Update app.py

app.py

@@ -3,7 +3,7 @@ import pandas as pd
 import matplotlib.pyplot as plt
 from datetime import datetime
 from model import predict_delay, get_weather_condition
-from utils import validate_inputs, generate_heatmap, send_to_salesforce
+from utils import validate_inputs, generate_heatmap
 from reportlab.lib.pagesizes import letter
 from reportlab.platypus import SimpleDocTemplate, Paragraph, Spacer, Image
 from reportlab.lib.styles import getSampleStyleSheet
@@ -14,7 +14,6 @@ from fastapi import FastAPI, HTTPException
 from pydantic import BaseModel
 import uvicorn
 import nest_asyncio
-import os
 
 # Apply nest_asyncio to allow FastAPI in Streamlit's event loop
 nest_asyncio.apply()
@@ -61,17 +60,10 @@ async def predict(project_input: ProjectInput):
     pdf_base64 = base64.b64encode(pdf_buffer.getvalue()).decode('utf-8')
     plt.close(fig)
     
-    # Send prediction to Salesforce
-    try:
-        salesforce_result = send_to_salesforce(input_data, prediction)
-    except Exception as e:
-        raise HTTPException(status_code=500, detail=f"Salesforce integration failed: {str(e)}")
-    
-    # Return prediction, PDF, and Salesforce result
+    # Return prediction and PDF
     return {
         "prediction": prediction,
-        "pdf_base64": pdf_base64,
-        "salesforce_result": salesforce_result
+        "pdf_base64": pdf_base64
     }
 
 # Streamlit app configuration
@@ -233,13 +225,6 @@ if submit_button:
                 mime="application/pdf"
             )
             
-            # Send to Salesforce and display result
-            try:
-                salesforce_result = send_to_salesforce(input_data, prediction)
-                st.success(f"Salesforce Integration: {salesforce_result}")
-            except Exception as e:
-                st.error(f"Salesforce Integration Failed: {str(e)}")
-            
             st.session_state.prediction = prediction
             st.session_state.input_data = input_data