Python: Fixed AutoGen migration and tool samples

python/samples/02-agents/providers/ollama/ollama_chat_client.py

@@ -3,7 +3,7 @@
 import asyncio
 from datetime import datetime
 
-from agent_framework import tool
+from agent_framework import Message, tool
 from agent_framework.ollama import OllamaChatClient
 
 """
@@ -29,16 +29,17 @@ def get_time():
 async def main() -> None:
     client = OllamaChatClient()
     message = "What time is it? Use a tool call"
+    messages = [Message(role="user", text=message)]
     stream = False
     print(f"User: {message}")
     if stream:
         print("Assistant: ", end="")
-        async for chunk in client.get_response(message, tools=get_time, stream=True):
+        async for chunk in client.get_response(messages, tools=get_time, stream=True):
             if str(chunk):
                 print(str(chunk), end="")
         print("")
     else:
-        response = await client.get_response(message, tools=get_time)
+        response = await client.get_response(messages, tools=get_time)
         print(f"Assistant: {response}")
 
 

python/samples/02-agents/providers/ollama/ollama_chat_multimodal.py

@@ -40,7 +40,7 @@ async def test_image() -> None:
         ],
     )
 
-    response = await client.get_response(message)
+    response = await client.get_response([message])
     print(f"Image Response: {response}")
 
 

python/samples/02-agents/tools/function_tool_with_approval_and_sessions.py

@@ -5,6 +5,7 @@
 
 from agent_framework import Agent, Message, tool
 from agent_framework.azure import AzureOpenAIChatClient
+from azure.identity import AzureCliCredential
 
 """
 Tool Approvals with Sessions
@@ -29,7 +30,7 @@ async def approval_example() -> None:
     print("=== Tool Approval with Session ===\n")
 
     agent = Agent(
-        client=AzureOpenAIChatClient(),
+        client=AzureOpenAIChatClient(credential=AzureCliCredential()),
         name="CalendarAgent",
         instructions="You are a helpful calendar assistant.",
         tools=[add_to_calendar],
@@ -65,7 +66,7 @@ async def rejection_example() -> None:
     print("=== Tool Rejection with Session ===\n")
 
     agent = Agent(
-        client=AzureOpenAIChatClient(),
+        client=AzureOpenAIChatClient(credential=AzureCliCredential()),
         name="CalendarAgent",
         instructions="You are a helpful calendar assistant.",
         tools=[add_to_calendar],

python/samples/02-agents/tools/function_tool_with_max_exceptions.py

@@ -67,8 +67,6 @@ async def main():
 ============================================================
 Step 1: Call divide(10, 0) - tool raises exception
     Tool failed with error: division by zero
-[2025-10-31 15:39:53 - /Users/edvan/Work/agent-framework/python/packages/core/agent_framework/_tools.py:718 - ERROR]
-Function failed. Error: division by zero
 Response: Division by zero is undefined in standard arithmetic. There is no finite value for 10 ÷ 0.
 
 If you want alternatives:
@@ -80,9 +78,6 @@ async def main():
 Would you like me to show a safe division snippet in a specific language, or compute something else?
 ============================================================
 Step 2: Call divide(100, 0) - will refuse to execute due to max_invocations
-[2025-10-31 15:40:09 - /Users/edvan/Work/agent-framework/python/packages/core/agent_framework/_tools.py:718 - ERROR]
-Function failed. Error: Function 'safe_divide' has reached its maximum exception limit, you tried to use this
-tool too many times and it kept failing.
 Response: Division by zero is undefined in standard arithmetic, so 100 ÷ 0 has no finite value.
 
 If you’re coding and want safe handling, here are quick patterns in a few languages:

python/samples/02-agents/tools/function_tool_with_max_invocations.py

@@ -58,9 +58,6 @@ async def main():
 Response: Five unicorns summoned: 🦄🦄🦄🦄🦄✨
 ============================================================
 Step 2: Call unicorn_function again - will refuse to execute due to max_invocations
-[2025-10-31 15:54:40 - /Users/edvan/Work/agent-framework/python/packages/core/agent_framework/_tools.py:718 - ERROR]
-Function failed. Error: Function 'unicorn_function' has reached its maximum invocation limit,
-you can no longer use this tool.
 Response: The unicorn function has reached its maximum invocation limit. I can’t call it again right now.
 
 Here are 10 unicorns manually: 🦄 🦄 🦄 🦄 🦄 🦄 🦄 🦄 🦄 🦄

python/samples/02-agents/tools/function_tool_with_session_injection.py

@@ -43,8 +43,10 @@ async def main() -> None:
     session = agent.create_session()
 
     # Run the agent with the session
-    print(f"Agent: {await agent.run('What is the weather in London?', session=session)}")
-    print(f"Agent: {await agent.run('What is the weather in Amsterdam?', session=session)}")
+    # Pass session via additional_function_arguments so tools can access it via **kwargs
+    opts = {"additional_function_arguments": {"session": session}}
+    print(f"Agent: {await agent.run('What is the weather in London?', session=session, options=opts)}")
+    print(f"Agent: {await agent.run('What is the weather in Amsterdam?', session=session, options=opts)}")
     print(f"Agent: {await agent.run('What cities did I ask about?', session=session)}")
 
 

python/samples/02-agents/tools/tool_in_class.py

@@ -79,8 +79,6 @@ async def main():
 see more on limits or handle it with a tiny epsilon?
 ============================================================
 Step 2: Call set safe to False and call again
-[2025-10-31 16:17:44 - /Users/edvan/Work/agent-framework/python/packages/core/agent_framework/_tools.py:718 - ERROR]
-Function failed. Error: division by zero
 Response: Division by zero is undefined in standard arithmetic. There is no number y such that 0 × y = 10.
 
 If you’re looking at limits:

python/samples/autogen-migration/orchestrations/01_round_robin_group_chat.py

@@ -17,7 +17,7 @@
 
 import asyncio
 
-from agent_framework import AgentResponseUpdate
+from agent_framework import Message
 
 
 async def run_autogen() -> None:
@@ -91,17 +91,12 @@ async def run_agent_framework() -> None:
 
     # Run the workflow
     print("[Agent Framework] Sequential conversation:")
-    current_executor = None
     async for event in workflow.run("Create a brief summary about electric vehicles", stream=True):
-        if event.type == "output" and isinstance(event.data, AgentResponseUpdate):
-            # Print executor name header when switching to a new agent
-            if current_executor != event.executor_id:
-                if current_executor is not None:
-                    print()  # Newline after previous agent's message
-                print(f"---------- {event.executor_id} ----------")
-                current_executor = event.executor_id
-            print(event.data.text, end="", flush=True)
-    print()  # Final newline after conversation
+        if event.type == "output" and isinstance(event.data, list):
+            for message in event.data:
+                if isinstance(message, Message) and message.role == "assistant" and message.text:
+                    print(f"---------- {message.author_name} ----------")
+                    print(message.text)
 
 
 async def run_agent_framework_with_cycle() -> None:

python/samples/autogen-migration/orchestrations/02_selector_group_chat.py

@@ -17,7 +17,7 @@
 
 import asyncio
 
-from agent_framework import AgentResponseUpdate
+from agent_framework import Message
 
 
 async def run_autogen() -> None:
@@ -106,18 +106,12 @@ async def run_agent_framework() -> None:
 
     # Run with a question that requires expert selection
     print("[Agent Framework] Group chat conversation:")
-    current_executor = None
     async for event in workflow.run("How do I connect to a PostgreSQL database using Python?", stream=True):
-        if event.type == "output" and isinstance(event.data, AgentResponseUpdate):
-            # Print executor name header when switching to a new agent
-            if current_executor != event.executor_id:
-                if current_executor is not None:
-                    print()  # Newline after previous agent's message
-                print(f"---------- {event.executor_id} ----------")
-                current_executor = event.executor_id
-            if event.data:
-                print(event.data.text, end="", flush=True)
-    print()  # Final newline after conversation
+        if event.type == "output" and isinstance(event.data, list):
+            for message in event.data:
+                if isinstance(message, Message) and message.role == "assistant" and message.text:
+                    print(f"---------- {message.author_name} ----------")
+                    print(message.text)
 
 
 async def main() -> None:

python/samples/autogen-migration/orchestrations/03_swarm.py

@@ -18,7 +18,7 @@
 import asyncio
 
 from agent_framework import AgentResponseUpdate, WorkflowEvent
-from orderedmultidict import Any
+from typing import Any
 
 
 async def run_autogen() -> None:
@@ -197,7 +197,9 @@ async def run_agent_framework() -> None:
         print("---------- user ----------")
         print(user_response)
 
-        responses: dict[str, Any] = {req.request_id: user_response for req in pending_requests}  # type: ignore
+        responses: dict[str, Any] = {
+            req.request_id: HandoffAgentUserRequest.create_response(user_response) for req in pending_requests
+        }  # type: ignore
         pending_requests = []
         current_executor = None
         stream_line_open = False

python/samples/autogen-migration/single_agent/03_assistant_agent_thread_and_stream.py

@@ -42,7 +42,7 @@ async def run_autogen() -> None:
 
     print("\n[AutoGen] Streaming response:")
     # Stream response with Console for token streaming
-    await Console(agent.run(task="Count from 1 to 5", stream=True))
+    await Console(agent.run_stream(task="Count from 1 to 5"))
 
 
 async def run_agent_framework() -> None:

python/samples/autogen-migration/single_agent/04_agent_as_tool.py

@@ -53,7 +53,7 @@ async def run_autogen() -> None:
 
     # Run coordinator with streaming - it will delegate to writer
     print("[AutoGen]")
-    await Console(coordinator.run(task="Create a tagline for a coffee shop", stream=True))
+    await Console(coordinator.run_stream(task="Create a tagline for a coffee shop"))
 
 
 async def run_agent_framework() -> None: