# Deep Dive Intelligence Pipeline — Production Container
# Issue: #830 — Sovereign NotebookLM Daily Briefing
#
# Build:
#   docker build -t deepdive:latest .
# Run dry-run:
#   docker run --rm -v $(pwd)/config.yaml:/app/config.yaml deepdive:latest --dry-run

FROM python:3.11-slim

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

WORKDIR /app

# Install Python dependencies first (layer caching)
COPY requirements.txt .
RUN pip install --no-cache-dir -r requirements.txt

# Pre-download embedding model for faster cold starts
RUN python3 -c "from sentence_transformers import SentenceTransformer; SentenceTransformer('all-MiniLM-L6-v2')"

# Copy application code
COPY pipeline.py tts_engine.py fleet_context.py telegram_command.py quality_eval.py ./
COPY prompts/ ./prompts/
COPY tests/ ./tests/
COPY Makefile README.md QUICKSTART.md OPERATIONAL_READINESS.md ./

# Create cache and output directories
RUN mkdir -p /app/cache /app/output
ENV DEEPDIVE_CACHE_DIR=/app/cache
ENV PYTHONUNBUFFERED=1

# Default: run pipeline with mounted config
ENTRYPOINT ["python3", "pipeline.py", "--config", "/app/config.yaml"]
CMD ["--dry-run"]