modules/ai_engine.py

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