fix: 修复额外的内存泄露问题

1. hybrid_search.py: 修复 _search_vector 方法中的 SQLite 连接泄露
   - 使用 with 语句包装数据库连接
   - 添加异常处理确保连接正确关闭

2. symbol_extractor.py: 添加上下文管理器支持
   - 实现 __enter__ 和 __exit__ 方法
   - 支持 with 语句自动管理资源

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude Opus 4.5 <[email protected]>

Author: catlog22

codex-lens/src/codexlens/indexing/symbol_extractor.py

@@ -47,6 +47,15 @@ def connect(self) -> None:
         self.db_conn = sqlite3.connect(str(self.db_path))
         self._ensure_tables()
 
+    def __enter__(self) -> "SymbolExtractor":
+        """Context manager entry: connect to database."""
+        self.connect()
+        return self
+
+    def __exit__(self, exc_type: Any, exc_val: Any, exc_tb: Any) -> None:
+        """Context manager exit: close database connection."""
+        self.close()
+
     def _ensure_tables(self) -> None:
         """Create symbols and relationships tables if they don't exist."""
         if not self.db_conn:

codex-lens/src/codexlens/search/hybrid_search.py

@@ -241,12 +241,15 @@ def _search_vector(
         try:
             # Check if semantic chunks table exists
             import sqlite3
-            conn = sqlite3.connect(index_path)
-            cursor = conn.execute(
-                "SELECT name FROM sqlite_master WHERE type='table' AND name='semantic_chunks'"
-            )
-            has_semantic_table = cursor.fetchone() is not None
-            conn.close()
+            try:
+                with sqlite3.connect(index_path) as conn:
+                    cursor = conn.execute(
+                        "SELECT name FROM sqlite_master WHERE type='table' AND name='semantic_chunks'"
+                    )
+                    has_semantic_table = cursor.fetchone() is not None
+            except sqlite3.Error as e:
+                self.logger.error("Database check failed in vector search: %s", e)
+                return []
 
             if not has_semantic_table:
                 self.logger.info(