9b6417379b
- Replace libtesseract-dev with libgomp1 (OpenMP for PaddlePaddle) - Pre-download PP-OCRv4 models during Docker build - Add OCR engine env vars to all compose files (base, staging, prod) - Add optional Google Vision secret mount (commented, enable on demand) - Create google-vision-key.json.example placeholder Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
46 lines
1.6 KiB
Docker
46 lines
1.6 KiB
Docker
# Production Dockerfile for MotoVaultPro OCR Service
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# Uses mirrored base images from Gitea Package Registry
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#
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# Primary engine: PaddleOCR PP-OCRv4 (models baked into image)
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# Backward compat: Tesseract 5.x (optional, via TesseractEngine)
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# Cloud fallback: Google Vision (optional, requires API key at runtime)
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# Build argument for registry (defaults to Gitea mirrors, falls back to Docker Hub)
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ARG REGISTRY_MIRRORS=git.motovaultpro.com/egullickson/mirrors
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FROM ${REGISTRY_MIRRORS}/python:3.13-slim
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# System dependencies
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# - tesseract-ocr/eng: Backward-compatible OCR engine (used by TesseractEngine)
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# - libgomp1: OpenMP runtime required by PaddlePaddle
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# - libheif1/libheif-dev: HEIF image support (iPhone photos)
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# - libglib2.0-0: GLib shared library (OpenCV dependency)
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# - libmagic1: File type detection
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# - curl: Health check endpoint
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RUN apt-get update && apt-get install -y --no-install-recommends \
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tesseract-ocr \
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tesseract-ocr-eng \
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libgomp1 \
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libheif1 \
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libheif-dev \
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libglib2.0-0 \
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libmagic1 \
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curl \
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&& rm -rf /var/lib/apt/lists/*
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# Python dependencies
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WORKDIR /app
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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 PaddleOCR PP-OCRv4 models during build (not at runtime).
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# Models are baked into the image so container starts are fast and
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# no network access is needed at runtime for model download.
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RUN python -c "from paddleocr import PaddleOCR; PaddleOCR(use_angle_cls=True, lang='en', use_gpu=False, show_log=False)" \
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&& echo "PaddleOCR PP-OCRv4 models downloaded and verified"
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COPY . .
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EXPOSE 8000
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CMD ["uvicorn", "app.main:app", "--host", "0.0.0.0", "--port", "8000"]
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