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πŸ€– The free, Open Source alternative to OpenAI, Claude and others. Self-hosted and local-first. Drop-in replacement for OpenAI, running on consumer-grade hardware. No GPU required. Runs gguf, transformers, diffusers and many more models architectures. Features: Generate Text, Audio, Video, Images, Voice Cloning, Distributed, P2P inference

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LocalAI

LocalAI forks LocalAI stars LocalAI pull-requests

LocalAI Docker hub LocalAI Quay.io

Follow LocalAI_API Join LocalAI Discord Community

mudler%2FLocalAI | Trendshift

πŸ’‘ Get help - ❓FAQ πŸ’­Discussions πŸ’¬ Discord πŸ“– Documentation website

πŸ’» Quickstart πŸ–ΌοΈ Models πŸš€ Roadmap πŸ₯½ Demo 🌍 Explorer πŸ›« Examples

testsBuild and Releasebuild container imagesBump dependenciesArtifact Hub

LocalAI is the free, Open Source OpenAI alternative. LocalAI act as a drop-in replacement REST API that’s compatible with OpenAI (Elevenlabs, Anthropic... ) API specifications for local AI inferencing. It allows you to run LLMs, generate images, audio (and not only) locally or on-prem with consumer grade hardware, supporting multiple model families. Does not require GPU. It is created and maintained by Ettore Di Giacinto.

screen

Run the installer script:

curl https://localai.io/install.sh | sh

Or run with docker:

# CPU only image:
docker run -ti --name local-ai -p 8080:8080 localai/localai:latest-cpu

# Nvidia GPU:
docker run -ti --name local-ai -p 8080:8080 --gpus all localai/localai:latest-gpu-nvidia-cuda-12

# CPU and GPU image (bigger size):
docker run -ti --name local-ai -p 8080:8080 localai/localai:latest

# AIO images (it will pre-download a set of models ready for use, see https://localai.io/basics/container/)
docker run -ti --name local-ai -p 8080:8080 localai/localai:latest-aio-cpu

To load models:

# From the model gallery (see available models with `local-ai models list`, in the WebUI from the model tab, or visiting https://models.localai.io)
local-ai run llama-3.2-1b-instruct:q4_k_m
# Start LocalAI with the phi-2 model directly from huggingface
local-ai run huggingface://TheBloke/phi-2-GGUF/phi-2.Q8_0.gguf
# Install and run a model from the Ollama OCI registry
local-ai run ollama://gemma:2b
# Run a model from a configuration file
local-ai run https://gist.githubusercontent.com/.../phi-2.yaml
# Install and run a model from a standard OCI registry (e.g., Docker Hub)
local-ai run oci://localai/phi-2:latest

πŸ’» Getting started

πŸ“° Latest project news

Roadmap items: List of issues

πŸ”₯πŸ”₯ Hot topics (looking for help):

If you want to help and contribute, issues up for grabs: https://github.com/mudler/LocalAI/issues?q=is%3Aissue+is%3Aopen+label%3A%22up+for+grabs%22

πŸš€ Features

πŸ’» Usage

Check out the Getting started section in our documentation.

πŸ”— Community and integrations

Build and deploy custom containers:

WebUIs:

Model galleries

Other:

πŸ”— Resources

πŸ“– πŸŽ₯ Media, Blogs, Social

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 covering CI expenses, and our Sponsor list:


🌟 Star history

LocalAI Star history Chart

πŸ“– License

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

MIT - Author Ettore Di Giacinto mudler@localai.io

πŸ™‡ Acknowledgements

LocalAI couldn't have been built without the help of great software already available from the community. Thank you!

πŸ€— Contributors

This is a community project, a special thanks to our contributors! πŸ€—

About

πŸ€– The free, Open Source alternative to OpenAI, Claude and others. Self-hosted and local-first. Drop-in replacement for OpenAI, running on consumer-grade hardware. No GPU required. Runs gguf, transformers, diffusers and many more models architectures. Features: Generate Text, Audio, Video, Images, Voice Cloning, Distributed, P2P inference

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