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4e9b744 | 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 | import logging
from sentence_transformers import SentenceTransformer, util
logger = logging.getLogger(__name__)
class SemanticService:
_instance = None
_model = None
def __new__(cls):
if cls._instance is None:
cls._instance = super(SemanticService, cls).__new__(cls)
return cls._instance
def _load_model(self):
if self._model is None:
logger.info("Loading Semantic model (all-MiniLM-L6-v2)...")
try:
self._model = SentenceTransformer('all-MiniLM-L6-v2')
except Exception as e:
logger.error(f"Failed to load Semantic model: {e}")
raise e
def compute_similarity(self, text1: str, text2: str) -> float:
"""
Computes semantic similarity between two texts.
Returns a score between 0.0 and 1.0.
"""
if not text1 or not text2:
return 0.0
self._load_model()
embeddings1 = self._model.encode(text1, convert_to_tensor=True)
embeddings2 = self._model.encode(text2, convert_to_tensor=True)
cosine_scores = util.cos_sim(embeddings1, embeddings2)
return float(cosine_scores[0][0])
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