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
@@ -1,99 +1,84 @@
-"""大模型回退层：Mock 与 OpenAI 兼容 API 两种后端。"""
-from __future__ import annotations
-
-import asyncio
-from typing import Dict, Optional
-
-from .models import ExpertResponse
-
-
-class FallbackProvider:
-    name: str = "fallback"
-
-    async def generate(self, query: str) -> ExpertResponse:
-        raise NotImplementedError
-
-
-class MockFallback(FallbackProvider):
-    """确定性 mock 大模型：标识为 fallback，便于测试升级路径。"""
-
-    def __init__(self, model: str = "mock-large"):
-        self.model = model
-        self.name = f"fallback-{model}"
-
-    async def generate(self, query: str) -> ExpertResponse:
-        await asyncio.sleep(0.002)
-        body = (
-            f"（大模型回退）「{query}」\n\n"
-            "这是一条来自大模型回退路径的完整回答。\n"
-            "要点：\n"
-            "1. 对复杂/跨域任务给出综合推理\n"
-            "2. 补充领域专家未覆盖的上下文\n"
-            "3. 给出可执行的后续建议\n"
-        )
-        return ExpertResponse(
-            text=body,
-            model_used=self.model,
-            latency_ms=2.0,
-            tokens=120,
-            cost_est=2.0 * 120 / 1_000_000,
-        )
-
-
-class APIFallback(FallbackProvider):
-    """OpenAI 兼容大模型 API（如 DeepSeek / OpenAI / 本地 vLLM）。"""
-
-    def __init__(self, model: str, base_url: str, api_key: str):
-        self.model = model
-        self.base_url = base_url.rstrip("/")
-        self.api_key = api_key
-        self.name = f"fallback-{model}"
-        self._client = None
-
-    def _get_client(self):
-        if self._client is None:
-            import httpx
-            self._client = httpx.AsyncClient(timeout=90.0)
-        return self._client
-
-    async def generate(self, query: str) -> ExpertResponse:
-        client = self._get_client()
-        resp = await client.post(
-            f"{self.base_url}/chat/completions",
-            headers={"Authorization": f"Bearer {self.api_key}"},
-            json={
-                "model": self.model,
-                "messages": [{"role": "user", "content": query}],
-                "temperature": 0.3,
-                "max_tokens": 2048,
-            },
-        )
-        resp.raise_for_status()
-        data = resp.json()
-        body = data["choices"][0]["message"]["content"]
-        usage = data.get("usage", {})
-        tokens = usage.get("completion_tokens", int(len(body) / 2.2))
-        return ExpertResponse(
-            text=body,
-            model_used=self.model,
-            latency_ms=0.0,
-            tokens=tokens,
-            cost_est=2.0 * tokens / 1_000_000,
-        )
-
-
-def build_fallback(cfg: Dict) -> FallbackProvider:
-    """cfg 为 fallback 段配置。"""
-    ftype = cfg.get("type", "mock")
-    model = cfg.get("model", "deepseek-chat")
-    if ftype == "mock":
-        return MockFallback(model=model)
-    if ftype == "api":
-        import os
-        api_key = cfg.get("api_key") or os.environ.get(cfg.get("api_key_env", "API_KEY"))
-        if not api_key:
-            raise RuntimeError(
-                f"APIFallback 缺少 API Key：请设置环境变量 {cfg.get('api_key_env')} 或配置 api_key"
-            )
-        return APIFallback(model, cfg.get("base_url", "https://api.deepseek.com/v1"), api_key)
-    raise ValueError(f"未知 fallback 类型: {ftype}（支持 mock | api）")␍
+"""大模型回退层：Mock 与 OpenAI 兼容 API 两种后端。"""
+from __future__ import annotations
+
+import asyncio
+from typing import Dict
+
+from .config import get_api_key
+from .llm_client import OpenAICompatClient
+from .models import ExpertResponse
+
+
+class FallbackProvider:
+    name: str = "fallback"
+
+    async def generate(self, query: str) -> ExpertResponse:
+        raise NotImplementedError
+
+
+class MockFallback(FallbackProvider):
+    """确定性 mock 大模型：标识为 fallback，便于测试升级路径。"""
+
+    def __init__(self, model: str = "mock-large"):
+        self.model = model
+        self.name = f"fallback-{model}"
+
+    async def generate(self, query: str) -> ExpertResponse:
+        await asyncio.sleep(0.002)
+        body = (
+            f"（大模型回退）「{query}」\n\n"
+            "这是一条来自大模型回退路径的完整回答。\n"
+            "要点：\n"
+            "1. 对复杂/跨域任务给出综合推理\n"
+            "2. 补充领域专家未覆盖的上下文\n"
+            "3. 给出可执行的后续建议\n"
+        )
+        return ExpertResponse(
+            text=body,
+            model_used=self.model,
+            latency_ms=2.0,
+            tokens=120,
+            cost_est=2.0 * 120 / 1_000_000,
+        )
+
+
+class APIFallback(FallbackProvider):
+    """OpenAI 兼容大模型 API（如 DeepSeek / OpenAI / 本地 vLLM）。"""
+
+    def __init__(self, model: str, base_url: str, api_key: str):
+        self.model = model
+        self.name = f"fallback-{model}"
+        self._client = OpenAICompatClient(base_url, api_key, timeout=90.0)
+
+    async def generate(self, query: str) -> ExpertResponse:
+        data = await self._client.chat(
+            self.model,
+            [{"role": "user", "content": query}],
+            temperature=0.3,
+            max_tokens=2048,
+        )
+        body = self._client.completion_text(data)
+        tokens = self._client.completion_tokens(data, body)
+        return ExpertResponse(
+            text=body,
+            model_used=self.model,
+            latency_ms=0.0,
+            tokens=tokens,
+            cost_est=2.0 * tokens / 1_000_000,
+        )
+
+
+def build_fallback(cfg: Dict) -> FallbackProvider:
+    """cfg 为 fallback 段配置。"""
+    ftype = cfg.get("type", "mock")
+    model = cfg.get("model", "deepseek-chat")
+    if ftype == "mock":
+        return MockFallback(model=model)
+    if ftype == "api":
+        api_key = cfg.get("api_key") or get_api_key(cfg)
+        if not api_key:
+            raise RuntimeError(
+                f"APIFallback 缺少 API Key：请设置环境变量 {cfg.get('api_key_env')} 或配置 api_key"
+            )
+        return APIFallback(model, cfg.get("base_url", "https://api.deepseek.com/v1"), api_key)
+    raise ValueError(f"未知 fallback 类型: {ftype}（支持 mock | api）")