Update app.py

app.py

@@ -14,7 +14,7 @@ db = SQLAlchemy(app)
 
 
 # Set up logging  
-logging.basicConfig(level=logging.DEBUG)  
+logging.basicConfig(level=logging.DEBUG, format='%(asctime)s - %(levelname)s - %(message)s')  
 logger = logging.getLogger(__name__)  
 
 # Database model for storing economic indicators  
@@ -43,6 +43,7 @@ def create_dummy_data():
 @app.route('/search', methods=['POST'])  
 def search():  
     """Search for economic indicators."""  
+    logger.debug("Search endpoint hit.")  # Log when the endpoint is accessed  
     try:  
         query = request.json['query']  
         results = EconomicData.query.filter(EconomicData.indicator.ilike(f'%{query}%')).all()  
@@ -92,44 +93,5 @@ def gradio_ui():
         response = requests.post(f'http://localhost:5000/search', json={'query': query})  
         return response.json()  
 
-    def call_predict(num_predictions):  
-        response = requests.post(f'http://localhost:5000/predict', json={'num_predictions': num_predictions})  
-        return response.json()  
-
-    def call_economic_data():  
-        response = requests.get('http://localhost:5000/economic_data')  
-        return response.json()  
-
-    with gr.Blocks() as demo:  
-        gr.Markdown("# Economic DataHub")  
-        gr.Markdown("Welcome to the interactive Economic DataHub. Explore economic indicators, make predictions, and access detailed economic data.")  
-        
-        with gr.Tab("Search Economic Indicators"):  
-            search_input = gr.Textbox(label="Search for Economic Terms:", placeholder="Enter an economic term...")  
-            search_button = gr.Button("Search")  
-            search_output = gr.Textbox(label="Results", interactive=False)  
-
-            search_button.click(call_search, inputs=search_input, outputs=search_output)  
-
-        with gr.Tab("Time Series Prediction"):  
-            num_predictions = gr.Slider(minimum=1, maximum=30, step=1, label="Number of Days to Predict")  
-            predict_button = gr.Button("Predict")  
-            prediction_output = gr.Textbox(label="Predictions", interactive=False)  
-
-            predict_button.click(call_predict, inputs=num_predictions, outputs=prediction_output)  
-
-        with gr.Tab("Retrieve Economic Data"):  
-            retrieve_button = gr.Button("Get Economic Data")  
-            data_output = gr.Textbox(label="Economic Data", interactive=False)  
-
-            retrieve_button.click(call_economic_data, outputs=data_output)  
-
-    demo.launch(server_name="0.0.0.0", server_port=7860, share=True)  
-
-# Initialize database and run the app  
-if __name__ == '__main__':  
-    initialize_db()  # Initialize the database  
-    # Start the Flask app in a separate thread  
-    threading.Thread(target=app.run, kwargs={'debug': True}).start()  
-    # Start the Gradio UI  
-    gradio_ui()  
+    def call
+