diff --git a/eval/eval_mhqa.py b/eval/eval_mhqa.py
index 7075445..3dd5664 100644
--- a/eval/eval_mhqa.py
+++ b/eval/eval_mhqa.py
@@ -68,7 +68,7 @@ def wrap_embedding_func_with_attrs(**kwargs):
 @wrap_embedding_func_with_attrs(embedding_dim=2048, max_token_size=8192)
 async def GLM_embedding(texts: list[str]) -> np.ndarray:
     model_name = GLM_MODEL # "embedding-3"
-    client = OpenAI(
+    client = AsyncOpenAI(
         api_key=GLM_API_KEY,
         base_url=GLM_URL
     ) 
@@ -82,7 +82,7 @@ async def GLM_embedding(texts: list[str]) -> np.ndarray:
 @wrap_embedding_func_with_attrs(embedding_dim=4096, max_token_size=8192)
 async def NV_embedding(texts: list[str]) -> np.ndarray:
     model_name = NVIDIA_MODEL # "nvidia/nv-embed-v1"
-    client = OpenAI(
+    client = AsyncOpenAI(
         api_key=NVIDIA_API_KEY,
         base_url=NVIDIA_URL,
     ) 
diff --git a/eval/test_deepseek.py b/eval/test_deepseek.py
index d4b86b9..14add06 100644
--- a/eval/test_deepseek.py
+++ b/eval/test_deepseek.py
@@ -59,7 +59,7 @@ def wrap_embedding_func_with_attrs(**kwargs):
 @wrap_embedding_func_with_attrs(embedding_dim=2048, max_token_size=8192)
 async def GLM_embedding(texts: list[str]) -> np.ndarray:
     model_name = "embedding-3"
-    client = OpenAI(
+    client = AsyncOpenAI(
         api_key=GLM_API_KEY,
         base_url="https://open.bigmodel.cn/api/paas/v4/"
     ) 
diff --git a/eval/test_glm.py b/eval/test_glm.py
index 23799f0..407eccc 100644
--- a/eval/test_glm.py
+++ b/eval/test_glm.py
@@ -50,7 +50,7 @@ def wrap_embedding_func_with_attrs(**kwargs):
 @wrap_embedding_func_with_attrs(embedding_dim=2048, max_token_size=8192)
 async def GLM_embedding(texts: list[str]) -> np.ndarray:
     model_name = "embedding-3"
-    client = OpenAI(
+    client = AsyncOpenAI(
         api_key=GLM_API_KEY,
         base_url="https://open.bigmodel.cn/api/paas/v4/"
     ) 
diff --git a/hi_Search_deepseek.py b/hi_Search_deepseek.py
index 12f7cbf..41bba1a 100644
--- a/hi_Search_deepseek.py
+++ b/hi_Search_deepseek.py
@@ -42,7 +42,7 @@ def wrap_embedding_func_with_attrs(**kwargs):
 @wrap_embedding_func_with_attrs(embedding_dim=config['model_params']['glm_embedding_dim'], max_token_size=config['model_params']['max_token_size'])
 async def GLM_embedding(texts: list[str]) -> np.ndarray:
     model_name = "embedding-3"
-    client = OpenAI(
+    client = AsyncOpenAI(
         api_key=GLM_API_KEY,
         base_url=GLM_URL
     ) 
diff --git a/hi_Search_glm.py b/hi_Search_glm.py
index 4a39452..9486f99 100644
--- a/hi_Search_glm.py
+++ b/hi_Search_glm.py
@@ -39,7 +39,7 @@ def wrap_embedding_func_with_attrs(**kwargs):
 @wrap_embedding_func_with_attrs(embedding_dim=config['model_params']['glm_embedding_dim'], max_token_size=config['model_params']['max_token_size'])
 async def GLM_embedding(texts: list[str]) -> np.ndarray:
     model_name = config['glm']['embedding_model']
-    client = OpenAI(
+    client = AsyncOpenAI(
         api_key=GLM_API_KEY,
         base_url=GLM_URL
     ) 
diff --git a/hi_Search_openai.py b/hi_Search_openai.py
index 6b4648e..1efe715 100644
--- a/hi_Search_openai.py
+++ b/hi_Search_openai.py
@@ -50,7 +50,7 @@ async def OPENAI_embedding(texts: list[str]) -> np.ndarray:
 @wrap_embedding_func_with_attrs(embedding_dim=config['model_params']['glm_embedding_dim'], max_token_size=config['model_params']['max_token_size'])
 async def GLM_embedding(texts: list[str]) -> np.ndarray:
     model_name = config['glm']['embedding_model']
-    client = OpenAI(
+    client = AsyncOpenAI(
         api_key=GLM_API_KEY,
         base_url=GLM_URL
     )