Contributing

贡献指南 / Contributing

中文

当你准备向 DomainPostTrain 提交代码、数据或文档变更时，使用本页。

贡献边界

保持仓库领域中立。不要加入：

• 专有客户数据
• 真实凭据或 token
• 私有 URL
• 内部 system prompt
• 产品专属语料
• 许可证受限训练数据

开源前先检查 data/、configs/、outputs/、models/ 和 Wiki 示例，确认没有泄露私有信息。

推荐检查

运行：

python -m compileall pipeline scripts
python scripts/training/train_pipeline.py --config configs/domain_post_training.yaml --smoke_test --device cpu

如果因为本机缺少 ML 依赖无法运行 smoke test，请说明：

• 精确失败原因
• 已运行的静态检查
• 环境限制，例如无 CUDA 或缺少包管理器

文档变更规则

修改行为时：

1. 只有项目高层行为或最快启动方式变化时，才更新 README.md。
2. 配置语义变化时，更新 configs/README.md。
3. 用户流程、排障或发布方式变化时，更新 .wiki/ 页面。
4. JSON/JSONL 行契约变化时，更新 Data-Contracts.md。
5. 修复的问题仍可能影响旧版本或常见环境时，更新 Troubleshooting.md。

GRPO 变更的测试预期

至少运行：

py -m unittest tests.test_grpo_core
py -m compileall pipeline scripts tests

GRPO reward judge 变更应覆盖：

• 配置校验
• judge disabled 行为
• judge enabled builder 行为
• JSON score 解析
• score clamp
• 不记录敏感密钥的元数据

安全报告

安全问题请遵循 SECURITY.md：打开 private advisory 或直接联系维护者，并提供复现步骤、预期影响和已验证的安全缓解方案。

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English

Use this page when preparing code, data, or documentation changes for DomainPostTrain.

Contribution Boundary

Keep the repository domain-neutral. Do not add:

• proprietary customer data
• real credentials or tokens
• private URLs
• internal system prompts
• product-specific corpora
• license-restricted training data

Before open-sourcing, check data/, configs/, outputs/, models/, and Wiki examples to avoid leaking private information.

Recommended Checks

Run:

python -m compileall pipeline scripts
python scripts/training/train_pipeline.py --config configs/domain_post_training.yaml --smoke_test --device cpu

If the smoke test cannot run because the local machine lacks ML dependencies, include:

• the exact failure reason
• the static checks you did run
• any environment constraints, such as no CUDA or missing package manager

Documentation Changes

When changing behavior:

1. Update README.md only for high-level project behavior or fastest-start guidance.
2. Update configs/README.md when config semantics change.
3. Update .wiki/ pages when user procedures, troubleshooting, or publishing guidance changes.
4. Update Data-Contracts.md when any JSON/JSONL row contract changes.
5. Update Troubleshooting.md when a fixed bug can still affect older versions or common setups.

Test Expectations for GRPO Changes

At minimum, run:

py -m unittest tests.test_grpo_core
py -m compileall pipeline scripts tests

GRPO reward judge changes should cover:

• config validation
• disabled judge behavior
• enabled judge builder behavior
• JSON score parsing
• score clamping
• secret-free metadata

Security Reports

For security issues, follow SECURITY.md: open a private advisory or contact the maintainer directly, and include reproduction steps, expected impact, and any safe mitigation already tested.