Add app.py

app.py

@@ -0,0 +1,93 @@
+"""
+MindScan — Flask Backend
+NCI H9DAI Research Project 2026
+
+Loads all 12 models (3 classical + XLM-RoBERTa per dataset)
+and serves predictions via a single /predict endpoint.
+
+Run:  python app.py
+Open: http://localhost:5000
+"""
+
+from flask import Flask, request, jsonify, render_template
+import os, time
+
+# Import our prediction module
+from predict import load_all_models, predict_all, models_loaded
+
+app = Flask(__name__)
+
+# ─────────────────────────────────────────────────────────────────
+# Load models once at startup — not per request
+# ─────────────────────────────────────────────────────────────────
+print("\n" + "="*55)
+print("  MindScan — Starting up")
+print("="*55)
+print("  Loading models... (XLM-RoBERTa takes ~30s on CPU)")
+
+start = time.time()
+load_all_models()
+elapsed = time.time() - start
+
+print(f"  ✅ All models loaded in {elapsed:.1f}s")
+print(f"  🌐 Open: http://localhost:5000")
+print("="*55 + "\n")
+
+
+# ─────────────────────────────────────────────────────────────────
+# ROUTES
+# ─────────────────────────────────────────────────────────────────
+
+@app.route('/')
+def index():
+    """Serve the main UI."""
+    return render_template('index.html')
+
+
+@app.route('/predict', methods=['POST'])
+def predict():
+    """
+    POST /predict
+    Body: { "text": "your text here" }
+    Returns: full prediction JSON from all 12 models
+    """
+    data = request.get_json()
+
+    if not data or 'text' not in data:
+        return jsonify({'error': 'Missing "text" field in request body'}), 400
+
+    text = data['text'].strip()
+
+    if not text:
+        return jsonify({'error': 'Text cannot be empty'}), 400
+
+    if len(text) > 5000:
+        return jsonify({'error': 'Text too long (max 5000 characters)'}), 400
+
+    if not models_loaded():
+        return jsonify({'error': 'Models not loaded yet — try again in a moment'}), 503
+
+    try:
+        t0 = time.time()
+        result = predict_all(text)
+        result['processing_time_ms'] = round((time.time() - t0) * 1000)
+        return jsonify(result)
+    except Exception as e:
+        print(f"Prediction error: {e}")
+        return jsonify({'error': f'Prediction failed: {str(e)}'}), 500
+
+
+@app.route('/health')
+def health():
+    """Quick health check endpoint."""
+    return jsonify({
+        'status': 'ok',
+        'models_ready': models_loaded()
+    })
+
+
+# ─────────────────────────────────────────────────────────────────
+# START
+# ─────────────────────────────────────────────────────────────────
+if __name__ == '__main__':
+    app.run(debug=False, host='0.0.0.0', port=int(os.environ.get('PORT', 5000)))