FROM python:3.11-slim

# Set working directory
WORKDIR /app

# Install system dependencies including CUDA-related packages
RUN apt-get update && apt-get install -y \
    ffmpeg \
    git \
    wget \
    curl \
    build-essential \
    && rm -rf /var/lib/apt/lists/*

# Copy requirements first for better Docker layer caching
COPY requirements.txt .

# Upgrade pip and install build tools
RUN pip install --upgrade pip setuptools wheel

# Install CUDA-optimized PyTorch FIRST (before other requirements)
# Using latest versions from cu118 index for SpeechBrain 1.0 / pyannote diarization compatibility
RUN pip install --no-cache-dir torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu118

# Install numpy first as many packages depend on it
RUN pip install --no-cache-dir "numpy>=1.24.0"

# Install remaining dependencies from requirements.txt
RUN pip install --no-cache-dir -r requirements.txt

# Copy application code
COPY . .

# Create directories for mounted volumes
RUN mkdir -p /app/data/videos /app/data/outputs /app/data/cache

# Set environment variables
ENV STREAMLIT_SERVER_PORT=8501
ENV STREAMLIT_SERVER_ADDRESS=0.0.0.0
ENV STREAMLIT_SERVER_HEADLESS=true
ENV STREAMLIT_BROWSER_GATHER_USAGE_STATS=false

# GPU-specific environment variables
ENV CUDA_VISIBLE_DEVICES=0
ENV NVIDIA_VISIBLE_DEVICES=all
ENV NVIDIA_DRIVER_CAPABILITIES=compute,utility

# Expose Streamlit port
EXPOSE 8501

# Health check
HEALTHCHECK --interval=30s --timeout=10s --start-period=60s --retries=3 \
    CMD curl -f http://localhost:8501/_stcore/health || exit 1

# Start the application
CMD ["streamlit", "run", "app.py", "--server.port=8501", "--server.address=0.0.0.0"]