app.py

# ==============================================================================
# ENHANCED APP: AI-Powered Fitness Coach
# ==============================================================================
#
# Author: Your Name (Originally by [Original Author Name])
# Bootcamp: GenAI Bootcamp
# Project: Showcase Project
#
# Description:
# This Gradio application serves as a multi-agent AI fitness coach. It provides
# personalized recommendations for BMI/TDEE, workout plans, and nutrition.
#
# Enhancements in this version:
#   1.  **Code Refactoring & Readability:** Improved structure, comments, and type hints.
#   2.  **AI Coach Persona:** A new "persona" layer that delivers advice in a more
#       conversational and encouraging tone, simulating a real coach.
#   3.  **Improved UI/UX:** More polished Markdown outputs for a better user experience.
#   4.  **Modular & Scalable:** Clear separation of concerns between data calculation
#       (helpers), plan generation (agents), and user interface (Gradio).
#   5.  **Educational Comments:** Added comments to explain key concepts and formulas,
#       useful for the project presentation.
#
# ==============================================================================

import gradio as gr
from typing import List, Literal, Tuple

# ==============================================================================
# SECTION 1: CONFIGURATION & CONSTANTS
# ==============================================================================

# --- Motivation Banner (JavaScript) ---
# This JS snippet rotates motivational quotes in the UI to keep users engaged.
MOTIVATION_JS = """
<div id="motivation" class="motivation">Let’s begin strong! 🚀</div>
<script>
  const MOTIVATION = [
    "You’re doing great—one step at a time! 💪",
    "Small habits, big results. Keep going. 🔁",
    "Hydrate and move—your future self thanks you. 💧",
    "Form first, weight second. You’ve got this. 🧠",
    "Consistency beats intensity. Show up today. ✅",
  ];
  let i = 0;
  function tick(){
    const el = document.getElementById("motivation");
    if (!el) return;
    el.textContent = MOTIVATION[i % MOTIVATION.length];
    i++;
  }
  tick();
  setInterval(tick, 10000);
</script>
"""

# --- Activity Level Multipliers ---
# These values are used to calculate TDEE based on the Mifflin-St Jeor formula.
ACTIVITY_MULTIPLIERS = {
    "Sedentary (office/no exercise)": 1.2,
    "Light (1-3x/wk)": 1.375,
    "Moderate (3-5x/wk)": 1.55,
    "Active (6-7x/wk)": 1.725,
    "Athlete (2x/day)": 1.9,
}

# --- Nutrition Constants ---
PROTEIN_PER_KG = 1.6   # g/kg, a good starting point for muscle synthesis
FAT_MIN_G_PER_KG = 0.6 # g/kg, essential for hormonal function

# --- Default Food Options ---
# These lists provide a baseline for the meal planner if the user doesn't specify preferences.
DEFAULT_FOODS = {
    "proteins": ["chicken breast", "eggs", "tuna", "lean beef", "laban protein", "tofu"],
    "carbs": ["rice", "oats", "potatoes", "pasta", "whole-wheat bread", "dates", "fruit"],
    "fats": ["olive oil", "avocado", "nuts", "tahini", "peanut butter"],
    "veggies": ["salad mix", "cucumber", "tomato", "broccoli", "spinach"],
}

# ==============================================================================
# SECTION 2: CORE HELPER FUNCTIONS
# (These functions perform the core calculations for fitness metrics.)
# ==============================================================================

def calculate_bmi(height_cm: float, weight_kg: float) -> float:
    """Calculates Body Mass Index (BMI)."""
    if height_cm <= 0 or weight_kg <= 0:
        return 0.0
    height_m = height_cm / 100.0
    return round(weight_kg / (height_m ** 2), 2)

def get_bmi_category(bmi: float) -> str:
    """Returns the BMI category string based on the BMI value."""
    if bmi <= 0: return "Invalid inputs"
    if bmi < 18.5: return "Underweight"
    if bmi < 25:   return "Normal"
    if bmi < 30:   return "Overweight"
    return "Obese"

def calculate_bmr_mifflin(sex: Literal["male", "female"], age: int, height_cm: float, weight_kg: float) -> float:
    """Calculates Basal Metabolic Rate (BMR) using the Mifflin-St Jeor equation."""
    # The Mifflin-St Jeor equation is considered more accurate than the older Harris-Benedict formula.
    s_offset = 5 if sex == "male" else -161
    return (10 * weight_kg) + (6.25 * height_cm) - (5 * age) + s_offset

def calculate_tdee(sex: str, age: int, height_cm: float, weight_kg: float, activity: str) -> Tuple[int, int, int]:
    """Calculates Total Daily Energy Expenditure (TDEE) and target calories."""
    bmr = calculate_bmr_mifflin(sex, age, height_cm, weight_kg)
    factor = ACTIVITY_MULTIPLIERS.get(activity, 1.2)
    maintenance_calories = round(bmr * factor)
    # Gentle fat loss (-500 kcal) and lean bulk (+300 kcal) are common, sustainable targets.
    cut_calories = maintenance_calories - 500
    bulk_calories = maintenance_calories + 300
    return maintenance_calories, cut_calories, bulk_calories

def calculate_water_intake(weight_kg: float) -> int:
    """Estimates daily water intake based on body weight."""
    # A common guideline is 35 ml of water per kg of body weight.
    return int(weight_kg * 35)

def calculate_macros(weight_kg: float, calories: int) -> Tuple[int, int, int]:
    """Calculates macronutrient split (Protein, Carbs, Fat) for a given calorie target."""
    protein_g = int(round(PROTEIN_PER_KG * weight_kg))
    fat_g = int(round(FAT_MIN_G_PER_KG * weight_kg))
    calories_from_protein = protein_g * 4
    calories_from_fat = fat_g * 9
    remaining_calories = calories - calories_from_protein - calories_from_fat
    carbs_g = max(0, int(round(remaining_calories / 4)))
    return protein_g, carbs_g, fat_g



def filter_foods(options: List[str], avoid: List[str]) -> List[str]:
    """Filters a list of food options based on a list of items to avoid."""
    avoid_set = {a.strip().lower() for a in avoid if a.strip()}
    res = []
    for o in options:
        if any(bad in o.lower() for bad in avoid_set):
            continue
        res.append(o)
    return res

# --- Workout Split Definitions ---
# These define the workout routines for different goals and days.
GOAL_SPLITS = {
    "Lose fat": ["FBW", "FBW", "LISS Cardio", "Mobility"],
    "Maintain": ["Upper", "Lower", "Full Body", "HIIT/Cardio", "Mobility"],
    "Build muscle": ["Push", "Pull", "Legs", "Upper", "Lower", "Mobility"],
}

def session_template(name: str) -> List[str]:
    """Provides a compact, beginner-friendly template for a given workout session type."""
    # Equipment and level considerations can be added here for more dynamic templates.
    if name == "FBW":
        return [
            "Goblet Squat 3x8-10",
            "Push-ups (incline if needed) 3x6-10",
            "Dumbbell Row 3x10",
            "Hip Hinge (RDL/Good Morning) 3x10",
            "Plank 3x30-45s",
        ]
    if name == "Upper":
        return [
            "DB Bench Press 3x8-10",
            "One-arm Row 3x10/side",
            "DB Shoulder Press 3x10",
            "Lat Pulldown or Assisted Pull 3x8-10",
            "Facepull / Band Pull-apart 3x12-15",
        ]
    if name == "Lower":
        return [
            "Squat pattern 4x6-10",
            "Hinge pattern 3x8-10",
            "Split Squat/Lunge 3x8/leg",
            "Calf Raise 3x12-15",
            "Core: Deadbug 3x10",
        ]
    if name == "Push":
        return [
            "DB Bench Press 4x6-10",
            "Incline Push-ups 3x10",
            "DB Shoulder Press 3x8-10",
            "Lateral Raise 3x12-15",
            "Triceps Extensions 3x10-12",
        ]
    if name == "Pull":
        return [
            "Lat Pulldown / Assisted Pull-ups 4x6-10",
            "Seated Row / One-arm Row 3x10",
            "Rear Delt Raise 3x12-15",
            "DB Curl 3x10-12",
            "Back Extension 3x12",
        ]
    if name == "Legs":
        return [
            "Back/Front/Goblet Squat 4x6-10",
            "Romanian Deadlift 3x8-10",
            "Leg Press or Step-ups 3x10",
            "Hamstring Curl 3x10-12",
            "Core: Side Plank 3x30s/side",
        ]
    if name == "HIIT/Cardio":
        return ["20–25 min intervals (1 fast / 1 easy) OR 30–40 min brisk walk"]
    if name == "LISS Cardio":
        return ["30–45 min easy jog/bike/walk (Zone 2)"]
    if name == "Mobility":
        return ["15–20 min mobility + light stretching & breathing"]
    return ["Rest / Light activity (walk 6–8k steps)"]


# ==============================================================================
# SECTION 3: AGENT FUNCTIONS
# (These functions act as specialized "agents" providing fitness advice.)
# ==============================================================================

def agent_bmi_tdee(sex: str, age: int, height_cm: float, weight_kg: float, activity: str, goal: str) -> str:
    """Agent for calculating BMI, TDEE, and daily calorie targets."""
    bmi = calculate_bmi(height_cm, weight_kg)
    category = get_bmi_category(bmi)
    maintenance_cals, cut_cals, bulk_cals = calculate_tdee(sex, age, height_cm, weight_kg, activity)

    target_cals = {"Lose fat": cut_cals, "Maintain": maintenance_cals, "Build muscle": bulk_cals}[goal]
    water_ml = calculate_water_intake(weight_kg)
    water_l = round(water_ml / 1000, 1)

    coach_message = generate_coach_response("bmi_tdee", {
        "bmi": bmi, "category": category, "maintenance_cals": maintenance_cals,
        "target_cals": target_cals, "goal": goal, "water_l": water_l
    })
    return coach_message

def agent_workout(level: str, days_per_week: int, goal: str, equipment: str) -> str:
    """Agent for generating a weekly workout plan."""
    days_per_week = max(2, min(6, int(days_per_week))) # Ensure days are between 2 and 6
    base_split = GOAL_SPLITS[goal]
    workout_plan = []

    for i in range(days_per_week):
        session_name = base_split[i % len(base_split)]
        exercises = session_template(session_name)
        workout_plan.append((f"Day {i+1} — {session_name}", exercises))

    coach_message = generate_coach_response("workout", {
        "workout_plan": workout_plan, "goal": goal, "level": level, "equipment": equipment
    })
    return coach_message

def agent_nutrition(weight_kg: float, target_kcal: int, liked_csv: str, avoid_csv: str, meals: int) -> str:
    """Agent for generating a nutrition plan and macronutrient breakdown."""
    liked_foods = [x.strip() for x in liked_csv.split(",") if x.strip()]
    avoid_foods = [x.strip() for x in avoid_csv.split(",") if x.strip()]

    # Filter default foods based on user preferences and avoidances
    proteins = filter_foods((liked_foods or DEFAULT_FOODS["proteins"]), avoid_foods)
    carbs    = filter_foods(DEFAULT_FOODS["carbs"], avoid_foods)
    fats     = filter_foods(DEFAULT_FOODS["fats"], avoid_foods)
    veggies  = filter_foods(DEFAULT_FOODS["veggies"], avoid_foods)

    protein_g, carb_g, fat_g = calculate_macros(weight_kg, target_kcal)
    meals_per_day = max(1, meals)
    protein_per_meal, carb_per_meal, fat_per_meal = protein_g // meals_per_day, carb_g // meals_per_day, fat_g // meals_per_day

    sample_day_meals = [
        f"Meal {i+1}: {proteins[i % len(proteins)]} + {carbs[i % len(carbs)]} "
        f"+ {veggies[i % len(veggies)]} + {fats[i % len(fats)]}"
        for i in range(meals_per_day)
    ]

    coach_message = generate_coach_response("nutrition", {
        "target_kcal": target_kcal, "protein_g": protein_g, "carb_g": carb_g, "fat_g": fat_g,
        "protein_per_meal": protein_per_meal, "carb_per_meal": carb_per_meal, "fat_per_meal": fat_per_meal,
        "sample_day_meals": sample_day_meals, "proteins": proteins, "carbs": carbs, "fats": fats, "veggies": veggies
    })
    return coach_message

def coach_all_in_one(
    sex, age, height_cm, weight_kg, activity, goal,
    level, days, equipment,
    liked_csv, avoid_csv, meals
) -> str:
    """Combines all agents to provide a comprehensive fitness and nutrition plan."""
    # BMI & TDEE Report
    bmi_tdee_report = agent_bmi_tdee(sex, age, height_cm, weight_kg, activity, goal)

    # Calculate target calories for nutrition agent
    _, cut_cals, bulk_cals = calculate_tdee(sex, age, height_cm, weight_kg, activity)
    target_kcal_for_nutrition = {"Lose fat": cut_cals, "Maintain": calculate_tdee(sex, age, height_cm, weight_kg, activity)[0], "Build muscle": bulk_cals}[goal]

    # Workout Plan
    workout_report = agent_workout(level, days, goal, equipment)

    # Nutrition Plan
    nutrition_report = agent_nutrition(weight_kg, target_kcal_for_nutrition, liked_csv, avoid_csv, meals)

    return f"{bmi_tdee_report}\n---\n{workout_report}\n---\n{nutrition_report}"


# ==============================================================================
# SECTION 4: AI COACH PERSONA - RESPONSE GENERATION
# (This function adds a conversational layer to the output.)
# ==============================================================================

def generate_coach_response(agent_type: str, data: dict) -> str:
    """Generates a coach-like, encouraging response based on agent output.
    This adds a 'persona' to the AI, making the interaction more engaging.
    """
    if agent_type == "bmi_tdee":
        bmi = data["bmi"]
        category = data["category"]
        maintenance_cals = data["maintenance_cals"]
        target_cals = data["target_cals"]
        goal = data["goal"]
        water_l = data["water_l"]

        response = f"""### 📊 Your Fitness Snapshot, Coach!
Hey there, future fitness legend! Let's break down your numbers:

- **BMI:** `{bmi}` → **{category}**
  *Coach says:* This gives us a baseline, but remember, it's just one piece of the puzzle! We focus on overall health.
- **Maintenance Calories:** **{maintenance_cals} kcal/day**
  *Coach says:* This is your daily energy sweet spot to stay exactly where you are.
- **Target for your goal ({goal}):** **{target_cals} kcal/day**
  *Coach says:* To hit your {goal.lower()} goal, we're aiming for this calorie target. Every bite counts towards your success!
- **Water recommendation:** ~ **{water_l} L/day**
  *Coach says:* Hydration is key for energy, recovery, and overall awesomeness! Keep that water bottle close.

Great start! Let's keep this momentum going!"""

    elif agent_type == "workout":
        workout_plan = data["workout_plan"]
        goal = data["goal"]
        level = data["level"]
        equipment = data["equipment"]

        plan_md = ""
        for title, items in workout_plan:
            plan_md += f"\n**{title}**\n" + "\n".join([f"- {x}" for x in items]) + "\n"

        response = f"""### 🏋️ Your Personalized Workout Plan, Champ!
Alright, {level} athlete! Here’s your custom workout roadmap to {goal.lower()}:
{plan_md}
*Coach says:* Remember to warm up, cool down, and listen to your body. Focus on form over weight, and let's crush those goals! Rest 60–90s between sets. Aim for ~2 reps in reserve (RIR 2).

Let's get those gains!"""

    elif agent_type == "nutrition":
        target_kcal = data["target_kcal"]
        protein_g = data["protein_g"]
        carb_g = data["carb_g"]
        fat_g = data["fat_g"]
        protein_per_meal = data["protein_per_meal"]
        carb_per_meal = data["carb_per_meal"]
        fat_per_meal = data["fat_per_meal"]
        sample_day_meals = data["sample_day_meals"]
        proteins = data["proteins"]
        carbs = data["carbs"]
        fats = data["fats"]
        veggies = data["veggies"]

        sample_meals_md = chr(10).join([f"- {m}" for m in sample_day_meals])

        response = f"""### 🥗 Fuel Your Success: Your Nutrition Blueprint!
Nutrition is your secret weapon, and here’s how we’re fueling your body for **{target_kcal} kcal/day**:

- **Macros (approx.):** Protein **{protein_g} g**, Carbs **{carb_g} g**, Fat **{fat_g} g**
  *Coach says:* This balance will support your energy and recovery. Per meal, that's roughly **{protein_per_meal}/{carb_per_meal}/{fat_per_meal} g** (P/C/F).
- **Preferred foods used:** {

", ".join(proteins[:3])} …

**Sample Day:**
{sample_meals_md}

**Grocery list (starter):**
- **Protein:** {", ".join(proteins)}
- **Carbs:** {", ".join(carbs)}
- **Fats:** {", ".join(fats)}
- **Veggies:** {", ".join(veggies)}

*Coach says:* Aim for 20–30g protein per meal, load up on diverse veggies, and don't forget 1–2 pieces of fruit daily for those vital micronutrients! Let’s nourish that body!"""

    else:
        response = """### 🤔 Unrecognized Request
My apologies, coach. I'm not sure how to respond to that request yet. Let's stick to the plan!"""

    return response


# ==============================================================================
# SECTION 5: GRADIO USER INTERFACE
# (Defines the interactive web interface using Gradio.)
# ==============================================================================

with gr.Blocks(
    title="Beginner Gym Coach — Multi-Agent",
    css="""
      .motivation{
        background:#fff6e5;
        border-left:6px solid #ffa84b;
        padding:10px 14px;
        border-radius:8px;
        font-size:16px;
        margin-bottom:10px;
      }
      h3 { font-size: 1.5em; margin-top: 1em; }
      h4 { font-size: 1.2em; margin-top: 0.8em; }
      strong { color: #2E8B57; } /* A nice green for emphasis */
      /* Further styling can be added here for a more polished look */
    """
) as demo:
    gr.Markdown("## 🏋️ Beginner Gym Coach — Multi-Agent\n### Your AI-Powered Guide to a Healthier You!\nGive me your basics and I’ll coach you to success.")
    gr.HTML(MOTIVATION_JS)

    with gr.Tabs():
        # -------- BMI & TDEE Tab --------
        with gr.Tab("BMI & TDEE"):
            gr.Markdown("#### Understand your body composition and daily energy needs.")
            with gr.Row():
                with gr.Column(scale=1):
                    sex = gr.Radio(["male","female"], value="female", label="Sex")
                    age = gr.Slider(15, 70, value=24, step=1, label="Age")
                    height = gr.Slider(130, 210, value=165, step=1, label="Height (cm)")
                    weight = gr.Slider(35, 160, value=60, step=0.5, label="Weight (kg)")
                    activity = gr.Dropdown(list(ACTIVITY_MULTIPLIERS.keys()),
                                           value="Light (1-3x/wk)", label="Activity Level")
                    goal = gr.Radio(["Lose fat","Maintain","Build muscle"],
                                    value="Maintain", label="Fitness Goal")
                    btn1 = gr.Button("Calculate BMI & TDEE")
                with gr.Column(scale=1):
                    out1 = gr.Markdown()
            btn1.click(agent_bmi_tdee, [sex, age, height, weight, activity, goal], out1)

        # -------- Workout Plan Tab --------
        with gr.Tab("Workout Plan"):
            gr.Markdown("#### Get a structured weekly workout plan tailored to your goals.")
            with gr.Row():
                with gr.Column(scale=1):
                    level = gr.Radio(["Beginner","Intermediate"], value="Beginner", label="Experience Level")
                    days = gr.Slider(2, 6, value=4, step=1, label="Training Days per Week")
                    goal_w = gr.Radio(["Lose fat","Maintain","Build muscle"],
                                      value="Build muscle", label="Workout Goal")
                    equipment = gr.Dropdown(["Gym (machines/dumbbells)",
                                             "Home (bands/db)", "Bodyweight only"],
                                            value="Gym (machines/dumbbells)", label="Available Equipment")
                    btn2 = gr.Button("Generate Workout Plan")
                with gr.Column(scale=1):
                    out2 = gr.Markdown()
            btn2.click(agent_workout, [level, days, goal_w, equipment], out2)

        # -------- Nutrition Tab --------
        with gr.Tab("Nutrition"):
            gr.Markdown("#### Discover your macro breakdown and a sample meal plan.")
            with gr.Row():
                with gr.Column(scale=1):
                    target_kcal = gr.Number(value=1900, label="Target Calories (kcal/day)")
                    weight_n = gr.Number(value=60, label="Current Weight (kg)")
                    liked = gr.Textbox(label="Preferred foods (comma-separated)",
                                       placeholder="e.g., chicken, eggs, rice, oats, salad, laban")
                    avoid = gr.Textbox(label="Foods to avoid (allergies, dislikes - comma-separated)",
                                       placeholder="e.g., nuts, shrimp, gluten")
                    meals = gr.Slider(2, 6, value=3, step=1, label="Meals per Day")
                    btn3 = gr.Button("Build Meal Plan")
                with gr.Column(scale=1):
                    out3 = gr.Markdown()
            btn3.click(agent_nutrition, [weight_n, target_kcal, liked, avoid, meals], out3)

        # -------- All-in-One Coach Tab --------
        with gr.Tab("All-in-One Coach"):
            gr.Markdown("#### Get a complete, integrated fitness and nutrition strategy.")
            with gr.Row():
                with gr.Column(scale=1):
                    sex2 = gr.Radio(["male","female"], value="female", label="Sex")
                    age2 = gr.Slider(15, 70, value=24, step=1, label="Age")
                    height2 = gr.Slider(130, 210, value=165, step=1, label="Height (cm)")
                    weight2 = gr.Slider(35, 160, value=60, step=0.5, label="Weight (kg)")
                    activity2 = gr.Dropdown(list(ACTIVITY_MULTIPLIERS.keys()),
                                            value="Light (1-3x/wk)", label="Activity Level")
                    goal2 = gr.Radio(["Lose fat","Maintain","Build muscle"],
                                     value="Build muscle", label="Overall Goal")
                    level2 = gr.Radio(["Beginner","Intermediate"], value="Beginner", label="Experience Level")
                    days2 = gr.Slider(2, 6, value=4, step=1, label="Training Days per Week")
                    equipment2 = gr.Dropdown(["Gym (machines/dumbbells)",
                                              "Home (bands/db)", "Bodyweight only"],
                                             value="Gym (machines/dumbbells)", label="Available Equipment")
                    liked2 = gr.Textbox(label="Preferred foods", placeholder="e.g., chicken, eggs, rice, potatoes")
                    avoid2 = gr.Textbox(label="Foods to avoid", placeholder="e.g., nuts, shrimp")
                    meals2 = gr.Slider(2, 6, value=3, step=1, label="Meals per Day")
                    btn4 = gr.Button("Get My Full Plan 🚀")
                with gr.Column(scale=1):
                    out4 = gr.Markdown()
            btn4.click(
                coach_all_in_one,
                [sex2, age2, height2, weight2, activity2, goal2,
                 level2, days2, equipment2, liked2, avoid2, meals2],
                out4
            )

if __name__ == "__main__":
    demo.launch()