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from abc import abstractmethod
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from typing import List, Tuple
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2024-02-22 23:58:44 +00:00
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from langchain_core.output_parsers import BaseOutputParser
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Use a submodule for pydantic v1 compat (#9371)
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2023-08-17 15:35:49 +00:00
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from langchain_experimental.pydantic_v1 import BaseModel, Field
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class Step(BaseModel):
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"""Step."""
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value: str
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"""The value."""
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class Plan(BaseModel):
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"""Plan."""
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steps: List[Step]
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"""The steps."""
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class StepResponse(BaseModel):
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"""Step response."""
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response: str
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"""The response."""
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class BaseStepContainer(BaseModel):
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"""Base step container."""
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@abstractmethod
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def add_step(self, step: Step, step_response: StepResponse) -> None:
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"""Add step and step response to the container."""
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@abstractmethod
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def get_final_response(self) -> str:
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"""Return the final response based on steps taken."""
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class ListStepContainer(BaseStepContainer):
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"""Container for List of steps."""
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steps: List[Tuple[Step, StepResponse]] = Field(default_factory=list)
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"""The steps."""
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def add_step(self, step: Step, step_response: StepResponse) -> None:
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self.steps.append((step, step_response))
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def get_steps(self) -> List[Tuple[Step, StepResponse]]:
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return self.steps
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def get_final_response(self) -> str:
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return self.steps[-1][1].response
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class PlanOutputParser(BaseOutputParser):
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"""Plan output parser."""
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@abstractmethod
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def parse(self, text: str) -> Plan:
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"""Parse into a plan."""
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