src/llm_explain/utility/graph_of_thoughts/parser/parser.py

'''
Copyright 2024 Infosys Ltd.

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), 
to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, 
and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies 
or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, 
INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE 
AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, 
DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, 
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
'''

from __future__ import annotations
from abc import ABC, abstractmethod
from typing import Dict, List, Union


class Parser(ABC):
    """
    Abstract base class that defines the interface for all parsers.
    Parsers are used to parse the responses from the language models.
    """

    @abstractmethod
    def parse_aggregation_answer(
        self, states: List[Dict], texts: List[str]
    ) -> Union[Dict, List[Dict]]:
        """
        Parse the response from the language model for a aggregation prompt.

        :param states: The thought states used to generate the prompt.
        :type states: List[Dict]
        :param texts: The responses to the prompt from the language model.
        :type texts: List[str]
        :return: The new thought states after parsing the response from the language model.
        :rtype: Union[Dict, List[Dict]]
        """
        pass

    @abstractmethod
    def parse_improve_answer(self, state: Dict, texts: List[str]) -> Dict:
        """
        Parse the response from the language model for an improve prompt.

        :param state: The thought state used to generate the prompt.
        :type state: Dict
        :param texts: The responses to the prompt from the language model.
        :type texts: List[str]
        :return: The new thought state after parsing the response from the language model.
        :rtype: Dict
        """
        pass

    @abstractmethod
    def parse_generate_answer(self, state: Dict, texts: List[str]) -> List[Dict]:
        """
        Parse the response from the language model for a generate prompt.

        :param state: The thought state used to generate the prompt.
        :type state: Dict
        :param texts: The responses to the prompt from the language model.
        :type texts: List[str]
        :return: The new thought states after parsing the response from the language model.
        :rtype: List[Dict]
        """
        pass

    @abstractmethod
    def parse_validation_answer(self, state: Dict, texts: List[str]) -> bool:
        """
        Parse the response from the language model for a validation prompt.

        :param state: The thought state used to generate the prompt.
        :type state: Dict
        :param texts: The responses to the prompt from the language model.
        :type texts: List[str]
        :return: Whether the thought state is valid or not.
        :rtype: bool
        """
        pass

    @abstractmethod
    def parse_score_answer(self, states: List[Dict], texts: List[str]) -> List[float]:
        """
        Parse the response from the language model for a score prompt.

        :param states: The thought states used to generate the prompt.
        :type states: List[Dict]
        :param texts: The responses to the prompt from the language model.
        :type texts: List[str]
        :return: The scores for the thought states.
        :rtype: List[float]
        """
        pass