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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>
21 lines
680 B
Python
21 lines
680 B
Python
"""OCR Service Configuration."""
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import os
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class Settings:
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"""Application settings loaded from environment variables."""
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def __init__(self) -> None:
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self.log_level: str = os.getenv("LOG_LEVEL", "info")
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self.host: str = os.getenv("HOST", "0.0.0.0")
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self.port: int = int(os.getenv("PORT", "8000"))
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self.tesseract_cmd: str = os.getenv("TESSERACT_CMD", "/usr/bin/tesseract")
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# Redis configuration for job queue
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self.redis_host: str = os.getenv("REDIS_HOST", "mvp-redis")
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self.redis_port: int = int(os.getenv("REDIS_PORT", "6379"))
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self.redis_db: int = int(os.getenv("REDIS_DB", "1"))
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settings = Settings()
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