class_docstr: Client for OpenAI's ChatGPT (https://openai.com/blog/chatgpt).
  We use the unofficial ChatGPT Python client: https://github.com/acheong08/ChatGPT.
  See https://github.com/acheong08/ChatGPT/wiki/Setup for the setup. The client requires Chrome or Chromium installed.
class_docstr_tok: ["Client","for","OpenAI","'s","ChatGPT","(","https",":","\/\/openai.com\/blog\/chatgpt",")",".","We","use","the","unofficial","ChatGPT","Python","client",":","https",":","\/\/github.com\/acheong08\/ChatGPT",".","See","https",":","\/\/github.com\/acheong08\/ChatGPT\/wiki\/Setup","for","the","setup",".","The","client","requires","Chrome","or","Chromium","installed","."]
code: def make_request(self, request: Request) -> RequestResult:
      completions: List[Sequence] = []
      all_cached = True
      request_time = 0
      request_datetime: Optional[int] = None
  
      # `num_completions` is not supported, so instead make `num_completions` separate requests.
      for completion_index in range(request.num_completions):
          try:
  
              def do_it():
                  with self._lock:
                      chat_bot = self._get_chat_bot_client()
                      chat_bot.refresh_session()
                      result: Dict[str, Any] = chat_bot.ask(
                          request.prompt
                      )
                      assert (
                          "message" in result
                      ), f"Invalid response: {result}"
                      hlog(f"Response: {result['message']}")
                      chat_bot.reset_chat()
                      return result
  
              raw_request: Dict[str, Any] = {
                  "model": request.model_engine,
                  "prompt": request.prompt,
                  "completion_index": completion_index,
              }
              cache_key = Client.make_cache_key(raw_request, request)
              response, cached = self.cache.get(
                  cache_key, wrap_request_time(do_it)
              )
              if not cached:
                  # Add some sleep between requests to attempt to hit the rate limit.
                  # The rate limit seems to be ~60 requests/hour
                  hlog("Made a request. Sleeping...")
                  time.sleep(ChatGPTClient.SECONDS_BETWEEN_REQUESTS)
          except Exception as e:
              error: str = f"ChatGPT error: {e}"
              return RequestResult(
                  success=False,
                  cached=False,
                  error=error,
                  completions=[],
                  embedding=[],
              )
  
          # The ChatGPT API doesn't support echo. If `echo_prompt` is true, combine the prompt and completion.
          text: str = (
              request.prompt + response["message"]
              if request.echo_prompt
              else response["message"]
          )
          # The ChatGPT API doesn't return us tokens or logprobs, so we tokenize ourselves.
          tokenization_result: TokenizationRequestResult = self.tokenize(
              # We're assuming ChatGPT uses the GPT-2 tokenizer.
              TokenizationRequest(text, tokenizer="huggingface/gpt2")
          )
  
          # Log probs are not currently not supported by the ChatGPT, so set to 0 for now.
          tokens: List[Token] = [
              Token(text=str(text), logprob=0, top_logprobs={})
              for text in tokenization_result.raw_tokens
          ]
          completion = Sequence(
              text=response["message"], logprob=0, tokens=tokens
          )
          completions.append(
              truncate_sequence(completion, request)
          )  # Truncate the text by stop sequences
          request_time += response["request_time"]
          request_datetime = (
              request_datetime or response["request_datetime"]
          )
          all_cached = all_cached and cached
  
      return RequestResult(
          success=True,
          cached=all_cached,
          request_time=request_time,
          request_datetime=request_datetime,
          completions=completions,
          embedding=[],
      )
  
file_path: H2O/h2o_hf/helm/src/helm/proxy/clients/chat_gpt_client.py
imports: import time
  from typing import Any, Dict, List, Optional
  from filelock import FileLock
  from helm.common.cache import Cache, CacheConfig
  from helm.common.hierarchical_logger import hlog
  from helm.common.request import Request, RequestResult, Sequence, Token
  from helm.common.tokenization_request import TokenizationRequest, TokenizationRequestResult, DecodeRequest, DecodeRequestResult
  from .client import Client, truncate_sequence, wrap_request_time
label_desc: Use image node_id 3 for calling the ChatGPTClient obj's underlying member method code with example usage: obj.make_request(request) and returns: RequestResult, RequestResult, result