Update app.py

app.py

@@ -273,11 +273,13 @@ elif page == "Price Prediction":
             lstm_price = lstm_model.predict(input_scaled.reshape(1, 1, -1))[0][0]
             transformer_price = transformer_model.predict(input_scaled.reshape(1, 1, -1))[0][0]
             rl_price = rl_model.predict(input_with_step)[0]
+            # Extract the single float value from the RL prediction
+            rl_price_value = rl_price.item() if isinstance(rl_price, np.ndarray) else rl_price
             
             # Display results
             st.success(f"LSTM Predicted Price: ${lstm_price:.2f}")
             st.success(f"Transformer Predicted Price: ${transformer_price:.2f}")
-            st.success(f"RL Predicted Price: ${rl_price:.2f}")
+            st.success(f"RL Predicted Price: ${rl_price_value:.2f}")
             
             st.subheader("LLM Pricing Analysis:")
             st.write(llm_analysis)