mirror of https://github.com/Mai-with-u/MaiBot.git
trying resolves conflicts
SnowindMe
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README.md
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README.md
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<img src="depends-data/maimai.png" alt="MaiBot" title="作者:略nd" width="300">
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# 麦麦！MaiCore-MaiBot
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[](https://deepwiki.com/DrSmoothl/MaiBot)
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<div style="text-align: center">
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<strong>
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<a href="https://www.bilibili.com/video/BV1amAneGE3P">🌟 演示视频</a> |
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<a href="#-更新和安装">🚀 快速入门</a> |
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<a href="#-文档">📃 教程</a> |
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<a href="#-讨论">💬 讨论</a> |
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<a href="#-贡献和致谢">🙋 贡献指南</a>
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</strong>
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</div>
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## 🎉 介绍
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**🍔MaiCore 是一个基于大语言模型的可交互智能体**
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- 💭 **智能对话系统**：基于 LLM 的自然语言交互。
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- 🤔 **实时思维系统**：模拟人类思考过程。
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- 💝 **情感表达系统**：丰富的表情包和情绪表达。
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- 🧠 **持久记忆系统**：基于图的长期记忆存储。
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- 🔄 **动态人格系统**：自适应的性格特征和表达方式。
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<div style="text-align: center">
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<a href="https://www.bilibili.com/video/BV1amAneGE3P" target="_blank">
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<picture>
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<source media="(max-width: 600px)" srcset="depends-data/video.png" width="100%">
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<img src="depends-data/video.png" width="30%" alt="麦麦演示视频">
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</picture>
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<br />
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👆 点击观看麦麦演示视频 👆
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</a>
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</div>
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## 🔥 更新和安装
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**最新版本: v0.7.0** ([更新日志](changelogs/changelog.md))
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可前往 [Release](https://github.com/MaiM-with-u/MaiBot/releases/) 页面下载最新版本
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可前往 [启动器发布页面](https://github.com/MaiM-with-u/mailauncher/releases/tag/v0.1.0)下载最新启动器
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**GitHub 分支说明：**
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- `main`: 稳定发布版本(推荐)
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- `dev`: 开发测试版本(不稳定)
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- `classical`: 旧版本(停止维护)
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### 最新版本部署教程
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- [从0.6升级须知](https://docs.mai-mai.org/faq/maibot/update_to_07.html)
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- [🚀 最新版本部署教程](https://docs.mai-mai.org/manual/deployment/mmc_deploy_windows.html) - 基于 MaiCore 的新版本部署方式(与旧版本不兼容)
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> [!WARNING]
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> - 从 0.6.x 旧版本升级前请务必阅读：[升级指南](https://docs.mai-mai.org/faq/maibot/update_to_07.html)
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> - 项目处于活跃开发阶段，功能和 API 可能随时调整。
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> - 文档未完善，有问题可以提交 Issue 或者 Discussion。
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> - QQ 机器人存在被限制风险，请自行了解，谨慎使用。
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> - 由于持续迭代，可能存在一些已知或未知的 bug。
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> - 由于程序处于开发中，可能消耗较多 token。
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## 💬 讨论
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- [一群](https://qm.qq.com/q/VQ3XZrWgMs) |
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[四群](https://qm.qq.com/q/wGePTl1UyY) |
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[二群](https://qm.qq.com/q/RzmCiRtHEW) |
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[五群](https://qm.qq.com/q/JxvHZnxyec)(已满) |
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[三群](https://qm.qq.com/q/wlH5eT8OmQ)(已满)
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## 📚 文档
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**部分内容可能更新不够及时，请注意版本对应**
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- [📚 核心 Wiki 文档](https://docs.mai-mai.org) - 项目最全面的文档中心，你可以了解麦麦有关的一切。
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### 设计理念(原始时代的火花)
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> **千石可乐说：**
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> - 这个项目最初只是为了给牛牛 bot 添加一点额外的功能，但是功能越写越多，最后决定重写。其目的是为了创造一个活跃在 QQ 群聊的"生命体"。目的并不是为了写一个功能齐全的机器人，而是一个尽可能让人感知到真实的类人存在。
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> - 程序的功能设计理念基于一个核心的原则："最像而不是好"。
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> - 如果人类真的需要一个 AI 来陪伴自己，并不是所有人都需要一个完美的，能解决所有问题的"helpful assistant"，而是一个会犯错的，拥有自己感知和想法的"生命形式"。
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> - 代码会保持开源和开放，但个人希望 MaiMbot 的运行时数据保持封闭，尽量避免以显式命令来对其进行控制和调试。我认为一个你无法完全掌控的个体才更能让你感觉到它的自主性，而视其成为一个对话机器。
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> - SengokuCola~~纯编程外行，面向 cursor 编程，很多代码写得不好多多包涵~~已得到大脑升级。
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## 🙋 贡献和致谢
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你可以阅读[开发文档](https://docs.mai-mai.org/develop/)来更好的了解麦麦!
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MaiCore 是一个开源项目，我们非常欢迎你的参与。你的贡献，无论是提交 bug 报告、功能需求还是代码 pr，都对项目非常宝贵。我们非常感谢你的支持！🎉
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但无序的讨论会降低沟通效率，进而影响问题的解决速度，因此在提交任何贡献前，请务必先阅读本项目的[贡献指南](docs/CONTRIBUTE.md)。(待补完)
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### 贡献者
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感谢各位大佬！
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<a href="https://github.com/MaiM-with-u/MaiBot/graphs/contributors">
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<img alt="contributors" src="https://contrib.rocks/image?repo=MaiM-with-u/MaiBot" />
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</a>
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### 致谢
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- [略nd](https://space.bilibili.com/1344099355): 为麦麦绘制人设。
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- [NapCat](https://github.com/NapNeko/NapCatQQ): 现代化的基于 NTQQ 的 Bot 协议端实现。
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**也感谢每一位给麦麦发展提出宝贵意见与建议的用户，感谢陪伴麦麦走到现在的你们！**
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## 📌 注意事项
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> [!WARNING]
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> 使用本项目前必须阅读和同意[用户协议](EULA.md)和[隐私协议](PRIVACY.md)。
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> 本应用生成内容来自人工智能模型，由 AI 生成，请仔细甄别，请勿用于违反法律的用途，AI 生成内容不代表本项目团队的观点和立场。
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## 麦麦仓库状态
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### Star 趋势
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[](https://starchart.cc/MaiM-with-u/MaiBot)
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## License
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GPL-3.0
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File diff suppressed because it is too large
Load Diff
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import time
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import os
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from typing import Optional, Dict, Any
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from src.common.logger_manager import get_logger
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import json
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logger = get_logger("hfc") # Logger Name Changed
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log_dir = "log/log_cycle_debug/"
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class CycleDetail:
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"""循环信息记录类"""
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def __init__(self, cycle_id: int):
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self.cycle_id = cycle_id
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self.prefix = ""
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self.thinking_id = ""
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self.start_time = time.time()
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self.end_time: Optional[float] = None
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self.timers: Dict[str, float] = {}
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# 新字段
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self.loop_observation_info: Dict[str, Any] = {}
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self.loop_process_info: Dict[str, Any] = {}
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self.loop_plan_info: Dict[str, Any] = {}
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self.loop_action_info: Dict[str, Any] = {}
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def to_dict(self) -> Dict[str, Any]:
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"""将循环信息转换为字典格式"""
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def convert_to_serializable(obj, depth=0, seen=None):
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if seen is None:
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seen = set()
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# 防止递归过深
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if depth > 5: # 降低递归深度限制
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return str(obj)
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# 防止循环引用
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obj_id = id(obj)
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if obj_id in seen:
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return str(obj)
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seen.add(obj_id)
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try:
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if hasattr(obj, "to_dict"):
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# 对于有to_dict方法的对象，直接调用其to_dict方法
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return obj.to_dict()
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elif isinstance(obj, dict):
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# 对于字典，只保留基本类型和可序列化的值
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return {
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k: convert_to_serializable(v, depth + 1, seen)
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for k, v in obj.items()
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if isinstance(k, (str, int, float, bool))
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}
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elif isinstance(obj, (list, tuple)):
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# 对于列表和元组，只保留可序列化的元素
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return [
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convert_to_serializable(item, depth + 1, seen)
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for item in obj
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if not isinstance(item, (dict, list, tuple))
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or isinstance(item, (str, int, float, bool, type(None)))
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]
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elif isinstance(obj, (str, int, float, bool, type(None))):
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return obj
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else:
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return str(obj)
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finally:
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seen.remove(obj_id)
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return {
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"cycle_id": self.cycle_id,
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"start_time": self.start_time,
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"end_time": self.end_time,
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"timers": self.timers,
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"thinking_id": self.thinking_id,
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"loop_observation_info": convert_to_serializable(self.loop_observation_info),
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"loop_process_info": convert_to_serializable(self.loop_process_info),
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"loop_plan_info": convert_to_serializable(self.loop_plan_info),
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"loop_action_info": convert_to_serializable(self.loop_action_info),
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}
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def complete_cycle(self):
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"""完成循环，记录结束时间"""
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self.end_time = time.time()
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# 处理 prefix，只保留中英文字符和基本标点
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if not self.prefix:
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self.prefix = "group"
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else:
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# 只保留中文、英文字母、数字和基本标点
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allowed_chars = set("abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789-_")
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self.prefix = (
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"".join(char for char in self.prefix if "\u4e00" <= char <= "\u9fff" or char in allowed_chars)
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or "group"
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)
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current_time_minute = time.strftime("%Y%m%d_%H%M", time.localtime())
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try:
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self.log_cycle_to_file(
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log_dir + self.prefix + f"/{current_time_minute}_cycle_" + str(self.cycle_id) + ".json"
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)
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except Exception as e:
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logger.warning(f"写入文件日志，可能是群名称包含非法字符: {e}")
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def log_cycle_to_file(self, file_path: str):
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"""将循环信息写入文件"""
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# 如果目录不存在，则创建目
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dir_name = os.path.dirname(file_path)
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# 去除特殊字符，保留字母、数字、下划线、中划线和中文
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dir_name = "".join(
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char for char in dir_name if char.isalnum() or char in ["_", "-", "/"] or "\u4e00" <= char <= "\u9fff"
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)
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# print("dir_name:", dir_name)
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if dir_name and not os.path.exists(dir_name):
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os.makedirs(dir_name, exist_ok=True)
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# 写入文件
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file_path = os.path.join(dir_name, os.path.basename(file_path))
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# print("file_path:", file_path)
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with open(file_path, "a", encoding="utf-8") as f:
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f.write(json.dumps(self.to_dict(), ensure_ascii=False) + "\n")
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def set_thinking_id(self, thinking_id: str):
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"""设置思考消息ID"""
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self.thinking_id = thinking_id
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def set_loop_info(self, loop_info: Dict[str, Any]):
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"""设置循环信息"""
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self.loop_observation_info = loop_info["loop_observation_info"]
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self.loop_processor_info = loop_info["loop_processor_info"]
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self.loop_plan_info = loop_info["loop_plan_info"]
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self.loop_action_info = loop_info["loop_action_info"]
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import asyncio
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import contextlib
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import time
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import traceback
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from collections import deque
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from typing import List, Optional, Dict, Any, Deque, Callable, Awaitable
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from src.chat.message_receive.chat_stream import ChatStream
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from src.chat.message_receive.chat_stream import chat_manager
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from rich.traceback import install
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from src.chat.utils.prompt_builder import global_prompt_manager
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from src.common.logger_manager import get_logger
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from src.chat.utils.timer_calculator import Timer
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from src.chat.heart_flow.observation.observation import Observation
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from src.chat.focus_chat.heartFC_Cycleinfo import CycleDetail
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from src.chat.focus_chat.info.info_base import InfoBase
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from src.chat.focus_chat.info_processors.chattinginfo_processor import ChattingInfoProcessor
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from src.chat.focus_chat.info_processors.relationship_processor import RelationshipProcessor
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from src.chat.focus_chat.info_processors.mind_processor import MindProcessor
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from src.chat.focus_chat.info_processors.working_memory_processor import WorkingMemoryProcessor
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# from src.chat.focus_chat.info_processors.action_processor import ActionProcessor
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from src.chat.heart_flow.observation.hfcloop_observation import HFCloopObservation
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from src.chat.heart_flow.observation.working_observation import WorkingMemoryObservation
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from src.chat.heart_flow.observation.chatting_observation import ChattingObservation
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from src.chat.heart_flow.observation.structure_observation import StructureObservation
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from src.chat.heart_flow.observation.actions_observation import ActionObservation
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from src.chat.focus_chat.info_processors.tool_processor import ToolProcessor
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from src.chat.focus_chat.expressors.default_expressor import DefaultExpressor
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from src.chat.focus_chat.replyer.default_replyer import DefaultReplyer
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from src.chat.focus_chat.memory_activator import MemoryActivator
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from src.chat.focus_chat.info_processors.base_processor import BaseProcessor
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from src.chat.focus_chat.info_processors.self_processor import SelfProcessor
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from src.chat.focus_chat.planners.planner_factory import PlannerFactory
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from src.chat.focus_chat.planners.modify_actions import ActionModifier
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from src.chat.focus_chat.planners.action_manager import ActionManager
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from src.chat.focus_chat.working_memory.working_memory import WorkingMemory
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from src.config.config import global_config
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install(extra_lines=3)
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# 定义观察器映射：键是观察器名称，值是 (观察器类, 初始化参数)
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OBSERVATION_CLASSES = {
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"ChattingObservation": (ChattingObservation, "chat_id"),
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"WorkingMemoryObservation": (WorkingMemoryObservation, "observe_id"),
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"HFCloopObservation": (HFCloopObservation, "observe_id"),
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"StructureObservation": (StructureObservation, "observe_id"),
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}
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# 定义处理器映射：键是处理器名称，值是 (处理器类, 可选的配置键名)
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PROCESSOR_CLASSES = {
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"ChattingInfoProcessor": (ChattingInfoProcessor, None),
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"MindProcessor": (MindProcessor, "mind_processor"),
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"ToolProcessor": (ToolProcessor, "tool_use_processor"),
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"WorkingMemoryProcessor": (WorkingMemoryProcessor, "working_memory_processor"),
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"SelfProcessor": (SelfProcessor, "self_identify_processor"),
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"RelationshipProcessor": (RelationshipProcessor, "relationship_processor"),
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}
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logger = get_logger("hfc") # Logger Name Changed
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async def _handle_cycle_delay(action_taken_this_cycle: bool, cycle_start_time: float, log_prefix: str):
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"""处理循环延迟"""
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cycle_duration = time.monotonic() - cycle_start_time
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try:
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sleep_duration = 0.0
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if not action_taken_this_cycle and cycle_duration < 1:
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sleep_duration = 1 - cycle_duration
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elif cycle_duration < 0.2:
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sleep_duration = 0.2
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if sleep_duration > 0:
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await asyncio.sleep(sleep_duration)
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except asyncio.CancelledError:
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logger.info(f"{log_prefix} Sleep interrupted, loop likely cancelling.")
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raise
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class HeartFChatting:
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"""
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管理一个连续的Focus Chat循环
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用于在特定聊天流中生成回复。
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其生命周期现在由其关联的 SubHeartflow 的 FOCUSED 状态控制。
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"""
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def __init__(
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self,
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chat_id: str,
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||||
on_stop_focus_chat: Optional[Callable[[], Awaitable[None]]] = None,
|
||||
):
|
||||
"""
|
||||
HeartFChatting 初始化函数
|
||||
|
||||
参数:
|
||||
chat_id: 聊天流唯一标识符(如stream_id)
|
||||
on_stop_focus_chat: 当收到stop_focus_chat命令时调用的回调函数
|
||||
"""
|
||||
# 基础属性
|
||||
self.stream_id: str = chat_id # 聊天流ID
|
||||
self.chat_stream = chat_manager.get_stream(self.stream_id)
|
||||
self.log_prefix = f"[{chat_manager.get_stream_name(self.stream_id) or self.stream_id}]"
|
||||
|
||||
self.memory_activator = MemoryActivator()
|
||||
|
||||
# 初始化观察器
|
||||
self.observations: List[Observation] = []
|
||||
self._register_observations()
|
||||
|
||||
# 根据配置文件和默认规则确定启用的处理器
|
||||
config_processor_settings = global_config.focus_chat_processor
|
||||
self.enabled_processor_names = [
|
||||
proc_name for proc_name, (_proc_class, config_key) in PROCESSOR_CLASSES.items()
|
||||
if not config_key or getattr(config_processor_settings, config_key, True)
|
||||
]
|
||||
|
||||
# logger.info(f"{self.log_prefix} 将启用的处理器: {self.enabled_processor_names}")
|
||||
|
||||
self.processors: List[BaseProcessor] = []
|
||||
self._register_default_processors()
|
||||
|
||||
self.expressor = DefaultExpressor(chat_stream=self.chat_stream)
|
||||
self.replyer = DefaultReplyer(chat_stream=self.chat_stream)
|
||||
|
||||
|
||||
self.action_manager = ActionManager()
|
||||
self.action_planner = PlannerFactory.create_planner(
|
||||
log_prefix=self.log_prefix, action_manager=self.action_manager
|
||||
)
|
||||
self.action_modifier = ActionModifier(action_manager=self.action_manager)
|
||||
self.action_observation = ActionObservation(observe_id=self.stream_id)
|
||||
self.action_observation.set_action_manager(self.action_manager)
|
||||
|
||||
|
||||
self._processing_lock = asyncio.Lock()
|
||||
|
||||
# 循环控制内部状态
|
||||
self._loop_active: bool = False # 循环是否正在运行
|
||||
self._loop_task: Optional[asyncio.Task] = None # 主循环任务
|
||||
|
||||
# 添加循环信息管理相关的属性
|
||||
self._cycle_counter = 0
|
||||
self._cycle_history: Deque[CycleDetail] = deque(maxlen=10) # 保留最近10个循环的信息
|
||||
self._current_cycle_detail: Optional[CycleDetail] = None
|
||||
self._shutting_down: bool = False # 关闭标志位
|
||||
|
||||
# 存储回调函数
|
||||
self.on_stop_focus_chat = on_stop_focus_chat
|
||||
|
||||
def _register_observations(self):
|
||||
"""注册所有观察器"""
|
||||
self.observations = [] # 清空已有的
|
||||
|
||||
for name, (observation_class, param_name) in OBSERVATION_CLASSES.items():
|
||||
try:
|
||||
# 根据参数名使用正确的参数
|
||||
kwargs = {param_name: self.stream_id}
|
||||
observation = observation_class(**kwargs)
|
||||
self.observations.append(observation)
|
||||
logger.debug(f"{self.log_prefix} 注册观察器 {name}")
|
||||
except Exception as e:
|
||||
logger.error(f"{self.log_prefix} 观察器 {name} 构造失败: {e}")
|
||||
|
||||
if self.observations:
|
||||
logger.info(f"{self.log_prefix} 已注册观察器: {[o.__class__.__name__ for o in self.observations]}")
|
||||
else:
|
||||
logger.warning(f"{self.log_prefix} 没有注册任何观察器")
|
||||
|
||||
def _register_default_processors(self):
|
||||
"""根据 self.enabled_processor_names 注册信息处理器"""
|
||||
self.processors = [] # 清空已有的
|
||||
|
||||
for name in self.enabled_processor_names: # 'name' is "ChattingInfoProcessor", etc.
|
||||
processor_info = PROCESSOR_CLASSES.get(name) # processor_info is (ProcessorClass, config_key)
|
||||
if processor_info:
|
||||
processor_actual_class = processor_info[0] # 获取实际的类定义
|
||||
# 根据处理器类名判断是否需要 subheartflow_id
|
||||
if name in ["MindProcessor", "ToolProcessor", "WorkingMemoryProcessor", "SelfProcessor", "RelationshipProcessor"]:
|
||||
self.processors.append(processor_actual_class(subheartflow_id=self.stream_id))
|
||||
elif name == "ChattingInfoProcessor":
|
||||
self.processors.append(processor_actual_class())
|
||||
else:
|
||||
# 对于PROCESSOR_CLASSES中定义但此处未明确处理构造的处理器
|
||||
# (例如, 新增了一个处理器到PROCESSOR_CLASSES, 它不需要id, 也不叫ChattingInfoProcessor)
|
||||
try:
|
||||
self.processors.append(processor_actual_class()) # 尝试无参构造
|
||||
logger.debug(f"{self.log_prefix} 注册处理器 {name} (尝试无参构造).")
|
||||
except TypeError:
|
||||
logger.error(
|
||||
f"{self.log_prefix} 处理器 {name} 构造失败。它可能需要参数（如 subheartflow_id）但未在注册逻辑中明确处理。"
|
||||
)
|
||||
else:
|
||||
# 这理论上不应该发生，因为 enabled_processor_names 是从 PROCESSOR_CLASSES 的键生成的
|
||||
logger.warning(
|
||||
f"{self.log_prefix} 在 PROCESSOR_CLASSES 中未找到名为 '{name}' 的处理器定义，将跳过注册。"
|
||||
)
|
||||
|
||||
if self.processors:
|
||||
logger.info(
|
||||
f"{self.log_prefix} 已注册处理器: {[p.__class__.__name__ for p in self.processors]}"
|
||||
)
|
||||
else:
|
||||
logger.warning(f"{self.log_prefix} 没有注册任何处理器。这可能是由于配置错误或所有处理器都被禁用了。")
|
||||
|
||||
async def start(self):
|
||||
"""检查是否需要启动主循环，如果未激活则启动。"""
|
||||
# 如果循环已经激活，直接返回
|
||||
if self._loop_active:
|
||||
return
|
||||
|
||||
# 标记为活动状态，防止重复启动
|
||||
self._loop_active = True
|
||||
|
||||
# 检查是否已有任务在运行（理论上不应该，因为 _loop_active=False）
|
||||
if self._loop_task and not self._loop_task.done():
|
||||
logger.warning(f"{self.log_prefix} 发现之前的循环任务仍在运行（不符合预期）。取消旧任务。")
|
||||
self._loop_task.cancel()
|
||||
try:
|
||||
# 等待旧任务确实被取消
|
||||
await asyncio.wait_for(self._loop_task, timeout=0.5)
|
||||
except (asyncio.CancelledError, asyncio.TimeoutError):
|
||||
pass # 忽略取消或超时错误
|
||||
self._loop_task = None # 清理旧任务引用
|
||||
|
||||
self._loop_task = asyncio.create_task(self._run_focus_chat())
|
||||
self._loop_task.add_done_callback(self._handle_loop_completion)
|
||||
|
||||
def _handle_loop_completion(self, task: asyncio.Task):
|
||||
"""当 _hfc_loop 任务完成时执行的回调。"""
|
||||
try:
|
||||
exception = task.exception()
|
||||
if exception:
|
||||
logger.error(f"{self.log_prefix} HeartFChatting: 脱离了聊天(异常): {exception}")
|
||||
logger.error(traceback.format_exc()) # Log full traceback for exceptions
|
||||
else:
|
||||
logger.info(f"{self.log_prefix} HeartFChatting: 脱离了聊天 (外部停止)")
|
||||
except asyncio.CancelledError:
|
||||
logger.info(f"{self.log_prefix} HeartFChatting: 脱离了聊天(任务取消)")
|
||||
finally:
|
||||
self._loop_active = False
|
||||
self._loop_task = None
|
||||
if self._processing_lock.locked():
|
||||
logger.warning(f"{self.log_prefix} HeartFChatting: 处理锁在循环结束时仍被锁定，强制释放。")
|
||||
self._processing_lock.release()
|
||||
|
||||
async def _run_focus_chat(self):
|
||||
"""主循环，持续进行计划并可能回复消息，直到被外部取消。"""
|
||||
try:
|
||||
while True: # 主循环
|
||||
logger.debug(f"{self.log_prefix} 开始第{self._cycle_counter}次循环")
|
||||
if self._shutting_down:
|
||||
logger.info(f"{self.log_prefix} 检测到关闭标志，退出 Focus Chat 循环。")
|
||||
break
|
||||
|
||||
# 创建新的循环信息
|
||||
self._cycle_counter += 1
|
||||
self._current_cycle_detail = CycleDetail(self._cycle_counter)
|
||||
self._current_cycle_detail.prefix = self.log_prefix
|
||||
|
||||
# 初始化周期状态
|
||||
cycle_timers = {}
|
||||
loop_cycle_start_time = time.monotonic()
|
||||
|
||||
# 执行规划和处理阶段
|
||||
async with self._get_cycle_context():
|
||||
thinking_id = "tid" + str(round(time.time(), 2))
|
||||
self._current_cycle_detail.set_thinking_id(thinking_id)
|
||||
# 主循环：思考->决策->执行
|
||||
async with global_prompt_manager.async_message_scope(self.chat_stream.context.get_template_name()):
|
||||
logger.debug(f"模板 {self.chat_stream.context.get_template_name()}")
|
||||
loop_info = await self._observe_process_plan_action_loop(cycle_timers, thinking_id)
|
||||
|
||||
if loop_info["loop_action_info"]["command"] == "stop_focus_chat":
|
||||
logger.info(f"{self.log_prefix} 麦麦决定停止专注聊天")
|
||||
# 如果设置了回调函数，则调用它
|
||||
if self.on_stop_focus_chat:
|
||||
try:
|
||||
await self.on_stop_focus_chat()
|
||||
logger.info(f"{self.log_prefix} 成功调用回调函数处理停止专注聊天")
|
||||
except Exception as e:
|
||||
logger.error(f"{self.log_prefix} 调用停止专注聊天回调函数时出错: {e}")
|
||||
logger.error(traceback.format_exc())
|
||||
break
|
||||
|
||||
self._current_cycle_detail.set_loop_info(loop_info)
|
||||
|
||||
# 从observations列表中获取HFCloopObservation
|
||||
hfcloop_observation = next((obs for obs in self.observations if isinstance(obs, HFCloopObservation)), None)
|
||||
if hfcloop_observation:
|
||||
hfcloop_observation.add_loop_info(self._current_cycle_detail)
|
||||
else:
|
||||
logger.warning(f"{self.log_prefix} 未找到HFCloopObservation实例")
|
||||
|
||||
self._current_cycle_detail.timers = cycle_timers
|
||||
|
||||
# 防止循环过快消耗资源
|
||||
await _handle_cycle_delay(
|
||||
loop_info["loop_action_info"]["action_taken"], loop_cycle_start_time, self.log_prefix
|
||||
)
|
||||
|
||||
# 完成当前循环并保存历史
|
||||
self._current_cycle_detail.complete_cycle()
|
||||
self._cycle_history.append(self._current_cycle_detail)
|
||||
|
||||
# 记录循环信息和计时器结果
|
||||
timer_strings = []
|
||||
for name, elapsed in cycle_timers.items():
|
||||
formatted_time = f"{elapsed * 1000:.2f}毫秒" if elapsed < 1 else f"{elapsed:.2f}秒"
|
||||
timer_strings.append(f"{name}: {formatted_time}")
|
||||
|
||||
# 新增：输出每个处理器的耗时
|
||||
processor_time_costs = self._current_cycle_detail.loop_processor_info.get("processor_time_costs", {})
|
||||
processor_time_strings = []
|
||||
for pname, ptime in processor_time_costs.items():
|
||||
formatted_ptime = f"{ptime * 1000:.2f}毫秒" if ptime < 1 else f"{ptime:.2f}秒"
|
||||
processor_time_strings.append(f"{pname}: {formatted_ptime}")
|
||||
processor_time_log = (
|
||||
("\n各处理器耗时: " + "; ".join(processor_time_strings)) if processor_time_strings else ""
|
||||
)
|
||||
|
||||
logger.info(
|
||||
f"{self.log_prefix} 第{self._current_cycle_detail.cycle_id}次思考,"
|
||||
f"耗时: {self._current_cycle_detail.end_time - self._current_cycle_detail.start_time:.1f}秒, "
|
||||
f"动作: {self._current_cycle_detail.loop_plan_info['action_result']['action_type']}"
|
||||
+ (f"\n详情: {'; '.join(timer_strings)}" if timer_strings else "")
|
||||
+ processor_time_log
|
||||
)
|
||||
|
||||
await asyncio.sleep(global_config.focus_chat.think_interval)
|
||||
|
||||
except asyncio.CancelledError:
|
||||
# 设置了关闭标志位后被取消是正常流程
|
||||
if not self._shutting_down:
|
||||
logger.warning(f"{self.log_prefix} 麦麦Focus聊天模式意外被取消")
|
||||
else:
|
||||
logger.info(f"{self.log_prefix} 麦麦已离开Focus聊天模式")
|
||||
except Exception as e:
|
||||
logger.error(f"{self.log_prefix} 麦麦Focus聊天模式意外错误: {e}")
|
||||
print(traceback.format_exc())
|
||||
|
||||
@contextlib.asynccontextmanager
|
||||
async def _get_cycle_context(self):
|
||||
"""
|
||||
循环周期的上下文管理器
|
||||
|
||||
用于确保资源的正确获取和释放：
|
||||
1. 获取处理锁
|
||||
2. 执行操作
|
||||
3. 释放锁
|
||||
"""
|
||||
acquired = False
|
||||
try:
|
||||
await self._processing_lock.acquire()
|
||||
acquired = True
|
||||
yield acquired
|
||||
finally:
|
||||
if acquired and self._processing_lock.locked():
|
||||
self._processing_lock.release()
|
||||
|
||||
async def _process_processors(
|
||||
self, observations: List[Observation], running_memorys: List[Dict[str, Any]]
|
||||
) -> tuple[List[InfoBase], Dict[str, float]]:
|
||||
# 记录并行任务开始时间
|
||||
parallel_start_time = time.time()
|
||||
logger.debug(f"{self.log_prefix} 开始信息处理器并行任务")
|
||||
|
||||
processor_tasks = []
|
||||
task_to_name_map = {}
|
||||
processor_time_costs = {} # 新增: 记录每个处理器耗时
|
||||
|
||||
for processor in self.processors:
|
||||
processor_name = processor.__class__.log_prefix
|
||||
|
||||
async def run_with_timeout(proc=processor):
|
||||
return await asyncio.wait_for(
|
||||
proc.process_info(observations=observations, running_memorys=running_memorys),
|
||||
timeout=global_config.focus_chat.processor_max_time,
|
||||
)
|
||||
|
||||
task = asyncio.create_task(run_with_timeout())
|
||||
processor_tasks.append(task)
|
||||
task_to_name_map[task] = processor_name
|
||||
logger.debug(f"{self.log_prefix} 启动处理器任务: {processor_name}")
|
||||
|
||||
pending_tasks = set(processor_tasks)
|
||||
all_plan_info: List[InfoBase] = []
|
||||
|
||||
while pending_tasks:
|
||||
done, pending_tasks = await asyncio.wait(pending_tasks, return_when=asyncio.FIRST_COMPLETED)
|
||||
|
||||
for task in done:
|
||||
processor_name = task_to_name_map[task]
|
||||
task_completed_time = time.time()
|
||||
duration_since_parallel_start = task_completed_time - parallel_start_time
|
||||
|
||||
try:
|
||||
result_list = await task
|
||||
logger.info(f"{self.log_prefix} 处理器 {processor_name} 已完成!")
|
||||
if result_list is not None:
|
||||
all_plan_info.extend(result_list)
|
||||
else:
|
||||
logger.warning(f"{self.log_prefix} 处理器 {processor_name} 返回了 None")
|
||||
# 记录耗时
|
||||
processor_time_costs[processor_name] = duration_since_parallel_start
|
||||
except asyncio.TimeoutError:
|
||||
logger.info(
|
||||
f"{self.log_prefix} 处理器 {processor_name} 超时（>{global_config.focus_chat.processor_max_time}s），已跳过"
|
||||
)
|
||||
processor_time_costs[processor_name] = global_config.focus_chat.processor_max_time
|
||||
except Exception as e:
|
||||
logger.error(
|
||||
f"{self.log_prefix} 处理器 {processor_name} 执行失败，耗时 (自并行开始): {duration_since_parallel_start:.2f}秒. 错误: {e}",
|
||||
exc_info=True,
|
||||
)
|
||||
traceback.print_exc()
|
||||
processor_time_costs[processor_name] = duration_since_parallel_start
|
||||
|
||||
if pending_tasks:
|
||||
current_progress_time = time.time()
|
||||
elapsed_for_log = current_progress_time - parallel_start_time
|
||||
pending_names_for_log = [task_to_name_map[t] for t in pending_tasks]
|
||||
logger.info(
|
||||
f"{self.log_prefix} 信息处理已进行 {elapsed_for_log:.2f}秒，待完成任务: {', '.join(pending_names_for_log)}"
|
||||
)
|
||||
|
||||
# 所有任务完成后的最终日志
|
||||
parallel_end_time = time.time()
|
||||
total_duration = parallel_end_time - parallel_start_time
|
||||
logger.info(f"{self.log_prefix} 所有处理器任务全部完成，总耗时: {total_duration:.2f}秒")
|
||||
# logger.debug(f"{self.log_prefix} 所有信息处理器处理后的信息: {all_plan_info}")
|
||||
|
||||
return all_plan_info, processor_time_costs
|
||||
|
||||
async def _observe_process_plan_action_loop(self, cycle_timers: dict, thinking_id: str) -> dict:
|
||||
try:
|
||||
with Timer("观察", cycle_timers):
|
||||
# 执行所有观察器的观察
|
||||
for observation in self.observations:
|
||||
await observation.observe()
|
||||
|
||||
loop_observation_info = {
|
||||
"observations": self.observations,
|
||||
}
|
||||
|
||||
with Timer("调整动作", cycle_timers):
|
||||
# 处理特殊的观察
|
||||
await self.action_modifier.modify_actions(observations=self.observations)
|
||||
await self.action_observation.observe()
|
||||
self.observations.append(self.action_observation)
|
||||
|
||||
# 根据配置决定是否并行执行回忆和处理器阶段
|
||||
# print(global_config.focus_chat.parallel_processing)
|
||||
if global_config.focus_chat.parallel_processing:
|
||||
# 并行执行回忆和处理器阶段
|
||||
with Timer("并行回忆和处理", cycle_timers):
|
||||
memory_task = asyncio.create_task(self.memory_activator.activate_memory(self.observations))
|
||||
processor_task = asyncio.create_task(self._process_processors(self.observations, []))
|
||||
|
||||
# 等待两个任务完成
|
||||
running_memorys, (all_plan_info, processor_time_costs) = await asyncio.gather(
|
||||
memory_task, processor_task
|
||||
)
|
||||
else:
|
||||
# 串行执行
|
||||
with Timer("回忆", cycle_timers):
|
||||
running_memorys = await self.memory_activator.activate_memory(self.observations)
|
||||
|
||||
with Timer("执行 信息处理器", cycle_timers):
|
||||
all_plan_info, processor_time_costs = await self._process_processors(self.observations, running_memorys)
|
||||
|
||||
loop_processor_info = {
|
||||
"all_plan_info": all_plan_info,
|
||||
"processor_time_costs": processor_time_costs,
|
||||
}
|
||||
|
||||
with Timer("规划器", cycle_timers):
|
||||
plan_result = await self.action_planner.plan(all_plan_info, running_memorys)
|
||||
|
||||
loop_plan_info = {
|
||||
"action_result": plan_result.get("action_result", {}),
|
||||
"current_mind": plan_result.get("current_mind", ""),
|
||||
"observed_messages": plan_result.get("observed_messages", ""),
|
||||
}
|
||||
|
||||
with Timer("执行动作", cycle_timers):
|
||||
action_type, action_data, reasoning = (
|
||||
plan_result.get("action_result", {}).get("action_type", "error"),
|
||||
plan_result.get("action_result", {}).get("action_data", {}),
|
||||
plan_result.get("action_result", {}).get("reasoning", "未提供理由"),
|
||||
)
|
||||
|
||||
if action_type == "reply":
|
||||
action_str = "回复"
|
||||
elif action_type == "no_reply":
|
||||
action_str = "不回复"
|
||||
else:
|
||||
action_str = action_type
|
||||
|
||||
logger.debug(f"{self.log_prefix} 麦麦想要：'{action_str}'")
|
||||
|
||||
success, reply_text, command = await self._handle_action(
|
||||
action_type, reasoning, action_data, cycle_timers, thinking_id, self.observations
|
||||
)
|
||||
|
||||
loop_action_info = {
|
||||
"action_taken": success,
|
||||
"reply_text": reply_text,
|
||||
"command": command,
|
||||
"taken_time": time.time(),
|
||||
}
|
||||
|
||||
loop_info = {
|
||||
"loop_observation_info": loop_observation_info,
|
||||
"loop_processor_info": loop_processor_info,
|
||||
"loop_plan_info": loop_plan_info,
|
||||
"loop_action_info": loop_action_info,
|
||||
}
|
||||
|
||||
return loop_info
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"{self.log_prefix} FOCUS聊天处理失败: {e}")
|
||||
logger.error(traceback.format_exc())
|
||||
return {
|
||||
"loop_observation_info": {},
|
||||
"loop_processor_info": {},
|
||||
"loop_plan_info": {},
|
||||
"loop_action_info": {"action_taken": False, "reply_text": "", "command": ""},
|
||||
}
|
||||
|
||||
async def _handle_action(
|
||||
self,
|
||||
action: str,
|
||||
reasoning: str,
|
||||
action_data: dict,
|
||||
cycle_timers: dict,
|
||||
thinking_id: str,
|
||||
observations: List[Observation],
|
||||
) -> tuple[bool, str, str]:
|
||||
"""
|
||||
处理规划动作，使用动作工厂创建相应的动作处理器
|
||||
|
||||
参数:
|
||||
action: 动作类型
|
||||
reasoning: 决策理由
|
||||
action_data: 动作数据，包含不同动作需要的参数
|
||||
cycle_timers: 计时器字典
|
||||
thinking_id: 思考ID
|
||||
|
||||
返回:
|
||||
tuple[bool, str, str]: (是否执行了动作, 思考消息ID, 命令)
|
||||
"""
|
||||
try:
|
||||
# 使用工厂创建动作处理器实例
|
||||
try:
|
||||
action_handler = self.action_manager.create_action(
|
||||
action_name=action,
|
||||
action_data=action_data,
|
||||
reasoning=reasoning,
|
||||
cycle_timers=cycle_timers,
|
||||
thinking_id=thinking_id,
|
||||
observations=observations,
|
||||
expressor=self.expressor,
|
||||
replyer=self.replyer,
|
||||
chat_stream=self.chat_stream,
|
||||
log_prefix=self.log_prefix,
|
||||
shutting_down=self._shutting_down,
|
||||
)
|
||||
except Exception as e:
|
||||
logger.error(f"{self.log_prefix} 创建动作处理器时出错: {e}")
|
||||
traceback.print_exc()
|
||||
return False, "", ""
|
||||
|
||||
if not action_handler:
|
||||
logger.warning(f"{self.log_prefix} 未能创建动作处理器: {action}, 原因: {reasoning}")
|
||||
return False, "", ""
|
||||
|
||||
# 处理动作并获取结果
|
||||
result = await action_handler.handle_action()
|
||||
if len(result) == 3:
|
||||
success, reply_text, command = result
|
||||
else:
|
||||
success, reply_text = result
|
||||
command = ""
|
||||
logger.debug(
|
||||
f"{self.log_prefix} 麦麦执行了'{action}', 返回结果'{success}', '{reply_text}', '{command}'"
|
||||
)
|
||||
return success, reply_text, command
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"{self.log_prefix} 处理{action}时出错: {e}")
|
||||
traceback.print_exc()
|
||||
return False, "", ""
|
||||
|
||||
async def shutdown(self):
|
||||
"""优雅关闭HeartFChatting实例，取消活动循环任务"""
|
||||
logger.info(f"{self.log_prefix} 正在关闭HeartFChatting...")
|
||||
self._shutting_down = True # <-- 在开始关闭时设置标志位
|
||||
|
||||
# 取消循环任务
|
||||
if self._loop_task and not self._loop_task.done():
|
||||
logger.info(f"{self.log_prefix} 正在取消HeartFChatting循环任务")
|
||||
self._loop_task.cancel()
|
||||
try:
|
||||
await asyncio.wait_for(self._loop_task, timeout=1.0)
|
||||
logger.info(f"{self.log_prefix} HeartFChatting循环任务已取消")
|
||||
except (asyncio.CancelledError, asyncio.TimeoutError):
|
||||
pass
|
||||
except Exception as e:
|
||||
logger.error(f"{self.log_prefix} 取消循环任务出错: {e}")
|
||||
else:
|
||||
logger.info(f"{self.log_prefix} 没有活动的HeartFChatting循环任务")
|
||||
|
||||
# 清理状态
|
||||
self._loop_active = False
|
||||
self._loop_task = None
|
||||
if self._processing_lock.locked():
|
||||
self._processing_lock.release()
|
||||
logger.warning(f"{self.log_prefix} 已释放处理锁")
|
||||
|
||||
logger.info(f"{self.log_prefix} HeartFChatting关闭完成")
|
||||
|
||||
def get_cycle_history(self, last_n: Optional[int] = None) -> List[Dict[str, Any]]:
|
||||
"""获取循环历史记录
|
||||
|
||||
参数:
|
||||
last_n: 获取最近n个循环的信息，如果为None则获取所有历史记录
|
||||
|
||||
返回:
|
||||
List[Dict[str, Any]]: 循环历史记录列表
|
||||
"""
|
||||
history = list(self._cycle_history)
|
||||
if last_n is not None:
|
||||
history = history[-last_n:]
|
||||
return [cycle.to_dict() for cycle in history]
|
||||
|
|
@ -1,290 +0,0 @@
|
|||
from datetime import datetime
|
||||
from src.config.config import global_config
|
||||
import traceback
|
||||
from src.chat.utils.chat_message_builder import (
|
||||
get_raw_msg_before_timestamp_with_chat,
|
||||
build_readable_messages,
|
||||
get_raw_msg_by_timestamp_with_chat,
|
||||
num_new_messages_since,
|
||||
get_person_id_list,
|
||||
)
|
||||
from src.chat.utils.prompt_builder import global_prompt_manager
|
||||
from typing import Optional
|
||||
import difflib
|
||||
from src.chat.message_receive.message import MessageRecv # 添加 MessageRecv 导入
|
||||
from src.chat.heart_flow.observation.observation import Observation
|
||||
|
||||
from src.common.logger_manager import get_logger
|
||||
from src.chat.heart_flow.utils_chat import get_chat_type_and_target_info
|
||||
from src.chat.utils.prompt_builder import Prompt
|
||||
|
||||
|
||||
logger = get_logger("observation")
|
||||
|
||||
|
||||
Prompt(
|
||||
"""这是qq群聊的聊天记录，请总结以下聊天记录的主题：
|
||||
{chat_logs}
|
||||
请用一句话概括，包括人物、事件和主要信息，不要分点。""",
|
||||
"chat_summary_group_prompt", # Template for group chat
|
||||
)
|
||||
|
||||
Prompt(
|
||||
"""这是你和{chat_target}的私聊记录，请总结以下聊天记录的主题：
|
||||
{chat_logs}
|
||||
请用一句话概括，包括事件，时间，和主要信息，不要分点。""",
|
||||
"chat_summary_private_prompt", # Template for private chat
|
||||
)
|
||||
# --- End Prompt Template Definition ---
|
||||
|
||||
|
||||
# 聊天观察
|
||||
class ChattingObservation(Observation):
|
||||
def __init__(self, chat_id):
|
||||
super().__init__(chat_id)
|
||||
self.chat_id = chat_id
|
||||
self.platform = "qq"
|
||||
|
||||
self.is_group_chat, self.chat_target_info = get_chat_type_and_target_info(self.chat_id)
|
||||
|
||||
# --- Other attributes initialized in __init__ ---
|
||||
self.talking_message = []
|
||||
self.talking_message_str = ""
|
||||
self.talking_message_str_truncate = ""
|
||||
self.name = global_config.bot.nickname
|
||||
self.nick_name = global_config.bot.alias_names
|
||||
self.max_now_obs_len = global_config.focus_chat.observation_context_size
|
||||
self.overlap_len = global_config.focus_chat.compressed_length
|
||||
self.mid_memories = []
|
||||
self.max_mid_memory_len = global_config.focus_chat.compress_length_limit
|
||||
self.mid_memory_info = ""
|
||||
self.person_list = []
|
||||
self.oldest_messages = []
|
||||
self.oldest_messages_str = ""
|
||||
self.compressor_prompt = ""
|
||||
|
||||
initial_messages = get_raw_msg_before_timestamp_with_chat(self.chat_id, self.last_observe_time, 10)
|
||||
self.last_observe_time = initial_messages[-1]["time"] if initial_messages else self.last_observe_time
|
||||
self.talking_message = initial_messages
|
||||
self.talking_message_str = build_readable_messages(self.talking_message)
|
||||
|
||||
|
||||
def to_dict(self) -> dict:
|
||||
"""将观察对象转换为可序列化的字典"""
|
||||
return {
|
||||
"chat_id": self.chat_id,
|
||||
"platform": self.platform,
|
||||
"is_group_chat": self.is_group_chat,
|
||||
"chat_target_info": self.chat_target_info,
|
||||
"talking_message_str": self.talking_message_str,
|
||||
"talking_message_str_truncate": self.talking_message_str_truncate,
|
||||
"name": self.name,
|
||||
"nick_name": self.nick_name,
|
||||
"mid_memory_info": self.mid_memory_info,
|
||||
"person_list": self.person_list,
|
||||
"oldest_messages_str": self.oldest_messages_str,
|
||||
"compressor_prompt": self.compressor_prompt,
|
||||
"last_observe_time": self.last_observe_time,
|
||||
}
|
||||
|
||||
# 进行一次观察 返回观察结果observe_info
|
||||
def get_observe_info(self, ids=None):
|
||||
mid_memory_str = ""
|
||||
if ids:
|
||||
for id in ids:
|
||||
print(f"id：{id}")
|
||||
try:
|
||||
for mid_memory in self.mid_memories:
|
||||
if mid_memory["id"] == id:
|
||||
mid_memory_by_id = mid_memory
|
||||
msg_str = ""
|
||||
for msg in mid_memory_by_id["messages"]:
|
||||
msg_str += f"{msg['detailed_plain_text']}"
|
||||
# time_diff = int((datetime.now().timestamp() - mid_memory_by_id["created_at"]) / 60)
|
||||
# mid_memory_str += f"距离现在{time_diff}分钟前：\n{msg_str}\n"
|
||||
mid_memory_str += f"{msg_str}\n"
|
||||
except Exception as e:
|
||||
logger.error(f"获取mid_memory_id失败: {e}")
|
||||
traceback.print_exc()
|
||||
return self.talking_message_str
|
||||
|
||||
return mid_memory_str + "现在群里正在聊：\n" + self.talking_message_str
|
||||
|
||||
else:
|
||||
mid_memory_str = "之前的聊天内容：\n"
|
||||
for mid_memory in self.mid_memories:
|
||||
mid_memory_str += f"{mid_memory['theme']}\n"
|
||||
return mid_memory_str + "现在群里正在聊：\n" + self.talking_message_str
|
||||
|
||||
def search_message_by_text(self, text: str) -> Optional[MessageRecv]:
|
||||
"""
|
||||
根据回复的纯文本
|
||||
1. 在talking_message中查找最新的，最匹配的消息
|
||||
2. 如果找到，则返回消息
|
||||
"""
|
||||
msg_list = []
|
||||
find_msg = None
|
||||
reverse_talking_message = list(reversed(self.talking_message))
|
||||
|
||||
for message in reverse_talking_message:
|
||||
if message["processed_plain_text"] == text:
|
||||
find_msg = message
|
||||
# logger.debug(f"找到的锚定消息：find_msg: {find_msg}")
|
||||
break
|
||||
else:
|
||||
similarity = difflib.SequenceMatcher(None, text, message["processed_plain_text"]).ratio()
|
||||
msg_list.append({"message": message, "similarity": similarity})
|
||||
# logger.debug(f"对锚定消息检查：message: {message['processed_plain_text']},similarity: {similarity}")
|
||||
if not find_msg:
|
||||
if msg_list:
|
||||
msg_list.sort(key=lambda x: x["similarity"], reverse=True)
|
||||
if msg_list[0]["similarity"] >= 0.5: # 只返回相似度大于等于0.5的消息
|
||||
find_msg = msg_list[0]["message"]
|
||||
else:
|
||||
logger.debug("没有找到锚定消息,相似度低")
|
||||
return None
|
||||
else:
|
||||
logger.debug("没有找到锚定消息，没有消息捕获")
|
||||
return None
|
||||
|
||||
# logger.debug(f"找到的锚定消息：find_msg: {find_msg}")
|
||||
|
||||
# 创建所需的user_info字段
|
||||
user_info = {
|
||||
"platform": find_msg.get("user_platform", ""),
|
||||
"user_id": find_msg.get("user_id", ""),
|
||||
"user_nickname": find_msg.get("user_nickname", ""),
|
||||
"user_cardname": find_msg.get("user_cardname", ""),
|
||||
}
|
||||
|
||||
# 创建所需的group_info字段，如果是群聊的话
|
||||
group_info = {}
|
||||
if find_msg.get("chat_info_group_id"):
|
||||
group_info = {
|
||||
"platform": find_msg.get("chat_info_group_platform", ""),
|
||||
"group_id": find_msg.get("chat_info_group_id", ""),
|
||||
"group_name": find_msg.get("chat_info_group_name", ""),
|
||||
}
|
||||
|
||||
content_format = ""
|
||||
accept_format = ""
|
||||
template_items = {}
|
||||
|
||||
format_info = {"content_format": content_format, "accept_format": accept_format}
|
||||
template_info = {
|
||||
"template_items": template_items,
|
||||
}
|
||||
|
||||
message_info = {
|
||||
"platform": self.platform,
|
||||
"message_id": find_msg.get("message_id"),
|
||||
"time": find_msg.get("time"),
|
||||
"group_info": group_info,
|
||||
"user_info": user_info,
|
||||
"additional_config": find_msg.get("additional_config"),
|
||||
"format_info": format_info,
|
||||
"template_info": template_info,
|
||||
}
|
||||
message_dict = {
|
||||
"message_info": message_info,
|
||||
"raw_message": find_msg.get("processed_plain_text"),
|
||||
"detailed_plain_text": find_msg.get("processed_plain_text"),
|
||||
"processed_plain_text": find_msg.get("processed_plain_text"),
|
||||
}
|
||||
find_rec_msg = MessageRecv(message_dict)
|
||||
# logger.debug(f"锚定消息处理后：find_rec_msg: {find_rec_msg}")
|
||||
return find_rec_msg
|
||||
|
||||
async def observe(self):
|
||||
# 自上一次观察的新消息
|
||||
new_messages_list = get_raw_msg_by_timestamp_with_chat(
|
||||
chat_id=self.chat_id,
|
||||
timestamp_start=self.last_observe_time,
|
||||
timestamp_end=datetime.now().timestamp(),
|
||||
limit=self.max_now_obs_len,
|
||||
limit_mode="latest",
|
||||
)
|
||||
|
||||
# print(f"new_messages_list: {new_messages_list}")
|
||||
|
||||
last_obs_time_mark = self.last_observe_time
|
||||
if new_messages_list:
|
||||
self.last_observe_time = new_messages_list[-1]["time"]
|
||||
self.talking_message.extend(new_messages_list)
|
||||
|
||||
if len(self.talking_message) > self.max_now_obs_len:
|
||||
# 计算需要移除的消息数量，保留最新的 max_now_obs_len 条
|
||||
messages_to_remove_count = len(self.talking_message) - self.max_now_obs_len
|
||||
oldest_messages = self.talking_message[:messages_to_remove_count]
|
||||
self.talking_message = self.talking_message[messages_to_remove_count:] # 保留后半部分，即最新的
|
||||
|
||||
# print(f"压缩中：oldest_messages: {oldest_messages}")
|
||||
oldest_messages_str = build_readable_messages(
|
||||
messages=oldest_messages, timestamp_mode="normal_no_YMD", read_mark=0
|
||||
)
|
||||
|
||||
# --- Build prompt using template ---
|
||||
prompt = None # Initialize prompt as None
|
||||
try:
|
||||
# 构建 Prompt - 根据 is_group_chat 选择模板
|
||||
if self.is_group_chat:
|
||||
prompt_template_name = "chat_summary_group_prompt"
|
||||
prompt = await global_prompt_manager.format_prompt(
|
||||
prompt_template_name, chat_logs=oldest_messages_str
|
||||
)
|
||||
else:
|
||||
# For private chat, add chat_target to the prompt variables
|
||||
prompt_template_name = "chat_summary_private_prompt"
|
||||
# Determine the target name for the prompt
|
||||
chat_target_name = "对方" # Default fallback
|
||||
if self.chat_target_info:
|
||||
# Prioritize person_name, then nickname
|
||||
chat_target_name = (
|
||||
self.chat_target_info.get("person_name")
|
||||
or self.chat_target_info.get("user_nickname")
|
||||
or chat_target_name
|
||||
)
|
||||
|
||||
# Format the private chat prompt
|
||||
prompt = await global_prompt_manager.format_prompt(
|
||||
prompt_template_name,
|
||||
# Assuming the private prompt template uses {chat_target}
|
||||
chat_target=chat_target_name,
|
||||
chat_logs=oldest_messages_str,
|
||||
)
|
||||
except Exception as e:
|
||||
logger.error(f"构建总结 Prompt 失败 for chat {self.chat_id}: {e}")
|
||||
# prompt remains None
|
||||
|
||||
if prompt: # Check if prompt was built successfully
|
||||
self.compressor_prompt = prompt
|
||||
self.oldest_messages = oldest_messages
|
||||
self.oldest_messages_str = oldest_messages_str
|
||||
|
||||
# 构建中
|
||||
# print(f"构建中：self.talking_message: {self.talking_message}")
|
||||
self.talking_message_str = build_readable_messages(
|
||||
messages=self.talking_message,
|
||||
timestamp_mode="lite",
|
||||
read_mark=last_obs_time_mark,
|
||||
)
|
||||
# print(f"构建中：self.talking_message_str: {self.talking_message_str}")
|
||||
self.talking_message_str_truncate = build_readable_messages(
|
||||
messages=self.talking_message,
|
||||
timestamp_mode="normal_no_YMD",
|
||||
read_mark=last_obs_time_mark,
|
||||
truncate=True,
|
||||
)
|
||||
# print(f"构建中：self.talking_message_str_truncate: {self.talking_message_str_truncate}")
|
||||
|
||||
self.person_list = await get_person_id_list(self.talking_message)
|
||||
# print(f"构建中：self.person_list: {self.person_list}")
|
||||
|
||||
logger.trace(
|
||||
f"Chat {self.chat_id} - 压缩早期记忆：{self.mid_memory_info}\n现在聊天内容：{self.talking_message_str}"
|
||||
)
|
||||
|
||||
async def has_new_messages_since(self, timestamp: float) -> bool:
|
||||
"""检查指定时间戳之后是否有新消息"""
|
||||
count = num_new_messages_since(chat_id=self.chat_id, timestamp_start=timestamp)
|
||||
return count > 0
|
||||
|
|
@ -1,125 +0,0 @@
|
|||
# 定义了来自外部世界的信息
|
||||
# 外部世界可以是某个聊天 不同平台的聊天 也可以是任意媒体
|
||||
from datetime import datetime
|
||||
from src.common.logger_manager import get_logger
|
||||
from src.chat.focus_chat.heartFC_Cycleinfo import CycleDetail
|
||||
from typing import List
|
||||
# Import the new utility function
|
||||
|
||||
logger = get_logger("observation")
|
||||
|
||||
|
||||
# 所有观察的基类
|
||||
class HFCloopObservation:
|
||||
def __init__(self, observe_id):
|
||||
self.observe_info = ""
|
||||
self.observe_id = observe_id
|
||||
self.last_observe_time = datetime.now().timestamp() # 初始化为当前时间
|
||||
self.history_loop: List[CycleDetail] = []
|
||||
|
||||
def get_observe_info(self):
|
||||
return self.observe_info
|
||||
|
||||
def add_loop_info(self, loop_info: CycleDetail):
|
||||
self.history_loop.append(loop_info)
|
||||
|
||||
async def observe(self):
|
||||
recent_active_cycles: List[CycleDetail] = []
|
||||
for cycle in reversed(self.history_loop):
|
||||
# 只关心实际执行了动作的循环
|
||||
# action_taken = cycle.loop_action_info["action_taken"]
|
||||
# if action_taken:
|
||||
recent_active_cycles.append(cycle)
|
||||
if len(recent_active_cycles) == 5:
|
||||
break
|
||||
|
||||
cycle_info_block = ""
|
||||
action_detailed_str = ""
|
||||
consecutive_text_replies = 0
|
||||
responses_for_prompt = []
|
||||
|
||||
cycle_last_reason = ""
|
||||
|
||||
# 检查这最近的活动循环中有多少是连续的文本回复 (从最近的开始看)
|
||||
for cycle in recent_active_cycles:
|
||||
action_type = cycle.loop_plan_info["action_result"]["action_type"]
|
||||
action_reasoning = cycle.loop_plan_info["action_result"]["reasoning"]
|
||||
is_taken = cycle.loop_action_info["action_taken"]
|
||||
action_taken_time = cycle.loop_action_info["taken_time"]
|
||||
action_taken_time_str = datetime.fromtimestamp(action_taken_time).strftime("%H:%M:%S")
|
||||
# print(action_type)
|
||||
# print(action_reasoning)
|
||||
# print(is_taken)
|
||||
# print(action_taken_time_str)
|
||||
# print("--------------------------------")
|
||||
if action_reasoning != cycle_last_reason:
|
||||
cycle_last_reason = action_reasoning
|
||||
action_reasoning_str = f"你选择这个action的原因是:{action_reasoning}"
|
||||
else:
|
||||
action_reasoning_str = ""
|
||||
|
||||
if action_type == "reply":
|
||||
consecutive_text_replies += 1
|
||||
response_text = cycle.loop_action_info["reply_text"]
|
||||
responses_for_prompt.append(response_text)
|
||||
|
||||
if is_taken:
|
||||
action_detailed_str += f"{action_taken_time_str}时，你选择回复(action:{action_type},内容是:'{response_text}')。{action_reasoning_str}\n"
|
||||
else:
|
||||
action_detailed_str += f"{action_taken_time_str}时，你选择回复(action:{action_type},内容是:'{response_text}')，但是动作失败了。{action_reasoning_str}\n"
|
||||
elif action_type == "no_reply":
|
||||
# action_detailed_str += (
|
||||
# f"{action_taken_time_str}时，你选择不回复(action:{action_type})，{action_reasoning_str}\n"
|
||||
# )
|
||||
pass
|
||||
else:
|
||||
if is_taken:
|
||||
action_detailed_str += (
|
||||
f"{action_taken_time_str}时，你选择执行了(action:{action_type})，{action_reasoning_str}\n"
|
||||
)
|
||||
else:
|
||||
action_detailed_str += f"{action_taken_time_str}时，你选择执行了(action:{action_type})，但是动作失败了。{action_reasoning_str}\n"
|
||||
|
||||
if action_detailed_str:
|
||||
cycle_info_block = f"\n你最近做的事：\n{action_detailed_str}\n"
|
||||
else:
|
||||
cycle_info_block = "\n"
|
||||
|
||||
# 根据连续文本回复的数量构建提示信息
|
||||
if consecutive_text_replies >= 3: # 如果最近的三个活动都是文本回复
|
||||
cycle_info_block = f'你已经连续回复了三条消息（最近: "{responses_for_prompt[0]}"，第二近: "{responses_for_prompt[1]}"，第三近: "{responses_for_prompt[2]}"）。你回复的有点多了，请注意'
|
||||
elif consecutive_text_replies == 2: # 如果最近的两个活动是文本回复
|
||||
cycle_info_block = f'你已经连续回复了两条消息（最近: "{responses_for_prompt[0]}"，第二近: "{responses_for_prompt[1]}"），请注意'
|
||||
|
||||
# 包装提示块，增加可读性，即使没有连续回复也给个标记
|
||||
# if cycle_info_block:
|
||||
# cycle_info_block = f"\n你最近的回复\n{cycle_info_block}\n"
|
||||
# else:
|
||||
# cycle_info_block = "\n"
|
||||
|
||||
# 获取history_loop中最新添加的
|
||||
if self.history_loop:
|
||||
last_loop = self.history_loop[0]
|
||||
start_time = last_loop.start_time
|
||||
end_time = last_loop.end_time
|
||||
if start_time is not None and end_time is not None:
|
||||
time_diff = int(end_time - start_time)
|
||||
if time_diff > 60:
|
||||
cycle_info_block += f"距离你上一次阅读消息并思考和规划，已经过去了{int(time_diff / 60)}分钟\n"
|
||||
else:
|
||||
cycle_info_block += f"距离你上一次阅读消息并思考和规划，已经过去了{time_diff}秒\n"
|
||||
else:
|
||||
cycle_info_block += "你还没看过消息\n"
|
||||
|
||||
self.observe_info = cycle_info_block
|
||||
|
||||
def to_dict(self) -> dict:
|
||||
"""将观察对象转换为可序列化的字典"""
|
||||
# 只序列化基本信息，避免循环引用
|
||||
return {
|
||||
"observe_info": self.observe_info,
|
||||
"observe_id": self.observe_id,
|
||||
"last_observe_time": self.last_observe_time,
|
||||
# 不序列化history_loop，避免循环引用
|
||||
"history_loop_count": len(self.history_loop),
|
||||
}
|
||||
|
|
@ -1,190 +0,0 @@
|
|||
import os
|
||||
from dataclasses import field, dataclass
|
||||
|
||||
import tomlkit
|
||||
import shutil
|
||||
from datetime import datetime
|
||||
|
||||
from tomlkit import TOMLDocument
|
||||
from tomlkit.items import Table
|
||||
|
||||
from src.common.logger_manager import get_logger
|
||||
from rich.traceback import install
|
||||
|
||||
from src.config.config_base import ConfigBase
|
||||
from src.config.official_configs import (
|
||||
BotConfig,
|
||||
PersonalityConfig,
|
||||
IdentityConfig,
|
||||
ExpressionConfig,
|
||||
ChatConfig,
|
||||
NormalChatConfig,
|
||||
FocusChatConfig,
|
||||
EmojiConfig,
|
||||
MemoryConfig,
|
||||
MoodConfig,
|
||||
KeywordReactionConfig,
|
||||
ChineseTypoConfig,
|
||||
ResponseSplitterConfig,
|
||||
TelemetryConfig,
|
||||
ExperimentalConfig,
|
||||
ModelConfig,
|
||||
FocusChatProcessorConfig,
|
||||
MessageReceiveConfig,
|
||||
MaimMessageConfig,
|
||||
RelationshipConfig,
|
||||
)
|
||||
|
||||
install(extra_lines=3)
|
||||
|
||||
|
||||
# 配置主程序日志格式
|
||||
logger = get_logger("config")
|
||||
|
||||
CONFIG_DIR = "config"
|
||||
TEMPLATE_DIR = "template"
|
||||
|
||||
# 考虑到，实际上配置文件中的mai_version是不会自动更新的,所以采用硬编码
|
||||
# 对该字段的更新，请严格参照语义化版本规范：https://semver.org/lang/zh-CN/
|
||||
MMC_VERSION = "0.7.1-snapshot.1"
|
||||
|
||||
|
||||
def update_config():
|
||||
# 获取根目录路径
|
||||
old_config_dir = f"{CONFIG_DIR}/old"
|
||||
|
||||
# 定义文件路径
|
||||
template_path = f"{TEMPLATE_DIR}/bot_config_template.toml"
|
||||
old_config_path = f"{CONFIG_DIR}/bot_config.toml"
|
||||
new_config_path = f"{CONFIG_DIR}/bot_config.toml"
|
||||
|
||||
# 检查配置文件是否存在
|
||||
if not os.path.exists(old_config_path):
|
||||
logger.info("配置文件不存在，从模板创建新配置")
|
||||
os.makedirs(CONFIG_DIR, exist_ok=True) # 创建文件夹
|
||||
shutil.copy2(template_path, old_config_path) # 复制模板文件
|
||||
logger.info(f"已创建新配置文件，请填写后重新运行: {old_config_path}")
|
||||
# 如果是新创建的配置文件,直接返回
|
||||
quit()
|
||||
|
||||
# 读取旧配置文件和模板文件
|
||||
with open(old_config_path, "r", encoding="utf-8") as f:
|
||||
old_config = tomlkit.load(f)
|
||||
with open(template_path, "r", encoding="utf-8") as f:
|
||||
new_config = tomlkit.load(f)
|
||||
|
||||
# 检查version是否相同
|
||||
if old_config and "inner" in old_config and "inner" in new_config:
|
||||
old_version = old_config["inner"].get("version")
|
||||
new_version = new_config["inner"].get("version")
|
||||
if old_version and new_version and old_version == new_version:
|
||||
logger.info(f"检测到配置文件版本号相同 (v{old_version})，跳过更新")
|
||||
return
|
||||
else:
|
||||
logger.info(f"检测到版本号不同: 旧版本 v{old_version} -> 新版本 v{new_version}")
|
||||
else:
|
||||
logger.info("已有配置文件未检测到版本号，可能是旧版本。将进行更新")
|
||||
|
||||
# 创建old目录（如果不存在）
|
||||
os.makedirs(old_config_dir, exist_ok=True)
|
||||
|
||||
# 生成带时间戳的新文件名
|
||||
timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
|
||||
old_backup_path = f"{old_config_dir}/bot_config_{timestamp}.toml"
|
||||
|
||||
# 移动旧配置文件到old目录
|
||||
shutil.move(old_config_path, old_backup_path)
|
||||
logger.info(f"已备份旧配置文件到: {old_backup_path}")
|
||||
|
||||
# 复制模板文件到配置目录
|
||||
shutil.copy2(template_path, new_config_path)
|
||||
logger.info(f"已创建新配置文件: {new_config_path}")
|
||||
|
||||
def update_dict(target: TOMLDocument | dict, source: TOMLDocument | dict):
|
||||
"""
|
||||
将source字典的值更新到target字典中（如果target中存在相同的键）
|
||||
"""
|
||||
for key, value in source.items():
|
||||
# 跳过version字段的更新
|
||||
if key == "version":
|
||||
continue
|
||||
if key in target:
|
||||
if isinstance(value, dict) and isinstance(target[key], (dict, Table)):
|
||||
update_dict(target[key], value)
|
||||
else:
|
||||
try:
|
||||
# 对数组类型进行特殊处理
|
||||
if isinstance(value, list):
|
||||
# 如果是空数组，确保它保持为空数组
|
||||
target[key] = tomlkit.array(str(value)) if value else tomlkit.array()
|
||||
else:
|
||||
# 其他类型使用item方法创建新值
|
||||
target[key] = tomlkit.item(value)
|
||||
except (TypeError, ValueError):
|
||||
# 如果转换失败，直接赋值
|
||||
target[key] = value
|
||||
|
||||
# 将旧配置的值更新到新配置中
|
||||
logger.info("开始合并新旧配置...")
|
||||
update_dict(new_config, old_config)
|
||||
|
||||
# 保存更新后的配置（保留注释和格式）
|
||||
with open(new_config_path, "w", encoding="utf-8") as f:
|
||||
f.write(tomlkit.dumps(new_config))
|
||||
logger.info("配置文件更新完成，建议检查新配置文件中的内容，以免丢失重要信息")
|
||||
quit()
|
||||
|
||||
|
||||
@dataclass
|
||||
class Config(ConfigBase):
|
||||
"""总配置类"""
|
||||
|
||||
MMC_VERSION: str = field(default=MMC_VERSION, repr=False, init=False) # 硬编码的版本信息
|
||||
|
||||
bot: BotConfig
|
||||
personality: PersonalityConfig
|
||||
identity: IdentityConfig
|
||||
relationship: RelationshipConfig
|
||||
chat: ChatConfig
|
||||
message_receive: MessageReceiveConfig
|
||||
normal_chat: NormalChatConfig
|
||||
focus_chat: FocusChatConfig
|
||||
focus_chat_processor: FocusChatProcessorConfig
|
||||
emoji: EmojiConfig
|
||||
expression: ExpressionConfig
|
||||
memory: MemoryConfig
|
||||
mood: MoodConfig
|
||||
keyword_reaction: KeywordReactionConfig
|
||||
chinese_typo: ChineseTypoConfig
|
||||
response_splitter: ResponseSplitterConfig
|
||||
telemetry: TelemetryConfig
|
||||
experimental: ExperimentalConfig
|
||||
model: ModelConfig
|
||||
maim_message: MaimMessageConfig
|
||||
|
||||
|
||||
def load_config(config_path: str) -> Config:
|
||||
"""
|
||||
加载配置文件
|
||||
:param config_path: 配置文件路径
|
||||
:return: Config对象
|
||||
"""
|
||||
# 读取配置文件
|
||||
with open(config_path, "r", encoding="utf-8") as f:
|
||||
config_data = tomlkit.load(f)
|
||||
|
||||
# 创建Config对象
|
||||
try:
|
||||
return Config.from_dict(config_data)
|
||||
except Exception as e:
|
||||
logger.critical("配置文件解析失败")
|
||||
raise e
|
||||
|
||||
|
||||
# 获取配置文件路径
|
||||
logger.info(f"MaiCore当前版本: {MMC_VERSION}")
|
||||
update_config()
|
||||
|
||||
logger.info("正在品鉴配置文件...")
|
||||
global_config = load_config(config_path=f"{CONFIG_DIR}/bot_config.toml")
|
||||
logger.info("非常的新鲜，非常的美味！")
|
||||
|
|
@ -1,468 +0,0 @@
|
|||
from dataclasses import dataclass, field
|
||||
from typing import Any, Literal
|
||||
import re
|
||||
|
||||
from src.config.config_base import ConfigBase
|
||||
|
||||
"""
|
||||
须知：
|
||||
1. 本文件中记录了所有的配置项
|
||||
2. 所有新增的class都需要继承自ConfigBase
|
||||
3. 所有新增的class都应在config.py中的Config类中添加字段
|
||||
4. 对于新增的字段，若为可选项，则应在其后添加field()并设置default_factory或default
|
||||
"""
|
||||
|
||||
|
||||
@dataclass
|
||||
class BotConfig(ConfigBase):
|
||||
"""QQ机器人配置类"""
|
||||
|
||||
qq_account: str
|
||||
"""QQ账号"""
|
||||
|
||||
nickname: str
|
||||
"""昵称"""
|
||||
|
||||
alias_names: list[str] = field(default_factory=lambda: [])
|
||||
"""别名列表"""
|
||||
|
||||
|
||||
@dataclass
|
||||
class PersonalityConfig(ConfigBase):
|
||||
"""人格配置类"""
|
||||
|
||||
personality_core: str
|
||||
"""核心人格"""
|
||||
|
||||
personality_sides: list[str] = field(default_factory=lambda: [])
|
||||
"""人格侧写"""
|
||||
|
||||
|
||||
@dataclass
|
||||
class IdentityConfig(ConfigBase):
|
||||
"""个体特征配置类"""
|
||||
|
||||
identity_detail: list[str] = field(default_factory=lambda: [])
|
||||
"""身份特征"""
|
||||
|
||||
|
||||
@dataclass
|
||||
class RelationshipConfig(ConfigBase):
|
||||
"""关系配置类"""
|
||||
|
||||
give_name: bool = False
|
||||
"""是否给其他人取名"""
|
||||
|
||||
|
||||
@dataclass
|
||||
class ChatConfig(ConfigBase):
|
||||
"""聊天配置类"""
|
||||
|
||||
chat_mode: str = "normal"
|
||||
"""聊天模式"""
|
||||
|
||||
auto_focus_threshold: float = 1.0
|
||||
"""自动切换到专注聊天的阈值，越低越容易进入专注聊天"""
|
||||
|
||||
exit_focus_threshold: float = 1.0
|
||||
"""自动退出专注聊天的阈值，越低越容易退出专注聊天"""
|
||||
|
||||
|
||||
@dataclass
|
||||
class MessageReceiveConfig(ConfigBase):
|
||||
"""消息接收配置类"""
|
||||
|
||||
ban_words: set[str] = field(default_factory=lambda: set())
|
||||
"""过滤词列表"""
|
||||
|
||||
ban_msgs_regex: set[str] = field(default_factory=lambda: set())
|
||||
"""过滤正则表达式列表"""
|
||||
|
||||
|
||||
@dataclass
|
||||
class NormalChatConfig(ConfigBase):
|
||||
"""普通聊天配置类"""
|
||||
|
||||
normal_chat_first_probability: float = 0.3
|
||||
"""
|
||||
发言时选择推理模型的概率（0-1之间）
|
||||
选择普通模型的概率为 1 - reasoning_normal_model_probability
|
||||
"""
|
||||
|
||||
max_context_size: int = 15
|
||||
"""上下文长度"""
|
||||
|
||||
message_buffer: bool = False
|
||||
"""消息缓冲器"""
|
||||
|
||||
emoji_chance: float = 0.2
|
||||
"""发送表情包的基础概率"""
|
||||
|
||||
thinking_timeout: int = 120
|
||||
"""最长思考时间"""
|
||||
|
||||
willing_mode: str = "classical"
|
||||
"""意愿模式"""
|
||||
|
||||
talk_frequency: float = 1
|
||||
"""回复频率阈值"""
|
||||
|
||||
response_willing_amplifier: float = 1.0
|
||||
"""回复意愿放大系数"""
|
||||
|
||||
response_interested_rate_amplifier: float = 1.0
|
||||
"""回复兴趣度放大系数"""
|
||||
|
||||
talk_frequency_down_groups: list[str] = field(default_factory=lambda: [])
|
||||
"""降低回复频率的群组"""
|
||||
|
||||
down_frequency_rate: float = 3.0
|
||||
"""降低回复频率的群组回复意愿降低系数"""
|
||||
|
||||
emoji_response_penalty: float = 0.0
|
||||
"""表情包回复惩罚系数"""
|
||||
|
||||
mentioned_bot_inevitable_reply: bool = False
|
||||
"""提及 bot 必然回复"""
|
||||
|
||||
at_bot_inevitable_reply: bool = False
|
||||
"""@bot 必然回复"""
|
||||
|
||||
enable_planner: bool = False
|
||||
"""是否启用动作规划器"""
|
||||
|
||||
|
||||
@dataclass
|
||||
class FocusChatConfig(ConfigBase):
|
||||
"""专注聊天配置类"""
|
||||
|
||||
observation_context_size: int = 12
|
||||
"""可观察到的最长上下文大小，超过这个值的上下文会被压缩"""
|
||||
|
||||
compressed_length: int = 5
|
||||
"""心流上下文压缩的最短压缩长度，超过心流观察到的上下文长度，会压缩，最短压缩长度为5"""
|
||||
|
||||
compress_length_limit: int = 5
|
||||
"""最多压缩份数，超过该数值的压缩上下文会被删除"""
|
||||
|
||||
think_interval: float = 1
|
||||
"""思考间隔（秒）"""
|
||||
|
||||
consecutive_replies: float = 1
|
||||
"""连续回复能力，值越高，麦麦连续回复的概率越高"""
|
||||
|
||||
parallel_processing: bool = False
|
||||
"""是否允许处理器阶段和回忆阶段并行执行"""
|
||||
|
||||
processor_max_time: int = 25
|
||||
"""处理器最大时间，单位秒，如果超过这个时间，处理器会自动停止"""
|
||||
|
||||
planner_type: str = "simple"
|
||||
"""规划器类型，可选值：default（默认规划器）, simple（简单规划器）"""
|
||||
|
||||
|
||||
@dataclass
|
||||
class FocusChatProcessorConfig(ConfigBase):
|
||||
"""专注聊天处理器配置类"""
|
||||
|
||||
mind_processor: bool = False
|
||||
"""是否启用思维处理器"""
|
||||
|
||||
self_identify_processor: bool = True
|
||||
"""是否启用自我识别处理器"""
|
||||
|
||||
relation_processor: bool = True
|
||||
"""是否启用关系识别处理器"""
|
||||
|
||||
tool_use_processor: bool = True
|
||||
"""是否启用工具使用处理器"""
|
||||
|
||||
working_memory_processor: bool = True
|
||||
"""是否启用工作记忆处理器"""
|
||||
|
||||
|
||||
@dataclass
|
||||
class ExpressionConfig(ConfigBase):
|
||||
"""表达配置类"""
|
||||
|
||||
expression_style: str = ""
|
||||
"""表达风格"""
|
||||
|
||||
learning_interval: int = 300
|
||||
"""学习间隔（秒）"""
|
||||
|
||||
enable_expression_learning: bool = True
|
||||
"""是否启用表达学习"""
|
||||
|
||||
|
||||
@dataclass
|
||||
class EmojiConfig(ConfigBase):
|
||||
"""表情包配置类"""
|
||||
|
||||
max_reg_num: int = 200
|
||||
"""表情包最大注册数量"""
|
||||
|
||||
do_replace: bool = True
|
||||
"""达到最大注册数量时替换旧表情包"""
|
||||
|
||||
check_interval: int = 120
|
||||
"""表情包检查间隔（分钟）"""
|
||||
|
||||
steal_emoji: bool = True
|
||||
"""是否偷取表情包，让麦麦可以发送她保存的这些表情包"""
|
||||
|
||||
content_filtration: bool = False
|
||||
"""是否开启表情包过滤"""
|
||||
|
||||
filtration_prompt: str = "符合公序良俗"
|
||||
"""表情包过滤要求"""
|
||||
|
||||
|
||||
@dataclass
|
||||
class MemoryConfig(ConfigBase):
|
||||
"""记忆配置类"""
|
||||
|
||||
memory_build_interval: int = 600
|
||||
"""记忆构建间隔（秒）"""
|
||||
|
||||
memory_build_distribution: tuple[
|
||||
float,
|
||||
float,
|
||||
float,
|
||||
float,
|
||||
float,
|
||||
float,
|
||||
] = field(default_factory=lambda: (6.0, 3.0, 0.6, 32.0, 12.0, 0.4))
|
||||
"""记忆构建分布，参数：分布1均值，标准差，权重，分布2均值，标准差，权重"""
|
||||
|
||||
memory_build_sample_num: int = 8
|
||||
"""记忆构建采样数量"""
|
||||
|
||||
memory_build_sample_length: int = 40
|
||||
"""记忆构建采样长度"""
|
||||
|
||||
memory_compress_rate: float = 0.1
|
||||
"""记忆压缩率"""
|
||||
|
||||
forget_memory_interval: int = 1000
|
||||
"""记忆遗忘间隔（秒）"""
|
||||
|
||||
memory_forget_time: int = 24
|
||||
"""记忆遗忘时间（小时）"""
|
||||
|
||||
memory_forget_percentage: float = 0.01
|
||||
"""记忆遗忘比例"""
|
||||
|
||||
consolidate_memory_interval: int = 1000
|
||||
"""记忆整合间隔（秒）"""
|
||||
|
||||
consolidation_similarity_threshold: float = 0.7
|
||||
"""整合相似度阈值"""
|
||||
|
||||
consolidate_memory_percentage: float = 0.01
|
||||
"""整合检查节点比例"""
|
||||
|
||||
memory_ban_words: list[str] = field(default_factory=lambda: ["表情包", "图片", "回复", "聊天记录"])
|
||||
"""不允许记忆的词列表"""
|
||||
|
||||
|
||||
@dataclass
|
||||
class MoodConfig(ConfigBase):
|
||||
"""情绪配置类"""
|
||||
|
||||
mood_update_interval: int = 1
|
||||
"""情绪更新间隔（秒）"""
|
||||
|
||||
mood_decay_rate: float = 0.95
|
||||
"""情绪衰减率"""
|
||||
|
||||
mood_intensity_factor: float = 0.7
|
||||
"""情绪强度因子"""
|
||||
|
||||
|
||||
@dataclass
|
||||
class KeywordRuleConfig(ConfigBase):
|
||||
"""关键词规则配置类"""
|
||||
|
||||
keywords: list[str] = field(default_factory=lambda: [])
|
||||
"""关键词列表"""
|
||||
|
||||
regex: list[str] = field(default_factory=lambda: [])
|
||||
"""正则表达式列表"""
|
||||
|
||||
reaction: str = ""
|
||||
"""关键词触发的反应"""
|
||||
|
||||
def __post_init__(self):
|
||||
"""验证配置"""
|
||||
if not self.keywords and not self.regex:
|
||||
raise ValueError("关键词规则必须至少包含keywords或regex中的一个")
|
||||
|
||||
if not self.reaction:
|
||||
raise ValueError("关键词规则必须包含reaction")
|
||||
|
||||
# 验证正则表达式
|
||||
for pattern in self.regex:
|
||||
try:
|
||||
re.compile(pattern)
|
||||
except re.error as e:
|
||||
raise ValueError(f"无效的正则表达式 '{pattern}': {str(e)}") from e
|
||||
|
||||
|
||||
@dataclass
|
||||
class KeywordReactionConfig(ConfigBase):
|
||||
"""关键词配置类"""
|
||||
|
||||
keyword_rules: list[KeywordRuleConfig] = field(default_factory=lambda: [])
|
||||
"""关键词规则列表"""
|
||||
|
||||
regex_rules: list[KeywordRuleConfig] = field(default_factory=lambda: [])
|
||||
"""正则表达式规则列表"""
|
||||
|
||||
def __post_init__(self):
|
||||
"""验证配置"""
|
||||
# 验证所有规则
|
||||
for rule in self.keyword_rules + self.regex_rules:
|
||||
if not isinstance(rule, KeywordRuleConfig):
|
||||
raise ValueError(f"规则必须是KeywordRuleConfig类型，而不是{type(rule).__name__}")
|
||||
|
||||
|
||||
@dataclass
|
||||
class ChineseTypoConfig(ConfigBase):
|
||||
"""中文错别字配置类"""
|
||||
|
||||
enable: bool = True
|
||||
"""是否启用中文错别字生成器"""
|
||||
|
||||
error_rate: float = 0.01
|
||||
"""单字替换概率"""
|
||||
|
||||
min_freq: int = 9
|
||||
"""最小字频阈值"""
|
||||
|
||||
tone_error_rate: float = 0.1
|
||||
"""声调错误概率"""
|
||||
|
||||
word_replace_rate: float = 0.006
|
||||
"""整词替换概率"""
|
||||
|
||||
|
||||
@dataclass
|
||||
class ResponseSplitterConfig(ConfigBase):
|
||||
"""回复分割器配置类"""
|
||||
|
||||
enable: bool = True
|
||||
"""是否启用回复分割器"""
|
||||
|
||||
max_length: int = 256
|
||||
"""回复允许的最大长度"""
|
||||
|
||||
max_sentence_num: int = 3
|
||||
"""回复允许的最大句子数"""
|
||||
|
||||
enable_kaomoji_protection: bool = False
|
||||
"""是否启用颜文字保护"""
|
||||
|
||||
|
||||
@dataclass
|
||||
class TelemetryConfig(ConfigBase):
|
||||
"""遥测配置类"""
|
||||
|
||||
enable: bool = True
|
||||
"""是否启用遥测"""
|
||||
|
||||
|
||||
@dataclass
|
||||
class ExperimentalConfig(ConfigBase):
|
||||
"""实验功能配置类"""
|
||||
|
||||
debug_show_chat_mode: bool = False
|
||||
"""是否在回复后显示当前聊天模式"""
|
||||
|
||||
enable_friend_chat: bool = False
|
||||
"""是否启用好友聊天"""
|
||||
|
||||
pfc_chatting: bool = False
|
||||
"""是否启用PFC"""
|
||||
|
||||
|
||||
@dataclass
|
||||
class MaimMessageConfig(ConfigBase):
|
||||
"""maim_message配置类"""
|
||||
|
||||
use_custom: bool = False
|
||||
"""是否使用自定义的maim_message配置"""
|
||||
|
||||
host: str = "127.0.0.1"
|
||||
"""主机地址"""
|
||||
|
||||
port: int = 8090
|
||||
""""端口号"""
|
||||
|
||||
mode: Literal["ws", "tcp"] = "ws"
|
||||
"""连接模式，支持ws和tcp"""
|
||||
|
||||
use_wss: bool = False
|
||||
"""是否使用WSS安全连接"""
|
||||
|
||||
cert_file: str = ""
|
||||
"""SSL证书文件路径，仅在use_wss=True时有效"""
|
||||
|
||||
key_file: str = ""
|
||||
"""SSL密钥文件路径，仅在use_wss=True时有效"""
|
||||
|
||||
auth_token: list[str] = field(default_factory=lambda: [])
|
||||
"""认证令牌，用于API验证，为空则不启用验证"""
|
||||
|
||||
|
||||
@dataclass
|
||||
class ModelConfig(ConfigBase):
|
||||
"""模型配置类"""
|
||||
|
||||
model_max_output_length: int = 800 # 最大回复长度
|
||||
|
||||
utils: dict[str, Any] = field(default_factory=lambda: {})
|
||||
"""组件模型配置"""
|
||||
|
||||
utils_small: dict[str, Any] = field(default_factory=lambda: {})
|
||||
"""组件小模型配置"""
|
||||
|
||||
normal_chat_1: dict[str, Any] = field(default_factory=lambda: {})
|
||||
"""normal_chat首要回复模型模型配置"""
|
||||
|
||||
normal_chat_2: dict[str, Any] = field(default_factory=lambda: {})
|
||||
"""normal_chat次要回复模型配置"""
|
||||
|
||||
memory_summary: dict[str, Any] = field(default_factory=lambda: {})
|
||||
"""记忆的概括模型配置"""
|
||||
|
||||
vlm: dict[str, Any] = field(default_factory=lambda: {})
|
||||
"""视觉语言模型配置"""
|
||||
|
||||
focus_working_memory: dict[str, Any] = field(default_factory=lambda: {})
|
||||
"""专注工作记忆模型配置"""
|
||||
|
||||
|
||||
focus_tool_use: dict[str, Any] = field(default_factory=lambda: {})
|
||||
"""专注工具使用模型配置"""
|
||||
|
||||
planner: dict[str, Any] = field(default_factory=lambda: {})
|
||||
"""规划模型配置"""
|
||||
|
||||
relation: dict[str, Any] = field(default_factory=lambda: {})
|
||||
"""关系模型配置"""
|
||||
|
||||
focus_expressor: dict[str, Any] = field(default_factory=lambda: {})
|
||||
"""专注表达器模型配置"""
|
||||
|
||||
embedding: dict[str, Any] = field(default_factory=lambda: {})
|
||||
"""嵌入模型配置"""
|
||||
|
||||
pfc_action_planner: dict[str, Any] = field(default_factory=lambda: {})
|
||||
"""PFC动作规划模型配置"""
|
||||
|
||||
pfc_chat: dict[str, Any] = field(default_factory=lambda: {})
|
||||
"""PFC聊天模型配置"""
|
||||
|
||||
pfc_reply_checker: dict[str, Any] = field(default_factory=lambda: {})
|
||||
"""PFC回复检查模型配置"""
|
||||
Loading…
Reference in New Issue