"""Create the full inputs for the LLMChain from intermediate steps."""
        thoughts = self._construct_scratchpad(intermediate_steps)
        new_inputs = {"agent_scratchpad": thoughts, "stop": self._stop}
        full_inputs = {**kwargs, **new_inputs}
        return full_inputs
    @property
    def input_keys(self) -> List[str]:
        """Return the input keys.
        :meta private:
        """
        return list(set(self.llm_chain.input_keys) - {"agent_scratchpad"})
    @root_validator()
    def validate_prompt(cls, values: Dict) -> Dict:
        """Validate that prompt matches format."""
        prompt = values["llm_chain"].prompt
        if "agent_scratchpad" not in prompt.input_variables:
            logger.warning(
                "`agent_scratchpad` should be a variable in prompt.input_variables."
                " Did not find it, so adding it at the end."
            )
            prompt.input_variables.append("agent_scratchpad")
            if isinstance(prompt, PromptTemplate):
                prompt.template += "\n{agent_scratchpad}"
            elif isinstance(prompt, FewShotPromptTemplate):
                prompt.suffix += "\n{agent_scratchpad}"
            else:
                raise ValueError(f"Got unexpected prompt type {type(prompt)}")
        return values
    @property
    @abstractmethod
    def observation_prefix(self) -> str:
        """Prefix to append the observation with."""
    @property
    @abstractmethod
    def llm_prefix(self) -> str:
        """Prefix to append the LLM call with."""
[docs]    @classmethod
    @abstractmethod
    def create_prompt(cls, tools: Sequence[BaseTool]) -> BasePromptTemplate:
        """Create a prompt for this class."""
    @classmethod
rtdocs_stable/api.python.langchain.com/en/stable/_modules/langchain/agents/agent.html