class_docstr: Model parameters for the LLM API interface
class_docstr_tok: ["Model","parameters","for","the","LLM","API","interface"]
code: def openai_model_must_be_supported(cls, v, values):
      supported_models = get_available_openai_model_ids(values)
      if v not in supported_models:
          raise InvalidOpenAIModel(
              f"'model_id' must be one of {supported_models}, got {v}"
          )
      return v
  
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 1 for calling the OpenAIParameters obj's underlying member method code with example usage: obj.openai_model_must_be_supported(cls, v, values) and returns: v