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OCR Service (Python/FastAPI):
- POST /extract for synchronous OCR extraction
- POST /jobs and GET /jobs/{job_id} for async processing
- Image preprocessing (deskew, denoise) for accuracy
- HEIC conversion via pillow-heif
- Redis job queue for async processing
Backend (Fastify):
- POST /api/ocr/extract - authenticated proxy to OCR
- POST /api/ocr/jobs - async job submission
- GET /api/ocr/jobs/:jobId - job polling
- Multipart file upload handling
- JWT authentication required
File size limits: 10MB sync, 200MB async
Processing time target: <3 seconds for typical photos
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
26 lines
359 B
Plaintext
26 lines
359 B
Plaintext
node_modules/
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.env
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.env.local
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.env.backup
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dist/
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*.log
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.DS_Store
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coverage/
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.vscode/
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.idea/
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*.swp
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*.swo
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.venv
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.playwright-mcp
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__pycache__/
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*.py[cod]
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*$py.class
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# K8s-aligned secret mounts (real files ignored; examples committed)
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secrets/**
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!secrets/
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!secrets/**/
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!secrets/**/*.example
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# Traefik ACME certificates (contains private keys)
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data/traefik/acme.json |