Source code for langchain_experimental.tot.checker

from abc import ABC, abstractmethod
from typing import Any, Dict, List, Optional, Tuple

from langchain.chains.base import Chain
from langchain_core.callbacks.manager import CallbackManagerForChainRun

from langchain_experimental.tot.thought import ThoughtValidity

[docs]class ToTChecker(Chain, ABC): """ Tree of Thought (ToT) checker. This is an abstract ToT checker that must be implemented by the user. You can implement a simple rule-based checker or a more sophisticated neural network based classifier. """ output_key: str = "validity" #: :meta private: @property def input_keys(self) -> List[str]: """The checker input keys. :meta private: """ return ["problem_description", "thoughts"] @property def output_keys(self) -> List[str]: """The checker output keys. :meta private: """ return [self.output_key]
[docs] @abstractmethod def evaluate( self, problem_description: str, thoughts: Tuple[str, ...] = (), ) -> ThoughtValidity: """ Evaluate the response to the problem description and return the solution type. """
def _call( self, inputs: Dict[str, Any], run_manager: Optional[CallbackManagerForChainRun] = None, ) -> Dict[str, ThoughtValidity]: return {self.output_key: self.evaluate(**inputs)}