Update app.py

app.py

@@ -1,69 +1,73 @@
 import gradio as gr
 from huggingface_hub import InferenceClient
 import os
-import json
 
-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
+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]})
 
-    messages.append({"role": "user", "content": 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]})
 
-    response = ""
+messages.append({"role": "user", "content": message})
 
-    try:
-        async 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
-    except Exception as e:
-        yield f"An error occurred: {e}"
+response = ""
 
+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
+    
 example_prompts = [
     ["How to cook Kung Pao chicken the tastiest?"],
-    ["Help me create an email expressing my greetings to an old friend."],
+    ["你是谁开发的？"],
     ["写一篇关于青春的五言绝句"],
-    ["你是谁？"]
+    ["你是谁?"]
+]
+latex_delimiters = [
+    {"left": "$$", "right": "$$", "display": True},
+    {"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, show_copy_button=True)
+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)