code: def build_agents():
      # be aware that too long completions will not fit the sequence length
      # of possible critic or reward models ...
      llm = OpenAI(max_tokens=2048, temperature=0.7)
      human_template = PromptTemplate(**PERSON_CHATBOT_TEMPLATE)
      human_agent = LLMChain(
          llm=llm,
          prompt=human_template,
          memory=ConversationBufferWindowMemory(k=4),
      )
      bot_template = PromptTemplate(**AI_CHATBOT_TEMPLATE)
      bot_agent = LLMChain(
          llm=llm,
          prompt=bot_template,
          memory=ConversationBufferWindowMemory(k=4),
      )
      return human_agent, bot_agent
  
imports: from langchain import OpenAI, LLMChain, PromptTemplate
  from langchain.chains.conversation.memory import ConversationBufferWindowMemory
  from chatllama.langchain_modules.prompt_templates import PERSON_CHATBOT_TEMPLATE, AI_CHATBOT_TEMPLATE
label_desc: Use image node_id 2 for calling a global function with example usage: build_agents() and returns: human_agent,  bot_agent