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https://github.com/modelstudioai/cli.git
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69 lines
2.1 KiB
JavaScript
69 lines
2.1 KiB
JavaScript
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#!/usr/bin/env node
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/**
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* `text chat` 并发压测。
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*/
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import { defineStressTarget } from "../lib/define-stress-target.mjs";
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import { parseTextChatResult, extractError } from "../lib/parsers.mjs";
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import { escapeHtml, escapeTableCell, getErrorMessage } from "../lib/report.mjs";
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const snippets = [
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"用两句话解释机器学习。",
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"列举三个节能习惯。",
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"写一首五言绝句，主题为春雨。",
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"什么是 REST API？",
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"简述 TypeScript 与 JavaScript 的区别。",
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];
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export const runStress = defineStressTarget({
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canonical: "text",
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defaultModel: "qwen3.6-plus",
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batchDirPrefix: "text-chat-batch",
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helpText: "pnpm run test:stress -- text -- --count 20 --concurrency 5",
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defaultTimeoutMs: 120_000,
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minTimeoutMs: 10_000,
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defaultRateLimitMax: 10,
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defaultRateLimitWindowMs: 1000,
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defaultRetryBaseMs: 3000,
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defaultMaxRetries: 3,
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generatePrompt: (idx) =>
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`${snippets[idx % snippets.length]} [run-${idx}-${Date.now().toString(36)}]`,
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buildCliArgs: ({ MODEL, prompt, CLI_TIMEOUT_SEC }) => [
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"text",
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"chat",
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"--model",
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MODEL,
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"--message",
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prompt,
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"--output",
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"json",
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"--timeout",
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String(CLI_TIMEOUT_SEC),
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],
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parseStdout: (stdout) => Promise.resolve(parseTextChatResult(stdout)),
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reportSpec: {
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titleMd: "文本对话批量压测报告（text chat）",
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titleHtml: "文本对话批量压测报告（text chat）",
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promptColumnMd: "Message",
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promptColumnHtml: "Message",
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outcomeColumnMd: "回复摘要 / 错误信息",
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outcomeColumnHtml: "回复摘要 / 错误信息",
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formatOutcomeMd: (r) => {
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if (r.status === "success") {
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return escapeTableCell(String(r.replyTextPreview ?? "").slice(0, 500));
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}
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return escapeTableCell(getErrorMessage(r, extractError));
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},
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formatOutcomeHtml: (r) => {
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if (r.status === "success") {
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return `<code class="path">${escapeHtml(String(r.replyTextPreview ?? "").slice(0, 800))}</code>`;
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}
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return `<span class="outcome-error">${escapeHtml(getErrorMessage(r, extractError))}</span>`;
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},
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},
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});
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