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Runtime error
File size: 1,210 Bytes
8e30b6a dcb5a1a 8e30b6a dcb5a1a 8e30b6a dcb5a1a 8e30b6a dcb5a1a 8e30b6a dcb5a1a | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 | import logging
import time
from typing import Dict, Any
from transformers import pipeline
logger = logging.getLogger(__name__)
_text_classifier = None
def _load_model():
global _text_classifier
if _text_classifier is None:
logger.info("Loading XLM-RoBERTa text detector model...")
_text_classifier = pipeline(
"text-classification",
model="yaya36095/xlm-roberta-text-detector",
device=-1
)
logger.info("Text detector model loaded successfully")
return _text_classifier
async def analyze_text(text: str) -> Dict[str, Any]:
start_time = time.time()
logger.info(f"Starting text analysis, length: {len(text)} chars")
classifier = _load_model()
result = classifier(text)
label = result[0]["label"]
score = result[0]["score"]
is_deepfake = label.lower() == "fake"
confidence = score
analysis_time = time.time() - start_time
response = {
"is_deepfake": is_deepfake,
"confidence": round(confidence, 3),
"analysis_time": round(analysis_time, 3),
}
logger.info(f"Text analysis completed. Result: {response}")
return response
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