modules/huggingface_inference.py

import requests

def predict_alerts(df, hf_url, hf_token):
    headers = {"Authorization": f"Bearer {hf_token}"}
    preds = []

    for _, row in df.iterrows():
        input_payload = {
            "inputs": {
                "solar": row.get("Solar_Generation__c"),
                "wind": row.get("Wind_Generation__c"),
                "tilt": row.get("Tilt__c"),
                "vibration": row.get("Vibration__c"),
                "camera": row.get("Camera_Status__c")
            }
        }
        response = requests.post(hf_url, headers=headers, json=input_payload)
        if response.status_code == 200:
            result = response.json()
            preds.append(result[0]['label'] if isinstance(result, list) else result.get("label", "Unknown"))
        else:
            preds.append("Error")
    df["Alert_Prediction"] = preds
    return df