add nutrition_model

models-server/models/nutrition_model.py

@@ -1,94 +1,96 @@
-import random 
+import random
 import pandas as pd
-import numpy as np 
+import numpy as np
 import pickle
-import sys
 import os
-import pickle
 
 SERVER_FILE_DIR = os.path.dirname(os.path.abspath(__file__))
-NUTRITION_MODEL_PATH = os.path.join(
-    SERVER_FILE_DIR, *"../resources/models/nutrition_model.pkl".split("/")
-)
+NUTRITION_MODEL_PATH = os.path.join(SERVER_FILE_DIR, "../resources/models/nutrition_model.pkl")
+MEALS_JSON_PATH = os.path.join(SERVER_FILE_DIR, "../../src/resources/meals.json")
+
+# Ensure the file exists
+if not os.path.exists(MEALS_JSON_PATH):
+    raise FileNotFoundError(f"File {MEALS_JSON_PATH} does not exist")
 
+df = pd.read_json(MEALS_JSON_PATH)
 
 class NutritionModel:
-    def generate_plan(self,calories):
-        the_model = self.nutrition_model
-        lunch_attr = {"Calories":calories*0.5, 
-        "FatContent":random.uniform(19, 97), 
-        "SaturatedFatContent":random.uniform(6, 12), 
-        "CholesterolContent": random.uniform(77, 299), 
-        "SodiumContent":random.uniform(565, 2299), 
-        "CarbohydrateContent":random.uniform(28, 317), 
-        "FiberContent": random.uniform(2, 38), 
-        "SugarContent": random.uniform(0, 38),
-        "ProteinContent":random.uniform(20, 123)}
+    def __init__(self):
+        self.load()
+
+    def generate_plan(self, calories):
+        lunch_attr = {
+            "Calories": calories * 0.5,
+            "FatContent": random.uniform(19, 97),
+            "SaturatedFatContent": random.uniform(6, 12),
+            "CholesterolContent": random.uniform(77, 299),
+            "SodiumContent": random.uniform(565, 2299),
+            "CarbohydrateContent": random.uniform(28, 317),
+            "FiberContent": random.uniform(2, 38),
+            "SugarContent": random.uniform(0, 38),
+            "ProteinContent": random.uniform(20, 123)
+        }
         
         lunch_df = pd.DataFrame(lunch_attr, index=[0])
         
-        breakfast_attr = {"Calories":calories*0.30, 
-        "FatContent":random.uniform(8.7, 20), 
-        "SaturatedFatContent":random.uniform(1.7, 3.7), 
-        "CholesterolContent": random.uniform(0, 63), 
-        "SodiumContent":random.uniform(163, 650), 
-        "CarbohydrateContent":random.uniform(23, 56), 
-        "FiberContent": random.uniform(2.6, 8), 
-        "SugarContent": random.uniform(3.5, 13),
-        "ProteinContent":random.uniform(6, 25)}
+        breakfast_attr = {
+            "Calories": calories * 0.30,
+            "FatContent": random.uniform(8.7, 20),
+            "SaturatedFatContent": random.uniform(1.7, 3.7),
+            "CholesterolContent": random.uniform(0, 63),
+            "SodiumContent": random.uniform(163, 650),
+            "CarbohydrateContent": random.uniform(23, 56),
+            "FiberContent": random.uniform(2.6, 8),
+            "SugarContent": random.uniform(3.5, 13),
+            "ProteinContent": random.uniform(6, 25)
+        }
         
         breakfast_df = pd.DataFrame(breakfast_attr, index=[0])
         
-        dinner_attr = {"Calories":calories*0.30, 
-        "FatContent":random.uniform(15, 33), 
-        "SaturatedFatContent":random.uniform(6, 8), 
-        "CholesterolContent": random.uniform(22, 86), 
-        "SodiumContent":random.uniform(265, 775), 
-        "CarbohydrateContent":random.uniform(14, 44), 
-        "FiberContent": random.uniform(101, 110), 
-        "SugarContent": random.uniform(3, 13),
-        "ProteinContent":random.uniform(11, 25)}
+        dinner_attr = {
+            "Calories": calories * 0.30,
+            "FatContent": random.uniform(8.7, 20),
+            "SaturatedFatContent": random.uniform(1.7, 3.7),
+            "CholesterolContent": random.uniform(0, 63),
+            "SodiumContent": random.uniform(163, 650),
+            "CarbohydrateContent": random.uniform(23, 56),
+            "FiberContent": random.uniform(2.6, 8),
+            "SugarContent": random.uniform(3.5, 13),
+            "ProteinContent": random.uniform(6, 25)
+        }
         
         dinner_df = pd.DataFrame(dinner_attr, index=[0])
         
-        snack_attr = {"Calories":random.uniform(90, 190), 
-        "FatContent":random.uniform(1.7, 10), 
-        "SaturatedFatContent":random.uniform(0.7, 3), 
-        "CholesterolContent": random.uniform(2, 16), 
-        "SodiumContent":random.uniform(47, 200), 
-        "CarbohydrateContent":random.uniform(10, 31), 
-        "FiberContent": random.uniform(0.4, 2.5), 
-        "SugarContent": random.uniform(5.7, 21),
-        "ProteinContent":random.uniform(3, 20)}
+        snack_attr = {
+            "Calories": random.uniform(90, 190),
+            "FatContent": random.uniform(1.7, 10),
+            "SaturatedFatContent": random.uniform(0.7, 3),
+            "CholesterolContent": random.uniform(2, 16),
+            "SodiumContent": random.uniform(47, 200),
+            "CarbohydrateContent": random.uniform(10, 31),
+            "FiberContent": random.uniform(0.4, 2.5),
+            "SugarContent": random.uniform(5.7, 21),
+            "ProteinContent": random.uniform(3, 20)
+        }
         
         snack_df = pd.DataFrame(snack_attr, index=[0])
         
-        drinks_attr = {"Calories":random.uniform(60, 125), 
-        "FatContent":random.uniform(0.2, 0.6), 
-        "SaturatedFatContent":random.uniform(0, 0.1), 
-        "CholesterolContent": random.uniform(0, 0.1), 
-        "SodiumContent":random.uniform(3.5, 51), 
-        "CarbohydrateContent":random.uniform(14, 30), 
-        "FiberContent": random.uniform(0.2, 3.6), 
-        "SugarContent": random.uniform(109, 122),
-        "ProteinContent":random.uniform(0.4, 6)}
-        
-        drink_df = pd.DataFrame(drinks_attr, index=[0])
-        
-        lunch = the_model.transform(lunch_df)
-        breakfast = the_model.transform(breakfast_df)
-        dinner = the_model.transform(dinner_df)
-        snack = the_model.transform(snack_df)
-        drink = the_model.transform(drink_df)
+        lunch = self.nutrition_model.transform(lunch_df)
+        breakfast = self.nutrition_model.transform(breakfast_df)
+        dinner = self.nutrition_model.transform(dinner_df)
+        snack = self.nutrition_model.transform(snack_df)
 
-        meals = np.concatenate((breakfast, lunch, dinner, snack, drink), axis=0)
+        meals = np.concatenate((breakfast, lunch, dinner, snack), axis=0)
         meals = np.transpose(meals)
-        
-        return meals
-    
 
-    def load(self):
+        days = []
+        for i in range(7):
+            day_meals = df.iloc[meals[i]].to_dict(orient="records")
+            days.append(day_meals)
 
+        return days
+
+    def load(self):
         with open(NUTRITION_MODEL_PATH, "rb") as f:
             self.nutrition_model = pickle.load(f)
 

models-server/server.py

@@ -55,8 +55,7 @@ def nutrition_predict():
         if value is None:
             return jsonify({"error": f"{paramName} is missing"}), 400
         params[paramName] = value
-    print("nutrition_model", nutrition_model.generate_plan(**params), type(nutrition_model.generate_plan(**params)))
-    return jsonify({"result": list(nutrition_model.generate_plan(**params))})
+    return jsonify({"result": nutrition_model.generate_plan(**params)})
 
 
 if __name__ == "__main__":

src/common/models/meal-plan.model.ts

@@ -16,6 +16,7 @@ export interface IMealPlan {
     day_number: number;
     meals: mongoose.Types.ObjectId[];
   }[];
+  aiGenerated: boolean;
 }
 
 const mealPlanSchema = new Schema({
@@ -36,6 +37,7 @@ const mealPlanSchema = new Schema({
       ],
     },
   ],
+  aiGenerated: { type: Boolean, required: true, default: false },
 });
 
 

src/lib/models/nutrition_model.ts

@@ -0,0 +1,46 @@
+import { config } from "@configs/config";
+
+const endpoint = '/nutrition';
+
+// Define the structure of a Nutrition Prediction Item
+export interface INutritionPredictionItem {
+  Calories: number;
+  CarbohydrateContent: number;
+  FatContent: number;
+  Images: string[];
+  Name: string;
+  ProteinContent: number;
+  RecipeIngredientParts: string[];
+  RecipeInstructions: string[];
+  type: string;
+}
+
+export interface INParams {
+  calories: number
+}
+
+export class NutritionModel {
+  public static async predictMealPlan(
+    params: INParams
+  ): Promise<INutritionPredictionItem[][]> {
+    const response = await fetch(
+      `${config.modelsServerUrl}${endpoint}`,
+      {
+        method: "POST",
+        headers: {
+          "Content-Type": "application/json",
+        },
+        body: JSON.stringify(params),
+      }
+    );
+
+    if (!response.ok) {
+      console.error(await response.text());
+      throw new Error("Failed to fetch data from the server");
+    }
+
+    return response.json().then((data) => {
+      return data.result as INutritionPredictionItem[][];
+    });
+  }
+}

src/modules/users/modules/meal-plans/controller/meal-plans.controller.ts

@@ -23,6 +23,7 @@ export class UsersMealPlansController extends BaseController {
 
   setRoutes(): void {
     this.router.get("/", asyncHandler(this.list));
+    this.router.get("/ss", asyncHandler(this.ss));
   }
 
   @SwaggerGet()
@@ -48,4 +49,27 @@ export class UsersMealPlansController extends BaseController {
       res
     );
   };
+
+  @SwaggerGet("/ss")
+  ss = async (req: Request, res: Response) => {
+    let pMealPlan = await this.mealPlansService.createModelMealPlan({
+      id: "664a4b170da4e428849859a0",
+      name: "User 0",
+      email: "[email protected]",
+      image: "https://placehold.co/300x400",
+      role: "user" as any,
+      gender: "male" as any,
+      dob: new Date("1990-01-31T22:00:00.000+00:00"),
+      height: 170,
+      weight: 70,
+      fitness_level: "beginner" as any,
+    });
+  
+    return JsonResponse.success(
+      {
+        data: { pMealPlan: pMealPlan},
+      },
+      res
+    );
+  };
 }

src/modules/users/modules/meal-plans/services/meal-plans.service.ts

@@ -1,4 +1,73 @@
 import { MealPlan } from "@common/models/meal-plan.model";
 import { CrudService } from "@lib/services/crud.service";
+import { NutritionModel, INParams, INutritionPredictionItem } from "@lib/models/nutrition_model";
+import { calcAge } from "@lib/utils/age";
+import { MealsService } from "../../meals/services/meals.service";
+import { UserRegisteredMealPlansService } from "../../user-registered-meal-plans/services/user-registered-meal-plans.service";
 
-export class MealPlansService extends CrudService(MealPlan) {}
+export class MealPlansService extends CrudService(MealPlan) {
+    private mealsService = new MealsService();
+    private userRegisteredMealPlansService = new UserRegisteredMealPlansService();
+
+    public async createModelMealPlan(user: any) {
+        let caloriesPerDay = 0;
+        if (user.gender === "male") {
+            caloriesPerDay = 10 * user.weight + 6.25 * user.height - 5 * calcAge(user.dob) + 5;
+        } else {
+            caloriesPerDay = 10 * user.weight + 6.25 * user.height - 5 * calcAge(user.dob) - 161;
+        }
+
+        const params: INParams = {
+            calories: caloriesPerDay,
+        };
+
+        let pMealPlan: INutritionPredictionItem[][] = [];
+        for (let i = 0; i < 4; i++) {
+            const mealPlanChunk = await NutritionModel.predictMealPlan(params);
+            pMealPlan = pMealPlan.concat(mealPlanChunk);
+        }
+
+        const mealsNames = pMealPlan.flat().map((meal) => meal.Name);
+        const meals = await this.mealsService.listAll({ name: { $in: mealsNames } });
+
+        const mealPlan = await this.create({
+            aiGenerated: true,
+            image: "https://placehold.co/300x400",
+            description: `AI Generated Meal Plan (${new Date().toLocaleDateString()})`,
+            duration: 28,
+            level: user.fitness_level,
+            your_journey: `Welcome to your personalized meal plan journey! As someone with a ${user.fitness_level} fitness level, this plan is tailored to meet your specific needs.`,
+            key_features: [
+                {
+                    title: "Balanced Nutrition",
+                    description: `Each meal provides a well-balanced mix of nutrients to support your health goals.`,
+                },
+                {
+                    title: "Customizable Meals",
+                    description: `Meals can be adjusted to fit your dietary preferences.`,
+                },
+                {
+                    title: "Easy to Prepare",
+                    description: `All meals are designed to be quick and easy to prepare.`,
+                },
+                {
+                    title: "Variety and Flavor",
+                    description: `Enjoy a diverse range of delicious meals.`,
+                },
+            ],
+            days: pMealPlan.map((day, i) => ({
+                day_number: i + 1,
+                meals: day.map((m) => meals.find((meal) => meal.name === m.Name)?._id),
+            })),
+        });
+
+        await this.userRegisteredMealPlansService.createForUser(
+            {
+                MealPlan: mealPlan._id,
+            },
+            user._id
+        );
+
+        return mealPlan;
+    }
+}

src/modules/users/modules/user-registered-meal-plans/services/user-registered-meal-plans.service.ts

@@ -2,10 +2,12 @@ import { UserRegisteredMealPlan } from "@common/models/user-registered-meal-plan
 import { CrudService } from "@lib/services/crud.service";
 import { MealPlansService } from "../../meal-plans/services/meal-plans.service";
 import { HttpError } from "@lib/error-handling/http-error";
+import { MealPlan } from "@common/models/meal-plan.model";
+
 
 
 export class UserRegisteredMealPlansService extends CrudService(UserRegisteredMealPlan) {
-  private mealPlansService: MealPlansService = new MealPlansService();
+  private mealPlansService = new (CrudService(MealPlan))()
 
   async unregisterCurrentMealPlan(userId: string) {
     return await this.updateMany({

src/modules/users/modules/workouts/controllers/workouts.controller.ts

@@ -49,13 +49,7 @@ export class UsersWorkoutController extends BaseController {
     }
 
     const { docs, paginationData } = await this.workoutsService.list(
-      {
-        ...filter,
-        $or: [
-          { aiGenerated: true, created_by: req.jwtPayload.id },
-          { aiGenerated: false },
-        ],
-      },
+      filter,
       paginationQuery
     );
 

src/modules/users/modules/workouts/services/workouts.service.ts

@@ -7,11 +7,7 @@ import { calcAge } from "@lib/utils/age";
 import { ExerciseService } from "../../exercises/services/exercises.service";
 import { UserRegisteredWorkoutsService } from "../../user-registered-workouts/services/user-registered-workouts.service";
 
-export class WorkoutService extends CrudService(Workout, {
-  defaultFilter: {
-    aiGenerated: false,
-  },
-}) {
+export class WorkoutService extends CrudService(Workout) {
   private exerciseService = new ExerciseService();
   private userRegisteredWorkoutsService = new UserRegisteredWorkoutsService();