
awesome-LangGraph
A curated list of awesome projects, resources, and tools for building stateful, multi-actor applications with LangGraph π¦πΈοΈ
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Awesome LangGraph is a curated list of projects, resources, and tools for building stateful, multi-actor applications with LangGraph. It provides valuable resources for developers at all stages of development, from beginners to those building production-ready systems. The repository covers core ecosystem components, LangChain ecosystem, LangGraph platform, official resources, starter templates, pre-built agents, example applications, development tools, community projects, AI assistants, content & media, knowledge & retrieval, finance & business, sustainability, learning resources, companies using LangGraph, contributing guidelines, and acknowledgments.
README:
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
- Official Resources
- Community Projects
- Learning Resources
- 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:

Source: LangChain Documentation
LangChain
- Foundation framework for LLM application development
- Provides standardized interfaces for LLMs and related technologies
- Includes extensive integrations with embedding models and vector stores
- Features reusable components for chains, agents, and memory systems
π Documentation: Python | TypeScript
LangGraph
- Built on top of LangChain for advanced workflow orchestration
- Enables building stateful, multi-agent systems
- Provides first-class streaming support
- Includes built-in human-in-the-loop capabilities
- Supports complex agent interactions and coordination
π Documentation: LangGraph Docs | TypeScript Docs
LangSmith
- Comprehensive observability and debugging platform
- Debugging and testing tools
- Playground for experimentation
- Prompt management and versioning
- Annotation and evaluation
- Performance monitoring
- Testing automation
π Documentation: LangSmith Platform | LangSmith Docs
LangGraph Platform
- Production deployment and management solution
- API generation for LangGraph applications
- Deployment automation
- Scaling infrastructure
- Production monitoring
π Documentation: Platform Overview
More details about the platform components and features in the section below.
The LangGraph Platform provides tools and services for building, deploying, and managing production-grade applications:

Source: LangGraph Platform Documentation
LangGraph Server
- Opinionated API architecture for deploying agentic applications
- Built-in support for streaming, background runs, and task queues
- Horizontally scalable infrastructure
- Integrated monitoring with LangSmith
π Documentation: Server Docs
LangGraph Studio
- Visual IDE for development and debugging
- Real-time graph visualization
- Interactive testing environment
- Integrated debugging tools
π Documentation: Studio Docs
LangGraph CLI
- Command-line interface for local development
- Project scaffolding and management
- Deployment automation
- Configuration management
π Documentation: CLI Docs
LangGraph SDK
- Core development toolkit
- Graph construction and management
- State management utilities
- Integration helpers
π Documentation: SDK Docs
Remote Graph
- Remote execution of deployed applications
- Seamless integration with deployed servers
- State synchronization
- Distributed execution support
π Documentation: Remote Graph Guide
Official templates, tools, and libraries maintained by LangChain and LangGraph teams.
Templates to help you get started with LangGraph. For deployment instructions, check out the LangGraph CLI Documentation.
Template | Description | ||
---|---|---|---|
New Project | Basic chatbot with memory | langchain-ai/new-langgraph-project | langchain-ai/new-langgraphjs-project |
ReAct Agent | Tool-using agent framework | langchain-ai/react-agent | langchain-ai/react-agent-js |
Memory Agent | Cross-thread memory persistence | langchain-ai/memory-agent | langchain-ai/memory-agent-js |
Retrieval Agent | Knowledge-based QA system | langchain-ai/retrieval-agent-template | langchain-ai/retrieval-agent-template-js |
Data Enrichment | Web search & data organization | langchain-ai/data-enrichment | langchain-ai/data-enrichment-js |
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:
Agent | Description | ||
---|---|---|---|
Computer Use Agent | Agent for automating computer interactions and tasks | langgraph-cua-py | langgraph-cua |
Swarm Agent | Build swarm-style multi-agent systems | langgraph-swarm-py | langgraph-swarm |
Supervisor | Build supervisor multi-agent systems | langgraph-supervisor-py | langgraph-supervisor |
MCP Adapters | Make Anthropic MCP tools compatible with agents | langchain-mcp-adapters | β |
LangMem | Agents that learn and adapt from interactions | langmem | β |
CodeAct | Advanced function-calling with code generation | langgraph-codeact | β |
Reflection | Agent architecture with self-review capabilities | langgraph-reflection | β |
BigTool | Build agents with large numbers of tools | langgraph-bigtool | β |
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.
Name | Description |
---|---|
Open Agent Platform |
No-code platform for building customizable agents with MCP tools integration, LangConnect RAG support, and multi-agent supervision capabilities. Features a modern web interface and pre-built agent templates. |
LangConnect |
Managed RAG service with FastAPI and PostgreSQL/pgvector integration, featuring document collection management, semantic search, and Docker deployment support. |
ChatLangChain |
Documentation assistant powered by RAG-based semantic search with intelligent query analysis. Features automated content indexing, duplicate prevention, GenUI, and sophisticated document tracking system. |
OpenGPTs |
Open-source GPT alternative supporting 60+ LLM providers and tools. Implements three cognitive architectures (Assistant, RAG, Chatbot) with PostgreSQL backend and flexible deployment options. |
Executive AI Assistant |
Smart email management system with calendar integration. Provides intelligent triage, automated response drafting, and meeting coordination through Gmail API with customizable workflows. |
Agent Inbox |
Centralized interface for AI agent interactions featuring real-time communication, interrupt handling, and configurable response systems for both local and cloud deployments. |
Python Fullstack |
All-in-one chatbot template combining React-style agents with modern UI. Built with FastHTML components and Claude 3, featuring single-deployment architecture and extensible tools. |
LangGraph UI Examples |
Showcase of generative UI agents including stockbroker, trip planner, and email tools. Demonstrates human-in-the-loop workflows with customizable components and tool integrations. |
LangChain Next.js |
Next.js starter template showcasing LangChain.js modules. Includes streaming chat, structured output, multi-step agents, and RAG implementations with Vercel AI SDK integration. |
Custom Auth |
Supabase-powered authentication template for LangGraph deployments. Implements OAuth2 with Google, user management, and secure chatbot access with conversation thread isolation. |
Gen UI Computer Use |
A Generative UI web app for interacting with Computer Use Agents (CUA) via the @langchain/langgraph-cua prebuilt package. Features a modern interface for computer automation and task management. |
Multi-Modal Researcher |
Research and podcast generation workflow using LangGraph with Gemini 2.5 model family. Features video understanding, Google search integration, and multi-speaker text-to-speech for creating comprehensive research reports and audio podcasts. |
Deep Agents UI |
Next.js interface for Deep Agents with streaming support and LangGraph Platform integration. Generic AI agents capable of handling tasks of varying complexity with customizable UI components. |
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 β Visual canvas for designing cognitive architectures of LangGraph applications with code generation for Python and TypeScript
- LangGraph Generator β CLI tool for generating LangGraph application stubs from YAML specifications
Access official documentation in LLM-readable formats, enabling LLMs and agents to understand and work with the frameworks, particularly within integrated development environments (IDEs). Learn more in the official documentation.
Framework | Index File | Full Documentation |
---|---|---|
LangGraph Python | llms.txt | llms-full.txt |
LangGraph JS | llms.txt | llms-full.txt |
LangChain Python | llms.txt | - |
LangChain JS | llms.txt | - |
The llms.txt
files serve as lightweight indexes for quick reference, while llms-full.txt
provides comprehensive documentation for deeper understanding and integration.
Ready-to-use integrations for extending LangGraph with external services and tools. Access everything from LLMs, vector stores to databases to development tools.
π Python Packages | π 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
-
Data Science Team - AI-powered data science team for common tasks
-
Delve - A taxonomy generator for unstructured data
-
Nodeology - Enable researcher to build scientific workflows easily with simplified interface
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Breeze Agent - A streamlined research system built inspired on STORM and built on LangGraph
Want to contribute your own pre-built agent? Check out the contribution guidelines in the documentation.
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LlamaBot β Web development coding agent that helps create HTML/CSS/JavaScript projects, featuring game creation, portfolio websites, and business landing pages with LangGraph orchestration.
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DeerFlow β Community-driven deep research framework combining language models with specialized tools for web search, crawling, and Python execution, featuring interactive research planning and human-in-the-loop capabilities.
-
Telegram Link Summarizer Agent β Agentic Telegram bot that summarizes links (articles, papers, tweets, LinkedIn posts, PDFs) shared in a channel using LangGraph orchestration, BAML integration, and multi-tool content extraction.
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Voice File Agent β Voice-controlled file management system using LangGraph's ReAct agent, featuring natural language commands, OpenAI transcription, and ElevenLabs voice feedback.
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Tavily Meeting Prep Agent β Advanced meeting preparation system combining calendar integration, real-time web search, and profile research capabilities with MCP and ReAct agent flows.
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AI-Data-Analysis-MultiAgent β Multi-agent system for data analysis, visualization, and report generation.
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AI Coding Assistant β Development tool that uses LangGraph agents to aid coding workflow with natural language.
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Brainstormers β Tool with curated, optimized chains for brainstorming using real-world techniques.
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Clevrr Computer β Automation agent for basic computer tasks with a focus on safety and accuracy.
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ContentMind AI β Turns websites into LLM-ready research content with automated documentation indexing.
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CopilotKit β Framework for building AI copilots with generative UI, chat interfaces, and human-in-the-loop capabilities
-
RD-Agent β Microsoft's R&D automation tool for data mining, paper analysis, and model tuning.
-
WebRover β Autonomous AI agent for automating web tasks and research.
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AI Conversation Simulator β Test and develop AI assistants through simulated conversations with configurable personas and LangSmith integration
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SurfSense β Customizable AI research agent that integrates personal knowledge bases with external sources like Tavily, Slack, and Notion
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RAI β Flexible multi-agent framework for developing and deploying Embodied AI features in robotics with multi-modal interaction support
-
Open Multi-Agent Canvas β Dynamic chat interface for managing multiple agents in one conversation, featuring travel planning and research capabilities through MCP servers, built with Next.js and LangGraph.
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InboxHero β Smart email management assistant built with LangGraph that prioritizes messages, reads attachments, and drafts replies using ChatGroq, featuring interactive chat mode and customizable time frames.
-
Multi-Agent Medical Assistant β AI-powered multi-agent system for medical diagnosis, research, and patient interaction, featuring LLMs, RAG, and human-in-the-loop validation.
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LangGraph WhatsApp Agent β Template for building scalable WhatsApp AI agents with LangGraph, supporting multi-agent systems, image processing, and MCP integration.
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Voice Agent Base β Voice-enabled AI agent application with React interface, featuring speech-to-text via OpenAI Whisper, text-to-speech via ElevenLabs, and web search capabilities through Tavily integration.
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AI Agent Smart Assist β LangChain-powered AI agent for text classification, knowledge base management, and intelligent Q&A. Features document ingestion with FAISS vector storage, smart text routing, and RAG-style question answering with a modern Next.js frontend and FastAPI backend.
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Synapse Workflows β Multi-agent platform with three specialized AI agents: Smart Search Agent for real-time web search, Productivity Assistant for task automation, and Data Analysis Agent for dataset insights and visualization.
-
ChuanhuChatGPT β Comprehensive GUI for ChatGPT API and multiple LLMs with agent support, file-based QA, web search integration, and GPT fine-tuning capabilities. Features auto-naming conversations, knowledge base functionality, and beautiful UI with PWA support.
-
Agentic AI Browser β AI-driven web automation agent emphasizing intelligent design over brute force, featuring behavioral caching, DOM-based task fidelity, success pattern recording, and single-agent architecture for efficient browser automation.
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SWE Agent β AI-powered software engineering multi-agent system featuring researcher and developer agents that automate code implementation through intelligent planning, execution, and atomic task breakdown with LangGraph workflows.
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ARMA β Azure Resource Management Assistant built with LangGraph and LangChain, featuring multi-agent architecture for Azure resource provisioning, ARM template validation, and comprehensive resource management with Streamlit UI.
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ScienceBridge β AI-powered scientific research accelerator that autonomously analyzes datasets, generates hypotheses, and validates them through code, featuring ML model integration and automated visualization.
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AI Agent Service Toolkit β Framework for deploying AI agents with FastAPI and Streamlit.
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Browser Use: Web AI β Library for AI agents to interact with websites and automate web tasks.
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Khoj β Self-hostable AI second brain for web or docs with custom agents.
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Hyperbolic-AgentKit β AI agent framework with blockchain and compute features.
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Agent Protocol β Codified, framework-agnostic APIs for serving LLM agents in production.
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SRAgent β Multi-agent framework for automating genomic research and RNA sequencing workflows from scientific databases.
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Google GenAI Toolbox β Production-grade infrastructure for connecting AI agents with databases, featuring security, observability, and connection pooling
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LangGraph MCP Agents β Toolkit for integrating Model Context Protocol (MCP) with LangGraph agents, featuring Streamlit interface, dynamic tool management, and real-time streaming responses.
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LangManus β Community-driven AI automation framework combining language models with specialized tools for web search, crawling, and Python code execution.
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FastAPI LangGraph Agent Template β Production-ready FastAPI template for building AI agent applications with LangGraph integration, featuring high-performance async API endpoints, LLM observability, structured logging, PostgreSQL persistence, Docker support, and comprehensive security features.
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Ryoma β AI-powered data agent framework for data analysis, engineering, and visualization, combining LangChain, Reflex, Apache Arrow, and more.
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FastAPI MCP LangGraph Template β Production-ready FastAPI template integrating LangGraph and MCP for agent orchestration, streaming UX, and database persistence.
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ScrapeCraft β AI-powered web scraping editor with visual workflow builder using LangGraph and ScrapeGraphAI. Features natural language scraping pipeline creation, multi-URL bulk scraping, and real-time WebSocket streaming with Docker deployment.
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DeepMCPAgent β Model-agnostic LangChain/LangGraph agent framework powered entirely by MCP tools over HTTP/SSE. Features plug-and-play architecture, dynamic tool discovery, and support for both DeepAgents and ReAct patterns with comprehensive observability.
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AgentWrite β Automated content generation tool that breaks down writing tasks.
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Podcastfy.ai β Transforms multi-modal content into audio conversations in multiple languages.
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Robo-blogger β Voice-to-content pipeline for converting spoken ideas into structured blog posts.
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Social Media Agent β Generates Twitter & LinkedIn posts from URLs with optional human review.
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YT Navigator β AI-powered tool for efficient navigation and search through YouTube channel content
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AI-Powered Podcast Creation β Automated workflow for creating engaging podcasts from academic texts using AI agents, featuring content summarization, script writing, and self-improving prompt optimization based on user feedback.
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News Agent β AI-powered news aggregation agent that provides personalized daily news summaries using Tavily web crawling. Features adaptive learning from user preferences, memory-based personalization, and intelligent content curation.
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Agentic-Qdrant-RAG β Agentic RAG system demonstrating LangGraph integration with Qdrant vector database for intelligent document retrieval and complex query processing.
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II-Researcher β Powerful deep search agent using BAML functions for intelligent web searches, featuring multi-provider web scraping, multi-step reasoning, and asynchronous operations with Tavily/SerpAPI integration.
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RAG Challenge Winner β State-of-the-art RAG implementation featuring custom PDF parsing, vector search with parent retrieval, LLM reranking, and chain-of-thought reasoning for company report analysis.
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RAGLight β Lightweight and modular Python library for implementing Retrieval-Augmented Generation (RAG), Agentic RAG, and RAT (Retrieval Augmented Thinking). Features multi-provider LLM support (Ollama, LMStudio, OpenAI, Mistral), flexible embedding models, and both simple and agentic pipeline architectures.
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Local Chat RAG β Privacy-first RAG chat application with local LLM support via Ollama, featuring document parsing, source citations, and a modern React frontend.
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Company Research Agent β Multi-agent system for comprehensive company research using Gemini 2.0 Flash and GPT-4.1, featuring real-time progress streaming, AI-powered content filtering, and modular research pipeline.
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bRAG β Tutorial series on RAG (Retrieval Augmented Generation) from basics to advanced.
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DeepGit β Advanced LangGraph-based agentic workflow for intelligent GitHub repository discovery, featuring hybrid dense retrieval, cross-encoder re-ranking, and comprehensive activity analysis.
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AI PDF Chatbot β Customizable template for building AI chatbots that process PDF documents using LangChain and LangGraph, featuring document ingestion, vector storage, and streaming responses.
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Demo Bank Support Bot β RAG-powered banking support chatbot designed to prevent hallucinations.
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Denser Chat β Chatbot that answers questions from PDFs and webpages with text extraction.
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IdentityRAG Insights β Chatbot that merges customer data into golden records for context-aware replies.
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King RAGent β AI research assistant with PDF processing, vector storage, and web search integration.
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Reply gAI β AI clone for X/Twitter profiles with long-term memory and RAG.
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Shandu β LLM-based research system that automates source evaluation and knowledge synthesis.
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Local Deep Research β Privacy-focused research assistant performing deep analysis using multiple LLMs and web searches with local execution capability
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GPT Researcher β Open deep research agent producing detailed reports with citations, using Plan-and-Solve and RAG techniques
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Curie - Research Experimentation Agent - AI research agent to automate rigorous scientific experimentation and produce meaningful empirical results, driving discovery across ML, systems & more.
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LangConnect-Client β Streamlit-based RAG client with comprehensive document management and vector search capabilities. Features semantic/hybrid search, multi-format support (PDF/DOCX/MD), Supabase authentication, and MCP integration for AI assistants with PostgreSQL/pgvector backend.
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Local Deep Search Academic β Academic research assistant that automates paper discovery using Semantic Scholar API, intelligent filtering, and RAPTOR indexing. Features conversational QA with local LLMs and professional report generation from research sessions.
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Marketing Analyst Agent β AI-powered marketing analysis system built with LangChain, featuring market trend forecasting, sentiment analysis, campaign evaluation, and automated report generation with strategic recommendations.
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AI Case Study Analyzer - Discovers and analyzes enterprise AI case studies.
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AI Hedge Fund - Six AI agents collaborating through LangChain for smart trading decisions.
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gotoHuman Lead Agent - AI-powered sales solution for automated personalized email drafting with human oversight.
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AI Bank Statement Document Automation β Automated bank statement processing system using LLM models for document extraction, RAG techniques, and personal financial analysis. Features OCR, computer vision, and multi-agent workflows for converting unstructured PDF documents into structured data with natural language querying capabilities.
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DeepAgents Stock Research β AI-powered stock research assistant using LangChain DeepAgents with specialized sub-agents for fundamental, technical, and risk analysis. Features real-time data integration, systematic research workflows, and professional investment reports with price targets.
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AI IPO Analyst β Custom research AI agent for analyzing Indian IPOs using DRHP documents. Features automated PDF parsing, financial statement extraction, web-enabled market data enrichment, and comprehensive investment analysis reports with Streamlit interface.
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GreenMe β AI sustainability guide that analyzes lifestyle for carbon footprint reduction.
Official courses from LangChain Academy for learning LangGraph and related technologies:
- Foundation: Introduction to LangGraph - Learn the basics of LangGraph framework for building agentic and multi-agent applications. Covers motivation, simple graphs, chains, routers, agents, state management, memory, streaming, and deployment.
- Project: Building Ambient Agents with LangGraph - Build your own ambient agent to manage email. Learn LangGraph fundamentals while building an email assistant from scratch, including agent evaluations and LangSmith integration.
- Project: Deep Research with LangGraph - Build your own deep research agent to handle research tasks. Learn how to use LangGraph to build a multi-agent system with research agents, MCP integration, and research supervisors.
- Foundation: Introduction to Agent Observability & Evaluations - Learn essentials of agent observability and evaluations with LangSmith. Covers tracing, testing, evaluation, prompt engineering, human feedback collection, and production monitoring.
- LangGraph - Develop LLM powered AI agents - Course on building AI agents with LangGraph by @emarco177
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Ava WhatsApp Agent - Course on building a WhatsApp agent with LangGraph, featuring voice processing, image generation, and long-term memory.
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GenAI Agents - Agent implementation examples
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RAG Techniques - Several RAG implementations and tutorials
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Grounding RAG Applications Workshop - Hands-on workshop building RAG chatbots and travel planning agents with JavaScript and Elasticsearch
A comprehensive list of organizations using LangGraph in production environments. For more details and case studies, visit the official adopters page.
Company | Industry | Use Case | Reference |
---|---|---|---|
Social Media | Code generation; Search & discovery | Blog post, 2025 | |
Uber | Transportation | Developer productivity; Code generation | Presentation, 2024 |
GitLab | Software & Technology | Code generation | Duo workflow docs |
Klarna | Fintech | Copilot for domain-specific task | Case study, 2025 |
Rakuten | E-commerce / Fintech | Copilot for domain-specific task | Blog post, 2025 |
Minimal | E-commerce | Customer support | Case study, 2025 |
Komodo Health | Healthcare | Copilot for domain-specific task | Blog post |
OpenRecovery | Healthcare | Copilot for domain-specific task | Case study, 2024 |
AppFolio | Real Estate | Copilot for domain-specific task | Case study, 2024 |
Cisco Outshift | Software & Technology | DevOps | Blog post, 2025 |
Elastic | Software & Technology | Copilot for domain-specific task | Blog post, 2025 |
Infor | Software & Technology | GenAI embedded product experiences; customer support; copilot | Case study, 2025 |
AirTop | Software & Technology (GenAI Native) | Browser automation for AI agents | Case study, 2024 |
Athena Intelligence | Software & Technology (GenAI Native) | Research & summarization | Case study, 2024 |
Captide | Software & Technology (GenAI Native) | Data extraction | Case study, 2025 |
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:
- Fork the repository
- Add your project following the established format
- 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.
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Awesome LangGraph is a curated list of projects, resources, and tools for building stateful, multi-actor applications with LangGraph. It provides valuable resources for developers at all stages of development, from beginners to those building production-ready systems. The repository covers core ecosystem components, LangChain ecosystem, LangGraph platform, official resources, starter templates, pre-built agents, example applications, development tools, community projects, AI assistants, content & media, knowledge & retrieval, finance & business, sustainability, learning resources, companies using LangGraph, contributing guidelines, and acknowledgments.

Flowise
Flowise is a tool that allows users to build customized LLM flows with a drag-and-drop UI. It is open-source and self-hostable, and it supports various deployments, including AWS, Azure, Digital Ocean, GCP, Railway, Render, HuggingFace Spaces, Elestio, Sealos, and RepoCloud. Flowise has three different modules in a single mono repository: server, ui, and components. The server module is a Node backend that serves API logics, the ui module is a React frontend, and the components module contains third-party node integrations. Flowise supports different environment variables to configure your instance, and you can specify these variables in the .env file inside the packages/server folder.

nlux
nlux is an open-source Javascript and React JS library that makes it super simple to integrate powerful large language models (LLMs) like ChatGPT into your web app or website. With just a few lines of code, you can add conversational AI capabilities and interact with your favourite LLM.

generative-ai-go
The Google AI Go SDK enables developers to use Google's state-of-the-art generative AI models (like Gemini) to build AI-powered features and applications. It supports use cases like generating text from text-only input, generating text from text-and-images input (multimodal), building multi-turn conversations (chat), and embedding.

awesome-langchain-zh
The awesome-langchain-zh repository is a collection of resources related to LangChain, a framework for building AI applications using large language models (LLMs). The repository includes sections on the LangChain framework itself, other language ports of LangChain, tools for low-code development, services, agents, templates, platforms, open-source projects related to knowledge management and chatbots, as well as learning resources such as notebooks, videos, and articles. It also covers other LLM frameworks and provides additional resources for exploring and working with LLMs. The repository serves as a comprehensive guide for developers and AI enthusiasts interested in leveraging LangChain and LLMs for various applications.

Large-Language-Model-Notebooks-Course
This practical free hands-on course focuses on Large Language models and their applications, providing a hands-on experience using models from OpenAI and the Hugging Face library. The course is divided into three major sections: Techniques and Libraries, Projects, and Enterprise Solutions. It covers topics such as Chatbots, Code Generation, Vector databases, LangChain, Fine Tuning, PEFT Fine Tuning, Soft Prompt tuning, LoRA, QLoRA, Evaluate Models, Knowledge Distillation, and more. Each section contains chapters with lessons supported by notebooks and articles. The course aims to help users build projects and explore enterprise solutions using Large Language Models.

ai-chatbot
Next.js AI Chatbot is an open-source app template for building AI chatbots using Next.js, Vercel AI SDK, OpenAI, and Vercel KV. It includes features like Next.js App Router, React Server Components, Vercel AI SDK for streaming chat UI, support for various AI models, Tailwind CSS styling, Radix UI for headless components, chat history management, rate limiting, session storage with Vercel KV, and authentication with NextAuth.js. The template allows easy deployment to Vercel and customization of AI model providers.

awesome-local-llms
The 'awesome-local-llms' repository is a curated list of open-source tools for local Large Language Model (LLM) inference, covering both proprietary and open weights LLMs. The repository categorizes these tools into LLM inference backend engines, LLM front end UIs, and all-in-one desktop applications. It collects GitHub repository metrics as proxies for popularity and active maintenance. Contributions are encouraged, and users can suggest additional open-source repositories through the Issues section or by running a provided script to update the README and make a pull request. The repository aims to provide a comprehensive resource for exploring and utilizing local LLM tools.
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promptflow
**Prompt flow** is a suite of development tools designed to streamline the end-to-end development cycle of LLM-based AI applications, from ideation, prototyping, testing, evaluation to production deployment and monitoring. It makes prompt engineering much easier and enables you to build LLM apps with production quality.

deepeval
DeepEval is a simple-to-use, open-source LLM evaluation framework specialized for unit testing LLM outputs. It incorporates various metrics such as G-Eval, hallucination, answer relevancy, RAGAS, etc., and runs locally on your machine for evaluation. It provides a wide range of ready-to-use evaluation metrics, allows for creating custom metrics, integrates with any CI/CD environment, and enables benchmarking LLMs on popular benchmarks. DeepEval is designed for evaluating RAG and fine-tuning applications, helping users optimize hyperparameters, prevent prompt drifting, and transition from OpenAI to hosting their own Llama2 with confidence.

MegaDetector
MegaDetector is an AI model that identifies animals, people, and vehicles in camera trap images (which also makes it useful for eliminating blank images). This model is trained on several million images from a variety of ecosystems. MegaDetector is just one of many tools that aims to make conservation biologists more efficient with AI. If you want to learn about other ways to use AI to accelerate camera trap workflows, check out our of the field, affectionately titled "Everything I know about machine learning and camera traps".

leapfrogai
LeapfrogAI is a self-hosted AI platform designed to be deployed in air-gapped resource-constrained environments. It brings sophisticated AI solutions to these environments by hosting all the necessary components of an AI stack, including vector databases, model backends, API, and UI. LeapfrogAI's API closely matches that of OpenAI, allowing tools built for OpenAI/ChatGPT to function seamlessly with a LeapfrogAI backend. It provides several backends for various use cases, including llama-cpp-python, whisper, text-embeddings, and vllm. LeapfrogAI leverages Chainguard's apko to harden base python images, ensuring the latest supported Python versions are used by the other components of the stack. The LeapfrogAI SDK provides a standard set of protobuffs and python utilities for implementing backends and gRPC. LeapfrogAI offers UI options for common use-cases like chat, summarization, and transcription. It can be deployed and run locally via UDS and Kubernetes, built out using Zarf packages. LeapfrogAI is supported by a community of users and contributors, including Defense Unicorns, Beast Code, Chainguard, Exovera, Hypergiant, Pulze, SOSi, United States Navy, United States Air Force, and United States Space Force.

llava-docker
This Docker image for LLaVA (Large Language and Vision Assistant) provides a convenient way to run LLaVA locally or on RunPod. LLaVA is a powerful AI tool that combines natural language processing and computer vision capabilities. With this Docker image, you can easily access LLaVA's functionalities for various tasks, including image captioning, visual question answering, text summarization, and more. The image comes pre-installed with LLaVA v1.2.0, Torch 2.1.2, xformers 0.0.23.post1, and other necessary dependencies. You can customize the model used by setting the MODEL environment variable. The image also includes a Jupyter Lab environment for interactive development and exploration. Overall, this Docker image offers a comprehensive and user-friendly platform for leveraging LLaVA's capabilities.

carrot
The 'carrot' repository on GitHub provides a list of free and user-friendly ChatGPT mirror sites for easy access. The repository includes sponsored sites offering various GPT models and services. Users can find and share sites, report errors, and access stable and recommended sites for ChatGPT usage. The repository also includes a detailed list of ChatGPT sites, their features, and accessibility options, making it a valuable resource for ChatGPT users seeking free and unlimited GPT services.

TrustLLM
TrustLLM is a comprehensive study of trustworthiness in LLMs, including principles for different dimensions of trustworthiness, established benchmark, evaluation, and analysis of trustworthiness for mainstream LLMs, and discussion of open challenges and future directions. Specifically, we first propose a set of principles for trustworthy LLMs that span eight different dimensions. Based on these principles, we further establish a benchmark across six dimensions including truthfulness, safety, fairness, robustness, privacy, and machine ethics. We then present a study evaluating 16 mainstream LLMs in TrustLLM, consisting of over 30 datasets. The document explains how to use the trustllm python package to help you assess the performance of your LLM in trustworthiness more quickly. For more details about TrustLLM, please refer to project website.

AI-YinMei
AI-YinMei is an AI virtual anchor Vtuber development tool (N card version). It supports fastgpt knowledge base chat dialogue, a complete set of solutions for LLM large language models: [fastgpt] + [one-api] + [Xinference], supports docking bilibili live broadcast barrage reply and entering live broadcast welcome speech, supports Microsoft edge-tts speech synthesis, supports Bert-VITS2 speech synthesis, supports GPT-SoVITS speech synthesis, supports expression control Vtuber Studio, supports painting stable-diffusion-webui output OBS live broadcast room, supports painting picture pornography public-NSFW-y-distinguish, supports search and image search service duckduckgo (requires magic Internet access), supports image search service Baidu image search (no magic Internet access), supports AI reply chat box [html plug-in], supports AI singing Auto-Convert-Music, supports playlist [html plug-in], supports dancing function, supports expression video playback, supports head touching action, supports gift smashing action, supports singing automatic start dancing function, chat and singing automatic cycle swing action, supports multi scene switching, background music switching, day and night automatic switching scene, supports open singing and painting, let AI automatically judge the content.