File size: 573 Bytes
b5816b4 | 1 2 3 4 5 6 7 8 9 10 11 12 13 | from src.ECRecom.constants import VECTOR_DB_PATH, EMBEDDING_MODEL
from langchain_community.vectorstores import FAISS
from langchain_huggingface import HuggingFaceEmbeddings
class LoadVectorDB:
def __init__(self):
self.vector_db_path=VECTOR_DB_PATH
def initiate(self,k:int=5):
embeddings = HuggingFaceEmbeddings(model_name=EMBEDDING_MODEL)
vector_db=FAISS.load_local(self.vector_db_path, embeddings=embeddings, allow_dangerous_deserialization=True)
retriver=vector_db.as_retriever(search_kwargs={"k": k})
return retriver |