text: {})Define the Chainsâ€‹BabyAGI relies on three LLM chains:Task creation chain to select new tasks to add to the listTask prioritization chain to re-prioritize tasksExecution Chain to execute the tasksNOTE: in this notebook, the Execution chain will now be an agent.class TaskCreationChain(LLMChain):    """Chain to generates tasks."""    @classmethod    def from_llm(cls, llm: BaseLLM, verbose: bool = True) -> LLMChain:        """Get the response parser."""        task_creation_template = (            "You are an task creation AI that uses the result of an execution agent"            " to create new tasks with the following objective: {objective},"            " The last completed task has the result: {result}."            " This result was based on this task description: {task_description}."            " These are incomplete tasks: {incomplete_tasks}."            " Based on the result, create new tasks to be completed"            " by the AI system that do not overlap with incomplete tasks."            " Return the tasks as an array."        )        prompt = PromptTemplate(            template=task_creation_template,            input_variables=[                "result",