Generate Project README using LangGraph is an AWS sample tool showcasing how to build AI-powered documentation generators with LangGraph, an innovative graph-based AI workflow framework. It traverses your project files, understands code structures, dependencies, and usage patterns, then automatically generates a clear, organized README in Markdown. By integrating LangGraph’s customizable nodes, developers define workflows that extract module descriptions, code examples, installation instructions, and contribution guidelines. The output supports multiple templates for different languages and frameworks. Users can extend the workflow with custom prompts, connectors, and template engines. This sample streamlines onboarding for new contributors, ensures consistent documentation across repositories, and can be integrated into CI/CD pipelines to auto-update READMEs on code changes.

This starter project provides a ready-to-use FastAPI application preconfigured for AI agent development. It uses Pydantic for request/response validation, environment-based configuration for OpenAI API keys, and modular endpoint scaffolding. Built-in features include Swagger UI docs, CORS handling, and structured logging, enabling teams to rapidly prototype and deploy AI-driven endpoints without boilerplate overhead. Developers simply define Pydantic models and agent functions to get a production-ready API server.