mirror of
https://github.com/microsoft/SkillOpt.git
synced 2026-07-03 14:02:58 +08:00
e4ea6a6771
Highlights since v0.1.0: - feat: SkillOpt-Sleep engine — nightly offline self-evolution (harvest -> mine -> replay -> consolidate behind a validation gate), with multi-objective reward, experience replay + dream rollouts, slow-update long-term memory, and secret redaction in cycle diagnostics. Shipped as the `skillopt-sleep` CLI. - feat: cross-tool backends & plugin shells — Claude, Codex (+Desktop harvest), Copilot, Devin, and OpenClaw. - feat: SearchQA split materialization + rollout fail-fast. - fix: Windows robustness for claude/codex backends, hardened JSON fallback, Qwen timeout/thinking gating, Codex failure surfacing. Packaging: - Bump pyproject / skillopt / skillopt_sleep to 0.2.0. - Restore skillopt_webui to the packaged wheel. See CHANGELOG.md for the full changelog and contributor acknowledgements. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
83 lines
2.5 KiB
TOML
83 lines
2.5 KiB
TOML
[build-system]
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requires = ["setuptools>=68.0", "wheel"]
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build-backend = "setuptools.build_meta"
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[project]
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name = "skillopt"
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version = "0.2.0"
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description = "SkillOpt: Agentic Skill Optimization via Reflective Training Loops"
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readme = "README.md"
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license = {text = "MIT"}
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requires-python = ">=3.10"
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authors = [
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{name = "SkillOpt Team"},
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]
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keywords = ["agent", "prompt-optimization", "skill-learning", "LLM", "agentic"]
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classifiers = [
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"Development Status :: 3 - Alpha",
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"Intended Audience :: Science/Research",
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"License :: OSI Approved :: MIT License",
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"Programming Language :: Python :: 3",
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"Programming Language :: Python :: 3.10",
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"Programming Language :: Python :: 3.11",
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"Programming Language :: Python :: 3.12",
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"Topic :: Scientific/Engineering :: Artificial Intelligence",
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]
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dependencies = [
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"openai>=1.30.0",
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"pyyaml>=6.0",
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"numpy>=1.24.0",
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"openpyxl>=3.1.0",
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"azure-identity>=1.15.0",
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"azure-core>=1.30.0",
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"httpx>=0.27.0",
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]
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[project.optional-dependencies]
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# Benchmark-specific dependencies
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alfworld = ["alfworld>=0.4.0", "gymnasium>=0.29.0"]
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# Claude model backend
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claude = ["claude-agent-sdk>=0.1.0", "json_repair>=0.61.0"]
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# Qwen local model backend (via vLLM)
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qwen = ["vllm>=0.4.0", "json_repair>=0.61.0"]
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# SearchQA data materialization
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searchqa = ["datasets>=2.18.0"]
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# Documentation site
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docs = ["mkdocs-material>=9.5.0", "mkdocstrings[python]>=0.24.0"]
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# WebUI dashboard
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webui = ["gradio>=4.0.0"]
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# Development tools
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dev = ["ruff>=0.4.0", "pytest>=8.0.0"]
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# All optional dependencies (except docs/dev/webui)
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all = [
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"alfworld>=0.4.0",
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"gymnasium>=0.29.0",
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"claude-agent-sdk>=0.1.0",
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"json_repair>=0.61.0",
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]
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[project.scripts]
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skillopt-train = "scripts.train:main"
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skillopt-eval = "scripts.eval_only:main"
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skillopt-sleep = "skillopt_sleep.__main__:main"
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[project.urls]
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Homepage = "https://github.com/microsoft/SkillOpt"
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Documentation = "https://microsoft.github.io/SkillOpt"
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Repository = "https://github.com/microsoft/SkillOpt"
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Issues = "https://github.com/microsoft/SkillOpt/issues"
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[tool.setuptools.packages.find]
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# skillopt* = the research package
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# skillopt_sleep = the open-source Sleep tool (decoupled, zero research dep)
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# skillopt_webui = the Gradio dashboard (installed via the `webui` extra)
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include = ["skillopt", "skillopt.*", "skillopt_sleep", "skillopt_sleep.*", "skillopt_webui", "skillopt_webui.*", "scripts*"]
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[tool.ruff]
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line-length = 120
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target-version = "py310"
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[tool.ruff.lint]
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select = ["E", "F", "I", "W"]
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ignore = ["E501"]
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