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1,037 projects · updated 7/22/2026
# Made with LangChain

> A curated, daily-updated gallery of the best open-source projects built with LangChain, ranked by GitHub stars. Discover dashboards, UI kits, e-commerce, blogs and dev tools.

## About

- Gallery: https://madewithwhat.net/langchain/
- Domain: madewithlangchain.com
- Projects indexed: 1,037
- Data source: GitHub (refreshed daily)
- Last scraped: 2026-07-22T09:29:07.959747+00:00

## Top projects

- [markitdown](https://madewithwhat.net/langchain/project/markitdown/): Python tool for converting files and office documents to Markdown. (165,707 stars, AI & ML)
- [open-webui](https://madewithwhat.net/langchain/project/open-webui/): User-friendly AI Interface (Supports Ollama, OpenAI API,...) (145,348 stars, AI & ML)
- [deer-flow](https://madewithwhat.net/langchain/project/deer-flow/): An open-source long-horizon SuperAgent harness that researches, codes, and creates. With the help of sandboxes, memories, tools, skill, subagents and message gateway, it handles different levels of tasks that could take minutes to hours. (76,969 stars, AI & ML)
- [headroom](https://madewithwhat.net/langchain/project/headroom/): Compress tool outputs, logs, files, and RAG chunks before they reach the LLM. 60-95% fewer tokens, same answers. Library, proxy, MCP server. (59,005 stars, AI & ML)
- [Flowise](https://madewithwhat.net/langchain/project/flowise/): Build AI Agents, Visually (54,588 stars, AI & ML)
- [litellm](https://madewithwhat.net/langchain/project/litellm/): Python SDK, Proxy Server (AI Gateway) to call 100+ LLM APIs in OpenAI (or native) format, with cost tracking, guardrails, loadbalancing and logging. [Bedrock, Azure, OpenAI, VertexAI, Cohere, Anthropic, Sagemaker, HuggingFace, VLLM, NVIDIA NIM] (53,514 stars, AI & ML)
- [Langchain-Chatchat](https://madewithwhat.net/langchain/project/langchain-chatchat/): Langchain-Chatchat(Langchain-ChatGLM) Langchain ChatGLM, Qwen Llama RAG Agent | Langchain-Chatchat (formerly langchain-ChatGLM), local knowledge based LLM (like ChatGLM, Qwen and Llama) RAG and Agent app with langchain (38,426 stars, AI & ML)
- [langgraph](https://madewithwhat.net/langchain/project/langgraph/): Build resilient agents. (37,239 stars, AI & ML)
- [posthog](https://madewithwhat.net/langchain/project/posthog/): PostHog is an all-in-one developer platform for building successful products. We offer product analytics, web analytics, session replay, error tracking, feature flags, experimentation, surveys, data warehouse, a CDP, and an AI product assistant to help debug your code, ship features faster, and keep all your usage and customer data in one stack. (35,484 stars, Dashboards)
- [hackathon-starter](https://madewithwhat.net/langchain/project/hackathon-starter/): A boilerplate for Node.js web applications (35,235 stars, Templates)
- [langfuse](https://madewithwhat.net/langchain/project/langfuse/): Open source AI engineering platform: LLM evals, observability, metrics, prompt management, playground, datasets. Integrates with OpenTelemetry, LangChain, OpenAI SDK, LiteLLM, and more. YC W23 (31,096 stars, AI & ML)
- [onyx](https://madewithwhat.net/langchain/project/onyx/): Open Source AI Platform - AI Chat with advanced features that works with every LLM (30,865 stars, AI & ML)
- [agents-course](https://madewithwhat.net/langchain/project/agents-course/): This repository contains the Hugging Face Agents Course. (30,012 stars, AI & ML)
- [RAG_Techniques](https://madewithwhat.net/langchain/project/rag-techniques/): This repository showcases various advanced techniques for Retrieval-Augmented Generation (RAG) systems. Each technique has a detailed notebook tutorial. (28,532 stars, AI & ML)
- [mlflow](https://madewithwhat.net/langchain/project/mlflow/): The open source AI engineering platform for agents, LLMs, and ML models. MLflow enables teams of all sizes to debug, evaluate, monitor, and optimize production-quality AI applications while controlling costs and managing access to models and data. (27,013 stars, AI & ML)
- [deepagents](https://madewithwhat.net/langchain/project/deepagents/): The batteries-included agent harness. (26,204 stars, AI & ML)
- [GenAI_Agents](https://madewithwhat.net/langchain/project/genai-agents/): 50+ tutorials and implementations for Generative AI Agent techniques, from basic conversational bots to complex multi-agent systems. (23,143 stars, AI & ML)
- [MaxKB](https://madewithwhat.net/langchain/project/maxkb/): MaxKB is an open-source platform for building enterprise-grade agents. 。 (22,080 stars, AI & ML)
- [opik](https://madewithwhat.net/langchain/project/opik/): Debug, evaluate, and monitor your LLM applications, RAG systems, and agentic workflows with comprehensive tracing, automated evaluations, and production-ready dashboards. (20,580 stars, AI & ML)
- [llama-cookbook](https://madewithwhat.net/langchain/project/llama-cookbook/): Welcome to the Llama Cookbook! This is your go to guide for Building with Llama: Getting started with Inference, Fine-Tuning, RAG. We also show you how to solve end to end problems using Llama model family and using them on various provider services (18,401 stars, AI & ML)
- [generative-ai](https://madewithwhat.net/langchain/project/generative-ai/): Sample code and notebooks for Generative AI on Google Cloud, with Gemini Enterprise Agent Platform (17,227 stars, AI & ML)
- [LangBot](https://madewithwhat.net/langchain/project/langbot/): Production-grade platform for building agentic IM bots - / Agent、、 / Bots for Discord / Slack / LINE / Telegram / WeChat / / / QQ / Matrix e.g. Integrated with ChatGPT(GPT), DeepSeek, Dify, n8n, Langflow, Coze, Claude, Gemini, GLM, Ollama, SiliconFlow, Moonshot, openclaw / hermes agent, deerflow (16,871 stars, AI & ML)
- [SurfSense](https://madewithwhat.net/langchain/project/surfsense/): NotebookLM for Competitive Intelligence Research. Give your AI agents Competitive Intelligence. Join our Discord: https://discord.gg/ejRNvftDp9 (15,228 stars, AI & ML)
- [unstructured](https://madewithwhat.net/langchain/project/unstructured/): Convert documents to structured data effortlessly. Unstructured is open-source ETL solution for transforming complex documents into clean, structured formats for language models. Visit our website to learn more about our enterprise grade Platform product for production grade workflows, partitioning, enrichments, chunking and embedding. (15,126 stars, AI & ML)
- [botpress](https://madewithwhat.net/langchain/project/botpress/): The open-source hub to build & deploy GPT/LLM Agents (14,784 stars, AI & ML)
- [llm-universe](https://madewithwhat.net/langchain/project/llm-universe/): ,:https://datawhalechina.github.io/llm-universe/ (13,478 stars, AI & ML)
- [LEANN](https://madewithwhat.net/langchain/project/leann/): [MLsys2026]: RAG on Everything with LEANN. Enjoy 97% storage savings while running a fast, accurate, and 100% private RAG application on your personal device. (12,678 stars, AI & ML)
- [langchain4j](https://madewithwhat.net/langchain/project/langchain4j/): LangChain4j is an idiomatic, open-source Java library for building LLM-powered applications on the JVM. It offers a unified API over popular LLM providers and vector stores, and makes implementing tool calling (including MCP support), agents and RAG easy. It integrates seamlessly with enterprise Java frameworks like Quarkus and Spring Boot. (12,591 stars, AI & ML)
- [gateway](https://madewithwhat.net/langchain/project/gateway/): A blazing fast AI Gateway with integrated guardrails. Route to 1,600+ LLMs, 50+ AI Guardrails with 1 fast & friendly API. (12,432 stars, AI & ML)
- [chainlit](https://madewithwhat.net/langchain/project/chainlit/): Build Conversational AI in minutes (12,310 stars, AI & ML)

## Useful links

- Full catalog, all 1,037 projects by category: https://madewithwhat.net/langchain/llms-full.txt
- RSS feed: https://madewithwhat.net/langchain/rss.xml
- Submit a project: https://madewithwhat.net/langchain/submit/
- Browse categories: https://madewithwhat.net/langchain/categories/
- Newsletter: https://madewithwhat.net/langchain/newsletter/

## Optional

This catalog ranks open-source projects by GitHub stars. Each project page includes description, stack, languages, license, and related projects.
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