from langchain.text_splitter import RecursiveCharacterTextSplitter
from langchain.vectorstores import FAISS
from langchain_huggingface import HuggingFaceEmbeddings

embedding = HuggingFaceEmbeddings(model_name='sentence-transformers/all-MiniLM-L6-v2')

def vectorStore(data, embedding):
    splitter = RecursiveCharacterTextSplitter(chunk_size=1000, chunk_overlap=50)
    chunks = splitter.split_documents(data)
    vector = FAISS.from_documents(chunks, embedding)
    retriever = vector.as_retriever()
    return retriever