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# LangChain Examples
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This section includes several examples of using LangChain.
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# LangChain Resources
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This section includes several resources and examples of using LangChain.
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## Langchain Smith and Cookbook
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- [Langchain Smith](https://smith.langchain.com/hub?organizationId=1efeb0d9-eab7-54d7-bfd6-22070d7756de): a unified developer platform for building, testing, and monitoring LLM applications.
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- [Chat Langchain](https://chat.langchain.com/): Ask me anything about LangChain's Python documentation!
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- [Langchain Cookbook](https://github.com/langchain-ai/langchain/tree/master/cookbook)
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## LangChain Framework
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- [LangChain](https://github.com/hwchase17/langchain): the original 🐍 
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- [LangChain.js](https://github.com/hwchase17/langchainjs): the js brother ✨ 
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- [Concepts](https://docs.langchain.com/docs/): Langchain concepts doc
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- [Twitter account](https://twitter.com/LangChainAI): follow to get fresh updates
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- [Youtube Channel](https://www.youtube.com/channel/UCC-lyoTfSrcJzA1ab3APAgw)
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- [Discord](https://discord.gg/6adMQxSpJS): discussion
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- [Langchain Blog](https://blog.langchain.dev/): The Official Langchain blog
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- [LangChainHub](https://github.com/hwchase17/langchain-hub): collection of all artifacts useful for working with LangChain primitives such as prompts, chains and agents 
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- [LangServe](https://github.com/langchain-ai/langserve): LangServe helps developers deploy LangChain runnables and chains as a REST API. 
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## Ports to other languages
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List of non-official ports of LangChain to other languages.
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- [Langchain Go](https://github.com/tmc/langchaingo): Golang Langchain 
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- [LangchainRb](https://github.com/andreibondarev/langchainrb): Ruby Langchain 
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- [BoxCars](https://github.com/BoxcarsAI/boxcars): Ruby gem, Building applications with composability using Boxcars with LLM's. Inspired by LangChain. 
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- [LangTorch](https://github.com/Knowly-ai/langtorch): Building composable LLM applications with Java / JVM. Inspired by LangChain. 
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- [LangChain4j](https://github.com/langchain4j/langchain4j): LangChain for Java 
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- [LangChainJSDotNet](https://github.com/iassafc/LangChainJSDotNet): Use the official LangChain.js library in .NET 
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- [LangChainDart](https://github.com/davidmigloz/langchain_dart): Build powerful LLM-based Dart/Flutter applications. 
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## Tools
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### Low-code
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- [Flowise](https://github.com/FlowiseAI/Flowise): Drag & drop UI to build your customized LLM flow using LangchainJS 
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- [Langflow](https://github.com/logspace-ai/langflow): LangFlow is a UI for LangChain 
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### Services
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- [GPTCache](https://github.com/zilliztech/GPTCache): A Library for Creating Semantic Cache for LLM Queries 
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- [Gorilla](https://github.com/ShishirPatil/gorilla): An API store for LLMs 
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- [LlamaHub](https://github.com/emptycrown/llama-hub): a library of data loaders for LLMs made by the community 
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- [EVAL](https://github.com/corca-ai/EVAL): Elastic Versatile Agent with Langchain. will execute all your requests. 
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- [Auto-evaluator](https://github.com/PineappleExpress808/auto-evaluator): a lightweight evaluation tool for question-answering using Langchain 
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- [Langchain visualizer](https://github.com/amosjyng/langchain-visualizer): visualization and debugging tool for LangChain workflows 
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- [LLM Strategy](https://github.com/BlackHC/llm-strategy): implementing the Strategy Pattern using LLMs 
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- [datasetGPT](https://github.com/radi-cho/datasetGPT): A command-line interface to generate textual and conversational datasets with LLMs. 
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- [spellbook-forge](https://github.com/rafalzawadzki/spellbook-forge): Make your LLM prompts executable and version controlled. 
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- [Auto Evaluator](https://github.com/langchain-ai/auto-evaluator): Langchain auto evaluator 
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- [Jina](https://github.com/jina-ai/langchain-serve): Langchain Apps on Production with Jina 
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- [Gradio Tools](https://github.com/freddyaboulton/gradio-tools): Gradio 🤝 LLM Agents 
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- [steamship-langchain](https://github.com/steamship-core/steamship-langchain): adapters for Steamship, enabling LangChain developers to rapidly deploy their apps on Steamship 🐍 
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- [LangForge](https://github.com/mme/langforge): A Toolkit for Creating and Deploying LangChain Apps 
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- [BentoChain](https://github.com/ssheng/BentoChain): LangChain Deployment on BentoML 
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- [LangCorn](https://github.com/msoedov/langcorn): Serving LangChain apps automagically with FastApi 
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- [Langchain Service](https://github.com/kyrolabs/langchain-service): Opinionated Langchain setup with Qdrant vector store and Kong gateway 
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- [Lanarky](https://github.com/ajndkr/lanarky): 🚢 Ship production-ready LLM projects with FastAPI 
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- [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. 
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- [LangchainJS Worker](https://github.com/rickyrobinett/langchainjs-workers): LangchainJS worker on cloudflare 
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- [Chainlit](https://github.com/Chainlit/chainlit): Build Python LLM apps in minutes ⚡️ 
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- [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. 
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- [Zep](https://github.com/getzep/zep): Zep: A long-term memory store for LLM / Chatbot applications 
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- [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 
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- [FastAPI + Chroma](https://github.com/experienced-dev/chatgpt-plugin-fastapi-langchain-chroma): An Example Plugin for ChatGPT, Utilizing FastAPI, LangChain and Chroma
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- [AilingBot](https://github.com/ericzhang-cn/ailingbot): Quickly integrate applications built on Langchain into IM such as Slack, WeChat Work, Feishu, DingTalk.
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- [Llama2 Embedding Server](https://github.com/Dicklesworthstone/llama_embeddings_fastapi_service): Llama2 Embeddings FastAPI Service using LangChain 
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### Agents
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- [Private GPT](https://github.com/imartinez/privateGPT): Interact privately with your documents using the power of GPT, 100% privately, no data leaks 
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- [CollosalAI Chat](https://github.com/hpcaitech/ColossalAI/tree/main/applications/Chat): implement LLM with RLHF, powered by the Colossal-AI project 
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- [AgentGPT](https://github.com/reworkd/AgentGPT): AI Agents with Langchain & OpenAI (Vercel / Nextjs) 
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- [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 
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- [GPT Researcher](https://github.com/assafelovic/gpt-researcher): GPT Researcher is an autonomous agent designed for comprehensive online research on a variety of tasks. 
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- [ThinkGPT](https://github.com/alaeddine-13/thinkgpt): Agent techniques to augment your LLM and push it beyond its limits 
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- [Camel-AutoGPT](https://github.com/SamurAIGPT/Camel-AutoGPT): role-playing approach for LLMs and auto-agents like BabyAGI & AutoGPT 
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- [RasaGPT](https://github.com/paulpierre/RasaGPT): RasaGPT is the first headless LLM chatbot platform built on top of Rasa and Langchain. 
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- [SkyAGI](https://github.com/litanlitudan/skyagi): Emerging human-behavior simulation capability in LLM agents 
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- [PyCodeAGI](https://github.com/chakkaradeep/pyCodeAGI): A small AGI experiment to generate a Python app given what app the user wants to build 
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- [BabyAGI UI](https://github.com/miurla/babyagi-ui): Make it easier to run and develop with babyagi in a web app, like a ChatGPT 
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- [SuperAgent](https://github.com/homanp/superagent): Deploy LLM Agents to production 
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- [Voyager](https://github.com/MineDojo/Voyager): An Open-Ended Embodied Agent with Large Language Models 
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- [ix](https://github.com/kreneskyp/ix): Autonomous GPT-4 agent platform 
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- [DuetGPT](https://github.com/kristoferlund/duet-gpt): A conversational semi-autonomous developer assistant, AI pair programming without the copypasta. 
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- [Multi-Modal LangChain agents in Production](https://github.com/steamship-packages/langchain-agent-production-starter): Deploy LangChain Agents and connect them to Telegram 
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- [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. 
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- [SuperAGI](https://github.com/TransformerOptimus/SuperAGI): SuperAGI - A dev-first open source autonomous AI agent framework 
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- [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 
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- [BlockAGI](https://github.com/blockpipe/blockagi): BlockAGI conducts iterative, domain-specific research, and outputs detailed narrative reports to showcase its findings 
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- [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. 
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### Templates
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- [AI](https://github.com/vercel-labs/ai): Vercel template to build AI-powered applications with React, Svelte, and Vue, fist class support for LangChain 
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- [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 
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- [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. 
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- [Streamlit Template](https://github.com/hwchase17/langchain-streamlit-template): template for how to deploy a LangChain on Streamlit 
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- [Codespaces Template](https://github.com/lostintangent/codespaces-langchain): a Codespaces template for getting up-and-running with LangChain in seconds! 
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- [Gradio Template](https://github.com/hwchase17/langchain-gradio-template): template for how to deploy a LangChain on Gradio 
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- [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 
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- [Embedchain](https://github.com/embedchain/embedchain): Framework to easily create LLM powered bots over any dataset. 
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### Platforms
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- [Modal](https://modal.com/docs/guide/ex/potus_speech_qanda): End-to-end stack for cloud/ML compute
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- [Metal](https://getmetal.io/): Metal is a managed service that allows you to build AI products without the hassle of managing infrastructure
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- [Graphsignal](https://graphsignal.com/): Observability for AI agents and LLM-powered applications. Trace, monitor and debug LangChain in production.
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- [Mona](https://github.com/monalabs/mona-openai): Live monitoring for your OpenAI usage
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- [Openllmetry](https://github.com/traceloop/openllmetry): Open-source observability for your LLM application, based on OpenTelemetry 
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## Open Source Projects
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### Knowledge Management
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- [Quiver](https://github.com/StanGirard/quiver): Dump your brain into your GenerativeAI Vault 
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- [DocsGPT](https://github.com/arc53/docsgpt): GPT-powered chat for documentation search & assistance. 
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- [Chaindesk](https://github.com/gmpetrov/databerry): The no-code platform for semantic search and documents retrieval 
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- [Knowledge GPT](https://github.com/mmz-001/knowledge_gpt): Accurate answers and instant citations for your documents. 
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- [Knowledge](https://github.com/KnowledgeCanvas/knowledge): Knowledge is a tool for saving, searching, accessing, and exploring all of your favorite websites, documents and files. 
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- [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. 
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- [DocNavigator](https://github.com/vgulerianb/DocNavigator): AI-powered chatbot builder that is designed to improve the user experience on product documentation/support websites 
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- [ChatFiles](https://github.com/guangzhengli/ChatFiles): Upload your document and then chat with it. Powered by GPT / Embedding / TS / NextJS. 
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- [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. 
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- [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. 
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- [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. 
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### Other / Chatbots
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- [DB GPT](https://github.com/csunny/DB-GPT): Interact your data and environment using the local GPT, no data leaks, 100% privately, 100% security 
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- [AudioGPT](https://github.com/AIGC-Audio/AudioGPT): Understanding and Generating Speech, Music, Sound, and Talking Head 
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- [Paper QA](https://github.com/whitead/paper-qa): LLM Chain for answering questions from documents with citations 
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- [Chat Langchain](https://github.com/hwchase17/chat-langchain): locally hosted chatbot specifically focused on question answering over the LangChain documentation 
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- [Langchain Chat](https://github.com/zahidkhawaja/langchain-chat-nextjs): another Next.js frontend for LangChain Chat. 
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- [Book GPT](https://github.com/fraserxu/book-gpt): drop a book, start asking question. 
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- [Chat LangchainJS](https://github.com/sullivan-sean/chat-langchainjs): NextJS version of Chat Langchain 
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- [Doc Search](https://github.com/namuan/dr-doc-search): converse with book - Built with GPT-3 
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- [Fact Checker](https://github.com/jagilley/fact-checker): fact-checking LLM outputs with langchain 
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- [MM ReAct](https://github.com/microsoft/MM-REACT): Multi Modal ReAct Design
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- [QABot](https://github.com/hardbyte/qabot): Query local or remote files or databases with natural language queries powered by langchain and openai 
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- [GPT Automator](https://github.com/chidiwilliams/GPT-Automator): Your voice-controlled Mac assistant. 
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- [Teams LangchainJS](https://github.com/SidU/teams-langchain-js): Demonstration of LangChainJS with Teams / Bot Framework bots 
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- [ChatGPT](https://github.com/biff-ai/chatgpt-langchainjs-example): ChatGPT & langchain example for node.js & Docker 
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- [FlowGPT](https://github.com/nilooy/flowgpt): Generate diagram with AI 
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- [langchain-text-summarizer](https://github.com/alphasecio/langchain-text-summarizer): A sample streamlit application summarizing text using LangChain 
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- [Langchain Chat Websocket](https://github.com/pors/langchain-chat-websockets): About LangChain LLM chat with streaming response over websockets 
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- [langchain_yt_tools](https://github.com/venuv/langchain_yt_tools): Langchain tools to search/extract/transcribe text transcripts of Youtube videos 
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- [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 
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- [Howdol](https://github.com/bborn/howdoi.ai): a helpful chatbot that can answer questions 
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- [MrsStax](https://github.com/normandmickey/MrsStax): QA Slack Bot 
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- [ThoughtSource⚡](https://github.com/OpenBioLink/ThoughtSource): A framework for the science of machine thinking 
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- [ChatGPT Langchain](https://huggingface.co/spaces/JavaFXpert/Chat-GPT-LangChain): ChatGPT clone using langchain on Huggingface
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- [Chat Math Techniques](https://huggingface.co/spaces/JavaFXpert/gpt-math-techniques): langchain chat with math techniques on Huggingface
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- [Notion QA](https://github.com/hwchase17/notion-qa): Notion Question-Answering Bot 
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- [QNimGPT](https://huggingface.co/spaces/rituthombre/QNim): Play Nim against an IBM Quantum Computer simulator or OpenAI GPT-3.5
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- [ChatPDF](https://github.com/akshata29/chatpdf): ChatGPT + Enterprise data with Azure OpenAI 
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- [Chat with Scanned Documents](https://github.com/tony-xlh/Chat-with-Scanned-Documents): A demo chatting with documents scanned with Dynamic Web TWAIN.
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- [snowChat ❄️](https://github.com/kaarthik108/snowChat): Chat with you're snowflake database 
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- [Airtable-QnA](https://github.com/ikram-shah/airtable-qna): 🌟 a question-answering tool for your Airtable content
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- [WingmanAI](https://github.com/e-johnstonn/wingmanAI): tool for interacting with real-time transcription of both system and microphone audio
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- [TutorGPT](https://github.com/plastic-labs/tutor-gpt): Dynamic few-shot metaprompting for the task of tutoring. 
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- [Cheshire Cat](https://github.com/cheshire-cat-ai/core): Custom AGI boT with ready-to-use chat integration and plugins development platform. 
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- [Got Chaat Bot](https://github.com/parker84/GoT-chat-bot): Repo for creating GoT Chatbots (ex: talk with Tyrion Lannister) 
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- [Dialoqbase](https://github.com/n4ze3m/dialoqbase): web application that allows you to create custom chatbots with your own knowledge base 
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- [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.
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- [MindGeniusAI](https://github.com/xianjianlf2/MindGeniusAI): Auto generate MindMap with ChatGPT 
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- [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 ⚡.
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- [AI Chatbot](https://github.com/vercel-labs/ai-chatbot): A full-featured, hackable Next.js AI chatbot built by Vercel Labs 
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- [Instrukt](https://github.com/blob42/Instrukt): A fully-fledged AI environment in the terminal. Build, test and instruct agents. 
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- [OpenChat](https://github.com/openchatai/OpenChat/): LLMs custom-chatbots console ⚡. 
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- [Twitter Agent](https://github.com/ahmedbesbes/twitter-agent/): Scrape tweets, summarize them and chat with them in an interactive terminal. 
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- [GPT Migrate](https://github.com/0xpayne/gpt-migrate): Easily migrate your codebase from one framework or language to another.
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- [Code Interpreter API](https://github.com/shroominic/codeinterpreter-api): About Open source implementation of the ChatGPT Code Interpreter 
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- [Recommender](https://github.com/vishwasg217/recommender): Create captivating email marketing campaigns tailored to your business needs 
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- [Autonomous HR Chatbot](https://github.com/stepanogil/autonomous-hr-chatbot) An autonomous HR agent that can answer user queries using tools 
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- [Lobe Chat](https://github.com/lobehub/lobe-chat) An open-source, extensible (Function Calling), high-performance chatbot framework 
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- [Funcchain](https://github.com/shroominic/funcchain): write prompts, pythonic 
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- [PersonalityChatbot](https://github.com/btrcm00/chatbot-with-langchain): Langchain chatbot for chat with personality using Langchain🦜 | LangSmith | MongoDB. 
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## Learn
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### Notebooks
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- [Langchain Tutorials](https://github.com/gkamradt/langchain-tutorials): overview and tutorial of the LangChain Library 
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- [LangChain Chinese Getting Started Guide](https://github.com/liaokongVFX/LangChain-Chinese-Getting-Started-Guide): Chinese LangChain Tutorial for Beginners 
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- [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
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- [LangChain Handbook](https://github.com/pinecone-io/examples/tree/master/generation/langchain/handbook): Pinecone / James Briggs' LangChain handbook
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- [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
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- [llm-lobbyist](https://github.com/JohnNay/llm-lobbyist): Large Language Models as Corporate Lobbyists
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- [Langchain Semantic Search](https://github.com/venuv/langchain_semantic_search): Search and indexing your own Google Drive Files using GPT3, LangChain, and Python
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- [GPT Political Compass](https://colab.research.google.com/drive/1xt2IsFPGYMEQdoJFNgWNAjWGxa60VXdV)
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- [llm-grovers-search-party](https://github.com/JavaFXpert/llm-grovers-search-party): Leveraging Qiskit, OpenAI and LangChain to demonstrate Grover's algorithm
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- [TextWorld ReAct Agent](https://colab.research.google.com/drive/19WTIWC3prw5LDMHmRMvqNV2loD9FHls6?usp=sharing)
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- [LangChain <> Wolfram Alpha](https://colab.research.google.com/drive/1AAyEdTz-Z6ShKvewbt1ZHUICqak0MiwR?usp=sharing)
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- [BYO Knowledge Graph](https://github.com/prof-frink-lab/slangchain/blob/main/docs/modules/knowledge_graph/examples/byo_knowledge_graph.ipynb)
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- [Large Language Models Course](https://github.com/peremartra/Large-Language-Model-Notebooks-Course) 
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### Videos Playlists
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- [LangChain Series by Sam Witteveen](https://www.youtube.com/watch?v=J_0qvRt4LNk&list=PL8motc6AQftk1Bs42EW45kwYbyJ4jOdiZ)
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- [LangChain Tutorials Playlist](https://www.youtube.com/playlist?list=PL611FKPtL866MnlDPHvI3KwVGqCB-QJAx)
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- [LangChain James Briggs' Playlist](https://www.youtube.com/watch?v=nE2skSRWTTs&list=PLIUOU7oqGTLieV9uTIFMm6_4PXg-hlN6F)
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- [Greg Kamradt Playlist](https://www.youtube.com/watch?v=_v_fgW2SkkQ&list=PLqZXAkvF1bPNQER9mLmDbntNfSpzdDIU5)
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## Other LLM Frameworks
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- [Transformers Agents](https://huggingface.co/docs/transformers/transformers_agents): Provides a natural language API on top of transformers
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- [LlamaIndex](https://github.com/jerryjliu/llama_index): provides a central interface to connect your LLM's with external data. 
|
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- [Botpress](https://github.com/botpress/botpress): The building blocks for building chatbots 
|
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- [Haystack](https://github.com/deepset-ai/haystack): NLP framework to interact with your data using Transformer models and LLMs 
|
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- [Semantic Kernel](https://github.com/microsoft/semantic-kernel): Microsoft C# SDK to integrate cutting-edge LLM technology quickly and easily into your apps 
|
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- [Promptify](https://github.com/promptslab/Promptify): Prompt Engineering | Use GPT or other prompt based models to get structured output. 
|
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- [PromptSource](https://github.com/bigscience-workshop/promptsource): About Toolkit for creating, sharing and using natural language prompts. 
|
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- [Agent-LLM](https://github.com/Josh-XT/Agent-LLM): An Artificial Intelligence Automation Platform. 
|
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- [LLM Agents](https://github.com/mpaepper/llm_agents): Build agents which are controlled by LLMs 
|
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- [MiniChain](https://github.com/srush/MiniChain): A tiny library for coding with large language models. 
|
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- [Griptape](https://github.com/griptape-ai/griptape): Python framework for AI workflows and pipelines with chain of thought reasoning, external tools, and memory. 
|
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- [llm-chain](https://github.com/sobelio/llm-chain): is a powerful rust crate for building chains in LLMs allowing you to summarise text and complete complex tasks. 
|
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- [PromptFlow](https://github.com/InsuranceToolkits/promptflow): Create executable flowcharts that link LLMs (Large Language Models), Prompts, Python functions, and conditional logic together. 
|
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- [OpenLM](https://github.com/r2d4/openlm): a drop-in OpenAI-compatible library that can call LLMs from any other hosted inference API. Also [Typescript](https://github.com/r2d4/llm.ts) 
|
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- [Dust](https://github.com/dust-tt/dust): Design and Deploy Large Language Model Apps 
|
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- [e2b](https://github.com/e2b-dev/e2b): Open-source platform for building & deploying virtual developers’ agents
|
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- [SuperAGI](https://github.com/TransformerOptimus/SuperAGI): A dev-first open source autonomous AI agent framework. 
|
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- [SmartGPT](https://github.com/Cormanz/smartgpt): A program that provides LLMs with the ability to complete complex tasks using plugins. 
|
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- [TermGPT](https://github.com/Sentdex/TermGPT): Giving LLMs like GPT-4 the ability to plan and execute terminal commands 
|
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- [ReLLM](https://github.com/r2d4/rellm): Regular Expressions for Language Model Completions. 
|
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- [OpenDAN](https://github.com/fiatrete/OpenDAN-Personal-AI-OS): open source Personal AI OS , which consolidates various AI modules in one place for your personal use. 
|
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- [OpenLLM](https://github.com/bentoml/OpenLLM): An open platform for operating large language models (LLMs) in production. Fine-tune, serve, deploy, and monitor any LLMs with ease using OpenLLM. 
|
||||
- [FlagAI](https://github.com/FlagAI-Open/FlagAI): FlagAI (Fast LArge-scale General AI models) is a fast, easy-to-use and extensible toolkit for large-scale model. 
|
||||
- [AI.JSX](https://github.com/fixie-ai/ai-jsx): The AI Application Framework for Javascript 
|
||||
- [Outlines](https://github.com/normal-computing/outlines): Generative Model Programming (Python) 
|
||||
- [AI Utils](https://github.com/lgrammel/ai-utils.js): TypeScript-first library for building AI apps, chatbots, and agents. 
|
||||
- [MetaGPT](https://github.com/geekan/MetaGPT): The Multi-Agent Meta Programming Framework: Given one line Requirement, return PRD, Design, Tasks, Repo and CI 
|
||||
- [Hyv](https://github.com/failfa-st/hyv): Probably the easiest way to use any AI Model in Node.js and create complex interactions with ease. 
|
||||
- [Autochain](https://github.com/Forethought-Technologies/AutoChain): Build lightweight, extensible, and testable LLM Agents with AutoChain. 
|
||||
- [TypeChat](https://github.com/microsoft/TypeChat): TypeChat is a library that makes it easy to build natural language interfaces using types. 
|
||||
- [Marvin](https://github.com/PrefectHQ/marvin): ✨ Build AI interfaces that spark joy 
|
||||
- [LMQL](https://github.com/eth-sri/lmql): A programming language for large language models. 
|
||||
- [LLMFlow](https://github.com/stoyan-stoyanov/llmflows): Simple, Explicit and Transparent LLM Apps 
|
||||
- [Ax](https://github.com/axilla-io/ax): A comprehensive AI framework for TypeScript 
|
||||
- [TextAI](https://github.com/neuml/txtai): 💡 All-in-one open-source embeddings database for semantic search, LLM orchestration and language model workflows. 
|
||||
- [AgentFlow](https://github.com/simonmesmith/agentflow): About Complex LLM Workflows from Simple JSON. 
|
||||
- [Outlines](https://github.com/normal-computing/outlines): Fast and reliable neural text generation. 
|
||||
- [SimpleAIChat](https://github.com/minimaxir/simpleaichat): Python package for easily interfacing with chat apps, with robust features and minimal code complexity. 
|
||||
- [LLFn](https://github.com/orgexyz/LLFn): A light-weight framework for creating applications using LLMs 
|
||||
- [LLMStack](https://github.com/trypromptly/LLMStack): No code platform for building LLM-powered applications with custom data. 
|
||||
- [Lagent](https://github.com/InternLM/lagent): A lightweight framework for building LLM-based agents 
|
||||
- [Embedbase](https://github.com/different-ai/embedbase): The native Software 3.0 stack for building AI-powered applications. 
|
||||
- [Rivet](https://github.com/Ironclad/rivet): An IDE for creating complex AI agents and prompt chaining, and embedding it in your application. 
|
||||
- [Promptfoo](https://github.com/promptfoo/promptfoo): Test your prompts. Evaluate and compare LLM outputs, catch regressions, and improve prompt quality. 
|
||||
- [RestGPT](https://github.com/Yifan-Song793/RestGPT): An LLM-based autonomous agent controlling real-world applications via RESTful APIs 
|
||||
- [LangStream](https://github.com/LangStream/langstream): Framework for building and running event-driven LLM applications using no-code and Python (including LangChain-based) agents. 
|
||||
- [Magentic](https://github.com/jackmpcollins/magentic): Seamlessly integrate LLMs as Python functions 
|
||||
- [Autogen](https://github.com/microsoft/autogen): Enable Next-Gen Large Language Model Applications.
|
||||
- [AgentVerse](https://github.com/openbmb/agentverse) Provides a flexible framework that simplifies the process of building custom multi-agent environments for LLMs 
|
||||
- [Flappy](https://github.com/pleisto/flappy): Production-Ready LLM Agent SDK for Every Developer ![Github Repo stars]
|
||||
- [MemGPT](https://github.com/cpacker/MemGPT): Teaching LLMs memory management for unbounded context 
|
||||
|
|
|
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Reference in a new issue