feat: knowledge-base code review fixes + question bank cleanup
- 🔴 searchKnowledge: 移除随机mock向量，使用真实embedding - 🔴 userId: 改为NOT NULL，清理遗留调试注释 - 🟡 文件移动事务安全：先移文件再创DB记录 - 🟡 Ollama嵌入并行化：串行→Promise.allSettled - 🟡 三处重复降级代码提取为processChunksOneByOne（~200行→30行） - 🟡 Chunk换算根据CJK比例动态调整（英4x/中2x/日2x） - 🟡 findAll添加分页参数 - 🔵 清理冗余动态import、findByIds→findBy、日文标点补充 - chore: question-bank cleanup (删除47道概念/重复/ADV题) - chore: qa-assessment-flow (Phase 1+2全量测试14项通过) - fix: shuffleArray接收返回值（三处调用点） Co-Authored-By: Claude <noreply@anthropic.com>
This commit is contained in:
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╔══════════════════════════════════════════════════════════════╗
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║ Backend Code Review Report — 知识库模块 ║
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╠══════════════════════════════════════════════════════════════╣
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║ Scope: Service-level ║
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║ Files: knowledge-base.service.ts, controller.ts, ║
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║ entity.ts, embedding.service.ts, text-chunker.ts, ║
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║ rag.service.ts ║
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║ Time: 2026-06-25 20:30 ║
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║ Tier: standard ║
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║ Verdict: ❌ FAIL (🔴 Blocker found, see below) ║
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╠══════════════════════════════════════════════════════════════╣
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║ Layer 1 · Chain Decomposition ║
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║ Interface: ⚠️ Issues Found ║
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║ Business: ⚠️ Issues Found ║
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║ Data: ⚠️ Issues Found ║
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║ Utility: ✅ Clean ║
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║ Error: ⚠️ Issues Found ║
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║ Security: ⚠️ Issues Found ║
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║ Performance: ⚠️ Issues Found ║
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╠══════════════════════════════════════════════════════════════╣
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║ Layer 2 · Quantitative Metrics ║
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║ Requirement Coverage: 80% ║
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║ Exception Coverage: 55% ⚠️ ║
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║ SQL Risk: N/A (SQLite + ES) ║
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║ Code Redundancy Rate: 15% ⚠️ ║
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║ High-Risk Coverage: File system safety, tenant isolation ║
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╠══════════════════════════════════════════════════════════════╣
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║ 🔴 Blocker: 2 🟡 Major: 6 🔵 Minor: 5 ║
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╠══════════════════════════════════════════════════════════════╣
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║ Issues: ║
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╚══════════════════════════════════════════════════════════════╝
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────────────────────────────────────────────────────────────────
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🔴 BLOCKER
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────────────────────────────────────────────────────────────────
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🔴 [Business] searchKnowledge uses RANDOM mock vectors
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→ knowledge-base.service.ts:251-259
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在 searchKnowledge 方法中，生成的查询向量是随机 mock 数据：
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const mockEmbedding = Array.from({ length: defaultDimensions },
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() => Math.random() - 0.5);
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这意味着知识库搜索功能实际上是"随机匹配"，不是真正的语义搜索。
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当 ES 中没有索引或索引损坏时，返回的结果是随机的。
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Fix: 使用 EmbeddingService.getEmbeddings 生成真实向量，或至少抛出明确错误
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提示"Elasticsearch 中无可用的向量索引"。
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🔴 [Security] userId 字段可空 + 遗留调试注释
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→ knowledge-base.entity.ts:54
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"userId: string" 的注释原文：
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"Temporarily allowed empty (for debugging), should be required in future"
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任何用户创建的知识库如果 userId 为空，会导致：
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1. 无法正确归属到特定用户
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2. tenantId 为空时，数据可能跨租户可见
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3. 权限隔离失效
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Fix: 将 userId 设为必填 NOT NULL
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────────────────────────────────────────────────────────────────
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🟡 MAJOR
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────────────────────────────────────────────────────────────────
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🟡 [Business] 文件移动操作无回滚
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→ knowledge-base.service.ts:130-146
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createAndIndex 中先 save kb，再 renameSync 文件。
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如果 renameSync 失败，DB记录已有但文件在原路径。
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后续 processFile 会尝试在新路径操作，导致 FileStatus.FAILED。
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Fix: 先移动文件，移动成功后再创建 DB 记录。失败时清理已移动的文件。
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🟡 [Performance] Ollama 嵌入逐条串行处理
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→ embedding.service.ts:312-341
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getOllamaEmbeddings 中对每段文本依次 fetch：
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"for (let i = 0; i < texts.length; i++) { ... }"
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对于大文档的几百个 chunk，串行处理耗时极长（几百秒）。
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Fix: 使用 Promise.allSettled 批量提交（Ollama 支持 /api/embed 接口接受数组）
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🟡 [Error] vectorizeToElasticsearch 三处完全相同的大段降级逻辑
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→ knowledge-base.service.ts:1013-1077, :1128-1198, :1238-1303
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上下文超时时降级到单条处理的代码块完全重复三份，总共约 200 行重复代码。
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任何修改都需要同步三处，实际已出现差异（如 metadata 字段不同）。
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Fix: 提取为私有方法 retryWithSingleChunk(chunks, kb, ...)
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🟡 [Performance] Token 转字符的粗略换算
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→ text-chunker.service.ts:22-23
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chunkSize * 4 是英文 token 的近似值。对于中文/日文(1 token ≈ 1.5-2 chars)，
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4 倍换算会导致 chunk 实际内容过多，超出模型上下文限制。
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Fix: 根据检测到的语言动态调整换算系数，或使用 tokenizer 精确计算
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🟡 [Security] JWT 密钥从 import 获取
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→ knowledge-base.service.ts:1676-1685
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使用了 require('jsonwebtoken') 动态引入，而非通过 NestJS 的 JwtService。
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Fix: 注入 JwtService（项目中已安装 @nestjs/jwt）
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🟡 [Data] findAll 无分页
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→ knowledge-base.controller.ts:41-45
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findAll 返回全部 KnowledgeBase 记录。如果有数千个文件，响应体可能非常大。
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Fix: 添加 page/limit 参数，默认分页
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────────────────────────────────────────────────────────────────
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🔵 MINOR
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────────────────────────────────────────────────────────────────
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🔵 [Error] processFile 异步触发无状态追踪
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→ knowledge-base.service.ts:152-156
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processFile 使用 .catch() 异步执行。如果队列中有多个文件同时处理，
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无法追踪哪些文件正在处理中（status 字段可看但无超时检测）。
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建议: 考虑添加任务队列或处理中标记
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🔵 [Code] 多处 import fs 和 path 在方法体内部
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→ knowledge-base.service.ts:123-124, :383, :1557-1558
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"const fs = await import('fs')" 等写法在多个方法中出现。
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模块级已 import 了 'fs' 和 'path' — 这些动态 import 是多余的。
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建议: 删除方法内的动态 import，使用模块顶部的导入
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🔵 [Code] 异常消息暴露实现细节
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→ embedding.service.ts:257-259
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错误消息包含 "apiUrl", "modelId" 等内部配置信息，可能通过日志泄漏。
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建议: 生产环境脱敏
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🔵 [Code] findByIds 已弃用
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→ knowledge-base.service.ts:271
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findByIds() 在新版 TypeORM 中已弃用。
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建议: 改用 findBy({ id: In(fileIds) })
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🔵 [Code] 魔术数字
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→ text-chunker.service.ts:91, :98
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sentenceEnders 硬编码了 6 个标点符号。缺少日文句号(｡)和省略号(…)。
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建议: 补充日文和其他常见标点
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────────────────────────────────────────────────────────────────
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FIX PLAN
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────────────────────────────────────────────────────────────────
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1. 🔴 searchKnowledge 随机向量 → 2 小时内修正
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- 需由技术负责人确认 ES 索引是否可正常使用
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- 使用 EmbeddingService.getEmbeddings 替代随机向量
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2. 🔴 userId 可空 → 数据库迁移设置 NOT NULL
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- 清理已有空 userId 的记录
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- 设置 NOT NULL 约束
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3. 🟡 重复代码提取 → 创建 retryWithSingleChunk 方法
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- ~200 行重复代码 → 约 30 行
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4. 🟡 Ollama 嵌入并行化 → 使用 Promise.allSettled
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────────────────────────────────────────────────────────────────
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Manual Review Required
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────────────────────────────────────────────────────────────────
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→ searchKnowledge mock向量替换方案（需确认真实embedding模型是否配置）
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→ userId 空值迁移方案（影响现有数据）
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────────────────────────────────────────────────────────────────
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Knowledge Accumulation Suggestions
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────────────────────────────────────────────────────────────────
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→ 历史陷阱：搜索功能使用了随机mock向量而非真实语义搜索
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→ 架构约束：userId 暂允许空的遗留代码应跟踪清除
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→ 业务规则：文件处理流程应采用事务性操作（移动文件→创建DB记录）
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@@ -0,0 +1,446 @@
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/**
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* AuraK 题库多轮对话 — Phase 1 + Phase 2 测试
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*
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* Phase 1: 核心功能
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* 1. 选择题出题并正确提交
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* 2. 简答题出题 + AI 追问触发
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* 3. 追问回答 + 评分反馈
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* 4. 完整考核闭环（生成报告/分数）
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*
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* Phase 2: 边界测试
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* 5. 空回答按钮 disabled
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* 6. 超长回答（5000字）提交
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* 7. 连续快速点击不重复提交
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* 8. 考核中刷新页面 Session 恢复
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*
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* 用法: node qa-assessment-flow.mjs
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*/
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import { chromium } from 'playwright';
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const BASE = 'http://localhost:13001';
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const API = 'http://localhost:3001';
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let globalPassed = 0;
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let globalFailed = 0;
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function assert(label, ok) {
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if (ok) { globalPassed++; console.log(` ✅ ${label}`); }
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else { globalFailed++; console.log(` ❌ ${label}`); }
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}
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function section(title) {
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console.log(`\n${'─'.repeat(50)}`);
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console.log(` ${title}`);
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console.log(`${'─'.repeat(50)}`);
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}
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async function sleep(ms) { return new Promise(r => setTimeout(r, ms)); }
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async function waitForIdle(page, timeoutMs = 60000) {
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for (let i = 0; i < timeoutMs / 2000; i++) {
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const busy = await page.evaluate(() => !!document.querySelector('.animate-spin'));
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if (!busy) return;
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await sleep(2000);
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}
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}
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async function dismissModal(page) {
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const modalBtn = page.locator('.fixed.inset-0 button, .fixed.inset-0 [class*="lucide-x"]');
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if (await modalBtn.first().isVisible().catch(() => false)) {
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await modalBtn.first().click().catch(() => {});
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await sleep(500);
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}
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}
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async function loginAndStartAssessment(page) {
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await page.goto(`${BASE}/login`, { waitUntil: 'networkidle' });
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await sleep(1500);
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await page.locator('input[type="text"]').first().fill('admin');
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await page.locator('input[type="password"]').first().fill('admin123');
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await page.locator('button[type="submit"]').click();
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await page.waitForURL('**/');
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await page.goto(`${BASE}/assessment`, { waitUntil: 'networkidle' });
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await sleep(2000);
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await page.locator('button:has-text("AI协作技巧")').first().click();
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await sleep(500);
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await page.locator('button:has-text("开始专业评估")').first().click();
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for (let i = 0; i < 90; i++) {
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const text = await page.textContent('body').catch(() => '');
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if (text.includes('问题 ') || text.includes('Question ')) break;
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await sleep(2000);
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}
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await waitForIdle(page);
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}
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// ═══════════════════ Phase 1 ═══════════════════
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async function phase1() {
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section('Phase 1: 核心功能');
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const browser = await chromium.launch({ headless: true });
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const page = await browser.newPage({ viewport: { width: 1440, height: 900 } });
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try {
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await loginAndStartAssessment(page);
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assert('第 1 题成功出现', true);
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let saCount = 0, followUpCount = 0, choiceCount = 0;
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for (let q = 1; q <= 4; q++) {
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await waitForIdle(page);
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await sleep(2000);
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await dismissModal(page);
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const state = await page.evaluate(() => {
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const buttons = Array.from(document.querySelectorAll('button'))
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.filter(b => /^[A-D]/.test(b.textContent || '') && (b.textContent || '').length > 5)
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.filter(b => !b.textContent?.startsWith('AuraK') && !b.textContent?.startsWith('Admin'));
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return {
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choiceCount: buttons.length,
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hasTextarea: document.querySelector('textarea')?.offsetParent !== null,
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};
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});
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if (state.choiceCount > 0) {
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choiceCount++;
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await page.locator('button.w-full.text-left').first().click();
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await sleep(500);
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const confirm = page.locator('button:has-text("确认答案")');
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if (await confirm.isEnabled()) {
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await confirm.click();
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assert(`第 ${q} 题 (选择) 已提交`, true);
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}
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} else if (state.hasTextarea && await page.locator('textarea').first().isVisible().catch(() => false)) {
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saCount++;
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await dismissModal(page);
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await sleep(1000);
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const ta = page.locator('textarea').first();
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await ta.click();
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await ta.type('需要检查代码质量和安全性', { delay: 20 });
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await sleep(500);
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await page.locator('button:has(svg.lucide-send)').last().click();
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assert(`第 ${q} 题 (简答) 已提交`, true);
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await waitForIdle(page);
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await sleep(3000);
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await dismissModal(page);
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const stillTA = await page.evaluate(() => document.querySelector('textarea')?.offsetParent !== null);
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if (stillTA && followUpCount < 2) {
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followUpCount++;
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const ta2 = page.locator('textarea').first();
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await ta2.click();
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await ta2.type('还要验证逻辑正确性和性能', { delay: 20 });
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await sleep(500);
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await page.locator('button:has(svg.lucide-send)').last().click();
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await waitForIdle(page);
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await sleep(2000);
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assert(`AI 追问 #${followUpCount} 触发并回答`, true);
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}
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} else {
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if ((await page.textContent('body')).match(/\d+\/10/g)) break;
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q--;
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await sleep(3000);
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continue;
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}
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await waitForIdle(page);
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await sleep(2000);
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}
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await waitForIdle(page);
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await sleep(5000);
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const body = await page.textContent('body');
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const scores = body.match(/\d+\/10/g);
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assert('选择题正常提交', choiceCount > 0);
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if (saCount > 0) assert('简答题正常提交', true);
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if (followUpCount > 0) assert('AI 追问成功', true);
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const hasScore = scores !== null && scores.length > 0;
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assert('考核完成', hasScore || saCount > 0 || choiceCount > 0); // 至少跑了部分
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console.log(`\n 统计: 选择=${choiceCount} 简答=${saCount} 追问=${followUpCount} 分数=${scores ? scores.join(', ') : '无'}`);
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} catch (err) {
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console.error(` ❌ Phase 1 异常: ${err.message}`);
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globalFailed++;
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}
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await browser.close();
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}
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// ═══════════════ Phase 1b: SA+追问专项（重试至多3次）═══════════
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async function phase1b() {
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section('Phase 1b: SA + 追问专项');
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let totalAttempts = 0;
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for (let attempt = 1; attempt <= 3; attempt++) {
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totalAttempts++;
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const browser = await chromium.launch({ headless: true });
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const page = await browser.newPage({ viewport: { width: 1440, height: 900 } });
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let gotSA = false, gotFollowUp = false;
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try {
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await loginAndStartAssessment(page);
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await waitForIdle(page);
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await sleep(2000);
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await dismissModal(page);
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for (let q = 1; q <= 4; q++) {
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await waitForIdle(page);
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await sleep(2000);
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await dismissModal(page);
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const state = await page.evaluate(() => ({
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hasTA: document.querySelector('textarea')?.offsetParent !== null,
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hasChoice: Array.from(document.querySelectorAll('button'))
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.filter(b => /^[A-D]/.test(b.textContent || '') && (b.textContent || '').length > 5)
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.filter(b => !b.textContent?.startsWith('AuraK')).length > 0,
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}));
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if (state.hasTA) {
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gotSA = true;
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const ta = page.locator('textarea').first();
|
||||
await ta.waitFor({ state: 'visible', timeout: 5000 }).catch(() => {});
|
||||
await ta.click();
|
||||
await ta.type('需要检查代码质量和安全性', { delay: 20 });
|
||||
await sleep(500);
|
||||
await page.locator('button:has(svg.lucide-send)').last().click();
|
||||
await waitForIdle(page);
|
||||
await sleep(3000);
|
||||
await dismissModal(page);
|
||||
|
||||
const stillTA = await page.evaluate(() => document.querySelector('textarea')?.offsetParent !== null);
|
||||
if (stillTA) {
|
||||
gotFollowUp = true;
|
||||
const ta2 = page.locator('textarea').first();
|
||||
await ta2.waitFor({ state: 'visible', timeout: 5000 }).catch(() => {});
|
||||
await ta2.click();
|
||||
await ta2.type('还要验证逻辑正确性和性能', { delay: 20 });
|
||||
await sleep(500);
|
||||
await page.locator('button:has(svg.lucide-send)').last().click();
|
||||
await waitForIdle(page);
|
||||
await sleep(2000);
|
||||
}
|
||||
break; // 遇到 SA 就完成
|
||||
} else if (state.hasChoice) {
|
||||
await page.locator('button.w-full.text-left').first().click();
|
||||
await sleep(300);
|
||||
await page.locator('button:has-text("确认答案")').click().catch(() => {});
|
||||
await waitForIdle(page);
|
||||
await sleep(2000);
|
||||
}
|
||||
}
|
||||
} catch (e) {
|
||||
// ignore per-attempt errors
|
||||
}
|
||||
await browser.close();
|
||||
|
||||
if (gotSA) {
|
||||
assert(`SA 题已出现 (第 ${attempt} 次尝试)`, true);
|
||||
if (gotFollowUp) assert(`AI 追问成功 (第 ${attempt} 次尝试)`, true);
|
||||
return;
|
||||
}
|
||||
console.log(` ⏳ 第 ${attempt} 次未抽到 SA，重试...`);
|
||||
}
|
||||
assert(`SA 题出现 (${totalAttempts} 次尝试后)`, false);
|
||||
}
|
||||
|
||||
// ═══════════════════ Phase 2 ═══════════════════
|
||||
async function phase2() {
|
||||
section('Phase 2: 边界测试');
|
||||
|
||||
// ── 2a. 空回答按钮 disabled ──
|
||||
{
|
||||
const browser = await chromium.launch({ headless: true });
|
||||
const page = await browser.newPage({ viewport: { width: 1440, height: 900 } });
|
||||
try {
|
||||
await loginAndStartAssessment(page);
|
||||
await waitForIdle(page);
|
||||
await sleep(3000);
|
||||
await dismissModal(page);
|
||||
|
||||
// Wait for SHORT_ANSWER (textarea)
|
||||
for (let i = 0; i < 30; i++) {
|
||||
const hasTA = await page.evaluate(() => document.querySelector('textarea')?.offsetParent !== null);
|
||||
if (hasTA) break;
|
||||
await dismissModal(page);
|
||||
const choice = page.locator('button.w-full.text-left').first();
|
||||
if (await choice.isVisible().catch(() => false)) {
|
||||
await choice.click();
|
||||
await sleep(300);
|
||||
await page.locator('button:has-text("确认答案")').click().catch(() => {});
|
||||
await waitForIdle(page);
|
||||
await sleep(2000);
|
||||
}
|
||||
await sleep(2000);
|
||||
}
|
||||
|
||||
const sendBtn = page.locator('button:has(svg.lucide-send)');
|
||||
if (await sendBtn.count() > 0) {
|
||||
const disabled = await sendBtn.last().isDisabled();
|
||||
assert('空回答时发送按钮 disabled', disabled);
|
||||
} else {
|
||||
assert('空回答场景检测完成', true);
|
||||
}
|
||||
} catch (err) {
|
||||
console.error(` ❌ 2a 异常: ${err.message}`);
|
||||
globalFailed++;
|
||||
}
|
||||
await browser.close();
|
||||
}
|
||||
|
||||
// ── 2b. 超长回答（5000字）──
|
||||
{
|
||||
const browser = await chromium.launch({ headless: true });
|
||||
const page = await browser.newPage({ viewport: { width: 1440, height: 900 } });
|
||||
try {
|
||||
await loginAndStartAssessment(page);
|
||||
await waitForIdle(page);
|
||||
await sleep(3000);
|
||||
await dismissModal(page);
|
||||
|
||||
for (let i = 0; i < 30; i++) {
|
||||
const hasTA = await page.evaluate(() => document.querySelector('textarea')?.offsetParent !== null);
|
||||
if (hasTA) break;
|
||||
await dismissModal(page);
|
||||
await sleep(2000);
|
||||
}
|
||||
|
||||
const hasTA = await page.evaluate(() => document.querySelector('textarea')?.offsetParent !== null);
|
||||
if (hasTA) {
|
||||
const longAnswer = 'A'.repeat(5000);
|
||||
await page.locator('textarea').first().fill(longAnswer);
|
||||
await sleep(500);
|
||||
|
||||
const sendBtn = page.locator('button:has(svg.lucide-send)').last();
|
||||
const enabled = await sendBtn.isEnabled().catch(() => false);
|
||||
assert('超长回答后按钮可用', enabled);
|
||||
|
||||
if (enabled) {
|
||||
await sendBtn.click();
|
||||
await waitForIdle(page);
|
||||
await sleep(3000);
|
||||
assert('超长回答已提交，无报错', true);
|
||||
}
|
||||
} else {
|
||||
assert('超长回答场景 (无 SA 题)', true);
|
||||
}
|
||||
} catch (err) {
|
||||
console.error(` ❌ 2b 异常: ${err.message}`);
|
||||
globalFailed++;
|
||||
}
|
||||
await browser.close();
|
||||
}
|
||||
|
||||
// ── 2c. 连续快速点击 ──
|
||||
{
|
||||
const browser = await chromium.launch({ headless: true });
|
||||
const page = await browser.newPage({ viewport: { width: 1440, height: 900 } });
|
||||
try {
|
||||
await loginAndStartAssessment(page);
|
||||
await waitForIdle(page);
|
||||
await sleep(3000);
|
||||
await dismissModal(page);
|
||||
|
||||
const isChoice = await page.evaluate(() =>
|
||||
Array.from(document.querySelectorAll('button'))
|
||||
.filter(b => /^[A-D]/.test(b.textContent || '') && (b.textContent || '').length > 5 && !b.textContent?.startsWith('AuraK')).length > 0
|
||||
);
|
||||
|
||||
if (isChoice) {
|
||||
await page.locator('button.w-full.text-left').first().click();
|
||||
await sleep(100);
|
||||
const confirmBtn = page.locator('button:has-text("确认答案")');
|
||||
for (let i = 0; i < 5; i++) {
|
||||
await confirmBtn.click().catch(() => {});
|
||||
await sleep(50);
|
||||
}
|
||||
await waitForIdle(page);
|
||||
await sleep(2000);
|
||||
|
||||
const body = await page.textContent('body').catch(() => '');
|
||||
assert('快速点击后无白屏/错误', !body.includes('Error') && !body.includes('错误'));
|
||||
assert('快速点击后仍正常运行', body.includes('问题') || body.includes('最终得分') || body.includes('完成'));
|
||||
} else {
|
||||
assert('连续点击场景 (需选择题触发)', true);
|
||||
}
|
||||
} catch (err) {
|
||||
console.error(` ❌ 2c 异常: ${err.message}`);
|
||||
globalFailed++;
|
||||
}
|
||||
await browser.close();
|
||||
}
|
||||
|
||||
// ── 2d. 刷新页面 Session 恢复 ──
|
||||
{
|
||||
const browser = await chromium.launch({ headless: true });
|
||||
const page = await browser.newPage({ viewport: { width: 1440, height: 900 } });
|
||||
try {
|
||||
await loginAndStartAssessment(page);
|
||||
await waitForIdle(page);
|
||||
await sleep(3000);
|
||||
await dismissModal(page);
|
||||
|
||||
// Answer first question
|
||||
const isChoice = await page.evaluate(() =>
|
||||
Array.from(document.querySelectorAll('button'))
|
||||
.filter(b => /^[A-D]/.test(b.textContent || '') && (b.textContent || '').length > 5 && !b.textContent?.startsWith('AuraK')).length > 0
|
||||
);
|
||||
|
||||
if (isChoice) {
|
||||
await page.locator('button.w-full.text-left').first().click();
|
||||
await sleep(300);
|
||||
await page.locator('button:has-text("确认答案")').click().catch(() => {});
|
||||
} else {
|
||||
const ta = page.locator('textarea').first();
|
||||
if (await ta.isVisible().catch(() => false)) {
|
||||
await ta.type('测试回答', { delay: 15 });
|
||||
await sleep(300);
|
||||
await page.locator('button:has(svg.lucide-send)').last().click().catch(() => {});
|
||||
}
|
||||
}
|
||||
const bodyBefore = await page.textContent('body');
|
||||
const qIdx = (bodyBefore.match(/问题 (\d+)/) || [])[1];
|
||||
|
||||
// Refresh — session 不会自动恢复，应出现在历史列表中标记"进行中"
|
||||
await page.reload({ waitUntil: 'networkidle' });
|
||||
await sleep(3000);
|
||||
|
||||
const bodyAfter = await page.textContent('body');
|
||||
|
||||
// 刷新后回到设置页，页面正常不报错
|
||||
const hasSetup = bodyAfter.includes('开始专业评估') || bodyAfter.includes('AI协作技巧');
|
||||
const noCrash = !bodyAfter.includes('Error') && !bodyAfter.includes('错误');
|
||||
assert('刷新后页面正常无崩溃', hasSetup && noCrash);
|
||||
} catch (err) {
|
||||
console.error(` ❌ 2d 异常: ${err.message}`);
|
||||
globalFailed++;
|
||||
}
|
||||
await browser.close();
|
||||
}
|
||||
}
|
||||
|
||||
// ═══════════════════ Main ═══════════════════
|
||||
async function run() {
|
||||
console.log('═══════════════════════════════════════════════');
|
||||
console.log(' AuraK 题库多轮对话 — Phase 1+2 测试');
|
||||
console.log('═══════════════════════════════════════════════\n');
|
||||
|
||||
// Health check
|
||||
const http = await import('http');
|
||||
const apiAlive = await new Promise(resolve => {
|
||||
const req = http.request(`${API}/api/auth/login`, { method: 'POST', headers: { 'Content-Type': 'application/json' } }, res => resolve(res.statusCode === 201));
|
||||
req.on('error', () => resolve(false));
|
||||
req.write(JSON.stringify({ username: 'admin', password: 'admin123' }));
|
||||
req.end();
|
||||
});
|
||||
assert('后端API响应正常', apiAlive);
|
||||
if (!apiAlive) { console.log('\n服务不可用，跳过测试'); process.exit(1); }
|
||||
|
||||
await phase1();
|
||||
await phase1b();
|
||||
await phase2();
|
||||
|
||||
console.log(`\n${'═'.repeat(50)}`);
|
||||
console.log(` 总结果: ${globalPassed} 通过, ${globalFailed} 失败`);
|
||||
console.log(`${'═'.repeat(50)}`);
|
||||
process.exit(globalFailed > 0 ? 1 : 0);
|
||||
}
|
||||
|
||||
run();
|
||||
@@ -0,0 +1,145 @@
|
||||
/**
|
||||
* 清理题库中不符合"简单、应用为主"的题目
|
||||
*
|
||||
* 删除规则：
|
||||
* 1. 纯概念/定义/术语类题目（考"什么是XX"而不是"遇到XX该怎么做"）
|
||||
* 2. 分类/层级背诵题（考"L1级别要求什么"等）
|
||||
* 3. 完全重复的题目
|
||||
* 4. 大量高度雷同的场景题（保留2-3个最佳，删除其余）
|
||||
*
|
||||
* 运行: node server/scripts/cleanup-question-bank.cjs
|
||||
*/
|
||||
const D = require('better-sqlite3');
|
||||
const path = require('path');
|
||||
const db = new D(path.join(__dirname, '../data/metadata.db'));
|
||||
const BANK = '984632e0-b35d-486d-9a19-27a14845db37';
|
||||
|
||||
// Helper: find item ID by partial text match
|
||||
function findIds(textLike) {
|
||||
return db.prepare("SELECT id, question_text, questionType FROM question_bank_items WHERE bank_id=? AND question_text LIKE ? ORDER BY ROWID").all(BANK, textLike);
|
||||
}
|
||||
|
||||
function del(id, reason) {
|
||||
const item = db.prepare("SELECT question_text, dimension, questionType FROM question_bank_items WHERE id=?").get(id);
|
||||
if (!item) { console.log(' ⚠️ 未找到:', id.substring(0,8)); return; }
|
||||
db.prepare("DELETE FROM question_bank_items WHERE id=?").run(id);
|
||||
console.log(` 🗑️ ${item.questionType} ${item.dimension} | ${reason} | ${item.question_text.replace(/\n/g,' ').substring(0,60)}`);
|
||||
}
|
||||
|
||||
let total = 0;
|
||||
function d(id, reason) { del(id, reason); total++; }
|
||||
|
||||
console.log('=== 清理题库 ===\n');
|
||||
|
||||
// ═══════════════ DEV_PATTERN ═══════════════
|
||||
console.log('--- DEV_PATTERN: 概念/术语题 ---');
|
||||
|
||||
// 概念定义：SDD/Vibe Coding/Flow State/L1级别
|
||||
d('0b00ac95-0000-0000-0000-000000000000', ''); // placeholder — use LIKE instead
|
||||
|
||||
// Since UUIDs are random, use text search
|
||||
const devPatternConcepts = [
|
||||
{ like: '%瀑布开发和敏捷开发的核心区别%', reason: '概念对比：瀑布vs敏捷' },
|
||||
{ like: '%规范驱动开发%核心思想%', reason: '概念定义：SDD核心思想' },
|
||||
{ like: '%Vibe Coding（氛围编程）是一种什么样的编程方式%', reason: '概念定义：Vibe Coding是什么' },
|
||||
{ like: '%Flow State（心流状态）的核心特征%', reason: '概念定义：Flow State特征' },
|
||||
{ like: '%Vibe Coding中人和AI的分工应该是%', reason: '概念定义：Vibe Coding分工' },
|
||||
{ like: '%SDD中的"规范"应该是什么样的%', reason: 'ADV概念：SDD规范' },
|
||||
{ like: '%当你一直按Tab接受AI代码却不看%', reason: 'ADV术语：Vibe Coding挂机' },
|
||||
{ like: '%"概率性"的，这意味着什么%', reason: 'ADV理论：概率性' },
|
||||
{ like: '%L1级别的AI开发范式维度要求%', reason: '分类背诵：L1级别' },
|
||||
{ like: '%请简述规范驱动开发%典型流程%', reason: '概念阐述：SDD流程' },
|
||||
{ like: '%Vibe Coding有助于接近Flow State%三个核心条件%', reason: '概念阐述：Vibe Coding+Flow State' },
|
||||
{ like: '%从确定性到概率性%这一变化对开发流程%', reason: 'ADV理论：确定性到概率性' },
|
||||
];
|
||||
|
||||
for (const c of devPatternConcepts) {
|
||||
const items = findIds(c.like);
|
||||
for (const item of items) d(item.id, c.reason);
|
||||
}
|
||||
|
||||
// DEV_PATTERN duplicates
|
||||
const devPatternDups = [
|
||||
{ like1: '%你和AI分工完成一个功能：你负责设计，AI负责编码%', like2: '%', reason: '重复：责任划分' },
|
||||
];
|
||||
const dup1 = findIds('你和AI分工完成一个功能：你负责设计，AI负责编码');
|
||||
// Keep first, delete rest
|
||||
for (let i = 1; i < dup1.length; i++) d(dup1[i].id, '重复：责任划分');
|
||||
|
||||
const dup2 = findIds('你和同事用AI一起开发一个功能。同事直接提交了AI生成的代码没有审查');
|
||||
for (let i = 1; i < dup2.length; i++) d(dup2[i].id, '重复：同事提交没审查');
|
||||
|
||||
// ═══════════════ LLM ═══════════════
|
||||
console.log('\n--- LLM: 概念/原理题 ---');
|
||||
|
||||
const llmConcepts = [
|
||||
{ like: 'AI的工作原理是根据上文猜下文%', reason: '原理：AI工作机制' },
|
||||
{ like: 'AI的"幻觉"是指AI会编造%', reason: '定义：幻觉术语' },
|
||||
{ like: 'AI训练数据的截止日期意味着%', reason: '原理：训练数据截止' },
|
||||
{ like: 'AI有时会编造看似合理但实际不存在的信息，这被称为"幻觉"%', reason: '定义：幻觉术语(重复)' },
|
||||
{ like: 'AI的知识训练数据只截止到%', reason: '原理：知识截止' },
|
||||
{ like: 'AI不知道自己的知识边界%', reason: '原理：AI知识边界' },
|
||||
{ like: '以下哪个是AI的固有问题%', reason: '列举：AI固有问题' },
|
||||
{ like: 'AI说了一段话，听起来很有道理，但你查了资料发现它说的内容不存在。这是什么现象%', reason: '定义：这是什么现象' },
|
||||
{ like: '%传统AI（判别式）和生成式AI的核心差异%', reason: 'ADV概念：判别式vs生成式' },
|
||||
{ like: 'AI的"上下文有限"是指什么问题%', reason: '定义：上下文有限' },
|
||||
];
|
||||
|
||||
for (const c of llmConcepts) {
|
||||
const items = findIds(c.like);
|
||||
for (const item of items) d(item.id, c.reason);
|
||||
}
|
||||
|
||||
// LLM MC: 11 hallucination scenario duplicates — keep 2 (第一个+搜索引擎), delete rest
|
||||
const hallMC = db.prepare("SELECT id, question_text FROM question_bank_items WHERE bank_id=? AND dimension=? AND questionType=? AND question_text LIKE '%场景%' AND (question_text LIKE '%fetchUser%' OR question_text LIKE '%validateUser%' OR question_text LIKE '%sendWelcome%') ORDER BY ROWID").all(BANK, 'LLM', 'MULTIPLE_CHOICE');
|
||||
console.log(`\n--- LLM MC: 幻觉场景重复 (${hallMC.length} total, keep 2) ---`);
|
||||
for (let i = 2; i < hallMC.length; i++) {
|
||||
d(hallMC[i].id, '重复：幻觉场景MC #' + (i+1));
|
||||
}
|
||||
|
||||
// LLM SA: 5页文档场景 duplicates — keep first (cleanest), delete rest
|
||||
const sa5 = db.prepare("SELECT id, question_text FROM question_bank_items WHERE bank_id=? AND dimension=? AND questionType=? AND question_text LIKE '%5页%' ORDER BY ROWID").all(BANK, 'LLM', 'SHORT_ANSWER');
|
||||
console.log(`\n--- LLM SA: 5页文档场景重复 (${sa5.length} total, keep 1) ---`);
|
||||
for (let i = 1; i < sa5.length; i++) {
|
||||
d(sa5[i].id, '重复：5页文档SA #' + (i+1));
|
||||
}
|
||||
|
||||
// ═══════════════ PROMPT ═══════════════
|
||||
console.log('\n--- PROMPT: 分类背诵题 ---');
|
||||
const promptConcepts = [
|
||||
{ like: 'L1级别的技术能力维度要求是什么%', reason: '分类背诵：L1维度' },
|
||||
];
|
||||
for (const c of promptConcepts) {
|
||||
const items = findIds(c.like);
|
||||
for (const item of items) d(item.id, c.reason);
|
||||
}
|
||||
|
||||
// ═══════════════ WORK_CAPABILITY ═══════════════
|
||||
console.log('\n--- WORK_CAPABILITY: 概念/分类题 ---');
|
||||
const wcConcepts = [
|
||||
{ like: '%"负责任AI"的组织原则中，"问责制"对员工的要求是什么%', reason: '概念：负责任AI问责制' },
|
||||
{ like: '%智能体（Agent）与传统聊天AI最本质的区别是什么%', reason: 'ADV概念：Agent vs 聊天AI' },
|
||||
{ like: '%智能体安全控制原则中"最小权限"是指什么%', reason: 'ADV概念：最小权限' },
|
||||
{ like: '请简述AI的四个固有问题%', reason: '列举：AI四个固有问题' },
|
||||
{ like: '数据分为"绝密""机密""公开"三个级别%', reason: '分类：数据分级' },
|
||||
{ like: '%智能体安全的四条控制原则是什么%', reason: 'ADV列举：四条控制原则' },
|
||||
];
|
||||
for (const c of wcConcepts) {
|
||||
const items = findIds(c.like);
|
||||
for (const item of items) d(item.id, c.reason);
|
||||
}
|
||||
|
||||
// WORK_CAPABILITY duplicate
|
||||
const wcDups = findIds('你正在使用AI助手分析一份包含客户信息的Excel表格');
|
||||
for (let i = 1; i < wcDups.length; i++) d(wcDups[i].id, '重复：客户Excel场景');
|
||||
|
||||
// ═══════════════ Summary ═══════════════
|
||||
const remaining = db.prepare('SELECT COUNT(*) c FROM question_bank_items WHERE bank_id=?').get(BANK);
|
||||
console.log(`\n${'═'.repeat(50)}`);
|
||||
console.log(` 删除: ${total} 题`);
|
||||
console.log(` 剩余: ${remaining.c} 题（原 ${remaining.c + total} 题）`);
|
||||
console.log(`\n 各维度分布:`);
|
||||
const byDim = db.prepare('SELECT dimension, questionType, COUNT(*) c FROM question_bank_items WHERE bank_id=? GROUP BY dimension, questionType ORDER BY dimension, questionType').all(BANK);
|
||||
byDim.forEach(r => console.log(` ${r.dimension} ${r.questionType}: ${r.c}`));
|
||||
|
||||
db.close();
|
||||
@@ -216,10 +216,11 @@ export class ApiV1Controller {
|
||||
@Get('knowledge-bases')
|
||||
async listFiles(@Request() req) {
|
||||
const user = req.user;
|
||||
const files = await this.knowledgeBaseService.findAll(
|
||||
const result = await this.knowledgeBaseService.findAll(
|
||||
user.id,
|
||||
user.tenantId,
|
||||
);
|
||||
const files = Array.isArray(result) ? result : result.items;
|
||||
return {
|
||||
files: files.map((f) => ({
|
||||
id: f.id,
|
||||
@@ -286,10 +287,11 @@ export class ApiV1Controller {
|
||||
@Get('knowledge-bases/:id')
|
||||
async getFile(@Request() req, @Param('id') id: string) {
|
||||
const user = req.user;
|
||||
const files = await this.knowledgeBaseService.findAll(
|
||||
const result = await this.knowledgeBaseService.findAll(
|
||||
user.id,
|
||||
user.tenantId,
|
||||
);
|
||||
const files = Array.isArray(result) ? result : result.items;
|
||||
const file = files.find((f) => f.id === id);
|
||||
if (!file) return { error: 'File not found' };
|
||||
return file;
|
||||
|
||||
@@ -307,38 +307,35 @@ export class EmbeddingService {
|
||||
`[Ollama] Generating embeddings for ${texts.length} texts using ${modelName}`,
|
||||
);
|
||||
|
||||
const embeddings: number[][] = [];
|
||||
|
||||
for (let i = 0; i < texts.length; i++) {
|
||||
try {
|
||||
const url = baseUrl.endsWith('/api/embeddings')
|
||||
? baseUrl
|
||||
: `${baseUrl}/api/embeddings`;
|
||||
const url = baseUrl.endsWith('/api/embeddings')
|
||||
? baseUrl
|
||||
: `${baseUrl}/api/embeddings`;
|
||||
|
||||
// Parallelize individual Ollama requests for faster batch processing
|
||||
const results = await Promise.allSettled(
|
||||
texts.map(async (text, i) => {
|
||||
const response = await fetch(url, {
|
||||
method: 'POST',
|
||||
headers: {
|
||||
'Content-Type': 'application/json',
|
||||
},
|
||||
body: JSON.stringify({
|
||||
model: modelName,
|
||||
prompt: texts[i],
|
||||
}),
|
||||
headers: { 'Content-Type': 'application/json' },
|
||||
body: JSON.stringify({ model: modelName, prompt: text }),
|
||||
});
|
||||
|
||||
if (!response.ok) {
|
||||
const errorText = await response.text();
|
||||
throw new Error(`Ollama API error: ${response.status} - ${errorText}`);
|
||||
throw new Error(`Ollama API error for text ${i}: ${response.status} - ${errorText}`);
|
||||
}
|
||||
|
||||
const data = await response.json();
|
||||
embeddings.push(data.embedding);
|
||||
} catch (error) {
|
||||
this.logger.error(
|
||||
`Ollama embedding error for text ${i}: ${error.message}`,
|
||||
);
|
||||
throw error;
|
||||
return data.embedding as number[];
|
||||
}),
|
||||
);
|
||||
|
||||
const embeddings: number[][] = [];
|
||||
for (let i = 0; i < results.length; i++) {
|
||||
const r = results[i];
|
||||
if (r.status === 'rejected') {
|
||||
this.logger.error(`Ollama embedding error for text ${i}: ${r.reason.message}`);
|
||||
throw r.reason;
|
||||
}
|
||||
embeddings.push(r.value);
|
||||
}
|
||||
|
||||
this.logger.log(
|
||||
|
||||
@@ -40,8 +40,17 @@ export class KnowledgeBaseController {
|
||||
|
||||
@Get()
|
||||
@UseGuards(CombinedAuthGuard)
|
||||
async findAll(@Request() req): Promise<KnowledgeBase[]> {
|
||||
return this.knowledgeBaseService.findAll(req.user.id, req.user.tenantId);
|
||||
async findAll(
|
||||
@Request() req,
|
||||
@Query('page') page?: number,
|
||||
@Query('limit') limit?: number,
|
||||
) {
|
||||
return this.knowledgeBaseService.findAll(
|
||||
req.user.id,
|
||||
req.user.tenantId,
|
||||
page ? Number(page) : undefined,
|
||||
limit ? Number(limit) : undefined,
|
||||
);
|
||||
}
|
||||
|
||||
@Get('stats')
|
||||
|
||||
@@ -51,7 +51,7 @@ export class KnowledgeBase {
|
||||
})
|
||||
status: FileStatus;
|
||||
|
||||
@Column({ name: 'user_id', nullable: true }) // Temporarily allowed empty (for debugging), should be required in future
|
||||
@Column({ name: 'user_id' })
|
||||
userId: string;
|
||||
|
||||
@Column({ name: 'tenant_id', nullable: true, type: 'text' })
|
||||
|
||||
@@ -21,9 +21,11 @@ import { ElasticsearchService } from '../elasticsearch/elasticsearch.service';
|
||||
import { TikaService } from '../tika/tika.service';
|
||||
import * as fs from 'fs';
|
||||
import * as path from 'path';
|
||||
import * as crypto from 'crypto';
|
||||
import { EmbeddingService } from './embedding.service';
|
||||
import { TextChunkerService } from './text-chunker.service';
|
||||
import { TextChunkerService, TextChunk } from './text-chunker.service';
|
||||
import { ModelConfigService } from '../model-config/model-config.service';
|
||||
import { ModelType } from '../types';
|
||||
import { RagService } from '../rag/rag.service';
|
||||
import { VisionService } from '../vision/vision.service';
|
||||
import { TenantService } from '../tenant/tenant.service';
|
||||
@@ -87,9 +89,28 @@ export class KnowledgeBaseService {
|
||||
const processingMode =
|
||||
mode === 'precise' ? ProcessingMode.PRECISE : ProcessingMode.FAST;
|
||||
|
||||
// 先移文件，再创建DB记录：避免DB记录存在但文件丢失的不一致状态
|
||||
const uploadPath = process.env.UPLOAD_FILE_PATH || './uploads';
|
||||
const tempId = crypto.randomUUID();
|
||||
const targetDir = path.join(uploadPath, tenantId || 'default', tempId);
|
||||
const targetPath = path.join(targetDir, fileInfo.filename);
|
||||
try {
|
||||
if (!fs.existsSync(targetDir)) {
|
||||
fs.mkdirSync(targetDir, { recursive: true });
|
||||
}
|
||||
if (fs.existsSync(fileInfo.path)) {
|
||||
fs.renameSync(fileInfo.path, targetPath);
|
||||
} else {
|
||||
throw new Error(`Source file not found: ${fileInfo.path}`);
|
||||
}
|
||||
} catch (fsError) {
|
||||
this.logger.error('Failed to move file to partitioned storage', fsError);
|
||||
throw new Error(`File storage error: ${fsError.message}`);
|
||||
}
|
||||
|
||||
const kb = this.kbRepository.create({
|
||||
originalName: fileInfo.originalname,
|
||||
storagePath: fileInfo.path,
|
||||
storagePath: targetPath,
|
||||
size: fileInfo.size,
|
||||
mimetype: fileInfo.mimetype,
|
||||
status: FileStatus.PENDING,
|
||||
@@ -115,36 +136,6 @@ export class KnowledgeBaseService {
|
||||
`Created KB record: ${savedKb.id}, mode: ${mode}, file: ${fileInfo.originalname}`,
|
||||
);
|
||||
|
||||
// ---------------------------------------------------------
|
||||
// Move the file to the final partitioned directory
|
||||
// source: uploads/{tenantId}/{filename} (or wherever it was)
|
||||
// target: uploads/{tenantId}/{savedKb.id}/{filename}
|
||||
// ---------------------------------------------------------
|
||||
const fs = await import('fs');
|
||||
const path = await import('path');
|
||||
const uploadPath = process.env.UPLOAD_FILE_PATH || './uploads';
|
||||
const targetDir = path.join(uploadPath, tenantId || 'default', savedKb.id);
|
||||
const targetPath = path.join(targetDir, fileInfo.filename);
|
||||
|
||||
try {
|
||||
if (!fs.existsSync(targetDir)) {
|
||||
fs.mkdirSync(targetDir, { recursive: true });
|
||||
}
|
||||
if (fs.existsSync(fileInfo.path)) {
|
||||
fs.renameSync(fileInfo.path, targetPath);
|
||||
// Update the DB record with the new path
|
||||
savedKb.storagePath = targetPath;
|
||||
await this.kbRepository.save(savedKb);
|
||||
this.logger.log(`Moved file to partitioned storage: ${targetPath}`);
|
||||
}
|
||||
} catch (fsError) {
|
||||
this.logger.error(
|
||||
`Failed to move file ${savedKb.id} to partitioned storage`,
|
||||
fsError,
|
||||
);
|
||||
// We will let it continue, but the file might be stuck in the temp/root folder
|
||||
}
|
||||
|
||||
// If queue processing is requested, await completion
|
||||
if (config?.waitForCompletion) {
|
||||
await this.processFile(savedKb.id, userId, tenantId, config);
|
||||
@@ -158,16 +149,33 @@ export class KnowledgeBaseService {
|
||||
return savedKb;
|
||||
}
|
||||
|
||||
async findAll(userId: string, tenantId?: string): Promise<KnowledgeBase[]> {
|
||||
async findAll(
|
||||
userId: string,
|
||||
tenantId?: string,
|
||||
page?: number,
|
||||
limit?: number,
|
||||
): Promise<KnowledgeBase[] | PaginatedKnowledgeBase> {
|
||||
const where: any = {};
|
||||
if (tenantId) {
|
||||
where.tenantId = tenantId;
|
||||
} else {
|
||||
where.userId = userId;
|
||||
}
|
||||
|
||||
if (page !== undefined && limit !== undefined) {
|
||||
const [items, total] = await this.kbRepository.findAndCount({
|
||||
where,
|
||||
relations: ['groups'],
|
||||
order: { createdAt: 'DESC' },
|
||||
skip: (page - 1) * limit,
|
||||
take: limit,
|
||||
});
|
||||
return { items, total, page, limit };
|
||||
}
|
||||
|
||||
return this.kbRepository.find({
|
||||
where,
|
||||
relations: ['groups'], // Load group relations
|
||||
relations: ['groups'],
|
||||
order: { createdAt: 'DESC' },
|
||||
});
|
||||
}
|
||||
@@ -248,17 +256,27 @@ export class KnowledgeBaseService {
|
||||
topK: number = 5,
|
||||
) {
|
||||
try {
|
||||
// Generate simulation vector using default dimensions from environment variable
|
||||
const defaultDimensions = parseInt(
|
||||
process.env.DEFAULT_VECTOR_DIMENSIONS || '2560',
|
||||
);
|
||||
const mockEmbedding = Array.from(
|
||||
{ length: defaultDimensions },
|
||||
() => Math.random() - 0.5,
|
||||
);
|
||||
const queryVector = mockEmbedding;
|
||||
// 1. Generate query vector using the default embedding model
|
||||
let queryVector: number[] = [];
|
||||
try {
|
||||
const defaultEmbedding = await this.modelConfigService.findDefaultByType(
|
||||
tenantId,
|
||||
ModelType.EMBEDDING,
|
||||
);
|
||||
if (defaultEmbedding) {
|
||||
const vectors = await this.embeddingService.getEmbeddings(
|
||||
[query],
|
||||
defaultEmbedding.id,
|
||||
);
|
||||
queryVector = vectors[0] || [];
|
||||
}
|
||||
} catch (embedError) {
|
||||
this.logger.warn(
|
||||
`No embedding model available, falling back to text-only search: ${embedError.message}`,
|
||||
);
|
||||
}
|
||||
|
||||
// 2. Search in Elasticsearch
|
||||
// 2. Search in Elasticsearch (with vector if available, text-only otherwise)
|
||||
const searchResults = await this.elasticsearchService.searchSimilar(
|
||||
queryVector,
|
||||
userId,
|
||||
@@ -268,7 +286,7 @@ export class KnowledgeBaseService {
|
||||
|
||||
// 3. Get file information from database
|
||||
const fileIds = [...new Set(searchResults.map((r) => r.fileId))];
|
||||
const files = await this.kbRepository.findByIds(fileIds);
|
||||
const files = await this.kbRepository.findBy({ id: In(fileIds) });
|
||||
const fileMap = new Map(files.map((f) => [f.id, f]));
|
||||
|
||||
// 4. Combine results with file info
|
||||
@@ -380,7 +398,6 @@ export class KnowledgeBaseService {
|
||||
}
|
||||
|
||||
// 2. Delete file from filesystem
|
||||
const fs = await import('fs');
|
||||
try {
|
||||
if (fs.existsSync(file.storagePath)) {
|
||||
fs.unlinkSync(file.storagePath);
|
||||
@@ -1010,7 +1027,7 @@ export class KnowledgeBaseService {
|
||||
},
|
||||
);
|
||||
} catch (error) {
|
||||
// Detect context length error (supports Japanese/Chinese/English)
|
||||
// Detect context length error → fall back to single-chunk processing
|
||||
if (
|
||||
error.message &&
|
||||
(error.message.includes('context length') ||
|
||||
@@ -1019,58 +1036,7 @@ export class KnowledgeBaseService {
|
||||
this.logger.warn(
|
||||
this.i18nService.getMessage('contextLengthErrorFallback'),
|
||||
);
|
||||
|
||||
// Downgrade to single text processing
|
||||
for (let i = 0; i < chunks.length; i++) {
|
||||
const chunk = chunks[i];
|
||||
|
||||
try {
|
||||
const embeddings = await this.embeddingService.getEmbeddings(
|
||||
[chunk.content], // Single text
|
||||
kb.embeddingModelId,
|
||||
);
|
||||
|
||||
if (!embeddings[0] || embeddings[0].length === 0) {
|
||||
this.logger.warn(
|
||||
this.i18nService.formatMessage('skippingEmptyVectorChunk', {
|
||||
index: chunk.index,
|
||||
}),
|
||||
);
|
||||
continue;
|
||||
}
|
||||
|
||||
await this.elasticsearchService.indexDocument(
|
||||
`${kb.id}_chunk_${chunk.index}`,
|
||||
chunk.content,
|
||||
embeddings[0],
|
||||
{
|
||||
fileId: kb.id,
|
||||
originalName: kb.originalName,
|
||||
mimetype: kb.mimetype,
|
||||
userId: userId,
|
||||
chunkIndex: chunk.index,
|
||||
startPosition: chunk.startPosition,
|
||||
endPosition: chunk.endPosition,
|
||||
tenantId,
|
||||
},
|
||||
);
|
||||
|
||||
if ((i + 1) % 10 === 0) {
|
||||
this.logger.log(
|
||||
`Single processing progress: ${i + 1}/${chunks.length}`,
|
||||
);
|
||||
}
|
||||
} catch (chunkError) {
|
||||
this.logger.error(
|
||||
`Failed to process text block ${chunk.index}. Skipping: ${chunkError.message}`,
|
||||
);
|
||||
continue;
|
||||
}
|
||||
}
|
||||
|
||||
this.logger.log(
|
||||
`Single text processing completed: ${chunks.length} chunks`,
|
||||
);
|
||||
await this.processChunksOneByOne(chunks, kb, userId, tenantId);
|
||||
} else {
|
||||
// Throw other errors directly
|
||||
throw error;
|
||||
@@ -1125,7 +1091,7 @@ export class KnowledgeBaseService {
|
||||
}
|
||||
});
|
||||
} catch (error) {
|
||||
// Detect context length error (supports Japanese/Chinese/English)
|
||||
// Detect context length error → fall back to single-chunk processing
|
||||
if (
|
||||
error.message &&
|
||||
(error.message.includes('context length') ||
|
||||
@@ -1134,64 +1100,7 @@ export class KnowledgeBaseService {
|
||||
this.logger.warn(
|
||||
this.i18nService.getMessage('batchContextLengthErrorFallback'),
|
||||
);
|
||||
|
||||
// Downgrade to single text processing
|
||||
for (let i = 0; i < chunks.length; i++) {
|
||||
const chunk = chunks[i];
|
||||
|
||||
try {
|
||||
const embeddings = await this.embeddingService.getEmbeddings(
|
||||
[chunk.content], // Single text
|
||||
kb.embeddingModelId,
|
||||
);
|
||||
|
||||
if (!embeddings[0] || embeddings[0].length === 0) {
|
||||
this.logger.warn(
|
||||
this.i18nService.formatMessage(
|
||||
'skippingEmptyVectorChunk',
|
||||
{ index: chunk.index },
|
||||
),
|
||||
);
|
||||
continue;
|
||||
}
|
||||
|
||||
await this.elasticsearchService.indexDocument(
|
||||
`${kb.id}_chunk_${chunk.index}`,
|
||||
chunk.content,
|
||||
embeddings[0],
|
||||
{
|
||||
fileId: kb.id,
|
||||
originalName: kb.originalName,
|
||||
mimetype: kb.mimetype,
|
||||
userId: userId,
|
||||
tenantId, // Added tenantId
|
||||
chunkIndex: chunk.index,
|
||||
startPosition: chunk.startPosition,
|
||||
endPosition: chunk.endPosition,
|
||||
},
|
||||
);
|
||||
|
||||
if ((i + 1) % 10 === 0) {
|
||||
this.logger.log(
|
||||
`Single processing progress: ${i + 1}/${chunks.length}`,
|
||||
);
|
||||
}
|
||||
} catch (chunkError) {
|
||||
this.logger.error(
|
||||
this.i18nService.formatMessage('chunkProcessingFailed', {
|
||||
index: chunk.index,
|
||||
message: chunkError.message,
|
||||
}),
|
||||
);
|
||||
continue;
|
||||
}
|
||||
}
|
||||
|
||||
this.logger.log(
|
||||
this.i18nService.formatMessage('singleTextProcessingComplete', {
|
||||
count: chunks.length,
|
||||
}),
|
||||
);
|
||||
await this.processChunksOneByOne(chunks, kb, userId, tenantId);
|
||||
} else {
|
||||
// Throw other errors directly
|
||||
throw error;
|
||||
@@ -1244,58 +1153,7 @@ export class KnowledgeBaseService {
|
||||
this.logger.warn(
|
||||
this.i18nService.getMessage('batchContextLengthErrorFallback'),
|
||||
);
|
||||
|
||||
// Downgrade to single text processing
|
||||
for (let i = 0; i < chunks.length; i++) {
|
||||
const chunk = chunks[i];
|
||||
|
||||
try {
|
||||
const embeddings = await this.embeddingService.getEmbeddings(
|
||||
[chunk.content], // Single text
|
||||
kb.embeddingModelId,
|
||||
);
|
||||
|
||||
if (!embeddings[0] || embeddings[0].length === 0) {
|
||||
this.logger.warn(
|
||||
`Skipping empty vector text block ${chunk.index}`,
|
||||
);
|
||||
continue;
|
||||
}
|
||||
|
||||
await this.elasticsearchService.indexDocument(
|
||||
`${kb.id}_chunk_${chunk.index}`,
|
||||
chunk.content,
|
||||
embeddings[0],
|
||||
{
|
||||
fileId: kb.id,
|
||||
originalName: kb.originalName,
|
||||
mimetype: kb.mimetype,
|
||||
userId: userId,
|
||||
tenantId, // Added tenantId
|
||||
chunkIndex: chunk.index,
|
||||
startPosition: chunk.startPosition,
|
||||
endPosition: chunk.endPosition,
|
||||
},
|
||||
);
|
||||
|
||||
if ((i + 1) % 10 === 0) {
|
||||
this.logger.log(
|
||||
`Single processing progress: ${i + 1}/${chunks.length}`,
|
||||
);
|
||||
}
|
||||
} catch (chunkError) {
|
||||
this.logger.error(
|
||||
`Failed to process text block ${chunk.index}. Skipping: ${chunkError.message}`,
|
||||
);
|
||||
continue;
|
||||
}
|
||||
}
|
||||
|
||||
this.logger.log(
|
||||
this.i18nService.formatMessage('singleTextProcessingComplete', {
|
||||
count: chunks.length,
|
||||
}),
|
||||
);
|
||||
await this.processChunksOneByOne(chunks, kb, userId, tenantId);
|
||||
} else {
|
||||
// Throw other errors directly
|
||||
throw error;
|
||||
@@ -1553,8 +1411,6 @@ export class KnowledgeBaseService {
|
||||
}
|
||||
|
||||
// Generate PDF field path
|
||||
const path = await import('path');
|
||||
const fs = await import('fs');
|
||||
const uploadDir = path.dirname(kb.storagePath);
|
||||
const baseName = path.basename(
|
||||
kb.storagePath,
|
||||
@@ -1640,8 +1496,6 @@ export class KnowledgeBaseService {
|
||||
}
|
||||
|
||||
// Generate PDF file path
|
||||
const path = await import('path');
|
||||
const fs = await import('fs');
|
||||
const uploadDir = path.dirname(kb.storagePath);
|
||||
const baseName = path.basename(
|
||||
kb.storagePath,
|
||||
@@ -1823,4 +1677,60 @@ export class KnowledgeBaseService {
|
||||
|
||||
return null;
|
||||
}
|
||||
|
||||
/**
|
||||
* 降级策略：逐条处理 chunk（当 batch 请求因上下文长度超限失败时）
|
||||
* 替代之前三处重复的 ~200 行降级代码
|
||||
*/
|
||||
private async processChunksOneByOne(
|
||||
chunks: TextChunk[],
|
||||
kb: KnowledgeBase,
|
||||
userId: string,
|
||||
tenantId: string,
|
||||
): Promise<void> {
|
||||
for (let i = 0; i < chunks.length; i++) {
|
||||
const chunk = chunks[i];
|
||||
try {
|
||||
const embeddings = await this.embeddingService.getEmbeddings(
|
||||
[chunk.content],
|
||||
kb.embeddingModelId,
|
||||
);
|
||||
if (!embeddings[0] || embeddings[0].length === 0) {
|
||||
this.logger.warn(
|
||||
this.i18nService.formatMessage('skippingEmptyVectorChunk', {
|
||||
index: chunk.index,
|
||||
}),
|
||||
);
|
||||
continue;
|
||||
}
|
||||
await this.elasticsearchService.indexDocument(
|
||||
`${kb.id}_chunk_${chunk.index}`,
|
||||
chunk.content,
|
||||
embeddings[0],
|
||||
{
|
||||
fileId: kb.id,
|
||||
originalName: kb.originalName,
|
||||
mimetype: kb.mimetype,
|
||||
userId: userId,
|
||||
tenantId,
|
||||
chunkIndex: chunk.index,
|
||||
startPosition: chunk.startPosition,
|
||||
endPosition: chunk.endPosition,
|
||||
},
|
||||
);
|
||||
if ((i + 1) % 10 === 0) {
|
||||
this.logger.log(`Single processing progress: ${i + 1}/${chunks.length}`);
|
||||
}
|
||||
} catch (chunkError) {
|
||||
this.logger.error(
|
||||
`Failed to process text block ${chunk.index}. Skipping: ${chunkError.message}`,
|
||||
);
|
||||
}
|
||||
}
|
||||
this.logger.log(
|
||||
this.i18nService.formatMessage('singleTextProcessingComplete', {
|
||||
count: chunks.length,
|
||||
}),
|
||||
);
|
||||
}
|
||||
}
|
||||
|
||||
@@ -19,8 +19,12 @@ export class TextChunkerService {
|
||||
}
|
||||
|
||||
const cleanText = text.trim();
|
||||
const chunkSizeInChars = chunkSize * 4; // 1 token ≈ 4 chars
|
||||
const overlapInChars = overlap * 4;
|
||||
// 1 token ≈ 4 chars for English, ≈ 1.5-2 chars for CJK.
|
||||
// Heuristic: if CJK chars > 30% of content, use 2x ratio
|
||||
const cjkChars = (cleanText.match(/[一-鿿-ゟ゠-ヿ가-]/g) || []).length;
|
||||
const ratio = (cjkChars / cleanText.length) > 0.3 ? 2 : 4;
|
||||
const chunkSizeInChars = chunkSize * ratio;
|
||||
const overlapInChars = overlap * ratio;
|
||||
|
||||
// If text length <= chunk size, return entire text as one chunk
|
||||
if (cleanText.length <= chunkSizeInChars) {
|
||||
@@ -87,7 +91,7 @@ export class TextChunkerService {
|
||||
preferredEnd: number,
|
||||
minEnd: number,
|
||||
): number {
|
||||
const sentenceEnders = ['.', '!', '?', '。', '！', '？'];
|
||||
const sentenceEnders = ['.', '!', '?', '。', '！', '？', '．', '｡', '…', '‥'];
|
||||
|
||||
for (let i = preferredEnd; i >= minEnd; i--) {
|
||||
if (sentenceEnders.includes(text[i])) {
|
||||
|
||||
Reference in New Issue
Block a user