diff --git a/backend/.env.example b/backend/.env.example
index de2fec5..3b20391 100644
--- a/backend/.env.example
+++ b/backend/.env.example
@@ -61,3 +61,8 @@ JWT_EXPIRE_HOURS=168
 # 服务启动时自动创建的管理员账号
 ADMIN_PHONE=15549380526
 ADMIN_PASSWORD=lam1988324
+
+# =============== GLM AI 配置 ===============
+# 智谱 GLM API 配置 (用于生成标题和标签)
+GLM_API_KEY=32440cd3f3444d1f8fe721304acea8bd.YXNLrk7eIJMKcg4t
+GLM_MODEL=glm-4.7-flash
diff --git a/backend/app/core/config.py b/backend/app/core/config.py
index 9be622c..b7ca06e 100644
--- a/backend/app/core/config.py
+++ b/backend/app/core/config.py
@@ -39,6 +39,10 @@ class Settings(BaseSettings):
     ADMIN_PHONE: str = ""
     ADMIN_PASSWORD: str = ""
     
+    # GLM AI 配置
+    GLM_API_KEY: str = ""
+    GLM_MODEL: str = "glm-4.7-flash"
+    
     @property
     def LATENTSYNC_DIR(self) -> Path:
         """LatentSync 目录路径 (动态计算)"""
diff --git a/backend/app/services/glm_service.py b/backend/app/services/glm_service.py
index 56e2427..0ce428d 100644
--- a/backend/app/services/glm_service.py
+++ b/backend/app/services/glm_service.py
@@ -1,19 +1,29 @@
 """
 GLM AI 服务
-使用智谱 GLM-4.7-Flash 生成标题和标签
+使用智谱 GLM 生成标题和标签
 """
 
 import json
 import re
-import httpx
 from loguru import logger
+from zai import ZhipuAiClient
+
+from app.core.config import settings
 
 
 class GLMService:
     """GLM AI 服务"""
 
-    API_URL = "https://open.bigmodel.cn/api/paas/v4/chat/completions"
-    API_KEY = "5915240ea48d4e93b454bc2412d1cc54.e054ej4pPqi9G6rc"
+    def __init__(self):
+        self.client = None
+
+    def _get_client(self):
+        """获取或创建 ZhipuAI 客户端"""
+        if self.client is None:
+            if not settings.GLM_API_KEY:
+                raise Exception("GLM_API_KEY 未配置")
+            self.client = ZhipuAiClient(api_key=settings.GLM_API_KEY)
+        return self.client
 
     async def generate_title_tags(self, text: str) -> dict:
         """
@@ -38,34 +48,25 @@ class GLMService:
 {{"title": "标题", "tags": ["标签1", "标签2", "标签3"]}}"""
 
         try:
-            async with httpx.AsyncClient(timeout=30.0) as client:
-                response = await client.post(
-                    self.API_URL,
-                    headers={
-                        "Content-Type": "application/json",
-                        "Authorization": f"Bearer {self.API_KEY}"
-                    },
-                    json={
-                        "model": "glm-4-flash",
-                        "messages": [{"role": "user", "content": prompt}],
-                        "max_tokens": 500,
-                        "temperature": 0.7
-                    }
-                )
-                response.raise_for_status()
-                data = response.json()
+            client = self._get_client()
+            logger.info(f"Calling GLM API with model: {settings.GLM_MODEL}")
+            
+            response = client.chat.completions.create(
+                model=settings.GLM_MODEL,
+                messages=[{"role": "user", "content": prompt}],
+                thinking={"type": "disabled"},  # 禁用思考模式，加快响应
+                max_tokens=500,
+                temperature=0.7
+            )
 
-                # 提取生成的内容
-                content = data["choices"][0]["message"]["content"]
-                logger.info(f"GLM response: {content}")
+            # 提取生成的内容
+            content = response.choices[0].message.content
+            logger.info(f"GLM response (model: {settings.GLM_MODEL}): {content}")
 
-                # 解析 JSON
-                result = self._parse_json_response(content)
-                return result
+            # 解析 JSON
+            result = self._parse_json_response(content)
+            return result
 
-        except httpx.HTTPError as e:
-            logger.error(f"GLM API request failed: {e}")
-            raise Exception(f"AI 服务请求失败: {str(e)}")
         except Exception as e:
             logger.error(f"GLM service error: {e}")
             raise Exception(f"AI 生成失败: {str(e)}")