Update app.py

app.py

@@ -49,7 +49,20 @@ def lstm_prediction(file, epochs):
     model.add(LSTM(4, input_shape=(1, look_back)))
     model.add(Dense(1))
     model.compile(loss='mean_squared_error', optimizer='adam')
-    model.fit(trainX, trainY, epochs=epochs, batch_size=1, verbose=2)
+
+    # Set up a callback to update Streamlit during training
+    class StreamlitCallback(tf.keras.callbacks.Callback):
+        def __init__(self):
+            super().__init__()
+            self.epoch_bar = st.progress(0)
+            self.loss_placeholder = st.empty()
+
+        def on_epoch_end(self, epoch, logs=None):
+            self.epoch_bar.progress((epoch + 1) / epochs)
+            self.loss_placeholder.text(f'Epoch {epoch + 1}/{epochs}, Loss: {logs["loss"]:.4f}')
+
+    # Fit the model
+    model.fit(trainX, trainY, epochs=epochs, batch_size=1, verbose=0, callbacks=[StreamlitCallback()])
 
     # Make predictions
     trainPredict = model.predict(trainX)