@arizeai/phoenix-mcp

# Code Generation Agent Example ## Overview This folder contains examples for building a Code Generation (Code-Gen) agent using the LangChain library. This agent is designed to generate, refine, and validate code using OpenAI models. ## Features * Construction of a Code-Gen agent workflow using LangChain * Integration with OpenAI models for generating and refining code * Example usage of tools such as code analysis, execution, and generation * Auto-instrumentation with OpenInference decorators to fully instrument the agent * End-to-end tracing with Phoenix to track agent performance ## Requirements * LangChain library * OpenAI API key * Langgraph (for managing agent logic and workflows) * Python 3.x * Gradio (for UI) ## Installation If you are running this code from inside the `phoenix` repository, we recommend running it with `uv` to avoid dependency issues. 1. Install `uv` 2. Run `uv run --isolated --with-requirements requirements.txt python app.py` ## Usage 1. Run the `app.py` script to start the RAG agent. 2. Click on the local host link provided in the output. 3. Interact with the agent by entering prompts and receiving generated code responses. ## Files * `app.py`: The main script for starting the application, this will run the web server with default port(7860) * `agent.py`: The main script for the code generation agent * `tools.py`: Contains tools for code analysis, generation, execution, and merging * `requirements.txt`: Lists the required libraries for the project ## Notes * All the Key's must be inputted from the UI application. * This application will support the HTML based sources.