class_docstr: A `Prompt` object that wraps prompts to be compatible with chat models, which use `openai.ChatCompletion.create`.
  
  The format expected by chat models is a list of messages, where each message is a dict with "role" and "content" keys.
class_docstr_tok: ["A","`","Prompt","`","object","that","wraps","prompts","to","be","compatible","with","chat","models",",","which","use","`","openai.ChatCompletion.create","`",".","The","format","expected","by","chat","models","is","a","list","of","messages",",","where","each","message","is","a","dict","with","``","role","''","and","``","content","''","keys","."]
docstr: Render a text string as a chat prompt. The default option we adopt here is to simply take the full prompt
  and treat it as a system message.
docstr_tok: ["Render","a","text","string","as","a","chat","prompt",".","The","default","option","we","adopt","here","is","to","simply","take","the","full","prompt","and","treat","it","as","a","system","message","."]
code: def _render_text_as_chat_prompt(
      self, prompt: str
  ) -> OpenAICreateChatPrompt:
      """
      Render a text string as a chat prompt. The default option we adopt here is to simply take the full prompt
      and treat it as a system message.
      """
      return text_prompt_to_chat_prompt(prompt)
  
file_path: evals/evals/prompt/base.py
imports: import logging
  import threading
  from abc import ABC, abstractmethod
  from dataclasses import dataclass
  from typing import Dict, List, Union
label_desc: Use image node_id 1 for calling the ChatCompletionPrompt obj's underlying member method code with example usage: obj._render_text_as_chat_prompt(prompt) and returns: text_prompt_to_chat_prompt