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https://github.com/escalante29/healthy-fit.git
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184c8330a7
Introduces DSPy-based nutrition and plan generation modules, including image analysis for nutritional info and personalized diet/exercise plans. Adds new API endpoints for health metrics/goals, nutrition image analysis, and plan management. Updates models, schemas, and backend structure to support these features, and includes initial training data and configuration for prompt optimization.
31 lines
1011 B
Python
31 lines
1011 B
Python
from datetime import datetime
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from typing import Dict, List, Optional
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from pgvector.sqlalchemy import Vector
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from sqlalchemy import Column
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from sqlmodel import JSON, Field, SQLModel
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class FoodItem(SQLModel, table=True):
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id: Optional[int] = Field(default=None, primary_key=True)
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name: str = Field(index=True)
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calories: float
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protein: float
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carbs: float
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fats: float
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micros: Dict = Field(default={}, sa_column=Column(JSON))
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embedding: List[float] = Field(sa_column=Column(Vector(1536))) # OpenAI embedding size
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class FoodLog(SQLModel, table=True):
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id: Optional[int] = Field(default=None, primary_key=True)
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user_id: int = Field(foreign_key="user.id")
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food_item_id: Optional[int] = Field(default=None, foreign_key="fooditem.id")
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name: str # In case no food item is linked or custom entry
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calories: float
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protein: float
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carbs: float
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fats: float
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image_url: Optional[str] = None
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timestamp: datetime = Field(default_factory=datetime.utcnow)
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