rag/settings.py

from langchain_community.vectorstores import FAISS
from langchain_huggingface import HuggingFaceEmbeddings


def get_embeddings_model():
    embeddings = HuggingFaceEmbeddings(
        model_name="sentence-transformers/all-MiniLM-L6-v2",
        model_kwargs={"device": "cuda"},
        encode_kwargs={"normalize_embeddings": True},
        show_progress=True,
    )
    print("Loaded embeddings model")
    return embeddings


def get_vector_store():
    return FAISS.load_local(
        folder_path="vector_store",
        embeddings=get_embeddings_model(),
        index_name="object_detection_models_faiss_index",
        allow_dangerous_deserialization=True,
    )