SkillOpt v0.1.0: initial release
- 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
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# SkillOpt default configuration — base for all environments.
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# Environment configs should inherit via: _base_: default.yaml
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model:
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backend: azure_openai
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teacher: gpt-5.5
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student: gpt-5.5
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teacher_backend: openai_chat
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student_backend: openai_chat
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reasoning_effort: medium
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rewrite_reasoning_effort: ""
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rewrite_max_completion_tokens: 64000
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codex_exec_path: codex
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codex_exec_sandbox: workspace-write
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codex_exec_profile: ""
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codex_exec_full_auto: false
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codex_exec_reasoning_effort: none
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codex_exec_use_sdk: auto
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codex_exec_network_access: false
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codex_exec_web_search: false
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codex_exec_approval_policy: never
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claude_code_exec_path: claude
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claude_code_exec_profile: ""
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claude_code_exec_use_sdk: auto
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claude_code_exec_effort: medium
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claude_code_exec_max_thinking_tokens: 16384
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codex_trace_to_teacher: true
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azure_openai_endpoint: "" # e.g. "https://your-resource.openai.azure.com/"
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azure_openai_api_version: "2024-12-01-preview"
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azure_openai_api_key: "" # Fill locally if you do not export AZURE_OPENAI_API_KEY
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azure_openai_auth_mode: azure_cli
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azure_openai_ad_scope: "https://cognitiveservices.azure.com/.default"
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azure_openai_managed_identity_client_id: ""
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teacher_azure_openai_endpoint: "" # e.g. "https://your-resource.openai.azure.com/"
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teacher_azure_openai_api_version: "2024-12-01-preview"
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teacher_azure_openai_api_key: ""
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teacher_azure_openai_auth_mode: azure_cli
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teacher_azure_openai_ad_scope: "https://cognitiveservices.azure.com/.default"
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teacher_azure_openai_managed_identity_client_id: ""
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student_azure_openai_endpoint: "" # e.g. "https://your-resource.openai.azure.com/"
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student_azure_openai_api_version: "2024-12-01-preview"
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student_azure_openai_api_key: ""
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student_azure_openai_auth_mode: azure_cli
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student_azure_openai_ad_scope: "https://cognitiveservices.azure.com/.default"
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student_azure_openai_managed_identity_client_id: ""
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train:
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num_epochs: 4
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train_size: 0 # 0 = derive from dataset split when available
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batch_size: 40
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accumulation: 1
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seed: 42
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gradient:
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minibatch_size: 8
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merge_batch_size: 8
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analyst_workers: 16
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max_analyst_rounds: 3
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failure_only: false
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use_deep_reflect: false
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deep_reflect_failures: 4
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deep_reflect_successes: 2
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optimizer:
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learning_rate: 4 # max edits per step (edit_budget)
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min_learning_rate: 2 # min edits for decay schedulers
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lr_scheduler: cosine # constant / linear / cosine / autonomous
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lr_control_mode: fixed # fixed / autonomous / none
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skill_update_mode: patch # patch / rewrite_from_suggestions / full_rewrite_minibatch
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use_meta_reflect: false
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meta_learning_rate: 4 # max edits per epoch-level meta-reflect
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use_slow_update: true
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slow_update_samples: 20
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longitudinal_pair_policy: mixed # mixed / changed / unchanged
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use_meta_skill: true
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evaluation:
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use_gate: true
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sel_env_num: 0
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test_env_num: 0
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eval_test: true
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env:
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name: ""
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skill_init: ""
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split_mode: ratio # ratio = build deterministic split from data_path; split_dir = use pre-split train/val/test
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split_ratio: "2:1:7" # explicit default for dataset-backed benchmarks: train:val:test
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split_seed: 42
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split_dir: ""
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data_path: ""
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split_output_dir: ""
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exec_timeout: 120 # per student model/code-agent call timeout in seconds
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out_root: ""
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