v0.4.0 支持任意替换的模型，改进配置文件

好好好好好好好好好

src/plugins/schedule/schedule_generator.py

@@ -1,10 +1,10 @@
 import datetime
 import os
 from typing import List, Dict
-from .schedule_llm_module import LLMModel
 from ...common.database import Database  # 使用正确的导入语法
 from src.plugins.chat.config import global_config
 from nonebot import get_driver
+from ..models.utils_model import LLM_request
 
 driver = get_driver()
 config = driver.config
@@ -21,22 +21,27 @@ Database.initialize(
 
 class ScheduleGenerator:
     def __init__(self):
-        if global_config.API_USING == "siliconflow":
-            self.llm_scheduler = LLMModel(model_name=global_config.SILICONFLOW_MODEL_V3)
-        elif global_config.API_USING == "deepseek":
-            self.llm_scheduler = LLMModel(model_name=global_config.DEEPSEEK_MODEL_V3)
+        #根据global_config.llm_normal这一字典配置指定模型
+        # self.llm_scheduler = LLMModel(model = global_config.llm_normal,temperature=0.9)
+        self.llm_scheduler = LLM_request(model = global_config.llm_normal,temperature=0.9)
         self.db = Database.get_instance()
-        
+        self.today_schedule_text = ""
+        self.today_schedule = {}
+        self.tomorrow_schedule_text = ""
+        self.tomorrow_schedule = {}
+        self.yesterday_schedule_text = ""
+        self.yesterday_schedule = {}
+    
+    async def initialize(self):
         today = datetime.datetime.now()
         tomorrow = datetime.datetime.now() + datetime.timedelta(days=1)
         yesterday = datetime.datetime.now() - datetime.timedelta(days=1)
         
-        self.today_schedule_text, self.today_schedule = self.generate_daily_schedule(target_date=today)
-        
-        self.tomorrow_schedule_text, self.tomorrow_schedule = self.generate_daily_schedule(target_date=tomorrow,read_only=True)
-        self.yesterday_schedule_text, self.yesterday_schedule = self.generate_daily_schedule(target_date=yesterday,read_only=True)
+        self.today_schedule_text, self.today_schedule = await self.generate_daily_schedule(target_date=today)
+        self.tomorrow_schedule_text, self.tomorrow_schedule = await self.generate_daily_schedule(target_date=tomorrow,read_only=True)
+        self.yesterday_schedule_text, self.yesterday_schedule = await self.generate_daily_schedule(target_date=yesterday,read_only=True)
             
-    def generate_daily_schedule(self, target_date: datetime.datetime = None,read_only:bool = False) -> Dict[str, str]:
+    async def generate_daily_schedule(self, target_date: datetime.datetime = None,read_only:bool = False) -> Dict[str, str]:
         if target_date is None:
             target_date = datetime.datetime.now()
             
@@ -60,7 +65,7 @@ class ScheduleGenerator:
             3. 晚上的计划和休息时间
             请按照时间顺序列出具体时间点和对应的活动，用一个时间点而不是时间段来表示时间，用逗号,隔开时间与活动，格式为"时间,活动"，例如"08:00,起床"。"""
             
-            schedule_text, _ = self.llm_scheduler.generate_response(prompt)
+            schedule_text, _ = await self.llm_scheduler.generate_response(prompt)
             # print(self.schedule_text)
             self.db.db.schedule.insert_one({"date": date_str, "schedule": schedule_text})
         else:

src/plugins/schedule/schedule_llm_module.py

@@ -1,61 +0,0 @@
-import os
-import requests
-import aiohttp
-from typing import Tuple, Union
-from nonebot import get_driver
-from src.plugins.chat.config import global_config
-driver = get_driver()
-config = driver.config
-
-class LLMModel:
-    # def __init__(self, model_name="deepseek-ai/DeepSeek-R1-Distill-Qwen-32B", **kwargs):
-    def __init__(self, model_name=global_config.SILICONFLOW_MODEL_R1,api_using=None, **kwargs):
-        if api_using == "deepseek":
-            self.api_key = config.deep_seek_key
-            self.base_url = config.deep_seek_base_url
-            self.model_name = global_config.DEEPSEEK_MODEL_R1
-        else:
-            self.api_key = config.siliconflow_key
-            self.base_url = config.siliconflow_base_url
-            self.model_name = model_name
-        self.params = kwargs
-
-    def generate_response(self, prompt: str) -> Tuple[str, str]:
-        """根据输入的提示生成模型的响应"""
-        headers = {
-            "Authorization": f"Bearer {self.api_key}",
-            "Content-Type": "application/json"
-        }
-        
-        # 构建请求体
-        data = {
-            "model": self.model_name,
-            "messages": [{"role": "user", "content": prompt}],
-            "temperature": 0.9,
-            **self.params
-        }
-        
-        # 发送请求到完整的chat/completions端点
-        api_url = f"{self.base_url.rstrip('/')}/chat/completions"
-        
-        try:
-            response = requests.post(api_url, headers=headers, json=data)
-            response.raise_for_status()  # 检查响应状态
-            
-            result = response.json()
-            if "choices" in result and len(result["choices"]) > 0:
-                content = result["choices"][0]["message"]["content"]
-                reasoning_content = result["choices"][0]["message"].get("reasoning_content", "")
-                return content, reasoning_content  # 返回内容和推理内容
-            return "没有返回结果", ""  # 返回两个值
-                
-        except Exception as e:
-            return f"请求失败: {str(e)}", ""  # 返回错误信息和空字符串
-
-# 示例用法
-if __name__ == "__main__":
-    model = LLMModel()  # 默认使用 DeepSeek-V3 模型
-    prompt = "你好，你喜欢我吗？"
-    result, reasoning = model.generate_response(prompt)
-    print("回复内容:", result)
-    print("推理内容:", reasoning)