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- 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
104 lines
4.0 KiB
Python
104 lines
4.0 KiB
Python
"""规则 Planner：把查询拆解为子任务 DAG（任务分解，专家系统风格，零参数）。
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拆解逻辑（确定性规则）：
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1. 在分类领域内匹配知识规则
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2. 取最高优先级且带 template 的命中规则 → 对应任务模板
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3. 非 easy 难度且有模板 → 生成多节点 DAG（模板 steps 转 TaskNode，含依赖）
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4. easy 难度或无模板命中 → 单节点直接求解（不拆，最小开销）
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5. 拆解深度防护：节点不再递归拆解（当前为单层拆解，模板本身即最终粒度）
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对齐架构目标："路由模型把任务拆解后分步骤交给各个小模型"，
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L0 模式下各子任务由规则执行器完成（零参数），L2 模式可交给本地小模型。
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"""
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from __future__ import annotations
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from typing import List, Optional
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from .knowledge import KnowledgeBase
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from .memory import TaskGraph, TaskNode
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from .models import Classification
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# 单节点求解时按领域选择默认动作 kind
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_SINGLE_KIND = {
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"code": "implement",
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"math": "solve",
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"legal": "conclude",
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"medical": "advise",
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"general": "explain",
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"finance": "conclude",
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"life": "advise",
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"education": "design",
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}
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# 强制拆解领域：即使 easy 也走完整任务模板
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# （legal 需要 retrieve+disclaimer，medical 需要 advise+warning，
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# finance 需要 retrieve+风险免责——均为领域硬要求）
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FORCE_SPLIT_DOMAINS = {"legal", "medical", "finance"}
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# 强制拆解模板：命中即拆（debug 流程必须 analyze→diagnose→fix→verify）
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FORCE_SPLIT_TEMPLATES = {"code-debug"}
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class Planner:
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"""规则 Planner：查询 → 子任务 DAG。"""
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def __init__(self, kb: KnowledgeBase, max_depth: int = 3):
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self.kb = kb
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self.max_depth = max_depth
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# ---------------------------------------------------------------
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def plan(self, query: str, classification: Classification) -> TaskGraph:
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domain = classification.domain
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difficulty = classification.difficulty
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# 1. 领域内匹配规则，取最高优先级带模板的规则
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template_id: Optional[str] = None
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hits = self.kb.match(query, domain=domain)
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for h in hits:
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if h.template:
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template_id = h.template
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break
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graph = TaskGraph()
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# 2. 非 easy / 强制拆解领域 / 强制拆解模板 → 多节点 DAG
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if template_id and (difficulty != "easy"
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or domain in FORCE_SPLIT_DOMAINS
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or template_id in FORCE_SPLIT_TEMPLATES):
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tpl = self.kb.task_template(template_id)
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if tpl and tpl.get("steps"):
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for step in tpl["steps"]:
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node = TaskNode(
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id=str(step["id"]),
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kind=str(step.get("kind", "solve")),
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domain=str(step.get("domain", domain)),
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query=query,
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deps=[str(d) for d in step.get("deps", [])],
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desc=str(step.get("desc", "")),
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)
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graph.add_node(node)
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return graph
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# 3. easy / 无模板 → 单节点
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kind = _SINGLE_KIND.get(domain, "explain")
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graph.add_node(TaskNode(
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id="solve",
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kind=kind,
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domain=domain,
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query=query,
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desc=f"单节点求解（{domain}/{difficulty}）",
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))
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return graph
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# ---------------------------------------------------------------
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def explain_plan(self, graph: TaskGraph) -> List[str]:
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"""把 DAG 渲染为可读的拆解轨迹（用于 route 与 --trace）。"""
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if len(graph) == 1:
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n = graph.nodes()[0]
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return [f"plan:single[{n.kind}]"]
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parts = []
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for n in graph.topo_order():
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dep = f"<{','.join(n.deps)}" if n.deps else ""
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parts.append(f"{n.id}:{n.kind}{dep}")
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return [f"plan:multi[{len(graph)}]({' -> '.join(parts)})"]
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