import gradio as gr
import random

def simulate_edge(device_type, ai_model, edge_location):
    latency = round(random.uniform(2, 25), 1)
    accuracy = round(random.uniform(88, 99), 1)
    power = round(random.uniform(2, 12), 1)
    throughput = random.randint(15, 120)
    
    result = f"""### AIoT Edge Simulation Results

**Device Type**: {device_type}  
**AI Model**: {ai_model}  
**Edge Location**: {edge_location}

🎮 **Simulation Metrics**:
- Inference Latency: {latency}ms
- Model Accuracy: {accuracy}%
- Power Consumption: {power}W
- Throughput: {throughput} inferences/sec
- Edge Processing: {'Enabled' if random.choice([True, False]) else 'Cloud Fallback'}

**Status**: ✅ Simulation completed successfully

---
**Anktechsol** - AIoT & Edge AI Solutions  
🔗 [Visit anktechsol.com](https://anktechsol.com)"""
    return result

with gr.Blocks(title="AIoT Edge Simulator") as demo:
    gr.Markdown("# 🌐 AIoT & Edge AI Simulator")
    gr.Markdown("Test AIoT deployments - **Anktechsol**")
    
    with gr.Row():
        with gr.Column():
            device = gr.Dropdown(["Raspberry Pi 4", "Jetson Nano", "AWS IoT Greengrass", "Azure IoT Edge"], label="Edge Device", value="Raspberry Pi 4")
            model = gr.Dropdown(["Object Detection", "Image Classification", "Anomaly Detection", "Predictive Model"], label="AI Model", value="Object Detection")
            location = gr.Radio(["Factory Floor", "Warehouse", "Retail Store", "Remote Site"], label="Deployment Location", value="Factory Floor")
            btn = gr.Button("Run Simulation")
        
        with gr.Column():
            output = gr.Markdown()
    
    btn.click(simulate_edge, inputs=[device, model, location], outputs=output)
    
    gr.Markdown("""---
### Anktechsol - AIoT Specialists
Edge AI deployment & AIoT consulting. [Get started](https://anktechsol.com)""")

demo.launch()