app.py

from flask import Flask, request, jsonify, render_template
import requests
import os
import math
import logging

app = Flask(__name__)
app.static_folder = 'static'

# Configure logging
logging.basicConfig(level=logging.DEBUG)

# Configuration
USDA_API_ENDPOINT = "https://api.nal.usda.gov/fdc/v1"
USDA_API_KEY = os.environ.get('USDA_API_KEY')

# Error messages
INVALID_INPUT_ERROR = "Invalid input"
MISSING_REQUIRED_FIELDS_ERROR = "Missing required fields"
FAILED_TO_FETCH_NUTRIENT_DATA_ERROR = "Failed to fetch nutrient data"

@app.route('/')
def index():
    return render_template('index.html')

@app.route('/api/calculate-metrics', methods=['POST'])
def calculate_metrics():
    data = request.json
    app.logger.debug(f"Received data for calculate_metrics: {data}")
    
    required_fields = ['age', 'gender', 'heightFeet', 'heightInches', 'weight', 'targetWeight', 'waist', 'neck', 'hip', 'steps', 'standingHours']
    missing_fields = [field for field in required_fields if field not in data or data[field] is None]
    
    if missing_fields:
        app.logger.error(f"Missing required fields: {', '.join(missing_fields)}")
        return jsonify({"error": MISSING_REQUIRED_FIELDS_ERROR, "missing_fields": missing_fields}), 400

    try:
        age = int(data['age'])
        gender = data['gender']
        height_feet = int(data['heightFeet'])
        height_inches = int(data['heightInches'])
        weight = float(data['weight'])  # in kg
        target_weight = float(data['targetWeight'])  # in kg
        waist = float(data['waist'])  # in cm
        neck = float(data['neck'])  # in cm
        hip = float(data['hip'])  # in cm
        steps = int(data['steps'])
        standing_hours = float(data['standingHours'])
        
        # Convert height to cm
        height = (height_feet * 30.48) + (height_inches * 2.54)  # Convert to cm
        
    except (ValueError, KeyError) as e:
        app.logger.error(f"Invalid input: {str(e)}")
        return jsonify({"error": INVALID_INPUT_ERROR, "details": str(e)}), 400

    if age <= 0 or height <= 0 or weight <= 0 or target_weight <= 0 or waist <= 0 or neck <= 0 or hip <= 0 or steps < 0 or standing_hours < 0:
        app.logger.error("Invalid input values")
        return jsonify({"error": INVALID_INPUT_ERROR, "details": "Input values must be positive numbers"}), 400

    if gender not in ['male', 'female', 'other']:
        app.logger.error("Invalid gender")
        return jsonify({"error": INVALID_INPUT_ERROR, "details": "Gender must be 'male', 'female', or 'other'"}), 400

    # Calculate BMI
    bmi = weight / ((height / 100) ** 2)

    # Calculate body fat percentage (using U.S. Navy method)
    if gender == 'male':
        body_fat = 86.010 * math.log10(waist - neck) - 70.041 * math.log10(height) + 36.76
    elif gender == 'female':
        body_fat = 163.205 * math.log10(waist + hip - neck) - 97.684 * math.log10(height) - 78.387
    else:
        # For 'other' gender, use an average of male and female calculations
        body_fat_male = 86.010 * math.log10(waist - neck) - 70.041 * math.log10(height) + 36.76
        body_fat_female = 163.205 * math.log10(waist + hip - neck) - 97.684 * math.log10(height) - 78.387
        body_fat = (body_fat_male + body_fat_female) / 2

    # Calculate lean body mass
    lean_body_mass = weight * (1 - (body_fat / 100))

    # Calculate recommended calorie intake (using Mifflin-St Jeor Equation)
    if gender == 'male':
        bmr = 10 * weight + 6.25 * height - 5 * age + 5
    elif gender == 'female':
        bmr = 10 * weight + 6.25 * height - 5 * age - 161
    else:
        # For 'other' gender, use an average of male and female calculations
        bmr_male = 10 * weight + 6.25 * height - 5 * age + 5
        bmr_female = 10 * weight + 6.25 * height - 5 * age - 161
        bmr = (bmr_male + bmr_female) / 2

    # Adjust for activity level
    activity_factor = 1.2 + (steps / 10000) * 0.1 + (standing_hours / 24) * 0.1
    recommended_calories = bmr * activity_factor

    # Calculate time to reach target weight
    weight_difference = abs(weight - target_weight)
    daily_calorie_deficit = 500  # Assuming a 500 calorie deficit per day
    days_to_target = (weight_difference * 7700) / daily_calorie_deficit  # 7700 calories ≈ 1 kg of body fat

    response = {
        'bmi': round(bmi, 2),
        'bodyFatPercentage': round(body_fat, 2),
        'leanBodyMass': round(lean_body_mass, 2),
        'recommendedCalories': round(recommended_calories),
        'timeToTargetWeight': f"{round(days_to_target)} days"
    }

    app.logger.debug(f"Calculated metrics: {response}")
    return jsonify(response)

@app.route('/api/personalized-recommendations', methods=['POST'])
def get_personalized_recommendations():
    data = request.json
    app.logger.debug(f"Received data for personalized_recommendations: {data}")

    required_fields = ['age', 'gender', 'height', 'weight', 'targetWeight', 'bmi', 'bodyFatPercentage', 'recommendedCalories', 'steps', 'standingHours']
    missing_fields = [field for field in required_fields if field not in data or data[field] is None]
    if missing_fields:
        app.logger.error(f"Missing required fields: {', '.join(missing_fields)}")
        return jsonify({"error": MISSING_REQUIRED_FIELDS_ERROR, "missing_fields": missing_fields}), 400

    try:
        age = int(data['age'])
        gender = data['gender']
        height = float(data['height'])
        weight = float(data['weight'])
        target_weight = float(data['targetWeight'])
        bmi = float(data['bmi'])
        body_fat_percentage = float(data['bodyFatPercentage'])
        recommended_calories = int(data['recommendedCalories'])
        steps = int(data['steps'])
        standing_hours = float(data['standingHours'])
    except (ValueError, KeyError) as e:
        app.logger.error(f"Invalid input: {str(e)}")
        return jsonify({"error": INVALID_INPUT_ERROR, "details": str(e)}), 400

    # Diet recommendations
    diet_recommendations = []
    if bmi < 18.5:
        diet_recommendations.append("Increase calorie intake with nutrient-dense foods to reach a healthy weight")
        diet_recommendations.append("Focus on foods high in healthy fats, such as avocados, nuts, and olive oil")
        diet_recommendations.append("Incorporate protein-rich foods like lean meats, fish, eggs, and legumes")
    elif 18.5 <= bmi < 25:
        diet_recommendations.append("Maintain a balanced diet with a focus on whole foods")
        diet_recommendations.append("Ensure adequate intake of fruits, vegetables, whole grains, and lean proteins")
        diet_recommendations.append("Monitor portion sizes to maintain your healthy weight")
    elif 25 <= bmi < 30:
        diet_recommendations.append("Slightly reduce calorie intake and focus on nutrient-dense, low-calorie foods")
        diet_recommendations.append("Increase fiber intake through vegetables, fruits, and whole grains")
        diet_recommendations.append("Choose lean proteins and limit saturated fats")
    else:
        diet_recommendations.append("Reduce calorie intake and focus on whole, unprocessed foods")
        diet_recommendations.append("Prioritize vegetables, lean proteins, and complex carbohydrates")
        diet_recommendations.append("Avoid sugary drinks and high-calorie snacks")

    if (gender == 'male' and body_fat_percentage > 25) or (gender == 'female' and body_fat_percentage > 32) or (gender == 'other' and body_fat_percentage > 28):
        diet_recommendations.append("Increase protein intake to support lean muscle mass")
        diet_recommendations.append("Consider adding a protein shake or Greek yogurt as a snack")
        diet_recommendations.append("Include more fish, chicken, turkey, or plant-based proteins in your meals")

    diet_recommendations.append(f"Aim for {recommended_calories} calories per day")
    diet_recommendations.append("Include a variety of colorful fruits and vegetables in your diet")
    diet_recommendations.append("Stay hydrated by drinking at least 8 glasses of water daily")
    diet_recommendations.append("Limit processed foods and choose whole grains over refined grains")

    if weight > target_weight:
        diet_recommendations.append("Create a calorie deficit of 500 calories per day to lose weight")
        diet_recommendations.append("Use smaller plates to help control portion sizes")
        diet_recommendations.append("Start meals with a salad or vegetable soup to increase satiety")
    elif weight < target_weight:
        diet_recommendations.append("Increase your calorie intake by 500 calories per day to gain weight")
        diet_recommendations.append("Add healthy, calorie-dense foods like nuts, seeds, and dried fruits to your meals")
        diet_recommendations.append("Consider drinking smoothies made with fruits, oats, and protein powder")
    else:
        diet_recommendations.append("Maintain your current calorie intake to maintain your weight")
        diet_recommendations.append("Practice mindful eating and listen to your body's hunger and fullness cues")

    # Exercise recommendations
    exercise_recommendations = []
    if steps < 5000:
        exercise_recommendations.append("Gradually increase your daily step count to at least 7,500 steps")
        exercise_recommendations.append("Take short walks during breaks or after meals")
        exercise_recommendations.append("Use stairs instead of elevators when possible")
    elif 5000 <= steps < 10000:
        exercise_recommendations.append("Aim to reach 10,000 steps per day for better health")
        exercise_recommendations.append("Try brisk walking or light jogging to increase step count")
        exercise_recommendations.append("Consider using a treadmill desk or walking meetings")
    else:
        exercise_recommendations.append("Great job on your step count! Consider adding more intense exercises")
        exercise_recommendations.append("Incorporate interval training or hill walks to challenge yourself")
        exercise_recommendations.append("Set new step goals to maintain motivation")

    if standing_hours < 2:
        exercise_recommendations.append("Try to increase your standing time to at least 2-4 hours per day")
        exercise_recommendations.append("Use a standing desk or elevate your workstation for part of the day")
        exercise_recommendations.append("Take phone calls while standing or walking")
    elif 2 <= standing_hours < 4:
        exercise_recommendations.append("Good job on standing! Aim to increase your standing time to 4-6 hours per day")
        exercise_recommendations.append("Alternate between sitting and standing every 30-60 minutes")
        exercise_recommendations.append("Try gentle exercises or stretches while standing")
    else:
        exercise_recommendations.append("Excellent standing habits! Maintain your current standing routine")
        exercise_recommendations.append("Incorporate balance exercises or yoga poses while standing")
        exercise_recommendations.append("Consider a treadmill desk for light walking while working")

    exercise_recommendations.append("Include strength training exercises at least 2-3 times per week")
    exercise_recommendations.append("Aim for at least 150 minutes of moderate-intensity aerobic activity per week")
    exercise_recommendations.append("Don't forget to stretch before and after exercises to improve flexibility")

    if weight > target_weight:
        exercise_recommendations.append("Incorporate high-intensity interval training (HIIT) to boost fat burning")
        exercise_recommendations.append("Try circuit training to combine strength and cardio exercises")
        exercise_recommendations.append("Consider joining group fitness classes for motivation and guidance")
    elif weight < target_weight:
        exercise_recommendations.append("Focus on compound exercises and progressive overload to build muscle mass")
        exercise_recommendations.append("Incorporate resistance band exercises for muscle growth")
        exercise_recommendations.append("Ensure adequate rest between workouts for muscle recovery and growth")
    else:
        exercise_recommendations.append("Mix cardio and strength training to maintain your current weight and improve overall fitness")
        exercise_recommendations.append("Try new activities or sports to keep your routine interesting")
        exercise_recommendations.append("Set performance-based goals to stay motivated")

    if age > 50:
        exercise_recommendations.append("Include balance and flexibility exercises to maintain mobility")
        exercise_recommendations.append("Consider low-impact activities like swimming or cycling to protect joints")

    response = {
        'dietRecommendations': diet_recommendations,
        'exerciseRecommendations': exercise_recommendations
    }

    app.logger.debug(f"Generated recommendations: {response}")
    return jsonify(response)

@app.route('/api/search-food', methods=['GET'])
def search_food():
    query = request.args.get('query', '')
    if not query:
        return jsonify({"error": "Missing query parameter"}), 400

    try:
        response = requests.get(
            f"{USDA_API_ENDPOINT}/foods/search",
            params={
                "api_key": USDA_API_KEY,
                "query": query,
                "dataType": ["Survey (FNDDS)"],
                "pageSize": 10
            }
        )
        response.raise_for_status()
        data = response.json()

        results = []
        for food in data.get('foods', []):
            nutrients = {nutrient['nutrientName']: nutrient['value'] for nutrient in food.get('foodNutrients', [])}
            results.append({
                'description': food['description'],
                'calories': nutrients.get('Energy', 0),
                'protein': nutrients.get('Protein', 0),
                'carbs': nutrients.get('Carbohydrate, by difference', 0),
                'fat': nutrients.get('Total lipid (fat)', 0)
            })

        return jsonify(results)

    except requests.RequestException as e:
        app.logger.error(f"Error fetching food data: {str(e)}")
        return jsonify({"error": "Failed to fetch food data"}), 500

if __name__ == '__main__':
    app.run(host='0.0.0.0', port=7860, debug=True)