[split-required] Split 500-850 LOC files (batch 2)
backend-lehrer (10 files): - game/database.py (785 → 5), correction_api.py (683 → 4) - classroom_engine/antizipation.py (676 → 5) - llm_gateway schools/edu_search already done in prior batch klausur-service (12 files): - orientation_crop_api.py (694 → 5), pdf_export.py (677 → 4) - zeugnis_crawler.py (676 → 5), grid_editor_api.py (671 → 5) - eh_templates.py (658 → 5), mail/api.py (651 → 5) - qdrant_service.py (638 → 5), training_api.py (625 → 4) website (6 pages): - middleware (696 → 8), mail (733 → 6), consent (628 → 8) - compliance/risks (622 → 5), export (502 → 5), brandbook (629 → 7) studio-v2 (3 components): - B2BMigrationWizard (848 → 3), CleanupPanel (765 → 2) - dashboard-experimental (739 → 2) admin-lehrer (4 files): - uebersetzungen (769 → 4), manager (670 → 2) - ChunkBrowserQA (675 → 6), dsfa/page (674 → 5) Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
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Benjamin Admin
177
klausur-service/backend/grid_editor_api_box.py
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177
klausur-service/backend/grid_editor_api_box.py
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"""
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Grid Editor API — box-grid-review endpoints.
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"""
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import logging
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from fastapi import APIRouter, HTTPException, Request
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from grid_editor_helpers import _words_in_zone
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from ocr_pipeline_session_store import (
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get_session_db,
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update_session_db,
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)
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logger = logging.getLogger(__name__)
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router = APIRouter(prefix="/api/v1/ocr-pipeline", tags=["grid-editor"])
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@router.post("/sessions/{session_id}/build-box-grids")
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async def build_box_grids(session_id: str, request: Request):
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"""Rebuild grid structure for all detected boxes with layout-aware detection.
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Uses structure_result.boxes (from Step 7) as the source of box coordinates,
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and raw_paddle_words as OCR word source. Creates or updates box zones in
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the grid_editor_result.
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Optional body: { "overrides": { "0": "bullet_list" } }
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Maps box_index -> forced layout_type.
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"""
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session = await get_session_db(session_id)
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if not session:
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raise HTTPException(status_code=404, detail=f"Session {session_id} not found")
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grid_data = session.get("grid_editor_result")
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if not grid_data:
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raise HTTPException(status_code=400, detail="No grid data. Run build-grid first.")
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# Get raw OCR words (with top/left/width/height keys)
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word_result = session.get("word_result") or {}
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all_words = word_result.get("raw_paddle_words") or word_result.get("raw_tesseract_words") or []
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if not all_words:
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raise HTTPException(status_code=400, detail="No raw OCR words available.")
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# Get detected boxes from structure_result
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structure_result = session.get("structure_result") or {}
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gt = session.get("ground_truth") or {}
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if not structure_result:
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structure_result = gt.get("structure_result") or {}
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detected_boxes = structure_result.get("boxes") or []
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if not detected_boxes:
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return {"session_id": session_id, "box_zones_rebuilt": 0, "spell_fixes": 0, "message": "No boxes detected"}
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# Filter out false-positive boxes in header/footer margins.
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img_h_for_filter = grid_data.get("image_height", 0) or word_result.get("image_height", 0)
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if img_h_for_filter > 0:
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margin_frac = 0.07 # 7% of image height
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margin_top = img_h_for_filter * margin_frac
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margin_bottom = img_h_for_filter * (1 - margin_frac)
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filtered = []
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for box in detected_boxes:
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by = box.get("y", 0)
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bh = box.get("h", 0)
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box_center_y = by + bh / 2
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if box_center_y < margin_top or box_center_y > margin_bottom:
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logger.info("build-box-grids: skipping header/footer box at y=%d h=%d (center=%.0f, margins=%.0f/%.0f)",
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by, bh, box_center_y, margin_top, margin_bottom)
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continue
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filtered.append(box)
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detected_boxes = filtered
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body = {}
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try:
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body = await request.json()
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except Exception:
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pass
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layout_overrides = body.get("overrides", {})
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from cv_box_layout import build_box_zone_grid
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img_w = grid_data.get("image_width", 0) or word_result.get("image_width", 0)
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img_h = grid_data.get("image_height", 0) or word_result.get("image_height", 0)
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zones = grid_data.get("zones", [])
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# Find highest existing zone_index
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max_zone_idx = max((z.get("zone_index", 0) for z in zones), default=-1)
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# Remove old box zones (we'll rebuild them)
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zones = [z for z in zones if z.get("zone_type") != "box"]
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box_count = 0
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spell_fixes = 0
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for box_idx, box in enumerate(detected_boxes):
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bx = box.get("x", 0)
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by = box.get("y", 0)
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bw = box.get("w", 0)
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bh = box.get("h", 0)
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if bw <= 0 or bh <= 0:
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continue
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# Filter raw OCR words inside this box
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zone_words = _words_in_zone(all_words, by, bh, bx, bw)
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if not zone_words:
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logger.info("Box %d: no words found in bbox (%d,%d,%d,%d)", box_idx, bx, by, bw, bh)
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continue
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zone_idx = max_zone_idx + 1 + box_idx
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forced_layout = layout_overrides.get(str(box_idx))
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# Build box grid
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box_grid = build_box_zone_grid(
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zone_words, bx, by, bw, bh,
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zone_idx, img_w, img_h,
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layout_type=forced_layout,
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)
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# Apply SmartSpellChecker to all box cells
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try:
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from smart_spell import SmartSpellChecker
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ssc = SmartSpellChecker()
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for cell in box_grid.get("cells", []):
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text = cell.get("text", "")
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if not text:
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continue
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result = ssc.correct_text(text, lang="auto")
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if result.changed:
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cell["text"] = result.corrected
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spell_fixes += 1
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except ImportError:
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pass
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# Build zone entry
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zone_entry = {
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"zone_index": zone_idx,
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"zone_type": "box",
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"bbox_px": {"x": bx, "y": by, "w": bw, "h": bh},
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"bbox_pct": {
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"x": round(bx / img_w * 100, 2) if img_w else 0,
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"y": round(by / img_h * 100, 2) if img_h else 0,
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"w": round(bw / img_w * 100, 2) if img_w else 0,
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"h": round(bh / img_h * 100, 2) if img_h else 0,
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},
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"border": None,
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"word_count": len(zone_words),
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"columns": box_grid["columns"],
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"rows": box_grid["rows"],
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"cells": box_grid["cells"],
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"header_rows": box_grid.get("header_rows", []),
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"box_layout_type": box_grid.get("box_layout_type", "flowing"),
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"box_grid_reviewed": False,
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"box_bg_color": box.get("bg_color_name", ""),
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"box_bg_hex": box.get("bg_color_hex", ""),
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}
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zones.append(zone_entry)
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box_count += 1
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# Sort zones by y-position for correct reading order
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zones.sort(key=lambda z: z.get("bbox_px", {}).get("y", 0))
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grid_data["zones"] = zones
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await update_session_db(session_id, grid_editor_result=grid_data)
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logger.info(
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"build-box-grids session %s: %d boxes processed (%d words spell-fixed) from %d detected",
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session_id, box_count, spell_fixes, len(detected_boxes),
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)
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return {
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"session_id": session_id,
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"box_zones_rebuilt": box_count,
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"total_detected_boxes": len(detected_boxes),
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"spell_fixes": spell_fixes,
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"zones": zones,
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}
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