# AI Music Attribution - Full Stack Docker Image
# For deployment on HuggingFace Spaces (Docker SDK)
#
# Build: docker build -t aimusic .
# Run:   docker run -p 7860:3000 aimusic

FROM node:20-slim

# Install Python and system dependencies
RUN apt-get update && apt-get install -y \
    python3 \
    python3-pip \
    python3-venv \
    ffmpeg \
    libsndfile1 \
    libchromaprint-tools \
    && rm -rf /var/lib/apt/lists/*

# Create app directory
WORKDIR /app

# Create Python virtual environment
RUN python3 -m venv /app/venv
ENV PATH="/app/venv/bin:$PATH"
ENV PYTHON_PATH="/app/venv/bin/python3"

# Copy Python requirements first (for caching)
COPY ml/requirements.txt ml/requirements.txt
RUN pip install --no-cache-dir -r ml/requirements.txt

# Copy package files and patches
COPY package.json pnpm-lock.yaml ./
COPY patches/ patches/

# Install pnpm and Node dependencies
RUN npm install -g pnpm && pnpm install --frozen-lockfile

# Copy application code
COPY . .

# Build frontend
RUN pnpm build

# Create data directories
RUN mkdir -p data/mert_index data/uploads data/training_tracks data/fma_seeds data/test_ai_continuations

# Copy pre-computed embeddings (if available)
# These should be added to your Space's persistent storage
# COPY data/mert_index/embeddings.json data/mert_index/

# Expose port (HF Spaces expects 7860)
EXPOSE 7860

# Environment variables
ENV NODE_ENV=production
ENV PORT=7860
ENV HOST=0.0.0.0

# ML optimization: enable multi-threading and ONNX
ENV OMP_NUM_THREADS=8
ENV MKL_NUM_THREADS=8
ENV OPENBLAS_NUM_THREADS=8
ENV USE_ONNX=0

# Start the server
CMD ["pnpm", "start"]