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feat: include extra ingredients + amounts in NLP parser output (#7191)
This commit is contained in:
Michael Genson
GitHub
@@ -0,0 +1,93 @@
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import pytest
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from pydantic import UUID4
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from sqlalchemy.orm import Session
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from mealie.repos.all_repositories import get_repositories
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from mealie.repos.repository_factory import AllRepositories
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from mealie.schema.recipe.recipe_ingredient import (
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CreateIngredientFoodAlias,
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CreateIngredientUnitAlias,
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IngredientFood,
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IngredientUnit,
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SaveIngredientFood,
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SaveIngredientUnit,
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)
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from mealie.schema.user.user import GroupBase
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from tests.utils.factories import random_int, random_string
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@pytest.fixture()
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def unique_local_group_id(unfiltered_database: AllRepositories) -> UUID4:
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return str(unfiltered_database.groups.create(GroupBase(name=random_string())).id)
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@pytest.fixture()
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def unique_db(session: Session, unique_local_group_id: str):
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return get_repositories(session, group_id=unique_local_group_id)
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@pytest.fixture()
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def parsed_ingredient_data(
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unique_db: AllRepositories, unique_local_group_id: UUID4
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) -> tuple[list[IngredientFood], list[IngredientUnit]]:
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foods = unique_db.ingredient_foods.create_many(
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[
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SaveIngredientFood(name="potatoes", group_id=unique_local_group_id),
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SaveIngredientFood(name="onion", group_id=unique_local_group_id),
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SaveIngredientFood(name="green onion", group_id=unique_local_group_id),
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SaveIngredientFood(name="frozen pearl onions", group_id=unique_local_group_id),
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SaveIngredientFood(name="bell peppers", group_id=unique_local_group_id),
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SaveIngredientFood(name="red pepper flakes", group_id=unique_local_group_id),
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SaveIngredientFood(name="fresh ginger", group_id=unique_local_group_id),
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SaveIngredientFood(name="ground ginger", group_id=unique_local_group_id),
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SaveIngredientFood(name="ñör̃m̈ãl̈ĩz̈ẽm̈ẽ", group_id=unique_local_group_id),
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SaveIngredientFood(name="PluralFoodTest", plural_name="myfoodisplural", group_id=unique_local_group_id),
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SaveIngredientFood(
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name="IHaveAnAlias",
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group_id=unique_local_group_id,
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aliases=[CreateIngredientFoodAlias(name="thisismyalias")],
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),
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]
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)
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foods.extend(
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unique_db.ingredient_foods.create_many(
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[
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SaveIngredientFood(name=f"{random_string()} food", group_id=unique_local_group_id)
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for _ in range(random_int(10, 15))
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]
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)
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)
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units = unique_db.ingredient_units.create_many(
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[
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SaveIngredientUnit(name="Cups", group_id=unique_local_group_id),
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SaveIngredientUnit(name="Tablespoon", group_id=unique_local_group_id),
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SaveIngredientUnit(name="Teaspoon", group_id=unique_local_group_id),
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SaveIngredientUnit(name="Stalk", group_id=unique_local_group_id),
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SaveIngredientUnit(name="My Very Long Unit Name", abbreviation="mvlun", group_id=unique_local_group_id),
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SaveIngredientUnit(
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name="PluralUnitName",
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plural_name="abc123",
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abbreviation="doremiabc",
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plural_abbreviation="doremi123",
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group_id=unique_local_group_id,
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),
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SaveIngredientUnit(
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name="IHaveAnAliasToo",
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group_id=unique_local_group_id,
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aliases=[CreateIngredientUnitAlias(name="thisismyalias")],
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),
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]
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)
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units.extend(
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unique_db.ingredient_foods.create_many(
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[
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SaveIngredientUnit(name=f"{random_string()} unit", group_id=unique_local_group_id)
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for _ in range(random_int(10, 15))
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]
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)
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)
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return foods, units
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@@ -0,0 +1,351 @@
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import asyncio
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import pytest
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from pydantic import UUID4
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from mealie.db.db_setup import session_context
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from mealie.lang.providers import get_locale_provider
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from mealie.schema.recipe.recipe_ingredient import (
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CreateIngredientFood,
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CreateIngredientUnit,
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IngredientFood,
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IngredientUnit,
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ParsedIngredient,
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RecipeIngredient,
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)
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from mealie.services.parser_services import RegisteredParser, get_parser
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def build_parsed_ing(food: str | None, unit: str | None) -> ParsedIngredient:
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ing = RecipeIngredient(unit=None, food=None)
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if food:
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ing.food = CreateIngredientFood(name=food)
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if unit:
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ing.unit = CreateIngredientUnit(name=unit)
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return ParsedIngredient(input=None, ingredient=ing)
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@pytest.mark.parametrize(
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"input, quantity, unit, food, comment",
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[
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pytest.param("1 theelepel koffie", 1, "theelepel", "koffie", "", id="1 theelepel koffie"),
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pytest.param("3 theelepels koffie", 3, "theelepels", "koffie", "", id="3 theelepels koffie"),
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pytest.param("1 eetlepel tarwe", 1, "eetlepel", "tarwe", "", id="1 eetlepel tarwe"),
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pytest.param("20 eetlepels bloem", 20, "eetlepels", "bloem", "", id="20 eetlepels bloem"),
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pytest.param("1 mespunt kaneel", 1, "mespunt", "kaneel", "", id="1 mespunt kaneel"),
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pytest.param("1 snuf(je) zout", 1, "snuf(je)", "zout", "", id="1 snuf(je) zout"),
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pytest.param(
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"2 tbsp minced cilantro, leaves and stems",
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2,
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"tbsp",
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"minced cilantro",
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"leaves and stems",
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id="2 tbsp minced cilantro, leaves and stems",
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),
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pytest.param(
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"1 large yellow onion, coarsely chopped",
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1,
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"large",
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"yellow onion",
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"coarsely chopped",
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id="1 large yellow onion, coarsely chopped",
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),
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pytest.param("1 1/2 tsp garam masala", 1.5, "tsp", "garam masala", "", id="1 1/2 tsp garam masala"),
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pytest.param(
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"2 cups mango chunks, (2 large mangoes) (fresh or frozen)",
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2,
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"Cups",
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"mango chunks, (2 large mangoes)",
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"fresh or frozen",
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id="2 cups mango chunks, (2 large mangoes) (fresh or frozen)",
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),
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pytest.param("stalk onion", 0, "Stalk", "onion", "", id="stalk onion"),
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pytest.param("a stalk bell peppers", 0, "Stalk", "bell peppers", "", id="a stalk bell peppers"),
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pytest.param("a tablespoon unknownFood", 0, "Tablespoon", "unknownFood", "", id="a tablespoon unknownFood"),
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pytest.param(
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"stalk bell peppers, cut in pieces",
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0,
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"Stalk",
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"bell peppers",
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"cut in pieces",
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id="stalk bell peppers, cut in pieces",
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),
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pytest.param(
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"a stalk bell peppers, cut in pieces",
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0,
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"Stalk",
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"bell peppers",
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"cut in pieces",
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id="a stalk bell peppers, cut in pieces",
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),
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pytest.param("red pepper flakes", 0, "", "red pepper flakes", "", id="red pepper flakes"),
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pytest.param("1 bell peppers", 1, "", "bell peppers", "", id="1 bell peppers"),
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pytest.param("1 stalk bell peppers", 1, "Stalk", "bell peppers", "", id="1 big stalk bell peppers"),
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pytest.param("a big stalk bell peppers", 0, "Stalk", "bell peppers", "", id="a big stalk bell peppers"),
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pytest.param(
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"1 bell peppers, cut in pieces", 1, "", "bell peppers", "cut in pieces", id="1 bell peppers, cut in pieces"
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),
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pytest.param(
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"bell peppers, cut in pieces", 0, "", "bell peppers", "cut in pieces", id="bell peppers, cut in pieces"
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),
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],
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)
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def test_brute_parser(
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unique_local_group_id: UUID4,
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parsed_ingredient_data: tuple[list[IngredientFood], list[IngredientUnit]], # required so database is populated
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input: str,
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quantity: int | float,
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unit: str,
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food: str,
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comment: str,
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):
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with session_context() as session:
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loop = asyncio.get_event_loop()
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parser = get_parser(RegisteredParser.brute, unique_local_group_id, session, get_locale_provider())
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parsed = loop.run_until_complete(parser.parse_one(input))
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ing = parsed.ingredient
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if ing.quantity:
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assert ing.quantity == quantity
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else:
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assert not quantity
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if ing.unit:
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assert ing.unit.name == unit
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else:
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assert not unit
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if ing.food:
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assert ing.food.name == food
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else:
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assert not food
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if ing.note:
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assert ing.note == comment
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else:
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assert not comment
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@pytest.mark.parametrize(
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"unit, food, expect_unit_match, expect_food_match, expected_avg",
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[
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pytest.param("Cups", "potatoes", True, True, 1.0, id="all matched"),
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pytest.param("Cups", "veryuniquefood", True, False, 0.75, id="unit matched only"),
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pytest.param("veryuniqueunit", "potatoes", False, True, 0.75, id="food matched only"),
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pytest.param("veryuniqueunit", "veryuniquefood", False, False, 0.5, id="neither matched"),
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],
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)
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def test_brute_parser_confidence(
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unit: str,
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food: str,
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expect_unit_match: bool,
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expect_food_match: bool,
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expected_avg: float,
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unique_local_group_id: UUID4,
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parsed_ingredient_data: tuple[list[IngredientFood], list[IngredientUnit]],
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):
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input_str = f"1 {unit} {food}"
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with session_context() as session:
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original_loop = asyncio.get_event_loop()
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try:
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loop = asyncio.new_event_loop()
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asyncio.set_event_loop(loop)
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parser = get_parser(RegisteredParser.brute, unique_local_group_id, session, get_locale_provider())
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parsed = loop.run_until_complete(parser.parse_one(input_str))
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finally:
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loop.close()
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asyncio.set_event_loop(original_loop)
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conf = parsed.confidence
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assert conf.quantity == 1
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assert conf.comment == 1
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assert conf.unit == (1 if expect_unit_match or not unit else 0)
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assert conf.food == (1 if expect_food_match or not food else 0)
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assert conf.average == expected_avg
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@pytest.mark.parametrize(
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"input, expected_unit_name, expected_food_name, expect_unit_match, expect_food_match",
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(
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pytest.param(
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build_parsed_ing(unit="cup", food="potatoes"),
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"Cups",
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"potatoes",
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True,
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True,
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id="basic match",
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),
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pytest.param( # this should work in sqlite since "potato" is contained within "potatoes"
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build_parsed_ing(unit="cup", food="potato"),
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"Cups",
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"potatoes",
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True,
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True,
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id="basic fuzzy match",
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),
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pytest.param(
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build_parsed_ing(unit="tablespoon", food="onion"),
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"Tablespoon",
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"onion",
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True,
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True,
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id="nested match 1",
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),
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pytest.param(
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build_parsed_ing(unit="teaspoon", food="green onion"),
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"Teaspoon",
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"green onion",
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True,
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True,
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id="nested match 2",
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),
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pytest.param(
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build_parsed_ing(unit="cup", food="gren onion"),
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"Cups",
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"green onion",
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True,
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True,
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id="nested match 3",
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),
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pytest.param(
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build_parsed_ing(unit="stalk", food="very unique"),
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"Stalk",
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"very unique",
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True,
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False,
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id="no food match",
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),
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pytest.param(
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build_parsed_ing(unit="cup", food=None),
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"Cups",
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None,
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True,
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False,
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id="no food input",
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),
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pytest.param(
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build_parsed_ing(unit="very unique", food="fresh ginger"),
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"very unique",
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"fresh ginger",
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False,
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True,
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id="no unit match",
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),
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pytest.param(
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build_parsed_ing(unit=None, food="potatoes"),
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None,
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"potatoes",
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False,
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True,
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id="no unit input",
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),
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pytest.param(
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build_parsed_ing(unit="very unique", food="very unique"),
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"very unique",
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"very unique",
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False,
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False,
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id="no matches",
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),
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pytest.param(
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build_parsed_ing(unit=None, food=None),
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None,
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None,
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False,
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False,
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id="no input",
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),
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pytest.param(
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build_parsed_ing(unit="mvlun", food="potatoes"),
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"My Very Long Unit Name",
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"potatoes",
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True,
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True,
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id="unit abbreviation",
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),
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pytest.param(
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build_parsed_ing(unit=None, food="n̅ōr̅m̄a̅l̄i̅z̄e̅m̄e̅"),
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None,
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"ñör̃m̈ãl̈ĩz̈ẽm̈ẽ",
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False,
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True,
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id="normalization",
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),
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pytest.param(
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build_parsed_ing(unit=None, food="myfoodisplural"),
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None,
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"PluralFoodTest",
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False,
|
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True,
|
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id="plural food name",
|
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),
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pytest.param(
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build_parsed_ing(unit="abc123", food=None),
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"PluralUnitName",
|
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None,
|
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True,
|
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False,
|
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id="plural unit name",
|
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),
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pytest.param(
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build_parsed_ing(unit="doremi123", food=None),
|
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"PluralUnitName",
|
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None,
|
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True,
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False,
|
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id="plural unit abbreviation",
|
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),
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pytest.param(
|
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build_parsed_ing(unit=None, food="thisismyalias"),
|
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None,
|
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"IHaveAnAlias",
|
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False,
|
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True,
|
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id="food alias",
|
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),
|
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pytest.param(
|
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build_parsed_ing(unit="thisismyalias", food=None),
|
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"IHaveAnAliasToo",
|
||||
None,
|
||||
True,
|
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False,
|
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id="unit alias",
|
||||
),
|
||||
),
|
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)
|
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def test_parser_ingredient_match(
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expected_food_name: str | None,
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expected_unit_name: str | None,
|
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expect_food_match: bool,
|
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expect_unit_match: bool,
|
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input: ParsedIngredient,
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parsed_ingredient_data: tuple[list[IngredientFood], list[IngredientUnit]], # required so database is populated
|
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unique_local_group_id: UUID4,
|
||||
):
|
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with session_context() as session:
|
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parser = get_parser(RegisteredParser.brute, unique_local_group_id, session, get_locale_provider())
|
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parsed_ingredient = parser.find_ingredient_match(input)
|
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|
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if expected_food_name:
|
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assert parsed_ingredient.ingredient.food and parsed_ingredient.ingredient.food.name == expected_food_name
|
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else:
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assert parsed_ingredient.ingredient.food is None
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|
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if expect_food_match:
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assert isinstance(parsed_ingredient.ingredient.food, IngredientFood)
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elif parsed_ingredient.ingredient.food and parsed_ingredient.ingredient.food.name:
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assert isinstance(parsed_ingredient.ingredient.food, CreateIngredientFood)
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else:
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assert parsed_ingredient.ingredient.food is None
|
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|
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if expected_unit_name:
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assert parsed_ingredient.ingredient.unit and parsed_ingredient.ingredient.unit.name == expected_unit_name
|
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else:
|
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assert parsed_ingredient.ingredient.unit is None
|
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|
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if expect_unit_match:
|
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assert isinstance(parsed_ingredient.ingredient.unit, IngredientUnit)
|
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elif parsed_ingredient.ingredient.unit and parsed_ingredient.ingredient.unit.name:
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assert isinstance(parsed_ingredient.ingredient.unit, CreateIngredientUnit)
|
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else:
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assert parsed_ingredient.ingredient.unit is None
|
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@@ -0,0 +1,113 @@
|
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import asyncio
|
||||
import re
|
||||
from dataclasses import dataclass
|
||||
|
||||
import pytest
|
||||
from pydantic import UUID4
|
||||
from rapidfuzz import fuzz
|
||||
from text_unidecode import unidecode
|
||||
|
||||
from mealie.db.db_setup import session_context
|
||||
from mealie.lang.providers import get_locale_provider
|
||||
from mealie.services.parser_services import RegisteredParser, get_parser
|
||||
|
||||
|
||||
@dataclass
|
||||
class TestIngredient:
|
||||
input: str
|
||||
quantity: float
|
||||
unit: str
|
||||
food: str
|
||||
comments: str
|
||||
|
||||
|
||||
def normalize(val: str) -> str:
|
||||
val = unidecode(val).lower().strip()
|
||||
val = re.sub(r"[^a-z0-9\s]", "", val)
|
||||
return val
|
||||
|
||||
|
||||
@pytest.mark.parametrize(
|
||||
"test_ingredient",
|
||||
[
|
||||
TestIngredient("½ cup all-purpose flour", 0.5, "cup", "all-purpose flour", ""),
|
||||
TestIngredient("1 ½ teaspoons ground black pepper", 1.5, "teaspoon", "black pepper", "ground"),
|
||||
TestIngredient("⅔ cup unsweetened flaked coconut", 0.667, "cup", "unsweetened flaked coconut", ""),
|
||||
TestIngredient("⅓ cup panko bread crumbs", 0.333, "cup", "panko bread crumbs", ""),
|
||||
TestIngredient("1/8 cup all-purpose flour", 0.125, "cup", "all-purpose flour", ""),
|
||||
TestIngredient("1/32 cup all-purpose flour", 0.031, "cup", "all-purpose flour", ""),
|
||||
TestIngredient("1 1/2 cups chopped onion ", 1.5, "cup", "onion", "chopped"),
|
||||
TestIngredient(
|
||||
"2 pounds russet potatoes, peeled, and cut into 3/4-inch cubes ",
|
||||
2,
|
||||
"pound",
|
||||
"russet potatoes",
|
||||
"peeled, and cut into 3/4 inch cubes",
|
||||
),
|
||||
TestIngredient("2 teaspoons salt (to taste) ", 2, "teaspoon", "salt", "to taste"),
|
||||
TestIngredient("1/2 cup", 0.5, "cup", "", ""),
|
||||
],
|
||||
)
|
||||
def test_nlp_parser(unique_local_group_id: UUID4, test_ingredient: TestIngredient):
|
||||
with session_context() as session:
|
||||
loop = asyncio.get_event_loop()
|
||||
parser = get_parser(RegisteredParser.nlp, unique_local_group_id, session, get_locale_provider())
|
||||
parsed = loop.run_until_complete(parser.parse_one(test_ingredient.input))
|
||||
ing = parsed.ingredient
|
||||
|
||||
assert ing.quantity == pytest.approx(test_ingredient.quantity)
|
||||
if ing.unit:
|
||||
assert ing.unit.name == test_ingredient.unit
|
||||
else:
|
||||
assert not test_ingredient.unit
|
||||
if ing.food:
|
||||
assert ing.food.name == test_ingredient.food
|
||||
else:
|
||||
assert not test_ingredient.food
|
||||
if ing.note:
|
||||
assert ing.note == test_ingredient.comments
|
||||
else:
|
||||
assert not test_ingredient.comments
|
||||
|
||||
|
||||
@pytest.mark.parametrize(
|
||||
("source_str", "expected_str"),
|
||||
[
|
||||
(
|
||||
"2 teaspoon chopped fresh or dried rosemary",
|
||||
"2 teaspoon fresh rosemary or dried rosemary chopped",
|
||||
),
|
||||
(
|
||||
"153 grams 00 flour (1 cup plus 1 tablespoon)",
|
||||
"153 gram 00 flour or 1 cup and 1 tablespoon",
|
||||
),
|
||||
(
|
||||
"153 grams all-purpose flour (1 cup plus 1 tablespoon and 2 teaspoons)",
|
||||
"153 gram all-purpose flour or 1 cup plus 1 tablespoon and 2 teaspoons",
|
||||
),
|
||||
(
|
||||
"2 cups chicken broth or beef broth",
|
||||
"2 cup chicken broth or beef broth",
|
||||
),
|
||||
(
|
||||
"2 tablespoons (30ml) vegetable oil",
|
||||
"2 tablespoon vegetable oil or 30 milliliter",
|
||||
),
|
||||
(
|
||||
"1 cup fresh basil or 2 tablespoons dried basil",
|
||||
"1 cup fresh basil or 2 tablespoons dried basil",
|
||||
),
|
||||
],
|
||||
)
|
||||
@pytest.mark.asyncio
|
||||
async def test_nlp_parser_keeps_all_text(unique_local_group_id: UUID4, source_str: str, expected_str: str):
|
||||
with session_context() as session:
|
||||
parser = get_parser(RegisteredParser.nlp, unique_local_group_id, session, get_locale_provider())
|
||||
parsed = await parser.parse_one(source_str)
|
||||
|
||||
ing = parsed.ingredient
|
||||
|
||||
# The parser behavior may change slightly, so we check that it's pretty close rather than exact
|
||||
# fuzz.ratio returns a string from 0 - 100 where 100 is an exact match
|
||||
score = fuzz.ratio(ing.display, expected_str)
|
||||
assert score >= 90, f"'{ing.display}' does not sufficiently match expected '{expected_str}'"
|
||||
@@ -0,0 +1,311 @@
|
||||
import asyncio
|
||||
import json
|
||||
from typing import cast
|
||||
from unittest.mock import MagicMock
|
||||
|
||||
import pytest
|
||||
from pydantic import UUID4
|
||||
|
||||
from mealie.db.db_setup import session_context
|
||||
from mealie.lang.providers import get_locale_provider
|
||||
from mealie.schema.openai.recipe_ingredient import OpenAIIngredient, OpenAIIngredients
|
||||
from mealie.schema.recipe.recipe import Recipe
|
||||
from mealie.schema.recipe.recipe_ingredient import (
|
||||
CreateIngredientFood,
|
||||
CreateIngredientUnit,
|
||||
IngredientFood,
|
||||
IngredientUnit,
|
||||
ParsedIngredient,
|
||||
RecipeIngredient,
|
||||
SaveIngredientFood,
|
||||
)
|
||||
from mealie.services.openai import OpenAIService
|
||||
from mealie.services.parser_services import RegisteredParser, get_parser
|
||||
from tests.utils.factories import random_int, random_string
|
||||
from tests.utils.fixture_schemas import TestUser
|
||||
|
||||
|
||||
def test_openai_parser(
|
||||
unique_local_group_id: UUID4,
|
||||
parsed_ingredient_data: tuple[list[IngredientFood], list[IngredientUnit]], # required so database is populated
|
||||
monkeypatch: pytest.MonkeyPatch,
|
||||
):
|
||||
ingredient_count = random_int(10, 20)
|
||||
|
||||
async def mock_get_response(self, prompt: str, message: str, *args, **kwargs) -> OpenAIIngredients | None:
|
||||
inputs = json.loads(message)
|
||||
data = OpenAIIngredients(
|
||||
ingredients=[
|
||||
OpenAIIngredient(
|
||||
quantity=random_int(0, 10),
|
||||
unit=random_string(),
|
||||
food=random_string(),
|
||||
note=random_string(),
|
||||
)
|
||||
for _ in inputs
|
||||
]
|
||||
)
|
||||
return data
|
||||
|
||||
monkeypatch.setattr(OpenAIService, "get_response", mock_get_response)
|
||||
|
||||
with session_context() as session:
|
||||
loop = asyncio.get_event_loop()
|
||||
parser = get_parser(RegisteredParser.openai, unique_local_group_id, session, get_locale_provider())
|
||||
|
||||
inputs = [random_string() for _ in range(ingredient_count)]
|
||||
parsed = loop.run_until_complete(parser.parse(inputs))
|
||||
|
||||
# since OpenAI is mocked, we don't need to validate the data, we just need to make sure parsing works
|
||||
# and that it preserves order
|
||||
assert len(parsed) == ingredient_count
|
||||
for input, output in zip(inputs, parsed, strict=True):
|
||||
assert output.input == input
|
||||
|
||||
|
||||
def test_openai_parser_sanitize_output(
|
||||
unique_local_group_id: UUID4,
|
||||
unique_user: TestUser,
|
||||
parsed_ingredient_data: tuple[list[IngredientFood], list[IngredientUnit]], # required so database is populated
|
||||
monkeypatch: pytest.MonkeyPatch,
|
||||
):
|
||||
async def mock_get_raw_response(self, prompt: str, content: list[dict], response_schema) -> MagicMock:
|
||||
# Create data with null character in JSON to test preprocessing
|
||||
data = OpenAIIngredients(
|
||||
ingredients=[
|
||||
OpenAIIngredient(
|
||||
quantity=random_int(0, 10),
|
||||
unit="",
|
||||
food="there is a null character here: \x00",
|
||||
note="",
|
||||
)
|
||||
]
|
||||
)
|
||||
|
||||
# Create a mock raw response which matches the OpenAI chat response format
|
||||
mock_response = MagicMock()
|
||||
mock_response.choices = [MagicMock()]
|
||||
mock_response.choices[0].message.content = data.model_dump_json()
|
||||
return mock_response
|
||||
|
||||
# Mock the raw response here since we want to make sure our service executes processing before loading the model
|
||||
monkeypatch.setattr(OpenAIService, "_get_raw_response", mock_get_raw_response)
|
||||
|
||||
with session_context() as session:
|
||||
loop = asyncio.get_event_loop()
|
||||
parser = get_parser(RegisteredParser.openai, unique_local_group_id, session, get_locale_provider())
|
||||
|
||||
parsed = loop.run_until_complete(parser.parse([""]))
|
||||
assert len(parsed) == 1
|
||||
parsed_ing = cast(ParsedIngredient, parsed[0])
|
||||
assert parsed_ing.ingredient.food
|
||||
assert parsed_ing.ingredient.food.name == "there is a null character here: "
|
||||
|
||||
# Make sure we can create a recipe with this ingredient
|
||||
assert isinstance(parsed_ing.ingredient.food, CreateIngredientFood)
|
||||
food = unique_user.repos.ingredient_foods.create(
|
||||
parsed_ing.ingredient.food.cast(SaveIngredientFood, group_id=unique_user.group_id)
|
||||
)
|
||||
parsed_ing.ingredient.food = food
|
||||
unique_user.repos.recipes.create(
|
||||
Recipe(
|
||||
user_id=unique_user.user_id,
|
||||
group_id=unique_user.group_id,
|
||||
name=random_string(),
|
||||
recipe_ingredient=[parsed_ing.ingredient],
|
||||
)
|
||||
)
|
||||
|
||||
|
||||
@pytest.mark.parametrize(
|
||||
"original_text,quantity,unit,food,note,qty_range,unit_range,food_range,note_range",
|
||||
[
|
||||
pytest.param(
|
||||
"2 cups flour",
|
||||
2.0,
|
||||
"Cups",
|
||||
"flour",
|
||||
"",
|
||||
(1.0, 1.0),
|
||||
(1.0, 1.0),
|
||||
(1.0, 1.0),
|
||||
(1.0, 1.0),
|
||||
id="perfect_match_all_components",
|
||||
),
|
||||
pytest.param(
|
||||
"2 cups flour",
|
||||
3.0,
|
||||
"Cups",
|
||||
"flour",
|
||||
"",
|
||||
(0.0, 0.0),
|
||||
(1.0, 1.0),
|
||||
(1.0, 1.0),
|
||||
(1.0, 1.0),
|
||||
id="quantity_mismatch",
|
||||
),
|
||||
pytest.param(
|
||||
"2 cups flour",
|
||||
2.0,
|
||||
None,
|
||||
"flour",
|
||||
"",
|
||||
(1.0, 1.0),
|
||||
(0.4, 0.9),
|
||||
(1.0, 1.0),
|
||||
(1.0, 1.0),
|
||||
id="missing_unit_fallback",
|
||||
),
|
||||
pytest.param(
|
||||
"2 cups flour",
|
||||
2.0,
|
||||
"Cups",
|
||||
None,
|
||||
"",
|
||||
(1.0, 1.0),
|
||||
(1.0, 1.0),
|
||||
(0.4, 0.9),
|
||||
(1.0, 1.0),
|
||||
id="missing_food_fallback",
|
||||
),
|
||||
pytest.param(
|
||||
"2 cups flour sifted fresh",
|
||||
2.0,
|
||||
"Cups",
|
||||
"flour",
|
||||
"sifted fresh",
|
||||
(1.0, 1.0),
|
||||
(1.0, 1.0),
|
||||
(1.0, 1.0),
|
||||
(0.8, 1.0),
|
||||
id="note_full_match",
|
||||
),
|
||||
pytest.param(
|
||||
"2 cups flour sifted",
|
||||
2.0,
|
||||
"Cups",
|
||||
"flour",
|
||||
"sifted chopped",
|
||||
(1.0, 1.0),
|
||||
(1.0, 1.0),
|
||||
(1.0, 1.0),
|
||||
(0.4, 0.6),
|
||||
id="note_partial_match",
|
||||
),
|
||||
pytest.param(
|
||||
"2 cups flour",
|
||||
2.0,
|
||||
"Cups",
|
||||
"flour",
|
||||
"chopped minced",
|
||||
(1.0, 1.0),
|
||||
(1.0, 1.0),
|
||||
(1.0, 1.0),
|
||||
(0.0, 0.0),
|
||||
id="note_no_match",
|
||||
),
|
||||
pytest.param(
|
||||
"1.5 tsp salt kosher",
|
||||
1.0,
|
||||
None,
|
||||
None,
|
||||
"kosher fine",
|
||||
(0.0, 0.0),
|
||||
(0.3, 0.7),
|
||||
(0.3, 0.7),
|
||||
(0.4, 0.6),
|
||||
id="multiple_issues",
|
||||
),
|
||||
pytest.param(
|
||||
"",
|
||||
1.0,
|
||||
"Cups",
|
||||
"flour",
|
||||
"fresh",
|
||||
(0.0, 0.0),
|
||||
(1.0, 1.0),
|
||||
(1.0, 1.0),
|
||||
(0.0, 0.0),
|
||||
id="empty_original_text",
|
||||
),
|
||||
pytest.param(
|
||||
"salt",
|
||||
0.0,
|
||||
None,
|
||||
"salt",
|
||||
"",
|
||||
(1.0, 1.0),
|
||||
(1.0, 1.0),
|
||||
(1.0, 1.0),
|
||||
(1.0, 1.0),
|
||||
id="zero_quantity_match",
|
||||
),
|
||||
],
|
||||
)
|
||||
def test_openai_parser_confidence(
|
||||
original_text: str,
|
||||
quantity: float | None,
|
||||
unit: str | None,
|
||||
food: str | None,
|
||||
note: str,
|
||||
qty_range: tuple[float, float],
|
||||
unit_range: tuple[float, float],
|
||||
food_range: tuple[float, float],
|
||||
note_range: tuple[float, float],
|
||||
unique_local_group_id: UUID4,
|
||||
parsed_ingredient_data: tuple[list[IngredientFood], list[IngredientUnit]], # required so database is populated
|
||||
):
|
||||
"""Test the _calculate_confidence method of OpenAIParser with various input scenarios."""
|
||||
|
||||
with session_context() as session:
|
||||
from mealie.services.parser_services.openai.parser import OpenAIParser
|
||||
|
||||
parser = cast(
|
||||
OpenAIParser, get_parser(RegisteredParser.openai, unique_local_group_id, session, get_locale_provider())
|
||||
)
|
||||
|
||||
# Create test ingredient
|
||||
ingredient = RecipeIngredient(
|
||||
original_text=original_text,
|
||||
quantity=quantity,
|
||||
unit=CreateIngredientUnit(name=unit) if unit else None,
|
||||
food=CreateIngredientFood(name=food) if food else None,
|
||||
note=note if note else None,
|
||||
)
|
||||
|
||||
# Calculate confidence
|
||||
confidence = parser._calculate_confidence(original_text, ingredient)
|
||||
|
||||
# All confidence values should be populated (not None) by the method
|
||||
assert confidence.quantity is not None, "Quantity confidence should not be None"
|
||||
assert confidence.unit is not None, "Unit confidence should not be None"
|
||||
assert confidence.food is not None, "Food confidence should not be None"
|
||||
assert confidence.comment is not None, "Comment confidence should not be None"
|
||||
assert confidence.average is not None, "Average confidence should not be None"
|
||||
|
||||
# Range-based assertions to handle fuzzy matching variability
|
||||
qty_min, qty_max = qty_range
|
||||
assert qty_min <= confidence.quantity <= qty_max, (
|
||||
f"Quantity confidence out of range: expected {qty_range}, got {confidence.quantity}"
|
||||
)
|
||||
|
||||
unit_min, unit_max = unit_range
|
||||
assert unit_min <= confidence.unit <= unit_max, (
|
||||
f"Unit confidence out of range: expected {unit_range}, got {confidence.unit}"
|
||||
)
|
||||
|
||||
food_min, food_max = food_range
|
||||
assert food_min <= confidence.food <= food_max, (
|
||||
f"Food confidence out of range: expected {food_range}, got {confidence.food}"
|
||||
)
|
||||
|
||||
note_min, note_max = note_range
|
||||
assert note_min <= confidence.comment <= note_max, (
|
||||
f"Note confidence out of range: expected {note_range}, got {confidence.comment}"
|
||||
)
|
||||
|
||||
# Check that average is calculated correctly
|
||||
expected_avg = (confidence.quantity + confidence.unit + confidence.food + confidence.comment) / 4
|
||||
assert abs(confidence.average - expected_avg) < 0.001, (
|
||||
f"Average confidence mismatch: expected {expected_avg}, got {confidence.average}"
|
||||
)
|
||||
Reference in New Issue
Block a user