Update src/streamlit_app.py

src/streamlit_app.py

@@ -1,81 +1,101 @@
 import streamlit as st
-from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
-import torch
-# -------------------------
-# 1. Function to Craft Prompt
-# -------------------------
+from transformers import pipeline
 
-def create_workout_prompt(days, level, goal, equipment):
+# Load model only once
+@st.cache_resource
+def load_model():
+    return pipeline("text-generation", model="google/flan-t5-base")
 
-    prompt = f"""
-    Generate a {days}-day workout plan.
+generator = load_model()
 
-    User Details:
-    Fitness Level: {level}
-    Goal: {goal}
-    Available Equipment: {equipment}
+st.set_page_config(page_title="FitPlan AI - BMI Calculator", page_icon="💪")
+st.title("💪 FitPlan AI - Fitness Profile & BMI Calculator")
+
+st.write("Fill in your details to calculate your BMI and get AI workout plan.")
+
+# -------------------------
+# 1. Personal Information
+# -------------------------
 
-    Requirements:
-    - Include warm-up
-    - Include exercises with sets and reps
-    - Include rest time
-    - Keep it structured day-wise
-    """
+name = st.text_input("Enter Your Name *")
 
-    return prompt
+gender = st.selectbox("Select Gender", ["Male", "Female", "Other"])
 
+height_cm = st.number_input("Enter Height (in centimeters) *", min_value=0.0, format="%.2f")
+weight_kg = st.number_input("Enter Weight (in kilograms) *", min_value=0.0, format="%.2f")
 
 # -------------------------
-# 2. Load Model (Cached)
+# 2. Fitness Details
 # -------------------------
 
-@st.cache_resource
-def load_model():
-    tokenizer = AutoTokenizer.from_pretrained("google/flan-t5-small")
-    model = AutoModelForSeq2SeqLM.from_pretrained("google/flan-t5-small")
-    return tokenizer, model
+st.subheader("Fitness Details")
+
+goal = st.selectbox(
+    "Select Your Fitness Goal",
+    ["Build Muscle", "Weight Loss", "Strength Gain", "Abs Building", "Flexible"]
+)
 
-tokenizer, model = load_model()
+equipment = st.multiselect(
+    "Available Equipment",
+    ["Dumbbells", "Resistance Band", "Yoga Mat", "No Equipment"]
+)
 
+fitness_level = st.radio(
+    "Fitness Level",
+    ["Beginner", "Intermediate", "Advanced"]
+)
 
 # -------------------------
-# Streamlit UI
+# BMI Functions
 # -------------------------
 
-st.title("💪 FitPlan AI — Workout Generator")
-
-days = st.selectbox("Number of Days", [3, 4, 5, 6])
-level = st.selectbox("Fitness Level", ["Beginner", "Intermediate", "Advanced"])
-goal = st.selectbox("Goal", ["Build Muscle", "Weight Loss", "Strength Gain"])
-equipment = st.text_input("Equipment (e.g., Dumbbells)")
+def calculate_bmi(weight, height_cm):
+    height_m = height_cm / 100
+    bmi = weight / (height_m ** 2)
+    return round(bmi, 2)
+
+def bmi_category(bmi):
+    if bmi < 18.5:
+        return "Underweight"
+    elif bmi < 24.9:
+        return "Normal"
+    elif bmi < 29.9:
+        return "Overweight"
+    else:
+        return "Obese"
 
 # -------------------------
-# Generate Button
+# Submit Button
 # -------------------------
 
-if st.button("Generate Workout Plan"):
+if st.button("Submit Profile"):
 
-    if not equipment:
-        st.error("Please enter equipment")
+    # Validation
+    if not name:
+        st.error("Please enter your name.")
+    elif height_cm <= 0 or weight_kg <= 0:
+        st.error("Enter valid height and weight.")
+    elif not equipment:
+        st.error("Select at least one equipment option.")
     else:
-        prompt = create_workout_prompt(days, level, goal, equipment)
+        st.success("✅ Profile Submitted Successfully!")
+
+        # Calculate BMI
+        bmi = calculate_bmi(weight_kg, height_cm)
+        bmi_status = bmi_category(bmi)
 
-        st.write("### Generated Prompt")
-        st.code(prompt)
+        st.write(f"### 📊 BMI: {bmi} ({bmi_status})")
 
-        with st.spinner("Generating plan..."):
-            inputs = tokenizer(prompt, return_tensors="pt", truncation=True)
+        equipment_list = ", ".join(equipment)
 
-            outputs = model.generate(
-                **inputs,
-                max_new_tokens=300,
-                temperature=0.7,
-                do_sample=True
-            )
+        prompt = f"""
+        Generate a 5-day structured workout plan.
 
-            result = tokenizer.decode(outputs[0], skip_special_tokens=True)
+        Include warmup, exercises with sets & reps, rest time.
+        """
 
-        st.success("Workout Plan Generated ✅")
+        with st.spinner("Generating your AI workout plan..."):
+            result = generator(prompt, max_new_tokens=400)[0]["generated_text"]
 
-        st.subheader("🏋️ Your Workout Plan")
+        st.subheader("🏋️ Your Personalized Workout Plan")
         st.write(result)