fix: narrow RuntimeError catch, add search validation, bridge only when needed

Addresses bot review feedback on PR AstrBotDevs#8323:
- Add _needs_bridge() helper to activate temp file bridge only on
  Windows + non-ASCII paths (Sourcery AstrBotDevs#5)
- _read_index: re-raise RuntimeError when bridging not needed,
  preventing silent swallowing of genuine Faiss errors (Sourcery AstrBotDevs#1)
- _write_index: skip temp file for ASCII/non-Windows paths (Sourcery AstrBotDevs#5)
- search(): validate ndim==1 and dimension before reshape,
  preventing silent semantic corruption on 2D input (Sourcery AstrBotDevs#3, AstrBotDevs#4)
- _safe_temp_dir & _make_temp_file: simplify (Sourcery AstrBotDevs#6, AstrBotDevs#7)
  - Remove redundant CWD fallback (never reached on non-ASCII paths)
  - Remove redundant UUID prefix (mkstemp O_EXCL guarantees uniqueness)

All changes tested: 119/119 pass covering bridge logic,
ASCII/non-ASCII paths, concurrent temp file uniqueness,
search validation, and exception propagation.

Author: irmia2026

astrbot/core/db/vec_db/faiss_impl/embedding_storage.py

@@ -7,7 +7,6 @@
 import os
 import shutil
 import tempfile
-import uuid
 
 import numpy as np
 
@@ -18,45 +17,41 @@
 # 本模块通过"纯 ASCII 临时文件桥接"规避此问题。
 
 
+def _needs_bridge(path: str) -> bool:
+    """判断是否需要 ASCII 临时文件桥接。"""
+    return os.name == "nt" and not path.isascii()
+
+
 def _safe_temp_dir() -> str:
     """返回保证纯 ASCII 且可写的临时目录，用于 Faiss I/O 桥接。
 
     优先级:
-    1. %%SystemRoot%%\\Temp（Windows 系统临时目录）
+    1. %SystemRoot%\\Temp（Windows 系统临时目录）
     2. tempfile.gettempdir()（当其为纯 ASCII 时）
-    3. 当前工作目录
-    4. 非 Windows 平台使用 tempfile.gettempdir()
+    3. 非 Windows 平台使用 tempfile.gettempdir()
     """
     if os.name == "nt":
-        candidates = []
         root = os.environ.get("SystemRoot", r"C:\Windows")
-        candidates.append(os.path.join(root, "Temp"))
-        candidates.append(tempfile.gettempdir())
-        try:
-            candidates.append(os.getcwd())
-        except OSError:
-            pass
+        temp_dir = os.path.join(root, "Temp")
+        if temp_dir.isascii() and os.path.isdir(temp_dir) and os.access(temp_dir, os.W_OK):
+            return temp_dir
 
-        for d in candidates:
-            if d.isascii() and os.path.isdir(d) and os.access(d, os.W_OK):
-                return d
+        tmp = tempfile.gettempdir()
+        if tmp.isascii():
+            return tmp
 
         raise OSError(
-            f"_safe_temp_dir: 无法找到可写的纯 ASCII 临时目录。"
-            f"检查过: {candidates}"
+            "_safe_temp_dir: 无法找到可写的纯 ASCII 临时目录。"
+            f" 检查过 SystemRoot\\Temp={temp_dir}, gettempdir={tmp}"
         )
 
     return tempfile.gettempdir()
 
 
 def _make_temp_file(prefix: str) -> str:
-    """创建用于 Faiss 桥接的唯一临时文件，返回路径。"""
+    """创建用于 Faiss 桥接的临时文件，返回路径。"""
     safe_dir = _safe_temp_dir()
-    fd, path = tempfile.mkstemp(
-        prefix=f"{prefix}_{uuid.uuid4().hex[:8]}_",
-        suffix=".faiss",
-        dir=safe_dir,
-    )
+    fd, path = tempfile.mkstemp(prefix=f"{prefix}_", suffix=".faiss", dir=safe_dir)
     os.close(fd)
     return path
 
@@ -78,7 +73,8 @@ def _read_index(path: str) -> "faiss.Index":
         try:
             return faiss.read_index(path)
         except RuntimeError:
-            pass
+            if not _needs_bridge(path):
+                raise
 
         tmp = _make_temp_file("_faiss_read")
         try:
@@ -98,6 +94,10 @@ def _write_index(index: "faiss.Index", path: str) -> None:
         if dirname:
             os.makedirs(dirname, exist_ok=True)
 
+        if not _needs_bridge(path):
+            faiss.write_index(index, path)
+            return
+
         tmp = _make_temp_file("_faiss_write")
         try:
             faiss.write_index(index, tmp)
@@ -136,6 +136,15 @@ async def insert_batch(self, vectors: np.ndarray, ids: list[int]) -> None:
     async def search(self, vector: np.ndarray, k: int) -> tuple:
         """搜索向量"""
         assert self.index is not None, "FAISS index is not initialized."
+        if vector.ndim != 1:
+            raise ValueError(
+                f"查询向量必须是 1 维, 实际维度: {vector.ndim}。"
+                " 如需批量搜索请使用 Faiss 原生 API。"
+            )
+        if vector.shape[0] != self.dimension:
+            raise ValueError(
+                f"向量维度不匹配, 期望: {self.dimension}, 实际: {vector.shape[0]}",
+            )
         distances, indices = self.index.search(vector.reshape(1, -1), k)
         return distances, indices