enhance: use urllib join instead of fstring (#9549)

api/services/enterprise/base.py

@@ -1,4 +1,5 @@
 import os
+from urllib.parse import urljoin
 
 import requests
 
@@ -15,8 +16,7 @@ class EnterpriseRequest:
     @classmethod
     def send_request(cls, method, endpoint, json=None, params=None):
         headers = {"Content-Type": "application/json", "Enterprise-Api-Secret-Key": cls.secret_key}
-
-        url = f"{cls.base_url}{endpoint}"
+        url = urljoin(cls.base_url, endpoint)
         response = requests.request(method, url, json=json, params=params, headers=headers, proxies=cls.proxies)
 
         return response.json()

api/tests/unit_tests/core/model_runtime/model_providers/wenxin/test_text_embedding.py

@@ -1,3 +1,5 @@
+import string
+
 import numpy as np
 
 from core.model_runtime.entities.text_embedding_entities import TextEmbeddingResult
@@ -31,7 +33,7 @@ def test_max_chunks():
     max_chunks = embedding_model._get_max_chunks(model, credentials)
     embedding_model._create_text_embedding = _create_text_embedding
 
-    texts = ["0123456789" for i in range(0, max_chunks * 2)]
+    texts = [string.digits for i in range(0, max_chunks * 2)]
     result: TextEmbeddingResult = embedding_model.invoke(model, credentials, texts, "test")
     assert len(result.embeddings) == max_chunks * 2