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backend/app/services/extractor.py

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+"""Transaction data extraction: LLM Vision + persistence."""
+
+from app.models import Transaction
+from app.models.database import async_session_maker
+from app.schemas.transaction import TransactionExtractItem, TransactionResponse
+from app.services.llm import get_llm_provider
+
+
+async def extract_and_save(
+    case_id: int,
+    screenshot_id: int,
+    image_bytes: bytes,
+) -> list[TransactionResponse]:
+    """
+    Run vision extraction on image and persist transactions to DB.
+    Returns list of created transactions; low-confidence items are still saved but flagged.
+    """
+    provider = get_llm_provider()
+    items: list[TransactionExtractItem] = await provider.extract_from_image(image_bytes)
+    results: list[TransactionResponse] = []
+    async with async_session_maker() as session:
+        for it in items:
+            t = Transaction(
+                case_id=case_id,
+                screenshot_id=screenshot_id,
+                app_source=it.app_source,
+                transaction_type=it.transaction_type,
+                amount=it.amount,
+                currency=it.currency or "CNY",
+                counterparty_name=it.counterparty_name,
+                counterparty_account=it.counterparty_account,
+                order_number=it.order_number,
+                transaction_time=it.transaction_time,
+                remark=it.remark,
+                confidence=it.confidence if it.confidence in ("high", "medium", "low") else "medium",
+                raw_text=None,
+            )
+            session.add(t)
+            await session.flush()
+            results.append(TransactionResponse.model_validate(t))
+        await session.commit()
+    return results