Update app.py

app.py

@@ -7,7 +7,7 @@ import matplotlib.pyplot as plt
 text = "<h1 style='text-align: center; color: #333333; font-size: 40px;'>TCO Comparison Calculator"
 text2 = "Please note that the cost/request only defines the infrastructure cost for deployment. The labor cost must be added for the whole AI model service deployment TCO."
 description=f"""
-<p>In this demo application, we help you compare different AI model services, such as Open source or SaaS solutions, based on the Total Cost of Ownership (TOC) for their deployment. 😊</p> 
+<p>In this demo application, we help you compare different AI model services, such as Open source or SaaS solutions, based on the Total Cost of Ownership for their deployment. 😊</p> 
 <p>Please note that we focus on getting the service up and running, but not the maintenance that follows.🚀</p>
 <p>If you want to <strong>contribute to the calculator</strong> by adding your own AI service option, follow this <a href="https://huggingface.co/spaces/mithril-security/TCO_calculator/blob/main/How_to_contribute.md">tutorial</a> 👈. </p>
 """
@@ -30,54 +30,62 @@ def on_use_case_change(use_case):
         return gr.update(value=50), gr.update(value=10)
     
 def compare_info(tco1, tco2, dropdown, dropdown2):
-    #Compute the cost/request ratio
-    r = tco1 / tco2   
-    if r < 1:
-        comparison_result = f"""The cost/request of the second {dropdown2} service is <b>{1/r:.5f} times more expensive</b> than the one of the first {dropdown} service."""   
-    elif r > 1:
-        comparison_result = f"""The cost/request of the second {dropdown2} service is <b>{r:.5f} times cheaper</b> than the one of the first {dropdown} service."""
-    else:
-        comparison_result = f"""Both solutions have the <b>same cost/request</b>."""
+    if error_occurred == False :
+        #Compute the cost/request ratio
+        r = tco1 / tco2   
+        if r < 1:
+            comparison_result = f"""The cost/request of the second {dropdown2} service is <b>{1/r:.5f} times more expensive</b> than the one of the first {dropdown} service."""   
+        elif r > 1:
+            comparison_result = f"""The cost/request of the second {dropdown2} service is <b>{r:.5f} times cheaper</b> than the one of the first {dropdown} service."""
+        else:
+            comparison_result = f"""Both solutions have the <b>same cost/request</b>."""
+            
+        # Create a bar chart
+        services = [dropdown, dropdown2]
+        costs_to_compare = [tco1, tco2]
         
-    # Create a bar chart
-    services = [dropdown, dropdown2]
-    costs_to_compare = [tco1, tco2]
-    
-    plt.figure(figsize=(6, 4))
-    plt.bar(services, costs_to_compare, color=['red', 'green'])
-    plt.xlabel('AI option services', fontsize=10)
-    plt.ylabel('($) Cost/Request', fontsize=10)
-    plt.title('Comparison of Cost/Request', fontsize=14)
+        plt.figure(figsize=(6, 4))
+        plt.bar(services, costs_to_compare, color=['red', 'green'])
+        plt.xlabel('AI option services', fontsize=10)
+        plt.ylabel('($) Cost/Request', fontsize=10)
+        plt.title('Comparison of Cost/Request', fontsize=14)
 
-    plt.tight_layout()
-    plt.savefig('cost_comparison.png')  # Save to a file
+        plt.tight_layout()
+        plt.savefig('cost_comparison.png')  # Save to a file
 
-    return gr.update(value='cost_comparison.png', visible=True), comparison_result
+        return gr.update(value='cost_comparison.png', visible=True), comparison_result
+    else:
+        return None, ""
 
 def create_table(tco1, tco2, labor_cost1, labor_cost2, dropdown, dropdown2, latency, latency2):
-    list_values = []
-    first_sol = [tco1, labor_cost1, latency]
-    second_sol = [tco2, labor_cost2, latency2]
-    list_values.append(first_sol)
-    list_values.append(second_sol)
+    if error_occurred == False:
+        list_values = []
+        first_sol = [tco1, labor_cost1, latency]
+        second_sol = [tco2, labor_cost2, latency2]
+        list_values.append(first_sol)
+        list_values.append(second_sol)
 
-    data = pd.DataFrame(list_values, index=[dropdown, dropdown2], columns=["Cost/request ($) ", "Labor Cost ($/month)", "Average latency (s)"])
-    
-    formatted_data = data.copy()
-    formatted_data["Cost/request ($) "] = formatted_data["Cost/request ($) "].apply('{:.5f}'.format)
-    formatted_data["Labor Cost ($/month)"] = formatted_data["Labor Cost ($/month)"].apply('{:.0f}'.format)
+        data = pd.DataFrame(list_values, index=[dropdown, dropdown2], columns=["Cost/request ($) ", "Labor Cost ($/month)", "Average latency (s)"])
+        
+        formatted_data = data.copy()
+        formatted_data["Cost/request ($) "] = formatted_data["Cost/request ($) "].apply('{:.5f}'.format)
+        formatted_data["Labor Cost ($/month)"] = formatted_data["Labor Cost ($/month)"].apply('{:.0f}'.format)
 
-    styled_data = formatted_data.style\
-        .set_properties(**{'background-color': '#ffffff', 'color': '#000000', 'border-color': '#e0e0e0', 'border-width': '1px', 'border-style': 'solid'})\
-        .to_html()
-    centered_styled_data = f"<center>{styled_data}</center>"
-    
-    return gr.update(value=centered_styled_data)
+        styled_data = formatted_data.style\
+            .set_properties(**{'background-color': '#ffffff', 'color': '#000000', 'border-color': '#e0e0e0', 'border-width': '1px', 'border-style': 'solid'})\
+            .to_html()
+        centered_styled_data = f"<center>{styled_data}</center>"
+        
+        return gr.update(value=centered_styled_data)
+    else:
+        return ""
 
 def compute_cost_per_request(*args):
     dropdown_id = args[-2]
     dropdown_id2 = args[-1]
+    global error_occurred 
     if dropdown_id!="" and dropdown_id2!="":
+        error_occurred = False
         args_page1 = list(args) + [dropdown_id, input_tokens, output_tokens]
         args_page2 = list(args) + [dropdown_id2, input_tokens, output_tokens]
         result_page1 = page1.compute_cost_per_token(*args_page1)
@@ -86,22 +94,26 @@ def compute_cost_per_request(*args):
         tco2, latency2, labor_cost2 = result_page2   
         return tco1, latency, labor_cost1, tco2, latency2, labor_cost2
     else: 
+        error_occurred = True
         raise gr.Error("Please select two AI service options.")
 
 def update_plot(tco1, tco2, dropdown, dropdown2, labour_cost1, labour_cost2):
-    
-    request_ranges = list(range(0, 1001, 100)) + list(range(1000, 10001, 500)) + list(range(10000, 100001, 1000)) + list(range(100000, 2000001, 100000))
-    costs_tco1 = [(tco1 * req + labour_cost1) for req in request_ranges]
-    costs_tco2 = [(tco2 * req + labour_cost2) for req in request_ranges]
-
-    data = pd.DataFrame({
-        "Number of requests": request_ranges * 2,
-        "Cost ($)": costs_tco1 + costs_tco2,
-        "AI model service": ["1)" + " " + dropdown] * len(request_ranges) + ["2)" + " " + dropdown2] * len(request_ranges)
-        }
-    )
-    return gr.LinePlot.update(data, visible=True, x="Number of requests", y="Cost ($)",color="AI model service",color_legend_position="bottom", title="Set-up TCO for one month", height=300, width=500, tooltip=["Number of requests", "Cost ($)", "AI model service"])
+    if error_occurred == False:
+        request_ranges = list(range(0, 1001, 100)) + list(range(1000, 10001, 500)) + list(range(10000, 100001, 1000)) + list(range(100000, 2000001, 100000))
+        costs_tco1 = [(tco1 * req + labour_cost1) for req in request_ranges]
+        costs_tco2 = [(tco2 * req + labour_cost2) for req in request_ranges]
 
+        data = pd.DataFrame({
+            "Number of requests": request_ranges * 2,
+            "Cost ($)": costs_tco1 + costs_tco2,
+            "AI model service": ["1)" + " " + dropdown] * len(request_ranges) + ["2)" + " " + dropdown2] * len(request_ranges)
+            }
+        )
+        return gr.LinePlot.update(data, visible=True, x="Number of requests", y="Cost ($)",color="AI model service",color_legend_position="bottom", title="Set-up TCO for one month", height=300, width=500, tooltip=["Number of requests", "Cost ($)", "AI model service"])
+    else:
+        return ""
+    
+error_occurred = False
 style = theme.Style()
 
 with gr.Blocks(theme=style) as demo:
@@ -164,6 +176,9 @@ with gr.Blocks(theme=style) as demo:
                 with gr.Column(scale=2):
                     plot = gr.LinePlot(visible=False)
     
-    compute_tco_btn.click(compute_cost_per_request, inputs=page1.get_all_components_for_cost_computing() + page2.get_all_components_for_cost_computing() + [dropdown, dropdown2], outputs=[tco1, latency, labor_cost1, tco2, latency2, labor_cost2]).then(create_table, inputs=[tco1, tco2, labor_cost1, labor_cost2, dropdown, dropdown2, latency, latency2], outputs=table).then(compare_info, inputs=[tco1, tco2, dropdown, dropdown2], outputs=[image, ratio]).then(update_plot, inputs=[tco1, tco2, dropdown, dropdown2, labor_cost1, labor_cost2], outputs=plot)
+    compute_tco_btn.click(compute_cost_per_request, inputs=page1.get_all_components_for_cost_computing() + page2.get_all_components_for_cost_computing() + [dropdown, dropdown2], outputs=[tco1, latency, labor_cost1, tco2, latency2, labor_cost2])\
+        .then(create_table, inputs=[tco1, tco2, labor_cost1, labor_cost2, dropdown, dropdown2, latency, latency2], outputs=table)\
+        .then(compare_info, inputs=[tco1, tco2, dropdown, dropdown2], outputs=[image, ratio])\
+        .then(update_plot, inputs=[tco1, tco2, dropdown, dropdown2, labor_cost1, labor_cost2], outputs=plot)
 
 demo.launch(debug=True)