code: def test_large_trimming_multiple_messages():
      messages = [
          {
              "role": "user",
              "content": "This is a singlelongwordthatexceedsthelimit.",
          },
          {
              "role": "user",
              "content": "This is a singlelongwordthatexceedsthelimit.",
          },
          {
              "role": "user",
              "content": "This is a singlelongwordthatexceedsthelimit.",
          },
          {
              "role": "user",
              "content": "This is a singlelongwordthatexceedsthelimit.",
          },
          {
              "role": "user",
              "content": "This is a singlelongwordthatexceedsthelimit.",
          },
      ]
      trimmed_messages = trim_messages(
          messages, max_tokens=20, model="gpt-4-0613"
      )
      print("trimmed messages")
      print(trimmed_messages)
      assert (
          get_token_count(messages=trimmed_messages, model="gpt-4-0613")
      ) <= 20
  
imports: import sys, os
  from dotenv import load_dotenv
  import copy
  import os
  import pytest
  import litellm
  from litellm.utils import trim_messages, get_token_count, get_valid_models, check_valid_key, validate_environment, function_to_dict, token_counter
label_desc: Use image node_id 5 for calling a global function with example usage: test_large_trimming_multiple_messages() without return types