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_inr, chart_image):
+def generate_pdf(planned_cost, actual_spend, forecast_cost, total_risk, insights, status, top_causes, forecast_cost_inr, category, 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
@@ -87,6 +87,8 @@ def generate_pdf(planned_cost, actual_spend, forecast_cost, total_risk, insights
     # Prediction Metrics
     c.setFont("Helvetica", 12)
     y_position = height - 100
+    c.drawString(50, y_position, f"Category: {category}")
+    y_position -= 20
     c.drawString(50, y_position, f"Planned Cost: ${planned_cost:,.2f}")
     y_position -= 20
     c.drawString(50, y_position, f"Actual Spend: ${actual_spend:,.2f}")
@@ -113,8 +115,9 @@ 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_inr):
+def generate_excel(planned_cost, actual_spend, forecast_cost, total_risk, insights, status, top_causes, forecast_cost_inr, category):
     data = {
+        "Category": [category],
         "Planned Cost ($)": [planned_cost],
         "Actual Spend ($)": [actual_spend],
         "Forecasted Cost ($)": [forecast_cost],
@@ -216,12 +219,12 @@ def predict_risk(planned_cost, actual_spend, category, cement_index, labor_index
         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_inr, chart_image_pdf)
+    pdf_file = generate_pdf(planned_cost, actual_spend, forecast_cost, total_risk, insights, status, top_causes, forecast_cost_inr, category, chart_image_pdf)
 
     # Generate Excel file
-    excel_file = generate_excel(planned_cost, actual_spend, forecast_cost, total_risk, insights, status, top_causes, forecast_cost_inr)
+    excel_file = generate_excel(planned_cost, actual_spend, forecast_cost, total_risk, insights, status, top_causes, forecast_cost_inr, category)
 
-    # Format the output for Gradio with enhanced summary and risk percentage
+    # Format the output for Gradio with enhanced summary, risk percentage, and category
     risk_level = "High" if total_risk == 1 else "Low"
     output_text = (
         f"Risk Summary\n"
@@ -230,6 +233,12 @@ def predict_risk(planned_cost, actual_spend, category, cement_index, labor_index
         f"Risk Percentage: {risk_percentage}%\n"
         f"Status: {status}\n"
         f"Insights: {insights} due to {top_causes.lower()}.\n\n"
+        f"Project Details\n"
+        f"----------------------------------------\n"
+        f"Category: {category}\n"
+        f"Project Phase: {project_phase}\n"
+        f"Cement Index: {cement_index}\n"
+        f"Labor Index: {labor_index}\n\n"
         f"Forecast Chart\n"
         f"----------------------------------------\n"
         f"[Chart displayed below]\n\n"
@@ -263,7 +272,7 @@ with gr.Blocks(title="Budget Overrun Risk Estimator") as demo:
                 submit_button = gr.Button("Submit", variant="primary")
 
         with gr.Column():
-            output_text = gr.Textbox(label="Prediction Results")
+            output_text = gr.Textbox(label="Prediction Results", lines=20, max_lines=30)  # Increased lines to ensure full display
             output_chart = gr.Image(label="Forecast Chart")
             output_pdf = gr.File(label="Download Local PDF Report")
             output_excel = gr.File(label="Download Excel Report")