Create app.py

app.py

@@ -0,0 +1,196 @@
+import gradio as gr
+import plotly.graph_objects as go
+import pandas as pd
+import numpy as np
+
+def calculate_runpod_cost(
+    requests_per_hour,
+    execution_time_per_request,
+    active_cost_per_second,
+    flex_cost_per_second,
+    cold_start_penalty=30,
+    active_request_percentage=0.5
+):
+    # Calculate monthly requests
+    monthly_requests = requests_per_hour * 24 * 30
+    
+    # Split requests between active and flex workers
+    active_requests = monthly_requests * active_request_percentage
+    flex_requests = monthly_requests * (1 - active_request_percentage)
+    
+    # Calculate active worker cost
+    active_cost = active_requests * execution_time_per_request * active_cost_per_second
+    
+    # Calculate flex worker cost (including cold start penalty)
+    flex_cost = flex_requests * (execution_time_per_request + cold_start_penalty) * flex_cost_per_second
+    
+    # Total monthly cost
+    total_monthly_cost = active_cost + flex_cost
+    
+    return {
+        "monthly_requests": monthly_requests,
+        "active_requests": active_requests,
+        "flex_requests": flex_requests,
+        "active_cost": active_cost,
+        "flex_cost": flex_cost,
+        "total_monthly_cost": total_monthly_cost
+    }
+
+def generate_cost_projection(
+    min_requests,
+    max_requests,
+    execution_time,
+    active_cost,
+    flex_cost,
+    active_percentage,
+    cold_start
+):
+    # Generate data for different request volumes
+    request_volumes = np.linspace(min_requests, max_requests, 20)
+    results = []
+
+    for req_vol in request_volumes:
+        result = calculate_runpod_cost(
+            req_vol, 
+            execution_time, 
+            active_cost, 
+            flex_cost, 
+            cold_start, 
+            active_percentage/100
+        )
+        results.append({
+            'requests_per_hour': req_vol,
+            'monthly_requests': result['monthly_requests'],
+            'active_cost': result['active_cost'],
+            'flex_cost': result['flex_cost'],
+            'total_cost': result['total_monthly_cost']
+        })
+
+    df = pd.DataFrame(results)
+
+    # Create plotly figure
+    fig = go.Figure()
+    fig.add_trace(go.Scatter(
+        x=df['requests_per_hour'],
+        y=df['active_cost'],
+        name='Active Worker Cost',
+        line=dict(color='blue')
+    ))
+    fig.add_trace(go.Scatter(
+        x=df['requests_per_hour'],
+        y=df['flex_cost'],
+        name='Flex Worker Cost',
+        line=dict(color='orange')
+    ))
+    fig.add_trace(go.Scatter(
+        x=df['requests_per_hour'],
+        y=df['total_cost'],
+        name='Total Cost',
+        line=dict(color='green', width=3)
+    ))
+
+    fig.update_layout(
+        title='RunPod Serverless Monthly Cost Projection',
+        xaxis_title='Requests per Hour',
+        yaxis_title='Monthly Cost ($)',
+        hovermode='x unified'
+    )
+    
+    return fig
+
+def calculate_specific_cost(
+    requests,
+    execution_time,
+    active_cost,
+    flex_cost,
+    active_percentage,
+    cold_start
+):
+    result = calculate_runpod_cost(
+        requests, 
+        execution_time, 
+        active_cost, 
+        flex_cost, 
+        cold_start, 
+        active_percentage/100
+    )
+    
+    # Format the output HTML for the table
+    html = f"""
+    <table style="width:100%; border-collapse: collapse;">
+      <tr style="background-color: #f2f2f2;">
+        <th style="padding: 12px; text-align: left; border: 1px solid #ddd;">Metric</th>
+        <th style="padding: 12px; text-align: right; border: 1px solid #ddd;">Value</th>
+      </tr>
+      <tr>
+        <td style="padding: 8px; border: 1px solid #ddd;">Monthly Requests</td>
+        <td style="padding: 8px; text-align: right; border: 1px solid #ddd;">{result['monthly_requests']:,.0f}</td>
+      </tr>
+      <tr>
+        <td style="padding: 8px; border: 1px solid #ddd;">Active Worker Cost</td>
+        <td style="padding: 8px; text-align: right; border: 1px solid #ddd;">${result['active_cost']:,.2f}</td>
+      </tr>
+      <tr>
+        <td style="padding: 8px; border: 1px solid #ddd;">Flex Worker Cost</td>
+        <td style="padding: 8px; text-align: right; border: 1px solid #ddd;">${result['flex_cost']:,.2f}</td>
+      </tr>
+      <tr style="font-weight: bold;">
+        <td style="padding: 8px; border: 1px solid #ddd;">Total Monthly Cost</td>
+        <td style="padding: 8px; text-align: right; border: 1px solid #ddd;">${result['total_monthly_cost']:,.2f}</td>
+      </tr>
+    </table>
+    """
+    
+    return html
+
+theme = gr.themes.Default(
+    primary_hue=gr.themes.colors.red,
+    secondary_hue=gr.themes.colors.red,
+    neutral_hue=gr.themes.colors.slate,
+)
+
+# Create Gradio interface
+with gr.Blocks(title="RunPod Serverless Cost Estimator", theme=theme) as demo:
+    gr.Markdown("# RunPod Serverless Cost Estimator")
+    gr.Markdown("Estimate your monthly RunPod Serverless costs based on request volume and execution time")
+    
+    with gr.Row():
+        with gr.Column(scale=1):
+            min_requests = gr.Slider(minimum=100, maximum=50000, value=1000, step=1000, label="Minimum Requests/Hour")
+            max_requests = gr.Slider(minimum=1000, maximum=100000, value=20000, step=1000, label="Maximum Requests/Hour")
+            execution_time = gr.Slider(minimum=1, maximum=120, value=30, step=1, label="Execution Time per Request (seconds)")
+            active_cost = gr.Number(value=0.00019, label="Active Worker Cost ($/second)", precision=5)
+            flex_cost = gr.Number(value=0.00031, label="Flex Worker Cost ($/second)", precision=5)
+            active_percentage = gr.Slider(minimum=0, maximum=100, value=50, step=1, label="% Requests on Active Workers")
+            cold_start = gr.Slider(minimum=0, maximum=60, value=30, step=1, label="Cold Start Penalty (seconds)")
+            
+            plot_button = gr.Button("Generate Cost Projection")
+        
+        with gr.Column(scale=2):
+            plot_output = gr.Plot(label="Cost Projection")
+    
+    gr.Markdown("## Cost Breakdown for Specific Request Volume")
+    
+    with gr.Row():
+        with gr.Column(scale=1):
+            specific_requests = gr.Number(value=10000, label="Requests per Hour", precision=0)
+            calc_button = gr.Button("Calculate Cost")
+        
+        with gr.Column(scale=2):
+            cost_table = gr.HTML()
+    
+    plot_button.click(
+        generate_cost_projection,
+        inputs=[min_requests, max_requests, execution_time, active_cost, flex_cost, active_percentage, cold_start],
+        outputs=plot_output
+    )
+    
+    calc_button.click(
+        calculate_specific_cost,
+        inputs=[specific_requests, execution_time, active_cost, flex_cost, active_percentage, cold_start],
+        outputs=cost_table
+    )
+
+# Launch the app
+if __name__ == "__main__":
+    demo.launch()