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| import pandas as pd | |
| import gradio as gr | |
| import matplotlib.pyplot as plt | |
| shared_page1 = None | |
| shared_page2 = None | |
| def set_shared_pages(page1, page2): | |
| global shared_page1, shared_page2 | |
| shared_page1 = page1 | |
| shared_page2 = page2 | |
| def compare_info(tco1, tco2, dropdown, dropdown2): | |
| 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] | |
| 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 | |
| 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): | |
| if error_occurred == False: | |
| if shared_page1 is None or shared_page2 is None: | |
| raise ValueError("Shared instances not set.") | |
| 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) | |
| 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[-4] | |
| dropdown_id2 = args[-3] | |
| input_tokens = args[-2] | |
| output_tokens = args[-1] | |
| global error_occurred | |
| if dropdown_id!="" and dropdown_id2!="": | |
| error_occurred = False | |
| page1 = shared_page1 | |
| page2 = shared_page2 | |
| 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) | |
| result_page2 = page2.compute_cost_per_token(*args_page2) | |
| tco1, latency, labor_cost1 = result_page1 | |
| 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): | |
| if error_occurred == False: | |
| request_ranges = list(range(0, 1001, 100)) + list(range(1000, 10001, 500)) + list(range(10000, 100001, 1000)) + list(range(100000, 1600001, 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 ($)", color="AI model service", color_legend_title=" ", color_legend_position="right", title="TCO for one month", height=300, width=500, tooltip=["Number of requests", "Cost ($)", "AI model service"]) | |
| else: | |
| return "" | |
| error_occurred = False |