text: return []    @property    def output_keys(self) -> List[str]:        return []    def seed_agent(self):        # Step 1: seed the conversation        self.current_conversation_stage = self.retrieve_conversation_stage("1")        self.conversation_history = []    def determine_conversation_stage(self):        conversation_stage_id = self.stage_analyzer_chain.run(            conversation_history='"\n"'.join(self.conversation_history),            current_conversation_stage=self.current_conversation_stage,        )        self.current_conversation_stage = self.retrieve_conversation_stage(            conversation_stage_id        )        print(f"Conversation Stage: {self.current_conversation_stage}")    def human_step(self, human_input):        # process human input        human_input = "User: " + human_input + " <END_OF_TURN>"        self.conversation_history.append(human_input)    def step(self):        self._call(inputs={})    def _call(self, inputs: Dict[str, Any]) -> None:        """Run one step of the sales agent."""        # Generate agent's utterance        if self.use_tools:            ai_message = self.sales_agent_executor.run(