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graph_of_thoughts/prompter/__init__.py

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+from .prompter import Prompter

graph_of_thoughts/prompter/prompter.py

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+# Copyright (c) 2023 ETH Zurich.
+#                    All rights reserved.
+#
+# Use of this source code is governed by a BSD-style license that can be
+# found in the LICENSE file.
+#
+# main authors: Robert Gerstenberger, Nils Blach
+
+from __future__ import annotations
+from abc import ABC, abstractmethod
+from typing import Dict, List
+
+
+class Prompter(ABC):
+    """
+    Abstract base class that defines the interface for all prompters.
+    Prompters are used to generate the prompts for the language models.
+    """
+
+    @abstractmethod
+    def aggregation_prompt(self, state_dicts: List[Dict], **kwargs) -> str:
+        """
+        Generate a aggregation prompt for the language model.
+
+        :param state_dicts: The thought states that should be aggregated.
+        :type state_dicts: List[Dict]
+        :param kwargs: Additional keyword arguments.
+        :return: The aggregation prompt.
+        :rtype: str
+        """
+        pass
+
+    @abstractmethod
+    def improve_prompt(self, **kwargs) -> str:
+        """
+        Generate an improve prompt for the language model.
+        The thought state is unpacked to allow for additional keyword arguments
+        and concrete implementations to specify required arguments explicitly.
+
+        :param kwargs: Additional keyword arguments.
+        :return: The improve prompt.
+        :rtype: str
+        """
+        pass
+
+    @abstractmethod
+    def generate_prompt(self, num_branches: int, **kwargs) -> str:
+        """
+        Generate a generate prompt for the language model.
+        The thought state is unpacked to allow for additional keyword arguments
+        and concrete implementations to specify required arguments explicitly.
+
+        :param num_branches: The number of responses the prompt should ask the LM to generate.
+        :type num_branches: int
+        :param kwargs: Additional keyword arguments.
+        :return: The generate prompt.
+        :rtype: str
+        """
+        pass
+
+    @abstractmethod
+    def validation_prompt(self, **kwargs) -> str:
+        """
+        Generate a validation prompt for the language model.
+        The thought state is unpacked to allow for additional keyword arguments
+        and concrete implementations to specify required arguments explicitly.
+
+        :param kwargs: Additional keyword arguments.
+        :return: The validation prompt.
+        :rtype: str
+        """
+        pass
+
+    @abstractmethod
+    def score_prompt(self, state_dicts: List[Dict], **kwargs) -> str:
+        """
+        Generate a score prompt for the language model.
+
+        :param state_dicts: The thought states that should be scored,
+                            if more than one, they should be scored together.
+        :type state_dicts: List[Dict]
+        :param kwargs: Additional keyword arguments.
+        :return: The score prompt.
+        :rtype: str
+        """
+        pass