diff --git a/![新版麦麦开始学习.bat b/![新版麦麦开始学习.bat new file mode 100644 index 000000000..41fc98368 --- /dev/null +++ b/![新版麦麦开始学习.bat @@ -0,0 +1,46 @@ +@echo off +CHCP 65001 > nul +setlocal enabledelayedexpansion + +REM 查找venv虚拟环境 +set "venv_path=%~dp0venv\Scripts\activate.bat" +if not exist "%venv_path%" ( + echo 错误: 未找到虚拟环境，请确保venv目录存在 + pause + exit /b 1 +) + +REM 激活虚拟环境 +call "%venv_path%" +if %ERRORLEVEL% neq 0 ( + echo 错误: 虚拟环境激活失败 + pause + exit /b 1 +) + +REM 运行预处理脚本 +python "%~dp0scripts\raw_data_preprocessor.py" +if %ERRORLEVEL% neq 0 ( + echo 错误: raw_data_preprocessor.py 执行失败 + pause + exit /b 1 +) + +REM 运行信息提取脚本 +python "%~dp0scripts\info_extraction.py" +if %ERRORLEVEL% neq 0 ( + echo 错误: info_extraction.py 执行失败 + pause + exit /b 1 +) + +REM 运行OpenIE导入脚本 +python "%~dp0scripts\import_openie.py" +if %ERRORLEVEL% neq 0 ( + echo 错误: import_openie.py 执行失败 + pause + exit /b 1 +) + +echo 所有处理步骤完成! +pause \ No newline at end of file diff --git a/.dockerignore b/.dockerignore index 6c2d07736..fac1bf99a 100644 --- a/.dockerignore +++ b/.dockerignore @@ -1,6 +1,5 @@ .git __pycache__ -*.pyc *.pyo *.pyd .DS_Store diff --git a/.github/workflows/docker-image.yml b/.github/workflows/docker-image.yml index 76636d746..605d838ce 100644 --- a/.github/workflows/docker-image.yml +++ b/.github/workflows/docker-image.yml @@ -24,6 +24,9 @@ jobs: - name: Clone maim_message run: git clone https://github.com/MaiM-with-u/maim_message maim_message + - name: Clone lpmm + run: git clone https://github.com/MaiM-with-u/MaiMBot-LPMM.git MaiMBot-LPMM + - name: Set up Docker Buildx uses: docker/setup-buildx-action@v3 diff --git a/.github/workflows/ruff-pr.yml b/.github/workflows/ruff-pr.yml new file mode 100644 index 000000000..bb83de8c9 --- /dev/null +++ b/.github/workflows/ruff-pr.yml @@ -0,0 +1,9 @@ +name: Ruff +on: [ pull_request ] +jobs: + ruff: + runs-on: ubuntu-latest + steps: + - uses: actions/checkout@v4 + - uses: astral-sh/ruff-action@v3 + diff --git a/.github/workflows/ruff.yml b/.github/workflows/ruff.yml index b3056fa6a..58921a76f 100644 --- a/.github/workflows/ruff.yml +++ b/.github/workflows/ruff.yml @@ -1,5 +1,5 @@ name: Ruff -on: [ push, pull_request ] +on: [ push ] permissions: contents: write diff --git a/.gitignore b/.gitignore index 3e9b98685..88995eccc 100644 --- a/.gitignore +++ b/.gitignore @@ -4,7 +4,9 @@ mongodb/ NapCat.Framework.Windows.Once/ log/ logs/ +tool_call_benchmark.py run_ad.bat +llm_tool_benchmark_results.json MaiBot-Napcat-Adapter-main MaiBot-Napcat-Adapter /test @@ -28,8 +30,9 @@ memory_graph.gml config/bot_config_dev.toml config/bot_config.toml config/bot_config.toml.bak +config/lpmm_config.toml +config/lpmm_config.toml.bak src/plugins/remote/client_uuid.json -run_none.bat （测试版）麦麦生成人格.bat （临时版）麦麦开始学习.bat src/plugins/utils/statistic.py @@ -240,6 +243,57 @@ logs .vscode /config/* -run_none.bat config/old/bot_config_20250405_212257.toml +temp/ +# General +.DS_Store +.AppleDouble +.LSOverride + +# Icon must end with two \r +Icon + +# Thumbnails +._* + +# Files that might appear in the root of a volume +.DocumentRevisions-V100 +.fseventsd +.Spotlight-V100 +.TemporaryItems +.Trashes +.VolumeIcon.icns +.com.apple.timemachine.donotpresent + +# Directories potentially created on remote AFP share +.AppleDB +.AppleDesktop +Network Trash Folder +Temporary Items +.apdisk + +# Windows thumbnail cache files +Thumbs.db +Thumbs.db:encryptable +ehthumbs.db +ehthumbs_vista.db + +# Dump file +*.stackdump + +# Folder config file +[Dd]esktop.ini + +# Recycle Bin used on file shares +$RECYCLE.BIN/ + +# Windows Installer files +*.cab +*.msi +*.msix +*.msm +*.msp + +# Windows shortcuts +*.lnk diff --git a/Dockerfile b/Dockerfile index 838e2b993..23165a23e 100644 --- a/Dockerfile +++ b/Dockerfile @@ -6,12 +6,22 @@ WORKDIR /MaiMBot # 复制依赖列表 COPY requirements.txt . -# 同级目录下需要有 maim_message -COPY maim_message /maim_message +# 同级目录下需要有 maim_message MaiMBot-LPMM +#COPY maim_message /maim_message +COPY MaiMBot-LPMM /MaiMBot-LPMM + +# 编译器 +RUN apt-get update && apt-get install -y build-essential + +# lpmm编译安装 +RUN cd /MaiMBot-LPMM && uv pip install --system -r requirements.txt +RUN uv pip install --system Cython py-cpuinfo setuptools +RUN cd /MaiMBot-LPMM/lib/quick_algo && python build_lib.py --cleanup --cythonize --install + # 安装依赖 RUN uv pip install --system --upgrade pip -RUN uv pip install --system -e /maim_message +#RUN uv pip install --system -e /maim_message RUN uv pip install --system -r requirements.txt # 复制项目代码 diff --git a/README.md b/README.md index 325e3ad22..58cb82c7d 100644 --- a/README.md +++ b/README.md @@ -14,7 +14,7 @@

- Logo + Logo
@@ -34,7 +34,6 @@ · 提出新特性

-

## 新版0.6.x部署前先阅读：https://docs.mai-mai.org/manual/usage/mmc_q_a @@ -53,7 +52,7 @@
- 麦麦演示视频 + 麦麦演示视频
👆 点击观看麦麦演示视频 👆 @@ -62,7 +61,7 @@ ### 📢 版本信息 -**最新版本: v0.6.2** ([查看更新日志](changelogs/changelog.md)) +**最新版本: v0.6.3** ([查看更新日志](changelogs/changelog.md)) > [!WARNING] > 请阅读教程后更新！！！！！！！ > 请阅读教程后更新！！！！！！！ @@ -91,15 +90,15 @@ - 项目处于活跃开发阶段，功能和API可能随时调整 ### 💬交流群（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 +- [二群](https://qm.qq.com/q/RzmCiRtHEW) 571780722 - [五群](https://qm.qq.com/q/JxvHZnxyec) 1022489779 -- [一群](https://qm.qq.com/q/VQ3XZrWgMs) 766798517 【已满】 -- [二群](https://qm.qq.com/q/RzmCiRtHEW) 571780722【已满】 - [三群](https://qm.qq.com/q/wlH5eT8OmQ) 1035228475【已满】 - [四群](https://qm.qq.com/q/wlH5eT8OmQ) 729957033【已满】
-

📚 文档

+

📚 文档

### (部分内容可能过时，请注意版本对应) @@ -111,19 +110,20 @@ - [🚀 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） -## 🎯 功能介绍 +## 🎯 0.6.3 功能介绍 -| 模块 | 主要功能 | 特点 | -|------|---------|------| -| 💬 聊天系统 | • 心流/推理聊天
• 关键词主动发言
• 多模型支持
• 动态prompt构建
• 私聊功能(PFC) | 拟人化交互 | -| 🧠 心流系统 | • 实时思考生成
• 自动启停机制
• 日程系统联动
• 工具调用能力 | 智能化决策 | -| 🧠 记忆系统 | • 优化记忆抽取
• 海马体记忆机制
• 聊天记录概括 | 持久化记忆 | -| 😊 表情系统 | • 情绪匹配发送
• GIF支持
• 自动收集与审查 | 丰富表达 | -| 📅 日程系统 | • 动态日程生成
• 自定义想象力
• 思维流联动 | 智能规划 | -| 👥 关系系统 | • 关系管理优化
• 丰富接口支持
• 个性化交互 | 深度社交 | -| 📊 统计系统 | • 使用数据统计
• LLM调用记录
• 实时控制台显示 | 数据可视 | -| 🔧 系统功能 | • 优雅关闭机制
• 自动数据保存
• 异常处理完善 | 稳定可靠 | -| 🛠️ 工具系统 | • 知识获取工具
• 自动注册机制
• 多工具支持 | 扩展功能 | +| 模块 | 主要功能 | 特点 | +|----------|------------------------------------------------------------------|-------| +| 💬 聊天系统 | • **统一调控不同回复逻辑**
• 智能交互模式 (普通聊天/专注聊天)
• 关键词主动发言
• 多模型支持
• 动态prompt构建
• 私聊功能(PFC)增强 | 拟人化交互 | +| 🧠 心流系统 | • 实时思考生成
• **智能状态管理**
• **概率回复机制**
• 自动启停机制
• 日程系统联动
• **上下文感知工具调用** | 智能化决策 | +| 🧠 记忆系统 | • **记忆整合与提取**
• 海马体记忆机制
• 聊天记录概括 | 持久化记忆 | +| 😊 表情系统 | • **全新表情包系统**
• **优化选择逻辑**
• 情绪匹配发送
• GIF支持
• 自动收集与审查 | 丰富表达 | +| 📅 日程系统 | • 动态日程生成
• 自定义想象力
• 思维流联动 | 智能规划 | +| 👥 关系系统 | • **工具调用动态更新**
• 关系管理优化
• 丰富接口支持
• 个性化交互 | 深度社交 | +| 📊 统计系统 | • 使用数据统计
• LLM调用记录
• 实时控制台显示 | 数据可视 | +| 🛠️ 工具系统 | • **LPMM知识库集成**
• **上下文感知调用**
• 知识获取工具
• 自动注册机制
• 多工具支持 | 扩展功能 | +| 📚 **知识库(LPMM)** | • **全新LPMM系统**
• **强大的信息检索能力** | 知识增强 | +| ✨ **昵称系统** | • **自动为群友取昵称**
• **降低认错人概率** (早期阶段) | 身份识别 | ## 📐 项目架构 @@ -143,21 +143,9 @@ graph TD E --> M[情绪识别] ``` - -## 开发计划TODO：LIST - -- 人格功能：WIP -- 对特定对象的侧写功能 -- 图片发送，转发功能：WIP -- 幽默和meme功能：WIP -- 兼容gif的解析和保存 -- 小程序转发链接解析 -- 修复已知bug -- 自动生成的回复逻辑，例如自生成的回复方向，回复风格 - ## ✍️如何给本项目报告BUG/提交建议/做贡献 -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！🎉 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](CONTRIBUTE.md)（待补完） +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！🎉 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](depends-data/CONTRIBUTE.md)（待补完） @@ -181,12 +169,16 @@ MaiCore是一个开源项目，我们非常欢迎你的参与。你的贡献， - [NapCat](https://github.com/NapNeko/NapCatQQ): 现代化的基于 NTQQ 的 Bot 协议端实现 +## 麦麦仓库状态 + +![Alt](https://repobeats.axiom.co/api/embed/9faca9fccfc467931b87dd357b60c6362b5cfae0.svg "Repobeats analytics image") + ### 贡献者 感谢各位大佬！ - + contributors **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** diff --git a/bot.py b/bot.py index 653efd45d..d547c360e 100644 --- a/bot.py +++ b/bot.py @@ -6,17 +6,17 @@ import sys from pathlib import Path import time import platform +import traceback from dotenv import load_dotenv -from src.common.logger import get_module_logger, LogConfig, CONFIRM_STYLE_CONFIG +from src.common.logger_manager import get_logger + +# from src.common.logger import LogConfig, CONFIRM_STYLE_CONFIG from src.common.crash_logger import install_crash_handler from src.main import MainSystem -logger = get_module_logger("main_bot") -confirm_logger_config = LogConfig( - console_format=CONFIRM_STYLE_CONFIG["console_format"], - file_format=CONFIRM_STYLE_CONFIG["file_format"], -) -confirm_logger = get_module_logger("confirm", config=confirm_logger_config) + +logger = get_logger("main") +confirm_logger = get_logger("confirm") # 获取没有加载env时的环境变量 env_mask = {key: os.getenv(key) for key in os.environ} @@ -51,6 +51,16 @@ def init_config(): shutil.copy("template/bot_config_template.toml", "config/bot_config.toml") logger.info("复制完成，请修改config/bot_config.toml和.env中的配置后重新启动") + if not os.path.exists("config/lpmm_config.toml"): + logger.warning("检测到lpmm_config.toml不存在，正在从模板复制") + + # 检查config目录是否存在 + if not os.path.exists("config"): + os.makedirs("config") + logger.info("创建config目录") + + shutil.copy("template/lpmm_config_template.toml", "config/lpmm_config.toml") + logger.info("复制完成，请修改config/lpmm_config.toml和.env中的配置后重新启动") def init_env(): @@ -236,7 +246,7 @@ if __name__ == "__main__": loop.close() except Exception as e: - logger.error(f"主程序异常: {str(e)}") + logger.error(f"主程序异常: {str(e)} {str(traceback.format_exc())}") if loop and not loop.is_closed(): loop.run_until_complete(graceful_shutdown()) loop.close() diff --git a/changelogs/changelog.md b/changelogs/changelog.md index 0ddb486bf..0d6608b02 100644 --- a/changelogs/changelog.md +++ b/changelogs/changelog.md @@ -1,5 +1,84 @@ # Changelog +## [0.6.3] - 2025-4-15 + +### 摘要 +- MaiBot 0.6.3 版本发布！核心重构回复逻辑，统一为心流系统管理，智能切换交互模式。 +- 引入全新的 LPMM 知识库系统，大幅提升信息获取能力。 +- 新增昵称系统，改善群聊中的身份识别。 +- 提供独立的桌宠适配器连接程序。 +- 优化日志输出，修复若干问题。 + +### 🌟 核心功能增强 +#### 统一回复逻辑 (Unified Reply Logic) +- **核心重构**: 移除了经典 (Reasoning) 与心流 (Heart Flow) 模式的区分，将回复逻辑完全整合到 `SubHeartflow` 中进行统一管理，由主心流统一调控。保留 Heart FC 模式的特色功能。 +- **智能交互模式**: `SubHeartflow` 现在可以根据情境智能选择不同的交互模式： + - **普通聊天 (Normal Chat)**: 类似于之前的 Reasoning 模式，进行常规回复（激活逻辑暂未改变）。 + - **心流聊天 (Heart Flow Chat)**: 基于改进的 PFC 模式，能更好地理解上下文，减少重复和认错人的情况，并支持**工具调用**以获取额外信息。 + - **离线模式 (Offline/Absent)**: 在特定情况下，麦麦可能会选择暂时不查看或回复群聊消息。 +- **状态管理**: 交互模式的切换由 `SubHeartflow` 内部逻辑和 `SubHeartflowManager` 根据整体状态 (`MaiState`) 和配置进行管理。 +- **流程优化**: 拆分了子心流的思考模块，使整体对话流程更加清晰。 +- **状态判断改进**: 将 CHAT 状态判断交给 LLM 处理，使对话更自然。 +- **回复机制**: 实现更为灵活的概率回复机制，使机器人能够自然地融入群聊环境。 +- **重复性检查**: 加入心流回复重复性检查机制，防止麦麦陷入固定回复模式。 + +#### 全新知识库系统 (New Knowledge Base System - LPMM) +- **引入 LPMM**: 新增了 **LPMM (Large Psychology Model Maker)** 知识库系统，具有强大的信息检索能力，能显著提升麦麦获取和利用知识的效率。 +- **功能集成**: 集成了 LPMM 知识库查询功能，进一步扩展信息检索能力。 +- **推荐使用**: 强烈建议使用新的 LPMM 系统以获得最佳体验。旧的知识库系统仍然可用作为备选。 + +#### 昵称系统 (Nickname System) +- **自动取名**: 麦麦现在会尝试给群友取昵称，减少对易变的群昵称的依赖，从而降低认错人的概率。 +- **持续完善**: 该系统目前仍处于早期阶段，会持续进行优化。 + +#### 记忆与上下文增强 (Memory and Context Enhancement) +- **聊天记录压缩**: 大幅优化聊天记录压缩系统，使机器人能够处理5倍于之前的上下文记忆量。 +- **长消息截断**: 新增了长消息自动截断与模糊化功能，随着时间推移降低超长消息的权重，避免被特定冗余信息干扰。 +- **记忆提取**: 优化记忆提取功能，提高对历史对话的理解和引用能力。 +- **记忆整合**: 为记忆系统加入了合并与整合机制，优化长期记忆的结构与效率。 +- **中期记忆调用**: 完善中期记忆调用机制，使机器人能够更自然地回忆和引用较早前的对话。 +- **Prompt 优化**: 进一步优化了关系系统和记忆系统相关的提示词（prompt）。 + +#### 私聊 PFC 功能增强 (Private Chat PFC Enhancement) +- **功能修复与优化**: 修复了私聊 PFC 载入聊天记录缺失的 bug，优化了 prompt 构建，增加了审核机制，调整了重试次数，并将机器人发言存入数据库。 +- **实验性质**: 请注意，PFC 仍然是一个实验性功能，可能在未来版本中被修改或移除，目前不接受相关 Bug 反馈。 + +#### 情感与互动增强 (Emotion and Interaction Enhancement) +- **全新表情包系统**: 新的表情包系统上线，表情含义更丰富，发送更快速。 +- **表情包使用优化**: 优化了表情包的选择逻辑，减少重复使用特定表情包的情况，使表达更生动。 +- **提示词优化**: 优化提示词（prompt）构建，增强对话质量和情感表达。 +- **积极性配置**: 优化"让麦麦更愿意说话"的相关配置，使机器人更积极参与对话。 +- **颜文字保护**: 保护颜文字处理机制，确保表情正确显示。 + +#### 工具与集成 (Tools and Integration) +- **动态更新**: 使用工具调用来更新关系和心情，取代原先的固定更新机制。 +- **智能调用**: 工具调用时会考虑上下文，使调用更加智能。 +- **知识库依赖**: 添加 LPMM 知识库依赖，扩展知识检索工具。 + +### 💻 系统架构优化 +#### 日志优化 (Logging Optimization) +- **输出更清晰**: 优化了日志信息的格式和内容，使其更易于阅读和理解。 + +#### 模型与消息整合 (Model and Message Integration) +- **模型合并**: 合并工具调用模型和心流模型，提高整体一致性。 +- **消息规范**: 全面改用 `maim_message`，移除对 `rest` 的支持。 + +#### (临时) 简易 GUI (Temporary Simple GUI) +- **运行状态查看**: 提供了一个非常基础的图形用户界面，用于查看麦麦的运行状态。 +- **临时方案**: 这是一个临时性的解决方案，功能简陋，**将在 0.6.4 版本中被全新的 Web UI 所取代**。此 GUI 不会包含在主程序包中，而是通过一键包提供，并且不接受 Bug 反馈。 + +### 🐛 问题修复 +- **记忆检索优化**: 提高了记忆检索的准确性和效率。 +- 修复了一些其他小问题。 + +### 🔧 其他改进 +#### 桌宠适配器 (Bug Catcher Adapter) +- **独立适配器**: 提供了一个"桌宠"独立适配器，用于连接麦麦和桌宠。 +- **获取方式**: 可在 MaiBot 的 GitHub 组织中找到该适配器，不包含在主程序内。 + +#### 一键包内容 (One-Click Package Contents) +- **辅助程序**: 一键包中包含了简易 GUI 和 **麦麦帮助配置** 等辅助程序，后者可在配置出现问题时提供帮助。 + ## [0.6.2] - 2025-4-14 ### 摘要 diff --git a/changelogs/changelog_config.md b/changelogs/changelog_config.md index e438ea31e..5aa5fb922 100644 --- a/changelogs/changelog_config.md +++ b/changelogs/changelog_config.md @@ -33,7 +33,7 @@ - 调整了部分配置项的默认值 - 调整了配置项的顺序，将 `groups` 配置项移到了更靠前的位置 - 在 `message` 配置项中： - - 新增了 `max_response_length` 参数 + - 新增了 `model_max_output_length` 参数 - 在 `willing` 配置项中新增了 `emoji_response_penalty` 参数 - 将 `personality` 配置项中的 `prompt_schedule` 重命名为 `prompt_schedule_gen` diff --git a/CONTRIBUTE.md b/depends-data/CONTRIBUTE.md similarity index 99% rename from CONTRIBUTE.md rename to depends-data/CONTRIBUTE.md index 440a8202d..c372aebe8 100644 --- a/CONTRIBUTE.md +++ b/depends-data/CONTRIBUTE.md @@ -19,7 +19,6 @@ ● [我有问题](#我有问题) ● [我想做贡献](#我想做贡献) -● [我想报告BUG](#报告BUG) ● [我想提出建议](#提出建议) ## 我有问题 diff --git a/llm_tool_benchmark_results.json b/llm_tool_benchmark_results.json new file mode 100644 index 000000000..6caa7c315 --- /dev/null +++ b/llm_tool_benchmark_results.json @@ -0,0 +1,145 @@ +{ + "测试时间": "2025-04-28 14:12:36", + "测试迭代次数": 10, + "不使用工具调用": { + "平均耗时": 4.596814393997192, + "最短耗时": 2.957131862640381, + "最长耗时": 10.121938705444336, + "标准差": 2.1705468730949593, + "所有耗时": [ + 3.18, + 4.65, + 10.12, + 3.5, + 4.46, + 4.24, + 3.23, + 6.2, + 2.96, + 3.42 + ] + }, + "不使用工具调用_详细响应": [ + { + "内容摘要": "```json\n{\n \"action\": \"text_reply\",\n \"content\": \"怎么啦？\",\n \"emoji_query\": \"友好地询问\"\n}\n```", + "推理内容摘要": "" + }, + { + "内容摘要": "decide_reply_action(\n action=\"text_reply\",\n reasoning=\"千石连续两次叫了我的名字，显然是想引起我的注意或有事要说，作为礼貌应当回应\",\n emoji_query=\"友善的回应\"\n)", + "推理内容摘要": "" + }, + { + "内容摘要": "```json\n{\n \"action\": \"text_reply\",\n \"content\": \"怎么啦？我在呢~\",\n \"emoji_query\": \"友好的询问\",\n \"reasoning\": \"由于对方连续两次提到我的名字，显然是想与我交流，应当及时给予友好回应避免冷场\"\n}\n```", + "推理内容摘要": "" + }, + { + "内容摘要": "```json\n{\n \"action\": \"text_reply\",\n \"content\": \"在呢在呢~怎么啦？\",\n \"emoji_query\": \"好奇的回应\"\n}\n```", + "推理内容摘要": "" + }, + { + "内容摘要": "decide_reply_action(\n action=\"text_reply\",\n reasoning=\"千石连续两次提到我的名字，显然需要我回应。文字回复更正式且能明确表示我在关注他的信息。\",\n emoji_query=\"友好的回应\"\n)", + "推理内容摘要": "" + }, + { + "内容摘要": "```json\n{\n \"action\": \"text_reply\",\n \"reasoning\": \"千石连续两次提到我的名字，显然是需要我的回应。作为日常交流，应该给予友善简短的答复。\",\n \"emoji_query\": \"疑惑的歪头\"\n}\n```", + "推理内容摘要": "" + }, + { + "内容摘要": "```json\n{\n \"action\": \"text_reply\",\n \"content\": \"咋啦千石~\",\n \"emoji_query\": \"好奇的询问\"\n}\n```", + "推理内容摘要": "" + }, + { + "内容摘要": "decide_reply_action\n```json\n{\n \"action\": \"text_reply\",\n \"content\": \"我在呢～怎么啦？\",\n \"emoji_query\": \"友好的关心\",\n \"reasoning\": \"千石连续两次呼唤我的名字，显然是有事情要找我或想引起我的注意。根据回复原则2（有人提到你但未回应），应该用友善的文字进行回应，并附上表达关心的表情符号来延...", + "推理内容摘要": "" + }, + { + "内容摘要": "```json\n{\n \"action\": \"text_reply\",\n \"content\": \"千石怎么啦～\",\n \"emoji_query\": \"好奇的探询\"\n}\n```", + "推理内容摘要": "" + }, + { + "内容摘要": "```json\n{\n \"action\": \"text_reply\",\n \"content\": \"怎么啦？突然叫我两次\",\n \"emoji_query\": \"好奇的疑问\"\n}\n```", + "推理内容摘要": "" + } + ], + "使用工具调用": { + "平均耗时": 8.139546775817871, + "最短耗时": 4.9980738162994385, + "最长耗时": 18.803313732147217, + "标准差": 4.008772720760647, + "所有耗时": [ + 5.81, + 18.8, + 6.06, + 8.06, + 10.07, + 6.34, + 7.9, + 6.66, + 5.0, + 6.69 + ] + }, + "使用工具调用_详细响应": [ + { + "内容摘要": "", + "推理内容摘要": "", + "工具调用数量": 0, + "工具调用详情": [] + }, + { + "内容摘要": "", + "推理内容摘要": "", + "工具调用数量": 0, + "工具调用详情": [] + }, + { + "内容摘要": "", + "推理内容摘要": "", + "工具调用数量": 0, + "工具调用详情": [] + }, + { + "内容摘要": "", + "推理内容摘要": "", + "工具调用数量": 0, + "工具调用详情": [] + }, + { + "内容摘要": "", + "推理内容摘要": "", + "工具调用数量": 0, + "工具调用详情": [] + }, + { + "内容摘要": "", + "推理内容摘要": "", + "工具调用数量": 0, + "工具调用详情": [] + }, + { + "内容摘要": "", + "推理内容摘要": "", + "工具调用数量": 0, + "工具调用详情": [] + }, + { + "内容摘要": "", + "推理内容摘要": "", + "工具调用数量": 0, + "工具调用详情": [] + }, + { + "内容摘要": "", + "推理内容摘要": "", + "工具调用数量": 0, + "工具调用详情": [] + }, + { + "内容摘要": "", + "推理内容摘要": "", + "工具调用数量": 0, + "工具调用详情": [] + } + ], + "差异百分比": 77.07 +} \ No newline at end of file diff --git a/requirements.txt b/requirements.txt index 0fcb31f83..06068d888 100644 Binary files a/requirements.txt and b/requirements.txt differ diff --git a/scripts/import_openie.py b/scripts/import_openie.py new file mode 100644 index 000000000..26cbd8ce1 --- /dev/null +++ b/scripts/import_openie.py @@ -0,0 +1,167 @@ +# try: +# import src.plugins.knowledge.lib.quick_algo +# except ImportError: +# print("未找到quick_algo库，无法使用quick_algo算法") +# print("请安装quick_algo库 - 在lib.quick_algo中，执行命令：python setup.py build_ext --inplace") + +import sys +import os + +sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), ".."))) +from typing import Dict, List + +from src.plugins.knowledge.src.lpmmconfig import PG_NAMESPACE, global_config +from src.plugins.knowledge.src.embedding_store import EmbeddingManager +from src.plugins.knowledge.src.llm_client import LLMClient +from src.plugins.knowledge.src.open_ie import OpenIE +from src.plugins.knowledge.src.kg_manager import KGManager +from src.common.logger import get_module_logger +from src.plugins.knowledge.src.utils.hash import get_sha256 + + +# 添加项目根目录到 sys.path + + +logger = get_module_logger("LPMM知识库-OpenIE导入") + + +def hash_deduplicate( + raw_paragraphs: Dict[str, str], + triple_list_data: Dict[str, List[List[str]]], + stored_pg_hashes: set, + stored_paragraph_hashes: set, +): + """Hash去重 + + Args: + raw_paragraphs: 索引的段落原文 + triple_list_data: 索引的三元组列表 + stored_pg_hashes: 已存储的段落hash集合 + stored_paragraph_hashes: 已存储的段落hash集合 + + Returns: + new_raw_paragraphs: 去重后的段落 + new_triple_list_data: 去重后的三元组 + """ + # 保存去重后的段落 + new_raw_paragraphs = dict() + # 保存去重后的三元组 + new_triple_list_data = dict() + + for _, (raw_paragraph, triple_list) in enumerate(zip(raw_paragraphs.values(), triple_list_data.values())): + # 段落hash + paragraph_hash = get_sha256(raw_paragraph) + if ((PG_NAMESPACE + "-" + paragraph_hash) in stored_pg_hashes) and (paragraph_hash in stored_paragraph_hashes): + continue + new_raw_paragraphs[paragraph_hash] = raw_paragraph + new_triple_list_data[paragraph_hash] = triple_list + + return new_raw_paragraphs, new_triple_list_data + + +def handle_import_openie(openie_data: OpenIE, embed_manager: EmbeddingManager, kg_manager: KGManager) -> bool: + # 从OpenIE数据中提取段落原文与三元组列表 + # 索引的段落原文 + raw_paragraphs = openie_data.extract_raw_paragraph_dict() + # 索引的实体列表 + entity_list_data = openie_data.extract_entity_dict() + # 索引的三元组列表 + triple_list_data = openie_data.extract_triple_dict() + if len(raw_paragraphs) != len(entity_list_data) or len(raw_paragraphs) != len(triple_list_data): + logger.error("OpenIE数据存在异常") + return False + # 将索引换为对应段落的hash值 + logger.info("正在进行段落去重与重索引") + raw_paragraphs, triple_list_data = hash_deduplicate( + raw_paragraphs, + triple_list_data, + embed_manager.stored_pg_hashes, + kg_manager.stored_paragraph_hashes, + ) + if len(raw_paragraphs) != 0: + # 获取嵌入并保存 + logger.info(f"段落去重完成，剩余待处理的段落数量：{len(raw_paragraphs)}") + logger.info("开始Embedding") + embed_manager.store_new_data_set(raw_paragraphs, triple_list_data) + # Embedding-Faiss重索引 + logger.info("正在重新构建向量索引") + embed_manager.rebuild_faiss_index() + logger.info("向量索引构建完成") + embed_manager.save_to_file() + logger.info("Embedding完成") + # 构建新段落的RAG + logger.info("开始构建RAG") + kg_manager.build_kg(triple_list_data, embed_manager) + kg_manager.save_to_file() + logger.info("RAG构建完成") + else: + logger.info("无新段落需要处理") + return True + + +def main(): + # 新增确认提示 + print("=== 重要操作确认 ===") + print("OpenIE导入时会大量发送请求，可能会撞到请求速度上限，请注意选用的模型") + print("同之前样例：在本地模型下，在70分钟内我们发送了约8万条请求，在网络允许下，速度会更快") + print("推荐使用硅基流动的Pro/BAAI/bge-m3") + print("每百万Token费用为0.7元") + print("知识导入时，会消耗大量系统资源，建议在较好配置电脑上运行") + print("同上样例，导入时10700K几乎跑满，14900HX占用80%，峰值内存占用约3G") + confirm = input("确认继续执行？(y/n): ").strip().lower() + if confirm != "y": + logger.info("用户取消操作") + print("操作已取消") + sys.exit(1) + print("\n" + "=" * 40 + "\n") + + logger.info("----开始导入openie数据----\n") + + logger.info("创建LLM客户端") + llm_client_list = dict() + for key in global_config["llm_providers"]: + llm_client_list[key] = LLMClient( + global_config["llm_providers"][key]["base_url"], + global_config["llm_providers"][key]["api_key"], + ) + + # 初始化Embedding库 + embed_manager = embed_manager = EmbeddingManager(llm_client_list[global_config["embedding"]["provider"]]) + logger.info("正在从文件加载Embedding库") + try: + embed_manager.load_from_file() + except Exception as e: + logger.error("从文件加载Embedding库时发生错误：{}".format(e)) + logger.info("Embedding库加载完成") + # 初始化KG + kg_manager = KGManager() + logger.info("正在从文件加载KG") + try: + kg_manager.load_from_file() + except Exception as e: + logger.error("从文件加载KG时发生错误：{}".format(e)) + logger.info("KG加载完成") + + logger.info(f"KG节点数量：{len(kg_manager.graph.get_node_list())}") + logger.info(f"KG边数量：{len(kg_manager.graph.get_edge_list())}") + + # 数据比对：Embedding库与KG的段落hash集合 + for pg_hash in kg_manager.stored_paragraph_hashes: + key = PG_NAMESPACE + "-" + pg_hash + if key not in embed_manager.stored_pg_hashes: + logger.warning(f"KG中存在Embedding库中不存在的段落：{key}") + + logger.info("正在导入OpenIE数据文件") + try: + openie_data = OpenIE.load() + except Exception as e: + logger.error("导入OpenIE数据文件时发生错误：{}".format(e)) + return False + if handle_import_openie(openie_data, embed_manager, kg_manager) is False: + logger.error("处理OpenIE数据时发生错误") + return False + return None + + +if __name__ == "__main__": + main() diff --git a/scripts/info_extraction.py b/scripts/info_extraction.py new file mode 100644 index 000000000..fdb445285 --- /dev/null +++ b/scripts/info_extraction.py @@ -0,0 +1,178 @@ +import json +import os +import signal +from concurrent.futures import ThreadPoolExecutor, as_completed +from threading import Lock, Event +import sys + +sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), ".."))) +# 添加项目根目录到 sys.path + +import tqdm + +from src.common.logger import get_module_logger +from src.plugins.knowledge.src.lpmmconfig import global_config +from src.plugins.knowledge.src.ie_process import info_extract_from_str +from src.plugins.knowledge.src.llm_client import LLMClient +from src.plugins.knowledge.src.open_ie import OpenIE +from src.plugins.knowledge.src.raw_processing import load_raw_data + +logger = get_module_logger("LPMM知识库-信息提取") + +TEMP_DIR = "./temp" + +# 创建一个线程安全的锁，用于保护文件操作和共享数据 +file_lock = Lock() +open_ie_doc_lock = Lock() + +# 创建一个事件标志，用于控制程序终止 +shutdown_event = Event() + + +def process_single_text(pg_hash, raw_data, llm_client_list): + """处理单个文本的函数，用于线程池""" + temp_file_path = f"{TEMP_DIR}/{pg_hash}.json" + + # 使用文件锁检查和读取缓存文件 + with file_lock: + if os.path.exists(temp_file_path): + try: + # 存在对应的提取结果 + logger.info(f"找到缓存的提取结果：{pg_hash}") + with open(temp_file_path, "r", encoding="utf-8") as f: + return json.load(f), None + except json.JSONDecodeError: + # 如果JSON文件损坏，删除它并重新处理 + logger.warning(f"缓存文件损坏，重新处理：{pg_hash}") + os.remove(temp_file_path) + + entity_list, rdf_triple_list = info_extract_from_str( + llm_client_list[global_config["entity_extract"]["llm"]["provider"]], + llm_client_list[global_config["rdf_build"]["llm"]["provider"]], + raw_data, + ) + if entity_list is None or rdf_triple_list is None: + return None, pg_hash + else: + doc_item = { + "idx": pg_hash, + "passage": raw_data, + "extracted_entities": entity_list, + "extracted_triples": rdf_triple_list, + } + # 保存临时提取结果 + with file_lock: + try: + with open(temp_file_path, "w", encoding="utf-8") as f: + json.dump(doc_item, f, ensure_ascii=False, indent=4) + except Exception as e: + logger.error(f"保存缓存文件失败：{pg_hash}, 错误：{e}") + # 如果保存失败，确保不会留下损坏的文件 + if os.path.exists(temp_file_path): + os.remove(temp_file_path) + # 设置shutdown_event以终止程序 + shutdown_event.set() + return None, pg_hash + return doc_item, None + + +def signal_handler(signum, frame): + """处理Ctrl+C信号""" + logger.info("\n接收到中断信号，正在优雅地关闭程序...") + shutdown_event.set() + + +def main(): + # 设置信号处理器 + signal.signal(signal.SIGINT, signal_handler) + + # 新增用户确认提示 + print("=== 重要操作确认 ===") + print("实体提取操作将会花费较多资金和时间，建议在空闲时段执行。") + print("举例：600万字全剧情，提取选用deepseek v3 0324，消耗约40元，约3小时。") + print("建议使用硅基流动的非Pro模型") + print("或者使用可以用赠金抵扣的Pro模型") + print("请确保账户余额充足，并且在执行前确认无误。") + confirm = input("确认继续执行？(y/n): ").strip().lower() + if confirm != "y": + logger.info("用户取消操作") + print("操作已取消") + sys.exit(1) + print("\n" + "=" * 40 + "\n") + + logger.info("--------进行信息提取--------\n") + + logger.info("创建LLM客户端") + llm_client_list = dict() + for key in global_config["llm_providers"]: + llm_client_list[key] = LLMClient( + global_config["llm_providers"][key]["base_url"], + global_config["llm_providers"][key]["api_key"], + ) + + logger.info("正在加载原始数据") + sha256_list, raw_datas = load_raw_data() + logger.info("原始数据加载完成\n") + + # 创建临时目录 + if not os.path.exists(f"{TEMP_DIR}"): + os.makedirs(f"{TEMP_DIR}") + + failed_sha256 = [] + open_ie_doc = [] + + # 创建线程池，最大线程数为50 + workers = global_config["info_extraction"]["workers"] + with ThreadPoolExecutor(max_workers=workers) as executor: + # 提交所有任务到线程池 + future_to_hash = { + executor.submit(process_single_text, pg_hash, raw_data, llm_client_list): pg_hash + for pg_hash, raw_data in zip(sha256_list, raw_datas) + } + + # 使用tqdm显示进度 + with tqdm.tqdm(total=len(future_to_hash), postfix="正在进行提取：") as pbar: + # 处理完成的任务 + try: + for future in as_completed(future_to_hash): + if shutdown_event.is_set(): + # 取消所有未完成的任务 + for f in future_to_hash: + if not f.done(): + f.cancel() + break + + doc_item, failed_hash = future.result() + if failed_hash: + failed_sha256.append(failed_hash) + logger.error(f"提取失败：{failed_hash}") + elif doc_item: + with open_ie_doc_lock: + open_ie_doc.append(doc_item) + pbar.update(1) + except KeyboardInterrupt: + # 如果在这里捕获到KeyboardInterrupt，说明signal_handler可能没有正常工作 + logger.info("\n接收到中断信号，正在优雅地关闭程序...") + shutdown_event.set() + # 取消所有未完成的任务 + for f in future_to_hash: + if not f.done(): + f.cancel() + + # 保存信息提取结果 + sum_phrase_chars = sum([len(e) for chunk in open_ie_doc for e in chunk["extracted_entities"]]) + sum_phrase_words = sum([len(e.split()) for chunk in open_ie_doc for e in chunk["extracted_entities"]]) + num_phrases = sum([len(chunk["extracted_entities"]) for chunk in open_ie_doc]) + openie_obj = OpenIE( + open_ie_doc, + round(sum_phrase_chars / num_phrases, 4), + round(sum_phrase_words / num_phrases, 4), + ) + OpenIE.save(openie_obj) + + logger.info("--------信息提取完成--------") + logger.info(f"提取失败的文段SHA256：{failed_sha256}") + + +if __name__ == "__main__": + main() diff --git a/scripts/interest_monitor_gui.py b/scripts/interest_monitor_gui.py new file mode 100644 index 000000000..1f03b9695 --- /dev/null +++ b/scripts/interest_monitor_gui.py @@ -0,0 +1,667 @@ +import tkinter as tk +from tkinter import ttk +import time +import os +from datetime import datetime, timedelta +import random +from collections import deque +import json # 引入 json + +# --- 引入 Matplotlib --- +from matplotlib.figure import Figure +from matplotlib.backends.backend_tkagg import FigureCanvasTkAgg +import matplotlib.dates as mdates # 用于处理日期格式 +import matplotlib # 导入 matplotlib + +# --- 配置 --- +LOG_FILE_PATH = os.path.join("logs", "interest", "interest_history.log") # 指向历史日志文件 +REFRESH_INTERVAL_MS = 200 # 刷新间隔 (毫秒) - 可以适当调长，因为读取文件可能耗时 +WINDOW_TITLE = "Interest Monitor (Live History)" +MAX_HISTORY_POINTS = 1000 # 图表上显示的最大历史点数 (可以增加) +MAX_STREAMS_TO_DISPLAY = 15 # 最多显示多少个聊天流的折线图 (可以增加) +MAX_QUEUE_SIZE = 30 # 新增：历史想法队列最大长度 + +# *** 添加 Matplotlib 中文字体配置 *** +# 尝试使用 'SimHei' 或 'Microsoft YaHei'，如果找不到，matplotlib 会回退到默认字体 +# 确保你的系统上安装了这些字体 +matplotlib.rcParams["font.sans-serif"] = ["SimHei", "Microsoft YaHei"] +matplotlib.rcParams["axes.unicode_minus"] = False # 解决负号'-'显示为方块的问题 + + +class InterestMonitorApp: + def __init__(self, root): + self.root = root + self.root.title(WINDOW_TITLE) + self.root.geometry("1800x800") # 调整窗口大小以适应图表 + + # --- 数据存储 --- + # 使用 deque 来存储有限的历史数据点 + # key: stream_id, value: deque([(timestamp, interest_level), ...]) + self.stream_history = {} + # key: stream_id, value: deque([(timestamp, reply_probability), ...]) + self.probability_history = {} + self.stream_colors = {} # 为每个 stream 分配颜色 + self.stream_display_names = {} # 存储显示名称 (group_name) + self.selected_stream_id = tk.StringVar() # 用于 Combobox 绑定 + + # --- 新增：存储其他参数 --- + # 顶层信息 + self.latest_main_mind = tk.StringVar(value="N/A") + self.latest_mai_state = tk.StringVar(value="N/A") + self.latest_subflow_count = tk.IntVar(value=0) + # 子流最新状态 (key: stream_id) + self.stream_sub_minds = {} + self.stream_chat_states = {} + self.stream_threshold_status = {} + self.stream_last_active = {} + self.stream_last_interaction = {} + # 用于显示单个流详情的 StringVar + self.single_stream_sub_mind = tk.StringVar(value="想法: N/A") + self.single_stream_chat_state = tk.StringVar(value="状态: N/A") + self.single_stream_threshold = tk.StringVar(value="阈值: N/A") + self.single_stream_last_active = tk.StringVar(value="活跃: N/A") + self.single_stream_last_interaction = tk.StringVar(value="交互: N/A") + + # 新增：历史想法队列 + self.main_mind_history = deque(maxlen=MAX_QUEUE_SIZE) + self.last_main_mind_timestamp = 0 # 记录最后一条main_mind的时间戳 + + # --- UI 元素 --- + + # --- 新增：顶部全局信息框架 --- + self.global_info_frame = ttk.Frame(root, padding="5 0 5 5") # 顶部内边距调整 + self.global_info_frame.pack(side=tk.TOP, fill=tk.X, pady=(5, 0)) # 底部外边距为0 + + ttk.Label(self.global_info_frame, text="全局状态:").pack(side=tk.LEFT, padx=(0, 10)) + ttk.Label(self.global_info_frame, textvariable=self.latest_mai_state).pack(side=tk.LEFT, padx=5) + ttk.Label(self.global_info_frame, text="想法:").pack(side=tk.LEFT, padx=(10, 0)) + ttk.Label(self.global_info_frame, textvariable=self.latest_main_mind).pack(side=tk.LEFT, padx=5) + ttk.Label(self.global_info_frame, text="子流数:").pack(side=tk.LEFT, padx=(10, 0)) + ttk.Label(self.global_info_frame, textvariable=self.latest_subflow_count).pack(side=tk.LEFT, padx=5) + + # 创建 Notebook (选项卡控件) + self.notebook = ttk.Notebook(root) + # 修改：fill 和 expand，让 notebook 填充剩余空间 + self.notebook.pack(pady=(5, 0), padx=10, fill=tk.BOTH, expand=1) # 顶部外边距改小 + + # --- 第一个选项卡：所有流 --- + self.frame_all = ttk.Frame(self.notebook, padding="5 5 5 5") + self.notebook.add(self.frame_all, text="所有聊天流") + + # 状态标签 (移动到最底部) + self.status_label = tk.Label(root, text="Initializing...", anchor="w", fg="grey") + self.status_label.pack(side=tk.BOTTOM, fill=tk.X, padx=10, pady=(0, 5)) # 调整边距 + + # Matplotlib 图表设置 (用于第一个选项卡) + self.fig = Figure(figsize=(5, 4), dpi=100) + self.ax = self.fig.add_subplot(111) + # 配置在 update_plot 中进行，避免重复 + + # 创建 Tkinter 画布嵌入 Matplotlib 图表 (用于第一个选项卡) + self.canvas = FigureCanvasTkAgg(self.fig, master=self.frame_all) # <--- 放入 frame_all + self.canvas_widget = self.canvas.get_tk_widget() + self.canvas_widget.pack(side=tk.TOP, fill=tk.BOTH, expand=1) + + # --- 第二个选项卡：单个流 --- + self.frame_single = ttk.Frame(self.notebook, padding="5 5 5 5") + self.notebook.add(self.frame_single, text="单个聊天流详情") + + # 单个流选项卡的上部控制区域 + self.control_frame_single = ttk.Frame(self.frame_single) + self.control_frame_single.pack(side=tk.TOP, fill=tk.X, pady=5) + + ttk.Label(self.control_frame_single, text="选择聊天流:").pack(side=tk.LEFT, padx=(0, 5)) + self.stream_selector = ttk.Combobox( + self.control_frame_single, textvariable=self.selected_stream_id, state="readonly", width=50 + ) + self.stream_selector.pack(side=tk.LEFT, fill=tk.X, expand=True) + self.stream_selector.bind("<>", self.on_stream_selected) + + # --- 新增：单个流详情显示区域 --- + self.single_stream_details_frame = ttk.Frame(self.frame_single, padding="5 5 5 0") + self.single_stream_details_frame.pack(side=tk.TOP, fill=tk.X, pady=(0, 5)) + + ttk.Label(self.single_stream_details_frame, textvariable=self.single_stream_sub_mind).pack(side=tk.LEFT, padx=5) + ttk.Label(self.single_stream_details_frame, textvariable=self.single_stream_chat_state).pack( + side=tk.LEFT, padx=5 + ) + ttk.Label(self.single_stream_details_frame, textvariable=self.single_stream_threshold).pack( + side=tk.LEFT, padx=5 + ) + ttk.Label(self.single_stream_details_frame, textvariable=self.single_stream_last_active).pack( + side=tk.LEFT, padx=5 + ) + ttk.Label(self.single_stream_details_frame, textvariable=self.single_stream_last_interaction).pack( + side=tk.LEFT, padx=5 + ) + + # Matplotlib 图表设置 (用于第二个选项卡) + self.fig_single = Figure(figsize=(5, 4), dpi=100) + # 修改：创建两个子图，一个显示兴趣度，一个显示概率 + self.ax_single_interest = self.fig_single.add_subplot(211) # 2行1列的第1个 + self.ax_single_probability = self.fig_single.add_subplot( + 212, sharex=self.ax_single_interest + ) # 2行1列的第2个，共享X轴 + + # 创建 Tkinter 画布嵌入 Matplotlib 图表 (用于第二个选项卡) + self.canvas_single = FigureCanvasTkAgg(self.fig_single, master=self.frame_single) # <--- 放入 frame_single + self.canvas_widget_single = self.canvas_single.get_tk_widget() + self.canvas_widget_single.pack(side=tk.TOP, fill=tk.BOTH, expand=1) + + # --- 新增第三个选项卡：麦麦历史想法 --- + self.frame_mind_history = ttk.Frame(self.notebook, padding="5 5 5 5") + self.notebook.add(self.frame_mind_history, text="麦麦历史想法") + + # 聊天框样式的文本框（只读）+ 滚动条 + self.mind_text_scroll = tk.Scrollbar(self.frame_mind_history) + self.mind_text_scroll.pack(side=tk.RIGHT, fill=tk.Y) + self.mind_text = tk.Text( + self.frame_mind_history, + height=25, + state="disabled", + wrap="word", + font=("微软雅黑", 12), + yscrollcommand=self.mind_text_scroll.set, + ) + self.mind_text.pack(side=tk.LEFT, fill=tk.BOTH, expand=1, padx=5, pady=5) + self.mind_text_scroll.config(command=self.mind_text.yview) + + # --- 初始化和启动刷新 --- + self.update_display() # 首次加载并开始刷新循环 + + def on_stream_selected(self, event=None): + """当 Combobox 选择改变时调用，更新单个流的图表""" + self.update_single_stream_plot() + + def get_random_color(self): + """生成随机颜色用于区分线条""" + return "#{:06x}".format(random.randint(0, 0xFFFFFF)) + + def load_main_mind_history(self): + """只读取包含main_mind的日志行，维护历史想法队列""" + if not os.path.exists(LOG_FILE_PATH): + return + + main_mind_entries = [] + try: + with open(LOG_FILE_PATH, "r", encoding="utf-8") as f: + for line in f: + try: + log_entry = json.loads(line.strip()) + if "main_mind" in log_entry: + ts = log_entry.get("timestamp", 0) + main_mind_entries.append((ts, log_entry)) + except Exception: + continue + main_mind_entries.sort(key=lambda x: x[0]) + recent_entries = main_mind_entries[-MAX_QUEUE_SIZE:] + self.main_mind_history.clear() + for _ts, entry in recent_entries: + self.main_mind_history.append(entry) + if recent_entries: + self.last_main_mind_timestamp = recent_entries[-1][0] + # 首次加载时刷新 + self.refresh_mind_text() + except Exception: + pass + + def update_main_mind_history(self): + """实时监控log文件，发现新main_mind数据则更新队列和展示（仅有新数据时刷新）""" + if not os.path.exists(LOG_FILE_PATH): + return + + new_entries = [] + try: + with open(LOG_FILE_PATH, "r", encoding="utf-8") as f: + for line in reversed(list(f)): + try: + log_entry = json.loads(line.strip()) + if "main_mind" in log_entry: + ts = log_entry.get("timestamp", 0) + if ts > self.last_main_mind_timestamp: + new_entries.append((ts, log_entry)) + else: + break + except Exception: + continue + if new_entries: + for ts, entry in sorted(new_entries): + if len(self.main_mind_history) >= MAX_QUEUE_SIZE: + self.main_mind_history.popleft() + self.main_mind_history.append(entry) + self.last_main_mind_timestamp = ts + self.refresh_mind_text() # 只有有新数据时才刷新 + except Exception: + pass + + def refresh_mind_text(self): + """刷新聊天框样式的历史想法展示""" + self.mind_text.config(state="normal") + self.mind_text.delete(1.0, tk.END) + for entry in self.main_mind_history: + ts = entry.get("timestamp", 0) + dt_str = datetime.fromtimestamp(ts).strftime("%Y-%m-%d %H:%M:%S") if ts else "" + main_mind = entry.get("main_mind", "") + mai_state = entry.get("mai_state", "") + subflow_count = entry.get("subflow_count", "") + msg = f"[{dt_str}] 状态:{mai_state} 子流:{subflow_count}\n{main_mind}\n\n" + self.mind_text.insert(tk.END, msg) + self.mind_text.see(tk.END) + self.mind_text.config(state="disabled") + + def load_and_update_history(self): + """从 history log 文件加载数据并更新历史记录""" + if not os.path.exists(LOG_FILE_PATH): + self.set_status(f"Error: Log file not found at {LOG_FILE_PATH}", "red") + # 如果文件不存在，不清空现有数据，以便显示最后一次成功读取的状态 + return + + # *** Reset display names each time we reload *** + new_stream_history = {} + new_stream_display_names = {} + new_probability_history = {} # <--- 重置概率历史 + # --- 新增：重置其他子流状态 --- (如果需要的话，但通常覆盖即可) + # self.stream_sub_minds = {} + # self.stream_chat_states = {} + # ... 等等 ... + + read_count = 0 + error_count = 0 + # *** Calculate the timestamp threshold for the last 30 minutes *** + current_time = time.time() + time_threshold = current_time - (15 * 60) # 30 minutes in seconds + + try: + with open(LOG_FILE_PATH, "r", encoding="utf-8") as f: + for line in f: + read_count += 1 + try: + log_entry = json.loads(line.strip()) + timestamp = log_entry.get("timestamp") # 获取顶层时间戳 + + # *** 时间过滤 *** + if timestamp is None: + error_count += 1 + continue # 跳过没有时间戳的行 + try: + entry_timestamp = float(timestamp) + if entry_timestamp < time_threshold: + continue # 跳过时间过早的条目 + except (ValueError, TypeError): + error_count += 1 + continue # 跳过时间戳格式错误的行 + + # --- 新增：更新顶层信息 (使用最后一个有效行的数据) --- + self.latest_main_mind.set( + log_entry.get("main_mind", self.latest_main_mind.get()) + ) # 保留旧值如果缺失 + self.latest_mai_state.set(log_entry.get("mai_state", self.latest_mai_state.get())) + self.latest_subflow_count.set(log_entry.get("subflow_count", self.latest_subflow_count.get())) + + # --- 修改开始：迭代 subflows --- + subflows = log_entry.get("subflows") + if not isinstance(subflows, list): # 检查 subflows 是否存在且为列表 + error_count += 1 + continue # 跳过没有 subflows 或格式无效的行 + + for subflow_entry in subflows: + stream_id = subflow_entry.get("stream_id") + interest_level = subflow_entry.get("interest_level") + # 获取 group_name，如果不存在则回退到 stream_id + group_name = subflow_entry.get("group_name", stream_id) + # reply_probability = subflow_entry.get("reply_probability") # 获取概率值 # <-- 注释掉旧行 + start_hfc_probability = subflow_entry.get( + "start_hfc_probability" + ) # <-- 添加新行，读取新字段 + + # *** 检查必要的字段 *** + # 注意：时间戳已在顶层检查过 + if stream_id is None or interest_level is None: + # 这里可以选择记录子流错误，但暂时跳过 + continue # 跳过无效的 subflow 条目 + + # 确保 interest_level 可以转换为浮点数 + try: + interest_level_float = float(interest_level) + except (ValueError, TypeError): + continue # 跳过 interest_level 无效的 subflow + + # 如果是第一次读到这个 stream_id，则创建 deque + if stream_id not in new_stream_history: + new_stream_history[stream_id] = deque(maxlen=MAX_HISTORY_POINTS) + new_probability_history[stream_id] = deque(maxlen=MAX_HISTORY_POINTS) # 创建概率 deque + # 检查是否已有颜色，没有则分配 + if stream_id not in self.stream_colors: + self.stream_colors[stream_id] = self.get_random_color() + + # *** 存储此 stream_id 最新的显示名称 *** + new_stream_display_names[stream_id] = group_name + + # --- 新增：存储其他子流信息 --- + self.stream_sub_minds[stream_id] = subflow_entry.get("sub_mind", "N/A") + self.stream_chat_states[stream_id] = subflow_entry.get("sub_chat_state", "N/A") + self.stream_threshold_status[stream_id] = subflow_entry.get("is_above_threshold", False) + self.stream_last_active[stream_id] = subflow_entry.get( + "chat_state_changed_time" + ) # 存储原始时间戳 + + # 添加数据点 (使用顶层时间戳) + new_stream_history[stream_id].append((entry_timestamp, interest_level_float)) + + # 添加概率数据点 (如果存在且有效) + # if reply_probability is not None: # <-- 注释掉旧判断 + if start_hfc_probability is not None: # <-- 修改判断条件 + try: + # 尝试将概率转换为浮点数 + # probability_float = float(reply_probability) # <-- 注释掉旧转换 + probability_float = float(start_hfc_probability) # <-- 使用新变量 + new_probability_history[stream_id].append((entry_timestamp, probability_float)) + except (TypeError, ValueError): + # 如果概率值无效，可以跳过或记录一个默认值，这里跳过 + pass + # --- 修改结束 --- + + except json.JSONDecodeError: + error_count += 1 + # logger.warning(f"Skipping invalid JSON line: {line.strip()}") + continue # 跳过无法解析的行 + # except (TypeError, ValueError) as e: # 这个外层 catch 可能不再需要，因为类型错误在内部处理了 + # error_count += 1 + # # logger.warning(f"Skipping line due to data type error ({e}): {line.strip()}") + # continue # 跳过数据类型错误的行 + + # 读取完成后，用新数据替换旧数据 + self.stream_history = new_stream_history + self.stream_display_names = new_stream_display_names # *** Update display names *** + self.probability_history = new_probability_history # <--- 更新概率历史 + # 清理不再存在的 stream_id 的附加信息 (可选，但保持一致性) + streams_to_remove = set(self.stream_sub_minds.keys()) - set(new_stream_history.keys()) + for sid in streams_to_remove: + self.stream_sub_minds.pop(sid, None) + self.stream_chat_states.pop(sid, None) + self.stream_threshold_status.pop(sid, None) + self.stream_last_active.pop(sid, None) + self.stream_last_interaction.pop(sid, None) + # 颜色和显示名称也应该清理，但当前逻辑是保留旧颜色 + # self.stream_colors.pop(sid, None) + status_msg = f"Data loaded at {datetime.now().strftime('%H:%M:%S')}. Lines read: {read_count}." + if error_count > 0: + status_msg += f" Skipped {error_count} invalid lines." + self.set_status(status_msg, "orange") + else: + self.set_status(status_msg, "green") + + except IOError as e: + self.set_status(f"Error reading file {LOG_FILE_PATH}: {e}", "red") + except Exception as e: + self.set_status(f"An unexpected error occurred during loading: {e}", "red") + + # --- 更新 Combobox --- + self.update_stream_selector() + + def update_stream_selector(self): + """更新单个流选项卡中的 Combobox 列表""" + # 创建 (display_name, stream_id) 对的列表，按 display_name 排序 + available_streams = sorted( + [ + (name, sid) + for sid, name in self.stream_display_names.items() + if sid in self.stream_history and self.stream_history[sid] + ], + key=lambda item: item[0], # 按显示名称排序 + ) + + # 更新 Combobox 的值 (仅显示 display_name) + self.stream_selector["values"] = [name for name, sid in available_streams] + + # 检查当前选中的 stream_id 是否仍然有效 + current_selection_name = self.selected_stream_id.get() + current_selection_valid = any(name == current_selection_name for name, sid in available_streams) + + if not current_selection_valid and available_streams: + # 如果当前选择无效，并且有可选流，则默认选中第一个 + self.selected_stream_id.set(available_streams[0][0]) + # 手动触发一次更新，因为 set 不会触发 <> + self.update_single_stream_plot() + elif not available_streams: + # 如果没有可选流，清空选择 + self.selected_stream_id.set("") + self.update_single_stream_plot() # 清空图表 + + def update_all_streams_plot(self): + """更新第一个选项卡的 Matplotlib 图表 (显示所有流)""" + self.ax.clear() # 清除旧图 + # *** 设置中文标题和标签 *** + self.ax.set_title("兴趣度随时间变化图 (所有活跃流)") + self.ax.set_xlabel("时间") + self.ax.set_ylabel("兴趣度") + self.ax.xaxis.set_major_formatter(mdates.DateFormatter("%H:%M:%S")) + self.ax.grid(True) + self.ax.set_ylim(0, 10) # 固定 Y 轴范围 0-10 + + # 只绘制最新的 N 个 stream (按最后记录的兴趣度排序) + # 注意：现在是基于文件读取的快照排序，可能不是实时最新 + active_streams = sorted( + self.stream_history.items(), + key=lambda item: item[1][-1][1] if item[1] else 0, # 按最后兴趣度排序 + reverse=True, + )[:MAX_STREAMS_TO_DISPLAY] + + all_times = [] # 用于确定 X 轴范围 + + for stream_id, history in active_streams: + if not history: + continue + + timestamps, interests = zip(*history) + # 将 time.time() 时间戳转换为 matplotlib 可识别的日期格式 + try: + mpl_dates = [datetime.fromtimestamp(ts) for ts in timestamps] + all_times.extend(mpl_dates) # 收集所有时间点 + + # *** Use display name for label *** + display_label = self.stream_display_names.get(stream_id, stream_id) + + self.ax.plot( + mpl_dates, + interests, + label=display_label, # *** Use display_label *** + color=self.stream_colors.get(stream_id, "grey"), + marker=".", + markersize=3, + linestyle="-", + linewidth=1, + ) + except ValueError as e: + print(f"Skipping plot for {stream_id} due to invalid timestamp: {e}") + continue + + if all_times: + # 根据数据动态调整 X 轴范围，留一点边距 + min_time = min(all_times) + max_time = max(all_times) + # delta = max_time - min_time + # self.ax.set_xlim(min_time - delta * 0.05, max_time + delta * 0.05) + self.ax.set_xlim(min_time, max_time) + + # 自动格式化X轴标签 + self.fig.autofmt_xdate() + else: + # 如果没有数据，设置一个默认的时间范围，例如最近一小时 + now = datetime.now() + one_hour_ago = now - timedelta(hours=1) + self.ax.set_xlim(one_hour_ago, now) + + # 添加图例 + if active_streams: + # 调整图例位置和大小 + # 字体已通过全局 matplotlib.rcParams 设置 + self.ax.legend(loc="upper left", bbox_to_anchor=(1.02, 1), borderaxespad=0.0, fontsize="x-small") + # 调整布局，确保图例不被裁剪 + self.fig.tight_layout(rect=[0, 0, 0.85, 1]) # 右侧留出空间给图例 + + self.canvas.draw() # 重绘画布 + + def update_single_stream_plot(self): + """更新第二个选项卡的 Matplotlib 图表 (显示单个选定的流)""" + self.ax_single_interest.clear() + self.ax_single_probability.clear() + + # 设置子图标题和标签 + self.ax_single_interest.set_title("兴趣度") + self.ax_single_interest.set_ylim(0, 10) # 固定 Y 轴范围 0-10 + + # self.ax_single_probability.set_title("回复评估概率") # <-- 注释掉旧标题 + self.ax_single_probability.set_title("HFC 启动概率") # <-- 修改标题 + self.ax_single_probability.set_xlabel("时间") + # self.ax_single_probability.set_ylabel("概率") # <-- 注释掉旧标签 + self.ax_single_probability.set_ylabel("HFC 概率") # <-- 修改 Y 轴标签 + self.ax_single_probability.grid(True) + self.ax_single_probability.set_ylim(0, 1.05) # 固定 Y 轴范围 0-1 + self.ax_single_probability.xaxis.set_major_formatter(mdates.DateFormatter("%H:%M:%S")) + + selected_name = self.selected_stream_id.get() + selected_sid = None + + # --- 新增：根据选中的名称找到 stream_id --- + if selected_name: + for sid, name in self.stream_display_names.items(): + if name == selected_name: + selected_sid = sid + break + + all_times = [] # 用于确定 X 轴范围 + + # --- 新增：绘制兴趣度图 --- + if selected_sid and selected_sid in self.stream_history and self.stream_history[selected_sid]: + history = self.stream_history[selected_sid] + timestamps, interests = zip(*history) + try: + mpl_dates = [datetime.fromtimestamp(ts) for ts in timestamps] + all_times.extend(mpl_dates) + self.ax_single_interest.plot( + mpl_dates, + interests, + color=self.stream_colors.get(selected_sid, "blue"), + marker=".", + markersize=3, + linestyle="-", + linewidth=1, + ) + except ValueError as e: + print(f"Skipping interest plot for {selected_sid} due to invalid timestamp: {e}") + + # --- 新增：绘制概率图 --- + if selected_sid and selected_sid in self.probability_history and self.probability_history[selected_sid]: + prob_history = self.probability_history[selected_sid] + prob_timestamps, probabilities = zip(*prob_history) + try: + prob_mpl_dates = [datetime.fromtimestamp(ts) for ts in prob_timestamps] + # 注意：概率图的时间点可能与兴趣度不同，也需要加入 all_times + all_times.extend(prob_mpl_dates) + self.ax_single_probability.plot( + prob_mpl_dates, + probabilities, + color=self.stream_colors.get(selected_sid, "green"), # 可以用不同颜色 + marker=".", + markersize=3, + linestyle="-", + linewidth=1, + ) + except ValueError as e: + print(f"Skipping probability plot for {selected_sid} due to invalid timestamp: {e}") + + # --- 新增：调整 X 轴范围和格式 --- + if all_times: + min_time = min(all_times) + max_time = max(all_times) + # 设置共享的 X 轴范围 + self.ax_single_interest.set_xlim(min_time, max_time) + # self.ax_single_probability.set_xlim(min_time, max_time) # sharex 会自动同步 + # 自动格式化X轴标签 (应用到共享轴的最后一个子图上通常即可) + self.fig_single.autofmt_xdate() + else: + # 如果没有数据，设置一个默认的时间范围 + now = datetime.now() + one_hour_ago = now - timedelta(hours=1) + self.ax_single_interest.set_xlim(one_hour_ago, now) + # self.ax_single_probability.set_xlim(one_hour_ago, now) # sharex 会自动同步 + + # --- 新增：更新单个流的详细信息标签 --- + self.update_single_stream_details(selected_sid) + + # --- 新增：重新绘制画布 --- + self.canvas_single.draw() + + def format_timestamp(self, ts): + """辅助函数：格式化时间戳，处理 None 或无效值""" + if ts is None: + return "N/A" + try: + # 假设 ts 是 float 类型的时间戳 + dt_object = datetime.fromtimestamp(float(ts)) + return dt_object.strftime("%Y-%m-%d %H:%M:%S") + except (ValueError, TypeError): + return "Invalid Time" + + def update_single_stream_details(self, stream_id): + """更新单个流详情区域的标签内容""" + if stream_id: + sub_mind = self.stream_sub_minds.get(stream_id, "N/A") + chat_state = self.stream_chat_states.get(stream_id, "N/A") + threshold = self.stream_threshold_status.get(stream_id, False) + last_active_ts = self.stream_last_active.get(stream_id) + last_interaction_ts = self.stream_last_interaction.get(stream_id) + + self.single_stream_sub_mind.set(f"想法: {sub_mind}") + self.single_stream_chat_state.set(f"状态: {chat_state}") + self.single_stream_threshold.set(f"阈值以上: {'是' if threshold else '否'}") + self.single_stream_last_active.set(f"最后活跃: {self.format_timestamp(last_active_ts)}") + self.single_stream_last_interaction.set(f"最后交互: {self.format_timestamp(last_interaction_ts)}") + else: + # 如果没有选择流，则清空详情 + self.single_stream_sub_mind.set("想法: N/A") + self.single_stream_chat_state.set("状态: N/A") + self.single_stream_threshold.set("阈值: N/A") + self.single_stream_last_active.set("活跃: N/A") + self.single_stream_last_interaction.set("交互: N/A") + + def update_display(self): + """主更新循环""" + try: + # --- 新增：首次加载历史想法 --- + if not hasattr(self, "_main_mind_loaded"): + self.load_main_mind_history() + self._main_mind_loaded = True + else: + self.update_main_mind_history() # 只有有新main_mind数据时才刷新界面 + # *** 修改：分别调用两个图表的更新方法 *** + self.load_and_update_history() # 从文件加载数据并更新内部状态 + self.update_all_streams_plot() # 更新所有流的图表 + self.update_single_stream_plot() # 更新单个流的图表 + except Exception as e: + # 提供更详细的错误信息 + import traceback + + error_msg = f"Error during update: {e}\n{traceback.format_exc()}" + self.set_status(error_msg, "red") + print(error_msg) # 打印详细错误到控制台 + + # 安排下一次刷新 + self.root.after(REFRESH_INTERVAL_MS, self.update_display) + + def set_status(self, message: str, color: str = "grey"): + """更新状态栏标签""" + # 限制状态栏消息长度 + max_len = 150 + display_message = (message[:max_len] + "...") if len(message) > max_len else message + self.status_label.config(text=display_message, fg=color) + + +if __name__ == "__main__": + # 导入 timedelta 用于默认时间范围 + from datetime import timedelta + + root = tk.Tk() + app = InterestMonitorApp(root) + root.mainloop() diff --git a/scripts/raw_data_preprocessor.py b/scripts/raw_data_preprocessor.py new file mode 100644 index 000000000..2fc30352e --- /dev/null +++ b/scripts/raw_data_preprocessor.py @@ -0,0 +1,92 @@ +import json +import os +from pathlib import Path +import sys # 新增系统模块导入 + +sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), ".."))) +from src.common.logger import get_module_logger + +logger = get_module_logger("LPMM数据库-原始数据处理") + +# 添加项目根目录到 sys.path + + +def check_and_create_dirs(): + """检查并创建必要的目录""" + required_dirs = ["data/lpmm_raw_data", "data/imported_lpmm_data"] + + for dir_path in required_dirs: + if not os.path.exists(dir_path): + os.makedirs(dir_path) + logger.info(f"已创建目录: {dir_path}") + + +def process_text_file(file_path): + """处理单个文本文件，返回段落列表""" + with open(file_path, "r", encoding="utf-8") as f: + raw = f.read() + + paragraphs = [] + paragraph = "" + for line in raw.split("\n"): + if line.strip() == "": + if paragraph != "": + paragraphs.append(paragraph.strip()) + paragraph = "" + else: + paragraph += line + "\n" + + if paragraph != "": + paragraphs.append(paragraph.strip()) + + return paragraphs + + +def main(): + # 新增用户确认提示 + print("=== 重要操作确认 ===") + print("如果你并非第一次导入知识") + print("请先删除data/import.json文件，备份data/openie.json文件") + print("在进行知识库导入之前") + print("请修改config/lpmm_config.toml中的配置项") + confirm = input("确认继续执行？(y/n): ").strip().lower() + if confirm != "y": + logger.error("操作已取消") + sys.exit(1) + print("\n" + "=" * 40 + "\n") + + # 检查并创建必要的目录 + check_and_create_dirs() + + # 检查输出文件是否存在 + if os.path.exists("data/import.json"): + logger.error("错误: data/import.json 已存在，请先处理或删除该文件") + sys.exit(1) + + if os.path.exists("data/openie.json"): + logger.error("错误: data/openie.json 已存在，请先处理或删除该文件") + sys.exit(1) + + # 获取所有原始文本文件 + raw_files = list(Path("data/lpmm_raw_data").glob("*.txt")) + if not raw_files: + logger.warning("警告: data/lpmm_raw_data 中没有找到任何 .txt 文件") + sys.exit(1) + + # 处理所有文件 + all_paragraphs = [] + for file in raw_files: + logger.info(f"正在处理文件: {file.name}") + paragraphs = process_text_file(file) + all_paragraphs.extend(paragraphs) + + # 保存合并后的结果 + output_path = "data/import.json" + with open(output_path, "w", encoding="utf-8") as f: + json.dump(all_paragraphs, f, ensure_ascii=False, indent=4) + + logger.info(f"处理完成，结果已保存到: {output_path}") + + +if __name__ == "__main__": + main() diff --git a/scripts/run.sh b/scripts/run.sh index b7ecbc849..9fd3127f6 100644 --- a/scripts/run.sh +++ b/scripts/run.sh @@ -4,7 +4,7 @@ # 适用于Arch/Ubuntu 24.10/Debian 12/CentOS 9 # 请小心使用任何一键脚本！ -INSTALLER_VERSION="0.0.3-refactor" +INSTALLER_VERSION="0.0.4-refactor" LANG=C.UTF-8 # 如无法访问GitHub请修改此处镜像地址 @@ -19,10 +19,10 @@ RESET="\e[0m" declare -A REQUIRED_PACKAGES=( ["common"]="git sudo python3 curl gnupg" - ["debian"]="python3-venv python3-pip" - ["ubuntu"]="python3-venv python3-pip" - ["centos"]="python3-pip" - ["arch"]="python-virtualenv python-pip" + ["debian"]="python3-venv python3-pip build-essential" + ["ubuntu"]="python3-venv python3-pip build-essential" + ["centos"]="epel-release python3-pip python3-devel gcc gcc-c++ make" + ["arch"]="python-virtualenv python-pip base-devel" ) # 默认项目目录 diff --git a/src/MaiBot0.6roadmap.md b/src/MaiBot0.6roadmap.md new file mode 100644 index 000000000..54774197e --- /dev/null +++ b/src/MaiBot0.6roadmap.md @@ -0,0 +1,16 @@ +MaiCore/MaiBot 0.6路线图 draft + +0.6.3：解决0.6.x版本核心问题，改进功能 +主要功能加入 +LPMM全面替代旧知识库 +采用新的HFC回复模式，取代旧心流 +合并推理模式和心流模式，根据麦麦自己决策回复模式 +提供新的表情包系统 + +0.6.4：提升用户体验，交互优化 +加入webui +提供麦麦 API +修复prompt建构的各种问题 +修复各种bug +调整代码文件结构，重构部分落后设计 + diff --git a/src/api/__init__.py b/src/api/__init__.py new file mode 100644 index 000000000..f5bc08a6e --- /dev/null +++ b/src/api/__init__.py @@ -0,0 +1,8 @@ +from fastapi import FastAPI +from strawberry.fastapi import GraphQLRouter + +app = FastAPI() + +graphql_router = GraphQLRouter(schema=None, path="/") # Replace `None` with your actual schema + +app.include_router(graphql_router, prefix="/graphql", tags=["GraphQL"]) diff --git a/src/api/config_api.py b/src/api/config_api.py new file mode 100644 index 000000000..025888d82 --- /dev/null +++ b/src/api/config_api.py @@ -0,0 +1,155 @@ +from typing import Dict, List, Optional +import strawberry + +# from packaging.version import Version, InvalidVersion +# from packaging.specifiers import SpecifierSet, InvalidSpecifier +# from ..config.config import global_config +# import os +from packaging.version import Version + + +@strawberry.type +class BotConfig: + """机器人配置类""" + + INNER_VERSION: Version + MAI_VERSION: str # 硬编码的版本信息 + + # bot + BOT_QQ: Optional[int] + BOT_NICKNAME: Optional[str] + BOT_ALIAS_NAMES: List[str] # 别名，可以通过这个叫它 + + # group + talk_allowed_groups: set + talk_frequency_down_groups: set + ban_user_id: set + + # personality + personality_core: str # 建议20字以内，谁再写3000字小作文敲谁脑袋 + personality_sides: List[str] + # identity + identity_detail: List[str] + height: int # 身高 单位厘米 + weight: int # 体重 单位千克 + age: int # 年龄 单位岁 + gender: str # 性别 + appearance: str # 外貌特征 + + # schedule + ENABLE_SCHEDULE_GEN: bool # 是否启用日程生成 + PROMPT_SCHEDULE_GEN: str + SCHEDULE_DOING_UPDATE_INTERVAL: int # 日程表更新间隔 单位秒 + SCHEDULE_TEMPERATURE: float # 日程表温度，建议0.5-1.0 + TIME_ZONE: str # 时区 + + # message + MAX_CONTEXT_SIZE: int # 上下文最大消息数 + emoji_chance: float # 发送表情包的基础概率 + thinking_timeout: int # 思考时间 + model_max_output_length: int # 最大回复长度 + message_buffer: bool # 消息缓冲器 + + ban_words: set + ban_msgs_regex: set + # heartflow + # enable_heartflow: bool = False # 是否启用心流 + sub_heart_flow_update_interval: int # 子心流更新频率，间隔 单位秒 + sub_heart_flow_freeze_time: int # 子心流冻结时间，超过这个时间没有回复，子心流会冻结，间隔 单位秒 + sub_heart_flow_stop_time: int # 子心流停止时间，超过这个时间没有回复，子心流会停止，间隔 单位秒 + heart_flow_update_interval: int # 心流更新频率，间隔 单位秒 + observation_context_size: int # 心流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 # 不能大于observation_context_size,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 # 最多压缩份数，超过该数值的压缩上下文会被删除 + + # willing + willing_mode: str # 意愿模式 + response_willing_amplifier: float # 回复意愿放大系数 + response_interested_rate_amplifier: float # 回复兴趣度放大系数 + down_frequency_rate: float # 降低回复频率的群组回复意愿降低系数 + emoji_response_penalty: float # 表情包回复惩罚 + mentioned_bot_inevitable_reply: bool # 提及 bot 必然回复 + at_bot_inevitable_reply: bool # @bot 必然回复 + + # response + response_mode: str # 回复策略 + MODEL_R1_PROBABILITY: float # R1模型概率 + MODEL_V3_PROBABILITY: float # V3模型概率 + # MODEL_R1_DISTILL_PROBABILITY: float # R1蒸馏模型概率 + + # emoji + max_emoji_num: int # 表情包最大数量 + max_reach_deletion: bool # 开启则在达到最大数量时删除表情包，关闭则不会继续收集表情包 + EMOJI_CHECK_INTERVAL: int # 表情包检查间隔（分钟） + EMOJI_REGISTER_INTERVAL: int # 表情包注册间隔（分钟） + EMOJI_SAVE: bool # 偷表情包 + EMOJI_CHECK: bool # 是否开启过滤 + EMOJI_CHECK_PROMPT: str # 表情包过滤要求 + + # memory + build_memory_interval: int # 记忆构建间隔（秒） + memory_build_distribution: list # 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 + build_memory_sample_num: int # 记忆构建采样数量 + build_memory_sample_length: int # 记忆构建采样长度 + memory_compress_rate: float # 记忆压缩率 + + forget_memory_interval: int # 记忆遗忘间隔（秒） + memory_forget_time: int # 记忆遗忘时间（小时） + memory_forget_percentage: float # 记忆遗忘比例 + + memory_ban_words: list # 添加新的配置项默认值 + + # mood + mood_update_interval: float # 情绪更新间隔 单位秒 + mood_decay_rate: float # 情绪衰减率 + mood_intensity_factor: float # 情绪强度因子 + + # keywords + keywords_reaction_rules: list # 关键词回复规则 + + # chinese_typo + chinese_typo_enable: bool # 是否启用中文错别字生成器 + chinese_typo_error_rate: float # 单字替换概率 + chinese_typo_min_freq: int # 最小字频阈值 + chinese_typo_tone_error_rate: float # 声调错误概率 + chinese_typo_word_replace_rate: float # 整词替换概率 + + # response_splitter + enable_response_splitter: bool # 是否启用回复分割器 + response_max_length: int # 回复允许的最大长度 + response_max_sentence_num: int # 回复允许的最大句子数 + + # remote + remote_enable: bool # 是否启用远程控制 + + # experimental + enable_friend_chat: bool # 是否启用好友聊天 + # enable_think_flow: bool # 是否启用思考流程 + enable_pfc_chatting: bool # 是否启用PFC聊天 + + # 模型配置 + llm_reasoning: Dict[str, str] # LLM推理 + # llm_reasoning_minor: Dict[str, str] + llm_normal: Dict[str, str] # LLM普通 + llm_topic_judge: Dict[str, str] # LLM话题判断 + llm_summary: Dict[str, str] # LLM话题总结 + llm_emotion_judge: Dict[str, str] # LLM情感判断 + embedding: Dict[str, str] # 嵌入 + vlm: Dict[str, str] # VLM + moderation: Dict[str, str] # 审核 + + # 实验性 + llm_observation: Dict[str, str] # LLM观察 + llm_sub_heartflow: Dict[str, str] # LLM子心流 + llm_heartflow: Dict[str, str] # LLM心流 + + api_urls: Dict[str, str] # API URLs + + +@strawberry.type +class EnvConfig: + pass + + @strawberry.field + def get_env(self) -> str: + return "env" diff --git a/src/api/graphql/__init__.py b/src/api/graphql/__init__.py new file mode 100644 index 000000000..b0efa7f9a --- /dev/null +++ b/src/api/graphql/__init__.py @@ -0,0 +1,22 @@ +import strawberry + +from fastapi import FastAPI +from strawberry.fastapi import GraphQLRouter + +from src.common.server import global_server + + +@strawberry.type +class Query: + @strawberry.field + def hello(self) -> str: + return "Hello World" + + +schema = strawberry.Schema(Query) + +graphql_app = GraphQLRouter(schema) + +fast_api_app: FastAPI = global_server.get_app() + +fast_api_app.include_router(graphql_app, prefix="/graphql") diff --git a/src/api/graphql/schema.py b/src/api/graphql/schema.py new file mode 100644 index 000000000..2ae28399f --- /dev/null +++ b/src/api/graphql/schema.py @@ -0,0 +1 @@ +pass diff --git a/src/common/log_decorators.py b/src/common/log_decorators.py new file mode 100644 index 000000000..9838717f9 --- /dev/null +++ b/src/common/log_decorators.py @@ -0,0 +1,107 @@ +import functools +import inspect +from typing import Callable, Any +from .logger import logger, add_custom_style_handler + + +def use_log_style( + style_name: str, + console_format: str, + console_level: str = "INFO", + # file_format: Optional[str] = None, # 暂未支持文件输出 + # file_level: str = "DEBUG", +) -> Callable: + """装饰器：为函数内的日志启用特定的自定义样式。 + + Args: + style_name (str): 自定义样式的唯一名称。 + console_format (str): 控制台输出的格式字符串。 + console_level (str, optional): 控制台日志级别. Defaults to "INFO". + # file_format (Optional[str], optional): 文件输出格式 (暂未支持). Defaults to None. + # file_level (str, optional): 文件日志级别 (暂未支持). Defaults to "DEBUG". + + Returns: + Callable: 返回装饰器本身。 + """ + + def decorator(func: Callable) -> Callable: + # 获取被装饰函数所在的模块名 + module = inspect.getmodule(func) + if module is None: + # 如果无法获取模块（例如，在交互式解释器中定义函数），则使用默认名称 + module_name = "unknown_module" + logger.warning(f"无法确定函数 {func.__name__} 的模块，将使用 '{module_name}'") + else: + module_name = module.__name__ + + # 在函数首次被调用（或模块加载时）确保自定义处理器已添加 + # 注意：这会在模块加载时执行，而不是每次函数调用时 + # print(f"Setting up custom style '{style_name}' for module '{module_name}' in decorator definition") + add_custom_style_handler( + module_name=module_name, + style_name=style_name, + console_format=console_format, + console_level=console_level, + # file_format=file_format, + # file_level=file_level, + ) + + @functools.wraps(func) + def wrapper(*args: Any, **kwargs: Any) -> Any: + # 创建绑定了模块名和自定义样式标记的 logger 实例 + custom_logger = logger.bind(module=module_name, custom_style=style_name) + # print(f"Executing {func.__name__} with custom logger for style '{style_name}'") + # 将自定义 logger 作为第一个参数传递给原函数 + # 注意：这要求被装饰的函数第一个参数用于接收 logger + try: + return func(custom_logger, *args, **kwargs) + except TypeError as e: + # 捕获可能的类型错误，比如原函数不接受 logger 参数 + logger.error( + f"调用 {func.__name__} 时出错：请确保该函数接受一个 logger 实例作为其第一个参数。错误：{e}" + ) + # 可以选择重新抛出异常或返回特定值 + raise e + + return wrapper + + return decorator + + +# --- 示例用法 (可以在其他模块中这样使用) --- + +# # 假设这是你的模块 my_module.py +# from src.common.log_decorators import use_log_style +# from src.common.logger import get_module_logger, LoguruLogger + +# # 获取模块的标准 logger +# standard_logger = get_module_logger(__name__) + +# # 定义一个自定义样式 +# MY_SPECIAL_STYLE = "special" +# MY_SPECIAL_FORMAT = " SPECIAL [{time:HH:mm:ss}] | {message}" + +# @use_log_style(style_name=MY_SPECIAL_STYLE, console_format=MY_SPECIAL_FORMAT) +# def my_function_with_special_logs(custom_logger: LoguruLogger, x: int, y: int): +# standard_logger.info("这是一条使用标准格式的日志") +# custom_logger.info(f"开始执行特殊操作，参数: x={x}, y={y}") +# result = x + y +# custom_logger.success(f"特殊操作完成，结果: {result}") +# standard_logger.info("标准格式日志：函数即将结束") +# return result + +# @use_log_style(style_name="another_style", console_format="任务: {message}") +# def another_task(task_logger: LoguruLogger, task_name: str): +# standard_logger.debug("准备执行另一个任务") +# task_logger.info(f"正在处理任务 '{task_name}'") +# # ... 执行任务 ... +# task_logger.warning("任务处理中遇到一个警告") +# standard_logger.info("另一个任务的标准日志") + +# if __name__ == "__main__": +# print("\n--- 调用 my_function_with_special_logs ---") +# my_function_with_special_logs(10, 5) +# print("\n--- 调用 another_task ---") +# another_task("数据清理") +# print("\n--- 单独使用标准 logger ---") +# standard_logger.info("这是一条完全独立的标准日志") diff --git a/src/common/logger.py b/src/common/logger.py index 7365e34a6..b5317d58b 100644 --- a/src/common/logger.py +++ b/src/common/logger.py @@ -1,11 +1,61 @@ from loguru import logger -from typing import Dict, Optional, Union, List +from typing import Dict, Optional, Union, List, Tuple import sys import os from types import ModuleType from pathlib import Path from dotenv import load_dotenv -# from ..plugins.chat.config import global_config + +""" +日志颜色说明: + +1. 主程序(Main) +浅黄色标题 | 浅黄色消息 + +2. 海马体(Memory) +浅黄色标题 | 浅黄色消息 + +3. PFC(前额叶皮质) +浅绿色标题 | 浅绿色消息 + +4. 心情(Mood) +品红色标题 | 品红色消息 + +5. 工具使用(Tool) +品红色标题 | 品红色消息 + +6. 关系(Relation) +浅品红色标题 | 浅品红色消息 + +7. 配置(Config) +浅青色标题 | 浅青色消息 + +8. 麦麦大脑袋 +浅绿色标题 | 浅绿色消息 + +9. 在干嘛 +青色标题 | 青色消息 + +10. 麦麦组织语言 +浅绿色标题 | 浅绿色消息 + +11. 见闻(Chat) +浅蓝色标题 | 绿色消息 + +12. 表情包(Emoji) +橙色标题 | 橙色消息 fg #FFD700 + +13. 子心流 + +13. 其他模块 +模块名标题 | 对应颜色消息 + + +注意: +1. 级别颜色遵循loguru默认配置 +2. 可通过环境变量修改日志级别 +""" + # 加载 .env 文件 env_path = Path(__file__).resolve().parent.parent.parent / ".env" @@ -26,12 +76,17 @@ LoguruLogger = logger.__class__ # 全局注册表：记录模块与处理器ID的映射 _handler_registry: Dict[str, List[int]] = {} +_custom_style_handlers: Dict[Tuple[str, str], List[int]] = {} # 记录自定义样式处理器ID # 获取日志存储根地址 current_file_path = Path(__file__).resolve() LOG_ROOT = "logs" -SIMPLE_OUTPUT = os.getenv("SIMPLE_OUTPUT", "false") +SIMPLE_OUTPUT = os.getenv("SIMPLE_OUTPUT", "false").strip().lower() +if SIMPLE_OUTPUT == "true": + SIMPLE_OUTPUT = True +else: + SIMPLE_OUTPUT = False print(f"SIMPLE_OUTPUT: {SIMPLE_OUTPUT}") if not SIMPLE_OUTPUT: @@ -42,12 +97,9 @@ if not SIMPLE_OUTPUT: "file_level": "DEBUG", # 格式配置 "console_format": ( - "{time:YYYY-MM-DD HH:mm:ss} | " - "{level: <8} | " - "{extra[module]: <12} | " - "{message}" + "{time:YYYY-MM-DD HH:mm:ss} | {extra[module]: <12} | {message}" ), - "file_format": ("{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | {message}"), + "file_format": "{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | {message}", "log_dir": LOG_ROOT, "rotation": "00:00", "retention": "3 days", @@ -59,8 +111,8 @@ else: "console_level": "INFO", "file_level": "DEBUG", # 格式配置 - "console_format": ("{time:MM-DD HH:mm} | {extra[module]} | {message}"), - "file_format": ("{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | {message}"), + "console_format": "{time:MM-DD HH:mm} | {extra[module]} | {message}", + "file_format": "{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | {message}", "log_dir": LOG_ROOT, "rotation": "00:00", "retention": "3 days", @@ -68,59 +120,73 @@ else: } -# 海马体日志样式配置 -MEMORY_STYLE_CONFIG = { +MAIN_STYLE_CONFIG = { "advanced": { "console_format": ( - "{time:YYYY-MM-DD HH:mm:ss} | " + "{time:YYYY-MM-DD HH:mm:ss} | " "{level: <8} | " - "{extra[module]: <12} | " - "海马体 | " + "主程序 | " "{message}" ), - "file_format": ("{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | 海马体 | {message}"), + "file_format": "{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | 主程序 | {message}", }, "simple": { "console_format": ( - "{time:MM-DD HH:mm} | 海马体 | {message}" + "{time:MM-DD HH:mm} | 主程序 | {message}" ), - "file_format": ("{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | 海马体 | {message}"), + "file_format": "{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | 主程序 | {message}", }, } +# pfc配置 +PFC_STYLE_CONFIG = { + "advanced": { + "console_format": ( + "{time:YYYY-MM-DD HH:mm:ss} | " + "{level: <8} | " + "PFC | " + "{message}" + ), + "file_format": "{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | PFC | {message}", + }, + "simple": { + "console_format": ( + "{time:MM-DD HH:mm} | PFC | {message}" + ), + "file_format": "{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | PFC | {message}", + }, +} # MOOD MOOD_STYLE_CONFIG = { "advanced": { "console_format": ( - "{time:YYYY-MM-DD HH:mm:ss} | " + "{time:YYYY-MM-DD HH:mm:ss} | " "{level: <8} | " - "{extra[module]: <12} | " - "心情 | " + "心情 | " "{message}" ), - "file_format": ("{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | 心情 | {message}"), + "file_format": "{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | 心情 | {message}", }, "simple": { - "console_format": ("{time:MM-DD HH:mm} | 心情 | {message}"), - "file_format": ("{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | 心情 | {message}"), + "console_format": "{time:MM-DD HH:mm} | 心情 | {message} ", + "file_format": "{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | 心情 | {message}", }, } # tool use TOOL_USE_STYLE_CONFIG = { "advanced": { "console_format": ( - "{time:YYYY-MM-DD HH:mm:ss} | " + "{time:YYYY-MM-DD HH:mm:ss} | " "{level: <8} | " - "{extra[module]: <12} | " "工具使用 | " "{message}" ), - "file_format": ("{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | 工具使用 | {message}"), + "file_format": "{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | 工具使用 | {message}", }, "simple": { - "console_format": ("{time:MM-DD HH:mm} | 工具使用 | {message}"), - "file_format": ("{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | 工具使用 | {message}"), + "console_format": "{time:MM-DD HH:mm} | 工具使用 | {message}", + "file_format": "{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | 工具使用 | {message}", }, } @@ -129,17 +195,16 @@ TOOL_USE_STYLE_CONFIG = { RELATION_STYLE_CONFIG = { "advanced": { "console_format": ( - "{time:YYYY-MM-DD HH:mm:ss} | " + "{time:YYYY-MM-DD HH:mm:ss} | " "{level: <8} | " - "{extra[module]: <12} | " "关系 | " "{message}" ), - "file_format": ("{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | 关系 | {message}"), + "file_format": "{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | 关系 | {message}", }, "simple": { - "console_format": ("{time:MM-DD HH:mm} | 关系 | {message}"), - "file_format": ("{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | 关系 | {message}"), + "console_format": "{time:MM-DD HH:mm} | 关系 | {message}", + "file_format": "{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | 关系 | {message}", }, } @@ -147,87 +212,82 @@ RELATION_STYLE_CONFIG = { CONFIG_STYLE_CONFIG = { "advanced": { "console_format": ( - "{time:YYYY-MM-DD HH:mm:ss} | " + "{time:YYYY-MM-DD HH:mm:ss} | " "{level: <8} | " - "{extra[module]: <12} | " "配置 | " "{message}" ), - "file_format": ("{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | 配置 | {message}"), + "file_format": "{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | 配置 | {message}", }, "simple": { - "console_format": ("{time:MM-DD HH:mm} | 配置 | {message}"), - "file_format": ("{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | 配置 | {message}"), + "console_format": "{time:MM-DD HH:mm} | 配置 | {message}", + "file_format": "{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | 配置 | {message}", }, } SENDER_STYLE_CONFIG = { "advanced": { "console_format": ( - "{time:YYYY-MM-DD HH:mm:ss} | " + "{time:YYYY-MM-DD HH:mm:ss} | " "{level: <8} | " - "{extra[module]: <12} | " "消息发送 | " "{message}" ), - "file_format": ("{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | 消息发送 | {message}"), + "file_format": "{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | 消息发送 | {message}", }, "simple": { - "console_format": ("{time:MM-DD HH:mm} | 消息发送 | {message}"), - "file_format": ("{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | 消息发送 | {message}"), + "console_format": "{time:MM-DD HH:mm} | 消息发送 | {message}", + "file_format": "{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | 消息发送 | {message}", }, } HEARTFLOW_STYLE_CONFIG = { "advanced": { "console_format": ( - "{time:YYYY-MM-DD HH:mm:ss} | " + "{time:YYYY-MM-DD HH:mm:ss} | " "{level: <8} | " - "{extra[module]: <12} | " "麦麦大脑袋 | " "{message}" ), - "file_format": ("{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | 麦麦大脑袋 | {message}"), + "file_format": "{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | 麦麦大脑袋 | {message}", }, "simple": { "console_format": ( - "{time:MM-DD HH:mm} | 麦麦大脑袋 | {message}" + "{time:MM-DD HH:mm} | 麦麦大脑袋 | {message}" ), # noqa: E501 - "file_format": ("{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | 麦麦大脑袋 | {message}"), + "file_format": "{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | 麦麦大脑袋 | {message}", }, } SCHEDULE_STYLE_CONFIG = { "advanced": { "console_format": ( - "{time:YYYY-MM-DD HH:mm:ss} | " + "{time:YYYY-MM-DD HH:mm:ss} | " "{level: <8} | " - "{extra[module]: <12} | " "在干嘛 | " "{message}" ), - "file_format": ("{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | 在干嘛 | {message}"), + "file_format": "{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | 在干嘛 | {message}", }, "simple": { - "console_format": ("{time:MM-DD HH:mm} | 在干嘛 | {message}"), - "file_format": ("{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | 在干嘛 | {message}"), + "console_format": "{time:MM-DD HH:mm} | 在干嘛 | {message}", + "file_format": "{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | 在干嘛 | {message}", }, } LLM_STYLE_CONFIG = { "advanced": { "console_format": ( - "{time:YYYY-MM-DD HH:mm:ss} | " + "{time:YYYY-MM-DD HH:mm:ss} | " "{level: <8} | " - "{extra[module]: <12} | " "麦麦组织语言 | " "{message}" ), - "file_format": ("{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | 麦麦组织语言 | {message}"), + "file_format": "{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | 麦麦组织语言 | {message}", }, "simple": { - "console_format": ("{time:MM-DD HH:mm} | 麦麦组织语言 | {message}"), - "file_format": ("{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | 麦麦组织语言 | {message}"), + "console_format": "{time:MM-DD HH:mm} | 麦麦组织语言 | {message}", + "file_format": "{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | 麦麦组织语言 | {message}", }, } @@ -236,17 +296,16 @@ LLM_STYLE_CONFIG = { TOPIC_STYLE_CONFIG = { "advanced": { "console_format": ( - "{time:YYYY-MM-DD HH:mm:ss} | " + "{time:YYYY-MM-DD HH:mm:ss} | " "{level: <8} | " - "{extra[module]: <12} | " "话题 | " "{message}" ), - "file_format": ("{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | 话题 | {message}"), + "file_format": "{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | 话题 | {message}", }, "simple": { - "console_format": ("{time:MM-DD HH:mm} | 主题 | {message}"), - "file_format": ("{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | 话题 | {message}"), + "console_format": "{time:MM-DD HH:mm} | 主题 | {message}", + "file_format": "{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | 话题 | {message}", }, } @@ -254,65 +313,520 @@ TOPIC_STYLE_CONFIG = { CHAT_STYLE_CONFIG = { "advanced": { "console_format": ( - "{time:YYYY-MM-DD HH:mm:ss} | " + "{time:YYYY-MM-DD HH:mm:ss} | " "{level: <8} | " - "{extra[module]: <12} | " - "见闻 | " + "见闻 | " "{message}" ), - "file_format": ("{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | 见闻 | {message}"), + "file_format": "{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | 见闻 | {message}", }, "simple": { + "console_format": ("{time:MM-DD HH:mm} | 见闻 | {message}"), # noqa: E501 + "file_format": "{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | 见闻 | {message}", + }, +} + +REMOTE_STYLE_CONFIG = { + "advanced": { "console_format": ( - "{time:MM-DD HH:mm} | 见闻 | {message}" - ), # noqa: E501 - "file_format": ("{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | 见闻 | {message}"), + "{time:YYYY-MM-DD HH:mm:ss} | " + "{level: <8} | " + "远程 | " + "{message}" + ), + "file_format": "{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | 远程 | {message}", + }, + "simple": { + "console_format": "{time:MM-DD HH:mm} | 远程| {message}", + "file_format": "{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | 远程 | {message}", }, } SUB_HEARTFLOW_STYLE_CONFIG = { "advanced": { "console_format": ( - "{time:YYYY-MM-DD HH:mm:ss} | " + "{time:YYYY-MM-DD HH:mm:ss} | " + "{level: <8} | " + "麦麦水群 | " + "{message}" + ), + "file_format": "{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | 麦麦小脑袋 | {message}", + }, + "simple": { + "console_format": ("{time:MM-DD HH:mm} | 麦麦水群 | {message}"), # noqa: E501 + "file_format": "{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | 麦麦水群 | {message}", + }, +} + +SUB_HEARTFLOW_MIND_STYLE_CONFIG = { + "advanced": { + "console_format": ( + "{time:YYYY-MM-DD HH:mm:ss} | " "{level: <8} | " - "{extra[module]: <12} | " "麦麦小脑袋 | " "{message}" ), - "file_format": ("{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | 麦麦小脑袋 | {message}"), + "file_format": "{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | 麦麦小脑袋 | {message}", + }, + "simple": { + "console_format": ("{time:MM-DD HH:mm} | 麦麦小脑袋 | {message}"), # noqa: E501 + "file_format": "{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | 麦麦小脑袋 | {message}", + }, +} + +SUBHEARTFLOW_MANAGER_STYLE_CONFIG = { + "advanced": { + "console_format": ( + "{time:YYYY-MM-DD HH:mm:ss} | " + "{level: <8} | " + "麦麦水群[管理] | " + "{message}" + ), + "file_format": "{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | 麦麦水群[管理] | {message}", + }, + "simple": { + "console_format": ("{time:MM-DD HH:mm} | 麦麦水群[管理] | {message}"), # noqa: E501 + "file_format": "{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | 麦麦水群[管理] | {message}", + }, +} + +BASE_TOOL_STYLE_CONFIG = { + "advanced": { + "console_format": ( + "{time:YYYY-MM-DD HH:mm:ss} | " + "{level: <8} | " + "工具使用 | " + "{message}" + ), + "file_format": "{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | 工具使用 | {message}", }, "simple": { "console_format": ( - "{time:MM-DD HH:mm} | 麦麦小脑袋 | {message}" + "{time:MM-DD HH:mm} | 工具使用 | {message}" ), # noqa: E501 - "file_format": ("{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | 麦麦小脑袋 | {message}"), + "file_format": "{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | 工具使用 | {message}", + }, +} + +CHAT_STREAM_STYLE_CONFIG = { + "advanced": { + "console_format": ( + "{time:YYYY-MM-DD HH:mm:ss} | " + "{level: <8} | " + "聊天流 | " + "{message}" + ), + "file_format": "{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | 聊天流 | {message}", + }, + "simple": { + "console_format": ( + "{time:MM-DD HH:mm} | 聊天流 | {message}" + ), + "file_format": "{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | 聊天流 | {message}", + }, +} + +CHAT_MESSAGE_STYLE_CONFIG = { + "advanced": { + "console_format": ( + "{time:YYYY-MM-DD HH:mm:ss} | " + "{level: <8} | " + "聊天消息 | " + "{message}" + ), + "file_format": "{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | 聊天消息 | {message}", + }, + "simple": { + "console_format": ( + "{time:MM-DD HH:mm} | 聊天消息 | {message}" + ), # noqa: E501 + "file_format": "{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | 聊天消息 | {message}", + }, +} + +PERSON_INFO_STYLE_CONFIG = { + "advanced": { + "console_format": ( + "{time:YYYY-MM-DD HH:mm:ss} | " + "{level: <8} | " + "人物信息 | " + "{message}" + ), + "file_format": "{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | 人物信息 | {message}", + }, + "simple": { + "console_format": ( + "{time:MM-DD HH:mm} | 人物信息 | {message}" + ), # noqa: E501 + "file_format": "{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | 人物信息 | {message}", + }, +} + +BACKGROUND_TASKS_STYLE_CONFIG = { + "advanced": { + "console_format": ( + "{time:YYYY-MM-DD HH:mm:ss} | " + "{level: <8} | " + "后台任务 | " + "{message}" + ), + "file_format": "{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | 后台任务 | {message}", + }, + "simple": { + "console_format": ( + "{time:MM-DD HH:mm} | 后台任务 | {message}" + ), # noqa: E501 + "file_format": "{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | 后台任务 | {message}", }, } WILLING_STYLE_CONFIG = { "advanced": { "console_format": ( - "{time:YYYY-MM-DD HH:mm:ss} | " + "{time:YYYY-MM-DD HH:mm:ss} | " "{level: <8} | " - "{extra[module]: <12} | " "意愿 | " "{message}" ), - "file_format": ("{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | 意愿 | {message}"), + "file_format": "{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | 意愿 | {message}", }, "simple": { - "console_format": ("{time:MM-DD HH:mm} | 意愿 | {message}"), # noqa: E501 - "file_format": ("{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | 意愿 | {message}"), + "console_format": "{time:MM-DD HH:mm} | 意愿 | {message} ", # noqa: E501 + "file_format": "{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | 意愿 | {message}", + }, +} + +PFC_ACTION_PLANNER_STYLE_CONFIG = { + "advanced": { + "console_format": ( + "{time:YYYY-MM-DD HH:mm:ss} | " + "{level: <8} | " + "PFC私聊规划 | " + "{message}" + ), + "file_format": "{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | PFC私聊规划 | {message}", + }, + "simple": { + "console_format": "{time:MM-DD HH:mm} | PFC私聊规划 | {message} ", # noqa: E501 + "file_format": "{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | PFC私聊规划 | {message}", + }, +} + +# EMOJI，橙色，全着色 +EMOJI_STYLE_CONFIG = { + "advanced": { + "console_format": ( + "{time:YYYY-MM-DD HH:mm:ss} | " + "{level: <8} | " + "表情包 | " + "{message}" + ), + "file_format": "{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | 表情包 | {message}", + }, + "simple": { + "console_format": "{time:MM-DD HH:mm} | 表情包 | {message} ", # noqa: E501 + "file_format": "{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | 表情包 | {message}", + }, +} + +MAI_STATE_CONFIG = { + "advanced": { + "console_format": ( + "{time:YYYY-MM-DD HH:mm:ss} | " + "{level: <8} | " + "麦麦状态 | " + "{message}" + ), + "file_format": "{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | 麦麦状态 | {message}", + }, + "simple": { + "console_format": "{time:MM-DD HH:mm} | 麦麦状态 | {message} ", # noqa: E501 + "file_format": "{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | 麦麦状态 | {message}", + }, +} + + +# 海马体日志样式配置 +MEMORY_STYLE_CONFIG = { + "advanced": { + "console_format": ( + "{time:YYYY-MM-DD HH:mm:ss} | " + "{level: <8} | " + "海马体 | " + "{message}" + ), + "file_format": "{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | 海马体 | {message}", + }, + "simple": { + "console_format": ( + "{time:MM-DD HH:mm} | 海马体 | {message}" + ), + "file_format": "{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | 海马体 | {message}", + }, +} + + +# LPMM配置 +LPMM_STYLE_CONFIG = { + "advanced": { + "console_format": ( + "{time:YYYY-MM-DD HH:mm:ss} | " + "{level: <8} | " + "LPMM | " + "{message}" + ), + "file_format": "{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | LPMM | {message}", + }, + "simple": { + "console_format": ( + "{time:MM-DD HH:mm} | LPMM | {message}" + ), + "file_format": "{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | LPMM | {message}", + }, +} + +OBSERVATION_STYLE_CONFIG = { + "advanced": { + "console_format": ( + "{time:YYYY-MM-DD HH:mm:ss} | " + "{level: <8} | " + "聊天观察 | " + "{message}" + ), + "file_format": "{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | 聊天观察 | {message}", + }, + "simple": { + "console_format": ( + "{time:MM-DD HH:mm} | 聊天观察 | {message}" + ), # noqa: E501 + "file_format": "{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | 聊天观察 | {message}", + }, +} + +CHAT_IMAGE_STYLE_CONFIG = { + "advanced": { + "console_format": ( + "{time:YYYY-MM-DD HH:mm:ss} | " + "{level: <8} | " + "聊天图片 | " + "{message}" + ), + "file_format": "{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | 聊天图片 | {message}", + }, + "simple": { + "console_format": ( + "{time:MM-DD HH:mm} | 聊天图片 | {message}" + ), # noqa: E501 + "file_format": "{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | 聊天图片 | {message}", + }, +} + +# HFC log +HFC_STYLE_CONFIG = { + "advanced": { + "console_format": ( + "{time:YYYY-MM-DD HH:mm:ss} | " + "{level: <8} | " + "专注聊天 | " + "{message}" + ), + "file_format": "{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | 专注聊天 | {message}", + }, + "simple": { + "console_format": ( + "{time:MM-DD HH:mm} | 专注聊天 | {message}" + ), + "file_format": "{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | 专注聊天 | {message}", }, } CONFIRM_STYLE_CONFIG = { - "console_format": ("{message}"), # noqa: E501 - "file_format": ("{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | EULA与PRIVACY确认 | {message}"), + "console_format": "{message}", # noqa: E501 + "file_format": "{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | EULA与PRIVACY确认 | {message}", } +# 天依蓝配置 +TIANYI_STYLE_CONFIG = { + "advanced": { + "console_format": ( + "{time:YYYY-MM-DD HH:mm:ss} | " + "{level: <8} | " + "天依 | " + "{message}" + ), + "file_format": "{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | 天依 | {message}", + }, + "simple": { + "console_format": ( + "{time:MM-DD HH:mm} | 天依 | {message}" + ), + "file_format": "{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | 天依 | {message}", + }, +} + +# 模型日志样式配置 +MODEL_UTILS_STYLE_CONFIG = { + "advanced": { + "console_format": ( + "{time:YYYY-MM-DD HH:mm:ss} | " + "{level: <8} | " + "模型 | " + "{message}" + ), + "file_format": "{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | 模型 | {message}", + }, + "simple": { + "console_format": "{time:MM-DD HH:mm} | 模型 | {message}", + "file_format": "{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | 模型 | {message}", + }, +} + +MESSAGE_BUFFER_STYLE_CONFIG = { + "advanced": { + "console_format": ( + "{time:YYYY-MM-DD HH:mm:ss} | " + "{level: <8} | " + "消息缓存 | " + "{message}" + ), + "file_format": "{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | 消息缓存 | {message}", + }, + "simple": { + "console_format": "{time:MM-DD HH:mm} | 消息缓存 | {message}", + "file_format": "{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | 消息缓存 | {message}", + }, +} + +PROMPT_STYLE_CONFIG = { + "advanced": { + "console_format": ( + "{time:YYYY-MM-DD HH:mm:ss} | " + "{level: <8} | " + "提示词构建 | " + "{message}" + ), + "file_format": "{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | 提示词构建 | {message}", + }, + "simple": { + "console_format": "{time:MM-DD HH:mm} | 提示词构建 | {message}", + "file_format": "{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | 提示词构建 | {message}", + }, +} + +CHANGE_MOOD_TOOL_STYLE_CONFIG = { + "advanced": { + "console_format": ( + "{time:YYYY-MM-DD HH:mm:ss} | " + "{level: <8} | " + "心情工具 | " + "{message}" + ), + "file_format": "{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | 心情工具 | {message}", + }, + "simple": { + "console_format": "{time:MM-DD HH:mm} | 心情工具 | {message}", + "file_format": "{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | 心情工具 | {message}", + }, +} + +CHANGE_RELATIONSHIP_TOOL_STYLE_CONFIG = { + "advanced": { + "console_format": ( + "{time:YYYY-MM-DD HH:mm:ss} | " + "{level: <8} | " + "关系工具 | " + "{message}" + ), + "file_format": "{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | 关系工具 | {message}", + }, + "simple": { + "console_format": "{time:MM-DD HH:mm} | 关系工具 | {message}", + "file_format": "{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | 关系工具 | {message}", + }, +} + +GET_KNOWLEDGE_TOOL_STYLE_CONFIG = { + "advanced": { + "console_format": ( + "{time:YYYY-MM-DD HH:mm:ss} | " + "{level: <8} | " + "获取知识 | " + "{message}" + ), + "file_format": "{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | 获取知识 | {message}", + }, + "simple": { + "console_format": "{time:MM-DD HH:mm} | 获取知识 | {message}", + "file_format": "{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | 获取知识 | {message}", + }, +} + +GET_TIME_DATE_TOOL_STYLE_CONFIG = { + "advanced": { + "console_format": ( + "{time:YYYY-MM-DD HH:mm:ss} | " + "{level: <8} | " + "获取时间日期 | " + "{message}" + ), + "file_format": "{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | 获取时间日期 | {message}", + }, + "simple": { + "console_format": "{time:MM-DD HH:mm} | 获取时间日期 | {message}", + "file_format": "{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | 获取时间日期 | {message}", + }, +} + +LPMM_GET_KNOWLEDGE_TOOL_STYLE_CONFIG = { + "advanced": { + "console_format": ( + "{time:YYYY-MM-DD HH:mm:ss} | " + "{level: <8} | " + "LPMM获取知识 | " + "{message}" + ), + "file_format": "{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | LPMM获取知识 | {message}", + }, + "simple": { + "console_format": "{time:MM-DD HH:mm} | LPMM获取知识 | {message}", + "file_format": "{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | LPMM获取知识 | {message}", + }, +} + +INIT_STYLE_CONFIG = { + "advanced": { + "console_format": ( + "{time:YYYY-MM-DD HH:mm:ss} | " + "{level: <8} | " + "初始化 | " + "{message}" + ), + "file_format": "{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | 初始化 | {message}", + }, + "simple": { + "console_format": "{time:MM-DD HH:mm} | 初始化 | {message}", + "file_format": "{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {extra[module]: <15} | 初始化 | {message}", + }, +} + + # 根据SIMPLE_OUTPUT选择配置 +MAIN_STYLE_CONFIG = MAIN_STYLE_CONFIG["simple"] if SIMPLE_OUTPUT else MAIN_STYLE_CONFIG["advanced"] +EMOJI_STYLE_CONFIG = EMOJI_STYLE_CONFIG["simple"] if SIMPLE_OUTPUT else EMOJI_STYLE_CONFIG["advanced"] +PFC_ACTION_PLANNER_STYLE_CONFIG = ( + PFC_ACTION_PLANNER_STYLE_CONFIG["simple"] if SIMPLE_OUTPUT else PFC_ACTION_PLANNER_STYLE_CONFIG["advanced"] +) +REMOTE_STYLE_CONFIG = REMOTE_STYLE_CONFIG["simple"] if SIMPLE_OUTPUT else REMOTE_STYLE_CONFIG["advanced"] +BASE_TOOL_STYLE_CONFIG = BASE_TOOL_STYLE_CONFIG["simple"] if SIMPLE_OUTPUT else BASE_TOOL_STYLE_CONFIG["advanced"] +PERSON_INFO_STYLE_CONFIG = PERSON_INFO_STYLE_CONFIG["simple"] if SIMPLE_OUTPUT else PERSON_INFO_STYLE_CONFIG["advanced"] +SUBHEARTFLOW_MANAGER_STYLE_CONFIG = ( + SUBHEARTFLOW_MANAGER_STYLE_CONFIG["simple"] if SIMPLE_OUTPUT else SUBHEARTFLOW_MANAGER_STYLE_CONFIG["advanced"] +) +BACKGROUND_TASKS_STYLE_CONFIG = ( + BACKGROUND_TASKS_STYLE_CONFIG["simple"] if SIMPLE_OUTPUT else BACKGROUND_TASKS_STYLE_CONFIG["advanced"] +) MEMORY_STYLE_CONFIG = MEMORY_STYLE_CONFIG["simple"] if SIMPLE_OUTPUT else MEMORY_STYLE_CONFIG["advanced"] +CHAT_STREAM_STYLE_CONFIG = CHAT_STREAM_STYLE_CONFIG["simple"] if SIMPLE_OUTPUT else CHAT_STREAM_STYLE_CONFIG["advanced"] TOPIC_STYLE_CONFIG = TOPIC_STYLE_CONFIG["simple"] if SIMPLE_OUTPUT else TOPIC_STYLE_CONFIG["advanced"] SENDER_STYLE_CONFIG = SENDER_STYLE_CONFIG["simple"] if SIMPLE_OUTPUT else SENDER_STYLE_CONFIG["advanced"] LLM_STYLE_CONFIG = LLM_STYLE_CONFIG["simple"] if SIMPLE_OUTPUT else LLM_STYLE_CONFIG["advanced"] @@ -324,9 +838,47 @@ HEARTFLOW_STYLE_CONFIG = HEARTFLOW_STYLE_CONFIG["simple"] if SIMPLE_OUTPUT else SUB_HEARTFLOW_STYLE_CONFIG = ( SUB_HEARTFLOW_STYLE_CONFIG["simple"] if SIMPLE_OUTPUT else SUB_HEARTFLOW_STYLE_CONFIG["advanced"] ) # noqa: E501 +SUB_HEARTFLOW_MIND_STYLE_CONFIG = ( + SUB_HEARTFLOW_MIND_STYLE_CONFIG["simple"] if SIMPLE_OUTPUT else SUB_HEARTFLOW_MIND_STYLE_CONFIG["advanced"] +) WILLING_STYLE_CONFIG = WILLING_STYLE_CONFIG["simple"] if SIMPLE_OUTPUT else WILLING_STYLE_CONFIG["advanced"] +MAI_STATE_CONFIG = MAI_STATE_CONFIG["simple"] if SIMPLE_OUTPUT else MAI_STATE_CONFIG["advanced"] CONFIG_STYLE_CONFIG = CONFIG_STYLE_CONFIG["simple"] if SIMPLE_OUTPUT else CONFIG_STYLE_CONFIG["advanced"] TOOL_USE_STYLE_CONFIG = TOOL_USE_STYLE_CONFIG["simple"] if SIMPLE_OUTPUT else TOOL_USE_STYLE_CONFIG["advanced"] +PFC_STYLE_CONFIG = PFC_STYLE_CONFIG["simple"] if SIMPLE_OUTPUT else PFC_STYLE_CONFIG["advanced"] +LPMM_STYLE_CONFIG = LPMM_STYLE_CONFIG["simple"] if SIMPLE_OUTPUT else LPMM_STYLE_CONFIG["advanced"] +HFC_STYLE_CONFIG = HFC_STYLE_CONFIG["simple"] if SIMPLE_OUTPUT else HFC_STYLE_CONFIG["advanced"] +TIANYI_STYLE_CONFIG = TIANYI_STYLE_CONFIG["simple"] if SIMPLE_OUTPUT else TIANYI_STYLE_CONFIG["advanced"] +MODEL_UTILS_STYLE_CONFIG = MODEL_UTILS_STYLE_CONFIG["simple"] if SIMPLE_OUTPUT else MODEL_UTILS_STYLE_CONFIG["advanced"] +PROMPT_STYLE_CONFIG = PROMPT_STYLE_CONFIG["simple"] if SIMPLE_OUTPUT else PROMPT_STYLE_CONFIG["advanced"] +CHANGE_MOOD_TOOL_STYLE_CONFIG = ( + CHANGE_MOOD_TOOL_STYLE_CONFIG["simple"] if SIMPLE_OUTPUT else CHANGE_MOOD_TOOL_STYLE_CONFIG["advanced"] +) +CHANGE_RELATIONSHIP_TOOL_STYLE_CONFIG = ( + CHANGE_RELATIONSHIP_TOOL_STYLE_CONFIG["simple"] + if SIMPLE_OUTPUT + else CHANGE_RELATIONSHIP_TOOL_STYLE_CONFIG["advanced"] +) +GET_KNOWLEDGE_TOOL_STYLE_CONFIG = ( + GET_KNOWLEDGE_TOOL_STYLE_CONFIG["simple"] if SIMPLE_OUTPUT else GET_KNOWLEDGE_TOOL_STYLE_CONFIG["advanced"] +) +GET_TIME_DATE_TOOL_STYLE_CONFIG = ( + GET_TIME_DATE_TOOL_STYLE_CONFIG["simple"] if SIMPLE_OUTPUT else GET_TIME_DATE_TOOL_STYLE_CONFIG["advanced"] +) +LPMM_GET_KNOWLEDGE_TOOL_STYLE_CONFIG = ( + LPMM_GET_KNOWLEDGE_TOOL_STYLE_CONFIG["simple"] + if SIMPLE_OUTPUT + else LPMM_GET_KNOWLEDGE_TOOL_STYLE_CONFIG["advanced"] +) +OBSERVATION_STYLE_CONFIG = OBSERVATION_STYLE_CONFIG["simple"] if SIMPLE_OUTPUT else OBSERVATION_STYLE_CONFIG["advanced"] +MESSAGE_BUFFER_STYLE_CONFIG = ( + MESSAGE_BUFFER_STYLE_CONFIG["simple"] if SIMPLE_OUTPUT else MESSAGE_BUFFER_STYLE_CONFIG["advanced"] +) +CHAT_MESSAGE_STYLE_CONFIG = ( + CHAT_MESSAGE_STYLE_CONFIG["simple"] if SIMPLE_OUTPUT else CHAT_MESSAGE_STYLE_CONFIG["advanced"] +) +CHAT_IMAGE_STYLE_CONFIG = CHAT_IMAGE_STYLE_CONFIG["simple"] if SIMPLE_OUTPUT else CHAT_IMAGE_STYLE_CONFIG["advanced"] +INIT_STYLE_CONFIG = INIT_STYLE_CONFIG["simple"] if SIMPLE_OUTPUT else INIT_STYLE_CONFIG["advanced"] def is_registered_module(record: dict) -> bool: @@ -391,7 +943,7 @@ def get_module_logger( sink=sys.stderr, level=os.getenv("CONSOLE_LOG_LEVEL", console_level or current_config["console_level"]), format=current_config["console_format"], - filter=lambda record: record["extra"].get("module") == module_name, + filter=lambda record: record["extra"].get("module") == module_name and "custom_style" not in record["extra"], enqueue=True, ) handler_ids.append(console_id) @@ -410,7 +962,7 @@ def get_module_logger( retention=current_config["retention"], compression=current_config["compression"], encoding="utf-8", - filter=lambda record: record["extra"].get("module") == module_name, + filter=lambda record: record["extra"].get("module") == module_name and "custom_style" not in record["extra"], enqueue=True, ) handler_ids.append(file_id) @@ -427,6 +979,87 @@ def get_module_logger( return logger.bind(module=module_name) +def add_custom_style_handler( + module_name: str, + style_name: str, + console_format: str, + console_level: str = "INFO", + # file_format: Optional[str] = None, # 暂时只支持控制台 + # file_level: str = "DEBUG", + # config: Optional[LogConfig] = None, # 暂时不使用全局配置 +) -> None: + """为指定模块和样式名添加自定义日志处理器（目前仅支持控制台）.""" + handler_key = (module_name, style_name) + + # 如果已存在该模块和样式的处理器，则不重复添加 + if handler_key in _custom_style_handlers: + # print(f"Custom handler for {handler_key} already exists.") + return + + handler_ids = [] + + # 添加自定义控制台处理器 + try: + custom_console_id = logger.add( + sink=sys.stderr, + level=os.getenv(f"{module_name.upper()}_{style_name.upper()}_CONSOLE_LEVEL", console_level), + format=console_format, + filter=lambda record: record["extra"].get("module") == module_name + and record["extra"].get("custom_style") == style_name, + enqueue=True, + ) + handler_ids.append(custom_console_id) + # print(f"Added custom console handler {custom_console_id} for {handler_key}") + except Exception as e: + logger.error(f"Failed to add custom console handler for {handler_key}: {e}") + # 如果添加失败，确保列表为空，避免记录不存在的ID + handler_ids = [] + + # # 文件处理器 (可选，按需启用) + # if file_format: + # current_config = config.config if config else DEFAULT_CONFIG + # log_dir = Path(current_config["log_dir"]) + # log_dir.mkdir(parents=True, exist_ok=True) + # # 可以考虑将自定义样式的日志写入单独文件或模块主文件 + # log_file = log_dir / module_name / f"{style_name}_{{time:YYYY-MM-DD}}.log" + # log_file.parent.mkdir(parents=True, exist_ok=True) + # try: + # custom_file_id = logger.add( + # sink=str(log_file), + # level=os.getenv(f"{module_name.upper()}_{style_name.upper()}_FILE_LEVEL", file_level), + # format=file_format, + # rotation=current_config["rotation"], + # retention=current_config["retention"], + # compression=current_config["compression"], + # encoding="utf-8", + # filter=lambda record: record["extra"].get("module") == module_name + # and record["extra"].get("custom_style") == style_name, + # enqueue=True, + # ) + # handler_ids.append(custom_file_id) + # except Exception as e: + # logger.error(f"Failed to add custom file handler for {handler_key}: {e}") + + # 更新自定义处理器注册表 + if handler_ids: + _custom_style_handlers[handler_key] = handler_ids + + +def remove_custom_style_handler(module_name: str, style_name: str) -> None: + """移除指定模块和样式名的自定义日志处理器.""" + handler_key = (module_name, style_name) + if handler_key in _custom_style_handlers: + for handler_id in _custom_style_handlers[handler_key]: + try: + logger.remove(handler_id) + # print(f"Removed custom handler {handler_id} for {handler_key}") + except ValueError: + # 可能已经被移除或不存在 + # print(f"Handler {handler_id} for {handler_key} already removed or invalid.") + pass + del _custom_style_handlers[handler_key] + + def remove_module_logger(module_name: str) -> None: """清理指定模块的日志处理器""" if module_name in _handler_registry: @@ -459,7 +1092,7 @@ other_log_dir.mkdir(parents=True, exist_ok=True) DEFAULT_FILE_HANDLER = logger.add( sink=str(other_log_dir / "{time:YYYY-MM-DD}.log"), level=os.getenv("DEFAULT_FILE_LOG_LEVEL", "DEBUG"), - format=("{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {name: <15} | {message}"), + format="{time:YYYY-MM-DD HH:mm:ss} | {level: <8} | {name: <15} | {message}", rotation=DEFAULT_CONFIG["rotation"], retention=DEFAULT_CONFIG["retention"], compression=DEFAULT_CONFIG["compression"], diff --git a/src/common/logger_manager.py b/src/common/logger_manager.py new file mode 100644 index 000000000..5c5538385 --- /dev/null +++ b/src/common/logger_manager.py @@ -0,0 +1,102 @@ +from src.common.logger import get_module_logger, LogConfig +from src.common.logger import ( + BACKGROUND_TASKS_STYLE_CONFIG, + MAIN_STYLE_CONFIG, + MEMORY_STYLE_CONFIG, + PFC_STYLE_CONFIG, + MOOD_STYLE_CONFIG, + TOOL_USE_STYLE_CONFIG, + RELATION_STYLE_CONFIG, + CONFIG_STYLE_CONFIG, + HEARTFLOW_STYLE_CONFIG, + SCHEDULE_STYLE_CONFIG, + LLM_STYLE_CONFIG, + CHAT_STYLE_CONFIG, + EMOJI_STYLE_CONFIG, + SUB_HEARTFLOW_STYLE_CONFIG, + SUB_HEARTFLOW_MIND_STYLE_CONFIG, + SUBHEARTFLOW_MANAGER_STYLE_CONFIG, + BASE_TOOL_STYLE_CONFIG, + CHAT_STREAM_STYLE_CONFIG, + PERSON_INFO_STYLE_CONFIG, + WILLING_STYLE_CONFIG, + PFC_ACTION_PLANNER_STYLE_CONFIG, + MAI_STATE_CONFIG, + LPMM_STYLE_CONFIG, + HFC_STYLE_CONFIG, + TIANYI_STYLE_CONFIG, + REMOTE_STYLE_CONFIG, + TOPIC_STYLE_CONFIG, + SENDER_STYLE_CONFIG, + CONFIRM_STYLE_CONFIG, + MODEL_UTILS_STYLE_CONFIG, + PROMPT_STYLE_CONFIG, + CHANGE_MOOD_TOOL_STYLE_CONFIG, + CHANGE_RELATIONSHIP_TOOL_STYLE_CONFIG, + GET_KNOWLEDGE_TOOL_STYLE_CONFIG, + GET_TIME_DATE_TOOL_STYLE_CONFIG, + LPMM_GET_KNOWLEDGE_TOOL_STYLE_CONFIG, + OBSERVATION_STYLE_CONFIG, + MESSAGE_BUFFER_STYLE_CONFIG, + CHAT_MESSAGE_STYLE_CONFIG, + CHAT_IMAGE_STYLE_CONFIG, + INIT_STYLE_CONFIG, +) + +# 可根据实际需要补充更多模块配置 +MODULE_LOGGER_CONFIGS = { + "background_tasks": BACKGROUND_TASKS_STYLE_CONFIG, # 后台任务 + "main": MAIN_STYLE_CONFIG, # 主程序 + "memory": MEMORY_STYLE_CONFIG, # 海马体 + "pfc": PFC_STYLE_CONFIG, # PFC + "mood": MOOD_STYLE_CONFIG, # 心情 + "tool_use": TOOL_USE_STYLE_CONFIG, # 工具使用 + "relation": RELATION_STYLE_CONFIG, # 关系 + "config": CONFIG_STYLE_CONFIG, # 配置 + "heartflow": HEARTFLOW_STYLE_CONFIG, # 麦麦大脑袋 + "schedule": SCHEDULE_STYLE_CONFIG, # 在干嘛 + "llm": LLM_STYLE_CONFIG, # 麦麦组织语言 + "chat": CHAT_STYLE_CONFIG, # 见闻 + "emoji": EMOJI_STYLE_CONFIG, # 表情包 + "sub_heartflow": SUB_HEARTFLOW_STYLE_CONFIG, # 麦麦水群 + "sub_heartflow_mind": SUB_HEARTFLOW_MIND_STYLE_CONFIG, # 麦麦小脑袋 + "subheartflow_manager": SUBHEARTFLOW_MANAGER_STYLE_CONFIG, # 麦麦水群[管理] + "base_tool": BASE_TOOL_STYLE_CONFIG, # 工具使用 + "chat_stream": CHAT_STREAM_STYLE_CONFIG, # 聊天流 + "person_info": PERSON_INFO_STYLE_CONFIG, # 人物信息 + "willing": WILLING_STYLE_CONFIG, # 意愿 + "pfc_action_planner": PFC_ACTION_PLANNER_STYLE_CONFIG, # PFC私聊规划 + "mai_state": MAI_STATE_CONFIG, # 麦麦状态 + "lpmm": LPMM_STYLE_CONFIG, # LPMM + "hfc": HFC_STYLE_CONFIG, # HFC + "tianyi": TIANYI_STYLE_CONFIG, # 天依 + "remote": REMOTE_STYLE_CONFIG, # 远程 + "topic": TOPIC_STYLE_CONFIG, # 话题 + "sender": SENDER_STYLE_CONFIG, # 消息发送 + "confirm": CONFIRM_STYLE_CONFIG, # EULA与PRIVACY确认 + "model_utils": MODEL_UTILS_STYLE_CONFIG, # 模型工具 + "prompt": PROMPT_STYLE_CONFIG, # 提示词 + "change_mood_tool": CHANGE_MOOD_TOOL_STYLE_CONFIG, # 改变心情工具 + "change_relationship": CHANGE_RELATIONSHIP_TOOL_STYLE_CONFIG, # 改变关系工具 + "get_knowledge_tool": GET_KNOWLEDGE_TOOL_STYLE_CONFIG, # 获取知识工具 + "get_time_date": GET_TIME_DATE_TOOL_STYLE_CONFIG, # 获取时间日期工具 + "lpm_get_knowledge_tool": LPMM_GET_KNOWLEDGE_TOOL_STYLE_CONFIG, # LPMM获取知识工具 + "observation": OBSERVATION_STYLE_CONFIG, # 聊天观察 + "message_buffer": MESSAGE_BUFFER_STYLE_CONFIG, # 消息缓冲 + "chat_message": CHAT_MESSAGE_STYLE_CONFIG, # 聊天消息 + "chat_image": CHAT_IMAGE_STYLE_CONFIG, # 聊天图片 + "init": INIT_STYLE_CONFIG, # 初始化 + # ...如有更多模块，继续添加... +} + + +def get_logger(module_name: str): + style_config = MODULE_LOGGER_CONFIGS.get(module_name) + if style_config: + log_config = LogConfig( + console_format=style_config["console_format"], + file_format=style_config["file_format"], + ) + return get_module_logger(module_name, config=log_config) + # 若无特殊样式，使用默认 + return get_module_logger(module_name) diff --git a/src/common/message_repository.py b/src/common/message_repository.py new file mode 100644 index 000000000..fc7b7e542 --- /dev/null +++ b/src/common/message_repository.py @@ -0,0 +1,75 @@ +from src.common.database import db +from src.common.logger import get_module_logger +import traceback +from typing import List, Dict, Any, Optional + +logger = get_module_logger(__name__) + + +def find_messages( + filter: Dict[str, Any], sort: Optional[List[tuple[str, int]]] = None, limit: int = 0, limit_mode: str = "latest" +) -> List[Dict[str, Any]]: + """ + 根据提供的过滤器、排序和限制条件查找消息。 + + Args: + filter: MongoDB 查询过滤器。 + sort: MongoDB 排序条件列表，例如 [('time', 1)]。仅在 limit 为 0 时生效。 + limit: 返回的最大文档数，0表示不限制。 + limit_mode: 当 limit > 0 时生效。 'earliest' 表示获取最早的记录， 'latest' 表示获取最新的记录（结果仍按时间正序排列）。默认为 'latest'。 + + Returns: + 消息文档列表，如果出错则返回空列表。 + """ + try: + query = db.messages.find(filter) + results: List[Dict[str, Any]] = [] + + if limit > 0: + if limit_mode == "earliest": + # 获取时间最早的 limit 条记录，已经是正序 + query = query.sort([("time", 1)]).limit(limit) + results = list(query) + else: # 默认为 'latest' + # 获取时间最晚的 limit 条记录 + query = query.sort([("time", -1)]).limit(limit) + latest_results = list(query) + # 将结果按时间正序排列 + # 假设消息文档中总是有 'time' 字段且可排序 + results = sorted(latest_results, key=lambda msg: msg.get("time")) + else: + # limit 为 0 时，应用传入的 sort 参数 + if sort: + query = query.sort(sort) + results = list(query) + + return results + except Exception as e: + log_message = ( + f"查找消息失败 (filter={filter}, sort={sort}, limit={limit}, limit_mode={limit_mode}): {e}\n" + + traceback.format_exc() + ) + logger.error(log_message) + return [] + + +def count_messages(filter: Dict[str, Any]) -> int: + """ + 根据提供的过滤器计算消息数量。 + + Args: + filter: MongoDB 查询过滤器。 + + Returns: + 符合条件的消息数量，如果出错则返回 0。 + """ + try: + count = db.messages.count_documents(filter) + return count + except Exception as e: + log_message = f"计数消息失败 (filter={filter}): {e}\n" + traceback.format_exc() + logger.error(log_message) + return 0 + + +# 你可以在这里添加更多与 messages 集合相关的数据库操作函数，例如 find_one_message, insert_message 等。 diff --git a/src/common/server.py b/src/common/server.py index a4998a305..517996293 100644 --- a/src/common/server.py +++ b/src/common/server.py @@ -45,7 +45,8 @@ class Server: async def run(self): """启动服务器""" - config = Config(app=self.app, host=self._host, port=self._port) + # 禁用 uvicorn 默认日志和访问日志 + config = Config(app=self.app, host=self._host, port=self._port, log_config=None, access_log=False) self._server = UvicornServer(config=config) try: await self._server.serve() diff --git a/src/plugins/config/auto_update.py b/src/config/auto_update.py similarity index 100% rename from src/plugins/config/auto_update.py rename to src/config/auto_update.py diff --git a/src/plugins/config/config.py b/src/config/config.py similarity index 80% rename from src/plugins/config/config.py rename to src/config/config.py index d0a209d35..e6cf16d4d 100644 --- a/src/plugins/config/config.py +++ b/src/config/config.py @@ -13,21 +13,15 @@ from packaging import version from packaging.version import Version, InvalidVersion from packaging.specifiers import SpecifierSet, InvalidSpecifier -from src.common.logger import get_module_logger, CONFIG_STYLE_CONFIG, LogConfig +from src.common.logger_manager import get_logger -# 定义日志配置 -config_config = LogConfig( - # 使用消息发送专用样式 - console_format=CONFIG_STYLE_CONFIG["console_format"], - file_format=CONFIG_STYLE_CONFIG["file_format"], -) # 配置主程序日志格式 -logger = get_module_logger("config", config=config_config) +logger = get_logger("config") # 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 is_test = False -mai_version_main = "0.6.2" +mai_version_main = "0.6.3" mai_version_fix = "" if mai_version_fix: @@ -44,7 +38,7 @@ else: def update_config(): # 获取根目录路径 - root_dir = Path(__file__).parent.parent.parent.parent + root_dir = Path(__file__).parent.parent.parent template_dir = root_dir / "template" config_dir = root_dir / "config" old_config_dir = config_dir / "old" @@ -62,8 +56,7 @@ def update_config(): shutil.copy2(template_path, old_config_path) 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() - return + return quit() # 读取旧配置文件和模板文件 with open(old_config_path, "r", encoding="utf-8") as f: @@ -131,9 +124,6 @@ def update_config(): logger.info("配置文件更新完成") -logger = get_module_logger("config") - - @dataclass class BotConfig: """机器人配置类""" @@ -142,7 +132,7 @@ class BotConfig: MAI_VERSION: str = mai_version # 硬编码的版本信息 # bot - BOT_QQ: Optional[int] = 114514 + BOT_QQ: Optional[str] = "114514" BOT_NICKNAME: Optional[str] = None BOT_ALIAS_NAMES: List[str] = field(default_factory=list) # 别名，可以通过这个叫它 @@ -180,27 +170,34 @@ class BotConfig: SCHEDULE_TEMPERATURE: float = 0.5 # 日程表温度，建议0.5-1.0 TIME_ZONE: str = "Asia/Shanghai" # 时区 - # message - MAX_CONTEXT_SIZE: int = 15 # 上下文最大消息数 - emoji_chance: float = 0.2 # 发送表情包的基础概率 - thinking_timeout: int = 120 # 思考时间 - max_response_length: int = 1024 # 最大回复长度 + # chat + allow_focus_mode: bool = True # 是否允许专注聊天状态 + + base_normal_chat_num: int = 3 # 最多允许多少个群进行普通聊天 + base_focused_chat_num: int = 2 # 最多允许多少个群进行专注聊天 + + observation_context_size: int = 12 # 心流观察到的最长上下文大小，超过这个值的上下文会被压缩 + message_buffer: bool = True # 消息缓冲器 ban_words = set() ban_msgs_regex = set() - # heartflow - # enable_heartflow: bool = False # 是否启用心流 - sub_heart_flow_update_interval: int = 60 # 子心流更新频率，间隔 单位秒 - sub_heart_flow_freeze_time: int = 120 # 子心流冻结时间，超过这个时间没有回复，子心流会冻结，间隔 单位秒 - sub_heart_flow_stop_time: int = 600 # 子心流停止时间，超过这个时间没有回复，子心流会停止，间隔 单位秒 - heart_flow_update_interval: int = 300 # 心流更新频率，间隔 单位秒 - observation_context_size: int = 20 # 心流观察到的最长上下文大小，超过这个值的上下文会被压缩 + # focus_chat + reply_trigger_threshold: float = 3.0 # 心流聊天触发阈值，越低越容易触发 + default_decay_rate_per_second: float = 0.98 # 默认衰减率，越大衰减越慢 + consecutive_no_reply_threshold = 3 + compressed_length: int = 5 # 不能大于observation_context_size,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 - # willing + # normal_chat + model_reasoning_probability: float = 0.7 # 麦麦回答时选择推理模型(主要)模型概率 + model_normal_probability: float = 0.3 # 麦麦回答时选择一般模型(次要)模型概率 + + emoji_chance: float = 0.2 # 发送表情包的基础概率 + thinking_timeout: int = 120 # 思考时间 + willing_mode: str = "classical" # 意愿模式 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 @@ -209,18 +206,15 @@ class BotConfig: mentioned_bot_inevitable_reply: bool = False # 提及 bot 必然回复 at_bot_inevitable_reply: bool = False # @bot 必然回复 - # response - response_mode: str = "heart_flow" # 回复策略 - MODEL_R1_PROBABILITY: float = 0.8 # R1模型概率 - MODEL_V3_PROBABILITY: float = 0.1 # V3模型概率 - # MODEL_R1_DISTILL_PROBABILITY: float = 0.1 # R1蒸馏模型概率 - # emoji max_emoji_num: int = 200 # 表情包最大数量 max_reach_deletion: bool = True # 开启则在达到最大数量时删除表情包，关闭则不会继续收集表情包 EMOJI_CHECK_INTERVAL: int = 120 # 表情包检查间隔（分钟） - EMOJI_REGISTER_INTERVAL: int = 10 # 表情包注册间隔（分钟） - EMOJI_SAVE: bool = True # 偷表情包 + + save_pic: bool = False # 是否保存图片 + save_emoji: bool = False # 是否保存表情包 + 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 + EMOJI_CHECK: bool = False # 是否开启过滤 EMOJI_CHECK_PROMPT: str = "符合公序良俗" # 表情包过滤要求 @@ -237,6 +231,10 @@ class BotConfig: 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 # 相似度阈值 + consolidate_memory_percentage: float = 0.01 # 检查节点比例 + memory_ban_words: list = field( default_factory=lambda: ["表情包", "图片", "回复", "聊天记录"] ) # 添加新的配置项默认值 @@ -257,10 +255,13 @@ class BotConfig: chinese_typo_word_replace_rate = 0.02 # 整词替换概率 # response_splitter + enable_kaomoji_protection = False # 是否启用颜文字保护 enable_response_splitter = True # 是否启用回复分割器 response_max_length = 100 # 回复允许的最大长度 response_max_sentence_num = 3 # 回复允许的最大句子数 + model_max_output_length: int = 800 # 最大回复长度 + # remote remote_enable: bool = True # 是否启用远程控制 @@ -274,31 +275,16 @@ class BotConfig: # llm_reasoning_minor: Dict[str, str] = field(default_factory=lambda: {}) llm_normal: Dict[str, str] = field(default_factory=lambda: {}) llm_topic_judge: Dict[str, str] = field(default_factory=lambda: {}) - llm_summary_by_topic: Dict[str, str] = field(default_factory=lambda: {}) - llm_emotion_judge: Dict[str, str] = field(default_factory=lambda: {}) + llm_summary: Dict[str, str] = field(default_factory=lambda: {}) embedding: Dict[str, str] = field(default_factory=lambda: {}) vlm: Dict[str, str] = field(default_factory=lambda: {}) moderation: Dict[str, str] = field(default_factory=lambda: {}) - # 实验性 llm_observation: Dict[str, str] = field(default_factory=lambda: {}) llm_sub_heartflow: Dict[str, str] = field(default_factory=lambda: {}) llm_heartflow: Dict[str, str] = field(default_factory=lambda: {}) - - build_memory_interval: int = 600 # 记忆构建间隔（秒） - - forget_memory_interval: int = 600 # 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 - memory_compress_rate: float = 0.1 # 记忆压缩率 - build_memory_sample_num: int = 10 # 记忆构建采样数量 - build_memory_sample_length: int = 20 # 记忆构建采样长度 - memory_build_distribution: list = field( - default_factory=lambda: [4, 2, 0.6, 24, 8, 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_ban_words: list = field( - default_factory=lambda: ["表情包", "图片", "回复", "聊天记录"] - ) # 添加新的配置项默认值 + llm_tool_use: Dict[str, str] = field(default_factory=lambda: {}) + llm_plan: Dict[str, str] = field(default_factory=lambda: {}) api_urls: Dict[str, str] = field(default_factory=lambda: {}) @@ -306,7 +292,7 @@ class BotConfig: def get_config_dir() -> str: """获取配置文件目录""" current_dir = os.path.dirname(os.path.abspath(__file__)) - root_dir = os.path.abspath(os.path.join(current_dir, "..", "..", "..")) + root_dir = os.path.abspath(os.path.join(current_dir, "..", "..")) config_dir = os.path.join(root_dir, "config") if not os.path.exists(config_dir): os.makedirs(config_dir) @@ -402,78 +388,80 @@ class BotConfig: def emoji(parent: dict): emoji_config = parent["emoji"] config.EMOJI_CHECK_INTERVAL = emoji_config.get("check_interval", config.EMOJI_CHECK_INTERVAL) - config.EMOJI_REGISTER_INTERVAL = emoji_config.get("register_interval", config.EMOJI_REGISTER_INTERVAL) config.EMOJI_CHECK_PROMPT = emoji_config.get("check_prompt", config.EMOJI_CHECK_PROMPT) - config.EMOJI_SAVE = emoji_config.get("auto_save", config.EMOJI_SAVE) config.EMOJI_CHECK = emoji_config.get("enable_check", config.EMOJI_CHECK) if config.INNER_VERSION in SpecifierSet(">=1.1.1"): config.max_emoji_num = emoji_config.get("max_emoji_num", config.max_emoji_num) config.max_reach_deletion = emoji_config.get("max_reach_deletion", config.max_reach_deletion) + if config.INNER_VERSION in SpecifierSet(">=1.4.2"): + config.save_pic = emoji_config.get("save_pic", config.save_pic) + config.save_emoji = emoji_config.get("save_emoji", config.save_emoji) + config.steal_emoji = emoji_config.get("steal_emoji", config.steal_emoji) def bot(parent: dict): # 机器人基础配置 bot_config = parent["bot"] bot_qq = bot_config.get("qq") - config.BOT_QQ = int(bot_qq) + config.BOT_QQ = str(bot_qq) config.BOT_NICKNAME = bot_config.get("nickname", config.BOT_NICKNAME) config.BOT_ALIAS_NAMES = bot_config.get("alias_names", config.BOT_ALIAS_NAMES) - def response(parent: dict): - response_config = parent["response"] - config.MODEL_R1_PROBABILITY = response_config.get("model_r1_probability", config.MODEL_R1_PROBABILITY) - config.MODEL_V3_PROBABILITY = response_config.get("model_v3_probability", config.MODEL_V3_PROBABILITY) - # config.MODEL_R1_DISTILL_PROBABILITY = response_config.get( - # "model_r1_distill_probability", config.MODEL_R1_DISTILL_PROBABILITY - # ) - config.max_response_length = response_config.get("max_response_length", config.max_response_length) - if config.INNER_VERSION in SpecifierSet(">=1.0.4"): - config.response_mode = response_config.get("response_mode", config.response_mode) + def chat(parent: dict): + chat_config = parent["chat"] + config.allow_focus_mode = chat_config.get("allow_focus_mode", config.allow_focus_mode) + config.base_normal_chat_num = chat_config.get("base_normal_chat_num", config.base_normal_chat_num) + config.base_focused_chat_num = chat_config.get("base_focused_chat_num", config.base_focused_chat_num) + config.observation_context_size = chat_config.get( + "observation_context_size", config.observation_context_size + ) + config.message_buffer = chat_config.get("message_buffer", config.message_buffer) + config.ban_words = chat_config.get("ban_words", config.ban_words) + for r in chat_config.get("ban_msgs_regex", config.ban_msgs_regex): + config.ban_msgs_regex.add(re.compile(r)) - def heartflow(parent: dict): - heartflow_config = parent["heartflow"] - config.sub_heart_flow_update_interval = heartflow_config.get( - "sub_heart_flow_update_interval", config.sub_heart_flow_update_interval + def normal_chat(parent: dict): + normal_chat_config = parent["normal_chat"] + config.model_reasoning_probability = normal_chat_config.get( + "model_reasoning_probability", config.model_reasoning_probability ) - config.sub_heart_flow_freeze_time = heartflow_config.get( - "sub_heart_flow_freeze_time", config.sub_heart_flow_freeze_time + config.model_normal_probability = normal_chat_config.get( + "model_normal_probability", config.model_normal_probability ) - config.sub_heart_flow_stop_time = heartflow_config.get( - "sub_heart_flow_stop_time", config.sub_heart_flow_stop_time - ) - config.heart_flow_update_interval = heartflow_config.get( - "heart_flow_update_interval", config.heart_flow_update_interval - ) - if config.INNER_VERSION in SpecifierSet(">=1.3.0"): - config.observation_context_size = heartflow_config.get( - "observation_context_size", config.observation_context_size - ) - config.compressed_length = heartflow_config.get("compressed_length", config.compressed_length) - config.compress_length_limit = heartflow_config.get( - "compress_length_limit", config.compress_length_limit - ) + config.emoji_chance = normal_chat_config.get("emoji_chance", config.emoji_chance) + config.thinking_timeout = normal_chat_config.get("thinking_timeout", config.thinking_timeout) - def willing(parent: dict): - willing_config = parent["willing"] - config.willing_mode = willing_config.get("willing_mode", config.willing_mode) + config.willing_mode = normal_chat_config.get("willing_mode", config.willing_mode) + config.response_willing_amplifier = normal_chat_config.get( + "response_willing_amplifier", config.response_willing_amplifier + ) + config.response_interested_rate_amplifier = normal_chat_config.get( + "response_interested_rate_amplifier", config.response_interested_rate_amplifier + ) + config.down_frequency_rate = normal_chat_config.get("down_frequency_rate", config.down_frequency_rate) + config.emoji_response_penalty = normal_chat_config.get( + "emoji_response_penalty", config.emoji_response_penalty + ) - if config.INNER_VERSION in SpecifierSet(">=0.0.11"): - config.response_willing_amplifier = willing_config.get( - "response_willing_amplifier", config.response_willing_amplifier - ) - config.response_interested_rate_amplifier = willing_config.get( - "response_interested_rate_amplifier", config.response_interested_rate_amplifier - ) - config.down_frequency_rate = willing_config.get("down_frequency_rate", config.down_frequency_rate) - config.emoji_response_penalty = willing_config.get( - "emoji_response_penalty", config.emoji_response_penalty - ) - if config.INNER_VERSION in SpecifierSet(">=1.2.5"): - config.mentioned_bot_inevitable_reply = willing_config.get( - "mentioned_bot_inevitable_reply", config.mentioned_bot_inevitable_reply - ) - config.at_bot_inevitable_reply = willing_config.get( - "at_bot_inevitable_reply", config.at_bot_inevitable_reply - ) + config.mentioned_bot_inevitable_reply = normal_chat_config.get( + "mentioned_bot_inevitable_reply", config.mentioned_bot_inevitable_reply + ) + config.at_bot_inevitable_reply = normal_chat_config.get( + "at_bot_inevitable_reply", config.at_bot_inevitable_reply + ) + + def focus_chat(parent: dict): + focus_chat_config = parent["focus_chat"] + config.compressed_length = focus_chat_config.get("compressed_length", config.compressed_length) + config.compress_length_limit = focus_chat_config.get("compress_length_limit", config.compress_length_limit) + config.reply_trigger_threshold = focus_chat_config.get( + "reply_trigger_threshold", config.reply_trigger_threshold + ) + config.default_decay_rate_per_second = focus_chat_config.get( + "default_decay_rate_per_second", config.default_decay_rate_per_second + ) + config.consecutive_no_reply_threshold = focus_chat_config.get( + "consecutive_no_reply_threshold", config.consecutive_no_reply_threshold + ) def model(parent: dict): # 加载模型配置 @@ -484,14 +472,17 @@ class BotConfig: # "llm_reasoning_minor", "llm_normal", "llm_topic_judge", - "llm_summary_by_topic", - "llm_emotion_judge", + "llm_summary", "vlm", "embedding", "llm_tool_use", "llm_observation", "llm_sub_heartflow", + "llm_plan", "llm_heartflow", + "llm_PFC_action_planner", + "llm_PFC_chat", + "llm_PFC_reply_checker", ] for item in config_list: @@ -560,26 +551,6 @@ class BotConfig: logger.error(f"模型 {item} 在config中不存在，请检查，或尝试更新配置文件") raise KeyError(f"模型 {item} 在config中不存在，请检查，或尝试更新配置文件") - def message(parent: dict): - msg_config = parent["message"] - config.MAX_CONTEXT_SIZE = msg_config.get("max_context_size", config.MAX_CONTEXT_SIZE) - config.emoji_chance = msg_config.get("emoji_chance", config.emoji_chance) - config.ban_words = msg_config.get("ban_words", config.ban_words) - config.thinking_timeout = msg_config.get("thinking_timeout", config.thinking_timeout) - config.response_willing_amplifier = msg_config.get( - "response_willing_amplifier", config.response_willing_amplifier - ) - config.response_interested_rate_amplifier = msg_config.get( - "response_interested_rate_amplifier", config.response_interested_rate_amplifier - ) - config.down_frequency_rate = msg_config.get("down_frequency_rate", config.down_frequency_rate) - for r in msg_config.get("ban_msgs_regex", config.ban_msgs_regex): - config.ban_msgs_regex.add(re.compile(r)) - if config.INNER_VERSION in SpecifierSet(">=0.0.11"): - config.max_response_length = msg_config.get("max_response_length", config.max_response_length) - if config.INNER_VERSION in SpecifierSet(">=1.1.4"): - config.message_buffer = msg_config.get("message_buffer", config.message_buffer) - def memory(parent: dict): memory_config = parent["memory"] config.build_memory_interval = memory_config.get("build_memory_interval", config.build_memory_interval) @@ -600,6 +571,16 @@ class BotConfig: config.build_memory_sample_length = memory_config.get( "build_memory_sample_length", config.build_memory_sample_length ) + if config.INNER_VERSION in SpecifierSet(">=1.5.1"): + config.consolidate_memory_interval = memory_config.get( + "consolidate_memory_interval", config.consolidate_memory_interval + ) + config.consolidation_similarity_threshold = memory_config.get( + "consolidation_similarity_threshold", config.consolidation_similarity_threshold + ) + config.consolidate_memory_percentage = memory_config.get( + "consolidate_memory_percentage", config.consolidate_memory_percentage + ) def remote(parent: dict): remote_config = parent["remote"] @@ -640,12 +621,25 @@ class BotConfig: config.response_max_sentence_num = response_splitter_config.get( "response_max_sentence_num", config.response_max_sentence_num ) + if config.INNER_VERSION in SpecifierSet(">=1.4.2"): + config.enable_kaomoji_protection = response_splitter_config.get( + "enable_kaomoji_protection", config.enable_kaomoji_protection + ) + if config.INNER_VERSION in SpecifierSet(">=1.6.0"): + config.model_max_output_length = response_splitter_config.get( + "model_max_output_length", config.model_max_output_length + ) def groups(parent: dict): groups_config = parent["groups"] - config.talk_allowed_groups = set(groups_config.get("talk_allowed", [])) - config.talk_frequency_down_groups = set(groups_config.get("talk_frequency_down", [])) - config.ban_user_id = set(groups_config.get("ban_user_id", [])) + # config.talk_allowed_groups = set(groups_config.get("talk_allowed", [])) + config.talk_allowed_groups = set(str(group) for group in groups_config.get("talk_allowed", [])) + # config.talk_frequency_down_groups = set(groups_config.get("talk_frequency_down", [])) + config.talk_frequency_down_groups = set( + str(group) for group in groups_config.get("talk_frequency_down", []) + ) + # config.ban_user_id = set(groups_config.get("ban_user_id", [])) + config.ban_user_id = set(str(user) for user in groups_config.get("ban_user_id", [])) def platforms(parent: dict): platforms_config = parent["platforms"] @@ -680,10 +674,7 @@ class BotConfig: "personality": {"func": personality, "support": ">=0.0.0"}, "identity": {"func": identity, "support": ">=1.2.4"}, "schedule": {"func": schedule, "support": ">=0.0.11", "necessary": False}, - "message": {"func": message, "support": ">=0.0.0"}, - "willing": {"func": willing, "support": ">=0.0.9", "necessary": False}, "emoji": {"func": emoji, "support": ">=0.0.0"}, - "response": {"func": response, "support": ">=0.0.0"}, "model": {"func": model, "support": ">=0.0.0"}, "memory": {"func": memory, "support": ">=0.0.0", "necessary": False}, "mood": {"func": mood, "support": ">=0.0.0"}, @@ -693,7 +684,9 @@ class BotConfig: "platforms": {"func": platforms, "support": ">=1.0.0"}, "response_splitter": {"func": response_splitter, "support": ">=0.0.11", "necessary": False}, "experimental": {"func": experimental, "support": ">=0.0.11", "necessary": False}, - "heartflow": {"func": heartflow, "support": ">=1.0.2", "necessary": False}, + "chat": {"func": chat, "support": ">=1.6.0", "necessary": False}, + "normal_chat": {"func": normal_chat, "support": ">=1.6.0", "necessary": False}, + "focus_chat": {"func": focus_chat, "support": ">=1.6.0", "necessary": False}, } # 原地修改，将 字符串版本表达式 转换成 版本对象 diff --git a/src/do_tool/tool_can_use/change_mood.py b/src/do_tool/not_used/change_mood.py similarity index 71% rename from src/do_tool/tool_can_use/change_mood.py rename to src/do_tool/not_used/change_mood.py index 53410068f..430561a26 100644 --- a/src/do_tool/tool_can_use/change_mood.py +++ b/src/do_tool/not_used/change_mood.py @@ -1,12 +1,11 @@ from src.do_tool.tool_can_use.base_tool import BaseTool -from src.plugins.config.config import global_config -from src.common.logger import get_module_logger +from src.config.config import global_config +from src.common.logger_manager import get_logger from src.plugins.moods.moods import MoodManager -from src.plugins.chat_module.think_flow_chat.think_flow_generator import ResponseGenerator from typing import Dict, Any -logger = get_module_logger("change_mood_tool") +logger = get_logger("change_mood_tool") class ChangeMoodTool(BaseTool): @@ -23,29 +22,29 @@ class ChangeMoodTool(BaseTool): "required": ["text", "response_set"], } - async def execute(self, function_args: Dict[str, Any], message_txt: str) -> Dict[str, Any]: + async def execute(self, function_args: Dict[str, Any], message_txt: str = "") -> Dict[str, Any]: """执行心情改变 Args: function_args: 工具参数 - message_processed_plain_text: 原始消息文本 - response_set: 原始消息文本 + message_txt: 原始消息文本 Returns: Dict: 工具执行结果 """ try: response_set = function_args.get("response_set") - message_processed_plain_text = function_args.get("text") + _message_processed_plain_text = function_args.get("text") mood_manager = MoodManager.get_instance() - gpt = ResponseGenerator() + # gpt = ResponseGenerator() if response_set is None: response_set = ["你还没有回复"] - ori_response = ",".join(response_set) - _stance, emotion = await gpt._get_emotion_tags(ori_response, message_processed_plain_text) + _ori_response = ",".join(response_set) + # _stance, emotion = await gpt._get_emotion_tags(ori_response, message_processed_plain_text) + emotion = "平静" mood_manager.update_mood_from_emotion(emotion, global_config.mood_intensity_factor) return {"name": "change_mood", "content": f"你的心情刚刚变化了，现在的心情是: {emotion}"} except Exception as e: diff --git a/src/do_tool/tool_can_use/change_relationship.py b/src/do_tool/not_used/change_relationship.py similarity index 63% rename from src/do_tool/tool_can_use/change_relationship.py rename to src/do_tool/not_used/change_relationship.py index 9aa084855..4af32fb8c 100644 --- a/src/do_tool/tool_can_use/change_relationship.py +++ b/src/do_tool/not_used/change_relationship.py @@ -1,10 +1,9 @@ -# from src.plugins.person_info.relationship_manager import relationship_manager -from src.common.logger import get_module_logger +from typing import Dict, Any +from src.common.logger_manager import get_logger from src.do_tool.tool_can_use.base_tool import BaseTool -# from src.plugins.chat_module.think_flow_chat.think_flow_generator import ResponseGenerator -logger = get_module_logger("relationship_tool") +logger = get_logger("relationship_tool") class RelationshipTool(BaseTool): @@ -20,22 +19,20 @@ class RelationshipTool(BaseTool): "required": ["text", "changed_value", "reason"], } - async def execute(self, args: dict, message_txt: str) -> dict: + async def execute(self, function_args: Dict[str, Any], message_txt: str = "") -> dict: """执行工具功能 Args: - args: 包含工具参数的字典 - text: 原始消息文本 - changed_value: 变更值 - reason: 变更原因 + function_args: 包含工具参数的字典 + message_txt: 原始消息文本 Returns: dict: 包含执行结果的字典 """ try: - text = args.get("text") - changed_value = args.get("changed_value") - reason = args.get("reason") + text = function_args.get("text") + changed_value = function_args.get("changed_value") + reason = function_args.get("reason") return {"content": f"因为你刚刚因为{reason}，所以你和发[{text}]这条消息的人的关系值变化为{changed_value}"} diff --git a/src/do_tool/tool_can_use/get_current_task.py b/src/do_tool/not_used/get_current_task.py similarity index 100% rename from src/do_tool/tool_can_use/get_current_task.py rename to src/do_tool/not_used/get_current_task.py diff --git a/src/do_tool/tool_can_use/mid_chat_mem.py b/src/do_tool/not_used/mid_chat_mem.py similarity index 86% rename from src/do_tool/tool_can_use/mid_chat_mem.py rename to src/do_tool/not_used/mid_chat_mem.py index 26d26704a..71726a57f 100644 --- a/src/do_tool/tool_can_use/mid_chat_mem.py +++ b/src/do_tool/not_used/mid_chat_mem.py @@ -9,11 +9,11 @@ class GetMidMemoryTool(BaseTool): """从记忆系统中获取相关记忆的工具""" name = "mid_chat_mem" - description = "之前的聊天内容中获取具体信息，当最新消息提到，或者你需要回复的消息中提到，你可以使用这个工具" + description = "之前的聊天内容概述id中获取具体信息，如果没有聊天内容概述id，就不要使用" parameters = { "type": "object", "properties": { - "id": {"type": "integer", "description": "要查询的聊天记录id"}, + "id": {"type": "integer", "description": "要查询的聊天记录概述id"}, }, "required": ["id"], } diff --git a/src/do_tool/tool_can_use/send_emoji.py b/src/do_tool/not_used/send_emoji.py similarity index 95% rename from src/do_tool/tool_can_use/send_emoji.py rename to src/do_tool/not_used/send_emoji.py index 9cd48f0e4..3c6c8a3f1 100644 --- a/src/do_tool/tool_can_use/send_emoji.py +++ b/src/do_tool/not_used/send_emoji.py @@ -17,7 +17,7 @@ class SendEmojiTool(BaseTool): "required": ["text"], } - async def execute(self, function_args: Dict[str, Any], message_txt: str) -> Dict[str, Any]: + async def execute(self, function_args: Dict[str, Any], message_txt: str = "") -> Dict[str, Any]: text = function_args.get("text", message_txt) return { "name": "send_emoji", diff --git a/src/do_tool/tool_can_use/base_tool.py b/src/do_tool/tool_can_use/base_tool.py index b1edf8055..1dd15bafc 100644 --- a/src/do_tool/tool_can_use/base_tool.py +++ b/src/do_tool/tool_can_use/base_tool.py @@ -3,9 +3,9 @@ import inspect import importlib import pkgutil import os -from src.common.logger import get_module_logger +from src.common.logger_manager import get_logger -logger = get_module_logger("base_tool") +logger = get_logger("base_tool") # 工具注册表 TOOL_REGISTRY = {} @@ -36,12 +36,11 @@ class BaseTool: "function": {"name": cls.name, "description": cls.description, "parameters": cls.parameters}, } - async def execute(self, function_args: Dict[str, Any], message_txt: str = "") -> Dict[str, Any]: + async def execute(self, function_args: Dict[str, Any]) -> Dict[str, Any]: """执行工具函数 Args: function_args: 工具调用参数 - message_txt: 原始消息文本 Returns: Dict: 工具执行结果 @@ -63,7 +62,7 @@ def register_tool(tool_class: Type[BaseTool]): raise ValueError(f"工具类 {tool_class.__name__} 没有定义 name 属性") TOOL_REGISTRY[tool_name] = tool_class - logger.info(f"已注册工具: {tool_name}") + logger.info(f"已注册: {tool_name}") def discover_tools(): diff --git a/src/do_tool/tool_can_use/compare_numbers_tool.py b/src/do_tool/tool_can_use/compare_numbers_tool.py index 48cee5157..1fbd812a0 100644 --- a/src/do_tool/tool_can_use/compare_numbers_tool.py +++ b/src/do_tool/tool_can_use/compare_numbers_tool.py @@ -19,7 +19,7 @@ class CompareNumbersTool(BaseTool): "required": ["num1", "num2"], } - async def execute(self, function_args: Dict[str, Any], message_txt: str = "") -> Dict[str, Any]: + async def execute(self, function_args: Dict[str, Any]) -> Dict[str, Any]: """执行比较两个数的大小 Args: diff --git a/src/do_tool/tool_can_use/get_knowledge.py b/src/do_tool/tool_can_use/get_knowledge.py index b78c07750..bd4ce86b4 100644 --- a/src/do_tool/tool_can_use/get_knowledge.py +++ b/src/do_tool/tool_can_use/get_knowledge.py @@ -1,10 +1,10 @@ from src.do_tool.tool_can_use.base_tool import BaseTool from src.plugins.chat.utils import get_embedding from src.common.database import db -from src.common.logger import get_module_logger +from src.common.logger_manager import get_logger from typing import Dict, Any, Union -logger = get_module_logger("get_knowledge_tool") +logger = get_logger("get_knowledge_tool") class SearchKnowledgeTool(BaseTool): @@ -21,7 +21,7 @@ class SearchKnowledgeTool(BaseTool): "required": ["query"], } - async def execute(self, function_args: Dict[str, Any], message_txt: str = "") -> Dict[str, Any]: + async def execute(self, function_args: Dict[str, Any]) -> Dict[str, Any]: """执行知识库搜索 Args: @@ -32,7 +32,7 @@ class SearchKnowledgeTool(BaseTool): Dict: 工具执行结果 """ try: - query = function_args.get("query", message_txt) + query = function_args.get("query") threshold = function_args.get("threshold", 0.4) # 调用知识库搜索 @@ -49,8 +49,9 @@ class SearchKnowledgeTool(BaseTool): logger.error(f"知识库搜索工具执行失败: {str(e)}") return {"name": "search_knowledge", "content": f"知识库搜索失败: {str(e)}"} + @staticmethod def get_info_from_db( - self, query_embedding: list, limit: int = 1, threshold: float = 0.5, return_raw: bool = False + query_embedding: list, limit: int = 1, threshold: float = 0.5, return_raw: bool = False ) -> Union[str, list]: """从数据库中获取相关信息 diff --git a/src/do_tool/tool_can_use/get_memory.py b/src/do_tool/tool_can_use/get_memory.py index 6a3c1c391..b38423ed0 100644 --- a/src/do_tool/tool_can_use/get_memory.py +++ b/src/do_tool/tool_can_use/get_memory.py @@ -9,18 +9,18 @@ logger = get_module_logger("mid_chat_mem_tool") class GetMemoryTool(BaseTool): """从记忆系统中获取相关记忆的工具""" - name = "mid_chat_mem" + name = "get_memory" description = "从记忆系统中获取相关记忆" parameters = { "type": "object", "properties": { - "text": {"type": "string", "description": "要查询的相关文本"}, + "topic": {"type": "string", "description": "要查询的相关主题,用逗号隔开"}, "max_memory_num": {"type": "integer", "description": "最大返回记忆数量"}, }, - "required": ["text"], + "required": ["topic"], } - async def execute(self, function_args: Dict[str, Any], message_txt: str = "") -> Dict[str, Any]: + async def execute(self, function_args: Dict[str, Any]) -> Dict[str, Any]: """执行记忆获取 Args: @@ -31,12 +31,15 @@ class GetMemoryTool(BaseTool): Dict: 工具执行结果 """ try: - text = function_args.get("text", message_txt) + topic = function_args.get("topic") max_memory_num = function_args.get("max_memory_num", 2) + # 将主题字符串转换为列表 + topic_list = topic.split(",") + # 调用记忆系统 - related_memory = await HippocampusManager.get_instance().get_memory_from_text( - text=text, max_memory_num=max_memory_num, max_memory_length=2, max_depth=3, fast_retrieval=False + related_memory = await HippocampusManager.get_instance().get_memory_from_topic( + valid_keywords=topic_list, max_memory_num=max_memory_num, max_memory_length=2, max_depth=3 ) memory_info = "" @@ -45,14 +48,16 @@ class GetMemoryTool(BaseTool): memory_info += memory[1] + "\n" if memory_info: - content = f"你记得这些事情: {memory_info}" - else: - content = f"你不太记得有关{text}的记忆，你对此不太了解" + content = f"你记得这些事情: {memory_info}\n" + content += "以上是你的回忆，不一定是目前聊天里的人说的，也不一定是现在发生的事情，请记住。\n" - return {"name": "mid_chat_mem", "content": content} + else: + content = f"{topic}的记忆，你记不太清" + + return {"name": "get_memory", "content": content} except Exception as e: logger.error(f"记忆获取工具执行失败: {str(e)}") - return {"name": "mid_chat_mem", "content": f"记忆获取失败: {str(e)}"} + return {"name": "get_memory", "content": f"记忆获取失败: {str(e)}"} # 注册工具 diff --git a/src/do_tool/tool_can_use/get_time_date.py b/src/do_tool/tool_can_use/get_time_date.py index c3c9c8376..6104026ef 100644 --- a/src/do_tool/tool_can_use/get_time_date.py +++ b/src/do_tool/tool_can_use/get_time_date.py @@ -1,9 +1,9 @@ from src.do_tool.tool_can_use.base_tool import BaseTool -from src.common.logger import get_module_logger +from src.common.logger_manager import get_logger from typing import Dict, Any from datetime import datetime -logger = get_module_logger("get_time_date") +logger = get_logger("get_time_date") class GetCurrentDateTimeTool(BaseTool): @@ -17,7 +17,7 @@ class GetCurrentDateTimeTool(BaseTool): "required": [], } - async def execute(self, function_args: Dict[str, Any], message_txt: str = "") -> Dict[str, Any]: + async def execute(self, function_args: Dict[str, Any]) -> Dict[str, Any]: """执行获取当前时间、日期、年份和星期 Args: diff --git a/src/do_tool/tool_can_use/lpmm_get_knowledge.py b/src/do_tool/tool_can_use/lpmm_get_knowledge.py new file mode 100644 index 000000000..4dba1bc71 --- /dev/null +++ b/src/do_tool/tool_can_use/lpmm_get_knowledge.py @@ -0,0 +1,139 @@ +from src.do_tool.tool_can_use.base_tool import BaseTool +from src.plugins.chat.utils import get_embedding + +# from src.common.database import db +from src.common.logger_manager import get_logger +from typing import Dict, Any +from src.plugins.knowledge.knowledge_lib import qa_manager + + +logger = get_logger("lpmm_get_knowledge_tool") + + +class SearchKnowledgeFromLPMMTool(BaseTool): + """从LPMM知识库中搜索相关信息的工具""" + + name = "lpmm_search_knowledge" + description = "从知识库中搜索相关信息，如果你需要知识，就使用这个工具" + parameters = { + "type": "object", + "properties": { + "query": {"type": "string", "description": "搜索查询关键词"}, + "threshold": {"type": "number", "description": "相似度阈值，0.0到1.0之间"}, + }, + "required": ["query"], + } + + async def execute(self, function_args: Dict[str, Any]) -> Dict[str, Any]: + """执行知识库搜索 + + Args: + function_args: 工具参数 + message_txt: 原始消息文本 + + Returns: + Dict: 工具执行结果 + """ + try: + query = function_args.get("query") + # threshold = function_args.get("threshold", 0.4) + + # 调用知识库搜索 + embedding = await get_embedding(query, request_type="info_retrieval") + if embedding: + knowledge_info = qa_manager.get_knowledge(query) + logger.debug(f"知识库查询结果: {knowledge_info}") + if knowledge_info: + content = f"你知道这些知识: {knowledge_info}" + else: + content = f"你不太了解有关{query}的知识" + return {"name": "search_knowledge", "content": content} + return {"name": "search_knowledge", "content": f"无法获取关于'{query}'的嵌入向量"} + except Exception as e: + logger.error(f"知识库搜索工具执行失败: {str(e)}") + return {"name": "search_knowledge", "content": f"知识库搜索失败: {str(e)}"} + + # def get_info_from_db( + # self, query_embedding: list, limit: int = 1, threshold: float = 0.5, return_raw: bool = False + # ) -> Union[str, list]: + # """从数据库中获取相关信息 + + # Args: + # query_embedding: 查询的嵌入向量 + # limit: 最大返回结果数 + # threshold: 相似度阈值 + # return_raw: 是否返回原始结果 + + # Returns: + # Union[str, list]: 格式化的信息字符串或原始结果列表 + # """ + # if not query_embedding: + # return "" if not return_raw else [] + + # # 使用余弦相似度计算 + # pipeline = [ + # { + # "$addFields": { + # "dotProduct": { + # "$reduce": { + # "input": {"$range": [0, {"$size": "$embedding"}]}, + # "initialValue": 0, + # "in": { + # "$add": [ + # "$$value", + # { + # "$multiply": [ + # {"$arrayElemAt": ["$embedding", "$$this"]}, + # {"$arrayElemAt": [query_embedding, "$$this"]}, + # ] + # }, + # ] + # }, + # } + # }, + # "magnitude1": { + # "$sqrt": { + # "$reduce": { + # "input": "$embedding", + # "initialValue": 0, + # "in": {"$add": ["$$value", {"$multiply": ["$$this", "$$this"]}]}, + # } + # } + # }, + # "magnitude2": { + # "$sqrt": { + # "$reduce": { + # "input": query_embedding, + # "initialValue": 0, + # "in": {"$add": ["$$value", {"$multiply": ["$$this", "$$this"]}]}, + # } + # } + # }, + # } + # }, + # {"$addFields": {"similarity": {"$divide": ["$dotProduct", {"$multiply": ["$magnitude1", "$magnitude2"]}]}}}, + # { + # "$match": { + # "similarity": {"$gte": threshold} # 只保留相似度大于等于阈值的结果 + # } + # }, + # {"$sort": {"similarity": -1}}, + # {"$limit": limit}, + # {"$project": {"content": 1, "similarity": 1}}, + # ] + + # results = list(db.knowledges.aggregate(pipeline)) + # logger.debug(f"知识库查询结果数量: {len(results)}") + + # if not results: + # return "" if not return_raw else [] + + # if return_raw: + # return results + # else: + # # 返回所有找到的内容，用换行分隔 + # return "\n".join(str(result["content"]) for result in results) + + +# 注册工具 +# register_tool(SearchKnowledgeTool) diff --git a/src/do_tool/tool_use.py b/src/do_tool/tool_use.py index b14927be8..88289fe01 100644 --- a/src/do_tool/tool_use.py +++ b/src/do_tool/tool_use.py @@ -1,66 +1,60 @@ -from src.plugins.models.utils_model import LLM_request -from src.plugins.config.config import global_config -from src.plugins.chat.chat_stream import ChatStream -from src.common.database import db -import time +from src.plugins.models.utils_model import LLMRequest +from src.config.config import global_config import json -from src.common.logger import get_module_logger, TOOL_USE_STYLE_CONFIG, LogConfig +from src.common.logger_manager import get_logger from src.do_tool.tool_can_use import get_all_tool_definitions, get_tool_instance -from src.heart_flow.sub_heartflow import SubHeartflow +import traceback +from src.plugins.person_info.relationship_manager import relationship_manager +from src.plugins.chat.utils import parse_text_timestamps +from src.plugins.chat.chat_stream import ChatStream +from src.heart_flow.observation import ChattingObservation -tool_use_config = LogConfig( - # 使用消息发送专用样式 - console_format=TOOL_USE_STYLE_CONFIG["console_format"], - file_format=TOOL_USE_STYLE_CONFIG["file_format"], -) -logger = get_module_logger("tool_use", config=tool_use_config) +logger = get_logger("tool_use") class ToolUser: def __init__(self): - self.llm_model_tool = LLM_request( + self.llm_model_tool = LLMRequest( model=global_config.llm_tool_use, temperature=0.2, max_tokens=1000, request_type="tool_use" ) + @staticmethod async def _build_tool_prompt( - self, message_txt: str, sender_name: str, chat_stream: ChatStream, subheartflow: SubHeartflow = None + message_txt: str, chat_stream: ChatStream = None, observation: ChattingObservation = None ): """构建工具使用的提示词 Args: message_txt: 用户消息文本 - sender_name: 发送者名称 - chat_stream: 聊天流对象 + subheartflow: 子心流对象 Returns: str: 构建好的提示词 """ - if subheartflow: - mid_memory_info = subheartflow.observations[0].mid_memory_info - # print(f"intol111111111111111111111111111111111222222222222mid_memory_info：{mid_memory_info}") - else: - mid_memory_info = "" - new_messages = list( - db.messages.find({"chat_id": chat_stream.stream_id, "time": {"$gt": time.time()}}).sort("time", 1).limit(15) - ) - new_messages_str = "" - for msg in new_messages: - if "detailed_plain_text" in msg: - new_messages_str += f"{msg['detailed_plain_text']}" + if observation: + mid_memory_info = observation.mid_memory_info + # print(f"intol111111111111111111111111111111111222222222222mid_memory_info：{mid_memory_info}") # 这些信息应该从调用者传入，而不是从self获取 bot_name = global_config.BOT_NICKNAME prompt = "" prompt += mid_memory_info prompt += "你正在思考如何回复群里的消息。\n" - prompt += f"你注意到{sender_name}刚刚说：{message_txt}\n" - prompt += f"注意你就是{bot_name}，{bot_name}指的就是你。" + prompt += "之前群里进行了如下讨论:\n" + prompt += message_txt + # prompt += f"你注意到{sender_name}刚刚说：{message_txt}\n" + prompt += f"注意你就是{bot_name}，{bot_name}是你的名字。根据之前的聊天记录补充问题信息，搜索时避开你的名字。\n" + # prompt += "必须调用 'lpmm_get_knowledge' 工具来获取知识。\n" + prompt += "你现在需要对群里的聊天内容进行回复，请你思考应该使用什么工具，然后选择工具来对消息和你的回复进行处理，你是否需要额外的信息，比如回忆或者搜寻已有的知识，改变关系和情感，或者了解你现在正在做什么。" + + prompt = await relationship_manager.convert_all_person_sign_to_person_name(prompt) + prompt = parse_text_timestamps(prompt, mode="lite") - prompt += "你现在需要对群里的聊天内容进行回复，现在选择工具来对消息和你的回复进行处理，你是否需要额外的信息，比如回忆或者搜寻已有的知识，改变关系和情感，或者了解你现在正在做什么。" return prompt - def _define_tools(self): + @staticmethod + def _define_tools(): """获取所有已注册工具的定义 Returns: @@ -68,7 +62,8 @@ class ToolUser: """ return get_all_tool_definitions() - async def _execute_tool_call(self, tool_call, message_txt: str): + @staticmethod + async def _execute_tool_call(tool_call): """执行特定的工具调用 Args: @@ -89,7 +84,7 @@ class ToolUser: return None # 执行工具 - result = await tool_instance.execute(function_args, message_txt) + result = await tool_instance.execute(function_args) if result: # 直接使用 function_name 作为 tool_type tool_type = function_name @@ -106,22 +101,25 @@ class ToolUser: logger.error(f"执行工具调用时发生错误: {str(e)}") return None - async def use_tool( - self, message_txt: str, sender_name: str, chat_stream: ChatStream, subheartflow: SubHeartflow = None - ): + async def use_tool(self, message_txt: str, chat_stream: ChatStream = None, observation: ChattingObservation = None): """使用工具辅助思考，判断是否需要额外信息 Args: message_txt: 用户消息文本 sender_name: 发送者名称 chat_stream: 聊天流对象 + observation: 观察对象（可选） Returns: dict: 工具使用结果，包含结构化的信息 """ try: # 构建提示词 - prompt = await self._build_tool_prompt(message_txt, sender_name, chat_stream, subheartflow) + prompt = await self._build_tool_prompt( + message_txt=message_txt, + chat_stream=chat_stream, + observation=observation, + ) # 定义可用工具 tools = self._define_tools() @@ -131,7 +129,6 @@ class ToolUser: payload = { "model": self.llm_model_tool.model_name, "messages": [{"role": "user", "content": prompt}], - "max_tokens": global_config.max_response_length, "tools": tools, "temperature": 0.2, } @@ -156,13 +153,15 @@ class ToolUser: tool_calls_str = "" for tool_call in tool_calls: tool_calls_str += f"{tool_call['function']['name']}\n" - logger.info(f"根据:\n{prompt}\n模型请求调用{len(tool_calls)}个工具: {tool_calls_str}") + logger.info( + f"根据:\n{prompt}\n\n内容：{content}\n\n模型请求调用{len(tool_calls)}个工具: {tool_calls_str}" + ) tool_results = [] structured_info = {} # 动态生成键 # 执行所有工具调用 for tool_call in tool_calls: - result = await self._execute_tool_call(tool_call, message_txt) + result = await self._execute_tool_call(tool_call) if result: tool_results.append(result) # 使用工具名称作为键 @@ -173,7 +172,7 @@ class ToolUser: # 如果有工具结果，返回结构化的信息 if structured_info: - logger.info(f"工具调用收集到结构化信息: {json.dumps(structured_info, ensure_ascii=False)}") + logger.debug(f"工具调用收集到结构化信息: {json.dumps(structured_info, ensure_ascii=False)}") return {"used_tools": True, "structured_info": structured_info} else: # 没有工具调用 @@ -187,6 +186,7 @@ class ToolUser: except Exception as e: logger.error(f"工具调用过程中出错: {str(e)}") + logger.error(f"工具调用过程中出错: {traceback.format_exc()}") return { "used_tools": False, "error": str(e), diff --git a/src/gui/logger_gui.py b/src/gui/logger_gui.py deleted file mode 100644 index ad6edafb8..000000000 --- a/src/gui/logger_gui.py +++ /dev/null @@ -1,378 +0,0 @@ -# import customtkinter as ctk -# import subprocess -# import threading -# import queue -# import re -# import os -# import signal -# from collections import deque -# import sys - -# # 设置应用的外观模式和默认颜色主题 -# ctk.set_appearance_mode("dark") -# ctk.set_default_color_theme("blue") - - -# class LogViewerApp(ctk.CTk): -# """日志查看器应用的主类，继承自customtkinter的CTk类""" - -# def __init__(self): -# """初始化日志查看器应用的界面和状态""" -# super().__init__() -# self.title("日志查看器") -# self.geometry("1200x800") - -# # 标记GUI是否运行中 -# self.is_running = True - -# # 程序关闭时的清理操作 -# self.protocol("WM_DELETE_WINDOW", self._on_closing) - -# # 初始化进程、日志队列、日志数据等变量 -# self.process = None -# self.log_queue = queue.Queue() -# self.log_data = deque(maxlen=10000) # 使用固定长度队列 -# self.available_levels = set() -# self.available_modules = set() -# self.sorted_modules = [] -# self.module_checkboxes = {} # 存储模块复选框的字典 - -# # 日志颜色配置 -# self.color_config = { -# "time": "#888888", -# "DEBUG": "#2196F3", -# "INFO": "#4CAF50", -# "WARNING": "#FF9800", -# "ERROR": "#F44336", -# "module": "#D4D0AB", -# "default": "#FFFFFF", -# } - -# # 列可见性配置 -# self.column_visibility = {"show_time": True, "show_level": True, "show_module": True} - -# # 选中的日志等级和模块 -# self.selected_levels = set() -# self.selected_modules = set() - -# # 创建界面组件并启动日志队列处理 -# self.create_widgets() -# self.after(100, self.process_log_queue) - -# def create_widgets(self): -# """创建应用界面的各个组件""" -# self.grid_columnconfigure(0, weight=1) -# self.grid_rowconfigure(1, weight=1) - -# # 控制面板 -# control_frame = ctk.CTkFrame(self) -# control_frame.grid(row=0, column=0, sticky="ew", padx=10, pady=5) - -# self.start_btn = ctk.CTkButton(control_frame, text="启动", command=self.start_process) -# self.start_btn.pack(side="left", padx=5) - -# self.stop_btn = ctk.CTkButton(control_frame, text="停止", command=self.stop_process, state="disabled") -# self.stop_btn.pack(side="left", padx=5) - -# self.clear_btn = ctk.CTkButton(control_frame, text="清屏", command=self.clear_logs) -# self.clear_btn.pack(side="left", padx=5) - -# column_filter_frame = ctk.CTkFrame(control_frame) -# column_filter_frame.pack(side="left", padx=20) - -# self.time_check = ctk.CTkCheckBox(column_filter_frame, text="显示时间", command=self.refresh_logs) -# self.time_check.pack(side="left", padx=5) -# self.time_check.select() - -# self.level_check = ctk.CTkCheckBox(column_filter_frame, text="显示等级", command=self.refresh_logs) -# self.level_check.pack(side="left", padx=5) -# self.level_check.select() - -# self.module_check = ctk.CTkCheckBox(column_filter_frame, text="显示模块", command=self.refresh_logs) -# self.module_check.pack(side="left", padx=5) -# self.module_check.select() - -# # 筛选面板 -# filter_frame = ctk.CTkFrame(self) -# filter_frame.grid(row=0, column=1, rowspan=2, sticky="ns", padx=5) - -# ctk.CTkLabel(filter_frame, text="日志等级筛选").pack(pady=5) -# self.level_scroll = ctk.CTkScrollableFrame(filter_frame, width=150, height=200) -# self.level_scroll.pack(fill="both", expand=True, padx=5) - -# ctk.CTkLabel(filter_frame, text="模块筛选").pack(pady=5) -# self.module_filter_entry = ctk.CTkEntry(filter_frame, placeholder_text="输入模块过滤词") -# self.module_filter_entry.pack(pady=5) -# self.module_filter_entry.bind("", self.update_module_filter) - -# self.module_scroll = ctk.CTkScrollableFrame(filter_frame, width=300, height=200) -# self.module_scroll.pack(fill="both", expand=True, padx=5) - -# self.log_text = ctk.CTkTextbox(self, wrap="word") -# self.log_text.grid(row=1, column=0, sticky="nsew", padx=10, pady=5) - -# self.init_text_tags() - -# def update_module_filter(self, event): -# """根据模块过滤词更新模块复选框的显示""" -# filter_text = self.module_filter_entry.get().strip().lower() -# for module, checkbox in self.module_checkboxes.items(): -# if filter_text in module.lower(): -# checkbox.pack(anchor="w", padx=5, pady=2) -# else: -# checkbox.pack_forget() - -# def update_filters(self, level, module): -# """更新日志等级和模块的筛选器""" -# if level not in self.available_levels: -# self.available_levels.add(level) -# self.add_checkbox(self.level_scroll, level, "level") - -# module_key = self.get_module_key(module) -# if module_key not in self.available_modules: -# self.available_modules.add(module_key) -# self.sorted_modules = sorted(self.available_modules, key=lambda x: x.lower()) -# self.rebuild_module_checkboxes() - -# def rebuild_module_checkboxes(self): -# """重新构建模块复选框""" -# # 清空现有复选框 -# for widget in self.module_scroll.winfo_children(): -# widget.destroy() -# self.module_checkboxes.clear() - -# # 重建排序后的复选框 -# for module in self.sorted_modules: -# self.add_checkbox(self.module_scroll, module, "module") - -# def add_checkbox(self, parent, text, type_): -# """在指定父组件中添加复选框""" - -# def update_filter(): -# current = cb.get() -# if type_ == "level": -# (self.selected_levels.add if current else self.selected_levels.discard)(text) -# else: -# (self.selected_modules.add if current else self.selected_modules.discard)(text) -# self.refresh_logs() - -# cb = ctk.CTkCheckBox(parent, text=text, command=update_filter) -# cb.select() # 初始选中 - -# # 手动同步初始状态到集合（关键修复） -# if type_ == "level": -# self.selected_levels.add(text) -# else: -# self.selected_modules.add(text) - -# if type_ == "module": -# self.module_checkboxes[text] = cb -# cb.pack(anchor="w", padx=5, pady=2) -# return cb - -# def check_filter(self, entry): -# """检查日志条目是否符合当前筛选条件""" -# level_ok = not self.selected_levels or entry["level"] in self.selected_levels -# module_key = self.get_module_key(entry["module"]) -# module_ok = not self.selected_modules or module_key in self.selected_modules -# return level_ok and module_ok - -# def init_text_tags(self): -# """初始化日志文本的颜色标签""" -# for tag, color in self.color_config.items(): -# self.log_text.tag_config(tag, foreground=color) -# self.log_text.tag_config("default", foreground=self.color_config["default"]) - -# def start_process(self): -# """启动日志进程并开始读取输出""" -# self.process = subprocess.Popen( -# ["nb", "run"], -# stdout=subprocess.PIPE, -# stderr=subprocess.STDOUT, -# text=True, -# bufsize=1, -# encoding="utf-8", -# errors="ignore", -# ) -# self.start_btn.configure(state="disabled") -# self.stop_btn.configure(state="normal") -# threading.Thread(target=self.read_output, daemon=True).start() - -# def stop_process(self): -# """停止日志进程并清理相关资源""" -# if self.process: -# try: -# if hasattr(self.process, "pid"): -# if os.name == "nt": -# subprocess.run( -# ["taskkill", "/F", "/T", "/PID", str(self.process.pid)], check=True, capture_output=True -# ) -# else: -# os.killpg(os.getpgid(self.process.pid), signal.SIGTERM) -# except (subprocess.CalledProcessError, ProcessLookupError, OSError) as e: -# print(f"终止进程失败: {e}") -# finally: -# self.process = None -# self.log_queue.queue.clear() -# self.start_btn.configure(state="normal") -# self.stop_btn.configure(state="disabled") -# self.refresh_logs() - -# def read_output(self): -# """读取日志进程的输出并放入队列""" -# try: -# while self.process and self.process.poll() is None and self.is_running: -# line = self.process.stdout.readline() -# if line: -# self.log_queue.put(line) -# else: -# break # 避免空循环 -# self.process.stdout.close() # 确保关闭文件描述符 -# except ValueError: # 处理可能的I/O操作异常 -# pass - -# def process_log_queue(self): -# """处理日志队列中的日志条目""" -# while not self.log_queue.empty(): -# line = self.log_queue.get() -# self.process_log_line(line) - -# # 仅在GUI仍在运行时继续处理队列 -# if self.is_running: -# self.after(100, self.process_log_queue) - -# def process_log_line(self, line): -# """解析单行日志并更新日志数据和筛选器""" -# match = re.match( -# r"""^ -# (?:(?P