Update Dockerfile

Dockerfile

@@ -1,52 +1,4 @@
-# # Use a Python base image
-# FROM  nvidia/cuda:12.4.1-runtime-ubuntu22.04
 
-# # Set the working directory
-# WORKDIR /DocQA
-# # Install dependencies
-# RUN apt-get update && apt-get install -y \
-#     git \
-#     python3.10 \
-#     python3-pip \
-#     && apt-get clean
-
-
-# RUN apt-get install poppler-utils -y
-
-
-# RUN pip3 install torch torchvision torchaudio --extra-index-url https://download.pytorch.org/whl/cu113
-# RUN useradd -m -u 1000 user
-
-# USER user
-
-# ENV HOME=/home/user \
-# 	PATH=/home/user/.local/bin:$PATH
-
-# WORKDIR $HOME/app
-# # Copy the requirements.txt file
-# COPY --chown=user requirements.txt $HOME/app
-
-# RUN pip install --no-cache-dir -r requirements.txt 
-
-# # Copy the rest of the application codeDocQA
-# COPY --chown=user images $HOME/app
-# COPY --chown=user app.py $HOME/app
-# COPY --chown=user ./classification.py $HOME/app
-# COPY --chown=user donut_inference.py $HOME/app
-# COPY --chown=user non_form_llama_parse.py $HOME/app
-# COPY --chown=user RAG.py $HOME/app
-# COPY --chown=user best_resnet152_model.h5 $HOME/app
-# COPY --chown=user Model $HOME/app
-
-# # Expose the port the app runs on
-# # EXPOSE 7860
-# EXPOSE 8501
-
-
-# # Start the application
-# # CMD ["streamlit", "run", "app.py"]
-# ENTRYPOINT ["streamlit", "run","app.py" ,"--server.enableXsrfProtection", "false"]
-# Use a base image from NVIDIA that includes CUDA and cuDNN
 FROM nvidia/cuda:12.4.1-runtime-ubuntu22.04
 
 # Set the working directory in the container
@@ -77,7 +29,7 @@ WORKDIR $HOME/app
 # Copy the requirements.txt first to leverage Docker cache
 COPY --chown=user requirements.txt $HOME/app/
 RUN pip install --no-cache-dir -r requirements.txt
-RUN pip install torch torchvision torchaudio --extra-index-url https://download.pytorch.org/whl/cu113
+# RUN pip install torch torchvision torchaudio --extra-index-url https://download.pytorch.org/whl/cu113
 
 # Copy the rest of the application's code to the container
 COPY --chown=user . $HOME/app