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Sample to show passing in JSON schema for structured outputs (#2362)

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This commit is contained in:
Evan Mattson
2025-11-21 10:42:46 +09:00
committed by GitHub
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parent cf13e35c73
commit 5bdf8a774a
4 changed files with 116 additions and 2 deletions
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python/packages/core/agent_framework/_agents.py
+4 -2
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@@ -853,6 +853,7 @@ class ChatAgent(BaseAgent):
await self._async_exit_stack.enter_async_context(mcp_server)
final_tools.extend(mcp_server.functions)
merged_additional_options = additional_chat_options or {}
co = run_chat_options & ChatOptions(
model_id=model_id,
conversation_id=thread.service_thread_id,
@@ -871,7 +872,7 @@ class ChatAgent(BaseAgent):
tools=final_tools,
top_p=top_p,
user=user,
**(additional_chat_options or {}),
additional_properties=merged_additional_options, # type: ignore[arg-type]
)
# Filter chat_options from kwargs to prevent duplicate keyword argument
filtered_kwargs = {k: v for k, v in kwargs.items() if k != "chat_options"}
@@ -986,6 +987,7 @@ class ChatAgent(BaseAgent):
await self._async_exit_stack.enter_async_context(mcp_server)
final_tools.extend(mcp_server.functions)
merged_additional_options = additional_chat_options or {}
co = run_chat_options & ChatOptions(
conversation_id=thread.service_thread_id,
allow_multiple_tool_calls=allow_multiple_tool_calls,
@@ -1004,7 +1006,7 @@ class ChatAgent(BaseAgent):
tools=final_tools,
top_p=top_p,
user=user,
**(additional_chat_options or {}),
additional_properties=merged_additional_options, # type: ignore[arg-type]
)
# Filter chat_options from kwargs to prevent duplicate keyword argument
python/samples/README.md
+1
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@@ -118,6 +118,7 @@ This directory contains samples demonstrating the capabilities of Microsoft Agen
| [`getting_started/agents/openai/openai_chat_client_with_local_mcp.py`](./getting_started/agents/openai/openai_chat_client_with_local_mcp.py) | OpenAI Chat Client with Local MCP Example |
| [`getting_started/agents/openai/openai_chat_client_with_thread.py`](./getting_started/agents/openai/openai_chat_client_with_thread.py) | OpenAI Chat Client with Thread Management Example |
| [`getting_started/agents/openai/openai_chat_client_with_web_search.py`](./getting_started/agents/openai/openai_chat_client_with_web_search.py) | OpenAI Chat Client with Web Search Example |
| [`getting_started/agents/openai/openai_chat_client_with_runtime_json_schema.py`](./getting_started/agents/openai/openai_chat_client_with_runtime_json_schema.py) | OpenAI Chat Client with runtime JSON Schema for structured output without a Pydantic model |
| [`getting_started/agents/openai/openai_responses_client_basic.py`](./getting_started/agents/openai/openai_responses_client_basic.py) | OpenAI Responses Client Basic Example |
| [`getting_started/agents/openai/openai_responses_client_image_analysis.py`](./getting_started/agents/openai/openai_responses_client_image_analysis.py) | OpenAI Responses Client Image Analysis Example |
| [`getting_started/agents/openai/openai_responses_client_image_generation.py`](./getting_started/agents/openai/openai_responses_client_image_generation.py) | OpenAI Responses Client Image Generation Example |
python/samples/getting_started/agents/openai/README.md
+1
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@@ -19,6 +19,7 @@ This folder contains examples demonstrating different ways to create and use age
| [`openai_chat_client_with_local_mcp.py`](openai_chat_client_with_local_mcp.py) | Shows how to integrate OpenAI agents with local Model Context Protocol (MCP) servers for enhanced functionality and tool integration. |
| [`openai_chat_client_with_thread.py`](openai_chat_client_with_thread.py) | Demonstrates thread management with OpenAI agents, including automatic thread creation for stateless conversations and explicit thread management for maintaining conversation context across multiple interactions. |
| [`openai_chat_client_with_web_search.py`](openai_chat_client_with_web_search.py) | Shows how to use web search capabilities with OpenAI agents to retrieve and use information from the internet in responses. |
| [`openai_chat_client_with_runtime_json_schema.py`](openai_chat_client_with_runtime_json_schema.py) | Shows how to supply a runtime JSON Schema via `additional_chat_options` for structured output without defining a Pydantic model. |
| [`openai_responses_client_basic.py`](openai_responses_client_basic.py) | The simplest way to create an agent using `ChatAgent` with `OpenAIResponsesClient`. Shows both streaming and non-streaming responses for structured response generation with OpenAI models. |
| [`openai_responses_client_image_analysis.py`](openai_responses_client_image_analysis.py) | Demonstrates how to use vision capabilities with agents to analyze images. |
| [`openai_responses_client_image_generation.py`](openai_responses_client_image_generation.py) | Demonstrates how to use image generation capabilities with OpenAI agents to create images based on text descriptions. Requires PIL (Pillow) for image display. |
python/samples/getting_started/agents/openai/openai_chat_client_with_runtime_json_schema.py
+110
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@@ -0,0 +1,110 @@
# Copyright (c) Microsoft. All rights reserved.
import asyncio
import json
from agent_framework.openai import OpenAIChatClient
"""
OpenAI Chat Client Runtime JSON Schema Example
Demonstrates structured outputs when the schema is only known at runtime.
Uses additional_chat_options to pass a JSON Schema payload directly to OpenAI
without defining a Pydantic model up front.
"""
runtime_schema = {
"title": "WeatherDigest",
"type": "object",
"properties": {
"location": {"type": "string"},
"conditions": {"type": "string"},
"temperature_c": {"type": "number"},
"advisory": {"type": "string"},
},
# OpenAI strict mode requires every property to appear in required.
"required": ["location", "conditions", "temperature_c", "advisory"],
"additionalProperties": False,
}
async def non_streaming_example() -> None:
print("=== Non-streaming runtime JSON schema example ===")
agent = OpenAIChatClient().create_agent(
name="RuntimeSchemaAgent",
instructions="Return only JSON that matches the provided schema. Do not add commentary.",
)
query = "Give a brief weather digest for Seattle."
print(f"User: {query}")
response = await agent.run(
query,
additional_chat_options={
"response_format": {
"type": "json_schema",
"json_schema": {
"name": runtime_schema["title"],
"strict": True,
"schema": runtime_schema,
},
},
},
)
print("Model output:")
print(response.text)
parsed = json.loads(response.text)
print("Parsed dict:")
print(parsed)
async def streaming_example() -> None:
print("=== Streaming runtime JSON schema example ===")
agent = OpenAIChatClient().create_agent(
name="RuntimeSchemaAgent",
instructions="Return only JSON that matches the provided schema. Do not add commentary.",
)
query = "Give a brief weather digest for Portland."
print(f"User: {query}")
chunks = []
async for chunk in agent.run_stream(
query,
additional_chat_options={
"response_format": {
"type": "json_schema",
"json_schema": {
"name": runtime_schema["title"],
"strict": True,
"schema": runtime_schema,
},
},
},
):
if chunk.text:
chunks.append(chunk.text)
raw_text = "".join(chunks)
print("Model output:")
print(raw_text)
parsed = json.loads(raw_text)
print("Parsed dict:")
print(parsed)
async def main() -> None:
print("=== OpenAI Chat Client with runtime JSON Schema ===")
await non_streaming_example()
await streaming_example()
if __name__ == "__main__":
asyncio.run(main())