No GPU support while running llama-cpp-python inside a docker container

I'm trying to run llama index with llama cpp by following the installation docs but inside a docker container.

Following this repo for installation of llama_cpp_python==0.2.6.

DOCKERFILE

# Use the official Python image for Python 3.11
FROM python:3.11

# Set the working directory in the container
WORKDIR /app

# Copy the current directory contents into the container at /app
COPY . /app

# ARG FORCE_CMAKE=1

# ARG CMAKE_ARGS="-DLLAMA_CUBLAS=on"


# Install project dependencies

 RUN FORCE_CMAKE=1 CMAKE_ARGS="-DLLAMA_CUBLAS=on" python -m pip install -r requirements.txt

# Command to run the server
CMD ["python", "./server.py"]

Run cmd:
docker build -t llm_server ./llm
docker run -it -p 2023:2023 --gpus all llm_server

Problem: For some reason, the env variables in the llama cpp docs do not work as expected in a docker container.

Current behaviour: BLAS= 0 (llm using CPU) llm initialization

Expected behaviour: BLAS= 1 (llm using GPU)

nvidia-smi output inside container:

# nvidia-smi
Thu Nov 23 05:48:30 2023       
+---------------------------------------------------------------------------------------+
| NVIDIA-SMI 545.29.01              Driver Version: 546.01       CUDA Version: 12.3     |
|-----------------------------------------+----------------------+----------------------+
| GPU  Name                 Persistence-M | Bus-Id        Disp.A | Volatile Uncorr. ECC |
| Fan  Temp   Perf          Pwr:Usage/Cap |         Memory-Usage | GPU-Util  Compute M. |
|                                         |                      |               MIG M. |
|=========================================+======================+======================|
|   0  NVIDIA GeForce GTX 1660 Ti     On  | 00000000:01:00.0  On |                  N/A |
| N/A   48C    P8               4W /  80W |   1257MiB /  6144MiB |      7%      Default |
|                                         |                      |                  N/A |
+-----------------------------------------+----------------------+----------------------+
                                                                                         
+---------------------------------------------------------------------------------------+
| Processes:                                                                            |
|  GPU   GI   CI        PID   Type   Process name                            GPU Memory |
|        ID   ID                                                             Usage      |
|=======================================================================================|
|    0   N/A  N/A        20      G   /Xwayland                                 N/A      |
|    0   N/A  N/A        20      G   /Xwayland                                 N/A      |
|    0   N/A  N/A       392      G   /Xwayland                                 N/A      |
+---------------------------------------------------------------------------------------+
#

• Tried setting the env variables in the following ways inside dockerfile.

# ARG FORCE_CMAKE=1

# ARG CMAKE_ARGS="-DLLAMA_CUBLAS=on"
# ENV FORCE_CMAKE=1

# ENV CMAKE_ARGS="-DLLAMA_CUBLAS=on"

# Install project dependencies

 RUN FORCE_CMAKE=1 CMAKE_ARGS="-DLLAMA_CUBLAS=on" python -m pip install -r requirements.txt```

• Tried re-installing llama-cpp-python again inside a running container using env variables.

CMAKE_ARGS="-DLLAMA_CUBLAS=on" pip install llama-cpp-python

Update: This docker file works thanks to the person who answered.

FROM nvidia/cuda:11.7.1-devel-ubuntu22.04

# Set the working directory in the container
WORKDIR /app

# Copy the current directory contents into the container at /app
COPY . /app

# Install Python and pip
RUN apt-get update && apt-get install -y python3 python3-pip

# Set environment variable
ENV CMAKE_ARGS="-DLLAMA_CUBLAS=ON"

# Install Python dependencies
RUN pip install --no-cache-dir --upgrade pip && \
    pip install -r requirements.txt --no-cache-dir

# Command to run the server
CMD ["python3", "./server.py"]