motleycrew.tools.agentic_validation_loop

Classes

AgenticValidationLoop(name, description, prompt)
PivotConfigToolInputSchema(*, question, ...)

class motleycrew.tools.agentic_validation_loop.PivotConfigToolInputSchema(*, question: str, datasource_kv_store_keys: List[str])

Bases: BaseModel

question: str

datasource_kv_store_keys: List[str]

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

class motleycrew.tools.agentic_validation_loop.AgenticValidationLoop(name: str, description: str, prompt: str | BasePromptTemplate, schema: Type[BaseModel] | None = None, post_process: Callable | None = None, llm: Any | None = None)

Bases: MotleyTool

__init__(name: str, description: str, prompt: str | BasePromptTemplate, schema: Type[BaseModel] | None = None, post_process: Callable | None = None, llm: Any | None = None)

Initialize the MotleyTool.

Parameters:

• name – Name of the tool (required if tool is None).

• description – Description of the tool (required if tool is None).

• args_schema – Schema of the tool arguments (required if tool is None).

• return_direct – If True, the tool’s output will be returned directly to the user.

• handle_exceptions –

  Whether to handle exceptions (return their message as output).

  If True, the tool will return any raised exception’s message as its output.

  If a list of exceptions is provided, only these exceptions will be handled.

  If False, the tool will raise the exception.

  If return_direct is True, the tool will always handle InvalidOutput exceptions, as the tool is considered an output handler.

• retry_config – Configuration for retry behavior. If None, exceptions will not be retried.

• tool – Langchain BaseTool to wrap. Usually not needed, as the tool is created from the run method.

run(**kwargs) → Any

Run the tool with the provided inputs.