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docs/docs/guides/02-installation/05-docker.md
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@ -13,13 +13,13 @@ keywords:
no-subscription fee,
large language model,
docker installation,
cpu mode,
gpu mode,
]
---
# Installing Jan using Docker
## Installation
### Pre-requisites
:::note
@ -37,66 +37,87 @@ 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](https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/latest/install-guide.html) for installation.
### Instructions
### Run Jan in Docker Mode
- Run Jan in Docker mode
| Docker compose Profile | Description |
| ---------------------- | -------------------------------------------- |
| `cpu-fs` | Run Jan in CPU mode with default file system |
| `cpu-s3fs` | Run Jan in CPU mode with S3 file system |
| `gpu-fs` | Run Jan in GPU mode with default file system |
| `gpu-s3fs` | Run Jan in GPU mode with S3 file system |
- **Option 1**: Run Jan in CPU mode
| Environment Variable | Description |
| ----------------------- | ------------------------------------------------------------------------------------------------------- |
| `S3_BUCKET_NAME` | S3 bucket name - leave blank for default file system |
| `AWS_ACCESS_KEY_ID` | AWS access key ID - leave blank for default file system |
| `AWS_SECRET_ACCESS_KEY` | AWS secret access key - leave blank for default file system |
| `AWS_ENDPOINT` | AWS endpoint URL - leave blank for default file system |
| `AWS_REGION` | AWS region - leave blank for default file system |
| `API_BASE_URL` | Jan Server URL, please modify it as your public ip address or domain name default http://localhost:1377 |
- **Option 1**: Run Jan in CPU mode
```bash
# cpu mode with default file system
docker compose --profile cpu-fs up -d
# cpu mode with S3 file system
docker compose --profile cpu-s3fs 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
```bash
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 ](https://catalog.ngc.nvidia.com/orgs/nvidia/containers/cuda/tags) 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
```bash
docker compose --profile cpu up -d
# GPU mode with default file system
docker compose --profile gpu up -d
# GPU mode with S3 file system
docker compose --profile gpu-s3fs 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
```bash
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 ](https://catalog.ngc.nvidia.com/orgs/nvidia/containers/cuda/tags) 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
```bash
# GPU mode
docker compose --profile gpu up -d
```
This will start the web server and you can access Jan at `http://localhost:3000`.
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.
- RAG feature is not supported in Docker mode with s3fs yet.
:::