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Python: restructure: Python samples into progressive 01-05 layout (#3862)
* restructure: Python samples into progressive 01-05 layout - 01-get-started/: 6 numbered steps (hello agent → hosting) - 02-agents/: all agent concept samples (tools, middleware, providers, etc.) - 03-workflows/: ALL existing workflow samples preserved as-is - 04-hosting/: azure-functions, durabletask, a2a - 05-end-to-end/: demos, evaluation, hosted agents - Old files moved to _to_delete/ for review - Added AGENTS.md with structure documentation - autogen-migration/ and semantic-kernel-migration/ preserved at root * fix: switch to AzureOpenAI Foundry, fix CI failures - Switch all 01-get-started samples to AzureOpenAIResponsesClient with Azure AI Foundry project endpoint (AZURE_AI_PROJECT_ENDPOINT + AZURE_OPENAI_RESPONSES_DEPLOYMENT_NAME + AzureCliCredential) - Add _to_delete/ and 05-end-to-end/ to pyrightconfig.samples.json excludes - Fix test paths in packages/ that referenced old getting_started/ dirs: durabletask conftest + streaming test, azurefunctions conftest, devui conftest + capture_messages + openai_sdk_integration - Fix workflow_as_agent_human_in_the_loop.py import (sibling import) - Update hosting READMEs and tool comment paths - Replace root README.md with new structure overview - Update AGENTS.md to document Azure OpenAI Foundry as default provider * cleanup: remove _to_delete folder, copy resource files to active dirs All files in _to_delete/ were either: - Exact duplicates of files in the new structure (240 files) - Same file with only comment path updates (100 files) - One import-fix diff (workflow_as_agent_human_in_the_loop.py) - One superseded minimal_sample.py Resource files (sample.pdf, countries.json, employees.pdf, weather.json) copied to 02-agents/sample_assets/ and 02-agents/resources/ since active samples reference them. * fix: address PR review comments, centralize resources, remove root duplicates - Fix type annotation in 04_memory.py (string union -> proper types) - Fix old sample paths in observability files - Fix grammar/spelling in observability samples - Move sample_assets/ and resources/ to shared/ folder - Remove 8 duplicate observability files from 02-agents root - Update resource path references in multimodal_input and provider samples * fix: update broken links from old getting_started paths to new structure - Update relative paths in READMEs: getting_started/ → 01-get-started/, 02-agents/, 03-workflows/, 04-hosting/, 05-end-to-end/ - Fix absolute GitHub URLs in package READMEs - Fix broken link in ollama package README * fix: convert absolute GitHub URLs to relative paths for link checker Absolute URLs to python/samples/ on main branch 404 until PR merges. Converted to relative paths that linkspector can verify locally. * fix: update link for handoff sample moved to orchestrations/ * fix: update chatkit-integration README path from demos/ to 05-end-to-end/ * fix: update broken links in orchestrations README to match flat directory structure
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# Chat Client Examples
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This folder contains simple examples demonstrating direct usage of various chat clients.
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## Examples
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| File | Description |
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|------|-------------|
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| [`azure_assistants_client.py`](azure_assistants_client.py) | Direct usage of Azure Assistants Client for basic chat interactions with Azure OpenAI assistants. |
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| [`azure_chat_client.py`](azure_chat_client.py) | Direct usage of Azure Chat Client for chat interactions with Azure OpenAI models. |
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| [`azure_responses_client.py`](azure_responses_client.py) | Direct usage of Azure Responses Client for structured response generation with Azure OpenAI models. |
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| [`chat_response_cancellation.py`](chat_response_cancellation.py) | Demonstrates how to cancel chat responses during streaming, showing proper cancellation handling and cleanup. |
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| [`azure_ai_chat_client.py`](azure_ai_chat_client.py) | Direct usage of Azure AI Chat Client for chat interactions with Azure AI models. |
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| [`openai_assistants_client.py`](openai_assistants_client.py) | Direct usage of OpenAI Assistants Client for basic chat interactions with OpenAI assistants. |
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| [`openai_chat_client.py`](openai_chat_client.py) | Direct usage of OpenAI Chat Client for chat interactions with OpenAI models. |
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| [`openai_responses_client.py`](openai_responses_client.py) | Direct usage of OpenAI Responses Client for structured response generation with OpenAI models. |
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| [`custom_chat_client.py`](custom_chat_client.py) | Demonstrates how to create custom chat clients by extending the `BaseChatClient` class. Shows a `EchoingChatClient` implementation and how to integrate it with `Agent` using the `as_agent()` method. |
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## Environment Variables
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Depending on which client you're using, set the appropriate environment variables:
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**For Azure clients:**
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- `AZURE_OPENAI_ENDPOINT`: Your Azure OpenAI endpoint
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- `AZURE_OPENAI_CHAT_DEPLOYMENT_NAME`: The name of your Azure OpenAI chat deployment
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- `AZURE_OPENAI_RESPONSES_DEPLOYMENT_NAME`: The name of your Azure OpenAI responses deployment
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**For Azure AI client:**
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- `AZURE_AI_PROJECT_ENDPOINT`: Your Azure AI project endpoint
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- `AZURE_AI_MODEL_DEPLOYMENT_NAME`: The name of your model deployment
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**For OpenAI clients:**
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- `OPENAI_API_KEY`: Your OpenAI API key
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- `OPENAI_CHAT_MODEL_ID`: The OpenAI model to use for chat clients (e.g., `gpt-4o`, `gpt-4o-mini`, `gpt-3.5-turbo`)
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- `OPENAI_RESPONSES_MODEL_ID`: The OpenAI model to use for responses clients (e.g., `gpt-4o`, `gpt-4o-mini`, `gpt-3.5-turbo`)
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**For Ollama client:**
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- `OLLAMA_HOST`: Your Ollama server URL (defaults to `http://localhost:11434` if not set)
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- `OLLAMA_MODEL_ID`: The Ollama model to use for chat (e.g., `llama3.2`, `llama2`, `codellama`)
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> **Note**: For Ollama, ensure you have Ollama installed and running locally with at least one model downloaded. Visit [https://ollama.com/](https://ollama.com/) for installation instructions.
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# Copyright (c) Microsoft. All rights reserved.
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import asyncio
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from random import randint
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from typing import Annotated
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from agent_framework import tool
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from agent_framework.azure import AzureAIAgentClient
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from azure.identity.aio import AzureCliCredential
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from pydantic import Field
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"""
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Azure AI Chat Client Direct Usage Example
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Demonstrates direct AzureAIChatClient usage for chat interactions with Azure AI models.
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Shows function calling capabilities with custom business logic.
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"""
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# NOTE: approval_mode="never_require" is for sample brevity. Use "always_require" in production; see samples/02-agents/tools/function_tool_with_approval.py and samples/02-agents/tools/function_tool_with_approval_and_threads.py.
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@tool(approval_mode="never_require")
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def get_weather(
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location: Annotated[str, Field(description="The location to get the weather for.")],
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) -> str:
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"""Get the weather for a given location."""
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conditions = ["sunny", "cloudy", "rainy", "stormy"]
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return f"The weather in {location} is {conditions[randint(0, 3)]} with a high of {randint(10, 30)}°C."
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async def main() -> None:
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# For authentication, run `az login` command in terminal or replace AzureCliCredential with preferred
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# authentication option.
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async with AzureAIAgentClient(credential=AzureCliCredential()) as client:
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message = "What's the weather in Amsterdam and in Paris?"
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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_weather, 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_weather)
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print(f"Assistant: {response}")
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if __name__ == "__main__":
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asyncio.run(main())
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# Copyright (c) Microsoft. All rights reserved.
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import asyncio
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from random import randint
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from typing import Annotated
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from agent_framework import tool
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from agent_framework.azure import AzureOpenAIAssistantsClient
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from azure.identity import AzureCliCredential
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from pydantic import Field
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"""
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Azure Assistants Client Direct Usage Example
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Demonstrates direct AzureAssistantsClient usage for chat interactions with Azure OpenAI assistants.
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Shows function calling capabilities and automatic assistant creation.
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"""
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# NOTE: approval_mode="never_require" is for sample brevity. Use "always_require" in production; see samples/02-agents/tools/function_tool_with_approval.py and samples/02-agents/tools/function_tool_with_approval_and_threads.py.
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@tool(approval_mode="never_require")
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def get_weather(
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location: Annotated[str, Field(description="The location to get the weather for.")],
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) -> str:
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"""Get the weather for a given location."""
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conditions = ["sunny", "cloudy", "rainy", "stormy"]
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return f"The weather in {location} is {conditions[randint(0, 3)]} with a high of {randint(10, 30)}°C."
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async def main() -> None:
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# For authentication, run `az login` command in terminal or replace AzureCliCredential with preferred
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# authentication option.
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async with AzureOpenAIAssistantsClient(credential=AzureCliCredential()) as client:
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message = "What's the weather in Amsterdam and in Paris?"
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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_weather, 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_weather)
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print(f"Assistant: {response}")
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if __name__ == "__main__":
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asyncio.run(main())
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# Copyright (c) Microsoft. All rights reserved.
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import asyncio
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from random import randint
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from typing import Annotated
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from agent_framework import tool
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from agent_framework.azure import AzureOpenAIChatClient
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from azure.identity import AzureCliCredential
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from pydantic import Field
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"""
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Azure Chat Client Direct Usage Example
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Demonstrates direct AzureChatClient usage for chat interactions with Azure OpenAI models.
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Shows function calling capabilities with custom business logic.
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"""
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# NOTE: approval_mode="never_require" is for sample brevity. Use "always_require" in production; see samples/02-agents/tools/function_tool_with_approval.py and samples/02-agents/tools/function_tool_with_approval_and_threads.py.
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@tool(approval_mode="never_require")
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def get_weather(
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location: Annotated[str, Field(description="The location to get the weather for.")],
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) -> str:
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"""Get the weather for a given location."""
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conditions = ["sunny", "cloudy", "rainy", "stormy"]
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return f"The weather in {location} is {conditions[randint(0, 3)]} with a high of {randint(10, 30)}°C."
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async def main() -> None:
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# For authentication, run `az login` command in terminal or replace AzureCliCredential with preferred
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# authentication option.
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client = AzureOpenAIChatClient(credential=AzureCliCredential())
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message = "What's the weather in Amsterdam and in Paris?"
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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_weather, 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_weather)
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print(f"Assistant: {response}")
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if __name__ == "__main__":
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asyncio.run(main())
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# Copyright (c) Microsoft. All rights reserved.
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import asyncio
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from random import randint
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from typing import Annotated
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from agent_framework import tool
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from agent_framework.azure import AzureOpenAIResponsesClient
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from azure.identity import AzureCliCredential
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from pydantic import BaseModel
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"""
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Azure Responses Client Direct Usage Example
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Demonstrates direct AzureResponsesClient usage for structured response generation with Azure OpenAI models.
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Shows function calling capabilities with custom business logic.
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"""
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# NOTE: approval_mode="never_require" is for sample brevity. Use "always_require" in production; see samples/02-agents/tools/function_tool_with_approval.py and samples/02-agents/tools/function_tool_with_approval_and_threads.py.
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@tool(approval_mode="never_require")
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def get_weather(
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location: Annotated[str, "The location to get the weather for."],
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) -> str:
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"""Get the weather for a given location."""
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conditions = ["sunny", "cloudy", "rainy", "stormy"]
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return f"The weather in {location} is {conditions[randint(0, 3)]} with a high of {randint(10, 30)}°C."
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@tool(approval_mode="never_require")
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def get_time():
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"""Get the current time."""
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from datetime import datetime
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now = datetime.now()
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return f"The current date time is {now.strftime('%Y-%m-%d - %H:%M:%S')}."
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class WeatherDetail(BaseModel):
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"""Structured output for weather information."""
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location: str
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weather: str
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class Weather(BaseModel):
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"""Container for multiple outputs."""
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date_time: str
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weather_details: list[WeatherDetail]
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async def main() -> None:
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# For authentication, run `az login` command in terminal or replace AzureCliCredential with preferred
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# authentication option.
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client = AzureOpenAIResponsesClient(credential=AzureCliCredential(), api_version="preview")
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message = "What's the weather in Amsterdam and in Paris?"
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stream = True
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print(f"User: {message}")
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response = client.get_response(
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message,
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options={"response_format": Weather, "tools": [get_weather, get_time]},
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stream=stream,
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)
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if stream:
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response = await response.get_final_response()
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else:
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response = await response
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if result := response.value:
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print(f"Assistant: {result.model_dump_json(indent=2)}")
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else:
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print(f"Assistant: {response.text}")
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# Expected output (time will be different):
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"""
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User: What's the weather in Amsterdam and in Paris?
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Assistant: {
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"date_time": "2026-02-06 - 13:30:40",
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"weather_details": [
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{
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"location": "Amsterdam",
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"weather": "The weather in Amsterdam is cloudy with a high of 21°C."
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},
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{
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"location": "Paris",
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"weather": "The weather in Paris is sunny with a high of 27°C."
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}
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]
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}
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"""
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if __name__ == "__main__":
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asyncio.run(main())
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# Copyright (c) Microsoft. All rights reserved.
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import asyncio
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from agent_framework.openai import OpenAIChatClient
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"""
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Chat Response Cancellation Example
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Demonstrates proper cancellation of streaming chat responses during execution.
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Shows asyncio task cancellation and resource cleanup techniques.
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"""
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async def main() -> None:
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"""
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Demonstrates cancelling a chat request after 1 second.
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Creates a task for the chat request, waits briefly, then cancels it to show proper cleanup.
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Configuration:
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- OpenAI model ID: Use "model_id" parameter or "OPENAI_CHAT_MODEL_ID" environment variable
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- OpenAI API key: Use "api_key" parameter or "OPENAI_API_KEY" environment variable
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"""
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client = OpenAIChatClient()
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try:
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task = asyncio.create_task(client.get_response(messages=["Tell me a fantasy story."]))
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await asyncio.sleep(1)
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task.cancel()
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await task
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except asyncio.CancelledError:
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print("Request was cancelled")
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if __name__ == "__main__":
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asyncio.run(main())
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# Copyright (c) Microsoft. All rights reserved.
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import asyncio
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import random
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import sys
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from collections.abc import AsyncIterable, Awaitable, Mapping, Sequence
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from typing import Any, ClassVar, Generic
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from agent_framework import (
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BaseChatClient,
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ChatMiddlewareLayer,
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ChatResponse,
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ChatResponseUpdate,
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Content,
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FunctionInvocationLayer,
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Message,
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ResponseStream,
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Role,
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)
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from agent_framework._clients import OptionsCoT
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from agent_framework.observability import ChatTelemetryLayer
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if sys.version_info >= (3, 13):
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pass
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else:
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pass
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if sys.version_info >= (3, 12):
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from typing import override # type: ignore # pragma: no cover
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else:
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from typing_extensions import override # type: ignore[import] # pragma: no cover
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"""
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Custom Chat Client Implementation Example
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This sample demonstrates implementing a custom chat client and optionally composing
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middleware, telemetry, and function invocation layers explicitly.
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"""
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class EchoingChatClient(BaseChatClient[OptionsCoT], Generic[OptionsCoT]):
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"""A custom chat client that echoes messages back with modifications.
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This demonstrates how to implement a custom chat client by extending BaseChatClient
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and implementing the required _inner_get_response() method.
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"""
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OTEL_PROVIDER_NAME: ClassVar[str] = "EchoingChatClient"
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def __init__(self, *, prefix: str = "Echo:", **kwargs: Any) -> None:
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"""Initialize the EchoingChatClient.
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Args:
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prefix: Prefix to add to echoed messages.
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**kwargs: Additional keyword arguments passed to BaseChatClient.
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"""
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super().__init__(**kwargs)
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self.prefix = prefix
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@override
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def _inner_get_response(
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self,
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*,
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messages: Sequence[Message],
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stream: bool = False,
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options: Mapping[str, Any],
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**kwargs: Any,
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) -> Awaitable[ChatResponse] | ResponseStream[ChatResponseUpdate, ChatResponse]:
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"""Echo back the user's message with a prefix."""
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if not messages:
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response_text = "No messages to echo!"
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else:
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# Echo the last user message
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last_user_message = None
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for message in reversed(messages):
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if message.role == Role.USER:
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last_user_message = message
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break
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if last_user_message and last_user_message.text:
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response_text = f"{self.prefix} {last_user_message.text}"
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else:
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response_text = f"{self.prefix} [No text message found]"
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response_message = Message(role=Role.ASSISTANT, contents=[Content.from_text(response_text)])
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response = ChatResponse(
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messages=[response_message],
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model_id="echo-model-v1",
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response_id=f"echo-resp-{random.randint(1000, 9999)}",
|
||||
)
|
||||
|
||||
if not stream:
|
||||
|
||||
async def _get_response() -> ChatResponse:
|
||||
return response
|
||||
|
||||
return _get_response()
|
||||
|
||||
async def _stream() -> AsyncIterable[ChatResponseUpdate]:
|
||||
response_text_local = response_message.text or ""
|
||||
for char in response_text_local:
|
||||
yield ChatResponseUpdate(
|
||||
contents=[Content.from_text(char)],
|
||||
role=Role.ASSISTANT,
|
||||
response_id=f"echo-stream-resp-{random.randint(1000, 9999)}",
|
||||
model_id="echo-model-v1",
|
||||
)
|
||||
await asyncio.sleep(0.05)
|
||||
|
||||
return ResponseStream(_stream(), finalizer=lambda updates: response)
|
||||
|
||||
|
||||
class EchoingChatClientWithLayers( # type: ignore[misc,type-var]
|
||||
ChatMiddlewareLayer[OptionsCoT],
|
||||
ChatTelemetryLayer[OptionsCoT],
|
||||
FunctionInvocationLayer[OptionsCoT],
|
||||
EchoingChatClient[OptionsCoT],
|
||||
Generic[OptionsCoT],
|
||||
):
|
||||
"""Echoing chat client that explicitly composes middleware, telemetry, and function layers."""
|
||||
|
||||
OTEL_PROVIDER_NAME: ClassVar[str] = "EchoingChatClientWithLayers"
|
||||
|
||||
|
||||
async def main() -> None:
|
||||
"""Demonstrates how to implement and use a custom chat client with Agent."""
|
||||
print("=== Custom Chat Client Example ===\n")
|
||||
|
||||
# Create the custom chat client
|
||||
print("--- EchoingChatClient Example ---")
|
||||
|
||||
echo_client = EchoingChatClientWithLayers(prefix="🔊 Echo:")
|
||||
|
||||
# Use the chat client directly
|
||||
print("Using chat client directly:")
|
||||
direct_response = await echo_client.get_response("Hello, custom chat client!")
|
||||
print(f"Direct response: {direct_response.messages[0].text}")
|
||||
|
||||
# Create an agent using the custom chat client
|
||||
echo_agent = echo_client.as_agent(
|
||||
name="EchoAgent",
|
||||
instructions="You are a helpful assistant that echoes back what users say.",
|
||||
)
|
||||
|
||||
print(f"\nAgent Name: {echo_agent.name}")
|
||||
|
||||
# Test non-streaming with agent
|
||||
query = "This is a test message"
|
||||
print(f"\nUser: {query}")
|
||||
result = await echo_agent.run(query)
|
||||
print(f"Agent: {result.messages[0].text}")
|
||||
|
||||
# Test streaming with agent
|
||||
query2 = "Stream this message back to me"
|
||||
print(f"\nUser: {query2}")
|
||||
print("Agent: ", end="", flush=True)
|
||||
async for chunk in echo_agent.run(query2, stream=True):
|
||||
if chunk.text:
|
||||
print(chunk.text, end="", flush=True)
|
||||
print()
|
||||
|
||||
# Example: Using with threads and conversation history
|
||||
print("\n--- Using Custom Chat Client with Thread ---")
|
||||
|
||||
thread = echo_agent.get_new_thread()
|
||||
|
||||
# Multiple messages in conversation
|
||||
messages = [
|
||||
"Hello, I'm starting a conversation",
|
||||
"How are you doing?",
|
||||
"Thanks for chatting!",
|
||||
]
|
||||
|
||||
for msg in messages:
|
||||
result = await echo_agent.run(msg, thread=thread)
|
||||
print(f"User: {msg}")
|
||||
print(f"Agent: {result.messages[0].text}\n")
|
||||
|
||||
# Check conversation history
|
||||
if thread.message_store:
|
||||
thread_messages = await thread.message_store.list_messages()
|
||||
print(f"Thread contains {len(thread_messages)} messages")
|
||||
else:
|
||||
print("Thread has no message store configured")
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
asyncio.run(main())
|
||||
@@ -0,0 +1,47 @@
|
||||
# Copyright (c) Microsoft. All rights reserved.
|
||||
|
||||
import asyncio
|
||||
from random import randint
|
||||
from typing import Annotated
|
||||
|
||||
from agent_framework import tool
|
||||
from agent_framework.openai import OpenAIAssistantsClient
|
||||
from pydantic import Field
|
||||
|
||||
"""
|
||||
OpenAI Assistants Client Direct Usage Example
|
||||
|
||||
Demonstrates direct OpenAIAssistantsClient usage for chat interactions with OpenAI assistants.
|
||||
Shows function calling capabilities and automatic assistant creation.
|
||||
|
||||
"""
|
||||
|
||||
|
||||
# NOTE: approval_mode="never_require" is for sample brevity. Use "always_require" in production; see samples/02-agents/tools/function_tool_with_approval.py and samples/02-agents/tools/function_tool_with_approval_and_threads.py.
|
||||
@tool(approval_mode="never_require")
|
||||
def get_weather(
|
||||
location: Annotated[str, Field(description="The location to get the weather for.")],
|
||||
) -> str:
|
||||
"""Get the weather for a given location."""
|
||||
conditions = ["sunny", "cloudy", "rainy", "stormy"]
|
||||
return f"The weather in {location} is {conditions[randint(0, 3)]} with a high of {randint(10, 30)}°C."
|
||||
|
||||
|
||||
async def main() -> None:
|
||||
async with OpenAIAssistantsClient() as client:
|
||||
message = "What's the weather in Amsterdam and in Paris?"
|
||||
stream = False
|
||||
print(f"User: {message}")
|
||||
if stream:
|
||||
print("Assistant: ", end="")
|
||||
async for chunk in client.get_response(message, tools=get_weather, stream=True):
|
||||
if str(chunk):
|
||||
print(str(chunk), end="")
|
||||
print("")
|
||||
else:
|
||||
response = await client.get_response(message, tools=get_weather)
|
||||
print(f"Assistant: {response}")
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
asyncio.run(main())
|
||||
@@ -0,0 +1,47 @@
|
||||
# Copyright (c) Microsoft. All rights reserved.
|
||||
|
||||
import asyncio
|
||||
from random import randint
|
||||
from typing import Annotated
|
||||
|
||||
from agent_framework import tool
|
||||
from agent_framework.openai import OpenAIChatClient
|
||||
from pydantic import Field
|
||||
|
||||
"""
|
||||
OpenAI Chat Client Direct Usage Example
|
||||
|
||||
Demonstrates direct OpenAIChatClient usage for chat interactions with OpenAI models.
|
||||
Shows function calling capabilities with custom business logic.
|
||||
|
||||
"""
|
||||
|
||||
|
||||
# NOTE: approval_mode="never_require" is for sample brevity. Use "always_require" in production; see samples/02-agents/tools/function_tool_with_approval.py and samples/02-agents/tools/function_tool_with_approval_and_threads.py.
|
||||
@tool(approval_mode="never_require")
|
||||
def get_weather(
|
||||
location: Annotated[str, Field(description="The location to get the weather for.")],
|
||||
) -> str:
|
||||
"""Get the weather for a given location."""
|
||||
conditions = ["sunny", "cloudy", "rainy", "stormy"]
|
||||
return f"The weather in {location} is {conditions[randint(0, 3)]} with a high of {randint(10, 30)}°C."
|
||||
|
||||
|
||||
async def main() -> None:
|
||||
client = OpenAIChatClient()
|
||||
message = "What's the weather in Amsterdam and in Paris?"
|
||||
stream = True
|
||||
print(f"User: {message}")
|
||||
if stream:
|
||||
print("Assistant: ", end="")
|
||||
async for chunk in client.get_response(message, tools=get_weather, stream=True):
|
||||
if chunk.text:
|
||||
print(chunk.text, end="")
|
||||
print("")
|
||||
else:
|
||||
response = await client.get_response(message, tools=get_weather)
|
||||
print(f"Assistant: {response}")
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
asyncio.run(main())
|
||||
@@ -0,0 +1,47 @@
|
||||
# Copyright (c) Microsoft. All rights reserved.
|
||||
|
||||
import asyncio
|
||||
from random import randint
|
||||
from typing import Annotated
|
||||
|
||||
from agent_framework import tool
|
||||
from agent_framework.openai import OpenAIResponsesClient
|
||||
from pydantic import Field
|
||||
|
||||
"""
|
||||
OpenAI Responses Client Direct Usage Example
|
||||
|
||||
Demonstrates direct OpenAIResponsesClient usage for structured response generation with OpenAI models.
|
||||
Shows function calling capabilities with custom business logic.
|
||||
|
||||
"""
|
||||
|
||||
|
||||
# NOTE: approval_mode="never_require" is for sample brevity. Use "always_require" in production; see samples/02-agents/tools/function_tool_with_approval.py and samples/02-agents/tools/function_tool_with_approval_and_threads.py.
|
||||
@tool(approval_mode="never_require")
|
||||
def get_weather(
|
||||
location: Annotated[str, Field(description="The location to get the weather for.")],
|
||||
) -> str:
|
||||
"""Get the weather for a given location."""
|
||||
conditions = ["sunny", "cloudy", "rainy", "stormy"]
|
||||
return f"The weather in {location} is {conditions[randint(0, 3)]} with a high of {randint(10, 30)}°C."
|
||||
|
||||
|
||||
async def main() -> None:
|
||||
client = OpenAIResponsesClient()
|
||||
message = "What's the weather in Amsterdam and in Paris?"
|
||||
stream = True
|
||||
print(f"User: {message}")
|
||||
print("Assistant: ", end="")
|
||||
response = client.get_response(message, stream=stream, options={"tools": get_weather})
|
||||
if stream:
|
||||
# TODO: review names of the methods, could be related to things like HTTP clients?
|
||||
response.with_transform_hook(lambda chunk: print(chunk.text, end=""))
|
||||
await response.get_final_response()
|
||||
else:
|
||||
response = await response
|
||||
print(f"Assistant: {response}")
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
asyncio.run(main())
|
||||
Reference in New Issue
Block a user