Source code for neo4j_graphrag.llm.mistralai_llm

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#  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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from __future__ import annotations

import os
from typing import Any, Optional, Union

from ..exceptions import LLMGenerationError
from .base import LLMInterface
from .types import LLMResponse

try:
    from mistralai import Mistral
    from mistralai.models.assistantmessage import AssistantMessage
    from mistralai.models.sdkerror import SDKError
    from mistralai.models.systemmessage import SystemMessage
    from mistralai.models.toolmessage import ToolMessage
    from mistralai.models.usermessage import UserMessage

    MessageType = Union[AssistantMessage, SystemMessage, ToolMessage, UserMessage]
except ImportError:
    Mistral = None  # type: ignore
    SDKError = None  # type: ignore


[docs] class MistralAILLM(LLMInterface): def __init__( self, model_name: str, model_params: Optional[dict[str, Any]] = None, **kwargs: Any, ): """ Args: model_name (str): model_params (str): Parameters like temperature and such that will be passed to the chat completions endpoint kwargs: All other parameters will be passed to the Mistral client. """ if Mistral is None: raise ImportError( """Could not import Mistral Python client. Please install it with `pip install "neo4j-graphrag[mistralai]"`.""" ) super().__init__(model_name, model_params) api_key = kwargs.pop("api_key", None) if api_key is None: api_key = os.getenv("MISTRAL_API_KEY", "") self.client = Mistral(api_key=api_key, **kwargs)
[docs] def get_messages(self, input: str) -> list[MessageType]: return [UserMessage(content=input)]
[docs] def invoke(self, input: str) -> LLMResponse: """Sends a text input to the Mistral chat completion model and returns the response's content. Args: input (str): Text sent to the LLM Returns: LLMResponse: The response from MistralAI. Raises: LLMGenerationError: If anything goes wrong. """ try: response = self.client.chat.complete( model=self.model_name, messages=self.get_messages(input), **self.model_params, ) content: str = "" if response and response.choices: possible_content = response.choices[0].message.content if isinstance(possible_content, str): content = possible_content return LLMResponse(content=content) except SDKError as e: raise LLMGenerationError(e)
[docs] async def ainvoke(self, input: str) -> LLMResponse: """Asynchronously sends a text input to the MistralAI chat completion model and returns the response's content. Args: input (str): Text sent to the LLM Returns: LLMResponse: The response from MistralAI. Raises: LLMGenerationError: If anything goes wrong. """ try: response = await self.client.chat.complete_async( model=self.model_name, messages=self.get_messages(input), **self.model_params, ) content: str = "" if response and response.choices: possible_content = response.choices[0].message.content if isinstance(possible_content, str): content = possible_content return LLMResponse(content=content) except SDKError as e: raise LLMGenerationError(e)