code: def log_event(
      self, kwargs, response_obj, start_time, end_time, print_verbose
  ):
      # Method definition
      # inspired by Langsmith http api here: https://github.com/langchain-ai/langsmith-cookbook/blob/main/tracing-examples/rest/rest.ipynb
      metadata = {}
      if "litellm_params" in kwargs:
          metadata = kwargs["litellm_params"].get("metadata", {})
      # set project name and run_name for langsmith logging
      # users can pass project_name and run name to litellm.completion()
      # Example: litellm.completion(model, messages, metadata={"project_name": "my-litellm-project", "run_name": "my-langsmith-run"})
      # if not set litellm will use default project_name = litellm-completion, run_name = LLMRun
      project_name = metadata.get("project_name", "litellm-completion")
      run_name = metadata.get("run_name", "LLMRun")
      print_verbose(
          f"Langsmith Logging - project_name: {project_name}, run_name {run_name}"
      )
      try:
          print_verbose(
              f"Langsmith Logging - Enters logging function for model {kwargs}"
          )
          import requests
          import datetime
          from datetime import timezone
  
          try:
              start_time = (
                  kwargs["start_time"]
                  .astimezone(timezone.utc)
                  .isoformat()
              )
              end_time = (
                  kwargs["end_time"]
                  .astimezone(timezone.utc)
                  .isoformat()
              )
          except:
              start_time = datetime.datetime.utcnow().isoformat()
              end_time = datetime.datetime.utcnow().isoformat()
  
          # filter out kwargs to not include any dicts, langsmith throws an erros when trying to log kwargs
          new_kwargs = {}
          for key in kwargs:
              value = kwargs[key]
              if key == "start_time" or key == "end_time":
                  pass
              elif type(value) != dict:
                  new_kwargs[key] = value
  
          requests.post(
              "https://api.smith.langchain.com/runs",
              json={
                  "name": run_name,
                  "run_type": "llm",  # this should always be llm, since litellm always logs llm calls. Langsmith allow us to log "chain"
                  "inputs": {**new_kwargs},
                  "outputs": response_obj.json(),
                  "session_name": project_name,
                  "start_time": start_time,
                  "end_time": end_time,
              },
              headers={"x-api-key": self.langsmith_api_key},
          )
          print_verbose(
              f"Langsmith Layer Logging - final response object: {response_obj}"
          )
      except:
          # traceback.print_exc()
          print_verbose(
              f"Langsmith Layer Error - {traceback.format_exc()}"
          )
          pass
  
file_path: litellm/litellm/integrations/langsmith.py
imports: import dotenv, os
  import requests
  import requests
  from datetime import datetime
  import traceback
label_desc: Use image node_id 2 for calling the LangsmithLogger obj's underlying member method code with example usage: obj.log_event(kwargs, response_obj, start_time, end_time, print_verbose) without return types