Create app.py

app.py

@@ -0,0 +1,64 @@
+import gradio as gr
+import joblib
+import pandas as pd
+
+# 1. Load the trained model
+model = joblib.load('fitness_model.joblib')
+
+# 2. Define the prediction function
+def predict_plan(age, gender, weight, height, goal, equipment, injury, experience):
+    # Create DataFrame with exact column names as trained
+    input_data = pd.DataFrame({
+        'Age': [age],
+        'Gender': [gender],
+        'Weight_kg': [weight],
+        'Height_cm': [height],
+        'Goal': [goal],
+        'Equipment': [equipment],
+        'Injury': [injury],
+        'Experience': [experience]
+    })
+    
+    # Predict
+    prediction = model.predict(input_data)[0]
+    
+    # Generate Smart Tip based on logic
+    tip = f"Goal: {goal}. "
+    
+    if injury != 'None':
+        tip += f"Note: Because of your {injury} injury, this plan avoids high impact stress on that area."
+    elif goal == 'Muscle Gain':
+        tip += "Focus on progressive overload and sufficient protein intake."
+    elif goal == 'Weight Loss':
+        tip += "Combine this workout with a slight caloric deficit for best results."
+    elif goal == 'Strength':
+        tip += "Rest periods of 3-5 minutes between sets are recommended for strength."
+    else:
+        tip += "Stay consistent and listen to your body!"
+        
+    return prediction, tip
+
+# 3. Create the Gradio Interface
+iface = gr.Interface(
+    fn=predict_plan,
+    inputs=[
+        gr.Slider(18, 80, value=30, label="Age"),
+        gr.Radio(["Male", "Female"], label="Gender", value="Male"),
+        gr.Number(label="Weight (kg)", value=75),
+        gr.Number(label="Height (cm)", value=175),
+        gr.Dropdown(['Weight Loss', 'Muscle Gain', 'Endurance', 'General Health', 'Strength', 'Athletic Performance'], label="Goal", value="General Health"),
+        gr.Dropdown(['Gym Membership', 'Home Dumbbells', 'Bodyweight Only', 'Full Home Gym (Rack+Barbell)'], label="Equipment", value="Gym Membership"),
+        gr.Dropdown(['None', 'Knee', 'Back', 'Shoulder', 'Ankle'], label="Injury", value="None"),
+        gr.Radio(['Beginner', 'Intermediate', 'Advanced'], label="Experience", value="Beginner")
+    ],
+    outputs=[
+        gr.Textbox(label="Recommended Workout Plan", type="text"),
+        gr.Textbox(label="AI Coach Tip", type="text")
+    ],
+    title="SmartFit AI - Workout Recommender",
+    description="Enter your profile details to get a machine-learning optimized workout plan based on 10,000 synthetic profiles.",
+    theme="soft"
+)
+
+# 4. Launch App
+iface.launch()