bs1.json 115 KB

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  1. {
  2. "title": "NPCs",
  3. "prompt": "提示",
  4. "login": {
  5. "slogen": "便捷、灵活、可靠的企业级大模型应用开发平台",
  6. "account": "账号",
  7. "password": "密码",
  8. "confirmPassword": "确认密码",
  9. "noAccountRegister": "没有账号,注册",
  10. "haveAccountLogin": "已有账号,登录",
  11. "loginButton": "登 录",
  12. "registerButton": "注 册",
  13. "document": "文档",
  14. "pleaseEnterAccount": "请填写账号",
  15. "pleaseEnterPassword": "请填写密码",
  16. "accountTooShort": "账号过短",
  17. "passwordTooShort": "请填写密码,至少8位",
  18. "passwordError": "密码必须包含大小写字母、数字和特殊字符!",
  19. "passwordMismatch": "两次密码不一致",
  20. "registrationSuccess": "注册成功,请输入密码进行登录",
  21. "pleaseEnterCaptcha": "请输入验证码"
  22. },
  23. "menu": {
  24. "app": "应 用",
  25. "skills": "技 能",
  26. "knowledge": "知 识",
  27. "models": "模 型",
  28. "system": "系 统",
  29. "themeSwitch": "主题切换",
  30. "document": "文档",
  31. "logout": "退出",
  32. "logoutDescription": "退出登录",
  33. "forBestExperience": "为了您的良好体验,请在 PC 端访问该网站",
  34. "onlineDocumentation": "在线文档"
  35. },
  36. "system": {
  37. "userManagement": "用户管理",
  38. "roleManagement": "角色管理",
  39. "systemConfiguration": "系统配置",
  40. "username": "用户名",
  41. "confirmDisable": "确认禁用该用户?",
  42. "roleSelect": "角色选择",
  43. "roleList": "角色列表",
  44. "confirmText": "是否删除",
  45. "roleName": "角色名称",
  46. "skillAuthorization": "技能授权",
  47. "knowledgeAuthorization": "知识库授权",
  48. "skillName": "技能名称",
  49. "creator": "创建人",
  50. "usePermission": "使用权限",
  51. "managePermission": "管理权限",
  52. "roleNamePrompt": "角色名称不能超过50字符",
  53. "roleNameRequired": "角色名称不能为空",
  54. "roleNameExists": "角色名称已存在",
  55. "parameterConfig": "参数配置",
  56. "language": "语言"
  57. },
  58. "skills": {
  59. "manageTemplate": "管理技能模板",
  60. "createNew": "新建",
  61. "manageProjects": "这里管理您的个人项目,对技能上下线、编辑等等",
  62. "skillSearch": "技能搜索",
  63. "confirmDeleteSkill": "确认删除该技能?",
  64. "backToSkillList": "返回技能列表",
  65. "skillTemplateManagement": "技能模板管理,模板对所有用户可见,支持拖拽排序、删除操作",
  66. "templateName": "模板名称",
  67. "templateDescription": "模板描述",
  68. "confirmText": "是否确认删除该技能模板?",
  69. "skillSettings": "技能设置",
  70. "basicInfo": "基础信息",
  71. "skillName": "技能名称",
  72. "description": "描述",
  73. "parameterInfo": "参数信息",
  74. "advancedConfiguration": "高级配置",
  75. "nextStep": "下一步,高级配置",
  76. "skillNameRequired": "请填写技能名称",
  77. "skillNameTooLong": "技能名称过长,不要超过30字",
  78. "skillNameExists": "该名称已存在",
  79. "skillDescRequired": "请填写技能描述",
  80. "skillDescTooLong": "技能描述过长,不要超过200字",
  81. "errorTitle": "关键信息有误",
  82. "onlineFailure": "上线失败",
  83. "custom": "自定义",
  84. "skillTemplate": "技能模板",
  85. "skillTemplateChoose": "您可以从这里挑选一个模板开始,或者自定义高级模板",
  86. "createTemplate": "创建模板",
  87. "createSuccessTitle": "技能创建成功",
  88. "createFailureTitle": "创建失败",
  89. "createdBy": "创建用户",
  90. "offline": "下线",
  91. "online": "上线"
  92. },
  93. "chat": {
  94. "newChat": "新建会话",
  95. "selectChat": "选择一个对话开始文擎睿见",
  96. "inputPlaceholder": "请输入问题",
  97. "uploadFileTooltip": "上传文件",
  98. "sendTooltip": "发送",
  99. "skillTempsTitle": "技能选择",
  100. "skillTempsDesc": "选择一个您想使用的线上技能",
  101. "networkError": "网络连接出现错误,请尝试以下方法",
  102. "networkErrorList1": "操作不要过快",
  103. "networkErrorList2": "刷新页面",
  104. "networkErrorList3": "检查后台是否启动",
  105. "buildError": "您好像缺少了某些配置",
  106. "connectionbreakTip": "链接异常断开:",
  107. "connectionbreak": "网络断开!",
  108. "copyTip": "内容已复制",
  109. "noAccess": "因权限不足,该答案剔除了无权查看的内容",
  110. "source": "参考来源",
  111. "file": "文件",
  112. "filePrsing": "文件正在解析中",
  113. "sourceTooltip": "来源段落",
  114. "filterLabel": "筛选标签",
  115. "tooltipText": "系统自动根据答案生成关键信息标签,也可手动增删标签,系统根据标签计算各个文件及段落相关性。",
  116. "customLabel": "自定义",
  117. "addCustomLabel": "+自定义",
  118. "sourceDocumentsLabel": "来源文档",
  119. "downloadPDFTooltip": "下载双层PDF",
  120. "downloadOriginalTooltip": "下载原文件",
  121. "noMatchedFilesMessage": "无匹配的源文件",
  122. "fileStorageFailure": " 文件地址失效!",
  123. "confirmDeleteChat": "确认删除该会话?",
  124. "roundOver": "本轮结束",
  125. "chatDialogTip": "设置提示模板中定义的输入变量。与代理和链互动",
  126. "feedback": "反馈",
  127. "feedbackRequired": "反馈信息不能为空"
  128. },
  129. "model": {
  130. "modelConfiguration": "模型配置",
  131. "modelName": "模型名称",
  132. "modelConfigLabel": "模型配置",
  133. "modelConfigExplanationLink": "模型配置参数说明",
  134. "jsonFormatError": "JSON格式有误",
  135. "onlineStatus": "已上线",
  136. "offlineStatus": "未上线",
  137. "exceptionStatus": "异常",
  138. "warningTooltip": "处理异常",
  139. "inProgressOnlineStatus": "上线中",
  140. "inProgressOfflineStatus": "下线中",
  141. "confirmModelOffline": "是否确认下线该模型,下线后使用该模型服务的技能将无法正常工作",
  142. "confirmOfflineButtonText": "下线",
  143. "modelManagement": "模型管理",
  144. "modelFineTune": "模型Finetune",
  145. "refreshButton": "刷新",
  146. "gpuResourceUsage": "GPU资源使用情况",
  147. "rtServiceManagement": "RT服务管理",
  148. "modelCollectionCaption": "模型集合",
  149. "machine": "机器",
  150. "serviceAddress": "服务地址",
  151. "status": "状态",
  152. "online": "上线",
  153. "offline": "下线",
  154. "gpuResourceUsageTitle": "GPU资源使用情况",
  155. "gpuNumber": "GPU序号",
  156. "gpuID": "GPU-ID",
  157. "totalMemory": "总显存",
  158. "freeMemory": "空余显存",
  159. "gpuUtilization": "GPU利用率",
  160. "machineName": "机器名",
  161. "addOne": "加一条"
  162. },
  163. "flow": {
  164. "unsavedChangesConfirmation": "您有未保存的更改,确定要离开吗?",
  165. "leave": "离开",
  166. "leaveAndSave": "离开并保存",
  167. "simplifyConfig": "简化配置",
  168. "simplify": "简化",
  169. "notifications": "通知",
  170. "exit": "退出",
  171. "import": "导入",
  172. "export": "导出",
  173. "code": "代码",
  174. "searchComponent": "查找组件",
  175. "knowledgeBaseSelection": "知识库选择",
  176. "searchKnowledgeBase": "搜索知识库",
  177. "minimumParamSetDescription": "您可以在此设置技能所需的最小参数集",
  178. "paramList": "参数列表",
  179. "saveConfig": "保存配置",
  180. "componentLabel": "组件",
  181. "aliasLabel": "别名",
  182. "editAlias": "修改别名",
  183. "parameterLabel": "参数",
  184. "notification": "消息",
  185. "noNewNotifications": "没有新的通知",
  186. "skillName": "技能名",
  187. "nameTooLong": "名称过长",
  188. "skillDescription": "技能描述",
  189. "enterVarName": "请输入变量名",
  190. "varNameExists": "变量名重复",
  191. "text": "文本",
  192. "dropdown": "下拉框",
  193. "maxLength": "最大长度",
  194. "options": "选项",
  195. "variableName": "变量名",
  196. "varOptionRequired": "请输入选项内容",
  197. "optionRepeated": "选项重复"
  198. },
  199. "lib": {
  200. "enterLibraryName": "请输入知识库名称",
  201. "libraryNameLimit": "知识库名称字数不得超过30字",
  202. "selectModel": "请选择一个模型",
  203. "nameExists": "该名称已存在",
  204. "descriptionLimit": "知识库描述字数不得超过200字",
  205. "createLibrary": "创建知识库",
  206. "libraryName": "知识库名称",
  207. "description": "描述",
  208. "model": "模型",
  209. "fileData": "文件数据",
  210. "structuredData": "结构化数据",
  211. "libraryCollection": "知识库集合",
  212. "createUser": "创建用户",
  213. "details": "详情",
  214. "confirmDeleteLibrary": "确认删除该知识库?",
  215. "fileList": "文件列表",
  216. "systemIntegration": "系统对接",
  217. "upload": "上传",
  218. "fileName": "文件名称",
  219. "status": "状态",
  220. "uploadTime": "上传时间",
  221. "parseFailed": "解析失败",
  222. "parsing": "解析中",
  223. "completed": "完成",
  224. "confirmDeleteFile": "确认删除该文件?",
  225. "fileUploadResult": "共上传 {{total}} 份文件,有 {{failed}} 份文件上传失败"
  226. },
  227. "code": {
  228. "editPythonCodeDescription": "编辑你的 Python 代码此代码片段接受模块导入和一个函数定义。确保您的函数返回一个字符串。",
  229. "editCode": "编辑代码",
  230. "codeReadyToRun": "代码准备运行",
  231. "functionError": "您的函数中存在一个错误",
  232. "importsError": "您的导入有误",
  233. "errorOccurred": "出错了,请重试",
  234. "codeError": "这段代码有问题,请检查以下",
  235. "checkAndSave": "检查 & 保存",
  236. "export": "导出",
  237. "exportToJSON": "导出技能到json文件中",
  238. "keyInformationMissing": "您有一些关键信息没有填: ",
  239. "skillNameMissing": "请填写技能名称",
  240. "useOwnAPIKeys": "使用自己的API keys",
  241. "exportSkill": "导出技能",
  242. "uploadFile": "上传文件",
  243. "clickOrDragHere": "点击或将文件拖拽到这里上传",
  244. "dropFileHere": "将文件拖拽到这里上传",
  245. "delimiter": "切分符(多个以;分隔)",
  246. "splitLength": "切分文本长度",
  247. "smartSplit": "智能语义切分",
  248. "manualSplit": "手动设置切分",
  249. "delimiterPlaceholder": "切分符号",
  250. "splitSizePlaceholder": "切分大小",
  251. "complete": "完成",
  252. "setSplitSize": "请设置文件切分大小",
  253. "selectFileToUpload": "请先选择文件上传",
  254. "fileSizeExceedsLimit": "文件不能超50M",
  255. "file": "文件",
  256. "sizeExceedsLimit": "超过50M,已移除",
  257. "editDictionary": "编辑词典",
  258. "exportCodeDialogTip": "生成代码,将流程集成到外部应用程序中 (打开此页面前请先build技能)。",
  259. "chunkOverlap": "切分文本重叠长度"
  260. },
  261. "report": {
  262. "reportTemplate": "报告模板",
  263. "reportDescription": "报告生成描述...",
  264. "newButton": "新建",
  265. "importButton": "导入",
  266. "start": "开始",
  267. "formSettings": "表单设置",
  268. "requiredLabel": "必填",
  269. "isRequired": "是必填项",
  270. "fileRequired": "当前文件为空",
  271. "selectComponent": "选择一个组件",
  272. "varLength": "长度不能超过"
  273. },
  274. "status": {
  275. "1004": "该技能已被删除",
  276. "1008": "当前技能未上线,无法直接对话",
  277. "1005": ""
  278. },
  279. "confirmButton": "确定",
  280. "add": "添加",
  281. "back": "返回",
  282. "create": "创建",
  283. "delete": "删除",
  284. "createTime": "创建时间",
  285. "updateTime": "更新时间",
  286. "success": "保存成功",
  287. "edit": "编辑",
  288. "enable": "启用",
  289. "disable": "禁用",
  290. "close": "关闭",
  291. "cancel": "取消",
  292. "save": "保存",
  293. "submit": "提交",
  294. "operations": "操作",
  295. "previousPage": "上一页",
  296. "nextPage": "下一页",
  297. "formatError": "格式错误",
  298. "agents": {
  299. "AgentInitializer": {
  300. "display_name": "AgentInitializer",
  301. "description": "从LLM和工具构建零射击代理。",
  302. "template": {
  303. "input_node": {
  304. "display_name": "预设问题"
  305. },
  306. "llm": {
  307. "display_name": "LLM"
  308. },
  309. "memory": {
  310. "display_name": "内存"
  311. },
  312. "tools": {
  313. "display_name": "工具"
  314. },
  315. "agent": {
  316. "display_name": "代理",
  317. "options": [
  318. "零射击-反应描述",
  319. "反应-文档存储",
  320. "自问自答-带搜索",
  321. "对话-反应描述",
  322. "openai-功能",
  323. "openai-多功能"
  324. ]
  325. }
  326. }
  327. },
  328. "CSVAgent": {
  329. "display_name": "CSV代理",
  330. "template": {
  331. "input_node": {
  332. "display_name": "预设问题"
  333. },
  334. "llm": {
  335. "display_name": "LLM"
  336. },
  337. "path": {
  338. "display_name": "路径"
  339. },
  340. "format_instructions": {
  341. "display_name": "格式说明",
  342. "value": "使用以下格式:\n\n问题:您必须回答的输入问题\n思考:您应该始终考虑要做什么\n操作:要执行的操作,应该是[{tool_names}]之一\n操作输入:操作的输入\n观察:操作的结果\n...(这个思考/操作/操作输入/观察可以重复N次)\n思考:我现在知道最终答案\n最终答案:原始输入问题的最终答案"
  343. },
  344. "input_variables": {
  345. "display_name": "输入变量",
  346. "value": [
  347. "df_head",
  348. "输入",
  349. "代理备忘录"
  350. ]
  351. },
  352. "prefix": {
  353. "display_name": "前缀",
  354. "value": "\n您正在使用Python中的pandas数据框。数据框的名称是 `df`。\n您应该使用下面的工具来回答您提出的问题:"
  355. },
  356. "suffix": {
  357. "display_name": "后缀",
  358. "value": "\n这是 `print(df.head())` 的结果:\n{df_head}\n\n开始吧!\n问题:{input}\n{agent_scratchpad}"
  359. }
  360. }
  361. },
  362. "ChatglmFunctionsAgent": {
  363. "display_name": "ChatglmFunctionsAgent",
  364. "description": "从LLM和工具构建代理。",
  365. "template": {
  366. "input_node": {
  367. "display_name": "预设问题"
  368. },
  369. "llm": {
  370. "display_name": "LLM"
  371. },
  372. "tools": {
  373. "display_name": "工具"
  374. }
  375. }
  376. },
  377. "JsonAgent": {
  378. "display_name": "JsonAgent",
  379. "description": "从LLM和工具构建JSON代理。",
  380. "template": {
  381. "input_node": {
  382. "display_name": "预设问题"
  383. },
  384. "llm": {
  385. "display_name": "LLM"
  386. },
  387. "toolkit": {
  388. "display_name": "工具包"
  389. }
  390. }
  391. },
  392. "LLMFunctionsAgent": {
  393. "display_name": "LLMFunctionsAgent",
  394. "description": "从LLM和工具构建代理。",
  395. "template": {
  396. "input_node": {
  397. "display_name": "预设问题"
  398. },
  399. "llm": {
  400. "display_name": "LLM"
  401. },
  402. "tools": {
  403. "display_name": "工具"
  404. }
  405. }
  406. },
  407. "SQLAgent": {
  408. "display_name": "SQL代理",
  409. "description": "从LLM和工具构建SQL代理。",
  410. "template": {
  411. "input_node": {
  412. "display_name": "预设问题"
  413. },
  414. "llm": {
  415. "display_name": "LLM"
  416. },
  417. "database_uri": {
  418. "display_name": "数据库URI"
  419. },
  420. "format_instructions": {
  421. "display_name": "格式说明",
  422. "value": "使用以下格式:\n\n问题:您必须回答的输入问题\n思考:您应该始终考虑要做什么\n操作:要执行的操作,应该是[{tool_names}]之一\n操作输入:操作的输入\n观察:操作的结果\n...(这个思考/操作/操作输入/观察可以重复N次)\n思考:我现在知道最终答案\n最终答案:原始输入问题的最终答案"
  423. },
  424. "input_variables": {
  425. "display_name": "输入变量",
  426. "value": [
  427. "输入",
  428. "代理备忘录"
  429. ]
  430. },
  431. "prefix": {
  432. "display_name": "前缀",
  433. "value": "您是一个与SQL数据库交互的代理。\n给定一个输入问题,请创建一个语法正确的{dialect}查询,然后查看查询的结果并返回答案。\n除非用户指定要获取的特定示例数,否则始终限制查询至多返回{top_k}个结果。\n您可以按相关列对结果进行排序,以返回数据库中最有趣的示例。\n永远不要查询特定表的所有列,只有在给定问题的情况下才请求相关列。\n您可以使用与数据库交互的工具。\n只使用下面的工具。只使用下面工具返回的信息构建最终答案。\n在执行查询之前,务必仔细检查您的查询。如果在执行查询时出错,请重新编写查询并重试。\n\n不要对数据库进行任何DML语句(INSERT,UPDATE,DELETE,DROP等)。\n\n如果问题似乎与数据库无关,只需返回 '我不知道' 作为答案。"
  434. },
  435. "suffix": {
  436. "display_name": "后缀",
  437. "value": "开始吧!\n\n问题:{input}\n思考:我应该查看数据库中的表,看看我可以查询什么。然后,我应该查询最相关表的模式。\n{agent_scratchpad}"
  438. }
  439. }
  440. },
  441. "VectorStoreAgent": {
  442. "display_name": "VectorStoreAgent",
  443. "description": "从矢量存储构建代理。",
  444. "template": {
  445. "input_node": {
  446. "display_name": "预设问题"
  447. },
  448. "llm": {
  449. "display_name": "LLM"
  450. },
  451. "vectorstoreinfo": {
  452. "display_name": "矢量存储信息"
  453. }
  454. }
  455. },
  456. "VectorStoreRouterAgent": {
  457. "display_name": "VectorStoreRouterAgent",
  458. "description": "从矢量存储路由器构建代理。",
  459. "template": {
  460. "input_node": {
  461. "display_name": "预设问题"
  462. },
  463. "llm": {
  464. "display_name": "LLM"
  465. },
  466. "vectorstoreroutertoolkit": {
  467. "display_name": "矢量存储路由器工具包"
  468. }
  469. }
  470. },
  471. "ZeroShotAgent": {
  472. "display_name": "零射击代理",
  473. "description": "从LLM和工具构建代理。",
  474. "template": {
  475. "input_node": {
  476. "display_name": "预设问题"
  477. },
  478. "llm": {
  479. "display_name": "LLM"
  480. },
  481. "tools": {
  482. "display_name": "工具"
  483. },
  484. "format_instructions": {
  485. "display_name": "格式说明",
  486. "value": "使用以下格式:\n\n问题:您必须回答的输入问题\n思考:您应该始终考虑要做什么\n操作:要执行的操作,应该是一种[{tool_names}]之一\n操作输入:操作的输入\n观察:操作的结果\n...(这个思考/操作/操作输入/观察可以重复N次)\n思考:我现在知道最终答案\n最终答案:原始输入问题的最终答案"
  487. },
  488. "input_variables": {
  489. "display_name": "输入变量"
  490. },
  491. "prefix": {
  492. "display_name": "前缀",
  493. "value": "尽力回答以下问题。您可以使用以下工具:"
  494. },
  495. "suffix": {
  496. "display_name": "后缀",
  497. "value": "开始吧!\n\n问题:{input}\n思考:{agent_scratchpad}"
  498. }
  499. }
  500. }
  501. },
  502. "autogen_roles": {
  503. "AutoGenAssistant": {
  504. "display_name": "自动生成助手",
  505. "description": "助手代理,设计用于使用LLM解决任务。",
  506. "template": {
  507. "model_name": {
  508. "display_name": "模型名称"
  509. },
  510. "name": {
  511. "display_name": "名称"
  512. },
  513. "openai_api_base": {
  514. "display_name": "openai_api_base"
  515. },
  516. "openai_api_key": {
  517. "display_name": "openai_api_key"
  518. },
  519. "openai_proxy": {
  520. "display_name": "openai_proxy"
  521. },
  522. "system_message": {
  523. "display_name": "系统消息"
  524. },
  525. "temperature": {
  526. "display_name": "温度"
  527. }
  528. }
  529. },
  530. "AutoGenCoder": {
  531. "display_name": "自动生成编码器",
  532. "description": "Coder的代理,可以执行代码到其他代理。",
  533. "template": {
  534. "name": {
  535. "display_name": "名称"
  536. },
  537. "system_message": {
  538. "display_name": "系统消息"
  539. }
  540. }
  541. },
  542. "AutoGenCustomRole": {
  543. "display_name": "自动生成自定义角色",
  544. "description": "可以使用langchain代理和链的自定义代理。",
  545. "template": {
  546. "func": {
  547. "display_name": "函数"
  548. },
  549. "name": {
  550. "display_name": "名称"
  551. },
  552. "system_message": {
  553. "display_name": "系统消息"
  554. }
  555. }
  556. },
  557. "AutoGenGroupChatManager": {
  558. "display_name": "自动生成群聊管理器",
  559. "description": "一个可以管理多个代理的群聊管理器代理。",
  560. "template": {
  561. "agents": {
  562. "display_name": "代理"
  563. },
  564. "max_round": {
  565. "display_name": "最大轮次"
  566. },
  567. "model_name": {
  568. "display_name": "模型名称"
  569. },
  570. "name": {
  571. "display_name": "名称",
  572. "value": "chat_manage"
  573. },
  574. "openai_api_base": {
  575. "display_name": "openai_api_base"
  576. },
  577. "openai_api_key": {
  578. "display_name": "openai_api_key"
  579. },
  580. "openai_proxy": {
  581. "display_name": "openai_proxy"
  582. },
  583. "system_message": {
  584. "display_name": "系统消息"
  585. },
  586. "temperature": {
  587. "display_name": "温度"
  588. }
  589. }
  590. },
  591. "AutoGenUser": {
  592. "display_name": "自动生成用户",
  593. "description": "用户的代理,可以向其他代理提供反馈。",
  594. "template": {
  595. "human_input_mode": {
  596. "display_name": "人类输入模式"
  597. },
  598. "max_consecutive_auto_reply": {
  599. "display_name": "最大连续自动回复"
  600. },
  601. "name": {
  602. "display_name": "名称",
  603. "value": "chat_manage"
  604. },
  605. "system_message": {
  606. "display_name": "系统消息"
  607. }
  608. }
  609. }
  610. },
  611. "chains": {
  612. "APIChain": {
  613. "display_name": "API链",
  614. "description": "从仅LLM和api文档加载链。",
  615. "template": {
  616. "api_response_prompt": {
  617. "display_name": "api响应提示"
  618. },
  619. "api_url_prompt": {
  620. "display_name": "api URL提示"
  621. },
  622. "input_node": {
  623. "display_name": "预设问题"
  624. },
  625. "llm": {
  626. "display_name": "LLM"
  627. },
  628. "api_docs": {
  629. "display_name": "api文档"
  630. },
  631. "headers": {
  632. "display_name": "头部"
  633. }
  634. }
  635. },
  636. "AutoGenChain": {
  637. "display_name": "自动生成链",
  638. "description": "打印加载器输出的链。",
  639. "template": {
  640. "input_node": {
  641. "display_name": "预设问题"
  642. },
  643. "memory": {
  644. "display_name": "内存"
  645. },
  646. "recipient": {
  647. "display_name": "AutogenRole"
  648. },
  649. "user_proxy_agent": {
  650. "display_name": "用户代理"
  651. }
  652. }
  653. },
  654. "CombineDocsChain": {
  655. "display_name": "合并文档链",
  656. "description": "加载问答链。",
  657. "template": {
  658. "document_prompt": {
  659. "display_name": "文档提示"
  660. },
  661. "llm": {
  662. "display_name": "LLM"
  663. },
  664. "prompt": {
  665. "display_name": "提示"
  666. },
  667. "chain_type": {
  668. "display_name": "链类型",
  669. "options": [
  670. "stuff",
  671. "map_reduce",
  672. "map_rerank",
  673. "refine"
  674. ]
  675. },
  676. "token_max": {
  677. "display_name": "最大令牌"
  678. }
  679. }
  680. },
  681. "ConversationChain": {
  682. "display_name": "对话链",
  683. "description": "进行对话并从内存中加载上下文的链。",
  684. "template": {
  685. "input_node": {
  686. "display_name": "预设问题"
  687. },
  688. "llm": {
  689. "display_name": "LLM"
  690. },
  691. "memory": {
  692. "display_name": "内存"
  693. }
  694. }
  695. },
  696. "ConversationalRetrievalChain": {
  697. "display_name": "对话检索链",
  698. "description": "从LLM和检索器中方便地加载链的方法。",
  699. "template": {
  700. "combine_docs_chain_kwargs": {
  701. "display_name": "提示"
  702. },
  703. "condense_question_prompt": {
  704. "display_name": "压缩问题提示"
  705. },
  706. "document_prompt": {
  707. "display_name": "文档提示"
  708. },
  709. "input_node": {
  710. "display_name": "预设问题"
  711. },
  712. "llm": {
  713. "display_name": "LLM"
  714. },
  715. "memory": {
  716. "display_name": "内存"
  717. },
  718. "retriever": {
  719. "display_name": "检索器"
  720. },
  721. "chain_type": {
  722. "display_name": "链类型",
  723. "options": [
  724. "stuff",
  725. "map_reduce",
  726. "map_rerank",
  727. "refine"
  728. ]
  729. }
  730. }
  731. },
  732. "LLMChain": {
  733. "display_name": "LLM链",
  734. "description": "对LLM运行查询的链。",
  735. "template": {
  736. "input_node": {
  737. "display_name": "预设问题"
  738. },
  739. "llm": {
  740. "display_name": "LLM"
  741. },
  742. "memory": {
  743. "display_name": "内存"
  744. },
  745. "prompt": {
  746. "display_name": "提示"
  747. }
  748. }
  749. },
  750. "LLMMathChain": {
  751. "display_name": "LLM数学链",
  752. "description": "解释提示并执行Python代码进行数学运算的链。",
  753. "template": {
  754. "input_node": {
  755. "display_name": "预设问题"
  756. },
  757. "llm": {
  758. "display_name": "LLM"
  759. },
  760. "llm_chain": {
  761. "display_name": "LLM链"
  762. },
  763. "memory": {
  764. "display_name": "内存"
  765. }
  766. }
  767. },
  768. "LoaderOutputChain": {
  769. "display_name": "加载器输出链",
  770. "description": "打印加载器输出的链。",
  771. "template": {
  772. "documents": {
  773. "display_name": "文档"
  774. },
  775. "input_node": {
  776. "display_name": "预设问题"
  777. },
  778. "memory": {
  779. "display_name": "内存"
  780. }
  781. }
  782. },
  783. "MidJourneyPromptChain": {
  784. "display_name": "中程提示链",
  785. "description": "MidJourneyPromptChain是您可以使用的链,用于生成新的MidJourney提示。",
  786. "template": {
  787. "input_node": {
  788. "display_name": "预设问题"
  789. },
  790. "llm": {
  791. "display_name": "LLM"
  792. },
  793. "memory": {
  794. "display_name": "内存"
  795. }
  796. }
  797. },
  798. "MultiPromptChain": {
  799. "display_name": "多提示链",
  800. "description": "使用LLM路由链选择提示的多路链。",
  801. "template": {
  802. "LLMChains": {
  803. "display_name": "LLM链"
  804. },
  805. "default_chain": {
  806. "display_name": "默认链"
  807. },
  808. "input_node": {
  809. "display_name": "预设问题"
  810. },
  811. "memory": {
  812. "display_name": "内存"
  813. },
  814. "router_chain": {
  815. "display_name": "路由链"
  816. },
  817. "destination_chain_name": {
  818. "display_name": "目标链名称"
  819. }
  820. }
  821. },
  822. "MultiRuleChain": {
  823. "display_name": "多规则链",
  824. "template": {
  825. "LLMChains": {
  826. "display_name": "LLM链"
  827. },
  828. "default_chain": {
  829. "display_name": "默认链"
  830. },
  831. "input_node": {
  832. "display_name": "预设问题"
  833. },
  834. "memory": {
  835. "display_name": "内存"
  836. },
  837. "router_chain": {
  838. "display_name": "路由链"
  839. },
  840. "destination_chain_name": {
  841. "display_name": "目标链名称"
  842. },
  843. "output_variables": {
  844. "display_name": "输出变量"
  845. }
  846. }
  847. },
  848. "RetrievalChain": {
  849. "display_name": "检索链",
  850. "description": "用于合并文档的链。",
  851. "template": {
  852. "input_node": {
  853. "display_name": "预设问题"
  854. },
  855. "memory": {
  856. "display_name": "内存"
  857. },
  858. "retriever": {
  859. "display_name": "检索器"
  860. }
  861. }
  862. },
  863. "RuleBasedRouter": {
  864. "display_name": "基于规则的路由器",
  865. "template": {
  866. "input_node": {
  867. "display_name": "预设问题"
  868. },
  869. "memory": {
  870. "display_name": "内存"
  871. },
  872. "rule_function": {
  873. "display_name": "规则函数"
  874. },
  875. "input_variables": {
  876. "display_name": "输入变量"
  877. }
  878. }
  879. },
  880. "SQLDatabaseChain": {
  881. "display_name": "SQL数据库链",
  882. "template": {
  883. "db": {
  884. "display_name": "数据库"
  885. },
  886. "input_node": {
  887. "display_name": "预设问题"
  888. },
  889. "llm": {
  890. "display_name": "LLM"
  891. },
  892. "prompt": {
  893. "display_name": "提示"
  894. }
  895. }
  896. },
  897. "SequentialChain": {
  898. "display_name": "顺序链",
  899. "description": "一个链的输出直接进入下一个链的链。",
  900. "template": {
  901. "chains": {
  902. "display_name": "链"
  903. },
  904. "input_node": {
  905. "display_name": "预设问题"
  906. },
  907. "memory": {
  908. "display_name": "内存"
  909. },
  910. "chain_order": {
  911. "display_name": "链顺序"
  912. },
  913. "input_variables": {
  914. "display_name": "输入变量"
  915. },
  916. "output_variables": {
  917. "display_name": "输出变量"
  918. }
  919. }
  920. },
  921. "SeriesCharacterChain": {
  922. "display_name": "系列角色链",
  923. "description": "SeriesCharacterChain是您可以使用的链,用于与系列中的角色进行对话。",
  924. "template": {
  925. "input_node": {
  926. "display_name": "预设问题"
  927. },
  928. "llm": {
  929. "display_name": "LLM"
  930. },
  931. "character": {
  932. "display_name": "角色"
  933. },
  934. "series": {
  935. "display_name": "系列"
  936. }
  937. }
  938. },
  939. "SimpleSequentialChain": {
  940. "display_name": "简单顺序链",
  941. "description": "简单的链,其中一个步骤的输出直接进入下一个步骤。",
  942. "template": {
  943. "chains": {
  944. "display_name": "链"
  945. },
  946. "input_node": {
  947. "display_name": "预设问题"
  948. },
  949. "memory": {
  950. "display_name": "内存"
  951. }
  952. }
  953. },
  954. "TimeTravelGuideChain": {
  955. "display_name": "时光导游链",
  956. "description": "时光导游链。",
  957. "template": {
  958. "input_node": {
  959. "display_name": "预设问题"
  960. },
  961. "llm": {
  962. "display_name": "LLM"
  963. },
  964. "memory": {
  965. "display_name": "内存"
  966. }
  967. }
  968. },
  969. "TransformChain": {
  970. "display_name": "转换链",
  971. "description": "链转换链输出。",
  972. "template": {
  973. "input_node": {
  974. "display_name": "预设问题"
  975. },
  976. "memory": {
  977. "display_name": "内存"
  978. },
  979. "transform": {
  980. "display_name": "转换"
  981. },
  982. "input_variables": {
  983. "display_name": "输入变量"
  984. },
  985. "output_variables": {
  986. "display_name": "输出变量"
  987. }
  988. }
  989. }
  990. },
  991. "documentloaders": {
  992. "AZLyricsLoader": {
  993. "display_name": "AZLyricsLoader",
  994. "description": "加载AZLyrics网页。",
  995. "template": {
  996. "metadata": {
  997. "display_name": "元数据"
  998. },
  999. "web_path": {
  1000. "display_name": "Web路径"
  1001. }
  1002. },
  1003. "base_classes": [
  1004. "文档"
  1005. ]
  1006. },
  1007. "AirbyteJSONLoader": {
  1008. "display_name": "AirbyteJSONLoader",
  1009. "description": "加载本地airbyte json文件。",
  1010. "template": {
  1011. "file_path": {
  1012. "display_name": "文件路径"
  1013. },
  1014. "metadata": {
  1015. "display_name": "元数据"
  1016. }
  1017. },
  1018. "base_classes": [
  1019. "文档"
  1020. ]
  1021. },
  1022. "BSHTMLLoader": {
  1023. "display_name": "BSHTMLLoader",
  1024. "description": "使用beautiful soup解析HTML文件的加载器。",
  1025. "template": {
  1026. "file_path": {
  1027. "display_name": "文件路径"
  1028. },
  1029. "metadata": {
  1030. "display_name": "元数据"
  1031. }
  1032. },
  1033. "base_classes": [
  1034. "文档"
  1035. ]
  1036. },
  1037. "CSVLoader": {
  1038. "display_name": "CSVLoader",
  1039. "description": "将CSV文件加载到文档列表中。",
  1040. "template": {
  1041. "file_path": {
  1042. "display_name": "文件路径"
  1043. },
  1044. "metadata": {
  1045. "display_name": "元数据"
  1046. }
  1047. },
  1048. "base_classes": [
  1049. "文档"
  1050. ]
  1051. },
  1052. "CoNLLULoader": {
  1053. "display_name": "CoNLLULoader",
  1054. "description": "加载CoNLL-U文件。",
  1055. "template": {
  1056. "file_path": {
  1057. "display_name": "文件路径"
  1058. },
  1059. "metadata": {
  1060. "display_name": "元数据"
  1061. }
  1062. },
  1063. "base_classes": [
  1064. "文档"
  1065. ]
  1066. },
  1067. "CollegeConfidentialLoader": {
  1068. "display_name": "CollegeConfidentialLoader",
  1069. "description": "加载College Confidential网页。",
  1070. "template": {
  1071. "metadata": {
  1072. "display_name": "元数据"
  1073. },
  1074. "web_path": {
  1075. "display_name": "Web路径"
  1076. }
  1077. },
  1078. "base_classes": [
  1079. "文档"
  1080. ]
  1081. },
  1082. "CustomKVLoader": {
  1083. "display_name": "CustomKVLoader",
  1084. "description": "从pdf或图像中提取键值对的加载器。",
  1085. "template": {
  1086. "file_path": {
  1087. "display_name": "文件路径"
  1088. },
  1089. "elem_server_id": {
  1090. "display_name": "元素服务器ID"
  1091. },
  1092. "elm_api_base_url": {
  1093. "display_name": "elm API基本URL"
  1094. },
  1095. "elm_api_key": {
  1096. "display_name": "elm API密钥"
  1097. },
  1098. "metadata": {
  1099. "display_name": "元数据"
  1100. },
  1101. "schemas": {
  1102. "display_name": "模式"
  1103. },
  1104. "task_type": {
  1105. "display_name": "任务类型"
  1106. }
  1107. },
  1108. "base_classes": [
  1109. "文档"
  1110. ]
  1111. },
  1112. "DirectoryLoader": {
  1113. "display_name": "DirectoryLoader",
  1114. "description": "从目录加载文档。",
  1115. "template": {
  1116. "glob": {
  1117. "display_name": "全局通配符"
  1118. },
  1119. "metadata": {
  1120. "display_name": "元数据"
  1121. },
  1122. "path": {
  1123. "display_name": "本地目录"
  1124. }
  1125. },
  1126. "base_classes": [
  1127. "文档"
  1128. ]
  1129. },
  1130. "ElemUnstructuredLoaderV0": {
  1131. "display_name": "ElemUnstructuredLoaderV0",
  1132. "description": "根据文件格式自动选择适当的解析器,并支持OCR的加载器。",
  1133. "template": {
  1134. "file_path": {
  1135. "display_name": "文件路径"
  1136. },
  1137. "metadata": {
  1138. "display_name": "元数据"
  1139. },
  1140. "unstructured_api_url": {
  1141. "display_name": "非结构化API URL"
  1142. }
  1143. },
  1144. "base_classes": [
  1145. "文档"
  1146. ]
  1147. },
  1148. "EverNoteLoader": {
  1149. "display_name": "EverNoteLoader",
  1150. "description": "EverNote加载器。",
  1151. "template": {
  1152. "file_path": {
  1153. "display_name": "文件路径"
  1154. },
  1155. "metadata": {
  1156. "display_name": "元数据"
  1157. }
  1158. },
  1159. "base_classes": [
  1160. "文档"
  1161. ]
  1162. },
  1163. "FacebookChatLoader": {
  1164. "display_name": "FacebookChatLoader",
  1165. "description": "加载Facebook消息json目录转储。",
  1166. "template": {
  1167. "file_path": {
  1168. "display_name": "文件路径"
  1169. },
  1170. "metadata": {
  1171. "display_name": "元数据"
  1172. }
  1173. },
  1174. "base_classes": [
  1175. "文档"
  1176. ]
  1177. },
  1178. "GitLoader": {
  1179. "display_name": "GitLoader",
  1180. "description": "从Git存储库加载文件到文档列表。",
  1181. "template": {
  1182. "branch": {
  1183. "display_name": "分支"
  1184. },
  1185. "clone_url": {
  1186. "display_name": "克隆URL"
  1187. },
  1188. "file_filter": {
  1189. "display_name": "文件扩展名(逗号分隔)"
  1190. },
  1191. "metadata": {
  1192. "display_name": "元数据"
  1193. },
  1194. "repo_path": {
  1195. "display_name": "存储库路径"
  1196. }
  1197. },
  1198. "base_classes": [
  1199. "文档"
  1200. ]
  1201. },
  1202. "GitbookLoader": {
  1203. "display_name": "GitbookLoader",
  1204. "description": "加载GitBook数据。",
  1205. "template": {
  1206. "metadata": {
  1207. "display_name": "元数据"
  1208. },
  1209. "web_page": {
  1210. "display_name": "Web页面"
  1211. }
  1212. },
  1213. "base_classes": [
  1214. "文档"
  1215. ]
  1216. },
  1217. "GutenbergLoader": {
  1218. "display_name": "GutenbergLoader",
  1219. "description": "使用urllib加载.txt网页文件的加载器。",
  1220. "template": {
  1221. "metadata": {
  1222. "display_name": "元数据"
  1223. },
  1224. "web_page": {
  1225. "display_name": "Web页面"
  1226. }
  1227. },
  1228. "base_classes": [
  1229. "文档"
  1230. ]
  1231. },
  1232. "HNLoader": {
  1233. "display_name": "HNLoader",
  1234. "description": "从Hacker News加载数据,可以是主页结果或评论页面。",
  1235. "template": {
  1236. "metadata": {
  1237. "display_name": "元数据"
  1238. },
  1239. "web_page": {
  1240. "display_name": "Web页面"
  1241. }
  1242. },
  1243. "base_classes": [
  1244. "文档"
  1245. ]
  1246. },
  1247. "IFixitLoader": {
  1248. "display_name": "IFixitLoader",
  1249. "description": "加载iFixit修复指南、设备维基和答案。",
  1250. "template": {
  1251. "metadata": {
  1252. "display_name": "元数据"
  1253. },
  1254. "web_page": {
  1255. "display_name": "Web页面"
  1256. }
  1257. },
  1258. "base_classes": [
  1259. "文档"
  1260. ]
  1261. },
  1262. "IMSDbLoader": {
  1263. "display_name": "IMSDbLoader",
  1264. "description": "加载IMSDb网页。",
  1265. "template": {
  1266. "metadata": {
  1267. "display_name": "元数据"
  1268. },
  1269. "web_page": {
  1270. "display_name": "Web页面"
  1271. }
  1272. },
  1273. "base_classes": [
  1274. "文档"
  1275. ]
  1276. },
  1277. "NotionDirectoryLoader": {
  1278. "display_name": "NotionDirectoryLoader",
  1279. "description": "加载Notion目录转储。",
  1280. "template": {
  1281. "metadata": {
  1282. "display_name": "元数据"
  1283. },
  1284. "path": {
  1285. "display_name": "本地目录"
  1286. }
  1287. },
  1288. "base_classes": [
  1289. "文档"
  1290. ]
  1291. },
  1292. "PDFWithSemanticLoader": {
  1293. "display_name": "PDFWithSemanticLoader",
  1294. "description": "使用pypdf加载PDF并以字符级别切块。",
  1295. "template": {
  1296. "file_path": {
  1297. "display_name": "文件路径"
  1298. },
  1299. "layout_api_key": {
  1300. "display_name": "布局API密钥"
  1301. },
  1302. "layout_api_url": {
  1303. "display_name": "布局API URL"
  1304. },
  1305. "metadata": {
  1306. "display_name": "元数据"
  1307. }
  1308. },
  1309. "base_classes": [
  1310. "文档"
  1311. ]
  1312. },
  1313. "PyPDFDirectoryLoader": {
  1314. "display_name": "PyPDFDirectoryLoader",
  1315. "description": "使用pypdf从目录加载具有字符级别切块的PDF文件。",
  1316. "template": {
  1317. "metadata": {
  1318. "display_name": "元数据"
  1319. },
  1320. "path": {
  1321. "display_name": "本地目录"
  1322. }
  1323. },
  1324. "base_classes": [
  1325. "文档"
  1326. ]
  1327. },
  1328. "PyPDFLoader": {
  1329. "display_name": "PyPDFLoader",
  1330. "description": "使用pypdf加载具有字符级别切块的PDF文件。",
  1331. "template": {
  1332. "file_path": {
  1333. "display_name": "文件路径"
  1334. },
  1335. "metadata": {
  1336. "display_name": "元数据"
  1337. }
  1338. },
  1339. "base_classes": [
  1340. "文档"
  1341. ]
  1342. },
  1343. "ReadTheDocsLoader": {
  1344. "display_name": "ReadTheDocsLoader",
  1345. "description": "加载ReadTheDocs文档目录转储。",
  1346. "template": {
  1347. "metadata": {
  1348. "display_name": "元数据"
  1349. },
  1350. "path": {
  1351. "display_name": "本地目录"
  1352. }
  1353. },
  1354. "base_classes": [
  1355. "文档"
  1356. ]
  1357. },
  1358. "SRTLoader": {
  1359. "display_name": "SRTLoader",
  1360. "description": "用于.srt(字幕)文件的加载器。",
  1361. "template": {
  1362. "file_path": {
  1363. "display_name": "文件路径"
  1364. },
  1365. "metadata": {
  1366. "display_name": "元数据"
  1367. }
  1368. },
  1369. "base_classes": [
  1370. "文档"
  1371. ]
  1372. },
  1373. "SlackDirectoryLoader": {
  1374. "display_name": "SlackDirectoryLoader",
  1375. "description": "从Slack目录转储加载文档。",
  1376. "template": {
  1377. "file_path": {
  1378. "display_name": "文件路径"
  1379. },
  1380. "metadata": {
  1381. "display_name": "元数据"
  1382. }
  1383. },
  1384. "base_classes": [
  1385. "文档"
  1386. ]
  1387. },
  1388. "TextLoader": {
  1389. "display_name": "TextLoader",
  1390. "description": "加载文本文件。",
  1391. "template": {
  1392. "file_path": {
  1393. "display_name": "文件路径"
  1394. },
  1395. "metadata": {
  1396. "display_name": "元数据"
  1397. }
  1398. },
  1399. "base_classes": [
  1400. "文档"
  1401. ]
  1402. },
  1403. "UniversalKVLoader": {
  1404. "display_name": "UniversalKVLoader",
  1405. "description": "从pdf或图像中提取键值对的加载器。",
  1406. "template": {
  1407. "file_path": {
  1408. "display_name": "文件路径"
  1409. },
  1410. "ellm_model_url": {
  1411. "display_name": "ellm模型URL"
  1412. },
  1413. "max_pages": {
  1414. "display_name": "最大页数"
  1415. },
  1416. "metadata": {
  1417. "display_name": "元数据"
  1418. },
  1419. "schema": {
  1420. "display_name": "模式"
  1421. }
  1422. },
  1423. "base_classes": [
  1424. "文档"
  1425. ]
  1426. },
  1427. "WebBaseLoader": {
  1428. "display_name": "WebBaseLoader",
  1429. "description": "使用urllib和beautiful soup加载网页的加载器。",
  1430. "template": {
  1431. "metadata": {
  1432. "display_name": "元数据"
  1433. },
  1434. "web_path": {
  1435. "display_name": "Web页面"
  1436. }
  1437. },
  1438. "base_classes": [
  1439. "文档"
  1440. ]
  1441. }
  1442. },
  1443. "embeddings": {
  1444. "CohereEmbeddings": {
  1445. "display_name": "CohereEmbeddings",
  1446. "description": "Cohere嵌入模型的封装。",
  1447. "template": {
  1448. "cohere_api_key": {
  1449. "display_name": "cohere_api_key"
  1450. },
  1451. "model": {
  1452. "display_name": "模型"
  1453. }
  1454. },
  1455. "base_classes": [
  1456. "CohereEmbeddings",
  1457. "嵌入模型"
  1458. ]
  1459. },
  1460. "HostEmbeddings": {
  1461. "display_name": "HostEmbeddings",
  1462. "description": "主机嵌入模型。",
  1463. "template": {
  1464. "host_base_url": {
  1465. "display_name": "主机基础URL"
  1466. },
  1467. "model": {
  1468. "display_name": "模型"
  1469. }
  1470. },
  1471. "base_classes": [
  1472. "嵌入模型",
  1473. "HostEmbeddings"
  1474. ]
  1475. },
  1476. "HuggingFaceEmbeddings": {
  1477. "display_name": "HuggingFaceEmbeddings",
  1478. "description": "sentence_transformers嵌入模型的封装。",
  1479. "base_classes": [
  1480. "嵌入模型",
  1481. "HostEmbeddings"
  1482. ]
  1483. },
  1484. "OpenAIEmbeddings": {
  1485. "display_name": "OpenAIEmbeddings",
  1486. "description": "OpenAI嵌入模型的封装。",
  1487. "template": {
  1488. "model": {
  1489. "display_name": "模型"
  1490. },
  1491. "openai_api_key": {
  1492. "display_name": "OpenAI API密钥"
  1493. },
  1494. "tiktoken_model_name": {
  1495. "display_name": "tiktoken模型名称"
  1496. }
  1497. },
  1498. "base_classes": [
  1499. "嵌入模型",
  1500. "OpenAI嵌入模型"
  1501. ]
  1502. },
  1503. "OpenAIProxyEmbedding": {
  1504. "display_name": "OpenAIProxyEmbedding",
  1505. "description": "使用自建的embedding服务使用OpenAI进行嵌入。",
  1506. "base_classes": [
  1507. "嵌入模型"
  1508. ]
  1509. },
  1510. "WenxinEmbeddings": {
  1511. "display_name": "WenxinEmbeddings",
  1512. "description": "Wenxin嵌入模型。",
  1513. "template": {
  1514. "model": {
  1515. "display_name": "模型"
  1516. },
  1517. "wenxin_api_key": {
  1518. "display_name": "Wenxin API密钥"
  1519. }
  1520. },
  1521. "base_classes": [
  1522. "嵌入模型",
  1523. "Wenxin嵌入模型"
  1524. ]
  1525. }
  1526. },
  1527. "input_output": {
  1528. "InputFileNode": {
  1529. "display_name": "InputFileNode",
  1530. "description": "输入文件节点,用于自动连接输入。",
  1531. "template": {
  1532. "file_path": {
  1533. "display_name": "文件路径"
  1534. },
  1535. "file_type": {
  1536. "display_name": "文件类型"
  1537. }
  1538. },
  1539. "base_classes": [
  1540. "文件节点"
  1541. ]
  1542. },
  1543. "InputNode": {
  1544. "display_name": "InputNode",
  1545. "description": "输入节点,用于自动连接输入。",
  1546. "template": {
  1547. "input": {
  1548. "display_name": "输入内容"
  1549. }
  1550. },
  1551. "base_classes": [
  1552. "输入节点"
  1553. ]
  1554. },
  1555. "Report": {
  1556. "display_name": "Report",
  1557. "template": {
  1558. "chains": {
  1559. "display_name": "功能链"
  1560. },
  1561. "variables": {
  1562. "display_name": "变量"
  1563. },
  1564. "report_name": {
  1565. "display_name": "报告名称"
  1566. }
  1567. },
  1568. "base_classes": [
  1569. "报告",
  1570. "功能链"
  1571. ]
  1572. },
  1573. "VariableNode": {
  1574. "display_name": "VariableNode",
  1575. "description": "用于设置变量。",
  1576. "template": {
  1577. "variables": {
  1578. "display_name": "变量"
  1579. }
  1580. },
  1581. "base_classes": [
  1582. "变量节点"
  1583. ]
  1584. }
  1585. },
  1586. "llms": {
  1587. "Anthropic": {
  1588. "display_name": "Anthropic",
  1589. "description": "Anthropic大型语言模型的封装。",
  1590. "template": {
  1591. "anthropic_api_key": {
  1592. "display_name": "anthropic_api_key"
  1593. },
  1594. "anthropic_api_url": {
  1595. "display_name": "anthropic_api_url"
  1596. },
  1597. "temperature": {
  1598. "display_name": "温度"
  1599. }
  1600. },
  1601. "base_classes": [
  1602. "Anthropic",
  1603. "BaseLLM",
  1604. "_AnthropicCommon",
  1605. "BaseLanguageModel",
  1606. "LLM"
  1607. ]
  1608. },
  1609. "AzureChatOpenAI": {
  1610. "display_name": "AzureChatOpenAI",
  1611. "description": "Azure OpenAI聊天完成API的封装。要使用此类,您需要",
  1612. "template": {
  1613. "model_name": {
  1614. "display_name": "model_name"
  1615. },
  1616. "openai_proxy": {
  1617. "display_name": "OpenAI代理"
  1618. },
  1619. "temperature": {
  1620. "display_name": "温度"
  1621. }
  1622. },
  1623. "base_classes": [
  1624. "BaseChatModel",
  1625. "AzureChatOpenAI",
  1626. "ChatOpenAI",
  1627. "BaseLanguageModel",
  1628. "BaseLLM"
  1629. ]
  1630. },
  1631. "CTransformers": {
  1632. "display_name": "CTransformers",
  1633. "description": "C Transformers LLM接口的封装。",
  1634. "template": {
  1635. "model": {
  1636. "display_name": "model"
  1637. },
  1638. "model_file": {
  1639. "display_name": "model_file"
  1640. },
  1641. "model_type": {
  1642. "display_name": "model_type"
  1643. }
  1644. },
  1645. "base_classes": [
  1646. "CTransformers",
  1647. "BaseLLM",
  1648. "BaseLanguageModel",
  1649. "LLM"
  1650. ]
  1651. },
  1652. "ChatAnthropic": {
  1653. "display_name": "ChatAnthropic",
  1654. "description": "Anthropic大型语言模型的封装。",
  1655. "template": {
  1656. "anthropic_api_key": {
  1657. "display_name": "anthropic_api_key"
  1658. },
  1659. "anthropic_api_url": {
  1660. "display_name": "anthropic_api_url"
  1661. },
  1662. "temperature": {
  1663. "display_name": "温度"
  1664. }
  1665. },
  1666. "base_classes": [
  1667. "BaseChatModel",
  1668. "_AnthropicCommon",
  1669. "BaseLanguageModel",
  1670. "ChatAnthropic",
  1671. "BaseLLM"
  1672. ]
  1673. },
  1674. "ChatMinimaxAI": {
  1675. "display_name": "ChatMinimaxAI",
  1676. "description": "代理Chat大型语言模型的封装。",
  1677. "template": {
  1678. "minimaxai_api_key": {
  1679. "display_name": "minimaxai_api_key"
  1680. },
  1681. "minimaxai_group_id": {
  1682. "display_name": "minimaxai_group_id"
  1683. },
  1684. "model_name": {
  1685. "display_name": "model_name"
  1686. },
  1687. "temperature": {
  1688. "display_name": "温度"
  1689. }
  1690. },
  1691. "base_classes": [
  1692. "ChatMinimaxAI",
  1693. "BaseLanguageModel",
  1694. "BaseChatModel",
  1695. "BaseLLM"
  1696. ]
  1697. },
  1698. "ChatOpenAI": {
  1699. "display_name": "ChatOpenAI",
  1700. "description": "OpenAI Chat大型语言模型的封装。",
  1701. "template": {
  1702. "model_name": {
  1703. "display_name": "model_name",
  1704. "options": [
  1705. "gpt-3.5-turbo-0613",
  1706. "gpt-3.5-turbo",
  1707. "gpt-3.5-turbo-16k-0613",
  1708. "gpt-3.5-turbo-16k",
  1709. "gpt-4-0613",
  1710. "gpt-4-32k-0613",
  1711. "gpt-4",
  1712. "gpt-4-32k",
  1713. "gpt-4-1106-preview"
  1714. ]
  1715. },
  1716. "openai_api_base": {
  1717. "display_name": "OpenAI API Base"
  1718. },
  1719. "openai_api_key": {
  1720. "display_name": "OpenAI API Key"
  1721. },
  1722. "openai_proxy": {
  1723. "display_name": "OpenAI代理"
  1724. },
  1725. "temperature": {
  1726. "display_name": "温度"
  1727. }
  1728. },
  1729. "base_classes": [
  1730. "ChatOpenAI",
  1731. "BaseLanguageModel",
  1732. "BaseChatModel",
  1733. "BaseLLM"
  1734. ]
  1735. },
  1736. "ChatQWen": {
  1737. "display_name": "ChatQWen",
  1738. "description": "代理Chat大型语言模型的封装。",
  1739. "template": {
  1740. "api_key": {
  1741. "display_name": "api_key"
  1742. },
  1743. "model_name": {
  1744. "display_name": "model_name"
  1745. },
  1746. "temperature": {
  1747. "display_name": "温度"
  1748. }
  1749. },
  1750. "base_classes": [
  1751. "ChatQWen",
  1752. "BaseLanguageModel",
  1753. "BaseChatModel",
  1754. "BaseLLM"
  1755. ]
  1756. },
  1757. "ChatWenxin": {
  1758. "display_name": "ChatWenxin",
  1759. "description": "代理Chat大型语言模型的封装。",
  1760. "template": {
  1761. "model_name": {
  1762. "display_name": "model_name"
  1763. },
  1764. "temperature": {
  1765. "display_name": "温度"
  1766. },
  1767. "wenxin_api_key": {
  1768. "display_name": "wenxin_api_key"
  1769. },
  1770. "wenxin_secret_key": {
  1771. "display_name": "wenxin_secret_key"
  1772. }
  1773. },
  1774. "base_classes": [
  1775. "BaseLanguageModel",
  1776. "ChatWenxin",
  1777. "BaseChatModel",
  1778. "BaseLLM"
  1779. ]
  1780. },
  1781. "ChatXunfeiAI": {
  1782. "display_name": "ChatXunfeiAI",
  1783. "description": "代理Chat大型语言模型的封装。",
  1784. "template": {
  1785. "model_name": {
  1786. "display_name": "model_name"
  1787. },
  1788. "temperature": {
  1789. "display_name": "温度"
  1790. },
  1791. "xunfeiai_api_key": {
  1792. "display_name": "xunfeiai_api_key"
  1793. },
  1794. "xunfeiai_api_secret": {
  1795. "display_name": "xunfeiai_api_secret"
  1796. },
  1797. "xunfeiai_appid": {
  1798. "display_name": "xunfeiai_appid"
  1799. }
  1800. },
  1801. "base_classes": [
  1802. "ChatXunfeiAI",
  1803. "BaseLanguageModel",
  1804. "BaseChatModel",
  1805. "BaseLLM"
  1806. ]
  1807. },
  1808. "ChatZhipuAI": {
  1809. "display_name": "ChatZhipuAI",
  1810. "description": "ZhipuAI Chat大型语言模型的封装。",
  1811. "template": {
  1812. "model_name": {
  1813. "display_name": "model_name"
  1814. },
  1815. "temperature": {
  1816. "display_name": "温度"
  1817. },
  1818. "zhipuai_api_key": {
  1819. "display_name": "zhipuai_api_key"
  1820. }
  1821. },
  1822. "base_classes": [
  1823. "ChatZhipuAI",
  1824. "BaseLanguageModel",
  1825. "BaseChatModel",
  1826. "BaseLLM"
  1827. ]
  1828. },
  1829. "Cohere": {
  1830. "display_name": "Cohere",
  1831. "description": "Cohere大型语言模型的封装。",
  1832. "template": {
  1833. "cohere_api_key": {
  1834. "display_name": "cohere_api_key"
  1835. },
  1836. "temperature": {
  1837. "display_name": "温度"
  1838. }
  1839. },
  1840. "base_classes": [
  1841. "BaseLLM",
  1842. "Cohere",
  1843. "BaseLanguageModel",
  1844. "LLM"
  1845. ]
  1846. },
  1847. "CustomLLMChat": {
  1848. "display_name": "CustomLLMChat",
  1849. "template": {
  1850. "host_base_url": {
  1851. "display_name": "host_base_url"
  1852. },
  1853. "model_name": {
  1854. "display_name": "model_name"
  1855. },
  1856. "temperature": {
  1857. "display_name": "温度"
  1858. }
  1859. },
  1860. "base_classes": [
  1861. "BaseChatModel",
  1862. "BaseHostChatLLM",
  1863. "CustomLLMChat",
  1864. "BaseLanguageModel",
  1865. "BaseLLM"
  1866. ]
  1867. },
  1868. "HostBaichuanChat": {
  1869. "display_name": "HostBaichuanChat",
  1870. "template": {
  1871. "host_base_url": {
  1872. "display_name": "host_base_url"
  1873. },
  1874. "model_name": {
  1875. "display_name": "model_name"
  1876. },
  1877. "temperature": {
  1878. "display_name": "温度"
  1879. }
  1880. },
  1881. "base_classes": [
  1882. "BaseChatModel",
  1883. "BaseHostChatLLM",
  1884. "HostBaichuanChat",
  1885. "BaseLanguageModel",
  1886. "BaseLLM"
  1887. ]
  1888. },
  1889. "HostChatGLM": {
  1890. "display_name": "HostChatGLM",
  1891. "template": {
  1892. "host_base_url": {
  1893. "display_name": "host_base_url"
  1894. },
  1895. "model_name": {
  1896. "display_name": "model_name"
  1897. },
  1898. "temperature": {
  1899. "display_name": "温度"
  1900. }
  1901. },
  1902. "base_classes": [
  1903. "BaseChatModel",
  1904. "BaseHostChatLLM",
  1905. "BaseLanguageModel",
  1906. "HostChatGLM",
  1907. "BaseLLM"
  1908. ]
  1909. },
  1910. "HostLlama2Chat": {
  1911. "display_name": "HostLlama2Chat",
  1912. "template": {
  1913. "host_base_url": {
  1914. "display_name": "host_base_url"
  1915. },
  1916. "model_name": {
  1917. "display_name": "model_name"
  1918. },
  1919. "temperature": {
  1920. "display_name": "温度"
  1921. }
  1922. },
  1923. "base_classes": [
  1924. "HostLlama2Chat",
  1925. "BaseChatModel",
  1926. "BaseHostChatLLM",
  1927. "BaseLanguageModel",
  1928. "BaseLLM"
  1929. ]
  1930. },
  1931. "HostQwenChat": {
  1932. "display_name": "HostQwenChat",
  1933. "template": {
  1934. "host_base_url": {
  1935. "display_name": "host_base_url"
  1936. },
  1937. "model_name": {
  1938. "display_name": "model_name"
  1939. },
  1940. "temperature": {
  1941. "display_name": "温度"
  1942. }
  1943. },
  1944. "base_classes": [
  1945. "BaseChatModel",
  1946. "BaseHostChatLLM",
  1947. "HostQwenChat",
  1948. "BaseLanguageModel",
  1949. "BaseLLM"
  1950. ]
  1951. },
  1952. "HuggingFaceHub": {
  1953. "display_name": "HuggingFaceHub",
  1954. "description": "HuggingFaceHub模型的封装。",
  1955. "template": {
  1956. "huggingfacehub_api_token": {
  1957. "display_name": "HuggingFace Hub API Token"
  1958. },
  1959. "repo_id": {
  1960. "display_name": "repo_id"
  1961. }
  1962. },
  1963. "base_classes": [
  1964. "BaseLLM",
  1965. "BaseLanguageModel",
  1966. "HuggingFaceHub",
  1967. "LLM"
  1968. ]
  1969. },
  1970. "LlamaCpp": {
  1971. "display_name": "HuggingFaceHub",
  1972. "description": "llama.cpp模型的封装。",
  1973. "template": {
  1974. "model_path": {
  1975. "display_name": "model_path"
  1976. },
  1977. "temperature": {
  1978. "display_name": "温度"
  1979. }
  1980. },
  1981. "base_classes": [
  1982. "BaseLLM",
  1983. "LlamaCpp",
  1984. "BaseLanguageModel",
  1985. "LLM"
  1986. ]
  1987. },
  1988. "OpenAI": {
  1989. "display_name": "OpenAI",
  1990. "description": "包装了OpenAI大型语言模型。",
  1991. "template": {
  1992. "model_name": {
  1993. "display_name": "模型名称",
  1994. "options": [
  1995. "text-davinci-003",
  1996. "text-davinci-002",
  1997. "text-curie-001",
  1998. "text-babbage-001",
  1999. "text-ada-001"
  2000. ]
  2001. },
  2002. "openai_api_base": {
  2003. "display_name": "OpenAI API基础地址"
  2004. },
  2005. "openai_api_key": {
  2006. "display_name": "OpenAI API密钥"
  2007. },
  2008. "openai_proxy": {
  2009. "display_name": "OpenAI代理"
  2010. },
  2011. "temperature": {
  2012. "display_name": "温度"
  2013. }
  2014. },
  2015. "base_classes": [
  2016. "BaseLLM",
  2017. "OpenAI",
  2018. "BaseOpenAI",
  2019. "BaseLanguageModel"
  2020. ]
  2021. },
  2022. "ProxyChatLLM": {
  2023. "display_name": "ProxyChatLLM",
  2024. "description": "包装了代理Chat大型语言模型。",
  2025. "template": {
  2026. "elemai_api_key": {
  2027. "display_name": "elemai_api_key"
  2028. },
  2029. "elemai_base_url": {
  2030. "display_name": "elemai_base_url"
  2031. },
  2032. "model_name": {
  2033. "display_name": "模型名称"
  2034. },
  2035. "temperature": {
  2036. "display_name": "温度"
  2037. }
  2038. },
  2039. "base_classes": [
  2040. "ProxyChatLLM",
  2041. "BaseLanguageModel",
  2042. "BaseChatModel",
  2043. "BaseLLM"
  2044. ]
  2045. },
  2046. "VertexAI": {
  2047. "display_name": "VertexAI",
  2048. "description": "包装了Google Vertex AI大型语言模型。",
  2049. "template": {
  2050. "credentials": {
  2051. "display_name": "凭据"
  2052. },
  2053. "location": {
  2054. "display_name": "位置"
  2055. },
  2056. "max_retries": {
  2057. "display_name": "最大重试次数"
  2058. },
  2059. "metadata": {
  2060. "display_name": "元数据"
  2061. },
  2062. "model_name": {
  2063. "display_name": "模型名称"
  2064. },
  2065. "project": {
  2066. "display_name": "项目"
  2067. },
  2068. "request_parallelism": {
  2069. "display_name": "请求并行度"
  2070. },
  2071. "temperature": {
  2072. "display_name": "温度"
  2073. }
  2074. },
  2075. "base_classes": [
  2076. "VertexAI",
  2077. "BaseLLM",
  2078. "_VertexAICommon",
  2079. "BaseLanguageModel",
  2080. "LLM"
  2081. ]
  2082. }
  2083. },
  2084. "memories": {
  2085. "ConversationBufferMemory": {
  2086. "display_name": "ConversationBufferMemory",
  2087. "description": "用于存储对话记忆的缓冲区。",
  2088. "template": {
  2089. "chat_memory": {
  2090. "display_name": "聊天记忆"
  2091. },
  2092. "input_key": {
  2093. "display_name": "输入键"
  2094. },
  2095. "memory_key": {
  2096. "display_name": "记忆键"
  2097. },
  2098. "output_key": {
  2099. "display_name": "输出键"
  2100. },
  2101. "return_messages": {
  2102. "display_name": "返回消息"
  2103. }
  2104. },
  2105. "base_classes": [
  2106. "BaseMemory",
  2107. "BaseChatMemory",
  2108. "ConversationBufferMemory"
  2109. ]
  2110. },
  2111. "ConversationBufferWindowMemory": {
  2112. "display_name": "ConversationBufferWindowMemory",
  2113. "description": "用于存储对话记忆的缓冲区。",
  2114. "template": {
  2115. "chat_memory": {
  2116. "display_name": "聊天记忆"
  2117. },
  2118. "input_key": {
  2119. "display_name": "输入键"
  2120. },
  2121. "k": {
  2122. "display_name": "记忆大小"
  2123. },
  2124. "memory_key": {
  2125. "display_name": "记忆键"
  2126. },
  2127. "output_key": {
  2128. "display_name": "输出键"
  2129. },
  2130. "return_messages": {
  2131. "display_name": "返回消息"
  2132. }
  2133. },
  2134. "base_classes": [
  2135. "ConversationBufferWindowMemory",
  2136. "BaseMemory",
  2137. "BaseChatMemory"
  2138. ]
  2139. },
  2140. "ConversationEntityMemory": {
  2141. "display_name": "ConversationEntityMemory",
  2142. "description": "实体提取器和摘要生成器的记忆。",
  2143. "template": {
  2144. "chat_memory": {
  2145. "display_name": "聊天记忆"
  2146. },
  2147. "llm": {
  2148. "display_name": "llm"
  2149. },
  2150. "chat_history_key": {
  2151. "display_name": "聊天历史键"
  2152. },
  2153. "input_key": {
  2154. "display_name": "输入键"
  2155. },
  2156. "k": {
  2157. "display_name": "记忆大小"
  2158. },
  2159. "output_key": {
  2160. "display_name": "输出键"
  2161. },
  2162. "return_messages": {
  2163. "display_name": "返回消息"
  2164. }
  2165. },
  2166. "base_classes": [
  2167. "ConversationEntityMemory",
  2168. "BaseMemory",
  2169. "BaseChatMemory"
  2170. ]
  2171. },
  2172. "ConversationKGMemory": {
  2173. "display_name": "ConversationKGMemory",
  2174. "description": "用于存储对话记忆的知识图记忆。",
  2175. "template": {
  2176. "chat_memory": {
  2177. "display_name": "聊天记忆"
  2178. },
  2179. "llm": {
  2180. "display_name": "llm"
  2181. },
  2182. "input_key": {
  2183. "display_name": "输入键"
  2184. },
  2185. "k": {
  2186. "display_name": "记忆大小"
  2187. },
  2188. "memory_key": {
  2189. "display_name": "记忆键"
  2190. },
  2191. "output_key": {
  2192. "display_name": "输出键"
  2193. },
  2194. "return_messages": {
  2195. "display_name": "返回消息"
  2196. }
  2197. },
  2198. "base_classes": [
  2199. "ConversationEntityMemory",
  2200. "BaseMemory",
  2201. "BaseChatMemory"
  2202. ]
  2203. },
  2204. "ConversationSummaryMemory": {
  2205. "display_name": "ConversationSummaryMemory",
  2206. "description": "用于对话摘要的记忆。",
  2207. "template": {
  2208. "chat_memory": {
  2209. "display_name": "聊天记忆"
  2210. },
  2211. "llm": {
  2212. "display_name": "llm"
  2213. },
  2214. "input_key": {
  2215. "display_name": "输入键"
  2216. },
  2217. "memory_key": {
  2218. "display_name": "记忆键"
  2219. },
  2220. "output_key": {
  2221. "display_name": "输出键"
  2222. },
  2223. "return_messages": {
  2224. "display_name": "返回消息"
  2225. }
  2226. },
  2227. "base_classes": [
  2228. "BaseChatMemory",
  2229. "SummarizerMixin",
  2230. "ConversationSummaryMemory",
  2231. "BaseMemory"
  2232. ]
  2233. },
  2234. "MongoDBChatMessageHistory": {
  2235. "display_name": "MongoDBChatMessageHistory",
  2236. "description": "使用MongoDB的内存存储。",
  2237. "template": {
  2238. "collection_name": {
  2239. "display_name": "集合名称"
  2240. },
  2241. "connection_string": {
  2242. "display_name": "连接字符串"
  2243. },
  2244. "database_name": {
  2245. "display_name": "数据库名称"
  2246. },
  2247. "session_id": {
  2248. "display_name": "会话ID"
  2249. }
  2250. },
  2251. "base_classes": [
  2252. "MongoDBChatMessageHistory",
  2253. "BaseChatMessageHistory"
  2254. ]
  2255. },
  2256. "PostgresChatMessageHistory": {
  2257. "display_name": "PostgresChatMessageHistory",
  2258. "description": "使用Postgres的内存存储。",
  2259. "template": {
  2260. "connection_string": {
  2261. "display_name": "连接字符串"
  2262. },
  2263. "session_id": {
  2264. "display_name": "会话ID"
  2265. },
  2266. "table_name": {
  2267. "display_name": "表名"
  2268. }
  2269. },
  2270. "base_classes": [
  2271. "PostgresChatMessageHistory",
  2272. "BaseChatMessageHistory"
  2273. ]
  2274. },
  2275. "VectorStoreRetrieverMemory": {
  2276. "display_name": "VectorStoreRetrieverMemory",
  2277. "description": "用于基于VectorStore的内存对象的类。",
  2278. "template": {
  2279. "retriever": {
  2280. "display_name": "检索器"
  2281. },
  2282. "input_key": {
  2283. "display_name": "输入键"
  2284. },
  2285. "memory_key": {
  2286. "display_name": "记忆键"
  2287. },
  2288. "return_messages": {
  2289. "display_name": "返回消息"
  2290. }
  2291. },
  2292. "base_classes": [
  2293. "VectorStoreRetrieverMemory",
  2294. "BaseMemory"
  2295. ]
  2296. }
  2297. },
  2298. "output_parsers": {
  2299. "ResponseSchema": {
  2300. "display_name": "ResponseSchema",
  2301. "template": {
  2302. "description": {
  2303. "display_name": "描述"
  2304. },
  2305. "name": {
  2306. "display_name": "名称"
  2307. },
  2308. "type": {
  2309. "display_name": "类型"
  2310. }
  2311. },
  2312. "base_classes": [
  2313. "ResponseSchema"
  2314. ]
  2315. },
  2316. "StructuredOutputParser": {
  2317. "display_name": "StructuredOutputParser",
  2318. "template": {
  2319. "response_schemas": {
  2320. "display_name": "响应模式"
  2321. }
  2322. },
  2323. "base_classes": [
  2324. "Generic",
  2325. "StructuredOutputParser",
  2326. "BaseOutputParser",
  2327. "BaseLLMOutputParser"
  2328. ]
  2329. }
  2330. },
  2331. "prompts": {
  2332. "ChatMessagePromptTemplate": {
  2333. "display_name": "ChatMessagePromptTemplate",
  2334. "template": {
  2335. "prompt": {
  2336. "display_name": "提示"
  2337. },
  2338. "role": {
  2339. "display_name": "角色"
  2340. }
  2341. },
  2342. "base_classes": [
  2343. "BaseStringMessagePromptTemplate",
  2344. "ChatMessagePromptTemplate",
  2345. "BaseMessagePromptTemplate"
  2346. ]
  2347. },
  2348. "ChatMessagePromptTemplate": {
  2349. "display_name": "ChatMessagePromptTemplate",
  2350. "template": {
  2351. "prompt": {
  2352. "display_name": "提示"
  2353. },
  2354. "role": {
  2355. "display_name": "角色"
  2356. }
  2357. },
  2358. "base_classes": [
  2359. "BaseStringMessagePromptTemplate",
  2360. "ChatMessagePromptTemplate",
  2361. "BaseMessagePromptTemplate"
  2362. ]
  2363. },
  2364. "ChatPromptTemplate": {
  2365. "display_name": "ChatPromptTemplate",
  2366. "template": {
  2367. "messages": {
  2368. "display_name": "消息"
  2369. },
  2370. "output_parser": {
  2371. "display_name": "输出解析器"
  2372. }
  2373. },
  2374. "base_classes": [
  2375. "BasePromptTemplate",
  2376. "ChatPromptTemplate",
  2377. "BaseChatPromptTemplate"
  2378. ]
  2379. },
  2380. "HumanMessagePromptTemplate": {
  2381. "display_name": "HumanMessagePromptTemplate",
  2382. "template": {
  2383. "prompt": {
  2384. "display_name": "提示"
  2385. }
  2386. },
  2387. "base_classes": [
  2388. "BaseStringMessagePromptTemplate",
  2389. "HumanMessagePromptTemplate",
  2390. "BaseMessagePromptTemplate"
  2391. ]
  2392. },
  2393. "PromptTemplate": {
  2394. "display_name": "PromptTemplate",
  2395. "description": "表示LLM提示的模式。",
  2396. "template": {
  2397. "output_parser": {
  2398. "display_name": "输出解析器"
  2399. },
  2400. "template": {
  2401. "display_name": "模板"
  2402. }
  2403. },
  2404. "base_classes": [
  2405. "StringPromptTemplate",
  2406. "BasePromptTemplate",
  2407. "PromptTemplate"
  2408. ]
  2409. },
  2410. "SystemMessagePromptTemplate": {
  2411. "display_name": "SystemMessagePromptTemplate",
  2412. "template": {
  2413. "prompt": {
  2414. "display_name": "提示"
  2415. }
  2416. },
  2417. "base_classes": [
  2418. "BaseStringMessagePromptTemplate",
  2419. "SystemMessagePromptTemplate",
  2420. "BaseMessagePromptTemplate"
  2421. ]
  2422. }
  2423. },
  2424. "retrievers": {
  2425. "MixEsVectorRetriever": {
  2426. "display_name": "MixEsVectorRetriever",
  2427. "description": "该类集成了es检索器和向量检索器的结果。",
  2428. "template": {
  2429. "keyword_retriever": {
  2430. "display_name": "关键词检索器"
  2431. },
  2432. "vector_retriever": {
  2433. "display_name": "向量检索器"
  2434. },
  2435. "combine_strategy": {
  2436. "display_name": "合并策略",
  2437. "options": [
  2438. "关键词在前",
  2439. "向量在前",
  2440. "混合"
  2441. ]
  2442. }
  2443. },
  2444. "base_classes": [
  2445. "MixEsVectorRetriever",
  2446. "BaseRetriever"
  2447. ]
  2448. },
  2449. "MultiQueryRetriever": {
  2450. "display_name": "MultiQueryRetriever",
  2451. "description": "从LLM使用默认模板初始化。",
  2452. "template": {
  2453. "llm": {
  2454. "display_name": "LLM"
  2455. },
  2456. "prompt": {
  2457. "display_name": "提示"
  2458. },
  2459. "retriever": {
  2460. "display_name": "检索器"
  2461. }
  2462. },
  2463. "base_classes": [
  2464. "MultiQueryRetriever",
  2465. "BaseRetriever"
  2466. ]
  2467. }
  2468. },
  2469. "textsplitters": {
  2470. "CharacterTextSplitter": {
  2471. "display_name": "CharacterTextSplitter",
  2472. "description": "基于字符的文本拆分实现。",
  2473. "template": {
  2474. "documents": {
  2475. "display_name": "文档"
  2476. },
  2477. "chunk_overlap": {
  2478. "display_name": "块重叠"
  2479. },
  2480. "chunk_size": {
  2481. "display_name": "块大小"
  2482. },
  2483. "separator": {
  2484. "display_name": "分隔符"
  2485. }
  2486. },
  2487. "base_classes": [
  2488. "文档"
  2489. ]
  2490. },
  2491. "RecursiveCharacterTextSplitter": {
  2492. "display_name": "RecursiveCharacterTextSplitter",
  2493. "description": "基于字符的文本拆分实现。",
  2494. "template": {
  2495. "documents": {
  2496. "display_name": "文档"
  2497. },
  2498. "chunk_overlap": {
  2499. "display_name": "块重叠"
  2500. },
  2501. "chunk_size": {
  2502. "display_name": "块大小"
  2503. },
  2504. "separator_type": {
  2505. "display_name": "分隔符类型"
  2506. },
  2507. "separator": {
  2508. "display_name": "分隔符"
  2509. }
  2510. },
  2511. "base_classes": [
  2512. "文档"
  2513. ]
  2514. }
  2515. },
  2516. "toolkits": {
  2517. "JsonToolkit": {
  2518. "display_name": "JsonToolkit",
  2519. "description": "与JSON规范交互的工具包。",
  2520. "template": {
  2521. "spec": {
  2522. "display_name": "规范"
  2523. }
  2524. },
  2525. "base_classes": [
  2526. "BaseToolkit",
  2527. "JsonToolkit",
  2528. "工具"
  2529. ]
  2530. },
  2531. "OpenAPIToolkit": {
  2532. "display_name": "OpenAPIToolkit",
  2533. "description": "与OpenAPI API交互的工具包。",
  2534. "template": {
  2535. "json_agent": {
  2536. "display_name": "JSON代理"
  2537. },
  2538. "requests_wrapper": {
  2539. "display_name": "请求封装"
  2540. }
  2541. },
  2542. "base_classes": [
  2543. "OpenAPIToolkit",
  2544. "BaseToolkit",
  2545. "工具"
  2546. ]
  2547. },
  2548. "VectorStoreInfo": {
  2549. "display_name": "VectorStoreInfo",
  2550. "description": "关于矢量存储的信息。",
  2551. "template": {
  2552. "vectorstore": {
  2553. "display_name": "矢量存储"
  2554. },
  2555. "description": {
  2556. "display_name": "描述"
  2557. },
  2558. "name": {
  2559. "display_name": "名称"
  2560. }
  2561. },
  2562. "base_classes": [
  2563. "VectorStoreInfo"
  2564. ]
  2565. },
  2566. "VectorStoreRouterToolkit": {
  2567. "display_name": "VectorStoreRouterToolkit",
  2568. "description": "用于在矢量存储之间进行路由的工具包。",
  2569. "template": {
  2570. "vectorstores": {
  2571. "display_name": "矢量存储"
  2572. }
  2573. },
  2574. "base_classes": [
  2575. "BaseToolkit",
  2576. "VectorStoreRouterToolkit",
  2577. "工具"
  2578. ]
  2579. },
  2580. "VectorStoreToolkit": {
  2581. "display_name": "VectorStoreToolkit",
  2582. "description": "与矢量存储交互的工具包。",
  2583. "template": {
  2584. "vectorstore_info": {
  2585. "display_name": "矢量存储信息"
  2586. }
  2587. },
  2588. "base_classes": [
  2589. "BaseToolkit",
  2590. "VectorStoreToolkit",
  2591. "工具"
  2592. ]
  2593. }
  2594. },
  2595. "tools": {
  2596. "BingSearchRun": {
  2597. "display_name": "BingSearchRun",
  2598. "description": "Bing搜索的封装。在需要回答有关当前事件的问题时很有用。输入应为搜索查询。",
  2599. "template": {
  2600. "api_wrapper": {
  2601. "display_name": "API封装"
  2602. },
  2603. "args_schema": {
  2604. "display_name": "参数模式"
  2605. }
  2606. },
  2607. "base_classes": [
  2608. "Tool",
  2609. "BaseTool",
  2610. "BingSearchRun",
  2611. "BaseTool"
  2612. ]
  2613. },
  2614. "Calculator": {
  2615. "display_name": "Calculator",
  2616. "description": "在需要回答数学问题时很有用。",
  2617. "template": {
  2618. "llm": {
  2619. "display_name": "llm"
  2620. },
  2621. "args_schema": {
  2622. "display_name": "参数模式"
  2623. }
  2624. },
  2625. "base_classes": [
  2626. "Tool",
  2627. "BaseTool"
  2628. ]
  2629. },
  2630. "GoogleSearchResults": {
  2631. "display_name": "GoogleSearchResults",
  2632. "description": "Google搜索的封装。在需要回答有关当前事件的问题时很有用。输入应为搜索查询。输出是查询结果的JSON数组。",
  2633. "template": {
  2634. "api_wrapper": {
  2635. "display_name": "API封装"
  2636. },
  2637. "args_schema": {
  2638. "display_name": "参数模式"
  2639. }
  2640. },
  2641. "base_classes": [
  2642. "Tool",
  2643. "BaseTool",
  2644. "GoogleSearchResults",
  2645. "BaseTool"
  2646. ]
  2647. },
  2648. "GoogleSearchRun": {
  2649. "display_name": "GoogleSearchRun",
  2650. "description": "Google搜索的封装。在需要回答有关当前事件的问题时很有用。输入应为搜索查询。",
  2651. "template": {
  2652. "api_wrapper": {
  2653. "display_name": "API封装"
  2654. },
  2655. "args_schema": {
  2656. "display_name": "参数模式"
  2657. }
  2658. },
  2659. "base_classes": [
  2660. "Tool",
  2661. "BaseTool",
  2662. "GoogleSearchRun",
  2663. "BaseTool"
  2664. ]
  2665. },
  2666. "InfoSQLDatabaseTool": {
  2667. "display_name": "InfoSQLDatabaseTool",
  2668. "description": "此工具的输入是表的逗号分隔列表,输出是这些表的模式和示例行。\n\n 示例输入:'table1, table2, table3'",
  2669. "template": {
  2670. "db": {
  2671. "display_name": "数据库"
  2672. },
  2673. "args_schema": {
  2674. "display_name": "参数模式"
  2675. }
  2676. },
  2677. "base_classes": [
  2678. "Tool",
  2679. "BaseTool",
  2680. "InfoSQLDatabaseTool",
  2681. "BaseTool",
  2682. "BaseSQLDatabaseTool"
  2683. ]
  2684. },
  2685. "JsonGetValueTool": {
  2686. "display_name": "JsonGetValueTool",
  2687. "description": "可用于查看给定路径上的字符串格式值。\n在调用之前,您应确保此路径存在。\n输入是Python语法中字典路径的文本表示形式(例如data[\"key1\"][0][\"key2\"])。",
  2688. "template": {
  2689. "spec": {
  2690. "display_name": "规范"
  2691. },
  2692. "args_schema": {
  2693. "display_name": "参数模式"
  2694. }
  2695. },
  2696. "base_classes": [
  2697. "Tool",
  2698. "BaseTool",
  2699. "JsonGetValueTool",
  2700. "BaseTool"
  2701. ]
  2702. },
  2703. "JsonListKeysTool": {
  2704. "display_name": "JsonListKeysTool",
  2705. "description": "可用于查看给定路径上的字符串格式值。\n在调用之前,您应确保此路径存在。\n输入是Python语法中字典路径的文本表示形式(例如data[\"key1\"][0][\"key2\"])。",
  2706. "template": {
  2707. "spec": {
  2708. "display_name": "规范"
  2709. },
  2710. "args_schema": {
  2711. "display_name": "参数模式"
  2712. }
  2713. },
  2714. "base_classes": [
  2715. "Tool",
  2716. "BaseTool",
  2717. "JsonListKeysTool",
  2718. "BaseTool"
  2719. ]
  2720. },
  2721. "JsonSpec": {
  2722. "display_name": "JsonSpec",
  2723. "template": {
  2724. "path": {
  2725. "display_name": "路径"
  2726. },
  2727. "args_schema": {
  2728. "display_name": "参数模式"
  2729. },
  2730. "max_value_length": {
  2731. "display_name": "最大值长度"
  2732. }
  2733. },
  2734. "base_classes": [
  2735. "Tool",
  2736. "BaseTool",
  2737. "JsonSpec"
  2738. ]
  2739. },
  2740. "ListSQLDatabaseTool": {
  2741. "display_name": "ListSQLDatabaseTool",
  2742. "description": "输入为空字符串,输出是数据库中表的逗号分隔列表。",
  2743. "template": {
  2744. "db": {
  2745. "display_name": "数据库"
  2746. },
  2747. "args_schema": {
  2748. "display_name": "参数模式"
  2749. }
  2750. },
  2751. "base_classes": [
  2752. "Tool",
  2753. "BaseTool",
  2754. "ListSQLDatabaseTool",
  2755. "BaseTool",
  2756. "BaseSQLDatabaseTool"
  2757. ]
  2758. },
  2759. "News API": {
  2760. "display_name": "News API",
  2761. "description": "在您想要获取有关当前新闻头条的信息时使用。输入应为此API可以回答的自然语言中的问题。",
  2762. "template": {
  2763. "llm": {
  2764. "display_name": "llm"
  2765. },
  2766. "args_schema": {
  2767. "display_name": "参数模式"
  2768. },
  2769. "news_api_key": {
  2770. "display_name": "新闻API密钥"
  2771. }
  2772. },
  2773. "base_classes": [
  2774. "Tool",
  2775. "BaseTool"
  2776. ]
  2777. },
  2778. "PAL-MATH": {
  2779. "display_name": "PAL-MATH",
  2780. "description": "一个非常擅长解决复杂数学问题的语言模型。输入应为完全用文字表达的复杂数学问题。",
  2781. "template": {
  2782. "llm": {
  2783. "display_name": "llm"
  2784. },
  2785. "args_schema": {
  2786. "display_name": "参数模式"
  2787. }
  2788. },
  2789. "base_classes": [
  2790. "Tool",
  2791. "BaseTool"
  2792. ]
  2793. },
  2794. "Podcast API": {
  2795. "display_name": "Podcast API",
  2796. "description": "使用Listen Notes Podcast API搜索所有播客或剧集。输入应为此API可以回答的自然语言中的问题。",
  2797. "template": {
  2798. "llm": {
  2799. "display_name": "llm"
  2800. },
  2801. "args_schema": {
  2802. "display_name": "参数模式"
  2803. },
  2804. "listen_api_key": {
  2805. "display_name": "Listen API密钥"
  2806. }
  2807. },
  2808. "base_classes": [
  2809. "Tool",
  2810. "BaseTool"
  2811. ]
  2812. },
  2813. "PythonAstREPLTool": {
  2814. "display_name": "PythonAstREPLTool",
  2815. "description": "一个Python shell。使用它来执行Python命令。输入应为有效的Python命令。在使用此工具时,有时输出会被缩写 - 在在答案中使用之前,请确保它看起来不是缩写的。",
  2816. "template": {
  2817. "args_schema": {
  2818. "display_name": "参数模式"
  2819. }
  2820. },
  2821. "base_classes": [
  2822. "Tool",
  2823. "BaseTool",
  2824. "PythonAstREPLTool",
  2825. "BaseTool"
  2826. ]
  2827. },
  2828. "PythonFunction": {
  2829. "display_name": "PythonFunction",
  2830. "description": "要执行的Python函数。",
  2831. "template": {
  2832. "code": {
  2833. "display_name": "代码"
  2834. }
  2835. },
  2836. "base_classes": [
  2837. "function"
  2838. ]
  2839. },
  2840. "PythonFunctionTool": {
  2841. "display_name": "PythonAstREPLTool",
  2842. "description": "要执行的Python函数。",
  2843. "template": {
  2844. "code": {
  2845. "display_name": "代码"
  2846. },
  2847. "description": {
  2848. "display_name": "描述"
  2849. },
  2850. "name": {
  2851. "display_name": "名称"
  2852. },
  2853. "return_direct": {
  2854. "display_name": "直接返回"
  2855. }
  2856. },
  2857. "base_classes": [
  2858. "BaseTool",
  2859. "Tool"
  2860. ]
  2861. },
  2862. "PythonREPLTool": {
  2863. "display_name": "PythonREPLTool",
  2864. "description": "一个Python shell。使用它来执行Python命令。输入应为有效的Python命令。如果要查看值的输出,应使用`print(...)`将其打印出来。",
  2865. "template": {
  2866. "args_schema": {
  2867. "display_name": "参数模式"
  2868. }
  2869. },
  2870. "base_classes": [
  2871. "Tool",
  2872. "BaseTool",
  2873. "PythonREPLTool",
  2874. "BaseTool"
  2875. ]
  2876. },
  2877. "QuerySQLDataBaseTool": {
  2878. "display_name": "PythonREPLTool",
  2879. "description": "此工具的输入是详细而正确的SQL查询,输出是来自数据库的结果。\n如果查询不正确,将返回错误消息。\n如果返回错误,请重新编写查询,检查查询,然后重试。",
  2880. "template": {
  2881. "db": {
  2882. "display_name": "数据库"
  2883. },
  2884. "args_schema": {
  2885. "display_name": "参数模式"
  2886. }
  2887. },
  2888. "base_classes": [
  2889. "Tool",
  2890. "BaseTool",
  2891. "QuerySQLDataBaseTool",
  2892. "BaseTool",
  2893. "BaseSQLDatabaseTool"
  2894. ]
  2895. },
  2896. "RequestsDeleteTool": {
  2897. "display_name": "RequestsDeleteTool",
  2898. "description": "互联网门户。在需要向URL发出DELETE请求时使用。输入应为特定的URL,输出将是DELETE请求的文本响应。",
  2899. "template": {
  2900. "requests_wrapper": {
  2901. "display_name": "请求封装"
  2902. },
  2903. "args_schema": {
  2904. "display_name": "参数模式"
  2905. }
  2906. },
  2907. "base_classes": [
  2908. "Tool",
  2909. "BaseTool",
  2910. "RequestsDeleteTool",
  2911. "BaseRequestsTool",
  2912. "BaseTool"
  2913. ]
  2914. },
  2915. "RequestsGetTool": {
  2916. "display_name": "RequestsGetTool",
  2917. "description": "互联网门户。在需要从网站获取特定内容时使用。输入应为URL(即https://www.google.com)。输出将是GET请求的文本响应。",
  2918. "template": {
  2919. "requests_wrapper": {
  2920. "display_name": "请求封装"
  2921. },
  2922. "args_schema": {
  2923. "display_name": "参数模式"
  2924. }
  2925. },
  2926. "base_classes": [
  2927. "Tool",
  2928. "BaseTool",
  2929. "RequestsGetTool",
  2930. "BaseRequestsTool",
  2931. "BaseTool"
  2932. ]
  2933. },
  2934. "RequestsPatchTool": {
  2935. "display_name": "RequestsPatchTool",
  2936. "description": "在想要对网站进行PATCH时使用。\n输入应为具有两个键的json字符串:\"url\"和\"data\"。\n\"url\"的值应为字符串,\"data\"的值应为要PATCH到url的键值对字典。\n务必始终在json字符串中使用双引号。\n输出将是PATCH请求的文本响应。\n",
  2937. "template": {
  2938. "requests_wrapper": {
  2939. "display_name": "请求封装"
  2940. },
  2941. "args_schema": {
  2942. "display_name": "参数模式"
  2943. }
  2944. },
  2945. "base_classes": [
  2946. "Tool",
  2947. "BaseTool",
  2948. "BaseRequestsTool",
  2949. "BaseTool",
  2950. "RequestsPatchTool"
  2951. ]
  2952. },
  2953. "RequestsPostTool": {
  2954. "display_name": "RequestsPostTool",
  2955. "description": "在想要对网站进行POST时使用。\n输入应为具有两个键的json字符串:\"url\"和\"data\"。\n\"url\"的值应为字符串,\"data\"的值应为要POST到url的键值对字典。\n务必始终在json字符串中使用双引号。\n输出将是POST请求的文本响应。\n",
  2956. "template": {
  2957. "requests_wrapper": {
  2958. "display_name": "请求封装"
  2959. },
  2960. "args_schema": {
  2961. "display_name": "参数模式"
  2962. }
  2963. },
  2964. "base_classes": [
  2965. "Tool",
  2966. "BaseTool",
  2967. "RequestsPostTool",
  2968. "BaseRequestsTool",
  2969. "BaseTool"
  2970. ]
  2971. },
  2972. "RequestsPutTool": {
  2973. "display_name": "RequestsPutTool",
  2974. "description": "在需要对网站进行PUT请求时使用此工具。\n输入应为包含两个键的JSON字符串:\"url\"和\"data\"。\n\"url\"的值应为字符串,\"data\"的值应为要PUT到URL的键值对字典。\n在JSON字符串中始终要小心使用双引号括起字符串。\n输出将是PUT请求的文本响应。",
  2975. "template": {
  2976. "requests_wrapper": {
  2977. "display_name": "请求封装"
  2978. },
  2979. "args_schema": {
  2980. "display_name": "参数模式"
  2981. }
  2982. },
  2983. "base_classes": [
  2984. "Tool",
  2985. "BaseTool",
  2986. "BaseRequestsTool",
  2987. "BaseTool",
  2988. "RequestsPutTool"
  2989. ]
  2990. },
  2991. "Search": {
  2992. "display_name": "搜索",
  2993. "description": "一个搜索引擎。在需要回答有关当前事件的问题时非常有用。输入应为搜索查询。",
  2994. "template": {
  2995. "args_schema": {
  2996. "display_name": "参数模式"
  2997. },
  2998. "serpapi_api_key": {
  2999. "display_name": "serpapi_api_key"
  3000. }
  3001. },
  3002. "base_classes": [
  3003. "Tool",
  3004. "BaseTool"
  3005. ]
  3006. },
  3007. "TMDB API": {
  3008. "display_name": "TMDB API",
  3009. "description": "在您想要从电影数据库获取信息时非常有用。输入应为此API可以回答的自然语言问题。",
  3010. "template": {
  3011. "llm": {
  3012. "display_name": "llm"
  3013. },
  3014. "args_schema": {
  3015. "display_name": "参数模式"
  3016. },
  3017. "tmdb_bearer_token": {
  3018. "display_name": "tmdb_bearer_token"
  3019. }
  3020. },
  3021. "base_classes": [
  3022. "Tool",
  3023. "BaseTool"
  3024. ]
  3025. },
  3026. "Tool": {
  3027. "display_name": "工具",
  3028. "description": "将链、代理或函数转换为工具。",
  3029. "template": {
  3030. "func": {
  3031. "display_name": "函数"
  3032. },
  3033. "args_schema": {
  3034. "display_name": "参数模式"
  3035. },
  3036. "description": {
  3037. "display_name": "描述"
  3038. },
  3039. "name": {
  3040. "display_name": "名称"
  3041. },
  3042. "return_direct": {
  3043. "display_name": "直接返回"
  3044. }
  3045. },
  3046. "base_classes": [
  3047. "Tool",
  3048. "BaseTool"
  3049. ]
  3050. },
  3051. "WikipediaQueryRun": {
  3052. "display_name": "WikipediaQueryRun",
  3053. "description": "围绕维基百科的包装器。在需要回答有关人物、地点、公司、事实、历史事件或其他主题的一般问题时非常有用。输入应为搜索查询。",
  3054. "template": {
  3055. "api_wrapper": {
  3056. "display_name": "API封装"
  3057. },
  3058. "args_schema": {
  3059. "display_name": "参数模式"
  3060. }
  3061. },
  3062. "base_classes": [
  3063. "Tool",
  3064. "BaseTool",
  3065. "WikipediaQueryRun",
  3066. "BaseTool"
  3067. ]
  3068. },
  3069. "WolframAlphaQueryRun": {
  3070. "display_name": "WolframAlphaQueryRun",
  3071. "description": "围绕沃尔夫拉姆阿尔法的包装器。在需要回答有关数学、科学、技术、文化、社会和日常生活的问题时非常有用。输入应为搜索查询。",
  3072. "template": {
  3073. "api_wrapper": {
  3074. "display_name": "API封装"
  3075. },
  3076. "args_schema": {
  3077. "display_name": "参数模式"
  3078. }
  3079. },
  3080. "base_classes": [
  3081. "Tool",
  3082. "BaseTool",
  3083. "WolframAlphaQueryRun",
  3084. "BaseTool"
  3085. ]
  3086. }
  3087. },
  3088. "utilities": {
  3089. "BingSearchAPIWrapper": {
  3090. "display_name": "BingSearchAPIWrapper",
  3091. "description": "Bing Search API的封装器。",
  3092. "template": {
  3093. "bing_search_url": {
  3094. "display_name": "必应搜索 URL"
  3095. },
  3096. "bing_subscription_key": {
  3097. "display_name": "必应订阅密钥"
  3098. }
  3099. },
  3100. "base_classes": [
  3101. "BingSearchAPIWrapper"
  3102. ]
  3103. },
  3104. "GoogleSearchAPIWrapper": {
  3105. "display_name": "GoogleSearchAPIWrapper",
  3106. "description": "Google搜索API的封装器。",
  3107. "template": {
  3108. "google_api_key": {
  3109. "display_name": "Google API密钥"
  3110. }
  3111. },
  3112. "base_classes": [
  3113. "GoogleSearchAPIWrapper"
  3114. ]
  3115. },
  3116. "GoogleSerperAPIWrapper": {
  3117. "display_name": "GoogleSerperAPIWrapper",
  3118. "description": "围绕 Serper.dev Google搜索API的封装器。",
  3119. "template": {
  3120. "result_key_for_type": {
  3121. "display_name": "类型的结果键"
  3122. },
  3123. "serper_api_key": {
  3124. "display_name": "Serper API密钥"
  3125. }
  3126. },
  3127. "base_classes": [
  3128. "GoogleSerperAPIWrapper"
  3129. ]
  3130. },
  3131. "SearxSearchWrapper": {
  3132. "display_name": "SearxSearchWrapper",
  3133. "description": "Searx API的封装器。",
  3134. "template": {
  3135. "headers": {
  3136. "display_name": "标头"
  3137. }
  3138. },
  3139. "base_classes": [
  3140. "SearxSearchWrapper"
  3141. ]
  3142. },
  3143. "SerpAPIWrapper": {
  3144. "display_name": "SerpAPIWrapper",
  3145. "description": "围绕 SerpAPI 的封装器。",
  3146. "template": {
  3147. "serpapi_api_key": {
  3148. "display_name": "SerpAPI API密钥"
  3149. }
  3150. },
  3151. "base_classes": [
  3152. "SerpAPIWrapper"
  3153. ]
  3154. },
  3155. "WikipediaAPIWrapper": {
  3156. "display_name": "WikipediaAPIWrapper",
  3157. "description": "围绕 WikipediaAPI 的封装器。",
  3158. "base_classes": [
  3159. "WikipediaAPIWrapper"
  3160. ]
  3161. },
  3162. "WolframAlphaAPIWrapper": {
  3163. "display_name": "WolframAlphaAPIWrapper",
  3164. "description": "Wolfram Alpha的封装器。",
  3165. "base_classes": [
  3166. "WolframAlphaAPIWrapper"
  3167. ]
  3168. }
  3169. },
  3170. "vectorstores": {
  3171. "Chroma": {
  3172. "display_name": "Chroma",
  3173. "description": "从原始文档创建 Chroma 向量存储。",
  3174. "template": {
  3175. "documents": {
  3176. "display_name": "文档"
  3177. },
  3178. "embedding": {
  3179. "display_name": "嵌入"
  3180. },
  3181. "collection_name": {
  3182. "display_name": "集合名称"
  3183. },
  3184. "persist": {
  3185. "display_name": "持久化"
  3186. },
  3187. "persist_directory": {
  3188. "display_name": "持久化目录"
  3189. }
  3190. },
  3191. "base_classes": [
  3192. "Chroma",
  3193. "VectorStore",
  3194. "BaseRetriever",
  3195. "VectorStoreRetriever"
  3196. ]
  3197. },
  3198. "ElasticKeywordsSearch": {
  3199. "display_name": "ElasticKeywordsSearch",
  3200. "description": "从原始文档构建 ElasticKeywordsSearch 包装器。",
  3201. "template": {
  3202. "documents": {
  3203. "display_name": "文档"
  3204. },
  3205. "llm": {
  3206. "display_name": "LLM"
  3207. },
  3208. "prompt": {
  3209. "display_name": "提示"
  3210. },
  3211. "elasticsearch_url": {
  3212. "display_name": "ES 连接 URL"
  3213. },
  3214. "index_name": {
  3215. "display_name": "索引名称"
  3216. },
  3217. "ssl_verify": {
  3218. "display_name": "SSL 验证"
  3219. }
  3220. },
  3221. "base_classes": [
  3222. "ElasticKeywordsSearch",
  3223. "VectorStore",
  3224. "BaseRetriever",
  3225. "VectorStoreRetriever"
  3226. ]
  3227. },
  3228. "FAISS": {
  3229. "display_name": "FAISS",
  3230. "description": "从原始文档构建 FAISS 包装器。",
  3231. "template": {
  3232. "documents": {
  3233. "display_name": "文档"
  3234. },
  3235. "embedding": {
  3236. "display_name": "嵌入"
  3237. },
  3238. "folder_path": {
  3239. "display_name": "本地路径"
  3240. },
  3241. "index_name": {
  3242. "display_name": "索引名称"
  3243. }
  3244. },
  3245. "base_classes": [
  3246. "FAISS",
  3247. "VectorStore",
  3248. "BaseRetriever",
  3249. "VectorStoreRetriever"
  3250. ]
  3251. },
  3252. "Milvus": {
  3253. "display_name": "Milvus",
  3254. "description": "创建 Milvus 集合,使用 HNSW 进行索引并插入数据。",
  3255. "template": {
  3256. "documents": {
  3257. "display_name": "文档"
  3258. },
  3259. "embedding": {
  3260. "display_name": "嵌入"
  3261. },
  3262. "collection_name": {
  3263. "display_name": "集合名称"
  3264. },
  3265. "connection_args": {
  3266. "display_name": "连接参数"
  3267. }
  3268. },
  3269. "base_classes": [
  3270. "Milvus",
  3271. "VectorStore",
  3272. "BaseRetriever",
  3273. "VectorStoreRetriever"
  3274. ]
  3275. },
  3276. "MongoDBAtlasVectorSearch": {
  3277. "display_name": "MongoDB Atlas",
  3278. "description": "创建 Milvus 集合,使用 HNSW 进行索引并插入数据。",
  3279. "template": {
  3280. "documents": {
  3281. "display_name": "文档"
  3282. },
  3283. "embedding": {
  3284. "display_name": "嵌入"
  3285. },
  3286. "collection_name": {
  3287. "display_name": "集合名称"
  3288. },
  3289. "db_name": {
  3290. "display_name": "数据库名称"
  3291. },
  3292. "index_name": {
  3293. "display_name": "索引名称"
  3294. },
  3295. "mongodb_atlas_cluster_uri": {
  3296. "display_name": "MongoDB Atlas 集群 URI"
  3297. }
  3298. },
  3299. "base_classes": [
  3300. "MongoDBAtlasVectorSearch",
  3301. "VectorStore",
  3302. "BaseRetriever",
  3303. "VectorStoreRetriever"
  3304. ]
  3305. },
  3306. "Pinecone": {
  3307. "display_name": "Pinecone",
  3308. "description": "从原始文档构建 Pinecone 包装器。",
  3309. "template": {
  3310. "documents": {
  3311. "display_name": "文档"
  3312. },
  3313. "embedding": {
  3314. "display_name": "嵌入"
  3315. },
  3316. "index_name": {
  3317. "display_name": "索引名称"
  3318. },
  3319. "namespace": {
  3320. "display_name": "命名空间"
  3321. }
  3322. },
  3323. "base_classes": [
  3324. "Pinecone",
  3325. "VectorStore",
  3326. "BaseRetriever",
  3327. "VectorStoreRetriever"
  3328. ]
  3329. },
  3330. "Qdrant": {
  3331. "display_name": "Qdrant",
  3332. "description": "从文本列表构建 Qdrant 包装器。",
  3333. "template": {
  3334. "documents": {
  3335. "display_name": "文档"
  3336. },
  3337. "embedding": {
  3338. "display_name": "嵌入"
  3339. },
  3340. "api_key": {
  3341. "display_name": "API 密钥"
  3342. },
  3343. "collection_name": {
  3344. "display_name": "集合名称"
  3345. },
  3346. "location": {
  3347. "display_name": "位置"
  3348. }
  3349. },
  3350. "base_classes": [
  3351. "Qdrant",
  3352. "VectorStore",
  3353. "BaseRetriever",
  3354. "VectorStoreRetriever"
  3355. ]
  3356. },
  3357. "SupabaseVectorStore": {
  3358. "display_name": "Supabase",
  3359. "description": "从文本和嵌入初始化 VectorStore 的 Supabase 包装器。",
  3360. "template": {
  3361. "documents": {
  3362. "display_name": "文档"
  3363. },
  3364. "embedding": {
  3365. "display_name": "嵌入"
  3366. },
  3367. "query_name": {
  3368. "display_name": "查询名称"
  3369. },
  3370. "supabase_service_key": {
  3371. "display_name": "Supabase 服务密钥"
  3372. },
  3373. "supabase_url": {
  3374. "display_name": "Supabase URL"
  3375. },
  3376. "table_name": {
  3377. "display_name": "表名称"
  3378. }
  3379. },
  3380. "base_classes": [
  3381. "SupabaseVectorStore",
  3382. "VectorStore",
  3383. "BaseRetriever",
  3384. "VectorStoreRetriever"
  3385. ]
  3386. },
  3387. "Weaviate": {
  3388. "display_name": "Weaviate",
  3389. "description": "从原始文档构建 Weaviate 包装器。",
  3390. "template": {
  3391. "documents": {
  3392. "display_name": "文档"
  3393. },
  3394. "embedding": {
  3395. "display_name": "嵌入"
  3396. },
  3397. "weaviate_url": {
  3398. "display_name": "Weaviate URL"
  3399. }
  3400. },
  3401. "base_classes": [
  3402. "Weaviate",
  3403. "VectorStore",
  3404. "BaseRetriever",
  3405. "VectorStoreRetriever"
  3406. ]
  3407. }
  3408. },
  3409. "wrappers": {
  3410. "SQLDatabase": {
  3411. "display_name": "SQLDatabase",
  3412. "description": "从 URI 构建一个 SQLAlchemy 引擎。",
  3413. "template": {
  3414. "database_uri": {
  3415. "display_name": "数据库 URI"
  3416. }
  3417. },
  3418. "base_classes": [
  3419. "SQLDatabase",
  3420. "function"
  3421. ]
  3422. },
  3423. "TextRequestsWrapper": {
  3424. "display_name": "TextRequestsWrapper",
  3425. "description": "对 requests 库的轻量级封装。",
  3426. "template": {
  3427. "headers": {
  3428. "display_name": "标头"
  3429. }
  3430. },
  3431. "base_classes": [
  3432. "TextRequestsWrapper"
  3433. ]
  3434. }
  3435. }
  3436. }