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Python: Fixed AutoGen migration and tool samples (#4027)
* Fixed ollama_chat_client sample * Fixed ollama_chat_multimodal sample * Fixed function_tool_with_approval_and_sessions sample * Updated function_tool_with_session_injection sample * Small clean-up * Update 01_round_robin_group_chat.py * Update 02_selector_group_chat.py * Update 03_swarm.py * Update 03_assistant_agent_thread_and_stream.py * Update 04_agent_as_tool.py * Resolved comments
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@@ -3,7 +3,7 @@
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import asyncio
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from datetime import datetime
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from agent_framework import tool
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from agent_framework import Message, tool
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from agent_framework.ollama import OllamaChatClient
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"""
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@@ -29,16 +29,17 @@ def get_time():
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async def main() -> None:
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client = OllamaChatClient()
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message = "What time is it? Use a tool call"
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messages = [Message(role="user", text=message)]
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stream = False
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print(f"User: {message}")
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if stream:
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print("Assistant: ", end="")
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async for chunk in client.get_response(message, tools=get_time, stream=True):
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async for chunk in client.get_response(messages, tools=get_time, stream=True):
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if str(chunk):
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print(str(chunk), end="")
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print("")
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else:
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response = await client.get_response(message, tools=get_time)
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response = await client.get_response(messages, tools=get_time)
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print(f"Assistant: {response}")
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@@ -40,7 +40,7 @@ async def test_image() -> None:
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],
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)
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response = await client.get_response(message)
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response = await client.get_response([message])
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print(f"Image Response: {response}")
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@@ -5,6 +5,7 @@ from typing import Annotated
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from agent_framework import Agent, Message, tool
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from agent_framework.azure import AzureOpenAIChatClient
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from azure.identity import AzureCliCredential
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"""
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Tool Approvals with Sessions
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@@ -29,7 +30,7 @@ async def approval_example() -> None:
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print("=== Tool Approval with Session ===\n")
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agent = Agent(
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client=AzureOpenAIChatClient(),
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client=AzureOpenAIChatClient(credential=AzureCliCredential()),
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name="CalendarAgent",
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instructions="You are a helpful calendar assistant.",
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tools=[add_to_calendar],
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@@ -65,7 +66,7 @@ async def rejection_example() -> None:
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print("=== Tool Rejection with Session ===\n")
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agent = Agent(
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client=AzureOpenAIChatClient(),
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client=AzureOpenAIChatClient(credential=AzureCliCredential()),
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name="CalendarAgent",
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instructions="You are a helpful calendar assistant.",
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tools=[add_to_calendar],
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@@ -67,8 +67,6 @@ Expected Output:
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============================================================
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Step 1: Call divide(10, 0) - tool raises exception
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Tool failed with error: division by zero
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[2025-10-31 15:39:53 - /Users/edvan/Work/agent-framework/python/packages/core/agent_framework/_tools.py:718 - ERROR]
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Function failed. Error: division by zero
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Response: Division by zero is undefined in standard arithmetic. There is no finite value for 10 ÷ 0.
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If you want alternatives:
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@@ -80,9 +78,6 @@ If you want alternatives:
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Would you like me to show a safe division snippet in a specific language, or compute something else?
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============================================================
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Step 2: Call divide(100, 0) - will refuse to execute due to max_invocations
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[2025-10-31 15:40:09 - /Users/edvan/Work/agent-framework/python/packages/core/agent_framework/_tools.py:718 - ERROR]
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Function failed. Error: Function 'safe_divide' has reached its maximum exception limit, you tried to use this
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tool too many times and it kept failing.
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Response: Division by zero is undefined in standard arithmetic, so 100 ÷ 0 has no finite value.
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If you’re coding and want safe handling, here are quick patterns in a few languages:
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@@ -58,9 +58,6 @@ Step 1: Call unicorn_function
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Response: Five unicorns summoned: 🦄🦄🦄🦄🦄✨
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============================================================
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Step 2: Call unicorn_function again - will refuse to execute due to max_invocations
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[2025-10-31 15:54:40 - /Users/edvan/Work/agent-framework/python/packages/core/agent_framework/_tools.py:718 - ERROR]
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Function failed. Error: Function 'unicorn_function' has reached its maximum invocation limit,
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you can no longer use this tool.
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Response: The unicorn function has reached its maximum invocation limit. I can’t call it again right now.
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Here are 10 unicorns manually: 🦄 🦄 🦄 🦄 🦄 🦄 🦄 🦄 🦄 🦄
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@@ -43,8 +43,10 @@ async def main() -> None:
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session = agent.create_session()
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# Run the agent with the session
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print(f"Agent: {await agent.run('What is the weather in London?', session=session)}")
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print(f"Agent: {await agent.run('What is the weather in Amsterdam?', session=session)}")
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# Pass session via additional_function_arguments so tools can access it via **kwargs
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opts = {"additional_function_arguments": {"session": session}}
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print(f"Agent: {await agent.run('What is the weather in London?', session=session, options=opts)}")
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print(f"Agent: {await agent.run('What is the weather in Amsterdam?', session=session, options=opts)}")
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print(f"Agent: {await agent.run('What cities did I ask about?', session=session)}")
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@@ -79,8 +79,6 @@ If you want a numeric surrogate, you can use a small nonzero denominator, e.g.,
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see more on limits or handle it with a tiny epsilon?
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============================================================
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Step 2: Call set safe to False and call again
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[2025-10-31 16:17:44 - /Users/edvan/Work/agent-framework/python/packages/core/agent_framework/_tools.py:718 - ERROR]
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Function failed. Error: division by zero
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Response: Division by zero is undefined in standard arithmetic. There is no number y such that 0 × y = 10.
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If you’re looking at limits:
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@@ -17,7 +17,7 @@ the task in a round-robin fashion.
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import asyncio
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from agent_framework import AgentResponseUpdate
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from agent_framework import Message
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async def run_autogen() -> None:
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@@ -91,17 +91,12 @@ async def run_agent_framework() -> None:
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# Run the workflow
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print("[Agent Framework] Sequential conversation:")
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current_executor = None
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async for event in workflow.run("Create a brief summary about electric vehicles", stream=True):
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if event.type == "output" and isinstance(event.data, AgentResponseUpdate):
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# Print executor name header when switching to a new agent
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if current_executor != event.executor_id:
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if current_executor is not None:
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print() # Newline after previous agent's message
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print(f"---------- {event.executor_id} ----------")
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current_executor = event.executor_id
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print(event.data.text, end="", flush=True)
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print() # Final newline after conversation
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if event.type == "output" and isinstance(event.data, list):
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for message in event.data:
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if isinstance(message, Message) and message.role == "assistant" and message.text:
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print(f"---------- {message.author_name} ----------")
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print(message.text)
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async def run_agent_framework_with_cycle() -> None:
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@@ -17,7 +17,7 @@ which agent should speak next based on the conversation context.
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import asyncio
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from agent_framework import AgentResponseUpdate
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from agent_framework import Message
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async def run_autogen() -> None:
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@@ -106,18 +106,12 @@ async def run_agent_framework() -> None:
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# Run with a question that requires expert selection
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print("[Agent Framework] Group chat conversation:")
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current_executor = None
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async for event in workflow.run("How do I connect to a PostgreSQL database using Python?", stream=True):
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if event.type == "output" and isinstance(event.data, AgentResponseUpdate):
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# Print executor name header when switching to a new agent
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if current_executor != event.executor_id:
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if current_executor is not None:
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print() # Newline after previous agent's message
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print(f"---------- {event.executor_id} ----------")
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current_executor = event.executor_id
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if event.data:
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print(event.data.text, end="", flush=True)
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print() # Final newline after conversation
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if event.type == "output" and isinstance(event.data, list):
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for message in event.data:
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if isinstance(message, Message) and message.role == "assistant" and message.text:
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print(f"---------- {message.author_name} ----------")
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print(message.text)
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async def main() -> None:
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@@ -18,7 +18,7 @@ to other specialized agents based on the task requirements.
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import asyncio
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from agent_framework import AgentResponseUpdate, WorkflowEvent
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from orderedmultidict import Any
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from typing import Any
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async def run_autogen() -> None:
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@@ -197,7 +197,9 @@ async def run_agent_framework() -> None:
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print("---------- user ----------")
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print(user_response)
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responses: dict[str, Any] = {req.request_id: user_response for req in pending_requests} # type: ignore
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responses: dict[str, Any] = {
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req.request_id: HandoffAgentUserRequest.create_response(user_response) for req in pending_requests
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} # type: ignore
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pending_requests = []
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current_executor = None
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stream_line_open = False
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+1
-1
@@ -42,7 +42,7 @@ async def run_autogen() -> None:
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print("\n[AutoGen] Streaming response:")
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# Stream response with Console for token streaming
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await Console(agent.run(task="Count from 1 to 5", stream=True))
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await Console(agent.run_stream(task="Count from 1 to 5"))
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async def run_agent_framework() -> None:
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@@ -53,7 +53,7 @@ async def run_autogen() -> None:
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# Run coordinator with streaming - it will delegate to writer
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print("[AutoGen]")
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await Console(coordinator.run(task="Create a tagline for a coffee shop", stream=True))
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await Console(coordinator.run_stream(task="Create a tagline for a coffee shop"))
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async def run_agent_framework() -> None:
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