fix(deps): update dependency ingredient-parser-nlp to v2 (#5137)

mealie/services/parser_services/ingredient_parser.py

@@ -1,3 +1,5 @@
+from fractions import Fraction
+
 from ingredient_parser import parse_ingredient
 from ingredient_parser.dataclasses import CompositeIngredientAmount, IngredientAmount
 from ingredient_parser.dataclasses import ParsedIngredient as IngredientParserParsedIngredient
@@ -54,7 +56,9 @@ class NLPParser(ABCIngredientParser):
     @staticmethod
     def _extract_amount(ingredient: IngredientParserParsedIngredient) -> IngredientAmount:
         if not (ingredient_amounts := ingredient.amount):
-            return IngredientAmount(quantity=0, quantity_max=0, unit="", text="", confidence=0, starting_index=-1)
+            return IngredientAmount(
+                quantity=Fraction(0), quantity_max=Fraction(0), unit="", text="", confidence=0, starting_index=-1
+            )
 
         ingredient_amount = ingredient_amounts[0]
         if isinstance(ingredient_amount, CompositeIngredientAmount):
@@ -67,12 +71,15 @@ class NLPParser(ABCIngredientParser):
         confidence = ingredient_amount.confidence
 
         if isinstance(ingredient_amount.quantity, str):
-            return extract_quantity_from_string(ingredient_amount.quantity)[0], confidence
+            qty = extract_quantity_from_string(ingredient_amount.quantity)[0]
         else:
             try:
-                return float(ingredient_amount.quantity), confidence
+                qty = float(ingredient_amount.quantity)
             except ValueError:
-                return 0, 0
+                qty = 0
+                confidence = 0
+
+        return qty, confidence
 
     @staticmethod
     def _extract_unit(ingredient_amount: IngredientAmount) -> tuple[str, float]:
@@ -82,8 +89,13 @@ class NLPParser(ABCIngredientParser):
 
     @staticmethod
     def _extract_food(ingredient: IngredientParserParsedIngredient) -> tuple[str, float]:
-        confidence = ingredient.name.confidence if ingredient.name else 0
+        if not ingredient.name:
-        food = str(ingredient.name.text) if ingredient.name else ""
+            return "", 0
+
+        ingredient_name = ingredient.name[0]
+        confidence = ingredient_name.confidence
+        food = ingredient_name.text
+
         return food, confidence
 
     @staticmethod

poetry.lock

@@ -733,6 +733,53 @@ typing-extensions = "*"
 [package.extras]
 test = ["pytest", "pytest-cov", "pytest-mpl", "pytest-subtests"]
 
+[[package]]
+name = "floret"
+version = "0.10.5"
+description = "floret Python bindings"
+optional = false
+python-versions = "*"
+groups = ["main"]
+files = [
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+    {file = "floret-0.10.5-cp310-cp310-macosx_11_0_x86_64.whl", hash = "sha256:f3d78f7a0da75a7d6481db1a6b6d5c495caa558f52fcaa7800b05b013518732f"},
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+    {file = "floret-0.10.5-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:7d8efe2add424b711ff6021f670498e9e0298dd92131553e52570558ec8b4c7c"},
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+    {file = "floret-0.10.5-cp39-cp39-win_amd64.whl", hash = "sha256:1f777dddfb4c2de9eec60bda92a1c4d4aea811a4d566ffe28ec4f56dacaaf139"},
+    {file = "floret-0.10.5.tar.gz", hash = "sha256:8a94654a87b3335499cd4d14532a6f947a8cc14bd3e28044d7ccf06e99084156"},
+]
+
+[package.dependencies]
+numpy = "*"
+
 [[package]]
 name = "freezegun"
 version = "1.5.1"
@@ -1031,17 +1078,18 @@ files = [
 
 [[package]]
 name = "ingredient-parser-nlp"
-version = "1.3.2"
+version = "2.0.0"
 description = "A Python package to parse structured information from recipe ingredient sentences"
 optional = false
 python-versions = "<3.14,>=3.10"
 groups = ["main"]
 files = [
-    {file = "ingredient_parser_nlp-1.3.2-py3-none-any.whl", hash = "sha256:4e9b18a977e6b93985edd5a2668e5bb4f1dd3c570374316fb7f811a21ca55523"},
+    {file = "ingredient_parser_nlp-2.0.0-py3-none-any.whl", hash = "sha256:d027d2bb2648b9ec512582bd18cc9374aacef47dc2736b350061f34fba99d80f"},
-    {file = "ingredient_parser_nlp-1.3.2.tar.gz", hash = "sha256:12f4d34717364881b828b476bd5b5f8a72c96474883b8cbe94911a39fd71e719"},
+    {file = "ingredient_parser_nlp-2.0.0.tar.gz", hash = "sha256:f1dfe810e89e6c9522b2052902359f92030d5f078b7da9f09dea67044b447f3f"},
 ]
 
 [package.dependencies]
+floret = "*"
 nltk = ">=3.9.1"
 pint = ">=0.24.4"
 python-crfsuite = "*"
@@ -1751,6 +1799,71 @@ files = [
 [package.dependencies]
 setuptools = "*"
 
+[[package]]
+name = "numpy"
+version = "2.2.3"
+description = "Fundamental package for array computing in Python"
+optional = false
+python-versions = ">=3.10"
+groups = ["main"]
+files = [
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+    {file = "numpy-2.2.3-cp313-cp313t-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:deaa09cd492e24fd9b15296844c0ad1b3c976da7907e1c1ed3a0ad21dded6f76"},
+    {file = "numpy-2.2.3-cp313-cp313t-musllinux_1_2_aarch64.whl", hash = "sha256:246535e2f7496b7ac85deffe932896a3577be7af8fb7eebe7146444680297e9a"},
+    {file = "numpy-2.2.3-cp313-cp313t-musllinux_1_2_x86_64.whl", hash = "sha256:daf43a3d1ea699402c5a850e5313680ac355b4adc9770cd5cfc2940e7861f1bf"},
+    {file = "numpy-2.2.3-cp313-cp313t-win32.whl", hash = "sha256:cf802eef1f0134afb81fef94020351be4fe1d6681aadf9c5e862af6602af64ef"},
+    {file = "numpy-2.2.3-cp313-cp313t-win_amd64.whl", hash = "sha256:aee2512827ceb6d7f517c8b85aa5d3923afe8fc7a57d028cffcd522f1c6fd082"},
+    {file = "numpy-2.2.3-pp310-pypy310_pp73-macosx_10_15_x86_64.whl", hash = "sha256:3c2ec8a0f51d60f1e9c0c5ab116b7fc104b165ada3f6c58abf881cb2eb16044d"},
+    {file = "numpy-2.2.3-pp310-pypy310_pp73-macosx_14_0_x86_64.whl", hash = "sha256:ed2cf9ed4e8ebc3b754d398cba12f24359f018b416c380f577bbae112ca52fc9"},
+    {file = "numpy-2.2.3-pp310-pypy310_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:39261798d208c3095ae4f7bc8eaeb3481ea8c6e03dc48028057d3cbdbdb8937e"},
+    {file = "numpy-2.2.3-pp310-pypy310_pp73-win_amd64.whl", hash = "sha256:783145835458e60fa97afac25d511d00a1eca94d4a8f3ace9fe2043003c678e4"},
+    {file = "numpy-2.2.3.tar.gz", hash = "sha256:dbdc15f0c81611925f382dfa97b3bd0bc2c1ce19d4fe50482cb0ddc12ba30020"},
+]
+
 [[package]]
 name = "oauthlib"
 version = "3.2.2"
@@ -3769,4 +3882,4 @@ pgsql = ["psycopg2-binary"]
 [metadata]
 lock-version = "2.1"
 python-versions = ">=3.12,<3.13"
-content-hash = "9a19a1b0f75cce3df8c69bcb8b41da14f12fc127e0d26e1a8fb0de2776666448"
+content-hash = "8dbeaaa25b196433ef250820ab9aec4306968827a0e6e06e70da1aa08bf5779d"

pyproject.toml

@@ -54,7 +54,7 @@ pyjwt = "^2.8.0"
 openai = "^1.63.0"
 typing-extensions = "^4.12.2"
 itsdangerous = "^2.2.0"
-ingredient-parser-nlp = "^1.3.2"
+ingredient-parser-nlp = "^2.0.0"
 
 [tool.poetry.group.postgres.dependencies]
 psycopg2-binary = { version = "^2.9.1" }

tests/integration_tests/user_recipe_tests/test_recipe_ingredient_parser.py

@@ -8,7 +8,7 @@ from tests.utils.fixture_schemas import TestUser
 
 nlp_test_ingredients = [
     TestIngredient("½ cup all-purpose flour", 0.5, "cup", "all-purpose flour", ""),
-    TestIngredient("1 ½ teaspoons ground black pepper", 1.5, "teaspoon", "ground black pepper", ""),
+    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", ""),
@@ -23,14 +23,21 @@ nlp_test_ingredients = [
     ),
     TestIngredient("2 tablespoons (30ml) vegetable oil ", 2, "tablespoon", "vegetable oil", ""),
     TestIngredient("2 teaspoons salt (to taste) ", 2, "teaspoon", "salt", "to taste"),
+    TestIngredient("2 cups chicken broth or beef broth ", 2, "cup", "chicken broth", ""),
+    TestIngredient("1/2 cup", 0.5, "cup", "", ""),
 ]
 
 
 def assert_ingredient(api_response: dict, test_ingredient: TestIngredient):
-    assert api_response["ingredient"]["quantity"] == pytest.approx(test_ingredient.quantity)
+    response_quantity = api_response["ingredient"]["quantity"]
-    assert api_response["ingredient"]["unit"]["name"] == test_ingredient.unit
+    response_unit = api_response["ingredient"]["unit"]["name"] if api_response["ingredient"]["unit"] else ""
-    assert api_response["ingredient"]["food"]["name"] == test_ingredient.food
+    response_food = api_response["ingredient"]["food"]["name"] if api_response["ingredient"]["food"] else ""
-    assert api_response["ingredient"]["note"] == test_ingredient.comments
+    response_note = api_response["ingredient"]["note"]
+
+    assert response_quantity == pytest.approx(test_ingredient.quantity)
+    assert response_unit == test_ingredient.unit
+    assert response_food == test_ingredient.food
+    assert response_note == test_ingredient.comments
 
 
 @pytest.mark.parametrize("test_ingredient", nlp_test_ingredients)