Create app.py

app.py

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+import gradio as gr
+import pandas as pd
+import numpy as np
+import plotly.graph_objects as go
+from datetime import datetime
+
+# Fault classification logic
+def classify_fault(temperature, vibration, humidity, power, pressure):
+    """Classify device status based on sensor readings"""
+    
+    # Define thresholds
+    temp_normal = (15, 35)
+    vib_normal = (0, 50)
+    humidity_normal = (30, 70)
+    power_normal = (80, 120)
+    pressure_normal = (950, 1050)
+    
+    faults = []
+    severity_score = 0
+    
+    # Check temperature
+    if temperature < temp_normal[0] or temperature > temp_normal[1]:
+        if temperature < temp_normal[0] - 10 or temperature > temp_normal[1] + 10:
+            faults.append("❌ **CRITICAL**: Temperature out of range")
+            severity_score += 3
+        else:
+            faults.append("⚠️ **WARNING**: Temperature abnormal")
+            severity_score += 1
+    
+    # Check vibration
+    if vibration > vib_normal[1]:
+        if vibration > vib_normal[1] * 1.5:
+            faults.append("❌ **CRITICAL**: Excessive vibration detected")
+            severity_score += 3
+        else:
+            faults.append("⚠️ **WARNING**: Elevated vibration")
+            severity_score += 1
+    
+    # Check humidity
+    if humidity < humidity_normal[0] or humidity > humidity_normal[1]:
+        faults.append("⚠️ **WARNING**: Humidity out of optimal range")
+        severity_score += 1
+    
+    # Check power
+    if power < power_normal[0] or power > power_normal[1]:
+        if power < power_normal[0] * 0.7 or power > power_normal[1] * 1.3:
+            faults.append("❌ **CRITICAL**: Power consumption anomaly")
+            severity_score += 3
+        else:
+            faults.append("⚠️ **WARNING**: Power consumption unusual")
+            severity_score += 1
+    
+    # Check pressure
+    if pressure < pressure_normal[0] or pressure > pressure_normal[1]:
+        faults.append("⚠️ **WARNING**: Pressure deviation detected")
+        severity_score += 1
+    
+    # Determine overall status
+    if severity_score == 0:
+        status = "✅ NORMAL"
+        color = "green"
+        recommendation = "Device operating within normal parameters. Continue routine monitoring."
+    elif severity_score <= 3:
+        status = "⚠️ WARNING"
+        color = "orange"
+        recommendation = "Schedule inspection. Monitor closely for further degradation."
+    else:
+        status = "❌ FAILURE"
+        color = "red"
+        recommendation = "IMMEDIATE ACTION REQUIRED. Stop device and perform maintenance."
+    
+    # Create gauge chart
+    fig = go.Figure(go.Indicator(
+        mode="gauge+number+delta",
+        value=severity_score,
+        domain={'x': [0, 1], 'y': [0, 1]},
+        title={'text': "Fault Severity Score"},
+        delta={'reference': 0},
+        gauge={
+            'axis': {'range': [None, 10]},
+            'bar': {'color': color},
+            'steps': [
+                {'range': [0, 3], 'color': "lightgreen"},
+                {'range': [3, 6], 'color': "lightyellow"},
+                {'range': [6, 10], 'color': "lightcoral"}],
+            'threshold': {
+                'line': {'color': "red", 'width': 4},
+                'thickness': 0.75,
+                'value': 7}}))
+    
+    fig.update_layout(height=300)
+    
+    # Generate report
+    report = f"## {status}\n\n"
+    report += f"**Timestamp**: {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}\n"
+    report += f"**Severity Score**: {severity_score}/10\n\n"
+    
+    if faults:
+        report += "### Detected Issues:\n"
+        for fault in faults:
+            report += f"- {fault}\n"
+    else:
+        report += "### ✅ No Issues Detected\n"
+    
+    report += f"\n### Recommendation:\n{recommendation}\n\n"
+    report += "---\n**Sensor Readings:**\n"
+    report += f"- Temperature: {temperature}°C\n"
+    report += f"- Vibration: {vibration} Hz\n"
+    report += f"- Humidity: {humidity}%\n"
+    report += f"- Power: {power} W\n"
+    report += f"- Pressure: {pressure} hPa\n"
+    
+    return fig, report
+
+def classify_from_csv(file):
+    """Process CSV file with sensor data"""
+    if file is None:
+        return None, "Please upload a CSV file"
+    
+    try:
+        df = pd.read_csv(file.name)
+        
+        # Check required columns
+        required = ['temperature', 'vibration', 'humidity', 'power', 'pressure']
+        if not all(col in df.columns for col in required):
+            return None, f"⚠️ Missing columns. Required: {', '.join(required)}"
+        
+        # Process last row
+        last_row = df.iloc[-1]
+        return classify_fault(
+            last_row['temperature'],
+            last_row['vibration'],
+            last_row['humidity'],
+            last_row['power'],
+            last_row['pressure']
+        )
+    except Exception as e:
+        return None, f"❌ Error processing file: {str(e)}"
+
+# Create Gradio interface
+with gr.Blocks(title="Device Fault Classifier - Anktechsol", theme=gr.themes.Soft()) as demo:
+    gr.Markdown("""
+    # 🔧 IoT Device Fault Classifier
+    ### by **Anktechsol** - AI + IoT Experts
+    
+    Intelligent fault detection and classification for industrial IoT devices using AI-powered sensor analysis.
+    Identify device failures before they cause downtime!
+    """)
+    
+    with gr.Tabs():
+        with gr.Tab("📊 Manual Input"):
+            with gr.Row():
+                with gr.Column():
+                    temp_input = gr.Slider(0, 100, value=25, label="Temperature (°C)")
+                    vib_input = gr.Slider(0, 150, value=30, label="Vibration (Hz)")
+                    humid_input = gr.Slider(0, 100, value=50, label="Humidity (%)")
+                    power_input = gr.Slider(0, 200, value=100, label="Power (W)")
+                    pressure_input = gr.Slider(800, 1200, value=1013, label="Pressure (hPa)")
+                    classify_btn = gr.Button("🔍 Classify Status", variant="primary", size="lg")
+                    gr.Markdown("""
+                    ---
+                    ### 🔗 Resources
+                    - [Anktechsol](https://anktechsol.com)
+                    - [More Tools](https://huggingface.co/anktechsol)
+                    """)
+                
+                with gr.Column():
+                    gauge_plot = gr.Plot(label="Severity Gauge")
+                    report_output = gr.Markdown()
+            
+            classify_btn.click(
+                fn=classify_fault,
+                inputs=[temp_input, vib_input, humid_input, power_input, pressure_input],
+                outputs=[gauge_plot, report_output]
+            )
+        
+        with gr.Tab("📄 CSV Upload"):
+            gr.Markdown("""
+            Upload a CSV file with columns: `temperature`, `vibration`, `humidity`, `power`, `pressure`
+            
+            The classifier will analyze the most recent reading.
+            """)
+            with gr.Row():
+                csv_input = gr.File(label="Upload Sensor Data CSV", file_types=[".csv"])
+            with gr.Row():
+                csv_gauge = gr.Plot(label="Severity Gauge")
+            with gr.Row():
+                csv_report = gr.Markdown()
+            
+            csv_input.change(
+                fn=classify_from_csv,
+                inputs=[csv_input],
+                outputs=[csv_gauge, csv_report]
+            )
+    
+    # Auto-load demo
+    demo.load(
+        fn=lambda: classify_fault(25, 30, 50, 100, 1013),
+        outputs=[gauge_plot, report_output]
+    )
+
+if __name__ == "__main__":
+    demo.launch()