Untitled

# Embed chunks
@st.cache_data
def embed_chunks(chunks: list, store_name: str, api: str):           
    store_name = store_name
    if os.path.exists(f"{store_name}.pkl"):
        with open(f"{store_name}.pkl", "rb") as f:
            VectorStore = pickle.load(f)
        # st.write("Embeddings loaded from the disk")
        return VectorStore
    else:
        embeddings = OpenAIEmbeddings(openai_api_key=api)
        VectorStore = FAISS.from_texts(chunks, embeddings)
        with open(f"{store_name}.pkl", "wb") as f:
            pickle.dump(VectorStore, f)
        # st.write("Embeddings generated and saved to disk")
        return VectorStore