test

python/samples/semantic-kernel-migration/openai_responses/01_basic_responses_agent.py

@@ -0,0 +1,48 @@
+# Copyright (c) Microsoft. All rights reserved.
+"""Issue a basic Responses API call using SK and Agent Framework."""
+
+import asyncio
+
+
+async def run_semantic_kernel() -> None:
+    from azure.identity import AzureCliCredential
+    from semantic_kernel.agents import AzureResponsesAgent
+    from semantic_kernel.connectors.ai.open_ai import AzureOpenAISettings
+
+    credential = AzureCliCredential()
+    try:
+        client = AzureResponsesAgent.create_client(credential=credential)
+        # SK response agents wrap Azure OpenAI's hosted Responses API.
+        agent = AzureResponsesAgent(
+            ai_model_id=AzureOpenAISettings().responses_deployment_name,
+            client=client,
+            instructions="Answer in one concise sentence.",
+            name="Expert",
+        )
+        response = await agent.get_response("Why is the sky blue?")
+        print("[SK]", response.message.content)
+    finally:
+        await credential.close()
+
+
+async def run_agent_framework() -> None:
+    from agent_framework import ChatAgent
+    from agent_framework.openai import OpenAIResponsesClient
+
+    # AF ChatAgent can swap in an OpenAIResponsesClient directly.
+    chat_agent = ChatAgent(
+        chat_client=OpenAIResponsesClient(),
+        instructions="Answer in one concise sentence.",
+        name="Expert",
+    )
+    reply = await chat_agent.run("Why is the sky blue?")
+    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/openai_responses/02_responses_agent_with_tool.py

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+# Copyright (c) Microsoft. All rights reserved.
+"""Attach a lightweight function tool to the Responses API in SK and AF."""
+
+import asyncio
+
+
+async def run_semantic_kernel() -> None:
+    from azure.identity import AzureCliCredential
+    from semantic_kernel.agents import AzureResponsesAgent
+    from semantic_kernel.connectors.ai.open_ai import AzureOpenAISettings
+    from semantic_kernel.functions import kernel_function
+
+    class MathPlugin:
+        @kernel_function(name="add", description="Add two numbers")
+        def add(self, a: float, b: float) -> float:
+            return a + b
+
+    credential = AzureCliCredential()
+    try:
+        client = AzureResponsesAgent.create_client(credential=credential)
+        # Plugins advertise callable tools to the Responses agent.
+        agent = AzureResponsesAgent(
+            ai_model_id=AzureOpenAISettings().responses_deployment_name,
+            client=client,
+            instructions="Use the add tool when math is required.",
+            name="MathExpert",
+            plugins=[MathPlugin()],
+        )
+        response = await agent.get_response("Use add(41, 1) and explain the result.")
+        print("[SK]", response.message.content)
+    finally:
+        await credential.close()
+
+
+async def run_agent_framework() -> None:
+    from agent_framework import ChatAgent
+    from agent_framework._tools import ai_function
+    from agent_framework.openai import OpenAIResponsesClient
+
+    @ai_function(name="add", description="Add two numbers")
+    async def add(a: float, b: float) -> float:
+        return a + b
+
+    chat_agent = ChatAgent(
+        chat_client=OpenAIResponsesClient(),
+        instructions="Use the add tool when math is required.",
+        name="MathExpert",
+        # AF registers the async function as a tool at construction.
+        tools=[add],
+    )
+    reply = await chat_agent.run("Use add(41, 1) and explain the result.")
+    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/openai_responses/03_responses_agent_structured_output.py

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+# Copyright (c) Microsoft. All rights reserved.
+"""Request structured JSON output from the Responses API in SK and AF."""
+
+import asyncio
+
+from pydantic import BaseModel
+
+
+class ReleaseBrief(BaseModel):
+    feature: str
+    benefit: str
+    launch_date: str
+
+
+async def run_semantic_kernel() -> None:
+    from azure.identity import AzureCliCredential
+    from semantic_kernel.agents import AzureResponsesAgent
+    from semantic_kernel.connectors.ai.open_ai import AzureOpenAISettings
+
+    credential = AzureCliCredential()
+    try:
+        client = AzureResponsesAgent.create_client(credential=credential)
+        # response_format requests schema-constrained output from the model.
+        agent = AzureResponsesAgent(
+            ai_model_id=AzureOpenAISettings().responses_deployment_name,
+            client=client,
+            instructions="Return launch briefs as structured JSON.",
+            name="ProductMarketer",
+            text=AzureResponsesAgent.configure_response_format(ReleaseBrief),
+        )
+        response = await agent.get_response(
+            "Draft a launch brief for the Contoso Note app.",
+            response_format=ReleaseBrief,
+        )
+        print("[SK]", response.message.content)
+    finally:
+        await credential.close()
+
+
+async def run_agent_framework() -> None:
+    from agent_framework import ChatAgent
+    from agent_framework.openai import OpenAIResponsesClient
+
+    chat_agent = ChatAgent(
+        chat_client=OpenAIResponsesClient(),
+        instructions="Return launch briefs as structured JSON.",
+        name="ProductMarketer",
+    )
+    # AF forwards the same response_format payload at invocation time.
+    reply = await chat_agent.run(
+        "Draft a launch brief for the Contoso Note app.",
+        options={"response_format": ReleaseBrief},
+    )
+    print("[AF]", reply.text)
+
+
+async def main() -> None:
+    await run_semantic_kernel()
+    await run_agent_framework()
+
+
+if __name__ == "__main__":
+    asyncio.run(main())