chore: T-P-1 工作区收敛——并行会话成果与历史未入库文件整理入库
- 入库历史遗漏源码/测试：router_system 9 模块（agent/executors/inference/knowledge/ memory/planner/skills/trace）、tests 11 个测试文件、config/knowledge 领域知识 - 入库根目录方案文档（v2/v3/可行性×2）、references 文献（arxiv 14-18/cnki_open/ 参考文献清单）、research 论文素材（routerarena/paper/中文文献 PDF） - 前端构建产物刷新（新 hash）；webapp 误写文档删除 - gitignore 增补：deepseek-harness、research/_refs、.mimosa/.zcode、网关日志/pid、 临时调试脚本、tests/e2e/node_modules、AI代理功能开发/prefix - 基线确认：318 passed
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"""Skill 技能体系（T12：Agent-Skill 路由器·先行实现）。
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把路由器独立为"技能注册表 + Agent 规划器"：
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- 用户只需提供需求，无需指定领域/模型
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- Agent 路由器自行分析需求 → 规划 skill 调用序列（可组合、可依赖）→ 执行
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Skill 抽象：name（唯一标识）+ description（能力描述，供规划器选择）
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+ params（参数说明）+ execute(ctx)（执行，返回文本结果）。
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内置技能（把专家系统内核能力封装为可调用单元）：
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- es.<kind> ：规则执行器模板生成（analyze/design/implement/solve/... 共 18 种）
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- kb.retrieve ：知识库事实检索（法律/医疗/金融事实条目）
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- kb.answer ：规则 output 知识问答（git/docker/天气/翻译等常识条目）
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- judge.evaluate：质量评分
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- fallback.call ：最后处理者（升级）
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- cache.get / cache.put：两阶段缓存
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"""
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from __future__ import annotations
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from dataclasses import dataclass, field
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from typing import Any, Dict, List, Optional
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from .executors import RuleExecutor
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from .knowledge import KnowledgeBase
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from .memory import TaskNode, WorkingMemory
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from .models import ExpertResponse
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@dataclass
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class SkillContext:
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"""一次 skill 调用的执行上下文（黑板 + 输入参数）。"""
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query: str
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domain: str
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difficulty: str
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memory: WorkingMemory
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kb: Optional[KnowledgeBase] = None
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args: Dict[str, Any] = field(default_factory=dict)
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class Skill:
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"""技能抽象：可被 Agent 路由器调用的能力单元。"""
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name: str = "skill"
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description: str = ""
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params: List[str] = field(default_factory=list)
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async def execute(self, ctx: SkillContext) -> str:
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raise NotImplementedError
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def __repr__(self) -> str:
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return f"<Skill {self.name}>"
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class SkillRegistry:
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"""技能注册表：注册 / 发现 / 执行。"""
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def __init__(self):
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self._skills: Dict[str, Skill] = {}
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def register(self, skill: Skill) -> None:
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if skill.name in self._skills:
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raise ValueError(f"技能重复注册: {skill.name}")
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self._skills[skill.name] = skill
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def get(self, name: str) -> Optional[Skill]:
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return self._skills.get(name)
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def has(self, name: str) -> bool:
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return name in self._skills
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def list(self) -> List[str]:
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return sorted(self._skills.keys())
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def catalog(self) -> List[Dict[str, Any]]:
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"""技能目录（供 Agent 规划器 / 用户发现使用）。"""
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return [
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{"name": s.name, "description": s.description, "params": list(s.params)}
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for s in sorted(self._skills.values(), key=lambda s: s.name)
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]
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async def execute(self, name: str, ctx: SkillContext) -> str:
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skill = self._skills.get(name)
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if skill is None:
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raise KeyError(f"未注册技能: {name}（可用: {self.list()}）")
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return await skill.execute(ctx)
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# ===============================================================
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# 内置技能实现
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# ===============================================================
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class TemplateSkill(Skill):
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"""es.<kind>：规则执行器模板生成（确定性、零参数）。"""
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def __init__(self, kind: str, executor: RuleExecutor):
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self.kind = kind
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self._executor = executor
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self.name = f"es.{kind}"
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self.description = f"规则模板生成（{kind}）：结构化确定性输出"
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self.params = ["domain", "difficulty", "memory"]
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async def execute(self, ctx: SkillContext) -> str:
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node = TaskNode(
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id="skill", kind=self.kind, domain=ctx.domain,
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query=ctx.query, desc=f"skill:{self.name}",
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)
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resp: ExpertResponse = await self._executor.generate(
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ctx.query, ctx.difficulty, ctx.memory, node)
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return resp.text
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class KBRetrieveSkill(Skill):
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"""kb.retrieve：知识库事实检索（法律/医疗/金融事实条目）。"""
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name = "kb.retrieve"
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description = "从知识库事实表检索领域知识条目（法条/指南/理财常识等）"
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params = ["domain", "query"]
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def __init__(self, kb: Optional[KnowledgeBase] = None):
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self._kb = kb
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async def execute(self, ctx: SkillContext) -> str:
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kb = self._kb or ctx.kb
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if kb is None:
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return "（kb.retrieve）未配置知识库。"
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facts = kb.facts(ctx.domain)
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hits = [f for f in facts if any(k in ctx.query for k in f.get("keywords", []))]
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if hits:
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lines = [f"- {f['statement']}" for f in hits]
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return f"【{ctx.domain} 知识检索】\n" + "\n".join(lines)
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return (f"【{ctx.domain} 知识检索】\n未命中知识库条目；"
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f"建议以现行有效法规/最新指南为准。")
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class KBAnswerSkill(Skill):
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"""kb.answer：规则 output 知识问答（git/docker/天气/翻译等常识条目）。"""
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name = "kb.answer"
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description = "知识库规则问答：命中 output 规则直接给出知识章节"
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params = ["domain", "query"]
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def __init__(self, kb: Optional[KnowledgeBase] = None):
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self._kb = kb
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async def execute(self, ctx: SkillContext) -> str:
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kb = self._kb or ctx.kb
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if kb is None:
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return "（kb.answer）未配置知识库。"
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hits = kb.match(ctx.query, domain=ctx.domain)
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for h in hits:
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if h.output:
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from .inference import render_template
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return render_template(h.output, ctx.query, {})
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return "（kb.answer）未命中知识规则。"
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class JudgeSkill(Skill):
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"""judge.evaluate：质量评分（5 维：覆盖/长度/格式/安全/知识引用）。"""
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name = "judge.evaluate"
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description = "评估回答质量（0-1 分），低于阈值建议升级"
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params = ["query", "response", "domain"]
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def __init__(self, judge, fallback_threshold: float = 0.70):
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self._judge = judge
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self._threshold = fallback_threshold
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async def execute(self, ctx: SkillContext) -> str:
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response = ctx.args.get("response", "")
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domain = ctx.args.get("domain", ctx.domain)
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eval_result = await self._judge.evaluate(ctx.query, response, domain)
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return (f"【质量评分】{eval_result.overall_score:.2f} "
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f"{'(需升级)' if eval_result.needs_fallback else '(达标)'} "
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f"{'; '.join(eval_result.reasons)}")
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class FallbackSkill(Skill):
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"""fallback.call：最后处理者（升级/降级兜底）。"""
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name = "fallback.call"
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description = "调用最后处理者（本地≤8B 模型 / 降级模板 / mock）"
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params = ["query"]
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def __init__(self, fallback):
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self._fallback = fallback
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async def execute(self, ctx: SkillContext) -> str:
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resp = await self._fallback.generate(ctx.query)
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return resp.text
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def build_skill_registry(kb: Optional[KnowledgeBase] = None,
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executor: Optional[RuleExecutor] = None,
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judge=None, fallback=None,
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fallback_threshold: float = 0.70) -> SkillRegistry:
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"""构建内置技能注册表。
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模板技能自动注册 18 种 kind（analyze/design/implement/solve/diagnose/fix/
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retrieve/conclude/advise/explain/disclaimer/verify/refactor/testcase/
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complexity/optimize/draft/polish）；retrieve 由 kb.retrieve 接管（更专）。
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"""
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reg = SkillRegistry()
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exec_ = executor or RuleExecutor("rule-executor", "general", kb=kb)
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_EXCLUDED = {"retrieve"} # retrieve 用 kb.retrieve（知识库驱动）
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for kind in ("analyze", "design", "implement", "solve", "diagnose", "fix",
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"conclude", "advise", "explain", "disclaimer", "verify",
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"refactor", "testcase", "complexity", "optimize", "draft",
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"polish"):
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if kind not in _EXCLUDED:
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reg.register(TemplateSkill(kind, exec_))
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reg.register(KBRetrieveSkill(kb=kb))
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reg.register(KBAnswerSkill(kb=kb))
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if judge is not None:
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reg.register(JudgeSkill(judge, fallback_threshold=fallback_threshold))
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if fallback is not None:
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reg.register(FallbackSkill(fallback))
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return reg
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