code: def test_no_examples(examples):
      model = EvaluationModel(
          name="correctness",
          definition="definition",
          grading_prompt="grading prompt",
          examples=examples,
      ).to_dict()
  
      args_string = ""
      expected_prompt2 = """
      Task:
      You must return the following fields in your response in two lines, one below the other:
      score: Your numerical score for the model's correctness based on the rubric
      justification: Your reasoning about the model's correctness score
  
      You are an impartial judge. You will be given an input that was sent to a machine
      learning model, and you will be given an output that the model produced. You
      may also be given additional information that was used by the model to generate the output.
  
      Your task is to determine a numerical score called correctness based on the input and output.
      A definition of correctness and a grading rubric are provided below.
      You must use the grading rubric to determine your score. You must also justify your score.
  
      Examples could be included below for reference. Make sure to use them as references and to
      understand them before completing the task.
  
      Input:
      This is an input
  
      Output:
      This is an output
  
      Metric definition:
      definition
  
      Grading rubric:
      grading prompt
  
      You must return the following fields in your response in two lines, one below the other:
      score: Your numerical score for the model's correctness based on the rubric
      justification: Your reasoning about the model's correctness score
  
      Do not add additional new lines. Do not add any other fields.
        """
      prompt2 = model["eval_prompt"].format(
          input="This is an input",
          output="This is an output",
          grading_context_columns=args_string,
      )
      assert re.sub(r"\s+", "", prompt2) == re.sub(
          r"\s+", "", expected_prompt2
      )
  
imports: import re
  import pytest
  from mlflow.metrics.genai import EvaluationExample
  from mlflow.metrics.genai.prompts.v1 import EvaluationModel
label_desc: Use image node_id 2 for calling a global function with example usage: test_no_examples(examples) without return types