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) [![](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. For a list of the supported model families, please see [the model compatibility table](https://localai.io/model-compatibility/index.html#model-compatibility-table). 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: - πŸ—£ Text to Audio πŸŽΊπŸ†• - πŸ”ˆ Audio to Text (Audio transcription with `whisper.cpp`) - πŸ“– Text generation with GPTs (`llama.cpp`, `gpt4all.cpp`, ... and more) - 🎨 Image generation with stable diffusion - πŸƒ 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! 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)| | ## News - πŸ”₯πŸ”₯πŸ”₯ 28-06-2023: **v1.20.0**: Added text to audio and gallery huggingface repositories! [Release notes](https://localai.io/basics/news/index.html#-28-06-2023-__v1200__-) [Changelog](https://github.com/go-skynet/LocalAI/releases/tag/v1.20.0) - πŸ”₯πŸ”₯πŸ”₯ 19-06-2023: **v1.19.0**: CUDA support! [Release notes](https://localai.io/basics/news/index.html#-19-06-2023-__v1190__-) [Changelog](https://github.com/go-skynet/LocalAI/releases/tag/v1.19.0) - πŸ”₯πŸ”₯πŸ”₯ 06-06-2023: **v1.18.0**: Many updates, new features, and much more πŸš€, check out the [Release notes](https://localai.io/basics/news/index.html#-06-06-2023-__v1180__-)! - 29-05-2023: LocalAI now has a website, [https://localai.io](https://localai.io)! check the news in the [dedicated section](https://localai.io/basics/news/index.html)! For latest news, follow also on Twitter [@LocalAI_API](https://twitter.com/LocalAI_API) and [@mudler_it](https://twitter.com/mudler_it) ## 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 supported API endpoints](https://localai.io/api-endpoints/index.html) and how to configure image generation and audio transcription. ## 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) ## Short-term roadmap - [x] Mimic OpenAI API (https://github.com/go-skynet/LocalAI/issues/10) - [x] Binary releases (https://github.com/go-skynet/LocalAI/issues/6) - [ ] Upstream our golang bindings to llama.cpp (https://github.com/ggerganov/llama.cpp/issues/351) - [x] Upstream [gpt4all](https://github.com/go-skynet/LocalAI/issues/85) bindings - [x] Multi-model support - [x] Have a webUI! - [x] Allow configuration of defaults for models. - [x] Support for embeddings - [x] Support for audio transcription with https://github.com/ggerganov/whisper.cpp - [x] GPU/CUDA support ( https://github.com/go-skynet/LocalAI/issues/69 ) - [X] Enable automatic downloading of models from a curated gallery - [ ] Enable automatic downloading of models from HuggingFace - [ ] Enable gallery management directly from the webui. - [ ] πŸ”₯ OpenAI functions: https://github.com/go-skynet/LocalAI/issues/588 ## 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