A curated list of awesome projects, resources, and tools for building stateful, multi-actor applications with LangGraph.

Welcome to Awesome LangGraph! This repository is your go-to resource for discovering tools, templates, and examples for building powerful AI applications with LangGraph. Whether you're just getting started or building production-ready systems, you'll find valuable resources to accelerate your development.

• Core Ecosystem
  • LangChain Ecosystem Overview
  • LangGraph Platform
• Official Resources
  • Starter Templates
  • Pre-built Agents
  • Example Applications
  • Tools & Integrations
    • Official Tools
    • Third-Party Packages
• Community Projects
  • Pre-built Agents
  • AI Assistants
  • Development & Tools
  • Content & Media
  • Knowledge & Retrieval
  • Finance & Business
  • Sustainability
• Learning Resources
  • Courses
  • Tutorials & Examples
• Companies Using LangGraph
• Contributing
• Acknowledgments

LangGraph extends the LangChain ecosystem to provide flexible orchestration for LLM-powered systems. The ecosystem consists of several key components working together to support the entire LLM application lifecycle:

The LangGraph Platform provides tools and services for building, deploying, and managing production-grade applications:

Templates to help you get started with LangGraph. For deployment instructions, check out the LangGraph CLI Documentation.

LangGraph comes with a built-in React agent pattern, and the community has developed numerous additional agent libraries. Below are some of the most popular community-built options that extend LangGraph's functionality in various ways.

These are the official agents provided and maintained by LangGraph:

These applications demonstrate real-world implementations using LangGraph. From chatbots to content generation, each example showcases different patterns and best practices for building production-ready systems and can be deployed with LanGraph Cloud.

You can use these as reference architectures or starting points for your own projects.

LangGraph provides official development tools to streamline your workflow, from visual design to code generation. These tools help you build and deploy LangGraph applications more efficiently.

• LangGraph Builder – Visual canvas for designing cognitive architectures of LangGraph applications with code generation for Python and TypeScript
• LangGraph Generator – CLI tool for generating LangGraph application stubs from YAML specifications

Ready-to-use integrations for extending LangGraph with external services and tools. Access everything from LLMs, vector stores to databases to development tools.

🔗 Python Packages | 🔗 JavaScript Packages

This is a curated list of open-source agent and LLM projects. They are grouped by category for easier discovery.

• TrustCall - Tenacious tool calling built on LangGraph GitHub stars
• Data Science Team - AI-powered data science team for common tasks GitHub stars
• Delve - A taxonomy generator for unstructured data GitHub stars
• Nodeology - Enable researcher to build scientific workflows easily with simplified interface GitHub stars
• Breeze Agent - A streamlined research system built inspired on STORM and built on LangGraph GitHub stars

Want to contribute your own pre-built agent? Check out the contribution guidelines in the documentation.

• AI-Data-Analysis-MultiAgent – Multi-agent system for data analysis, visualization, and report generation. GitHub stars
• AI Coding Assistant – Development tool that uses LangGraph agents to aid coding workflow with natural language. GitHub stars
• Brainstormers – Tool with curated, optimized chains for brainstorming using real-world techniques. GitHub stars
• Clevrr Computer – Automation agent for basic computer tasks with a focus on safety and accuracy. GitHub stars
• ContentMind AI – Turns websites into LLM-ready research content with automated documentation indexing. GitHub stars
• CopilotKit – Framework for building AI copilots with generative UI, chat interfaces, and human-in-the-loop capabilities GitHub stars
• RD-Agent – Microsoft's R&D automation tool for data mining, paper analysis, and model tuning. GitHub stars
• WebRover – Autonomous AI agent for automating web tasks and research. GitHub stars
• AI Conversation Simulator – Test and develop AI assistants through simulated conversations with configurable personas and LangSmith integration GitHub stars
• SurfSense – Customizable AI research agent that integrates personal knowledge bases with external sources like Tavily, Slack, and Notion GitHub stars
• RAI – Flexible multi-agent framework for developing and deploying Embodied AI features in robotics with multi-modal interaction support GitHub stars

• AI Agent Service Toolkit – Framework for deploying AI agents with FastAPI and Streamlit. GitHub stars
• Browser Use: Web AI – Library for AI agents to interact with websites and automate web tasks. GitHub stars
• Khoj – Self-hostable AI second brain for web or docs with custom agents. GitHub stars
• Hyperbolic-AgentKit – AI agent framework with blockchain and compute features. GitHub stars
• Agent Protocol – Codified, framework-agnostic APIs for serving LLM agents in production. GitHub stars
• SRAgent – Multi-agent framework for automating genomic research and RNA sequencing workflows from scientific databases. GitHub stars
• Google GenAI Toolbox – Production-grade infrastructure for connecting AI agents with databases, featuring security, observability, and connection pooling GitHub stars

• AgentWrite – Automated content generation tool that breaks down writing tasks. GitHub stars
• Podcastfy.ai – Transforms multi-modal content into audio conversations in multiple languages. GitHub stars
• Robo-blogger – Voice-to-content pipeline for converting spoken ideas into structured blog posts. GitHub stars
• Social Media Agent – Generates Twitter & LinkedIn posts from URLs with optional human review. GitHub stars
• YT Navigator – AI-powered tool for efficient navigation and search through YouTube channel content GitHub stars

• bRAG – Tutorial series on RAG (Retrieval Augmented Generation) from basics to advanced. GitHub stars
• Demo Bank Support Bot – RAG-powered banking support chatbot designed to prevent hallucinations. GitHub stars
• Denser Chat – Chatbot that answers questions from PDFs and webpages with text extraction. GitHub stars
• IdentityRAG Insights – Chatbot that merges customer data into golden records for context-aware replies. GitHub stars
• King RAGent – AI research assistant with PDF processing, vector storage, and web search integration. GitHub stars
• Reply gAI – AI clone for X/Twitter profiles with long-term memory and RAG. GitHub stars
• Shandu – LLM-based research system that automates source evaluation and knowledge synthesis. GitHub stars
• Local Deep Research – Privacy-focused research assistant performing deep analysis using multiple LLMs and web searches with local execution capability GitHub stars
• GPT Researcher – Open deep research agent producing detailed reports with citations, using Plan-and-Solve and RAG techniques GitHub stars

• GreenMe – AI sustainability guide that analyzes lifestyle for carbon footprint reduction. GitHub stars

• Introduction to LangGraph - Official course covering fundamentals and practical use cases.
• LangGraph - Develop LLM powered AI agents - Course on building AI agents with LangGraph by @emarco177

• GenAI_Agents - Agent implementation examples GitHub stars
• RAG_Techniques - Several RAG implementations and tutorials GitHub stars
• Grounding RAG Applications Workshop - Hands-on workshop building RAG chatbots and travel planning agents with JavaScript and Elasticsearch GitHub stars

A comprehensive list of organizations using LangGraph in production environments. For more details and case studies, visit the official adopters page.

We welcome contributions to this awesome list! Please ensure your submission:

• Includes a clear description of its purpose and value
• Follows the existing format and style
• Is placed in the appropriate category

To contribute:

1. Fork the repository
2. Add your project following the established format
3. Create a pull request with a brief explanation

For questions or suggestions, please open an issue.

Special thanks to the @langchain-ai team for building such an amazing framework and ecosystem that enables developers to create powerful AI applications.

This list is inspired by awesome-langchain, which has been a great resource for the community.