code: def test_check_abnormal_completions(self, caplog):
      component = OpenAIGenerator(api_key="test-api-key")
  
      # underlying implementation uses ChatMessage objects so we have to use them here
      messages: List[ChatMessage] = []
      for i, _ in enumerate(range(4)):
          message = ChatMessage.from_assistant("Hello")
          metadata = {
              "finish_reason": "content_filter"
              if i % 2 == 0
              else "length",
              "index": i,
          }
          message.meta.update(metadata)
          messages.append(message)
  
      for m in messages:
          component._check_finish_reason(m)
  
      # check truncation warning
      message_template = (
          "The completion for index {index} has been truncated before reaching a natural stopping point. "
          "Increase the max_tokens parameter to allow for longer completions."
      )
  
      for index in [1, 3]:
          assert caplog.records[
              index
          ].message == message_template.format(index=index)
  
      # check content filter warning
      message_template = "The completion for index {index} has been truncated due to the content filter."
      for index in [0, 2]:
          assert caplog.records[
              index
          ].message == message_template.format(index=index)
  
imports: import os
  from typing import List
  import pytest
  from openai import OpenAIError
  from haystack.components.generators import OpenAIGenerator
  from haystack.components.generators.utils import default_streaming_callback
  from haystack.dataclasses import StreamingChunk, ChatMessage
label_desc: Use image node_id 12 for calling the TestOpenAIGenerator obj's underlying member method code with example usage: obj.test_check_abnormal_completions(caplog) without return types