test

python/samples/semantic-kernel-migration/azure_ai_agent/01_basic_azure_ai_agent.py

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+# Copyright (c) Microsoft. All rights reserved.
+"""Create an Azure AI agent using both Semantic Kernel and Agent Framework.
+
+Prerequisites:
+- Azure AI agent resource with a deployed model.
+- Logged-in Azure CLI or other credential supported by AzureCliCredential.
+"""
+
+import asyncio
+
+
+async def run_semantic_kernel() -> None:
+    from azure.identity.aio import AzureCliCredential
+    from semantic_kernel.agents import AzureAIAgent, AzureAIAgentSettings
+
+    async with AzureCliCredential() as credential, AzureAIAgent.create_client(credential=credential) as client:
+        settings = AzureAIAgentSettings()  # Reads env vars for region/deployment.
+        # SK builds the remote agent definition then wraps it with AzureAIAgent.
+        definition = await client.agents.as_agent(
+            model=settings.model_deployment_name,
+            name="Support",
+            instructions="Answer customer questions in one paragraph.",
+        )
+        agent = AzureAIAgent(client=client, definition=definition)
+        response = await agent.get_response("How do I upgrade my plan?")
+        print("[SK]", response.message.content)
+
+
+async def run_agent_framework() -> None:
+    from agent_framework.azure import AzureAIAgentClient
+    from azure.identity.aio import AzureCliCredential
+
+    async with (
+        AzureCliCredential() as credential,
+        AzureAIAgentClient(credential=credential).as_agent(
+            name="Support",
+            instructions="Answer customer questions in one paragraph.",
+        ) as agent,
+    ):
+        # AF client returns an asynchronous context manager for remote agents.
+        reply = await agent.run("How do I upgrade my plan?")
+        print("[AF]", reply.text)
+
+
+async def main() -> None:
+    await run_semantic_kernel()
+    await run_agent_framework()
+
+
+if __name__ == "__main__":
+    asyncio.run(main())

python/samples/semantic-kernel-migration/azure_ai_agent/02_azure_ai_agent_with_code_interpreter.py

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+# Copyright (c) Microsoft. All rights reserved.
+"""Enable the hosted code interpreter for Azure AI agents in SK and AF.
+
+The Azure AI service natively executes the code interpreter tool. Provide the
+resource details via AzureAIAgentSettings (SK) or environment variables consumed
+by AzureAIAgentClient (AF).
+"""
+
+import asyncio
+
+
+async def run_semantic_kernel() -> None:
+    from azure.identity.aio import AzureCliCredential
+    from semantic_kernel.agents import AzureAIAgent, AzureAIAgentSettings
+
+    async with AzureCliCredential() as credential, AzureAIAgent.create_client(credential=credential) as client:
+        settings = AzureAIAgentSettings()
+        # Register the hosted code interpreter tool with the remote agent.
+        definition = await client.agents.as_agent(
+            model=settings.model_deployment_name,
+            name="Analyst",
+            instructions="Use the code interpreter for numeric work.",
+            tools=[{"type": "code_interpreter"}],
+        )
+        agent = AzureAIAgent(client=client, definition=definition)
+        response = await agent.get_response(
+            "Use Python to compute 42 ** 2 and explain the result.",
+        )
+        print("[SK]", response.message.content)
+
+
+async def run_agent_framework() -> None:
+    from agent_framework.azure import AzureAIAgentClient, HostedCodeInterpreterTool
+    from azure.identity.aio import AzureCliCredential
+
+    async with (
+        AzureCliCredential() as credential,
+        AzureAIAgentClient(credential=credential).as_agent(
+            name="Analyst",
+            instructions="Use the code interpreter for numeric work.",
+            tools=[HostedCodeInterpreterTool()],
+        ) as agent,
+    ):
+        # HostedCodeInterpreterTool mirrors the built-in Azure AI capability.
+        reply = await agent.run(
+            "Use Python to compute 42 ** 2 and explain the result.",
+            tool_choice="auto",
+        )
+        print("[AF]", reply.text)
+
+
+async def main() -> None:
+    await run_semantic_kernel()
+    await run_agent_framework()
+
+
+if __name__ == "__main__":
+    asyncio.run(main())

python/samples/semantic-kernel-migration/azure_ai_agent/03_azure_ai_agent_threads_and_followups.py

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+# Copyright (c) Microsoft. All rights reserved.
+"""Maintain Azure AI agent conversation state across turns in SK and AF."""
+
+import asyncio
+
+
+async def run_semantic_kernel() -> None:
+    from azure.identity.aio import AzureCliCredential
+    from semantic_kernel.agents import AzureAIAgent, AzureAIAgentSettings, AzureAIAgentThread
+
+    async with AzureCliCredential() as credential, AzureAIAgent.create_client(credential=credential) as client:
+        settings = AzureAIAgentSettings()
+        definition = await client.agents.as_agent(
+            model=settings.model_deployment_name,
+            name="Planner",
+            instructions="Track follow-up questions within the same thread.",
+        )
+        agent = AzureAIAgent(client=client, definition=definition)
+
+        thread: AzureAIAgentThread | None = None
+        # SK returns the updated AzureAIAgentThread on each response.
+        first = await agent.get_response("Outline the onboarding checklist.", thread=thread)
+        thread = first.thread
+        print("[SK][turn1]", first.message.content)
+
+        second = await agent.get_response(
+            "Highlight the items that require legal review.",
+            thread=thread,
+        )
+        print("[SK][turn2]", second.message.content)
+        if thread is not None:
+            print("[SK][thread-id]", thread.id)
+
+
+async def run_agent_framework() -> None:
+    from agent_framework.azure import AzureAIAgentClient
+    from azure.identity.aio import AzureCliCredential
+
+    async with (
+        AzureCliCredential() as credential,
+        AzureAIAgentClient(credential=credential).as_agent(
+            name="Planner",
+            instructions="Track follow-up questions within the same thread.",
+        ) as agent,
+    ):
+        thread = agent.get_new_thread()
+        # AF threads are explicit and can be serialized for external storage.
+        first = await agent.run("Outline the onboarding checklist.", thread=thread)
+        print("[AF][turn1]", first.text)
+
+        second = await agent.run(
+            "Highlight the items that require legal review.",
+            thread=thread,
+        )
+        print("[AF][turn2]", second.text)
+
+        serialized = await thread.serialize()
+        print("[AF][thread-json]", serialized)
+
+
+async def main() -> None:
+    await run_semantic_kernel()
+    await run_agent_framework()
+
+
+if __name__ == "__main__":
+    asyncio.run(main())