code: def test_chat_response():
      chat.ResponsePayload(
          **{
              "created": 100,
              "model": "gpt-4",
              "choices": [
                  {
                      "message": {"role": "user", "content": "content"},
                      "index": 0,
                  },
              ],
              "usage": {
                  "prompt_tokens": 1,
                  "completion_tokens": 1,
                  "total_tokens": 1,
              },
          }
      )
  
      chat.ResponsePayload(
          **{
              "id": "foobar",
              "created": 100,
              "model": "gpt-4",
              "object": "chat.completion",
              "choices": [
                  {
                      "message": {"role": "user", "content": "content"},
                      "finish_reason": "stop",
                      "index": 0,
                  },
              ],
              "usage": {
                  "prompt_tokens": 1,
                  "completion_tokens": 1,
                  "total_tokens": 1,
              },
          }
      )
  
      with pytest.raises(
          pydantic.ValidationError, match=r"(?i)field required"
      ):
          chat.ResponsePayload(**{"usage": {}})
  
imports: import pydantic
  import pytest
  from mlflow.gateway.schemas import chat
label_desc: Use image node_id 2 for calling a global function with example usage: test_chat_response() without return types