File size: 435 Bytes
e364d7d | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 | # embedding_handler.py
from sentence_transformers import SentenceTransformer
import numpy as np
class EmbeddingHandler:
def __init__(self, model_name: str = "intfloat/e5-base"):
self.model = SentenceTransformer(model_name)
def encode(self, text: str) -> np.ndarray:
if not text:
return np.zeros((768,))
return self.model.encode(text, convert_to_numpy=True, normalize_embeddings=True)
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