base-model/src, branch v0.1.7 BaseModel for HydroRoll https://git.hydroroll.team/base-model/atom?h=v0.1.7 2026-01-05T06:33:37Z feat: add max_length validation in TRPGParser to enforce input constraints 2026-01-05T06:33:37Z HsiangNianian i@jyunko.cn 2026-01-05T06:33:37Z urn:sha1:753119374a952cac55a0d87c13e5ae081e09de4b feat: update max_length parameter for TRPGParser and onnx_infer to improve text parsing capabilities 2026-01-05T06:33:10Z HsiangNianian i@jyunko.cn 2026-01-05T06:33:10Z urn:sha1:df94eb6c125279a9c32bc85de8633371d50afbed refactor: Clean up publish workflow by removing Test PyPI steps and improving artifact packaging 2025-12-30T12:54:06Z HsiangNianian i@jyunko.cn 2025-12-30T12:54:06Z urn:sha1:18c946aac2b0e16ec4e66bb4c40c62403af6f205 feat: Enhance model download functionality to support zip file retrieval and extraction 2025-12-30T12:49:12Z HsiangNianian i@jyunko.cn 2025-12-30T12:49:12Z urn:sha1:a4dd04f6e3af86ce3f96c7f7ebc88e195db366f4 feat: Bump version to 0.1.3 in pyproject.toml and __init__.py 2025-12-30T12:43:06Z HsiangNianian i@jyunko.cn 2025-12-30T12:43:06Z urn:sha1:3ce2bae75f9e3c2a7e3e3ee4576961bcde98965b refactor: Update model download functionality and improve inference module to support automatic model retrieval from GitHub releases 2025-12-30T12:39:34Z HsiangNianian i@jyunko.cn 2025-12-30T12:39:34Z urn:sha1:298035052b3e3d083b57f5dbac0e86de4f94efba refactor: Refactor TRPG NER model SDK: restructure codebase into base_model_trpgner package, implement training and inference modules, and add model download functionality. Remove legacy training and utils modules. Enhance documentation and examples for better usability. 2025-12-30T12:16:05Z HsiangNianian i@jyunko.cn 2025-12-30T12:16:05Z urn:sha1:5dd166366b8a2f4699c1841ebd7fceabcd9868a4 feat: Refactor and enhance TRPG NER model SDK 2025-12-30T11:54:08Z HsiangNianian i@jyunko.cn 2025-12-30T11:54:08Z urn:sha1:575114661ef9afb95df2a211e1d8498686340e6b - Removed deprecated `word_conll_to_char_conll.py` utility and integrated its functionality into the new `utils` module. - Introduced a comprehensive GitHub Actions workflow for automated publishing to PyPI and GitHub Releases. - Added `__init__.py` files to establish package structure for `basemodel`, `inference`, `training`, and `utils` modules. - Implemented model downloading functionality in `download_model.py` to fetch pre-trained ONNX models. - Developed `TRPGParser` class for ONNX-based inference, including methods for parsing TRPG logs. - Created training utilities in `training/__init__.py` for NER model training with Hugging Face Transformers. - Enhanced utility functions for CoNLL file parsing and dataset creation. - Added command-line interface for converting CoNLL files to datasets with validation options. feat: Implement TRPG NER training and inference script with robust model path detection and enhanced timestamp/speaker handling 2025-12-30T11:14:39Z HsiangNianian i@jyunko.cn 2025-12-30T11:14:39Z urn:sha1:7ac684f1f82023c6284cd7d7efde11b8dc98c149 - Added main training and inference logic in main.py, including CoNLL parsing, tokenization, and model training. - Introduced TRPGParser class for inference with entity aggregation and special handling for timestamps and speakers. - Developed utility functions for converting word-level CoNLL to char-level and saving datasets in various formats. - Added ONNX export functionality for the trained model. - Created a comprehensive requirements.txt and updated pyproject.toml with necessary dependencies. - Implemented tests for ONNX inference to validate model outputs.