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Dallas98
254
frontend/src/mock/knowledgeBase.tsx
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254
frontend/src/mock/knowledgeBase.tsx
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export const mockChunks = Array.from({ length: 23 }, (_, i) => ({
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id: i + 1,
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content: `这是第 ${
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i + 1
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} 个文档分块的内容示例。在实际应用中，这里会显示从原始文档中提取和分割的具体文本内容。用户可以在这里查看和编辑分块的内容，确保知识库的质量和准确性。这个分块包含了重要的业务信息和技术细节，需要仔细维护以确保检索的准确性。`,
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position: i + 1,
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tokens: Math.floor(Math.random() * 200) + 100,
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embedding: Array.from({ length: 1536 }, () => Math.random() - 0.5),
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similarity: (Math.random() * 0.3 + 0.7).toFixed(3),
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createdAt: "2024-01-22 10:35",
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updatedAt: "2024-01-22 10:35",
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vectorId: `vec_${i + 1}_${Math.random().toString(36).substr(2, 9)}`,
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sliceOperator: ["semantic-split", "paragraph-split", "table-extract"][
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Math.floor(Math.random() * 3)
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],
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parentChunkId: i > 0 ? Math.floor(Math.random() * i) + 1 : undefined,
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metadata: {
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source: "API文档.pdf",
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page: Math.floor(i / 5) + 1,
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section: `第${Math.floor(i / 3) + 1}章`,
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},
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}));
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export const mockQAPairs = [
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{
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id: 1,
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question: "什么是API文档的主要用途？",
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answer:
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"API文档的主要用途是为开发者提供详细的接口说明，包括请求参数、响应格式和使用示例.",
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},
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{
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id: 2,
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question: "如何正确使用这个API？",
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answer:
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"使用API时需要先获取访问令牌，然后按照文档中的格式发送请求，注意处理错误响应.",
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},
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];
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export const sliceOperators: SliceOperator[] = [
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{
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id: "paragraph-split",
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name: "段落分割",
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description: "按段落自然分割文档",
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type: "text",
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icon: "📄",
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params: { minLength: 50, maxLength: 1000 },
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},
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{
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id: "sentence-split",
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name: "句子分割",
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description: "按句子边界分割文档",
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type: "text",
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icon: "📝",
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params: { maxSentences: 5, overlap: 1 },
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},
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{
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id: "semantic-split",
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name: "语义分割",
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description: "基于语义相似度智能分割",
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type: "semantic",
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icon: "🧠",
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params: { threshold: 0.7, windowSize: 3 },
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},
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{
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id: "length-split",
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name: "长度分割",
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description: "按固定字符长度分割",
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type: "text",
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icon: "📏",
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params: { chunkSize: 512, overlap: 50 },
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},
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{
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id: "structure-split",
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name: "结构化分割",
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description: "按文档结构（标题、章节）分割",
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type: "structure",
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icon: "🏗️",
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params: { preserveHeaders: true, minSectionLength: 100 },
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},
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{
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id: "table-extract",
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name: "表格提取",
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description: "提取并单独处理表格内容",
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type: "structure",
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icon: "📊",
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params: { includeHeaders: true, mergeRows: false },
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},
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{
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id: "code-extract",
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name: "代码提取",
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description: "识别并提取代码块",
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type: "custom",
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icon: "💻",
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params: {
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languages: ["python", "javascript", "sql"],
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preserveIndentation: true,
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},
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},
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{
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id: "qa-extract",
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name: "问答提取",
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description: "自动识别问答格式内容",
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type: "semantic",
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icon: "❓",
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params: { confidenceThreshold: 0.8, generateAnswers: true },
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},
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];
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export const vectorDatabases = [
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{
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id: "pinecone",
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name: "Pinecone",
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description: "云端向量数据库，高性能检索",
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},
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{
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id: "weaviate",
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name: "Weaviate",
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description: "开源向量数据库，支持多模态",
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},
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{ id: "qdrant", name: "Qdrant", description: "高性能向量搜索引擎" },
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{ id: "chroma", name: "ChromaDB", description: "轻量级向量数据库" },
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{ id: "milvus", name: "Milvus", description: "分布式向量数据库" },
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{ id: "faiss", name: "FAISS", description: "Facebook AI 相似性搜索库" },
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];
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export const mockKnowledgeBases: KnowledgeBase[] = [
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{
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id: 1,
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name: "产品技术文档库",
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description:
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"包含所有产品相关的技术文档和API说明，支持多种格式文档的智能解析和向量化处理",
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type: "unstructured",
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status: "ready",
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fileCount: 45,
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chunkCount: 1250,
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vectorCount: 1250,
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size: "2.3 GB",
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progress: 100,
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createdAt: "2024-01-15",
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lastUpdated: "2024-01-22",
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vectorDatabase: "pinecone",
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config: {
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embeddingModel: "text-embedding-3-large",
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llmModel: "gpt-4o",
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chunkSize: 512,
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overlap: 50,
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sliceMethod: "semantic",
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enableQA: true,
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vectorDimension: 1536,
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sliceOperators: ["semantic-split", "paragraph-split", "table-extract"],
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},
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files: [
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{
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id: 1,
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name: "API文档.pdf",
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type: "pdf",
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size: "2.5 MB",
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status: "completed",
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chunkCount: 156,
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progress: 100,
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uploadedAt: "2024-01-15",
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source: "upload",
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vectorizationStatus: "completed",
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},
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{
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id: 2,
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name: "用户手册.docx",
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type: "docx",
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size: "1.8 MB",
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status: "disabled",
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chunkCount: 89,
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progress: 65,
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uploadedAt: "2024-01-22",
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source: "dataset",
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datasetId: "dataset-1",
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vectorizationStatus: "failed",
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},
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],
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vectorizationHistory: [
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{
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id: 1,
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timestamp: "2024-01-22 14:30:00",
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operation: "create",
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fileId: 1,
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fileName: "API文档.pdf",
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chunksProcessed: 156,
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vectorsGenerated: 156,
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status: "success",
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duration: "2m 15s",
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config: {
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embeddingModel: "text-embedding-3-large",
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chunkSize: 512,
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sliceMethod: "semantic",
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},
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},
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{
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id: 2,
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timestamp: "2024-01-22 15:45:00",
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operation: "update",
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fileId: 2,
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fileName: "用户手册.docx",
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chunksProcessed: 89,
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vectorsGenerated: 0,
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status: "failed",
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duration: "0m 45s",
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config: {
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embeddingModel: "text-embedding-3-large",
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chunkSize: 512,
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sliceMethod: "semantic",
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},
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error: "向量化服务连接超时",
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},
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],
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},
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{
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id: 2,
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name: "FAQ结构化知识库",
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description: "客服常见问题的结构化问答对，支持快速检索和智能匹配",
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type: "structured",
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status: "vectorizing",
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fileCount: 12,
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chunkCount: 890,
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vectorCount: 750,
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size: "156 MB",
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progress: 75,
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createdAt: "2024-01-20",
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lastUpdated: "2024-01-23",
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vectorDatabase: "weaviate",
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config: {
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embeddingModel: "text-embedding-ada-002",
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chunkSize: 256,
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overlap: 0,
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sliceMethod: "paragraph",
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enableQA: false,
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vectorDimension: 1536,
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sliceOperators: ["qa-extract", "paragraph-split"],
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},
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files: [
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{
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id: 3,
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name: "FAQ模板.xlsx",
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type: "xlsx",
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size: "450 KB",
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status: "vectorizing",
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chunkCount: 234,
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progress: 75,
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uploadedAt: "2024-01-20",
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source: "upload",
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vectorizationStatus: "processing",
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},
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],
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vectorizationHistory: [],
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},
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];
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