This section includes several resources and examples of using LangChain.
## Langchain Smith and Cookbook
- [Langchain Smith](https://smith.langchain.com/hub?organizationId=1efeb0d9-eab7-54d7-bfd6-22070d7756de): a unified developer platform for building, testing, and monitoring LLM applications.
- [Chat Langchain](https://chat.langchain.com/): Ask me anything about LangChain's Python documentation!
- [LangChainHub](https://github.com/hwchase17/langchain-hub): collection of all artifacts useful for working with LangChain primitives such as prompts, chains and agents
- [LangServe](https://github.com/langchain-ai/langserve): LangServe helps developers deploy LangChain runnables and chains as a REST API.
- [steamship-langchain](https://github.com/steamship-core/steamship-langchain): adapters for Steamship, enabling LangChain developers to rapidly deploy their apps on Steamship 🐍
- [LangForge](https://github.com/mme/langforge): A Toolkit for Creating and Deploying LangChain Apps
- [BentoChain](https://github.com/ssheng/BentoChain): LangChain Deployment on BentoML
- [LangCorn](https://github.com/msoedov/langcorn): Serving LangChain apps automagically with FastApi
- [Langchain Service](https://github.com/kyrolabs/langchain-service): Opinionated Langchain setup with Qdrant vector store and Kong gateway
- [Lanarky](https://github.com/ajndkr/lanarky): 🚢 Ship production-ready LLM projects with FastAPI
- [Dify](https://github.com/langgenius/dify): One API for plugins and datasets, one interface for prompt engineering and visual operation, all for creating powerful AI applications.
- [LangchainJS Worker](https://github.com/rickyrobinett/langchainjs-workers): LangchainJS worker on cloudflare
- [Chainlit](https://github.com/Chainlit/chainlit): Build Python LLM apps in minutes ⚡️
- [Psychic](https://github.com/psychic-api/psychic): Universal APIs for unstructured data. Sync documents from SaaS tools to a SQL or vector database, where they can be easily queried by AI applications like ChatGPT.
- [Zep](https://github.com/getzep/zep): Zep: A long-term memory store for LLM / Chatbot applications
- [Langchain Decorators](https://github.com/ju-bezdek/langchain-decorators): a layer on the top op LangChain that provides syntactic sugar 🍭 for writing custom langchain prompts and chains
- [FastAPI + Chroma](https://github.com/experienced-dev/chatgpt-plugin-fastapi-langchain-chroma): An Example Plugin for ChatGPT, Utilizing FastAPI, LangChain and Chroma
- [AilingBot](https://github.com/ericzhang-cn/ailingbot): Quickly integrate applications built on Langchain into IM such as Slack, WeChat Work, Feishu, DingTalk.
- [Private GPT](https://github.com/imartinez/privateGPT): Interact privately with your documents using the power of GPT, 100% privately, no data leaks
- [CollosalAI Chat](https://github.com/hpcaitech/ColossalAI/tree/main/applications/Chat): implement LLM with RLHF, powered by the Colossal-AI project
- [AgentGPT](https://github.com/reworkd/AgentGPT): AI Agents with Langchain & OpenAI (Vercel / Nextjs)
- [Local GPT](https://github.com/PromtEngineer/localGPT): Inspired on Private GPT with the GPT4ALL model replaced with the Vicuna-7B model and using the InstructorEmbeddings instead of LlamaEmbeddings
- [GPT Researcher](https://github.com/assafelovic/gpt-researcher): GPT Researcher is an autonomous agent designed for comprehensive online research on a variety of tasks.
- [ThinkGPT](https://github.com/alaeddine-13/thinkgpt): Agent techniques to augment your LLM and push it beyond its limits
- [Camel-AutoGPT](https://github.com/SamurAIGPT/Camel-AutoGPT): role-playing approach for LLMs and auto-agents like BabyAGI & AutoGPT
- [RasaGPT](https://github.com/paulpierre/RasaGPT): RasaGPT is the first headless LLM chatbot platform built on top of Rasa and Langchain.
- [SkyAGI](https://github.com/litanlitudan/skyagi): Emerging human-behavior simulation capability in LLM agents
- [PyCodeAGI](https://github.com/chakkaradeep/pyCodeAGI): A small AGI experiment to generate a Python app given what app the user wants to build
- [BabyAGI UI](https://github.com/miurla/babyagi-ui): Make it easier to run and develop with babyagi in a web app, like a ChatGPT
- [SuperAgent](https://github.com/homanp/superagent): Deploy LLM Agents to production
- [Voyager](https://github.com/MineDojo/Voyager): An Open-Ended Embodied Agent with Large Language Models
- [DuetGPT](https://github.com/kristoferlund/duet-gpt): A conversational semi-autonomous developer assistant, AI pair programming without the copypasta.
- [Multi-Modal LangChain agents in Production](https://github.com/steamship-packages/langchain-agent-production-starter): Deploy LangChain Agents and connect them to Telegram
- [DemoGPT](https://github.com/melih-unsal/DemoGPT): DemoGPT enables you to create quick demos by just using prompt. It applies ToT approach on Langchain documentation tree.
- [SuperAGI](https://github.com/TransformerOptimus/SuperAGI): SuperAGI - A dev-first open source autonomous AI agent framework
- [Autonomous HR Chatbot](https://github.com/stepanogil/autonomous-hr-chatbot): An autonomous agent that can answer HR related queries autonomously using the tools it has on hand
- [BlockAGI](https://github.com/blockpipe/blockagi): BlockAGI conducts iterative, domain-specific research, and outputs detailed narrative reports to showcase its findings
- [waggledance.ai](https://github.com/agi-merge/waggle-dance): An opinionated, concurrent system of AI Agents. It implements Plan-Validate-Solve with data and tools for general goal-solving.
- [AI](https://github.com/vercel-labs/ai): Vercel template to build AI-powered applications with React, Svelte, and Vue, fist class support for LangChain
- [create-t3-turbo-ai](https://github.com/zckly/create-t3-turbo-ai): t3 based, Langchain-friendly boilerplate for building type-safe, full-stack, LLM-powered web apps with Nextjs and Prisma
- [LangChain.js LLM Template](https://github.com/Conner1115/LangChain.js-LLM-Template): LangChain LLM template that allows you to train your own custom AI LLM model.
- [Streamlit Template](https://github.com/hwchase17/langchain-streamlit-template): template for how to deploy a LangChain on Streamlit
- [Codespaces Template](https://github.com/lostintangent/codespaces-langchain): a Codespaces template for getting up-and-running with LangChain in seconds!
- [Gradio Template](https://github.com/hwchase17/langchain-gradio-template): template for how to deploy a LangChain on Gradio
- [AI Getting Started](https://github.com/a16z-infra/ai-getting-started): A Javascript AI getting started stack for weekend projects, including image/text models, vector stores, auth, and deployment configs
- [Embedchain](https://github.com/embedchain/embedchain): Framework to easily create LLM powered bots over any dataset.
- [Quiver](https://github.com/StanGirard/quiver): Dump your brain into your GenerativeAI Vault
- [DocsGPT](https://github.com/arc53/docsgpt): GPT-powered chat for documentation search & assistance.
- [Chaindesk](https://github.com/gmpetrov/databerry): The no-code platform for semantic search and documents retrieval
- [Knowledge GPT](https://github.com/mmz-001/knowledge_gpt): Accurate answers and instant citations for your documents.
- [Knowledge](https://github.com/KnowledgeCanvas/knowledge): Knowledge is a tool for saving, searching, accessing, and exploring all of your favorite websites, documents and files.
- [Anything LLM](https://github.com/Mintplex-Labs/anything-llm): A full-stack application that turns any documents into an intelligent chatbot with a sleek UI and easier way to manage your workspaces.
- [DocNavigator](https://github.com/vgulerianb/DocNavigator): AI-powered chatbot builder that is designed to improve the user experience on product documentation/support websites
- [ChatFiles](https://github.com/guangzhengli/ChatFiles): Upload your document and then chat with it. Powered by GPT / Embedding / TS / NextJS.
- [DataChad](https://github.com/gustavz/DataChad): A streamlit app that let's you chat with any data source. Supporting both OpenAI and local mode with GPT4All.
- [Second Brain AI Agent](https://github.com/flepied/second-brain-agent): A streamlit app automaticall dialog with your second brain notes using OpenAI and ChromaDB locally.
- [examor](https://github.com/codeacme17/examor): A website application that allows you to take exams based on your knowledge notes. Let you really remember what you have learned and written.
- [DB GPT](https://github.com/csunny/DB-GPT): Interact your data and environment using the local GPT, no data leaks, 100% privately, 100% security
- [AudioGPT](https://github.com/AIGC-Audio/AudioGPT): Understanding and Generating Speech, Music, Sound, and Talking Head
- [Paper QA](https://github.com/whitead/paper-qa): LLM Chain for answering questions from documents with citations
- [Chat Langchain](https://github.com/hwchase17/chat-langchain): locally hosted chatbot specifically focused on question answering over the LangChain documentation
- [Langchain Chat](https://github.com/zahidkhawaja/langchain-chat-nextjs): another Next.js frontend for LangChain Chat.
- [Book GPT](https://github.com/fraserxu/book-gpt): drop a book, start asking question.
- [Chat LangchainJS](https://github.com/sullivan-sean/chat-langchainjs): NextJS version of Chat Langchain
- [Doc Search](https://github.com/namuan/dr-doc-search): converse with book - Built with GPT-3
- [Fact Checker](https://github.com/jagilley/fact-checker): fact-checking LLM outputs with langchain
- [QABot](https://github.com/hardbyte/qabot): Query local or remote files or databases with natural language queries powered by langchain and openai
- [GPT Automator](https://github.com/chidiwilliams/GPT-Automator): Your voice-controlled Mac assistant.
- [Teams LangchainJS](https://github.com/SidU/teams-langchain-js): Demonstration of LangChainJS with Teams / Bot Framework bots
- [ChatGPT](https://github.com/biff-ai/chatgpt-langchainjs-example): ChatGPT & langchain example for node.js & Docker
- [FlowGPT](https://github.com/nilooy/flowgpt): Generate diagram with AI
- [langchain-text-summarizer](https://github.com/alphasecio/langchain-text-summarizer): A sample streamlit application summarizing text using LangChain
- [Langchain Chat Websocket](https://github.com/pors/langchain-chat-websockets): About LangChain LLM chat with streaming response over websockets
- [langchain_yt_tools](https://github.com/venuv/langchain_yt_tools): Langchain tools to search/extract/transcribe text transcripts of Youtube videos
- [SmartPilot](https://github.com/jaredkirby/SmartPilot): A Python program leveraging OpenAI's language models to generate, analyze, and select the best answer to a given question
- [Howdol](https://github.com/bborn/howdoi.ai): a helpful chatbot that can answer questions
- [Chat with Scanned Documents](https://github.com/tony-xlh/Chat-with-Scanned-Documents): A demo chatting with documents scanned with Dynamic Web TWAIN.
- [CSV-AI 🧠](https://python.langchain.com/en/latest/modules/indexes/document_loaders/examples/snowflake.html): CSV-AI is the ultimate app powered by LangChain that allows you to unlock hidden insights in your CSV files.
- [Robby-Chatbot](https://github.com/yvann-hub/Robby-chatbot): AI chatbot 🤖 for chat with CSV, PDF, TXT files 📄 and YTB videos 🎥 | using Langchain🦜 | OpenAI | Streamlit ⚡.
- [PersonalityChatbot](https://github.com/btrcm00/chatbot-with-langchain): Langchain chatbot for chat with personality using Langchain🦜 | LangSmith | MongoDB.
- [Langchain Tutorials](https://github.com/gkamradt/langchain-tutorials): overview and tutorial of the LangChain Library
- [LangChain Chinese Getting Started Guide](https://github.com/liaokongVFX/LangChain-Chinese-Getting-Started-Guide): Chinese LangChain Tutorial for Beginners
- [Flan5 LLM](https://colab.research.google.com/drive/1AVh9dOsG9DKzfK7gOFrJuitPIcLPqlbO?usp=sharing): PDF QA using LangChain for chain of thought and multi-task instructions, Flan5 on HuggingFace
- [LangChain Handbook](https://github.com/pinecone-io/examples/tree/master/generation/langchain/handbook): Pinecone / James Briggs' LangChain handbook
- [Query the YouTube video transcripts](https://colab.research.google.com/drive/1sKSTjt9cPstl_WMZ86JsgEqFG-aSAwkn?usp=sharing): Query the YouTube video transcripts, returning timestamps as sources to legitimize the answers
- [llm-lobbyist](https://github.com/JohnNay/llm-lobbyist): Large Language Models as Corporate Lobbyists
- [Langchain Semantic Search](https://github.com/venuv/langchain_semantic_search): Search and indexing your own Google Drive Files using GPT3, LangChain, and Python
- [GPT Political Compass](https://colab.research.google.com/drive/1xt2IsFPGYMEQdoJFNgWNAjWGxa60VXdV)
- [llm-grovers-search-party](https://github.com/JavaFXpert/llm-grovers-search-party): Leveraging Qiskit, OpenAI and LangChain to demonstrate Grover's algorithm
