Run with container images

LocalAI provides a variety of images to support different environments. These images are available on quay.io and Docker Hub.

All-in-One images comes with a pre-configured set of models and backends, standard images instead do not have any model pre-configured and installed.

For GPU Acceleration support for Nvidia video graphic cards, use the Nvidia/CUDA images, if you don’t have a GPU, use the CPU images. If you have AMD or Mac Silicon, see the build section.

Prerequisites

Before you begin, ensure you have a container engine installed if you are not using the binaries. Suitable options include Docker or Podman. For installation instructions, refer to the following guides:

• Install Docker Desktop (Mac, Windows, Linux)
• Install Podman (Linux)
• Install Docker engine (Servers)

Standard container images

Standard container images do not have pre-installed models. Use these if you want to configure models manually.

All-in-one images

All-In-One images are images that come pre-configured with a set of models and backends to fully leverage almost all the LocalAI featureset. These images are available for both CPU and GPU environments. The AIO images are designed to be easy to use and require no configuration. Models configuration can be found here separated by size.

In the AIO images there are models configured with the names of OpenAI models, however, they are really backed by Open Source models. You can find the table below

Usage

Select the image (CPU or GPU) and start the container with Docker:

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

LocalAI will automatically download all the required models, and the API will be available at localhost:8080.

Or with a docker-compose file:

version: "3.9"
services:
  api:
    image: localai/localai:latest-aio-cpu
    # For a specific version:
    # image: localai/localai:v3.7.0-aio-cpu
    # For Nvidia GPUs decomment one of the following (cuda11 or cuda12):
    # image: localai/localai:v3.7.0-aio-gpu-nvidia-cuda-11
    # image: localai/localai:v3.7.0-aio-gpu-nvidia-cuda-12
    # image: localai/localai:latest-aio-gpu-nvidia-cuda-11
    # image: localai/localai:latest-aio-gpu-nvidia-cuda-12
    healthcheck:
      test: ["CMD", "curl", "-f", "http://localhost:8080/readyz"]
      interval: 1m
      timeout: 20m
      retries: 5
    ports:
      - 8080:8080
    environment:
      - DEBUG=true
      # ...
    volumes:
      - ./models:/models:cached
    # decomment the following piece if running with Nvidia GPUs
    # deploy:
    #   resources:
    #     reservations:
    #       devices:
    #         - driver: nvidia
    #           count: 1
    #           capabilities: [gpu]

docker run -p 8080:8080 --name local-ai -ti -v $PWD/models:/models localai/localai:latest-aio-cpu

docker volume create localai-models
docker run -p 8080:8080 --name local-ai -ti -v localai-models:/models localai/localai:latest-aio-cpu

Available AIO images

Available environment variables

The AIO Images are inheriting the same environment variables as the base images and the environment of LocalAI (that you can inspect by calling --help). However, it supports additional environment variables available only from the container image

See Also

• GPU acceleration