Update docs run Jan Server in Docker mode (#1960)

Co-authored-by: Hien To <tominhhien97@gmail.com>

Dockerfile.gpu

@@ -1,10 +1,22 @@
-FROM nvidia/cuda:12.0.0-devel-ubuntu22.04 AS base
+# Please change the base image to the appropriate CUDA version base on NVIDIA Driver Compatibility
+# Run nvidia-smi to check the CUDA version and the corresponding driver version
+# Then update the base image to the appropriate CUDA version refer https://catalog.ngc.nvidia.com/orgs/nvidia/containers/cuda/tags
+
+FROM nvidia/cuda:12.2.2-runtime-ubuntu22.04 AS base 
 
 # 1. Install dependencies only when needed
 FROM base AS builder
 
 # Install g++ 11
-RUN apt update && apt install -y gcc-11 g++-11 cpp-11 jq xsel curl gnupg && curl -sL https://deb.nodesource.com/setup_20.x | bash - && apt install nodejs -y && rm -rf /var/lib/apt/lists/*
+RUN apt update && apt install -y gcc-11 g++-11 cpp-11 jq xsel curl gnupg make python3-dev && curl -sL https://deb.nodesource.com/setup_20.x | bash - && apt install nodejs -y && rm -rf /var/lib/apt/lists/*
+
+# Update alternatives for GCC and related tools
+RUN update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-11 110 \
+                         --slave /usr/bin/g++ g++ /usr/bin/g++-11 \
+                         --slave /usr/bin/gcov gcov /usr/bin/gcov-11 \
+                         --slave /usr/bin/gcc-ar gcc-ar /usr/bin/gcc-ar-11 \
+                         --slave /usr/bin/gcc-ranlib gcc-ranlib /usr/bin/gcc-ranlib-11 && \
+    update-alternatives --install /usr/bin/cpp cpp /usr/bin/cpp-11 110
 
 RUN npm install -g yarn
 
@@ -24,7 +36,15 @@ RUN export NODE_ENV=production && yarn workspace jan-web build
 FROM base AS runner
 
 # Install g++ 11
-RUN apt update && apt install -y gcc-11 g++-11 cpp-11 jq xsel curl gnupg && curl -sL https://deb.nodesource.com/setup_20.x | bash - && apt-get install nodejs -y && rm -rf /var/lib/apt/lists/*
+RUN apt update && apt install -y gcc-11 g++-11 cpp-11 jq xsel curl gnupg make python3-dev && curl -sL https://deb.nodesource.com/setup_20.x | bash - && apt-get install nodejs -y && rm -rf /var/lib/apt/lists/*
+
+# Update alternatives for GCC and related tools
+RUN update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-11 110 \
+                         --slave /usr/bin/g++ g++ /usr/bin/g++-11 \
+                         --slave /usr/bin/gcov gcov /usr/bin/gcov-11 \
+                         --slave /usr/bin/gcc-ar gcc-ar /usr/bin/gcc-ar-11 \
+                         --slave /usr/bin/gcc-ranlib gcc-ranlib /usr/bin/gcc-ranlib-11 && \
+    update-alternatives --install /usr/bin/cpp cpp /usr/bin/cpp-11 110
 
 RUN npm install -g yarn
 

README.md

@@ -229,18 +229,62 @@ This will build the app MacOS m1/m2 for production (with code signing already do
     sudo sh ./get-docker.sh --dry-run
     ```
 
-  - `nvidia docker`, follow instruction [here](https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/latest/install-guide.html) (If you want to run with GPU mode)
+  - `nvidia-driver` and `nvidia-docker2`, follow instruction [here](https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/latest/install-guide.html) (If you want to run with GPU mode)
 
 - Run Jan in Docker mode
 
-    ```bash
+  - **Option 1**: Run Jan in CPU mode
-    # CPU mode
-    docker compose --profile cpu up
 
-    # GPU mode
+    ```bash
-    docker compose --profile gpu up
+    docker compose --profile cpu up
     ```
 
+  - **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**: Go to https://catalog.ngc.nvidia.com/orgs/nvidia/containers/cuda/tags and find the lates minor version of image tag that matches the cuda version from the output of `nvidia-smi` (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:12.2.2-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
+      ```
+
   This will start the web server and you can access Jan at `http://localhost:3000`.
 
 ## Acknowledgements