Add vector embedded data from PDF's to PineCone using Langchain and OpenAI

Question

I'm not sure what the alternative to .get() is for PineCone and Langchain. I want this code to run, but I keep getting an error that .get is not an attribute for Pinecone. I'm not sure what the alternative is to replace it.

def add_to_pinecone(chunks: list[Document]):
    VectorStore = Pinecone(index='portfolio-assistant', embedding=get_embeddings() ,pinecone_api_key=pc_api_key) # Connecting to Pinecone
    
    chunks_with_ids = calculate_chunk_ids(chunks)
    existing_items = **VectorStore.get(include=[])**
    existing_ids = set(existing_items["ids"])
    print(f'Number of existing documents in VectorStore: {len(existing_ids)}')

    new_chunks = []
    for chunk in chunks_with_ids:
        if chunk.metadata["id"] not in existing_ids:
            new_chunks.append(chunk)

    if len(new_chunks):
        print(f"Adding new documents: {len(new_chunks)}")
        new_chunk_ids = [chunk.metadata["id"] for chunk in new_chunks]
        VectorStore.add_document(new_chunks, ids=new_chunk_ids)
    else:
        print("No new documents to add")