# Use the official Python 3.9 slim image
FROM python:3.9-slim AS base

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

# Create a non-root user
RUN useradd --create-home --shell /bin/bash appuser

# Set working directory
WORKDIR /app

# Copy requirements file
COPY requirements.txt .  

# Install dependencies and create virtual environment
RUN apt-get update && apt-get install -y curl && rm -rf /var/lib/apt/lists/*

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 Hugging Face cache directory exists and assign proper permissions
RUN mkdir -p $HF_HOME && \
    chown -R appuser:appuser $HF_HOME && \
    chmod -R 777 $HF_HOME

# Copy application files
COPY main.py .  

# Set up Hugging Face token as a build argument (secured via environment variables)
ARG HF_TOKEN
ENV HF_TOKEN=${HF_TOKEN}

# Pre-download models as the new user
USER appuser

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 English model'

# Expose FastAPI port
EXPOSE 7860

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