Update app.py

app.py

@@ -21,11 +21,8 @@ base_questions = [
 # ============================ Forward 模式问题 ============================
 forward_additional_questions = [
     ("bg_info", """那么接下来我会需要你提供一些你的资料，并分享一些你的性格和喜好。请先告诉我，你的学校、年级、专业，和主修课程是什么？如果能提供你的选课表或resume就更好啦。"""),
-
     ("work_value", """非常好！那你认为“工作”的意义是什么？你觉得一份理想的工作，应该带来哪些价值或满足感？（例如：帮助他人、赚大钱、自由时间、个人成长、创意空间等）"""),
-
     ("personality_summary", "用几句话总结你的性格：比如外向/内向？喜欢挑战？注重细节？讨厌重复吗？"),
-
     ("dream_day", "再描述一下你理想工作的一天是什么样：在哪工作？做什么？和谁合作？忙还是闲？更自由还是更有秩序？")
 ]
 
@@ -46,7 +43,6 @@ forward_done = False
 backward_done = False
 forward_recommendation_given = False
 
-# 新增：多次换方向、深度分析、路线图
 recommendation_round = 0
 forward_deep_dive_done = False
 roadmap_offered = False
@@ -105,7 +101,7 @@ def do_time_roadmap():
     except Exception as e:
         return f"生成路线图时出错: {str(e)}"
 
-# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 深度分析（3个具体职业） ~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 深度分析函数 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 def do_deep_analysis():
     direction = user_profile["forward_direction_choice"] or "尚未选择"
     bg_info = user_profile["bg_info"] or "未知背景"
@@ -161,7 +157,7 @@ def recommend_3directions():
     rec_prompt = f"""
 请根据以下信息，写一份条理清晰的人物画像+3个大方向，并结尾让学生选1~3或'换'：
 - 学术背景: {bg_info}
-- 工作价值: {wv}
+- 工作意义: {wv}
 - 性格: {ps}
 - 理想工作: {dd}
 分两部分：
@@ -204,7 +200,7 @@ def generate_system_prompt():
     dd = user_profile["dream_day"]
     fwd = user_profile["forward_direction_choice"]
 
-    if mode == "是":  # 只有当base question回答“是”时 -> backward
+    if mode == "是":
         return f"""
 你是一位专业的职业规划顾问，使用Backward Design方法帮助学生达成他们的职业目标。
 目标职业: {sc}
@@ -265,15 +261,11 @@ def predict(message, history):
     # ===== 如果在base_questions环节 =====
     if 0 < current_q_index <= len(questions):
         key = questions[current_q_index - 1][0]
-        # 仅当 key == "mode" 且我们还在问第1题 时, 才存回答到 user_profile["mode"]
         if key == "mode" and current_q_index == 1:
-            # 这是回答第一个问题 => 决定 forward/backward
-            user_profile["mode"] = message.strip()
+            user_profile["mode"] = message.strip()   # 只这里写 mode
         else:
-            # 其他base问题(目前没别的), 可以存到 user_profile 也行
             user_profile[key] = message.strip()
 
-    # 如果 base_questions 没问完 -> 问下一道
     if current_q_index < len(questions):
         nxt = questions[current_q_index][1]
         current_q_index += 1
@@ -281,7 +273,7 @@ def predict(message, history):
 
     mode = user_profile.get("mode") or ""
 
-    # ~~~~~~~~~~~~ Backward 模式 ~~~~~~~~~~~~
+    # ~~~~~~~~~~~~ Backward模式 ~~~~~~~~~~~~
     if mode == "是":
         if in_backward_flow and not backward_done:
             if backward_index > 0 and backward_index <= len(backward_additional_questions):
@@ -296,15 +288,14 @@ def predict(message, history):
                 backward_done = True
 
         if backward_done:
-            # 生成backward结果
-            import_text = generate_system_prompt()
             try:
                 api_key = os.environ.get("API_TOKEN")
                 if not api_key:
                     return "错误：API_TOKEN 未设置"
                 client = OpenAI(api_key=api_key)
+                sprompt = generate_system_prompt()
                 msgs = [
-                    {"role":"system","content": import_text},
+                    {"role":"system","content": sprompt},
                     {"role":"user","content": f"请根据{user_profile}给出最终规划"}
                 ]
                 resp = client.chat.completions.create(
@@ -319,25 +310,21 @@ def predict(message, history):
             except Exception as e:
                 return f"发生错误: {str(e)}"
 
-    # ~~~~~~~~~~~~ Forward 模式 ~~~~~~~~~~~~
+    # ~~~~~~~~~~~~ Forward模式 ~~~~~~~~~~~~
     else:
         if in_forward_flow and not forward_done and not forward_deep_dive_done and not roadmap_done:
-            # 存储上一回答(不影响mode)
             if forward_index > 0 and forward_index <= len(forward_additional_questions):
                 prev_key = forward_additional_questions[forward_index - 1][0]
                 user_profile[prev_key] = message.strip()
 
-            # 如果还有forward附加问题没问完
             if forward_index < len(forward_additional_questions):
                 k, prompt_text = forward_additional_questions[forward_index]
                 forward_index += 1
                 return prompt_text
-            # 问完4个问题 -> 推荐3方向
             elif not forward_recommendation_given:
                 forward_recommendation_given = True
                 return recommend_3directions()
             else:
-                # 用户选1/2/3或 '换'
                 choice = message.strip().lower()
                 if choice in ["1","2","3"]:
                     user_profile["forward_direction_choice"] = choice
@@ -347,19 +334,17 @@ def predict(message, history):
                     recommendation_round += 1
                     if recommendation_round > 2:
                         forward_done = True
-                        return "已多次换方向，先结束推荐吧。"
+                        return "已多次换方向，结束推荐了~"
                     else:
                         return recommend_3directions()
                 else:
-                    return "请回复1/2/3选择方向，或输入'换'来重新推荐"
+                    return "请回复1/2/3选择方向，或输入'换'来重选"
 
         elif forward_deep_dive_done and not roadmap_offered:
-            # 深度分析完 -> 问路线图
             roadmap_offered = True
-            return "需要一个时间轴式的职业路线图吗？如果是，请回复“是”，否则回复“否”。"
+            return "需要一个时间轴式职业路线图吗？如果是，请回复“是”，否则回复“否”。"
 
         elif roadmap_offered and not roadmap_done:
-            # 学生答 “是” or “否”
             ans = message.strip().lower()
             if ans == "是":
                 roadmap_done = True
@@ -368,19 +353,18 @@ def predict(message, history):
             else:
                 roadmap_done = True
                 forward_done = True
-                return "好的，不生成路线图，本次规划结束了~"
+                return "好的，不生成时间轴，本次就到这里。"
 
         if forward_done:
-            # 最终输出
-            sprompt = generate_system_prompt()
             try:
                 api_key = os.environ.get("API_TOKEN")
                 if not api_key:
                     return "错误：API_TOKEN 未设置"
                 client = OpenAI(api_key=api_key)
+                sprompt = generate_system_prompt()
                 msgs = [
                     {"role":"system","content":sprompt},
-                    {"role":"user","content": f"以下是学生资料: {user_profile}. 需要更多咨询请提问。"}
+                    {"role":"user","content": f"这是最终资料: {user_profile}, 如果还需要帮助请提问。"}
                 ]
                 resp = client.chat.completions.create(
                     model=model_default,
@@ -394,8 +378,7 @@ def predict(message, history):
             except Exception as e:
                 return f"发生错误: {str(e)}"
 
-    return "信息收集完毕，若尚未得到最终回复，请输入任意内容以继续。"
-
+    return "信息收集完毕，如果尚未得到最终回复，请再输入任意文字继续。"
 
 # ============================ Gradio UI ============================
 with gr.Blocks(css="""
@@ -455,19 +438,20 @@ footer {
           <img src='https://media3.giphy.com/media/v1.Y2lkPTc5MGI3NjExMmFucGwxbmNsd3J5NXV0Y282NXNtMzNsZW5jMm4wNWh6c2dqbXIwdiZlcD12MV9pbnRlcm5hbF9naWZfYnlfaWQmY3Q9Zw/l41m18LjqpzxUr2WA/giphy.gif' width='200' style='border-radius: 12px; box-shadow: 0 0 10px #ec4899;'>
           <div style='text-align: left;'>
             <h1 style='color:white; font-size: 36px; margin-bottom: 6px;'>🎓 多步职业规划助手</h1>
-            <p style='font-size: 18px; font-weight:bold; color:#ec4899; margin-top: 0;'>Forward三步：推荐大方向→深度分析→可选时间轴路线图</p>
+            <p style='font-size: 18px; font-weight:bold; color:#ec4899; margin-top: 0;'>Forward三步：推荐大方向→深度分析→可选时间轴</p>
           </div>
         </div>
         """)
-   gr.Markdown("""
-    **📝 Forward / Backward 多轮交互，附带换方向、深度分析、以及可选时间轴路线图**  
-    1. 如果你已有明确职业目标 => 回答“是”（Backward）  
-    2. 如果还在探索 => 回答“否”（Forward）  
-    3. Forward模式下：先问4个问题→推荐3大方向→可换→选定后深度分析→询问是否要路线图
-    """)
-
-    chatbot = gr.Chatbot(height=500, show_label=False, show_copy_button=True, type="messages")
-
+    gr.Markdown("""
+**Forward / Backward** 多轮交互；Forward可换方向+深度分析+时间轴；Backward直接问目标职业+背景
+""")
+
+    chatbot = gr.Chatbot(
+        height=500,
+        show_label=False,
+        show_copy_button=True,
+        type="messages"
+    )
     with gr.Row():
         with gr.Column(scale=8):
             msg = gr.Textbox(placeholder="请在这���输入你的回答...", show_label=False, container=False)
@@ -476,25 +460,25 @@ footer {
 
     with gr.Row():
         reset_btn = gr.Button("🔄 重新开始")
-        
-    def add_user_message(m, h):
-        h = h or []
-        h.append({"role":"user","content":m})
-        return "", h
 
-    def add_bot_response(h):
-        user_m = h[-1]["content"]
-        bot_m = predict(user_m, h[:-1])
-        h.append({"role":"assistant","content":bot_m})
-        return h
+    def add_message(m, hist):
+        hist = hist or []
+        hist.append({"role":"user","content":m})
+        return "", hist
 
-    send.click(add_user_message, [msg, chatbot], [msg, chatbot]) \
-        .then(add_bot_response, chatbot, chatbot)
+    def bot_response(hist):
+        hist = hist or []
+        user_m = hist[-1]["content"]
+        bot_m = predict(user_m, hist[:-1])
+        hist.append({"role":"assistant","content":bot_m})
+        return hist
 
-    msg.submit(add_user_message, [msg, chatbot], [msg, chatbot]) \
-       .then(add_bot_response, chatbot, chatbot)
+    submit_btn.click(add_message, [msg, chatbot], [msg, chatbot]) \
+        .then(bot_response, chatbot, chatbot)
+    msg.submit(add_message, [msg, chatbot], [msg, chatbot]) \
+       .then(bot_response, chatbot, chatbot)
 
-    def reset_all():
+    def reset_state():
         global current_q_index, questions
         global in_forward_flow, in_backward_flow
         global forward_index, backward_index
@@ -509,21 +493,23 @@ footer {
         for k in user_profile:
             user_profile[k] = None
 
-        in_forward_flow = in_backward_flow = False
-        forward_index = backward_index = 0
-        forward_done = backward_done = False
+        in_forward_flow = False
+        in_backward_flow = False
+        forward_index = 0
+        backward_index = 0
+        forward_done = False
+        backward_done = False
         forward_recommendation_given = False
         recommendation_round = 0
         forward_deep_dive_done = False
         roadmap_offered = False
         roadmap_done = False
-        return []
-
-    reset.click(reset_all, outputs=chatbot)
 
-    def start():
-        return [{"role":"assistant","content": questions[0][1]}]
+        return []
+    reset_btn.click(reset_state, outputs=chatbot)
 
-    demo.load(start, outputs=chatbot)
+    def auto_first():
+        return [{"role": "assistant", "content": questions[0][1]}]
 
-demo.launch()
+    demo.load(auto_first, outputs=chatbot)
+    demo.launch()