b4613e26f3
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>
87 lines
2.4 KiB
Python
87 lines
2.4 KiB
Python
"""
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Orientation & Crop shared helpers - cache management and pipeline logging.
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"""
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import logging
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from typing import Any, Dict
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import cv2
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import numpy as np
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from fastapi import HTTPException
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from ocr_pipeline_session_store import (
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get_session_db,
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get_session_image,
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update_session_db,
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)
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logger = logging.getLogger(__name__)
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# Reference to the shared cache from ocr_pipeline_api (set in main.py)
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_cache: Dict[str, Dict[str, Any]] = {}
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def set_cache_ref(cache: Dict[str, Dict[str, Any]]):
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"""Set reference to the shared cache from ocr_pipeline_api."""
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global _cache
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_cache = cache
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def get_cache_ref() -> Dict[str, Dict[str, Any]]:
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"""Get reference to the shared cache."""
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return _cache
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async def ensure_cached(session_id: str) -> Dict[str, Any]:
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"""Ensure session is in cache, loading from DB if needed."""
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if session_id in _cache:
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return _cache[session_id]
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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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cache_entry: Dict[str, Any] = {
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"id": session_id,
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**session,
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"original_bgr": None,
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"oriented_bgr": None,
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"cropped_bgr": None,
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"deskewed_bgr": None,
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"dewarped_bgr": None,
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}
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for img_type, bgr_key in [
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("original", "original_bgr"),
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("oriented", "oriented_bgr"),
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("cropped", "cropped_bgr"),
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("deskewed", "deskewed_bgr"),
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("dewarped", "dewarped_bgr"),
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]:
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png_data = await get_session_image(session_id, img_type)
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if png_data:
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arr = np.frombuffer(png_data, dtype=np.uint8)
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bgr = cv2.imdecode(arr, cv2.IMREAD_COLOR)
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cache_entry[bgr_key] = bgr
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_cache[session_id] = cache_entry
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return cache_entry
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async def append_pipeline_log(session_id: str, step: str, metrics: dict, duration_ms: int):
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"""Append a step entry to the pipeline log."""
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from datetime import datetime
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session = await get_session_db(session_id)
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if not session:
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return
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pipeline_log = session.get("pipeline_log") or {"steps": []}
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pipeline_log["steps"].append({
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"step": step,
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"completed_at": datetime.utcnow().isoformat(),
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"success": True,
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"duration_ms": duration_ms,
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"metrics": metrics,
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})
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await update_session_db(session_id, pipeline_log=pipeline_log)
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