models/anomaly.py

import pandas as pd
from transformers import pipeline
import logging

logger = logging.getLogger(__name__)

def detect_anomalies(df):
    """Detect anomalies in log data using a Hugging Face model."""
    logger.info("Detecting anomalies...")
    try:
        detector = pipeline(
            "text-classification",
            model="prajjwal1/bert-tiny",
            tokenizer="prajjwal1/bert-tiny",
            clean_up_tokenization_spaces=True
        )
        df["text"] = df["status"] + " Usage:" + df["usage_count"].astype(str)
        results = detector(df["text"].tolist())
        df["anomaly"] = [r["label"] for r in results]
        anomalies = df[df["anomaly"] == "POSITIVE"]
        logger.info(f"Detected {len(anomalies)} anomalies.")
        return anomalies
    except Exception as e:
        logger.error(f"Failed to detect anomalies: {e}")
        raise