feat: add model card packaging

[marcellodebernardi]

This PR adds automatic model card generation during packaging, producing a MODEL_CARD.md artifact with summary, dataset details, feature usage, evaluation highlights, hyperparameters, limitations, and reproducibility metadata. The aim is to make packaged models self-documenting and easier to review and deploy. It also adds unit tests covering both full-context and minimal-context generation flows.

Testing

• poetry run pytest tests/unit/workflow/test_model_card.py
• poetry run pytest tests/unit/test_imports.py

[greptile-apps]

Greptile Summary

This PR adds automatic model card generation during the packaging phase, producing a comprehensive MODEL_CARD.md artifact with model metadata, dataset details, feature usage, performance metrics, and reproducibility information.

Key changes:

• Implemented generate_model_card() function with robust error handling, fallbacks for missing data, and support for various input formats
• Integrated model card generation into the packaging workflow (Phase 6) to retrieve evaluation report from context.scratch and write MODEL_CARD.md
• Added comprehensive unit tests covering both full-context and minimal-context generation flows
• Version bumped to 1.3.3

Code quality:

• Defensive programming with comprehensive None checking and exception handling for file I/O
• Proper use of yaml.safe_load() for security
• Type hints throughout
• Clean integration following existing workflow patterns

Confidence Score: 5/5

• This PR is safe to merge with no critical issues
• The implementation is well-designed with comprehensive error handling, proper security practices, and thorough test coverage. No logical errors, security vulnerabilities, or critical bugs were found. The code follows defensive programming principles with fallbacks for missing data and uses safe YAML loading. Integration into the existing workflow is clean and follows established patterns.
• No files require special attention

Important Files Changed

Filename	Overview
plexe/templates/packaging/model_card_template.py	added comprehensive model card generator with robust error handling and fallbacks
plexe/workflow.py	integrated model card generation into packaging phase with proper data flow
tests/unit/workflow/test_model_card.py	added comprehensive tests covering full-context and minimal-context scenarios

_{Last reviewed commit: 7109c9a}

[greptile-apps]

_{6 files reviewed, 1 comment}

_{Edit Code Review Agent Settings | Greptile}

[marcellodebernardi]

@greptileai review again with latest changes

[Copilot]

Pull request overview

This PR introduces automatic generation of a MODEL_CARD.md artifact during the model packaging workflow, aiming to make packaged models self-documenting and easier to review/deploy.

Changes:

• Add a model card generator that composes Markdown from packaged artifacts (model.yaml, input schema, hyperparameters) plus optional evaluation outputs.
• Integrate model card generation into package_final_model() so MODEL_CARD.md is written into the packaged model directory.
• Add unit tests covering full-context vs minimal-context model card generation paths, and update test/code index docs.

Reviewed changes

Copilot reviewed 7 out of 7 changed files in this pull request and generated 4 comments.

Show a summary per file

File	Description
plexe/workflow.py	Calls the model card generator during packaging and writes MODEL_CARD.md into the package.
plexe/templates/packaging/model_card_template.py	Implements the Markdown model card generator and supporting helpers.
tests/unit/workflow/test_model_card.py	Adds unit tests validating headers/sections and minimal fallback behavior.
tests/unit/workflow/__init__.py	Adds workflow unit test package marker/docstring.
tests/CODE_INDEX.md	Regenerates test code index to include new workflow test module.
plexe/CODE_INDEX.md	Regenerates plexe code index to include the new packaging template module.

---

💡 Add Copilot custom instructions for smarter, more guided reviews. Learn how to get started.

[marcellodebernardi]

@greptileai please review again with latest changes

[marcellodebernardi]

@greptileai review again with latest changes

[marcellodebernardi]

@greptileai please review again with latest changes