Dockerfile

# Dockerfile for Hugging Face Spaces with FastAPI + Gradio

# Use an official Python runtime as a parent image
FROM python:3.9-slim

# Set the working directory inside the container
WORKDIR /app

# Install system dependencies
RUN apt-get update && apt-get install -y \
    gcc \
    g++ \
    curl \
    && rm -rf /var/lib/apt/lists/*

# Copy the requirements file and install dependencies first for better caching
COPY requirements.txt .
RUN pip install --no-cache-dir -r requirements.txt

# Copy all your application code into the container
COPY . .

# IMPORTANT: Download and cache the models during the build process.
# This makes the application start much faster when the Space wakes up.
RUN python -c "from classifier import classify_with_model; classify_with_model('test')"
RUN python -c "from ner import get_ner_pipeline; get_ner_pipeline()"
RUN python -c "from sentiment import get_emotion_classifier; get_emotion_classifier()"
RUN python -c "from translate import get_translator; get_translator()"

# Create startup script
RUN echo '#!/bin/bash\n\
echo "🚀 Starting FastAPI server on port 8000..."\n\
python -m uvicorn api:app --host 0.0.0.0 --port 8000 &\n\
echo "🌊 Starting Gradio web interface on port 7860..."\n\
python app.py' > start_services.sh

RUN chmod +x start_services.sh

# Expose ports for both services
EXPOSE 7860  # Gradio web interface
EXPOSE 8000  # FastAPI

# Health check
HEALTHCHECK --interval=30s --timeout=10s --start-period=60s --retries=3 \
  CMD curl -f http://localhost:8000/health || exit 1

# Start both services
CMD ["./start_services.sh"]