embedding/vector_store.py

from langchain_huggingface import HuggingFaceEmbeddings
from langchain_community.vectorstores import Chroma

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

def initialize_vector_store(split_docs, persist_directory="./chroma_db"):
    return Chroma.from_documents(
        documents=split_docs,
        embedding=embeddings,
        persist_directory=persist_directory
    )