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familienarchiv/ocr-service/main.py
Marcel 4500c99e40
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fix(ocr): use presigned URLs for MinIO access from OCR service
The OCR service was getting 403 Forbidden because it tried to
download PDFs from MinIO using plain internal URLs without
authentication. MinIO buckets are private.

- Add S3Presigner bean to MinioConfig
- FileService.generatePresignedUrl(): generates 15-min presigned URLs
- OcrService uses presigned URLs instead of plain internal URLs
- Remove unused s3InternalUrl / bucketName @Value fields from OcrService

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-04-12 22:16:52 +02:00

101 lines
3.1 KiB
Python

"""OCR microservice — FastAPI app with Surya and Kraken engine support."""
import io
import logging
from contextlib import asynccontextmanager
import httpx
import pypdfium2 as pdfium
from fastapi import FastAPI, HTTPException
from PIL import Image
from confidence import apply_confidence_markers, get_threshold
from engines import kraken as kraken_engine
from engines import surya as surya_engine
from models import OcrBlock, OcrRequest
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)
_models_ready = False
@asynccontextmanager
async def lifespan(app: FastAPI):
"""Load all OCR models at startup before accepting requests."""
global _models_ready
logger.info("Loading OCR models at startup...")
surya_engine.load_models()
kraken_engine.load_models()
_models_ready = True
logger.info("All OCR models loaded — ready to accept requests")
yield
logger.info("Shutting down OCR service")
app = FastAPI(title="Familienarchiv OCR Service", lifespan=lifespan)
@app.get("/health")
def health():
"""Health endpoint — returns 200 only after models are loaded."""
if not _models_ready:
raise HTTPException(status_code=503, detail="Models not loaded yet")
return {"status": "ok", "surya": True, "kraken": kraken_engine.is_available()}
@app.post("/ocr", response_model=list[OcrBlock])
async def run_ocr(request: OcrRequest):
"""Run OCR on a PDF document.
Downloads the PDF from the provided URL, converts pages to images,
and runs the appropriate OCR engine based on scriptType.
"""
if not _models_ready:
raise HTTPException(status_code=503, detail="Models not loaded yet")
images = await _download_and_convert_pdf(request.pdf_url)
script_type = request.script_type.upper()
if script_type == "HANDWRITING_KURRENT":
if not kraken_engine.is_available():
raise HTTPException(
status_code=400,
detail="Kraken model not available — cannot process Kurrent script",
)
blocks = kraken_engine.extract_blocks(images, request.language)
else:
# TYPEWRITER, HANDWRITING_LATIN, UNKNOWN — all use Surya
blocks = surya_engine.extract_blocks(images, request.language)
threshold = get_threshold(script_type)
for block in blocks:
if block.get("words"):
block["text"] = apply_confidence_markers(block["words"], threshold)
block.pop("words", None)
return [OcrBlock(**b) for b in blocks]
async def _download_and_convert_pdf(url: str) -> list[Image.Image]:
"""Download a PDF from a presigned URL and convert each page to a PIL Image."""
async with httpx.AsyncClient(timeout=httpx.Timeout(300.0)) as client:
response = await client.get(url)
response.raise_for_status()
pdf = pdfium.PdfDocument(io.BytesIO(response.content))
images = []
for page_idx in range(len(pdf)):
page = pdf[page_idx]
# Render at 300 DPI for good OCR quality
bitmap = page.render(scale=300 / 72)
pil_image = bitmap.to_pil()
images.append(pil_image)
return images