Update app.py

app.py

@@ -2,72 +2,71 @@ import gradio as gr
 from huggingface_hub import InferenceClient
 import os
 
-api_key=os.environ.get('qwen_API_KEY')
+api_key = os.environ.get('qwen_API_KEY')
 """
 For more information on huggingface_hub Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference
 """
-client = InferenceClient("Qwen/Qwen2.5-72B-Instruct",token=api_key)
+client = InferenceClient("Qwen/Qwen2.5-72B-Instruct", token=api_key)
 
 def respond(
-message,
-history: list[tuple[str, str]],
-system_message,
-max_tokens,
-temperature,
-top_p
+    message,
+    history: list[tuple[str, str]],
+    system_message,
+    max_tokens,
+    temperature,
+    top_p
 ):
-messages = [{"role": "system", "content": system_message}]
+    messages = [{"role": "system", "content": system_message}]
 
+    for val in history:
+        if val[0]:
+            messages.append({"role": "user", "content": val[0]})
+        if val[1]:
+            messages.append({"role": "assistant", "content": val[1]})
 
-for val in history:
-    if val[0]:
-        messages.append({"role": "user", "content": val[0]})
-    if val[1]:
-        messages.append({"role": "assistant", "content": val[1]})
+    messages.append({"role": "user", "content": message})
 
-messages.append({"role": "user", "content": message})
+    response = ""
 
-response = ""
+    for message in client.chat_completion(
+        messages,
+        max_tokens=max_tokens,
+        stream_response=True,
+        temperature=temperature,
+        top_p=top_p
+    ):
+        token = message.choices[0].delta.content
 
-for message in client.chat_completion(
-    messages,
-    max_tokens=max_tokens,
-    stream=True,
-    temperature=temperature,
-    top_p=top_p
-):
-    token = message.choices[0].delta.content
-
-    response += token
-    yield response
+        response += token
+        yield response
     
 example_prompts = [
-    ["How to cook Kung Pao chicken the tastiest?"],
-    ["你是谁开发的？"],
-    ["写一篇关于青春的五言绝句"],
-    ["你是谁?"]
+    ["How to cook Kung Pao chicken the tastiest?", ""],
+    ["你是谁开发的？", ""],
+    ["写一篇关于青春的五言绝句", ""],
+    ["你是谁?", ""]
 ]
 latex_delimiters = [
     {"left": "$$", "right": "$$", "display": True},
-    {"left": "\\[", "right": "\\]", "display": True},{"left": "$", "right": "$", "display": False},
+    {"left": "\\[", "right": "\\]", "display": True},
+    {"left": "$", "right": "$", "display": False},
     {"left": "\\(", "right": "\\)", "display": False}
 ]
 
 demo = gr.ChatInterface(
-respond,
-examples=example_prompts,
-title="千问2.5-72B",
-description="千问2.5-72B聊天机器人",
-additional_inputs=[
-gr.Textbox(value="You are Qwen, created by Alibaba Cloud. You are a helpful assistant.", label="System message"),
-gr.Slider(minimum=1, maximum=8888, value=2048, step=1, label="Max new tokens"),
-gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
-gr.Slider(minimum=0.1, maximum=1.0, value=0.95, step=0.05, label="Top-p (nucleus sampling)"),
-],
-chatbot=gr.Chatbot(show_label=True,latex_delimiters=latex_delimiters, show_copy_button=True)
-
+    fn=respond,
+    examples=example_prompts,
+    title="千问2.5-72B",
+    description="千问2.5-72B聊天机器人",
+    additional_inputs=[
+        gr.Textbox(value="You are Qwen, created by Alibaba Cloud. You are a helpful assistant.", label="System message"),
+        gr.Slider(minimum=1, maximum=8888, value=2048, step=1, label="Max new tokens"),
+        gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
+        gr.Slider(minimum=0.1, maximum=1.0, value=0.95, step=0.05, label="Top-p (nucleus sampling)"),
+    ],
+    chatbot=gr.Chatbot(show_label=True, latex_delimiters=latex_delimiters, show_copy_button=True)
 )
 
-if name == "main":
-demo.queue(default_concurrency_limit=40)
-demo.launch(max_threads=40)
+if __name__ == "__main__":
+    demo.queue(default_concurrency_limit=40)
+    demo.launch(max_threads=40)