Update app.py

app.py

@@ -1,57 +1,44 @@
-from flask import Flask, request, jsonify
-from flask_cors import CORS
-import os
+import gradio as gr
 import sys
+import os
 
 sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
-from api.predict import predict_review, load_resources
-
-app = Flask(__name__)
-CORS(app)
+from api.predict import predict_review
 
-print("loading models on startup...")
-try:
-    load_resources()
-    print("models loaded")
-except Exception as e:
-    print(f"couldnt preload models: {e}")
-
-@app.route('/health', methods=['GET'])
-def health():
-    return jsonify({"status": "ok"}), 200
-
-@app.route('/predict', methods=['POST'])
-def predict():
+def predict_api(text):
     try:
-        data = request.get_json()
-        
-        if not data or 'text' not in data:
-            return jsonify({"error": "missing 'text' field"}), 400
+        if not text or len(text.strip()) == 0:
+            return {
+                "error": "text cannot be empty",
+                "prediction": None,
+                "confidence": 0.0,
+                "is_fake": False
+            }
         
-        reviewText = data['text']
+        result = predict_review(text)
         
-        if not isinstance(reviewText, str):
-            return jsonify({"error": "'text' must be a string"}), 400
-        
-        if len(reviewText.strip()) == 0:
-            return jsonify({"error": "text cannot be empty"}), 400
-        
-        result = predict_review(reviewText)
-        
-        if 'error' in result:
-            return jsonify({"error": result['error']}), 400
-        
-        return jsonify({
+        return {
             "prediction": result['prediction'],
             "confidence": result['confidence'],
-            "is_fake": result['is_fake'],
-            "length_category": result.get('length_category'),
-            "token_count": result.get('token_count')
-        }), 200
+            "is_fake": result['is_fake']
+        }
         
     except Exception as e:
-        return jsonify({"error": str(e)}), 500
+        return {
+            "error": str(e),
+            "prediction": None,
+            "confidence": 0.0,
+            "is_fake": False
+        }
+
+demo = gr.Interface(
+    fn=predict_api,
+    inputs=gr.Textbox(label="review text", lines=5, placeholder="enter review text here..."),
+    outputs=gr.JSON(label="result"),
+    title="sentinelcheck api",
+    description="check if review is fake or real",
+    api_name="predict"
+)
 
-if __name__ == '__main__':
-    print("starting api server")
-    app.run(host='0.0.0.0', port=7860, debug=False)
+if __name__ == "__main__":
+    demo.launch()