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

def create_vectorstore(documents):
    if not documents:
        raise ValueError(
            "No valid source code found to build vector index."
        )

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

    return FAISS.from_documents(documents, embeddings)