# Copyright (c) "Neo4j"
# Neo4j Sweden AB [https://neo4j.com]
# #
# 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
# #
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from __future__ import annotations
from abc import ABC, abstractmethod
from typing import Any, Optional
from .types import (
LLMMessage,
LLMResponse,
)
[docs]
class LLMInterface(ABC):
"""Interface for large language models.
Args:
model_name (str): The name of the language model.
model_params (Optional[dict]): 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,
**kwargs: Any,
):
self.model_name = model_name
self.model_params = model_params or {}
[docs]
@abstractmethod
def invoke(
self,
input: str,
message_history: Optional[list[LLMMessage]] = None,
system_instruction: Optional[str] = None,
) -> LLMResponse:
"""Sends a text input to the LLM and retrieves a response.
Args:
input (str): Text sent to the LLM.
message_history (Optional[list]): A collection previous messages, with each message having a specific role assigned.
system_instruction (Optional[str]): An option to override the llm system message for this invokation.
Returns:
LLMResponse: The response from the LLM.
Raises:
LLMGenerationError: If anything goes wrong.
"""
[docs]
@abstractmethod
async def ainvoke(
self,
input: str,
message_history: Optional[list[LLMMessage]] = None,
system_instruction: Optional[str] = None,
) -> LLMResponse:
"""Asynchronously sends a text input to the LLM and retrieves a response.
Args:
input (str): Text sent to the LLM.
message_history (Optional[list]): A collection previous messages, with each message having a specific role assigned.
system_instruction (Optional[str]): An option to override the llm system message for this invokation.
Returns:
LLMResponse: The response from the LLM.
Raises:
LLMGenerationError: If anything goes wrong.
"""