app.py

import gradio as gr

def calculate_tco(model_choice, vm_rental_choice):
    VM_cost_per_hour=3.6730 
    tokens_per_request = 64
    
    if model_choice == "Llama-2-7B":
        tokens_per_second=694.38
        
    elif model_choice == "Llama-2-13B":
        tokens_per_second=1000
    
    elif model_choice == "Llama-2-70B":
        tokens_per_second=10000
    
    if vm_rental_option == "1 month" or "3 months" or "6 months":
        reduction = 0
    
    elif vm_rental_option == "1 year":
        reduction = 0.34
    
    elif vm_rental_option == "3 years":
        reduction = 0.62
        
    homemade_cost_per_request = VM_cost_per_hour * (1 - reduction) * tokens_per_request / (tokens_per_second * 3600) #* 0.8 * 0.5 
    saas_cost_per_request = 0.018 * tokens_per_request

    output = f"Cost/request with a plan for {vm_rental_choice} using:\n"
    output += f"- SaaS solution from OpenAI: ${saas_cost_per_request:.5f}\n"
    output += f"- Home-made solution with the model {model_choice}: ${homemade_cost_per_request:.5f}"
    return output

models = ["Llama-2-7B", "Llama-2-13B", "Llama-2-70B"]
vm_rental_option = ["1 month", "3 months", "6 months", "1 year", "3 years"]

iface = gr.Interface(
    fn=calculate_tco,
    inputs=[gr.inputs.Dropdown(models, label="Select AI Model"), 
            gr.inputs.Dropdown(vm_rental_option, label="Select VM Rental Duration")],
    outputs=gr.outputs.Textbox()
)

iface.launch()