async function handleResponseAsStream(clientResponse, apiResponse) {
  const reader = apiResponse.body.getReader();
  const nextDecoder = new TextDecoder();

  clientResponse.write("data: " + JSON.stringify(createBeginChunk()) + "\n\n");

  new ReadableStream({
    start(controller) {
      return pump();
      function pump() {
        return reader.read().then(({ done, value }) => {
          const textData = nextDecoder.decode(value);

          clientResponse.write(
            "data: " + JSON.stringify(createMessageChunk(textData)) + "\n\n"
          );

          // When no more data needs to be consumed, close the stream
          if (done) {
            clientResponse.write(
              "data: " + JSON.stringify(createEndChunk()) + "\n\n"
            );
            clientResponse.end();
            controller.close();
            return;
          }
          // Enqueue the next data chunk into our target stream
          controller.enqueue(value);
          return pump();
        });
      }
    },
  });
}

const createBeginChunk = () => ({
  id: "chatcmpl-123",
  object: "chat.completion.chunk",
  created: getCurrentDate(),
  model: "gpt-4",
  system_fingerprint: "",
  choices: [
    {
      index: 0,
      delta: { role: "assistant", content: "" },
      logprobs: null,
      finish_reason: null,
    },
  ],
});

const createMessageChunk = (text) => ({
  id: "chatcmpl-123",
  object: "chat.completion.chunk",
  created: getCurrentDate(),
  model: "gpt-4",
  system_fingerprint: "",
  choices: [
    {
      index: 0,
      delta: { content: text },
      logprobs: null,
      finish_reason: null,
    },
  ],
});

const createEndChunk = () => ({
  id: "chatcmpl-123",
  object: "chat.completion.chunk",
  created: getCurrentDate(),
  model: "gpt-4",
  system_fingerprint: "",
  choices: [{ index: 0, delta: {}, logprobs: null, finish_reason: "stop" }],
});