Update Dockerfile

Dockerfile

@@ -6,13 +6,24 @@ WORKDIR /app
 # Install necessary dependencies
 RUN apt-get update && apt-get install -y busybox wget curl && rm -rf /var/lib/apt/lists/*
 
+# Create cache directories with proper permissions BEFORE installing packages
+RUN mkdir -p /app/cache/huggingface /app/cache/transformers /app/cache/datasets
+RUN chmod -R 777 /app/cache
+
+# Set Hugging Face environment variables
+ENV HF_HOME=/app/cache/huggingface
+ENV TRANSFORMERS_CACHE=/app/cache/transformers
+ENV HF_DATASETS_CACHE=/app/cache/datasets
+ENV HUGGINGFACE_HUB_CACHE=/app/cache/huggingface
+ENV HF_HUB_CACHE=/app/cache/huggingface
+
 # Install Python dependencies
 RUN pip install --no-cache-dir \
-    torch==2.0.1+cpu -f https://download.pytorch.org/whl/cpu/torch_stable.html 
+    torch==2.0.1+cpu -f https://download.pytorch.org/whl/cpu/torch_stable.html
 
 RUN pip install --no-cache-dir \
     pandas "numpy<2" matplotlib scikit-learn tqdm scipy networkx \
-    torch-geometric requests schedule fastapi uvicorn jinja2 python-multipart gradio datasets 
+    torch-geometric requests schedule fastapi uvicorn jinja2 python-multipart gradio datasets
 
 # Create necessary directories with correct permissions
 RUN mkdir -p /app/logs /app/models /app/scripts /app/data /app/templates
@@ -30,5 +41,4 @@ COPY app.py /app/app.py
 RUN chmod +x /app/train.py /app/scheduler.py
 
 # Run both FastAPI server and the training scheduler in parallel
-CMD ["sh", "-c", "python scheduler.py && python app.py"]
-
+CMD ["sh", "-c", "python scheduler.py && python app.py"]