LocalAI/docs/content/overview.md

+++ title = "Overview" weight = 1 toc = true description = "What is LocalAI?" tags = ["Beginners"] categories = [""] url = "/docs/overview" author = "Ettore Di Giacinto" icon = "info" +++

LocalAI is your complete AI stack for running AI models locally. It's designed to be simple, efficient, and accessible, providing a drop-in replacement for OpenAI's API while keeping your data private and secure.

Why LocalAI?

In today's AI landscape, privacy, control, and flexibility are paramount. LocalAI addresses these needs by:

• Privacy First: Your data never leaves your machine
• Complete Control: Run models on your terms, with your hardware
• Open Source: MIT licensed and community-driven
• Flexible Deployment: From laptops to servers, with or without GPUs
• Extensible: Add new models and features as needed

What's Included

LocalAI is a single binary (or container) that gives you everything you need:

• OpenAI-compatible API — Drop-in replacement for OpenAI, Anthropic, and Open Responses APIs
• Built-in Web Interface — Chat, model management, agent creation, image generation, and system monitoring
• AI Agents — Create autonomous agents with MCP (Model Context Protocol) tool support, directly from the UI
• Multiple Model Support — LLMs, image generation, text-to-speech, speech-to-text, vision, embeddings, and more
• GPU Acceleration — Automatic detection and support for NVIDIA, AMD, Intel, and Vulkan GPUs
• Distributed Mode — Scale horizontally with worker nodes, P2P federation, and model sharding
• No GPU Required — Runs on CPU with consumer-grade hardware

LocalAI integrates LocalAGI (agent platform) and LocalRecall (semantic memory) as built-in libraries — no separate installation needed.

Getting Started

LocalAI can be installed in several ways. Docker is the recommended installation method for most users as it provides the easiest setup and works across all platforms.

Recommended: Docker Installation

The quickest way to get started with LocalAI is using Docker:

docker run -p 8080:8080 --name local-ai -ti localai/localai:latest-cpu

Then open http://localhost:8080 to access the web interface, install models, and start chatting.

For GPU support, see the [Container images reference]({{% relref "getting-started/container-images" %}}) or the [Quickstart guide]({{% relref "getting-started/quickstart" %}}).

For complete installation instructions including Docker, macOS, Linux, Kubernetes, and building from source, see the Installation guide.

Key Features

• Text Generation: Run various LLMs locally (llama.cpp, transformers, vLLM, and more)
• Image Generation: Create images with Stable Diffusion, Flux, and other models
• Audio Processing: Text-to-speech and speech-to-text
• Vision API: Image understanding and analysis
• Embeddings: Vector representations for search and retrieval
• Function Calling: OpenAI-compatible tool use
• AI Agents: Autonomous agents with MCP tool support
• MCP Apps: Interactive tool UIs in the web interface
• P2P & Distributed: Federated inference and model sharding across machines

Community and Support

LocalAI is a community-driven project. You can:

• Join our Discord community
• Check out our GitHub repository
• Contribute to the project
• Share your use cases and examples

Next Steps

Ready to dive in? Here are some recommended next steps:

1. Install LocalAI - Start with Docker installation (recommended) or choose another method
2. [Quickstart guide]({{% relref "getting-started/quickstart" %}}) - Get up and running in minutes
3. Explore available models
4. Model compatibility
5. [Try out examples]({{% relref "getting-started/try-it-out" %}})
6. Join the community

License

LocalAI is MIT licensed, created and maintained by Ettore Di Giacinto.