Update app.py

app.py

@@ -3,6 +3,8 @@ from flask_sqlalchemy import SQLAlchemy
 import numpy as np  
 import pandas as pd  
 import xgboost as xgb  
+import gradio as gr  
+import threading  
 
 app = Flask(__name__)  
 app.config['SQLALCHEMY_DATABASE_URI'] = 'postgresql://username:password@your-render-database-url/economic_data_db'  
@@ -62,5 +64,49 @@ def get_economic_data():
     records = EconomicData.query.all()  # Retrieve all records  
     return jsonify({record.indicator: record.value for record in records})  
 
+# Gradio UI function  
+def gradio_ui():  
+    def query_api(query):  
+        response = requests.post('http://localhost:5000/search', json={'query': query})  
+        return response.json()  
+
+    def predict_time_series(num_predictions):  
+        response = requests.post('http://localhost:5000/predict', json={'num_predictions': num_predictions})  
+        return response.json()["predictions"]  
+
+    def retrieve_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")  
+            output_text = gr.Textbox(label="Results", interactive=False)  
+
+            search_button.click(query_api, inputs=search_input, outputs=output_text)  
+
+        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(predict_time_series, 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(retrieve_economic_data, outputs=data_output)  
+
+    demo.launch(server_name="0.0.0.0", server_port=7860, share=True)  # Adjusted for Hugging Face Spaces  
+
+# Run the Flask app and Gradio UI in separate threads  
 if __name__ == '__main__':  
-    app.run(debug=True)
+    # Start the Flask app in a separate thread  
+    threading.Thread(target=app.run).start()  
+    # Start the Gradio UI  
+    gradio_ui()