pyr0ball
8cbde774e5
Pantry tracker app with: - FastAPI backend + Vue 3 SPA frontend - SQLite via circuitforge-core (migrations 001-005) - Inventory CRUD, barcode scan, receipt OCR pipeline - Expiry prediction (deterministic + LLM fallback) - CF-core tier system integration - Cloud session support (menagerie)
126 lines
5.5 KiB
Python
126 lines
5.5 KiB
Python
"""
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Receipt processing service — orchestrates the OCR pipeline.
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Pipeline stages:
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1. Preprocess — enhance image, convert to PNG
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2. Quality — score image; abort to 'low_quality' if below threshold
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3. OCR — VisionLanguageOCR extracts structured data
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4. Persist — flatten result into receipt_data table
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5. Stage — set status to 'staged'; items await human approval
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Items are NOT added to inventory automatically. Use the
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POST /receipts/{id}/ocr/approve endpoint to commit approved items.
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"""
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from __future__ import annotations
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import logging
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from pathlib import Path
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from typing import Any
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from app.db.store import Store
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logger = logging.getLogger(__name__)
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def _flatten_ocr_result(result: dict[str, Any]) -> dict[str, Any]:
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"""Map nested VisionLanguageOCR output to the flat receipt_data schema."""
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merchant = result.get("merchant") or {}
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transaction = result.get("transaction") or {}
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totals = result.get("totals") or {}
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return {
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"merchant_name": merchant.get("name"),
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"merchant_address": merchant.get("address"),
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"merchant_phone": merchant.get("phone"),
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"transaction_date": transaction.get("date"),
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"transaction_time": transaction.get("time"),
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"receipt_number": transaction.get("receipt_number"),
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"register_number": transaction.get("register"),
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"cashier_name": transaction.get("cashier"),
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"items": result.get("items") or [],
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"subtotal": totals.get("subtotal"),
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"tax": totals.get("tax"),
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"discount": totals.get("discount"),
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"total": totals.get("total"),
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"payment_method": totals.get("payment_method"),
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"amount_paid": totals.get("amount_paid"),
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"change_given": totals.get("change"),
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"raw_text": result.get("raw_text"),
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"confidence_scores": result.get("confidence") or {},
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"warnings": result.get("warnings") or [],
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}
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class ReceiptService:
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def __init__(self, store: Store) -> None:
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self.store = store
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async def process(self, receipt_id: int, image_path: Path) -> None:
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"""Run the full OCR pipeline for a receipt image.
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Stages run synchronously inside asyncio.to_thread so SQLite and the
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VLM (which uses torch) both stay off the async event loop.
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"""
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import asyncio
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await asyncio.to_thread(self._run_pipeline, receipt_id, image_path)
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def _run_pipeline(self, receipt_id: int, image_path: Path) -> None:
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from app.core.config import settings
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from app.services.image_preprocessing.enhancement import ImageEnhancer
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from app.services.image_preprocessing.format_conversion import FormatConverter
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from app.services.quality.assessment import QualityAssessor
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# ── Stage 1: Preprocess ───────────────────────────────────────────────
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enhancer = ImageEnhancer()
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converter = FormatConverter()
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enhanced = enhancer.enhance(image_path)
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processed_path = converter.to_png(enhanced)
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# ── Stage 2: Quality assessment ───────────────────────────────────────
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assessor = QualityAssessor()
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assessment = assessor.assess(processed_path)
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self.store.upsert_quality_assessment(
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receipt_id,
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overall_score=assessment["overall_score"],
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is_acceptable=assessment["is_acceptable"],
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metrics=assessment.get("metrics", {}),
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suggestions=assessment.get("suggestions", []),
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)
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if not assessment["is_acceptable"]:
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self.store.update_receipt_status(receipt_id, "low_quality")
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logger.warning(
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"Receipt %s: quality too low for OCR (score=%.1f) — %s",
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receipt_id, assessment["overall_score"],
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"; ".join(assessment.get("suggestions", [])),
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)
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return
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if not settings.ENABLE_OCR:
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self.store.update_receipt_status(receipt_id, "processed")
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logger.info("Receipt %s: quality OK but ENABLE_OCR=false — skipping OCR", receipt_id)
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return
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# ── Stage 3: OCR extraction ───────────────────────────────────────────
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from app.services.ocr.vl_model import VisionLanguageOCR
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ocr = VisionLanguageOCR()
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result = ocr.extract_receipt_data(str(processed_path))
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if result.get("error"):
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self.store.update_receipt_status(receipt_id, "error", result["error"])
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logger.error("Receipt %s: OCR failed — %s", receipt_id, result["error"])
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return
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# ── Stage 4: Persist extracted data ───────────────────────────────────
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flat = _flatten_ocr_result(result)
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self.store.upsert_receipt_data(receipt_id, flat)
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item_count = len(flat.get("items") or [])
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# ── Stage 5: Stage for human approval ────────────────────────────────
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self.store.update_receipt_status(receipt_id, "staged")
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logger.info(
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"Receipt %s: OCR complete — %d item(s) staged for review "
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"(confidence=%.2f)",
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receipt_id, item_count,
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(result.get("confidence") or {}).get("overall", 0.0),
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)
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