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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.
+
+## Examples
+
+| File | Description |
+|------|-------------|
+| [`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_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_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. |
+| [`openai_chat_client_basic.py`](openai_chat_client_basic.py) | The simplest way to create an agent using `ChatAgent` with `OpenAIChatClient`. Shows both streaming and non-streaming responses for chat-based interactions with OpenAI models. |
+| [`openai_chat_client_with_explicit_settings.py`](openai_chat_client_with_explicit_settings.py) | Shows how to initialize an agent with a specific chat client, configuring settings explicitly including API key and model ID. |
+| [`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_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. |
+| [`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_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_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_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. |
+
+## Environment Variables
+
+Make sure to set the following environment variables before running the examples:
+
+- `OPENAI_API_KEY`: Your OpenAI API key
+- `OPENAI_CHAT_MODEL_ID`: The OpenAI model to use (e.g., `gpt-4o`, `gpt-4o-mini`, `gpt-3.5-turbo`)
+- `OPENAI_RESPONSES_MODEL_ID`: The OpenAI model to use (e.g., `gpt-4o`, `gpt-4o-mini`, `gpt-3.5-turbo`)
+- For image processing examples, use a vision-capable model like `gpt-4o` or `gpt-4o-mini`
+
+Optionally, you can set:
+- `OPENAI_ORG_ID`: Your OpenAI organization ID (if applicable)
+- `OPENAI_API_BASE_URL`: Your OpenAI base URL (if using a different base URL)
+
+## Optional Dependencies
+
+Some examples require additional dependencies:
+
+- **Image Generation Example**: The `openai_responses_client_image_generation.py` example requires PIL (Pillow) for image display. Install with:
+  ```bash
+  # Using uv
+  uv add pillow
+
+  # Or using pip
+  pip install pillow
+  ```