app.py

from flask import Flask, render_template, request
import pandas as pd
import pickle
import os

app = Flask(__name__)

@app.route('/', methods=['GET', 'POST'])
def index():
    prediction = None
    error = None
    if request.method == 'POST':
        try:
            # Load model
            if os.path.exists('static/model.pkl'):
                with open('static/model.pkl', 'rb') as f:
                    model = pickle.load(f)
                # Get form data
                features = [
                    float(request.form['age']),
                    float(request.form['mood']),
                    float(request.form['sleep']),
                    float(request.form['stress']),
                    float(request.form['anxiety'])
                ]
                # Predict
                pred = model.predict([features])[0]
                prob = model.predict_proba([features])[0][1] * 100
                message = "Potential mental health issue" if pred == 1 else "No significant concern"
                prediction = {'message': message, 'probability': f"{prob:.1f}"}
            else:
                error = "Model not found. Please run train.py."
        except Exception as e:
            error = f"Error processing input: {str(e)}"
    return render_template('index.html', prediction=prediction, error=error)

if __name__ == '__main__':
    app.run(host='0.0.0.0', port=7860, debug=False)  # Use port 7860 for HF Spaces, disable debug for production