feat: OpenAI Ingredient Parsing (#3581)

tests/unit_tests/test_ingredient_parser.py

@@ -1,3 +1,5 @@
+import asyncio
+import json
 import shutil
 from dataclasses import dataclass
 from fractions import Fraction
@@ -20,10 +22,11 @@ from mealie.schema.recipe.recipe_ingredient import (
     SaveIngredientUnit,
 )
 from mealie.schema.user.user import GroupBase
+from mealie.services.openai import OpenAIService
 from mealie.services.parser_services import RegisteredParser, get_parser
 from mealie.services.parser_services.crfpp.processor import CRFIngredient, convert_list_to_crf_model
+from mealie.services.parser_services.openai.parser import OpenAIIngredient, OpenAIIngredients
 from tests.utils.factories import random_int, random_string
-from tests.utils.fixture_schemas import TestUser
 
 
 @dataclass
@@ -223,8 +226,9 @@ def test_brute_parser(
     comment: str,
 ):
     with session_context() as session:
+        loop = asyncio.get_event_loop()
         parser = get_parser(RegisteredParser.brute, unique_local_group_id, session)
-        parsed = parser.parse_one(input)
+        parsed = loop.run_until_complete(parser.parse_one(input))
         ing = parsed.ingredient
 
         if ing.quantity:
@@ -430,3 +434,43 @@ def test_parser_ingredient_match(
             assert parsed_ingredient.ingredient.unit is None or isinstance(
                 parsed_ingredient.ingredient.unit, CreateIngredientUnit
             )
+
+
+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) -> str | None:
+        inputs = json.loads(message)
+        data = OpenAIIngredients(
+            ingredients=[
+                OpenAIIngredient(
+                    input=input,
+                    confidence=1,
+                    quantity=random_int(0, 10),
+                    unit=random_string(),
+                    food=random_string(),
+                    note=random_string(),
+                )
+                for input in inputs
+            ]
+        )
+        return data.model_dump_json()
+
+    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)
+
+        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