diff --git a/fastchat/serve/api_provider.py b/fastchat/serve/api_provider.py
index 9fa852bca..1e319f0a2 100644
--- a/fastchat/serve/api_provider.py
+++ b/fastchat/serve/api_provider.py
@@ -99,17 +99,19 @@ def openai_api_stream_iter(
 ):
     import openai
 
-    is_azure = False
+    api_key = api_key or os.environ["OPENAI_API_KEY"]
+
     if "azure" in model_name:
-        is_azure = True
-        openai.api_type = "azure"
-        openai.api_version = "2023-07-01-preview"
+        client = openai.AzureOpenAI(
+            api_version="2023-07-01-preview",
+            azure_endpoint=api_base or "https://api.openai.com/v1",
+            api_key=api_key,
+        )
     else:
-        openai.api_type = "open_ai"
-        openai.api_version = None
+        client = openai.OpenAI(
+            base_url=api_base or "https://api.openai.com/v1", api_key=api_key
+        )
 
-    openai.api_base = api_base or "https://api.openai.com/v1"
-    openai.api_key = api_key or os.environ["OPENAI_API_KEY"]
     if model_name == "gpt-4-turbo":
         model_name = "gpt-4-1106-preview"
 
@@ -123,26 +125,17 @@ def openai_api_stream_iter(
     }
     logger.info(f"==== request ====\n{gen_params}")
 
-    if is_azure:
-        res = openai.ChatCompletion.create(
-            engine=model_name,
-            messages=messages,
-            temperature=temperature,
-            max_tokens=max_new_tokens,
-            stream=True,
-        )
-    else:
-        res = openai.ChatCompletion.create(
-            model=model_name,
-            messages=messages,
-            temperature=temperature,
-            max_tokens=max_new_tokens,
-            stream=True,
-        )
+    res = client.chat.completions.create(
+        model=model_name,
+        messages=messages,
+        temperature=temperature,
+        max_tokens=max_new_tokens,
+        stream=True,
+    )
     text = ""
     for chunk in res:
-        if len(chunk["choices"]) > 0:
-            text += chunk["choices"][0]["delta"].get("content", "")
+        if len(chunk.choices) > 0:
+            text += chunk.choices[0].delta.content or ""
             data = {
                 "text": text,
                 "error_code": 0,
diff --git a/fastchat/serve/gradio_block_arena_vision.py b/fastchat/serve/gradio_block_arena_vision.py
index 60cad07c6..e9a7e7b17 100644
--- a/fastchat/serve/gradio_block_arena_vision.py
+++ b/fastchat/serve/gradio_block_arena_vision.py
@@ -41,7 +41,6 @@ def build_single_vision_language_model_ui(models, add_promotion_links=False):
     notice_markdown = f"""
 # 🏔️ Chat with Open Large Vision-Language Models
 {promotion}
-## 🤖 Choose any model to chat
 """
 
     state = gr.State()
diff --git a/fastchat/utils.py b/fastchat/utils.py
index 13a6333f0..5f14abce8 100644
--- a/fastchat/utils.py
+++ b/fastchat/utils.py
@@ -154,10 +154,7 @@ def oai_moderation(text):
     """
     import openai
 
-    openai.api_base = "https://api.openai.com/v1"
-    openai.api_key = os.environ["OPENAI_API_KEY"]
-    openai.api_type = "open_ai"
-    openai.api_version = None
+    client = openai.OpenAI(api_key=os.environ["OPENAI_API_KEY"])
 
     threshold_dict = {
         "sexual": 0.2,
@@ -165,13 +162,13 @@ def oai_moderation(text):
     MAX_RETRY = 3
     for _ in range(MAX_RETRY):
         try:
-            res = openai.Moderation.create(input=text)
-            flagged = res["results"][0]["flagged"]
+            res = client.moderations.create(input=text)
+            flagged = res.results[0].flagged
             for category, threshold in threshold_dict.items():
-                if res["results"][0]["category_scores"][category] > threshold:
+                if getattr(res.results[0].category_scores, category) > threshold:
                     flagged = True
             break
-        except (openai.error.OpenAIError, KeyError, IndexError) as e:
+        except (openai.OpenAIError, KeyError, IndexError) as e:
             # flag true to be conservative
             flagged = True
             print(f"MODERATION ERROR: {e}\nInput: {text}")