- Assembly template system (13 templates: burrito, fried rice, omelette, stir fry, pasta, sandwich, grain bowl, soup/stew, casserole, pancakes, porridge, pie, pudding) with role-based matching, whole-word single-keyword guard, deterministic titles via MD5 pantry hash - Prep-state stripping: strips 'melted butter' → 'butter' for coverage checks; reconstructs actionable states as 'Before you start:' cooking instructions (NutritionPanel prep_notes field + RecipesView.vue display block) - FTS5 fixes: always double-quote all terms; strip apostrophes to prevent syntax errors on brands like "Stouffer's"; 'plant-based' → bare 'based' crash - Bidirectional synonym expansion: alt-meat, alt-chicken, alt-beef, alt-pork mapped to canonical texture class; pantry expansion covers 'hamburger' from 'burger patties' etc. - Texture profile backfill script (378K ingredient_profiles rows) with macro-derived classification in priority order (fatty → creamy → starchy → firm → fibrous → tender → liquid → neutral); oats/legumes starchy-first fix - LLM prompt: ban flavoured/sweetened ingredients (vanilla yoghurt) from savoury - Migrations 014 (nutrition macros) + 015 (recipe FTS index) - Nutrition estimation pipeline script - gitignore MagicMock sqlite test artifacts
81 lines
2.6 KiB
Python
81 lines
2.6 KiB
Python
"""Pydantic schemas for the recipe engine API."""
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from __future__ import annotations
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from pydantic import BaseModel, Field
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class SwapCandidate(BaseModel):
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original_name: str
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substitute_name: str
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constraint_label: str
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explanation: str
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compensation_hints: list[dict] = Field(default_factory=list)
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class NutritionPanel(BaseModel):
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"""Per-recipe macro summary. All values are per-serving when servings is known,
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otherwise for the full recipe. None means data is unavailable."""
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calories: float | None = None
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fat_g: float | None = None
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protein_g: float | None = None
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carbs_g: float | None = None
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fiber_g: float | None = None
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sugar_g: float | None = None
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sodium_mg: float | None = None
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servings: float | None = None
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estimated: bool = False # True when nutrition was inferred from ingredient profiles
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class RecipeSuggestion(BaseModel):
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id: int
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title: str
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match_count: int
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element_coverage: dict[str, float] = Field(default_factory=dict)
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swap_candidates: list[SwapCandidate] = Field(default_factory=list)
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missing_ingredients: list[str] = Field(default_factory=list)
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directions: list[str] = Field(default_factory=list)
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prep_notes: list[str] = Field(default_factory=list)
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notes: str = ""
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level: int = 1
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is_wildcard: bool = False
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nutrition: NutritionPanel | None = None
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class GroceryLink(BaseModel):
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ingredient: str
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retailer: str
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url: str
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class RecipeResult(BaseModel):
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suggestions: list[RecipeSuggestion]
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element_gaps: list[str]
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grocery_list: list[str] = Field(default_factory=list)
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grocery_links: list[GroceryLink] = Field(default_factory=list)
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rate_limited: bool = False
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rate_limit_count: int = 0
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class NutritionFilters(BaseModel):
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"""Optional per-serving upper bounds for macro filtering. None = no filter."""
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max_calories: float | None = None
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max_sugar_g: float | None = None
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max_carbs_g: float | None = None
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max_sodium_mg: float | None = None
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class RecipeRequest(BaseModel):
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pantry_items: list[str]
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level: int = Field(default=1, ge=1, le=4)
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constraints: list[str] = Field(default_factory=list)
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expiry_first: bool = False
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hard_day_mode: bool = False
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max_missing: int | None = None
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style_id: str | None = None
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category: str | None = None
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tier: str = "free"
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has_byok: bool = False
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wildcard_confirmed: bool = False
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allergies: list[str] = Field(default_factory=list)
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nutrition_filters: NutritionFilters = Field(default_factory=NutritionFilters)
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excluded_ids: list[int] = Field(default_factory=list)
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