from langchain_community.document_loaders import PyPDFLoader
from langchain_community.vectorstores import FAISS
from langchain_huggingface import HuggingFaceEmbeddings
from langchain_text_splitters import RecursiveCharacterTextSplitter
from config import EMBEDDING_MODEL, FAISS_PATH, PDF_SOURCE

def make_vectorization():
    embedding_model = HuggingFaceEmbeddings(model_name=EMBEDDING_MODEL)

    loader = PyPDFLoader(PDF_SOURCE)
    documents = loader.load()

    text_splitter = RecursiveCharacterTextSplitter(
        chunk_size=1000,
        chunk_overlap=100,
        length_function=len,
        is_separator_regex=False
    )
    documents = text_splitter.split_documents(documents)
    vectorstore = FAISS.from_documents(documents, embedding_model)
    vectorstore.save_local(FAISS_PATH)

    return vectorstore