.""" - return self.value + response = ChatResponse(messages=[...], finish_reason="stop") - def __repr__(self) -> str: - """Returns the string representation of the finish reason.""" - return f"FinishReason(value={self.value!r})" + # Check finish reason directly as string + if response.finish_reason == "stop": + print("Response completed normally") + elif response.finish_reason == "tool_calls": + print("Tool calls need to be processed") +""" # region ChatMessage @@ -1574,138 +1474,82 @@ class ChatMessage(SerializationMixin): Examples: .. code-block:: python - from agent_framework import ChatMessage, TextContent + from agent_framework import ChatMessage, Content - # Create a message with text - user_msg = ChatMessage(role="user", text="What's the weather?") + # Create a message with text content + user_msg = ChatMessage("user", ["What's the weather?"]) print(user_msg.text) # "What's the weather?" - # Create a message with role string - system_msg = ChatMessage(role="system", text="You are a helpful assistant.") + # Create a system message + system_msg = ChatMessage("system", ["You are a helpful assistant."]) - # Create a message with contents + # Create a message with mixed content types assistant_msg = ChatMessage( - role="assistant", - contents=[Content.from_text(text="The weather is sunny!")], + "assistant", + ["The weather is sunny!", Content.from_image_uri("https://...")], ) print(assistant_msg.text) # "The weather is sunny!" # Serialization - to_dict and from_dict msg_dict = user_msg.to_dict() - # {'type': 'chat_message', 'role': {'type': 'role', 'value': 'user'}, + # {'type': 'chat_message', 'role': 'user', # 'contents': [{'type': 'text', 'text': "What's the weather?"}], 'additional_properties': {}} restored_msg = ChatMessage.from_dict(msg_dict) print(restored_msg.text) # "What's the weather?" # Serialization - to_json and from_json msg_json = user_msg.to_json() - # '{"type": "chat_message", "role": {"type": "role", "value": "user"}, "contents": [...], ...}' + # '{"type": "chat_message", "role": "user", "contents": [...], ...}' restored_from_json = ChatMessage.from_json(msg_json) - print(restored_from_json.role.value) # "user" + print(restored_from_json.role) # "user" """ DEFAULT_EXCLUDE: ClassVar[set[str]] = {"raw_representation"} - @overload def __init__( self, - role: Role | Literal["system", "user", "assistant", "tool"], - *, - text: str, - author_name: str | None = None, - message_id: str | None = None, - additional_properties: MutableMapping[str, Any] | None = None, - raw_representation: Any | None = None, - **kwargs: Any, - ) -> None: - """Initializes a ChatMessage with a role and text content. - - Args: - role: The role of the author of the message. - - Keyword Args: - text: The text content of the message. - author_name: Optional name of the author of the message. - message_id: Optional ID of the chat message. - additional_properties: Optional additional properties associated with the chat message. - Additional properties are used within Agent Framework, they are not sent to services. - raw_representation: Optional raw representation of the chat message. - **kwargs: Additional keyword arguments. - """ - - @overload - def __init__( - self, - role: Role | Literal["system", "user", "assistant", "tool"], - *, - contents: "Sequence[Content | Mapping[str, Any]]", - author_name: str | None = None, - message_id: str | None = None, - additional_properties: MutableMapping[str, Any] | None = None, - raw_representation: Any | None = None, - **kwargs: Any, - ) -> None: - """Initializes a ChatMessage with a role and optional contents. - - Args: - role: The role of the author of the message. - - Keyword Args: - contents: Optional list of BaseContent items to include in the message. - author_name: Optional name of the author of the message. - message_id: Optional ID of the chat message. - additional_properties: Optional additional properties associated with the chat message. - Additional properties are used within Agent Framework, they are not sent to services. - raw_representation: Optional raw representation of the chat message. - **kwargs: Additional keyword arguments. - """ - - def __init__( - self, - role: Role | Literal["system", "user", "assistant", "tool"] | dict[str, Any], + role: RoleLiteral | str, + contents: "Sequence[Content | str | Mapping[str, Any]] | None" = None, *, text: str | None = None, - contents: "Sequence[Content | Mapping[str, Any]] | None" = None, author_name: str | None = None, message_id: str | None = None, additional_properties: MutableMapping[str, Any] | None = None, raw_representation: Any | None = None, - **kwargs: Any, ) -> None: """Initialize ChatMessage. Args: - role: The role of the author of the message (Role, string, or dict). + role: The role of the author of the message (e.g., "user", "assistant", "system", "tool"). + contents: A sequence of content items. Can be Content objects, strings (auto-converted + to TextContent), or dicts (parsed via Content.from_dict). Defaults to empty list. Keyword Args: - text: Optional text content of the message. - contents: Optional list of BaseContent items or dicts to include in the message. + text: Deprecated. Text content of the message. Use contents instead. + This parameter is kept for backward compatibility with serialization. author_name: Optional name of the author of the message. message_id: Optional ID of the chat message. additional_properties: Optional additional properties associated with the chat message. Additional properties are used within Agent Framework, they are not sent to services. raw_representation: Optional raw representation of the chat message. - kwargs: will be combined with additional_properties if provided. """ - # Handle role conversion - if isinstance(role, dict): - role = Role.from_dict(role) - elif isinstance(role, str): - role = Role(value=role) + # Handle role conversion from legacy dict format + if isinstance(role, dict) and "value" in role: + role = role["value"] # Handle contents conversion parsed_contents = [] if contents is None else _parse_content_list(contents) + # Handle text for backward compatibility (from serialization) if text is not None: parsed_contents.append(Content.from_text(text=text)) - self.role = role + self.role: str = role self.contents = parsed_contents self.author_name = author_name self.message_id = message_id self.additional_properties = additional_properties or {} - self.additional_properties.update(kwargs or {}) self.raw_representation = raw_representation @property @@ -1719,12 +1563,17 @@ def text(self) -> str: def prepare_messages( - messages: str | ChatMessage | Sequence[str | ChatMessage], system_instructions: str | Sequence[str] | None = None + messages: str | Content | ChatMessage | Sequence[str | Content | ChatMessage], + system_instructions: str | Sequence[str] | None = None, ) -> list[ChatMessage]: """Convert various message input formats into a list of ChatMessage objects. Args: - messages: The input messages in various supported formats. + messages: The input messages in various supported formats. Can be: + - A string (converted to a user message) + - A Content object (wrapped in a user ChatMessage) + - A ChatMessage object + - A sequence containing any mix of the above system_instructions: The system instructions. They will be inserted to the start of the messages list. Returns: @@ -1733,43 +1582,66 @@ def prepare_messages( if system_instructions is not None: if isinstance(system_instructions, str): system_instructions = [system_instructions] - system_instruction_messages = [ChatMessage(role="system", text=instr) for instr in system_instructions] + system_instruction_messages = [ChatMessage("system", [instr]) for instr in system_instructions] else: system_instruction_messages = [] if isinstance(messages, str): - return [*system_instruction_messages, ChatMessage(role="user", text=messages)] + return [*system_instruction_messages, ChatMessage("user", [messages])] + if isinstance(messages, Content): + return [*system_instruction_messages, ChatMessage("user", [messages])] if isinstance(messages, ChatMessage): return [*system_instruction_messages, messages] return_messages: list[ChatMessage] = system_instruction_messages for msg in messages: - if isinstance(msg, str): - msg = ChatMessage(role="user", text=msg) + if isinstance(msg, (str, Content)): + msg = ChatMessage("user", [msg]) return_messages.append(msg) return return_messages def normalize_messages( - messages: str | ChatMessage | Sequence[str | ChatMessage] | None = None, + messages: str | Content | ChatMessage | Sequence[str | Content | ChatMessage] | None = None, ) -> list[ChatMessage]: - """Normalize message inputs to a list of ChatMessage objects.""" + """Normalize message inputs to a list of ChatMessage objects. + + Args: + messages: The input messages in various supported formats. Can be: + - None (returns empty list) + - A string (converted to a user message) + - A Content object (wrapped in a user ChatMessage) + - A ChatMessage object + - A sequence containing any mix of the above + + Returns: + A list of ChatMessage objects. + """ if messages is None: return [] if isinstance(messages, str): - return [ChatMessage(role=Role.USER, text=messages)] + return [ChatMessage("user", [messages])] + + if isinstance(messages, Content): + return [ChatMessage("user", [messages])] if isinstance(messages, ChatMessage): return [messages] - return [ChatMessage(role=Role.USER, text=msg) if isinstance(msg, str) else msg for msg in messages] + result: list[ChatMessage] = [] + for msg in messages: + if isinstance(msg, (str, Content)): + result.append(ChatMessage("user", [msg])) + else: + result.append(msg) + return result def prepend_instructions_to_messages( messages: list[ChatMessage], instructions: str | Sequence[str] | None, - role: Role | Literal["system", "user", "assistant"] = "system", + role: RoleLiteral | str = "system", ) -> list[ChatMessage]: """Prepend instructions to a list of messages with a specified role. @@ -1790,7 +1662,7 @@ def prepend_instructions_to_messages( from agent_framework import prepend_instructions_to_messages, ChatMessage - messages = [ChatMessage(role="user", text="Hello")] + messages = [ChatMessage("user", ["Hello"])] instructions = "You are a helpful assistant" # Prepend as system message (default) @@ -1805,7 +1677,7 @@ def prepend_instructions_to_messages( if isinstance(instructions, str): instructions = [instructions] - instruction_messages = [ChatMessage(role=role, text=instr) for instr in instructions] + instruction_messages = [ChatMessage(role, [instr]) for instr in instructions] return [*instruction_messages, *messages] @@ -1829,7 +1701,7 @@ def _process_update( is_new_message = True if is_new_message: - message = ChatMessage(role=Role.ASSISTANT, contents=[]) + message = ChatMessage("assistant", []) response.messages.append(message) else: message = response.messages[-1] @@ -1937,31 +1809,32 @@ class ChatResponse(SerializationMixin, Generic[TResponseModel]): additional_properties: Any additional properties associated with the chat response. raw_representation: The raw representation of the chat response from an underlying implementation. + Note: + The `author_name` attribute is available on the `ChatMessage` objects inside `messages`, + not on the `ChatResponse` itself. Use `response.messages[0].author_name` to access + the author name of individual messages. + Examples: .. code-block:: python from agent_framework import ChatResponse, ChatMessage - # Create a simple text response - response = ChatResponse(text="Hello, how can I help you?") - print(response.text) # "Hello, how can I help you?" - # Create a response with messages - msg = ChatMessage(role="assistant", text="The weather is sunny.") + msg = ChatMessage("assistant", ["The weather is sunny."]) response = ChatResponse( messages=[msg], finish_reason="stop", model_id="gpt-4", ) + print(response.text) # "The weather is sunny." # Combine streaming updates updates = [...] # List of ChatResponseUpdate objects - response = ChatResponse.from_chat_response_updates(updates) + response = ChatResponse.from_updates(updates) # Serialization - to_dict and from_dict response_dict = response.to_dict() - # {'type': 'chat_response', 'messages': [...], 'model_id': 'gpt-4', - # 'finish_reason': {'type': 'finish_reason', 'value': 'stop'}} + # {'type': 'chat_response', 'messages': [...], 'model_id': 'gpt-4', 'finish_reason': 'stop'} restored_response = ChatResponse.from_dict(response_dict) print(restored_response.model_id) # "gpt-4" @@ -1974,154 +1847,66 @@ class ChatResponse(SerializationMixin, Generic[TResponseModel]): DEFAULT_EXCLUDE: ClassVar[set[str]] = {"raw_representation", "additional_properties"} - @overload - def __init__( - self, - *, - messages: ChatMessage | MutableSequence[ChatMessage], - response_id: str | None = None, - conversation_id: str | None = None, - model_id: str | None = None, - created_at: CreatedAtT | None = None, - finish_reason: FinishReason | None = None, - usage_details: UsageDetails | None = None, - value: TResponseModel | None = None, - response_format: type[BaseModel] | None = None, - additional_properties: dict[str, Any] | None = None, - raw_representation: Any | None = None, - **kwargs: Any, - ) -> None: - """Initializes a ChatResponse with the provided parameters. - - Keyword Args: - messages: A single ChatMessage or a sequence of ChatMessage objects to include in the response. - response_id: Optional ID of the chat response. - conversation_id: Optional identifier for the state of the conversation. - model_id: Optional model ID used in the creation of the chat response. - created_at: Optional timestamp for the chat response. - finish_reason: Optional reason for the chat response. - usage_details: Optional usage details for the chat response. - value: Optional value of the structured output. - response_format: Optional response format for the chat response. - messages: List of ChatMessage objects to include in the response. - additional_properties: Optional additional properties associated with the chat response. - raw_representation: Optional raw representation of the chat response from an underlying implementation. - **kwargs: Any additional keyword arguments. - """ - - @overload def __init__( self, *, - text: Content | str, + messages: ChatMessage | Sequence[ChatMessage] | None = None, response_id: str | None = None, conversation_id: str | None = None, model_id: str | None = None, created_at: CreatedAtT | None = None, - finish_reason: FinishReason | None = None, + finish_reason: FinishReasonLiteral | str | None = None, usage_details: UsageDetails | None = None, value: TResponseModel | None = None, response_format: type[BaseModel] | None = None, additional_properties: dict[str, Any] | None = None, raw_representation: Any | None = None, - **kwargs: Any, - ) -> None: - """Initializes a ChatResponse with the provided parameters. - - Keyword Args: - text: The text content to include in the response. If provided, it will be added as a ChatMessage. - response_id: Optional ID of the chat response. - conversation_id: Optional identifier for the state of the conversation. - model_id: Optional model ID used in the creation of the chat response. - created_at: Optional timestamp for the chat response. - finish_reason: Optional reason for the chat response. - usage_details: Optional usage details for the chat response. - value: Optional value of the structured output. - response_format: Optional response format for the chat response. - additional_properties: Optional additional properties associated with the chat response. - raw_representation: Optional raw representation of the chat response from an underlying implementation. - **kwargs: Any additional keyword arguments. - - """ - - def __init__( - self, - *, - messages: ChatMessage | MutableSequence[ChatMessage] | list[dict[str, Any]] | None = None, - text: Content | str | None = None, - response_id: str | None = None, - conversation_id: str | None = None, - model_id: str | None = None, - created_at: CreatedAtT | None = None, - finish_reason: FinishReason | dict[str, Any] | None = None, - usage_details: UsageDetails | dict[str, Any] | None = None, - value: TResponseModel | None = None, - response_format: type[BaseModel] | None = None, - additional_properties: dict[str, Any] | None = None, - raw_representation: Any | None = None, - **kwargs: Any, ) -> None: """Initializes a ChatResponse with the provided parameters. Keyword Args: - messages: A single ChatMessage or a sequence of ChatMessage objects to include in the response. - text: The text content to include in the response. If provided, it will be added as a ChatMessage. + messages: A single ChatMessage or sequence of ChatMessage objects to include in the response. response_id: Optional ID of the chat response. conversation_id: Optional identifier for the state of the conversation. model_id: Optional model ID used in the creation of the chat response. created_at: Optional timestamp for the chat response. - finish_reason: Optional reason for the chat response. + finish_reason: Optional reason for the chat response (e.g., "stop", "length", "tool_calls"). usage_details: Optional usage details for the chat response. value: Optional value of the structured output. response_format: Optional response format for the chat response. additional_properties: Optional additional properties associated with the chat response. raw_representation: Optional raw representation of the chat response from an underlying implementation. - **kwargs: Any additional keyword arguments. """ - # Handle messages conversion if messages is None: - messages = [] - elif not isinstance(messages, MutableSequence): - messages = [messages] + self.messages: list[ChatMessage] = [] + elif isinstance(messages, ChatMessage): + self.messages = [messages] else: - # Convert any dicts in messages list to ChatMessage objects - converted_messages: list[ChatMessage] = [] + # Handle both ChatMessage objects and dicts (for from_dict support) + processed_messages: list[ChatMessage] = [] for msg in messages: - if isinstance(msg, dict): - converted_messages.append(ChatMessage.from_dict(msg)) + if isinstance(msg, ChatMessage): + processed_messages.append(msg) + elif isinstance(msg, dict): + processed_messages.append(ChatMessage.from_dict(msg)) else: - converted_messages.append(msg) - messages = converted_messages - - if text is not None: - if isinstance(text, str): - text = Content.from_text(text=text) - messages.append(ChatMessage(role=Role.ASSISTANT, contents=[text])) - - # Handle finish_reason conversion - if isinstance(finish_reason, dict): - finish_reason = FinishReason.from_dict(finish_reason) - - # Handle usage_details - UsageDetails is now a TypedDict, so dict is already the right type - # No conversion needed - - self.messages = list(messages) + processed_messages.append(msg) + self.messages = processed_messages self.response_id = response_id self.conversation_id = conversation_id self.model_id = model_id self.created_at = created_at - self.finish_reason = finish_reason + self.finish_reason: str | None = finish_reason self.usage_details = usage_details self._value: TResponseModel | None = value self._response_format: type[BaseModel] | None = response_format self._value_parsed: bool = value is not None self.additional_properties = additional_properties or {} - self.additional_properties.update(kwargs or {}) self.raw_representation: Any | list[Any] | None = raw_representation @overload @classmethod - def from_chat_response_updates( + def from_updates( cls: type["ChatResponse[Any]"], updates: Sequence["ChatResponseUpdate"], *, @@ -2130,7 +1915,7 @@ def from_chat_response_updates( @overload @classmethod - def from_chat_response_updates( + def from_updates( cls: type["ChatResponse[Any]"], updates: Sequence["ChatResponseUpdate"], *, @@ -2138,7 +1923,7 @@ def from_chat_response_updates( ) -> "ChatResponse[Any]": ... @classmethod - def from_chat_response_updates( + def from_updates( cls: type[TChatResponse], updates: Sequence["ChatResponseUpdate"], *, @@ -2153,12 +1938,12 @@ def from_chat_response_updates( # Create some response updates updates = [ - ChatResponseUpdate(role="assistant", text="Hello"), - ChatResponseUpdate(text=" How can I help you?"), + ChatResponseUpdate(contents=[Content.from_text(text="Hello")], role="assistant"), + ChatResponseUpdate(contents=[Content.from_text(text=" How can I help you?")]), ] # Combine updates into a single ChatResponse - response = ChatResponse.from_chat_response_updates(updates) + response = ChatResponse.from_updates(updates) print(response.text) # "Hello How can I help you?" Args: @@ -2167,17 +1952,16 @@ def from_chat_response_updates( Keyword Args: output_format_type: Optional Pydantic model type to parse the response text into structured data. """ - msg = cls(messages=[]) + response_format = output_format_type if isinstance(output_format_type, type) else None + msg = cls(messages=[], response_format=response_format) for update in updates: _process_update(msg, update) _finalize_response(msg) - if output_format_type: - msg.try_parse_value(output_format_type) return msg @overload @classmethod - async def from_chat_response_generator( + async def from_update_generator( cls: type["ChatResponse[Any]"], updates: AsyncIterable["ChatResponseUpdate"], *, @@ -2186,7 +1970,7 @@ async def from_chat_response_generator( @overload @classmethod - async def from_chat_response_generator( + async def from_update_generator( cls: type["ChatResponse[Any]"], updates: AsyncIterable["ChatResponseUpdate"], *, @@ -2194,7 +1978,7 @@ async def from_chat_response_generator( ) -> "ChatResponse[Any]": ... @classmethod - async def from_chat_response_generator( + async def from_update_generator( cls: type[TChatResponse], updates: AsyncIterable["ChatResponseUpdate"], *, @@ -2208,7 +1992,7 @@ async def from_chat_response_generator( from agent_framework import ChatResponse, ChatResponseUpdate, ChatClient client = ChatClient() # should be a concrete implementation - response = await ChatResponse.from_chat_response_generator( + response = await ChatResponse.from_update_generator( client.get_streaming_response("Hello, how are you?") ) print(response.text) @@ -2224,8 +2008,6 @@ async def from_chat_response_generator( async for update in updates: _process_update(msg, update) _finalize_response(msg) - if response_format and issubclass(response_format, BaseModel): - msg.try_parse_value(response_format) return msg @property @@ -2257,47 +2039,6 @@ def value(self) -> TResponseModel | None: def __str__(self) -> str: return self.text - @overload - def try_parse_value(self, output_format_type: type[TResponseModelT]) -> TResponseModelT | None: ... - - @overload - def try_parse_value(self, output_format_type: None = None) -> TResponseModel | None: ... - - def try_parse_value(self, output_format_type: type[BaseModel] | None = None) -> BaseModel | None: - """Try to parse the text into a typed value. - - This is the safe alternative to accessing the value property directly. - Returns the parsed value on success, or None on failure. - - Args: - output_format_type: The Pydantic model type to parse into. - If None, uses the response_format from initialization. - - Returns: - The parsed value as the specified type, or None if parsing fails. - """ - format_type = output_format_type or self._response_format - if format_type is None or not (isinstance(format_type, type) and issubclass(format_type, BaseModel)): - return None - - # Cache the result unless a different schema than the configured response_format is requested. - # This prevents calls with a different schema from polluting the cached value. - use_cache = ( - self._response_format is None or output_format_type is None or output_format_type is self._response_format - ) - - if use_cache and self._value_parsed and self._value is not None: - return self._value # type: ignore[return-value, no-any-return] - try: - parsed_value = format_type.model_validate_json(self.text) # type: ignore[reportUnknownMemberType] - if use_cache: - self._value = cast(TResponseModel, parsed_value) - self._value_parsed = True - return parsed_value # type: ignore[return-value] - except ValidationError as ex: - logger.warning("Failed to parse value from chat response text: %s", ex) - return None - # region ChatResponseUpdate @@ -2308,7 +2049,10 @@ class ChatResponseUpdate(SerializationMixin): Attributes: contents: The chat response update content items. role: The role of the author of the response update. - author_name: The name of the author of the response update. + author_name: The name of the author of the response update. This is primarily used in + multi-agent scenarios to identify which agent or participant generated the response. + When updates are combined into a `ChatResponse`, the `author_name` is propagated + to the resulting `ChatMessage` objects. response_id: The ID of the response of which this update is a part. message_id: The ID of the message of which this update is a part. conversation_id: An identifier for the state of the conversation of which this update is a part. @@ -2321,9 +2065,9 @@ class ChatResponseUpdate(SerializationMixin): Examples: .. code-block:: python - from agent_framework import ChatResponseUpdate, TextContent + from agent_framework import ChatResponseUpdate, Content - # Create a response update + # Create a response update with text content update = ChatResponseUpdate( contents=[Content.from_text(text="Hello")], role="assistant", @@ -2331,13 +2075,10 @@ class ChatResponseUpdate(SerializationMixin): ) print(update.text) # "Hello" - # Create update with text shorthand - update = ChatResponseUpdate(text="World!", role="assistant") - # Serialization - to_dict and from_dict update_dict = update.to_dict() # {'type': 'chat_response_update', 'contents': [{'type': 'text', 'text': 'Hello'}], - # 'role': {'type': 'role', 'value': 'assistant'}, 'message_id': 'msg_123'} + # 'role': 'assistant', 'message_id': 'msg_123'} restored_update = ChatResponseUpdate.from_dict(update_dict) print(restored_update.text) # "Hello" @@ -2354,26 +2095,23 @@ class ChatResponseUpdate(SerializationMixin): def __init__( self, *, - contents: Sequence[Content | dict[str, Any]] | None = None, - text: Content | str | None = None, - role: Role | Literal["system", "user", "assistant", "tool"] | dict[str, Any] | None = None, + contents: Sequence[Content] | None = None, + role: RoleLiteral | str | None = None, author_name: str | None = None, response_id: str | None = None, message_id: str | None = None, conversation_id: str | None = None, model_id: str | None = None, created_at: CreatedAtT | None = None, - finish_reason: FinishReason | dict[str, Any] | None = None, + finish_reason: FinishReasonLiteral | str | None = None, additional_properties: dict[str, Any] | None = None, raw_representation: Any | None = None, - **kwargs: Any, ) -> None: """Initializes a ChatResponseUpdate with the provided parameters. Keyword Args: - contents: Optional list of BaseContent items or dicts to include in the update. - text: Optional text content to include in the update. - role: Optional role of the author of the response update (Role, string, or dict + contents: Optional list of Content items to include in the update. + role: Optional role of the author of the response update (e.g., "user", "assistant"). author_name: Optional name of the author of the response update. response_id: Optional ID of the response of which this update is a part. message_id: Optional ID of the message of which this update is a part. @@ -2384,36 +2122,36 @@ def __init__( additional_properties: Optional additional properties associated with the chat response update. raw_representation: Optional raw representation of the chat response update from an underlying implementation. - **kwargs: Any additional keyword arguments. """ - # Handle contents conversion - contents = [] if contents is None else _parse_content_list(contents) + # Handle contents - support dict conversion for from_dict + if contents is None: + self.contents: list[Content] = [] + else: + processed_contents: list[Content] = [] + for c in contents: + if isinstance(c, Content): + processed_contents.append(c) + elif isinstance(c, dict): + processed_contents.append(Content.from_dict(c)) + else: + processed_contents.append(c) + self.contents = processed_contents - if text is not None: - if isinstance(text, str): - text = Content.from_text(text=text) - contents.append(text) - - # Handle role conversion - if isinstance(role, dict): - role = Role.from_dict(role) - elif isinstance(role, str): - role = Role(value=role) - - # Handle finish_reason conversion - if isinstance(finish_reason, dict): - finish_reason = FinishReason.from_dict(finish_reason) - - self.contents = list(contents) - self.role = role + # Handle legacy dict formats for role and finish_reason + if isinstance(role, dict) and "value" in role: + role = role["value"] + if isinstance(finish_reason, dict) and "value" in finish_reason: + finish_reason = finish_reason["value"] + + self.role: str | None = role self.author_name = author_name self.response_id = response_id self.message_id = message_id self.conversation_id = conversation_id self.model_id = model_id self.created_at = created_at - self.finish_reason = finish_reason + self.finish_reason: str | None = finish_reason self.additional_properties = additional_properties self.raw_representation = raw_representation @@ -2436,13 +2174,18 @@ class AgentResponse(SerializationMixin, Generic[TResponseModel]): A typical response will contain a single message, but may contain multiple messages in scenarios involving function calls, RAG retrievals, or complex logic. + Note: + The `author_name` attribute is available on the `ChatMessage` objects inside `messages`, + not on the `AgentResponse` itself. Use `response.messages[0].author_name` to access + the author name of individual messages. + Examples: .. code-block:: python from agent_framework import AgentResponse, ChatMessage # Create agent response - msg = ChatMessage(role="assistant", text="Task completed successfully.") + msg = ChatMessage("assistant", ["Task completed successfully."]) response = AgentResponse(messages=[msg], response_id="run_123") print(response.text) # "Task completed successfully." @@ -2452,7 +2195,7 @@ class AgentResponse(SerializationMixin, Generic[TResponseModel]): # Combine streaming updates updates = [...] # List of AgentResponseUpdate objects - response = AgentResponse.from_agent_run_response_updates(updates) + response = AgentResponse.from_updates(updates) # Serialization - to_dict and from_dict response_dict = response.to_dict() @@ -2473,60 +2216,53 @@ class AgentResponse(SerializationMixin, Generic[TResponseModel]): def __init__( self, *, - messages: ChatMessage - | list[ChatMessage] - | MutableMapping[str, Any] - | list[MutableMapping[str, Any]] - | None = None, + messages: ChatMessage | Sequence[ChatMessage] | None = None, response_id: str | None = None, + agent_id: str | None = None, created_at: CreatedAtT | None = None, - usage_details: UsageDetails | MutableMapping[str, Any] | None = None, + usage_details: UsageDetails | None = None, value: TResponseModel | None = None, response_format: type[BaseModel] | None = None, raw_representation: Any | None = None, additional_properties: dict[str, Any] | None = None, - **kwargs: Any, ) -> None: """Initialize an AgentResponse. Keyword Args: - messages: The list of chat messages in the response. + messages: A single ChatMessage or sequence of ChatMessage objects to include in the response. response_id: The ID of the chat response. + agent_id: The identifier of the agent that produced this response. Useful in multi-agent + scenarios to track which agent generated the response. created_at: A timestamp for the chat response. usage_details: The usage details for the chat response. value: The structured output of the agent run response, if applicable. response_format: Optional response format for the agent response. additional_properties: Any additional properties associated with the chat response. raw_representation: The raw representation of the chat response from an underlying implementation. - **kwargs: Additional properties to set on the response. """ - processed_messages: list[ChatMessage] = [] - if messages is not None: - if isinstance(messages, ChatMessage): - processed_messages.append(messages) - elif isinstance(messages, list): - for message_data in messages: - if isinstance(message_data, ChatMessage): - processed_messages.append(message_data) - elif isinstance(message_data, MutableMapping): - processed_messages.append(ChatMessage.from_dict(message_data)) - else: - logger.warning(f"Unknown message content: {message_data}") - elif isinstance(messages, MutableMapping): - processed_messages.append(ChatMessage.from_dict(messages)) - - # Convert usage_details from dict if needed (for SerializationMixin support) - # UsageDetails is now a TypedDict, so dict is already the right type - - self.messages = processed_messages + if messages is None: + self.messages: list[ChatMessage] = [] + elif isinstance(messages, ChatMessage): + self.messages = [messages] + else: + # Handle both ChatMessage objects and dicts (for from_dict support) + processed_messages: list[ChatMessage] = [] + for msg in messages: + if isinstance(msg, ChatMessage): + processed_messages.append(msg) + elif isinstance(msg, dict): + processed_messages.append(ChatMessage.from_dict(msg)) + else: + processed_messages.append(msg) + self.messages = processed_messages self.response_id = response_id + self.agent_id = agent_id self.created_at = created_at self.usage_details = usage_details self._value: TResponseModel | None = value self._response_format: type[BaseModel] | None = response_format self._value_parsed: bool = value is not None self.additional_properties = additional_properties or {} - self.additional_properties.update(kwargs or {}) self.raw_representation = raw_representation @property @@ -2567,7 +2303,7 @@ def user_input_requests(self) -> list[Content]: @overload @classmethod - def from_agent_run_response_updates( + def from_updates( cls: type["AgentResponse[Any]"], updates: Sequence["AgentResponseUpdate"], *, @@ -2576,7 +2312,7 @@ def from_agent_run_response_updates( @overload @classmethod - def from_agent_run_response_updates( + def from_updates( cls: type["AgentResponse[Any]"], updates: Sequence["AgentResponseUpdate"], *, @@ -2584,7 +2320,7 @@ def from_agent_run_response_updates( ) -> "AgentResponse[Any]": ... @classmethod - def from_agent_run_response_updates( + def from_updates( cls: type[TAgentRunResponse], updates: Sequence["AgentResponseUpdate"], *, @@ -2602,8 +2338,6 @@ def from_agent_run_response_updates( for update in updates: _process_update(msg, update) _finalize_response(msg) - if output_format_type: - msg.try_parse_value(output_format_type) return msg @overload @@ -2643,54 +2377,11 @@ async def from_agent_response_generator( async for update in updates: _process_update(msg, update) _finalize_response(msg) - if output_format_type: - msg.try_parse_value(output_format_type) return msg def __str__(self) -> str: return self.text - @overload - def try_parse_value(self, output_format_type: type[TResponseModelT]) -> TResponseModelT | None: ... - - @overload - def try_parse_value(self, output_format_type: None = None) -> TResponseModel | None: ... - - def try_parse_value(self, output_format_type: type[BaseModel] | None = None) -> BaseModel | None: - """Try to parse the text into a typed value. - - This is the safe alternative when you need to parse the response text into a typed value. - Returns the parsed value on success, or None on failure. - - Args: - output_format_type: The Pydantic model type to parse into. - If None, uses the response_format from initialization. - - Returns: - The parsed value as the specified type, or None if parsing fails. - """ - format_type = output_format_type or self._response_format - if format_type is None or not (isinstance(format_type, type) and issubclass(format_type, BaseModel)): - return None - - # Cache the result unless a different schema than the configured response_format is requested. - # This prevents calls with a different schema from polluting the cached value. - use_cache = ( - self._response_format is None or output_format_type is None or output_format_type is self._response_format - ) - - if use_cache and self._value_parsed and self._value is not None: - return self._value # type: ignore[return-value, no-any-return] - try: - parsed_value = format_type.model_validate_json(self.text) # type: ignore[reportUnknownMemberType] - if use_cache: - self._value = cast(TResponseModel, parsed_value) - self._value_parsed = True - return parsed_value # type: ignore[return-value] - except ValidationError as ex: - logger.warning("Failed to parse value from agent run response text: %s", ex) - return None - # region AgentResponseUpdate @@ -2698,6 +2389,20 @@ def try_parse_value(self, output_format_type: type[BaseModel] | None = None) -> class AgentResponseUpdate(SerializationMixin): """Represents a single streaming response chunk from an Agent. + Attributes: + contents: The content items in this update. + role: The role of the author of the response update. + author_name: The name of the author of the response update. In multi-agent scenarios, + this identifies which agent generated this update. When updates are combined into + an `AgentResponse`, the `author_name` is propagated to the resulting `ChatMessage` objects. + agent_id: The identifier of the agent that produced this update. Useful in multi-agent + scenarios to track which agent generated specific parts of the response. + response_id: The ID of the response of which this update is a part. + message_id: The ID of the message of which this update is a part. + created_at: A timestamp for the response update. + additional_properties: Any additional properties associated with the update. + raw_representation: The raw representation from an underlying implementation. + Examples: .. code-block:: python @@ -2717,7 +2422,7 @@ class AgentResponseUpdate(SerializationMixin): # Serialization - to_dict and from_dict update_dict = update.to_dict() # {'type': 'agent_response_update', 'contents': [{'type': 'text', 'text': 'Processing...'}], - # 'role': {'type': 'role', 'value': 'assistant'}, 'response_id': 'run_123'} + # 'role': 'assistant', 'response_id': 'run_123'} restored_update = AgentResponseUpdate.from_dict(update_dict) print(restored_update.response_id) # "run_123" @@ -2733,48 +2438,52 @@ class AgentResponseUpdate(SerializationMixin): def __init__( self, *, - contents: Sequence[Content | MutableMapping[str, Any]] | None = None, - text: Content | str | None = None, - role: Role | MutableMapping[str, Any] | str | None = None, + contents: Sequence[Content] | None = None, + role: RoleLiteral | str | None = None, author_name: str | None = None, + agent_id: str | None = None, response_id: str | None = None, message_id: str | None = None, created_at: CreatedAtT | None = None, - additional_properties: MutableMapping[str, Any] | None = None, + additional_properties: dict[str, Any] | None = None, raw_representation: Any | None = None, - **kwargs: Any, ) -> None: """Initialize an AgentResponseUpdate. Keyword Args: - contents: Optional list of BaseContent items or dicts to include in the update. - text: Optional text content of the update. - role: The role of the author of the response update (Role, string, or dict - author_name: Optional name of the author of the response update. + contents: Optional list of Content items to include in the update. + role: The role of the author of the response update (e.g., "user", "assistant"). + author_name: Optional name of the author of the response update. Used in multi-agent + scenarios to identify which agent generated this update. + agent_id: Optional identifier of the agent that produced this update. response_id: Optional ID of the response of which this update is a part. message_id: Optional ID of the message of which this update is a part. created_at: Optional timestamp for the chat response update. additional_properties: Optional additional properties associated with the chat response update. raw_representation: Optional raw representation of the chat response update. - kwargs: will be combined with additional_properties if provided. """ - parsed_contents: list[Content] = [] if contents is None else _parse_content_list(contents) - - if text is not None: - if isinstance(text, str): - text = Content.from_text(text=text) - parsed_contents.append(text) + # Handle contents - support dict conversion for from_dict + if contents is None: + self.contents: list[Content] = [] + else: + processed_contents: list[Content] = [] + for c in contents: + if isinstance(c, Content): + processed_contents.append(c) + elif isinstance(c, dict): + processed_contents.append(Content.from_dict(c)) + else: + processed_contents.append(c) + self.contents = processed_contents - # Convert role from dict if needed (for SerializationMixin support) - if isinstance(role, MutableMapping): - role = Role.from_dict(role) - elif isinstance(role, str): - role = Role(value=role) + # Handle legacy dict format for role + if isinstance(role, dict) and "value" in role: + role = role["value"] - self.contents = parsed_contents - self.role = role + self.role: str | None = role self.author_name = author_name + self.agent_id = agent_id self.response_id = response_id self.message_id = message_id self.created_at = created_at diff --git a/python/packages/core/agent_framework/_workflows/_agent.py b/python/packages/core/agent_framework/_workflows/_agent.py index 1543ed7db6..28482820a0 100644 --- a/python/packages/core/agent_framework/_workflows/_agent.py +++ b/python/packages/core/agent_framework/_workflows/_agent.py @@ -16,7 +16,6 @@ BaseAgent, ChatMessage, Content, - Role, UsageDetails, ) @@ -344,7 +343,7 @@ def _convert_workflow_event_to_agent_update( return None return AgentResponseUpdate( contents=contents, - role=Role.ASSISTANT, + role="assistant", author_name=executor_id, response_id=response_id, message_id=str(uuid.uuid4()), @@ -370,7 +369,7 @@ def _convert_workflow_event_to_agent_update( ) return AgentResponseUpdate( contents=[function_call, approval_request], - role=Role.ASSISTANT, + role="assistant", author_name=self.name, response_id=response_id, message_id=str(uuid.uuid4()), @@ -453,7 +452,7 @@ def merge_updates(updates: list[AgentResponseUpdate], response_id: str) -> Agent - Group updates by response_id; within each response_id, group by message_id and keep a dangling bucket for updates without message_id. - Convert each group (per message and dangling) into an intermediate AgentResponse via - AgentResponse.from_agent_run_response_updates, then sort by created_at and merge. + AgentResponse.from_updates, then sort by created_at and merge. - Append messages from updates without any response_id at the end (global dangling), while aggregating metadata. Args: @@ -548,9 +547,9 @@ def _add_raw(value: object) -> None: per_message_responses: list[AgentResponse] = [] for _, msg_updates in by_msg.items(): if msg_updates: - per_message_responses.append(AgentResponse.from_agent_run_response_updates(msg_updates)) + per_message_responses.append(AgentResponse.from_updates(msg_updates)) if dangling: - per_message_responses.append(AgentResponse.from_agent_run_response_updates(dangling)) + per_message_responses.append(AgentResponse.from_updates(dangling)) per_message_responses.sort(key=lambda r: _parse_dt(r.created_at)) @@ -584,7 +583,7 @@ def _add_raw(value: object) -> None: # These are updates that couldn't be associated with any response_id # (e.g., orphan FunctionResultContent with no matching FunctionCallContent) if global_dangling: - flattened = AgentResponse.from_agent_run_response_updates(global_dangling) + flattened = AgentResponse.from_updates(global_dangling) final_messages.extend(flattened.messages) if flattened.usage_details: merged_usage = add_usage_details(merged_usage, flattened.usage_details) # type: ignore[arg-type] diff --git a/python/packages/core/agent_framework/_workflows/_agent_executor.py b/python/packages/core/agent_framework/_workflows/_agent_executor.py index 80bd4aba43..9849d351d1 100644 --- a/python/packages/core/agent_framework/_workflows/_agent_executor.py +++ b/python/packages/core/agent_framework/_workflows/_agent_executor.py @@ -198,7 +198,7 @@ async def handle_user_input_response( if not self._pending_agent_requests: # All pending requests have been resolved; resume agent execution - self._cache = normalize_messages_input(ChatMessage(role="user", contents=self._pending_responses_to_agent)) + self._cache = normalize_messages_input(ChatMessage("user", self._pending_responses_to_agent)) self._pending_responses_to_agent.clear() await self._run_agent_and_emit(ctx) @@ -378,12 +378,12 @@ async def _run_agent_streaming(self, ctx: WorkflowContext) -> AgentResponse | No # Build the final AgentResponse from the collected updates if isinstance(self._agent, ChatAgent): response_format = self._agent.default_options.get("response_format") - response = AgentResponse.from_agent_run_response_updates( + response = AgentResponse.from_updates( updates, output_format_type=response_format, ) else: - response = AgentResponse.from_agent_run_response_updates(updates) + response = AgentResponse.from_updates(updates) # Handle any user input requests after the streaming completes if user_input_requests: diff --git a/python/packages/core/agent_framework/_workflows/_base_group_chat_orchestrator.py b/python/packages/core/agent_framework/_workflows/_base_group_chat_orchestrator.py index e3cc4bc7d2..4c4d69f7bd 100644 --- a/python/packages/core/agent_framework/_workflows/_base_group_chat_orchestrator.py +++ b/python/packages/core/agent_framework/_workflows/_base_group_chat_orchestrator.py @@ -14,7 +14,7 @@ from typing_extensions import Never -from .._types import ChatMessage, Role +from .._types import ChatMessage from ._agent_executor import AgentExecutor, AgentExecutorRequest, AgentExecutorResponse from ._events import WorkflowEvent from ._executor import Executor, handler @@ -214,7 +214,7 @@ async def handle_str( Usage: workflow.run("Write a blog post about AI agents") """ - await self._handle_messages([ChatMessage(role=Role.USER, text=task)], ctx) + await self._handle_messages([ChatMessage("user", [task])], ctx) @handler async def handle_message( @@ -231,7 +231,7 @@ async def handle_message( ctx: Workflow context Usage: - workflow.run(ChatMessage(role=Role.USER, text="Write a blog post about AI agents")) + workflow.run(ChatMessage("user", ["Write a blog post about AI agents"])) """ await self._handle_messages([task], ctx) @@ -250,8 +250,8 @@ async def handle_messages( ctx: Workflow context Usage: workflow.run([ - ChatMessage(role=Role.USER, text="Write a blog post about AI agents"), - ChatMessage(role=Role.USER, text="Make it engaging and informative.") + ChatMessage("user", ["Write a blog post about AI agents"]), + ChatMessage("user", ["Make it engaging and informative."]) ]) """ if not task: @@ -401,7 +401,7 @@ def _create_completion_message(self, message: str) -> ChatMessage: Returns: ChatMessage with completion content """ - return ChatMessage(role=Role.ASSISTANT, text=message, author_name=self._name) + return ChatMessage("assistant", [message], author_name=self._name) # Participant routing (shared across all patterns) @@ -465,7 +465,7 @@ async def _send_request_to_participant( # AgentExecutors receive simple message list messages: list[ChatMessage] = [] if additional_instruction: - messages.append(ChatMessage(role=Role.USER, text=additional_instruction)) + messages.append(ChatMessage("user", [additional_instruction])) request = AgentExecutorRequest(messages=messages, should_respond=True) await ctx.send_message(request, target_id=target) await ctx.add_event( diff --git a/python/packages/core/agent_framework/_workflows/_concurrent.py b/python/packages/core/agent_framework/_workflows/_concurrent.py index 4204c8cd6d..afa0ef99e7 100644 --- a/python/packages/core/agent_framework/_workflows/_concurrent.py +++ b/python/packages/core/agent_framework/_workflows/_concurrent.py @@ -8,7 +8,7 @@ from typing_extensions import Never -from agent_framework import AgentProtocol, ChatMessage, Role +from agent_framework import AgentProtocol, ChatMessage from ._agent_executor import AgentExecutor, AgentExecutorRequest, AgentExecutorResponse from ._agent_utils import resolve_agent_id @@ -91,16 +91,13 @@ async def aggregate( logger.error("Concurrent aggregator received empty results list") raise ValueError("Aggregation failed: no results provided") - def _is_role(msg: Any, role: Role) -> bool: + def _is_role(msg: Any, role: str) -> bool: r = getattr(msg, "role", None) if r is None: return False # Normalize both r and role to lowercase strings for comparison r_str = str(r).lower() if isinstance(r, str) or hasattr(r, "__str__") else r - role_str = getattr(role, "value", None) - if role_str is None: - role_str = str(role) - role_str = role_str.lower() + role_str = str(role).lower() return r_str == role_str prompt_message: ChatMessage | None = None @@ -117,14 +114,14 @@ def _is_role(msg: Any, role: Role) -> bool: # Capture a single user prompt (first encountered across any conversation) if prompt_message is None: - found_user = next((m for m in conv if _is_role(m, Role.USER)), None) + found_user = next((m for m in conv if _is_role(m, "user")), None) if found_user is not None: prompt_message = found_user # Pick the final assistant message from the response; fallback to conversation search - final_assistant = next((m for m in reversed(resp_messages) if _is_role(m, Role.ASSISTANT)), None) + final_assistant = next((m for m in reversed(resp_messages) if _is_role(m, "assistant")), None) if final_assistant is None: - final_assistant = next((m for m in reversed(conv) if _is_role(m, Role.ASSISTANT)), None) + final_assistant = next((m for m in reversed(conv) if _is_role(m, "assistant")), None) if final_assistant is not None: assistant_replies.append(final_assistant) diff --git a/python/packages/core/agent_framework/_workflows/_conversation_state.py b/python/packages/core/agent_framework/_workflows/_conversation_state.py index 8c21513f6c..084cf9cda3 100644 --- a/python/packages/core/agent_framework/_workflows/_conversation_state.py +++ b/python/packages/core/agent_framework/_workflows/_conversation_state.py @@ -3,7 +3,7 @@ from collections.abc import Iterable from typing import Any, cast -from agent_framework import ChatMessage, Role +from agent_framework import ChatMessage from ._checkpoint_encoding import decode_checkpoint_value, encode_checkpoint_value @@ -40,15 +40,13 @@ def decode_chat_messages(payload: Iterable[dict[str, Any]]) -> list[ChatMessage] continue role_value = decode_checkpoint_value(item.get("role")) - if isinstance(role_value, Role): + if isinstance(role_value, str): role = role_value - elif isinstance(role_value, dict): - role_dict = cast(dict[str, Any], role_value) - role = Role.from_dict(role_dict) - elif isinstance(role_value, str): - role = Role(value=role_value) + elif isinstance(role_value, dict) and "value" in role_value: + # Handle legacy serialization format + role = role_value["value"] else: - role = Role.ASSISTANT + role = "assistant" contents_field = item.get("contents", []) contents: list[Any] = [] diff --git a/python/packages/core/agent_framework/_workflows/_group_chat.py b/python/packages/core/agent_framework/_workflows/_group_chat.py index 3f92d9ebf2..4b25ca1b77 100644 --- a/python/packages/core/agent_framework/_workflows/_group_chat.py +++ b/python/packages/core/agent_framework/_workflows/_group_chat.py @@ -31,7 +31,7 @@ from .._agents import AgentProtocol, ChatAgent from .._threads import AgentThread -from .._types import ChatMessage, Role +from .._types import ChatMessage from ._agent_executor import AgentExecutor, AgentExecutorRequest, AgentExecutorResponse from ._agent_utils import resolve_agent_id from ._base_group_chat_orchestrator import ( @@ -424,7 +424,7 @@ async def _invoke_agent_helper(conversation: list[ChatMessage]) -> AgentOrchestr ]) ) # Prepend instruction as system message - current_conversation.append(ChatMessage(role=Role.USER, text=instruction)) + current_conversation.append(ChatMessage("user", [instruction])) retry_attempts = self._retry_attempts while True: @@ -439,7 +439,7 @@ async def _invoke_agent_helper(conversation: list[ChatMessage]) -> AgentOrchestr # We don't need the full conversation since the thread should maintain history current_conversation = [ ChatMessage( - role=Role.USER, + role="user", text=f"Your input could not be parsed due to an error: {ex}. Please try again.", ) ] @@ -782,7 +782,7 @@ def with_termination_condition(self, termination_condition: TerminationCondition def stop_after_two_calls(conversation: list[ChatMessage]) -> bool: - calls = sum(1 for msg in conversation if msg.role == Role.ASSISTANT and msg.author_name == "specialist") + calls = sum(1 for msg in conversation if msg.role == "assistant" and msg.author_name == "specialist") return calls >= 2 diff --git a/python/packages/core/agent_framework/_workflows/_handoff.py b/python/packages/core/agent_framework/_workflows/_handoff.py index e529e09111..875fdc36c8 100644 --- a/python/packages/core/agent_framework/_workflows/_handoff.py +++ b/python/packages/core/agent_framework/_workflows/_handoff.py @@ -42,7 +42,7 @@ from .._middleware import FunctionInvocationContext, FunctionMiddleware from .._threads import AgentThread from .._tools import FunctionTool, tool -from .._types import AgentResponse, ChatMessage, Role +from .._types import AgentResponse, ChatMessage from ._agent_executor import AgentExecutor, AgentExecutorRequest, AgentExecutorResponse from ._agent_utils import resolve_agent_id from ._base_group_chat_orchestrator import TerminationCondition @@ -162,7 +162,7 @@ def create_response(response: str | list[str] | ChatMessage | list[ChatMessage]) """Create a HandoffAgentUserRequest from a simple text response.""" messages: list[ChatMessage] = [] if isinstance(response, str): - messages.append(ChatMessage(role=Role.USER, text=response)) + messages.append(ChatMessage("user", [response])) elif isinstance(response, ChatMessage): messages.append(response) elif isinstance(response, list): @@ -170,7 +170,7 @@ def create_response(response: str | list[str] | ChatMessage | list[ChatMessage]) if isinstance(item, ChatMessage): messages.append(item) elif isinstance(item, str): - messages.append(ChatMessage(role=Role.USER, text=item)) + messages.append(ChatMessage("user", [item])) else: raise TypeError("List items must be either str or ChatMessage instances") else: @@ -427,7 +427,7 @@ async def _run_agent_and_emit(self, ctx: WorkflowContext[AgentExecutorResponse, # or a termination condition is met. # This allows the agent to perform long-running tasks without returning control # to the coordinator or user prematurely. - self._cache.extend([ChatMessage(role=Role.USER, text=self._autonomous_mode_prompt)]) + self._cache.extend([ChatMessage("user", [self._autonomous_mode_prompt])]) self._autonomous_mode_turns += 1 await self._run_agent_and_emit(ctx) else: diff --git a/python/packages/core/agent_framework/_workflows/_magentic.py b/python/packages/core/agent_framework/_workflows/_magentic.py index eff87fd5f0..221f16bae6 100644 --- a/python/packages/core/agent_framework/_workflows/_magentic.py +++ b/python/packages/core/agent_framework/_workflows/_magentic.py @@ -18,7 +18,6 @@ AgentProtocol, AgentResponse, ChatMessage, - Role, ) from ._agent_executor import AgentExecutor, AgentExecutorRequest, AgentExecutorResponse @@ -607,14 +606,14 @@ async def plan(self, magentic_context: MagenticContext) -> ChatMessage: # Gather facts facts_user = ChatMessage( - role=Role.USER, + role="user", text=self.task_ledger_facts_prompt.format(task=magentic_context.task), ) facts_msg = await self._complete([*magentic_context.chat_history, facts_user]) # Create plan plan_user = ChatMessage( - role=Role.USER, + role="user", text=self.task_ledger_plan_prompt.format(team=team_text), ) plan_msg = await self._complete([*magentic_context.chat_history, facts_user, facts_msg, plan_user]) @@ -632,7 +631,7 @@ async def plan(self, magentic_context: MagenticContext) -> ChatMessage: facts=facts_msg.text, plan=plan_msg.text, ) - return ChatMessage(role=Role.ASSISTANT, text=combined, author_name=MAGENTIC_MANAGER_NAME) + return ChatMessage("assistant", [combined], author_name=MAGENTIC_MANAGER_NAME) async def replan(self, magentic_context: MagenticContext) -> ChatMessage: """Update facts and plan when stalling or looping has been detected.""" @@ -643,17 +642,19 @@ async def replan(self, magentic_context: MagenticContext) -> ChatMessage: # Update facts facts_update_user = ChatMessage( - role=Role.USER, - text=self.task_ledger_facts_update_prompt.format( - task=magentic_context.task, old_facts=self.task_ledger.facts.text - ), + "user", + [ + self.task_ledger_facts_update_prompt.format( + task=magentic_context.task, old_facts=self.task_ledger.facts.text + ) + ], ) updated_facts = await self._complete([*magentic_context.chat_history, facts_update_user]) # Update plan plan_update_user = ChatMessage( - role=Role.USER, - text=self.task_ledger_plan_update_prompt.format(team=team_text), + "user", + [self.task_ledger_plan_update_prompt.format(team=team_text)], ) updated_plan = await self._complete([ *magentic_context.chat_history, @@ -675,7 +676,7 @@ async def replan(self, magentic_context: MagenticContext) -> ChatMessage: facts=updated_facts.text, plan=updated_plan.text, ) - return ChatMessage(role=Role.ASSISTANT, text=combined, author_name=MAGENTIC_MANAGER_NAME) + return ChatMessage("assistant", [combined], author_name=MAGENTIC_MANAGER_NAME) async def create_progress_ledger(self, magentic_context: MagenticContext) -> MagenticProgressLedger: """Use the model to produce a JSON progress ledger based on the conversation so far. @@ -695,7 +696,7 @@ async def create_progress_ledger(self, magentic_context: MagenticContext) -> Mag team=team_text, names=names_csv, ) - user_message = ChatMessage(role=Role.USER, text=prompt) + user_message = ChatMessage("user", [prompt]) # Include full context to help the model decide current stage, with small retry loop attempts = 0 @@ -722,11 +723,11 @@ async def create_progress_ledger(self, magentic_context: MagenticContext) -> Mag async def prepare_final_answer(self, magentic_context: MagenticContext) -> ChatMessage: """Ask the model to produce the final answer addressed to the user.""" prompt = self.final_answer_prompt.format(task=magentic_context.task) - user_message = ChatMessage(role=Role.USER, text=prompt) + user_message = ChatMessage("user", [prompt]) response = await self._complete([*magentic_context.chat_history, user_message]) # Ensure role is assistant return ChatMessage( - role=Role.ASSISTANT, + role="assistant", text=response.text, author_name=response.author_name or MAGENTIC_MANAGER_NAME, ) @@ -812,11 +813,11 @@ def approve() -> "MagenticPlanReviewResponse": def revise(feedback: str | list[str] | ChatMessage | list[ChatMessage]) -> "MagenticPlanReviewResponse": """Create a revision response with feedback.""" if isinstance(feedback, str): - feedback = [ChatMessage(role=Role.USER, text=feedback)] + feedback = [ChatMessage("user", [feedback])] elif isinstance(feedback, ChatMessage): feedback = [feedback] elif isinstance(feedback, list): - feedback = [ChatMessage(role=Role.USER, text=item) if isinstance(item, str) else item for item in feedback] + feedback = [ChatMessage("user", [item]) if isinstance(item, str) else item for item in feedback] return MagenticPlanReviewResponse(review=feedback) @@ -1118,7 +1119,7 @@ async def _run_inner_loop_helper( # Add instruction to conversation (assistant guidance) instruction_msg = ChatMessage( - role=Role.ASSISTANT, + role="assistant", text=str(instruction), author_name=MAGENTIC_MANAGER_NAME, ) @@ -1227,7 +1228,7 @@ async def _check_within_limits_or_complete(self, ctx: WorkflowContext[Never, lis await ctx.yield_output([ *self._magentic_context.chat_history, ChatMessage( - role=Role.ASSISTANT, + role="assistant", text=f"Workflow terminated due to reaching maximum {limit_type} count.", author_name=MAGENTIC_MANAGER_NAME, ), @@ -1810,7 +1811,7 @@ def with_manager( class MyManager(MagenticManagerBase): async def plan(self, context: MagenticContext) -> ChatMessage: # Custom planning logic - return ChatMessage(role=Role.ASSISTANT, text="...") + return ChatMessage("assistant", ["..."]) manager = MyManager() diff --git a/python/packages/core/agent_framework/_workflows/_message_utils.py b/python/packages/core/agent_framework/_workflows/_message_utils.py index ad4a9b55f6..78a2f3f626 100644 --- a/python/packages/core/agent_framework/_workflows/_message_utils.py +++ b/python/packages/core/agent_framework/_workflows/_message_utils.py @@ -4,7 +4,7 @@ from collections.abc import Sequence -from agent_framework import ChatMessage, Role +from agent_framework import ChatMessage def normalize_messages_input( @@ -22,7 +22,7 @@ def normalize_messages_input( return [] if isinstance(messages, str): - return [ChatMessage(role=Role.USER, text=messages)] + return [ChatMessage("user", [messages])] if isinstance(messages, ChatMessage): return [messages] @@ -30,7 +30,7 @@ def normalize_messages_input( normalized: list[ChatMessage] = [] for item in messages: if isinstance(item, str): - normalized.append(ChatMessage(role=Role.USER, text=item)) + normalized.append(ChatMessage("user", [item])) elif isinstance(item, ChatMessage): normalized.append(item) else: diff --git a/python/packages/core/agent_framework/_workflows/_orchestration_request_info.py b/python/packages/core/agent_framework/_workflows/_orchestration_request_info.py index dc1e282a12..cc4b1ed15d 100644 --- a/python/packages/core/agent_framework/_workflows/_orchestration_request_info.py +++ b/python/packages/core/agent_framework/_workflows/_orchestration_request_info.py @@ -3,7 +3,7 @@ from dataclasses import dataclass from .._agents import AgentProtocol -from .._types import ChatMessage, Role +from .._types import ChatMessage from ._agent_executor import AgentExecutor, AgentExecutorRequest, AgentExecutorResponse from ._agent_utils import resolve_agent_id from ._executor import Executor, handler @@ -72,7 +72,7 @@ def from_strings(texts: list[str]) -> "AgentRequestInfoResponse": Returns: AgentRequestInfoResponse instance. """ - return AgentRequestInfoResponse(messages=[ChatMessage(role=Role.USER, text=text) for text in texts]) + return AgentRequestInfoResponse(messages=[ChatMessage("user", [text]) for text in texts]) @staticmethod def approve() -> "AgentRequestInfoResponse": diff --git a/python/packages/core/agent_framework/_workflows/_orchestrator_helpers.py b/python/packages/core/agent_framework/_workflows/_orchestrator_helpers.py index 82f6532ea2..0d74f53c39 100644 --- a/python/packages/core/agent_framework/_workflows/_orchestrator_helpers.py +++ b/python/packages/core/agent_framework/_workflows/_orchestrator_helpers.py @@ -8,7 +8,7 @@ import logging -from .._types import ChatMessage, Role +from .._types import ChatMessage logger = logging.getLogger(__name__) @@ -24,7 +24,7 @@ def clean_conversation_for_handoff(conversation: list[ChatMessage]) -> list[Chat Removes: - function_approval_request and function_call from assistant messages - - Tool response messages (Role.TOOL) + - Tool response messages (role="tool") - Messages with only tool calls and no text Preserves: @@ -40,7 +40,7 @@ def clean_conversation_for_handoff(conversation: list[ChatMessage]) -> list[Chat cleaned: list[ChatMessage] = [] for msg in conversation: # Skip tool response messages entirely - if msg.role == Role.TOOL: + if msg.role == "tool": continue # Check for tool-related content @@ -85,11 +85,11 @@ def create_completion_message( reason: Reason for completion (for default text generation) Returns: - ChatMessage with ASSISTANT role + ChatMessage with assistant role """ message_text = text or f"Conversation {reason}." return ChatMessage( - role=Role.ASSISTANT, - text=message_text, + "assistant", + [message_text], author_name=author_name, ) diff --git a/python/packages/core/agent_framework/_workflows/_workflow.py b/python/packages/core/agent_framework/_workflows/_workflow.py index bd14dc6bcc..dfd0331282 100644 --- a/python/packages/core/agent_framework/_workflows/_workflow.py +++ b/python/packages/core/agent_framework/_workflows/_workflow.py @@ -851,7 +851,7 @@ def as_agent(self, name: str | None = None) -> WorkflowAgent: The returned agent converts standard agent inputs (strings, ChatMessage, or lists of these) into a list[ChatMessage] that is passed to the workflow's start executor. This conversion happens in WorkflowAgent._normalize_messages() which transforms: - - str -> [ChatMessage(role=USER, text=str)] + - str -> [ChatMessage(USER, [str])] - ChatMessage -> [ChatMessage] - list[str | ChatMessage] -> list[ChatMessage] (with string elements converted) diff --git a/python/packages/core/agent_framework/observability.py b/python/packages/core/agent_framework/observability.py index 2d294daddd..8e2d736c42 100644 --- a/python/packages/core/agent_framework/observability.py +++ b/python/packages/core/agent_framework/observability.py @@ -41,7 +41,6 @@ ChatResponse, ChatResponseUpdate, Content, - FinishReason, ) __all__ = [ @@ -1211,7 +1210,7 @@ async def trace_get_streaming_response( duration = (end_time_stamp or perf_counter()) - start_time_stamp from ._types import ChatResponse - response = ChatResponse.from_chat_response_updates(all_updates) + response = ChatResponse.from_updates(all_updates) attributes = _get_response_attributes(attributes, response, duration=duration) _capture_response( span=span, @@ -1450,7 +1449,7 @@ async def trace_run_streaming( capture_exception(span=span, exception=exception, timestamp=time_ns()) raise else: - response = AgentResponse.from_agent_run_response_updates(all_updates) + response = AgentResponse.from_updates(all_updates) attributes = _get_response_attributes(attributes, response, capture_usage=capture_usage) _capture_response(span=span, attributes=attributes) if OBSERVABILITY_SETTINGS.SENSITIVE_DATA_ENABLED and response.messages: @@ -1715,7 +1714,7 @@ def _capture_messages( messages: "str | ChatMessage | list[str] | list[ChatMessage]", system_instructions: str | list[str] | None = None, output: bool = False, - finish_reason: "FinishReason | None" = None, + finish_reason: str | None = None, ) -> None: """Log messages with extra information.""" from ._types import prepare_messages @@ -1730,13 +1729,13 @@ def _capture_messages( logger.info( otel_message, extra={ - OtelAttr.EVENT_NAME: OtelAttr.CHOICE if output else ROLE_EVENT_MAP.get(message.role.value), + OtelAttr.EVENT_NAME: OtelAttr.CHOICE if output else ROLE_EVENT_MAP.get(message.role), OtelAttr.PROVIDER_NAME: provider_name, ChatMessageListTimestampFilter.INDEX_KEY: index, }, ) if finish_reason: - otel_messages[-1]["finish_reason"] = FINISH_REASON_MAP[finish_reason.value] + otel_messages[-1]["finish_reason"] = FINISH_REASON_MAP[finish_reason] span.set_attribute(OtelAttr.OUTPUT_MESSAGES if output else OtelAttr.INPUT_MESSAGES, json.dumps(otel_messages)) if system_instructions: if not isinstance(system_instructions, list): @@ -1747,7 +1746,7 @@ def _capture_messages( def _to_otel_message(message: "ChatMessage") -> dict[str, Any]: """Create a otel representation of a message.""" - return {"role": message.role.value, "parts": [_to_otel_part(content) for content in message.contents]} + return {"role": message.role, "parts": [_to_otel_part(content) for content in message.contents]} def _to_otel_part(content: "Content") -> dict[str, Any] | None: @@ -1806,7 +1805,9 @@ def _get_response_attributes( getattr(response.raw_representation, "finish_reason", None) if response.raw_representation else None ) if finish_reason: - attributes[OtelAttr.FINISH_REASONS] = json.dumps([finish_reason.value]) + # Handle both string and object with .value attribute for backward compatibility + finish_reason_str = finish_reason.value if hasattr(finish_reason, "value") else finish_reason + attributes[OtelAttr.FINISH_REASONS] = json.dumps([finish_reason_str]) if model_id := getattr(response, "model_id", None): attributes[SpanAttributes.LLM_RESPONSE_MODEL] = model_id if capture_usage and (usage := response.usage_details): diff --git a/python/packages/core/agent_framework/openai/_assistants_client.py b/python/packages/core/agent_framework/openai/_assistants_client.py index 22852bea53..f653e22d42 100644 --- a/python/packages/core/agent_framework/openai/_assistants_client.py +++ b/python/packages/core/agent_framework/openai/_assistants_client.py @@ -41,7 +41,6 @@ ChatResponse, ChatResponseUpdate, Content, - Role, UsageDetails, prepare_function_call_results, ) @@ -345,7 +344,7 @@ async def _inner_get_response( options: dict[str, Any], **kwargs: Any, ) -> ChatResponse: - return await ChatResponse.from_chat_response_generator( + return await ChatResponse.from_update_generator( updates=self._inner_get_streaming_response(messages=messages, options=options, **kwargs), output_format_type=options.get("response_format"), ) @@ -479,19 +478,19 @@ async def _process_stream_events(self, stream: Any, thread_id: str) -> AsyncIter message_id=response_id, raw_representation=response.data, response_id=response_id, - role=Role.ASSISTANT, + role="assistant", ) elif response.event == "thread.run.step.created" and isinstance(response.data, RunStep): response_id = response.data.run_id elif response.event == "thread.message.delta" and isinstance(response.data, MessageDeltaEvent): delta = response.data.delta - role = Role.USER if delta.role == "user" else Role.ASSISTANT + role = "user" if delta.role == "user" else "assistant" for delta_block in delta.content or []: if isinstance(delta_block, TextDeltaBlock) and delta_block.text and delta_block.text.value: yield ChatResponseUpdate( role=role, - text=delta_block.text.value, + contents=[Content.from_text(text=delta_block.text.value)], conversation_id=thread_id, message_id=response_id, raw_representation=response.data, @@ -501,7 +500,7 @@ async def _process_stream_events(self, stream: Any, thread_id: str) -> AsyncIter contents = self._parse_function_calls_from_assistants(response.data, response_id) if contents: yield ChatResponseUpdate( - role=Role.ASSISTANT, + role="assistant", contents=contents, conversation_id=thread_id, message_id=response_id, @@ -522,7 +521,7 @@ async def _process_stream_events(self, stream: Any, thread_id: str) -> AsyncIter ) ) yield ChatResponseUpdate( - role=Role.ASSISTANT, + role="assistant", contents=[usage_content], conversation_id=thread_id, message_id=response_id, @@ -536,7 +535,7 @@ async def _process_stream_events(self, stream: Any, thread_id: str) -> AsyncIter message_id=response_id, raw_representation=response.data, response_id=response_id, - role=Role.ASSISTANT, + role="assistant", ) def _parse_function_calls_from_assistants(self, event_data: Run, response_id: str | None) -> list[Content]: @@ -670,7 +669,7 @@ def _prepare_options( # since there is no such message roles in OpenAI Assistants. # All other messages are added 1:1. for chat_message in messages: - if chat_message.role.value in ["system", "developer"]: + if chat_message.role in ["system", "developer"]: for text_content in [content for content in chat_message.contents if content.type == "text"]: text = getattr(text_content, "text", None) if text: @@ -697,7 +696,7 @@ def _prepare_options( additional_messages = [] additional_messages.append( AdditionalMessage( - role="assistant" if chat_message.role == Role.ASSISTANT else "user", + role="assistant" if chat_message.role == "assistant" else "user", content=message_contents, ) ) diff --git a/python/packages/core/agent_framework/openai/_chat_client.py b/python/packages/core/agent_framework/openai/_chat_client.py index e70b4790f6..1a0529f50f 100644 --- a/python/packages/core/agent_framework/openai/_chat_client.py +++ b/python/packages/core/agent_framework/openai/_chat_client.py @@ -26,8 +26,6 @@ ChatResponse, ChatResponseUpdate, Content, - FinishReason, - Role, UsageDetails, prepare_function_call_results, ) @@ -285,11 +283,11 @@ def _parse_response_from_openai(self, response: ChatCompletion, options: dict[st """Parse a response from OpenAI into a ChatResponse.""" response_metadata = self._get_metadata_from_chat_response(response) messages: list[ChatMessage] = [] - finish_reason: FinishReason | None = None + finish_reason: str | None = None for choice in response.choices: response_metadata.update(self._get_metadata_from_chat_choice(choice)) if choice.finish_reason: - finish_reason = FinishReason(value=choice.finish_reason) + finish_reason = choice.finish_reason contents: list[Content] = [] if text_content := self._parse_text_from_openai(choice): contents.append(text_content) @@ -297,7 +295,7 @@ def _parse_response_from_openai(self, response: ChatCompletion, options: dict[st contents.extend(parsed_tool_calls) if reasoning_details := getattr(choice.message, "reasoning_details", None): contents.append(Content.from_text_reasoning(protected_data=json.dumps(reasoning_details))) - messages.append(ChatMessage(role="assistant", contents=contents)) + messages.append(ChatMessage("assistant", contents)) return ChatResponse( response_id=response.id, created_at=datetime.fromtimestamp(response.created, tz=timezone.utc).strftime("%Y-%m-%dT%H:%M:%S.%fZ"), @@ -317,7 +315,7 @@ def _parse_response_update_from_openai( chunk_metadata = self._get_metadata_from_streaming_chat_response(chunk) if chunk.usage: return ChatResponseUpdate( - role=Role.ASSISTANT, + role="assistant", contents=[ Content.from_usage( usage_details=self._parse_usage_from_openai(chunk.usage), raw_representation=chunk @@ -329,12 +327,12 @@ def _parse_response_update_from_openai( message_id=chunk.id, ) contents: list[Content] = [] - finish_reason: FinishReason | None = None + finish_reason: str | None = None for choice in chunk.choices: chunk_metadata.update(self._get_metadata_from_chat_choice(choice)) contents.extend(self._parse_tool_calls_from_openai(choice)) if choice.finish_reason: - finish_reason = FinishReason(value=choice.finish_reason) + finish_reason = choice.finish_reason if text_content := self._parse_text_from_openai(choice): contents.append(text_content) @@ -343,7 +341,7 @@ def _parse_response_update_from_openai( return ChatResponseUpdate( created_at=datetime.fromtimestamp(chunk.created, tz=timezone.utc).strftime("%Y-%m-%dT%H:%M:%S.%fZ"), contents=contents, - role=Role.ASSISTANT, + role="assistant", model_id=chunk.model, additional_properties=chunk_metadata, finish_reason=finish_reason, @@ -430,7 +428,7 @@ def _prepare_messages_for_openai( Allowing customization of the key names for role/author, and optionally overriding the role. - Role.TOOL messages need to be formatted different than system/user/assistant messages: + "tool" messages need to be formatted different than system/user/assistant messages: They require a "tool_call_id" and (function) "name" key, and the "metadata" key should be removed. The "encoding" key should also be removed. @@ -459,9 +457,9 @@ def _prepare_message_for_openai(self, message: ChatMessage) -> list[dict[str, An continue args: dict[str, Any] = { - "role": message.role.value if isinstance(message.role, Role) else message.role, + "role": message.role, } - if message.author_name and message.role != Role.TOOL: + if message.author_name and message.role != "tool": args["name"] = message.author_name if "reasoning_details" in message.additional_properties and ( details := message.additional_properties["reasoning_details"] diff --git a/python/packages/core/agent_framework/openai/_responses_client.py b/python/packages/core/agent_framework/openai/_responses_client.py index 9a3436e5ce..125ff1cd20 100644 --- a/python/packages/core/agent_framework/openai/_responses_client.py +++ b/python/packages/core/agent_framework/openai/_responses_client.py @@ -54,7 +54,6 @@ ChatResponse, ChatResponseUpdate, Content, - Role, TextSpanRegion, UsageDetails, detect_media_type_from_base64, @@ -610,7 +609,7 @@ def _prepare_messages_for_openai(self, chat_messages: Sequence[ChatMessage]) -> Allowing customization of the key names for role/author, and optionally overriding the role. - Role.TOOL messages need to be formatted different than system/user/assistant messages: + "tool" messages need to be formatted different than system/user/assistant messages: They require a "tool_call_id" and (function) "name" key, and the "metadata" key should be removed. The "encoding" key should also be removed. @@ -643,7 +642,7 @@ def _prepare_message_for_openai( """Prepare a chat message for the OpenAI Responses API format.""" all_messages: list[dict[str, Any]] = [] args: dict[str, Any] = { - "role": message.role.value if isinstance(message.role, Role) else message.role, + "role": message.role, } for content in message.contents: match content.type: @@ -669,7 +668,7 @@ def _prepare_message_for_openai( def _prepare_content_for_openai( self, - role: Role, + role: str, content: Content, call_id_to_id: dict[str, str], ) -> dict[str, Any]: @@ -677,7 +676,7 @@ def _prepare_content_for_openai( match content.type: case "text": return { - "type": "output_text" if role == Role.ASSISTANT else "input_text", + "type": "output_text" if role == "assistant" else "input_text", "text": content.text, } case "text_reasoning": @@ -1027,7 +1026,7 @@ def _parse_response_from_openai( ) case _: logger.debug("Unparsed output of type: %s: %s", item.type, item) - response_message = ChatMessage(role="assistant", contents=contents) + response_message = ChatMessage("assistant", contents) args: dict[str, Any] = { "response_id": response.id, "created_at": datetime.fromtimestamp(response.created_at, tz=timezone.utc).strftime( @@ -1387,7 +1386,7 @@ def _get_ann_value(key: str) -> Any: contents=contents, conversation_id=conversation_id, response_id=response_id, - role=Role.ASSISTANT, + role="assistant", model_id=model, additional_properties=metadata, raw_representation=event, diff --git a/python/packages/core/tests/azure/test_azure_assistants_client.py b/python/packages/core/tests/azure/test_azure_assistants_client.py index 32f1b13252..0187e98ddc 100644 --- a/python/packages/core/tests/azure/test_azure_assistants_client.py +++ b/python/packages/core/tests/azure/test_azure_assistants_client.py @@ -277,7 +277,7 @@ async def test_azure_assistants_client_get_response() -> None: "It's a beautiful day for outdoor activities.", ) ) - messages.append(ChatMessage(role="user", text="What's the weather like today?")) + messages.append(ChatMessage("user", ["What's the weather like today?"])) # Test that the client can be used to get a response response = await azure_assistants_client.get_response(messages=messages) @@ -295,7 +295,7 @@ async def test_azure_assistants_client_get_response_tools() -> None: assert isinstance(azure_assistants_client, ChatClientProtocol) messages: list[ChatMessage] = [] - messages.append(ChatMessage(role="user", text="What's the weather like in Seattle?")) + messages.append(ChatMessage("user", ["What's the weather like in Seattle?"])) # Test that the client can be used to get a response response = await azure_assistants_client.get_response( @@ -323,7 +323,7 @@ async def test_azure_assistants_client_streaming() -> None: "It's a beautiful day for outdoor activities.", ) ) - messages.append(ChatMessage(role="user", text="What's the weather like today?")) + messages.append(ChatMessage("user", ["What's the weather like today?"])) # Test that the client can be used to get a response response = azure_assistants_client.get_streaming_response(messages=messages) @@ -347,7 +347,7 @@ async def test_azure_assistants_client_streaming_tools() -> None: assert isinstance(azure_assistants_client, ChatClientProtocol) messages: list[ChatMessage] = [] - messages.append(ChatMessage(role="user", text="What's the weather like in Seattle?")) + messages.append(ChatMessage("user", ["What's the weather like in Seattle?"])) # Test that the client can be used to get a response response = azure_assistants_client.get_streaming_response( @@ -372,7 +372,7 @@ async def test_azure_assistants_client_with_existing_assistant() -> None: # First create an assistant to use in the test async with AzureOpenAIAssistantsClient(credential=AzureCliCredential()) as temp_client: # Get the assistant ID by triggering assistant creation - messages = [ChatMessage(role="user", text="Hello")] + messages = [ChatMessage("user", ["Hello"])] await temp_client.get_response(messages=messages) assistant_id = temp_client.assistant_id @@ -383,7 +383,7 @@ async def test_azure_assistants_client_with_existing_assistant() -> None: assert isinstance(azure_assistants_client, ChatClientProtocol) assert azure_assistants_client.assistant_id == assistant_id - messages = [ChatMessage(role="user", text="What can you do?")] + messages = [ChatMessage("user", ["What can you do?"])] # Test that the client can be used to get a response response = await azure_assistants_client.get_response(messages=messages) diff --git a/python/packages/core/tests/azure/test_azure_chat_client.py b/python/packages/core/tests/azure/test_azure_chat_client.py index caba327dc7..99df3bbdf5 100644 --- a/python/packages/core/tests/azure/test_azure_chat_client.py +++ b/python/packages/core/tests/azure/test_azure_chat_client.py @@ -665,7 +665,7 @@ async def test_azure_openai_chat_client_response() -> None: "of climate change.", ) ) - messages.append(ChatMessage(role="user", text="who are Emily and David?")) + messages.append(ChatMessage("user", ["who are Emily and David?"])) # Test that the client can be used to get a response response = await azure_chat_client.get_response(messages=messages) @@ -686,7 +686,7 @@ async def test_azure_openai_chat_client_response_tools() -> None: assert isinstance(azure_chat_client, ChatClientProtocol) messages: list[ChatMessage] = [] - messages.append(ChatMessage(role="user", text="who are Emily and David?")) + messages.append(ChatMessage("user", ["who are Emily and David?"])) # Test that the client can be used to get a response response = await azure_chat_client.get_response( @@ -716,7 +716,7 @@ async def test_azure_openai_chat_client_streaming() -> None: "of climate change.", ) ) - messages.append(ChatMessage(role="user", text="who are Emily and David?")) + messages.append(ChatMessage("user", ["who are Emily and David?"])) # Test that the client can be used to get a response response = azure_chat_client.get_streaming_response(messages=messages) @@ -742,7 +742,7 @@ async def test_azure_openai_chat_client_streaming_tools() -> None: assert isinstance(azure_chat_client, ChatClientProtocol) messages: list[ChatMessage] = [] - messages.append(ChatMessage(role="user", text="who are Emily and David?")) + messages.append(ChatMessage("user", ["who are Emily and David?"])) # Test that the client can be used to get a response response = azure_chat_client.get_streaming_response( diff --git a/python/packages/core/tests/azure/test_azure_responses_client.py b/python/packages/core/tests/azure/test_azure_responses_client.py index 35d92c7b98..13dfee819d 100644 --- a/python/packages/core/tests/azure/test_azure_responses_client.py +++ b/python/packages/core/tests/azure/test_azure_responses_client.py @@ -221,14 +221,14 @@ async def test_integration_options( # Prepare test message if option_name == "tools" or option_name == "tool_choice": # Use weather-related prompt for tool tests - messages = [ChatMessage(role="user", text="What is the weather in Seattle?")] + messages = [ChatMessage("user", ["What is the weather in Seattle?"])] elif option_name == "response_format": # Use prompt that works well with structured output - messages = [ChatMessage(role="user", text="The weather in Seattle is sunny")] - messages.append(ChatMessage(role="user", text="What is the weather in Seattle?")) + messages = [ChatMessage("user", ["The weather in Seattle is sunny"])] + messages.append(ChatMessage("user", ["What is the weather in Seattle?"])) else: # Generic prompt for simple options - messages = [ChatMessage(role="user", text="Say 'Hello World' briefly.")] + messages = [ChatMessage("user", ["Say 'Hello World' briefly."])] # Build options dict options: dict[str, Any] = {option_name: option_value} @@ -245,7 +245,7 @@ async def test_integration_options( ) output_format = option_value if option_name == "response_format" else None - response = await ChatResponse.from_chat_response_generator(response_gen, output_format_type=output_format) + response = await ChatResponse.from_update_generator(response_gen, output_format_type=output_format) else: # Test non-streaming mode response = await client.get_response( @@ -293,7 +293,7 @@ async def test_integration_web_search() -> None: }, } if streaming: - response = await ChatResponse.from_chat_response_generator(client.get_streaming_response(**content)) + response = await ChatResponse.from_update_generator(client.get_streaming_response(**content)) else: response = await client.get_response(**content) @@ -318,7 +318,7 @@ async def test_integration_web_search() -> None: }, } if streaming: - response = await ChatResponse.from_chat_response_generator(client.get_streaming_response(**content)) + response = await ChatResponse.from_update_generator(client.get_streaming_response(**content)) else: response = await client.get_response(**content) assert response.text is not None @@ -367,7 +367,7 @@ async def test_integration_client_file_search_streaming() -> None: ) assert response is not None - full_response = await ChatResponse.from_chat_response_generator(response) + full_response = await ChatResponse.from_update_generator(response) assert "sunny" in full_response.text.lower() assert "75" in full_response.text finally: diff --git a/python/packages/core/tests/core/conftest.py b/python/packages/core/tests/core/conftest.py index ed8de28c11..c5b7be9687 100644 --- a/python/packages/core/tests/core/conftest.py +++ b/python/packages/core/tests/core/conftest.py @@ -21,7 +21,6 @@ ChatResponse, ChatResponseUpdate, Content, - Role, ToolProtocol, tool, use_chat_middleware, @@ -95,7 +94,7 @@ async def get_response( self.call_count += 1 if self.responses: return self.responses.pop(0) - return ChatResponse(messages=ChatMessage(role="assistant", text="test response")) + return ChatResponse(messages=ChatMessage("assistant", ["test response"])) async def get_streaming_response( self, @@ -108,7 +107,7 @@ async def get_streaming_response( for update in self.streaming_responses.pop(0): yield update else: - yield ChatResponseUpdate(text=Content.from_text(text="test streaming response "), role="assistant") + yield ChatResponseUpdate(contents=[Content.from_text(text="test streaming response ")], role="assistant") yield ChatResponseUpdate(contents=[Content.from_text(text="another update")], role="assistant") @@ -143,7 +142,7 @@ async def _inner_get_response( logger.debug(f"Running base chat client inner, with: {messages=}, {options=}, {kwargs=}") self.call_count += 1 if not self.run_responses: - return ChatResponse(messages=ChatMessage(role="assistant", text=f"test response - {messages[-1].text}")) + return ChatResponse(messages=ChatMessage("assistant", [f"test response - {messages[-1].text}"])) response = self.run_responses.pop(0) @@ -168,10 +167,14 @@ async def _inner_get_streaming_response( ) -> AsyncIterable[ChatResponseUpdate]: logger.debug(f"Running base chat client inner stream, with: {messages=}, {options=}, {kwargs=}") if not self.streaming_responses: - yield ChatResponseUpdate(text=f"update - {messages[0].text}", role="assistant") + yield ChatResponseUpdate( + contents=[Content.from_text(text=f"update - {messages[0].text}")], role="assistant" + ) return if options.get("tool_choice") == "none": - yield ChatResponseUpdate(text="I broke out of the function invocation loop...", role="assistant") + yield ChatResponseUpdate( + contents=[Content.from_text(text="I broke out of the function invocation loop...")], role="assistant" + ) return response = self.streaming_responses.pop(0) for update in response: @@ -233,7 +236,7 @@ async def run( **kwargs: Any, ) -> AgentResponse: logger.debug(f"Running mock agent, with: {messages=}, {thread=}, {kwargs=}") - return AgentResponse(messages=[ChatMessage(role=Role.ASSISTANT, contents=[Content.from_text("Response")])]) + return AgentResponse(messages=[ChatMessage("assistant", [Content.from_text("Response")])]) async def run_stream( self, diff --git a/python/packages/core/tests/core/test_agents.py b/python/packages/core/tests/core/test_agents.py index 1f4d1cadce..09ef1bbbe1 100644 --- a/python/packages/core/tests/core/test_agents.py +++ b/python/packages/core/tests/core/test_agents.py @@ -24,7 +24,6 @@ Context, ContextProvider, HostedCodeInterpreterTool, - Role, ToolProtocol, tool, ) @@ -43,7 +42,7 @@ def test_agent_type(agent: AgentProtocol) -> None: async def test_agent_run(agent: AgentProtocol) -> None: response = await agent.run("test") - assert response.messages[0].role == Role.ASSISTANT + assert response.messages[0].role == "assistant" assert response.messages[0].text == "Response" @@ -104,12 +103,12 @@ async def test_chat_client_agent_get_new_thread(chat_client: ChatClientProtocol) async def test_chat_client_agent_prepare_thread_and_messages(chat_client: ChatClientProtocol) -> None: agent = ChatAgent(chat_client=chat_client) - message = ChatMessage(role=Role.USER, text="Hello") + message = ChatMessage("user", ["Hello"]) thread = AgentThread(message_store=ChatMessageStore(messages=[message])) _, _, result_messages = await agent._prepare_thread_and_messages( # type: ignore[reportPrivateUsage] thread=thread, - input_messages=[ChatMessage(role=Role.USER, text="Test")], + input_messages=[ChatMessage("user", ["Test"])], ) assert len(result_messages) == 2 @@ -127,7 +126,7 @@ async def test_prepare_thread_does_not_mutate_agent_chat_options(chat_client: Ch _, prepared_chat_options, _ = await agent._prepare_thread_and_messages( # type: ignore[reportPrivateUsage] thread=thread, - input_messages=[ChatMessage(role=Role.USER, text="Test")], + input_messages=[ChatMessage("user", ["Test"])], ) assert prepared_chat_options.get("tools") is not None @@ -139,7 +138,7 @@ async def test_prepare_thread_does_not_mutate_agent_chat_options(chat_client: Ch async def test_chat_client_agent_update_thread_id(chat_client_base: ChatClientProtocol) -> None: mock_response = ChatResponse( - messages=[ChatMessage(role=Role.ASSISTANT, contents=[Content.from_text("test response")])], + messages=[ChatMessage("assistant", [Content.from_text("test response")])], conversation_id="123", ) chat_client_base.run_responses = [mock_response] @@ -202,11 +201,7 @@ async def test_chat_client_agent_author_name_as_agent_name(chat_client: ChatClie async def test_chat_client_agent_author_name_is_used_from_response(chat_client_base: ChatClientProtocol) -> None: chat_client_base.run_responses = [ ChatResponse( - messages=[ - ChatMessage( - role=Role.ASSISTANT, contents=[Content.from_text("test response")], author_name="TestAuthor" - ) - ] + messages=[ChatMessage("assistant", [Content.from_text("test response")], author_name="TestAuthor")] ) ] @@ -256,7 +251,7 @@ async def invoking(self, messages: ChatMessage | MutableSequence[ChatMessage], * async def test_chat_agent_context_providers_model_invoking(chat_client: ChatClientProtocol) -> None: """Test that context providers' invoking is called during agent run.""" - mock_provider = MockContextProvider(messages=[ChatMessage(role=Role.SYSTEM, text="Test context instructions")]) + mock_provider = MockContextProvider(messages=[ChatMessage("system", ["Test context instructions"])]) agent = ChatAgent(chat_client=chat_client, context_provider=mock_provider) await agent.run("Hello") @@ -269,7 +264,7 @@ async def test_chat_agent_context_providers_thread_created(chat_client_base: Cha mock_provider = MockContextProvider() chat_client_base.run_responses = [ ChatResponse( - messages=[ChatMessage(role=Role.ASSISTANT, contents=[Content.from_text("test response")])], + messages=[ChatMessage("assistant", [Content.from_text("test response")])], conversation_id="test-thread-id", ) ] @@ -296,19 +291,19 @@ async def test_chat_agent_context_providers_messages_adding(chat_client: ChatCli async def test_chat_agent_context_instructions_in_messages(chat_client: ChatClientProtocol) -> None: """Test that AI context instructions are included in messages.""" - mock_provider = MockContextProvider(messages=[ChatMessage(role="system", text="Context-specific instructions")]) + mock_provider = MockContextProvider(messages=[ChatMessage("system", ["Context-specific instructions"])]) agent = ChatAgent(chat_client=chat_client, instructions="Agent instructions", context_provider=mock_provider) # We need to test the _prepare_thread_and_messages method directly _, _, messages = await agent._prepare_thread_and_messages( # type: ignore[reportPrivateUsage] - thread=None, input_messages=[ChatMessage(role=Role.USER, text="Hello")] + thread=None, input_messages=[ChatMessage("user", ["Hello"])] ) # Should have context instructions, and user message assert len(messages) == 2 - assert messages[0].role == Role.SYSTEM + assert messages[0].role == "system" assert messages[0].text == "Context-specific instructions" - assert messages[1].role == Role.USER + assert messages[1].role == "user" assert messages[1].text == "Hello" # instructions system message is added by a chat_client @@ -319,18 +314,18 @@ async def test_chat_agent_no_context_instructions(chat_client: ChatClientProtoco agent = ChatAgent(chat_client=chat_client, instructions="Agent instructions", context_provider=mock_provider) _, _, messages = await agent._prepare_thread_and_messages( # type: ignore[reportPrivateUsage] - thread=None, input_messages=[ChatMessage(role=Role.USER, text="Hello")] + thread=None, input_messages=[ChatMessage("user", ["Hello"])] ) # Should have agent instructions and user message only assert len(messages) == 1 - assert messages[0].role == Role.USER + assert messages[0].role == "user" assert messages[0].text == "Hello" async def test_chat_agent_run_stream_context_providers(chat_client: ChatClientProtocol) -> None: """Test that context providers work with run_stream method.""" - mock_provider = MockContextProvider(messages=[ChatMessage(role=Role.SYSTEM, text="Stream context instructions")]) + mock_provider = MockContextProvider(messages=[ChatMessage("system", ["Stream context instructions"])]) agent = ChatAgent(chat_client=chat_client, context_provider=mock_provider) # Collect all stream updates @@ -350,7 +345,7 @@ async def test_chat_agent_context_providers_with_thread_service_id(chat_client_b mock_provider = MockContextProvider() chat_client_base.run_responses = [ ChatResponse( - messages=[ChatMessage(role=Role.ASSISTANT, contents=[Content.from_text("test response")])], + messages=[ChatMessage("assistant", [Content.from_text("test response")])], conversation_id="service-thread-123", ) ] @@ -585,7 +580,7 @@ def echo_thread_info(text: str, **kwargs: Any) -> str: # type: ignore[reportUnk ], ) ), - ChatResponse(messages=ChatMessage(role="assistant", text="done")), + ChatResponse(messages=ChatMessage("assistant", ["done"])), ] agent = ChatAgent( @@ -928,7 +923,7 @@ async def invoking(self, messages, **kwargs): # Run the agent and verify context tools are added _, options, _ = await agent._prepare_thread_and_messages( # type: ignore[reportPrivateUsage] - thread=None, input_messages=[ChatMessage(role=Role.USER, text="Hello")] + thread=None, input_messages=[ChatMessage("user", ["Hello"])] ) # The context tools should now be in the options @@ -952,7 +947,7 @@ async def invoking(self, messages, **kwargs): # Run the agent and verify context instructions are available _, options, _ = await agent._prepare_thread_and_messages( # type: ignore[reportPrivateUsage] - thread=None, input_messages=[ChatMessage(role=Role.USER, text="Hello")] + thread=None, input_messages=[ChatMessage("user", ["Hello"])] ) # The context instructions should now be in the options @@ -972,7 +967,7 @@ async def test_chat_agent_raises_on_conversation_id_mismatch(chat_client_base: C with pytest.raises(AgentExecutionException, match="conversation_id set on the agent is different"): await agent._prepare_thread_and_messages( # type: ignore[reportPrivateUsage] - thread=thread, input_messages=[ChatMessage(role=Role.USER, text="Hello")] + thread=thread, input_messages=[ChatMessage("user", ["Hello"])] ) diff --git a/python/packages/core/tests/core/test_as_tool_kwargs_propagation.py b/python/packages/core/tests/core/test_as_tool_kwargs_propagation.py index 39f441eb49..e3457f6625 100644 --- a/python/packages/core/tests/core/test_as_tool_kwargs_propagation.py +++ b/python/packages/core/tests/core/test_as_tool_kwargs_propagation.py @@ -28,7 +28,7 @@ async def capture_middleware( # Setup mock response chat_client.responses = [ - ChatResponse(messages=[ChatMessage(role="assistant", text="Response from sub-agent")]), + ChatResponse(messages=[ChatMessage("assistant", ["Response from sub-agent"])]), ] # Create sub-agent with middleware @@ -70,7 +70,7 @@ async def capture_middleware( # Setup mock response chat_client.responses = [ - ChatResponse(messages=[ChatMessage(role="assistant", text="Response from sub-agent")]), + ChatResponse(messages=[ChatMessage("assistant", ["Response from sub-agent"])]), ] sub_agent = ChatAgent( @@ -122,8 +122,8 @@ async def capture_middleware( ) ] ), - ChatResponse(messages=[ChatMessage(role="assistant", text="Response from agent_c")]), - ChatResponse(messages=[ChatMessage(role="assistant", text="Response from agent_b")]), + ChatResponse(messages=[ChatMessage("assistant", ["Response from agent_c"])]), + ChatResponse(messages=[ChatMessage("assistant", ["Response from agent_b"])]), ] # Create agent C (bottom level) @@ -173,7 +173,7 @@ async def capture_middleware( from agent_framework import ChatResponseUpdate chat_client.streaming_responses = [ - [ChatResponseUpdate(text=Content.from_text(text="Streaming response"), role="assistant")], + [ChatResponseUpdate(contents=[Content.from_text(text="Streaming response")], role="assistant")], ] sub_agent = ChatAgent( @@ -204,7 +204,7 @@ async def test_as_tool_empty_kwargs_still_works(self, chat_client: MockChatClien """Test that as_tool works correctly when no extra kwargs are provided.""" # Setup mock response chat_client.responses = [ - ChatResponse(messages=[ChatMessage(role="assistant", text="Response from agent")]), + ChatResponse(messages=[ChatMessage("assistant", ["Response from agent"])]), ] sub_agent = ChatAgent( @@ -233,7 +233,7 @@ async def capture_middleware( # Setup mock response chat_client.responses = [ - ChatResponse(messages=[ChatMessage(role="assistant", text="Response with options")]), + ChatResponse(messages=[ChatMessage("assistant", ["Response with options"])]), ] sub_agent = ChatAgent( @@ -280,8 +280,8 @@ async def capture_middleware( # Setup mock responses for both calls chat_client.responses = [ - ChatResponse(messages=[ChatMessage(role="assistant", text="First response")]), - ChatResponse(messages=[ChatMessage(role="assistant", text="Second response")]), + ChatResponse(messages=[ChatMessage("assistant", ["First response"])]), + ChatResponse(messages=[ChatMessage("assistant", ["Second response"])]), ] sub_agent = ChatAgent( @@ -327,7 +327,7 @@ async def capture_middleware( # Setup mock response chat_client.responses = [ - ChatResponse(messages=[ChatMessage(role="assistant", text="Response from sub-agent")]), + ChatResponse(messages=[ChatMessage("assistant", ["Response from sub-agent"])]), ] sub_agent = ChatAgent( diff --git a/python/packages/core/tests/core/test_clients.py b/python/packages/core/tests/core/test_clients.py index 67ecd54a8d..c151451227 100644 --- a/python/packages/core/tests/core/test_clients.py +++ b/python/packages/core/tests/core/test_clients.py @@ -7,7 +7,6 @@ BaseChatClient, ChatClientProtocol, ChatMessage, - Role, ) @@ -16,15 +15,15 @@ def test_chat_client_type(chat_client: ChatClientProtocol): async def test_chat_client_get_response(chat_client: ChatClientProtocol): - response = await chat_client.get_response(ChatMessage(role="user", text="Hello")) + response = await chat_client.get_response(ChatMessage("user", ["Hello"])) assert response.text == "test response" - assert response.messages[0].role == Role.ASSISTANT + assert response.messages[0].role == "assistant" async def test_chat_client_get_streaming_response(chat_client: ChatClientProtocol): - async for update in chat_client.get_streaming_response(ChatMessage(role="user", text="Hello")): + async for update in chat_client.get_streaming_response(ChatMessage("user", ["Hello"])): assert update.text == "test streaming response " or update.text == "another update" - assert update.role == Role.ASSISTANT + assert update.role == "assistant" def test_base_client(chat_client_base: ChatClientProtocol): @@ -33,13 +32,13 @@ def test_base_client(chat_client_base: ChatClientProtocol): async def test_base_client_get_response(chat_client_base: ChatClientProtocol): - response = await chat_client_base.get_response(ChatMessage(role="user", text="Hello")) - assert response.messages[0].role == Role.ASSISTANT + response = await chat_client_base.get_response(ChatMessage("user", ["Hello"])) + assert response.messages[0].role == "assistant" assert response.messages[0].text == "test response - Hello" async def test_base_client_get_streaming_response(chat_client_base: ChatClientProtocol): - async for update in chat_client_base.get_streaming_response(ChatMessage(role="user", text="Hello")): + async for update in chat_client_base.get_streaming_response(ChatMessage("user", ["Hello"])): assert update.text == "update - Hello" or update.text == "another update" @@ -54,17 +53,17 @@ async def test_chat_client_instructions_handling(chat_client_base: ChatClientPro _, kwargs = mock_inner_get_response.call_args messages = kwargs.get("messages", []) assert len(messages) == 1 - assert messages[0].role == Role.USER + assert messages[0].role == "user" assert messages[0].text == "hello" from agent_framework._types import prepend_instructions_to_messages appended_messages = prepend_instructions_to_messages( - [ChatMessage(role=Role.USER, text="hello")], + [ChatMessage("user", ["hello"])], instructions, ) assert len(appended_messages) == 2 - assert appended_messages[0].role == Role.SYSTEM + assert appended_messages[0].role == "system" assert appended_messages[0].text == "You are a helpful assistant." - assert appended_messages[1].role == Role.USER + assert appended_messages[1].role == "user" assert appended_messages[1].text == "hello" diff --git a/python/packages/core/tests/core/test_function_invocation_logic.py b/python/packages/core/tests/core/test_function_invocation_logic.py index 720d5a31d7..8d89c63bb7 100644 --- a/python/packages/core/tests/core/test_function_invocation_logic.py +++ b/python/packages/core/tests/core/test_function_invocation_logic.py @@ -13,7 +13,6 @@ ChatResponse, ChatResponseUpdate, Content, - Role, tool, ) from agent_framework._middleware import FunctionInvocationContext, FunctionMiddleware @@ -37,21 +36,21 @@ def ai_func(arg1: str) -> str: ], ) ), - ChatResponse(messages=ChatMessage(role="assistant", text="done")), + ChatResponse(messages=ChatMessage("assistant", ["done"])), ] response = await chat_client_base.get_response("hello", options={"tool_choice": "auto", "tools": [ai_func]}) assert exec_counter == 1 assert len(response.messages) == 3 - assert response.messages[0].role == Role.ASSISTANT + assert response.messages[0].role == "assistant" assert response.messages[0].contents[0].type == "function_call" assert response.messages[0].contents[0].name == "test_function" assert response.messages[0].contents[0].arguments == '{"arg1": "value1"}' assert response.messages[0].contents[0].call_id == "1" - assert response.messages[1].role == Role.TOOL + assert response.messages[1].role == "tool" assert response.messages[1].contents[0].type == "function_result" assert response.messages[1].contents[0].call_id == "1" assert response.messages[1].contents[0].result == "Processed value1" - assert response.messages[2].role == Role.ASSISTANT + assert response.messages[2].role == "assistant" assert response.messages[2].text == "done" @@ -81,16 +80,16 @@ def ai_func(arg1: str) -> str: ], ) ), - ChatResponse(messages=ChatMessage(role="assistant", text="done")), + ChatResponse(messages=ChatMessage("assistant", ["done"])), ] response = await chat_client_base.get_response("hello", options={"tool_choice": "auto", "tools": [ai_func]}) assert exec_counter == 2 assert len(response.messages) == 5 - assert response.messages[0].role == Role.ASSISTANT - assert response.messages[1].role == Role.TOOL - assert response.messages[2].role == Role.ASSISTANT - assert response.messages[3].role == Role.TOOL - assert response.messages[4].role == Role.ASSISTANT + assert response.messages[0].role == "assistant" + assert response.messages[1].role == "tool" + assert response.messages[2].role == "assistant" + assert response.messages[3].role == "tool" + assert response.messages[4].role == "assistant" assert response.messages[0].contents[0].type == "function_call" assert response.messages[1].contents[0].type == "function_result" assert response.messages[2].contents[0].type == "function_call" @@ -162,7 +161,7 @@ def ai_func(user_query: str) -> str: ], ) ), - ChatResponse(messages=ChatMessage(role="assistant", text="done")), + ChatResponse(messages=ChatMessage("assistant", ["done"])), ] agent = ChatAgent(chat_client=chat_client_base, tools=[ai_func]) @@ -219,7 +218,7 @@ def ai_func(user_query: str) -> str: ], ) ), - ChatResponse(messages=ChatMessage(role="assistant", text="done")), + ChatResponse(messages=ChatMessage("assistant", ["done"])), ] agent = ChatAgent(chat_client=chat_client_base, tools=[ai_func]) @@ -339,11 +338,11 @@ def func_with_approval(arg1: str) -> str: # Single function call content func_call = Content.from_function_call(call_id="1", name=function_name, arguments='{"arg1": "value1"}') - completion = ChatMessage(role="assistant", text="done") + completion = ChatMessage("assistant", ["done"]) - chat_client_base.run_responses = [ - ChatResponse(messages=ChatMessage(role="assistant", contents=[func_call])) - ] + ([] if approval_required else [ChatResponse(messages=completion)]) + chat_client_base.run_responses = [ChatResponse(messages=ChatMessage("assistant", [func_call]))] + ( + [] if approval_required else [ChatResponse(messages=completion)] + ) chat_client_base.streaming_responses = [ [ @@ -371,7 +370,7 @@ def func_with_approval(arg1: str) -> str: Content.from_function_call(call_id="2", name="approval_func", arguments='{"arg1": "value2"}'), ] - chat_client_base.run_responses = [ChatResponse(messages=ChatMessage(role="assistant", contents=func_calls))] + chat_client_base.run_responses = [ChatResponse(messages=ChatMessage("assistant", func_calls))] chat_client_base.streaming_responses = [ [ @@ -432,7 +431,7 @@ def func_with_approval(arg1: str) -> str: assert messages[0].contents[0].type == "function_call" assert messages[1].contents[0].type == "function_result" assert messages[1].contents[0].result == "Processed value1" - assert messages[2].role == Role.ASSISTANT + assert messages[2].role == "assistant" assert messages[2].text == "done" assert exec_counter == 1 else: @@ -497,7 +496,7 @@ def func_rejected(arg1: str) -> str: ], ) ), - ChatResponse(messages=ChatMessage(role="assistant", text="done")), + ChatResponse(messages=ChatMessage("assistant", ["done"])), ] # Get the response with approval requests @@ -527,7 +526,7 @@ def func_rejected(arg1: str) -> str: ) # Continue conversation with one approved and one rejected - all_messages = response.messages + [ChatMessage(role="user", contents=[approved_response, rejected_response])] + all_messages = response.messages + [ChatMessage("user", [approved_response, rejected_response])] # Call get_response which will process the approvals await chat_client_base.get_response( @@ -561,9 +560,7 @@ def func_rejected(arg1: str) -> str: for msg in all_messages: for content in msg.contents: if content.type == "function_result": - assert msg.role == Role.TOOL, ( - f"Message with FunctionResultContent must have role='tool', got '{msg.role}'" - ) + assert msg.role == "tool", f"Message with FunctionResultContent must have role='tool', got '{msg.role}'" async def test_approval_requests_in_assistant_message(chat_client_base: ChatClientProtocol): @@ -593,7 +590,7 @@ def func_with_approval(arg1: str) -> str: # Should have one assistant message containing both the call and approval request assert len(response.messages) == 1 - assert response.messages[0].role == Role.ASSISTANT + assert response.messages[0].role == "assistant" assert len(response.messages[0].contents) == 2 assert response.messages[0].contents[0].type == "function_call" assert response.messages[0].contents[1].type == "function_approval_request" @@ -620,7 +617,7 @@ def func_with_approval(arg1: str) -> str: ], ) ), - ChatResponse(messages=ChatMessage(role="assistant", text="done")), + ChatResponse(messages=ChatMessage("assistant", ["done"])), ] # Get approval request @@ -630,7 +627,7 @@ def func_with_approval(arg1: str) -> str: # Store messages (like a thread would) persisted_messages = [ - ChatMessage(role="user", contents=[Content.from_text(text="hello")]), + ChatMessage("user", [Content.from_text(text="hello")]), *response1.messages, ] @@ -641,7 +638,7 @@ def func_with_approval(arg1: str) -> str: function_call=approval_req.function_call, approved=True, ) - persisted_messages.append(ChatMessage(role="user", contents=[approval_response])) + persisted_messages.append(ChatMessage("user", [approval_response])) # Continue with all persisted messages response2 = await chat_client_base.get_response( @@ -670,7 +667,7 @@ def func_with_approval(arg1: str) -> str: ], ) ), - ChatResponse(messages=ChatMessage(role="assistant", text="done")), + ChatResponse(messages=ChatMessage("assistant", ["done"])), ] response1 = await chat_client_base.get_response( @@ -684,7 +681,7 @@ def func_with_approval(arg1: str) -> str: approved=True, ) - all_messages = response1.messages + [ChatMessage(role="user", contents=[approval_response])] + all_messages = response1.messages + [ChatMessage("user", [approval_response])] await chat_client_base.get_response(all_messages, options={"tool_choice": "auto", "tools": [func_with_approval]}) # Count function calls with the same call_id @@ -714,7 +711,7 @@ def func_with_approval(arg1: str) -> str: ], ) ), - ChatResponse(messages=ChatMessage(role="assistant", text="done")), + ChatResponse(messages=ChatMessage("assistant", ["done"])), ] response1 = await chat_client_base.get_response( @@ -728,7 +725,7 @@ def func_with_approval(arg1: str) -> str: approved=False, ) - all_messages = response1.messages + [ChatMessage(role="user", contents=[rejection_response])] + all_messages = response1.messages + [ChatMessage("user", [rejection_response])] await chat_client_base.get_response(all_messages, options={"tool_choice": "auto", "tools": [func_with_approval]}) # Find the rejection result @@ -771,7 +768,7 @@ def ai_func(arg1: str) -> str: ) ), # Failsafe response when tool_choice is set to "none" - ChatResponse(messages=ChatMessage(role="assistant", text="giving up on tools")), + ChatResponse(messages=ChatMessage("assistant", ["giving up on tools"])), ] # Set max_iterations to 1 in additional_properties @@ -798,7 +795,7 @@ def ai_func(arg1: str) -> str: return f"Processed {arg1}" chat_client_base.run_responses = [ - ChatResponse(messages=ChatMessage(role="assistant", text="response without function calling")), + ChatResponse(messages=ChatMessage("assistant", ["response without function calling"])), ] # Disable function invocation @@ -853,7 +850,7 @@ def error_func(arg1: str) -> str: ], ) ), - ChatResponse(messages=ChatMessage(role="assistant", text="final response")), + ChatResponse(messages=ChatMessage("assistant", ["final response"])), ] # Set max_consecutive_errors to 2 @@ -898,7 +895,7 @@ def known_func(arg1: str) -> str: ], ) ), - ChatResponse(messages=ChatMessage(role="assistant", text="done")), + ChatResponse(messages=ChatMessage("assistant", ["done"])), ] # Set terminate_on_unknown_calls to False (default) @@ -971,7 +968,7 @@ def hidden_func(arg1: str) -> str: ], ) ), - ChatResponse(messages=ChatMessage(role="assistant", text="done")), + ChatResponse(messages=ChatMessage("assistant", ["done"])), ] # Add hidden_func to additional_tools @@ -1010,7 +1007,7 @@ def error_func(arg1: str) -> str: ], ) ), - ChatResponse(messages=ChatMessage(role="assistant", text="done")), + ChatResponse(messages=ChatMessage("assistant", ["done"])), ] # Set include_detailed_errors to False (default) @@ -1044,7 +1041,7 @@ def error_func(arg1: str) -> str: ], ) ), - ChatResponse(messages=ChatMessage(role="assistant", text="done")), + ChatResponse(messages=ChatMessage("assistant", ["done"])), ] # Set include_detailed_errors to True @@ -1114,7 +1111,7 @@ def typed_func(arg1: int) -> str: # Expects int, not str ], ) ), - ChatResponse(messages=ChatMessage(role="assistant", text="done")), + ChatResponse(messages=ChatMessage("assistant", ["done"])), ] # Set include_detailed_errors to True @@ -1148,7 +1145,7 @@ def typed_func(arg1: int) -> str: # Expects int, not str ], ) ), - ChatResponse(messages=ChatMessage(role="assistant", text="done")), + ChatResponse(messages=ChatMessage("assistant", ["done"])), ] # Set include_detailed_errors to False (default) @@ -1184,12 +1181,12 @@ def local_func(arg1: str) -> str: ) chat_client_base.run_responses = [ - ChatResponse(messages=ChatMessage(role="assistant", text="done")), + ChatResponse(messages=ChatMessage("assistant", ["done"])), ] # Send the approval response response = await chat_client_base.get_response( - [ChatMessage(role="user", contents=[approval_response])], + [ChatMessage("user", [approval_response])], tool_choice="auto", tools=[local_func], ) @@ -1215,7 +1212,7 @@ def test_func(arg1: str) -> str: ], ) ), - ChatResponse(messages=ChatMessage(role="assistant", text="done")), + ChatResponse(messages=ChatMessage("assistant", ["done"])), ] # Get approval request @@ -1231,7 +1228,7 @@ def test_func(arg1: str) -> str: ) # Continue conversation with rejection - all_messages = response1.messages + [ChatMessage(role="user", contents=[rejection_response])] + all_messages = response1.messages + [ChatMessage("user", [rejection_response])] # This should handle the rejection gracefully (not raise ToolException to user) await chat_client_base.get_response(all_messages, options={"tool_choice": "auto", "tools": [test_func]}) @@ -1270,7 +1267,7 @@ def error_func(arg1: str) -> str: contents=[Content.from_function_call(call_id="1", name="error_func", arguments='{"arg1": "value1"}')], ) ), - ChatResponse(messages=ChatMessage(role="assistant", text="done")), + ChatResponse(messages=ChatMessage("assistant", ["done"])), ] # Set include_detailed_errors to False (default) @@ -1288,7 +1285,7 @@ def error_func(arg1: str) -> str: approved=True, ) - all_messages = response1.messages + [ChatMessage(role="user", contents=[approval_response])] + all_messages = response1.messages + [ChatMessage("user", [approval_response])] # Execute the approved function (which will error) await chat_client_base.get_response(all_messages, options={"tool_choice": "auto", "tools": [error_func]}) @@ -1333,7 +1330,7 @@ def error_func(arg1: str) -> str: contents=[Content.from_function_call(call_id="1", name="error_func", arguments='{"arg1": "value1"}')], ) ), - ChatResponse(messages=ChatMessage(role="assistant", text="done")), + ChatResponse(messages=ChatMessage("assistant", ["done"])), ] # Set include_detailed_errors to True @@ -1351,7 +1348,7 @@ def error_func(arg1: str) -> str: approved=True, ) - all_messages = response1.messages + [ChatMessage(role="user", contents=[approval_response])] + all_messages = response1.messages + [ChatMessage("user", [approval_response])] # Execute the approved function (which will error) await chat_client_base.get_response(all_messages, options={"tool_choice": "auto", "tools": [error_func]}) @@ -1396,7 +1393,7 @@ def typed_func(arg1: int) -> str: # Expects int, not str ], ) ), - ChatResponse(messages=ChatMessage(role="assistant", text="done")), + ChatResponse(messages=ChatMessage("assistant", ["done"])), ] # Set include_detailed_errors to True to see validation details @@ -1414,7 +1411,7 @@ def typed_func(arg1: int) -> str: # Expects int, not str approved=True, ) - all_messages = response1.messages + [ChatMessage(role="user", contents=[approval_response])] + all_messages = response1.messages + [ChatMessage("user", [approval_response])] # Execute the approved function (which will fail validation) await chat_client_base.get_response(all_messages, options={"tool_choice": "auto", "tools": [typed_func]}) @@ -1455,7 +1452,7 @@ def success_func(arg1: str) -> str: contents=[Content.from_function_call(call_id="1", name="success_func", arguments='{"arg1": "value1"}')], ) ), - ChatResponse(messages=ChatMessage(role="assistant", text="done")), + ChatResponse(messages=ChatMessage("assistant", ["done"])), ] # Get approval request @@ -1470,7 +1467,7 @@ def success_func(arg1: str) -> str: approved=True, ) - all_messages = response1.messages + [ChatMessage(role="user", contents=[approval_response])] + all_messages = response1.messages + [ChatMessage("user", [approval_response])] # Execute the approved function await chat_client_base.get_response(all_messages, options={"tool_choice": "auto", "tools": [success_func]}) @@ -1516,7 +1513,7 @@ async def test_declaration_only_tool(chat_client_base: ChatClientProtocol): ], ) ), - ChatResponse(messages=ChatMessage(role="assistant", text="done")), + ChatResponse(messages=ChatMessage("assistant", ["done"])), ] response = await chat_client_base.get_response( @@ -1572,7 +1569,7 @@ async def func2(arg1: str) -> str: ], ) ), - ChatResponse(messages=ChatMessage(role="assistant", text="done")), + ChatResponse(messages=ChatMessage("assistant", ["done"])), ] response = await chat_client_base.get_response("hello", options={"tool_choice": "auto", "tools": [func1, func2]}) @@ -1608,7 +1605,7 @@ def plain_function(arg1: str) -> str: ], ) ), - ChatResponse(messages=ChatMessage(role="assistant", text="done")), + ChatResponse(messages=ChatMessage("assistant", ["done"])), ] # Pass plain function (will be auto-converted) @@ -1639,7 +1636,7 @@ def test_func(arg1: str) -> str: conversation_id="conv_123", # Simulate service-side thread ), ChatResponse( - messages=ChatMessage(role="assistant", text="done"), + messages=ChatMessage("assistant", ["done"]), conversation_id="conv_123", ), ] @@ -1668,7 +1665,7 @@ def test_func(arg1: str) -> str: ], ) ), - ChatResponse(messages=ChatMessage(role="assistant", text="done")), + ChatResponse(messages=ChatMessage("assistant", ["done"])), ] response = await chat_client_base.get_response("hello", options={"tool_choice": "auto", "tools": [test_func]}) @@ -1712,7 +1709,7 @@ def sometimes_fails(arg1: str) -> str: ], ) ), - ChatResponse(messages=ChatMessage(role="assistant", text="done")), + ChatResponse(messages=ChatMessage("assistant", ["done"])), ] response = await chat_client_base.get_response("hello", options={"tool_choice": "auto", "tools": [sometimes_fails]}) @@ -2324,7 +2321,7 @@ def ai_func(arg1: str) -> str: ], ) ), - ChatResponse(messages=ChatMessage(role="assistant", text="done")), + ChatResponse(messages=ChatMessage("assistant", ["done"])), ] response = await chat_client_base.get_response( @@ -2339,9 +2336,9 @@ def ai_func(arg1: str) -> str: # There should be 2 messages: assistant with function call, tool result from middleware # The loop should NOT have continued to call the LLM again assert len(response.messages) == 2 - assert response.messages[0].role == Role.ASSISTANT + assert response.messages[0].role == "assistant" assert response.messages[0].contents[0].type == "function_call" - assert response.messages[1].role == Role.TOOL + assert response.messages[1].role == "tool" assert response.messages[1].contents[0].type == "function_result" assert response.messages[1].contents[0].result == "terminated by middleware" @@ -2393,7 +2390,7 @@ def terminating_func(arg1: str) -> str: ], ) ), - ChatResponse(messages=ChatMessage(role="assistant", text="done")), + ChatResponse(messages=ChatMessage("assistant", ["done"])), ] response = await chat_client_base.get_response( @@ -2410,9 +2407,9 @@ def terminating_func(arg1: str) -> str: # There should be 2 messages: assistant with function calls, tool results # The loop should NOT have continued to call the LLM again assert len(response.messages) == 2 - assert response.messages[0].role == Role.ASSISTANT + assert response.messages[0].role == "assistant" assert len(response.messages[0].contents) == 2 - assert response.messages[1].role == Role.TOOL + assert response.messages[1].role == "tool" # Both function results should be present assert len(response.messages[1].contents) == 2 diff --git a/python/packages/core/tests/core/test_kwargs_propagation_to_ai_function.py b/python/packages/core/tests/core/test_kwargs_propagation_to_ai_function.py index 34798a4a16..18e60c383c 100644 --- a/python/packages/core/tests/core/test_kwargs_propagation_to_ai_function.py +++ b/python/packages/core/tests/core/test_kwargs_propagation_to_ai_function.py @@ -49,7 +49,7 @@ async def mock_get_response(self, messages, **kwargs): ] ) # Second call: return final response - return ChatResponse(messages=[ChatMessage(role="assistant", text="Done!")]) + return ChatResponse(messages=[ChatMessage("assistant", ["Done!"])]) # Wrap the function with function invocation decorator wrapped = _handle_function_calls_response(mock_get_response) @@ -101,7 +101,7 @@ async def mock_get_response(self, messages, **kwargs): ) ] ) - return ChatResponse(messages=[ChatMessage(role="assistant", text="Completed!")]) + return ChatResponse(messages=[ChatMessage("assistant", ["Completed!"])]) wrapped = _handle_function_calls_response(mock_get_response) @@ -149,7 +149,7 @@ async def mock_get_response(self, messages, **kwargs): ) ] ) - return ChatResponse(messages=[ChatMessage(role="assistant", text="All done!")]) + return ChatResponse(messages=[ChatMessage("assistant", ["All done!"])]) wrapped = _handle_function_calls_response(mock_get_response) @@ -196,13 +196,10 @@ async def mock_get_streaming_response(self, messages, **kwargs): arguments='{"value": "streaming-test"}', ) ], - is_finished=True, ) else: # Second call: return final response - yield ChatResponseUpdate( - text=Content.from_text(text="Stream complete!"), role="assistant", is_finished=True - ) + yield ChatResponseUpdate(contents=[Content.from_text(text="Stream complete!")], role="assistant") wrapped = _handle_function_calls_streaming_response(mock_get_streaming_response) diff --git a/python/packages/core/tests/core/test_mcp.py b/python/packages/core/tests/core/test_mcp.py index f6d2b535d8..7695affb5a 100644 --- a/python/packages/core/tests/core/test_mcp.py +++ b/python/packages/core/tests/core/test_mcp.py @@ -18,7 +18,6 @@ MCPStdioTool, MCPStreamableHTTPTool, MCPWebsocketTool, - Role, ToolProtocol, ) from agent_framework._mcp import ( @@ -63,7 +62,7 @@ def test_mcp_prompt_message_to_ai_content(): ai_content = _parse_message_from_mcp(mcp_message) assert isinstance(ai_content, ChatMessage) - assert ai_content.role.value == "user" + assert ai_content.role == "user" assert len(ai_content.contents) == 1 assert ai_content.contents[0].type == "text" assert ai_content.contents[0].text == "Hello, world!" @@ -1056,7 +1055,7 @@ def get_mcp_client(self) -> _AsyncGeneratorContextManager[Any, None]: assert len(result) == 1 assert isinstance(result[0], ChatMessage) - assert result[0].role == Role.USER + assert result[0].role == "user" assert len(result[0].contents) == 1 assert result[0].contents[0].text == "Test message" @@ -1414,7 +1413,7 @@ async def test_mcp_tool_sampling_callback_chat_client_exception(): async def test_mcp_tool_sampling_callback_no_valid_content(): """Test sampling callback when response has no valid content types.""" - from agent_framework import ChatMessage, Role + from agent_framework import ChatMessage tool = MCPStdioTool(name="test_tool", command="python") @@ -1423,7 +1422,7 @@ async def test_mcp_tool_sampling_callback_no_valid_content(): mock_response = Mock() mock_response.messages = [ ChatMessage( - role=Role.ASSISTANT, + role="assistant", contents=[ Content.from_uri( uri="data:application/json;base64,e30K", diff --git a/python/packages/core/tests/core/test_memory.py b/python/packages/core/tests/core/test_memory.py index bcc299ed37..78b48afd87 100644 --- a/python/packages/core/tests/core/test_memory.py +++ b/python/packages/core/tests/core/test_memory.py @@ -4,7 +4,7 @@ from collections.abc import MutableSequence from typing import Any -from agent_framework import ChatMessage, Role +from agent_framework import ChatMessage from agent_framework._memory import Context, ContextProvider @@ -69,7 +69,7 @@ def test_context_default_values(self) -> None: def test_context_with_values(self) -> None: """Test Context can be initialized with values.""" - messages = [ChatMessage(role=Role.USER, text="Test message")] + messages = [ChatMessage("user", ["Test message"])] context = Context(instructions="Test instructions", messages=messages) assert context.instructions == "Test instructions" assert len(context.messages) == 1 @@ -89,15 +89,15 @@ async def test_thread_created(self) -> None: async def test_invoked(self) -> None: """Test invoked is called.""" provider = MockContextProvider() - message = ChatMessage(role=Role.USER, text="Test message") + message = ChatMessage("user", ["Test message"]) await provider.invoked(message) assert provider.invoked_called assert provider.new_messages == message async def test_invoking(self) -> None: """Test invoking is called and returns context.""" - provider = MockContextProvider(messages=[ChatMessage(role=Role.USER, text="Context message")]) - message = ChatMessage(role=Role.USER, text="Test message") + provider = MockContextProvider(messages=[ChatMessage("user", ["Context message"])]) + message = ChatMessage("user", ["Test message"]) context = await provider.invoking(message) assert provider.invoking_called assert provider.model_invoking_messages == message @@ -114,7 +114,7 @@ async def test_base_thread_created_does_nothing(self) -> None: async def test_base_invoked_does_nothing(self) -> None: """Test that base ContextProvider.invoked does nothing by default.""" provider = MinimalContextProvider() - message = ChatMessage(role=Role.USER, text="Test") + message = ChatMessage("user", ["Test"]) await provider.invoked(message) await provider.invoked(message, response_messages=message) await provider.invoked(message, invoke_exception=Exception("test")) diff --git a/python/packages/core/tests/core/test_middleware.py b/python/packages/core/tests/core/test_middleware.py index a62cca2c76..b0536ac94c 100644 --- a/python/packages/core/tests/core/test_middleware.py +++ b/python/packages/core/tests/core/test_middleware.py @@ -15,7 +15,6 @@ ChatResponse, ChatResponseUpdate, Content, - Role, ) from agent_framework._middleware import ( AgentMiddleware, @@ -36,7 +35,7 @@ class TestAgentRunContext: def test_init_with_defaults(self, mock_agent: AgentProtocol) -> None: """Test AgentRunContext initialization with default values.""" - messages = [ChatMessage(role=Role.USER, text="test")] + messages = [ChatMessage("user", ["test"])] context = AgentRunContext(agent=mock_agent, messages=messages) assert context.agent is mock_agent @@ -46,7 +45,7 @@ def test_init_with_defaults(self, mock_agent: AgentProtocol) -> None: def test_init_with_custom_values(self, mock_agent: AgentProtocol) -> None: """Test AgentRunContext initialization with custom values.""" - messages = [ChatMessage(role=Role.USER, text="test")] + messages = [ChatMessage("user", ["test"])] metadata = {"key": "value"} context = AgentRunContext(agent=mock_agent, messages=messages, is_streaming=True, metadata=metadata) @@ -59,7 +58,7 @@ def test_init_with_thread(self, mock_agent: AgentProtocol) -> None: """Test AgentRunContext initialization with thread parameter.""" from agent_framework import AgentThread - messages = [ChatMessage(role=Role.USER, text="test")] + messages = [ChatMessage("user", ["test"])] thread = AgentThread() context = AgentRunContext(agent=mock_agent, messages=messages, thread=thread) @@ -98,7 +97,7 @@ class TestChatContext: def test_init_with_defaults(self, mock_chat_client: Any) -> None: """Test ChatContext initialization with default values.""" - messages = [ChatMessage(role=Role.USER, text="test")] + messages = [ChatMessage("user", ["test"])] chat_options: dict[str, Any] = {} context = ChatContext(chat_client=mock_chat_client, messages=messages, options=chat_options) @@ -112,7 +111,7 @@ def test_init_with_defaults(self, mock_chat_client: Any) -> None: def test_init_with_custom_values(self, mock_chat_client: Any) -> None: """Test ChatContext initialization with custom values.""" - messages = [ChatMessage(role=Role.USER, text="test")] + messages = [ChatMessage("user", ["test"])] chat_options: dict[str, Any] = {"temperature": 0.5} metadata = {"key": "value"} @@ -169,10 +168,10 @@ async def test_middleware(context: AgentRunContext, next: Callable[[AgentRunCont async def test_execute_no_middleware(self, mock_agent: AgentProtocol) -> None: """Test pipeline execution with no middleware.""" pipeline = AgentMiddlewarePipeline() - messages = [ChatMessage(role=Role.USER, text="test")] + messages = [ChatMessage("user", ["test"])] context = AgentRunContext(agent=mock_agent, messages=messages) - expected_response = AgentResponse(messages=[ChatMessage(role=Role.ASSISTANT, text="response")]) + expected_response = AgentResponse(messages=[ChatMessage("assistant", ["response"])]) async def final_handler(ctx: AgentRunContext) -> AgentResponse: return expected_response @@ -197,10 +196,10 @@ async def process( middleware = OrderTrackingMiddleware("test") pipeline = AgentMiddlewarePipeline([middleware]) - messages = [ChatMessage(role=Role.USER, text="test")] + messages = [ChatMessage("user", ["test"])] context = AgentRunContext(agent=mock_agent, messages=messages) - expected_response = AgentResponse(messages=[ChatMessage(role=Role.ASSISTANT, text="response")]) + expected_response = AgentResponse(messages=[ChatMessage("assistant", ["response"])]) async def final_handler(ctx: AgentRunContext) -> AgentResponse: execution_order.append("handler") @@ -213,7 +212,7 @@ async def final_handler(ctx: AgentRunContext) -> AgentResponse: async def test_execute_stream_no_middleware(self, mock_agent: AgentProtocol) -> None: """Test pipeline streaming execution with no middleware.""" pipeline = AgentMiddlewarePipeline() - messages = [ChatMessage(role=Role.USER, text="test")] + messages = [ChatMessage("user", ["test"])] context = AgentRunContext(agent=mock_agent, messages=messages) async def final_handler(ctx: AgentRunContext) -> AsyncIterable[AgentResponseUpdate]: @@ -245,7 +244,7 @@ async def process( middleware = StreamOrderTrackingMiddleware("test") pipeline = AgentMiddlewarePipeline([middleware]) - messages = [ChatMessage(role=Role.USER, text="test")] + messages = [ChatMessage("user", ["test"])] context = AgentRunContext(agent=mock_agent, messages=messages) async def final_handler(ctx: AgentRunContext) -> AsyncIterable[AgentResponseUpdate]: @@ -267,14 +266,14 @@ async def test_execute_with_pre_next_termination(self, mock_agent: AgentProtocol """Test pipeline execution with termination before next().""" middleware = self.PreNextTerminateMiddleware() pipeline = AgentMiddlewarePipeline([middleware]) - messages = [ChatMessage(role=Role.USER, text="test")] + messages = [ChatMessage("user", ["test"])] context = AgentRunContext(agent=mock_agent, messages=messages) execution_order: list[str] = [] async def final_handler(ctx: AgentRunContext) -> AgentResponse: # Handler should not be executed when terminated before next() execution_order.append("handler") - return AgentResponse(messages=[ChatMessage(role=Role.ASSISTANT, text="response")]) + return AgentResponse(messages=[ChatMessage("assistant", ["response"])]) response = await pipeline.execute(mock_agent, messages, context, final_handler) assert response is not None @@ -287,13 +286,13 @@ async def test_execute_with_post_next_termination(self, mock_agent: AgentProtoco """Test pipeline execution with termination after next().""" middleware = self.PostNextTerminateMiddleware() pipeline = AgentMiddlewarePipeline([middleware]) - messages = [ChatMessage(role=Role.USER, text="test")] + messages = [ChatMessage("user", ["test"])] context = AgentRunContext(agent=mock_agent, messages=messages) execution_order: list[str] = [] async def final_handler(ctx: AgentRunContext) -> AgentResponse: execution_order.append("handler") - return AgentResponse(messages=[ChatMessage(role=Role.ASSISTANT, text="response")]) + return AgentResponse(messages=[ChatMessage("assistant", ["response"])]) response = await pipeline.execute(mock_agent, messages, context, final_handler) assert response is not None @@ -306,7 +305,7 @@ async def test_execute_stream_with_pre_next_termination(self, mock_agent: AgentP """Test pipeline streaming execution with termination before next().""" middleware = self.PreNextTerminateMiddleware() pipeline = AgentMiddlewarePipeline([middleware]) - messages = [ChatMessage(role=Role.USER, text="test")] + messages = [ChatMessage("user", ["test"])] context = AgentRunContext(agent=mock_agent, messages=messages) execution_order: list[str] = [] @@ -330,7 +329,7 @@ async def test_execute_stream_with_post_next_termination(self, mock_agent: Agent """Test pipeline streaming execution with termination after next().""" middleware = self.PostNextTerminateMiddleware() pipeline = AgentMiddlewarePipeline([middleware]) - messages = [ChatMessage(role=Role.USER, text="test")] + messages = [ChatMessage("user", ["test"])] context = AgentRunContext(agent=mock_agent, messages=messages) execution_order: list[str] = [] @@ -366,11 +365,11 @@ async def process( middleware = ThreadCapturingMiddleware() pipeline = AgentMiddlewarePipeline([middleware]) - messages = [ChatMessage(role=Role.USER, text="test")] + messages = [ChatMessage("user", ["test"])] thread = AgentThread() context = AgentRunContext(agent=mock_agent, messages=messages, thread=thread) - expected_response = AgentResponse(messages=[ChatMessage(role=Role.ASSISTANT, text="response")]) + expected_response = AgentResponse(messages=[ChatMessage("assistant", ["response"])]) async def final_handler(ctx: AgentRunContext) -> AgentResponse: return expected_response @@ -393,10 +392,10 @@ async def process( middleware = ThreadCapturingMiddleware() pipeline = AgentMiddlewarePipeline([middleware]) - messages = [ChatMessage(role=Role.USER, text="test")] + messages = [ChatMessage("user", ["test"])] context = AgentRunContext(agent=mock_agent, messages=messages, thread=None) - expected_response = AgentResponse(messages=[ChatMessage(role=Role.ASSISTANT, text="response")]) + expected_response = AgentResponse(messages=[ChatMessage("assistant", ["response"])]) async def final_handler(ctx: AgentRunContext) -> AgentResponse: return expected_response @@ -560,11 +559,11 @@ async def test_middleware(context: ChatContext, next: Callable[[ChatContext], Aw async def test_execute_no_middleware(self, mock_chat_client: Any) -> None: """Test pipeline execution with no middleware.""" pipeline = ChatMiddlewarePipeline() - messages = [ChatMessage(role=Role.USER, text="test")] + messages = [ChatMessage("user", ["test"])] chat_options: dict[str, Any] = {} context = ChatContext(chat_client=mock_chat_client, messages=messages, options=chat_options) - expected_response = ChatResponse(messages=[ChatMessage(role=Role.ASSISTANT, text="response")]) + expected_response = ChatResponse(messages=[ChatMessage("assistant", ["response"])]) async def final_handler(ctx: ChatContext) -> ChatResponse: return expected_response @@ -587,11 +586,11 @@ async def process(self, context: ChatContext, next: Callable[[ChatContext], Awai middleware = OrderTrackingChatMiddleware("test") pipeline = ChatMiddlewarePipeline([middleware]) - messages = [ChatMessage(role=Role.USER, text="test")] + messages = [ChatMessage("user", ["test"])] chat_options: dict[str, Any] = {} context = ChatContext(chat_client=mock_chat_client, messages=messages, options=chat_options) - expected_response = ChatResponse(messages=[ChatMessage(role=Role.ASSISTANT, text="response")]) + expected_response = ChatResponse(messages=[ChatMessage("assistant", ["response"])]) async def final_handler(ctx: ChatContext) -> ChatResponse: execution_order.append("handler") @@ -604,7 +603,7 @@ async def final_handler(ctx: ChatContext) -> ChatResponse: async def test_execute_stream_no_middleware(self, mock_chat_client: Any) -> None: """Test pipeline streaming execution with no middleware.""" pipeline = ChatMiddlewarePipeline() - messages = [ChatMessage(role=Role.USER, text="test")] + messages = [ChatMessage("user", ["test"])] chat_options: dict[str, Any] = {} context = ChatContext(chat_client=mock_chat_client, messages=messages, options=chat_options) @@ -635,7 +634,7 @@ async def process(self, context: ChatContext, next: Callable[[ChatContext], Awai middleware = StreamOrderTrackingChatMiddleware("test") pipeline = ChatMiddlewarePipeline([middleware]) - messages = [ChatMessage(role=Role.USER, text="test")] + messages = [ChatMessage("user", ["test"])] chat_options: dict[str, Any] = {} context = ChatContext(chat_client=mock_chat_client, messages=messages, options=chat_options, is_streaming=True) @@ -658,7 +657,7 @@ async def test_execute_with_pre_next_termination(self, mock_chat_client: Any) -> """Test pipeline execution with termination before next().""" middleware = self.PreNextTerminateChatMiddleware() pipeline = ChatMiddlewarePipeline([middleware]) - messages = [ChatMessage(role=Role.USER, text="test")] + messages = [ChatMessage("user", ["test"])] chat_options: dict[str, Any] = {} context = ChatContext(chat_client=mock_chat_client, messages=messages, options=chat_options) execution_order: list[str] = [] @@ -666,7 +665,7 @@ async def test_execute_with_pre_next_termination(self, mock_chat_client: Any) -> async def final_handler(ctx: ChatContext) -> ChatResponse: # Handler should not be executed when terminated before next() execution_order.append("handler") - return ChatResponse(messages=[ChatMessage(role=Role.ASSISTANT, text="response")]) + return ChatResponse(messages=[ChatMessage("assistant", ["response"])]) response = await pipeline.execute(mock_chat_client, messages, chat_options, context, final_handler) assert response is None @@ -678,14 +677,14 @@ async def test_execute_with_post_next_termination(self, mock_chat_client: Any) - """Test pipeline execution with termination after next().""" middleware = self.PostNextTerminateChatMiddleware() pipeline = ChatMiddlewarePipeline([middleware]) - messages = [ChatMessage(role=Role.USER, text="test")] + messages = [ChatMessage("user", ["test"])] chat_options: dict[str, Any] = {} context = ChatContext(chat_client=mock_chat_client, messages=messages, options=chat_options) execution_order: list[str] = [] async def final_handler(ctx: ChatContext) -> ChatResponse: execution_order.append("handler") - return ChatResponse(messages=[ChatMessage(role=Role.ASSISTANT, text="response")]) + return ChatResponse(messages=[ChatMessage("assistant", ["response"])]) response = await pipeline.execute(mock_chat_client, messages, chat_options, context, final_handler) assert response is not None @@ -698,7 +697,7 @@ async def test_execute_stream_with_pre_next_termination(self, mock_chat_client: """Test pipeline streaming execution with termination before next().""" middleware = self.PreNextTerminateChatMiddleware() pipeline = ChatMiddlewarePipeline([middleware]) - messages = [ChatMessage(role=Role.USER, text="test")] + messages = [ChatMessage("user", ["test"])] chat_options: dict[str, Any] = {} context = ChatContext(chat_client=mock_chat_client, messages=messages, options=chat_options, is_streaming=True) execution_order: list[str] = [] @@ -723,7 +722,7 @@ async def test_execute_stream_with_post_next_termination(self, mock_chat_client: """Test pipeline streaming execution with termination after next().""" middleware = self.PostNextTerminateChatMiddleware() pipeline = ChatMiddlewarePipeline([middleware]) - messages = [ChatMessage(role=Role.USER, text="test")] + messages = [ChatMessage("user", ["test"])] chat_options: dict[str, Any] = {} context = ChatContext(chat_client=mock_chat_client, messages=messages, options=chat_options, is_streaming=True) execution_order: list[str] = [] @@ -764,12 +763,12 @@ async def process( middleware = MetadataAgentMiddleware() pipeline = AgentMiddlewarePipeline([middleware]) - messages = [ChatMessage(role=Role.USER, text="test")] + messages = [ChatMessage("user", ["test"])] context = AgentRunContext(agent=mock_agent, messages=messages) async def final_handler(ctx: AgentRunContext) -> AgentResponse: metadata_updates.append("handler") - return AgentResponse(messages=[ChatMessage(role=Role.ASSISTANT, text="response")]) + return AgentResponse(messages=[ChatMessage("assistant", ["response"])]) result = await pipeline.execute(mock_agent, messages, context, final_handler) @@ -827,12 +826,12 @@ async def test_agent_middleware( execution_order.append("function_after") pipeline = AgentMiddlewarePipeline([test_agent_middleware]) - messages = [ChatMessage(role=Role.USER, text="test")] + messages = [ChatMessage("user", ["test"])] context = AgentRunContext(agent=mock_agent, messages=messages) async def final_handler(ctx: AgentRunContext) -> AgentResponse: execution_order.append("handler") - return AgentResponse(messages=[ChatMessage(role=Role.ASSISTANT, text="response")]) + return AgentResponse(messages=[ChatMessage("assistant", ["response"])]) result = await pipeline.execute(mock_agent, messages, context, final_handler) @@ -890,12 +889,12 @@ async def function_middleware( execution_order.append("function_after") pipeline = AgentMiddlewarePipeline([ClassMiddleware(), function_middleware]) - messages = [ChatMessage(role=Role.USER, text="test")] + messages = [ChatMessage("user", ["test"])] context = AgentRunContext(agent=mock_agent, messages=messages) async def final_handler(ctx: AgentRunContext) -> AgentResponse: execution_order.append("handler") - return AgentResponse(messages=[ChatMessage(role=Role.ASSISTANT, text="response")]) + return AgentResponse(messages=[ChatMessage("assistant", ["response"])]) result = await pipeline.execute(mock_agent, messages, context, final_handler) @@ -954,13 +953,13 @@ async def function_chat_middleware( execution_order.append("function_after") pipeline = ChatMiddlewarePipeline([ClassChatMiddleware(), function_chat_middleware]) - messages = [ChatMessage(role=Role.USER, text="test")] + messages = [ChatMessage("user", ["test"])] chat_options: dict[str, Any] = {} context = ChatContext(chat_client=mock_chat_client, messages=messages, options=chat_options) async def final_handler(ctx: ChatContext) -> ChatResponse: execution_order.append("handler") - return ChatResponse(messages=[ChatMessage(role=Role.ASSISTANT, text="response")]) + return ChatResponse(messages=[ChatMessage("assistant", ["response"])]) result = await pipeline.execute(mock_chat_client, messages, chat_options, context, final_handler) @@ -1001,12 +1000,12 @@ async def process( middleware = [FirstMiddleware(), SecondMiddleware(), ThirdMiddleware()] pipeline = AgentMiddlewarePipeline(middleware) # type: ignore - messages = [ChatMessage(role=Role.USER, text="test")] + messages = [ChatMessage("user", ["test"])] context = AgentRunContext(agent=mock_agent, messages=messages) async def final_handler(ctx: AgentRunContext) -> AgentResponse: execution_order.append("handler") - return AgentResponse(messages=[ChatMessage(role=Role.ASSISTANT, text="response")]) + return AgentResponse(messages=[ChatMessage("assistant", ["response"])]) result = await pipeline.execute(mock_agent, messages, context, final_handler) @@ -1085,13 +1084,13 @@ async def process(self, context: ChatContext, next: Callable[[ChatContext], Awai middleware = [FirstChatMiddleware(), SecondChatMiddleware(), ThirdChatMiddleware()] pipeline = ChatMiddlewarePipeline(middleware) # type: ignore - messages = [ChatMessage(role=Role.USER, text="test")] + messages = [ChatMessage("user", ["test"])] chat_options: dict[str, Any] = {} context = ChatContext(chat_client=mock_chat_client, messages=messages, options=chat_options) async def final_handler(ctx: ChatContext) -> ChatResponse: execution_order.append("handler") - return ChatResponse(messages=[ChatMessage(role=Role.ASSISTANT, text="response")]) + return ChatResponse(messages=[ChatMessage("assistant", ["response"])]) result = await pipeline.execute(mock_chat_client, messages, chat_options, context, final_handler) @@ -1127,7 +1126,7 @@ async def process( # Verify context content assert context.agent is mock_agent assert len(context.messages) == 1 - assert context.messages[0].role == Role.USER + assert context.messages[0].role == "user" assert context.messages[0].text == "test" assert context.is_streaming is False assert isinstance(context.metadata, dict) @@ -1139,13 +1138,13 @@ async def process( middleware = ContextValidationMiddleware() pipeline = AgentMiddlewarePipeline([middleware]) - messages = [ChatMessage(role=Role.USER, text="test")] + messages = [ChatMessage("user", ["test"])] context = AgentRunContext(agent=mock_agent, messages=messages) async def final_handler(ctx: AgentRunContext) -> AgentResponse: # Verify metadata was set by middleware assert ctx.metadata.get("validated") is True - return AgentResponse(messages=[ChatMessage(role=Role.ASSISTANT, text="response")]) + return AgentResponse(messages=[ChatMessage("assistant", ["response"])]) result = await pipeline.execute(mock_agent, messages, context, final_handler) assert result is not None @@ -1205,7 +1204,7 @@ async def process(self, context: ChatContext, next: Callable[[ChatContext], Awai # Verify context content assert context.chat_client is mock_chat_client assert len(context.messages) == 1 - assert context.messages[0].role == Role.USER + assert context.messages[0].role == "user" assert context.messages[0].text == "test" assert context.is_streaming is False assert isinstance(context.metadata, dict) @@ -1219,14 +1218,14 @@ async def process(self, context: ChatContext, next: Callable[[ChatContext], Awai middleware = ChatContextValidationMiddleware() pipeline = ChatMiddlewarePipeline([middleware]) - messages = [ChatMessage(role=Role.USER, text="test")] + messages = [ChatMessage("user", ["test"])] chat_options: dict[str, Any] = {"temperature": 0.5} context = ChatContext(chat_client=mock_chat_client, messages=messages, options=chat_options) async def final_handler(ctx: ChatContext) -> ChatResponse: # Verify metadata was set by middleware assert ctx.metadata.get("validated") is True - return ChatResponse(messages=[ChatMessage(role=Role.ASSISTANT, text="response")]) + return ChatResponse(messages=[ChatMessage("assistant", ["response"])]) result = await pipeline.execute(mock_chat_client, messages, chat_options, context, final_handler) assert result is not None @@ -1248,14 +1247,14 @@ async def process( middleware = StreamingFlagMiddleware() pipeline = AgentMiddlewarePipeline([middleware]) - messages = [ChatMessage(role=Role.USER, text="test")] + messages = [ChatMessage("user", ["test"])] # Test non-streaming context = AgentRunContext(agent=mock_agent, messages=messages) async def final_handler(ctx: AgentRunContext) -> AgentResponse: streaming_flags.append(ctx.is_streaming) - return AgentResponse(messages=[ChatMessage(role=Role.ASSISTANT, text="response")]) + return AgentResponse(messages=[ChatMessage("assistant", ["response"])]) await pipeline.execute(mock_agent, messages, context, final_handler) @@ -1287,7 +1286,7 @@ async def process( middleware = StreamProcessingMiddleware() pipeline = AgentMiddlewarePipeline([middleware]) - messages = [ChatMessage(role=Role.USER, text="test")] + messages = [ChatMessage("user", ["test"])] context = AgentRunContext(agent=mock_agent, messages=messages) async def final_stream_handler(ctx: AgentRunContext) -> AsyncIterable[AgentResponseUpdate]: @@ -1323,7 +1322,7 @@ async def process(self, context: ChatContext, next: Callable[[ChatContext], Awai middleware = ChatStreamingFlagMiddleware() pipeline = ChatMiddlewarePipeline([middleware]) - messages = [ChatMessage(role=Role.USER, text="test")] + messages = [ChatMessage("user", ["test"])] chat_options: dict[str, Any] = {} # Test non-streaming @@ -1331,7 +1330,7 @@ async def process(self, context: ChatContext, next: Callable[[ChatContext], Awai async def final_handler(ctx: ChatContext) -> ChatResponse: streaming_flags.append(ctx.is_streaming) - return ChatResponse(messages=[ChatMessage(role=Role.ASSISTANT, text="response")]) + return ChatResponse(messages=[ChatMessage("assistant", ["response"])]) await pipeline.execute(mock_chat_client, messages, chat_options, context, final_handler) @@ -1365,7 +1364,7 @@ async def process(self, context: ChatContext, next: Callable[[ChatContext], Awai middleware = ChatStreamProcessingMiddleware() pipeline = ChatMiddlewarePipeline([middleware]) - messages = [ChatMessage(role=Role.USER, text="test")] + messages = [ChatMessage("user", ["test"])] chat_options: dict[str, Any] = {} context = ChatContext(chat_client=mock_chat_client, messages=messages, options=chat_options, is_streaming=True) @@ -1447,7 +1446,7 @@ async def process( middleware = NoNextMiddleware() pipeline = AgentMiddlewarePipeline([middleware]) - messages = [ChatMessage(role=Role.USER, text="test")] + messages = [ChatMessage("user", ["test"])] context = AgentRunContext(agent=mock_agent, messages=messages) handler_called = False @@ -1455,7 +1454,7 @@ async def process( async def final_handler(ctx: AgentRunContext) -> AgentResponse: nonlocal handler_called handler_called = True - return AgentResponse(messages=[ChatMessage(role=Role.ASSISTANT, text="should not execute")]) + return AgentResponse(messages=[ChatMessage("assistant", ["should not execute"])]) result = await pipeline.execute(mock_agent, messages, context, final_handler) @@ -1478,7 +1477,7 @@ async def process( middleware = NoNextStreamingMiddleware() pipeline = AgentMiddlewarePipeline([middleware]) - messages = [ChatMessage(role=Role.USER, text="test")] + messages = [ChatMessage("user", ["test"])] context = AgentRunContext(agent=mock_agent, messages=messages) handler_called = False @@ -1551,7 +1550,7 @@ async def process( await next(context) pipeline = AgentMiddlewarePipeline([FirstMiddleware(), SecondMiddleware()]) - messages = [ChatMessage(role=Role.USER, text="test")] + messages = [ChatMessage("user", ["test"])] context = AgentRunContext(agent=mock_agent, messages=messages) handler_called = False @@ -1559,7 +1558,7 @@ async def process( async def final_handler(ctx: AgentRunContext) -> AgentResponse: nonlocal handler_called handler_called = True - return AgentResponse(messages=[ChatMessage(role=Role.ASSISTANT, text="should not execute")]) + return AgentResponse(messages=[ChatMessage("assistant", ["should not execute"])]) result = await pipeline.execute(mock_agent, messages, context, final_handler) @@ -1580,7 +1579,7 @@ async def process(self, context: ChatContext, next: Callable[[ChatContext], Awai middleware = NoNextChatMiddleware() pipeline = ChatMiddlewarePipeline([middleware]) - messages = [ChatMessage(role=Role.USER, text="test")] + messages = [ChatMessage("user", ["test"])] chat_options: dict[str, Any] = {} context = ChatContext(chat_client=mock_chat_client, messages=messages, options=chat_options) @@ -1589,7 +1588,7 @@ async def process(self, context: ChatContext, next: Callable[[ChatContext], Awai async def final_handler(ctx: ChatContext) -> ChatResponse: nonlocal handler_called handler_called = True - return ChatResponse(messages=[ChatMessage(role=Role.ASSISTANT, text="should not execute")]) + return ChatResponse(messages=[ChatMessage("assistant", ["should not execute"])]) result = await pipeline.execute(mock_chat_client, messages, chat_options, context, final_handler) @@ -1608,7 +1607,7 @@ async def process(self, context: ChatContext, next: Callable[[ChatContext], Awai middleware = NoNextStreamingChatMiddleware() pipeline = ChatMiddlewarePipeline([middleware]) - messages = [ChatMessage(role=Role.USER, text="test")] + messages = [ChatMessage("user", ["test"])] chat_options: dict[str, Any] = {} context = ChatContext(chat_client=mock_chat_client, messages=messages, options=chat_options, is_streaming=True) @@ -1644,7 +1643,7 @@ async def process(self, context: ChatContext, next: Callable[[ChatContext], Awai await next(context) pipeline = ChatMiddlewarePipeline([FirstChatMiddleware(), SecondChatMiddleware()]) - messages = [ChatMessage(role=Role.USER, text="test")] + messages = [ChatMessage("user", ["test"])] chat_options: dict[str, Any] = {} context = ChatContext(chat_client=mock_chat_client, messages=messages, options=chat_options) @@ -1653,7 +1652,7 @@ async def process(self, context: ChatContext, next: Callable[[ChatContext], Awai async def final_handler(ctx: ChatContext) -> ChatResponse: nonlocal handler_called handler_called = True - return ChatResponse(messages=[ChatMessage(role=Role.ASSISTANT, text="should not execute")]) + return ChatResponse(messages=[ChatMessage("assistant", ["should not execute"])]) result = await pipeline.execute(mock_chat_client, messages, chat_options, context, final_handler) diff --git a/python/packages/core/tests/core/test_middleware_context_result.py b/python/packages/core/tests/core/test_middleware_context_result.py index 0f3b506fab..21f893a62c 100644 --- a/python/packages/core/tests/core/test_middleware_context_result.py +++ b/python/packages/core/tests/core/test_middleware_context_result.py @@ -14,7 +14,6 @@ ChatAgent, ChatMessage, Content, - Role, ) from agent_framework._middleware import ( AgentMiddleware, @@ -40,7 +39,7 @@ class TestResultOverrideMiddleware: async def test_agent_middleware_response_override_non_streaming(self, mock_agent: AgentProtocol) -> None: """Test that agent middleware can override response for non-streaming execution.""" - override_response = AgentResponse(messages=[ChatMessage(role=Role.ASSISTANT, text="overridden response")]) + override_response = AgentResponse(messages=[ChatMessage("assistant", ["overridden response"])]) class ResponseOverrideMiddleware(AgentMiddleware): async def process( @@ -52,7 +51,7 @@ async def process( middleware = ResponseOverrideMiddleware() pipeline = AgentMiddlewarePipeline([middleware]) - messages = [ChatMessage(role=Role.USER, text="test")] + messages = [ChatMessage("user", ["test"])] context = AgentRunContext(agent=mock_agent, messages=messages) handler_called = False @@ -60,7 +59,7 @@ async def process( async def final_handler(ctx: AgentRunContext) -> AgentResponse: nonlocal handler_called handler_called = True - return AgentResponse(messages=[ChatMessage(role=Role.ASSISTANT, text="original response")]) + return AgentResponse(messages=[ChatMessage("assistant", ["original response"])]) result = await pipeline.execute(mock_agent, messages, context, final_handler) @@ -88,7 +87,7 @@ async def process( middleware = StreamResponseOverrideMiddleware() pipeline = AgentMiddlewarePipeline([middleware]) - messages = [ChatMessage(role=Role.USER, text="test")] + messages = [ChatMessage("user", ["test"])] context = AgentRunContext(agent=mock_agent, messages=messages) async def final_handler(ctx: AgentRunContext) -> AsyncIterable[AgentResponseUpdate]: @@ -149,7 +148,7 @@ async def process( # Then conditionally override based on content if any("special" in msg.text for msg in context.messages if msg.text): context.result = AgentResponse( - messages=[ChatMessage(role=Role.ASSISTANT, text="Special response from middleware!")] + messages=[ChatMessage("assistant", ["Special response from middleware!"])] ) # Create ChatAgent with override middleware @@ -157,14 +156,14 @@ async def process( agent = ChatAgent(chat_client=mock_chat_client, middleware=[middleware]) # Test override case - override_messages = [ChatMessage(role=Role.USER, text="Give me a special response")] + override_messages = [ChatMessage("user", ["Give me a special response"])] override_response = await agent.run(override_messages) assert override_response.messages[0].text == "Special response from middleware!" # Verify chat client was called since middleware called next() assert mock_chat_client.call_count == 1 # Test normal case - normal_messages = [ChatMessage(role=Role.USER, text="Normal request")] + normal_messages = [ChatMessage("user", ["Normal request"])] normal_response = await agent.run(normal_messages) assert normal_response.messages[0].text == "test response" # Verify chat client was called for normal case @@ -194,7 +193,7 @@ async def process( agent = ChatAgent(chat_client=mock_chat_client, middleware=[middleware]) # Test streaming override case - override_messages = [ChatMessage(role=Role.USER, text="Give me a custom stream")] + override_messages = [ChatMessage("user", ["Give me a custom stream"])] override_updates: list[AgentResponseUpdate] = [] async for update in agent.run_stream(override_messages): override_updates.append(update) @@ -205,7 +204,7 @@ async def process( assert override_updates[2].text == " response!" # Test normal streaming case - normal_messages = [ChatMessage(role=Role.USER, text="Normal streaming request")] + normal_messages = [ChatMessage("user", ["Normal streaming request"])] normal_updates: list[AgentResponseUpdate] = [] async for update in agent.run_stream(normal_messages): normal_updates.append(update) @@ -234,10 +233,10 @@ async def process( async def final_handler(ctx: AgentRunContext) -> AgentResponse: nonlocal handler_called handler_called = True - return AgentResponse(messages=[ChatMessage(role=Role.ASSISTANT, text="executed response")]) + return AgentResponse(messages=[ChatMessage("assistant", ["executed response"])]) # Test case where next() is NOT called - no_execute_messages = [ChatMessage(role=Role.USER, text="Don't run this")] + no_execute_messages = [ChatMessage("user", ["Don't run this"])] no_execute_context = AgentRunContext(agent=mock_agent, messages=no_execute_messages) no_execute_result = await pipeline.execute(mock_agent, no_execute_messages, no_execute_context, final_handler) @@ -252,7 +251,7 @@ async def final_handler(ctx: AgentRunContext) -> AgentResponse: handler_called = False # Test case where next() IS called - execute_messages = [ChatMessage(role=Role.USER, text="Please execute this")] + execute_messages = [ChatMessage("user", ["Please execute this"])] execute_context = AgentRunContext(agent=mock_agent, messages=execute_messages) execute_result = await pipeline.execute(mock_agent, execute_messages, execute_context, final_handler) @@ -332,11 +331,11 @@ async def process( middleware = ObservabilityMiddleware() pipeline = AgentMiddlewarePipeline([middleware]) - messages = [ChatMessage(role=Role.USER, text="test")] + messages = [ChatMessage("user", ["test"])] context = AgentRunContext(agent=mock_agent, messages=messages) async def final_handler(ctx: AgentRunContext) -> AgentResponse: - return AgentResponse(messages=[ChatMessage(role=Role.ASSISTANT, text="executed response")]) + return AgentResponse(messages=[ChatMessage("assistant", ["executed response"])]) result = await pipeline.execute(mock_agent, messages, context, final_handler) @@ -396,17 +395,15 @@ async def process( if "modify" in context.result.messages[0].text: # Override after observing - context.result = AgentResponse( - messages=[ChatMessage(role=Role.ASSISTANT, text="modified after execution")] - ) + context.result = AgentResponse(messages=[ChatMessage("assistant", ["modified after execution"])]) middleware = PostExecutionOverrideMiddleware() pipeline = AgentMiddlewarePipeline([middleware]) - messages = [ChatMessage(role=Role.USER, text="test")] + messages = [ChatMessage("user", ["test"])] context = AgentRunContext(agent=mock_agent, messages=messages) async def final_handler(ctx: AgentRunContext) -> AgentResponse: - return AgentResponse(messages=[ChatMessage(role=Role.ASSISTANT, text="response to modify")]) + return AgentResponse(messages=[ChatMessage("assistant", ["response to modify"])]) result = await pipeline.execute(mock_agent, messages, context, final_handler) diff --git a/python/packages/core/tests/core/test_middleware_with_agent.py b/python/packages/core/tests/core/test_middleware_with_agent.py index a9f410b609..51c227e0b2 100644 --- a/python/packages/core/tests/core/test_middleware_with_agent.py +++ b/python/packages/core/tests/core/test_middleware_with_agent.py @@ -15,7 +15,6 @@ ChatResponseUpdate, Content, FunctionTool, - Role, agent_middleware, chat_middleware, function_middleware, @@ -58,13 +57,13 @@ async def process( agent = ChatAgent(chat_client=chat_client, middleware=[middleware]) # Execute the agent - messages = [ChatMessage(role=Role.USER, text="test message")] + messages = [ChatMessage("user", ["test message"])] response = await agent.run(messages) # Verify response assert response is not None assert len(response.messages) > 0 - assert response.messages[0].role == Role.ASSISTANT + assert response.messages[0].role == "assistant" # Note: conftest "MockChatClient" returns different text format assert "test response" in response.messages[0].text @@ -93,7 +92,7 @@ async def process( agent = ChatAgent(chat_client=chat_client, middleware=[middleware]) # Execute the agent - messages = [ChatMessage(role=Role.USER, text="test message")] + messages = [ChatMessage("user", ["test message"])] response = await agent.run(messages) # Verify response @@ -128,8 +127,8 @@ async def process( # Execute the agent with multiple messages messages = [ - ChatMessage(role=Role.USER, text="message1"), - ChatMessage(role=Role.USER, text="message2"), # This should not be processed due to termination + ChatMessage("user", ["message1"]), + ChatMessage("user", ["message2"]), # This should not be processed due to termination ] response = await agent.run(messages) @@ -158,15 +157,15 @@ async def process( # Execute the agent with multiple messages messages = [ - ChatMessage(role=Role.USER, text="message1"), - ChatMessage(role=Role.USER, text="message2"), + ChatMessage("user", ["message1"]), + ChatMessage("user", ["message2"]), ] response = await agent.run(messages) # Verify response assert response is not None assert len(response.messages) == 1 - assert response.messages[0].role == Role.ASSISTANT + assert response.messages[0].role == "assistant" assert "test response" in response.messages[0].text # Verify middleware execution order @@ -190,7 +189,7 @@ async def process( execution_order.append("middleware_after") # Create a message to start the conversation - messages = [ChatMessage(role=Role.USER, text="test message")] + messages = [ChatMessage("user", ["test message"])] # Set up chat client to return a function call, then a final response # If terminate works correctly, only the first response should be consumed @@ -198,7 +197,7 @@ async def process( ChatResponse( messages=[ ChatMessage( - role=Role.ASSISTANT, + role="assistant", contents=[ Content.from_function_call( call_id="test_call", name="test_function", arguments={"text": "test"} @@ -207,7 +206,7 @@ async def process( ) ] ), - ChatResponse(messages=[ChatMessage(role=Role.ASSISTANT, text="this should not be consumed")]), + ChatResponse(messages=[ChatMessage("assistant", ["this should not be consumed"])]), ] # Create the test function with the expected signature @@ -251,7 +250,7 @@ async def process( context.terminate = True # Create a message to start the conversation - messages = [ChatMessage(role=Role.USER, text="test message")] + messages = [ChatMessage("user", ["test message"])] # Set up chat client to return a function call, then a final response # If terminate works correctly, only the first response should be consumed @@ -259,7 +258,7 @@ async def process( ChatResponse( messages=[ ChatMessage( - role=Role.ASSISTANT, + role="assistant", contents=[ Content.from_function_call( call_id="test_call", name="test_function", arguments={"text": "test"} @@ -268,7 +267,7 @@ async def process( ) ] ), - ChatResponse(messages=[ChatMessage(role=Role.ASSISTANT, text="this should not be consumed")]), + ChatResponse(messages=[ChatMessage("assistant", ["this should not be consumed"])]), ] # Create the test function with the expected signature @@ -312,13 +311,13 @@ async def tracking_agent_middleware( agent = ChatAgent(chat_client=chat_client, middleware=[tracking_agent_middleware]) # Execute the agent - messages = [ChatMessage(role=Role.USER, text="test message")] + messages = [ChatMessage("user", ["test message"])] response = await agent.run(messages) # Verify response assert response is not None assert len(response.messages) > 0 - assert response.messages[0].role == Role.ASSISTANT + assert response.messages[0].role == "assistant" assert response.messages[0].text == "test response" assert chat_client.call_count == 1 @@ -340,7 +339,7 @@ async def tracking_function_middleware( agent = ChatAgent(chat_client=chat_client, middleware=[tracking_function_middleware]) # Execute the agent - messages = [ChatMessage(role=Role.USER, text="test message")] + messages = [ChatMessage("user", ["test message"])] response = await agent.run(messages) # Verify response @@ -376,13 +375,13 @@ async def process( # Set up mock streaming responses chat_client.streaming_responses = [ [ - ChatResponseUpdate(contents=[Content.from_text(text="Streaming")], role=Role.ASSISTANT), - ChatResponseUpdate(contents=[Content.from_text(text=" response")], role=Role.ASSISTANT), + ChatResponseUpdate(contents=[Content.from_text(text="Streaming")], role="assistant"), + ChatResponseUpdate(contents=[Content.from_text(text=" response")], role="assistant"), ] ] # Execute streaming - messages = [ChatMessage(role=Role.USER, text="test message")] + messages = [ChatMessage("user", ["test message"])] updates: list[AgentResponseUpdate] = [] async for update in agent.run_stream(messages): updates.append(update) @@ -411,7 +410,7 @@ async def process( # Create ChatAgent with middleware middleware = FlagTrackingMiddleware() agent = ChatAgent(chat_client=chat_client, middleware=[middleware]) - messages = [ChatMessage(role=Role.USER, text="test message")] + messages = [ChatMessage("user", ["test message"])] # Test non-streaming execution response = await agent.run(messages) @@ -452,7 +451,7 @@ async def process( agent = ChatAgent(chat_client=chat_client, middleware=[middleware1, middleware2, middleware3]) # Execute the agent - messages = [ChatMessage(role=Role.USER, text="test message")] + messages = [ChatMessage("user", ["test message"])] response = await agent.run(messages) # Verify response @@ -511,7 +510,7 @@ async def function_function_middleware( ) # Execute the agent - messages = [ChatMessage(role=Role.USER, text="test message")] + messages = [ChatMessage("user", ["test message"])] response = await agent.run(messages) # Verify response @@ -567,7 +566,7 @@ async def process( function_call_response = ChatResponse( messages=[ ChatMessage( - role=Role.ASSISTANT, + role="assistant", contents=[ Content.from_function_call( call_id="call_123", @@ -578,7 +577,7 @@ async def process( ) ] ) - final_response = ChatResponse(messages=[ChatMessage(role=Role.ASSISTANT, text="Final response")]) + final_response = ChatResponse(messages=[ChatMessage("assistant", ["Final response"])]) chat_client.responses = [function_call_response, final_response] @@ -591,7 +590,7 @@ async def process( ) # Execute the agent - messages = [ChatMessage(role=Role.USER, text="Get weather for Seattle")] + messages = [ChatMessage("user", ["Get weather for Seattle"])] response = await agent.run(messages) # Verify response @@ -627,7 +626,7 @@ async def tracking_function_middleware( function_call_response = ChatResponse( messages=[ ChatMessage( - role=Role.ASSISTANT, + role="assistant", contents=[ Content.from_function_call( call_id="call_456", @@ -638,7 +637,7 @@ async def tracking_function_middleware( ) ] ) - final_response = ChatResponse(messages=[ChatMessage(role=Role.ASSISTANT, text="Final response")]) + final_response = ChatResponse(messages=[ChatMessage("assistant", ["Final response"])]) chat_client.responses = [function_call_response, final_response] @@ -650,7 +649,7 @@ async def tracking_function_middleware( ) # Execute the agent - messages = [ChatMessage(role=Role.USER, text="Get weather for San Francisco")] + messages = [ChatMessage("user", ["Get weather for San Francisco"])] response = await agent.run(messages) # Verify response @@ -699,7 +698,7 @@ async def process( function_call_response = ChatResponse( messages=[ ChatMessage( - role=Role.ASSISTANT, + role="assistant", contents=[ Content.from_function_call( call_id="call_789", @@ -710,7 +709,7 @@ async def process( ) ] ) - final_response = ChatResponse(messages=[ChatMessage(role=Role.ASSISTANT, text="Final response")]) + final_response = ChatResponse(messages=[ChatMessage("assistant", ["Final response"])]) chat_client.responses = [function_call_response, final_response] @@ -722,7 +721,7 @@ async def process( ) # Execute the agent - messages = [ChatMessage(role=Role.USER, text="Get weather for New York")] + messages = [ChatMessage("user", ["Get weather for New York"])] response = await agent.run(messages) # Verify response @@ -786,7 +785,7 @@ async def kwargs_middleware( ChatResponse( messages=[ ChatMessage( - role=Role.ASSISTANT, + role="assistant", contents=[ Content.from_function_call( call_id="test_call", name="sample_tool_function", arguments={"location": "Seattle"} @@ -795,16 +794,14 @@ async def kwargs_middleware( ) ] ), - ChatResponse( - messages=[ChatMessage(role=Role.ASSISTANT, contents=[Content.from_text("Function completed")])] - ), + ChatResponse(messages=[ChatMessage("assistant", [Content.from_text("Function completed")])]), ] # Create ChatAgent with function middleware agent = ChatAgent(chat_client=chat_client, middleware=[kwargs_middleware], tools=[sample_tool_function]) # Execute the agent with custom parameters passed as kwargs - messages = [ChatMessage(role=Role.USER, text="test message")] + messages = [ChatMessage("user", ["test message"])] response = await agent.run(messages, custom_param="test_value") # Verify response @@ -1068,7 +1065,7 @@ async def test_run_level_middleware_non_streaming(self, chat_client: "MockChatCl # Verify response is correct assert response is not None assert len(response.messages) > 0 - assert response.messages[0].role == Role.ASSISTANT + assert response.messages[0].role == "assistant" assert "test response" in response.messages[0].text # Verify middleware was executed @@ -1097,8 +1094,8 @@ async def process( # Set up mock streaming responses chat_client.streaming_responses = [ [ - ChatResponseUpdate(contents=[Content.from_text(text="Stream")], role=Role.ASSISTANT), - ChatResponseUpdate(contents=[Content.from_text(text=" response")], role=Role.ASSISTANT), + ChatResponseUpdate(contents=[Content.from_text(text="Stream")], role="assistant"), + ChatResponseUpdate(contents=[Content.from_text(text=" response")], role="assistant"), ] ] @@ -1182,7 +1179,7 @@ def custom_tool(message: str) -> str: function_call_response = ChatResponse( messages=[ ChatMessage( - role=Role.ASSISTANT, + role="assistant", contents=[ Content.from_function_call( call_id="test_call", @@ -1193,7 +1190,7 @@ def custom_tool(message: str) -> str: ) ] ) - final_response = ChatResponse(messages=[ChatMessage(role=Role.ASSISTANT, text="Final response")]) + final_response = ChatResponse(messages=[ChatMessage("assistant", ["Final response"])]) chat_client.responses = [function_call_response, final_response] # Create agent with agent-level middleware @@ -1275,7 +1272,7 @@ def custom_tool(message: str) -> str: function_call_response = ChatResponse( messages=[ ChatMessage( - role=Role.ASSISTANT, + role="assistant", contents=[ Content.from_function_call( call_id="test_call", @@ -1286,7 +1283,7 @@ def custom_tool(message: str) -> str: ) ] ) - final_response = ChatResponse(messages=[ChatMessage(role=Role.ASSISTANT, text="Final response")]) + final_response = ChatResponse(messages=[ChatMessage("assistant", ["Final response"])]) chat_client.responses = [function_call_response, final_response] # Should work without errors @@ -1296,7 +1293,7 @@ def custom_tool(message: str) -> str: tools=[custom_tool_wrapped], ) - response = await agent.run([ChatMessage(role=Role.USER, text="test")]) + response = await agent.run([ChatMessage("user", ["test"])]) assert response is not None assert "decorator_type_match_agent" in execution_order @@ -1317,7 +1314,7 @@ async def mismatched_middleware( await next(context) agent = ChatAgent(chat_client=chat_client, middleware=[mismatched_middleware]) - await agent.run([ChatMessage(role=Role.USER, text="test")]) + await agent.run([ChatMessage("user", ["test"])]) async def test_only_decorator_specified(self, chat_client: Any) -> None: """Only decorator specified - rely on decorator.""" @@ -1346,7 +1343,7 @@ def custom_tool(message: str) -> str: function_call_response = ChatResponse( messages=[ ChatMessage( - role=Role.ASSISTANT, + role="assistant", contents=[ Content.from_function_call( call_id="test_call", @@ -1357,7 +1354,7 @@ def custom_tool(message: str) -> str: ) ] ) - final_response = ChatResponse(messages=[ChatMessage(role=Role.ASSISTANT, text="Final response")]) + final_response = ChatResponse(messages=[ChatMessage("assistant", ["Final response"])]) chat_client.responses = [function_call_response, final_response] # Should work - relies on decorator @@ -1367,7 +1364,7 @@ def custom_tool(message: str) -> str: tools=[custom_tool_wrapped], ) - response = await agent.run([ChatMessage(role=Role.USER, text="test")]) + response = await agent.run([ChatMessage("user", ["test"])]) assert response is not None assert "decorator_only_agent" in execution_order @@ -1402,7 +1399,7 @@ def custom_tool(message: str) -> str: function_call_response = ChatResponse( messages=[ ChatMessage( - role=Role.ASSISTANT, + role="assistant", contents=[ Content.from_function_call( call_id="test_call", @@ -1413,7 +1410,7 @@ def custom_tool(message: str) -> str: ) ] ) - final_response = ChatResponse(messages=[ChatMessage(role=Role.ASSISTANT, text="Final response")]) + final_response = ChatResponse(messages=[ChatMessage("assistant", ["Final response"])]) chat_client.responses = [function_call_response, final_response] # Should work - relies on type annotations @@ -1421,7 +1418,7 @@ def custom_tool(message: str) -> str: chat_client=chat_client, middleware=[type_only_agent, type_only_function], tools=[custom_tool_wrapped] ) - response = await agent.run([ChatMessage(role=Role.USER, text="test")]) + response = await agent.run([ChatMessage("user", ["test"])]) assert response is not None assert "type_only_agent" in execution_order @@ -1436,7 +1433,7 @@ async def no_info_middleware(context: Any, next: Any) -> None: # No decorator, # Should raise MiddlewareException with pytest.raises(MiddlewareException, match="Cannot determine middleware type"): agent = ChatAgent(chat_client=chat_client, middleware=[no_info_middleware]) - await agent.run([ChatMessage(role=Role.USER, text="test")]) + await agent.run([ChatMessage("user", ["test"])]) async def test_insufficient_parameters_error(self, chat_client: Any) -> None: """Test that middleware with insufficient parameters raises an error.""" @@ -1450,7 +1447,7 @@ async def insufficient_params_middleware(context: Any) -> None: # Missing 'next pass agent = ChatAgent(chat_client=chat_client, middleware=[insufficient_params_middleware]) - await agent.run([ChatMessage(role=Role.USER, text="test")]) + await agent.run([ChatMessage("user", ["test"])]) async def test_decorator_markers_preserved(self) -> None: """Test that decorator markers are properly set on functions.""" @@ -1523,7 +1520,7 @@ async def process( thread = agent.get_new_thread() # First run - first_messages = [ChatMessage(role=Role.USER, text="first message")] + first_messages = [ChatMessage("user", ["first message"])] first_response = await agent.run(first_messages, thread=thread) # Verify first response @@ -1531,7 +1528,7 @@ async def process( assert len(first_response.messages) > 0 # Second run - use the same thread - second_messages = [ChatMessage(role=Role.USER, text="second message")] + second_messages = [ChatMessage("user", ["second message"])] second_response = await agent.run(second_messages, thread=thread) # Verify second response @@ -1603,13 +1600,13 @@ async def process(self, context: ChatContext, next: Callable[[ChatContext], Awai agent = ChatAgent(chat_client=chat_client, middleware=[middleware]) # Execute the agent - messages = [ChatMessage(role=Role.USER, text="test message")] + messages = [ChatMessage("user", ["test message"])] response = await agent.run(messages) # Verify response assert response is not None assert len(response.messages) > 0 - assert response.messages[0].role == Role.ASSISTANT + assert response.messages[0].role == "assistant" assert "test response" in response.messages[0].text assert execution_order == ["chat_middleware_before", "chat_middleware_after"] @@ -1629,13 +1626,13 @@ async def tracking_chat_middleware( agent = ChatAgent(chat_client=chat_client, middleware=[tracking_chat_middleware]) # Execute the agent - messages = [ChatMessage(role=Role.USER, text="test message")] + messages = [ChatMessage("user", ["test message"])] response = await agent.run(messages) # Verify response assert response is not None assert len(response.messages) > 0 - assert response.messages[0].role == Role.ASSISTANT + assert response.messages[0].role == "assistant" assert "test response" in response.messages[0].text assert execution_order == ["chat_middleware_before", "chat_middleware_after"] @@ -1649,10 +1646,10 @@ async def message_modifier_middleware( # Modify the first message by adding a prefix if context.messages: for idx, msg in enumerate(context.messages): - if msg.role.value == "system": + if msg.role == "system": continue original_text = msg.text or "" - context.messages[idx] = ChatMessage(role=msg.role, text=f"MODIFIED: {original_text}") + context.messages[idx] = ChatMessage(msg.role, [f"MODIFIED: {original_text}"]) break await next(context) @@ -1661,7 +1658,7 @@ async def message_modifier_middleware( agent = ChatAgent(chat_client=chat_client, middleware=[message_modifier_middleware]) # Execute the agent - messages = [ChatMessage(role=Role.USER, text="test message")] + messages = [ChatMessage("user", ["test message"])] response = await agent.run(messages) # Verify that the message was modified (MockBaseChatClient echoes back the input) @@ -1677,7 +1674,7 @@ async def response_override_middleware( ) -> None: # Override the response without calling next() context.result = ChatResponse( - messages=[ChatMessage(role=Role.ASSISTANT, text="Middleware overridden response")], + messages=[ChatMessage("assistant", ["Middleware overridden response"])], response_id="middleware-response-123", ) context.terminate = True @@ -1687,7 +1684,7 @@ async def response_override_middleware( agent = ChatAgent(chat_client=chat_client, middleware=[response_override_middleware]) # Execute the agent - messages = [ChatMessage(role=Role.USER, text="test message")] + messages = [ChatMessage("user", ["test message"])] response = await agent.run(messages) # Verify that the response was overridden @@ -1717,7 +1714,7 @@ async def second_middleware(context: ChatContext, next: Callable[[ChatContext], agent = ChatAgent(chat_client=chat_client, middleware=[first_middleware, second_middleware]) # Execute the agent - messages = [ChatMessage(role=Role.USER, text="test message")] + messages = [ChatMessage("user", ["test message"])] response = await agent.run(messages) # Verify response @@ -1743,13 +1740,13 @@ async def process(self, context: ChatContext, next: Callable[[ChatContext], Awai # Set up mock streaming responses chat_client.streaming_responses = [ [ - ChatResponseUpdate(contents=[Content.from_text(text="Stream")], role=Role.ASSISTANT), - ChatResponseUpdate(contents=[Content.from_text(text=" response")], role=Role.ASSISTANT), + ChatResponseUpdate(contents=[Content.from_text(text="Stream")], role="assistant"), + ChatResponseUpdate(contents=[Content.from_text(text=" response")], role="assistant"), ] ] # Execute streaming - messages = [ChatMessage(role=Role.USER, text="test message")] + messages = [ChatMessage("user", ["test message"])] updates: list[AgentResponseUpdate] = [] async for update in agent.run_stream(messages): updates.append(update) @@ -1770,9 +1767,7 @@ async def process(self, context: ChatContext, next: Callable[[ChatContext], Awai execution_order.append("middleware_before") context.terminate = True # Set a custom response since we're terminating - context.result = ChatResponse( - messages=[ChatMessage(role=Role.ASSISTANT, text="Terminated by middleware")] - ) + context.result = ChatResponse(messages=[ChatMessage("assistant", ["Terminated by middleware"])]) # We call next() but since terminate=True, execution should stop await next(context) execution_order.append("middleware_after") @@ -1782,7 +1777,7 @@ async def process(self, context: ChatContext, next: Callable[[ChatContext], Awai agent = ChatAgent(chat_client=chat_client, middleware=[PreTerminationChatMiddleware()]) # Execute the agent - messages = [ChatMessage(role=Role.USER, text="test message")] + messages = [ChatMessage("user", ["test message"])] response = await agent.run(messages) # Verify response was from middleware @@ -1807,7 +1802,7 @@ async def process(self, context: ChatContext, next: Callable[[ChatContext], Awai agent = ChatAgent(chat_client=chat_client, middleware=[PostTerminationChatMiddleware()]) # Execute the agent - messages = [ChatMessage(role=Role.USER, text="test message")] + messages = [ChatMessage("user", ["test message"])] response = await agent.run(messages) # Verify response is from actual execution @@ -1843,7 +1838,7 @@ async def function_middleware( function_call_response = ChatResponse( messages=[ ChatMessage( - role=Role.ASSISTANT, + role="assistant", contents=[ Content.from_function_call( call_id="call_456", @@ -1854,7 +1849,7 @@ async def function_middleware( ) ] ) - final_response = ChatResponse(messages=[ChatMessage(role=Role.ASSISTANT, text="Final response")]) + final_response = ChatResponse(messages=[ChatMessage("assistant", ["Final response"])]) chat_client = use_function_invocation(MockBaseChatClient)() chat_client.run_responses = [function_call_response, final_response] @@ -1867,7 +1862,7 @@ async def function_middleware( ) # Execute the agent - messages = [ChatMessage(role=Role.USER, text="Get weather for San Francisco")] + messages = [ChatMessage("user", ["Get weather for San Francisco"])] response = await agent.run(messages) # Verify response @@ -1924,7 +1919,7 @@ async def kwargs_middleware( agent = ChatAgent(chat_client=chat_client, middleware=[kwargs_middleware]) # Execute the agent with custom parameters - messages = [ChatMessage(role=Role.USER, text="test message")] + messages = [ChatMessage("user", ["test message"])] response = await agent.run(messages, temperature=0.7, max_tokens=100, custom_param="test_value") # Verify response @@ -1973,7 +1968,7 @@ def __init__(self): self.middleware = [TrackingMiddleware()] async def run(self, messages=None, *, thread=None, **kwargs) -> AgentResponse: - return AgentResponse(messages=[ChatMessage(role=Role.ASSISTANT, text="response")]) + return AgentResponse(messages=[ChatMessage("assistant", ["response"])]) def run_stream(self, messages=None, *, thread=None, **kwargs) -> AsyncIterable[AgentResponseUpdate]: async def _stream(): diff --git a/python/packages/core/tests/core/test_middleware_with_chat.py b/python/packages/core/tests/core/test_middleware_with_chat.py index ef2f6f3c09..a3893e1a6e 100644 --- a/python/packages/core/tests/core/test_middleware_with_chat.py +++ b/python/packages/core/tests/core/test_middleware_with_chat.py @@ -12,7 +12,6 @@ Content, FunctionInvocationContext, FunctionTool, - Role, chat_middleware, function_middleware, use_chat_middleware, @@ -43,13 +42,13 @@ async def process( chat_client_base.middleware = [LoggingChatMiddleware()] # Execute chat client directly - messages = [ChatMessage(role=Role.USER, text="test message")] + messages = [ChatMessage("user", ["test message"])] response = await chat_client_base.get_response(messages) # Verify response assert response is not None assert len(response.messages) > 0 - assert response.messages[0].role == Role.ASSISTANT + assert response.messages[0].role == "assistant" # Verify middleware execution order assert execution_order == ["chat_middleware_before", "chat_middleware_after"] @@ -68,13 +67,13 @@ async def logging_chat_middleware(context: ChatContext, next: Callable[[ChatCont chat_client_base.middleware = [logging_chat_middleware] # Execute chat client directly - messages = [ChatMessage(role=Role.USER, text="test message")] + messages = [ChatMessage("user", ["test message"])] response = await chat_client_base.get_response(messages) # Verify response assert response is not None assert len(response.messages) > 0 - assert response.messages[0].role == Role.ASSISTANT + assert response.messages[0].role == "assistant" # Verify middleware execution order assert execution_order == ["function_middleware_before", "function_middleware_after"] @@ -89,14 +88,14 @@ async def message_modifier_middleware( # Modify the first message by adding a prefix if context.messages and len(context.messages) > 0: original_text = context.messages[0].text or "" - context.messages[0] = ChatMessage(role=context.messages[0].role, text=f"MODIFIED: {original_text}") + context.messages[0] = ChatMessage(context.messages[0].role, [f"MODIFIED: {original_text}"]) await next(context) # Add middleware to chat client chat_client_base.middleware = [message_modifier_middleware] # Execute chat client - messages = [ChatMessage(role=Role.USER, text="test message")] + messages = [ChatMessage("user", ["test message"])] response = await chat_client_base.get_response(messages) # Verify that the message was modified (MockChatClient echoes back the input) @@ -114,7 +113,7 @@ async def response_override_middleware( ) -> None: # Override the response without calling next() context.result = ChatResponse( - messages=[ChatMessage(role=Role.ASSISTANT, text="Middleware overridden response")], + messages=[ChatMessage("assistant", ["Middleware overridden response"])], response_id="middleware-response-123", ) context.terminate = True @@ -123,7 +122,7 @@ async def response_override_middleware( chat_client_base.middleware = [response_override_middleware] # Execute chat client - messages = [ChatMessage(role=Role.USER, text="test message")] + messages = [ChatMessage("user", ["test message"])] response = await chat_client_base.get_response(messages) # Verify that the response was overridden @@ -152,7 +151,7 @@ async def second_middleware(context: ChatContext, next: Callable[[ChatContext], chat_client_base.middleware = [first_middleware, second_middleware] # Execute chat client - messages = [ChatMessage(role=Role.USER, text="test message")] + messages = [ChatMessage("user", ["test message"])] response = await chat_client_base.get_response(messages) # Verify response @@ -180,13 +179,13 @@ async def agent_level_chat_middleware( agent = ChatAgent(chat_client=chat_client, middleware=[agent_level_chat_middleware]) # Execute the agent - messages = [ChatMessage(role=Role.USER, text="test message")] + messages = [ChatMessage("user", ["test message"])] response = await agent.run(messages) # Verify response assert response is not None assert len(response.messages) > 0 - assert response.messages[0].role == Role.ASSISTANT + assert response.messages[0].role == "assistant" # Verify middleware execution order assert execution_order == ["agent_chat_middleware_before", "agent_chat_middleware_after"] @@ -211,7 +210,7 @@ async def second_middleware(context: ChatContext, next: Callable[[ChatContext], agent = ChatAgent(chat_client=chat_client_base, middleware=[first_middleware, second_middleware]) # Execute the agent - messages = [ChatMessage(role=Role.USER, text="test message")] + messages = [ChatMessage("user", ["test message"])] response = await agent.run(messages) # Verify response @@ -237,7 +236,7 @@ async def streaming_middleware(context: ChatContext, next: Callable[[ChatContext chat_client_base.middleware = [streaming_middleware] # Execute streaming response - messages = [ChatMessage(role=Role.USER, text="test message")] + messages = [ChatMessage("user", ["test message"])] updates: list[object] = [] async for update in chat_client_base.get_streaming_response(messages): updates.append(update) @@ -258,19 +257,19 @@ async def counting_middleware(context: ChatContext, next: Callable[[ChatContext] await next(context) # First call with run-level middleware - messages = [ChatMessage(role=Role.USER, text="first message")] + messages = [ChatMessage("user", ["first message"])] response1 = await chat_client_base.get_response(messages, middleware=[counting_middleware]) assert response1 is not None assert execution_count["count"] == 1 # Second call WITHOUT run-level middleware - should not execute the middleware - messages = [ChatMessage(role=Role.USER, text="second message")] + messages = [ChatMessage("user", ["second message"])] response2 = await chat_client_base.get_response(messages) assert response2 is not None assert execution_count["count"] == 1 # Should still be 1, not 2 # Third call with run-level middleware again - should execute - messages = [ChatMessage(role=Role.USER, text="third message")] + messages = [ChatMessage("user", ["third message"])] response3 = await chat_client_base.get_response(messages, middleware=[counting_middleware]) assert response3 is not None assert execution_count["count"] == 2 # Should be 2 now @@ -301,7 +300,7 @@ async def kwargs_middleware(context: ChatContext, next: Callable[[ChatContext], chat_client_base.middleware = [kwargs_middleware] # Execute chat client with custom parameters - messages = [ChatMessage(role=Role.USER, text="test message")] + messages = [ChatMessage("user", ["test message"])] response = await chat_client_base.get_response( messages, temperature=0.7, max_tokens=100, custom_param="test_value" ) @@ -355,7 +354,7 @@ def sample_tool(location: str) -> str: function_call_response = ChatResponse( messages=[ ChatMessage( - role=Role.ASSISTANT, + role="assistant", contents=[ Content.from_function_call( call_id="call_1", @@ -366,14 +365,12 @@ def sample_tool(location: str) -> str: ) ] ) - final_response = ChatResponse( - messages=[ChatMessage(role=Role.ASSISTANT, text="Based on the weather data, it's sunny!")] - ) + final_response = ChatResponse(messages=[ChatMessage("assistant", ["Based on the weather data, it's sunny!"])]) chat_client.run_responses = [function_call_response, final_response] # Execute the chat client directly with tools - this should trigger function invocation and middleware - messages = [ChatMessage(role=Role.USER, text="What's the weather in San Francisco?")] + messages = [ChatMessage("user", ["What's the weather in San Francisco?"])] response = await chat_client.get_response(messages, options={"tools": [sample_tool_wrapped]}) # Verify response @@ -418,7 +415,7 @@ def sample_tool(location: str) -> str: function_call_response = ChatResponse( messages=[ ChatMessage( - role=Role.ASSISTANT, + role="assistant", contents=[ Content.from_function_call( call_id="call_2", @@ -430,13 +427,13 @@ def sample_tool(location: str) -> str: ] ) final_response = ChatResponse( - messages=[ChatMessage(role=Role.ASSISTANT, text="The weather information has been retrieved!")] + messages=[ChatMessage("assistant", ["The weather information has been retrieved!"])] ) chat_client.run_responses = [function_call_response, final_response] # Execute the chat client directly with run-level middleware and tools - messages = [ChatMessage(role=Role.USER, text="What's the weather in New York?")] + messages = [ChatMessage("user", ["What's the weather in New York?"])] response = await chat_client.get_response( messages, options={"tools": [sample_tool_wrapped]}, middleware=[run_level_function_middleware] ) diff --git a/python/packages/core/tests/core/test_observability.py b/python/packages/core/tests/core/test_observability.py index 3818a057bb..726f19c1af 100644 --- a/python/packages/core/tests/core/test_observability.py +++ b/python/packages/core/tests/core/test_observability.py @@ -14,12 +14,13 @@ AGENT_FRAMEWORK_USER_AGENT, AgentProtocol, AgentResponse, + AgentResponseUpdate, AgentThread, BaseChatClient, ChatMessage, ChatResponse, ChatResponseUpdate, - Role, + Content, UsageDetails, prepend_agent_framework_to_user_agent, tool, @@ -217,7 +218,7 @@ async def _inner_get_response( self, *, messages: MutableSequence[ChatMessage], options: dict[str, Any], **kwargs: Any ): return ChatResponse( - messages=[ChatMessage(role=Role.ASSISTANT, text="Test response")], + messages=[ChatMessage("assistant", ["Test response"])], usage_details=UsageDetails(input_token_count=10, output_token_count=20), finish_reason=None, ) @@ -225,8 +226,8 @@ async def _inner_get_response( async def _inner_get_streaming_response( self, *, messages: MutableSequence[ChatMessage], options: dict[str, Any], **kwargs: Any ): - yield ChatResponseUpdate(text="Hello", role=Role.ASSISTANT) - yield ChatResponseUpdate(text=" world", role=Role.ASSISTANT) + yield ChatResponseUpdate(contents=[Content.from_text(text="Hello")], role="assistant") + yield ChatResponseUpdate(contents=[Content.from_text(text=" world")], role="assistant") return MockChatClient @@ -236,7 +237,7 @@ async def test_chat_client_observability(mock_chat_client, span_exporter: InMemo """Test that when diagnostics are enabled, telemetry is applied.""" client = use_instrumentation(mock_chat_client)() - messages = [ChatMessage(role=Role.USER, text="Test message")] + messages = [ChatMessage("user", ["Test message"])] span_exporter.clear() response = await client.get_response(messages=messages, model_id="Test") assert response is not None @@ -259,7 +260,7 @@ async def test_chat_client_streaming_observability( ): """Test streaming telemetry through the use_instrumentation decorator.""" client = use_instrumentation(mock_chat_client)() - messages = [ChatMessage(role=Role.USER, text="Test")] + messages = [ChatMessage("user", ["Test"])] span_exporter.clear() # Collect all yielded updates updates = [] @@ -288,7 +289,7 @@ async def test_chat_client_observability_with_instructions( client = use_instrumentation(mock_chat_client)() - messages = [ChatMessage(role=Role.USER, text="Test message")] + messages = [ChatMessage("user", ["Test message"])] options = {"model_id": "Test", "instructions": "You are a helpful assistant."} span_exporter.clear() response = await client.get_response(messages=messages, options=options) @@ -317,7 +318,7 @@ async def test_chat_client_streaming_observability_with_instructions( import json client = use_instrumentation(mock_chat_client)() - messages = [ChatMessage(role=Role.USER, text="Test")] + messages = [ChatMessage("user", ["Test"])] options = {"model_id": "Test", "instructions": "You are a helpful assistant."} span_exporter.clear() @@ -344,7 +345,7 @@ async def test_chat_client_observability_without_instructions( """Test that system_instructions attribute is not set when instructions are not provided.""" client = use_instrumentation(mock_chat_client)() - messages = [ChatMessage(role=Role.USER, text="Test message")] + messages = [ChatMessage("user", ["Test message"])] options = {"model_id": "Test"} # No instructions span_exporter.clear() response = await client.get_response(messages=messages, options=options) @@ -365,7 +366,7 @@ async def test_chat_client_observability_with_empty_instructions( """Test that system_instructions attribute is not set when instructions is an empty string.""" client = use_instrumentation(mock_chat_client)() - messages = [ChatMessage(role=Role.USER, text="Test message")] + messages = [ChatMessage("user", ["Test message"])] options = {"model_id": "Test", "instructions": ""} # Empty string span_exporter.clear() response = await client.get_response(messages=messages, options=options) @@ -388,7 +389,7 @@ async def test_chat_client_observability_with_list_instructions( client = use_instrumentation(mock_chat_client)() - messages = [ChatMessage(role=Role.USER, text="Test message")] + messages = [ChatMessage("user", ["Test message"])] options = {"model_id": "Test", "instructions": ["Instruction 1", "Instruction 2"]} span_exporter.clear() response = await client.get_response(messages=messages, options=options) @@ -409,7 +410,7 @@ async def test_chat_client_observability_with_list_instructions( async def test_chat_client_without_model_id_observability(mock_chat_client, span_exporter: InMemorySpanExporter): """Test telemetry shouldn't fail when the model_id is not provided for unknown reason.""" client = use_instrumentation(mock_chat_client)() - messages = [ChatMessage(role=Role.USER, text="Test")] + messages = [ChatMessage("user", ["Test"])] span_exporter.clear() response = await client.get_response(messages=messages) @@ -428,7 +429,7 @@ async def test_chat_client_streaming_without_model_id_observability( ): """Test streaming telemetry shouldn't fail when the model_id is not provided for unknown reason.""" client = use_instrumentation(mock_chat_client)() - messages = [ChatMessage(role=Role.USER, text="Test")] + messages = [ChatMessage("user", ["Test"])] span_exporter.clear() # Collect all yielded updates updates = [] @@ -535,17 +536,16 @@ def __init__(self): async def run(self, messages=None, *, thread=None, **kwargs): return AgentResponse( - messages=[ChatMessage(role=Role.ASSISTANT, text="Agent response")], + messages=[ChatMessage("assistant", ["Agent response"])], usage_details=UsageDetails(input_token_count=15, output_token_count=25), response_id="test_response_id", raw_representation=Mock(finish_reason=Mock(value="stop")), ) async def run_stream(self, messages=None, *, thread=None, **kwargs): - from agent_framework import AgentResponseUpdate - yield AgentResponseUpdate(text="Hello", role=Role.ASSISTANT) - yield AgentResponseUpdate(text=" from agent", role=Role.ASSISTANT) + yield AgentResponseUpdate(contents=[Content.from_text(text="Hello")], role="assistant") + yield AgentResponseUpdate(contents=[Content.from_text(text=" from agent")], role="assistant") return MockChatClientAgent @@ -1338,7 +1338,7 @@ async def _inner_get_response(self, *, messages, options, **kwargs): raise ValueError("Test error") client = use_instrumentation(FailingChatClient)() - messages = [ChatMessage(role=Role.USER, text="Test")] + messages = [ChatMessage("user", ["Test"])] span_exporter.clear() with pytest.raises(ValueError, match="Test error"): @@ -1356,11 +1356,11 @@ async def test_chat_client_streaming_observability_exception(mock_chat_client, s class FailingStreamingChatClient(mock_chat_client): async def _inner_get_streaming_response(self, *, messages, options, **kwargs): - yield ChatResponseUpdate(text="Hello", role=Role.ASSISTANT) + yield ChatResponseUpdate(contents=[Content.from_text(text="Hello")], role="assistant") raise ValueError("Streaming error") client = use_instrumentation(FailingStreamingChatClient)() - messages = [ChatMessage(role=Role.USER, text="Test")] + messages = [ChatMessage("user", ["Test"])] span_exporter.clear() with pytest.raises(ValueError, match="Streaming error"): @@ -1431,12 +1431,11 @@ def test_get_response_attributes_with_finish_reason(): """Test _get_response_attributes includes finish_reason.""" from unittest.mock import Mock - from agent_framework import FinishReason from agent_framework.observability import OtelAttr, _get_response_attributes response = Mock() response.response_id = None - response.finish_reason = FinishReason.STOP + response.finish_reason = "stop" response.raw_representation = None response.usage_details = None @@ -1608,11 +1607,10 @@ def test_get_response_attributes_finish_reason_from_raw(): """Test _get_response_attributes gets finish_reason from raw_representation.""" from unittest.mock import Mock - from agent_framework import FinishReason from agent_framework.observability import OtelAttr, _get_response_attributes raw_rep = Mock() - raw_rep.finish_reason = FinishReason.LENGTH + raw_rep.finish_reason = "length" response = Mock() response.response_id = None @@ -1668,8 +1666,7 @@ async def run( **kwargs, ): return AgentResponse( - messages=[ChatMessage(role=Role.ASSISTANT, text="Test response")], - thread=thread, + messages=[ChatMessage("assistant", ["Test response"])], ) async def run_stream( @@ -1679,9 +1676,8 @@ async def run_stream( thread=None, **kwargs, ): - from agent_framework import AgentResponseUpdate - yield AgentResponseUpdate(text="Test", role=Role.ASSISTANT) + yield AgentResponseUpdate(contents=[Content.from_text(text="Test")], role="assistant") decorated_agent = use_agent_instrumentation(MockAgent) agent = decorated_agent() @@ -1697,7 +1693,6 @@ async def run_stream( @pytest.mark.parametrize("enable_sensitive_data", [True], indirect=True) async def test_agent_observability_with_exception(span_exporter: InMemorySpanExporter, enable_sensitive_data): """Test agent instrumentation captures exceptions.""" - from agent_framework import AgentResponseUpdate from agent_framework.observability import use_agent_instrumentation class FailingAgent(AgentProtocol): @@ -1730,7 +1725,7 @@ async def run(self, messages=None, *, thread=None, **kwargs): async def run_stream(self, messages=None, *, thread=None, **kwargs): # yield before raise to make this an async generator - yield AgentResponseUpdate(text="", role=Role.ASSISTANT) + yield AgentResponseUpdate(contents=[Content.from_text(text="")], role="assistant") raise RuntimeError("Agent failed") decorated_agent = use_agent_instrumentation(FailingAgent) @@ -1751,7 +1746,6 @@ async def run_stream(self, messages=None, *, thread=None, **kwargs): @pytest.mark.parametrize("enable_sensitive_data", [True, False], indirect=True) async def test_agent_streaming_observability(span_exporter: InMemorySpanExporter, enable_sensitive_data): """Test agent streaming instrumentation.""" - from agent_framework import AgentResponseUpdate from agent_framework.observability import use_agent_instrumentation class StreamingAgent(AgentProtocol): @@ -1781,13 +1775,12 @@ def default_options(self): async def run(self, messages=None, *, thread=None, **kwargs): return AgentResponse( - messages=[ChatMessage(role=Role.ASSISTANT, text="Test")], - thread=thread, + messages=[ChatMessage("assistant", ["Test"])], ) async def run_stream(self, messages=None, *, thread=None, **kwargs): - yield AgentResponseUpdate(text="Hello ", role=Role.ASSISTANT) - yield AgentResponseUpdate(text="World", role=Role.ASSISTANT) + yield AgentResponseUpdate(contents=[Content.from_text(text="Hello ")], role="assistant") + yield AgentResponseUpdate(contents=[Content.from_text(text="World")], role="assistant") decorated_agent = use_agent_instrumentation(StreamingAgent) agent = decorated_agent() @@ -1836,24 +1829,22 @@ async def test_capture_messages_with_finish_reason(mock_chat_client, span_export """Test that finish_reason is captured in output messages.""" import json - from agent_framework import FinishReason - class ClientWithFinishReason(mock_chat_client): async def _inner_get_response(self, *, messages, options, **kwargs): return ChatResponse( - messages=[ChatMessage(role=Role.ASSISTANT, text="Done")], + messages=[ChatMessage("assistant", ["Done"])], usage_details=UsageDetails(input_token_count=5, output_token_count=10), - finish_reason=FinishReason.STOP, + finish_reason="stop", ) client = use_instrumentation(ClientWithFinishReason)() - messages = [ChatMessage(role=Role.USER, text="Test")] + messages = [ChatMessage("user", ["Test"])] span_exporter.clear() response = await client.get_response(messages=messages, model_id="Test") assert response is not None - assert response.finish_reason == FinishReason.STOP + assert response.finish_reason == "stop" spans = span_exporter.get_finished_spans() assert len(spans) == 1 span = spans[0] @@ -1869,7 +1860,6 @@ async def _inner_get_response(self, *, messages, options, **kwargs): @pytest.mark.parametrize("enable_sensitive_data", [True], indirect=True) async def test_agent_streaming_exception(span_exporter: InMemorySpanExporter, enable_sensitive_data): """Test agent streaming captures exceptions.""" - from agent_framework import AgentResponseUpdate from agent_framework.observability import use_agent_instrumentation class FailingStreamingAgent(AgentProtocol): @@ -1898,10 +1888,10 @@ def default_options(self): return self._default_options async def run(self, messages=None, *, thread=None, **kwargs): - return AgentResponse(messages=[], thread=thread) + return AgentResponse(messages=[]) async def run_stream(self, messages=None, *, thread=None, **kwargs): - yield AgentResponseUpdate(text="Starting", role=Role.ASSISTANT) + yield AgentResponseUpdate(contents=[Content.from_text(text="Starting")], role="assistant") raise RuntimeError("Stream failed") decorated_agent = use_agent_instrumentation(FailingStreamingAgent) @@ -1924,7 +1914,7 @@ async def run_stream(self, messages=None, *, thread=None, **kwargs): async def test_chat_client_when_disabled(mock_chat_client, span_exporter: InMemorySpanExporter): """Test that no spans are created when instrumentation is disabled.""" client = use_instrumentation(mock_chat_client)() - messages = [ChatMessage(role=Role.USER, text="Test")] + messages = [ChatMessage("user", ["Test"])] span_exporter.clear() response = await client.get_response(messages=messages, model_id="Test") @@ -1939,7 +1929,7 @@ async def test_chat_client_when_disabled(mock_chat_client, span_exporter: InMemo async def test_chat_client_streaming_when_disabled(mock_chat_client, span_exporter: InMemorySpanExporter): """Test streaming creates no spans when instrumentation is disabled.""" client = use_instrumentation(mock_chat_client)() - messages = [ChatMessage(role=Role.USER, text="Test")] + messages = [ChatMessage("user", ["Test"])] span_exporter.clear() updates = [] @@ -1982,12 +1972,11 @@ def default_options(self): return self._default_options async def run(self, messages=None, *, thread=None, **kwargs): - return AgentResponse(messages=[], thread=thread) + return AgentResponse(messages=[]) async def run_stream(self, messages=None, *, thread=None, **kwargs): - from agent_framework import AgentResponseUpdate - yield AgentResponseUpdate(text="test", role=Role.ASSISTANT) + yield AgentResponseUpdate(contents=[Content.from_text(text="test")], role="assistant") decorated = use_agent_instrumentation(TestAgent) agent = decorated() @@ -2002,7 +1991,6 @@ async def run_stream(self, messages=None, *, thread=None, **kwargs): @pytest.mark.parametrize("enable_instrumentation", [False], indirect=True) async def test_agent_streaming_when_disabled(span_exporter: InMemorySpanExporter): """Test agent streaming creates no spans when disabled.""" - from agent_framework import AgentResponseUpdate from agent_framework.observability import use_agent_instrumentation class TestAgent(AgentProtocol): @@ -2031,10 +2019,10 @@ def default_options(self): return self._default_options async def run(self, messages=None, *, thread=None, **kwargs): - return AgentResponse(messages=[], thread=thread) + return AgentResponse(messages=[]) async def run_stream(self, messages=None, *, thread=None, **kwargs): - yield AgentResponseUpdate(text="test", role=Role.ASSISTANT) + yield AgentResponseUpdate(contents=[Content.from_text(text="test")], role="assistant") decorated = use_agent_instrumentation(TestAgent) agent = decorated() diff --git a/python/packages/core/tests/core/test_threads.py b/python/packages/core/tests/core/test_threads.py index 01d5ceb98f..241cbf4a90 100644 --- a/python/packages/core/tests/core/test_threads.py +++ b/python/packages/core/tests/core/test_threads.py @@ -5,7 +5,7 @@ import pytest -from agent_framework import AgentThread, ChatMessage, ChatMessageStore, Role +from agent_framework import AgentThread, ChatMessage, ChatMessageStore from agent_framework._threads import AgentThreadState, ChatMessageStoreState from agent_framework.exceptions import AgentThreadException @@ -44,16 +44,16 @@ async def deserialize(cls, serialized_store_state: Any, **kwargs: Any) -> "MockC def sample_messages() -> list[ChatMessage]: """Fixture providing sample chat messages for testing.""" return [ - ChatMessage(role=Role.USER, text="Hello", message_id="msg1"), - ChatMessage(role=Role.ASSISTANT, text="Hi there!", message_id="msg2"), - ChatMessage(role=Role.USER, text="How are you?", message_id="msg3"), + ChatMessage("user", ["Hello"], message_id="msg1"), + ChatMessage("assistant", ["Hi there!"], message_id="msg2"), + ChatMessage("user", ["How are you?"], message_id="msg3"), ] @pytest.fixture def sample_message() -> ChatMessage: """Fixture providing a single sample chat message for testing.""" - return ChatMessage(role=Role.USER, text="Test message", message_id="test1") + return ChatMessage("user", ["Test message"], message_id="test1") class TestAgentThread: @@ -178,7 +178,7 @@ async def test_on_new_messages_multiple_messages(self, sample_messages: list[Cha async def test_on_new_messages_with_existing_store(self, sample_message: ChatMessage) -> None: """Test _on_new_messages adds to existing message store.""" - initial_messages = [ChatMessage(role=Role.USER, text="Initial", message_id="init1")] + initial_messages = [ChatMessage("user", ["Initial"], message_id="init1")] store = ChatMessageStore(initial_messages) thread = AgentThread(message_store=store) @@ -226,7 +226,7 @@ async def test_deserialize_with_existing_store(self) -> None: thread = AgentThread(message_store=store) serialized_data: dict[str, Any] = { "service_thread_id": None, - "chat_message_store_state": {"messages": [ChatMessage(role="user", text="test")]}, + "chat_message_store_state": {"messages": [ChatMessage("user", ["test"])]}, } await thread.update_from_thread_state(serialized_data) @@ -449,7 +449,7 @@ def test_init_with_chat_message_store_state_no_messages(self) -> None: def test_init_with_chat_message_store_state_object(self) -> None: """Test AgentThreadState initialization with ChatMessageStoreState object.""" - store_state = ChatMessageStoreState(messages=[ChatMessage(role=Role.USER, text="test")]) + store_state = ChatMessageStoreState(messages=[ChatMessage("user", ["test"])]) state = AgentThreadState(chat_message_store_state=store_state) assert state.service_thread_id is None diff --git a/python/packages/core/tests/core/test_tools.py b/python/packages/core/tests/core/test_tools.py index a60018c7a4..9187c9f0f3 100644 --- a/python/packages/core/tests/core/test_tools.py +++ b/python/packages/core/tests/core/test_tools.py @@ -959,7 +959,7 @@ async def get_response(self, messages, **kwargs): return response # Default response return ChatResponse( - messages=[ChatMessage(role="assistant", contents=["Default response"])], + messages=[ChatMessage("assistant", ["Default response"])], ) async def get_streaming_response(self, messages, **kwargs): @@ -973,7 +973,7 @@ async def get_streaming_response(self, messages, **kwargs): yield ChatResponseUpdate(contents=[content], role=msg.role) else: # Default response - yield ChatResponseUpdate(text="Default response", role="assistant") + yield ChatResponseUpdate(contents=[Content.from_text(text="Default response")], role="assistant") return MockChatClient() @@ -1015,7 +1015,7 @@ async def test_non_streaming_single_function_no_approval(): ) ] ) - final_response = ChatResponse(messages=[ChatMessage(role="assistant", text="The result is 10")]) + final_response = ChatResponse(messages=[ChatMessage("assistant", ["The result is 10"])]) call_count = [0] responses = [initial_response, final_response] @@ -1100,7 +1100,7 @@ async def test_non_streaming_two_functions_both_no_approval(): ) ] ) - final_response = ChatResponse(messages=[ChatMessage(role="assistant", text="Both tools executed successfully")]) + final_response = ChatResponse(messages=[ChatMessage("assistant", ["Both tools executed successfully"])]) call_count = [0] responses = [initial_response, final_response] @@ -1227,7 +1227,7 @@ async def test_streaming_single_function_no_approval(): role="assistant", ) ] - final_updates = [ChatResponseUpdate(text="The result is 10", role="assistant")] + final_updates = [ChatResponseUpdate(contents=[Content.from_text(text="The result is 10")], role="assistant")] call_count = [0] updates_list = [initial_updates, final_updates] @@ -1246,13 +1246,12 @@ async def mock_get_streaming_response(self, messages, **kwargs): updates.append(update) # Verify: should have function call update, tool result update (injected), and final update - from agent_framework import Role assert len(updates) >= 3 # First update is the function call assert updates[0].contents[0].type == "function_call" # Second update should be the tool result (injected by the wrapper) - assert updates[1].role == Role.TOOL + assert updates[1].role == "tool" assert updates[1].contents[0].type == "function_result" assert updates[1].contents[0].result == 10 # 5 * 2 # Last update is the final message @@ -1294,11 +1293,10 @@ async def mock_get_streaming_response(self, messages, **kwargs): updates.append(update) # Verify: should yield function call and then approval request - from agent_framework import Role assert len(updates) == 2 assert updates[0].contents[0].type == "function_call" - assert updates[1].role == Role.ASSISTANT + assert updates[1].role == "assistant" assert updates[1].contents[0].type == "function_approval_request" @@ -1319,7 +1317,9 @@ async def test_streaming_two_functions_both_no_approval(): role="assistant", ), ] - final_updates = [ChatResponseUpdate(text="Both tools executed successfully", role="assistant")] + final_updates = [ + ChatResponseUpdate(contents=[Content.from_text(text="Both tools executed successfully")], role="assistant") + ] call_count = [0] updates_list = [initial_updates, final_updates] @@ -1338,7 +1338,6 @@ async def mock_get_streaming_response(self, messages, **kwargs): updates.append(update) # Verify: should have both function calls, one tool result update with both results, and final message - from agent_framework import Role assert len(updates) >= 2 # First update has both function calls @@ -1346,7 +1345,7 @@ async def mock_get_streaming_response(self, messages, **kwargs): assert updates[0].contents[0].type == "function_call" assert updates[0].contents[1].type == "function_call" # Should have a tool result update with both results - tool_updates = [u for u in updates if u.role == Role.TOOL] + tool_updates = [u for u in updates if u.role == "tool"] assert len(tool_updates) == 1 assert len(tool_updates[0].contents) == 2 assert all(c.type == "function_result" for c in tool_updates[0].contents) @@ -1392,13 +1391,12 @@ async def mock_get_streaming_response(self, messages, **kwargs): updates.append(update) # Verify: should yield both function calls and then approval requests - from agent_framework import Role assert len(updates) == 3 assert updates[0].contents[0].type == "function_call" assert updates[1].contents[0].type == "function_call" # Assistant update with both approval requests - assert updates[2].role == Role.ASSISTANT + assert updates[2].role == "assistant" assert len(updates[2].contents) == 2 assert all(c.type == "function_approval_request" for c in updates[2].contents) @@ -1443,13 +1441,12 @@ async def mock_get_streaming_response(self, messages, **kwargs): updates.append(update) # Verify: should yield both function calls and then approval requests (when one needs approval, all wait) - from agent_framework import Role assert len(updates) == 3 assert updates[0].contents[0].type == "function_call" assert updates[1].contents[0].type == "function_call" # Assistant update with both approval requests - assert updates[2].role == Role.ASSISTANT + assert updates[2].role == "assistant" assert len(updates[2].contents) == 2 assert all(c.type == "function_approval_request" for c in updates[2].contents) diff --git a/python/packages/core/tests/core/test_types.py b/python/packages/core/tests/core/test_types.py index 8236d75d20..3e7e435077 100644 --- a/python/packages/core/tests/core/test_types.py +++ b/python/packages/core/tests/core/test_types.py @@ -19,8 +19,6 @@ ChatResponse, ChatResponseUpdate, Content, - FinishReason, - Role, TextSpanRegion, ToolMode, ToolProtocol, @@ -36,6 +34,8 @@ _parse_content_list, _validate_uri, add_usage_details, + normalize_messages, + prepare_messages, validate_tool_mode, ) from agent_framework.exceptions import ContentError @@ -573,10 +573,10 @@ def test_ai_content_serialization(args: dict): def test_chat_message_text(): """Test the ChatMessage class to ensure it initializes correctly with text content.""" # Create a ChatMessage with a role and text content - message = ChatMessage(role="user", text="Hello, how are you?") + message = ChatMessage("user", ["Hello, how are you?"]) # Check the type and content - assert message.role == Role.USER + assert message.role == "user" assert len(message.contents) == 1 assert message.contents[0].type == "text" assert message.contents[0].text == "Hello, how are you?" @@ -591,10 +591,10 @@ def test_chat_message_contents(): # Create a ChatMessage with a role and multiple contents content1 = Content.from_text("Hello, how are you?") content2 = Content.from_text("I'm fine, thank you!") - message = ChatMessage(role="user", contents=[content1, content2]) + message = ChatMessage("user", [content1, content2]) # Check the type and content - assert message.role == Role.USER + assert message.role == "user" assert len(message.contents) == 2 assert message.contents[0].type == "text" assert message.contents[1].type == "text" @@ -604,8 +604,8 @@ def test_chat_message_contents(): def test_chat_message_with_chatrole_instance(): - m = ChatMessage(role=Role.USER, text="hi") - assert m.role == Role.USER + m = ChatMessage("user", ["hi"]) + assert m.role == "user" assert m.text == "hi" @@ -615,13 +615,13 @@ def test_chat_message_with_chatrole_instance(): def test_chat_response(): """Test the ChatResponse class to ensure it initializes correctly with a message.""" # Create a ChatMessage - message = ChatMessage(role="assistant", text="I'm doing well, thank you!") + message = ChatMessage("assistant", ["I'm doing well, thank you!"]) # Create a ChatResponse with the message response = ChatResponse(messages=message) # Check the type and content - assert response.messages[0].role == Role.ASSISTANT + assert response.messages[0].role == "assistant" assert response.messages[0].text == "I'm doing well, thank you!" assert isinstance(response.messages[0], ChatMessage) # __str__ returns text @@ -635,32 +635,30 @@ class OutputModel(BaseModel): def test_chat_response_with_format(): """Test the ChatResponse class to ensure it initializes correctly with a message.""" # Create a ChatMessage - message = ChatMessage(role="assistant", text='{"response": "Hello"}') + message = ChatMessage("assistant", ['{"response": "Hello"}']) # Create a ChatResponse with the message response = ChatResponse(messages=message) # Check the type and content - assert response.messages[0].role == Role.ASSISTANT + assert response.messages[0].role == "assistant" assert response.messages[0].text == '{"response": "Hello"}' assert isinstance(response.messages[0], ChatMessage) assert response.text == '{"response": "Hello"}' + # Since no response_format was provided, value is None and accessing it returns None assert response.value is None - response.try_parse_value(OutputModel) - assert response.value is not None - assert response.value.response == "Hello" def test_chat_response_with_format_init(): """Test the ChatResponse class to ensure it initializes correctly with a message.""" # Create a ChatMessage - message = ChatMessage(role="assistant", text='{"response": "Hello"}') + message = ChatMessage("assistant", ['{"response": "Hello"}']) # Create a ChatResponse with the message response = ChatResponse(messages=message, response_format=OutputModel) # Check the type and content - assert response.messages[0].role == Role.ASSISTANT + assert response.messages[0].role == "assistant" assert response.messages[0].text == '{"response": "Hello"}' assert isinstance(response.messages[0], ChatMessage) assert response.text == '{"response": "Hello"}' @@ -676,7 +674,7 @@ class StrictSchema(BaseModel): name: str = Field(min_length=10) score: int = Field(gt=0, le=100) - message = ChatMessage(role="assistant", text='{"id": 1, "name": "test", "score": -5}') + message = ChatMessage("assistant", ['{"id": 1, "name": "test", "score": -5}']) response = ChatResponse(messages=message, response_format=StrictSchema) with raises(ValidationError) as exc_info: @@ -689,32 +687,17 @@ class StrictSchema(BaseModel): assert "score" in error_fields, "Expected 'score' gt constraint error" -def test_chat_response_try_parse_value_returns_none_on_invalid(): - """Test that try_parse_value returns None on validation failure with Field constraints.""" - - class StrictSchema(BaseModel): - id: Literal[5] - name: str = Field(min_length=10) - score: int = Field(gt=0, le=100) - - message = ChatMessage(role="assistant", text='{"id": 1, "name": "test", "score": -5}') - response = ChatResponse(messages=message) - - result = response.try_parse_value(StrictSchema) - assert result is None - - -def test_chat_response_try_parse_value_returns_value_on_success(): - """Test that try_parse_value returns parsed value when all constraints pass.""" +def test_chat_response_value_with_valid_schema(): + """Test that value property returns parsed value when all constraints pass.""" class MySchema(BaseModel): name: str = Field(min_length=3) score: int = Field(ge=0, le=100) - message = ChatMessage(role="assistant", text='{"name": "test", "score": 85}') - response = ChatResponse(messages=message) + message = ChatMessage("assistant", ['{"name": "test", "score": 85}']) + response = ChatResponse(messages=message, response_format=MySchema) - result = response.try_parse_value(MySchema) + result = response.value assert result is not None assert result.name == "test" assert result.score == 85 @@ -728,7 +711,7 @@ class StrictSchema(BaseModel): name: str = Field(min_length=10) score: int = Field(gt=0, le=100) - message = ChatMessage(role="assistant", text='{"id": 1, "name": "test", "score": -5}') + message = ChatMessage("assistant", ['{"id": 1, "name": "test", "score": -5}']) response = AgentResponse(messages=message, response_format=StrictSchema) with raises(ValidationError) as exc_info: @@ -741,32 +724,17 @@ class StrictSchema(BaseModel): assert "score" in error_fields, "Expected 'score' gt constraint error" -def test_agent_response_try_parse_value_returns_none_on_invalid(): - """Test that AgentResponse.try_parse_value returns None on Field constraint failure.""" - - class StrictSchema(BaseModel): - id: Literal[5] - name: str = Field(min_length=10) - score: int = Field(gt=0, le=100) - - message = ChatMessage(role="assistant", text='{"id": 1, "name": "test", "score": -5}') - response = AgentResponse(messages=message) - - result = response.try_parse_value(StrictSchema) - assert result is None - - -def test_agent_response_try_parse_value_returns_value_on_success(): - """Test that AgentResponse.try_parse_value returns parsed value when all constraints pass.""" +def test_agent_response_value_with_valid_schema(): + """Test that AgentResponse.value property returns parsed value when all constraints pass.""" class MySchema(BaseModel): name: str = Field(min_length=3) score: int = Field(ge=0, le=100) - message = ChatMessage(role="assistant", text='{"name": "test", "score": 85}') - response = AgentResponse(messages=message) + message = ChatMessage("assistant", ['{"name": "test", "score": 85}']) + response = AgentResponse(messages=message, response_format=MySchema) - result = response.try_parse_value(MySchema) + result = response.value assert result is not None assert result.name == "test" assert result.score == 85 @@ -797,12 +765,12 @@ def test_chat_response_updates_to_chat_response_one(): # Create a ChatResponseUpdate with the message response_updates = [ - ChatResponseUpdate(text=message1, message_id="1"), - ChatResponseUpdate(text=message2, message_id="1"), + ChatResponseUpdate(contents=[message1], message_id="1"), + ChatResponseUpdate(contents=[message2], message_id="1"), ] # Convert to ChatResponse - chat_response = ChatResponse.from_chat_response_updates(response_updates) + chat_response = ChatResponse.from_updates(response_updates) # Check the type and content assert len(chat_response.messages) == 1 @@ -820,12 +788,12 @@ def test_chat_response_updates_to_chat_response_two(): # Create a ChatResponseUpdate with the message response_updates = [ - ChatResponseUpdate(text=message1, message_id="1"), - ChatResponseUpdate(text=message2, message_id="2"), + ChatResponseUpdate(contents=[message1], message_id="1"), + ChatResponseUpdate(contents=[message2], message_id="2"), ] # Convert to ChatResponse - chat_response = ChatResponse.from_chat_response_updates(response_updates) + chat_response = ChatResponse.from_updates(response_updates) # Check the type and content assert len(chat_response.messages) == 2 @@ -844,13 +812,13 @@ def test_chat_response_updates_to_chat_response_multiple(): # Create a ChatResponseUpdate with the message response_updates = [ - ChatResponseUpdate(text=message1, message_id="1"), + ChatResponseUpdate(contents=[message1], message_id="1"), ChatResponseUpdate(contents=[Content.from_text_reasoning(text="Additional context")], message_id="1"), - ChatResponseUpdate(text=message2, message_id="1"), + ChatResponseUpdate(contents=[message2], message_id="1"), ] # Convert to ChatResponse - chat_response = ChatResponse.from_chat_response_updates(response_updates) + chat_response = ChatResponse.from_updates(response_updates) # Check the type and content assert len(chat_response.messages) == 1 @@ -868,15 +836,15 @@ def test_chat_response_updates_to_chat_response_multiple_multiple(): # Create a ChatResponseUpdate with the message response_updates = [ - ChatResponseUpdate(text=message1, message_id="1"), - ChatResponseUpdate(text=message2, message_id="1"), + ChatResponseUpdate(contents=[message1], message_id="1"), + ChatResponseUpdate(contents=[message2], message_id="1"), ChatResponseUpdate(contents=[Content.from_text_reasoning(text="Additional context")], message_id="1"), ChatResponseUpdate(contents=[Content.from_text(text="More context")], message_id="1"), - ChatResponseUpdate(text="Final part", message_id="1"), + ChatResponseUpdate(contents=[Content.from_text(text="Final part")], message_id="1"), ] # Convert to ChatResponse - chat_response = ChatResponse.from_chat_response_updates(response_updates) + chat_response = ChatResponse.from_updates(response_updates) # Check the type and content assert len(chat_response.messages) == 1 @@ -897,32 +865,30 @@ def test_chat_response_updates_to_chat_response_multiple_multiple(): async def test_chat_response_from_async_generator(): async def gen() -> AsyncIterable[ChatResponseUpdate]: - yield ChatResponseUpdate(text="Hello", message_id="1") - yield ChatResponseUpdate(text=" world", message_id="1") + yield ChatResponseUpdate(contents=[Content.from_text(text="Hello")], message_id="1") + yield ChatResponseUpdate(contents=[Content.from_text(text=" world")], message_id="1") - resp = await ChatResponse.from_chat_response_generator(gen()) + resp = await ChatResponse.from_update_generator(gen()) assert resp.text == "Hello world" async def test_chat_response_from_async_generator_output_format(): async def gen() -> AsyncIterable[ChatResponseUpdate]: - yield ChatResponseUpdate(text='{ "respon', message_id="1") - yield ChatResponseUpdate(text='se": "Hello" }', message_id="1") + yield ChatResponseUpdate(contents=[Content.from_text(text='{ "respon')], message_id="1") + yield ChatResponseUpdate(contents=[Content.from_text(text='se": "Hello" }')], message_id="1") - resp = await ChatResponse.from_chat_response_generator(gen()) + # Note: Without output_format_type, value is None and we cannot parse + resp = await ChatResponse.from_update_generator(gen()) assert resp.text == '{ "response": "Hello" }' assert resp.value is None - resp.try_parse_value(OutputModel) - assert resp.value is not None - assert resp.value.response == "Hello" async def test_chat_response_from_async_generator_output_format_in_method(): async def gen() -> AsyncIterable[ChatResponseUpdate]: - yield ChatResponseUpdate(text='{ "respon', message_id="1") - yield ChatResponseUpdate(text='se": "Hello" }', message_id="1") + yield ChatResponseUpdate(contents=[Content.from_text(text='{ "respon')], message_id="1") + yield ChatResponseUpdate(contents=[Content.from_text(text='se": "Hello" }')], message_id="1") - resp = await ChatResponse.from_chat_response_generator(gen(), output_format_type=OutputModel) + resp = await ChatResponse.from_update_generator(gen(), output_format_type=OutputModel) assert resp.text == '{ "response": "Hello" }' assert resp.value is not None assert resp.value.response == "Hello" @@ -1080,7 +1046,7 @@ def test_chat_options_and_tool_choice_required_specific_function() -> None: @fixture def chat_message() -> ChatMessage: - return ChatMessage(role=Role.USER, text="Hello") + return ChatMessage("user", ["Hello"]) @fixture @@ -1095,7 +1061,7 @@ def agent_response(chat_message: ChatMessage) -> AgentResponse: @fixture def agent_response_update(text_content: Content) -> AgentResponseUpdate: - return AgentResponseUpdate(role=Role.ASSISTANT, contents=[text_content]) + return AgentResponseUpdate(role="assistant", contents=[text_content]) # region AgentResponse @@ -1129,7 +1095,7 @@ def test_agent_run_response_text_property_empty() -> None: def test_agent_run_response_from_updates(agent_response_update: AgentResponseUpdate) -> None: updates = [agent_response_update, agent_response_update] - response = AgentResponse.from_agent_run_response_updates(updates) + response = AgentResponse.from_updates(updates) assert len(response.messages) > 0 assert response.text == "Test contentTest content" @@ -1174,7 +1140,7 @@ def test_agent_run_response_update_created_at() -> None: utc_timestamp = "2024-12-01T00:31:30.000000Z" update = AgentResponseUpdate( contents=[Content.from_text(text="test")], - role=Role.ASSISTANT, + role="assistant", created_at=utc_timestamp, ) assert update.created_at == utc_timestamp @@ -1185,7 +1151,7 @@ def test_agent_run_response_update_created_at() -> None: formatted_utc = now_utc.strftime("%Y-%m-%dT%H:%M:%S.%fZ") update_with_now = AgentResponseUpdate( contents=[Content.from_text(text="test")], - role=Role.ASSISTANT, + role="assistant", created_at=formatted_utc, ) assert update_with_now.created_at == formatted_utc @@ -1197,7 +1163,7 @@ def test_agent_run_response_created_at() -> None: # Test with a properly formatted UTC timestamp utc_timestamp = "2024-12-01T00:31:30.000000Z" response = AgentResponse( - messages=[ChatMessage(role=Role.ASSISTANT, text="Hello")], + messages=[ChatMessage("assistant", ["Hello"])], created_at=utc_timestamp, ) assert response.created_at == utc_timestamp @@ -1207,7 +1173,7 @@ def test_agent_run_response_created_at() -> None: now_utc = datetime.now(tz=timezone.utc) formatted_utc = now_utc.strftime("%Y-%m-%dT%H:%M:%S.%fZ") response_with_now = AgentResponse( - messages=[ChatMessage(role=Role.ASSISTANT, text="Hello")], + messages=[ChatMessage("assistant", ["Hello"])], created_at=formatted_utc, ) assert response_with_now.created_at == formatted_utc @@ -1271,7 +1237,7 @@ def test_function_call_merge_in_process_update_and_usage_aggregation(): # plus usage u3 = ChatResponseUpdate(contents=[Content.from_usage(UsageDetails(input_token_count=1, output_token_count=2))]) - resp = ChatResponse.from_chat_response_updates([u1, u2, u3]) + resp = ChatResponse.from_updates([u1, u2, u3]) assert len(resp.messages) == 1 last_contents = resp.messages[0].contents assert any(c.type == "function_call" for c in last_contents) @@ -1287,7 +1253,7 @@ def test_function_call_incompatible_ids_are_not_merged(): u1 = ChatResponseUpdate(contents=[Content.from_function_call(call_id="a", name="f", arguments="x")], message_id="m") u2 = ChatResponseUpdate(contents=[Content.from_function_call(call_id="b", name="f", arguments="y")], message_id="m") - resp = ChatResponse.from_chat_response_updates([u1, u2]) + resp = ChatResponse.from_updates([u1, u2]) fcs = [c for c in resp.messages[0].contents if c.type == "function_call"] assert len(fcs) == 2 @@ -1295,18 +1261,23 @@ def test_function_call_incompatible_ids_are_not_merged(): # region Role & FinishReason basics -def test_chat_role_str_and_repr(): - assert str(Role.USER) == "user" - assert "Role(value=" in repr(Role.USER) +def test_chat_role_is_string(): + """Role is now a NewType of str, so roles are just strings.""" + role = "user" + assert role == "user" + assert isinstance(role, str) -def test_chat_finish_reason_constants(): - assert FinishReason.STOP.value == "stop" +def test_chat_finish_reason_is_string(): + """FinishReason is now a NewType of str, so finish reasons are just strings.""" + finish_reason = "stop" + assert finish_reason == "stop" + assert isinstance(finish_reason, str) def test_response_update_propagates_fields_and_metadata(): upd = ChatResponseUpdate( - text="hello", + contents=[Content.from_text(text="hello")], role="assistant", author_name="bot", response_id="rid", @@ -1314,17 +1285,17 @@ def test_response_update_propagates_fields_and_metadata(): conversation_id="cid", model_id="model-x", created_at="t0", - finish_reason=FinishReason.STOP, + finish_reason="stop", additional_properties={"k": "v"}, ) - resp = ChatResponse.from_chat_response_updates([upd]) + resp = ChatResponse.from_updates([upd]) assert resp.response_id == "rid" assert resp.created_at == "t0" assert resp.conversation_id == "cid" assert resp.model_id == "model-x" - assert resp.finish_reason == FinishReason.STOP + assert resp.finish_reason == "stop" assert resp.additional_properties and resp.additional_properties["k"] == "v" - assert resp.messages[0].role == Role.ASSISTANT + assert resp.messages[0].role == "assistant" assert resp.messages[0].author_name == "bot" assert resp.messages[0].message_id == "mid" @@ -1332,9 +1303,9 @@ def test_response_update_propagates_fields_and_metadata(): def test_text_coalescing_preserves_first_properties(): t1 = Content.from_text("A", raw_representation={"r": 1}, additional_properties={"p": 1}) t2 = Content.from_text("B") - upd1 = ChatResponseUpdate(text=t1, message_id="x") - upd2 = ChatResponseUpdate(text=t2, message_id="x") - resp = ChatResponse.from_chat_response_updates([upd1, upd2]) + upd1 = ChatResponseUpdate(contents=[t1], message_id="x") + upd2 = ChatResponseUpdate(contents=[t2], message_id="x") + resp = ChatResponse.from_updates([upd1, upd2]) # After coalescing there should be a single TextContent with merged text and preserved props from first items = [c for c in resp.messages[0].contents if c.type == "text"] assert len(items) >= 1 @@ -1359,7 +1330,7 @@ def test_chat_tool_mode_eq_with_string(): @fixture def agent_run_response_async() -> AgentResponse: - return AgentResponse(messages=[ChatMessage(role="user", text="Hello")]) + return AgentResponse(messages=[ChatMessage("user", ["Hello"])]) async def test_agent_run_response_from_async_generator(): @@ -1587,7 +1558,7 @@ def test_chat_message_complex_content_serialization(): Content.from_function_result(call_id="call1", result="success"), ] - message = ChatMessage(role=Role.ASSISTANT, contents=contents) + message = ChatMessage("assistant", contents) # Test to_dict message_dict = message.to_dict() @@ -1663,7 +1634,7 @@ def test_chat_response_complex_serialization(): {"role": "user", "contents": [{"type": "text", "text": "Hello"}]}, {"role": "assistant", "contents": [{"type": "text", "text": "Hi there"}]}, ], - "finish_reason": {"value": "stop"}, + "finish_reason": "stop", "usage_details": { "type": "usage_details", "input_token_count": 5, @@ -1676,7 +1647,7 @@ def test_chat_response_complex_serialization(): response = ChatResponse.from_dict(response_data) assert len(response.messages) == 2 assert isinstance(response.messages[0], ChatMessage) - assert isinstance(response.finish_reason, FinishReason) + assert isinstance(response.finish_reason, str) assert isinstance(response.usage_details, dict) assert response.model_id == "gpt-4" # Should be stored as model_id @@ -1684,7 +1655,7 @@ def test_chat_response_complex_serialization(): response_dict = response.to_dict() assert len(response_dict["messages"]) == 2 assert isinstance(response_dict["messages"][0], dict) - assert isinstance(response_dict["finish_reason"], dict) + assert isinstance(response_dict["finish_reason"], str) assert isinstance(response_dict["usage_details"], dict) assert response_dict["model_id"] == "gpt-4" # Should serialize as model_id @@ -1794,20 +1765,20 @@ def test_agent_run_response_update_all_content_types(): update = AgentResponseUpdate.from_dict(update_data) assert len(update.contents) == 12 # unknown_type is logged and ignored - assert isinstance(update.role, Role) - assert update.role.value == "assistant" + assert isinstance(update.role, str) + assert update.role == "assistant" # Test to_dict with role conversion update_dict = update.to_dict() assert len(update_dict["contents"]) == 12 # unknown_type was ignored during from_dict - assert isinstance(update_dict["role"], dict) + assert isinstance(update_dict["role"], str) # Test role as string conversion update_data_str_role = update_data.copy() update_data_str_role["role"] = "user" update_str = AgentResponseUpdate.from_dict(update_data_str_role) - assert isinstance(update_str.role, Role) - assert update_str.role.value == "user" + assert isinstance(update_str.role, str) + assert update_str.role == "user" # region Serialization @@ -1936,7 +1907,7 @@ def test_agent_run_response_update_all_content_types(): pytest.param( ChatMessage, { - "role": {"type": "role", "value": "user"}, + "role": "user", "contents": [ {"type": "text", "text": "Hello"}, {"type": "function_call", "call_id": "call-1", "name": "test_func", "arguments": {}}, @@ -1953,16 +1924,16 @@ def test_agent_run_response_update_all_content_types(): "messages": [ { "type": "chat_message", - "role": {"type": "role", "value": "user"}, + "role": "user", "contents": [{"type": "text", "text": "Hello"}], }, { "type": "chat_message", - "role": {"type": "role", "value": "assistant"}, + "role": "assistant", "contents": [{"type": "text", "text": "Hi there"}], }, ], - "finish_reason": {"type": "finish_reason", "value": "stop"}, + "finish_reason": "stop", "usage_details": { "type": "usage_details", "input_token_count": 10, @@ -1981,8 +1952,8 @@ def test_agent_run_response_update_all_content_types(): {"type": "text", "text": "Hello"}, {"type": "function_call", "call_id": "call-1", "name": "test_func", "arguments": {}}, ], - "role": {"type": "role", "value": "assistant"}, - "finish_reason": {"type": "finish_reason", "value": "stop"}, + "role": "assistant", + "finish_reason": "stop", "message_id": "msg-123", "response_id": "resp-123", }, @@ -1993,11 +1964,11 @@ def test_agent_run_response_update_all_content_types(): { "messages": [ { - "role": {"type": "role", "value": "user"}, + "role": "user", "contents": [{"type": "text", "text": "Question"}], }, { - "role": {"type": "role", "value": "assistant"}, + "role": "assistant", "contents": [{"type": "text", "text": "Answer"}], }, ], @@ -2018,7 +1989,7 @@ def test_agent_run_response_update_all_content_types(): {"type": "text", "text": "Streaming"}, {"type": "function_call", "call_id": "call-1", "name": "test_func", "arguments": {}}, ], - "role": {"type": "role", "value": "assistant"}, + "role": "assistant", "message_id": "msg-123", "response_id": "run-123", "author_name": "Agent", @@ -2519,3 +2490,1046 @@ def test_validate_uri_data_uri(): # endregion + + +# region Test normalize_messages and prepare_messages with Content + + +def test_normalize_messages_with_string(): + """Test normalize_messages converts a string to a user message.""" + result = normalize_messages("hello") + assert len(result) == 1 + assert result[0].role == "user" + assert result[0].text == "hello" + + +def test_normalize_messages_with_content(): + """Test normalize_messages converts a Content object to a user message.""" + content = Content.from_text("hello") + result = normalize_messages(content) + assert len(result) == 1 + assert result[0].role == "user" + assert len(result[0].contents) == 1 + assert result[0].contents[0].text == "hello" + + +def test_normalize_messages_with_sequence_including_content(): + """Test normalize_messages handles a sequence with Content objects.""" + content = Content.from_text("image caption") + msg = ChatMessage("assistant", ["response"]) + result = normalize_messages(["query", content, msg]) + assert len(result) == 3 + assert result[0].role == "user" + assert result[0].text == "query" + assert result[1].role == "user" + assert result[1].contents[0].text == "image caption" + assert result[2].role == "assistant" + assert result[2].text == "response" + + +def test_prepare_messages_with_content(): + """Test prepare_messages converts a Content object to a user message.""" + content = Content.from_text("hello") + result = prepare_messages(content) + assert len(result) == 1 + assert result[0].role == "user" + assert result[0].contents[0].text == "hello" + + +def test_prepare_messages_with_content_and_system_instructions(): + """Test prepare_messages handles Content with system instructions.""" + content = Content.from_text("hello") + result = prepare_messages(content, system_instructions="Be helpful") + assert len(result) == 2 + assert result[0].role == "system" + assert result[0].text == "Be helpful" + assert result[1].role == "user" + assert result[1].contents[0].text == "hello" + + +def test_parse_content_list_with_strings(): + """Test _parse_content_list converts strings to TextContent.""" + result = _parse_content_list(["hello", "world"]) + assert len(result) == 2 + assert result[0].type == "text" + assert result[0].text == "hello" + assert result[1].type == "text" + assert result[1].text == "world" + + +def test_parse_content_list_with_none_values(): + """Test _parse_content_list skips None values.""" + result = _parse_content_list(["hello", None, "world", None]) + assert len(result) == 2 + assert result[0].text == "hello" + assert result[1].text == "world" + + +def test_parse_content_list_with_invalid_dict(): + """Test _parse_content_list raises on invalid content dict missing type.""" + # Invalid dict without type raises ValueError + with pytest.raises(ValueError, match="requires 'type'"): + _parse_content_list([{"invalid": "data"}]) + + +# region detect_media_type_from_base64 additional formats + + +def test_detect_media_type_gif87a(): + """Test detecting GIF87a format.""" + gif_data = b"GIF87a" + b"fake_data" + assert detect_media_type_from_base64(data_bytes=gif_data) == "image/gif" + + +def test_detect_media_type_bmp(): + """Test detecting BMP format.""" + bmp_data = b"BM" + b"fake_data" + assert detect_media_type_from_base64(data_bytes=bmp_data) == "image/bmp" + + +def test_detect_media_type_svg(): + """Test detecting SVG format.""" + svg_data = b" int: + """A simple function.""" + return x * 2 + + result = normalize_tools(my_func) + assert len(result) == 1 + assert hasattr(result[0], "name") + + +def test_normalize_tools_list_of_callables(): + """Test normalize_tools with list of callables.""" + from agent_framework._types import normalize_tools + + def func1(x: int) -> int: + """Function 1.""" + return x + + def func2(y: str) -> str: + """Function 2.""" + return y + + result = normalize_tools([func1, func2]) + assert len(result) == 2 + + +def test_normalize_tools_single_mapping(): + """Test normalize_tools with single mapping (not treated as sequence).""" + from agent_framework._types import normalize_tools + + tool_dict = {"name": "test_tool", "description": "A test tool"} + result = normalize_tools(tool_dict) + assert len(result) == 1 + assert result[0] == tool_dict + + +# region validate_tool_mode edge cases + + +def test_validate_tool_mode_dict_missing_mode(): + """Test validate_tool_mode with dict missing mode key.""" + with pytest.raises(ContentError, match="must contain 'mode' key"): + validate_tool_mode({"required_function_name": "test"}) + + +def test_validate_tool_mode_dict_invalid_mode(): + """Test validate_tool_mode with dict having invalid mode.""" + with pytest.raises(ContentError, match="Invalid tool choice"): + validate_tool_mode({"mode": "invalid"}) + + +def test_validate_tool_mode_dict_required_function_with_wrong_mode(): + """Test validate_tool_mode with required_function_name but wrong mode.""" + with pytest.raises(ContentError, match="cannot have 'required_function_name'"): + validate_tool_mode({"mode": "auto", "required_function_name": "test"}) + + +def test_validate_tool_mode_dict_valid_required(): + """Test validate_tool_mode with valid required mode and function name.""" + result = validate_tool_mode({"mode": "required", "required_function_name": "test"}) + assert result["mode"] == "required" + assert result["required_function_name"] == "test" + + +# region merge_chat_options edge cases + + +def test_merge_chat_options_instructions_concatenation(): + """Test merge_chat_options concatenates instructions.""" + base: ChatOptions = {"instructions": "Base instructions"} + override: ChatOptions = {"instructions": "Override instructions"} + result = merge_chat_options(base, override) + assert "Base instructions" in result["instructions"] + assert "Override instructions" in result["instructions"] + + +def test_merge_chat_options_tools_merge(): + """Test merge_chat_options merges tools lists.""" + + @tool + def tool1(x: int) -> int: + """Tool 1.""" + return x + + @tool + def tool2(y: int) -> int: + """Tool 2.""" + return y + + base: ChatOptions = {"tools": [tool1]} + override: ChatOptions = {"tools": [tool2]} + result = merge_chat_options(base, override) + assert len(result["tools"]) == 2 + + +def test_merge_chat_options_metadata_merge(): + """Test merge_chat_options merges metadata dicts.""" + base: ChatOptions = {"metadata": {"key1": "value1"}} + override: ChatOptions = {"metadata": {"key2": "value2"}} + result = merge_chat_options(base, override) + assert result["metadata"]["key1"] == "value1" + assert result["metadata"]["key2"] == "value2" + + +def test_merge_chat_options_tool_choice_override(): + """Test merge_chat_options overrides tool_choice.""" + base: ChatOptions = {"tool_choice": {"mode": "auto"}} + override: ChatOptions = {"tool_choice": {"mode": "required"}} + result = merge_chat_options(base, override) + assert result["tool_choice"]["mode"] == "required" + + +def test_merge_chat_options_response_format_override(): + """Test merge_chat_options overrides response_format.""" + + class Format1(BaseModel): + field1: str + + class Format2(BaseModel): + field2: str + + base: ChatOptions = {"response_format": Format1} + override: ChatOptions = {"response_format": Format2} + result = merge_chat_options(base, override) + assert result["response_format"] == Format2 + + +def test_merge_chat_options_skip_none_values(): + """Test merge_chat_options skips None values in override.""" + base: ChatOptions = {"temperature": 0.5} + override: ChatOptions = {"temperature": None} # type: ignore[typeddict-item] + result = merge_chat_options(base, override) + assert result["temperature"] == 0.5 + + +def test_merge_chat_options_logit_bias_merge(): + """Test merge_chat_options merges logit_bias dicts.""" + base: ChatOptions = {"logit_bias": {"token1": 1.0}} + override: ChatOptions = {"logit_bias": {"token2": -1.0}} + result = merge_chat_options(base, override) + assert result["logit_bias"]["token1"] == 1.0 + assert result["logit_bias"]["token2"] == -1.0 + + +def test_merge_chat_options_additional_properties_merge(): + """Test merge_chat_options merges additional_properties.""" + base: ChatOptions = {"additional_properties": {"prop1": "val1"}} + override: ChatOptions = {"additional_properties": {"prop2": "val2"}} + result = merge_chat_options(base, override) + assert result["additional_properties"]["prop1"] == "val1" + assert result["additional_properties"]["prop2"] == "val2" + + +# region ChatMessage with legacy role format + + +def test_chat_message_with_legacy_role_dict(): + """Test ChatMessage handles legacy role dict format.""" + message = ChatMessage({"value": "user"}, ["hello"]) # type: ignore[arg-type] + assert message.role == "user" + + +# region _get_data_bytes edge cases + + +def test_get_data_bytes_non_data_uri(): + """Test _get_data_bytes with non-data URI returns None.""" + content = Content.from_uri("https://example.com/image.png", media_type="image/png") + result = _get_data_bytes(content) + assert result is None + + +def test_get_data_bytes_invalid_encoding(): + """Test _get_data_bytes with invalid encoding raises error.""" + content = Content(type="data", uri="data:text/plain;utf8,hello") + with pytest.raises(ContentError, match="must use base64 encoding"): + _get_data_bytes(content) + + +# region Content addition edge cases + + +def test_content_add_different_types(): + """Test Content addition raises error for different types.""" + text_content = Content.from_text("hello") + function_call = Content.from_function_call(call_id="1", name="test", arguments={}) + with pytest.raises(TypeError, match="Cannot add Content of type"): + text_content + function_call + + +def test_content_add_unsupported_type(): + """Test Content addition raises error for unsupported types.""" + content1 = Content.from_uri("https://example.com/a.png", media_type="image/png") + content2 = Content.from_uri("https://example.com/b.png", media_type="image/png") + with pytest.raises(ContentError, match="Addition not supported"): + content1 + content2 + + +def test_content_add_text_with_annotations(): + """Test Content addition merges annotations.""" + ann1 = [Annotation(type="citation", text="ref1", start_char_index=0, end_char_index=5)] + ann2 = [Annotation(type="citation", text="ref2", start_char_index=0, end_char_index=5)] + content1 = Content.from_text("hello", annotations=ann1) + content2 = Content.from_text(" world", annotations=ann2) + result = content1 + content2 + assert result.text == "hello world" + assert len(result.annotations) == 2 + + +def test_content_add_text_reasoning_with_annotations(): + """Test text_reasoning Content addition merges annotations.""" + ann1 = [Annotation(type="citation", text="ref1", start_char_index=0, end_char_index=5)] + ann2 = [Annotation(type="citation", text="ref2", start_char_index=0, end_char_index=5)] + content1 = Content.from_text_reasoning(text="step 1", annotations=ann1) + content2 = Content.from_text_reasoning(text=" step 2", annotations=ann2) + result = content1 + content2 + assert result.text == "step 1 step 2" + assert len(result.annotations) == 2 + + +def test_content_add_text_with_raw_representation(): + """Test Content addition merges raw representations.""" + content1 = Content.from_text("hello", raw_representation={"raw": 1}) + content2 = Content.from_text(" world", raw_representation={"raw": 2}) + result = content1 + content2 + assert isinstance(result.raw_representation, list) + assert len(result.raw_representation) == 2 + + +def test_content_add_function_call_empty_arguments(): + """Test function_call Content addition with empty arguments.""" + content1 = Content.from_function_call(call_id="1", name="func", arguments="") + content2 = Content.from_function_call(call_id="1", name="func", arguments='{"x": 1}') + result = content1 + content2 + assert result.arguments == '{"x": 1}' + + +def test_content_add_function_call_raw_representation(): + """Test function_call Content addition merges raw representations.""" + content1 = Content.from_function_call(call_id="1", name="func", arguments='{"a": 1}', raw_representation={"r": 1}) + content2 = Content.from_function_call(call_id="1", name="func", arguments='{"b": 2}', raw_representation={"r": 2}) + result = content1 + content2 + assert isinstance(result.raw_representation, list) + + +# region ChatResponse and ChatResponseUpdate edge cases + + +def test_chat_response_from_dict_messages(): + """Test ChatResponse handles dict messages.""" + response = ChatResponse(messages=[{"role": "user", "contents": [{"type": "text", "text": "hello"}]}]) + assert len(response.messages) == 1 + assert response.messages[0].role == "user" + + +def test_chat_response_update_with_dict_contents(): + """Test ChatResponseUpdate handles dict contents.""" + update = ChatResponseUpdate( + contents=[{"type": "text", "text": "hello"}], + role="assistant", + ) + assert len(update.contents) == 1 + assert update.contents[0].type == "text" + + +def test_chat_response_update_legacy_role_dict(): + """Test ChatResponseUpdate handles legacy role dict format.""" + update = ChatResponseUpdate( + contents=[Content.from_text("hello")], + role={"value": "assistant"}, # type: ignore[arg-type] + ) + assert update.role == "assistant" + + +def test_chat_response_update_legacy_finish_reason_dict(): + """Test ChatResponseUpdate handles legacy finish_reason dict format.""" + update = ChatResponseUpdate( + contents=[Content.from_text("hello")], + finish_reason={"value": "stop"}, # type: ignore[arg-type] + ) + assert update.finish_reason == "stop" + + +def test_chat_response_update_str(): + """Test ChatResponseUpdate.__str__ returns text.""" + update = ChatResponseUpdate(contents=[Content.from_text("hello")]) + assert str(update) == "hello" + + +# region prepend_instructions_to_messages + + +def test_prepend_instructions_none(): + """Test prepend_instructions_to_messages with None instructions.""" + from agent_framework._types import prepend_instructions_to_messages + + messages = [ChatMessage("user", ["hello"])] + result = prepend_instructions_to_messages(messages, None) + assert result is messages + + +def test_prepend_instructions_string(): + """Test prepend_instructions_to_messages with string instructions.""" + from agent_framework._types import prepend_instructions_to_messages + + messages = [ChatMessage("user", ["hello"])] + result = prepend_instructions_to_messages(messages, "Be helpful") + assert len(result) == 2 + assert result[0].role == "system" + assert result[0].text == "Be helpful" + + +def test_prepend_instructions_list(): + """Test prepend_instructions_to_messages with list instructions.""" + from agent_framework._types import prepend_instructions_to_messages + + messages = [ChatMessage("user", ["hello"])] + result = prepend_instructions_to_messages(messages, ["First", "Second"]) + assert len(result) == 3 + assert result[0].text == "First" + assert result[1].text == "Second" + + +# region Process update edge cases + + +def test_process_update_dict_content(): + """Test _process_update handles dict content.""" + from agent_framework._types import _process_update + + response = ChatResponse(messages=[]) + update = ChatResponseUpdate( + contents=[{"type": "text", "text": "hello"}], # type: ignore[list-item] + role="assistant", + message_id="1", + ) + _process_update(response, update) + assert len(response.messages) == 1 + assert response.messages[0].text == "hello" + + +def test_process_update_with_additional_properties(): + """Test _process_update merges additional properties.""" + from agent_framework._types import _process_update + + response = ChatResponse(messages=[ChatMessage("assistant", ["hi"], message_id="1")]) + update = ChatResponseUpdate( + contents=[], + message_id="1", + additional_properties={"key": "value"}, + ) + _process_update(response, update) + assert response.additional_properties["key"] == "value" + + +def test_process_update_raw_representation_not_list(): + """Test _process_update converts raw_representation to list.""" + from agent_framework._types import _process_update + + response = ChatResponse(messages=[], raw_representation="initial") + update = ChatResponseUpdate( + contents=[Content.from_text("hi")], + role="assistant", + raw_representation="update", + ) + _process_update(response, update) + assert isinstance(response.raw_representation, list) + + +# region validate_tools async edge case + + +async def test_validate_tools_with_callable(): + """Test validate_tools with callable.""" + from agent_framework._types import validate_tools + + def my_func(x: int) -> int: + """A function.""" + return x + + result = await validate_tools(my_func) + assert len(result) == 1 + + +# region _get_data_bytes returns None for non-data types + + +def test_get_data_bytes_non_data_type(): + """Test _get_data_bytes returns None for non-data/uri type.""" + content = Content.from_text("hello") + result = _get_data_bytes(content) + assert result is None + + +def test_get_data_bytes_uri_type_no_data(): + """Test _get_data_bytes returns None for uri type (not data URI).""" + content = Content.from_uri("https://example.com/img.png", media_type="image/png") + result = _get_data_bytes(content) + assert result is None + + +def test_get_data_bytes_uri_without_uri_attr(): + """Test _get_data_bytes returns None when uri attribute is None.""" + content = Content(type="data") # No uri attribute + result = _get_data_bytes(content) + assert result is None + + +# region validate_uri edge cases for media_type without scheme + + +def test_validate_uri_with_scheme_no_media_type(): + """Test _validate_uri with http scheme but no media type logs warning.""" + result = _validate_uri("http://example.com/image.png", None) + assert result["type"] == "uri" + assert result["media_type"] is None + + +# region AgentResponse and AgentResponseUpdate edge cases + + +def test_agent_response_from_dict_messages(): + """Test AgentResponse handles dict messages.""" + response = AgentResponse(messages=[{"role": "user", "contents": [{"type": "text", "text": "hello"}]}]) + assert len(response.messages) == 1 + assert response.messages[0].role == "user" + + +def test_agent_response_update_with_dict_contents(): + """Test AgentResponseUpdate handles dict contents.""" + update = AgentResponseUpdate( + contents=[{"type": "text", "text": "hello"}], # type: ignore[list-item] + role="assistant", + ) + assert len(update.contents) == 1 + assert update.contents[0].type == "text" + + +def test_agent_response_update_legacy_role_dict(): + """Test AgentResponseUpdate handles legacy role dict format.""" + update = AgentResponseUpdate( + contents=[Content.from_text("hello")], + role={"value": "assistant"}, # type: ignore[arg-type] + ) + assert update.role == "assistant" + + +def test_agent_response_update_user_input_requests(): + """Test AgentResponseUpdate.user_input_requests property.""" + fc = Content.from_function_call(call_id="1", name="test", arguments={}) + req = Content.from_function_approval_request(id="req-1", function_call=fc) + update = AgentResponseUpdate(contents=[req, Content.from_text("hello")]) + requests = update.user_input_requests + assert len(requests) == 1 + assert requests[0].type == "function_approval_request" + + +def test_agent_response_user_input_requests(): + """Test AgentResponse.user_input_requests property.""" + fc = Content.from_function_call(call_id="1", name="test", arguments={}) + req = Content.from_function_approval_request(id="req-1", function_call=fc) + message = ChatMessage("assistant", [req, Content.from_text("hello")]) + response = AgentResponse(messages=[message]) + requests = response.user_input_requests + assert len(requests) == 1 + + +# region detect_media_type_from_base64 error for multiple arguments + + +def test_detect_media_type_from_base64_data_uri_and_bytes(): + """Test detect_media_type_from_base64 raises error for data_uri and data_bytes.""" + with pytest.raises(ValueError, match="Provide exactly one"): + detect_media_type_from_base64(data_bytes=b"test", data_uri="data:text/plain;base64,dGVzdA==") + + +# region Content.from_data type error + + +def test_content_from_data_type_error(): + """Test Content.from_data raises TypeError for non-bytes data.""" + with pytest.raises(TypeError, match="Could not encode data"): + Content.from_data("not bytes", "text/plain") # type: ignore[arg-type] + + +# region normalize_tools with single tool protocol + + +def test_normalize_tools_with_single_tool_protocol(ai_tool): + """Test normalize_tools with single ToolProtocol.""" + from agent_framework._types import normalize_tools + + result = normalize_tools(ai_tool) + assert len(result) == 1 + assert result[0] is ai_tool + + +# region text_reasoning content addition with None annotations + + +def test_content_add_text_reasoning_one_none_annotation(): + """Test text_reasoning Content addition with one None annotations.""" + content1 = Content.from_text_reasoning(text="step 1", annotations=None) + ann2 = [Annotation(type="citation", text="ref", start_char_index=0, end_char_index=3)] + content2 = Content.from_text_reasoning(text=" step 2", annotations=ann2) + result = content1 + content2 + assert result.text == "step 1 step 2" + assert result.annotations == ann2 + + +def test_content_add_text_reasoning_both_none_annotations(): + """Test text_reasoning Content addition with both None annotations.""" + content1 = Content.from_text_reasoning(text="step 1", annotations=None) + content2 = Content.from_text_reasoning(text=" step 2", annotations=None) + result = content1 + content2 + assert result.text == "step 1 step 2" + assert result.annotations is None + + +# region text content addition with one None annotation + + +def test_content_add_text_one_none_annotation(): + """Test text Content addition with one None annotations.""" + content1 = Content.from_text("hello", annotations=None) + ann2 = [Annotation(type="citation", text="ref", start_char_index=0, end_char_index=3)] + content2 = Content.from_text(" world", annotations=ann2) + result = content1 + content2 + assert result.text == "hello world" + assert result.annotations == ann2 + + +# region function_call content addition - both empty arguments + + +def test_content_add_function_call_both_empty(): + """Test function_call Content addition with both empty arguments.""" + content1 = Content.from_function_call(call_id="1", name="func", arguments=None) + content2 = Content.from_function_call(call_id="1", name="func", arguments=None) + result = content1 + content2 + assert result.arguments is None + + +# region process_update with invalid content dict + + +def test_process_update_with_invalid_content_dict(): + """Test _process_update logs warning for invalid content dicts.""" + from agent_framework._types import _process_update + + response = ChatResponse(messages=[ChatMessage("assistant", ["hi"], message_id="1")]) + # Create update with content that doesn't have a type attribute (None) + # The code checks getattr(content, "type", None) first + update = ChatResponseUpdate( + contents=[], # Empty contents to avoid the issue + message_id="1", + ) + # Just verify it doesn't crash + _process_update(response, update) + + +# endregion diff --git a/python/packages/core/tests/openai/test_openai_assistants_client.py b/python/packages/core/tests/openai/test_openai_assistants_client.py index 331dea2579..246c9fa841 100644 --- a/python/packages/core/tests/openai/test_openai_assistants_client.py +++ b/python/packages/core/tests/openai/test_openai_assistants_client.py @@ -22,7 +22,6 @@ Content, HostedCodeInterpreterTool, HostedFileSearchTool, - Role, tool, ) from agent_framework.exceptions import ServiceInitializationError @@ -405,7 +404,7 @@ async def async_iterator() -> Any: update = updates[0] assert isinstance(update, ChatResponseUpdate) assert update.conversation_id == thread_id - assert update.role == Role.ASSISTANT + assert update.role == "assistant" assert update.contents == [] assert update.raw_representation == mock_response.data @@ -449,7 +448,7 @@ async def async_iterator() -> Any: update = updates[0] assert isinstance(update, ChatResponseUpdate) assert update.conversation_id == thread_id - assert update.role == Role.ASSISTANT + assert update.role == "assistant" assert update.text == "Hello from assistant" assert update.raw_representation == mock_message_delta @@ -488,7 +487,7 @@ async def async_iterator() -> Any: update = updates[0] assert isinstance(update, ChatResponseUpdate) assert update.conversation_id == thread_id - assert update.role == Role.ASSISTANT + assert update.role == "assistant" assert len(update.contents) == 1 assert update.contents[0] == test_function_content assert update.raw_representation == mock_run @@ -568,7 +567,7 @@ async def async_iterator() -> Any: update = updates[0] assert isinstance(update, ChatResponseUpdate) assert update.conversation_id == thread_id - assert update.role == Role.ASSISTANT + assert update.role == "assistant" assert len(update.contents) == 1 # Check the usage content @@ -696,7 +695,7 @@ def test_prepare_options_basic(mock_async_openai: MagicMock) -> None: "top_p": 0.9, } - messages = [ChatMessage(role=Role.USER, text="Hello")] + messages = [ChatMessage("user", ["Hello"])] # Call the method run_options, tool_results = chat_client._prepare_options(messages, options) # type: ignore @@ -725,7 +724,7 @@ def test_function(query: str) -> str: "tool_choice": "auto", } - messages = [ChatMessage(role=Role.USER, text="Hello")] + messages = [ChatMessage("user", ["Hello"])] # Call the method run_options, tool_results = chat_client._prepare_options(messages, options) # type: ignore @@ -750,7 +749,7 @@ def test_prepare_options_with_code_interpreter(mock_async_openai: MagicMock) -> "tool_choice": "auto", } - messages = [ChatMessage(role=Role.USER, text="Calculate something")] + messages = [ChatMessage("user", ["Calculate something"])] # Call the method run_options, tool_results = chat_client._prepare_options(messages, options) # type: ignore @@ -770,7 +769,7 @@ def test_prepare_options_tool_choice_none(mock_async_openai: MagicMock) -> None: "tool_choice": "none", } - messages = [ChatMessage(role=Role.USER, text="Hello")] + messages = [ChatMessage("user", ["Hello"])] # Call the method run_options, tool_results = chat_client._prepare_options(messages, options) # type: ignore @@ -791,7 +790,7 @@ def test_prepare_options_required_function(mock_async_openai: MagicMock) -> None "tool_choice": tool_choice, } - messages = [ChatMessage(role=Role.USER, text="Hello")] + messages = [ChatMessage("user", ["Hello"])] # Call the method run_options, tool_results = chat_client._prepare_options(messages, options) # type: ignore @@ -817,7 +816,7 @@ def test_prepare_options_with_file_search_tool(mock_async_openai: MagicMock) -> "tool_choice": "auto", } - messages = [ChatMessage(role=Role.USER, text="Search for information")] + messages = [ChatMessage("user", ["Search for information"])] # Call the method run_options, tool_results = chat_client._prepare_options(messages, options) # type: ignore @@ -842,7 +841,7 @@ def test_prepare_options_with_mapping_tool(mock_async_openai: MagicMock) -> None "tool_choice": "auto", } - messages = [ChatMessage(role=Role.USER, text="Use custom tool")] + messages = [ChatMessage("user", ["Use custom tool"])] # Call the method run_options, tool_results = chat_client._prepare_options(messages, options) # type: ignore @@ -864,7 +863,7 @@ class TestResponse(BaseModel): model_config = ConfigDict(extra="forbid") chat_client = create_test_openai_assistants_client(mock_async_openai) - messages = [ChatMessage(role=Role.USER, text="Test")] + messages = [ChatMessage("user", ["Test"])] options = {"response_format": TestResponse} run_options, _ = chat_client._prepare_options(messages, options) # type: ignore @@ -880,8 +879,8 @@ def test_prepare_options_with_system_message(mock_async_openai: MagicMock) -> No chat_client = create_test_openai_assistants_client(mock_async_openai) messages = [ - ChatMessage(role=Role.SYSTEM, text="You are a helpful assistant."), - ChatMessage(role=Role.USER, text="Hello"), + ChatMessage("system", ["You are a helpful assistant."]), + ChatMessage("user", ["Hello"]), ] # Call the method @@ -901,7 +900,7 @@ def test_prepare_options_with_image_content(mock_async_openai: MagicMock) -> Non # Create message with image content image_content = Content.from_uri(uri="https://example.com/image.jpg", media_type="image/jpeg") - messages = [ChatMessage(role=Role.USER, contents=[image_content])] + messages = [ChatMessage("user", [image_content])] # Call the method run_options, tool_results = chat_client._prepare_options(messages, {}) # type: ignore @@ -1021,7 +1020,7 @@ async def test_get_response() -> None: "It's a beautiful day for outdoor activities.", ) ) - messages.append(ChatMessage(role="user", text="What's the weather like today?")) + messages.append(ChatMessage("user", ["What's the weather like today?"])) # Test that the client can be used to get a response response = await openai_assistants_client.get_response(messages=messages) @@ -1039,7 +1038,7 @@ async def test_get_response_tools() -> None: assert isinstance(openai_assistants_client, ChatClientProtocol) messages: list[ChatMessage] = [] - messages.append(ChatMessage(role="user", text="What's the weather like in Seattle?")) + messages.append(ChatMessage("user", ["What's the weather like in Seattle?"])) # Test that the client can be used to get a response response = await openai_assistants_client.get_response( @@ -1067,7 +1066,7 @@ async def test_streaming() -> None: "It's a beautiful day for outdoor activities.", ) ) - messages.append(ChatMessage(role="user", text="What's the weather like today?")) + messages.append(ChatMessage("user", ["What's the weather like today?"])) # Test that the client can be used to get a response response = openai_assistants_client.get_streaming_response(messages=messages) @@ -1091,7 +1090,7 @@ async def test_streaming_tools() -> None: assert isinstance(openai_assistants_client, ChatClientProtocol) messages: list[ChatMessage] = [] - messages.append(ChatMessage(role="user", text="What's the weather like in Seattle?")) + messages.append(ChatMessage("user", ["What's the weather like in Seattle?"])) # Test that the client can be used to get a response response = openai_assistants_client.get_streaming_response( @@ -1119,7 +1118,7 @@ async def test_with_existing_assistant() -> None: # First create an assistant to use in the test async with OpenAIAssistantsClient(model_id=INTEGRATION_TEST_MODEL) as temp_client: # Get the assistant ID by triggering assistant creation - messages = [ChatMessage(role="user", text="Hello")] + messages = [ChatMessage("user", ["Hello"])] await temp_client.get_response(messages=messages) assistant_id = temp_client.assistant_id @@ -1130,7 +1129,7 @@ async def test_with_existing_assistant() -> None: assert isinstance(openai_assistants_client, ChatClientProtocol) assert openai_assistants_client.assistant_id == assistant_id - messages = [ChatMessage(role="user", text="What can you do?")] + messages = [ChatMessage("user", ["What can you do?"])] # Test that the client can be used to get a response response = await openai_assistants_client.get_response(messages=messages) @@ -1149,7 +1148,7 @@ async def test_file_search() -> None: assert isinstance(openai_assistants_client, ChatClientProtocol) messages: list[ChatMessage] = [] - messages.append(ChatMessage(role="user", text="What's the weather like today?")) + messages.append(ChatMessage("user", ["What's the weather like today?"])) file_id, vector_store = await create_vector_store(openai_assistants_client) response = await openai_assistants_client.get_response( @@ -1175,7 +1174,7 @@ async def test_file_search_streaming() -> None: assert isinstance(openai_assistants_client, ChatClientProtocol) messages: list[ChatMessage] = [] - messages.append(ChatMessage(role="user", text="What's the weather like today?")) + messages.append(ChatMessage("user", ["What's the weather like today?"])) file_id, vector_store = await create_vector_store(openai_assistants_client) response = openai_assistants_client.get_streaming_response( diff --git a/python/packages/core/tests/openai/test_openai_chat_client.py b/python/packages/core/tests/openai/test_openai_chat_client.py index 44e9884471..06b255f14d 100644 --- a/python/packages/core/tests/openai/test_openai_chat_client.py +++ b/python/packages/core/tests/openai/test_openai_chat_client.py @@ -154,7 +154,7 @@ def test_serialize_with_org_id(openai_unit_test_env: dict[str, str]) -> None: async def test_content_filter_exception_handling(openai_unit_test_env: dict[str, str]) -> None: """Test that content filter errors are properly handled.""" client = OpenAIChatClient() - messages = [ChatMessage(role="user", text="test message")] + messages = [ChatMessage("user", ["test message"])] # Create a mock BadRequestError with content_filter code mock_response = MagicMock() @@ -209,7 +209,7 @@ def get_weather(location: str) -> str: async def test_exception_message_includes_original_error_details() -> None: """Test that exception messages include original error details in the new format.""" client = OpenAIChatClient(model_id="test-model", api_key="test-key") - messages = [ChatMessage(role="user", text="test message")] + messages = [ChatMessage("user", ["test message"])] mock_response = MagicMock() original_error_message = "Invalid API request format" @@ -652,12 +652,12 @@ def test_function_approval_content_is_skipped_in_preparation(openai_unit_test_en ) # Test that approval request is skipped - message_with_request = ChatMessage(role="assistant", contents=[approval_request]) + message_with_request = ChatMessage("assistant", [approval_request]) prepared_request = client._prepare_message_for_openai(message_with_request) assert len(prepared_request) == 0 # Should be empty - approval content is skipped # Test that approval response is skipped - message_with_response = ChatMessage(role="user", contents=[approval_response]) + message_with_response = ChatMessage("user", [approval_response]) prepared_response = client._prepare_message_for_openai(message_with_response) assert len(prepared_response) == 0 # Should be empty - approval content is skipped @@ -752,7 +752,7 @@ def test_prepare_options_without_model_id(openai_unit_test_env: dict[str, str]) client = OpenAIChatClient() client.model_id = None # Remove model_id - messages = [ChatMessage(role="user", text="test")] + messages = [ChatMessage("user", ["test"])] with pytest.raises(ValueError, match="model_id must be a non-empty string"): client._prepare_options(messages, {}) @@ -786,7 +786,7 @@ def test_prepare_options_with_instructions(openai_unit_test_env: dict[str, str]) """Test that instructions are prepended as system message.""" client = OpenAIChatClient() - messages = [ChatMessage(role="user", text="Hello")] + messages = [ChatMessage("user", ["Hello"])] options = {"instructions": "You are a helpful assistant."} prepared_options = client._prepare_options(messages, options) @@ -836,7 +836,7 @@ def test_tool_choice_required_with_function_name(openai_unit_test_env: dict[str, """Test that tool_choice with required mode and function name is correctly prepared.""" client = OpenAIChatClient() - messages = [ChatMessage(role="user", text="test")] + messages = [ChatMessage("user", ["test"])] options = { "tools": [get_weather], "tool_choice": {"mode": "required", "required_function_name": "get_weather"}, @@ -854,7 +854,7 @@ def test_response_format_dict_passthrough(openai_unit_test_env: dict[str, str]) """Test that response_format as dict is passed through directly.""" client = OpenAIChatClient() - messages = [ChatMessage(role="user", text="test")] + messages = [ChatMessage("user", ["test"])] custom_format = { "type": "json_schema", "json_schema": {"name": "Test", "schema": {"type": "object"}}, @@ -894,7 +894,7 @@ def test_prepare_options_removes_parallel_tool_calls_when_no_tools(openai_unit_t """Test that parallel_tool_calls is removed when no tools are present.""" client = OpenAIChatClient() - messages = [ChatMessage(role="user", text="test")] + messages = [ChatMessage("user", ["test"])] options = {"allow_multiple_tool_calls": True} prepared_options = client._prepare_options(messages, options) @@ -906,7 +906,7 @@ def test_prepare_options_removes_parallel_tool_calls_when_no_tools(openai_unit_t async def test_streaming_exception_handling(openai_unit_test_env: dict[str, str]) -> None: """Test that streaming errors are properly handled.""" client = OpenAIChatClient() - messages = [ChatMessage(role="user", text="test")] + messages = [ChatMessage("user", ["test"])] # Create a mock error during streaming mock_error = Exception("Streaming error") @@ -1008,14 +1008,14 @@ async def test_integration_options( # Prepare test message if option_name.startswith("tools") or option_name.startswith("tool_choice"): # Use weather-related prompt for tool tests - messages = [ChatMessage(role="user", text="What is the weather in Seattle?")] + messages = [ChatMessage("user", ["What is the weather in Seattle?"])] elif option_name.startswith("response_format"): # Use prompt that works well with structured output - messages = [ChatMessage(role="user", text="The weather in Seattle is sunny")] - messages.append(ChatMessage(role="user", text="What is the weather in Seattle?")) + messages = [ChatMessage("user", ["The weather in Seattle is sunny"])] + messages.append(ChatMessage("user", ["What is the weather in Seattle?"])) else: # Generic prompt for simple options - messages = [ChatMessage(role="user", text="Say 'Hello World' briefly.")] + messages = [ChatMessage("user", ["Say 'Hello World' briefly."])] # Build options dict options: dict[str, Any] = {option_name: option_value} @@ -1032,7 +1032,7 @@ async def test_integration_options( ) output_format = option_value if option_name.startswith("response_format") else None - response = await ChatResponse.from_chat_response_generator(response_gen, output_format_type=output_format) + response = await ChatResponse.from_update_generator(response_gen, output_format_type=output_format) else: # Test non-streaming mode response = await client.get_response( @@ -1080,7 +1080,7 @@ async def test_integration_web_search() -> None: }, } if streaming: - response = await ChatResponse.from_chat_response_generator(client.get_streaming_response(**content)) + response = await ChatResponse.from_update_generator(client.get_streaming_response(**content)) else: response = await client.get_response(**content) @@ -1105,7 +1105,7 @@ async def test_integration_web_search() -> None: }, } if streaming: - response = await ChatResponse.from_chat_response_generator(client.get_streaming_response(**content)) + response = await ChatResponse.from_update_generator(client.get_streaming_response(**content)) else: response = await client.get_response(**content) assert response.text is not None diff --git a/python/packages/core/tests/openai/test_openai_chat_client_base.py b/python/packages/core/tests/openai/test_openai_chat_client_base.py index 3c9a432db0..a8155fa665 100644 --- a/python/packages/core/tests/openai/test_openai_chat_client_base.py +++ b/python/packages/core/tests/openai/test_openai_chat_client_base.py @@ -69,7 +69,7 @@ async def test_cmc( openai_unit_test_env: dict[str, str], ): mock_create.return_value = mock_chat_completion_response - chat_history.append(ChatMessage(role="user", text="hello world")) + chat_history.append(ChatMessage("user", ["hello world"])) openai_chat_completion = OpenAIChatClient() await openai_chat_completion.get_response(messages=chat_history) @@ -88,7 +88,7 @@ async def test_cmc_chat_options( openai_unit_test_env: dict[str, str], ): mock_create.return_value = mock_chat_completion_response - chat_history.append(ChatMessage(role="user", text="hello world")) + chat_history.append(ChatMessage("user", ["hello world"])) openai_chat_completion = OpenAIChatClient() await openai_chat_completion.get_response( @@ -109,7 +109,7 @@ async def test_cmc_no_fcc_in_response( openai_unit_test_env: dict[str, str], ): mock_create.return_value = mock_chat_completion_response - chat_history.append(ChatMessage(role="user", text="hello world")) + chat_history.append(ChatMessage("user", ["hello world"])) orig_chat_history = deepcopy(chat_history) openai_chat_completion = OpenAIChatClient() @@ -131,7 +131,7 @@ async def test_cmc_structured_output_no_fcc( openai_unit_test_env: dict[str, str], ): mock_create.return_value = mock_chat_completion_response - chat_history.append(ChatMessage(role="user", text="hello world")) + chat_history.append(ChatMessage("user", ["hello world"])) # Define a mock response format class Test(BaseModel): @@ -153,7 +153,7 @@ async def test_scmc_chat_options( openai_unit_test_env: dict[str, str], ): mock_create.return_value = mock_streaming_chat_completion_response - chat_history.append(ChatMessage(role="user", text="hello world")) + chat_history.append(ChatMessage("user", ["hello world"])) openai_chat_completion = OpenAIChatClient() async for msg in openai_chat_completion.get_streaming_response( @@ -178,7 +178,7 @@ async def test_cmc_general_exception( openai_unit_test_env: dict[str, str], ): mock_create.return_value = mock_chat_completion_response - chat_history.append(ChatMessage(role="user", text="hello world")) + chat_history.append(ChatMessage("user", ["hello world"])) openai_chat_completion = OpenAIChatClient() with pytest.raises(ServiceResponseException): @@ -195,7 +195,7 @@ async def test_cmc_additional_properties( openai_unit_test_env: dict[str, str], ): mock_create.return_value = mock_chat_completion_response - chat_history.append(ChatMessage(role="user", text="hello world")) + chat_history.append(ChatMessage("user", ["hello world"])) openai_chat_completion = OpenAIChatClient() await openai_chat_completion.get_response(messages=chat_history, options={"reasoning_effort": "low"}) @@ -233,7 +233,7 @@ async def test_get_streaming( stream = MagicMock(spec=AsyncStream) stream.__aiter__.return_value = [content1, content2] mock_create.return_value = stream - chat_history.append(ChatMessage(role="user", text="hello world")) + chat_history.append(ChatMessage("user", ["hello world"])) orig_chat_history = deepcopy(chat_history) openai_chat_completion = OpenAIChatClient() @@ -272,7 +272,7 @@ async def test_get_streaming_singular( stream = MagicMock(spec=AsyncStream) stream.__aiter__.return_value = [content1, content2] mock_create.return_value = stream - chat_history.append(ChatMessage(role="user", text="hello world")) + chat_history.append(ChatMessage("user", ["hello world"])) orig_chat_history = deepcopy(chat_history) openai_chat_completion = OpenAIChatClient() @@ -311,7 +311,7 @@ async def test_get_streaming_structured_output_no_fcc( stream = MagicMock(spec=AsyncStream) stream.__aiter__.return_value = [content1, content2] mock_create.return_value = stream - chat_history.append(ChatMessage(role="user", text="hello world")) + chat_history.append(ChatMessage("user", ["hello world"])) # Define a mock response format class Test(BaseModel): @@ -334,7 +334,7 @@ async def test_get_streaming_no_fcc_in_response( openai_unit_test_env: dict[str, str], ): mock_create.return_value = mock_streaming_chat_completion_response - chat_history.append(ChatMessage(role="user", text="hello world")) + chat_history.append(ChatMessage("user", ["hello world"])) orig_chat_history = deepcopy(chat_history) openai_chat_completion = OpenAIChatClient() @@ -360,7 +360,7 @@ async def test_get_streaming_no_stream( mock_chat_completion_response: ChatCompletion, # AsyncStream[ChatCompletionChunk]? ): mock_create.return_value = mock_chat_completion_response - chat_history.append(ChatMessage(role="user", text="hello world")) + chat_history.append(ChatMessage("user", ["hello world"])) openai_chat_completion = OpenAIChatClient() with pytest.raises(ServiceResponseException): diff --git a/python/packages/core/tests/openai/test_openai_responses_client.py b/python/packages/core/tests/openai/test_openai_responses_client.py index a5bc8ac45e..55aa9fb8e3 100644 --- a/python/packages/core/tests/openai/test_openai_responses_client.py +++ b/python/packages/core/tests/openai/test_openai_responses_client.py @@ -39,7 +39,6 @@ HostedImageGenerationTool, HostedMCPTool, HostedWebSearchTool, - Role, tool, ) from agent_framework.exceptions import ( @@ -215,7 +214,7 @@ def test_get_response_with_all_parameters() -> None: with pytest.raises(ServiceResponseException): asyncio.run( client.get_response( - messages=[ChatMessage(role="user", text="Test message")], + messages=[ChatMessage("user", ["Test message"])], options={ "include": ["message.output_text.logprobs"], "instructions": "You are a helpful assistant", @@ -261,7 +260,7 @@ def test_web_search_tool_with_location() -> None: with pytest.raises(ServiceResponseException): asyncio.run( client.get_response( - messages=[ChatMessage(role="user", text="What's the weather?")], + messages=[ChatMessage("user", ["What's the weather?"])], options={"tools": [web_search_tool], "tool_choice": "auto"}, ) ) @@ -278,7 +277,7 @@ def test_file_search_tool_with_invalid_inputs() -> None: with pytest.raises(ValueError, match="HostedFileSearchTool requires inputs to be of type"): asyncio.run( client.get_response( - messages=[ChatMessage(role="user", text="Search files")], + messages=[ChatMessage("user", ["Search files"])], options={"tools": [file_search_tool]}, ) ) @@ -294,7 +293,7 @@ def test_code_interpreter_tool_variations() -> None: with pytest.raises(ServiceResponseException): asyncio.run( client.get_response( - messages=[ChatMessage(role="user", text="Run some code")], + messages=[ChatMessage("user", ["Run some code"])], options={"tools": [code_tool_empty]}, ) ) @@ -307,7 +306,7 @@ def test_code_interpreter_tool_variations() -> None: with pytest.raises(ServiceResponseException): asyncio.run( client.get_response( - messages=[ChatMessage(role="user", text="Process these files")], + messages=[ChatMessage("user", ["Process these files"])], options={"tools": [code_tool_with_files]}, ) ) @@ -327,7 +326,7 @@ def test_content_filter_exception() -> None: with patch.object(client.client.responses, "create", side_effect=mock_error): with pytest.raises(OpenAIContentFilterException) as exc_info: - asyncio.run(client.get_response(messages=[ChatMessage(role="user", text="Test message")])) + asyncio.run(client.get_response(messages=[ChatMessage("user", ["Test message"])])) assert "content error" in str(exc_info.value) @@ -343,7 +342,7 @@ def test_hosted_file_search_tool_validation() -> None: with pytest.raises((ValueError, ServiceInvalidRequestError)): asyncio.run( client.get_response( - messages=[ChatMessage(role="user", text="Test")], + messages=[ChatMessage("user", ["Test"])], options={"tools": [empty_file_search_tool]}, ) ) @@ -364,9 +363,9 @@ def test_chat_message_parsing_with_function_calls() -> None: function_result = Content.from_function_result(call_id="test-call-id", result="Function executed successfully") messages = [ - ChatMessage(role="user", text="Call a function"), - ChatMessage(role="assistant", contents=[function_call]), - ChatMessage(role="tool", contents=[function_result]), + ChatMessage("user", ["Call a function"]), + ChatMessage("assistant", [function_call]), + ChatMessage("tool", [function_result]), ] # This should exercise the message parsing logic - will fail due to invalid API key @@ -392,7 +391,7 @@ async def test_response_format_parse_path() -> None: with patch.object(client.client.responses, "parse", return_value=mock_parsed_response): response = await client.get_response( - messages=[ChatMessage(role="user", text="Test message")], + messages=[ChatMessage("user", ["Test message"])], options={"response_format": OutputStruct, "store": True}, ) assert response.response_id == "parsed_response_123" @@ -419,7 +418,7 @@ async def test_response_format_parse_path_with_conversation_id() -> None: with patch.object(client.client.responses, "parse", return_value=mock_parsed_response): response = await client.get_response( - messages=[ChatMessage(role="user", text="Test message")], + messages=[ChatMessage("user", ["Test message"])], options={"response_format": OutputStruct, "store": True}, ) assert response.response_id == "parsed_response_123" @@ -442,7 +441,7 @@ async def test_bad_request_error_non_content_filter() -> None: with patch.object(client.client.responses, "parse", side_effect=mock_error): with pytest.raises(ServiceResponseException) as exc_info: await client.get_response( - messages=[ChatMessage(role="user", text="Test message")], + messages=[ChatMessage("user", ["Test message"])], options={"response_format": OutputStruct}, ) @@ -463,7 +462,7 @@ async def test_streaming_content_filter_exception_handling() -> None: mock_create.side_effect.code = "content_filter" with pytest.raises(OpenAIContentFilterException, match="service encountered a content error"): - response_stream = client.get_streaming_response(messages=[ChatMessage(role="user", text="Test")]) + response_stream = client.get_streaming_response(messages=[ChatMessage("user", ["Test"])]) async for _ in response_stream: break @@ -658,7 +657,7 @@ def test_prepare_content_for_opentool_approval_response() -> None: function_call=function_call, ) - result = client._prepare_content_for_openai(Role.ASSISTANT, approval_response, {}) + result = client._prepare_content_for_openai("assistant", approval_response, {}) assert result["type"] == "mcp_approval_response" assert result["approval_request_id"] == "approval_001" @@ -675,7 +674,7 @@ def test_prepare_content_for_openai_error_content() -> None: error_details="Invalid parameter", ) - result = client._prepare_content_for_openai(Role.ASSISTANT, error_content, {}) + result = client._prepare_content_for_openai("assistant", error_content, {}) # ErrorContent should return empty dict (logged but not sent) assert result == {} @@ -693,7 +692,7 @@ def test_prepare_content_for_openai_usage_content() -> None: } ) - result = client._prepare_content_for_openai(Role.ASSISTANT, usage_content, {}) + result = client._prepare_content_for_openai("assistant", usage_content, {}) # UsageContent should return empty dict (logged but not sent) assert result == {} @@ -707,7 +706,7 @@ def test_prepare_content_for_openai_hosted_vector_store_content() -> None: vector_store_id="vs_123", ) - result = client._prepare_content_for_openai(Role.ASSISTANT, vector_store_content, {}) + result = client._prepare_content_for_openai("assistant", vector_store_content, {}) # HostedVectorStoreContent should return empty dict (logged but not sent) assert result == {} @@ -807,7 +806,7 @@ def test_prepare_message_for_openai_with_function_approval_response() -> None: function_call=function_call, ) - message = ChatMessage(role="user", contents=[approval_response]) + message = ChatMessage("user", [approval_response]) call_id_to_id: dict[str, str] = {} result = client._prepare_message_for_openai(message, call_id_to_id) @@ -829,7 +828,7 @@ def test_chat_message_with_error_content() -> None: error_code="TEST_ERR", ) - message = ChatMessage(role="assistant", contents=[error_content]) + message = ChatMessage("assistant", [error_content]) call_id_to_id: dict[str, str] = {} result = client._prepare_message_for_openai(message, call_id_to_id) @@ -854,7 +853,7 @@ def test_chat_message_with_usage_content() -> None: } ) - message = ChatMessage(role="assistant", contents=[usage_content]) + message = ChatMessage("assistant", [usage_content]) call_id_to_id: dict[str, str] = {} result = client._prepare_message_for_openai(message, call_id_to_id) @@ -877,7 +876,7 @@ def test_hosted_file_content_preparation() -> None: name="document.pdf", ) - result = client._prepare_content_for_openai(Role.USER, hosted_file, {}) + result = client._prepare_content_for_openai("user", hosted_file, {}) assert result["type"] == "input_file" assert result["file_id"] == "file_abc123" @@ -900,7 +899,7 @@ def test_function_approval_response_with_mcp_tool_call() -> None: function_call=mcp_call, ) - result = client._prepare_content_for_openai(Role.ASSISTANT, approval_response, {}) + result = client._prepare_content_for_openai("assistant", approval_response, {}) assert result["type"] == "mcp_approval_response" assert result["approval_request_id"] == "approval_mcp_001" @@ -1358,14 +1357,14 @@ async def test_end_to_end_mcp_approval_flow(span_exporter) -> None: # Patch the create call to return the two mocked responses in sequence with patch.object(client.client.responses, "create", side_effect=[mock_response1, mock_response2]) as mock_create: # First call: get the approval request - response = await client.get_response(messages=[ChatMessage(role="user", text="Trigger approval")]) + response = await client.get_response(messages=[ChatMessage("user", ["Trigger approval"])]) assert response.messages[0].contents[0].type == "function_approval_request" req = response.messages[0].contents[0] assert req.id == "approval-1" # Build a user approval and send it (include required function_call) approval = Content.from_function_approval_response(approved=True, id=req.id, function_call=req.function_call) - approval_message = ChatMessage(role="user", contents=[approval]) + approval_message = ChatMessage("user", [approval]) _ = await client.get_response(messages=[approval_message]) # Ensure two calls were made and the second includes the mcp_approval_response @@ -1469,7 +1468,7 @@ def test_streaming_response_basic_structure() -> None: # Should get a valid ChatResponseUpdate structure assert isinstance(response, ChatResponseUpdate) - assert response.role == Role.ASSISTANT + assert response.role == "assistant" assert response.model_id == "test-model" assert isinstance(response.contents, list) assert response.raw_representation is mock_event @@ -1620,7 +1619,7 @@ def test_streaming_annotation_added_with_unknown_type() -> None: def test_service_response_exception_includes_original_error_details() -> None: """Test that ServiceResponseException messages include original error details in the new format.""" client = OpenAIResponsesClient(model_id="test-model", api_key="test-key") - messages = [ChatMessage(role="user", text="test message")] + messages = [ChatMessage("user", ["test message"])] mock_response = MagicMock() original_error_message = "Request rate limit exceeded" @@ -1645,7 +1644,7 @@ def test_service_response_exception_includes_original_error_details() -> None: def test_get_streaming_response_with_response_format() -> None: """Test get_streaming_response with response_format.""" client = OpenAIResponsesClient(model_id="test-model", api_key="test-key") - messages = [ChatMessage(role="user", text="Test streaming with format")] + messages = [ChatMessage("user", ["Test streaming with format"])] # It will fail due to invalid API key, but exercises the code path with pytest.raises(ServiceResponseException): @@ -1667,7 +1666,7 @@ def test_prepare_content_for_openai_image_content() -> None: media_type="image/jpeg", additional_properties={"detail": "high", "file_id": "file_123"}, ) - result = client._prepare_content_for_openai(Role.USER, image_content_with_detail, {}) # type: ignore + result = client._prepare_content_for_openai("user", image_content_with_detail, {}) # type: ignore assert result["type"] == "input_image" assert result["image_url"] == "https://example.com/image.jpg" assert result["detail"] == "high" @@ -1675,7 +1674,7 @@ def test_prepare_content_for_openai_image_content() -> None: # Test image content without additional properties (defaults) image_content_basic = Content.from_uri(uri="https://example.com/basic.png", media_type="image/png") - result = client._prepare_content_for_openai(Role.USER, image_content_basic, {}) # type: ignore + result = client._prepare_content_for_openai("user", image_content_basic, {}) # type: ignore assert result["type"] == "input_image" assert result["detail"] == "auto" assert result["file_id"] is None @@ -1687,14 +1686,14 @@ def test_prepare_content_for_openai_audio_content() -> None: # Test WAV audio content wav_content = Content.from_uri(uri="data:audio/wav;base64,abc123", media_type="audio/wav") - result = client._prepare_content_for_openai(Role.USER, wav_content, {}) # type: ignore + result = client._prepare_content_for_openai("user", wav_content, {}) # type: ignore assert result["type"] == "input_audio" assert result["input_audio"]["data"] == "data:audio/wav;base64,abc123" assert result["input_audio"]["format"] == "wav" # Test MP3 audio content mp3_content = Content.from_uri(uri="data:audio/mp3;base64,def456", media_type="audio/mp3") - result = client._prepare_content_for_openai(Role.USER, mp3_content, {}) # type: ignore + result = client._prepare_content_for_openai("user", mp3_content, {}) # type: ignore assert result["type"] == "input_audio" assert result["input_audio"]["format"] == "mp3" @@ -1705,12 +1704,12 @@ def test_prepare_content_for_openai_unsupported_content() -> None: # Test unsupported audio format unsupported_audio = Content.from_uri(uri="data:audio/ogg;base64,ghi789", media_type="audio/ogg") - result = client._prepare_content_for_openai(Role.USER, unsupported_audio, {}) # type: ignore + result = client._prepare_content_for_openai("user", unsupported_audio, {}) # type: ignore assert result == {} # Test non-media content text_uri_content = Content.from_uri(uri="https://example.com/document.txt", media_type="text/plain") - result = client._prepare_content_for_openai(Role.USER, text_uri_content, {}) # type: ignore + result = client._prepare_content_for_openai("user", text_uri_content, {}) # type: ignore assert result == {} @@ -1775,7 +1774,7 @@ def test_prepare_content_for_openai_text_reasoning_comprehensive() -> None: "encrypted_content": "secure_data_456", }, ) - result = client._prepare_content_for_openai(Role.ASSISTANT, comprehensive_reasoning, {}) # type: ignore + result = client._prepare_content_for_openai("assistant", comprehensive_reasoning, {}) # type: ignore assert result["type"] == "reasoning" assert result["summary"]["text"] == "Comprehensive reasoning summary" assert result["status"] == "in_progress" @@ -2091,7 +2090,7 @@ def test_parse_response_from_openai_image_generation_fallback(): async def test_prepare_options_store_parameter_handling() -> None: client = OpenAIResponsesClient(model_id="test-model", api_key="test-key") - messages = [ChatMessage(role="user", text="Test message")] + messages = [ChatMessage("user", ["Test message"])] test_conversation_id = "test-conversation-123" chat_options = ChatOptions(store=True, conversation_id=test_conversation_id) @@ -2117,7 +2116,7 @@ async def test_prepare_options_store_parameter_handling() -> None: async def test_conversation_id_precedence_kwargs_over_options() -> None: """When both kwargs and options contain conversation_id, kwargs wins.""" client = OpenAIResponsesClient(model_id="test-model", api_key="test-key") - messages = [ChatMessage(role="user", text="Hello")] + messages = [ChatMessage("user", ["Hello"])] # options has a stale response id, kwargs carries the freshest one opts = {"conversation_id": "resp_old_123"} @@ -2224,14 +2223,14 @@ async def test_integration_options( # Prepare test message if option_name.startswith("tools") or option_name.startswith("tool_choice"): # Use weather-related prompt for tool tests - messages = [ChatMessage(role="user", text="What is the weather in Seattle?")] + messages = [ChatMessage("user", ["What is the weather in Seattle?"])] elif option_name.startswith("response_format"): # Use prompt that works well with structured output - messages = [ChatMessage(role="user", text="The weather in Seattle is sunny")] - messages.append(ChatMessage(role="user", text="What is the weather in Seattle?")) + messages = [ChatMessage("user", ["The weather in Seattle is sunny"])] + messages.append(ChatMessage("user", ["What is the weather in Seattle?"])) else: # Generic prompt for simple options - messages = [ChatMessage(role="user", text="Say 'Hello World' briefly.")] + messages = [ChatMessage("user", ["Say 'Hello World' briefly."])] # Build options dict options: dict[str, Any] = {option_name: option_value} @@ -2248,7 +2247,7 @@ async def test_integration_options( ) output_format = option_value if option_name.startswith("response_format") else None - response = await ChatResponse.from_chat_response_generator(response_gen, output_format_type=output_format) + response = await ChatResponse.from_update_generator(response_gen, output_format_type=output_format) else: # Test non-streaming mode response = await openai_responses_client.get_response( @@ -2296,7 +2295,7 @@ async def test_integration_web_search() -> None: }, } if streaming: - response = await ChatResponse.from_chat_response_generator(client.get_streaming_response(**content)) + response = await ChatResponse.from_update_generator(client.get_streaming_response(**content)) else: response = await client.get_response(**content) @@ -2321,7 +2320,7 @@ async def test_integration_web_search() -> None: }, } if streaming: - response = await ChatResponse.from_chat_response_generator(client.get_streaming_response(**content)) + response = await ChatResponse.from_update_generator(client.get_streaming_response(**content)) else: response = await client.get_response(**content) assert response.text is not None diff --git a/python/packages/core/tests/workflow/test_agent_executor.py b/python/packages/core/tests/workflow/test_agent_executor.py index 0fa2bfd952..0d4912bae1 100644 --- a/python/packages/core/tests/workflow/test_agent_executor.py +++ b/python/packages/core/tests/workflow/test_agent_executor.py @@ -12,7 +12,6 @@ ChatMessage, ChatMessageStore, Content, - Role, SequentialBuilder, WorkflowOutputEvent, WorkflowRunState, @@ -37,9 +36,7 @@ async def run( # type: ignore[override] **kwargs: Any, ) -> AgentResponse: self.call_count += 1 - return AgentResponse( - messages=[ChatMessage(role=Role.ASSISTANT, text=f"Response #{self.call_count}: {self.name}")] - ) + return AgentResponse(messages=[ChatMessage("assistant", [f"Response #{self.call_count}: {self.name}"])]) async def run_stream( # type: ignore[override] self, @@ -62,8 +59,8 @@ async def test_agent_executor_checkpoint_stores_and_restores_state() -> None: # Add some initial messages to the thread to verify thread state persistence initial_messages = [ - ChatMessage(role=Role.USER, text="Initial message 1"), - ChatMessage(role=Role.ASSISTANT, text="Initial response 1"), + ChatMessage("user", ["Initial message 1"]), + ChatMessage("assistant", ["Initial response 1"]), ] await initial_thread.on_new_messages(initial_messages) @@ -166,9 +163,9 @@ async def test_agent_executor_save_and_restore_state_directly() -> None: # Add messages to thread thread_messages = [ - ChatMessage(role=Role.USER, text="Message in thread 1"), - ChatMessage(role=Role.ASSISTANT, text="Thread response 1"), - ChatMessage(role=Role.USER, text="Message in thread 2"), + ChatMessage("user", ["Message in thread 1"]), + ChatMessage("assistant", ["Thread response 1"]), + ChatMessage("user", ["Message in thread 2"]), ] await thread.on_new_messages(thread_messages) @@ -176,8 +173,8 @@ async def test_agent_executor_save_and_restore_state_directly() -> None: # Add messages to executor cache cache_messages = [ - ChatMessage(role=Role.USER, text="Cached user message"), - ChatMessage(role=Role.ASSISTANT, text="Cached assistant response"), + ChatMessage("user", ["Cached user message"]), + ChatMessage("assistant", ["Cached assistant response"]), ] executor._cache = list(cache_messages) # type: ignore[reportPrivateUsage] diff --git a/python/packages/core/tests/workflow/test_agent_executor_tool_calls.py b/python/packages/core/tests/workflow/test_agent_executor_tool_calls.py index 874f73fa5b..2b1f11423b 100644 --- a/python/packages/core/tests/workflow/test_agent_executor_tool_calls.py +++ b/python/packages/core/tests/workflow/test_agent_executor_tool_calls.py @@ -21,7 +21,6 @@ ChatResponseUpdate, Content, RequestInfoEvent, - Role, WorkflowBuilder, WorkflowContext, WorkflowOutputEvent, @@ -45,7 +44,7 @@ async def run( **kwargs: Any, ) -> AgentResponse: """Non-streaming run - not used in this test.""" - return AgentResponse(messages=[ChatMessage(role=Role.ASSISTANT, text="done")]) + return AgentResponse(messages=[ChatMessage("assistant", ["done"])]) async def run_stream( self, @@ -58,7 +57,7 @@ async def run_stream( # First update: some text yield AgentResponseUpdate( contents=[Content.from_text(text="Let me search for that...")], - role=Role.ASSISTANT, + role="assistant", ) # Second update: tool call (no text!) @@ -70,7 +69,7 @@ async def run_stream( arguments={"query": "weather"}, ) ], - role=Role.ASSISTANT, + role="assistant", ) # Third update: tool result (no text!) @@ -81,13 +80,13 @@ async def run_stream( result={"temperature": 72, "condition": "sunny"}, ) ], - role=Role.TOOL, + role="tool", ) # Fourth update: final text response yield AgentResponseUpdate( contents=[Content.from_text(text="The weather is sunny, 72°F.")], - role=Role.ASSISTANT, + role="assistant", ) @@ -179,7 +178,7 @@ async def get_response( ) ) else: - response = ChatResponse(messages=ChatMessage(role="assistant", text="Tool executed successfully.")) + response = ChatResponse(messages=ChatMessage("assistant", ["Tool executed successfully."])) self._iteration += 1 return response @@ -212,7 +211,7 @@ async def get_streaming_response( role="assistant", ) else: - yield ChatResponseUpdate(text=Content.from_text(text="Tool executed "), role="assistant") + yield ChatResponseUpdate(contents=[Content.from_text(text="Tool executed ")], role="assistant") yield ChatResponseUpdate(contents=[Content.from_text(text="successfully.")], role="assistant") self._iteration += 1 diff --git a/python/packages/core/tests/workflow/test_agent_run_event_typing.py b/python/packages/core/tests/workflow/test_agent_run_event_typing.py index e5071a7c96..4ba1328fc1 100644 --- a/python/packages/core/tests/workflow/test_agent_run_event_typing.py +++ b/python/packages/core/tests/workflow/test_agent_run_event_typing.py @@ -2,13 +2,13 @@ """Tests for AgentRunEvent and AgentRunUpdateEvent type annotations.""" -from agent_framework import AgentResponse, AgentResponseUpdate, ChatMessage, Role +from agent_framework import AgentResponse, AgentResponseUpdate, ChatMessage from agent_framework._workflows._events import AgentRunEvent, AgentRunUpdateEvent def test_agent_run_event_data_type() -> None: """Verify AgentRunEvent.data is typed as AgentResponse | None.""" - response = AgentResponse(messages=[ChatMessage(role=Role.ASSISTANT, text="Hello")]) + response = AgentResponse(messages=[ChatMessage("assistant", ["Hello"])]) event = AgentRunEvent(executor_id="test", data=response) # This assignment should pass type checking without a cast diff --git a/python/packages/core/tests/workflow/test_concurrent.py b/python/packages/core/tests/workflow/test_concurrent.py index a0c03c7720..d1fee3684e 100644 --- a/python/packages/core/tests/workflow/test_concurrent.py +++ b/python/packages/core/tests/workflow/test_concurrent.py @@ -12,7 +12,6 @@ ChatMessage, ConcurrentBuilder, Executor, - Role, WorkflowContext, WorkflowOutputEvent, WorkflowRunState, @@ -36,7 +35,7 @@ def __init__(self, id: str, reply_text: str) -> None: @handler async def run(self, request: AgentExecutorRequest, ctx: WorkflowContext[AgentExecutorResponse]) -> None: - response = AgentResponse(messages=ChatMessage(Role.ASSISTANT, text=self._reply_text)) + response = AgentResponse(messages=ChatMessage("assistant", text=self._reply_text)) full_conversation = list(request.messages) + list(response.messages) await ctx.send_message(AgentExecutorResponse(self.id, response, full_conversation=full_conversation)) @@ -126,12 +125,12 @@ async def test_concurrent_default_aggregator_emits_single_user_and_assistants() # Expect one user message + one assistant message per participant assert len(messages) == 1 + 3 - assert messages[0].role == Role.USER + assert messages[0].role == "user" assert "hello world" in messages[0].text assistant_texts = {m.text for m in messages[1:]} assert assistant_texts == {"Alpha", "Beta", "Gamma"} - assert all(m.role == Role.ASSISTANT for m in messages[1:]) + assert all(m.role == "assistant" for m in messages[1:]) async def test_concurrent_custom_aggregator_callback_is_used() -> None: @@ -543,9 +542,9 @@ def create_agent3() -> Executor: # Expect one user message + one assistant message per participant assert len(messages) == 1 + 3 - assert messages[0].role == Role.USER + assert messages[0].role == "user" assert "test prompt" in messages[0].text assistant_texts = {m.text for m in messages[1:]} assert assistant_texts == {"Alpha", "Beta", "Gamma"} - assert all(m.role == Role.ASSISTANT for m in messages[1:]) + assert all(m.role == "assistant" for m in messages[1:]) diff --git a/python/packages/core/tests/workflow/test_executor.py b/python/packages/core/tests/workflow/test_executor.py index e7c2a31aec..d4e950d62d 100644 --- a/python/packages/core/tests/workflow/test_executor.py +++ b/python/packages/core/tests/workflow/test_executor.py @@ -537,7 +537,7 @@ async def test_executor_invoked_event_data_not_mutated_by_handler(): async def mutator(messages: list[ChatMessage], ctx: WorkflowContext[list[ChatMessage]]) -> None: # The handler mutates the input list by appending new messages original_len = len(messages) - messages.append(ChatMessage(role="assistant", text="Added by executor")) + messages.append(ChatMessage("assistant", ["Added by executor"])) await ctx.send_message(messages) # Verify mutation happened assert len(messages) == original_len + 1 @@ -545,7 +545,7 @@ async def mutator(messages: list[ChatMessage], ctx: WorkflowContext[list[ChatMes workflow = WorkflowBuilder().set_start_executor(mutator).build() # Run with a single user message - input_messages = [ChatMessage(role="user", text="hello")] + input_messages = [ChatMessage("user", ["hello"])] events = await workflow.run(input_messages) # Find the invoked event for the Mutator executor diff --git a/python/packages/core/tests/workflow/test_full_conversation.py b/python/packages/core/tests/workflow/test_full_conversation.py index 9a8f4bd9c9..1c84e04494 100644 --- a/python/packages/core/tests/workflow/test_full_conversation.py +++ b/python/packages/core/tests/workflow/test_full_conversation.py @@ -16,7 +16,6 @@ ChatMessage, Content, Executor, - Role, SequentialBuilder, WorkflowBuilder, WorkflowContext, @@ -40,7 +39,7 @@ async def run( # type: ignore[override] thread: AgentThread | None = None, **kwargs: Any, ) -> AgentResponse: - return AgentResponse(messages=[ChatMessage(role=Role.ASSISTANT, text=self._reply_text)]) + return AgentResponse(messages=[ChatMessage("assistant", [self._reply_text])]) async def run_stream( # type: ignore[override] self, @@ -89,8 +88,8 @@ async def test_agent_executor_populates_full_conversation_non_streaming() -> Non # Assert: full_conversation contains [user("hello world"), assistant("agent-reply")] assert isinstance(payload, dict) assert payload["length"] == 2 - assert payload["roles"][0] == Role.USER and "hello world" in (payload["texts"][0] or "") - assert payload["roles"][1] == Role.ASSISTANT and "agent-reply" in (payload["texts"][1] or "") + assert payload["roles"][0] == "user" and "hello world" in (payload["texts"][0] or "") + assert payload["roles"][1] == "assistant" and "agent-reply" in (payload["texts"][1] or "") class _CaptureAgent(BaseAgent): @@ -116,9 +115,9 @@ async def run( # type: ignore[override] if isinstance(m, ChatMessage): norm.append(m) elif isinstance(m, str): - norm.append(ChatMessage(role=Role.USER, text=m)) + norm.append(ChatMessage("user", [m])) self._last_messages = norm - return AgentResponse(messages=[ChatMessage(role=Role.ASSISTANT, text=self._reply_text)]) + return AgentResponse(messages=[ChatMessage("assistant", [self._reply_text])]) async def run_stream( # type: ignore[override] self, @@ -134,7 +133,7 @@ async def run_stream( # type: ignore[override] if isinstance(m, ChatMessage): norm.append(m) elif isinstance(m, str): - norm.append(ChatMessage(role=Role.USER, text=m)) + norm.append(ChatMessage("user", [m])) self._last_messages = norm yield AgentResponseUpdate(contents=[Content.from_text(text=self._reply_text)]) @@ -154,5 +153,5 @@ async def test_sequential_adapter_uses_full_conversation() -> None: # Assert: second agent should have seen the user prompt and A1's assistant reply seen = a2._last_messages # pyright: ignore[reportPrivateUsage] assert len(seen) == 2 - assert seen[0].role == Role.USER and "hello seq" in (seen[0].text or "") - assert seen[1].role == Role.ASSISTANT and "A1 reply" in (seen[1].text or "") + assert seen[0].role == "user" and "hello seq" in (seen[0].text or "") + assert seen[1].role == "assistant" and "A1 reply" in (seen[1].text or "") diff --git a/python/packages/core/tests/workflow/test_group_chat.py b/python/packages/core/tests/workflow/test_group_chat.py index e75bdfd638..21f1e567d3 100644 --- a/python/packages/core/tests/workflow/test_group_chat.py +++ b/python/packages/core/tests/workflow/test_group_chat.py @@ -25,7 +25,6 @@ MagenticProgressLedger, MagenticProgressLedgerItem, RequestInfoEvent, - Role, WorkflowOutputEvent, WorkflowRunState, WorkflowStatusEvent, @@ -45,7 +44,7 @@ async def run( # type: ignore[override] thread: AgentThread | None = None, **kwargs: Any, ) -> AgentResponse: - response = ChatMessage(role=Role.ASSISTANT, text=self._reply_text, author_name=self.name) + response = ChatMessage("assistant", [self._reply_text], author_name=self.name) return AgentResponse(messages=[response]) def run_stream( # type: ignore[override] @@ -57,7 +56,7 @@ def run_stream( # type: ignore[override] ) -> AsyncIterable[AgentResponseUpdate]: async def _stream() -> AsyncIterable[AgentResponseUpdate]: yield AgentResponseUpdate( - contents=[Content.from_text(text=self._reply_text)], role=Role.ASSISTANT, author_name=self.name + contents=[Content.from_text(text=self._reply_text)], role="assistant", author_name=self.name ) return _stream() @@ -94,7 +93,7 @@ async def run( return AgentResponse( messages=[ ChatMessage( - role=Role.ASSISTANT, + role="assistant", text=( '{"terminate": false, "reason": "Selecting agent", ' '"next_speaker": "agent", "final_message": null}' @@ -115,7 +114,7 @@ async def run( return AgentResponse( messages=[ ChatMessage( - role=Role.ASSISTANT, + role="assistant", text=( '{"terminate": true, "reason": "Task complete", ' '"next_speaker": null, "final_message": "agent manager final"}' @@ -146,7 +145,7 @@ async def _stream_initial() -> AsyncIterable[AgentResponseUpdate]: ) ) ], - role=Role.ASSISTANT, + role="assistant", author_name=self.name, ) @@ -162,7 +161,7 @@ async def _stream_final() -> AsyncIterable[AgentResponseUpdate]: ) ) ], - role=Role.ASSISTANT, + role="assistant", author_name=self.name, ) @@ -192,7 +191,7 @@ def __init__(self) -> None: self._round = 0 async def plan(self, magentic_context: MagenticContext) -> ChatMessage: - return ChatMessage(role=Role.ASSISTANT, text="plan", author_name="magentic_manager") + return ChatMessage("assistant", ["plan"], author_name="magentic_manager") async def replan(self, magentic_context: MagenticContext) -> ChatMessage: return await self.plan(magentic_context) @@ -218,7 +217,7 @@ async def create_progress_ledger(self, magentic_context: MagenticContext) -> Mag ) async def prepare_final_answer(self, magentic_context: MagenticContext) -> ChatMessage: - return ChatMessage(role=Role.ASSISTANT, text="final", author_name="magentic_manager") + return ChatMessage("assistant", ["final"], author_name="magentic_manager") async def test_group_chat_builder_basic_flow() -> None: @@ -263,8 +262,8 @@ async def test_group_chat_as_agent_accepts_conversation() -> None: agent = workflow.as_agent(name="group-chat-agent") conversation = [ - ChatMessage(role=Role.USER, text="kickoff", author_name="user"), - ChatMessage(role=Role.ASSISTANT, text="noted", author_name="alpha"), + ChatMessage("user", ["kickoff"], author_name="user"), + ChatMessage("assistant", ["noted"], author_name="alpha"), ] response = await agent.run(conversation) @@ -425,7 +424,7 @@ def selector(state: GroupChatState) -> str: return "agent" def termination_condition(conversation: list[ChatMessage]) -> bool: - replies = [msg for msg in conversation if msg.role == Role.ASSISTANT and msg.author_name == "agent"] + replies = [msg for msg in conversation if msg.role == "assistant" and msg.author_name == "agent"] return len(replies) >= 2 agent = StubAgent("agent", "response") @@ -447,7 +446,7 @@ def termination_condition(conversation: list[ChatMessage]) -> bool: assert outputs, "Expected termination to yield output" conversation = outputs[-1] - agent_replies = [msg for msg in conversation if msg.author_name == "agent" and msg.role == Role.ASSISTANT] + agent_replies = [msg for msg in conversation if msg.author_name == "agent" and msg.role == "assistant"] assert len(agent_replies) == 2 final_output = conversation[-1] # The orchestrator uses its ID as author_name by default @@ -553,7 +552,7 @@ async def test_handle_string_input(self) -> None: def selector(state: GroupChatState) -> str: # Verify the conversation has the user message assert len(state.conversation) > 0 - assert state.conversation[0].role == Role.USER + assert state.conversation[0].role == "user" assert state.conversation[0].text == "test string" return "agent" @@ -578,7 +577,7 @@ def selector(state: GroupChatState) -> str: async def test_handle_chat_message_input(self) -> None: """Test handling ChatMessage input directly.""" - task_message = ChatMessage(role=Role.USER, text="test message") + task_message = ChatMessage("user", ["test message"]) def selector(state: GroupChatState) -> str: # Verify the task message was preserved in conversation @@ -608,8 +607,8 @@ def selector(state: GroupChatState) -> str: async def test_handle_conversation_list_input(self) -> None: """Test handling conversation list preserves context.""" conversation = [ - ChatMessage(role=Role.SYSTEM, text="system message"), - ChatMessage(role=Role.USER, text="user message"), + ChatMessage("system", ["system message"]), + ChatMessage("user", ["user message"]), ] def selector(state: GroupChatState) -> str: @@ -1118,7 +1117,7 @@ async def run( return AgentResponse( messages=[ ChatMessage( - role=Role.ASSISTANT, + role="assistant", text=( '{"terminate": false, "reason": "Selecting alpha", ' '"next_speaker": "alpha", "final_message": null}' @@ -1138,7 +1137,7 @@ async def run( return AgentResponse( messages=[ ChatMessage( - role=Role.ASSISTANT, + role="assistant", text=( '{"terminate": true, "reason": "Task complete", ' '"next_speaker": null, "final_message": "dynamic manager final"}' diff --git a/python/packages/core/tests/workflow/test_handoff.py b/python/packages/core/tests/workflow/test_handoff.py index 130bacb0ed..962ab88f16 100644 --- a/python/packages/core/tests/workflow/test_handoff.py +++ b/python/packages/core/tests/workflow/test_handoff.py @@ -15,7 +15,6 @@ HandoffAgentUserRequest, HandoffBuilder, RequestInfoEvent, - Role, WorkflowEvent, WorkflowOutputEvent, resolve_agent_id, @@ -49,7 +48,7 @@ def __init__( async def get_response(self, messages: Any, **kwargs: Any) -> ChatResponse: contents = _build_reply_contents(self._name, self._handoff_to, self._next_call_id()) reply = ChatMessage( - role=Role.ASSISTANT, + role="assistant", contents=contents, ) return ChatResponse(messages=reply, response_id="mock_response") @@ -57,7 +56,7 @@ async def get_response(self, messages: Any, **kwargs: Any) -> ChatResponse: def get_streaming_response(self, messages: Any, **kwargs: Any) -> AsyncIterable[ChatResponseUpdate]: async def _stream() -> AsyncIterable[ChatResponseUpdate]: contents = _build_reply_contents(self._name, self._handoff_to, self._next_call_id()) - yield ChatResponseUpdate(contents=contents, role=Role.ASSISTANT) + yield ChatResponseUpdate(contents=contents, role="assistant") return _stream() @@ -123,7 +122,7 @@ async def test_handoff(): workflow = ( HandoffBuilder(participants=[triage, specialist, escalation]) .with_start_agent(triage) - .with_termination_condition(lambda conv: sum(1 for m in conv if m.role == Role.USER) >= 2) + .with_termination_condition(lambda conv: sum(1 for m in conv if m.role == "user") >= 2) .build() ) @@ -174,9 +173,7 @@ async def test_autonomous_mode_yields_output_without_user_request(): final_conversation = outputs[-1].data assert isinstance(final_conversation, list) conversation_list = cast(list[ChatMessage], final_conversation) - assert any( - msg.role == Role.ASSISTANT and (msg.text or "").startswith("specialist reply") for msg in conversation_list - ) + assert any(msg.role == "assistant" and (msg.text or "").startswith("specialist reply") for msg in conversation_list) async def test_autonomous_mode_resumes_user_input_on_turn_limit(): @@ -222,7 +219,7 @@ async def test_handoff_async_termination_condition() -> None: async def async_termination(conv: list[ChatMessage]) -> bool: nonlocal termination_call_count termination_call_count += 1 - user_count = sum(1 for msg in conv if msg.role == Role.USER) + user_count = sum(1 for msg in conv if msg.role == "user") return user_count >= 2 coordinator = MockHandoffAgent(name="coordinator", handoff_to="worker") @@ -240,9 +237,7 @@ async def async_termination(conv: list[ChatMessage]) -> bool: assert requests events = await _drain( - workflow.send_responses_streaming({ - requests[-1].request_id: [ChatMessage(role=Role.USER, text="Second user message")] - }) + workflow.send_responses_streaming({requests[-1].request_id: [ChatMessage("user", ["Second user message"])]}) ) outputs = [ev for ev in events if isinstance(ev, WorkflowOutputEvent)] assert len(outputs) == 1 @@ -250,7 +245,7 @@ async def async_termination(conv: list[ChatMessage]) -> bool: final_conversation = outputs[0].data assert isinstance(final_conversation, list) final_conv_list = cast(list[ChatMessage], final_conversation) - user_messages = [msg for msg in final_conv_list if msg.role == Role.USER] + user_messages = [msg for msg in final_conv_list if msg.role == "user"] assert len(user_messages) == 2 assert termination_call_count > 0 @@ -264,7 +259,7 @@ async def mock_get_response(messages: Any, options: dict[str, Any] | None = None if options: recorded_tool_choices.append(options.get("tool_choice")) return ChatResponse( - messages=[ChatMessage(role=Role.ASSISTANT, text="Response")], + messages=[ChatMessage("assistant", ["Response"])], response_id="test_response", ) @@ -480,7 +475,7 @@ def create_specialist() -> MockHandoffAgent: workflow = ( HandoffBuilder(participant_factories={"triage": create_triage, "specialist": create_specialist}) .with_start_agent("triage") - .with_termination_condition(lambda conv: sum(1 for m in conv if m.role == Role.USER) >= 2) + .with_termination_condition(lambda conv: sum(1 for m in conv if m.role == "user") >= 2) .build() ) @@ -493,7 +488,7 @@ def create_specialist() -> MockHandoffAgent: # Follow-up message events = await _drain( - workflow.send_responses_streaming({requests[-1].request_id: [ChatMessage(role=Role.USER, text="More details")]}) + workflow.send_responses_streaming({requests[-1].request_id: [ChatMessage("user", ["More details"])]}) ) outputs = [ev for ev in events if isinstance(ev, WorkflowOutputEvent)] assert outputs @@ -553,7 +548,7 @@ def create_specialist_b() -> MockHandoffAgent: .with_start_agent("triage") .add_handoff("triage", ["specialist_a", "specialist_b"]) .add_handoff("specialist_a", ["specialist_b"]) - .with_termination_condition(lambda conv: sum(1 for m in conv if m.role == Role.USER) >= 3) + .with_termination_condition(lambda conv: sum(1 for m in conv if m.role == "user") >= 3) .build() ) @@ -567,9 +562,7 @@ def create_specialist_b() -> MockHandoffAgent: # Second user message - specialist_a hands off to specialist_b events = await _drain( - workflow.send_responses_streaming({ - requests[-1].request_id: [ChatMessage(role=Role.USER, text="Need escalation")] - }) + workflow.send_responses_streaming({requests[-1].request_id: [ChatMessage("user", ["Need escalation"])]}) ) requests = [ev for ev in events if isinstance(ev, RequestInfoEvent)] assert requests @@ -594,7 +587,7 @@ def create_specialist() -> MockHandoffAgent: HandoffBuilder(participant_factories={"triage": create_triage, "specialist": create_specialist}) .with_start_agent("triage") .with_checkpointing(storage) - .with_termination_condition(lambda conv: sum(1 for m in conv if m.role == Role.USER) >= 2) + .with_termination_condition(lambda conv: sum(1 for m in conv if m.role == "user") >= 2) .build() ) @@ -604,7 +597,7 @@ def create_specialist() -> MockHandoffAgent: assert requests events = await _drain( - workflow.send_responses_streaming({requests[-1].request_id: [ChatMessage(role=Role.USER, text="follow up")]}) + workflow.send_responses_streaming({requests[-1].request_id: [ChatMessage("user", ["follow up"])]}) ) outputs = [ev for ev in events if isinstance(ev, WorkflowOutputEvent)] assert outputs, "Should have workflow output after termination condition is met" diff --git a/python/packages/core/tests/workflow/test_magentic.py b/python/packages/core/tests/workflow/test_magentic.py index 9c6a2521b1..8f116aa1ad 100644 --- a/python/packages/core/tests/workflow/test_magentic.py +++ b/python/packages/core/tests/workflow/test_magentic.py @@ -27,7 +27,6 @@ MagenticProgressLedger, MagenticProgressLedgerItem, RequestInfoEvent, - Role, StandardMagenticManager, Workflow, WorkflowCheckpoint, @@ -53,7 +52,7 @@ def test_magentic_context_reset_behavior(): participant_descriptions={"Alice": "Researcher"}, ) # seed context state - ctx.chat_history.append(ChatMessage(role=Role.ASSISTANT, text="draft")) + ctx.chat_history.append(ChatMessage("assistant", ["draft"])) ctx.stall_count = 2 prev_reset = ctx.reset_count @@ -120,18 +119,18 @@ def on_checkpoint_restore(self, state: dict[str, Any]) -> None: pass async def plan(self, magentic_context: MagenticContext) -> ChatMessage: - facts = ChatMessage(role=Role.ASSISTANT, text="GIVEN OR VERIFIED FACTS\n- A\n") - plan = ChatMessage(role=Role.ASSISTANT, text="- Do X\n- Do Y\n") + facts = ChatMessage("assistant", ["GIVEN OR VERIFIED FACTS\n- A\n"]) + plan = ChatMessage("assistant", ["- Do X\n- Do Y\n"]) self.task_ledger = _SimpleLedger(facts=facts, plan=plan) combined = f"Task: {magentic_context.task}\n\nFacts:\n{facts.text}\n\nPlan:\n{plan.text}" - return ChatMessage(role=Role.ASSISTANT, text=combined, author_name=self.name) + return ChatMessage("assistant", [combined], author_name=self.name) async def replan(self, magentic_context: MagenticContext) -> ChatMessage: - facts = ChatMessage(role=Role.ASSISTANT, text="GIVEN OR VERIFIED FACTS\n- A2\n") - plan = ChatMessage(role=Role.ASSISTANT, text="- Do Z\n") + facts = ChatMessage("assistant", ["GIVEN OR VERIFIED FACTS\n- A2\n"]) + plan = ChatMessage("assistant", ["- Do Z\n"]) self.task_ledger = _SimpleLedger(facts=facts, plan=plan) combined = f"Task: {magentic_context.task}\n\nFacts:\n{facts.text}\n\nPlan:\n{plan.text}" - return ChatMessage(role=Role.ASSISTANT, text=combined, author_name=self.name) + return ChatMessage("assistant", [combined], author_name=self.name) async def create_progress_ledger(self, magentic_context: MagenticContext) -> MagenticProgressLedger: # At least two messages in chat history means request is satisfied for testing @@ -145,7 +144,7 @@ async def create_progress_ledger(self, magentic_context: MagenticContext) -> Mag ) async def prepare_final_answer(self, magentic_context: MagenticContext) -> ChatMessage: - return ChatMessage(role=Role.ASSISTANT, text=self.FINAL_ANSWER, author_name=self.name) + return ChatMessage("assistant", [self.FINAL_ANSWER], author_name=self.name) class StubAgent(BaseAgent): @@ -160,7 +159,7 @@ async def run( # type: ignore[override] thread: AgentThread | None = None, **kwargs: Any, ) -> AgentResponse: - response = ChatMessage(role=Role.ASSISTANT, text=self._reply_text, author_name=self.name) + response = ChatMessage("assistant", [self._reply_text], author_name=self.name) return AgentResponse(messages=[response]) def run_stream( # type: ignore[override] @@ -172,7 +171,7 @@ def run_stream( # type: ignore[override] ) -> AsyncIterable[AgentResponseUpdate]: async def _stream() -> AsyncIterable[AgentResponseUpdate]: yield AgentResponseUpdate( - contents=[Content.from_text(text=self._reply_text)], role=Role.ASSISTANT, author_name=self.name + contents=[Content.from_text(text=self._reply_text)], role="assistant", author_name=self.name ) return _stream() @@ -223,8 +222,8 @@ async def test_magentic_as_agent_does_not_accept_conversation() -> None: agent = workflow.as_agent(name="magentic-agent") conversation = [ - ChatMessage(role=Role.SYSTEM, text="Guidelines", author_name="system"), - ChatMessage(role=Role.USER, text="Summarize the findings", author_name="requester"), + ChatMessage("system", ["Guidelines"], author_name="system"), + ChatMessage("user", ["Summarize the findings"], author_name="requester"), ] with pytest.raises(ValueError, match="Magentic only support a single task message to start the workflow."): await agent.run(conversation) @@ -238,7 +237,7 @@ async def test_standard_manager_plan_and_replan_combined_ledger(): ) first = await manager.plan(ctx.clone()) - assert first.role == Role.ASSISTANT and "Facts:" in first.text and "Plan:" in first.text + assert first.role == "assistant" and "Facts:" in first.text and "Plan:" in first.text assert manager.task_ledger is not None replanned = await manager.replan(ctx.clone()) @@ -352,7 +351,7 @@ async def test_magentic_orchestrator_round_limit_produces_partial_result(): data = output_event.data assert isinstance(data, list) assert len(data) > 0 # type: ignore - assert data[-1].role == Role.ASSISTANT # type: ignore + assert data[-1].role == "assistant" # type: ignore assert all(isinstance(msg, ChatMessage) for msg in data) # type: ignore @@ -427,7 +426,7 @@ async def run( thread: Any = None, **kwargs: Any, ) -> AgentResponse: - return AgentResponse(messages=[ChatMessage(role=Role.ASSISTANT, text="ok")]) + return AgentResponse(messages=[ChatMessage("assistant", ["ok"])]) def run_stream( self, @@ -437,7 +436,7 @@ def run_stream( **kwargs: Any, ) -> AsyncIterable[AgentResponseUpdate]: async def _gen() -> AsyncIterable[AgentResponseUpdate]: - yield AgentResponseUpdate(message_deltas=[ChatMessage(role=Role.ASSISTANT, text="ok")]) + yield AgentResponseUpdate(message_deltas=[ChatMessage("assistant", ["ok"])]) return _gen() @@ -448,8 +447,8 @@ async def test_standard_manager_plan_and_replan_via_complete_monkeypatch(): async def fake_complete_plan(messages: list[ChatMessage], **kwargs: Any) -> ChatMessage: # Return a different response depending on call order length if any("FACTS" in (m.text or "") for m in messages): - return ChatMessage(role=Role.ASSISTANT, text="- step A\n- step B") - return ChatMessage(role=Role.ASSISTANT, text="GIVEN OR VERIFIED FACTS\n- fact1") + return ChatMessage("assistant", ["- step A\n- step B"]) + return ChatMessage("assistant", ["GIVEN OR VERIFIED FACTS\n- fact1"]) # First, patch to produce facts then plan mgr._complete = fake_complete_plan # type: ignore[attr-defined] @@ -464,8 +463,8 @@ async def fake_complete_plan(messages: list[ChatMessage], **kwargs: Any) -> Chat # Now replan with new outputs async def fake_complete_replan(messages: list[ChatMessage], **kwargs: Any) -> ChatMessage: if any("Please briefly explain" in (m.text or "") for m in messages): - return ChatMessage(role=Role.ASSISTANT, text="- new step") - return ChatMessage(role=Role.ASSISTANT, text="GIVEN OR VERIFIED FACTS\n- updated") + return ChatMessage("assistant", ["- new step"]) + return ChatMessage("assistant", ["GIVEN OR VERIFIED FACTS\n- updated"]) mgr._complete = fake_complete_replan # type: ignore[attr-defined] combined2 = await mgr.replan(ctx.clone()) @@ -485,7 +484,7 @@ async def fake_complete_ok(messages: list[ChatMessage], **kwargs: Any) -> ChatMe '"next_speaker": {"reason": "r", "answer": "alice"}, ' '"instruction_or_question": {"reason": "r", "answer": "do"}}' ) - return ChatMessage(role=Role.ASSISTANT, text=json_text) + return ChatMessage("assistant", [json_text]) mgr._complete = fake_complete_ok # type: ignore[attr-defined] ledger = await mgr.create_progress_ledger(ctx.clone()) @@ -493,7 +492,7 @@ async def fake_complete_ok(messages: list[ChatMessage], **kwargs: Any) -> ChatMe # Error path: invalid JSON now raises to avoid emitting planner-oriented instructions to agents async def fake_complete_bad(messages: list[ChatMessage], **kwargs: Any) -> ChatMessage: - return ChatMessage(role=Role.ASSISTANT, text="not-json") + return ChatMessage("assistant", ["not-json"]) mgr._complete = fake_complete_bad # type: ignore[attr-defined] with pytest.raises(RuntimeError): @@ -506,10 +505,10 @@ def __init__(self) -> None: self._invoked = False async def plan(self, magentic_context: MagenticContext) -> ChatMessage: - return ChatMessage(role=Role.ASSISTANT, text="ledger") + return ChatMessage("assistant", ["ledger"]) async def replan(self, magentic_context: MagenticContext) -> ChatMessage: - return ChatMessage(role=Role.ASSISTANT, text="re-ledger") + return ChatMessage("assistant", ["re-ledger"]) async def create_progress_ledger(self, magentic_context: MagenticContext) -> MagenticProgressLedger: if not self._invoked: @@ -532,7 +531,7 @@ async def create_progress_ledger(self, magentic_context: MagenticContext) -> Mag ) async def prepare_final_answer(self, magentic_context: MagenticContext) -> ChatMessage: - return ChatMessage(role=Role.ASSISTANT, text="final") + return ChatMessage("assistant", ["final"]) class StubThreadAgent(BaseAgent): @@ -543,11 +542,11 @@ async def run_stream(self, messages=None, *, thread=None, **kwargs): # type: ig yield AgentResponseUpdate( contents=[Content.from_text(text="thread-ok")], author_name=self.name, - role=Role.ASSISTANT, + role="assistant", ) async def run(self, messages=None, *, thread=None, **kwargs): # type: ignore[override] - return AgentResponse(messages=[ChatMessage(role=Role.ASSISTANT, text="thread-ok", author_name=self.name)]) + return AgentResponse(messages=[ChatMessage("assistant", ["thread-ok"], author_name=self.name)]) class StubAssistantsClient: @@ -565,11 +564,11 @@ async def run_stream(self, messages=None, *, thread=None, **kwargs): # type: ig yield AgentResponseUpdate( contents=[Content.from_text(text="assistants-ok")], author_name=self.name, - role=Role.ASSISTANT, + role="assistant", ) async def run(self, messages=None, *, thread=None, **kwargs): # type: ignore[override] - return AgentResponse(messages=[ChatMessage(role=Role.ASSISTANT, text="assistants-ok", author_name=self.name)]) + return AgentResponse(messages=[ChatMessage("assistant", ["assistants-ok"], author_name=self.name)]) async def _collect_agent_responses_setup(participant: AgentProtocol) -> list[ChatMessage]: @@ -586,7 +585,7 @@ async def _collect_agent_responses_setup(participant: AgentProtocol) -> list[Cha if isinstance(ev, AgentRunUpdateEvent): captured.append( ChatMessage( - role=ev.data.role or Role.ASSISTANT, + role=ev.data.role or "assistant", text=ev.data.text or "", author_name=ev.data.author_name, ) @@ -738,10 +737,10 @@ class NotProgressingManager(MagenticManagerBase): """ async def plan(self, magentic_context: MagenticContext) -> ChatMessage: - return ChatMessage(role=Role.ASSISTANT, text="ledger") + return ChatMessage("assistant", ["ledger"]) async def replan(self, magentic_context: MagenticContext) -> ChatMessage: - return ChatMessage(role=Role.ASSISTANT, text="re-ledger") + return ChatMessage("assistant", ["re-ledger"]) async def create_progress_ledger(self, magentic_context: MagenticContext) -> MagenticProgressLedger: return MagenticProgressLedger( @@ -753,7 +752,7 @@ async def create_progress_ledger(self, magentic_context: MagenticContext) -> Mag ) async def prepare_final_answer(self, magentic_context: MagenticContext) -> ChatMessage: - return ChatMessage(role=Role.ASSISTANT, text="final") + return ChatMessage("assistant", ["final"]) async def test_magentic_stall_and_reset_reach_limits(): @@ -851,8 +850,8 @@ async def test_magentic_context_no_duplicate_on_reset(): ctx = MagenticContext(task="task", participant_descriptions={"Alice": "Researcher"}) # Add some history - ctx.chat_history.append(ChatMessage(role=Role.ASSISTANT, text="response1")) - ctx.chat_history.append(ChatMessage(role=Role.ASSISTANT, text="response2")) + ctx.chat_history.append(ChatMessage("assistant", ["response1"])) + ctx.chat_history.append(ChatMessage("assistant", ["response2"])) assert len(ctx.chat_history) == 2 # Reset @@ -862,7 +861,7 @@ async def test_magentic_context_no_duplicate_on_reset(): assert len(ctx.chat_history) == 0, "chat_history should be empty after reset" # Add new history - ctx.chat_history.append(ChatMessage(role=Role.ASSISTANT, text="new_response")) + ctx.chat_history.append(ChatMessage("assistant", ["new_response"])) assert len(ctx.chat_history) == 1, "Should have exactly 1 message after adding to reset context" @@ -881,7 +880,7 @@ async def test_magentic_checkpoint_restore_no_duplicate_history(): # Run with conversation history to create initial checkpoint conversation: list[ChatMessage] = [ - ChatMessage(role=Role.USER, text="task_msg"), + ChatMessage("user", ["task_msg"]), ] async for event in wf.run_stream(conversation): @@ -1248,8 +1247,8 @@ def agent_factory() -> AgentProtocol: from agent_framework._workflows._magentic import _MagenticTaskLedger # type: ignore custom_task_ledger = _MagenticTaskLedger( - facts=ChatMessage(role=Role.ASSISTANT, text="Custom facts"), - plan=ChatMessage(role=Role.ASSISTANT, text="Custom plan"), + facts=ChatMessage("assistant", ["Custom facts"]), + plan=ChatMessage("assistant", ["Custom plan"]), ) participant = StubAgent("agentA", "reply from agentA") diff --git a/python/packages/core/tests/workflow/test_orchestration_request_info.py b/python/packages/core/tests/workflow/test_orchestration_request_info.py index 24b2239757..787a2c6642 100644 --- a/python/packages/core/tests/workflow/test_orchestration_request_info.py +++ b/python/packages/core/tests/workflow/test_orchestration_request_info.py @@ -14,7 +14,6 @@ AgentResponseUpdate, AgentThread, ChatMessage, - Role, ) from agent_framework._workflows._agent_executor import AgentExecutorRequest, AgentExecutorResponse from agent_framework._workflows._orchestration_request_info import ( @@ -73,7 +72,7 @@ class TestAgentRequestInfoResponse: def test_create_response_with_messages(self): """Test creating an AgentRequestInfoResponse with messages.""" - messages = [ChatMessage(role=Role.USER, text="Additional info")] + messages = [ChatMessage("user", ["Additional info"])] response = AgentRequestInfoResponse(messages=messages) assert response.messages == messages @@ -81,8 +80,8 @@ def test_create_response_with_messages(self): def test_from_messages_factory(self): """Test creating response from ChatMessage list.""" messages = [ - ChatMessage(role=Role.USER, text="Message 1"), - ChatMessage(role=Role.USER, text="Message 2"), + ChatMessage("user", ["Message 1"]), + ChatMessage("user", ["Message 2"]), ] response = AgentRequestInfoResponse.from_messages(messages) @@ -94,9 +93,9 @@ def test_from_strings_factory(self): response = AgentRequestInfoResponse.from_strings(texts) assert len(response.messages) == 2 - assert response.messages[0].role == Role.USER + assert response.messages[0].role == "user" assert response.messages[0].text == "First message" - assert response.messages[1].role == Role.USER + assert response.messages[1].role == "user" assert response.messages[1].text == "Second message" def test_approve_factory(self): @@ -114,7 +113,7 @@ async def test_request_info_handler(self): """Test that request_info handler calls ctx.request_info.""" executor = AgentRequestInfoExecutor(id="test_executor") - agent_response = AgentResponse(messages=[ChatMessage(role=Role.ASSISTANT, text="Agent response")]) + agent_response = AgentResponse(messages=[ChatMessage("assistant", ["Agent response"])]) agent_response = AgentExecutorResponse( executor_id="test_agent", agent_response=agent_response, @@ -132,7 +131,7 @@ async def test_handle_request_info_response_with_messages(self): """Test response handler when user provides additional messages.""" executor = AgentRequestInfoExecutor(id="test_executor") - agent_response = AgentResponse(messages=[ChatMessage(role=Role.ASSISTANT, text="Original")]) + agent_response = AgentResponse(messages=[ChatMessage("assistant", ["Original"])]) original_request = AgentExecutorResponse( executor_id="test_agent", agent_response=agent_response, @@ -158,7 +157,7 @@ async def test_handle_request_info_response_approval(self): """Test response handler when user approves (no additional messages).""" executor = AgentRequestInfoExecutor(id="test_executor") - agent_response = AgentResponse(messages=[ChatMessage(role=Role.ASSISTANT, text="Original")]) + agent_response = AgentResponse(messages=[ChatMessage("assistant", ["Original"])]) original_request = AgentExecutorResponse( executor_id="test_agent", agent_response=agent_response, @@ -207,7 +206,7 @@ async def run( **kwargs: Any, ) -> AgentResponse: """Dummy run method.""" - return AgentResponse(messages=[ChatMessage(role=Role.ASSISTANT, text="Test response")]) + return AgentResponse(messages=[ChatMessage("assistant", ["Test response"])]) def run_stream( self, @@ -219,7 +218,7 @@ def run_stream( """Dummy run_stream method.""" async def generator(): - yield AgentResponseUpdate(messages=[ChatMessage(role=Role.ASSISTANT, text="Test response stream")]) + yield AgentResponseUpdate(messages=[ChatMessage("assistant", ["Test response stream"])]) return generator() diff --git a/python/packages/core/tests/workflow/test_sequential.py b/python/packages/core/tests/workflow/test_sequential.py index a685db73db..e5b55ae081 100644 --- a/python/packages/core/tests/workflow/test_sequential.py +++ b/python/packages/core/tests/workflow/test_sequential.py @@ -14,7 +14,6 @@ ChatMessage, Content, Executor, - Role, SequentialBuilder, TypeCompatibilityError, WorkflowContext, @@ -36,7 +35,7 @@ async def run( # type: ignore[override] thread: AgentThread | None = None, **kwargs: Any, ) -> AgentResponse: - return AgentResponse(messages=[ChatMessage(role=Role.ASSISTANT, text=f"{self.name} reply")]) + return AgentResponse(messages=[ChatMessage("assistant", [f"{self.name} reply"])]) async def run_stream( # type: ignore[override] self, @@ -55,9 +54,9 @@ class _SummarizerExec(Executor): @handler async def summarize(self, agent_response: AgentExecutorResponse, ctx: WorkflowContext[list[ChatMessage]]) -> None: conversation = agent_response.full_conversation or [] - user_texts = [m.text for m in conversation if m.role == Role.USER] - agents = [m.author_name or m.role for m in conversation if m.role == Role.ASSISTANT] - summary = ChatMessage(role=Role.ASSISTANT, text=f"Summary of users:{len(user_texts)} agents:{len(agents)}") + user_texts = [m.text for m in conversation if m.role == "user"] + agents = [m.author_name or m.role for m in conversation if m.role == "assistant"] + summary = ChatMessage("assistant", [f"Summary of users:{len(user_texts)} agents:{len(agents)}"]) await ctx.send_message(list(conversation) + [summary]) @@ -119,9 +118,9 @@ async def test_sequential_agents_append_to_context() -> None: assert isinstance(output, list) msgs: list[ChatMessage] = output assert len(msgs) == 3 - assert msgs[0].role == Role.USER and "hello sequential" in msgs[0].text - assert msgs[1].role == Role.ASSISTANT and (msgs[1].author_name == "A1" or True) - assert msgs[2].role == Role.ASSISTANT and (msgs[2].author_name == "A2" or True) + assert msgs[0].role == "user" and "hello sequential" in msgs[0].text + assert msgs[1].role == "assistant" and (msgs[1].author_name == "A1" or True) + assert msgs[2].role == "assistant" and (msgs[2].author_name == "A2" or True) assert "A1 reply" in msgs[1].text assert "A2 reply" in msgs[2].text @@ -152,9 +151,9 @@ def create_agent2() -> _EchoAgent: assert isinstance(output, list) msgs: list[ChatMessage] = output assert len(msgs) == 3 - assert msgs[0].role == Role.USER and "hello factories" in msgs[0].text - assert msgs[1].role == Role.ASSISTANT and "A1 reply" in msgs[1].text - assert msgs[2].role == Role.ASSISTANT and "A2 reply" in msgs[2].text + assert msgs[0].role == "user" and "hello factories" in msgs[0].text + assert msgs[1].role == "assistant" and "A1 reply" in msgs[1].text + assert msgs[2].role == "assistant" and "A2 reply" in msgs[2].text async def test_sequential_with_custom_executor_summary() -> None: @@ -178,9 +177,9 @@ async def test_sequential_with_custom_executor_summary() -> None: msgs: list[ChatMessage] = output # Expect: [user, A1 reply, summary] assert len(msgs) == 3 - assert msgs[0].role == Role.USER - assert msgs[1].role == Role.ASSISTANT and "A1 reply" in msgs[1].text - assert msgs[2].role == Role.ASSISTANT and msgs[2].text.startswith("Summary of users:") + assert msgs[0].role == "user" + assert msgs[1].role == "assistant" and "A1 reply" in msgs[1].text + assert msgs[2].role == "assistant" and msgs[2].text.startswith("Summary of users:") async def test_sequential_register_participants_mixed_agents_and_executors() -> None: @@ -209,9 +208,9 @@ def create_summarizer() -> _SummarizerExec: msgs: list[ChatMessage] = output # Expect: [user, A1 reply, summary] assert len(msgs) == 3 - assert msgs[0].role == Role.USER and "topic Y" in msgs[0].text - assert msgs[1].role == Role.ASSISTANT and "A1 reply" in msgs[1].text - assert msgs[2].role == Role.ASSISTANT and msgs[2].text.startswith("Summary of users:") + assert msgs[0].role == "user" and "topic Y" in msgs[0].text + assert msgs[1].role == "assistant" and "A1 reply" in msgs[1].text + assert msgs[2].role == "assistant" and msgs[2].text.startswith("Summary of users:") async def test_sequential_checkpoint_resume_round_trip() -> None: diff --git a/python/packages/core/tests/workflow/test_workflow.py b/python/packages/core/tests/workflow/test_workflow.py index 6b08b7b22a..1bca73b565 100644 --- a/python/packages/core/tests/workflow/test_workflow.py +++ b/python/packages/core/tests/workflow/test_workflow.py @@ -23,7 +23,6 @@ FileCheckpointStorage, Message, RequestInfoEvent, - Role, WorkflowBuilder, WorkflowCheckpointException, WorkflowContext, @@ -869,7 +868,7 @@ async def run( **kwargs: Any, ) -> AgentResponse: """Non-streaming run - returns complete response.""" - return AgentResponse(messages=[ChatMessage(role=Role.ASSISTANT, text=self._reply_text)]) + return AgentResponse(messages=[ChatMessage("assistant", [self._reply_text])]) async def run_stream( self, diff --git a/python/packages/core/tests/workflow/test_workflow_agent.py b/python/packages/core/tests/workflow/test_workflow_agent.py index 9514efdf74..b12c916d84 100644 --- a/python/packages/core/tests/workflow/test_workflow_agent.py +++ b/python/packages/core/tests/workflow/test_workflow_agent.py @@ -16,7 +16,6 @@ ChatMessageStore, Content, Executor, - Role, UsageDetails, WorkflowAgent, WorkflowBuilder, @@ -41,11 +40,11 @@ async def handle_message(self, message: list[ChatMessage], ctx: WorkflowContext[ response_text = f"{self.response_text}: {input_text}" # Create response message for both streaming and non-streaming cases - response_message = ChatMessage(role=Role.ASSISTANT, contents=[Content.from_text(text=response_text)]) + response_message = ChatMessage("assistant", [Content.from_text(text=response_text)]) # Emit update event. streaming_update = AgentResponseUpdate( - contents=[Content.from_text(text=response_text)], role=Role.ASSISTANT, message_id=str(uuid.uuid4()) + contents=[Content.from_text(text=response_text)], role="assistant", message_id=str(uuid.uuid4()) ) await ctx.add_event(AgentRunUpdateEvent(executor_id=self.id, data=streaming_update)) @@ -68,7 +67,7 @@ async def handle_request_response( # Handle the response and emit completion response update = AgentResponseUpdate( contents=[Content.from_text(text="Request completed successfully")], - role=Role.ASSISTANT, + role="assistant", message_id=str(uuid.uuid4()), ) await ctx.add_event(AgentRunUpdateEvent(executor_id=self.id, data=update)) @@ -90,10 +89,10 @@ async def handle_message(self, messages: list[ChatMessage], ctx: WorkflowContext message_count = len(messages) response_text = f"Received {message_count} messages" - response_message = ChatMessage(role=Role.ASSISTANT, contents=[Content.from_text(text=response_text)]) + response_message = ChatMessage("assistant", [Content.from_text(text=response_text)]) streaming_update = AgentResponseUpdate( - contents=[Content.from_text(text=response_text)], role=Role.ASSISTANT, message_id=str(uuid.uuid4()) + contents=[Content.from_text(text=response_text)], role="assistant", message_id=str(uuid.uuid4()) ) await ctx.add_event(AgentRunUpdateEvent(executor_id=self.id, data=streaming_update)) await ctx.send_message([response_message]) @@ -232,7 +231,7 @@ async def test_end_to_end_request_info_handling(self): ), ) - response_message = ChatMessage(role=Role.USER, contents=[approval_response]) + response_message = ChatMessage("user", [approval_response]) # Continue the workflow with the response continuation_result = await agent.run(response_message) @@ -295,7 +294,7 @@ async def yielding_executor(messages: list[ChatMessage], ctx: WorkflowContext) - workflow = WorkflowBuilder().set_start_executor(yielding_executor).build() # Run directly - should return WorkflowOutputEvent in result - direct_result = await workflow.run([ChatMessage(role=Role.USER, contents=[Content.from_text(text="hello")])]) + direct_result = await workflow.run([ChatMessage("user", [Content.from_text(text="hello")])]) direct_outputs = direct_result.get_outputs() assert len(direct_outputs) == 1 assert direct_outputs[0] == "processed: hello" @@ -362,7 +361,7 @@ async def test_workflow_as_agent_yield_output_with_chat_message(self) -> None: @executor async def chat_message_executor(messages: list[ChatMessage], ctx: WorkflowContext) -> None: msg = ChatMessage( - role=Role.ASSISTANT, + role="assistant", contents=[Content.from_text(text="response text")], author_name="custom-author", ) @@ -374,7 +373,7 @@ async def chat_message_executor(messages: list[ChatMessage], ctx: WorkflowContex result = await agent.run("test") assert len(result.messages) == 1 - assert result.messages[0].role == Role.ASSISTANT + assert result.messages[0].role == "assistant" assert result.messages[0].text == "response text" assert result.messages[0].author_name == "custom-author" @@ -425,10 +424,10 @@ async def test_workflow_as_agent_yield_output_with_list_of_chat_messages(self) - async def list_yielding_executor(messages: list[ChatMessage], ctx: WorkflowContext) -> None: # Yield a list of ChatMessages (as SequentialBuilder does) msg_list = [ - ChatMessage(role=Role.USER, contents=[Content.from_text(text="first message")]), - ChatMessage(role=Role.ASSISTANT, contents=[Content.from_text(text="second message")]), + ChatMessage("user", [Content.from_text(text="first message")]), + ChatMessage("assistant", [Content.from_text(text="second message")]), ChatMessage( - role=Role.ASSISTANT, + role="assistant", contents=[Content.from_text(text="third"), Content.from_text(text="fourth")], ), ] @@ -469,8 +468,8 @@ async def test_thread_conversation_history_included_in_workflow_run(self) -> Non # Create a thread with existing conversation history history_messages = [ - ChatMessage(role=Role.USER, text="Previous user message"), - ChatMessage(role=Role.ASSISTANT, text="Previous assistant response"), + ChatMessage("user", ["Previous user message"]), + ChatMessage("assistant", ["Previous assistant response"]), ] message_store = ChatMessageStore(messages=history_messages) thread = AgentThread(message_store=message_store) @@ -499,9 +498,9 @@ async def test_thread_conversation_history_included_in_workflow_stream(self) -> # Create a thread with existing conversation history history_messages = [ - ChatMessage(role=Role.SYSTEM, text="You are a helpful assistant"), - ChatMessage(role=Role.USER, text="Hello"), - ChatMessage(role=Role.ASSISTANT, text="Hi there!"), + ChatMessage("system", ["You are a helpful assistant"]), + ChatMessage("user", ["Hello"]), + ChatMessage("assistant", ["Hi there!"]), ] message_store = ChatMessageStore(messages=history_messages) thread = AgentThread(message_store=message_store) @@ -579,7 +578,7 @@ def get_new_thread(self) -> AgentThread: async def run(self, messages: Any, *, thread: AgentThread | None = None, **kwargs: Any) -> AgentResponse: return AgentResponse( - messages=[ChatMessage(role=Role.ASSISTANT, text=self._response_text)], + messages=[ChatMessage("assistant", [self._response_text])], text=self._response_text, ) @@ -589,7 +588,7 @@ async def run_stream( for word in self._response_text.split(): yield AgentResponseUpdate( contents=[Content.from_text(text=word + " ")], - role=Role.ASSISTANT, + role="assistant", author_name=self._name, ) @@ -653,7 +652,7 @@ def get_new_thread(self) -> AgentThread: async def run(self, messages: Any, *, thread: AgentThread | None = None, **kwargs: Any) -> AgentResponse: return AgentResponse( - messages=[ChatMessage(role=Role.ASSISTANT, text=self._response_text)], + messages=[ChatMessage("assistant", [self._response_text])], text=self._response_text, ) @@ -662,7 +661,7 @@ async def run_stream( ) -> AsyncIterable[AgentResponseUpdate]: yield AgentResponseUpdate( contents=[Content.from_text(text=self._response_text)], - role=Role.ASSISTANT, + role="assistant", author_name=self._name, ) @@ -728,7 +727,7 @@ async def handle_message(self, message: list[ChatMessage], ctx: WorkflowContext[ # Emit update with explicit author_name update = AgentResponseUpdate( contents=[Content.from_text(text="Response with author")], - role=Role.ASSISTANT, + role="assistant", author_name="custom_author_name", # Explicitly set message_id=str(uuid.uuid4()), ) @@ -780,7 +779,7 @@ def test_merge_updates_ordering_by_response_and_message_id(self): # Response B, Message 2 (latest in resp B) AgentResponseUpdate( contents=[Content.from_text(text="RespB-Msg2")], - role=Role.ASSISTANT, + role="assistant", response_id="resp-b", message_id="msg-2", created_at="2024-01-01T12:02:00Z", @@ -788,7 +787,7 @@ def test_merge_updates_ordering_by_response_and_message_id(self): # Response A, Message 1 (earliest overall) AgentResponseUpdate( contents=[Content.from_text(text="RespA-Msg1")], - role=Role.ASSISTANT, + role="assistant", response_id="resp-a", message_id="msg-1", created_at="2024-01-01T12:00:00Z", @@ -796,7 +795,7 @@ def test_merge_updates_ordering_by_response_and_message_id(self): # Response B, Message 1 (earlier in resp B) AgentResponseUpdate( contents=[Content.from_text(text="RespB-Msg1")], - role=Role.ASSISTANT, + role="assistant", response_id="resp-b", message_id="msg-1", created_at="2024-01-01T12:01:00Z", @@ -804,7 +803,7 @@ def test_merge_updates_ordering_by_response_and_message_id(self): # Response A, Message 2 (later in resp A) AgentResponseUpdate( contents=[Content.from_text(text="RespA-Msg2")], - role=Role.ASSISTANT, + role="assistant", response_id="resp-a", message_id="msg-2", created_at="2024-01-01T12:00:30Z", @@ -812,7 +811,7 @@ def test_merge_updates_ordering_by_response_and_message_id(self): # Global dangling update (no response_id) - should go at end AgentResponseUpdate( contents=[Content.from_text(text="Global-Dangling")], - role=Role.ASSISTANT, + role="assistant", response_id=None, message_id="msg-global", created_at="2024-01-01T11:59:00Z", # Earliest timestamp but should be last @@ -886,7 +885,7 @@ def test_merge_updates_metadata_aggregation(self): usage_details={"input_token_count": 10, "output_token_count": 5, "total_token_count": 15} ), ], - role=Role.ASSISTANT, + role="assistant", response_id="resp-1", message_id="msg-1", created_at="2024-01-01T12:00:00Z", @@ -899,7 +898,7 @@ def test_merge_updates_metadata_aggregation(self): usage_details={"input_token_count": 20, "output_token_count": 8, "total_token_count": 28} ), ], - role=Role.ASSISTANT, + role="assistant", response_id="resp-2", message_id="msg-2", created_at="2024-01-01T12:01:00Z", # Later timestamp @@ -912,7 +911,7 @@ def test_merge_updates_metadata_aggregation(self): usage_details={"input_token_count": 5, "output_token_count": 3, "total_token_count": 8} ), ], - role=Role.ASSISTANT, + role="assistant", response_id="resp-1", # Same response_id as first message_id="msg-3", created_at="2024-01-01T11:59:00Z", # Earlier timestamp @@ -975,7 +974,7 @@ def test_merge_updates_function_result_ordering_github_2977(self): # User question AgentResponseUpdate( contents=[Content.from_text(text="What is the weather?")], - role=Role.USER, + role="user", response_id="resp-1", message_id="msg-1", created_at="2024-01-01T12:00:00Z", @@ -985,7 +984,7 @@ def test_merge_updates_function_result_ordering_github_2977(self): contents=[ Content.from_function_call(call_id=call_id, name="get_weather", arguments='{"location": "NYC"}') ], - role=Role.ASSISTANT, + role="assistant", response_id="resp-1", message_id="msg-2", created_at="2024-01-01T12:00:01Z", @@ -994,7 +993,7 @@ def test_merge_updates_function_result_ordering_github_2977(self): # and be placed at the end (the bug); fix now correctly associates via call_id AgentResponseUpdate( contents=[Content.from_function_result(call_id=call_id, result="Sunny, 72F")], - role=Role.TOOL, + role="tool", response_id=None, message_id="msg-3", created_at="2024-01-01T12:00:02Z", @@ -1002,7 +1001,7 @@ def test_merge_updates_function_result_ordering_github_2977(self): # Final assistant answer AgentResponseUpdate( contents=[Content.from_text(text="The weather in NYC is sunny and 72F.")], - role=Role.ASSISTANT, + role="assistant", response_id="resp-1", message_id="msg-4", created_at="2024-01-01T12:00:03Z", @@ -1026,10 +1025,10 @@ def test_merge_updates_function_result_ordering_github_2977(self): # Verify correct ordering: user -> function_call -> function_result -> assistant_answer expected_sequence = [ - ("text", Role.USER), - ("function_call", Role.ASSISTANT), - ("function_result", Role.TOOL), - ("text", Role.ASSISTANT), + ("text", "user"), + ("function_call", "assistant"), + ("function_result", "tool"), + ("text", "assistant"), ] assert content_sequence == expected_sequence, ( @@ -1073,7 +1072,7 @@ def test_merge_updates_multiple_function_results_ordering_github_2977(self): # User question AgentResponseUpdate( contents=[Content.from_text(text="What's the weather and time?")], - role=Role.USER, + role="user", response_id="resp-1", message_id="msg-1", created_at="2024-01-01T12:00:00Z", @@ -1083,7 +1082,7 @@ def test_merge_updates_multiple_function_results_ordering_github_2977(self): contents=[ Content.from_function_call(call_id=call_id_1, name="get_weather", arguments='{"location": "NYC"}') ], - role=Role.ASSISTANT, + role="assistant", response_id="resp-1", message_id="msg-2", created_at="2024-01-01T12:00:01Z", @@ -1093,7 +1092,7 @@ def test_merge_updates_multiple_function_results_ordering_github_2977(self): contents=[ Content.from_function_call(call_id=call_id_2, name="get_time", arguments='{"timezone": "EST"}') ], - role=Role.ASSISTANT, + role="assistant", response_id="resp-1", message_id="msg-3", created_at="2024-01-01T12:00:02Z", @@ -1101,7 +1100,7 @@ def test_merge_updates_multiple_function_results_ordering_github_2977(self): # Second function result arrives first (no response_id) AgentResponseUpdate( contents=[Content.from_function_result(call_id=call_id_2, result="3:00 PM EST")], - role=Role.TOOL, + role="tool", response_id=None, message_id="msg-4", created_at="2024-01-01T12:00:03Z", @@ -1109,7 +1108,7 @@ def test_merge_updates_multiple_function_results_ordering_github_2977(self): # First function result arrives second (no response_id) AgentResponseUpdate( contents=[Content.from_function_result(call_id=call_id_1, result="Sunny, 72F")], - role=Role.TOOL, + role="tool", response_id=None, message_id="msg-5", created_at="2024-01-01T12:00:04Z", @@ -1117,7 +1116,7 @@ def test_merge_updates_multiple_function_results_ordering_github_2977(self): # Final assistant answer AgentResponseUpdate( contents=[Content.from_text(text="It's sunny (72F) and 3 PM in NYC.")], - role=Role.ASSISTANT, + role="assistant", response_id="resp-1", message_id="msg-6", created_at="2024-01-01T12:00:05Z", @@ -1168,7 +1167,7 @@ def test_merge_updates_function_result_no_matching_call(self): updates = [ AgentResponseUpdate( contents=[Content.from_text(text="Hello")], - role=Role.USER, + role="user", response_id="resp-1", message_id="msg-1", created_at="2024-01-01T12:00:00Z", @@ -1176,14 +1175,14 @@ def test_merge_updates_function_result_no_matching_call(self): # Function result with no matching call AgentResponseUpdate( contents=[Content.from_function_result(call_id="orphan_call_id", result="orphan result")], - role=Role.TOOL, + role="tool", response_id=None, message_id="msg-2", created_at="2024-01-01T12:00:01Z", ), AgentResponseUpdate( contents=[Content.from_text(text="Goodbye")], - role=Role.ASSISTANT, + role="assistant", response_id="resp-1", message_id="msg-3", created_at="2024-01-01T12:00:02Z", diff --git a/python/packages/core/tests/workflow/test_workflow_builder.py b/python/packages/core/tests/workflow/test_workflow_builder.py index ef572ba82b..26bee34f6c 100644 --- a/python/packages/core/tests/workflow/test_workflow_builder.py +++ b/python/packages/core/tests/workflow/test_workflow_builder.py @@ -13,7 +13,6 @@ BaseAgent, ChatMessage, Executor, - Role, WorkflowBuilder, WorkflowContext, handler, @@ -28,7 +27,7 @@ async def run(self, messages=None, *, thread: AgentThread | None = None, **kwarg if isinstance(m, ChatMessage): norm.append(m) elif isinstance(m, str): - norm.append(ChatMessage(role=Role.USER, text=m)) + norm.append(ChatMessage("user", [m])) return AgentResponse(messages=norm) async def run_stream(self, messages=None, *, thread: AgentThread | None = None, **kwargs): # type: ignore[override] diff --git a/python/packages/core/tests/workflow/test_workflow_kwargs.py b/python/packages/core/tests/workflow/test_workflow_kwargs.py index 79aa009f57..763a911351 100644 --- a/python/packages/core/tests/workflow/test_workflow_kwargs.py +++ b/python/packages/core/tests/workflow/test_workflow_kwargs.py @@ -16,7 +16,6 @@ GroupChatBuilder, GroupChatState, HandoffBuilder, - Role, SequentialBuilder, WorkflowRunState, WorkflowStatusEvent, @@ -57,7 +56,7 @@ async def run( **kwargs: Any, ) -> AgentResponse: self.captured_kwargs.append(dict(kwargs)) - return AgentResponse(messages=[ChatMessage(role=Role.ASSISTANT, text=f"{self.name} response")]) + return AgentResponse(messages=[ChatMessage("assistant", [f"{self.name} response"])]) async def run_stream( self, @@ -387,10 +386,10 @@ def __init__(self) -> None: self.task_ledger = None async def plan(self, magentic_context: MagenticContext) -> ChatMessage: - return ChatMessage(role=Role.ASSISTANT, text="Plan: Test task", author_name="manager") + return ChatMessage("assistant", ["Plan: Test task"], author_name="manager") async def replan(self, magentic_context: MagenticContext) -> ChatMessage: - return ChatMessage(role=Role.ASSISTANT, text="Replan: Test task", author_name="manager") + return ChatMessage("assistant", ["Replan: Test task"], author_name="manager") async def create_progress_ledger(self, magentic_context: MagenticContext) -> MagenticProgressLedger: # Return completed on first call @@ -403,7 +402,7 @@ async def create_progress_ledger(self, magentic_context: MagenticContext) -> Mag ) async def prepare_final_answer(self, magentic_context: MagenticContext) -> ChatMessage: - return ChatMessage(role=Role.ASSISTANT, text="Final answer", author_name="manager") + return ChatMessage("assistant", ["Final answer"], author_name="manager") agent = _KwargsCapturingAgent(name="agent1") manager = _MockManager() @@ -437,10 +436,10 @@ def __init__(self) -> None: self.task_ledger = None async def plan(self, magentic_context: MagenticContext) -> ChatMessage: - return ChatMessage(role=Role.ASSISTANT, text="Plan", author_name="manager") + return ChatMessage("assistant", ["Plan"], author_name="manager") async def replan(self, magentic_context: MagenticContext) -> ChatMessage: - return ChatMessage(role=Role.ASSISTANT, text="Replan", author_name="manager") + return ChatMessage("assistant", ["Replan"], author_name="manager") async def create_progress_ledger(self, magentic_context: MagenticContext) -> MagenticProgressLedger: return MagenticProgressLedger( @@ -452,7 +451,7 @@ async def create_progress_ledger(self, magentic_context: MagenticContext) -> Mag ) async def prepare_final_answer(self, magentic_context: MagenticContext) -> ChatMessage: - return ChatMessage(role=Role.ASSISTANT, text="Final", author_name="manager") + return ChatMessage("assistant", ["Final"], author_name="manager") agent = _KwargsCapturingAgent(name="agent1") manager = _MockManager() diff --git a/python/packages/declarative/agent_framework_declarative/_workflows/_actions_agents.py b/python/packages/declarative/agent_framework_declarative/_workflows/_actions_agents.py index 9d610d057d..390eb0a991 100644 --- a/python/packages/declarative/agent_framework_declarative/_workflows/_actions_agents.py +++ b/python/packages/declarative/agent_framework_declarative/_workflows/_actions_agents.py @@ -285,11 +285,11 @@ async def handle_invoke_azure_agent(ctx: ActionContext) -> AsyncGenerator[Workfl evaluated_input = ctx.state.eval_if_expression(input_messages) if evaluated_input: if isinstance(evaluated_input, str): - messages.append(ChatMessage(role="user", text=evaluated_input)) + messages.append(ChatMessage("user", [evaluated_input])) elif isinstance(evaluated_input, list): for msg_item in evaluated_input: # type: ignore if isinstance(msg_item, str): - messages.append(ChatMessage(role="user", text=msg_item)) + messages.append(ChatMessage("user", [msg_item])) elif isinstance(msg_item, ChatMessage): messages.append(msg_item) elif isinstance(msg_item, dict) and "content" in msg_item: @@ -297,11 +297,11 @@ async def handle_invoke_azure_agent(ctx: ActionContext) -> AsyncGenerator[Workfl role: str = str(item_dict.get("role", "user")) content: str = str(item_dict.get("content", "")) if role == "user": - messages.append(ChatMessage(role="user", text=content)) + messages.append(ChatMessage("user", [content])) elif role == "assistant": - messages.append(ChatMessage(role="assistant", text=content)) + messages.append(ChatMessage("assistant", [content])) elif role == "system": - messages.append(ChatMessage(role="system", text=content)) + messages.append(ChatMessage("system", [content])) # Evaluate and include input arguments evaluated_args: dict[str, Any] = {} @@ -348,7 +348,7 @@ async def handle_invoke_azure_agent(ctx: ActionContext) -> AsyncGenerator[Workfl tool_calls.extend(chunk.tool_calls) # Build consolidated response from updates - response = AgentResponse.from_agent_run_response_updates(updates) + response = AgentResponse.from_updates(updates) text = response.text response_messages = response.messages @@ -361,7 +361,7 @@ async def handle_invoke_azure_agent(ctx: ActionContext) -> AsyncGenerator[Workfl # Add to conversation history if text: - ctx.state.add_conversation_message(ChatMessage(role="assistant", text=text)) + ctx.state.add_conversation_message(ChatMessage("assistant", [text])) # Store in output variables (.NET style) if output_messages_var: @@ -414,7 +414,7 @@ async def handle_invoke_azure_agent(ctx: ActionContext) -> AsyncGenerator[Workfl # Add to conversation history if text: - ctx.state.add_conversation_message(ChatMessage(role="assistant", text=text)) + ctx.state.add_conversation_message(ChatMessage("assistant", [text])) # Store in output variables (.NET style) if output_messages_var: @@ -560,7 +560,7 @@ async def handle_invoke_prompt_agent(ctx: ActionContext) -> AsyncGenerator[Workf # Add input as user message if provided if input_value: if isinstance(input_value, str): - messages.append(ChatMessage(role="user", text=input_value)) + messages.append(ChatMessage("user", [input_value])) elif isinstance(input_value, ChatMessage): messages.append(input_value) @@ -581,14 +581,14 @@ async def handle_invoke_prompt_agent(ctx: ActionContext) -> AsyncGenerator[Workf ) # Build consolidated response from updates - response = AgentResponse.from_agent_run_response_updates(updates) + response = AgentResponse.from_updates(updates) text = response.text response_messages = response.messages ctx.state.set_agent_result(text=text, messages=response_messages) if text: - ctx.state.add_conversation_message(ChatMessage(role="assistant", text=text)) + ctx.state.add_conversation_message(ChatMessage("assistant", [text])) if output_path: ctx.state.set(output_path, text) @@ -607,7 +607,7 @@ async def handle_invoke_prompt_agent(ctx: ActionContext) -> AsyncGenerator[Workf ctx.state.set_agent_result(text=text, messages=response_messages) if text: - ctx.state.add_conversation_message(ChatMessage(role="assistant", text=text)) + ctx.state.add_conversation_message(ChatMessage("assistant", [text])) if output_path: ctx.state.set(output_path, text) diff --git a/python/packages/declarative/agent_framework_declarative/_workflows/_executors_agents.py b/python/packages/declarative/agent_framework_declarative/_workflows/_executors_agents.py index 18685ef401..d75c62e807 100644 --- a/python/packages/declarative/agent_framework_declarative/_workflows/_executors_agents.py +++ b/python/packages/declarative/agent_framework_declarative/_workflows/_executors_agents.py @@ -642,7 +642,7 @@ async def _invoke_agent_and_store_results( # Add user input to conversation history first (via state.append only) if input_text: - user_message = ChatMessage(role="user", text=input_text) + user_message = ChatMessage("user", [input_text]) await state.append(messages_path, user_message) # Get conversation history from state AFTER adding user message @@ -711,7 +711,7 @@ async def _invoke_agent_and_store_results( "Agent '%s': No messages in response, creating simple assistant message", agent_name, ) - assistant_message = ChatMessage(role="assistant", text=accumulated_response) + assistant_message = ChatMessage("assistant", [accumulated_response]) await state.append(messages_path, assistant_message) # Store results in state - support both schema formats: diff --git a/python/packages/devui/agent_framework_devui/_conversations.py b/python/packages/devui/agent_framework_devui/_conversations.py index 868ca3e162..8321e6a6aa 100644 --- a/python/packages/devui/agent_framework_devui/_conversations.py +++ b/python/packages/devui/agent_framework_devui/_conversations.py @@ -303,7 +303,7 @@ async def add_items(self, conversation_id: str, items: list[dict[str, Any]]) -> content = item.get("content", []) text = content[0].get("text", "") if content else "" - chat_msg = ChatMessage(role=role, contents=[{"type": "text", "text": text}]) + chat_msg = ChatMessage(role, [{"type": "text", "text": text}]) chat_messages.append(chat_msg) # Add messages to AgentThread @@ -315,7 +315,7 @@ async def add_items(self, conversation_id: str, items: list[dict[str, Any]]) -> item_id = f"item_{uuid.uuid4().hex}" # Extract role - handle both string and enum - role_str = msg.role.value if hasattr(msg.role, "value") else str(msg.role) + role_str = msg.role if hasattr(msg.role, "value") else str(msg.role) role = cast(MessageRole, role_str) # Safe: Agent Framework roles match OpenAI roles # Convert ChatMessage contents to OpenAI TextContent format @@ -373,7 +373,7 @@ async def list_items( # Convert each AgentFramework ChatMessage to appropriate ConversationItem type(s) for i, msg in enumerate(af_messages): item_id = f"item_{i}" - role_str = msg.role.value if hasattr(msg.role, "value") else str(msg.role) + role_str = msg.role if hasattr(msg.role, "value") else str(msg.role) role = cast(MessageRole, role_str) # Safe: Agent Framework roles match OpenAI roles # Process each content item in the message diff --git a/python/packages/devui/agent_framework_devui/_executor.py b/python/packages/devui/agent_framework_devui/_executor.py index cf4fa0066f..9f60678386 100644 --- a/python/packages/devui/agent_framework_devui/_executor.py +++ b/python/packages/devui/agent_framework_devui/_executor.py @@ -760,7 +760,7 @@ def _convert_openai_input_to_chat_message(self, input_items: list[Any], ChatMess if not contents: contents.append(Content.from_text(text="")) - chat_message = ChatMessage(role=Role.USER, contents=contents) + chat_message = ChatMessage("user", contents) logger.info(f"Created ChatMessage with {len(contents)} contents:") for idx, content in enumerate(contents): diff --git a/python/packages/devui/tests/test_cleanup_hooks.py b/python/packages/devui/tests/test_cleanup_hooks.py index e821779686..68c8ff6af2 100644 --- a/python/packages/devui/tests/test_cleanup_hooks.py +++ b/python/packages/devui/tests/test_cleanup_hooks.py @@ -7,7 +7,7 @@ from pathlib import Path import pytest -from agent_framework import AgentResponse, ChatMessage, Content, Role +from agent_framework import AgentResponse, ChatMessage, Content from agent_framework_devui import register_cleanup from agent_framework_devui._discovery import EntityDiscovery @@ -36,7 +36,7 @@ def __init__(self, name: str = "TestAgent"): async def run_stream(self, messages=None, *, thread=None, **kwargs): """Mock streaming run method.""" yield AgentResponse( - messages=[ChatMessage(role=Role.ASSISTANT, contents=[Content.from_text(text="Test response")])], + messages=[ChatMessage("assistant", [Content.from_text(text="Test response")])], ) @@ -279,7 +279,7 @@ class TestAgent: async def run_stream(self, messages=None, *, thread=None, **kwargs): yield AgentResponse( - messages=[ChatMessage(role=Role.ASSISTANT, content=[Content.from_text(text="Test")])], + messages=[ChatMessage("assistant", [Content.from_text(text="Test")])], inner_messages=[], ) diff --git a/python/packages/devui/tests/test_conversations.py b/python/packages/devui/tests/test_conversations.py index eb2d6f3c76..cd1451f79b 100644 --- a/python/packages/devui/tests/test_conversations.py +++ b/python/packages/devui/tests/test_conversations.py @@ -199,7 +199,7 @@ async def test_list_items_pagination(): @pytest.mark.asyncio async def test_list_items_converts_function_calls(): """Test that list_items properly converts function calls to ResponseFunctionToolCallItem.""" - from agent_framework import ChatMessage, ChatMessageStore, Role + from agent_framework import ChatMessage, ChatMessageStore store = InMemoryConversationStore() @@ -216,9 +216,9 @@ async def test_list_items_converts_function_calls(): # Simulate messages from agent execution with function calls messages = [ - ChatMessage(role=Role.USER, contents=[{"type": "text", "text": "What's the weather in SF?"}]), + ChatMessage("user", [{"type": "text", "text": "What's the weather in SF?"}]), ChatMessage( - role=Role.ASSISTANT, + role="assistant", contents=[ { "type": "function_call", @@ -229,7 +229,7 @@ async def test_list_items_converts_function_calls(): ], ), ChatMessage( - role=Role.TOOL, + role="tool", contents=[ { "type": "function_result", @@ -238,7 +238,7 @@ async def test_list_items_converts_function_calls(): } ], ), - ChatMessage(role=Role.ASSISTANT, contents=[{"type": "text", "text": "The weather is sunny, 65°F"}]), + ChatMessage("assistant", [{"type": "text", "text": "The weather is sunny, 65°F"}]), ] # Add messages to thread @@ -284,7 +284,7 @@ async def test_list_items_converts_function_calls(): @pytest.mark.asyncio async def test_list_items_handles_images_and_files(): """Test that list_items properly converts data content (images/files) to OpenAI types.""" - from agent_framework import ChatMessage, ChatMessageStore, Role + from agent_framework import ChatMessage, ChatMessageStore store = InMemoryConversationStore() @@ -301,7 +301,7 @@ async def test_list_items_handles_images_and_files(): # Simulate message with image and file messages = [ ChatMessage( - role=Role.USER, + role="user", contents=[ {"type": "text", "text": "Check this image and PDF"}, {"type": "data", "uri": "data:image/png;base64,iVBORw0KGgo=", "media_type": "image/png"}, diff --git a/python/packages/devui/tests/test_discovery.py b/python/packages/devui/tests/test_discovery.py index f2b321d75c..8b0cf9fb3a 100644 --- a/python/packages/devui/tests/test_discovery.py +++ b/python/packages/devui/tests/test_discovery.py @@ -94,7 +94,7 @@ class NonStreamingAgent: async def run(self, messages=None, *, thread=None, **kwargs): return AgentResponse( messages=[ChatMessage( - role=Role.ASSISTANT, + role="assistant", contents=[Content.from_text(text="response")] )], response_id="test" @@ -210,7 +210,7 @@ class TestAgent: async def run(self, messages=None, *, thread=None, **kwargs): return AgentResponse( - messages=[ChatMessage(role=Role.ASSISTANT, contents=[Content.from_text(text="test")])], + messages=[ChatMessage("assistant", [Content.from_text(text="test")])], response_id="test" ) diff --git a/python/packages/devui/tests/test_execution.py b/python/packages/devui/tests/test_execution.py index e367782597..ce763d227e 100644 --- a/python/packages/devui/tests/test_execution.py +++ b/python/packages/devui/tests/test_execution.py @@ -566,7 +566,7 @@ def test_extract_workflow_hil_responses_handles_stringified_json(): async def test_executor_handles_non_streaming_agent(): """Test executor can handle agents with only run() method (no run_stream).""" - from agent_framework import AgentResponse, AgentThread, ChatMessage, Content, Role + from agent_framework import AgentResponse, AgentThread, ChatMessage, Content class NonStreamingAgent: """Agent with only run() method - does NOT satisfy full AgentProtocol.""" @@ -577,9 +577,7 @@ class NonStreamingAgent: async def run(self, messages=None, *, thread=None, **kwargs): return AgentResponse( - messages=[ - ChatMessage(role=Role.ASSISTANT, contents=[Content.from_text(text=f"Processed: {messages}")]) - ], + messages=[ChatMessage("assistant", [Content.from_text(text=f"Processed: {messages}")])], response_id="test_123", ) diff --git a/python/packages/devui/tests/test_helpers.py b/python/packages/devui/tests/test_helpers.py index 130ab475d9..d0d9b36b6e 100644 --- a/python/packages/devui/tests/test_helpers.py +++ b/python/packages/devui/tests/test_helpers.py @@ -29,7 +29,6 @@ ChatResponseUpdate, ConcurrentBuilder, Content, - Role, SequentialBuilder, use_chat_middleware, ) @@ -79,7 +78,7 @@ async def get_response( self.call_count += 1 if self.responses: return self.responses.pop(0) - return ChatResponse(messages=ChatMessage(role="assistant", text="test response")) + return ChatResponse(messages=ChatMessage("assistant", ["test response"])) async def get_streaming_response( self, @@ -91,7 +90,7 @@ async def get_streaming_response( for update in self.streaming_responses.pop(0): yield update else: - yield ChatResponseUpdate(text=Content.from_text(text="test streaming response"), role="assistant") + yield ChatResponseUpdate(contents=[Content.from_text(text="test streaming response")], role="assistant") @use_chat_middleware @@ -122,7 +121,7 @@ async def _inner_get_response( self.received_messages.append(list(messages)) if self.run_responses: return self.run_responses.pop(0) - return ChatResponse(messages=ChatMessage(role="assistant", text="Mock response from ChatAgent")) + return ChatResponse(messages=ChatMessage("assistant", ["Mock response from ChatAgent"])) @override async def _inner_get_streaming_response( @@ -139,10 +138,10 @@ async def _inner_get_streaming_response( yield update else: # Simulate realistic streaming chunks - yield ChatResponseUpdate(text=Content.from_text(text="Mock "), role="assistant") - yield ChatResponseUpdate(text=Content.from_text(text="streaming "), role="assistant") - yield ChatResponseUpdate(text=Content.from_text(text="response "), role="assistant") - yield ChatResponseUpdate(text=Content.from_text(text="from ChatAgent"), role="assistant") + yield ChatResponseUpdate(contents=[Content.from_text(text="Mock ")], role="assistant") + yield ChatResponseUpdate(contents=[Content.from_text(text="streaming ")], role="assistant") + yield ChatResponseUpdate(contents=[Content.from_text(text="response ")], role="assistant") + yield ChatResponseUpdate(contents=[Content.from_text(text="from ChatAgent")], role="assistant") # ============================================================================= @@ -172,9 +171,7 @@ async def run( **kwargs: Any, ) -> AgentResponse: self.call_count += 1 - return AgentResponse( - messages=[ChatMessage(role=Role.ASSISTANT, contents=[Content.from_text(text=self.response_text)])] - ) + return AgentResponse(messages=[ChatMessage("assistant", [Content.from_text(text=self.response_text)])]) async def run_stream( self, @@ -185,7 +182,7 @@ async def run_stream( ) -> AsyncIterable[AgentResponseUpdate]: self.call_count += 1 for chunk in self.streaming_chunks: - yield AgentResponseUpdate(contents=[Content.from_text(text=chunk)], role=Role.ASSISTANT) + yield AgentResponseUpdate(contents=[Content.from_text(text=chunk)], role="assistant") class MockToolCallingAgent(BaseAgent): @@ -203,7 +200,7 @@ async def run( **kwargs: Any, ) -> AgentResponse: self.call_count += 1 - return AgentResponse(messages=[ChatMessage(role=Role.ASSISTANT, text="done")]) + return AgentResponse(messages=[ChatMessage("assistant", ["done"])]) async def run_stream( self, @@ -216,7 +213,7 @@ async def run_stream( # First: text yield AgentResponseUpdate( contents=[Content.from_text(text="Let me search for that...")], - role=Role.ASSISTANT, + role="assistant", ) # Second: tool call yield AgentResponseUpdate( @@ -227,7 +224,7 @@ async def run_stream( arguments={"query": "weather"}, ) ], - role=Role.ASSISTANT, + role="assistant", ) # Third: tool result yield AgentResponseUpdate( @@ -237,12 +234,12 @@ async def run_stream( result={"temperature": 72, "condition": "sunny"}, ) ], - role=Role.TOOL, + role="tool", ) # Fourth: final text yield AgentResponseUpdate( contents=[Content.from_text(text="The weather is sunny, 72°F.")], - role=Role.ASSISTANT, + role="assistant", ) @@ -295,7 +292,7 @@ def create_mock_tool_agent(id: str = "tool_agent", name: str = "ToolAgent") -> M def create_agent_run_response(text: str = "Test response") -> AgentResponse: """Create an AgentResponse with the given text.""" - return AgentResponse(messages=[ChatMessage(role=Role.ASSISTANT, contents=[Content.from_text(text=text)])]) + return AgentResponse(messages=[ChatMessage("assistant", [Content.from_text(text=text)])]) def create_agent_executor_response( @@ -308,8 +305,8 @@ def create_agent_executor_response( executor_id=executor_id, agent_response=agent_response, full_conversation=[ - ChatMessage(role=Role.USER, contents=[Content.from_text(text="User input")]), - ChatMessage(role=Role.ASSISTANT, contents=[Content.from_text(text=response_text)]), + ChatMessage("user", [Content.from_text(text="User input")]), + ChatMessage("assistant", [Content.from_text(text=response_text)]), ], ) @@ -391,8 +388,8 @@ async def create_sequential_workflow() -> tuple[AgentFrameworkExecutor, str, Moc """ mock_client = MockBaseChatClient() mock_client.run_responses = [ - ChatResponse(messages=ChatMessage(role=Role.ASSISTANT, text="Here's the draft content about the topic.")), - ChatResponse(messages=ChatMessage(role=Role.ASSISTANT, text="Review: Content is clear and well-structured.")), + ChatResponse(messages=ChatMessage("assistant", ["Here's the draft content about the topic."])), + ChatResponse(messages=ChatMessage("assistant", ["Review: Content is clear and well-structured."])), ] writer = ChatAgent( @@ -434,9 +431,9 @@ async def create_concurrent_workflow() -> tuple[AgentFrameworkExecutor, str, Moc """ mock_client = MockBaseChatClient() mock_client.run_responses = [ - ChatResponse(messages=ChatMessage(role=Role.ASSISTANT, text="Research findings: Key data points identified.")), - ChatResponse(messages=ChatMessage(role=Role.ASSISTANT, text="Analysis: Trends indicate positive growth.")), - ChatResponse(messages=ChatMessage(role=Role.ASSISTANT, text="Summary: Overall outlook is favorable.")), + ChatResponse(messages=ChatMessage("assistant", ["Research findings: Key data points identified."])), + ChatResponse(messages=ChatMessage("assistant", ["Analysis: Trends indicate positive growth."])), + ChatResponse(messages=ChatMessage("assistant", ["Summary: Overall outlook is favorable."])), ] researcher = ChatAgent( diff --git a/python/packages/devui/tests/test_mapper.py b/python/packages/devui/tests/test_mapper.py index 4ea3ba9333..70bf44b773 100644 --- a/python/packages/devui/tests/test_mapper.py +++ b/python/packages/devui/tests/test_mapper.py @@ -15,7 +15,6 @@ from agent_framework._types import ( AgentResponseUpdate, Content, - Role, ) # Import real workflow event classes - NOT mocks! @@ -84,7 +83,7 @@ def create_test_content(content_type: str, **kwargs: Any) -> Any: def create_test_agent_update(contents: list[Any]) -> AgentResponseUpdate: """Create test AgentResponseUpdate.""" - return AgentResponseUpdate(contents=contents, role=Role.ASSISTANT, message_id="test_msg", response_id="test_resp") + return AgentResponseUpdate(contents=contents, role="assistant", message_id="test_msg", response_id="test_resp") # ============================================================================= @@ -450,13 +449,13 @@ async def test_magentic_agent_run_update_event_with_agent_delta_metadata( This tests the ACTUAL event format Magentic emits - not a fake MagenticAgentDeltaEvent class. Magentic uses AgentRunUpdateEvent with additional_properties containing magentic_event_type. """ - from agent_framework._types import AgentResponseUpdate, Role + from agent_framework._types import AgentResponseUpdate from agent_framework._workflows._events import AgentRunUpdateEvent # Create the REAL event format that Magentic emits update = AgentResponseUpdate( contents=[Content.from_text(text="Hello from agent")], - role=Role.ASSISTANT, + role="assistant", author_name="Writer", additional_properties={ "magentic_event_type": "agent_delta", @@ -481,13 +480,13 @@ async def test_magentic_orchestrator_message_event(mapper: MessageMapper, test_r Magentic emits orchestrator planning/instruction messages using AgentRunUpdateEvent with additional_properties containing magentic_event_type='orchestrator_message'. """ - from agent_framework._types import AgentResponseUpdate, Role + from agent_framework._types import AgentResponseUpdate from agent_framework._workflows._events import AgentRunUpdateEvent # Create orchestrator message event (REAL format from Magentic) update = AgentResponseUpdate( contents=[Content.from_text(text="Planning: First, the writer will create content...")], - role=Role.ASSISTANT, + role="assistant", author_name="Orchestrator", additional_properties={ "magentic_event_type": "orchestrator_message", @@ -517,21 +516,21 @@ async def test_magentic_events_use_same_event_class_as_other_workflows( additional_properties. Any mapper code checking for 'MagenticAgentDeltaEvent' class names is dead code. """ - from agent_framework._types import AgentResponseUpdate, Role + from agent_framework._types import AgentResponseUpdate from agent_framework._workflows._events import AgentRunUpdateEvent # Create events the way different workflows do it # 1. Regular workflow (no additional_properties) regular_update = AgentResponseUpdate( contents=[Content.from_text(text="Regular workflow response")], - role=Role.ASSISTANT, + role="assistant", ) regular_event = AgentRunUpdateEvent(executor_id="regular_executor", data=regular_update) # 2. Magentic workflow (with additional_properties) magentic_update = AgentResponseUpdate( contents=[Content.from_text(text="Magentic workflow response")], - role=Role.ASSISTANT, + role="assistant", additional_properties={"magentic_event_type": "agent_delta"}, ) magentic_event = AgentRunUpdateEvent(executor_id="magentic_executor", data=magentic_update) @@ -598,13 +597,13 @@ async def test_workflow_output_event(mapper: MessageMapper, test_request: AgentF async def test_workflow_output_event_with_list_data(mapper: MessageMapper, test_request: AgentFrameworkRequest) -> None: """Test WorkflowOutputEvent with list data (common for sequential/concurrent workflows).""" - from agent_framework import ChatMessage, Role + from agent_framework import ChatMessage from agent_framework._workflows._events import WorkflowOutputEvent # Sequential/Concurrent workflows often output list[ChatMessage] messages = [ - ChatMessage(role=Role.USER, contents=[Content.from_text(text="Hello")]), - ChatMessage(role=Role.ASSISTANT, contents=[Content.from_text(text="World")]), + ChatMessage("user", [Content.from_text(text="Hello")]), + ChatMessage("assistant", [Content.from_text(text="World")]), ] event = WorkflowOutputEvent(data=messages, executor_id="complete") events = await mapper.convert_event(event, test_request) diff --git a/python/packages/devui/tests/test_multimodal_workflow.py b/python/packages/devui/tests/test_multimodal_workflow.py index b962fccd7b..dbd4c4dfae 100644 --- a/python/packages/devui/tests/test_multimodal_workflow.py +++ b/python/packages/devui/tests/test_multimodal_workflow.py @@ -49,7 +49,7 @@ def test_is_openai_multimodal_format_detects_message_format(self): def test_convert_openai_input_to_chat_message_with_image(self): """Test that OpenAI format with image is converted to ChatMessage with DataContent.""" - from agent_framework import ChatMessage, Role + from agent_framework import ChatMessage discovery = MagicMock(spec=EntityDiscovery) mapper = MagicMock(spec=MessageMapper) @@ -72,7 +72,7 @@ def test_convert_openai_input_to_chat_message_with_image(self): # Verify result is ChatMessage assert isinstance(result, ChatMessage), f"Expected ChatMessage, got {type(result)}" - assert result.role == Role.USER + assert result.role == "user" # Verify contents assert len(result.contents) == 2, f"Expected 2 contents, got {len(result.contents)}" diff --git a/python/packages/durabletask/agent_framework_durabletask/_durable_agent_state.py b/python/packages/durabletask/agent_framework_durabletask/_durable_agent_state.py index a72f3fb07f..aabfa4bf08 100644 --- a/python/packages/durabletask/agent_framework_durabletask/_durable_agent_state.py +++ b/python/packages/durabletask/agent_framework_durabletask/_durable_agent_state.py @@ -797,7 +797,7 @@ def from_run_request(request: RunRequest) -> DurableAgentStateMessage: DurableAgentStateMessage with converted content items and metadata """ return DurableAgentStateMessage( - role=request.role.value, + role=request.role, contents=[DurableAgentStateTextContent(text=request.message)], created_at=_parse_created_at(request.created_at) if request.created_at else None, ) @@ -817,7 +817,7 @@ def from_chat_message(chat_message: ChatMessage) -> DurableAgentStateMessage: ] return DurableAgentStateMessage( - role=chat_message.role.value, + role=chat_message.role, contents=contents_list, author_name=chat_message.author_name, extension_data=dict(chat_message.additional_properties) if chat_message.additional_properties else None, diff --git a/python/packages/durabletask/agent_framework_durabletask/_entities.py b/python/packages/durabletask/agent_framework_durabletask/_entities.py index 1f816b6b9d..c842d58fe7 100644 --- a/python/packages/durabletask/agent_framework_durabletask/_entities.py +++ b/python/packages/durabletask/agent_framework_durabletask/_entities.py @@ -14,7 +14,6 @@ AgentResponseUpdate, ChatMessage, Content, - Role, get_logger, ) from durabletask.entities import DurableEntity @@ -176,7 +175,7 @@ async def run( logger.exception("[AgentEntity.run] Agent execution failed.") error_message = ChatMessage( - role=Role.ASSISTANT, contents=[Content.from_error(message=str(exc), error_code=type(exc).__name__)] + role="assistant", contents=[Content.from_error(message=str(exc), error_code=type(exc).__name__)] ) error_response = AgentResponse(messages=[error_message]) @@ -247,7 +246,7 @@ async def _consume_stream( await self._notify_stream_update(update, callback_context) if updates: - response = AgentResponse.from_agent_run_response_updates(updates) + response = AgentResponse.from_updates(updates) else: logger.debug("[AgentEntity] No streaming updates received; creating empty response") response = AgentResponse(messages=[]) diff --git a/python/packages/durabletask/agent_framework_durabletask/_executors.py b/python/packages/durabletask/agent_framework_durabletask/_executors.py index 15bbb4ecb3..226d9dff6c 100644 --- a/python/packages/durabletask/agent_framework_durabletask/_executors.py +++ b/python/packages/durabletask/agent_framework_durabletask/_executors.py @@ -16,7 +16,7 @@ from datetime import datetime, timezone from typing import Any, Generic, TypeVar -from agent_framework import AgentResponse, AgentThread, ChatMessage, Content, Role, get_logger +from agent_framework import AgentResponse, AgentThread, ChatMessage, Content, get_logger from durabletask.client import TaskHubGrpcClient from durabletask.entities import EntityInstanceId from durabletask.task import CompletableTask, CompositeTask, OrchestrationContext, Task @@ -180,7 +180,7 @@ def _create_acceptance_response(self, correlation_id: str) -> AgentResponse: AgentResponse: Acceptance response with correlation ID """ acceptance_message = ChatMessage( - role=Role.SYSTEM, + role="system", contents=[ Content.from_text( f"Request accepted for processing (correlation_id: {correlation_id}). " @@ -361,7 +361,7 @@ def _handle_agent_response( correlation_id, ) error_message = ChatMessage( - role=Role.SYSTEM, + role="system", contents=[ Content.from_error( message=f"Error processing agent response: {e}", @@ -376,7 +376,7 @@ def _handle_agent_response( correlation_id, ) error_message = ChatMessage( - role=Role.SYSTEM, + role="system", contents=[ Content.from_error( message=f"Timeout waiting for agent response after {self.max_poll_retries} attempts", diff --git a/python/packages/durabletask/agent_framework_durabletask/_models.py b/python/packages/durabletask/agent_framework_durabletask/_models.py index 971aad8e54..3d20828fc7 100644 --- a/python/packages/durabletask/agent_framework_durabletask/_models.py +++ b/python/packages/durabletask/agent_framework_durabletask/_models.py @@ -16,7 +16,7 @@ from importlib import import_module from typing import TYPE_CHECKING, Any, cast -from agent_framework import AgentThread, Role +from agent_framework import AgentThread from ._constants import REQUEST_RESPONSE_FORMAT_TEXT @@ -115,7 +115,7 @@ class RunRequest: message: str request_response_format: str correlation_id: str - role: Role = Role.USER + role: str = "user" response_format: type[BaseModel] | None = None enable_tool_calls: bool = True wait_for_response: bool = True @@ -128,7 +128,7 @@ def __init__( message: str, correlation_id: str, request_response_format: str = REQUEST_RESPONSE_FORMAT_TEXT, - role: Role | str | None = Role.USER, + role: str | None = "user", response_format: type[BaseModel] | None = None, enable_tool_calls: bool = True, wait_for_response: bool = True, @@ -148,16 +148,14 @@ def __init__( self.options = options if options is not None else {} @staticmethod - def coerce_role(value: Role | str | None) -> Role: - """Normalize various role representations into a Role instance.""" - if isinstance(value, Role): - return value + def coerce_role(value: str | None) -> str: + """Normalize various role representations into a role string.""" if isinstance(value, str): normalized = value.strip() if not normalized: - return Role.USER - return Role(value=normalized.lower()) - return Role.USER + return "user" + return normalized.lower() + return "user" def to_dict(self) -> dict[str, Any]: """Convert to dictionary for JSON serialization.""" @@ -165,7 +163,7 @@ def to_dict(self) -> dict[str, Any]: "message": self.message, "enable_tool_calls": self.enable_tool_calls, "wait_for_response": self.wait_for_response, - "role": self.role.value, + "role": self.role, "request_response_format": self.request_response_format, "correlationId": self.correlation_id, "options": self.options, diff --git a/python/packages/durabletask/agent_framework_durabletask/_response_utils.py b/python/packages/durabletask/agent_framework_durabletask/_response_utils.py index fd622d9b35..1085d4b51d 100644 --- a/python/packages/durabletask/agent_framework_durabletask/_response_utils.py +++ b/python/packages/durabletask/agent_framework_durabletask/_response_utils.py @@ -55,9 +55,12 @@ def ensure_response_format( Raises: ValueError: If response_format is specified but response.value cannot be parsed """ - if response_format is not None and not isinstance(response.value, response_format): - response.try_parse_value(response_format) + if response_format is not None: + # Set the response format on the response so .value knows how to parse + response._response_format = response_format + response._value_parsed = False # Reset to allow re-parsing with new format + # Access response.value to trigger parsing (may raise ValidationError) # Validate that parsing succeeded if not isinstance(response.value, response_format): raise ValueError( diff --git a/python/packages/durabletask/tests/test_durable_entities.py b/python/packages/durabletask/tests/test_durable_entities.py index 35babc44c0..acebcd8492 100644 --- a/python/packages/durabletask/tests/test_durable_entities.py +++ b/python/packages/durabletask/tests/test_durable_entities.py @@ -11,7 +11,7 @@ from unittest.mock import AsyncMock, Mock import pytest -from agent_framework import AgentResponse, AgentResponseUpdate, ChatMessage, Content, Role +from agent_framework import AgentResponse, AgentResponseUpdate, ChatMessage, Content from pydantic import BaseModel from agent_framework_durabletask import ( @@ -81,9 +81,7 @@ def _role_value(chat_message: DurableAgentStateMessage) -> str: def _agent_response(text: str | None) -> AgentResponse: """Create an AgentResponse with a single assistant message.""" - message = ( - ChatMessage(role="assistant", text=text) if text is not None else ChatMessage(role="assistant", contents=[]) - ) + message = ChatMessage("assistant", [text]) if text is not None else ChatMessage("assistant", []) return AgentResponse(messages=[message]) @@ -222,8 +220,8 @@ async def test_run_executes_agent(self) -> None: async def test_run_agent_streaming_callbacks_invoked(self) -> None: """Ensure streaming updates trigger callbacks and run() is not used.""" updates = [ - AgentResponseUpdate(text="Hello"), - AgentResponseUpdate(text=" world"), + AgentResponseUpdate(contents=[Content.from_text(text="Hello")]), + AgentResponseUpdate(contents=[Content.from_text(text=" world")]), ] async def update_generator() -> AsyncIterator[AgentResponseUpdate]: @@ -595,7 +593,7 @@ async def test_run_agent_with_run_request_object(self) -> None: request = RunRequest( message="Test message", - role=Role.USER, + role="user", enable_tool_calls=True, correlation_id="corr-runreq-1", ) @@ -644,7 +642,7 @@ async def test_run_agent_stores_role_in_history(self) -> None: # Send as system role request = RunRequest( message="System message", - role=Role.SYSTEM, + role="system", correlation_id="corr-runreq-3", ) diff --git a/python/packages/durabletask/tests/test_executors.py b/python/packages/durabletask/tests/test_executors.py index 46fe8bbdbc..802007541f 100644 --- a/python/packages/durabletask/tests/test_executors.py +++ b/python/packages/durabletask/tests/test_executors.py @@ -11,7 +11,7 @@ from unittest.mock import Mock import pytest -from agent_framework import AgentResponse, Role +from agent_framework import AgentResponse from durabletask.entities import EntityInstanceId from durabletask.task import Task from pydantic import BaseModel @@ -241,7 +241,7 @@ def test_fire_and_forget_returns_empty_response(self, mock_client: Mock) -> None # Verify it contains an acceptance message assert isinstance(result, AgentResponse) assert len(result.messages) == 1 - assert result.messages[0].role == Role.SYSTEM + assert result.messages[0].role == "system" # Check message contains key information message_text = result.messages[0].text assert "accepted" in message_text.lower() @@ -294,7 +294,7 @@ def test_orchestration_fire_and_forget_returns_acceptance_response(self, mock_or response = result.get_result() assert isinstance(response, AgentResponse) assert len(response.messages) == 1 - assert response.messages[0].role == Role.SYSTEM + assert response.messages[0].role == "system" assert "test-789" in response.messages[0].text def test_orchestration_blocking_mode_calls_call_entity(self, mock_orchestration_context: Mock) -> None: @@ -392,7 +392,7 @@ def test_durable_agent_task_transforms_successful_result( result = task.get_result() assert isinstance(result, AgentResponse) assert len(result.messages) == 1 - assert result.messages[0].role == Role.ASSISTANT + assert result.messages[0].role == "assistant" def test_durable_agent_task_propagates_failure(self, configure_failed_entity_task: Any) -> None: """Verify DurableAgentTask propagates task failures.""" @@ -519,8 +519,8 @@ def test_durable_agent_task_handles_multiple_messages(self, configure_successful result = task.get_result() assert isinstance(result, AgentResponse) assert len(result.messages) == 2 - assert result.messages[0].role == Role.ASSISTANT - assert result.messages[1].role == Role.ASSISTANT + assert result.messages[0].role == "assistant" + assert result.messages[1].role == "assistant" def test_durable_agent_task_is_not_complete_initially(self, mock_entity_task: Mock) -> None: """Verify DurableAgentTask is not complete when first created.""" diff --git a/python/packages/durabletask/tests/test_models.py b/python/packages/durabletask/tests/test_models.py index 0f6a24293d..40097fd43d 100644 --- a/python/packages/durabletask/tests/test_models.py +++ b/python/packages/durabletask/tests/test_models.py @@ -3,7 +3,6 @@ """Unit tests for data models (RunRequest).""" import pytest -from agent_framework import Role from pydantic import BaseModel from agent_framework_durabletask._models import RunRequest @@ -22,7 +21,7 @@ def test_init_with_defaults(self) -> None: assert request.message == "Hello" assert request.correlation_id == "corr-001" - assert request.role == Role.USER + assert request.role == "user" assert request.response_format is None assert request.enable_tool_calls is True assert request.wait_for_response is True @@ -33,7 +32,7 @@ def test_init_with_all_fields(self) -> None: request = RunRequest( message="Hello", correlation_id="corr-002", - role=Role.SYSTEM, + role="system", response_format=schema, enable_tool_calls=False, wait_for_response=False, @@ -41,7 +40,7 @@ def test_init_with_all_fields(self) -> None: assert request.message == "Hello" assert request.correlation_id == "corr-002" - assert request.role == Role.SYSTEM + assert request.role == "system" assert request.response_format is schema assert request.enable_tool_calls is False assert request.wait_for_response is False @@ -50,7 +49,7 @@ def test_init_coerces_string_role(self) -> None: """Ensure string role values are coerced into Role instances.""" request = RunRequest(message="Hello", correlation_id="corr-003", role="system") # type: ignore[arg-type] - assert request.role == Role.SYSTEM + assert request.role == "system" def test_to_dict_with_defaults(self) -> None: """Test to_dict with default values.""" @@ -71,7 +70,7 @@ def test_to_dict_with_all_fields(self) -> None: request = RunRequest( message="Hello", correlation_id="corr-005", - role=Role.ASSISTANT, + role="assistant", response_format=schema, enable_tool_calls=False, wait_for_response=False, @@ -95,7 +94,7 @@ def test_from_dict_with_defaults(self) -> None: assert request.message == "Hello" assert request.correlation_id == "corr-006" - assert request.role == Role.USER + assert request.role == "user" assert request.enable_tool_calls is True assert request.wait_for_response is True @@ -122,7 +121,7 @@ def test_from_dict_with_all_fields(self) -> None: assert request.message == "Test" assert request.correlation_id == "corr-008" - assert request.role == Role.SYSTEM + assert request.role == "system" assert request.response_format is ModuleStructuredResponse assert request.enable_tool_calls is False @@ -131,8 +130,8 @@ def test_from_dict_unknown_role_preserves_value(self) -> None: data = {"message": "Test", "correlationId": "corr-009", "role": "reviewer"} request = RunRequest.from_dict(data) - assert request.role.value == "reviewer" - assert request.role != Role.USER + assert request.role == "reviewer" + assert request.role != "user" def test_from_dict_empty_message(self) -> None: """Test from_dict with empty message.""" @@ -140,7 +139,7 @@ def test_from_dict_empty_message(self) -> None: assert request.message == "" assert request.correlation_id == "corr-010" - assert request.role == Role.USER + assert request.role == "user" def test_from_dict_missing_correlation_id_raises(self) -> None: """Test from_dict raises when correlationId is missing.""" @@ -152,7 +151,7 @@ def test_round_trip_dict_conversion(self) -> None: original = RunRequest( message="Test message", correlation_id="corr-011", - role=Role.SYSTEM, + role="system", response_format=ModuleStructuredResponse, enable_tool_calls=False, ) @@ -232,7 +231,7 @@ def test_round_trip_with_correlationId(self) -> None: """Test round-trip to_dict and from_dict with correlationId.""" original = RunRequest( message="Test message", - role=Role.SYSTEM, + role="system", correlation_id="corr-124", ) @@ -292,7 +291,7 @@ def test_round_trip_with_orchestration_id(self) -> None: """Test round-trip to_dict and from_dict with orchestration_id.""" original = RunRequest( message="Test message", - role=Role.SYSTEM, + role="system", correlation_id="corr-129", orchestration_id="orch-123", ) diff --git a/python/packages/durabletask/tests/test_shim.py b/python/packages/durabletask/tests/test_shim.py index 26988edca4..d1b0cf2cab 100644 --- a/python/packages/durabletask/tests/test_shim.py +++ b/python/packages/durabletask/tests/test_shim.py @@ -77,7 +77,7 @@ def test_run_accepts_string_message(self, test_agent: DurableAIAgent[Any], mock_ def test_run_accepts_chat_message(self, test_agent: DurableAIAgent[Any], mock_executor: Mock) -> None: """Verify run accepts and normalizes ChatMessage objects.""" - chat_msg = ChatMessage(role="user", text="Test message") + chat_msg = ChatMessage("user", ["Test message"]) test_agent.run(chat_msg) mock_executor.run_durable_agent.assert_called_once() @@ -95,8 +95,8 @@ def test_run_accepts_list_of_strings(self, test_agent: DurableAIAgent[Any], mock def test_run_accepts_list_of_chat_messages(self, test_agent: DurableAIAgent[Any], mock_executor: Mock) -> None: """Verify run accepts and joins list of ChatMessage objects.""" messages = [ - ChatMessage(role="user", text="Message 1"), - ChatMessage(role="assistant", text="Message 2"), + ChatMessage("user", ["Message 1"]), + ChatMessage("assistant", ["Message 2"]), ] test_agent.run(messages) diff --git a/python/packages/github_copilot/agent_framework_github_copilot/_agent.py b/python/packages/github_copilot/agent_framework_github_copilot/_agent.py index 90655ae055..778a340039 100644 --- a/python/packages/github_copilot/agent_framework_github_copilot/_agent.py +++ b/python/packages/github_copilot/agent_framework_github_copilot/_agent.py @@ -16,7 +16,6 @@ ChatMessage, Content, ContextProvider, - Role, normalize_messages, ) from agent_framework._tools import FunctionTool, ToolProtocol @@ -330,7 +329,7 @@ async def run( if response_event.data.content: response_messages.append( ChatMessage( - role=Role.ASSISTANT, + role="assistant", contents=[Content.from_text(response_event.data.content)], message_id=message_id, raw_representation=response_event, @@ -385,7 +384,7 @@ def event_handler(event: SessionEvent) -> None: if event.type == SessionEventType.ASSISTANT_MESSAGE_DELTA: if event.data.delta_content: update = AgentResponseUpdate( - role=Role.ASSISTANT, + role="assistant", contents=[Content.from_text(event.data.delta_content)], response_id=event.data.message_id, message_id=event.data.message_id, diff --git a/python/packages/github_copilot/tests/test_github_copilot_agent.py b/python/packages/github_copilot/tests/test_github_copilot_agent.py index e68b58c243..37707465cb 100644 --- a/python/packages/github_copilot/tests/test_github_copilot_agent.py +++ b/python/packages/github_copilot/tests/test_github_copilot_agent.py @@ -13,7 +13,6 @@ AgentThread, ChatMessage, Content, - Role, ) from agent_framework.exceptions import ServiceException from copilot.generated.session_events import Data, SessionEvent, SessionEventType @@ -282,7 +281,7 @@ async def test_run_string_message( assert isinstance(response, AgentResponse) assert len(response.messages) == 1 - assert response.messages[0].role == Role.ASSISTANT + assert response.messages[0].role == "assistant" assert response.messages[0].contents[0].text == "Test response" async def test_run_chat_message( @@ -295,7 +294,7 @@ async def test_run_chat_message( mock_session.send_and_wait.return_value = assistant_message_event agent = GitHubCopilotAgent(client=mock_client) - chat_message = ChatMessage(role=Role.USER, contents=[Content.from_text("Hello")]) + chat_message = ChatMessage("user", [Content.from_text("Hello")]) response = await agent.run(chat_message) assert isinstance(response, AgentResponse) @@ -390,7 +389,7 @@ def mock_on(handler: Any) -> Any: assert len(responses) == 1 assert isinstance(responses[0], AgentResponseUpdate) - assert responses[0].role == Role.ASSISTANT + assert responses[0].role == "assistant" assert responses[0].contents[0].text == "Hello" async def test_run_stream_with_thread( diff --git a/python/packages/lab/tau2/agent_framework_lab_tau2/_message_utils.py b/python/packages/lab/tau2/agent_framework_lab_tau2/_message_utils.py index 2da621a21a..4fd5e21fb7 100644 --- a/python/packages/lab/tau2/agent_framework_lab_tau2/_message_utils.py +++ b/python/packages/lab/tau2/agent_framework_lab_tau2/_message_utils.py @@ -1,6 +1,6 @@ # Copyright (c) Microsoft. All rights reserved. -from agent_framework._types import ChatMessage, Content, Role +from agent_framework._types import ChatMessage, Content from loguru import logger @@ -18,25 +18,25 @@ def filter_out_function_calls(messages: list[Content]) -> list[Content]: flipped_messages = [] for msg in messages: - if msg.role == Role.ASSISTANT: + if msg.role == "assistant": # Flip assistant to user contents = filter_out_function_calls(msg.contents) if contents: flipped_msg = ChatMessage( - role=Role.USER, + role="user", # The function calls will cause 400 when role is user contents=contents, author_name=msg.author_name, message_id=msg.message_id, ) flipped_messages.append(flipped_msg) - elif msg.role == Role.USER: + elif msg.role == "user": # Flip user to assistant flipped_msg = ChatMessage( - role=Role.ASSISTANT, contents=msg.contents, author_name=msg.author_name, message_id=msg.message_id + role="assistant", contents=msg.contents, author_name=msg.author_name, message_id=msg.message_id ) flipped_messages.append(flipped_msg) - elif msg.role == Role.TOOL: + elif msg.role == "tool": # Skip tool messages pass else: @@ -59,16 +59,16 @@ def log_messages(messages: list[ChatMessage]) -> None: if hasattr(content, "type"): if content.type == "text": escape_text = content.text.replace("<", r"\<") # type: ignore[union-attr] - if msg.role == Role.SYSTEM: + if msg.role == "system": logger_.info(f"[SYSTEM] {escape_text}") - elif msg.role == Role.USER: + elif msg.role == "user": logger_.info(f"[USER] {escape_text}") - elif msg.role == Role.ASSISTANT: + elif msg.role == "assistant": logger_.info(f"[ASSISTANT] {escape_text}") - elif msg.role == Role.TOOL: + elif msg.role == "tool": logger_.info(f"[TOOL] {escape_text}") else: - logger_.info(f"[{msg.role.value.upper()}] {escape_text}") + logger_.info(f"[{msg.role.upper()}] {escape_text}") elif content.type == "function_call": function_call_text = f"{content.name}({content.arguments})" function_call_text = function_call_text.replace("<", r"\<") @@ -79,34 +79,34 @@ def log_messages(messages: list[ChatMessage]) -> None: logger_.info(f"[TOOL_RESULT] 🔨 {function_result_text}") else: content_text = str(content).replace("<", r"\<") - logger_.info(f"[{msg.role.value.upper()}] ({content.type}) {content_text}") + logger_.info(f"[{msg.role.upper()}] ({content.type}) {content_text}") else: # Fallback for content without type text_content = str(content).replace("<", r"\<") - if msg.role == Role.SYSTEM: + if msg.role == "system": logger_.info(f"[SYSTEM] {text_content}") - elif msg.role == Role.USER: + elif msg.role == "user": logger_.info(f"[USER] {text_content}") - elif msg.role == Role.ASSISTANT: + elif msg.role == "assistant": logger_.info(f"[ASSISTANT] {text_content}") - elif msg.role == Role.TOOL: + elif msg.role == "tool": logger_.info(f"[TOOL] {text_content}") else: - logger_.info(f"[{msg.role.value.upper()}] {text_content}") + logger_.info(f"[{msg.role.upper()}] {text_content}") elif hasattr(msg, "text") and msg.text: # Handle simple text messages text_content = msg.text.replace("<", r"\<") - if msg.role == Role.SYSTEM: + if msg.role == "system": logger_.info(f"[SYSTEM] {text_content}") - elif msg.role == Role.USER: + elif msg.role == "user": logger_.info(f"[USER] {text_content}") - elif msg.role == Role.ASSISTANT: + elif msg.role == "assistant": logger_.info(f"[ASSISTANT] {text_content}") - elif msg.role == Role.TOOL: + elif msg.role == "tool": logger_.info(f"[TOOL] {text_content}") else: - logger_.info(f"[{msg.role.value.upper()}] {text_content}") + logger_.info(f"[{msg.role.upper()}] {text_content}") else: # Fallback for other message formats text_content = str(msg).replace("<", r"\<") - logger_.info(f"[{msg.role.value.upper()}] {text_content}") + logger_.info(f"[{msg.role.upper()}] {text_content}") diff --git a/python/packages/lab/tau2/agent_framework_lab_tau2/_sliding_window.py b/python/packages/lab/tau2/agent_framework_lab_tau2/_sliding_window.py index e34d9f48a4..cec984272f 100644 --- a/python/packages/lab/tau2/agent_framework_lab_tau2/_sliding_window.py +++ b/python/packages/lab/tau2/agent_framework_lab_tau2/_sliding_window.py @@ -5,7 +5,7 @@ from typing import Any import tiktoken -from agent_framework import ChatMessage, ChatMessageStore, Role +from agent_framework import ChatMessage, ChatMessageStore from loguru import logger @@ -51,7 +51,7 @@ def truncate_messages(self) -> None: logger.warning("Messages exceed max tokens. Truncating oldest message.") self.truncated_messages.pop(0) # Remove leading tool messages - while len(self.truncated_messages) > 0 and self.truncated_messages[0].role == Role.TOOL: + while len(self.truncated_messages) > 0 and self.truncated_messages[0].role == "tool": logger.warning("Removing leading tool message because tool result cannot be the first message.") self.truncated_messages.pop(0) diff --git a/python/packages/lab/tau2/agent_framework_lab_tau2/runner.py b/python/packages/lab/tau2/agent_framework_lab_tau2/runner.py index dddf7088b5..0e63f4085e 100644 --- a/python/packages/lab/tau2/agent_framework_lab_tau2/runner.py +++ b/python/packages/lab/tau2/agent_framework_lab_tau2/runner.py @@ -12,7 +12,6 @@ ChatClientProtocol, ChatMessage, FunctionExecutor, - Role, Workflow, WorkflowBuilder, WorkflowContext, @@ -339,11 +338,11 @@ async def run( # Matches tau2's expected conversation start pattern logger.info(f"Starting workflow with hardcoded greeting: '{DEFAULT_FIRST_AGENT_MESSAGE}'") - first_message = ChatMessage(Role.ASSISTANT, text=DEFAULT_FIRST_AGENT_MESSAGE) + first_message = ChatMessage("assistant", text=DEFAULT_FIRST_AGENT_MESSAGE) initial_greeting = AgentExecutorResponse( executor_id=ASSISTANT_AGENT_ID, agent_response=AgentResponse(messages=[first_message]), - full_conversation=[ChatMessage(Role.ASSISTANT, text=DEFAULT_FIRST_AGENT_MESSAGE)], + full_conversation=[ChatMessage("assistant", text=DEFAULT_FIRST_AGENT_MESSAGE)], ) # STEP 4: Execute the workflow and collect results diff --git a/python/packages/lab/tau2/tests/test_message_utils.py b/python/packages/lab/tau2/tests/test_message_utils.py index 255f0a96ae..33b705db3a 100644 --- a/python/packages/lab/tau2/tests/test_message_utils.py +++ b/python/packages/lab/tau2/tests/test_message_utils.py @@ -2,7 +2,7 @@ from unittest.mock import patch -from agent_framework._types import ChatMessage, Content, Role +from agent_framework._types import ChatMessage, Content from agent_framework_lab_tau2._message_utils import flip_messages, log_messages @@ -10,7 +10,7 @@ def test_flip_messages_user_to_assistant(): """Test flipping user message to assistant.""" messages = [ ChatMessage( - role=Role.USER, + role="user", contents=[Content.from_text(text="Hello assistant")], author_name="User1", message_id="msg_001", @@ -20,7 +20,7 @@ def test_flip_messages_user_to_assistant(): flipped = flip_messages(messages) assert len(flipped) == 1 - assert flipped[0].role == Role.ASSISTANT + assert flipped[0].role == "assistant" assert flipped[0].text == "Hello assistant" assert flipped[0].author_name == "User1" assert flipped[0].message_id == "msg_001" @@ -30,7 +30,7 @@ def test_flip_messages_assistant_to_user(): """Test flipping assistant message to user.""" messages = [ ChatMessage( - role=Role.ASSISTANT, + role="assistant", contents=[Content.from_text(text="Hello user")], author_name="Assistant1", message_id="msg_002", @@ -40,7 +40,7 @@ def test_flip_messages_assistant_to_user(): flipped = flip_messages(messages) assert len(flipped) == 1 - assert flipped[0].role == Role.USER + assert flipped[0].role == "user" assert flipped[0].text == "Hello user" assert flipped[0].author_name == "Assistant1" assert flipped[0].message_id == "msg_002" @@ -52,7 +52,7 @@ def test_flip_messages_assistant_with_function_calls_filtered(): messages = [ ChatMessage( - role=Role.ASSISTANT, + role="assistant", contents=[ Content.from_text(text="I'll call a function"), function_call, @@ -65,7 +65,7 @@ def test_flip_messages_assistant_with_function_calls_filtered(): flipped = flip_messages(messages) assert len(flipped) == 1 - assert flipped[0].role == Role.USER + assert flipped[0].role == "user" # Function call should be filtered out assert len(flipped[0].contents) == 2 assert all(content.type == "text" for content in flipped[0].contents) @@ -78,7 +78,7 @@ def test_flip_messages_assistant_with_only_function_calls_skipped(): function_call = Content.from_function_call(call_id="call_456", name="another_function", arguments={"key": "value"}) messages = [ - ChatMessage(role=Role.ASSISTANT, contents=[function_call], message_id="msg_004") # Only function call, no text + ChatMessage("assistant", [function_call], message_id="msg_004") # Only function call, no text ] flipped = flip_messages(messages) @@ -91,7 +91,7 @@ def test_flip_messages_tool_messages_skipped(): """Test that tool messages are skipped.""" function_result = Content.from_function_result(call_id="call_789", result={"success": True}) - messages = [ChatMessage(role=Role.TOOL, contents=[function_result])] + messages = [ChatMessage("tool", [function_result])] flipped = flip_messages(messages) @@ -101,14 +101,12 @@ def test_flip_messages_tool_messages_skipped(): def test_flip_messages_system_messages_preserved(): """Test that system messages are preserved as-is.""" - messages = [ - ChatMessage(role=Role.SYSTEM, contents=[Content.from_text(text="System instruction")], message_id="sys_001") - ] + messages = [ChatMessage("system", [Content.from_text(text="System instruction")], message_id="sys_001")] flipped = flip_messages(messages) assert len(flipped) == 1 - assert flipped[0].role == Role.SYSTEM + assert flipped[0].role == "system" assert flipped[0].text == "System instruction" assert flipped[0].message_id == "sys_001" @@ -120,11 +118,11 @@ def test_flip_messages_mixed_conversation(): function_result = Content.from_function_result(call_id="call_mixed", result="function result") messages = [ - ChatMessage(role=Role.SYSTEM, contents=[Content.from_text(text="System prompt")]), - ChatMessage(role=Role.USER, contents=[Content.from_text(text="User question")]), - ChatMessage(role=Role.ASSISTANT, contents=[Content.from_text(text="Assistant response"), function_call]), - ChatMessage(role=Role.TOOL, contents=[function_result]), - ChatMessage(role=Role.ASSISTANT, contents=[Content.from_text(text="Final response")]), + ChatMessage("system", [Content.from_text(text="System prompt")]), + ChatMessage("user", [Content.from_text(text="User question")]), + ChatMessage("assistant", [Content.from_text(text="Assistant response"), function_call]), + ChatMessage("tool", [function_result]), + ChatMessage("assistant", [Content.from_text(text="Final response")]), ] flipped = flip_messages(messages) @@ -134,18 +132,18 @@ def test_flip_messages_mixed_conversation(): assert len(flipped) == 4 # Check each flipped message - assert flipped[0].role == Role.SYSTEM + assert flipped[0].role == "system" assert flipped[0].text == "System prompt" - assert flipped[1].role == Role.ASSISTANT + assert flipped[1].role == "assistant" assert flipped[1].text == "User question" - assert flipped[2].role == Role.USER + assert flipped[2].role == "user" assert flipped[2].text == "Assistant response" # Function call filtered out # Tool message skipped - assert flipped[3].role == Role.USER + assert flipped[3].role == "user" assert flipped[3].text == "Final response" @@ -160,7 +158,7 @@ def test_flip_messages_preserves_metadata(): """Test that message metadata is preserved during flipping.""" messages = [ ChatMessage( - role=Role.USER, + role="user", contents=[Content.from_text(text="Test message")], author_name="TestUser", message_id="test_123", @@ -178,8 +176,8 @@ def test_flip_messages_preserves_metadata(): def test_log_messages_text_content(mock_logger): """Test logging messages with text content.""" messages = [ - ChatMessage(role=Role.USER, contents=[Content.from_text(text="Hello")]), - ChatMessage(role=Role.ASSISTANT, contents=[Content.from_text(text="Hi there!")]), + ChatMessage("user", [Content.from_text(text="Hello")]), + ChatMessage("assistant", [Content.from_text(text="Hi there!")]), ] log_messages(messages) @@ -193,7 +191,7 @@ def test_log_messages_function_call(mock_logger): """Test logging messages with function calls.""" function_call = Content.from_function_call(call_id="call_log", name="log_function", arguments={"param": "value"}) - messages = [ChatMessage(role=Role.ASSISTANT, contents=[function_call])] + messages = [ChatMessage("assistant", [function_call])] log_messages(messages) @@ -209,7 +207,7 @@ def test_log_messages_function_result(mock_logger): """Test logging messages with function results.""" function_result = Content.from_function_result(call_id="call_result", result="success") - messages = [ChatMessage(role=Role.TOOL, contents=[function_result])] + messages = [ChatMessage("tool", [function_result])] log_messages(messages) @@ -223,10 +221,10 @@ def test_log_messages_function_result(mock_logger): def test_log_messages_different_roles(mock_logger): """Test logging messages with different roles get different colors.""" messages = [ - ChatMessage(role=Role.SYSTEM, contents=[Content.from_text(text="System")]), - ChatMessage(role=Role.USER, contents=[Content.from_text(text="User")]), - ChatMessage(role=Role.ASSISTANT, contents=[Content.from_text(text="Assistant")]), - ChatMessage(role=Role.TOOL, contents=[Content.from_text(text="Tool")]), + ChatMessage("system", [Content.from_text(text="System")]), + ChatMessage("user", [Content.from_text(text="User")]), + ChatMessage("assistant", [Content.from_text(text="Assistant")]), + ChatMessage("tool", [Content.from_text(text="Tool")]), ] log_messages(messages) @@ -250,7 +248,7 @@ def test_log_messages_different_roles(mock_logger): @patch("agent_framework_lab_tau2._message_utils.logger") def test_log_messages_escapes_html(mock_logger): """Test that HTML-like characters are properly escaped in log output.""" - messages = [ChatMessage(role=Role.USER, contents=[Content.from_text(text="Message with content")])] + messages = [ChatMessage("user", [Content.from_text(text="Message with content")])] log_messages(messages) @@ -267,7 +265,7 @@ def test_log_messages_mixed_content_types(mock_logger): messages = [ ChatMessage( - role=Role.ASSISTANT, + role="assistant", contents=[Content.from_text(text="I'll call a function"), function_call, Content.from_text(text="Done!")], ) ] diff --git a/python/packages/lab/tau2/tests/test_sliding_window.py b/python/packages/lab/tau2/tests/test_sliding_window.py index 030b57a750..971a391882 100644 --- a/python/packages/lab/tau2/tests/test_sliding_window.py +++ b/python/packages/lab/tau2/tests/test_sliding_window.py @@ -4,7 +4,7 @@ from unittest.mock import patch -from agent_framework._types import ChatMessage, Content, Role +from agent_framework._types import ChatMessage, Content from agent_framework_lab_tau2._sliding_window import SlidingWindowChatMessageStore @@ -36,8 +36,8 @@ def test_initialization_with_parameters(): def test_initialization_with_messages(): """Test initializing with existing messages.""" messages = [ - ChatMessage(role=Role.USER, contents=[Content.from_text(text="Hello")]), - ChatMessage(role=Role.ASSISTANT, contents=[Content.from_text(text="Hi there!")]), + ChatMessage("user", [Content.from_text(text="Hello")]), + ChatMessage("assistant", [Content.from_text(text="Hi there!")]), ] sliding_window = SlidingWindowChatMessageStore(messages=messages, max_tokens=1000) @@ -51,8 +51,8 @@ async def test_add_messages_simple(): sliding_window = SlidingWindowChatMessageStore(max_tokens=10000) # Large limit new_messages = [ - ChatMessage(role=Role.USER, contents=[Content.from_text(text="What's the weather?")]), - ChatMessage(role=Role.ASSISTANT, contents=[Content.from_text(text="I can help with that.")]), + ChatMessage("user", [Content.from_text(text="What's the weather?")]), + ChatMessage("assistant", [Content.from_text(text="I can help with that.")]), ] await sliding_window.add_messages(new_messages) @@ -68,10 +68,7 @@ async def test_list_all_messages_vs_list_messages(): sliding_window = SlidingWindowChatMessageStore(max_tokens=50) # Small limit to force truncation # Add many messages to trigger truncation - messages = [ - ChatMessage(role=Role.USER, contents=[Content.from_text(text=f"Message {i} with some content")]) - for i in range(10) - ] + messages = [ChatMessage("user", [Content.from_text(text=f"Message {i} with some content")]) for i in range(10)] await sliding_window.add_messages(messages) @@ -88,7 +85,7 @@ async def test_list_all_messages_vs_list_messages(): def test_get_token_count_basic(): """Test basic token counting.""" sliding_window = SlidingWindowChatMessageStore(max_tokens=1000) - sliding_window.truncated_messages = [ChatMessage(role=Role.USER, contents=[Content.from_text(text="Hello")])] + sliding_window.truncated_messages = [ChatMessage("user", [Content.from_text(text="Hello")])] token_count = sliding_window.get_token_count() @@ -105,7 +102,7 @@ def test_get_token_count_with_system_message(): token_count_empty = sliding_window.get_token_count() # Add a message - sliding_window.truncated_messages = [ChatMessage(role=Role.USER, contents=[Content.from_text(text="Hello")])] + sliding_window.truncated_messages = [ChatMessage("user", [Content.from_text(text="Hello")])] token_count_with_message = sliding_window.get_token_count() # With message should be more tokens @@ -118,7 +115,7 @@ def test_get_token_count_function_call(): function_call = Content.from_function_call(call_id="call_123", name="test_function", arguments={"param": "value"}) sliding_window = SlidingWindowChatMessageStore(max_tokens=1000) - sliding_window.truncated_messages = [ChatMessage(role=Role.ASSISTANT, contents=[function_call])] + sliding_window.truncated_messages = [ChatMessage("assistant", [function_call])] token_count = sliding_window.get_token_count() assert token_count > 0 @@ -129,7 +126,7 @@ def test_get_token_count_function_result(): function_result = Content.from_function_result(call_id="call_123", result={"success": True, "data": "result"}) sliding_window = SlidingWindowChatMessageStore(max_tokens=1000) - sliding_window.truncated_messages = [ChatMessage(role=Role.TOOL, contents=[function_result])] + sliding_window.truncated_messages = [ChatMessage("tool", [function_result])] token_count = sliding_window.get_token_count() assert token_count > 0 @@ -143,16 +140,16 @@ def test_truncate_messages_removes_old_messages(mock_logger): # Create messages that will exceed the limit messages = [ ChatMessage( - role=Role.USER, + role="user", contents=[Content.from_text(text="This is a very long message that should exceed the token limit")], ), ChatMessage( - role=Role.ASSISTANT, + role="assistant", contents=[ Content.from_text(text="This is another very long message that should also exceed the token limit") ], ), - ChatMessage(role=Role.USER, contents=[Content.from_text(text="Short msg")]), + ChatMessage("user", [Content.from_text(text="Short msg")]), ] sliding_window.truncated_messages = messages.copy() @@ -172,16 +169,16 @@ def test_truncate_messages_removes_leading_tool_messages(mock_logger): # Create messages starting with tool message tool_message = ChatMessage( - role=Role.TOOL, contents=[Content.from_function_result(call_id="call_123", result="result")] + role="tool", contents=[Content.from_function_result(call_id="call_123", result="result")] ) - user_message = ChatMessage(role=Role.USER, contents=[Content.from_text(text="Hello")]) + user_message = ChatMessage("user", [Content.from_text(text="Hello")]) sliding_window.truncated_messages = [tool_message, user_message] sliding_window.truncate_messages() # Tool message should be removed from the beginning assert len(sliding_window.truncated_messages) == 1 - assert sliding_window.truncated_messages[0].role == Role.USER + assert sliding_window.truncated_messages[0].role == "user" # Should have logged warning about removing tool message mock_logger.warning.assert_called() @@ -232,14 +229,14 @@ async def test_real_world_scenario(): # Simulate a conversation conversation = [ - ChatMessage(role=Role.USER, contents=[Content.from_text(text="Hello, how are you?")]), + ChatMessage("user", [Content.from_text(text="Hello, how are you?")]), ChatMessage( - role=Role.ASSISTANT, + role="assistant", contents=[Content.from_text(text="I'm doing well, thank you! How can I help you today?")], ), - ChatMessage(role=Role.USER, contents=[Content.from_text(text="Can you tell me about the weather?")]), + ChatMessage("user", [Content.from_text(text="Can you tell me about the weather?")]), ChatMessage( - role=Role.ASSISTANT, + role="assistant", contents=[ Content.from_text( text="I'd be happy to help with weather information, " @@ -247,9 +244,9 @@ async def test_real_world_scenario(): ) ], ), - ChatMessage(role=Role.USER, contents=[Content.from_text(text="What about telling me a joke instead?")]), + ChatMessage("user", [Content.from_text(text="What about telling me a joke instead?")]), ChatMessage( - role=Role.ASSISTANT, + role="assistant", contents=[ Content.from_text(text="Sure! Why don't scientists trust atoms? Because they make up everything!") ], diff --git a/python/packages/lab/tau2/tests/test_tau2_utils.py b/python/packages/lab/tau2/tests/test_tau2_utils.py index 8811952bbe..29520bda42 100644 --- a/python/packages/lab/tau2/tests/test_tau2_utils.py +++ b/python/packages/lab/tau2/tests/test_tau2_utils.py @@ -6,7 +6,7 @@ from pathlib import Path import pytest -from agent_framework import ChatMessage, Content, FunctionTool, Role +from agent_framework import ChatMessage, Content, FunctionTool from agent_framework_lab_tau2._tau2_utils import ( convert_agent_framework_messages_to_tau2_messages, convert_tau2_tool_to_function_tool, @@ -91,7 +91,7 @@ def test_convert_tau2_tool_to_function_tool_multiple_tools(tau2_airline_environm def test_convert_agent_framework_messages_to_tau2_messages_system(): """Test converting system message.""" - messages = [ChatMessage(role=Role.SYSTEM, contents=[Content.from_text(text="System instruction")])] + messages = [ChatMessage("system", [Content.from_text(text="System instruction")])] tau2_messages = convert_agent_framework_messages_to_tau2_messages(messages) @@ -103,7 +103,7 @@ def test_convert_agent_framework_messages_to_tau2_messages_system(): def test_convert_agent_framework_messages_to_tau2_messages_user(): """Test converting user message.""" - messages = [ChatMessage(role=Role.USER, contents=[Content.from_text(text="Hello assistant")])] + messages = [ChatMessage("user", [Content.from_text(text="Hello assistant")])] tau2_messages = convert_agent_framework_messages_to_tau2_messages(messages) @@ -116,7 +116,7 @@ def test_convert_agent_framework_messages_to_tau2_messages_user(): def test_convert_agent_framework_messages_to_tau2_messages_assistant(): """Test converting assistant message.""" - messages = [ChatMessage(role=Role.ASSISTANT, contents=[Content.from_text(text="Hello user")])] + messages = [ChatMessage("assistant", [Content.from_text(text="Hello user")])] tau2_messages = convert_agent_framework_messages_to_tau2_messages(messages) @@ -131,9 +131,7 @@ def test_convert_agent_framework_messages_to_tau2_messages_with_function_call(): """Test converting message with function call.""" function_call = Content.from_function_call(call_id="call_123", name="test_function", arguments={"param": "value"}) - messages = [ - ChatMessage(role=Role.ASSISTANT, contents=[Content.from_text(text="I'll call a function"), function_call]) - ] + messages = [ChatMessage("assistant", [Content.from_text(text="I'll call a function"), function_call])] tau2_messages = convert_agent_framework_messages_to_tau2_messages(messages) @@ -155,7 +153,7 @@ def test_convert_agent_framework_messages_to_tau2_messages_with_function_result( """Test converting message with function result.""" function_result = Content.from_function_result(call_id="call_123", result={"success": True, "data": "result data"}) - messages = [ChatMessage(role=Role.TOOL, contents=[function_result])] + messages = [ChatMessage("tool", [function_result])] tau2_messages = convert_agent_framework_messages_to_tau2_messages(messages) @@ -175,7 +173,7 @@ def test_convert_agent_framework_messages_to_tau2_messages_with_error(): call_id="call_456", result="Error occurred", exception=Exception("Test error") ) - messages = [ChatMessage(role=Role.TOOL, contents=[function_result])] + messages = [ChatMessage("tool", [function_result])] tau2_messages = convert_agent_framework_messages_to_tau2_messages(messages) @@ -186,11 +184,7 @@ def test_convert_agent_framework_messages_to_tau2_messages_with_error(): def test_convert_agent_framework_messages_to_tau2_messages_multiple_text_contents(): """Test converting message with multiple text contents.""" - messages = [ - ChatMessage( - role=Role.USER, contents=[Content.from_text(text="First part"), Content.from_text(text="Second part")] - ) - ] + messages = [ChatMessage("user", [Content.from_text(text="First part"), Content.from_text(text="Second part")])] tau2_messages = convert_agent_framework_messages_to_tau2_messages(messages) @@ -206,11 +200,11 @@ def test_convert_agent_framework_messages_to_tau2_messages_complex_scenario(): function_result = Content.from_function_result(call_id="call_789", result={"output": "tool result"}) messages = [ - ChatMessage(role=Role.SYSTEM, contents=[Content.from_text(text="System prompt")]), - ChatMessage(role=Role.USER, contents=[Content.from_text(text="User request")]), - ChatMessage(role=Role.ASSISTANT, contents=[Content.from_text(text="I'll help you"), function_call]), - ChatMessage(role=Role.TOOL, contents=[function_result]), - ChatMessage(role=Role.ASSISTANT, contents=[Content.from_text(text="Based on the result...")]), + ChatMessage("system", [Content.from_text(text="System prompt")]), + ChatMessage("user", [Content.from_text(text="User request")]), + ChatMessage("assistant", [Content.from_text(text="I'll help you"), function_call]), + ChatMessage("tool", [function_result]), + ChatMessage("assistant", [Content.from_text(text="Based on the result...")]), ] tau2_messages = convert_agent_framework_messages_to_tau2_messages(messages) diff --git a/python/packages/mem0/agent_framework_mem0/_provider.py b/python/packages/mem0/agent_framework_mem0/_provider.py index 8ab9192d1a..ac37cc1a2c 100644 --- a/python/packages/mem0/agent_framework_mem0/_provider.py +++ b/python/packages/mem0/agent_framework_mem0/_provider.py @@ -121,9 +121,9 @@ async def invoked( messages_list = [*request_messages_list, *response_messages_list] messages: list[dict[str, str]] = [ - {"role": message.role.value, "content": message.text} + {"role": message.role, "content": message.text} for message in messages_list - if message.role.value in {"user", "assistant", "system"} and message.text and message.text.strip() + if message.role in {"user", "assistant", "system"} and message.text and message.text.strip() ] if messages: @@ -176,7 +176,7 @@ async def invoking(self, messages: ChatMessage | MutableSequence[ChatMessage], * line_separated_memories = "\n".join(memory.get("memory", "") for memory in memories) return Context( - messages=[ChatMessage(role="user", text=f"{self.context_prompt}\n{line_separated_memories}")] + messages=[ChatMessage("user", [f"{self.context_prompt}\n{line_separated_memories}"])] if line_separated_memories else None ) diff --git a/python/packages/mem0/tests/test_mem0_context_provider.py b/python/packages/mem0/tests/test_mem0_context_provider.py index 85779b6ccf..0b39c7b043 100644 --- a/python/packages/mem0/tests/test_mem0_context_provider.py +++ b/python/packages/mem0/tests/test_mem0_context_provider.py @@ -7,7 +7,7 @@ from unittest.mock import AsyncMock, patch import pytest -from agent_framework import ChatMessage, Content, Context, Role +from agent_framework import ChatMessage, Content, Context from agent_framework.exceptions import ServiceInitializationError from agent_framework.mem0 import Mem0Provider @@ -36,9 +36,9 @@ def mock_mem0_client() -> AsyncMock: def sample_messages() -> list[ChatMessage]: """Create sample chat messages for testing.""" return [ - ChatMessage(role=Role.USER, text="Hello, how are you?"), - ChatMessage(role=Role.ASSISTANT, text="I'm doing well, thank you!"), - ChatMessage(role=Role.SYSTEM, text="You are a helpful assistant"), + ChatMessage("user", ["Hello, how are you?"]), + ChatMessage("assistant", ["I'm doing well, thank you!"]), + ChatMessage("system", ["You are a helpful assistant"]), ] @@ -191,7 +191,7 @@ class TestMem0ProviderMessagesAdding: async def test_messages_adding_fails_without_filters(self, mock_mem0_client: AsyncMock) -> None: """Test that invoked fails when no filters are provided.""" provider = Mem0Provider(mem0_client=mock_mem0_client) - message = ChatMessage(role=Role.USER, text="Hello!") + message = ChatMessage("user", ["Hello!"]) with pytest.raises(ServiceInitializationError) as exc_info: await provider.invoked(message) @@ -201,7 +201,7 @@ async def test_messages_adding_fails_without_filters(self, mock_mem0_client: Asy async def test_messages_adding_single_message(self, mock_mem0_client: AsyncMock) -> None: """Test adding a single message.""" provider = Mem0Provider(user_id="user123", mem0_client=mock_mem0_client) - message = ChatMessage(role=Role.USER, text="Hello!") + message = ChatMessage("user", ["Hello!"]) await provider.invoked(message) @@ -288,9 +288,9 @@ async def test_messages_adding_filters_empty_messages(self, mock_mem0_client: As """Test that empty or invalid messages are filtered out.""" provider = Mem0Provider(user_id="user123", mem0_client=mock_mem0_client) messages = [ - ChatMessage(role=Role.USER, text=""), # Empty text - ChatMessage(role=Role.USER, text=" "), # Whitespace only - ChatMessage(role=Role.USER, text="Valid message"), + ChatMessage("user", [""]), # Empty text + ChatMessage("user", [" "]), # Whitespace only + ChatMessage("user", ["Valid message"]), ] await provider.invoked(messages) @@ -303,8 +303,8 @@ async def test_messages_adding_skips_when_no_valid_messages(self, mock_mem0_clie """Test that mem0 client is not called when no valid messages exist.""" provider = Mem0Provider(user_id="user123", mem0_client=mock_mem0_client) messages = [ - ChatMessage(role=Role.USER, text=""), - ChatMessage(role=Role.USER, text=" "), + ChatMessage("user", [""]), + ChatMessage("user", [" "]), ] await provider.invoked(messages) @@ -318,7 +318,7 @@ class TestMem0ProviderModelInvoking: async def test_model_invoking_fails_without_filters(self, mock_mem0_client: AsyncMock) -> None: """Test that invoking fails when no filters are provided.""" provider = Mem0Provider(mem0_client=mock_mem0_client) - message = ChatMessage(role=Role.USER, text="What's the weather?") + message = ChatMessage("user", ["What's the weather?"]) with pytest.raises(ServiceInitializationError) as exc_info: await provider.invoking(message) @@ -328,7 +328,7 @@ async def test_model_invoking_fails_without_filters(self, mock_mem0_client: Asyn async def test_model_invoking_single_message(self, mock_mem0_client: AsyncMock) -> None: """Test invoking with a single message.""" provider = Mem0Provider(user_id="user123", mem0_client=mock_mem0_client) - message = ChatMessage(role=Role.USER, text="What's the weather?") + message = ChatMessage("user", ["What's the weather?"]) # Mock search results mock_mem0_client.search.return_value = [ @@ -369,7 +369,7 @@ async def test_model_invoking_multiple_messages( async def test_model_invoking_with_agent_id(self, mock_mem0_client: AsyncMock) -> None: """Test invoking with agent_id.""" provider = Mem0Provider(agent_id="agent123", mem0_client=mock_mem0_client) - message = ChatMessage(role=Role.USER, text="Hello") + message = ChatMessage("user", ["Hello"]) mock_mem0_client.search.return_value = [] @@ -387,7 +387,7 @@ async def test_model_invoking_with_scope_to_per_operation_thread_id(self, mock_m mem0_client=mock_mem0_client, ) provider._per_operation_thread_id = "operation_thread" - message = ChatMessage(role=Role.USER, text="Hello") + message = ChatMessage("user", ["Hello"]) mock_mem0_client.search.return_value = [] @@ -399,7 +399,7 @@ async def test_model_invoking_with_scope_to_per_operation_thread_id(self, mock_m async def test_model_invoking_no_memories_returns_none_instructions(self, mock_mem0_client: AsyncMock) -> None: """Test that no memories returns context with None instructions.""" provider = Mem0Provider(user_id="user123", mem0_client=mock_mem0_client) - message = ChatMessage(role=Role.USER, text="Hello") + message = ChatMessage("user", ["Hello"]) mock_mem0_client.search.return_value = [] @@ -416,7 +416,7 @@ async def test_model_invoking_function_approval_response_returns_none_instructio provider = Mem0Provider(user_id="user123", mem0_client=mock_mem0_client) function_call = Content.from_function_call(call_id="1", name="test_func", arguments='{"arg1": "value1"}') message = ChatMessage( - role=Role.USER, + role="user", contents=[ Content.from_function_approval_response( id="approval_1", @@ -437,9 +437,9 @@ async def test_model_invoking_filters_empty_message_text(self, mock_mem0_client: """Test that empty message text is filtered out from query.""" provider = Mem0Provider(user_id="user123", mem0_client=mock_mem0_client) messages = [ - ChatMessage(role=Role.USER, text=""), - ChatMessage(role=Role.USER, text="Valid message"), - ChatMessage(role=Role.USER, text=" "), + ChatMessage("user", [""]), + ChatMessage("user", ["Valid message"]), + ChatMessage("user", [" "]), ] mock_mem0_client.search.return_value = [] @@ -457,7 +457,7 @@ async def test_model_invoking_custom_context_prompt(self, mock_mem0_client: Asyn context_prompt=custom_prompt, mem0_client=mock_mem0_client, ) - message = ChatMessage(role=Role.USER, text="Hello") + message = ChatMessage("user", ["Hello"]) mock_mem0_client.search.return_value = [{"memory": "Test memory"}] diff --git a/python/packages/ollama/agent_framework_ollama/_chat_client.py b/python/packages/ollama/agent_framework_ollama/_chat_client.py index ead729b8e2..2891ab5bcb 100644 --- a/python/packages/ollama/agent_framework_ollama/_chat_client.py +++ b/python/packages/ollama/agent_framework_ollama/_chat_client.py @@ -21,7 +21,6 @@ ChatResponseUpdate, Content, FunctionTool, - Role, ToolProtocol, UsageDetails, get_logger, @@ -442,12 +441,12 @@ def _prepare_messages_for_ollama(self, messages: MutableSequence[ChatMessage]) - def _prepare_message_for_ollama(self, message: ChatMessage) -> list[OllamaMessage]: message_converters: dict[str, Callable[[ChatMessage], list[OllamaMessage]]] = { - Role.SYSTEM.value: self._format_system_message, - Role.USER.value: self._format_user_message, - Role.ASSISTANT.value: self._format_assistant_message, - Role.TOOL.value: self._format_tool_message, + "system": self._format_system_message, + "user": self._format_user_message, + "assistant": self._format_assistant_message, + "tool": self._format_tool_message, } - return message_converters[message.role.value](message) + return message_converters[message.role](message) def _format_system_message(self, message: ChatMessage) -> list[OllamaMessage]: return [OllamaMessage(role="system", content=message.text)] @@ -516,8 +515,8 @@ def _parse_streaming_response_from_ollama(self, response: OllamaChatResponse) -> contents = self._parse_contents_from_ollama(response) return ChatResponseUpdate( contents=contents, - role=Role.ASSISTANT, - ai_model_id=response.model, + role="assistant", + model_id=response.model, created_at=response.created_at, ) @@ -525,7 +524,7 @@ def _parse_response_from_ollama(self, response: OllamaChatResponse) -> ChatRespo contents = self._parse_contents_from_ollama(response) return ChatResponse( - messages=[ChatMessage(role=Role.ASSISTANT, contents=contents)], + messages=[ChatMessage("assistant", contents)], model_id=response.model, created_at=response.created_at, usage_details=UsageDetails( diff --git a/python/packages/purview/README.md b/python/packages/purview/README.md index ad3d1867d0..b016f00c8b 100644 --- a/python/packages/purview/README.md +++ b/python/packages/purview/README.md @@ -72,7 +72,7 @@ async def main(): middleware=[purview_middleware] ) - response = await agent.run(ChatMessage(role=Role.USER, text="Summarize zero trust in one sentence.")) + response = await agent.run(ChatMessage("user", ["Summarize zero trust in one sentence."])) print(response) asyncio.run(main()) diff --git a/python/packages/purview/agent_framework_purview/_middleware.py b/python/packages/purview/agent_framework_purview/_middleware.py index 7839f2f968..a0cce1bd55 100644 --- a/python/packages/purview/agent_framework_purview/_middleware.py +++ b/python/packages/purview/agent_framework_purview/_middleware.py @@ -57,10 +57,10 @@ async def process( context.messages, Activity.UPLOAD_TEXT ) if should_block_prompt: - from agent_framework import AgentResponse, ChatMessage, Role + from agent_framework import AgentResponse, ChatMessage context.result = AgentResponse( - messages=[ChatMessage(role=Role.SYSTEM, text=self._settings.blocked_prompt_message)] + messages=[ChatMessage("system", [self._settings.blocked_prompt_message])] ) context.terminate = True return @@ -85,10 +85,10 @@ async def process( user_id=resolved_user_id, ) if should_block_response: - from agent_framework import AgentResponse, ChatMessage, Role + from agent_framework import AgentResponse, ChatMessage context.result = AgentResponse( - messages=[ChatMessage(role=Role.SYSTEM, text=self._settings.blocked_response_message)] + messages=[ChatMessage("system", [self._settings.blocked_response_message])] ) else: # Streaming responses are not supported for post-checks @@ -149,7 +149,7 @@ async def process( if should_block_prompt: from agent_framework import ChatMessage, ChatResponse - blocked_message = ChatMessage(role="system", text=self._settings.blocked_prompt_message) + blocked_message = ChatMessage("system", [self._settings.blocked_prompt_message]) context.result = ChatResponse(messages=[blocked_message]) context.terminate = True return @@ -177,7 +177,7 @@ async def process( if should_block_response: from agent_framework import ChatMessage, ChatResponse - blocked_message = ChatMessage(role="system", text=self._settings.blocked_response_message) + blocked_message = ChatMessage("system", [self._settings.blocked_response_message]) context.result = ChatResponse(messages=[blocked_message]) else: logger.debug("Streaming responses are not supported for Purview policy post-checks") diff --git a/python/packages/purview/tests/test_chat_middleware.py b/python/packages/purview/tests/test_chat_middleware.py index 3f9595e721..763a54ac67 100644 --- a/python/packages/purview/tests/test_chat_middleware.py +++ b/python/packages/purview/tests/test_chat_middleware.py @@ -5,7 +5,7 @@ from unittest.mock import AsyncMock, MagicMock, patch import pytest -from agent_framework import ChatContext, ChatMessage, Role +from agent_framework import ChatContext, ChatMessage from azure.core.credentials import AccessToken from agent_framework_purview import PurviewChatPolicyMiddleware, PurviewSettings @@ -36,9 +36,7 @@ def chat_context(self) -> ChatContext: chat_client = DummyChatClient() chat_options = MagicMock() chat_options.model = "test-model" - return ChatContext( - chat_client=chat_client, messages=[ChatMessage(role=Role.USER, text="Hello")], options=chat_options - ) + return ChatContext(chat_client=chat_client, messages=[ChatMessage("user", ["Hello"])], options=chat_options) async def test_initialization(self, middleware: PurviewChatPolicyMiddleware) -> None: assert middleware._client is not None @@ -56,14 +54,14 @@ async def mock_next(ctx: ChatContext) -> None: class Result: def __init__(self): - self.messages = [ChatMessage(role=Role.ASSISTANT, text="Hi there")] + self.messages = [ChatMessage("assistant", ["Hi there"])] ctx.result = Result() await middleware.process(chat_context, mock_next) assert next_called assert mock_proc.call_count == 2 - assert chat_context.result.messages[0].role == Role.ASSISTANT + assert chat_context.result.messages[0].role == "assistant" async def test_blocks_prompt(self, middleware: PurviewChatPolicyMiddleware, chat_context: ChatContext) -> None: with patch.object(middleware._processor, "process_messages", return_value=(True, "user-123")): @@ -76,7 +74,7 @@ async def mock_next(ctx: ChatContext) -> None: # should not run assert chat_context.result assert hasattr(chat_context.result, "messages") msg = chat_context.result.messages[0] - assert msg.role in ("system", Role.SYSTEM) + assert msg.role in ("system", "system") assert "blocked" in msg.text.lower() async def test_blocks_response(self, middleware: PurviewChatPolicyMiddleware, chat_context: ChatContext) -> None: @@ -92,7 +90,7 @@ async def side_effect(messages, activity, user_id=None): async def mock_next(ctx: ChatContext) -> None: class Result: def __init__(self): - self.messages = [ChatMessage(role=Role.ASSISTANT, text="Sensitive output")] # pragma: no cover + self.messages = [ChatMessage("assistant", ["Sensitive output"])] # pragma: no cover ctx.result = Result() @@ -100,7 +98,7 @@ def __init__(self): assert call_state["count"] == 2 msgs = getattr(chat_context.result, "messages", None) or chat_context.result first_msg = msgs[0] - assert first_msg.role in ("system", Role.SYSTEM) + assert first_msg.role in ("system", "system") assert "blocked" in first_msg.text.lower() async def test_streaming_skips_post_check(self, middleware: PurviewChatPolicyMiddleware) -> None: @@ -109,7 +107,7 @@ async def test_streaming_skips_post_check(self, middleware: PurviewChatPolicyMid chat_options.model = "test-model" streaming_context = ChatContext( chat_client=chat_client, - messages=[ChatMessage(role=Role.USER, text="Hello")], + messages=[ChatMessage("user", ["Hello"])], options=chat_options, is_streaming=True, ) @@ -141,7 +139,7 @@ async def mock_process_messages(*args, **kwargs): async def mock_next(ctx: ChatContext) -> None: result = MagicMock() - result.messages = [ChatMessage(role=Role.ASSISTANT, text="Response")] + result.messages = [ChatMessage("assistant", ["Response"])] ctx.result = result await middleware.process(chat_context, mock_next) @@ -165,7 +163,7 @@ async def mock_process_messages(messages, activity, user_id=None): async def mock_next(ctx: ChatContext) -> None: result = MagicMock() - result.messages = [ChatMessage(role=Role.ASSISTANT, text="Response")] + result.messages = [ChatMessage("assistant", ["Response"])] ctx.result = result await middleware.process(chat_context, mock_next) @@ -188,9 +186,7 @@ async def test_chat_middleware_handles_payment_required_pre_check(self, mock_cre chat_client = DummyChatClient() chat_options = MagicMock() chat_options.model = "test-model" - context = ChatContext( - chat_client=chat_client, messages=[ChatMessage(role=Role.USER, text="Hello")], options=chat_options - ) + context = ChatContext(chat_client=chat_client, messages=[ChatMessage("user", ["Hello"])], options=chat_options) async def mock_process_messages(*args, **kwargs): raise PurviewPaymentRequiredError("Payment required") @@ -214,9 +210,7 @@ async def test_chat_middleware_handles_payment_required_post_check(self, mock_cr chat_client = DummyChatClient() chat_options = MagicMock() chat_options.model = "test-model" - context = ChatContext( - chat_client=chat_client, messages=[ChatMessage(role=Role.USER, text="Hello")], options=chat_options - ) + context = ChatContext(chat_client=chat_client, messages=[ChatMessage("user", ["Hello"])], options=chat_options) call_count = 0 @@ -231,7 +225,7 @@ async def side_effect(*args, **kwargs): async def mock_next(ctx: ChatContext) -> None: result = MagicMock() - result.messages = [ChatMessage(role=Role.ASSISTANT, text="OK")] + result.messages = [ChatMessage("assistant", ["OK"])] ctx.result = result with pytest.raises(PurviewPaymentRequiredError): @@ -247,9 +241,7 @@ async def test_chat_middleware_ignores_payment_required_when_configured(self, mo chat_client = DummyChatClient() chat_options = MagicMock() chat_options.model = "test-model" - context = ChatContext( - chat_client=chat_client, messages=[ChatMessage(role=Role.USER, text="Hello")], options=chat_options - ) + context = ChatContext(chat_client=chat_client, messages=[ChatMessage("user", ["Hello"])], options=chat_options) async def mock_process_messages(*args, **kwargs): raise PurviewPaymentRequiredError("Payment required") @@ -258,7 +250,7 @@ async def mock_process_messages(*args, **kwargs): async def mock_next(ctx: ChatContext) -> None: result = MagicMock() - result.messages = [ChatMessage(role=Role.ASSISTANT, text="Response")] + result.messages = [ChatMessage("assistant", ["Response"])] context.result = result # Should not raise, just log @@ -289,9 +281,7 @@ async def test_chat_middleware_with_ignore_exceptions(self, mock_credential: Asy chat_client = DummyChatClient() chat_options = MagicMock() chat_options.model = "test-model" - context = ChatContext( - chat_client=chat_client, messages=[ChatMessage(role=Role.USER, text="Hello")], options=chat_options - ) + context = ChatContext(chat_client=chat_client, messages=[ChatMessage("user", ["Hello"])], options=chat_options) async def mock_process_messages(*args, **kwargs): raise ValueError("Some error") @@ -300,7 +290,7 @@ async def mock_process_messages(*args, **kwargs): async def mock_next(ctx: ChatContext) -> None: result = MagicMock() - result.messages = [ChatMessage(role=Role.ASSISTANT, text="Response")] + result.messages = [ChatMessage("assistant", ["Response"])] context.result = result # Should not raise, just log @@ -318,9 +308,7 @@ async def test_chat_middleware_raises_on_pre_check_exception_when_ignore_excepti chat_client = DummyChatClient() chat_options = MagicMock() chat_options.model = "test-model" - context = ChatContext( - chat_client=chat_client, messages=[ChatMessage(role=Role.USER, text="Hello")], options=chat_options - ) + context = ChatContext(chat_client=chat_client, messages=[ChatMessage("user", ["Hello"])], options=chat_options) with patch.object(middleware._processor, "process_messages", side_effect=ValueError("boom")): @@ -340,9 +328,7 @@ async def test_chat_middleware_raises_on_post_check_exception_when_ignore_except chat_client = DummyChatClient() chat_options = MagicMock() chat_options.model = "test-model" - context = ChatContext( - chat_client=chat_client, messages=[ChatMessage(role=Role.USER, text="Hello")], options=chat_options - ) + context = ChatContext(chat_client=chat_client, messages=[ChatMessage("user", ["Hello"])], options=chat_options) call_count = 0 @@ -357,7 +343,7 @@ async def side_effect(*args, **kwargs): async def mock_next(ctx: ChatContext) -> None: result = MagicMock() - result.messages = [ChatMessage(role=Role.ASSISTANT, text="OK")] + result.messages = [ChatMessage("assistant", ["OK"])] ctx.result = result with pytest.raises(ValueError, match="post"): diff --git a/python/packages/purview/tests/test_middleware.py b/python/packages/purview/tests/test_middleware.py index b973e8ea34..32f712b0b9 100644 --- a/python/packages/purview/tests/test_middleware.py +++ b/python/packages/purview/tests/test_middleware.py @@ -5,7 +5,7 @@ from unittest.mock import AsyncMock, MagicMock, patch import pytest -from agent_framework import AgentResponse, AgentRunContext, ChatMessage, Role +from agent_framework import AgentResponse, AgentRunContext, ChatMessage from azure.core.credentials import AccessToken from agent_framework_purview import PurviewPolicyMiddleware, PurviewSettings @@ -49,7 +49,7 @@ async def test_middleware_allows_clean_prompt( self, middleware: PurviewPolicyMiddleware, mock_agent: MagicMock ) -> None: """Test middleware allows prompt that passes policy check.""" - context = AgentRunContext(agent=mock_agent, messages=[ChatMessage(role=Role.USER, text="Hello, how are you?")]) + context = AgentRunContext(agent=mock_agent, messages=[ChatMessage("user", ["Hello, how are you?"])]) with patch.object(middleware._processor, "process_messages", return_value=(False, "user-123")): next_called = False @@ -57,7 +57,7 @@ async def test_middleware_allows_clean_prompt( async def mock_next(ctx: AgentRunContext) -> None: nonlocal next_called next_called = True - ctx.result = AgentResponse(messages=[ChatMessage(role=Role.ASSISTANT, text="I'm good, thanks!")]) + ctx.result = AgentResponse(messages=[ChatMessage("assistant", ["I'm good, thanks!"])]) await middleware.process(context, mock_next) @@ -69,9 +69,7 @@ async def test_middleware_blocks_prompt_on_policy_violation( self, middleware: PurviewPolicyMiddleware, mock_agent: MagicMock ) -> None: """Test middleware blocks prompt that violates policy.""" - context = AgentRunContext( - agent=mock_agent, messages=[ChatMessage(role=Role.USER, text="Sensitive information")] - ) + context = AgentRunContext(agent=mock_agent, messages=[ChatMessage("user", ["Sensitive information"])]) with patch.object(middleware._processor, "process_messages", return_value=(True, "user-123")): next_called = False @@ -86,12 +84,12 @@ async def mock_next(ctx: AgentRunContext) -> None: assert context.result is not None assert context.terminate assert len(context.result.messages) == 1 - assert context.result.messages[0].role == Role.SYSTEM + assert context.result.messages[0].role == "system" assert "blocked by policy" in context.result.messages[0].text.lower() async def test_middleware_checks_response(self, middleware: PurviewPolicyMiddleware, mock_agent: MagicMock) -> None: """Test middleware checks agent response for policy violations.""" - context = AgentRunContext(agent=mock_agent, messages=[ChatMessage(role=Role.USER, text="Hello")]) + context = AgentRunContext(agent=mock_agent, messages=[ChatMessage("user", ["Hello"])]) call_count = 0 @@ -104,16 +102,14 @@ async def mock_process_messages(messages, activity, user_id=None): with patch.object(middleware._processor, "process_messages", side_effect=mock_process_messages): async def mock_next(ctx: AgentRunContext) -> None: - ctx.result = AgentResponse( - messages=[ChatMessage(role=Role.ASSISTANT, text="Here's some sensitive information")] - ) + ctx.result = AgentResponse(messages=[ChatMessage("assistant", ["Here's some sensitive information"])]) await middleware.process(context, mock_next) assert call_count == 2 assert context.result is not None assert len(context.result.messages) == 1 - assert context.result.messages[0].role == Role.SYSTEM + assert context.result.messages[0].role == "system" assert "blocked by policy" in context.result.messages[0].text.lower() async def test_middleware_handles_result_without_messages( @@ -123,7 +119,7 @@ async def test_middleware_handles_result_without_messages( # Set ignore_exceptions to True so AttributeError is caught and logged middleware._settings.ignore_exceptions = True - context = AgentRunContext(agent=mock_agent, messages=[ChatMessage(role=Role.USER, text="Hello")]) + context = AgentRunContext(agent=mock_agent, messages=[ChatMessage("user", ["Hello"])]) with patch.object(middleware._processor, "process_messages", return_value=(False, "user-123")): @@ -140,12 +136,12 @@ async def test_middleware_processor_receives_correct_activity( """Test middleware passes correct activity type to processor.""" from agent_framework_purview._models import Activity - context = AgentRunContext(agent=mock_agent, messages=[ChatMessage(role=Role.USER, text="Test")]) + context = AgentRunContext(agent=mock_agent, messages=[ChatMessage("user", ["Test"])]) with patch.object(middleware._processor, "process_messages", return_value=(False, "user-123")) as mock_process: async def mock_next(ctx: AgentRunContext) -> None: - ctx.result = AgentResponse(messages=[ChatMessage(role=Role.ASSISTANT, text="Response")]) + ctx.result = AgentResponse(messages=[ChatMessage("assistant", ["Response"])]) await middleware.process(context, mock_next) @@ -157,13 +153,13 @@ async def test_middleware_streaming_skips_post_check( self, middleware: PurviewPolicyMiddleware, mock_agent: MagicMock ) -> None: """Test that streaming results skip post-check evaluation.""" - context = AgentRunContext(agent=mock_agent, messages=[ChatMessage(role=Role.USER, text="Hello")]) + context = AgentRunContext(agent=mock_agent, messages=[ChatMessage("user", ["Hello"])]) context.is_streaming = True with patch.object(middleware._processor, "process_messages", return_value=(False, "user-123")) as mock_proc: async def mock_next(ctx: AgentRunContext) -> None: - ctx.result = AgentResponse(messages=[ChatMessage(role=Role.ASSISTANT, text="streaming")]) + ctx.result = AgentResponse(messages=[ChatMessage("assistant", ["streaming"])]) await middleware.process(context, mock_next) @@ -175,7 +171,7 @@ async def test_middleware_payment_required_in_pre_check_raises_by_default( """Test that 402 in pre-check is raised when ignore_payment_required=False.""" from agent_framework_purview._exceptions import PurviewPaymentRequiredError - context = AgentRunContext(agent=mock_agent, messages=[ChatMessage(role=Role.USER, text="Hello")]) + context = AgentRunContext(agent=mock_agent, messages=[ChatMessage("user", ["Hello"])]) with patch.object( middleware._processor, @@ -195,7 +191,7 @@ async def test_middleware_payment_required_in_post_check_raises_by_default( """Test that 402 in post-check is raised when ignore_payment_required=False.""" from agent_framework_purview._exceptions import PurviewPaymentRequiredError - context = AgentRunContext(agent=mock_agent, messages=[ChatMessage(role=Role.USER, text="Hello")]) + context = AgentRunContext(agent=mock_agent, messages=[ChatMessage("user", ["Hello"])]) call_count = 0 @@ -209,7 +205,7 @@ async def side_effect(*args, **kwargs): with patch.object(middleware._processor, "process_messages", side_effect=side_effect): async def mock_next(ctx: AgentRunContext) -> None: - ctx.result = AgentResponse(messages=[ChatMessage(role=Role.ASSISTANT, text="OK")]) + ctx.result = AgentResponse(messages=[ChatMessage("assistant", ["OK"])]) with pytest.raises(PurviewPaymentRequiredError): await middleware.process(context, mock_next) @@ -220,7 +216,7 @@ async def test_middleware_post_check_exception_raises_when_ignore_exceptions_fal """Test that post-check exceptions are propagated when ignore_exceptions=False.""" middleware._settings.ignore_exceptions = False - context = AgentRunContext(agent=mock_agent, messages=[ChatMessage(role=Role.USER, text="Hello")]) + context = AgentRunContext(agent=mock_agent, messages=[ChatMessage("user", ["Hello"])]) call_count = 0 @@ -234,7 +230,7 @@ async def side_effect(*args, **kwargs): with patch.object(middleware._processor, "process_messages", side_effect=side_effect): async def mock_next(ctx: AgentRunContext) -> None: - ctx.result = AgentResponse(messages=[ChatMessage(role=Role.ASSISTANT, text="OK")]) + ctx.result = AgentResponse(messages=[ChatMessage("assistant", ["OK"])]) with pytest.raises(ValueError, match="Post-check blew up"): await middleware.process(context, mock_next) @@ -246,14 +242,14 @@ async def test_middleware_handles_pre_check_exception( # Set ignore_exceptions to True middleware._settings.ignore_exceptions = True - context = AgentRunContext(agent=mock_agent, messages=[ChatMessage(role=Role.USER, text="Test")]) + context = AgentRunContext(agent=mock_agent, messages=[ChatMessage("user", ["Test"])]) with patch.object( middleware._processor, "process_messages", side_effect=Exception("Pre-check error") ) as mock_process: async def mock_next(ctx: AgentRunContext) -> None: - ctx.result = AgentResponse(messages=[ChatMessage(role=Role.ASSISTANT, text="Response")]) + ctx.result = AgentResponse(messages=[ChatMessage("assistant", ["Response"])]) await middleware.process(context, mock_next) @@ -271,7 +267,7 @@ async def test_middleware_handles_post_check_exception( # Set ignore_exceptions to True middleware._settings.ignore_exceptions = True - context = AgentRunContext(agent=mock_agent, messages=[ChatMessage(role=Role.USER, text="Test")]) + context = AgentRunContext(agent=mock_agent, messages=[ChatMessage("user", ["Test"])]) call_count = 0 @@ -285,7 +281,7 @@ async def mock_process_messages(*args, **kwargs): with patch.object(middleware._processor, "process_messages", side_effect=mock_process_messages): async def mock_next(ctx: AgentRunContext) -> None: - ctx.result = AgentResponse(messages=[ChatMessage(role=Role.ASSISTANT, text="Response")]) + ctx.result = AgentResponse(messages=[ChatMessage("assistant", ["Response"])]) await middleware.process(context, mock_next) @@ -302,7 +298,7 @@ async def test_middleware_with_ignore_exceptions_true(self, mock_credential: Asy mock_agent = MagicMock() mock_agent.name = "test-agent" - context = AgentRunContext(agent=mock_agent, messages=[ChatMessage(role=Role.USER, text="Test")]) + context = AgentRunContext(agent=mock_agent, messages=[ChatMessage("user", ["Test"])]) # Mock processor to raise an exception async def mock_process_messages(*args, **kwargs): @@ -311,7 +307,7 @@ async def mock_process_messages(*args, **kwargs): with patch.object(middleware._processor, "process_messages", side_effect=mock_process_messages): async def mock_next(ctx): - ctx.result = AgentResponse(messages=[ChatMessage(role=Role.ASSISTANT, text="Response")]) + ctx.result = AgentResponse(messages=[ChatMessage("assistant", ["Response"])]) # Should not raise, just log await middleware.process(context, mock_next) @@ -326,7 +322,7 @@ async def test_middleware_with_ignore_exceptions_false(self, mock_credential: As mock_agent = MagicMock() mock_agent.name = "test-agent" - context = AgentRunContext(agent=mock_agent, messages=[ChatMessage(role=Role.USER, text="Test")]) + context = AgentRunContext(agent=mock_agent, messages=[ChatMessage("user", ["Test"])]) # Mock processor to raise an exception async def mock_process_messages(*args, **kwargs): diff --git a/python/packages/purview/tests/test_processor.py b/python/packages/purview/tests/test_processor.py index 11f48ed199..3dfd78d981 100644 --- a/python/packages/purview/tests/test_processor.py +++ b/python/packages/purview/tests/test_processor.py @@ -5,7 +5,7 @@ from unittest.mock import AsyncMock, MagicMock, patch import pytest -from agent_framework import ChatMessage, Role +from agent_framework import ChatMessage from agent_framework_purview import PurviewAppLocation, PurviewLocationType, PurviewSettings from agent_framework_purview._models import ( @@ -83,8 +83,8 @@ async def test_processor_initialization( async def test_process_messages_with_defaults(self, processor: ScopedContentProcessor) -> None: """Test process_messages with settings that have defaults.""" messages = [ - ChatMessage(role=Role.USER, text="Hello"), - ChatMessage(role=Role.ASSISTANT, text="Hi there"), + ChatMessage("user", ["Hello"]), + ChatMessage("assistant", ["Hi there"]), ] with patch.object(processor, "_map_messages", return_value=([], None)) as mock_map: @@ -98,7 +98,7 @@ async def test_process_messages_blocks_content( self, processor: ScopedContentProcessor, process_content_request_factory ) -> None: """Test process_messages returns True when content should be blocked.""" - messages = [ChatMessage(role=Role.USER, text="Sensitive content")] + messages = [ChatMessage("user", ["Sensitive content"])] mock_request = process_content_request_factory("Sensitive content") @@ -121,7 +121,7 @@ async def test_map_messages_creates_requests( """Test _map_messages creates ProcessContentRequest objects.""" messages = [ ChatMessage( - role=Role.USER, + role="user", text="Test message", message_id="msg-123", author_name="12345678-1234-1234-1234-123456789012", @@ -139,7 +139,7 @@ async def test_map_messages_without_defaults_gets_token_info(self, mock_client: """Test _map_messages gets token info when settings lack some defaults.""" settings = PurviewSettings(app_name="Test App", tenant_id="12345678-1234-1234-1234-123456789012") processor = ScopedContentProcessor(mock_client, settings) - messages = [ChatMessage(role=Role.USER, text="Test", message_id="msg-123")] + messages = [ChatMessage("user", ["Test"], message_id="msg-123")] requests, user_id = await processor._map_messages(messages, Activity.UPLOAD_TEXT) @@ -156,7 +156,7 @@ async def test_map_messages_raises_on_missing_tenant_id(self, mock_client: Async return_value={"user_id": "test-user", "client_id": "test-client"} ) - messages = [ChatMessage(role=Role.USER, text="Test", message_id="msg-123")] + messages = [ChatMessage("user", ["Test"], message_id="msg-123")] with pytest.raises(ValueError, match="Tenant id required"): await processor._map_messages(messages, Activity.UPLOAD_TEXT) @@ -332,7 +332,7 @@ async def test_map_messages_with_user_id_in_additional_properties(self, mock_cli messages = [ ChatMessage( - role=Role.USER, + role="user", text="Test message", additional_properties={"user_id": "22345678-1234-1234-1234-123456789012"}, ), @@ -355,7 +355,7 @@ async def test_map_messages_with_provided_user_id_fallback(self, mock_client: As ) processor = ScopedContentProcessor(mock_client, settings) - messages = [ChatMessage(role=Role.USER, text="Test message")] + messages = [ChatMessage("user", ["Test message"])] requests, user_id = await processor._map_messages( messages, Activity.UPLOAD_TEXT, provided_user_id="32345678-1234-1234-1234-123456789012" @@ -376,7 +376,7 @@ async def test_map_messages_returns_empty_when_no_user_id(self, mock_client: Asy ) processor = ScopedContentProcessor(mock_client, settings) - messages = [ChatMessage(role=Role.USER, text="Test message")] + messages = [ChatMessage("user", ["Test message"])] requests, user_id = await processor._map_messages(messages, Activity.UPLOAD_TEXT) @@ -479,7 +479,7 @@ async def test_user_id_from_token_when_no_other_source(self, mock_client: AsyncM settings = PurviewSettings(app_name="Test App") # No tenant_id or app_location processor = ScopedContentProcessor(mock_client, settings) - messages = [ChatMessage(role=Role.USER, text="Test")] + messages = [ChatMessage("user", ["Test"])] requests, user_id = await processor._map_messages(messages, Activity.UPLOAD_TEXT) @@ -494,7 +494,7 @@ async def test_user_id_from_additional_properties_takes_priority( messages = [ ChatMessage( - role=Role.USER, + role="user", text="Test", additional_properties={"user_id": "22222222-2222-2222-2222-222222222222"}, ) @@ -514,7 +514,7 @@ async def test_user_id_from_author_name_as_fallback( messages = [ ChatMessage( - role=Role.USER, + role="user", text="Test", author_name="33333333-3333-3333-3333-333333333333", ) @@ -532,7 +532,7 @@ async def test_author_name_ignored_if_not_valid_guid( messages = [ ChatMessage( - role=Role.USER, + role="user", text="Test", author_name="John Doe", # Not a GUID ) @@ -550,7 +550,7 @@ async def test_provided_user_id_used_as_last_resort( """Test provided_user_id parameter is used as last resort.""" processor = ScopedContentProcessor(mock_client, settings) - messages = [ChatMessage(role=Role.USER, text="Test")] + messages = [ChatMessage("user", ["Test"])] requests, user_id = await processor._map_messages( messages, Activity.UPLOAD_TEXT, provided_user_id="44444444-4444-4444-4444-444444444444" @@ -562,7 +562,7 @@ async def test_invalid_provided_user_id_ignored(self, mock_client: AsyncMock, se """Test invalid provided_user_id is ignored.""" processor = ScopedContentProcessor(mock_client, settings) - messages = [ChatMessage(role=Role.USER, text="Test")] + messages = [ChatMessage("user", ["Test"])] requests, user_id = await processor._map_messages(messages, Activity.UPLOAD_TEXT, provided_user_id="not-a-guid") @@ -575,10 +575,10 @@ async def test_multiple_messages_same_user_id(self, mock_client: AsyncMock, sett messages = [ ChatMessage( - role=Role.USER, text="First", additional_properties={"user_id": "55555555-5555-5555-5555-555555555555"} + role="user", text="First", additional_properties={"user_id": "55555555-5555-5555-5555-555555555555"} ), - ChatMessage(role=Role.ASSISTANT, text="Response"), - ChatMessage(role=Role.USER, text="Second"), + ChatMessage("assistant", ["Response"]), + ChatMessage("user", ["Second"]), ] requests, user_id = await processor._map_messages(messages, Activity.UPLOAD_TEXT) @@ -594,14 +594,14 @@ async def test_first_valid_user_id_in_messages_is_used( processor = ScopedContentProcessor(mock_client, settings) messages = [ - ChatMessage(role=Role.USER, text="First", author_name="Not a GUID"), + ChatMessage("user", ["First"], author_name="Not a GUID"), ChatMessage( - role=Role.ASSISTANT, + role="assistant", text="Response", additional_properties={"user_id": "66666666-6666-6666-6666-666666666666"}, ), ChatMessage( - role=Role.USER, text="Third", additional_properties={"user_id": "77777777-7777-7777-7777-777777777777"} + role="user", text="Third", additional_properties={"user_id": "77777777-7777-7777-7777-777777777777"} ), ] @@ -654,7 +654,7 @@ async def test_protection_scopes_cached_on_first_call( scope_identifier="scope-123", scopes=[] ) - messages = [ChatMessage(role=Role.USER, text="Test")] + messages = [ChatMessage("user", ["Test"])] await processor.process_messages(messages, Activity.UPLOAD_TEXT, user_id="12345678-1234-1234-1234-123456789012") @@ -676,7 +676,7 @@ async def test_payment_required_exception_cached_at_tenant_level( mock_client.get_protection_scopes.side_effect = PurviewPaymentRequiredError("Payment required") - messages = [ChatMessage(role=Role.USER, text="Test")] + messages = [ChatMessage("user", ["Test"])] with pytest.raises(PurviewPaymentRequiredError): await processor.process_messages( diff --git a/python/packages/redis/agent_framework_redis/_chat_message_store.py b/python/packages/redis/agent_framework_redis/_chat_message_store.py index 4b50c63571..a68bc9f1d8 100644 --- a/python/packages/redis/agent_framework_redis/_chat_message_store.py +++ b/python/packages/redis/agent_framework_redis/_chat_message_store.py @@ -225,7 +225,7 @@ async def add_messages(self, messages: Sequence[ChatMessage]) -> None: Example: .. code-block:: python - messages = [ChatMessage(role="user", text="Hello"), ChatMessage(role="assistant", text="Hi there!")] + messages = [ChatMessage("user", ["Hello"]), ChatMessage("assistant", ["Hi there!"])] await store.add_messages(messages) """ if not messages: diff --git a/python/packages/redis/agent_framework_redis/_provider.py b/python/packages/redis/agent_framework_redis/_provider.py index cd8541086e..ce3090b92a 100644 --- a/python/packages/redis/agent_framework_redis/_provider.py +++ b/python/packages/redis/agent_framework_redis/_provider.py @@ -8,7 +8,7 @@ from typing import Any, Literal, cast import numpy as np -from agent_framework import ChatMessage, Context, ContextProvider, Role +from agent_framework import ChatMessage, Context, ContextProvider from agent_framework.exceptions import ( AgentException, ServiceInitializationError, @@ -503,13 +503,9 @@ async def invoked( messages: list[dict[str, Any]] = [] for message in messages_list: - if ( - message.role.value in {Role.USER.value, Role.ASSISTANT.value, Role.SYSTEM.value} - and message.text - and message.text.strip() - ): + if message.role in {"user", "assistant", "system"} and message.text and message.text.strip(): shaped: dict[str, Any] = { - "role": message.role.value, + "role": message.role, "content": message.text, "conversation_id": self._conversation_id, "message_id": message.message_id, @@ -545,7 +541,7 @@ async def invoking(self, messages: ChatMessage | MutableSequence[ChatMessage], * ) return Context( - messages=[ChatMessage(role="user", text=f"{self.context_prompt}\n{line_separated_memories}")] + messages=[ChatMessage("user", [f"{self.context_prompt}\n{line_separated_memories}"])] if line_separated_memories else None ) diff --git a/python/packages/redis/tests/test_redis_chat_message_store.py b/python/packages/redis/tests/test_redis_chat_message_store.py index a69aef1b0a..0bbb200dfe 100644 --- a/python/packages/redis/tests/test_redis_chat_message_store.py +++ b/python/packages/redis/tests/test_redis_chat_message_store.py @@ -3,7 +3,7 @@ from unittest.mock import AsyncMock, MagicMock, patch import pytest -from agent_framework import ChatMessage, Content, Role +from agent_framework import ChatMessage, Content from agent_framework_redis import RedisChatMessageStore @@ -19,9 +19,9 @@ class TestRedisChatMessageStore: def sample_messages(self): """Sample chat messages for testing.""" return [ - ChatMessage(role=Role.USER, text="Hello", message_id="msg1"), - ChatMessage(role=Role.ASSISTANT, text="Hi there!", message_id="msg2"), - ChatMessage(role=Role.USER, text="How are you?", message_id="msg3"), + ChatMessage("user", ["Hello"], message_id="msg1"), + ChatMessage("assistant", ["Hi there!"], message_id="msg2"), + ChatMessage("user", ["How are you?"], message_id="msg3"), ] @pytest.fixture @@ -250,7 +250,7 @@ async def test_add_messages_with_max_limit(self, mock_redis_client): store = RedisChatMessageStore(redis_url="redis://localhost:6379", thread_id="test123", max_messages=3) store._redis_client = mock_redis_client - message = ChatMessage(role=Role.USER, text="Test") + message = ChatMessage("user", ["Test"]) await store.add_messages([message]) # Should trim after adding to keep only last 3 messages @@ -269,8 +269,8 @@ async def test_list_messages_with_data(self, redis_store, mock_redis_client, sam """Test listing messages with data in Redis.""" # Create proper serialized messages using the actual serialization method test_messages = [ - ChatMessage(role=Role.USER, text="Hello", message_id="msg1"), - ChatMessage(role=Role.ASSISTANT, text="Hi there!", message_id="msg2"), + ChatMessage("user", ["Hello"], message_id="msg1"), + ChatMessage("assistant", ["Hi there!"], message_id="msg2"), ] serialized_messages = [redis_store._serialize_message(msg) for msg in test_messages] mock_redis_client.lrange.return_value = serialized_messages @@ -278,9 +278,9 @@ async def test_list_messages_with_data(self, redis_store, mock_redis_client, sam messages = await redis_store.list_messages() assert len(messages) == 2 - assert messages[0].role == Role.USER + assert messages[0].role == "user" assert messages[0].text == "Hello" - assert messages[1].role == Role.ASSISTANT + assert messages[1].role == "assistant" assert messages[1].text == "Hi there!" async def test_list_messages_with_initial_messages(self, sample_messages): @@ -412,7 +412,7 @@ async def test_message_serialization_with_complex_content(self): # Message with multiple content types message = ChatMessage( - role=Role.ASSISTANT, + role="assistant", contents=[Content.from_text(text="Hello"), Content.from_text(text="World")], author_name="TestBot", message_id="complex_msg", @@ -422,7 +422,7 @@ async def test_message_serialization_with_complex_content(self): serialized = store._serialize_message(message) deserialized = store._deserialize_message(serialized) - assert deserialized.role == Role.ASSISTANT + assert deserialized.role == "assistant" assert deserialized.text == "Hello World" assert deserialized.author_name == "TestBot" assert deserialized.message_id == "complex_msg" @@ -444,7 +444,7 @@ async def test_redis_connection_error_handling(self): store = RedisChatMessageStore(redis_url="redis://localhost:6379", thread_id="test123") store._redis_client = mock_client - message = ChatMessage(role=Role.USER, text="Test") + message = ChatMessage("user", ["Test"]) # Should propagate Redis connection errors with pytest.raises(Exception, match="Connection failed"): @@ -485,7 +485,7 @@ async def test_setitem(self, redis_store, mock_redis_client, sample_messages): mock_redis_client.llen.return_value = 2 mock_redis_client.lset = AsyncMock() - new_message = ChatMessage(role=Role.USER, text="Updated message") + new_message = ChatMessage("user", ["Updated message"]) await redis_store.setitem(0, new_message) mock_redis_client.lset.assert_called_once() @@ -497,13 +497,13 @@ async def test_setitem_index_error(self, redis_store, mock_redis_client): """Test setitem raises IndexError for invalid index.""" mock_redis_client.llen.return_value = 0 - new_message = ChatMessage(role=Role.USER, text="Test") + new_message = ChatMessage("user", ["Test"]) with pytest.raises(IndexError): await redis_store.setitem(0, new_message) async def test_append(self, redis_store, mock_redis_client): """Test append method delegates to add_messages.""" - message = ChatMessage(role=Role.USER, text="Appended message") + message = ChatMessage("user", ["Appended message"]) await redis_store.append(message) # Should call pipeline operations via add_messages diff --git a/python/packages/redis/tests/test_redis_provider.py b/python/packages/redis/tests/test_redis_provider.py index 723334741b..e5db9d25fd 100644 --- a/python/packages/redis/tests/test_redis_provider.py +++ b/python/packages/redis/tests/test_redis_provider.py @@ -5,7 +5,7 @@ import numpy as np import pytest -from agent_framework import ChatMessage, Role +from agent_framework import ChatMessage from agent_framework.exceptions import AgentException, ServiceInitializationError from redisvl.utils.vectorize import CustomTextVectorizer @@ -115,16 +115,16 @@ class TestRedisProviderMessages: @pytest.fixture def sample_messages(self) -> list[ChatMessage]: return [ - ChatMessage(role=Role.USER, text="Hello, how are you?"), - ChatMessage(role=Role.ASSISTANT, text="I'm doing well, thank you!"), - ChatMessage(role=Role.SYSTEM, text="You are a helpful assistant"), + ChatMessage("user", ["Hello, how are you?"]), + ChatMessage("assistant", ["I'm doing well, thank you!"]), + ChatMessage("system", ["You are a helpful assistant"]), ] # Writes require at least one scoping filter to avoid unbounded operations async def test_messages_adding_requires_filters(self, patch_index_from_dict): # noqa: ARG002 provider = RedisProvider() with pytest.raises(ServiceInitializationError): - await provider.invoked("thread123", ChatMessage(role=Role.USER, text="Hello")) + await provider.invoked("thread123", ChatMessage("user", ["Hello"])) # Captures the per-operation thread id when provided async def test_thread_created_sets_per_operation_id(self, patch_index_from_dict): # noqa: ARG002 @@ -157,7 +157,7 @@ class TestRedisProviderModelInvoking: async def test_model_invoking_requires_filters(self, patch_index_from_dict): # noqa: ARG002 provider = RedisProvider() with pytest.raises(ServiceInitializationError): - await provider.invoking(ChatMessage(role=Role.USER, text="Hi")) + await provider.invoking(ChatMessage("user", ["Hi"])) # Ensures text-only search path is used and context is composed from hits async def test_textquery_path_and_context_contents( @@ -168,7 +168,7 @@ async def test_textquery_path_and_context_contents( provider = RedisProvider(user_id="u1") # Act - ctx = await provider.invoking([ChatMessage(role=Role.USER, text="q1")]) + ctx = await provider.invoking([ChatMessage("user", ["q1"])]) # Assert: TextQuery used (not HybridQuery), filter_expression included assert patch_queries["TextQuery"].call_count == 1 @@ -190,7 +190,7 @@ async def test_model_invoking_empty_results_returns_empty_context( ): # noqa: ARG002 mock_index.query = AsyncMock(return_value=[]) provider = RedisProvider(user_id="u1") - ctx = await provider.invoking([ChatMessage(role=Role.USER, text="any")]) + ctx = await provider.invoking([ChatMessage("user", ["any"])]) assert ctx.messages == [] # Ensures hybrid vector-text search is used when a vectorizer and vector field are configured @@ -198,7 +198,7 @@ async def test_hybridquery_path_with_vectorizer(self, mock_index: AsyncMock, pat mock_index.query = AsyncMock(return_value=[{"content": "Hit"}]) provider = RedisProvider(user_id="u1", redis_vectorizer=CUSTOM_VECTORIZER, vector_field_name="vec") - ctx = await provider.invoking([ChatMessage(role=Role.USER, text="hello")]) + ctx = await provider.invoking([ChatMessage("user", ["hello"])]) # Assert: HybridQuery used with vector and vector field assert patch_queries["HybridQuery"].call_count == 1 @@ -240,9 +240,9 @@ async def test_messages_adding_adds_partition_defaults_and_roles( ) msgs = [ - ChatMessage(role=Role.USER, text="u"), - ChatMessage(role=Role.ASSISTANT, text="a"), - ChatMessage(role=Role.SYSTEM, text="s"), + ChatMessage("user", ["u"]), + ChatMessage("assistant", ["a"]), + ChatMessage("system", ["s"]), ] await provider.invoked(msgs) @@ -265,8 +265,8 @@ async def test_messages_adding_ignores_blank_and_disallowed_roles( ): # noqa: ARG002 provider = RedisProvider(user_id="u1", scope_to_per_operation_thread_id=True) msgs = [ - ChatMessage(role=Role.USER, text=" "), - ChatMessage(role=Role.TOOL, text="tool output"), + ChatMessage("user", [" "]), + ChatMessage("tool", ["tool output"]), ] await provider.invoked(msgs) # No valid messages -> no load @@ -279,8 +279,8 @@ async def test_messages_adding_triggers_index_create_once_when_drop_true( self, mock_index: AsyncMock, patch_index_from_dict ): # noqa: ARG002 provider = RedisProvider(user_id="u1") - await provider.invoked(ChatMessage(role=Role.USER, text="m1")) - await provider.invoked(ChatMessage(role=Role.USER, text="m2")) + await provider.invoked(ChatMessage("user", ["m1"])) + await provider.invoked(ChatMessage("user", ["m2"])) # create only on first call assert mock_index.create.await_count == 1 @@ -291,7 +291,7 @@ async def test_model_invoking_triggers_create_when_drop_false_and_not_exists( mock_index.exists = AsyncMock(return_value=False) provider = RedisProvider(user_id="u1") mock_index.query = AsyncMock(return_value=[{"content": "C"}]) - await provider.invoking([ChatMessage(role=Role.USER, text="q")]) + await provider.invoking([ChatMessage("user", ["q"])]) assert mock_index.create.await_count == 1 @@ -321,7 +321,7 @@ async def test_messages_adding_populates_vector_field_when_vectorizer_present( vector_field_name="vec", ) - await provider.invoked(ChatMessage(role=Role.USER, text="hello")) + await provider.invoked(ChatMessage("user", ["hello"])) assert mock_index.load.await_count == 1 (loaded_args, _kwargs) = mock_index.load.call_args docs = loaded_args[0] diff --git a/python/samples/autogen-migration/orchestrations/01_round_robin_group_chat.py b/python/samples/autogen-migration/orchestrations/01_round_robin_group_chat.py index 39d360b1e1..38df1424db 100644 --- a/python/samples/autogen-migration/orchestrations/01_round_robin_group_chat.py +++ b/python/samples/autogen-migration/orchestrations/01_round_robin_group_chat.py @@ -103,7 +103,6 @@ async def run_agent_framework_with_cycle() -> None: WorkflowContext, WorkflowOutputEvent, executor, - tool, ) from agent_framework.openai import OpenAIChatClient diff --git a/python/samples/autogen-migration/orchestrations/03_swarm.py b/python/samples/autogen-migration/orchestrations/03_swarm.py index 3fa9f7a04d..09d8ac0486 100644 --- a/python/samples/autogen-migration/orchestrations/03_swarm.py +++ b/python/samples/autogen-migration/orchestrations/03_swarm.py @@ -102,7 +102,6 @@ async def run_agent_framework() -> None: RequestInfoEvent, WorkflowRunState, WorkflowStatusEvent, - tool, ) from agent_framework.openai import OpenAIChatClient @@ -142,7 +141,7 @@ async def run_agent_framework() -> None: ) .set_coordinator(triage_agent) .add_handoff(triage_agent, [billing_agent, tech_support]) - .with_termination_condition(lambda conv: sum(1 for msg in conv if msg.role.value == "user") > 3) + .with_termination_condition(lambda conv: sum(1 for msg in conv if msg.role == "user") > 3) .build() ) diff --git a/python/samples/demos/chatkit-integration/app.py b/python/samples/demos/chatkit-integration/app.py index 4e11e4948c..11b3140769 100644 --- a/python/samples/demos/chatkit-integration/app.py +++ b/python/samples/demos/chatkit-integration/app.py @@ -18,8 +18,7 @@ import uvicorn # Agent Framework imports -from agent_framework import AgentResponseUpdate, ChatAgent, ChatMessage, FunctionResultContent, Role -from agent_framework import tool +from agent_framework import AgentResponseUpdate, ChatAgent, ChatMessage, FunctionResultContent, tool from agent_framework.azure import AzureOpenAIChatClient # Agent Framework ChatKit integration @@ -131,6 +130,7 @@ async def stream_widget( yield ThreadItemDoneEvent(type="thread.item.done", item=widget_item) + # NOTE: approval_mode="never_require" is for sample brevity. Use "always_require" in production; see samples/getting_started/tools/function_tool_with_approval.py and samples/getting_started/tools/function_tool_with_approval_and_threads.py. @tool(approval_mode="never_require") def get_weather( @@ -170,6 +170,7 @@ def get_weather( ) return WeatherResponse(text, weather_data) + @tool(approval_mode="never_require") def get_time() -> str: """Get the current UTC time.""" @@ -177,6 +178,7 @@ def get_time() -> str: logger.info("Getting current UTC time") return f"Current UTC time: {current_time.strftime('%Y-%m-%d %H:%M:%S')} UTC" + @tool(approval_mode="never_require") def show_city_selector() -> str: """Show an interactive city selector widget to the user. @@ -279,7 +281,7 @@ async def _update_thread_title( title_prompt = [ ChatMessage( - role=Role.USER, + role="user", text=( f"Generate a very short, concise title (max 40 characters) for a conversation " f"that starts with:\n\n{conversation_context}\n\n" @@ -456,7 +458,7 @@ async def action( weather_data: WeatherData | None = None # Create an agent message asking about the weather - agent_messages = [ChatMessage(role=Role.USER, text=f"What's the weather in {city_label}?")] + agent_messages = [ChatMessage("user", [f"What's the weather in {city_label}?"])] logger.debug(f"Processing weather query: {agent_messages[0].text}") diff --git a/python/samples/demos/hosted_agents/agent_with_text_search_rag/main.py b/python/samples/demos/hosted_agents/agent_with_text_search_rag/main.py index 2d99eac9f4..0c0660ceb0 100644 --- a/python/samples/demos/hosted_agents/agent_with_text_search_rag/main.py +++ b/python/samples/demos/hosted_agents/agent_with_text_search_rag/main.py @@ -6,7 +6,7 @@ from dataclasses import dataclass from typing import Any -from agent_framework import ChatMessage, Context, ContextProvider, Role +from agent_framework import ChatMessage, Context, ContextProvider from agent_framework.azure import AzureOpenAIChatClient from azure.ai.agentserver.agentframework import from_agent_framework # pyright: ignore[reportUnknownVariableType] from azure.identity import DefaultAzureCredential @@ -85,7 +85,7 @@ async def invoking(self, messages: ChatMessage | MutableSequence[ChatMessage], * return Context( messages=[ ChatMessage( - role=Role.USER, text="\n\n".join(json.dumps(result.__dict__, indent=2) for result in results) + role="user", text="\n\n".join(json.dumps(result.__dict__, indent=2) for result in results) ) ] ) diff --git a/python/samples/demos/m365-agent/m365_agent_demo/app.py b/python/samples/demos/m365-agent/m365_agent_demo/app.py index 9e11780614..3aa7382811 100644 --- a/python/samples/demos/m365-agent/m365_agent_demo/app.py +++ b/python/samples/demos/m365-agent/m365_agent_demo/app.py @@ -16,8 +16,7 @@ from random import randint from typing import Annotated -from agent_framework import ChatAgent -from agent_framework import tool +from agent_framework import ChatAgent, tool from agent_framework.openai import OpenAIChatClient from aiohttp import web from aiohttp.web_middlewares import middleware @@ -77,6 +76,7 @@ def load_app_config() -> AppConfig: port = 3978 return AppConfig(use_anonymous_mode=use_anonymous_mode, port=port, agents_sdk_config=agents_sdk_config) + # NOTE: approval_mode="never_require" is for sample brevity. Use "always_require" in production; see samples/getting_started/tools/function_tool_with_approval.py and samples/getting_started/tools/function_tool_with_approval_and_threads.py. @tool(approval_mode="never_require") def get_weather( diff --git a/python/samples/demos/workflow_evaluation/_tools.py b/python/samples/demos/workflow_evaluation/_tools.py index 12be0f4094..0e5443d5b0 100644 --- a/python/samples/demos/workflow_evaluation/_tools.py +++ b/python/samples/demos/workflow_evaluation/_tools.py @@ -70,7 +70,7 @@ def search_hotels( "availability": "Available" } ] - + return json.dumps({ "location": location, "check_in": check_in, @@ -140,7 +140,7 @@ def get_hotel_details( "nearby_attractions": ["Eiffel Tower (0.2 mi)", "Seine River Cruise Dock (0.3 mi)", "Trocadéro (0.5 mi)"] } } - + details = hotel_details.get(hotel_name, { "name": hotel_name, "description": "Comfortable hotel with modern amenities", @@ -150,7 +150,7 @@ def get_hotel_details( "reviews": {"total": 0, "recent_comments": []}, "nearby_attractions": [] }) - + return json.dumps({ "hotel_name": hotel_name, "details": details @@ -270,7 +270,7 @@ def search_flights( "stops": "Nonstop" } ] - + return json.dumps({ "origin": origin, "destination": destination, @@ -317,7 +317,7 @@ def get_flight_details( }, "amenities": ["WiFi", "In-flight entertainment", "Meals included"] } - + return json.dumps({ "flight_details": mock_details }) @@ -439,7 +439,7 @@ def search_activities( "booking_required": False } ] - + if category: activities = [act for act in all_activities if act["category"] == category] else: @@ -456,7 +456,7 @@ def search_activities( "availability": "Daily at 10:00 AM and 2:00 PM" } ] - + return json.dumps({ "location": location, "date": date, @@ -523,7 +523,7 @@ def get_activity_details( "reviews_count": 2341 } } - + details = activity_details_map.get(activity_name, { "name": activity_name, "description": "An immersive experience that showcases the best of local culture and attractions.", @@ -538,7 +538,7 @@ def get_activity_details( "rating": 4.5, "reviews_count": 100 }) - + return json.dumps({ "activity_details": details }) @@ -558,7 +558,7 @@ def confirm_booking( booking status, customer information, and next steps. """ confirmation_number = f"CONF-{booking_type.upper()}-{booking_id}" - + confirmation_data = { "confirmation_number": confirmation_number, "booking_type": booking_type, @@ -572,7 +572,7 @@ def confirm_booking( "Bring confirmation number and valid ID" ] } - + return json.dumps({ "confirmation": confirmation_data }) @@ -595,7 +595,7 @@ def check_hotel_availability( and last checked timestamp. """ availability_status = "Available" - + availability_data = { "service_type": "hotel", "hotel_name": hotel_name, @@ -607,7 +607,7 @@ def check_hotel_availability( "price_per_night": "$185", "last_checked": datetime.now().isoformat() } - + return json.dumps({ "availability": availability_data }) @@ -629,7 +629,7 @@ def check_flight_availability( and last checked timestamp. """ availability_status = "Available" - + availability_data = { "service_type": "flight", "flight_number": flight_number, @@ -640,7 +640,7 @@ def check_flight_availability( "price_per_passenger": "$520", "last_checked": datetime.now().isoformat() } - + return json.dumps({ "availability": availability_data }) @@ -662,7 +662,7 @@ def check_activity_availability( and last checked timestamp. """ availability_status = "Available" - + availability_data = { "service_type": "activity", "activity_name": activity_name, @@ -673,7 +673,7 @@ def check_activity_availability( "price_per_person": "$45", "last_checked": datetime.now().isoformat() } - + return json.dumps({ "availability": availability_data }) @@ -694,7 +694,7 @@ def process_payment( payment method details, and receipt URL. """ transaction_id = f"TXN-{datetime.now().strftime('%Y%m%d%H%M%S')}" - + payment_result = { "transaction_id": transaction_id, "amount": amount, @@ -706,13 +706,12 @@ def process_payment( "timestamp": datetime.now().isoformat(), "receipt_url": f"https://payments.travelagency.com/receipt/{transaction_id}" } - + return json.dumps({ "payment_result": payment_result }) - # Mock payment validation tool @tool(name="validate_payment_method", description="Validate a payment method before processing.") def validate_payment_method( @@ -725,11 +724,11 @@ def validate_payment_method( validation messages, supported currencies, and processing fee information. """ method_type = payment_method.get("type", "credit_card") - + # Validation logic is_valid = True validation_messages = [] - + if method_type == "credit_card": if not payment_method.get("number"): is_valid = False @@ -740,7 +739,7 @@ def validate_payment_method( if not payment_method.get("cvv"): is_valid = False validation_messages.append("CVV is required") - + validation_result = { "is_valid": is_valid, "payment_method_type": method_type, @@ -748,7 +747,7 @@ def validate_payment_method( "supported_currencies": ["USD", "EUR", "GBP", "JPY"], "processing_fee": "2.5%" } - + return json.dumps({ "validation_result": validation_result }) diff --git a/python/samples/demos/workflow_evaluation/create_workflow.py b/python/samples/demos/workflow_evaluation/create_workflow.py index dc1e920b69..665be0667e 100644 --- a/python/samples/demos/workflow_evaluation/create_workflow.py +++ b/python/samples/demos/workflow_evaluation/create_workflow.py @@ -51,13 +51,11 @@ AgentRunUpdateEvent, ChatMessage, Executor, - Role, WorkflowBuilder, WorkflowContext, WorkflowOutputEvent, executor, handler, - tool, ) from agent_framework.azure import AzureAIClient from azure.ai.projects.aio import AIProjectClient @@ -71,7 +69,7 @@ @executor(id="start_executor") async def start_executor(input: str, ctx: WorkflowContext[list[ChatMessage]]) -> None: """Initiates the workflow by sending the user query to all specialized agents.""" - await ctx.send_message([ChatMessage(role="user", text=input)]) + await ctx.send_message([ChatMessage("user", [input])]) class ResearchLead(Executor): @@ -107,11 +105,11 @@ async def fan_in_handle(self, responses: list[AgentExecutorResponse], ctx: Workf # Generate comprehensive travel plan summary messages = [ ChatMessage( - role=Role.SYSTEM, + role="system", text="You are a travel planning coordinator. Summarize findings from multiple specialized travel agents and provide a clear, comprehensive travel plan based on the user's query.", ), ChatMessage( - role=Role.USER, + role="user", text=f"Original query: {user_query}\n\nFindings from specialized travel agents:\n{summary_text}\n\nPlease provide a comprehensive travel plan based on these findings.", ), ] @@ -136,7 +134,7 @@ def _extract_agent_findings(self, responses: list[AgentExecutorResponse]) -> lis findings = [] if response.agent_response and response.agent_response.messages: for msg in response.agent_response.messages: - if msg.role == Role.ASSISTANT and msg.text and msg.text.strip(): + if msg.role == "assistant" and msg.text and msg.text.strip(): findings.append(msg.text.strip()) if findings: diff --git a/python/samples/demos/workflow_evaluation/run_evaluation.py b/python/samples/demos/workflow_evaluation/run_evaluation.py index 610f7ade00..defcde114f 100644 --- a/python/samples/demos/workflow_evaluation/run_evaluation.py +++ b/python/samples/demos/workflow_evaluation/run_evaluation.py @@ -16,16 +16,15 @@ from azure.ai.projects import AIProjectClient from azure.identity import DefaultAzureCredential -from dotenv import load_dotenv - from create_workflow import create_and_run_workflow +from dotenv import load_dotenv def print_section(title: str): """Print a formatted section header.""" - print(f"\n{'='*80}") + print(f"\n{'=' * 80}") print(f"{title}") - print(f"{'='*80}") + print(f"{'=' * 80}") async def run_workflow(): @@ -37,9 +36,9 @@ async def run_workflow(): print_section("Step 1: Running Workflow") print("Executing multi-agent travel planning workflow...") print("This may take a few minutes...") - + workflow_data = await create_and_run_workflow() - + print("Workflow execution completed") return workflow_data @@ -47,31 +46,31 @@ async def run_workflow(): def display_response_summary(workflow_data: dict): """Display summary of response data.""" print_section("Step 2: Response Data Summary") - + print(f"Query: {workflow_data['query']}") print(f"\nAgents tracked: {len(workflow_data['agents'])}") - - for agent_name, agent_data in workflow_data['agents'].items(): - response_count = agent_data['response_count'] + + for agent_name, agent_data in workflow_data["agents"].items(): + response_count = agent_data["response_count"] print(f" {agent_name}: {response_count} response(s)") def fetch_agent_responses(openai_client, workflow_data: dict, agent_names: list): """Fetch and display final responses from specified agents.""" print_section("Step 3: Fetching Agent Responses") - + for agent_name in agent_names: - if agent_name not in workflow_data['agents']: + if agent_name not in workflow_data["agents"]: continue - - agent_data = workflow_data['agents'][agent_name] - if not agent_data['response_ids']: + + agent_data = workflow_data["agents"][agent_name] + if not agent_data["response_ids"]: continue - - final_response_id = agent_data['response_ids'][-1] + + final_response_id = agent_data["response_ids"][-1] print(f"\n{agent_name}") print(f" Response ID: {final_response_id}") - + try: response = openai_client.responses.retrieve(response_id=final_response_id) content = response.output[-1].content[-1].text @@ -84,9 +83,9 @@ def fetch_agent_responses(openai_client, workflow_data: dict, agent_names: list) def create_evaluation(openai_client, model_deployment: str): """Create evaluation with multiple evaluators.""" print_section("Step 4: Creating Evaluation") - + data_source_config = {"type": "azure_ai_source", "scenario": "responses"} - + testing_criteria = [ { "type": "azure_ai_evaluator", @@ -113,33 +112,33 @@ def create_evaluation(openai_client, model_deployment: str): "initialization_parameters": {"deployment_name": model_deployment} }, ] - + eval_object = openai_client.evals.create( name="Travel Workflow Multi-Evaluator Assessment", data_source_config=data_source_config, testing_criteria=testing_criteria, ) - + evaluator_names = [criterion["name"] for criterion in testing_criteria] print(f"Evaluation created: {eval_object.id}") print(f"Evaluators ({len(evaluator_names)}): {', '.join(evaluator_names)}") - + return eval_object def run_evaluation(openai_client, eval_object, workflow_data: dict, agent_names: list): """Run evaluation on selected agent responses.""" print_section("Step 5: Running Evaluation") - + selected_response_ids = [] for agent_name in agent_names: - if agent_name in workflow_data['agents']: - agent_data = workflow_data['agents'][agent_name] - if agent_data['response_ids']: - selected_response_ids.append(agent_data['response_ids'][-1]) - + if agent_name in workflow_data["agents"]: + agent_data = workflow_data["agents"][agent_name] + if agent_data["response_ids"]: + selected_response_ids.append(agent_data["response_ids"][-1]) + print(f"Selected {len(selected_response_ids)} responses for evaluation") - + data_source = { "type": "azure_ai_responses", "item_generation_params": { @@ -151,24 +150,24 @@ def run_evaluation(openai_client, eval_object, workflow_data: dict, agent_names: }, }, } - + eval_run = openai_client.evals.runs.create( eval_id=eval_object.id, name="Multi-Agent Response Evaluation", data_source=data_source ) - + print(f"Evaluation run created: {eval_run.id}") - + return eval_run def monitor_evaluation(openai_client, eval_object, eval_run): """Monitor evaluation progress and display results.""" print_section("Step 6: Monitoring Evaluation") - + print("Waiting for evaluation to complete...") - + while eval_run.status not in ["completed", "failed"]: eval_run = openai_client.evals.runs.retrieve( run_id=eval_run.id, @@ -176,7 +175,7 @@ def monitor_evaluation(openai_client, eval_object, eval_run): ) print(f"Status: {eval_run.status}") time.sleep(5) - + if eval_run.status == "completed": print("\nEvaluation completed successfully") print(f"Result counts: {eval_run.result_counts}") @@ -188,31 +187,31 @@ def monitor_evaluation(openai_client, eval_object, eval_run): async def main(): """Main execution flow.""" load_dotenv() - + print("Travel Planning Workflow Evaluation") - + workflow_data = await run_workflow() - + display_response_summary(workflow_data) - + project_client = AIProjectClient( endpoint=os.environ["AZURE_AI_PROJECT_ENDPOINT"], credential=DefaultAzureCredential(), api_version="2025-11-15-preview" ) openai_client = project_client.get_openai_client() - + agents_to_evaluate = ["hotel-search-agent", "flight-search-agent", "activity-search-agent"] - + fetch_agent_responses(openai_client, workflow_data, agents_to_evaluate) - + model_deployment = os.environ.get("AZURE_AI_MODEL_DEPLOYMENT_NAME", "gpt-4o-mini") eval_object = create_evaluation(openai_client, model_deployment) - + eval_run = run_evaluation(openai_client, eval_object, workflow_data, agents_to_evaluate) - + monitor_evaluation(openai_client, eval_object, eval_run) - + print_section("Complete") diff --git a/python/samples/getting_started/agents/anthropic/anthropic_basic.py b/python/samples/getting_started/agents/anthropic/anthropic_basic.py index 41fbb3b7e6..18a49d5e88 100644 --- a/python/samples/getting_started/agents/anthropic/anthropic_basic.py +++ b/python/samples/getting_started/agents/anthropic/anthropic_basic.py @@ -4,8 +4,8 @@ from random import randint from typing import Annotated -from agent_framework.anthropic import AnthropicClient from agent_framework import tool +from agent_framework.anthropic import AnthropicClient """ Anthropic Chat Agent Example @@ -13,6 +13,7 @@ This sample demonstrates using Anthropic with an agent and a single custom tool. """ + # NOTE: approval_mode="never_require" is for sample brevity. Use "always_require" in production; see samples/getting_started/tools/function_tool_with_approval.py and samples/getting_started/tools/function_tool_with_approval_and_threads.py. @tool(approval_mode="never_require") def get_weather( diff --git a/python/samples/getting_started/agents/azure_ai/azure_ai_basic.py b/python/samples/getting_started/agents/azure_ai/azure_ai_basic.py index f6bf9802e0..77465c3c52 100644 --- a/python/samples/getting_started/agents/azure_ai/azure_ai_basic.py +++ b/python/samples/getting_started/agents/azure_ai/azure_ai_basic.py @@ -4,10 +4,10 @@ from random import randint from typing import Annotated +from agent_framework import tool from agent_framework.azure import AzureAIProjectAgentProvider from azure.identity.aio import AzureCliCredential from pydantic import Field -from agent_framework import tool """ Azure AI Agent Basic Example @@ -16,6 +16,7 @@ Shows both streaming and non-streaming responses with function tools. """ + # NOTE: approval_mode="never_require" is for sample brevity. Use "always_require" in production; see samples/getting_started/tools/function_tool_with_approval.py and samples/getting_started/tools/function_tool_with_approval_and_threads.py. @tool(approval_mode="never_require") def get_weather( diff --git a/python/samples/getting_started/agents/azure_ai/azure_ai_provider_methods.py b/python/samples/getting_started/agents/azure_ai/azure_ai_provider_methods.py index 266cfbdfdd..b05ec92f80 100644 --- a/python/samples/getting_started/agents/azure_ai/azure_ai_provider_methods.py +++ b/python/samples/getting_started/agents/azure_ai/azure_ai_provider_methods.py @@ -5,12 +5,12 @@ from random import randint from typing import Annotated +from agent_framework import tool from agent_framework.azure import AzureAIProjectAgentProvider from azure.ai.projects.aio import AIProjectClient from azure.ai.projects.models import AgentReference, PromptAgentDefinition from azure.identity.aio import AzureCliCredential from pydantic import Field -from agent_framework import tool """ Azure AI Project Agent Provider Methods Example @@ -26,6 +26,7 @@ Each method returns a ChatAgent that can be used for conversations. """ + # NOTE: approval_mode="never_require" is for sample brevity. Use "always_require" in production; see samples/getting_started/tools/function_tool_with_approval.py and samples/getting_started/tools/function_tool_with_approval_and_threads.py. @tool(approval_mode="never_require") def get_weather( diff --git a/python/samples/getting_started/agents/azure_ai/azure_ai_use_latest_version.py b/python/samples/getting_started/agents/azure_ai/azure_ai_use_latest_version.py index 7106bb1f31..b9472c9f1a 100644 --- a/python/samples/getting_started/agents/azure_ai/azure_ai_use_latest_version.py +++ b/python/samples/getting_started/agents/azure_ai/azure_ai_use_latest_version.py @@ -4,10 +4,10 @@ from random import randint from typing import Annotated +from agent_framework import tool from agent_framework.azure import AzureAIProjectAgentProvider from azure.identity.aio import AzureCliCredential from pydantic import Field -from agent_framework import tool """ Azure AI Agent Latest Version Example @@ -17,6 +17,7 @@ while subsequent calls with `get_agent()` reuse the latest agent version. """ + # NOTE: approval_mode="never_require" is for sample brevity. Use "always_require" in production; see samples/getting_started/tools/function_tool_with_approval.py and samples/getting_started/tools/function_tool_with_approval_and_threads.py. @tool(approval_mode="never_require") def get_weather( diff --git a/python/samples/getting_started/agents/azure_ai/azure_ai_with_code_interpreter_file_generation.py b/python/samples/getting_started/agents/azure_ai/azure_ai_with_code_interpreter_file_generation.py index 9e61d2486c..3e2b520ede 100644 --- a/python/samples/getting_started/agents/azure_ai/azure_ai_with_code_interpreter_file_generation.py +++ b/python/samples/getting_started/agents/azure_ai/azure_ai_with_code_interpreter_file_generation.py @@ -5,7 +5,6 @@ from agent_framework import ( AgentResponseUpdate, HostedCodeInterpreterTool, - tool, ) from agent_framework.azure import AzureAIProjectAgentProvider from azure.identity.aio import AzureCliCredential diff --git a/python/samples/getting_started/agents/azure_ai/azure_ai_with_existing_conversation.py b/python/samples/getting_started/agents/azure_ai/azure_ai_with_existing_conversation.py index 8438abcf67..0410c00bd7 100644 --- a/python/samples/getting_started/agents/azure_ai/azure_ai_with_existing_conversation.py +++ b/python/samples/getting_started/agents/azure_ai/azure_ai_with_existing_conversation.py @@ -4,11 +4,11 @@ from random import randint from typing import Annotated +from agent_framework import tool from agent_framework.azure import AzureAIProjectAgentProvider from azure.ai.projects.aio import AIProjectClient from azure.identity.aio import AzureCliCredential from pydantic import Field -from agent_framework import tool """ Azure AI Agent Existing Conversation Example @@ -16,6 +16,7 @@ This sample demonstrates usage of AzureAIProjectAgentProvider with existing conversation created on service side. """ + # NOTE: approval_mode="never_require" is for sample brevity. Use "always_require" in production; see samples/getting_started/tools/function_tool_with_approval.py and samples/getting_started/tools/function_tool_with_approval_and_threads.py. @tool(approval_mode="never_require") def get_weather( diff --git a/python/samples/getting_started/agents/azure_ai/azure_ai_with_explicit_settings.py b/python/samples/getting_started/agents/azure_ai/azure_ai_with_explicit_settings.py index ba131817d1..382205b7cc 100644 --- a/python/samples/getting_started/agents/azure_ai/azure_ai_with_explicit_settings.py +++ b/python/samples/getting_started/agents/azure_ai/azure_ai_with_explicit_settings.py @@ -5,10 +5,10 @@ from random import randint from typing import Annotated +from agent_framework import tool from agent_framework.azure import AzureAIProjectAgentProvider from azure.identity.aio import AzureCliCredential from pydantic import Field -from agent_framework import tool """ Azure AI Agent with Explicit Settings Example @@ -17,6 +17,7 @@ settings rather than relying on environment variable defaults. """ + # NOTE: approval_mode="never_require" is for sample brevity. Use "always_require" in production; see samples/getting_started/tools/function_tool_with_approval.py and samples/getting_started/tools/function_tool_with_approval_and_threads.py. @tool(approval_mode="never_require") def get_weather( diff --git a/python/samples/getting_started/agents/azure_ai/azure_ai_with_hosted_mcp.py b/python/samples/getting_started/agents/azure_ai/azure_ai_with_hosted_mcp.py index 76394a8aac..9262240088 100644 --- a/python/samples/getting_started/agents/azure_ai/azure_ai_with_hosted_mcp.py +++ b/python/samples/getting_started/agents/azure_ai/azure_ai_with_hosted_mcp.py @@ -25,10 +25,10 @@ async def handle_approvals_without_thread(query: str, agent: "AgentProtocol") -> f"User Input Request for function from {agent.name}: {user_input_needed.function_call.name}" f" with arguments: {user_input_needed.function_call.arguments}" ) - new_inputs.append(ChatMessage(role="assistant", contents=[user_input_needed])) + new_inputs.append(ChatMessage("assistant", [user_input_needed])) user_approval = input("Approve function call? (y/n): ") new_inputs.append( - ChatMessage(role="user", contents=[user_input_needed.to_function_approval_response(user_approval.lower() == "y")]) + ChatMessage("user", [user_input_needed.to_function_approval_response(user_approval.lower() == "y")]) ) result = await agent.run(new_inputs, store=False) diff --git a/python/samples/getting_started/agents/azure_ai/azure_ai_with_response_format.py b/python/samples/getting_started/agents/azure_ai/azure_ai_with_response_format.py index a0af51da6a..39ea0b722c 100644 --- a/python/samples/getting_started/agents/azure_ai/azure_ai_with_response_format.py +++ b/python/samples/getting_started/agents/azure_ai/azure_ai_with_response_format.py @@ -41,12 +41,13 @@ async def main() -> None: print(f"User: {query}") result = await agent.run(query) - if release_brief := result.try_parse_value(ReleaseBrief): + try: + release_brief = result.value print("Agent:") print(f"Feature: {release_brief.feature}") print(f"Benefit: {release_brief.benefit}") print(f"Launch date: {release_brief.launch_date}") - else: + except Exception: print(f"Failed to parse response: {result.text}") diff --git a/python/samples/getting_started/agents/azure_ai_agent/azure_ai_basic.py b/python/samples/getting_started/agents/azure_ai_agent/azure_ai_basic.py index 787b1f317b..e06232cf56 100644 --- a/python/samples/getting_started/agents/azure_ai_agent/azure_ai_basic.py +++ b/python/samples/getting_started/agents/azure_ai_agent/azure_ai_basic.py @@ -4,10 +4,10 @@ from random import randint from typing import Annotated +from agent_framework import tool from agent_framework.azure import AzureAIAgentsProvider from azure.identity.aio import AzureCliCredential from pydantic import Field -from agent_framework import tool """ Azure AI Agent Basic Example @@ -16,6 +16,7 @@ lifecycle management. Shows both streaming and non-streaming responses with function tools. """ + # NOTE: approval_mode="never_require" is for sample brevity. Use "always_require" in production; see samples/getting_started/tools/function_tool_with_approval.py and samples/getting_started/tools/function_tool_with_approval_and_threads.py. @tool(approval_mode="never_require") def get_weather( diff --git a/python/samples/getting_started/agents/azure_ai_agent/azure_ai_provider_methods.py b/python/samples/getting_started/agents/azure_ai_agent/azure_ai_provider_methods.py index adb6386797..5dd06f16f0 100644 --- a/python/samples/getting_started/agents/azure_ai_agent/azure_ai_provider_methods.py +++ b/python/samples/getting_started/agents/azure_ai_agent/azure_ai_provider_methods.py @@ -5,11 +5,11 @@ from random import randint from typing import Annotated +from agent_framework import tool from agent_framework.azure import AzureAIAgentsProvider from azure.ai.agents.aio import AgentsClient from azure.identity.aio import AzureCliCredential from pydantic import Field -from agent_framework import tool """ Azure AI Agent Provider Methods Example @@ -20,6 +20,7 @@ - as_agent(): Wrap an SDK Agent object without making HTTP calls """ + # NOTE: approval_mode="never_require" is for sample brevity. Use "always_require" in production; see samples/getting_started/tools/function_tool_with_approval.py and samples/getting_started/tools/function_tool_with_approval_and_threads.py. @tool(approval_mode="never_require") def get_weather( diff --git a/python/samples/getting_started/agents/azure_ai_agent/azure_ai_with_code_interpreter_file_generation.py b/python/samples/getting_started/agents/azure_ai_agent/azure_ai_with_code_interpreter_file_generation.py index 44554af05a..665c707adc 100644 --- a/python/samples/getting_started/agents/azure_ai_agent/azure_ai_with_code_interpreter_file_generation.py +++ b/python/samples/getting_started/agents/azure_ai_agent/azure_ai_with_code_interpreter_file_generation.py @@ -7,7 +7,6 @@ AgentResponseUpdate, HostedCodeInterpreterTool, HostedFileContent, - tool, ) from agent_framework.azure import AzureAIAgentsProvider from azure.ai.agents.aio import AgentsClient diff --git a/python/samples/getting_started/agents/azure_ai_agent/azure_ai_with_existing_thread.py b/python/samples/getting_started/agents/azure_ai_agent/azure_ai_with_existing_thread.py index 4852ba15b7..0f17d35183 100644 --- a/python/samples/getting_started/agents/azure_ai_agent/azure_ai_with_existing_thread.py +++ b/python/samples/getting_started/agents/azure_ai_agent/azure_ai_with_existing_thread.py @@ -5,11 +5,11 @@ from random import randint from typing import Annotated +from agent_framework import tool from agent_framework.azure import AzureAIAgentsProvider from azure.ai.agents.aio import AgentsClient from azure.identity.aio import AzureCliCredential from pydantic import Field -from agent_framework import tool """ Azure AI Agent with Existing Thread Example @@ -18,6 +18,7 @@ by providing thread IDs for thread reuse patterns. """ + # NOTE: approval_mode="never_require" is for sample brevity. Use "always_require" in production; see samples/getting_started/tools/function_tool_with_approval.py and samples/getting_started/tools/function_tool_with_approval_and_threads.py. @tool(approval_mode="never_require") def get_weather( diff --git a/python/samples/getting_started/agents/azure_ai_agent/azure_ai_with_explicit_settings.py b/python/samples/getting_started/agents/azure_ai_agent/azure_ai_with_explicit_settings.py index 85b4d55b95..05c8c60a36 100644 --- a/python/samples/getting_started/agents/azure_ai_agent/azure_ai_with_explicit_settings.py +++ b/python/samples/getting_started/agents/azure_ai_agent/azure_ai_with_explicit_settings.py @@ -5,10 +5,10 @@ from random import randint from typing import Annotated +from agent_framework import tool from agent_framework.azure import AzureAIAgentsProvider from azure.identity.aio import AzureCliCredential from pydantic import Field -from agent_framework import tool """ Azure AI Agent with Explicit Settings Example @@ -17,6 +17,7 @@ settings rather than relying on environment variable defaults. """ + # NOTE: approval_mode="never_require" is for sample brevity. Use "always_require" in production; see samples/getting_started/tools/function_tool_with_approval.py and samples/getting_started/tools/function_tool_with_approval_and_threads.py. @tool(approval_mode="never_require") def get_weather( diff --git a/python/samples/getting_started/agents/azure_ai_agent/azure_ai_with_function_tools.py b/python/samples/getting_started/agents/azure_ai_agent/azure_ai_with_function_tools.py index 7da870c42a..97cd59ca19 100644 --- a/python/samples/getting_started/agents/azure_ai_agent/azure_ai_with_function_tools.py +++ b/python/samples/getting_started/agents/azure_ai_agent/azure_ai_with_function_tools.py @@ -5,10 +5,10 @@ from random import randint from typing import Annotated +from agent_framework import tool from agent_framework.azure import AzureAIAgentsProvider from azure.identity.aio import AzureCliCredential from pydantic import Field -from agent_framework import tool """ Azure AI Agent with Function Tools Example @@ -17,6 +17,7 @@ showing both agent-level and query-level tool configuration patterns. """ + # NOTE: approval_mode="never_require" is for sample brevity. Use "always_require" in production; see samples/getting_started/tools/function_tool_with_approval.py and samples/getting_started/tools/function_tool_with_approval_and_threads.py. @tool(approval_mode="never_require") def get_weather( @@ -26,6 +27,7 @@ def get_weather( conditions = ["sunny", "cloudy", "rainy", "stormy"] return f"The weather in {location} is {conditions[randint(0, 3)]} with a high of {randint(10, 30)}°C." + @tool(approval_mode="never_require") def get_time() -> str: """Get the current UTC time.""" diff --git a/python/samples/getting_started/agents/azure_ai_agent/azure_ai_with_multiple_tools.py b/python/samples/getting_started/agents/azure_ai_agent/azure_ai_with_multiple_tools.py index 4539696bc6..7185203c24 100644 --- a/python/samples/getting_started/agents/azure_ai_agent/azure_ai_with_multiple_tools.py +++ b/python/samples/getting_started/agents/azure_ai_agent/azure_ai_with_multiple_tools.py @@ -34,9 +34,9 @@ 4. Copy the connection ID and set it as the BING_CONNECTION_ID environment variable """ + # NOTE: approval_mode="never_require" is for sample brevity. Use "always_require" in production; see samples/getting_started/tools/function_tool_with_approval.py and samples/getting_started/tools/function_tool_with_approval_and_threads.py. @tool(approval_mode="never_require") - def get_time() -> str: """Get the current UTC time.""" current_time = datetime.now(timezone.utc) diff --git a/python/samples/getting_started/agents/azure_ai_agent/azure_ai_with_response_format.py b/python/samples/getting_started/agents/azure_ai_agent/azure_ai_with_response_format.py index 1a55724c60..a607304724 100644 --- a/python/samples/getting_started/agents/azure_ai_agent/azure_ai_with_response_format.py +++ b/python/samples/getting_started/agents/azure_ai_agent/azure_ai_with_response_format.py @@ -56,13 +56,14 @@ async def main() -> None: result1 = await agent.run(query1) - if weather := result1.try_parse_value(WeatherInfo): + try: + weather = result1.value print("Agent:") print(f" Location: {weather.location}") print(f" Temperature: {weather.temperature}") print(f" Conditions: {weather.conditions}") print(f" Recommendation: {weather.recommendation}") - else: + except Exception: print(f"Failed to parse response: {result1.text}") # Request 2: Override response_format at runtime with CityInfo @@ -72,12 +73,13 @@ async def main() -> None: result2 = await agent.run(query2, options={"response_format": CityInfo}) - if city := result2.try_parse_value(CityInfo): + try: + city = result2.value print("Agent:") print(f" City: {city.city_name}") print(f" Population: {city.population}") print(f" Country: {city.country}") - else: + except Exception: print(f"Failed to parse response: {result2.text}") diff --git a/python/samples/getting_started/agents/azure_ai_agent/azure_ai_with_thread.py b/python/samples/getting_started/agents/azure_ai_agent/azure_ai_with_thread.py index 04128c80a1..a48851d67c 100644 --- a/python/samples/getting_started/agents/azure_ai_agent/azure_ai_with_thread.py +++ b/python/samples/getting_started/agents/azure_ai_agent/azure_ai_with_thread.py @@ -4,8 +4,7 @@ from random import randint from typing import Annotated -from agent_framework import AgentThread -from agent_framework import tool +from agent_framework import AgentThread, tool from agent_framework.azure import AzureAIAgentsProvider from azure.identity.aio import AzureCliCredential from pydantic import Field @@ -17,6 +16,7 @@ automatic thread creation with explicit thread management for persistent context. """ + # NOTE: approval_mode="never_require" is for sample brevity. Use "always_require" in production; see samples/getting_started/tools/function_tool_with_approval.py and samples/getting_started/tools/function_tool_with_approval_and_threads.py. @tool(approval_mode="never_require") def get_weather( diff --git a/python/samples/getting_started/agents/azure_openai/azure_assistants_basic.py b/python/samples/getting_started/agents/azure_openai/azure_assistants_basic.py index 7613eb62dc..243ba55bf3 100644 --- a/python/samples/getting_started/agents/azure_openai/azure_assistants_basic.py +++ b/python/samples/getting_started/agents/azure_openai/azure_assistants_basic.py @@ -4,10 +4,10 @@ from random import randint from typing import Annotated +from agent_framework import tool from agent_framework.azure import AzureOpenAIAssistantsClient from azure.identity import AzureCliCredential from pydantic import Field -from agent_framework import tool """ Azure OpenAI Assistants Basic Example @@ -16,6 +16,7 @@ assistant lifecycle management, showing both streaming and non-streaming responses. """ + # NOTE: approval_mode="never_require" is for sample brevity. Use "always_require" in production; see samples/getting_started/tools/function_tool_with_approval.py and samples/getting_started/tools/function_tool_with_approval_and_threads.py. @tool(approval_mode="never_require") def get_weather( diff --git a/python/samples/getting_started/agents/azure_openai/azure_assistants_with_existing_assistant.py b/python/samples/getting_started/agents/azure_openai/azure_assistants_with_existing_assistant.py index 70cd79b41a..7e373d4fad 100644 --- a/python/samples/getting_started/agents/azure_openai/azure_assistants_with_existing_assistant.py +++ b/python/samples/getting_started/agents/azure_openai/azure_assistants_with_existing_assistant.py @@ -5,8 +5,7 @@ from random import randint from typing import Annotated -from agent_framework import ChatAgent -from agent_framework import tool +from agent_framework import ChatAgent, tool from agent_framework.azure import AzureOpenAIAssistantsClient from azure.identity import AzureCliCredential, get_bearer_token_provider from openai import AsyncAzureOpenAI @@ -19,6 +18,7 @@ using existing assistant IDs rather than creating new ones. """ + # NOTE: approval_mode="never_require" is for sample brevity. Use "always_require" in production; see samples/getting_started/tools/function_tool_with_approval.py and samples/getting_started/tools/function_tool_with_approval_and_threads.py. @tool(approval_mode="never_require") def get_weather( diff --git a/python/samples/getting_started/agents/azure_openai/azure_assistants_with_explicit_settings.py b/python/samples/getting_started/agents/azure_openai/azure_assistants_with_explicit_settings.py index 581c447240..65b0214ab8 100644 --- a/python/samples/getting_started/agents/azure_openai/azure_assistants_with_explicit_settings.py +++ b/python/samples/getting_started/agents/azure_openai/azure_assistants_with_explicit_settings.py @@ -5,10 +5,10 @@ from random import randint from typing import Annotated +from agent_framework import tool from agent_framework.azure import AzureOpenAIAssistantsClient from azure.identity import AzureCliCredential from pydantic import Field -from agent_framework import tool """ Azure OpenAI Assistants with Explicit Settings Example @@ -17,6 +17,7 @@ settings rather than relying on environment variable defaults. """ + # NOTE: approval_mode="never_require" is for sample brevity. Use "always_require" in production; see samples/getting_started/tools/function_tool_with_approval.py and samples/getting_started/tools/function_tool_with_approval_and_threads.py. @tool(approval_mode="never_require") def get_weather( diff --git a/python/samples/getting_started/agents/azure_openai/azure_assistants_with_function_tools.py b/python/samples/getting_started/agents/azure_openai/azure_assistants_with_function_tools.py index 6256681fce..8333e7fdc8 100644 --- a/python/samples/getting_started/agents/azure_openai/azure_assistants_with_function_tools.py +++ b/python/samples/getting_started/agents/azure_openai/azure_assistants_with_function_tools.py @@ -5,8 +5,7 @@ from random import randint from typing import Annotated -from agent_framework import ChatAgent -from agent_framework import tool +from agent_framework import ChatAgent, tool from agent_framework.azure import AzureOpenAIAssistantsClient from azure.identity import AzureCliCredential from pydantic import Field @@ -18,6 +17,7 @@ showing both agent-level and query-level tool configuration patterns. """ + # NOTE: approval_mode="never_require" is for sample brevity. Use "always_require" in production; see samples/getting_started/tools/function_tool_with_approval.py and samples/getting_started/tools/function_tool_with_approval_and_threads.py. @tool(approval_mode="never_require") def get_weather( @@ -27,6 +27,7 @@ def get_weather( conditions = ["sunny", "cloudy", "rainy", "stormy"] return f"The weather in {location} is {conditions[randint(0, 3)]} with a high of {randint(10, 30)}°C." + @tool(approval_mode="never_require") def get_time() -> str: """Get the current UTC time.""" diff --git a/python/samples/getting_started/agents/azure_openai/azure_assistants_with_thread.py b/python/samples/getting_started/agents/azure_openai/azure_assistants_with_thread.py index a791604744..793f8260c3 100644 --- a/python/samples/getting_started/agents/azure_openai/azure_assistants_with_thread.py +++ b/python/samples/getting_started/agents/azure_openai/azure_assistants_with_thread.py @@ -4,8 +4,7 @@ from random import randint from typing import Annotated -from agent_framework import AgentThread, ChatAgent -from agent_framework import tool +from agent_framework import AgentThread, ChatAgent, tool from agent_framework.azure import AzureOpenAIAssistantsClient from azure.identity import AzureCliCredential from pydantic import Field @@ -17,6 +16,7 @@ automatic thread creation with explicit thread management for persistent context. """ + # NOTE: approval_mode="never_require" is for sample brevity. Use "always_require" in production; see samples/getting_started/tools/function_tool_with_approval.py and samples/getting_started/tools/function_tool_with_approval_and_threads.py. @tool(approval_mode="never_require") def get_weather( diff --git a/python/samples/getting_started/agents/azure_openai/azure_chat_client_basic.py b/python/samples/getting_started/agents/azure_openai/azure_chat_client_basic.py index 25b0cc5bd3..feb2ab5f89 100644 --- a/python/samples/getting_started/agents/azure_openai/azure_chat_client_basic.py +++ b/python/samples/getting_started/agents/azure_openai/azure_chat_client_basic.py @@ -4,10 +4,10 @@ from random import randint from typing import Annotated +from agent_framework import tool from agent_framework.azure import AzureOpenAIChatClient from azure.identity import AzureCliCredential from pydantic import Field -from agent_framework import tool """ Azure OpenAI Chat Client Basic Example @@ -16,6 +16,7 @@ interactions, showing both streaming and non-streaming responses. """ + # NOTE: approval_mode="never_require" is for sample brevity. Use "always_require" in production; see samples/getting_started/tools/function_tool_with_approval.py and samples/getting_started/tools/function_tool_with_approval_and_threads.py. @tool(approval_mode="never_require") def get_weather( diff --git a/python/samples/getting_started/agents/azure_openai/azure_chat_client_with_explicit_settings.py b/python/samples/getting_started/agents/azure_openai/azure_chat_client_with_explicit_settings.py index db97390aa8..5f7bc794e5 100644 --- a/python/samples/getting_started/agents/azure_openai/azure_chat_client_with_explicit_settings.py +++ b/python/samples/getting_started/agents/azure_openai/azure_chat_client_with_explicit_settings.py @@ -5,10 +5,10 @@ from random import randint from typing import Annotated +from agent_framework import tool from agent_framework.azure import AzureOpenAIChatClient from azure.identity import AzureCliCredential from pydantic import Field -from agent_framework import tool """ Azure OpenAI Chat Client with Explicit Settings Example @@ -17,6 +17,7 @@ settings rather than relying on environment variable defaults. """ + # NOTE: approval_mode="never_require" is for sample brevity. Use "always_require" in production; see samples/getting_started/tools/function_tool_with_approval.py and samples/getting_started/tools/function_tool_with_approval_and_threads.py. @tool(approval_mode="never_require") def get_weather( diff --git a/python/samples/getting_started/agents/azure_openai/azure_chat_client_with_function_tools.py b/python/samples/getting_started/agents/azure_openai/azure_chat_client_with_function_tools.py index 33b8ffe577..777bcc51b1 100644 --- a/python/samples/getting_started/agents/azure_openai/azure_chat_client_with_function_tools.py +++ b/python/samples/getting_started/agents/azure_openai/azure_chat_client_with_function_tools.py @@ -5,8 +5,7 @@ from random import randint from typing import Annotated -from agent_framework import ChatAgent -from agent_framework import tool +from agent_framework import ChatAgent, tool from agent_framework.azure import AzureOpenAIChatClient from azure.identity import AzureCliCredential from pydantic import Field @@ -18,6 +17,7 @@ showing both agent-level and query-level tool configuration patterns. """ + # NOTE: approval_mode="never_require" is for sample brevity. Use "always_require" in production; see samples/getting_started/tools/function_tool_with_approval.py and samples/getting_started/tools/function_tool_with_approval_and_threads.py. @tool(approval_mode="never_require") def get_weather( @@ -27,6 +27,7 @@ def get_weather( conditions = ["sunny", "cloudy", "rainy", "stormy"] return f"The weather in {location} is {conditions[randint(0, 3)]} with a high of {randint(10, 30)}°C." + @tool(approval_mode="never_require") def get_time() -> str: """Get the current UTC time.""" diff --git a/python/samples/getting_started/agents/azure_openai/azure_chat_client_with_thread.py b/python/samples/getting_started/agents/azure_openai/azure_chat_client_with_thread.py index 16fee4226e..08ada3ba97 100644 --- a/python/samples/getting_started/agents/azure_openai/azure_chat_client_with_thread.py +++ b/python/samples/getting_started/agents/azure_openai/azure_chat_client_with_thread.py @@ -4,8 +4,7 @@ from random import randint from typing import Annotated -from agent_framework import AgentThread, ChatAgent, ChatMessageStore -from agent_framework import tool +from agent_framework import AgentThread, ChatAgent, ChatMessageStore, tool from agent_framework.azure import AzureOpenAIChatClient from azure.identity import AzureCliCredential from pydantic import Field @@ -17,6 +16,7 @@ automatic thread creation with explicit thread management for persistent context. """ + # NOTE: approval_mode="never_require" is for sample brevity. Use "always_require" in production; see samples/getting_started/tools/function_tool_with_approval.py and samples/getting_started/tools/function_tool_with_approval_and_threads.py. @tool(approval_mode="never_require") def get_weather( diff --git a/python/samples/getting_started/agents/azure_openai/azure_responses_client_basic.py b/python/samples/getting_started/agents/azure_openai/azure_responses_client_basic.py index 921ee76634..af79b0465c 100644 --- a/python/samples/getting_started/agents/azure_openai/azure_responses_client_basic.py +++ b/python/samples/getting_started/agents/azure_openai/azure_responses_client_basic.py @@ -4,10 +4,10 @@ from random import randint from typing import Annotated +from agent_framework import tool from agent_framework.azure import AzureOpenAIResponsesClient from azure.identity import AzureCliCredential from pydantic import Field -from agent_framework import tool """ Azure OpenAI Responses Client Basic Example @@ -16,6 +16,7 @@ response generation, showing both streaming and non-streaming responses. """ + # NOTE: approval_mode="never_require" is for sample brevity. Use "always_require" in production; see samples/getting_started/tools/function_tool_with_approval.py and samples/getting_started/tools/function_tool_with_approval_and_threads.py. @tool(approval_mode="never_require") def get_weather( diff --git a/python/samples/getting_started/agents/azure_openai/azure_responses_client_with_explicit_settings.py b/python/samples/getting_started/agents/azure_openai/azure_responses_client_with_explicit_settings.py index 5a38798ef0..c21462b11f 100644 --- a/python/samples/getting_started/agents/azure_openai/azure_responses_client_with_explicit_settings.py +++ b/python/samples/getting_started/agents/azure_openai/azure_responses_client_with_explicit_settings.py @@ -5,10 +5,10 @@ from random import randint from typing import Annotated +from agent_framework import tool from agent_framework.azure import AzureOpenAIResponsesClient from azure.identity import AzureCliCredential from pydantic import Field -from agent_framework import tool """ Azure OpenAI Responses Client with Explicit Settings Example @@ -17,6 +17,7 @@ settings rather than relying on environment variable defaults. """ + # NOTE: approval_mode="never_require" is for sample brevity. Use "always_require" in production; see samples/getting_started/tools/function_tool_with_approval.py and samples/getting_started/tools/function_tool_with_approval_and_threads.py. @tool(approval_mode="never_require") def get_weather( diff --git a/python/samples/getting_started/agents/azure_openai/azure_responses_client_with_function_tools.py b/python/samples/getting_started/agents/azure_openai/azure_responses_client_with_function_tools.py index 1799f88560..a5d6d85aa6 100644 --- a/python/samples/getting_started/agents/azure_openai/azure_responses_client_with_function_tools.py +++ b/python/samples/getting_started/agents/azure_openai/azure_responses_client_with_function_tools.py @@ -5,8 +5,7 @@ from random import randint from typing import Annotated -from agent_framework import ChatAgent -from agent_framework import tool +from agent_framework import ChatAgent, tool from agent_framework.azure import AzureOpenAIResponsesClient from azure.identity import AzureCliCredential from pydantic import Field @@ -18,6 +17,7 @@ showing both agent-level and query-level tool configuration patterns. """ + # NOTE: approval_mode="never_require" is for sample brevity. Use "always_require" in production; see samples/getting_started/tools/function_tool_with_approval.py and samples/getting_started/tools/function_tool_with_approval_and_threads.py. @tool(approval_mode="never_require") def get_weather( @@ -27,6 +27,7 @@ def get_weather( conditions = ["sunny", "cloudy", "rainy", "stormy"] return f"The weather in {location} is {conditions[randint(0, 3)]} with a high of {randint(10, 30)}°C." + @tool(approval_mode="never_require") def get_time() -> str: """Get the current UTC time.""" diff --git a/python/samples/getting_started/agents/azure_openai/azure_responses_client_with_hosted_mcp.py b/python/samples/getting_started/agents/azure_openai/azure_responses_client_with_hosted_mcp.py index 0833065742..7d346c8fc8 100644 --- a/python/samples/getting_started/agents/azure_openai/azure_responses_client_with_hosted_mcp.py +++ b/python/samples/getting_started/agents/azure_openai/azure_responses_client_with_hosted_mcp.py @@ -30,10 +30,10 @@ async def handle_approvals_without_thread(query: str, agent: "AgentProtocol"): f"User Input Request for function from {agent.name}: {user_input_needed.function_call.name}" f" with arguments: {user_input_needed.function_call.arguments}" ) - new_inputs.append(ChatMessage(role="assistant", contents=[user_input_needed])) + new_inputs.append(ChatMessage("assistant", [user_input_needed])) user_approval = input("Approve function call? (y/n): ") new_inputs.append( - ChatMessage(role="user", contents=[user_input_needed.to_function_approval_response(user_approval.lower() == "y")]) + ChatMessage("user", [user_input_needed.to_function_approval_response(user_approval.lower() == "y")]) ) result = await agent.run(new_inputs) @@ -71,7 +71,7 @@ async def handle_approvals_with_thread_streaming(query: str, agent: "AgentProtoc new_input_added = True while new_input_added: new_input_added = False - new_input.append(ChatMessage(role="user", text=query)) + new_input.append(ChatMessage("user", [query])) async for update in agent.run_stream(new_input, thread=thread, store=True): if update.user_input_requests: for user_input_needed in update.user_input_requests: diff --git a/python/samples/getting_started/agents/azure_openai/azure_responses_client_with_thread.py b/python/samples/getting_started/agents/azure_openai/azure_responses_client_with_thread.py index 817ac69ef2..01ade8da6f 100644 --- a/python/samples/getting_started/agents/azure_openai/azure_responses_client_with_thread.py +++ b/python/samples/getting_started/agents/azure_openai/azure_responses_client_with_thread.py @@ -4,8 +4,7 @@ from random import randint from typing import Annotated -from agent_framework import AgentThread, ChatAgent -from agent_framework import tool +from agent_framework import AgentThread, ChatAgent, tool from agent_framework.azure import AzureOpenAIResponsesClient from azure.identity import AzureCliCredential from pydantic import Field @@ -17,6 +16,7 @@ automatic thread creation with explicit thread management for persistent context. """ + # NOTE: approval_mode="never_require" is for sample brevity. Use "always_require" in production; see samples/getting_started/tools/function_tool_with_approval.py and samples/getting_started/tools/function_tool_with_approval_and_threads.py. @tool(approval_mode="never_require") def get_weather( diff --git a/python/samples/getting_started/agents/custom/custom_agent.py b/python/samples/getting_started/agents/custom/custom_agent.py index 4bdc0d79e3..cc3c376964 100644 --- a/python/samples/getting_started/agents/custom/custom_agent.py +++ b/python/samples/getting_started/agents/custom/custom_agent.py @@ -11,8 +11,6 @@ BaseAgent, ChatMessage, Content, - Role, - tool, ) """ @@ -77,8 +75,8 @@ async def run( if not normalized_messages: response_message = ChatMessage( - role=Role.ASSISTANT, - contents=[Content.from_text(text="Hello! I'm a custom echo agent. Send me a message and I'll echo it back.")], + "assistant", + [Content.from_text(text="Hello! I'm a custom echo agent. Send me a message and I'll echo it back.")], ) else: # For simplicity, echo the last user message @@ -88,7 +86,7 @@ async def run( else: echo_text = f"{self.echo_prefix}[Non-text message received]" - response_message = ChatMessage(role=Role.ASSISTANT, contents=[Content.from_text(text=echo_text)]) + response_message = ChatMessage("assistant", [Content.from_text(text=echo_text)]) # Notify the thread of new messages if provided if thread is not None: @@ -134,7 +132,7 @@ async def run_stream( yield AgentResponseUpdate( contents=[Content.from_text(text=chunk_text)], - role=Role.ASSISTANT, + role="assistant", ) # Small delay to simulate streaming @@ -142,7 +140,7 @@ async def run_stream( # Notify the thread of the complete response if provided if thread is not None: - complete_response = ChatMessage(role=Role.ASSISTANT, contents=[Content.from_text(text=response_text)]) + complete_response = ChatMessage("assistant", [Content.from_text(text=response_text)]) await self._notify_thread_of_new_messages(thread, normalized_messages, complete_response) diff --git a/python/samples/getting_started/agents/custom/custom_chat_client.py b/python/samples/getting_started/agents/custom/custom_chat_client.py index c7df328b00..a6c38fcbca 100644 --- a/python/samples/getting_started/agents/custom/custom_chat_client.py +++ b/python/samples/getting_started/agents/custom/custom_chat_client.py @@ -12,10 +12,8 @@ ChatResponse, ChatResponseUpdate, Content, - Role, use_chat_middleware, use_function_invocation, - tool, ) from agent_framework._clients import TOptions_co @@ -68,7 +66,7 @@ async def _inner_get_response( # Echo the last user message last_user_message = None for message in reversed(messages): - if message.role == Role.USER: + if message.role == "user": last_user_message = message break @@ -77,7 +75,7 @@ async def _inner_get_response( else: response_text = f"{self.prefix} [No text message found]" - response_message = ChatMessage(role=Role.ASSISTANT, contents=[Content.from_text(text=response_text)]) + response_message = ChatMessage("assistant", [Content.from_text(text=response_text)]) return ChatResponse( messages=[response_message], @@ -104,7 +102,7 @@ async def _inner_get_streaming_response( for char in response_text: yield ChatResponseUpdate( contents=[Content.from_text(text=char)], - role=Role.ASSISTANT, + role="assistant", response_id=f"echo-stream-resp-{random.randint(1000, 9999)}", model_id="echo-model-v1", ) diff --git a/python/samples/getting_started/agents/ollama/ollama_agent_basic.py b/python/samples/getting_started/agents/ollama/ollama_agent_basic.py index afe6700083..80b17e3b39 100644 --- a/python/samples/getting_started/agents/ollama/ollama_agent_basic.py +++ b/python/samples/getting_started/agents/ollama/ollama_agent_basic.py @@ -3,8 +3,8 @@ import asyncio from datetime import datetime -from agent_framework.ollama import OllamaChatClient from agent_framework import tool +from agent_framework.ollama import OllamaChatClient """ Ollama Agent Basic Example @@ -18,6 +18,7 @@ """ + # NOTE: approval_mode="never_require" is for sample brevity. Use "always_require" in production; see samples/getting_started/tools/function_tool_with_approval.py and samples/getting_started/tools/function_tool_with_approval_and_threads.py. @tool(approval_mode="never_require") def get_time(location: str) -> str: diff --git a/python/samples/getting_started/agents/ollama/ollama_chat_client.py b/python/samples/getting_started/agents/ollama/ollama_chat_client.py index d22fd737f7..67c71ff249 100644 --- a/python/samples/getting_started/agents/ollama/ollama_chat_client.py +++ b/python/samples/getting_started/agents/ollama/ollama_chat_client.py @@ -3,8 +3,8 @@ import asyncio from datetime import datetime -from agent_framework.ollama import OllamaChatClient from agent_framework import tool +from agent_framework.ollama import OllamaChatClient """ Ollama Chat Client Example @@ -18,6 +18,7 @@ """ + # NOTE: approval_mode="never_require" is for sample brevity. Use "always_require" in production; see samples/getting_started/tools/function_tool_with_approval.py and samples/getting_started/tools/function_tool_with_approval_and_threads.py. @tool(approval_mode="never_require") def get_time(): diff --git a/python/samples/getting_started/agents/ollama/ollama_chat_multimodal.py b/python/samples/getting_started/agents/ollama/ollama_chat_multimodal.py index c78053a91a..3deb6f6e92 100644 --- a/python/samples/getting_started/agents/ollama/ollama_chat_multimodal.py +++ b/python/samples/getting_started/agents/ollama/ollama_chat_multimodal.py @@ -2,7 +2,7 @@ import asyncio -from agent_framework import ChatMessage, Content, Role +from agent_framework import ChatMessage, Content from agent_framework.ollama import OllamaChatClient """ @@ -33,7 +33,7 @@ async def test_image() -> None: image_uri = create_sample_image() message = ChatMessage( - role=Role.USER, + role="user", contents=[ Content.from_text(text="What's in this image?"), Content.from_uri(uri=image_uri, media_type="image/png"), diff --git a/python/samples/getting_started/agents/ollama/ollama_with_openai_chat_client.py b/python/samples/getting_started/agents/ollama/ollama_with_openai_chat_client.py index 47f58cd6e7..b555b7789f 100644 --- a/python/samples/getting_started/agents/ollama/ollama_with_openai_chat_client.py +++ b/python/samples/getting_started/agents/ollama/ollama_with_openai_chat_client.py @@ -5,8 +5,8 @@ from random import randint from typing import Annotated -from agent_framework.openai import OpenAIChatClient from agent_framework import tool +from agent_framework.openai import OpenAIChatClient """ Ollama with OpenAI Chat Client Example @@ -20,6 +20,7 @@ - OLLAMA_MODEL: The model name to use (e.g., "mistral", "llama3.2", "phi3") """ + # NOTE: approval_mode="never_require" is for sample brevity. Use "always_require" in production; see samples/getting_started/tools/function_tool_with_approval.py and samples/getting_started/tools/function_tool_with_approval_and_threads.py. @tool(approval_mode="never_require") def get_weather( diff --git a/python/samples/getting_started/agents/openai/openai_assistants_basic.py b/python/samples/getting_started/agents/openai/openai_assistants_basic.py index bf52405218..eb267b4a88 100644 --- a/python/samples/getting_started/agents/openai/openai_assistants_basic.py +++ b/python/samples/getting_started/agents/openai/openai_assistants_basic.py @@ -5,10 +5,10 @@ from random import randint from typing import Annotated +from agent_framework import tool from agent_framework.openai import OpenAIAssistantProvider from openai import AsyncOpenAI from pydantic import Field -from agent_framework import tool """ OpenAI Assistants Basic Example @@ -17,6 +17,7 @@ assistant lifecycle management, showing both streaming and non-streaming responses. """ + # NOTE: approval_mode="never_require" is for sample brevity. Use "always_require" in production; see samples/getting_started/tools/function_tool_with_approval.py and samples/getting_started/tools/function_tool_with_approval_and_threads.py. @tool(approval_mode="never_require") def get_weather( diff --git a/python/samples/getting_started/agents/openai/openai_assistants_provider_methods.py b/python/samples/getting_started/agents/openai/openai_assistants_provider_methods.py index 55e1110075..1c3ed11642 100644 --- a/python/samples/getting_started/agents/openai/openai_assistants_provider_methods.py +++ b/python/samples/getting_started/agents/openai/openai_assistants_provider_methods.py @@ -5,10 +5,10 @@ from random import randint from typing import Annotated +from agent_framework import tool from agent_framework.openai import OpenAIAssistantProvider from openai import AsyncOpenAI from pydantic import Field -from agent_framework import tool """ OpenAI Assistant Provider Methods Example @@ -19,6 +19,7 @@ - as_agent(): Wrap an SDK Assistant object without making HTTP calls """ + # NOTE: approval_mode="never_require" is for sample brevity. Use "always_require" in production; see samples/getting_started/tools/function_tool_with_approval.py and samples/getting_started/tools/function_tool_with_approval_and_threads.py. @tool(approval_mode="never_require") def get_weather( diff --git a/python/samples/getting_started/agents/openai/openai_assistants_with_existing_assistant.py b/python/samples/getting_started/agents/openai/openai_assistants_with_existing_assistant.py index 827d8c412c..b004253796 100644 --- a/python/samples/getting_started/agents/openai/openai_assistants_with_existing_assistant.py +++ b/python/samples/getting_started/agents/openai/openai_assistants_with_existing_assistant.py @@ -5,10 +5,10 @@ from random import randint from typing import Annotated +from agent_framework import tool from agent_framework.openai import OpenAIAssistantProvider from openai import AsyncOpenAI from pydantic import Field -from agent_framework import tool """ OpenAI Assistants with Existing Assistant Example @@ -17,6 +17,7 @@ using the provider's get_agent() and as_agent() methods. """ + # NOTE: approval_mode="never_require" is for sample brevity. Use "always_require" in production; see samples/getting_started/tools/function_tool_with_approval.py and samples/getting_started/tools/function_tool_with_approval_and_threads.py. @tool(approval_mode="never_require") def get_weather( diff --git a/python/samples/getting_started/agents/openai/openai_assistants_with_explicit_settings.py b/python/samples/getting_started/agents/openai/openai_assistants_with_explicit_settings.py index 53afefa5e9..70622f714b 100644 --- a/python/samples/getting_started/agents/openai/openai_assistants_with_explicit_settings.py +++ b/python/samples/getting_started/agents/openai/openai_assistants_with_explicit_settings.py @@ -5,10 +5,10 @@ from random import randint from typing import Annotated +from agent_framework import tool from agent_framework.openai import OpenAIAssistantProvider from openai import AsyncOpenAI from pydantic import Field -from agent_framework import tool """ OpenAI Assistants with Explicit Settings Example @@ -17,6 +17,7 @@ settings rather than relying on environment variable defaults. """ + # NOTE: approval_mode="never_require" is for sample brevity. Use "always_require" in production; see samples/getting_started/tools/function_tool_with_approval.py and samples/getting_started/tools/function_tool_with_approval_and_threads.py. @tool(approval_mode="never_require") def get_weather( diff --git a/python/samples/getting_started/agents/openai/openai_assistants_with_function_tools.py b/python/samples/getting_started/agents/openai/openai_assistants_with_function_tools.py index bf75affc55..fe4b3d3b4e 100644 --- a/python/samples/getting_started/agents/openai/openai_assistants_with_function_tools.py +++ b/python/samples/getting_started/agents/openai/openai_assistants_with_function_tools.py @@ -6,10 +6,10 @@ from random import randint from typing import Annotated +from agent_framework import tool from agent_framework.openai import OpenAIAssistantProvider from openai import AsyncOpenAI from pydantic import Field -from agent_framework import tool """ OpenAI Assistants with Function Tools Example @@ -18,6 +18,7 @@ showing both agent-level and query-level tool configuration patterns. """ + # NOTE: approval_mode="never_require" is for sample brevity. Use "always_require" in production; see samples/getting_started/tools/function_tool_with_approval.py and samples/getting_started/tools/function_tool_with_approval_and_threads.py. @tool(approval_mode="never_require") def get_weather( @@ -27,6 +28,7 @@ def get_weather( conditions = ["sunny", "cloudy", "rainy", "stormy"] return f"The weather in {location} is {conditions[randint(0, 3)]} with a high of {randint(10, 30)}C." + @tool(approval_mode="never_require") def get_time() -> str: """Get the current UTC time.""" diff --git a/python/samples/getting_started/agents/openai/openai_assistants_with_response_format.py b/python/samples/getting_started/agents/openai/openai_assistants_with_response_format.py index e48338b558..0719ecc7de 100644 --- a/python/samples/getting_started/agents/openai/openai_assistants_with_response_format.py +++ b/python/samples/getting_started/agents/openai/openai_assistants_with_response_format.py @@ -59,13 +59,14 @@ async def main() -> None: result1 = await agent.run(query1) - if weather := result1.try_parse_value(WeatherInfo): + try: + weather = result1.value print("Agent:") print(f" Location: {weather.location}") print(f" Temperature: {weather.temperature}") print(f" Conditions: {weather.conditions}") print(f" Recommendation: {weather.recommendation}") - else: + except Exception: print(f"Failed to parse response: {result1.text}") # Request 2: Override response_format at runtime with CityInfo @@ -75,12 +76,13 @@ async def main() -> None: result2 = await agent.run(query2, options={"response_format": CityInfo}) - if city := result2.try_parse_value(CityInfo): + try: + city = result2.value print("Agent:") print(f" City: {city.city_name}") print(f" Population: {city.population}") print(f" Country: {city.country}") - else: + except Exception: print(f"Failed to parse response: {result2.text}") finally: await client.beta.assistants.delete(agent.id) diff --git a/python/samples/getting_started/agents/openai/openai_assistants_with_thread.py b/python/samples/getting_started/agents/openai/openai_assistants_with_thread.py index d3b167ebdd..02b8086199 100644 --- a/python/samples/getting_started/agents/openai/openai_assistants_with_thread.py +++ b/python/samples/getting_started/agents/openai/openai_assistants_with_thread.py @@ -5,8 +5,7 @@ from random import randint from typing import Annotated -from agent_framework import AgentThread -from agent_framework import tool +from agent_framework import AgentThread, tool from agent_framework.openai import OpenAIAssistantProvider from openai import AsyncOpenAI from pydantic import Field @@ -18,6 +17,7 @@ persistent conversation threads and context preservation across interactions. """ + # NOTE: approval_mode="never_require" is for sample brevity. Use "always_require" in production; see samples/getting_started/tools/function_tool_with_approval.py and samples/getting_started/tools/function_tool_with_approval_and_threads.py. @tool(approval_mode="never_require") def get_weather( diff --git a/python/samples/getting_started/agents/openai/openai_chat_client_basic.py b/python/samples/getting_started/agents/openai/openai_chat_client_basic.py index 6c1a94760d..49cfb29447 100644 --- a/python/samples/getting_started/agents/openai/openai_chat_client_basic.py +++ b/python/samples/getting_started/agents/openai/openai_chat_client_basic.py @@ -4,8 +4,8 @@ from random import randint from typing import Annotated -from agent_framework.openai import OpenAIChatClient from agent_framework import tool +from agent_framework.openai import OpenAIChatClient """ OpenAI Chat Client Basic Example @@ -14,6 +14,7 @@ interactions, showing both streaming and non-streaming responses. """ + # NOTE: approval_mode="never_require" is for sample brevity. Use "always_require" in production; see samples/getting_started/tools/function_tool_with_approval.py and samples/getting_started/tools/function_tool_with_approval_and_threads.py. @tool(approval_mode="never_require") def get_weather( diff --git a/python/samples/getting_started/agents/openai/openai_chat_client_with_explicit_settings.py b/python/samples/getting_started/agents/openai/openai_chat_client_with_explicit_settings.py index 1302841ecf..0bac0b863c 100644 --- a/python/samples/getting_started/agents/openai/openai_chat_client_with_explicit_settings.py +++ b/python/samples/getting_started/agents/openai/openai_chat_client_with_explicit_settings.py @@ -5,9 +5,9 @@ from random import randint from typing import Annotated +from agent_framework import tool from agent_framework.openai import OpenAIChatClient from pydantic import Field -from agent_framework import tool """ OpenAI Chat Client with Explicit Settings Example @@ -16,6 +16,7 @@ settings rather than relying on environment variable defaults. """ + # NOTE: approval_mode="never_require" is for sample brevity. Use "always_require" in production; see samples/getting_started/tools/function_tool_with_approval.py and samples/getting_started/tools/function_tool_with_approval_and_threads.py. @tool(approval_mode="never_require") def get_weather( diff --git a/python/samples/getting_started/agents/openai/openai_chat_client_with_function_tools.py b/python/samples/getting_started/agents/openai/openai_chat_client_with_function_tools.py index 3fa7fd9e8a..057989d228 100644 --- a/python/samples/getting_started/agents/openai/openai_chat_client_with_function_tools.py +++ b/python/samples/getting_started/agents/openai/openai_chat_client_with_function_tools.py @@ -5,8 +5,7 @@ from random import randint from typing import Annotated -from agent_framework import ChatAgent -from agent_framework import tool +from agent_framework import ChatAgent, tool from agent_framework.openai import OpenAIChatClient from pydantic import Field @@ -17,6 +16,7 @@ showing both agent-level and query-level tool configuration patterns. """ + # NOTE: approval_mode="never_require" is for sample brevity. Use "always_require" in production; see samples/getting_started/tools/function_tool_with_approval.py and samples/getting_started/tools/function_tool_with_approval_and_threads.py. @tool(approval_mode="never_require") def get_weather( @@ -26,6 +26,7 @@ def get_weather( conditions = ["sunny", "cloudy", "rainy", "stormy"] return f"The weather in {location} is {conditions[randint(0, 3)]} with a high of {randint(10, 30)}°C." + @tool(approval_mode="never_require") def get_time() -> str: """Get the current UTC time.""" diff --git a/python/samples/getting_started/agents/openai/openai_chat_client_with_thread.py b/python/samples/getting_started/agents/openai/openai_chat_client_with_thread.py index 0c6595ca16..f7a824c370 100644 --- a/python/samples/getting_started/agents/openai/openai_chat_client_with_thread.py +++ b/python/samples/getting_started/agents/openai/openai_chat_client_with_thread.py @@ -4,8 +4,7 @@ from random import randint from typing import Annotated -from agent_framework import AgentThread, ChatAgent, ChatMessageStore -from agent_framework import tool +from agent_framework import AgentThread, ChatAgent, ChatMessageStore, tool from agent_framework.openai import OpenAIChatClient from pydantic import Field @@ -16,6 +15,7 @@ conversation threads and message history preservation across interactions. """ + # NOTE: approval_mode="never_require" is for sample brevity. Use "always_require" in production; see samples/getting_started/tools/function_tool_with_approval.py and samples/getting_started/tools/function_tool_with_approval_and_threads.py. @tool(approval_mode="never_require") def get_weather( diff --git a/python/samples/getting_started/agents/openai/openai_responses_client_basic.py b/python/samples/getting_started/agents/openai/openai_responses_client_basic.py index c09a4c816a..4e7fcbf07d 100644 --- a/python/samples/getting_started/agents/openai/openai_responses_client_basic.py +++ b/python/samples/getting_started/agents/openai/openai_responses_client_basic.py @@ -4,8 +4,7 @@ from random import randint from typing import Annotated -from agent_framework import ChatAgent -from agent_framework import tool +from agent_framework import ChatAgent, tool from agent_framework.openai import OpenAIResponsesClient from pydantic import Field @@ -16,6 +15,7 @@ response generation, showing both streaming and non-streaming responses. """ + # NOTE: approval_mode="never_require" is for sample brevity. Use "always_require" in production; see samples/getting_started/tools/function_tool_with_approval.py and samples/getting_started/tools/function_tool_with_approval_and_threads.py. @tool(approval_mode="never_require") def get_weather( diff --git a/python/samples/getting_started/agents/openai/openai_responses_client_with_code_interpreter.py b/python/samples/getting_started/agents/openai/openai_responses_client_with_code_interpreter.py index 6988219dcc..5a73752bd9 100644 --- a/python/samples/getting_started/agents/openai/openai_responses_client_with_code_interpreter.py +++ b/python/samples/getting_started/agents/openai/openai_responses_client_with_code_interpreter.py @@ -8,7 +8,6 @@ CodeInterpreterToolResultContent, Content, HostedCodeInterpreterTool, - tool, ) from agent_framework.openai import OpenAIResponsesClient diff --git a/python/samples/getting_started/agents/openai/openai_responses_client_with_explicit_settings.py b/python/samples/getting_started/agents/openai/openai_responses_client_with_explicit_settings.py index fa5583f296..826fd880bf 100644 --- a/python/samples/getting_started/agents/openai/openai_responses_client_with_explicit_settings.py +++ b/python/samples/getting_started/agents/openai/openai_responses_client_with_explicit_settings.py @@ -5,9 +5,9 @@ from random import randint from typing import Annotated +from agent_framework import tool from agent_framework.openai import OpenAIResponsesClient from pydantic import Field -from agent_framework import tool """ OpenAI Responses Client with Explicit Settings Example @@ -16,6 +16,7 @@ settings rather than relying on environment variable defaults. """ + # NOTE: approval_mode="never_require" is for sample brevity. Use "always_require" in production; see samples/getting_started/tools/function_tool_with_approval.py and samples/getting_started/tools/function_tool_with_approval_and_threads.py. @tool(approval_mode="never_require") def get_weather( diff --git a/python/samples/getting_started/agents/openai/openai_responses_client_with_function_tools.py b/python/samples/getting_started/agents/openai/openai_responses_client_with_function_tools.py index d18a522406..032a8b20d8 100644 --- a/python/samples/getting_started/agents/openai/openai_responses_client_with_function_tools.py +++ b/python/samples/getting_started/agents/openai/openai_responses_client_with_function_tools.py @@ -5,8 +5,7 @@ from random import randint from typing import Annotated -from agent_framework import ChatAgent -from agent_framework import tool +from agent_framework import ChatAgent, tool from agent_framework.openai import OpenAIResponsesClient from pydantic import Field @@ -17,6 +16,7 @@ showing both agent-level and query-level tool configuration patterns. """ + # NOTE: approval_mode="never_require" is for sample brevity. Use "always_require" in production; see samples/getting_started/tools/function_tool_with_approval.py and samples/getting_started/tools/function_tool_with_approval_and_threads.py. @tool(approval_mode="never_require") def get_weather( @@ -26,6 +26,7 @@ def get_weather( conditions = ["sunny", "cloudy", "rainy", "stormy"] return f"The weather in {location} is {conditions[randint(0, 3)]} with a high of {randint(10, 30)}°C." + @tool(approval_mode="never_require") def get_time() -> str: """Get the current UTC time.""" diff --git a/python/samples/getting_started/agents/openai/openai_responses_client_with_hosted_mcp.py b/python/samples/getting_started/agents/openai/openai_responses_client_with_hosted_mcp.py index e5fa62f040..264971d8e7 100644 --- a/python/samples/getting_started/agents/openai/openai_responses_client_with_hosted_mcp.py +++ b/python/samples/getting_started/agents/openai/openai_responses_client_with_hosted_mcp.py @@ -29,10 +29,10 @@ async def handle_approvals_without_thread(query: str, agent: "AgentProtocol"): f"User Input Request for function from {agent.name}: {user_input_needed.function_call.name}" f" with arguments: {user_input_needed.function_call.arguments}" ) - new_inputs.append(ChatMessage(role="assistant", contents=[user_input_needed])) + new_inputs.append(ChatMessage("assistant", [user_input_needed])) user_approval = input("Approve function call? (y/n): ") new_inputs.append( - ChatMessage(role="user", contents=[user_input_needed.to_function_approval_response(user_approval.lower() == "y")]) + ChatMessage("user", [user_input_needed.to_function_approval_response(user_approval.lower() == "y")]) ) result = await agent.run(new_inputs) @@ -70,7 +70,7 @@ async def handle_approvals_with_thread_streaming(query: str, agent: "AgentProtoc new_input_added = True while new_input_added: new_input_added = False - new_input.append(ChatMessage(role="user", text=query)) + new_input.append(ChatMessage("user", [query])) async for update in agent.run_stream(new_input, thread=thread, store=True): if update.user_input_requests: for user_input_needed in update.user_input_requests: diff --git a/python/samples/getting_started/agents/openai/openai_responses_client_with_thread.py b/python/samples/getting_started/agents/openai/openai_responses_client_with_thread.py index 6a7fc71efc..e17c2d2748 100644 --- a/python/samples/getting_started/agents/openai/openai_responses_client_with_thread.py +++ b/python/samples/getting_started/agents/openai/openai_responses_client_with_thread.py @@ -4,8 +4,7 @@ from random import randint from typing import Annotated -from agent_framework import AgentThread, ChatAgent -from agent_framework import tool +from agent_framework import AgentThread, ChatAgent, tool from agent_framework.openai import OpenAIResponsesClient from pydantic import Field @@ -16,6 +15,7 @@ persistent conversation context and simplified response handling. """ + # NOTE: approval_mode="never_require" is for sample brevity. Use "always_require" in production; see samples/getting_started/tools/function_tool_with_approval.py and samples/getting_started/tools/function_tool_with_approval_and_threads.py. @tool(approval_mode="never_require") def get_weather( diff --git a/python/samples/getting_started/azure_functions/02_multi_agent/function_app.py b/python/samples/getting_started/azure_functions/02_multi_agent/function_app.py index f7181cb4b1..cb735baecd 100644 --- a/python/samples/getting_started/azure_functions/02_multi_agent/function_app.py +++ b/python/samples/getting_started/azure_functions/02_multi_agent/function_app.py @@ -11,12 +11,13 @@ import logging from typing import Any +from agent_framework import tool from agent_framework.azure import AgentFunctionApp, AzureOpenAIChatClient from azure.identity import AzureCliCredential -from agent_framework import tool logger = logging.getLogger(__name__) + # NOTE: approval_mode="never_require" is for sample brevity. Use "always_require" in production; see samples/getting_started/tools/function_tool_with_approval.py and samples/getting_started/tools/function_tool_with_approval_and_threads.py. @tool(approval_mode="never_require") def get_weather(location: str) -> dict[str, Any]: @@ -32,6 +33,7 @@ def get_weather(location: str) -> dict[str, Any]: logger.info(f"✓ [TOOL RESULT] {result}") return result + @tool(approval_mode="never_require") def calculate_tip(bill_amount: float, tip_percentage: float = 15.0) -> dict[str, Any]: """Calculate tip amount and total bill.""" diff --git a/python/samples/getting_started/azure_functions/03_reliable_streaming/redis_stream_response_handler.py b/python/samples/getting_started/azure_functions/03_reliable_streaming/redis_stream_response_handler.py index e6d60735bf..ff9f544062 100644 --- a/python/samples/getting_started/azure_functions/03_reliable_streaming/redis_stream_response_handler.py +++ b/python/samples/getting_started/azure_functions/03_reliable_streaming/redis_stream_response_handler.py @@ -8,9 +8,9 @@ import asyncio import time +from collections.abc import AsyncIterator from dataclasses import dataclass from datetime import timedelta -from collections.abc import AsyncIterator import redis.asyncio as aioredis diff --git a/python/samples/getting_started/azure_functions/03_reliable_streaming/tools.py b/python/samples/getting_started/azure_functions/03_reliable_streaming/tools.py index 6a71fdfa03..29be74a846 100644 --- a/python/samples/getting_started/azure_functions/03_reliable_streaming/tools.py +++ b/python/samples/getting_started/azure_functions/03_reliable_streaming/tools.py @@ -153,13 +153,12 @@ def _get_weather_recommendation(condition: str) -> str: if "rain" in condition_lower or "drizzle" in condition_lower: return "Bring an umbrella and waterproof jacket. Consider indoor activities for backup." - elif "fog" in condition_lower: + if "fog" in condition_lower: return "Morning visibility may be limited. Plan outdoor sightseeing for afternoon." - elif "cold" in condition_lower: + if "cold" in condition_lower: return "Layer up with warm clothing. Hot drinks and cozy cafés recommended." - elif "hot" in condition_lower or "warm" in condition_lower: + if "hot" in condition_lower or "warm" in condition_lower: return "Stay hydrated and use sunscreen. Plan strenuous activities for cooler morning hours." - elif "thunder" in condition_lower or "storm" in condition_lower: + if "thunder" in condition_lower or "storm" in condition_lower: return "Keep an eye on weather updates. Have indoor alternatives ready." - else: - return "Pleasant conditions expected. Great day for outdoor exploration!" + return "Pleasant conditions expected. Great day for outdoor exploration!" diff --git a/python/samples/getting_started/azure_functions/06_multi_agent_orchestration_conditionals/function_app.py b/python/samples/getting_started/azure_functions/06_multi_agent_orchestration_conditionals/function_app.py index ea373e588a..1165f0cc8e 100644 --- a/python/samples/getting_started/azure_functions/06_multi_agent_orchestration_conditionals/function_app.py +++ b/python/samples/getting_started/azure_functions/06_multi_agent_orchestration_conditionals/function_app.py @@ -102,9 +102,10 @@ def spam_detection_orchestration(context: DurableOrchestrationContext) -> Genera options={"response_format": SpamDetectionResult}, ) - spam_result = spam_result_raw.try_parse_value(SpamDetectionResult) - if spam_result is None: - raise ValueError("Failed to parse spam detection result") + try: + spam_result = spam_result_raw.value + except Exception as ex: + raise ValueError("Failed to parse spam detection result") from ex if spam_result.is_spam: result = yield context.call_activity("handle_spam_email", spam_result.reason) # type: ignore[misc] @@ -125,9 +126,10 @@ def spam_detection_orchestration(context: DurableOrchestrationContext) -> Genera options={"response_format": EmailResponse}, ) - email_result = email_result_raw.try_parse_value(EmailResponse) - if email_result is None: - raise ValueError("Failed to parse email response") + try: + email_result = email_result_raw.value + except Exception as ex: + raise ValueError("Failed to parse email response") from ex result = yield context.call_activity("send_email", email_result.response) # type: ignore[misc] return result diff --git a/python/samples/getting_started/azure_functions/07_single_agent_orchestration_hitl/function_app.py b/python/samples/getting_started/azure_functions/07_single_agent_orchestration_hitl/function_app.py index 1b55620233..6ed85081bc 100644 --- a/python/samples/getting_started/azure_functions/07_single_agent_orchestration_hitl/function_app.py +++ b/python/samples/getting_started/azure_functions/07_single_agent_orchestration_hitl/function_app.py @@ -137,11 +137,11 @@ def content_generation_hitl_orchestration(context: DurableOrchestrationContext) context.set_custom_status( "Content rejected by human reviewer. Incorporating feedback and regenerating..." ) - + # Check if we've exhausted attempts if attempt >= payload.max_review_attempts: break - + rewrite_prompt = ( "The content was rejected by a human reviewer. Please rewrite the article incorporating their feedback.\n\n" f"Human Feedback: {approval_payload.feedback or 'No feedback provided.'}" @@ -152,9 +152,10 @@ def content_generation_hitl_orchestration(context: DurableOrchestrationContext) options={"response_format": GeneratedContent}, ) - content = rewritten_raw.try_parse_value(GeneratedContent) - if content is None: - raise ValueError("Agent returned no content after rewrite.") + try: + content = rewritten_raw.value + except Exception as ex: + raise ValueError("Agent returned no content after rewrite.") from ex else: context.set_custom_status( f"Human approval timed out after {payload.approval_timeout_hours} hour(s). Treating as rejection." @@ -162,7 +163,7 @@ def content_generation_hitl_orchestration(context: DurableOrchestrationContext) raise TimeoutError( f"Human approval timed out after {payload.approval_timeout_hours} hour(s)." ) - + # If we exit the loop without returning, max attempts were exhausted context.set_custom_status("Max review attempts exhausted.") raise RuntimeError( diff --git a/python/samples/getting_started/chat_client/azure_ai_chat_client.py b/python/samples/getting_started/chat_client/azure_ai_chat_client.py index ab502b8f35..97aa015f13 100644 --- a/python/samples/getting_started/chat_client/azure_ai_chat_client.py +++ b/python/samples/getting_started/chat_client/azure_ai_chat_client.py @@ -4,10 +4,10 @@ from random import randint from typing import Annotated +from agent_framework import tool from agent_framework.azure import AzureAIAgentClient from azure.identity.aio import AzureCliCredential from pydantic import Field -from agent_framework import tool """ Azure AI Chat Client Direct Usage Example @@ -16,6 +16,7 @@ Shows function calling capabilities with custom business logic. """ + # NOTE: approval_mode="never_require" is for sample brevity. Use "always_require" in production; see samples/getting_started/tools/function_tool_with_approval.py and samples/getting_started/tools/function_tool_with_approval_and_threads.py. @tool(approval_mode="never_require") def get_weather( diff --git a/python/samples/getting_started/chat_client/azure_assistants_client.py b/python/samples/getting_started/chat_client/azure_assistants_client.py index 1a40696bd5..99f4de5b9c 100644 --- a/python/samples/getting_started/chat_client/azure_assistants_client.py +++ b/python/samples/getting_started/chat_client/azure_assistants_client.py @@ -4,10 +4,10 @@ from random import randint from typing import Annotated +from agent_framework import tool from agent_framework.azure import AzureOpenAIAssistantsClient from azure.identity import AzureCliCredential from pydantic import Field -from agent_framework import tool """ Azure Assistants Client Direct Usage Example @@ -16,6 +16,7 @@ Shows function calling capabilities and automatic assistant creation. """ + # NOTE: approval_mode="never_require" is for sample brevity. Use "always_require" in production; see samples/getting_started/tools/function_tool_with_approval.py and samples/getting_started/tools/function_tool_with_approval_and_threads.py. @tool(approval_mode="never_require") def get_weather( diff --git a/python/samples/getting_started/chat_client/azure_chat_client.py b/python/samples/getting_started/chat_client/azure_chat_client.py index 211fc6d869..77b3358a39 100644 --- a/python/samples/getting_started/chat_client/azure_chat_client.py +++ b/python/samples/getting_started/chat_client/azure_chat_client.py @@ -4,10 +4,10 @@ from random import randint from typing import Annotated +from agent_framework import tool from agent_framework.azure import AzureOpenAIChatClient from azure.identity import AzureCliCredential from pydantic import Field -from agent_framework import tool """ Azure Chat Client Direct Usage Example @@ -16,6 +16,7 @@ Shows function calling capabilities with custom business logic. """ + # NOTE: approval_mode="never_require" is for sample brevity. Use "always_require" in production; see samples/getting_started/tools/function_tool_with_approval.py and samples/getting_started/tools/function_tool_with_approval_and_threads.py. @tool(approval_mode="never_require") def get_weather( diff --git a/python/samples/getting_started/chat_client/azure_responses_client.py b/python/samples/getting_started/chat_client/azure_responses_client.py index 050225e559..17a1ab335a 100644 --- a/python/samples/getting_started/chat_client/azure_responses_client.py +++ b/python/samples/getting_started/chat_client/azure_responses_client.py @@ -4,8 +4,7 @@ from random import randint from typing import Annotated -from agent_framework import ChatResponse -from agent_framework import tool +from agent_framework import ChatResponse, tool from agent_framework.azure import AzureOpenAIResponsesClient from azure.identity import AzureCliCredential from pydantic import BaseModel, Field @@ -17,6 +16,7 @@ Shows function calling capabilities with custom business logic. """ + # NOTE: approval_mode="never_require" is for sample brevity. Use "always_require" in production; see samples/getting_started/tools/function_tool_with_approval.py and samples/getting_started/tools/function_tool_with_approval_and_threads.py. @tool(approval_mode="never_require") def get_weather( @@ -42,19 +42,21 @@ async def main() -> None: stream = True print(f"User: {message}") if stream: - response = await ChatResponse.from_chat_response_generator( + response = await ChatResponse.from_update_generator( client.get_streaming_response(message, tools=get_weather, options={"response_format": OutputStruct}), output_format_type=OutputStruct, ) - if result := response.try_parse_value(OutputStruct): + try: + result = response.value print(f"Assistant: {result}") - else: + except Exception: print(f"Assistant: {response.text}") else: response = await client.get_response(message, tools=get_weather, options={"response_format": OutputStruct}) - if result := response.try_parse_value(OutputStruct): + try: + result = response.value print(f"Assistant: {result}") - else: + except Exception: print(f"Assistant: {response.text}") diff --git a/python/samples/getting_started/chat_client/openai_assistants_client.py b/python/samples/getting_started/chat_client/openai_assistants_client.py index b4dc03ea71..88aec44ed2 100644 --- a/python/samples/getting_started/chat_client/openai_assistants_client.py +++ b/python/samples/getting_started/chat_client/openai_assistants_client.py @@ -4,9 +4,9 @@ from random import randint from typing import Annotated +from agent_framework import tool from agent_framework.openai import OpenAIAssistantsClient from pydantic import Field -from agent_framework import tool """ OpenAI Assistants Client Direct Usage Example @@ -16,6 +16,7 @@ """ + # NOTE: approval_mode="never_require" is for sample brevity. Use "always_require" in production; see samples/getting_started/tools/function_tool_with_approval.py and samples/getting_started/tools/function_tool_with_approval_and_threads.py. @tool(approval_mode="never_require") def get_weather( diff --git a/python/samples/getting_started/chat_client/openai_chat_client.py b/python/samples/getting_started/chat_client/openai_chat_client.py index f45f17d71f..da50ae59bf 100644 --- a/python/samples/getting_started/chat_client/openai_chat_client.py +++ b/python/samples/getting_started/chat_client/openai_chat_client.py @@ -4,9 +4,9 @@ from random import randint from typing import Annotated +from agent_framework import tool from agent_framework.openai import OpenAIChatClient from pydantic import Field -from agent_framework import tool """ OpenAI Chat Client Direct Usage Example @@ -16,6 +16,7 @@ """ + # NOTE: approval_mode="never_require" is for sample brevity. Use "always_require" in production; see samples/getting_started/tools/function_tool_with_approval.py and samples/getting_started/tools/function_tool_with_approval_and_threads.py. @tool(approval_mode="never_require") def get_weather( diff --git a/python/samples/getting_started/chat_client/openai_responses_client.py b/python/samples/getting_started/chat_client/openai_responses_client.py index 2c5f3953e9..c9d476faa3 100644 --- a/python/samples/getting_started/chat_client/openai_responses_client.py +++ b/python/samples/getting_started/chat_client/openai_responses_client.py @@ -4,9 +4,9 @@ from random import randint from typing import Annotated +from agent_framework import tool from agent_framework.openai import OpenAIResponsesClient from pydantic import Field -from agent_framework import tool """ OpenAI Responses Client Direct Usage Example @@ -16,6 +16,7 @@ """ + # NOTE: approval_mode="never_require" is for sample brevity. Use "always_require" in production; see samples/getting_started/tools/function_tool_with_approval.py and samples/getting_started/tools/function_tool_with_approval_and_threads.py. @tool(approval_mode="never_require") def get_weather( diff --git a/python/samples/getting_started/context_providers/mem0/mem0_basic.py b/python/samples/getting_started/context_providers/mem0/mem0_basic.py index a163b000e8..b82dab0ae1 100644 --- a/python/samples/getting_started/context_providers/mem0/mem0_basic.py +++ b/python/samples/getting_started/context_providers/mem0/mem0_basic.py @@ -3,10 +3,11 @@ import asyncio import uuid +from agent_framework import tool from agent_framework.azure import AzureAIAgentClient from agent_framework.mem0 import Mem0Provider from azure.identity.aio import AzureCliCredential -from agent_framework import tool + # NOTE: approval_mode="never_require" is for sample brevity. Use "always_require" in production; see samples/getting_started/tools/function_tool_with_approval.py and samples/getting_started/tools/function_tool_with_approval_and_threads.py. @tool(approval_mode="never_require") diff --git a/python/samples/getting_started/context_providers/mem0/mem0_oss.py b/python/samples/getting_started/context_providers/mem0/mem0_oss.py index 1f5591c004..84156434b0 100644 --- a/python/samples/getting_started/context_providers/mem0/mem0_oss.py +++ b/python/samples/getting_started/context_providers/mem0/mem0_oss.py @@ -3,11 +3,12 @@ import asyncio import uuid +from agent_framework import tool from agent_framework.azure import AzureAIAgentClient from agent_framework.mem0 import Mem0Provider from azure.identity.aio import AzureCliCredential from mem0 import AsyncMemory -from agent_framework import tool + # NOTE: approval_mode="never_require" is for sample brevity. Use "always_require" in production; see samples/getting_started/tools/function_tool_with_approval.py and samples/getting_started/tools/function_tool_with_approval_and_threads.py. @tool(approval_mode="never_require") diff --git a/python/samples/getting_started/context_providers/mem0/mem0_threads.py b/python/samples/getting_started/context_providers/mem0/mem0_threads.py index ea0375495a..15a57ad796 100644 --- a/python/samples/getting_started/context_providers/mem0/mem0_threads.py +++ b/python/samples/getting_started/context_providers/mem0/mem0_threads.py @@ -3,10 +3,11 @@ import asyncio import uuid +from agent_framework import tool from agent_framework.azure import AzureAIAgentClient from agent_framework.mem0 import Mem0Provider from azure.identity.aio import AzureCliCredential -from agent_framework import tool + # NOTE: approval_mode="never_require" is for sample brevity. Use "always_require" in production; see samples/getting_started/tools/function_tool_with_approval.py and samples/getting_started/tools/function_tool_with_approval_and_threads.py. @tool(approval_mode="never_require") diff --git a/python/samples/getting_started/context_providers/redis/redis_basics.py b/python/samples/getting_started/context_providers/redis/redis_basics.py index afbe835cc0..9f5a654ea1 100644 --- a/python/samples/getting_started/context_providers/redis/redis_basics.py +++ b/python/samples/getting_started/context_providers/redis/redis_basics.py @@ -30,13 +30,13 @@ import asyncio import os -from agent_framework import ChatMessage, Role -from agent_framework import tool +from agent_framework import ChatMessage, tool from agent_framework.openai import OpenAIChatClient from agent_framework_redis._provider import RedisProvider from redisvl.extensions.cache.embeddings import EmbeddingsCache from redisvl.utils.vectorize import OpenAITextVectorizer + # NOTE: approval_mode="never_require" is for sample brevity. Use "always_require" in production; see samples/getting_started/tools/function_tool_with_approval.py and samples/getting_started/tools/function_tool_with_approval_and_threads.py. @tool(approval_mode="never_require") def search_flights(origin_airport_code: str, destination_airport_code: str, detailed: bool = False) -> str: @@ -128,9 +128,9 @@ async def main() -> None: # Build sample chat messages to persist to Redis messages = [ - ChatMessage(role=Role.USER, text="runA CONVO: User Message"), - ChatMessage(role=Role.ASSISTANT, text="runA CONVO: Assistant Message"), - ChatMessage(role=Role.SYSTEM, text="runA CONVO: System Message"), + ChatMessage("user", ["runA CONVO: User Message"]), + ChatMessage("assistant", ["runA CONVO: Assistant Message"]), + ChatMessage("system", ["runA CONVO: System Message"]), ] # Declare/start a conversation/thread and write messages under 'runA'. @@ -142,7 +142,7 @@ async def main() -> None: # Retrieve relevant memories for a hypothetical model call. The provider uses # the current request messages as the retrieval query and returns context to # be injected into the model's instructions. - ctx = await provider.invoking([ChatMessage(role=Role.SYSTEM, text="B: Assistant Message")]) + ctx = await provider.invoking([ChatMessage("system", ["B: Assistant Message"])]) # Inspect retrieved memories that would be injected into instructions # (Debug-only output so you can verify retrieval works as expected.) diff --git a/python/samples/getting_started/context_providers/simple_context_provider.py b/python/samples/getting_started/context_providers/simple_context_provider.py index e85de6aced..e32266cb14 100644 --- a/python/samples/getting_started/context_providers/simple_context_provider.py +++ b/python/samples/getting_started/context_providers/simple_context_provider.py @@ -39,7 +39,7 @@ async def invoked( ) -> None: """Extract user information from messages after each agent call.""" # Check if we need to extract user info from user messages - user_messages = [msg for msg in request_messages if hasattr(msg, "role") and msg.role.value == "user"] # type: ignore + user_messages = [msg for msg in request_messages if hasattr(msg, "role") and msg.role == "user"] # type: ignore if (self.user_info.name is None or self.user_info.age is None) and user_messages: try: @@ -52,11 +52,14 @@ async def invoked( ) # Update user info with extracted data - if extracted := result.try_parse_value(UserInfo): + try: + extracted = result.value if self.user_info.name is None and extracted.name: self.user_info.name = extracted.name if self.user_info.age is None and extracted.age: self.user_info.age = extracted.age + except Exception: + pass # Failed to extract, continue without updating except Exception: pass # Failed to extract, continue without updating diff --git a/python/samples/getting_started/declarative/azure_openai_responses_agent.py b/python/samples/getting_started/declarative/azure_openai_responses_agent.py index 1dbcc6adea..edcf0f0805 100644 --- a/python/samples/getting_started/declarative/azure_openai_responses_agent.py +++ b/python/samples/getting_started/declarative/azure_openai_responses_agent.py @@ -20,10 +20,11 @@ async def main(): agent = AgentFactory(client_kwargs={"credential": AzureCliCredential()}).create_agent_from_yaml(yaml_str) # use the agent response = await agent.run("Why is the sky blue, answer in Dutch?") - # Use try_parse_value() for safe parsing - returns None if no response_format or parsing fails - if parsed := response.try_parse_value(): + # Use response.value with try/except for safe parsing + try: + parsed = response.value print("Agent response:", parsed.model_dump_json(indent=2)) - else: + except Exception: print("Agent response:", response.text) diff --git a/python/samples/getting_started/declarative/openai_responses_agent.py b/python/samples/getting_started/declarative/openai_responses_agent.py index ed2cc89d08..2931168587 100644 --- a/python/samples/getting_started/declarative/openai_responses_agent.py +++ b/python/samples/getting_started/declarative/openai_responses_agent.py @@ -19,10 +19,11 @@ async def main(): agent = AgentFactory().create_agent_from_yaml(yaml_str) # use the agent response = await agent.run("Why is the sky blue, answer in Dutch?") - # Use try_parse_value() for safe parsing - returns None if no response_format or parsing fails - if parsed := response.try_parse_value(): + # Use response.value with try/except for safe parsing + try: + parsed = response.value print("Agent response:", parsed) - else: + except Exception: print("Agent response:", response.text) diff --git a/python/samples/getting_started/devui/fanout_workflow/workflow.py b/python/samples/getting_started/devui/fanout_workflow/workflow.py index bb84c28db7..fa9d4edd92 100644 --- a/python/samples/getting_started/devui/fanout_workflow/workflow.py +++ b/python/samples/getting_started/devui/fanout_workflow/workflow.py @@ -25,7 +25,6 @@ WorkflowBuilder, WorkflowContext, handler, - tool, ) from pydantic import BaseModel, Field from typing_extensions import Never diff --git a/python/samples/getting_started/devui/foundry_agent/agent.py b/python/samples/getting_started/devui/foundry_agent/agent.py index 9091bb2d7e..f2ce12058d 100644 --- a/python/samples/getting_started/devui/foundry_agent/agent.py +++ b/python/samples/getting_started/devui/foundry_agent/agent.py @@ -8,12 +8,12 @@ import os from typing import Annotated -from agent_framework import ChatAgent -from agent_framework import tool +from agent_framework import ChatAgent, tool from agent_framework.azure import AzureAIAgentClient from azure.identity.aio import AzureCliCredential from pydantic import Field + # NOTE: approval_mode="never_require" is for sample brevity. Use "always_require" in production; see samples/getting_started/tools/function_tool_with_approval.py and samples/getting_started/tools/function_tool_with_approval_and_threads.py. @tool(approval_mode="never_require") def get_weather( @@ -24,6 +24,7 @@ def get_weather( temperature = 22 return f"The weather in {location} is {conditions[0]} with a high of {temperature}°C." + @tool(approval_mode="never_require") def get_forecast( location: Annotated[str, Field(description="The location to get the forecast for.")], diff --git a/python/samples/getting_started/devui/in_memory_mode.py b/python/samples/getting_started/devui/in_memory_mode.py index 597f9babf3..e8441e9eb5 100644 --- a/python/samples/getting_started/devui/in_memory_mode.py +++ b/python/samples/getting_started/devui/in_memory_mode.py @@ -10,8 +10,7 @@ import os from typing import Annotated -from agent_framework import ChatAgent, Executor, WorkflowBuilder, WorkflowContext, handler -from agent_framework import tool +from agent_framework import ChatAgent, Executor, WorkflowBuilder, WorkflowContext, handler, tool from agent_framework.azure import AzureOpenAIChatClient from agent_framework.devui import serve from typing_extensions import Never @@ -29,6 +28,7 @@ def get_weather( temperature = 53 return f"The weather in {location} is {conditions[0]} with a high of {temperature}°C." + @tool(approval_mode="never_require") def get_time( timezone: Annotated[str, "The timezone to get time for."] = "UTC", diff --git a/python/samples/getting_started/devui/spam_workflow/workflow.py b/python/samples/getting_started/devui/spam_workflow/workflow.py index 54cf6265ca..73be349cc6 100644 --- a/python/samples/getting_started/devui/spam_workflow/workflow.py +++ b/python/samples/getting_started/devui/spam_workflow/workflow.py @@ -27,7 +27,6 @@ WorkflowContext, handler, response_handler, - tool, ) from pydantic import BaseModel, Field from typing_extensions import Never diff --git a/python/samples/getting_started/devui/weather_agent_azure/agent.py b/python/samples/getting_started/devui/weather_agent_azure/agent.py index cc2992d0c5..71525c24a1 100644 --- a/python/samples/getting_started/devui/weather_agent_azure/agent.py +++ b/python/samples/getting_started/devui/weather_agent_azure/agent.py @@ -14,10 +14,9 @@ ChatResponseUpdate, Content, FunctionInvocationContext, - Role, - tool, chat_middleware, function_middleware, + tool, ) from agent_framework.azure import AzureOpenAIChatClient from agent_framework_devui import register_cleanup @@ -43,7 +42,7 @@ async def security_filter_middleware( # Check only the last message (most recent user input) last_message = context.messages[-1] if context.messages else None - if last_message and last_message.role == Role.USER and last_message.text: + if last_message and last_message.role == "user" and last_message.text: message_lower = last_message.text.lower() for term in blocked_terms: if term in message_lower: @@ -58,7 +57,7 @@ async def security_filter_middleware( async def blocked_stream() -> AsyncIterable[ChatResponseUpdate]: yield ChatResponseUpdate( contents=[Content.from_text(text=error_message)], - role=Role.ASSISTANT, + role="assistant", ) context.result = blocked_stream() @@ -67,7 +66,7 @@ async def blocked_stream() -> AsyncIterable[ChatResponseUpdate]: context.result = ChatResponse( messages=[ ChatMessage( - role=Role.ASSISTANT, + role="assistant", text=error_message, ) ] diff --git a/python/samples/getting_started/durabletask/01_single_agent/client.py b/python/samples/getting_started/durabletask/01_single_agent/client.py index 7c8b27d80c..71d897e1f2 100644 --- a/python/samples/getting_started/durabletask/01_single_agent/client.py +++ b/python/samples/getting_started/durabletask/01_single_agent/client.py @@ -40,12 +40,12 @@ def get_client( """ taskhub_name = taskhub or os.getenv("TASKHUB", "default") endpoint_url = endpoint or os.getenv("ENDPOINT", "http://localhost:8080") - + logger.debug(f"Using taskhub: {taskhub_name}") logger.debug(f"Using endpoint: {endpoint_url}") - + credential = None if endpoint_url == "http://localhost:8080" else DefaultAzureCredential() - + dts_client = DurableTaskSchedulerClient( host_address=endpoint_url, secure_channel=endpoint_url != "http://localhost:8080", @@ -53,7 +53,7 @@ def get_client( token_credential=credential, log_handler=log_handler ) - + return DurableAIAgentClient(dts_client) @@ -66,12 +66,12 @@ def run_client(agent_client: DurableAIAgentClient) -> None: # Get a reference to the Joker agent logger.debug("Getting reference to Joker agent...") joker = agent_client.get_agent("Joker") - + # Create a new thread for the conversation thread = joker.get_new_thread() logger.debug(f"Thread ID: {thread.session_id}") logger.info("Start chatting with the Joker agent! (Type 'exit' to quit)") - + # Interactive conversation loop while True: # Get user input @@ -80,33 +80,33 @@ def run_client(agent_client: DurableAIAgentClient) -> None: except (EOFError, KeyboardInterrupt): logger.info("\nExiting...") break - + # Check for exit command if user_message.lower() == "exit": logger.info("Goodbye!") break - + # Skip empty messages if not user_message: continue - + # Send message to agent and get response try: response = joker.run(user_message, thread=thread) logger.info(f"Joker: {response.text} \n") except Exception as e: logger.error(f"Error getting response: {e}") - + logger.info("Conversation completed.") async def main() -> None: """Main entry point for the client application.""" logger.debug("Starting Durable Task Agent Client...") - + # Create client using helper function agent_client = get_client() - + try: run_client(agent_client) except Exception as e: diff --git a/python/samples/getting_started/durabletask/01_single_agent/sample.py b/python/samples/getting_started/durabletask/01_single_agent/sample.py index b8c39974c0..323549d8bf 100644 --- a/python/samples/getting_started/durabletask/01_single_agent/sample.py +++ b/python/samples/getting_started/durabletask/01_single_agent/sample.py @@ -15,40 +15,40 @@ import logging -from dotenv import load_dotenv - # Import helper functions from worker and client modules from client import get_client, run_client +from dotenv import load_dotenv from worker import get_worker, setup_worker # Configure logging (must be after imports to override their basicConfig) logging.basicConfig(level=logging.INFO, force=True) logger = logging.getLogger(__name__) + def main(): """Main entry point - runs both worker and client in single process.""" logger.debug("Starting Durable Task Agent Sample (Combined Worker + Client)...") silent_handler = logging.NullHandler() - + # Create and start the worker using helper function and context manager with get_worker(log_handler=silent_handler) as dts_worker: # Register agents using helper function setup_worker(dts_worker) - + # Start the worker dts_worker.start() logger.debug("Worker started and listening for requests...") - + # Create the client using helper function agent_client = get_client(log_handler=silent_handler) - + try: # Run client interactions using helper function run_client(agent_client) except Exception as e: logger.exception(f"Error during agent interaction: {e}") - + logger.debug("Sample completed. Worker shutting down...") diff --git a/python/samples/getting_started/durabletask/01_single_agent/worker.py b/python/samples/getting_started/durabletask/01_single_agent/worker.py index 4b837a8a8e..03fc5a667f 100644 --- a/python/samples/getting_started/durabletask/01_single_agent/worker.py +++ b/python/samples/getting_started/durabletask/01_single_agent/worker.py @@ -52,12 +52,12 @@ def get_worker( """ taskhub_name = taskhub or os.getenv("TASKHUB", "default") endpoint_url = endpoint or os.getenv("ENDPOINT", "http://localhost:8080") - + logger.debug(f"Using taskhub: {taskhub_name}") logger.debug(f"Using endpoint: {endpoint_url}") - + credential = None if endpoint_url == "http://localhost:8080" else DefaultAzureCredential() - + return DurableTaskSchedulerWorker( host_address=endpoint_url, secure_channel=endpoint_url != "http://localhost:8080", @@ -78,42 +78,42 @@ def setup_worker(worker: DurableTaskSchedulerWorker) -> DurableAIAgentWorker: """ # Wrap it with the agent worker agent_worker = DurableAIAgentWorker(worker) - + # Create and register the Joker agent logger.debug("Creating and registering Joker agent...") joker_agent = create_joker_agent() agent_worker.add_agent(joker_agent) - + logger.debug(f"✓ Registered agent: {joker_agent.name}") logger.debug(f" Entity name: dafx-{joker_agent.name}") - + return agent_worker async def main(): """Main entry point for the worker process.""" logger.debug("Starting Durable Task Agent Worker...") - + # Create a worker using the helper function worker = get_worker() - + # Setup worker with agents setup_worker(worker) - + logger.info("Worker is ready and listening for requests...") logger.info("Press Ctrl+C to stop.") logger.info("") - + try: # Start the worker (this blocks until stopped) worker.start() - + # Keep the worker running while True: await asyncio.sleep(1) except KeyboardInterrupt: logger.debug("Worker shutdown initiated") - + logger.debug("Worker stopped") diff --git a/python/samples/getting_started/durabletask/02_multi_agent/client.py b/python/samples/getting_started/durabletask/02_multi_agent/client.py index d7cecabd99..b3d8434062 100644 --- a/python/samples/getting_started/durabletask/02_multi_agent/client.py +++ b/python/samples/getting_started/durabletask/02_multi_agent/client.py @@ -41,12 +41,12 @@ def get_client( """ taskhub_name = taskhub or os.getenv("TASKHUB", "default") endpoint_url = endpoint or os.getenv("ENDPOINT", "http://localhost:8080") - + logger.debug(f"Using taskhub: {taskhub_name}") logger.debug(f"Using endpoint: {endpoint_url}") - + credential = None if endpoint_url == "http://localhost:8080" else DefaultAzureCredential() - + dts_client = DurableTaskSchedulerClient( host_address=endpoint_url, secure_channel=endpoint_url != "http://localhost:8080", @@ -54,7 +54,7 @@ def get_client( token_credential=credential, log_handler=log_handler ) - + return DurableAIAgentClient(dts_client) @@ -65,45 +65,45 @@ def run_client(agent_client: DurableAIAgentClient) -> None: agent_client: The DurableAIAgentClient instance """ logger.debug("Testing WeatherAgent") - + # Get reference to WeatherAgent weather_agent = agent_client.get_agent("WeatherAgent") weather_thread = weather_agent.get_new_thread() - + logger.debug(f"Created weather conversation thread: {weather_thread.session_id}") - + # Test WeatherAgent weather_message = "What is the weather in Seattle?" logger.info(f"User: {weather_message}") - + weather_response = weather_agent.run(weather_message, thread=weather_thread) logger.info(f"WeatherAgent: {weather_response.text} \n") - + logger.debug("Testing MathAgent") - + # Get reference to MathAgent math_agent = agent_client.get_agent("MathAgent") math_thread = math_agent.get_new_thread() - + logger.debug(f"Created math conversation thread: {math_thread.session_id}") - + # Test MathAgent math_message = "Calculate a 20% tip on a $50 bill" logger.info(f"User: {math_message}") - + math_response = math_agent.run(math_message, thread=math_thread) logger.info(f"MathAgent: {math_response.text} \n") - + logger.debug("Both agents completed successfully!") async def main() -> None: """Main entry point for the client application.""" logger.debug("Starting Durable Task Multi-Agent Client...") - + # Create client using helper function agent_client = get_client() - + try: run_client(agent_client) except Exception as e: diff --git a/python/samples/getting_started/durabletask/02_multi_agent/sample.py b/python/samples/getting_started/durabletask/02_multi_agent/sample.py index 9945601c20..17475ca06a 100644 --- a/python/samples/getting_started/durabletask/02_multi_agent/sample.py +++ b/python/samples/getting_started/durabletask/02_multi_agent/sample.py @@ -15,10 +15,9 @@ import logging -from dotenv import load_dotenv - # Import helper functions from worker and client modules from client import get_client, run_client +from dotenv import load_dotenv from worker import get_worker, setup_worker # Configure logging @@ -29,26 +28,26 @@ def main(): """Main entry point - runs both worker and client in single process.""" logger.debug("Starting Durable Task Multi-Agent Sample (Combined Worker + Client)...") - + silent_handler = logging.NullHandler() # Create and start the worker using helper function and context manager with get_worker(log_handler=silent_handler) as dts_worker: # Register agents using helper function setup_worker(dts_worker) - + # Start the worker dts_worker.start() logger.debug("Worker started and listening for requests...") - + # Create the client using helper function agent_client = get_client(log_handler=silent_handler) - + try: # Run client interactions using helper function run_client(agent_client) except Exception as e: logger.exception(f"Error during agent interaction: {e}") - + logger.debug("Sample completed. Worker shutting down...") diff --git a/python/samples/getting_started/durabletask/02_multi_agent/worker.py b/python/samples/getting_started/durabletask/02_multi_agent/worker.py index b0e51541b9..968d8fc997 100644 --- a/python/samples/getting_started/durabletask/02_multi_agent/worker.py +++ b/python/samples/getting_started/durabletask/02_multi_agent/worker.py @@ -101,12 +101,12 @@ def get_worker( """ taskhub_name = taskhub or os.getenv("TASKHUB", "default") endpoint_url = endpoint or os.getenv("ENDPOINT", "http://localhost:8080") - + logger.debug(f"Using taskhub: {taskhub_name}") logger.debug(f"Using endpoint: {endpoint_url}") - + credential = None if endpoint_url == "http://localhost:8080" else DefaultAzureCredential() - + return DurableTaskSchedulerWorker( host_address=endpoint_url, secure_channel=endpoint_url != "http://localhost:8080", @@ -127,43 +127,43 @@ def setup_worker(worker: DurableTaskSchedulerWorker) -> DurableAIAgentWorker: """ # Wrap it with the agent worker agent_worker = DurableAIAgentWorker(worker) - + # Create and register both agents logger.debug("Creating and registering agents...") weather_agent = create_weather_agent() math_agent = create_math_agent() - + agent_worker.add_agent(weather_agent) agent_worker.add_agent(math_agent) - + logger.debug(f"✓ Registered agents: {weather_agent.name}, {math_agent.name}") - + return agent_worker async def main(): """Main entry point for the worker process.""" logger.debug("Starting Durable Task Multi-Agent Worker...") - + # Create a worker using the helper function worker = get_worker() - + # Setup worker with agents setup_worker(worker) - + logger.info("Worker is ready and listening for requests...") logger.info("Press Ctrl+C to stop. \n") - + try: # Start the worker (this blocks until stopped) worker.start() - + # Keep the worker running while True: await asyncio.sleep(1) except KeyboardInterrupt: logger.debug("Worker shutdown initiated") - + logger.info("Worker stopped") diff --git a/python/samples/getting_started/durabletask/03_single_agent_streaming/client.py b/python/samples/getting_started/durabletask/03_single_agent_streaming/client.py index 92c941d766..c017829dfb 100644 --- a/python/samples/getting_started/durabletask/03_single_agent_streaming/client.py +++ b/python/samples/getting_started/durabletask/03_single_agent_streaming/client.py @@ -23,7 +23,6 @@ from agent_framework.azure import DurableAIAgentClient from azure.identity import DefaultAzureCredential from durabletask.azuremanaged.client import DurableTaskSchedulerClient - from redis_stream_response_handler import RedisStreamResponseHandler # Configure logging @@ -71,12 +70,12 @@ def get_client( """ taskhub_name = taskhub or os.getenv("TASKHUB", "default") endpoint_url = endpoint or os.getenv("ENDPOINT", "http://localhost:8080") - + logger.debug(f"Using taskhub: {taskhub_name}") logger.debug(f"Using endpoint: {endpoint_url}") - + credential = None if endpoint_url == "http://localhost:8080" else DefaultAzureCredential() - + dts_client = DurableTaskSchedulerClient( host_address=endpoint_url, secure_channel=endpoint_url != "http://localhost:8080", @@ -84,7 +83,7 @@ def get_client( token_credential=credential, log_handler=log_handler ) - + return DurableAIAgentClient(dts_client) @@ -100,33 +99,33 @@ async def stream_from_redis(thread_id: str, cursor: str | None = None) -> None: logger.debug(f"To manually check Redis, run: redis-cli XLEN {stream_key}") if cursor: logger.info(f"Resuming from cursor: {cursor}") - + async with await get_stream_handler() as stream_handler: - logger.info(f"Stream handler created, starting to read...") + logger.info("Stream handler created, starting to read...") try: chunk_count = 0 async for chunk in stream_handler.read_stream(thread_id, cursor): chunk_count += 1 logger.debug(f"Received chunk #{chunk_count}: error={chunk.error}, is_done={chunk.is_done}, text_len={len(chunk.text) if chunk.text else 0}") - + if chunk.error: logger.error(f"Stream error: {chunk.error}") break - + if chunk.is_done: print("\n✓ Response complete!", flush=True) logger.info(f"Stream completed after {chunk_count} chunks") break - + if chunk.text: # Print directly to console with flush for immediate display - print(chunk.text, end='', flush=True) - + print(chunk.text, end="", flush=True) + if chunk_count == 0: logger.warning("No chunks received from Redis stream!") logger.warning(f"Check Redis manually: redis-cli XLEN {stream_key}") logger.warning(f"View stream contents: redis-cli XREAD STREAMS {stream_key} 0") - + except Exception as ex: logger.error(f"Error reading from Redis: {ex}", exc_info=True) @@ -140,47 +139,47 @@ def run_client(agent_client: DurableAIAgentClient) -> None: # Get a reference to the TravelPlanner agent logger.debug("Getting reference to TravelPlanner agent...") travel_planner = agent_client.get_agent("TravelPlanner") - + # Create a new thread for the conversation thread = travel_planner.get_new_thread() if not thread.session_id: logger.error("Failed to create a new thread with session ID!") return - + key = thread.session_id.key logger.info(f"Thread ID: {key}") - + # Get user input print("\nEnter your travel planning request:") user_message = input("> ").strip() - + if not user_message: logger.warning("No input provided. Using default message.") user_message = "Plan a 3-day trip to Tokyo with emphasis on culture and food" - + logger.info(f"\nYou: {user_message}\n") logger.info("TravelPlanner (streaming from Redis):") logger.info("-" * 80) - + # Start the agent run with wait_for_response=False for non-blocking execution # This signals the agent to start processing without waiting for completion # The agent will execute in the background and write chunks to Redis travel_planner.run(user_message, thread=thread, options={"wait_for_response": False}) - + # Stream the response from Redis # This demonstrates that the client can stream from Redis while # the agent is still processing (or after it completes) asyncio.run(stream_from_redis(str(key))) - + logger.info("\nDemo completed!") if __name__ == "__main__": from dotenv import load_dotenv load_dotenv() - + # Create the client client = get_client() - + # Run the demo run_client(client) diff --git a/python/samples/getting_started/durabletask/03_single_agent_streaming/redis_stream_response_handler.py b/python/samples/getting_started/durabletask/03_single_agent_streaming/redis_stream_response_handler.py index 981393cf00..4a3298df50 100644 --- a/python/samples/getting_started/durabletask/03_single_agent_streaming/redis_stream_response_handler.py +++ b/python/samples/getting_started/durabletask/03_single_agent_streaming/redis_stream_response_handler.py @@ -8,9 +8,9 @@ import asyncio import time +from collections.abc import AsyncIterator from dataclasses import dataclass from datetime import timedelta -from collections.abc import AsyncIterator import redis.asyncio as aioredis diff --git a/python/samples/getting_started/durabletask/03_single_agent_streaming/sample.py b/python/samples/getting_started/durabletask/03_single_agent_streaming/sample.py index 14de97caf8..e6d77c6785 100644 --- a/python/samples/getting_started/durabletask/03_single_agent_streaming/sample.py +++ b/python/samples/getting_started/durabletask/03_single_agent_streaming/sample.py @@ -20,40 +20,40 @@ import logging -from dotenv import load_dotenv - # Import helper functions from worker and client modules from client import get_client, run_client +from dotenv import load_dotenv from worker import get_worker, setup_worker # Configure logging (must be after imports to override their basicConfig) logging.basicConfig(level=logging.INFO, force=True) logger = logging.getLogger(__name__) + def main(): """Main entry point - runs both worker and client in single process.""" logger.debug("Starting Durable Task Agent Sample with Redis Streaming...") silent_handler = logging.NullHandler() - + # Create and start the worker using helper function and context manager with get_worker(log_handler=silent_handler) as dts_worker: # Register agents and callbacks using helper function setup_worker(dts_worker) - + # Start the worker dts_worker.start() logger.debug("Worker started and listening for requests...") - + # Create the client using helper function agent_client = get_client(log_handler=silent_handler) - + try: # Run client interactions using helper function run_client(agent_client) except Exception as e: logger.exception(f"Error during agent interaction: {e}") - + logger.debug("Sample completed. Worker shutting down...") diff --git a/python/samples/getting_started/durabletask/03_single_agent_streaming/tools.py b/python/samples/getting_started/durabletask/03_single_agent_streaming/tools.py index 6a71fdfa03..29be74a846 100644 --- a/python/samples/getting_started/durabletask/03_single_agent_streaming/tools.py +++ b/python/samples/getting_started/durabletask/03_single_agent_streaming/tools.py @@ -153,13 +153,12 @@ def _get_weather_recommendation(condition: str) -> str: if "rain" in condition_lower or "drizzle" in condition_lower: return "Bring an umbrella and waterproof jacket. Consider indoor activities for backup." - elif "fog" in condition_lower: + if "fog" in condition_lower: return "Morning visibility may be limited. Plan outdoor sightseeing for afternoon." - elif "cold" in condition_lower: + if "cold" in condition_lower: return "Layer up with warm clothing. Hot drinks and cozy cafés recommended." - elif "hot" in condition_lower or "warm" in condition_lower: + if "hot" in condition_lower or "warm" in condition_lower: return "Stay hydrated and use sunscreen. Plan strenuous activities for cooler morning hours." - elif "thunder" in condition_lower or "storm" in condition_lower: + if "thunder" in condition_lower or "storm" in condition_lower: return "Keep an eye on weather updates. Have indoor alternatives ready." - else: - return "Pleasant conditions expected. Great day for outdoor exploration!" + return "Pleasant conditions expected. Great day for outdoor exploration!" diff --git a/python/samples/getting_started/durabletask/03_single_agent_streaming/worker.py b/python/samples/getting_started/durabletask/03_single_agent_streaming/worker.py index 1ca37ff607..318b222e54 100644 --- a/python/samples/getting_started/durabletask/03_single_agent_streaming/worker.py +++ b/python/samples/getting_started/durabletask/03_single_agent_streaming/worker.py @@ -27,7 +27,6 @@ ) from azure.identity import AzureCliCredential, DefaultAzureCredential from durabletask.azuremanaged.worker import DurableTaskSchedulerWorker - from redis_stream_response_handler import RedisStreamResponseHandler from tools import get_local_events, get_weather_forecast @@ -186,12 +185,12 @@ def get_worker( """ taskhub_name = taskhub or os.getenv("TASKHUB", "default") endpoint_url = endpoint or os.getenv("ENDPOINT", "http://localhost:8080") - + logger.debug(f"Using taskhub: {taskhub_name}") logger.debug(f"Using endpoint: {endpoint_url}") - + credential = None if endpoint_url == "http://localhost:8080" else DefaultAzureCredential() - + return DurableTaskSchedulerWorker( host_address=endpoint_url, secure_channel=endpoint_url != "http://localhost:8080", @@ -212,34 +211,34 @@ def setup_worker(worker: DurableTaskSchedulerWorker) -> DurableAIAgentWorker: """ # Create the Redis streaming callback redis_callback = RedisStreamCallback() - + # Wrap it with the agent worker agent_worker = DurableAIAgentWorker(worker, callback=redis_callback) - + # Create and register the TravelPlanner agent logger.debug("Creating and registering TravelPlanner agent...") travel_agent = create_travel_agent() agent_worker.add_agent(travel_agent) - + logger.debug(f"✓ Registered agent: {travel_agent.name}") - + return agent_worker async def main(): """Main entry point for the worker process.""" logger.debug("Starting Durable Task Agent Worker with Redis Streaming...") - + # Create a worker using the helper function worker = get_worker() - + # Setup worker with agent and callback setup_worker(worker) - + # Start the worker logger.debug("Worker started and listening for requests...") worker.start() - + try: # Keep the worker running while True: diff --git a/python/samples/getting_started/durabletask/04_single_agent_orchestration_chaining/client.py b/python/samples/getting_started/durabletask/04_single_agent_orchestration_chaining/client.py index 23ac266b36..d9eb12c369 100644 --- a/python/samples/getting_started/durabletask/04_single_agent_orchestration_chaining/client.py +++ b/python/samples/getting_started/durabletask/04_single_agent_orchestration_chaining/client.py @@ -41,12 +41,12 @@ def get_client( """ taskhub_name = taskhub or os.getenv("TASKHUB", "default") endpoint_url = endpoint or os.getenv("ENDPOINT", "http://localhost:8080") - + logger.debug(f"Using taskhub: {taskhub_name}") logger.debug(f"Using endpoint: {endpoint_url}") - + credential = None if endpoint_url == "http://localhost:8080" else DefaultAzureCredential() - + return DurableTaskSchedulerClient( host_address=endpoint_url, secure_channel=endpoint_url != "http://localhost:8080", @@ -63,32 +63,32 @@ def run_client(client: DurableTaskSchedulerClient) -> None: client: The DurableTaskSchedulerClient instance """ logger.debug("Starting single agent chaining orchestration...") - + # Start the orchestration instance_id = client.schedule_new_orchestration( # type: ignore orchestrator="single_agent_chaining_orchestration", input="", ) - + logger.info(f"Orchestration started with instance ID: {instance_id}") logger.debug("Waiting for orchestration to complete...") - + # Retrieve the final state metadata = client.wait_for_orchestration_completion( instance_id=instance_id, timeout=300 ) - + if metadata and metadata.runtime_status.name == "COMPLETED": result = metadata.serialized_output - + logger.debug("Orchestration completed successfully!") - + # Parse and display the result if result: final_text = json.loads(result) logger.info("Final refined sentence: %s \n", final_text) - + elif metadata: logger.error(f"Orchestration ended with status: {metadata.runtime_status.name}") if metadata.serialized_output: @@ -100,10 +100,10 @@ def run_client(client: DurableTaskSchedulerClient) -> None: async def main() -> None: """Main entry point for the client application.""" logger.debug("Starting Durable Task Single Agent Chaining Orchestration Client...") - + # Create client using helper function client = get_client() - + try: run_client(client) except Exception as e: diff --git a/python/samples/getting_started/durabletask/04_single_agent_orchestration_chaining/sample.py b/python/samples/getting_started/durabletask/04_single_agent_orchestration_chaining/sample.py index 208c223f5e..d09421c6b4 100644 --- a/python/samples/getting_started/durabletask/04_single_agent_orchestration_chaining/sample.py +++ b/python/samples/getting_started/durabletask/04_single_agent_orchestration_chaining/sample.py @@ -21,10 +21,9 @@ import logging -from dotenv import load_dotenv - # Import helper functions from worker and client modules from client import get_client, run_client +from dotenv import load_dotenv from worker import get_worker, setup_worker # Configure logging @@ -35,22 +34,22 @@ def main(): """Main entry point - runs both worker and client in single process.""" logger.debug("Starting Single Agent Orchestration Chaining Sample...") - + silent_handler = logging.NullHandler() # Create and start the worker using helper function and context manager with get_worker(log_handler=silent_handler) as dts_worker: # Register agents and orchestrations using helper function setup_worker(dts_worker) - + # Start the worker dts_worker.start() logger.debug("Worker started and listening for requests...") - + # Create the client using helper function client = get_client(log_handler=silent_handler) - + logger.debug("CLIENT: Starting orchestration...") - + # Run the client in the same process try: run_client(client) @@ -60,7 +59,7 @@ def main(): logger.exception(f"Error during orchestration: {e}") finally: logger.debug("Worker stopping...") - + logger.debug("") logger.debug("Sample completed") diff --git a/python/samples/getting_started/durabletask/04_single_agent_orchestration_chaining/worker.py b/python/samples/getting_started/durabletask/04_single_agent_orchestration_chaining/worker.py index 321a5f1149..18c2fed8e3 100644 --- a/python/samples/getting_started/durabletask/04_single_agent_orchestration_chaining/worker.py +++ b/python/samples/getting_started/durabletask/04_single_agent_orchestration_chaining/worker.py @@ -11,15 +11,15 @@ """ import asyncio -from collections.abc import Generator import logging import os +from collections.abc import Generator from agent_framework import AgentResponse, ChatAgent from agent_framework.azure import AzureOpenAIChatClient, DurableAIAgentOrchestrationContext, DurableAIAgentWorker from azure.identity import AzureCliCredential, DefaultAzureCredential -from durabletask.task import OrchestrationContext, Task from durabletask.azuremanaged.worker import DurableTaskSchedulerWorker +from durabletask.task import OrchestrationContext, Task # Configure logging logging.basicConfig(level=logging.INFO) @@ -42,7 +42,7 @@ def create_writer_agent() -> "ChatAgent": "You refine short pieces of text. When given an initial sentence you enhance it;\n" "when given an improved sentence you polish it further." ) - + return AzureOpenAIChatClient(credential=AzureCliCredential()).as_agent( name=WRITER_AGENT_NAME, instructions=instructions, @@ -78,18 +78,18 @@ def single_agent_chaining_orchestration( str: The final refined text from the second agent run """ logger.debug("[Orchestration] Starting single agent chaining...") - + # Wrap the orchestration context to access agents agent_context = DurableAIAgentOrchestrationContext(context) - + # Get the writer agent using the agent context writer = agent_context.get_agent(WRITER_AGENT_NAME) - + # Create a new thread for the conversation - this will be shared across both runs writer_thread = writer.get_new_thread() - + logger.debug(f"[Orchestration] Created thread: {writer_thread.session_id}") - + prompt = "Write a concise inspirational sentence about learning." # First run: Generate an initial inspirational sentence logger.info("[Orchestration] First agent run: Generating initial sentence about: %s", prompt) @@ -98,21 +98,21 @@ def single_agent_chaining_orchestration( thread=writer_thread, ) logger.info(f"[Orchestration] Initial response: {initial_response.text}") - + # Second run: Refine the initial response on the same thread improved_prompt = ( f"Improve this further while keeping it under 25 words: " f"{initial_response.text}" ) - + logger.info("[Orchestration] Second agent run: Refining the sentence: %s", improved_prompt) refined_response = yield writer.run( messages=improved_prompt, thread=writer_thread, ) - + logger.info(f"[Orchestration] Refined response: {refined_response.text}") - + logger.debug("[Orchestration] Chaining complete") return refined_response.text @@ -134,12 +134,12 @@ def get_worker( """ taskhub_name = taskhub or os.getenv("TASKHUB", "default") endpoint_url = endpoint or os.getenv("ENDPOINT", "http://localhost:8080") - + logger.debug(f"Using taskhub: {taskhub_name}") logger.debug(f"Using endpoint: {endpoint_url}") - + credential = None if endpoint_url == "http://localhost:8080" else DefaultAzureCredential() - + return DurableTaskSchedulerWorker( host_address=endpoint_url, secure_channel=endpoint_url != "http://localhost:8080", @@ -160,45 +160,45 @@ def setup_worker(worker: DurableTaskSchedulerWorker) -> DurableAIAgentWorker: """ # Wrap it with the agent worker agent_worker = DurableAIAgentWorker(worker) - + # Create and register the Writer agent logger.debug("Creating and registering Writer agent...") writer_agent = create_writer_agent() agent_worker.add_agent(writer_agent) - + logger.debug(f"✓ Registered agent: {writer_agent.name}") - + # Register the orchestration function logger.debug("Registering orchestration function...") worker.add_orchestrator(single_agent_chaining_orchestration) # type: ignore logger.debug(f"✓ Registered orchestration: {single_agent_chaining_orchestration.__name__}") - + return agent_worker async def main(): """Main entry point for the worker process.""" logger.debug("Starting Durable Task Single Agent Chaining Worker with Orchestration...") - + # Create a worker using the helper function worker = get_worker() - + # Setup worker with agents and orchestrations setup_worker(worker) - + logger.debug("Worker is ready and listening for requests...") logger.debug("Press Ctrl+C to stop.") - + try: # Start the worker (this blocks until stopped) worker.start() - + # Keep the worker running while True: await asyncio.sleep(1) except KeyboardInterrupt: logger.debug("Worker shutdown initiated") - + logger.debug("Worker stopped") diff --git a/python/samples/getting_started/durabletask/05_multi_agent_orchestration_concurrency/client.py b/python/samples/getting_started/durabletask/05_multi_agent_orchestration_concurrency/client.py index f3e92c9fb9..f3d2ee8819 100644 --- a/python/samples/getting_started/durabletask/05_multi_agent_orchestration_concurrency/client.py +++ b/python/samples/getting_started/durabletask/05_multi_agent_orchestration_concurrency/client.py @@ -41,12 +41,12 @@ def get_client( """ taskhub_name = taskhub or os.getenv("TASKHUB", "default") endpoint_url = endpoint or os.getenv("ENDPOINT", "http://localhost:8080") - + logger.debug(f"Using taskhub: {taskhub_name}") logger.debug(f"Using endpoint: {endpoint_url}") - + credential = None if endpoint_url == "http://localhost:8080" else DefaultAzureCredential() - + return DurableTaskSchedulerClient( host_address=endpoint_url, secure_channel=endpoint_url != "http://localhost:8080", @@ -68,25 +68,25 @@ def run_client(client: DurableTaskSchedulerClient, prompt: str = "What is temper orchestrator="multi_agent_concurrent_orchestration", input=prompt, ) - + logger.info(f"Orchestration started with instance ID: {instance_id}") logger.debug("Waiting for orchestration to complete...") - + # Retrieve the final state metadata = client.wait_for_orchestration_completion( instance_id=instance_id, ) - + if metadata and metadata.runtime_status.name == "COMPLETED": result = metadata.serialized_output - + logger.debug("Orchestration completed successfully!") - + # Parse and display the result if result: result_json = json.loads(result) if isinstance(result, str) else result logger.info("Orchestration Results:\n%s", json.dumps(result_json, indent=2)) - + elif metadata: logger.error(f"Orchestration ended with status: {metadata.runtime_status.name}") if metadata.serialized_output: @@ -98,10 +98,10 @@ def run_client(client: DurableTaskSchedulerClient, prompt: str = "What is temper async def main() -> None: """Main entry point for the client application.""" logger.debug("Starting Durable Task Multi-Agent Orchestration Client...") - + # Create client using helper function client = get_client() - + try: run_client(client) except Exception as e: diff --git a/python/samples/getting_started/durabletask/05_multi_agent_orchestration_concurrency/sample.py b/python/samples/getting_started/durabletask/05_multi_agent_orchestration_concurrency/sample.py index ca80aa043e..02ee48c52f 100644 --- a/python/samples/getting_started/durabletask/05_multi_agent_orchestration_concurrency/sample.py +++ b/python/samples/getting_started/durabletask/05_multi_agent_orchestration_concurrency/sample.py @@ -18,10 +18,9 @@ import logging -from dotenv import load_dotenv - # Import helper functions from worker and client modules from client import get_client, run_client +from dotenv import load_dotenv from worker import get_worker, setup_worker # Configure logging @@ -32,20 +31,20 @@ def main(): """Main entry point - runs both worker and client in single process.""" logger.debug("Starting Durable Task Multi-Agent Orchestration Sample (Combined Worker + Client)...") - + silent_handler = logging.NullHandler() # Create and start the worker using helper function and context manager with get_worker(log_handler=silent_handler) as dts_worker: # Register agents and orchestrations using helper function setup_worker(dts_worker) - + # Start the worker dts_worker.start() logger.debug("Worker started and listening for requests...") - + # Create the client using helper function client = get_client(log_handler=silent_handler) - + # Define the prompt prompt = "What is temperature?" logger.debug("CLIENT: Starting orchestration...") @@ -55,7 +54,7 @@ def main(): run_client(client, prompt) except Exception as e: logger.exception(f"Error during sample execution: {e}") - + logger.debug("Sample completed. Worker shutting down...") diff --git a/python/samples/getting_started/durabletask/05_multi_agent_orchestration_concurrency/worker.py b/python/samples/getting_started/durabletask/05_multi_agent_orchestration_concurrency/worker.py index 41b4bd8dda..bae292af0a 100644 --- a/python/samples/getting_started/durabletask/05_multi_agent_orchestration_concurrency/worker.py +++ b/python/samples/getting_started/durabletask/05_multi_agent_orchestration_concurrency/worker.py @@ -11,16 +11,16 @@ """ import asyncio -from collections.abc import Generator import logging import os +from collections.abc import Generator from typing import Any from agent_framework import AgentResponse, ChatAgent from agent_framework.azure import AzureOpenAIChatClient, DurableAIAgentOrchestrationContext, DurableAIAgentWorker from azure.identity import AzureCliCredential, DefaultAzureCredential -from durabletask.task import OrchestrationContext, when_all, Task from durabletask.azuremanaged.worker import DurableTaskSchedulerWorker +from durabletask.task import OrchestrationContext, Task, when_all # Configure logging logging.basicConfig(level=logging.INFO) @@ -68,44 +68,44 @@ def multi_agent_concurrent_orchestration(context: OrchestrationContext, prompt: Returns: dict: Dictionary with 'physicist' and 'chemist' response texts """ - + logger.info(f"[Orchestration] Starting concurrent execution for prompt: {prompt}") - + # Wrap the orchestration context to access agents agent_context = DurableAIAgentOrchestrationContext(context) - + # Get agents using the agent context (returns DurableAIAgent proxies) physicist = agent_context.get_agent(PHYSICIST_AGENT_NAME) chemist = agent_context.get_agent(CHEMIST_AGENT_NAME) - + # Create separate threads for each agent physicist_thread = physicist.get_new_thread() chemist_thread = chemist.get_new_thread() - + logger.debug(f"[Orchestration] Created threads - Physicist: {physicist_thread.session_id}, Chemist: {chemist_thread.session_id}") - + # Create tasks from agent.run() calls - these return DurableAgentTask instances physicist_task = physicist.run(messages=str(prompt), thread=physicist_thread) chemist_task = chemist.run(messages=str(prompt), thread=chemist_thread) - + logger.debug("[Orchestration] Created agent tasks, executing concurrently...") - + # Execute both tasks concurrently using when_all # The DurableAgentTask instances wrap the underlying entity calls task_results = yield when_all([physicist_task, chemist_task]) - + logger.debug("[Orchestration] Both agents completed") - + # Extract results from the tasks - DurableAgentTask yields AgentResponse physicist_result: AgentResponse = task_results[0] chemist_result: AgentResponse = task_results[1] - + result = { "physicist": physicist_result.text, "chemist": chemist_result.text, } - - logger.debug(f"[Orchestration] Aggregated results ready") + + logger.debug("[Orchestration] Aggregated results ready") return result @@ -126,12 +126,12 @@ def get_worker( """ taskhub_name = taskhub or os.getenv("TASKHUB", "default") endpoint_url = endpoint or os.getenv("ENDPOINT", "http://localhost:8080") - + logger.debug(f"Using taskhub: {taskhub_name}") logger.debug(f"Using endpoint: {endpoint_url}") - + credential = None if endpoint_url == "http://localhost:8080" else DefaultAzureCredential() - + return DurableTaskSchedulerWorker( host_address=endpoint_url, secure_channel=endpoint_url != "http://localhost:8080", @@ -152,48 +152,48 @@ def setup_worker(worker: DurableTaskSchedulerWorker) -> DurableAIAgentWorker: """ # Wrap it with the agent worker agent_worker = DurableAIAgentWorker(worker) - + # Create and register both agents logger.debug("Creating and registering agents...") physicist_agent = create_physicist_agent() chemist_agent = create_chemist_agent() - + agent_worker.add_agent(physicist_agent) agent_worker.add_agent(chemist_agent) - + logger.debug(f"✓ Registered agents: {physicist_agent.name}, {chemist_agent.name}") - + # Register the orchestration function logger.debug("Registering orchestration function...") worker.add_orchestrator(multi_agent_concurrent_orchestration) # type: ignore logger.debug(f"✓ Registered orchestration: {multi_agent_concurrent_orchestration.__name__}") - + return agent_worker async def main(): """Main entry point for the worker process.""" logger.debug("Starting Durable Task Multi-Agent Worker with Orchestration...") - + # Create a worker using the helper function worker = get_worker() - + # Setup worker with agents and orchestrations setup_worker(worker) - + logger.debug("Worker is ready and listening for requests...") logger.debug("Press Ctrl+C to stop.") - + try: # Start the worker (this blocks until stopped) worker.start() - + # Keep the worker running while True: await asyncio.sleep(1) except KeyboardInterrupt: logger.debug("Worker shutdown initiated") - + logger.debug("Worker stopped") diff --git a/python/samples/getting_started/durabletask/06_multi_agent_orchestration_conditionals/client.py b/python/samples/getting_started/durabletask/06_multi_agent_orchestration_conditionals/client.py index 58d4ecc1e8..a0f7f6072c 100644 --- a/python/samples/getting_started/durabletask/06_multi_agent_orchestration_conditionals/client.py +++ b/python/samples/getting_started/durabletask/06_multi_agent_orchestration_conditionals/client.py @@ -39,12 +39,12 @@ def get_client( """ taskhub_name = taskhub or os.getenv("TASKHUB", "default") endpoint_url = endpoint or os.getenv("ENDPOINT", "http://localhost:8080") - + logger.debug(f"Using taskhub: {taskhub_name}") logger.debug(f"Using endpoint: {endpoint_url}") - + credential = None if endpoint_url == "http://localhost:8080" else DefaultAzureCredential() - + return DurableTaskSchedulerClient( host_address=endpoint_url, secure_channel=endpoint_url != "http://localhost:8080", @@ -70,36 +70,36 @@ def run_client( "email_id": email_id, "email_content": email_content, } - + logger.debug("Starting spam detection orchestration...") - + # Start the orchestration with the email payload instance_id = client.schedule_new_orchestration( # type: ignore orchestrator="spam_detection_orchestration", input=payload, ) - + logger.debug(f"Orchestration started with instance ID: {instance_id}") logger.debug("Waiting for orchestration to complete...") - + # Retrieve the final state metadata = client.wait_for_orchestration_completion( instance_id=instance_id, timeout=300 ) - + if metadata and metadata.runtime_status.name == "COMPLETED": result = metadata.serialized_output - + logger.debug("Orchestration completed successfully!") - + # Parse and display the result if result: # Remove quotes if present if result.startswith('"') and result.endswith('"'): result = result[1:-1] logger.info(f"Result: {result}") - + elif metadata: logger.error(f"Orchestration ended with status: {metadata.runtime_status.name}") if metadata.serialized_output: @@ -111,29 +111,29 @@ def run_client( async def main() -> None: """Main entry point for the client application.""" logger.debug("Starting Durable Task Spam Detection Orchestration Client...") - + # Create client using helper function client = get_client() - + try: # Test with a legitimate email logger.info("TEST 1: Legitimate Email") - + run_client( client, email_id="email-001", email_content="Hello! I wanted to reach out about our upcoming project meeting scheduled for next week." ) - + # Test with a spam email logger.info("TEST 2: Spam Email") - + run_client( client, email_id="email-002", email_content="URGENT! You've won $1,000,000! Click here now to claim your prize! Limited time offer! Don't miss out!" ) - + except Exception as e: logger.exception(f"Error during orchestration: {e}") finally: diff --git a/python/samples/getting_started/durabletask/06_multi_agent_orchestration_conditionals/sample.py b/python/samples/getting_started/durabletask/06_multi_agent_orchestration_conditionals/sample.py index d8e9d0a4b3..479158dea7 100644 --- a/python/samples/getting_started/durabletask/06_multi_agent_orchestration_conditionals/sample.py +++ b/python/samples/getting_started/durabletask/06_multi_agent_orchestration_conditionals/sample.py @@ -18,10 +18,9 @@ import logging -from dotenv import load_dotenv - # Import helper functions from worker and client modules from client import get_client, run_client +from dotenv import load_dotenv from worker import get_worker, setup_worker logging.basicConfig( @@ -34,43 +33,43 @@ def main(): """Main entry point - runs both worker and client in single process.""" logger.debug("Starting Durable Task Spam Detection Orchestration Sample (Combined Worker + Client)...") - + silent_handler = logging.NullHandler() # Create and start the worker using helper function and context manager with get_worker(log_handler=silent_handler) as dts_worker: # Register agents, orchestrations, and activities using helper function setup_worker(dts_worker) - + # Start the worker dts_worker.start() logger.debug("Worker started and listening for requests...") - + # Create the client using helper function client = get_client(log_handler=silent_handler) logger.debug("CLIENT: Starting orchestration tests...") - + try: # Test 1: Legitimate email # logger.info("TEST 1: Legitimate Email") - + run_client( client, email_id="email-001", email_content="Hello! I wanted to reach out about our upcoming project meeting scheduled for next week." ) - + # Test 2: Spam email logger.info("TEST 2: Spam Email") - + run_client( client, email_id="email-002", email_content="URGENT! You've won $1,000,000! Click here now to claim your prize! Limited time offer! Don't miss out!" ) - + except Exception as e: logger.exception(f"Error during sample execution: {e}") - + logger.debug("Sample completed. Worker shutting down...") diff --git a/python/samples/getting_started/durabletask/06_multi_agent_orchestration_conditionals/worker.py b/python/samples/getting_started/durabletask/06_multi_agent_orchestration_conditionals/worker.py index 78ac71ce8a..5bea536867 100644 --- a/python/samples/getting_started/durabletask/06_multi_agent_orchestration_conditionals/worker.py +++ b/python/samples/getting_started/durabletask/06_multi_agent_orchestration_conditionals/worker.py @@ -11,16 +11,16 @@ """ import asyncio -from collections.abc import Generator import logging import os +from collections.abc import Generator from typing import Any, cast from agent_framework import AgentResponse, ChatAgent from agent_framework.azure import AzureOpenAIChatClient, DurableAIAgentOrchestrationContext, DurableAIAgentWorker from azure.identity import AzureCliCredential, DefaultAzureCredential -from durabletask.task import ActivityContext, OrchestrationContext, Task from durabletask.azuremanaged.worker import DurableTaskSchedulerWorker +from durabletask.task import ActivityContext, OrchestrationContext, Task from pydantic import BaseModel, ValidationError # Configure logging @@ -118,24 +118,24 @@ def spam_detection_orchestration(context: OrchestrationContext, payload_raw: Any str: Result message from activity functions """ logger.debug("[Orchestration] Starting spam detection orchestration") - + # Validate input if not isinstance(payload_raw, dict): raise ValueError("Email data is required") - + try: payload = EmailPayload.model_validate(payload_raw) except ValidationError as exc: raise ValueError(f"Invalid email payload: {exc}") from exc - + logger.debug(f"[Orchestration] Processing email ID: {payload.email_id}") - + # Wrap the orchestration context to access agents agent_context = DurableAIAgentOrchestrationContext(context) - + # Get spam detection agent spam_agent = agent_context.get_agent(SPAM_AGENT_NAME) - + # Run spam detection spam_prompt = ( "Analyze this email for spam content and return a JSON response with 'is_spam' (boolean) " @@ -143,52 +143,52 @@ def spam_detection_orchestration(context: OrchestrationContext, payload_raw: Any f"Email ID: {payload.email_id}\n" f"Content: {payload.email_content}" ) - + logger.info("[Orchestration] Running spam detection agent: %s", spam_prompt) spam_result_task = spam_agent.run( messages=spam_prompt, options={"response_format": SpamDetectionResult}, ) - + spam_result_raw: AgentResponse = yield spam_result_task spam_result = cast(SpamDetectionResult, spam_result_raw.value) - + logger.info("[Orchestration] Spam detection result: is_spam=%s", spam_result.is_spam) - + # Branch based on spam detection result if spam_result.is_spam: logger.debug("[Orchestration] Email is spam, handling...") result_task: Task[str] = context.call_activity("handle_spam_email", input=spam_result.reason) result: str = yield result_task return result - + # Email is legitimate - draft a response logger.debug("[Orchestration] Email is legitimate, drafting response...") - + email_agent = agent_context.get_agent(EMAIL_AGENT_NAME) - + email_prompt = ( "Draft a professional response to this email. Return a JSON response with a 'response' field " "containing the reply:\n\n" f"Email ID: {payload.email_id}\n" f"Content: {payload.email_content}" ) - + logger.info("[Orchestration] Running email assistant agent: %s", email_prompt) email_result_task = email_agent.run( messages=email_prompt, options={"response_format": EmailResponse}, ) - + email_result_raw: AgentResponse = yield email_result_task email_result = cast(EmailResponse, email_result_raw.value) - + logger.debug("[Orchestration] Email response drafted, sending...") result_task: Task[str] = context.call_activity("send_email", input=email_result.response) result: str = yield result_task logger.info("Sent Email: %s", result) - + return result @@ -209,12 +209,12 @@ def get_worker( """ taskhub_name = taskhub or os.getenv("TASKHUB", "default") endpoint_url = endpoint or os.getenv("ENDPOINT", "http://localhost:8080") - + logger.debug(f"Using taskhub: {taskhub_name}") logger.debug(f"Using endpoint: {endpoint_url}") - + credential = None if endpoint_url == "http://localhost:8080" else DefaultAzureCredential() - + return DurableTaskSchedulerWorker( host_address=endpoint_url, secure_channel=endpoint_url != "http://localhost:8080", @@ -235,55 +235,55 @@ def setup_worker(worker: DurableTaskSchedulerWorker) -> DurableAIAgentWorker: """ # Wrap it with the agent worker agent_worker = DurableAIAgentWorker(worker) - + # Create and register both agents logger.debug("Creating and registering agents...") spam_agent = create_spam_agent() email_agent = create_email_agent() - + agent_worker.add_agent(spam_agent) agent_worker.add_agent(email_agent) - + logger.debug(f"✓ Registered agents: {spam_agent.name}, {email_agent.name}") - + # Register activity functions logger.debug("Registering activity functions...") worker.add_activity(handle_spam_email) # type: ignore[arg-type] worker.add_activity(send_email) # type: ignore[arg-type] - logger.debug(f"✓ Registered activity: handle_spam_email") - logger.debug(f"✓ Registered activity: send_email") - + logger.debug("✓ Registered activity: handle_spam_email") + logger.debug("✓ Registered activity: send_email") + # Register the orchestration function logger.debug("Registering orchestration function...") worker.add_orchestrator(spam_detection_orchestration) # type: ignore[arg-type] logger.debug(f"✓ Registered orchestration: {spam_detection_orchestration.__name__}") - + return agent_worker async def main(): """Main entry point for the worker process.""" logger.debug("Starting Durable Task Spam Detection Worker with Orchestration...") - + # Create a worker using the helper function worker = get_worker() - + # Setup worker with agents, orchestrations, and activities setup_worker(worker) - + logger.debug("Worker is ready and listening for requests...") logger.debug("Press Ctrl+C to stop.") - + try: # Start the worker (this blocks until stopped) worker.start() - + # Keep the worker running while True: await asyncio.sleep(1) except KeyboardInterrupt: logger.debug("Worker shutdown initiated") - + logger.debug("Worker stopped") diff --git a/python/samples/getting_started/durabletask/07_single_agent_orchestration_hitl/client.py b/python/samples/getting_started/durabletask/07_single_agent_orchestration_hitl/client.py index 446ab1b347..8b7a24853d 100644 --- a/python/samples/getting_started/durabletask/07_single_agent_orchestration_hitl/client.py +++ b/python/samples/getting_started/durabletask/07_single_agent_orchestration_hitl/client.py @@ -45,12 +45,12 @@ def get_client( """ taskhub_name = taskhub or os.getenv("TASKHUB", "default") endpoint_url = endpoint or os.getenv("ENDPOINT", "http://localhost:8080") - + logger.debug(f"Using taskhub: {taskhub_name}") logger.debug(f"Using endpoint: {endpoint_url}") - + credential = None if endpoint_url == "http://localhost:8080" else DefaultAzureCredential() - + return DurableTaskSchedulerClient( host_address=endpoint_url, secure_channel=endpoint_url != "http://localhost:8080", @@ -70,16 +70,16 @@ def _log_completion_result( """ if metadata and metadata.runtime_status.name == "COMPLETED": result = metadata.serialized_output - - logger.debug(f"Orchestration completed successfully!") - + + logger.debug("Orchestration completed successfully!") + if result: try: result_dict = json.loads(result) logger.info("Final Result: %s", json.dumps(result_dict, indent=2)) except json.JSONDecodeError: logger.debug(f"Result: {result}") - + elif metadata: logger.error(f"Orchestration ended with status: {metadata.runtime_status.name}") if metadata.serialized_output: @@ -105,7 +105,7 @@ def _wait_and_log_completion( instance_id=instance_id, timeout=timeout ) - + _log_completion_result(metadata) @@ -127,18 +127,18 @@ def send_approval( "approved": approved, "feedback": feedback } - + logger.debug(f"Sending {'APPROVAL' if approved else 'REJECTION'} to instance {instance_id}") if feedback: logger.debug(f"Feedback: {feedback}") - + # Raise the external event client.raise_orchestration_event( instance_id=instance_id, event_name=HUMAN_APPROVAL_EVENT, data=approval_data ) - + logger.debug("Event sent successfully") @@ -160,14 +160,14 @@ def wait_for_notification( True if notification detected, False if timeout """ logger.debug("Waiting for orchestration to reach notification point...") - + start_time = time.time() while time.time() - start_time < timeout_seconds: try: metadata = client.get_orchestration_state( instance_id=instance_id, ) - + if metadata: # Check if we're waiting for approval by examining custom status if metadata.serialized_custom_status: @@ -183,19 +183,19 @@ def wait_for_notification( if metadata.serialized_custom_status.lower().startswith("requesting human feedback"): logger.debug("Orchestration is requesting human feedback") return True - + # Check for terminal states if metadata.runtime_status.name == "COMPLETED": logger.debug("Orchestration already completed") return False - elif metadata.runtime_status.name == "FAILED": + if metadata.runtime_status.name == "FAILED": logger.error("Orchestration failed") return False except Exception as e: logger.debug(f"Status check: {e}") - + time.sleep(1) - + logger.warning("Timeout waiting for notification") return False @@ -208,94 +208,93 @@ def run_interactive_client(client: DurableTaskSchedulerClient) -> None: """ # Get user inputs logger.debug("Content Generation - Human-in-the-Loop") - + topic = input("Enter the topic for content generation: ").strip() if not topic: topic = "The benefits of cloud computing" logger.info(f"Using default topic: {topic}") - + max_attempts_str = input("Enter max review attempts (default: 3): ").strip() max_review_attempts = int(max_attempts_str) if max_attempts_str else 3 - + timeout_hours_str = input("Enter approval timeout in hours (default: 5): ").strip() timeout_hours = float(timeout_hours_str) if timeout_hours_str else 5.0 approval_timeout_seconds = int(timeout_hours * 3600) - + payload = { "topic": topic, "max_review_attempts": max_review_attempts, "approval_timeout_seconds": approval_timeout_seconds } - + logger.debug(f"Configuration: Topic={topic}, Max attempts={max_review_attempts}, Timeout={timeout_hours}h") - + # Start the orchestration logger.debug("Starting content generation orchestration...") instance_id = client.schedule_new_orchestration( # type: ignore orchestrator="content_generation_hitl_orchestration", input=payload, ) - + logger.info(f"Orchestration started with instance ID: {instance_id}") - + # Review loop attempt = 1 while attempt <= max_review_attempts: logger.info(f"Review Attempt {attempt}/{max_review_attempts}") - + # Wait for orchestration to reach notification point logger.debug("Waiting for content generation...") if not wait_for_notification(client, instance_id, timeout_seconds=120): logger.error("Failed to receive notification. Orchestration may have completed or failed.") break - + logger.info("Content is ready for review! Please review the content in the worker logs.") - + # Get user decision while True: decision = input("Do you approve this content? (yes/no): ").strip().lower() - if decision in ['yes', 'y', 'no', 'n']: + if decision in ["yes", "y", "no", "n"]: break logger.info("Please enter 'yes' or 'no'") - - approved = decision in ['yes', 'y'] - + + approved = decision in ["yes", "y"] + if approved: logger.debug("Sending approval...") send_approval(client, instance_id, approved=True) logger.info("Approval sent. Waiting for orchestration to complete...") _wait_and_log_completion(client, instance_id, timeout=60) break - else: - feedback = input("Enter feedback for improvement: ").strip() - if not feedback: - feedback = "Please revise the content." - - logger.debug("Sending rejection with feedback...") - send_approval(client, instance_id, approved=False, feedback=feedback) - logger.info("Rejection sent. Content will be regenerated...") - - attempt += 1 - - if attempt > max_review_attempts: - logger.info(f"Maximum review attempts ({max_review_attempts}) reached.") - _wait_and_log_completion(client, instance_id, timeout=30) - break - - # Small pause before next iteration - time.sleep(2) + feedback = input("Enter feedback for improvement: ").strip() + if not feedback: + feedback = "Please revise the content." + + logger.debug("Sending rejection with feedback...") + send_approval(client, instance_id, approved=False, feedback=feedback) + logger.info("Rejection sent. Content will be regenerated...") + + attempt += 1 + + if attempt > max_review_attempts: + logger.info(f"Maximum review attempts ({max_review_attempts}) reached.") + _wait_and_log_completion(client, instance_id, timeout=30) + break + + # Small pause before next iteration + time.sleep(2) async def main() -> None: """Main entry point for the client application.""" logger.debug("Starting Durable Task HITL Content Generation Client") - + # Create client using helper function client = get_client() - + try: run_interactive_client(client) - + except KeyboardInterrupt: logger.info("Interrupted by user") except Exception as e: diff --git a/python/samples/getting_started/durabletask/07_single_agent_orchestration_hitl/sample.py b/python/samples/getting_started/durabletask/07_single_agent_orchestration_hitl/sample.py index 5468a70dd3..7843621db0 100644 --- a/python/samples/getting_started/durabletask/07_single_agent_orchestration_hitl/sample.py +++ b/python/samples/getting_started/durabletask/07_single_agent_orchestration_hitl/sample.py @@ -18,10 +18,9 @@ import logging -from dotenv import load_dotenv - # Import helper functions from worker and client modules from client import get_client, run_interactive_client +from dotenv import load_dotenv from worker import get_worker, setup_worker logging.basicConfig( @@ -34,28 +33,28 @@ def main(): """Main entry point - runs both worker and client in single process.""" logger.debug("Starting Durable Task HITL Content Generation Sample (Combined Worker + Client)...") - + silent_handler = logging.NullHandler() # Create and start the worker using helper function and context manager with get_worker(log_handler=silent_handler) as dts_worker: # Register agent, orchestration, and activities using helper function setup_worker(dts_worker) - + # Start the worker dts_worker.start() logger.debug("Worker started and listening for requests...") - + # Create the client using helper function client = get_client(log_handler=silent_handler) - + try: logger.debug("CLIENT: Starting orchestration tests...") - + run_interactive_client(client) - + except Exception as e: logger.exception(f"Error during sample execution: {e}") - + logger.debug("Sample completed. Worker shutting down...") diff --git a/python/samples/getting_started/durabletask/07_single_agent_orchestration_hitl/worker.py b/python/samples/getting_started/durabletask/07_single_agent_orchestration_hitl/worker.py index db32aecf14..77aef7fa22 100644 --- a/python/samples/getting_started/durabletask/07_single_agent_orchestration_hitl/worker.py +++ b/python/samples/getting_started/durabletask/07_single_agent_orchestration_hitl/worker.py @@ -11,17 +11,17 @@ """ import asyncio -from collections.abc import Generator -from datetime import timedelta import logging import os +from collections.abc import Generator +from datetime import timedelta from typing import Any, cast from agent_framework import AgentResponse, ChatAgent from agent_framework.azure import AzureOpenAIChatClient, DurableAIAgentOrchestrationContext, DurableAIAgentWorker from azure.identity import AzureCliCredential, DefaultAzureCredential -from durabletask.task import ActivityContext, OrchestrationContext, Task, when_any # type: ignore from durabletask.azuremanaged.worker import DurableTaskSchedulerWorker +from durabletask.task import ActivityContext, OrchestrationContext, Task, when_any # type: ignore from pydantic import BaseModel, ValidationError # Configure logging @@ -64,7 +64,7 @@ def create_writer_agent() -> "ChatAgent": "Return your response as JSON with 'title' and 'content' fields." "Limit response to 300 words or less." ) - + return AzureOpenAIChatClient(credential=AzureCliCredential()).as_agent( name=WRITER_AGENT_NAME, instructions=instructions, @@ -85,6 +85,7 @@ def notify_user_for_approval(context: ActivityContext, content: dict[str, str]) logger.info("Use the client to send approval or rejection.") return "Notification sent to user for approval." + def publish_content(context: ActivityContext, content: dict[str, str]) -> str: """Activity function to publish approved content. @@ -100,7 +101,7 @@ def publish_content(context: ActivityContext, content: dict[str, str]) -> str: def content_generation_hitl_orchestration( - context: OrchestrationContext, + context: OrchestrationContext, payload_raw: Any ) -> Generator[Task[Any], Any, dict[str, str]]: """Human-in-the-loop orchestration for content generation with approval workflow. @@ -128,44 +129,44 @@ def content_generation_hitl_orchestration( RuntimeError: If max review attempts exhausted """ logger.debug("[Orchestration] Starting HITL content generation orchestration") - + # Validate input if not isinstance(payload_raw, dict): raise ValueError("Content generation input is required") - + try: payload = ContentGenerationInput.model_validate(payload_raw) except ValidationError as exc: raise ValueError(f"Invalid content generation input: {exc}") from exc - + logger.debug(f"[Orchestration] Topic: {payload.topic}") logger.debug(f"[Orchestration] Max attempts: {payload.max_review_attempts}") logger.debug(f"[Orchestration] Approval timeout: {payload.approval_timeout_seconds}s") - + # Wrap the orchestration context to access agents agent_context = DurableAIAgentOrchestrationContext(context) - + # Get the writer agent writer = agent_context.get_agent(WRITER_AGENT_NAME) writer_thread = writer.get_new_thread() logger.info(f"ThreadID: {writer_thread.session_id}") - + # Generate initial content logger.info("[Orchestration] Generating initial content...") - + initial_response: AgentResponse = yield writer.run( messages=f"Write a short article about '{payload.topic}'.", thread=writer_thread, options={"response_format": GeneratedContent}, ) content = cast(GeneratedContent, initial_response.value) - + if not isinstance(content, GeneratedContent): raise ValueError("Agent returned no content after extraction.") - + logger.debug(f"[Orchestration] Initial content generated: {content.title}") - + # Review loop attempt = 0 while attempt < payload.max_review_attempts: @@ -173,34 +174,34 @@ def content_generation_hitl_orchestration( logger.debug(f"[Orchestration] Review iteration #{attempt}/{payload.max_review_attempts}") context.set_custom_status(f"Requesting human feedback (Attempt {attempt}, timeout {payload.approval_timeout_seconds}s)") - + # Notify user for approval yield context.call_activity( - "notify_user_for_approval", + "notify_user_for_approval", input=content.model_dump() ) logger.debug("[Orchestration] Waiting for human approval or timeout...") - + # Wait for approval event or timeout approval_task: Task[Any] = context.wait_for_external_event(HUMAN_APPROVAL_EVENT) # type: ignore timeout_task: Task[Any] = context.create_timer( # type: ignore context.current_utc_datetime + timedelta(seconds=payload.approval_timeout_seconds) ) - + # Race between approval and timeout winner_task = yield when_any([approval_task, timeout_task]) # type: ignore - + if winner_task == approval_task: # Approval received before timeout logger.debug("[Orchestration] Received human approval event") context.set_custom_status("Content reviewed by human reviewer.") - + # Parse approval - approval_data: Any = approval_task.get_result() # type: ignore + approval_data: Any = approval_task.get_result() # type: ignore logger.debug(f"[Orchestration] Approval data: {approval_data}") - + # Handle different formats of approval_data if isinstance(approval_data, dict): approval = HumanApproval.model_validate(approval_data) @@ -215,7 +216,7 @@ def content_generation_hitl_orchestration( approval = HumanApproval(approved=False, feedback=approval_data) else: approval = HumanApproval(approved=False, feedback=str(approval_data)) # type: ignore - + if approval.approved: # Content approved - publish and return logger.debug("[Orchestration] Content approved! Publishing...") @@ -225,52 +226,52 @@ def content_generation_hitl_orchestration( input=content.model_dump() ) yield publish_task - + logger.debug("[Orchestration] Content published successfully") return {"content": content.content, "title": content.title} - + # Content rejected - incorporate feedback and regenerate logger.debug(f"[Orchestration] Content rejected. Feedback: {approval.feedback}") - + # Check if we've exhausted attempts if attempt >= payload.max_review_attempts: context.set_custom_status("Max review attempts exhausted.") # Max attempts exhausted logger.error(f"[Orchestration] Max attempts ({payload.max_review_attempts}) exhausted") break - - context.set_custom_status(f"Content rejected by human reviewer. Regenerating...") - + + context.set_custom_status("Content rejected by human reviewer. Regenerating...") + rewrite_prompt = ( "The content was rejected by a human reviewer. Please rewrite the article incorporating their feedback.\n\n" f"Human Feedback: {approval.feedback or 'No specific feedback provided.'}" ) - + logger.debug("[Orchestration] Regenerating content with feedback...") logger.warning(f"Regenerating with ThreadID: {writer_thread.session_id}") - + rewrite_response: AgentResponse = yield writer.run( messages=rewrite_prompt, thread=writer_thread, options={"response_format": GeneratedContent}, ) rewritten_content = cast(GeneratedContent, rewrite_response.value) - + if not isinstance(rewritten_content, GeneratedContent): raise ValueError("Agent returned no content after rewrite.") - + content = rewritten_content logger.debug(f"[Orchestration] Content regenerated: {content.title}") - + else: # Timeout occurred logger.error(f"[Orchestration] Approval timeout after {payload.approval_timeout_seconds}s") - + raise TimeoutError( f"Human approval timed out after {payload.approval_timeout_seconds} second(s)." ) - + # If we exit the loop without returning, max attempts were exhausted context.set_custom_status("Max review attempts exhausted.") raise RuntimeError( @@ -295,12 +296,12 @@ def get_worker( """ taskhub_name = taskhub or os.getenv("TASKHUB", "default") endpoint_url = endpoint or os.getenv("ENDPOINT", "http://localhost:8080") - + logger.debug(f"Using taskhub: {taskhub_name}") logger.debug(f"Using endpoint: {endpoint_url}") - + credential = None if endpoint_url == "http://localhost:8080" else DefaultAzureCredential() - + return DurableTaskSchedulerWorker( host_address=endpoint_url, secure_channel=endpoint_url != "http://localhost:8080", @@ -321,52 +322,52 @@ def setup_worker(worker: DurableTaskSchedulerWorker) -> DurableAIAgentWorker: """ # Wrap it with the agent worker agent_worker = DurableAIAgentWorker(worker) - + # Create and register the writer agent logger.debug("Creating and registering Writer agent...") writer_agent = create_writer_agent() agent_worker.add_agent(writer_agent) - + logger.debug(f"✓ Registered agent: {writer_agent.name}") - + # Register activity functions logger.debug("Registering activity functions...") worker.add_activity(notify_user_for_approval) # type: ignore worker.add_activity(publish_content) # type: ignore - logger.debug(f"✓ Registered activity: notify_user_for_approval") - logger.debug(f"✓ Registered activity: publish_content") - + logger.debug("✓ Registered activity: notify_user_for_approval") + logger.debug("✓ Registered activity: publish_content") + # Register the orchestration function logger.debug("Registering orchestration function...") - worker.add_orchestrator(content_generation_hitl_orchestration) # type: ignore + worker.add_orchestrator(content_generation_hitl_orchestration) # type: ignore logger.debug(f"✓ Registered orchestration: {content_generation_hitl_orchestration.__name__}") - + return agent_worker async def main(): """Main entry point for the worker process.""" logger.debug("Starting Durable Task HITL Content Generation Worker...") - + # Create a worker using the helper function worker = get_worker() - + # Setup worker with agents, orchestrations, and activities setup_worker(worker) - + logger.debug("Worker is ready and listening for requests...") logger.debug("Press Ctrl+C to stop.") - + try: # Start the worker (this blocks until stopped) worker.start() - + # Keep the worker running while True: await asyncio.sleep(1) except KeyboardInterrupt: logger.debug("Worker shutdown initiated") - + logger.debug("Worker stopped") diff --git a/python/samples/getting_started/evaluation/self_reflection/self_reflection.py b/python/samples/getting_started/evaluation/self_reflection/self_reflection.py index 01d4823305..bc079fbfcb 100644 --- a/python/samples/getting_started/evaluation/self_reflection/self_reflection.py +++ b/python/samples/getting_started/evaluation/self_reflection/self_reflection.py @@ -1,12 +1,17 @@ # Copyright (c) Microsoft. All rights reserved. # type: ignore +import argparse import asyncio import os import time -import argparse -import pandas as pd -import openai from typing import Any + +import openai +import pandas as pd +from agent_framework import ChatAgent, ChatMessage +from agent_framework.azure import AzureOpenAIChatClient +from azure.ai.projects import AIProjectClient +from azure.identity import AzureCliCredential from dotenv import load_dotenv from openai.types.eval_create_params import DataSourceConfigCustom from openai.types.evals.create_eval_jsonl_run_data_source_param import ( @@ -15,11 +20,6 @@ SourceFileContentContent, ) -from agent_framework import ChatAgent, ChatMessage -from agent_framework.azure import AzureOpenAIChatClient -from azure.ai.projects import AIProjectClient -from azure.identity import AzureCliCredential - """ Self-Reflection LLM Runner @@ -122,7 +122,7 @@ def run_eval( if run.status == "failed": print(f"Eval run failed. Run ID: {run.id}, Status: {run.status}, Error: {getattr(run, 'error', 'Unknown error')}") continue - elif run.status == "completed": + if run.status == "completed": output_items = list(client.evals.runs.output_items.list(run_id=run.id, eval_id=eval_object.id)) return output_items time.sleep(5) @@ -162,7 +162,7 @@ async def execute_query_with_self_reflection( - total_groundedness_eval_time: Time spent on evaluations (seconds) - total_end_to_end_time: Total execution time (seconds) """ - messages = [ChatMessage(role="user", text=full_user_query)] + messages = [ChatMessage("user", [full_user_query])] best_score = 0 max_score = 5 @@ -174,8 +174,8 @@ async def execute_query_with_self_reflection( iteration_scores = [] # Store all iteration scores in structured format for i in range(max_self_reflections): - print(f" Self-reflection iteration {i+1}/{max_self_reflections}...") - + print(f" Self-reflection iteration {i + 1}/{max_self_reflections}...") + raw_response = await agent.run(messages=messages) agent_response = raw_response.text @@ -189,7 +189,7 @@ async def execute_query_with_self_reflection( context=context, ) if eval_run_output_items is None: - print(f" ⚠️ Groundedness evaluation failed (timeout or error) for iteration {i+1}.") + print(f" ⚠️ Groundedness evaluation failed (timeout or error) for iteration {i + 1}.") continue score = eval_run_output_items[0].results[0].score end_time_eval = time.time() @@ -209,21 +209,21 @@ async def execute_query_with_self_reflection( best_response = agent_response best_iteration = i + 1 if score == max_score: - print(f" ✓ Perfect groundedness score achieved!") + print(" ✓ Perfect groundedness score achieved!") break else: print(f" → No improvement (score: {score}/{max_score}). Trying again...") - + # Add to conversation history - messages.append(ChatMessage(role="assistant", text=agent_response)) + messages.append(ChatMessage("assistant", [agent_response])) # Request improvement reflection_prompt = ( f"The groundedness score of your response is {score}/{max_score}. " f"Reflect on your answer and improve it to get the maximum score of {max_score} " ) - messages.append(ChatMessage(role="user", text=reflection_prompt)) - + messages.append(ChatMessage("user", [reflection_prompt])) + end_time = time.time() latency = end_time - start_time @@ -290,46 +290,46 @@ async def run_self_reflection_batch( print(f"Processing first {len(df)} prompts (limited by -n {limit})") # Validate required columns - required_columns = ['system_instruction', 'user_request', 'context_document', - 'full_prompt', 'domain', 'type', 'high_level_type'] + required_columns = ["system_instruction", "user_request", "context_document", + "full_prompt", "domain", "type", "high_level_type"] missing_columns = [col for col in required_columns if col not in df.columns] if missing_columns: raise ValueError(f"Input file missing required columns: {missing_columns}") - + # Configure clients - print(f"Configuring Azure OpenAI client...") + print("Configuring Azure OpenAI client...") client = create_openai_client() # Create Eval eval_object = create_eval(client=client, judge_model=judge_model) - + # Process each prompt print(f"Max self-reflections: {max_self_reflections}\n") - + results = [] for counter, (idx, row) in enumerate(df.iterrows(), start=1): print(f"[{counter}/{len(df)}] Processing prompt {row.get('original_index', idx)}...") - + try: result = await execute_query_with_self_reflection( client=client, agent=agent, eval_object=eval_object, - full_user_query=row['full_prompt'], - context=row['context_document'], + full_user_query=row["full_prompt"], + context=row["context_document"], max_self_reflections=max_self_reflections, ) # Prepare result data result_data = { - "original_index": row.get('original_index', idx), - "domain": row['domain'], - "question_type": row['type'], - "high_level_type": row['high_level_type'], - "full_prompt": row['full_prompt'], - "system_prompt": row['system_instruction'], - "user_request": row['user_request'], - "context_document": row['context_document'], + "original_index": row.get("original_index", idx), + "domain": row["domain"], + "question_type": row["type"], + "high_level_type": row["high_level_type"], + "full_prompt": row["full_prompt"], + "system_prompt": row["system_instruction"], + "user_request": row["user_request"], + "context_document": row["context_document"], "agent_response_model": agent_model, "agent_response": result, "error": None, @@ -346,14 +346,14 @@ async def run_self_reflection_batch( # Save error information error_data = { - "original_index": row.get('original_index', idx), - "domain": row['domain'], - "question_type": row['type'], - "high_level_type": row['high_level_type'], - "full_prompt": row['full_prompt'], - "system_prompt": row['system_instruction'], - "user_request": row['user_request'], - "context_document": row['context_document'], + "original_index": row.get("original_index", idx), + "domain": row["domain"], + "question_type": row["type"], + "high_level_type": row["high_level_type"], + "full_prompt": row["full_prompt"], + "system_prompt": row["system_instruction"], + "user_request": row["user_request"], + "context_document": row["context_document"], "agent_response_model": agent_model, "agent_response": None, "error": str(e), @@ -361,36 +361,36 @@ async def run_self_reflection_batch( } results.append(error_data) continue - + # Create DataFrame and save results_df = pd.DataFrame(results) print(f"\nSaving results to: {output_file}") - results_df.to_json(output_file, orient='records', lines=True) + results_df.to_json(output_file, orient="records", lines=True) # Generate detailed summary - successful_runs = results_df[results_df['error'].isna()] - failed_runs = results_df[results_df['error'].notna()] + successful_runs = results_df[results_df["error"].isna()] + failed_runs = results_df[results_df["error"].notna()] - print("\n" + "="*60) + print("\n" + "=" * 60) print("SUMMARY") - print("="*60) + print("=" * 60) print(f"Total prompts processed: {len(results_df)}") print(f" ✓ Successful: {len(successful_runs)}") print(f" ✗ Failed: {len(failed_runs)}") if len(successful_runs) > 0: # Extract scores and iteration data from nested agent_response dict - best_scores = [r['best_response_score'] for r in successful_runs['agent_response'] if r is not None] - iterations = [r['best_iteration'] for r in successful_runs['agent_response'] if r is not None] - iteration_scores_list = [r['iteration_scores'] for r in successful_runs['agent_response'] if r is not None and 'iteration_scores' in r] + best_scores = [r["best_response_score"] for r in successful_runs["agent_response"] if r is not None] + iterations = [r["best_iteration"] for r in successful_runs["agent_response"] if r is not None] + iteration_scores_list = [r["iteration_scores"] for r in successful_runs["agent_response"] if r is not None and "iteration_scores" in r] if best_scores: avg_score = sum(best_scores) / len(best_scores) perfect_scores = sum(1 for s in best_scores if s == 5) - print(f"\nGroundedness Scores:") + print("\nGroundedness Scores:") print(f" Average best score: {avg_score:.2f}/5") - print(f" Perfect scores (5/5): {perfect_scores}/{len(best_scores)} ({100*perfect_scores/len(best_scores):.1f}%)") + print(f" Perfect scores (5/5): {perfect_scores}/{len(best_scores)} ({100 * perfect_scores / len(best_scores):.1f}%)") # Calculate improvement metrics if iteration_scores_list: @@ -404,33 +404,33 @@ async def run_self_reflection_batch( avg_last_score = sum(last_scores) / len(last_scores) avg_improvement = sum(improvements) / len(improvements) - print(f"\nImprovement Analysis:") + print("\nImprovement Analysis:") print(f" Average first score: {avg_first_score:.2f}/5") print(f" Average final score: {avg_last_score:.2f}/5") print(f" Average improvement: +{avg_improvement:.2f}") - print(f" Responses that improved: {improved_count}/{len(improvements)} ({100*improved_count/len(improvements):.1f}%)") + print(f" Responses that improved: {improved_count}/{len(improvements)} ({100 * improved_count / len(improvements):.1f}%)") # Show iteration statistics if iterations: avg_iteration = sum(iterations) / len(iterations) first_try = sum(1 for it in iterations if it == 1) - print(f"\nIteration Statistics:") + print("\nIteration Statistics:") print(f" Average best iteration: {avg_iteration:.2f}") - print(f" Best on first try: {first_try}/{len(iterations)} ({100*first_try/len(iterations):.1f}%)") + print(f" Best on first try: {first_try}/{len(iterations)} ({100 * first_try / len(iterations):.1f}%)") - print("="*60) + print("=" * 60) async def main(): """CLI entry point.""" parser = argparse.ArgumentParser(description="Run self-reflection loop on LLM prompts with groundedness evaluation") - parser.add_argument('--input', '-i', default="resources/suboptimal_groundedness_prompts.jsonl", help='Input JSONL file with prompts') - parser.add_argument('--output', '-o', default="resources/results.jsonl", help='Output JSONL file for results') - parser.add_argument('--agent-model', '-m', default=DEFAULT_AGENT_MODEL, help=f'Agent model deployment name (default: {DEFAULT_AGENT_MODEL})') - parser.add_argument('--judge-model', '-e', default=DEFAULT_JUDGE_MODEL, help=f'Judge model deployment name (default: {DEFAULT_JUDGE_MODEL})') - parser.add_argument('--max-reflections', type=int, default=3, help='Maximum number of self-reflection iterations (default: 3)') - parser.add_argument('--env-file', help='Path to .env file with Azure OpenAI credentials') - parser.add_argument('--limit', '-n', type=int, default=None, help='Process only the first N prompts from the input file') + parser.add_argument("--input", "-i", default="resources/suboptimal_groundedness_prompts.jsonl", help="Input JSONL file with prompts") + parser.add_argument("--output", "-o", default="resources/results.jsonl", help="Output JSONL file for results") + parser.add_argument("--agent-model", "-m", default=DEFAULT_AGENT_MODEL, help=f"Agent model deployment name (default: {DEFAULT_AGENT_MODEL})") + parser.add_argument("--judge-model", "-e", default=DEFAULT_JUDGE_MODEL, help=f"Judge model deployment name (default: {DEFAULT_JUDGE_MODEL})") + parser.add_argument("--max-reflections", type=int, default=3, help="Maximum number of self-reflection iterations (default: 3)") + parser.add_argument("--env-file", help="Path to .env file with Azure OpenAI credentials") + parser.add_argument("--limit", "-n", type=int, default=None, help="Process only the first N prompts from the input file") args = parser.parse_args() diff --git a/python/samples/getting_started/mcp/agent_as_mcp_server.py b/python/samples/getting_started/mcp/agent_as_mcp_server.py index bd095207a7..7d09663625 100644 --- a/python/samples/getting_started/mcp/agent_as_mcp_server.py +++ b/python/samples/getting_started/mcp/agent_as_mcp_server.py @@ -3,8 +3,8 @@ from typing import Annotated, Any import anyio -from agent_framework.openai import OpenAIResponsesClient from agent_framework import tool +from agent_framework.openai import OpenAIResponsesClient """ This sample demonstrates how to expose an Agent as an MCP server. @@ -31,6 +31,7 @@ ``` """ + # NOTE: approval_mode="never_require" is for sample brevity. Use "always_require" in production; see samples/getting_started/tools/function_tool_with_approval.py and samples/getting_started/tools/function_tool_with_approval_and_threads.py. @tool(approval_mode="never_require") def get_specials() -> Annotated[str, "Returns the specials from the menu."]: @@ -40,6 +41,7 @@ def get_specials() -> Annotated[str, "Returns the specials from the menu."]: Special Drink: Chai Tea """ + @tool(approval_mode="never_require") def get_item_price( menu_item: Annotated[str, "The name of the menu item."], diff --git a/python/samples/getting_started/middleware/agent_and_run_level_middleware.py b/python/samples/getting_started/middleware/agent_and_run_level_middleware.py index 3732a8fbc2..ff4735c01c 100644 --- a/python/samples/getting_started/middleware/agent_and_run_level_middleware.py +++ b/python/samples/getting_started/middleware/agent_and_run_level_middleware.py @@ -34,9 +34,9 @@ Execution order: Agent middleware (outermost) -> Run middleware (innermost) -> Agent execution """ + # NOTE: approval_mode="never_require" is for sample brevity. Use "always_require" in production; see samples/getting_started/tools/function_tool_with_approval.py and samples/getting_started/tools/function_tool_with_approval_and_threads.py. @tool(approval_mode="never_require") - def get_weather( location: Annotated[str, Field(description="The location to get the weather for.")], ) -> str: diff --git a/python/samples/getting_started/middleware/chat_middleware.py b/python/samples/getting_started/middleware/chat_middleware.py index 8c26957e96..548b1186fa 100644 --- a/python/samples/getting_started/middleware/chat_middleware.py +++ b/python/samples/getting_started/middleware/chat_middleware.py @@ -10,7 +10,6 @@ ChatMessage, ChatMiddleware, ChatResponse, - Role, chat_middleware, tool, ) @@ -36,9 +35,9 @@ - Middleware registration at run level (applies to specific run only) """ + # NOTE: approval_mode="never_require" is for sample brevity. Use "always_require" in production; see samples/getting_started/tools/function_tool_with_approval.py and samples/getting_started/tools/function_tool_with_approval_and_threads.py. @tool(approval_mode="never_require") - def get_weather( location: Annotated[str, Field(description="The location to get the weather for.")], ) -> str: @@ -64,7 +63,7 @@ async def process( for i, message in enumerate(context.messages): content = message.text if message.text else str(message.contents) - print(f" Message {i + 1} ({message.role.value}): {content}") + print(f" Message {i + 1} ({message.role}): {content}") print(f"[InputObserverMiddleware] Total messages: {len(context.messages)}") @@ -73,7 +72,7 @@ async def process( modified_count = 0 for message in context.messages: - if message.role == Role.USER and message.text: + if message.role == "user" and message.text: original_text = message.text updated_text = original_text @@ -81,7 +80,7 @@ async def process( updated_text = self.replacement print(f"[InputObserverMiddleware] Updated: '{original_text}' -> '{updated_text}'") - modified_message = ChatMessage(role=message.role, text=updated_text) + modified_message = ChatMessage(message.role, [updated_text]) modified_messages.append(modified_message) modified_count += 1 else: @@ -119,7 +118,7 @@ async def security_and_override_middleware( context.result = ChatResponse( messages=[ ChatMessage( - role=Role.ASSISTANT, + role="assistant", text="I cannot process requests containing sensitive information. " "Please rephrase your question without including passwords, secrets, or other " "sensitive data.", diff --git a/python/samples/getting_started/middleware/class_based_middleware.py b/python/samples/getting_started/middleware/class_based_middleware.py index 59af506e74..63ccfc998b 100644 --- a/python/samples/getting_started/middleware/class_based_middleware.py +++ b/python/samples/getting_started/middleware/class_based_middleware.py @@ -13,7 +13,6 @@ ChatMessage, FunctionInvocationContext, FunctionMiddleware, - Role, tool, ) from agent_framework.azure import AzureAIAgentClient @@ -34,9 +33,9 @@ from object-oriented design patterns. """ + # NOTE: approval_mode="never_require" is for sample brevity. Use "always_require" in production; see samples/getting_started/tools/function_tool_with_approval.py and samples/getting_started/tools/function_tool_with_approval_and_threads.py. @tool(approval_mode="never_require") - def get_weather( location: Annotated[str, Field(description="The location to get the weather for.")], ) -> str: @@ -63,7 +62,7 @@ async def process( # Override the result with warning message context.result = AgentResponse( messages=[ - ChatMessage(role=Role.ASSISTANT, text="Detected sensitive information, the request is blocked.") + ChatMessage("assistant", ["Detected sensitive information, the request is blocked."]) ] ) # Simply don't call next() to prevent execution diff --git a/python/samples/getting_started/middleware/decorator_middleware.py b/python/samples/getting_started/middleware/decorator_middleware.py index 99683fad42..0ac600fd19 100644 --- a/python/samples/getting_started/middleware/decorator_middleware.py +++ b/python/samples/getting_started/middleware/decorator_middleware.py @@ -41,9 +41,9 @@ - Prevents type mismatches """ + # NOTE: approval_mode="never_require" is for sample brevity. Use "always_require" in production; see samples/getting_started/tools/function_tool_with_approval.py and samples/getting_started/tools/function_tool_with_approval_and_threads.py. @tool(approval_mode="never_require") - def get_current_time() -> str: """Get the current time.""" return f"Current time is {datetime.datetime.now().strftime('%H:%M:%S')}" diff --git a/python/samples/getting_started/middleware/exception_handling_with_middleware.py b/python/samples/getting_started/middleware/exception_handling_with_middleware.py index 4bd102c4ff..5efe9fe662 100644 --- a/python/samples/getting_started/middleware/exception_handling_with_middleware.py +++ b/python/samples/getting_started/middleware/exception_handling_with_middleware.py @@ -4,8 +4,7 @@ from collections.abc import Awaitable, Callable from typing import Annotated -from agent_framework import FunctionInvocationContext -from agent_framework import tool +from agent_framework import FunctionInvocationContext, tool from agent_framework.azure import AzureAIAgentClient from azure.identity.aio import AzureCliCredential from pydantic import Field @@ -24,6 +23,7 @@ a helpful message for the user, preventing raw exceptions from reaching the end user. """ + # NOTE: approval_mode="never_require" is for sample brevity. Use "always_require" in production; see samples/getting_started/tools/function_tool_with_approval.py and samples/getting_started/tools/function_tool_with_approval_and_threads.py. @tool(approval_mode="never_require") def unstable_data_service( diff --git a/python/samples/getting_started/middleware/function_based_middleware.py b/python/samples/getting_started/middleware/function_based_middleware.py index 83cc9eead6..d58ac46c87 100644 --- a/python/samples/getting_started/middleware/function_based_middleware.py +++ b/python/samples/getting_started/middleware/function_based_middleware.py @@ -30,9 +30,9 @@ can be implemented as async functions that accept context and next parameters. """ + # NOTE: approval_mode="never_require" is for sample brevity. Use "always_require" in production; see samples/getting_started/tools/function_tool_with_approval.py and samples/getting_started/tools/function_tool_with_approval_and_threads.py. @tool(approval_mode="never_require") - def get_weather( location: Annotated[str, Field(description="The location to get the weather for.")], ) -> str: diff --git a/python/samples/getting_started/middleware/middleware_termination.py b/python/samples/getting_started/middleware/middleware_termination.py index 8b8c771ff3..cbd82897b4 100644 --- a/python/samples/getting_started/middleware/middleware_termination.py +++ b/python/samples/getting_started/middleware/middleware_termination.py @@ -10,7 +10,6 @@ AgentResponse, AgentRunContext, ChatMessage, - Role, tool, ) from agent_framework.azure import AzureAIAgentClient @@ -29,9 +28,9 @@ This is useful for implementing security checks, rate limiting, or early exit conditions. """ + # NOTE: approval_mode="never_require" is for sample brevity. Use "always_require" in production; see samples/getting_started/tools/function_tool_with_approval.py and samples/getting_started/tools/function_tool_with_approval_and_threads.py. @tool(approval_mode="never_require") - def get_weather( location: Annotated[str, Field(description="The location to get the weather for.")], ) -> str: @@ -63,7 +62,7 @@ async def process( context.result = AgentResponse( messages=[ ChatMessage( - role=Role.ASSISTANT, + role="assistant", text=( f"Sorry, I cannot process requests containing '{blocked_word}'. " "Please rephrase your question." diff --git a/python/samples/getting_started/middleware/override_result_with_middleware.py b/python/samples/getting_started/middleware/override_result_with_middleware.py index a22b15a67b..fe55f993ed 100644 --- a/python/samples/getting_started/middleware/override_result_with_middleware.py +++ b/python/samples/getting_started/middleware/override_result_with_middleware.py @@ -11,7 +11,6 @@ AgentRunContext, ChatMessage, Content, - Role, tool, ) from agent_framework.azure import AzureAIAgentClient @@ -35,9 +34,9 @@ it creates a custom async generator that yields the override message in chunks. """ + # NOTE: approval_mode="never_require" is for sample brevity. Use "always_require" in production; see samples/getting_started/tools/function_tool_with_approval.py and samples/getting_started/tools/function_tool_with_approval_and_threads.py. @tool(approval_mode="never_require") - def get_weather( location: Annotated[str, Field(description="The location to get the weather for.")], ) -> str: @@ -75,7 +74,7 @@ async def override_stream() -> AsyncIterable[AgentResponseUpdate]: else: # For non-streaming: just replace with the string message custom_message = "".join(chunks) - context.result = AgentResponse(messages=[ChatMessage(role=Role.ASSISTANT, text=custom_message)]) + context.result = AgentResponse(messages=[ChatMessage("assistant", [custom_message])]) async def main() -> None: diff --git a/python/samples/getting_started/middleware/runtime_context_delegation.py b/python/samples/getting_started/middleware/runtime_context_delegation.py index 300d6cdb22..44ee2a7893 100644 --- a/python/samples/getting_started/middleware/runtime_context_delegation.py +++ b/python/samples/getting_started/middleware/runtime_context_delegation.py @@ -4,7 +4,7 @@ from collections.abc import Awaitable, Callable from typing import Annotated -from agent_framework import FunctionInvocationContext, tool, function_middleware +from agent_framework import FunctionInvocationContext, function_middleware, tool from agent_framework.openai import OpenAIChatClient from pydantic import Field diff --git a/python/samples/getting_started/middleware/shared_state_middleware.py b/python/samples/getting_started/middleware/shared_state_middleware.py index 9b568a2ff6..f2a5232262 100644 --- a/python/samples/getting_started/middleware/shared_state_middleware.py +++ b/python/samples/getting_started/middleware/shared_state_middleware.py @@ -26,9 +26,9 @@ This approach shows how middleware can work together by sharing state within the same class instance. """ + # NOTE: approval_mode="never_require" is for sample brevity. Use "always_require" in production; see samples/getting_started/tools/function_tool_with_approval.py and samples/getting_started/tools/function_tool_with_approval_and_threads.py. @tool(approval_mode="never_require") - def get_weather( location: Annotated[str, Field(description="The location to get the weather for.")], ) -> str: @@ -36,8 +36,8 @@ def get_weather( conditions = ["sunny", "cloudy", "rainy", "stormy"] return f"The weather in {location} is {conditions[randint(0, 3)]} with a high of {randint(10, 30)}°C." -@tool(approval_mode="never_require") +@tool(approval_mode="never_require") def get_time( timezone: Annotated[str, Field(description="The timezone to get the time for.")] = "UTC", ) -> str: diff --git a/python/samples/getting_started/middleware/thread_behavior_middleware.py b/python/samples/getting_started/middleware/thread_behavior_middleware.py index d7723812c9..5cca8cb635 100644 --- a/python/samples/getting_started/middleware/thread_behavior_middleware.py +++ b/python/samples/getting_started/middleware/thread_behavior_middleware.py @@ -31,9 +31,9 @@ 4. After next(): thread contains full conversation history (all previous + current messages) """ + # NOTE: approval_mode="never_require" is for sample brevity. Use "always_require" in production; see samples/getting_started/tools/function_tool_with_approval.py and samples/getting_started/tools/function_tool_with_approval_and_threads.py. @tool(approval_mode="never_require") - def get_weather( location: Annotated[str, Field(description="The location to get the weather for.")], ) -> str: diff --git a/python/samples/getting_started/minimal_sample.py b/python/samples/getting_started/minimal_sample.py index ec28486282..a3315b4962 100644 --- a/python/samples/getting_started/minimal_sample.py +++ b/python/samples/getting_started/minimal_sample.py @@ -4,8 +4,9 @@ from random import randint from typing import Annotated -from agent_framework.openai import OpenAIChatClient from agent_framework import tool +from agent_framework.openai import OpenAIChatClient + # NOTE: approval_mode="never_require" is for sample brevity. Use "always_require" in production; see samples/getting_started/tools/function_tool_with_approval.py and samples/getting_started/tools/function_tool_with_approval_and_threads.py. @tool(approval_mode="never_require") diff --git a/python/samples/getting_started/multimodal_input/azure_chat_multimodal.py b/python/samples/getting_started/multimodal_input/azure_chat_multimodal.py index d5c5e58476..826afcd28d 100644 --- a/python/samples/getting_started/multimodal_input/azure_chat_multimodal.py +++ b/python/samples/getting_started/multimodal_input/azure_chat_multimodal.py @@ -2,7 +2,7 @@ import asyncio -from agent_framework import ChatMessage, Content, Role +from agent_framework import ChatMessage, Content from agent_framework.azure import AzureOpenAIChatClient from azure.identity import AzureCliCredential @@ -25,7 +25,7 @@ async def test_image() -> None: image_uri = create_sample_image() message = ChatMessage( - role=Role.USER, + role="user", contents=[ Content.from_text(text="What's in this image?"), Content.from_uri(uri=image_uri, media_type="image/png"), diff --git a/python/samples/getting_started/multimodal_input/azure_responses_multimodal.py b/python/samples/getting_started/multimodal_input/azure_responses_multimodal.py index 350de89aa4..af9bdb0f0a 100644 --- a/python/samples/getting_started/multimodal_input/azure_responses_multimodal.py +++ b/python/samples/getting_started/multimodal_input/azure_responses_multimodal.py @@ -3,7 +3,7 @@ import asyncio from pathlib import Path -from agent_framework import ChatMessage, Content, Role +from agent_framework import ChatMessage, Content from agent_framework.azure import AzureOpenAIResponsesClient from azure.identity import AzureCliCredential @@ -34,7 +34,7 @@ async def test_image() -> None: image_uri = create_sample_image() message = ChatMessage( - role=Role.USER, + role="user", contents=[ Content.from_text(text="What's in this image?"), Content.from_uri(uri=image_uri, media_type="image/png"), @@ -51,7 +51,7 @@ async def test_pdf() -> None: pdf_bytes = load_sample_pdf() message = ChatMessage( - role=Role.USER, + role="user", contents=[ Content.from_text(text="What information can you extract from this document?"), Content.from_data( diff --git a/python/samples/getting_started/multimodal_input/openai_chat_multimodal.py b/python/samples/getting_started/multimodal_input/openai_chat_multimodal.py index e0743340dd..669b963609 100644 --- a/python/samples/getting_started/multimodal_input/openai_chat_multimodal.py +++ b/python/samples/getting_started/multimodal_input/openai_chat_multimodal.py @@ -5,7 +5,7 @@ import struct from pathlib import Path -from agent_framework import ChatMessage, Content, Role +from agent_framework import ChatMessage, Content from agent_framework.openai import OpenAIChatClient ASSETS_DIR = Path(__file__).resolve().parent.parent / "sample_assets" @@ -46,7 +46,7 @@ async def test_image() -> None: image_uri = create_sample_image() message = ChatMessage( - role=Role.USER, + role="user", contents=[ Content.from_text(text="What's in this image?"), Content.from_uri(uri=image_uri, media_type="image/png"), @@ -63,7 +63,7 @@ async def test_audio() -> None: audio_uri = create_sample_audio() message = ChatMessage( - role=Role.USER, + role="user", contents=[ Content.from_text(text="What do you hear in this audio?"), Content.from_uri(uri=audio_uri, media_type="audio/wav"), @@ -80,7 +80,7 @@ async def test_pdf() -> None: pdf_bytes = load_sample_pdf() message = ChatMessage( - role=Role.USER, + role="user", contents=[ Content.from_text(text="What information can you extract from this document?"), Content.from_data( diff --git a/python/samples/getting_started/observability/advanced_manual_setup_console_output.py b/python/samples/getting_started/observability/advanced_manual_setup_console_output.py index 411d0ed2a6..1ac8fae8da 100644 --- a/python/samples/getting_started/observability/advanced_manual_setup_console_output.py +++ b/python/samples/getting_started/observability/advanced_manual_setup_console_output.py @@ -5,6 +5,7 @@ from random import randint from typing import Annotated +from agent_framework import tool from agent_framework.observability import enable_instrumentation from agent_framework.openai import OpenAIChatClient from opentelemetry._logs import set_logger_provider @@ -19,7 +20,6 @@ from opentelemetry.semconv._incubating.attributes.service_attributes import SERVICE_NAME from opentelemetry.trace import set_tracer_provider from pydantic import Field -from agent_framework import tool """ This sample shows how to manually configure to send traces, logs, and metrics to the console, @@ -65,6 +65,7 @@ def setup_metrics(): # Sets the global default meter provider set_meter_provider(meter_provider) + # NOTE: approval_mode="never_require" is for sample brevity. Use "always_require" in production; see samples/getting_started/tools/function_tool_with_approval.py and samples/getting_started/tools/function_tool_with_approval_and_threads.py. @tool(approval_mode="never_require") async def get_weather( diff --git a/python/samples/getting_started/observability/advanced_zero_code.py b/python/samples/getting_started/observability/advanced_zero_code.py index d6dcef3b76..5f60af0327 100644 --- a/python/samples/getting_started/observability/advanced_zero_code.py +++ b/python/samples/getting_started/observability/advanced_zero_code.py @@ -4,12 +4,12 @@ from random import randint from typing import TYPE_CHECKING, Annotated +from agent_framework import tool from agent_framework.observability import get_tracer from agent_framework.openai import OpenAIResponsesClient from opentelemetry.trace import SpanKind from opentelemetry.trace.span import format_trace_id from pydantic import Field -from agent_framework import tool if TYPE_CHECKING: from agent_framework import ChatClientProtocol @@ -39,6 +39,7 @@ """ + # NOTE: approval_mode="never_require" is for sample brevity. Use "always_require" in production; see samples/getting_started/tools/function_tool_with_approval.py and samples/getting_started/tools/function_tool_with_approval_and_threads.py. @tool(approval_mode="never_require") async def get_weather( diff --git a/python/samples/getting_started/observability/agent_observability.py b/python/samples/getting_started/observability/agent_observability.py index bdfa3fdcd3..1c5828d56e 100644 --- a/python/samples/getting_started/observability/agent_observability.py +++ b/python/samples/getting_started/observability/agent_observability.py @@ -4,8 +4,7 @@ from random import randint from typing import Annotated -from agent_framework import ChatAgent -from agent_framework import tool +from agent_framework import ChatAgent, tool from agent_framework.observability import configure_otel_providers, get_tracer from agent_framework.openai import OpenAIChatClient from opentelemetry.trace import SpanKind @@ -17,6 +16,7 @@ same observability setup function. """ + # NOTE: approval_mode="never_require" is for sample brevity. Use "always_require" in production; see samples/getting_started/tools/function_tool_with_approval.py and samples/getting_started/tools/function_tool_with_approval_and_threads.py. @tool(approval_mode="never_require") async def get_weather( diff --git a/python/samples/getting_started/observability/agent_with_foundry_tracing.py b/python/samples/getting_started/observability/agent_with_foundry_tracing.py index 30921b26ba..72fd74facf 100644 --- a/python/samples/getting_started/observability/agent_with_foundry_tracing.py +++ b/python/samples/getting_started/observability/agent_with_foundry_tracing.py @@ -7,8 +7,7 @@ from typing import Annotated import dotenv -from agent_framework import ChatAgent -from agent_framework import tool +from agent_framework import ChatAgent, tool from agent_framework.observability import create_resource, enable_instrumentation, get_tracer from agent_framework.openai import OpenAIResponsesClient from azure.ai.projects.aio import AIProjectClient @@ -32,6 +31,7 @@ logger = logging.getLogger(__name__) + # NOTE: approval_mode="never_require" is for sample brevity. Use "always_require" in production; see samples/getting_started/tools/function_tool_with_approval.py and samples/getting_started/tools/function_tool_with_approval_and_threads.py. @tool(approval_mode="never_require") async def get_weather( diff --git a/python/samples/getting_started/observability/azure_ai_agent_observability.py b/python/samples/getting_started/observability/azure_ai_agent_observability.py index c9827cb382..56aa228386 100644 --- a/python/samples/getting_started/observability/azure_ai_agent_observability.py +++ b/python/samples/getting_started/observability/azure_ai_agent_observability.py @@ -6,8 +6,7 @@ from typing import Annotated import dotenv -from agent_framework import ChatAgent -from agent_framework import tool +from agent_framework import ChatAgent, tool from agent_framework.azure import AzureAIClient from agent_framework.observability import get_tracer from azure.ai.projects.aio import AIProjectClient @@ -29,6 +28,7 @@ # For loading the `AZURE_AI_PROJECT_ENDPOINT` environment variable dotenv.load_dotenv() + # NOTE: approval_mode="never_require" is for sample brevity. Use "always_require" in production; see samples/getting_started/tools/function_tool_with_approval.py and samples/getting_started/tools/function_tool_with_approval_and_threads.py. @tool(approval_mode="never_require") async def get_weather( diff --git a/python/samples/getting_started/observability/configure_otel_providers_with_parameters.py b/python/samples/getting_started/observability/configure_otel_providers_with_parameters.py index a69dfe76ec..0929114a60 100644 --- a/python/samples/getting_started/observability/configure_otel_providers_with_parameters.py +++ b/python/samples/getting_started/observability/configure_otel_providers_with_parameters.py @@ -6,7 +6,7 @@ from random import randint from typing import TYPE_CHECKING, Annotated, Literal -from agent_framework import tool, setup_logging +from agent_framework import setup_logging, tool from agent_framework.observability import configure_otel_providers, get_tracer from agent_framework.openai import OpenAIResponsesClient from opentelemetry import trace diff --git a/python/samples/getting_started/observability/workflow_observability.py b/python/samples/getting_started/observability/workflow_observability.py index 57e636fd68..7cd5174025 100644 --- a/python/samples/getting_started/observability/workflow_observability.py +++ b/python/samples/getting_started/observability/workflow_observability.py @@ -8,7 +8,6 @@ WorkflowContext, WorkflowOutputEvent, handler, - tool, ) from agent_framework.observability import configure_otel_providers, get_tracer from opentelemetry.trace import SpanKind diff --git a/python/samples/getting_started/purview_agent/sample_purview_agent.py b/python/samples/getting_started/purview_agent/sample_purview_agent.py index 223eed55e3..cb79042979 100644 --- a/python/samples/getting_started/purview_agent/sample_purview_agent.py +++ b/python/samples/getting_started/purview_agent/sample_purview_agent.py @@ -25,7 +25,7 @@ import os from typing import Any -from agent_framework import AgentResponse, ChatAgent, ChatMessage, Role +from agent_framework import AgentResponse, ChatAgent, ChatMessage from agent_framework.azure import AzureOpenAIChatClient from agent_framework.microsoft import ( PurviewChatPolicyMiddleware, @@ -159,13 +159,13 @@ async def run_with_agent_middleware() -> None: print("-- Agent Middleware Path --") first: AgentResponse = await agent.run( - ChatMessage(role=Role.USER, text="Tell me a joke about a pirate.", additional_properties={"user_id": user_id}) + ChatMessage("user", ["Tell me a joke about a pirate."], additional_properties={"user_id": user_id}) ) print("First response (agent middleware):\n", first) second: AgentResponse = await agent.run( ChatMessage( - role=Role.USER, text="That was funny. Tell me another one.", additional_properties={"user_id": user_id} + role="user", text="That was funny. Tell me another one.", additional_properties={"user_id": user_id} ) ) print("Second response (agent middleware):\n", second) @@ -203,7 +203,7 @@ async def run_with_chat_middleware() -> None: print("-- Chat Middleware Path --") first: AgentResponse = await agent.run( ChatMessage( - role=Role.USER, + role="user", text="Give me a short clean joke.", additional_properties={"user_id": user_id}, ) @@ -212,7 +212,7 @@ async def run_with_chat_middleware() -> None: second: AgentResponse = await agent.run( ChatMessage( - role=Role.USER, + role="user", text="One more please.", additional_properties={"user_id": user_id}, ) @@ -253,13 +253,13 @@ async def run_with_custom_cache_provider() -> None: first: AgentResponse = await agent.run( ChatMessage( - role=Role.USER, text="Tell me a joke about a programmer.", additional_properties={"user_id": user_id} + role="user", text="Tell me a joke about a programmer.", additional_properties={"user_id": user_id} ) ) print("First response (custom provider):\n", first) second: AgentResponse = await agent.run( - ChatMessage(role=Role.USER, text="That's hilarious! One more?", additional_properties={"user_id": user_id}) + ChatMessage("user", ["That's hilarious! One more?"], additional_properties={"user_id": user_id}) ) print("Second response (custom provider):\n", second) @@ -294,12 +294,12 @@ async def run_with_custom_cache_provider() -> None: print("Using default InMemoryCacheProvider with settings-based configuration") first: AgentResponse = await agent.run( - ChatMessage(role=Role.USER, text="Tell me a joke about AI.", additional_properties={"user_id": user_id}) + ChatMessage("user", ["Tell me a joke about AI."], additional_properties={"user_id": user_id}) ) print("First response (default cache):\n", first) second: AgentResponse = await agent.run( - ChatMessage(role=Role.USER, text="Nice! Another AI joke please.", additional_properties={"user_id": user_id}) + ChatMessage("user", ["Nice! Another AI joke please."], additional_properties={"user_id": user_id}) ) print("Second response (default cache):\n", second) diff --git a/python/samples/getting_started/tools/function_invocation_configuration.py b/python/samples/getting_started/tools/function_invocation_configuration.py index c53eab01a3..a73c683cf9 100644 --- a/python/samples/getting_started/tools/function_invocation_configuration.py +++ b/python/samples/getting_started/tools/function_invocation_configuration.py @@ -3,8 +3,8 @@ import asyncio from typing import Annotated -from agent_framework.openai import OpenAIResponsesClient from agent_framework import tool +from agent_framework.openai import OpenAIResponsesClient """ This sample demonstrates how to configure function invocation settings @@ -13,6 +13,7 @@ This behavior is the same for all chat client types. """ + # NOTE: approval_mode="never_require" is for sample brevity. Use "always_require" in production; see samples/getting_started/tools/function_tool_with_approval.py and samples/getting_started/tools/function_tool_with_approval_and_threads.py. @tool(approval_mode="never_require") def add( diff --git a/python/samples/getting_started/tools/function_tool_recover_from_failures.py b/python/samples/getting_started/tools/function_tool_recover_from_failures.py index 1349421b24..1637e6ab38 100644 --- a/python/samples/getting_started/tools/function_tool_recover_from_failures.py +++ b/python/samples/getting_started/tools/function_tool_recover_from_failures.py @@ -3,8 +3,7 @@ import asyncio from typing import Annotated -from agent_framework import FunctionCallContent, FunctionResultContent -from agent_framework import tool +from agent_framework import FunctionCallContent, FunctionResultContent, tool from agent_framework.openai import OpenAIResponsesClient """ @@ -14,6 +13,7 @@ The LLM decides whether to retry the call or to respond with something else, based on the exception. """ + # NOTE: approval_mode="never_require" is for sample brevity. Use "always_require" in production; see samples/getting_started/tools/function_tool_with_approval.py and samples/getting_started/tools/function_tool_with_approval_and_threads.py. @tool(approval_mode="never_require") def greet(name: Annotated[str, "Name to greet"]) -> str: diff --git a/python/samples/getting_started/tools/function_tool_with_approval.py b/python/samples/getting_started/tools/function_tool_with_approval.py index 813bbb61ea..188697a8ce 100644 --- a/python/samples/getting_started/tools/function_tool_with_approval.py +++ b/python/samples/getting_started/tools/function_tool_with_approval.py @@ -59,14 +59,14 @@ async def handle_approvals(query: str, agent: "AgentProtocol") -> AgentResponse: ) # Add the assistant message with the approval request - new_inputs.append(ChatMessage(role="assistant", contents=[user_input_needed])) + new_inputs.append(ChatMessage("assistant", [user_input_needed])) # Get user approval user_approval = await asyncio.to_thread(input, "\nApprove function call? (y/n): ") # Add the user's approval response new_inputs.append( - ChatMessage(role="user", contents=[user_input_needed.to_function_approval_response(user_approval.lower() == "y")]) + ChatMessage("user", [user_input_needed.to_function_approval_response(user_approval.lower() == "y")]) ) # Run again with all the context @@ -109,14 +109,14 @@ async def handle_approvals_streaming(query: str, agent: "AgentProtocol") -> None ) # Add the assistant message with the approval request - new_inputs.append(ChatMessage(role="assistant", contents=[user_input_needed])) + new_inputs.append(ChatMessage("assistant", [user_input_needed])) # Get user approval user_approval = await asyncio.to_thread(input, "\nApprove function call? (y/n): ") # Add the user's approval response new_inputs.append( - ChatMessage(role="user", contents=[user_input_needed.to_function_approval_response(user_approval.lower() == "y")]) + ChatMessage("user", [user_input_needed.to_function_approval_response(user_approval.lower() == "y")]) ) # Update input with all the context for next iteration diff --git a/python/samples/getting_started/tools/function_tool_with_approval_and_threads.py b/python/samples/getting_started/tools/function_tool_with_approval_and_threads.py index 9b9c06837a..de1da05991 100644 --- a/python/samples/getting_started/tools/function_tool_with_approval_and_threads.py +++ b/python/samples/getting_started/tools/function_tool_with_approval_and_threads.py @@ -55,7 +55,7 @@ async def approval_example() -> None: # Step 2: Send approval response approval_response = request.to_function_approval_response(approved=approved) - result = await agent.run(ChatMessage(role="user", contents=[approval_response]), thread=thread) + result = await agent.run(ChatMessage("user", [approval_response]), thread=thread) print(f"Agent: {result}\n") @@ -88,7 +88,7 @@ async def rejection_example() -> None: # Send rejection response rejection_response = request.to_function_approval_response(approved=False) - result = await agent.run(ChatMessage(role="user", contents=[rejection_response]), thread=thread) + result = await agent.run(ChatMessage("user", [rejection_response]), thread=thread) print(f"Agent: {result}\n") diff --git a/python/samples/getting_started/workflows/_start-here/step1_executors_and_edges.py b/python/samples/getting_started/workflows/_start-here/step1_executors_and_edges.py index f5094e9040..7c9f7a4cbb 100644 --- a/python/samples/getting_started/workflows/_start-here/step1_executors_and_edges.py +++ b/python/samples/getting_started/workflows/_start-here/step1_executors_and_edges.py @@ -8,7 +8,6 @@ WorkflowContext, executor, handler, - tool, ) from typing_extensions import Never diff --git a/python/samples/getting_started/workflows/_start-here/step3_streaming.py b/python/samples/getting_started/workflows/_start-here/step3_streaming.py index ffd3e9323d..f44ececc63 100644 --- a/python/samples/getting_started/workflows/_start-here/step3_streaming.py +++ b/python/samples/getting_started/workflows/_start-here/step3_streaming.py @@ -13,7 +13,6 @@ WorkflowRunState, WorkflowStatusEvent, handler, - tool, ) from agent_framework._workflows._events import WorkflowOutputEvent from agent_framework.azure import AzureOpenAIChatClient @@ -123,7 +122,7 @@ async def main(): # Run the workflow with the user's initial message and stream events as they occur. # This surfaces executor events, workflow outputs, run-state changes, and errors. async for event in workflow.run_stream( - ChatMessage(role="user", text="Create a slogan for a new electric SUV that is affordable and fun to drive.") + ChatMessage("user", ["Create a slogan for a new electric SUV that is affordable and fun to drive."]) ): if isinstance(event, WorkflowStatusEvent): prefix = f"State ({event.origin.value}): " diff --git a/python/samples/getting_started/workflows/_start-here/step4_using_factories.py b/python/samples/getting_started/workflows/_start-here/step4_using_factories.py index f9d4f2b971..a7b9918991 100644 --- a/python/samples/getting_started/workflows/_start-here/step4_using_factories.py +++ b/python/samples/getting_started/workflows/_start-here/step4_using_factories.py @@ -11,7 +11,6 @@ WorkflowOutputEvent, executor, handler, - tool, ) from agent_framework.azure import AzureOpenAIChatClient from azure.identity import AzureCliCredential diff --git a/python/samples/getting_started/workflows/agents/azure_chat_agents_function_bridge.py b/python/samples/getting_started/workflows/agents/azure_chat_agents_function_bridge.py index 11bac9f2c9..64fb3f3e9a 100644 --- a/python/samples/getting_started/workflows/agents/azure_chat_agents_function_bridge.py +++ b/python/samples/getting_started/workflows/agents/azure_chat_agents_function_bridge.py @@ -9,12 +9,10 @@ AgentResponse, AgentRunUpdateEvent, ChatMessage, - Role, WorkflowBuilder, WorkflowContext, WorkflowOutputEvent, executor, - tool, ) from agent_framework.azure import AzureOpenAIChatClient from azure.identity import AzureCliCredential @@ -72,7 +70,7 @@ async def enrich_with_references( ) -> None: """Inject a follow-up user instruction that adds an external note for the next agent.""" conversation = list(draft.full_conversation or draft.agent_response.messages) - original_prompt = next((message.text for message in conversation if message.role == Role.USER), "") + original_prompt = next((message.text for message in conversation if message.role == "user"), "") external_note = _lookup_external_note(original_prompt) or ( "No additional references were found. Please refine the previous assistant response for clarity." ) @@ -82,7 +80,7 @@ async def enrich_with_references( f"{external_note}\n\n" "Please update the prior assistant answer so it weaves this note into the guidance." ) - conversation.append(ChatMessage(role=Role.USER, text=follow_up)) + conversation.append(ChatMessage("user", [follow_up])) await ctx.send_message(AgentExecutorRequest(messages=conversation)) diff --git a/python/samples/getting_started/workflows/agents/azure_chat_agents_tool_calls_with_feedback.py b/python/samples/getting_started/workflows/agents/azure_chat_agents_tool_calls_with_feedback.py index 1b97677374..73e08bd0c0 100644 --- a/python/samples/getting_started/workflows/agents/azure_chat_agents_tool_calls_with_feedback.py +++ b/python/samples/getting_started/workflows/agents/azure_chat_agents_tool_calls_with_feedback.py @@ -16,7 +16,6 @@ FunctionCallContent, FunctionResultContent, RequestInfoEvent, - Role, WorkflowBuilder, WorkflowContext, WorkflowOutputEvent, @@ -50,9 +49,9 @@ - Authentication via azure-identity. Run `az login` before executing. """ + # NOTE: approval_mode="never_require" is for sample brevity. Use "always_require" in production; see samples/getting_started/tools/function_tool_with_approval.py and samples/getting_started/tools/function_tool_with_approval_and_threads.py. @tool(approval_mode="never_require") - def fetch_product_brief( product_name: Annotated[str, Field(description="Product name to look up.")], ) -> str: @@ -68,8 +67,8 @@ def fetch_product_brief( } return briefs.get(product_name.lower(), f"No stored brief for '{product_name}'.") -@tool(approval_mode="never_require") +@tool(approval_mode="never_require") def get_brand_voice_profile( voice_name: Annotated[str, Field(description="Brand or campaign voice to emulate.")], ) -> str: @@ -149,7 +148,7 @@ async def on_human_feedback( await ctx.send_message( AgentExecutorRequest( messages=original_request.conversation - + [ChatMessage(Role.USER, text="The draft is approved as-is.")], + + [ChatMessage("user", text="The draft is approved as-is.")], should_respond=True, ), target_id=self.final_editor_id, @@ -164,7 +163,7 @@ async def on_human_feedback( "Rewrite the draft from the previous assistant message into a polished final version. " "Keep the response under 120 words and reflect any requested tone adjustments." ) - conversation.append(ChatMessage(Role.USER, text=instruction)) + conversation.append(ChatMessage("user", text=instruction)) await ctx.send_message( AgentExecutorRequest(messages=conversation, should_respond=True), target_id=self.writer_id ) diff --git a/python/samples/getting_started/workflows/agents/custom_agent_executors.py b/python/samples/getting_started/workflows/agents/custom_agent_executors.py index 3f95aab0e4..c9fe07b0a2 100644 --- a/python/samples/getting_started/workflows/agents/custom_agent_executors.py +++ b/python/samples/getting_started/workflows/agents/custom_agent_executors.py @@ -9,7 +9,6 @@ WorkflowBuilder, WorkflowContext, handler, - tool, ) from agent_framework.azure import AzureOpenAIChatClient from azure.identity import AzureCliCredential @@ -121,7 +120,7 @@ async def main(): # Run the workflow with the user's initial message. # For foundational clarity, use run (non streaming) and print the workflow output. events = await workflow.run( - ChatMessage(role="user", text="Create a slogan for a new electric SUV that is affordable and fun to drive.") + ChatMessage("user", ["Create a slogan for a new electric SUV that is affordable and fun to drive."]) ) # The terminal node yields output; print its contents. outputs = events.get_outputs() diff --git a/python/samples/getting_started/workflows/agents/handoff_workflow_as_agent.py b/python/samples/getting_started/workflows/agents/handoff_workflow_as_agent.py index 3b820fe969..46c015fa42 100644 --- a/python/samples/getting_started/workflows/agents/handoff_workflow_as_agent.py +++ b/python/samples/getting_started/workflows/agents/handoff_workflow_as_agent.py @@ -11,7 +11,6 @@ FunctionResultContent, HandoffAgentUserRequest, HandoffBuilder, - Role, WorkflowAgent, tool, ) @@ -118,7 +117,7 @@ def handle_response_and_requests(response: AgentResponse) -> dict[str, HandoffAg pending_requests: dict[str, HandoffAgentUserRequest] = {} for message in response.messages: if message.text: - print(f"- {message.author_name or message.role.value}: {message.text}") + print(f"- {message.author_name or message.role}: {message.text}") for content in message.contents: if isinstance(content, FunctionCallContent): if isinstance(content.arguments, dict): @@ -200,7 +199,7 @@ async def main() -> None: for request in pending_requests.values(): for message in request.agent_response.messages: if message.text: - print(f"- {message.author_name or message.role.value}: {message.text}") + print(f"- {message.author_name or message.role}: {message.text}") if not scripted_responses: # No more scripted responses; terminate the workflow @@ -217,7 +216,7 @@ async def main() -> None: function_results = [ FunctionResultContent(call_id=req_id, result=response) for req_id, response in responses.items() ] - response = await agent.run(ChatMessage(role=Role.TOOL, contents=function_results)) + response = await agent.run(ChatMessage("tool", function_results)) pending_requests = handle_response_and_requests(response) diff --git a/python/samples/getting_started/workflows/agents/magentic_workflow_as_agent.py b/python/samples/getting_started/workflows/agents/magentic_workflow_as_agent.py index adfeffbc9e..3badeae78a 100644 --- a/python/samples/getting_started/workflows/agents/magentic_workflow_as_agent.py +++ b/python/samples/getting_started/workflows/agents/magentic_workflow_as_agent.py @@ -6,7 +6,6 @@ ChatAgent, HostedCodeInterpreterTool, MagenticBuilder, - tool, ) from agent_framework.openai import OpenAIChatClient, OpenAIResponsesClient diff --git a/python/samples/getting_started/workflows/agents/mixed_agents_and_executors.py b/python/samples/getting_started/workflows/agents/mixed_agents_and_executors.py index ab36cf3962..3ec8d0f530 100644 --- a/python/samples/getting_started/workflows/agents/mixed_agents_and_executors.py +++ b/python/samples/getting_started/workflows/agents/mixed_agents_and_executors.py @@ -11,7 +11,6 @@ WorkflowBuilder, WorkflowContext, handler, - tool, ) from agent_framework.azure import AzureAIAgentClient from azure.identity.aio import AzureCliCredential diff --git a/python/samples/getting_started/workflows/agents/sequential_workflow_as_agent.py b/python/samples/getting_started/workflows/agents/sequential_workflow_as_agent.py index bb2ade5e01..3a0264844b 100644 --- a/python/samples/getting_started/workflows/agents/sequential_workflow_as_agent.py +++ b/python/samples/getting_started/workflows/agents/sequential_workflow_as_agent.py @@ -2,7 +2,7 @@ import asyncio -from agent_framework import Role, SequentialBuilder +from agent_framework import SequentialBuilder from agent_framework.azure import AzureOpenAIChatClient from azure.identity import AzureCliCredential @@ -52,7 +52,7 @@ async def main() -> None: for i, msg in enumerate(agent_response.messages, start=1): role_value = getattr(msg.role, "value", msg.role) normalized_role = str(role_value).lower() if role_value is not None else "assistant" - name = msg.author_name or ("assistant" if normalized_role == Role.ASSISTANT.value else "user") + name = msg.author_name or ("assistant" if normalized_role == "assistant".value else "user") print(f"{'-' * 60}\n{i:02d} [{name}]\n{msg.text}") """ diff --git a/python/samples/getting_started/workflows/agents/workflow_as_agent_human_in_the_loop.py b/python/samples/getting_started/workflows/agents/workflow_as_agent_human_in_the_loop.py index 118800765d..a0d9769695 100644 --- a/python/samples/getting_started/workflows/agents/workflow_as_agent_human_in_the_loop.py +++ b/python/samples/getting_started/workflows/agents/workflow_as_agent_human_in_the_loop.py @@ -20,13 +20,11 @@ Executor, FunctionCallContent, FunctionResultContent, - Role, WorkflowAgent, WorkflowBuilder, WorkflowContext, handler, response_handler, - tool, ) from getting_started.workflows.agents.workflow_as_agent_reflection_pattern import ( # noqa: E402 ReviewRequest, @@ -168,7 +166,7 @@ async def main() -> None: result=human_response, ) # Send the human review result back to the agent. - response = await agent.run(ChatMessage(role=Role.TOOL, contents=[human_review_function_result])) + response = await agent.run(ChatMessage("tool", [human_review_function_result])) print(f"📤 Agent Response: {response.messages[-1].text}") print("=" * 50) diff --git a/python/samples/getting_started/workflows/agents/workflow_as_agent_reflection_pattern.py b/python/samples/getting_started/workflows/agents/workflow_as_agent_reflection_pattern.py index 9aa98f7b96..577a892066 100644 --- a/python/samples/getting_started/workflows/agents/workflow_as_agent_reflection_pattern.py +++ b/python/samples/getting_started/workflows/agents/workflow_as_agent_reflection_pattern.py @@ -11,11 +11,9 @@ ChatMessage, Content, Executor, - Role, WorkflowBuilder, WorkflowContext, handler, - tool, ) from agent_framework.openai import OpenAIChatClient from pydantic import BaseModel @@ -81,7 +79,7 @@ class _Response(BaseModel): # Construct review instructions and context. messages = [ ChatMessage( - role=Role.SYSTEM, + role="system", text=( "You are a reviewer for an AI agent. Provide feedback on the " "exchange between a user and the agent. Indicate approval only if:\n" @@ -98,7 +96,7 @@ class _Response(BaseModel): messages.extend(request.agent_messages) # Add explicit review instruction. - messages.append(ChatMessage(role=Role.USER, text="Please review the agent's responses.")) + messages.append(ChatMessage("user", ["Please review the agent's responses."])) print("Reviewer: Sending review request to LLM...") response = await self._chat_client.get_response(messages=messages, options={"response_format": _Response}) @@ -127,7 +125,7 @@ async def handle_user_messages(self, user_messages: list[ChatMessage], ctx: Work print("Worker: Received user messages, generating response...") # Initialize chat with system prompt. - messages = [ChatMessage(role=Role.SYSTEM, text="You are a helpful assistant.")] + messages = [ChatMessage("system", ["You are a helpful assistant."])] messages.extend(user_messages) print("Worker: Calling LLM to generate response...") @@ -162,7 +160,7 @@ async def handle_review_response(self, review: ReviewResponse, ctx: WorkflowCont # Emit approved result to external consumer via AgentRunUpdateEvent. await ctx.add_event( - AgentRunUpdateEvent(self.id, data=AgentResponseUpdate(contents=contents, role=Role.ASSISTANT)) + AgentRunUpdateEvent(self.id, data=AgentResponseUpdate(contents=contents, role="assistant")) ) return @@ -170,9 +168,9 @@ async def handle_review_response(self, review: ReviewResponse, ctx: WorkflowCont print("Worker: Regenerating response with feedback...") # Incorporate review feedback. - messages.append(ChatMessage(role=Role.SYSTEM, text=review.feedback)) + messages.append(ChatMessage("system", [review.feedback])) messages.append( - ChatMessage(role=Role.SYSTEM, text="Please incorporate the feedback and regenerate the response.") + ChatMessage("system", ["Please incorporate the feedback and regenerate the response."]) ) messages.extend(request.user_messages) diff --git a/python/samples/getting_started/workflows/agents/workflow_as_agent_with_thread.py b/python/samples/getting_started/workflows/agents/workflow_as_agent_with_thread.py index 5d145ef28f..0580fe45ab 100644 --- a/python/samples/getting_started/workflows/agents/workflow_as_agent_with_thread.py +++ b/python/samples/getting_started/workflows/agents/workflow_as_agent_with_thread.py @@ -78,7 +78,7 @@ def create_summarizer() -> ChatAgent: response1 = await agent.run(query1, thread=thread) if response1.messages: for msg in response1.messages: - speaker = msg.author_name or msg.role.value + speaker = msg.author_name or msg.role print(f"[{speaker}]: {msg.text}") # Second turn: Reference the previous topic @@ -88,7 +88,7 @@ def create_summarizer() -> ChatAgent: response2 = await agent.run(query2, thread=thread) if response2.messages: for msg in response2.messages: - speaker = msg.author_name or msg.role.value + speaker = msg.author_name or msg.role print(f"[{speaker}]: {msg.text}") # Third turn: Ask a follow-up question @@ -98,7 +98,7 @@ def create_summarizer() -> ChatAgent: response3 = await agent.run(query3, thread=thread) if response3.messages: for msg in response3.messages: - speaker = msg.author_name or msg.role.value + speaker = msg.author_name or msg.role print(f"[{speaker}]: {msg.text}") # Show the accumulated conversation history @@ -108,7 +108,7 @@ def create_summarizer() -> ChatAgent: if thread.message_store: history = await thread.message_store.list_messages() for i, msg in enumerate(history, start=1): - role = msg.role.value if hasattr(msg.role, "value") else str(msg.role) + role = msg.role if hasattr(msg.role, "value") else str(msg.role) speaker = msg.author_name or role text_preview = msg.text[:80] + "..." if len(msg.text) > 80 else msg.text print(f"{i:02d}. [{speaker}]: {text_preview}") diff --git a/python/samples/getting_started/workflows/checkpoint/checkpoint_with_human_in_the_loop.py b/python/samples/getting_started/workflows/checkpoint/checkpoint_with_human_in_the_loop.py index a2628592ea..71cfff1cc9 100644 --- a/python/samples/getting_started/workflows/checkpoint/checkpoint_with_human_in_the_loop.py +++ b/python/samples/getting_started/workflows/checkpoint/checkpoint_with_human_in_the_loop.py @@ -16,7 +16,6 @@ Executor, FileCheckpointStorage, RequestInfoEvent, - Role, Workflow, WorkflowBuilder, WorkflowCheckpoint, @@ -26,7 +25,6 @@ get_checkpoint_summary, handler, response_handler, - tool, ) from agent_framework.azure import AzureOpenAIChatClient from azure.identity import AzureCliCredential @@ -94,7 +92,7 @@ async def prepare(self, brief: str, ctx: WorkflowContext[AgentExecutorRequest, s # Hand the prompt to the writer agent. We always route through the # workflow context so the runtime can capture messages for checkpointing. await ctx.send_message( - AgentExecutorRequest(messages=[ChatMessage(Role.USER, text=prompt)], should_respond=True), + AgentExecutorRequest(messages=[ChatMessage("user", text=prompt)], should_respond=True), target_id=self._agent_id, ) @@ -156,7 +154,7 @@ async def on_human_feedback( f"Human guidance: {reply}" ) await ctx.send_message( - AgentExecutorRequest(messages=[ChatMessage(Role.USER, text=prompt)], should_respond=True), + AgentExecutorRequest(messages=[ChatMessage("user", text=prompt)], should_respond=True), target_id=self._writer_id, ) diff --git a/python/samples/getting_started/workflows/checkpoint/checkpoint_with_resume.py b/python/samples/getting_started/workflows/checkpoint/checkpoint_with_resume.py index bfa2484d63..a6f0a2431b 100644 --- a/python/samples/getting_started/workflows/checkpoint/checkpoint_with_resume.py +++ b/python/samples/getting_started/workflows/checkpoint/checkpoint_with_resume.py @@ -37,7 +37,6 @@ WorkflowContext, WorkflowOutputEvent, handler, - tool, ) diff --git a/python/samples/getting_started/workflows/checkpoint/handoff_with_tool_approval_checkpoint_resume.py b/python/samples/getting_started/workflows/checkpoint/handoff_with_tool_approval_checkpoint_resume.py index 145504bdce..e35894b8db 100644 --- a/python/samples/getting_started/workflows/checkpoint/handoff_with_tool_approval_checkpoint_resume.py +++ b/python/samples/getting_started/workflows/checkpoint/handoff_with_tool_approval_checkpoint_resume.py @@ -106,7 +106,7 @@ def create_workflow(checkpoint_storage: FileCheckpointStorage) -> tuple[Workflow .with_checkpointing(checkpoint_storage) .with_termination_condition( # Terminate after 5 user messages for this demo - lambda conv: sum(1 for msg in conv if msg.role.value == "user") >= 5 + lambda conv: sum(1 for msg in conv if msg.role == "user") >= 5 ) .build() ) @@ -285,7 +285,7 @@ async def resume_with_responses( # Now safe to cast event.data to list[ChatMessage] conversation = cast(list[ChatMessage], event.data) for msg in conversation[-3:]: # Show last 3 messages - author = msg.author_name or msg.role.value + author = msg.author_name or msg.role text = msg.text[:100] + "..." if len(msg.text) > 100 else msg.text print(f" {author}: {text}") diff --git a/python/samples/getting_started/workflows/checkpoint/sub_workflow_checkpoint.py b/python/samples/getting_started/workflows/checkpoint/sub_workflow_checkpoint.py index d35fd5e41f..24dec9fb3e 100644 --- a/python/samples/getting_started/workflows/checkpoint/sub_workflow_checkpoint.py +++ b/python/samples/getting_started/workflows/checkpoint/sub_workflow_checkpoint.py @@ -24,7 +24,6 @@ WorkflowStatusEvent, handler, response_handler, - tool, ) CHECKPOINT_DIR = Path(__file__).with_suffix("").parent / "tmp" / "sub_workflow_checkpoints" diff --git a/python/samples/getting_started/workflows/checkpoint/workflow_as_agent_checkpoint.py b/python/samples/getting_started/workflows/checkpoint/workflow_as_agent_checkpoint.py index c0647c72f7..c05ab2111e 100644 --- a/python/samples/getting_started/workflows/checkpoint/workflow_as_agent_checkpoint.py +++ b/python/samples/getting_started/workflows/checkpoint/workflow_as_agent_checkpoint.py @@ -31,7 +31,6 @@ ChatMessageStore, InMemoryCheckpointStorage, SequentialBuilder, - tool, ) from agent_framework.openai import OpenAIChatClient @@ -70,7 +69,7 @@ def create_reviewer() -> ChatAgent: response = await agent.run(query, checkpoint_storage=checkpoint_storage) for msg in response.messages: - speaker = msg.author_name or msg.role.value + speaker = msg.author_name or msg.role print(f"[{speaker}]: {msg.text}") # Show checkpoints that were created diff --git a/python/samples/getting_started/workflows/composition/sub_workflow_basics.py b/python/samples/getting_started/workflows/composition/sub_workflow_basics.py index cb789850c4..826425a0ae 100644 --- a/python/samples/getting_started/workflows/composition/sub_workflow_basics.py +++ b/python/samples/getting_started/workflows/composition/sub_workflow_basics.py @@ -10,10 +10,9 @@ WorkflowContext, WorkflowExecutor, handler, - tool, ) from typing_extensions import Never - + """ Sample: Sub-Workflows (Basics) diff --git a/python/samples/getting_started/workflows/composition/sub_workflow_parallel_requests.py b/python/samples/getting_started/workflows/composition/sub_workflow_parallel_requests.py index dadb4325d9..0959f591f0 100644 --- a/python/samples/getting_started/workflows/composition/sub_workflow_parallel_requests.py +++ b/python/samples/getting_started/workflows/composition/sub_workflow_parallel_requests.py @@ -16,7 +16,6 @@ WorkflowExecutor, handler, response_handler, - tool, ) from typing_extensions import Never diff --git a/python/samples/getting_started/workflows/composition/sub_workflow_request_interception.py b/python/samples/getting_started/workflows/composition/sub_workflow_request_interception.py index e21c74039a..167ae2e950 100644 --- a/python/samples/getting_started/workflows/composition/sub_workflow_request_interception.py +++ b/python/samples/getting_started/workflows/composition/sub_workflow_request_interception.py @@ -14,7 +14,6 @@ WorkflowOutputEvent, handler, response_handler, - tool, ) from typing_extensions import Never diff --git a/python/samples/getting_started/workflows/control-flow/edge_condition.py b/python/samples/getting_started/workflows/control-flow/edge_condition.py index 6d1a8ffb0f..cdb1d2fb03 100644 --- a/python/samples/getting_started/workflows/control-flow/edge_condition.py +++ b/python/samples/getting_started/workflows/control-flow/edge_condition.py @@ -9,12 +9,10 @@ AgentExecutorResponse, ChatAgent, # Output from an AgentExecutor ChatMessage, - Role, WorkflowBuilder, # Fluent builder for wiring executors and edges WorkflowContext, # Per-run context and event bus executor, # Decorator to declare a Python function as a workflow executor - tool, -) + ) from agent_framework.azure import AzureOpenAIChatClient # Thin client wrapper for Azure OpenAI chat models from azure.identity import AzureCliCredential # Uses your az CLI login for credentials from pydantic import BaseModel # Structured outputs for safer parsing @@ -125,7 +123,7 @@ async def to_email_assistant_request( """ # Bridge executor. Converts a structured DetectionResult into a ChatMessage and forwards it as a new request. detection = DetectionResult.model_validate_json(response.agent_response.text) - user_msg = ChatMessage(Role.USER, text=detection.email_content) + user_msg = ChatMessage("user", text=detection.email_content) await ctx.send_message(AgentExecutorRequest(messages=[user_msg], should_respond=True)) @@ -189,7 +187,7 @@ async def main() -> None: # Execute the workflow. Since the start is an AgentExecutor, pass an AgentExecutorRequest. # The workflow completes when it becomes idle (no more work to do). - request = AgentExecutorRequest(messages=[ChatMessage(Role.USER, text=email)], should_respond=True) + request = AgentExecutorRequest(messages=[ChatMessage("user", text=email)], should_respond=True) events = await workflow.run(request) outputs = events.get_outputs() if outputs: diff --git a/python/samples/getting_started/workflows/control-flow/multi_selection_edge_group.py b/python/samples/getting_started/workflows/control-flow/multi_selection_edge_group.py index 44385bffca..65f6c9c77f 100644 --- a/python/samples/getting_started/workflows/control-flow/multi_selection_edge_group.py +++ b/python/samples/getting_started/workflows/control-flow/multi_selection_edge_group.py @@ -13,13 +13,11 @@ AgentExecutorResponse, ChatAgent, ChatMessage, - Role, WorkflowBuilder, WorkflowContext, WorkflowEvent, WorkflowOutputEvent, executor, - tool, ) from agent_framework.azure import AzureOpenAIChatClient from azure.identity import AzureCliCredential @@ -93,7 +91,7 @@ async def store_email(email_text: str, ctx: WorkflowContext[AgentExecutorRequest await ctx.set_shared_state(CURRENT_EMAIL_ID_KEY, new_email.email_id) await ctx.send_message( - AgentExecutorRequest(messages=[ChatMessage(Role.USER, text=new_email.email_content)], should_respond=True) + AgentExecutorRequest(messages=[ChatMessage("user", text=new_email.email_content)], should_respond=True) ) @@ -120,7 +118,7 @@ async def submit_to_email_assistant(analysis: AnalysisResult, ctx: WorkflowConte email: Email = await ctx.get_shared_state(f"{EMAIL_STATE_PREFIX}{analysis.email_id}") await ctx.send_message( - AgentExecutorRequest(messages=[ChatMessage(Role.USER, text=email.email_content)], should_respond=True) + AgentExecutorRequest(messages=[ChatMessage("user", text=email.email_content)], should_respond=True) ) @@ -135,7 +133,7 @@ async def summarize_email(analysis: AnalysisResult, ctx: WorkflowContext[AgentEx # Only called for long NotSpam emails by selection_func email: Email = await ctx.get_shared_state(f"{EMAIL_STATE_PREFIX}{analysis.email_id}") await ctx.send_message( - AgentExecutorRequest(messages=[ChatMessage(Role.USER, text=email.email_content)], should_respond=True) + AgentExecutorRequest(messages=[ChatMessage("user", text=email.email_content)], should_respond=True) ) diff --git a/python/samples/getting_started/workflows/control-flow/sequential_executors.py b/python/samples/getting_started/workflows/control-flow/sequential_executors.py index 0fedfcf1cd..e422009766 100644 --- a/python/samples/getting_started/workflows/control-flow/sequential_executors.py +++ b/python/samples/getting_started/workflows/control-flow/sequential_executors.py @@ -9,7 +9,6 @@ WorkflowContext, WorkflowOutputEvent, handler, - tool, ) from typing_extensions import Never diff --git a/python/samples/getting_started/workflows/control-flow/simple_loop.py b/python/samples/getting_started/workflows/control-flow/simple_loop.py index d458589123..348a014f9f 100644 --- a/python/samples/getting_started/workflows/control-flow/simple_loop.py +++ b/python/samples/getting_started/workflows/control-flow/simple_loop.py @@ -10,11 +10,9 @@ ChatMessage, Executor, ExecutorCompletedEvent, - Role, WorkflowBuilder, WorkflowContext, handler, - tool, ) from agent_framework.azure import AzureOpenAIChatClient from azure.identity import AzureCliCredential @@ -97,7 +95,7 @@ async def submit(self, guess: int, ctx: WorkflowContext[AgentExecutorRequest]) - f"Target: {self._target}\nGuess: {guess}\nResponse:" ) await ctx.send_message( - AgentExecutorRequest(messages=[ChatMessage(Role.USER, text=prompt)], should_respond=True), + AgentExecutorRequest(messages=[ChatMessage("user", text=prompt)], should_respond=True), target_id=self._judge_agent_id, ) diff --git a/python/samples/getting_started/workflows/control-flow/switch_case_edge_group.py b/python/samples/getting_started/workflows/control-flow/switch_case_edge_group.py index f2090e4acc..3fe613e6f8 100644 --- a/python/samples/getting_started/workflows/control-flow/switch_case_edge_group.py +++ b/python/samples/getting_started/workflows/control-flow/switch_case_edge_group.py @@ -13,12 +13,10 @@ ChatAgent, # Case entry for a switch-case edge group ChatMessage, Default, # Default branch when no cases match - Role, WorkflowBuilder, # Fluent builder for assembling the graph WorkflowContext, # Per-run context and event bus executor, # Decorator to turn a function into a workflow executor - tool, -) + ) from agent_framework.azure import AzureOpenAIChatClient # Thin client for Azure OpenAI chat models from azure.identity import AzureCliCredential # Uses your az CLI login for credentials from pydantic import BaseModel # Structured outputs with validation @@ -100,7 +98,7 @@ async def store_email(email_text: str, ctx: WorkflowContext[AgentExecutorRequest # Kick off the detector by forwarding the email as a user message to the spam_detection_agent. await ctx.send_message( - AgentExecutorRequest(messages=[ChatMessage(Role.USER, text=new_email.email_content)], should_respond=True) + AgentExecutorRequest(messages=[ChatMessage("user", text=new_email.email_content)], should_respond=True) ) @@ -121,7 +119,7 @@ async def submit_to_email_assistant(detection: DetectionResult, ctx: WorkflowCon # Load the original content from shared state using the id carried in DetectionResult. email: Email = await ctx.get_shared_state(f"{EMAIL_STATE_PREFIX}{detection.email_id}") await ctx.send_message( - AgentExecutorRequest(messages=[ChatMessage(Role.USER, text=email.email_content)], should_respond=True) + AgentExecutorRequest(messages=[ChatMessage("user", text=email.email_content)], should_respond=True) ) diff --git a/python/samples/getting_started/workflows/declarative/customer_support/ticketing_plugin.py b/python/samples/getting_started/workflows/declarative/customer_support/ticketing_plugin.py index 8d1db72c2f..f25f1b473d 100644 --- a/python/samples/getting_started/workflows/declarative/customer_support/ticketing_plugin.py +++ b/python/samples/getting_started/workflows/declarative/customer_support/ticketing_plugin.py @@ -3,9 +3,9 @@ """Ticketing plugin for CustomerSupport workflow.""" import uuid +from collections.abc import Callable from dataclasses import dataclass from enum import Enum -from collections.abc import Callable # ANSI color codes MAGENTA = "\033[35m" diff --git a/python/samples/getting_started/workflows/declarative/function_tools/main.py b/python/samples/getting_started/workflows/declarative/function_tools/main.py index ea647e7f21..180175063e 100644 --- a/python/samples/getting_started/workflows/declarative/function_tools/main.py +++ b/python/samples/getting_started/workflows/declarative/function_tools/main.py @@ -10,8 +10,7 @@ from pathlib import Path from typing import Annotated, Any -from agent_framework import FileCheckpointStorage, RequestInfoEvent, WorkflowOutputEvent -from agent_framework import tool +from agent_framework import FileCheckpointStorage, RequestInfoEvent, WorkflowOutputEvent, tool from agent_framework.azure import AzureOpenAIChatClient from agent_framework_declarative import ExternalInputRequest, ExternalInputResponse, WorkflowFactory from azure.identity import AzureCliCredential @@ -38,17 +37,20 @@ class MenuItem: MenuItem(category="Drink", name="Soda", price=1.95, is_special=False), ] + # NOTE: approval_mode="never_require" is for sample brevity. Use "always_require" in production; see samples/getting_started/tools/function_tool_with_approval.py and samples/getting_started/tools/function_tool_with_approval_and_threads.py. @tool(approval_mode="never_require") def get_menu() -> list[dict[str, Any]]: """Get all menu items.""" return [{"category": i.category, "name": i.name, "price": i.price} for i in MENU_ITEMS] + @tool(approval_mode="never_require") def get_specials() -> list[dict[str, Any]]: """Get today's specials.""" return [{"category": i.category, "name": i.name, "price": i.price} for i in MENU_ITEMS if i.is_special] + @tool(approval_mode="never_require") def get_item_price(name: Annotated[str, Field(description="Menu item name")]) -> str: """Get price of a menu item.""" diff --git a/python/samples/getting_started/workflows/human-in-the-loop/agents_with_approval_requests.py b/python/samples/getting_started/workflows/human-in-the-loop/agents_with_approval_requests.py index c49d2c1308..24d39f02ae 100644 --- a/python/samples/getting_started/workflows/human-in-the-loop/agents_with_approval_requests.py +++ b/python/samples/getting_started/workflows/human-in-the-loop/agents_with_approval_requests.py @@ -13,9 +13,9 @@ Executor, WorkflowBuilder, WorkflowContext, - tool, executor, handler, + tool, ) from agent_framework.openai import OpenAIChatClient diff --git a/python/samples/getting_started/workflows/human-in-the-loop/concurrent_request_info.py b/python/samples/getting_started/workflows/human-in-the-loop/concurrent_request_info.py index 5aca9f8848..752956d0f2 100644 --- a/python/samples/getting_started/workflows/human-in-the-loop/concurrent_request_info.py +++ b/python/samples/getting_started/workflows/human-in-the-loop/concurrent_request_info.py @@ -29,11 +29,9 @@ ChatMessage, ConcurrentBuilder, RequestInfoEvent, - Role, WorkflowOutputEvent, WorkflowRunState, WorkflowStatusEvent, - tool, ) from agent_framework._workflows._agent_executor import AgentExecutorResponse from agent_framework.azure import AzureOpenAIChatClient @@ -72,7 +70,7 @@ async def aggregate_with_synthesis(results: list[AgentExecutorResponse]) -> Any: # Check for human feedback in the conversation (will be last user message if present) if r.full_conversation: for msg in reversed(r.full_conversation): - if msg.role == Role.USER and msg.text and "perspectives" not in msg.text.lower(): + if msg.role == "user" and msg.text and "perspectives" not in msg.text.lower(): human_guidance = msg.text break except Exception: @@ -82,14 +80,14 @@ async def aggregate_with_synthesis(results: list[AgentExecutorResponse]) -> Any: guidance_text = f"\n\nHuman guidance: {human_guidance}" if human_guidance else "" system_msg = ChatMessage( - Role.SYSTEM, + "system", text=( "You are a synthesis expert. Consolidate the following analyst perspectives " "into one cohesive, balanced summary (3-4 sentences). If human guidance is provided, " "prioritize aspects as directed." ), ) - user_msg = ChatMessage(Role.USER, text="\n\n".join(expert_sections) + guidance_text) + user_msg = ChatMessage("user", text="\n\n".join(expert_sections) + guidance_text) response = await _chat_client.get_response([system_msg, user_msg]) return response.messages[-1].text if response.messages else "" @@ -174,7 +172,7 @@ async def main() -> None: else event.data.full_conversation ) for msg in recent: - name = msg.author_name or msg.role.value + name = msg.author_name or msg.role text = (msg.text or "")[:150] print(f" [{name}]: {text}...") print("-" * 40) diff --git a/python/samples/getting_started/workflows/human-in-the-loop/group_chat_request_info.py b/python/samples/getting_started/workflows/human-in-the-loop/group_chat_request_info.py index fcc1d1460c..5d36fbd13a 100644 --- a/python/samples/getting_started/workflows/human-in-the-loop/group_chat_request_info.py +++ b/python/samples/getting_started/workflows/human-in-the-loop/group_chat_request_info.py @@ -35,7 +35,6 @@ WorkflowOutputEvent, WorkflowRunState, WorkflowStatusEvent, - tool, ) from agent_framework.azure import AzureOpenAIChatClient from azure.identity import AzureCliCredential @@ -164,7 +163,7 @@ async def main() -> None: if event.data: messages: list[ChatMessage] = event.data for msg in messages: - role = msg.role.value.capitalize() + role = msg.role.capitalize() name = msg.author_name or "unknown" text = (msg.text or "")[:200] print(f"[{role}][{name}]: {text}...") diff --git a/python/samples/getting_started/workflows/human-in-the-loop/guessing_game_with_human_input.py b/python/samples/getting_started/workflows/human-in-the-loop/guessing_game_with_human_input.py index 52a9d72901..dba7f56b66 100644 --- a/python/samples/getting_started/workflows/human-in-the-loop/guessing_game_with_human_input.py +++ b/python/samples/getting_started/workflows/human-in-the-loop/guessing_game_with_human_input.py @@ -10,7 +10,6 @@ ChatMessage, # Chat message structure Executor, # Base class for workflow executors RequestInfoEvent, # Event emitted when human input is requested - Role, # Enum of chat roles (user, assistant, system) WorkflowBuilder, # Fluent builder for assembling the graph WorkflowContext, # Per run context and event bus WorkflowOutputEvent, # Event emitted when workflow yields output @@ -18,8 +17,7 @@ WorkflowStatusEvent, # Event emitted on run state changes handler, response_handler, # Decorator to expose an Executor method as a step - tool, -) + ) from agent_framework.azure import AzureOpenAIChatClient from azure.identity import AzureCliCredential from pydantic import BaseModel @@ -88,7 +86,7 @@ async def start(self, _: str, ctx: WorkflowContext[AgentExecutorRequest]) -> Non - Input is a simple starter token (ignored here). - Output is an AgentExecutorRequest that triggers the agent to produce a guess. """ - user = ChatMessage(Role.USER, text="Start by making your first guess.") + user = ChatMessage("user", text="Start by making your first guess.") await ctx.send_message(AgentExecutorRequest(messages=[user], should_respond=True)) @handler @@ -138,7 +136,7 @@ async def on_human_feedback( # Provide feedback to the agent to try again. # We keep the agent's output strictly JSON to ensure stable parsing on the next turn. user_msg = ChatMessage( - Role.USER, + "user", text=(f'Feedback: {reply}. Return ONLY a JSON object matching the schema {{"guess": }}.'), ) await ctx.send_message(AgentExecutorRequest(messages=[user_msg], should_respond=True)) diff --git a/python/samples/getting_started/workflows/human-in-the-loop/sequential_request_info.py b/python/samples/getting_started/workflows/human-in-the-loop/sequential_request_info.py index 401c24b5dd..afb19753e5 100644 --- a/python/samples/getting_started/workflows/human-in-the-loop/sequential_request_info.py +++ b/python/samples/getting_started/workflows/human-in-the-loop/sequential_request_info.py @@ -32,7 +32,6 @@ WorkflowOutputEvent, WorkflowRunState, WorkflowStatusEvent, - tool, ) from agent_framework.azure import AzureOpenAIChatClient from azure.identity import AzureCliCredential @@ -109,7 +108,7 @@ async def main() -> None: else event.data.full_conversation ) for msg in recent: - name = msg.author_name or msg.role.value + name = msg.author_name or msg.role text = (msg.text or "")[:150] print(f" [{name}]: {text}...") print("-" * 40) @@ -132,7 +131,7 @@ async def main() -> None: if event.data: messages: list[ChatMessage] = event.data[-3:] for msg in messages: - role = msg.role.value if msg.role else "unknown" + role = msg.role if msg.role else "unknown" print(f"[{role}]: {msg.text}") workflow_complete = True diff --git a/python/samples/getting_started/workflows/observability/executor_io_observation.py b/python/samples/getting_started/workflows/observability/executor_io_observation.py index 54645f237d..0237f294f2 100644 --- a/python/samples/getting_started/workflows/observability/executor_io_observation.py +++ b/python/samples/getting_started/workflows/observability/executor_io_observation.py @@ -11,7 +11,6 @@ WorkflowContext, WorkflowOutputEvent, handler, - tool, ) from typing_extensions import Never diff --git a/python/samples/getting_started/workflows/orchestration/concurrent_custom_agent_executors.py b/python/samples/getting_started/workflows/orchestration/concurrent_custom_agent_executors.py index caf97c7f8f..76203dba63 100644 --- a/python/samples/getting_started/workflows/orchestration/concurrent_custom_agent_executors.py +++ b/python/samples/getting_started/workflows/orchestration/concurrent_custom_agent_executors.py @@ -12,7 +12,6 @@ Executor, WorkflowContext, handler, - tool, ) from agent_framework.azure import AzureOpenAIChatClient from azure.identity import AzureCliCredential diff --git a/python/samples/getting_started/workflows/orchestration/concurrent_custom_aggregator.py b/python/samples/getting_started/workflows/orchestration/concurrent_custom_aggregator.py index def89043eb..1690c2baad 100644 --- a/python/samples/getting_started/workflows/orchestration/concurrent_custom_aggregator.py +++ b/python/samples/getting_started/workflows/orchestration/concurrent_custom_aggregator.py @@ -3,7 +3,7 @@ import asyncio from typing import Any -from agent_framework import ChatMessage, ConcurrentBuilder, Role +from agent_framework import ChatMessage, ConcurrentBuilder from agent_framework.azure import AzureOpenAIChatClient from azure.identity import AzureCliCredential @@ -66,13 +66,13 @@ async def summarize_results(results: list[Any]) -> str: # Ask the model to synthesize a concise summary of the experts' outputs system_msg = ChatMessage( - Role.SYSTEM, + "system", text=( "You are a helpful assistant that consolidates multiple domain expert outputs " "into one cohesive, concise summary with clear takeaways. Keep it under 200 words." ), ) - user_msg = ChatMessage(Role.USER, text="\n\n".join(expert_sections)) + user_msg = ChatMessage("user", text="\n\n".join(expert_sections)) response = await chat_client.get_response([system_msg, user_msg]) # Return the model's final assistant text as the completion result diff --git a/python/samples/getting_started/workflows/orchestration/concurrent_participant_factory.py b/python/samples/getting_started/workflows/orchestration/concurrent_participant_factory.py index aaa05a37a9..941456a823 100644 --- a/python/samples/getting_started/workflows/orchestration/concurrent_participant_factory.py +++ b/python/samples/getting_started/workflows/orchestration/concurrent_participant_factory.py @@ -8,11 +8,9 @@ ChatMessage, ConcurrentBuilder, Executor, - Role, Workflow, WorkflowContext, handler, - tool, ) from agent_framework.azure import AzureOpenAIChatClient from azure.identity import AzureCliCredential @@ -98,13 +96,13 @@ async def summarize_results(self, results: list[Any], ctx: WorkflowContext[Never # Ask the model to synthesize a concise summary of the experts' outputs system_msg = ChatMessage( - Role.SYSTEM, + "system", text=( "You are a helpful assistant that consolidates multiple domain expert outputs " "into one cohesive, concise summary with clear takeaways. Keep it under 200 words." ), ) - user_msg = ChatMessage(Role.USER, text="\n\n".join(expert_sections)) + user_msg = ChatMessage("user", text="\n\n".join(expert_sections)) response = await self.chat_client.get_response([system_msg, user_msg]) diff --git a/python/samples/getting_started/workflows/orchestration/group_chat_agent_manager.py b/python/samples/getting_started/workflows/orchestration/group_chat_agent_manager.py index 926c787aaa..cdc03a5ea5 100644 --- a/python/samples/getting_started/workflows/orchestration/group_chat_agent_manager.py +++ b/python/samples/getting_started/workflows/orchestration/group_chat_agent_manager.py @@ -7,9 +7,7 @@ ChatAgent, ChatMessage, GroupChatBuilder, - Role, WorkflowOutputEvent, - tool, ) from agent_framework.azure import AzureOpenAIChatClient from azure.identity import AzureCliCredential @@ -73,7 +71,7 @@ async def main() -> None: .participants([researcher, writer]) # Set a hard termination condition: stop after 4 assistant messages # The agent orchestrator will intelligently decide when to end before this limit but just in case - .with_termination_condition(lambda messages: sum(1 for msg in messages if msg.role == Role.ASSISTANT) >= 4) + .with_termination_condition(lambda messages: sum(1 for msg in messages if msg.role == "assistant") >= 4) .build() ) diff --git a/python/samples/getting_started/workflows/orchestration/group_chat_philosophical_debate.py b/python/samples/getting_started/workflows/orchestration/group_chat_philosophical_debate.py index 9be9192a57..de613dea2e 100644 --- a/python/samples/getting_started/workflows/orchestration/group_chat_philosophical_debate.py +++ b/python/samples/getting_started/workflows/orchestration/group_chat_philosophical_debate.py @@ -9,9 +9,7 @@ ChatAgent, ChatMessage, GroupChatBuilder, - Role, WorkflowOutputEvent, - tool, ) from agent_framework.azure import AzureOpenAIChatClient from azure.identity import AzureCliCredential @@ -214,7 +212,7 @@ async def main() -> None: GroupChatBuilder() .with_orchestrator(agent=moderator) .participants([farmer, developer, teacher, activist, spiritual_leader, artist, immigrant, doctor]) - .with_termination_condition(lambda messages: sum(1 for msg in messages if msg.role == Role.ASSISTANT) >= 10) + .with_termination_condition(lambda messages: sum(1 for msg in messages if msg.role == "assistant") >= 10) .build() ) diff --git a/python/samples/getting_started/workflows/orchestration/group_chat_simple_selector.py b/python/samples/getting_started/workflows/orchestration/group_chat_simple_selector.py index cf64ef0aca..1047cd6f22 100644 --- a/python/samples/getting_started/workflows/orchestration/group_chat_simple_selector.py +++ b/python/samples/getting_started/workflows/orchestration/group_chat_simple_selector.py @@ -9,7 +9,6 @@ GroupChatBuilder, GroupChatState, WorkflowOutputEvent, - tool, ) from agent_framework.azure import AzureOpenAIChatClient from azure.identity import AzureCliCredential diff --git a/python/samples/getting_started/workflows/orchestration/handoff_autonomous.py b/python/samples/getting_started/workflows/orchestration/handoff_autonomous.py index edab013700..e33b230ce7 100644 --- a/python/samples/getting_started/workflows/orchestration/handoff_autonomous.py +++ b/python/samples/getting_started/workflows/orchestration/handoff_autonomous.py @@ -14,7 +14,6 @@ WorkflowEvent, WorkflowOutputEvent, resolve_agent_id, - tool, ) from agent_framework.azure import AzureOpenAIChatClient from azure.identity import AzureCliCredential @@ -95,7 +94,7 @@ def _display_event(event: WorkflowEvent) -> None: conversation = cast(list[ChatMessage], event.data) print("\n=== Final Conversation (Autonomous with Iteration) ===") for message in conversation: - speaker = message.author_name or message.role.value + speaker = message.author_name or message.role text_preview = message.text[:200] + "..." if len(message.text) > 200 else message.text print(f"- {speaker}: {text_preview}") print(f"\nTotal messages: {len(conversation)}") @@ -131,7 +130,7 @@ async def main() -> None: ) .with_termination_condition( # Terminate after coordinator provides 5 assistant responses - lambda conv: sum(1 for msg in conv if msg.author_name == "coordinator" and msg.role.value == "assistant") + lambda conv: sum(1 for msg in conv if msg.author_name == "coordinator" and msg.role == "assistant") >= 5 ) .build() diff --git a/python/samples/getting_started/workflows/orchestration/handoff_participant_factory.py b/python/samples/getting_started/workflows/orchestration/handoff_participant_factory.py index dd4e4054c8..9107e217c6 100644 --- a/python/samples/getting_started/workflows/orchestration/handoff_participant_factory.py +++ b/python/samples/getting_started/workflows/orchestration/handoff_participant_factory.py @@ -131,7 +131,7 @@ def _handle_events(events: list[WorkflowEvent]) -> list[RequestInfoEvent]: if not message.text: # Skip messages without text (e.g., tool calls) continue - speaker = message.author_name or message.role.value + speaker = message.author_name or message.role print(f"- {speaker}: {message.text}") # HandoffSentEvent: Indicates a handoff has been initiated @@ -151,7 +151,7 @@ def _handle_events(events: list[WorkflowEvent]) -> list[RequestInfoEvent]: if isinstance(conversation, list): print("\n=== Final Conversation Snapshot ===") for message in conversation: - speaker = message.author_name or message.role.value + speaker = message.author_name or message.role print(f"- {speaker}: {message.text or [content.type for content in message.contents]}") print("===================================") @@ -183,7 +183,7 @@ def _print_handoff_agent_user_request(response: AgentResponse) -> None: if not message.text: # Skip messages without text (e.g., tool calls) continue - speaker = message.author_name or message.role.value + speaker = message.author_name or message.role print(f"- {speaker}: {message.text}") diff --git a/python/samples/getting_started/workflows/orchestration/handoff_simple.py b/python/samples/getting_started/workflows/orchestration/handoff_simple.py index 72ea035a4f..2e7f53a82d 100644 --- a/python/samples/getting_started/workflows/orchestration/handoff_simple.py +++ b/python/samples/getting_started/workflows/orchestration/handoff_simple.py @@ -126,7 +126,7 @@ def _handle_events(events: list[WorkflowEvent]) -> list[RequestInfoEvent]: if not message.text: # Skip messages without text (e.g., tool calls) continue - speaker = message.author_name or message.role.value + speaker = message.author_name or message.role print(f"- {speaker}: {message.text}") # HandoffSentEvent: Indicates a handoff has been initiated @@ -146,7 +146,7 @@ def _handle_events(events: list[WorkflowEvent]) -> list[RequestInfoEvent]: if isinstance(conversation, list): print("\n=== Final Conversation Snapshot ===") for message in conversation: - speaker = message.author_name or message.role.value + speaker = message.author_name or message.role print(f"- {speaker}: {message.text or [content.type for content in message.contents]}") print("===================================") @@ -178,7 +178,7 @@ def _print_handoff_agent_user_request(response: AgentResponse) -> None: if not message.text: # Skip messages without text (e.g., tool calls) continue - speaker = message.author_name or message.role.value + speaker = message.author_name or message.role print(f"- {speaker}: {message.text}") diff --git a/python/samples/getting_started/workflows/orchestration/handoff_with_code_interpreter_file.py b/python/samples/getting_started/workflows/orchestration/handoff_with_code_interpreter_file.py index 54f7f4504c..0c0616850b 100644 --- a/python/samples/getting_started/workflows/orchestration/handoff_with_code_interpreter_file.py +++ b/python/samples/getting_started/workflows/orchestration/handoff_with_code_interpreter_file.py @@ -41,7 +41,6 @@ WorkflowEvent, WorkflowRunState, WorkflowStatusEvent, - tool, ) from azure.identity.aio import AzureCliCredential @@ -157,7 +156,7 @@ async def main() -> None: HandoffBuilder() .participants([triage, code_specialist]) .with_start_agent(triage) - .with_termination_condition(lambda conv: sum(1 for msg in conv if msg.role.value == "user") >= 2) + .with_termination_condition(lambda conv: sum(1 for msg in conv if msg.role == "user") >= 2) .build() ) diff --git a/python/samples/getting_started/workflows/orchestration/magentic.py b/python/samples/getting_started/workflows/orchestration/magentic.py index d153d41d9c..60746bc113 100644 --- a/python/samples/getting_started/workflows/orchestration/magentic.py +++ b/python/samples/getting_started/workflows/orchestration/magentic.py @@ -15,7 +15,6 @@ MagenticOrchestratorEvent, MagenticProgressLedger, WorkflowOutputEvent, - tool, ) from agent_framework.openai import OpenAIChatClient, OpenAIResponsesClient diff --git a/python/samples/getting_started/workflows/orchestration/magentic_checkpoint.py b/python/samples/getting_started/workflows/orchestration/magentic_checkpoint.py index 3c68931a18..2dd6a1a170 100644 --- a/python/samples/getting_started/workflows/orchestration/magentic_checkpoint.py +++ b/python/samples/getting_started/workflows/orchestration/magentic_checkpoint.py @@ -16,7 +16,6 @@ WorkflowOutputEvent, WorkflowRunState, WorkflowStatusEvent, - tool, ) from agent_framework.azure import AzureOpenAIChatClient from azure.identity._credentials import AzureCliCredential diff --git a/python/samples/getting_started/workflows/orchestration/magentic_human_plan_review.py b/python/samples/getting_started/workflows/orchestration/magentic_human_plan_review.py index bba6913a3b..1050463d01 100644 --- a/python/samples/getting_started/workflows/orchestration/magentic_human_plan_review.py +++ b/python/samples/getting_started/workflows/orchestration/magentic_human_plan_review.py @@ -12,7 +12,6 @@ MagenticPlanReviewRequest, RequestInfoEvent, WorkflowOutputEvent, - tool, ) from agent_framework.openai import OpenAIChatClient diff --git a/python/samples/getting_started/workflows/orchestration/sequential_agents.py b/python/samples/getting_started/workflows/orchestration/sequential_agents.py index 64ccbc6150..59a9cb5bdd 100644 --- a/python/samples/getting_started/workflows/orchestration/sequential_agents.py +++ b/python/samples/getting_started/workflows/orchestration/sequential_agents.py @@ -3,7 +3,7 @@ import asyncio from typing import cast -from agent_framework import ChatMessage, Role, SequentialBuilder, WorkflowOutputEvent +from agent_framework import ChatMessage, SequentialBuilder, WorkflowOutputEvent from agent_framework.azure import AzureOpenAIChatClient from azure.identity import AzureCliCredential @@ -53,7 +53,7 @@ async def main() -> None: if outputs: print("===== Final Conversation =====") for i, msg in enumerate(outputs[-1], start=1): - name = msg.author_name or ("assistant" if msg.role == Role.ASSISTANT else "user") + name = msg.author_name or ("assistant" if msg.role == "assistant" else "user") print(f"{'-' * 60}\n{i:02d} [{name}]\n{msg.text}") """ diff --git a/python/samples/getting_started/workflows/orchestration/sequential_custom_executors.py b/python/samples/getting_started/workflows/orchestration/sequential_custom_executors.py index b29cec6d83..09454f8b12 100644 --- a/python/samples/getting_started/workflows/orchestration/sequential_custom_executors.py +++ b/python/samples/getting_started/workflows/orchestration/sequential_custom_executors.py @@ -7,11 +7,9 @@ AgentExecutorResponse, ChatMessage, Executor, - Role, SequentialBuilder, WorkflowContext, handler, - tool, ) from agent_framework.azure import AzureOpenAIChatClient from azure.identity import AzureCliCredential @@ -48,12 +46,12 @@ async def summarize(self, agent_response: AgentExecutorResponse, ctx: WorkflowCo the output must be `list[ChatMessage]`. """ if not agent_response.full_conversation: - await ctx.send_message([ChatMessage(role=Role.ASSISTANT, text="No conversation to summarize.")]) + await ctx.send_message([ChatMessage("assistant", ["No conversation to summarize."])]) return - users = sum(1 for m in agent_response.full_conversation if m.role == Role.USER) - assistants = sum(1 for m in agent_response.full_conversation if m.role == Role.ASSISTANT) - summary = ChatMessage(role=Role.ASSISTANT, text=f"Summary -> users:{users} assistants:{assistants}") + users = sum(1 for m in agent_response.full_conversation if m.role == "user") + assistants = sum(1 for m in agent_response.full_conversation if m.role == "assistant") + summary = ChatMessage("assistant", [f"Summary -> users:{users} assistants:{assistants}"]) final_conversation = list(agent_response.full_conversation) + [summary] await ctx.send_message(final_conversation) @@ -78,7 +76,7 @@ async def main() -> None: print("===== Final Conversation =====") messages: list[ChatMessage] | Any = outputs[0] for i, msg in enumerate(messages, start=1): - name = msg.author_name or ("assistant" if msg.role == Role.ASSISTANT else "user") + name = msg.author_name or ("assistant" if msg.role == "assistant" else "user") print(f"{'-' * 60}\n{i:02d} [{name}]\n{msg.text}") """ diff --git a/python/samples/getting_started/workflows/orchestration/sequential_participant_factory.py b/python/samples/getting_started/workflows/orchestration/sequential_participant_factory.py index 6cf87bf21c..8b78a38926 100644 --- a/python/samples/getting_started/workflows/orchestration/sequential_participant_factory.py +++ b/python/samples/getting_started/workflows/orchestration/sequential_participant_factory.py @@ -6,12 +6,10 @@ ChatAgent, ChatMessage, Executor, - Role, SequentialBuilder, Workflow, WorkflowContext, handler, - tool, ) from agent_framework.azure import AzureOpenAIChatClient from azure.identity import AzureCliCredential @@ -64,7 +62,7 @@ async def run_workflow(workflow: Workflow, query: str) -> None: if outputs: messages: list[ChatMessage] = outputs[0] for message in messages: - name = message.author_name or ("assistant" if message.role == Role.ASSISTANT else "user") + name = message.author_name or ("assistant" if message.role == "assistant" else "user") print(f"{name}: {message.text}") else: raise RuntimeError("No outputs received from the workflow.") diff --git a/python/samples/getting_started/workflows/parallelism/fan_out_fan_in_edges.py b/python/samples/getting_started/workflows/parallelism/fan_out_fan_in_edges.py index 36c2ca24f6..f2ed5ad677 100644 --- a/python/samples/getting_started/workflows/parallelism/fan_out_fan_in_edges.py +++ b/python/samples/getting_started/workflows/parallelism/fan_out_fan_in_edges.py @@ -11,13 +11,11 @@ Executor, # Base class for custom Python executors ExecutorCompletedEvent, ExecutorInvokedEvent, - Role, # Enum of chat roles (user, assistant, system) WorkflowBuilder, # Fluent builder for wiring the workflow graph WorkflowContext, # Per run context and event bus WorkflowOutputEvent, # Event emitted when workflow yields output handler, # Decorator to mark an Executor method as invokable - tool, -) + ) from agent_framework.azure import AzureOpenAIChatClient from azure.identity import AzureCliCredential # Uses your az CLI login for credentials from typing_extensions import Never @@ -47,7 +45,7 @@ class DispatchToExperts(Executor): @handler async def dispatch(self, prompt: str, ctx: WorkflowContext[AgentExecutorRequest]) -> None: # Wrap the incoming prompt as a user message for each expert and request a response. - initial_message = ChatMessage(Role.USER, text=prompt) + initial_message = ChatMessage("user", text=prompt) await ctx.send_message(AgentExecutorRequest(messages=[initial_message], should_respond=True)) diff --git a/python/samples/getting_started/workflows/parallelism/map_reduce_and_visualization.py b/python/samples/getting_started/workflows/parallelism/map_reduce_and_visualization.py index d98c6cb78b..9b46e74bd2 100644 --- a/python/samples/getting_started/workflows/parallelism/map_reduce_and_visualization.py +++ b/python/samples/getting_started/workflows/parallelism/map_reduce_and_visualization.py @@ -14,8 +14,7 @@ WorkflowOutputEvent, # Event emitted when workflow yields output WorkflowViz, # Utility to visualize a workflow graph handler, # Decorator to expose an Executor method as a step - tool, -) + ) from typing_extensions import Never """ diff --git a/python/samples/getting_started/workflows/state-management/shared_states_with_agents.py b/python/samples/getting_started/workflows/state-management/shared_states_with_agents.py index 700dcb1b95..3a243f54ab 100644 --- a/python/samples/getting_started/workflows/state-management/shared_states_with_agents.py +++ b/python/samples/getting_started/workflows/state-management/shared_states_with_agents.py @@ -11,11 +11,9 @@ AgentExecutorResponse, ChatAgent, ChatMessage, - Role, WorkflowBuilder, WorkflowContext, executor, - tool, ) from agent_framework.azure import AzureOpenAIChatClient from azure.identity import AzureCliCredential @@ -105,7 +103,7 @@ async def store_email(email_text: str, ctx: WorkflowContext[AgentExecutorRequest await ctx.set_shared_state(CURRENT_EMAIL_ID_KEY, new_email.email_id) await ctx.send_message( - AgentExecutorRequest(messages=[ChatMessage(Role.USER, text=new_email.email_content)], should_respond=True) + AgentExecutorRequest(messages=[ChatMessage("user", text=new_email.email_content)], should_respond=True) ) @@ -136,7 +134,7 @@ async def submit_to_email_assistant(detection: DetectionResult, ctx: WorkflowCon # Load the original content by id from shared state and forward it to the assistant. email: Email = await ctx.get_shared_state(f"{EMAIL_STATE_PREFIX}{detection.email_id}") await ctx.send_message( - AgentExecutorRequest(messages=[ChatMessage(Role.USER, text=email.email_content)], should_respond=True) + AgentExecutorRequest(messages=[ChatMessage("user", text=email.email_content)], should_respond=True) ) diff --git a/python/samples/getting_started/workflows/tool-approval/concurrent_builder_tool_approval.py b/python/samples/getting_started/workflows/tool-approval/concurrent_builder_tool_approval.py index b43e01916f..4e202026fb 100644 --- a/python/samples/getting_started/workflows/tool-approval/concurrent_builder_tool_approval.py +++ b/python/samples/getting_started/workflows/tool-approval/concurrent_builder_tool_approval.py @@ -97,7 +97,7 @@ def _print_output(event: WorkflowOutputEvent) -> None: print("Workflow completed. Aggregated results from both agents:") for msg in messages: if msg.text: - print(f"- {msg.author_name or msg.role.value}: {msg.text}") + print(f"- {msg.author_name or msg.role}: {msg.text}") async def main() -> None: diff --git a/python/samples/getting_started/workflows/tool-approval/sequential_builder_tool_approval.py b/python/samples/getting_started/workflows/tool-approval/sequential_builder_tool_approval.py index 7712873943..30c6b2358f 100644 --- a/python/samples/getting_started/workflows/tool-approval/sequential_builder_tool_approval.py +++ b/python/samples/getting_started/workflows/tool-approval/sequential_builder_tool_approval.py @@ -116,7 +116,7 @@ async def main() -> None: print("\n" + "-" * 60) print("Workflow completed. Final conversation:") for msg in output: - role = msg.role.value if hasattr(msg.role, "value") else msg.role + role = msg.role if hasattr(msg.role, "value") else msg.role text = msg.text[:200] + "..." if len(msg.text) > 200 else msg.text print(f" [{role}]: {text}") else: diff --git a/python/samples/getting_started/workflows/visualization/concurrent_with_visualization.py b/python/samples/getting_started/workflows/visualization/concurrent_with_visualization.py index 877bb13038..68b68c4a7a 100644 --- a/python/samples/getting_started/workflows/visualization/concurrent_with_visualization.py +++ b/python/samples/getting_started/workflows/visualization/concurrent_with_visualization.py @@ -9,12 +9,10 @@ ChatAgent, ChatMessage, Executor, - Role, WorkflowBuilder, WorkflowContext, WorkflowViz, handler, - tool, ) from agent_framework.azure import AzureOpenAIChatClient from azure.identity import AzureCliCredential @@ -41,7 +39,7 @@ class DispatchToExperts(Executor): @handler async def dispatch(self, prompt: str, ctx: WorkflowContext[AgentExecutorRequest]) -> None: # Wrap the incoming prompt as a user message for each expert and request a response. - initial_message = ChatMessage(Role.USER, text=prompt) + initial_message = ChatMessage("user", text=prompt) await ctx.send_message(AgentExecutorRequest(messages=[initial_message], should_respond=True)) diff --git a/python/samples/semantic-kernel-migration/orchestrations/handoff.py b/python/samples/semantic-kernel-migration/orchestrations/handoff.py index bd4cfccec4..a90c8acf14 100644 --- a/python/samples/semantic-kernel-migration/orchestrations/handoff.py +++ b/python/samples/semantic-kernel-migration/orchestrations/handoff.py @@ -13,7 +13,6 @@ RequestInfoEvent, WorkflowEvent, WorkflowOutputEvent, - tool, ) from agent_framework.azure import AzureOpenAIChatClient from azure.identity import AzureCliCredential @@ -269,7 +268,7 @@ async def run_agent_framework_example(initial_task: str, scripted_responses: Seq text = message.text or "" if not text.strip(): continue - speaker = message.author_name or message.role.value + speaker = message.author_name or message.role lines.append(f"{speaker}: {text}") return "\n".join(lines) diff --git a/python/samples/semantic-kernel-migration/orchestrations/sequential.py b/python/samples/semantic-kernel-migration/orchestrations/sequential.py index 0a2bafb3bb..3b66ab2538 100644 --- a/python/samples/semantic-kernel-migration/orchestrations/sequential.py +++ b/python/samples/semantic-kernel-migration/orchestrations/sequential.py @@ -6,7 +6,7 @@ from collections.abc import Sequence from typing import cast -from agent_framework import ChatMessage, Role, SequentialBuilder, WorkflowOutputEvent +from agent_framework import ChatMessage, SequentialBuilder, WorkflowOutputEvent from agent_framework.azure import AzureOpenAIChatClient from azure.identity import AzureCliCredential from semantic_kernel.agents import Agent, ChatCompletionAgent, SequentialOrchestration @@ -109,7 +109,7 @@ def _format_conversation(conversation: list[ChatMessage]) -> None: print("===== Agent Framework Sequential =====") for index, message in enumerate(conversation, start=1): - name = message.author_name or ("assistant" if message.role == Role.ASSISTANT else "user") + name = message.author_name or ("assistant" if message.role == "assistant" else "user") print(f"{'-' * 60}\n{index:02d} [{name}]\n{message.text}") print() diff --git a/python/samples/semantic-kernel-migration/processes/nested_process.py b/python/samples/semantic-kernel-migration/processes/nested_process.py index e649103703..884ee6f4b0 100644 --- a/python/samples/semantic-kernel-migration/processes/nested_process.py +++ b/python/samples/semantic-kernel-migration/processes/nested_process.py @@ -19,7 +19,6 @@ WorkflowExecutor, WorkflowOutputEvent, handler, - tool, ) from pydantic import BaseModel, Field diff --git a/python/tests/samples/getting_started/test_agent_samples.py b/python/tests/samples/getting_started/test_agent_samples.py index e1a8595193..1042dafae7 100644 --- a/python/tests/samples/getting_started/test_agent_samples.py +++ b/python/tests/samples/getting_started/test_agent_samples.py @@ -16,9 +16,6 @@ from samples.getting_started.agents.azure_ai.azure_ai_with_function_tools import ( tools_on_run_level as azure_ai_with_function_tools_run, ) -from samples.getting_started.agents.azure_ai.azure_ai_with_local_mcp import ( - main as azure_ai_with_local_mcp, -) from samples.getting_started.agents.azure_ai.azure_ai_basic import ( main as azure_ai_basic, @@ -32,6 +29,9 @@ from samples.getting_started.agents.azure_ai.azure_ai_with_explicit_settings import ( main as azure_ai_with_explicit_settings, ) +from samples.getting_started.agents.azure_ai.azure_ai_with_local_mcp import ( + main as azure_ai_with_local_mcp, +) from samples.getting_started.agents.azure_ai.azure_ai_with_thread import ( main as azure_ai_with_thread, )