diff --git a/.dockerignore b/.dockerignore index f1fa1a8..a9629f6 100644 --- a/.dockerignore +++ b/.dockerignore @@ -1,23 +1,15 @@ -# Exclude large directories to keep build context small -node_modules/ -.git/ -frontend/node_modules/ -frontend/dist/ -infra-cdk/node_modules/ -infra-cdk/cdk.out/ -.ruff_cache/ -__pycache__/ -*.pyc -.pytest_cache/ -.coverage -htmlcov/ -dist/ -build/ -*.egg-info/ -.vscode/ -.idea/ +# Default-deny the repo root and only include the runtime inputs we need. +** -# Keep only what we need for Docker builds -!gateway/ +!.dockerignore !pyproject.toml +!gateway/ +!gateway/** !patterns/ +!patterns/** +!tools/ +!tools/** +!ag_ui_langgraph/ +!ag_ui_langgraph/** +!copilotkit/ +!copilotkit/** diff --git a/ag_ui_langgraph/__init__.py b/ag_ui_langgraph/__init__.py new file mode 100644 index 0000000..2b69e1a --- /dev/null +++ b/ag_ui_langgraph/__init__.py @@ -0,0 +1,35 @@ +from .agent import LangGraphAgent +from .types import ( + LangGraphEventTypes, + CustomEventNames, + State, + SchemaKeys, + MessageInProgress, + RunMetadata, + MessagesInProgressRecord, + ToolCall, + BaseLangGraphPlatformMessage, + LangGraphPlatformResultMessage, + LangGraphPlatformActionExecutionMessage, + LangGraphPlatformMessage, + PredictStateTool +) +from .endpoint import add_langgraph_fastapi_endpoint + +__all__ = [ + "LangGraphAgent", + "LangGraphEventTypes", + "CustomEventNames", + "State", + "SchemaKeys", + "MessageInProgress", + "RunMetadata", + "MessagesInProgressRecord", + "ToolCall", + "BaseLangGraphPlatformMessage", + "LangGraphPlatformResultMessage", + "LangGraphPlatformActionExecutionMessage", + "LangGraphPlatformMessage", + "PredictStateTool", + "add_langgraph_fastapi_endpoint" +] diff --git a/ag_ui_langgraph/agent.py b/ag_ui_langgraph/agent.py new file mode 100644 index 0000000..469f994 --- /dev/null +++ b/ag_ui_langgraph/agent.py @@ -0,0 +1,1064 @@ +import re +import uuid +import json +from typing import Optional, List, Any, Union, AsyncGenerator, Generator, Literal, Dict +import inspect + +from langgraph.graph.state import CompiledStateGraph + +try: + from langchain.schema import BaseMessage, SystemMessage, ToolMessage +except ImportError: + # Langchain >= 1.0.0 + from langchain_core.messages import BaseMessage, SystemMessage, ToolMessage + +from langchain_core.runnables import RunnableConfig, ensure_config +from langchain_core.messages import AIMessage, HumanMessage +from langgraph.types import Command + +from .types import ( + State, + LangGraphPlatformMessage, + MessagesInProgressRecord, + SchemaKeys, + MessageInProgress, + RunMetadata, + LangGraphEventTypes, + CustomEventNames, + LangGraphReasoning +) +from .utils import ( + agui_messages_to_langchain, + DEFAULT_SCHEMA_KEYS, + filter_object_by_schema_keys, + get_stream_payload_input, + langchain_messages_to_agui, + resolve_reasoning_content, + resolve_encrypted_reasoning_content, + resolve_message_content, + camel_to_snake, + json_safe_stringify, + make_json_safe, + normalize_tool_content +) + +from ag_ui.core import ( + EventType, + CustomEvent, + MessagesSnapshotEvent, + RawEvent, + RunAgentInput, + RunErrorEvent, + RunFinishedEvent, + RunStartedEvent, + StateDeltaEvent, + StateSnapshotEvent, + StepFinishedEvent, + StepStartedEvent, + TextMessageContentEvent, + TextMessageEndEvent, + TextMessageStartEvent, + ToolCallArgsEvent, + ToolCallEndEvent, + ToolCallStartEvent, + ToolCallResultEvent, + ReasoningStartEvent, + ReasoningMessageStartEvent, + ReasoningMessageContentEvent, + ReasoningMessageEndEvent, + ReasoningEndEvent, + ReasoningEncryptedValueEvent, +) +from ag_ui.encoder import EventEncoder + +ProcessedEvents = Union[ + TextMessageStartEvent, + TextMessageContentEvent, + TextMessageEndEvent, + ReasoningStartEvent, + ReasoningMessageStartEvent, + ReasoningMessageContentEvent, + ReasoningMessageEndEvent, + ReasoningEndEvent, + ReasoningEncryptedValueEvent, + ToolCallStartEvent, + ToolCallArgsEvent, + ToolCallEndEvent, + StateSnapshotEvent, + StateDeltaEvent, + MessagesSnapshotEvent, + RawEvent, + CustomEvent, + RunStartedEvent, + RunFinishedEvent, + RunErrorEvent, + StepStartedEvent, + StepFinishedEvent, +] + +class LangGraphAgent: + def __init__(self, *, name: str, graph: CompiledStateGraph, description: Optional[str] = None, config: Union[Optional[RunnableConfig], dict] = None): + self.name = name + self.description = description + self.graph = graph + self.config = config or {} + self.messages_in_process: MessagesInProgressRecord = {} + self.active_run: Optional[RunMetadata] = None + self.constant_schema_keys = ['messages', 'tools'] + + def _dispatch_event(self, event: ProcessedEvents) -> str: + if event.type == EventType.RAW: + event.event = make_json_safe(event.event) + elif event.raw_event: + event.raw_event = make_json_safe(event.raw_event) + + return event + + async def run(self, input: RunAgentInput) -> AsyncGenerator[str, None]: + forwarded_props = {} + if hasattr(input, "forwarded_props") and input.forwarded_props: + forwarded_props = { + camel_to_snake(k): v for k, v in input.forwarded_props.items() + } + async for event_str in self._handle_stream_events(input.copy(update={"forwarded_props": forwarded_props})): + yield event_str + + async def _handle_stream_events(self, input: RunAgentInput) -> AsyncGenerator[str, None]: + thread_id = input.thread_id or str(uuid.uuid4()) + INITIAL_ACTIVE_RUN = { + "id": input.run_id, + "thread_id": thread_id, + "reasoning_process": None, + "node_name": None, + "has_function_streaming": False, + } + self.active_run = INITIAL_ACTIVE_RUN + + forwarded_props = input.forwarded_props + node_name_input = forwarded_props.get('node_name', None) if forwarded_props else None + + self.active_run["manually_emitted_state"] = None + + config = ensure_config(self.config.copy() if self.config else {}) + config["configurable"] = {**(config.get('configurable', {})), "thread_id": thread_id} + + agent_state = await self.graph.aget_state(config) + resume_input = forwarded_props.get('command', {}).get('resume', None) + + if resume_input is None and thread_id and self.active_run.get("node_name") != "__end__" and self.active_run.get("node_name"): + self.active_run["mode"] = "continue" + else: + self.active_run["mode"] = "start" + + prepared_stream_response = await self.prepare_stream(input=input, agent_state=agent_state, config=config) + + yield self._dispatch_event( + RunStartedEvent(type=EventType.RUN_STARTED, thread_id=thread_id, run_id=self.active_run["id"]) + ) + self.handle_node_change(node_name_input) + + # In case of resume (interrupt), re-start resumed step + if resume_input and self.active_run.get("node_name"): + for ev in self.handle_node_change(self.active_run.get("node_name")): + yield ev + + state = prepared_stream_response["state"] + stream = prepared_stream_response["stream"] + config = prepared_stream_response["config"] + events_to_dispatch = prepared_stream_response.get('events_to_dispatch', None) + + if events_to_dispatch is not None and len(events_to_dispatch) > 0: + for event in events_to_dispatch: + yield self._dispatch_event(event) + return + + should_exit = False + current_graph_state = state + + try: + async for event in stream: + subgraphs_stream_enabled = input.forwarded_props.get('stream_subgraphs') if input.forwarded_props else False + is_subgraph_stream = (subgraphs_stream_enabled and ( + event.get("event", "").startswith("events") or + event.get("event", "").startswith("values") + )) + if event["event"] == "error": + yield self._dispatch_event( + RunErrorEvent(type=EventType.RUN_ERROR, message=event["data"]["message"], raw_event=event) + ) + break + + current_node_name = event.get("metadata", {}).get("langgraph_node") + event_type = event.get("event") + self.active_run["id"] = event.get("run_id") + exiting_node = False + + if event_type == "on_chain_end" and isinstance( + event.get("data", {}).get("output"), dict + ): + current_graph_state.update(event["data"]["output"]) + exiting_node = self.active_run["node_name"] == current_node_name + + should_exit = should_exit or ( + event_type == "on_custom_event" and + event["name"] == "exit" + ) + + if current_node_name and current_node_name != self.active_run.get("node_name"): + for ev in self.handle_node_change(current_node_name): + yield ev + + updated_state = self.active_run.get("manually_emitted_state") or current_graph_state + has_state_diff = updated_state != state + if exiting_node or (has_state_diff and not self.get_message_in_progress(self.active_run["id"])): + state = updated_state + self.active_run["prev_node_name"] = self.active_run["node_name"] + current_graph_state.update(updated_state) + yield self._dispatch_event( + StateSnapshotEvent( + type=EventType.STATE_SNAPSHOT, + snapshot=self.get_state_snapshot(state), + raw_event=event, + ) + ) + + yield self._dispatch_event( + RawEvent(type=EventType.RAW, event=event) + ) + + async for single_event in self._handle_single_event(event, state): + yield single_event + + state = await self.graph.aget_state(config) + + tasks = state.tasks if len(state.tasks) > 0 else None + interrupts = tasks[0].interrupts if tasks else [] + + writes = state.metadata.get("writes", {}) or {} + node_name = self.active_run["node_name"] if interrupts else next(iter(writes), None) + next_nodes = state.next or () + is_end_node = len(next_nodes) == 0 and not interrupts + + node_name = "__end__" if is_end_node else node_name + + for interrupt in interrupts: + yield self._dispatch_event( + CustomEvent( + type=EventType.CUSTOM, + name=LangGraphEventTypes.OnInterrupt.value, + value=dump_json_safe(interrupt.value), + raw_event=interrupt, + ) + ) + + if self.active_run.get("node_name") != node_name: + for ev in self.handle_node_change(node_name): + yield ev + + state_values = state.values if state.values else state + yield self._dispatch_event( + StateSnapshotEvent(type=EventType.STATE_SNAPSHOT, snapshot=self.get_state_snapshot(state_values)) + ) + + snapshot_messages = self._filter_orphan_tool_messages(state_values.get("messages", [])) + yield self._dispatch_event( + MessagesSnapshotEvent( + type=EventType.MESSAGES_SNAPSHOT, + messages=langchain_messages_to_agui(snapshot_messages), + ) + ) + + for ev in self.handle_node_change(None): + yield ev + + yield self._dispatch_event( + RunFinishedEvent(type=EventType.RUN_FINISHED, thread_id=thread_id, run_id=self.active_run["id"]) + ) + # Reset active run to how it was before the stream started + self.active_run = INITIAL_ACTIVE_RUN + except Exception: + raise + + + async def prepare_stream(self, input: RunAgentInput, agent_state: State, config: RunnableConfig): + state_input = input.state or {} + messages = input.messages or [] + forwarded_props = input.forwarded_props or {} + thread_id = input.thread_id + + state_input["messages"] = agent_state.values.get("messages", []) + self.active_run["current_graph_state"] = agent_state.values.copy() + langchain_messages = agui_messages_to_langchain(messages) + state = self.langgraph_default_merge_state(state_input, langchain_messages, input) + self.active_run["current_graph_state"].update(state) + config["configurable"]["thread_id"] = thread_id + interrupts = agent_state.tasks[0].interrupts if agent_state.tasks and len(agent_state.tasks) > 0 else [] + has_active_interrupts = len(interrupts) > 0 + resume_input = forwarded_props.get('command', {}).get('resume', None) + + self.active_run["schema_keys"] = self.get_schema_keys(config) + + non_system_messages = [msg for msg in langchain_messages if not isinstance(msg, SystemMessage)] + if len(agent_state.values.get("messages", [])) > len(non_system_messages): + # Only trigger time-travel regeneration if the incoming messages are NOT already + # in the checkpoint. If they are, this is a continuation (e.g. after CopilotKit + # intercepted a tool call), not a time-travel edit — regenerating would loop. + # + # We exclude ToolMessages from the ID comparison because CopilotKit assigns new + # IDs to tool results that won't match the placeholder IDs AgentCoreMemorySaver + # wrote to the checkpoint. Human and AI message IDs are stable across requests + # and are sufficient to distinguish continuation from time-travel. + incoming_non_tool_ids = { + getattr(m, "id", None) + for m in langchain_messages + if getattr(m, "id", None) and not isinstance(m, ToolMessage) + } + checkpoint_ids = {getattr(m, "id", None) for m in agent_state.values.get("messages", []) if getattr(m, "id", None)} + is_continuation = bool(incoming_non_tool_ids) and incoming_non_tool_ids.issubset(checkpoint_ids) + + if not is_continuation: + # Find the last user message by working backwards from the last message + last_user_message = None + for i in range(len(langchain_messages) - 1, -1, -1): + if isinstance(langchain_messages[i], HumanMessage): + last_user_message = langchain_messages[i] + break + + if last_user_message: + last_user_id = getattr(last_user_message, "id", None) + # Only time-travel if the message already exists in the checkpoint. + # A brand-new follow-up message (not yet in any checkpoint) is a + # continuation turn, not a time-travel edit — fall through to normal + # mode which merges the new message via langgraph_default_merge_state. + if last_user_id and last_user_id in checkpoint_ids: + return await self.prepare_regenerate_stream( + input=input, + message_checkpoint=last_user_message, + config=config + ) + + events_to_dispatch = [] + if has_active_interrupts and not resume_input: + events_to_dispatch.append( + RunStartedEvent(type=EventType.RUN_STARTED, thread_id=thread_id, run_id=self.active_run["id"]) + ) + + for interrupt in interrupts: + events_to_dispatch.append( + CustomEvent( + type=EventType.CUSTOM, + name=LangGraphEventTypes.OnInterrupt.value, + value=dump_json_safe(interrupt.value), + raw_event=interrupt, + ) + ) + + events_to_dispatch.append( + RunFinishedEvent(type=EventType.RUN_FINISHED, thread_id=thread_id, run_id=self.active_run["id"]) + ) + return { + "stream": None, + "state": None, + "config": None, + "events_to_dispatch": events_to_dispatch, + } + + if self.active_run["mode"] == "continue": + await self.graph.aupdate_state(config, state, as_node=self.active_run.get("node_name")) + + if resume_input: + if isinstance(resume_input, str): + try: + resume_input = json.loads(resume_input) + except json.JSONDecodeError: + pass # Keep as string if not valid JSON + stream_input = Command(resume=resume_input) + else: + payload_input = get_stream_payload_input( + mode=self.active_run["mode"], + state=state, + schema_keys=self.active_run["schema_keys"], + ) + stream_input = {**forwarded_props, **payload_input} if payload_input else None + + + subgraphs_stream_enabled = input.forwarded_props.get('stream_subgraphs') if input.forwarded_props else False + + kwargs = self.get_stream_kwargs( + input=stream_input, + config=config, + subgraphs=bool(subgraphs_stream_enabled), + version="v2", + ) + + stream = self.graph.astream_events(**kwargs) + + return { + "stream": stream, + "state": state, + "config": config + } + + async def prepare_regenerate_stream( # pylint: disable=too-many-arguments + self, + input: RunAgentInput, + message_checkpoint: HumanMessage, + config: RunnableConfig + ): + tools = input.tools or [] + thread_id = input.thread_id + + time_travel_checkpoint = await self.get_checkpoint_before_message(message_checkpoint.id, thread_id, config) + if time_travel_checkpoint is None: + return None + + fork = await self.graph.aupdate_state( + time_travel_checkpoint.config, + time_travel_checkpoint.values, + as_node=time_travel_checkpoint.next[0] if time_travel_checkpoint.next else "__start__" + ) + + stream_input = self.langgraph_default_merge_state(time_travel_checkpoint.values, [message_checkpoint], input) + subgraphs_stream_enabled = input.forwarded_props.get('stream_subgraphs') if input.forwarded_props else False + + kwargs = self.get_stream_kwargs( + input=stream_input, + config=fork, + subgraphs=bool(subgraphs_stream_enabled), + version="v2", + ) + stream = self.graph.astream_events(**kwargs) + + return { + "stream": stream, + "state": time_travel_checkpoint.values, + "config": config + } + + def get_message_in_progress(self, run_id: str) -> Optional[MessageInProgress]: + return self.messages_in_process.get(run_id) + + def set_message_in_progress(self, run_id: str, data: MessageInProgress): + current_message_in_progress = self.messages_in_process.get(run_id) or {} + self.messages_in_process[run_id] = { + **current_message_in_progress, + **data, + } + + def get_schema_keys(self, config) -> SchemaKeys: + try: + input_schema = self.graph.get_input_jsonschema(config) + output_schema = self.graph.get_output_jsonschema(config) + config_schema = self.graph.config_schema().schema() + + input_schema_keys = list(input_schema["properties"].keys()) if "properties" in input_schema else [] + output_schema_keys = list(output_schema["properties"].keys()) if "properties" in output_schema else [] + config_schema_keys = list(config_schema["properties"].keys()) if "properties" in config_schema else [] + context_schema_keys = [] + + if hasattr(self.graph, "context_schema") and self.graph.context_schema is not None: + context_schema = self.graph.context_schema().schema() + context_schema_keys = list(context_schema["properties"].keys()) if "properties" in context_schema else [] + + + return { + "input": [*input_schema_keys, *self.constant_schema_keys], + "output": [*output_schema_keys, *self.constant_schema_keys], + "config": config_schema_keys, + "context": context_schema_keys, + } + except Exception: + return { + "input": self.constant_schema_keys, + "output": self.constant_schema_keys, + "config": [], + "context": [], + } + + def langgraph_default_merge_state(self, state: State, messages: List[BaseMessage], input: RunAgentInput) -> State: + if messages and isinstance(messages[0], SystemMessage): + messages = messages[1:] + + existing_messages: List[LangGraphPlatformMessage] = state.get("messages", []) + + # Fix tool_call args that are strings instead of dicts. + # This happens when CopilotKit's after_agent restores frontend tool_calls + # and the checkpoint saves them with string args. Bedrock Converse API + # requires toolUse.input to be a JSON object (dict). + for msg in existing_messages: + if isinstance(msg, AIMessage) and getattr(msg, 'tool_calls', None): + for tc in msg.tool_calls: + if isinstance(tc.get('args'), str): + try: + tc['args'] = json.loads(tc['args']) + except (json.JSONDecodeError, TypeError): + tc['args'] = {} + + # Pass all incoming messages that aren't already in the checkpoint. + # Incoming ToolMessages (CopilotKit frontend tool results) are included here; + # patch_orphan_tool_calls adds a placeholder with a new random ID on every + # checkpoint load, so ID-based replacement is unreliable. Instead, we let + # both the placeholder and the real ToolMessage coexist in the graph state, + # and _fix_messages_for_bedrock deduplicates by tool_call_id before each + # Converse API call (keeping the real result over the interrupted placeholder). + existing_message_ids = {msg.id for msg in existing_messages} + new_messages = [ + msg for msg in messages + if msg.id not in existing_message_ids + ] + + tools = input.tools or [] + tools_as_dicts = [] + if tools: + for tool in tools: + if hasattr(tool, "model_dump"): + tools_as_dicts.append(tool.model_dump()) + elif hasattr(tool, "dict"): + tools_as_dicts.append(tool.dict()) + else: + tools_as_dicts.append(tool) + + all_tools = [*state.get("tools", []), *tools_as_dicts] + + # Remove duplicates based on tool name + seen_names = set() + unique_tools = [] + for tool in all_tools: + tool_name = tool.get("name") if isinstance(tool, dict) else getattr(tool, "name", None) + if tool_name and tool_name not in seen_names: + seen_names.add(tool_name) + unique_tools.append(tool) + elif not tool_name: + # Keep tools without names (shouldn't happen, but just in case) + unique_tools.append(tool) + + return { + **state, + "messages": new_messages, + "tools": unique_tools, + "ag-ui": { + "tools": unique_tools, + "context": input.context or [] + }, + "copilotkit": { + **state.get("copilotkit", {}), + "actions": unique_tools, + }, + } + + _ORPHAN_TOOL_MSG_RE = re.compile( + r"^Tool call '.+' with id '.+' was interrupted before completion\.$" + ) + + def _filter_orphan_tool_messages(self, messages: list) -> list: + """Remove fake ToolMessages injected by patch_orphan_tool_calls, + but only between the last user message and the end of the list.""" + # Find the index of the last HumanMessage + last_human_idx = -1 + for i in range(len(messages) - 1, -1, -1): + if isinstance(messages[i], HumanMessage): + last_human_idx = i + break + + if last_human_idx == -1: + return messages + + # Keep everything before the last user message as-is, + # filter the tail + head = messages[:last_human_idx + 1] + tail = [ + m for m in messages[last_human_idx + 1:] + if not ( + isinstance(m, ToolMessage) + and isinstance(m.content, str) + and self._ORPHAN_TOOL_MSG_RE.match(m.content) + ) + ] + return head + tail + + def get_state_snapshot(self, state: State) -> State: + schema_keys = self.active_run["schema_keys"] + if schema_keys and schema_keys.get("output"): + state = filter_object_by_schema_keys(state, [*DEFAULT_SCHEMA_KEYS, *schema_keys["output"]]) + return state + + async def _handle_single_event(self, event: Any, state: State) -> AsyncGenerator[str, None]: + event_type = event.get("event") + if event_type == LangGraphEventTypes.OnChatModelStream: + should_emit_messages = event["metadata"].get("emit-messages", True) + should_emit_tool_calls = event["metadata"].get("emit-tool-calls", True) + + if event["data"]["chunk"].response_metadata.get('finish_reason', None): + return + + current_stream = self.get_message_in_progress(self.active_run["id"]) + has_current_stream = bool(current_stream and current_stream.get("id")) + tool_call_data = event["data"]["chunk"].tool_call_chunks[0] if event["data"]["chunk"].tool_call_chunks else None + predict_state_metadata = event["metadata"].get("predict_state", []) + tool_call_used_to_predict_state = False + if tool_call_data and tool_call_data.get("name") and predict_state_metadata: + tool_call_used_to_predict_state = any( + predict_tool.get("tool") == tool_call_data["name"] + for predict_tool in predict_state_metadata + ) + + is_tool_call_start_event = not has_current_stream and tool_call_data and tool_call_data.get("name") + is_tool_call_args_event = has_current_stream and current_stream.get("tool_call_id") and tool_call_data and tool_call_data.get("args") + is_tool_call_end_event = has_current_stream and current_stream.get("tool_call_id") and not tool_call_data + + if is_tool_call_start_event or is_tool_call_end_event or is_tool_call_args_event: + self.active_run["has_function_streaming"] = True + + reasoning_data = resolve_reasoning_content(event["data"]["chunk"]) if event["data"]["chunk"] else None + encrypted_reasoning_data = resolve_encrypted_reasoning_content(event["data"]["chunk"]) if event["data"]["chunk"] else None + message_content = resolve_message_content(event["data"]["chunk"].content) if event["data"]["chunk"] and event["data"]["chunk"].content else None + is_message_content_event = tool_call_data is None and message_content + is_message_end_event = has_current_stream and not current_stream.get("tool_call_id") and not is_message_content_event + + if reasoning_data: + for event_str in self.handle_reasoning_event(reasoning_data): + yield event_str + return + + # Handle redacted_thinking blocks (encrypted reasoning content) + if encrypted_reasoning_data and self.active_run.get('reasoning_process', None) is not None: + reasoning_message_id = self.active_run["reasoning_process"]["message_id"] + yield self._dispatch_event( + ReasoningEncryptedValueEvent( + type=EventType.REASONING_ENCRYPTED_VALUE, + subtype="message", + entity_id=reasoning_message_id, + encrypted_value=encrypted_reasoning_data, + ) + ) + return + + if reasoning_data is None and self.active_run.get('reasoning_process', None) is not None: + reasoning_message_id = self.active_run["reasoning_process"]["message_id"] + # Emit signature as encrypted value if accumulated during reasoning + if self.active_run["reasoning_process"].get("signature"): + yield self._dispatch_event( + ReasoningEncryptedValueEvent( + type=EventType.REASONING_ENCRYPTED_VALUE, + subtype="message", + entity_id=reasoning_message_id, + encrypted_value=self.active_run["reasoning_process"]["signature"], + ) + ) + yield self._dispatch_event( + ReasoningMessageEndEvent( + type=EventType.REASONING_MESSAGE_END, + message_id=reasoning_message_id, + ) + ) + yield self._dispatch_event( + ReasoningEndEvent( + type=EventType.REASONING_END, + message_id=reasoning_message_id, + ) + ) + self.active_run["reasoning_process"] = None + + if tool_call_used_to_predict_state: + yield self._dispatch_event( + CustomEvent( + type=EventType.CUSTOM, + name="PredictState", + value=predict_state_metadata, + raw_event=event + ) + ) + + if is_tool_call_end_event: + yield self._dispatch_event( + ToolCallEndEvent(type=EventType.TOOL_CALL_END, tool_call_id=current_stream["tool_call_id"], raw_event=event) + ) + self.messages_in_process[self.active_run["id"]] = None + return + + + if is_message_end_event: + yield self._dispatch_event( + TextMessageEndEvent(type=EventType.TEXT_MESSAGE_END, message_id=current_stream["id"], raw_event=event) + ) + self.messages_in_process[self.active_run["id"]] = None + return + + if is_tool_call_start_event and should_emit_tool_calls: + yield self._dispatch_event( + ToolCallStartEvent( + type=EventType.TOOL_CALL_START, + tool_call_id=tool_call_data["id"], + tool_call_name=tool_call_data["name"], + parent_message_id=event["data"]["chunk"].id, + raw_event=event, + ) + ) + self.set_message_in_progress( + self.active_run["id"], + MessageInProgress(id=event["data"]["chunk"].id, tool_call_id=tool_call_data["id"], tool_call_name=tool_call_data["name"]) + ) + return + + if is_tool_call_args_event and should_emit_tool_calls: + yield self._dispatch_event( + ToolCallArgsEvent( + type=EventType.TOOL_CALL_ARGS, + tool_call_id=current_stream["tool_call_id"], + delta=tool_call_data["args"], + raw_event=event + ) + ) + return + + if is_message_content_event and should_emit_messages: + if bool(current_stream and current_stream.get("id")) == False: + yield self._dispatch_event( + TextMessageStartEvent( + type=EventType.TEXT_MESSAGE_START, + role="assistant", + message_id=event["data"]["chunk"].id, + raw_event=event, + ) + ) + self.set_message_in_progress( + self.active_run["id"], + MessageInProgress( + id=event["data"]["chunk"].id, + tool_call_id=None, + tool_call_name=None + ) + ) + current_stream = self.get_message_in_progress(self.active_run["id"]) + + yield self._dispatch_event( + TextMessageContentEvent( + type=EventType.TEXT_MESSAGE_CONTENT, + message_id=current_stream["id"], + delta=message_content, + raw_event=event, + ) + ) + return + + elif event_type == LangGraphEventTypes.OnChatModelEnd: + if self.get_message_in_progress(self.active_run["id"]) and self.get_message_in_progress(self.active_run["id"]).get("tool_call_id"): + resolved = self._dispatch_event( + ToolCallEndEvent(type=EventType.TOOL_CALL_END, tool_call_id=self.get_message_in_progress(self.active_run["id"])["tool_call_id"], raw_event=event) + ) + if resolved: + self.messages_in_process[self.active_run["id"]] = None + yield resolved + elif self.get_message_in_progress(self.active_run["id"]) and self.get_message_in_progress(self.active_run["id"]).get("id"): + resolved = self._dispatch_event( + TextMessageEndEvent(type=EventType.TEXT_MESSAGE_END, message_id=self.get_message_in_progress(self.active_run["id"])["id"], raw_event=event) + ) + if resolved: + self.messages_in_process[self.active_run["id"]] = None + yield resolved + + elif event_type == LangGraphEventTypes.OnCustomEvent: + if event["name"] == CustomEventNames.ManuallyEmitMessage: + yield self._dispatch_event( + TextMessageStartEvent(type=EventType.TEXT_MESSAGE_START, role="assistant", message_id=event["data"]["message_id"], raw_event=event) + ) + yield self._dispatch_event( + TextMessageContentEvent( + type=EventType.TEXT_MESSAGE_CONTENT, + message_id=event["data"]["message_id"], + delta=event["data"]["message"], + raw_event=event, + ) + ) + yield self._dispatch_event( + TextMessageEndEvent(type=EventType.TEXT_MESSAGE_END, message_id=event["data"]["message_id"], raw_event=event) + ) + + elif event["name"] == CustomEventNames.ManuallyEmitToolCall: + yield self._dispatch_event( + ToolCallStartEvent( + type=EventType.TOOL_CALL_START, + tool_call_id=event["data"]["id"], + tool_call_name=event["data"]["name"], + parent_message_id=event["data"]["id"], + raw_event=event, + ) + ) + yield self._dispatch_event( + ToolCallArgsEvent( + type=EventType.TOOL_CALL_ARGS, + tool_call_id=event["data"]["id"], + delta=event["data"]["args"] if isinstance(event["data"]["args"], str) else json.dumps( + event["data"]["args"]), + raw_event=event + ) + ) + yield self._dispatch_event( + ToolCallEndEvent(type=EventType.TOOL_CALL_END, tool_call_id=event["data"]["id"], raw_event=event) + ) + + elif event["name"] == CustomEventNames.ManuallyEmitState: + self.active_run["manually_emitted_state"] = event["data"] + yield self._dispatch_event( + StateSnapshotEvent(type=EventType.STATE_SNAPSHOT, snapshot=self.get_state_snapshot(self.active_run["manually_emitted_state"]), raw_event=event) + ) + + yield self._dispatch_event( + CustomEvent(type=EventType.CUSTOM, name=event["name"], value=event["data"], raw_event=event) + ) + + elif event_type == LangGraphEventTypes.OnToolEnd: + tool_call_output = event["data"]["output"] + + if isinstance(tool_call_output, Command): + # Extract ToolMessages from Command.update + messages = tool_call_output.update.get('messages', []) + tool_messages = [m for m in messages if isinstance(m, ToolMessage)] + + # Process each tool message + for tool_msg in tool_messages: + if not self.active_run["has_function_streaming"]: + yield self._dispatch_event( + ToolCallStartEvent( + type=EventType.TOOL_CALL_START, + tool_call_id=tool_msg.tool_call_id, + tool_call_name=tool_msg.name, + parent_message_id=tool_msg.id, + raw_event=event, + ) + ) + yield self._dispatch_event( + ToolCallArgsEvent( + type=EventType.TOOL_CALL_ARGS, + tool_call_id=tool_msg.tool_call_id, + delta=json.dumps(event["data"].get("input", {})), + raw_event=event + ) + ) + yield self._dispatch_event( + ToolCallEndEvent( + type=EventType.TOOL_CALL_END, + tool_call_id=tool_msg.tool_call_id, + raw_event=event + ) + ) + + yield self._dispatch_event( + ToolCallResultEvent( + type=EventType.TOOL_CALL_RESULT, + tool_call_id=tool_msg.tool_call_id, + message_id=str(uuid.uuid4()), + content=normalize_tool_content(tool_msg.content), + role="tool" + ) + ) + return + + if not self.active_run["has_function_streaming"]: + yield self._dispatch_event( + ToolCallStartEvent( + type=EventType.TOOL_CALL_START, + tool_call_id=tool_call_output.tool_call_id, + tool_call_name=tool_call_output.name, + parent_message_id=tool_call_output.id, + raw_event=event, + ) + ) + yield self._dispatch_event( + ToolCallArgsEvent( + type=EventType.TOOL_CALL_ARGS, + tool_call_id=tool_call_output.tool_call_id, + delta=dump_json_safe(event["data"]["input"]), + raw_event=event + ) + ) + yield self._dispatch_event( + ToolCallEndEvent( + type=EventType.TOOL_CALL_END, + tool_call_id=tool_call_output.tool_call_id, + raw_event=event + ) + ) + + yield self._dispatch_event( + ToolCallResultEvent( + type=EventType.TOOL_CALL_RESULT, + tool_call_id=tool_call_output.tool_call_id, + message_id=str(uuid.uuid4()), + content=normalize_tool_content(tool_call_output.content), + role="tool" + ) + ) + + def handle_reasoning_event(self, reasoning_data: LangGraphReasoning) -> Generator[str, Any, str | None]: + if not reasoning_data or "type" not in reasoning_data or "text" not in reasoning_data: + return "" + + reasoning_step_index = reasoning_data.get("index") + + if (self.active_run.get("reasoning_process") and + self.active_run["reasoning_process"].get("index") and + self.active_run["reasoning_process"]["index"] != reasoning_step_index): + + reasoning_message_id = self.active_run["reasoning_process"]["message_id"] + if self.active_run["reasoning_process"].get("type"): + yield self._dispatch_event( + ReasoningMessageEndEvent( + type=EventType.REASONING_MESSAGE_END, + message_id=reasoning_message_id, + ) + ) + yield self._dispatch_event( + ReasoningEndEvent( + type=EventType.REASONING_END, + message_id=reasoning_message_id, + ) + ) + self.active_run["reasoning_process"] = None + + if not self.active_run.get("reasoning_process"): + message_id = str(uuid.uuid4()) + yield self._dispatch_event( + ReasoningStartEvent( + type=EventType.REASONING_START, + message_id=message_id, + ) + ) + self.active_run["reasoning_process"] = { + "index": reasoning_step_index, + "message_id": message_id, + } + + if self.active_run["reasoning_process"].get("type") != reasoning_data["type"]: + yield self._dispatch_event( + ReasoningMessageStartEvent( + type=EventType.REASONING_MESSAGE_START, + message_id=self.active_run["reasoning_process"]["message_id"], + role="assistant", + ) + ) + self.active_run["reasoning_process"]["type"] = reasoning_data["type"] + + # Accumulate signature if present (Anthropic extended thinking) + if reasoning_data.get("signature"): + self.active_run["reasoning_process"]["signature"] = reasoning_data["signature"] + + if self.active_run["reasoning_process"].get("type"): + yield self._dispatch_event( + ReasoningMessageContentEvent( + type=EventType.REASONING_MESSAGE_CONTENT, + message_id=self.active_run["reasoning_process"]["message_id"], + delta=reasoning_data["text"] + ) + ) + + async def get_checkpoint_before_message(self, message_id: str, thread_id: str, config: Optional[RunnableConfig] = None): + if not thread_id: + raise ValueError("Missing thread_id in config") + + history_config = {**(config or {}), "configurable": {**(config.get("configurable", {}) if config else {}), "thread_id": thread_id}} + history_list = [] + async for snapshot in self.graph.aget_state_history(history_config): + history_list.append(snapshot) + + history_list.reverse() + for idx, snapshot in enumerate(history_list): + messages = snapshot.values.get("messages", []) + if any(getattr(m, "id", None) == message_id for m in messages): + if idx == 0: + # No snapshot before this + # Return synthetic "empty before" version + empty_snapshot = snapshot + empty_snapshot.values["messages"] = [] + return empty_snapshot + + snapshot_values_without_messages = snapshot.values.copy() + del snapshot_values_without_messages["messages"] + checkpoint = history_list[idx - 1] + + merged_values = {**checkpoint.values, **snapshot_values_without_messages} + checkpoint = checkpoint._replace(values=merged_values) + + return checkpoint + + raise ValueError("Message ID not found in history") + + def handle_node_change(self, node_name: Optional[str]): + """ + Centralized method to handle node name changes and step transitions. + Automatically manages step start/end events based on node name changes. + """ + if node_name == "__end__": + node_name = None + + if node_name != self.active_run.get("node_name"): + # End current step if we have one + if self.active_run.get("node_name"): + yield self.end_step() + + # Start new step if we have a node name + if node_name: + for event in self.start_step(node_name): + yield event + + self.active_run["node_name"] = node_name + + def start_step(self, step_name: str): + """Simple step start event dispatcher - node_name management handled by handle_node_change""" + yield self._dispatch_event( + StepStartedEvent( + type=EventType.STEP_STARTED, + step_name=step_name + ) + ) + + def end_step(self): + """Simple step end event dispatcher - node_name management handled by handle_node_change""" + if not self.active_run.get("node_name"): + raise ValueError("No active step to end") + + return self._dispatch_event( + StepFinishedEvent( + type=EventType.STEP_FINISHED, + step_name=self.active_run["node_name"] + ) + ) + + # Check if some kwargs are enabled per LG version, to "catch all versions" and backwards compatibility + def get_stream_kwargs( + self, + input: Any, + subgraphs: bool = False, + version: Literal["v1", "v2"] = "v2", + config: Optional[RunnableConfig] = None, + context: Optional[Dict[str, Any]] = None, + fork: Optional[Any] = None, + ): + kwargs = dict( + input=input, + subgraphs=subgraphs, + version=version, + ) + + # Only add context if supported + sig = inspect.signature(self.graph.astream_events) + if 'context' in sig.parameters: + base_context = {} + if isinstance(config, dict) and 'configurable' in config and isinstance(config['configurable'], dict): + base_context.update(config['configurable']) + if context: # context might be None or {} + base_context.update(context) + if base_context: # only add if there's something to pass + kwargs['context'] = base_context + + if config: + kwargs['config'] = config + + if fork: + kwargs.update(fork) + + return kwargs + + +def dump_json_safe(value): + return json.dumps(value, default=json_safe_stringify) if not isinstance(value, str) else value \ No newline at end of file diff --git a/ag_ui_langgraph/endpoint.py b/ag_ui_langgraph/endpoint.py new file mode 100644 index 0000000..e2b5e35 --- /dev/null +++ b/ag_ui_langgraph/endpoint.py @@ -0,0 +1,37 @@ +from fastapi import FastAPI, HTTPException, Request +from fastapi.responses import StreamingResponse + +from ag_ui.core.types import RunAgentInput +from ag_ui.encoder import EventEncoder + +from .agent import LangGraphAgent + +def add_langgraph_fastapi_endpoint(app: FastAPI, agent: LangGraphAgent, path: str = "/"): + """Adds an endpoint to the FastAPI app.""" + + @app.post(path) + async def langgraph_agent_endpoint(input_data: RunAgentInput, request: Request): + # Get the accept header from the request + accept_header = request.headers.get("accept") + + # Create an event encoder to properly format SSE events + encoder = EventEncoder(accept=accept_header) + + async def event_generator(): + async for event in agent.run(input_data): + yield encoder.encode(event) + + return StreamingResponse( + event_generator(), + media_type=encoder.get_content_type() + ) + + @app.get(f"{path}/health") + def health(): + """Health check.""" + return { + "status": "ok", + "agent": { + "name": agent.name, + } + } \ No newline at end of file diff --git a/ag_ui_langgraph/types.py b/ag_ui_langgraph/types.py new file mode 100644 index 0000000..8aef56b --- /dev/null +++ b/ag_ui_langgraph/types.py @@ -0,0 +1,94 @@ +from typing import TypedDict, Optional, List, Any, Dict, Union, Literal +from typing_extensions import NotRequired +from enum import Enum + +class LangGraphEventTypes(str, Enum): + OnChainStart = "on_chain_start" + OnChainStream = "on_chain_stream" + OnChainEnd = "on_chain_end" + OnChatModelStart = "on_chat_model_start" + OnChatModelStream = "on_chat_model_stream" + OnChatModelEnd = "on_chat_model_end" + OnToolStart = "on_tool_start" + OnToolEnd = "on_tool_end" + OnCustomEvent = "on_custom_event" + OnInterrupt = "on_interrupt" + +class CustomEventNames(str, Enum): + ManuallyEmitMessage = "manually_emit_message" + ManuallyEmitToolCall = "manually_emit_tool_call" + ManuallyEmitState = "manually_emit_state" + Exit = "exit" + +State = Dict[str, Any] + +SchemaKeys = TypedDict("SchemaKeys", { + "input": NotRequired[Optional[List[str]]], + "output": NotRequired[Optional[List[str]]], + "config": NotRequired[Optional[List[str]]], + "context": NotRequired[Optional[List[str]]] +}) + +ThinkingProcess = TypedDict("ThinkingProcess", { + "index": int, + "type": NotRequired[Optional[Literal['text']]], +}) + +MessageInProgress = TypedDict("MessageInProgress", { + "id": str, + "tool_call_id": NotRequired[Optional[str]], + "tool_call_name": NotRequired[Optional[str]] +}) + +RunMetadata = TypedDict("RunMetadata", { + "id": str, + "schema_keys": NotRequired[Optional[SchemaKeys]], + "node_name": NotRequired[Optional[str]], + "prev_node_name": NotRequired[Optional[str]], + "exiting_node": NotRequired[bool], + "manually_emitted_state": NotRequired[Optional[State]], + "thread_id": NotRequired[Optional[ThinkingProcess]], + "reasoning_process": NotRequired[Optional[str]], + "has_function_streaming": NotRequired[bool], +}) + +MessagesInProgressRecord = Dict[str, Optional[MessageInProgress]] + +ToolCall = TypedDict("ToolCall", { + "id": str, + "name": str, + "args": Dict[str, Any] +}) + +class BaseLangGraphPlatformMessage(TypedDict): + content: str + role: str + additional_kwargs: NotRequired[Dict[str, Any]] + type: str + id: str + +class LangGraphPlatformResultMessage(BaseLangGraphPlatformMessage): + tool_call_id: str + name: str + +class LangGraphPlatformActionExecutionMessage(BaseLangGraphPlatformMessage): + tool_calls: List[ToolCall] + +LangGraphPlatformMessage = Union[ + LangGraphPlatformActionExecutionMessage, + LangGraphPlatformResultMessage, + BaseLangGraphPlatformMessage, +] + +PredictStateTool = TypedDict("PredictStateTool", { + "tool": str, + "state_key": str, + "tool_argument": str +}) + +LangGraphReasoning = TypedDict("LangGraphReasoning", { + "type": str, + "text": str, + "index": int, + "signature": NotRequired[Optional[str]], +}) diff --git a/ag_ui_langgraph/utils.py b/ag_ui_langgraph/utils.py new file mode 100644 index 0000000..e199db2 --- /dev/null +++ b/ag_ui_langgraph/utils.py @@ -0,0 +1,463 @@ +import json +import re +from enum import Enum + +from pydantic import TypeAdapter +from pydantic_core import PydanticSerializationError +from typing import List, Any, Dict, Union +from dataclasses import is_dataclass, asdict, fields +from datetime import date, datetime + +from langchain_core.messages import BaseMessage, HumanMessage, AIMessage, SystemMessage, ToolMessage +from ag_ui.core import ( + Message as AGUIMessage, + UserMessage as AGUIUserMessage, + AssistantMessage as AGUIAssistantMessage, + SystemMessage as AGUISystemMessage, + ToolMessage as AGUIToolMessage, + ToolCall as AGUIToolCall, + FunctionCall as AGUIFunctionCall, + TextInputContent, + BinaryInputContent, +) +from .types import State, SchemaKeys, LangGraphReasoning + +DEFAULT_SCHEMA_KEYS = ["tools"] + +def filter_object_by_schema_keys(obj: Dict[str, Any], schema_keys: List[str]) -> Dict[str, Any]: + if not obj: + return {} + return {k: v for k, v in obj.items() if k in schema_keys} + +def get_stream_payload_input( + *, + mode: str, + state: State, + schema_keys: SchemaKeys, +) -> Union[State, None]: + input_payload = state if mode == "start" else None + if input_payload and schema_keys and schema_keys.get("input"): + input_payload = filter_object_by_schema_keys(input_payload, [*DEFAULT_SCHEMA_KEYS, *schema_keys["input"]]) + return input_payload + +def stringify_if_needed(item: Any) -> str: + if item is None: + return '' + if isinstance(item, str): + return item + return json.dumps(item) + +def convert_langchain_multimodal_to_agui(content: List[Dict[str, Any]]) -> List[Union[TextInputContent, BinaryInputContent]]: + """Convert LangChain's multimodal content to AG-UI format.""" + agui_content = [] + for item in content: + if isinstance(item, dict): + if item.get("type") == "text": + agui_content.append(TextInputContent( + type="text", + text=item.get("text", "") + )) + elif item.get("type") == "image_url": + image_url_data = item.get("image_url", {}) + url = image_url_data.get("url", "") if isinstance(image_url_data, dict) else image_url_data + + # Parse data URLs to extract base64 data + if url.startswith("data:"): + # Format: data:mime_type;base64,data + parts = url.split(",", 1) + header = parts[0] + data = parts[1] if len(parts) > 1 else "" + mime_type = header.split(":")[1].split(";")[0] if ":" in header else "image/png" + + agui_content.append(BinaryInputContent( + type="binary", + mime_type=mime_type, + data=data + )) + else: + # Regular URL or ID + agui_content.append(BinaryInputContent( + type="binary", + mime_type="image/png", # Default MIME type + url=url + )) + return agui_content + +def langchain_messages_to_agui(messages: List[BaseMessage]) -> List[AGUIMessage]: + agui_messages: List[AGUIMessage] = [] + for message in messages: + if isinstance(message, HumanMessage): + # Handle multimodal content + if isinstance(message.content, list): + content = convert_langchain_multimodal_to_agui(message.content) + else: + content = stringify_if_needed(resolve_message_content(message.content)) + + agui_messages.append(AGUIUserMessage( + id=str(message.id), + role="user", + content=content, + name=message.name, + )) + elif isinstance(message, AIMessage): + tool_calls = None + if message.tool_calls: + tool_calls = [ + AGUIToolCall( + id=str(tc["id"]), + type="function", + function=AGUIFunctionCall( + name=tc["name"], + arguments=json.dumps(tc.get("args", {})), + ), + ) + for tc in message.tool_calls + ] + + agui_messages.append(AGUIAssistantMessage( + id=str(message.id), + role="assistant", + content=stringify_if_needed(resolve_message_content(message.content)), + tool_calls=tool_calls, + name=message.name, + )) + elif isinstance(message, SystemMessage): + agui_messages.append(AGUISystemMessage( + id=str(message.id), + role="system", + content=stringify_if_needed(resolve_message_content(message.content)), + name=message.name, + )) + elif isinstance(message, ToolMessage): + agui_messages.append(AGUIToolMessage( + id=str(message.id), + role="tool", + content=stringify_if_needed(resolve_message_content(message.content)), + tool_call_id=message.tool_call_id, + )) + else: + raise TypeError(f"Unsupported message type: {type(message)}") + return agui_messages + +def convert_agui_multimodal_to_langchain(content: List[Union[TextInputContent, BinaryInputContent]]) -> List[Dict[str, Any]]: + """Convert AG-UI multimodal content to LangChain's multimodal format.""" + langchain_content = [] + for item in content: + if isinstance(item, TextInputContent): + langchain_content.append({ + "type": "text", + "text": item.text + }) + elif isinstance(item, BinaryInputContent): + # LangChain uses image_url format (OpenAI-style) + content_dict = {"type": "image_url"} + + # Prioritize url, then data, then id + if item.url: + content_dict["image_url"] = {"url": item.url} + elif item.data: + # Construct data URL from base64 data + content_dict["image_url"] = {"url": f"data:{item.mime_type};base64,{item.data}"} + elif item.id: + # Use id as a reference (some providers may support this) + content_dict["image_url"] = {"url": item.id} + + langchain_content.append(content_dict) + + return langchain_content + +def agui_messages_to_langchain(messages: List[AGUIMessage]) -> List[BaseMessage]: + langchain_messages = [] + for message in messages: + role = message.role + if role == "user": + # Handle multimodal content + if isinstance(message.content, str): + content = message.content + elif isinstance(message.content, list): + content = convert_agui_multimodal_to_langchain(message.content) + else: + content = str(message.content) + + langchain_messages.append(HumanMessage( + id=message.id, + content=content, + name=message.name, + )) + elif role == "assistant": + tool_calls = [] + if hasattr(message, "tool_calls") and message.tool_calls: + for tc in message.tool_calls: + tool_calls.append({ + "id": tc.id, + "name": tc.function.name, + "args": json.loads(tc.function.arguments) if hasattr(tc, "function") and tc.function.arguments else {}, + "type": "tool_call", + }) + langchain_messages.append(AIMessage( + id=message.id, + content=message.content or "", + tool_calls=tool_calls, + name=message.name, + )) + elif role == "system": + langchain_messages.append(SystemMessage( + id=message.id, + content=message.content, + name=message.name, + )) + elif role == "tool": + langchain_messages.append(ToolMessage( + id=message.id, + content=message.content, + tool_call_id=message.tool_call_id, + )) + else: + raise ValueError(f"Unsupported message role: {role}") + return langchain_messages + +def resolve_reasoning_content(chunk: Any) -> LangGraphReasoning | None: + content = chunk.content + if not content: + # Fall through to check additional_kwargs for OpenAI legacy format + pass + + if isinstance(content, list) and content and content[0]: + block = content[0] + block_type = block.get("type") if isinstance(block, dict) else None + + # Old langchain-anthropic format: { type: "thinking", thinking: "..." } + if block_type == "thinking" and block.get("thinking"): + result = LangGraphReasoning( + text=block["thinking"], + type="text", + index=block.get("index", 0) + ) + # Extract signature if present (Anthropic extended thinking signature) + if block.get("signature"): + result["signature"] = block["signature"] + return result + + # New LangChain standardized format: { type: "reasoning", reasoning: "..." } + if block_type == "reasoning" and block.get("reasoning"): + return LangGraphReasoning( + text=block["reasoning"], + type="text", + index=block.get("index", 0) + ) + + # OpenAI Responses API v1 format: { type: "reasoning", summary: [{ text: "..." }] } + if block_type == "reasoning" and block.get("summary"): + summaries = block["summary"] + if summaries and isinstance(summaries, list) and summaries[0]: + data = summaries[0] + if data.get("text"): + return LangGraphReasoning( + type="text", + text=data["text"], + index=data.get("index", 0) + ) + + # OpenAI legacy format via additional_kwargs + if hasattr(chunk, "additional_kwargs"): + reasoning = chunk.additional_kwargs.get("reasoning", {}) + summary = reasoning.get("summary", []) + if summary: + data = summary[0] + if not data or not data.get("text"): + return None + return LangGraphReasoning( + type="text", + text=data["text"], + index=data.get("index", 0) + ) + + return None + + +def resolve_encrypted_reasoning_content(chunk: Any) -> str | None: + """ + Resolves encrypted reasoning content from Anthropic responses. + This handles: + - `redacted_thinking` blocks with encrypted `data` (redacted chain-of-thought) + """ + content = chunk.content if chunk else None + if not content or not isinstance(content, list) or not content or not content[0]: + return None + + # Anthropic redacted_thinking block: { type: "redacted_thinking", data: "..." } + if content[0].get("type") == "redacted_thinking" and content[0].get("data"): + return content[0]["data"] + + return None + +def resolve_message_content(content: Any) -> str | None: + if not content: + return None + + if isinstance(content, str): + return content + + if isinstance(content, list) and content: + content_text = next((c.get("text") for c in content if isinstance(c, dict) and c.get("type") == "text"), None) + return content_text + + return None + + +def flatten_user_content(content: Any) -> str: + """ + Flatten multimodal content into plain text. + Used for backwards compatibility or when multimodal is not supported. + """ + if content is None: + return "" + + if isinstance(content, str): + return content + + if isinstance(content, list): + parts = [] + for item in content: + if isinstance(item, TextInputContent): + if item.text: + parts.append(item.text) + elif isinstance(item, BinaryInputContent): + # Add descriptive placeholder for binary content + if item.filename: + parts.append(f"[Binary content: {item.filename}]") + elif item.url: + parts.append(f"[Binary content: {item.url}]") + else: + parts.append(f"[Binary content: {item.mime_type}]") + return "\n".join(parts) + + return str(content) + + +def normalize_tool_content(content: Any) -> str: + """ + Normalize tool message content to a string. + Handles the various content block formats from LangChain/LangGraph. + + Content can be: + - A plain string + - A list of strings or content blocks (e.g., {"type": "text", "text": "..."}) + """ + if isinstance(content, str): + return content + + if isinstance(content, list): + parts = [] + for block in content: + if isinstance(block, str): + parts.append(block) + elif isinstance(block, dict) and block.get('type') == 'text': + parts.append(block.get('text', '')) + else: + parts.append(json.dumps(block)) + return ''.join(parts) + + return json.dumps(content) + + +def camel_to_snake(name): + return re.sub(r'(? Any: + """ + Convert `value` into something that `json.dumps` can always handle. + + Rules (in order): + - primitives → as-is + - Enum → its .value (recursively made safe) + - dict → keys & values made safe + - list/tuple/set/frozenset → list of safe values + - dataclasses → asdict() then recurse + - Pydantic-style models → model_dump()/dict()/to_dict() then recurse + - objects with __dict__ → vars(obj) then recurse + - everything else → repr(obj) + + Cycles are detected and replaced with the string "". + """ + if _seen is None: + _seen = set() + + obj_id = id(value) + if obj_id in _seen: + return "" + + # --- 1. Primitives ----------------------------------------------------- + if isinstance(value, (str, int, float, bool)) or value is None: + return value + + # --- 2. Enum → use underlying value ----------------------------------- + if isinstance(value, Enum): + return make_json_safe(value.value, _seen) + + # --- 3. Dicts ---------------------------------------------------------- + if isinstance(value, dict): + _seen.add(obj_id) + # LangGraph/LangChain tool calls inject non-serializable runtime/config; skip them. + return { + make_json_safe(k, _seen): make_json_safe(v, _seen) + for k, v in value.items() + if k not in ("runtime", "config") + } + + # --- 4. Iterable containers ------------------------------------------- + if isinstance(value, (list, tuple, set, frozenset)): + _seen.add(obj_id) + return [make_json_safe(v, _seen) for v in value] + + # --- 5. Dataclasses ---------------------------------------------------- + if is_dataclass(value): + _seen.add(obj_id) + # Skip runtime/config (LangGraph-injected, not serializable) + d = {f.name: getattr(value, f.name) for f in fields(value) if f.name not in ("runtime", "config")} + return make_json_safe(d, _seen) + + # --- 6. Pydantic-like models (v2: model_dump) ------------------------- + if hasattr(value, "model_dump") and callable(getattr(value, "model_dump")): + _seen.add(obj_id) + try: + return make_json_safe(value.model_dump(), _seen) + except Exception: + # fall through to other options + pass + + # --- 7. Pydantic v1-style / other libs with .dict() ------------------- + if hasattr(value, "dict") and callable(getattr(value, "dict")): + _seen.add(obj_id) + try: + return make_json_safe(value.dict(), _seen) + except Exception: + pass + + # --- 8. Generic "to_dict" pattern ------------------------------------- + if hasattr(value, "to_dict") and callable(getattr(value, "to_dict")): + _seen.add(obj_id) + try: + return make_json_safe(value.to_dict(), _seen) + except Exception: + pass + + # --- 9. Generic Python objects with __dict__ -------------------------- + if hasattr(value, "__dict__"): + _seen.add(obj_id) + try: + return make_json_safe(vars(value), _seen) + except Exception: + pass + + # --- 10. Last resort --------------------------------------------------- + return repr(value) diff --git a/copilotkit/__init__.py b/copilotkit/__init__.py new file mode 100644 index 0000000..2faff7a --- /dev/null +++ b/copilotkit/__init__.py @@ -0,0 +1,26 @@ +"""CopilotKit SDK""" +from .sdk import CopilotKitRemoteEndpoint, CopilotKitContext, CopilotKitSDK, CopilotKitSDKContext +from .action import Action +from .langgraph import CopilotKitState +from .parameter import Parameter +from .agent import Agent +from .langgraph_agent import LangGraphAgent +from .langgraph_agui_agent import LangGraphAGUIAgent +from .copilotkit_lg_middleware import CopilotKitMiddleware + + + +__all__ = [ + 'CopilotKitRemoteEndpoint', + 'CopilotKitSDK', + 'Action', + 'CopilotKitState', + 'Parameter', + 'Agent', + 'CopilotKitContext', + 'CopilotKitSDKContext', + 'CrewAIAgent', # pyright: ignore[reportUnsupportedDunderAll] pylint: disable=undefined-all-variable + 'LangGraphAgent', # pyright: ignore[reportUnsupportedDunderAll] pylint: disable=undefined-all-variable + "LangGraphAGUIAgent", + "CopilotKitMiddleware" +] diff --git a/copilotkit/action.py b/copilotkit/action.py new file mode 100644 index 0000000..5da6e5f --- /dev/null +++ b/copilotkit/action.py @@ -0,0 +1,57 @@ +"""Actions""" + +import re +from inspect import iscoroutinefunction +from typing import Optional, List, Callable, TypedDict, Any, cast +from .parameter import Parameter, normalize_parameters + +class ActionDict(TypedDict): + """Dict representation of an action""" + name: str + description: str + parameters: List[Parameter] + +class ActionResultDict(TypedDict): + """Dict representation of an action result""" + result: Any + +class Action: # pylint: disable=too-few-public-methods + """Action class for CopilotKit""" + def __init__( + self, + *, + name: str, + handler: Callable, + description: Optional[str] = None, + parameters: Optional[List[Parameter]] = None, + ): + self.name = name + self.description = description + self.parameters = parameters + self.handler = handler + + if not re.match(r"^[a-zA-Z0-9_-]+$", name): + raise ValueError( + f"Invalid action name '{name}': " + + "must consist of alphanumeric characters, underscores, and hyphens only" + ) + + async def execute( + self, + *, + arguments: dict + ) -> ActionResultDict: + """Execute the action""" + result = self.handler(**arguments) + + return { + "result": await result if iscoroutinefunction(self.handler) else result + } + + def dict_repr(self) -> ActionDict: + """Dict representation of the action""" + return { + 'name': self.name, + 'description': self.description or '', + 'parameters': normalize_parameters(cast(Any, self.parameters)), + } diff --git a/copilotkit/agent.py b/copilotkit/agent.py new file mode 100644 index 0000000..49e6003 --- /dev/null +++ b/copilotkit/agent.py @@ -0,0 +1,66 @@ +"""Agents""" + +import re +from typing import Optional, List, TypedDict +from abc import ABC, abstractmethod +from .types import Message +from .action import ActionDict +from .types import MetaEvent + +class AgentDict(TypedDict): + """Agent dictionary""" + name: str + description: Optional[str] + +class Agent(ABC): + """Agent class for CopilotKit""" + def __init__( + self, + *, + name: str, + description: Optional[str] = None, + ): + self.name = name + self.description = description + + if not re.match(r"^[a-zA-Z0-9_-]+$", name): + raise ValueError( + f"Invalid agent name '{name}': " + + "must consist of alphanumeric characters, underscores, and hyphens only" + ) + + @abstractmethod + def execute( # pylint: disable=too-many-arguments + self, + *, + state: dict, + config: Optional[dict] = None, + messages: List[Message], + thread_id: str, + actions: Optional[List[ActionDict]] = None, + meta_events: Optional[List[MetaEvent]] = None, + **kwargs, + ): + """Execute the agent""" + + @abstractmethod + async def get_state( + self, + *, + thread_id: str, + ): + """Default get_state implementation""" + return { + "threadId": thread_id or "", + "threadExists": False, + "state": {}, + "messages": [] + } + + + def dict_repr(self) -> AgentDict: + """Dict representation of the action""" + return { + 'name': self.name, + 'description': self.description or '' + } diff --git a/copilotkit/copilotkit_lg_middleware.py b/copilotkit/copilotkit_lg_middleware.py new file mode 100644 index 0000000..6c8a0df --- /dev/null +++ b/copilotkit/copilotkit_lg_middleware.py @@ -0,0 +1,408 @@ +""" +CopilotKit Middleware for LangGraph agents. + +Works with any agent (prebuilt or custom). + +Example: + from langgraph.prebuilt import create_agent + from copilotkit import CopilotKitMiddleware + + agent = create_agent( + model="openai:gpt-4o", + tools=[backend_tool], + middleware=[CopilotKitMiddleware()], + ) +""" + +import json +import re +from typing import Any, Callable, Awaitable, ClassVar, List + +from langchain_core.messages import AIMessage, SystemMessage, ToolMessage +from langchain.agents.middleware import ( + AgentMiddleware, + AgentState, + ModelRequest, + ModelResponse, +) +from langgraph.runtime import Runtime + +from .langgraph import CopilotKitProperties + +class StateSchema(AgentState): + copilotkit: CopilotKitProperties + + +class CopilotKitMiddleware(AgentMiddleware[StateSchema, Any]): + """CopilotKit Middleware for LangGraph agents. + + Handles frontend tool injection and interception for CopilotKit. + """ + + state_schema = StateSchema + tools: ClassVar[list] = [] + + @property + def name(self) -> str: + return "CopilotKitMiddleware" + + # Inject frontend tools before model call + def wrap_model_call( + self, + request: ModelRequest, + handler: Callable[[ModelRequest], ModelResponse], + ) -> ModelResponse: + frontend_tools = request.state.get("copilotkit", {}).get("actions", []) + + if not frontend_tools: + return handler(request) + + # Merge frontend tools with existing tools + merged_tools = [*request.tools, *frontend_tools] + + return handler(request.override(tools=merged_tools)) + + @staticmethod + def _fix_messages_for_bedrock(messages: list) -> list: + """Fix messages loaded from checkpoint before sending to Bedrock. + + Handles four issues caused by CopilotKit's after_agent restoring + frontend tool_calls to the checkpoint: + 1. Strip unanswered tool_calls (no matching ToolMessage) — Bedrock + rejects toolUse without a corresponding toolResult. + 2. Sync msg.content tool_use blocks with msg.tool_calls. + 3. Fix tool_use content blocks with string input (must be dict). + 4. Deduplicate ToolMessages by tool_call_id — patch_orphan_tool_calls + injects a placeholder with a new random ID on every checkpoint load; + when the real result is later appended alongside it, Bedrock rejects + the duplicate toolResult IDs. We keep the real result (non-interrupted) + over the placeholder, falling back to the last occurrence if both look + real. + """ + # 4. Deduplicate ToolMessages by tool_call_id before all other processing. + # patch_orphan_tool_calls adds "…was interrupted before completion." + # placeholders with fresh random IDs on every checkpoint load. The real + # result comes in as a separate message with a different ID, so both end + # up in the list. Keep the real (non-interrupted) one; if multiple real + # ones exist, keep the last. + _INTERRUPTED_PAT = re.compile( + r"^Tool call '.+' with id '.+' was interrupted before completion\.$" + ) + # Group ToolMessages by tool_call_id, preserving position + tc_groups: dict[str, list] = {} + for i, msg in enumerate(messages): + if isinstance(msg, ToolMessage): + tc_id = getattr(msg, 'tool_call_id', None) + if tc_id: + tc_groups.setdefault(tc_id, []).append(i) + + drop_indices: set = set() + for tc_id, indices in tc_groups.items(): + if len(indices) <= 1: + continue + # Separate interrupted placeholders from real results + real_indices = [ + i for i in indices + if not (isinstance(messages[i].content, str) + and _INTERRUPTED_PAT.match(messages[i].content)) + ] + interrupted_indices = [i for i in indices if i not in real_indices] + if real_indices: + # Drop all interrupted placeholders; keep real (last wins if >1) + drop_indices.update(interrupted_indices) + drop_indices.update(real_indices[:-1]) # keep only last real + else: + # All interrupted — keep only the last + drop_indices.update(interrupted_indices[:-1]) + + if drop_indices: + messages[:] = [msg for i, msg in enumerate(messages) if i not in drop_indices] + + # Collect all tool_call_ids that have a ToolMessage answer + answered_tc_ids = { + m.tool_call_id for m in messages + if isinstance(m, ToolMessage) and hasattr(m, 'tool_call_id') + } + + for msg in messages: + if not isinstance(msg, AIMessage): + continue + + tool_calls = getattr(msg, 'tool_calls', None) or [] + + # 1. Sync content with tool_calls: remove tool_use content blocks + # that aren't in msg.tool_calls (e.g. stripped by after_model + # but content blocks left behind in checkpoint). + if tool_calls and isinstance(msg.content, list): + tc_ids = {tc.get('id') for tc in tool_calls} + msg.content = [ + block for block in msg.content + if not (isinstance(block, dict) + and block.get('type') == 'tool_use' + and block.get('id') not in tc_ids) + ] + elif not tool_calls and isinstance(msg.content, list): + # No tool_calls at all — strip ALL tool_use content blocks + msg.content = [ + block for block in msg.content + if not (isinstance(block, dict) + and block.get('type') == 'tool_use') + ] + + if not tool_calls: + continue + + # 2. Strip unanswered tool_calls (no matching ToolMessage) + unanswered = [tc for tc in tool_calls if tc.get('id') not in answered_tc_ids] + if unanswered: + unanswered_ids = {tc['id'] for tc in unanswered} + msg.tool_calls = [tc for tc in tool_calls if tc.get('id') in answered_tc_ids] + + # Also strip matching content blocks + if isinstance(msg.content, list): + msg.content = [ + block for block in msg.content + if not (isinstance(block, dict) + and block.get('type') == 'tool_use' + and block.get('id') in unanswered_ids) + ] + + # 3. Fix string args in tool_calls + for tc in (msg.tool_calls or []): + if isinstance(tc.get('args'), str): + try: + tc['args'] = json.loads(tc['args']) + except (json.JSONDecodeError, TypeError): + tc['args'] = {} + + # 4. Fix string input in content blocks + if isinstance(msg.content, list): + for block in msg.content: + if isinstance(block, dict) and block.get('type') == 'tool_use': + inp = block.get('input') + if isinstance(inp, str): + try: + block['input'] = json.loads(inp) if inp else {} + except (json.JSONDecodeError, TypeError): + block['input'] = {} + elif inp is None: + block['input'] = {} + + return messages + + async def awrap_model_call( + self, + request: ModelRequest, + handler: Callable[[ModelRequest], Awaitable[ModelResponse]], + ) -> ModelResponse: + self._fix_messages_for_bedrock(request.messages) + + frontend_tools = request.state.get("copilotkit", {}).get("actions", []) + + if not frontend_tools: + return await handler(request) + + # Merge frontend tools with existing tools + merged_tools = [*request.tools, *frontend_tools] + + return await handler(request.override(tools=merged_tools)) + + # Inject app context before agent runs + def before_agent( + self, + state: StateSchema, + runtime: Runtime[Any], + ) -> dict[str, Any] | None: + messages = state.get("messages", []) + + if not messages: + return None + + # Get app context from state or runtime + copilotkit_state = state.get("copilotkit", {}) + app_context = copilotkit_state.get("context") or getattr(runtime, "context", None) + + # Check if app_context is missing or empty + if not app_context: + return None + if isinstance(app_context, str) and app_context.strip() == "": + return None + if isinstance(app_context, dict) and len(app_context) == 0: + return None + + # Create the context content + if isinstance(app_context, str): + context_content = app_context + else: + context_content = json.dumps(app_context, indent=2) + + context_message_content = f"App Context:\n{context_content}" + context_message_prefix = "App Context:\n" + + # Helper to get message content as string + def get_content_string(msg: Any) -> str | None: + content = getattr(msg, "content", None) + if isinstance(content, str): + return content + if isinstance(content, list) and content and isinstance(content[0], dict): + return content[0].get("text") + return None + + # Find the first system/developer message (not our context message) + # to determine where to insert our context message (right after it) + first_system_index = -1 + + for i, msg in enumerate(messages): + msg_type = getattr(msg, "type", None) + if msg_type in ("system", "developer"): + content = get_content_string(msg) + # Skip if this is our own context message + if content and content.startswith(context_message_prefix): + continue + first_system_index = i + break + + # Check if our context message already exists + existing_context_index = -1 + for i, msg in enumerate(messages): + msg_type = getattr(msg, "type", None) + if msg_type in ("system", "developer"): + content = get_content_string(msg) + if content and content.startswith(context_message_prefix): + existing_context_index = i + break + + # Create the context message + context_message = SystemMessage(content=context_message_content) + + if existing_context_index != -1: + # Replace existing context message + updated_messages = list(messages) + updated_messages[existing_context_index] = context_message + else: + # Insert after the first system message, or at position 0 if no system message + insert_index = first_system_index + 1 if first_system_index != -1 else 0 + updated_messages = [ + *messages[:insert_index], + context_message, + *messages[insert_index:], + ] + + return { + **state, + "messages": updated_messages, + } + + async def abefore_agent( + self, + state: StateSchema, + runtime: Runtime[Any], + ) -> dict[str, Any] | None: + # Delegate to sync implementation + return self.before_agent(state, runtime) + + # Intercept frontend tool calls after model returns, before ToolNode executes + def after_model( + self, + state: StateSchema, + runtime: Runtime[Any], + ) -> dict[str, Any] | None: + frontend_tools = state.get("copilotkit", {}).get("actions", []) + if not frontend_tools: + return None + + frontend_tool_names = { + t.get("function", {}).get("name") or t.get("name") + for t in frontend_tools + } + + # Find last AI message with tool calls + messages = state.get("messages", []) + if not messages: + return None + + last_message = messages[-1] + if not isinstance(last_message, AIMessage): + return None + + tool_calls = getattr(last_message, "tool_calls", None) or [] + if not tool_calls: + return None + + backend_tool_calls = [] + frontend_tool_calls = [] + + for call in tool_calls: + if call.get("name") in frontend_tool_names: + frontend_tool_calls.append(call) + else: + backend_tool_calls.append(call) + + if not frontend_tool_calls: + return None + + # Create updated AIMessage with only backend tool calls + updated_ai_message = AIMessage( + content=last_message.content, + tool_calls=backend_tool_calls, + id=last_message.id, + ) + + return { + "messages": [*messages[:-1], updated_ai_message], + "copilotkit": { + "intercepted_tool_calls": frontend_tool_calls, + "original_ai_message_id": last_message.id, + }, + } + + async def aafter_model( + self, + state: StateSchema, + runtime: Runtime[Any], + ) -> dict[str, Any] | None: + # Delegate to sync implementation + return self.after_model(state, runtime) + + # Restore frontend tool calls to AIMessage before agent exits + def after_agent( + self, + state: StateSchema, + runtime: Runtime[Any], + ) -> dict[str, Any] | None: + copilotkit_state = state.get("copilotkit", {}) + intercepted_tool_calls = copilotkit_state.get("intercepted_tool_calls") + original_message_id = copilotkit_state.get("original_ai_message_id") + + if not intercepted_tool_calls or not original_message_id: + return None + + messages = state.get("messages", []) + updated_messages = [] + + for msg in messages: + if isinstance(msg, AIMessage) and msg.id == original_message_id: + existing_tool_calls = getattr(msg, "tool_calls", None) or [] + updated_messages.append(AIMessage( + content=msg.content, + tool_calls=[*existing_tool_calls, *intercepted_tool_calls], + id=msg.id, + )) + else: + updated_messages.append(msg) + + return { + "messages": updated_messages, + "copilotkit": { + "intercepted_tool_calls": None, + "original_ai_message_id": None, + }, + } + + async def aafter_agent( + self, + state: StateSchema, + runtime: Runtime[Any], + ) -> dict[str, Any] | None: + # Delegate to sync implementation + return self.after_agent(state, runtime) diff --git a/copilotkit/crewai/__init__.py b/copilotkit/crewai/__init__.py new file mode 100644 index 0000000..fa588d5 --- /dev/null +++ b/copilotkit/crewai/__init__.py @@ -0,0 +1,43 @@ +""" +CrewAI +""" +from .crewai_agent import CrewAIAgent +from .crewai_sdk import ( + CopilotKitProperties, + CopilotKitState, + copilotkit_emit_state, + copilotkit_emit_message, + copilotkit_emit_tool_call, + copilotkit_stream, + copilotkit_exit, + copilotkit_predict_state, +) +from .copilotkit_integration import ( + CopilotKitFlow, + CopilotKitToolCallEvent, + register_tool_call_listener, + tool_calls_log, + create_tool_proxy, + FlowInputState, + CopilotKitStateUpdateEvent, + emit_copilotkit_state_update_event +) +__all__ = [ + "CrewAIAgent", + "CopilotKitProperties", + "CopilotKitState", + "copilotkit_emit_state", + "copilotkit_emit_message", + "copilotkit_emit_tool_call", + "copilotkit_stream", + "copilotkit_exit", + "copilotkit_predict_state", + "CopilotKitFlow", + "CopilotKitToolCallEvent", + "register_tool_call_listener", + "tool_calls_log", + "create_tool_proxy", + "FlowInputState", + "CopilotKitStateUpdateEvent", + "emit_copilotkit_state_update_event" +] diff --git a/copilotkit/crewai/copilotkit_integration.py b/copilotkit/crewai/copilotkit_integration.py new file mode 100644 index 0000000..185256a --- /dev/null +++ b/copilotkit/crewai/copilotkit_integration.py @@ -0,0 +1,278 @@ +#!/usr/bin/env python +from typing import Dict, Any, List, Optional, Generic +import datetime +from crewai.flow import Flow +from crewai import LLM +from crewai.utilities.events import crewai_event_bus +import logging +from crewai.utilities.events.base_events import BaseEvent +from pydantic import Field +from typing import TypeVar +from pydantic import BaseModel + +# Define a generic type variable for the state +S = TypeVar('S') + +logger = logging.getLogger(__name__) + +# Tool calls log for tracking +tool_calls_log = [] + +class FlowInputState(BaseModel): + """Defines the expected input state for the AgenticChatFlow.""" + messages: List[Dict[str, str]] = [] # Current message(s) from the user + tools: List[Dict[str, Any]] = [] # CopilotKit tool format: name, description, parameters + conversation_history: List[Dict[str, str]] = [] # Full conversation history (persisted between runs) + + +class CopilotKitToolCallEvent(BaseEvent): + """Event emitted when a tool call is made through CopilotKit""" + type: str = "copilotkit_frontend_tool_call" + + tool_name: str + args: Dict[str, Any] + timestamp: str = Field(default_factory=lambda: datetime.datetime.now().isoformat()) + + def __init__(self, **data): + # If timestamp is not provided, it will use the default_factory + super().__init__(**data) + +class CopilotKitStateUpdateEvent(BaseEvent): + """Event for state updates in CopilotKit""" + type: str = "copilotkit_state_update" + tool_name: str + args: dict[str, Any] + timestamp: str = Field(default_factory=lambda: datetime.datetime.now().isoformat()) + + def __init__(self, **data): + # If timestamp is not provided, it will use the default_factory + super().__init__(**data) + +def create_tool_proxy(tool_name): + def tool_proxy(**kwargs): + event = CopilotKitToolCallEvent(tool_name=tool_name, args=kwargs) + tool_calls_log.append({ + "tool_name": tool_name, + "args": kwargs, + "timestamp": event.timestamp + }) + assert hasattr(crewai_event_bus, "emit") + logger.info(f"create_tool_proxy: Emitting tool call event for {tool_name} with parameters: {kwargs}") + crewai_event_bus.emit(None, event=event) + return f"\n\nTool {tool_name} called successfully with parameters: {kwargs}\n\n" + return tool_proxy + +class CopilotKitFlow(Flow[S], Generic[S]): # Make it generic + _tools_from_input: List[Dict[str, Any]] = [] # Store raw tool definitions + + def __class_getitem__(cls, item): + # Pass type info down to Flow's __class_getitem__ + super().__class_getitem__(item) + cls._initial_state_T = item + return cls + + def kickoff(self, state: Optional[S] = None, inputs: Optional[Dict[str, Any]] = None): + # CrewAI's Flow class initializes self.state from the 'state' parameter or + # by instantiating S using 'inputs' if 'state' is None and 'inputs' is a dict. + # We need to ensure tools from 'inputs' (if any) are captured if not part of S's direct fields + # or if S is initialized before this kickoff by CrewAI. + + # If inputs dict contains 'tools', store them for get_available_tools + if isinstance(inputs, dict) and "tools" in inputs: + # Be careful with class-level _tools_from_input if multiple instances run concurrently + # It might be better to store this on self. + CopilotKitFlow._tools_from_input = inputs.get("tools", []) + print(f"Tools from inputs dict: {CopilotKitFlow._tools_from_input}") + + # The actual_input for super().kickoff should be the state model instance S + # or the dict 'inputs' if state is None. + # The base Flow's kickoff will handle initializing self.state. + # If state is already an instance of S, pass it. + # If state is None and inputs is a dict, Flow.__init__ will use inputs to create S. + + # Let the base Flow handle state initialization. + # Our main job here is to potentially intercept 'inputs' if it has a structure + # not directly mapping to S (e.g., tools in a separate key). + # However, with AgentInputState having 'tools', this should be cleaner. + + # Call parent's kickoff - note that base Flow.kickoff() only accepts 'inputs' + # If state is not None, we should convert it to dict and use as inputs + if state is not None and inputs is None: + # If we have a state model instance but no inputs, convert state to dict for inputs + if hasattr(state, "dict") and callable(getattr(state, "dict")): + inputs_dict = state.dict() + result = super().kickoff(inputs=inputs_dict) + else: + # If state can't be converted via .dict(), use it directly as inputs + result = super().kickoff(inputs=state) + else: + # Normal case: just pass inputs (which might be None) + result = super().kickoff(inputs=inputs) + + return result # Return what the base Flow.kickoff returns + + def get_message_history(self, system_prompt: Optional[str] = None, max_messages: int = 20) -> List[Dict[str, str]]: + messages: List[Dict[str, str]] = [] + + # PRIORITIZE conversation_history if available (for persistence between runs) + if hasattr(self.state, "conversation_history") and isinstance(self.state.conversation_history, list) and self.state.conversation_history: + # If we have conversation history, use it as the primary source of messages + messages.extend(self.state.conversation_history) + logger.info(f"get_message_history: Loaded {len(self.state.conversation_history)} messages from conversation history") + + # If there are new messages not in the history, add them temporarily (they'll be saved to history later) + if hasattr(self.state, "messages") and isinstance(self.state.messages, list): + for msg in self.state.messages: + if msg not in messages: + messages.append(msg) + logger.info(f"get_message_history: Added new message (not yet in history): {msg.get('content', '')[:30]}...") + + # If no conversation history, try current messages + elif hasattr(self.state, "messages") and isinstance(self.state.messages, list): + messages.extend(self.state.messages) + print(f"get_message_history: Loaded {len(self.state.messages)} messages from current messages") + + # Fallback for raw input if state isn't populated as expected (less ideal) + elif hasattr(self, "_raw_input") and isinstance(self._raw_input, dict) and "messages" in self._raw_input: + messages.extend(self._raw_input["messages"]) + logger.info(f"get_message_history: Loaded {len(self._raw_input['messages'])} messages from _raw_input") + + # Add system prompt if needed + if system_prompt: + # Check if we already have a system message + has_system_message = any(msg.get('role') == 'system' for msg in messages) + + if not has_system_message: + # Add system message at the beginning + messages.insert(0, {"role": "system", "content": system_prompt}) + logger.info(f"get_message_history: Added system prompt message") + + # Limit to max_messages, but keep the system message if present + if len(messages) > max_messages: + # If first message is system message, keep it and take the (max_messages-1) most recent messages + if messages and messages[0].get('role') == 'system': + system_msg = messages[0] + recent_msgs = messages[-(max_messages-1):] + messages = [system_msg] + recent_msgs + logger.info(f"get_message_history: Truncated to {len(messages)} messages (including system message)") + else: + # Otherwise just take most recent messages + messages = messages[-max_messages:] + logger.info(f"get_message_history: Truncated to {len(messages)} most recent messages") + + return messages + + def get_available_tools(self) -> List[Dict[str, Any]]: + raw_tools: List[Dict[str, Any]] = [] + + # Primary source: self.state.tools (from AgentInputState) + if hasattr(self.state, "tools") and isinstance(self.state.tools, list): + raw_tools = self.state.tools + logger.info(f"get_available_tools: Loaded {len(raw_tools)} tools from self.state.tools") + + # Fallback to _tools_from_input (populated in kickoff from raw 'inputs' dict) + # This is useful if 'tools' was passed separately and not as part of the state model S. + elif CopilotKitFlow._tools_from_input: + raw_tools = CopilotKitFlow._tools_from_input + logger.info(f"get_available_tools: Loaded {len(raw_tools)} tools from _tools_from_input") + + # Fallback for raw input (less ideal) + elif hasattr(self, "_raw_input") and isinstance(self._raw_input, dict) and "tools" in self._raw_input: + raw_tools = self._raw_input["tools"] + logger.info(f"get_available_tools: Loaded {len(raw_tools)} tools from _raw_input") + + return raw_tools + + def format_tools_for_llm(self, tools_definitions: List[Dict[str, Any]]) -> tuple[List[Dict[str, Any]], Dict[str, callable]]: + formatted_tools = [] + available_functions = {} + + logger.info(f"format_tools_for_llm: Processing {len(tools_definitions)} tool definitions.") + for tool_def in tools_definitions: + if "name" in tool_def and "parameters" in tool_def and "description" in tool_def: + # Standard OpenAI tool format + formatted_tool = { + "type": "function", + "function": { + "name": tool_def["name"], + "description": tool_def["description"], + "parameters": tool_def["parameters"] + } + } + formatted_tools.append(formatted_tool) + + # Create and store the proxy function + tool_name = tool_def["name"] + available_functions[tool_name] = create_tool_proxy(tool_name) + logger.info(f"format_tools_for_llm: Created proxy for tool: {tool_name}") + else: + logger.info(f"format_tools_for_llm: Skipped invalid tool definition: {tool_def.get('name', 'N/A')}") + + return formatted_tools, available_functions + + def handle_tool_responses( + self, + llm: LLM, + response_text: str, # Changed from 'response' to 'response_text' for clarity + messages: List[Dict[str, str]], + tools_called_count_before_llm_call: int, # More descriptive name + follow_up_prompt: Optional[str] = None + ) -> str: + new_tools_called_during_interaction = len(tool_calls_log) > tools_called_count_before_llm_call + + # Check if a follow-up is needed (tools were called but no substantive natural language content) + need_followup = new_tools_called_during_interaction and ( + not response_text.strip() or + all(f"Tool {call['tool_name']}" in response_text for call in tool_calls_log[tools_called_count_before_llm_call:]) + ) + + if need_followup: + logger.info("handle_tool_responses: Follow-up needed after tool call.") + follow_up_messages = messages.copy() + # Add the assistant's response that included tool calls (or was just tool call confirmations) + follow_up_messages.append({"role": "assistant", "content": response_text}) + + # Add tool call results as messages (CopilotKit might do this differently, adjust if needed) + # For OpenAI, tool results are typically added with role 'tool' + # This part might need alignment with how CopilotKit expects tool results to be fed back. + # The current [create_tool_proxy](cci:1://file:///Users/croonnicola/Downloads/agentic_chat/src/agentic_chat/copilotkit_integration.py:22:0-42:21) returns a string. This string becomes the 'content' + # of the assistant's message. If the LLM needs explicit tool result messages, + # this needs adjustment. For now, we assume the proxy's string output is sufficient. + + prompt_for_final_answer = follow_up_prompt or "Tools have been called. Continue with your response." + follow_up_messages.append({"role": "user", "content": prompt_for_final_answer}) + + logger.info(f"handle_tool_responses: Calling LLM for follow-up with {len(follow_up_messages)} messages.") + # Call LLM without tools for a final natural language response + final_response_text = llm.call(messages=follow_up_messages, tools=None, available_functions=None) + + # Combine initial tool call confirmations with the final natural language response + # This behavior might need tuning based on desired output verbosity + # combined_response = response_text + "\n\n" + final_response_text + # Often, you just want the final_response_text + return final_response_text + else: + return response_text # No follow-up needed, return original LLM response + + def get_tools_summary(self) -> str: # Remains the same + summary = f"\nTotal tool calls: {len(tool_calls_log)}\n" + for i, call in enumerate(tool_calls_log): + summary += f"\n[{i+1}] Tool: {call['tool_name']}" + summary += f"\n Args: {call['args']}" + summary += f"\n Time: {call['timestamp']}\n" + return summary + +# Register event listener (remains the same) +def register_tool_call_listener(): + @crewai_event_bus.on(CopilotKitToolCallEvent) + def on_tool_call_event(source, event): + print(f"Received CopilotKit tool call event: Tool: {event.tool_name}, Args: {event.args}, Time: {event.timestamp}") + pass + +# Use this function to emit state updates to the client UI (STATE_SNAPSHOT) +# This is particularly useful when you need to update the UI state from within a tool call +# or when you want to reflect state changes in the AG-UI interface +# Example: emit_copilotkit_state_update_event("write_document", {"document": state.data["document"]}) +def emit_copilotkit_state_update_event(tool_name: str, args: dict[str, Any]): + event = CopilotKitStateUpdateEvent(tool_name=tool_name, args=args) + crewai_event_bus.emit(None, event=event) \ No newline at end of file diff --git a/copilotkit/crewai/crewai_agent.py b/copilotkit/crewai/crewai_agent.py new file mode 100644 index 0000000..cfef1a1 --- /dev/null +++ b/copilotkit/crewai/crewai_agent.py @@ -0,0 +1,501 @@ +""" +CrewAI Agent +""" + +import uuid +import json +from copy import deepcopy +from typing import Optional, List, Callable +from typing_extensions import TypedDict, NotRequired, Any, Dict, cast +from pydantic import BaseModel +from crewai import Crew, Flow +from crewai.flow import start +from crewai.cli.crew_chat import ( + initialize_chat_llm as crew_chat_initialize_chat_llm, + generate_crew_chat_inputs as crew_chat_generate_crew_chat_inputs, + generate_crew_tool_schema as crew_chat_generate_crew_tool_schema, + build_system_message as crew_chat_build_system_message, + create_tool_function as crew_chat_create_tool_function +) +from litellm import completion +from copilotkit.agent import Agent +from copilotkit.types import Message +from copilotkit.action import ActionDict +from copilotkit.protocol import ( + emit_runtime_events, + agent_state_message, +) +from copilotkit.crewai.crewai_sdk import ( + copilotkit_messages_to_crewai_flow, + crewai_flow_messages_to_copilotkit, + crewai_flow_async_runner, + copilotkit_stream, + copilotkit_exit, + logger +) + +from copilotkit.runloop import copilotkit_run, CopilotKitRunExecution + +class CopilotKitConfig(TypedDict): + """ + CopilotKit config for CrewAIAgent + + This is used for advanced cases where you want to customize how CopilotKit interacts with + CrewAI. + + ```python + # Function signatures: + def merge_state( + *, + state: dict, + messages: List[BaseMessage], + actions: List[Any], + agent_name: str + ): + # ...implementation... + + ``` + + Parameters + ---------- + merge_state : Callable + This function lets you customize how CopilotKit merges the agent state. + """ + merge_state: NotRequired[Callable] + +class CrewAIFlowExecutionState(TypedDict): + """ + State for an execution of a CrewAI Flow agent + """ + should_exit: bool + node_name: str + is_finished: bool + predict_state_configuration: Dict[str, Any] + predicted_state: Dict[str, Any] + argument_buffer: str + current_tool_call: Optional[str] + +class CrewAIAgent(Agent): + """ + CrewAIAgent lets you define your agent for use with CopilotKit. + + To install, run: + + ```bash + pip install copilotkit[crewai] + ``` + + Every agent must have the `name` and either `crew` or `flow` properties defined. An optional + `description` can also be provided. This is used when CopilotKit is dynamically routing requests + to the agent. + + ## Serving a Crew based agent + + To serve a Crew based agent, pass in a `Crew` object to the `crew` parameter. + + Note: + You need to make sure to have a `chat_llm` set on the `Crew` object. + See [the CrewAI docs](https://docs.crewai.com/concepts/cli#9-chat) for more information. + + ```python + from copilotkit import CrewAIAgent + + + CrewAIAgent( + name="email_agent_crew", + description="This crew based agent sends emails", + crew=SendEmailCrew(), + ) + ``` + + ## Serving a Flow based agent + + To serve a Flow based agent, pass in a `Flow` object to the `flow` parameter. + + ```python + CrewAIAgent( + name="email_agent_flow", + description="This flow based agent sends emails", + flow=SendEmailFlow(), + ) + ``` + + Note: + Either a `crew` or `flow` must be provided to CrewAIAgent. + + Parameters + ---------- + name : str + The name of the agent. + crew : Crew + When using a Crew based agent, pass in a `Crew` object to the `crew` parameter. + flow : Flow + When using a Flow based agent, pass in a `Flow` object to the `flow` parameter. + description : Optional[str] + The description of the agent. + copilotkit_config : Optional[CopilotKitConfig] + The CopilotKit config to use with the agent. + + """ + def __init__( + self, + *, + name: str, + description: Optional[str] = None, + crew: Optional[Crew] = None, + flow: Optional[Flow] = None, + copilotkit_config: Optional[CopilotKitConfig] = None, + ): + super().__init__( + name=name, + description=description, + ) + if (crew is None) == (flow is None): + raise ValueError("Either crew or flow must be provided to CrewAIAgent") + + + self.crew = crew + self.flow = flow + self.copilotkit_config = copilotkit_config or {} + + def execute( # pylint: disable=too-many-arguments + self, + *, + state: dict, + thread_id: str, + messages: List[Message], + actions: Optional[List[ActionDict]] = None, + **kwargs, + ): + """Execute the agent""" + if self.crew: + crew = deepcopy(self.crew) + return self.execute_crew( + state=state, + messages=messages, + thread_id=thread_id, + actions=actions, + crew=crew, + **kwargs + ) + + if self.flow: + flow = deepcopy(self.flow) + return self.execute_flow( + state=state, + messages=messages, + thread_id=thread_id, + actions=actions, + flow=flow, + **kwargs + ) + + raise ValueError("Either crew or flow must be provided to CrewAIAgent") + + def execute_crew( # pylint: disable=too-many-arguments,unused-argument + self, + *, + state: dict, + crew: Crew, + thread_id: str, + messages: List[Message], + actions: Optional[List[ActionDict]] = None, + **kwargs, + ): + """Execute a `Crew` based agent""" + + flow = ChatWithCrewFlow( + crew=crew, + crew_name=self.name, + thread_id=thread_id, + cache_key=f"crew_{id(self.crew)}" + ) + + return self.execute_flow( + state=state, + messages=messages, + thread_id=thread_id, + actions=actions, + flow=flow, + **kwargs + ) + + + async def execute_flow( # pylint: disable=too-many-arguments,unused-argument,too-many-locals + self, + *, + state: dict, + messages: List[Message], + thread_id: Optional[str] = None, + actions: Optional[List[ActionDict]] = None, + flow: Flow, + **kwargs, + ): + """Execute a `Flow` based agent""" + + if thread_id is None: + raise ValueError("Thread ID is required") + + run_id = str(uuid.uuid4()) + + + merge_state = self.copilotkit_config.get("merge_state", crewai_flow_default_merge_state) + + crewai_flow_messages = copilotkit_messages_to_crewai_flow(messages) + + state = merge_state( + state=state, + messages=crewai_flow_messages, + actions=actions or [], + agent_name=self.name, + flow=flow + ) + + execution: CopilotKitRunExecution = CopilotKitRunExecution( + thread_id=thread_id, + agent_name=self.name, + run_id=run_id, + should_exit=False, + node_name="start", + is_finished=False, + predict_state_configuration={}, + predicted_state={}, + argument_buffer="", + current_tool_call=None, + state=state + ) + + async for event in copilotkit_run( + fn=lambda: crewai_flow_async_runner(flow, deepcopy(state)), + execution=execution + ): + yield event + + state = {**(flow.state.model_dump() if isinstance(flow.state, BaseModel) else flow.state)} + if "messages" in state: + state["messages"] = crewai_flow_messages_to_copilotkit(state["messages"]) + + # emit the final state + yield emit_runtime_events( + agent_state_message( + thread_id=thread_id, + agent_name=self.name, + node_name=execution["node_name"], + run_id=run_id, + active=False, + role="assistant", + state=json.dumps(filter_state(state, exclude_keys=["id"])), + running=not execution["should_exit"] + ) + ) + + async def get_state( + self, + *, + thread_id: str, + ): + if self.flow and self.flow._persistence: # pylint: disable=protected-access + try: + stored_state = self.flow._persistence.load_state(thread_id) # pylint: disable=protected-access + messages = [] + if "messages" in stored_state and stored_state["messages"]: + try: + messages = crewai_flow_messages_to_copilotkit(stored_state["messages"]) + except Exception as e: # pylint: disable=broad-except + # If conversion fails, we'll return empty messages + logger.warning(f"Failed to convert messages from stored state: {str(e)}") + return { + "threadId": thread_id, + "threadExists": True, + "state": stored_state, + "messages": messages + } + except Exception as e: # pylint: disable=broad-except + logger.warning(f"Failed to load state for thread {thread_id}: {str(e)}") + + return { + "threadId": thread_id, + "threadExists": False, + "state": {}, + "messages": [] + } + + + def dict_repr(self): + super_repr = super().dict_repr() + return { + **super_repr, + 'type': 'crewai' + } + +def crewai_flow_default_merge_state( # pylint: disable=unused-argument, too-many-arguments + *, + state: dict, + flow: Flow, + messages: List[Any], + actions: List[Any], + agent_name: str, + ): + """Default merge state for CrewAI""" + if len(messages) > 0: + if "role" in messages[0] and messages[0]["role"] == "system": + messages = messages[1:] + + + actions = [{ + "type": "function", + "function": { + **action, + } + } for action in actions] + + new_state = { + **state, + "messages": messages, + "copilotkit": { + "actions": actions + } + } + + return new_state + + +def filter_state(state: Dict[str, Any], exclude_keys: Optional[List[str]] = None) -> Dict[str, Any]: + """Filter out messages and id from the state""" + exclude_keys = exclude_keys or ["messages", "id"] + return {k: v for k, v in state.items() if k not in exclude_keys} + +CREW_EXIT_TOOL = { + "type": "function", + "function": { + "name": "crew_exit", + "description": "Call this when the user has indicated that they are done with the crew", + "parameters": { + "type": "object", + "properties": {}, + "required": [], + }, + }, +} + +_CREW_INPUTS_CACHE = {} + +class ChatWithCrewFlow(Flow): + """Chat with crew""" + + def __init__( + self, *, + crew: Crew, + crew_name: str, + thread_id: str, + cache_key: str + ): + super().__init__() + + self.crew = cast(Any, crew).crew() + + if self.crew.chat_llm is None: + raise ValueError("Crew chat LLM is not set") + + self.crew_name = crew_name + self.thread_id = thread_id + self.chat_llm = crew_chat_initialize_chat_llm(self.crew) + + if cache_key not in _CREW_INPUTS_CACHE: + self.crew_chat_inputs = crew_chat_generate_crew_chat_inputs( + self.crew, + self.crew_name, + self.chat_llm + ) + _CREW_INPUTS_CACHE[cache_key] = self.crew_chat_inputs + else: + self.crew_chat_inputs = _CREW_INPUTS_CACHE[cache_key] + + self.crew_tool_schema = crew_chat_generate_crew_tool_schema(self.crew_chat_inputs) + self.system_message = crew_chat_build_system_message(self.crew_chat_inputs) + + super().__init__() + + @start() + async def chat(self): + """Chat with the crew""" + + system_message = self.system_message + if self.state.get("inputs"): + system_message += "\n\nCurrent inputs: " + json.dumps(self.state["inputs"]) + + messages = [ + { + "role": "system", + "content": system_message, + "id": self.thread_id + "-system" + }, + *self.state["messages"] + ] + + tools = [action for action in self.state["copilotkit"]["actions"] + if action["function"]["name"] != self.crew_name] + + tools += [self.crew_tool_schema, CREW_EXIT_TOOL] + + response = await copilotkit_stream( + completion( + model=self.crew.chat_llm, + messages=messages, + tools=tools, + parallel_tool_calls=False, + stream=True + ) + ) + + message = cast(Any, response).choices[0]["message"] + self.state["messages"].append(message) + + if message.get("tool_calls"): + if message["tool_calls"][0]["function"]["name"] == self.crew_name: + # run the crew + crew_function = crew_chat_create_tool_function(self.crew, messages) + args = json.loads(message["tool_calls"][0]["function"]["arguments"]) + result = crew_function(**args) + + if isinstance(result, str): + self.state["outputs"] = result + elif hasattr(result, "json_dict"): + self.state["outputs"] = result.json_dict + elif hasattr(result, "raw"): + self.state["outputs"] = result.raw + else: + raise ValueError("Unexpected result type", type(result)) + + self.state["messages"].append({ + "role": "tool", + "content": result, + "tool_call_id": message["tool_calls"][0]["id"] + }) + elif message["tool_calls"][0]["function"]["name"] == CREW_EXIT_TOOL["function"]["name"]: + await copilotkit_exit() + self.state["messages"].append({ + "role": "tool", + "content": "Crew exited", + "tool_call_id": message["tool_calls"][0]["id"] + }) + + response = await copilotkit_stream( + completion( # pylint: disable=too-many-arguments + model=self.crew.chat_llm, + messages = [ + { + "role": "system", + "content": "Indicate to the user that the crew has exited", + "id": self.thread_id + "-system" + }, + *self.state["messages"] + ], + tools=tools, + parallel_tool_calls=False, + stream=True, + tool_choice="none" + ) + ) + message = cast(Any, response).choices[0]["message"] + self.state["messages"].append(message) diff --git a/copilotkit/crewai/crewai_sdk.py b/copilotkit/crewai/crewai_sdk.py new file mode 100644 index 0000000..bfe9b5d --- /dev/null +++ b/copilotkit/crewai/crewai_sdk.py @@ -0,0 +1,613 @@ +""" +CrewAI integration for CopilotKit +""" + +import uuid +import json +import asyncio +from typing_extensions import Any, Dict, List, Literal +from pydantic import BaseModel, Field +from litellm.types.utils import ( + ModelResponse, + Choices, + Message as LiteLLMMessage, + ChatCompletionMessageToolCall, + Function as LiteLLMFunction +) +from litellm.litellm_core_utils.streaming_handler import CustomStreamWrapper +from crewai.flow.flow import FlowState, Flow +from crewai.utilities.events.flow_events import ( + FlowEvent as CrewAIFlowEvent, + FlowStartedEvent, + MethodExecutionStartedEvent, + MethodExecutionFinishedEvent, + FlowFinishedEvent, +) +from crewai.utilities.events import crewai_event_bus as _crewai_event_bus + +from copilotkit.types import Message +from copilotkit.logging import get_logger +from copilotkit.runloop import queue_put, get_context_execution +from copilotkit.protocol import ( + RuntimeEventTypes, + RunStarted, + RunFinished, + RunError, + NodeStarted, + NodeFinished, + agent_state_message, + text_message_start, + text_message_content, + text_message_end, + action_execution_start, + action_execution_args, + action_execution_end, + meta_event, + RuntimeMetaEventName, + PredictStateConfig +) + +logger = get_logger(__name__) + +class CopilotKitProperties(BaseModel): + """CopilotKit properties""" + actions: List[Any] = Field(default_factory=list) + +class CopilotKitState(FlowState): + """CopilotKit state""" + messages: List[Any] = Field(default_factory=list) + copilotkit: CopilotKitProperties = Field(default_factory=CopilotKitProperties) + +async def crewai_flow_async_runner(flow: Flow, inputs: Dict[str, Any]): + """ + Runs a flow in a separate thread. Workaround since the flow will use + asyncio.run(). + """ + + async def crewai_flow_event_subscriber(flow: Any, event: CrewAIFlowEvent): + if isinstance(event, FlowStartedEvent): + await queue_put(RunStarted( + type=RuntimeEventTypes.RUN_STARTED, + state=flow.state + ), priority=True) + elif isinstance(event, MethodExecutionStartedEvent): + await queue_put(NodeStarted( + type=RuntimeEventTypes.NODE_STARTED, + node_name=event.method_name, + state=flow.state + ), priority=True) + elif isinstance(event, MethodExecutionFinishedEvent): + await queue_put(NodeFinished( + type=RuntimeEventTypes.NODE_FINISHED, + node_name=event.method_name, + state=flow.state + ), priority=True) + elif isinstance(event, FlowFinishedEvent): + await queue_put(RunFinished( + type=RuntimeEventTypes.RUN_FINISHED, + state=flow.state + ), priority=True) + + + def _global_event_listener(_sender: Any, _event: CrewAIFlowEvent, **_kw): # noqa: D401 + # Forward to the async handler inside the flow's loop + loop = asyncio.get_running_loop() + loop.call_soon(lambda: asyncio.create_task(crewai_flow_event_subscriber(flow, _event))) + + # Register for the specific event classes we care about to avoid noise + for _ev_cls in (FlowStartedEvent, MethodExecutionStartedEvent, MethodExecutionFinishedEvent, FlowFinishedEvent): + _crewai_event_bus.on(_ev_cls)(_global_event_listener) # type: ignore + + try: + await flow.kickoff_async(inputs=inputs) + except Exception as e: # pylint: disable=broad-except + await queue_put(RunError( + type=RuntimeEventTypes.RUN_ERROR, + error=e + )) + +async def copilotkit_emit_state(state: Any) -> Literal[True]: + """ + Emits intermediate state to CopilotKit. + Useful if you have a longer running node and you want to update the user with the current state of the node. + + To install the CopilotKit SDK, run: + + ```bash + pip install copilotkit[crewai] + ``` + + ### Examples + + ```python + from copilotkit.crewai import copilotkit_emit_state + + for i in range(10): + await some_long_running_operation(i) + await copilotkit_emit_state({"progress": i}) + ``` + + Parameters + ---------- + state : Any + The state to emit (Must be JSON serializable). + + Returns + ------- + Awaitable[bool] + Always return True. + + """ + execution = get_context_execution() + + state_as_dict = state.model_dump() if isinstance(state, BaseModel) else state + state = { + k: v for k, v in state_as_dict.items() if k not in ["messages", "copilotkit"] + } + + await queue_put( + agent_state_message( + thread_id=execution["thread_id"], + agent_name=execution["agent_name"], + node_name=execution["node_name"], + run_id=execution["run_id"], + active=True, + role="assistant", + state=json.dumps(state_as_dict), + running=True + ) + ) + + + return True + +async def copilotkit_emit_message(message: str) -> str: + """ + Manually emits a message to CopilotKit. Useful in longer running nodes to update the user. + Important: You still need to return the messages from the node. + + ### Examples + + ```python + from copilotkit.crewai import copilotkit_emit_message + + message = "Step 1 of 10 complete" + await copilotkit_emit_message(message) + + # Return the message from the node + return { + "messages": [AIMessage(content=message)] + } + ``` + + Parameters + ---------- + message : str + The message to emit. + + Returns + ------- + Awaitable[bool] + Always return True. + """ + message_id = str(uuid.uuid4()) + + await queue_put( + text_message_start( + message_id=message_id, + parent_message_id=None + ), + text_message_content( + message_id=message_id, + content=message + ), + text_message_end( + message_id=message_id + ) + ) + + return message_id + +async def copilotkit_emit_tool_call(*, name: str, args: Dict[str, Any]) -> str: + """ + Manually emits a tool call to CopilotKit. + + ```python + from copilotkit.crewai import copilotkit_emit_tool_call + + await copilotkit_emit_tool_call(name="SearchTool", args={"steps": 10}) + ``` + + Parameters + ---------- + name : str + The name of the tool to emit. + args : Dict[str, Any] + The arguments to emit. + + Returns + ------- + Awaitable[bool] + Always return True. + """ + message_id = str(uuid.uuid4()) + await queue_put( + action_execution_start( + action_execution_id=message_id, + action_name=name, + parent_message_id=message_id + ), + action_execution_args( + action_execution_id=message_id, + args=json.dumps(args) + ), + action_execution_end( + action_execution_id=message_id + ) + ) + + return message_id + + +async def copilotkit_stream(response): + """ + Stream litellm responses token by token to CopilotKit. + + ```python + response = await copilotkit_stream( + completion( + model="openai/gpt-4o", + messages=messages, + tools=tools, + stream=True # this must be set to True for streaming + ) + ) + ``` + """ + if isinstance(response, ModelResponse): + return _copilotkit_stream_response(response) + if isinstance(response, CustomStreamWrapper): + return await _copilotkit_stream_custom_stream_wrapper(response) + raise ValueError("Invalid response type") + + +async def _copilotkit_stream_custom_stream_wrapper(response: CustomStreamWrapper): + message_id: str = "" + tool_call_id: str = "" + content = "" + created = 0 + model = "" + system_fingerprint = "" + finish_reason=None + mode = None + all_tool_calls = [] + + for chunk in response: + if message_id is None: + message_id = chunk["id"] + + tool_calls = chunk["choices"][0]["delta"]["tool_calls"] + finish_reason = chunk["choices"][0]["finish_reason"] + created = chunk["created"] + model = chunk["model"] + system_fingerprint = chunk["system_fingerprint"] + + if mode == "text" and (tool_calls is not None or finish_reason is not None): + # end the current text message + await queue_put( + text_message_end( + message_id=message_id + ) + ) + + elif mode == "tool" and (tool_calls is None or finish_reason is not None): + # end the current tool call + await queue_put( + action_execution_end( + action_execution_id=tool_call_id + ) + ) + + if finish_reason is not None: + break + + if mode != "text" and tool_calls is None: + # start a new text message + await queue_put( + text_message_start( + message_id=message_id, + parent_message_id=None + ) + ) + elif mode != "tool" and tool_calls is not None and tool_calls[0].id is not None: + # start a new tool call + tool_call_id = tool_calls[0].id + + await queue_put( + action_execution_start( + action_execution_id=tool_call_id, + action_name=tool_calls[0].function["name"], + parent_message_id=message_id + ) + ) + + all_tool_calls.append( + { + "id": tool_call_id, + "name": tool_calls[0].function["name"], + "arguments": "", + } + ) + + mode = "tool" if tool_calls is not None else "text" + + if mode == "text": + text_content = chunk["choices"][0]["delta"]["content"] + if text_content is not None: + content += text_content + await queue_put( + text_message_content( + message_id=message_id, + content=text_content + ) + ) + + elif mode == "tool": + tool_arguments = tool_calls[0].function["arguments"] + if tool_arguments is not None: + await queue_put( + action_execution_args( + action_execution_id=tool_call_id, + args=tool_arguments + ) + ) + + all_tool_calls[-1]["arguments"] += tool_arguments + + tool_calls = [ + ChatCompletionMessageToolCall( + function=LiteLLMFunction( + arguments=tool_call["arguments"], + name=tool_call["name"] + ), + id=tool_call["id"], + type="function" + ) + for tool_call in all_tool_calls + ] + return ModelResponse( + id=message_id, + created=created, + model=model, + object='chat.completion', + system_fingerprint=system_fingerprint, + choices=[ + Choices( + finish_reason=finish_reason, + index=0, + message=LiteLLMMessage( + content=content, + role='assistant', + tool_calls=tool_calls if len(tool_calls) > 0 else None, + function_call=None + ) + ) + ] + ) + +def _copilotkit_stream_response(response: ModelResponse): + return response + + +async def copilotkit_exit() -> Literal[True]: + """ + Exits the current agent after the run completes. Calling copilotkit_exit() will + not immediately stop the agent. Instead, it signals to CopilotKit to stop the agent after + the run completes. + + ### Examples + + ```python + from copilotkit.crewai import copilotkit_exit + + def my_function(): + await copilotkit_exit() + return state + ``` + + Returns + ------- + Awaitable[bool] + Always return True. + """ + await queue_put( + meta_event( + name=RuntimeMetaEventName.EXIT, + value=True + ) + ) + return True + + +async def copilotkit_predict_state( + config: Dict[str, PredictStateConfig] + ) -> Literal[True]: + """ + Stream tool calls as state to CopilotKit. + + To emit a tool call as streaming CrewAI state, pass the destination key in state, + the tool name and optionally the tool argument. (If you don't pass the argument name, + all arguments are emitted under the state key.) + + ```python + from copilotkit.crewai import copilotkit_predict_state + + await copilotkit_predict_state( + { + "steps": { + "tool_name": "SearchTool", + "tool_argument": "steps", + }, + } + ) + ``` + + Parameters + ---------- + config : Dict[str, CopilotKitPredictStateConfig] + The configuration to predict the state. + + Returns + ------- + Awaitable[bool] + Always return True. + """ + + await queue_put( + meta_event( + name=RuntimeMetaEventName.PREDICT_STATE, + value=config + ) + ) + return True + + +def copilotkit_messages_to_crewai_flow(messages: List[Message]) -> List[Any]: + """ + Convert CopilotKit messages to CrewAI Flow messages + """ + result = [] + processed_action_executions = set() + + for message in messages: + message_id = message["id"] + message_type = message.get("type") + + if message_type == "TextMessage": + result.append({ + "id": message_id, + "role": message.get("role"), + "content": message.get("content") + }) + elif message_type == "ActionExecutionMessage": + # convert multiple tool calls to a single message + original_message_id = message.get("parentMessageId", message_id) + if original_message_id in processed_action_executions: + continue + + processed_action_executions.add(original_message_id) + + all_tool_calls = [] + + # Find all tool calls for this message + for msg in messages: + msg_id = msg["id"] + if (msg.get("parentMessageId", None) == original_message_id or + msg_id == original_message_id): + all_tool_calls.append(msg) + + tool_calls = [ + { + "type": "function", + "function": { + "name": t["name"], + "arguments": json.dumps(t["arguments"]), + }, + "id": t["id"], + } for t in all_tool_calls] + + result.append( + { + "id": original_message_id, + "role": "assistant", + "content": "", + "tool_calls": tool_calls + } + ) + + elif message_type == "ResultMessage": + result.append( + { + "id": message_id, + "role": "tool", + "tool_call_id": message.get("actionExecutionId"), + "content": message.get("result"), + } + ) + + return result + +def crewai_flow_messages_to_copilotkit(messages: List[Dict]) -> List[Message]: # pylint: disable=too-many-branches + """ + Convert CrewAI Flow messages to CopilotKit messages + """ + result = [] + tool_call_names = {} + + message_ids = { + id(m): m.get("id", str(uuid.uuid4())) for m in messages + } + + for message in messages: + if "content" in message and message.get("role") == "assistant": + if message.get("tool_calls"): + for tool_call in message["tool_calls"]: + tool_call_names[tool_call["id"]] = tool_call["function"]["name"] + + for message in messages: + message_id = message_ids[id(message)] + + if message.get("role") == "tool": + result.append({ + "actionExecutionId": message["tool_call_id"], + "actionName": tool_call_names.get(message["tool_call_id"], message.get("name", "")), + "result": message["content"], + "id": message_id, + }) + elif message.get("tool_calls"): + for tool_call in message["tool_calls"]: + if tool_call.get("function"): + result.append({ + "id": tool_call["id"], + "name": tool_call["function"]["name"], + "arguments": json.loads(tool_call["function"]["arguments"]), + "parentMessageId": message_id, + }) + else: + result.append({ + "id": tool_call["id"], + "name": tool_call["name"], + "arguments": tool_call["arguments"], + "parentMessageId": message_id, + }) + elif message.get("content"): + result.append({ + "role": message["role"], + "content": message["content"], + "id": message_id, + }) + + # Create a dictionary to map message ids to their corresponding messages + results_dict = {msg["actionExecutionId"]: msg for msg in result if "actionExecutionId" in msg} + + + # since we are splitting multiple tool calls into multiple messages, + # we need to reorder the corresponding result messages to be after the tool call + reordered_result = [] + + for msg in result: + + # add all messages that are not tool call results + if not "actionExecutionId" in msg: + reordered_result.append(msg) + + # if the message is a tool call, also add the corresponding result message + # immediately after the tool call + if msg.get("name"): + msg_id = msg["id"] + if msg_id in results_dict: + reordered_result.append(results_dict[msg_id]) + else: + logger.warning("Tool call result message not found for id: %s", msg_id) + + return reordered_result diff --git a/copilotkit/exc.py b/copilotkit/exc.py new file mode 100644 index 0000000..2cfc63e --- /dev/null +++ b/copilotkit/exc.py @@ -0,0 +1,31 @@ +"""Exceptions for CopilotKit.""" + +class ActionNotFoundException(Exception): + """Exception raised when an action or agent is not found.""" + + def __init__(self, name: str): + self.name = name + super().__init__(f"Action '{name}' not found.") + +class AgentNotFoundException(Exception): + """Exception raised when an agent is not found.""" + + def __init__(self, name: str): + self.name = name + super().__init__(f"Agent '{name}' not found.") + +class ActionExecutionException(Exception): + """Exception raised when an action fails to execute.""" + + def __init__(self, name: str, error: Exception): + self.name = name + self.error = error + super().__init__(f"Action '{name}' failed to execute: {error}") + +class AgentExecutionException(Exception): + """Exception raised when an agent fails to execute.""" + + def __init__(self, name: str, error: Exception): + self.name = name + self.error = error + super().__init__(f"Agent '{name}' failed to execute: {error}") diff --git a/copilotkit/html.py b/copilotkit/html.py new file mode 100644 index 0000000..46afc52 --- /dev/null +++ b/copilotkit/html.py @@ -0,0 +1,176 @@ +""" +HTML templates, used when the info endpoint is accessed from the browser. +""" +import json +from copilotkit.sdk import InfoDict + +HEAD_HTML = """ + + + + CopilotKit Remote Endpoint v0.1.12 + + +""" + +INFO_TEMPLATE= """ + + +{head_html} + +
+
+

🪁CopilotKit Remote Endpoint (v{version})

+
+ +
+
+

Actions

+
+ {action_html} +
+
+
+

Agents

+
+ {agent_html} +
+
+
+
+ + +""" + +ACTION_TEMPLATE = """ +
+

{name}

+

{description}

+

Arguments:

+ 
{arguments}
+
+""" + +AGENT_TEMPLATE = """ +
+

{name} {type}

+

{description}

+
+""" + +NO_ACTIONS_FOUND_HTML = """ +
+

No actions found

+
+""" + +NO_AGENTS_FOUND_HTML = """ +
+

No agents found

+
+""" + +def generate_info_html(info: InfoDict) -> str: + """ + Generate HTML for the info endpoint + """ + print(info, flush=True) + action_html = "" + for action in info["actions"]: + action_html += ACTION_TEMPLATE.format( + name=action["name"], + description=action["description"], + arguments=json.dumps(action.get("parameters", []), indent=2), + ) + agent_html = "" + for agent in info["agents"]: + agent_type = agent.get("type", "Unknown") + if agent_type == "langgraph": + agent_type = "LangGraph" + elif agent_type == "crewai": + agent_type = "CrewAI" + + agent_html += AGENT_TEMPLATE.format( + name=agent["name"], + type=agent_type, + description=agent["description"], + ) + return INFO_TEMPLATE.format( + head_html=HEAD_HTML, + version=info["sdkVersion"], + action_html=action_html or NO_ACTIONS_FOUND_HTML, + agent_html=agent_html or NO_AGENTS_FOUND_HTML, + ) diff --git a/copilotkit/integrations/__init__.py b/copilotkit/integrations/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/copilotkit/integrations/fastapi.py b/copilotkit/integrations/fastapi.py new file mode 100644 index 0000000..6f6ac97 --- /dev/null +++ b/copilotkit/integrations/fastapi.py @@ -0,0 +1,327 @@ +"""FastAPI integration""" + +import logging +import asyncio +import re +import uuid +import warnings +from concurrent.futures import ThreadPoolExecutor +from typing import List, Any, cast, Optional +from fastapi import FastAPI, Request, HTTPException +from fastapi.responses import JSONResponse, StreamingResponse, HTMLResponse +from fastapi.encoders import jsonable_encoder +from ..sdk import CopilotKitRemoteEndpoint, CopilotKitContext +from ..types import Message, MetaEvent +from ..exc import ( + ActionNotFoundException, + ActionExecutionException, + AgentNotFoundException, + AgentExecutionException, +) +from ..action import ActionDict +from ..html import generate_info_html +logging.basicConfig(level=logging.ERROR) +logger = logging.getLogger(__name__) + +def add_fastapi_endpoint( + fastapi_app: FastAPI, + sdk: CopilotKitRemoteEndpoint, + prefix: str, + *, + use_thread_pool: bool = False, + max_workers: int = 10, + ): + """Add FastAPI endpoint with configurable ThreadPoolExecutor size""" + if use_thread_pool: + warnings.warn( + "The 'use_thread_pool' parameter is deprecated " + + "and will be removed in a future version.", + DeprecationWarning + ) + + def run_handler_in_thread(request: Request, sdk: CopilotKitRemoteEndpoint): + # Run the handler coroutine in the event loop + loop = asyncio.new_event_loop() + asyncio.set_event_loop(loop) + return loop.run_until_complete(handler(request, sdk)) + + async def make_handler(request: Request): + if use_thread_pool: + executor = ThreadPoolExecutor(max_workers=max_workers) + loop = asyncio.get_event_loop() + future = loop.run_in_executor(executor, run_handler_in_thread, request, sdk) + return await future + return await handler(request, sdk) + + + # Ensure the prefix starts with a slash and remove trailing slashes + normalized_prefix = '/' + prefix.strip('/') + + fastapi_app.add_api_route( + f"{normalized_prefix}/{{path:path}}", + make_handler, + methods=['GET', 'POST', 'PUT', 'DELETE', 'OPTIONS'], + ) + +def body_get_or_raise(body: Any, key: str): + """Get value from body or raise an error""" + value = body.get(key) + if value is None: + raise HTTPException(status_code=400, detail=f"{key} is required") + return value + + +async def handler(request: Request, sdk: CopilotKitRemoteEndpoint): + """Handle FastAPI request""" + + try: + body = await request.json() + except: # pylint: disable=bare-except + body = None + + path = request.path_params.get('path') + method = request.method + context = cast( + CopilotKitContext, + { + "properties": (body or {}).get("properties", {}), + "frontend_url": (body or {}).get("frontendUrl", None), + "headers": request.headers, + } + ) + + # handle / request for info endpoint + if method in ['GET', 'POST'] and path == '': + accept_header = request.headers.get('accept', '') + return await handle_info( + sdk=sdk, + context=context, + as_html='text/html' in accept_header, + ) + + # handle /agent/name request for executing an agent + if method == 'POST' and (match := re.match(r'agent/([a-zA-Z0-9_-]+)', path)): + name = match.group(1) + body = body or {} + + thread_id = body.get("threadId", str(uuid.uuid4())) + state = body.get("state", {}) + messages = body.get("messages", []) + actions = body.get("actions", []) + + # used for LangGraph only + node_name = body.get("nodeName") + + return handle_execute_agent( + sdk=sdk, + context=context, + thread_id=thread_id, + node_name=node_name, + name=name, + state=state, + messages=messages, + actions=actions, + ) + + # handle /agent/name/state request for getting agent state + if method == 'POST' and (match := re.match(r'agent/([a-zA-Z0-9_-]+)/state', path)): + name = match.group(1) + thread_id = body_get_or_raise(body, "threadId") + + return await handle_get_agent_state( + sdk=sdk, + context=context, + thread_id=thread_id, + name=name, + ) + + # handle /action/name request for executing an action + if method == 'POST' and (match := re.match(r'action/([a-zA-Z0-9_-]+)', path)): + name = match.group(1) + arguments = body.get("arguments", {}) + + return await handle_execute_action( + sdk=sdk, + context=context, + name=name, + arguments=arguments, + ) + + # v2: POST /agents/name/state + + # Deal with backwards compatibility + result_v1 = await handler_v1( + sdk=sdk, + method=method, + path=path, + body=body, + context=context, + ) + + if result_v1 is not None: + return result_v1 + + + raise HTTPException(status_code=404, detail="Not found") + +async def handler_v1( + sdk: CopilotKitRemoteEndpoint, + method: str, + path: str, + body: Any, + context: CopilotKitContext, + ): + """Handle FastAPI request for v1""" + + if body is None: + raise HTTPException(status_code=400, detail="Request body is required") + + if method == 'POST' and path == 'info': + return await handle_info(sdk=sdk, context=context) + + + if method == 'POST' and path == 'actions/execute': + name = body_get_or_raise(body, "name") + arguments = body.get("arguments", {}) + + return await handle_execute_action( + sdk=sdk, + context=context, + name=name, + arguments=arguments, + ) + + if method == 'POST' and path == 'agents/execute': + thread_id = body.get("threadId") + node_name = body.get("nodeName") + config = body.get("config") + + name = body_get_or_raise(body, "name") + state = body_get_or_raise(body, "state") + messages = body_get_or_raise(body, "messages") + actions = cast(List[ActionDict], body.get("actions", [])) + meta_events = cast(List[MetaEvent], body.get("metaEvents", [])) + + return handle_execute_agent( + sdk=sdk, + context=context, + thread_id=thread_id, + node_name=node_name, + name=name, + state=state, + config=config, + messages=messages, + actions=actions, + meta_events=meta_events, + ) + + + if method == 'POST' and path == 'agents/state': + thread_id = body_get_or_raise(body, "threadId") + name = body_get_or_raise(body, "name") + + return await handle_get_agent_state( + sdk=sdk, + context=context, + thread_id=thread_id, + name=name, + ) + + return None + + +async def handle_info( + *, + sdk: CopilotKitRemoteEndpoint, + context: CopilotKitContext, + as_html: bool = False, + ): + """Handle info request with FastAPI""" + result = sdk.info(context=context) + if as_html: + return HTMLResponse(content=generate_info_html(result)) + return JSONResponse(content=jsonable_encoder(result)) + +async def handle_execute_action( + *, + sdk: CopilotKitRemoteEndpoint, + context: CopilotKitContext, + name: str, + arguments: dict, + ): + """Handle execute action request with FastAPI""" + try: + result = await sdk.execute_action( + context=context, + name=name, + arguments=arguments + ) + return JSONResponse(content=jsonable_encoder(result)) + except ActionNotFoundException as exc: + logger.error("Action not found: %s", exc) + return JSONResponse(content={"error": str(exc)}, status_code=404) + except ActionExecutionException as exc: + logger.error("Action execution error: %s", exc) + return JSONResponse(content={"error": str(exc)}, status_code=500) + except Exception as exc: # pylint: disable=broad-except + logger.error("Action execution error: %s", exc) + return JSONResponse(content={"error": str(exc)}, status_code=500) + +def handle_execute_agent( # pylint: disable=too-many-arguments + *, + sdk: CopilotKitRemoteEndpoint, + context: CopilotKitContext, + thread_id: str, + name: str, + state: dict, + config: Optional[dict] = None, + messages: List[Message], + actions: List[ActionDict], + node_name: str, + meta_events: Optional[List[MetaEvent]] = None, + ): + """Handle continue agent execution request with FastAPI""" + try: + events = sdk.execute_agent( + context=context, + thread_id=thread_id, + name=name, + node_name=node_name, + state=state, + config=config, + messages=messages, + actions=actions, + meta_events=meta_events, + ) + return StreamingResponse(events, media_type="application/json") + except AgentNotFoundException as exc: + logger.error("Agent not found: %s", exc, exc_info=True) + return JSONResponse(content={"error": str(exc)}, status_code=404) + except AgentExecutionException as exc: + logger.error("Agent execution error: %s", exc, exc_info=True) + return JSONResponse(content={"error": str(exc)}, status_code=500) + except Exception as exc: # pylint: disable=broad-except + logger.error("Agent execution error: %s", exc, exc_info=True) + return JSONResponse(content={"error": str(exc)}, status_code=500) + +async def handle_get_agent_state( + *, + sdk: CopilotKitRemoteEndpoint, + context: CopilotKitContext, + thread_id: str, + name: str, + ): + """Handle get agent state request with FastAPI""" + try: + result = await sdk.get_agent_state( + context=context, + thread_id=thread_id, + name=name, + ) + return JSONResponse(content=jsonable_encoder(result)) + except AgentNotFoundException as exc: + logger.error("Agent not found: %s", exc, exc_info=True) + return JSONResponse(content={"error": str(exc)}, status_code=404) + except Exception as exc: # pylint: disable=broad-except + logger.error("Agent get state error: %s", exc, exc_info=True) + return JSONResponse(content={"error": str(exc)}, status_code=500) diff --git a/copilotkit/langchain.py b/copilotkit/langchain.py new file mode 100644 index 0000000..b921e5c --- /dev/null +++ b/copilotkit/langchain.py @@ -0,0 +1,31 @@ +""" +copilotkit.langchain is deprecated. Use copilotkit.langgraph instead. +""" +import warnings +from copilotkit.langgraph import ( + langchain_messages_to_copilotkit, + copilotkit_messages_to_langchain, + copilotkit_customize_config, + copilotkit_exit, + copilotkit_emit_state, + copilotkit_emit_message, + copilotkit_emit_tool_call, + copilotkit_interrupt, +) + +warnings.warn( + "copilotkit.langchain is deprecated. Use copilotkit.langgraph instead.", + DeprecationWarning, + stacklevel=2 +) + +__all__ = [ + "langchain_messages_to_copilotkit", + "copilotkit_messages_to_langchain", + "copilotkit_customize_config", + "copilotkit_exit", + "copilotkit_emit_state", + "copilotkit_emit_message", + "copilotkit_emit_tool_call", + "copilotkit_interrupt", +] diff --git a/copilotkit/langgraph.py b/copilotkit/langgraph.py new file mode 100644 index 0000000..34c7e49 --- /dev/null +++ b/copilotkit/langgraph.py @@ -0,0 +1,502 @@ +""" +LangChain specific utilities for CopilotKit +""" + +import uuid +import json +import warnings +import asyncio +from typing import List, Optional, Any, Union, Dict, Callable, cast +from typing_extensions import TypedDict +from langgraph.graph import MessagesState + + +from langchain_core.messages import ( + HumanMessage, + SystemMessage, + BaseMessage, + AIMessage, + ToolMessage +) +from langchain_core.runnables import RunnableConfig +from langchain_core.callbacks.manager import adispatch_custom_event +from langgraph.types import interrupt + +from .types import Message, IntermediateStateConfig +from .logging import get_logger + +logger = get_logger(__name__) + +class CopilotContextItem(TypedDict): + """Copilot context item""" + description: str + value: Any + +class CopilotKitProperties(TypedDict): + """CopilotKit state""" + actions: List[Any] + context: List[CopilotContextItem] + + # Private state for CopilotKit middleware + intercepted_tool_calls: Any + original_ai_message_id: Any + +class CopilotKitState(MessagesState): + """CopilotKit state""" + copilotkit: CopilotKitProperties + + +def copilotkit_messages_to_langchain( + use_function_call: bool = False + ) -> Callable[[List[Message]], List[BaseMessage]]: + """ + Convert CopilotKit messages to LangChain messages + """ + def _copilotkit_messages_to_langchain(messages: List[Message]) -> List[BaseMessage]: + result = [] + processed_action_executions = set() + for message in cast(Any, messages): + if message["type"] == "TextMessage": + if message["role"] == "user": + result.append(HumanMessage(content=message["content"], id=message["id"])) + elif message["role"] == "system": + result.append(SystemMessage(content=message["content"], id=message["id"])) + elif message["role"] == "assistant": + result.append(AIMessage(content=message["content"], id=message["id"])) + elif message["type"] == "ActionExecutionMessage": + if use_function_call: + result.append(AIMessage( + id=message["id"], + content="", + additional_kwargs={ + 'function_call':{ + 'name': message["name"], + 'arguments': json.dumps(message["arguments"]), + } + } + )) + else: + # convert multiple tool calls to a single message + message_id = message.get("parentMessageId") + if message_id is None: + message_id = message["id"] + + if message_id in processed_action_executions: + continue + + processed_action_executions.add(message_id) + + all_tool_calls = [] + + # Find all tool calls for this message (only ActionExecutionMessage type) + for msg in messages: + if msg.get("type") != "ActionExecutionMessage": + continue + if msg.get("parentMessageId", None) == message_id or msg["id"] == message_id: + all_tool_calls.append(msg) + + tool_calls = [{ + "name": t["name"], + "args": t["arguments"], + "id": t["id"], + } for t in all_tool_calls] + + result.append( + AIMessage( + id=message_id, + content="", + tool_calls=tool_calls + ) + ) + + elif message["type"] == "ResultMessage": + result.append(ToolMessage( + id=message["id"], + content=message["result"], + name=message["actionName"], + tool_call_id=message["actionExecutionId"] + )) + + return result + + return _copilotkit_messages_to_langchain + + +def langchain_messages_to_copilotkit( + messages: List[BaseMessage] + ) -> List[Message]: + """ + Convert LangChain messages to CopilotKit messages + """ + result = [] + tool_call_names = {} + + for message in messages: + if isinstance(message, AIMessage): + for tool_call in message.tool_calls or []: + tool_call_names[tool_call["id"]] = tool_call["name"] + + for message in messages: + content = None + + if hasattr(message, "content"): + content = message.content + + # Check if content is a list and use the first element + if isinstance(content, list): + content = content[0] if content else "" + + # Anthropic models return a dict with a "text" key + if isinstance(content, dict): + content = content.get("text", "") + + if isinstance(message, HumanMessage): + result.append({ + "role": "user", + "content": content, + "id": message.id, + }) + elif isinstance(message, SystemMessage): + result.append({ + "role": "system", + "content": content, + "id": message.id, + }) + elif isinstance(message, AIMessage): + if content: + result.append({ + "role": "assistant", + "content": content, + "id": message.id, + }) + if message.tool_calls: + for tool_call in message.tool_calls: + result.append({ + "id": tool_call["id"], + "name": tool_call["name"], + "arguments": tool_call["args"], + "parentMessageId": message.id, + }) + elif isinstance(message, ToolMessage): + result.append({ + "actionExecutionId": message.tool_call_id, + "actionName": tool_call_names.get(message.tool_call_id, message.name or ""), + "result": content, + "id": message.id, + }) + + # Create a dictionary to map message ids to their corresponding messages + results_dict = {msg["actionExecutionId"]: msg for msg in result if "actionExecutionId" in msg} + + + # since we are splitting multiple tool calls into multiple messages, + # we need to reorder the corresponding result messages to be after the tool call + reordered_result = [] + + for msg in result: + + # add all messages that are not tool call results + if not "actionExecutionId" in msg: + reordered_result.append(msg) + + # if the message is a tool call, also add the corresponding result message + # immediately after the tool call + if "arguments" in msg: + msg_id = msg["id"] + if msg_id in results_dict: + reordered_result.append(results_dict[msg_id]) + else: + logger.warning("Tool call result message not found for id: %s", msg_id) + + return reordered_result + +def copilotkit_customize_config( + base_config: Optional[RunnableConfig] = None, + *, + emit_messages: Optional[bool] = None, + emit_tool_calls: Optional[Union[bool, str, List[str]]] = None, + emit_intermediate_state: Optional[List[IntermediateStateConfig]] = None, + emit_all: Optional[bool] = None, # deprecated + ) -> RunnableConfig: + """ + Customize the LangGraph configuration for use in CopilotKit. + + To install the CopilotKit SDK, run: + + ```bash + pip install copilotkit + ``` + + ### Examples + + Disable emitting messages and tool calls: + + ```python + from copilotkit.langgraph import copilotkit_customize_config + + config = copilotkit_customize_config( + config, + emit_messages=False, + emit_tool_calls=False + ) + ``` + + To emit a tool call as streaming LangGraph state, pass the destination key in state, + the tool name and optionally the tool argument. (If you don't pass the argument name, + all arguments are emitted under the state key.) + + ```python + from copilotkit.langgraph import copilotkit_customize_config + + config = copilotkit_customize_config( + config, + emit_intermediate_state=[ + { + "state_key": "steps", + "tool": "SearchTool", + "tool_argument": "steps" + }, + ] + ) + ``` + + Parameters + ---------- + base_config : Optional[RunnableConfig] + The LangChain/LangGraph configuration to customize. Pass None to make a new configuration. + emit_messages : Optional[bool] + Configure how messages are emitted. By default, all messages are emitted. Pass False to + disable emitting messages. + emit_tool_calls : Optional[Union[bool, str, List[str]]] + Configure how tool calls are emitted. By default, all tool calls are emitted. Pass False to + disable emitting tool calls. Pass a string or list of strings to emit only specific tool calls. + emit_intermediate_state : Optional[List[IntermediateStateConfig]] + Lets you emit tool calls as streaming LangGraph state. + + Returns + ------- + RunnableConfig + The customized LangGraph configuration. + """ + if emit_all is not None: + warnings.warn( + "The `emit_all` parameter is deprecated and will be removed in a future version. " + "CopilotKit will now emit all messages and tool calls by default.", + DeprecationWarning, + stacklevel=2 + ) + metadata = base_config.get("metadata", {}) if base_config else {} + + if emit_all is True: + metadata["copilotkit:emit-tool-calls"] = True + metadata["copilotkit:emit-messages"] = True + else: + if emit_tool_calls is not None: + metadata["copilotkit:emit-tool-calls"] = emit_tool_calls + if emit_messages is not None: + metadata["copilotkit:emit-messages"] = emit_messages + + if emit_intermediate_state: + metadata["copilotkit:emit-intermediate-state"] = emit_intermediate_state + + base_config = base_config or {} + + return { + **base_config, + "metadata": metadata + } + + +async def copilotkit_exit(config: RunnableConfig): + """ + Exits the current agent after the run completes. Calling copilotkit_exit() will + not immediately stop the agent. Instead, it signals to CopilotKit to stop the agent after + the run completes. + + ### Examples + + ```python + from copilotkit.langgraph import copilotkit_exit + + def my_node(state: Any): + await copilotkit_exit(config) + return state + ``` + + Parameters + ---------- + config : RunnableConfig + The LangGraph configuration. + + Returns + ------- + Awaitable[bool] + Always return True. + """ + + await adispatch_custom_event( + "copilotkit_exit", + {}, + config=config, + ) + await asyncio.sleep(0.02) + + return True + +async def copilotkit_emit_state(config: RunnableConfig, state: Any): + """ + Emits intermediate state to CopilotKit. Useful if you have a longer running node and you want to + update the user with the current state of the node. + + ### Examples + + ```python + from copilotkit.langgraph import copilotkit_emit_state + + for i in range(10): + await some_long_running_operation(i) + await copilotkit_emit_state(config, {"progress": i}) + ``` + + Parameters + ---------- + config : RunnableConfig + The LangGraph configuration. + state : Any + The state to emit (Must be JSON serializable). + + Returns + ------- + Awaitable[bool] + Always return True. + """ + + await adispatch_custom_event( + "copilotkit_manually_emit_intermediate_state", + state, + config=config, + ) + await asyncio.sleep(0.02) + + return True + +async def copilotkit_emit_message(config: RunnableConfig, message: str): + """ + Manually emits a message to CopilotKit. Useful in longer running nodes to update the user. + Important: You still need to return the messages from the node. + + ### Examples + + ```python + from copilotkit.langgraph import copilotkit_emit_message + + message = "Step 1 of 10 complete" + await copilotkit_emit_message(config, message) + + # Return the message from the node + return { + "messages": [AIMessage(content=message)] + } + ``` + + Parameters + ---------- + config : RunnableConfig + The LangGraph configuration. + message : str + The message to emit. + + Returns + ------- + Awaitable[bool] + Always return True. + """ + await adispatch_custom_event( + "copilotkit_manually_emit_message", + { + "message": message, + "message_id": str(uuid.uuid4()), + "role": "assistant" + }, + config=config, + ) + await asyncio.sleep(0.02) + + return True + + +async def copilotkit_emit_tool_call(config: RunnableConfig, *, name: str, args: Dict[str, Any]): + """ + Manually emits a tool call to CopilotKit. + + ```python + from copilotkit.langgraph import copilotkit_emit_tool_call + + await copilotkit_emit_tool_call(config, name="SearchTool", args={"steps": 10}) + ``` + + Parameters + ---------- + config : RunnableConfig + The LangGraph configuration. + name : str + The name of the tool to emit. + args : Dict[str, Any] + The arguments to emit. + + Returns + ------- + Awaitable[bool] + Always return True. + """ + + await adispatch_custom_event( + "copilotkit_manually_emit_tool_call", + { + "name": name, + "args": args, + "id": str(uuid.uuid4()) + }, + config=config, + ) + await asyncio.sleep(0.02) + + return True + +def copilotkit_interrupt( + message: Optional[str] = None, + action: Optional[str] = None, + args: Optional[Dict[str, Any]] = None +): + if message is None and action is None: + raise ValueError('Either message or action (and optional arguments) must be provided') + + interrupt_message = None + interrupt_values = None + answer = None + + if message is not None: + interrupt_values = message + interrupt_message = AIMessage(content=message, id=str(uuid.uuid4())) + else: + tool_id = str(uuid.uuid4()) + interrupt_message = AIMessage( + content="", + tool_calls=[{ + "id": tool_id, + "name": action, + "args": args or {} + }] + ) + interrupt_values = { + "action": action, + "args": args or {} + } + + response = interrupt({ + "__copilotkit_interrupt_value__": interrupt_values, + "__copilotkit_messages__": [interrupt_message] + }) + answer = response[-1].content + + return answer, response diff --git a/copilotkit/langgraph_agent.py b/copilotkit/langgraph_agent.py new file mode 100644 index 0000000..f65154a --- /dev/null +++ b/copilotkit/langgraph_agent.py @@ -0,0 +1,788 @@ +"""LangGraph agent for CopilotKit""" + +import uuid +import json +from typing import Optional, List, Callable, Any, cast, Union, TypedDict, Literal + +from langgraph.graph.state import CompiledStateGraph +from typing_extensions import NotRequired + +from langgraph.types import Command + +try: + from langchain.load.dump import dumps as langchain_dumps + from langchain.schema import BaseMessage, SystemMessage +except ImportError: + # Langchain >= 1.0.0 + from langchain_core.load import dumps as langchain_dumps + from langchain_core.messages import BaseMessage, SystemMessage + +from langchain_core.runnables import RunnableConfig, ensure_config +from langchain_core.messages import HumanMessage + +from partialjson.json_parser import JSONParser + +from .types import Message, MetaEvent +from .utils import filter_by_schema_keys +from .langgraph import copilotkit_messages_to_langchain, langchain_messages_to_copilotkit +from .action import ActionDict +from .agent import Agent +from .logging import get_logger + +logger = get_logger(__name__) + +class CopilotKitConfig(TypedDict): + """ + CopilotKit config for LangGraphAgent + + This is used for advanced cases where you want to customize how CopilotKit interacts with + LangGraph. + + ```python + # Function signatures: + def merge_state( + *, + state: dict, + messages: List[BaseMessage], + actions: List[Any], + agent_name: str + ): + # ...implementation... + + def convert_messages(messages: List[Message]): + # ...implementation... + ``` + + Parameters + ---------- + merge_state : Callable + This function lets you customize how CopilotKit merges the agent state. + convert_messages : Callable + Use this function to customize how CopilotKit converts its messages to LangChain messages.` + """ + merge_state: NotRequired[Callable] + convert_messages: NotRequired[Callable] + +def langgraph_default_merge_state( # pylint: disable=unused-argument + *, + state: dict, + messages: List[BaseMessage], + actions: List[Any], + agent_name: str + ): + """Default merge state for LangGraph""" + if len(messages) > 0 and isinstance(messages[0], SystemMessage): + # remove system message + messages = messages[1:] + + existing_messages = state.get("messages", []) + existing_message_ids = {message.id for message in existing_messages} + + new_messages = [message for message in messages if message.id not in existing_message_ids] + + return { + **state, + "messages": new_messages, + "copilotkit": { + "actions": actions + } + } + + +class LangGraphAgent(Agent): + """ + LangGraphAgent lets you define your agent for use with CopilotKit. + + To install, run: + + ```bash + pip install copilotkit + ``` + + ### Examples + + Every agent must have the `name` and `graph` properties defined. An optional `description` + can also be provided. This is used when CopilotKit is dynamically routing requests to the + agent. + + ```python + from copilotkit import LangGraphAgent + + LangGraphAgent( + name="email_agent", + description="This agent sends emails", + graph=graph, + ) + ``` + + If you have a custom LangGraph/LangChain config that you want to use with the agent, you can + pass it in as the `langgraph_config` parameter. + + ```python + LangGraphAgent( + ... + langgraph_config=config, + ) + ``` + + Parameters + ---------- + name : str + The name of the agent. + graph : CompiledStateGraph + The LangGraph graph to use with the agent. + description : Optional[str] + The description of the agent. + langgraph_config : Optional[RunnableConfig] + The LangGraph/LangChain config to use with the agent. + copilotkit_config : Optional[CopilotKitConfig] + The CopilotKit config to use with the agent. + """ + def __init__( + self, + *, + name: str, + graph: Optional[CompiledStateGraph] = None, + description: Optional[str] = None, + langgraph_config: Union[Optional[RunnableConfig], dict] = None, + copilotkit_config: Optional[CopilotKitConfig] = None, + + # deprecated - use langgraph_config instead + config: Union[Optional[RunnableConfig], dict] = None, + # deprecated - use graph instead + agent: Optional[CompiledStateGraph] = None, + # deprecated - use copilotkit_config instead + merge_state: Optional[Callable] = None, + ): + if config is not None: + logger.warning("Warning: config is deprecated, use langgraph_config instead") + + if agent is not None: + logger.warning("Warning: agent is deprecated, use graph instead") + + if merge_state is not None: + logger.warning("Warning: merge_state is deprecated, use copilotkit_config instead") + + if graph is None and agent is None: + raise ValueError("graph must be provided") + + super().__init__( + name=name, + description=description, + ) + + self.merge_state = None + self.thread_state = {} + if copilotkit_config is not None: + self.merge_state = copilotkit_config.get("merge_state") + if not self.merge_state and merge_state is not None: + self.merge_state = merge_state + if not self.merge_state: + self.merge_state = langgraph_default_merge_state + + self.convert_messages = ( + copilotkit_config.get("convert_messages") + if copilotkit_config + else None + ) or copilotkit_messages_to_langchain(use_function_call=False) + + self.langgraph_config = langgraph_config or config + + self.graph = cast(CompiledStateGraph, graph or agent) + self.active_interrupt_event = False + + def execute( # pylint: disable=too-many-arguments + self, + *, + state: dict, + config: Optional[dict] = None, + messages: List[Message], + thread_id: str, + actions: Optional[List[ActionDict]] = None, + meta_events: Optional[List[MetaEvent]] = None, + **kwargs + ): + node_name = kwargs.get("node_name") + + return self._stream_events( + state=state, + config=config, + messages=messages, + actions=actions, + thread_id=thread_id, + node_name=node_name, + meta_events=meta_events + ) + + async def prepare_stream( # pylint: disable=too-many-arguments + self, + *, + state_input: Any, + agent_state: Any, + config: Optional[dict] = None, + messages: List[Message], + thread_id: str, + actions: Optional[List[ActionDict]] = None, + node_name: Optional[str] = None, + meta_events: Optional[List[MetaEvent]] = None, + ): + active_interrupts = agent_state.tasks[0].interrupts if agent_state.tasks and agent_state.tasks[0].interrupts else None + state_input["messages"] = agent_state.values.get("messages", []) + current_graph_state = agent_state.values + langchain_messages = self.convert_messages(messages) + state = cast(Callable, self.merge_state)( + state=state_input, + messages=langchain_messages, + actions=actions, + agent_name=self.name + ) + current_graph_state.update(state) + lg_interrupt_meta_event = next((ev for ev in (meta_events or []) if ev.get("name") == "LangGraphInterruptEvent"), None) + has_active_interrupts = active_interrupts is not None and len(active_interrupts) > 0 + + resume_input = None + + # An active interrupt event that runs through messages. Use latest message as response + if has_active_interrupts and lg_interrupt_meta_event is None: + # state["messages"] only includes the messages we need to add at this point, tool call+result if applicable, and user text + resume_input = Command(resume=state["messages"]) + + if lg_interrupt_meta_event and "response" in lg_interrupt_meta_event: + resume_input = Command(resume=lg_interrupt_meta_event["response"]) + + mode = "continue" if thread_id and node_name != "__end__" and node_name is not None else "start" + thread_id = thread_id or str(uuid.uuid4()) + config["configurable"]["thread_id"] = thread_id + + if mode == "continue" and not has_active_interrupts: + await self.graph.aupdate_state(config, state, as_node=node_name) + + + initial_state = state if mode == "start" else None + + # Use provided resume_input or fallback to initial_state + stream_input = resume_input if resume_input else initial_state + + # Get the output and input schema keys the user has allowed for this graph + input_keys, output_keys, config_keys = self.get_schema_keys(config) + self.output_schema_keys = output_keys + self.input_schema_keys = input_keys + + stream_input = self.filter_state_on_schema_keys(stream_input, 'input') + config["configurable"] = filter_by_schema_keys(config["configurable"], config_keys) + + if has_active_interrupts and (not resume_input): + value = active_interrupts[0].value + return { + "stream": None, + "state": None, + "config": None, + "interrupt_event": self.get_interrupt_event(value), + } + + return { + "stream": self.graph.astream_events(stream_input, config, version="v2"), + "state": current_graph_state, + "config": config + } + + async def prepare_regenerate_stream( # pylint: disable=too-many-arguments + self, + *, + state: Any, + config: Optional[dict] = None, + actions: Optional[List[ActionDict]] = None, + message_checkpoint: HumanMessage + ): + thread_id = config.get("configurable", {}).get("thread_id") + time_travel_checkpoint = await self.get_checkpoint_before_message(message_checkpoint.id, thread_id) + if time_travel_checkpoint is None: + return None + + fork = await self.graph.aupdate_state( + time_travel_checkpoint.config, + time_travel_checkpoint.values, + as_node=time_travel_checkpoint.next[0] if time_travel_checkpoint.next else "__start__" + ) + + stream_input = cast(Callable, self.merge_state)( + state=time_travel_checkpoint.values, + messages=[message_checkpoint], + actions=actions, + agent_name=self.name + ) + stream = self.graph.astream_events(stream_input, fork, version="v2") + return { + "stream": stream, + "state": state, + "config": config + } + + + async def _stream_events( # pylint: disable=too-many-locals + self, + *, + state: Any, + config: Optional[dict] = None, + messages: List[Message], + thread_id: str, + actions: Optional[List[ActionDict]] = None, + node_name: Optional[str] = None, + meta_events: Optional[List[MetaEvent]] = None, + ): + default_config = ensure_config(cast(Any, self.langgraph_config.copy()) if self.langgraph_config else {}) # pylint: disable=line-too-long + config = {**default_config, **(self.graph.config or {}), **(config or {})} + config["configurable"] = {**config.get("configurable", {}), **(config["configurable"] or {})} + config["configurable"]["thread_id"] = thread_id + + streaming_state_extractor = _StreamingStateExtractor([]) + prev_node_name = None + emit_intermediate_state_until_end = None + should_exit = False + manually_emitted_state = None + thread_id = cast(Any, config)["configurable"]["thread_id"] + + agent_state = await self.graph.aget_state(config) + prepared_stream_response = await self.prepare_stream( + state_input=state, + agent_state=agent_state, + config=config, + messages=messages, + actions=actions, + thread_id=thread_id, + node_name=node_name, + meta_events=meta_events + ) + + langchain_messages = self.convert_messages(messages) + non_system_messages = [msg for msg in langchain_messages if not isinstance(msg, SystemMessage)] + if len(agent_state.values.get("messages", [])) > len(non_system_messages): + # Find the last user message by working backwards from the last message + last_user_message = None + for i in range(len(langchain_messages) - 1, -1, -1): + if isinstance(langchain_messages[i], HumanMessage): + last_user_message = langchain_messages[i] + break + + if last_user_message: + prepared_stream_response = await self.prepare_regenerate_stream( + state=state, + config=config, + message_checkpoint=last_user_message, + actions=actions, + ) + + state = prepared_stream_response["state"] + current_graph_state = prepared_stream_response["state"] + stream = prepared_stream_response["stream"] + config = prepared_stream_response["config"] + interrupt_event = prepared_stream_response.get('interrupt_event', None) + + if interrupt_event: + yield interrupt_event + return + + try: + async for event in stream: + current_node_name = event.get("name") + event_type = event.get("event") + run_id = event.get("run_id") + metadata = event.get("metadata", {}) + + interrupt_event = ( + event["data"].get("chunk", {}).get("__interrupt__", None) + if ( + isinstance(event.get("data"), dict) and + isinstance(event["data"].get("chunk"), dict) + ) + else None + ) + if interrupt_event: + value = interrupt_event[0].value + yield self.get_interrupt_event(value) + continue + + should_exit = should_exit or ( + event_type == "on_custom_event" and + event["name"] == "copilotkit_exit" + ) + + # OPTIMIZATION: Update local state from chain_end events to avoid checkpointer calls + if event_type == "on_chain_end" and isinstance( + event.get("data", {}).get("output"), dict + ): + current_graph_state.update(event["data"]["output"]) + + emit_intermediate_state = metadata.get("copilotkit:emit-intermediate-state") + manually_emit_intermediate_state = ( + event_type == "on_custom_event" and + event["name"] == "copilotkit_manually_emit_intermediate_state" + ) + + + # we only want to update the node name under certain conditions + # since we don't need any internal node names to be sent to the frontend + if current_node_name in self.graph.nodes.keys(): + node_name = current_node_name + + # we don't have a node name yet, so we can't update the state + if node_name is None: + continue + + exiting_node = node_name == current_node_name and event_type == "on_chain_end" + + if exiting_node: + manually_emitted_state = None + + if manually_emit_intermediate_state: + manually_emitted_state = cast(Any, event["data"]) + yield self._emit_state_sync_event( + thread_id=thread_id, + run_id=run_id, + node_name=node_name, + state=manually_emitted_state, + running=True, + active=True + ) + "\n" + continue + + + if emit_intermediate_state and emit_intermediate_state_until_end is None: + emit_intermediate_state_until_end = node_name + + if emit_intermediate_state and event_type == "on_chat_model_start": + # reset the streaming state extractor + streaming_state_extractor = _StreamingStateExtractor(emit_intermediate_state) + + # OPTIMIZATION: Use locally maintained state instead of hitting checkpointer repeatedly + updated_state = manually_emitted_state or current_graph_state + + if emit_intermediate_state and event_type == "on_chat_model_stream": + streaming_state_extractor.buffer_tool_calls(event) + + if emit_intermediate_state_until_end is not None: + updated_state = { + **updated_state, + **streaming_state_extractor.extract_state() + } + + if (not emit_intermediate_state and + current_node_name == emit_intermediate_state_until_end and + event_type == "on_chain_end"): + # stop emitting function call state + emit_intermediate_state_until_end = None + + # we send state sync events when: + # a) the state has changed + # b) the node has changed + # c) the node is ending + if updated_state != state or prev_node_name != node_name or exiting_node: + state = updated_state + prev_node_name = node_name + current_graph_state.update(updated_state) + yield self._emit_state_sync_event( + thread_id=thread_id, + run_id=run_id, + node_name=node_name, + state=state, + running=True, + active=not exiting_node + ) + "\n" + + yield langchain_dumps(event) + "\n" + except Exception as error: + # Emit error information through streaming protocol before terminating + # This preserves the semantic error details that would otherwise be lost + error_message = str(error) + error_type = type(error).__name__ + + # Extract additional error details for common error types + error_details = { + "message": error_message, + "type": error_type, + "agent_name": self.name, + } + + # Add specific details for OpenAI errors + if hasattr(error, 'status_code'): + error_details["status_code"] = error.status_code + if hasattr(error, 'response') and hasattr(error.response, 'json'): + try: + error_details["response_data"] = error.response.json() + except: + pass + + # Emit error events in both formats to support both LangGraph Platform and direct LangGraph modes + + # Format for LangGraph Platform (remote-lg-action.ts) + yield langchain_dumps({ + "event": "error", + "data": { + "message": f"{error_type}: {error_message}", + "error_details": error_details, + "thread_id": thread_id, + "agent_name": self.name, + "node_name": node_name or "unknown" + } + }) + "\n" + + # Format for direct LangGraph mode (event-source.ts) + yield langchain_dumps({ + "event": "on_copilotkit_error", + "data": { + "error": error_details, + "thread_id": thread_id, + "agent_name": self.name, + "node_name": node_name or "unknown" + } + }) + "\n" + + # Re-raise the exception to maintain normal error handling flow + raise + + state = await self.graph.aget_state(config) + tasks = state.tasks + interrupts = tasks[0].interrupts if tasks and len(tasks) > 0 else None + if interrupts: + # node_name is already set earlier from the interrupt origin + pass + elif "writes" in state.metadata and state.metadata["writes"]: + node_name = list(state.metadata["writes"].keys())[0] + elif hasattr(state, "next") and state.next and state.next[0]: + node_name = state.next[0] + else: + node_name = "__end__" + is_end_node = state.next == () and not interrupts + + yield self._emit_state_sync_event( + thread_id=thread_id, + run_id=run_id, + node_name=cast(str, node_name) if not is_end_node else "__end__", + state=state.values, + running=not should_exit, + # at this point, the node is ending so we set active to false + active=False, + # sync messages at the end of the run + include_messages=True + ) + "\n" + + def _emit_state_sync_event( + self, + *, + thread_id: str, + run_id: str, + node_name: str, + state: dict, + running: bool, + active: bool, + include_messages: bool = False + ): + # First handle messages as before + if not include_messages: + state = { + k: v for k, v in state.items() if k != "messages" + } + else: + state = { + **state, + "messages": langchain_messages_to_copilotkit(state.get("messages", [])) + } + + # Filter by schema keys if available + state = self.filter_state_on_schema_keys(state, 'output') + + return langchain_dumps({ + "event": "on_copilotkit_state_sync", + "thread_id": thread_id, + "run_id": run_id, + "agent_name": self.name, + "node_name": node_name, + "active": active, + "state": state, + "running": running, + "role": "assistant" + }) + + async def get_state( + self, + *, + thread_id: str, + ): + if not thread_id: + return { + "threadId": "", + "threadExists": False, + "state": {}, + "messages": [] + } + + config = ensure_config(cast(Any, self.langgraph_config.copy()) if self.langgraph_config else {}) # pylint: disable=line-too-long + config["configurable"] = config.get("configurable", {}) + config["configurable"]["thread_id"] = thread_id + + if self.thread_state.get(thread_id, None) is None: + self.thread_state[thread_id] = {**(await self.graph.aget_state(config)).values} + + state = self.thread_state[thread_id] + if state == {}: + return { + "threadId": thread_id or "", + "threadExists": False, + "state": {}, + "messages": [] + } + + messages = langchain_messages_to_copilotkit(state.get("messages", [])) + state_copy = state.copy() + state_copy.pop("messages", None) + + return { + "threadId": thread_id, + "threadExists": True, + "state": state_copy, + "messages": messages + } + + def dict_repr(self): + super_repr = super().dict_repr() + return { + **super_repr, + 'type': 'langgraph' + } + + def get_schema_keys(self, config): + CONSTANT_KEYS = ['copilotkit', 'messages'] + CONSTANT_CONFIG_KEYS = ['checkpoint_id', 'checkpoint_ns', 'thread_id'] + try: + input_schema = self.graph.get_input_jsonschema(config) + output_schema = self.graph.get_output_jsonschema(config) + input_schema_keys = list(input_schema["properties"].keys()) + output_schema_keys = list(output_schema["properties"].keys()) + + try: + schema_dict = self.graph.config_schema().schema() + configurable_schema = schema_dict["$defs"]["Configurable"] + config_schema_keys = list(configurable_schema["properties"].keys()) + + # If only constant keys are present, it means no schema was passed, we allow everything + if set(config_schema_keys) == set(CONSTANT_CONFIG_KEYS): + config_schema_keys = None + except: + config_schema_keys = None + + # We add "copilotkit" and "messages" as they are always sent and received. + for key in CONSTANT_KEYS: + if key not in input_schema_keys: + input_schema_keys.append(key) + if key not in output_schema_keys: + output_schema_keys.append(key) + + return input_schema_keys, output_schema_keys, config_schema_keys + except Exception: + return None + + def filter_state_on_schema_keys(self, state, schema_type: Literal["input", "output"]): + try: + schema_keys_name = f"{schema_type}_schema_keys" + if hasattr(self, schema_keys_name) and getattr(self, schema_keys_name): + return filter_by_schema_keys(state, getattr(self, schema_keys_name)) + except Exception: + return state + + def get_interrupt_event(self, value): + if not isinstance(value, str) and "__copilotkit_interrupt_value__" in value: + ev_value = value["__copilotkit_interrupt_value__"] + return langchain_dumps({ + "event": "on_copilotkit_interrupt", + "data": { "value": ev_value if isinstance(ev_value, str) else json.dumps(ev_value), "messages": langchain_messages_to_copilotkit(value["__copilotkit_messages__"]) } + }) + "\n" + else: + return langchain_dumps({ + "event": "on_interrupt", + "value": value if isinstance(value, str) else json.dumps(value) + }) + "\n" + + async def get_checkpoint_before_message(self, message_id: str, thread_id: str): + if not thread_id: + raise ValueError("Missing thread_id in config") + + history_list = [] + async for snapshot in self.graph.aget_state_history({"configurable": {"thread_id": thread_id}}): + history_list.append(snapshot) + + history_list.reverse() + for idx, snapshot in enumerate(history_list): + messages = snapshot.values.get("messages", []) + if any(getattr(m, "id", None) == message_id for m in messages): + if idx == 0: + # No snapshot before this + # Return synthetic "empty before" version + empty_snapshot = snapshot + empty_snapshot.values["messages"] = [] + return empty_snapshot + return history_list[idx - 1] # return one snapshot *before* the one that includes the message + + raise ValueError("Message ID not found in history") + +class _StreamingStateExtractor: + def __init__(self, emit_intermediate_state: List[dict]): + self.emit_intermediate_state = emit_intermediate_state + self.tool_call_buffer = {} + self.current_tool_call = None + + self.previously_parsable_state = {} + + def buffer_tool_calls(self, event: Any): + """Buffer the tool calls""" + if len(event["data"]["chunk"].tool_call_chunks) > 0: + chunk = event["data"]["chunk"].tool_call_chunks[0] + if chunk["name"] is not None: + self.current_tool_call = chunk["name"] + self.tool_call_buffer[self.current_tool_call] = chunk["args"] + elif self.current_tool_call is not None: + self.tool_call_buffer[self.current_tool_call] = ( + self.tool_call_buffer[self.current_tool_call] + chunk["args"] + ) + + def get_emit_state_config(self, current_tool_name): + """Get the emit state config""" + + for config in self.emit_intermediate_state: + state_key = config.get("state_key") + tool = config.get("tool") + tool_argument = config.get("tool_argument") + + if current_tool_name == tool: + return (tool_argument, state_key) + + return (None, None) + + + def extract_state(self): + """Extract the streaming state""" + parser = JSONParser() + + state = {} + + for key, value in self.tool_call_buffer.items(): + argument_name, state_key = self.get_emit_state_config(key) + + if state_key is None: + continue + + try: + parsed_value = parser.parse(value) + except Exception as _exc: # pylint: disable=broad-except + if key in self.previously_parsable_state: + parsed_value = self.previously_parsable_state[key] + else: + continue + + self.previously_parsable_state[key] = parsed_value + + if argument_name is None: + state[state_key] = parsed_value + else: + state[state_key] = parsed_value.get(argument_name) + + return state diff --git a/copilotkit/langgraph_agui_agent.py b/copilotkit/langgraph_agui_agent.py new file mode 100644 index 0000000..f878261 --- /dev/null +++ b/copilotkit/langgraph_agui_agent.py @@ -0,0 +1,212 @@ +import json +from typing import Dict, Any, List, Optional, Union, AsyncGenerator +from enum import Enum +from ag_ui_langgraph import LangGraphAgent +from ag_ui.core import ( + EventType, + CustomEvent, + TextMessageStartEvent, + TextMessageContentEvent, + TextMessageEndEvent, + ToolCallStartEvent, + ToolCallArgsEvent, + ToolCallEndEvent, + StateSnapshotEvent, +) +from langgraph.graph.state import CompiledStateGraph +from langchain_core.runnables import RunnableConfig + +try: + from langchain.schema import BaseMessage +except ImportError: + # Langchain >= 1.0.0 + from langchain_core.messages import BaseMessage + + +class CustomEventNames(Enum): + """Custom event names for CopilotKit""" + ManuallyEmitMessage = "copilotkit_manually_emit_message" + ManuallyEmitToolCall = "copilotkit_manually_emit_tool_call" + ManuallyEmitState = "copilotkit_manually_emit_intermediate_state" + + +class LangGraphEventTypes(Enum): + """LangGraph event types""" + OnChatModelStream = "on_chat_model_stream" + OnCustomEvent = "on_custom_event" + + +class PredictStateTool: + def __init__(self, tool: str, state_key: str, tool_argument: str): + self.tool = tool + self.state_key = state_key + self.tool_argument = tool_argument + + +State = Dict[str, Any] +SchemaKeys = Dict[str, List[str]] +TextMessageEvents = Union[TextMessageStartEvent, TextMessageContentEvent, TextMessageEndEvent] +ToolCallEvents = Union[ToolCallStartEvent, ToolCallArgsEvent, ToolCallEndEvent] + + +class LangGraphAGUIAgent(LangGraphAgent): + def __init__(self, *, name: str, graph: CompiledStateGraph, description: Optional[str] = None, config: Union[Optional[RunnableConfig], dict] = None): + super().__init__(name=name, graph=graph, description=description, config=config) + self.constant_schema_keys = self.constant_schema_keys + ["copilotkit"] + + def _dispatch_event(self, event) -> str: + """Override the dispatch event method to handle custom CopilotKit events and filtering. + + Note: Returns None for filtered events (which violates the str return type annotation, + but the base class also violates it by returning event objects). The None values are + filtered out in run() before reaching the encoder. + """ + + if event.type == EventType.CUSTOM: + custom_event = event + + if custom_event.name == CustomEventNames.ManuallyEmitMessage.value: + # Emit the message events + super()._dispatch_event( + TextMessageStartEvent( + type=EventType.TEXT_MESSAGE_START, + role="assistant", + message_id=custom_event.value["message_id"], + raw_event=event, + ) + ) + super()._dispatch_event( + TextMessageContentEvent( + type=EventType.TEXT_MESSAGE_CONTENT, + message_id=custom_event.value["message_id"], + delta=custom_event.value["message"], + raw_event=event, + ) + ) + super()._dispatch_event( + TextMessageEndEvent( + type=EventType.TEXT_MESSAGE_END, + message_id=custom_event.value["message_id"], + raw_event=event, + ) + ) + return super()._dispatch_event(event) + + if custom_event.name == CustomEventNames.ManuallyEmitToolCall.value: + # Emit the tool call events + super()._dispatch_event( + ToolCallStartEvent( + type=EventType.TOOL_CALL_START, + tool_call_id=custom_event.value["id"], + tool_call_name=custom_event.value["name"], + parent_message_id=custom_event.value["id"], + raw_event=event, + ) + ) + super()._dispatch_event( + ToolCallArgsEvent( + type=EventType.TOOL_CALL_ARGS, + tool_call_id=custom_event.value["id"], + delta=custom_event.value["args"] if isinstance(custom_event.value["args"], str) else json.dumps( + custom_event.value["args"]), + raw_event=event, + ) + ) + super()._dispatch_event( + ToolCallEndEvent( + type=EventType.TOOL_CALL_END, + tool_call_id=custom_event.value["id"], + raw_event=event, + ) + ) + return super()._dispatch_event(event) + + if custom_event.name == CustomEventNames.ManuallyEmitState.value: + self.active_run["manually_emitted_state"] = custom_event.value + return super()._dispatch_event( + StateSnapshotEvent( + type=EventType.STATE_SNAPSHOT, + snapshot=self.get_state_snapshot(self.active_run["manually_emitted_state"]), + raw_event=event, + ) + ) + + if custom_event.name == "copilotkit_exit": + return super()._dispatch_event( + CustomEvent( + type=EventType.CUSTOM, + name="Exit", + value=True, + raw_event=event, + ) + ) + + # Handle filtering based on metadata for text messages and tool calls + raw_event = getattr(event, 'raw_event', None) + if raw_event: + is_message_event = event.type in [ + EventType.TEXT_MESSAGE_START, + EventType.TEXT_MESSAGE_CONTENT, + EventType.TEXT_MESSAGE_END + ] + is_tool_event = event.type in [ + EventType.TOOL_CALL_START, + EventType.TOOL_CALL_ARGS, + EventType.TOOL_CALL_END + ] + + # Handle both dict and object cases for raw_event + # See: https://github.com/CopilotKit/CopilotKit/issues/2066 + metadata = (raw_event.get('metadata', {}) if isinstance(raw_event, dict) + else getattr(raw_event, 'metadata', {})) or {} + + if "copilotkit:emit-tool-calls" in metadata: + if metadata["copilotkit:emit-tool-calls"] is False and is_tool_event: + return None # Don't dispatch this event + + if "copilotkit:emit-messages" in metadata: + if metadata["copilotkit:emit-messages"] is False and is_message_event: + return None # Don't dispatch this event + + return super()._dispatch_event(event) + + async def run(self, input): + """Override run to filter out None events from _dispatch_event filtering.""" + async for event in super().run(input): + if event is not None: + yield event + + async def _handle_single_event(self, event: Any, state: State) -> AsyncGenerator[str, None]: + """Override to add custom event processing for PredictState events""" + + # First, check if this is a raw event that should generate a PredictState event + if event.get("event") == LangGraphEventTypes.OnChatModelStream.value: + predict_state_metadata = event.get("metadata", {}).get("copilotkit:emit-intermediate-state", None) + if predict_state_metadata is not None: + event["metadata"]['predict_state'] = predict_state_metadata + + # Call the parent method to handle all other events + async for event_str in super()._handle_single_event(event, state): + yield event_str + + def langgraph_default_merge_state(self, state: State, messages: List[BaseMessage], input: Any) -> State: + """Override to add CopilotKit actions to the state""" + merged_state = super().langgraph_default_merge_state(state, messages, input) + # Extract tools from the merged state and add them as CopilotKit actions + agui_properties = merged_state.get('ag-ui', {}) or merged_state + + return { + **merged_state, + 'copilotkit': { + 'actions': agui_properties.get('tools', []), + 'context': agui_properties.get('context', []) + }, + } + + def dict_repr(self): + """Return dictionary representation of the agent""" + super_repr = super().dict_repr() + return { + **super_repr, + 'type': 'langgraph_agui' + } diff --git a/copilotkit/logging.py b/copilotkit/logging.py new file mode 100644 index 0000000..2deaefb --- /dev/null +++ b/copilotkit/logging.py @@ -0,0 +1,25 @@ +""" +Logging setup for CopilotKit. +""" + +import logging +import os +import sys + +def get_logger(name: str): + """ + Get a logger with the given name. + """ + logger = logging.getLogger(name) + log_level = os.getenv('LOG_LEVEL') + if log_level: + logger.setLevel(log_level.upper()) + return logger + +def bold(text: str) -> str: + """ + Bold the given text. + """ + if hasattr(sys.stdout, 'isatty') and sys.stdout.isatty(): + return f"\033[1m{text}\033[0m" + return text diff --git a/copilotkit/parameter.py b/copilotkit/parameter.py new file mode 100644 index 0000000..6e8ee26 --- /dev/null +++ b/copilotkit/parameter.py @@ -0,0 +1,53 @@ +"""Parameter classes for CopilotKit""" + +from typing import TypedDict, Optional, Literal, List, Union, cast, Any +from typing_extensions import NotRequired + +class SimpleParameter(TypedDict): + """Simple parameter class""" + name: str + description: NotRequired[str] + required: NotRequired[bool] + type: NotRequired[Literal[ + "number", + "boolean", + "number[]", + "boolean[]" + ]] + +class ObjectParameter(TypedDict): + """Object parameter class""" + name: str + description: NotRequired[str] + required: NotRequired[bool] + type: Literal["object", "object[]"] + attributes: List['Parameter'] + +class StringParameter(TypedDict): + """String parameter class""" + name: str + description: NotRequired[str] + required: NotRequired[bool] + type: Literal["string", "string[]"] + enum: NotRequired[List[str]] + +Parameter = Union[SimpleParameter, ObjectParameter, StringParameter] + +def normalize_parameters(parameters: Optional[List[Parameter]]) -> List[Parameter]: + """Normalize the parameters to ensure they have the correct type and format.""" + if parameters is None: + return [] + return [_normalize_parameter(parameter) for parameter in parameters] + +def _normalize_parameter(parameter: Parameter) -> Parameter: + """Normalize a parameter to ensure it has the correct type and format.""" + if not "type" in parameter: + cast(Any, parameter)['type'] = 'string' + if not 'required' in parameter: + parameter['required'] = True + if not 'description' in parameter: + parameter['description'] = '' + + if 'type' in parameter and (parameter['type'] == 'object' or parameter['type'] == 'object[]'): + cast(Any, parameter)['attributes'] = normalize_parameters(parameter.get('attributes')) + return parameter diff --git a/copilotkit/protocol.py b/copilotkit/protocol.py new file mode 100644 index 0000000..4dae786 --- /dev/null +++ b/copilotkit/protocol.py @@ -0,0 +1,268 @@ +""" +CopilotKit Protocol +""" + +import json +from enum import Enum +from typing import Union, Optional +from typing_extensions import TypedDict, Literal, Any, Dict + +class RuntimeEventTypes(Enum): + """CopilotKit Runtime Event Types""" + TEXT_MESSAGE_START = "TextMessageStart" + TEXT_MESSAGE_CONTENT = "TextMessageContent" + TEXT_MESSAGE_END = "TextMessageEnd" + ACTION_EXECUTION_START = "ActionExecutionStart" + ACTION_EXECUTION_ARGS = "ActionExecutionArgs" + ACTION_EXECUTION_END = "ActionExecutionEnd" + ACTION_EXECUTION_RESULT = "ActionExecutionResult" + AGENT_STATE_MESSAGE = "AgentStateMessage" + META_EVENT = "MetaEvent" + RUN_STARTED = "RunStarted" + RUN_FINISHED = "RunFinished" + RUN_ERROR = "RunError" + NODE_STARTED = "NodeStarted" + NODE_FINISHED = "NodeFinished" + +class RuntimeMetaEventName(Enum): + """Runtime Meta Event Name""" + LANG_GRAPH_INTERRUPT_EVENT = "LangGraphInterruptEvent" + PREDICT_STATE = "PredictState" + EXIT = "Exit" + + +class TextMessageStart(TypedDict): + """Text Message Start Event""" + type: Literal[RuntimeEventTypes.TEXT_MESSAGE_START] + messageId: str + parentMessageId: Optional[str] + +class TextMessageContent(TypedDict): + """Text Message Content Event""" + type: Literal[RuntimeEventTypes.TEXT_MESSAGE_CONTENT] + messageId: str + content: str + +class TextMessageEnd(TypedDict): + """Text Message End Event""" + type: Literal[RuntimeEventTypes.TEXT_MESSAGE_END] + messageId: str + +class ActionExecutionStart(TypedDict): + """Action Execution Start Event""" + type: Literal[RuntimeEventTypes.ACTION_EXECUTION_START] + actionExecutionId: str + actionName: str + parentMessageId: Optional[str] + +class ActionExecutionArgs(TypedDict): + """Action Execution Args Event""" + type: Literal[RuntimeEventTypes.ACTION_EXECUTION_ARGS] + actionExecutionId: str + args: str + +class ActionExecutionEnd(TypedDict): + """Action Execution End Event""" + type: Literal[RuntimeEventTypes.ACTION_EXECUTION_END] + actionExecutionId: str + +class ActionExecutionResult(TypedDict): + """Action Execution Result Event""" + type: Literal[RuntimeEventTypes.ACTION_EXECUTION_RESULT] + actionName: str + actionExecutionId: str + result: str + +class AgentStateMessage(TypedDict): + """Agent State Message Event""" + type: Literal[RuntimeEventTypes.AGENT_STATE_MESSAGE] + threadId: str + agentName: str + nodeName: str + runId: str + active: bool + role: str + state: str + running: bool + +class MetaEvent(TypedDict): + """Meta Event""" + type: Literal[RuntimeEventTypes.META_EVENT] + name: RuntimeMetaEventName + value: Any + +class RunStarted(TypedDict): + """Run Started Event""" + type: Literal[RuntimeEventTypes.RUN_STARTED] + state: Dict[str, Any] + +class RunFinished(TypedDict): + """Run Finished Event""" + type: Literal[RuntimeEventTypes.RUN_FINISHED] + state: Dict[str, Any] + +class RunError(TypedDict): + """Run Error Event""" + type: Literal[RuntimeEventTypes.RUN_ERROR] + error: Any + +class NodeStarted(TypedDict): + """Node Started Event""" + type: Literal[RuntimeEventTypes.NODE_STARTED] + node_name: str + state: Dict[str, Any] + +class NodeFinished(TypedDict): + """Node Finished Event""" + type: Literal[RuntimeEventTypes.NODE_FINISHED] + node_name: str + state: Dict[str, Any] + +RuntimeProtocolEvent = Union[ + TextMessageStart, + TextMessageContent, + TextMessageEnd, + ActionExecutionStart, + ActionExecutionArgs, + ActionExecutionEnd, + ActionExecutionResult, + AgentStateMessage, + MetaEvent +] + +RuntimeLifecycleEvent = Union[ + RunStarted, + RunFinished, + RunError, + NodeStarted, + NodeFinished, +] + +RuntimeEvent = Union[ + RuntimeProtocolEvent, + RuntimeLifecycleEvent, +] + + +class PredictStateConfig(TypedDict): + """ + Predict State Config + """ + tool_name: str + tool_argument: Optional[str] + +def text_message_start( + *, + message_id: str, + parent_message_id: Optional[str] = None + ) -> TextMessageStart: + """Utility function to create a text message start event""" + return { + "type": RuntimeEventTypes.TEXT_MESSAGE_START, + "messageId": message_id, + "parentMessageId": parent_message_id + } + +def text_message_content(*, message_id: str, content: str) -> TextMessageContent: + """Utility function to create a text message content event""" + return { + "type": RuntimeEventTypes.TEXT_MESSAGE_CONTENT, + "messageId": message_id, + "content": content + } + +def text_message_end(*, message_id: str) -> TextMessageEnd: + """Utility function to create a text message end event""" + return { + "type": RuntimeEventTypes.TEXT_MESSAGE_END, + "messageId": message_id + } + +def action_execution_start( + *, + action_execution_id: str, + action_name: str, + parent_message_id: Optional[str] = None + ) -> ActionExecutionStart: + """Utility function to create an action execution start event""" + return { + "type": RuntimeEventTypes.ACTION_EXECUTION_START, + "actionExecutionId": action_execution_id, + "actionName": action_name, + "parentMessageId": parent_message_id + } + +def action_execution_args(*, action_execution_id: str, args: str) -> ActionExecutionArgs: + """Utility function to create an action execution args event""" + return { + "type": RuntimeEventTypes.ACTION_EXECUTION_ARGS, + "actionExecutionId": action_execution_id, + "args": args + } + +def action_execution_end(*, action_execution_id: str) -> ActionExecutionEnd: + """Utility function to create an action execution end event""" + return { + "type": RuntimeEventTypes.ACTION_EXECUTION_END, + "actionExecutionId": action_execution_id + } + +def action_execution_result( + *, + action_name: str, + action_execution_id: str, + result: str + ) -> ActionExecutionResult: + """Utility function to create an action execution result event""" + return { + "type": RuntimeEventTypes.ACTION_EXECUTION_RESULT, + "actionName": action_name, + "actionExecutionId": action_execution_id, + "result": result + } + +def agent_state_message( # pylint: disable=too-many-arguments + *, + thread_id: str, + agent_name: str, + node_name: str, + run_id: str, + active: bool, + role: str, + state: str, + running: bool + ) -> AgentStateMessage: + """Utility function to create an agent state message event""" + return { + "type": RuntimeEventTypes.AGENT_STATE_MESSAGE, + "threadId": thread_id, + "agentName": agent_name, + "nodeName": node_name, + "runId": run_id, + "active": active, + "role": role, + "state": state, + "running": running + } + +def meta_event(*, name: RuntimeMetaEventName, value: Any) -> MetaEvent: + """Utility function to create a meta event""" + return { + "type": RuntimeEventTypes.META_EVENT, + "name": name, + "value": value + } + +def emit_runtime_events(*events: RuntimeProtocolEvent) -> str: + """Emit a list of runtime events""" + def serialize_event(event): + # Convert enum values to their string representation + if isinstance(event, dict): + return {k: (v.value if isinstance(v, Enum) else v) for k, v in event.items()} + return event + + return "\n".join(json.dumps(serialize_event(event)) for event in events) + "\n" + +def emit_runtime_event(event: RuntimeProtocolEvent) -> str: + """Emit a single runtime event""" + return emit_runtime_events(event) diff --git a/copilotkit/runloop.py b/copilotkit/runloop.py new file mode 100644 index 0000000..d773e43 --- /dev/null +++ b/copilotkit/runloop.py @@ -0,0 +1,350 @@ +""" +CopilotKit Run Loop +""" + +import asyncio +import contextvars +import json +import traceback +from typing import Callable +from pydantic import BaseModel +from typing_extensions import Any, Dict, Optional, List, TypedDict, cast +from partialjson.json_parser import JSONParser as PartialJSONParser + +from .protocol import ( + RuntimeEvent, + RuntimeEventTypes, + RuntimeMetaEventName, + emit_runtime_event, + emit_runtime_events, + agent_state_message, + AgentStateMessage, + PredictStateConfig, + RuntimeProtocolEvent +) + +async def yield_control(): + """ + Yield control to the event loop. + """ + loop = asyncio.get_running_loop() + future = loop.create_future() + loop.call_soon(future.set_result, None) + await future + + +class CopilotKitRunExecution(TypedDict): + """ + CopilotKit Run Execution + """ + thread_id: str + agent_name: str + run_id: str + should_exit: bool + node_name: str + is_finished: bool + predict_state_configuration: Dict[str, PredictStateConfig] + predicted_state: Dict[str, Any] + argument_buffer: str + current_tool_call: Optional[str] + state: Dict[str, Any] + +_CONTEXT_QUEUE = contextvars.ContextVar('queue', default=None) +_CONTEXT_EXECUTION = contextvars.ContextVar('execution', default=None) + +def get_context_queue() -> asyncio.Queue: + """ + Retrieve the queue from this task's context. + """ + q = _CONTEXT_QUEUE.get() + if q is None: + raise RuntimeError("No context queue is set!") + return q + +def set_context_queue(q: asyncio.Queue) -> contextvars.Token: + """ + Set the queue in this task's context. + """ + token = _CONTEXT_QUEUE.set(cast(Any, q)) + return token + +def reset_context_queue(token: contextvars.Token): + """ + Reset the queue in this task's context. + """ + _CONTEXT_QUEUE.reset(token) + +def get_context_execution() -> CopilotKitRunExecution: + """ + Get the execution from this task's context. + """ + return cast(CopilotKitRunExecution, _CONTEXT_EXECUTION.get()) + +def set_context_execution(execution: CopilotKitRunExecution) -> contextvars.Token: + """ + Set the execution in this task's context. + """ + token = _CONTEXT_EXECUTION.set(cast(Any, execution)) + return token + +def reset_context_execution(token: contextvars.Token): + """ + Reset the execution in this task's context. + """ + _CONTEXT_EXECUTION.reset(token) + + +async def queue_put(*events: RuntimeEvent, priority: bool = False): + """ + Put an event in the queue. + """ + if not priority: + # yield control so that priority events can be processed first + await yield_control() + + q = get_context_queue() + for event in events: + await q.put(event) + + # yield control so that the reader can process the event + await yield_control() + + +def _to_dict_if_pydantic(obj): + if isinstance(obj, BaseModel): + return obj.model_dump() + return obj + +def _filter_state( + *, + state: Dict[str, Any], + exclude_keys: Optional[List[str]] = None + ) -> Dict[str, Any]: + """Filter out messages and id from the state""" + state = _to_dict_if_pydantic(state) + exclude_keys = exclude_keys or ["messages", "id"] + return {k: v for k, v in state.items() if k not in exclude_keys} + + +async def copilotkit_run( + fn: Callable, + *, + execution: CopilotKitRunExecution +): + """ + Run a task with a local queue. + """ + local_queue = asyncio.Queue() + token_queue = set_context_queue(local_queue) + token_execution = set_context_execution(execution) + + task = asyncio.create_task( + fn() + ) + try: + while True: + event = await local_queue.get() + local_queue.task_done() + + json_lines = handle_runtime_event( + event=event, + execution=execution + ) + + if json_lines is not None: + yield json_lines + + if execution["is_finished"]: + break + + # return control to the containing run loop to send events + await yield_control() + + await task + + finally: + reset_context_queue(token_queue) + reset_context_execution(token_execution) + +def handle_runtime_event( + *, + event: RuntimeEvent, + execution: CopilotKitRunExecution +) -> Optional[str]: + """ + Handle a runtime event. + """ + + if event["type"] in [ + RuntimeEventTypes.TEXT_MESSAGE_START, + RuntimeEventTypes.TEXT_MESSAGE_CONTENT, + RuntimeEventTypes.TEXT_MESSAGE_END, + RuntimeEventTypes.ACTION_EXECUTION_START, + RuntimeEventTypes.ACTION_EXECUTION_ARGS, + RuntimeEventTypes.ACTION_EXECUTION_END, + RuntimeEventTypes.ACTION_EXECUTION_RESULT, + RuntimeEventTypes.AGENT_STATE_MESSAGE + ]: + events: List[RuntimeProtocolEvent] = [cast(RuntimeProtocolEvent, event)] + if event["type"] in [ + RuntimeEventTypes.ACTION_EXECUTION_START, + RuntimeEventTypes.ACTION_EXECUTION_ARGS + ]: + message = predict_state( + thread_id=execution["thread_id"], + agent_name=execution["agent_name"], + run_id=execution["run_id"], + event=event, + execution=execution, + ) + if message is not None: + events.append(message) + return emit_runtime_events(*events) + + if event["type"] == RuntimeEventTypes.META_EVENT: + if event["name"] == RuntimeMetaEventName.PREDICT_STATE: + execution["predict_state_configuration"] = event["value"] + return None + if event["name"] == RuntimeMetaEventName.EXIT: + execution["should_exit"] = event["value"] + return None + return None + + if event["type"] == RuntimeEventTypes.RUN_STARTED: + execution["state"] = event["state"] + return None + + if event["type"] == RuntimeEventTypes.NODE_STARTED: + execution["node_name"] = event["node_name"] + execution["state"] = event["state"] + + return emit_runtime_event( + agent_state_message( + thread_id=execution["thread_id"], + agent_name=execution["agent_name"], + node_name=execution["node_name"], + run_id=execution["run_id"], + active=True, + role="assistant", + state=json.dumps(_filter_state(state=execution["state"])), + running=True + ) + ) + + if event["type"] == RuntimeEventTypes.NODE_FINISHED: + + # reset the predict state configuration at the end of the method execution + execution["predict_state_configuration"] = {} + execution["current_tool_call"] = None + execution["argument_buffer"] = "" + execution["predicted_state"] = {} + execution["state"] = event["state"] + + return emit_runtime_event( + agent_state_message( + thread_id=execution["thread_id"], + agent_name=execution["agent_name"], + node_name=execution["node_name"], + run_id=execution["run_id"], + active=False, + role="assistant", + state=json.dumps(_filter_state(state=execution["state"])), + running=True + ) + ) + + if event["type"] == RuntimeEventTypes.RUN_FINISHED: + execution["is_finished"] = True + return None + + if event["type"] == RuntimeEventTypes.RUN_ERROR: + print("Flow execution error", flush=True) + error_info = event["error"] + + if isinstance(error_info, Exception): + # If it's an exception, print the traceback + print("Exception occurred:", flush=True) + print( + ''.join( + traceback.format_exception( + None, + error_info, + error_info.__traceback__ + ) + ), + flush=True + ) + else: + # Otherwise, assume it's a string and print it + print(error_info, flush=True) + + execution["is_finished"] = True + return None + +def predict_state( + *, + thread_id: str, + agent_name: str, + run_id: str, + event: Any, + execution: CopilotKitRunExecution, +) -> Optional[AgentStateMessage]: + """Predict the state""" + + if event["type"] == RuntimeEventTypes.ACTION_EXECUTION_START: + execution["current_tool_call"] = event["actionName"] + execution["argument_buffer"] = "" + elif event["type"] == RuntimeEventTypes.ACTION_EXECUTION_ARGS: + execution["argument_buffer"] += event["args"] + + tool_names = [ + config.get("tool_name") + for config in execution["predict_state_configuration"].values() + ] + + if execution["current_tool_call"] not in tool_names: + return None + + current_arguments = {} + try: + current_arguments = PartialJSONParser().parse(execution["argument_buffer"]) + except: # pylint: disable=bare-except + return None + + emit_update = False + for k, v in execution["predict_state_configuration"].items(): + if v["tool_name"] == execution["current_tool_call"]: + tool_argument = v.get("tool_argument") + if tool_argument is not None: + argument_value = current_arguments.get(tool_argument) + if argument_value is not None: + execution["predicted_state"][k] = argument_value + emit_update = True + else: + execution["predicted_state"][k] = current_arguments + emit_update = True + + if emit_update: + return agent_state_message( + thread_id=thread_id, + agent_name=agent_name, + node_name=execution["node_name"], + run_id=run_id, + active=True, + role="assistant", + state=json.dumps( + _filter_state( + state={ + **( + execution["state"].model_dump() + if isinstance(execution["state"], BaseModel) + else execution["state"] + ), + **execution["predicted_state"] + } + ) + ), + running=True + ) + + return None diff --git a/copilotkit/sdk.py b/copilotkit/sdk.py new file mode 100644 index 0000000..3cf77ca --- /dev/null +++ b/copilotkit/sdk.py @@ -0,0 +1,409 @@ +"""CopilotKit SDK""" + +import warnings +from importlib import metadata + +from pprint import pformat +from typing import List, Callable, Union, Optional, Any, Coroutine +from typing_extensions import TypedDict, Tuple, cast, Mapping +from .agent import Agent, AgentDict +from .action import Action, ActionDict, ActionResultDict +from .types import Message, MetaEvent +from .exc import ( + ActionNotFoundException, + AgentNotFoundException, + ActionExecutionException, + AgentExecutionException +) +from .logging import get_logger, bold + + +try: + __version__ = metadata.version(cast(str, __package__)) +except metadata.PackageNotFoundError: + # Case where package metadata is not available. + __version__ = "" +del metadata # optional, avoids polluting the results of dir(__package__) + +COPILOTKIT_SDK_VERSION = __version__ + +logger = get_logger(__name__) + +class InfoDict(TypedDict): + """ + Info dictionary + """ + sdkVersion: str + actions: List[ActionDict] + agents: List[AgentDict] + +class CopilotKitContext(TypedDict): + """ + CopilotKit Context + + Parameters + ---------- + properties : Any + The properties provided to the frontend via `` + frontend_url : Optional[str] + The current URL of the frontend + headers : Mapping[str, str] + The headers of the request + """ + properties: Any + frontend_url: Optional[str] + headers: Mapping[str, str] + +# Alias for backwards compatibility +CopilotKitSDKContext = CopilotKitContext + + +class CopilotKitRemoteEndpoint: + """ + CopilotKitRemoteEndpoint lets you connect actions and agents written in Python to your + CopilotKit application. + + To install CopilotKit for Python, run: + + ```bash + pip install copilotkit + # or to include crewai + pip install copilotkit[crewai] + ``` + + ## Adding actions + + In this example, we provide a simple action to the Copilot: + + ```python + from copilotkit import CopilotKitRemoteEndpoint, Action + + sdk = CopilotKitRemoteEndpoint( + actions=[ + Action( + name="greet_user", + handler=greet_user_handler, + description="Greet the user", + parameters=[ + { + "name": "name", + "type": "string", + "description": "The name of the user" + } + ] + ) + ] + ) + ``` + + You can also dynamically build actions by providing a callable that returns a list of actions. + In this example, we use "name" from the `properties` object to parameterize the action handler. + + ```python + from copilotkit import CopilotKitRemoteEndpoint, Action + + sdk = CopilotKitRemoteEndpoint( + actions=lambda context: [ + Action( + name="greet_user", + handler=make_greet_user_handler(context["properties"]["name"]), + description="Greet the user" + ) + ] + ) + ``` + + Using the same approach, you can restrict the actions available to the Copilot: + + ```python + from copilotkit import CopilotKitRemoteEndpoint, Action + + sdk = CopilotKitRemoteEndpoint( + actions=lambda context: ( + [action_a, action_b] if is_admin(context["properties"]["token"]) else [action_a] + ) + ) + ``` + + ## Adding agents + + Serving agents works in a similar way to serving actions: + + ```python + from copilotkit import CopilotKitRemoteEndpoint, LangGraphAgent + from my_agent.agent import graph + + sdk = CopilotKitRemoteEndpoint( + agents=[ + LangGraphAgent( + name="email_agent", + description="This agent sends emails", + graph=graph, + ) + ] + ) + ``` + + To dynamically build agents, provide a callable that returns a list of agents: + + ```python + from copilotkit import CopilotKitRemoteEndpoint, LangGraphAgent + from my_agent.agent import graph + + sdk = CopilotKitRemoteEndpoint( + agents=lambda context: [ + LangGraphAgent( + name="email_agent", + description="This agent sends emails", + graph=graph, + langgraph_config={ + "token": context["properties"]["token"] + } + ) + ] + ) + ``` + + To restrict the agents available to the Copilot, simply return a different list of agents based on the `context`: + + ```python + from copilotkit import CopilotKitRemoteEndpoint + from my_agents import agent_a, agent_b, is_admin + + sdk = CopilotKitRemoteEndpoint( + agents=lambda context: ( + [agent_a, agent_b] if is_admin(context["properties"]["token"]) else [agent_a] + ) + ) + ``` + + ## Serving the CopilotKit SDK + + To serve the CopilotKit SDK, you can use the `add_fastapi_endpoint` function from the `copilotkit.integrations.fastapi` module: + + ```python + from copilotkit.integrations.fastapi import add_fastapi_endpoint + from fastapi import FastAPI + + app = FastAPI() + sdk = CopilotKitRemoteEndpoint(...) + add_fastapi_endpoint(app, sdk, "/copilotkit") + + def main(): + uvicorn.run( + "your_package:app", + host="0.0.0.0", + port=8000, + reload=True, + ) + + ``` + + Parameters + ---------- + actions : Optional[Union[List[Action], Callable[[CopilotKitContext], List[Action]]]] + The actions to make available to the Copilot. + agents : Optional[Union[List[Agent], Callable[[CopilotKitContext], List[Agent]]]] + The agents to make available to the Copilot. + """ + + def __init__( + self, + *, + actions: Optional[ + Union[ + List[Action], + Callable[[CopilotKitContext], List[Action]] + ] + ] = None, + agents: Optional[ + Union[ + List[Agent], + Callable[[CopilotKitContext], List[Agent]] + ] + ] = None, + ): + self.agents = agents or [] + self.actions = actions or [] + + if isinstance(agents, list): + from .langgraph_agent import LangGraphAgent + for agent in agents: + if isinstance(agent, LangGraphAgent): + raise ValueError( + "LangGraphAgent should be instantiated using LangGraphAGUIAgent. Refer to https://docs.copilotkit.ai/langgraph for more information.") + + + def info( + self, + *, + context: CopilotKitContext + ) -> InfoDict: + """ + Returns information about available actions and agents + """ + + actions = self.actions(context) if callable(self.actions) else self.actions + agents = self.agents(context) if callable(self.agents) else self.agents + + actions_list = [action.dict_repr() for action in actions] + agents_list = [agent.dict_repr() for agent in agents] + + self._log_request_info( + title="Handling info request:", + data=[ + ("Context", context), + ("Actions", actions_list), + ("Agents", agents_list), + ] + ) + + return { + "actions": actions_list, + "agents": agents_list, + "sdkVersion": COPILOTKIT_SDK_VERSION + } + + def _get_action( + self, + *, + context: CopilotKitContext, + name: str, + ) -> Action: + """ + Get an action by name + """ + actions = self.actions(context) if callable(self.actions) else self.actions + action = next((action for action in actions if action.name == name), None) + if action is None: + raise ActionNotFoundException(name) + return action + + def execute_action( + self, + *, + context: CopilotKitContext, + name: str, + arguments: dict, + ) -> Coroutine[Any, Any, ActionResultDict]: + """ + Execute an action + """ + + action = self._get_action(context=context, name=name) + + self._log_request_info( + title="Handling execute action request:", + data=[ + ("Context", context), + ("Action", action.dict_repr()), + ("Arguments", arguments), + ] + ) + + try: + result = action.execute(arguments=arguments) + return result + except Exception as error: + raise ActionExecutionException(name, error) from error + + def execute_agent( # pylint: disable=too-many-arguments + self, + *, + context: CopilotKitContext, + name: str, + thread_id: str, + state: dict, + config: Optional[dict] = None, + messages: List[Message], + actions: List[ActionDict], + node_name: str, + meta_events: Optional[List[MetaEvent]] = None, + ) -> Any: + """ + Execute an agent + """ + agents = self.agents(context) if callable(self.agents) else self.agents + agent = next((agent for agent in agents if agent.name == name), None) + if agent is None: + raise AgentNotFoundException(name) + + self._log_request_info( + title="Handling execute agent request:", + data=[ + ("Context", context), + ("Agent", agent.dict_repr()), + ("Thread ID", thread_id), + ("Node Name", node_name), + ("State", state), + ("Config", config), + ("Messages", messages), + ("Actions", actions), + ("MetaEvents", meta_events), + ] + ) + + try: + return agent.execute( + thread_id=thread_id, + node_name=node_name, + state=state, + config=config, + messages=messages, + actions=actions, + meta_events=meta_events + ) + except Exception as error: + raise AgentExecutionException(name, error) from error + + async def get_agent_state( + self, + *, + context: CopilotKitContext, + thread_id: str, + name: str, + ): + """ + Get agent state + """ + agents = self.agents(context) if callable(self.agents) else self.agents + agent = next((agent for agent in agents if agent.name == name), None) + if agent is None: + raise AgentNotFoundException(name) + + self._log_request_info( + title="Handling get agent state request:", + data=[ + ("Context", context), + ("Agent", agent.dict_repr()), + ("Thread ID", thread_id), + ] + ) + try: + return await agent.get_state(thread_id=thread_id) + except Exception as error: + raise AgentExecutionException(name, error) from error + + def _log_request_info(self, title: str, data: List[Tuple[str, Any]]): + """ + Log request info + """ + logger.info(bold(title)) + logger.info("--------------------------") + for key, value in data: + logger.info(bold(key+":")) + logger.info(pformat(value)) + logger.info("--------------------------") + +# Alias for backwards compatibility +class CopilotKitSDK(CopilotKitRemoteEndpoint): + """Deprecated: Use CopilotKitRemoteEndpoint instead. This class will be removed in a future version.""" + + def __init__(self, *args, **kwargs): + warnings.warn( + "CopilotKitSDK is deprecated since version 0.1.31. " + "Use CopilotKitRemoteEndpoint instead.", + DeprecationWarning, + stacklevel=2 + ) + super().__init__(*args, **kwargs) diff --git a/copilotkit/types.py b/copilotkit/types.py new file mode 100644 index 0000000..4d09890 --- /dev/null +++ b/copilotkit/types.py @@ -0,0 +1,45 @@ +"""State for CopilotKit""" + +from typing import TypedDict +from enum import Enum +from typing_extensions import NotRequired + +class MessageRole(Enum): + """Message role""" + ASSISTANT = "assistant" + SYSTEM = "system" + USER = "user" + +class Message(TypedDict): + """Message""" + id: str + createdAt: str + +class TextMessage(Message): + """Text message""" + parentMessageId: NotRequired[str] + role: MessageRole + content: str + +class ActionExecutionMessage(Message): + """Action execution message""" + parentMessageId: NotRequired[str] + name: str + arguments: dict + +class ResultMessage(Message): + """Result message""" + actionExecutionId: str + actionName: str + result: str + +class IntermediateStateConfig(TypedDict): + """Intermediate state config""" + state_key: str + tool: str + tool_argument: NotRequired[str] + +class MetaEvent(TypedDict): + """Type definition for meta events""" + name: str + response: NotRequired[str] \ No newline at end of file diff --git a/copilotkit/utils.py b/copilotkit/utils.py new file mode 100644 index 0000000..e123e55 --- /dev/null +++ b/copilotkit/utils.py @@ -0,0 +1,8 @@ +def filter_by_schema_keys(obj, schema): + try: + return { + k: v for k, v in obj.items() + if k in schema or k == "messages" + } + except Exception: + return obj \ No newline at end of file diff --git a/frontend/package-lock.json b/frontend/package-lock.json index 0ff80cb..fdbade4 100644 --- a/frontend/package-lock.json +++ b/frontend/package-lock.json @@ -8,6 +8,8 @@ "name": "fullstack-agentcore-solution-template-frontend", "version": "0.4.0", "dependencies": { + "@copilotkit/react-core": "^1.54.0", + "@copilotkit/react-ui": "^1.54.0", 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"https://opencollective.com/unified" + } + }, "node_modules/unist-util-stringify-position": { "version": "4.0.0", "resolved": "https://registry.npmjs.org/unist-util-stringify-position/-/unist-util-stringify-position-4.0.0.tgz", @@ -15445,6 +19364,12 @@ "url": "https://github.com/sponsors/kettanaito" } }, + "node_modules/untruncate-json": { + "version": "0.0.1", + "resolved": "https://registry.npmjs.org/untruncate-json/-/untruncate-json-0.0.1.tgz", + "integrity": "sha512-4W9enDK4X1y1s2S/Rz7ysw6kDuMS3VmRjMFg7GZrNO+98OSe+x5Lh7PKYoVjy3lW/1wmhs6HW0lusnQRHgMarA==", + "license": "MIT" + }, "node_modules/update-browserslist-db": { "version": "1.2.3", "resolved": "https://registry.npmjs.org/update-browserslist-db/-/update-browserslist-db-1.2.3.tgz", @@ -15497,6 +19422,20 @@ "requires-port": "^1.0.0" } }, + "node_modules/urql": { + "version": "4.2.2", + "resolved": "https://registry.npmjs.org/urql/-/urql-4.2.2.tgz", + "integrity": 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-15569,6 +19517,42 @@ "uuid": "dist/esm/bin/uuid" } }, + "node_modules/uvu": { + "version": "0.5.6", + "resolved": "https://registry.npmjs.org/uvu/-/uvu-0.5.6.tgz", + "integrity": "sha512-+g8ENReyr8YsOc6fv/NVJs2vFdHBnBNdfE49rshrTzDWOlUx4Gq7KOS2GD8eqhy2j+Ejq29+SbKH8yjkAqXqoA==", + "license": "MIT", + "dependencies": { + "dequal": "^2.0.0", + "diff": "^5.0.0", + "kleur": "^4.0.3", + "sade": "^1.7.3" + }, + "bin": { + "uvu": "bin.js" + }, + "engines": { + "node": ">=8" + } + }, + "node_modules/uvu/node_modules/diff": { + "version": "5.2.2", + "resolved": "https://registry.npmjs.org/diff/-/diff-5.2.2.tgz", + "integrity": "sha512-vtcDfH3TOjP8UekytvnHH1o1P4FcUdt4eQ1Y+Abap1tk/OB2MWQvcwS2ClCd1zuIhc3JKOx6p3kod8Vfys3E+A==", + "license": "BSD-3-Clause", + "engines": { + "node": ">=0.3.1" + } + }, + "node_modules/uvu/node_modules/kleur": { + "version": "4.1.5", + "resolved": "https://registry.npmjs.org/kleur/-/kleur-4.1.5.tgz", + "integrity": 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"node_modules/victory-vendor": { + "version": "37.3.6", + "resolved": "https://registry.npmjs.org/victory-vendor/-/victory-vendor-37.3.6.tgz", + "integrity": "sha512-SbPDPdDBYp+5MJHhBCAyI7wKM3d5ivekigc2Dk2s7pgbZ9wIgIBYGVw4zGHBml/qTFbexrofXW6Gu4noGxrOwQ==", + "license": "MIT AND ISC", + "dependencies": { + "@types/d3-array": "^3.0.3", + "@types/d3-ease": "^3.0.0", + "@types/d3-interpolate": "^3.0.1", + "@types/d3-scale": "^4.0.2", + "@types/d3-shape": "^3.1.0", + "@types/d3-time": "^3.0.0", + "@types/d3-timer": "^3.0.0", + "d3-array": "^3.1.6", + "d3-ease": "^3.0.1", + "d3-interpolate": "^3.0.1", + "d3-scale": "^4.0.2", + "d3-shape": "^3.1.0", + "d3-time": "^3.0.0", + "d3-timer": "^3.0.1" + } + }, "node_modules/vite": { "version": "7.3.1", "resolved": "https://registry.npmjs.org/vite/-/vite-7.3.1.tgz", @@ -15760,6 +19780,55 @@ } } }, + "node_modules/vscode-jsonrpc": { + "version": "8.2.0", + "resolved": "https://registry.npmjs.org/vscode-jsonrpc/-/vscode-jsonrpc-8.2.0.tgz", + "integrity": "sha512-C+r0eKJUIfiDIfwJhria30+TYWPtuHJXHtI7J0YlOmKAo7ogxP20T0zxB7HZQIFhIyvoBPwWskjxrvAtfjyZfA==", + "license": "MIT", + "engines": { + "node": ">=14.0.0" + } + }, + "node_modules/vscode-languageserver": { + "version": "9.0.1", + "resolved": "https://registry.npmjs.org/vscode-languageserver/-/vscode-languageserver-9.0.1.tgz", + "integrity": "sha512-woByF3PDpkHFUreUa7Hos7+pUWdeWMXRd26+ZX2A8cFx6v/JPTtd4/uN0/jB6XQHYaOlHbio03NTHCqrgG5n7g==", + "license": "MIT", + "dependencies": { + "vscode-languageserver-protocol": "3.17.5" + }, + "bin": { + "installServerIntoExtension": "bin/installServerIntoExtension" + } + }, + "node_modules/vscode-languageserver-protocol": { + "version": "3.17.5", + "resolved": "https://registry.npmjs.org/vscode-languageserver-protocol/-/vscode-languageserver-protocol-3.17.5.tgz", + "integrity": "sha512-mb1bvRJN8SVznADSGWM9u/b07H7Ecg0I3OgXDuLdn307rl/J3A9YD6/eYOssqhecL27hK1IPZAsaqh00i/Jljg==", + "license": "MIT", + "dependencies": { + "vscode-jsonrpc": "8.2.0", + "vscode-languageserver-types": "3.17.5" + } + }, + "node_modules/vscode-languageserver-textdocument": { + "version": "1.0.12", + "resolved": "https://registry.npmjs.org/vscode-languageserver-textdocument/-/vscode-languageserver-textdocument-1.0.12.tgz", + "integrity": "sha512-cxWNPesCnQCcMPeenjKKsOCKQZ/L6Tv19DTRIGuLWe32lyzWhihGVJ/rcckZXJxfdKCFvRLS3fpBIsV/ZGX4zA==", + "license": "MIT" + }, + "node_modules/vscode-languageserver-types": { + "version": "3.17.5", + "resolved": "https://registry.npmjs.org/vscode-languageserver-types/-/vscode-languageserver-types-3.17.5.tgz", + "integrity": "sha512-Ld1VelNuX9pdF39h2Hgaeb5hEZM2Z3jUrrMgWQAu82jMtZp7p3vJT3BzToKtZI7NgQssZje5o0zryOrhQvzQAg==", + "license": "MIT" + }, + "node_modules/vscode-uri": { + "version": "3.1.0", + "resolved": "https://registry.npmjs.org/vscode-uri/-/vscode-uri-3.1.0.tgz", + "integrity": "sha512-/BpdSx+yCQGnCvecbyXdxHDkuk55/G3xwnC0GqY4gmQ3j+A+g8kzzgB4Nk/SINjqn6+waqw3EgbVF2QKExkRxQ==", + "license": "MIT" + }, "node_modules/w3c-xmlserializer": { "version": "5.0.0", "resolved": "https://registry.npmjs.org/w3c-xmlserializer/-/w3c-xmlserializer-5.0.0.tgz", @@ -15783,6 +19852,16 @@ "defaults": "^1.0.3" } }, + "node_modules/web-namespaces": { + "version": "2.0.1", + "resolved": "https://registry.npmjs.org/web-namespaces/-/web-namespaces-2.0.1.tgz", + "integrity": "sha512-bKr1DkiNa2krS7qxNtdrtHAmzuYGFQLiQ13TsorsdT6ULTkPLKuu5+GsFpDlg6JFjUTwX2DyhMPG2be8uPrqsQ==", + "license": "MIT", + "funding": { + "type": "github", + "url": "https://github.com/sponsors/wooorm" + } + }, "node_modules/web-streams-polyfill": { "version": "3.3.3", "resolved": "https://registry.npmjs.org/web-streams-polyfill/-/web-streams-polyfill-3.3.3.tgz", @@ -15887,6 +19966,12 @@ "node": ">=8" } }, + "node_modules/wonka": { + "version": "6.3.5", + "resolved": "https://registry.npmjs.org/wonka/-/wonka-6.3.5.tgz", + "integrity": "sha512-SSil+ecw6B4/Dm7Pf2sAshKQ5hWFvfyGlfPbEd6A14dOH6VDjrmbY86u6nZvy9omGwwIPFR8V41+of1EezgoUw==", + "license": "MIT" + }, "node_modules/word-wrap": { "version": "1.2.5", "resolved": "https://registry.npmjs.org/word-wrap/-/word-wrap-1.2.5.tgz", @@ -15960,6 +20045,15 @@ "dev": true, "license": "MIT" }, + "node_modules/xtend": { + "version": "4.0.2", + "resolved": "https://registry.npmjs.org/xtend/-/xtend-4.0.2.tgz", + "integrity": "sha512-LKYU1iAXJXUgAXn9URjiu+MWhyUXHsvfp7mcuYm9dSUKK0/CjtrUwFAxD82/mCWbtLsGjFIad0wIsod4zrTAEQ==", + "license": "MIT", + "engines": { + "node": ">=0.4" + } + }, "node_modules/y18n": { "version": "5.0.8", "resolved": "https://registry.npmjs.org/y18n/-/y18n-5.0.8.tgz", @@ -16071,7 +20165,6 @@ "version": "3.25.76", "resolved": "https://registry.npmjs.org/zod/-/zod-3.25.76.tgz", "integrity": "sha512-gzUt/qt81nXsFGKIFcC3YnfEAx5NkunCfnDlvuBSSFS02bcXu4Lmea0AFIUwbLWxWPx3d9p8S5QoaujKcNQxcQ==", - "dev": true, "license": "MIT", "funding": { "url": "https://github.com/sponsors/colinhacks" @@ -16081,7 +20174,6 @@ "version": "3.25.1", "resolved": "https://registry.npmjs.org/zod-to-json-schema/-/zod-to-json-schema-3.25.1.tgz", "integrity": "sha512-pM/SU9d3YAggzi6MtR4h7ruuQlqKtad8e9S0fmxcMi+ueAK5Korys/aWcV9LIIHTVbj01NdzxcnXSN+O74ZIVA==", - "dev": true, "license": "ISC", "peerDependencies": { "zod": "^3.25 || ^4" diff --git a/frontend/package.json b/frontend/package.json index 33d6346..a83e51b 100644 --- a/frontend/package.json +++ b/frontend/package.json @@ -13,6 +13,8 @@ "clean": "rm -rf build/ node_modules/ .vite/" }, "dependencies": { + "@copilotkit/react-core": "^1.54.0", + "@copilotkit/react-ui": "^1.54.0", "@radix-ui/react-alert-dialog": "^1.1.15", "@radix-ui/react-dialog": "^1.1.15", "@radix-ui/react-progress": "^1.1.7", @@ -32,8 +34,10 @@ "react-router-dom": "^6.21.0", "react-spinners": "^0.17.0", "react-syntax-highlighter": "^16.1.0", + "recharts": "^3.8.0", "remark-gfm": "^4.0.1", - "tailwind-merge": "^3.2.0" + "tailwind-merge": "^3.2.0", + "zod": "^3.25.76" }, "devDependencies": { "@eslint/eslintrc": "^3", diff --git a/frontend/src/components/canvas/TodoCanvas.tsx b/frontend/src/components/canvas/TodoCanvas.tsx new file mode 100644 index 0000000..db23b91 --- /dev/null +++ b/frontend/src/components/canvas/TodoCanvas.tsx @@ -0,0 +1,22 @@ +// The canvas is always visible alongside the chat pane (spec: "render chat plus a +// todo canvas in the same page shell"). It shows an empty state when there are no +// todos, and fills in as the agent or user adds items. +import { useAgent } from "@copilotkit/react-core/v2" +import { TodoList } from "./TodoList" +import type { Todo } from "./types" + +export function TodoCanvas() { + const { agent } = useAgent() + + return ( +
+
+ agent.setState({ todos: updatedTodos })} + isAgentRunning={agent.isRunning} + /> +
+
+ ) +} diff --git a/frontend/src/components/canvas/TodoCard.tsx b/frontend/src/components/canvas/TodoCard.tsx new file mode 100644 index 0000000..b444d62 --- /dev/null +++ b/frontend/src/components/canvas/TodoCard.tsx @@ -0,0 +1,190 @@ +import { useState, useRef, useEffect } from "react" +import type { Todo } from "./types" + +interface TodoCardProps { + todo: Todo + onToggleStatus: (todo: Todo) => void + onDelete: (todo: Todo) => void + onUpdateTitle: (todoId: string, title: string) => void + onUpdateDescription: (todoId: string, description: string) => void + onUpdateEmoji: (todoId: string, emoji: string) => void +} + +const EMOJI_OPTIONS = ["✅", "🔥", "🎯", "💡", "🚀"] + +export function TodoCard({ + todo, + onToggleStatus, + onDelete, + onUpdateTitle, + onUpdateDescription, + onUpdateEmoji, +}: TodoCardProps) { + const [editingField, setEditingField] = useState<"title" | "description" | null>(null) + const [editValue, setEditValue] = useState("") + const [showEmojiPicker, setShowEmojiPicker] = useState(false) + const textareaRef = useRef(null) + + const isCompleted = todo.status === "completed" + const truncatedDescription = + todo.description.length > 120 + ? todo.description.slice(0, 120) + "..." + : todo.description + + const startEdit = (field: "title" | "description") => { + setEditingField(field) + setEditValue(field === "title" ? todo.title : todo.description) + } + + const saveEdit = (field: "title" | "description") => { + if (!editValue.trim()) { + // Don't save empty value — keep the editor open + return + } + if (field === "title") onUpdateTitle(todo.id, editValue.trim()) + else onUpdateDescription(todo.id, editValue.trim()) + setEditingField(null) + setEditValue("") + } + + const cancelEdit = () => { + setEditingField(null) + setEditValue("") + } + + useEffect(() => { + if (textareaRef.current) { + textareaRef.current.style.height = "auto" + textareaRef.current.style.height = textareaRef.current.scrollHeight + "px" + } + }, [editValue]) + + return ( +
+ {/* Delete button — visible on hover */} + + + {/* Emoji avatar */} +
+ + {showEmojiPicker && ( +
+ {EMOJI_OPTIONS.map((emoji) => ( + + ))} +
+ )} +
+ + {/* Title + description */} +
+ + +
+ {editingField === "title" ? ( + setEditValue(e.target.value)} + onBlur={() => saveEdit("title")} + onKeyDown={(e) => { + if (e.key === "Enter") saveEdit("title") + if (e.key === "Escape") cancelEdit() + }} + className="w-full text-[16px] font-semibold focus:outline-none bg-transparent text-neutral-900 dark:text-neutral-100 border-b-2 border-neutral-900 dark:border-neutral-100 pb-[2px]" + autoFocus + aria-label="Edit todo title" + /> + ) : ( +
startEdit("title")} + className={`text-[16px] font-semibold cursor-text break-words leading-snug ${ + isCompleted + ? "text-neutral-400 line-through dark:text-neutral-500" + : "text-neutral-900 dark:text-neutral-100" + }`} + > + {todo.title} +
+ )} + + {editingField === "description" ? ( +