vector_store.py

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


def create_vector_store(documents):
    text_splitter = RecursiveCharacterTextSplitter(
        chunk_size=800,
        chunk_overlap=150
    )

    chunks = text_splitter.split_text(documents)

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

    vector_store = FAISS.from_texts(chunks, embeddings)
    return vector_store