LocalAI

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GitHub Go MIT

Description

Open-source AI engine to run any model — LLMs, vision, voice, image, video — on any hardware without GPU. Provides OpenAI-compatible API for fully local, privacy-first AI inference.

Key Features

  • Composable backend architecture — Each backend (llama.cpp, vLLM, whisper.cpp, etc.) is a separate image pulled on demand
  • OpenAI/Anthropic/ElevenLabs-compatible API — Unified API interface across all backends for seamless cloud replacement
  • Any modality support — LLMs, vision, voice, image, and video models behind a single unified API
  • Any hardware support — Runs on NVIDIA, AMD, Intel, Apple Silicon, Vulkan, or CPU-only configurations
  • Built-in AI agents — Autonomous agents with tool use, RAG, MCP, and skills support
  • Multi-user ready — API key authentication, per-user quotas, and role-based access control

Use Cases

💡 Private AI infrastructure: Build fully localized AI inference platforms for enterprises with data staying on-premise
💡 Multimodal AI application development: Access LLMs, speech recognition, image generation through a unified API
💡 Multi-tenant AI platforms: Build user-facing AI services with API key and quota management
💡 Edge device deployment: Run AI models on GPU-less edge devices for industrial IoT and embedded scenarios

Categories

Quick Start

# One-click Docker start (CPU only)
docker run -ti --name local-ai -p 8080:8080 localai/localai:latest

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

# Load model and run
local-ai run llama-3.2-1b-instruct:q4_k_m

# Load from HuggingFace
local-ai run huggingface://TheBloke/phi-2-GGUF/phi-2.Q8_0.gguf

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