# Made with LangChain — full catalog

> 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/
- Curated summary: https://madewithwhat.net/langchain/llms.txt
- Projects indexed: 1,037
- Data source: GitHub (refreshed daily)
- Last scraped: 2026-07-22T09:29:07.959747+00:00

## AI & ML (1,004)

- [markitdown](https://madewithwhat.net/langchain/project/markitdown/): Python tool for converting files and office documents to Markdown. (165,707 stars, MIT)
- [open-webui](https://madewithwhat.net/langchain/project/open-webui/): User-friendly AI Interface (Supports Ollama, OpenAI API,...) (145,348 stars)
- [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, MIT)
- [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, Apache-2.0)
- [Flowise](https://madewithwhat.net/langchain/project/flowise/): Build AI Agents, Visually (54,588 stars)
- [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)
- [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, Apache-2.0)
- [langgraph](https://madewithwhat.net/langchain/project/langgraph/): Build resilient agents. (37,239 stars, MIT)
- [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)
- [onyx](https://madewithwhat.net/langchain/project/onyx/): Open Source AI Platform - AI Chat with advanced features that works with every LLM (30,865 stars)
- [agents-course](https://madewithwhat.net/langchain/project/agents-course/): This repository contains the Hugging Face Agents Course. (30,012 stars, Apache-2.0)
- [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)
- [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, Apache-2.0)
- [deepagents](https://madewithwhat.net/langchain/project/deepagents/): The batteries-included agent harness. (26,204 stars, MIT)
- [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)
- [MaxKB](https://madewithwhat.net/langchain/project/maxkb/): MaxKB is an open-source platform for building enterprise-grade agents. 。 (22,080 stars, GPL-3.0)
- [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, Apache-2.0)
- [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, MIT)
- [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, Apache-2.0)
- [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, Apache-2.0)
- [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)
- [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, Apache-2.0)
- [botpress](https://madewithwhat.net/langchain/project/botpress/): The open-source hub to build & deploy GPT/LLM Agents (14,784 stars, MIT)
- [llm-universe](https://madewithwhat.net/langchain/project/llm-universe/): ，：https://datawhalechina.github.io/llm-universe/ (13,478 stars)
- [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, MIT)
- [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, Apache-2.0)
- [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, MIT)
- [chainlit](https://madewithwhat.net/langchain/project/chainlit/): Build Conversational AI in minutes (12,310 stars, Apache-2.0)
- [eino](https://madewithwhat.net/langchain/project/eino/): The ultimate LLM/AI application development framework in Go. (12,280 stars, Apache-2.0)
- [phoenix](https://madewithwhat.net/langchain/project/phoenix/): AI Observability & Evaluation (10,546 stars)
- [all-in-rag](https://madewithwhat.net/langchain/project/all-in-rag/): ：RAG ，：https://datawhalechina.github.io/all-in-rag/ (9,565 stars)
- [langchaingo](https://madewithwhat.net/langchain/project/langchaingo/): LangChain for Go, the easiest way to write LLM-based programs in Go (9,544 stars, MIT)
- [LangChain-Chinese-Getting-Started-Guide](https://madewithwhat.net/langchain/project/langchain-chinese-getting-started-guide/): LangChain (9,060 stars)
- [local-deep-research](https://madewithwhat.net/langchain/project/local-deep-research/): ~95% on SimpleQA (e.g. Qwen3.6-27B on a 3090). Supports all local and cloud LLMs (llama.cpp, Ollama, Google,...). 10+ search engines - arXiv, PubMed, your private documents. Everything Local & Encrypted. (8,712 stars, MIT)
- [GPTCache](https://madewithwhat.net/langchain/project/gptcache/): Semantic cache for LLMs. Fully integrated with LangChain and llama_index. (8,097 stars, MIT)
- [page-assist](https://madewithwhat.net/langchain/project/page-assist/): Use your locally running AI models to assist you in your web browsing (8,065 stars, MIT)
- [Prompt_Engineering](https://madewithwhat.net/langchain/project/prompt-engineering/): 22 prompt engineering techniques with hands-on Jupyter Notebook tutorials, from fundamental concepts to advanced strategies for leveraging LLMs. (7,678 stars)
- [AgentGuide](https://madewithwhat.net/langchain/project/agentguide/): https://adongwanai.github.io/AgentGuide | AI Agent | LangGraph | RAG | | | | | ｜ (6,954 stars)
- [swarms](https://madewithwhat.net/langchain/project/swarms/): The Enterprise-Grade Production-Ready Multi-Agent Orchestration Framework. Website: https://swarms.ai (6,943 stars, Apache-2.0)
- [llm-scraper](https://madewithwhat.net/langchain/project/llm-scraper/): Turn any webpage into structured data using LLMs (6,833 stars, MIT)
- [TaxHacker](https://madewithwhat.net/langchain/project/taxhacker/): Self-hosted AI accounting app. LLM analyzer for receipts, invoices, transactions with custom prompts and categories (6,534 stars, MIT)
- [honcho](https://madewithwhat.net/langchain/project/honcho/): Memory library for building stateful agents (5,948 stars, AGPL-3.0)
- [helicone](https://madewithwhat.net/langchain/project/helicone/): Open source LLM observability platform. One line of code to monitor, evaluate, and experiment. YC W23 (5,944 stars, Apache-2.0)
- [agentops](https://madewithwhat.net/langchain/project/agentops/): Python SDK for AI agent monitoring, LLM cost tracking, benchmarking, and more. Integrates with most LLMs and agent frameworks including CrewAI, Agno, OpenAI Agents SDK, Langchain, Autogen, AG2, and CamelAI (5,707 stars, MIT)
- [coze-loop](https://madewithwhat.net/langchain/project/coze-loop/): Next-generation AI Agent Optimization Platform: Cozeloop addresses challenges in AI agent development by providing full-lifecycle management capabilities from development, debugging, and evaluation to monitoring. (5,606 stars, Apache-2.0)
- [openagent](https://madewithwhat.net/langchain/project/openagent/): next-generation personal AI assistant powered by LLM, RAG and agent loops, supporting computer-use, browser-use and coding agent, demo: https://demo.openagentai.org (5,399 stars, Apache-2.0)
- [TaskingAI](https://madewithwhat.net/langchain/project/taskingai/): The open source platform for AI-native application development. (5,391 stars, Apache-2.0)
- [argilla](https://madewithwhat.net/langchain/project/argilla/): Argilla is a collaboration tool for AI engineers and domain experts to build high-quality datasets (5,034 stars, Apache-2.0)
- [llm-graph-builder](https://madewithwhat.net/langchain/project/llm-graph-builder/): Neo4j graph construction from unstructured data using LLMs (4,947 stars, Apache-2.0)
- [Decepticon](https://madewithwhat.net/langchain/project/decepticon/): Autonomous Hacking Agent for Red Team (4,700 stars, Apache-2.0)
- [logfire](https://madewithwhat.net/langchain/project/logfire/): AI observability platform for production LLM and agent systems. (4,372 stars, MIT)
- [mcp-context-forge](https://madewithwhat.net/langchain/project/mcp-context-forge/): An AI Gateway, registry, and proxy that sits in front of any MCP, A2A, or REST/gRPC APIs, exposing a unified endpoint with centralized discovery, guardrails and management. Optimizes Agent & Tool calling, and supports plugins. (4,086 stars, Apache-2.0)
- [LazyLLM](https://madewithwhat.net/langchain/project/lazyllm/): Easiest and laziest way for building multi-agent LLMs applications. (3,853 stars, Apache-2.0)
- [codeinterpreter-api](https://madewithwhat.net/langchain/project/codeinterpreter-api/): Open source implementation of the ChatGPT Code Interpreter (3,845 stars, MIT)
- [all-agentic-architectures](https://madewithwhat.net/langchain/project/all-agentic-architectures/): 35 production-grade agentic AI architectures (Reflexion, LATS, GraphRAG, MemGPT, Voyager, BrowserAgent,...) — a Python library and runnable textbook with multi-provider LLM support and a 17-task benchmark leaderboard. (3,806 stars, MIT)
- [agentic-rag-for-dummies](https://madewithwhat.net/langchain/project/agentic-rag-for-dummies/): A modular Agentic RAG built with LangGraph — learn Retrieval-Augmented Generation Agents in minutes. (3,652 stars, MIT)
- [langchain-mcp-adapters](https://madewithwhat.net/langchain/project/langchain-mcp-adapters/): LangChain MCP (3,598 stars, MIT)
- [Ask-Anything](https://madewithwhat.net/langchain/project/ask-anything/): [CVPR2024 Highlight][VideoChatGPT] ChatGPT with video understanding! And many more supported LMs such as miniGPT4, StableLM, and MOSS. (3,344 stars, MIT)
- [mirage](https://madewithwhat.net/langchain/project/mirage/): The World's First Unified Virtual Filesystem For AI Agents (3,315 stars, Apache-2.0)
- [LangChain-ChatGLM-Webui](https://madewithwhat.net/langchain/project/langchain-chatglm-webui/): LangChainChatGLM-6BLLM (3,315 stars, Apache-2.0)
- [cascadeflow](https://madewithwhat.net/langchain/project/cascadeflow/): Cascading runtime for AI agents. Optimize cost, latency, quality, and policy decisions inside the agent loop. (3,295 stars, MIT)
- [pezzo](https://madewithwhat.net/langchain/project/pezzo/): Open-source, developer-first LLMOps platform designed to streamline prompt design, version management, instant delivery, collaboration, troubleshooting, observability and more. (3,254 stars, Apache-2.0)
- [InternGPT](https://madewithwhat.net/langchain/project/interngpt/): InternGPT (iGPT) is an open source demo platform where you can easily showcase your AI models. Now it supports DragGAN, ChatGPT, ImageBind, multimodal chat like GPT-4, SAM, interactive image editing, etc. Try it at igpt.opengvlab.com (3,202 stars, Apache-2.0)
- [FireRed-OpenStoryline](https://madewithwhat.net/langchain/project/firered-openstoryline/): FireRed-OpenStoryline is an AI video editing agent that transforms manual editing into intention-driven directing through natural language interaction, LLM-powered planning, and precise tool orchestration. It facilitates transparent, human-in-the-loop creation with reusable Style Skills for consistent, professional storytelling. (3,093 stars, Apache-2.0)
- [rag-web-ui](https://madewithwhat.net/langchain/project/rag-web-ui/): RAG Web UI is an intelligent dialogue system based on RAG (Retrieval-Augmented Generation) technology. (3,063 stars, Apache-2.0)
- [pipeshub-ai](https://madewithwhat.net/langchain/project/pipeshub-ai/): PipesHub is an open-source fully extensible AI context layer that unifies your business data for explainable enterprise search and agentic workflow automation. (3,025 stars, Apache-2.0)
- [seekdb](https://madewithwhat.net/langchain/project/seekdb/): The AI-Native Search Database. Best for agent storage, it unifies vector, text, structured, and semi-structured data into a single engine. This all-in-one database makes agents smarter, easier to run, and more stable. (2,823 stars, Apache-2.0)
- [ai-agents-from-zero](https://madewithwhat.net/langchain/project/ai-agents-from-zero/): 2026 AI Agent ｜ · + + · · LangChain / LangGraph / Coze / Dify / MCP / skills / LLM / RAG / · · 0 + + (2,724 stars, MIT)
- [openlit](https://madewithwhat.net/langchain/project/openlit/): Open source platform for AI Engineering: OpenTelemetry-native LLM Observability, GPU Monitoring, Guardrails, Evaluations, Prompt Management, Vault, Playground. Integrates with 50+ LLM Providers, VectorDBs, Agent Frameworks and GPUs. (2,597 stars, Apache-2.0)
- [rag-cookbooks](https://madewithwhat.net/langchain/project/rag-cookbooks/): This repository contains various advanced techniques for Retrieval-Augmented Generation (RAG) systems. (2,554 stars, MIT)
- [generative-ai](https://madewithwhat.net/langchain/project/generative-ai/): Comprehensive resources on Generative AI, including a detailed roadmap, projects, use cases, interview preparation, and coding preparation. (2,552 stars, MIT)
- [fastapi-langgraph-agent-production-ready-template](https://madewithwhat.net/langchain/project/fastapi-langgraph-agent-production-ready-template/): A production-ready FastAPI template for building AI agent applications with LangGraph integration. This template provides a robust foundation for building scalable, secure, and maintainable AI agent services. (2,508 stars, MIT)
- [handy-ollama](https://madewithwhat.net/langchain/project/handy-ollama/): Ollama，CPU，：https://datawhalechina.github.io/handy-ollama/ (2,471 stars)
- [RasaGPT](https://madewithwhat.net/langchain/project/rasagpt/): RasaGPT is the first headless LLM chatbot platform built on top of Rasa and Langchain. Built w/ Rasa, FastAPI, Langchain, LlamaIndex, SQLModel, pgvector, ngrok, telegram (2,464 stars, MIT)
- [api-for-open-llm](https://madewithwhat.net/langchain/project/api-for-open-llm/): Openai style api for open large language models, using LLMs just as chatgpt! Support for LLaMA, LLaMA-2, BLOOM, Falcon, Baichuan, Qwen, Xverse, SqlCoder, CodeLLaMA, ChatGLM, ChatGLM2, ChatGLM3 etc. (2,458 stars, Apache-2.0)
- [autolabel](https://madewithwhat.net/langchain/project/autolabel/): Label, clean and enrich text datasets with LLMs. (2,325 stars, MIT)
- [comfyui_LLM_party](https://madewithwhat.net/langchain/project/comfyui-llm-party/): LLM Agent Framework in ComfyUI includes MCP sever, Omost,GPT-sovits, ChatTTS,GOT-OCR2.0, and FLUX prompt nodes,access to Feishu,discord,and adapts to all llms with similar openai / aisuite interfaces, such as o1,ollama, gemini, grok, qwen, GLM, deepseek, kimi,doubao. Adapted to local llms, vlm, gguf such as llama-3.3 Janus-Pro, Linkage graphRAG (2,303 stars, AGPL-3.0)
- [ai-chatbot-framework](https://madewithwhat.net/langchain/project/ai-chatbot-framework/): A python chatbot framework with Natural Language Understanding and Artificial Intelligence. (2,163 stars, MIT)
- [langchain-kr](https://madewithwhat.net/langchain/project/langchain-kr/): LangChain Document, Cookbook,. LangChain. (2,032 stars, Apache-2.0)
- [company-research-agent](https://madewithwhat.net/langchain/project/company-research-agent/): An agentic company research tool powered by LangGraph and Tavily that conducts deep diligence on companies using a multi-agent framework. It leverages Google's Gemini 2.5 Flash and OpenAI's GPT-5.1 on the backend for inference. (2,004 stars, Apache-2.0)
- [knowhere](https://madewithwhat.net/langchain/project/knowhere/): Knowhere extracts, parses, and outputs structured chunks ready for AI Agents and RAG. (1,914 stars, Apache-2.0)
- [Dot](https://madewithwhat.net/langchain/project/dot/): Text-To-Speech, RAG, and LLMs. All local! (1,910 stars, GPL-3.0)
- [DemoGPT](https://madewithwhat.net/langchain/project/demogpt/): Create LLM agents in a second with your prompts. Everything you need to create an LLM Agent - tools, prompts, frameworks, and models - all in one place. (1,901 stars, MIT)
- [Large-Language-Model-Notebooks-Course](https://madewithwhat.net/langchain/project/large-language-model-notebooks-course/): Practical course about Large Language Models. (1,818 stars, MIT)
- [DATAGEN](https://madewithwhat.net/langchain/project/datagen/): DATAGEN: AI-driven multi-agent research assistant automating hypothesis generation, data analysis, and report writing. (1,769 stars, MIT)
- [Chrome-GPT](https://madewithwhat.net/langchain/project/chrome-gpt/): An AutoGPT agent that controls Chrome on your desktop (1,742 stars, GPL-3.0)
- [solana-agent-kit](https://madewithwhat.net/langchain/project/solana-agent-kit/): connect any ai agents to solana protocols (1,703 stars, Apache-2.0)
- [PageLM](https://madewithwhat.net/langchain/project/pagelm/): PageLM is a community driven version of NotebookLM & a education platform that transforms study materials into interactive resources like quizzes, flashcards, notes, and podcasts. (1,680 stars)
- [memanto](https://madewithwhat.net/langchain/project/memanto/): Memory that AI Agents Love! (1,640 stars, MIT)
- [Controllable-RAG-Agent](https://madewithwhat.net/langchain/project/controllable-rag-agent/): This repository provides an advanced Retrieval-Augmented Generation (RAG) solution for complex question answering. It uses sophisticated graph based algorithm to handle the tasks. (1,614 stars, Apache-2.0)
- [llm-chain](https://madewithwhat.net/langchain/project/llm-chain/): `llm-chain` is a powerful rust crate for building chains in large language models allowing you to summarise text and complete complex tasks (1,602 stars, MIT)
- [ExtractThinker](https://madewithwhat.net/langchain/project/extractthinker/): ExtractThinker is a Document Intelligence library for LLMs, offering ORM-style interaction for flexible and powerful document workflows. (1,585 stars, Apache-2.0)
- [LangAlpha](https://madewithwhat.net/langchain/project/langalpha/): Claude Code for Investing (1,541 stars, Apache-2.0)
- [full-stack-ai-agent-template](https://madewithwhat.net/langchain/project/full-stack-ai-agent-template/): Full-stack AI app generator — FastAPI + Next.js with AI Agents, RAG, streaming, auth, and 20+ integrations out of the box. (1,528 stars, MIT)
- [langchain-course](https://madewithwhat.net/langchain/project/langchain-course/): A project-based course repository for developing AI agents using LangChain v1+ and LangGraph: search agents, RAG systems, reflection agents, and code interpreters. (1,519 stars, Apache-2.0)
- [Lumos](https://madewithwhat.net/langchain/project/lumos/): A RAG LLM co-pilot for browsing the web, powered by local LLMs (1,515 stars, MIT)
- [amazon-bedrock-samples](https://madewithwhat.net/langchain/project/amazon-bedrock-samples/): This repository contains examples for customers to get started using the Amazon Bedrock Service. This contains examples for all available foundational models (1,471 stars, MIT-0)
- [deepagentsjs](https://madewithwhat.net/langchain/project/deepagentsjs/): The batteries included agent harness. (1,406 stars, MIT)
- [aws-genai-llm-chatbot](https://madewithwhat.net/langchain/project/aws-genai-llm-chatbot/): A modular and comprehensive solution to deploy a Multi-LLM and Multi-RAG powered chatbot (Amazon Bedrock, Anthropic, HuggingFace, OpenAI, Meta, AI21, Cohere, Mistral) using AWS CDK on AWS (1,400 stars, MIT-0)
- [generative_ai_with_langchain](https://madewithwhat.net/langchain/project/generative-ai-with-langchain/): Build production-ready LLM applications and advanced agents using Python, LangChain, and LangGraph. This is the companion repository for the book on generative AI with LangChain. (1,385 stars, MIT)
- [row-bot](https://madewithwhat.net/langchain/project/row-bot/): Row-Bot - Personal AI Sovereignty. A local-first AI assistant with integrated tools, a personal knowledge graph, voice, vision, shell, browser automation, scheduled tasks, health tracking, and messaging channels. Run locally via Ollama or add opt-in cloud models. Your data stays on your machine. (1,372 stars, Apache-2.0)
- [azure-openai-proxy](https://madewithwhat.net/langchain/project/azure-openai-proxy/): Azure OpenAI Service Proxy. Convert OpenAI official API request to Azure OpenAI API request. Support GPT-4,Embeddings,Langchain. Adapter from OpenAI to Azure OpenAI. (1,346 stars, Apache-2.0)
- [devops-ai-guidelines](https://madewithwhat.net/langchain/project/devops-ai-guidelines/): First AI Journey for DevOps - with comprehensive learning paths, practical tips, and enterprise guidelines (1,341 stars, MIT)
- [rocketnotes](https://madewithwhat.net/langchain/project/rocketnotes/): AI-powered markdown editor - leverage LLMs with your documents - 100% local or in the cloud (1,336 stars, Apache-2.0)
- [magic-context](https://madewithwhat.net/langchain/project/magic-context/): Unbounded context. Memory that manages itself. One session, for life. The hippocampus for coding agents, part of CortexKit. (1,334 stars, MIT)
- [langchain-rust](https://madewithwhat.net/langchain/project/langchain-rust/): LangChain for Rust, the easiest way to write LLM-based programs in Rust (1,328 stars, MIT)
- [codefuse-chatbot](https://madewithwhat.net/langchain/project/codefuse-chatbot/): An intelligent assistant serving the entire software development lifecycle, powered by a Multi-Agent Framework, working with DevOps Toolkits, Code&Doc Repo RAG, etc. (1,290 stars)
- [sre](https://madewithwhat.net/langchain/project/sre/): The SmythOS Runtime Environment (SRE) is an open-source, cloud-native runtime for agentic AI. Secure, modular, and production-ready, it lets developers build, run, and manage intelligent agents across local, cloud, and edge environments. (1,285 stars, MIT)
- [ChatGPT-Telegram-Bot](https://madewithwhat.net/langchain/project/chatgpt-telegram-bot/): TeleChat: an AI chat Telegram bot can Web Search Powered by GPT-5, DALL·E, Groq, Gemini 2.5 Pro/Flash and the official Claude4.1 API using Python on Zeabur, fly.io and Replit. (1,283 stars, GPL-3.0)
- [Get-Things-Done-with-Prompt-Engineering-and-LangChain](https://madewithwhat.net/langchain/project/get-things-done-with-prompt-engineering-and-langchain/): LangChain & Prompt Engineering tutorials on Large Language Models (LLMs) such as ChatGPT with custom data. Jupyter notebooks on loading and indexing data, creating prompt templates, CSV agents, and using retrieval QA chains to query the custom data. Projects for using a private LLM (Llama 2) for chat with PDF files, tweets sentiment analysis. (1,244 stars, Apache-2.0)
- [langtrace](https://madewithwhat.net/langchain/project/langtrace/): Langtrace is an open-source, Open Telemetry based end-to-end observability tool for LLM applications, providing real-time tracing, evaluations and metrics for popular LLMs, LLM frameworks, vectorDBs and more.. Integrate using Typescript, Python. (1,215 stars, AGPL-3.0)
- [MedRAX](https://madewithwhat.net/langchain/project/medrax/): MedRAX: Medical Reasoning Agent for Chest X-ray - ICML 2025 (1,195 stars, Apache-2.0)
- [enterprise-deep-research](https://madewithwhat.net/langchain/project/enterprise-deep-research/): Salesforce Enterprise Deep Research (1,193 stars, Apache-2.0)
- [intelligent-audit-system](https://madewithwhat.net/langchain/project/intelligent-audit-system/): Enterprise audit agent workspace with Agentic RAG, governed tool use, evaluation harness, memory, and human-review delivery workflows. (1,161 stars)
- [deepagents-in-action](https://madewithwhat.net/langchain/project/deepagents-in-action/): 《Deep Agents 》—— LangChain ， LangChain / LangGraph ， AI Agent (1,160 stars)
- [shell-ai](https://madewithwhat.net/langchain/project/shell-ai/): LangChain powered shell command generator and runner CLI (1,153 stars, MIT)
- [langchain-experiments](https://madewithwhat.net/langchain/project/langchain-experiments/): Building Apps with LLMs (1,139 stars, MIT)
- [telegram-chatgpt-concierge-bot](https://madewithwhat.net/langchain/project/telegram-chatgpt-concierge-bot/): Interact with OpenAI's ChatGPT via Telegram and Voice. (1,132 stars)
- [elasticsearch-labs](https://madewithwhat.net/langchain/project/elasticsearch-labs/): Notebooks & Example Apps for Search & AI Applications with Elasticsearch (1,112 stars, Apache-2.0)
- [flock](https://madewithwhat.net/langchain/project/flock/): A desktop multi-agent harness built with Rust, Tauri, and React, powered by langgraph-rust. (1,090 stars, Apache-2.0)
- [LangChain-OpenTutorial](https://madewithwhat.net/langchain/project/langchain-opentutorial/): LangChain, LangGraph Open Tutorial for everyone! (1,087 stars, MIT)
- [openinference](https://madewithwhat.net/langchain/project/openinference/): OpenTelemetry Instrumentation for AI Observability (1,084 stars, Apache-2.0)
- [aegra](https://madewithwhat.net/langchain/project/aegra/): Open source alternative to LangGraph Platform (now LangSmith Deployments) - Self-hosted AI agent backend with FastAPI and PostgreSQL. Zero vendor lock-in, full control over your agent infrastructure. (1,052 stars, Apache-2.0)
- [minima](https://madewithwhat.net/langchain/project/minima/): On-premises conversational RAG with configurable containers (1,052 stars, MPL-2.0)
- [llm_agents](https://madewithwhat.net/langchain/project/llm-agents/): Build agents which are controlled by LLMs (1,050 stars, MIT)
- [judgeval](https://madewithwhat.net/langchain/project/judgeval/): The Continuous-Improvement Stack for Agents. Our environment data and evals power agent improvement and monitoring. (1,041 stars, Apache-2.0)
- [agents-flex](https://madewithwhat.net/langchain/project/agents-flex/): Agents-flex is A lightweight Java AI agent development framework (positioned as a counterpart to Spring AI). It supports features such as RAG, MCP, Skills, Text2SQL, LLM Wiki, Sub-agents, Web Search, TTS (synchronous and streaming), and STT. (1,028 stars, Apache-2.0)
- [langchain-chat-nextjs](https://madewithwhat.net/langchain/project/langchain-chat-nextjs/): Next.js frontend for LangChain Chat. (1,015 stars, MIT)
- [RepoAgent](https://madewithwhat.net/langchain/project/repoagent/): An LLM-powered repository agent designed to assist developers and teams in generating documentation and understanding repositories quickly. (1,009 stars, Apache-2.0)
- [Llama-2-Open-Source-LLM-CPU-Inference](https://madewithwhat.net/langchain/project/llama-2-open-source-llm-cpu-inference/): Running Llama 2 and other Open-Source LLMs on CPU Inference Locally for Document Q&A (971 stars, MIT)
- [vectordb-recipes](https://madewithwhat.net/langchain/project/vectordb-recipes/): Resource, examples & tutorials for multimodal AI, RAG and agents using vector search and LLMs (968 stars, Apache-2.0)
- [GenAI_LLM_timeline](https://madewithwhat.net/langchain/project/genai-llm-timeline/): ChatGPT, GenerativeAI and LLMs Timeline (953 stars)
- [agentic-soc-platform](https://madewithwhat.net/langchain/project/agentic-soc-platform/): Agentic SOC Platform: A powerful, flexible, open-source, and agent-centric automated security operations platform (AI SOC) (948 stars)
- [langcorn](https://madewithwhat.net/langchain/project/langcorn/): Serving LangChain LLM apps and agents automagically with FastApi. LLMops (938 stars, MIT)
- [Multi-Agent-Medical-Assistant](https://madewithwhat.net/langchain/project/multi-agent-medical-assistant/): GenAI powered multi-agentic medical diagnostics and healthcare research assistance chatbot. Designed for healthcare professionals, researchers and patients. (930 stars, Apache-2.0)
- [llm-python](https://madewithwhat.net/langchain/project/llm-python/): Large Language Models (LLMs) tutorials & sample scripts, ft. langchain, openai, llamaindex, gpt, chromadb & pinecone (925 stars, MIT)
- [AI-Bootcamp](https://madewithwhat.net/langchain/project/ai-bootcamp/): Self-paced bootcamp on Generative AI. Tutorials on ML fundamentals, Ollama, LLMs, RAGs, LangChain, LangGraph, Fine-tuning, DSPy & AI Agents (CrewAI), (Using ChatGPT, gpt-oss, Claude, Qwen, Gemma, Llama, Gemini) (920 stars, MIT)
- [langchain-ui](https://madewithwhat.net/langchain/project/langchain-ui/): The open source chat-ai toolkit (914 stars, MIT)
- [DeepGit](https://madewithwhat.net/langchain/project/deepgit/): Deep research agent to help you find the best GitHub repositories! (889 stars)
- [LaunchStack](https://madewithwhat.net/langchain/project/launchstack/): AI-powered StartUp Accelerator Engine built with Next.js, LangChain, PostgreSQL + pgvector. Upload, organize, and chat with documents. Includes predictive missing-document detection, role-based workflows, and page-level insight extraction. (884 stars, Apache-2.0)
- [production-grade-agentic-system](https://madewithwhat.net/langchain/project/production-grade-agentic-system/): Core 7 layers of production grade agentic system (876 stars, MIT)
- [ai-agents-the-definitive-guide](https://madewithwhat.net/langchain/project/ai-agents-the-definitive-guide/): Repo for AI Agents The Definitive Guide (869 stars)
- [entaoai](https://madewithwhat.net/langchain/project/entaoai/): Chat and Ask on your own data. Accelerator to quickly upload your own enterprise data and use OpenAI services to chat to that uploaded data and ask questions (866 stars, MIT)
- [pocketpaw](https://madewithwhat.net/langchain/project/pocketpaw/): Your AI agent in 30 seconds. Not 30 hours. Self-hosted, open-source personal AI with desktop installer, multi-agent Command Center(Deep Work), and 7-layer security. Anthropic, OpenAI, or Ollama. (866 stars, MIT)
- [rag_api](https://madewithwhat.net/langchain/project/rag-api/): ID-based RAG FastAPI: Integration with Langchain and PostgreSQL/pgvector (864 stars, MIT)
- [doc-chatbot](https://madewithwhat.net/langchain/project/doc-chatbot/): Document chatbot — multiple files, topics, chat windows and chat history. Powered by GPT. (855 stars)
- [Magick](https://madewithwhat.net/langchain/project/magick/): Magick is a cutting-edge toolkit for a new kind of AI builder. Make Magick with us! (841 stars)
- [openagent](https://madewithwhat.net/langchain/project/openagent/): What if OpenAI Deep Research and Dify were one platform? OpenAgent — harness architecture for rapidly building vertical AI agents, with deep reasoning loops, visual workflows, RAG, and A2A delegation. (832 stars, MIT)
- [swapper-toolkit](https://madewithwhat.net/langchain/project/swapper-toolkit/): DeFi toolkit for AI agents and coding assistants — deposit funds, execute trades, and manage crypto wallets. Works with Claude Code, Cursor, Windsurf, OpenClaw, CrewAI, AutoGPT, and other AI agent frameworks. (828 stars, MIT)
- [neuro-san-studio](https://madewithwhat.net/langchain/project/neuro-san-studio/): A playground for neuro-san (827 stars, Apache-2.0)
- [Robby-chatbot](https://madewithwhat.net/langchain/project/robby-chatbot/): AI chatbot for chat with CSV, PDF, TXT files and YTB videos | using Langchain | OpenAI | Streamlit (816 stars, Apache-2.0)
- [vllora](https://madewithwhat.net/langchain/project/vllora/): Debug your AI agents (810 stars)
- [AgentChat](https://madewithwhat.net/langchain/project/agentchat/): AgentChat LLM ， Agent Agent。，Agent 。 LangChain、Function Call、MCP 、RAG、Memory、HITL、Skill、Milvus ElasticSearch ，， FastAPI 。 (802 stars, MIT)
- [IncarnaMind](https://madewithwhat.net/langchain/project/incarnamind/): Connect and chat with your multiple documents (pdf and txt) through GPT 3.5, GPT-4 Turbo, Claude and Local Open-Source LLMs (801 stars, Apache-2.0)
- [learn-generative-ai](https://madewithwhat.net/langchain/project/learn-generative-ai/): Learn Cloud Applied Generative AI Engineering (GenEng) using OpenAI, Gemini, Streamlit, Containers, Serverless, Postgres, LangChain, Pinecone, and Next.js (793 stars)
- [Agent_Memory_Techniques](https://madewithwhat.net/langchain/project/agent-memory-techniques/): Agent memory for LLMs: 30 runnable Jupyter notebooks covering conversation buffers, vector stores, knowledge graphs, episodic and semantic memory, MemGPT, Mem0, Letta, Zep, Graphiti, LoCoMo benchmarks, and production patterns. (784 stars, Apache-2.0)
- [skyagi](https://madewithwhat.net/langchain/project/skyagi/): SkyAGI: Emerging human-behavior simulation capability in LLM (777 stars, Apache-2.0)
- [llm-books](https://madewithwhat.net/langchain/project/llm-books/): LLM (767 stars)
- [semantic-search-nextjs-pinecone-langchain-chatgpt](https://madewithwhat.net/langchain/project/semantic-search-nextjs-pinecone-langchain-chatgpt/): Embeds text files into vectors, stores them on Pinecone, and enables semantic search using GPT3 and Langchain in a Next.js UI (762 stars)
- [langchain-in-action](https://madewithwhat.net/langchain/project/langchain-in-action/): Practical LangChain patterns and implementations for real-world LLM applications. ：LangChain - LangChain。LangChain，。（），LangChain。 (761 stars)
- [miyagi](https://madewithwhat.net/langchain/project/miyagi/): Sample to envision intelligent apps with Microsoft's Copilot stack for AI-infused product experiences. (751 stars)
- [chatdocs](https://madewithwhat.net/langchain/project/chatdocs/): Chat with your documents offline using AI. (738 stars, MIT)
- [langchain-visualizer](https://madewithwhat.net/langchain/project/langchain-visualizer/): Visualization and debugging tool for LangChain workflows (736 stars, MIT)
- [langup-ai](https://madewithwhat.net/langchain/project/langup-ai/): AGI Bot. BiliBili | | @ | bot | | (727 stars, MIT)
- [open-ptc-agent](https://madewithwhat.net/langchain/project/open-ptc-agent/): An open source implementation of code execution with MCP (Programatic Tool Calling) (722 stars, MIT)
- [Interactive-LLM-Powered-NPCs](https://madewithwhat.net/langchain/project/interactive-llm-powered-npcs/): Interactive LLM Powered NPCs, is an open-source project that completely transforms your interaction with non-player characters (NPCs) in any game! (716 stars, MIT)
- [mcp-client-cli](https://madewithwhat.net/langchain/project/mcp-client-cli/): A simple CLI to run LLM prompt and implement MCP client. (678 stars, MIT)
- [PanWatch](https://madewithwhat.net/langchain/project/panwatch/): PanWatch · AI ， TradingAgents Agent | A//、、、 (671 stars, MIT)
- [RAGLight](https://madewithwhat.net/langchain/project/raglight/): RAGLight is a modular framework for Retrieval-Augmented Generation (RAG). It makes it easy to plug in different LLMs, embeddings, and vector stores, and now includes seamless MCP integration to connect external tools and data sources. (670 stars, MIT)
- [gpt-home](https://madewithwhat.net/langchain/project/gpt-home/): ChatGPT at home! A better alternative to commercial smart home assistants, built on the Raspberry Pi using LiteLLM and LangGraph. (644 stars, GPL-3.0)
- [langgraph-course](https://madewithwhat.net/langchain/project/langgraph-course/): Hands-on LangGraph course repo for building production-grade LLM agents with Agentic RAG, ReAct, and reflection workflows. (638 stars, Apache-2.0)
- [langchain-ask-pdf](https://madewithwhat.net/langchain/project/langchain-ask-pdf/): An AI-app that allows you to upload a PDF and ask questions about it. It uses OpenAI's LLMs to generate a response. (636 stars)
- [paper_to_podcast](https://madewithwhat.net/langchain/project/paper-to-podcast/): A very quick project that transforms research papers into engaging three-person discussions, offering an intuitive and thought-provoking listening experience. Perfect for podcast enthusiasts seeking a fresh way to explore academic content. (618 stars, Apache-2.0)
- [hackerai](https://madewithwhat.net/langchain/project/hackerai/): Find and fix vulnerabilities by chatting with AI (613 stars)
- [swarmclaw](https://madewithwhat.net/langchain/project/swarmclaw/): Open-source self-hosted AI agent runtime and multi-agent framework for autonomous agent swarms. Agent memory, MCP tools, schedules, delegation, and 23+ LLM providers (Claude, GPT, Gemini, OpenRouter, Ollama). A practical Claude Code and LangChain alternative. (611 stars, MIT)
- [agentchain](https://madewithwhat.net/langchain/project/agentchain/): Chain together LLMs for reasoning & orchestrate multiple large models for accomplishing complex tasks (610 stars, MIT)
- [ai-hedge-fund-crypto](https://madewithwhat.net/langchain/project/ai-hedge-fund-crypto/): AI-Hedge-Fund for Crypto AI-powered hedge fund for cryptocurrency trading, leveraging LLM agents for intelligent decision-making. (604 stars, MIT)
- [END-TO-END-GENERATIVE-AI-PROJECTS](https://madewithwhat.net/langchain/project/end-to-end-generative-ai-projects/): End to End Generative AI Industry Projects on LLM Models with Deployment_Awesome LLM Projects (604 stars, MIT)
- [YT-Navigator](https://madewithwhat.net/langchain/project/yt-navigator/): YT Navigator: AI-powered YouTube content explorer that lets you search and chat with channel videos using AI agents. Extract insights from hours of content in seconds with semantic search and precise timestamps. (601 stars, MIT)
- [ChatPilot](https://madewithwhat.net/langchain/project/chatpilot/): ChatPilot: Chat Agent Web UI，Chat，Google、（RAG）、，Kimi Chat。 (600 stars, Apache-2.0)
- [can-ai-code](https://madewithwhat.net/langchain/project/can-ai-code/): Self-evaluating interview for AI coders (599 stars, MIT)
- [openchatbi](https://madewithwhat.net/langchain/project/openchatbi/): OpenChatBI is an intelligent chat-based BI tool powered by large language models, designed to help users query, analyze, and visualize data through natural language conversations. It uses LangGraph and LangChain to build chat agent and workflows that support natural language to SQL conversion and data analysis. (598 stars, MIT)
- [dr-doc-search](https://madewithwhat.net/langchain/project/dr-doc-search/): Converse with book - Built with GPT-3 (598 stars, MIT)
- [AI-Bank-Statement-Document-Automation-By-LLM-And-Personal-Finanical-Analysis-Prediction](https://madewithwhat.net/langchain/project/ai-bank-statement-document-automation-by-llm-and-personal-finanical-analysis-prediction/): AI Bank Statement Document Automation By LLM model and Personal Finanical Analysis (597 stars, Apache-2.0)
- [AI-in-a-Box](https://madewithwhat.net/langchain/project/ai-in-a-box/): AI-in-a-Box leverages the expertise of Microsoft across the globe to develop and provide AI and ML solutions to the technical community. Our intent is to present a curated collection of solution accelerators that can help engineers establish their AI/ML environments and solutions rapidly and with minimal friction. (596 stars, MIT)
- [VLog](https://madewithwhat.net/langchain/project/vlog/): [CVPR 2025] Video Narration as Vocabulary & Video as Long Document (588 stars)
- [Langchain1.0-Langgraph1.0-Learning](https://madewithwhat.net/langchain/project/langchain1-0-langgraph1-0-learning/): LangChain 1.0 LangGraph 1.0 ，agent，。 (586 stars, MIT)
- [CookHero](https://madewithwhat.net/langchain/project/cookhero/): CookHero LLM + RAG + Agent + ，、、AI 、、Web ， ReAct Agent / Subagent ，“”。 (578 stars, Apache-2.0)
- [DeepZero](https://madewithwhat.net/langchain/project/deepzero/): Find zero-days while you sleep. DeepZero is an automated vulnerability research framework that parses, decompiles, and analyzes thousands of Windows kernel drivers for exploitable IOCTLs natively using AI agents. (577 stars, MIT)
- [langchain-java](https://madewithwhat.net/langchain/project/langchain-java/): Java version of LangChain, while empowering LLM for Big Data. (566 stars, Apache-2.0)
- [ArXivChatGuru](https://madewithwhat.net/langchain/project/arxivchatguru/): Use ArXiv ChatGuru to talk to research papers. This app uses LangChain, OpenAI, Streamlit, and Redis as a vector database/semantic cache. (562 stars, MIT)
- [ragbook-notebooks](https://madewithwhat.net/langchain/project/ragbook-notebooks/): Repository for the "Building LLMs for Production" book by Towards AI. (554 stars)
- [fullstack-solution-template-for-agentcore](https://madewithwhat.net/langchain/project/fullstack-solution-template-for-agentcore/): Flexible Fullstack solution template for production-ready deployments of any use case on Amazon Bedrock AgentCore. (554 stars, Apache-2.0)
- [snowChat](https://madewithwhat.net/langchain/project/snowchat/): Chat snowflake - Text to SQL (553 stars)
- [ScienceClaw](https://madewithwhat.net/langchain/project/scienceclaw/): ScienceClaw is a personal research assistant built with LangChain DeepAgents and AIO Sandbox infrastructure, adopting a completely new architecture beyond OpenClaw. It offers stronger security, better transparency, and a more user-friendly experience. (553 stars)
- [Swarm](https://madewithwhat.net/langchain/project/swarm/): LangGraph for Swift — build stateful AI agent workflows natively on Apple/Linux platforms. (552 stars, MIT)
- [langchain-examples](https://madewithwhat.net/langchain/project/langchain-examples/): A collection of apps powered by the LangChain LLM framework. (549 stars, MIT)
- [generative-ai-cdk-constructs](https://madewithwhat.net/langchain/project/generative-ai-cdk-constructs/): AWS Generative AI CDK Constructs are sample implementations of AWS CDK for common generative AI patterns. (541 stars, Apache-2.0)
- [simplemind](https://madewithwhat.net/langchain/project/simplemind/): Python API client for AI providers that intends to replace LangChain and LangGraph for most common use cases. (541 stars, Apache-2.0)
- [ollama_pdf_rag](https://madewithwhat.net/langchain/project/ollama-pdf-rag/): A full-stack demo showcasing a local RAG (Retrieval Augmented Generation) pipeline to chat with your PDFs. (529 stars, MIT)
- [wdoc](https://madewithwhat.net/langchain/project/wdoc/): Summarize and query from a lot of heterogeneous documents. Any LLM provider, any filetype, advanced RAG, advanced summaries, scriptable, etc (518 stars, AGPL-3.0)
- [promptulate](https://madewithwhat.net/langchain/project/promptulate/): Lightweight Large language model automation and Autonomous Language Agents development framework. Build your LLM Agent Application in a pythonic way! (513 stars, Apache-2.0)
- [ReMind](https://madewithwhat.net/langchain/project/remind/): Your Local Artificial Memory on your Device. (512 stars, Apache-2.0)
- [restai](https://madewithwhat.net/langchain/project/restai/): RESTai is an AIaaS (AI as a Service) open-source platform. Supports many public and local LLM suported by Ollama/vLLM/etc. Precise embeddings usage, tuning, analytics etc. Built-in image/audio generation with dynamic loading generators. Live chat deployment. Built-in block based graphical language. Prompt versioning and much more... (512 stars, Apache-2.0)
- [dawnai](https://madewithwhat.net/langchain/project/dawnai/): Build LangGraph agents like Next.js apps. (510 stars, MIT)
- [CoexistAI](https://madewithwhat.net/langchain/project/coexistai/): CoexistAI is a modular, developer-friendly research assistant framework. It enables you to build, search, summarize, and automate research workflows using LLMs, web search, Reddit, YouTube, and mapping tools—all with simple MCP tool calls or API calls or Python functions. (507 stars)
- [eidolon](https://madewithwhat.net/langchain/project/eidolon/): The first AI Agent Server, Eidolon is a pluggable Agent SDK and enterprise ready, deployment server for Agentic applications (494 stars, Apache-2.0)
- [firesearch](https://madewithwhat.net/langchain/project/firesearch/): AI-powered deep research tool that breaks down complex queries, validates answers, and provides cited comprehensive results using Firecrawl and LangGraph (493 stars)
- [Advanced_RAG](https://madewithwhat.net/langchain/project/advanced-rag/): Advanced Retrieval-Augmented Generation (RAG) through practical notebooks, using the power of the Langchain, OpenAI GPTs,META LLAMA3,Agents. (483 stars)
- [parllama](https://madewithwhat.net/langchain/project/parllama/): TUI for Ollama and other LLM providers (480 stars, MIT)
- [langchain-production-starter](https://madewithwhat.net/langchain/project/langchain-production-starter/): Deploy LangChain Agents and connect them to Telegram (477 stars)
- [AgentLLM](https://madewithwhat.net/langchain/project/agentllm/): AgentLLM is a PoC for browser-native autonomous agents (470 stars, GPL-3.0)
- [boxcars](https://madewithwhat.net/langchain/project/boxcars/): Building applications with composability using Boxcars with LLM's. (463 stars, MIT)
- [GPTRouter](https://madewithwhat.net/langchain/project/gptrouter/): Smoothly Manage Multiple LLMs (OpenAI, Anthropic, Azure) and Image Models (Dall-E, SDXL), Speed Up Responses, and Ensure Non-Stop Reliability. (454 stars, MIT)
- [autonomous-hr-chatbot](https://madewithwhat.net/langchain/project/autonomous-hr-chatbot/): An autonomous HR agent that can answer user queries using tools (453 stars, MIT)
- [ChatLLM](https://madewithwhat.net/langchain/project/chatllm/): LLMopenai&langchain，、、、ChatGLM (449 stars, MIT)
- [predikit](https://madewithwhat.net/langchain/project/predikit/): The missing bridge between your ML models and your AI agents. (448 stars, MIT)
- [MindSQL](https://madewithwhat.net/langchain/project/mindsql/): MindSQL: A Python Text-to-SQL RAG Library simplifying database interactions. Seamlessly integrates with PostgreSQL, MySQL, SQLite, Snowflake, and BigQuery. Powered by GPT-4 and Llama 2, it enables natural language queries. Supports ChromaDB and Faiss for context-aware responses. (445 stars, GPL-3.0)
- [sagify](https://madewithwhat.net/langchain/project/sagify/): LLMs and Machine Learning done easily (443 stars, MIT)
- [dialog](https://madewithwhat.net/langchain/project/dialog/): RAG LLM Ops App for easy deployment and testing (429 stars, MIT)
- [langstream](https://madewithwhat.net/langchain/project/langstream/): LangStream. Event-Driven Developer Platform for Building and Running LLM AI Apps. Powered by Kubernetes and Kafka. (428 stars, Apache-2.0)
- [chatluna](https://madewithwhat.net/langchain/project/chatluna/): ，，， | A bot plugin for LLM chat with multi-model integration, extensibility, and various output formats (426 stars, AGPL-3.0)
- [django-ai-assistant](https://madewithwhat.net/langchain/project/django-ai-assistant/): Integrate AI Assistants with Django to build intelligent applications (425 stars, MIT)
- [mcpadapt](https://madewithwhat.net/langchain/project/mcpadapt/): Unlock 650+ MCP servers tools in your favorite agentic framework. (422 stars, MIT)
- [scraperai](https://madewithwhat.net/langchain/project/scraperai/): ScraperAI is an open-source, AI-powered tool designed to simplify web scraping for users of all skill levels. (420 stars, GPL-3.0)
- [easy-langent](https://madewithwhat.net/langchain/project/easy-langent/): “langent”“lang”“agent” (418 stars, Apache-2.0)
- [lobe-cli-toolbox](https://madewithwhat.net/langchain/project/lobe-cli-toolbox/): Lobe CLI Toolbox - AI CLI Toolbox, enhancing git commit and i18n workflow efficiency (414 stars, MIT)
- [resume_render_from_job_description](https://madewithwhat.net/langchain/project/resume-render-from-job-description/): Resume_Builder_AIHawk is a powerful Python tool that allows you to automatically customize your resume based on a job URL, ensuring it perfectly aligns with the job requirements and skills. With an interactive command-line interface, this tool makes it easy to navigate through options and select from various pre-defined styles (410 stars, MIT)
- [local-assistant-examples](https://madewithwhat.net/langchain/project/local-assistant-examples/): Build your own ChatPDF and run it locally (409 stars, MIT)
- [llm-strategy](https://madewithwhat.net/langchain/project/llm-strategy/): Directly Connecting Python to LLMs via Strongly-Typed Functions, Dataclasses, Interfaces & Generic Types (399 stars, MIT)
- [langchain-google](https://madewithwhat.net/langchain/project/langchain-google/): LangChain interfaces to Google's suite of AI products (e.g. Gemini & Vertex AI) (392 stars, MIT)
- [open-research-ANA](https://madewithwhat.net/langchain/project/open-research-ana/): An open-source, AI agent-native research canvas application that performs real-time search with HITL (Human in The Loop) capabilities, powered by CopilotKit, Tavily and LangGraph (391 stars)
- [Adrian](https://madewithwhat.net/langchain/project/adrian/): Open-source runtime AI agent security tool - monitors and controls AI agents, catching malicious tool use, prompt injection, and policy drift in real time, before the agent acts. (390 stars, Apache-2.0)
- [RAGNotebook](https://madewithwhat.net/langchain/project/ragnotebook/): LangChain、FastAPIReactRAG，RAG，base-ragRAG (387 stars, MIT)
- [localforge](https://madewithwhat.net/langchain/project/localforge/): Local coding agent with neat UI (387 stars, MIT)
- [LLMstudio](https://madewithwhat.net/langchain/project/llmstudio/): Framework to bring LLM applications to production (384 stars, MPL-2.0)
- [gpt-runner](https://madewithwhat.net/langchain/project/gpt-runner/): Conversations with your files! Manage and run your AI presets! (382 stars, MIT)
- [lc-studylab](https://madewithwhat.net/langchain/project/lc-studylab/): LC-StudyLab LangChain v1.0 ， LangGraph、DeepAgents、RAG 、Guardrails ， LangChain v1 (381 stars, MIT)
- [agent-craft](https://madewithwhat.net/langchain/project/agent-craft/): AI Agent | LangChain、RAG、LangGraph、MCP | | | (381 stars, MIT)
- [repo2pdf](https://madewithwhat.net/langchain/project/repo2pdf/): repo2pdf is a tool that allows you to convert a GitHub repository into a PDF file. It clones the repository, processes the files, and then creates a PDF. --- DOCS: https://bankkroll-repo2pdf.mintlify.app (373 stars, MIT)
- [Aegis](https://madewithwhat.net/langchain/project/aegis/): Runtime policy enforcement for AI agents. Cryptographic audit trail, human-in-the-loop approvals, kill switch. Zero code changes. (365 stars, MIT)
- [open-assistant-api](https://madewithwhat.net/langchain/project/open-assistant-api/): The Open Assistant API is a ready-to-use, open-source, self-hosted agent/gpts orchestration creation framework, supporting customized extensions for LLM, RAG, function call, and tools capabilities. It also supports seamless integration with the openai/langchain sdk. (364 stars, MIT)
- [Multi-Agent-AI-System](https://madewithwhat.net/langchain/project/multi-agent-ai-system/): Building a Multi-Agent AI System with LangGraph and LangSmith (361 stars, MIT)
- [repogpt](https://madewithwhat.net/langchain/project/repogpt/): RepoGPT: AI-powered GitHub assistant to chat, manage, and explore your repos effortlessly. (360 stars, MIT)
- [site-rag](https://madewithwhat.net/langchain/project/site-rag/): A Chrome extension for asking questions over websites (358 stars)
- [GustoBot](https://madewithwhat.net/langchain/project/gustobot/): :Multi-Agent ，langraph，txt2sql,txt2cypher, lightrag, (354 stars, Apache-2.0)
- [create-t3-turbo-ai](https://madewithwhat.net/langchain/project/create-t3-turbo-ai/): Build full-stack, type-safe, LLM-powered apps with the T3 Stack, Turborepo, OpenAI, and Langchain (354 stars, MIT)
- [Octopoda-OS](https://madewithwhat.net/langchain/project/octopoda-os/): The open-source memory operating system for AI agents. Persistent memory, semantic search, loop detection, agent messaging, crash recovery, and real-time observability. (353 stars)
- [megabots](https://madewithwhat.net/langchain/project/megabots/): State-of-the-art, production ready LLM apps made mega-easy, so you don't have to build them from scratch Create a bot, now (349 stars, MIT)
- [ThinkRAG](https://madewithwhat.net/langchain/project/thinkrag/): A LLM RAG system runs on your laptop. ，，。 (347 stars, MIT)
- [palico-ai](https://madewithwhat.net/langchain/project/palico-ai/): Build, Improve Performance, and Productionize your AI Application (342 stars, MIT)
- [sales-outreach-automation-langgraph](https://madewithwhat.net/langchain/project/sales-outreach-automation-langgraph/): Automate lead research, qualification, and outreach with AI agents and Langgraph, creating personalized messaging and connecting with your CRMs (HubSpot, Airtable, Google Sheets) (342 stars)
- [funcchain](https://madewithwhat.net/langchain/project/funcchain/): build cognitive systems, pythonic (341 stars, MIT)
- [CSV-AI](https://madewithwhat.net/langchain/project/csv-ai/): CSV-AI is the ultimate app powered by LangChain, OpenAI, and Streamlit that allows you to unlock hidden insights in your CSV files. With CSV-AI, you can effortlessly interact with, summarize, and analyze your CSV files in one convenient place. (340 stars, MIT)
- [agentica](https://madewithwhat.net/langchain/project/agentica/): Agentica: Lightweight async-first Python framework for AI agents. AI Agent，、RAG、MCP。 (332 stars, Apache-2.0)
- [langchain-aws](https://madewithwhat.net/langchain/project/langchain-aws/): Build LangChain Applications on AWS (331 stars, MIT)
- [lang-agent](https://madewithwhat.net/langchain/project/lang-agent/): LangChainLangGraphAI Agent (331 stars, Apache-2.0)
- [openai](https://madewithwhat.net/langchain/project/openai/): LLMs Best Tricks (328 stars, MIT)
- [Instrukt](https://madewithwhat.net/langchain/project/instrukt/): Integrated AI environment in the terminal. Build, test and instruct agents. (328 stars, AGPL-3.0)
- [QA-Pilot](https://madewithwhat.net/langchain/project/qa-pilot/): QA-Pilot is an interactive chat project that leverages online/local LLM for rapid understanding and navigation of GitHub code repository. (326 stars, Apache-2.0)
- [documentation-helper](https://madewithwhat.net/langchain/project/documentation-helper/): Reference implementation of a RAG-based documentation helper using LangChain, Pinecone, and Tavily.. (326 stars, Apache-2.0)
- [ai-playground](https://madewithwhat.net/langchain/project/ai-playground/): Code from tutorials presented on the "Code AI with Rok" YouTube channel (322 stars, MIT)
- [DataChad](https://madewithwhat.net/langchain/project/datachad/): Ask questions about any data source by leveraging langchains (321 stars, Apache-2.0)
- [ChatGPT-OpenAI-Smart-Speaker](https://madewithwhat.net/langchain/project/chatgpt-openai-smart-speaker/): This AI Smart Speaker uses speech recognition, TTS (text-to-speech), and STT (speech-to-text) to enable voice and vision-driven conversations, with additional web search capabilities via OpenAI and Langchain agents. (318 stars, MIT)
- [repochat](https://madewithwhat.net/langchain/project/repochat/): Chatbot assistant enabling GitHub repository interaction using LLMs with Retrieval Augmented Generation (317 stars, Apache-2.0)
- [leanctx](https://madewithwhat.net/langchain/project/leanctx/): Drop-in prompt compression for production LLM apps. Cut your token bill 40-60% without changing your code. Python SDK, LLMLingua-2, MIT. (312 stars, MIT)
- [CyberClaw](https://madewithwhat.net/langchain/project/cyberclaw/): | Next-Gen Transparent Agent Architecture | | | ⏰ P0 80% | OpenClaw + Claude Code (312 stars, MIT)
- [summarizepaper](https://madewithwhat.net/langchain/project/summarizepaper/): An AI-powered arXiv paper summarization website with a virtual assistant for answering questions. (310 stars)
- [second-brain-agent](https://madewithwhat.net/langchain/project/second-brain-agent/): Second Brain AI agent (308 stars, GPL-3.0)
- [DistiLlama](https://madewithwhat.net/langchain/project/distillama/): Chrome Extension to Summarize or Chat with Web Pages/Local Documents Using locally running LLMs. Keep all of your data and conversations private. (305 stars, MIT)
- [langtorch](https://madewithwhat.net/langchain/project/langtorch/): Building composable LLM applications & workflow with Java. (305 stars, MIT)
- [flowgpt](https://madewithwhat.net/langchain/project/flowgpt/): Generate diagram with AI (304 stars, MIT)
- [bookwith](https://madewithwhat.net/langchain/project/bookwith/): BookWith – A New Reading Experience with AI. A next-generation conversational reading platform that goes beyond traditional e-book readers (302 stars, AGPL-3.0)
- [local_llama](https://madewithwhat.net/langchain/project/local-llama/): This repo is to showcase how you can run a model locally and offline, free of OpenAI dependencies. (297 stars, Apache-2.0)
- [reelsmaker](https://madewithwhat.net/langchain/project/reelsmaker/): ReelsMaker is a Python-based/streamlit application designed to create captivating faceless videos for social media platforms like TikTok and YouTube. (294 stars, MIT)
- [oreilly-ai-agents](https://madewithwhat.net/langchain/project/oreilly-ai-agents/): An introduction to the world of AI Agents (293 stars)
- [agent_learning](https://madewithwhat.net/langchain/project/agent-learning/): A systematic AI Agent development tutorial covering LLM agents, RAG, tool use, memory systems, multi-agent systems, LangChain, LangGraph, MCP, and agentic RL.｜ AI Agent | 、、 Agent | arXiv | Learn AI Agent Development from Scratch (293 stars, MIT)
- [ai-devices](https://madewithwhat.net/langchain/project/ai-devices/): AI Device Template Featuring Whisper, TTS, Groq, Llama3, OpenAI and more (293 stars, MIT)
- [lawglance](https://madewithwhat.net/langchain/project/lawglance/): A free open source RAG based AI legal assistant. (292 stars, Apache-2.0)
- [LLMChat](https://madewithwhat.net/langchain/project/llmchat/): A full-stack Webui implementation of Large Language model, such as ChatGPT or LLaMA. (291 stars, MIT)
- [llama-github](https://madewithwhat.net/langchain/project/llama-github/): Llama-github is an open-source Python library that empowers LLM Chatbots, AI Agents, and Auto-dev Solutions to conduct Agentic RAG from actively selected GitHub public projects. It Augments through LLMs and Generates context for any coding question, in order to streamline the development of sophisticated AI-driven applications. (291 stars, Apache-2.0)
- [ROScribe](https://madewithwhat.net/langchain/project/roscribe/): Write your robot software in minutes. (290 stars, MIT)
- [generativeAgent_LLM](https://madewithwhat.net/langchain/project/generativeagent-llm/): Implementation of "Generative Agents: Interactive Simulacra of Human Behavior" paper with Guidance and Langchain. Full features and work with local LLMs. (288 stars)
- [GPT-Synthesizer](https://madewithwhat.net/langchain/project/gpt-synthesizer/): Software design & development with AI (287 stars, MIT)
- [local-LLM-with-RAG](https://madewithwhat.net/langchain/project/local-llm-with-rag/): Running local Language Language Models (LLM) to perform Retrieval-Augmented Generation (RAG) (286 stars, MIT)
- [langchain-chat-with-documents](https://madewithwhat.net/langchain/project/langchain-chat-with-documents/): Chat with documents (pdf, docx, txt) using ChatGPT and Langchain (286 stars, MIT)
- [SecGPT](https://madewithwhat.net/langchain/project/secgpt/): A Test Project for a Network Security-oriented LLM Tool Emulating AutoGPT (286 stars, Apache-2.0)
- [DashClaw](https://madewithwhat.net/langchain/project/dashclaw/): The governance runtime for AI agents. Intercept actions, enforce guard policies, require approvals, and produce audit-ready decision trails. (284 stars, MIT)
- [Autoxhs](https://madewithwhat.net/langchain/project/autoxhs/): Autoxsh is an open-source tool that utilizes OpenAI's API to automate the generation and publishing of content on Xiaohongshu (Little Red Book), including images, titles, text, and tags. (284 stars)
- [dexter-jp](https://madewithwhat.net/langchain/project/dexter-jp/): AI｜AI agent for deep financial research on Japanese listed companies. Powered by EDINET DB + J-Quants. (283 stars, MIT)
- [learning-llms-and-genai-for-dev-sec-ops](https://madewithwhat.net/langchain/project/learning-llms-and-genai-for-dev-sec-ops/): A set of lessons aimed at anyone learning LLM and generative AI concepts, with sections on operations and security, as well as development. (282 stars)
- [langgraphgo](https://madewithwhat.net/langchain/project/langgraphgo/): langgraph for Go (281 stars, MIT)
- [langchain-chatbot](https://madewithwhat.net/langchain/project/langchain-chatbot/): Examples of chatbot implementations with Langchain and Streamlit (277 stars, Apache-2.0)
- [cognify](https://madewithwhat.net/langchain/project/cognify/): Multi-Faceted AI Agent and Workflow Autotuning. Automatically optimizes LangChain, LangGraph, DSPy programs for better quality, lower execution latency, and lower execution cost. Also has a simple agent/workflow framework (277 stars, Apache-2.0)
- [langgraphgo](https://madewithwhat.net/langchain/project/langgraphgo/): It's actively developed around agent, agentic, ai, and is a solid reference for anyone building with these tools. (275 stars, MIT)
- [Paper-Agent](https://madewithwhat.net/langchain/project/paper-agent/): Paper-Agent 。（AutoGen + LangGraph），（NLP）、，、，。Paper-Agent 、、、，。、、，。 (274 stars, MIT)
- [LangChain-ReAct-Agent](https://madewithwhat.net/langchain/project/langchain-react-agent/): LangChain/LangGraph ReAct Agent ， RAG、 Streamlit ，。 (270 stars, MIT)
- [MisakaNet](https://madewithwhat.net/langchain/project/misakanet/): A zero-dependency, git-backed micro-lesson library for AI Agents to asynchronously share and search verified debugging experience. Python stdlib only. | https://misakanet.org (263 stars, Apache-2.0)
- [GPTInterviewer](https://madewithwhat.net/langchain/project/gptinterviewer/): GPT Interviewer - Practice interview with AI interviewer based on job descriptions and resume (262 stars, MIT)
- [langgraph-email-automation](https://madewithwhat.net/langchain/project/langgraph-email-automation/): Multi AI agents for customer support email automation built with Langchain & Langgraph (259 stars)
- [cryptocurrency.cv](https://madewithwhat.net/langchain/project/cryptocurrency-cv/): Free crypto news API - real-time aggregator for Bitcoin, Ethereum, DeFi, Solana & altcoins. No API key required. RSS/Atom feeds, JSON REST API, historical archive with market context, embeddable widgets, ChatGPT plugin, Claude MCP server, SDKs (Python, TypeScript, Go, React, PHP). AI/LLM ready. Vibe coding friendly. Open source. (259 stars)
- [benchllm](https://madewithwhat.net/langchain/project/benchllm/): Continuous Integration for LLM powered applications (259 stars, MIT)
- [akcio](https://madewithwhat.net/langchain/project/akcio/): Akcio is a demonstration project for Retrieval Augmented Generation (RAG). It leverages the power of LLM to generate responses and uses vector databases to fetch relevant documents to enhance the quality and relevance of the output. (258 stars)
- [llama_ros](https://madewithwhat.net/langchain/project/llama-ros/): llama.cpp (GGUF LLMs) and llava.cpp (GGUF VLMs) for ROS 2 (258 stars, MIT)
- [docGPT-langchain](https://madewithwhat.net/langchain/project/docgpt-langchain/): Free GPT-3.5 chat with your docs (PDF, WORD, CSV, TXT) (257 stars, MIT)
- [dolphin](https://madewithwhat.net/langchain/project/dolphin/): General video interaction platform based on LLMs, including Video ChatGPT (257 stars, MIT)
- [deepdoc](https://madewithwhat.net/langchain/project/deepdoc/): Deep research tool for local knowledge base. (256 stars, MIT)
- [GPT-Automator](https://madewithwhat.net/langchain/project/gpt-automator/): Your voice-controlled Mac assistant (255 stars)
- [voxelgpt](https://madewithwhat.net/langchain/project/voxelgpt/): AI assistant that can query visual datasets, search the FiftyOne docs, and answer general computer vision questions (255 stars, Apache-2.0)
- [nim-anywhere](https://madewithwhat.net/langchain/project/nim-anywhere/): Accelerate your Gen AI with NVIDIA NIM and NVIDIA AI Workbench (255 stars, Apache-2.0)
- [conversational-agent-langchain](https://madewithwhat.net/langchain/project/conversational-agent-langchain/): FastAPI Backend for a Conversational Agent using Cohere, (Azure) OpenAI, Langchain & Langgraph and Qdrant as VectorDB (254 stars, MIT)
- [oneShotCodeGen](https://madewithwhat.net/langchain/project/oneshotcodegen/): Create full stack webapps with single prompt (253 stars)
- [RapidRAG](https://madewithwhat.net/langchain/project/rapidrag/): QA based on local knowledge and LLM. (250 stars, Apache-2.0)
- [BYO-LLM-WIKI](https://madewithwhat.net/langchain/project/byo-llm-wiki/): Build your own LLM-native WIKI (knowledge library). Search, extract, summarize, Q&A with contextual RAG, layered knowledge graph, and reinforced memory. Importantly use selected context to automatically generate skills, empowered by Claude subagents + CodeAct pipeline and gated by human review. Try Live Demo: https://byo-wiki-demo.onrender.com (249 stars)
- [event-deep-research](https://madewithwhat.net/langchain/project/event-deep-research/): AI Agent that researches the lives of historical figures and extracts events into structured JSON timelines using LangGraph multi-agent orchestration. (249 stars, MIT)
- [llm-movieagent](https://madewithwhat.net/langchain/project/llm-movieagent/): Semantic layer on top of a graph database to provide an LLM with a set of robust tools to interact with the database (247 stars, MIT)
- [gpt-instagram](https://madewithwhat.net/langchain/project/gpt-instagram/): A GPT-based autonomous multi-agent AI in Next.js that research & recommends Instagram Viral Posts reflecting your personality. (244 stars, MIT)
- [rag-ecosystem](https://madewithwhat.net/langchain/project/rag-ecosystem/): Understand and code every important component of RAG architecture (243 stars, MIT)
- [Ally](https://madewithwhat.net/langchain/project/ally/): A local private agentic system that works in your terminal. (241 stars, Apache-2.0)
- [prompt-cache](https://madewithwhat.net/langchain/project/prompt-cache/): Cut LLM costs by up to 80% and unlock sub-millisecond responses with intelligent semantic caching.A drop-in, provider-agnostic LLM proxy written in Go with sub-millisecond response (240 stars, MIT)
- [A5-Browser-Use](https://madewithwhat.net/langchain/project/a5-browser-use/): Your commands control the browser - made easy | Chrome Extension and RESTful API for Browser-Use (239 stars)
- [identity-rag-customer-insights-chatbot](https://madewithwhat.net/langchain/project/identity-rag-customer-insights-chatbot/): Connect to your customer data using any LLM and gain actionable insights. IdentityRAG creates a single comprehensive customer 360 view (golden record) by unifying, consolidating, disambiguating and deduplicating data across multiple sources through identity resolution. (238 stars, MIT)
- [question_extractor](https://madewithwhat.net/langchain/project/question-extractor/): Generate question/answer training pairs out of raw text. (238 stars, Apache-2.0)
- [ai-tutor-rag-system](https://madewithwhat.net/langchain/project/ai-tutor-rag-system/): This is a repository for the course "From Beginner to LLM Developer" by Towards AI. (238 stars)
- [financial-chat](https://madewithwhat.net/langchain/project/financial-chat/): A financial chat application powered by LangChain, OpenBB, and Claude 3 Opus. (237 stars)
- [team-of-ai-agents](https://madewithwhat.net/langchain/project/team-of-ai-agents/): Open-source framework to make AI agents' team collaboration as effective as human collaboration. (236 stars)
- [langchain-learning](https://madewithwhat.net/langchain/project/langchain-learning/): langchain，langchain、langchain、langchain。 (235 stars)
- [graphsignal-profiler](https://madewithwhat.net/langchain/project/graphsignal-profiler/): Graphsignal Profiler (235 stars, Apache-2.0)
- [langchain-decorators](https://madewithwhat.net/langchain/project/langchain-decorators/): syntactic sugar for langchain (234 stars, MIT)
- [gpt-all-star](https://madewithwhat.net/langchain/project/gpt-all-star/): AI-powered code generation tool for scratch development of web applications with a team collaboration of autonomous AI agents. (233 stars, MIT)
- [langchain_data_agent](https://madewithwhat.net/langchain/project/langchain-data-agent/): NL2SQL - Ask questions in plain English, get SQL queries and results. Powered by LangGraph. (232 stars, MIT)
- [AlphaSuite](https://madewithwhat.net/langchain/project/alphasuite/): AlphaSuite is an open-source quantitative analysis platform that gives you the power to build, test, and deploy professional-grade trading strategies. It's designed for traders and analysts who want to move beyond simple backtests and develop a genuine, data-driven edge in the financial markets. (230 stars, MIT)
- [langgraph-redis](https://madewithwhat.net/langchain/project/langgraph-redis/): Redis checkpointer and store for memory management in LangGraph (230 stars, MIT)
- [law_ai](https://madewithwhat.net/langchain/project/law-ai/): AI，RAG，200+、LLM，， langchain，Gradio，openai，chroma，duckduckgo-search (229 stars)
- [fastui-chat](https://madewithwhat.net/langchain/project/fastui-chat/): minimalistic ChatBot Interface in pure python (228 stars, MIT)
- [LangAlpha](https://madewithwhat.net/langchain/project/langalpha/): Multi-Agent Financial Research workflow (228 stars)
- [home-generative-agent](https://madewithwhat.net/langchain/project/home-generative-agent/): A home assistant generative agent integration based on langchain and langgraph. (225 stars, MIT)
- [gemini_multipdf_chat](https://madewithwhat.net/langchain/project/gemini-multipdf-chat/): Gemini PDF Chatbot: A Streamlit-based application powered by the Gemini conversational AI model. Upload multiple PDF files, extract text, and engage in natural language conversations to receive detailed responses based on the document context. Enhance your interaction with PDF documents using this intuitive and intelligent chatbot. (223 stars, MIT)
- [asqav-sdk](https://madewithwhat.net/langchain/project/asqav-sdk/): Python and TypeScript SDKs for verifiable evidence of AI agent actions. Signed receipts, policy enforcement, audit trails. Works with LangChain, CrewAI, MCP. (223 stars)
- [corpusos](https://madewithwhat.net/langchain/project/corpusos/): Open-source protocol suite standardizing LLM, Vector, Graph, and Embedding infrastructure across LangChain, LlamaIndex, AutoGen, CrewAI, Semantic Kernel, and MCP. 3,330+ conformance tests. One protocol. Any framework. Any provider. (223 stars, Apache-2.0)
- [CASALIOY](https://madewithwhat.net/langchain/project/casalioy/): Tiny toolkit for air-gapped LLMs on consumer-grade hardware (222 stars, Apache-2.0)
- [openai_trtllm](https://madewithwhat.net/langchain/project/openai-trtllm/): OpenAI compatible API for TensorRT LLM triton backend (221 stars, MIT)
- [hia](https://madewithwhat.net/langchain/project/hia/): Hia (Health Insights Agent) - AI Agent to analyze blood reports and provide detailed health insights. (221 stars, MIT)
- [rag-arena](https://madewithwhat.net/langchain/project/rag-arena/): Open-source RAG evaluation through users' feedback (220 stars, MIT)
- [weam](https://madewithwhat.net/langchain/project/weam/): Web app for teams of 20+ members. In-built connections to major LLMs via API. Share chats, prompts, and agents in team or private folders. Modern, fully responsive stack (Next.js, Node.js). Deploy your own vibe-coded AI apps, agents, or workflows or use ready-made solutions from the library. (219 stars)
- [fin-sight](https://madewithwhat.net/langchain/project/fin-sight/): FinSight - Financial Insights at Your Fingertip: FinSight is a cutting-edge AI assistant tailored for portfolio managers, investors, and finance enthusiasts. It streamlines the process of gaining crucial insights and summaries about a company in a user-friendly manner. (218 stars)
- [salute](https://madewithwhat.net/langchain/project/salute/): A simple and declarative way to control LLMs (218 stars, MIT)
- [HealthChain](https://madewithwhat.net/langchain/project/healthchain/): Python SDK for healthcare AI — typed, validated FHIR tools for agents, real-time EHR connectivity, production deployment (216 stars, Apache-2.0)
- [Local-LLM-Langchain](https://madewithwhat.net/langchain/project/local-llm-langchain/): Load local LLMs effortlessly in a Jupyter notebook for testing purposes alongside Langchain or other agents. Contains Oobagooga and KoboldAI versions of the langchain notebooks with examples. (216 stars)
- [AI-Blueprints](https://madewithwhat.net/langchain/project/ai-blueprints/): This repository hosts a growing collection of AI blueprint projects that run end-to-end using Jupyter notebooks, MLflow deployments, and Streamlit web apps. All projects are built using HP AI Studio with If you find this useful, please don’t forget to star the repository ⭐ and support our work (215 stars, MIT)
- [Autono](https://madewithwhat.net/langchain/project/autono/): A ReAct-Based Highly Robust Autonomous Agent (Harness) Framework. (212 stars, GPL-3.0)
- [pdf_parsing](https://madewithwhat.net/langchain/project/pdf-parsing/): PDF（，，，，），(ChatGLM2-6B, RWKV)+langchain+streamlitPDF，， (211 stars)
- [LangChain-for-LLM-Application-Development](https://madewithwhat.net/langchain/project/langchain-for-llm-application-development/): In LangChain for LLM Application Development, you will gain essential skills in expanding the use cases and capabilities of language models in application development using the LangChain framework. (210 stars)
- [autonomous-agentic-rag](https://madewithwhat.net/langchain/project/autonomous-agentic-rag/): Self improving agentic rag pipeline (209 stars, MIT)
- [ClassGPT](https://madewithwhat.net/langchain/project/classgpt/): ChatGPT for lecture slides (209 stars, MIT)
- [renumics-rag](https://madewithwhat.net/langchain/project/renumics-rag/): Visualization for a Retrieval-Augmented Generation (RAG) Assistant (207 stars, MIT)
- [AutoAgents](https://madewithwhat.net/langchain/project/autoagents/): Complex question answering in LLMs with enhanced reasoning and information-seeking capabilities. (207 stars, MIT)
- [AI-Resume-Analyzer-and-LinkedIn-Scraper-using-Generative-AI](https://madewithwhat.net/langchain/project/ai-resume-analyzer-and-linkedin-scraper-using-generative-ai/): Developed an AI application using LLM to analyze user resumes and provided the summarization, strengths, weaknesses, suggestions, suitable job titles, and also scraping job details from LinkedIn using Selenium. This application reduces time by 30% and helps candidates tailor their resumes effectively. (206 stars, MIT)
- [M-Cube](https://madewithwhat.net/langchain/project/m-cube/): M-Cube (M³) — Multi-thinking, Multimodal, Multi-verification Patent Drafting Assistant (205 stars, MIT)
- [LangGraphProjects](https://madewithwhat.net/langchain/project/langgraphprojects/): This is the official companion repository for the book The Complete LangGraph Blueprint: Build 50+ AI Agents for Business Success. The repository provides source code, practical examples, and resources to help you build dynamic AI agents using LangGraph, a cutting-edge graph-based framework for artificial intelligence workflows. (204 stars)
- [readwren](https://madewithwhat.net/langchain/project/readwren/): An adaptive multi-agent system that extracts your literary DNA through conversation and generates actionable reading profiles. (203 stars, MIT)
- [Local-Multimodal-AI-Chat](https://madewithwhat.net/langchain/project/local-multimodal-ai-chat/): Self-hostable multimodal chat with local LLMs (Ollama/OpenAI): PDF RAG, image chat, and Whisper voice, Streamlit + Docker. (203 stars, GPL-3.0)
- [traceAI](https://madewithwhat.net/langchain/project/traceai/): Open Source AI Tracing Framework built on Opentelemetry for AI Applications and Frameworks (203 stars, Apache-2.0)
- [KnowledgeBase-RAG-LLM-System](https://madewithwhat.net/langchain/project/knowledgebase-rag-llm-system/): Streamlit、LangChain Chroma RAG ，、。 (203 stars, MIT)
- [AI-agents-for-cybersecurity](https://madewithwhat.net/langchain/project/ai-agents-for-cybersecurity/): This repository contains resources and materials for courses and presentations related to AI Agents and Agentic Systems for Cybersecurity Operations by Omar Santos. (203 stars, BSD-3-Clause)
- [orchestkit](https://madewithwhat.net/langchain/project/orchestkit/): The Complete AI Development Toolkit for Claude Code — 114 skills, 37 agents, 212 hooks. Production-ready patterns for full-stack development. (202 stars, MIT)
- [EduGPT](https://madewithwhat.net/langchain/project/edugpt/): Implementation of an AI Instructor using LLMs and Langchain (201 stars, MIT)
- [wavefront](https://madewithwhat.net/langchain/project/wavefront/): Enterprise AI middleware, alternative to unifyapps, n8n, lyzr (200 stars)
- [esperanto](https://madewithwhat.net/langchain/project/esperanto/): A unified interface for various AI model providers (199 stars, MIT)
- [DocsMind](https://madewithwhat.net/langchain/project/docsmind/): DocsMind allows you to chat with your docs and summarize your docs, support pdf, md. (197 stars, AGPL-3.0)
- [agent-audit](https://madewithwhat.net/langchain/project/agent-audit/): Static security scanner for LLM agents — prompt injection, MCP config auditing, taint analysis. 51 rules mapped to OWASP Agentic Top 10 (2026). Works with LangChain, CrewAI, AutoGen. (195 stars, MIT)
- [langserve_ollama](https://madewithwhat.net/langchain/project/langserve-ollama/): 🇰🇷 LLM. LangServe, Ollama, streamlit + RAG (194 stars)
- [BentoChain](https://madewithwhat.net/langchain/project/bentochain/): A voice-enabled chatbot application built using of LangChain, text-to-speech, and speech-to-text models from Hugging Face, and BentoML. (194 stars)
- [idun-agent-platform](https://madewithwhat.net/langchain/project/idun-agent-platform/): Open-source runtime that ships any LangGraph or Google ADK agent as a production-ready FastAPI service. Bundled, AG-UI copilotkit API, chat UI, 15+ guardrails, MCP, OpenTelemetry, OIDC. One pip install. Self-hosted, no vendor lock-in. (194 stars, GPL-3.0)
- [promptlib](https://madewithwhat.net/langchain/project/promptlib/): A collection of prompts for use with GPT-4 via ChatGPT, OpenAI API w/ Gradio frontend & notebook (194 stars)
- [fiddler-auditor](https://madewithwhat.net/langchain/project/fiddler-auditor/): Fiddler Auditor is a tool to evaluate language models. (193 stars)
- [ToolBrain](https://madewithwhat.net/langchain/project/toolbrain/): A framework for agentic tool use training with reinforcement learning (193 stars)
- [CatGPT-Gateway](https://madewithwhat.net/langchain/project/catgpt-gateway/): Turn your ChatGPT or Claude account into a fully working OpenAI-compatible API. No API keys needed. Supports tool calling, vision, file attachments, and image generation. (192 stars, MIT)
- [uxie](https://madewithwhat.net/langchain/project/uxie/): pdf reader app with note taking, annotations, collaboration, ai features (chat, flashcards generation w. ai-feedbacks), tts and ocr. (191 stars)
- [LangChain-Chat-with-Your-Data](https://madewithwhat.net/langchain/project/langchain-chat-with-your-data/): Explore LangChain and build powerful chatbots that interact with your own data. Gain insights into document loading, splitting, retrieval, question answering, and more. (191 stars)
- [shopkeeper-agent](https://madewithwhat.net/langchain/project/shopkeeper-agent/): AI Agent， LangGraph ： LangGraph、FastAPI、Qdrant、Elasticsearch、MySQL React，、、 NL2SQL 、SQL 。，Docker ， ai-agents-from-zero 。、 Agent AI 。 (191 stars, MIT)
- [mcp-toolbox-sdk-python](https://madewithwhat.net/langchain/project/mcp-toolbox-sdk-python/): Python SDK for interacting with the MCP Toolbox for Databases. (191 stars, Apache-2.0)
- [watch-skill](https://madewithwhat.net/langchain/project/watch-skill/): Video understanding and self-verification for AI agents. Turn videos, streams, and agent screen recordings into searchable, timestamped evidence—then use THE LOOP to inspect, fix, and verify the work. MCP, CLI, REST, local-first. (191 stars, MIT)
- [Pilipili-AutoVideo](https://madewithwhat.net/langchain/project/pilipili-autovideo/): AI · · Fully Automated AI Video Agent · Local Deployment (190 stars)
- [LLM_book](https://madewithwhat.net/langchain/project/llm-book/): LLM (189 stars)
- [Resume-Screening-RAG-Pipeline](https://madewithwhat.net/langchain/project/resume-screening-rag-pipeline/): An LLM Chatbot that dynamically retrieves and processes resumes using RAG to perform resume screening. (189 stars, Apache-2.0)
- [open-extract](https://madewithwhat.net/langchain/project/open-extract/): Structured Data Extractor for AI Agents. Search your documents or the web for specific data and get it back in JSON or Markdown in a single tool call. (188 stars, MIT)
- [langchain-gpt4free](https://madewithwhat.net/langchain/project/langchain-gpt4free/): LangChain x gpt4free (188 stars, MIT)
- [langboot](https://madewithwhat.net/langchain/project/langboot/): Using Langchain's ideas to build SpringBoot AI applications | langchain，SpringBoot AI (187 stars, Apache-2.0)
- [LangGraph-Chatchat](https://madewithwhat.net/langchain/project/langgraph-chatchat/): A project worth exploring. (186 stars, Apache-2.0)
- [langchainzh](https://madewithwhat.net/langchain/project/langchainzh/): langchainlangchain (186 stars, MIT)
- [RAG-Chatbot-with-Confluence](https://madewithwhat.net/langchain/project/rag-chatbot-with-confluence/): RAG Chatbot with Confluence (184 stars, MIT)
- [LangChain-Tutior](https://madewithwhat.net/langchain/project/langchain-tutior/): LangChain ，deeplearning.ai ：Python、NodeJs、Golang (184 stars, MIT)
- [private-chatbot-mpt30b-langchain](https://madewithwhat.net/langchain/project/private-chatbot-mpt30b-langchain/): Chat with your data privately using MPT-30b (183 stars, MIT)
- [gpt4-openai-api](https://madewithwhat.net/langchain/project/gpt4-openai-api/): Python package that provides (unofficial) API access to the GPT-4 through chat.openai.com. Works with langchain. Supports search DALL-E 3, plugins, continuing generation. (183 stars)
- [DocPaws](https://madewithwhat.net/langchain/project/docpaws/): RAG ：、PDF 、Agent 、scope 、。FastAPI + Vue3 (182 stars, MIT)
- [chatpdf-gpt](https://madewithwhat.net/langchain/project/chatpdf-gpt/): ChatPDF-GPT is an innovative chat interface application powered by LangChain and OpenAI, allowing users to upload and chat with PDF documents, stored in Pinecone vector database and Supabase storage. (182 stars, MIT)
- [oxidizePdf](https://madewithwhat.net/langchain/project/oxidizepdf/): Pure Rust PDF library for AI/RAG: structure-aware chunking, no ML, no C deps. (182 stars, MIT)
- [deepsearch-academic](https://madewithwhat.net/langchain/project/deepsearch-academic/): An implementation of Google Deep Search with support for 1000+ references, local inference, chatting with your scraping session using RAPTOR, and report generation. (181 stars)
- [hal9](https://madewithwhat.net/langchain/project/hal9/): Hal9 — Create and Share Generative Apps (181 stars, MIT)
- [document-parsers-list](https://madewithwhat.net/langchain/project/document-parsers-list/): A comprehensive list of document parsers, covering PDF-to-text conversion and layout extraction. Each tested for support of tables, equations, handwriting, two-column layouts, and multi-column layouts. (180 stars)
- [twitter-agent](https://madewithwhat.net/langchain/project/twitter-agent/): Build AI-powered Agents for Twitter (179 stars, MIT)
- [deep-research-agent](https://madewithwhat.net/langchain/project/deep-research-agent/): Multi-agent autonomous research system using LangGraph and LangChain. Generates citation-backed reports with credibility scoring and web search (177 stars, MIT)
- [CampusX-courses](https://madewithwhat.net/langchain/project/campusx-courses/): Free courses offer by CampusX (176 stars)
- [personal-ai-assistant](https://madewithwhat.net/langchain/project/personal-ai-assistant/): Your personal AI assistant powered by multiple AI agents. Connects to WhatsApp, Slack, or Telegram to manage your emails, schedule, to-dos, messages, and daily research. (176 stars)
- [cnllm](https://madewithwhat.net/langchain/project/cnllm/): Python toolkit for Chinese LLMs, with flexible batch capacity, structured real-time visulization and automated accumulation for streaming, and explicit feedback on vendor-native parameter validation. (173 stars, Apache-2.0)
- [langchain-graphrag](https://madewithwhat.net/langchain/project/langchain-graphrag/): GraphRAG / From Local to Global: A Graph RAG Approach to Query-Focused Summarization (173 stars, Apache-2.0)
- [generative-ai-cdk-constructs-samples](https://madewithwhat.net/langchain/project/generative-ai-cdk-constructs-samples/): This repo provides sample generative AI stacks built atop the AWS Generative AI CDK Constructs. (172 stars, Apache-2.0)
- [c4-genai-suite](https://madewithwhat.net/langchain/project/c4-genai-suite/): c4 GenAI Suite (171 stars, Apache-2.0)
- [open-text-embeddings](https://madewithwhat.net/langchain/project/open-text-embeddings/): Open Source Text Embedding Models with OpenAI Compatible API (170 stars, MIT)
- [drqa](https://madewithwhat.net/langchain/project/drqa/): How to create Question-Answering system combining Langchain and OpenAI (169 stars)
- [llm-api](https://madewithwhat.net/langchain/project/llm-api/): Run any Large Language Model behind a unified API (169 stars, MIT)
- [SearchGPT](https://madewithwhat.net/langchain/project/searchgpt/): GPT Enhanced with Real-Time Web Browsing (168 stars, MIT)
- [RAG-Chatbot](https://madewithwhat.net/langchain/project/rag-chatbot/): RAG enabled Chatbots using LangChain and Databutton (168 stars, MIT)
- [Agent_In_Action](https://madewithwhat.net/langchain/project/agent-in-action/): Agentic AI (168 stars, MIT)
- [Code-Interpreter-Api](https://madewithwhat.net/langchain/project/code-interpreter-api/): Committed to being the best code interpreter in the world. (168 stars, GPL-3.0)
- [langforge](https://madewithwhat.net/langchain/project/langforge/): A Toolkit for Creating and Deploying LangChain Apps (167 stars, MIT)
- [libre-chat](https://madewithwhat.net/langchain/project/libre-chat/): Free and Open Source Large Language Model (LLM) chatbot web UI and API. Self-hosted, offline capable and easy to setup. (166 stars, MIT)
- [AgentQuant](https://madewithwhat.net/langchain/project/agentquant/): Autonomous quantitative trading research platform that transforms stock lists into fully backtested strategies using AI agents, real market data, and mathematical formulations, all without requiring any coding. (166 stars)
- [Multi-AI-Agent-Systems-with-crewAI](https://madewithwhat.net/langchain/project/multi-ai-agent-systems-with-crewai/): Automate complex business workflows with our Multi-AI-Agent Systems using crewAI. This framework leverages autonomous, role-specific AI agents to collaboratively perform multi-step tasks, enhancing efficiency and accuracy across various domains. Ideal for applications in resume tailoring, website design, research, customer support, and more. (166 stars)
- [manufacturing-agents](https://madewithwhat.net/langchain/project/manufacturing-agents/): Multi-agent LLM system for intelligent replenishment decisions in manufacturing supply chains (166 stars, Apache-2.0)
- [flexible-graphrag](https://madewithwhat.net/langchain/project/flexible-graphrag/): Python, LlamaIndex, LangChain, Docker Compose: 15 Property Graph, 4 RDF, 10 Vector, OpenSearch, Elasticsearch, Alfresco DBs. 13 data sources (9 auto-sync), KG auto-building, Ontologies, LLMs, Docling or LlamaParse doc processing, GraphRAG, RAG only, Hybrid Search, AI Chat. TypeScript React, Vue, Angular frontends, FastAPI REST backend, MCP Server. (164 stars, Apache-2.0)
- [legal-tech-chat](https://madewithwhat.net/langchain/project/legal-tech-chat/): Extract structured data from CUAD contracts using LangChain, build a knowledge graph, and query insights through a LangGraph agent - transforming legal agreements into actionable intelligence. (162 stars, MIT)
- [langgraph-in-action](https://madewithwhat.net/langchain/project/langgraph-in-action/): 《LangGraph 》 (162 stars)
- [MemoryBot](https://madewithwhat.net/langchain/project/memorybot/): A chatbot which remembers using LangChain OpenAI | Streamlit | DataButton (161 stars, MIT)
- [Free-personal-AI-Assistant-with-plugin](https://madewithwhat.net/langchain/project/free-personal-ai-assistant-with-plugin/): Would you like to use GPT4 with Plugins but don't want to pay $20/month? This is the solution! With this repository you can have free clone of ChatGPT with plugin (161 stars, GPL-3.0)
- [chat_with_your_docs](https://madewithwhat.net/langchain/project/chat-with-your-docs/): Discover and converse with advanced AI models like Mistral, LLAMA2, and GPT-3.5 from leading sources like OLLAMA, Hugging Face, and OpenAI. Easily extract insights from PDFs, web pages, and YouTube videos with our intuitive interface. Unlock the power of knowledge with seamless chat interactions. (160 stars, MIT)
- [LangGraph-learn](https://madewithwhat.net/langchain/project/langgraph-learn/): learning resource of langgraph for dummy (158 stars, MIT)
- [anchoring-ai](https://madewithwhat.net/langchain/project/anchoring-ai/): An open-source no-code tool for teams to collaborate on building, evaluating, and hosting applications leveraging GPT and other large language models. You could easily build and share LLM-powered apps, manage your budget and run batch jobs. (155 stars, Apache-2.0)
- [media-agent](https://madewithwhat.net/langchain/project/media-agent/): Scrape data from social media and chat with it using Langchain (155 stars)
- [langchain_demo](https://madewithwhat.net/langchain/project/langchain-demo/): Demo web project using the Elixir LangChain library (154 stars)
- [One-Eval](https://madewithwhat.net/langchain/project/one-eval/): Automated system for LLM evaluation via agents. Doc as below: (153 stars, Apache-2.0)
- [LangChain-for-LLM-Application-Development](https://madewithwhat.net/langchain/project/langchain-for-llm-application-development/): Apply LLMs to your data, build personal assistants, and expand your use of LLMs with agents, chains, and memories. (153 stars)
- [langchain-ask-csv](https://madewithwhat.net/langchain/project/langchain-ask-csv/): A Langchain app that allows you to ask questions to a CSV file (153 stars)
- [Langchain-ChatBI](https://madewithwhat.net/langchain/project/langchain-chatbi/): LangchainBI，、，、，，。 (153 stars)
- [zero-to-ai-fullstack](https://madewithwhat.net/langchain/project/zero-to-ai-fullstack/): A Java backend engineer learning AI full-stack in public — Python · FastAPI · RAG · pgvector · Next.js (153 stars, MIT)
- [invincat](https://madewithwhat.net/langchain/project/invincat/): A native Python agent CLI built on DeepAgents CLI, featuring an independent memory Agent that captures learnings after each task and delivers efficient AI coding assistance through hierarchical memory management. (152 stars, MIT)
- [azure-openai-rag-workshop](https://madewithwhat.net/langchain/project/azure-openai-rag-workshop/): Create your own ChatGPT with Retrieval-Augmented-Generation workshop (151 stars, MIT)
- [Upwork-AI-jobs-applier](https://madewithwhat.net/langchain/project/upwork-ai-jobs-applier/): AI tool for automating Upwork job applications using AI agents to find and qualify jobs, write personalized cover letters, and prepare for interviews based on your skills and experience. (151 stars)
- [scalable-rag-pipeline](https://madewithwhat.net/langchain/project/scalable-rag-pipeline/): A scalable RAG platform combining LangGraph agents, hybrid retrieval (Vector+Graph), and Ray orchestration on Kubernetes. (151 stars, MIT)
- [skillkit](https://madewithwhat.net/langchain/project/skillkit/): Implementing Skills functionality for your agents (149 stars, MIT)
- [podcast-llm](https://madewithwhat.net/langchain/project/podcast-llm/): Automatically generate engaging AI podcasts from nothing but an episode title. (148 stars)
- [ChatSQL](https://madewithwhat.net/langchain/project/chatsql/): Convert the given plain text to MySQL query by ChatGPT (148 stars)
- [BrainChulo](https://madewithwhat.net/langchain/project/brainchulo/): Harnessing the Memory Power of the Camelids (147 stars, MIT)
- [chunky](https://madewithwhat.net/langchain/project/chunky/): Open-source toolkit for reliable RAG pipelines: convert PDFs to Markdown, clean documents, inspect chunks, compare chunking strategies, and enrich metadata for LLM applications. (146 stars, MIT)
- [Hello-Agents](https://madewithwhat.net/langchain/project/hello-agents/): Building AI Agent Systems from Scratch — A comprehensive, practical tutorial from fundamentals to production-grade multi-agent applications (146 stars)
- [toolformer](https://madewithwhat.net/langchain/project/toolformer/): Implementation of Toolformer: Language Models Can Teach Themselves to Use Tools (146 stars, MIT)
- [browser-copilot](https://madewithwhat.net/langchain/project/browser-copilot/): Browser extension and framework to use and build AI assistants for any web application (145 stars, Apache-2.0)
- [GenAIBook](https://madewithwhat.net/langchain/project/genaibook/): "Generative AI in Action" book's code repository (144 stars, MIT)
- [Eva01](https://madewithwhat.net/langchain/project/eva01/): Eva01 is NOT an assistant. She is an AI being with her own mind, feelings, and intrinsic drives. Multimodal, Modular design. Built-in voice & face recognition. Plug'n play tools. Compatible with ChatGPT, Claude, Deepseek, Gemini, Grok, and Ollama. Explore the possibilities of Human-AI Interaction. (142 stars, MIT)
- [local-rag-researcher-deepseek](https://madewithwhat.net/langchain/project/local-rag-researcher-deepseek/): Local RAG researcher agent built using Langgraph, DeepSeek R1 and Ollama (142 stars)
- [LLM_Notebooks](https://madewithwhat.net/langchain/project/llm-notebooks/): Notebooks and Code about Generative Ai, LLMs, MLOPS, NLP, CV and Graph databases (141 stars)
- [memex](https://madewithwhat.net/langchain/project/memex/): Your second brain for the web browsing. An AI powered Chrome extension that constructs personal knowledge base for you. (140 stars, GPL-3.0)
- [chat-with-your-doc](https://madewithwhat.net/langchain/project/chat-with-your-doc/): Chat with your docs in PDF/PPTX/DOCX format, using LangChain and GPT4/ChatGPT from both Azure OpenAI Service and OpenAI (140 stars)
- [tickup](https://madewithwhat.net/langchain/project/tickup/): Supper clone Clickup 3.0, Follow Clean Architecture + DDD with latest Nextjs (138 stars)
- [ESEILANE](https://madewithwhat.net/langchain/project/eseilane/): High-performance Knowledge Graph engine for AI, LLMs, and GraphRAG — built for the next generation of intelligent applications. (137 stars)
- [docmind-ai-llm](https://madewithwhat.net/langchain/project/docmind-ai-llm/): DocMind AI is a powerful, open-source Streamlit application leveraging LlamaIndex, LangGraph, and local Large Language Models (LLMs) via Ollama, LMStudio, llama.cpp, or vLLM for advanced document analysis. Analyze, summarize, and extract insights from a wide array of file formats, securely and privately, all offline. (137 stars, MIT)
- [neuro-san](https://madewithwhat.net/langchain/project/neuro-san/): Neuro AI System of Agent Networks (136 stars, Apache-2.0)
- [torra-community](https://madewithwhat.net/langchain/project/torra-community/): Open-source visual platform for AI agent and workflow development. Inspired by Coze & Langflow, built with Nuxt4, VueFlow, TypeScript, FeathersJS & Shadcn. Drag, connect, deploy — self-hosted and fully extensible by design. (136 stars)
- [Retrieval-Augmented-Generation-Engine-with-LangChain-and-Streamlit](https://madewithwhat.net/langchain/project/retrieval-augmented-generation-engine-with-langchain-and-streamlit/): Powerful web application that combines Streamlit, LangChain, and Pinecone to simplify document analysis. Powered by OpenAI's GPT-3, RAG enables dynamic, interactive document conversations, making it ideal for efficient document retrieval and summarization. (135 stars)
- [Anaxa](https://madewithwhat.net/langchain/project/anaxa/): Anaxa 。，，、、、、。 (135 stars, MIT)
- [PDFChat](https://madewithwhat.net/langchain/project/pdfchat/): The PDFChat app allows you to chat with your PDF files in natural language. (134 stars)
- [bedrock-book](https://madewithwhat.net/langchain/project/bedrock-book/): 「Amazon Bedrock AI」 (132 stars, MIT)
- [Multi-PDFs_ChatApp_AI-Agent](https://madewithwhat.net/langchain/project/multi-pdfs-chatapp-ai-agent/): Meet MultiPDF Chat AI App! Chat seamlessly with Multiple PDFs using Langchain, Google Gemini Pro & FAISS Vector DB with Seamless Streamlit Deployment. Get instant, accurate responses from Awesome Google Gemini OpenSource language Model. Transform your PDF experience now! (132 stars, MIT)
- [RAG-using-Llama3-Langchain-and-ChromaDB](https://madewithwhat.net/langchain/project/rag-using-llama3-langchain-and-chromadb/): RAG using Llama3, Langchain and ChromaDB (132 stars, MIT)
- [obsidian-rag](https://madewithwhat.net/langchain/project/obsidian-rag/): Talk to your Obsidian notes! (131 stars, MIT)
- [polar](https://madewithwhat.net/langchain/project/polar/): A LLDB plugin which brings LLMs to LLDB (130 stars, Apache-2.0)
- [chat-to-your-database](https://madewithwhat.net/langchain/project/chat-to-your-database/): Chat to your database with AI. An experimental app to test the abilities of LLMs to query SQL databases using natural language. (129 stars)
- [airbyte-agent-sdk](https://madewithwhat.net/langchain/project/airbyte-agent-sdk/): Drop-in tools that give AI agents reliable, permission-aware access to external systems. (129 stars)
- [langchainjs-juejin](https://madewithwhat.net/langchain/project/langchainjs-juejin/): AI：langchain.js (128 stars)
- [Mastering-NLP-from-Foundations-to-LLMs](https://madewithwhat.net/langchain/project/mastering-nlp-from-foundations-to-llms/): Mastering NLP from Foundations to LLMs, Published by Packt (128 stars, MIT)
- [ragbase](https://madewithwhat.net/langchain/project/ragbase/): Completely local RAG. Chat with your PDF documents (with open LLM) and UI to that uses LangChain, Streamlit, Ollama (Llama 3.1), Qdrant and advanced methods like reranking and semantic chunking. (128 stars, MIT)
- [fast_dash](https://madewithwhat.net/langchain/project/fast-dash/): Turn your Python functions into interactive apps! Fast Dash is an innovative way to deploy your Python code as interactive web apps with minimal changes. (128 stars, MIT)
- [LangChain-GPT-Researcher](https://madewithwhat.net/langchain/project/langchain-gpt-researcher/): GPT-Researcher as a LangChain tool to be used in Agents and Chains (127 stars, MIT)
- [vector-cookbook](https://madewithwhat.net/langchain/project/vector-cookbook/): Timescale Vector Cookbook. A collection of recipes to build applications with LLMs using PostgreSQL and Timescale Vector. (127 stars)
- [langchain-teddynote](https://madewithwhat.net/langchain/project/langchain-teddynote/): LangChain,. (127 stars, Apache-2.0)
- [language-ai-engineering-lab](https://madewithwhat.net/langchain/project/language-ai-engineering-lab/): Language AI Engineering Lab, a place where you can deeply understand and build modern Language AI systems, from fundamentals to production. (126 stars, GPL-3.0)
- [novice-ChatGPT](https://madewithwhat.net/langchain/project/novice-chatgpt/): ChatGPT API Usage using LangChain, LlamaIndex, Guardrails, AutoGPT and more (126 stars)
- [websum](https://madewithwhat.net/langchain/project/websum/): Summarize web pages and YouTube videos with pluggable LLM backends (Ollama, OpenAI). CLI, library, and Gradio UI. (125 stars, MIT)
- [langchain-coder](https://madewithwhat.net/langchain/project/langchain-coder/): Web Application that can generate code and fix bugs and run using various LLM's (GPT,Gemini,PALM) (125 stars, MIT)
- [ai-agent-tools-catalog](https://madewithwhat.net/langchain/project/ai-agent-tools-catalog/): Explore the must-have external ready-made toolkits to integrate with your AI agents built with Python and TypeScript (125 stars)
- [REMO-langflow](https://madewithwhat.net/langchain/project/remo-langflow/): A chat interface that uses the REMO memory system with LangFlow (124 stars, MIT)
- [jobsmith](https://madewithwhat.net/langchain/project/jobsmith/): AI co-pilot：、、（）。 Claude Code／Codex CLI API key， OpenAI 。 (124 stars, Apache-2.0)
- [towards-agi](https://madewithwhat.net/langchain/project/towards-agi/): A collection of personally developed projects contributing towards the advancement of Artificial General Intelligence(AGI) (124 stars)
- [OneRAG](https://madewithwhat.net/langchain/project/onerag/): Production-ready RAG Framework (Python/FastAPI). 1-line config swaps: 6 Vector DBs (Weaviate, Pinecone, Qdrant, ChromaDB, pgvector, MongoDB), 5 LLMs (Gemini, OpenAI, Claude, Ollama, OpenRouter). OpenAI-compatible API. 2100+ tests. (124 stars, MIT)
- [shellward](https://madewithwhat.net/langchain/project/shellward/): AI · AI 「 / / 」（·PIPL·2.0··AI），； · · · (123 stars, Apache-2.0)
- [memorybot](https://madewithwhat.net/langchain/project/memorybot/): A Node.js AI chatbot with unlimited context and chat history. (123 stars, MIT)
- [DocumentGPT](https://madewithwhat.net/langchain/project/documentgpt/): DocumentGPT is a web application that allows you to chat over your research document using OpenAI's chat API and perform semantic search using vector databases. This tool provides a seamless interface for interacting with your research document, exploring search results, and engaging in a conversation with an AI chatbot. (122 stars, MIT)
- [YouTube-Tutorials](https://madewithwhat.net/langchain/project/youtube-tutorials/): Collection of my Youtube Tutorials over the years! Read, write, and share what you create (122 stars, MIT)
- [XAUUSD_TRADING_ASISTENT_AI](https://madewithwhat.net/langchain/project/xauusd-trading-asistent-ai/): Gold Trading Bot Assistant | Deepseek | Langchain | Python | Gen AI (121 stars)
- [Lectures](https://madewithwhat.net/langchain/project/lectures/): " AI/LLM- Python: " LLM-,., Mistral AI API, LangChain, Arize Phoenix, FastAPI, PostgreSQL Docker. (121 stars)
- [fullstack-langgraph-nextjs-agent](https://madewithwhat.net/langchain/project/fullstack-langgraph-nextjs-agent/): Production-ready Next.js template for building AI agents with LangGraph.js. Features MCP integration for dynamic tool loading, human-in-the-loop tool approval, persistent conversation memory with PostgreSQL, and real-time streaming responses. Built with TypeScript, React, Prisma, and Tailwind CSS. (120 stars, MIT)
- [Langchain-Projects-LLM](https://madewithwhat.net/langchain/project/langchain-projects-llm/): Various projects using Large Language Model (GPT & LLAMA) other open source model from HuggingFace and OpenAI. OpenAI API required for running various model (119 stars, Unlicense)
- [SecGPT](https://madewithwhat.net/langchain/project/secgpt/): An Execution Isolation Architecture for LLM-Based Agentic Systems (117 stars)
- [wxflows](https://madewithwhat.net/langchain/project/wxflows/): Examples and tutorials for building AI applications with watsonx.ai Flows Engine (117 stars, MIT)
- [golc](https://madewithwhat.net/langchain/project/golc/): Building Go applications with LLMs through composability (117 stars, MIT)
- [Streamly](https://madewithwhat.net/langchain/project/streamly/): Streamly - Streamlit Assistant is designed to provide the latest updates from Streamlit, generate code snippets for Streamlit widgets, and answer questions about Streamlit's latest features, issues, and more (117 stars, MIT)
- [snowBrain](https://madewithwhat.net/langchain/project/snowbrain/): snowBrain - AI-Driven Insights with Snowflake (New version- https://github.com/kaarthik108/snowbrain-AGUI) (116 stars)
- [ChatGLM-LangChain](https://madewithwhat.net/langchain/project/chatglm-langchain/): ChatGLM 6B UI， LangChain ， (116 stars)
- [OgbujiPT](https://madewithwhat.net/langchain/project/ogbujipt/): Client-side toolkit for using large language models, including where self-hosted (115 stars, Apache-2.0)
- [Whatsapp-Langgraph-Agent-Integration](https://madewithwhat.net/langchain/project/whatsapp-langgraph-agent-integration/): A WhatsApp AI Agent powered by LangGraph, FastAPI, and Groq. Acts as an empathetic therapist, Dr. Sofia, handling text and voice messages with natural conversations. Supports multi-language, PostgreSQL-backed memory, and real-time synthesis. (115 stars)
- [rag-chunk](https://madewithwhat.net/langchain/project/rag-chunk/): A Python CLI to test, benchmark, and find the best RAG chunking strategy for your Markdown documents. (113 stars, MIT)
- [llm-apps-workshop](https://madewithwhat.net/langchain/project/llm-apps-workshop/): Use LLMs for building real-world apps (113 stars, MIT-0)
- [arcadia](https://madewithwhat.net/langchain/project/arcadia/): A diverse, simple, and secure all-in-one LLMOps platform (113 stars, Apache-2.0)
- [codespaces-langchain](https://madewithwhat.net/langchain/project/codespaces-langchain/): A Codespaces template for getting up-and-running with LangChain in seconds! (113 stars)
- [Chat2Anything](https://madewithwhat.net/langchain/project/chat2anything/): An LLM-based tool to chat with your documents and databases, including a management system | (LLM)， (113 stars, MIT)
- [langgraph-ai](https://madewithwhat.net/langchain/project/langgraph-ai/): A comprehensive collection of LangGraph implementations, tutorials, and advanced AI workflows covering Agentic RAG systems, MCP (Model Context Protocol) development, and practical AI application patterns. (113 stars, MIT)
- [langchain-mongodb](https://madewithwhat.net/langchain/project/langchain-mongodb/): Integrations between MongoDB, Atlas, LangChain, and LangGraph (113 stars, MIT)
- [deepagents-backends](https://madewithwhat.net/langchain/project/deepagents-backends/): S3, PostgreSQL, Azure Blob, GCS, MongoDB, and Redis remote backends for LangChain Deep Agents (112 stars, MIT)
- [Prompt-Enhancer](https://madewithwhat.net/langchain/project/prompt-enhancer/): Prompt Engineering at Your Fingertips! (111 stars, MIT)
- [agent-interview-hub](https://madewithwhat.net/langchain/project/agent-interview-hub/): AI Agent - 、、 (111 stars)
- [arxie](https://madewithwhat.net/langchain/project/arxie/): Research feedback grounded in the papers that define your field (110 stars, MIT)
- [Advanced_RAG](https://madewithwhat.net/langchain/project/advanced-rag/): Advanced Retrieval-Augmented Generation (RAG) through practical notebooks, using the power of the Langchain, OpenAI GPTs,META LLAMA3, Agents. (109 stars)
- [pdf-analyze-streamlit](https://madewithwhat.net/langchain/project/pdf-analyze-streamlit/): A project worth exploring. (108 stars, GPL-3.0)
- [agentic-stock-research-system](https://madewithwhat.net/langchain/project/agentic-stock-research-system/): A sophisticated multi-agent AI system for analyzing Indian NSE-listed stocks using real-time data, technical indicators, news sentiment, and advanced AI reasoning. (107 stars)
- [NomAI-App](https://madewithwhat.net/langchain/project/nomai-app/): CalAI? Nah NomAI (107 stars)
- [WindRise](https://madewithwhat.net/langchain/project/windrise/): It's actively developed around agent, ai, fastapi, and is a solid reference for anyone building with these tools. (107 stars)
- [llm-api-starterkit](https://madewithwhat.net/langchain/project/llm-api-starterkit/): Beginner-friendly repository for launching your first LLM API with Python, LangChain and FastAPI, using local models or the OpenAI API. (107 stars)
- [mentedb](https://madewithwhat.net/langchain/project/mentedb/): A cognition aware database engine for AI agent memory. Purpose built in Rust with WAL, HNSW, knowledge graphs, and speculative context pre assembly. Not a wrapper, a ground up storage engine that thinks. (106 stars, Apache-2.0)
- [coding-agent](https://madewithwhat.net/langchain/project/coding-agent/): Your own Coding Agent (106 stars)
- [Flamehaven-Filesearch](https://madewithwhat.net/langchain/project/flamehaven-filesearch/): Self-hosted RAG search engine — 34 formats, BM25+hybrid search, multi-LLM (Gemini/OpenAI/Claude/Ollama), FastAPI + Docker, production-ready in 3 min (106 stars, MIT)
- [ObsidianRAG](https://madewithwhat.net/langchain/project/obsidianrag/): Ask questions about your Obsidian notes using local AI. Privacy-first RAG with Ollama, LM Studio, or any OpenAI-compatible server. Obsidian plugin + Docker + PyPI. (106 stars, MIT)
- [ai-chatkit](https://madewithwhat.net/langchain/project/ai-chatkit/): A full-stack ai agent chat project, built with langgraph+fastapi+nextjs, supporting tool invocation and RAG knowledge base (106 stars)
- [langchainex](https://madewithwhat.net/langchain/project/langchainex/): Language Chain Library for Elixir (106 stars, MIT)
- [amazon-bedrock-agents-quickstart](https://madewithwhat.net/langchain/project/amazon-bedrock-agents-quickstart/): Learn how to quickly build Agents with Amazon Bedrock (105 stars, MIT-0)
- [agents-shipgate](https://madewithwhat.net/langchain/project/agents-shipgate/): The deterministic merge gate for AI-generated agent capability changes — a local-first, static Tool-Use Readiness review for MCP, OpenAPI, and SDK tool surfaces. Open-source CLI + GitHub Action. (104 stars, Apache-2.0)
- [agentic-ai-roadmap](https://madewithwhat.net/langchain/project/agentic-ai-roadmap/): A comprehensive AI learning roadmap covering Python fundamentals, mathematics, machine learning, deep learning, LLMs, and agentic systems — focused on hands-on projects, practical tools, and real-world deployment. (103 stars, MIT)
- [deepsearch-agents](https://madewithwhat.net/langchain/project/deepsearch-agents/): AI Agents， DeepAgents ｜AI Deep Research Agent · LangGraph + RAGFlow + Tavily + FastAPI + WebSocket 0。，Docker ， ai-agents-from-zero 。、 Agent AI (102 stars)
- [PrivateDocBot](https://madewithwhat.net/langchain/project/privatedocbot/): Local PDF-Integrated Chat Bot: Secure Conversations and Document Assistance with LLM-Powered Privacy (102 stars, Apache-2.0)
- [kyros-ai](https://madewithwhat.net/langchain/project/kyros-ai/): Kyros — The Memory OS for AI Agents Give your AI agents secure, self-correcting, persistent memory in 3 lines of code. Three memory types (episodic, semantic, procedural) with built-in forgetting curves, cryptographic integrity, and automatic contradiction resolution. Model-agnostic REST API with Python and TypeScript SDKs. (101 stars, Apache-2.0)
- [rag-with-amazon-bedrock-and-pgvector](https://madewithwhat.net/langchain/project/rag-with-amazon-bedrock-and-pgvector/): Opinionated sample on how to build/deploy a RAG web app on AWS powered by Amazon Bedrock and PGVector (on Amazon RDS) (100 stars, MIT-0)
- [pdfai](https://madewithwhat.net/langchain/project/pdfai/): PDF based Chatbot using streamlit LangChain & OpenAI. (99 stars)
- [ARIES](https://madewithwhat.net/langchain/project/aries/): ， RWKV | 「Intel 2025 」AutoOPS: Provide the chaos brought by language models to the operation and maintenance industry! LLM ， Windows Server/Linux/macOS/Cisco IOS，，【//IoT/WebHook//Workflow】 (99 stars, GPL-2.0)
- [LLMinator](https://madewithwhat.net/langchain/project/llminator/): Gradio based tool to run opensource LLM models directly from Huggingface (99 stars, MIT)
- [PersonalMemoryBot](https://madewithwhat.net/langchain/project/personalmemorybot/): Memory to your Personal ChatBot | LangChainAI and Databutton (97 stars, MIT)
- [GPTube](https://madewithwhat.net/langchain/project/gptube/): Youtube Video Summarizer and Question Answering App Using Whisper and Langchain (97 stars)
- [langchain-chat-websockets](https://madewithwhat.net/langchain/project/langchain-chat-websockets/): LangChain LLM chat with streaming response over websockets (97 stars, Apache-2.0)
- [local-genAI-search](https://madewithwhat.net/langchain/project/local-genai-search/): Local-GenAI-Search is a generative search engine based on Llama 3, langchain and qdrant that answers questions based on your local files (96 stars, GPL-3.0)
- [SigmAIQ](https://madewithwhat.net/langchain/project/sigmaiq/): A pySigma wrapper and langchain toolkit for automatic rule creation/translation (96 stars, LGPL-2.1)
- [sales-ai-agent-langgraph](https://madewithwhat.net/langchain/project/sales-ai-agent-langgraph/): A Virtual Sales Agent that uses LangChain, LangGraph, and Gemini Flash to simulate customer interactions. Features include product inquiries, order management, and personalized recommendations through a user-friendly Streamlit interface. (96 stars, MIT)
- [resume-ranking](https://madewithwhat.net/langchain/project/resume-ranking/): Apply LLMs for automated ranking Resume (96 stars, GPL-3.0)
- [DocSentinel](https://madewithwhat.net/langchain/project/docsentinel/): MCP server for AI agent for cybersecurity: automate assessment of documents, questionnaires & reports. Multi-format parsing, RAG knowledge base,Risks, compliance gaps, remediations. (96 stars, MIT)
- [slidespeak-backend](https://madewithwhat.net/langchain/project/slidespeak-backend/): Backend for SlideSpeak. Create PowerPoints with AI. Get summaries, ask questions, create presentations and more. (95 stars)
- [faramesh-core](https://madewithwhat.net/langchain/project/faramesh-core/): Governance-as-Code for AI agents. Declarative constraints with deterministic enforcement. Provisioning Identity, Tool-based rules, Brokering Credentials & Ensuring safe deployment (95 stars)
- [talksheet](https://madewithwhat.net/langchain/project/talksheet/): A GPT powered CLI tool that answers questions about your data (95 stars)
- [TalkWithYourFiles](https://madewithwhat.net/langchain/project/talkwithyourfiles/): An LLM GUI application; enables you to interact with your files, offering dynamic parameters that can modify response behavior during runtime. (94 stars, MIT)
- [agentic-parallelism](https://madewithwhat.net/langchain/project/agentic-parallelism/): Core concepts - where to apply parallelism in agentic solution (94 stars, MIT)
- [contextual-engineering-guide](https://madewithwhat.net/langchain/project/contextual-engineering-guide/): Implementation of contextual engineering pipeline with LangChain and LangGraph Agents (94 stars)
- [Corvus](https://madewithwhat.net/langchain/project/corvus/): Multi-agent AI research system — finds academic papers via semantic search & citation snowballing, then answers questions over them using agentic RAG with self-reflection. Built with LangGraph, FastAPI, Celery, and Qdrant. (94 stars, MIT)
- [langport](https://madewithwhat.net/langchain/project/langport/): Langport is a language model inference service (94 stars, MIT)
- [AI-Agents](https://madewithwhat.net/langchain/project/ai-agents/): Design Patterns for Multi Agents Frameworks Like Autogen, Langraph, Taskweaver,Crewai,etc (94 stars)
- [quarkus-workshop-langchain4j](https://madewithwhat.net/langchain/project/quarkus-workshop-langchain4j/): Quarkus LangChain4J Workshop that demonstrates both single AI service capabilities and Agentic AI orchestration (92 stars, Apache-2.0)
- [temporal-ai-agent-pipeline](https://madewithwhat.net/langchain/project/temporal-ai-agent-pipeline/): Optimizing Dynamic Knowledge Base Using AI Agent (92 stars, MIT)
- [jeecg-ai](https://madewithwhat.net/langchain/project/jeecg-ai/): 【AI】AI，AI ！：AI、、AI、AI、AI、Chat2BI (92 stars, Apache-2.0)
- [AIAgents4Pharma](https://madewithwhat.net/langchain/project/aiagents4pharma/): AI Agents for drug discovery, drug development, and other pharmaceutical R&D (91 stars, MIT)
- [ai-resume-builder](https://madewithwhat.net/langchain/project/ai-resume-builder/): Create LaTeX resumes tailored to job postings by an AI model (91 stars, GPL-3.0)
- [langchain-ask-pdf-local](https://madewithwhat.net/langchain/project/langchain-ask-pdf-local/): An AI-app that allows you to upload a PDF and ask questions about it. It uses StableVicuna 13B and runs locally. (90 stars)
- [langchain-langgraph-tutorial](https://madewithwhat.net/langchain/project/langchain-langgraph-tutorial/): Comprehensive tutorials for LangChain, LangGraph, and LangSmith using Groq LLM. Learn to build advanced AI systems, from basics to production-ready applications. Covers key concepts, real-world examples, and best practices. Ideal for beginners and experts alike. Elevate your AI development skills! (90 stars)
- [spring-ai-demo](https://madewithwhat.net/langchain/project/spring-ai-demo/): SpringAI & alibaba、Agent (90 stars)
- [a2a-adapter](https://madewithwhat.net/langchain/project/a2a-adapter/): Open Source A2A Protocol Adapter SDK for Different Agent Frameworks (89 stars, Apache-2.0)
- [gen-ai](https://madewithwhat.net/langchain/project/gen-ai/): Generative AI concepts to hands on projects (89 stars)
- [substack-newsletters-search-course](https://madewithwhat.net/langchain/project/substack-newsletters-search-course/): Production RAG System Course (89 stars, MIT)
- [graph-rag](https://madewithwhat.net/langchain/project/graph-rag/): Graph traversal for improved RAG (89 stars, Apache-2.0)
- [chat-your-doc](https://madewithwhat.net/langchain/project/chat-your-doc/): Awesome LLM application repo (89 stars)
- [Food-tour-planner-agent](https://madewithwhat.net/langchain/project/food-tour-planner-agent/): Food tour planner using LangChain DeepAgents, Google Maps API, and Tavily research. Explore multi-agent coordination patterns: task delegation via SubAgentMiddleware, planning with TodoListMiddleware (89 stars)
- [langchain-chat-gui](https://madewithwhat.net/langchain/project/langchain-chat-gui/): Langchain chat with memory and a GUI made in Streamlit (88 stars)
- [PolyGPT-alpha](https://madewithwhat.net/langchain/project/polygpt-alpha/): PolyGPT: An Overview of Agent-Based System Architecture for Autonomous Business Operations (88 stars)
- [LangSim](https://madewithwhat.net/langchain/project/langsim/): Application of Large Language Models (LLM) for computational materials science - visit jan-janssen.com/LangSim (88 stars, BSD-3-Clause)
- [Local-RAG-with-Ollama](https://madewithwhat.net/langchain/project/local-rag-with-ollama/): Build a 100% local Retrieval Augmented Generation (RAG) system with Python, LangChain, Ollama and ChromaDB! (88 stars)
- [llm-course-zh](https://madewithwhat.net/langchain/project/llm-course-zh/): (LLM)code，github、、code，pythonLLM、 (88 stars)
- [whisk](https://madewithwhat.net/langchain/project/whisk/): The AI runtime that turns your framework functions into OpenAI compatible endpoints (88 stars)
- [context-compressor](https://madewithwhat.net/langchain/project/context-compressor/): AI-powered text compression library for RAG systems and API calls. Reduce token usage by up to 50-60% while preserving semantic meaning with advanced compression strategies. (87 stars, MIT)
- [Generative-AI-LLM-Projects](https://madewithwhat.net/langchain/project/generative-ai-llm-projects/): Gen AI Large Language Model Projects (87 stars, MIT)
- [langchain-quickstart](https://madewithwhat.net/langchain/project/langchain-quickstart/): Build your first LLM powered app with Langchain and Streamlit. (87 stars)
- [GPT_Resume_analysing](https://madewithwhat.net/langchain/project/gpt-resume-analysing/): Using Langchain and OpenAI to analyse resume (87 stars)
- [airgapped-offfline-rag](https://madewithwhat.net/langchain/project/airgapped-offfline-rag/): Secure, locally-run Retrieval-Augmented Generation system for document-based question-answering, utilizing Llama 3, Mistral, and Gemini models with a user-friendly Streamlit interface. (86 stars, GPL-3.0)
- [DocGenius-Revolutionizing-PDFs-with-AI](https://madewithwhat.net/langchain/project/docgenius-revolutionizing-pdfs-with-ai/): This is a Python application that allows you to load a PDF and ask questions about it using natural language. The application uses a LLM to generate a response about your PDF. The LLM will not answer questions unrelated to the document. (86 stars, GPL-3.0)
- [www-project-agent-memory-guard](https://madewithwhat.net/langchain/project/www-project-agent-memory-guard/): OWASP Foundation web repository (86 stars, Apache-2.0)
- [minipilot](https://madewithwhat.net/langchain/project/minipilot/): MiniPilot is a GenAI-assisted chatbot backed by Redis. Chat with your documents (86 stars, MIT)
- [End-to-End-Agentic-Ai-Automation-Lab](https://madewithwhat.net/langchain/project/end-to-end-agentic-ai-automation-lab/): This repository contains hands-on projects, code examples, and deployment workflows. Explore multi-agent systems, LangChain, LangGraph, AutoGen, CrewAI, RAG, MCP, automation with n8n, and scalable agent deployment using Docker, AWS, and BentoML. (85 stars, MIT)
- [semantic-search-openai-nextjs-sample](https://madewithwhat.net/langchain/project/semantic-search-openai-nextjs-sample/): This repository is a sample application and guided walkthrough for a semantic search question-and-answer style interaction with custom user-uploaded documents. Typescript, NextJS, OpenAI, Langchain, Pinecone (85 stars)
- [tiny-ai-client](https://madewithwhat.net/langchain/project/tiny-ai-client/): Tiny client for LLMs with vision and tool calling. As simple as it gets. (85 stars, Apache-2.0)
- [meeper](https://madewithwhat.net/langchain/project/meeper/): Meeper - is your secretary for any in-browser conference. (84 stars, MPL-2.0)
- [LinkedInGPT](https://madewithwhat.net/langchain/project/linkedingpt/): Skynet (84 stars, MIT)
- [mate](https://madewithwhat.net/langchain/project/mate/): Production-ready multi-agent orchestration engine built on Google ADK. Database-driven agent config, 50+ LLM providers, MCP protocol, persistent memory, web dashboard, RBAC. (84 stars, Apache-2.0)
- [llm-rag-with-reranker-demo](https://madewithwhat.net/langchain/project/llm-rag-with-reranker-demo/): LLM RAG Application with Cross-Encoders Re-ranking for YouTube video (83 stars)
- [Fast-LLM-Agent-MCP](https://madewithwhat.net/langchain/project/fast-llm-agent-mcp/): This repo covers LLM, Agents, MCP Tools, Skills concepts with sample codes: LangChain & LangGraph, AWS Strands Agents, Google Agent Development Kit, Fundamentals. (83 stars)
- [generate_article](https://madewithwhat.net/langchain/project/generate-article/): It's actively developed around agent, chatopenai, langchain, and is a solid reference for anyone building with these tools. (83 stars)
- [blogger](https://madewithwhat.net/langchain/project/blogger/): An AI agent that writes SEO-optimised blog posts and outputs markdown. (82 stars, MIT)
- [vcr-langchain](https://madewithwhat.net/langchain/project/vcr-langchain/): Record and replay LLM interactions for langchain (82 stars, MIT)
- [PDF-RAG-with-Llama2-and-Gradio](https://madewithwhat.net/langchain/project/pdf-rag-with-llama2-and-gradio/): Build your own Custom RAG Chatbot using Gradio, Langchain and Llama2 (81 stars, Apache-2.0)
- [spellbook-forge](https://madewithwhat.net/langchain/project/spellbook-forge/): Make your LLM prompts executable and version controlled. (81 stars, MIT)
- [ecrivai](https://madewithwhat.net/langchain/project/ecrivai/): Fully automated AI blog writer that uses LangChain and GPT type LLMs for topic selection and content generation (81 stars, MIT)
- [Travel-Agent-based-on-Qwen2-RLHF](https://madewithwhat.net/langchain/project/travel-agent-based-on-qwen2-rlhf/): A travel agent based on Qwen2.5, fine-tuned by SFT + DPO/PPO/GRPO using traveling question-answer dataset, a mindmap can be output using the response. A RAG system is build upon the tuned qwen2, using Prompt-Template + Tool-Use + Chroma embedding database + LangChain (80 stars)
- [swarms-examples](https://madewithwhat.net/langchain/project/swarms-examples/): A vast array of examples for the enterprise-grade and production-ready swarms framework. (80 stars, MIT)
- [langchain-telegram-gpt-chatbot](https://madewithwhat.net/langchain/project/langchain-telegram-gpt-chatbot/): An AI-powered chatbot integrated with Telegram, using OpenAI GPT-3.5 Turbo, language embeddings, and FAISS for similarity search to provide more contextually relevant responses to user queries (80 stars, MIT)
- [goai](https://madewithwhat.net/langchain/project/goai/): A friendly API and abstractions for developing AI applications. (80 stars, Apache-2.0)
- [azure_openai_langchain_sample](https://madewithwhat.net/langchain/project/azure-openai-langchain-sample/): This repository contains various examples of how to use LangChain, a way to use natural language to interact with LLM, a large language model from Azure OpenAI Service. (79 stars)
- [tableau_langchain](https://madewithwhat.net/langchain/project/tableau-langchain/): Tableau tools for Agentic use cases with Langchain & Langgraph. Enfuse agents with updated data so they make better informed decisions that scale with your analytics practice (79 stars, MIT)
- [n8n-desk](https://madewithwhat.net/langchain/project/n8n-desk/): Bringing n8n to your Machine — a desktop & mobile companion app for n8n. Chat with agents, build workflows conversationally, work with local files. (79 stars)
- [Magic-Resume](https://madewithwhat.net/langchain/project/magic-resume/): Open-source AI career platform that helps users build, optimize, analyze, and tailor resumes with intelligent job matching, ATS optimization, and career guidance. (79 stars, MIT)
- [GenAI-Roadmap-with-Notes-and-Projects](https://madewithwhat.net/langchain/project/genai-roadmap-with-notes-and-projects/): A comprehensive learning path and practical guide for Generative AI development with hands-on LangChain implementations and detailed notes. (79 stars, MIT)
- [Chatchat-Lite](https://madewithwhat.net/langchain/project/chatchat-lite/): LangGraph Streamlit RAG、Agent (79 stars, Apache-2.0)
- [Roy](https://madewithwhat.net/langchain/project/roy/): Roy: A lightweight, model-agnostic framework for crafting advanced multi-agent systems using large language models. (79 stars)
- [open-tutor-ai-CE](https://madewithwhat.net/langchain/project/open-tutor-ai-ce/): An open-source project designed to provide an educational and collaborative AI-powered platform (78 stars, BSD-3-Clause)
- [AskScribe](https://madewithwhat.net/langchain/project/askscribe/): With AskScribe, you can simply upload your PDF and engage in a conversation. Ask questions, seek clarification, and let AskScribe intelligently analyze and extract the most relevant information for you. Whether you're conducting research, studying, or simply trying to find that one elusive detail, AskScribe is your go to companion (78 stars)
- [deploy-langfuse-on-ecs-with-fargate](https://madewithwhat.net/langchain/project/deploy-langfuse-on-ecs-with-fargate/): Self-hosting Langfuse on Amazon ECS with Fargate using CDK Python (77 stars, MIT-0)
- [ShibaClaw](https://madewithwhat.net/langchain/project/shibaclaw/): Self-hosted security-first AI agent · 28 providers · 11 chat channels · WebUI · 3-level memory · task-schedule · automation · skills · MCP (77 stars, Apache-2.0)
- [AI-Agents-in-LangGraph](https://madewithwhat.net/langchain/project/ai-agents-in-langgraph/): Master the art of building and enhancing AI agents. Learn to develop flow-based applications, implement agentic search, and incorporate human-in-the-loop systems using LangGraph's powerful components. (77 stars)
- [git-gpt](https://madewithwhat.net/langchain/project/git-gpt/): Ask questions against any git repository, and get a response from OpenAI GPT-3 model. (77 stars)
- [rag_api](https://madewithwhat.net/langchain/project/rag-api/): Retrieval Augmented Generation API using Open LLMs and FastAPI (77 stars)
- [examples](https://madewithwhat.net/langchain/project/examples/): Examples and code snippets demonstrating common ways of integrating Neon with various frameworks and languages. (77 stars)
- [Agentic-AI-Pipeline](https://madewithwhat.net/langchain/project/agentic-ai-pipeline/): A production‑ready research outreach AI agent that plans, discovers, reasons, uses tools, auto‑builds cited briefings, and drafts tailored emails with tool‑chaining, memory, tests, and turnkey Docker, AWS, Ansible & Terraform deploys. Bonus: An Agentic RAG System & a Coding Pipeline with multistep planning, self-critique, and autonomous agents. (77 stars, Apache-2.0)
- [tenuo](https://madewithwhat.net/langchain/project/tenuo/): High-performance capability authorization engine for AI agents. Cryptographically attenuated warrants, task-scoped authority, verifiable offline. Rust core. (76 stars)
- [mcp-toolbox-sdk-js](https://madewithwhat.net/langchain/project/mcp-toolbox-sdk-js/): Javascript SDK for interacting with the MCP Toolbox for Databases. (76 stars, Apache-2.0)
- [Querypls](https://madewithwhat.net/langchain/project/querypls/): Querypls: WebApp that Simplify SQL with Your Prompts. Transforming questions into SQL commands effortlessly. (76 stars, MIT)
- [LLM-Dynamic-Analytics-Policing](https://madewithwhat.net/langchain/project/llm-dynamic-analytics-policing/): A project worth exploring. (76 stars)
- [ciana-parrot](https://madewithwhat.net/langchain/project/ciana-parrot/): Self-hosted AI assistant with multi-channel support, scheduled tasks, and extensible skills (76 stars, MIT)
- [Hermes-router](https://madewithwhat.net/langchain/project/hermes-router/): OpenAI/Anthropic-compatible AI router that keeps apps online with provider failover, key rotation, caching, analytics, and local-model fallback. (76 stars, MIT)
- [vCache](https://madewithwhat.net/langchain/project/vcache/): Reliable and Efficient Semantic Prompt Caching with vCache (75 stars)
- [crewai-rag-langchain-qdrant](https://madewithwhat.net/langchain/project/crewai-rag-langchain-qdrant/): Collaborative Multi-Agent RAG with CrewAI (75 stars)
- [BrainX](https://madewithwhat.net/langchain/project/brainx/): BrainX ，，，，、。。 (75 stars, Apache-2.0)
- [smart-llm-loader](https://madewithwhat.net/langchain/project/smart-llm-loader/): smart-llm-loader is a lightweight yet powerful Python package that transforms any document into LLM-ready chunks. Spend less time on preprocessing headaches and more time building what matters. From RAG systems to chatbots to document Q&A, SmartLLMLoader handles the heavy lifting so you can focus on creating exceptional AI applications. (75 stars, MIT)
- [NeMo-Relay](https://madewithwhat.net/langchain/project/nemo-relay/): Multi-language agent runtime and library for execution scope management, lifecycle events, and middleware on tool and LLM calls. (75 stars, Apache-2.0)
- [laozy](https://madewithwhat.net/langchain/project/laozy/): Laozy is a self-hosted web application that helps you build and deploy LLM-based dialogue robots. The robot you built can connect to instant messaging platforms like WeChat, Telegram, etc. You can also integrate it into your app with REST APIs. (74 stars)
- [AIrXiv](https://madewithwhat.net/langchain/project/airxiv/): AI-powered arXiv research assistant prototype. (74 stars, MIT)
- [build-your-own-rag-chatbot](https://madewithwhat.net/langchain/project/build-your-own-rag-chatbot/): Workshop to build and deploy your own Chat Agent using Retrieval Augmented Generation with Astra DB (73 stars)
- [python_langchain_cn](https://madewithwhat.net/langchain/project/python-langchain-cn/): langchainlangchainpython (73 stars)
- [zapier-langchain-quickstart](https://madewithwhat.net/langchain/project/zapier-langchain-quickstart/): A Jupyter python notebook to Execute Zapier Tasks with GPT completion via Langchain (73 stars)
- [nextjs-fastapi-your-chat](https://madewithwhat.net/langchain/project/nextjs-fastapi-your-chat/): Chat with any website using FastAPI, Next.js, and the latest LangChain version for seamless integration. (73 stars, MIT)
- [reportAI](https://madewithwhat.net/langchain/project/reportai/): Generate full fledged PDF reports using LLMs like GPT, Claude, Llama (73 stars, Apache-2.0)
- [uipath-langchain-python](https://madewithwhat.net/langchain/project/uipath-langchain-python/): Python SDK that enables developers to build and deploy LangGraph agents to the UiPath Cloud Platform (72 stars, MIT)
- [GPT4-LangChain-Internet-Research-Agent-App](https://madewithwhat.net/langchain/project/gpt4-langchain-internet-research-agent-app/): Python Streamlit web app utilizing OpenAI (GPT4) and LangChain LLM tools with access to Wikipedia, DuckDuckgo Search, and a ChromaDB with previous research embeddings. Ultimately delivering a research report for a user-specified input, including an introduction, quantitative facts, as well as relevant publications, books, and youtube links. (72 stars)
- [otto-m8](https://madewithwhat.net/langchain/project/otto-m8/): Flowchart-like UI to interconnect LLM's and Huggingface models, and deploy them as a REST API with little to no code. (72 stars, Apache-2.0)
- [Crawllama](https://madewithwhat.net/langchain/project/crawllama/): CrawlLama is an local AI agent that answers questions via Ollama and integrates web- and RAG-based research. (71 stars)
- [ZON](https://madewithwhat.net/langchain/project/zon/): ZON → 35-70% cheaper LLM prompts than JSON/TOON. Zero overhead. (71 stars, MIT)
- [Agent-Git](https://madewithwhat.net/langchain/project/agent-git/): Agent Git: Agent Version Control, Open-Branching, and Reinforcement Learning MDP for Agentic AI. A Standalone Agentic AI Infrastructure Layer for LangGraph Ecosystems (71 stars, Apache-2.0)
- [DevAssistant](https://madewithwhat.net/langchain/project/devassistant/): Personal Task-Driven Autonomous Agent (71 stars)
- [STORM-Research-Assistant](https://madewithwhat.net/langchain/project/storm-research-assistant/): AI research assistant that generates Wikipedia-quality articles through multi-perspective analysis. Based on Stanford's STORM methodology. (70 stars, MIT)
- [smol-dev-go](https://madewithwhat.net/langchain/project/smol-dev-go/): smol-dev-go, a Go implementation of smol developer (70 stars)
- [ai-investment-agent](https://madewithwhat.net/langchain/project/ai-investment-agent/): Agentic AI ex-US equity evaluator (LangGraph+Gemini) (70 stars, MIT)
- [AI-Agent-Digital-Human](https://madewithwhat.net/langchain/project/ai-agent-digital-human/): The virtual secretary, Lisa, is designed to interact naturally with users through text, voice, emotion, and a real-time animated avatar. (70 stars)
- [markitdown-rs](https://madewithwhat.net/langchain/project/markitdown-rs/): A Rust library designed to facilitate the conversion of various document formats into markdown text. (69 stars, MIT)
- [aws-openai](https://madewithwhat.net/langchain/project/aws-openai/): Example ChatGPT chatbots using Langchain and OpenAI (69 stars, AGPL-3.0)
- [easy-data-x-ai](https://madewithwhat.net/langchain/project/easy-data-x-ai/): 《Easy Data x AI》 AI AI 。， AI Agent。 (69 stars)
- [react-gpt](https://madewithwhat.net/langchain/project/react-gpt/): An experimental chat-gpt experience focused on React using LangChain & OpenAI (68 stars)
- [nutrient-dws-mcp-server](https://madewithwhat.net/langchain/project/nutrient-dws-mcp-server/): A Model Context Protocol (MCP) server implementation that integrates with the Nutrient Document Web Service (DWS) Processor API, providing powerful PDF processing capabilities for AI assistants. (68 stars, MIT)
- [pyllamacpp](https://madewithwhat.net/langchain/project/pyllamacpp/): Python bindings for llama.cpp (68 stars, MIT)
- [cognite](https://madewithwhat.net/langchain/project/cognite/): Create and share chatbots with external knowledge (67 stars, AGPL-3.0)
- [300DaysOFMachineLearning-DeepLearning-LLM](https://madewithwhat.net/langchain/project/300daysofmachinelearning-deeplearning-llm/): Hello everyone this repo will contain my journey of machine learning and DeepLearning with some exciting projects (67 stars, MIT)
- [Cosmic-Food-RAG-app](https://madewithwhat.net/langchain/project/cosmic-food-rag-app/): A chat-based recommendation application that revolutionizes the culinary experience. (67 stars, MIT)
- [Network-AI](https://madewithwhat.net/langchain/project/network-ai/): Traffic light for AI Agents and TypeScript/Node multi-agent orchestrator with shared state, guardrails, and adapters for 29 AI frameworks (67 stars, MIT)
- [reagent](https://madewithwhat.net/langchain/project/reagent/): A full-stack framework for building AI workflows (67 stars, MIT)
- [OpenAI-Whisper-Audio-Transcription-And-Summarization-Chatbot](https://madewithwhat.net/langchain/project/openai-whisper-audio-transcription-and-summarization-chatbot/): Web app enabling users to either record or upload audio files. Then utilizing OpenAI API (Whisper, GPT4) generates transcriptions, summaries, fact checks, sentiment analysis, and text metrics. Users can also intelligently chat about their transcriptions with a GPT4 chatbot. Data is stored relationally in SQLite and also vectorized in Pinecone. (67 stars)
- [reddit_karma_farmer_auto_commentator_with_AI](https://madewithwhat.net/langchain/project/reddit-karma-farmer-auto-commentator-with-ai/): Reddit_Commentator_AIHawk is a Python project showcasing the power of artificial intelligence in social media interaction. This tool demonstrates AI's capability to generate contextually relevant Reddit comments using GPT models and LangChain. It automates the process of analyzing trending posts and creating engaging responses. (66 stars)
- [NoPII](https://madewithwhat.net/langchain/project/nopii/): Ready-to-run examples showing NoPII PII protection with OpenAI, Anthropic, LangChain, LlamaIndex, and more (66 stars, MIT)
- [microllama](https://madewithwhat.net/langchain/project/microllama/): The smallest possible LLM API (65 stars, MIT)
- [FinchBot](https://madewithwhat.net/langchain/project/finchbot/): FinchBot is an AI Agent framework that empowers agents with true autonomy, built on LangChain v1.2 and LangGraph v1.0. With fully async architecture, agents gain the ability to self-decide, self-extend, and self-evolve (65 stars, MIT)
- [langchain-ask-the-doc](https://madewithwhat.net/langchain/project/langchain-ask-the-doc/): Ask the Doc app built using Langchain and Streamlit. (65 stars)
- [LawGPT](https://madewithwhat.net/langchain/project/lawgpt/): A RAG based Generative AI Attorney fed with Indian Penal Code data. Developed using Streamlit, LangChain and TogetherAI API. (65 stars)
- [condo_gpt](https://madewithwhat.net/langchain/project/condo-gpt/): An intelligent assistant for querying and analyzing real estate condo data in Miami. (65 stars)
- [RAG-To-Know](https://madewithwhat.net/langchain/project/rag-to-know/): The repository explores various RAG techniques, including implementation guides, use cases, and best practices. Each article is designed to help researchers, developers, and enthusiasts understand and implement RAG systems efficiently. (65 stars)
- [langchain-weaviate](https://madewithwhat.net/langchain/project/langchain-weaviate/): LangChain interface to Weaviate (64 stars, MIT)
- [ai-content](https://madewithwhat.net/langchain/project/ai-content/): An AI Power content generator based on Next.js starter for Contentlayer that includes Tailwind CSS, MDX, and TypeScript. (64 stars, MIT)
- [OpenAI-LangChain-Pandas-DF-Agent-Query-Streamlit-App](https://madewithwhat.net/langchain/project/openai-langchain-pandas-df-agent-query-streamlit-app/): Python Streamlit web app allowing users to interact with their data from a CSV or XLSX file, utilizing OpenAI API and LangChain. It imports necessary libraries, handles API key loading, displays a user-friendly interface for file upload and data preview, creates a Pandas DF agent with OpenAI, and executes user queries. (64 stars)
- [template-mcp-server](https://madewithwhat.net/langchain/project/template-mcp-server/): Production-ready Python template for building MCP servers with FastMCP, FastAPI, OAuth, and OpenShift deployment. (64 stars, Apache-2.0)
- [agentic-rag-financial-parser](https://madewithwhat.net/langchain/project/agentic-rag-financial-parser/): Enterprise RAG ecosystem managing 32000+ semantic chunks. Features hybrid parsing (LlamaParse/PyMuPDF) and 256-dim MRL embeddings for 512MB RAM environments (64 stars)
- [ailingbot](https://madewithwhat.net/langchain/project/ailingbot/): One-stop solution to empower your IM bot with AI. (64 stars, MIT)
- [rhua-chatgpt-web](https://madewithwhat.net/langchain/project/rhua-chatgpt-web/): react + semi ui + tauriLLM，。 (64 stars, MIT)
- [Medical-RAG-using-Meditron-7B-LLM](https://madewithwhat.net/langchain/project/medical-rag-using-meditron-7b-llm/): Medical RAG QA App using Meditron 7B LLM, Qdrant Vector Database, and PubMedBERT Embedding Model. (64 stars, MIT)
- [Brainiac](https://madewithwhat.net/langchain/project/brainiac/): Agentic AI-driven Quantitative Alpha Builder. Streamline alpha generation with autonomous research navigation and backtesting. (63 stars)
- [Devseeker](https://madewithwhat.net/langchain/project/devseeker/): prompt to app ai coding agent (63 stars, MIT)
- [obsidian-agent](https://madewithwhat.net/langchain/project/obsidian-agent/): Empower your Obsidian vault with an AI agent from the provider of your choice. (63 stars, MIT)
- [langchain-chatbot](https://madewithwhat.net/langchain/project/langchain-chatbot/): This code is an implementation of a chatbot using LLM chat model API and Langchain. (63 stars, MIT)
- [LangGraph-GUI-backend](https://madewithwhat.net/langchain/project/langgraph-gui-backend/): LangGraph-GUI backend with fastapi (62 stars, MIT)
- [sklearn-diagnose](https://madewithwhat.net/langchain/project/sklearn-diagnose/): AI-powered diagnosis for Scikit-learn models: Detect overfitting, data leakage, class imbalance & more with LLM-generated insights (62 stars, MIT)
- [medgraph-ai](https://madewithwhat.net/langchain/project/medgraph-ai/): Healthcare RAG agent with Neo4j knowledge graphs - Query medical data using LangChain, FastAPI & Streamlit (62 stars)
- [RAG-examples](https://madewithwhat.net/langchain/project/rag-examples/): Retrieval Augmented Generation Examples - Original, GPT based, Semantic Search based. (62 stars, MIT)
- [genai-job-agents](https://madewithwhat.net/langchain/project/genai-job-agents/): A LLM Agent with Langchain/Langgraph helps to analyze CV, look relevant jobs via API, and write a cover letter according to it (61 stars, MIT)
- [uretken-yapayzeka-chatbot-gelistirme-temelleri](https://madewithwhat.net/langchain/project/uretken-yapayzeka-chatbot-gelistirme-temelleri/): Sektörde Kampüs Kapsamında Üretken Yapay Zeka Yardımı ile Chatbot Geliştirme Temelleri dersinin notlarını bu repository üzerinde paylaşaca… (61 stars)
- [llm_optimize](https://madewithwhat.net/langchain/project/llm-optimize/): LLM Optimize is a proof-of-concept library for doing LLM (large language model) guided blackbox optimization. (61 stars, MIT)
- [anthropic-max-router](https://madewithwhat.net/langchain/project/anthropic-max-router/): Dual API router (Anthropic + OpenAI compatible) for Claude MAX Plan - Use flat-rate billing with ANY AI tool: OpenAI SDK, LangChain, Anthropic SDK, and more (61 stars, MIT)
- [lc2mcp](https://madewithwhat.net/langchain/project/lc2mcp/): Convert LangChain tools to FastMCP tools (61 stars, MIT)
- [autochat-bot](https://madewithwhat.net/langchain/project/autochat-bot/): Chatbot created with flask and openai API (61 stars)
- [EasyTrip](https://madewithwhat.net/langchain/project/easytrip/): Champion at BUET CSE FEST 2024 Hackathon - EasyTrip is an AI-powered platform that simplifies travel planning by generating smart itineraries, integrating interactive maps and weather updates, and automating content creation like blogs and vlogs. (60 stars)
- [customer-service-ai-agent](https://madewithwhat.net/langchain/project/customer-service-ai-agent/): LangGraph (60 stars, Apache-2.0)
- [local-rag](https://madewithwhat.net/langchain/project/local-rag/): Local RAG app chat, search and analyse PDF files (60 stars)
- [Build-An-LLM-RAG-Chatbot-With-LangChain-Python](https://madewithwhat.net/langchain/project/build-an-llm-rag-chatbot-with-langchain-python/): Build-An-LLM-RAG-Chatbot-With-LangChain-Python (60 stars)
- [using-llama3-locally](https://madewithwhat.net/langchain/project/using-llama3-locally/): Running llama3 using Ollama-Python, Curl, LangChain, Chroma, and User interface. (59 stars, Apache-2.0)
- [instinct.cpp](https://madewithwhat.net/langchain/project/instinct-cpp/): instinct.cpp provides ready to use alternatives to OpenAI Assistant API and built-in utilities for developing AI Agent applications (RAG, Chatbot, Code interpreter) powered by language models. Call it langchain.cpp if you like. (59 stars, Apache-2.0)
- [Multi-Agent-RAG-Template](https://madewithwhat.net/langchain/project/multi-agent-rag-template/): This template demonstrates how to create a collaborative team of AI agents that work together to process, analyze, and generate insights from documents. (59 stars, MIT)
- [llmdantic](https://madewithwhat.net/langchain/project/llmdantic/): Structured Output Is All You Need! (59 stars, MIT)
- [ctxvault](https://madewithwhat.net/langchain/project/ctxvault/): Local memory infrastructure for AI agents. Store knowledge and skills in isolated vaults you compose, control and query. (59 stars, MIT)
- [Chat-To-Your-Database](https://madewithwhat.net/langchain/project/chat-to-your-database/): Natural language querying allows users to interact with databases more intuitively and efficiently. By leveraging the power of LangChain, SQL Agents, and OpenAI’s Large Language Models (LLMs) like GPT, we have created an application that enable users to query databases using NLP (59 stars, MIT)
- [rag-with-amazon-bedrock-and-opensearch](https://madewithwhat.net/langchain/project/rag-with-amazon-bedrock-and-opensearch/): Opinionated sample on how to build and deploy a RAG application with Amazon Bedrock and OpenSearch (59 stars, MIT-0)
- [GenerativeAI](https://madewithwhat.net/langchain/project/generativeai/): GenAI Experimentation (59 stars)
- [nextjs-starter-template](https://madewithwhat.net/langchain/project/nextjs-starter-template/): A starter template for building Next.js applications with Supabase for authentication, TypeScript, and Tailwind CSS. Includes branches for creating Langchain and LLM chat interfaces and integrating Stripe subscription payments, making it ideal for setting up modern, scalable web apps with robust auth, AI-driven features, and payment processing. (59 stars)
- [CryptoGPT-Crypto-Twitter-Sentiment-Analysis-with-ChatGPT-and-LangChain](https://madewithwhat.net/langchain/project/cryptogpt-crypto-twitter-sentiment-analysis-with-chatgpt-and-langchain/): Streamlit application that leverages ChatGPT and LangChain to analyze tweet sentiment from selected Twitter authors. (59 stars, Apache-2.0)
- [gptstonks](https://madewithwhat.net/langchain/project/gptstonks/): GPTStonks is a financial chatbot powered by LLMs and enhanced with data frameworks. It provides natural language conversation capabilities for financial topics, making it an ideal choice for a wide range of financial applications. (58 stars, MIT)
- [langchain-embeddings](https://madewithwhat.net/langchain/project/langchain-embeddings/): This repository demonstrates the construction of a state-of-the-art multimodal search engine, leveraging Amazon Titan Embeddings, Amazon Bedrock, and LangChain. (58 stars, MIT-0)
- [doccano-mini](https://madewithwhat.net/langchain/project/doccano-mini/): Annotation meets Large Language Models (ChatGPT, GPT-3 and alike). (58 stars, MIT)
- [fred](https://madewithwhat.net/langchain/project/fred/): the UI and agentic backend of the fred innovation track (58 stars, Apache-2.0)
- [Multi-Agent-System-A2A-ADK-MCP](https://madewithwhat.net/langchain/project/multi-agent-system-a2a-adk-mcp/): Multi-Agent Systems with Google's Agent Development Kit + A2A + MCP (57 stars, Apache-2.0)
- [dunetrace](https://madewithwhat.net/langchain/project/dunetrace/): Real-time monitoring of production AI agents. (57 stars)
- [ollama-deep-researcher-ts](https://madewithwhat.net/langchain/project/ollama-deep-researcher-ts/): Fully local web research and report writing assistant. This repo is a Typescript edition of the Ollama Deep Researcher. (57 stars, Unlicense)
- [papa-ts](https://madewithwhat.net/langchain/project/papa-ts/): This library exposes PAPA, your Personal Assistant powered by Private AI, which can be used in any browser environment and completely offline (57 stars, AGPL-3.0)
- [ai-agent-flight-scanner](https://madewithwhat.net/langchain/project/ai-agent-flight-scanner/): AI agent to search Google Flights data (57 stars)
- [mcp-toolbox-sdk-go](https://madewithwhat.net/langchain/project/mcp-toolbox-sdk-go/): Go SDK for interacting with the MCP Toolbox for Databases. (57 stars, Apache-2.0)
- [RAG-Enterprise](https://madewithwhat.net/langchain/project/rag-enterprise/): 100% local RAG system with one-command setup. Your data never leaves your server. AGPL-3.0 (57 stars)
- [AnyChat](https://madewithwhat.net/langchain/project/anychat/): Chat with your Documents(PDF, TXT, DOCX, ODT, PPTX etc), Websites and Youtube Chat too!, CSV files. Uses langchain, Ollama, Groq, Gemini, Streamlit. Llama3 available (57 stars, MIT)
- [Image-to-Speech-GenAI-Tool-Using-LLM](https://madewithwhat.net/langchain/project/image-to-speech-genai-tool-using-llm/): AI tool that generates an Audio short story based on the context of an uploaded image by prompting a GenAI LLM model, Hugging Face AI models together with OpenAI & LangChain (56 stars, MIT)
- [autopentest](https://madewithwhat.net/langchain/project/autopentest/): CLI enabling more autonomous black-box penetration tests using Large Language Models (LLMs) (56 stars)
- [langchain-milvus](https://madewithwhat.net/langchain/project/langchain-milvus/): The LangChain wrapper of Milvus vector database for efficient vector search, full-text search, hybrid retrieval and RAG. (56 stars, MIT)
- [Ctrip-Style-AI-Travel-Assistant](https://madewithwhat.net/langchain/project/ctrip-style-ai-travel-assistant/): A stateful multi-agent travel service system built on LangChain & LangGraph. Features intelligent task delegation, permission control, and human-in-the-loop verification for flight booking, hotel reservations, car rentals, and tour planning. (56 stars)
- [NoLLMChat](https://madewithwhat.net/langchain/project/nollmchat/): Not-Only LLM Chat. An AI application that enhances creativity and user experience beyond just LLM chat. Noted: Seems it beta version of there is issue with DB please clear site Data in debug (56 stars, MIT)
- [ai-starter-kit](https://madewithwhat.net/langchain/project/ai-starter-kit/): A Web app stack written in FastAPI, Qdrant, and React for creating AI projects (55 stars)
- [pensyve](https://madewithwhat.net/langchain/project/pensyve/): Universal memory runtime for AI agents (55 stars)
- [Qwen3-VL-MoeLORA](https://madewithwhat.net/langchain/project/qwen3-vl-moelora/): image-textQwen3-VL-4B-Instruct lora，langchain+RAG+(Multi-Agent) (55 stars, Apache-2.0)
- [myscale-telemetry](https://madewithwhat.net/langchain/project/myscale-telemetry/): Open-source observability for your LLM application. (55 stars, MIT)
- [hello-world-langchain](https://madewithwhat.net/langchain/project/hello-world-langchain/): An example of how to set your LangChain application up to enable deployment on Kinsta App Hosting services. (55 stars)
- [gpt_chatbot](https://madewithwhat.net/langchain/project/gpt-chatbot/): This chatbot lets you use your microphone to communicate with GPT-4. It uses the OpenAI text to speech to respond with a voice. It uses Pinecone to store long term information and retrieves it to create context. API keys for OpenAI and Pinecone required. Tested on Windows (55 stars)
- [jargons.dev](https://madewithwhat.net/langchain/project/jargons-dev/): A community-driven dictionary that simplifies software, engineering and tech terms for all levels. (54 stars, GPL-2.0)
- [LangChain-Pinecone-RAG](https://madewithwhat.net/langchain/project/langchain-pinecone-rag/): A project worth exploring. (54 stars)
- [langgraph-AI-interview-agent](https://madewithwhat.net/langchain/project/langgraph-ai-interview-agent/): This project is a comprehensive recruitment and interview assistance system developed based on large models and agents, leveraging the langgraph and llamaindex agent frameworks. It aims to enhance job search efficiency and interview performance by automating and intelligentizing the entire interview process. it is China Software Cup A3 competition (54 stars)
- [zettelforge](https://madewithwhat.net/langchain/project/zettelforge/): Agentic memory for CTI in Python — STIX knowledge graphs, threat-actor alias resolution, offline-first RAG, MCP server for Claude Code and LangChain agents (54 stars, MIT)
- [python-openai-projects](https://madewithwhat.net/langchain/project/python-openai-projects/): 13 projects using ChatGPT API, Whisper, Embeddings, and DALL-E with Python. (54 stars)
- [function-chain](https://madewithwhat.net/langchain/project/function-chain/): The FunctionChain is a tool that simplifies and organizes the process of invoking OpenAI functions in your Node.js applications. With this toolkit, you can easily scaffold out and isolate all the OpenAI function calls you need, making your code more modular, maintainable, and scalable. (54 stars)
- [agentic-playground](https://madewithwhat.net/langchain/project/agentic-playground/): This is an AI agent playground to demonstrate different agent orchestration patterns and capabilities (54 stars)
- [navalmanac](https://madewithwhat.net/langchain/project/navalmanac/): Chatbot based on Almanac of Naval Ravikant. Uses OpenAI's chat completion API (54 stars)
- [Article-Assistant--RAG-Telegram-Bot](https://madewithwhat.net/langchain/project/article-assistant-rag-telegram-bot/): A sophisticated RAG (Retrieval-Augmented Generation) Telegram bot that transforms articles and documents into interactive knowledge bases. Upload PDFs/URLs and get AI-powered answers with source citations. (54 stars, MIT)
- [twitter-llm-bot](https://madewithwhat.net/langchain/project/twitter-llm-bot/): Fully automatic asynchronous AI operated Twitter bot using Large Language Models through OpenAI and Hugging Face to schedule and generate contextual content. (53 stars, MIT)
- [easy-llms](https://madewithwhat.net/langchain/project/easy-llms/): Easy "1-line" calling of all LLMs from OpenAI, MS Azure, AWS Bedrock, GCP Vertex, and Ollama (53 stars, MIT)
- [langserve-assistant-ui](https://madewithwhat.net/langchain/project/langserve-assistant-ui/): A developer-friendly template for building AI assistants that combines the best of LangServe, LangGraph, and assistant-ui into one seamless package. (53 stars, MIT)
- [lingmengcan](https://madewithwhat.net/langchain/project/lingmengcan/): AIGC Application Platform: Lingmengcan AI, large language model, aigc, stable diffusion, langchainjs, nestjs, vue3, naive ui, DeepSeek, chromadb (52 stars, MIT)
- [TaskEaseGPT](https://madewithwhat.net/langchain/project/taskeasegpt/): (WIP) A user-friendly, AI-powered task manager emphasizing efficient work over planning. Streamlines workflow with intelligent task generation & execution. Boost your productivity today! (52 stars, AGPL-3.0)
- [telegramGPT](https://madewithwhat.net/langchain/project/telegramgpt/): step-by-step guide on creating your very own AI bot using Python, Telegram, and OpenAI GPT models. (52 stars, GPL-3.0)
- [customgpt-starter-kit](https://madewithwhat.net/langchain/project/customgpt-starter-kit/): CustomGPT.ai’s RAG API’s Starter Kit, including multi-instance embedded widgets, floating buttons, and standalone application. (52 stars)
- [sam-assistant](https://madewithwhat.net/langchain/project/sam-assistant/): Sam-assistant is a personal assistant that is designed to understand your documents, search the internet, and in future versions, create and understand images, and communicate with you. It is built in Python, mainly using Langchain and implements most of Langchain (52 stars)
- [AI-Lawyer-RAG-with-Deepseek](https://madewithwhat.net/langchain/project/ai-lawyer-rag-with-deepseek/): AI Lawyer is an intelligent reasoning legal assistant powered by DeepSeek, Ollama RAG and LangChain, designed to streamline legal research and document analysis. By leveraging retrieval-augmented generation (RAG), it provides precise legal insights, and contract summarization. With an intuitive Streamlit-based UI, analyze legal documents. (52 stars, MIT)
- [LangGraph-Mastery-Playbook](https://madewithwhat.net/langchain/project/langgraph-mastery-playbook/): LangGraph Mastery Playbook: guided, code-first lessons for building memory-aware LLM agents and workflows with LangGraph, TrustCall, and LangChain. (52 stars)
- [langchain-chromadb-rag-example](https://madewithwhat.net/langchain/project/langchain-chromadb-rag-example/): My attempt at implementing retreival augmented generation on Ollama and other LLM services using chromadb and langchain while also providing an easy to understand, clean code for others since nobody else does (52 stars)
- [clawos](https://madewithwhat.net/langchain/project/clawos/): Local AI agent for your laptop. Voice activation, multi-step tool use, 7-layer memory, human-in-the-loop approvals. Zero cloud. Zero API keys. Zero telemetry. (52 stars, AGPL-3.0)
- [clyro](https://madewithwhat.net/langchain/project/clyro/): Clyro is a governance platform for AI agents. While most tools let you watch agents fail, Clyro stops failures before they happen, catching infinite loops, runaway costs, and policy violations in real time. (52 stars, Apache-2.0)
- [Prove-My-Point](https://madewithwhat.net/langchain/project/prove-my-point/): Prove My Point is a web-based AI assistant designed to help users back their arguments with credible, research-backed information. It allows users to ask complex or controversial questions and instantly receive answers supported by real research papers from academic sources like arXiv, PubMed, and Semantic Scholar. (51 stars, MIT)
- [Langchain-Interview-Preparation](https://madewithwhat.net/langchain/project/langchain-interview-preparation/): A targeted resource for mastering LangChain, featuring practice problems, code examples, and interview-focused concepts for building AI applications with Python. Covers chaining LLMs, memory management, and tool integration for technical interview success. (51 stars, MIT)
- [Dingent](https://madewithwhat.net/langchain/project/dingent/): A lightweight, user-friendly LLM Agent framework focused on simplifying data retrieval application development. (51 stars, MIT)
- [Simple-RAG-Chatbot](https://madewithwhat.net/langchain/project/simple-rag-chatbot/): Build a simple RAG chatbot with LangChain and Streamlit (51 stars, MIT)
- [doc2mark](https://madewithwhat.net/langchain/project/doc2mark/): AI-powered Python library that converts any document (PDF, Word, Excel, PowerPoint, HTML) to clean Markdown while preserving complex tables and layouts using AI-Powered OCR technology. (51 stars, MIT)
- [markdown-langchain-rag](https://madewithwhat.net/langchain/project/markdown-langchain-rag/): Query and obtain data from Markdown documents with LangChain's RAG system (51 stars)
- [know-my-doc](https://madewithwhat.net/langchain/project/know-my-doc/): KnowMyDoc is a GPT3.5 Powered Python-based conversational AI utility that enables you to build a chatbot with your own data sources and web pages. With KnowMyDoc, you can easily create a chatbot that can answer complex questions by utilizing advanced machine learning techniques and natural language processing (NLP) algorithms. (51 stars)
- [langchain-wechat](https://madewithwhat.net/langchain/project/langchain-wechat/): WeChat chatbot built on LangChain + FastAPI + itchat · LangChain + FastAPI + itchat ， chatgpt-on-wechat (51 stars, MIT)
- [agent-tackle-box](https://madewithwhat.net/langchain/project/agent-tackle-box/): A toolkit for developing AI agents, including agent-debugger: Terminal debugger for LangGraph & LangChain agents. Debug LLM agents with state inspection, tool calls, semantic breakpoints, and Python program stepping in one Textual UI. (51 stars, MIT)
- [ai-agents-security](https://madewithwhat.net/langchain/project/ai-agents-security/): It's actively developed around agents, ai, ai-safety, and is a solid reference for anyone building with these tools. (51 stars, Apache-2.0)
- [deeptrade](https://madewithwhat.net/langchain/project/deeptrade/): ，ETH。LLM（DeepSeek、Qwen），。 (51 stars)
- [Eunomia](https://madewithwhat.net/langchain/project/eunomia/): Analyze your code locally using a GPT LLM. (51 stars, Apache-2.0)
- [RAG_local_tutorial](https://madewithwhat.net/langchain/project/rag-local-tutorial/): Simple RAG tutorials that can be run locally or using Google Colab (only Pro version). (51 stars)
- [fastapi-langchain-rag](https://madewithwhat.net/langchain/project/fastapi-langchain-rag/): (Let's start with a) Scalable question-answering system utilizing FastAPI, LangChain (LCEL), and PGVector, featuring an ingestion pipeline. Deployed on GCP Cloud Run via Terraform. (50 stars)
- [frr-qa](https://madewithwhat.net/langchain/project/frr-qa/): It's actively developed around chatgpt, chatgpt-bot, chatgpt-python, and is a solid reference for anyone building with these tools. (50 stars, MIT)
- [ask-ripeseed](https://madewithwhat.net/langchain/project/ask-ripeseed/): An AI Assistant to answer user queries based on your own knowledge base! (50 stars, MIT)
- [Perspective](https://madewithwhat.net/langchain/project/perspective/): Perspective analyzes your news or social feed and presents credible counter-narratives from reliable sources—helping you think critically, reduce bias, and see the full picture. Don’t settle for one-sided stories. Get complete, nuanced facts. (50 stars, MIT)
- [PoRAG](https://madewithwhat.net/langchain/project/porag/): Fully Configurable RAG Pipeline for Bengali Language RAG Applications. Supports both Local and Huggingface Models, Built with Langchain. (50 stars, MIT)
- [synapse](https://madewithwhat.net/langchain/project/synapse/): Synapse is a powerful package that enables seamless integration and management of AI agents within Laravel applications. Inspired by Langchain and Laravel Saloon, it provides a flexible framework to create, manage, and scale AI agents using customizable memory options, dynamic prompts, and multiple integrations, including OpenAI and Claude. (50 stars, MIT)
- [spotify-langchain-gpt](https://madewithwhat.net/langchain/project/spotify-langchain-gpt/): Building Spotify playlists based on vibes using LangChain and GPT (50 stars)
- [solagent](https://madewithwhat.net/langchain/project/solagent/): The library for AI agents on Solana (50 stars, Apache-2.0)
- [groq-gmail-assistant](https://madewithwhat.net/langchain/project/groq-gmail-assistant/): Advanced AI email assistant using Groq for responsive replies, Llama for contextual information retrieval, and RAG with LangChain for enhanced accuracy. (50 stars)
- [Law-GPT](https://madewithwhat.net/langchain/project/law-gpt/): Chatbot for Indian Law using Llama-7B-chat using Langchain integration and Streamlit UI. (50 stars, MIT)
- [langchain-zhipuai](https://madewithwhat.net/langchain/project/langchain-zhipuai/): Langchain，GLM-4 AllTools (49 stars, MIT)
- [langchain-mcp-client](https://madewithwhat.net/langchain/project/langchain-mcp-client/): This Streamlit application provides a user interface for connecting to MCP (Model Context Protocol) servers and interacting with them using different LLM providers (OpenAI, Anthropic, Google, Ollama). (49 stars, MIT)
- [watsonx-developer-hub](https://madewithwhat.net/langchain/project/watsonx-developer-hub/): Examples and guides for building Gen AI applications on the watsonx platform. (49 stars, Apache-2.0)
- [AutoReviewer](https://madewithwhat.net/langchain/project/autoreviewer/): Use LLMs to perform automatic code reviews. (49 stars, MIT)
- [Langchain-RAG-DevelopmentKit](https://madewithwhat.net/langchain/project/langchain-rag-developmentkit/): Langchain Models for RAGs and Agents (49 stars)
- [Blog](https://madewithwhat.net/langchain/project/blog/): ！、、AIAgent、AI ：wgrape.github.io (49 stars, MIT)
- [inflearn-langgraph-agent](https://madewithwhat.net/langchain/project/inflearn-langgraph-agent/): "LangGraph AI Agent " (49 stars, MIT)
- [umix](https://madewithwhat.net/langchain/project/umix/): Let's make the web fun! (49 stars)
- [photo-GPT-telegram](https://madewithwhat.net/langchain/project/photo-gpt-telegram/): A telegram bot based on large language models (GPT-3) for image tasks like creating image, captioning, editing and general conversation like chatting about images based on stable diffusion, huggingface and langchain. (49 stars, Apache-2.0)
- [llm_qualitative_data_analysis](https://madewithwhat.net/langchain/project/llm-qualitative-data-analysis/): Qualitative Data Analysis done by AI (or LLMs). Streamlit & Langchain (49 stars)
- [chatgpt-plugin-fastapi-langchain-chroma](https://madewithwhat.net/langchain/project/chatgpt-plugin-fastapi-langchain-chroma/): An Example Plugin for ChatGPT, Utilizing FastAPI, LangChain and Chroma (49 stars, AGPL-3.0)
- [ubiquite](https://madewithwhat.net/langchain/project/ubiquite/): Ubiquité: Open-source Perplexity clone with multi-LLM support and KaTeX math rendering. (48 stars, AGPL-3.0)
- [llm-pdf-qa-workshop](https://madewithwhat.net/langchain/project/llm-pdf-qa-workshop/): Introduction to LLM App Development Workshop: PDF Q&A App using OpenAI, Langchain, and Chainlit (48 stars, GPL-3.0)
- [llm-langchain-sql-demo](https://madewithwhat.net/langchain/project/llm-langchain-sql-demo/): Using LangChain's SQL Database Chain and Agent with various LLMs to perform Natural Language Queries (NLQ) of an Amazon RDS for PostgreSQL database. (48 stars, MIT)
- [InstAgent](https://madewithwhat.net/langchain/project/instagent/): InstAgent - Instantly transform natural language descriptions into powerful multi-agent systems — define roles, equip them with the right tools, and generate ready-to-run code — all in one seamless flow, guided by a single instruction. (48 stars)
- [langgraph-editor](https://madewithwhat.net/langchain/project/langgraph-editor/): This is a visual editor for langgraph workflow. It helps to quickly design and debug the workflow from scratch. (48 stars, MIT)
- [rag-conversational-agent](https://madewithwhat.net/langchain/project/rag-conversational-agent/): A simple local Retrieval-Augmented Generation (RAG) chatbot that can answer to questions by acquiring information from personal PDF documents. (48 stars)
- [sveltekit-modal-langchain](https://madewithwhat.net/langchain/project/sveltekit-modal-langchain/): An example SvelteKit project using sveltekit-modal, with a Python server endpoint written in langchain. (48 stars)
- [llm-use](https://madewithwhat.net/langchain/project/llm-use/): LLM orchestration toolkit for agent workflows: planner + workers + synthesis, optional router (LLM + learned fallback), supports OpenAI/Anthropic/Ollama/llama.cpp, real scraping with caching, MCP server integration, and a TUI chat UI. (48 stars, MIT)
- [django-ai-agent](https://madewithwhat.net/langchain/project/django-ai-agent/): Learn how to create an AI Agent with Django, LangGraph, and Permit. (48 stars)
- [Ollama-Workbench](https://madewithwhat.net/langchain/project/ollama-workbench/): A comprehensive platform for managing, testing, and leveraging Ollama AI models with advanced features for customization, workflow automation, and collaborative development. (48 stars, MIT)
- [appointment-agent](https://madewithwhat.net/langchain/project/appointment-agent/): A modular and AI-powered appointment booking agent designed to streamline scheduling for businesses, starting with dental clinics. Built with LangGraph, Composio, and Bland.com, it integrates Google Calendar and Gmail to manage appointments, send confirmations, and handle voice interactions. (47 stars)
- [MakerChecker](https://madewithwhat.net/langchain/project/makerchecker/): Open-source security gateway & static scanner for AI agents. Enforce role-based access control (RBAC), human-in-the-loop approvals, segregation of duties, and cryptographically signed, offline-verifiable audit logs. (47 stars, AGPL-3.0)
- [deep-research-agent](https://madewithwhat.net/langchain/project/deep-research-agent/): Deep research agentic system using Time Test Diffusion (47 stars, MIT)
- [teach-show-consult](https://madewithwhat.net/langchain/project/teach-show-consult/): Teach ChatGPT the Alda music programming language, show it some superb code, and consult with it to compose a melody. (47 stars, MIT)
- [llm-ollama-llamaindex-bootstrap](https://madewithwhat.net/langchain/project/llm-ollama-llamaindex-bootstrap/): Designed for offline use, this RAG application template offers a starting point for building your own local RAG pipeline, independent of online APIs and cloud-based LLM services like OpenAI. (47 stars, Apache-2.0)
- [llm_notebooks](https://madewithwhat.net/langchain/project/llm-notebooks/): Concepts and examples on using and training LLMs (47 stars)
- [langchain_faiss_vectorindex](https://madewithwhat.net/langchain/project/langchain-faiss-vectorindex/): Telegram bot that answers questions over your PDFs using retrieval-augmented generation (LangChain + FAISS). (47 stars)
- [Complete-Generative-AI](https://madewithwhat.net/langchain/project/complete-generative-ai/): A comprehensive collection of Generative AI projects and experiments, covering RAG, chatbots, LLM fine-tuning, and more. (47 stars, MIT)
- [dcode-agent-kit](https://madewithwhat.net/langchain/project/dcode-agent-kit/): A Claude Code skill that scaffolds ready-to-run LangChain Deep Agents and dcode CLI agents into any project. (47 stars, MIT)
- [rag-tutorial](https://madewithwhat.net/langchain/project/rag-tutorial/): RAG - ，。4、20、17Jupyter Notebooks、6 (47 stars, MIT)
- [patent-similarity-rag](https://madewithwhat.net/langchain/project/patent-similarity-rag/): RAG app for patent similarity search with chatgpt llm over google patents (47 stars)
- [linebot-langchain](https://madewithwhat.net/langchain/project/linebot-langchain/): Utilizing a LINE Bot integrated with LangChain in Python to assist with stock price inquiries. (47 stars)
- [maximem_synap_sdk](https://madewithwhat.net/langchain/project/maximem-synap-sdk/): Maximem Synap is the memory layer that makes AI agents remember. 92% LongMemEval, 93.2% on LOCOMO. Works natively with LangChain, LlamaIndex, CrewAI, Google ADK, AutoGen, OpenAI Agents, Semantic Kernel, Haystack, and Pydantic AI. (47 stars, Apache-2.0)
- [Agentic_AI_using_LangGraph](https://madewithwhat.net/langchain/project/agentic-ai-using-langgraph/): Agentic AI framework built using LangGraph and Multi-Agent Control Plane (MCP) for building structured, goal-driven multi-agent systems. (46 stars, MIT)
- [RAG-LangChain-AI-System](https://madewithwhat.net/langchain/project/rag-langchain-ai-system/): A production-grade, agentic RAG platform for portfolio intelligence, combining LangChain, Chroma/FAISS, Hugging Face embeddings, and Ollama with dynamic entity extraction, backend API tool-chaining, and a real-time interactive assistant across deploy-ready frontend, backend, and infrastructure stacks. (46 stars, MIT)
- [excel-parser](https://madewithwhat.net/langchain/project/excel-parser/): XLSX parser for LLMs, RAG, LangChain, LangGraph, CrewAI, Claude, MCP — turns Excel (.xlsx) into citation-ready JSON with formulas, charts, dependency graphs, and token-counted chunks. Open-source Python library (MIT). (46 stars, MIT)
- [ControllerGPT](https://madewithwhat.net/langchain/project/controllergpt/): AI controller that controls your robot. (46 stars, Apache-2.0)
- [langchaingo-ollama-rag](https://madewithwhat.net/langchain/project/langchaingo-ollama-rag/): langchaingoollamarag (46 stars, Apache-2.0)
- [TradingAgents-Telegram](https://madewithwhat.net/langchain/project/tradingagents-telegram/): Telegram bot wrapping TradingAgents — chat-driven watchlist with parallel multi-ticker analysis, cancellation, and Telegraph reports. (46 stars, MIT)
- [chatpdf](https://madewithwhat.net/langchain/project/chatpdf/): Chat to PDFs. (46 stars)
- [pace-genai-demos](https://madewithwhat.net/langchain/project/pace-genai-demos/): This repository features three demos that can be effortlessly integrated into your AWS environment. They serve as a practical guide to leveraging AWS services for crafting a sophisticated Large Language Model (LLM) Generative AI, geared towards creating a responsive Question and Answer Bot and localizing content generation. (46 stars, MIT-0)
- [ALMA-memory](https://madewithwhat.net/langchain/project/alma-memory/): Persistent memory for AI agents - Learn, remember, improve. Alternative to Mem0 with scoped learning, anti-patterns, multi-agent sharing, and MCP integration. (46 stars)
- [xbrain](https://madewithwhat.net/langchain/project/xbrain/): OpenAIChat (46 stars)
- [cartai](https://madewithwhat.net/langchain/project/cartai/): The OS AI engineering and monitoring agent. Oversight and compliance copilot for trustworthy AI. (46 stars, Apache-2.0)
- [rag-ollama](https://madewithwhat.net/langchain/project/rag-ollama/): A Retrieval Augmented Generation (RAG) system using LangChain, Ollama, Chroma DB and Gemma 7B model. (46 stars, MIT)
- [gemini-multimodal-chat](https://madewithwhat.net/langchain/project/gemini-multimodal-chat/): Multimodal Chat with Gemini API (46 stars)
- [artinet-sdk](https://madewithwhat.net/langchain/project/artinet-sdk/): Ship Agent2Agent in one line of code. (45 stars, Apache-2.0)
- [Qurio](https://madewithwhat.net/langchain/project/qurio/): Qurio brings multi-provider models, custom agents, reusable skills, MCP servers, HTTP tools, retrieval, long-term memory, Deep Research, and Scrapbook into one operating surface. (45 stars)
- [Multi-Agent-Template-App](https://madewithwhat.net/langchain/project/multi-agent-template-app/): A radically simple, reliable, and high performance template to enable you to quickly get set up building multi-agent applications (45 stars, MIT)
- [langgraph-up-monorepo](https://madewithwhat.net/langchain/project/langgraph-up-monorepo/): A batteries-included monorepo framework for building sophisticated LangGraph applications (45 stars)
- [AINote](https://madewithwhat.net/langchain/project/ainote/): I recently attended the Geekbang "Large Language Models Application Development Practice Camp", where I learned about the application development of Large Language Models. Below is a summary of the after-class exercises that I participated in the camp. (45 stars)
- [ai-agents-eval-techniques](https://madewithwhat.net/langchain/project/ai-agents-eval-techniques/): Implementation of 12 AI agents evaluation techniques (45 stars, MIT)
- [langchain-graphrag-baml](https://madewithwhat.net/langchain/project/langchain-graphrag-baml/): Improving langchain knowledge graphs using baml (45 stars)
- [Autonomous-Multi-Agent-Systems-with-CrewAI-Essay-Writer](https://madewithwhat.net/langchain/project/autonomous-multi-agent-systems-with-crewai-essay-writer/): This repository contains the source code for an autonomous multi-agent system built with CrewAI and LangChain. The project enables AI agents to collaborate on tasks such as researching, writing, and editing essays. (45 stars, MIT)
- [mcp-playground](https://madewithwhat.net/langchain/project/mcp-playground/): A Streamlit-based chat app for LLMs with plug-and-play tool support via Model Context Protocol (MCP), powered by LangChain, LangGraph, and Docker. (45 stars)
- [langchain-research-assistant-docker](https://madewithwhat.net/langchain/project/langchain-research-assistant-docker/): docker setup to run the LangChain research-assistant template using langserve (45 stars, MIT)
- [pytector](https://madewithwhat.net/langchain/project/pytector/): Easy to use LLM Prompt Injection Detection and Prompt Input Sanitization / Detector Python Package with support for local models, API-based safeguards, and LangChain guardrails. (45 stars, Apache-2.0)
- [docdocgo-core](https://madewithwhat.net/langchain/project/docdocgo-core/): Automate web research way beyond the first page of search results; curate knowledge bases to chat with. (45 stars, MIT)
- [agentic-guardrails](https://madewithwhat.net/langchain/project/agentic-guardrails/): Layered guardrails to make agentic AI safer and more reliable. (44 stars, MIT)
- [TitanX](https://madewithwhat.net/langchain/project/titanx/): Enterprise AI Agent Orchestration Platform — Secure, Observable, Configurable. Multi-agent teams with IAM policies, n8n workflows, LangChain memory, LangSmith traces, NemoClaw security, OpenTelemetry, and 20+ LLM providers. (44 stars, Apache-2.0)
- [langchain-gemini-api](https://madewithwhat.net/langchain/project/langchain-gemini-api/): An innovative AI conversation API leveraging Google's Gemini for multimodal understanding. Combines FastAPI, Langchain, and Redis for robust, scalable, and privacy-conscious text and image-based interactions (44 stars)
- [langchain-runnableparallel-company-research](https://madewithwhat.net/langchain/project/langchain-runnableparallel-company-research/): LangChain RunnableParallel example: Research a company by running API calls in parallel. Demonstrates RunnablePassthrough.assign, partial failure handling, and a canonical Pydantic schema as the retrieval layer output. Production-ready pattern for parallel data collection in LangChain. (44 stars, MIT)
- [git-agent](https://madewithwhat.net/langchain/project/git-agent/): Langchain Agent utilizing OpenAI Function Calls to execute Git commands using Natural Language (44 stars, MIT)
- [ai-chatbot-rag](https://madewithwhat.net/langchain/project/ai-chatbot-rag/): Streamlit + Langchain + LlamaCPP + Mistral + Rag (44 stars, MIT)
- [College.ai-main](https://madewithwhat.net/langchain/project/college-ai-main/): ⭐ College.ai is an advanced AI-powered platform that provide a set of tools for students, job seekers, and professionals. (44 stars, MIT)
- [OpenReason](https://madewithwhat.net/langchain/project/openreason/): Adaptive Reasoning Engine for Efficient and Context-Aware Intelligence (44 stars, Apache-2.0)
- [langchain-stock-screener](https://madewithwhat.net/langchain/project/langchain-stock-screener/): LangChain agent usable tool to screen stock data (44 stars, MIT)
- [ocap](https://madewithwhat.net/langchain/project/ocap/): Metad® Open Platform for Enterprise Data Analysis, Indicator Management and Reporting (44 stars)
- [master-langgraph-workflows-in-python-20-real-world-agent-projects-by-hereandnow-ai](https://madewithwhat.net/langchain/project/master-langgraph-workflows-in-python-20-real-world-agent-projects-by-hereandnow-ai/): Unlock the power of LangGraph v0.5.3 with 20 bite‑sized, beginner‑friendly agent projects—from chatbots and finance bots to multi-agent orchestrations. Developed by HERE AND NOW AI, this hands‑on tutorial delivers up‑to‑date Python code, practical business value, and scalable workflows built for today and beyond. (44 stars, MIT)
- [BlogIQ](https://madewithwhat.net/langchain/project/blogiq/): Clone of writesonic.com & copy.ai - BlogIQ is an innovative app powered by OpenAI and Langchain, designed to streamline the content creation process for bloggers. (44 stars)
- [LangChain-Chat-with-Your-Data](https://madewithwhat.net/langchain/project/langchain-chat-with-your-data/): Start building practical applications that allow you to interact with data using LangChain and LLMs. (43 stars)
- [agents-from-scratch-ts](https://madewithwhat.net/langchain/project/agents-from-scratch-ts/): LangGraph Typescript Agents Notebooks: email, human in the loop, memory (43 stars)
- [Multi-Agent-Study-Assistant](https://madewithwhat.net/langchain/project/multi-agent-study-assistant/): AI-powered learning platform with 6 specialized agents for personalized education. Features adaptive roadmaps, quizzes, tutoring, RAG document Q&A, and learning style adaptation. Built with Phidata, Streamlit, and LangChain. (43 stars)
- [LLM_Agri_Bot](https://madewithwhat.net/langchain/project/llm-agri-bot/): This Chatbot helps farmers make informed decisions by leveraging the power of LLM Model from OpenAI. (43 stars, MIT)
- [agentserve](https://madewithwhat.net/langchain/project/agentserve/): A framework for hosting and scaling AI agents. (43 stars, MIT)
- [FinSight](https://madewithwhat.net/langchain/project/finsight/): Multi-agent。（、、、），、8。LangGraph、FastAPIReact。 (43 stars, MIT)
- [recursive-agents](https://madewithwhat.net/langchain/project/recursive-agents/): A meta-framework for self-improving LLMs with transparent reasoning (43 stars, MIT)
- [CentralBank-LLM](https://madewithwhat.net/langchain/project/centralbank-llm/): The first Open-Souce RAG-LLM tool to analyse macroeconomic data and forecasts (43 stars, GPL-2.0)
- [LangChainExamples](https://madewithwhat.net/langchain/project/langchainexamples/): Langchain examples, mainly Google Colab notebooks, but could be others. (43 stars)
- [langchain-litellm](https://madewithwhat.net/langchain/project/langchain-litellm/): LangChain interface to LiteLLM (43 stars, MIT)
- [building-gen-ai-agent-on-aws](https://madewithwhat.net/langchain/project/building-gen-ai-agent-on-aws/): Building an AWS Solution Architect Agent with Generative AI (43 stars, MIT-0)
- [chat-with-pdf](https://madewithwhat.net/langchain/project/chat-with-pdf/): ChatWithPDF is a cutting-edge platform that enhances PDF functionality. Users can upload PDFs, extract summaries, and get answers to questions. It features an attractive UI with shadcn and Tailwind CSS and employs advanced tech like Langchain and OpenAI models for chat completions and text embeddings. It's a powerful tool for document management (42 stars)
- [solana-ai-agent](https://madewithwhat.net/langchain/project/solana-ai-agent/): AI Agent is a groundbreaking AI agent built on the Solana, integrating advanced artificial intelligence with social media capabilities and decentralized trading. An evolving digital entity striving to bridge the gap between AI, social media, and crypto. (42 stars)
- [lelu](https://madewithwhat.net/langchain/project/lelu/): Open source authorization engine for AI agents. Confidence-aware gating · Human-in-the-loop review · Policy-as-code · Full audit trail (42 stars, MIT)
- [AI-Plays-God-of-War](https://madewithwhat.net/langchain/project/ai-plays-god-of-war/): LLM Agent paired with Image Captioning and Yolov8 models plays God of War (42 stars, Unlicense)
- [Cookbook](https://madewithwhat.net/langchain/project/cookbook/): Examples and guides for using Swarms Framework (42 stars, MIT)
- [askdocs-ai](https://madewithwhat.net/langchain/project/askdocs-ai/): An AI-powered chatbot that leverages RAG (Retrieval-Augmented Generation) to answer your questions based on the content of uploaded PDFs (42 stars)
- [mAIcro](https://madewithwhat.net/langchain/project/maicro/): A reusable, open-source AI infrastructure designed for communities and organizations. It understands structured data, processes official announcements, and answers questions accurately by centralizing important information. (42 stars, MIT)
- [Interactive-RAG](https://madewithwhat.net/langchain/project/interactive-rag/): An interactive RAG agent built with LangChain and MongoDB Atlas. Manage your knowledge base, switch embedding models, and tune retrieval parameters on-the-fly through a conversational interface. (42 stars, Apache-2.0)
- [SemanticSlicer](https://madewithwhat.net/langchain/project/semanticslicer/): SemanticSlicer — A smart text chunker for LLM-ready documents. (42 stars, MIT)
- [langgraph_fly_base](https://madewithwhat.net/langchain/project/langgraph-fly-base/): Based on the large model development framework of langchain, LangGraph is integrated to create a scalable workflow architecture. RAG。langchain，LangGraph，RAG：（Milvus），，ChatGLM & OpenAI (42 stars)
- [SearchWithOpenAI](https://madewithwhat.net/langchain/project/searchwithopenai/): Quick start. Index multiple documents in a repository using HuggingFace embeddings. Save them in Chroma and / or FAISS for recall. Choose OpenAI or Azure OpenAI APIs to get answers to your questions - Q&A with OpenAI and Azure OpenAI. (42 stars, MIT)
- [clawmoat](https://madewithwhat.net/langchain/project/clawmoat/): The open-source agent firewall. Prevent AI agents from leaking data, using dangerous tools, and importing poisoned dependencies. (41 stars, MIT)
- [ms-springboot-ai](https://madewithwhat.net/langchain/project/ms-springboot-ai/): Java 23, SpringBoot 3.4.1 Examples using Deep Learning 4 Java & LangChain4J for Generative AI using ChatGPT LLM, RAG and other open source LLMs. Sentiment Analysis, Application Context based ChatBots. Custom Data Handling. LLMs - GPT 3.5 / 4o, Gemini Pro 1.5, Claude 3, Llama 3.1, Phi-3, Gemma 2, Falcon 3, Qwen 2.5, Mistral Nemo, Wizard Math (41 stars, Apache-2.0)
- [NotionRag](https://madewithwhat.net/langchain/project/notionrag/): Ask question over your Notion Database! A naive Retrieval-Augmented Generation (RAG) pipeline backed by Langchain and Streamlit (41 stars, MIT)
- [DeeperResearch](https://madewithwhat.net/langchain/project/deeperresearch/): （Multi-Agent），，、，、。 (41 stars, MIT)
- [youtube-assistant-langchain](https://madewithwhat.net/langchain/project/youtube-assistant-langchain/): A LLM powered YouTube Assistant, ask question about a YouTube video. (41 stars)
- [janus-llm](https://madewithwhat.net/langchain/project/janus-llm/): Leveraging LLMs for modernization through intelligent chunking, iterative prompting and reflection, and retrieval augmented generation (RAG). (41 stars, Apache-2.0)
- [asteria-agent](https://madewithwhat.net/langchain/project/asteria-agent/): Local-first AI research assistant: plans sub-queries, searches the web, and writes fully cited reports. LangChain + LangGraph multi-agent + FastAPI + Next.js, with email-OTP auth and per-user Postgres storage. (41 stars, Apache-2.0)
- [LangChain-Tutorials](https://madewithwhat.net/langchain/project/langchain-tutorials/): Practical step-by-step LangChain guides (41 stars)
- [justllms](https://madewithwhat.net/langchain/project/justllms/): Production-ready Python library for multi-provider LLM orchestration (41 stars, MIT)
- [ESG-Analysis-Using-Retrieval-Augmented-Generation-Engine](https://madewithwhat.net/langchain/project/esg-analysis-using-retrieval-augmented-generation-engine/): Analyse environmental, social, and governance policies for potential gaps using AI - powered by LLMs, RAG techniques, and a regulatory knowledge base using OpenAI API, LangChain, Pinecone and Streamlit. (41 stars)
- [GenSlide](https://madewithwhat.net/langchain/project/genslide/): Agentic AI PowerPoint Slide Generation using LangGraph and GPT-4o (41 stars, MIT)
- [AI-RAG-Assistant-Chatbot](https://madewithwhat.net/langchain/project/ai-rag-assistant-chatbot/): Meet Lumina – my personal AI assistant powered by hybrid RAG with Pinecone vector search and Neo4j graph traversal, Google AI, LangChain, and an MCP server with 30+ tools. Features real-time streaming, conversation branching, and a multi-agent agentic AI pipeline for intelligent, grounded responses with inline citations. (41 stars, MIT)
- [java-langchains](https://madewithwhat.net/langchain/project/java-langchains/): A Java 8+ LangChain implementation. Build powerful LLM based applications in an (enterprise) Java context. (41 stars, MIT)
- [javachain](https://madewithwhat.net/langchain/project/javachain/): JavaChain LLM， LangChain ，Java8。 (40 stars)
- [docs_langchain_cn](https://madewithwhat.net/langchain/project/docs-langchain-cn/): langchainlangchain (40 stars)
- [nextjs-langchain-example](https://madewithwhat.net/langchain/project/nextjs-langchain-example/): Demo of using LangChain.js with Next.js and Vercel Edge Functions (to stream the response) (40 stars)
- [Axon](https://madewithwhat.net/langchain/project/axon/): OpenTelemetry-native LLM observability CLI. Point any OTEL exporter at it and watch your LLM/agent traces in real time. (40 stars, MIT)
- [beam_weaver](https://madewithwhat.net/langchain/project/beam-weaver/): Elixir-native LangChain, LangGraph, and DeepAgents for traceable LLM apps: OTP workflows, tools, memory, human-in-the-loop, streaming, custom clients/adapters, minimal deps, and WeaveScope tracing. (40 stars, Apache-2.0)
- [deepresearch-datagen-cli](https://madewithwhat.net/langchain/project/deepresearch-datagen-cli/): Using deep research workflow to generate datasets for finetuning LLMs. (40 stars, MIT)
- [workcell](https://madewithwhat.net/langchain/project/workcell/): Instantly turn your python function into web app. (40 stars, Apache-2.0)
- [tool_juggler](https://madewithwhat.net/langchain/project/tool-juggler/): Create and manage custom AI assistant tools on-the-fly with a visual interface (40 stars, MIT)
- [LangChain-SynData-RAG-Eval](https://madewithwhat.net/langchain/project/langchain-syndata-rag-eval/): LangChain, Llama2-Chat, and zero- and few-shot prompting are used to generate synthetic datasets for IR and RAG system evaluation (40 stars, MIT)
- [Job-Placement-Prediction-ML-model](https://madewithwhat.net/langchain/project/job-placement-prediction-ml-model/): An AI-powered interactive web application built with Streamlit that predicts whether a candidate will get placed in a job (or admitted) based on academic performance and other features. (40 stars)
- [Agent-World-Protocol](https://madewithwhat.net/langchain/project/agent-world-protocol/): The open world for autonomous AI agents on Solana Trade. Build. Fight. Earn. Explore. Connect your AI agent to a persistent shared world. Trade real SOL, build structures, form guilds, fight for territory, complete bounties, gather resources across 7 biomes. Not a simulation — everything is real. (40 stars)
- [code_using_GPT](https://madewithwhat.net/langchain/project/code-using-gpt/): Analyzing code using GPT. (39 stars, Apache-2.0)
- [chatbot-template](https://madewithwhat.net/langchain/project/chatbot-template/): A modular backend framework for building AI chat applications powered by large language models (LLMs) (39 stars, MIT)
- [scene-based-generative-agent](https://madewithwhat.net/langchain/project/scene-based-generative-agent/): Scene-Based Generative Agent (39 stars, MIT)
- [langgraph-agents](https://madewithwhat.net/langchain/project/langgraph-agents/): A production-ready, scalable multi-agent system built with LangGraph, featuring specialized agents for different tasks with best coding practices. (39 stars)
- [MediGenius](https://madewithwhat.net/langchain/project/medigenius/): Advanced multi-agent Medical AI Assistant powered by LangGraph that delivers empathetic, doctor-like responses using a hybrid pipeline of LLM reasoning, RAG from medical PDFs, and intelligent fallback tools. Features Long-term memory with SQLite, dynamic tool routing, and state reasoning for reliable, context-aware consultation. (39 stars, MIT)
- [hass_llm_assist](https://madewithwhat.net/langchain/project/hass-llm-assist/): LLM conversation agent to control your devices in Home Assistant (39 stars, GPL-3.0)
- [word-teacher](https://madewithwhat.net/langchain/project/word-teacher/): Efficient AI English Learning: Read & Speak via Web | ，， AI ， Web (39 stars, MIT)
- [ai-course](https://madewithwhat.net/langchain/project/ai-course/): Learning Azure AI with APIM, Semantic Kernel and LangChain. (39 stars)
- [LangChain-RAG-Linux](https://madewithwhat.net/langchain/project/langchain-rag-linux/): Examples of RAG using LangChain with local LLMs - Mixtral 8x7B, Llama 2, Mistral 7B, Orca 2, Phi-2, Neural 7B (39 stars)
- [cloneme](https://madewithwhat.net/langchain/project/cloneme/): CloneMe is an advanced AI platform that builds your digital twin—an AI that chats like you, remembers details, and supports multiple platforms. Customizable, memory-driven, and hot-reloadable, it's the ultimate toolkit for creating intelligent, dynamic AI personas. (39 stars)
- [llama3-langchain-kor](https://madewithwhat.net/langchain/project/llama3-langchain-kor/): It shows a korean chatbot using LangChain based on Llama3 (39 stars, Apache-2.0)
- [langflow-client-ts](https://madewithwhat.net/langchain/project/langflow-client-ts/): A TypeScript client for running flows via the Langflow API (39 stars, Apache-2.0)
- [langchain-text-summarization](https://madewithwhat.net/langchain/project/langchain-text-summarization/): Text Summarization App built using Langchain and Streamlit (39 stars)
- [Reddit-AI-Agent](https://madewithwhat.net/langchain/project/reddit-ai-agent/): Reddit AI Agent is an intelligent tool that helps you explore Reddit like never before! It allows you to search for any query and fetch top Reddit threads along with their most relevant comments. (39 stars)
- [airtable-qna](https://madewithwhat.net/langchain/project/airtable-qna/): Ask question to your Airtable base in natural language (39 stars, MIT)
- [swarms-tools](https://madewithwhat.net/langchain/project/swarms-tools/): Swarms Tools provides a vast array of pre-built tools for your agents, MCP servers, and multi-agent systems. (39 stars, MIT)
- [Agentic-RAG-with-LangChain](https://madewithwhat.net/langchain/project/agentic-rag-with-langchain/): A project worth exploring. (39 stars, MIT)
- [PdfPal](https://madewithwhat.net/langchain/project/pdfpal/): Teach a chatbot to be a bookworm with Langchain and OpenAI's GPT-3.5 language model. Get answers to all your burning questions straight from the pages of a PDF! (39 stars, MIT)
- [Gemini-RAG](https://madewithwhat.net/langchain/project/gemini-rag/): Chatbot that uses Gemini-1.0-Pro to answer questions, with memory by using LangChain. Also, it's enriched by RAG and deployed in Dialogflow (39 stars, Apache-2.0)
- [toibot](https://madewithwhat.net/langchain/project/toibot/): ToiBot is a chatbot application built with Node.js that showcases the capabilities of the Flowise SDK. (39 stars)
- [Docprompt](https://madewithwhat.net/langchain/project/docprompt/): Enterprise-ready Document Analysis with Large Language Models (38 stars)
- [OxyJen](https://madewithwhat.net/langchain/project/oxyjen/): OxyJen is an open-source Java framework for orchestrating LLM workloads with graph-style execution, context-aware memory, and deterministic retry/fallback. It treats LLMs as native nodes (not helper utilities), allowing developers to build multi-step AI pipelines that integrate cleanly with existing Java code. (38 stars, Apache-2.0)
- [RAG-ChatBot](https://madewithwhat.net/langchain/project/rag-chatbot/): A basic application using langchain, streamlit, and large language models to build a system for Retrieval-Augmented Generation (RAG) based on documents, also includes how to use Groq and deploy your own applications. (38 stars)
- [kronos-agent-os](https://madewithwhat.net/langchain/project/kronos-agent-os/): Kronos Agent OS (KAOS): self-hosted runtime for durable AI agents with memory, skills, MCP tools, automations, dashboard, and optional swarm coordination. (38 stars, MIT)
- [kisahari](https://madewithwhat.net/langchain/project/kisahari/): a personal journaling app where you can chat with your entries locally (38 stars)
- [NeuralGPT](https://madewithwhat.net/langchain/project/neuralgpt/): Personalized all-purpose AI assistance platform based on hierarchical cooperative multi-agent framework which utilizes websocket connectivity for LLM<->LLM communication (38 stars, CC0-1.0)
- [AI-Chatbot-for-Lawyer](https://madewithwhat.net/langchain/project/ai-chatbot-for-lawyer/): AI-powered chatbot designed specifically for legal professionals. It aims to streamline client interactions, provide preliminary legal guidance, and enhance law firm efficiency. The chatbot offers features such as legal document analysis, client intake automation, legal research assistance, appointment scheduling, multi-language support,. (38 stars)
- [financial-research-analyst-agent](https://madewithwhat.net/langchain/project/financial-research-analyst-agent/): The Financial Research Analyst Agent is a hierarchical multi-agent system that provides comprehensive stock analysis by coordinating 11 specialized AI agents, 20+ analysis tools, a RAG knowledge pipeline, and a multi-provider data layer — all accessible through a Streamlit web app, REST API, and CLI. (38 stars)
- [quant-flow](https://madewithwhat.net/langchain/project/quant-flow/): AI-powered crypto perpetual futures trading bot for Hyperliquid DEX. (38 stars)
- [goAI](https://madewithwhat.net/langchain/project/goai/): A simple, modern, and reliable Go library for interacting with multiple LLM providers (38 stars)
- [llm_maze_agent](https://madewithwhat.net/langchain/project/llm-maze-agent/): Navigating a maze using LLM agent (38 stars, MIT)
- [llm-based-recommender](https://madewithwhat.net/langchain/project/llm-based-recommender/): AI-powered fashion recommendation system leveraging LLMs, embeddings, and retrieval techniques to deliver personalized shopping experiences. (38 stars)
- [amazon-bedrock-custom-langchain-agent](https://madewithwhat.net/langchain/project/amazon-bedrock-custom-langchain-agent/): Learn to build custom prompts and tools for LangChain agents (38 stars, MIT-0)
- [schema-miner](https://madewithwhat.net/langchain/project/schema-miner/): A Human-in-the-Loop Workflow for Scientific Schema Mining with Large Language Models (38 stars, MIT)
- [chatbot-sample](https://madewithwhat.net/langchain/project/chatbot-sample/): A project worth exploring. (37 stars)
- [multiagent-debugger](https://madewithwhat.net/langchain/project/multiagent-debugger/): Multi-Agent Debugger: An AI-powered debugging system using CrewAI to orchestrate specialized agents that analyze logs, trace code, and uncover root causes across your stack — powered by LLM providers. (37 stars, MIT)
- [signet](https://madewithwhat.net/langchain/project/signet/): Proof layer for AI agents. Cryptographically verify every action. (37 stars, Apache-2.0)
- [ai-chatbot](https://madewithwhat.net/langchain/project/ai-chatbot/): AI Chatbot with Streamlit, Langchain, and Mistral7b (37 stars, MIT)
- [Experimental_RAG_Tech](https://madewithwhat.net/langchain/project/experimental-rag-tech/): A collection of experimental Retrieval Augmented Generation (RAG) Techniques to elevate your pipelines, all with code and intuitive explanations (37 stars, MIT)
- [multi-agent-system-using-langgraph](https://madewithwhat.net/langchain/project/multi-agent-system-using-langgraph/): A complete LangGraph multi-agent system demo using SQL tools, Tavily search, MCP Toolbox, and OpenRouter models — with reproducible notebooks and a full supervisor-led agent workflow. (37 stars, MIT)
- [whisper-video](https://madewithwhat.net/langchain/project/whisper-video/): Generate subtitles for all the videos in a folder with OpenAI's Whisper privately in your computer. (37 stars, MIT)
- [write_agent](https://madewithwhat.net/langchain/project/write-agent/): AI writing assistant built with FastAPI, LangChain, LangGraph, RAG, and OpenAI-compatible APIs for style extraction, rewriting, review, and cover generation (37 stars, MIT)
- [aws-genai-rfpassistant](https://madewithwhat.net/langchain/project/aws-genai-rfpassistant/): This repository contains the code and infrastructure as code for a Generative AI-powered Request for Proposal (RFP) Assistant leveraging Amazon Bedrock and AWS Cloud Development Kit (CDK). (37 stars, MIT-0)
- [opencode-llm-proxy](https://madewithwhat.net/langchain/project/opencode-llm-proxy/): Local OpenCode-backed LLM gateway for OpenAI, Anthropic, Gemini, and Responses API-compatible tools, with streaming and tool/function calling. (37 stars, MIT)
- [chat-with-pdf-llm](https://madewithwhat.net/langchain/project/chat-with-pdf-llm/): Chat with your PDFs, built using Streamlit and Langchain. Allows the user to ask questions to a LLM, which will answer based on the content of the provided PDFs. (37 stars, MIT)
- [exact-rag](https://madewithwhat.net/langchain/project/exact-rag/): AI-augmented, conversational information retrieval and data exploration (37 stars, MIT)
- [auto-hyde](https://madewithwhat.net/langchain/project/auto-hyde/): A deep-dive into HyDE for Advanced LLM RAG + Introducing AutoHyDE, a semi-supervised framework to improve the effectiveness, coverage and applicability of HyDE (37 stars)
- [huxley-pdf](https://madewithwhat.net/langchain/project/huxley-pdf/): Upload personal docs and Chat with your PDF files with this GPT4-powered app. Built with LangChain, Pinecone Vector Database, deployed on Streamlit (37 stars, MIT)
- [Dokis](https://madewithwhat.net/langchain/project/dokis/): Lightweight RAG provenance middleware. Verifies every claim in an LLM response is grounded in a retrieved source - without an LLM call. (37 stars, MIT)
- [polymarket-intelligence](https://madewithwhat.net/langchain/project/polymarket-intelligence/): Real-time Polymarket tracker with news aggregation, large activity monitoring, price movement signals, top holder analysis, and AI Agents debate floor. (37 stars)
- [AI-Lawyer---RAG-with-DeepSeek-R1](https://madewithwhat.net/langchain/project/ai-lawyer-rag-with-deepseek-r1/): AI-powered legal chatbot that leverages Retrieval-Augmented Generation (RAG) with DeepSeek R1 for advanced legal reasoning and document analysis. It provides a sophisticated legal assistant that can process and analyze complex legal documents, retrieve relevant information using advanced vector search, and generate nuanced legal analysis. (36 stars, MIT)
- [Agentic-RAG-with-LangGraph-and-Ollama](https://madewithwhat.net/langchain/project/agentic-rag-with-langgraph-and-ollama/): Building production-ready Retrieval-Augmented Generation (RAG) systems with LangGraph orchestration and local Ollama models for privacy-preserving AI applications. (36 stars)
- [Smart-Marketing-Assistant-Crew-AI](https://madewithwhat.net/langchain/project/smart-marketing-assistant-crew-ai/): The Smart Marketing Assistant is an innovative project that leverages AI agents to automate tasks within an Instagram marketing workflow. This project aims to streamline and optimize various marketing activities, providing users with a powerful tool to enhance their social media strategies. (36 stars)
- [coding-assistant-codellama-streamlit](https://madewithwhat.net/langchain/project/coding-assistant-codellama-streamlit/): This project demonstrates how to utilize Codellama, a local open-source Large Language Model (LLM), and customize its behavior according to your specific requirements using a Modelfile. (36 stars)
- [RAG-learning](https://madewithwhat.net/langchain/project/rag-learning/): RE:0RAG。LangChain、LangGraph、LangSmith、PydanticAI。 (36 stars, MIT)
- [context-engine](https://madewithwhat.net/langchain/project/context-engine/): Engineering infrastructure for building retrieval, memory, and context-aware AI systems. (35 stars, MIT)
- [fluent_cli](https://madewithwhat.net/langchain/project/fluent-cli/): Fluent CLI is an advanced command-line interface designed to interact seamlessly with multiple workflow systems like FlowiseAI, Langflow, Make, and Zapier. Tailored for developers and IT professionals, Fluent CLI facilitates robust automation, simplifies complex interactions, and enhances productivity through a powerful and command suite (34 stars, Apache-2.0)
- [SmartDocs-Multillingual-Agentic-Rag](https://madewithwhat.net/langchain/project/smartdocs-multillingual-agentic-rag/): Intelligent multilingual PDF Q&A system for Indian professionals. Sarvam-30B + multilingual-e5-large. 22 Indian languages, no translation layer. (34 stars, MIT)
- [AI-Healthcare-System](https://madewithwhat.net/langchain/project/ai-healthcare-system/): AI Data Engineering Healthcare Platform: PySpark Medallion Lakehouse, Airflow DAGs, 5 ML Models, Local LLM RAG, and FastAPI Clinical Architecture. (34 stars, AGPL-3.0)
- [Drone-Rental-System](https://madewithwhat.net/langchain/project/drone-rental-system/): ，、，：Java 21 + Spring Boot 3.5.13 + Vue 3 + Spring AI + MCP + AI Memory，Dify/Coze、 Python LangChain/LangGraph Agent 。，，star，。 (34 stars, Apache-2.0)
- [togolm](https://madewithwhat.net/langchain/project/togolm/): First open-source AI knowledge layer for Togo — 62K+ documents, RAG API, fine-tuned LLM. Built for developers, startups and institutions in francophone West Africa (34 stars)
- [dagger-chatbot](https://madewithwhat.net/langchain/project/dagger-chatbot/): AI Chatbot that helps you learn how to use Dagger (34 stars, Apache-2.0)
- [GeoAgent](https://madewithwhat.net/langchain/project/geoagent/): Plugin for QGIS interaction using LLM. Enables geospatial analysis and data processing through natural language commands. (33 stars, MIT)
- [aiml-daily-grind](https://madewithwhat.net/langchain/project/aiml-daily-grind/): Day-by-day AI/ML roadmap — 5 phases, 33 weeks, 12 projects. From Python to GenAI. Built by a student, for students. (33 stars, MIT)
- [AgentNexus-LangChain-FastAPI](https://madewithwhat.net/langchain/project/agentnexus-langchain-fastapi/): Langchain FastAPI server (33 stars, MIT)
- [cidadao.ai-backend](https://madewithwhat.net/langchain/project/cidadao-ai-backend/): Sistema multi-agente de IA que transforma dados brutos do Portal da Transparência em investigações inteligentes, democratizando o acesso à informação pública através de processamento de linguagem natural de última geração. (33 stars, MIT)
- [llm-server](https://madewithwhat.net/langchain/project/llm-server/): Open-source LLM server (OpenAI, Ollama, Groq, Anthropic) with support for HTTP, Streaming, Agents, RAG (Deprecated check out Orchestra) -> (33 stars)
- [advanced-ai-intensive](https://madewithwhat.net/langchain/project/advanced-ai-intensive/): Build AI, agents and workflows with RAG, MCP, harnesses, & multi-agent orchestration in a 3-week cohort (32 stars)
- [Autosearch](https://madewithwhat.net/langchain/project/autosearch/): Open-source deep research for AI agents: 40 channels, 10+ Chinese sources. (32 stars, MIT)
- [stability-analysis-agent](https://madewithwhat.net/langchain/project/stability-analysis-agent/): AI Agent for app stability analysis — crash logs, ANR, OOM, freezes & more. Parses, symbolizes (addr2line/atos), extracts code context, and generates root-cause fix suggestions via LangGraph + RAG. iOS/Android/macOS/Linux/Windows. App Agent (32 stars, Apache-2.0)
- [synaptic-memory](https://madewithwhat.net/langchain/project/synaptic-memory/): Knowledge graph + MCP tool server for LLM agents with hybrid retrieval, live DB sync, Korean FTS, and memory feedback. (32 stars)
- [fastapi-langgraph-agent-production-ready-template](https://madewithwhat.net/langchain/project/fastapi-langgraph-agent-production-ready-template/): A production-ready FastAPI template for building AI agent applications with LangGraph integration. This template provides a robust foundation for building scalable, secure, and maintainable AI agent services. (32 stars)
- [ollama-docker-web-application](https://madewithwhat.net/langchain/project/ollama-docker-web-application/): Xây dựng AI Agent Website (31 stars)
- [Agentic-Design-Patterns](https://madewithwhat.net/langchain/project/agentic-design-patterns/): Complete Implementation of 21 Agentic Design Patterns A comprehensive collection of production-ready AI agent patterns, each as a runnable project. Master agentic design through practical examples covering prompt chaining, multi-agent systems, RAG, and more. Perfect for AI developers, researchers, and teams building complex AI workflows (31 stars, MIT)
- [codecut-blog](https://madewithwhat.net/langchain/project/codecut-blog/): 45+ production-ready tutorials on data science, MLOps, and AI tools. All code is executable and adaptable for real projects. (31 stars)
- [leads-db](https://madewithwhat.net/langchain/project/leads-db/): An AI-powered B2B lead generation system. Private preview available (30 stars)
- [SlotFlow](https://madewithwhat.net/langchain/project/slotflow/): Local-first, extensible AI agent workspace — FastAPI + Next.js + LangGraph, with skills, MCP tools, artifacts, long-term memory, sub-agents, and multi-provider (DeepSeek/OpenAI/Anthropic) reasoning streaming. (30 stars)
- [celai](https://madewithwhat.net/langchain/project/celai/): Open source framework designed to accelerate the development of omnichannel AI virtual assistants. (29 stars, MIT)
- [embedease-ai](https://madewithwhat.net/langchain/project/embedease-ai/): It's actively developed around agent, chatbot, customer-service, and is a solid reference for anyone building with these tools. (29 stars)
- [kakunin-samples](https://madewithwhat.net/langchain/project/kakunin-samples/): Runnable examples for AI agent identity & compliance — certificate issuance, scope enforcement, and integrations for LangChain, CrewAI, Next.js & more. (29 stars, MIT)
- [sagecompass](https://madewithwhat.net/langchain/project/sagecompass/): Augmented AI decision framework (29 stars, Apache-2.0)
- [Elpis](https://madewithwhat.net/langchain/project/elpis/): You put an agent into an Elpis, and it becomes Elpis; Be Elpis my friend. (29 stars, MIT)
- [LLM-RAG-Agent-Tutorial](https://madewithwhat.net/langchain/project/llm-rag-agent-tutorial/): LLM-RAG-Agent-Tutorial for AI application developers and researchers. (28 stars, MIT)
- [AgentWatch](https://madewithwhat.net/langchain/project/agentwatch/): AgentWatch — Real-time reasoning auditor and observability platform for AI agents. Catches silent failures in your agent's reasoning chain before they execute — not after they break production. (28 stars, Apache-2.0)
- [PyLangPipe](https://madewithwhat.net/langchain/project/pylangpipe/): a simple lightweight large language model pipeline framework. (28 stars, Apache-2.0)
- [quill](https://madewithwhat.net/langchain/project/quill/): Quill is an open-source software to make chatting to your PDF files easy. (27 stars, MIT)
- [tour-of-agents](https://madewithwhat.net/langchain/project/tour-of-agents/): A 30-minute course to get up to speed on how AI agents actually work (27 stars, MIT)
- [langdag](https://madewithwhat.net/langchain/project/langdag/): High-performance tool for managing LLM conversations and workflows as DAGs. (27 stars, MIT)
- [act-operator](https://madewithwhat.net/langchain/project/act-operator/): Provides and manages the standards of the Act Template. (27 stars, Apache-2.0)
- [agentql-integrations](https://madewithwhat.net/langchain/project/agentql-integrations/): AgentQL's integrations with workflow automation tools and AI agent frameworks let you extract structured data from web pages using queries or natural language and interact with the web with Playwright. Resilient, fast, and AI-ready. (26 stars, MIT)
- [pathlight](https://madewithwhat.net/langchain/project/pathlight/): Visual debugging, execution traces, and observability for AI agents. (25 stars)
- [generative-ai-toolkit-for-sap-hana-cloud](https://madewithwhat.net/langchain/project/generative-ai-toolkit-for-sap-hana-cloud/): Generative AI Client for SAP HANA Cloud is an extension of the existing HANA ML Python client library, mainly focusing on GenAI and related use cases. It includes many leading-edge GenAI related open source libraries and provides seamless integration with HANA ML, HANA vector engine, and other SAP GenAI Hub SDK. (25 stars, Apache-2.0)
- [tourist](https://madewithwhat.net/langchain/project/tourist/): Open-source, LLM-ready SERP and web scraping service (25 stars, MIT)
- [yunshu-ai-agent-platform](https://madewithwhat.net/langchain/project/yunshu-ai-agent-platform/): ChatBI 。 Agent 、RAG 、、Redis ， EmbedChat Token 。 (25 stars, MIT)
- [langgraph-interrupt-workflow-template](https://madewithwhat.net/langchain/project/langgraph-interrupt-workflow-template/): Production-ready LangGraph interrupt template with modern web interface | Human-in-the-loop AI workflows | FastAPI backend + Next.js frontend (24 stars, MIT)
- [YSocial](https://madewithwhat.net/langchain/project/ysocial/): An open-source, AI-driven Social Media Digital Twin powered by LLMs (Ollama, vLLM) for Computational Social Science simulations, network analysis, and human-agent interaction. (24 stars, GPL-3.0)
- [m2m-vector-search](https://madewithwhat.net/langchain/project/m2m-vector-search/): Edge Vector search engine with Vulkan GPU acceleration, hierarchical indexing (HRM2), and native LangChain integration. Gaussian splat-based architecture for similarity search on resource-constrained devices. (24 stars, AGPL-3.0)
- [Gozar](https://madewithwhat.net/langchain/project/gozar/): Self-hosted, Docker-first OpenAI-compatible LLM gateway with provider routing, fallbacks, API keys, and usage controls. (24 stars)
- [THETA](https://madewithwhat.net/langchain/project/theta/): LLM-adaptive embeddings (Zero-shot / LoRA) with Generative Topic Modeling & Agent-based workflow for social science text mining (23 stars, MIT)
- [openharness](https://madewithwhat.net/langchain/project/openharness/): Run coding agents in a sandbox, not on your machine. (23 stars, MIT)
- [LangChain.Providers](https://madewithwhat.net/langchain/project/langchain-providers/): Part of the LangChain.NET project. Has separate abstractions, does not contain dependencies on the main project and can be used independently (23 stars, MIT)
- [rag-firewall](https://madewithwhat.net/langchain/project/rag-firewall/): Client-side retrieval firewall for RAG systems — blocks prompt injection and secret leaks, re-ranks stale or untrusted content, and keeps all data inside your environment. (23 stars, Apache-2.0)
- [latent-gate](https://madewithwhat.net/langchain/project/latent-gate/): VL-JEPA inspired pipeline — compress images/text locally via Ollama, send compact payloads to any LLM API. Cut token costs by ~80%. (23 stars, MIT)
- [embedding_playbook](https://madewithwhat.net/langchain/project/embedding-playbook/): This playbook teaches you how to compose Tableau's varied product capabilities into applications that thrill customers, coworkers and friends! (22 stars, MIT)
- [fast-langgraph](https://madewithwhat.net/langchain/project/fast-langgraph/): High-performance Rust accelerators for LangGraph applications. Drop-in components that provide up to 700x speedups for checkpoint operations and 10-50x speedups for state management. (22 stars, MIT)
- [ollama-chat](https://madewithwhat.net/langchain/project/ollama-chat/): A customizable Python CLI tool for interacting with local Language Models, ensuring data privacy while providing conversation memory and extensibility through plugins and efficient Retrieval-Augmented Generation capabilities with ChromaDB integration. Also compatible with OpenAI API. (22 stars)
- [ai-natural-language-tests](https://madewithwhat.net/langchain/project/ai-natural-language-tests/): Enterprise-grade platform to generate and execute Cypress, Playwright, WebdriverIO, and Appium end-to-end tests from natural language requirements. (Appium is experimental and requires external mobile infrastructure.) (22 stars, AGPL-3.0)
- [Cogtrix](https://madewithwhat.net/langchain/project/cogtrix/): About Modular AI assistant — 60 built-in tools, multi-provider LLM support (Ollama, OpenAI, Anthropic, Gemini), hybrid memory, WhatsApp/Telegram daemon mode (21 stars)
- [swytchcode-examples](https://madewithwhat.net/langchain/project/swytchcode-examples/): Swytchcode demo projects with different agents (21 stars, MIT)
- [multi-model-AI-assistant-medical-bot](https://madewithwhat.net/langchain/project/multi-model-ai-assistant-medical-bot/): RAG-enabled multi-agentic system for medical diagnosis and assistance (21 stars, Apache-2.0)
- [analystOS](https://madewithwhat.net/langchain/project/analystos/): analystOS - AI research platform for stocks and crypto with Web UI + Notion automation. Upload docs, scrape URLs, chat with research via RAG. Powered by OpenRouter (50+ models). (21 stars)
- [rag-tui](https://madewithwhat.net/langchain/project/rag-tui/): Debug your RAG pipeline without leaving the terminal. Real-time chunking visualization, batch testing, quality metrics, and one-click export to LangChain/LlamaIndex. (21 stars, MIT)
- [Terradev](https://madewithwhat.net/langchain/project/terradev/): An imperative command-line-interface for AI workload orchestration (21 stars, Apache-2.0)
- [Diffguard](https://madewithwhat.net/langchain/project/diffguard/): AI Pipeline — 、、， Action 。 (20 stars, MIT)
- [openui-forge](https://madewithwhat.net/langchain/project/openui-forge/): Cross-IDE, multi-stack agent skill for OpenUI (the Open Standard for Generative UI). Adds OpenUI to existing projects across 12 backend stacks, any LLM provider, and 11 agent platforms. Scaffold, integrate, validate. (20 stars, MIT)
- [raven](https://madewithwhat.net/langchain/project/raven/): Raven is a self-hostable team Agent platform providing isolated workspaces and unified runtimes for multi-agent workflows. (20 stars, Apache-2.0)
- [daiv](https://madewithwhat.net/langchain/project/daiv/): Your AI-powered SWE teammate, built into your git workflow (20 stars, Apache-2.0)
- [RAGWire](https://madewithwhat.net/langchain/project/ragwire/): Production-grade RAG toolkit — ingest PDFs, DOCX, XLSX into Qdrant with LLM metadata extraction, hybrid search, and SHA256 deduplication. (20 stars, MIT)
- [langchain-pymupdf4llm](https://madewithwhat.net/langchain/project/langchain-pymupdf4llm/): An integration package connecting PyMuPDF4LLM to LangChain (20 stars, AGPL-3.0)
- [tscg](https://madewithwhat.net/langchain/project/tscg/): TSCG — Deterministic tool-schema compiler for LLM agents. 50-72% token savings, 50 tools in 2.4ms. Phi-4 recovers from 0% to 90% accuracy. 459 tests, zero dependencies, MIT. (20 stars, MIT)
- [awaithumans-human-in-the-loop-ai-agents](https://madewithwhat.net/langchain/project/awaithumans-human-in-the-loop-ai-agents/): Pause your AI agent. Ask a human. Resume with their answer. Open source human-in-the-loop (HITL) library for production LLM agents: Slack, email, and web dashboard. Typed Pydantic and Zod responses. Durable Temporal and LangGraph adapters. AI verifier. Audit trail. Self-hosted, Apache 2.0. Python and TypeScript. (20 stars, Apache-2.0)

## DevTools (16)

- [Aix-DB](https://madewithwhat.net/langchain/project/aix-db/): Aix-DB LangChain/LangGraph ， MCP Skills ，。 (2,189 stars)
- [langconnect-client](https://madewithwhat.net/langchain/project/langconnect-client/): A Modern GUI Interface for Vector Database Management(Supports MCP integration) (327 stars, MIT)
- [AI-company](https://madewithwhat.net/langchain/project/ai-company/): Multi-agent team operating system for Claude Code. 108 MCP tools, 40+ agent templates, 10 lifecycle hooks, 7 pipeline workflows. Persistent teams, structured meetings, task wall, real-time React dashboard. No LangChain/AutoGen — pure CC native integration. (317 stars, MIT)
- [langchain-postgres](https://madewithwhat.net/langchain/project/langchain-postgres/): LangChain abstractions backed by Postgres Backend (278 stars, MIT)
- [mermaid-trace](https://madewithwhat.net/langchain/project/mermaid-trace/): Stop reading logs. Start watching them. MermaidTrace is a specialized logging tool that automatically generates Mermaid JS sequence diagrams from your code execution. It's perfect for visualizing complex business logic, microservice interactions, or asynchronous flows. (84 stars, MIT)
- [starpilot](https://madewithwhat.net/langchain/project/starpilot/): Use you a GitHub stars for great good! (75 stars, MIT)
- [aletheia](https://madewithwhat.net/langchain/project/aletheia/): https://aletheiafact.org a Crowd-sourced fact checking platform. (53 stars, GPL-3.0)
- [langchain-chainlit-docker-deployment-template](https://madewithwhat.net/langchain/project/langchain-chainlit-docker-deployment-template/): A template to run Lanchain Powered App using Chainlit Front UI (53 stars, MIT)
- [openstudio-beta](https://madewithwhat.net/langchain/project/openstudio-beta/): Open Studio is an open-source AI ecosystem powering research and automation with specialized agents like ChatHub for AI conversations and OpenStudio Tube for YouTube creators. More niche AI tools on the way—powerful, open, and built for impact! (44 stars)
- [python-for-devops](https://madewithwhat.net/langchain/project/python-for-devops/): Python For DevOps [AI Edition] is a hands-on, beginner-friendly live course that teaches you the exact Python skills needed to automate real DevOps workflows, build tools, integrate with cloud services, and apply AI in day-to-day engineering tasks. (42 stars)
- [snok](https://madewithwhat.net/langchain/project/snok/): A simple, modern, full-stack toolkit for Python (39 stars, MIT)
- [rolemule](https://madewithwhat.net/langchain/project/rolemule/): RoleMule — One mule for every role. Self-hosted AI job companion. Paste a posting (or Chrome extension): five agents analyze the role, score fit, research the company, write a cover letter, and produce resume tips in ~30s. Dashboard, interview prep, mock sessions, hiring outreach, six career tools, CLI. BYOK Gemini/OpenAI/Anthropic/Ollama. (36 stars, MIT)
- [reviewcerberus](https://madewithwhat.net/langchain/project/reviewcerberus/): AI-powered code review tool that analyzes git branch differences and generates comprehensive review reports. Supports AWS Bedrock and Anthropic API. Features automated analysis of logic, security, performance, and code quality with smart token efficiency through prompt caching. (32 stars, MIT)
- [lemoncrow](https://madewithwhat.net/langchain/project/lemoncrow/): Runtime for coding agents. Honestly, get $ 30% more out of your Claude subscription. A real software engineering end to end measured. 80% reduction in input/output tokens 90% reduction in tool calls. (26 stars)
- [ageniusdesk-ce](https://madewithwhat.net/langchain/project/ageniusdesk-ce/): The command center for n8n automation operators: multi-instance management, real-time error tracking, AI-assisted debugging, a Code Lab, and one-click container deployment. Self-hosted, source-available (MIT). (26 stars, MIT)
- [ampersend-sdk](https://madewithwhat.net/langchain/project/ampersend-sdk/): Tooling for building applications with x402 payment capabilities. Supports buyer and seller roles. (23 stars, Apache-2.0)

## Docs (4)

- [dive-into-langgraph](https://madewithwhat.net/langchain/project/dive-into-langgraph/): LangGraph 1.0 Tutorial (419 stars)
- [docs](https://madewithwhat.net/langchain/project/docs/): Unified LangChain documentation. (375 stars, MIT)
- [langsmith-docs](https://madewithwhat.net/langchain/project/langsmith-docs/): This repo is deprecated. Please go to langchain-ai/docs. (173 stars, MIT)
- [confluence2md](https://madewithwhat.net/langchain/project/confluence2md/): Convert Confluence MIME exports (.doc) to clean Markdown (45 stars, Apache-2.0)

## Templates (3)

- [hackathon-starter](https://madewithwhat.net/langchain/project/hackathon-starter/): A boilerplate for Node.js web applications (35,235 stars, MIT)
- [aegis-stack](https://madewithwhat.net/langchain/project/aegis-stack/): A production-ready FastAPI platform with modular components and a built-in control plane. (126 stars, MIT)
- [create-fastapi-project](https://madewithwhat.net/langchain/project/create-fastapi-project/): CLI to create Fastapi projects easily. (122 stars, MIT)

## Dashboards (2)

- [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)
- [ai-crm-agents](https://madewithwhat.net/langchain/project/ai-crm-agents/): Production-ready AI-powered CRM with 6 autonomous agents for lead qualification, email intelligence, sales pipeline, customer success, meeting scheduling, and analytics (49 stars)

## UI Kits (2)

- [agent-prism](https://madewithwhat.net/langchain/project/agent-prism/): React components for visualizing traces from AI agents (371 stars, MIT)
- [maxi-blocks](https://madewithwhat.net/langchain/project/maxi-blocks/): Fast-styling web templates for professional site creators. Build better, launch faster. (69 stars)

## Blogs (2)

- [smart-portfolio](https://madewithwhat.net/langchain/project/smart-portfolio/): A Portfolio Website with an AI chatbot that can answer any question about you. (47 stars, MIT)
- [adarsha.dev](https://madewithwhat.net/langchain/project/adarsha-dev/): My personal website and blog. (28 stars, MIT)

## Mobile (1)

- [mobile-use](https://madewithwhat.net/langchain/project/mobile-use/): AI agents can now use real Android and iOS apps, just like a human. (2,676 stars, Apache-2.0)

## Real-time (1)

- [chanx](https://madewithwhat.net/langchain/project/chanx/): A batteries-included WebSocket framework for Django Channels, FastAPI, and ASGI-based applications. (153 stars)

## Authentication (1)

- [grantex](https://madewithwhat.net/langchain/project/grantex/): grantex is the identity, authorization, and audit infrastructure for AI agents — the "OAuth moment" for the agentic internet. We provide a universal SDK and cloud service that lets any AI agent act on behalf of a human with scoped, revocable permissions, cryptographic identity, and an immutable audit trail. Developers integrate in minutes. (30 stars)

## E-commerce (1)

- [agoragentic-integrations](https://madewithwhat.net/langchain/project/agoragentic-integrations/): Drop-in adapters connecting 50+ agent frameworks (LangChain, CrewAI, AutoGen, OpenAI Agents, MCP, A2A, x402) to the Agoragentic marketplace: route a task with execute, get a receipt, settle in USDC on Base. Monorepo + npm packages for MCP, Micro ECF, and local readiness tooling. (23 stars, MIT)