class_docstr: Saves vector store to disk
class_docstr_tok: ["Saves","vector","store","to","disk"]
code: def save_vector_store(self, vector_store: VectorStore):
      method_name = f"save_{self.config.vector_store_name}"
      getattr(self, method_name)(vector_store)
  
imports: import json
  from dataclasses import dataclass
  from functools import lru_cache, partial
  from typing import Any, Dict, List, Union
  import html2text
  import openai
  import pandas
  import requests
  import writer
  from langchain import Writer
  from langchain.callbacks.streaming_stdout import StreamingStdOutCallbackHandler
  from langchain.docstore.document import Document
  from langchain.document_loaders import DataFrameLoader
  from langchain.embeddings.base import Embeddings
  from langchain.embeddings.huggingface import HuggingFaceEmbeddings
  from langchain.vectorstores import FAISS, Chroma, VectorStore
  from pydantic import BaseModel, Extra, Field, validator
  from mindsdb.integrations.handlers.chromadb_handler.chromadb_handler import get_chromadb
  from mindsdb.integrations.handlers.rag_handler.exceptions import InvalidOpenAIModel, InvalidPromptTemplate, InvalidWriterModel, UnsupportedLLM, UnsupportedVectorStore
label_desc: Use image node_id 2 for calling the PersistedVectorStoreSaver obj's underlying member method code with example usage: obj.save_vector_store(vector_store) without return types