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| import streamlit as st | |
| from transformers import AutoTokenizer, AutoModelForSeq2SeqLM | |
| import torch | |
| # ------------------------- | |
| # PAGE CONFIG | |
| # ------------------------- | |
| st.set_page_config(page_title="FitPlan-AI", page_icon="πͺ") | |
| st.title("πͺ FitPlan-AI: Personalized Fitness Profile") | |
| # ------------------------- | |
| # BMI FUNCTIONS | |
| # ------------------------- | |
| def calculate_bmi(weight, height_cm): | |
| height_m = height_cm / 100 | |
| return round(weight / (height_m ** 2), 2) | |
| def get_category(bmi): | |
| if bmi < 18.5: | |
| return "Underweight" | |
| elif bmi < 24.9: | |
| return "Normal" | |
| elif bmi < 29.9: | |
| return "Overweight" | |
| else: | |
| return "Obese" | |
| # ------------------------- | |
| # LOAD MODEL | |
| # ------------------------- | |
| def load_model(): | |
| tokenizer = AutoTokenizer.from_pretrained("google/flan-t5-base") | |
| model = AutoModelForSeq2SeqLM.from_pretrained("google/flan-t5-base") | |
| return tokenizer, model | |
| tokenizer, model = load_model() | |
| # ------------------------- | |
| # FORM | |
| # ------------------------- | |
| with st.form("fitness_form"): | |
| st.subheader("Personal Information") | |
| name = st.text_input("Full Name*", placeholder="Enter your name") | |
| col1, col2 = st.columns(2) | |
| with col1: | |
| height = st.number_input("Height (cm)*", min_value=1.0, step=0.1) | |
| with col2: | |
| weight = st.number_input("Weight (kg)*", min_value=1.0, step=0.1) | |
| st.subheader("Fitness Details") | |
| goal = st.selectbox( | |
| "Fitness Goal", | |
| ["Build Muscle", "Weight Loss", "Strength Gain", "Abs Building", "Flexibility"] | |
| ) | |
| level = st.radio( | |
| "Fitness Level", | |
| ["Beginner", "Intermediate", "Advanced"] | |
| ) | |
| equipment = st.multiselect( | |
| "Available Equipment", | |
| ["Dumbbells", "Resistance Band", "Yoga Mat", "No Equipment", | |
| "Kettlebell", "Pull-up Bar"] | |
| ) | |
| submit = st.form_submit_button("Submit Profile") | |
| # ------------------------- | |
| # HANDLE SUBMISSION | |
| # ------------------------- | |
| if submit: | |
| if not name: | |
| st.error("Please enter your name.") | |
| elif height <= 0 or weight <= 0: | |
| st.error("Please enter valid height and weight.") | |
| elif not equipment: | |
| st.error("Please select at least one equipment option.") | |
| else: | |
| st.success("Profile Submitted Successfully!") | |
| # Calculate BMI | |
| bmi = calculate_bmi(weight, height) | |
| bmi_status = get_category(bmi) | |
| st.write(f"### π Your BMI: {bmi} ({bmi_status})") | |
| # ------------------------- | |
| # GENERATE 5-DAY PLAN (SINGLE PROMPT METHOD) | |
| # ------------------------- | |
| from prompt_builder import build_prompt | |
| with st.spinner("Generating your 5-day workout plan..."): | |
| prompt, bmi, bmi_status = build_prompt( | |
| name=name, | |
| gender="Not specified", # You can add gender field later | |
| height=height, | |
| weight=weight, | |
| goal=goal, | |
| fitness_level=level, | |
| equipment=equipment | |
| ) | |
| inputs = tokenizer(prompt, return_tensors="pt", truncation=True) | |
| outputs = model.generate( | |
| **inputs, | |
| max_new_tokens=2000, | |
| temperature=0.7, | |
| do_sample=True, | |
| repetition_penalty=1.1 | |
| ) | |
| full_plan = tokenizer.decode( | |
| outputs[0], | |
| skip_special_tokens=True | |
| ).strip() | |
| # ------------------------- | |
| # DISPLAY PLAN | |
| # ------------------------- | |
| st.subheader("ποΈ Your Personalized 5-Day Workout Plan") | |
| st.write(full_plan) |