快速开始

自然语言 E2E 测试，确定性回放 —— LLM 只规划一次，回放无需它参与。

用纯自然语言描述一个测试 —— “以测试账户登录，把商品 X 加入购物车，结账并验证订单确认信息” —— Windup 就会把它变成一份确定性的浏览器操作 JSON 计划。从第二次运行起，测试以零 LLM 调用回放：~1 秒、$0，结果稳定。

npm i -D windupjs        # Chromium is provisioned automatically (one-time, machine-wide cache)
npx windup init          # 3 questions → windup.config.ts + example scenario
npx windup scan          # index your app's routes & elements from source code
npx windup new "log in as admin and create an invoice"   # LLM-assisted scenario authoring
npx windup run checkout  # 1st run: the LLM plans · every run after: ~1s replay, $0

环境要求

• Node ≥ 20。
• 在 .env.local 或 .env 中为规划器 LLM 准备一个 API 密钥（.env.local 优先 —— 当你的 .env 已提交到仓库时用它）：Google（默认）用 GOOGLE_GENERATIVE_AI_API_KEY，OpenAI 用 OPENAI_API_KEY。

密钥仅用于规划；缓存回放从不调用 LLM。若要使用已有的 Chrome 而非自动下载的 Chromium，设置 CHROME_PATH；若要完全跳过下载，设置 PLAYWRIGHT_SKIP_BROWSER_DOWNLOAD=1。

五分钟上手

在一个全新项目上的完整工作流，以及你应当看到的结果：

# 1. Install — Chromium is provisioned automatically
npm i -D windupjs

# 2. Initialize — 3 questions (base URL, model, scenarios dir)
npx windup init
#    → windup.config.ts + e2e/scenarios/ + .windup/ (gitignored)

# 3. Index your app from source — before anything ever runs
npx windup scan
#    scan complete (full): framework=react-router routes=106 elements=1125
#    The site map now knows your real routes and selectors; the planner
#    will use them instead of guessing. Re-run after big changes
#    (windup scan --update re-indexes only files changed since, via git).

# 4. Register test credentials once — values never touch git
npx windup secret set admin        # hidden prompts → .env.local + mapping

# 5. Author a scenario from a rough instruction
npx windup new "log in with the admin account and create an invoice for ACME"
#    → e2e/scenarios/create-invoice-acme.json — precise task grounded in
#      your real screens, account referenced by name, final verification

# 6. First run — the LLM plans once (~3s, ~$0.002)
npx windup run create-invoice-acme
#    PASS  create-invoice-acme  cache=miss llm_calls=1 ... cost=$0.0024

# 7. Every run after — deterministic replay, zero LLM
npx windup run create-invoice-acme
#    PASS  create-invoice-acme  cache=hit llm_calls=0 total=600ms cost=$0

# 8. Read results like a human, ship reports to CI
npx windup run --all --summary --reporter html
npx windup costs                   # AI spend: totals, per provider/model

如果某次运行在应用变更后失败，缓存的计划会失效，并在下一次运行时自动重新规划 —— 你编辑的是场景，而非选择器。