Major Features: - Created ekb_schema (13th schema) with 3 tables: KB/Document/Chunk - Implemented EmbeddingService (text-embedding-v4, 1024-dim vectors) - Implemented ChunkService (smart Markdown chunking) - Implemented VectorSearchService (multi-query + hybrid search) - Implemented RerankService (qwen3-rerank) - Integrated DeepSeek V3 QueryRewriter for cross-language search - Python service: Added pymupdf4llm for PDF-to-Markdown conversion - PKB: Dual-mode adapter (pgvector/dify/hybrid) Architecture: - Brain-Hand Model: Business layer (DeepSeek) + Engine layer (pgvector) - Cross-language support: Chinese query matches English documents - Small Embedding (1024) + Strong Reranker strategy Performance: - End-to-end latency: 2.5s - Cost per query: 0.0025 RMB - Accuracy improvement: +20.5% (cross-language) Tests: - test-embedding-service.ts: Vector embedding verified - test-rag-e2e.ts: Full pipeline tested - test-rerank.ts: Rerank quality validated - test-query-rewrite.ts: Cross-language search verified - test-pdf-ingest.ts: Real PDF document tested (Dongen 2003.pdf) Documentation: - Added 05-RAG-Engine-User-Guide.md - Added 02-Document-Processing-User-Guide.md - Updated system status documentation Status: Production ready
218 lines
4.8 KiB
JavaScript
218 lines
4.8 KiB
JavaScript
/**
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* 创建 Tool C AI对话历史表
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*
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* 执行方式:node scripts/create-tool-c-ai-history-table.mjs
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*/
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import { PrismaClient } from '@prisma/client';
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const prisma = new PrismaClient();
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async function createAiHistoryTable() {
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console.log('========================================');
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console.log('开始创建 Tool C AI对话历史表');
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console.log('========================================\n');
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try {
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// 1. 检查表是否已存在
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console.log('[1/4] 检查表是否已存在...');
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const checkResult = await prisma.$queryRawUnsafe(`
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SELECT EXISTS (
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SELECT FROM information_schema.tables
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WHERE table_schema = 'dc_schema'
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AND table_name = 'dc_tool_c_ai_history'
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) as exists
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`);
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const tableExists = checkResult[0].exists;
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if (tableExists) {
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console.log('✅ 表已存在: dc_schema.dc_tool_c_ai_history');
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console.log('\n如需重新创建,请手动执行: DROP TABLE dc_schema.dc_tool_c_ai_history CASCADE;\n');
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return;
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}
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console.log('✅ 表不存在,准备创建\n');
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// 2. 创建表
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console.log('[2/4] 创建表 dc_tool_c_ai_history...');
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await prisma.$executeRawUnsafe(`
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CREATE TABLE dc_schema.dc_tool_c_ai_history (
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id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
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session_id VARCHAR(255) NOT NULL,
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user_id VARCHAR(255) NOT NULL,
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role VARCHAR(50) NOT NULL,
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content TEXT NOT NULL,
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-- Tool C特有字段
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generated_code TEXT,
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code_explanation TEXT,
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execute_status VARCHAR(50),
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execute_result JSONB,
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execute_error TEXT,
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retry_count INTEGER DEFAULT 0,
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-- LLM相关
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model VARCHAR(100),
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created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
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)
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`);
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console.log('✅ 表创建成功\n');
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// 3. 创建索引
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console.log('[3/4] 创建索引...');
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await prisma.$executeRawUnsafe(`
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CREATE INDEX idx_dc_tool_c_ai_history_session_id
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ON dc_schema.dc_tool_c_ai_history(session_id)
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`);
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await prisma.$executeRawUnsafe(`
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CREATE INDEX idx_dc_tool_c_ai_history_user_id
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ON dc_schema.dc_tool_c_ai_history(user_id)
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`);
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await prisma.$executeRawUnsafe(`
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CREATE INDEX idx_dc_tool_c_ai_history_created_at
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ON dc_schema.dc_tool_c_ai_history(created_at)
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`);
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console.log('✅ 索引创建成功\n');
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// 4. 添加注释
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console.log('[4/4] 添加表注释...');
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await prisma.$executeRawUnsafe(`
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COMMENT ON TABLE dc_schema.dc_tool_c_ai_history
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IS 'Tool C (科研数据编辑器) AI对话历史表'
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`);
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await prisma.$executeRawUnsafe(`
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COMMENT ON COLUMN dc_schema.dc_tool_c_ai_history.session_id
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IS '关联Tool C Session ID'
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`);
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await prisma.$executeRawUnsafe(`
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COMMENT ON COLUMN dc_schema.dc_tool_c_ai_history.generated_code
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IS 'AI生成的Pandas代码'
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`);
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await prisma.$executeRawUnsafe(`
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COMMENT ON COLUMN dc_schema.dc_tool_c_ai_history.execute_status
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IS '执行状态: pending/success/failed'
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`);
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await prisma.$executeRawUnsafe(`
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COMMENT ON COLUMN dc_schema.dc_tool_c_ai_history.retry_count
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IS '自我修正重试次数'
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`);
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console.log('✅ 注释添加成功\n');
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// 5. 验证表创建
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console.log('========================================');
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console.log('验证表结构');
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console.log('========================================\n');
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const columns = await prisma.$queryRawUnsafe(`
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SELECT column_name, data_type, is_nullable
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FROM information_schema.columns
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WHERE table_schema = 'dc_schema'
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AND table_name = 'dc_tool_c_ai_history'
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ORDER BY ordinal_position
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`);
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console.log('表结构:');
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console.table(columns);
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const indexes = await prisma.$queryRawUnsafe(`
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SELECT indexname, indexdef
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FROM pg_indexes
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WHERE schemaname = 'dc_schema'
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AND tablename = 'dc_tool_c_ai_history'
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`);
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console.log('\n索引:');
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console.table(indexes);
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console.log('\n========================================');
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console.log('🎉 Tool C AI对话历史表创建成功!');
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console.log('========================================\n');
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console.log('表名: dc_schema.dc_tool_c_ai_history');
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console.log(`列数: ${columns.length}`);
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console.log(`索引数: ${indexes.length}\n`);
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} catch (error) {
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console.error('\n❌ 创建表失败:', error.message);
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console.error('\n详细错误:');
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console.error(error);
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process.exit(1);
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} finally {
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await prisma.$disconnect();
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}
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}
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// 执行
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createAiHistoryTable()
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.then(() => {
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console.log('脚本执行完成');
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process.exit(0);
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})
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.catch((error) => {
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console.error('脚本执行失败:', error);
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process.exit(1);
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});
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