diff --git a/README.md b/README.md index b005bc189..8dfbbe430 100644 --- a/README.md +++ b/README.md @@ -130,7 +130,7 @@ MaiMBot是一个开源项目，我们非常欢迎你的参与。你的贡献， ### 💬交流群 - [五群](https://qm.qq.com/q/JxvHZnxyec) 1022489779（开发和建议相关讨论）不一定有空回复，会优先写文档和代码 - [一群](https://qm.qq.com/q/VQ3XZrWgMs) 766798517 【已满】（开发和建议相关讨论）不一定有空回复，会优先写文档和代码 -- [二群](https://qm.qq.com/q/RzmCiRtHEW) 571780722 【已满】（开发和建议相关讨论）不一定有空回复，会优先写文档和代码 +- [二群](https://qm.qq.com/q/RzmCiRtHEW) 571780722（开发和建议相关讨论）不一定有空回复，会优先写文档和代码 - [三群](https://qm.qq.com/q/wlH5eT8OmQ) 1035228475【已满】（开发和建议相关讨论）不一定有空回复，会优先写文档和代码 - [四群](https://qm.qq.com/q/wlH5eT8OmQ) 729957033【已满】（开发和建议相关讨论）不一定有空回复，会优先写文档和代码 diff --git a/src/plugins/schedule/offline_llm.py b/src/plugins/schedule/offline_llm.py index e4dc23f93..5c56d9e00 100644 --- a/src/plugins/schedule/offline_llm.py +++ b/src/plugins/schedule/offline_llm.py @@ -22,57 +22,7 @@ class LLMModel: logger.info(f"API URL: {self.base_url}") # 使用 logger 记录 base_url - def generate_response(self, prompt: str) -> Union[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": 0.5, - **self.params, - } - - # 发送请求到完整的 chat/completions 端点 - api_url = f"{self.base_url.rstrip('/')}/chat/completions" - logger.info(f"Request URL: {api_url}") # 记录请求的 URL - - max_retries = 3 - base_wait_time = 15 # 基础等待时间（秒） - - for retry in range(max_retries): - try: - response = requests.post(api_url, headers=headers, json=data) - - if response.status_code == 429: - wait_time = base_wait_time * (2**retry) # 指数退避 - logger.warning(f"遇到请求限制(429)，等待{wait_time}秒后重试...") - time.sleep(wait_time) - continue - - response.raise_for_status() # 检查其他响应状态 - - 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 - return "没有返回结果", "" - - except Exception as e: - if retry < max_retries - 1: # 如果还有重试机会 - wait_time = base_wait_time * (2**retry) - logger.error(f"[回复]请求失败，等待{wait_time}秒后重试... 错误: {str(e)}") - time.sleep(wait_time) - else: - logger.error(f"请求失败: {str(e)}") - return f"请求失败: {str(e)}", "" - - logger.error("达到最大重试次数，请求仍然失败") - return "达到最大重试次数，请求仍然失败", "" - - async def generate_response_async(self, prompt: str) -> Union[str, Tuple[str, str]]: + async def generate_response_async(self, prompt: str) -> str: """异步方式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"} diff --git a/src/plugins/schedule/schedule_generator_pro.py b/src/plugins/schedule/schedule_generator_pro.py index 5a2c2a687..ceaf2afd2 100644 --- a/src/plugins/schedule/schedule_generator_pro.py +++ b/src/plugins/schedule/schedule_generator_pro.py @@ -20,7 +20,7 @@ class ScheduleGenerator: def __init__(self, name: str = "bot_name", personality: str = "你是一个爱国爱党的新时代青年", behavior: str = "你非常外向，喜欢尝试新事物和人交流"): # 使用离线LLM模型 - self.llm_scheduler = LLMModel(model_name="Pro/deepseek-ai/DeepSeek-V3", temperature=0.9) + self.llm_scheduler = LLMModel(model_name="Qwen/Qwen2.5-32B-Instruct", temperature=0.9) self.today_schedule_text = "" self.today_done_list = [] @@ -33,6 +33,8 @@ class ScheduleGenerator: self.behavior = behavior self.start_time = datetime.datetime.now() + + self.schedule_doing_update_interval = 60 #最好大于60 async def mai_schedule_start(self): """启动日程系统，每5分钟执行一次move_doing，并在日期变化时重新检查日程""" @@ -43,6 +45,8 @@ class ScheduleGenerator: self.print_schedule() while True: + print(self.get_current_num_task(1, True)) + current_time = datetime.datetime.now() # 检查是否需要重新生成日程（日期变化） @@ -56,8 +60,7 @@ class ScheduleGenerator: current_activity = await self.move_doing() logger.info(f"当前活动: {current_activity}") - # 等待5分钟 - await asyncio.sleep(300) # 300秒 = 5分钟 + await asyncio.sleep(self.schedule_doing_update_interval) except Exception as e: logger.error(f"日程系统运行时出错: {str(e)}") @@ -79,6 +82,8 @@ class ScheduleGenerator: # 检查今天的日程 self.today_schedule_text, self.today_done_list = self.load_schedule_from_db(today) + if not self.today_done_list: + self.today_done_list = [] if not self.today_schedule_text: logger.info(f"{today.strftime('%Y-%m-%d')}的日程不存在，准备生成新的日程") self.today_schedule_text = await self.generate_daily_schedule(target_date=today) @@ -98,10 +103,16 @@ class ScheduleGenerator: def construct_doing_prompt(self,time: datetime.datetime): now_time = time.strftime("%H:%M") - previous_doing = self.today_done_list[-20:] if len(self.today_done_list) > 20 else self.today_done_list + if self.today_done_list: + previous_doing = self.get_current_num_task(10, True) + print(previous_doing) + else: + previous_doing = "我没做什么事情" + + prompt = f"我是{self.name}，{self.personality}，{self.behavior}" prompt += f"我今天的日程是：{self.today_schedule_text}\n" - prompt += f"我之前做了的事情是：{previous_doing}\n" + prompt += f"我之前做了的事情是：{previous_doing}，从之前到现在已经过去了{self.schedule_doing_update_interval/60}分钟了\n" prompt += f"现在是{now_time}，结合我的个人特点和行为习惯," prompt += "推测我现在做什么，具体一些，详细一些\n" prompt += "直接返回我在做的事情，不要输出其他内容：" @@ -110,7 +121,7 @@ class ScheduleGenerator: async def generate_daily_schedule( self, target_date: datetime.datetime = None,) -> Dict[str, str]: daytime_prompt = self.construct_daytime_prompt(target_date) - daytime_response, _ = await self.llm_scheduler.generate_response(daytime_prompt) + daytime_response,_ = await self.llm_scheduler.generate_response_async(daytime_prompt) return daytime_response def _time_diff(self, time1: str, time2: str) -> int: @@ -160,15 +171,54 @@ class ScheduleGenerator: current_time = datetime.datetime.now() time_str = current_time.strftime("%H:%M") doing_prompt = self.construct_doing_prompt(current_time) - doing_response, _ = await self.llm_scheduler.generate_response(doing_prompt) - self.today_done_list.append(current_time,time_str + "在" + doing_response) + doing_response,_ = await self.llm_scheduler.generate_response_async(doing_prompt) + self.today_done_list.append((current_time, time_str + "时，" + doing_response)) await self.update_today_done_list() return doing_response + async def get_task_from_time_to_time(self, start_time: str, end_time: str): + """获取指定时间范围内的任务列表 + + Args: + start_time (str): 开始时间，格式为"HH:MM" + end_time (str): 结束时间，格式为"HH:MM" + + Returns: + list: 时间范围内的任务列表 + """ + result = [] + for task in self.today_done_list: + task_time = task[0] # 获取任务的时间戳 + task_time_str = task_time.strftime("%H:%M") + + # 检查任务时间是否在指定范围内 + if self._time_diff(start_time, task_time_str) >= 0 and self._time_diff(task_time_str, end_time) >= 0: + result.append(task) + + return result - + def get_current_num_task(self, num=1, time_info = False): + """获取最新加入的指定数量的日程 + + Args: + num (int): 需要获取的日程数量，默认为1 + + Returns: + list: 最新加入的日程列表 + """ + if not self.today_done_list: + return [] + + # 确保num不超过列表长度 + num = min(num, len(self.today_done_list)) + pre_doing = "" + for doing in self.today_done_list[-num:]: + pre_doing += doing[1] + + # 返回最新的num条日程 + return pre_doing def save_today_schedule_to_db(self): """保存日程到数据库，同时初始化 today_done_list""" @@ -200,18 +250,10 @@ class ScheduleGenerator: async def main(): # 使用示例 - scheduler = ScheduleGenerator(name="麦麦", personality="你叫麦麦，你19岁，是一个大二的女大学生，你有一头黑色短发，你会刷贴吧，你现在在学习心理学", behavior="你比较内向") - await scheduler.check_and_create_today_schedule() - scheduler.print_schedule() - print("\n当前任务：") - print(await scheduler.get_current_task()) + scheduler = ScheduleGenerator(name="麦麦", personality="你叫麦麦，你19岁，是一个大二的女大学生，你有一头黑色短发，你会刷贴吧，你现在在学习心理学", behavior="你比较内向，一般熬夜比较晚，然后第二天早上10点起床吃早午饭") + await scheduler.mai_schedule_start() + - print("昨天日程：") - print(scheduler.yesterday_schedule) - print("今天日程：") - print(scheduler.today_schedule) - print("明天日程：") - print(scheduler.tomorrow_schedule) # 当作为组件导入时使用的实例 bot_schedule = ScheduleGenerator()