30d2c2f45b
- Drop image padding in GLMOCREndToEndService.recognize(); use raw image directly - Fix F821 undefined `padded` references replaced with `image` - Fix F601 duplicate dict key "≠" in converter - Fix F841 unused `image_cls_ids` variable in layout_postprocess - Fix E702 semicolon-separated statements in layout_postprocess - Fix UP031 percent-format replaced with f-string in logging_config - Auto-fix 44 additional ruff violations (import order, UP035/UP045/UP006, F401, F541) Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
73 lines
2.5 KiB
Python
73 lines
2.5 KiB
Python
"""Image OCR endpoint."""
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import time
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import uuid
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from fastapi import APIRouter, Depends, HTTPException, Request, Response
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from app.core.dependencies import (
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get_glmocr_endtoend_service,
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get_image_processor,
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)
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from app.core.logging_config import RequestIDAdapter, get_logger
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from app.schemas.image import ImageOCRRequest, ImageOCRResponse
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from app.services.image_processor import ImageProcessor
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from app.services.ocr_service import GLMOCREndToEndService
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router = APIRouter()
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logger = get_logger()
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@router.post("/ocr", response_model=ImageOCRResponse)
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async def process_image_ocr(
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request: ImageOCRRequest,
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http_request: Request,
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response: Response,
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image_processor: ImageProcessor = Depends(get_image_processor),
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glmocr_service: GLMOCREndToEndService = Depends(get_glmocr_endtoend_service),
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) -> ImageOCRResponse:
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"""Process an image and extract content as LaTeX, Markdown, and MathML.
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The processing pipeline:
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1. Load and preprocess image
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2. Detect layout regions using PP-DocLayoutV3
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3. Crop each region and recognize with GLM-OCR via vLLM (task-specific prompts)
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4. Aggregate region results into Markdown
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5. Convert to LaTeX, Markdown, and MathML formats
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Note: OMML conversion is not included due to performance overhead.
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Use the /convert/latex-to-omml endpoint to convert LaTeX to OMML separately.
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"""
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request_id = http_request.headers.get("x-request-id", str(uuid.uuid4()))
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response.headers["x-request-id"] = request_id
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log = RequestIDAdapter(logger, {"request_id": request_id})
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log.request_id = request_id
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try:
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log.info("Starting image OCR processing")
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start = time.time()
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image = image_processor.preprocess(
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image_url=request.image_url,
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image_base64=request.image_base64,
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)
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ocr_result = glmocr_service.recognize(image)
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log.info(f"OCR completed in {time.time() - start:.3f}s")
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except RuntimeError as e:
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log.error(f"OCR processing failed: {str(e)}", exc_info=True)
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raise HTTPException(status_code=503, detail=str(e))
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except Exception as e:
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log.error(f"Unexpected error during OCR processing: {str(e)}", exc_info=True)
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raise HTTPException(status_code=500, detail="Internal server error")
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return ImageOCRResponse(
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latex=ocr_result.get("latex", ""),
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markdown=ocr_result.get("markdown", ""),
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mathml=ocr_result.get("mathml", ""),
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mml=ocr_result.get("mml", ""),
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)
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