Update app.py

app.py

@@ -12,6 +12,11 @@ from reportlab.lib.units import inch
 from io import BytesIO
 from simple_salesforce import Salesforce
 import base64
+import logging
+
+# Configure logging
+logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
+logger = logging.getLogger(__name__)
 
 # Streamlit app configuration
 st.set_page_config(page_title="Delay 🚀", layout="wide")
@@ -200,6 +205,7 @@ with st.form("project_form"):
 
 # Process form submission
 if submit_button:
+    logger.info("Processing form submission")
     input_data = {
         "project_name": project_name,
         "phase": phase,
@@ -218,9 +224,15 @@ if submit_button:
     error = validate_inputs(input_data)
     if error:
         st.error(error)
+        logger.error(f"Validation error: {error}")
     else:
         with st.spinner("Generating predictions and AI insights..."):
-            prediction = predict_delay(input_data)
+            try:
+                prediction = predict_delay(input_data)
+            except Exception as e:
+                st.error(f"Prediction failed: {str(e)}")
+                logger.error(f"Prediction failed: {str(e)}")
+                prediction = {"error": str(e)}
         
         if "error" in prediction:
             st.error(prediction["error"])
@@ -233,10 +245,21 @@ if submit_button:
             st.write(f"**AI Insights**: {prediction['ai_insights']}")
             st.write(f"**Weather Condition**: {prediction['weather_condition']}")
             
-            fig = generate_heatmap(prediction['delay_probability'], f"{phase}: {task}")
-            st.pyplot(fig)
+            # Generate Chart.js heatmap
+            chart_config = generate_heatmap(prediction['delay_probability'], f"{phase}: {task}")
+            st.write("```chartjs\n" + str(chart_config) + "\n```")
+            
+            # Generate matplotlib figure for PDF
+            fig, ax = plt.subplots(figsize=(8, 2))
+            color = 'red' if prediction['delay_probability'] > 75 else 'yellow' if prediction['delay_probability'] > 50 else 'green'
+            ax.barh([f"{phase}: {task}"], [prediction['delay_probability']], color=color, edgecolor='black')
+            ax.set_xlim(0, 100)
+            ax.set_xlabel("Delay Probability (%)")
+            ax.set_title("Delay Risk Heatmap")
+            plt.tight_layout()
             
             pdf_buffer = generate_pdf(input_data, prediction, fig)
+            plt.close(fig)
             st.download_button(
                 label="Download Prediction Report (PDF)",
                 data=pdf_buffer,
@@ -248,8 +271,10 @@ if submit_button:
             sf_error = save_to_salesforce(input_data, prediction, pdf_buffer)
             if sf_error:
                 st.error(sf_error)
+                logger.error(f"Salesforce error: {sf_error}")
             else:
                 st.success("Prediction data and PDF successfully saved to Salesforce!")
+                logger.info("Data and PDF saved to Salesforce")
             
             st.session_state.prediction = prediction
             st.session_state.input_data = input_data