add test file
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163
scripts/test-ve-llm.mjs
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163
scripts/test-ve-llm.mjs
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import { readFileSync } from 'node:fs';
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import { resolve, dirname } from 'node:path';
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import { fileURLToPath } from 'node:url';
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const __dirname = dirname(fileURLToPath(import.meta.url));
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const root = resolve(__dirname, '..');
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function loadEnv(path) {
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const content = readFileSync(path, 'utf-8');
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const env = {};
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for (const line of content.split('\n')) {
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const trimmed = line.trim();
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if (!trimmed || trimmed.startsWith('#')) continue;
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const eqIndex = trimmed.indexOf('=');
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if (eqIndex === -1) continue;
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const key = trimmed.slice(0, eqIndex).trim();
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let value = trimmed.slice(eqIndex + 1).trim();
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if ((value.startsWith('"') && value.endsWith('"')) || (value.startsWith("'") && value.endsWith("'"))) {
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value = value.slice(1, -1);
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}
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env[key] = value;
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}
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return env;
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}
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const env = loadEnv(resolve(root, '.env.secrets.local'));
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const BASE = env.VECTOR_ENGINE_BASE_URL?.replace(/\/+$/, '') || 'https://api.vectorengine.cn';
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const KEY = env.VECTOR_ENGINE_API_KEY || '';
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if (!KEY) {
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console.error('未找到 VECTOR_ENGINE_API_KEY');
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process.exit(1);
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}
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const TIMEOUT_MS = 60_000;
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async function test(name, method, path, body = null) {
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const url = `${BASE}${path}`;
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const start = Date.now();
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try {
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const controller = new AbortController();
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const timer = setTimeout(() => controller.abort(), TIMEOUT_MS);
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const headers = {
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'Authorization': `Bearer ${KEY}`,
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'Content-Type': 'application/json',
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};
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const options = { method, headers, signal: controller.signal };
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if (body) options.body = JSON.stringify(body);
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const resp = await fetch(url, options);
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clearTimeout(timer);
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const elapsed = Date.now() - start;
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const text = await resp.text();
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let json = null;
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try { json = JSON.parse(text); } catch {}
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if (resp.ok) {
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const model = json?.model || json?.data?.[0]?.id || '?';
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const summary = json?.choices?.[0] ? `choices[0]: ${json.choices[0].message?.content?.slice(0, 80)}` :
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json?.output_text ? `output_text: ${json.output_text.slice(0, 80)}` :
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json?.data ? `${json.data.length} models` : JSON.stringify(json).slice(0, 120);
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return { ok: true, elapsed, code: resp.status, model, summary };
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} else {
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const errMsg = json?.error?.message || json?.message || text.slice(0, 200);
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return { ok: false, elapsed, code: resp.status, error: errMsg };
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}
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} catch (e) {
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const elapsed = Date.now() - start;
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return { ok: false, elapsed, code: 0, error: e.name === 'AbortError' ? `超时(${TIMEOUT_MS / 1000}s)` : e.message };
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}
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}
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console.log(`VectorEngine LLM 能力探测`);
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console.log(`目标: ${BASE}\n`);
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const tests = [
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// 1. 探测 /v1/models - 基础连通性 + 列出可用模型
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{ name: 'GET /v1/models (列出可用模型)', method: 'GET', path: '/v1/models' },
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// 2. Chat Completions - 最标准协议，项目已有 LlmProvider::OpenAiCompatible 支持
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{
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name: 'POST /v1/chat/completions (Chat)',
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method: 'POST',
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path: '/v1/chat/completions',
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body: {
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model: 'gpt-4o',
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messages: [{ role: 'user', content: '回复 ok，不要解释' }],
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max_tokens: 10,
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},
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},
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// 3. Responses - Apimart 当前使用的协议
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{
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name: 'POST /v1/responses (Responses)',
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method: 'POST',
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path: '/v1/responses',
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body: {
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model: 'gpt-4o',
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input: [
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{ role: 'user', content: [{ type: 'input_text', text: '回复 ok，不要解释' }] },
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],
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},
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},
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// 4. 测试 gpt-5 (creative_agent 模型)
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{
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name: 'POST /v1/chat/completions (gpt-5, Chat)',
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method: 'POST',
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path: '/v1/chat/completions',
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body: {
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model: 'gpt-5',
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messages: [{ role: 'user', content: '回复 ok' }],
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max_tokens: 10,
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},
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},
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// 5. 抓大鹅生成需要的 JSON 输出能力验证
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{
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name: 'POST /v1/chat/completions (JSON 输出: 抓大鹅物品)',
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method: 'POST',
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path: '/v1/chat/completions',
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body: {
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model: 'gpt-4o',
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messages: [
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{ role: 'system', content: '你是抓大鹅游戏编辑，只返回 JSON。' },
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{ role: 'user', content: '题材：水果。请生成 JSON：{"gameName":"水果切切乐","items":[{"name":"苹果","itemSize":"中"},{"name":"西瓜","itemSize":"大"}]}' },
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],
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max_tokens: 200,
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},
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},
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];
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let pass = 0;
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let fail = 0;
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for (let i = 0; i < tests.length; i++) {
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const t = tests[i];
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console.log(`[${i + 1}/${tests.length}] ${t.name}`);
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const result = await test(t.name, t.method, t.path, t.body);
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if (result.ok) {
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console.log(` ✅ HTTP ${result.code} ${result.elapsed}ms model: ${result.model}`);
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console.log(` ${result.summary}`);
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pass++;
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} else {
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const codeStr = result.code === 0 ? 'NET' : `HTTP ${result.code}`;
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console.log(` ❌ ${codeStr} ${result.elapsed}ms ${result.error}`);
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fail++;
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}
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console.log();
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}
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console.log(`=== 结果: ${pass}/${tests.length} 通过, ${fail}/${tests.length} 失败 ===`);
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// 结论
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if (pass >= 3) {
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console.log('\n✅ VectorEngine 支持 LLM 文本调用，可替代 Apimart。');
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console.log(' 将 .env.secrets.local 中 APIMART_BASE_URL 改为 VectorEngine 地址即可。');
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} else if (pass <= 1) {
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console.log('\n❌ VectorEngine 不支持 LLM 文本调用。');
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} else {
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console.log('\n⚠️ 部分支持，需进一步评估。');
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}
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