Context
The DS-Star / MLE-Star notebook series (Day5-DS-Star, Day6-MLE-Star in ML/DataScienceWithAgents/AgenticDataScience/) currently implements the DS-Star concept based on an independent reimplementation, likely from https://github.com/JulesLscx/DS-Star.
IBM has now released OpenDsStar, an official open-source implementation of the DeepMind DS-Star publication (which was published without code):
Task
-
Compare both implementations:
- Architecture quality, code maturity, test coverage
- Completeness vs the original DeepMind paper
- API design and extensibility
- Documentation quality
-
Evaluate integration opportunity:
- Can IBM's OpenDsStar replace the current DS-Star code in our notebooks?
- What would need to change in Lab10, Lab11, Lab12 (Day5-DS-Star)?
- What about Lab13-Lab16 (Day6-MLE-Star)?
-
Decision criteria:
- IBM's implementation is likely more robust (corporate backing, peer review)
- But verify: does it cover the same scope as our current notebooks?
- Migration effort vs quality gain
Affected notebooks
ML/DataScienceWithAgents/AgenticDataScience/Day5-DS-Star/Lab10-File-Analyzer.ipynb
ML/DataScienceWithAgents/AgenticDataScience/Day5-DS-Star/Lab11-Planner-Coder-Loop.ipynb
ML/DataScienceWithAgents/AgenticDataScience/Day5-DS-Star/Lab12-DS-Star-Workshop.ipynb
ML/DataScienceWithAgents/AgenticDataScience/Day6-MLE-Star/Lab13-Web-Search-SOTA.ipynb
ML/DataScienceWithAgents/AgenticDataScience/Day6-MLE-Star/Lab14-Ablation-Refinement.ipynb
ML/DataScienceWithAgents/AgenticDataScience/Day6-MLE-Star/Lab15-MLE-Star-Paper.ipynb
ML/DataScienceWithAgents/AgenticDataScience/Day6-MLE-Star/Lab16-MLE-Star-Workshop.ipynb
Context
The DS-Star / MLE-Star notebook series (Day5-DS-Star, Day6-MLE-Star in
ML/DataScienceWithAgents/AgenticDataScience/) currently implements the DS-Star concept based on an independent reimplementation, likely from https://github.com/JulesLscx/DS-Star.IBM has now released OpenDsStar, an official open-source implementation of the DeepMind DS-Star publication (which was published without code):
Task
Compare both implementations:
Evaluate integration opportunity:
Decision criteria:
Affected notebooks
ML/DataScienceWithAgents/AgenticDataScience/Day5-DS-Star/Lab10-File-Analyzer.ipynbML/DataScienceWithAgents/AgenticDataScience/Day5-DS-Star/Lab11-Planner-Coder-Loop.ipynbML/DataScienceWithAgents/AgenticDataScience/Day5-DS-Star/Lab12-DS-Star-Workshop.ipynbML/DataScienceWithAgents/AgenticDataScience/Day6-MLE-Star/Lab13-Web-Search-SOTA.ipynbML/DataScienceWithAgents/AgenticDataScience/Day6-MLE-Star/Lab14-Ablation-Refinement.ipynbML/DataScienceWithAgents/AgenticDataScience/Day6-MLE-Star/Lab15-MLE-Star-Paper.ipynbML/DataScienceWithAgents/AgenticDataScience/Day6-MLE-Star/Lab16-MLE-Star-Workshop.ipynb