jadehardouin commited on
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01f5691
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1 Parent(s): 42b592e

Update app.py

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Files changed (1) hide show
  1. app.py +9 -9
app.py CHANGED
@@ -7,7 +7,7 @@ import matplotlib.pyplot as plt
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  text = "<h1 style='text-align: center; color: #333333; font-size: 40px;'>TCO Comparison Calculator"
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  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."
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  description=f"""
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- <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>
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  <p>Please note that we focus on getting the service up and running, but not the maintenance that follows.πŸš€</p>
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  <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> πŸ‘ˆ. </p>
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  """
@@ -77,23 +77,23 @@ def create_table(tco1, tco2, labor_cost1, labor_cost2, dropdown, dropdown2, late
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  def compute_cost_per_request(*args):
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  dropdown_id = args[-2]
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  dropdown_id2 = args[-1]
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- if dropdown_id!=None and dropdown_id2!=None:
 
 
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  # Separate the arguments for page1 and page2
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- args_list = list(args)
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- args_page1 = args_list[:len(page1.get_all_components_for_cost_computing())] + [dropdown_id, input_tokens, output_tokens]
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- args_page2 = args_list[len(page1.get_all_components_for_cost_computing()):] + [dropdown_id2, input_tokens, output_tokens]
 
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  # Compute and compare using both pages
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  result_page1 = page1.compute_cost_per_token(*args_page1)
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  result_page2 = page2.compute_cost_per_token(*args_page2)
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  # Unpack the results from the functions
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  tco1, latency, labor_cost1 = result_page1
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- tco2, latency2, labor_cost2 = result_page2
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-
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  return tco1, latency, labor_cost1, tco2, latency2, labor_cost2
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  else:
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  raise gr.Error("Please select two AI service options.")
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-
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-
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  def update_plot(tco1, tco2, dropdown, dropdown2, labour_cost1, labour_cost2):
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  text = "<h1 style='text-align: center; color: #333333; font-size: 40px;'>TCO Comparison Calculator"
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  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."
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  description=f"""
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+ <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>
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  <p>Please note that we focus on getting the service up and running, but not the maintenance that follows.πŸš€</p>
12
  <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> πŸ‘ˆ. </p>
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  """
 
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  def compute_cost_per_request(*args):
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  dropdown_id = args[-2]
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  dropdown_id2 = args[-1]
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+ print("Dropdown 1 value:", dropdown_id)
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+ print("Dropdown 2 value:", dropdown_id2)
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+ if dropdown_id!="" and dropdown_id2!="":
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  # Separate the arguments for page1 and page2
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+ args_page1 = list(args) + [dropdown_id, input_tokens, output_tokens]
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+ args_page2 = list(args) + [dropdown_id2, input_tokens, output_tokens]
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+ print("Args for Page 1:", args_page1)
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+ print("Args for Page 2:", args_page2)
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  # Compute and compare using both pages
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  result_page1 = page1.compute_cost_per_token(*args_page1)
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  result_page2 = page2.compute_cost_per_token(*args_page2)
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  # Unpack the results from the functions
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  tco1, latency, labor_cost1 = result_page1
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+ tco2, latency2, labor_cost2 = result_page2
 
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  return tco1, latency, labor_cost1, tco2, latency2, labor_cost2
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  else:
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  raise gr.Error("Please select two AI service options.")
 
 
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  def update_plot(tco1, tco2, dropdown, dropdown2, labour_cost1, labour_cost2):
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