Update Dockerfile

Dockerfile

@@ -1,23 +1,31 @@
-# Use an official NVIDIA CUDA base image, which is great for PyTorch and GPU-heavy tasks
+# Use an official NVIDIA CUDA base image
 FROM pytorch/pytorch:2.1.0-cuda12.1-cudnn8-runtime
 
-# Set the working directory in the container
+# Set the working directory
 WORKDIR /code
 
-# Copy the requirements file into the container
+# [FIX] Install wget and other common utilities first
+# Running apt-get update before install is crucial
+RUN apt-get update && apt-get install -y wget git
+
+# [NEW] Now, run your command to install OpenVSCode Server
+RUN wget https://github.com/gitpod-io/openvscode-server/releases/download/openvscode-server-v1.86.2/openvscode-server-v1.86.2-linux-x64.tar.gz -O /tmp/openvscode-server.tar.gz && \
+    tar -xzf /tmp/openvscode-server.tar.gz -C /opt && \
+    rm /tmp/openvscode-server.tar.gz && \
+    mv /opt/openvscode-server-v1.86.2-linux-x64 /opt/openvscode-server && \
+    chown -R 1000:1000 /opt/openvscode-server
+
+# Copy the requirements file
 COPY ./requirements.txt /code/requirements.txt
 
-# Install dependencies from requirements.txt
-# --no-cache-dir ensures a smaller image size
-# --upgrade ensures we get the latest specified versions
+# Install Python dependencies
 RUN pip install --no-cache-dir --upgrade -r /code/requirements.txt
 
-# Copy all your application files (app.py, train.py, and your CSVs) into the container
+# Copy your application files
 COPY . /code/
 
-# Tell the container to expose port 7860, which is the default for Gradio
+# Expose the default Gradio port
 EXPOSE 7860
 
-# The command to run when the container starts.
-# This will launch your Gradio app.
+# The command to run when the container starts
 CMD ["python", "app.py"]