pyr0ball
07450bf59f
- 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
583 lines
22 KiB
Python
583 lines
22 KiB
Python
"""
|
|
RecipeEngine — orchestrates the four creativity levels.
|
|
|
|
Level 1: corpus lookup ranked by ingredient match + expiry urgency
|
|
Level 2: Level 1 + deterministic substitution swaps
|
|
Level 3: element scaffold → LLM constrained prompt (see llm_recipe.py)
|
|
Level 4: wildcard LLM (see llm_recipe.py)
|
|
|
|
Amendments:
|
|
- max_missing: filter to recipes missing ≤ N pantry items
|
|
- hard_day_mode: filter to easy-method recipes only
|
|
- grocery_list: aggregated missing ingredients across suggestions
|
|
"""
|
|
from __future__ import annotations
|
|
|
|
import json
|
|
import re
|
|
from typing import TYPE_CHECKING
|
|
|
|
if TYPE_CHECKING:
|
|
from app.db.store import Store
|
|
|
|
from app.models.schemas.recipe import GroceryLink, NutritionPanel, RecipeRequest, RecipeResult, RecipeSuggestion, SwapCandidate
|
|
from app.services.recipe.assembly_recipes import match_assembly_templates
|
|
from app.services.recipe.element_classifier import ElementClassifier
|
|
from app.services.recipe.grocery_links import GroceryLinkBuilder
|
|
from app.services.recipe.substitution_engine import SubstitutionEngine
|
|
|
|
_LEFTOVER_DAILY_MAX_FREE = 5
|
|
|
|
# Words that carry no ingredient-identity signal — stripped before overlap scoring
|
|
_SWAP_STOPWORDS = frozenset({
|
|
"a", "an", "the", "of", "in", "for", "with", "and", "or",
|
|
"to", "from", "at", "by", "as", "on",
|
|
})
|
|
|
|
# Maps product-label substrings to recipe-corpus canonical terms.
|
|
# Kept in sync with Store._FTS_SYNONYMS — both must agree on canonical names.
|
|
# Used to expand pantry_set so single-word recipe ingredients can match
|
|
# multi-word product names (e.g. "hamburger" satisfied by "burger patties").
|
|
_PANTRY_LABEL_SYNONYMS: dict[str, str] = {
|
|
"burger patt": "hamburger",
|
|
"beef patt": "hamburger",
|
|
"ground beef": "hamburger",
|
|
"ground chuck": "hamburger",
|
|
"ground round": "hamburger",
|
|
"mince": "hamburger",
|
|
"veggie burger": "hamburger",
|
|
"beyond burger": "hamburger",
|
|
"impossible burger": "hamburger",
|
|
"plant burger": "hamburger",
|
|
"chicken patt": "chicken patty",
|
|
"kielbasa": "sausage",
|
|
"bratwurst": "sausage",
|
|
"frankfurter": "hotdog",
|
|
"wiener": "hotdog",
|
|
"chicken breast": "chicken",
|
|
"chicken thigh": "chicken",
|
|
"chicken drumstick": "chicken",
|
|
"chicken wing": "chicken",
|
|
"rotisserie chicken": "chicken",
|
|
"chicken tender": "chicken",
|
|
"chicken strip": "chicken",
|
|
"chicken piece": "chicken",
|
|
"fake chicken": "chicken",
|
|
"plant chicken": "chicken",
|
|
"vegan chicken": "chicken",
|
|
"daring": "chicken",
|
|
"gardein chick": "chicken",
|
|
"quorn chick": "chicken",
|
|
"chick'n": "chicken",
|
|
"chikn": "chicken",
|
|
"not-chicken": "chicken",
|
|
"no-chicken": "chicken",
|
|
# Plant-based beef subs → broad "beef" (strips ≠ ground; texture matters)
|
|
"not-beef": "beef",
|
|
"no-beef": "beef",
|
|
"plant beef": "beef",
|
|
"vegan beef": "beef",
|
|
# Plant-based pork subs
|
|
"not-pork": "pork",
|
|
"no-pork": "pork",
|
|
"plant pork": "pork",
|
|
"vegan pork": "pork",
|
|
"omnipork": "pork",
|
|
"omni pork": "pork",
|
|
# Generic alt-meat catch-alls → broad "beef"
|
|
"fake meat": "beef",
|
|
"plant meat": "beef",
|
|
"vegan meat": "beef",
|
|
"meat-free": "beef",
|
|
"meatless": "beef",
|
|
"pork chop": "pork",
|
|
"pork loin": "pork",
|
|
"pork tenderloin": "pork",
|
|
"marinara": "tomato sauce",
|
|
"pasta sauce": "tomato sauce",
|
|
"spaghetti sauce": "tomato sauce",
|
|
"pizza sauce": "tomato sauce",
|
|
"macaroni": "pasta",
|
|
"noodles": "pasta",
|
|
"spaghetti": "pasta",
|
|
"penne": "pasta",
|
|
"fettuccine": "pasta",
|
|
"rigatoni": "pasta",
|
|
"linguine": "pasta",
|
|
"rotini": "pasta",
|
|
"farfalle": "pasta",
|
|
"shredded cheese": "cheese",
|
|
"sliced cheese": "cheese",
|
|
"american cheese": "cheese",
|
|
"cheddar": "cheese",
|
|
"mozzarella": "cheese",
|
|
"heavy cream": "cream",
|
|
"whipping cream": "cream",
|
|
"half and half": "cream",
|
|
"burger bun": "buns",
|
|
"hamburger bun": "buns",
|
|
"hot dog bun": "buns",
|
|
"bread roll": "buns",
|
|
"dinner roll": "buns",
|
|
# Tortillas / wraps — assembly dishes (burritos, tacos, quesadillas)
|
|
"flour tortilla": "tortillas",
|
|
"corn tortilla": "tortillas",
|
|
"tortilla wrap": "tortillas",
|
|
"soft taco shell": "tortillas",
|
|
"taco shell": "taco shells",
|
|
"pita bread": "pita",
|
|
"flatbread": "flatbread",
|
|
# Canned beans — extremely interchangeable in assembly dishes
|
|
"black bean": "beans",
|
|
"pinto bean": "beans",
|
|
"kidney bean": "beans",
|
|
"refried bean": "beans",
|
|
"chickpea": "beans",
|
|
"garbanzo": "beans",
|
|
# Rice variants
|
|
"white rice": "rice",
|
|
"brown rice": "rice",
|
|
"jasmine rice": "rice",
|
|
"basmati rice": "rice",
|
|
"instant rice": "rice",
|
|
"microwavable rice": "rice",
|
|
# Salsa / hot sauce
|
|
"hot sauce": "salsa",
|
|
"taco sauce": "salsa",
|
|
"enchilada sauce": "salsa",
|
|
# Sour cream / Greek yogurt — functional substitutes
|
|
"greek yogurt": "sour cream",
|
|
# Frozen/prepackaged meal token extraction — handled by individual token
|
|
# fallback in _normalize_for_fts; these are the most common single-serve meal types
|
|
"lean cuisine": "casserole",
|
|
"stouffer": "casserole",
|
|
"healthy choice": "casserole",
|
|
"marie callender": "casserole",
|
|
}
|
|
|
|
|
|
# Matches leading quantity/unit prefixes in recipe ingredient strings,
|
|
# e.g. "2 cups flour" → "flour", "1/2 c. ketchup" → "ketchup",
|
|
# "3 oz. butter" → "butter"
|
|
_QUANTITY_PREFIX = re.compile(
|
|
r"^\s*(?:\d+(?:[./]\d+)?\s*)?" # optional leading number (1, 1/2, 2.5)
|
|
r"(?:to\s+\d+\s*)?" # optional "to N" range
|
|
r"(?:c\.|cup|cups|tbsp|tsp|oz|lb|lbs|g|kg|ml|l|"
|
|
r"can|cans|pkg|pkg\.|package|slice|slices|clove|cloves|"
|
|
r"small|medium|large|bunch|head|piece|pieces|"
|
|
r"pinch|dash|handful|sprig|sprigs)\s*\b",
|
|
re.IGNORECASE,
|
|
)
|
|
|
|
|
|
# Preparation-state words that modify an ingredient without changing what it is.
|
|
# Stripped from both ends so "melted butter", "butter, melted" both → "butter".
|
|
_PREP_STATES = re.compile(
|
|
r"\b(melted|softened|cold|warm|hot|room.temperature|"
|
|
r"diced|sliced|chopped|minced|grated|shredded|shredded|beaten|whipped|"
|
|
r"cooked|raw|frozen|canned|dried|dehydrated|marinated|seasoned|"
|
|
r"roasted|toasted|ground|crushed|pressed|peeled|seeded|pitted|"
|
|
r"boneless|skinless|trimmed|halved|quartered|julienned|"
|
|
r"thinly|finely|roughly|coarsely|freshly|lightly|"
|
|
r"packed|heaping|level|sifted|divided|optional)\b",
|
|
re.IGNORECASE,
|
|
)
|
|
# Trailing comma + optional prep state (e.g. "butter, melted")
|
|
_TRAILING_PREP = re.compile(r",\s*\w+$")
|
|
|
|
|
|
# Maps prep-state words to human-readable instruction templates.
|
|
# {ingredient} is replaced with the actual ingredient name.
|
|
# None means the state is passive (frozen, canned) — no note needed.
|
|
_PREP_INSTRUCTIONS: dict[str, str | None] = {
|
|
"melted": "Melt the {ingredient} before starting.",
|
|
"softened": "Let the {ingredient} soften to room temperature before using.",
|
|
"room temperature": "Bring the {ingredient} to room temperature before using.",
|
|
"beaten": "Beat the {ingredient} lightly before adding.",
|
|
"whipped": "Whip the {ingredient} until soft peaks form.",
|
|
"sifted": "Sift the {ingredient} before measuring.",
|
|
"toasted": "Toast the {ingredient} in a dry pan until fragrant.",
|
|
"roasted": "Roast the {ingredient} before using.",
|
|
"pressed": "Press the {ingredient} to remove excess moisture.",
|
|
"diced": "Dice the {ingredient} into small pieces.",
|
|
"sliced": "Slice the {ingredient} thinly.",
|
|
"chopped": "Chop the {ingredient} roughly.",
|
|
"minced": "Mince the {ingredient} finely.",
|
|
"grated": "Grate the {ingredient}.",
|
|
"shredded": "Shred the {ingredient}.",
|
|
"ground": "Grind the {ingredient}.",
|
|
"crushed": "Crush the {ingredient}.",
|
|
"peeled": "Peel the {ingredient} before use.",
|
|
"seeded": "Remove seeds from the {ingredient}.",
|
|
"pitted": "Pit the {ingredient} before use.",
|
|
"trimmed": "Trim any excess from the {ingredient}.",
|
|
"julienned": "Cut the {ingredient} into thin matchstick strips.",
|
|
"cooked": "Pre-cook the {ingredient} before adding.",
|
|
# Passive states — ingredient is used as-is, no prep note needed
|
|
"cold": None,
|
|
"warm": None,
|
|
"hot": None,
|
|
"raw": None,
|
|
"frozen": None,
|
|
"canned": None,
|
|
"dried": None,
|
|
"dehydrated": None,
|
|
"marinated": None,
|
|
"seasoned": None,
|
|
"boneless": None,
|
|
"skinless": None,
|
|
"divided": None,
|
|
"optional": None,
|
|
"fresh": None,
|
|
"freshly": None,
|
|
"thinly": None,
|
|
"finely": None,
|
|
"roughly": None,
|
|
"coarsely": None,
|
|
"lightly": None,
|
|
"packed": None,
|
|
"heaping": None,
|
|
"level": None,
|
|
}
|
|
|
|
# Finds the first actionable prep state in an ingredient string
|
|
_PREP_STATE_SEARCH = re.compile(
|
|
r"\b(" + "|".join(re.escape(k) for k in _PREP_INSTRUCTIONS) + r")\b",
|
|
re.IGNORECASE,
|
|
)
|
|
|
|
|
|
def _strip_quantity(ingredient: str) -> str:
|
|
"""Remove leading quantity/unit and preparation-state words from a recipe ingredient.
|
|
|
|
e.g. "2 tbsp melted butter" → "butter"
|
|
"butter, melted" → "butter"
|
|
"1/4 cup flour, sifted" → "flour"
|
|
"""
|
|
stripped = _QUANTITY_PREFIX.sub("", ingredient).strip()
|
|
# Strip any remaining leading number (e.g. "3 eggs" → "eggs")
|
|
stripped = re.sub(r"^\d+\s+", "", stripped)
|
|
# Strip trailing ", prep_state"
|
|
stripped = _TRAILING_PREP.sub("", stripped).strip()
|
|
# Strip prep-state words (may be leading or embedded)
|
|
stripped = _PREP_STATES.sub("", stripped).strip()
|
|
# Clean up any double spaces left behind
|
|
stripped = re.sub(r"\s{2,}", " ", stripped).strip()
|
|
return stripped or ingredient
|
|
|
|
|
|
def _prep_note_for(ingredient: str) -> str | None:
|
|
"""Return a human-readable prep instruction for this ingredient string, or None.
|
|
|
|
e.g. "2 tbsp melted butter" → "Melt the butter before starting."
|
|
"onion, diced" → "Dice the onion into small pieces."
|
|
"frozen peas" → None (passive state, no action needed)
|
|
"""
|
|
match = _PREP_STATE_SEARCH.search(ingredient)
|
|
if not match:
|
|
return None
|
|
state = match.group(1).lower()
|
|
template = _PREP_INSTRUCTIONS.get(state)
|
|
if not template:
|
|
return None
|
|
# Use the stripped ingredient name as the subject
|
|
ingredient_name = _strip_quantity(ingredient)
|
|
return template.format(ingredient=ingredient_name)
|
|
|
|
|
|
def _expand_pantry_set(pantry_items: list[str]) -> set[str]:
|
|
"""Return pantry_set expanded with canonical recipe-corpus synonyms.
|
|
|
|
For each pantry item, checks _PANTRY_LABEL_SYNONYMS for substring matches
|
|
and adds the canonical form. This lets single-word recipe ingredients
|
|
("hamburger", "chicken") match product-label pantry entries
|
|
("burger patties", "rotisserie chicken").
|
|
"""
|
|
expanded: set[str] = set()
|
|
for item in pantry_items:
|
|
lower = item.lower().strip()
|
|
expanded.add(lower)
|
|
for pattern, canonical in _PANTRY_LABEL_SYNONYMS.items():
|
|
if pattern in lower:
|
|
expanded.add(canonical)
|
|
return expanded
|
|
|
|
|
|
def _ingredient_in_pantry(ingredient: str, pantry_set: set[str]) -> bool:
|
|
"""Return True if the recipe ingredient is satisfied by the pantry.
|
|
|
|
Checks three layers in order:
|
|
1. Exact match after quantity stripping
|
|
2. Synonym lookup: ingredient → canonical → in pantry_set
|
|
(handles "ground beef" matched by "burger patties" via shared canonical)
|
|
3. Token subset: all content tokens of the ingredient appear in pantry
|
|
(handles "diced onions" when "onions" is in pantry)
|
|
"""
|
|
clean = _strip_quantity(ingredient).lower()
|
|
if clean in pantry_set:
|
|
return True
|
|
|
|
# Check if this recipe ingredient maps to a canonical that's in pantry
|
|
for pattern, canonical in _PANTRY_LABEL_SYNONYMS.items():
|
|
if pattern in clean and canonical in pantry_set:
|
|
return True
|
|
|
|
# Single-token ingredient whose token appears in pantry (e.g. "ketchup" in "c. ketchup")
|
|
tokens = [t for t in clean.split() if t not in _SWAP_STOPWORDS and len(t) > 2]
|
|
if tokens and all(t in pantry_set for t in tokens):
|
|
return True
|
|
|
|
return False
|
|
|
|
|
|
def _content_tokens(text: str) -> frozenset[str]:
|
|
return frozenset(
|
|
w for w in text.lower().split()
|
|
if w not in _SWAP_STOPWORDS and len(w) > 1
|
|
)
|
|
|
|
|
|
def _pantry_creative_swap(required: str, pantry_items: set[str]) -> str | None:
|
|
"""Return a pantry item that's a plausible creative substitute, or None.
|
|
|
|
Requires ≥2 shared content tokens AND ≥50% bidirectional overlap so that
|
|
single-word differences (cream-of-mushroom vs cream-of-potato) qualify while
|
|
single-word ingredients (butter, flour) don't accidentally match supersets
|
|
(peanut butter, bread flour).
|
|
"""
|
|
req_tokens = _content_tokens(required)
|
|
if len(req_tokens) < 2:
|
|
return None # single-word ingredients must already be in pantry_set
|
|
|
|
best: str | None = None
|
|
best_score = 0.0
|
|
for item in pantry_items:
|
|
if item.lower() == required.lower():
|
|
continue
|
|
pan_tokens = _content_tokens(item)
|
|
if not pan_tokens:
|
|
continue
|
|
overlap = len(req_tokens & pan_tokens)
|
|
if overlap < 2:
|
|
continue
|
|
score = min(overlap / len(req_tokens), overlap / len(pan_tokens))
|
|
if score >= 0.5 and score > best_score:
|
|
best_score = score
|
|
best = item
|
|
return best
|
|
|
|
|
|
# Method complexity classification patterns
|
|
_EASY_METHODS = re.compile(
|
|
r"\b(microwave|mix|stir|blend|toast|assemble|heat)\b", re.IGNORECASE
|
|
)
|
|
_INVOLVED_METHODS = re.compile(
|
|
r"\b(braise|roast|knead|deep.?fry|fry|sauté|saute|bake|boil)\b", re.IGNORECASE
|
|
)
|
|
|
|
|
|
def _classify_method_complexity(
|
|
directions: list[str],
|
|
available_equipment: list[str] | None = None,
|
|
) -> str:
|
|
"""Classify recipe method complexity from direction strings.
|
|
|
|
Returns 'easy', 'moderate', or 'involved'.
|
|
available_equipment can expand the easy set (e.g. ['toaster', 'air fryer']).
|
|
"""
|
|
text = " ".join(directions).lower()
|
|
equipment_set = {e.lower() for e in (available_equipment or [])}
|
|
|
|
if _INVOLVED_METHODS.search(text):
|
|
return "involved"
|
|
|
|
if _EASY_METHODS.search(text):
|
|
return "easy"
|
|
|
|
# Check equipment-specific easy methods
|
|
for equip in equipment_set:
|
|
if equip in text:
|
|
return "easy"
|
|
|
|
return "moderate"
|
|
|
|
|
|
class RecipeEngine:
|
|
def __init__(self, store: "Store") -> None:
|
|
self._store = store
|
|
self._classifier = ElementClassifier(store)
|
|
self._substitution = SubstitutionEngine(store)
|
|
|
|
def suggest(
|
|
self,
|
|
req: RecipeRequest,
|
|
available_equipment: list[str] | None = None,
|
|
) -> RecipeResult:
|
|
# Load cooking equipment from user settings when hard_day_mode is active
|
|
if req.hard_day_mode and available_equipment is None:
|
|
equipment_json = self._store.get_setting("cooking_equipment")
|
|
if equipment_json:
|
|
try:
|
|
available_equipment = json.loads(equipment_json)
|
|
except (json.JSONDecodeError, TypeError):
|
|
available_equipment = []
|
|
else:
|
|
available_equipment = []
|
|
# Rate-limit leftover mode for free tier
|
|
if req.expiry_first and req.tier == "free":
|
|
allowed, count = self._store.check_and_increment_rate_limit(
|
|
"leftover_mode", _LEFTOVER_DAILY_MAX_FREE
|
|
)
|
|
if not allowed:
|
|
return RecipeResult(
|
|
suggestions=[], element_gaps=[], rate_limited=True, rate_limit_count=count
|
|
)
|
|
|
|
profiles = self._classifier.classify_batch(req.pantry_items)
|
|
gaps = self._classifier.identify_gaps(profiles)
|
|
pantry_set = _expand_pantry_set(req.pantry_items)
|
|
|
|
if req.level >= 3:
|
|
from app.services.recipe.llm_recipe import LLMRecipeGenerator
|
|
gen = LLMRecipeGenerator(self._store)
|
|
return gen.generate(req, profiles, gaps)
|
|
|
|
# Level 1 & 2: deterministic path
|
|
nf = req.nutrition_filters
|
|
rows = self._store.search_recipes_by_ingredients(
|
|
req.pantry_items,
|
|
limit=20,
|
|
category=req.category or None,
|
|
max_calories=nf.max_calories,
|
|
max_sugar_g=nf.max_sugar_g,
|
|
max_carbs_g=nf.max_carbs_g,
|
|
max_sodium_mg=nf.max_sodium_mg,
|
|
excluded_ids=req.excluded_ids or [],
|
|
)
|
|
suggestions = []
|
|
|
|
for row in rows:
|
|
ingredient_names: list[str] = row.get("ingredient_names") or []
|
|
if isinstance(ingredient_names, str):
|
|
try:
|
|
ingredient_names = json.loads(ingredient_names)
|
|
except Exception:
|
|
ingredient_names = []
|
|
|
|
# Compute missing ingredients, detecting pantry coverage first.
|
|
# When covered, collect any prep-state annotations (e.g. "melted butter"
|
|
# → note "Melt the butter before starting.") to surface separately.
|
|
swap_candidates: list[SwapCandidate] = []
|
|
missing: list[str] = []
|
|
prep_note_set: set[str] = set()
|
|
for n in ingredient_names:
|
|
if _ingredient_in_pantry(n, pantry_set):
|
|
note = _prep_note_for(n)
|
|
if note:
|
|
prep_note_set.add(note)
|
|
continue
|
|
swap_item = _pantry_creative_swap(n, pantry_set)
|
|
if swap_item:
|
|
swap_candidates.append(SwapCandidate(
|
|
original_name=n,
|
|
substitute_name=swap_item,
|
|
constraint_label="pantry_swap",
|
|
explanation=f"You have {swap_item} — use it in place of {n}.",
|
|
compensation_hints=[],
|
|
))
|
|
else:
|
|
missing.append(n)
|
|
|
|
# Filter by max_missing (pantry swaps don't count as missing)
|
|
if req.max_missing is not None and len(missing) > req.max_missing:
|
|
continue
|
|
|
|
# Filter by hard_day_mode
|
|
if req.hard_day_mode:
|
|
directions: list[str] = row.get("directions") or []
|
|
if isinstance(directions, str):
|
|
try:
|
|
directions = json.loads(directions)
|
|
except Exception:
|
|
directions = [directions]
|
|
complexity = _classify_method_complexity(directions, available_equipment)
|
|
if complexity == "involved":
|
|
continue
|
|
|
|
# Level 2: also add dietary constraint swaps from substitution_pairs
|
|
if req.level == 2 and req.constraints:
|
|
for ing in ingredient_names:
|
|
for constraint in req.constraints:
|
|
swaps = self._substitution.find_substitutes(ing, constraint)
|
|
for swap in swaps[:1]:
|
|
swap_candidates.append(SwapCandidate(
|
|
original_name=swap.original_name,
|
|
substitute_name=swap.substitute_name,
|
|
constraint_label=swap.constraint_label,
|
|
explanation=swap.explanation,
|
|
compensation_hints=swap.compensation_hints,
|
|
))
|
|
|
|
coverage_raw = row.get("element_coverage") or {}
|
|
if isinstance(coverage_raw, str):
|
|
try:
|
|
coverage_raw = json.loads(coverage_raw)
|
|
except Exception:
|
|
coverage_raw = {}
|
|
|
|
servings = row.get("servings") or None
|
|
nutrition = NutritionPanel(
|
|
calories=row.get("calories"),
|
|
fat_g=row.get("fat_g"),
|
|
protein_g=row.get("protein_g"),
|
|
carbs_g=row.get("carbs_g"),
|
|
fiber_g=row.get("fiber_g"),
|
|
sugar_g=row.get("sugar_g"),
|
|
sodium_mg=row.get("sodium_mg"),
|
|
servings=servings,
|
|
estimated=bool(row.get("nutrition_estimated", 0)),
|
|
)
|
|
has_nutrition = any(
|
|
v is not None
|
|
for v in (nutrition.calories, nutrition.sugar_g, nutrition.carbs_g)
|
|
)
|
|
suggestions.append(RecipeSuggestion(
|
|
id=row["id"],
|
|
title=row["title"],
|
|
match_count=int(row.get("match_count") or 0),
|
|
element_coverage=coverage_raw,
|
|
swap_candidates=swap_candidates,
|
|
missing_ingredients=missing,
|
|
prep_notes=sorted(prep_note_set),
|
|
level=req.level,
|
|
nutrition=nutrition if has_nutrition else None,
|
|
))
|
|
|
|
# Prepend assembly-dish templates (burrito, stir fry, omelette, etc.)
|
|
# These fire regardless of corpus coverage — any pantry can make a burrito.
|
|
assembly = match_assembly_templates(
|
|
pantry_items=req.pantry_items,
|
|
pantry_set=pantry_set,
|
|
excluded_ids=req.excluded_ids or [],
|
|
)
|
|
suggestions = assembly + suggestions
|
|
|
|
# Build grocery list — deduplicated union of all missing ingredients
|
|
seen: set[str] = set()
|
|
grocery_list: list[str] = []
|
|
for s in suggestions:
|
|
for item in s.missing_ingredients:
|
|
if item not in seen:
|
|
grocery_list.append(item)
|
|
seen.add(item)
|
|
|
|
# Build grocery links — affiliate deeplinks for each missing ingredient
|
|
link_builder = GroceryLinkBuilder(tier=req.tier, has_byok=req.has_byok)
|
|
grocery_links = link_builder.build_all(grocery_list)
|
|
|
|
return RecipeResult(
|
|
suggestions=suggestions,
|
|
element_gaps=gaps,
|
|
grocery_list=grocery_list,
|
|
grocery_links=grocery_links,
|
|
)
|