pyr0ball
17e62c451f
When a barcode scan finds no product in FDC/OFF, paid-tier users now see a "Capture label" offer instead of a dead-end "add manually" prompt. Backend: - Migration 036: captured_products local cache table (keyed by barcode, UPSERT on conflict so re-capture refreshes rather than errors) - store.get_captured_product / save_captured_product (with JSON decode for ingredient_names and allergens) - app/services/label_capture.py: wraps cf-core VisionRouter (caption API); graceful fallback to zero-confidence mock when stub/error; JSON fence stripping; confidence clamped to [0,1]; KIWI_LABEL_CAPTURE_MOCK=1 for tests - New schemas: LabelCaptureResponse, LabelConfirmRequest, LabelConfirmResponse - POST /inventory/scan/label-capture — image to extraction (paid+ gate, 403) - POST /inventory/scan/label-confirm — save confirmed product + optional inventory add - Both scan endpoints now: check captured_products cache before FDC/OFF; set needs_visual_capture=True for gap products on paid tier; BarcodeScanResult gains needs_visual_capture field - visual_label_capture feature gate added to tiers.py (paid) Tests: 42 new tests (service, store/migration, API endpoints) — 367 total passing Frontend: - InventoryList.vue: capturePhase state machine (offer => uploading => reviewing) - Offer card appears after scan gap (calm UX: no urgency, Discard always visible) - Review form: pre-populated from extraction; amber label highlights for unread fields (confidence < 0.7); comma-separated ingredients/allergens - api.ts: LabelCaptureResult + LabelConfirmRequest types; captureLabelPhoto() and confirmLabelCapture() API methods
59 lines
2 KiB
Python
59 lines
2 KiB
Python
"""Pydantic schemas for visual label capture (kiwi#79)."""
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from __future__ import annotations
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from typing import Any, Dict, List, Optional
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from pydantic import BaseModel, Field
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class LabelCaptureResponse(BaseModel):
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"""Extraction result returned after the user photographs a nutrition label."""
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barcode: str
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product_name: Optional[str] = None
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brand: Optional[str] = None
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serving_size_g: Optional[float] = None
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calories: Optional[float] = None
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fat_g: Optional[float] = None
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saturated_fat_g: Optional[float] = None
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carbs_g: Optional[float] = None
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sugar_g: Optional[float] = None
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fiber_g: Optional[float] = None
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protein_g: Optional[float] = None
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sodium_mg: Optional[float] = None
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ingredient_names: List[str] = Field(default_factory=list)
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allergens: List[str] = Field(default_factory=list)
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confidence: float = 0.0
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needs_review: bool = True # True when confidence < REVIEW_THRESHOLD
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class LabelConfirmRequest(BaseModel):
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"""User-confirmed extraction to save to the local product cache."""
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barcode: str
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product_name: Optional[str] = None
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brand: Optional[str] = None
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serving_size_g: Optional[float] = None
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calories: Optional[float] = None
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fat_g: Optional[float] = None
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saturated_fat_g: Optional[float] = None
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carbs_g: Optional[float] = None
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sugar_g: Optional[float] = None
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fiber_g: Optional[float] = None
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protein_g: Optional[float] = None
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sodium_mg: Optional[float] = None
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ingredient_names: List[str] = Field(default_factory=list)
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allergens: List[str] = Field(default_factory=list)
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confidence: float = 0.0
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# When True the confirmed product is also added to inventory
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location: str = "pantry"
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quantity: float = 1.0
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auto_add: bool = True
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class LabelConfirmResponse(BaseModel):
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"""Result of confirming a captured product."""
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ok: bool
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barcode: str
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product_id: Optional[int] = None
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inventory_item_id: Optional[int] = None
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message: str
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