langchain.agents.schema.AgentScratchPadChatPromptTemplate¶
class langchain.agents.schema.AgentScratchPadChatPromptTemplate[source]¶
Bases: ChatPromptTemplate
Chat prompt template for the agent scratchpad.
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
param input_variables: List[str] [Required]¶
List of input variables in template messages. Used for validation.
param messages: List[Union[BaseMessagePromptTemplate, BaseMessage, BaseChatPromptTemplate]] [Required]¶
List of messages consisting of either message prompt templates or messages.
param output_parser: Optional[BaseOutputParser] = None¶
How to parse the output of calling an LLM on this formatted prompt.
param partial_variables: Mapping[str, Union[str, Callable[[], str]]] [Optional]¶
async abatch(inputs: List[Input], config: Optional[Union[RunnableConfig, List[RunnableConfig]]] = None, *, max_concurrency: Optional[int] = None) → List[Output]¶
async ainvoke(input: Input, config: Optional[RunnableConfig] = None) → Output¶
async astream(input: Input, config: Optional[RunnableConfig] = None) → AsyncIterator[Output]¶
batch(inputs: List[Input], config: Optional[Union[RunnableConfig, List[RunnableConfig]]] = None, *, max_concurrency: Optional[int] = None) → List[Output]¶
bind(**kwargs: Any) → Runnable[Input, Output]¶
Bind arguments to a Runnable, returning a new Runnable.
classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) → Model¶
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data.