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Browse files- src/streamlit_app.py +0 -170
src/streamlit_app.py
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import streamlit as st
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from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
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import torch
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# 1. Page Configuration
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st.set_page_config(page_title="Fitness Profile Generator", layout="wide")
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# 2. Load AI Model (Large Version)
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@st.cache_resource
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def load_model():
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# Note: flan-t5-large is ~3GB. Ensure your Hugging Face Space has enough RAM.
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tokenizer = AutoTokenizer.from_pretrained("google/flan-t5-large")
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model = AutoModelForSeq2SeqLM.from_pretrained("google/flan-t5-large")
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return tokenizer, model
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tokenizer, model = load_model()
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# 3. Custom Styling (Gradient and Black Sidebar)
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st.markdown("""
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<style>
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.stApp {
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background: linear-gradient(135deg, #f6d365 0%, #fda085 100%);
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background-attachment: fixed;
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}
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section[data-testid="stSidebar"] {
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background-color: #000000 !important;
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}
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section[data-testid="stSidebar"] h1, section[data-testid="stSidebar"] p {
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color: #FFFFFF !important;
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}
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h1, h2, h3, p, label {
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color: #2D3436 !important;
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font-weight: 600;
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}
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div[data-baseweb="input"], div[data-baseweb="select"] {
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background-color: rgba(255, 255, 255, 0.9) !important;
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border-radius: 8px !important;
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}
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.stButton > button {
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background-color: #004d57 !important;
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color: white !important;
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border-radius: 8px !important;
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padding: 10px 24px !important;
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font-weight: bold !important;
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width: 100% !important;
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border: none !important;
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}
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.result-card {
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background-color: white;
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padding: 25px;
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border-radius: 15px;
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box-shadow: 0 10px 25px rgba(0,0,0,0.1);
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margin-top: 25px;
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border-left: 10px solid #004d57;
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}
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</style>
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""", unsafe_allow_html=True)
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# --- SIDEBAR ---
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with st.sidebar:
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st.markdown("# 👤 Personalised Fitness Plan Generator")
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st.write("---")
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st.write("Your digital coach for a healthier lifestyle.")
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# --- MAIN CONTENT ---
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st.title("🏋️ Create Your Fitness Profile")
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# SECTION 1: PERSONAL INFORMATION
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st.markdown("### 1️⃣ Personal Information")
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col_name, col_gender, col_age = st.columns([2, 1, 1])
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with col_name:
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name = st.text_input("Full Name *", placeholder="e.g. John Doe")
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with col_gender:
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gender = st.selectbox("Gender *", ["Male", "Female", "Other"])
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with col_age:
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age = st.number_input("Age *", min_value=1, max_value=120, value=25)
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col_h, col_w = st.columns(2)
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with col_h:
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height_cm = st.number_input("Height in centimeters *", min_value=0.0, step=0.1)
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with col_w:
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weight_kg = st.number_input("Weight in kilograms *", min_value=0.0, step=0.1)
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st.write("---")
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# SECTION 2: FITNESS DETAILS
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st.markdown("### 2️⃣ Fitness Details")
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col_goal, col_level = st.columns(2)
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with col_goal:
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goal = st.selectbox("Fitness Goal", ["Build Muscle", "Weight Loss", "Strength Gain", "Abs Building", "Flexible"])
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with col_level:
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fitness_level = st.selectbox("Fitness Level", ["Beginner", "Intermediate", "Advanced"])
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equipment = st.multiselect(
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"Available Equipment *",
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["Dumbbells", "Resistance Band", "Yoga Mat", "Kettlebells", "Pull-up Bar", "No Equipment"],
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default=["No Equipment"]
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)
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st.write("---")
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# --- SUBMIT BUTTON & LOGIC ---
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if st.button("Submit Profile"):
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if not name:
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st.error("Please enter your name.")
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elif height_cm <= 0 or weight_kg <= 0:
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st.error("Please enter valid height and weight.")
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elif not equipment:
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st.error("Please select at least one equipment option.")
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else:
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height_m = height_cm / 100
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bmi = weight_kg / (height_m ** 2)
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bmi_rounded = round(bmi, 2)
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if bmi_rounded < 18.5:
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bmi_status, status_color = "Underweight", "#3498db"
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elif 18.5 <= bmi_rounded < 25:
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bmi_status, status_color = "Normal", "#2ecc71"
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elif 25 <= bmi_rounded < 30:
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bmi_status, status_color = "Overweight", "#f1c40f"
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else:
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bmi_status, status_color = "Obese", "#e74c3c"
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st.success("Profile Submitted Successfully!")
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st.markdown(f"""
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<div class="result-card">
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<h2 style="color: #004d57; margin-top:0;">Assessment for {name}</h2>
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<p>{gender} | {age} Years Old</p>
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<p>Calculated BMI: <strong>{bmi_rounded}</strong> | Category: <span style="color: {status_color}; font-weight: bold;">{bmi_status}</span></p>
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</div>
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""", unsafe_allow_html=True)
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# 5. AI Prompt Preparation (Slightly adjusted for better logic)
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equipment_list = ", ".join(equipment)
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prompt = f"""Task: Create a detailed 5-day workout plan for a {gender} with a BMI of {bmi_rounded} ({bmi_status}).
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Goal: {goal}
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Level: {fitness_level}
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Available Equipment: {equipment_list}
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Instructions: Provide a structured routine for Day 1, Day 2, Day 3, Day 4, and Day 5. Include exercises and rest days.
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Workout Plan:
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Day 1:"""
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# 6. AI Generation (Using Optimized Parameters)
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with st.spinner("Generating your AI workout plan..."):
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try:
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inputs = tokenizer(prompt, return_tensors="pt", truncation=True)
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outputs = model.generate(
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**inputs,
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max_new_tokens=512, # 512 is usually enough for T5-Large
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min_new_tokens=150, # Forces the model to provide a longer response
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do_sample=True,
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temperature=0.8, # Slight increase for variety
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top_p=0.9,
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repetition_penalty=2.0 # Prevents it from getting stuck on one phrase
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)
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result = tokenizer.decode(outputs[0], skip_special_tokens=True).strip()
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# Prepending "Day 1:" because the prompt cuts off there
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final_plan = "Day 1: " + result
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st.subheader(" Your Personalized Workout Plan")
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st.write(final_plan)
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except Exception as e:
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st.error(f"AI Generation failed: {e}")
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