Create ai_engine.py

modules/ai_engine.py

@@ -0,0 +1,14 @@
+import torch
+from transformers import AutoModelForSequenceClassification, AutoTokenizer
+import pandas as pd
+
+class AIEngine:
+    def __init__(self):
+        self.model = AutoModelForSequenceClassification.from_pretrained("bert-base-uncased")
+        self.tokenizer = AutoTokenizer.from_pretrained("bert-base-uncased")
+    
+    def predict_health(self, df):
+        # Example prediction logic (using simple logic for now)
+        df['HealthScore'] = df['Solar Gen (kWh)'].apply(lambda x: 1.0 if x > 5 else 0.5)
+        df['ML_Anomaly'] = df['HealthScore'].apply(lambda x: 'Normal' if x > 0.7 else 'Risk')
+        return df