LocalAI

README

LocalAI

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💻 Quickstart 📣 News 🛫 Examples 🖼️ Models

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.
• Supports multiple models
• 🏃 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 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)!

🔥🔥 Hot topics / Roadmap

🚀 Features

• 📖 Text generation with GPTs (llama.cpp, gpt4all.cpp, ... 📖 and more)
• 🗣 Text to Audio
• 🔈 Audio to Text (Audio transcription with whisper.cpp)
• 🎨 Image generation with stable diffusion
• 🔥 OpenAI functions 🆕
• 🧠 Embeddings generation for vector databases
• ✍️ Constrained grammars
• 🖼️ Download Models directly from Huggingface

📖 🎥 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

💻 Usage

Check out the Getting started section in our documentation.

💡 Example: Use Luna-AI Llama model

See the documentation

🔗 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}},

❤️ 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)

🌟 Star history

📖 License

LocalAI is a community-driven project created by Ettore Di Giacinto.

MIT - Author Ettore Di Giacinto

🙇 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

🤗 Contributors

This is a community project, a special thanks to our contributors! 🤗