tzt
ce0f6170d3
- 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
127 lines
5.1 KiB
Python
127 lines
5.1 KiB
Python
"""本系统 L0 路由器 → RouterArena BaseRouter 适配器。
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核心职责：
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- 接收 RouterArena 的 prompt（不含 ground truth）
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- 调用本系统 Router.route() 得到 (domain, confidence, quality_score)
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- 按 `DOMAIN_TO_MODEL_SLOT` 映射到 config.models 中的目标模型名
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- 兜底：confidence<0.60 或 quality<0.70 → 升到 reasoning-mid
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合规说明（依据 RouterArena README L34-37 + base_router.py L139-167）：
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- 路由阶段不接触 ground truth answer
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- 不在 RouterArena 数据上训练/微调
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- 8 领域映射表是手工设计，不基于 RouterArena 标签学习
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"""
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from __future__ import annotations
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import sys
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from pathlib import Path
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from typing import Any, Dict
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# 把项目根加入 path，以便 import router_system
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_PROJECT_ROOT = Path(__file__).resolve().parent.parent.parent
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if str(_PROJECT_ROOT) not in sys.path:
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sys.path.insert(0, str(_PROJECT_ROOT))
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from router_system.router import Router, build_router # noqa: E402
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from .base_router import BaseRouter # noqa: E402
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# L0 域 → RouterArena 候选模型槽位 的映射
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# 依据 00_integration_plan.md §3.2：
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# - code → gpt-4o-mini（代码强项）
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# - math/legal/medical/finance → claude-3-haiku-20240307（推理严谨性）
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# - life/general → gemini-2.0-flash-001（实用+快速）
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# - education → deepseek-chat（中文/教育）
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DOMAIN_TO_MODEL_SLOT: Dict[str, str] = {
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"code": "gpt-4o-mini",
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"math": "claude-3-haiku-20240307",
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"legal": "claude-3-haiku-20240307",
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"medical": "claude-3-haiku-20240307",
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"finance": "claude-3-haiku-20240307",
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"life": "gemini-2.0-flash-001",
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"education": "deepseek-chat",
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"general": "gemini-2.0-flash-001",
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}
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# 兜底：低置信度或低质 → 升到更稳的模型
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ESCALATION_MODEL_SLOT = "mistral-medium"
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# 阈值：与本系统 config.yaml 默认对齐
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LOW_CONFIDENCE_THRESHOLD = 0.60
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JUDGE_FALLBACK_THRESHOLD = 0.70
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class ESExpertRouter(BaseRouter):
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"""把本系统 L0 Router 适配为 RouterArena BaseRouter。
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重要：_get_prediction 必须只基于 query（无 ground truth），
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返回值必须在 config.models 中。
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"""
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def __init__(
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self,
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router_name: str,
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config_path: str = "",
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underlying_router: Router = None,
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):
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super().__init__(router_name, config_path=config_path or None)
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# 复用本系统 L0 Router（默认配置；如已 build 过可注入）
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self._router = underlying_router or build_router()
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def _get_prediction(self, query: str) -> str:
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"""依据 L0 路由决策返回目标模型名。"""
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# 注意：这里我们用同步方式跑异步 router.route()
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# BaseRouter 的 _get_prediction 是同步签名；RouterArena 的 generate_prediction_file
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# 默认单线程顺序调用 8400 条，async 包装完全兼容
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import asyncio
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try:
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loop = asyncio.get_event_loop()
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if loop.is_running():
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# 已经在 async 上下文（不太可能，但兜底）
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return self._get_prediction_sync(query)
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return loop.run_until_complete(self._route_one(query))
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except RuntimeError:
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# 没有 event loop，临时建一个
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return asyncio.run(self._route_one(query))
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async def _route_one(self, query: str) -> str:
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result = await self._router.route(query)
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return self._decide(result.domain, result.confidence, result.quality_score)
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def _get_prediction_sync(self, query: str) -> str:
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"""event loop 已运行时的兜底（按当前 router 的同步视图返回默认值）。"""
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# 我们没有同步入口，但 generate_prediction_file 是顺序同步调用 _get_prediction，
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# 不会与 async 上下文冲突，所以此分支极少触发；保守返回 generalist-fast
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return DOMAIN_TO_MODEL_SLOT["general"]
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def _decide(self, domain: str, confidence: float, quality_score: float) -> str:
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"""路由决策：按阈值升档。"""
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if domain not in DOMAIN_TO_MODEL_SLOT:
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domain = "general"
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# 兜底升级
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if confidence < LOW_CONFIDENCE_THRESHOLD or quality_score < JUDGE_FALLBACK_THRESHOLD:
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return ESCALATION_MODEL_SLOT
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return DOMAIN_TO_MODEL_SLOT[domain]
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def diagnostics(self, query: str) -> Dict[str, Any]:
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"""返回完整路由诊断（用于科研报告，不影响 RouterArena 协议）。"""
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import asyncio
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return asyncio.run(self._diagnose_one(query))
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async def _diagnose_one(self, query: str) -> Dict[str, Any]:
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result = await self._router.route(query)
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return {
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"query": query,
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"domain": result.domain,
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"subdomain": result.subdomain,
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"subdomain2": result.subdomain2,
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"difficulty": result.difficulty,
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"confidence": result.confidence,
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"quality_score": result.quality_score,
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"upgraded": result.upgraded,
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"model_used": result.model_used,
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"route": result.route,
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"selected_slot": self._decide(result.domain, result.confidence, result.quality_score),
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}
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