# Use Python 3.10 slim image
FROM python:3.10-slim

# Set environment variables
ENV PYTHONDONTWRITEBYTECODE=1 \
    PYTHONUNBUFFERED=1 \
    HF_HOME=/app/.cache \
    TRANSFORMERS_VERBOSITY=error

# Set working directory and create necessary folders
WORKDIR /app
RUN mkdir -p /app/.cache /app/models/suno-bark /app/models/sentiment && \
    chmod -R 777 /app/.cache /app/models

# Install OS dependencies
RUN apt-get update && apt-get install -y --no-install-recommends \
    libsndfile1 ffmpeg ca-certificates && \
    rm -rf /var/lib/apt/lists/*

# Copy requirements and install Python dependencies
COPY requirements.txt .
RUN pip install --no-cache-dir --root-user-action=ignore -U pip && \
    pip install --no-cache-dir --root-user-action=ignore \
        "numpy<2" \
        "protobuf" && \
    pip install --no-cache-dir --root-user-action=ignore -r requirements.txt

# Install soundfile
RUN pip install soundfile

# Download Bark TTS model using snapshot_download
RUN python3 -c "\
from huggingface_hub import snapshot_download; \
snapshot_download(repo_id='suno/bark-small', local_dir='/app/models/suno-bark', local_dir_use_symlinks=False)"

# Download sentiment analysis model using snapshot_download
RUN python3 -c "\
from huggingface_hub import snapshot_download; \
snapshot_download(repo_id='cardiffnlp/twitter-xlm-roberta-base-sentiment', local_dir='/app/models/sentiment', local_dir_use_symlinks=False)"

# Copy application source code
COPY app.py .

# Expose port for the application
EXPOSE 7860

# Launch app using Uvicorn
CMD ["uvicorn", "app:app", "--host", "0.0.0.0", "--port", "7860"]