Source code for neo4j_graphrag.llm.base

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from __future__ import annotations

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

from .types import LLMResponse


[docs] 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, **kwargs: Any, ): self.model_name = model_name self.model_params = model_params or {}
[docs] @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. """
[docs] @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. """