diff --git a/config.py b/config.py
index 2c3bf42..2f8e305 100644
--- a/config.py
+++ b/config.py
@@ -5,7 +5,7 @@
 
 ################## LLM ##################
 LLM_OPTION = os.getenv('LLM_OPTION', 'openai')  # select your LLM service
-LANGUAGE = 'en'  # options: en, zh
+LANGUAGE = os.getenv('LANGUAGE', 'en')  # options: en, zh
 CHAT_CONFIG = {
     'openai': {
         'openai_model': 'gpt-3.5-turbo',
@@ -57,7 +57,7 @@
 
 ################## Embedding ##################
 TEXTENCODER_CONFIG = {
-    'model': 'multi-qa-mpnet-base-cos-v1',
+    'model': f'BAAI/bge-base-{LANGUAGE}',
     'device': -1, # -1 will use cpu
     'norm': True,
     'dim': 768
@@ -108,10 +108,17 @@
 
 
 ############### Rerank configs ##################
+if LANGUAGE == 'en' and INSERT_MODE == 'osschat-insert':
+    rerank_model = 'cross-encoder/ms-marco-MiniLM-L-12-v2'
+elif LANGUAGE == 'zh' and INSERT_MODE == 'osschat-insert':
+    rerank_model = 'amberoad/bert-multilingual-passage-reranking-msmarco'
+else:
+    raise NotImplementedError
+
 RERANK_CONFIG = {
-    'rerank': True,
-    'rerank_model': 'cross-encoder/ms-marco-MiniLM-L-12-v2',
-    'threshold': 0.6,
+    'rerank': True, # or False
+    'rerank_model': rerank_model,
+    'threshold': 0.0,
     'rerank_device': -1  # -1 will use cpu
 }
 
@@ -123,4 +130,4 @@
 QUESTIONGENERATOR_CONFIG = {
     'model_name': 'gpt-3.5-turbo',
     'temperature': 0,
-}
\ No newline at end of file
+}
diff --git a/tests/unit_tests/src_towhee/pipelines/test_pipelines.py b/tests/unit_tests/src_towhee/pipelines/test_pipelines.py
index 082ed56..1f84e24 100644
--- a/tests/unit_tests/src_towhee/pipelines/test_pipelines.py
+++ b/tests/unit_tests/src_towhee/pipelines/test_pipelines.py
@@ -84,7 +84,7 @@ def test_openai(self):
             token_count = 0
             for x in res:
                 token_count += x[0]['token_count']
-            assert token_count == 290
+            assert token_count == 261
             num = pipelines.count_entities(self.project)['vector store']
             assert len(res) <= num
 
@@ -121,7 +121,7 @@ def test_chatglm(self):
             token_count = 0
             for x in res:
                 token_count += x[0]['token_count']
-            assert token_count == 290
+            assert token_count == 261
             num = pipelines.count_entities(self.project)['vector store']
             assert len(res) <= num
 
@@ -160,7 +160,7 @@ def json(self):
             token_count = 0
             for x in res:
                 token_count += x[0]['token_count']
-            assert token_count == 290
+            assert token_count == 261
             num = pipelines.count_entities(self.project)['vector store']
             assert len(res) <= num
 
@@ -205,7 +205,7 @@ def output(self):
             token_count = 0
             for x in res:
                 token_count += x[0]['token_count']
-            assert token_count == 290
+            assert token_count == 261
             num = pipelines.count_entities(self.project)['vector store']
             assert len(res) <= num
 
@@ -244,7 +244,7 @@ def json(self):
             token_count = 0
             for x in res:
                 token_count += x[0]['token_count']
-            assert token_count == 290
+            assert token_count == 261
             num = pipelines.count_entities(self.project)['vector store']
             assert len(res) <= num
 
@@ -285,7 +285,7 @@ def iter_lines(self):
             token_count = 0
             for x in res:
                 token_count += x[0]['token_count']
-            assert token_count == 290
+            assert token_count == 261
             num = pipelines.count_entities(self.project)['vector store']
             assert len(res) <= num
 
@@ -323,7 +323,7 @@ def __call__(self, *args, **kwargs):
             token_count = 0
             for x in res:
                 token_count += x[0]['token_count']
-            assert token_count == 290
+            assert token_count == 261
             num = pipelines.count_entities(self.project)['vector store']
             assert len(res) <= num