Embedder/E5_Embeddedr.py

from sentence_transformers import SentenceTransformer,util
from Embedder.Embedder import Embedder

class E5_Embeddedr(Embedder):
    def __init__(self):
        self.model_name = "intfloat/multilingual-e5-small"
        self.model = SentenceTransformer(self.model_name)
        self.embedding_size = 384 # Fixed fot this model
    def embed(self,text):
      '''
      Embeds one text 
      
      Prefixed it with passage "passage" as e5 expect
      '''
      return self.model.encode(f"passage: {text}", normalize_embeddings=True)
    
#embed = E5_Embeddedr()
#embed.embed("مرحبا بك فى وى")