Add AI-powered nutrition and plan modules

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.

backend/app/ai/plans.py

@@ -0,0 +1,34 @@
+import dspy
+from pydantic import BaseModel, Field
+
+
+class PlanOutput(BaseModel):
+    reasoning: str = Field(description="Reasoning behind the selected plan based on user goals")
+    title: str = Field(description="Title of the plan")
+    summary: str = Field(description="Brief summary of the plan")
+    diet_plan: list[str] = Field(description="List of daily diet recommendations")
+    exercise_plan: list[str] = Field(description="List of daily exercise routines")
+    tips: list[str] = Field(description="Additional health tips")
+
+
+class GeneratePlan(dspy.Signature):
+    """Generate a personalized diet and exercise plan based on user goal and details.
+
+    Analyze the user's profile and goal, explain your reasoning, and then generate the plan.
+    """
+
+    user_profile: str = dspy.InputField(desc="User details (age, weight, height, etc)")
+    goal: str = dspy.InputField(desc="Specific user goal")
+    plan: PlanOutput = dspy.OutputField(desc="Structured plan with reasoning")
+
+
+class PlanModule(dspy.Module):
+    def __init__(self):
+        super().__init__()
+        self.generate = dspy.ChainOfThought(GeneratePlan)
+
+    def forward(self, user_profile: str, goal: str):
+        return self.generate(user_profile=user_profile, goal=goal)
+
+
+plan_module = PlanModule()