Update app.py

app.py

@@ -1,219 +1,61 @@
 import gradio as gr
 from openai import OpenAI
 import os
-import time
-
-# Store user responses
-user_profile = {
-    "mode": None,
-    "age": None,
-    "degree": None,
-    "interests": None,
-    "mbti": None
-}
-
-questions = [
-    ("mode", "Do you already have a target career, or are you still exploring? (Reply with 'Forward' or 'Backward')"),
-    ("age", "What's your age range? (e.g., 'under 18', '18-21', '21-25', '25-29')"),
-    ("degree", "What is your current degree? (e.g., Bachelor's, Master's, PhD)"),
-    ("interests", "List a few of your interests, separated by commas. (e.g., Programming, Psychology, Design)"),
-    ("mbti", "What's your MBTI personality type? (e.g., INFP, INTJ, ENFP, etc.)")
-]
-
-current_q_index = 0
-
-# Defaults
-system_prompt_default = "You are a helpful and knowledgeable AI career assistant."
-model_default = "gpt-4o"
-temp_default = 0.7
-top_p_default = 0.95
-token_default = 2000
-
-# Placeholder to store setting values
-system_prompt_box = gr.Textbox(system_prompt_default)
-model_dropdown = gr.Dropdown(["gpt-4o", "gpt-4o-mini"], value=model_default)
-token_slider = gr.Slider(800, 4000, value=token_default)
-temp_slider = gr.Slider(0, 1, value=temp_default)
-top_p_slider = gr.Slider(0, 1, value=top_p_default)
 
+# 简化版本的预测函数
 def predict(message, history):
-    global current_q_index
-
-    # Get values from global widgets
-    system_prompt = system_prompt_box.value
-    model = model_dropdown.value
-    max_tokens = token_slider.value
-    temperature = temp_slider.value
-    top_p = top_p_slider.value
-    
-    # Initialize the OpenAI client
-    client = OpenAI(
-        api_key=os.environ.get("API_TOKEN"),
-    )
-
-    if current_q_index > 0 and current_q_index <= len(questions):
-        key = questions[current_q_index - 1][0]
-        user_profile[key] = message.strip()
-
-    if current_q_index < len(questions):
-        question = questions[current_q_index][1]
-        current_q_index += 1
-        return question
-
-    # Profile-based response
-    mode = user_profile["mode"] or "Forward"
-    age = user_profile["age"]
-    degree = user_profile["degree"]
-    interests = user_profile["interests"]
-    mbti = user_profile["mbti"]
-
-    if "Forward" in mode:
-        system_prompt = system_prompt or f"""
-You are a career planning AI assistant. The student wants to explore suitable career options.
-Student profile:
-- Age: {age}
-- Degree: {degree}
-- Interests: {interests}
-- MBTI Type: {mbti}
-Please recommend several career paths based on this background, and describe entry requirements and preparation steps (courses, certifications, skills, etc.).
-"""
-    else:
-        system_prompt = system_prompt or f"""
-You are a career planning AI assistant. The student already has a target career.
-Student profile:
-- Age: {age}
-- Degree: {degree}
-- Interests: {interests}
-- MBTI Type: {mbti}
-Please reverse-design the career path based on this background, including required courses, skill preparation, school resources, and internship advice.
-"""
-
-    # Start with the system prompt
-    messages = [{"role": "system", "content": system_prompt}]
-
-    # Add the conversation history
-    messages.extend(history if history else [])
-
-    # Add the current user message
-    messages.append({"role": "user", "content": message})
-
-    # Create streaming response
-    response = client.chat.completions.create(
-        model=model,
-        messages=messages,
-        max_tokens=max_tokens,
-        temperature=temperature,
-        top_p=top_p,
-        stream=True
-    )
-
-    full_message = ""
-    last_yield_time = None
-
-    for chunk in response:
-        if chunk.choices and chunk.choices[0].delta.content:
-            full_message += chunk.choices[0].delta.content
-            current_time = time.time()
+    try:
+        # 初始化OpenAI客户端
+        api_key = os.environ.get("API_TOKEN")
+        if not api_key:
+            return "错误：API密钥未设置，请在Hugging Face Space设置中添加名为API_TOKEN的Secret。"
             
-            if last_yield_time is None or (current_time - last_yield_time >= 0.25):
-                yield full_message
-                last_yield_time = current_time
-
-    # Ensure to yield any remaining message that didn't meet the time threshold
-    if full_message:
-        yield full_message
-
+        client = OpenAI(api_key=api_key)
+        
+        # 构建消息
+        messages = [
+            {"role": "system", "content": "你是一个有用的AI助手。"},
+            {"role": "user", "content": message}
+        ]
+        
+        # 非流式调用，更简单更可靠
+        response = client.chat.completions.create(
+            model="gpt-4o",
+            messages=messages,
+            max_tokens=1000,
+            temperature=0.7,
+            stream=False  # 关闭流式响应
+        )
+        
+        return response.choices[0].message.content
+    except Exception as e:
+        return f"发生错误: {str(e)}"
 
-# Create the interface with custom styling
+# 创建简化版界面
 with gr.Blocks(css="""
-    body {
-        background-color: #1e1e1e;
-        color: #ffffff;
-    }
-
-    .gradio-container {
-        font-family: 'Segoe UI', sans-serif;
-    }
-
-    .gr-chatbot {
-        background-color: transparent !important;
-    }
-
-    .message.user {
-        background-color: #cce6ff !important;   /* Much lighter blue */
-        color: #000000 !important;
-        border-radius: 10px !important;
-        padding: 10px;
-        margin: 6px;
-    }
-
-    .message.bot {
-        background-color: #99ccff !important;   /* Lighter blue */
-        color: #000000 !important;
-        border-radius: 10px !important;
-        padding: 10px;
-        margin: 6px;
-    }
-
-    .gr-button {
-        border-radius: 8px;
-    }
-
     #custom-send {
         background-color: #ec4899 !important;
         color: white !important;
         border-radius: 999px !important;
         padding: 10px 24px !important;
         font-weight: bold;
-        box-shadow: 0 0 10px #ec4899;
-        transition: all 0.3s ease-in-out;
     }
-
-    #custom-send:hover {
-        background-color: #d63384 !important;
-        box-shadow: 0 0 12px #ec4899;
-    }
-
-    textarea, input {
-        background-color: #ffe4f1 !important;
-        color: #5e2c49 !important;
-        border: 1px solid #ec4899 !important;
-    }
-
+    
     footer {
         display: none !important;
     }
 """) as demo:
-
-    with gr.Row():
-        gr.HTML("""
-        <div style='display: flex; align-items: center; justify-content: center; gap: 20px; margin-bottom: 10px;'>
-        <!-- 左侧动图 -->
-         <img src='https://media3.giphy.com/media/v1.Y2lkPTc5MGI3NjExMmFucGwxbmNsd3J5NXV0Y282NXNtMzNsZW5jMm4wNWh6c2dqbXIwdiZlcD12MV9pbnRlcm5hbF9naWZfYnlfaWQmY3Q9Zw/l41m18LjqpzxUr2WA/giphy.gif' width='200' style='border-radius: 12px; box-shadow: 0 0 10px #ec4899;'>
-
-        <!-- 右侧标题 -->
-       <div style='text-align: left;'>
-        <h1 style='color:white; font-size: 36px; margin-bottom: 6px;'>🎓 AI Career Exploration Assistant</h1>
-        <p style='font-size: 18px; font-weight:bold; color:#ec4899; margin-top: 0;margin-left: 150px'>Hi! Lets Make the Dream Comes True 💖</p>
-       </div>
-       </div>
-        """)
-        
-    gr.Markdown("**Let's chat! 💬** Ask me anything you want")
+    gr.HTML("""
+    <div style='text-align: center; margin-bottom: 10px;'>
+    <h1 style='color:white; font-size: 28px; margin-bottom: 6px;'>🎓 AI Career Assistant</h1>
+    </div>
+    """)
     
-    gr.ChatInterface(
-        fn=predict,
-        chatbot=gr.Chatbot(height=500),
-        textbox=gr.Textbox(placeholder="Type your reply here..."),
-        submit_btn=gr.Button("🚀 Send", elem_id="custom-send")
-    )
-
-    with gr.Accordion("⚙️ Advanced Settings (Click to Show/Hide)", open=False):
-        gr.Markdown("#### Prompt & Model Settings")
-        system_prompt_box.render()
-        model_dropdown.render()
-        token_slider.render()
-        temp_slider.render()
-        top_p_slider.render()
+    chatbot = gr.Chatbot()
+    msg = gr.Textbox(placeholder="输入你的问题...", show_label=False)
+    send_btn = gr.Button("发送", elem_id="custom-send")
+    
+    send_btn.click(predict, [msg, chatbot], [chatbot])
+    msg.submit(predict, [msg, chatbot], [chatbot])
 
 demo.launch()