jadehardouin
commited on
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ea19e17
1
Parent(s):
0680f69
Update app.py
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app.py
CHANGED
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import gradio as gr
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import models
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Models: list[models.BaseTCOModel] = [models.OpenAIModel, models.OpenSourceLlama2Model]
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model_names = [Model().get_name() for Model in Models]
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with gr.Row():
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with gr.Column():
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page1 = models.ModelPage(Models)
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dropdown = gr.Dropdown(model_names, interactive=True)
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page1.render()
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with gr.Column():
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page2 = models.ModelPage(Models)
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dropdown2 = gr.Dropdown(model_names, interactive=True)
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page2.render()
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dropdown.change(page1.make_model_visible, inputs=dropdown, outputs=page1.get_all_components())
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dropdown2.change(page2.make_model_visible, inputs=dropdown2, outputs=page2.get_all_components())
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demo.launch(debug=True)
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import gradio as gr
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import models
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import time
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text = "<h1 style='text-align: center; color: blue; font-size: 30px;'>TCO Comparison Calculator"
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text1 = "<h1 style='text-align: center; color: blue; font-size: 20px;'>First solution"
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text2 = "<h1 style='text-align: center; color: blue; font-size: 20px;'>Second solution"
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text3 = "<h1 style='text-align: center; color: blue; font-size: 20px;'>Compute and compare TCOs"
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description=f"""
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<p>In this demo application, we help you compare different solutions for your AI incorporation plans, such as OpenSource or SaaS.</p>
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<p>First, you'll have to choose the two solutions you'd like to compare. Then, follow the instructions to select your configurations for each solution and we will compute the cost/token accordingly to them. Eventually, you can compare both solutions to evaluate which one best suits your needs.</p>
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"""
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def compute_ratio(tco1, tco2):
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time.sleep(2)
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try:
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r = tco1 / tco2
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if r < 1:
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comparison_result = f"First solution is cheaper, with a ratio of {r:.5f}."
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elif r > 1:
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comparison_result = f"Second solution is cheaper, with a ratio of {r:.5f}."
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else:
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comparison_result = "Both solutions will cost the same."
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return comparison_result
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except ValueError as e:
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return f"Error: {str(e)}"
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with gr.Blocks(theme=gr.themes.Soft()) as demo:
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Models: list[models.BaseTCOModel] = [models.OpenAIModel, models.OpenSourceLlama2Model]
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model_names = [Model().get_name() for Model in Models]
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gr.Markdown(value=text)
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gr.Markdown(value=description)
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with gr.Row():
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with gr.Column():
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gr.Markdown(value=text1)
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page1 = models.ModelPage(Models)
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dropdown = gr.Dropdown(model_names, interactive=True, label="First solution")
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page1.render()
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with gr.Column():
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gr.Markdown(value=text2)
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page2 = models.ModelPage(Models)
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dropdown2 = gr.Dropdown(model_names, interactive=True, label="Second solution")
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page2.render()
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dropdown.change(page1.make_model_visible, inputs=dropdown, outputs=page1.get_all_components())
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dropdown2.change(page2.make_model_visible, inputs=dropdown2, outputs=page2.get_all_components())
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gr.Markdown(value=text3)
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compute_tco_btn = gr.Button("Compute TCOs", size="lg")
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tco1 = gr.State()
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tco2 = gr.State()
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with gr.Row():
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with gr.Column():
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tco_output = gr.Text("Output 1: ", label="TCO for the first solution")
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with gr.Accordion("Open to see the formula", open=False):
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tco_formula = gr.Markdown()
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with gr.Column():
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tco_output2 = gr.Text("Output 2: ", label="TCO for the second solution")
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with gr.Accordion("Open to see the formula", open=False):
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tco_formula2 = gr.Markdown()
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ratio = gr.Text("Ratio: ", label="Ratio of cost/token for both solutions")
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compute_tco_btn.click(page1.compute_cost_per_token, inputs=page1.get_all_components_for_cost_computing() + [dropdown], outputs=[tco_output, tco1, tco_formula]).then(page2.compute_cost_per_token, inputs=page2.get_all_components_for_cost_computing() + [dropdown2], outputs=[tco_output2, tco2, tco_formula2]).then(compute_ratio, inputs=[tco1, tco2], outputs=ratio)
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demo.launch(debug=True)
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