Update app.py

app.py

@@ -3,7 +3,6 @@ import joblib
 import pandas as pd
 import json
 
-# Load files
 model = joblib.load("isolation_forest_model.joblib")
 scaler = joblib.load("standard_scaler.joblib")
 features = joblib.load("features_to_scale.joblib")
@@ -11,43 +10,59 @@ features = joblib.load("features_to_scale.joblib")
 def predict(json_input):
 
     try:
-        # Convert JSON string to dict
-        data_dict = json.loads(json_input)
 
-        # Create dataframe
-        df = pd.DataFrame([data_dict])
+        data = json.loads(json_input)
 
-        # Ensure feature order
+        row = {}
+
+        # Global values
+        row["CWL_SEC_LOAD"] = data["cooling_load"]
+        row["OA_TEMP_WB"] = data["wet_bulb"]
+
+        # Unit 1
+        row["CHL_COMP_SPD_CTRL_1"] = data["units"][0]["speed"]
+        row["CT_FAN_SPD_CTRL_1"] = data["units"][0]["fan"]
+        row["CHL_CW_FLOW_1"] = data["units"][0]["flow"]
+
+        # Unit 2
+        row["CHL_COMP_SPD_CTRL_2"] = data["units"][1]["speed"]
+        row["CT_FAN_SPD_CTRL_2"] = data["units"][1]["fan"]
+        row["CHL_CW_FLOW_2"] = data["units"][1]["flow"]
+
+        # Unit 3
+        row["CHL_COMP_SPD_CTRL_3"] = data["units"][2]["speed"]
+        row["CT_FAN_SPD_CTRL_3"] = data["units"][2]["fan"]
+        row["CHL_CW_FLOW_3"] = data["units"][2]["flow"]
+
+        # Fill missing features
+        for col in features:
+            if col not in row:
+                row[col] = 0
+
+        df = pd.DataFrame([row])
         df = df[features]
 
-        # Scale
         scaled = scaler.transform(df)
 
-        # Predict
         prediction = model.predict(scaled)
         score = model.decision_function(scaled)
 
-        result = {
-            "prediction": "Anomaly"
+        return {
+            "prediction": "Fault"
             if prediction[0] == -1
             else "Normal",
 
-            "anomaly_score": float(score[0])
+            "fault_score": float(score[0])
         }
 
-        return result
-
     except Exception as e:
         return {"error": str(e)}
 
 demo = gr.Interface(
     fn=predict,
-    inputs=gr.Textbox(
-        lines=20,
-        label="JSON Input"
-    ),
+    inputs=gr.Textbox(lines=20, label="JSON Input"),
     outputs="json",
-    title="HVAC Anomaly Detection"
+    title="HVAC Fault Detection"
 )
 
 demo.launch(server_name="0.0.0.0", server_port=7860)