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- Add Dockerfile for production containerized pipeline - Add docker-compose.yml for full stack deployment - Add .dockerignore for clean builds - Add deploy.sh: one-command build, test, and systemd timer install This provides a sovereign, reproducible deployment path for the Deep Dive daily briefing pipeline.
43 lines
1.3 KiB
Docker
43 lines
1.3 KiB
Docker
# Deep Dive Intelligence Pipeline — Production Container
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# Issue: #830 — Sovereign NotebookLM Daily Briefing
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#
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# Build:
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# docker build -t deepdive:latest .
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# Run dry-run:
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# docker run --rm -v $(pwd)/config.yaml:/app/config.yaml deepdive:latest --dry-run
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FROM python:3.11-slim
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# Install system dependencies
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RUN apt-get update && apt-get install -y --no-install-recommends \
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ffmpeg \
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wget \
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curl \
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ca-certificates \
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git \
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&& rm -rf /var/lib/apt/lists/*
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WORKDIR /app
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# Install Python dependencies first (layer caching)
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COPY requirements.txt .
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RUN pip install --no-cache-dir -r requirements.txt
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# Pre-download embedding model for faster cold starts
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RUN python3 -c "from sentence_transformers import SentenceTransformer; SentenceTransformer('all-MiniLM-L6-v2')"
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# Copy application code
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COPY pipeline.py tts_engine.py fleet_context.py telegram_command.py quality_eval.py ./
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COPY prompts/ ./prompts/
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COPY tests/ ./tests/
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COPY Makefile README.md QUICKSTART.md OPERATIONAL_READINESS.md ./
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# Create cache and output directories
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RUN mkdir -p /app/cache /app/output
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ENV DEEPDIVE_CACHE_DIR=/app/cache
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ENV PYTHONUNBUFFERED=1
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# Default: run pipeline with mounted config
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ENTRYPOINT ["python3", "pipeline.py", "--config", "/app/config.yaml"]
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CMD ["--dry-run"]
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