Update app.py

app.py

@@ -1,21 +1,28 @@
 import gradio as gr
-import json
-from model.anomaly_detector import detect_anomaly
+from model.anomaly_detector import detect_anomaly_plain_text
 
-def process_input(json_input):
-    try:
-        input_data = json.loads(json_input)
-        result = detect_anomaly(input_data)
-        return json.dumps(result, indent=2)
-    except Exception as e:
-        return f"Error: {str(e)}"
+def predict(agent_id, weekly_calls, missed_visits, travel_distance, lead_drop_rate):
+    input_data = {
+        "agent_id": agent_id,
+        "weekly_calls": weekly_calls,
+        "missed_visits": missed_visits,
+        "travel_distance": travel_distance,
+        "lead_drop_rate": lead_drop_rate
+    }
+    return detect_anomaly_plain_text(input_data)
 
 iface = gr.Interface(
-    fn=process_input,
-    inputs=gr.Textbox(label="Input JSON", lines=10, placeholder='Paste agent data in JSON format'),
-    outputs="text",
+    fn=predict,
+    inputs=[
+        gr.Textbox(label="Agent ID", placeholder="e.g., AG1541"),
+        gr.Slider(0, 20, step=1, label="Weekly Calls"),
+        gr.Slider(0, 20, step=1, label="Missed Visits"),
+        gr.Slider(0, 100, step=1, label="Travel Distance (km)"),
+        gr.Slider(0.0, 1.0, step=0.01, label="Lead Drop Rate")
+    ],
+    outputs=gr.Textbox(label="Analysis Result"),
     title="Agent Behavior Anomaly Detector",
-    description="Detects abnormal agent behavior using Isolation Forest"
+    description="Detects anomalies in agent behavior and provides reason in plain English."
 )
 
 if __name__ == "__main__":