feat(v1): 架构与算法优化二轮——共享 LLM 客户端去重、语义缓存 O(1) 提升/淘汰、分类器热路径清理

- 新增 router_system/llm_client.py：OpenAICompatClient 统一 experts/judge/fallback 三处复制的懒建 AsyncClient + /chat/completions + choices/usage 解析（~60 行去重）；密钥解析统一走 config.get_api_key（激活原死代码，顺带消除 experts 默认环境名不一致） - 语义缓存 L2：条目容器 list→OrderedDict（提升/淘汰 O(n)→O(1)），按 query 天然去重； n-gram 向量 lru_cache 复用（同一次 miss 的 get/put 免重复分词）； A/B：淘汰路径 0.040→0.034s，miss→put 往返 9.41→8.57s（-9%） - RuleJudge 覆盖度：response.lower() 提出逐词循环（原 O(terms×len) 重复复制） - extract_content_terms 纯函数 lru_cache 化（专家与 Judge 对同一查询免重复分词），返回 tuple - RuleClassifier：_score 去掉败者领域白建的命中词 list（胜出后单独收集）；修复 code 规则 ("api",0.7) 重复登记（原命中计 1.4 分） - difficulty：正则模块级预编译 - tests：恢复上一轮引入的乱码中文 docstring；网关测试输入串恢复为可判 code 的中文查询
2026-09-18 23:27:26 +08:00
parent 81b0bc9b9b
commit c072a1a237
10 changed files with 696 additions and 631 deletions
@@ -1,52 +1,56 @@
-"""查询难度估计器（启发式，纯标准库）。
-
-依据：RouterArena 用 Bloom 分类法把问题分为 easy/medium/hard。
-这里用查询长度、指令动词、数学/推理标记做轻量估计。
-"""
-from __future__ import annotations
-
-import re
-from typing import Tuple
-
-# 触发 hard 的指令动词 / 推理标记
-_HARD_MARKERS = [
-    "证明", "推导", "为什么", "如何", "对比", "比较", "分析", "评估", "设计", "优化",
-    "复杂度", "时间复杂度", "空间复杂度", "原理", "机制", "优缺点", "区别", "推论", "定理",
-    "proof", "prove", "derive", "explain why", "why", "how", "compare", "contrast",
-    "analy", "evaluate", "design", "optimize", "refactor", "architect",
-    "implement", "debug", "review", "plan", "synthesize",
-    "int", "sum", "sqrt", "lim", "log", "derivative", "integral",
-]
-# 触发 medium 的标记
-_MEDIUM_MARKERS = [
-    "用", "写", "计算", "求解", "生成", "翻译", "总结", "解释",
-    "注意", "建议", "是否", "实现", "步骤",
-    "write", "code", "function", "script", "calculate", "solve", "summarize",
-    "translate", "fix", "explain", "describe", "list",
-]
-
-
-def estimate_difficulty(query: str) -> Tuple[str, float]:
-    """返回 (difficulty, score)，score 属于 [0,1]。"""
-    q = query.lower()
-    hard_hits = sum(1 for m in _HARD_MARKERS if m in q)
-    medium_hits = sum(1 for m in _MEDIUM_MARKERS if m in q)
-    length = len(query)
-
-    score = 0.0
-    score += min(0.30, length / 600.0)          # 长度贡献
-    score += min(0.55, hard_hits * 0.25)        # 推理标记贡献
-    score += min(0.30, medium_hits * 0.08)      # 一般指令贡献
-
-    # 额外：代码 / 数学表达式（多步骤信号）
-    if "```" in query or re.search(r"\b(def|class|function|import)\b", q):
-        score += 0.15
-    if re.search(r"[0-9]+\s*[+\-*/^=]\s*[0-9xya-z]", q):
-        score += 0.15
-
-    score = max(0.0, min(1.0, score))
-    if score >= 0.55:
-        return "hard", score
-    if score >= 0.25:
-        return "medium", score
-    return "easy", score␍
+"""查询难度估计器（启发式，纯标准库）。
+
+依据：RouterArena 用 Bloom 分类法把问题分为 easy/medium/hard。
+这里用查询长度、指令动词、数学/推理标记做轻量估计。
+"""
+from __future__ import annotations
+
+import re
+from typing import Tuple
+
+# 触发 hard 的指令动词 / 推理标记
+_HARD_MARKERS = [
+    "证明", "推导", "为什么", "如何", "对比", "比较", "分析", "评估", "设计", "优化",
+    "复杂度", "时间复杂度", "空间复杂度", "原理", "机制", "优缺点", "区别", "推论", "定理",
+    "proof", "prove", "derive", "explain why", "why", "how", "compare", "contrast",
+    "analy", "evaluate", "design", "optimize", "refactor", "architect",
+    "implement", "debug", "review", "plan", "synthesize",
+    "int", "sum", "sqrt", "lim", "log", "derivative", "integral",
+]
+# 触发 medium 的标记
+_MEDIUM_MARKERS = [
+    "用", "写", "计算", "求解", "生成", "翻译", "总结", "解释",
+    "注意", "建议", "是否", "实现", "步骤",
+    "write", "code", "function", "script", "calculate", "solve", "summarize",
+    "translate", "fix", "explain", "describe", "list",
+]
+
+# 预编译正则（模块级一次，避免每次调用走 re 内部缓存查找）
+_RE_CODE_EXPR = re.compile(r"\b(def|class|function|import)\b")
+_RE_ARITH_EXPR = re.compile(r"[0-9]+\s*[+\-*/^=]\s*[0-9xya-z]")
+
+
+def estimate_difficulty(query: str) -> Tuple[str, float]:
+    """返回 (difficulty, score)，score 属于 [0,1]。"""
+    q = query.lower()
+    hard_hits = sum(1 for m in _HARD_MARKERS if m in q)
+    medium_hits = sum(1 for m in _MEDIUM_MARKERS if m in q)
+    length = len(query)
+
+    score = 0.0
+    score += min(0.30, length / 600.0)          # 长度贡献
+    score += min(0.55, hard_hits * 0.25)        # 推理标记贡献
+    score += min(0.30, medium_hits * 0.08)      # 一般指令贡献
+
+    # 额外：代码 / 数学表达式（多步骤信号）
+    if "```" in query or _RE_CODE_EXPR.search(q):
+        score += 0.15
+    if _RE_ARITH_EXPR.search(q):
+        score += 0.15
+
+    score = max(0.0, min(1.0, score))
+    if score >= 0.55:
+        return "hard", score
+    if score >= 0.25:
+        return "medium", score
+    return "easy", score