Update Dockerfile

Dockerfile

@@ -9,19 +9,19 @@ RUN apt-get update && apt-get install -y \
     git \
     && rm -rf /var/lib/apt/lists/*
 
-# Set environment variables
+# Set environment variables for cache
 ENV TRANSFORMERS_CACHE=/app/hf_cache
 ENV HF_HOME=/app/hf_cache
 ENV HF_DATASETS_CACHE=/app/hf_cache
 
-# Install Python dependencies
+# Copy dependency list and install Python packages
 COPY requirements.txt ./
 RUN pip install --no-cache-dir -r requirements.txt
 
-# Pre-download the model and tokenizer
+# Pre-download the Hugging Face model and tokenizer
 RUN python -c "from transformers import AutoTokenizer, AutoModelForSequenceClassification; \
-               AutoTokenizer.from_pretrained('finiteautomata/bertweet-base-sentiment-analysis'); \
-               AutoModelForSequenceClassification.from_pretrained('finiteautomata/bertweet-base-sentiment-analysis')"
+    AutoTokenizer.from_pretrained('finiteautomata/bertweet-base-sentiment-analysis', cache_dir='/app/hf_cache'); \
+    AutoModelForSequenceClassification.from_pretrained('finiteautomata/bertweet-base-sentiment-analysis', cache_dir='/app/hf_cache')"
 
 # Copy app code
 COPY app.py ./
@@ -29,8 +29,9 @@ COPY app.py ./
 # Expose Streamlit port
 EXPOSE 8501
 
-# Healthcheck to make Hugging Face know it's alive
+# Healthcheck (optional)
 HEALTHCHECK CMD curl --fail http://localhost:8501/_stcore/health || exit 1
 
 # Start Streamlit
 ENTRYPOINT ["streamlit", "run", "app.py", "--server.port=8501", "--server.address=0.0.0.0"]
+