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jan/docs/docs/guides/02-installation/05-docker.md
hieu-jan d518370e5c docs: add Jan installation using Docker
2024-02-09 21:00:39 +07:00

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Docker /install/docker Jan is a ChatGPT-alternative that runs on your own computer, with a local API server.
Jan AI
Jan
ChatGPT alternative
local AI
private AI
conversational AI
no-subscription fee
large language model
docker installation

Installing Jan using Docker

Installation

Pre-requisites

:::note

Supported OS: Linux, WSL2 Docker

:::

  • Docker Engine and Docker Compose are required to run Jan in Docker mode. Follow the instructions below to get started with Docker Engine on Ubuntu.
curl -fsSL https://get.docker.com -o get-docker.sh
sudo sh ./get-docker.sh --dry-run
  • If you intend to run Jan in GPU mode, you need to install nvidia-driver and nvidia-docker2. Follow the instruction here for installation.

Instructions

  • Run Jan in Docker mode

    • Option 1: Run Jan in CPU mode

      docker compose --profile cpu up -d

    • Option 2: Run Jan in GPU mode

      • Step 1: Check CUDA compatibility with your NVIDIA driver by running nvidia-smi and check the CUDA version in the output

        nvidia-smi

# Output
+---------------------------------------------------------------------------------------+
| NVIDIA-SMI 531.18                 Driver Version: 531.18       CUDA Version: 12.1     |
|-----------------------------------------+----------------------+----------------------+
| GPU  Name                      TCC/WDDM | Bus-Id        Disp.A | Volatile Uncorr. ECC |
| Fan  Temp  Perf            Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |
|                                         |                      |               MIG M. |
|=========================================+======================+======================|
|   0  NVIDIA GeForce RTX 4070 Ti    WDDM | 00000000:01:00.0  On |                  N/A |
|  0%   44C    P8               16W / 285W|   1481MiB / 12282MiB |      2%      Default |
|                                         |                      |                  N/A |
+-----------------------------------------+----------------------+----------------------+
|   1  NVIDIA GeForce GTX 1660 Ti    WDDM | 00000000:02:00.0 Off |                  N/A |
|  0%   49C    P8               14W / 120W|      0MiB /  6144MiB |      0%      Default |
|                                         |                      |                  N/A |
+-----------------------------------------+----------------------+----------------------+
|   2  NVIDIA GeForce GTX 1660 Ti    WDDM | 00000000:05:00.0 Off |                  N/A |
| 29%   38C    P8               11W / 120W|      0MiB /  6144MiB |      0%      Default |
|                                         |                      |                  N/A |
+-----------------------------------------+----------------------+----------------------+

+---------------------------------------------------------------------------------------+
| Processes:                                                                            |
|  GPU   GI   CI        PID   Type   Process name                            GPU Memory |
|        ID   ID                                                             Usage      |
|=======================================================================================|

      • Step 2: Visit NVIDIA NGC Catalog and find the smallest minor version of image tag that matches your CUDA version (e.g., 12.1 -> 12.1.0)

      • Step 3: Update the Dockerfile.gpu line number 5 with the latest minor version of the image tag from step 2 (e.g. change FROM nvidia/cuda:12.2.0-runtime-ubuntu22.04 AS base to FROM nvidia/cuda:12.1.0-runtime-ubuntu22.04 AS base)

      • Step 4: Run command to start Jan in GPU mode

        # GPU mode
docker compose --profile gpu up -d

    This will start the web server and you can access Jan at http://localhost:3000.

:::warning

  • Docker mode is currently only suitable for development and localhost. Production is not supported yet, and the RAG feature is not available in Docker mode.

:::