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- Skill optimization framework with training loop analogy - 11 benchmarks, 4 model backends (Azure OpenAI, Claude, Codex, Qwen) - WebUI for browser-based training control - Pluggable architecture for extending benchmarks and backends
Benchmark Template
This directory provides scaffold files for adding a new benchmark to SkillOpt.
Files
env_template.py— Environment adapter templateloader_template.py— Data loader templateconfig_template.yaml— Config file template
Usage
- Copy this directory:
cp -r skillopt/envs/_template skillopt/envs/your_benchmark - Rename files: remove
_templatesuffix - Implement the
TODOsections - Register in
skillopt/envs/__init__.py - Create config at
configs/your_benchmark/default.yaml
See the documentation for the full guide.