docling-project/docling-eval
Dec 2024 – Jan 2025
2 Months active
Languages Used
MarkdownPythonTOML
Technical Skills
Build ConfigurationCode QualityCode RefactoringDependency ManagementDevOpsDocumentation
Nikos Livathinos
PROFILE
Nikos Livathinos
Nli contributed to the docling-project/docling-eval repository by establishing a robust project foundation and enhancing the evaluation pipeline for document layout and text processing. Over two months, Nli set up project scaffolding with Python and TOML-based packaging, integrated DevOps workflows, and improved onboarding through comprehensive documentation. They refactored core components like LayoutEvaluator, introducing explicit type hints and clarifying usage to improve maintainability. Nli also addressed tokenizer reliability in MarkdownTextEvaluator by ensuring NLTK data availability, and streamlined dataset workflows with split-aware processing and improved parameter management. Their work demonstrated depth in build configuration, dataset management, and natural language processing.
Overall Statistics
Feature vs Bugs
80%Features
Repository Contributions
7Total
Bugs
1
Commits
7
Features
4
Lines of code
4,550
Activity Months2
Your Network
26 people
Work History
January 2025
3 Commits • 2 Features
Jan 1, 2025January 2025: Strengthened the docling-eval evaluation pipeline with tokenizer reliability, improved dataset workflow usability, and split-aware processing. Key items include: (1) Tokenizer data bootstrap for MarkdownTextEvaluator—ensured NLTK punkt_tab data is downloaded to enable correct tokenization-based evaluation; (2) Tableformer dataset workflow improvements—clarified PTN/FTN/P1M dataset creation examples, updated image handling to base64 URIs, and refactored dataset creation functions for clearer parameter management; (3) Split-aware evaluation/visualization—added a split argument to the CLI and refactored evaluators to respect train/test/val splits for finer-grained processing.
3 Commits • 2 Features
Jan 1, 2025January 2025: Strengthened the docling-eval evaluation pipeline with tokenizer reliability, improved dataset workflow usability, and split-aware processing. Key items include: (1) Tokenizer data bootstrap for MarkdownTextEvaluator—ensured NLTK punkt_tab data is downloaded to enable correct tokenization-based evaluation; (2) Tableformer dataset workflow improvements—clarified PTN/FTN/P1M dataset creation examples, updated image handling to base64 URIs, and refactored dataset creation functions for clearer parameter management; (3) Split-aware evaluation/visualization—added a split argument to the CLI and refactored evaluators to respect train/test/val splits for finer-grained processing.
January 2025
December 2024
4 Commits • 2 Features
Dec 1, 2024December 2024 focused on establishing a solid foundation for docling-eval and improving code quality, maintainability, and developer onboarding. The work delivered a capable project scaffold with packaging, licensing, and contribution guidelines, plus targeted enhancements to LayoutEvaluator with explicit type hints and clearer usage documentation. A configuration stabilization effort fixed packaging details in pyproject.toml, enabling reliable development and distribution. No critical bugs were surfaced this month; the groundwork now supports faster feature delivery and clearer ownership across the repository.
December 2024
4 Commits • 2 Features
Dec 1, 2024December 2024 focused on establishing a solid foundation for docling-eval and improving code quality, maintainability, and developer onboarding. The work delivered a capable project scaffold with packaging, licensing, and contribution guidelines, plus targeted enhancements to LayoutEvaluator with explicit type hints and clearer usage documentation. A configuration stabilization effort fixed packaging details in pyproject.toml, enabling reliable development and distribution. No critical bugs were surfaced this month; the groundwork now supports faster feature delivery and clearer ownership across the repository.
Activity
Loading activity data...
Quality Metrics
Correctness91.4%
Maintainability94.2%
Architecture88.6%
Performance82.8%
AI Usage20.0%
Skills & Technologies
Programming Languages
MarkdownPythonTOML
Technical Skills
Build ConfigurationCLI DevelopmentCode QualityCode RefactoringData EvaluationData ProcessingDataset ManagementDependency ManagementDevOpsDocumentationNatural Language ProcessingProject SetupPython DevelopmentScriptingType Hinting
Repositories Contributed To
Overview of all repositories you've contributed to across your timeline