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Abhijit Balaji
6c94c4d9ca
Established a Pareto-ready evaluation foundation for the Genetic-Pareto (GEPA)
optimizer, supporting simultaneous optimization of accuracy and density.
Key improvements:
- Core Architecture: Defined standardized `MetricResult` and `OptimizationDirection`
types in `packages/core/src/evals/types.ts` to support multi-objective fitness.
- Centralized Config: Implemented `packages/core/src/evals/config.ts` with tunable
weights and detailed documentation for scoring gradients.
- Tool Alignment Metric: Created `metrics/toolAlignment.ts` to measure functional
accuracy, argument precision, and explicit shell avoidance.
- Token Frugality Metric: Created `metrics/tokenFrugality.ts` to measure and
penalize conversational noise ("chatter") using a configurable threshold.
- Verification Suite: Added comprehensive unit tests for all metrics, achieving
100% coverage of scoring logic and gradient steps.
- Project Integration: Relocated `schema.ts` to the core package for build safety,
updated the data validator, and extended project-wide lint/format scripts.