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gherkai

用 Gherkin .feature 写 UI 端到端测试,交给 AI 浏览器引擎(Nova Act 或 Midscene)在云端浏览器里操作页面、判定断言。本包是 gherkai 的命令行入口:解析 .feature、按 tag 分组成可并发的 job、派给引擎执行、汇总每条用例的判定与报告。测试在你自己的 AWS 账户里运行,会产生真实 AWS 费用,金额以你的 AWS 账单为准。

安装

uv tool install gherkai                # 命令行本体,需 Python ≥ 3.13
uv tool install 'gherkai[local]'       # 附带在本机运行 Nova Act 引擎所需的 worker
npm i -g @gherkai/worker-midscene      # 在本机运行 Midscene 引擎所需的 worker,需 Node ≥ 22

Midscene worker 与命令行须是同一个版本:用 gherkai --version 查版本号,再装 npm i -g @gherkai/worker-midscene@<版本号>。

最小用法

export AWS_REGION=us-east-1               # region 必须有出处:--region、环境变量或 profile 配置
gherkai doctor                            # 自检环境;加 --backend cloud 连带查凭证与云端后端
gherkai plan features/checkout.feature    # 用例预检:分组与派发预期,不连云端、不产生费用
gherkai run features/checkout.feature     # 在本机起 worker 执行这个 run(浏览器与模型仍在云端);退出码给出判定
gherkai explain <run_id>                  # 读这个 run 的每步证据,看断言为什么这么判

全部命令与选项以 gherkai --help、gherkai <命令> --help 为准。plan、run、status、explain、doctor 等命令都支持 --json,便于脚本与 CI 解析。

用 AI agent(如 Claude Code、Codex)操作 gherkai 的话,先执行 gherkai skill install 把使用说明装进你的项目,之后直接告诉 agent 要测什么。

文档

项目主页与问题反馈:https://github.com/zhiyanliu/gherkai#readme

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