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```
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
``` |