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Description
Description：Ianvs serves as KubeEdge SIG AI distributed benchmark toolkit. As more and more contributors running, KubeEdge Ianvs now has 25 examples and the number is still increasing. KubeEdge Ianvs then faces mounting usability issues due to dependency evolution and validation mechanisms. As Python versions, third-party libraries, and Ianvs features advance, partial historical examples fail to execute. This has led to surging user-reported Issues from confused contributors, untested PRs breaking core functionality of legacy features, severely outdated documentation misaligning with actual capabilities. Without systematic intervention, the example risks becoming obsolete for edge-AI developers and especially newcomers. We then try to resurrect Ianvs’ usability with comprehensive example restoration.
Expected Outcome：
- Diagnose & fix bugs across examples, including dependency manifests, license scan and runtime configurations.
- Documentation Modernization, including revamp tutorials with reproducible step-by-step guides, publish developer-focused debugging playbooks for common failures
- Build a CI pipeline testing examples with GitHub Actions against multiple Python versions, critical Ianvs/upstream updates and block PRs that break validated examples
Recommended Skills： Python, Benchmark, KubeEdge-Ianvs, AI/ML