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Author SHA1 Message Date
dependabot[bot]andGitHub 0475251b76 build(deps): bump websockets from 14.2 to 16.0 in /main/xiaozhi-server
Bumps [websockets](https://github.com/python-websockets/websockets) from 14.2 to 16.0.
- [Release notes](https://github.com/python-websockets/websockets/releases)
- [Commits](https://github.com/python-websockets/websockets/compare/14.2...16.0)

---
updated-dependencies:
- dependency-name: websockets
  dependency-version: '16.0'
  dependency-type: direct:production
  update-type: version-update:semver-major
...

Signed-off-by: dependabot[bot] <support@github.com>
2026-05-11 11:43:31 +00:00
wengzhandGitHub 1b5c00231a Merge pull request #3165 from xinnan-tech/fix-chat-total
fix: 修复聊天记录左侧会话数量统计
2026-05-09 15:56:05 +08:00
zhuoqinglian 95acba1126 fix: 修复聊天记录左侧会话数量统计 2026-05-09 15:54:53 +08:00
wengzhandGitHub 1e6f0fd1be Merge pull request #3162 from xinnan-tech/perf-tool-call-optimization
fix:修复音乐播放工具TTS上报记录问题
2026-05-08 16:40:37 +08:00
DaGou12138 eb571fae57 fix:修复音乐播放工具TTS上报记录问题 2026-05-08 16:38:23 +08:00
wengzhandGitHub 2946be7284 Merge pull request #3161 from xinnan-tech/perf-tool-call-optimization
fix:优化天气工具调用提示词
2026-05-08 14:23:11 +08:00
DaGou12138 425cb1d6bd fix:优化天气工具调用提示词,本地上下文存在当前所在地的天气信息无需再度查询工具 2026-05-08 14:20:52 +08:00
wengzhandGitHub cf9b0ec712 Merge pull request #3160 from xinnan-tech/fix-chat-title
fix: 修复聊天记录标题过长展示异常的问题
2026-05-08 11:08:23 +08:00
zhuoqinglian 1b053dc9c8 fix: 修复聊天记录标题过长展示异常的问题 2026-05-08 11:05:20 +08:00
wengzhandGitHub d7ad656bd0 Merge pull request #3159 from xinnan-tech/perf-tool-call-optimization
fix:优化对话过程中JSON闭合符号清理的问题
2026-05-08 10:48:58 +08:00
DaGou12138 7dae67a57b fix:优化对话过程中JSON闭合符号清理的问题 2026-05-08 10:46:37 +08:00
wengzhandGitHub 7b0f59a747 Merge pull request #3158 from xinnan-tech/chore/cleanup
chore: 暂时移除近期不可用或不稳定的TTS供应器及相关配置
2026-05-08 10:38:53 +08:00
DaGou12138 2eaa5bbb11 fix:优化对话过程中异常符号记录的问题 2026-05-08 10:29:50 +08:00
FAN-yeB c693ff1564 update:linkerai 近期多次测试,linkerai接口无法提供稳定服务,先暂时下架这个供应器 2026-05-08 10:18:26 +08:00
DaGou12138andGitHub e9bf006d9d Merge pull request #3154 from haixinke/Bug-get-user-prifile-null
fix:当打开用户画像开关时,修复获取用户画像为空的问题
2026-05-07 16:01:57 +08:00
wengzhandGitHub bef96f36e2 Merge pull request #3157 from xinnan-tech/fix-streaming-tts-original-text
Fix streaming tts original text
2026-05-07 15:36:56 +08:00
wengzhandGitHub bebb7eac69 Merge pull request #3156 from xinnan-tech/perf-tool-call-optimization
perf:优化新闻工具新闻源配置获取的逻辑
2026-05-07 11:43:17 +08:00
DaGou12138 a787130b74 perf:
1、优化新闻工具新闻源获取的逻辑
2、调整新闻工具描述内容
2026-05-07 11:41:17 +08:00
FAN-yeB 8b7f16b9c2 update:TTS_GizwitsTTS 近期机智云语音合成不成功,先暂时下架这个供应器 2026-05-07 11:27:32 +08:00
FAN-yeB 9ed66ec013 update:TTS_ACGNTTS 海豚配音截止5月7日未找到token入口,先暂时下架这个供应器 2026-05-07 10:54:03 +08:00
FAN-yeB 05c22cdf2a update:更新 .gitignore忽略.claude目录 2026-05-07 10:23:02 +08:00
FAN-yeB 4bc0b67cd7 update:去除无用的.claude目录 2026-05-07 10:20:48 +08:00
Sakura-RanChen 0a6f811448 fix: 修复流式情况下替换词失败 2026-05-07 10:20:10 +08:00
wengzhandGitHub 5aeb55fffd Merge pull request #3155 from xinnan-tech/perf-tool-call-optimization
perf:优化工具调用问题、调整后端智能体搜索条件逻辑
2026-05-06 17:01:15 +08:00
DaGou12138 c33ee9442e perf:
1、优化小智后端智能体搜索条件逻辑
2、优化工具调用准确率问题,修改工具提示词,去除非必要的few-shot逻辑
3、优化工具描述内容
2026-05-06 16:53:06 +08:00
minwang 4670ad2925 delete log 2026-05-01 16:03:02 +08:00
minwangandClaude Sonnet 4.6 b542388053 🐛 修复PowerMem用户画像查询返回空的问题
修复 get_user_profile() 方法在缓存未命中时主动从 SDK 获取用户画
像,支持 profile_content 和 topics 两种格式,解决新对话中用户画像无法显示的问题

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-05-01 14:57:36 +08:00
rainv123 a71ce53a68 fix:修复使用替换词时,火山引擎双向流式tts的文本显示/上报问题 2026-04-30 17:33:40 +08:00
rainv123 dd88107131 Revert "fix: 修复流式TTS替换词显示/上报问题"
This reverts commit 8b847a3826.
2026-04-30 15:57:03 +08:00
rainv123 8b847a3826 fix: 修复流式TTS替换词显示/上报问题 2026-04-30 14:32:36 +08:00
wengzhandGitHub 036b89f24e Merge pull request #3151 from xinnan-tech/py-refactor-asr-tts
调整配置
2026-04-30 11:42:36 +08:00
Sakura-RanChen 354280d430 调整配置 2026-04-30 11:41:16 +08:00
hrzandGitHub e2d16ec8d4 Merge pull request #3150 from Mirrorium227/main
Closes #Issue3149 修复文档序号
2026-04-30 11:27:15 +08:00
Radar SongandGitHub 6a0192de27 Closes #Issue3149 修复文档序号 2026-04-29 20:18:17 +08:00
hrzandGitHub ac6eeb5c1f Merge pull request #3145 from haixinke/fix-bug_prompt_cache_key_wrong
Fix:【设备快速提示词缓存key错误】
2026-04-29 14:32:42 +08:00
minwang 23e213f6ea 修复设备快速提示词缓存key错误 2026-04-28 15:52:23 +08:00
wengzhandGitHub 382c948482 Merge pull request #3144 from xinnan-tech/fix-memory-config
fix:修复记忆模型配置保存字段未删除问题
2026-04-28 15:25:49 +08:00
DaGou12138 a67d938523 fix:修复记忆模型配置保存字段未删除问题 2026-04-28 15:23:57 +08:00
wengzhandGitHub 26aca54f4b Merge pull request #3141 from xinnan-tech/add-correct-word
fix修复 asyncio.gather 吞掉业务异常的问题
2026-04-27 17:31:47 +08:00
rainv123 4717b8beac fix修复 asyncio.gather 吞掉业务异常的问题 2026-04-27 17:29:41 +08:00
wengzhandGitHub cd580b6f81 Merge pull request #3139 from xinnan-tech/py-fix-mem0ai
fix: 修复Mem0AI记忆模式工具调用时保存记忆400错误
2026-04-27 16:57:26 +08:00
3030332422 70740af7a6 fix: 修复Mem0AI记忆模式工具调用时保存记忆400错误 2026-04-27 16:25:05 +08:00
wengzhandGitHub 7b30c25923 Merge pull request #3132 from xinnan-tech/replacement-word
feat: 新增替换词管理功能
2026-04-27 16:23:54 +08:00
wengzhandGitHub 7db13b8be2 Merge pull request #3130 from xinnan-tech/add-correct-word
add:替换词功能
2026-04-27 16:23:33 +08:00
wengzhandGitHub a0df41ac24 Merge pull request #3136 from xinnan-tech/performance_tester
update:解决base类修改后测速工具兼容性问题
2026-04-27 15:08:26 +08:00
FAN-yeB a432c295d3 update:解决base类修改后测速工具兼容性问题 2026-04-27 15:06:40 +08:00
wengzhandGitHub ab8a35e233 Merge pull request #3135 from xinnan-tech/perf-tool-call-optimization
Perf:优化工具调用准确性、禁用标题总结与记忆模型思考模式、拆分动态上下文
2026-04-27 14:54:16 +08:00
DaGou12138 160b67197f Merge branch 'refs/heads/main' into perf-tool-call-optimization 2026-04-27 14:23:28 +08:00
欣南科技andGitHub 3510282cd5 Merge pull request #3134 from xinnan-tech/0.9.3
Bump to 0.9.3
2026-04-27 12:46:10 +08:00
hrz bdf7c7facf Bump to 0.9.3 2026-04-27 12:44:02 +08:00
DaGou12138 151a0c1b99 perf:
1、优化工具调用相关提示词,拆分静态system-prompt和动态上下文。
2、新增few-shot示例,使用"调用→结果→回复"流程闭环,显著提高多次会话后工具调用准确性。
3、去除对话标题总结和记忆的模型思考模式。
2026-04-27 11:08:25 +08:00
zhuoqinglian 52af722463 update: 更新替换词数量限制 2026-04-24 14:54:37 +08:00
wengzhandGitHub fa91c97685 Merge pull request #3131 from xinnan-tech/fix-wifi-no-response
fix: 修复设备配网成功没有自动退出配网模式
2026-04-24 14:38:06 +08:00
zhuoqinglian a92d6ccdfb fix: 修复设备配网成功没有自动退出配网模式 2026-04-24 14:35:34 +08:00
zhuoqinglianandGitHub f5ce755fea Merge pull request #3116 from wujingquan/main
Add WiFi password translations for multiple languages
2026-04-24 14:15:27 +08:00
rainv123 606a42cfb2 update:替换词功能 2026-04-24 10:06:26 +08:00
zhuoqinglian f85e863144 feat: 新增替换词管理功能 2026-04-23 17:50:57 +08:00
wengzhandGitHub 550397de98 Merge pull request #3127 from xinnan-tech/py-fix-asr
Py fix asr
2026-04-23 10:46:09 +08:00
Sakura-RanChen ff66b815a5 fix: 在模型和工具调用期间进行打断后说完话错误退出问题 2026-04-23 10:17:43 +08:00
Sakura-RanChen 8c18e48b97 fix: 停止帧发送后与原先音频时序问题
回退退出工具打断处理(在大模型思考期间进行打断,然后大模型立马调用退出工具会造成死锁,因模型思考时间和是否调用工具不确定性,状态难管理)
2026-04-22 15:55:28 +08:00
wengzhandGitHub 4acd02e2b0 Merge pull request #3125 from xinnan-tech/py-fix-llm-chunk
fix: 修复频繁打断下生成器不会清理
2026-04-22 11:30:35 +08:00
wengzhandGitHub ddfbacc717 Merge pull request #3124 from xinnan-tech/py-add-ASRv2
使用双流优化版接口(速度提升),增加豆包流式语音识别模型2.0模型选择
2026-04-22 11:29:57 +08:00
Sakura-RanChen 2a4dbdb69b fix: 修复频繁打断下生成器不会清理 2026-04-22 11:24:43 +08:00
FAN-yeB e9a2489e48 update:测试工具更新豆包流式测试逻辑 2026-04-22 10:53:48 +08:00
Sakura-RanChen ce13a7e3e6 使用双流优化版接口(速度提升),增加豆包流式语音识别模型2.0模型选择 2026-04-22 10:28:47 +08:00
wengzhandGitHub 8a156e99f4 Merge pull request #3122 from xinnan-tech/py-add-TTS2.0
增加豆包语音合成模型2.0专属供应器
2026-04-21 15:44:04 +08:00
Sakura-RanChen 4313216816 增加豆包语音合成模型2.0专属供应器 2026-04-21 15:33:37 +08:00
DaGou12138 8c0899415a Merge branch 'refs/heads/main' into perf-tool-call-optimization 2026-04-21 15:02:31 +08:00
DaGou12138 3736a5845a perf:
1、优化提示词context动态变化导致的缓存失效问题,拆分静态system-prompt和动态上下文
2026-04-21 15:01:57 +08:00
wengzhandGitHub dc7615c008 Merge pull request #3120 from xinnan-tech/update-theme-generator
update: 更新设备主题生成功能,添加新表情
2026-04-21 14:50:53 +08:00
wengzhandGitHub b03f9374ea Merge pull request #3119 from xinnan-tech/fix-config-slm
feat: agent-models接口返回SLM模型,LLM类型同步返回所选SLM
2026-04-21 14:18:07 +08:00
欣南科技andGitHub cacfc9bfee Merge pull request #3121 from xinnan-tech/enhanced-prompts
update:优化提示词
2026-04-21 14:01:49 +08:00
hrz ce3c8a2bd8 update:优化提示词 2026-04-21 14:00:25 +08:00
zhuoqinglian e1a7e50e1f update: 更新设备主题生成功能,添加新表情 2026-04-21 11:44:03 +08:00
DaGou12138 90888de0ba perf:
1、新增工具调用Action枚举RECORD,通过完整的三段式 assistant(tool_calls) → tool → assistant(response)让模型准确学习到工具调用的正确行为,优化play_music的工具调用枚举NONE变更为RECORD,优化解决音乐播放工具调用缺陷问题。
2、处理悬空 tool_calls问题。
3、去除工具提示词强化注入逻辑。
2026-04-21 11:36:06 +08:00
rainv123 ad4d32a05d feat: agent-models接口返回SLM模型,LLM类型同步返回所选SLM 2026-04-21 11:12:18 +08:00
hrzandGitHub 08d6bb4056 Merge pull request #3118 from xinnan-tech/openai_nothinking
feat:默认禁用部分平台LLM思考模式
2026-04-20 17:39:20 +08:00
FAN-yeB 1f0db7dc47 feat:默认禁用部分平台LLM思考模式 2026-04-20 17:35:32 +08:00
wengzhandGitHub 6f52d004e8 Merge pull request #3115 from xinnan-tech/fix-knowledge-sync-ragflow-documents
fix: 实现知识库与RAGFlow双向同步(知识库名称/简介的修改、知识库删除、文档上传/删除)
2026-04-20 16:51:06 +08:00
rainv123 0681550bab fix: 实现知识库与RAGFlow双向同步(知识库名称/简介的修改、知识库删除、文档上传/删除),移除冷却机制确保实时生效,修复文档影子表UNIQUE约束冲突 2026-04-20 16:49:24 +08:00
wengzhandGitHub 97b9c95c2d Merge pull request #3117 from xinnan-tech/py-fix-ReportTime
fix: 修复聊天记录上报排序错乱的问题
2026-04-20 15:56:49 +08:00
wujingquan 6111c3b5a0 Add 'configuring' translation for multiple languages in device configuration 2026-04-20 15:24:53 +08:00
wujingquan 123c1e8880 Add WiFi password translations for multiple languages 2026-04-20 15:17:04 +08:00
rainv123 6ce4503b22 fix:实现知识库文档与RAGFlow双向同步,支持远端上传/删除自动对账 2026-04-20 14:49:01 +08:00
3030332422 b209de36f5 fix: 修复聊天记录上报排序错乱的问题 2026-04-20 11:00:04 +08:00
wengzhandGitHub fc3e0869fd Merge pull request #3112 from xinnan-tech/py-fix-repeated-text
Py fix repeated text
2026-04-20 10:43:09 +08:00
Sakura-RanChen 3436d50b43 只有文本内容一致的时候不进行合成 2026-04-20 10:40:08 +08:00
Sakura-RanChenandGitHub 7a58c04df3 Merge pull request #3077 from xuruiray/fix/duplicate-tts-on-tool-call
fix: LLM 流式输出文本后调用工具导致 TTS 重复播报
2026-04-20 10:08:06 +08:00
Sakura-RanChenandGitHub 150be65436 Merge branch 'py-fix-repeated-text' into fix/duplicate-tts-on-tool-call 2026-04-20 10:07:28 +08:00
wengzhandGitHub bacf4cd5e8 Merge pull request #3110 from xinnan-tech/fix_rag_pagerank
fix: 修复更新知识库时 pagerank 为 null 导致 RAGFlow 校验失败的问题
2026-04-17 16:52:02 +08:00
rainv123 7049e8cce7 fix: 修复更新知识库时 pagerank 为 null 导致 RAGFlow 校验失败的问题 2026-04-17 16:41:42 +08:00
wengzhandGitHub 61f137ce4b Merge pull request #3108 from xinnan-tech/fix-role-plugin
fix: 修复智能体tooltip高度超长的问题
2026-04-17 11:25:14 +08:00
zhuoqinglian 35ea14b95b fix: 修复智能体tooltip高度超长的问题 2026-04-17 11:10:33 +08:00
wengzhandGitHub b7d07f92a2 Merge pull request #3107 from xinnan-tech/py-fix-tts-markdown
fix: 调整处理顺序保留英文空格的同时修复markdown被识别为纯ASCII 字符的错误返回
2026-04-17 11:02:53 +08:00
Sakura-RanChen d2cbec0981 fix: 调整处理顺序保留英文空格的同时修复markdown被识别为纯ASCII 字符的错误返回 2026-04-17 10:59:29 +08:00
wengzhandGitHub 6348f12d60 Merge pull request #3106 from xinnan-tech/fix-role-plugin
fix: 修复角色配置-功能管理列表没有滚动条的问题
2026-04-17 10:51:45 +08:00
zhuoqinglian 11caf6bc8a fix: 修复角色配置-功能管理列表没有滚动条的问题 2026-04-17 10:42:47 +08:00
wengzhandGitHub 3cae9e3c32 Merge pull request #3102 from xinnan-tech/fix-title-summary
fix:将标题总结从记忆流程中拆分为独立接口,支持异步执行
2026-04-16 17:24:56 +08:00
欣南科技andGitHub 0161e642d0 Merge pull request #3104 from xinnan-tech/update-default-model
Update default model
2026-04-16 17:01:34 +08:00
hrz d41938fe07 update:这些文件已经完成使命,可移除 2026-04-16 16:54:33 +08:00
hrz e20c59e3df update:移除阿里云即将下架的模型 2026-04-16 16:42:34 +08:00
rainv123 fbaf28de5c fix:移除多余try和总结标题的异步 2026-04-16 14:43:16 +08:00
rainv123 2daf492e00 fix:将标题总结从记忆流程中拆分为独立接口,支持异步执行 2026-04-16 10:36:48 +08:00
wengzhandGitHub ac9083cfc7 Merge pull request #3101 from xinnan-tech/fix-title-summary
fix:修复PowerMem和Mem0AI记忆模型不会总结会话标题的问题
2026-04-16 09:04:58 +08:00
rainv123 f36e605aed fix:修复PowerMem和Mem0AI记忆模型不会总结会话标题的问题 2026-04-15 15:26:52 +08:00
wengzhandGitHub c1b836aaed Merge pull request #3100 from xinnan-tech/update-checkbox-style
update: 修改checkbox背景颜色
2026-04-15 14:32:46 +08:00
zhuoqinglian 07170f09eb update: 修改checkbox背景颜色 2026-04-15 14:28:20 +08:00
hrzandGitHub 8211de242f Merge pull request #3098 from xinnan-tech/fix-title-summary
fix:修复mem_report_only记忆模型没有总结会话标题
2026-04-15 14:20:34 +08:00
欣南科技andGitHub eea6807355 Merge pull request #3099 from xinnan-tech/agent-base-prompt
update:优化提示词
2026-04-15 13:59:04 +08:00
hrz 0ba7e81438 update:优化提示词 2026-04-15 12:59:15 +08:00
rainv123 703c707b4c fix:修复mem_report_only记忆模型没有总结会话标题 2026-04-15 11:54:22 +08:00
hrzandGitHub 3ab14578c2 Merge pull request #3097 from xinnan-tech/py-fix-stream-asr
fix: 修复豆包流式asr热词层级错误
2026-04-15 10:33:24 +08:00
Sakura-RanChen a15efa3090 fix: 修复豆包流式asr热词层级错误 2026-04-15 10:31:16 +08:00
wengzhandGitHub 8af8930997 Merge pull request #3094 from xinnan-tech/py-client-about
refactor:优化相关打断逻辑
2026-04-14 15:31:29 +08:00
Sakura-RanChen ad01b05940 打断判断优先级调整 2026-04-14 15:05:55 +08:00
Sakura-RanChen a0497fdc48 给复用型TTS增加相关过滤 2026-04-14 10:18:09 +08:00
Sakura-RanChen 9634f84a98 Merge remote-tracking branch 'origin/main' into py-client-about 2026-04-13 11:35:10 +08:00
Sakura-RanChen 27e5e1e9d7 refactor: 优化非流式音频过滤机制
fix: 修复等待中被打断队列被停止造成的死锁
2026-04-13 11:33:47 +08:00
wengzhandGitHub 8fd92729f2 Merge pull request #3090 from xinnan-tech/slm-and-title
update:添加SLM模型配置和会话标题功能
2026-04-13 09:08:11 +08:00
wengzhandGitHub 736ffd80bf Merge pull request #3086 from xinnan-tech/update-chat-history
角色配置表单标题添加Tooltip鼠标悬浮提示说明,调整小参数模型表单配置
2026-04-13 09:07:50 +08:00
wengzhandGitHub 3783351f5d Merge pull request #3085 from xinnan-tech/update-mobile-chat-history
mobile 角色配置添加小参数模型选项,历史记录标题优化,聊天详情参数记录折叠处理
2026-04-13 09:07:31 +08:00
zhuoqinglian 2cd9484c54 update: mobile 聊天记录获取最新数据 2026-04-10 16:11:04 +08:00
Sakura-RanChen 0f1e0d0d2e 音频会在队列积压等待发送,等待协程结果返回不设置超时时间 2026-04-10 14:22:36 +08:00
Sakura-RanChen 0e23672be7 fix: 修复直接回复是字幕未记录 2026-04-09 17:58:19 +08:00
Sakura-RanChen a6904f6ebd refactor: vad独立时间戳,相关残余状态处理 2026-04-09 17:15:35 +08:00
zhuoqinglian 784ba359f2 update: mobile 历史记录标题优化,聊天详情参数记录折叠处理 2026-04-09 14:32:32 +08:00
Sakura-RanChen e08eb48d9a refactor: 优化相关打断处理 2026-04-09 10:46:46 +08:00
rainv123 b9a1b154b7 update:添加SLM模型配置和会话标题功能 2026-04-09 09:23:54 +08:00
zhuoqinglian 64630e1b4e feat: mobile 角色配置添加小参数模型选项 2026-04-08 16:26:48 +08:00
zhuoqinglian 7dcc014ce4 update: 调整小参数模型表单配置 2026-04-08 11:41:12 +08:00
Rui Xu 389e8559aa fix: prevent duplicate TTS when LLM streams text before tool call 2026-04-06 21:49:28 +08:00
wengzhandGitHub c5f82369e5 Merge pull request #3060 from xinnan-tech/py_test_end
Py test end
2026-04-03 17:31:56 +08:00
wengzhandGitHub 52e63706a4 Merge pull request #3058 from xinnan-tech/py_fix_powermem
fix: 优化配置读取
2026-04-03 14:37:14 +08:00
Sakura-RanChenandGitHub a42a8b2b4b Merge pull request #3069 from xinnan-tech/py_fix_wakeup
fix:停止音频发送循环(仅在流控器已初始化时调用)
2026-04-03 09:48:16 +08:00
baigao 11142104af fix:停止音频发送循环(仅在流控器已初始化时调用) 2026-04-03 09:46:55 +08:00
wengzhandGitHub a9f5f1ab81 Merge pull request #3067 from xinnan-tech/memory-model-rename
fix:从有总结记忆的模型切换至仅上报聊天记录时,只清空记忆总结内容
2026-04-02 11:56:33 +08:00
rainv123 a8f68c42fc fix:从有总结记忆的模型切换至仅上报聊天记录时,只清空记忆 2026-04-02 11:27:11 +08:00
zhuoqinglian 1d3afb3c9a feat: 角色配置表单标题添加Tooltip鼠标悬浮提示说明 2026-04-02 09:45:33 +08:00
wengzhandGitHub 943622969a Merge pull request #3063 from xinnan-tech/py-bug-fix
fix:修复intent_llm模式下工具不存在时未正确播放提示信息的问题
2026-04-01 17:46:23 +08:00
wengzhandGitHub 9d39168a35 Merge pull request #3061 from xinnan-tech/memory-model-rename
选择仅上报聊天记录时,清除历史记忆;前端优化记忆模型切换体验
2026-04-01 15:57:44 +08:00
Sakura-RanChenandGitHub 61ab7f25d7 Merge branch 'main' into py_test_end 2026-04-01 14:45:05 +08:00
Sakura-RanChen 140fcd5887 补充sql,增加错误详情上报 2026-04-01 14:32:47 +08:00
rainv123 3c2024d00d fix: 前端优化记忆模型切换体验 - 切换无记忆模型时暂存记忆、切换恢复、保存配置后才真正清除 2026-04-01 14:32:30 +08:00
rainv123 2aee1bf567 fix:选择仅上报聊天记录时,清除历史记忆 2026-04-01 11:35:26 +08:00
wengzhandGitHub d89a26889c Merge pull request #3059 from xinnan-tech/memory-model-rename
fix:重命名记忆模型名称
2026-04-01 10:23:38 +08:00
rainv123 d611b2db73 update:重命名记忆模型名称 2026-04-01 09:54:46 +08:00
Sakura-RanChenandGitHub b0e911b248 Merge pull request #2996 from lgy1027/fix-end
fix: 优化退出流程并添加超时保护
2026-04-01 09:35:34 +08:00
Sakura-RanChenandGitHub fb3b7830ee Merge branch 'py_test_end' into fix-end 2026-04-01 09:35:23 +08:00
3030332422 10eeffdf31 fix:修复intent_llm模式下工具不存在时未正确播放提示信息的问题 2026-04-01 09:23:05 +08:00
rainv123 17847188dd Merge branch 'main' of https://github.com/xinnan-tech/xiaozhi-esp32-server into new 2026-04-01 09:12:39 +08:00
Sakura-RanChen 7b2bfc087d fix: 优化配置读取 2026-03-31 18:00:51 +08:00
wengzhandGitHub 24a8839753 Merge pull request #3044 from xinnan-tech/py-display
添加“工具调用日志记录”与“设备端工具调用信息显示”
2026-03-31 15:12:11 +08:00
CGDandGitHub 64d25533d9 Merge branch 'main' into py-display 2026-03-31 14:24:27 +08:00
3030332422 6f6c788cd5 update:修改ai_agent_chat_history表content字段类型为TEXT 2026-03-31 14:11:31 +08:00
欣南科技andGitHub 8aa12d0961 Merge pull request #3057 from xinnan-tech/weather-faq
update:补齐天气文档链接
2026-03-31 12:11:36 +08:00
hrz d770632152 udpate:补齐天气文档链接 2026-03-31 12:08:30 +08:00
wengzhandGitHub a30903b644 Merge pull request #3056 from xinnan-tech/update-manager-mobile
Update manager mobile
2026-03-31 11:02:40 +08:00
wengzhandGitHub 5469168d18 Merge pull request #3055 from xinnan-tech/fix-digital-human
fix: 修复数字人摄像头展示区域裁剪的问题
2026-03-31 11:02:21 +08:00
zhuoqinglian 3c31231781 fix: 修复数字人摄像头展示区域裁剪的问题 2026-03-31 10:34:38 +08:00
3030332422 cc2e30205f fix:修复play_music工具调用信息显示异常 2026-03-31 10:03:50 +08:00
3030332422 f01de027cd fix:修复 intent_llm 模式下工具调用不上报的问题 2026-03-30 16:36:30 +08:00
zhuoqinglian fb195fc57b update: mobile 切换记忆模式判断是否需要禁用历史记忆内容输入 2026-03-26 17:25:44 +08:00
zhuoqinglian cc504fe542 update: mobile 添加智能体限制调整 2026-03-26 14:21:03 +08:00
wengzhandGitHub fd93116d69 Merge pull request #3045 from xinnan-tech/fix_audioRateController
fix: 修复流式场景下的误判
2026-03-25 11:10:42 +08:00
Sakura-RanChen 5622a13735 fix: 修复流式场景下的误判 2026-03-25 11:07:43 +08:00
3030332422 079c8630d9 update:修改部分前端样式 2026-03-25 10:43:45 +08:00
wengzhandGitHub 11830b2f22 Merge pull request #3043 from xinnan-tech/update-manager-mobile
mobile 优化聊天记录音频播放功能
2026-03-25 09:34:29 +08:00
wengzhandGitHub 861b4dee4c Merge pull request #3042 from xinnan-tech/update-web-style
优化页面主体内容区域适配
2026-03-25 09:34:06 +08:00
zhuoqinglian 603fa67824 Merge branch 'main' into update-web-style 2026-03-25 09:27:30 +08:00
zhuoqinglian 4d8279d916 update: 优化页面主体内容区域适配 2026-03-25 09:26:33 +08:00
rainv123 f91c4acb8f Merge branch 'main' of https://github.com/xinnan-tech/xiaozhi-esp32-server into new 2026-03-24 11:12:32 +08:00
rainv123andGitHub 1342eccf86 Merge pull request #3039 from xinnan-tech/revert-3038-agent-chat-history-audio-retention
Revert "fix:修复智能体记忆模型配置变更时错误删除历史聊天音频的问题"
2026-03-24 11:08:44 +08:00
wengzhandGitHub 87f9ab7bb4 Revert "fix:修复智能体记忆模型配置变更时错误删除历史聊天音频的问题" 2026-03-24 11:05:35 +08:00
wengzhandGitHub 94cc8564aa Merge pull request #3038 from xinnan-tech/agent-chat-history-audio-retention
fix:修复智能体记忆模型配置变更时错误删除历史聊天音频的问题
2026-03-24 10:53:51 +08:00
rainv123 8fc2d05c99 Merge branch 'main' of https://github.com/xinnan-tech/xiaozhi-esp32-server into new 2026-03-24 09:51:14 +08:00
rainv123 1a6d9d7490 fix: 修复智能体配置变更时错误删除历史音频的问题 2026-03-24 09:49:57 +08:00
wengzhandGitHub 6c19f1bd26 Merge pull request #3035 from xinnan-tech/mem_report_only
fix:新增仅上报聊天记录的记忆模型供应器Mem report only
2026-03-24 09:01:31 +08:00
rainv123 6d89ae1c66 fix:增加仅上报模型说明和记忆模型排序 2026-03-23 16:58:51 +08:00
rainv123 2a49f0804c feat:新增仅上报聊天记录(mem_report_only)记忆供应器 2026-03-23 16:17:38 +08:00
zhuoqinglian d64bb36606 update: mobile 优化聊天记录音频播放功能 2026-03-23 14:18:53 +08:00
zhuoqinglian 852e097e0d fix: mobile 修复声纹管理-编辑模式下声纹向量展示异常的问题 2026-03-20 16:57:02 +08:00
zhuoqinglian 3aecb99f70 fix: 修复聊天记录播放音频重叠播放的问题 2026-03-20 16:21:58 +08:00
wengzhandGitHub 6eecf5d0cb Merge pull request #3026 from xinnan-tech/fix_audioRateController_state
fix: 修复队列恢复时音频播放时间错乱问题
2026-03-20 14:49:42 +08:00
wengzhandGitHub a4d02ca2ab Merge pull request #3029 from xinnan-tech/update-web-style
解决登录失败验证码刷新两次的问题
2026-03-20 14:48:45 +08:00
wengzhandGitHub 7ef5a67119 Merge pull request #3028 from xinnan-tech/update-manager-mobile
mobile 智能体管理多语言调整、缓存用户信息
2026-03-20 14:48:26 +08:00
zhuoqinglian 1c5dacd2d5 Merge branch 'main' into update-web-style 2026-03-20 14:45:50 +08:00
zhuoqinglian 7732b7b1b9 update: mobile 缓存用户信息 2026-03-20 14:42:47 +08:00
zhuoqinglian 6e7b938f51 fix: 解决登录失败验证码刷新两次的问题 2026-03-20 10:42:35 +08:00
zhuoqinglian 52f5859b1f update: mobile 智能体管理多语言调整 2026-03-19 17:56:27 +08:00
Sakura-RanChen 73d174bc4a fix: 修复队列恢复时音频播放时间错乱问题 2026-03-19 16:18:30 +08:00
Sakura-RanChen 9512fe642c 恢复多工具 2026-03-19 16:04:14 +08:00
Sakura-RanChen 0ef3a60a4c 调整缩进 2026-03-19 11:57:40 +08:00
Sakura-RanChen f40dc4a658 修复双重回复问题 2026-03-19 11:56:29 +08:00
wengzhandGitHub 4747e54f6c Merge pull request #3023 from xinnan-tech/update-manager-mobile
mobile 播放声纹弹窗样式调整,切换角色模板更新表单状态
2026-03-18 16:53:54 +08:00
wengzhandGitHub 9278fdb016 Merge pull request #3024 from xinnan-tech/update-web-style
解决MCP接入点输入框没有显示报错信息的问题
2026-03-18 16:53:14 +08:00
zhuoqinglian 5b23804954 Merge branch 'main' into update-manager-mobile 2026-03-18 16:50:29 +08:00
zhuoqinglian b2ed5eb2c0 fix: 解决MCP接入点输入框没有显示报错信息的问题 2026-03-18 16:47:48 +08:00
zhuoqinglian 07113dc4d2 update: mobile 播放声纹弹窗样式调整,切换角色模板更新表单状态 2026-03-18 16:44:27 +08:00
Sakura-RanChen 1a5dd2d9d9 fix: 修复日志音频上报 2026-03-18 16:40:32 +08:00
wengzhandGitHub 8a01432e9d Merge pull request #3022 from xinnan-tech/perf-userLanguage-complete
perf:补充MCP接入点国际化信息
2026-03-18 15:48:57 +08:00
DaGou12138 7a39fd0152 补充MCP接入点国际化信息 2026-03-18 09:48:11 +08:00
Sakura-RanChen 0d2cb7b3c9 增加工具调用日志记录,暂时单工具状态 2026-03-17 16:13:35 +08:00
wengzhandGitHub 9123a174da Merge pull request #3020 from xinnan-tech/update-web-style
优化表格底部按钮边距统一调整,修复刷新页面菜单、页脚闪动的问题
2026-03-17 16:11:54 +08:00
zhuoqinglian 2e165747d6 update: 参数弹窗去掉多余代码 2026-03-17 16:08:36 +08:00
zhuoqinglian 3bdf634e37 Merge branch 'main' into update-web-style 2026-03-17 16:04:22 +08:00
zhuoqinglian 20ac6f3f96 fix: 修复刷新页面菜单、页脚闪动的问题 2026-03-17 16:01:10 +08:00
zhuoqinglian 818ac1eefb style: 表格底部按钮边距统一调整 2026-03-17 10:30:43 +08:00
3030332422 980930cd42 update:在设备端显示工具调用信息 2026-03-16 13:11:45 +08:00
wengzhandGitHub 956ae37e56 Merge pull request #3015 from xinnan-tech/fix/update-sherpa-onnx
update:更新sherpa_onnx依赖至1.12.29版本
2026-03-16 11:51:01 +08:00
rainv123 15731892ad update:更新sherpa_onnx依赖至1.12.29版本 2026-03-16 11:43:07 +08:00
zhuoqinglian d6d50e0432 fix: 修复语言切换接口请求异常的问题 2026-03-16 10:37:47 +08:00
zhuoqinglian 286079c93a feat: 添加声纹管理-声纹向量音频播放功能 2026-03-16 09:50:24 +08:00
zhuoqinglian 860cbc36fd fix: 处理智能体管理全局触发下拉刷新问题 2026-03-16 09:46:43 +08:00
欣南科技andGitHub 2ac7e5be9c Merge pull request #3013 from xinnan-tech/version-num
Bump to 0.9.2
2026-03-14 08:06:31 +08:00
hrz ebfcfe148d Bump to 0.9.2 2026-03-14 08:05:57 +08:00
wengzhandGitHub 435860d339 Merge pull request #3011 from xinnan-tech/perf-userLanguage-pt-br
perf:新增葡萄牙语国际化提示
2026-03-13 17:56:46 +08:00
DaGou12138 b7cb97a373 新增葡萄牙语国际化提示 2026-03-13 17:53:07 +08:00
wengzhandGitHub e7b1daf021 Merge pull request #3010 from xinnan-tech/perf-llm-lazy-optimization
perf:优化提示词与工具调用偷懒逻辑
2026-03-13 17:28:17 +08:00
DaGou12138 bbf2febd6d 修改标签国际化相关提示词 2026-03-13 17:13:22 +08:00
DaGou12138 586520f321 Merge branch 'refs/heads/main' into perf-llm-lazy-optimization 2026-03-13 17:03:28 +08:00
wengzhandGitHub 22262be7cd Merge pull request #3007 from xinnan-tech/update-manager-mobile
mobile 更新智能体功能,解决遗留bug
2026-03-12 17:43:14 +08:00
zhuoqinglian 9021eac54e Merge branch 'main' into update-manager-mobile 2026-03-12 17:37:30 +08:00
wengzhandGitHub b72967bcc3 Merge pull request #3006 from xinnan-tech/captcha-validation-error
fix: 优化验证码验证错误提示
2026-03-12 17:37:05 +08:00
zhuoqinglian 469f836a82 fix: 修复 mobile 短信验证码错误重复提示、智能体插件保存异常问题 2026-03-12 17:36:51 +08:00
zhuoqinglian 1e8960f37c feat: mobile 添加用户协议和隐私政策 2026-03-12 17:34:59 +08:00
rainv123 7aad8da6f6 fix: 优化验证码验证错误提示 2026-03-12 17:34:04 +08:00
wengzhandGitHub dd24dc0abc Merge pull request #2995 from xinnan-tech/py_fix_HuoShanTTS
Py fix huo shan tts
2026-03-12 16:25:47 +08:00
wengzhandGitHub 4f6cdc745f Merge pull request #3001 from xinnan-tech/py_fix_clone_languages
fix: 克隆音色未显示
2026-03-12 15:51:57 +08:00
lgy1027 bcf03a0378 refactor: 优化超时配置,响应社区反馈
- 工具调用超时改为可配置项 tool_call_timeout,默认30秒
- OpenAI 超时恢复可配置机制,支持细粒度配置和单一值
- TTS 超时保护统一添加到所有流式TTS实现
- 将 ActionResponse 导入移到文件顶部
- 修复超时配置边界情况处理
2026-03-11 18:13:05 +08:00
lgy1027 4f615b3807 Merge remote-tracking branch 'origin/main' into fix-end 2026-03-11 17:15:59 +08:00
zhuoqinglian 48087582c2 update: mobile 编辑源和语速音调页面样式调整 2026-03-11 17:10:18 +08:00
Sakura-RanChen fbb0e02fdd 去除空格,最下端留空行 2026-03-11 14:59:23 +08:00
wengzhandGitHub d7ef85f6d2 Merge branch 'main' into py_fix_clone_languages 2026-03-11 14:37:55 +08:00
wengzhandGitHub 2f2bd38f1e Merge pull request #3002 from xinnan-tech/perf-rag-linqui-update
perf:新增ragflow改动相关所需数据集、调整ragflow知识库相关文档
2026-03-11 11:55:09 +08:00
DaGou12138 bc48a169f4 新增ragflow改动相关所需数据集、调整ragflow知识库相关文档 2026-03-11 11:43:29 +08:00
DaGou12138andGitHub e777db6ef3 Merge pull request #2950 from gzh246/feature/api-knowledge-dora
整理ragflow外部接口api(包括会话,知识库,文档分块,文件管理,智能体)等,基于ragflow的最新稳定的大版本tag-0.23.0。
2026-03-11 11:27:02 +08:00
Sakura-RanChen 60498b24ae fix: 克隆音色未显示 2026-03-11 10:30:29 +08:00
DaGou12138 caae839b1d pref:优化大模型工具调用偷懒问题,调整基础提示词与新增临时工具记忆加深 2026-03-11 10:13:13 +08:00
zhuoqinglian 6a14d694b0 Merge branch 'main' into update-manager-mobile 2026-03-10 16:15:51 +08:00
zhuoqinglian d86387971a fix: 修复web、h5同时打开token失效问题 2026-03-10 16:15:09 +08:00
zhuoqinglian ff1076deac update: mobile 服务端接口地址提示语优化 2026-03-10 16:14:04 +08:00
wengzhandGitHub 5b986bf57f Merge pull request #2997 from xinnan-tech/web-privacy-terms
add:增加用户协议和隐私政策
2026-03-10 14:34:48 +08:00
rainv123 f1b2080d99 add:增加用户协议和隐私政策 2026-03-10 14:28:47 +08:00
lgy1027 c2b95ca896 fix: 优化退出流程并添加超时保护
- 添加 is_exiting 标志防止退出流程被中断
- 工具调用添加 30 秒超时保护,避免流程卡死
- TTS 相关操作添加超时保护
- 优化 OpenAI 客户端超时配置
2026-03-10 11:45:38 +08:00
zhuoqinglian ed41de7b8e feat: mobile 修改设备添加逻辑,新增手动添加设备 2026-03-10 11:37:51 +08:00
Sakura-RanChen 42a132f5cd 调整新增音色时的默认填充 2026-03-10 11:29:05 +08:00
Sakura-RanChen 7b2f6c2eee fix: 单一语音流上报音频不全 2026-03-10 10:53:24 +08:00
Sakura-RanChen ee5a53d67d fix: 修复选用seed-tts-2.0文本缺失
fix: 设备端说话状态与服务端同步
2026-03-09 17:55:54 +08:00
wengzhandGitHub f691e9f0c9 Merge pull request #2993 from xinnan-tech/tag_fix
fix: 修复智能体标签顺序错乱问题
2026-03-09 14:18:13 +08:00
rainv123 7a32c208fb fix: 修复智能体标签顺序错乱问题 2026-03-09 14:15:31 +08:00
DaGou12138andGitHub 6984763ddc Merge pull request #2988 from xinnan-tech/update-manager-mobile
web端功能同步更新到mobile端
2026-03-06 15:21:18 +08:00
DaGou12138andGitHub d6c3659d70 Merge pull request #2987 from xinnan-tech/update-agent-style
update: 智能体管理样式优化
2026-03-06 15:20:57 +08:00
zhuoqinglian d51c2a241c feat: mobile端同步更新上报模式、语言设置功能 2026-03-06 09:40:04 +08:00
zhuoqinglian a1d37b61e4 Merge branch 'main' into update-manager-mobile 2026-03-06 09:23:59 +08:00
zhuoqinglian 8b24151756 update: 智能体管理样式优化 2026-03-06 09:20:15 +08:00
GZH a9854756ec ```
refactor(knowledge): 移除未完成的BotController实现

- 删除了BotController类的所有代码
2026-03-04 21:25:26 +08:00
GZH f95bed4189 Merge remote-tracking branch 'origin/feature/api-knowledge-dora' into feature/api-knowledge-dora
# Conflicts:
#	main/manager-api/src/main/java/xiaozhi/common/config/RestTemplateConfig.java
#	main/manager-api/src/main/java/xiaozhi/common/exception/ErrorCode.java
#	main/manager-api/src/main/java/xiaozhi/modules/knowledge/controller/KnowledgeBaseController.java
#	main/manager-api/src/main/java/xiaozhi/modules/knowledge/controller/KnowledgeFilesController.java
#	main/manager-api/src/main/java/xiaozhi/modules/knowledge/rag/KnowledgeBaseAdapter.java
#	main/manager-api/src/main/java/xiaozhi/modules/knowledge/rag/RAGFlowClient.java
#	main/manager-api/src/main/java/xiaozhi/modules/knowledge/rag/impl/RAGFlowAdapter.java
#	main/manager-api/src/main/resources/i18n/messages.properties
#	main/manager-api/src/main/resources/i18n/messages_de_DE.properties
#	main/manager-api/src/main/resources/i18n/messages_en_US.properties
#	main/manager-api/src/main/resources/i18n/messages_vi_VN.properties
#	main/manager-api/src/main/resources/i18n/messages_zh_TW.properties
2026-03-04 17:47:42 +08:00
GZH f7bf29a5e4 fix: 修复PR审查意见 - 新增单文档删除接口、删除BotController、优化imports、修复i18n
# Conflicts:
#	main/manager-api/src/main/resources/i18n/messages_de_DE.properties
#	main/manager-api/src/main/resources/i18n/messages_en_US.properties
#	main/manager-api/src/main/resources/i18n/messages_vi_VN.properties
2026-03-04 17:45:58 +08:00
GZH 5913dbbb7b refactor(knowledge):重构知识库模块架构并优化DTO结构
- 将BotController暂时注释以重新设计Agent集成方案
- 在多个DTO类中添加@JsonIgnoreProperties注解提升JSON序列化兼容性- 修改ChunkDTO中positions字段类型为嵌套列表并添加token字段
-为DatasetDTO和DocumentDTO添加更多时间日期字段映射
-重构KnowledgeBaseAdapter接口参数结构使用统一的请求对象
- 实现DocumentStatusSyncTask定时任务同步文档处理状态
-优化KnowledgeBaseService统计信息更新机制
- 修复数据集删除时的级联删除逻辑防止孤儿数据
- 统一本地实体ID与RAGFlow ID避免前端调用错误
2026-03-04 17:39:55 +08:00
GZH f6bb55ae90 refactor(knowledge):重构知识库模块的数据传输对象和接口适配器
- 将 BotController 类注释掉,暂时移除机器人功能实现
- 在多个 DTO 类中添加 @JsonIgnoreProperties 注解以忽略未知属性- 修改 ChunkDTO 中的 positions 字段类型为嵌套列表,并添加 token 字段
- 更新 DatasetDTO 和 DocumentDTO 中的时间日期字段格式说明-重构 KnowledgeBaseAdapter 接口方法签名,使用强类型 DTO 替代 Map 参数
- 在 KnowledgeBaseController 中注入 KnowledgeManagerService 并修改删除逻辑
- 更新数据库统计信息更新方法名称和参数结构-优化 KnowledgeBaseServiceImpl 中的数据集创建和查找逻辑
2026-03-04 17:39:55 +08:00
GZH 33e712b5fb refactor(knowledge):重构知识库模块架构并优化DTO结构
- 将BotController暂时注释以重新设计Agent集成方案
- 在多个DTO类中添加@JsonIgnoreProperties注解提升JSON序列化兼容性- 修改ChunkDTO中positions字段类型为嵌套列表并添加token字段
-为DatasetDTO和DocumentDTO添加更多时间日期字段映射
-重构KnowledgeBaseAdapter接口参数结构使用统一的请求对象
- 实现DocumentStatusSyncTask定时任务同步文档处理状态
-优化KnowledgeBaseService统计信息更新机制
- 修复数据集删除时的级联删除逻辑防止孤儿数据
- 统一本地实体ID与RAGFlow ID避免前端调用错误
2026-03-04 17:39:07 +08:00
GZH 1c26faddc4 整理ragflow外部接口api(包括会话,知识库,文档分块,文件管理,智能体)等,基于ragflow的最新稳定的大版本tag-0.23.0。
Adapter 模式落地,引入了 RAGFlowAdapter,彻底隔离了业务逻辑和底层 API 调用。现在 Service 层只管“做什么”,Adapter 层只管“怎么调用 RAGFlow ”。
代码瘦身,移除了所有手写的 HTTP 请求,全部走 Adapter统一管理。
逻辑修正,修复了重复创建、ID 冲突等 Bug,确保了事务的一致性。
在数据库中留下了拓展字段如embedding_model,chunk_method,parser_config,document_count。保证可循迹。并新增ai_rag_knowledge_document表做到ragflow远端文档信息可在本地查看,管理。后续仍需追加双端同步增加/修改/删除。

- 新增AgentDTO包含Agent管理、Webhook调试、会话和对话等完整功能
- 新增BotDTO支持SearchBot和AgentBot的检索和对话功能
- 新增ChatDTO整合对话助手、会话和消息的全套数据传输对象
- 添加ai_rag_dataset表扩展字段支持租户、头像、权限等配置
- 创建ai_rag_knowledge_document表关联RAGFlow远程文档与本地元信息
- 扩展AgentService接口添加智能体配置验证功能
- 实现validateAgentConfig方法对RAGFlow模型配置进行软同步校验
- 更新AgentServiceImpl集成新的配置验证逻辑和注释清理
2026-03-04 17:32:44 +08:00
zhuoqinglian ac887139ce feat: 新增智能体标签、上下文源功能 2026-03-04 16:33:22 +08:00
wengzhandGitHub bc2c68e89f Merge pull request #2982 from xinnan-tech/web-supplement-language
优化相关判断,补充国际化
2026-03-03 11:27:12 +08:00
Sakura-RanChen cdc2363af1 优化相关判断,补充国际化 2026-03-03 11:25:37 +08:00
DaGou12138andGitHub ba07c623df Merge pull request #2980 from xinnan-tech/fix-roleConfig
fix: 解决角色配置合并冲突异常问题
2026-03-02 17:14:22 +08:00
zhuoqinglian 344a73b87b fix: 解决角色配置合并冲突异常问题 2026-03-02 17:11:56 +08:00
DaGou12138andGitHub 9a81b6c0ee Merge pull request #2979 from xinnan-tech/milieyo-patch-1
fix:Liquibase yaml
2026-03-02 17:02:35 +08:00
wengzhandGitHub 96f65e7c35 fix:Liquibase yaml 2026-03-02 16:55:08 +08:00
wengzhandGitHub ff2cdeb483 Merge pull request #2972 from xinnan-tech/update-tts-voice-data
Update tts voice data
2026-03-02 16:50:33 +08:00
wengzhandGitHub fe8b82fcda Merge branch 'main' into update-tts-voice-data 2026-03-02 16:50:19 +08:00
wengzhandGitHub f007e6614d Merge pull request #2978 from xinnan-tech/agent-tag
feat:智能体添加标签功能
2026-03-02 16:13:59 +08:00
rainv123 0eafd37bf6 feat:智能体添加标签功能 2026-03-02 15:51:25 +08:00
wengzhandGitHub af3bc09403 Merge pull request #2977 from xinnan-tech/role-tag
新增角色标签配置
2026-03-02 15:40:59 +08:00
zhuoqinglian 90ebb8d499 feat: 语音合成-音色管理,编辑模式下添加取消操作 2026-03-02 15:35:47 +08:00
zhuoqinglian f2c6cb8641 update: 优化文本溢出悬浮窗样式 2026-03-02 15:33:38 +08:00
Sakura-RanChenandGitHub 116a6973cf Merge branch 'main' into update-tts-voice-data 2026-03-02 09:19:46 +08:00
欣南科技andGitHub 769407a5b0 Merge pull request #2976 from xinnan-tech/fix-play-music-bug
fix:重写 audio_to_opus_data_stream 方法,让音频文件处理使用独立编码器,避免与 TTS 流编码器冲突。
2026-03-01 13:00:25 +08:00
hrz a4583e273a fix:重写 audio_to_opus_data_stream 方法,让音频文件处理使用独立编码器,避免与 TTS 流编码器冲突。 2026-03-01 12:59:45 +08:00
zhuoqinglian 645462abd0 feat: 新增角色标签配置 2026-02-28 17:51:46 +08:00
Sakura-RanChen b49c4520f9 部分TTS参数调整 2026-02-27 16:37:31 +08:00
wengzhandGitHub acf45ae8ad Merge pull request #2971 from xinnan-tech/fix-manager-api-device-tools-api
fix:#2939 修复getDeviceTools()中未考虑分页问题
2026-02-27 16:36:37 +08:00
Sakura-RanChen 0d1c18f5dd Merge branch 'main' into update-tts-voice-data 2026-02-27 11:21:18 +08:00
Sakura-RanChen 7b020ba55c update: 增加智能体独立音频设置 2026-02-27 11:17:08 +08:00
DaGou12138 cc081bc9eb #2939 修复getDeviceTools()中未考虑分页问题 2026-02-26 17:46:20 +08:00
hrzandGitHub 187c2ee977 Merge pull request #2970 from ephemetra/patch-1
docs: 修复文档中的错误内容
2026-02-26 16:21:20 +08:00
ephemetraandGitHub 00ab407b04 docs: 修复文档中的错误内容
1. 修正第三部分的错误标题。
2. 修正了server.mqtt_manager_api填入`PUBLIC_IP`+`:`+`UDP_PORT`的错误内容。
2026-02-25 10:19:22 +08:00
欣南科技andGitHub bda7a90551 Merge pull request #2969 from xinnan-tech/i18n-pt_BR
I18n pt br
2026-02-24 08:05:45 +08:00
hrz 71b72f5b51 update:修正英文版翻译遗漏的chatHistory.前缀 2026-02-24 08:04:53 +08:00
hrzandGitHub 61fd8b21e0 Merge pull request #2965 from Alif254317/claude/explore-repository-YzYCv
feat: adicionar suporte a Português Brasileiro (pt_BR) no projeto
2026-02-24 07:28:45 +08:00
欣南科技andGitHub 9a4610ab04 Merge pull request #2968 from xinnan-tech/fix-vad-decoder
fix:高并发下,共享vad里decoder变量扰动
2026-02-24 02:00:29 +08:00
hrz fd8296262e fix:高并发下,共享vad里decoder变量扰动 2026-02-24 01:59:44 +08:00
Claude 63dfcf6659 feat: adicionar suporte a Português Brasileiro (pt_BR) no projeto
- Adiciona arquivo de tradução pt_BR.js para manager-web (~1332 chaves)
- Adiciona arquivo de tradução pt_BR.ts para manager-mobile (~440 chaves)
- Cria README_pt_BR.md com documentação traduzida completa
- Registra pt_BR no sistema i18n de ambos os frontends (web e mobile)
- Adiciona pt_BR nos seletores de idioma (HeaderBar, login, retrievePassword)
- Adiciona badge "Português (Brasil)" em todos os READMEs existentes
- Adiciona detecção automática de idioma pt/pt-BR no navegador
- Adiciona chave language.ptBR em todos os arquivos de tradução existentes

https://claude.ai/code/session_01XJMVWKBjy7UwqskN9BbsYM
2026-02-19 17:44:25 +00:00
hrzandGitHub 8897b4f3c6 Merge pull request #2962 from xinnan-tech/test_live2d
fix: 调整切换摄像头位置
2026-02-18 08:30:47 +08:00
GZH 8d46585101 refactor(knowledge):重构知识库模块架构并优化DTO结构
- 将BotController暂时注释以重新设计Agent集成方案
- 在多个DTO类中添加@JsonIgnoreProperties注解提升JSON序列化兼容性- 修改ChunkDTO中positions字段类型为嵌套列表并添加token字段
-为DatasetDTO和DocumentDTO添加更多时间日期字段映射
-重构KnowledgeBaseAdapter接口参数结构使用统一的请求对象
- 实现DocumentStatusSyncTask定时任务同步文档处理状态
-优化KnowledgeBaseService统计信息更新机制
- 修复数据集删除时的级联删除逻辑防止孤儿数据
- 统一本地实体ID与RAGFlow ID避免前端调用错误
2026-02-14 12:55:56 +08:00
GZH 6967b2bce2 refactor(knowledge):重构知识库模块的数据传输对象和接口适配器
- 将 BotController 类注释掉,暂时移除机器人功能实现
- 在多个 DTO 类中添加 @JsonIgnoreProperties 注解以忽略未知属性- 修改 ChunkDTO 中的 positions 字段类型为嵌套列表,并添加 token 字段
- 更新 DatasetDTO 和 DocumentDTO 中的时间日期字段格式说明-重构 KnowledgeBaseAdapter 接口方法签名,使用强类型 DTO 替代 Map 参数
- 在 KnowledgeBaseController 中注入 KnowledgeManagerService 并修改删除逻辑
- 更新数据库统计信息更新方法名称和参数结构-优化 KnowledgeBaseServiceImpl 中的数据集创建和查找逻辑
2026-02-14 12:55:56 +08:00
GZH 16a38bbfc4 refactor(knowledge):重构知识库模块架构并优化DTO结构
- 将BotController暂时注释以重新设计Agent集成方案
- 在多个DTO类中添加@JsonIgnoreProperties注解提升JSON序列化兼容性- 修改ChunkDTO中positions字段类型为嵌套列表并添加token字段
-为DatasetDTO和DocumentDTO添加更多时间日期字段映射
-重构KnowledgeBaseAdapter接口参数结构使用统一的请求对象
- 实现DocumentStatusSyncTask定时任务同步文档处理状态
-优化KnowledgeBaseService统计信息更新机制
- 修复数据集删除时的级联删除逻辑防止孤儿数据
- 统一本地实体ID与RAGFlow ID避免前端调用错误
2026-02-14 12:55:56 +08:00
GZH 861df73eab 整理ragflow外部接口api(包括会话,知识库,文档分块,文件管理,智能体)等,基于ragflow的最新稳定的大版本tag-0.23.0。
Adapter 模式落地,引入了 RAGFlowAdapter,彻底隔离了业务逻辑和底层 API 调用。现在 Service 层只管“做什么”,Adapter 层只管“怎么调用 RAGFlow ”。
代码瘦身,移除了所有手写的 HTTP 请求,全部走 Adapter统一管理。
逻辑修正,修复了重复创建、ID 冲突等 Bug,确保了事务的一致性。
在数据库中留下了拓展字段如embedding_model,chunk_method,parser_config,document_count。保证可循迹。并新增ai_rag_knowledge_document表做到ragflow远端文档信息可在本地查看,管理。后续仍需追加双端同步增加/修改/删除。

- 新增AgentDTO包含Agent管理、Webhook调试、会话和对话等完整功能
- 新增BotDTO支持SearchBot和AgentBot的检索和对话功能
- 新增ChatDTO整合对话助手、会话和消息的全套数据传输对象
- 添加ai_rag_dataset表扩展字段支持租户、头像、权限等配置
- 创建ai_rag_knowledge_document表关联RAGFlow远程文档与本地元信息
- 扩展AgentService接口添加智能体配置验证功能
- 实现validateAgentConfig方法对RAGFlow模型配置进行软同步校验
- 更新AgentServiceImpl集成新的配置验证逻辑和注释清理
2026-02-14 12:55:56 +08:00
lww155 fa9809bee1 fix: 调整切换摄像头位置 2026-02-11 17:41:52 +08:00
欣南科技andGitHub 2a93745d01 Merge pull request #2957 from xinnan-tech/test_live2d
fix:手机前后摄像头切换,调整摄像头为竖屏显示
2026-02-11 11:32:53 +08:00
lww155 85fab64588 fix: 优化h5样式 2026-02-10 09:54:39 +08:00
rainv123 b22f430e98 fix:调整摄像头显示区域为竖屏 2026-02-09 17:22:28 +08:00
lww155 c3da3e937e add: 前后摄像头切换 2026-02-09 16:50:23 +08:00
Sakura-RanChen 4ea3bea85c update: 增加TTS音色语种选择 2026-02-09 15:28:31 +08:00
DaGou12138 520e24a54e 修改统一规范ai_tts_voice语言类型数据语句 2026-02-06 17:12:47 +08:00
DaGou12138 e82cc53bfb 统一规范ai_tts_voice语言类型数据 2026-02-06 16:54:21 +08:00
wengzhandGitHub 3bddc1c722 Merge pull request #2953 from xinnan-tech/fix-modal-flicker
Fix modal flicker
2026-02-06 16:40:56 +08:00
lww155 f68fc5c90d fix: 修复点击用户框无法关闭菜单问题 2026-02-06 16:37:20 +08:00
lww155 ea8001a9c8 fix: 模态框闪烁问题 2026-02-06 14:49:17 +08:00
hrzandGitHub ca10d7290d Merge pull request #2949 from xinnan-tech/test_live2d
update:优化
2026-02-05 18:05:26 +08:00
rainv123 7b3db72285 update:优化 2026-02-05 18:02:18 +08:00
wengzhandGitHub 3639871dd2 Merge pull request #2944 from xinnan-tech/py_test_Memory_powermem
Py test memory powermem
2026-02-05 17:45:23 +08:00
wengzhandGitHub 5fb7fbe08f Merge branch 'main' into py_test_Memory_powermem 2026-02-05 17:45:07 +08:00
wengzhandGitHub 73f8a0977c Merge pull request #2948 from xinnan-tech/py_test_typing
Py test typing
2026-02-05 17:34:26 +08:00
wengzhandGitHub 87b99e0353 Merge pull request #2946 from xinnan-tech/fix_asr_Initialize
增加asr初始化ID判断
2026-02-05 17:33:35 +08:00
Sakura-RanChenandGitHub 795dcec698 Merge pull request #2890 from shengzhou1216/feature/python-typing
feat: 为多个模块添加类型注解以增强代码可读性
2026-02-05 17:15:00 +08:00
Sakura-RanChenandGitHub 4f61d21d17 Merge branch 'py_test_typing' into feature/python-typing 2026-02-05 17:14:47 +08:00
wengzhandGitHub 8a84428724 Merge pull request #2938 from xinnan-tech/test_live2d
update:测试页面增加切换live2d模型、拍照识物功能
2026-02-05 17:00:11 +08:00
wengzhandGitHub 46f1dee20e Merge pull request #2947 from xinnan-tech/fix/model-config-enable-check
新增模型配置启用开关禁用判断
2026-02-05 16:51:51 +08:00
lww155 75e24af858 新增模型配置启用开关禁用判断 2026-02-05 16:46:10 +08:00
rainv123 fae6db2198 fix:移除拨号按钮防抖,点击拨号后禁用按钮3秒 2026-02-05 16:32:05 +08:00
rainv123 32aea32e2c fix:删除工具描述输入框的多余空格 2026-02-05 16:09:52 +08:00
Sakura-RanChen 63d9dae18b 增加asr初始化ID判断 2026-02-05 15:42:23 +08:00
rainv123 041c254ea4 fix:拨号按钮和摄像头按钮增加防抖机制 2026-02-05 15:06:04 +08:00
rainv123 378d68aba9 fix: 测试页面MCP工具参数编辑样式调整 2026-02-05 14:44:37 +08:00
wengzhandGitHub 4076136fe4 Merge pull request #2945 from xinnan-tech/perf-manager-api-delTable
perf:新增数据集,删除无用业务表ai_voiceprint
2026-02-05 13:53:38 +08:00
DaGou12138 1e6e250dac 新增数据集,删除无用业务表ai_voiceprint 2026-02-05 11:28:31 +08:00
Sakura-RanChen 42b495d556 补充sql文件 2026-02-05 10:37:48 +08:00
Sakura-RanChen c88d709d56 Merge branch 'main' into py_test_Memory_powermem 2026-02-04 16:02:50 +08:00
wengzhandGitHub fa523dc615 Merge pull request #2942 from xinnan-tech/perf-manager-api-modelConfig
perf:新增关闭模型配置相关逻辑判断
2026-02-04 11:42:38 +08:00
DaGou12138 8718a07c7e 新增关闭模型配置相关逻辑判断 2026-02-04 11:32:10 +08:00
wengzhandGitHub 39124d4930 Merge pull request #2940 from xinnan-tech/py_fix_stream_asr
fix: 讯飞自动设备适应,阿里云等待时机过短
2026-02-04 10:38:29 +08:00
rainv123 8dbc0b9689 fix: 修复绑定验证码后重新连接摄像头不自动打开的问题 2026-02-04 10:29:48 +08:00
Sakura-RanChen 9fd3501605 fix: 讯飞自动设备适应,阿里云等待时机过短 2026-02-04 10:28:27 +08:00
lww155 4f72a516d3 update: 录音按钮新增防抖 2026-02-04 09:54:56 +08:00
lww155 e4cfabeb7e update: 优化代码 2026-02-04 09:54:21 +08:00
rainv123 85a83727fd feat: 摄像头验证码绑定检查 && 视觉分析URL动态获取 2026-02-03 11:52:22 +08:00
wengzhandGitHub a31e16c1d9 Merge pull request #2931 from xinnan-tech/py_test_error_response
Py test error response
2026-02-03 10:01:08 +08:00
Sakura-RanChen 3ab5dc49ac 去除无用代码,修复插入语句id缺失 2026-02-02 16:07:09 +08:00
rainv123 005dc55db3 add:测试页面增加拍照识物功能 2026-02-02 15:08:24 +08:00
Sakura-RanChenandGitHub ba1cf14ed4 Merge pull request #2888 from shengzhou1216/fix/2075
feat: 统一LLM错误处理并添加系统错误回复配置
2026-02-02 14:49:42 +08:00
Sakura-RanChenandGitHub 6da32a60c0 Merge branch 'py_test_error_response' into fix/2075 2026-02-02 14:49:26 +08:00
wengzhandGitHub ea9778f422 Merge pull request #2930 from xinnan-tech/py_test_AudioArtifacts
Py test audio artifacts
2026-02-02 14:23:09 +08:00
wengzhandGitHub f0b176768d Merge branch 'main' into py_test_AudioArtifacts 2026-02-02 14:23:01 +08:00
wengzhandGitHub 5aa671d6ff Merge pull request #2929 from xinnan-tech/py_fix_asr
fix: 模式切换时音频残余,优化相关状态管理
2026-02-02 14:05:07 +08:00
Sakura-RanChenandGitHub d02d094219 Merge pull request #2924 from shengzhou1216/refactor/asr-delete_audio
refactor(asr): 重构speech_to_text方法以接收artifacts参数
2026-02-02 11:42:59 +08:00
Sakura-RanChen f5b4bae927 fix: 模式切换时音频残余,优化相关状态管理 2026-02-02 11:29:47 +08:00
rainv123 19fdf5d917 update:测试页面切换模型和切换背景的按钮样式调整 2026-02-02 10:47:01 +08:00
欣南科技andGitHub 9682f615cf Merge pull request #2927 from xinnan-tech/update-test-bg
update:优化图片
2026-02-01 01:24:39 +08:00
hrz 8162adeca1 update:优化图片 2026-02-01 01:23:45 +08:00
rainv123 ba2749430f add:live2d增加可切换的男性角色 2026-01-30 17:59:06 +08:00
rainv123 e3088f4410 Merge branch 'main' of https://github.com/xinnan-tech/xiaozhi-esp32-server into new 2026-01-30 17:21:22 +08:00
huozaimengli 614b662e3d refactor(asr): 重构speech_to_text方法以接收artifacts参数
移除各ASR提供者中重复的get_current_artifacts调用,改为通过参数传递artifacts
修改base类中process_audio方法,根据combined_pcm_data长度决定是否创建artifacts
更新所有speech_to_text方法签名,添加artifacts可选参数并更新文档字符串
2026-01-29 16:39:35 +08:00
huozaimengli f5b9995f89 feat: 添加系统错误时的默认回复配置SQL
在 sys_params 表中插入新记录,用于配置系统发生错误时返回给用户的默认回复消息。该配置允许管理员自定义错误提示文本,提升用户体验。
2026-01-29 15:58:00 +08:00
huozaimengli 0ddd9ba8ff fix: 修正系统错误响应的句子类型为MIDDLE 2026-01-29 15:57:31 +08:00
欣南科技andGitHub 9c8d614d78 Merge pull request #2918 from xinnan-tech/test-arm64-docker
fix:docker 缺失nginx文件
2026-01-28 19:02:21 +08:00
hrz 0075550229 fix:docker 缺失nginx文件 2026-01-28 19:01:37 +08:00
rainv123 4a547be882 Merge branch 'main' of https://github.com/xinnan-tech/xiaozhi-esp32-server into new 2026-01-28 15:24:02 +08:00
Sakura-RanChenandGitHub 22d0dcdf58 Merge pull request #2887 from shengzhou1216/refactor/asr-delete_audio
refactor(asr): 统一音频预处理逻辑并引入AudioArtifacts
2026-01-27 15:41:46 +08:00
rainv123 122d1def1d Merge branch 'main' of https://github.com/xinnan-tech/xiaozhi-esp32-server into new 2026-01-27 11:59:03 +08:00
rainv123 0f16a8d31f Merge branch 'py_audio_rate' of https://github.com/xinnan-tech/xiaozhi-esp32-server into new 2026-01-26 17:39:29 +08:00
huozaimengli 4b573fb4e2 feat: 为多个模块添加类型注解以增强代码可读性
为 ConnectionHandler 相关的函数参数添加类型注解,使用 TYPE_CHECKING 避免循环导入。主要修改包括:
- 在 abortHandle、textHandle 等处理模块中为 conn 参数添加 ConnectionHandler 类型注解
- 在 websocket_server、connection 等核心模块中为方法参数添加类型注解
- 在 plugins_func 下的多个功能模块中为函数参数添加类型注解
- 在 providers 相关模块中为工具执行器和方法添加类型注解
- 统一代码格式,如将单引号字符串改为双引号

Fixes #2034
2026-01-25 17:47:52 +08:00
huozaimengli 6ae0af278b feat: 统一LLM错误处理并添加系统错误回复配置
在多个LLM提供者中移除try-catch块,将错误处理统一到connection.py的流处理层
添加system_error_response配置项,支持自定义系统错误时的回复内容
在意图识别和流处理中捕获异常时返回配置的错误回复,避免硬编码错误信息

Fixes #2075
2026-01-25 16:48:01 +08:00
huozaimengli 15650e1a6c refactor(asr): 统一音频预处理逻辑并引入AudioArtifacts
重构所有ASR提供商的speech_to_text方法,将重复的音频解码、合并和文件保存逻辑提取到基类的speech_to_text_wrapper中。引入AudioArtifacts数据类封装PCM帧、字节数据、文件路径和临时路径,简化各提供商实现。移除各提供商中的冗余文件清理代码,由基类统一处理。

新增requires_file()和prefers_temp_file()方法允许提供商声明文件需求,优化内存和磁盘使用。保持接口兼容性的同时提高代码复用性和可维护性。
2026-01-25 11:27:34 +08:00
Sakura-RanChenandGitHub 9368885355 Merge pull request #2859 from wayyoungboy/add-powermem
chore: 更新 powermem 依赖至 0.3.1 版本, 增加角色过滤的能力
2026-01-23 10:24:21 +08:00
渠磊 bfa638e17f chore: 更新 powermem 依赖至 0.3.1 版本, 增加角色过滤的能力 2026-01-19 14:16:12 +08:00
Sakura-RanChen 3bdccfea62 解析json字符串提取相关文本 2026-01-12 17:47:29 +08:00
Sakura-RanChenandGitHub 5fa50339b4 Merge pull request #2824 from wayyoungboy/add-powermem
docs(config): 更新配置文件和集成文档
2026-01-12 15:07:08 +08:00
Sakura-RanChen f0c95bc987 为空时不做相关查询(工具调用function_call时没有相关query) 2026-01-12 15:06:38 +08:00
渠磊 8edc23b888 docs(config): 更新配置文件和集成文档
- 添加embedding_dims配置项注释
- 同步配置文件修改到集成文档
2026-01-09 17:42:30 +08:00
Sakura-RanChen c4fc510a27 补充相关信息 2026-01-09 17:25:03 +08:00
Sakura-RanChen 134000996b query只传递相关的文本 2026-01-09 16:09:05 +08:00
Sakura-RanChen 111909c26d fix: 启用用户画像模式时,search为同步方法需包装 2026-01-09 15:46:08 +08:00
Sakura-RanChenandGitHub f66966d72f Merge pull request #2822 from wayyoungboy/add-powermem
fix: powermem sqlite支持用户画像以及修改配置模式
2026-01-09 14:46:31 +08:00
渠磊 06a2e6fbfa refactor(powermem): 移除未使用的内存提供者实例注册 2026-01-09 12:34:55 +08:00
渠磊 c8a28e98d6 Merge remote-tracking branch 'upstream/py_test_Memory_powermem' into add-powermem
# Conflicts:
#	main/xiaozhi-server/core/providers/memory/powermem/powermem.py
2026-01-09 12:32:59 +08:00
渠磊 564adbd851 feat(powermem): 升级配置结构并支持多数据库用户画像
- 重构配置结构为模块化设计(llm/embedder/vector_store)
- 用户画像功能支持oceanbase/seekdb/sqlite三种存储后端
- 更新文档说明和示例配置
2026-01-09 12:25:17 +08:00
Sakura-RanChen ad93f43145 去除默认初始化,补充函数签名缺失 2026-01-09 10:49:24 +08:00
wayyoungboy 2bf1123647 部分配置key修正 2026-01-08 23:52:19 +08:00
Sakura-RanChenandGitHub a6ff6426e9 Merge pull request #2819 from wayyoungboy/add-powermem
Add powermem
2026-01-08 17:54:57 +08:00
渠磊 de7aedab96 feat(memory): 添加用户画像功能支持
- 新增 `enable_user_profile` 配置项,支持用户画像模式
- 实现 `UserMemory` 类集成,自动提取用户信息
- 更新文档说明用户画像功能及配置要求
2026-01-08 14:43:48 +08:00
渠磊 dadf05ab4e feat: 添加 PowerMem 智能记忆支持
- 新增 PowerMem 配置选项和集成文档
- 更新 README 和多语言文档
- 添加 powermem 依赖包
2026-01-08 12:02:03 +08:00
493 changed files with 45059 additions and 6016 deletions
+4
View File
@@ -3,6 +3,9 @@ __pycache__/
.idea/
*.py[cod]
*$py.class
.vscode
.claude
AGENTS.md
# C extensions
*.so
@@ -146,6 +149,7 @@ tmp
.history
.DS_Store
main/xiaozhi-server/data
main/xiaozhi-server/.claude
main/manager-web/node_modules
.config.yaml
+2 -1
View File
@@ -23,7 +23,8 @@ RUN apk update && \
bash \
fontconfig \
ttf-dejavu \
&& rm -rf /var/cache/apk/*
&& rm -rf /var/cache/apk/* \
&& mkdir -p /run/nginx /var/log/nginx /var/tmp/nginx /etc/nginx/conf.d
# 复制项目自带的中文字体
COPY main/manager-web/public/generator/static/fonts/*.ttf /usr/share/fonts/
+5 -3
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@@ -21,6 +21,7 @@
<a href="./README_en.md"><img alt="README in English" src="https://img.shields.io/badge/English-DFE0E5"></a>
<a href="./README_vi.md"><img alt="Tiếng Việt" src="https://img.shields.io/badge/Tiếng Việt-DFE0E5"></a>
<a href="./README_de.md"><img alt="Deutsch" src="https://img.shields.io/badge/Deutsch-DFE0E5"></a>
<a href="./README_pt_BR.md"><img alt="Português (Brasil)" src="https://img.shields.io/badge/Português (Brasil)-DFE0E5"></a>
<a href="https://github.com/xinnan-tech/xiaozhi-esp32-server/releases">
<img alt="GitHub Contributors" src="https://img.shields.io/github/v/release/xinnan-tech/xiaozhi-esp32-server?logo=docker" />
</a>
@@ -213,8 +214,8 @@ Websocket接口地址: wss://2662r3426b.vicp.fun/xiaozhi/v1/
|:---:|:---:|:---:|
| ASR(语音识别) | FunASR(本地) | 👍XunfeiStreamASR(讯飞流式) |
| LLM(大模型) | glm-4-flash(智谱) | 👍qwen-flash(阿里百炼) |
| VLLM(视觉大模型) | glm-4v-flash(智谱) | 👍qwen2.5-vl-3b-instructh(阿里百炼) |
| TTS(语音合成) | ✅LinkeraiTTS(灵犀流式) | 👍HuoshanDoubleStreamTTS(火山流式) |
| VLLM(视觉大模型) | glm-4v-flash(智谱) | 👍qwen3.5-flash(阿里百炼) |
| TTS(语音合成) | EdgeTTS(微软) | 👍HuoshanDoubleStreamTTS(火山流式) |
| Intent(意图识别) | function_call(函数调用) | function_call(函数调用) |
| Memory(记忆功能) | mem_local_short(本地短期记忆) | mem_local_short(本地短期记忆) |
@@ -242,7 +243,7 @@ Websocket接口地址: wss://2662r3426b.vicp.fun/xiaozhi/v1/
| 智能对话 | 支持多种LLM(大语言模型),实现智能对话 |
| 视觉感知 | 支持多种VLLM(视觉大模型),实现多模态交互 |
| 意图识别 | 支持外挂的大模型意图识别、大模型自主函数调用,提供插件化意图处理机制 |
| 记忆系统 | 支持本地短期记忆、mem0ai接口记忆,具备记忆总结功能 |
| 记忆系统 | 支持本地短期记忆、mem0ai接口记忆、PowerMem智能记忆,具备记忆总结功能 |
| 知识库 | 支持RAGFlow知识库,让大模型判断需要调度知识库后再回答 |
| 工具调用 | 支持客户端IOT协议、客户MCP协议、服务端MCP协议、MCP接入点协议、自定义工具函数 |
| 指令下发 | 依托MQTT协议,支持从智控台将MCP指令下发到ESP32设备 |
@@ -330,6 +331,7 @@ Websocket接口地址: wss://2662r3426b.vicp.fun/xiaozhi/v1/
| 类型 | 平台名称 | 使用方式 | 收费模式 | 备注 |
|:------:|:---------------:|:----:|:---------:|:--:|
| Memory | mem0ai | 接口调用 | 1000次/月额度 | |
| Memory | [powermem](./docs/powermem-integration.md) | 本地总结 | 取决于LLM和DB | OceanBase开源,支持智能检索 |
| Memory | mem_local_short | 本地总结 | 免费 | |
| Memory | nomem | 无记忆模式 | 免费 | |
+6 -4
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@@ -21,6 +21,7 @@ Unterstützt MQTT+UDP-Protokoll, Websocket-Protokoll, MCP-Endpunkte und Stimmabd
<a href="./README_en.md"><img alt="README in English" src="https://img.shields.io/badge/English-DFE0E5"></a>
<a href="./README_vi.md"><img alt="Tiếng Việt" src="https://img.shields.io/badge/Tiếng Việt-DFE0E5"></a>
<a href="./README_de.md"><img alt="Deutsch" src="https://img.shields.io/badge/Deutsch-DBEDFA"></a>
<a href="./README_pt_BR.md"><img alt="Português (Brasil)" src="https://img.shields.io/badge/Português (Brasil)-DFE0E5"></a>
<a href="https://github.com/xinnan-tech/xiaozhi-esp32-server/releases">
<img alt="GitHub Contributors" src="https://img.shields.io/github/v/release/xinnan-tech/xiaozhi-esp32-server?logo=docker" />
</a>
@@ -211,8 +212,8 @@ Websocket-Schnittstellenadresse: wss://2662r3426b.vicp.fun/xiaozhi/v1/
|:---:|:---:|:---:|
| ASR (Spracherkennung) | FunASR (Lokal) | 👍XunfeiStreamASR (Xunfei-Streaming) |
| LLM (Großes Modell) | glm-4-flash (Zhipu) | 👍qwen-flash (Alibaba Bailian) |
| VLLM (Vision Large Model) | glm-4v-flash (Zhipu) | 👍qwen2.5-vl-3b-instructh (Alibaba Bailian) |
| TTS (Sprachsynthese) | ✅LinkeraiTTS (Lingxi-Streaming) | 👍HuoshanDoubleStreamTTS (Volcano-Streaming) |
| VLLM (Vision Large Model) | glm-4v-flash (Zhipu) | 👍qwen3.5-flash (Alibaba Bailian) |
| TTS (Sprachsynthese) | EdgeTTS (Microsoft) | 👍HuoshanDoubleStreamTTS (Volcano-Streaming) |
| Intent (Absichtserkennung) | function_call (Funktionsaufruf) | function_call (Funktionsaufruf) |
| Memory (Gedächtnisfunktion) | mem_local_short (Lokales Kurzzeitgedächtnis) | mem_local_short (Lokales Kurzzeitgedächtnis) |
@@ -240,7 +241,7 @@ Dieses Projekt bietet die folgenden Testwerkzeuge, um Ihnen bei der Überprüfun
| Intelligenter Dialog | Unterstützt mehrere LLM (große Sprachmodelle), implementiert intelligenten Dialog |
| Visuelle Wahrnehmung | Unterstützt mehrere VLLM (Vision Large Models), implementiert multimodale Interaktion |
| Absichtserkennung | Unterstützt LLM-Absichtserkennung, Function Call-Funktionsaufruf, bietet plugin-basierten Absichtsverarbeitungsmechanismus |
| Gedächtnissystem | Unterstützt lokales Kurzzeitgedächtnis, mem0ai-Schnittstellengedächtnis, mit Gedächtniszusammenfassungsfunktion |
| Gedächtnissystem | Unterstützt lokales Kurzzeitgedächtnis, mem0ai-Schnittstellengedächtnis, PowerMem intelligentes Gedächtnis, mit Gedächtniszusammenfassungsfunktion |
| Wissensdatenbank | Unterstützt RAGFlow-Wissensdatenbank, ermöglicht großem Modell die Bewertung, ob Wissensdatenbank benötigt wird, bevor geantwortet wird |
| Werkzeugaufruf | Unterstützt Client-IOT-Protokoll, Client-MCP-Protokoll, Server-MCP-Protokoll, MCP-Endpunktprotokoll, benutzerdefinierte Werkzeugfunktionen |
| Befehlsübermittlung | Basierend auf MQTT-Protokoll, unterstützt die Übermittlung von MCP-Befehlen von der intelligenten Steuerkonsole an ESP32-Geräte |
@@ -258,7 +259,7 @@ Wenn Sie ein Softwareentwickler sind, finden Sie hier einen [Offenen Brief an En
---
## Produktökosystem 👬
Xiaozhi ist ein Ökosystem. Wenn Sie dieses Produkt verwenden, können Sie sich auch andere [hervorragende Projekte](https://github.com/78/xiaozhi-esp32?tab=readme-ov-file#related-open-source-projects) in diesem Ökosystem ansehen
Xiaozhi ist ein Ökosystem. Wenn Sie dieses Produkt verwenden, können Sie sich auch andere [hervorragende Projekte](https://github.com/78/xiaozhi-esp32/blob/main/README_zh.md#%E7%9B%B8%E5%85%B3%E5%BC%80%E6%BA%90%E9%A1%B9%E7%9B%AE) in diesem Ökosystem ansehen
---
@@ -328,6 +329,7 @@ Tatsächlich kann jedes VLLM, das OpenAI-Schnittstellenaufrufe unterstützt, int
| Typ | Plattformname | Verwendungsmethode | Preismodell | Hinweise |
|:------:|:---------------:|:----:|:---------:|:--:|
| Memory | mem0ai | Schnittstellenaufrufe | 1000 Mal/Monat Kontingent | |
| Memory | [powermem](./docs/powermem-integration.md) | Lokale Zusammenfassung | Abhängig von LLM und DB | OceanBase Open Source, unterstützt intelligente Abfrage |
| Memory | mem_local_short | Lokale Zusammenfassung | Kostenlos | |
| Memory | nomem | Kein Gedächtnismodus | Kostenlos | |
+19 -17
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@@ -21,6 +21,7 @@ Support for MQTT+UDP protocol, Websocket protocol, MCP access point, voiceprint
<a href="./README_en.md"><img alt="README in English" src="https://img.shields.io/badge/English-DBEDFA"></a>
<a href="./README_vi.md"><img alt="Tiếng Việt" src="https://img.shields.io/badge/Tiếng Việt-DFE0E5"></a>
<a href="./README_de.md"><img alt="Deutsch" src="https://img.shields.io/badge/Deutsch-DFE0E5"></a>
<a href="./README_pt_BR.md"><img alt="Português (Brasil)" src="https://img.shields.io/badge/Português (Brasil)-DFE0E5"></a>
<a href="https://github.com/xinnan-tech/xiaozhi-esp32-server/releases">
<img alt="GitHub Contributors" src="https://img.shields.io/github/v/release/xinnan-tech/xiaozhi-esp32-server?logo=docker" />
</a>
@@ -182,8 +183,9 @@ This project provides two deployment methods. Please choose based on your specif
| Deployment Method | Features | Applicable Scenarios | Deployment Docs | Configuration Requirements | Video Tutorials |
|---------|------|---------|---------|---------|---------|
| **Simplified Installation** | Intelligent dialogue, single agent management | Low-configuration environments, data stored in config files, no database required | [①Docker Version](./docs/Deployment.md#%E6%96%B9%E5%BC%8F%E4%B8%80docker%E5%8F%AA%E8%BF%90%E8%A1%8Cserver) / [②Source Code Deployment](./docs/Deployment.md#%E6%96%B9%E5%BC%8F%E4%BA%8C%E6%9C%AC%E5%9C%B0%E6%BA%90%E7%A0%81%E5%8F%AA%E8%BF%90%E8%A1%8Cserver)| 2 cores 4GB if using `FunASR`, 2 cores 2GB if all APIs | - |
| **Full Module Installation** | Intelligent dialogue, multi-user management, multi-agent management, intelligent console interface operation | Complete functionality experience, data stored in database |[①Docker Version](./docs/Deployment_all.md#%E6%96%B9%E5%BC%8F%E4%B8%80docker%E8%BF%90%E8%A1%8C%E5%85%A8%E6%A8%A1%E5%9D%97) / [②Source Code Deployment](./docs/Deployment_all.md#%E6%96%B9%E5%BC%8F%E4%BA%8C%E6%9C%AC%E5%9C%B0%E6%BA%90%E7%A0%81%E8%BF%90%E8%A1%8C%E5%85%A8%E6%A8%A1%E5%9D%97) / [③Source Code Deployment Auto-Update Tutorial](./docs/dev-ops-integration.md) | 4 cores 8GB if using `FunASR`, 2 cores 4GB if all APIs| [Local Source Code Startup Video Tutorial](https://www.bilibili.com/video/BV1wBJhz4Ewe) |
| **Full Module Installation** | Intelligent dialogue, multi-user management, multi-agent management, intelligent console interface operation | Complete functionality experience, data stored in database |[①Docker Version](./docs/Deployment_all.md#%E6%96%B9%E5%BC%8F%E4%B8%80docker%E8%BF%90%E8%A1%8C%E5%85%A8%E6%A8%A1%E5%9D%97) / [②Source Code Deployment](./docs/Deployment_all.md#%E6%96%B9%E5%BC%8F%E4%BA%8C%E6%9C%AC%E5%9C%B0%E6%BA%90%E7%A0%81%E8%BF%90%E8%A1%8C%E5%85%A8%E6%A8%A1%E5%9D%97) / [③Source Code Deployment Auto-Update Tutorial](./docs/dev-ops-integration.md) | 4 cores 8GB if using `FunASR`, 2 cores 4GB if all APIs| [Local Source Code Startup Video Tutorial](https://www.bilibili.com/video/BV1wBJhz4Ewe) |
For frequently asked questions and related tutorials, please refer to [this link](./docs/FAQ.md)
> 💡 Note: Below is a test platform deployed with the latest code. You can burn and test if needed. Concurrent users: 6, data will be cleared daily.
@@ -210,19 +212,20 @@ Websocket Interface Address: wss://2662r3426b.vicp.fun/xiaozhi/v1/
|:---:|:---:|:---:|
| ASR(Speech Recognition) | FunASR(Local) | 👍XunfeiStreamASR(Xunfei Streaming) |
| LLM(Large Model) | glm-4-flash(Zhipu) | 👍qwen-flash(Alibaba Bailian) |
| VLLM(Vision Large Model) | glm-4v-flash(Zhipu) | 👍qwen2.5-vl-3b-instructh(Alibaba Bailian) |
| TTS(Speech Synthesis) | ✅LinkeraiTTS(Lingxi streaming) | 👍HuoshanDoubleStreamTTS(Volcano Streaming) |
| VLLM(Vision Large Model) | glm-4v-flash(Zhipu) | 👍qwen3.5-flash(Alibaba Bailian) |
| TTS(Speech Synthesis) | EdgeTTS(Microsoft) | 👍HuoshanDoubleStreamTTS(Volcano Streaming) |
| Intent(Intent Recognition) | function_call(Function calling) | function_call(Function calling) |
| Memory(Memory function) | mem_local_short(Local short-term memory) | mem_local_short(Local short-term memory) |
If you are concerned about the latency of each component, please refer to the [Xiaozhi Component Performance Test Report](https://github.com/xinnan-tech/xiaozhi-performance-research), and test in your own environment following the test methods in the report.
#### 🔧 Testing Tools
This project provides the following testing tools to help you verify the system and choose suitable models:
| Tool Name | Location | Usage Method | Function Description |
|:---:|:---|:---:|:---:|
| Audio Interaction Test Tool | main》xiaozhi-server》test》test_page.html | Open directly with Google Chrome | Tests audio playback and reception functions, verifies if Python-side audio processing is normal |
| Model Response Test Tool 1 | main》xiaozhi-server》performance_tester.py | Execute `python performance_tester.py` | Tests response speed of three core modules: ASR(speech recognition), LLM(large model), TTS(speech synthesis) |
| Model Response Test Tool 2 | main》xiaozhi-server》performance_tester_vllm.py | Execute `python performance_tester_vllm.py` | Tests VLLM(vision model) response speed |
| Model Response Test Tool | main》xiaozhi-server》performance_tester.py | Execute `python performance_tester.py` | Tests response speed of three core modules: ASR(speech recognition), LLM(large model), VLLM(vision model), TTS(speech synthesis) |
> 💡 Note: When testing model speed, only models with configured keys will be tested.
@@ -238,10 +241,10 @@ This project provides the following testing tools to help you verify the system
| Intelligent Dialogue | Supports multiple LLM(large language models), implements intelligent dialogue |
| Visual Perception | Supports multiple VLLM(vision large models), implements multimodal interaction |
| Intent Recognition | Supports LLM intent recognition, Function Call function calling, provides plugin-based intent processing mechanism |
| Memory System | Supports local short-term memory, mem0ai interface memory, with memory summarization functionality |
| Memory System | Supports local short-term memory, mem0ai interface memory, PowerMem intelligent memory, with memory summarization functionality |
| Knowledge Base | Supports RAGFlow knowledge base, enabling LLM to judge whether to schedule the knowledge base after receiving the user's question, and then answer the question |
| Command Delivery | Supports MCP command delivery to ESP32 devices via MQTT protocol from Smart Console |
| Tool Calling | Supports client IOT protocol, client MCP protocol, server MCP protocol, MCP endpoint protocol, custom tool functions |
| Command Delivery | Supports MCP command delivery to ESP32 devices via MQTT protocol from Smart Console |
| Management Backend | Provides Web management interface, supports user management, system configuration and device management; Supports Simplified Chinese, Traditional Chinese and English display |
| Testing Tools | Provides performance testing tools, vision model testing tools, and audio interaction testing tools |
| Deployment Support | Supports Docker deployment and local deployment, provides complete configuration file management |
@@ -249,20 +252,14 @@ This project provides the following testing tools to help you verify the system
### Under Development 🚧
To learn about specific development plan progress, [click here](https://github.com/users/xinnan-tech/projects/3)
To learn about specific development plan progress, [click here](https://github.com/users/xinnan-tech/projects/3). For frequently asked questions and related tutorials, please refer to [this link](./docs/FAQ.md)
If you are a software developer, here is an [Open Letter to Developers](docs/contributor_open_letter.md). Welcome to join!
---
## Product Ecosystem 👬
Xiaozhi is an ecosystem. When using this product, you can also check out other [excellent projects](https://github.com/78/xiaozhi-esp32?tab=readme-ov-file#related-open-source-projects) in this ecosystem
| Project Name | Project Address | Project Description |
|:---------------------|:--------|:--------|
| Xiaozhi Android Client | [xiaozhi-android-client](https://github.com/TOM88812/xiaozhi-android-client) | An Android and iOS voice dialogue application based on xiaozhi-server, supporting real-time voice interaction and text dialogue.<br/>Currently a Flutter version, connecting iOS and Android platforms. |
| Xiaozhi Desktop Client | [py-xiaozhi](https://github.com/Huang-junsen/py-xiaozhi) | This project provides a Python-based AI client for beginners, allowing users to experience Xiaozhi AI functionality through code even without physical hardware conditions. |
| Xiaozhi Java Server | [xiaozhi-esp32-server-java](https://github.com/joey-zhou/xiaozhi-esp32-server-java) | Xiaozhi open-source backend service Java version is a Java-based open-source project.<br/>It includes frontend and backend services, aiming to provide users with a complete backend service solution. |
Xiaozhi is an ecosystem. When using this product, you can also check out other [excellent projects](https://github.com/78/xiaozhi-esp32/blob/main/README_zh.md#%E7%9B%B8%E5%85%B3%E5%BC%80%E6%BA%90%E9%A1%B9%E7%9B%AE) in this ecosystem
---
@@ -276,8 +273,10 @@ Xiaozhi is an ecosystem. When using this product, you can also check out other [
| Dify interface calls | Dify | - |
| FastGPT interface calls | FastGPT | - |
| Coze interface calls | Coze | - |
| Xinference interface calls | Xinference | - |
| HomeAssistant interface calls | HomeAssistant | - |
In fact, any LLM that supports OpenAI interface calls can be integrated and used, including Xinference and HomeAssistant interfaces.
In fact, any LLM that supports OpenAI interface calls can be integrated and used.
---
@@ -296,7 +295,7 @@ In fact, any VLLM that supports OpenAI interface calls can be integrated and use
| Usage Method | Supported Platforms | Free Platforms |
|:---:|:---:|:---:|
| Interface calls | EdgeTTS, iFLYTEK, Volcano Engine, Tencent Cloud, Alibaba Cloud and Bailian, CosyVoiceSiliconflow, TTS302AI, CozeCnTTS, GizwitsTTS, ACGNTTS, OpenAITTS, Lingxi Streaming TTS, MinimaxTTS | Lingxi Streaming TTS, EdgeTTS, CosyVoiceSiliconflow(partial) |
| Local services | FishSpeech, GPT_SOVITS_V2, GPT_SOVITS_V3, MinimaxTTS | FishSpeech, GPT_SOVITS_V2, GPT_SOVITS_V3, MinimaxTTS |
| Local services | FishSpeech, GPT_SOVITS_V2, GPT_SOVITS_V3, Index-TTS, PaddleSpeech | Index-TTS, PaddleSpeech, FishSpeech, GPT_SOVITS_V2, GPT_SOVITS_V3 |
---
@@ -330,7 +329,9 @@ In fact, any VLLM that supports OpenAI interface calls can be integrated and use
| Type | Platform Name | Usage Method | Pricing Model | Notes |
|:------:|:---------------:|:----:|:---------:|:--:|
| Memory | mem0ai | Interface calls | 1000 times/month quota | |
| Memory | [powermem](./docs/powermem-integration.md) | Local summarization | Depends on LLM and DB | OceanBase open source, supports intelligent retrieval |
| Memory | mem_local_short | Local summarization | Free | |
| Memory | nomem | No memory mode | Free | |
---
@@ -340,6 +341,7 @@ In fact, any VLLM that supports OpenAI interface calls can be integrated and use
|:------:|:-------------:|:----:|:-------:|:---------------------:|
| Intent | intent_llm | Interface calls | Based on LLM pricing | Recognizes intent through large models, strong generalization |
| Intent | function_call | Interface calls | Based on LLM pricing | Completes intent through large model function calling, fast speed, good effect |
| Intent | nointent | No intent mode | Free | Does not perform intent recognition, directly returns dialogue result |
---
+376
View File
@@ -0,0 +1,376 @@
[![Banners](docs/images/banner1.png)](https://github.com/xinnan-tech/xiaozhi-esp32-server)
<h1 align="center">Serviço Backend Xiaozhi xiaozhi-esp32-server</h1>
<p align="center">
Este projeto é baseado na teoria e tecnologia de inteligência simbiótica humano-máquina para desenvolver sistemas inteligentes de hardware e software para terminais<br/>fornecendo serviços de backend para o projeto de hardware inteligente de código aberto
<a href="https://github.com/78/xiaozhi-esp32">xiaozhi-esp32</a><br/>
Implementado usando Python, Java e Vue de acordo com o <a href="https://ccnphfhqs21z.feishu.cn/wiki/M0XiwldO9iJwHikpXD5cEx71nKh">Protocolo de Comunicação Xiaozhi</a><br/>
Suporte ao protocolo MQTT+UDP, protocolo WebSocket, ponto de acesso MCP, reconhecimento de impressão vocal e base de conhecimento
</p>
<p align="center">
<a href="./docs/FAQ.md">Perguntas Frequentes</a>
· <a href="https://github.com/xinnan-tech/xiaozhi-esp32-server/issues">Reportar Problemas</a>
· <a href="./README.md#%E9%83%A8%E7%BD%B2%E6%96%87%E6%A1%A3">Documentação de Implantação</a>
· <a href="https://github.com/xinnan-tech/xiaozhi-esp32-server/releases">Notas de Lançamento</a>
</p>
<p align="center">
<a href="./README.md"><img alt="简体中文版自述文件" src="https://img.shields.io/badge/简体中文-DFE0E5"></a>
<a href="./README_en.md"><img alt="README in English" src="https://img.shields.io/badge/English-DFE0E5"></a>
<a href="./README_vi.md"><img alt="Tiếng Việt" src="https://img.shields.io/badge/Tiếng Việt-DFE0E5"></a>
<a href="./README_de.md"><img alt="Deutsch" src="https://img.shields.io/badge/Deutsch-DFE0E5"></a>
<a href="./README_pt_BR.md"><img alt="Português (Brasil)" src="https://img.shields.io/badge/Português (Brasil)-DBEDFA"></a>
<a href="https://github.com/xinnan-tech/xiaozhi-esp32-server/releases">
<img alt="GitHub Contributors" src="https://img.shields.io/github/v/release/xinnan-tech/xiaozhi-esp32-server?logo=docker" />
</a>
<a href="https://github.com/xinnan-tech/xiaozhi-esp32-server/blob/main/LICENSE">
<img alt="GitHub pull requests" src="https://img.shields.io/badge/license-MIT-white?labelColor=black" />
</a>
<a href="https://github.com/xinnan-tech/xiaozhi-esp32-server">
<img alt="stars" src="https://img.shields.io/github/stars/xinnan-tech/xiaozhi-esp32-server?color=ffcb47&labelColor=black" />
</a>
</p>
<p align="center">
Liderado pela Equipe do Professor Siyuan Liu (Universidade de Tecnologia do Sul da China)
</br>
刘思源教授团队主导研发(华南理工大学)
</br>
<img src="./docs/images/hnlg.jpg" alt="Universidade de Tecnologia do Sul da China (华南理工大学)" width="50%">
</p>
---
## Público-Alvo 👥
Este projeto requer dispositivos de hardware ESP32 para funcionar. Se você adquiriu hardware relacionado ao ESP32, conectou-se com sucesso ao serviço backend implantado pelo Brother Xia e deseja construir seu próprio serviço backend `xiaozhi-esp32` de forma independente, então este projeto é perfeito para você.
Quer ver os efeitos de uso? Clique nos vídeos abaixo 🎥
<table>
<tr>
<td>
<a href="https://www.bilibili.com/video/BV1FMFyejExX" target="_blank">
<picture>
<img alt="Experiência de velocidade de resposta" src="docs/images/demo9.png" />
</picture>
</a>
</td>
<td>
<a href="https://www.bilibili.com/video/BV1vchQzaEse" target="_blank">
<picture>
<img alt="Segredo da otimização de velocidade" src="docs/images/demo6.png" />
</picture>
</a>
</td>
<td>
<a href="https://www.bilibili.com/video/BV1C1tCzUEZh" target="_blank">
<picture>
<img alt="Cenário médico complexo" src="docs/images/demo1.png" />
</picture>
</a>
</td>
<td>
<a href="https://www.bilibili.com/video/BV1zUW5zJEkq" target="_blank">
<picture>
<img alt="Envio de comandos MQTT" src="docs/images/demo4.png" />
</picture>
</a>
</td>
<td>
<a href="https://www.bilibili.com/video/BV1Exu3zqEDe" target="_blank">
<picture>
<img alt="Reconhecimento de impressão vocal" src="docs/images/demo14.png" />
</picture>
</a>
</td>
</tr>
<tr>
<td>
<a href="https://www.bilibili.com/video/BV1pNXWYGEx1" target="_blank">
<picture>
<img alt="Controle de interruptores de eletrodomésticos" src="docs/images/demo5.png" />
</picture>
</a>
</td>
<td>
<a href="https://www.bilibili.com/video/BV1ZQKUzYExM" target="_blank">
<picture>
<img alt="Ponto de acesso MCP" src="docs/images/demo13.png" />
</picture>
</a>
</td>
<td>
<a href="https://www.bilibili.com/video/BV1TJ7WzzEo6" target="_blank">
<picture>
<img alt="Tarefas com múltiplos comandos" src="docs/images/demo11.png" />
</picture>
</a>
</td>
<td>
<a href="https://www.bilibili.com/video/BV1VC96Y5EMH" target="_blank">
<picture>
<img alt="Reproduzir música" src="docs/images/demo7.png" />
</picture>
</a>
</td>
<td>
<a href="https://www.bilibili.com/video/BV1Z8XuYZEAS" target="_blank">
<picture>
<img alt="Plugin de clima" src="docs/images/demo8.png" />
</picture>
</a>
</td>
</tr>
<tr>
<td>
<a href="https://www.bilibili.com/video/BV12J7WzBEaH" target="_blank">
<picture>
<img alt="Interrupção em tempo real" src="docs/images/demo10.png" />
</picture>
</a>
</td>
<td>
<a href="https://www.bilibili.com/video/BV1Co76z7EvK" target="_blank">
<picture>
<img alt="Fotografar e identificar objetos" src="docs/images/demo12.png" />
</picture>
</a>
</td>
<td>
<a href="https://www.bilibili.com/video/BV1CDKWemEU6" target="_blank">
<picture>
<img alt="Timbre de voz personalizado" src="docs/images/demo2.png" />
</picture>
</a>
</td>
<td>
<a href="https://www.bilibili.com/video/BV12yA2egEaC" target="_blank">
<picture>
<img alt="Comunicação em cantonês" src="docs/images/demo3.png" />
</picture>
</a>
</td>
<td>
<a href="https://www.bilibili.com/video/BV17LXWYvENb" target="_blank">
<picture>
<img alt="Transmissão de notícias" src="docs/images/demo0.png" />
</picture>
</a>
</td>
</tr>
</table>
---
## Avisos ⚠️
1. Este projeto é um software de código aberto. Este software não possui parceria comercial com nenhum provedor de serviços de API de terceiros (incluindo, mas não se limitando a reconhecimento de fala, modelos de linguagem, síntese de voz e outras plataformas) com os quais se conecta, e não fornece nenhuma forma de garantia quanto à qualidade de serviço ou segurança financeira desses provedores. Recomenda-se que os usuários priorizem provedores de serviço com licenças comerciais relevantes e leiam cuidadosamente seus termos de serviço e políticas de privacidade. Este software não armazena nenhuma chave de conta, não participa de fluxos de fundos e não assume o risco de perda de fundos recarregados.
2. A funcionalidade deste projeto não está completa e não passou por avaliação de segurança de rede. Por favor, não o utilize em ambientes de produção. Se você implantar este projeto para fins de aprendizado em um ambiente de rede pública, certifique-se de que as medidas de proteção necessárias estejam em vigor.
---
## Documentação de Implantação
![Banners](docs/images/banner2.png)
Este projeto oferece dois métodos de implantação. Por favor, escolha de acordo com suas necessidades específicas:
#### 🚀 Seleção do Método de Implantação
| Método de Implantação | Funcionalidades | Cenários Aplicáveis | Documentação de Implantação | Requisitos de Configuração | Tutoriais em Vídeo |
|---------|------|---------|---------|---------|---------|
| **Instalação Simplificada** | Diálogo inteligente, gerenciamento de agente único | Ambientes de baixa configuração, dados armazenados em arquivos de configuração, sem necessidade de banco de dados | [①Versão Docker](./docs/Deployment.md#%E6%96%B9%E5%BC%8F%E4%B8%80docker%E5%8F%AA%E8%BF%90%E8%A1%8Cserver) / [②Implantação via Código-Fonte](./docs/Deployment.md#%E6%96%B9%E5%BC%8F%E4%BA%8C%E6%9C%AC%E5%9C%B0%E6%BA%90%E7%A0%81%E5%8F%AA%E8%BF%90%E8%A1%8Cserver)| 2 núcleos 4GB se usar `FunASR`, 2 núcleos 2GB se todas APIs | - |
| **Instalação de Módulo Completo** | Diálogo inteligente, gerenciamento multiusuário, gerenciamento de múltiplos agentes, operação de interface do console inteligente | Experiência com funcionalidade completa, dados armazenados em banco de dados |[①Versão Docker](./docs/Deployment_all.md#%E6%96%B9%E5%BC%8F%E4%B8%80docker%E8%BF%90%E8%A1%8C%E5%85%A8%E6%A8%A1%E5%9D%97) / [②Implantação via Código-Fonte](./docs/Deployment_all.md#%E6%96%B9%E5%BC%8F%E4%BA%8C%E6%9C%AC%E5%9C%B0%E6%BA%90%E7%A0%81%E8%BF%90%E8%A1%8C%E5%85%A8%E6%A8%A1%E5%9D%97) / [③Tutorial de Atualização Automática via Código-Fonte](./docs/dev-ops-integration.md) | 4 núcleos 8GB se usar `FunASR`, 2 núcleos 4GB se todas APIs| [Tutorial em Vídeo de Inicialização via Código-Fonte Local](https://www.bilibili.com/video/BV1wBJhz4Ewe) |
Perguntas frequentes e tutoriais relacionados podem ser consultados [neste link](./docs/FAQ.md)
> 💡 Nota: Abaixo está uma plataforma de teste implantada com o código mais recente. Você pode gravar e testar se necessário. Usuários simultâneos: 6, os dados serão limpos diariamente.
```
Endereço do Console de Controle Inteligente: https://2662r3426b.vicp.fun
Endereço do Console de Controle Inteligente (H5): https://2662r3426b.vicp.fun/h5/index.html
Ferramenta de Teste de Serviço: https://2662r3426b.vicp.fun/test/
Endereço da Interface OTA: https://2662r3426b.vicp.fun/xiaozhi/ota/
Endereço da Interface WebSocket: wss://2662r3426b.vicp.fun/xiaozhi/v1/
```
#### 🚩 Descrição e Recomendações de Configuração
> [!Note]
> Este projeto oferece dois esquemas de configuração:
>
> 1. `Configurações Gratuitas Nível Básico`: Adequado para uso pessoal e doméstico, todos os componentes utilizam soluções gratuitas, sem necessidade de pagamento adicional.
>
> 2. `Configuração de Streaming`: Adequado para demonstrações, treinamentos, cenários com mais de 2 usuários simultâneos, etc. Utiliza tecnologia de processamento em streaming para velocidade de resposta mais rápida e melhor experiência.
>
> A partir da versão `0.5.2`, o projeto suporta configuração de streaming. Em comparação com versões anteriores, a velocidade de resposta é melhorada em aproximadamente `2,5 segundos`, melhorando significativamente a experiência do usuário.
| Nome do Módulo | Configurações Gratuitas Nível Básico | Configuração de Streaming |
|:---:|:---:|:---:|
| ASR(Reconhecimento de Fala) | FunASR(Local) | 👍XunfeiStreamASR(Xunfei Streaming) |
| LLM(Modelo de Linguagem) | glm-4-flash(Zhipu) | 👍qwen-flash(Alibaba Bailian) |
| VLLM(Modelo de Visão) | glm-4v-flash(Zhipu) | 👍qwen3.5-flash(Alibaba Bailian) |
| TTS(Síntese de Voz) | EdgeTTS(Microsoft) | 👍HuoshanDoubleStreamTTS(Volcano Streaming) |
| Intent(Reconhecimento de Intenção) | function_call(Chamada de função) | function_call(Chamada de função) |
| Memory(Função de Memória) | mem_local_short(Memória local de curto prazo) | mem_local_short(Memória local de curto prazo) |
Se você está preocupado com o tempo de resposta de cada componente, consulte o [Relatório de Teste de Desempenho dos Componentes Xiaozhi](https://github.com/xinnan-tech/xiaozhi-performance-research), e teste em seu próprio ambiente seguindo os métodos de teste do relatório.
#### 🔧 Ferramentas de Teste
Este projeto fornece as seguintes ferramentas de teste para ajudá-lo a verificar o sistema e escolher modelos adequados:
| Nome da Ferramenta | Localização | Método de Uso | Descrição da Função |
|:---:|:---|:---:|:---:|
| Ferramenta de Teste de Interação por Áudio | main》xiaozhi-server》test》test_page.html | Abrir diretamente com Google Chrome | Testa as funções de reprodução e recepção de áudio, verifica se o processamento de áudio no lado Python está normal |
| Ferramenta de Teste de Resposta de Modelo | main》xiaozhi-server》performance_tester.py | Execute `python performance_tester.py` | Testa a velocidade de resposta dos três módulos principais: ASR(reconhecimento de fala), LLM(modelo de linguagem), VLLM(modelo de visão), TTS(síntese de voz) |
> 💡 Nota: Ao testar a velocidade dos modelos, apenas os modelos com chaves configuradas serão testados.
---
## Lista de Funcionalidades ✨
### Implementado ✅
![请参考-全模块安装架构图](docs/images/deploy2.png)
| Módulo de Funcionalidade | Descrição |
|:---:|:---|
| Arquitetura Principal | Baseado em [gateway MQTT+UDP](https://github.com/xinnan-tech/xiaozhi-esp32-server/blob/main/docs/mqtt-gateway-integration.md), servidores WebSocket e HTTP, fornece sistema completo de gerenciamento de console e autenticação |
| Interação por Voz | Suporta ASR em streaming (reconhecimento de fala), TTS em streaming (síntese de voz), VAD (detecção de atividade vocal), suporta reconhecimento multilíngue e processamento de voz |
| Reconhecimento de Impressão Vocal | Suporta registro, gerenciamento e reconhecimento de impressão vocal de múltiplos usuários, processa em paralelo com o ASR, reconhecimento de identidade do falante em tempo real e repassa ao LLM para respostas personalizadas |
| Diálogo Inteligente | Suporta múltiplos LLM (modelos de linguagem de grande porte), implementa diálogo inteligente |
| Percepção Visual | Suporta múltiplos VLLM (modelos de visão de grande porte), implementa interação multimodal |
| Reconhecimento de Intenção | Suporta reconhecimento de intenção por LLM, Function Call (chamada de função), fornece mecanismo de processamento de intenção baseado em plugins |
| Sistema de Memória | Suporta memória local de curto prazo, memória via interface mem0ai, memória inteligente PowerMem, com funcionalidade de resumo de memória |
| Base de Conhecimento | Suporta base de conhecimento RAGFlow, permitindo que o LLM julgue se deve acionar a base de conhecimento após receber a pergunta do usuário, e então responda à pergunta |
| Chamada de Ferramentas | Suporta protocolo IOT do cliente, protocolo MCP do cliente, protocolo MCP do servidor, protocolo de endpoint MCP, funções de ferramentas personalizadas |
| Envio de Comandos | Suporta envio de comandos MCP para dispositivos ESP32 via protocolo MQTT a partir do Console Inteligente |
| Backend de Gerenciamento | Fornece interface de gerenciamento Web, suporta gerenciamento de usuários, configuração do sistema e gerenciamento de dispositivos; Suporta exibição em Chinês Simplificado, Chinês Tradicional e Inglês |
| Ferramentas de Teste | Fornece ferramentas de teste de desempenho, ferramentas de teste de modelo de visão e ferramentas de teste de interação por áudio |
| Suporte à Implantação | Suporta implantação via Docker e implantação local, fornece gerenciamento completo de arquivos de configuração |
| Sistema de Plugins | Suporta extensões de plugins funcionais, desenvolvimento de plugins personalizados e carregamento dinâmico de plugins |
### Em Desenvolvimento 🚧
Para conhecer o progresso específico do plano de desenvolvimento, [clique aqui](https://github.com/users/xinnan-tech/projects/3). Perguntas frequentes e tutoriais relacionados podem ser consultados [neste link](./docs/FAQ.md)
Se você é um desenvolvedor de software, aqui está uma [Carta Aberta aos Desenvolvedores](docs/contributor_open_letter.md). Seja bem-vindo a participar!
---
## Ecossistema do Produto 👬
Xiaozhi é um ecossistema. Ao utilizar este produto, você também pode conferir outros [projetos excelentes](https://github.com/78/xiaozhi-esp32/blob/main/README_zh.md#%E7%9B%B8%E5%85%B3%E5%BC%80%E6%BA%90%E9%A1%B9%E7%9B%AE) neste ecossistema
---
## Lista de Plataformas/Componentes Suportados 📋
### LLM Modelos de Linguagem
| Método de Uso | Plataformas Suportadas | Plataformas Gratuitas |
|:---:|:---:|:---:|
| Chamadas via interface OpenAI | Alibaba Bailian, Volcano Engine, DeepSeek, Zhipu, Gemini, iFLYTEK | Zhipu, Gemini |
| Chamadas via interface Ollama | Ollama | - |
| Chamadas via interface Dify | Dify | - |
| Chamadas via interface FastGPT | FastGPT | - |
| Chamadas via interface Coze | Coze | - |
| Chamadas via interface Xinference | Xinference | - |
| Chamadas via interface HomeAssistant | HomeAssistant | - |
Na verdade, qualquer LLM que suporte chamadas via interface openai pode ser integrado e utilizado.
---
### VLLM Modelos de Visão
| Método de Uso | Plataformas Suportadas | Plataformas Gratuitas |
|:---:|:---:|:---:|
| Chamadas via interface OpenAI | Alibaba Bailian, Zhipu ChatGLMVLLM | Zhipu ChatGLMVLLM |
Na verdade, qualquer VLLM que suporte chamadas via interface OpenAI pode ser integrado e utilizado.
---
### TTS Síntese de Voz
| Método de Uso | Plataformas Suportadas | Plataformas Gratuitas |
|:---:|:---:|:---:|
| Chamadas via interface | EdgeTTS, iFLYTEK, Volcano Engine, Tencent Cloud, Alibaba Cloud e Bailian, CosyVoiceSiliconflow, TTS302AI, CozeCnTTS, GizwitsTTS, ACGNTTS, OpenAITTS, Lingxi Streaming TTS, MinimaxTTS | Lingxi Streaming TTS, EdgeTTS, CosyVoiceSiliconflow(parcial) |
| Serviços locais | FishSpeech, GPT_SOVITS_V2, GPT_SOVITS_V3, Index-TTS, PaddleSpeech | Index-TTS, PaddleSpeech, FishSpeech, GPT_SOVITS_V2, GPT_SOVITS_V3 |
---
### VAD Detecção de Atividade Vocal
| Tipo | Nome da Plataforma | Método de Uso | Modelo de Preço | Observações |
|:---:|:---------:|:----:|:----:|:--:|
| VAD | SileroVAD | Uso local | Gratuito | |
---
### ASR Reconhecimento de Fala
| Método de Uso | Plataformas Suportadas | Plataformas Gratuitas |
|:---:|:---:|:---:|
| Uso local | FunASR, SherpaASR | FunASR, SherpaASR |
| Chamadas via interface | FunASRServer, Volcano Engine, iFLYTEK, Tencent Cloud, Alibaba Cloud, Baidu Cloud, OpenAI ASR | FunASRServer |
---
### Reconhecimento de Impressão Vocal
| Método de Uso | Plataformas Suportadas | Plataformas Gratuitas |
|:---:|:---:|:---:|
| Uso local | 3D-Speaker | 3D-Speaker |
---
### Armazenamento de Memória
| Tipo | Nome da Plataforma | Método de Uso | Modelo de Preço | Observações |
|:------:|:---------------:|:----:|:---------:|:--:|
| Memória | mem0ai | Chamadas via interface | Cota de 1000 vezes/mês | |
| Memória | [powermem](./docs/powermem-integration.md) | Resumo local | Depende do LLM e BD | OceanBase de código aberto, suporta busca inteligente |
| Memória | mem_local_short | Resumo local | Gratuito | |
| Memória | nomem | Modo sem memória | Gratuito | |
---
### Reconhecimento de Intenção
| Tipo | Nome da Plataforma | Método de Uso | Modelo de Preço | Observações |
|:------:|:-------------:|:----:|:-------:|:---------------------:|
| Intenção | intent_llm | Chamadas via interface | Baseado no preço do LLM | Reconhece intenção através de modelos de linguagem, forte generalização |
| Intenção | function_call | Chamadas via interface | Baseado no preço do LLM | Completa a intenção através de chamada de função do modelo de linguagem, velocidade rápida, bom resultado |
| Intenção | nointent | Modo sem intenção | Gratuito | Não realiza reconhecimento de intenção, retorna diretamente o resultado do diálogo |
---
### RAG Geração Aumentada por Recuperação
| Tipo | Nome da Plataforma | Método de Uso | Modelo de Preço | Observações |
|:------:|:-------------:|:----:|:-------:|:---------------------:|
| RAG | ragflow | Chamadas via interface | Cobrado com base nos tokens consumidos para fatiamento e segmentação de palavras | Utiliza o recurso de geração aumentada por recuperação do RagFlow para fornecer respostas de diálogo mais precisas |
---
## Agradecimentos 🙏
| Logo | Projeto/Empresa | Descrição |
|:---:|:---:|:---|
| <img src="./docs/images/logo_bailing.png" width="160"> | [Robô de Diálogo por Voz Bailing](https://github.com/wwbin2017/bailing) | Este projeto foi inspirado pelo [Robô de Diálogo por Voz Bailing](https://github.com/wwbin2017/bailing) e implementado com base nele |
| <img src="./docs/images/logo_tenclass.png" width="160"> | [Tenclass](https://www.tenclass.com/) | Agradecimentos à [Tenclass](https://www.tenclass.com/) por formular protocolos de comunicação padrão, soluções de compatibilidade multidispositivo e demonstrações práticas de cenários de alta concorrência para o ecossistema Xiaozhi; fornecendo suporte completo de documentação técnica para este projeto |
| <img src="./docs/images/logo_xuanfeng.png" width="160"> | [Xuanfeng Technology (玄凤科技)](https://github.com/Eric0308) | Agradecimentos à [Xuanfeng Technology](https://github.com/Eric0308) por contribuir com o framework de chamada de função, protocolo de comunicação MCP e implementação do mecanismo de chamada baseado em plugins. Através de um sistema padronizado de agendamento de instruções e capacidades de expansão dinâmica, melhora significativamente a eficiência de interação e extensibilidade funcional dos dispositivos de frontend (IoT) |
| <img src="./docs/images/logo_junsen.png" width="160"> | [huangjunsen](https://github.com/huangjunsen0406) | Agradecimentos a [huangjunsen](https://github.com/huangjunsen0406) por contribuir com o módulo `Console de Controle Inteligente Mobile`, que permite controle eficiente e interação em tempo real em dispositivos móveis, melhorando significativamente a conveniência operacional e a eficiência de gerenciamento do sistema em cenários móveis. |
| <img src="./docs/images/logo_huiyuan.png" width="160"> | [Huiyuan Design (汇远设计)](http://ui.kwd988.net/) | Agradecimentos à [Huiyuan Design](http://ui.kwd988.net/) por fornecer soluções visuais profissionais para este projeto, utilizando sua experiência prática de design atendendo mais de mil empresas para potencializar a experiência do usuário deste produto |
| <img src="./docs/images/logo_qinren.png" width="160"> | [Xi'an Qinren Information Technology (西安勤人信息科技)](https://www.029app.com/) | Agradecimentos à [Xi'an Qinren Information Technology](https://www.029app.com/) por aprofundar o sistema visual deste projeto, garantindo consistência e extensibilidade do estilo de design geral em aplicações de múltiplos cenários |
| <img src="./docs/images/logo_contributors.png" width="160"> | [Contribuidores de Código](https://github.com/xinnan-tech/xiaozhi-esp32-server/graphs/contributors) | Agradecimentos a [todos os contribuidores de código](https://github.com/xinnan-tech/xiaozhi-esp32-server/graphs/contributors), seus esforços tornaram o projeto mais robusto e poderoso. |
<a href="https://star-history.com/#xinnan-tech/xiaozhi-esp32-server&Date">
<picture>
<source media="(prefers-color-scheme: dark)" srcset="https://api.star-history.com/svg?repos=xinnan-tech/xiaozhi-esp32-server&type=Date&theme=dark" />
<source media="(prefers-color-scheme: light)" srcset="https://api.star-history.com/svg?repos=xinnan-tech/xiaozhi-esp32-server&type=Date" />
<img alt="Star History Chart" src="https://api.star-history.com/svg?repos=xinnan-tech/xiaozhi-esp32-server&type=Date" />
</picture>
</a>
+6 -4
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@@ -21,6 +21,7 @@ Hỗ trợ giao thức MQTT+UDP, giao thức Websocket, điểm truy cập MCP,
<a href="./README_en.md"><img alt="README in English" src="https://img.shields.io/badge/English-DFE0E5"></a>
<a href="./README_vi.md"><img alt="Tiếng Việt" src="https://img.shields.io/badge/Tiếng Việt-DBEDFA"></a>
<a href="./README_de.md"><img alt="Deutsch" src="https://img.shields.io/badge/Deutsch-DFE0E5"></a>
<a href="./README_pt_BR.md"><img alt="Português (Brasil)" src="https://img.shields.io/badge/Português (Brasil)-DFE0E5"></a>
<a href="https://github.com/xinnan-tech/xiaozhi-esp32-server/releases">
<img alt="GitHub Contributors" src="https://img.shields.io/github/v/release/xinnan-tech/xiaozhi-esp32-server?logo=docker" />
</a>
@@ -212,8 +213,8 @@ Công cụ kiểm tra dịch vụ: https://2662r3426b.vicp.fun/test/
|:---:|:---:|:---:|
| ASR(Nhận dạng giọng nói) | FunASR(Local) | 👍XunfeiStreamASR(Xunfei Streaming) |
| LLM(Mô hình lớn) | glm-4-flash(Zhipu) | 👍qwen-flash(Alibaba Bailian) |
| VLLM(Mô hình lớn thị giác) | glm-4v-flash(Zhipu) | 👍qwen2.5-vl-3b-instructh(Alibaba Bailian) |
| TTS(Tổng hợp giọng nói) | ✅LinkeraiTTS(Lingxi streaming) | 👍HuoshanDoubleStreamTTS(Volcano Streaming) |
| VLLM(Mô hình lớn thị giác) | glm-4v-flash(Zhipu) | 👍qwen3.5-flash(Alibaba Bailian) |
| TTS(Tổng hợp giọng nói) | EdgeTTS(Microsoft) | 👍HuoshanDoubleStreamTTS(Volcano Streaming) |
| Intent(Nhận dạng ý định) | function_call(Gọi hàm) | function_call(Gọi hàm) |
| Memory(Chức năng bộ nhớ) | mem_local_short(Bộ nhớ ngắn hạn cục bộ) | mem_local_short(Bộ nhớ ngắn hạn cục bộ) |
@@ -241,7 +242,7 @@ Dự án này cung cấp các công cụ kiểm tra sau để giúp bạn xác m
| Đối thoại thông minh | Hỗ trợ nhiều LLM(Mô hình ngôn ngữ lớn), thực hiện đối thoại thông minh |
| Cảm nhận thị giác | Hỗ trợ nhiều VLLM(Mô hình lớn thị giác), thực hiện tương tác đa phương thức |
| Nhận dạng ý định | Hỗ trợ nhận dạng ý định mô hình lớn gắn ngoài, gọi hàm tự chủ mô hình lớn, cung cấp cơ chế xử lý ý định dạng plugin |
| Hệ thống bộ nhớ | Hỗ trợ bộ nhớ ngắn hạn cục bộ, bộ nhớ giao diện mem0ai, có chức năng tóm tắt bộ nhớ |
| Hệ thống bộ nhớ | Hỗ trợ bộ nhớ ngắn hạn cục bộ, bộ nhớ giao diện mem0ai, bộ nhớ thông minh PowerMem, có chức năng tóm tắt bộ nhớ |
| Kho tri thức | Hỗ trợ kho tri thức RAGFlow, cho phép mô hình lớn đánh giá cần gọi kho tri thức trước khi trả lời |
| Gọi công cụ | Hỗ trợ giao thức IOT phía client, giao thức MCP phía client, giao thức MCP phía server, giao thức điểm truy cập MCP, hàm công cụ tùy chỉnh |
| Gửi lệnh | Dựa vào giao thức MQTT, hỗ trợ gửi lệnh MCP từ bảng điều khiển thông minh xuống thiết bị ESP32 |
@@ -259,7 +260,7 @@ Nếu bạn là một nhà phát triển phần mềm, đây có một [Lá thư
---
## Hệ sinh thái sản phẩm 👬
Xiaozhi là một hệ sinh thái, khi bạn sử dụng sản phẩm này, bạn cũng có thể xem các [dự án xuất sắc](https://github.com/78/xiaozhi-esp32?tab=readme-ov-file#related-open-source-projects) khác trong hệ sinh thái này
Xiaozhi là một hệ sinh thái, khi bạn sử dụng sản phẩm này, bạn cũng có thể xem các [dự án xuất sắc](https://github.com/78/xiaozhi-esp32/blob/main/README_zh.md#%E7%9B%B8%E5%85%B3%E5%BC%80%E6%BA%90%E9%A1%B9%E7%9B%AE) khác trong hệ sinh thái này
---
@@ -329,6 +330,7 @@ Trên thực tế, bất kỳ VLLM nào hỗ trợ gọi giao diện openai đ
| Loại | Tên nền tảng | Phương pháp sử dụng | Mô hình thu phí | Ghi chú |
|:------:|:---------------:|:----:|:---------:|:--:|
| Memory | mem0ai | Gọi giao diện | Hạn mức 1000 lần/tháng | |
| Memory | [powermem](./docs/powermem-integration.md) | Tóm tắt cục bộ | Phụ thuộc vào LLM và DB | OceanBase mã nguồn mở, hỗ trợ tìm kiếm thông minh |
| Memory | mem_local_short | Tóm tắt cục bộ | Miễn phí | |
| Memory | nomem | Chế độ không có bộ nhớ | Miễn phí | |
+1 -1
View File
@@ -418,7 +418,7 @@ manager-api:
secret: 12345678-xxxx-xxxx-xxxx-123456789000
```
## 5.运行项目
## 9.运行项目
```
# 确保在xiaozhi-server目录下执行
+4 -2
View File
@@ -40,8 +40,8 @@ conda install conda-forge::ffmpeg
|:---:|:---:|:---:|
| ASR(语音识别) | FunASR(本地) | 👍XunfeiStreamASR(讯飞流式) |
| LLM(大模型) | glm-4-flash(智谱) | 👍qwen-flash(阿里百炼) |
| VLLM(视觉大模型) | glm-4v-flash(智谱) | 👍qwen2.5-vl-3b-instructh(阿里百炼) |
| TTS(语音合成) | ✅LinkeraiTTS(灵犀流式) | 👍HuoshanDoubleStreamTTS(火山流式) |
| VLLM(视觉大模型) | glm-4v-flash(智谱) | 👍qwen3.5-flash(阿里百炼) |
| TTS(语音合成) | EdgeTTS(微软) | 👍HuoshanDoubleStreamTTS(火山流式) |
| Intent(意图识别) | function_call(函数调用) | function_call(函数调用) |
| Memory(记忆功能) | mem_local_short(本地短期记忆) | mem_local_short(本地短期记忆) |
@@ -82,6 +82,8 @@ VAD:
8、[新闻插件源配置指南](./newsnow_plugin_config.md)<br/>
9、[知识库ragflow集成指南](./ragflow-integration.md)<br/>
10、[如何部署上下文源](./context-provider-integration.md)<br/>
11、[如何集成PowerMem智能记忆](./powermem-integration.md)<br/>
12、[如何配置天气插件查询天气](./weather-integration.md)<br/>
### 11、语音克隆、本地语音部署相关教程
1、[如何在智控台克隆音色](./huoshan-streamTTS-voice-cloning.md)<br/>
+3 -3
View File
@@ -127,7 +127,7 @@ pm2 restart xz-mqtt
```
192.168.0.7:8884
```
4. 在智控台顶部,点击`参数管理`,搜索`server.mqtt_manager_api`,点击编辑,填入你在`.env`文件中设置的`PUBLIC_IP`+`:`+`UDP_PORT`。类似这样
4. 在智控台顶部,点击`参数管理`,搜索`server.mqtt_manager_api`,点击编辑,填入你在`.env`文件中设置的`PUBLIC_IP`+`:`+`API_PORT`。类似这样
```
192.168.0.7:8007
```
@@ -154,7 +154,7 @@ curl 'http://localhost:8002/xiaozhi/ota/' \
pm2 logs xz-mqtt
```
## 第三部分:模块运行实现小智硬件MQTT+UDP连接
## 第三部分:模块运行xiaozhi-server实现小智硬件MQTT+UDP连接
打开你的`data/.config.yaml`文件,在`server`下找到`mqtt_gateway`填入你在`.env`文件中设置的`PUBLIC_IP`+`:`+`MQTT_PORT`。类似这样
```
@@ -184,4 +184,4 @@ curl 'http://localhost:8002/xiaozhi/ota/' \
唤醒后留意mqtt-gateway的日志,确认是否有连接成功的日志。
```
pm2 logs xz-mqtt
```
```
+345
View File
@@ -0,0 +1,345 @@
# PowerMem 记忆组件集成指南
## 简介
[PowerMem](https://www.powermem.ai/) 是由 OceanBase 开源的 Agent 记忆组件,通过本地 LLM 进行记忆总结和智能检索,为 AI 代理提供高效的记忆管理功能。
费用说明:PowerMem 本身开源免费,实际费用取决于您选择的 LLM 和数据库:
- 使用 SQLite + 免费 LLM(如智谱 glm-4-flash= **完全免费**
- 使用云端 LLM 或云端数据库 = 按对应服务收费
> 💡 **最佳性能提示**PowerMem 配合 OceanBase 使用可实现最大性能释放,SQLite 仅建议在资源不足的情况下使用。
- **GitHub**: https://github.com/oceanbase/powermem
- **官网**: https://www.powermem.ai/
- **使用示例**: https://github.com/oceanbase/powermem/tree/main/examples
## 功能特性
- **本地总结**:通过 LLM 在本地进行记忆总结和提取
- **用户画像**:通过 `UserMemory` 自动提取用户信息(姓名、职业、兴趣等),持续更新用户画像
- **智能遗忘**:基于艾宾浩斯遗忘曲线,自动"遗忘"过时噪声信息
- **多种存储后端**:支持 OceanBase(推荐,最佳性能)、SeekDB(推荐,AI应用存储一体)、PostgreSQL、SQLite(轻量备选)
- **多种 LLM 支持**:通义千问、智谱(glm-4-flash 免费)、OpenAI 等
- **智能检索**:基于向量搜索的语义检索能力
- **私有部署**:完全支持本地私有化部署
- **异步操作**:高效的异步记忆管理
## 安装
PowerMem 已添加到项目依赖中,如果需要手动安装:
```bash
pip install powermem
```
## 配置说明
### 基础配置
`config.yaml` 中配置 PowerMem
```yaml
selected_module:
Memory: powermem
Memory:
powermem:
type: powermem
# 是否启用用户画像功能
# 用户画像支持: oceanbase、seekdb、sqlite (powermem 0.3.0+)
enable_user_profile: true
# ========== LLM 配置 ==========
llm:
provider: openai # 可选: qwen, openai, zhipu 等
config:
api_key: 你的LLM API密钥
model: qwen-plus
# openai_base_url: https://api.openai.com/v1 # 可选,自定义服务地址
# ========== Embedding 配置 ==========
embedder:
provider: openai # 可选: qwen, openai 等
config:
api_key: 你的嵌入模型API密钥
model: text-embedding-v4
openai_base_url: https://dashscope.aliyuncs.com/compatible-mode/v1
# embedding_dims: 1024 # 向量维度,非1536时需配置
# ========== Database 配置 ==========
vector_store:
provider: sqlite # 可选: oceanbase(推荐), seekdb(推荐), postgres, sqlite(轻量)
config: {} # SQLite 无需额外配置
```
### 配置参数详解
#### LLM 配置
| 参数 | 说明 | 可选值 |
|------|------|--------|
| `llm.provider` | LLM 提供商 | `qwen`, `openai`, `zhipu` 等 |
| `llm.config.api_key` | API 密钥 | - |
| `llm.config.model` | 模型名称 | 根据提供商选择 |
| `llm.config.openai_base_url` | 自定义服务地址(可选) | - |
#### Embedding 配置
| 参数 | 说明 | 可选值 |
|------|------|--------|
| `embedder.provider` | 嵌入模型提供商 | `qwen`, `openai` 等 |
| `embedder.config.api_key` | API 密钥 | - |
| `embedder.config.model` | 模型名称 | 根据提供商选择 |
| `embedder.config.openai_base_url` | 自定义服务地址(可选) | - |
#### Database 配置
| 参数 | 说明 | 可选值 |
|------|------|--------|
| `vector_store.provider` | 存储后端类型 | `oceanbase`(推荐), `seekdb`(推荐), `postgres`, `sqlite`(轻量) |
| `vector_store.config` | 数据库连接配置 | 根据 provider 设置 |
### 记忆模式说明
PowerMem 支持两种记忆模式:
| 模式 | 配置 | 功能 | 存储要求 |
|------|------|------|----------|
| **普通记忆** | `enable_user_profile: false` | 对话记忆存储与检索 | 支持所有数据库 |
| **用户画像** | `enable_user_profile: true` | 记忆 + 自动提取用户画像 | oceanbase、seekdb、sqlite |
> 📌 **版本说明**PowerMem 0.3.0+ 版本,用户画像功能支持 OceanBase、SeekDB、SQLite 三种存储后端。
### 使用通义千问(推荐)
1. 访问 [阿里云百炼平台](https://bailian.console.aliyun.com/) 注册账号
2. 在 [API Key 管理](https://bailian.console.aliyun.com/?apiKey=1#/api-key) 页面获取 API 密钥
3. 配置如下:
```yaml
Memory:
powermem:
type: powermem
enable_user_profile: true
llm:
provider: qwen
config:
api_key: sk-xxxxxxxxxxxxxxxx
model: qwen-plus
embedder:
provider: openai
config:
api_key: sk-xxxxxxxxxxxxxxxx
model: text-embedding-v4
openai_base_url: https://dashscope.aliyuncs.com/compatible-mode/v1
vector_store:
provider: sqlite
config: {}
```
### 使用智谱免费 LLM(完全免费方案)
智谱提供免费的 glm-4-flash 模型,配合 SQLite 可实现完全免费使用:
1. 访问 [智谱AI开放平台](https://bigmodel.cn/) 注册账号
2. 在 [API Keys](https://bigmodel.cn/usercenter/proj-mgmt/apikeys) 页面获取 API 密钥
3. 配置如下:
```yaml
Memory:
powermem:
type: powermem
enable_user_profile: true
llm:
provider: openai # 使用 openai 兼容模式
config:
api_key: xxxxxxxxxxxxxxxx.xxxxxxxxxxxxxxxx
model: glm-4-flash
openai_base_url: https://open.bigmodel.cn/api/paas/v4/
embedder:
provider: openai
config:
api_key: xxxxxxxxxxxxxxxx.xxxxxxxxxxxxxxxx
model: embedding-3
openai_base_url: https://open.bigmodel.cn/api/paas/v4/
vector_store:
provider: sqlite
config: {}
```
### 使用 OpenAI
```yaml
Memory:
powermem:
type: powermem
enable_user_profile: true
llm:
provider: openai
config:
api_key: sk-xxxxxxxxxxxxxxxx
model: gpt-4o-mini
openai_base_url: https://api.openai.com/v1
embedder:
provider: openai
config:
api_key: sk-xxxxxxxxxxxxxxxx
model: text-embedding-3-small
openai_base_url: https://api.openai.com/v1
vector_store:
provider: sqlite
config: {}
```
### 使用 OceanBase(最佳性能方案)
OceanBase 是 PowerMem 的最佳搭档,可实现最大性能释放:
1. 部署 OceanBase 数据库(支持开源本地部署或使用云服务)
- 开源部署:https://github.com/oceanbase/oceanbase
- 云服务:https://www.oceanbase.com/
2. 配置如下:
```yaml
Memory:
powermem:
type: powermem
enable_user_profile: true
llm:
provider: qwen
config:
api_key: sk-xxxxxxxxxxxxxxxx
model: qwen-plus
embedder:
provider: openai
config:
api_key: sk-xxxxxxxxxxxxxxxx
model: text-embedding-v4
openai_base_url: https://dashscope.aliyuncs.com/compatible-mode/v1
vector_store:
provider: oceanbase
config:
host: 127.0.0.1
port: 2881
user: root@test
password: your_password
db_name: powermem
collection_name: memories # 默认值
embedding_model_dims: 1536 # 嵌入向量维度,必需参数
```
## 设备记忆隔离
PowerMem 会自动使用设备 ID`device_id`)作为 `user_id` 进行记忆隔离。这意味着:
- 每个设备拥有独立的记忆空间
- 不同设备之间的记忆完全隔离
- 同一设备的多次对话可以共享记忆上下文
## 用户画像(UserMemory
PowerMem 提供 `UserMemory` 类,可自动从对话中提取用户画像信息。
> 📌 **版本说明**PowerMem 0.3.0+ 版本,用户画像功能支持 OceanBase、SeekDB、SQLite 三种存储后端。
### 启用用户画像
在配置中设置 `enable_user_profile: true` 即可启用:
```yaml
Memory:
powermem:
type: powermem
enable_user_profile: true # 启用用户画像
llm:
provider: qwen
config:
api_key: sk-xxxxxxxxxxxxxxxx
model: qwen-plus
embedder:
provider: openai
config:
api_key: sk-xxxxxxxxxxxxxxxx
model: text-embedding-v4
openai_base_url: https://dashscope.aliyuncs.com/compatible-mode/v1
vector_store:
provider: sqlite # 用户画像支持: oceanbase、seekdb、sqlite
config: {}
```
### 用户画像能力
| 能力 | 说明 |
|------|------|
| **信息提取** | 自动从对话中提取姓名、年龄、职业、兴趣等 |
| **持续更新** | 随着对话进行,不断完善用户画像 |
| **画像检索** | 将用户画像与记忆搜索结合,提升检索相关性 |
| **智能遗忘** | 基于艾宾浩斯遗忘曲线,淡化过时信息 |
### 工作原理
启用用户画像后,小智在查询记忆时会自动返回:
1. **用户画像**:用户的基本信息、兴趣爱好等
2. **相关记忆**:与当前对话相关的历史记忆
> ✅ **版本说明**PowerMem 0.3.0+ 版本,用户画像功能支持 OceanBase、SeekDB、SQLite 三种存储后端。
## 与其他记忆组件的对比
| 特性 | PowerMem | mem0ai | mem_local_short |
|------|----------|--------|-----------------|
| 工作方式 | 本地总结 | 云端接口 | 本地总结 |
| 存储位置 | 本地/云端DB | 云端 | 本地YAML |
| 费用 | 取决于LLM和DB | 1000次/月免费 | 完全免费 |
| 智能检索 | ✅ 向量搜索 | ✅ 向量搜索 | ❌ 全量返回 |
| 用户画像 | ✅ UserMemory | ❌ | ❌ |
| 智能遗忘 | ✅ 遗忘曲线 | ❌ | ❌ |
| 私有部署 | ✅ 支持 | ❌ 仅云端 | ✅ 支持 |
| 数据库支持 | OceanBase(推荐)/SeekDB/PostgreSQL/SQLite | - | YAML 文件 |
## 常见问题
### 1. API 密钥错误
如果出现 `API key is required` 错误,请检查:
- `llm_api_key``embedding_api_key` 是否正确填写
- API 密钥是否有效
### 2. 模型不存在
如果出现模型不存在的错误,请确认:
- `llm_model``embedding_model` 名称是否正确
- 对应的模型服务是否已开通
### 3. 连接超时
如果出现连接超时,可以尝试:
- 检查网络连接
- 如果使用代理,配置 `llm_base_url``embedding_base_url`
## 测试验证
可以在虚拟环境中测试 PowerMem 是否正常工作:
```bash
# 激活虚拟环境
source .venv/bin/activate
# 测试 PowerMem 导入
python -c "from powermem import AsyncMemory; print('PowerMem 导入成功')"
# 测试 UserMemory 导入(用户画像功能)
python -c "from powermem import UserMemory; print('UserMemory 导入成功')"
```
## 更多资源
- [PowerMem 官方文档](https://www.powermem.ai/)
- [PowerMem GitHub 仓库](https://github.com/oceanbase/powermem)
- [PowerMem 使用示例](https://github.com/oceanbase/powermem/tree/main/examples)
- [OceanBase 官网](https://www.oceanbase.com/)
- [OceanBase GitHub](https://github.com/oceanbase/oceanbase)
- [SeekDB GitHub](https://github.com/oceanbase/seekdb)AI原生搜索数据库)
- [阿里云百炼平台](https://bailian.console.aliyun.com/)
@@ -2,7 +2,9 @@ package xiaozhi.common.config;
import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.Configuration;
import org.springframework.http.client.JdkClientHttpRequestFactory;
import org.springframework.web.client.RestTemplate;
import java.time.Duration;
/**
* RestTemplate配置
@@ -12,6 +14,8 @@ public class RestTemplateConfig {
@Bean
public RestTemplate restTemplate() {
return new RestTemplate();
JdkClientHttpRequestFactory factory = new JdkClientHttpRequestFactory();
factory.setReadTimeout(Duration.ofSeconds(30));
return new RestTemplate(factory);
}
}
@@ -79,6 +79,30 @@ public class SwaggerConfig {
.build();
}
@Bean
public GroupedOpenApi knowledgeApi() {
return GroupedOpenApi.builder()
.group("knowledge")
.pathsToMatch("/datasets/**")
.build();
}
@Bean
public GroupedOpenApi botApi() {
return GroupedOpenApi.builder()
.group("bot")
.pathsToMatch("/api/v1/**")
.build();
}
@Bean
public GroupedOpenApi correctWordApi() {
return GroupedOpenApi.builder()
.group("correct-word")
.pathsToMatch("/correct-word/**")
.build();
}
@Bean
public OpenAPI customOpenAPI() {
return new OpenAPI().info(new Info()
@@ -151,6 +151,21 @@ public interface Constant {
*/
String MEMORY_NO_MEM = "Memory_nomem";
/**
* 仅上报聊天记录(不总结记忆)
*/
String MEMORY_MEM_REPORT_ONLY = "Memory_mem_report_only";
/**
* Mem0AI记忆
*/
String MEMORY_MEM0AI = "Memory_mem0ai";
/**
* PowerMem记忆
*/
String MEMORY_POWERMEM = "Memory_powermem";
/**
* 火山引擎双声道语音克隆
*/
@@ -304,7 +319,7 @@ public interface Constant {
/**
* 版本号
*/
public static final String VERSION = "0.9.1";
public static final String VERSION = "0.9.3";
/**
* 无效固件URL
@@ -245,4 +245,19 @@ public interface ErrorCode {
int DEVICE_NOT_EXIST = 10194; // 设备不存在
int OTA_UPLOAD_COUNT_EXCEED = 10195; // OTA上传次数超过限制
// 智能体标签相关错误码
int AGENT_TAG_NAME_DUPLICATE = 10196; // 标签名称已存在
int AGENT_TAG_NAME_EMPTY = 10197; // 标签名称不能为空
int AGENT_TAG_NOT_EXIST = 10198; // 标签不存在
int RAG_DOCUMENT_PARSING_DELETE_ERROR = 10199; // 文档解析中,禁止删除
// 智能体MCP相关错误码
int MCP_ACCESS_POINT_ADDRESS_NO_PERMISSION = 10200; // 没有权限查看该智能体的MCP接入点地址
int MCP_ACCESS_POINT_ADDRESS_NOT_CONFIGURED = 10201; // 请联系管理员进入参数管理配置mcp接入点地址
int MCP_ACCESS_POINT_TOOLS_LIST_NO_PERMISSION = 10202; // 没有权限查看该智能体的MCP工具列表
// 替换词相关错误码
int CORRECT_WORD_FILE_NAME_EXISTS = 10203; // 文件名已存在
int FILE_SIZE_OVER_LIMIT = 10204; // 文件大小超过限制
}
@@ -13,23 +13,25 @@ public class RenException extends RuntimeException {
private String msg;
public RenException(int code) {
super(MessageUtils.getMessage(code));
this.code = code;
this.msg = MessageUtils.getMessage(code);
}
public RenException(int code, String... params) {
super(MessageUtils.getMessage(code, params));
this.code = code;
this.msg = MessageUtils.getMessage(code, params);
}
public RenException(int code, Throwable e) {
super(e);
super(MessageUtils.getMessage(code), e);
this.code = code;
this.msg = MessageUtils.getMessage(code);
}
public RenException(int code, Throwable e, String... params) {
super(e);
super(MessageUtils.getMessage(code, params), e);
this.code = code;
this.msg = MessageUtils.getMessage(code, params);
}
@@ -187,4 +187,5 @@ public class RedisKeys {
public static String getOtaUploadCountKey(Long username) {
return "ota:upload:count:" + username;
}
}
@@ -12,28 +12,29 @@ import xiaozhi.modules.sys.service.SysParamsService;
* 封装了重复的SM2解密、验证码提取和验证逻辑
*/
public class Sm2DecryptUtil {
/**
* 验证码长度
*/
private static final int CAPTCHA_LENGTH = 5;
/**
* 解密SM2加密内容,提取验证码并验证
*
* @param encryptedPassword SM2加密的密码字符串
* @param captchaId 验证码ID
* @param captchaService 验证码服务
* @param sysParamsService 系统参数服务
* @param captchaId 验证码ID
* @param captchaService 验证码服务
* @param sysParamsService 系统参数服务
* @return 解密后的实际密码
*/
public static String decryptAndValidateCaptcha(String encryptedPassword, String captchaId,
CaptchaService captchaService, SysParamsService sysParamsService) {
public static String decryptAndValidateCaptcha(String encryptedPassword, String captchaId,
CaptchaService captchaService, SysParamsService sysParamsService) {
// 获取SM2私钥
String privateKeyStr = sysParamsService.getValue(Constant.SM2_PRIVATE_KEY, true);
if (StringUtils.isBlank(privateKeyStr)) {
throw new RenException(ErrorCode.SM2_KEY_NOT_CONFIGURED);
}
// 使用SM2私钥解密密码
String decryptedContent;
try {
@@ -41,19 +42,20 @@ public class Sm2DecryptUtil {
} catch (Exception e) {
throw new RenException(ErrorCode.SM2_DECRYPT_ERROR);
}
// 分离验证码和密码:前5位是验证码,后面是密码
if (decryptedContent.length() > CAPTCHA_LENGTH) {
String embeddedCaptcha = decryptedContent.substring(0, CAPTCHA_LENGTH);
String actualPassword = decryptedContent.substring(CAPTCHA_LENGTH);
// 验证嵌入的验证码是否正确
boolean embeddedCaptchaValid = captchaService.validate(captchaId, embeddedCaptcha, true);
if (!embeddedCaptchaValid) {
throw new RenException(ErrorCode.SMS_CAPTCHA_ERROR);
}
return actualPassword;
} else if (decryptedContent.length() > 0) {
throw new RenException(ErrorCode.SMS_CAPTCHA_ERROR);
} else {
throw new RenException(ErrorCode.SM2_DECRYPT_ERROR);
}
@@ -42,6 +42,9 @@ import xiaozhi.modules.agent.dto.AgentMemoryDTO;
import xiaozhi.modules.agent.dto.AgentUpdateDTO;
import xiaozhi.modules.agent.entity.AgentEntity;
import xiaozhi.modules.agent.entity.AgentTemplateEntity;
import xiaozhi.modules.agent.dto.AgentTagDTO;
import xiaozhi.modules.agent.entity.AgentTagEntity;
import xiaozhi.modules.agent.service.AgentTagService;
import xiaozhi.modules.agent.service.AgentChatAudioService;
import xiaozhi.modules.agent.service.AgentChatHistoryService;
import xiaozhi.modules.agent.service.AgentChatSummaryService;
@@ -49,6 +52,7 @@ import xiaozhi.modules.agent.service.AgentContextProviderService;
import xiaozhi.modules.agent.service.AgentPluginMappingService;
import xiaozhi.modules.agent.service.AgentService;
import xiaozhi.modules.agent.service.AgentTemplateService;
import xiaozhi.modules.correctword.service.CorrectWordFileService;
import xiaozhi.modules.agent.vo.AgentChatHistoryUserVO;
import xiaozhi.modules.agent.vo.AgentInfoVO;
import xiaozhi.modules.device.entity.DeviceEntity;
@@ -69,6 +73,8 @@ public class AgentController {
private final AgentContextProviderService agentContextProviderService;
private final AgentChatSummaryService agentChatSummaryService;
private final RedisUtils redisUtils;
private final AgentTagService agentTagService;
private final CorrectWordFileService correctWordFileService;
@GetMapping("/list")
@Operation(summary = "获取用户智能体列表")
@@ -77,7 +83,7 @@ public class AgentController {
@RequestParam(value = "keyword", required = false) String keyword,
@RequestParam(value = "searchType", defaultValue = "name") String searchType) {
UserDetail user = SecurityUser.getUser();
// 直接调用整合后的getUserAgents方法,无需再区分搜索和普通查询
List<AgentDTO> agents = agentService.getUserAgents(user.getId(), keyword, searchType);
return new Result<List<AgentDTO>>().ok(agents);
@@ -146,6 +152,13 @@ public class AgentController {
}
}
@PostMapping("/chat-title/{sessionId}/generate")
@Operation(summary = "根据会话ID生成聊天标题")
public Result<Void> generateAndSaveChatTitle(@PathVariable String sessionId) {
agentChatSummaryService.generateAndSaveChatTitle(sessionId);
return new Result<Void>().ok(null);
}
@PutMapping("/{id}")
@Operation(summary = "更新智能体")
@RequiresPermissions("sys:role:normal")
@@ -166,6 +179,8 @@ public class AgentController {
agentPluginMappingService.deleteByAgentId(id);
// 删除关联的上下文源配置
agentContextProviderService.deleteByAgentId(id);
// 删除关联的替换词文件关联记录
correctWordFileService.deleteMappingsByAgentId(id);
// 再删除智能体
agentService.deleteById(id);
return new Result<>();
@@ -275,6 +290,50 @@ public class AgentController {
.body(audioData);
}
@PostMapping("/tag")
@Operation(summary = "创建标签")
@RequiresPermissions("sys:role:normal")
public Result<AgentTagEntity> createTag(@RequestBody Map<String, String> params) {
String tagName = params.get("tagName");
if (StringUtils.isBlank(tagName)) {
return new Result<AgentTagEntity>().error("标签名称不能为空");
}
AgentTagEntity tag = agentTagService.saveTag(tagName);
return new Result<AgentTagEntity>().ok(tag);
}
@GetMapping("/tag/list")
@Operation(summary = "获取所有标签列表")
@RequiresPermissions("sys:role:normal")
public Result<List<AgentTagDTO>> getAllTags() {
List<AgentTagDTO> tags = agentTagService.getAllTags();
return new Result<List<AgentTagDTO>>().ok(tags);
}
@DeleteMapping("/tag/{id}")
@Operation(summary = "删除标签")
@RequiresPermissions("sys:role:normal")
public Result<Void> deleteTag(@PathVariable String id) {
agentTagService.deleteTag(id);
return new Result<Void>().ok(null);
}
@GetMapping("/{id}/tags")
@Operation(summary = "获取智能体的标签")
@RequiresPermissions("sys:role:normal")
public Result<List<AgentTagDTO>> getAgentTags(@PathVariable String id) {
List<AgentTagDTO> tags = agentTagService.getTagsByAgentId(id);
return new Result<List<AgentTagDTO>>().ok(tags);
}
@PutMapping("/{id}/tags")
@Operation(summary = "保存智能体的标签")
@RequiresPermissions("sys:role:normal")
public Result<Void> saveAgentTags(@PathVariable String id, @RequestBody Map<String, Object> params) {
List<String> tagIds = (List<String>) params.get("tagIds");
List<String> tagNames = (List<String>) params.get("tagNames");
agentTagService.saveAgentTags(id, tagIds, tagNames);
return new Result<Void>().ok(null);
}
}
@@ -11,6 +11,7 @@ import org.springframework.web.bind.annotation.RestController;
import io.swagger.v3.oas.annotations.Operation;
import io.swagger.v3.oas.annotations.tags.Tag;
import lombok.RequiredArgsConstructor;
import xiaozhi.common.exception.ErrorCode;
import xiaozhi.common.user.UserDetail;
import xiaozhi.common.utils.Result;
import xiaozhi.modules.agent.service.AgentMcpAccessPointService;
@@ -40,11 +41,11 @@ public class AgentMcpAccessPointController {
// 检查权限
if (!agentService.checkAgentPermission(agentId, user.getId())) {
return new Result<String>().error("没有权限查看该智能体的MCP接入点地址");
return new Result<String>().error(ErrorCode.MCP_ACCESS_POINT_ADDRESS_NO_PERMISSION);
}
String agentMcpAccessAddress = agentMcpAccessPointService.getAgentMcpAccessAddress(agentId);
if (agentMcpAccessAddress == null) {
return new Result<String>().ok("请联系管理员进入参数管理配置mcp接入点地址");
return new Result<String>().error(ErrorCode.MCP_ACCESS_POINT_ADDRESS_NOT_CONFIGURED);
}
return new Result<String>().ok(agentMcpAccessAddress);
}
@@ -58,7 +59,7 @@ public class AgentMcpAccessPointController {
// 检查权限
if (!agentService.checkAgentPermission(agentId, user.getId())) {
return new Result<List<String>>().error("没有权限查看该智能体的MCP工具列表");
return new Result<List<String>>().error(ErrorCode.MCP_ACCESS_POINT_TOOLS_LIST_NO_PERMISSION);
}
List<String> agentMcpToolsList = agentMcpAccessPointService.getAgentMcpToolsList(agentId);
return new Result<List<String>>().ok(agentMcpToolsList);
@@ -0,0 +1,12 @@
package xiaozhi.modules.agent.dao;
import org.apache.ibatis.annotations.Mapper;
import com.baomidou.mybatisplus.core.mapper.BaseMapper;
import xiaozhi.modules.agent.entity.AgentChatTitleEntity;
@Mapper
public interface AgentChatTitleDao extends BaseMapper<AgentChatTitleEntity> {
}
@@ -0,0 +1,21 @@
package xiaozhi.modules.agent.dao;
import java.util.List;
import org.apache.ibatis.annotations.Mapper;
import org.apache.ibatis.annotations.Param;
import xiaozhi.common.dao.BaseDao;
import xiaozhi.modules.agent.entity.AgentCorrectWordMappingEntity;
@Mapper
public interface AgentCorrectWordMappingDao extends BaseDao<AgentCorrectWordMappingEntity> {
int deleteByAgentId(@Param("agentId") String agentId);
int deleteByFileId(@Param("fileId") String fileId);
int batchInsertMapping(@Param("list") List<AgentCorrectWordMappingEntity> mappings);
List<AgentCorrectWordMappingEntity> selectByAgentId(@Param("agentId") String agentId);
}
@@ -0,0 +1,24 @@
package xiaozhi.modules.agent.dao;
import org.apache.ibatis.annotations.Mapper;
import org.apache.ibatis.annotations.Param;
import xiaozhi.common.dao.BaseDao;
import xiaozhi.modules.agent.entity.AgentTagEntity;
import java.util.List;
@Mapper
public interface AgentTagDao extends BaseDao<AgentTagEntity> {
List<AgentTagEntity> selectByAgentId(@Param("agentId") String agentId);
List<AgentTagEntity> selectByAgentIds(@Param("agentIds") List<String> agentIds);
List<AgentTagEntity> selectAll();
List<String> selectAgentIdsByTagName(@Param("tagName") String tagName);
List<AgentTagEntity> selectByTagNames(@Param("tagNames") List<String> tagNames);
int batchInsert(@Param("list") List<AgentTagEntity> tagList);
}
@@ -0,0 +1,18 @@
package xiaozhi.modules.agent.dao;
import org.apache.ibatis.annotations.Mapper;
import org.apache.ibatis.annotations.Param;
import xiaozhi.common.dao.BaseDao;
import xiaozhi.modules.agent.entity.AgentTagRelationEntity;
import java.util.List;
@Mapper
public interface AgentTagRelationDao extends BaseDao<AgentTagRelationEntity> {
int deleteByAgentId(@Param("agentId") String agentId);
int insertRelation(AgentTagRelationEntity relation);
int batchInsertRelation(@Param("list") List<AgentTagRelationEntity> relations);
}
@@ -23,4 +23,9 @@ public class AgentChatSessionDTO {
* 聊天条数
*/
private Integer chatCount;
/**
* 会话标题
*/
private String title;
}
@@ -5,6 +5,7 @@ import java.util.List;
import io.swagger.v3.oas.annotations.media.Schema;
import lombok.Data;
import xiaozhi.modules.agent.dto.AgentTagDTO;
/**
* 智能体数据传输对象
@@ -46,4 +47,7 @@ public class AgentDTO {
@Schema(description = "设备数量", example = "10")
private Integer deviceCount;
@Schema(description = "标签列表")
private List<AgentTagDTO> tags;
}
@@ -0,0 +1,20 @@
package xiaozhi.modules.agent.dto;
import io.swagger.v3.oas.annotations.media.Schema;
import lombok.Data;
import java.io.Serializable;
import java.util.List;
@Data
@Schema(description = "智能体标签DTO")
public class AgentTagDTO implements Serializable {
private static final long serialVersionUID = 1L;
@Schema(description = "标签ID")
private String id;
@Schema(description = "标签名称")
private String tagName;
}
@@ -1,6 +1,7 @@
package xiaozhi.modules.agent.dto;
import java.io.Serializable;
import java.math.BigDecimal;
import java.util.HashMap;
import java.util.List;
@@ -32,6 +33,9 @@ public class AgentUpdateDTO implements Serializable {
@Schema(description = "大语言模型标识", example = "llm_model_02", nullable = true)
private String llmModelId;
@Schema(description = "小模型标识", example = "slm_model_02", nullable = true)
private String slmModelId;
@Schema(description = "VLLM模型标识", example = "vllm_model_02", required = false)
private String vllmModelId;
@@ -41,6 +45,18 @@ public class AgentUpdateDTO implements Serializable {
@Schema(description = "音色标识", example = "voice_02", nullable = true)
private String ttsVoiceId;
@Schema(description = "音色语言", example = "普通话", nullable = true)
private String ttsLanguage;
@Schema(description = "TTS音量", example = "50", nullable = true)
private Integer ttsVolume;
@Schema(description = "TTS语速", example = "50", nullable = true)
private Integer ttsRate;
@Schema(description = "TTS音调", example = "50", nullable = true)
private Integer ttsPitch;
@Schema(description = "记忆模型标识", example = "mem_model_02", nullable = true)
private String memModelId;
@@ -72,6 +88,9 @@ public class AgentUpdateDTO implements Serializable {
@Schema(description = "上下文源配置", nullable = true)
private List<ContextProviderDTO> contextProviders;
@Schema(description = "替换词文件ID列表", nullable = true)
private List<String> correctWordFileIds;
@Data
@Schema(description = "插件函数信息")
public static class FunctionInfo implements Serializable {
@@ -0,0 +1,36 @@
package xiaozhi.modules.agent.entity;
import java.util.Date;
import com.baomidou.mybatisplus.annotation.IdType;
import com.baomidou.mybatisplus.annotation.TableField;
import com.baomidou.mybatisplus.annotation.TableId;
import com.baomidou.mybatisplus.annotation.TableName;
import lombok.AllArgsConstructor;
import lombok.Builder;
import lombok.Data;
import lombok.NoArgsConstructor;
@Data
@Builder
@AllArgsConstructor
@NoArgsConstructor
@TableName(value = "ai_agent_chat_title")
public class AgentChatTitleEntity {
@TableId(type = IdType.ASSIGN_UUID)
private String id;
@TableField(value = "session_id")
private String sessionId;
@TableField(value = "title")
private String title;
@TableField(value = "created_at")
private Date createdAt;
@TableField(value = "updated_at")
private Date updatedAt;
}
@@ -0,0 +1,38 @@
package xiaozhi.modules.agent.entity;
import java.util.Date;
import com.baomidou.mybatisplus.annotation.IdType;
import com.baomidou.mybatisplus.annotation.TableId;
import com.baomidou.mybatisplus.annotation.TableName;
import io.swagger.v3.oas.annotations.media.Schema;
import lombok.Data;
@Data
@TableName("ai_agent_correct_word_mapping")
@Schema(description = "智能体替换词文件关联")
public class AgentCorrectWordMappingEntity {
@TableId(type = IdType.ASSIGN_UUID)
@Schema(description = "主键")
private String id;
@Schema(description = "智能体ID")
private String agentId;
@Schema(description = "替换词文件ID")
private String fileId;
@Schema(description = "创建者")
private Long creator;
@Schema(description = "创建时间")
private Date createdAt;
@Schema(description = "更新者")
private Long updater;
@Schema(description = "更新时间")
private Date updatedAt;
}
@@ -1,5 +1,6 @@
package xiaozhi.modules.agent.entity;
import java.math.BigDecimal;
import java.util.Date;
import com.baomidou.mybatisplus.annotation.IdType;
@@ -36,6 +37,9 @@ public class AgentEntity {
@Schema(description = "大语言模型标识")
private String llmModelId;
@Schema(description = "小模型标识")
private String slmModelId;
@Schema(description = "VLLM模型标识")
private String vllmModelId;
@@ -45,6 +49,18 @@ public class AgentEntity {
@Schema(description = "音色标识")
private String ttsVoiceId;
@Schema(description = "音色语言")
private String ttsLanguage;
@Schema(description = "TTS音量")
private Integer ttsVolume;
@Schema(description = "TTS语速")
private Integer ttsRate;
@Schema(description = "TTS音调")
private Integer ttsPitch;
@Schema(description = "记忆模型标识")
private String memModelId;
@@ -0,0 +1,41 @@
package xiaozhi.modules.agent.entity;
import java.util.Date;
import com.baomidou.mybatisplus.annotation.IdType;
import com.baomidou.mybatisplus.annotation.TableId;
import com.baomidou.mybatisplus.annotation.TableName;
import io.swagger.v3.oas.annotations.media.Schema;
import lombok.Data;
@Data
@TableName("ai_agent_tag")
@Schema(description = "智能体标签")
public class AgentTagEntity {
@TableId(type = IdType.ASSIGN_UUID)
@Schema(description = "主键")
private String id;
@Schema(description = "标签名称")
private String tagName;
@Schema(description = "排序")
private Integer sort;
@Schema(description = "创建者")
private Long creator;
@Schema(description = "创建时间")
private Date createdAt;
@Schema(description = "更新者")
private Long updater;
@Schema(description = "更新时间")
private Date updatedAt;
@Schema(description = "删除标记")
private Integer deleted;
}
@@ -0,0 +1,41 @@
package xiaozhi.modules.agent.entity;
import java.util.Date;
import com.baomidou.mybatisplus.annotation.IdType;
import com.baomidou.mybatisplus.annotation.TableId;
import com.baomidou.mybatisplus.annotation.TableName;
import io.swagger.v3.oas.annotations.media.Schema;
import lombok.Data;
@Data
@TableName("ai_agent_tag_relation")
@Schema(description = "智能体标签关联")
public class AgentTagRelationEntity {
@TableId(type = IdType.ASSIGN_UUID)
@Schema(description = "主键")
private String id;
@Schema(description = "智能体ID")
private String agentId;
@Schema(description = "标签ID")
private String tagId;
@Schema(description = "排序")
private Integer sort;
@Schema(description = "创建者")
private Long creator;
@Schema(description = "创建时间")
private Date createdAt;
@Schema(description = "更新者")
private Long updater;
@Schema(description = "更新时间")
private Date updatedAt;
}
@@ -1,6 +1,7 @@
package xiaozhi.modules.agent.entity;
import java.io.Serializable;
import java.math.BigDecimal;
import java.util.Date;
import com.baomidou.mybatisplus.annotation.IdType;
@@ -64,6 +65,26 @@ public class AgentTemplateEntity implements Serializable {
*/
private String ttsVoiceId;
/**
* 音色语言
*/
private String ttsLanguage;
/**
* TTS音量
*/
private Integer ttsVolume;
/**
* TTS语速
*/
private Integer ttsRate;
/**
* TTS音调
*/
private Integer ttsPitch;
/**
* 记忆模型标识
*/
@@ -12,4 +12,12 @@ public interface AgentChatSummaryService {
* @return 保存结果
*/
boolean generateAndSaveChatSummary(String sessionId);
/**
* 根据会话ID生成聊天标题并保存
*
* @param sessionId 会话ID
* @return 是否成功
*/
boolean generateAndSaveChatTitle(String sessionId);
}
@@ -0,0 +1,10 @@
package xiaozhi.modules.agent.service;
import xiaozhi.modules.agent.entity.AgentChatTitleEntity;
public interface AgentChatTitleService {
void saveOrUpdateTitle(String sessionId, String title);
String getTitleBySessionId(String sessionId);
}
@@ -0,0 +1,25 @@
package xiaozhi.modules.agent.service;
import java.util.List;
import xiaozhi.modules.agent.dto.AgentTagDTO;
import xiaozhi.modules.agent.entity.AgentTagEntity;
public interface AgentTagService {
AgentTagEntity saveTag(String tagName);
void deleteTag(String tagId);
List<AgentTagDTO> getTagsByAgentId(String agentId);
void saveAgentTags(String agentId, List<String> tagIds, List<String> tagNames);
void deleteAgentTags(String agentId);
List<AgentTagDTO> getTagsByAgentIds(List<String> agentIds);
List<AgentTagDTO> getAllTags();
List<String> getAgentIdsByTagName(String tagName);
}
@@ -52,7 +52,7 @@ public class AgentChatHistoryBizServiceImpl implements AgentChatHistoryBizServic
public Boolean report(AgentChatHistoryReportDTO report) {
String macAddress = report.getMacAddress();
Byte chatType = report.getChatType();
Long reportTimeMillis = null != report.getReportTime() ? report.getReportTime() * 1000
Long reportTimeMillis = null != report.getReportTime() ? report.getReportTime()
: System.currentTimeMillis();
log.info("小智设备聊天上报请求: macAddress={}, type={} reportTime={}", macAddress, chatType, reportTimeMillis);
@@ -6,6 +6,7 @@ import java.util.Map;
import java.util.stream.Collectors;
import cn.hutool.core.collection.ListUtil;
import lombok.RequiredArgsConstructor;
import org.springframework.stereotype.Service;
import org.springframework.transaction.annotation.Transactional;
@@ -26,6 +27,7 @@ import xiaozhi.modules.agent.dto.AgentChatHistoryDTO;
import xiaozhi.modules.agent.dto.AgentChatSessionDTO;
import xiaozhi.modules.agent.entity.AgentChatHistoryEntity;
import xiaozhi.modules.agent.service.AgentChatHistoryService;
import xiaozhi.modules.agent.service.AgentChatTitleService;
import xiaozhi.modules.agent.vo.AgentChatHistoryUserVO;
/**
@@ -36,9 +38,12 @@ import xiaozhi.modules.agent.vo.AgentChatHistoryUserVO;
* @since 1.0.0
*/
@Service
@RequiredArgsConstructor
public class AgentChatHistoryServiceImpl extends ServiceImpl<AiAgentChatHistoryDao, AgentChatHistoryEntity>
implements AgentChatHistoryService {
private final AgentChatTitleService agentChatTitleService;
@Override
public PageData<AgentChatSessionDTO> getSessionListByAgentId(Map<String, Object> params) {
String agentId = (String) params.get("agentId");
@@ -61,6 +66,7 @@ public class AgentChatHistoryServiceImpl extends ServiceImpl<AiAgentChatHistoryD
dto.setSessionId((String) map.get("session_id"));
dto.setCreatedAt((LocalDateTime) map.get("created_at"));
dto.setChatCount(((Number) map.get("chat_count")).intValue());
dto.setTitle(agentChatTitleService.getTitleBySessionId(dto.getSessionId()));
return dto;
}).collect(Collectors.toList());
@@ -91,7 +97,7 @@ public class AgentChatHistoryServiceImpl extends ServiceImpl<AiAgentChatHistoryD
if (ToolUtil.isNotEmpty(audioIds)) {
// 每批删除1000条
List<List<String>> batch = ListUtil.split(audioIds, 1000);
batch.forEach(dataList->{
batch.forEach(dataList -> {
baseMapper.deleteAudioByIds(dataList);
});
}
@@ -14,6 +14,7 @@ import org.springframework.stereotype.Service;
import com.baomidou.mybatisplus.core.conditions.query.QueryWrapper;
import lombok.RequiredArgsConstructor;
import xiaozhi.common.constant.Constant;
import xiaozhi.modules.agent.dto.AgentChatHistoryDTO;
import xiaozhi.modules.agent.dto.AgentChatSummaryDTO;
import xiaozhi.modules.agent.dto.AgentMemoryDTO;
@@ -21,6 +22,7 @@ import xiaozhi.modules.agent.dto.AgentUpdateDTO;
import xiaozhi.modules.agent.entity.AgentChatHistoryEntity;
import xiaozhi.modules.agent.service.AgentChatHistoryService;
import xiaozhi.modules.agent.service.AgentChatSummaryService;
import xiaozhi.modules.agent.service.AgentChatTitleService;
import xiaozhi.modules.agent.service.AgentService;
import xiaozhi.modules.agent.vo.AgentInfoVO;
import xiaozhi.modules.device.entity.DeviceEntity;
@@ -41,6 +43,7 @@ public class AgentChatSummaryServiceImpl implements AgentChatSummaryService {
private final AgentChatHistoryService agentChatHistoryService;
private final AgentService agentService;
private final AgentChatTitleService agentChatTitleService;
private final DeviceService deviceService;
private final LLMService llmService;
private final ModelConfigService modelConfigService;
@@ -90,33 +93,40 @@ public class AgentChatSummaryServiceImpl implements AgentChatSummaryService {
@Override
public boolean generateAndSaveChatSummary(String sessionId) {
try {
// 1. 生成总结
AgentChatSummaryDTO summaryDTO = generateChatSummary(sessionId);
if (!summaryDTO.isSuccess()) {
log.info("生成总结失败: {}", summaryDTO.getErrorMessage());
return false;
}
// 2. 获取设备信息(通过会话关联的设备)
DeviceEntity device = getDeviceBySessionId(sessionId);
if (device == null) {
log.info("未找到与会话 {} 关联的设备", sessionId);
return false;
}
// 3. 更新智能体记忆
AgentMemoryDTO memoryDTO = new AgentMemoryDTO();
memoryDTO.setSummaryMemory(summaryDTO.getSummary());
String agentId = device.getAgentId();
String memModelId = agentService.getAgentById(agentId).getMemModelId();
// 调用现有接口更新记忆
agentService.updateAgentById(device.getAgentId(),
new AgentUpdateDTO() {
if (memModelId == null || memModelId.equals(Constant.MEMORY_MEM_REPORT_ONLY)) {
log.info("会话 {} 使用仅上报聊天记录模式,跳过记忆总结", sessionId);
return true;
}
boolean shouldSummarizeMemory = !memModelId.equals(Constant.MEMORY_NO_MEM)
&& !memModelId.equals(Constant.MEMORY_MEM0AI)
&& !memModelId.equals(Constant.MEMORY_POWERMEM);
if (shouldSummarizeMemory) {
AgentChatSummaryDTO summaryDTO = generateChatSummary(sessionId);
if (summaryDTO.isSuccess()) {
agentService.updateAgentById(agentId, new AgentUpdateDTO() {
{
setSummaryMemory(summaryDTO.getSummary());
}
});
log.info("成功保存会话 {} 的聊天记录总结到智能体 {}", sessionId, agentId);
} else {
log.info("生成总结失败: {}", summaryDTO.getErrorMessage());
}
} else {
log.info("会话 {} 使用 {} 模式,跳过记忆总结", sessionId, memModelId);
}
log.info("成功保存会话 {} 的聊天记录总结到智能体 {}", sessionId, device.getAgentId());
return true;
} catch (Exception e) {
@@ -125,6 +135,98 @@ public class AgentChatSummaryServiceImpl implements AgentChatSummaryService {
}
}
@Override
public boolean generateAndSaveChatTitle(String sessionId) {
try {
// 自动获取agentId
String agentId = findAgentIdBySessionId(sessionId);
if (StringUtils.isBlank(agentId)) {
log.warn("会话 {} 无法获取智能体信息,跳过标题生成", sessionId);
return false;
}
List<AgentChatHistoryDTO> chatHistory = getChatHistoryBySessionId(sessionId);
if (chatHistory == null || chatHistory.isEmpty()) {
return false;
}
List<String> meaningfulMessages = extractMeaningfulMessages(chatHistory);
if (meaningfulMessages.isEmpty()) {
return false;
}
StringBuilder conversation = new StringBuilder();
for (int i = 0; i < meaningfulMessages.size(); i++) {
conversation.append("消息").append(i + 1).append(": ").append(meaningfulMessages.get(i)).append("\n");
}
String slmModelId = getSlmModelId(agentId);
String title = llmService.generateTitle(conversation.toString(), slmModelId);
if (StringUtils.isNotBlank(title)) {
agentChatTitleService.saveOrUpdateTitle(sessionId, title);
log.info("成功保存会话 {} 的标题: {}", sessionId, title);
return true;
}
return false;
} catch (Exception e) {
log.error("生成会话 {} 的标题时发生错误: {}", sessionId, e.getMessage());
return false;
}
}
private String getSlmModelId(String agentId) {
try {
if (StringUtils.isBlank(agentId)) {
return null;
}
AgentInfoVO agentInfo = agentService.getAgentById(agentId);
if (agentInfo == null) {
return null;
}
String slmModelId = agentInfo.getSlmModelId();
if (StringUtils.isNotBlank(slmModelId)) {
log.info("会话 {} 使用SLM模型: {}", agentId, slmModelId);
return slmModelId;
}
ModelConfigEntity defaultLlmConfig = getDefaultLLMConfig();
if (defaultLlmConfig != null) {
log.info("会话 {} 使用默认LLM模型: {}", agentId, defaultLlmConfig.getId());
return defaultLlmConfig.getId();
}
String llmModelId = agentInfo.getLlmModelId();
log.info("会话 {} 使用LLM模型(最终回退): {}", agentId, llmModelId);
return llmModelId;
} catch (Exception e) {
log.error("获取智能体slm模型ID失败,agentId: {}, 错误: {}", agentId, e.getMessage());
return null;
}
}
private ModelConfigEntity getDefaultLLMConfig() {
try {
List<ModelConfigEntity> llmConfigs = modelConfigService.getEnabledModelsByType("LLM");
if (llmConfigs == null || llmConfigs.isEmpty()) {
return null;
}
for (ModelConfigEntity config : llmConfigs) {
if (config.getIsDefault() != null && config.getIsDefault() == 1) {
return config;
}
}
return llmConfigs.get(0);
} catch (Exception e) {
log.error("获取默认LLM配置失败: {}", e.getMessage());
return null;
}
}
/**
* 根据会话ID获取聊天记录
*/
@@ -305,15 +407,13 @@ public class AgentChatSummaryServiceImpl implements AgentChatSummaryService {
*/
private String callJavaLLMForSummaryWithHistory(String conversation, String historyMemory, String agentId) {
try {
// 获取智能体配置,从中提取记忆总结的模型ID
String modelId = getMemorySummaryModelId(agentId);
String modelId = getSlmModelId(agentId);
if (StringUtils.isBlank(modelId)) {
log.info("未找到记忆总结的LLM模型配置,使用默认LLM服务");
log.info("未找到SLM模型,使用默认LLM服务");
return llmService.generateSummaryWithHistory(conversation, historyMemory, null, null);
}
// 使用指定的模型ID调用LLM服务(支持历史记忆合并)
String summary = llmService.generateSummaryWithHistory(conversation, historyMemory, null, modelId);
if (StringUtils.isNotBlank(summary) && !summary.equals("服务暂不可用") && !summary.equals("总结生成失败")) {
@@ -333,15 +433,13 @@ public class AgentChatSummaryServiceImpl implements AgentChatSummaryService {
*/
private String callJavaLLMForSummary(String conversation, String agentId) {
try {
// 获取智能体配置,从中提取记忆总结的模型ID
String modelId = getMemorySummaryModelId(agentId);
String modelId = getSlmModelId(agentId);
if (StringUtils.isBlank(modelId)) {
log.info("未找到记忆总结的LLM模型配置,使用默认LLM服务");
log.info("未找到SLM模型,使用默认LLM服务");
return llmService.generateSummary(conversation);
}
// 使用指定的模型ID调用LLM服务
String summary = llmService.generateSummaryWithModel(conversation, modelId);
if (StringUtils.isNotBlank(summary) && !summary.equals("服务暂不可用") && !summary.equals("总结生成失败")) {
@@ -0,0 +1,60 @@
package xiaozhi.modules.agent.service.impl;
import java.util.Date;
import org.apache.commons.lang3.StringUtils;
import org.springframework.stereotype.Service;
import com.baomidou.mybatisplus.core.conditions.query.QueryWrapper;
import lombok.RequiredArgsConstructor;
import xiaozhi.modules.agent.dao.AgentChatTitleDao;
import xiaozhi.modules.agent.entity.AgentChatTitleEntity;
import xiaozhi.modules.agent.service.AgentChatTitleService;
@Service
@RequiredArgsConstructor
public class AgentChatTitleServiceImpl implements AgentChatTitleService {
private final AgentChatTitleDao agentChatTitleDao;
@Override
public void saveOrUpdateTitle(String sessionId, String title) {
if (StringUtils.isBlank(sessionId) || StringUtils.isBlank(title)) {
return;
}
QueryWrapper<AgentChatTitleEntity> wrapper = new QueryWrapper<>();
wrapper.eq("session_id", sessionId);
AgentChatTitleEntity existing = agentChatTitleDao.selectOne(wrapper);
if (existing != null) {
existing.setTitle(title);
existing.setUpdatedAt(new Date());
agentChatTitleDao.updateById(existing);
} else {
AgentChatTitleEntity newEntity = AgentChatTitleEntity.builder()
.id(java.util.UUID.randomUUID().toString().replace("-", ""))
.sessionId(sessionId)
.title(title)
.createdAt(new Date())
.updatedAt(new Date())
.build();
agentChatTitleDao.insert(newEntity);
}
}
@Override
public String getTitleBySessionId(String sessionId) {
if (StringUtils.isBlank(sessionId)) {
return null;
}
QueryWrapper<AgentChatTitleEntity> wrapper = new QueryWrapper<>();
wrapper.eq("session_id", sessionId);
AgentChatTitleEntity entity = agentChatTitleDao.selectOne(wrapper);
return entity != null ? entity.getTitle() : null;
}
}
@@ -31,19 +31,24 @@ import xiaozhi.common.utils.ConvertUtils;
import xiaozhi.common.utils.JsonUtils;
import xiaozhi.common.utils.ToolUtil;
import xiaozhi.modules.agent.dao.AgentDao;
import xiaozhi.modules.agent.dao.AgentTagDao;
import xiaozhi.modules.agent.dto.AgentCreateDTO;
import xiaozhi.modules.agent.dto.AgentDTO;
import xiaozhi.modules.agent.dto.AgentTagDTO;
import xiaozhi.modules.agent.dto.AgentUpdateDTO;
import xiaozhi.modules.agent.entity.AgentContextProviderEntity;
import xiaozhi.modules.agent.entity.AgentEntity;
import xiaozhi.modules.agent.entity.AgentPluginMapping;
import xiaozhi.modules.agent.entity.AgentTagEntity;
import xiaozhi.modules.agent.entity.AgentTemplateEntity;
import xiaozhi.modules.agent.service.AgentChatHistoryService;
import xiaozhi.modules.agent.service.AgentContextProviderService;
import xiaozhi.modules.agent.service.AgentPluginMappingService;
import xiaozhi.modules.agent.service.AgentService;
import xiaozhi.modules.agent.service.AgentTagService;
import xiaozhi.modules.agent.service.AgentTemplateService;
import xiaozhi.modules.agent.vo.AgentInfoVO;
import xiaozhi.modules.correctword.service.CorrectWordFileService;
import xiaozhi.modules.device.entity.DeviceEntity;
import xiaozhi.modules.device.service.DeviceService;
import xiaozhi.modules.model.dto.ModelProviderDTO;
@@ -59,6 +64,7 @@ import xiaozhi.modules.timbre.service.TimbreService;
@AllArgsConstructor
public class AgentServiceImpl extends BaseServiceImpl<AgentDao, AgentEntity> implements AgentService {
private final AgentDao agentDao;
private final AgentTagDao agentTagDao;
private final TimbreService timbreModelService;
private final ModelConfigService modelConfigService;
private final RedisUtils redisUtils;
@@ -68,6 +74,8 @@ public class AgentServiceImpl extends BaseServiceImpl<AgentDao, AgentEntity> imp
private final AgentTemplateService agentTemplateService;
private final ModelProviderService modelProviderService;
private final AgentContextProviderService agentContextProviderService;
private final AgentTagService agentTagService;
private final CorrectWordFileService correctWordFileService;
@Override
public PageData<AgentEntity> adminAgentList(Map<String, Object> params) {
@@ -98,6 +106,10 @@ public class AgentServiceImpl extends BaseServiceImpl<AgentDao, AgentEntity> imp
agent.setContextProviders(contextProviderEntity.getContextProviders());
}
// 查询替换词文件ID列表
List<String> correctWordFileIds = correctWordFileService.getAgentCorrectWordFileIds(id);
agent.setCorrectWordFileIds(correctWordFileIds);
// 无需额外查询插件列表,已通过SQL查询出来
return agent;
}
@@ -134,32 +146,32 @@ public class AgentServiceImpl extends BaseServiceImpl<AgentDao, AgentEntity> imp
QueryWrapper<AgentEntity> queryWrapper = new QueryWrapper<>();
queryWrapper.eq("user_id", userId).orderByDesc("created_at");
// 如果有搜索关键词,根据搜索类型添加相应的查询条件
if (StringUtils.isNotBlank(keyword)) {
if ("mac".equals(searchType)) {
// 按MAC地址搜索:先搜索设备,再获取对应的智能体
queryWrapper.and(w -> {
// 按名称搜索
w.like("agent_name", keyword);
// 按MAC地址搜索:先查设备,再获取对应的智能体ID
List<DeviceEntity> devices = Optional
.ofNullable(deviceService.searchDevicesByMacAddress(keyword, userId)).orElseGet(ArrayList::new);
// 获取设备对应的智能体ID列表
.ofNullable(deviceService.searchDevicesByMacAddress(keyword, userId))
.orElseGet(ArrayList::new);
List<String> agentIds = devices.stream()
.map(DeviceEntity::getAgentId)
.distinct()
.collect(Collectors.toList());
if (ToolUtil.isNotEmpty(agentIds)) {
queryWrapper.in("id", agentIds);
} else {
return new ArrayList<>();
w.or().in("id", agentIds);
}
} else {
// 按名搜索
queryWrapper.like("agent_name", keyword);
}
// 按标签名搜索
List<String> tagAgentIds = agentTagService.getAgentIdsByTagName(keyword);
if (ToolUtil.isNotEmpty(tagAgentIds)) {
w.or().in("id", tagAgentIds);
}
});
}
// 执行查询
List<AgentEntity> agentEntities = baseDao.selectList(queryWrapper);
// 转换为DTO并设置所有必要字段
return agentEntities.stream().map(this::buildAgentDTO).collect(Collectors.toList());
}
@@ -193,6 +205,19 @@ public class AgentServiceImpl extends BaseServiceImpl<AgentDao, AgentEntity> imp
// 获取设备数量
dto.setDeviceCount(getDeviceCountByAgentId(agent.getId()));
// 获取标签列表
List<AgentTagEntity> tags = agentTagDao.selectByAgentId(agent.getId());
if (ToolUtil.isNotEmpty(tags)) {
dto.setTags(tags.stream().map(this::convertTagToDTO).collect(Collectors.toList()));
}
return dto;
}
private AgentTagDTO convertTagToDTO(AgentTagEntity entity) {
AgentTagDTO dto = new AgentTagDTO();
dto.setId(entity.getId());
dto.setTagName(entity.getTagName());
return dto;
}
@@ -273,6 +298,9 @@ public class AgentServiceImpl extends BaseServiceImpl<AgentDao, AgentEntity> imp
if (dto.getLlmModelId() != null) {
existingEntity.setLlmModelId(dto.getLlmModelId());
}
if (dto.getSlmModelId() != null) {
existingEntity.setSlmModelId(dto.getSlmModelId());
}
if (dto.getVllmModelId() != null) {
existingEntity.setVllmModelId(dto.getVllmModelId());
}
@@ -282,6 +310,18 @@ public class AgentServiceImpl extends BaseServiceImpl<AgentDao, AgentEntity> imp
if (dto.getTtsVoiceId() != null) {
existingEntity.setTtsVoiceId(dto.getTtsVoiceId());
}
if (dto.getTtsLanguage() != null) {
existingEntity.setTtsLanguage(dto.getTtsLanguage());
}
if (dto.getTtsVolume() != null) {
existingEntity.setTtsVolume(dto.getTtsVolume());
}
if (dto.getTtsRate() != null) {
existingEntity.setTtsRate(dto.getTtsRate());
}
if (dto.getTtsPitch() != null) {
existingEntity.setTtsPitch(dto.getTtsPitch());
}
if (dto.getMemModelId() != null) {
existingEntity.setMemModelId(dto.getMemModelId());
}
@@ -367,13 +407,14 @@ public class AgentServiceImpl extends BaseServiceImpl<AgentDao, AgentEntity> imp
existingEntity.setUpdatedAt(new Date());
// 更新记忆策略
if (existingEntity.getMemModelId() == null || existingEntity.getMemModelId().equals(Constant.MEMORY_NO_MEM)) {
// 删除所有记录
// 删除所有记录
if (existingEntity.getMemModelId() != null && existingEntity.getMemModelId().equals(Constant.MEMORY_NO_MEM)) {
agentChatHistoryService.deleteByAgentId(existingEntity.getId(), true, true);
existingEntity.setSummaryMemory("");
} else if (existingEntity.getChatHistoryConf() != null && existingEntity.getChatHistoryConf() == 1) {
// 删除音频数据
agentChatHistoryService.deleteByAgentId(existingEntity.getId(), true, false);
// 删除记忆
} else if (existingEntity.getMemModelId() != null
&& existingEntity.getMemModelId().equals(Constant.MEMORY_MEM_REPORT_ONLY)) {
existingEntity.setSummaryMemory("");
}
// 更新上下文源配置
@@ -384,6 +425,11 @@ public class AgentServiceImpl extends BaseServiceImpl<AgentDao, AgentEntity> imp
agentContextProviderService.saveOrUpdateByAgentId(contextEntity);
}
// 更新替换词文件关联
if (dto.getCorrectWordFileIds() != null) {
correctWordFileService.saveAgentCorrectWords(agentId, dto.getCorrectWordFileIds());
}
boolean b = validateLLMIntentParams(dto.getLlmModelId(), dto.getIntentModelId());
if (!b) {
throw new RenException(ErrorCode.LLM_INTENT_PARAMS_MISMATCH);
@@ -466,6 +512,13 @@ public class AgentServiceImpl extends BaseServiceImpl<AgentDao, AgentEntity> imp
entity.setLanguage(template.getLanguage());
}
if (entity.getSlmModelId() == null) {
String defaultSlmModelId = getDefaultLLMModelId();
if (defaultSlmModelId != null) {
entity.setSlmModelId(defaultSlmModelId);
}
}
// 设置用户ID和创建者信息
UserDetail user = SecurityUser.getUser();
entity.setUserId(user.getId());
@@ -504,4 +557,23 @@ public class AgentServiceImpl extends BaseServiceImpl<AgentDao, AgentEntity> imp
return entity.getId();
}
private String getDefaultLLMModelId() {
try {
List<ModelConfigEntity> llmConfigs = modelConfigService.getEnabledModelsByType("LLM");
if (llmConfigs == null || llmConfigs.isEmpty()) {
return null;
}
for (ModelConfigEntity config : llmConfigs) {
if (config.getIsDefault() != null && config.getIsDefault() == 1) {
return config.getId();
}
}
return llmConfigs.get(0).getId();
} catch (Exception e) {
return null;
}
}
}
@@ -0,0 +1,198 @@
package xiaozhi.modules.agent.service.impl;
import java.util.ArrayList;
import java.util.Date;
import java.util.HashSet;
import java.util.List;
import java.util.Map;
import java.util.Set;
import java.util.UUID;
import java.util.stream.Collectors;
import org.springframework.stereotype.Service;
import org.springframework.transaction.annotation.Transactional;
import com.baomidou.mybatisplus.core.conditions.query.QueryWrapper;
import lombok.AllArgsConstructor;
import xiaozhi.common.exception.ErrorCode;
import xiaozhi.common.exception.RenException;
import xiaozhi.common.service.impl.BaseServiceImpl;
import xiaozhi.modules.agent.dao.AgentTagDao;
import xiaozhi.modules.agent.dao.AgentTagRelationDao;
import xiaozhi.modules.agent.dto.AgentTagDTO;
import xiaozhi.modules.agent.entity.AgentTagEntity;
import xiaozhi.modules.agent.entity.AgentTagRelationEntity;
import xiaozhi.modules.agent.service.AgentTagService;
@Service
@AllArgsConstructor
public class AgentTagServiceImpl extends BaseServiceImpl<AgentTagDao, AgentTagEntity> implements AgentTagService {
private final AgentTagRelationDao agentTagRelationDao;
@Override
public AgentTagEntity saveTag(String tagName) {
if (tagName == null || tagName.trim().isEmpty()) {
throw new RenException(ErrorCode.AGENT_TAG_NAME_EMPTY);
}
QueryWrapper<AgentTagEntity> wrapper = new QueryWrapper<>();
wrapper.eq("tag_name", tagName);
wrapper.eq("deleted", 0);
AgentTagEntity existTag = baseDao.selectOne(wrapper);
if (existTag != null) {
return existTag;
}
AgentTagEntity tag = new AgentTagEntity();
tag.setId(UUID.randomUUID().toString().replace("-", ""));
tag.setTagName(tagName);
tag.setSort(0);
tag.setCreatedAt(new Date());
tag.setUpdatedAt(new Date());
tag.setDeleted(0);
baseDao.insert(tag);
return tag;
}
@Override
public void deleteTag(String tagId) {
AgentTagEntity tag = baseDao.selectById(tagId);
if (tag != null) {
tag.setDeleted(1);
tag.setUpdatedAt(new Date());
baseDao.updateById(tag);
}
}
@Override
public List<AgentTagDTO> getTagsByAgentId(String agentId) {
List<AgentTagEntity> tags = baseDao.selectByAgentId(agentId);
return tags.stream().map(this::convertToDTO).collect(Collectors.toList());
}
@Override
@Transactional(rollbackFor = Exception.class)
public void saveAgentTags(String agentId, List<String> tagIds, List<String> tagNames) {
agentTagRelationDao.deleteByAgentId(agentId);
List<AgentTagEntity> currentTags = baseDao.selectByAgentId(agentId);
List<String> currentTagNames = currentTags.stream()
.map(AgentTagEntity::getTagName)
.collect(Collectors.toList());
List<String> allTagIds = new ArrayList<>();
List<String> newTagNames = new ArrayList<>();
if (tagNames != null && !tagNames.isEmpty()) {
Set<String> addedTagNames = new HashSet<>();
for (String tagName : tagNames) {
if (tagName == null || tagName.trim().isEmpty()) {
throw new RenException(ErrorCode.AGENT_TAG_NAME_EMPTY);
}
if (currentTagNames.contains(tagName) || addedTagNames.contains(tagName)) {
throw new RenException(ErrorCode.AGENT_TAG_NAME_DUPLICATE);
}
addedTagNames.add(tagName);
newTagNames.add(tagName);
}
}
List<AgentTagEntity> existTags = new ArrayList<>();
if (!newTagNames.isEmpty()) {
existTags = baseDao.selectByTagNames(newTagNames);
}
Map<String, AgentTagEntity> existTagMap = existTags.stream()
.collect(Collectors.toMap(AgentTagEntity::getTagName, t -> t, (a, b) -> a));
List<AgentTagEntity> tagsToInsert = new ArrayList<>();
for (String tagName : newTagNames) {
AgentTagEntity existTag = existTagMap.get(tagName);
if (existTag != null) {
allTagIds.add(existTag.getId());
} else {
AgentTagEntity tag = new AgentTagEntity();
tag.setId(UUID.randomUUID().toString().replace("-", ""));
tag.setTagName(tagName);
tag.setSort(0);
tag.setDeleted(0);
tag.setCreatedAt(new Date());
tag.setUpdatedAt(new Date());
tagsToInsert.add(tag);
}
}
if (!tagsToInsert.isEmpty()) {
baseDao.batchInsert(tagsToInsert);
for (AgentTagEntity tag : tagsToInsert) {
allTagIds.add(tag.getId());
}
}
if (tagIds != null && !tagIds.isEmpty()) {
List<AgentTagEntity> tagIdEntities = baseDao.selectBatchIds(tagIds);
for (AgentTagEntity tag : tagIdEntities) {
if (tag != null && (currentTagNames.contains(tag.getTagName()) ||
newTagNames.contains(tag.getTagName()))) {
throw new RenException(ErrorCode.AGENT_TAG_NAME_DUPLICATE);
}
}
allTagIds.addAll(tagIds);
}
if (allTagIds.isEmpty()) {
return;
}
List<AgentTagRelationEntity> relations = new ArrayList<>();
Date now = new Date();
int sort = 0;
for (String tagId : allTagIds) {
AgentTagRelationEntity relation = new AgentTagRelationEntity();
relation.setId(UUID.randomUUID().toString().replace("-", ""));
relation.setAgentId(agentId);
relation.setTagId(tagId);
relation.setSort(sort++);
relation.setCreatedAt(now);
relation.setUpdatedAt(now);
relations.add(relation);
}
agentTagRelationDao.batchInsertRelation(relations);
}
@Override
@Transactional(rollbackFor = Exception.class)
public void deleteAgentTags(String agentId) {
agentTagRelationDao.deleteByAgentId(agentId);
}
@Override
public List<AgentTagDTO> getTagsByAgentIds(List<String> agentIds) {
if (agentIds == null || agentIds.isEmpty()) {
return List.of();
}
List<AgentTagEntity> tags = baseDao.selectByAgentIds(agentIds);
return tags.stream().map(this::convertToDTO).collect(Collectors.toList());
}
@Override
public List<AgentTagDTO> getAllTags() {
List<AgentTagEntity> tags = baseDao.selectAll();
return tags.stream().map(this::convertToDTO).collect(Collectors.toList());
}
@Override
public List<String> getAgentIdsByTagName(String tagName) {
return baseDao.selectAgentIdsByTagName(tagName);
}
private AgentTagDTO convertToDTO(AgentTagEntity entity) {
AgentTagDTO dto = new AgentTagDTO();
dto.setId(entity.getId());
dto.setTagName(entity.getTagName());
return dto;
}
}
@@ -25,4 +25,7 @@ public class AgentInfoVO extends AgentEntity
@Schema(description = "上下文源配置")
private List<ContextProviderDTO> contextProviders;
@Schema(description = "替换词文件ID列表")
private List<String> correctWordFileIds;
}
@@ -1,5 +1,7 @@
package xiaozhi.modules.config.controller;
import java.util.List;
import org.springframework.web.bind.annotation.PostMapping;
import org.springframework.web.bind.annotation.RequestBody;
import org.springframework.web.bind.annotation.RequestMapping;
@@ -12,6 +14,7 @@ import lombok.AllArgsConstructor;
import xiaozhi.common.utils.Result;
import xiaozhi.common.validator.ValidatorUtils;
import xiaozhi.modules.config.dto.AgentModelsDTO;
import xiaozhi.modules.config.dto.CorrectWordsDTO;
import xiaozhi.modules.config.service.ConfigService;
/**
@@ -41,4 +44,12 @@ public class ConfigController {
Object models = configService.getAgentModels(dto.getMacAddress(), dto.getSelectedModule());
return new Result<Object>().ok(models);
}
@PostMapping("correct-words")
@Operation(summary = "获取智能体替换词")
public Result<Object> getCorrectWords(@Valid @RequestBody CorrectWordsDTO dto) {
ValidatorUtils.validateEntity(dto);
List<String> list = configService.getCorrectWords(dto.getMacAddress());
return new Result<Object>().ok(list);
}
}
@@ -0,0 +1,14 @@
package xiaozhi.modules.config.dto;
import io.swagger.v3.oas.annotations.media.Schema;
import jakarta.validation.constraints.NotBlank;
import lombok.Data;
@Data
@Schema(description = "获取智能体替换词DTO")
public class CorrectWordsDTO {
@NotBlank(message = "设备MAC地址不能为空")
@Schema(description = "设备MAC地址")
private String macAddress;
}
@@ -1,11 +1,12 @@
package xiaozhi.modules.config.service;
import java.util.List;
import java.util.Map;
public interface ConfigService {
/**
* 获取服务器配置
*
*
* @param isCache 是否缓存
* @return 配置信息
*/
@@ -13,10 +14,18 @@ public interface ConfigService {
/**
* 获取智能体模型配置
*
*
* @param macAddress MAC地址
* @param selectedModule 客户端已实例化的模型
* @return 模型配置信息
*/
Map<String, Object> getAgentModels(String macAddress, Map<String, String> selectedModule);
/**
* 获取智能体替换词
*
* @param macAddress 设备MAC地址
* @return 替换词列表,格式如 ["模板1|模板01", "模板2|模板02"]
*/
List<String> getCorrectWords(String macAddress);
}
@@ -1,10 +1,12 @@
package xiaozhi.modules.config.service.impl;
import java.util.ArrayList;
import java.util.Collections;
import java.util.HashMap;
import java.util.List;
import java.util.Map;
import java.util.Objects;
import java.util.stream.Collectors;
import org.apache.commons.lang3.StringUtils;
import org.springframework.stereotype.Service;
@@ -30,7 +32,9 @@ import xiaozhi.modules.agent.service.AgentMcpAccessPointService;
import xiaozhi.modules.agent.service.AgentPluginMappingService;
import xiaozhi.modules.agent.service.AgentService;
import xiaozhi.modules.agent.service.AgentTemplateService;
import xiaozhi.modules.correctword.service.CorrectWordFileService;
import xiaozhi.modules.agent.vo.AgentVoicePrintVO;
import xiaozhi.modules.correctword.vo.CorrectWordSimpleVO;
import xiaozhi.modules.config.service.ConfigService;
import xiaozhi.modules.device.entity.DeviceEntity;
import xiaozhi.modules.device.service.DeviceService;
@@ -58,6 +62,7 @@ public class ConfigServiceImpl implements ConfigService {
private final AgentContextProviderService agentContextProviderService;
private final VoiceCloneService cloneVoiceService;
private final AgentVoicePrintDao agentVoicePrintDao;
private final CorrectWordFileService correctWordFileService;
@Override
public Object getConfig(Boolean isCache) {
@@ -87,6 +92,10 @@ public class ConfigServiceImpl implements ConfigService {
null,
null,
null,
null,
null,
null,
null,
agent.getVadModelId(),
agent.getAsrModelId(),
null,
@@ -95,6 +104,7 @@ public class ConfigServiceImpl implements ConfigService {
null,
null,
null,
null,
result,
isCache);
@@ -109,7 +119,7 @@ public class ConfigServiceImpl implements ConfigService {
// 检查是否为管理控制台请求
String redisKey = RedisKeys.getTmpRegisterMacKey(macAddress);
Object isAdminRequest = redisUtils.get(redisKey);
if (isAdminRequest != null && "true".equals(isAdminRequest)) {
// 管理控制台请求,返回getConfig的结果
redisUtils.delete(redisKey); // 使用后清理
@@ -135,15 +145,24 @@ public class ConfigServiceImpl implements ConfigService {
String voice = null;
String referenceAudio = null;
String referenceText = null;
String language = null;
TimbreDetailsVO timbre = timbreService.get(agent.getTtsVoiceId());
if (timbre != null) {
voice = timbre.getTtsVoice();
referenceAudio = timbre.getReferenceAudio();
referenceText = timbre.getReferenceText();
// 优先使用用户选择的语言,如果没有则使用音色支持的第一个语言
if (StringUtils.isNotBlank(agent.getTtsLanguage())) {
language = agent.getTtsLanguage();
} else if (StringUtils.isNotBlank(timbre.getLanguages())) {
language = timbre.getLanguages().split("")[0].trim();
}
} else {
VoiceCloneEntity voice_print = cloneVoiceService.selectById(agent.getTtsVoiceId());
if (voice_print != null) {
voice = voice_print.getVoiceId();
// 优先使用用户选择的语言,如果没有则使用默认值
language = StringUtils.isNotBlank(agent.getTtsLanguage()) ? agent.getTtsLanguage() : "普通话";
}
}
// 构建返回数据
@@ -190,10 +209,11 @@ public class ConfigServiceImpl implements ConfigService {
mcpEndpoint = mcpEndpoint.replace("/mcp/", "/call/");
result.put("mcp_endpoint", mcpEndpoint);
}
// 获取上下文源配置
AgentContextProviderEntity contextProviderEntity = agentContextProviderService.getByAgentId(agent.getId());
if (contextProviderEntity != null && contextProviderEntity.getContextProviders() != null && !contextProviderEntity.getContextProviders().isEmpty()) {
if (contextProviderEntity != null && contextProviderEntity.getContextProviders() != null
&& !contextProviderEntity.getContextProviders().isEmpty()) {
result.put("context_providers", contextProviderEntity.getContextProviders());
}
@@ -208,10 +228,15 @@ public class ConfigServiceImpl implements ConfigService {
voice,
referenceAudio,
referenceText,
language,
agent.getTtsVolume(),
agent.getTtsRate(),
agent.getTtsPitch(),
agent.getVadModelId(),
agent.getAsrModelId(),
agent.getLlmModelId(),
agent.getVllmModelId(),
agent.getSlmModelId(),
agent.getTtsModelId(),
agent.getMemModelId(),
agent.getIntentModelId(),
@@ -222,6 +247,18 @@ public class ConfigServiceImpl implements ConfigService {
return result;
}
@Override
public List<String> getCorrectWords(String macAddress) {
DeviceEntity device = deviceService.getDeviceByMacAddress(macAddress);
if (device == null) {
return Collections.emptyList();
}
List<CorrectWordSimpleVO> items = correctWordFileService.getAllItemsByAgentId(device.getAgentId());
return items.stream()
.map(item -> item.getSourceWord() + "|" + item.getTargetWord())
.collect(Collectors.toList());
}
/**
* 构建配置信息
*
@@ -385,10 +422,15 @@ public class ConfigServiceImpl implements ConfigService {
String voice,
String referenceAudio,
String referenceText,
String language,
Integer ttsVolume,
Integer ttsRate,
Integer ttsPitch,
String vadModelId,
String asrModelId,
String llmModelId,
String vllmModelId,
String slmModelId,
String ttsModelId,
String memModelId,
String intentModelId,
@@ -397,9 +439,9 @@ public class ConfigServiceImpl implements ConfigService {
boolean isCache) {
Map<String, String> selectedModule = new HashMap<>();
String[] modelTypes = { "VAD", "ASR", "TTS", "Memory", "Intent", "LLM", "VLLM", "RAG" };
String[] modelTypes = { "VAD", "ASR", "TTS", "Memory", "Intent", "LLM", "VLLM", "SLM", "RAG" };
String[] modelIds = { vadModelId, asrModelId, ttsModelId, memModelId, intentModelId, llmModelId, vllmModelId,
ragModelId };
slmModelId, ragModelId };
String intentLLMModelId = null;
String memLocalShortLLMModelId = null;
@@ -423,11 +465,19 @@ public class ConfigServiceImpl implements ConfigService {
((Map<String, Object>) model.getConfigJson()).put("ref_audio", referenceAudio);
if (referenceText != null)
((Map<String, Object>) model.getConfigJson()).put("ref_text", referenceText);
if (language != null)
((Map<String, Object>) model.getConfigJson()).put("language", language);
if (ttsVolume != null)
((Map<String, Object>) model.getConfigJson()).put("ttsVolume", ttsVolume);
if (ttsRate != null)
((Map<String, Object>) model.getConfigJson()).put("ttsRate", ttsRate);
if (ttsPitch != null)
((Map<String, Object>) model.getConfigJson()).put("ttsPitch", ttsPitch);
// 火山引擎声音克隆需要替换resource_id
Map<String, Object> map = (Map<String, Object>) model.getConfigJson();
if (Constant.VOICE_CLONE_HUOSHAN_DOUBLE_STREAM.equals(map.get("type"))) {
// 如果voice是”S_开头的,使用seed-icl-1.0
// 如果voice是”S_开头的,使用seed-icl-1.0
if (voice != null && voice.startsWith("S_")) {
map.put("resource_id", "seed-icl-1.0");
}
@@ -445,7 +495,7 @@ public class ConfigServiceImpl implements ConfigService {
if (map.get("functions") != null) {
String functionStr = (String) map.get("functions");
if (StringUtils.isNotBlank(functionStr)) {
String[] functions = functionStr.split("\\;");
String[] functions = functionStr.split(";");
map.put("functions", functions);
}
}
@@ -478,6 +528,15 @@ public class ConfigServiceImpl implements ConfigService {
typeConfig.put(memLocalShortLLM.getId(), memLocalShortLLM.getConfigJson());
}
}
// LLM也返回所选的SLM,如果同名id则不重复显示
if (StringUtils.isNotBlank(slmModelId) && !slmModelId.equals(llmModelId)) {
if (!typeConfig.containsKey(slmModelId)) {
ModelConfigEntity slmModel = modelConfigService.getModelByIdFromCache(slmModelId);
if (slmModel != null && slmModel.getConfigJson() != null) {
typeConfig.put(slmModel.getId(), slmModel.getConfigJson());
}
}
}
}
}
result.put(modelTypes[i], typeConfig);
@@ -0,0 +1,116 @@
package xiaozhi.modules.correctword.controller;
import java.net.URLEncoder;
import java.nio.charset.StandardCharsets;
import java.util.List;
import java.util.Map;
import org.apache.shiro.authz.annotation.RequiresPermissions;
import org.springframework.http.HttpHeaders;
import org.springframework.http.MediaType;
import org.springframework.http.ResponseEntity;
import org.springframework.web.bind.annotation.DeleteMapping;
import org.springframework.web.bind.annotation.GetMapping;
import org.springframework.web.bind.annotation.PathVariable;
import org.springframework.web.bind.annotation.PostMapping;
import org.springframework.web.bind.annotation.PutMapping;
import org.springframework.web.bind.annotation.RequestBody;
import org.springframework.web.bind.annotation.RequestMapping;
import org.springframework.web.bind.annotation.RequestParam;
import org.springframework.web.bind.annotation.RestController;
import io.swagger.v3.oas.annotations.Operation;
import io.swagger.v3.oas.annotations.Parameter;
import io.swagger.v3.oas.annotations.Parameters;
import io.swagger.v3.oas.annotations.tags.Tag;
import jakarta.validation.Valid;
import lombok.AllArgsConstructor;
import xiaozhi.common.constant.Constant;
import xiaozhi.common.page.PageData;
import xiaozhi.common.utils.Result;
import xiaozhi.modules.correctword.dto.CorrectWordFileCreateDTO;
import xiaozhi.modules.correctword.service.CorrectWordFileService;
import xiaozhi.modules.correctword.vo.CorrectWordFileVO;
@RestController
@RequestMapping("/correct-word")
@Tag(name = "替换词管理")
@AllArgsConstructor
public class CorrectWordController {
private final CorrectWordFileService correctWordFileService;
@PostMapping("/file")
@Operation(summary = "创建替换词文件")
@RequiresPermissions("sys:role:normal")
public Result<CorrectWordFileVO> createFile(@Valid @RequestBody CorrectWordFileCreateDTO dto) {
CorrectWordFileVO vo = correctWordFileService.createFile(dto);
return new Result<CorrectWordFileVO>().ok(vo);
}
@PutMapping("/file/{fileId}")
@Operation(summary = "修改替换词文件")
@RequiresPermissions("sys:role:normal")
public Result<Void> updateFile(@PathVariable String fileId, @Valid @RequestBody CorrectWordFileCreateDTO dto) {
correctWordFileService.updateFile(fileId, dto);
return new Result<>();
}
@GetMapping("/file/list")
@Operation(summary = "分页获取当前用户替换词文件列表")
@RequiresPermissions("sys:role:normal")
@Parameters({
@Parameter(name = Constant.PAGE, description = "当前页码,从1开始", required = true),
@Parameter(name = Constant.LIMIT, description = "每页显示记录数", required = true),
})
public Result<PageData<CorrectWordFileVO>> listFiles(
@Parameter(hidden = true) @RequestParam Map<String, Object> params) {
PageData<CorrectWordFileVO> page = correctWordFileService.listFiles(params);
return new Result<PageData<CorrectWordFileVO>>().ok(page);
}
@GetMapping("/file/select")
@Operation(summary = "智能体获取当前用户替换词文件列表")
@RequiresPermissions("sys:role:normal")
public Result<List<CorrectWordFileVO>> listAllFiles() {
List<CorrectWordFileVO> list = correctWordFileService.listAllFiles();
return new Result<List<CorrectWordFileVO>>().ok(list);
}
@GetMapping("/file/download/{fileId}")
@Operation(summary = "下载替换词文件")
@RequiresPermissions("sys:role:normal")
public ResponseEntity<byte[]> downloadFile(@PathVariable String fileId) {
CorrectWordFileVO vo = correctWordFileService.getFileContent(fileId);
if (vo == null || vo.getContent() == null || vo.getContent().isEmpty()) {
return ResponseEntity.notFound().build();
}
byte[] bytes = String.join("\n", vo.getContent()).getBytes(StandardCharsets.UTF_8);
String encodedFileName = URLEncoder.encode(vo.getFileName(), StandardCharsets.UTF_8).replace("+", "%20");
String asciiFileName = vo.getFileName().replaceAll("[^\\x00-\\x7F]", "_");
return ResponseEntity.ok()
.header(HttpHeaders.CONTENT_DISPOSITION,
"attachment; filename=\"" + asciiFileName + "\"; filename*=UTF-8''" + encodedFileName)
.contentType(MediaType.APPLICATION_OCTET_STREAM)
.body(bytes);
}
@DeleteMapping("/file/{fileId}")
@Operation(summary = "删除替换词文件")
@RequiresPermissions("sys:role:normal")
public Result<Void> deleteFile(@PathVariable String fileId) {
correctWordFileService.deleteFile(fileId);
return new Result<>();
}
@PostMapping("/file/batch-delete")
@Operation(summary = "批量删除替换词文件")
@RequiresPermissions("sys:role:normal")
public Result<Void> batchDeleteFiles(@RequestBody List<String> fileIds) {
if (fileIds == null || fileIds.isEmpty()) {
return new Result<>();
}
correctWordFileService.batchDeleteFiles(fileIds);
return new Result<>();
}
}
@@ -0,0 +1,10 @@
package xiaozhi.modules.correctword.dao;
import org.apache.ibatis.annotations.Mapper;
import xiaozhi.common.dao.BaseDao;
import xiaozhi.modules.correctword.entity.CorrectWordFileEntity;
@Mapper
public interface CorrectWordFileDao extends BaseDao<CorrectWordFileEntity> {
}
@@ -0,0 +1,15 @@
package xiaozhi.modules.correctword.dao;
import java.util.List;
import org.apache.ibatis.annotations.Mapper;
import org.apache.ibatis.annotations.Param;
import xiaozhi.common.dao.BaseDao;
import xiaozhi.modules.correctword.entity.CorrectWordItemEntity;
@Mapper
public interface CorrectWordItemDao extends BaseDao<CorrectWordItemEntity> {
int batchInsert(@Param("list") List<CorrectWordItemEntity> items);
}
@@ -0,0 +1,24 @@
package xiaozhi.modules.correctword.dto;
import java.util.List;
import io.swagger.v3.oas.annotations.media.Schema;
import jakarta.validation.constraints.NotBlank;
import jakarta.validation.constraints.NotEmpty;
import lombok.Data;
@Data
@Schema(description = "创建替换词文件DTO")
public class CorrectWordFileCreateDTO {
@NotBlank(message = "文件名不能为空")
@Schema(description = "文件名")
private String fileName;
@NotEmpty(message = "替换词内容不能为空")
@Schema(description = "替换词内容,每条格式:原词|替换词")
private List<String> content;
@Schema(description = "文件大小(字节),不能超过1MB")
private Long fileSize;
}
@@ -0,0 +1,41 @@
package xiaozhi.modules.correctword.entity;
import java.util.Date;
import com.baomidou.mybatisplus.annotation.IdType;
import com.baomidou.mybatisplus.annotation.TableId;
import com.baomidou.mybatisplus.annotation.TableName;
import io.swagger.v3.oas.annotations.media.Schema;
import lombok.Data;
@Data
@TableName("ai_agent_correct_word_file")
@Schema(description = "智能体替换词文件")
public class CorrectWordFileEntity {
@TableId(type = IdType.ASSIGN_UUID)
@Schema(description = "替换词文件ID")
private String id;
@Schema(description = "原始文件名")
private String fileName;
@Schema(description = "替换词数量")
private Integer wordCount;
@Schema(description = "文件原始内容(用于下载)")
private String content;
@Schema(description = "创建者")
private Long creator;
@Schema(description = "创建时间")
private Date createdAt;
@Schema(description = "更新者")
private Long updater;
@Schema(description = "更新时间")
private Date updatedAt;
}
@@ -0,0 +1,27 @@
package xiaozhi.modules.correctword.entity;
import com.baomidou.mybatisplus.annotation.IdType;
import com.baomidou.mybatisplus.annotation.TableId;
import com.baomidou.mybatisplus.annotation.TableName;
import io.swagger.v3.oas.annotations.media.Schema;
import lombok.Data;
@Data
@TableName("ai_agent_correct_word_item")
@Schema(description = "替换词词条")
public class CorrectWordItemEntity {
@TableId(type = IdType.ASSIGN_UUID)
@Schema(description = "词条ID")
private String id;
@Schema(description = "所属文件ID")
private String fileId;
@Schema(description = "原词")
private String sourceWord;
@Schema(description = "替换词")
private String targetWord;
}
@@ -0,0 +1,96 @@
package xiaozhi.modules.correctword.service;
import java.util.List;
import java.util.Map;
import xiaozhi.common.page.PageData;
import xiaozhi.modules.correctword.dto.CorrectWordFileCreateDTO;
import xiaozhi.modules.correctword.vo.CorrectWordFileVO;
import xiaozhi.modules.correctword.vo.CorrectWordSimpleVO;
public interface CorrectWordFileService {
/**
* 创建替换词文件
*
* @param dto 创建参数
* @return 文件VO
*/
CorrectWordFileVO createFile(CorrectWordFileCreateDTO dto);
/**
* 修改替换词文件(全量替换词条)
*
* @param fileId 文件ID
* @param dto 修改参数
*/
void updateFile(String fileId, CorrectWordFileCreateDTO dto);
/**
* 获取当前用户的替换词文件列表
*
* @param params 分页参数
* @return 分页数据
*/
PageData<CorrectWordFileVO> listFiles(Map<String, Object> params);
/**
* 获取当前用户的替换词文件列表(不分页,用于下拉选择)
*
* @return 文件列表
*/
List<CorrectWordFileVO> listAllFiles();
/**
* 获取文件原始内容(用于下载)
*
* @param fileId 文件ID
* @return 文件实体
*/
CorrectWordFileVO getFileContent(String fileId);
/**
* 删除替换词文件及其所有词条和关联记录
*
* @param fileId 文件ID
*/
void deleteFile(String fileId);
/**
* 删除智能体关联的替换词文件关联记录(不删文件本身)
*
* @param agentId 智能体ID
*/
void deleteMappingsByAgentId(String agentId);
/**
* 获取智能体的所有替换词条(精简版,供设备端使用)
*
* @param agentId 智能体ID
* @return 替换词列表
*/
List<CorrectWordSimpleVO> getAllItemsByAgentId(String agentId);
/**
* 获取智能体关联的替换词文件ID列表
*
* @param agentId 智能体ID
* @return 文件ID列表
*/
List<String> getAgentCorrectWordFileIds(String agentId);
/**
* 保存智能体关联的替换词文件(全量替换)
*
* @param agentId 智能体ID
* @param fileIds 文件ID列表
*/
void saveAgentCorrectWords(String agentId, List<String> fileIds);
/**
* 批量删除替换词文件
*
* @param fileIds 文件ID列表
*/
void batchDeleteFiles(List<String> fileIds);
}
@@ -0,0 +1,296 @@
package xiaozhi.modules.correctword.service.impl;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.Date;
import java.util.List;
import java.util.Map;
import java.util.stream.Collectors;
import org.springframework.stereotype.Service;
import org.springframework.transaction.annotation.Transactional;
import com.baomidou.mybatisplus.core.conditions.query.LambdaQueryWrapper;
import com.baomidou.mybatisplus.core.metadata.IPage;
import lombok.AllArgsConstructor;
import xiaozhi.common.exception.ErrorCode;
import xiaozhi.common.exception.RenException;
import xiaozhi.common.page.PageData;
import xiaozhi.common.service.impl.BaseServiceImpl;
import xiaozhi.common.utils.ConvertUtils;
import xiaozhi.modules.agent.dao.AgentCorrectWordMappingDao;
import xiaozhi.modules.correctword.dao.CorrectWordFileDao;
import xiaozhi.modules.correctword.dao.CorrectWordItemDao;
import xiaozhi.modules.correctword.dto.CorrectWordFileCreateDTO;
import xiaozhi.modules.agent.entity.AgentCorrectWordMappingEntity;
import xiaozhi.modules.correctword.entity.CorrectWordFileEntity;
import xiaozhi.modules.correctword.entity.CorrectWordItemEntity;
import xiaozhi.modules.correctword.service.CorrectWordFileService;
import xiaozhi.modules.correctword.vo.CorrectWordFileVO;
import xiaozhi.modules.correctword.vo.CorrectWordSimpleVO;
import xiaozhi.modules.security.user.SecurityUser;
@Service
@AllArgsConstructor
public class CorrectWordFileServiceImpl extends BaseServiceImpl<CorrectWordFileDao, CorrectWordFileEntity>
implements CorrectWordFileService {
private final CorrectWordFileDao correctWordFileDao;
private final CorrectWordItemDao correctWordItemDao;
private final AgentCorrectWordMappingDao agentCorrectWordMappingDao;
@Override
@Transactional(rollbackFor = Exception.class)
public CorrectWordFileVO createFile(CorrectWordFileCreateDTO dto) {
// 校验文件大小不能超过1MB
if (dto.getFileSize() != null && dto.getFileSize() > 1024 * 1024) {
throw new RenException(ErrorCode.FILE_SIZE_OVER_LIMIT);
}
// 校验文件名是否重复
Long userId = SecurityUser.getUserId();
LambdaQueryWrapper<CorrectWordFileEntity> nameWrapper = new LambdaQueryWrapper<>();
nameWrapper.eq(CorrectWordFileEntity::getCreator, userId)
.eq(CorrectWordFileEntity::getFileName, dto.getFileName());
if (correctWordFileDao.selectCount(nameWrapper) > 0) {
throw new RenException(ErrorCode.CORRECT_WORD_FILE_NAME_EXISTS);
}
List<CorrectWordItemEntity> items = parseContent(dto.getContent());
// 保存文件记录
CorrectWordFileEntity fileEntity = new CorrectWordFileEntity();
fileEntity.setFileName(dto.getFileName());
fileEntity.setWordCount(items.size());
fileEntity.setContent(String.join("\n", dto.getContent()));
fileEntity.setCreator(SecurityUser.getUserId());
fileEntity.setCreatedAt(new Date());
correctWordFileDao.insert(fileEntity);
// 设置fileId并批量保存词条
String fileId = fileEntity.getId();
for (CorrectWordItemEntity item : items) {
item.setFileId(fileId);
}
if (!items.isEmpty()) {
correctWordItemDao.batchInsert(items);
}
return toVO(fileEntity);
}
@Override
@Transactional(rollbackFor = Exception.class)
public void updateFile(String fileId, CorrectWordFileCreateDTO dto) {
CorrectWordFileEntity fileEntity = correctWordFileDao.selectById(fileId);
if (fileEntity == null) {
return;
}
// 校验文件名是否重复(排除自身)
Long userId = SecurityUser.getUserId();
LambdaQueryWrapper<CorrectWordFileEntity> nameWrapper = new LambdaQueryWrapper<>();
nameWrapper.eq(CorrectWordFileEntity::getCreator, userId)
.eq(CorrectWordFileEntity::getFileName, dto.getFileName())
.ne(CorrectWordFileEntity::getId, fileId);
if (correctWordFileDao.selectCount(nameWrapper) > 0) {
throw new RenException("文件名已存在:" + dto.getFileName());
}
// 先删除旧词条
LambdaQueryWrapper<CorrectWordItemEntity> deleteWrapper = new LambdaQueryWrapper<>();
deleteWrapper.eq(CorrectWordItemEntity::getFileId, fileId);
correctWordItemDao.delete(deleteWrapper);
// 解析新词条并批量保存
List<CorrectWordItemEntity> items = parseContent(dto.getContent());
if (!items.isEmpty()) {
for (CorrectWordItemEntity item : items) {
item.setFileId(fileId);
}
correctWordItemDao.batchInsert(items);
}
// 更新文件记录
fileEntity.setFileName(dto.getFileName());
fileEntity.setWordCount(items.size());
fileEntity.setContent(String.join("\n", dto.getContent()));
fileEntity.setUpdater(SecurityUser.getUserId());
fileEntity.setUpdatedAt(new Date());
correctWordFileDao.updateById(fileEntity);
}
@Override
public PageData<CorrectWordFileVO> listFiles(Map<String, Object> params) {
Long userId = SecurityUser.getUserId();
IPage<CorrectWordFileEntity> page = getPage(params, "created_at", false);
LambdaQueryWrapper<CorrectWordFileEntity> wrapper = new LambdaQueryWrapper<>();
wrapper.eq(CorrectWordFileEntity::getCreator, userId)
.orderByDesc(CorrectWordFileEntity::getCreatedAt);
correctWordFileDao.selectPage(page, wrapper);
List<CorrectWordFileVO> voList = toVOList(page.getRecords());
return new PageData<>(voList, page.getTotal());
}
@Override
public List<CorrectWordFileVO> listAllFiles() {
Long userId = SecurityUser.getUserId();
LambdaQueryWrapper<CorrectWordFileEntity> wrapper = new LambdaQueryWrapper<>();
wrapper.eq(CorrectWordFileEntity::getCreator, userId)
.orderByDesc(CorrectWordFileEntity::getCreatedAt);
List<CorrectWordFileEntity> entities = correctWordFileDao.selectList(wrapper);
return toVOList(entities);
}
@Override
public CorrectWordFileVO getFileContent(String fileId) {
CorrectWordFileEntity entity = correctWordFileDao.selectById(fileId);
return toVO(entity);
}
@Override
@Transactional(rollbackFor = Exception.class)
public void deleteFile(String fileId) {
if (fileId == null || fileId.trim().isEmpty()) {
return;
}
// 先删除关联表记录
agentCorrectWordMappingDao.deleteByFileId(fileId);
// 删除词条
LambdaQueryWrapper<CorrectWordItemEntity> wrapper = new LambdaQueryWrapper<>();
wrapper.eq(CorrectWordItemEntity::getFileId, fileId);
correctWordItemDao.delete(wrapper);
// 删除文件
correctWordFileDao.deleteById(fileId);
}
@Override
@Transactional(rollbackFor = Exception.class)
public void deleteMappingsByAgentId(String agentId) {
agentCorrectWordMappingDao.deleteByAgentId(agentId);
}
@Override
public List<CorrectWordSimpleVO> getAllItemsByAgentId(String agentId) {
// 通过关联表获取文件ID列表
List<AgentCorrectWordMappingEntity> mappings = agentCorrectWordMappingDao.selectByAgentId(agentId);
if (mappings == null || mappings.isEmpty()) {
return new ArrayList<>();
}
List<String> fileIds = mappings.stream()
.map(AgentCorrectWordMappingEntity::getFileId)
.collect(Collectors.toList());
// 根据文件ID列表查询词条
LambdaQueryWrapper<CorrectWordItemEntity> wrapper = new LambdaQueryWrapper<>();
wrapper.in(CorrectWordItemEntity::getFileId, fileIds);
List<CorrectWordItemEntity> entities = correctWordItemDao.selectList(wrapper);
return ConvertUtils.sourceToTarget(entities, CorrectWordSimpleVO.class);
}
@Override
public List<String> getAgentCorrectWordFileIds(String agentId) {
List<AgentCorrectWordMappingEntity> mappings = agentCorrectWordMappingDao.selectByAgentId(agentId);
if (mappings == null || mappings.isEmpty()) {
return new ArrayList<>();
}
return mappings.stream()
.map(AgentCorrectWordMappingEntity::getFileId)
.collect(Collectors.toList());
}
@Override
@Transactional(rollbackFor = Exception.class)
public void saveAgentCorrectWords(String agentId, List<String> fileIds) {
// 先删除旧的关联记录
agentCorrectWordMappingDao.deleteByAgentId(agentId);
if (fileIds == null || fileIds.isEmpty()) {
return;
}
// 批量插入新的关联记录
Long userId = SecurityUser.getUserId();
Date now = new Date();
List<AgentCorrectWordMappingEntity> mappings = new ArrayList<>();
for (String fileId : fileIds) {
AgentCorrectWordMappingEntity mapping = new AgentCorrectWordMappingEntity();
mapping.setAgentId(agentId);
mapping.setFileId(fileId);
mapping.setCreator(userId);
mapping.setCreatedAt(now);
mapping.setUpdater(userId);
mapping.setUpdatedAt(now);
mappings.add(mapping);
}
agentCorrectWordMappingDao.batchInsertMapping(mappings);
}
@Override
@Transactional(rollbackFor = Exception.class)
public void batchDeleteFiles(List<String> fileIds) {
if (fileIds == null || fileIds.isEmpty()) {
return;
}
for (String fileId : fileIds) {
if (fileId == null || fileId.trim().isEmpty()) {
continue;
}
deleteFile(fileId.trim());
}
}
/**
* 解析替换词内容,每条格式:原词|替换词
*/
private List<CorrectWordItemEntity> parseContent(List<String> lines) {
List<CorrectWordItemEntity> items = new ArrayList<>();
if (lines == null || lines.isEmpty()) {
return items;
}
for (String line : lines) {
line = line.trim();
if (line.isEmpty()) {
continue;
}
int idx = line.indexOf('|');
if (idx <= 0 || idx >= line.length() - 1) {
continue;
}
String sourceWord = line.substring(0, idx).trim();
String targetWord = line.substring(idx + 1).trim();
if (sourceWord.isEmpty() || targetWord.isEmpty()) {
continue;
}
CorrectWordItemEntity item = new CorrectWordItemEntity();
item.setSourceWord(sourceWord);
item.setTargetWord(targetWord);
items.add(item);
}
return items;
}
private CorrectWordFileVO toVO(CorrectWordFileEntity entity) {
if (entity == null) {
return null;
}
CorrectWordFileVO vo = new CorrectWordFileVO();
vo.setId(entity.getId());
vo.setFileName(entity.getFileName());
vo.setWordCount(entity.getWordCount());
vo.setContent(entity.getContent() != null
? Arrays.asList(entity.getContent().split("\n"))
: new ArrayList<>());
vo.setCreatedAt(entity.getCreatedAt());
vo.setUpdatedAt(entity.getUpdatedAt());
return vo;
}
private List<CorrectWordFileVO> toVOList(List<CorrectWordFileEntity> entities) {
if (entities == null || entities.isEmpty()) {
return new ArrayList<>();
}
return entities.stream().map(this::toVO).collect(Collectors.toList());
}
}
@@ -0,0 +1,30 @@
package xiaozhi.modules.correctword.vo;
import java.util.Date;
import java.util.List;
import io.swagger.v3.oas.annotations.media.Schema;
import lombok.Data;
@Data
@Schema(description = "替换词文件列表VO")
public class CorrectWordFileVO {
@Schema(description = "替换词文件ID")
private String id;
@Schema(description = "原始文件名")
private String fileName;
@Schema(description = "替换词数量")
private Integer wordCount;
@Schema(description = "替换词内容,每行一条")
private List<String> content;
@Schema(description = "创建时间")
private Date createdAt;
@Schema(description = "更新时间")
private Date updatedAt;
}
@@ -0,0 +1,15 @@
package xiaozhi.modules.correctword.vo;
import io.swagger.v3.oas.annotations.media.Schema;
import lombok.Data;
@Data
@Schema(description = "替换词精简VO(设备端使用)")
public class CorrectWordSimpleVO {
@Schema(description = "原词")
private String sourceWord;
@Schema(description = "替换词")
private String targetWord;
}
@@ -4,6 +4,7 @@ import java.nio.charset.StandardCharsets;
import java.security.InvalidKeyException;
import java.security.NoSuchAlgorithmException;
import java.time.Instant;
import java.util.ArrayList;
import java.util.Base64;
import java.util.Date;
import java.util.HashMap;
@@ -38,6 +39,8 @@ import cn.hutool.crypto.digest.DigestUtil;
import cn.hutool.http.ContentType;
import cn.hutool.http.Header;
import cn.hutool.http.HttpRequest;
import cn.hutool.json.JSONArray;
import cn.hutool.json.JSONObject;
import cn.hutool.json.JSONUtil;
import jakarta.servlet.http.HttpServletRequest;
import lombok.AllArgsConstructor;
@@ -700,40 +703,82 @@ public class DeviceServiceImpl extends BaseServiceImpl<DeviceDao, DeviceEntity>
// 构建完整的URL
String url = StrUtil.format("http://{}/api/commands/{}", mqttGatewayUrl, clientId);
// 构建请求体
Map<String, Object> payload = MapUtil
.builder(new HashMap<String, Object>())
.put("jsonrpc", "2.0")
.put("id", 2)
.put("method", "tools/list")
.put("params", MapUtil.builder(new HashMap<String, Object>())
.put("withUserTools", true)
.build())
.build();
// 存储所有工具列表
List<Object> allTools = new ArrayList<>();
String cursor = null;
Map<String, Object> requestBody = MapUtil
.builder(new HashMap<String, Object>())
.put("type", "mcp")
.put("payload", payload)
.build();
// 发送请求
String resultMessage = HttpRequest.post(url)
.header(Header.CONTENT_TYPE, ContentType.JSON.getValue())
.header(Header.AUTHORIZATION, "Bearer " + generateBearerToken())
.body(JSONUtil.toJsonStr(requestBody))
.timeout(10000) // 超时,毫秒
.execute().body();
// 解析响应
if (StringUtils.isNotBlank(resultMessage)) {
cn.hutool.json.JSONObject jsonObject = JSONUtil.parseObj(resultMessage);
if (jsonObject.getBool("success", false)) {
return jsonObject.get("data");
// 循环获取分页数据
while (true) {
// 构建params
Map<String, Object> paramsMap = MapUtil.builder(new HashMap<String, Object>())
.put("withUserTools", true)
.build();
// 如果有cursor,添加到请求参数中
if (StringUtils.isNotBlank(cursor)) {
paramsMap.put("cursor", cursor);
}
// 构建请求体
Map<String, Object> payload = MapUtil
.builder(new HashMap<String, Object>())
.put("jsonrpc", "2.0")
.put("id", 2)
.put("method", "tools/list")
.put("params", paramsMap)
.build();
Map<String, Object> requestBody = MapUtil
.builder(new HashMap<String, Object>())
.put("type", "mcp")
.put("payload", payload)
.build();
// 发送请求
String resultMessage = HttpRequest.post(url)
.header(Header.CONTENT_TYPE, ContentType.JSON.getValue())
.header(Header.AUTHORIZATION, "Bearer " + generateBearerToken())
.body(JSONUtil.toJsonStr(requestBody))
.timeout(10000) // 超时,毫秒
.execute().body();
// 解析响应
if (StringUtils.isBlank(resultMessage)) {
break;
}
JSONObject jsonObject = JSONUtil.parseObj(resultMessage);
if (!jsonObject.getBool("success", false)) {
break;
}
JSONObject data = jsonObject.getJSONObject("data");
if (data == null) {
break;
}
// 获取当前页的工具列表
JSONArray tools = data.getJSONArray("tools");
if (tools != null && !tools.isEmpty()) {
allTools.addAll(tools);
}
// 获取下一页的cursor
String nextCursor = data.getStr("nextCursor");
if (StringUtils.isBlank(nextCursor)) {
// 没有下一页了
break;
}
cursor = nextCursor;
}
return null;
// 构建返回结果
if (allTools.isEmpty()) {
return null;
}
Map<String, Object> resultData = new HashMap<>();
resultData.put("tools", allTools);
return resultData;
}
@Override
@@ -66,7 +66,7 @@ public class OtaServiceImpl extends BaseServiceImpl<OtaDao, OtaEntity> implement
// 同类固件只保留最新的一条
List<OtaEntity> otaList = baseDao.selectList(queryWrapper);
if (otaList != null && otaList.size() > 0) {
OtaEntity otaBefore = otaList.getFirst();
OtaEntity otaBefore = otaList.get(0);
entity.setId(otaBefore.getId());
baseDao.updateById(entity);
return true;
@@ -0,0 +1,13 @@
package xiaozhi.modules.knowledge.config;
import org.springframework.context.annotation.Configuration;
import org.springframework.scheduling.annotation.EnableScheduling;
/**
* 知识库模块定时任务配置
* 启用 Spring Schedule 能力
*/
@Configuration
@EnableScheduling
public class RAGTaskConfig {
}
@@ -26,6 +26,7 @@ import xiaozhi.common.utils.Result;
import xiaozhi.common.utils.ToolUtil;
import xiaozhi.modules.knowledge.dto.KnowledgeBaseDTO;
import xiaozhi.modules.knowledge.service.KnowledgeBaseService;
import xiaozhi.modules.knowledge.service.KnowledgeManagerService;
import xiaozhi.modules.model.entity.ModelConfigEntity;
import xiaozhi.modules.security.user.SecurityUser;
@@ -36,6 +37,7 @@ import xiaozhi.modules.security.user.SecurityUser;
public class KnowledgeBaseController {
private final KnowledgeBaseService knowledgeBaseService;
private final KnowledgeManagerService knowledgeManagerService;
@GetMapping
@Operation(summary = "分页查询知识库列表")
@@ -96,6 +98,8 @@ public class KnowledgeBaseController {
throw new RenException(ErrorCode.NO_PERMISSION);
}
// [FIX] 注入 ID,防止 Service 层找不到记录
knowledgeBaseDTO.setId(existingKnowledgeBase.getId());
knowledgeBaseDTO.setDatasetId(datasetId);
KnowledgeBaseDTO resp = knowledgeBaseService.update(knowledgeBaseDTO);
return new Result<KnowledgeBaseDTO>().ok(resp);
@@ -117,7 +121,8 @@ public class KnowledgeBaseController {
throw new RenException(ErrorCode.NO_PERMISSION);
}
knowledgeBaseService.deleteByDatasetId(datasetId);
// [Architecture Fix] 通过编排层级联删除,防止孤儿数据并解决循环依赖
knowledgeManagerService.deleteDatasetWithFiles(datasetId);
return new Result<>();
}
@@ -133,15 +138,16 @@ public class KnowledgeBaseController {
// 获取当前登录用户ID
Long currentUserId = SecurityUser.getUserId();
List<String> idList = Arrays.asList(ids.split(","));
List<KnowledgeBaseDTO> knowledgeBaseDTOs = Optional.ofNullable(knowledgeBaseService.getByDatasetIdList(idList)).orElseGet(ArrayList::new);
List<KnowledgeBaseDTO> knowledgeBaseDTOs = Optional.ofNullable(knowledgeBaseService.getByDatasetIdList(idList))
.orElseGet(ArrayList::new);
if (ToolUtil.isNotEmpty(knowledgeBaseDTOs)) {
knowledgeBaseDTOs.forEach(item->{
knowledgeBaseDTOs.forEach(item -> {
// 检查权限:用户只能删除自己创建的知识库
if (item.getCreator() == null || !item.getCreator().equals(currentUserId)) {
throw new RenException(ErrorCode.NO_PERMISSION);
}
//删除
knowledgeBaseService.deleteByDatasetId(item.getDatasetId());
// [Architecture Fix] 通过编排层级联删除
knowledgeManagerService.deleteDatasetWithFiles(item.getDatasetId());
});
}
return new Result<>();
@@ -4,6 +4,7 @@ import java.util.List;
import java.util.Map;
import org.apache.shiro.authz.annotation.RequiresPermissions;
import org.springdoc.core.annotations.ParameterObject;
import org.springframework.web.bind.annotation.*;
import org.springframework.web.multipart.MultipartFile;
@@ -11,7 +12,6 @@ import com.fasterxml.jackson.core.type.TypeReference;
import com.fasterxml.jackson.databind.ObjectMapper;
import io.swagger.v3.oas.annotations.Operation;
import io.swagger.v3.oas.annotations.Parameter;
import io.swagger.v3.oas.annotations.tags.Tag;
import lombok.AllArgsConstructor;
import xiaozhi.common.exception.ErrorCode;
@@ -20,6 +20,9 @@ import xiaozhi.common.page.PageData;
import xiaozhi.common.utils.Result;
import xiaozhi.modules.knowledge.dto.KnowledgeBaseDTO;
import xiaozhi.modules.knowledge.dto.KnowledgeFilesDTO;
import xiaozhi.modules.knowledge.dto.document.ChunkDTO;
import xiaozhi.modules.knowledge.dto.document.DocumentDTO;
import xiaozhi.modules.knowledge.dto.document.RetrievalDTO;
import xiaozhi.modules.knowledge.service.KnowledgeBaseService;
import xiaozhi.modules.knowledge.service.KnowledgeFilesService;
import xiaozhi.modules.security.user.SecurityUser;
@@ -57,13 +60,13 @@ public class KnowledgeFilesController {
public Result<PageData<KnowledgeFilesDTO>> getPageList(
@PathVariable("dataset_id") String datasetId,
@RequestParam(required = false) String name,
@RequestParam(required = false) Integer status,
@RequestParam(required = false) String status,
@RequestParam(required = false, defaultValue = "1") Integer page,
@RequestParam(required = false, defaultValue = "10") Integer page_size) {
// 验证知识库权限
validateKnowledgeBasePermission(datasetId);
//组装参数
// 组装参数
KnowledgeFilesDTO knowledgeFilesDTO = new KnowledgeFilesDTO();
knowledgeFilesDTO.setDatasetId(datasetId);
knowledgeFilesDTO.setName(name);
@@ -77,12 +80,12 @@ public class KnowledgeFilesController {
@RequiresPermissions("sys:role:normal")
public Result<PageData<KnowledgeFilesDTO>> getPageListByStatus(
@PathVariable("dataset_id") String datasetId,
@PathVariable("status") Integer status,
@PathVariable("status") String status,
@RequestParam(required = false, defaultValue = "1") Integer page,
@RequestParam(required = false, defaultValue = "10") Integer page_size) {
// 验证知识库权限
validateKnowledgeBasePermission(datasetId);
//组装参数
// 组装参数
KnowledgeFilesDTO knowledgeFilesDTO = new KnowledgeFilesDTO();
knowledgeFilesDTO.setDatasetId(datasetId);
knowledgeFilesDTO.setStatus(status);
@@ -111,16 +114,29 @@ public class KnowledgeFilesController {
return new Result<KnowledgeFilesDTO>().ok(resp);
}
@DeleteMapping("/documents/{document_id}")
@Operation(summary = "删除单个文档")
@Parameter(name = "document_id", description = "文档ID", required = true)
@DeleteMapping("/documents")
@Operation(summary = "批量删除文档")
@RequiresPermissions("sys:role:normal")
public Result<Void> delete(@PathVariable("dataset_id") String datasetId,
@RequestBody DocumentDTO.BatchIdReq req) {
// 验证知识库权限
validateKnowledgeBasePermission(datasetId);
knowledgeFilesService.deleteDocuments(datasetId, req);
return new Result<>();
}
@DeleteMapping("/documents/{document_id}")
@Operation(summary = "删除单个文档")
@RequiresPermissions("sys:role:normal")
public Result<Void> deleteSingle(@PathVariable("dataset_id") String datasetId,
@PathVariable("document_id") String documentId) {
// 验证知识库权限
validateKnowledgeBasePermission(datasetId);
knowledgeFilesService.deleteByDocumentId(documentId, datasetId);
DocumentDTO.BatchIdReq req = new DocumentDTO.BatchIdReq();
req.setIds(java.util.Collections.singletonList(documentId));
knowledgeFilesService.deleteDocuments(datasetId, req);
return new Result<>();
}
@@ -148,64 +164,53 @@ public class KnowledgeFilesController {
@GetMapping("/documents/{document_id}/chunks")
@Operation(summary = "列出指定文档的切片")
@RequiresPermissions("sys:role:normal")
public Result<Map<String, Object>> listChunks(@PathVariable("dataset_id") String datasetId,
public Result<ChunkDTO.ListVO> listChunks(
@PathVariable("dataset_id") String datasetId,
@PathVariable("document_id") String documentId,
@RequestParam(required = false) String keywords,
@RequestParam(required = false, defaultValue = "1") Integer page,
@RequestParam(required = false, defaultValue = "1024") Integer page_size,
@RequestParam(required = false) String id) {
// 验证知识库权限
@ParameterObject ChunkDTO.ListReq req) {
// 验证权限 (内部已包含知识库存在性校验与归属权校验)
validateKnowledgeBasePermission(datasetId);
Map<String, Object> result = knowledgeFilesService.listChunks(datasetId, documentId, keywords, page, page_size, id);
return new Result<Map<String, Object>>().ok(result);
// 设置默认值
if (req.getPage() == null)
req.setPage(1);
if (req.getPageSize() == null)
req.setPageSize(50);
// 调用服务层获取强类型切片列表
ChunkDTO.ListVO result = knowledgeFilesService.listChunks(datasetId, documentId, req);
return new Result<ChunkDTO.ListVO>().ok(result);
}
/**
* 召回测试
*/
@PostMapping("/retrieval-test")
@Operation(summary = "召回测试")
@RequiresPermissions("sys:role:normal")
public Result<Map<String, Object>> retrievalTest(@PathVariable("dataset_id") String datasetId,
@RequestBody Map<String, Object> params) {
public Result<RetrievalDTO.ResultVO> retrievalTest(
@PathVariable("dataset_id") String datasetId,
@RequestBody RetrievalDTO.TestReq req) {
// 验证知识库权限
validateKnowledgeBasePermission(datasetId);
try {
// 提取参数
String question = (String) params.get("question");
if (question == null || question.trim().isEmpty()) {
return new Result<Map<String, Object>>().error("问题不能为空");
}
List<String> datasetIds = (List<String>) params.get("dataset_ids");
List<String> documentIds = (List<String>) params.get("document_ids");
Integer page = (Integer) params.get("page");
Integer pageSize = (Integer) params.get("page_size");
Float similarityThreshold = (Float) params.get("similarity_threshold");
Float vectorSimilarityWeight = (Float) params.get("vector_similarity_weight");
Integer topK = (Integer) params.get("top_k");
String rerankId = (String) params.get("rerank_id");
Boolean keyword = (Boolean) params.get("keyword");
Boolean highlight = (Boolean) params.get("highlight");
List<String> crossLanguages = (List<String>) params.get("cross_languages");
Map<String, Object> metadataCondition = (Map<String, Object>) params.get("metadata_condition");
// 如果未指定数据集ID,使用当前数据集
if (datasetIds == null || datasetIds.isEmpty()) {
datasetIds = java.util.Arrays.asList(datasetId);
}
Map<String, Object> result = knowledgeFilesService.retrievalTest(
question, datasetIds, documentIds, page, pageSize, similarityThreshold,
vectorSimilarityWeight, topK, rerankId, keyword, highlight, crossLanguages, metadataCondition);
return new Result<Map<String, Object>>().ok(result);
} catch (Exception e) {
return new Result<Map<String, Object>>().error("召回测试失败: " + e.getMessage());
// 业务下沉逻辑:如果未指定知识库ID,则设为当前路径中的 datasetId
if (req.getDatasetIds() == null || req.getDatasetIds().isEmpty()) {
req.setDatasetIds(java.util.Arrays.asList(datasetId));
}
// [Reinforce] 强管控分页参数,防止 RAGFlow 端出现 Negative Slicing 报错
if (req.getPage() == null || req.getPage() < 1) {
req.setPage(1);
}
if (req.getPageSize() == null || req.getPageSize() < 1) {
req.setPageSize(100);
}
// 调用检索服务,返回强类型聚合对象
RetrievalDTO.ResultVO result = knowledgeFilesService.retrievalTest(req);
return new Result<RetrievalDTO.ResultVO>().ok(result);
}
/**
* 解析JSON字符串为Map对象
*/
@@ -0,0 +1,12 @@
package xiaozhi.modules.knowledge.dao;
import org.apache.ibatis.annotations.Mapper;
import xiaozhi.common.dao.BaseDao;
import xiaozhi.modules.knowledge.entity.DocumentEntity;
/**
* 文档 DAO
*/
@Mapper
public interface DocumentDao extends BaseDao<DocumentEntity> {
}
@@ -19,4 +19,17 @@ public interface KnowledgeBaseDao extends BaseDao<KnowledgeBaseEntity> {
*/
void deletePluginMappingByKnowledgeBaseId(@Param("knowledgeBaseId") String knowledgeBaseId);
/**
* 通用维度原子更新知识库统计信息
*
* @param datasetId 数据集ID
* @param docDelta 文档数增量
* @param chunkDelta 分块数增量
* @param tokenDelta Token数增量
*/
void updateStatsAfterChange(@Param("datasetId") String datasetId,
@Param("docDelta") Integer docDelta,
@Param("chunkDelta") Long chunkDelta,
@Param("tokenDelta") Long tokenDelta);
}
@@ -0,0 +1,68 @@
package xiaozhi.modules.knowledge.dto;
import java.io.Serializable;
import java.util.Date;
import java.util.Map;
import io.swagger.v3.oas.annotations.media.Schema;
import lombok.Data;
/**
* 文档 DTO
*/
@Data
@Schema(description = "知识库文档")
public class DocumentDTO implements Serializable {
private static final long serialVersionUID = 1L;
@Schema(description = "本地ID")
private String id;
@Schema(description = "知识库ID")
private String datasetId;
@Schema(description = "RAGFlow文档ID")
private String documentId;
@Schema(description = "文档名称")
private String name;
@Schema(description = "文件大小")
private Long size;
@Schema(description = "文件类型")
private String type;
@Schema(description = "分块方法")
private String chunkMethod;
@Schema(description = "解析配置")
private Map<String, Object> parserConfig;
@Schema(description = "处理状态 (1:解析中 3:成功 4:失败)")
private Integer status;
@Schema(description = "错误信息")
private String error;
@Schema(description = "分块数量")
private Integer chunkCount;
@Schema(description = "Token数量")
private Long tokenCount;
@Schema(description = "是否启用")
private Integer enabled;
@Schema(description = "创建时间")
private Date createdAt;
@Schema(description = "更新时间")
private Date updatedAt;
@Schema(description = "上传进度 (虚拟字段)")
private Double progress;
@Schema(description = "缩略图/预览图 (虚拟字段)")
private String thumbnail;
}
@@ -26,9 +26,30 @@ public class KnowledgeBaseDTO implements Serializable {
@Schema(description = "知识库名称")
private String name;
@Schema(description = "知识库头像(Base64)")
private String avatar;
@Schema(description = "知识库描述")
private String description;
@Schema(description = "嵌入模型名称")
private String embeddingModel;
@Schema(description = "权限设置: me/team")
private String permission;
@Schema(description = "分块方法")
private String chunkMethod;
@Schema(description = "解析器配置(JSON String)")
private String parserConfig;
@Schema(description = "分块总数")
private Long chunkCount;
@Schema(description = "总Token数")
private Long tokenNum;
@Schema(description = "状态(0:禁用 1:启用)")
private Integer status;
@@ -6,10 +6,12 @@ import java.util.Date;
import java.util.Map;
import io.swagger.v3.oas.annotations.media.Schema;
import com.fasterxml.jackson.annotation.JsonIgnoreProperties;
import lombok.Data;
@Data
@Schema(description = "知识库文档")
@JsonIgnoreProperties(ignoreUnknown = true)
public class KnowledgeFilesDTO implements Serializable {
@Serial
@@ -35,7 +37,19 @@ public class KnowledgeFilesDTO implements Serializable {
@Schema(description = "文件路径")
private String filePath;
@Schema(description = "元数据字段")
@Schema(description = "解析进度 (0.0 ~ 1.0)")
private Double progress;
@Schema(description = "缩略图 (Base64 或 URL)")
private String thumbnail;
@Schema(description = "解析耗时 (单位: 秒)")
private Double processDuration;
@Schema(description = "来源类型 (local, s3, url 等)")
private String sourceType;
@Schema(description = "元数据字段 (Map 格式)")
private Map<String, Object> metaFields;
@Schema(description = "分块方法")
@@ -44,10 +58,10 @@ public class KnowledgeFilesDTO implements Serializable {
@Schema(description = "解析器配置")
private Map<String, Object> parserConfig;
@Schema(description = "状态")
private Integer status;
@Schema(description = "可用状态 (1: 启用/正常, 0: 禁用/失效)")
private String status;
@Schema(description = "文档解析状态")
@Schema(description = "运行状态 (UNSTART/RUNNING/CANCEL/DONE/FAIL)")
private String run;
@Schema(description = "创建者")
@@ -62,6 +76,15 @@ public class KnowledgeFilesDTO implements Serializable {
@Schema(description = "更新时间")
private Date updatedAt;
@Schema(description = "分块数量")
private Integer chunkCount;
@Schema(description = "Token数量")
private Long tokenCount;
@Schema(description = "解析错误信息")
private String error;
// 文档解析状态常量定义
private static final Integer STATUS_UNSTART = 0;
private static final Integer STATUS_RUNNING = 1;
@@ -0,0 +1,421 @@
package xiaozhi.modules.knowledge.dto.agent;
import lombok.*;
import io.swagger.v3.oas.annotations.media.Schema;
import java.io.Serializable;
import java.util.List;
import java.util.Map;
import com.fasterxml.jackson.annotation.JsonProperty;
import jakarta.validation.constraints.*;
@Schema(description = "智能体 (Agent) 管理聚合 DTO")
public class AgentDTO {
// ========== 1. Agent 管理 (CRUD) - 对应 RAGFlow_Agent接口详解 ==========
@Data
@Builder
@NoArgsConstructor
@AllArgsConstructor
@Schema(description = "Agent 创建请求")
public static class CreateReq implements Serializable {
@Schema(description = "Agent 标题", requiredMode = Schema.RequiredMode.REQUIRED, example = "My Agent")
@NotBlank(message = "Agent 标题不能为空")
@JsonProperty("title")
private String title;
@Schema(description = "DSL 定义 (画布 JSON)", requiredMode = Schema.RequiredMode.REQUIRED)
@NotNull(message = "DSL 定义不能为空")
@JsonProperty("dsl")
private Map<String, Object> dsl;
@Schema(description = "描述", example = "这是一个测试 Agent")
@JsonProperty("description")
private String description;
@Schema(description = "头像 URL", example = "http://example.com/avatar.png")
@JsonProperty("avatar")
private String avatar;
}
@Data
@Builder
@NoArgsConstructor
@AllArgsConstructor
@Schema(description = "Agent 更新请求")
public static class UpdateReq implements Serializable {
@Schema(description = "Agent 标题", example = "Updated Agent")
@JsonProperty("title")
private String title;
@Schema(description = "DSL 定义 (画布 JSON)")
@JsonProperty("dsl")
private Map<String, Object> dsl;
@Schema(description = "描述")
@JsonProperty("description")
private String description;
@Schema(description = "头像 URL")
@JsonProperty("avatar")
private String avatar;
}
@Data
@Builder
@NoArgsConstructor
@AllArgsConstructor
@Schema(description = "Agent 列表请求")
public static class ListReq implements Serializable {
@Schema(description = "页码", defaultValue = "1")
@JsonProperty("page")
@Builder.Default
private Integer page = 1;
@Schema(description = "每页大小", defaultValue = "10")
@JsonProperty("page_size")
@Builder.Default
private Integer pageSize = 10;
@Schema(description = "排序字段", defaultValue = "update_time")
@JsonProperty("orderby")
@Builder.Default
private String orderby = "update_time";
@Schema(description = "是否降序", defaultValue = "true")
@JsonProperty("desc")
@Builder.Default
private Boolean desc = true;
@Schema(description = "Agent ID 过滤")
@JsonProperty("id")
private String id;
@Schema(description = "标题模糊搜索")
@JsonProperty("title")
private String title;
}
@Data
@Builder
@NoArgsConstructor
@AllArgsConstructor
@Schema(description = "Agent 响应对象")
public static class AgentVO implements Serializable {
@Schema(description = "Agent ID")
@JsonProperty("id")
private String id;
@Schema(description = "标题")
@JsonProperty("title")
private String title;
@Schema(description = "描述")
@JsonProperty("description")
private String description;
@Schema(description = "头像")
@JsonProperty("avatar")
private String avatar;
@Schema(description = "DSL 定义")
@JsonProperty("dsl")
private Map<String, Object> dsl;
@Schema(description = "创建者 ID")
@JsonProperty("user_id")
private String userId;
@Schema(description = "画布分类")
@JsonProperty("canvas_category")
private String canvasCategory;
@Schema(description = "创建时间 (时间戳)")
@JsonProperty("create_time")
private Long createTime;
@Schema(description = "更新时间 (时间戳)")
@JsonProperty("update_time")
private Long updateTime;
}
// ========== 2. Webhook 调试与追踪 - 对应 RAGFlow_Agent接口详解 ==========
@Data
@Builder
@NoArgsConstructor
@AllArgsConstructor
@Schema(description = "Webhook 触发请求 (参数动态)")
public static class WebhookTriggerReq implements Serializable {
@Schema(description = "输入变量", requiredMode = Schema.RequiredMode.REQUIRED)
@NotNull(message = "输入变量不能为空")
@JsonProperty("inputs")
private Map<String, Object> inputs;
@Schema(description = "查询词", example = "Hello")
@JsonProperty("query")
private String query;
}
@Data
@Builder
@NoArgsConstructor
@AllArgsConstructor
@Schema(description = "Webhook 追踪请求")
public static class WebhookTraceReq implements Serializable {
@Schema(description = "时间戳游标", example = "1700000000.0")
@JsonProperty("since_ts")
private Double sinceTs;
@Schema(description = "Webhook ID")
@JsonProperty("webhook_id")
private String webhookId;
}
@Data
@Builder
@NoArgsConstructor
@AllArgsConstructor
@Schema(description = "Webhook 追踪响应")
public static class WebhookTraceVO implements Serializable {
@Schema(description = "Webhook ID")
@JsonProperty("webhook_id")
private String webhookId;
@Schema(description = "是否结束")
@JsonProperty("finished")
private Boolean finished;
@Schema(description = "下一次查询的时间戳游标")
@JsonProperty("next_since_ts")
private Double nextSinceTs;
@Schema(description = "事件列表")
@JsonProperty("events")
private List<TraceEvent> events;
@Data
@Builder
@NoArgsConstructor
@AllArgsConstructor
@Schema(description = "追踪事件项")
public static class TraceEvent implements Serializable {
@Schema(description = "时间戳")
@JsonProperty("ts")
private Double ts;
@Schema(description = "事件类型")
@JsonProperty("event")
private String event;
@Schema(description = "事件数据")
@JsonProperty("data")
private Object data;
}
}
// ========== 3. Agent 会话 (Session) - 对应 RAGFlow_Agent_Dify接口详解 ==========
@Data
@Builder
@NoArgsConstructor
@AllArgsConstructor
@Schema(description = "Session 创建请求")
public static class SessionCreateReq implements Serializable {
@Schema(description = "用户 ID")
@JsonProperty("user_id")
private String userId;
}
@Data
@Builder
@NoArgsConstructor
@AllArgsConstructor
@Schema(description = "Session 列表请求")
public static class SessionListReq implements Serializable {
@Schema(description = "页码", defaultValue = "1")
@JsonProperty("page")
@Builder.Default
private Integer page = 1;
@Schema(description = "每页大小", defaultValue = "10")
@JsonProperty("page_size")
@Builder.Default
private Integer pageSize = 10;
@Schema(description = "排序字段", defaultValue = "create_time")
@JsonProperty("orderby")
@Builder.Default
private String orderby = "create_time";
@Schema(description = "是否降序", defaultValue = "true")
@JsonProperty("desc")
@Builder.Default
private Boolean desc = true;
@Schema(description = "Session ID")
@JsonProperty("id")
private String id;
@Schema(description = "用户 ID")
@JsonProperty("user_id")
private String userId;
@Schema(description = "是否返回 DSL")
@JsonProperty("dsl")
@Builder.Default
private Boolean dsl = false;
}
@Data
@Builder
@NoArgsConstructor
@AllArgsConstructor
@Schema(description = "Session 批量删除请求")
public static class SessionBatchDeleteReq implements Serializable {
@Schema(description = "会话 ID 列表", requiredMode = Schema.RequiredMode.REQUIRED)
@JsonProperty("ids")
@NotEmpty(message = "ID列表不能为空")
private List<String> ids;
}
@Data
@Builder
@NoArgsConstructor
@AllArgsConstructor
@Schema(description = "Session 响应对象")
public static class SessionVO implements Serializable {
@Schema(description = "Session ID")
@JsonProperty("id")
private String id;
@Schema(description = "Agent ID")
@JsonProperty("agent_id")
private String agentId;
@Schema(description = "用户 ID")
@JsonProperty("user_id")
private String userId;
@Schema(description = "来源")
@JsonProperty("source")
private String source;
@Schema(description = "DSL 定义")
@JsonProperty("dsl")
private Map<String, Object> dsl;
@Schema(description = "消息列表")
@JsonProperty("messages")
private List<Map<String, Object>> messages;
}
// ========== 4. Agent 对话 (Completion) - 对应 RAGFlow_Agent_Dify接口详解 ==========
@Data
@Builder
@NoArgsConstructor
@AllArgsConstructor
@Schema(description = "Completion 对话请求")
public static class CompletionReq implements Serializable {
@Schema(description = "会话 ID", requiredMode = Schema.RequiredMode.REQUIRED)
@NotBlank(message = "会话 ID 不能为空")
@JsonProperty("session_id")
private String sessionId;
@Schema(description = "用户问题")
@JsonProperty("question")
private String question;
@Schema(description = "是否流式返回", defaultValue = "true")
@JsonProperty("stream")
@Builder.Default
private Boolean stream = true;
@Schema(description = "是否返回追踪信息", defaultValue = "false")
@JsonProperty("return_trace")
@Builder.Default
private Boolean returnTrace = false;
}
@Data
@Builder
@NoArgsConstructor
@AllArgsConstructor
@Schema(description = "Completion 对话响应")
public static class CompletionVO implements Serializable {
@Schema(description = "会话 ID")
@JsonProperty("id")
private String id;
@Schema(description = "回复内容")
@JsonProperty("content")
private String content;
@Schema(description = "引用来源")
@JsonProperty("reference")
private Map<String, Object> reference;
@Schema(description = "追踪信息")
@JsonProperty("trace")
private List<Object> trace;
}
// ========== 5. Dify 兼容检索 - 对应 RAGFlow_Agent_Dify接口详解 ==========
@Data
@Builder
@NoArgsConstructor
@AllArgsConstructor
@Schema(description = "Dify 兼容检索请求")
public static class DifyRetrievalReq implements Serializable {
@Schema(description = "知识库 ID")
@JsonProperty("knowledge_id")
private String knowledgeId;
@Schema(description = "查询词")
@JsonProperty("query")
private String query;
@Schema(description = "检索设置")
@JsonProperty("retrieval_setting")
private Map<String, Object> retrievalSetting;
@Schema(description = "元数据过滤条件")
@JsonProperty("metadata_condition")
private Map<String, Object> metadataCondition;
@Schema(description = "是否使用知识图谱")
@JsonProperty("use_kg")
private Boolean useKg;
}
@Data
@Builder
@NoArgsConstructor
@AllArgsConstructor
@Schema(description = "Dify 兼容检索响应")
public static class DifyRetrievalVO implements Serializable {
@Schema(description = "检索结果列表")
@JsonProperty("records")
private List<Record> records;
@Data
@Builder
@NoArgsConstructor
@AllArgsConstructor
@Schema(description = "检索记录")
public static class Record implements Serializable {
@Schema(description = "内容")
@JsonProperty("content")
private String content;
@Schema(description = "相似度分数")
@JsonProperty("score")
private Double score;
@Schema(description = "标题")
@JsonProperty("title")
private String title;
@Schema(description = "元数据")
@JsonProperty("metadata")
private Map<String, Object> metadata;
}
}
}
@@ -0,0 +1,126 @@
package xiaozhi.modules.knowledge.dto.bot;
import lombok.*;
import io.swagger.v3.oas.annotations.media.Schema;
import java.io.Serializable;
import java.util.List;
import java.util.Map;
import com.fasterxml.jackson.annotation.JsonProperty;
import jakarta.validation.constraints.*;
@Schema(description = "外部机器人 (Bot) 聚合 DTO")
public class BotDTO {
// ========== 1. SearchBot (检索机器人) ==========
// 对应 /api/v1/searchbots/ask
@Data
@Builder
@NoArgsConstructor
@AllArgsConstructor
@Schema(description = "SearchBot 提问请求")
public static class SearchAskReq implements Serializable {
@Schema(description = "用户问题", requiredMode = Schema.RequiredMode.REQUIRED, example = "What is RAG?")
@NotBlank(message = "问题不能为空")
@JsonProperty("question")
private String question;
@Schema(description = "是否返回引用", defaultValue = "false")
@JsonProperty("quote")
@Builder.Default
private Boolean quote = false;
@Schema(description = "是否流式返回", defaultValue = "true")
@JsonProperty("stream")
@Builder.Default
private Boolean stream = true;
}
@Data
@Builder
@NoArgsConstructor
@AllArgsConstructor
@Schema(description = "SearchBot 提问响应")
public static class SearchAskVO implements Serializable {
@Schema(description = "回答内容")
@JsonProperty("answer")
private String answer;
@Schema(description = "引用来源 (Value 结构通常对应 RetrievalDTO.HitVO)")
@JsonProperty("reference")
private Map<String, Object> reference;
}
// 对应 /api/v1/searchbots/related_questions
@Data
@Builder
@NoArgsConstructor
@AllArgsConstructor
@Schema(description = "相关问题请求")
public static class RelatedQuestionReq implements Serializable {
@Schema(description = "用户问题", requiredMode = Schema.RequiredMode.REQUIRED)
@NotBlank(message = "问题不能为空")
@JsonProperty("question")
private String question;
}
// 对应 /api/v1/searchbots/mindmap
@Data
@Builder
@NoArgsConstructor
@AllArgsConstructor
@Schema(description = "思维导图请求")
public static class MindMapReq implements Serializable {
@Schema(description = "用户问题", requiredMode = Schema.RequiredMode.REQUIRED)
@NotBlank(message = "问题不能为空")
@JsonProperty("question")
private String question;
}
// ========== 2. AgentBot (嵌入式 Agent) ==========
// 对应 /api/v1/agentbots/{id}/inputs
@Data
@Builder
@AllArgsConstructor
@Schema(description = "AgentBot 输入参数请求")
public static class AgentInputsReq implements Serializable {
}
@Data
@Builder
@NoArgsConstructor
@AllArgsConstructor
@Schema(description = "AgentBot 输入参数定义响应")
public static class AgentInputsVO implements Serializable {
@Schema(description = "表单变量定义列表")
@JsonProperty("variables")
private List<Map<String, Object>> variables;
}
// 对应 /api/v1/agentbots/{id}/completions
@Data
@Builder
@NoArgsConstructor
@AllArgsConstructor
@Schema(description = "AgentBot 对话请求")
public static class AgentCompletionReq implements Serializable {
@Schema(description = "输入参数值")
@JsonProperty("inputs")
private Map<String, Object> inputs;
@Schema(description = "用户查询", requiredMode = Schema.RequiredMode.REQUIRED)
@NotBlank(message = "查询内容不能为空")
@JsonProperty("question")
private String question;
@Schema(description = "是否流式返回", defaultValue = "true")
@JsonProperty("stream")
@Builder.Default
private Boolean stream = true;
@Schema(description = "会话 ID")
@JsonProperty("session_id")
private String sessionId;
}
}
@@ -0,0 +1,50 @@
package xiaozhi.modules.knowledge.dto.chat;
import java.io.Serializable;
import java.util.List;
import java.util.Map;
import com.fasterxml.jackson.annotation.JsonProperty;
import io.swagger.v3.oas.annotations.media.Schema;
import lombok.Data;
/**
* 聊天对话请求 DTO (OpenAI 兼容格式)
*/
@Data
@Schema(description = "聊天对话请求")
public class ChatCompletionRequest implements Serializable {
@Schema(description = "模型标识 (对应 agent_id 或 bot_id)", requiredMode = Schema.RequiredMode.REQUIRED)
@JsonProperty("model")
private String model;
@Schema(description = "对话消息列表", requiredMode = Schema.RequiredMode.REQUIRED)
@JsonProperty("messages")
private List<Message> messages;
@Schema(description = "是否流式返回", defaultValue = "false")
@JsonProperty("stream")
private Boolean stream = false;
@Schema(description = "温度系数 (0-1)", defaultValue = "0.7")
@JsonProperty("temperature")
private Double temperature;
@Schema(description = "Session ID (可选,用于延续会话)")
@JsonProperty("session_id")
private String sessionId;
@Schema(description = "其他RAGFlow特定参数 (可选)")
private Map<String, Object> extra;
@Data
public static class Message implements Serializable {
@Schema(description = "角色 (system, user, assistant)", requiredMode = Schema.RequiredMode.REQUIRED)
private String role;
@Schema(description = "内容", requiredMode = Schema.RequiredMode.REQUIRED)
private String content;
}
}
@@ -0,0 +1,523 @@
package xiaozhi.modules.knowledge.dto.chat;
import lombok.*;
import io.swagger.v3.oas.annotations.media.Schema;
import java.io.Serializable;
import java.util.List;
import java.util.Map;
import com.fasterxml.jackson.annotation.JsonProperty;
import jakarta.validation.constraints.*;
/**
* 对话管理聚合 DTO
* <p>
* 容器类,内含对话助手、会话和消息的所有请求/响应对象。
* </p>
*/
@Schema(description = "对话管理聚合 DTO")
public class ChatDTO {
// ========== 1. 对话助手 (Assistant/Bot) 相关 ==========
/**
* 提示词配置
*/
@Data
@NoArgsConstructor
@AllArgsConstructor
@Builder
@Schema(description = "提示词配置")
public static class PromptConfig implements Serializable {
@Schema(description = "系统提示词", example = "你是一个专业的客服助手...")
@JsonProperty("prompt")
private String systemPrompt;
@Schema(description = "开场白", example = "您好,我是您的智能助手,请问有什么可以帮您?")
private String opener;
@Schema(description = "空结果回复", example = "抱歉,我没有找到相关信息。")
@JsonProperty("empty_response")
private String emptyResponse;
@Schema(description = "是否展示引用", example = "true")
@JsonProperty("show_quote")
private Boolean quote;
@Schema(description = "是否启用 TTS", example = "false")
private Boolean tts;
@Schema(description = "相似度阈值 (0.0 - 1.0)", example = "0.2")
@JsonProperty("similarity_threshold")
private Float similarityThreshold;
@Schema(description = "关键词相似度权重 (0.0 - 1.0)", example = "0.7")
@JsonProperty("keywords_similarity_weight")
private Float vectorSimilarityWeight;
@Schema(description = "检索 Top N", example = "6")
@JsonProperty("top_n")
private Integer topK;
@Schema(description = "Rerank 模型", example = "rerank_model_001")
@JsonProperty("rerank_model")
private String rerankId;
@Schema(description = "是否启用多轮对话优化", example = "false")
@JsonProperty("refine_multiturn")
private Boolean refineMultigraph;
@Schema(description = "变量列表")
private List<Map<String, Object>> variables;
}
/**
* LLM 配置
*/
@Data
@NoArgsConstructor
@AllArgsConstructor
@Builder
@Schema(description = "LLM 模型配置")
public static class LLMConfig implements Serializable {
@NotBlank(message = "模型名称不能为空")
@Schema(description = "模型名称", requiredMode = Schema.RequiredMode.REQUIRED, example = "gpt-4")
@JsonProperty("model_name")
private String modelName;
@Schema(description = "温度参数 (0.0 - 2.0)", example = "0.7")
private Float temperature;
@Schema(description = "Top P 采样", example = "0.9")
@JsonProperty("top_p")
private Float topP;
@Schema(description = "最大 Token 数", example = "4096")
@JsonProperty("max_tokens")
private Integer maxTokens;
@Schema(description = "存在惩罚", example = "0.0")
@JsonProperty("presence_penalty")
private Float presencePenalty;
@Schema(description = "频率惩罚", example = "0.0")
@JsonProperty("frequency_penalty")
private Float frequencyPenalty;
}
/**
* 创建助手请求
*/
@Data
@NoArgsConstructor
@AllArgsConstructor
@Builder
@Schema(description = "创建助手请求")
public static class AssistantCreateReq implements Serializable {
@NotBlank(message = "助手名称不能为空")
@Schema(description = "助手名称", requiredMode = Schema.RequiredMode.REQUIRED, example = "智能客服助手")
private String name;
@Schema(description = "助手头像 (Base64 编码)", example = "")
private String avatar;
@Schema(description = "关联的知识库 ID 列表", example = "[\"kb_001\", \"kb_002\"]")
@JsonProperty("dataset_ids")
private List<String> datasetIds;
@Schema(description = "助手描述", example = "这是一个智能客服助手")
private String description;
@Schema(description = "LLM 模型配置")
@JsonProperty("llm")
private LLMConfig llm;
@Schema(description = "提示词配置")
@JsonProperty("prompt")
private PromptConfig promptConfig;
}
/**
* 更新助手请求
*/
@Data
@NoArgsConstructor
@AllArgsConstructor
@Builder
@Schema(description = "更新助手请求")
public static class AssistantUpdateReq implements Serializable {
@Schema(description = "助手名称", example = "智能客服助手 V2")
private String name;
@Schema(description = "助手头像 (Base64 编码)", example = "")
private String avatar;
@Schema(description = "关联的知识库 ID 列表", example = "[\"kb_001\", \"kb_002\"]")
@JsonProperty("dataset_ids")
private List<String> datasetIds;
@Schema(description = "助手描述", example = "这是一个智能客服助手")
private String description;
@Schema(description = "LLM 模型配置")
@JsonProperty("llm")
private LLMConfig llm;
@Schema(description = "提示词配置")
@JsonProperty("prompt")
private PromptConfig promptConfig;
}
/**
* 查询助手列表请求
*/
@Data
@NoArgsConstructor
@AllArgsConstructor
@Builder
@Schema(description = "查询助手列表请求")
public static class AssistantListReq implements Serializable {
@Schema(description = "页码 (从 1 开始)", example = "1")
private Integer page;
@Schema(description = "每页数量", example = "30")
@JsonProperty("page_size")
private Integer pageSize;
@Schema(description = "按名称过滤 (模糊匹配)", example = "客服")
private String name;
@Schema(description = "排序字段: create_time / update_time", example = "create_time")
private String orderby;
@Schema(description = "是否降序", example = "true")
private Boolean desc;
@Schema(description = "按 ID 精确筛选", example = "assistant_001")
private String id;
}
/**
* 助手详情 VO
*/
@Data
@NoArgsConstructor
@AllArgsConstructor
@Builder
@Schema(description = "助手详情 VO")
public static class AssistantVO implements Serializable {
@Schema(description = "助手 ID", example = "assistant_001")
private String id;
@Schema(description = "租户 ID", example = "tenant_001")
@JsonProperty("tenant_id")
private String tenantId;
@Schema(description = "助手名称", example = "智能客服助手")
private String name;
@Schema(description = "助手头像", example = "")
private String avatar;
@Schema(description = "关联的知识库 ID 列表")
@JsonProperty("dataset_ids")
private List<String> datasetIds;
@Schema(description = "关联的知识库列表 (详情)")
private List<SimpleDatasetVO> datasets;
@Schema(description = "助手描述")
private String description;
@Schema(description = "LLM 模型配置")
@JsonProperty("llm")
private LLMConfig llm;
@Schema(description = "提示词配置")
@JsonProperty("prompt")
private PromptConfig promptConfig;
@Schema(description = "创建时间 (时间戳)", example = "1700000000000")
@JsonProperty("create_time")
private Long createTime;
@Schema(description = "更新时间 (时间戳)", example = "1700000001000")
@JsonProperty("update_time")
private Long updateTime;
}
/**
* 删除助手请求
*/
@Data
@NoArgsConstructor
@AllArgsConstructor
@Builder
@Schema(description = "删除助手请求")
public static class AssistantDeleteReq implements Serializable {
@Schema(description = "要删除的助手 ID 列表", example = "[\"assistant_001\", \"assistant_002\"]")
private List<String> ids;
}
// ========== 2. 会话 (Session) 相关 ==========
/**
* 创建会话请求
*/
@Data
@NoArgsConstructor
@AllArgsConstructor
@Builder
@Schema(description = "创建会话请求")
public static class SessionCreateReq implements Serializable {
@Schema(description = "会话名称", example = "技术咨询会话")
private String name;
@Schema(description = "用户 ID", example = "user_001")
@JsonProperty("user_id")
private String userId;
}
/**
* 更新会话请求
*/
@Data
@NoArgsConstructor
@AllArgsConstructor
@Builder
@Schema(description = "更新会话请求")
public static class SessionUpdateReq implements Serializable {
@Schema(description = "会话名称", example = "技术咨询会话 - 更新")
private String name;
}
/**
* 查询会话列表请求
*/
@Data
@NoArgsConstructor
@AllArgsConstructor
@Builder
@Schema(description = "查询会话列表请求")
public static class SessionListReq implements Serializable {
@Schema(description = "助手 ID", example = "assistant_001")
@JsonProperty("assistant_id")
private String assistantId;
@Schema(description = "页码 (从 1 开始)", example = "1")
private Integer page;
@Schema(description = "每页数量", example = "30")
@JsonProperty("page_size")
private Integer pageSize;
@Schema(description = "按名称过滤", example = "技术")
private String name;
@Schema(description = "排序字段", example = "create_time")
private String orderby;
@Schema(description = "是否降序", example = "true")
private Boolean desc;
@Schema(description = "会话 ID 精确筛选", example = "session_001")
private String id;
@Schema(description = "用户标识筛选", example = "user_001")
@JsonProperty("user_id")
private String userId;
}
/**
* 会话详情 VO
*/
@Data
@NoArgsConstructor
@AllArgsConstructor
@Builder
@Schema(description = "会话详情 VO")
public static class SessionVO implements Serializable {
@Schema(description = "会话 ID", example = "session_001")
private String id;
@Schema(description = "助手 ID", example = "assistant_001")
@JsonProperty("chat_id")
private String chatId;
@Schema(description = "助手 ID (兼容旧版)", example = "assistant_001")
@JsonProperty("assistant_id")
private String assistantId;
@Schema(description = "会话名称", example = "技术咨询会话")
private String name;
@Schema(description = "创建时间 (时间戳)", example = "1700000000000")
@JsonProperty("create_time")
private Long createTime;
@Schema(description = "更新时间 (时间戳)", example = "1700000001000")
@JsonProperty("update_time")
private Long updateTime;
@Schema(description = "创建日期", example = "2024-05-01 10:00:00")
@JsonProperty("create_date")
private String createDate;
@Schema(description = "更新日期", example = "2024-05-01 10:00:00")
@JsonProperty("update_date")
private String updateDate;
@Schema(description = "用户 ID", example = "user_001")
@JsonProperty("user_id")
private String userId;
@Schema(description = "对话历史消息列表")
private List<Map<String, Object>> messages;
}
/**
* 删除会话请求
*/
@Data
@NoArgsConstructor
@AllArgsConstructor
@Builder
@Schema(description = "删除会话请求")
public static class SessionDeleteReq implements Serializable {
@Schema(description = "要删除的会话 ID 列表", example = "[\"session_001\", \"session_002\"]")
private List<String> ids;
}
// ========== 3. 消息/对话 (Completion) 相关 ==========
/**
* 发送消息请求
*/
@Data
@NoArgsConstructor
@AllArgsConstructor
@Builder
@Schema(description = "发送消息请求")
public static class CompletionReq implements Serializable {
@NotBlank(message = "问题内容不能为空")
@Schema(description = "用户问题", requiredMode = Schema.RequiredMode.REQUIRED, example = "请介绍一下你们的产品")
private String question;
@Schema(description = "是否使用流式响应 (SSE)", example = "true")
@Builder.Default
private Boolean stream = true;
@NotBlank(message = "会话 ID 不能为空")
@Schema(description = "会话 ID (可选,不传则创建新会话)", example = "session_001")
@JsonProperty("session_id")
private String sessionId;
@Schema(description = "是否展示引用", example = "true")
private Boolean quote;
@Schema(description = "指定检索的文档 ID 列表 (逗号分隔)", example = "doc_001,doc_002")
@JsonProperty("doc_ids")
private String docIds;
@Schema(description = "元数据过滤条件")
@JsonProperty("metadata_condition")
private Map<String, Object> metadataCondition;
}
/**
* 消息响应 VO
*/
@Data
@NoArgsConstructor
@AllArgsConstructor
@Builder
@Schema(description = "消息响应 VO")
public static class CompletionVO implements Serializable {
@Schema(description = "AI 回答内容")
private String answer;
@Schema(description = "引用信息")
private Reference reference;
@Schema(description = "会话 ID", example = "session_001")
@JsonProperty("session_id")
private String sessionId;
@Schema(description = "任务 ID (用于流式响应追踪)", example = "task_001")
@JsonProperty("task_id")
private String taskId;
/**
* 引用信息 (检索命中结果)
*/
@Data
@NoArgsConstructor
@AllArgsConstructor
@Builder
@Schema(description = "引用信息")
public static class Reference implements Serializable {
@Schema(description = "命中的文档块列表")
private List<xiaozhi.modules.knowledge.dto.document.RetrievalDTO.HitVO> chunks;
@Schema(description = "文档聚合信息")
@JsonProperty("doc_aggs")
private List<DocAgg> docAggs;
}
/**
* 文档聚合信息
*/
@Data
@NoArgsConstructor
@AllArgsConstructor
@Builder
@Schema(description = "文档聚合信息")
public static class DocAgg implements Serializable {
@Schema(description = "文档 ID", example = "doc_001")
@JsonProperty("doc_id")
private String docId;
@Schema(description = "文档名称", example = "产品手册.pdf")
@JsonProperty("doc_name")
private String docName;
@Schema(description = "命中次数", example = "3")
private Integer count;
}
}
/**
* 简易知识库 VO (用于 Assistant 列表)
*/
@Data
@NoArgsConstructor
@AllArgsConstructor
@Builder
@Schema(description = "简易知识库 VO")
public static class SimpleDatasetVO implements Serializable {
@Schema(description = "知识库 ID")
private String id;
@Schema(description = "知识库名称")
private String name;
@Schema(description = "头像")
private String avatar;
@Schema(description = "分块数量")
@JsonProperty("chunk_num")
private Integer chunkNum;
}
}
@@ -0,0 +1,79 @@
package xiaozhi.modules.knowledge.dto.common;
import lombok.*;
import io.swagger.v3.oas.annotations.media.Schema;
import java.io.Serializable;
import java.util.List;
import java.util.Map;
import com.fasterxml.jackson.annotation.JsonProperty;
import jakarta.validation.constraints.*;
@Schema(description = "通用扩展功能 DTO")
public class CommonDTO {
// ========== 1. 引用详情 (detail_share_embedded) ==========
@Data
@Builder
@NoArgsConstructor
@AllArgsConstructor
@Schema(description = "引用详情请求")
public static class ReferenceDetailReq implements Serializable {
@Schema(description = "切片 ID", requiredMode = Schema.RequiredMode.REQUIRED)
@NotBlank(message = "切片 ID 不能为空")
@JsonProperty("chunk_id")
private String chunkId;
@Schema(description = "知识库 ID")
@JsonProperty("knowledge_id")
private String knowledgeId;
}
@Data
@Builder
@NoArgsConstructor
@AllArgsConstructor
@Schema(description = "引用详情响应")
public static class ReferenceDetailVO implements Serializable {
@Schema(description = "切片 ID")
@JsonProperty("chunk_id")
private String chunkId;
@Schema(description = "完整内容")
@JsonProperty("content_with_weight")
private String contentWithWeight;
@Schema(description = "文档名称")
@JsonProperty("doc_name")
private String docName;
@Schema(description = "图片 ID 列表")
@JsonProperty("img_id")
private String imageId; // 注意:RAGFlow 有时返回 String 有时返回 List,需根据实际情况确认,暂定 String 用于 ID
@Schema(description = "文档 ID")
@JsonProperty("doc_id")
private String docId;
}
// ========== 2. 通用问答 (ask_about) - 调试用 ==========
@Data
@Builder
@NoArgsConstructor
@AllArgsConstructor
@Schema(description = "通用问答请求 (调试用)")
public static class AskAboutReq implements Serializable {
@Schema(description = "用户问题", requiredMode = Schema.RequiredMode.REQUIRED, example = "What is this dataset about?")
@NotBlank(message = "问题不能为空")
@JsonProperty("question")
private String question;
@Schema(description = "数据集 ID 列表", requiredMode = Schema.RequiredMode.REQUIRED)
@NotEmpty(message = "数据集列表不能为空")
@JsonProperty("dataset_ids")
private List<String> datasetIds;
}
// 响应通常复用 String 或者简单的 Map 结构,视具体实现而定,暂不定义专用 VO
}
@@ -0,0 +1,449 @@
package xiaozhi.modules.knowledge.dto.dataset;
import lombok.*;
import io.swagger.v3.oas.annotations.media.Schema;
import java.io.Serializable;
import java.util.List;
import java.util.Map;
import com.fasterxml.jackson.annotation.JsonProperty;
import com.fasterxml.jackson.annotation.JsonIgnoreProperties;
import com.fasterxml.jackson.annotation.JsonInclude;
import jakarta.validation.constraints.*;
/**
* 知识库管理聚合 DTO
* <p>
* 容器类,内含知识库模块所有请求/响应对象的静态内部类定义。
* </p>
*/
@Schema(description = "知识库管理聚合 DTO")
@JsonIgnoreProperties(ignoreUnknown = true)
public class DatasetDTO {
// ========== 通用内部类 ==========
/**
* 解析器配置
*/
@Data
@NoArgsConstructor
@AllArgsConstructor
@Builder
@Schema(description = "解析器配置")
@JsonIgnoreProperties(ignoreUnknown = true)
public static class ParserConfig implements Serializable {
@Schema(description = "分块 token 数量", example = "128")
@JsonProperty("chunk_token_num")
private Integer chunkTokenNum;
@Schema(description = "分隔符", example = "\\n!?;。;!?")
private String delimiter;
@Schema(description = "布局识别模型: DeepDOC / Simple", example = "DeepDOC")
@JsonProperty("layout_recognize")
private String layoutRecognize;
@Schema(description = "是否将 Excel 转为 HTML", example = "false")
private Boolean html4excel;
@Schema(description = "自动生成关键词数量 (0 表示关闭)", example = "0")
@JsonProperty("auto_keywords")
private Integer autoKeywords;
@Schema(description = "自动生成问题数量 (0 表示关闭)", example = "0")
@JsonProperty("auto_questions")
private Integer autoQuestions;
}
// ========== 请求类 ==========
/**
* 创建知识库请求 (映射接口 1: create)
*/
@Data
@NoArgsConstructor
@AllArgsConstructor
@Builder
@Schema(description = "创建知识库请求")
@JsonIgnoreProperties(ignoreUnknown = true)
public static class CreateReq implements Serializable {
@NotBlank(message = "知识库名称不能为空")
@Schema(description = "知识库名称", requiredMode = Schema.RequiredMode.REQUIRED, example = "my_dataset")
private String name;
@Schema(description = "知识库头像 (Base64 编码)", example = "")
private String avatar;
@Schema(description = "知识库描述", example = "用于存储产品文档")
private String description;
@Schema(description = "嵌入模型名称", example = "BAAI/bge-large-zh-v1.5")
@JsonProperty("embedding_model")
private String embeddingModel;
@Schema(description = "权限设置: me / team", example = "me")
private String permission;
@Schema(description = "分块方法: naive / manual / qa / table / paper / book / laws / presentation / picture / one / knowledge_graph / email", example = "naive")
@JsonProperty("chunk_method")
private String chunkMethod;
@Schema(description = "解析器配置")
@JsonProperty("parser_config")
private ParserConfig parserConfig;
}
/**
* 更新知识库请求 (映射接口 4: update)
*/
@Data
@NoArgsConstructor
@AllArgsConstructor
@Builder
@Schema(description = "更新知识库请求")
@JsonIgnoreProperties(ignoreUnknown = true)
public static class UpdateReq implements Serializable {
@Schema(description = "知识库名称", example = "updated_dataset")
private String name;
@Schema(description = "知识库头像 (Base64 编码)", example = "")
private String avatar;
@Schema(description = "知识库描述", example = "更新后的描述")
private String description;
@Schema(description = "权限设置: me / team", example = "team")
private String permission;
@Schema(description = "嵌入模型名称", example = "BAAI/bge-large-zh-v1.5")
@JsonProperty("embedding_model")
private String embeddingModel;
@Schema(description = "分块方法: naive / manual / qa / table / paper / book / laws / presentation / picture / one / knowledge_graph / email", example = "naive")
@JsonProperty("chunk_method")
private String chunkMethod;
@Schema(description = "解析器配置")
@JsonProperty("parser_config")
private ParserConfig parserConfig;
@JsonInclude(JsonInclude.Include.NON_NULL)
@Schema(description = "PageRank 权重 (0-100)", example = "50")
private Integer pagerank;
}
/**
* 查询知识库列表请求 (映射接口 3: list_datasets)
*/
@Data
@NoArgsConstructor
@AllArgsConstructor
@Builder
@Schema(description = "查询知识库列表请求")
@JsonIgnoreProperties(ignoreUnknown = true)
public static class ListReq implements Serializable {
@Schema(description = "页码 (从 1 开始)", example = "1")
private Integer page;
@Schema(description = "每页数量", example = "30")
@JsonProperty("page_size")
private Integer pageSize;
@Schema(description = "排序字段: create_time / update_time", example = "create_time")
private String orderby;
@Schema(description = "是否降序", example = "true")
private Boolean desc;
@Schema(description = "按名称过滤 (模糊匹配)", example = "my_dataset")
private String name;
@Schema(description = "按知识库 ID 过滤", example = "abc123")
private String id;
}
/**
* 批量删除知识库请求 (映射接口 2: delete)
*/
@Data
@NoArgsConstructor
@AllArgsConstructor
@Builder
@Schema(description = "批量删除知识库请求")
public static class BatchIdReq implements Serializable {
@NotNull(message = "知识库 ID 列表不能为空")
@Size(min = 1, message = "至少需要一个知识库 ID")
@Schema(description = "知识库 ID 列表", requiredMode = Schema.RequiredMode.REQUIRED, example = "[\"id1\", \"id2\"]")
private List<String> ids;
}
/**
* 运行 GraphRAG 请求
*/
@Data
@NoArgsConstructor
@AllArgsConstructor
@Builder
@Schema(description = "运行 GraphRAG 请求")
public static class RunGraphRagReq implements Serializable {
@Schema(description = "实体类型列表", example = "[\"person\", \"organization\"]")
@JsonProperty("entity_types")
private List<String> entityTypes;
@Schema(description = "构建方法: light / fast / full", example = "light")
private String method;
}
/**
* 运行 RAPTOR 请求
*/
@Data
@NoArgsConstructor
@AllArgsConstructor
@Builder
@Schema(description = "运行 RAPTOR 请求")
public static class RunRaptorReq implements Serializable {
@Schema(description = "最大聚类数", example = "64")
@JsonProperty("max_cluster")
private Integer maxCluster;
@Schema(description = "自定义提示词", example = "请总结以下内容...")
private String prompt;
}
/**
* 异步任务 ID 响应 VO (映射接口 7/8: run_graphrag/run_raptor)
*/
@Data
@NoArgsConstructor
@AllArgsConstructor
@Builder
@Schema(description = "异步任务 ID 响应")
@JsonIgnoreProperties(ignoreUnknown = true)
public static class TaskIdVO implements Serializable {
@Schema(description = "GraphRAG 任务 ID", example = "task_uuid_12345678")
@JsonProperty("graphrag_task_id")
private String graphragTaskId;
@Schema(description = "RAPTOR 任务 ID", example = "task_uuid_87654321")
@JsonProperty("raptor_task_id")
private String raptorTaskId;
}
// ========== 响应类 ==========
/**
* 知识库详情 VO (映射接口 1/3 的返回数据项)
*/
@Data
@NoArgsConstructor
@AllArgsConstructor
@Builder
@Schema(description = "知识库详情 VO")
@JsonIgnoreProperties(ignoreUnknown = true)
public static class InfoVO implements Serializable {
@Schema(description = "知识库 ID", example = "abc123")
private String id;
@Schema(description = "知识库名称", example = "my_dataset")
private String name;
@Schema(description = "知识库头像 (Base64 编码)", example = "")
private String avatar;
@Schema(description = "租户 ID", example = "tenant_001")
@JsonProperty("tenant_id")
private String tenantId;
@Schema(description = "知识库描述", example = "用于存储产品文档")
private String description;
@Schema(description = "嵌入模型名称", example = "BAAI/bge-large-zh-v1.5")
@JsonProperty("embedding_model")
private String embeddingModel;
@Schema(description = "权限设置: me / team", example = "me")
private String permission;
@Schema(description = "分块方法", example = "naive")
@JsonProperty("chunk_method")
private String chunkMethod;
@Schema(description = "解析器配置")
@JsonProperty("parser_config")
private ParserConfig parserConfig;
@Schema(description = "分块总数", example = "1024")
@JsonProperty("chunk_count")
private Long chunkCount;
@Schema(description = "文档总数", example = "50")
@JsonProperty("document_count")
private Long documentCount;
@Schema(description = "创建时间 (时间戳)", example = "1700000000000")
@JsonProperty("create_time")
private Long createTime;
@Schema(description = "更新时间 (时间戳)", example = "1700000001000")
@JsonProperty("update_time")
private Long updateTime;
@Schema(description = "总 Token 数", example = "102400")
@JsonProperty("token_num")
private Long tokenNum;
@Schema(description = "创建日期 (格式: yyyy-MM-dd HH:mm:ss)")
@JsonProperty("create_date")
private String createDate;
@Schema(description = "最后更新日期 (格式: yyyy-MM-dd HH:mm:ss)")
@JsonProperty("update_date")
private String updateDate;
}
/**
* 批量操作响应 VO
*/
@Data
@NoArgsConstructor
@AllArgsConstructor
@Builder
@Schema(description = "批量操作响应 VO")
public static class BatchOperationVO implements Serializable {
@Schema(description = "成功操作数量", example = "5")
@JsonProperty("success_count")
private Integer successCount;
@Schema(description = "错误列表")
private List<Object> errors;
}
// ========== 知识图谱相关 ==========
/**
* 知识图谱数据 VO (映射接口 5: knowledge_graph)
*/
@Data
@NoArgsConstructor
@AllArgsConstructor
@Builder
@Schema(description = "知识图谱数据 VO")
public static class GraphVO implements Serializable {
@Schema(description = "图谱节点列表")
private List<Node> nodes;
@Schema(description = "图谱边列表")
private List<Edge> edges;
@Schema(description = "思维导图数据")
@JsonProperty("mind_map")
private Map<String, Object> mindMap;
/**
* 图谱节点
*/
@Data
@NoArgsConstructor
@AllArgsConstructor
@Builder
@Schema(description = "图谱节点")
@JsonIgnoreProperties(ignoreUnknown = true)
public static class Node implements Serializable {
@Schema(description = "节点 ID", example = "node_001")
private String id;
@Schema(description = "节点标签", example = "产品")
private String label;
@Schema(description = "PageRank 值", example = "0.85")
private Double pagerank;
@Schema(description = "节点颜色", example = "#FF5733")
private String color;
@Schema(description = "节点图片 URL", example = "https://example.com/icon.png")
private String img;
}
/**
* 图谱边
*/
@Data
@NoArgsConstructor
@AllArgsConstructor
@Builder
@Schema(description = "图谱边")
@JsonIgnoreProperties(ignoreUnknown = true)
public static class Edge implements Serializable {
@Schema(description = "源节点 ID", example = "node_001")
private String source;
@Schema(description = "目标节点 ID", example = "node_002")
private String target;
@Schema(description = "边权重", example = "0.75")
private Double weight;
@Schema(description = "边标签 (关系描述)", example = "属于")
private String label;
}
}
// ========== 异步任务追踪 (GraphRAG/RAPTOR) ==========
/**
* 异步任务追踪 VO (映射接口 9/10: 任务进度返回)
*/
@Data
@NoArgsConstructor
@AllArgsConstructor
@Builder
@Schema(description = "异步任务追踪 VO")
@JsonIgnoreProperties(ignoreUnknown = true)
public static class TaskTraceVO implements Serializable {
@Schema(description = "任务 ID", example = "task_001")
private String id;
@Schema(description = "文档 ID", example = "doc_001")
@JsonProperty("doc_id")
private String docId;
@Schema(description = "起始页码", example = "1")
@JsonProperty("from_page")
private Integer fromPage;
@Schema(description = "结束页码", example = "10")
@JsonProperty("to_page")
private Integer toPage;
@Schema(description = "进度百分比 (0.0 - 1.0)", example = "0.75")
private Double progress;
@Schema(description = "进度消息", example = "正在处理第 5 页...")
@JsonProperty("progress_msg")
private String progressMsg;
@Schema(description = "创建时间 (时间戳)", example = "1700000000000")
@JsonProperty("create_time")
private Long createTime;
@Schema(description = "更新时间 (时间戳)", example = "1700000001000")
@JsonProperty("update_time")
private Long updateTime;
}
}
@@ -0,0 +1,182 @@
package xiaozhi.modules.knowledge.dto.document;
import lombok.*;
import io.swagger.v3.oas.annotations.media.Schema;
import java.io.Serializable;
import java.util.List;
import com.fasterxml.jackson.annotation.JsonProperty;
import com.fasterxml.jackson.annotation.JsonIgnoreProperties;
import jakarta.validation.constraints.*;
/**
* 切片管理聚合 DTO
*/
@Schema(description = "切片管理聚合 DTO")
@JsonIgnoreProperties(ignoreUnknown = true)
public class ChunkDTO {
/**
* 新增切片请求参数
*/
@Data
@Builder
@NoArgsConstructor
@AllArgsConstructor
@Schema(description = "新增切片请求参数")
@JsonIgnoreProperties(ignoreUnknown = true)
public static class AddReq implements Serializable {
private static final long serialVersionUID = 1L;
@Schema(description = "切片内容", requiredMode = Schema.RequiredMode.REQUIRED)
@NotBlank(message = "切片内容不能为空")
private String content;
@Schema(description = "重要关键词列表")
@JsonProperty("important_keywords")
private List<String> importantKeywords;
@Schema(description = "预设问题列表")
private List<String> questions;
}
/**
* 更新切片请求参数
*/
@Data
@Builder
@NoArgsConstructor
@AllArgsConstructor
@Schema(description = "更新切片请求参数")
@JsonIgnoreProperties(ignoreUnknown = true)
public static class UpdateReq implements Serializable {
private static final long serialVersionUID = 1L;
@Schema(description = "新的切片内容")
private String content;
@Schema(description = "更新关键词列表 (覆盖原有列表)")
@JsonProperty("important_keywords")
private List<String> importantKeywords;
@Schema(description = "启用/禁用 (true: 启用, false: 禁用)")
private Boolean available;
}
/**
* 获取切片列表请求参数
*/
@Data
@Builder
@NoArgsConstructor
@AllArgsConstructor
@Schema(description = "获取切片列表请求参数")
@JsonIgnoreProperties(ignoreUnknown = true)
public static class ListReq implements Serializable {
private static final long serialVersionUID = 1L;
@Schema(description = "页码 (默认 1)")
private Integer page;
@Schema(description = "每页数量 (默认 30)")
@JsonProperty("page_size")
private Integer pageSize;
@Schema(description = "搜索关键词 (全文检索)")
private String keywords;
@Schema(description = "精确切片 ID")
private String id;
}
/**
* 批量删除切片请求参数
*/
@Data
@Builder
@NoArgsConstructor
@AllArgsConstructor
@Schema(description = "批量删除切片请求参数")
@JsonIgnoreProperties(ignoreUnknown = true)
public static class RemoveReq implements Serializable {
private static final long serialVersionUID = 1L;
@Schema(description = "切片 ID 列表", requiredMode = Schema.RequiredMode.REQUIRED)
@JsonProperty("chunk_ids")
@NotEmpty(message = "切片ID列表不能为空")
private List<String> chunkIds;
}
/**
* 文档切片信息 VO
*/
@Data
@Builder
@NoArgsConstructor
@AllArgsConstructor
@Schema(description = "文档切片信息")
@JsonIgnoreProperties(ignoreUnknown = true)
public static class InfoVO implements Serializable {
private static final long serialVersionUID = 1L;
@Schema(description = "切片 ID (通常为 document_id + 索引)", requiredMode = Schema.RequiredMode.REQUIRED)
private String id;
@Schema(description = "切片文本内容 (全文检索的主要对象)", requiredMode = Schema.RequiredMode.REQUIRED)
private String content;
@Schema(description = "所属文档 ID", requiredMode = Schema.RequiredMode.REQUIRED)
@JsonProperty("document_id")
private String documentId;
@Schema(description = "文档名称 / 关键词")
@JsonProperty("docnm_kwd")
private String docnmKwd;
@Schema(description = "重要关键词列表 (用于关键词增强检索)")
@JsonProperty("important_keywords")
private List<String> importantKeywords;
@Schema(description = "预设问题列表 (用于 Q&A 模式增强)")
private List<String> questions;
@Schema(description = "关联的图片 ID")
@JsonProperty("image_id")
private String imageId;
@Schema(description = "所属知识库 ID")
@JsonProperty("dataset_id")
private String datasetId;
@Schema(description = "切片是否可用 (true: 参与检索, false: 被禁用)")
private Boolean available;
@Schema(description = "切片在原文中的位置索引列表 (RAGFlow返回嵌套数组, 如 [[start, end, filename]])")
private List<List<Object>> positions;
@Schema(description = "Token ID 列表")
@JsonProperty("token")
private List<Integer> token;
}
/**
* 分片列表聚合响应
*/
@Data
@Builder
@NoArgsConstructor
@AllArgsConstructor
@Schema(description = "分片列表聚合响应")
@JsonIgnoreProperties(ignoreUnknown = true)
public static class ListVO implements Serializable {
private static final long serialVersionUID = 1L;
@Schema(description = "切片信息列表")
private List<InfoVO> chunks;
@Schema(description = "关联的文档详细信息")
private DocumentDTO.InfoVO doc;
@Schema(description = "总记录数")
private Long total;
}
}
@@ -0,0 +1,407 @@
package xiaozhi.modules.knowledge.dto.document;
import lombok.*;
import io.swagger.v3.oas.annotations.media.Schema;
import java.io.Serializable;
import java.util.List;
import java.util.Map;
import com.fasterxml.jackson.annotation.JsonProperty;
import com.fasterxml.jackson.annotation.JsonAlias;
import com.fasterxml.jackson.annotation.JsonIgnoreProperties;
import jakarta.validation.constraints.*;
/**
* 文档管理聚合 DTO
*/
@Schema(description = "文档管理聚合 DTO")
@JsonIgnoreProperties(ignoreUnknown = true)
public class DocumentDTO {
/**
* 上传文档请求参数
*/
@Data
@Builder
@NoArgsConstructor
@AllArgsConstructor
@Schema(description = "上传文档请求参数")
@JsonIgnoreProperties(ignoreUnknown = true)
public static class UploadReq implements Serializable {
private static final long serialVersionUID = 1L;
@Schema(description = "知识库 ID (必须指定归属)", requiredMode = Schema.RequiredMode.REQUIRED)
@JsonProperty("dataset_id")
@NotBlank(message = "知识库ID不能为空")
private String datasetId;
@Schema(description = "文件名 (如果指定,则覆盖原始文件名)")
private String name;
@Schema(description = "分块方法")
@JsonProperty("chunk_method")
private DocumentDTO.InfoVO.ChunkMethod chunkMethod;
@Schema(description = "解析参数配置")
@JsonProperty("parser_config")
private DocumentDTO.InfoVO.ParserConfig parserConfig;
@Schema(description = "虚拟文件夹路径 (默认为 /)")
@JsonProperty("parent_path")
private String parentPath;
@Schema(description = "元数据字段")
@JsonProperty("meta")
private Map<String, Object> metaFields;
@Schema(description = "文件二进制流 (支持 PDF, DOCX, TXT, MD 等多种格式)", requiredMode = Schema.RequiredMode.REQUIRED)
@NotNull(message = "上传文件不能为空")
private org.springframework.web.multipart.MultipartFile file;
}
/**
* 更新文档请求参数
*/
@Data
@Builder
@NoArgsConstructor
@AllArgsConstructor
@Schema(description = "更新文档请求参数")
@JsonIgnoreProperties(ignoreUnknown = true)
public static class UpdateReq implements Serializable {
private static final long serialVersionUID = 1L;
@Schema(description = "新文档名称 (必须包含文件后缀,且不能更改原始类型)")
private String name;
@Schema(description = "启用/禁用状态 (true: 启用, false: 禁用; 禁用后不参与检索)")
private Boolean enabled;
@Schema(description = "新解析方法 (修改此项会重置解析状态)")
@JsonProperty("chunk_method")
private InfoVO.ChunkMethod chunkMethod;
@Schema(description = "新解析器详细配置 (应与 chunk_method 配套使用)")
@JsonProperty("parser_config")
private InfoVO.ParserConfig parserConfig;
}
/**
* 获取文档列表请求参数
*/
@Data
@Builder
@NoArgsConstructor
@AllArgsConstructor
@Schema(description = "获取文档列表请求参数")
@JsonIgnoreProperties(ignoreUnknown = true)
public static class ListReq implements Serializable {
private static final long serialVersionUID = 1L;
@Schema(description = "页码 (默认: 1)")
private Integer page;
@Schema(description = "每页数量 (默认: 30)")
@JsonProperty("page_size")
private Integer pageSize;
@Schema(description = "排序字段 (可选: create_time, name, size; 默认: create_time)")
private String orderby;
@Schema(description = "是否降序排列 (true: 最新/最大在前; false: 最旧/最小在前; 默认: true)")
private Boolean desc;
@Schema(description = "精确筛选: 文档 ID")
private String id;
@Schema(description = "精确筛选: 文档完整名称 (含后缀)")
private String name;
@Schema(description = "模糊搜索: 文档名称关键词")
private String keywords;
@Schema(description = "筛选: 文件后缀列表 (如 ['pdf', 'docx'])")
private List<String> suffix;
@Schema(description = "筛选: 运行状态列表")
private List<InfoVO.RunStatus> run;
@Schema(description = "筛选: 起始创建时间 (时间戳, 毫秒)")
@JsonProperty("create_time_from")
private Long createTimeFrom;
@Schema(description = "筛选: 结束创建时间 (时间戳, 毫秒)")
@JsonProperty("create_time_to")
private Long createTimeTo;
}
/**
* 批量文档操作请求参数 (用于删除、解析等)
*/
@Data
@Builder
@NoArgsConstructor
@AllArgsConstructor
@Schema(description = "批量文档操作请求参数")
@JsonIgnoreProperties(ignoreUnknown = true)
public static class BatchIdReq implements Serializable {
private static final long serialVersionUID = 1L;
@Schema(description = "文档 ID 列表", requiredMode = Schema.RequiredMode.REQUIRED)
@JsonProperty("ids") // 为了兼容性,也可以考虑支持 document_ids,但这里统一叫 ids
@JsonAlias("document_ids")
@NotEmpty(message = "文档ID列表不能为空")
private List<String> ids;
}
/**
* 知识库文档信息 VO
*/
@Data
@Builder
@NoArgsConstructor
@AllArgsConstructor
@Schema(description = "知识库文档信息")
@JsonIgnoreProperties(ignoreUnknown = true)
public static class InfoVO implements Serializable {
private static final long serialVersionUID = 1L;
@Schema(description = "文档 ID (唯一标识)", requiredMode = Schema.RequiredMode.REQUIRED)
private String id;
@Schema(description = "文档缩略图 URL (Base64 或 链接)")
private String thumbnail;
@Schema(description = "所属知识库 ID", requiredMode = Schema.RequiredMode.REQUIRED)
@JsonProperty("dataset_id")
private String datasetId;
@Schema(description = "文档解析方法 (决定了文档如何被切片)")
@JsonProperty("chunk_method")
private ChunkMethod chunkMethod;
@Schema(description = "关联的 ETL Pipeline ID (如有)")
@JsonProperty("pipeline_id")
private String pipelineId;
@Schema(description = "文档解析器的详细配置")
@JsonProperty("parser_config")
private ParserConfig parserConfig;
@Schema(description = "来源类型 (如 local, s3, url 等)")
@JsonProperty("source_type")
private String sourceType;
@Schema(description = "文档文件类型 (如 pdf, docx, txt)", requiredMode = Schema.RequiredMode.REQUIRED)
private String type;
@Schema(description = "创建者用户 ID")
@JsonProperty("created_by")
private String createdBy;
@Schema(description = "文档名称 (包含扩展名)", requiredMode = Schema.RequiredMode.REQUIRED)
private String name;
@Schema(description = "文件存储路径或位置标识")
private String location;
@Schema(description = "文件大小 (单位: Bytes)")
private Long size;
@Schema(description = "包含的 Token 总数 (解析后统计)")
@JsonProperty("token_count")
private Long tokenCount;
@Schema(description = "包含的切片 (Chunk) 总数")
@JsonProperty("chunk_count")
private Long chunkCount;
@Schema(description = "解析进度 (0.0 ~ 1.0, 1.0 表示完成)")
private Double progress;
@Schema(description = "当前进度描述或错误信息")
@JsonProperty("progress_msg")
private String progressMsg;
@Schema(description = "开始处理的时间戳 (RAGFlow返回RFC1123格式)")
@JsonProperty("process_begin_at")
private String processBeginAt;
@Schema(description = "处理总耗时 (单位: 秒)")
@JsonProperty("process_duration")
private Double processDuration;
@Schema(description = "自定义元数据字段 (Key-Value 键值对)")
@JsonProperty("meta_fields")
private Map<String, Object> metaFields;
@Schema(description = "文件后缀名 (不含点)")
private String suffix;
@Schema(description = "文档解析运行状态")
private RunStatus run;
@Schema(description = "文档可用状态 (1: 启用/正常, 0: 禁用/失效)", requiredMode = Schema.RequiredMode.REQUIRED)
private String status;
@Schema(description = "创建时间 (时间戳, 毫秒)", requiredMode = Schema.RequiredMode.REQUIRED)
@JsonProperty("create_time")
private Long createTime;
@Schema(description = "创建日期 (RAGFlow返回RFC1123格式)")
@JsonProperty("create_date")
private String createDate;
@Schema(description = "最后更新时间 (时间戳, 毫秒)")
@JsonProperty("update_time")
private Long updateTime;
@Schema(description = "最后更新日期 (RAGFlow返回RFC1123格式)")
@JsonProperty("update_date")
private String updateDate;
/**
* 解析方法枚举 (ChunkMethod)
*/
public enum ChunkMethod {
@Schema(description = "通用模式: 适用于大多数纯文本或混合文档")
@JsonProperty("naive")
NAIVE,
@Schema(description = "手动模式: 允许用户手动编辑切片")
@JsonProperty("manual")
MANUAL,
@Schema(description = "问答模式: 专门优化 Q&A 格式的文档")
@JsonProperty("qa")
QA,
@Schema(description = "表格模式: 专门优化 Excel 或 CSV 等表格数据")
@JsonProperty("table")
TABLE,
@Schema(description = "论文模式: 针对学术论文排版优化")
@JsonProperty("paper")
PAPER,
@Schema(description = "书籍模式: 针对书籍章节结构优化")
@JsonProperty("book")
BOOK,
@Schema(description = "法律法规模式: 针对法律条文结构优化")
@JsonProperty("laws")
LAWS,
@Schema(description = "演示文稿模式: 针对 PPT 等演示文件优化")
@JsonProperty("presentation")
PRESENTATION,
@Schema(description = "图片模式: 针对图片内容进行 OCR 和描述")
@JsonProperty("picture")
PICTURE,
@Schema(description = "整体模式: 将整个文档作为一个切片")
@JsonProperty("one")
ONE,
@Schema(description = "知识图谱模式: 提取实体关系构建图谱")
@JsonProperty("knowledge_graph")
KNOWLEDGE_GRAPH,
@Schema(description = "邮件模式: 针对邮件格式优化")
@JsonProperty("email")
EMAIL;
}
/**
* 运行状态枚举 (RunStatus)
*/
public enum RunStatus {
@Schema(description = "未开始: 等待解析队列")
@JsonProperty("UNSTART")
UNSTART,
@Schema(description = "进行中: 正在解析或索引")
@JsonProperty("RUNNING")
RUNNING,
@Schema(description = "已取消: 用户手动取消")
@JsonProperty("CANCEL")
CANCEL,
@Schema(description = "已完成: 解析成功")
@JsonProperty("DONE")
DONE,
@Schema(description = "失败: 解析过程中出错")
@JsonProperty("FAIL")
FAIL;
}
/**
* 布局识别模型枚举
*/
public enum LayoutRecognize {
@Schema(description = "深度文档理解模型: 适合复杂排版")
@JsonProperty("DeepDOC")
DeepDOC,
@Schema(description = "简单规则模型: 适合纯文本")
@JsonProperty("Simple")
Simple;
}
@Data
@Builder
@NoArgsConstructor
@AllArgsConstructor
@Schema(description = "文档解析器参数配置")
@JsonIgnoreProperties(ignoreUnknown = true)
public static class ParserConfig implements Serializable {
private static final long serialVersionUID = 1L;
@Schema(description = "切片最大 Token 数 (建议值: 512, 1024, 2048)")
@JsonProperty("chunk_token_num")
private Integer chunkTokenNum;
@Schema(description = "分段分隔符 (支持转义字符, 如 \\n)")
private String delimiter;
@Schema(description = "布局识别模型 (DeepDOC/Simple)")
@JsonProperty("layout_recognize")
private LayoutRecognize layoutRecognize;
@Schema(description = "是否将 Excel 转换为 HTML 表格")
@JsonProperty("html4excel")
private Boolean html4excel;
@Schema(description = "自动提取关键词数量 (0 表示不提取)")
@JsonProperty("auto_keywords")
private Integer autoKeywords;
@Schema(description = "自动生成问题数量 (0 表示不生成)")
@JsonProperty("auto_questions")
private Integer autoQuestions;
@Schema(description = "自动生成标签数量")
@JsonProperty("topn_tags")
private Integer topnTags;
@Schema(description = "RAPTOR 高级索引配置")
private RaptorConfig raptor;
@Schema(description = "GraphRAG 知识图谱配置")
@JsonProperty("graphrag")
private GraphRagConfig graphRag;
@Data
@Builder
@NoArgsConstructor
@AllArgsConstructor
@Schema(description = "RAPTOR (递归摘要索引) 配置")
@JsonIgnoreProperties(ignoreUnknown = true)
public static class RaptorConfig implements Serializable {
private static final long serialVersionUID = 1L;
@Schema(description = "是否启用 RAPTOR 索引")
@JsonProperty("use_raptor")
private Boolean useRaptor;
}
@Data
@Builder
@NoArgsConstructor
@AllArgsConstructor
@Schema(description = "GraphRAG (图增强检索) 配置")
@JsonIgnoreProperties(ignoreUnknown = true)
public static class GraphRagConfig implements Serializable {
private static final long serialVersionUID = 1L;
@Schema(description = "是否启用 GraphRAG 索引")
@JsonProperty("use_graphrag")
private Boolean useGraphRag;
}
}
}
}
@@ -0,0 +1,307 @@
package xiaozhi.modules.knowledge.dto.document;
import lombok.*;
import io.swagger.v3.oas.annotations.media.Schema;
import java.io.Serializable;
import java.util.List;
import java.util.Map;
import com.fasterxml.jackson.annotation.JsonProperty;
import com.fasterxml.jackson.annotation.JsonInclude;
import com.fasterxml.jackson.annotation.JsonIgnoreProperties;
import jakarta.validation.constraints.*;
/**
* 检索与元数据管理聚合 DTO
*/
@Schema(description = "检索与元数据管理聚合 DTO")
@JsonIgnoreProperties(ignoreUnknown = true)
public class RetrievalDTO {
/**
* 文档聚合信息 (VO)
*/
@Data
@Builder
@NoArgsConstructor
@AllArgsConstructor
@Schema(description = "文档聚合信息")
@JsonIgnoreProperties(ignoreUnknown = true)
public static class DocAggVO implements Serializable {
private static final long serialVersionUID = 1L;
@Schema(description = "文档名称")
@JsonProperty("doc_name")
private String docName;
@Schema(description = "文档 ID")
@JsonProperty("doc_id")
private String docId;
@Schema(description = "数量")
private Integer count;
}
/**
* 检索测试请求参数
*/
@Data
@Builder
@NoArgsConstructor
@AllArgsConstructor
@Schema(description = "检索测试请求参数")
@JsonIgnoreProperties(ignoreUnknown = true)
@JsonInclude(JsonInclude.Include.NON_NULL)
public static class TestReq implements Serializable {
private static final long serialVersionUID = 1L;
@Schema(description = "知识库 ID 列表", requiredMode = Schema.RequiredMode.REQUIRED)
@JsonProperty("dataset_ids")
@NotEmpty(message = "知识库ID列表不能为空")
private List<String> datasetIds;
@Schema(description = "文档 ID 列表 (可选,用于限定检索范围)")
@JsonProperty("document_ids")
private List<String> documentIds;
@Schema(description = "检索问题", requiredMode = Schema.RequiredMode.REQUIRED)
@NotBlank(message = "检索问题不能为空")
private String question;
@Schema(description = "页码 (默认 1)")
private Integer page;
@Schema(description = "每页数量 (默认 10)")
@JsonProperty("page_size")
private Integer pageSize;
@Schema(description = "相似度阈值 (默认 0.2)")
@JsonProperty("similarity_threshold")
private Float similarityThreshold;
@Schema(description = "向量相似度权重 (默认 0.3)")
@JsonProperty("vector_similarity_weight")
private Float vectorSimilarityWeight;
@Schema(description = "返回 Top K 切片 (默认 1024)")
@JsonProperty("top_k")
private Integer topK;
@Schema(description = "重排序模型 ID")
@JsonProperty("rerank_id")
private String rerankId;
@Schema(description = "是否高亮关键词")
private Boolean highlight;
@Schema(description = "是否启用关键词检索")
private Boolean keyword;
@Schema(description = "跨语言翻译列表 (可选)")
@JsonProperty("cross_languages")
private List<String> crossLanguages;
@Schema(description = "元数据过滤条件 (JSON 对象)")
@JsonProperty("metadata_condition")
private Map<String, Object> metadataCondition;
}
/**
* 检索命中结果 (VO)
*/
@Data
@Builder
@NoArgsConstructor
@AllArgsConstructor
@Schema(description = "检索命中切片详情")
@JsonIgnoreProperties(ignoreUnknown = true)
public static class HitVO implements Serializable {
private static final long serialVersionUID = 1L;
@Schema(description = "切片 ID", requiredMode = Schema.RequiredMode.REQUIRED)
private String id;
@Schema(description = "切片内容", requiredMode = Schema.RequiredMode.REQUIRED)
private String content;
@Schema(description = "所属文档 ID", requiredMode = Schema.RequiredMode.REQUIRED)
@JsonProperty("document_id")
private String documentId;
@Schema(description = "所属知识库 ID")
@JsonProperty("dataset_id")
private String datasetId;
@Schema(description = "文档名称")
@JsonProperty("document_name")
private String documentName;
@Schema(description = "文档关键词")
@JsonProperty("document_keyword")
private String documentKeyword;
@Schema(description = "综合相似度", requiredMode = Schema.RequiredMode.REQUIRED)
private Float similarity;
@Schema(description = "向量相似度")
@JsonProperty("vector_similarity")
private Float vectorSimilarity;
@Schema(description = "关键词相似度")
@JsonProperty("term_similarity")
private Float termSimilarity;
@Schema(description = "索引位置")
private Integer index;
@Schema(description = "高亮内容")
private String highlight;
@Schema(description = "重要关键词列表")
@JsonProperty("important_keywords")
private List<String> importantKeywords;
@Schema(description = "预设问题列表")
private List<String> questions;
@Schema(description = "图片 ID")
@JsonProperty("image_id")
private String imageId;
@Schema(description = "位置索引 (RAGFlow返回嵌套数组, 如 [[start, end, filename]])")
private Object positions;
}
/**
* 知识库元数据摘要 (VO)
*/
@Data
@Builder
@NoArgsConstructor
@AllArgsConstructor
@Schema(description = "知识库元数据摘要信息")
@JsonIgnoreProperties(ignoreUnknown = true)
public static class MetaSummaryVO implements Serializable {
private static final long serialVersionUID = 1L;
@Schema(description = "文档总数", requiredMode = Schema.RequiredMode.REQUIRED)
@JsonProperty("total_doc_count")
private Long totalDocCount;
@Schema(description = "Token 总数", requiredMode = Schema.RequiredMode.REQUIRED)
@JsonProperty("total_token_count")
private Long totalTokenCount;
@Schema(description = "文件类型分布 (key: 文件后缀, value: 数量)")
@JsonProperty("file_type_distribution")
private Map<String, Long> fileTypeDistribution;
@Schema(description = "文状态分布 (key: 状态码, value: 数量)")
@JsonProperty("status_distribution")
private Map<String, Long> statusDistribution;
@Schema(description = "自定义元数据统计 (key: 字段名, value: 数量/值)")
@JsonProperty("custom_metadata")
private Map<String, Object> customMetadata;
}
/**
* 批量更新元数据请求参数
*/
@Data
@Builder
@NoArgsConstructor
@AllArgsConstructor
@Schema(description = "批量更新元数据请求参数")
@JsonIgnoreProperties(ignoreUnknown = true)
public static class MetaBatchReq implements Serializable {
private static final long serialVersionUID = 1L;
@Schema(description = "筛选器: 用于指定要更新的文档范围 (默认全部)")
private Selector selector;
@Schema(description = "新增或更新的元数据列表")
private List<UpdateItem> updates;
@Schema(description = "需要删除的元数据键列表")
private List<DeleteItem> deletes;
/**
* 文档筛选器
*/
@Data
@Builder
@NoArgsConstructor
@AllArgsConstructor
@Schema(description = "元数据更新筛选器")
@JsonIgnoreProperties(ignoreUnknown = true)
public static class Selector implements Serializable {
private static final long serialVersionUID = 1L;
@Schema(description = "指定文档 ID 列表")
@JsonProperty("document_ids")
private List<String> documentIds;
@Schema(description = "元数据条件匹配 (key: 字段名, value: 匹配值)")
@JsonProperty("metadata_condition")
private Map<String, Object> metadataCondition;
}
/**
* 更新项
*/
@Data
@Builder
@NoArgsConstructor
@AllArgsConstructor
@Schema(description = "元数据更新项")
@JsonIgnoreProperties(ignoreUnknown = true)
public static class UpdateItem implements Serializable {
private static final long serialVersionUID = 1L;
@Schema(description = "元数据键名", requiredMode = Schema.RequiredMode.REQUIRED)
private String key;
@Schema(description = "元数据值", requiredMode = Schema.RequiredMode.REQUIRED)
private Object value;
}
/**
* 删除项
*/
@Data
@Builder
@NoArgsConstructor
@AllArgsConstructor
@Schema(description = "元数据删除项")
@JsonIgnoreProperties(ignoreUnknown = true)
public static class DeleteItem implements Serializable {
private static final long serialVersionUID = 1L;
@Schema(description = "需删除的元数据键名", requiredMode = Schema.RequiredMode.REQUIRED)
private String key;
}
}
/**
* 召回测试结果聚合响应
*/
@Data
@Builder
@NoArgsConstructor
@AllArgsConstructor
@Schema(description = "召回测试结果聚合响应")
@JsonIgnoreProperties(ignoreUnknown = true)
public static class ResultVO implements Serializable {
private static final long serialVersionUID = 1L;
@Schema(description = "检索命中的切片列表")
private List<HitVO> chunks;
@Schema(description = "文档分布统计")
@JsonProperty("doc_aggs")
private List<DocAggVO> docAggs;
@Schema(description = "总命中记录数")
private Long total;
}
}
@@ -0,0 +1,363 @@
package xiaozhi.modules.knowledge.dto.file;
import lombok.*;
import io.swagger.v3.oas.annotations.media.Schema;
import java.io.Serializable;
import java.util.List;
import com.fasterxml.jackson.annotation.JsonProperty;
import jakarta.validation.constraints.*;
import org.springframework.web.multipart.MultipartFile;
/**
* 文件管理聚合 DTO
* <p>
* 容器类,内含文件模块所有请求/响应对象的静态内部类定义。
* </p>
*/
@Schema(description = "文件管理聚合 DTO")
public class FileDTO {
// ========== 请求类 ==========
/**
* 文件上传请求 (对应接口 1: upload)
*/
@Data
@NoArgsConstructor
@AllArgsConstructor
@Builder
@Schema(description = "文件上传请求")
public static class UploadReq implements Serializable {
@NotNull(message = "文件不能为空")
@Schema(description = "上传的文件", requiredMode = Schema.RequiredMode.REQUIRED)
private MultipartFile file;
@Schema(description = "父文件夹 ID (为空则上传到根目录)", example = "folder_001")
@JsonProperty("parent_id")
private String parentId;
}
/**
* 新建文件夹请求 (对应接口 2: create)
*/
@Data
@NoArgsConstructor
@AllArgsConstructor
@Builder
@Schema(description = "新建文件夹请求")
public static class CreateReq implements Serializable {
@NotBlank(message = "文件夹名称不能为空")
@Schema(description = "文件夹名称", requiredMode = Schema.RequiredMode.REQUIRED, example = "新建文件夹")
private String name;
@Schema(description = "父文件夹 ID (为空则创建在根目录)", example = "folder_001")
@JsonProperty("parent_id")
private String parentId;
@NotBlank(message = "类型不能为空")
@Schema(description = "类型: FOLDER", requiredMode = Schema.RequiredMode.REQUIRED, example = "FOLDER")
@Builder.Default
private String type = "FOLDER";
}
/**
* 重命名请求 (对应接口 6: rename)
*/
@Data
@NoArgsConstructor
@AllArgsConstructor
@Builder
@Schema(description = "重命名请求")
public static class RenameReq implements Serializable {
@NotBlank(message = "文件 ID 不能为空")
@Schema(description = "文件/文件夹 ID", requiredMode = Schema.RequiredMode.REQUIRED, example = "file_001")
@JsonProperty("file_id")
private String fileId;
@NotBlank(message = "新名称不能为空")
@Schema(description = "新名称", requiredMode = Schema.RequiredMode.REQUIRED, example = "重命名后的文件")
private String name;
}
/**
* 移动请求 (对应接口 7: move)
*/
@Data
@NoArgsConstructor
@AllArgsConstructor
@Builder
@Schema(description = "移动请求")
public static class MoveReq implements Serializable {
@NotEmpty(message = "源文件 ID 列表不能为空")
@Schema(description = "源文件/文件夹 ID 列表", requiredMode = Schema.RequiredMode.REQUIRED, example = "[\"file_001\", \"file_002\"]")
@JsonProperty("src_file_ids")
private List<String> srcFileIds;
@NotBlank(message = "目标文件夹 ID 不能为空")
@Schema(description = "目标文件夹 ID", requiredMode = Schema.RequiredMode.REQUIRED, example = "folder_002")
@JsonProperty("dest_file_id")
private String destFileId;
}
/**
* 批量删除请求 (对应接口 8: rm)
*/
@Data
@NoArgsConstructor
@AllArgsConstructor
@Builder
@Schema(description = "批量删除请求")
public static class RemoveReq implements Serializable {
@NotEmpty(message = "文件 ID 列表不能为空")
@Schema(description = "文件/文件夹 ID 列表", requiredMode = Schema.RequiredMode.REQUIRED, example = "[\"file_001\", \"file_002\"]")
@JsonProperty("file_ids")
private List<String> fileIds;
}
/**
* 导入知识库请求 (对应接口 9: convert)
*/
@Data
@NoArgsConstructor
@AllArgsConstructor
@Builder
@Schema(description = "导入知识库请求")
public static class ConvertReq implements Serializable {
@NotEmpty(message = "文件 ID 列表不能为空")
@Schema(description = "文件 ID 列表", requiredMode = Schema.RequiredMode.REQUIRED, example = "[\"file_001\", \"file_002\"]")
@JsonProperty("file_ids")
private List<String> fileIds;
@NotEmpty(message = "知识库 ID 列表不能为空")
@Schema(description = "目标知识库 ID 列表", requiredMode = Schema.RequiredMode.REQUIRED, example = "[\"kb_001\"]")
@JsonProperty("kb_ids")
private List<String> kbIds;
}
/**
* 列表查询请求 (对应接口 3: list_files)
*/
@Data
@NoArgsConstructor
@AllArgsConstructor
@Builder
@Schema(description = "列表查询请求")
public static class ListReq implements Serializable {
@Schema(description = "父文件夹 ID (为空则查询根目录)", example = "folder_001")
@JsonProperty("parent_id")
private String parentId;
@Schema(description = "关键词搜索", example = "文档")
private String keywords;
@Schema(description = "页码 (从 1 开始)", example = "1")
private Integer page;
@Schema(description = "每页数量", example = "30")
@JsonProperty("page_size")
private Integer pageSize;
@Schema(description = "排序字段: create_time / update_time / name / size", example = "create_time")
private String orderby;
@Schema(description = "是否降序", example = "true")
private Boolean desc;
}
// ========== 响应类 ==========
/**
* 文件/文件夹基础信息 VO
*/
@Data
@NoArgsConstructor
@AllArgsConstructor
@Builder
@Schema(description = "文件/文件夹基础信息")
public static class InfoVO implements Serializable {
@Schema(description = "文件/文件夹 ID", example = "file_001")
private String id;
@Schema(description = "父文件夹 ID", example = "folder_001")
@JsonProperty("parent_id")
private String parentId;
@Schema(description = "租户 ID", example = "tenant_001")
@JsonProperty("tenant_id")
private String tenantId;
@Schema(description = "创建者 ID", example = "user_001")
@JsonProperty("created_by")
private String createdBy;
@Schema(description = "类型: FOLDER / FILE", example = "FOLDER")
private String type;
@Schema(description = "名称", example = "我的文件夹")
private String name;
@Schema(description = "路径位置", example = "/root/folder")
private String location;
@Schema(description = "文件大小 (字节)", example = "1024")
private Long size;
@Schema(description = "来源类型", example = "local")
@JsonProperty("source_type")
private String sourceType;
@Schema(description = "创建时间 (时间戳)", example = "1700000000000")
@JsonProperty("create_time")
private Long createTime;
@Schema(description = "创建日期 (格式化)", example = "2024-01-15 10:30:00")
@JsonProperty("create_date")
private String createDate;
@Schema(description = "更新时间 (时间戳)", example = "1700000001000")
@JsonProperty("update_time")
private Long updateTime;
@Schema(description = "更新日期 (格式化)", example = "2024-01-15 11:00:00")
@JsonProperty("update_date")
private String updateDate;
@Schema(description = "文件扩展名", example = "pdf")
private String extension;
}
/**
* 列表响应 VO (对应接口 3: list_files)
*/
@Data
@NoArgsConstructor
@AllArgsConstructor
@Builder
@Schema(description = "文件列表响应")
public static class ListVO implements Serializable {
@Schema(description = "总记录数", example = "100")
private Long total;
@Schema(description = "当前父文件夹信息")
@JsonProperty("parent_folder")
private InfoVO parentFolder;
@Schema(description = "文件/文件夹列表")
private List<InfoVO> files;
@Schema(description = "面包屑导航路径")
private List<InfoVO> breadcrumb;
}
/**
* 转换结果项 VO (对应接口 9: convert)
*/
@Data
@NoArgsConstructor
@AllArgsConstructor
@Builder
@Schema(description = "文件转换结果项")
public static class ConvertVO implements Serializable {
@Schema(description = "转换记录 ID", example = "convert_001")
private String id;
@Schema(description = "源文件 ID", example = "file_001")
@JsonProperty("file_id")
private String fileId;
@Schema(description = "目标文档 ID", example = "doc_001")
@JsonProperty("document_id")
private String documentId;
@Schema(description = "创建时间 (时间戳)", example = "1700000000000")
@JsonProperty("create_time")
private Long createTime;
@Schema(description = "创建日期 (格式化)", example = "2024-01-15 10:30:00")
@JsonProperty("create_date")
private String createDate;
@Schema(description = "更新时间 (时间戳)", example = "1700000001000")
@JsonProperty("update_time")
private Long updateTime;
@Schema(description = "更新日期 (格式化)", example = "2024-01-15 11:00:00")
@JsonProperty("update_date")
private String updateDate;
}
/**
* 转换状态 VO (对应接口 10: get_convert_status)
*/
@Data
@NoArgsConstructor
@AllArgsConstructor
@Builder
@Schema(description = "文件转换状态")
public static class ConvertStatusVO implements Serializable {
@Schema(description = "转换状态: pending / processing / completed / failed", example = "completed")
private String status;
@Schema(description = "转换进度 (0.0 - 1.0)", example = "1.0")
private Float progress;
@Schema(description = "状态消息", example = "转换完成")
private String message;
}
/**
* 面包屑 VO (对应接口 12: all_parent_folder)
*/
@Data
@NoArgsConstructor
@AllArgsConstructor
@Builder
@Schema(description = "面包屑导航 (所有父文件夹)")
public static class BreadcrumbVO implements Serializable {
@Schema(description = "父文件夹列表 (从根到当前的路径)")
@JsonProperty("parent_folders")
private List<InfoVO> parentFolders;
}
/**
* 根目录信息 VO (对应接口 10: get_root_folder)
*/
@Data
@NoArgsConstructor
@AllArgsConstructor
@Builder
@Schema(description = "根目录信息")
public static class RootFolderVO implements Serializable {
@Schema(description = "根文件夹信息")
@JsonProperty("root_folder")
private InfoVO rootFolder;
}
/**
* 父目录信息 VO (对应接口 11: get_parent_folder)
*/
@Data
@NoArgsConstructor
@AllArgsConstructor
@Builder
@Schema(description = "父目录信息")
public static class ParentFolderVO implements Serializable {
@Schema(description = "父文件夹信息")
@JsonProperty("parent_folder")
private InfoVO parentFolder;
}
}
@@ -0,0 +1,97 @@
package xiaozhi.modules.knowledge.entity;
import java.io.Serializable;
import java.util.Date;
import com.baomidou.mybatisplus.annotation.FieldFill;
import com.baomidou.mybatisplus.annotation.IdType;
import com.baomidou.mybatisplus.annotation.TableField;
import com.baomidou.mybatisplus.annotation.TableId;
import com.baomidou.mybatisplus.annotation.TableName;
import io.swagger.v3.oas.annotations.media.Schema;
import lombok.Data;
/**
* 文档表 (Shadow DB for RAGFlow Documents)
* 对应表名: ai_knowledge_document
*/
@Data
@TableName(value = "ai_rag_knowledge_document", autoResultMap = true)
@Schema(description = "知识库文档表")
public class DocumentEntity implements Serializable {
private static final long serialVersionUID = 1L;
@TableId(type = IdType.ASSIGN_UUID)
@Schema(description = "本地唯一ID")
private String id;
@Schema(description = "知识库ID (关联 ai_rag_dataset.dataset_id)")
private String datasetId;
@Schema(description = "RAGFlow文档ID (远程ID)")
private String documentId;
@Schema(description = "文档名称")
private String name;
@Schema(description = "文件大小(Bytes)")
private Long size;
@Schema(description = "文件类型(pdf/doc/txt等)")
private String type;
@Schema(description = "分块方法")
private String chunkMethod;
@Schema(description = "解析配置(JSON String)")
private String parserConfig;
@Schema(description = "可用状态 (1: 启用/正常, 0: 禁用/失效)")
private String status;
@Schema(description = "运行状态 (UNSTART/RUNNING/CANCEL/DONE/FAIL)")
private String run;
@Schema(description = "解析进度 (0.0 ~ 1.0)")
private Double progress;
@Schema(description = "缩略图 (Base64 或 URL)")
private String thumbnail;
@Schema(description = "解析耗时 (单位: 秒)")
private Double processDuration;
@Schema(description = "自定义元数据 (JSON 格式)")
private String metaFields;
@Schema(description = "来源类型 (local, s3, url 等)")
private String sourceType;
@Schema(description = "解析错误信息")
private String error;
@Schema(description = "分块数量")
private Integer chunkCount;
@Schema(description = "Token数量")
private Long tokenCount;
@Schema(description = "是否启用 (0:禁用 1:启用)")
private Integer enabled;
@Schema(description = "创建者")
@TableField(fill = FieldFill.INSERT)
private Long creator;
@Schema(description = "创建时间")
@TableField(fill = FieldFill.INSERT)
private Date createdAt;
@Schema(description = "更新时间")
@TableField(fill = FieldFill.UPDATE)
private Date updatedAt;
@Schema(description = "最新同步时间")
private Date lastSyncAt;
}
@@ -23,15 +23,43 @@ public class KnowledgeBaseEntity {
@Schema(description = "知识库ID")
private String datasetId;
@Schema(description = "RAG模型配置ID")
// @Deprecated
@Schema(description = "RAG模型配置ID (连接RAGFlow的凭证指针)")
private String ragModelId;
@Schema(description = "租户ID")
private String tenantId;
@Schema(description = "知识库名称")
private String name;
@Schema(description = "知识库头像(Base64)")
private String avatar;
@Schema(description = "知识库描述")
private String description;
@Schema(description = "嵌入模型名称")
private String embeddingModel;
@Schema(description = "权限设置: me/team")
private String permission;
@Schema(description = "分块方法")
private String chunkMethod;
@Schema(description = "解析器配置(JSON String)")
private String parserConfig;
@Schema(description = "分块总数")
private Long chunkCount;
@Schema(description = "文档总数")
private Long documentCount;
@Schema(description = "总Token数")
private Long tokenNum;
@Schema(description = "状态(0:禁用 1:启用)")
private Integer status;
@@ -3,10 +3,14 @@ package xiaozhi.modules.knowledge.rag;
import java.util.List;
import java.util.Map;
import org.springframework.web.multipart.MultipartFile;
import xiaozhi.modules.knowledge.dto.dataset.DatasetDTO;
import xiaozhi.common.page.PageData;
import xiaozhi.modules.knowledge.dto.KnowledgeFilesDTO;
import xiaozhi.modules.knowledge.dto.document.DocumentDTO;
import xiaozhi.modules.knowledge.dto.document.ChunkDTO;
import xiaozhi.modules.knowledge.dto.document.RetrievalDTO;
import java.util.function.Consumer;
/**
* 知识库API适配器抽象基类
@@ -46,35 +50,24 @@ public abstract class KnowledgeBaseAdapter {
* @return 分页数据
*/
public abstract PageData<KnowledgeFilesDTO> getDocumentList(String datasetId,
Map<String, Object> queryParams,
Integer page,
Integer limit);
DocumentDTO.ListReq req);
/**
* 根据文档ID获取文档详情
*
* @param datasetId 知识库ID
* @return 文档详情
* @param datasetId 知识库ID
* @param documentId 文档ID
* @return 文档详情 (强类型 InfoVO)
*/
public abstract KnowledgeFilesDTO getDocumentById(String datasetId, String documentId);
public abstract DocumentDTO.InfoVO getDocumentById(String datasetId, String documentId);
/**
* 上传文档到知识库
*
* @param datasetId 知识库ID
* @param file 上传的文件
* @param name 文档名称
* @param metaFields 元数据字段
* @param chunkMethod 分块方法
* @param parserConfig 解析器配置
* @param req 上传请求参数
* @return 上传的文档信息
*/
public abstract KnowledgeFilesDTO uploadDocument(String datasetId,
MultipartFile file,
String name,
Map<String, Object> metaFields,
String chunkMethod,
Map<String, Object> parserConfig);
public abstract KnowledgeFilesDTO uploadDocument(DocumentDTO.UploadReq req);
/**
* 根据状态分页查询文档列表
@@ -91,12 +84,12 @@ public abstract class KnowledgeBaseAdapter {
Integer limit);
/**
* 删除文档
* 删除文档 (支持批量删除)
*
* @param datasetId 知识库ID
* @param documentId 文档ID
* @param datasetId 知识库ID
* @param req 包含文档ID列表的请求对象
*/
public abstract void deleteDocument(String datasetId, String documentId);
public abstract void deleteDocument(String datasetId, DocumentDTO.BatchIdReq req);
/**
* 解析文档(切块)
@@ -112,32 +105,21 @@ public abstract class KnowledgeBaseAdapter {
*
* @param datasetId 知识库ID
* @param documentId 文档ID
* @param keywords 关键词过滤
* @param page 页码
* @param pageSize 每页数量
* @param chunkId 切片ID
* @return 切片列表信息
* @param req 列表请求参数 (分页、关键词等)
* @return 切片列表VO
*/
public abstract Map<String, Object> listChunks(String datasetId,
public abstract ChunkDTO.ListVO listChunks(String datasetId,
String documentId,
String keywords,
Integer page,
Integer pageSize,
String chunkId);
ChunkDTO.ListReq req);
/**
* 召回测试 - 从知识库中检索相关切片
*
* @param question 用户查询
* @param datasetIds 数据集ID列表
* @param documentIds 文档ID列表
* @param retrievalParams 检索参数
* @param req 检索测试请求参数
* @return 召回测试结果
*/
public abstract Map<String, Object> retrievalTest(String question,
List<String> datasetIds,
List<String> documentIds,
Map<String, Object> retrievalParams);
public abstract RetrievalDTO.ResultVO retrievalTest(
RetrievalDTO.TestReq req);
/**
* 测试连接
@@ -170,31 +152,73 @@ public abstract class KnowledgeBaseAdapter {
/**
* 创建数据集
*
* @param createParams 创建参数
* @return 数据集ID
* @param req 创建参数
* @return 数据集详情
*/
public abstract String createDataset(Map<String, Object> createParams);
public abstract DatasetDTO.InfoVO createDataset(DatasetDTO.CreateReq req);
/**
* 更新数据集
*
* @param datasetId 数据集ID
* @param updateParams 更新参数
* @param datasetId 数据集ID
* @param req 更新参数
* @return 数据集详情
*/
public abstract void updateDataset(String datasetId, Map<String, Object> updateParams);
public abstract DatasetDTO.InfoVO updateDataset(String datasetId, DatasetDTO.UpdateReq req);
/**
* 删除数据集
*
* @param datasetId 数据集ID
* @param req 删除请求参数(包含ID列表)
* @return 批量操作结果
*/
public abstract void deleteDataset(String datasetId);
public abstract DatasetDTO.BatchOperationVO deleteDataset(DatasetDTO.BatchIdReq req);
/**
* 获取数据集的文档数量
*
*
* @param datasetId 数据集ID
* @return 文档数量
*/
public abstract Integer getDocumentCount(String datasetId);
/**
* 获取数据集完整信息(名称、简介、文档数量等)
* 用于检测 RAGFlow 端是否已删除、同步名称/简介变更
*
* @param datasetId 数据集ID
* @return 数据集详情,若 RAGFlow 端不存在则返回 null
*/
public abstract DatasetDTO.InfoVO getDatasetInfo(String datasetId);
/**
* 发送流式请求 (SSE)
*
* @param endpoint API端点
* @param body 请求体
* @param onData 数据回调
*/
public abstract void postStream(String endpoint, Object body, Consumer<String> onData);
/**
* SearchBot 提问
*
* @param config RAG配置
* @param body 请求体
* @param onData 数据回调
* @return 响应对象
*/
public abstract Object postSearchBotAsk(Map<String, Object> config, Object body,
Consumer<String> onData);
/**
* AgentBot 对话
*
* @param config RAG配置
* @param agentId Agent ID
* @param body 请求体
* @param onData 数据回调
*/
public abstract void postAgentBotCompletion(Map<String, Object> config, String agentId, Object body,
Consumer<String> onData);
}
@@ -22,6 +22,9 @@ public class KnowledgeBaseAdapterFactory {
// 适配器实例缓存
private static final Map<String, KnowledgeBaseAdapter> adapterCache = new ConcurrentHashMap<>();
// 最大缓存实例数,防止内存泄露 (Issue 9)
private static final int MAX_CACHE_SIZE = 50;
static {
// 注册内置适配器类型
registerAdapter("ragflow", xiaozhi.modules.knowledge.rag.impl.RAGFlowAdapter.class);
@@ -61,7 +64,13 @@ public class KnowledgeBaseAdapterFactory {
// 创建新的适配器实例
KnowledgeBaseAdapter adapter = createAdapter(adapterType, config);
// 缓存适配器实例
// 缓存适配器实例 (带容量限制检查)
if (adapterCache.size() >= MAX_CACHE_SIZE) {
log.warn("适配器缓存已达上限 ({}),执行内存保护性清除", MAX_CACHE_SIZE);
// 简单处理:直接清空,生产环境下建议使用 LRU
adapterCache.clear();
}
adapterCache.put(cacheKey, adapter);
log.info("创建并缓存适配器实例: {}", cacheKey);
@@ -0,0 +1,278 @@
package xiaozhi.modules.knowledge.rag;
import java.time.Duration;
import java.nio.charset.StandardCharsets;
import java.util.Collections;
import java.util.Map;
import org.springframework.boot.web.client.RestTemplateBuilder;
import org.springframework.http.HttpEntity;
import org.springframework.http.HttpHeaders;
import org.springframework.http.HttpMethod;
import org.springframework.http.MediaType;
import org.springframework.http.ResponseEntity;
import org.springframework.util.MultiValueMap;
import org.springframework.web.client.RestTemplate;
import org.springframework.http.client.SimpleClientHttpRequestFactory;
import java.text.SimpleDateFormat;
import java.util.TimeZone;
import java.util.Locale;
import java.net.URLEncoder;
import java.io.UnsupportedEncodingException;
import java.net.http.HttpClient;
import java.net.http.HttpRequest;
import java.net.http.HttpResponse;
import java.net.URI;
import java.io.OutputStream;
import java.io.ByteArrayOutputStream;
import java.io.IOException;
import java.util.function.Consumer;
import com.fasterxml.jackson.databind.ObjectMapper;
import lombok.extern.slf4j.Slf4j;
import xiaozhi.common.exception.ErrorCode;
import xiaozhi.common.exception.RenException;
/**
* RAGFlow HTTP Client
* 统一处理HTTP通信、鉴权、超时与错误解析
*/
@Slf4j
public class RAGFlowClient {
private final String baseUrl;
private final String apiKey;
private final RestTemplate restTemplate;
private final ObjectMapper objectMapper;
// 默认超时时间 (秒)
private static final int DEFAULT_TIMEOUT = 30;
public RAGFlowClient(String baseUrl, String apiKey) {
this(baseUrl, apiKey, DEFAULT_TIMEOUT);
}
public RAGFlowClient(String baseUrl, String apiKey, int timeoutSeconds) {
this.baseUrl = baseUrl.endsWith("/") ? baseUrl.substring(0, baseUrl.length() - 1) : baseUrl;
this.apiKey = apiKey;
this.objectMapper = new ObjectMapper();
// [Reinforce] 兼容 RAGFlow 返回的 RFC 1123 日期格式 (如: Tue, 10 Feb 2026 10:27:35 GMT)
this.objectMapper
.setDateFormat(new SimpleDateFormat("EEE, dd MMM yyyy HH:mm:ss 'GMT'", Locale.US));
this.objectMapper.setTimeZone(TimeZone.getTimeZone("GMT"));
// 优先从 Spring 上下文中获取池化的 RestTemplate Bean (Issue 3: 连接池化)
RestTemplate pooledTemplate = null;
try {
pooledTemplate = xiaozhi.common.utils.SpringContextUtils.getBean(RestTemplate.class);
} catch (Exception e) {
log.warn("无法从 SpringContext 获取池化 RestTemplate,将退化为简单连接模式: {}", e.getMessage());
}
if (false) { // Force new RestTemplate for debugging
this.restTemplate = pooledTemplate;
log.debug("RAGFlowClient 已成功挂载全局池化 RestTemplate");
} else {
// 兜底方案:配置超时并创建简单 RestTemplate
log.info("RAGFlowClient 初始化: 使用独立 RestTemplate (Debug Mode)");
SimpleClientHttpRequestFactory factory = new SimpleClientHttpRequestFactory();
factory.setConnectTimeout(timeoutSeconds * 1000);
factory.setReadTimeout(timeoutSeconds * 1000);
this.restTemplate = new RestTemplate(factory);
}
}
/**
* 发送 GET 请求
*/
public Map<String, Object> get(String endpoint, Map<String, Object> queryParams) {
String url = buildUrl(endpoint, queryParams);
log.debug("GET {}", url);
return execute(url, HttpMethod.GET, null);
}
/**
* 发送 POST 请求 (JSON)
*/
public Map<String, Object> post(String endpoint, Object body) {
String url = buildUrl(endpoint, null);
log.info("RAGFlow Client POST Request: URL={}, BodyType={}", url,
body != null ? body.getClass().getName() : "null");
try {
return execute(url, HttpMethod.POST, body);
} catch (Exception e) {
log.error("RAGFlow Client POST Failed: URL={}", url, e);
throw e;
}
}
/**
* 发送 DELETE 请求
*/
public Map<String, Object> delete(String endpoint, Object body) {
String url = buildUrl(endpoint, null);
log.debug("DELETE {}", url);
return execute(url, HttpMethod.DELETE, body);
}
/**
* 发送 PUT 请求
*/
public Map<String, Object> put(String endpoint, Object body) {
String url = buildUrl(endpoint, null);
log.debug("PUT {}", url);
return execute(url, HttpMethod.PUT, body);
}
/**
* 发送 Multipart 请求 (文件上传)
*/
public Map<String, Object> postMultipart(String endpoint, MultiValueMap<String, Object> parts) {
String url = buildUrl(endpoint, null);
log.debug("POST MULTIPART {}", url);
HttpHeaders headers = new HttpHeaders();
headers.setContentType(MediaType.MULTIPART_FORM_DATA);
headers.setBearerAuth(apiKey);
// 为了防止中文文件名乱码,某些环境可能需要设置 Charset,但在 Multipart 中通常由 Part header 控制
HttpEntity<MultiValueMap<String, Object>> requestEntity = new HttpEntity<>(parts, headers);
return doExecute(url, HttpMethod.POST, requestEntity);
}
private Map<String, Object> execute(String url, HttpMethod method, Object body) {
HttpHeaders headers = new HttpHeaders();
headers.setContentType(MediaType.APPLICATION_JSON);
headers.setBearerAuth(apiKey);
// 强制 UTF-8
headers.setAcceptCharset(Collections.singletonList(StandardCharsets.UTF_8));
HttpEntity<Object> requestEntity = new HttpEntity<>(body, headers);
return doExecute(url, method, requestEntity);
}
private Map<String, Object> doExecute(String url, HttpMethod method, HttpEntity<?> requestEntity) {
try {
ResponseEntity<String> response = restTemplate.exchange(url, method, requestEntity, String.class);
if (!response.getStatusCode().is2xxSuccessful()) {
log.error("RAGFlow API Error Status: {}", response.getStatusCode());
throw new RenException(ErrorCode.RAG_API_ERROR, "HTTP " + response.getStatusCode());
}
String responseBody = response.getBody();
if (responseBody == null) {
throw new RenException(ErrorCode.RAG_API_ERROR, "Empty Response");
}
@SuppressWarnings("unchecked")
Map<String, Object> map = objectMapper.readValue(responseBody, Map.class);
Integer code = (Integer) map.get("code");
if (code != null && code != 0) {
String msg = (String) map.get("message");
log.error("RAGFlow Business Error: code={}, msg={}", code, msg);
throw new RenException(ErrorCode.RAG_API_ERROR, msg != null ? msg : "Unknown RAGFlow Error");
}
// 返回 data 字段,如果 data 不存在则返回整个 map (视具体情况,通常 RAGFlow 返回 code=0, data=...)
// 兼容性处理:如果 external caller 需要 check code,这里已经 check 过了。
// 统一返回 wrap 了 code 的 map 还是只返回 data?
// 根据分析报告,旧逻辑 check code==0 后取 data.
// 这里我们返回整个 Map,让 Adapter 决定怎么取,或者我们直接在这里剥离?
// 建议:为了灵活性,返回全量 Map,但在 Client 层做 code!=0 的抛错。
return map;
} catch (RenException re) {
throw re;
} catch (Exception e) {
log.error("RAGFlow Client Execute Error! URL: {}, Method: {}, Body Type: {}", url, method,
requestEntity.getBody() != null ? requestEntity.getBody().getClass().getName() : "null");
log.error("Full exception stack trace: ", e);
throw new RenException(ErrorCode.RAG_API_ERROR, "Request Failed: " + e.getMessage());
}
}
private String buildUrl(String endpoint, Map<String, Object> queryParams) {
StringBuilder sb = new StringBuilder(baseUrl);
if (!endpoint.startsWith("/")) {
sb.append("/");
}
sb.append(endpoint);
if (queryParams != null && !queryParams.isEmpty()) {
sb.append("?");
queryParams.forEach((k, v) -> {
if (v != null) {
try {
sb.append(k).append("=")
.append(URLEncoder.encode(v.toString(),
StandardCharsets.UTF_8.name()))
.append("&");
} catch (UnsupportedEncodingException e) {
log.warn("参数编码失败: k={}, v={}", k, v);
sb.append(k).append("=").append(v).append("&");
}
}
});
// 移除最后一个 &
sb.setLength(sb.length() - 1);
}
return sb.toString();
}
/**
* 发送流式 POST 请求 (SSE)
* 使用 Java 21 HttpClient 实现
*
* @param endpoint API端点
* @param body 请求体
* @param onData 数据回调(每收到一行数据调用一次)
*/
public void postStream(String endpoint, Object body, Consumer<String> onData) {
try {
String url = buildUrl(endpoint, null);
log.debug("POST STREAM {}", url);
String jsonBody = objectMapper.writeValueAsString(body);
HttpClient httpClient = HttpClient.newBuilder()
.connectTimeout(Duration.ofSeconds(DEFAULT_TIMEOUT))
.build();
HttpRequest request = HttpRequest.newBuilder()
.uri(URI.create(url))
.header("Content-Type", "application/json")
.header("Authorization", "Bearer " + apiKey)
.POST(HttpRequest.BodyPublishers.ofString(jsonBody, StandardCharsets.UTF_8))
.build();
// 发送请求并处理流式响应
httpClient.send(request, HttpResponse.BodyHandlers.ofInputStream())
.body()
.transferTo(new OutputStream() {
private final ByteArrayOutputStream buffer = new ByteArrayOutputStream();
@Override
public void write(int b) throws IOException {
if (b == '\n') {
String line = buffer.toString(StandardCharsets.UTF_8);
if (!line.trim().isEmpty()) {
onData.accept(line);
}
buffer.reset();
} else {
buffer.write(b);
}
}
});
} catch (Exception e) {
log.error("RAGFlow Stream Request Error", e);
throw new RenException(ErrorCode.RAG_API_ERROR, "Stream Request Failed: " + e.getMessage());
}
}
}
File diff suppressed because it is too large Load Diff
@@ -93,4 +93,14 @@ public interface KnowledgeBaseService extends BaseService<KnowledgeBaseEntity> {
* @return RAG模型列表
*/
List<ModelConfigEntity> getRAGModels();
/**
* 更新知识库统计信息 (用于被文件服务回调)
*
* @param datasetId 知识库ID
* @param docDelta 文档数增量
* @param chunkDelta 分块数增量
* @param tokenDelta Token数增量
*/
void updateStatistics(String datasetId, Integer docDelta, Long chunkDelta, Long tokenDelta);
}
@@ -7,6 +7,9 @@ import org.springframework.web.multipart.MultipartFile;
import xiaozhi.common.page.PageData;
import xiaozhi.modules.knowledge.dto.KnowledgeFilesDTO;
import xiaozhi.modules.knowledge.dto.document.ChunkDTO;
import xiaozhi.modules.knowledge.dto.document.RetrievalDTO;
import xiaozhi.modules.knowledge.dto.document.DocumentDTO;
/**
* 知识库文档服务接口
@@ -28,9 +31,9 @@ public interface KnowledgeFilesService {
*
* @param documentId 文档ID
* @param datasetId 知识库ID
* @return 文档详情
* @return 文档详情 (强类型 InfoVO)
*/
KnowledgeFilesDTO getByDocumentId(String documentId, String datasetId);
DocumentDTO.InfoVO getByDocumentId(String documentId, String datasetId);
/**
* 上传文档到知识库
@@ -48,12 +51,12 @@ public interface KnowledgeFilesService {
Map<String, Object> parserConfig);
/**
* 根据文档ID和知识库ID删除文档
* 批量删除文档
*
* @param documentId 文档ID
* @param datasetId 知识库ID
* @param datasetId 知识库ID
* @param req 删除请求参数 (含文档ID列表)
*/
void deleteByDocumentId(String documentId, String datasetId);
void deleteDocuments(String datasetId, DocumentDTO.BatchIdReq req);
/**
* 获取RAG配置信息
@@ -77,36 +80,53 @@ public interface KnowledgeFilesService {
*
* @param datasetId 知识库ID
* @param documentId 文档ID
* @param keywords 关键词过滤
* @param page 页码
* @param pageSize 每页数量
* @param chunkId 切片ID
* @param req 切片列表请求参数
* @return 切片列表信息
*/
Map<String, Object> listChunks(String datasetId, String documentId, String keywords,
Integer page, Integer pageSize, String chunkId);
ChunkDTO.ListVO listChunks(String datasetId, String documentId, ChunkDTO.ListReq req);
/**
* 召回测试 - 从指定数据集或文档中检索相关切片
* 召回测试
*
* @param question 用户查询或查询关键词
* @param datasetIds 数据集ID列表
* @param documentIds 文档ID列表
* @param page 页码
* @param pageSize 每页数量
* @param similarityThreshold 最小相似度阈值
* @param vectorSimilarityWeight 向量相似度权重
* @param topK 参与向量余弦计算的切片数量
* @param rerankId 重排模型ID
* @param keyword 是否启用关键词匹配
* @param highlight 是否启用高亮显示
* @param crossLanguages 跨语言翻译列表
* @param metadataCondition 元数据过滤条件
* @param req 检索测试请求参数
* @return 召回测试结果
*/
Map<String, Object> retrievalTest(String question, List<String> datasetIds, List<String> documentIds,
Integer page, Integer pageSize, Float similarityThreshold,
Float vectorSimilarityWeight, Integer topK, String rerankId,
Boolean keyword, Boolean highlight, List<String> crossLanguages,
Map<String, Object> metadataCondition);
RetrievalDTO.ResultVO retrievalTest(RetrievalDTO.TestReq req);
/**
* 保存文档影子记录
*/
boolean saveDocumentShadow(String datasetId, KnowledgeFilesDTO result, String originalName, String chunkMethod,
Map<String, Object> parserConfig);
/**
* 批量删除文档影子记录并同步统计数据
*
* @param documentIds 文档ID列表
* @param datasetId 数据集ID
* @param chunkDelta 待扣减的总分块数
* @param tokenDelta 待扣减的总Token数
*/
void deleteDocumentShadows(List<String> documentIds, String datasetId, Long chunkDelta, Long tokenDelta);
/**
* 根据数据集ID清理所有关联文档 (级联删除专用)
*
* @param datasetId 数据集ID
*/
void deleteDocumentsByDatasetId(String datasetId);
/**
* 同步所有处于 RUNNING 状态的文档 (供定时任务调用)
*/
void syncRunningDocuments();
/**
* 从RAGFlow全量同步文档到本地影子表
* 拉取远端所有文档,与本地影子表对比,插入缺失的记录
*
* @param datasetId 数据集ID
* @return 新同步的文档数量
*/
int syncDocumentsFromRAG(String datasetId);
}
@@ -0,0 +1,24 @@
package xiaozhi.modules.knowledge.service;
import java.util.List;
/**
* 知识库模块领域编排服务
* 用于处理跨 KnowledgeBase 和 KnowledgeFiles 的复杂业务流程,彻底解决 Service 间的循环依赖问题。
*/
public interface KnowledgeManagerService {
/**
* 级联删除知识库及其下属所有文档 (包括本地 DB 和 RAGFlow 远程数据)
*
* @param datasetId 知识库 ID
*/
void deleteDatasetWithFiles(String datasetId);
/**
* 批量级联删除知识库
*
* @param datasetIds 知识库 ID 列表
*/
void batchDeleteDatasetsWithFiles(List<String> datasetIds);
}
@@ -0,0 +1,47 @@
package xiaozhi.modules.knowledge.service.impl;
import lombok.RequiredArgsConstructor;
import lombok.extern.slf4j.Slf4j;
import org.springframework.stereotype.Service;
import org.springframework.transaction.annotation.Transactional;
import xiaozhi.modules.knowledge.service.KnowledgeBaseService;
import xiaozhi.modules.knowledge.service.KnowledgeFilesService;
import xiaozhi.modules.knowledge.service.KnowledgeManagerService;
import java.util.List;
@Service
@Slf4j
@RequiredArgsConstructor
public class KnowledgeManagerServiceImpl implements KnowledgeManagerService {
private final KnowledgeBaseService knowledgeBaseService;
private final KnowledgeFilesService knowledgeFilesService;
@Override
@Transactional(rollbackFor = Exception.class)
public void deleteDatasetWithFiles(String datasetId) {
log.info("=== 级联删除开始: datasetId={} ===", datasetId);
// 1. 先调用文件服务,清理该数据集下的所有文档记录 (含 RAGFlow 端)
log.info("Step 1: 清理关联文档...");
knowledgeFilesService.deleteDocumentsByDatasetId(datasetId);
// 2. 再调用知识库服务,彻底注销数据集 (含 RAGFlow 端)
log.info("Step 2: 删除数据集主体...");
knowledgeBaseService.deleteByDatasetId(datasetId);
log.info("=== 级联删除成功: datasetId={} ===", datasetId);
}
@Override
@Transactional(rollbackFor = Exception.class)
public void batchDeleteDatasetsWithFiles(List<String> datasetIds) {
if (datasetIds == null || datasetIds.isEmpty())
return;
log.info("=== 批量级联删除开始: count={} ===", datasetIds.size());
for (String id : datasetIds) {
deleteDatasetWithFiles(id);
}
}
}
@@ -0,0 +1,39 @@
package xiaozhi.modules.knowledge.task;
import org.springframework.scheduling.annotation.Scheduled;
import org.springframework.stereotype.Component;
import lombok.AllArgsConstructor;
import lombok.extern.slf4j.Slf4j;
import xiaozhi.modules.knowledge.service.KnowledgeFilesService;
/**
* 知识库文档状态同步定时任务
*
* 作用:
* 1. 自动扫描处于 "RUNNING" (解析中) 状态的文档
* 2. 调用 RAGFlow 接口获取最新状态
* 3. 状态翻转 (RUNNING -> SUCCESS/FAIL) 时,同步更新数据库
* 4. [关键] 解析成功时,补偿更新知识库的统计信息 (TokenCount)
*/
@Component
@AllArgsConstructor
@Slf4j
public class DocumentStatusSyncTask {
private final KnowledgeFilesService knowledgeFilesService;
/**
* 每 30 秒执行一次同步
* 采用 fixedDelay,确保上一次执行完 30 秒后才开始下一次,防止积压
*/
@Scheduled(fixedDelay = 30000)
public void syncRunningDocuments() {
try {
// log.debug("开始执行文档状态同步任务...");
knowledgeFilesService.syncRunningDocuments();
} catch (Exception e) {
log.error("文档状态同步任务异常", e);
}
}
}
@@ -67,4 +67,13 @@ public interface LLMService {
* @return 是否可用
*/
boolean isAvailable(String modelId);
/**
* 生成会话标题
*
* @param conversation 对话内容
* @param modelId 模型ID
* @return 标题(约15字)
*/
String generateTitle(String conversation, String modelId);
}
@@ -1,6 +1,7 @@
package xiaozhi.modules.llm.service.impl;
import java.util.HashMap;
import java.util.LinkedHashMap;
import java.util.List;
import java.util.Map;
@@ -30,13 +31,38 @@ import xiaozhi.modules.model.service.ModelConfigService;
@Service
public class OpenAIStyleLLMServiceImpl implements LLMService {
// 需要禁用思考模式的平台域名及其对应参数
private static final Map<String, Map<String, Object>> THINKING_DISABLED_DOMAINS = new LinkedHashMap<>();
static {
THINKING_DISABLED_DOMAINS.put("aliyuncs.com", Map.of("enable_thinking", false));
Map<String, Object> thinkingDisabled = Map.of("thinking", Map.of("type", "disabled"));
THINKING_DISABLED_DOMAINS.put("bigmodel.cn", thinkingDisabled);
THINKING_DISABLED_DOMAINS.put("moonshot.cn", thinkingDisabled);
THINKING_DISABLED_DOMAINS.put("volces.com", thinkingDisabled);
}
@Autowired
private ModelConfigService modelConfigService;
private final RestTemplate restTemplate = new RestTemplate();
/**
* 根据域名自动禁用思考模式
*/
private void applyThinkingDisabled(String baseUrl, Map<String, Object> requestBody) {
for (Map.Entry<String, Map<String, Object>> entry : THINKING_DISABLED_DOMAINS.entrySet()) {
if (baseUrl.contains(entry.getKey())) {
requestBody.putAll(entry.getValue());
log.info("为域名 {} 禁用思考模式,参数: {}", baseUrl, entry.getValue());
break;
}
}
}
private static final String DEFAULT_SUMMARY_PROMPT = "你是一个经验丰富的记忆总结者,擅长将对话内容进行总结摘要,遵循以下规则:\n1、总结用户的重要信息,以便在未来的对话中提供更个性化的服务\n2、不要重复总结,不要遗忘之前记忆,除非原来的记忆超过了1800字,否则不要遗忘、不要压缩用户的历史记忆\n3、用户操控的设备音量、播放音乐、天气、退出、不想对话等和用户本身无关的内容,这些信息不需要加入到总结中\n4、聊天内容中的今天的日期时间、今天的天气情况与用户事件无关的数据,这些信息如果当成记忆存储会影响后续对话,这些信息不需要加入到总结中\n5、不要把设备操控的成果结果和失败结果加入到总结中,也不要把用户的一些废话加入到总结中\n6、不要为了总结而总结,如果用户的聊天没有意义,请返回原来的历史记录也是可以的\n7、只需要返回总结摘要,严格控制在1800字内\n8、不要包含代码、xml,不需要解释、注释和说明,保存记忆时仅从对话提取信息,不要混入示例内容\n9、如果提供了历史记忆,请将新对话内容与历史记忆进行智能合并,保留有价值的历史信息,同时添加新的重要信息\n\n历史记忆:\n{history_memory}\n\n新对话内容:\n{conversation}";
private static final String DEFAULT_TITLE_PROMPT = "请根据以下对话内容,生成一个简洁的会话标题(约15字以内),只返回标题,不要包含任何解释或标点符号:\n{conversation}";
@Override
public String generateSummary(String conversation) {
return generateSummary(conversation, null, null);
@@ -100,6 +126,9 @@ public class OpenAIStyleLLMServiceImpl implements LLMService {
requestBody.put("temperature", temperature != null ? temperature : 0.7);
requestBody.put("max_tokens", maxTokens != null ? maxTokens : 2000);
// 禁用思考模式
applyThinkingDisabled(baseUrl, requestBody);
// 发送HTTP请求
HttpHeaders headers = new HttpHeaders();
headers.setContentType(MediaType.APPLICATION_JSON);
@@ -154,10 +183,8 @@ public class OpenAIStyleLLMServiceImpl implements LLMService {
// 从智控台获取LLM模型配置
ModelConfigEntity llmConfig;
if (modelId != null && !modelId.trim().isEmpty()) {
// 通过具体模型ID获取配置
llmConfig = modelConfigService.getModelByIdFromCache(modelId);
} else {
// 保持向后兼容,使用默认配置
llmConfig = getDefaultLLMConfig();
}
@@ -195,6 +222,9 @@ public class OpenAIStyleLLMServiceImpl implements LLMService {
requestBody.put("temperature", 0.2);
requestBody.put("max_tokens", 2000);
// 禁用思考模式
applyThinkingDisabled(baseUrl, requestBody);
// 发送HTTP请求
HttpHeaders headers = new HttpHeaders();
headers.setContentType(MediaType.APPLICATION_JSON);
@@ -302,4 +332,94 @@ public class OpenAIStyleLLMServiceImpl implements LLMService {
return null;
}
}
@Override
public String generateTitle(String conversation, String modelId) {
if (!isAvailable()) {
log.warn("LLM服务不可用,无法生成标题");
return null;
}
try {
ModelConfigEntity llmConfig;
if (modelId != null && !modelId.trim().isEmpty()) {
llmConfig = modelConfigService.getModelByIdFromCache(modelId);
} else {
llmConfig = getDefaultLLMConfig();
}
if (llmConfig == null || llmConfig.getConfigJson() == null) {
log.error("未找到可用的LLM模型配置,modelId: {}", modelId);
return null;
}
JSONObject configJson = llmConfig.getConfigJson();
String baseUrl = configJson.getStr("base_url");
String model = configJson.getStr("model_name");
String apiKey = configJson.getStr("api_key");
if (StringUtils.isBlank(baseUrl) || StringUtils.isBlank(apiKey)) {
log.error("LLM配置不完整,baseUrl或apiKey为空");
return null;
}
String prompt = DEFAULT_TITLE_PROMPT.replace("{conversation}", conversation);
Map<String, Object> requestBody = new HashMap<>();
requestBody.put("model", model != null ? model : "gpt-3.5-turbo");
Map<String, Object>[] messages = new Map[1];
Map<String, Object> message = new HashMap<>();
message.put("role", "user");
message.put("content", prompt);
messages[0] = message;
requestBody.put("messages", messages);
requestBody.put("temperature", 0.3);
requestBody.put("max_tokens", 50);
// 禁用思考模式
applyThinkingDisabled(baseUrl, requestBody);
HttpHeaders headers = new HttpHeaders();
headers.setContentType(MediaType.APPLICATION_JSON);
headers.set("Authorization", "Bearer " + apiKey);
HttpEntity<Map<String, Object>> entity = new HttpEntity<>(requestBody, headers);
String apiUrl = baseUrl;
if (!apiUrl.endsWith("/chat/completions")) {
if (!apiUrl.endsWith("/")) {
apiUrl += "/";
}
apiUrl += "chat/completions";
}
ResponseEntity<String> response = restTemplate.exchange(
apiUrl, HttpMethod.POST, entity, String.class);
if (response.getStatusCode().is2xxSuccessful()) {
JSONObject responseJson = JSONUtil.parseObj(response.getBody());
JSONArray choices = responseJson.getJSONArray("choices");
if (choices != null && choices.size() > 0) {
JSONObject choice = choices.getJSONObject(0);
JSONObject messageObj = choice.getJSONObject("message");
String title = messageObj.getStr("content");
if (StringUtils.isNotBlank(title)) {
title = title.trim().replaceAll("[,。!?、:;''\"\"【】()]", "");
if (title.length() > 15) {
title = title.substring(0, 15);
}
return title;
}
}
} else {
log.error("LLM API调用失败,状态码:{},响应:{}", response.getStatusCode(), response.getBody());
}
} catch (Exception e) {
log.error("调用LLM服务生成标题时发生异常,modelId: {}", modelId, e);
}
return null;
}
}
@@ -129,6 +129,10 @@ public class ModelController {
if (entity == null) {
return new Result<Void>().error("模型配置不存在");
}
// 不能关闭默认模型
if (status == 0 && entity.getIsDefault() > 0) {
return new Result<Void>().error("默认模型配置不允许关闭");
}
// 不更新ConfigJson字段
entity.setConfigJson(null);
entity.setIsEnabled(status);
@@ -23,6 +23,9 @@ public class VoiceDTO implements Serializable {
@Schema(description = "音频播放地址")
private String voiceDemo;
@Schema(description = "语言类型")
private String languages;
@Schema(description = "是否为克隆音色")
private Boolean isClone;
@@ -31,6 +34,7 @@ public class VoiceDTO implements Serializable {
this.id = id;
this.name = name;
this.voiceDemo = null;
this.languages = null;
this.isClone = false; // 默认不是克隆音色
}
@@ -39,6 +43,7 @@ public class VoiceDTO implements Serializable {
this.id = id;
this.name = name;
this.voiceDemo = voiceDemo;
this.languages = null;
this.isClone = false;
}
@@ -57,7 +57,8 @@ public class ModelConfigServiceImpl extends BaseServiceImpl<ModelConfigDao, Mode
.eq("model_type", modelType)
.eq("is_enabled", 1)
.like(StringUtils.isNotBlank(modelName), "model_name", modelName)
.select("id", "model_name"));
.select("id", "model_name")
.orderByAsc("sort"));
return ConvertUtils.sourceToTarget(entities, ModelBasicInfoDTO.class);
}
@@ -370,6 +371,13 @@ public class ModelConfigServiceImpl extends BaseServiceImpl<ModelConfigDao, Mode
}
}
// 删除在新JSON中不存在的非敏感字段
for (String oldKey : originalJson.keySet().toArray(new String[0])) {
if (!modelConfigBodyDTO.getConfigJson().containsKey(oldKey) && !SensitiveDataUtils.isSensitiveField(oldKey)) {
updatedJson.remove(oldKey);
}
}
modelConfigEntity.setConfigJson(updatedJson);
}
@@ -402,6 +410,13 @@ public class ModelConfigServiceImpl extends BaseServiceImpl<ModelConfigDao, Mode
}
}
}
// 删除在新JSON中不存在的非敏感子字段
for (String oldChildKey : originalChild.keySet().toArray(new String[0])) {
if (!updated.containsKey(oldChildKey) && !SensitiveDataUtils.isSensitiveField(oldChildKey)) {
originalChild.remove(oldChildKey);
}
}
}
/**
@@ -95,6 +95,7 @@ public class ModelProviderServiceImpl extends BaseServiceImpl<ModelProviderDao,
QueryWrapper<ModelProviderEntity> queryWrapper = new QueryWrapper<>();
queryWrapper.eq("model_type", StringUtils.isBlank(modelType) ? "" : modelType);
queryWrapper.orderByAsc("sort");
List<ModelProviderEntity> providerEntities = modelProviderDao.selectList(queryWrapper);
return ConvertUtils.sourceToTarget(providerEntities, ModelProviderDTO.class);
}
@@ -147,7 +148,8 @@ public class ModelProviderServiceImpl extends BaseServiceImpl<ModelProviderDao,
UserDetail user = SecurityUser.getUser();
modelProviderDTO.setUpdater(user.getId());
modelProviderDTO.setUpdateDate(new Date());
if (modelProviderDao.updateById(ConvertUtils.sourceToTarget(modelProviderDTO, ModelProviderEntity.class)) == 0) {
if (modelProviderDao
.updateById(ConvertUtils.sourceToTarget(modelProviderDTO, ModelProviderEntity.class)) == 0) {
throw new RenException(ErrorCode.UPDATE_DATA_FAILED);
}
return ConvertUtils.sourceToTarget(modelProviderDTO, ModelProviderDTO.class);
@@ -90,6 +90,7 @@ public class ShiroConfig {
filterMap.put("/agent/chat-history/report", "server");
filterMap.put("/agent/chat-history/download/**", "anon");
filterMap.put("/agent/chat-summary/**", "server");
filterMap.put("/agent/chat-title/**", "server");
filterMap.put("/agent/play/**", "anon");
filterMap.put("/voiceClone/play/**", "anon");
filterMap.put("/**", "oauth2");
@@ -56,7 +56,7 @@ public class SysUserServiceImpl extends BaseServiceImpl<SysUserDao, SysUserEntit
if (users == null || users.isEmpty()) {
return null;
}
SysUserEntity entity = users.getFirst();
SysUserEntity entity = users.get(0);
return ConvertUtils.sourceToTarget(entity, SysUserDTO.class);
}
@@ -197,7 +197,7 @@ public class SysUserServiceImpl extends BaseServiceImpl<SysUserDao, SysUserEntit
*/
private String generatePassword() {
StringBuilder password = new StringBuilder();
// 确保包含至少一个数字
password.append("0123456789".charAt(random.nextInt(10)));
// 确保包含至少一个小写字母
@@ -206,12 +206,12 @@ public class SysUserServiceImpl extends BaseServiceImpl<SysUserDao, SysUserEntit
password.append("ABCDEFGHIJKLMNOPQRSTUVWXYZ".charAt(random.nextInt(26)));
// 确保包含至少一个特殊符号
password.append("!@#$%^&*()".charAt(random.nextInt(10)));
// 生成剩余的8个字符
for (int i = 4; i < 12; i++) {
password.append(CHARACTERS.charAt(random.nextInt(CHARACTERS.length())));
}
// 打乱密码中字符的顺序
char[] passwordChars = password.toString().toCharArray();
for (int i = 0; i < passwordChars.length; i++) {
@@ -220,7 +220,7 @@ public class SysUserServiceImpl extends BaseServiceImpl<SysUserDao, SysUserEntit
passwordChars[i] = passwordChars[randomIndex];
passwordChars[randomIndex] = temp;
}
return new String(passwordChars);
}
@@ -129,6 +129,7 @@ public class TimbreServiceImpl extends BaseServiceImpl<TimbreDao, TimbreEntity>
.map(entity -> {
VoiceDTO dto = new VoiceDTO(entity.getId(), entity.getName());
dto.setVoiceDemo(entity.getVoiceDemo());
dto.setLanguages(entity.getLanguages()); // 设置语言类型
dto.setIsClone(false); // 设置为普通音色
return dto;
})
@@ -146,6 +147,7 @@ public class TimbreServiceImpl extends BaseServiceImpl<TimbreDao, TimbreEntity>
voiceDTO.setName(MessageUtils.getMessage(ErrorCode.VOICE_CLONE_PREFIX) + entity.getName());
// 保留从数据库查询到的voiceDemo字段
voiceDTO.setVoiceDemo(entity.getVoiceDemo());
voiceDTO.setLanguages(entity.getLanguages());
voiceDTO.setIsClone(true); // 设置为克隆音色
redisUtils.set(RedisKeys.getTimbreNameById(voiceDTO.getId()), voiceDTO.getName(),
RedisUtils.NOT_EXPIRE);

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