code: def claude_test_completion():
      litellm.AnthropicConfig(max_tokens_to_sample=200)
      # litellm.set_verbose=True
      try:
          # OVERRIDE WITH DYNAMIC MAX TOKENS
          response_1 = litellm.completion(
              model="claude-instant-1",
              messages=[
                  {"content": "Hello, how are you?", "role": "user"}
              ],
              max_tokens=10,
          )
          # Add any assertions here to check the response
          print(response_1)
          response_1_text = response_1.choices[0].message.content
  
          # USE CONFIG TOKENS
          response_2 = litellm.completion(
              model="claude-instant-1",
              messages=[
                  {"content": "Hello, how are you?", "role": "user"}
              ],
          )
          # Add any assertions here to check the response
          print(response_2)
          response_2_text = response_2.choices[0].message.content
  
          assert len(response_2_text) > len(response_1_text)
  
          try:
              response_3 = litellm.completion(
                  model="claude-instant-1",
                  messages=[
                      {"content": "Hello, how are you?", "role": "user"}
                  ],
                  n=2,
              )
  
          except Exception as e:
              print(e)
      except Exception as e:
          pytest.fail(f"Error occurred: {e}")
  
file_path: litellm/litellm/tests/test_provider_specific_config.py
imports: import sys, os
  import traceback
  import pytest
  import litellm
  from litellm import completion
  from litellm import RateLimitError
label_desc: Use image node_id 1 for calling a global function with example usage: claude_test_completion() without return types