Feat: Add documents limitation (#2662)

web/i18n/en-US/billing.ts

@@ -32,6 +32,7 @@ const translation = {
     vectorSpace: 'Vector Space',
     vectorSpaceBillingTooltip: 'Each 1MB can store about 1.2million characters of vectorized data(estimated using OpenAI Embeddings, varies across models).',
     vectorSpaceTooltip: 'Vector Space is the long-term memory system required for LLMs  to comprehend your data.',
+    documentsUploadQuota: 'Documents Upload Quota',
     documentProcessingPriority: 'Document Processing Priority',
     documentProcessingPriorityTip: 'For higher document processing priority, please upgrade your plan.',
     documentProcessingPriorityUpgrade: 'Process more data with higher accuracy at faster speeds.',
@@ -56,6 +57,7 @@ const translation = {
       dedicatedAPISupport: 'Dedicated API support',
       customIntegration: 'Custom integration and support',
       ragAPIRequest: 'RAG API Requests',
+      bulkUpload: 'Bulk upload documents',
       agentMode: 'Agent Mode',
       workflow: 'Workflow',
     },

web/i18n/zh-Hans/billing.ts

@@ -32,6 +32,7 @@ const translation = {
     vectorSpace: '向量空间',
     vectorSpaceTooltip: '向量空间是 LLMs 理解您的数据所需的长期记忆系统。',
     vectorSpaceBillingTooltip: '向量存储是将知识库向量化处理后为让 LLMs 理解数据而使用的长期记忆存储，1MB 大约能满足1.2 million character 的向量化后数据存储（以 OpenAI Embedding 模型估算，不同模型计算方式有差异）。在向量化过程中，实际的压缩或尺寸减小取决于内容的复杂性和冗余性。',
+    documentsUploadQuota: '文档上传配额',
     documentProcessingPriority: '文档处理优先级',
     documentProcessingPriorityTip: '如需更高的文档处理优先级，请升级您的套餐',
     documentProcessingPriorityUpgrade: '以更快的速度、更高的精度处理更多的数据。',
@@ -56,6 +57,7 @@ const translation = {
       dedicatedAPISupport: '专用 API 支持',
       customIntegration: '自定义集成和支持',
       ragAPIRequest: 'RAG API 请求',
+      bulkUpload: '批量上传文档',
       agentMode: '代理模式',
       workflow: '工作流',
     },