src/vector_store.py

import faiss
import numpy as np
import os


def build_faiss_index(embeddings):

    dimension = embeddings.shape[1]

    index = faiss.IndexFlatL2(dimension)

    index.add(np.array(embeddings))

    return index


def save_index(index, path="models/faiss_index"):

    faiss.write_index(index, path)


def load_index(path="models/faiss_index"):

    if os.path.exists(path):
        return faiss.read_index(path)
    else:
        return None