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Create app.py
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import gradio as gr
import random
def predict_maintenance(equipment, hours, vibration, temp):
risk_score = round(random.uniform(10, 95), 1)
days_until = random.randint(5, 120)
confidence = round(random.uniform(75, 98), 1)
if risk_score > 70:
status = "⚠️ High Risk"
color = "red"
elif risk_score > 40:
status = "🟡 Medium Risk"
color = "orange"
else:
status = "✅ Low Risk"
color = "green"
result = f"""## {status}
**Equipment**: {equipment}
**Operating Hours**: {hours}
**Vibration Level**: {vibration}
**Temperature**: {temp}°C
### Predictive Analysis
- **Failure Risk Score**: {risk_score}%
- **Estimated Days Until Maintenance**: {days_until} days
- **Prediction Confidence**: {confidence}%
**Recommendation**: {'Schedule immediate inspection' if risk_score > 70 else 'Monitor regularly' if risk_score > 40 else 'Continue normal operations'}
---
**Anktechsol** - Predictive Maintenance AI
🔗 [Learn more](https://anktechsol.com)"""
return result
with gr.Blocks(title="Predictive Maintenance") as demo:
gr.Markdown("# 🔧 AI-Powered Predictive Maintenance")
gr.Markdown("Industrial equipment failure prediction - **Anktechsol**")
with gr.Row():
with gr.Column():
equipment = gr.Dropdown(["Motor A1", "Pump B2", "Compressor C3", "Conveyor D4"], label="Equipment", value="Motor A1")
hours = gr.Slider(0, 10000, value=5000, label="Operating Hours")
vibration = gr.Slider(0, 100, value=45, label="Vibration Level (mm/s)")
temp = gr.Slider(20, 100, value=65, label="Temperature (°C)")
btn = gr.Button("Predict Maintenance")
with gr.Column():
output = gr.Markdown()
btn.click(predict_maintenance, inputs=[equipment, hours, vibration, temp], outputs=output)
gr.Markdown("""---
### Anktechsol - Predictive Maintenance Experts
AI-driven industrial maintenance solutions. [Contact us](https://anktechsol.com)""")
demo.launch()