README.md•1.56 kB
# 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
1. Install the required libraries by running `pip install -r requirements.txt`
2. Run app.py and input the required Keys(OpenAI, Phoenix API Key)
## 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.