LocalAI

[![tests](https://github.com/go-skynet/LocalAI/actions/workflows/test.yml/badge.svg)](https://github.com/go-skynet/LocalAI/actions/workflows/test.yml) [![build container images](https://github.com/go-skynet/LocalAI/actions/workflows/image.yml/badge.svg)](https://github.com/go-skynet/LocalAI/actions/workflows/image.yml) [![Artifact Hub](https://img.shields.io/endpoint?url=https://artifacthub.io/badge/repository/localai)](https://artifacthub.io/packages/search?repo=localai) [![](https://dcbadge.vercel.app/api/server/uJAeKSAGDy?style=flat-square&theme=default-inverted)](https://discord.gg/uJAeKSAGDy) [Documentation website](https://localai.io/) **LocalAI** is a drop-in replacement REST API that's compatible with OpenAI API specifications for local inferencing. It allows you to run LLMs (and not only) locally or on-prem with consumer grade hardware, supporting multiple model families that are compatible with the ggml format. Does not require GPU. In a nutshell: - Local, OpenAI drop-in alternative REST API. You own your data. - NO GPU required. NO Internet access is required either - Optional, GPU Acceleration is available in `llama.cpp`-compatible LLMs. See also the [build section](https://localai.io/basics/build/index.html). - Supports multiple models: - 📖 [Text generation with GPTs](https://localai.io/features/text-generation/) (`llama.cpp`, `gpt4all.cpp`, ... [:book: and more](https://localai.io/model-compatibility/index.html#model-compatibility-table)) - 🗣 [Text to Audio](https://localai.io/features/text-to-audio/) - 🔈 [Audio to Text](https://localai.io/features/audio-to-text/) (Audio transcription with `whisper.cpp`) - 🎨 [Image generation with stable diffusion](https://localai.io/features/image-generation) - 🔥 [OpenAI functions](https://localai.io/features/openai-functions/) 🆕 - 🧠 [Embeddings generation for vector databases](https://localai.io/features/embeddings/) - 🏃 Once loaded the first time, it keep models loaded in memory for faster inference - ⚡ Doesn't shell-out, but uses C++ bindings for a faster inference and better performance. LocalAI was created by [Ettore Di Giacinto](https://github.com/mudler/) and is a community-driven project, focused on making the AI accessible to anyone. Any contribution, feedback and PR is welcome! Note that this started just as a [fun weekend project](https://localai.io/#backstory) in order to try to create the necessary pieces for a full AI assistant like `ChatGPT`: the community is growing fast and we are working hard to make it better and more stable. If you want to help, please consider contributing (see below)! See the [Getting started](https://localai.io/basics/getting_started/index.html) and [examples](https://github.com/go-skynet/LocalAI/tree/master/examples/) sections to learn how to use LocalAI. For a list of curated models check out the [model gallery](https://localai.io/models/). | [ChatGPT OSS alternative](https://github.com/go-skynet/LocalAI/tree/master/examples/chatbot-ui) | [Image generation](https://localai.io/api-endpoints/index.html#image-generation) | |------------------------------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------------| | ![Screenshot from 2023-04-26 23-59-55](https://user-images.githubusercontent.com/2420543/234715439-98d12e03-d3ce-4f94-ab54-2b256808e05e.png) | ![b6441997879](https://github.com/go-skynet/LocalAI/assets/2420543/d50af51c-51b7-4f39-b6c2-bf04c403894c) | | [Telegram bot](https://github.com/go-skynet/LocalAI/tree/master/examples/telegram-bot) | [Flowise](https://github.com/go-skynet/LocalAI/tree/master/examples/flowise) | |------------------------------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------------| ![Screenshot from 2023-06-09 00-36-26](https://github.com/go-skynet/LocalAI/assets/2420543/e98b4305-fa2d-41cf-9d2f-1bb2d75ca902) | ![Screenshot from 2023-05-30 18-01-03](https://github.com/go-skynet/LocalAI/assets/2420543/02458782-0549-4131-971c-95ee56ec1af8)| | ## Hot topics / Roadmap - [x] Support for embeddings - [x] Support for audio transcription with https://github.com/ggerganov/whisper.cpp - [X] Support for text-to-audio - [x] GPU/CUDA support ( https://github.com/go-skynet/LocalAI/issues/69 ) - [X] Enable automatic downloading of models from a curated gallery - [X] Enable automatic downloading of models from HuggingFace - [ ] Upstream our golang bindings to llama.cpp (https://github.com/ggerganov/llama.cpp/issues/351) - [ ] Enable gallery management directly from the webui. - [x] 🔥 OpenAI functions: https://github.com/go-skynet/LocalAI/issues/588 - [ ] 🔥 GPTQ support: https://github.com/go-skynet/LocalAI/issues/796 ## News Check the news and the release notes in the [dedicated section](https://localai.io/basics/news/index.html) - 🔥🔥🔥 23-07-2023: **v1.22.0**: LLaMa2, huggingface embeddings, and more ! [Changelog](https://github.com/go-skynet/LocalAI/releases/tag/v1.22.0) For latest news, follow also on Twitter [@LocalAI_API](https://twitter.com/LocalAI_API) and [@mudler_it](https://twitter.com/mudler_it) ## Media, Blogs, Social - [Create a slackbot for teams and OSS projects that answer to documentation](https://mudler.pm/posts/smart-slackbot-for-teams/) - [LocalAI meets k8sgpt](https://www.youtube.com/watch?v=PKrDNuJ_dfE) - [Question Answering on Documents locally with LangChain, LocalAI, Chroma, and GPT4All](https://mudler.pm/posts/localai-question-answering/) - [Tutorial to use k8sgpt with LocalAI](https://medium.com/@tyler_97636/k8sgpt-localai-unlock-kubernetes-superpowers-for-free-584790de9b65) ## Contribute and help To help the project you can: - [Hacker news post](https://news.ycombinator.com/item?id=35726934) - help us out by voting if you like this project. - If you have technological skills and want to contribute to development, have a look at the open issues. If you are new you can have a look at the [good-first-issue](https://github.com/go-skynet/LocalAI/issues?q=is%3Aissue+is%3Aopen+label%3A%22good+first+issue%22) and [help-wanted](https://github.com/go-skynet/LocalAI/issues?q=is%3Aissue+is%3Aopen+label%3A%22help+wanted%22) labels. - If you don't have technological skills you can still help improving documentation or add examples or share your user-stories with our community, any help and contribution is welcome! ## Usage Check out the [Getting started](https://localai.io/basics/getting_started/index.html) section. Here below you will find generic, quick instructions to get ready and use LocalAI. The easiest way to run LocalAI is by using `docker-compose` (to build locally, see [building LocalAI](https://localai.io/basics/build/index.html)): ```bash git clone https://github.com/go-skynet/LocalAI cd LocalAI # (optional) Checkout a specific LocalAI tag # git checkout -b build # copy your models to models/ cp your-model.bin models/ # (optional) Edit the .env file to set things like context size and threads # vim .env # start with docker-compose docker-compose up -d --pull always # or you can build the images with: # docker-compose up -d --build # Now API is accessible at localhost:8080 curl http://localhost:8080/v1/models # {"object":"list","data":[{"id":"your-model.bin","object":"model"}]} curl http://localhost:8080/v1/completions -H "Content-Type: application/json" -d '{ "model": "your-model.bin", "prompt": "A long time ago in a galaxy far, far away", "temperature": 0.7 }' ``` ### Example: Use GPT4ALL-J model
```bash # Clone LocalAI git clone https://github.com/go-skynet/LocalAI cd LocalAI # (optional) Checkout a specific LocalAI tag # git checkout -b build # Download gpt4all-j to models/ wget https://gpt4all.io/models/ggml-gpt4all-j.bin -O models/ggml-gpt4all-j # Use a template from the examples cp -rf prompt-templates/ggml-gpt4all-j.tmpl models/ # (optional) Edit the .env file to set things like context size and threads # vim .env # start with docker-compose docker-compose up -d --pull always # or you can build the images with: # docker-compose up -d --build # Now API is accessible at localhost:8080 curl http://localhost:8080/v1/models # {"object":"list","data":[{"id":"ggml-gpt4all-j","object":"model"}]} curl http://localhost:8080/v1/chat/completions -H "Content-Type: application/json" -d '{ "model": "ggml-gpt4all-j", "messages": [{"role": "user", "content": "How are you?"}], "temperature": 0.9 }' # {"model":"ggml-gpt4all-j","choices":[{"message":{"role":"assistant","content":"I'm doing well, thanks. How about you?"}}]} ```
### Build locally
In order to build the `LocalAI` container image locally you can use `docker`: ``` # build the image docker build -t localai . docker run localai ``` Or you can build the binary with `make`: ``` make build ```
See the [build section](https://localai.io/basics/build/index.html) in our documentation for detailed instructions. ### Run LocalAI in Kubernetes LocalAI can be installed inside Kubernetes with helm. See [installation instructions](https://localai.io/basics/getting_started/index.html#run-localai-in-kubernetes). ## Supported API endpoints See the [list of the LocalAI features](https://localai.io/features/index.html) for a full tour of the available API endpoints. ## Frequently asked questions See [the FAQ](https://localai.io/faq/index.html) section for a list of common questions. ## Projects already using LocalAI to run local models Feel free to open up a PR to get your project listed! - [Kairos](https://github.com/kairos-io/kairos) - [k8sgpt](https://github.com/k8sgpt-ai/k8sgpt#running-local-models) - [Spark](https://github.com/cedriking/spark) - [autogpt4all](https://github.com/aorumbayev/autogpt4all) - [Mods](https://github.com/charmbracelet/mods) - [Flowise](https://github.com/FlowiseAI/Flowise) - [BMO Chatbot](https://github.com/longy2k/obsidian-bmo-chatbot) - [Mattermost OpenOps](https://openops.mattermost.com) ## Sponsors > Do you find LocalAI useful? Support the project by becoming [a backer or sponsor](https://github.com/sponsors/mudler). Your logo will show up here with a link to your website. A huge thank you to our generous sponsors who support this project: | ![Spectro Cloud logo_600x600px_transparent bg](https://github.com/go-skynet/LocalAI/assets/2420543/68a6f3cb-8a65-4a4d-99b5-6417a8905512) | |:-----------------------------------------------:| | [Spectro Cloud](https://www.spectrocloud.com/) | | Spectro Cloud kindly supports LocalAI by providing GPU and computing resources to run tests on lamdalabs! | ## Star history [![LocalAI Star history Chart](https://api.star-history.com/svg?repos=go-skynet/LocalAI&type=Date)](https://star-history.com/#go-skynet/LocalAI&Date) ## License LocalAI is a community-driven project created by [Ettore Di Giacinto](https://github.com/mudler/). MIT ## Author Ettore Di Giacinto and others ## Acknowledgements LocalAI couldn't have been built without the help of great software already available from the community. Thank you! - [llama.cpp](https://github.com/ggerganov/llama.cpp) - https://github.com/tatsu-lab/stanford_alpaca - https://github.com/cornelk/llama-go for the initial ideas - https://github.com/antimatter15/alpaca.cpp - https://github.com/EdVince/Stable-Diffusion-NCNN - https://github.com/ggerganov/whisper.cpp - https://github.com/saharNooby/rwkv.cpp ## Contributors