src/streamlit_app.py

import streamlit as st
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
import torch

st.set_page_config(page_title="FitPlan AI", layout="centered")

# LOAD MODEL 
@st.cache_resource
def load_model():
    tokenizer = AutoTokenizer.from_pretrained("google/flan-t5-large")
    model = AutoModelForSeq2SeqLM.from_pretrained("google/flan-t5-large")
    return tokenizer, model

tokenizer, model = load_model()


# TITLE
st.title(" FitPlan AI – User Fitness Profile")

# PERSONAL INFORMATION
st.subheader(" Personal Information")

name = st.text_input("Enter Your Name")

gender = st.radio(
    "Gender",
    ["Male", "Female"],
    horizontal=True
)

# ---------------------------------------------------
# HEIGHT & WEIGHT
# ---------------------------------------------------
col1, col2 = st.columns(2)

with col1:
    height = st.number_input(
        "Height (in cm)",
        min_value=0.0,
        max_value=250.0,
        value=0.0,
        step=0.1
    )

with col2:
    weight = st.number_input(
        "Weight (in kg)",
        min_value=0.0,
        max_value=200.0,
        value=0.0,
        step=0.1
    )

#BMI Function
def bmi_category(bmi):
    if bmi < 18.5:
        return "Underweight"
    elif bmi < 25:
        return "Normal weight"
    elif bmi < 30:
        return "Overweight"
    else:
        return "Obese"

# BMI CALCULATION
bmi = None

if height > 0 and weight > 0:
    height_m = height / 100
    bmi = weight / (height_m ** 2)

    st.metric("📊 Your BMI", f"{bmi:.2f}")
    st.info(f"BMI Category: {bmi_category(bmi)}")

# FITNESS GOAL
st.subheader("🎯 Fitness Goal")

goal = st.selectbox(
    "Select Your Goal",
    [
        "Flexible",
        "Weight Loss",
        "Build Muscle",
        "Strength Gaining",
        "Abs Building"
    ]
)

# EQUIPMENT

st.subheader(" Available Equipment")

equipment_map = {}

col1, col2, col3 = st.columns(3)

with col1:
    equipment_map["No Equipment"] = st.checkbox("No Equipment")
    equipment_map["Pull-up Bar"] = st.checkbox("Pull-up Bar")
    equipment_map["Dip Bars"] = st.checkbox("Dip Bars")
    equipment_map["Push-up Handles"] = st.checkbox("Push-up Handles")
    equipment_map["Dumbbells"] = st.checkbox("Dumbbells")
    equipment_map["Adjustable Dumbbells"] = st.checkbox("Adjustable Dumbbells")

with col2:
    equipment_map["Barbell"] = st.checkbox("Barbell")
    equipment_map["Weight Plates"] = st.checkbox("Weight Plates")
    equipment_map["Kettlebells"] = st.checkbox("Kettlebells")
    equipment_map["Medicine Ball"] = st.checkbox("Medicine Ball")
    equipment_map["Yoga Mat"] = st.checkbox("Yoga Mat")
    equipment_map["Resistance Band"] = st.checkbox("Resistance Band")

with col3:
    equipment_map["Bosu Ball"] = st.checkbox("Bosu Ball")
    equipment_map["Stability Ball"] = st.checkbox("Stability Ball")
    equipment_map["Foam Roller"] = st.checkbox("Foam Roller")
    equipment_map["Treadmill"] = st.checkbox("Treadmill")
    equipment_map["Exercise Bike"] = st.checkbox("Exercise Bike")
    equipment_map["Skipping Rope"] = st.checkbox("Skipping Rope")

equipment = [item for item, selected in equipment_map.items() if selected]


# FITNESS LEVEL
st.subheader("📈 Fitness Level")

fitness_level = st.radio(
    "Select Fitness Level",
    ["Beginner", "Intermediate", "Advanced"],
    horizontal=True
)

def create_prompt(gender, bmi, bmi_status, goal, level, equipment):

    equipment_list = ", ".join(equipment)

    prompt = f"""
Instruction:
You are a certified professional fitness trainer.

Generate a structured 5-day workout plan.

User Information:
Gender: {gender}
BMI: {bmi:.2f} ({bmi_status})
Goal: {goal}
Fitness Level: {level}
Equipment Available: {equipment_list}

Rules:
1. Only generate Day 1 to Day 5.
2. Each day must include:
   - Focus
   - 4 exercises
   - Sets x Reps
   - Rest time
3. Do not repeat days.
4. Do not generate explanations.
5. Keep output clean and professional.

Start directly with:
Day 1:
"""

    return prompt

def generate_workout_plan(prompt):

    inputs = tokenizer(prompt, return_tensors="pt", truncation=True)

    outputs = model.generate(
        **inputs,
        max_new_tokens=400,
        num_beams=4,
        early_stopping=True,
        no_repeat_ngram_size=3
    )

    result = tokenizer.decode(outputs[0], skip_special_tokens=True)

    return result


if st.button("Submit Profile"):

    prompt = create_prompt(
        gender,
        bmi,
        bmi_status,
        goal,
        fitness_level,
        equipment
    )

    with st.spinner("Generating AI workout plan..."):
        result = generate_workout_plan(prompt)

    st.subheader("Your Personalized Workout Plan")
    st.write(result)