LocalAI
π‘ Get help - βFAQ πDiscussions π¬ Discord π Documentation website
π» Quickstart π£ News π« Examples πΌοΈ Models π Roadmap
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, pytorch and more. Does not require GPU.
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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.
- Optional, GPU Acceleration is available in
- Supports multiple models
- π Once loaded the first time, it keep models loaded in memory for faster inference
- β‘ Doesn't shell-out, but uses C++ bindings for a faster inference and better performance.
LocalAI was created by Ettore Di Giacinto 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 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)!
π₯π₯ Hot topics / Roadmap
Hot topics:
π Features
- π Text generation with GPTs (
llama.cpp,gpt4all.cpp, ... π and more) - π£ Text to Audio
- π Audio to Text (Audio transcription with
whisper.cpp) - π¨ Image generation with stable diffusion
- π₯ OpenAI functions π
- π§ Embeddings generation for vector databases
- βοΈ Constrained grammars
- πΌοΈ Download Models directly from Huggingface
- π Vision API
π π₯ Media, Blogs, Social
- Create a slackbot for teams and OSS projects that answer to documentation
- LocalAI meets k8sgpt
- Question Answering on Documents locally with LangChain, LocalAI, Chroma, and GPT4All
- Tutorial to use k8sgpt with LocalAI
π» Usage
Check out the Getting started section in our documentation.
Community
WebUI
Model galleries
Other:
- Helm chart https://github.com/go-skynet/helm-charts
π Resources
- How to build locally
- How to install in Kubernetes
- Projects integrating LocalAI
- How tos section (curated by our community)
Citation
If you utilize this repository, data in a downstream project, please consider citing it with:
@misc{localai,
author = {Ettore Di Giacinto},
title = {LocalAI: The free, Open source OpenAI alternative},
year = {2023},
publisher = {GitHub},
journal = {GitHub repository},
howpublished = {\url{https://github.com/go-skynet/LocalAI}},
β€οΈ Sponsors
Do you find LocalAI useful?
Support the project by becoming a backer or sponsor. 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 |
| Spectro Cloud kindly supports LocalAI by providing GPU and computing resources to run tests on lamdalabs! |
And a huge shout-out to individuals sponsoring the project by donating hardware or backing the project.
- Sponsor list
- JDAM00 (donating HW for the CI)
π Star history
π License
LocalAI is a community-driven project created by Ettore Di Giacinto.
MIT - Author Ettore Di Giacinto
π 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/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
- https://github.com/rhasspy/piper
- https://github.com/cmp-nct/ggllm.cpp
π€ Contributors
This is a community project, a special thanks to our contributors! π€