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TrustLens v0.2.0 — Stability & Production Release

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@Khanz9664 Khanz9664 released this 24 Apr 09:12
· 88 commits to main since this release
v0.2.0
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🚀 TrustLens v0.2.0 — Codebase Stabilization & Contributor Experience Upgrade

This release focuses on strengthening the foundation of TrustLens—improving stability, clarity, and contributor experience—without introducing breaking changes.

Highlights

Stabilized Core Pipeline

  • Refined the ML evaluation pipeline to focus strictly on production-ready modules:

    • Calibration
    • Failure Analysis
    • Bias Detection
    • Representation Analysis

  • Ensured consistent behavior across analyze() and quick_analyze()

Experimental Module Isolation

  • Clearly separated experimental features (Explainability & Faithfulness) from the core pipeline

  • Introduced docs/EXPERIMENTAL.md:

    • Defines experimental modules
    • Provides contributor guidelines
    • Establishes promotion criteria for future integration

  • Preserved full importability without exposing unstable features in the public API

Stronger Developer Guardrails

  • Added a Pipeline Module Registry in api.py

  • Includes a checklist for safely introducing new modules:

    • dependency validation
    • API readiness
    • test coverage
    • maintainer approval

Improved Documentation & Onboarding

  • Updated CONTRIBUTING.md with:

    • dedicated Experimental Features section
    • clearer contribution flow

  • Enhanced README:

    • improved positioning (ML-first focus)
    • transparent note on experimental modules

  • Cleaned up project structure documentation

Example & Consistency Fixes

  • Renamed and aligned examples to reflect actual ML usage
  • Improved clarity for new users exploring the library

Quality & Verification

  • ✔ 118 tests passing
  • ✔ 73% code coverage (above threshold)
  • ✔ All pre-commit checks passing (lint, format, type-check)
  • ✔ No breaking changes

What This Means

TrustLens is now:

  • more reliable for real-world ML evaluation
  • easier to contribute to with clear guidelines
  • better structured for future feature expansion

Acknowledgements

Thanks to all contributors helping improve TrustLens and push it forward 🚀

Installation

pip install trustlens==0.2.0

What’s Next

Future releases will focus on:

  • advanced model comparison
  • drift detection
  • exportable trust reports

Stay tuned 👀

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