Dockerfile

# Use a stable Python base image
FROM python:3.9-slim

# Set environment variables
ENV PYTHONUNBUFFERED=1 \
    LANG=C.UTF-8 \
    HF_HOME="/app/huggingface_cache" \
    HUGGINGFACE_HUB_CACHE="/app/huggingface_cache"

# Set working directory
WORKDIR /app

# Copy the required files
COPY requirements.txt .  
COPY main.py .  

# Install dependencies using a virtual environment
RUN python -m venv /app/venv && \
    /app/venv/bin/pip install --no-cache-dir --upgrade pip && \
    /app/venv/bin/pip install --no-cache-dir -r requirements.txt

# Ensure the model cache directory exists
RUN mkdir -p $HF_HOME

# Add Hugging Face token as an environment variable in the container (this will be injected by Hugging Face Spaces' secrets management)
ARG HF_TOKEN
ENV HF_TOKEN=${HF_TOKEN}

# Pre-download models (handle errors gracefully)
RUN /app/venv/bin/python -c "from transformers import pipeline; \
    pipeline('sentiment-analysis', model='tabularisai/multilingual-sentiment-analysis', use_auth_token='$HF_TOKEN')" || echo 'Failed to download model 1'

RUN /app/venv/bin/python -c "from transformers import pipeline; \
    pipeline('sentiment-analysis', model='siebert/sentiment-roberta-large-english', use_auth_token='$HF_TOKEN')" || echo 'Failed to download model 2'

# Expose port for FastAPI
EXPOSE 7860

# Run FastAPI server using virtual environment
CMD ["/app/venv/bin/uvicorn", "main:app", "--host", "0.0.0.0", "--port", "7860"]