vectorstore.py

from langchain_community.vectorstores import FAISS
from langchain_community.embeddings import HuggingFaceEmbeddings

_embeddings = HuggingFaceEmbeddings(
    model_name="sentence-transformers/all-MiniLM-L6-v2"
)

_vector_db = None


def init_vectorstore(texts):
    global _vector_db
    _vector_db = FAISS.from_texts(texts, _embeddings)


def get_retriever():
    if _vector_db is None:
        return None
    return _vector_db.as_retriever(search_kwargs={"k": 4})