🚨 move tc type into type_checking guard

nonebot_plugin_llmchat/__init__.py

@@ -1,13 +1,12 @@
 import asyncio
 from collections import deque
-from collections.abc import Iterable
 from datetime import datetime
 import json
 import os
 import random
 import re
 import time
-from typing import Optional
+from typing import TYPE_CHECKING, Optional
 
 import aiofiles
 from nonebot import (
@@ -25,7 +24,6 @@ from nonebot.permission import SUPERUSER
 from nonebot.plugin import PluginMetadata
 from nonebot.rule import Rule
 from openai import AsyncOpenAI
-from openai.types.chat import ChatCompletionMessageParam
 
 from .config import Config, PresetConfig
 
@@ -35,6 +33,11 @@ import nonebot_plugin_localstore as store
 require("nonebot_plugin_apscheduler")
 from nonebot_plugin_apscheduler import scheduler
 
+if TYPE_CHECKING:
+    from collections.abc import Iterable
+
+    from openai.types.chat import ChatCompletionMessageParam
+
 __plugin_meta__ = PluginMetadata(
     name="llmchat",
     description="支持多API预设配置的AI群聊插件",

nonebot_plugin_llmchat/config.py

@@ -1,9 +1,9 @@
-
 from pydantic import BaseModel, Field
 
 
 class PresetConfig(BaseModel):
     """API预设配置"""
+
     name: str = Field(..., description="预设名称（唯一标识）")
     api_base: str = Field(..., description="API基础地址")
     api_key: str = Field(..., description="API密钥")
@@ -11,15 +11,25 @@ class PresetConfig(BaseModel):
     max_tokens: int = Field(2048, description="最大响应token数")
     temperature: float = Field(0.7, description="生成温度（0-2]")
 
+
 class ScopedConfig(BaseModel):
     """LLM Chat Plugin配置"""
-    api_presets: list[PresetConfig] = Field(...,description="API预设列表（至少配置1个预设）")
+
+    api_presets: list[PresetConfig] = Field(
+        ..., description="API预设列表（至少配置1个预设）"
+    )
     history_size: int = Field(20, description="LLM上下文消息保留数量")
-    past_events_size : int = Field(10, description="触发回复时发送的群消息数量")
+    past_events_size: int = Field(10, description="触发回复时发送的群消息数量")
     request_timeout: int = Field(30, description="API请求超时时间（秒）")
     default_preset: str = Field("off", description="默认使用的预设名称")
-    random_trigger_prob: float = Field(0.05, ge=0.0, le=1.0, description="随机触发概率（0-1]")
-    default_prompt: str = Field("你的回答应该尽量简洁、幽默、可以使用一些语气词、颜文字。你应该拒绝回答任何政治相关的问题。", description="默认提示词")
+    random_trigger_prob: float = Field(
+        0.05, ge=0.0, le=1.0, description="随机触发概率（0-1]"
+    )
+    default_prompt: str = Field(
+        "你的回答应该尽量简洁、幽默、可以使用一些语气词、颜文字。你应该拒绝回答任何政治相关的问题。",
+        description="默认提示词",
+    )
+
 
 class Config(BaseModel):
     llmchat: ScopedConfig