Prototyp

app/models.py

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+from __future__ import annotations
+from typing import Optional
+from pydantic import BaseModel
+
+
+class Ingredient(BaseModel):
+    name: str
+    amount: Optional[str] = None
+    unit: Optional[str] = None
+    note: Optional[str] = None
+
+
+class NutritionInfo(BaseModel):
+    kcal_per_serving: Optional[float] = None
+    kcal_total: Optional[float] = None
+    servings: Optional[int] = None
+    source: str = "extracted"  # "extracted" | "usda" | "gpt4_estimate"
+
+
+class Recipe(BaseModel):
+    title: str
+    description: Optional[str] = None
+    image_url: Optional[str] = None
+    source_url: str
+    servings: Optional[int] = None
+    prep_time_minutes: Optional[int] = None
+    cook_time_minutes: Optional[int] = None
+    ingredients: list[Ingredient] = []
+    steps: list[str] = []
+    nutrition: Optional[NutritionInfo] = None
+    tags: list[str] = []
+
+
+class TandoorStep(BaseModel):
+    instruction: str
+    ingredients: list[TandoorIngredient] = []
+    time: int = 0
+
+
+class TandoorIngredient(BaseModel):
+    food: dict  # {"name": str}
+    amount: float = 0
+    unit: Optional[dict] = None  # {"name": str} or None
+    note: str = ""
+
+
+class TandoorRecipe(BaseModel):
+    name: str
+    description: str = ""
+    servings: int = 1
+    working_time: int = 0
+    source_url: str = ""
+    image: Optional[str] = None
+    steps: list[TandoorStep] = []
+    keywords: list[dict] = []
+    internal: bool = True
+    show_ingredient_overview: bool = False
+    servings_text: str = "Portionen"
+
+
+class ExtractResponse(BaseModel):
+    recipe: Recipe
+    tandoor_json: TandoorRecipe
+    history_id: Optional[int] = None
+
+
+class StatusEvent(BaseModel):
+    stage: str
+    message: str
+    progress: int
+
+
+class ErrorEvent(BaseModel):
+    message: str