本文へ移動
cccskills
無料GitHub で公開

ci

Guide for testing conventions and CI pipelines — unit tests, integration smoke tests, pytest markers, and GitHub Actions workflows. Use when the user asks about testing, CI, running tests, or adding tests for a recipe.

インストール方法を見る

含まれるファイル(1)

  • SKILL.md4.0 KB

SKILL.md(原文)

インストールする前に、エージェントに与えられる指示の中身を確認できます。

Testing & CI

The repo has two layers of testing and two CI workflows.

Reference

Read these for details:

  • tests/helpers.py — run_recipe() helper for smoke tests
  • tests/conftest.py — Pytest configuration and API key handling
  • tests/recipes/ — Existing recipe smoke tests
  • .github/workflows/pytest.yaml — Unit test CI (every PR)
  • .github/workflows/smoke-test-recipes.yaml — Smoke test CI (daily)
  • CONTRIBUTING.md — Development setup and test commands
  • pyproject.toml — Pytest configuration (testpaths, markers, file patterns)

Test structure

tinker-cookbook/
├── tinker_cookbook/
│   ├── renderers/parsing_test.py     # Unit tests: *_test.py next to source
│   ├── recipes/math_rl/math_env_test.py
│   └── ...
└── tests/
    ├── conftest.py                   # Skips integration tests without API key
    ├── helpers.py                    # run_recipe() helper
    └── recipes/
        ├── test_recipe_chat_sl.py    # Integration tests: test_recipe_*.py
        ├── test_recipe_dpo.py
        └── ...

Unit tests (*_test.py)

Colocated with source code. Run without API key.

uv run pytest tinker_cookbook/

Conventions:

  • File naming: <module>_test.py next to the code it tests
  • No network calls, no TINKER_API_KEY required
  • Fast (< 1s per test)
  • Use standard pytest features (fixtures, parametrize, marks)
  • Test picklability for components used in distributed rollout

Example: tinker_cookbook/renderers/parsing_test.py

Integration / smoke tests (test_recipe_*.py)

Live in tests/recipes/. Require TINKER_API_KEY. Verify recipes can run.

# Run all integration tests
uv run pytest tests/ -v -x -s

# Run a specific recipe test
uv run pytest tests/recipes/test_recipe_chat_sl.py -v -x -s

Conventions:

  • File naming: tests/recipes/test_recipe_<name>.py
  • Mark with @pytest.mark.integration
  • Use run_recipe() from tests/helpers.py
  • run_recipe() passes max_steps=2 by default — recipe runs 2 training steps and exits
  • Always pass behavior_if_log_dir_exists=delete to avoid CI conflicts
  • Override batch sizes to small values for fast execution

Template:

import pytest
from tests.helpers import run_recipe

@pytest.mark.integration
def test_my_recipe():
    run_recipe(
        "tinker_cookbook.recipes.my_recipe.train",
        [
            "behavior_if_log_dir_exists=delete",
            "groups_per_batch=4",
        ],
    )

How run_recipe() works

  1. Launches uv run python -m <module> <args> max_steps=2 as a subprocess
  2. Streams stdout in real time for CI debuggability
  3. Waits for clean exit (exit code 0) within timeout (default: 1800s)
  4. Fails if process exits non-zero or times out

Pytest markers

Defined in pyproject.toml:

  • @pytest.mark.integration — Requires API key, skipped locally without TINKER_API_KEY
  • @pytest.mark.slow — Long-running tests

tests/conftest.py auto-skips integration tests when TINKER_API_KEY is not set (fails on CI if missing).

CI workflows

pytest.yaml — Unit tests (every PR/push to main)

Trigger: push to main, pull requests
Runs: uv run pytest tinker_cookbook/
Requires: HF_TOKEN (for tokenizer access)

smoke-test-recipes.yaml — Integration tests (daily + manual)

Trigger: daily at 6am UTC, manual dispatch
Runs: Each test_recipe_*.py in parallel (matrix strategy)
Requires: TINKER_API_KEY, HF_TOKEN
Timeout: 20 min per recipe
Concurrency: 1 (avoid API contention)

Adding tests/recipes/test_recipe_<name>.py is all that's needed — CI auto-discovers it.

Running pre-commit checks

uv run ruff check tinker_cookbook/
uv run ruff format tinker_cookbook/
uv run pyright tinker_cookbook/
pre-commit run --all-files

レビュー

まだレビューはありません。使ってみた感想をお寄せください。

同じリポジトリのスキル

概要と使いどころ

Guide for checkpointing — saving, loading, and resuming training with CheckpointRecord. Use when the user asks about saving weights, resuming training, checkpoint management, or the checkpoint lifecycle.

日本語の概要は準備中です。原文の説明を表示しています。

uiuc-kang-lab/rlvr_generalization_bounds52026年5月13日 更新

Guide for using completers — TokenCompleter and MessageCompleter for text generation during RL rollouts and evaluation. Use when the user asks about generating text, completing messages, or using completers in RL environments.

日本語の概要は準備中です。原文の説明を表示しています。

uiuc-kang-lab/rlvr_generalization_bounds52026年5月13日 更新

Guide for contributing to the tinker-cookbook repo — development setup, code style, type checking, PR process, and design conventions. Use when the user asks about how to contribute, set up the dev environment, code style, or project conventions.

日本語の概要は準備中です。原文の説明を表示しています。

uiuc-kang-lab/rlvr_generalization_bounds52026年5月13日 更新

datasets

無料

Guide for dataset construction — SupervisedDatasetBuilder, RLDatasetBuilder, ChatDatasetBuilder, and custom dataset creation from JSONL, HuggingFace, or conversation data. Use when the user asks about datasets, data loading, data preparation, or custom data formats.

日本語の概要は準備中です。原文の説明を表示しています。

uiuc-kang-lab/rlvr_generalization_bounds52026年5月13日 更新

Set up and run knowledge distillation (on-policy, off-policy, or multi-teacher) from a teacher model to a student model using the Tinker API. Use when the user wants to distill knowledge, compress models, or train a student from a teacher.

日本語の概要は準備中です。原文の説明を表示しています。

uiuc-kang-lab/rlvr_generalization_bounds52026年5月13日 更新

dpo

無料

Set up and run Direct Preference Optimization (DPO) training on preference datasets using the Tinker API. Use when the user wants to train with preference data, chosen/rejected pairs, or DPO.

日本語の概要は準備中です。原文の説明を表示しています。

uiuc-kang-lab/rlvr_generalization_bounds52026年5月13日 更新

uiuc-kang-lab のスキルをすべて見る

このスキルの問題を報告する