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Python: [BREAKING] Replace Hosted*Tool classes with tool methods (#3634)

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* Replace Hosted*Tool classes with client static factory methods

* fixed failing test

* mypy fix

* mypy fix 2

* declarative mypy fix

* addressed comments

* ToolProtocol removal

* fixed test

* agents mypy fix

* fix failing tests

* mypy fix

* addressed comments

* fixed tests

* addressed comments + added factory method overrides for azureai v2 client

* mypy fix

* added kwargs to azureai tool methods

* fixed in test

* _sessions fix

* test fix
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Giles Odigwe
2026-02-10 16:04:27 -08:00
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python/samples/getting_started/agents/openai/README.md
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# OpenAI Agent Framework Examples
This folder contains examples demonstrating different ways to create and use agents with the OpenAI Assistants client from the `agent_framework.openai` package.
This folder contains examples demonstrating different ways to create and use agents with the OpenAI clients from the `agent_framework.openai` package.
## Examples
@@ -8,10 +8,10 @@ This folder contains examples demonstrating different ways to create and use age
|------|-------------|
| [`openai_assistants_basic.py`](openai_assistants_basic.py) | Basic usage of `OpenAIAssistantProvider` with streaming and non-streaming responses. |
| [`openai_assistants_provider_methods.py`](openai_assistants_provider_methods.py) | Demonstrates all `OpenAIAssistantProvider` methods: `create_agent()`, `get_agent()`, and `as_agent()`. |
| [`openai_assistants_with_code_interpreter.py`](openai_assistants_with_code_interpreter.py) | Using `HostedCodeInterpreterTool` with `OpenAIAssistantProvider` to execute Python code. |
| [`openai_assistants_with_code_interpreter.py`](openai_assistants_with_code_interpreter.py) | Using `OpenAIAssistantsClient.get_code_interpreter_tool()` with `OpenAIAssistantProvider` to execute Python code. |
| [`openai_assistants_with_existing_assistant.py`](openai_assistants_with_existing_assistant.py) | Working with pre-existing assistants using `get_agent()` and `as_agent()` methods. |
| [`openai_assistants_with_explicit_settings.py`](openai_assistants_with_explicit_settings.py) | Configuring `OpenAIAssistantProvider` with explicit settings including API key and model ID. |
| [`openai_assistants_with_file_search.py`](openai_assistants_with_file_search.py) | Using `HostedFileSearchTool` with `OpenAIAssistantProvider` for file search capabilities. |
| [`openai_assistants_with_file_search.py`](openai_assistants_with_file_search.py) | Using `OpenAIAssistantsClient.get_file_search_tool()` with `OpenAIAssistantProvider` for file search capabilities. |
| [`openai_assistants_with_function_tools.py`](openai_assistants_with_function_tools.py) | Function tools with `OpenAIAssistantProvider` at both agent-level and query-level. |
| [`openai_assistants_with_response_format.py`](openai_assistants_with_response_format.py) | Structured outputs with `OpenAIAssistantProvider` using Pydantic models. |
| [`openai_assistants_with_thread.py`](openai_assistants_with_thread.py) | Thread management with `OpenAIAssistantProvider` for conversation context persistence. |
@@ -20,24 +20,25 @@ This folder contains examples demonstrating different ways to create and use age
| [`openai_chat_client_with_function_tools.py`](openai_chat_client_with_function_tools.py) | Demonstrates how to use function tools with agents. Shows both agent-level tools (defined when creating the agent) and query-level tools (provided with specific queries). |
| [`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_web_search.py`](openai_chat_client_with_web_search.py) | Shows how to use `OpenAIChatClient.get_web_search_tool()` for web search capabilities with OpenAI agents. |
| [`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 `Agent` 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. |
| [`openai_responses_client_image_generation.py`](openai_responses_client_image_generation.py) | Demonstrates how to use `OpenAIResponsesClient.get_image_generation_tool()` to create images based on text descriptions. |
| [`openai_responses_client_reasoning.py`](openai_responses_client_reasoning.py) | Demonstrates how to use reasoning capabilities with OpenAI agents, showing how the agent can provide detailed reasoning for its responses. |
| [`openai_responses_client_streaming_image_generation.py`](openai_responses_client_streaming_image_generation.py) | Demonstrates streaming image generation with partial images for real-time image creation feedback and improved user experience. |
| [`openai_responses_client_with_agent_as_tool.py`](openai_responses_client_with_agent_as_tool.py) | Shows how to use the agent-as-tool pattern with OpenAI Responses Client, where one agent delegates work to specialized sub-agents wrapped as tools using `as_tool()`. Demonstrates hierarchical agent architectures. |
| [`openai_responses_client_with_code_interpreter.py`](openai_responses_client_with_code_interpreter.py) | Shows how to use the HostedCodeInterpreterTool with OpenAI agents to write and execute Python code. Includes helper methods for accessing code interpreter data from response chunks. |
| [`openai_responses_client_with_code_interpreter.py`](openai_responses_client_with_code_interpreter.py) | Shows how to use `OpenAIResponsesClient.get_code_interpreter_tool()` to write and execute Python code. |
| [`openai_responses_client_with_code_interpreter_files.py`](openai_responses_client_with_code_interpreter_files.py) | Shows how to use code interpreter with uploaded files for data analysis. |
| [`openai_responses_client_with_explicit_settings.py`](openai_responses_client_with_explicit_settings.py) | Shows how to initialize an agent with a specific responses client, configuring settings explicitly including API key and model ID. |
| [`openai_responses_client_with_file_search.py`](openai_responses_client_with_file_search.py) | Demonstrates how to use file search capabilities with OpenAI agents, allowing the agent to search through uploaded files to answer questions. |
| [`openai_responses_client_with_file_search.py`](openai_responses_client_with_file_search.py) | Demonstrates how to use `OpenAIResponsesClient.get_file_search_tool()` for searching through uploaded files. |
| [`openai_responses_client_with_function_tools.py`](openai_responses_client_with_function_tools.py) | Demonstrates how to use function tools with agents. Shows both agent-level tools (defined when creating the agent) and run-level tools (provided with specific queries). |
| [`openai_responses_client_with_hosted_mcp.py`](openai_responses_client_with_hosted_mcp.py) | Shows how to integrate OpenAI agents with hosted Model Context Protocol (MCP) servers, including approval workflows and tool management for remote MCP services. |
| [`openai_responses_client_with_hosted_mcp.py`](openai_responses_client_with_hosted_mcp.py) | Shows how to use `OpenAIResponsesClient.get_mcp_tool()` for hosted MCP servers, including approval workflows. |
| [`openai_responses_client_with_local_mcp.py`](openai_responses_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_responses_client_with_runtime_json_schema.py`](openai_responses_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_with_structured_output.py`](openai_responses_client_with_structured_output.py) | Demonstrates how to use structured outputs with OpenAI agents to get structured data responses in predefined formats. |
| [`openai_responses_client_with_thread.py`](openai_responses_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_responses_client_with_web_search.py`](openai_responses_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_responses_client_with_web_search.py`](openai_responses_client_with_web_search.py) | Shows how to use `OpenAIResponsesClient.get_web_search_tool()` for web search capabilities. |
## Environment Variables