Update app.py

app.py

@@ -75,7 +75,7 @@ def generate_plot(planned_cost, actual_spend, forecast_cost):
     return image_base64, gradio_image, buf_pdf
 
 # Function to generate a PDF report locally
-def generate_pdf(planned_cost, actual_spend, forecast_cost, total_risk, insights, status, top_causes, forecast_cost_eur, chart_image):
+def generate_pdf(planned_cost, actual_spend, forecast_cost, total_risk, insights, status, top_causes, forecast_cost_inr, chart_image):
     pdf_path = f"budget_report_{datetime.now().strftime('%Y%m%d_%H%M%S')}.pdf"
     c = canvas.Canvas(pdf_path, pagesize=letter)
     width, height = letter
@@ -93,7 +93,7 @@ def generate_pdf(planned_cost, actual_spend, forecast_cost, total_risk, insights
     y_position -= 20
     c.drawString(50, y_position, f"Forecasted Cost: ${forecast_cost:,.2f}")
     y_position -= 20
-    c.drawString(50, y_position, f"Forecasted Cost (EUR): {forecast_cost_eur if isinstance(forecast_cost_eur, str) else f'{forecast_cost_eur:,.2f}'}")
+    c.drawString(50, y_position, f"Forecasted Cost (INR): {forecast_cost_inr if isinstance(forecast_cost_inr, str) else f'₹{forecast_cost_inr:,.2f}'}")
     y_position -= 20
     c.drawString(50, y_position, f"Total Risk: {total_risk}")
     y_position -= 20
@@ -113,12 +113,12 @@ def generate_pdf(planned_cost, actual_spend, forecast_cost, total_risk, insights
     return pdf_path
 
 # Function to generate an Excel file with prediction results
-def generate_excel(planned_cost, actual_spend, forecast_cost, total_risk, insights, status, top_causes, forecast_cost_eur):
+def generate_excel(planned_cost, actual_spend, forecast_cost, total_risk, insights, status, top_causes, forecast_cost_inr):
     data = {
         "Planned Cost ($)": [planned_cost],
         "Actual Spend ($)": [actual_spend],
         "Forecasted Cost ($)": [forecast_cost],
-        "Forecasted Cost (EUR)": [forecast_cost_eur if isinstance(forecast_cost_eur, str) else forecast_cost_eur],
+        "Forecasted Cost (INR)": [forecast_cost_inr if isinstance(forecast_cost_inr, str) else forecast_cost_inr],
         "Total Risk": [total_risk],
         "Insights": [insights],
         "Status": [status],
@@ -205,21 +205,21 @@ def predict_risk(planned_cost, actual_spend, category, cement_index, labor_index
         logger.error(f"Failed to save to Salesforce: {str(e)}")
         return f"Error: Failed to save to Salesforce: {str(e)}", None, None, None
 
-    # Fetch exchange rates
+    # Fetch exchange rates for USD to INR
     try:
         response = requests.get("https://api.exchangerate-api.com/v4/latest/USD")
         exchange_rates = response.json()
-        usd_to_eur = exchange_rates['rates']['EUR']
-        forecast_cost_eur = forecast_cost * usd_to_eur
+        usd_to_inr = exchange_rates['rates']['INR']
+        forecast_cost_inr = forecast_cost * usd_to_inr
     except Exception as e:
         logger.error(f"Failed to fetch exchange rates: {str(e)}")
-        forecast_cost_eur = "N/A"
+        forecast_cost_inr = "N/A"
 
     # Generate local PDF report
-    pdf_file = generate_pdf(planned_cost, actual_spend, forecast_cost, total_risk, insights, status, top_causes, forecast_cost_eur, chart_image_pdf)
+    pdf_file = generate_pdf(planned_cost, actual_spend, forecast_cost, total_risk, insights, status, top_causes, forecast_cost_inr, chart_image_pdf)
 
     # Generate Excel file
-    excel_file = generate_excel(planned_cost, actual_spend, forecast_cost, total_risk, insights, status, top_causes, forecast_cost_eur)
+    excel_file = generate_excel(planned_cost, actual_spend, forecast_cost, total_risk, insights, status, top_causes, forecast_cost_inr)
 
     # Format the output for Gradio with enhanced summary and risk percentage
     risk_level = "High" if total_risk == 1 else "Low"
@@ -236,7 +236,7 @@ def predict_risk(planned_cost, actual_spend, category, cement_index, labor_index
         f"Detailed Metrics\n"
         f"----------------------------------------\n"
         f"Total Risk: {total_risk}\n"
-        f"Forecasted Cost: ${forecast_cost:,.2f} (EUR: {forecast_cost_eur if isinstance(forecast_cost_eur, str) else f'{forecast_cost_eur:,.2f}'})\n"
+        f"Forecasted Cost: ${forecast_cost:,.2f} (INR: {forecast_cost_inr if isinstance(forecast_cost_inr, str) else f'₹{forecast_cost_inr:,.2f}'})\n"
         f"Top Causes: {top_causes}\n"
         f"Salesforce PDF URL (requires login): {pdf_url}\n"
         f"Local PDF Report: [Download link below]\n"