Update app.py

app.py

@@ -6,6 +6,8 @@ import yfinance as yf
 from datetime import datetime
 from tensorflow.keras.models import load_model
 from joblib import load
+import io
+from PIL import Image
 
 # Load the saved LSTM model and scaler
 lstm_model = load_model('lstm_model.h5')
@@ -71,9 +73,12 @@ def predict_stock_price(ticker, open_price, high_price, low_price, close_price,
         buf.seek(0)
         plt.close()
         
+      # Load the image from the buffer
+        img = Image.open(buf)
+        
         result = f"Predicted future price for {ticker}: ${next_day_lstm_price:.2f}"
 
-        return result,buf
+        return result, img
     except Exception as e:
         return str(e)
 
@@ -105,7 +110,7 @@ iface = gr.Interface(
         gr.Number(label="Adj Close"),
         gr.Number(label="Volume")
     ],
-    outputs=[gr.Textbox(), gr.Image(type="plot")],
+    outputs=[gr.Textbox(), gr.Image(type="pil")],
     title="Stock Price Predictor",
     description="Select the stock ticker and input the last recorded values to predict the closing price using the LSTM model."
 )