text: " Start the task list with number {next_task_id}."        )        prompt = PromptTemplate(            template=task_prioritization_template,            input_variables=["task_names", "next_task_id", "objective"],        )        return cls(prompt=prompt, llm=llm, verbose=verbose)class ExecutionChain(LLMChain):    """Chain to execute tasks."""    @classmethod    def from_llm(cls, llm: BaseLLM, verbose: bool = True) -> LLMChain:        """Get the response parser."""        execution_template = (            "You are an AI who performs one task based on the following objective: {objective}."            " Take into account these previously completed tasks: {context}."            " Your task: {task}."            " Response:"        )        prompt = PromptTemplate(            template=execution_template,            input_variables=["objective", "context", "task"],        )        return cls(prompt=prompt, llm=llm, verbose=verbose)Define the BabyAGI Controllerâ€‹BabyAGI composes the chains defined above in a (potentially-)infinite loop.def get_next_task(