mirror of
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V4.6.9-first commit (#899)
* perf: insert mongo dataset data session * perf: dataset data index * remove delay * rename bill schema * rename bill record * perf: bill table * perf: prompt * perf: sub plan * change the usage count * feat: usage bill * publish usages * doc * 新增团队聊天功能 (#20) * perf: doc * feat 添加标签部分 feat 信息团队标签配置 feat 新增团队同步管理 feat team分享页面 feat 完成team分享页面 feat 实现模糊搜索 style 格式化 fix 修复迷糊匹配 style 样式修改 fix 团队标签功能修复 * fix 修复鉴权功能 * merge 合并代码 * fix 修复引用错误 * fix 修复pr问题 * fix 修复ts格式问题 --------- Co-authored-by: archer <545436317@qq.com> Co-authored-by: liuxingwan <liuxingwan.lxw@alibaba-inc.com> * update extra plan * fix: ts * format * perf: bill field * feat: standard plan * fix: ts * feat 个人账号页面修改 (#22) * feat 添加标签部分 feat 信息团队标签配置 feat 新增团队同步管理 feat team分享页面 feat 完成team分享页面 feat 实现模糊搜索 style 格式化 fix 修复迷糊匹配 style 样式修改 fix 团队标签功能修复 * fix 修复鉴权功能 * merge 合并代码 * fix 修复引用错误 * fix 修复pr问题 * fix 修复ts格式问题 * feat 修改个人账号页 --------- Co-authored-by: liuxingwan <liuxingwan.lxw@alibaba-inc.com> * sub plan page (#23) * fix chunk index; error page text * feat: dataset process Integral prediction * feat: stand plan field * feat: sub plan limit * perf: index * query extension * perf: share link push app name * perf: plan point unit * perf: get sub plan * perf: account page * feat 新增套餐详情弹窗代码 (#24) * merge 合并代码 * fix 新增套餐详情弹框 * fix 修复pr问题 * feat: change http node input to prompt editor (#21) * feat: change http node input to prompt editor * fix * split PromptEditor to HttpInput * Team plans (#25) * perf: pay check * perf: team plan test * plan limit check * replace sensitive text * perf: fix some null * collection null check * perf: plans modal * perf: http module * pacakge (#26) * individuation page and pay modal amount (#27) * feat: individuation page * team chat config * pay modal * plan count and replace invalid chars (#29) * fix: user oneapi * fix: training queue * fix: qa queue * perf: remove space chars * replace invalid chars * change httpinput dropdown menu (#28) * perf: http * reseet free plan * perf: plan code to packages * remove llm config to package * perf: code * perf: faq * fix: get team plan --------- Co-authored-by: yst <77910600+yu-and-liu@users.noreply.github.com> Co-authored-by: liuxingwan <liuxingwan.lxw@alibaba-inc.com> Co-authored-by: heheer <71265218+newfish-cmyk@users.noreply.github.com>
This commit is contained in:
2
.vscode/settings.json
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.vscode/settings.json
vendored
@@ -10,6 +10,6 @@
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"i18n-ally.keystyle": "nested",
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"i18n-ally.sortKeys": true,
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"i18n-ally.keepFulfilled": true,
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"i18n-ally.sourceLanguage": "zh", // 根据此语言文件翻译其他语言文件的变量和内容
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"i18n-ally.sourceLanguage": "en", // 根据此语言文件翻译其他语言文件的变量和内容
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"i18n-ally.displayLanguage": "en", // 显示语言
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}
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@@ -56,7 +56,7 @@ FastGPT 采用了`PostgresSQL`的`PG Vector`插件作为向量检索器,索引
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### 检索方案
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1. 通过`问题补全`实现指代消除和问题扩展,从而增加连续对话的检索能力以及语义丰富度。
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1. 通过`问题优化`实现指代消除和问题扩展,从而增加连续对话的检索能力以及语义丰富度。
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2. 通过`Concat query`来增加`Rerank`连续对话的时,排序的准确性。
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3. 通过`RRF`合并方式,综合多个渠道的检索效果。
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4. 通过`Rerank`来二次排序,提高精度。
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@@ -97,7 +97,7 @@ FastGPT 采用了`PostgresSQL`的`PG Vector`插件作为向量检索器,索引
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#### 结果重排
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利用`ReRank`模型对搜索结果进行重排,绝大多数情况下,可以有效提高搜索结果的准确率。不过,重排模型与问题的完整度(主谓语齐全)有一些关系,通常会先走问题补全后再进行搜索-重排。重排后可以得到一个`0-1`的得分,代表着搜索内容与问题的相关度,该分数通常比向量的得分更加精确,可以根据得分进行过滤。
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利用`ReRank`模型对搜索结果进行重排,绝大多数情况下,可以有效提高搜索结果的准确率。不过,重排模型与问题的完整度(主谓语齐全)有一些关系,通常会先走问题优化后再进行搜索-重排。重排后可以得到一个`0-1`的得分,代表着搜索内容与问题的相关度,该分数通常比向量的得分更加精确,可以根据得分进行过滤。
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FastGPT 会使用 `RRF` 对重排结果、向量搜索结果、全文检索结果进行合并,得到最终的搜索结果。
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@@ -115,7 +115,7 @@ FastGPT 会使用 `RRF` 对重排结果、向量搜索结果、全文检索结
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该值仅在`语义检索`或使用`结果重排`时生效。
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### 问题补全
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### 问题优化
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#### 背景
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@@ -125,7 +125,7 @@ FastGPT 会使用 `RRF` 对重排结果、向量搜索结果、全文检索结
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用户在提问“第二点是什么”的时候,只会去知识库里查找“第二点是什么”,压根查不到内容。实际上需要查询的是“QA结构是什么”。因此我们需要引入一个【问题补全】模块,来对用户当前的问题进行补全,从而使得知识库搜索能够搜索到合适的内容。使用补全后效果如下:
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用户在提问“第二点是什么”的时候,只会去知识库里查找“第二点是什么”,压根查不到内容。实际上需要查询的是“QA结构是什么”。因此我们需要引入一个【问题优化】模块,来对用户当前的问题进行补全,从而使得知识库搜索能够搜索到合适的内容。使用补全后效果如下:
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@@ -13,163 +13,7 @@ weight: 708
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这个配置文件中包含了系统级参数、AI 对话的模型、function 模型等……
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## 4.6.8 以前版本完整配置参数
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**使用时,请务必去除注释!**
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以下配置适用于V4.6.6-alpha版本以后
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```json
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{
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"systemEnv": {
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"vectorMaxProcess": 15, // 向量生成最大进程,结合数据库性能和 key 来设置
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"qaMaxProcess": 15, // QA 生成最大进程,结合数据库性能和 key 来设置
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"pgHNSWEfSearch": 100 // pg vector 索引参数,越大精度高但速度慢
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},
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"chatModels": [ // 对话模型
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{
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"model": "gpt-3.5-turbo-1106",
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"name": "GPT35-1106",
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"inputPrice": 0, // 输入价格。 xx元/1k tokens
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"outputPrice": 0, // 输出价格。 xx元/1k tokens
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"maxContext": 16000, // 最大上下文长度
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"maxResponse": 4000, // 最大回复长度
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"quoteMaxToken": 2000, // 最大引用内容长度
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"maxTemperature": 1.2, // 最大温度值
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"censor": false, // 是否开启敏感词过滤(商业版)
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"vision": false, // 支持图片输入
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"defaultSystemChatPrompt": ""
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},
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{
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"model": "gpt-3.5-turbo-16k",
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"name": "GPT35-16k",
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"maxContext": 16000,
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"maxResponse": 16000,
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"inputPrice": 0,
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"outputPrice": 0,
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"quoteMaxToken": 8000,
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"maxTemperature": 1.2,
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"censor": false,
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"vision": false,
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"defaultSystemChatPrompt": ""
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},
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{
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"model": "gpt-4",
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"name": "GPT4-8k",
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"maxContext": 8000,
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"maxResponse": 8000,
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"inputPrice": 0,
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"outputPrice": 0,
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"quoteMaxToken": 4000,
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"maxTemperature": 1.2,
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"censor": false,
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"vision": false,
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"defaultSystemChatPrompt": ""
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},
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{
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"model": "gpt-4-vision-preview",
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"name": "GPT4-Vision",
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"maxContext": 128000,
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"maxResponse": 4000,
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"inputPrice": 0,
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"outputPrice": 0,
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"quoteMaxToken": 100000,
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"maxTemperature": 1.2,
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"censor": false,
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"vision": true,
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"defaultSystemChatPrompt": ""
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}
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],
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"qaModels": [ // QA 生成模型
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{
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"model": "gpt-3.5-turbo-16k",
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"name": "GPT35-16k",
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"maxContext": 16000,
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"maxResponse": 16000,
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"inputPrice": 0,
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"outputPrice": 0
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}
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],
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"cqModels": [ // 问题分类模型
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{
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"model": "gpt-3.5-turbo-1106",
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"name": "GPT35-1106",
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"maxContext": 16000,
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"maxResponse": 4000,
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"inputPrice": 0,
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"outputPrice": 0,
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"toolChoice": true, // 是否支持openai的 toolChoice, 不支持的模型需要设置为 false,会走提示词生成
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"functionPrompt": ""
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},
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{
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"model": "gpt-4",
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"name": "GPT4-8k",
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"maxContext": 8000,
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"maxResponse": 8000,
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"inputPrice": 0,
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"outputPrice": 0,
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"toolChoice": true,
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"functionPrompt": ""
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}
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],
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"extractModels": [ // 内容提取模型
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{
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"model": "gpt-3.5-turbo-1106",
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"name": "GPT35-1106",
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"maxContext": 16000,
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"maxResponse": 4000,
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"inputPrice": 0,
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"outputPrice": 0,
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"toolChoice": true,
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"functionPrompt": ""
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}
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],
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"qgModels": [ // 生成下一步指引
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{
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"model": "gpt-3.5-turbo-1106",
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"name": "GPT35-1106",
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"maxContext": 1600,
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"maxResponse": 4000,
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"inputPrice": 0,
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"outputPrice": 0
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}
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],
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"vectorModels": [ // 向量模型
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{
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"model": "text-embedding-ada-002",
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"name": "Embedding-2",
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"inputPrice": 0,
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"defaultToken": 700,
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"maxToken": 3000
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}
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],
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"reRankModels": [], // 重排模型,暂时填空数组
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"audioSpeechModels": [
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{
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"model": "tts-1",
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"name": "OpenAI TTS1",
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"inputPrice": 0,
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"baseUrl": "",
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"key": "",
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"voices": [
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{ "label": "Alloy", "value": "alloy", "bufferId": "openai-Alloy" },
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{ "label": "Echo", "value": "echo", "bufferId": "openai-Echo" },
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{ "label": "Fable", "value": "fable", "bufferId": "openai-Fable" },
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{ "label": "Onyx", "value": "onyx", "bufferId": "openai-Onyx" },
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{ "label": "Nova", "value": "nova", "bufferId": "openai-Nova" },
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{ "label": "Shimmer", "value": "shimmer", "bufferId": "openai-Shimmer" }
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]
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}
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],
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"whisperModel": {
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"model": "whisper-1",
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"name": "Whisper1",
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"inputPrice": 0
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}
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}
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```
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## 4.6.8 新配置文件
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## 4.6.8+ 版本新配置文件
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llm模型全部合并
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@@ -189,11 +33,10 @@ llm模型全部合并
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"maxResponse": 4000, // 最大回复
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"quoteMaxToken": 13000, // 最大引用内容
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"maxTemperature": 1.2, // 最大温度
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"inputPrice": 0,
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"outputPrice": 0,
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"charsPointsPrice": 0,
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"censor": false,
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"vision": false, // 是否支持图片输入
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"datasetProcess": false, // 是否设置为知识库处理模型
|
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"datasetProcess": false, // 是否设置为知识库处理模型(QA),务必保证至少有一个为true,否则知识库会报错
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"toolChoice": true, // 是否支持工具选择
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"functionCall": false, // 是否支持函数调用
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"customCQPrompt": "", // 自定义文本分类提示词(不支持工具和函数调用的模型
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@@ -208,8 +51,7 @@ llm模型全部合并
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"maxResponse": 16000,
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"quoteMaxToken": 13000,
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"maxTemperature": 1.2,
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"inputPrice": 0,
|
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"outputPrice": 0,
|
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"charsPointsPrice": 0,
|
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"censor": false,
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"vision": false,
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"datasetProcess": true,
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@@ -227,8 +69,7 @@ llm模型全部合并
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"maxResponse": 4000,
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"quoteMaxToken": 100000,
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"maxTemperature": 1.2,
|
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"inputPrice": 0,
|
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"outputPrice": 0,
|
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"charsPointsPrice": 0,
|
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"censor": false,
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"vision": false,
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"datasetProcess": false,
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@@ -246,10 +87,9 @@ llm模型全部合并
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"maxResponse": 4000,
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"quoteMaxToken": 100000,
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"maxTemperature": 1.2,
|
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"inputPrice": 0,
|
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"outputPrice": 0,
|
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"charsPointsPrice": 0,
|
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"censor": false,
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"vision": false,
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"vision": true,
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"datasetProcess": false,
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"toolChoice": true,
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"functionCall": false,
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@@ -263,8 +103,7 @@ llm模型全部合并
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{
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"model": "text-embedding-ada-002",
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"name": "Embedding-2",
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"inputPrice": 0,
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"outputPrice": 0,
|
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"charsPointsPrice": 0,
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"defaultToken": 700,
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"maxToken": 3000,
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"weight": 100,
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@@ -276,8 +115,7 @@ llm模型全部合并
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{
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"model": "tts-1",
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"name": "OpenAI TTS1",
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"inputPrice": 0,
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"outputPrice": 0,
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"charsPointsPrice": 0,
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"voices": [
|
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{ "label": "Alloy", "value": "alloy", "bufferId": "openai-Alloy" },
|
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{ "label": "Echo", "value": "echo", "bufferId": "openai-Echo" },
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@@ -291,8 +129,7 @@ llm模型全部合并
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"whisperModel": {
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"model": "whisper-1",
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"name": "Whisper1",
|
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"inputPrice": 0,
|
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"outputPrice": 0
|
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"charsPointsPrice": 0
|
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}
|
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}
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```
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@@ -313,7 +150,7 @@ llm模型全部合并
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{
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"model": "bge-reranker-base", // 随意
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"name": "检索重排-base", // 随意
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"inputPrice": 0,
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"charsPointsPrice": 0,
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"requestUrl": "{{host}}/api/v1/rerank",
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"requestAuth": "安全凭证,已自动补 Bearer"
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}
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|
@@ -110,6 +110,7 @@ curl -O https://raw.githubusercontent.com/labring/FastGPT/main/projects/app/data
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cd 项目目录
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# 创建 mongo 密钥
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openssl rand -base64 756 > ./mongodb.key
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# 600不行可以用chmod 999
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chmod 600 ./mongodb.key
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chown 999:root ./mongodb.key
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# 启动容器
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|
@@ -116,8 +116,7 @@ CHAT_API_KEY=sk-xxxxxx
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"maxResponse": 4000, // 最大回复
|
||||
"quoteMaxToken": 13000, // 最大引用内容
|
||||
"maxTemperature": 1.2, // 最大温度
|
||||
"inputPrice": 0,
|
||||
"outputPrice": 0,
|
||||
"charsPointsPrice": 0,
|
||||
"censor": false,
|
||||
"vision": false, // 是否支持图片输入
|
||||
"datasetProcess": false, // 是否设置为知识库处理模型
|
||||
|
@@ -13,12 +13,25 @@ weight: 853
|
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|
||||
|
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## 创建训练订单
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## 创建训练订单(4.6.9地址发生改动)
|
||||
|
||||
{{< tabs tabTotal="2" >}}
|
||||
{{< tab tabName="请求示例" >}}
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||||
{{< markdownify >}}
|
||||
|
||||
**新例子**
|
||||
|
||||
```bash
|
||||
curl --location --request POST 'https://api.fastgpt.in/api/support/wallet/usage/createTrainingUsage' \
|
||||
--header 'Authorization: Bearer {{apikey}}' \
|
||||
--header 'Content-Type: application/json' \
|
||||
--data-raw '{
|
||||
"name": "可选,自定义订单名称,例如:文档训练-fastgpt.docx"
|
||||
}'
|
||||
```
|
||||
|
||||
**x例子**
|
||||
|
||||
```bash
|
||||
curl --location --request POST 'https://api.fastgpt.in/api/support/wallet/bill/createTrainingBill' \
|
||||
--header 'Authorization: Bearer {{apikey}}' \
|
||||
@@ -154,7 +167,7 @@ curl --location --request GET 'http://localhost:3000/api/core/dataset/list?paren
|
||||
"vectorModel": {
|
||||
"model": "text-embedding-ada-002",
|
||||
"name": "Embedding-2",
|
||||
"inputPrice": 0,
|
||||
"charsPointsPrice": 0,
|
||||
"defaultToken": 512,
|
||||
"maxToken": 8000,
|
||||
"weight": 100
|
||||
@@ -213,7 +226,7 @@ curl --location --request GET 'http://localhost:3000/api/core/dataset/detail?id=
|
||||
"vectorModel": {
|
||||
"model": "text-embedding-ada-002",
|
||||
"name": "Embedding-2",
|
||||
"inputPrice": 0,
|
||||
"charsPointsPrice": 0,
|
||||
"defaultToken": 512,
|
||||
"maxToken": 8000,
|
||||
"weight": 100
|
||||
@@ -223,8 +236,7 @@ curl --location --request GET 'http://localhost:3000/api/core/dataset/detail?id=
|
||||
"name": "FastAI-16k",
|
||||
"maxContext": 16000,
|
||||
"maxResponse": 16000,
|
||||
"inputPrice": 0,
|
||||
"outputPrice": 0
|
||||
"charsPointsPrice": 0
|
||||
},
|
||||
"intro": "",
|
||||
"permission": "private",
|
||||
@@ -800,6 +812,33 @@ curl --location --request DELETE 'http://localhost:3000/api/core/dataset/collect
|
||||
|
||||
## 数据
|
||||
|
||||
### 数据的结构
|
||||
|
||||
**Data结构**
|
||||
|
||||
| 字段 | 类型 | 说明 | 必填 |
|
||||
| --- | --- | --- | --- |
|
||||
| teamId | String | 团队ID | ✅ |
|
||||
| tmbId | String | 成员ID | ✅ |
|
||||
| datasetId | String | 知识库ID | ✅ |
|
||||
| collectionId | String | 集合ID | ✅ |
|
||||
| q | String | 主要数据 | ✅ |
|
||||
| a | String | 辅助数据 | ✖ |
|
||||
| fullTextToken | String | 分词 | ✖ |
|
||||
| indexes | Index[] | 向量索引 | ✅ |
|
||||
| updateTime | Date | 更新时间 | ✅ |
|
||||
| chunkIndex | Number | 分块下表 | ✖ |
|
||||
|
||||
**Index结构**
|
||||
|
||||
每组数据的自定义索引最多5个
|
||||
|
||||
| 字段 | 类型 | 说明 | 必填 |
|
||||
| --- | --- | --- | --- |
|
||||
| defaultIndex | Boolean | 是否为默认索引 | ✅ |
|
||||
| dataId | String | 关联的向量ID | ✅ |
|
||||
| text | String | 文本内容 | ✅ |
|
||||
|
||||
### 为集合批量添加添加数据
|
||||
|
||||
注意,每次最多推送 200 组数据。
|
||||
@@ -825,11 +864,14 @@ curl --location --request POST 'https://api.fastgpt.in/api/core/dataset/data/pus
|
||||
{
|
||||
"q": "你会什么?",
|
||||
"a": "我什么都会",
|
||||
"indexes": [{
|
||||
"defaultIndex": false,
|
||||
"type":"custom",
|
||||
"text":"自定义索引,不使用默认索引"
|
||||
}]
|
||||
"indexes": [
|
||||
{
|
||||
"text":"自定义索引1"
|
||||
},
|
||||
{
|
||||
"text":"自定义索引2"
|
||||
}
|
||||
]
|
||||
}
|
||||
]
|
||||
}'
|
||||
@@ -850,7 +892,7 @@ curl --location --request POST 'https://api.fastgpt.in/api/core/dataset/data/pus
|
||||
- data:(具体数据)
|
||||
- q: 主要数据(必填)
|
||||
- a: 辅助数据(选填)
|
||||
- indexes: 自定义索引(选填),不传入则默认使用q和a构建索引。也可以传入
|
||||
- indexes: 自定义索引(选填)。可以不传或者传空数组,默认都会使用q和a组成一个索引。
|
||||
{{% /alert %}}
|
||||
|
||||
{{< /markdownify >}}
|
||||
@@ -866,7 +908,6 @@ curl --location --request POST 'https://api.fastgpt.in/api/core/dataset/data/pus
|
||||
"data": {
|
||||
"insertLen": 1, // 最终插入成功的数量
|
||||
"overToken": [], // 超出 token 的
|
||||
|
||||
"repeat": [], // 重复的数量
|
||||
"error": [] // 其他错误
|
||||
}
|
||||
@@ -1050,7 +1091,16 @@ curl --location --request PUT 'http://localhost:3000/api/core/dataset/data/updat
|
||||
"id":"65abd4b29d1448617cba61db",
|
||||
"q":"测试111",
|
||||
"a":"sss",
|
||||
"indexes":[]
|
||||
"indexes":[
|
||||
{
|
||||
"dataId": "xxx",
|
||||
"defaultIndex":false,
|
||||
"text":"自定义索引1"
|
||||
},
|
||||
{
|
||||
"text":"修改后的自定义索引2。(会删除原来的自定义索引2,并插入新的自定义索引2)"
|
||||
}
|
||||
]
|
||||
}'
|
||||
```
|
||||
|
||||
@@ -1064,7 +1114,7 @@ curl --location --request PUT 'http://localhost:3000/api/core/dataset/data/updat
|
||||
- id: 数据的id
|
||||
- q: 主要数据(选填)
|
||||
- a: 辅助数据(选填)
|
||||
- indexes: 自定义索引(选填),类型参考`为集合批量添加添加数据`,建议直接不传。更新q,a后,如果有默认索引,则会直接更新默认索引。
|
||||
- indexes: 自定义索引(选填),类型参考`为集合批量添加添加数据`。如果创建时候有自定义索引,
|
||||
{{% /alert %}}
|
||||
|
||||
{{< /markdownify >}}
|
||||
|
@@ -169,8 +169,6 @@ curl --location --request POST '{{host}}/shareAuth/start' \
|
||||
|
||||
响应值与[chat 接口格式相同](/docs/development/openapi/chat/#响应),仅多了一个`token`。
|
||||
|
||||
可以重点关注`responseData`里的`price`值,`price`与实际价格的倍率为`100000`,即 100000=1元。
|
||||
|
||||
```bash
|
||||
curl --location --request POST '{{host}}/shareAuth/finish' \
|
||||
--header 'Content-Type: application/json' \
|
||||
@@ -178,72 +176,117 @@ curl --location --request POST '{{host}}/shareAuth/finish' \
|
||||
"token": "{{authToken}}",
|
||||
"responseData": [
|
||||
{
|
||||
"moduleName": "KB Search",
|
||||
"price": 1.2000000000000002,
|
||||
"model": "Embedding-2",
|
||||
"tokens": 6,
|
||||
"similarity": 0.61,
|
||||
"limit": 3
|
||||
"moduleName": "core.module.template.Dataset search",
|
||||
"moduleType": "datasetSearchNode",
|
||||
"totalPoints": 1.5278,
|
||||
"query": "导演是谁\n《铃芽之旅》的导演是谁?\n这部电影的导演是谁?\n谁是《铃芽之旅》的导演?",
|
||||
"model": "Embedding-2(旧版,不推荐使用)",
|
||||
"charsLength": 1524,
|
||||
"similarity": 0.83,
|
||||
"limit": 400,
|
||||
"searchMode": "embedding",
|
||||
"searchUsingReRank": false,
|
||||
"extensionModel": "FastAI-4k",
|
||||
"extensionResult": "《铃芽之旅》的导演是谁?\n这部电影的导演是谁?\n谁是《铃芽之旅》的导演?",
|
||||
"runningTime": 2.15
|
||||
},
|
||||
{
|
||||
"moduleName": "AI Chat",
|
||||
"price": 454.5,
|
||||
"moduleName": "AI 对话",
|
||||
"moduleType": "chatNode",
|
||||
"totalPoints": 0.593,
|
||||
"model": "FastAI-4k",
|
||||
"tokens": 303,
|
||||
"question": "导演是谁",
|
||||
"answer": "电影《铃芽之旅》的导演是新海诚。",
|
||||
"maxToken": 2050,
|
||||
"charsLength": 593,
|
||||
"query": "导演是谁",
|
||||
"maxToken": 2000,
|
||||
"quoteList": [
|
||||
{
|
||||
"dataset_id": "646627f4f7b896cfd8910e38",
|
||||
"id": "8099",
|
||||
"q": "本作的主人公是谁?",
|
||||
"a": "本作的主人公是名叫铃芽的少女。",
|
||||
"source": "手动修改"
|
||||
},
|
||||
{
|
||||
"dataset_id": "646627f4f7b896cfd8910e38",
|
||||
"id": "8686",
|
||||
"q": "电影《铃芽之旅》男主角是谁?",
|
||||
"a": "电影《铃芽之旅》男主角是宗像草太,由松村北斗配音。",
|
||||
"source": ""
|
||||
},
|
||||
{
|
||||
"dataset_id": "646627f4f7b896cfd8910e38",
|
||||
"id": "19339",
|
||||
"q": "电影《铃芽之旅》的导演是谁?22",
|
||||
"id": "65bb346a53698398479a8854",
|
||||
"q": "导演是谁?",
|
||||
"a": "电影《铃芽之旅》的导演是新海诚。",
|
||||
"source": "手动修改"
|
||||
"chunkIndex": 0,
|
||||
"datasetId": "65af9b947916ae0e47c834d2",
|
||||
"collectionId": "65bb345c53698398479a868f",
|
||||
"sourceName": "dataset - 2024-01-23T151114.198.csv",
|
||||
"sourceId": "65bb345b53698398479a868d",
|
||||
"score": [
|
||||
{
|
||||
"type": "embedding",
|
||||
"value": 0.9377183318138123,
|
||||
"index": 0
|
||||
},
|
||||
{
|
||||
"type": "rrf",
|
||||
"value": 0.06557377049180328,
|
||||
"index": 0
|
||||
}
|
||||
]
|
||||
}
|
||||
],
|
||||
"completeMessages": [
|
||||
{
|
||||
"obj": "System",
|
||||
"value": "下面是知识库内容:\n1. [本作的主人公是谁?\n本作的主人公是名叫铃芽的少女。]\n2. [电影《铃芽之旅》男主角是谁?\n电影《铃芽之旅》男主角是宗像草太,由松村北斗配音。]\n3. [电影《铃芽之旅》的导演是谁?22\n电影《铃芽之旅》的导演是新海诚。]\n"
|
||||
},
|
||||
{
|
||||
"obj": "System",
|
||||
"value": "1.请记住,你的身份是百度的下一代知识增强语言模型,能够完全根据知识库提供的内容回答问题。\n\n2. 你忘记了关于电影《铃芽之旅》以外的内容。"
|
||||
},
|
||||
{
|
||||
"obj": "System",
|
||||
"value": "你仅回答关于电影《玲芽之旅》的问题,其余问题直接回复: 我不清楚。"
|
||||
},
|
||||
"historyPreview": [
|
||||
{
|
||||
"obj": "Human",
|
||||
"value": "导演是谁"
|
||||
"value": "使用 <Data></Data> 标记中的内容作为你的知识:\n\n<Data>\n导演是谁?\n电影《铃芽之旅》的导演是新海诚。\n------\n电影《铃芽之旅》的编剧是谁?22\n新海诚是本片的编剧。\n------\n电影《铃芽之旅》的女主角是谁?\n电影的女主角是铃芽。\n------\n电影《铃芽之旅》的制作团队中有哪位著名人士?2\n川村元气是本片的制作团队成员之一。\n------\n你是谁?\n我是电影《铃芽之旅》助手\n------\n电影《铃芽之旅》男主角是谁?\n电影《铃芽之旅》男主角是宗像草太,由松村北斗配音。\n------\n电影《铃芽之旅》的作者新海诚写了一本小说,叫什么名字?\n小说名字叫《铃芽之旅》。\n------\n电影《铃芽之旅》的女主角是谁?\n电影《铃芽之旅》的女主角是岩户铃芽,由原菜乃华配音。\n------\n电影《铃芽之旅》的故事背景是什么?\n日本\n------\n谁担任电影《铃芽之旅》中岩户环的配音?\n深津绘里担任电影《铃芽之旅》中岩户环的配音。\n</Data>\n\n回答要求:\n- 如果你不清楚答案,你需要澄清。\n- 避免提及你是从 <Data></Data> 获取的知识。\n- 保持答案与 <Data></Data> 中描述的一致。\n- 使用 Markdown 语法优化回答格式。\n- 使用与问题相同的语言回答。\n\n问题:\"\"\"导演是谁\"\"\""
|
||||
},
|
||||
{
|
||||
"obj": "AI",
|
||||
"value": "电影《铃芽之旅》的导演是新海诚。"
|
||||
}
|
||||
]
|
||||
],
|
||||
"contextTotalLen": 2,
|
||||
"runningTime": 1.32
|
||||
}
|
||||
]
|
||||
|
||||
|
||||
}'
|
||||
```
|
||||
|
||||
**responseData 完整字段说明:**
|
||||
|
||||
```ts
|
||||
type ResponseType = {
|
||||
moduleType: `${FlowNodeTypeEnum}`; // 模块类型
|
||||
moduleName: string; // 模块名
|
||||
moduleLogo?: string; // logo
|
||||
runningTime?: number; // 运行时间
|
||||
query?: string; // 用户问题/检索词
|
||||
textOutput?: string; // 文本输出
|
||||
|
||||
charsLength?: number; // 上下文总字数
|
||||
model?: string; // 使用到的模型
|
||||
contextTotalLen?: number; // 上下文总长度
|
||||
totalPoints?: number; // 总消耗AI积分
|
||||
|
||||
temperature?: number; // 温度
|
||||
maxToken?: number; // 模型的最大token
|
||||
quoteList?: SearchDataResponseItemType[]; // 引用列表
|
||||
historyPreview?: ChatItemType[]; // 上下文预览(历史记录会被裁剪)
|
||||
|
||||
similarity?: number; // 最低相关度
|
||||
limit?: number; // 引用上限token
|
||||
searchMode?: `${DatasetSearchModeEnum}`; // 搜索模式
|
||||
searchUsingReRank?: boolean; // 是否使用rerank
|
||||
extensionModel?: string; // 问题扩展模型
|
||||
extensionResult?: string; // 问题扩展结果
|
||||
extensionCharsLength?: number; // 问题扩展总字符长度
|
||||
|
||||
cqList?: ClassifyQuestionAgentItemType[]; // 分类问题列表
|
||||
cqResult?: string; // 分类问题结果
|
||||
|
||||
extractDescription?: string; // 内容提取描述
|
||||
extractResult?: Record<string, any>; // 内容提取结果
|
||||
|
||||
params?: Record<string, any>; // HTTP模块params
|
||||
body?: Record<string, any>; // HTTP模块body
|
||||
headers?: Record<string, any>; // HTTP模块headers
|
||||
httpResult?: Record<string, any>; // HTTP模块结果
|
||||
|
||||
pluginOutput?: Record<string, any>; // 插件输出
|
||||
pluginDetail?: ChatHistoryItemResType[]; // 插件详情
|
||||
|
||||
tfSwitchResult?: boolean; // 判断器结果
|
||||
}
|
||||
```
|
||||
|
||||
## 实践案例
|
||||
|
||||
|
@@ -15,13 +15,13 @@ weight: 831
|
||||
|
||||
1. 主要是修改模型的`functionCall`字段,改成`toolChoice`即可。设置为`true`的模型,会默认走 openai 的 tools 模式;未设置或设置为`false`的,会走提示词生成模式。
|
||||
|
||||
问题补全模型与内容提取模型使用同一组配置。
|
||||
问题优化模型与内容提取模型使用同一组配置。
|
||||
|
||||
2. 增加 `"ReRankModels": []`
|
||||
|
||||
## V4.6.5 功能介绍
|
||||
|
||||
1. 新增 - [问题补全模块](/docs/workflow/modules/coreferenceresolution/)
|
||||
1. 新增 - [问题优化模块](/docs/workflow/modules/coreferenceresolution/)
|
||||
2. 新增 - [文本编辑模块](/docs/workflow/modules/text_editor/)
|
||||
3. 新增 - [判断器模块](/docs/workflow/modules/tfswitch/)
|
||||
4. 新增 - [自定义反馈模块](/docs/workflow/modules/custom_feedback/)
|
||||
|
@@ -11,7 +11,7 @@ weight: 829
|
||||
|
||||
发起 1 个 HTTP 请求 ({{rootkey}} 替换成环境变量里的 `rootkey`,{{host}} 替换成自己域名)
|
||||
|
||||
1. https://xxxxx/api/admin/initv464
|
||||
1. https://xxxxx/api/admin/initv467
|
||||
|
||||
```bash
|
||||
curl --location --request POST 'https://{{host}}/api/admin/initv467' \
|
||||
|
@@ -36,6 +36,7 @@ mongo:
|
||||
cd 项目目录
|
||||
# 创建 mongo 密钥
|
||||
openssl rand -base64 756 > ./mongodb.key
|
||||
# 600不行可以用chmod 999
|
||||
chmod 600 ./mongodb.key
|
||||
chown 999:root ./mongodb.key
|
||||
# 重启 Mongo
|
||||
|
30
docSite/content/docs/development/upgrading/469.md
Normal file
30
docSite/content/docs/development/upgrading/469.md
Normal file
@@ -0,0 +1,30 @@
|
||||
---
|
||||
title: 'V4.6.9(进行中)'
|
||||
description: 'FastGPT V4.6.9更新说明'
|
||||
icon: 'upgrade'
|
||||
draft: false
|
||||
toc: true
|
||||
weight: 827
|
||||
---
|
||||
|
||||
## 初始化脚本
|
||||
|
||||
从任意终端,发起 1 个 HTTP 请求。其中 {{rootkey}} 替换成环境变量里的 `rootkey`;{{host}} 替换成自己域名
|
||||
|
||||
```bash
|
||||
curl --location --request POST 'https://{{host}}/api/init/v469' \
|
||||
--header 'rootkey: {{rootkey}}' \
|
||||
--header 'Content-Type: application/json'
|
||||
```
|
||||
|
||||
会重置计量表。
|
||||
|
||||
|
||||
## V4.6.9 更新说明
|
||||
|
||||
1. 新增 - 完善了HTTP模块的变量提示。
|
||||
2. 新增 - HTTP模块支持OpenAI单接口导入。
|
||||
3. 优化 - 问题补全。增加英文类型。同时可以设置为单独模块,方便复用。
|
||||
4. 优化 - 重写了计量模式
|
||||
5. 修复 - 标注功能。
|
||||
6. 修复 - qa生成线程计数错误。
|
@@ -66,7 +66,7 @@ Body:
|
||||
|
||||
Headers:
|
||||
|
||||
`Authorization: sk-xxx`
|
||||
`Authorization: Bearer sk-xxx`
|
||||
|
||||
Response:
|
||||
|
||||
|
@@ -135,7 +135,7 @@ export default async function (ctx: FunctionContext) {
|
||||
},
|
||||
{
|
||||
"key": "model",
|
||||
"type": "selectExtractModel",
|
||||
"type": "selectLLMModel",
|
||||
"valueType": "string",
|
||||
"label": "core.module.input.label.LLM",
|
||||
"required": true,
|
||||
@@ -264,7 +264,7 @@ export default async function (ctx: FunctionContext) {
|
||||
},
|
||||
{
|
||||
"key": "model",
|
||||
"type": "selectChatModel",
|
||||
"type": "selectLLMModel",
|
||||
"label": "core.module.input.label.aiModel",
|
||||
"required": true,
|
||||
"valueType": "string",
|
||||
@@ -635,7 +635,7 @@ export default async function (ctx: FunctionContext) {
|
||||
},
|
||||
{
|
||||
"key": "model",
|
||||
"type": "selectChatModel",
|
||||
"type": "selectLLMModel",
|
||||
"label": "core.module.input.label.aiModel",
|
||||
"required": true,
|
||||
"valueType": "string",
|
||||
|
@@ -139,7 +139,7 @@ HTTP 模块允许你调用任意 GET/POST 类型的 HTTP 接口,从而实现
|
||||
},
|
||||
{
|
||||
"key": "model",
|
||||
"type": "selectExtractModel",
|
||||
"type": "selectLLMModel",
|
||||
"valueType": "string",
|
||||
"label": "core.module.input.label.LLM",
|
||||
"required": true,
|
||||
@@ -401,7 +401,7 @@ HTTP 模块允许你调用任意 GET/POST 类型的 HTTP 接口,从而实现
|
||||
},
|
||||
{
|
||||
"key": "model",
|
||||
"type": "selectCQModel",
|
||||
"type": "selectLLMModel",
|
||||
"valueType": "string",
|
||||
"label": "core.module.input.label.Classify model",
|
||||
"required": true,
|
||||
@@ -614,7 +614,7 @@ HTTP 模块允许你调用任意 GET/POST 类型的 HTTP 接口,从而实现
|
||||
},
|
||||
{
|
||||
"key": "model",
|
||||
"type": "selectChatModel",
|
||||
"type": "selectLLMModel",
|
||||
"label": "core.module.input.label.aiModel",
|
||||
"required": true,
|
||||
"valueType": "string",
|
||||
@@ -835,7 +835,7 @@ HTTP 模块允许你调用任意 GET/POST 类型的 HTTP 接口,从而实现
|
||||
},
|
||||
{
|
||||
"key": "model",
|
||||
"type": "selectExtractModel",
|
||||
"type": "selectLLMModel",
|
||||
"valueType": "string",
|
||||
"label": "core.module.input.label.LLM",
|
||||
"required": true,
|
||||
|
@@ -1,6 +1,6 @@
|
||||
---
|
||||
title: "问题补全(已合并到知识库搜索)"
|
||||
description: "问题补全模块介绍和使用"
|
||||
title: "问题优化(已合并到知识库搜索)"
|
||||
description: "问题优化模块介绍和使用"
|
||||
icon: "input"
|
||||
draft: false
|
||||
toc: true
|
||||
@@ -23,7 +23,7 @@ weight: 364
|
||||
|
||||

|
||||
|
||||
用户在提问“第二点是什么”的时候,只会去知识库里查找“第二点是什么”,压根查不到内容。实际上需要查询的是“QA结构是什么”。因此我们需要引入一个【问题补全】模块,来对用户当前的问题进行补全,从而使得知识库搜索能够搜索到合适的内容。使用补全后效果如下:
|
||||
用户在提问“第二点是什么”的时候,只会去知识库里查找“第二点是什么”,压根查不到内容。实际上需要查询的是“QA结构是什么”。因此我们需要引入一个【问题优化】模块,来对用户当前的问题进行补全,从而使得知识库搜索能够搜索到合适的内容。使用补全后效果如下:
|
||||
|
||||

|
||||
|
||||
|
@@ -3,11 +3,25 @@ import { ErrType } from '../errorCode';
|
||||
/* team: 500000 */
|
||||
export enum TeamErrEnum {
|
||||
teamOverSize = 'teamOverSize',
|
||||
unAuthTeam = 'unAuthTeam'
|
||||
unAuthTeam = 'unAuthTeam',
|
||||
aiPointsNotEnough = 'aiPointsNotEnough',
|
||||
datasetSizeNotEnough = 'datasetSizeNotEnough',
|
||||
datasetAmountNotEnough = 'datasetAmountNotEnough',
|
||||
appAmountNotEnough = 'appAmountNotEnough',
|
||||
pluginAmountNotEnough = 'pluginAmountNotEnough',
|
||||
websiteSyncNotEnough = 'websiteSyncNotEnough',
|
||||
reRankNotEnough = 'reRankNotEnough'
|
||||
}
|
||||
const teamErr = [
|
||||
{ statusText: TeamErrEnum.teamOverSize, message: 'error.team.overSize' },
|
||||
{ statusText: TeamErrEnum.unAuthTeam, message: '无权操作该团队' }
|
||||
{ statusText: TeamErrEnum.unAuthTeam, message: '无权操作该团队' },
|
||||
{ statusText: TeamErrEnum.aiPointsNotEnough, message: 'AI积分已用完~' },
|
||||
{ statusText: TeamErrEnum.datasetSizeNotEnough, message: '知识库容量不足,请先扩容~' },
|
||||
{ statusText: TeamErrEnum.datasetAmountNotEnough, message: '知识库数量已达上限~' },
|
||||
{ statusText: TeamErrEnum.appAmountNotEnough, message: '应用数量已达上限~' },
|
||||
{ statusText: TeamErrEnum.pluginAmountNotEnough, message: '插件数量已达上限~' },
|
||||
{ statusText: TeamErrEnum.websiteSyncNotEnough, message: '无权使用Web站点同步~' },
|
||||
{ statusText: TeamErrEnum.reRankNotEnough, message: '无权使用检索重排~' }
|
||||
];
|
||||
export default teamErr.reduce((acc, cur, index) => {
|
||||
return {
|
||||
|
@@ -1,7 +1,7 @@
|
||||
import { replaceSensitiveLink } from '../string/tools';
|
||||
import { replaceSensitiveText } from '../string/tools';
|
||||
|
||||
export const getErrText = (err: any, def = '') => {
|
||||
const msg: string = typeof err === 'string' ? err : err?.message || def || '';
|
||||
msg && console.log('error =>', msg);
|
||||
return replaceSensitiveLink(msg);
|
||||
return replaceSensitiveText(msg);
|
||||
};
|
||||
|
4
packages/global/common/math/tools.ts
Normal file
4
packages/global/common/math/tools.ts
Normal file
@@ -0,0 +1,4 @@
|
||||
export const formatNumber = (num: number, digit = 1e4) => Math.round(num * digit) / digit;
|
||||
|
||||
export const formatNumber2Million = (num: number) => Math.round(num / 1000000);
|
||||
export const formatNumber2Thousand = (num: number) => Math.round(num / 1000);
|
@@ -2,3 +2,4 @@ import dayjs from 'dayjs';
|
||||
|
||||
export const formatTime2YMDHM = (time?: Date) =>
|
||||
time ? dayjs(time).format('YYYY-MM-DD HH:mm') : '';
|
||||
export const formatTime2YMD = (time?: Date) => (time ? dayjs(time).format('YYYY-MM-DD') : '');
|
||||
|
@@ -38,10 +38,14 @@ export function replaceVariable(text: string, obj: Record<string, string | numbe
|
||||
return text || '';
|
||||
}
|
||||
|
||||
/* replace sensitive link */
|
||||
export const replaceSensitiveLink = (text: string) => {
|
||||
const urlRegex = /(?<=https?:\/\/)[^\s]+/g;
|
||||
return text.replace(urlRegex, 'xxx');
|
||||
/* replace sensitive text */
|
||||
export const replaceSensitiveText = (text: string) => {
|
||||
// 1. http link
|
||||
text = text.replace(/(?<=https?:\/\/)[^\s]+/g, 'xxx');
|
||||
// 2. nx-xxx 全部替换成xxx
|
||||
text = text.replace(/ns-[\w-]+/g, 'xxx');
|
||||
|
||||
return text;
|
||||
};
|
||||
|
||||
export const getNanoid = (size = 12) => {
|
||||
|
@@ -30,6 +30,7 @@ export type FastGPTFeConfigsType = {
|
||||
show_pay?: boolean;
|
||||
show_openai_account?: boolean;
|
||||
show_promotion?: boolean;
|
||||
show_team_chat?: boolean;
|
||||
hide_app_flow?: boolean;
|
||||
concatMd?: string;
|
||||
docUrl?: string;
|
||||
|
15
packages/global/core/ai/model.d.ts
vendored
15
packages/global/core/ai/model.d.ts
vendored
@@ -6,8 +6,7 @@ export type LLMModelItemType = {
|
||||
quoteMaxToken: number;
|
||||
maxTemperature: number;
|
||||
|
||||
inputPrice: number;
|
||||
outputPrice: number;
|
||||
charsPointsPrice: number; // 1k chars=n points
|
||||
|
||||
censor?: boolean;
|
||||
vision?: boolean;
|
||||
@@ -27,8 +26,7 @@ export type VectorModelItemType = {
|
||||
model: string;
|
||||
name: string;
|
||||
defaultToken: number;
|
||||
inputPrice: number;
|
||||
outputPrice: number;
|
||||
charsPointsPrice: number;
|
||||
maxToken: number;
|
||||
weight: number;
|
||||
hidden?: boolean;
|
||||
@@ -38,8 +36,7 @@ export type VectorModelItemType = {
|
||||
export type ReRankModelItemType = {
|
||||
model: string;
|
||||
name: string;
|
||||
inputPrice: number;
|
||||
outputPrice?: number;
|
||||
charsPointsPrice: number;
|
||||
requestUrl?: string;
|
||||
requestAuth?: string;
|
||||
};
|
||||
@@ -47,14 +44,12 @@ export type ReRankModelItemType = {
|
||||
export type AudioSpeechModelType = {
|
||||
model: string;
|
||||
name: string;
|
||||
inputPrice: number;
|
||||
outputPrice?: number;
|
||||
charsPointsPrice: number;
|
||||
voices: { label: string; value: string; bufferId: string }[];
|
||||
};
|
||||
|
||||
export type WhisperModelType = {
|
||||
model: string;
|
||||
name: string;
|
||||
inputPrice: number;
|
||||
outputPrice?: number;
|
||||
charsPointsPrice: number; // 60s = n points
|
||||
};
|
||||
|
@@ -2,14 +2,13 @@ import type { LLMModelItemType, VectorModelItemType } from './model.d';
|
||||
|
||||
export const defaultQAModels: LLMModelItemType[] = [
|
||||
{
|
||||
model: 'gpt-3.5-turbo-16k',
|
||||
name: 'gpt-3.5-turbo-16k',
|
||||
model: 'gpt-3.5-turbo',
|
||||
name: 'gpt-3.5-turbo',
|
||||
maxContext: 16000,
|
||||
maxResponse: 16000,
|
||||
quoteMaxToken: 13000,
|
||||
maxTemperature: 1.2,
|
||||
inputPrice: 0,
|
||||
outputPrice: 0,
|
||||
charsPointsPrice: 0,
|
||||
censor: false,
|
||||
vision: false,
|
||||
datasetProcess: true,
|
||||
@@ -26,8 +25,7 @@ export const defaultVectorModels: VectorModelItemType[] = [
|
||||
{
|
||||
model: 'text-embedding-ada-002',
|
||||
name: 'Embedding-2',
|
||||
inputPrice: 0,
|
||||
outputPrice: 0,
|
||||
charsPointsPrice: 0,
|
||||
defaultToken: 500,
|
||||
maxToken: 3000,
|
||||
weight: 100
|
||||
|
1
packages/global/core/app/api.d.ts
vendored
1
packages/global/core/app/api.d.ts
vendored
@@ -17,6 +17,7 @@ export interface AppUpdateParams {
|
||||
intro?: string;
|
||||
modules?: AppSchema['modules'];
|
||||
permission?: AppSchema['permission'];
|
||||
teamTags?: AppSchema['teamTags'];
|
||||
}
|
||||
|
||||
export type FormatForm2ModulesProps = {
|
||||
|
3
packages/global/core/app/type.d.ts
vendored
3
packages/global/core/app/type.d.ts
vendored
@@ -5,7 +5,7 @@ import type { AIChatModuleProps, DatasetModuleProps } from '../module/node/type.
|
||||
import { VariableInputEnum } from '../module/constants';
|
||||
import { SelectedDatasetType } from '../module/api';
|
||||
import { DatasetSearchModeEnum } from '../dataset/constants';
|
||||
|
||||
import { TeamTagsSchema as TeamTagsSchemaType } from '@fastgpt/global/support/user/team/type.d';
|
||||
export interface AppSchema {
|
||||
_id: string;
|
||||
userId: string;
|
||||
@@ -20,6 +20,7 @@ export interface AppSchema {
|
||||
modules: ModuleItemType[];
|
||||
permission: `${PermissionTypeEnum}`;
|
||||
inited?: boolean;
|
||||
teamTags: [string];
|
||||
}
|
||||
|
||||
export type AppListItemType = {
|
||||
|
@@ -27,7 +27,8 @@ export enum ChatSourceEnum {
|
||||
test = 'test',
|
||||
online = 'online',
|
||||
share = 'share',
|
||||
api = 'api'
|
||||
api = 'api',
|
||||
team = 'team'
|
||||
}
|
||||
export const ChatSourceMap = {
|
||||
[ChatSourceEnum.test]: {
|
||||
@@ -41,6 +42,9 @@ export const ChatSourceMap = {
|
||||
},
|
||||
[ChatSourceEnum.api]: {
|
||||
name: 'core.chat.logs.api'
|
||||
},
|
||||
[ChatSourceEnum.team]: {
|
||||
name: 'core.chat.logs.team'
|
||||
}
|
||||
};
|
||||
|
||||
|
29
packages/global/core/chat/type.d.ts
vendored
29
packages/global/core/chat/type.d.ts
vendored
@@ -4,6 +4,7 @@ import { ChatRoleEnum, ChatSourceEnum, ChatStatusEnum } from './constants';
|
||||
import { FlowNodeTypeEnum } from '../module/node/constant';
|
||||
import { ModuleOutputKeyEnum } from '../module/constants';
|
||||
import { AppSchema } from '../app/type';
|
||||
import type { AppSchema as AppType } from '@fastgpt/global/core/app/type.d';
|
||||
import { DatasetSearchModeEnum } from '../dataset/constants';
|
||||
|
||||
export type ChatSchema = {
|
||||
@@ -25,6 +26,23 @@ export type ChatSchema = {
|
||||
metadata?: Record<string, any>;
|
||||
};
|
||||
|
||||
export type teamInfoType = {
|
||||
avatar: string;
|
||||
balance: number;
|
||||
createTime: string;
|
||||
maxSize: number;
|
||||
name: string;
|
||||
ownerId: string;
|
||||
tagsUrl: string;
|
||||
_id: string;
|
||||
};
|
||||
|
||||
export type chatAppListSchema = {
|
||||
apps: AppType[];
|
||||
teamInfo: teamInfoSchema;
|
||||
uid?: string;
|
||||
};
|
||||
|
||||
export type ChatWithAppSchema = Omit<ChatSchema, 'appId'> & {
|
||||
appId: AppSchema;
|
||||
};
|
||||
@@ -88,15 +106,15 @@ export type ChatHistoryItemType = HistoryItemType & {
|
||||
export type moduleDispatchResType = {
|
||||
// common
|
||||
moduleLogo?: string;
|
||||
price?: number;
|
||||
runningTime?: number;
|
||||
inputTokens?: number;
|
||||
outputTokens?: number;
|
||||
query?: string;
|
||||
textOutput?: string;
|
||||
|
||||
// bill
|
||||
charsLength?: number;
|
||||
model?: string;
|
||||
query?: string;
|
||||
contextTotalLen?: number;
|
||||
textOutput?: string;
|
||||
totalPoints?: number;
|
||||
|
||||
// chat
|
||||
temperature?: number;
|
||||
@@ -111,6 +129,7 @@ export type moduleDispatchResType = {
|
||||
searchUsingReRank?: boolean;
|
||||
extensionModel?: string;
|
||||
extensionResult?: string;
|
||||
extensionCharsLength?: number;
|
||||
|
||||
// cq
|
||||
cqList?: ClassifyQuestionAgentItemType[];
|
||||
|
@@ -71,30 +71,6 @@ export const DatasetCollectionSyncResultMap = {
|
||||
};
|
||||
|
||||
/* ------------ data -------------- */
|
||||
export enum DatasetDataIndexTypeEnum {
|
||||
chunk = 'chunk',
|
||||
qa = 'qa',
|
||||
summary = 'summary',
|
||||
hypothetical = 'hypothetical',
|
||||
custom = 'custom'
|
||||
}
|
||||
export const DatasetDataIndexTypeMap = {
|
||||
[DatasetDataIndexTypeEnum.chunk]: {
|
||||
name: 'dataset.data.indexes.chunk'
|
||||
},
|
||||
[DatasetDataIndexTypeEnum.summary]: {
|
||||
name: 'dataset.data.indexes.summary'
|
||||
},
|
||||
[DatasetDataIndexTypeEnum.hypothetical]: {
|
||||
name: 'dataset.data.indexes.hypothetical'
|
||||
},
|
||||
[DatasetDataIndexTypeEnum.qa]: {
|
||||
name: 'dataset.data.indexes.qa'
|
||||
},
|
||||
[DatasetDataIndexTypeEnum.custom]: {
|
||||
name: 'dataset.data.indexes.custom'
|
||||
}
|
||||
};
|
||||
|
||||
/* ------------ training -------------- */
|
||||
export enum TrainingModeEnum {
|
||||
|
5
packages/global/core/dataset/type.d.ts
vendored
5
packages/global/core/dataset/type.d.ts
vendored
@@ -3,7 +3,6 @@ import { PermissionTypeEnum } from '../../support/permission/constant';
|
||||
import { PushDatasetDataChunkProps } from './api';
|
||||
import {
|
||||
DatasetCollectionTypeEnum,
|
||||
DatasetDataIndexTypeEnum,
|
||||
DatasetStatusEnum,
|
||||
DatasetTypeEnum,
|
||||
SearchScoreTypeEnum,
|
||||
@@ -64,7 +63,6 @@ export type DatasetCollectionSchemaType = {
|
||||
export type DatasetDataIndexItemType = {
|
||||
defaultIndex: boolean;
|
||||
dataId: string; // pg data id
|
||||
type: `${DatasetDataIndexTypeEnum}`;
|
||||
text: string;
|
||||
};
|
||||
export type DatasetDataSchemaType = {
|
||||
@@ -142,6 +140,7 @@ export type DatasetCollectionItemType = CollectionWithDatasetType & {
|
||||
/* ================= data ===================== */
|
||||
export type DatasetDataItemType = {
|
||||
id: string;
|
||||
teamId: string;
|
||||
datasetId: string;
|
||||
collectionId: string;
|
||||
sourceName: string;
|
||||
@@ -173,7 +172,7 @@ export type DatasetFileSchema = {
|
||||
/* ============= search =============== */
|
||||
export type SearchDataResponseItemType = Omit<
|
||||
DatasetDataItemType,
|
||||
'indexes' | 'isOwner' | 'canWrite'
|
||||
'teamId' | 'indexes' | 'isOwner' | 'canWrite'
|
||||
> & {
|
||||
score: { type: `${SearchScoreTypeEnum}`; value: number; index: number }[];
|
||||
// score: number;
|
||||
|
@@ -1,4 +1,4 @@
|
||||
import { TrainingModeEnum, DatasetCollectionTypeEnum, DatasetDataIndexTypeEnum } from './constants';
|
||||
import { TrainingModeEnum, DatasetCollectionTypeEnum } from './constants';
|
||||
import { getFileIcon } from '../../common/file/icon';
|
||||
import { strIsLink } from '../../common/string/tools';
|
||||
|
||||
@@ -41,7 +41,6 @@ export function getDefaultIndex(props?: { q?: string; a?: string; dataId?: strin
|
||||
const qaStr = `${q}\n${a}`.trim();
|
||||
return {
|
||||
defaultIndex: true,
|
||||
type: a ? DatasetDataIndexTypeEnum.qa : DatasetDataIndexTypeEnum.chunk,
|
||||
text: a ? qaStr : q,
|
||||
dataId
|
||||
};
|
||||
|
@@ -89,9 +89,10 @@ export enum ModuleInputKeyEnum {
|
||||
|
||||
export enum ModuleOutputKeyEnum {
|
||||
// common
|
||||
responseData = 'responseData',
|
||||
moduleDispatchBills = 'moduleDispatchBills',
|
||||
userChatInput = 'userChatInput',
|
||||
finish = 'finish',
|
||||
responseData = 'responseData',
|
||||
history = 'history',
|
||||
answerText = 'answerText', // answer module text key
|
||||
success = 'success',
|
||||
|
@@ -20,9 +20,7 @@ export enum FlowNodeInputTypeEnum {
|
||||
aiSettings = 'aiSettings',
|
||||
|
||||
// ai model select
|
||||
selectChatModel = 'selectChatModel',
|
||||
selectCQModel = 'selectCQModel',
|
||||
selectExtractModel = 'selectExtractModel',
|
||||
selectLLMModel = 'selectLLMModel',
|
||||
|
||||
// dataset special input
|
||||
selectDataset = 'selectDataset',
|
||||
@@ -58,7 +56,7 @@ export enum FlowNodeTypeEnum {
|
||||
pluginModule = 'pluginModule',
|
||||
pluginInput = 'pluginInput',
|
||||
pluginOutput = 'pluginOutput',
|
||||
cfr = 'cfr'
|
||||
queryExtension = 'cfr'
|
||||
|
||||
// abandon
|
||||
}
|
||||
|
@@ -31,7 +31,7 @@ export const AiChatModule: FlowModuleTemplateType = {
|
||||
Input_Template_Switch,
|
||||
{
|
||||
key: ModuleInputKeyEnum.aiModel,
|
||||
type: FlowNodeInputTypeEnum.selectChatModel,
|
||||
type: FlowNodeInputTypeEnum.selectLLMModel,
|
||||
label: 'core.module.input.label.aiModel',
|
||||
required: true,
|
||||
valueType: ModuleIOValueTypeEnum.string,
|
||||
|
@@ -24,7 +24,7 @@ export const ClassifyQuestionModule: FlowModuleTemplateType = {
|
||||
Input_Template_Switch,
|
||||
{
|
||||
key: ModuleInputKeyEnum.aiModel,
|
||||
type: FlowNodeInputTypeEnum.selectCQModel,
|
||||
type: FlowNodeInputTypeEnum.selectLLMModel,
|
||||
valueType: ModuleIOValueTypeEnum.string,
|
||||
label: 'core.module.input.label.Classify model',
|
||||
required: true,
|
||||
|
@@ -24,7 +24,7 @@ export const ContextExtractModule: FlowModuleTemplateType = {
|
||||
Input_Template_Switch,
|
||||
{
|
||||
key: ModuleInputKeyEnum.aiModel,
|
||||
type: FlowNodeInputTypeEnum.selectExtractModel,
|
||||
type: FlowNodeInputTypeEnum.selectLLMModel,
|
||||
valueType: ModuleIOValueTypeEnum.string,
|
||||
label: 'core.module.input.label.LLM',
|
||||
required: true,
|
||||
|
@@ -85,7 +85,6 @@ export const HttpModule468: FlowModuleTemplateType = {
|
||||
...Input_Template_AddInputParam,
|
||||
editField: {
|
||||
key: true,
|
||||
name: true,
|
||||
description: true,
|
||||
required: true,
|
||||
dataType: true
|
||||
@@ -106,7 +105,6 @@ export const HttpModule468: FlowModuleTemplateType = {
|
||||
...Output_Template_AddOutput,
|
||||
editField: {
|
||||
key: true,
|
||||
name: true,
|
||||
description: true,
|
||||
dataType: true
|
||||
},
|
||||
|
@@ -3,7 +3,7 @@ import {
|
||||
FlowNodeOutputTypeEnum,
|
||||
FlowNodeTypeEnum
|
||||
} from '../../node/constant';
|
||||
import { FlowModuleTemplateType } from '../../type.d';
|
||||
import { FlowModuleTemplateType } from '../../type';
|
||||
import {
|
||||
ModuleIOValueTypeEnum,
|
||||
ModuleInputKeyEnum,
|
||||
@@ -17,19 +17,19 @@ import {
|
||||
} from '../input';
|
||||
import { Output_Template_UserChatInput } from '../output';
|
||||
|
||||
export const AiCFR: FlowModuleTemplateType = {
|
||||
export const AiQueryExtension: FlowModuleTemplateType = {
|
||||
id: FlowNodeTypeEnum.chatNode,
|
||||
templateType: ModuleTemplateTypeEnum.other,
|
||||
flowType: FlowNodeTypeEnum.cfr,
|
||||
flowType: FlowNodeTypeEnum.queryExtension,
|
||||
avatar: '/imgs/module/cfr.svg',
|
||||
name: 'core.module.template.Query extension',
|
||||
intro: '该模块已合并到知识库搜索参数中,无需单独使用。模块将于2024/3/31弃用,请尽快修改。',
|
||||
intro: 'core.module.template.Query extension intro',
|
||||
showStatus: true,
|
||||
inputs: [
|
||||
Input_Template_Switch,
|
||||
{
|
||||
key: ModuleInputKeyEnum.aiModel,
|
||||
type: FlowNodeInputTypeEnum.selectExtractModel,
|
||||
type: FlowNodeInputTypeEnum.selectLLMModel,
|
||||
label: 'core.module.input.label.aiModel',
|
||||
required: true,
|
||||
valueType: ModuleIOValueTypeEnum.string,
|
||||
@@ -39,7 +39,7 @@ export const AiCFR: FlowModuleTemplateType = {
|
||||
{
|
||||
key: ModuleInputKeyEnum.aiSystemPrompt,
|
||||
type: FlowNodeInputTypeEnum.textarea,
|
||||
label: 'core.module.input.label.Background',
|
||||
label: 'core.app.edit.Query extension background prompt',
|
||||
max: 300,
|
||||
valueType: ModuleIOValueTypeEnum.string,
|
||||
description: 'core.app.edit.Query extension background tip',
|
||||
@@ -54,7 +54,8 @@ export const AiCFR: FlowModuleTemplateType = {
|
||||
Output_Template_UserChatInput,
|
||||
{
|
||||
key: ModuleOutputKeyEnum.text,
|
||||
label: 'core.module.output.label.cfr result',
|
||||
label: 'core.module.output.label.query extension result',
|
||||
description: 'core.module.output.description.query extension result',
|
||||
valueType: ModuleIOValueTypeEnum.string,
|
||||
type: FlowNodeOutputTypeEnum.source,
|
||||
targets: []
|
19
packages/global/core/module/type.d.ts
vendored
19
packages/global/core/module/type.d.ts
vendored
@@ -1,6 +1,14 @@
|
||||
import { FlowNodeTypeEnum } from './node/constant';
|
||||
import { ModuleIOValueTypeEnum, ModuleTemplateTypeEnum, VariableInputEnum } from './constants';
|
||||
import {
|
||||
ModuleIOValueTypeEnum,
|
||||
ModuleOutputKeyEnum,
|
||||
ModuleTemplateTypeEnum,
|
||||
VariableInputEnum
|
||||
} from './constants';
|
||||
import { FlowNodeInputItemType, FlowNodeOutputItemType } from './node/type';
|
||||
import { UserModelSchema } from 'support/user/type';
|
||||
import { moduleDispatchResType } from '..//chat/type';
|
||||
import { ChatModuleBillType } from '../../support/wallet/bill/type';
|
||||
|
||||
export type FlowModuleTemplateType = {
|
||||
id: string; // module id, unique
|
||||
@@ -105,7 +113,7 @@ export type ChatDispatchProps = {
|
||||
mode: 'test' | 'chat';
|
||||
teamId: string;
|
||||
tmbId: string;
|
||||
user: UserType;
|
||||
user: UserModelSchema;
|
||||
appId: string;
|
||||
chatId?: string;
|
||||
responseChatItemId?: string;
|
||||
@@ -116,7 +124,10 @@ export type ChatDispatchProps = {
|
||||
};
|
||||
|
||||
export type ModuleDispatchProps<T> = ChatDispatchProps & {
|
||||
outputs: RunningModuleItemType['outputs'];
|
||||
inputs: RunningModuleItemType['inputs'];
|
||||
module: RunningModuleItemType;
|
||||
params: T;
|
||||
};
|
||||
export type ModuleDispatchResponse<T> = T & {
|
||||
[ModuleOutputKeyEnum.responseData]?: moduleDispatchResType;
|
||||
[ModuleOutputKeyEnum.moduleDispatchBills]?: ChatModuleBillType[];
|
||||
};
|
||||
|
5
packages/global/support/openapi/type.d.ts
vendored
5
packages/global/support/openapi/type.d.ts
vendored
@@ -1,6 +1,5 @@
|
||||
export type OpenApiSchema = {
|
||||
_id: string;
|
||||
userId: string;
|
||||
teamId: string;
|
||||
tmbId: string;
|
||||
createTime: Date;
|
||||
@@ -8,9 +7,9 @@ export type OpenApiSchema = {
|
||||
apiKey: string;
|
||||
appId?: string;
|
||||
name: string;
|
||||
usage: number;
|
||||
usagePoints: number;
|
||||
limit?: {
|
||||
expiredTime?: Date;
|
||||
credit?: number;
|
||||
maxUsagePoints: number;
|
||||
};
|
||||
};
|
||||
|
2
packages/global/support/outLink/api.d.ts
vendored
2
packages/global/support/outLink/api.d.ts
vendored
@@ -1,5 +1,5 @@
|
||||
import type { HistoryItemType, ChatSiteItemType } from '../../core/chat/type.d';
|
||||
import { OutLinkSchema } from '@fastgpt/global/support/outLink/type';
|
||||
import { OutLinkSchema } from './type.d';
|
||||
|
||||
export type AuthOutLinkInitProps = {
|
||||
outLinkUid: string;
|
||||
|
4
packages/global/support/outLink/type.d.ts
vendored
4
packages/global/support/outLink/type.d.ts
vendored
@@ -7,14 +7,14 @@ export type OutLinkSchema = {
|
||||
tmbId: string;
|
||||
appId: string;
|
||||
name: string;
|
||||
total: number;
|
||||
usagePoints: number;
|
||||
lastTime: Date;
|
||||
type: `${OutLinkTypeEnum}`;
|
||||
responseDetail: boolean;
|
||||
limit?: {
|
||||
expiredTime?: Date;
|
||||
QPM: number;
|
||||
credit: number;
|
||||
maxUsagePoints: number;
|
||||
hookUrl?: string;
|
||||
};
|
||||
};
|
||||
|
1
packages/global/support/permission/type.d.ts
vendored
1
packages/global/support/permission/type.d.ts
vendored
@@ -1,7 +1,6 @@
|
||||
import { AuthUserTypeEnum } from './constant';
|
||||
|
||||
export type AuthResponseType = {
|
||||
userId: string;
|
||||
teamId: string;
|
||||
tmbId: string;
|
||||
isOwner: boolean;
|
||||
|
@@ -1,5 +1,6 @@
|
||||
export const TeamCollectionName = 'teams';
|
||||
export const TeamMemberCollectionName = 'team.members';
|
||||
export const TeamTagsCollectionName = 'team.tags';
|
||||
|
||||
export enum TeamMemberRoleEnum {
|
||||
owner = 'owner',
|
||||
|
@@ -15,6 +15,7 @@ export type UpdateTeamProps = {
|
||||
teamId: string;
|
||||
name?: string;
|
||||
avatar?: string;
|
||||
tagsUrl?: string;
|
||||
};
|
||||
|
||||
/* ------------- member ----------- */
|
||||
|
18
packages/global/support/user/team/type.d.ts
vendored
18
packages/global/support/user/team/type.d.ts
vendored
@@ -9,11 +9,23 @@ export type TeamSchema = {
|
||||
createTime: Date;
|
||||
balance: number;
|
||||
maxSize: number;
|
||||
tagsUrl: string;
|
||||
limit: {
|
||||
lastExportDatasetTime: Date;
|
||||
lastWebsiteSyncTime: Date;
|
||||
};
|
||||
};
|
||||
export type tagsType = {
|
||||
label: string,
|
||||
key: string
|
||||
}
|
||||
export type TeamTagsSchema = {
|
||||
_id: string;
|
||||
label: string;
|
||||
teamId: string;
|
||||
key: string;
|
||||
createTime: Date;
|
||||
};
|
||||
|
||||
export type TeamMemberSchema = {
|
||||
_id: string;
|
||||
@@ -26,13 +38,13 @@ export type TeamMemberSchema = {
|
||||
defaultTeam: boolean;
|
||||
};
|
||||
|
||||
export type TeamMemberWithUserSchema = TeamMemberSchema & {
|
||||
export type TeamMemberWithUserSchema = Omit<TeamMemberSchema, 'userId'> & {
|
||||
userId: UserModelSchema;
|
||||
};
|
||||
export type TeamMemberWithTeamSchema = TeamMemberSchema & {
|
||||
export type TeamMemberWithTeamSchema = Omit<TeamMemberSchema, 'teamId'> & {
|
||||
teamId: TeamSchema;
|
||||
};
|
||||
export type TeamMemberWithTeamAndUserSchema = TeamMemberWithTeamSchema & {
|
||||
export type TeamMemberWithTeamAndUserSchema = Omit<TeamMemberWithTeamSchema, 'userId'> & {
|
||||
userId: UserModelSchema;
|
||||
};
|
||||
|
||||
|
1
packages/global/support/user/type.d.ts
vendored
1
packages/global/support/user/type.d.ts
vendored
@@ -29,4 +29,5 @@ export type UserType = {
|
||||
promotionRate: UserModelSchema['promotionRate'];
|
||||
openaiAccount: UserModelSchema['openaiAccount'];
|
||||
team: TeamItemType;
|
||||
standardInfo?: standardInfoType;
|
||||
};
|
||||
|
37
packages/global/support/wallet/bill/api.d.ts
vendored
37
packages/global/support/wallet/bill/api.d.ts
vendored
@@ -1,25 +1,18 @@
|
||||
import { BillSourceEnum } from './constants';
|
||||
import { BillListItemCountType, BillListItemType } from './type';
|
||||
|
||||
export type CreateTrainingBillProps = {
|
||||
name: string;
|
||||
datasetId: string;
|
||||
};
|
||||
|
||||
export type ConcatBillProps = BillListItemCountType & {
|
||||
teamId: string;
|
||||
tmbId: string;
|
||||
billId?: string;
|
||||
total: number;
|
||||
listIndex?: number;
|
||||
};
|
||||
import { BillTypeEnum } from './constants';
|
||||
|
||||
export type CreateBillProps = {
|
||||
teamId: string;
|
||||
tmbId: string;
|
||||
appName: string;
|
||||
appId?: string;
|
||||
total: number;
|
||||
source: `${BillSourceEnum}`;
|
||||
list: BillListItemType[];
|
||||
type: `${BillTypeEnum}`;
|
||||
|
||||
// balance
|
||||
balance?: number; // read
|
||||
|
||||
month?: number;
|
||||
// extra dataset size
|
||||
extraDatasetSize?: number; // 1k
|
||||
extraPoints?: number; // 100w
|
||||
};
|
||||
export type CreateBillResponse = {
|
||||
billId: string;
|
||||
codeUrl: string;
|
||||
readPrice: number;
|
||||
};
|
||||
|
@@ -1,34 +1,57 @@
|
||||
// model price: xxx/1k tokens
|
||||
// ¥1 = 100000.
|
||||
export const PRICE_SCALE = 100000;
|
||||
|
||||
export enum BillSourceEnum {
|
||||
fastgpt = 'fastgpt',
|
||||
api = 'api',
|
||||
shareLink = 'shareLink',
|
||||
training = 'training',
|
||||
|
||||
export enum BillTypeEnum {
|
||||
balance = 'balance',
|
||||
standSubPlan = 'standSubPlan',
|
||||
extraDatasetSub = 'extraDatasetSub'
|
||||
extraDatasetSub = 'extraDatasetSub',
|
||||
extraPoints = 'extraPoints'
|
||||
}
|
||||
|
||||
export const BillSourceMap = {
|
||||
[BillSourceEnum.fastgpt]: {
|
||||
label: '在线使用'
|
||||
export const billTypeMap = {
|
||||
[BillTypeEnum.balance]: {
|
||||
label: 'support.wallet.subscription.type.balance'
|
||||
},
|
||||
[BillSourceEnum.api]: {
|
||||
label: 'Api'
|
||||
},
|
||||
[BillSourceEnum.shareLink]: {
|
||||
label: '免登录链接'
|
||||
},
|
||||
[BillSourceEnum.training]: {
|
||||
label: 'dataset.Training Name'
|
||||
},
|
||||
[BillSourceEnum.standSubPlan]: {
|
||||
[BillTypeEnum.standSubPlan]: {
|
||||
label: 'support.wallet.subscription.type.standard'
|
||||
},
|
||||
[BillSourceEnum.extraDatasetSub]: {
|
||||
[BillTypeEnum.extraDatasetSub]: {
|
||||
label: 'support.wallet.subscription.type.extraDatasetSize'
|
||||
},
|
||||
[BillTypeEnum.extraPoints]: {
|
||||
label: 'support.wallet.subscription.type.extraPoints'
|
||||
}
|
||||
};
|
||||
|
||||
export enum BillStatusEnum {
|
||||
SUCCESS = 'SUCCESS',
|
||||
REFUND = 'REFUND',
|
||||
NOTPAY = 'NOTPAY',
|
||||
CLOSED = 'CLOSED'
|
||||
}
|
||||
export const billStatusMap = {
|
||||
[BillStatusEnum.SUCCESS]: {
|
||||
label: 'support.wallet.bill.status.success'
|
||||
},
|
||||
[BillStatusEnum.REFUND]: {
|
||||
label: 'support.wallet.bill.status.refund'
|
||||
},
|
||||
[BillStatusEnum.NOTPAY]: {
|
||||
label: 'support.wallet.bill.status.notpay'
|
||||
},
|
||||
[BillStatusEnum.CLOSED]: {
|
||||
label: 'support.wallet.bill.status.closed'
|
||||
}
|
||||
};
|
||||
|
||||
export enum BillPayWayEnum {
|
||||
balance = 'balance',
|
||||
wx = 'wx'
|
||||
}
|
||||
export const billPayWayMap = {
|
||||
[BillPayWayEnum.balance]: {
|
||||
label: 'support.wallet.bill.payWay.balance'
|
||||
},
|
||||
[BillPayWayEnum.wx]: {
|
||||
label: 'support.wallet.bill.payWay.wx'
|
||||
}
|
||||
};
|
||||
|
||||
export const SUB_DATASET_SIZE_RATE = 1000;
|
||||
export const SUB_EXTRA_POINT_RATE = 1000;
|
||||
|
@@ -1,26 +0,0 @@
|
||||
/* bill common */
|
||||
import { PRICE_SCALE } from './constants';
|
||||
import { BillSourceEnum } from './constants';
|
||||
import { AuthUserTypeEnum } from '../../permission/constant';
|
||||
|
||||
/**
|
||||
* dataset price / PRICE_SCALE = real price
|
||||
*/
|
||||
export const formatStorePrice2Read = (val = 0, multiple = 1) => {
|
||||
return Number(((val / PRICE_SCALE) * multiple).toFixed(10));
|
||||
};
|
||||
export const formatModelPrice2Read = (val = 0) => {
|
||||
return Number((val / 1000).toFixed(10));
|
||||
};
|
||||
|
||||
export const getBillSourceByAuthType = ({
|
||||
shareId,
|
||||
authType
|
||||
}: {
|
||||
shareId?: string;
|
||||
authType?: `${AuthUserTypeEnum}`;
|
||||
}) => {
|
||||
if (shareId) return BillSourceEnum.shareLink;
|
||||
if (authType === AuthUserTypeEnum.apikey) return BillSourceEnum.api;
|
||||
return BillSourceEnum.fastgpt;
|
||||
};
|
54
packages/global/support/wallet/bill/type.d.ts
vendored
54
packages/global/support/wallet/bill/type.d.ts
vendored
@@ -1,35 +1,29 @@
|
||||
import { CreateBillProps } from './api';
|
||||
import { BillSourceEnum } from './constants';
|
||||
import { StandardSubLevelEnum, SubModeEnum, SubTypeEnum } from '../sub/constants';
|
||||
import { BillPayWayEnum, BillTypeEnum } from './constants';
|
||||
|
||||
export type BillListItemCountType = {
|
||||
inputTokens?: number;
|
||||
outputTokens?: number;
|
||||
charsLength?: number;
|
||||
duration?: number;
|
||||
|
||||
// sub
|
||||
datasetSize?: number;
|
||||
|
||||
// abandon
|
||||
tokenLen?: number;
|
||||
};
|
||||
export type BillListItemType = BillListItemCountType & {
|
||||
moduleName: string;
|
||||
amount: number;
|
||||
model?: string;
|
||||
};
|
||||
|
||||
export type BillSchema = CreateBillProps & {
|
||||
export type BillSchemaType = {
|
||||
_id: string;
|
||||
time: Date;
|
||||
userId: string;
|
||||
teamId: string;
|
||||
tmbId: string;
|
||||
createTime: Date;
|
||||
orderId: string;
|
||||
status: 'SUCCESS' | 'REFUND' | 'NOTPAY' | 'CLOSED';
|
||||
type: `${BillTypeEnum}`;
|
||||
price: number;
|
||||
metadata: {
|
||||
payWay: `${BillPayWayEnum}`;
|
||||
subMode?: `${SubModeEnum}`;
|
||||
standSubLevel?: `${StandardSubLevelEnum}`;
|
||||
month?: number;
|
||||
datasetSize?: number;
|
||||
extraPoints?: number;
|
||||
};
|
||||
};
|
||||
|
||||
export type BillItemType = {
|
||||
id: string;
|
||||
// memberName: string;
|
||||
time: Date;
|
||||
appName: string;
|
||||
source: BillSchema['source'];
|
||||
total: number;
|
||||
list: BillSchema['list'];
|
||||
export type ChatModuleBillType = {
|
||||
totalPoints: number;
|
||||
moduleName: string;
|
||||
model?: string;
|
||||
charsLength?: number;
|
||||
};
|
||||
|
3
packages/global/support/wallet/constants.ts
Normal file
3
packages/global/support/wallet/constants.ts
Normal file
@@ -0,0 +1,3 @@
|
||||
// model price: xxx/1k tokens
|
||||
// ¥1 = 100000.
|
||||
export const PRICE_SCALE = 100000;
|
@@ -1,41 +0,0 @@
|
||||
export enum PayTypeEnum {
|
||||
balance = 'balance',
|
||||
subStandard = 'subStandard',
|
||||
subExtraDatasetSize = 'subExtraDatasetSize',
|
||||
subExtraPoints = 'subExtraPoints'
|
||||
}
|
||||
export const payTypeMap = {
|
||||
[PayTypeEnum.balance]: {
|
||||
label: 'support.user.team.pay.type.balance'
|
||||
},
|
||||
[PayTypeEnum.subStandard]: {
|
||||
label: 'support.wallet.subscription.type.standard'
|
||||
},
|
||||
[PayTypeEnum.subExtraDatasetSize]: {
|
||||
label: 'support.wallet.subscription.type.extraDatasetSize'
|
||||
},
|
||||
[PayTypeEnum.subExtraPoints]: {
|
||||
label: 'support.wallet.subscription.type.extraPoints'
|
||||
}
|
||||
};
|
||||
|
||||
export enum PayStatusEnum {
|
||||
SUCCESS = 'SUCCESS',
|
||||
REFUND = 'REFUND',
|
||||
NOTPAY = 'NOTPAY',
|
||||
CLOSED = 'CLOSED'
|
||||
}
|
||||
export const payStatusMap = {
|
||||
[PayStatusEnum.SUCCESS]: {
|
||||
label: 'support.user.team.pay.status.success'
|
||||
},
|
||||
[PayStatusEnum.REFUND]: {
|
||||
label: 'support.user.team.pay.status.refund'
|
||||
},
|
||||
[PayStatusEnum.NOTPAY]: {
|
||||
label: 'support.user.team.pay.status.notpay'
|
||||
},
|
||||
[PayStatusEnum.CLOSED]: {
|
||||
label: 'support.user.team.pay.status.closed'
|
||||
}
|
||||
};
|
18
packages/global/support/wallet/pay/type.d.ts
vendored
18
packages/global/support/wallet/pay/type.d.ts
vendored
@@ -1,18 +0,0 @@
|
||||
import { SubModeEnum, SubTypeEnum } from '../sub/constants';
|
||||
import { PayTypeEnum } from './constants';
|
||||
|
||||
export type PaySchema = {
|
||||
_id: string;
|
||||
userId: string;
|
||||
teamId: string;
|
||||
tmbId: string;
|
||||
createTime: Date;
|
||||
orderId: string;
|
||||
status: 'SUCCESS' | 'REFUND' | 'NOTPAY' | 'CLOSED';
|
||||
type: `${PayType}`;
|
||||
|
||||
price: number;
|
||||
payWay: 'balance' | 'wx';
|
||||
|
||||
subMetadata: {};
|
||||
};
|
14
packages/global/support/wallet/sub/api.d.ts
vendored
14
packages/global/support/wallet/sub/api.d.ts
vendored
@@ -1,26 +1,14 @@
|
||||
import { StandardSubLevelEnum, SubModeEnum } from './constants';
|
||||
import { TeamSubSchema } from './type.d';
|
||||
|
||||
export type SubDatasetSizeParams = {
|
||||
size: number;
|
||||
};
|
||||
export type StandardSubPlanParams = {
|
||||
level: `${StandardSubLevelEnum}`;
|
||||
mode: `${SubModeEnum}`;
|
||||
};
|
||||
|
||||
export type SubDatasetSizePreviewCheckResponse = {
|
||||
payForNewSub: boolean; // Does this change require payment
|
||||
newSubSize: number; // new sub dataset size
|
||||
alreadySubSize: number; // old sub dataset size
|
||||
payPrice: number; // this change require payment
|
||||
newPlanPrice: number; // the new sub price
|
||||
newSubStartTime: Date;
|
||||
newSubExpiredTime: Date;
|
||||
balanceEnough: boolean; // team balance is enough
|
||||
};
|
||||
export type StandardSubPlanUpdateResponse = {
|
||||
balanceEnough: boolean; // team balance is enough
|
||||
teamBalance: number;
|
||||
payPrice?: number;
|
||||
planPrice: number;
|
||||
planPointPrice: number;
|
||||
|
@@ -1,38 +1,36 @@
|
||||
export const POINTS_SCALE = 10000;
|
||||
|
||||
export enum SubTypeEnum {
|
||||
standard = 'standard',
|
||||
extraDatasetSize = 'extraDatasetSize',
|
||||
extraPoints = 'extraPoints'
|
||||
}
|
||||
|
||||
export const subTypeMap = {
|
||||
[SubTypeEnum.standard]: {
|
||||
label: 'support.wallet.subscription.type.standard'
|
||||
label: 'support.wallet.subscription.type.standard',
|
||||
icon: 'support/account/plans'
|
||||
},
|
||||
[SubTypeEnum.extraDatasetSize]: {
|
||||
label: 'support.wallet.subscription.type.extraDatasetSize'
|
||||
label: 'support.wallet.subscription.type.extraDatasetSize',
|
||||
icon: 'core/dataset/datasetLight'
|
||||
},
|
||||
[SubTypeEnum.extraPoints]: {
|
||||
label: 'support.wallet.subscription.type.extraPoints'
|
||||
label: 'support.wallet.subscription.type.extraPoints',
|
||||
icon: 'core/chat/chatLight'
|
||||
}
|
||||
};
|
||||
|
||||
export enum SubStatusEnum {
|
||||
active = 'active',
|
||||
canceled = 'canceled'
|
||||
expired = 'expired'
|
||||
}
|
||||
export const subStatusMap = {
|
||||
[SubStatusEnum.active]: {
|
||||
label: 'support.wallet.subscription.status.active'
|
||||
},
|
||||
[SubStatusEnum.canceled]: {
|
||||
[SubStatusEnum.expired]: {
|
||||
label: 'support.wallet.subscription.status.canceled'
|
||||
}
|
||||
};
|
||||
export const subSelectMap = {
|
||||
true: SubStatusEnum.active,
|
||||
false: SubStatusEnum.canceled
|
||||
};
|
||||
|
||||
export enum SubModeEnum {
|
||||
month = 'month',
|
||||
@@ -40,11 +38,11 @@ export enum SubModeEnum {
|
||||
}
|
||||
export const subModeMap = {
|
||||
[SubModeEnum.month]: {
|
||||
label: 'support.wallet.subscription.mode.month',
|
||||
label: 'support.wallet.subscription.mode.Month',
|
||||
durationMonth: 1
|
||||
},
|
||||
[SubModeEnum.year]: {
|
||||
label: 'support.wallet.subscription.mode.year',
|
||||
label: 'support.wallet.subscription.mode.Year',
|
||||
durationMonth: 12
|
||||
}
|
||||
};
|
||||
@@ -63,7 +61,7 @@ export const standardSubLevelMap = {
|
||||
},
|
||||
[StandardSubLevelEnum.experience]: {
|
||||
label: 'support.wallet.subscription.standardSubLevel.experience',
|
||||
desc: 'support.wallet.subscription.standardSubLevel.experience desc'
|
||||
desc: ''
|
||||
},
|
||||
[StandardSubLevelEnum.team]: {
|
||||
label: 'support.wallet.subscription.standardSubLevel.team',
|
||||
|
41
packages/global/support/wallet/sub/type.d.ts
vendored
41
packages/global/support/wallet/sub/type.d.ts
vendored
@@ -2,19 +2,19 @@ import { StandardSubLevelEnum, SubModeEnum, SubStatusEnum, SubTypeEnum } from '.
|
||||
|
||||
// Content of plan
|
||||
export type TeamStandardSubPlanItemType = {
|
||||
price: number; // read price
|
||||
pointPrice: number; // read price/ one ten thousand
|
||||
price: number; // read price / month
|
||||
pointPrice: number; // read price/ one thousand
|
||||
totalPoints: number; // n
|
||||
maxTeamMember: number;
|
||||
maxAppAmount: number; // max app or plugin amount
|
||||
maxDatasetAmount: number;
|
||||
chatHistoryStoreDuration: number; // n day
|
||||
maxDatasetSize: number;
|
||||
customApiKey: boolean;
|
||||
customCopyright: boolean; // feature
|
||||
websiteSyncInterval: number; // n hours
|
||||
trainingWeight: number; // 1~4
|
||||
reRankWeight: number; // 1~4
|
||||
totalPoints: number; // n ten thousand
|
||||
permissionCustomApiKey: boolean;
|
||||
permissionCustomCopyright: boolean; // feature
|
||||
permissionWebsiteSync: boolean;
|
||||
permissionReRank: boolean;
|
||||
};
|
||||
|
||||
export type StandSubPlanLevelMapType = Record<
|
||||
@@ -27,6 +27,9 @@ export type SubPlanType = {
|
||||
[SubTypeEnum.extraDatasetSize]: {
|
||||
price: number;
|
||||
};
|
||||
[SubTypeEnum.extraPoints]: {
|
||||
price: number;
|
||||
};
|
||||
};
|
||||
|
||||
export type TeamSubSchema = {
|
||||
@@ -34,40 +37,30 @@ export type TeamSubSchema = {
|
||||
teamId: string;
|
||||
type: `${SubTypeEnum}`;
|
||||
status: `${SubStatusEnum}`;
|
||||
currentMode: `${SubModeEnum}`;
|
||||
nextMode: `${SubModeEnum}`;
|
||||
startTime: Date;
|
||||
expiredTime: Date;
|
||||
price: number;
|
||||
|
||||
currentMode: `${SubModeEnum}`;
|
||||
nextMode: `${SubModeEnum}`;
|
||||
currentSubLevel: `${StandardSubLevelEnum}`;
|
||||
nextSubLevel: `${StandardSubLevelEnum}`;
|
||||
|
||||
pointPrice: number;
|
||||
totalPoints: number;
|
||||
|
||||
currentExtraDatasetSize: number;
|
||||
nextExtraDatasetSize: number;
|
||||
|
||||
currentExtraPoints: number;
|
||||
nextExtraPoints: number;
|
||||
|
||||
surplusPoints: number;
|
||||
|
||||
// abandon
|
||||
datasetStoreAmount?: number;
|
||||
renew?: boolean;
|
||||
currentExtraDatasetSize: number;
|
||||
};
|
||||
|
||||
export type FeTeamSubType = {
|
||||
export type FeTeamPlanStatusType = {
|
||||
[SubTypeEnum.standard]?: TeamSubSchema;
|
||||
[SubTypeEnum.extraDatasetSize]?: TeamSubSchema;
|
||||
[SubTypeEnum.extraPoints]?: TeamSubSchema;
|
||||
standardConstants?: TeamStandardSubPlanItemType;
|
||||
|
||||
standardMaxDatasetSize: number;
|
||||
totalPoints: number;
|
||||
usedPoints: number;
|
||||
|
||||
standardMaxPoints: number;
|
||||
// standard + extra
|
||||
datasetMaxSize: number;
|
||||
usedDatasetSize: number;
|
||||
};
|
||||
|
26
packages/global/support/wallet/usage/api.d.ts
vendored
Normal file
26
packages/global/support/wallet/usage/api.d.ts
vendored
Normal file
@@ -0,0 +1,26 @@
|
||||
import { UsageSourceEnum } from './constants';
|
||||
import { UsageListItemCountType, UsageListItemType } from './type';
|
||||
|
||||
export type CreateTrainingUsageProps = {
|
||||
name: string;
|
||||
datasetId: string;
|
||||
};
|
||||
|
||||
export type ConcatUsageProps = UsageListItemCountType & {
|
||||
teamId: string;
|
||||
tmbId: string;
|
||||
billId?: string;
|
||||
totalPoints: number;
|
||||
listIndex?: number;
|
||||
};
|
||||
|
||||
export type CreateUsageProps = {
|
||||
teamId: string;
|
||||
tmbId: string;
|
||||
appName: string;
|
||||
appId?: string;
|
||||
totalPoints: number;
|
||||
// inputTokens: number;
|
||||
source: `${UsageSourceEnum}`;
|
||||
list: UsageListItemType[];
|
||||
};
|
21
packages/global/support/wallet/usage/constants.ts
Normal file
21
packages/global/support/wallet/usage/constants.ts
Normal file
@@ -0,0 +1,21 @@
|
||||
export enum UsageSourceEnum {
|
||||
fastgpt = 'fastgpt',
|
||||
api = 'api',
|
||||
shareLink = 'shareLink',
|
||||
training = 'training'
|
||||
}
|
||||
|
||||
export const UsageSourceMap = {
|
||||
[UsageSourceEnum.fastgpt]: {
|
||||
label: '在线使用'
|
||||
},
|
||||
[UsageSourceEnum.api]: {
|
||||
label: 'Api'
|
||||
},
|
||||
[UsageSourceEnum.shareLink]: {
|
||||
label: '免登录链接'
|
||||
},
|
||||
[UsageSourceEnum.training]: {
|
||||
label: 'dataset.Training Name'
|
||||
}
|
||||
};
|
23
packages/global/support/wallet/usage/tools.ts
Normal file
23
packages/global/support/wallet/usage/tools.ts
Normal file
@@ -0,0 +1,23 @@
|
||||
/* bill common */
|
||||
import { PRICE_SCALE } from '../constants';
|
||||
import { UsageSourceEnum } from './constants';
|
||||
import { AuthUserTypeEnum } from '../../permission/constant';
|
||||
|
||||
/**
|
||||
* dataset price / PRICE_SCALE = real price
|
||||
*/
|
||||
export const formatStorePrice2Read = (val = 0, multiple = 1) => {
|
||||
return Number(((val / PRICE_SCALE) * multiple).toFixed(10));
|
||||
};
|
||||
|
||||
export const getUsageSourceByAuthType = ({
|
||||
shareId,
|
||||
authType
|
||||
}: {
|
||||
shareId?: string;
|
||||
authType?: `${AuthUserTypeEnum}`;
|
||||
}) => {
|
||||
if (shareId) return UsageSourceEnum.shareLink;
|
||||
if (authType === AuthUserTypeEnum.apikey) return UsageSourceEnum.api;
|
||||
return UsageSourceEnum.fastgpt;
|
||||
};
|
26
packages/global/support/wallet/usage/type.d.ts
vendored
Normal file
26
packages/global/support/wallet/usage/type.d.ts
vendored
Normal file
@@ -0,0 +1,26 @@
|
||||
import { CreateUsageProps } from './api';
|
||||
import { UsageSourceEnum } from './constants';
|
||||
|
||||
export type UsageListItemCountType = {
|
||||
charsLength?: number;
|
||||
duration?: number;
|
||||
};
|
||||
export type UsageListItemType = UsageListItemCountType & {
|
||||
moduleName: string;
|
||||
amount: number;
|
||||
model?: string;
|
||||
};
|
||||
|
||||
export type UsageSchemaType = CreateUsageProps & {
|
||||
_id: string;
|
||||
time: Date;
|
||||
};
|
||||
|
||||
export type UsageItemType = {
|
||||
id: string;
|
||||
time: Date;
|
||||
appName: string;
|
||||
source: UsageSchemaType['source'];
|
||||
totalPoints: number;
|
||||
list: UsageSchemaType['list'];
|
||||
};
|
@@ -3,7 +3,7 @@ import { sseResponseEventEnum } from './constant';
|
||||
import { proxyError, ERROR_RESPONSE, ERROR_ENUM } from '@fastgpt/global/common/error/errorCode';
|
||||
import { addLog } from '../system/log';
|
||||
import { clearCookie } from '../../support/permission/controller';
|
||||
import { replaceSensitiveLink } from '@fastgpt/global/common/string/tools';
|
||||
import { replaceSensitiveText } from '@fastgpt/global/common/string/tools';
|
||||
|
||||
export interface ResponseType<T = any> {
|
||||
code: number;
|
||||
@@ -53,7 +53,7 @@ export const jsonRes = <T = any>(
|
||||
res.status(code).json({
|
||||
code,
|
||||
statusText: '',
|
||||
message: replaceSensitiveLink(message || msg),
|
||||
message: replaceSensitiveText(message || msg),
|
||||
data: data !== undefined ? data : null
|
||||
});
|
||||
};
|
||||
@@ -91,7 +91,7 @@ export const sseErrRes = (res: NextApiResponse, error: any) => {
|
||||
responseWrite({
|
||||
res,
|
||||
event: sseResponseEventEnum.error,
|
||||
data: JSON.stringify({ message: replaceSensitiveLink(msg) })
|
||||
data: JSON.stringify({ message: replaceSensitiveText(msg) })
|
||||
});
|
||||
};
|
||||
|
||||
|
@@ -1,3 +1,4 @@
|
||||
import { FastGPTConfigFileType } from '@fastgpt/global/common/system/types';
|
||||
import { isIPv6 } from 'net';
|
||||
|
||||
export const SERVICE_LOCAL_PORT = `${process.env.PORT || 3000}`;
|
||||
@@ -5,3 +6,16 @@ export const SERVICE_LOCAL_HOST =
|
||||
process.env.HOSTNAME && isIPv6(process.env.HOSTNAME)
|
||||
? `[${process.env.HOSTNAME}]:${SERVICE_LOCAL_PORT}`
|
||||
: `${process.env.HOSTNAME || 'localhost'}:${SERVICE_LOCAL_PORT}`;
|
||||
|
||||
export const initFastGPTConfig = (config?: FastGPTConfigFileType) => {
|
||||
if (!config) return;
|
||||
|
||||
global.feConfigs = config.feConfigs;
|
||||
global.subPlans = config.subPlans;
|
||||
|
||||
global.llmModels = config.llmModels;
|
||||
global.vectorModels = config.vectorModels;
|
||||
global.audioSpeechModels = config.audioSpeechModels;
|
||||
global.whisperModel = config.whisperModel;
|
||||
global.reRankModels = config.reRankModels;
|
||||
};
|
||||
|
@@ -11,7 +11,6 @@ const getVectorObj = () => {
|
||||
export const initVectorStore = getVectorObj().init;
|
||||
export const deleteDatasetDataVector = getVectorObj().delete;
|
||||
export const recallFromVectorStore = getVectorObj().recall;
|
||||
export const checkVectorDataExist = getVectorObj().checkDataExist;
|
||||
export const getVectorDataByTime = getVectorObj().getVectorDataByTime;
|
||||
export const getVectorCountByTeamId = getVectorObj().getVectorCountByTeamId;
|
||||
|
||||
@@ -38,22 +37,22 @@ export const insertDatasetDataVector = async ({
|
||||
};
|
||||
};
|
||||
|
||||
export const updateDatasetDataVector = async ({
|
||||
id,
|
||||
...props
|
||||
}: InsertVectorProps & {
|
||||
id: string;
|
||||
query: string;
|
||||
model: VectorModelItemType;
|
||||
}) => {
|
||||
// insert new vector
|
||||
const { charsLength, insertId } = await insertDatasetDataVector(props);
|
||||
// export const updateDatasetDataVector = async ({
|
||||
// id,
|
||||
// ...props
|
||||
// }: InsertVectorProps & {
|
||||
// id: string;
|
||||
// query: string;
|
||||
// model: VectorModelItemType;
|
||||
// }) => {
|
||||
// // insert new vector
|
||||
// const { charsLength, insertId } = await insertDatasetDataVector(props);
|
||||
|
||||
// delete old vector
|
||||
await deleteDatasetDataVector({
|
||||
teamId: props.teamId,
|
||||
id
|
||||
});
|
||||
// // delete old vector
|
||||
// await deleteDatasetDataVector({
|
||||
// teamId: props.teamId,
|
||||
// id
|
||||
// });
|
||||
|
||||
return { charsLength, insertId };
|
||||
};
|
||||
// return { charsLength, insertId };
|
||||
// };
|
||||
|
@@ -4,8 +4,7 @@ import {
|
||||
deleteDatasetDataVector,
|
||||
embeddingRecall,
|
||||
getVectorDataByTime,
|
||||
getVectorCountByTeamId,
|
||||
checkDataExist
|
||||
getVectorCountByTeamId
|
||||
} from './controller';
|
||||
|
||||
export class PgVector {
|
||||
@@ -14,7 +13,6 @@ export class PgVector {
|
||||
insert = insertDatasetDataVector;
|
||||
delete = deleteDatasetDataVector;
|
||||
recall = embeddingRecall;
|
||||
checkDataExist = checkDataExist;
|
||||
getVectorCountByTeamId = getVectorCountByTeamId;
|
||||
getVectorDataByTime = getVectorDataByTime;
|
||||
}
|
||||
|
@@ -25,6 +25,18 @@ export async function initPg() {
|
||||
await PgClient.query(
|
||||
`CREATE INDEX CONCURRENTLY IF NOT EXISTS vector_index ON ${PgDatasetTableName} USING hnsw (vector vector_ip_ops) WITH (m = 32, ef_construction = 64);`
|
||||
);
|
||||
await PgClient.query(
|
||||
`CREATE INDEX CONCURRENTLY IF NOT EXISTS team_dataset_index ON ${PgDatasetTableName} USING btree(team_id, dataset_id);`
|
||||
);
|
||||
await PgClient.query(
|
||||
` CREATE INDEX CONCURRENTLY IF NOT EXISTS team_collection_index ON ${PgDatasetTableName} USING btree(team_id, collection_id);`
|
||||
);
|
||||
await PgClient.query(
|
||||
`CREATE INDEX CONCURRENTLY IF NOT EXISTS team_id_index ON ${PgDatasetTableName} USING btree(team_id, id);`
|
||||
);
|
||||
await PgClient.query(
|
||||
`CREATE INDEX CONCURRENTLY IF NOT EXISTS create_time_index ON ${PgDatasetTableName} USING btree(createtime);`
|
||||
);
|
||||
|
||||
console.log('init pg successful');
|
||||
} catch (error) {
|
||||
@@ -152,11 +164,6 @@ export const embeddingRecall = async (
|
||||
}
|
||||
};
|
||||
|
||||
export const checkDataExist = async (id: string) => {
|
||||
const { rows } = await PgClient.query(`SELECT id FROM ${PgDatasetTableName} WHERE id=${id};`);
|
||||
|
||||
return rows.length > 0;
|
||||
};
|
||||
export const getVectorCountByTeamId = async (teamId: string) => {
|
||||
const total = await PgClient.count(PgDatasetTableName, {
|
||||
where: [['team_id', String(teamId)]]
|
||||
|
@@ -11,6 +11,7 @@ export const getAIApi = (props?: {
|
||||
timeout?: number;
|
||||
}) => {
|
||||
const { userKey, timeout } = props || {};
|
||||
|
||||
return new OpenAI({
|
||||
apiKey: userKey?.key || systemAIChatKey,
|
||||
baseURL: userKey?.baseUrl || baseUrl,
|
||||
|
@@ -1,5 +1,6 @@
|
||||
import { VectorModelItemType } from '@fastgpt/global/core/ai/model.d';
|
||||
import { getAIApi } from '../config';
|
||||
import { replaceValidChars } from '../../chat/utils';
|
||||
|
||||
type GetVectorProps = {
|
||||
model: VectorModelItemType;
|
||||
@@ -36,7 +37,7 @@ export async function getVectorsByText({ model, input }: GetVectorProps) {
|
||||
}
|
||||
|
||||
return {
|
||||
charsLength: input.length,
|
||||
charsLength: replaceValidChars(input).length,
|
||||
vectors: await Promise.all(res.data.map((item) => unityDimensional(item.embedding)))
|
||||
};
|
||||
});
|
||||
|
@@ -1,159 +0,0 @@
|
||||
import { replaceVariable } from '@fastgpt/global/common/string/tools';
|
||||
import { getAIApi } from '../config';
|
||||
import { ChatItemType } from '@fastgpt/global/core/chat/type';
|
||||
|
||||
/*
|
||||
cfr: coreference resolution - 指代消除
|
||||
可以根据上下文,完事当前问题指代内容,利于检索。
|
||||
*/
|
||||
|
||||
const defaultPrompt = `请不要回答任何问题。
|
||||
你的任务是结合历史记录,为当前问题,实现代词替换,确保问题描述的对象清晰明确。例如:
|
||||
历史记录:
|
||||
"""
|
||||
Q: 对话背景。
|
||||
A: 关于 FatGPT 的介绍和使用等问题。
|
||||
"""
|
||||
当前问题: 怎么下载
|
||||
输出: FastGPT 怎么下载?
|
||||
----------------
|
||||
历史记录:
|
||||
"""
|
||||
Q: 报错 "no connection"
|
||||
A: FastGPT 报错"no connection"可能是因为……
|
||||
"""
|
||||
当前问题: 怎么解决
|
||||
输出: FastGPT 报错"no connection"如何解决?
|
||||
----------------
|
||||
历史记录:
|
||||
"""
|
||||
Q: 作者是谁?
|
||||
A: FastGPT 的作者是 labring。
|
||||
"""
|
||||
当前问题: 介绍下他
|
||||
输出: 介绍下 FastGPT 的作者 labring。
|
||||
----------------
|
||||
历史记录:
|
||||
"""
|
||||
Q: 作者是谁?
|
||||
A: FastGPT 的作者是 labring。
|
||||
"""
|
||||
当前问题: 我想购买商业版。
|
||||
输出: FastGPT 商业版如何购买?
|
||||
----------------
|
||||
历史记录:
|
||||
"""
|
||||
Q: 对话背景。
|
||||
A: 关于 FatGPT 的介绍和使用等问题。
|
||||
"""
|
||||
当前问题: nh
|
||||
输出: nh
|
||||
----------------
|
||||
历史记录:
|
||||
"""
|
||||
Q: FastGPT 如何收费?
|
||||
A: FastGPT 收费可以参考……
|
||||
"""
|
||||
当前问题: 你知道 laf 么?
|
||||
输出: 你知道 laf 么?
|
||||
----------------
|
||||
历史记录:
|
||||
"""
|
||||
Q: FastGPT 的优势
|
||||
A: 1. 开源
|
||||
2. 简便
|
||||
3. 扩展性强
|
||||
"""
|
||||
当前问题: 介绍下第2点。
|
||||
输出: 介绍下 FastGPT 简便的优势。
|
||||
----------------
|
||||
历史记录:
|
||||
"""
|
||||
Q: 什么是 FastGPT?
|
||||
A: FastGPT 是一个 RAG 平台。
|
||||
Q: 什么是 Sealos?
|
||||
A: Sealos 是一个云操作系统。
|
||||
"""
|
||||
当前问题: 它们有什么关系?
|
||||
输出: FastGPT 和 Sealos 有什么关系?
|
||||
----------------
|
||||
历史记录:
|
||||
"""
|
||||
{{histories}}
|
||||
"""
|
||||
当前问题: {{query}}
|
||||
输出: `;
|
||||
|
||||
export const queryCfr = async ({
|
||||
chatBg,
|
||||
query,
|
||||
histories = [],
|
||||
model
|
||||
}: {
|
||||
chatBg?: string;
|
||||
query: string;
|
||||
histories: ChatItemType[];
|
||||
model: string;
|
||||
}) => {
|
||||
if (histories.length === 0 && !chatBg) {
|
||||
return {
|
||||
rawQuery: query,
|
||||
cfrQuery: query,
|
||||
model,
|
||||
inputTokens: 0,
|
||||
outputTokens: 0
|
||||
};
|
||||
}
|
||||
|
||||
const systemFewShot = chatBg
|
||||
? `Q: 对话背景。
|
||||
A: ${chatBg}
|
||||
`
|
||||
: '';
|
||||
const historyFewShot = histories
|
||||
.map((item) => {
|
||||
const role = item.obj === 'Human' ? 'Q' : 'A';
|
||||
return `${role}: ${item.value}`;
|
||||
})
|
||||
.join('\n');
|
||||
const concatFewShot = `${systemFewShot}${historyFewShot}`.trim();
|
||||
|
||||
const ai = getAIApi({
|
||||
timeout: 480000
|
||||
});
|
||||
|
||||
const result = await ai.chat.completions.create({
|
||||
model: model,
|
||||
temperature: 0.01,
|
||||
max_tokens: 150,
|
||||
messages: [
|
||||
{
|
||||
role: 'user',
|
||||
content: replaceVariable(defaultPrompt, {
|
||||
query: `${query}`,
|
||||
histories: concatFewShot
|
||||
})
|
||||
}
|
||||
],
|
||||
stream: false
|
||||
});
|
||||
|
||||
const answer = result.choices?.[0]?.message?.content || '';
|
||||
if (!answer) {
|
||||
return {
|
||||
rawQuery: query,
|
||||
cfrQuery: query,
|
||||
model,
|
||||
inputTokens: 0,
|
||||
outputTokens: 0
|
||||
};
|
||||
}
|
||||
|
||||
return {
|
||||
rawQuery: query,
|
||||
cfrQuery: answer,
|
||||
model,
|
||||
inputTokens: result.usage?.prompt_tokens || 0,
|
||||
outputTokens: result.usage?.completion_tokens || 0
|
||||
};
|
||||
};
|
@@ -1,5 +1,6 @@
|
||||
import type { ChatMessageItemType } from '@fastgpt/global/core/ai/type.d';
|
||||
import { getAIApi } from '../config';
|
||||
import { countGptMessagesChars } from '../../chat/utils';
|
||||
|
||||
export const Prompt_QuestionGuide = `我不太清楚问你什么问题,请帮我生成 3 个问题,引导我继续提问。问题的长度应小于20个字符,按 JSON 格式返回: ["问题1", "问题2", "问题3"]`;
|
||||
|
||||
@@ -10,6 +11,13 @@ export async function createQuestionGuide({
|
||||
messages: ChatMessageItemType[];
|
||||
model: string;
|
||||
}) {
|
||||
const concatMessages: ChatMessageItemType[] = [
|
||||
...messages,
|
||||
{
|
||||
role: 'user',
|
||||
content: Prompt_QuestionGuide
|
||||
}
|
||||
];
|
||||
const ai = getAIApi({
|
||||
timeout: 480000
|
||||
});
|
||||
@@ -17,28 +25,21 @@ export async function createQuestionGuide({
|
||||
model: model,
|
||||
temperature: 0.1,
|
||||
max_tokens: 200,
|
||||
messages: [
|
||||
...messages,
|
||||
{
|
||||
role: 'user',
|
||||
content: Prompt_QuestionGuide
|
||||
}
|
||||
],
|
||||
messages: concatMessages,
|
||||
stream: false
|
||||
});
|
||||
|
||||
const answer = data.choices?.[0]?.message?.content || '';
|
||||
const inputTokens = data.usage?.prompt_tokens || 0;
|
||||
const outputTokens = data.usage?.completion_tokens || 0;
|
||||
|
||||
const start = answer.indexOf('[');
|
||||
const end = answer.lastIndexOf(']');
|
||||
|
||||
const charsLength = countGptMessagesChars(concatMessages);
|
||||
|
||||
if (start === -1 || end === -1) {
|
||||
return {
|
||||
result: [],
|
||||
inputTokens,
|
||||
outputTokens
|
||||
charsLength: 0
|
||||
};
|
||||
}
|
||||
|
||||
@@ -50,14 +51,12 @@ export async function createQuestionGuide({
|
||||
try {
|
||||
return {
|
||||
result: JSON.parse(jsonStr),
|
||||
inputTokens,
|
||||
outputTokens
|
||||
charsLength
|
||||
};
|
||||
} catch (error) {
|
||||
return {
|
||||
result: [],
|
||||
inputTokens,
|
||||
outputTokens
|
||||
charsLength: 0
|
||||
};
|
||||
}
|
||||
}
|
||||
|
@@ -1,18 +1,19 @@
|
||||
import { replaceVariable } from '@fastgpt/global/common/string/tools';
|
||||
import { getAIApi } from '../config';
|
||||
import { ChatItemType } from '@fastgpt/global/core/chat/type';
|
||||
import { countGptMessagesChars } from '../../chat/utils';
|
||||
|
||||
/*
|
||||
query extension - 问题扩展
|
||||
可以根据上下文,消除指代性问题以及扩展问题,利于检索。
|
||||
*/
|
||||
|
||||
const defaultPrompt = `作为一个向量检索助手,你的任务是结合历史记录,从不同角度,为“原问题”生成个不同版本的“检索词”,从而提高向量检索的语义丰富度,提高向量检索的精度。生成的问题要求指向对象清晰明确。例如:
|
||||
const defaultPrompt = `作为一个向量检索助手,你的任务是结合历史记录,从不同角度,为“原问题”生成个不同版本的“检索词”,从而提高向量检索的语义丰富度,提高向量检索的精度。生成的问题要求指向对象清晰明确,并与原问题语言相同。例如:
|
||||
历史记录:
|
||||
"""
|
||||
"""
|
||||
原问题: 介绍下剧情。
|
||||
检索词: ["发生了什么故事?","故事梗概是什么?","讲述了什么故事?"]
|
||||
检索词: ["介绍下故事的背景和主要人物。","故事的主题是什么?","剧情是是如何发展的?"]
|
||||
----------------
|
||||
历史记录:
|
||||
"""
|
||||
@@ -20,7 +21,7 @@ Q: 对话背景。
|
||||
A: 当前对话是关于 FatGPT 的介绍和使用等。
|
||||
"""
|
||||
原问题: 怎么下载
|
||||
检索词: ["FastGPT 怎么下载?","下载 FastGPT 需要什么条件?","有哪些渠道可以下载 FastGPT?"]
|
||||
检索词: ["FastGPT 如何下载?","下载 FastGPT 需要什么条件?","有哪些渠道可以下载 FastGPT?"]
|
||||
----------------
|
||||
历史记录:
|
||||
"""
|
||||
@@ -30,15 +31,15 @@ Q: 报错 "no connection"
|
||||
A: 报错"no connection"可能是因为……
|
||||
"""
|
||||
原问题: 怎么解决
|
||||
检索词: ["FastGPT 报错"no connection"如何解决?", "报错 'no connection' 是什么原因?", "FastGPT提示'no connection',要怎么办?"]
|
||||
检索词: ["FastGPT 报错"no connection"如何解决?", "造成 'no connection' 报错的原因。", "FastGPT提示'no connection',要怎么办?"]
|
||||
----------------
|
||||
历史记录:
|
||||
"""
|
||||
Q: 作者是谁?
|
||||
A: FastGPT 的作者是 labring。
|
||||
"""
|
||||
原问题: 介绍下他
|
||||
检索词: ["介绍下 FastGPT 的作者 labring。","作者 labring 的背景信息。","labring 为什么要做 FastGPT?"]
|
||||
原问题: Tell me about him
|
||||
检索词: ["Introduce labring, the author of FastGPT." ," Background information on author labring." "," Why does labring do FastGPT?"]
|
||||
----------------
|
||||
历史记录:
|
||||
"""
|
||||
@@ -105,8 +106,7 @@ export const queryExtension = async ({
|
||||
rawQuery: string;
|
||||
extensionQueries: string[];
|
||||
model: string;
|
||||
inputTokens: number;
|
||||
outputTokens: number;
|
||||
charsLength: number;
|
||||
}> => {
|
||||
const systemFewShot = chatBg
|
||||
? `Q: 对话背景。
|
||||
@@ -125,18 +125,20 @@ A: ${chatBg}
|
||||
timeout: 480000
|
||||
});
|
||||
|
||||
const messages = [
|
||||
{
|
||||
role: 'user',
|
||||
content: replaceVariable(defaultPrompt, {
|
||||
query: `${query}`,
|
||||
histories: concatFewShot
|
||||
})
|
||||
}
|
||||
];
|
||||
const result = await ai.chat.completions.create({
|
||||
model: model,
|
||||
temperature: 0.01,
|
||||
messages: [
|
||||
{
|
||||
role: 'user',
|
||||
content: replaceVariable(defaultPrompt, {
|
||||
query: `${query}`,
|
||||
histories: concatFewShot
|
||||
})
|
||||
}
|
||||
],
|
||||
// @ts-ignore
|
||||
messages,
|
||||
stream: false
|
||||
});
|
||||
|
||||
@@ -146,8 +148,7 @@ A: ${chatBg}
|
||||
rawQuery: query,
|
||||
extensionQueries: [],
|
||||
model,
|
||||
inputTokens: 0,
|
||||
outputTokens: 0
|
||||
charsLength: 0
|
||||
};
|
||||
}
|
||||
|
||||
@@ -160,8 +161,7 @@ A: ${chatBg}
|
||||
rawQuery: query,
|
||||
extensionQueries: queries,
|
||||
model,
|
||||
inputTokens: result.usage?.prompt_tokens || 0,
|
||||
outputTokens: result.usage?.completion_tokens || 0
|
||||
charsLength: countGptMessagesChars(messages)
|
||||
};
|
||||
} catch (error) {
|
||||
console.log(error);
|
||||
@@ -169,8 +169,7 @@ A: ${chatBg}
|
||||
rawQuery: query,
|
||||
extensionQueries: [],
|
||||
model,
|
||||
inputTokens: 0,
|
||||
outputTokens: 0
|
||||
charsLength: 0
|
||||
};
|
||||
}
|
||||
};
|
||||
|
@@ -61,6 +61,9 @@ const AppSchema = new Schema({
|
||||
type: String,
|
||||
enum: Object.keys(PermissionTypeMap),
|
||||
default: PermissionTypeEnum.private
|
||||
},
|
||||
teamTags: {
|
||||
type: [String]
|
||||
}
|
||||
});
|
||||
|
||||
|
@@ -92,6 +92,8 @@ try {
|
||||
ChatItemSchema.index({ appId: 1, chatId: 1, dataId: 1 }, { background: true });
|
||||
// admin charts
|
||||
ChatItemSchema.index({ time: -1, obj: 1 }, { background: true });
|
||||
// timer, clear history
|
||||
ChatItemSchema.index({ teamId: 1, time: -1 }, { background: true });
|
||||
} catch (error) {
|
||||
console.log(error);
|
||||
}
|
||||
|
@@ -83,6 +83,9 @@ try {
|
||||
ChatSchema.index({ teamId: 1, appId: 1, updateTime: -1 }, { background: true });
|
||||
// get share chat history
|
||||
ChatSchema.index({ shareId: 1, outLinkUid: 1, updateTime: -1, source: 1 }, { background: true });
|
||||
|
||||
// timer, clear history
|
||||
ChatSchema.index({ teamId: 1, updateTime: -1 }, { background: true });
|
||||
} catch (error) {
|
||||
console.log(error);
|
||||
}
|
||||
|
@@ -2,7 +2,10 @@ import type { ChatItemType } from '@fastgpt/global/core/chat/type.d';
|
||||
import { ChatRoleEnum, IMG_BLOCK_KEY } from '@fastgpt/global/core/chat/constants';
|
||||
import { countMessagesTokens, countPromptTokens } from '@fastgpt/global/common/string/tiktoken';
|
||||
import { adaptRole_Chat2Message } from '@fastgpt/global/core/chat/adapt';
|
||||
import type { ChatCompletionContentPart } from '@fastgpt/global/core/ai/type.d';
|
||||
import type {
|
||||
ChatCompletionContentPart,
|
||||
ChatMessageItemType
|
||||
} from '@fastgpt/global/core/ai/type.d';
|
||||
import axios from 'axios';
|
||||
|
||||
/* slice chat context by tokens */
|
||||
@@ -56,6 +59,16 @@ export function ChatContextFilter({
|
||||
return [...systemPrompts, ...chats];
|
||||
}
|
||||
|
||||
export const replaceValidChars = (str: string) => {
|
||||
const reg = /[\s\r\n]+/g;
|
||||
return str.replace(reg, '');
|
||||
};
|
||||
export const countMessagesChars = (messages: ChatItemType[]) => {
|
||||
return messages.reduce((sum, item) => sum + replaceValidChars(item.value).length, 0);
|
||||
};
|
||||
export const countGptMessagesChars = (messages: ChatMessageItemType[]) =>
|
||||
messages.reduce((sum, item) => sum + replaceValidChars(item.content).length, 0);
|
||||
|
||||
/**
|
||||
string to vision model. Follow the markdown code block rule for interception:
|
||||
|
||||
|
@@ -147,8 +147,6 @@ export async function delCollectionAndRelatedSources({
|
||||
collectionId: { $in: collectionIds }
|
||||
});
|
||||
|
||||
await delay(2000);
|
||||
|
||||
// delete dataset.datas
|
||||
await MongoDatasetData.deleteMany({ teamId, collectionId: { $in: collectionIds } }, { session });
|
||||
// delete imgs
|
||||
|
@@ -66,6 +66,11 @@ export async function delDatasetRelevantData({
|
||||
if (!datasets.length) return;
|
||||
|
||||
const teamId = datasets[0].teamId;
|
||||
|
||||
if (!teamId) {
|
||||
return Promise.reject('teamId is required');
|
||||
}
|
||||
|
||||
const datasetIds = datasets.map((item) => String(item._id));
|
||||
|
||||
// Get _id, teamId, fileId, metadata.relatedImgId for all collections
|
||||
|
@@ -7,10 +7,6 @@ import {
|
||||
} from '@fastgpt/global/support/user/team/constant';
|
||||
import { DatasetCollectionName } from '../schema';
|
||||
import { DatasetColCollectionName } from '../collection/schema';
|
||||
import {
|
||||
DatasetDataIndexTypeEnum,
|
||||
DatasetDataIndexTypeMap
|
||||
} from '@fastgpt/global/core/dataset/constants';
|
||||
|
||||
export const DatasetDataCollectionName = 'dataset.datas';
|
||||
|
||||
@@ -54,11 +50,6 @@ const DatasetDataSchema = new Schema({
|
||||
type: Boolean,
|
||||
default: false
|
||||
},
|
||||
type: {
|
||||
type: String,
|
||||
enum: Object.keys(DatasetDataIndexTypeMap),
|
||||
default: DatasetDataIndexTypeEnum.custom
|
||||
},
|
||||
dataId: {
|
||||
type: String,
|
||||
required: true
|
||||
|
@@ -14,22 +14,54 @@ export const datasetSearchQueryExtension = async ({
|
||||
extensionBg?: string;
|
||||
histories?: ChatItemType[];
|
||||
}) => {
|
||||
// concat query
|
||||
let queries = [query];
|
||||
let rewriteQuery =
|
||||
histories.length > 0
|
||||
? `${histories
|
||||
.map((item) => {
|
||||
return `${item.obj}: ${item.value}`;
|
||||
})
|
||||
.join('\n')}
|
||||
Human: ${query}
|
||||
`
|
||||
: query;
|
||||
const filterSamQuery = (queries: string[]) => {
|
||||
const set = new Set<string>();
|
||||
const filterSameQueries = queries.filter((item) => {
|
||||
// 删除所有的标点符号与空格等,只对文本进行比较
|
||||
const str = hashStr(item.replace(/[^\p{L}\p{N}]/gu, ''));
|
||||
if (set.has(str)) return false;
|
||||
set.add(str);
|
||||
return true;
|
||||
});
|
||||
|
||||
return filterSameQueries;
|
||||
};
|
||||
|
||||
let { queries, rewriteQuery, alreadyExtension } = (() => {
|
||||
// concat query
|
||||
let rewriteQuery =
|
||||
histories.length > 0
|
||||
? `${histories
|
||||
.map((item) => {
|
||||
return `${item.obj}: ${item.value}`;
|
||||
})
|
||||
.join('\n')}
|
||||
Human: ${query}
|
||||
`
|
||||
: query;
|
||||
|
||||
/* if query already extension, direct parse */
|
||||
try {
|
||||
const jsonParse = JSON.parse(query);
|
||||
const queries: string[] = Array.isArray(jsonParse) ? filterSamQuery(jsonParse) : [query];
|
||||
const alreadyExtension = Array.isArray(jsonParse);
|
||||
return {
|
||||
queries,
|
||||
rewriteQuery: alreadyExtension ? queries.join('\n') : rewriteQuery,
|
||||
alreadyExtension: alreadyExtension
|
||||
};
|
||||
} catch (error) {
|
||||
return {
|
||||
queries: [query],
|
||||
rewriteQuery,
|
||||
alreadyExtension: false
|
||||
};
|
||||
}
|
||||
})();
|
||||
|
||||
// ai extension
|
||||
const aiExtensionResult = await (async () => {
|
||||
if (!extensionModel) return;
|
||||
if (!extensionModel || alreadyExtension) return;
|
||||
const result = await queryExtension({
|
||||
chatBg: extensionBg,
|
||||
query,
|
||||
@@ -39,23 +71,13 @@ export const datasetSearchQueryExtension = async ({
|
||||
if (result.extensionQueries?.length === 0) return;
|
||||
return result;
|
||||
})();
|
||||
|
||||
if (aiExtensionResult) {
|
||||
queries = queries.concat(aiExtensionResult.extensionQueries);
|
||||
queries = filterSamQuery(queries.concat(aiExtensionResult.extensionQueries));
|
||||
rewriteQuery = queries.join('\n');
|
||||
}
|
||||
|
||||
const set = new Set<string>();
|
||||
const filterSameQueries = queries.filter((item) => {
|
||||
// 删除所有的标点符号与空格等,只对文本进行比较
|
||||
const str = hashStr(item.replace(/[^\p{L}\p{N}]/gu, ''));
|
||||
if (set.has(str)) return false;
|
||||
set.add(str);
|
||||
return true;
|
||||
});
|
||||
|
||||
return {
|
||||
concatQueries: filterSameQueries,
|
||||
concatQueries: queries,
|
||||
rewriteQuery,
|
||||
aiExtensionResult
|
||||
};
|
||||
|
@@ -11,7 +11,7 @@ import { simpleText } from '@fastgpt/global/common/string/tools';
|
||||
import { countPromptTokens } from '@fastgpt/global/common/string/tiktoken';
|
||||
import type { VectorModelItemType, LLMModelItemType } from '@fastgpt/global/core/ai/model.d';
|
||||
|
||||
export const lockTrainingDataByTeamId = async (teamId: string, retry = 3): Promise<any> => {
|
||||
export const lockTrainingDataByTeamId = async (teamId: string): Promise<any> => {
|
||||
try {
|
||||
await MongoDatasetTraining.updateMany(
|
||||
{
|
||||
@@ -21,13 +21,7 @@ export const lockTrainingDataByTeamId = async (teamId: string, retry = 3): Promi
|
||||
lockTime: new Date('2999/5/5')
|
||||
}
|
||||
);
|
||||
} catch (error) {
|
||||
if (retry > 0) {
|
||||
await delay(1000);
|
||||
return lockTrainingDataByTeamId(teamId, retry - 1);
|
||||
}
|
||||
return Promise.reject(error);
|
||||
}
|
||||
} catch (error) {}
|
||||
};
|
||||
|
||||
export async function pushDataListToTrainingQueue({
|
||||
@@ -51,17 +45,15 @@ export async function pushDataListToTrainingQueue({
|
||||
datasetId: { _id: datasetId, vectorModel, agentModel }
|
||||
} = await getCollectionWithDataset(collectionId);
|
||||
|
||||
const checkModelValid = async ({ collectionId }: { collectionId: string }) => {
|
||||
if (!collectionId) return Promise.reject(`CollectionId is empty`);
|
||||
|
||||
const checkModelValid = async () => {
|
||||
if (trainingMode === TrainingModeEnum.chunk) {
|
||||
const vectorModelData = vectorModelList?.find((item) => item.model === vectorModel);
|
||||
if (!vectorModelData) {
|
||||
return Promise.reject(`Model ${vectorModel} is inValid`);
|
||||
return Promise.reject(`File model ${vectorModel} is inValid`);
|
||||
}
|
||||
|
||||
return {
|
||||
maxToken: vectorModelData.maxToken * 1.5,
|
||||
maxToken: vectorModelData.maxToken * 1.3,
|
||||
model: vectorModelData.model,
|
||||
weight: vectorModelData.weight
|
||||
};
|
||||
@@ -70,7 +62,7 @@ export async function pushDataListToTrainingQueue({
|
||||
if (trainingMode === TrainingModeEnum.qa) {
|
||||
const qaModelData = datasetModelList?.find((item) => item.model === agentModel);
|
||||
if (!qaModelData) {
|
||||
return Promise.reject(`Model ${agentModel} is inValid`);
|
||||
return Promise.reject(`Vector model ${agentModel} is inValid`);
|
||||
}
|
||||
return {
|
||||
maxToken: qaModelData.maxContext * 0.8,
|
||||
@@ -81,9 +73,7 @@ export async function pushDataListToTrainingQueue({
|
||||
return Promise.reject(`Training mode "${trainingMode}" is inValid`);
|
||||
};
|
||||
|
||||
const { model, maxToken, weight } = await checkModelValid({
|
||||
collectionId
|
||||
});
|
||||
const { model, maxToken, weight } = await checkModelValid();
|
||||
|
||||
// format q and a, remove empty char
|
||||
data.forEach((item) => {
|
||||
|
@@ -2,7 +2,7 @@
|
||||
import { connectionMongo, type Model } from '../../../common/mongo';
|
||||
const { Schema, model, models } = connectionMongo;
|
||||
import { DatasetTrainingSchemaType } from '@fastgpt/global/core/dataset/type';
|
||||
import { DatasetDataIndexTypeMap, TrainingTypeMap } from '@fastgpt/global/core/dataset/constants';
|
||||
import { TrainingTypeMap } from '@fastgpt/global/core/dataset/constants';
|
||||
import { DatasetColCollectionName } from '../collection/schema';
|
||||
import { DatasetCollectionName } from '../schema';
|
||||
import {
|
||||
@@ -86,11 +86,6 @@ const TrainingDataSchema = new Schema({
|
||||
indexes: {
|
||||
type: [
|
||||
{
|
||||
type: {
|
||||
type: String,
|
||||
enum: Object.keys(DatasetDataIndexTypeMap),
|
||||
required: true
|
||||
},
|
||||
text: {
|
||||
type: String,
|
||||
required: true
|
||||
|
@@ -15,7 +15,7 @@
|
||||
"nextjs-cors": "^2.1.2",
|
||||
"node-cron": "^3.0.3",
|
||||
"pg": "^8.10.0",
|
||||
"date-fns": "^2.30.0",
|
||||
"date-fns": "2.30.0",
|
||||
"tunnel": "^0.0.6"
|
||||
},
|
||||
"devDependencies": {
|
||||
|
@@ -19,14 +19,15 @@ export async function authOpenApiKey({ apikey }: { apikey: string }) {
|
||||
// auth limit
|
||||
// @ts-ignore
|
||||
if (global.feConfigs?.isPlus) {
|
||||
await POST('/support/openapi/authLimit', { openApi } as AuthOpenApiLimitProps);
|
||||
await POST('/support/openapi/authLimit', {
|
||||
openApi: openApi.toObject()
|
||||
} as AuthOpenApiLimitProps);
|
||||
}
|
||||
|
||||
updateApiKeyUsedTime(openApi._id);
|
||||
|
||||
return {
|
||||
apikey,
|
||||
userId: String(openApi.userId),
|
||||
teamId: String(openApi.teamId),
|
||||
tmbId: String(openApi.tmbId),
|
||||
appId: openApi.appId || ''
|
||||
|
@@ -1,8 +1,6 @@
|
||||
import { connectionMongo, type Model } from '../../common/mongo';
|
||||
const { Schema, model, models } = connectionMongo;
|
||||
import type { OpenApiSchema } from '@fastgpt/global/support/openapi/type';
|
||||
import { PRICE_SCALE } from '@fastgpt/global/support/wallet/bill/constants';
|
||||
import { formatStorePrice2Read } from '@fastgpt/global/support/wallet/bill/tools';
|
||||
import {
|
||||
TeamCollectionName,
|
||||
TeamMemberCollectionName
|
||||
@@ -10,10 +8,6 @@ import {
|
||||
|
||||
const OpenApiSchema = new Schema(
|
||||
{
|
||||
userId: {
|
||||
type: Schema.Types.ObjectId,
|
||||
ref: 'user'
|
||||
},
|
||||
teamId: {
|
||||
type: Schema.Types.ObjectId,
|
||||
ref: TeamCollectionName,
|
||||
@@ -44,22 +38,17 @@ const OpenApiSchema = new Schema(
|
||||
type: String,
|
||||
default: 'Api Key'
|
||||
},
|
||||
usage: {
|
||||
// total usage. value from bill total
|
||||
usagePoints: {
|
||||
type: Number,
|
||||
default: 0,
|
||||
get: (val: number) => formatStorePrice2Read(val)
|
||||
default: 0
|
||||
},
|
||||
limit: {
|
||||
expiredTime: {
|
||||
type: Date
|
||||
},
|
||||
credit: {
|
||||
// value from user settings
|
||||
maxUsagePoints: {
|
||||
type: Number,
|
||||
default: -1,
|
||||
set: (val: number) => val * PRICE_SCALE,
|
||||
get: (val: number) => formatStorePrice2Read(val)
|
||||
default: -1
|
||||
}
|
||||
}
|
||||
},
|
||||
|
@@ -8,15 +8,21 @@ export function updateApiKeyUsedTime(id: string) {
|
||||
});
|
||||
}
|
||||
|
||||
export function updateApiKeyUsage({ apikey, usage }: { apikey: string; usage: number }) {
|
||||
export function updateApiKeyUsage({
|
||||
apikey,
|
||||
totalPoints
|
||||
}: {
|
||||
apikey: string;
|
||||
totalPoints: number;
|
||||
}) {
|
||||
MongoOpenApi.findOneAndUpdate(
|
||||
{ apiKey: apikey },
|
||||
{
|
||||
$inc: {
|
||||
usage
|
||||
usagePoints: totalPoints
|
||||
}
|
||||
}
|
||||
).catch((err) => {
|
||||
console.log('update apiKey usage error', err);
|
||||
console.log('update apiKey totalPoints error', err);
|
||||
});
|
||||
}
|
||||
|
@@ -35,8 +35,7 @@ const OutLinkSchema = new Schema({
|
||||
type: String,
|
||||
required: true
|
||||
},
|
||||
total: {
|
||||
// total amount
|
||||
usagePoints: {
|
||||
type: Number,
|
||||
default: 0
|
||||
},
|
||||
@@ -48,6 +47,10 @@ const OutLinkSchema = new Schema({
|
||||
default: false
|
||||
},
|
||||
limit: {
|
||||
maxUsagePoints: {
|
||||
type: Number,
|
||||
default: -1
|
||||
},
|
||||
expiredTime: {
|
||||
type: Date
|
||||
},
|
||||
@@ -55,16 +58,18 @@ const OutLinkSchema = new Schema({
|
||||
type: Number,
|
||||
default: 1000
|
||||
},
|
||||
credit: {
|
||||
type: Number,
|
||||
default: -1
|
||||
},
|
||||
hookUrl: {
|
||||
type: String
|
||||
}
|
||||
}
|
||||
});
|
||||
|
||||
try {
|
||||
OutLinkSchema.index({ shareId: -1 });
|
||||
} catch (error) {
|
||||
console.log(error);
|
||||
}
|
||||
|
||||
export const MongoOutLink: Model<SchemaType> =
|
||||
models['outlinks'] || model('outlinks', OutLinkSchema);
|
||||
|
||||
|
@@ -1,18 +1,19 @@
|
||||
import axios from 'axios';
|
||||
import { MongoOutLink } from './schema';
|
||||
import { FastGPTProUrl } from '../../common/system/constants';
|
||||
import { ChatHistoryItemResType } from '@fastgpt/global/core/chat/type';
|
||||
|
||||
export const updateOutLinkUsage = async ({
|
||||
export const addOutLinkUsage = async ({
|
||||
shareId,
|
||||
total
|
||||
totalPoints
|
||||
}: {
|
||||
shareId: string;
|
||||
total: number;
|
||||
totalPoints: number;
|
||||
}) => {
|
||||
MongoOutLink.findOneAndUpdate(
|
||||
{ shareId },
|
||||
{
|
||||
$inc: { total },
|
||||
$inc: { usagePoints: totalPoints },
|
||||
lastTime: new Date()
|
||||
}
|
||||
).catch((err) => {
|
||||
@@ -23,11 +24,13 @@ export const updateOutLinkUsage = async ({
|
||||
export const pushResult2Remote = async ({
|
||||
outLinkUid,
|
||||
shareId,
|
||||
appName,
|
||||
responseData
|
||||
}: {
|
||||
outLinkUid?: string; // raw id, not parse
|
||||
shareId?: string;
|
||||
responseData?: any[];
|
||||
appName: string;
|
||||
responseData?: ChatHistoryItemResType[];
|
||||
}) => {
|
||||
if (!shareId || !outLinkUid || !FastGPTProUrl) return;
|
||||
try {
|
||||
@@ -42,6 +45,7 @@ export const pushResult2Remote = async ({
|
||||
url: '/shareAuth/finish',
|
||||
data: {
|
||||
token: outLinkUid,
|
||||
appName,
|
||||
responseData
|
||||
}
|
||||
});
|
||||
|
@@ -107,7 +107,7 @@ export async function authDatasetCollection({
|
||||
collection: CollectionWithDatasetType;
|
||||
}
|
||||
> {
|
||||
const { userId, teamId, tmbId } = await parseHeaderCert(props);
|
||||
const { teamId, tmbId } = await parseHeaderCert(props);
|
||||
const { role } = await getTmbInfoByTmbId({ tmbId });
|
||||
|
||||
const { collection, isOwner, canWrite } = await (async () => {
|
||||
@@ -143,7 +143,6 @@ export async function authDatasetCollection({
|
||||
})();
|
||||
|
||||
return {
|
||||
userId,
|
||||
teamId,
|
||||
tmbId,
|
||||
collection,
|
||||
@@ -163,7 +162,7 @@ export async function authDatasetFile({
|
||||
file: DatasetFileSchema;
|
||||
}
|
||||
> {
|
||||
const { userId, teamId, tmbId } = await parseHeaderCert(props);
|
||||
const { teamId, tmbId } = await parseHeaderCert(props);
|
||||
|
||||
const [file, collection] = await Promise.all([
|
||||
getFileById({ bucketName: BucketNameEnum.dataset, fileId }),
|
||||
@@ -190,7 +189,6 @@ export async function authDatasetFile({
|
||||
});
|
||||
|
||||
return {
|
||||
userId,
|
||||
teamId,
|
||||
tmbId,
|
||||
file,
|
||||
|
@@ -12,7 +12,7 @@ export async function authUserNotVisitor(props: AuthModeType): Promise<
|
||||
role: `${TeamMemberRoleEnum}`;
|
||||
}
|
||||
> {
|
||||
const { userId, teamId, tmbId } = await parseHeaderCert(props);
|
||||
const { teamId, tmbId } = await parseHeaderCert(props);
|
||||
const team = await getTmbInfoByTmbId({ tmbId });
|
||||
|
||||
if (team.role === TeamMemberRoleEnum.visitor) {
|
||||
@@ -20,7 +20,6 @@ export async function authUserNotVisitor(props: AuthModeType): Promise<
|
||||
}
|
||||
|
||||
return {
|
||||
userId,
|
||||
teamId,
|
||||
tmbId,
|
||||
team,
|
||||
|
@@ -94,10 +94,10 @@ export async function parseHeaderCert({
|
||||
})();
|
||||
|
||||
// auth apikey
|
||||
const { userId, teamId, tmbId, appId: apiKeyAppId = '' } = await authOpenApiKey({ apikey });
|
||||
const { teamId, tmbId, appId: apiKeyAppId = '' } = await authOpenApiKey({ apikey });
|
||||
|
||||
return {
|
||||
uid: userId,
|
||||
uid: '',
|
||||
teamId,
|
||||
tmbId,
|
||||
apikey,
|
||||
|
@@ -1,23 +0,0 @@
|
||||
import { StandSubPlanLevelMapType } from '@fastgpt/global/support/wallet/sub/type';
|
||||
import { getVectorCountByTeamId } from '../../../common/vectorStore/controller';
|
||||
import { getTeamDatasetMaxSize } from '../../wallet/sub/utils';
|
||||
|
||||
export const checkDatasetLimit = async ({
|
||||
teamId,
|
||||
insertLen = 0,
|
||||
standardPlans
|
||||
}: {
|
||||
teamId: string;
|
||||
insertLen?: number;
|
||||
standardPlans?: StandSubPlanLevelMapType;
|
||||
}) => {
|
||||
const [{ maxSize }, usedSize] = await Promise.all([
|
||||
getTeamDatasetMaxSize({ teamId, standardPlans }),
|
||||
getVectorCountByTeamId(teamId)
|
||||
]);
|
||||
|
||||
if (usedSize + insertLen >= maxSize) {
|
||||
return Promise.reject(`数据库容量不足,无法继续添加。可以在账号页面进行扩容。`);
|
||||
}
|
||||
return;
|
||||
};
|
91
packages/service/support/permission/teamLimit.ts
Normal file
91
packages/service/support/permission/teamLimit.ts
Normal file
@@ -0,0 +1,91 @@
|
||||
import { getVectorCountByTeamId } from '../../common/vectorStore/controller';
|
||||
import { getTeamPlanStatus, getTeamStandPlan } from '../../support/wallet/sub/utils';
|
||||
import { MongoApp } from '../../core/app/schema';
|
||||
import { MongoPlugin } from '../../core/plugin/schema';
|
||||
import { MongoDataset } from '../../core/dataset/schema';
|
||||
import { DatasetTypeEnum } from '@fastgpt/global/core/dataset/constants';
|
||||
import { TeamErrEnum } from '@fastgpt/global/common/error/code/team';
|
||||
|
||||
export const checkDatasetLimit = async ({
|
||||
teamId,
|
||||
insertLen = 0
|
||||
}: {
|
||||
teamId: string;
|
||||
insertLen?: number;
|
||||
}) => {
|
||||
const [{ standardConstants, totalPoints, usedPoints, datasetMaxSize }, usedSize] =
|
||||
await Promise.all([getTeamPlanStatus({ teamId }), getVectorCountByTeamId(teamId)]);
|
||||
|
||||
if (!standardConstants) return;
|
||||
|
||||
if (usedSize + insertLen >= datasetMaxSize) {
|
||||
return Promise.reject(TeamErrEnum.datasetSizeNotEnough);
|
||||
}
|
||||
|
||||
if (usedPoints >= totalPoints) {
|
||||
return Promise.reject(TeamErrEnum.aiPointsNotEnough);
|
||||
}
|
||||
return;
|
||||
};
|
||||
|
||||
export const checkTeamAIPoints = async (teamId: string) => {
|
||||
const { standardConstants, totalPoints, usedPoints } = await getTeamPlanStatus({
|
||||
teamId
|
||||
});
|
||||
|
||||
if (!standardConstants) return;
|
||||
|
||||
if (usedPoints >= totalPoints) {
|
||||
return Promise.reject(TeamErrEnum.aiPointsNotEnough);
|
||||
}
|
||||
|
||||
return {
|
||||
totalPoints,
|
||||
usedPoints
|
||||
};
|
||||
};
|
||||
|
||||
export const checkTeamDatasetLimit = async (teamId: string) => {
|
||||
const [{ standardConstants }, datasetCount] = await Promise.all([
|
||||
getTeamStandPlan({ teamId }),
|
||||
MongoDataset.countDocuments({
|
||||
teamId,
|
||||
type: { $ne: DatasetTypeEnum.folder }
|
||||
})
|
||||
]);
|
||||
|
||||
if (standardConstants && datasetCount >= standardConstants.maxDatasetAmount) {
|
||||
return Promise.reject(TeamErrEnum.datasetAmountNotEnough);
|
||||
}
|
||||
};
|
||||
export const checkTeamAppLimit = async (teamId: string) => {
|
||||
const [{ standardConstants }, appCount] = await Promise.all([
|
||||
getTeamStandPlan({ teamId }),
|
||||
MongoApp.count({ teamId })
|
||||
]);
|
||||
|
||||
if (standardConstants && appCount >= standardConstants.maxAppAmount) {
|
||||
return Promise.reject(TeamErrEnum.appAmountNotEnough);
|
||||
}
|
||||
};
|
||||
export const checkTeamPluginLimit = async (teamId: string) => {
|
||||
const [{ standardConstants }, pluginCount] = await Promise.all([
|
||||
getTeamStandPlan({ teamId }),
|
||||
MongoPlugin.count({ teamId })
|
||||
]);
|
||||
|
||||
if (standardConstants && pluginCount >= standardConstants.maxAppAmount) {
|
||||
return Promise.reject(TeamErrEnum.pluginAmountNotEnough);
|
||||
}
|
||||
};
|
||||
|
||||
export const checkTeamReRankPermission = async (teamId: string) => {
|
||||
const { standardConstants } = await getTeamStandPlan({
|
||||
teamId
|
||||
});
|
||||
|
||||
if (standardConstants && !standardConstants?.permissionReRank) {
|
||||
return false;
|
||||
}
|
||||
return true;
|
||||
};
|
@@ -2,7 +2,6 @@ import { UserType } from '@fastgpt/global/support/user/type';
|
||||
import { MongoUser } from './schema';
|
||||
import { getTmbInfoByTmbId, getUserDefaultTeam } from './team/controller';
|
||||
import { ERROR_ENUM } from '@fastgpt/global/common/error/errorCode';
|
||||
import { UserErrEnum } from '@fastgpt/global/common/error/code/user';
|
||||
|
||||
export async function authUserExist({ userId, username }: { userId?: string; username?: string }) {
|
||||
if (userId) {
|
||||
@@ -47,22 +46,3 @@ export async function getUserDetail({
|
||||
team: tmb
|
||||
};
|
||||
}
|
||||
|
||||
export async function getUserAndAuthBalance({
|
||||
tmbId,
|
||||
minBalance
|
||||
}: {
|
||||
tmbId: string;
|
||||
minBalance?: number;
|
||||
}) {
|
||||
const user = await getUserDetail({ tmbId });
|
||||
|
||||
if (!user) {
|
||||
return Promise.reject(UserErrEnum.unAuthUser);
|
||||
}
|
||||
if (minBalance !== undefined && user.team.balance < minBalance) {
|
||||
return Promise.reject(UserErrEnum.balanceNotEnough);
|
||||
}
|
||||
|
||||
return user;
|
||||
}
|
||||
|
@@ -1,7 +1,7 @@
|
||||
import { connectionMongo, type Model } from '../../common/mongo';
|
||||
const { Schema, model, models } = connectionMongo;
|
||||
import { hashStr } from '@fastgpt/global/common/string/tools';
|
||||
import { PRICE_SCALE } from '@fastgpt/global/support/wallet/bill/constants';
|
||||
import { PRICE_SCALE } from '@fastgpt/global/support/wallet/constants';
|
||||
import type { UserModelSchema } from '@fastgpt/global/support/user/type';
|
||||
import { UserStatusEnum, userStatusMap } from '@fastgpt/global/support/user/constant';
|
||||
|
||||
@@ -63,6 +63,8 @@ const UserSchema = new Schema({
|
||||
});
|
||||
|
||||
try {
|
||||
// login
|
||||
UserSchema.index({ username: 1, password: 1 });
|
||||
UserSchema.index({ createTime: -1 });
|
||||
} catch (error) {
|
||||
console.log(error);
|
||||
|
@@ -36,7 +36,7 @@ export async function getTmbInfoByTmbId({ tmbId }: { tmbId: string }) {
|
||||
return Promise.reject('tmbId or userId is required');
|
||||
}
|
||||
return getTeamMember({
|
||||
_id: new Types.ObjectId(tmbId),
|
||||
_id: new Types.ObjectId(String(tmbId)),
|
||||
status: notLeaveStatus
|
||||
});
|
||||
}
|
||||
|
@@ -27,7 +27,10 @@ const TeamSchema = new Schema({
|
||||
},
|
||||
maxSize: {
|
||||
type: Number,
|
||||
default: 3
|
||||
default: 1
|
||||
},
|
||||
tagsUrl: {
|
||||
type: String
|
||||
},
|
||||
limit: {
|
||||
lastExportDatasetTime: {
|
||||
|
35
packages/service/support/user/team/teamTagsSchema.ts
Normal file
35
packages/service/support/user/team/teamTagsSchema.ts
Normal file
@@ -0,0 +1,35 @@
|
||||
import { connectionMongo, type Model } from '../../../common/mongo';
|
||||
const { Schema, model, models } = connectionMongo;
|
||||
import { TeamTagsSchema as TeamTagsSchemaType } from '@fastgpt/global/support/user/team/type.d';
|
||||
import {
|
||||
TeamCollectionName,
|
||||
TeamTagsCollectionName
|
||||
} from '@fastgpt/global/support/user/team/constant';
|
||||
|
||||
const TeamTagsSchema = new Schema({
|
||||
label: {
|
||||
type: String,
|
||||
required: true
|
||||
},
|
||||
teamId: {
|
||||
type: Schema.Types.ObjectId,
|
||||
ref: TeamCollectionName,
|
||||
required: true
|
||||
},
|
||||
key: {
|
||||
type: String
|
||||
},
|
||||
createTime: {
|
||||
type: Date,
|
||||
default: () => new Date()
|
||||
}
|
||||
});
|
||||
|
||||
try {
|
||||
TeamTagsSchema.index({ teamId: 1 });
|
||||
} catch (error) {
|
||||
console.log(error);
|
||||
}
|
||||
|
||||
export const MongoTeamTags: Model<TeamTagsSchemaType> =
|
||||
models[TeamTagsCollectionName] || model(TeamTagsCollectionName, TeamTagsSchema);
|
@@ -1,3 +1,8 @@
|
||||
/*
|
||||
user sub plan
|
||||
1. type=standard: There will only be 1, and each team will have one
|
||||
2. type=extraDatasetSize/extraPoints: Can buy multiple
|
||||
*/
|
||||
import { connectionMongo, type Model } from '../../../common/mongo';
|
||||
const { Schema, model, models } = connectionMongo;
|
||||
import { TeamCollectionName } from '@fastgpt/global/support/user/team/constant';
|
||||
@@ -23,25 +28,10 @@ const SubSchema = new Schema({
|
||||
required: true
|
||||
},
|
||||
status: {
|
||||
// active: continue sub; canceled: canceled sub;
|
||||
type: String,
|
||||
enum: Object.keys(subStatusMap),
|
||||
required: true
|
||||
},
|
||||
mode: {
|
||||
type: String,
|
||||
enum: Object.keys(subModeMap)
|
||||
},
|
||||
currentMode: {
|
||||
type: String,
|
||||
enum: Object.keys(subModeMap),
|
||||
required: true
|
||||
},
|
||||
nextMode: {
|
||||
type: String,
|
||||
enum: Object.keys(subModeMap),
|
||||
required: true
|
||||
},
|
||||
startTime: {
|
||||
type: Date,
|
||||
default: () => new Date()
|
||||
@@ -55,12 +45,16 @@ const SubSchema = new Schema({
|
||||
type: Number,
|
||||
required: true
|
||||
},
|
||||
pointPrice: {
|
||||
// stand level point total price
|
||||
type: Number
|
||||
},
|
||||
|
||||
// sub content
|
||||
// standard sub
|
||||
currentMode: {
|
||||
type: String,
|
||||
enum: Object.keys(subModeMap)
|
||||
},
|
||||
nextMode: {
|
||||
type: String,
|
||||
enum: Object.keys(subModeMap)
|
||||
},
|
||||
currentSubLevel: {
|
||||
type: String,
|
||||
enum: Object.keys(standardSubLevelMap)
|
||||
@@ -69,79 +63,32 @@ const SubSchema = new Schema({
|
||||
type: String,
|
||||
enum: Object.keys(standardSubLevelMap)
|
||||
},
|
||||
|
||||
// stand sub and extra points sub. Plan total points
|
||||
totalPoints: {
|
||||
type: Number
|
||||
},
|
||||
pointPrice: {
|
||||
// stand level point total price
|
||||
type: Number
|
||||
},
|
||||
surplusPoints: {
|
||||
// plan surplus points
|
||||
type: Number
|
||||
},
|
||||
|
||||
// extra dataset size
|
||||
currentExtraDatasetSize: {
|
||||
type: Number
|
||||
},
|
||||
nextExtraDatasetSize: {
|
||||
type: Number
|
||||
},
|
||||
|
||||
currentExtraPoints: {
|
||||
type: Number
|
||||
},
|
||||
nextExtraPoints: {
|
||||
type: Number
|
||||
},
|
||||
|
||||
// standard sub limit
|
||||
// maxTeamMember: {
|
||||
// type: Number
|
||||
// },
|
||||
// maxAppAmount: {
|
||||
// type: Number
|
||||
// },
|
||||
// maxDatasetAmount: {
|
||||
// type: Number
|
||||
// },
|
||||
// chatHistoryStoreDuration: {
|
||||
// // n day
|
||||
// type: Number
|
||||
// },
|
||||
// maxDatasetSize: {
|
||||
// type: Number
|
||||
// },
|
||||
// trainingWeight: {
|
||||
// // 0 1 2 3
|
||||
// type: Number
|
||||
// },
|
||||
// customApiKey: {
|
||||
// type: Boolean
|
||||
// },
|
||||
// customCopyright: {
|
||||
// type: Boolean
|
||||
// },
|
||||
// websiteSyncInterval: {
|
||||
// // hours
|
||||
// type: Number
|
||||
// },
|
||||
// reRankWeight: {
|
||||
// // 0 1 2 3
|
||||
// type: Number
|
||||
// },
|
||||
// totalPoints: {
|
||||
// // record standard sub points
|
||||
// type: Number
|
||||
// },
|
||||
|
||||
surplusPoints: {
|
||||
// standard sub / extra points sub
|
||||
type: Number
|
||||
},
|
||||
|
||||
// abandon
|
||||
renew: Boolean, //决定是否续费
|
||||
datasetStoreAmount: Number
|
||||
}
|
||||
});
|
||||
|
||||
try {
|
||||
SubSchema.index({ teamId: 1 });
|
||||
SubSchema.index({ status: 1 });
|
||||
SubSchema.index({ type: 1 });
|
||||
SubSchema.index({ expiredTime: -1 });
|
||||
// get team plan
|
||||
SubSchema.index({ teamId: 1, type: 1, expiredTime: -1 });
|
||||
|
||||
// timer task. check expired plan; update standard plan;
|
||||
SubSchema.index({ type: 1, currentSubLevel: 1, expiredTime: -1 });
|
||||
} catch (error) {
|
||||
console.log(error);
|
||||
}
|
||||
|
@@ -1,87 +1,147 @@
|
||||
import { SubTypeEnum } from '@fastgpt/global/support/wallet/sub/constants';
|
||||
import {
|
||||
StandardSubLevelEnum,
|
||||
SubModeEnum,
|
||||
SubStatusEnum,
|
||||
SubTypeEnum
|
||||
} from '@fastgpt/global/support/wallet/sub/constants';
|
||||
import { MongoTeamSub } from './schema';
|
||||
import { addHours } from 'date-fns';
|
||||
import { FeTeamSubType, StandSubPlanLevelMapType } from '@fastgpt/global/support/wallet/sub/type.d';
|
||||
import { FeTeamPlanStatusType } from '@fastgpt/global/support/wallet/sub/type.d';
|
||||
import { getVectorCountByTeamId } from '../../../common/vectorStore/controller';
|
||||
import dayjs from 'dayjs';
|
||||
import { ClientSession } from '../../../common/mongo';
|
||||
import { addMonths } from 'date-fns';
|
||||
|
||||
/* get team dataset max size */
|
||||
export const getTeamDatasetMaxSize = async ({
|
||||
teamId,
|
||||
standardPlans
|
||||
}: {
|
||||
teamId: string;
|
||||
standardPlans?: StandSubPlanLevelMapType;
|
||||
}) => {
|
||||
if (!standardPlans) {
|
||||
return {
|
||||
maxSize: Infinity,
|
||||
sub: null
|
||||
};
|
||||
}
|
||||
export const getStandardPlans = () => {
|
||||
return global?.subPlans?.standard;
|
||||
};
|
||||
export const getStandardPlan = (level: `${StandardSubLevelEnum}`) => {
|
||||
return global.subPlans?.standard?.[level];
|
||||
};
|
||||
|
||||
const plans = await MongoTeamSub.find({
|
||||
teamId,
|
||||
expiredTime: { $gte: addHours(new Date(), -3) }
|
||||
}).lean();
|
||||
|
||||
const standard = plans.find((plan) => plan.type === SubTypeEnum.standard);
|
||||
const extraDatasetSize = plans.find((plan) => plan.type === SubTypeEnum.extraDatasetSize);
|
||||
|
||||
const standardMaxDatasetSize =
|
||||
standard?.currentSubLevel && standardPlans
|
||||
? standardPlans[standard.currentSubLevel]?.maxDatasetSize || Infinity
|
||||
: Infinity;
|
||||
const totalDatasetSize =
|
||||
standardMaxDatasetSize + (extraDatasetSize?.currentExtraDatasetSize || 0);
|
||||
export const getTeamStandPlan = async ({ teamId }: { teamId: string }) => {
|
||||
const standardPlans = global.subPlans?.standard;
|
||||
const standard = await MongoTeamSub.findOne({ teamId, type: SubTypeEnum.standard }).lean();
|
||||
|
||||
return {
|
||||
maxSize: totalDatasetSize,
|
||||
sub: extraDatasetSize
|
||||
[SubTypeEnum.standard]: standard,
|
||||
standardConstants:
|
||||
standard?.currentSubLevel && standardPlans
|
||||
? standardPlans[standard.currentSubLevel]
|
||||
: undefined
|
||||
};
|
||||
};
|
||||
|
||||
export const getTeamSubPlanStatus = async ({
|
||||
export const initTeamStandardPlan2Free = async ({
|
||||
teamId,
|
||||
standardPlans
|
||||
session
|
||||
}: {
|
||||
teamId: string;
|
||||
standardPlans?: StandSubPlanLevelMapType;
|
||||
}): Promise<FeTeamSubType> => {
|
||||
session?: ClientSession;
|
||||
}) => {
|
||||
const freePoints = global?.subPlans?.standard?.free?.totalPoints || 100;
|
||||
|
||||
const teamStandardSub = await MongoTeamSub.findOne({ teamId, type: SubTypeEnum.standard });
|
||||
|
||||
if (teamStandardSub) {
|
||||
teamStandardSub.status = SubStatusEnum.active;
|
||||
teamStandardSub.currentMode = SubModeEnum.month;
|
||||
teamStandardSub.nextMode = SubModeEnum.month;
|
||||
teamStandardSub.startTime = new Date();
|
||||
teamStandardSub.expiredTime = addMonths(new Date(), 1);
|
||||
|
||||
teamStandardSub.currentSubLevel = StandardSubLevelEnum.free;
|
||||
teamStandardSub.nextSubLevel = StandardSubLevelEnum.free;
|
||||
|
||||
teamStandardSub.price = 0;
|
||||
teamStandardSub.pointPrice = 0;
|
||||
|
||||
teamStandardSub.totalPoints = freePoints;
|
||||
teamStandardSub.surplusPoints =
|
||||
teamStandardSub.surplusPoints && teamStandardSub.surplusPoints < 0
|
||||
? teamStandardSub.surplusPoints + freePoints
|
||||
: freePoints;
|
||||
return teamStandardSub.save({ session });
|
||||
}
|
||||
|
||||
return MongoTeamSub.create(
|
||||
[
|
||||
{
|
||||
teamId,
|
||||
type: SubTypeEnum.standard,
|
||||
status: SubStatusEnum.active,
|
||||
currentMode: SubModeEnum.month,
|
||||
nextMode: SubModeEnum.month,
|
||||
startTime: new Date(),
|
||||
expiredTime: addMonths(new Date(), 1),
|
||||
price: 0,
|
||||
pointPrice: 0,
|
||||
|
||||
currentSubLevel: StandardSubLevelEnum.free,
|
||||
nextSubLevel: StandardSubLevelEnum.free,
|
||||
|
||||
totalPoints: freePoints,
|
||||
surplusPoints: freePoints
|
||||
}
|
||||
],
|
||||
{ session }
|
||||
);
|
||||
};
|
||||
|
||||
export const getTeamPlanStatus = async ({
|
||||
teamId
|
||||
}: {
|
||||
teamId: string;
|
||||
}): Promise<FeTeamPlanStatusType> => {
|
||||
const standardPlans = global.subPlans?.standard;
|
||||
|
||||
const [plans, usedDatasetSize] = await Promise.all([
|
||||
MongoTeamSub.find({ teamId }).lean(),
|
||||
getVectorCountByTeamId(teamId)
|
||||
]);
|
||||
|
||||
const standard = plans.find((plan) => plan.type === SubTypeEnum.standard);
|
||||
const extraDatasetSize = plans.find((plan) => plan.type === SubTypeEnum.extraDatasetSize);
|
||||
const extraPoints = plans.find((plan) => plan.type === SubTypeEnum.extraPoints);
|
||||
const extraDatasetSize = plans.filter((plan) => plan.type === SubTypeEnum.extraDatasetSize);
|
||||
const extraPoints = plans.filter((plan) => plan.type === SubTypeEnum.extraPoints);
|
||||
|
||||
// Free user, first login after expiration. The free subscription plan will be reset
|
||||
if (
|
||||
standard &&
|
||||
standard.expiredTime &&
|
||||
standard.currentSubLevel === StandardSubLevelEnum.free &&
|
||||
dayjs(standard.expiredTime).isBefore(new Date())
|
||||
) {
|
||||
console.log('Init free stand plan', { teamId });
|
||||
await initTeamStandardPlan2Free({ teamId });
|
||||
return getTeamPlanStatus({ teamId });
|
||||
}
|
||||
|
||||
const totalPoints = standardPlans
|
||||
? (standard?.totalPoints || 0) +
|
||||
extraPoints.reduce((acc, cur) => acc + (cur.totalPoints || 0), 0)
|
||||
: Infinity;
|
||||
const surplusPoints =
|
||||
(standard?.surplusPoints || 0) +
|
||||
extraPoints.reduce((acc, cur) => acc + (cur.surplusPoints || 0), 0);
|
||||
|
||||
const standardMaxDatasetSize =
|
||||
standard?.currentSubLevel && standardPlans
|
||||
? standardPlans[standard.currentSubLevel]?.maxDatasetSize || Infinity
|
||||
: Infinity;
|
||||
const totalDatasetSize =
|
||||
standardMaxDatasetSize + (extraDatasetSize?.currentExtraDatasetSize || 0);
|
||||
|
||||
const standardMaxPoints =
|
||||
standard?.currentSubLevel && standardPlans
|
||||
? standardPlans[standard.currentSubLevel]?.totalPoints || Infinity
|
||||
: Infinity;
|
||||
const totalPoints = standardMaxPoints + (extraPoints?.currentExtraPoints || 0);
|
||||
|
||||
const surplusPoints = (standard?.surplusPoints || 0) + (extraPoints?.surplusPoints || 0);
|
||||
standardMaxDatasetSize +
|
||||
extraDatasetSize.reduce((acc, cur) => acc + (cur.currentExtraDatasetSize || 0), 0);
|
||||
|
||||
return {
|
||||
[SubTypeEnum.standard]: standard,
|
||||
[SubTypeEnum.extraDatasetSize]: extraDatasetSize,
|
||||
[SubTypeEnum.extraPoints]: extraPoints,
|
||||
standardConstants:
|
||||
standard?.currentSubLevel && standardPlans
|
||||
? standardPlans[standard.currentSubLevel]
|
||||
: undefined,
|
||||
|
||||
standardMaxDatasetSize,
|
||||
datasetMaxSize: totalDatasetSize,
|
||||
usedDatasetSize,
|
||||
|
||||
standardMaxPoints,
|
||||
totalPoints,
|
||||
usedPoints: totalPoints - surplusPoints
|
||||
usedPoints: totalPoints - surplusPoints,
|
||||
|
||||
datasetMaxSize: totalDatasetSize,
|
||||
usedDatasetSize
|
||||
};
|
||||
};
|
||||
|
@@ -1,8 +1,8 @@
|
||||
import { BillSourceEnum } from '@fastgpt/global/support/wallet/bill/constants';
|
||||
import { MongoBill } from './schema';
|
||||
import { UsageSourceEnum } from '@fastgpt/global/support/wallet/usage/constants';
|
||||
import { MongoUsage } from './schema';
|
||||
import { ClientSession } from '../../../common/mongo';
|
||||
|
||||
export const createTrainingBill = async ({
|
||||
export const createTrainingUsage = async ({
|
||||
teamId,
|
||||
tmbId,
|
||||
appName,
|
||||
@@ -14,33 +14,33 @@ export const createTrainingBill = async ({
|
||||
teamId: string;
|
||||
tmbId: string;
|
||||
appName: string;
|
||||
billSource: `${BillSourceEnum}`;
|
||||
billSource: `${UsageSourceEnum}`;
|
||||
vectorModel: string;
|
||||
agentModel: string;
|
||||
session?: ClientSession;
|
||||
}) => {
|
||||
const [{ _id }] = await MongoBill.create(
|
||||
const [{ _id }] = await MongoUsage.create(
|
||||
[
|
||||
{
|
||||
teamId,
|
||||
tmbId,
|
||||
appName,
|
||||
source: billSource,
|
||||
totalPoints: 0,
|
||||
list: [
|
||||
{
|
||||
moduleName: 'wallet.moduleName.index',
|
||||
moduleName: 'support.wallet.moduleName.index',
|
||||
model: vectorModel,
|
||||
charsLength: 0,
|
||||
amount: 0
|
||||
},
|
||||
{
|
||||
moduleName: 'wallet.moduleName.qa',
|
||||
moduleName: 'support.wallet.moduleName.qa',
|
||||
model: agentModel,
|
||||
charsLength: 0,
|
||||
amount: 0
|
||||
}
|
||||
],
|
||||
total: 0
|
||||
]
|
||||
}
|
||||
],
|
||||
{ session }
|
Some files were not shown because too many files have changed in this diff Show More
Reference in New Issue
Block a user