Dockerfile

# Use the NVIDIA CUDA image as the base image
FROM nvidia/cuda:11.7.1-cudnn8-devel-ubuntu22.04

# Install dependencies
RUN apt-get update && apt-get install -y wget git

# Download and install Miniconda
RUN wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh && \
    bash Miniconda3-latest-Linux-x86_64.sh -b -p /opt/conda && \
    rm Miniconda3-latest-Linux-x86_64.sh

# Add conda to PATH
ENV PATH /opt/conda/bin:$PATH

# Clone the LLaVA Interactive Demo repository
RUN git clone https://github.com/LLaVA-VL/LLaVA-Interactive-Demo.git

# Create a conda environment for LLaVA Interactive Demo
RUN conda create -n llava_int -c conda-forge -c pytorch python=3.10.8 pytorch=2.0.1 -y

# Activate the conda environment
SHELL ["conda", "run", "-n", "llava_int", "/bin/bash", "-c"]

# Navigate to the LLaVA Interactive Demo directory
WORKDIR /LLaVA-Interactive-Demo

# Install Python dependencies
RUN pip install -r requirements.txt

# Run the setup script
RUN source setup.sh

# The command to run the demo (optional)
# If you want to run the demo as the default command when the container starts, you can use:
CMD ["./run_demo.sh"]