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Python: Fix migration samples (#5015)
* Fix migration samples * Fix migration samples 2 * Fix formatting * Comments
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‎python/samples/autogen-migration/README.md‎

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@@ -6,9 +6,9 @@ This gallery helps AutoGen developers move to the Microsoft Agent Framework (AF)
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### Single-Agent Parity
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- [01_basic_assistant_agent.py](single_agent/01_basic_assistant_agent.py) — Minimal AutoGen `AssistantAgent` and AF `Agent` comparison.
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- [02_assistant_agent_with_tool.py](single_agent/02_assistant_agent_with_tool.py) — Function tool integration in both SDKs.
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- [03_assistant_agent_thread_and_stream.py](single_agent/03_assistant_agent_thread_and_stream.py) — Session management and streaming responses.
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- [01_basic_agent.py](single_agent/01_basic_agent.py) — Minimal AutoGen `AssistantAgent` and AF `Agent` comparison.
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- [02_agent_with_tool.py](single_agent/02_agent_with_tool.py) — Function tool integration in both SDKs.
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- [03_agent_thread_and_stream.py](single_agent/03_agent_thread_and_stream.py) — Session management and streaming responses.
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- [04_agent_as_tool.py](single_agent/04_agent_as_tool.py) — Using agents as tools (hierarchical agent pattern) and streaming with tools.
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### Multi-Agent Orchestration
@@ -35,7 +35,7 @@ Each script is fully async and the `main()` routine runs both implementations ba
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From the repository root:
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```bash
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python samples/autogen-migration/single_agent/01_basic_assistant_agent.py
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python samples/autogen-migration/single_agent/01_basic_agent.py
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```
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Every script accepts no CLI arguments and will first call the AutoGen implementation, followed by the AF version. Adjust the prompt or credentials inside the file as necessary before running.

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

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@@ -65,7 +65,7 @@ async def run_agent_framework() -> None:
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from agent_framework.openai import OpenAIChatClient
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from agent_framework.orchestrations import SequentialBuilder
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client = OpenAIChatClient(model_id="gpt-4.1-mini")
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client = OpenAIChatClient(model="gpt-4.1-mini")
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# Create specialized agents
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researcher = Agent(
@@ -112,7 +112,7 @@ async def run_agent_framework_with_cycle() -> None:
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)
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from agent_framework.openai import OpenAIChatClient
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client = OpenAIChatClient(model_id="gpt-4.1-mini")
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client = OpenAIChatClient(model="gpt-4.1-mini")
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# Create specialized agents
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researcher = Agent(

‎python/samples/autogen-migration/orchestrations/04_magentic_one.py‎

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@@ -76,7 +76,7 @@ async def run_agent_framework() -> None:
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from agent_framework.openai import OpenAIChatClient
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from agent_framework.orchestrations import MagenticBuilder
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client = OpenAIChatClient(model_id="gpt-4.1-mini")
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client = OpenAIChatClient(model="gpt-4.1-mini")
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# Create specialized agents
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researcher = Agent(

python/samples/autogen-migration/single_agent/01_basic_assistant_agent.py renamed to python/samples/autogen-migration/single_agent/01_basic_agent.py

File renamed without changes.

python/samples/autogen-migration/single_agent/02_assistant_agent_with_tool.py renamed to python/samples/autogen-migration/single_agent/02_agent_with_tool.py

File renamed without changes.

python/samples/autogen-migration/single_agent/03_assistant_agent_thread_and_stream.py renamed to python/samples/autogen-migration/single_agent/03_agent_thread_and_stream.py

File renamed without changes.

‎python/samples/semantic-kernel-migration/chat_completion/02_chat_completion_with_tool.py‎

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@@ -23,7 +23,7 @@
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async def run_semantic_kernel() -> None:
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from semantic_kernel.agents import ChatCompletionAgent, ChatHistoryAgentThread
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from semantic_kernel.agents import ChatCompletionAgent
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from semantic_kernel.connectors.ai.open_ai import OpenAIChatCompletion
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from semantic_kernel.functions import kernel_function
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@@ -39,11 +39,7 @@ def specials(self) -> str:
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instructions="Answer menu questions accurately.",
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plugins=[SpecialsPlugin()],
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)
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thread = ChatHistoryAgentThread()
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response = await agent.get_response(
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messages="What soup can I order today?",
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thread=thread,
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)
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response = await agent.get_response("What soup can I order today?")
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print("[SK]", response.message.content)
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@@ -62,12 +58,7 @@ async def specials() -> str:
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instructions="Answer menu questions accurately.",
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tools=[specials],
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)
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session = chat_agent.create_session()
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reply = await chat_agent.run(
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"What soup can I order today?",
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session=session,
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tool_choice="auto",
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)
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reply = await chat_agent.run("What soup can I order today?")
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print("[AF]", reply.text)
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‎python/samples/semantic-kernel-migration/openai_responses/01_basic_responses_agent.py‎

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@@ -22,10 +22,13 @@ async def run_semantic_kernel() -> None:
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from semantic_kernel.agents import OpenAIResponsesAgent
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from semantic_kernel.connectors.ai.open_ai import OpenAISettings
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openai_settings = OpenAISettings()
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assert openai_settings.responses_model_id is not None, "Responses model ID must be set in OpenAISettings"
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client = OpenAIResponsesAgent.create_client()
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# SK response agents wrap OpenAI's hosted Responses API.
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agent = OpenAIResponsesAgent(
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ai_model=OpenAISettings().responses_model_id,
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ai_model_id=openai_settings.responses_model_id,
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client=client,
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instructions="Answer in one concise sentence.",
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name="Expert",

‎python/samples/semantic-kernel-migration/openai_responses/02_responses_agent_with_tool.py‎

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Original file line numberDiff line numberDiff line change
@@ -28,10 +28,13 @@ class MathPlugin:
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def add(self, a: float, b: float) -> float:
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return a + b
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openai_settings = OpenAISettings()
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assert openai_settings.responses_model_id is not None, "Responses model ID must be set in OpenAISettings"
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client = OpenAIResponsesAgent.create_client()
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# Plugins advertise callable tools to the Responses agent.
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agent = OpenAIResponsesAgent(
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ai_model=OpenAISettings().responses_model_id,
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ai_model_id=openai_settings.responses_model_id,
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client=client,
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instructions="Use the add tool when math is required.",
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name="MathExpert",

‎python/samples/semantic-kernel-migration/openai_responses/03_responses_agent_structured_output.py‎

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Original file line numberDiff line numberDiff line change
@@ -29,14 +29,17 @@ async def run_semantic_kernel() -> None:
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from semantic_kernel.agents import OpenAIResponsesAgent
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from semantic_kernel.connectors.ai.open_ai import OpenAISettings
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openai_settings = OpenAISettings()
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assert openai_settings.responses_model_id is not None, "Responses model ID must be set in OpenAISettings"
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client = OpenAIResponsesAgent.create_client()
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# response_format requests schema-constrained output from the model.
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agent = OpenAIResponsesAgent(
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ai_model=OpenAISettings().responses_model_id,
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ai_model_id=openai_settings.responses_model_id,
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client=client,
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instructions="Return launch briefs as structured JSON.",
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name="ProductMarketer",
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text=OpenAIResponsesAgent.configure_response_format(ReleaseBrief),
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text=OpenAIResponsesAgent.configure_response_format(ReleaseBrief), # type: ignore
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)
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response = await agent.get_response(
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"Draft a launch brief for the Contoso Note app.",

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