Update app.py

app.py

@@ -1,4 +1,3 @@
-
 import gradio as gr
 import pandas as pd
 import numpy as np
@@ -26,9 +25,9 @@ BRAND_COLORS = {
 
 default_departments = pd.DataFrame({
     "Department": ["IT", "Finance", "HR", "Marketing", "Sales", "Operations"],
-    "Number of Employees": [15, 10, 8, 12, 20, 25],
+    "Number of Employees": [10, 15, 8, 12, 20, 25],
     "Average Salary": [95000, 85000, 70000, 75000, 85000, 65000],
-    "Hours Per Week on Manual Tasks": [20, 15, 12, 10, 8, 18]
+    "Hours Per Week on Manual Tasks": [20, 20, 15, 10, 12, 18]
 })
 
 default_subscriptions = pd.DataFrame({
@@ -204,30 +203,37 @@ department_use_cases = {
 
 
 def create_subscription_savings_chart(subscription_data):
-    categories = subscription_data["Tool Category"].tolist()
-    current_costs = []
-    savings = []
+    # Use pandas vectorized operations instead of loop
+    df = subscription_data.copy()
+
+    # Calculate costs and savings in one go
+    df['monthly_cost'] = df["Current Monthly Cost per User"] * df["Number of Users"]
+    df['savings'] = df['monthly_cost'] * (df["Estimated Reduction %"] / 100)
 
-    for _, row in subscription_data.iterrows():
-        monthly_cost = row["Current Monthly Cost per User"] * row[
-            "Number of Users"]
-        reduction = row["Estimated Reduction %"] / 100
-        current_costs.append(monthly_cost)
-        savings.append(monthly_cost * reduction)
+    # Convert to lists for plotly
+    categories = df["Tool Category"].tolist()
+    current_costs = df['monthly_cost'].tolist()
+    savings = df['savings'].tolist()
 
+    # Create the figure with all styling applied at once
     fig = go.Figure()
+
+    # Add both traces at once
     fig.add_trace(
         go.Bar(x=categories,
                y=current_costs,
                name="Current Monthly Cost",
                marker_color=BRAND_COLORS['primary'],
                opacity=0.9))
+
     fig.add_trace(
         go.Bar(x=categories,
                y=savings,
                name="Potential Monthly Savings",
                marker_color=BRAND_COLORS['accent'],
                opacity=0.9))
+
+    # Set layout all at once
     fig.update_layout(
         title="Potential Monthly Subscription Savings with AI",
         barmode='group',
@@ -238,15 +244,16 @@ def create_subscription_savings_chart(subscription_data):
                     y=1.02,
                     xanchor="center",
                     x=0.5,
-                    font=dict(color=BRAND_COLORS['light_text'])),  # white text
+                    font=dict(color=BRAND_COLORS['light_text'])),
         template="plotly_white",
         font=dict(family="Inter, sans-serif",
                   size=12,
-                  color=BRAND_COLORS['light_text']),  # white text
+                  color=BRAND_COLORS['light_text']),
         paper_bgcolor=BRAND_COLORS['dark_bg'],
         plot_bgcolor=BRAND_COLORS['dark_bg'],
-        margin=dict(l=40, r=40, t=80, b=40)  # black bg
+        margin=dict(l=40, r=40, t=80, b=40)
     )
+
     return fig
 
 
@@ -345,11 +352,11 @@ def recommend_preamble_solution(industry,
             description = f"""### ⚡ Guardrails Only
             Perfect for integrating with your existing AI application:
             - Quick API integration.
-            - Pre-built security rules.
+            - Pre-built security and privacy guardrails.
             - Basic compliance templates.
             - Agentless operation.
             - Free Trial available.
-            - {shadow_ai_blocker}
+            - Free Shadow AI Tool {shadow_ai_blocker}
             $0.005 per API call (Est. monthly cost: ${monthly_cost:,.2f} at {api_calls:,} calls/month)"""
             image = "🛡️"
         else:
@@ -361,7 +368,7 @@ def recommend_preamble_solution(industry,
             - Protection for up to 25 AI applications.
             - Secure Knowledge Base.
             - SaaS Hosting.
-            - {shadow_ai_blocker}
+            - Free Shadow AI Tool {shadow_ai_blocker}
             $50 per user/month"""
             image = "🏢"
     elif org_size >= 1000 or industry in high_risk_industries:
@@ -369,11 +376,12 @@ def recommend_preamble_solution(industry,
         description = f"""### 🏢 Enterprise License
         Perfect for large or high-risk organizations:
         - Complete compliance controls.
-        - Custom security model training.
+        - Custom AI Assistant Development Support.
         - Dedicated support team.
-        - Unlimited AI system protection.
+        - Private AI Marketplace.
+        - Custom integrations.
         - Private cloud/on-premise options.
-        - {shadow_ai_blocker}
+        - Free Shadow AI Tool {shadow_ai_blocker}
         Starting at $27,000/month with discounts for multi-year deals"""
         image = "🚀"
     elif org_size >= 100:  
@@ -382,10 +390,11 @@ def recommend_preamble_solution(industry,
         Perfect for teams getting started with AI:
         - Full platform features.
         - Standard compliance templates.
-        - Protection for up to 25 AI applications.
+        - Custom AI Assistants.
+        - Safe AI Search Agent
         - Secure Knowledge Base.
         - SaaS Hosting.
-        - {shadow_ai_blocker}
+        - Free Shadow AI Tool {shadow_ai_blocker}
         $50 per user/month"""
         image = "🏢"
 
@@ -395,11 +404,11 @@ def recommend_preamble_solution(industry,
         description = f"""### ⚡ Guardrails Only
             Perfect for integrating with your existing AI application:
             - Quick API integration.
-            - Pre-built security rules.
+            - Pre-built security and privacy guardrails.
             - Basic compliance templates.
             - Agentless operation.
             - Free Trial available.
-            - {shadow_ai_blocker}
+            - Free Shadow AI Tool {shadow_ai_blocker}
             $0.005 per API call (Est. monthly cost: ${monthly_cost:,.2f} at {api_calls:,} calls/month)"""
         image = "🛡️"
     return {"solution": solution, "description": description, "image": image}
@@ -567,11 +576,11 @@ def generate_recommendations(industry,
         f"**Industry:** {industry}\n**Organization Size:** {org_size:,} employees\n"
         f"**Monthly Budget:** ${monthly_budget:,.2f}\n"
         f"**Existing AI Application:** {'Yes' if has_ai_app else 'No'}\n"
-        f"**Total Potential Annual Savings:** ${total_dept_savings + subscription_savings['total_savings'] + compliance_savings['total_savings']:,.2f}\n"
-        f"### Recommended Preamble Solution\n{solution_rec['image']} {solution_rec['description']}\n"
+        f"**Total Potential Annual Savings:** ${total_dept_savings + subscription_savings['total_savings'] + compliance_savings['total_savings']:,.2f}\n\n"
+        f"## Recommended Preamble Solution\n{solution_rec['image']} {solution_rec['description']}\n\n"
         f"{build_vs_buy_text}\n"
-        f"## Department Recommendations\nThe following departments show the highest potential ROI for AI implementation:\n{dept_recommendations}"
-        f"{subscription_text}{compliance_text}{security_text}\n## Implementation Roadmap\n\n"
+        f"## Department Recommendations\nThe following departments show the highest potential ROI for AI implementation:\n{dept_recommendations}\n"
+        f"{subscription_text}{compliance_text}{security_text}\n\n## Implementation Roadmap\n\n"
         f"1. **Phase 1: Security Foundation** (1-2 months)\n"
         f"   - Deploy Preamble {solution_rec['solution']}\n"
         f"   - Establish AI governance framework\n"
@@ -1231,28 +1240,10 @@ def create_app():
                 Based on your inputs, we've generated a comprehensive AI security implementation plan tailored to your organization's needs, budget, and industry requirements.
                 </div>""")
 
-                with gr.Tabs():
-                    with gr.Tab("Executive Summary"):
-                        recommendation_output = gr.Markdown(
-                            elem_classes="result-card")
-
-                    with gr.Tab("Savings Analysis"):
-                        gr.Markdown("### Potential Cost Savings",
-                                    elem_classes="subsection-title")
-                        gr.Markdown(
-                            """This chart illustrates the potential monthly savings across your different tool categories by implementing AI solutions."""
-                        )
-                        subscription_chart = gr.Plot(
-                            elem_classes="chart-container")
-
-                    with gr.Tab("Build vs Buy Comparison"):
-                        gr.Markdown("### Build vs Buy Analysis",
-                                    elem_classes="subsection-title")
-                        gr.Markdown(
-                            """This chart compares the cost of building and maintaining your own AI security platform versus using Preamble's enterprise solution over 3 years."""
-                        )
-                        build_vs_buy_chart = gr.Plot(
-                            elem_classes="chart-container")
+                # Simplified output without tabs and plots for better performance
+                recommendation_output = gr.Markdown(
+                    elem_classes="result-card",
+                    render=True)
 
                 gr.Markdown(
                     """<div class="helper-text" style="margin-top: 20px; text-align: center;">
@@ -1278,18 +1269,30 @@ def create_app():
 
             def go_to_step2(org_size, step):
                 indicators = update_progress_indicator(2)
-                total_employees = int(org_size) if org_size is not None else 0
+                # Ensure org_size is valid
+                try:
+                    total_employees = int(org_size) if org_size is not None else 0
+                    if total_employees < 0:
+                        total_employees = 0
+                except (ValueError, TypeError):
+                    total_employees = 0
+
+                # Create copies of dataframes only once
                 updated_departments = default_departments.copy()
-                if total_employees != updated_departments[
-                        'Number of Employees'].sum():
-                    updated_departments.loc[
-                        updated_departments.index[-1],
-                        'Number of Employees'] += total_employees - updated_departments[
-                            'Number of Employees'].sum()
-
                 updated_subscriptions = default_subscriptions.copy()
+
+                # Update department employee count efficiently
+                if total_employees > 0:
+                    current_total = updated_departments['Number of Employees'].sum()
+                    if total_employees != current_total:
+                        # Add difference to last row
+                        diff = total_employees - current_total
+                        updated_departments.at[updated_departments.index[-1], 'Number of Employees'] += diff
+
+                # Update all subscription users at once
                 updated_subscriptions['Number of Users'] = total_employees
 
+                # Return updates all at once
                 return (gr.update(visible=False), gr.update(visible=True),
                         gr.update(visible=False), gr.update(visible=False), 
                         gr.update(visible=False), gr.update(value=2),
@@ -1326,11 +1329,10 @@ def create_app():
                                                   dept_roi_results,
                                                   sub_savings, comp_savings,
                                                   api_calls)[0]  # Only get the report
-                chart = create_subscription_savings_chart(subscription_df)
                 indicators = update_progress_indicator(4)
                 return (gr.update(visible=False), gr.update(visible=False),
                         gr.update(visible=False), gr.update(visible=False),
-                        gr.update(visible=True), report, chart, chart, *indicators)
+                        gr.update(visible=True), report, *indicators)
 
             def generate_recommendations_with_comparison(
                     industry, org_size, monthly_budget, has_ai_app, api_calls,
@@ -1345,13 +1347,10 @@ def create_app():
                     dept_roi_results, sub_savings, comp_savings, api_calls,
                     initial_dev_cost, num_ai_personnel, avg_annual_salary,
                     annual_maintenance, security_compliance)
-                subscription_chart = create_subscription_savings_chart(subscription_df)
-                comparison_chart = create_build_vs_buy_chart(comparison)
                 indicators = update_progress_indicator(4)
                 return (gr.update(visible=False), gr.update(visible=False),
                         gr.update(visible=False), gr.update(visible=False),
-                        gr.update(visible=True), report, subscription_chart, 
-                        comparison_chart, *indicators)
+                        gr.update(visible=True), report, *indicators)
 
 
             next_button1.click(fn=go_to_step2,
@@ -1413,8 +1412,7 @@ def create_app():
                                    ],
                                    outputs=[
                                        step1, step2, step3, step3_5, step4,
-                                       recommendation_output,
-                                       subscription_chart, build_vs_buy_chart, step1_indicator,
+                                       recommendation_output, step1_indicator,
                                        step2_indicator, step3_indicator, step4_indicator
                                    ])
 
@@ -1429,8 +1427,7 @@ def create_app():
                 ],
                 outputs=[
                     step1, step2, step3, step3_5, step4,
-                    recommendation_output, subscription_chart, 
-                    build_vs_buy_chart, step1_indicator, step2_indicator, 
+                    recommendation_output, step1_indicator, step2_indicator, 
                     step3_indicator, step4_indicator
                 ]
             )