* feat(run_eval): add checkpoint resume functionality and update example documentation;
- update new bootcamp benchmark dataset
* refactor(data_pipeline): optimize data generation pipeline; add multiple preset configurations for data generation
* docs: update bootcamp list and add new scripts
- Update Fulllist_InternBootcamp.md with new bootcamps and categories
- Add new scripts to .gitignore:
- examples/pipelines/filter_autogen_configs.py
- examples/pipelines/quickgen_data_configs_from_eval_meta.py
- Update dependencies in setup.py:
- Add scipy and scikit-learn
* refactor(internbootcamp): update bootcamp modules and improve error handling
- Update import statements in __init__.py files
- Add timestamp to target directory name in verl_data_preprocess.py
- Improve error handling and scoring logic in bootcamp_judger.py
- Remove unnecessary comments and update puzzle descriptions in multiple files
- Commented out all DEBUG print statements in circuit.py
- Commented out all DEBUG print statements in libcircuit.py
- Added pass statements where necessary to prevent syntax errors
- Reduce the number of generated InChIs and SMILES from 10 to 1
- Remove random selection, always return the first generated structure
- Comment out debug prints and unused code
- Add random selection of InChI and SMILES strings
- Implement relative error-based scoring for logP prediction
- Update verification functions to return scores instead of boolean
- Refactor InChI and SMILES generation for better randomness
