Source code for langchain_experimental.plan_and_execute.schema

from abc import abstractmethod
from typing import List, Tuple

from langchain_core.output_parsers import BaseOutputParser

from langchain_experimental.pydantic_v1 import BaseModel, Field

[docs]class Step(BaseModel): """Step.""" value: str """The value."""
[docs]class Plan(BaseModel): """Plan.""" steps: List[Step] """The steps."""
[docs]class StepResponse(BaseModel): """Step response.""" response: str """The response."""
[docs]class BaseStepContainer(BaseModel): """Base step container."""
[docs] @abstractmethod def add_step(self, step: Step, step_response: StepResponse) -> None: """Add step and step response to the container."""
[docs] @abstractmethod def get_final_response(self) -> str: """Return the final response based on steps taken."""
[docs]class ListStepContainer(BaseStepContainer): """Container for List of steps.""" steps: List[Tuple[Step, StepResponse]] = Field(default_factory=list) """The steps."""
[docs] def add_step(self, step: Step, step_response: StepResponse) -> None: self.steps.append((step, step_response))
[docs] def get_steps(self) -> List[Tuple[Step, StepResponse]]: return self.steps
[docs] def get_final_response(self) -> str: return self.steps[-1][1].response
[docs]class PlanOutputParser(BaseOutputParser): """Plan output parser."""
[docs] @abstractmethod def parse(self, text: str) -> Plan: """Parse into a plan."""