feat(inference): LLM 客户端全异步化（T8 架构审查整改）

- Issue9: client.py 由同步 httpx.Client 全异步化
  - LLMClient Protocol / HttpLLMClient.chat → async；httpx.AsyncClient + asyncio.sleep 退避
  - __enter__/__exit__ → __aenter__/__aexit__（async with 生命周期闭环）
- engine.py chat/chat_structured/_call 全部 async + await
- FakeLLMClient.chat → async；测试用 anyio pytest 插件转换（engine 32 + client 10 用例）
- 同步 inference-engine spec 与 milestone3 review 的 httpx 描述
- 全量 182 passed / 100.00%（987 stmts/252 br）

src/genesis/inference/client.py

@@ -1,7 +1,7 @@
 from __future__ import annotations
 
+import asyncio
 import json
-import time
 from typing import Protocol, Sequence
 
 import httpx
@@ -16,9 +16,9 @@ from .types import ChatMessage, TokenUsage
 
 
 class LLMClient(Protocol):
-    """LLM 调用适配器（可注入替换为 Fake）。"""
+    """LLM 调用适配器（可注入替换为 Fake）。T8 起为 async 接口。"""
 
-    def chat(
+    async def chat(
         self,
         *,
         model: str,
@@ -29,7 +29,11 @@ class LLMClient(Protocol):
 
 
 class HttpLLMClient:
-    """OpenAI Chat Completions 兼容的 httpx 实现；支持重试（指数退避）。"""
+    """OpenAI Chat Completions 兼容的 httpx 异步实现；支持重试（指数退避）。
+
+    T8（架构审查整改）：由同步 httpx.Client 全异步化——async def chat、
+    httpx.AsyncClient、asyncio.sleep 退避、__aenter__/__aexit__ 生命周期闭环。
+    """
 
     def __init__(
         self,
@@ -46,16 +50,16 @@ class HttpLLMClient:
         self._api_key = api_key
         self._timeout_sec = timeout_sec
         self._retry_backoff = retry_backoff
-        self._client = httpx.Client(timeout=timeout_sec, transport=transport)
+        self._client = httpx.AsyncClient(timeout=timeout_sec, transport=transport)
 
-    def __enter__(self) -> HttpLLMClient:
-        """支持 with 块：退出时自动关闭底层连接。"""
+    async def __aenter__(self) -> HttpLLMClient:
+        """支持 async with 块：退出时自动关闭底层连接。"""
         return self
 
-    def __exit__(self, exc_type, exc_val, exc_tb) -> None:
-        self._client.close()
+    async def __aexit__(self, exc_type, exc_val, exc_tb) -> None:
+        await self._client.aclose()
 
-    def chat(
+    async def chat(
         self,
         *,
         model: str,
@@ -79,9 +83,9 @@ class HttpLLMClient:
         last_error: Exception | None = None
         for attempt in range(attempts):
             if attempt > 0:
-                time.sleep(self._retry_backoff[attempt - 1])
+                await asyncio.sleep(self._retry_backoff[attempt - 1])
             try:
-                resp = self._client.post(url, json=payload, headers=headers)
+                resp = await self._client.post(url, json=payload, headers=headers)
             except httpx.TimeoutException as exc:
                 last_error = exc
                 continue
@@ -113,4 +117,4 @@ class HttpLLMClient:
 
         if isinstance(last_error, httpx.TimeoutException):
             raise LLMTimeoutError(f"LLM 超时（{self._timeout_sec}s）") from last_error
-        raise LLMNetworkError(f"LLM 调用失败（重试耗尽）: {last_error}") from last_error
+        raise LLMNetworkError(f"LLM 调用失败（重试耗尽）: {last_error}") from last_error

src/genesis/inference/engine.py

@@ -87,7 +87,7 @@ class InferenceEngine:
                 return names
         return ["deepseek-chat"]
 
-    def _call(
+    async def _call(
         self,
         *,
         model: str,
@@ -100,7 +100,7 @@ class InferenceEngine:
             ChatMessage(role="system", content=self._system_instruction),
             ChatMessage(role="user", content=self._wrap_user_data(rendered)),
         ]
-        return self._client.chat(
+        return await self._client.chat(
             model=model,
             messages=messages,
             temperature=temperature,
@@ -109,7 +109,7 @@ class InferenceEngine:
 
     # ---------- 公开 ----------
 
-    def chat(
+    async def chat(
         self,
         *,
         session_id: str,
@@ -129,7 +129,7 @@ class InferenceEngine:
         last_error_code: str | None = None
         for idx, name in enumerate(self._model_names(model)):
             try:
-                text, usage = self._call(
+                text, usage = await self._call(
                     model=name, rendered=rendered,
                     temperature=temperature, max_tokens=max_tokens,
                 )
@@ -150,7 +150,7 @@ class InferenceEngine:
             status="failed", error=last_error, error_code=last_error_code,
         )
 
-    def chat_structured(
+    async def chat_structured(
         self,
         *,
         session_id: str,
@@ -179,7 +179,7 @@ class InferenceEngine:
             attempts += 1
             for idx, name in enumerate(names):
                 try:
-                    text, usage = self._call(
+                    text, usage = await self._call(
                         model=name,
                         rendered=base_rendered,
                         temperature=0.0, max_tokens=4096,