feat(ocr): auto-insert [unleserlich] markers for low-confidence words

New confidence.py module with two functions:
- apply_confidence_markers(): replaces words below threshold with
  [unleserlich], collapses adjacent markers into one
- words_from_characters(): reconstructs word-level confidence from
  Kraken's character-level data

Surya 0.17 provides native word-level confidence via line.words.
Kraken 7.0 provides per-character confidences via record.confidences.
Both engines now pass word+confidence data through main.py, which
applies the marker post-processing before returning the API response.

Threshold configurable via OCR_CONFIDENCE_THRESHOLD env var (default 0.3).
Frontend already renders [unleserlich] markers via transcriptionMarkers.ts.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

ocr-service/main.py

@@ -9,6 +9,7 @@ import pypdfium2 as pdfium
 from fastapi import FastAPI, HTTPException
 from PIL import Image
 
+from confidence import apply_confidence_markers
 from engines import kraken as kraken_engine
 from engines import surya as surya_engine
 from models import OcrBlock, OcrRequest
@@ -71,6 +72,11 @@ async def run_ocr(request: OcrRequest):
         # TYPEWRITER, HANDWRITING_LATIN, UNKNOWN — all use Surya
         blocks = surya_engine.extract_blocks(images, request.language)
 
+    for block in blocks:
+        if block.get("words"):
+            block["text"] = apply_confidence_markers(block["words"])
+        block.pop("words", None)
+
     return [OcrBlock(**b) for b in blocks]