base.py

#  Copyright (c) "Neo4j"
#  Neo4j Sweden AB [https://neo4j.com]
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#  Licensed under the Apache License, Version 2.0 (the "License");
#  you may not use this file except in compliance with the License.
#  You may obtain a copy of the License at
#  #
#      https://www.apache.org/licenses/LICENSE-2.0
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#  distributed under the License is distributed on an "AS IS" BASIS,
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from __future__ import annotations

from abc import ABC, abstractmethod
from typing import Any, Optional

from .types import LLMResponse


class LLMInterface(ABC):
    """Interface for large language models.

    Args:
        model_name (str): The name of the language model.
        model_params (Optional[dict], optional): Additional parameters passed to the model when text is sent to it. Defaults to None.
        **kwargs (Any): Arguments passed to the model when for the class is initialised. Defaults to None.
    """

    def __init__(
        self,
        model_name: str,
        model_params: Optional[dict[str, Any]] = None,
        system_instruction: Optional[str] = None,
        **kwargs: Any,
    ):
        self.model_name = model_name
        self.model_params = model_params or {}
        self.system_instruction = system_instruction

    @abstractmethod
    def invoke(self, input: str) -> LLMResponse:
        """Sends a text input to the LLM and retrieves a response.

        Args:
            input (str): Text sent to the LLM

        Returns:
            LLMResponse: The response from the LLM.

        Raises:
            LLMGenerationError: If anything goes wrong.
        """

    @abstractmethod
    def chat(self, input: str, chat_history: list[str]) -> LLMResponse:
        """Sends a text input and a converstion history to the LLM and retrieves a response.

        Args:
            input (str): Text sent to the LLM
            chat_history (list[str]]): A list of previous messages in the conversation

        Returns:
            LLMResponse: The response from the LLM.

        Raises:
            LLMGenerationError: If anything goes wrong.
        """

    @abstractmethod
    async def ainvoke(self, input: str) -> LLMResponse:
        """Asynchronously sends a text input to the LLM and retrieves a response.

        Args:
            input (str): Text sent to the LLM

        Returns:
            LLMResponse: The response from the LLM.

        Raises:
            LLMGenerationError: If anything goes wrong.
        """