Update app.py

app.py

@@ -2,7 +2,7 @@ import gradio as gr
 import numpy as np
 import pandas as pd
 import yfinance as yf
-from datetime import datetime, timedelta
+from datetime import datetime
 from tensorflow.keras.models import load_model
 from joblib import load
 
@@ -109,40 +109,28 @@ def display_historical_data(ticker):
         return str(e)
 
 # Set up Gradio interface
-ticker_input = gr.Dropdown(choices=stock_list, label="Stock Ticker")
-
-iface = gr.Interface(
-    fn=predict_stock_price,
-    inputs=[
-        ticker_input,
-        gr.Number(label="Open"),
-        gr.Number(label="Close")
-    ],
-    outputs=gr.Textbox(),
-    title="Stock Price Predictor",
-    description="Select the stock ticker and input the last recorded values to predict the closing price using the LSTM model."
-)
-
-next_month_iface = gr.Interface(
-    fn=predict_next_month_price,
-    inputs=[ticker_input],
-    outputs=gr.Textbox(),
-    title="Next Month Stock Price Predictor",
-    description="Select the stock ticker to predict the closing price for the next month using the LSTM model."
-)
-
-historical_data_iface = gr.Interface(
-    fn=display_historical_data,
-    inputs=[ticker_input],
-    outputs=gr.Dataframe(),
-    title="Historical Data Viewer",
-    description="Select the stock ticker to view the historical data."
-)
-
-# Combine interfaces
-app = gr.TabbedInterface(
-    interface_list=[iface, next_month_iface, historical_data_iface],
-    tab_names=["Predict Today's Price", "Predict Next Month's Price", "View Historical Data"]
-)
+with gr.Blocks() as app:
+    with gr.Tab("Predict Today's Price"):
+        gr.Markdown("## Predict Today's Price")
+        ticker_input = gr.Dropdown(choices=stock_list, label="Stock Ticker")
+        open_price = gr.Number(label="Open")
+        close_price = gr.Number(label="Close")
+        predict_button = gr.Button("Predict")
+        predict_output = gr.Textbox()
+        predict_button.click(predict_stock_price, inputs=[ticker_input, open_price, close_price], outputs=predict_output)
+    
+    with gr.Tab("Predict Next Month's Price"):
+        gr.Markdown("## Predict Next Month's Price")
+        next_month_ticker_input = gr.Dropdown(choices=stock_list, label="Stock Ticker")
+        next_month_predict_button = gr.Button("Predict")
+        next_month_predict_output = gr.Textbox()
+        next_month_predict_button.click(predict_next_month_price, inputs=[next_month_ticker_input], outputs=next_month_predict_output)
+    
+    with gr.Tab("View Historical Data"):
+        gr.Markdown("## View Historical Data")
+        historical_ticker_input = gr.Dropdown(choices=stock_list, label="Stock Ticker")
+        historical_view_button = gr.Button("View Data")
+        historical_data_output = gr.Dataframe()
+        historical_view_button.click(display_historical_data, inputs=[historical_ticker_input], outputs=historical_data_output)
 
 app.launch()