mirror of
https://github.com/TencentCloud/TencentDB-Agent-Memory
synced 2026-07-10 20:34:30 +00:00
chore: release v0.3.5
This commit is contained in:
chrishuan
@@ -0,0 +1,634 @@
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#!/usr/bin/env node
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/**
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* 腾讯云 VDB (Tencent VectorDB) 数据导出脚本
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*
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* 连接腾讯云向量数据库实例，查询指定数据库下 collection 的文档，导出为 .jsonl 文件。
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* 仅支持腾讯云向量数据库（Tencent VectorDB），不支持其他厂商的向量数据库。
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*
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* 所有连接参数通过 CLI 传入，无需 .env 文件。
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*
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* 用法：
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* node ./bin/export-tencent-vdb.mjs --url <地址> --username <用户名> --api-key <密钥> --database <库名>
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* node ./bin/export-tencent-vdb.mjs --url <地址> --username <用户名> --api-key <密钥> --database <库名> --probe
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* node ./bin/export-tencent-vdb.mjs --url <地址> --username <用户名> --api-key <密钥> --database <库名> -c <collection> -o /tmp/backup
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*
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* 输出：
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* 默认输出到当前工作目录下的 ./vdb-export-YYYY-MM-DD/，可通过 -o 指定。
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* <outputDir>/
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* ├── <collection>.jsonl — 每行一个 JSON 文档
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* ├── schemas.json — 导出的 collection 表结构（索引、embedding 配置等）
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* └── export-meta.json — 导出元信息
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*
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* 导出字段说明：
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* 默认行为：导出所有字段，但跳过 vector（稠密向量，1024维浮点数组，体积大）。
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* 加 --include-vectors：导出全部字段，包括 vector，不跳过任何内容。
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* 注：sparse_vector（BM25 稀疏向量）始终导出，不受此开关影响。
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*
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* 依赖：Node.js >= 18（内置 fetch）
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*/
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import fs from "node:fs";
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import path from "node:path";
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// ============================================================
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// CLI 参数解析（含 VDB 连接信息）
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// ============================================================
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interface VDBConfig {
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url: string;
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username: string;
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apiKey: string;
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database: string;
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timeout: number;
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}
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interface CliArgs {
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// 连接参数
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url?: string;
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username?: string;
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apiKey?: string;
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database?: string;
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timeout: number;
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// 导出参数
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output: string;
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collection?: string;
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filter?: string;
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limit?: number;
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offset: number;
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includeVectors: boolean;
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probe: boolean;
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help: boolean;
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}
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const PAGE_SIZE = 100;
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function parseArgs(): CliArgs {
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const args = process.argv.slice(2);
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const result: CliArgs = {
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timeout: 30000,
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output: `./vdb-export-${new Date().toISOString().slice(0, 10)}`,
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offset: 0,
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includeVectors: false,
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probe: false,
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help: false,
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};
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for (let i = 0; i < args.length; i++) {
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switch (args[i]) {
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case "--url":
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result.url = args[++i];
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break;
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case "--username":
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result.username = args[++i];
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break;
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case "--api-key":
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result.apiKey = args[++i];
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break;
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case "--database":
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result.database = args[++i];
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break;
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case "--timeout":
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result.timeout = parseInt(args[++i], 10) || 30000;
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break;
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case "--output":
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case "-o":
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result.output = args[++i];
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break;
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case "--collection":
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case "-c":
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result.collection = args[++i];
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break;
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case "--filter":
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case "-f":
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result.filter = args[++i];
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break;
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case "--limit":
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case "-l": {
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const v = parseInt(args[++i], 10);
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if (isNaN(v) || v < 1) {
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console.error(`❌ --limit 必须 >= 1，收到: ${args[i]}`);
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process.exit(1);
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}
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result.limit = v;
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break;
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}
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case "--offset": {
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const v = parseInt(args[++i], 10);
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if (isNaN(v) || v < 0) {
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console.error(`❌ --offset 必须 >= 0，收到: ${args[i]}`);
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process.exit(1);
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}
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result.offset = v;
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break;
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}
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case "--include-vectors":
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result.includeVectors = true;
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break;
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case "--probe":
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result.probe = true;
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break;
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case "--help":
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case "-h":
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result.help = true;
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break;
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}
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}
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return result;
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}
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function validateConfig(args: CliArgs): VDBConfig {
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const missing: string[] = [];
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if (!args.url) missing.push("--url");
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if (!args.username) missing.push("--username");
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if (!args.apiKey) missing.push("--api-key");
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if (!args.database) missing.push("--database");
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if (missing.length > 0) {
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console.error("❌ 缺少必填参数：");
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for (const k of missing) {
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console.error(` - ${k}`);
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}
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console.error();
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console.error("示例：");
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console.error();
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console.error(' node ./bin/export-tencent-vdb.mjs \\');
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console.error(' --url "http://your-vdb-host:8100" \\');
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console.error(' --username "root" \\');
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console.error(' --api-key "your-api-key" \\');
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console.error(' --database "your-database"');
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console.error();
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console.error("使用 --help 查看完整参数说明。");
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process.exit(1);
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}
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return {
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url: args.url!,
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username: args.username!,
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apiKey: args.apiKey!,
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database: args.database!,
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timeout: args.timeout,
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};
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}
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function printHelp(): void {
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console.log(`
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腾讯云 VDB (Tencent VectorDB) 数据导出脚本
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用法：
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node ./bin/export-tencent-vdb.mjs [连接参数] [选项]
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连接参数（必填）：
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--url <地址> VDB 实例 HTTP 地址（如 http://your-vdb-host:8100）
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--username <用户名> 认证用户名（如 root）
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--api-key <密钥> 认证密钥
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--database <库名> 数据库名称
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选项：
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--timeout <毫秒> 单次请求超时（默认: 30000）
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-o, --output <目录> 输出目录（默认: ./vdb-export-YYYY-MM-DD）
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-c, --collection <全名> 只导出指定 collection（全名匹配，不指定则导出所有）
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-f, --filter <表达式> VDB Filter 过滤条件（如 'agent_id = "xxx"'）
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-l, --limit <数量> 最多导出多少条（不指定则导出全部）
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--offset <偏移> 从第几条开始（默认: 0），须为分页大小的整数倍
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--include-vectors 保留 vector 稠密向量字段（默认跳过）
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--probe 仅测试连通性，列出 collection 信息后退出
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-h, --help 显示帮助
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输出：
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<outputDir>/
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├── <collection全名>.jsonl 每行一个 JSON 文档
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├── schemas.json 表结构
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└── export-meta.json 导出元信息
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导出字段说明：
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默认跳过 vector（稠密向量），保留 sparse_vector（BM25）。
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加 --include-vectors 导出全部字段。
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示例：
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# 测试连通性
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node ./bin/export-tencent-vdb.mjs \\
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--url "http://gz-vdb-xxx:8100" --username root --api-key "xxx" --database mydb \\
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--probe
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# 全量导出
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node ./bin/export-tencent-vdb.mjs \\
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--url "http://gz-vdb-xxx:8100" --username root --api-key "xxx" --database mydb
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# 导出指定 collection 到指定目录
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node ./bin/export-tencent-vdb.mjs \\
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--url "http://gz-vdb-xxx:8100" --username root --api-key "xxx" --database mydb \\
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-c mydb_l0_conversations -o /tmp/backup
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# 带过滤条件
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node ./bin/export-tencent-vdb.mjs \\
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--url "http://gz-vdb-xxx:8100" --username root --api-key "xxx" --database mydb \\
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-f 'role = "user"'
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`);
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}
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// ============================================================
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// VDB HTTP Client
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// ============================================================
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class VDBClient {
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private baseUrl: string;
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private authHeader: string;
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private database: string;
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private timeout: number;
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constructor(cfg: VDBConfig) {
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this.baseUrl = cfg.url.replace(/\/$/, "");
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this.authHeader = `Bearer account=${cfg.username}&api_key=${cfg.apiKey}`;
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this.database = cfg.database;
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this.timeout = cfg.timeout;
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}
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async request<T>(apiPath: string, body: Record<string, unknown>): Promise<T> {
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const url = `${this.baseUrl}${apiPath}`;
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const resp = await fetch(url, {
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method: "POST",
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headers: {
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"Content-Type": "application/json",
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Authorization: this.authHeader,
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},
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body: JSON.stringify(body),
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signal: AbortSignal.timeout(this.timeout),
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});
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if (!resp.ok) {
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const text = await resp.text().catch(() => "(unable to read body)");
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throw new Error(`VDB API error: HTTP ${resp.status} — ${text.slice(0, 500)}`);
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}
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const json = (await resp.json()) as { code: number; msg: string } & T;
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if (json.code !== 0) {
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throw new Error(`VDB API error [${apiPath}]: code=${json.code}, msg=${json.msg}`);
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}
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return json;
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}
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async listCollections(): Promise<
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Array<{ collection: string; documentCount: number }>
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> {
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const result = await this.request<{
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collections: Array<{
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collection: string;
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documentCount: number;
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[key: string]: unknown;
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}>;
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}>("/collection/list", {
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database: this.database,
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});
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return (result.collections || []).map((c) => ({
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collection: c.collection,
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documentCount: c.documentCount ?? 0,
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}));
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}
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async queryDocuments(
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collection: string,
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options: {
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limit: number;
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offset: number;
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filter?: string;
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retrieveVector?: boolean;
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},
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): Promise<{
|
||||
documents: Array<Record<string, unknown>>;
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count: number;
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}> {
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const query: Record<string, unknown> = {
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limit: options.limit,
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||||
offset: options.offset,
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};
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if (options.filter) {
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query.filter = options.filter;
|
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}
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if (options.retrieveVector) {
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query.retrieveVector = true;
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}
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const result = await this.request<{
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documents: Array<Record<string, unknown>>;
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count: number;
|
||||
}>("/document/query", {
|
||||
database: this.database,
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||||
collection,
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readConsistency: "strongConsistency",
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query,
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});
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||||
|
||||
return {
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documents: result.documents || [],
|
||||
count: result.count ?? 0,
|
||||
};
|
||||
}
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|
||||
async describeCollection(collection: string): Promise<Record<string, unknown>> {
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||||
const result = await this.request<{
|
||||
collection: Record<string, unknown>;
|
||||
}>("/collection/describe", {
|
||||
database: this.database,
|
||||
collection,
|
||||
});
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||||
return result.collection || {};
|
||||
}
|
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}
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// ============================================================
|
||||
// 导出逻辑
|
||||
// ============================================================
|
||||
|
||||
interface ExportOptions {
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filter?: string;
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limit?: number;
|
||||
offset: number;
|
||||
includeVectors: boolean;
|
||||
expectedTotal?: number;
|
||||
}
|
||||
|
||||
async function exportCollection(
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client: VDBClient,
|
||||
collection: string,
|
||||
outputDir: string,
|
||||
options: ExportOptions,
|
||||
): Promise<{ docCount: number; filePath: string }> {
|
||||
const filePath = path.join(outputDir, `${collection}.jsonl`);
|
||||
const writeStream = fs.createWriteStream(filePath, { encoding: "utf-8" });
|
||||
|
||||
const isRangeMode = options.limit !== undefined;
|
||||
const maxDocs = options.limit ?? Infinity;
|
||||
const pageSize = isRangeMode ? Math.min(options.limit!, PAGE_SIZE) : PAGE_SIZE;
|
||||
|
||||
let currentOffset = options.offset;
|
||||
let totalExported = 0;
|
||||
let hasMore = true;
|
||||
|
||||
console.log(` 📦 ${collection}`);
|
||||
if (options.expectedTotal !== undefined) {
|
||||
console.log(` 文档总数: ${options.expectedTotal}`);
|
||||
}
|
||||
if (options.filter) {
|
||||
console.log(` 过滤条件: ${options.filter}`);
|
||||
}
|
||||
if (isRangeMode) {
|
||||
console.log(` 导出范围: offset=${options.offset}, limit=${options.limit}`);
|
||||
}
|
||||
|
||||
while (hasMore && totalExported < maxDocs) {
|
||||
const remaining = maxDocs - totalExported;
|
||||
const thisPageSize = Math.min(pageSize, remaining);
|
||||
|
||||
try {
|
||||
const result = await client.queryDocuments(collection, {
|
||||
limit: thisPageSize,
|
||||
offset: currentOffset,
|
||||
filter: options.filter,
|
||||
retrieveVector: options.includeVectors,
|
||||
});
|
||||
|
||||
const docs = result.documents;
|
||||
if (!docs || docs.length === 0) {
|
||||
hasMore = false;
|
||||
break;
|
||||
}
|
||||
|
||||
for (const doc of docs) {
|
||||
const exportDoc = { ...doc };
|
||||
if (!options.includeVectors) {
|
||||
delete exportDoc.vector;
|
||||
}
|
||||
writeStream.write(JSON.stringify(exportDoc) + "\n");
|
||||
}
|
||||
|
||||
totalExported += docs.length;
|
||||
currentOffset += docs.length;
|
||||
|
||||
if (options.expectedTotal !== undefined && !isRangeMode) {
|
||||
const pct = Math.min(
|
||||
100,
|
||||
Math.round((totalExported / options.expectedTotal) * 100),
|
||||
);
|
||||
process.stdout.write(
|
||||
`\r 进度: ${totalExported}/${options.expectedTotal} (${pct}%)`,
|
||||
);
|
||||
} else {
|
||||
process.stdout.write(`\r 已导出: ${totalExported} 条`);
|
||||
}
|
||||
|
||||
if (docs.length < thisPageSize) {
|
||||
hasMore = false;
|
||||
}
|
||||
} catch (err) {
|
||||
console.error(
|
||||
`\n ❌ 查询失败 (offset=${currentOffset}): ${err instanceof Error ? err.message : String(err)}`,
|
||||
);
|
||||
hasMore = false;
|
||||
}
|
||||
}
|
||||
|
||||
writeStream.end();
|
||||
await new Promise<void>((resolve) => writeStream.on("finish", resolve));
|
||||
|
||||
console.log(
|
||||
`\n ✅ 完成: ${totalExported} 条 → ${path.basename(filePath)}`,
|
||||
);
|
||||
|
||||
return { docCount: totalExported, filePath };
|
||||
}
|
||||
|
||||
// ============================================================
|
||||
// Main
|
||||
// ============================================================
|
||||
|
||||
async function main(): Promise<void> {
|
||||
const args = parseArgs();
|
||||
|
||||
if (args.help) {
|
||||
printHelp();
|
||||
process.exit(0);
|
||||
}
|
||||
|
||||
const config = validateConfig(args);
|
||||
|
||||
console.log("╔═══════════════════════════════════════════════════╗");
|
||||
console.log("║ 腾讯云 VDB (Tencent VectorDB) 数据导出工具 ║");
|
||||
console.log("╚═══════════════════════════════════════════════════╝");
|
||||
console.log();
|
||||
console.log(`📌 VDB 地址: ${config.url}`);
|
||||
console.log(`📌 数据库: ${config.database}`);
|
||||
console.log(`📌 输出目录: ${args.output}`);
|
||||
if (args.collection) {
|
||||
console.log(`📌 指定导出: ${args.collection}`);
|
||||
}
|
||||
if (args.filter) {
|
||||
console.log(`📌 过滤条件: ${args.filter}`);
|
||||
}
|
||||
if (args.limit !== undefined) {
|
||||
console.log(`📌 导出上限: ${args.limit} 条`);
|
||||
}
|
||||
if (args.offset > 0) {
|
||||
console.log(`📌 起始偏移: ${args.offset}`);
|
||||
}
|
||||
if (args.includeVectors) {
|
||||
console.log(`📌 包含向量: 是`);
|
||||
}
|
||||
console.log();
|
||||
|
||||
fs.mkdirSync(args.output, { recursive: true });
|
||||
|
||||
const client = new VDBClient(config);
|
||||
|
||||
let allCollections: Array<{ collection: string; documentCount: number }>;
|
||||
try {
|
||||
allCollections = await client.listCollections();
|
||||
} catch (err) {
|
||||
console.error(
|
||||
`❌ 列出 collection 失败: ${err instanceof Error ? err.message : String(err)}`,
|
||||
);
|
||||
process.exit(1);
|
||||
}
|
||||
|
||||
let targetCollections: Array<{ collection: string; documentCount: number }>;
|
||||
if (args.collection) {
|
||||
const found = allCollections.find((c) => c.collection === args.collection);
|
||||
if (!found) {
|
||||
console.error(
|
||||
`❌ Collection "${args.collection}" 不存在。可用的 collection：`,
|
||||
);
|
||||
for (const c of allCollections) {
|
||||
console.error(` - ${c.collection} (${c.documentCount} 条)`);
|
||||
}
|
||||
process.exit(1);
|
||||
}
|
||||
targetCollections = [found];
|
||||
} else {
|
||||
targetCollections = allCollections;
|
||||
console.log(
|
||||
`🔍 找到 ${targetCollections.length} 个 collection：`,
|
||||
);
|
||||
for (const c of targetCollections) {
|
||||
console.log(` - ${c.collection} (${c.documentCount} 条)`);
|
||||
}
|
||||
}
|
||||
|
||||
if (targetCollections.length === 0) {
|
||||
console.log("⚠️ 数据库中没有 collection，无数据可导出");
|
||||
process.exit(0);
|
||||
}
|
||||
|
||||
// --probe 模式：只测试连通性，列出信息后退出
|
||||
if (args.probe) {
|
||||
console.log();
|
||||
console.log("✅ 连通性测试通过");
|
||||
console.log();
|
||||
console.log(` VDB 地址: ${config.url}`);
|
||||
console.log(` 数据库: ${config.database}`);
|
||||
console.log(` Collection: ${targetCollections.length} 个`);
|
||||
const totalDocs = targetCollections.reduce((s, c) => s + c.documentCount, 0);
|
||||
console.log(` 总文档数: ${totalDocs}`);
|
||||
console.log();
|
||||
for (const c of targetCollections) {
|
||||
console.log(` - ${c.collection} (${c.documentCount} 条)`);
|
||||
}
|
||||
console.log();
|
||||
process.exit(0);
|
||||
}
|
||||
|
||||
console.log();
|
||||
|
||||
// 获取并保存表结构
|
||||
const schemas: Record<string, Record<string, unknown>> = {};
|
||||
console.log("📐 获取表结构...");
|
||||
for (const col of targetCollections) {
|
||||
try {
|
||||
const schema = await client.describeCollection(col.collection);
|
||||
schemas[col.collection] = schema;
|
||||
const indexCount = Array.isArray(schema.indexes) ? schema.indexes.length : 0;
|
||||
const emb = schema.embedding as Record<string, unknown> | undefined;
|
||||
const embInfo = emb ? `embedding=${emb.field}→${emb.model}` : "无 embedding";
|
||||
console.log(` ✅ ${col.collection} (${indexCount} 个索引, ${embInfo})`);
|
||||
} catch (err) {
|
||||
console.error(
|
||||
` ⚠️ ${col.collection} 表结构获取失败: ${err instanceof Error ? err.message : String(err)}`,
|
||||
);
|
||||
}
|
||||
}
|
||||
console.log();
|
||||
|
||||
const schemaPath = path.join(args.output, "schemas.json");
|
||||
fs.writeFileSync(schemaPath, JSON.stringify(schemas, null, 2) + "\n");
|
||||
|
||||
const exportResults: Array<{
|
||||
collection: string;
|
||||
docCount: number;
|
||||
filePath: string;
|
||||
}> = [];
|
||||
|
||||
for (const col of targetCollections) {
|
||||
try {
|
||||
const result = await exportCollection(client, col.collection, args.output, {
|
||||
filter: args.filter,
|
||||
limit: args.limit,
|
||||
offset: args.offset,
|
||||
includeVectors: args.includeVectors,
|
||||
expectedTotal: col.documentCount,
|
||||
});
|
||||
exportResults.push({ collection: col.collection, ...result });
|
||||
} catch (err) {
|
||||
console.error(
|
||||
`❌ 导出 ${col.collection} 失败: ${err instanceof Error ? err.message : String(err)}`,
|
||||
);
|
||||
exportResults.push({
|
||||
collection: col.collection,
|
||||
docCount: 0,
|
||||
filePath: "",
|
||||
});
|
||||
}
|
||||
console.log();
|
||||
}
|
||||
|
||||
const meta = {
|
||||
exportedAt: new Date().toISOString(),
|
||||
vdbUrl: config.url,
|
||||
database: config.database,
|
||||
filter: args.filter ?? null,
|
||||
offset: args.offset,
|
||||
limit: args.limit ?? null,
|
||||
includeVectors: args.includeVectors,
|
||||
collections: exportResults.map((r) => ({
|
||||
collection: r.collection,
|
||||
documentCount: r.docCount,
|
||||
file: r.filePath ? path.basename(r.filePath) : null,
|
||||
})),
|
||||
totalDocuments: exportResults.reduce((sum, r) => sum + r.docCount, 0),
|
||||
};
|
||||
|
||||
const metaPath = path.join(args.output, "export-meta.json");
|
||||
fs.writeFileSync(metaPath, JSON.stringify(meta, null, 2) + "\n");
|
||||
|
||||
console.log("═══════════════════════════════════════════════════");
|
||||
console.log(" ✅ 导出完成");
|
||||
console.log("═══════════════════════════════════════════════════");
|
||||
console.log();
|
||||
console.log(` 📁 输出目录: ${args.output}`);
|
||||
console.log(` 📊 总文档数: ${meta.totalDocuments}`);
|
||||
for (const r of exportResults) {
|
||||
const status = r.docCount > 0 ? "✅" : "⚠️";
|
||||
console.log(
|
||||
` ${status} ${r.collection}: ${r.docCount} 条`,
|
||||
);
|
||||
}
|
||||
console.log(` 📋 元信息: ${path.basename(metaPath)}`);
|
||||
console.log(` 📐 表结构: ${path.basename(schemaPath)}`);
|
||||
console.log();
|
||||
}
|
||||
|
||||
main().catch((err) => {
|
||||
console.error(
|
||||
`\n❌ 导出失败: ${err instanceof Error ? err.message : String(err)}`,
|
||||
);
|
||||
process.exit(1);
|
||||
});
|
||||
@@ -0,0 +1,19 @@
|
||||
{
|
||||
"compilerOptions": {
|
||||
"target": "ES2022",
|
||||
"module": "Node16",
|
||||
"moduleResolution": "Node16",
|
||||
"outDir": "./dist",
|
||||
"rootDir": ".",
|
||||
"strict": true,
|
||||
"esModuleInterop": true,
|
||||
"skipLibCheck": true,
|
||||
"forceConsistentCasingInFileNames": true,
|
||||
"resolveJsonModule": true,
|
||||
"types": ["node"],
|
||||
"declaration": false,
|
||||
"sourceMap": false
|
||||
},
|
||||
"include": ["export-tencent-vdb.ts"],
|
||||
"exclude": ["dist", "node_modules", "docs"]
|
||||
}
|
||||
Reference in New Issue
Block a user