code: def on_llm_start(
      self,
      serialized: Dict[str, Any],
      prompts: List[str],
      **kwargs: Any,
  ) -> None:
      if self._current_thought is None:
          self._current_thought = LLMThought(
              parent_container=self._parent_container,
              expanded=self._expand_new_thoughts,
              collapse_on_complete=self._collapse_completed_thoughts,
              labeler=self._thought_labeler,
          )
  
      self._current_thought.on_llm_start(serialized, prompts)
  
imports: from __future__ import annotations
  import time
  from enum import Enum
  from typing import TYPE_CHECKING, Any, Dict, List, NamedTuple, Optional
  from langchain.callbacks.base import BaseCallbackHandler
  from langchain.schema import AgentAction, AgentFinish, LLMResult
  from streamlit.runtime.metrics_util import gather_metrics
label_desc: Use image node_id 5 for calling the StreamlitCallbackHandler obj's underlying member method code with example usage: obj.on_llm_start(serialized, prompts) without return types