langchain/experimental/plan_and_execute/planners/chat_planner.py/load_chat_planner
def load_chat_planner(
    llm: BaseLanguageModel, system_prompt: str = SYSTEM_PROMPT
) -> LLMPlanner:
    prompt_template = ChatPromptTemplate.from_messages(
        [
            SystemMessage(content=system_prompt),
            HumanMessagePromptTemplate.from_template("{input}"),
        ]
    )
    llm_chain = LLMChain(llm=llm, prompt=prompt_template)
    return LLMPlanner(
        llm_chain=llm_chain,
        output_parser=PlanningOutputParser(),
        stop=["<END_OF_PLAN>"],
    )