CharlesYang030
244e346b83
- 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
42 lines
675 B
Plaintext
42 lines
675 B
Plaintext
__pycache__/
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*.pyc
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*.egg-info/
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build/
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dist/
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site/
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data/
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outputs/
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logs/
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external/
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/BabyVision/
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/MMRB/
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/SpreadsheetBench/
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/dl4ir-searchQA/
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configs/local/
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configs/**/*.local.yaml
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*.local.md
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*.secret.md
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*.bak
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.env
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.secrets/
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.codex_azure*/
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# Internal docs (not for open-source release)
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docs/ablation_plan.md
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docs/ablation_paper_tables.md
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docs/ablation_paper_tables.html
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docs/experiment_commands.md
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docs/slow_update_flowchart.md
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docs/session_memory.md
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docs/harness_fresh_machine_handoff.md
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docs/harness_monitoring_memory.md
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docs/harness_reproduction_secrets.secret.md
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docs/reflact_conda_env_export.yml
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docs/reflact_overview.html
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docs/render_ablation_paper_tables.py
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docs/让*
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