feat(infra): Stabilized Docker env, fixed circular imports, enabled AI Enricher Robot v1.1

backend/app/workers/ocr_robot.py

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+import asyncio
+import os
+import logging
+from PIL import Image
+from sqlalchemy import select, update
+from app.db.session import SessionLocal
+from app.models.document import Document # Feltételezve
+from app.models.identity import User
+from app.services.ai_service import AIService
+
+logging.basicConfig(level=logging.INFO)
+logger = logging.getLogger("Robot-OCR-V3")
+
+NAS_BASE_PATH = os.getenv("NAS_STORAGE_PATH", "/mnt/nas/user_vault")
+
+class OCRRobot:
+    @classmethod
+    async def process_queue(cls):
+        async with SessionLocal() as db:
+            # 1. Csak a várólistás és prémium jogosultságú dokumentumokat keressük
+            stmt = select(Document, User).join(User).where(
+                Document.status == "pending_ocr",
+                User.subscription_plan.in_(["PREMIUM_PLUS", "VIP_PLUS"])
+            ).limit(10)
+            
+            res = await db.execute(stmt)
+            tasks = res.all()
+
+            for doc, user in tasks:
+                try:
+                    logger.info(f"📸 OCR feldolgozás: {doc.filename} (User: {user.id})")
+                    
+                    # 2. AI OCR hívás
+                    with open(doc.temp_path, "rb") as f:
+                        image_bytes = f.read()
+                    
+                    ocr_result = await AIService.analyze_document_image(image_bytes, doc.doc_type)
+                    
+                    if ocr_result:
+                        # 3. Kép átméretezése (Thumbnail és Standard)
+                        target_dir = os.path.join(NAS_BASE_PATH, user.folder_slug, doc.doc_type)
+                        os.makedirs(target_dir, exist_ok=True)
+                        
+                        final_path = os.path.join(target_dir, f"{doc.id}.jpg")
+                        cls.resize_and_save(doc.temp_path, final_path)
+                        
+                        # 4. Adatbázis frissítése
+                        doc.ocr_data = ocr_result
+                        doc.file_link = final_path
+                        doc.status = "processed"
+                        
+                        # Ideiglenes fájl törlése
+                        os.remove(doc.temp_path)
+                        
+                    await db.commit()
+                except Exception as e:
+                    logger.error(f"❌ OCR Hiba ({doc.id}): {e}")
+                    await db.rollback()
+
+    @staticmethod
+    def resize_and_save(source, target):
+        with Image.open(source) as img:
+            img.convert('RGB').save(target, "JPEG", quality=85, optimize=True)
+
+if __name__ == "__main__":
+    asyncio.run(OCRRobot.process_queue())