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.
中文简介正在准备中。当前显示原文说明。
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.
中文简介正在准备中。当前显示原文说明。
安装前可以查看交给 AI 代理的指令内容。
The repo has two layers of testing and two CI workflows.
Read these for details:
tests/helpers.py — run_recipe() helper for smoke teststests/conftest.py — Pytest configuration and API key handlingtests/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 commandspyproject.toml — Pytest configuration (testpaths, markers, file patterns)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
└── ...
*_test.py)Colocated with source code. Run without API key.
uv run pytest tinker_cookbook/
Conventions:
<module>_test.py next to the code it testsTINKER_API_KEY requiredExample: tinker_cookbook/renderers/parsing_test.py
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:
tests/recipes/test_recipe_<name>.py@pytest.mark.integrationrun_recipe() from tests/helpers.pyrun_recipe() passes max_steps=2 by default — recipe runs 2 training steps and exitsbehavior_if_log_dir_exists=delete to avoid CI conflictsTemplate:
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",
],
)
run_recipe() worksuv run python -m <module> <args> max_steps=2 as a subprocessDefined in pyproject.toml:
@pytest.mark.integration — Requires API key, skipped locally without TINKER_API_KEY@pytest.mark.slow — Long-running teststests/conftest.py auto-skips integration tests when TINKER_API_KEY is not set (fails on CI if missing).
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.
uv run ruff check tinker_cookbook/
uv run ruff format tinker_cookbook/
uv run pyright tinker_cookbook/
pre-commit run --all-files
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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.
中文简介正在准备中。当前显示原文说明。
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.
中文简介正在准备中。当前显示原文说明。
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.
中文简介正在准备中。当前显示原文说明。
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.
中文简介正在准备中。当前显示原文说明。
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.
中文简介正在准备中。当前显示原文说明。
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.
中文简介正在准备中。当前显示原文说明。