界面已本地化;技能介绍与说明文档按所选语言由 AI 自动翻译,代码、命令、路径和专业术语保留原文,以原作者文档为准。
探索技能
数据与研究 · SKILL.md

cli-and-project-ops

cli-and-project-ops

【数据与研究】Guides the PandasAI pai CLI, login and dataset-create commands, API-key validation, project-root behavior, and lightweight repo maintenance operations.

独立 GitHub 快照 · 自动分类 · 以原作者文档为准

技能说明

GitHub

name: cli-and-project-ops description: "Guides the PandasAI pai CLI, login and dataset-create commands, API-key validation, project-root behavior, and lightweight repo maintenance operations." disable-model-invocation: true metadata: disco-role: operating license: NOASSERTION

CLI and Project Ops

Use this sub-skill when a task involves the pai command, PandaBI API-key login, guided CLI dataset creation, project-root/datasets layout, or maintainer commands for a PandasAI checkout.

Fast route

  1. Verify the CLI is importable and visible:

    pai --help
    pai dataset --help
    
  2. For login, validate the key format before writing .env:

    pai login PAI-xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx
    
  3. For interactive dataset creation, run from the intended project root because .env and datasets/ paths are resolved relative to project-root discovery.

  4. For programmatic schema creation or debugging, route to ../semantic-layer/SKILL.md.

  5. For source-code edits or tests, use the maintainer notes and choose focused tests instead of all extension targets unless the user needs them.

Read next

Boundaries

Safe validation

python sub-skills/cli-and-project-ops/scripts/pai_cli_smoke.py --show-help
python sub-skills/cli-and-project-ops/scripts/pai_cli_smoke.py --check-api-key PAI-59ca2c4a-7998-4195-81d1-5c597f998867
python sub-skills/cli-and-project-ops/scripts/pai_cli_smoke.py --isolated-login-smoke

The smoke uses Click's isolated runner and a fake valid-format key. It never uses real credentials.

Common gotchas

  • CLI import can fail if click is missing from the active environment.
  • pai login writes or updates PANDABI_API_KEY in .env under the detected project root and preserves unrelated variables.
  • pai dataset create is interactive. Automate it only with an isolated test runner or a deliberate input stream.
  • Dataset path validation is the same lowercase hyphenated organization/dataset contract used by the semantic layer.
  • Full extension tests can install many optional packages; prefer focused tests when validating a small source change.
我的收藏