Update app.py

app.py

@@ -107,6 +107,7 @@ def predict(message, history):
     global forward_done, backward_done
     global forward_recommendation_given
 
+    # 第一次对话，重置
     if not history:
         current_q_index = 0
         questions = base_questions[:]
@@ -121,47 +122,65 @@ def predict(message, history):
         backward_done = False
         forward_recommendation_given = False
 
-    # 如果还在问 base_questions
+    # ========== 存储 base_questions 回答 ==========
+    # 如果还在问 base_questions（只有1题，就1个循环）
     if 0 < current_q_index <= len(questions):
         key = questions[current_q_index - 1][0]
         user_profile[key] = message.strip()
-        if key == "mode" and "是" in user_profile["mode"]:
-            questions.insert(1, ("specific_career", "请具体描述你想要从事的职业方向。"))
-            in_backward_flow = True
-        elif key == "mode" and "否" in user_profile["mode"]:
-            in_forward_flow = True
-
+        # 如果回答了 mode 问题
+        if key == "mode":
+            if "是" in user_profile["mode"]:
+                questions.insert(1, ("specific_career", "请具体描述你想要从事的职业方向。"))
+                in_backward_flow = True
+            elif "否" in user_profile["mode"]:
+                in_forward_flow = True
+
+    # 如果 base_questions 还没问完，就继续问
     if current_q_index < len(questions):
         nxt = questions[current_q_index][1]
         current_q_index += 1
         return nxt
 
+    # ========== 进入 Forward / Backward 的额外问题 ==========
     mode = user_profile.get("mode") or ""
 
-    # ========== Backward ==========
+    # --- Backward 模式 ---
     if "是" in mode:
         if in_backward_flow and not backward_done:
+            # 存储上一次回答到 user_profile
+            # backward_index > 0 才说明至少问过1个 backward问题
+            if backward_index > 0 and backward_index <= len(backward_additional_questions):
+                prev_key = backward_additional_questions[backward_index - 1][0]
+                user_profile[prev_key] = message.strip()
+
+            # 是否还有下一个问题
             if backward_index < len(backward_additional_questions):
                 k, prompt_text = backward_additional_questions[backward_index]
                 backward_index += 1
                 return prompt_text
             else:
+                # 问完了
                 backward_done = True
 
-    # ========== Forward ==========
+    # --- Forward 模式 ---
     else:
         if in_forward_flow and not forward_done:
-            # 如果还没问完 Forward问题
+            # 存储上一次回答到 user_profile
+            # forward_index > 0 才说明至少问过1个 forward问题
+            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
 
-            # 如果已问完4个问题，但没推荐过方向
+            # 如果 4 个 Forward问题都问完，但还没推荐过方向
             elif not forward_recommendation_given:
                 forward_recommendation_given = True
 
-                # ================== 调试打印 user_profile ==================
                 print("===== Debug user_profile =====")
                 print(user_profile)
 
@@ -173,7 +192,7 @@ def predict(message, history):
 
                     recommendation_prompt = f"""
 请根据以下信息，为这位学生撰写一份结构化、条理清晰的“人物画像分析”：
-- 学术背景: {user_profile['bg_info']} 
+- 学术背景: {user_profile['bg_info']}
 - 工作意义: {user_profile['work_value']}
 - 性格总结: {user_profile['personality_summary']}
 - 理想工作状态: {user_profile['dream_day']}
@@ -199,7 +218,6 @@ def predict(message, history):
 如果信息不足，请基于通用逻辑合理推断。请使用中文分段写作，字数不少于500字。
 """
 
-                    # ================== 调试打印 recommendation_prompt ==================
                     print("===== Debug recommendation_prompt =====")
                     print(recommendation_prompt)
 
@@ -221,11 +239,11 @@ def predict(message, history):
                     return f"生成推荐方向时出错: {str(e)}"
 
             else:
-                # 等待用户输入方向choice
+                # 已推荐过方向，现在用户输入了方向选择
                 user_profile["forward_direction_choice"] = message.strip()
                 forward_done = True
 
-    # ========== 最终生成阶段 ==========
+    # 如果走到这里，说明 Backward_done / Forward_done
     if ("是" in mode and backward_done) or ("否" in mode and forward_done):
         try:
             api_key = os.environ.get("API_TOKEN")
@@ -312,24 +330,32 @@ footer {
         <div style='display: flex; align-items: center; justify-content: center; gap: 20px; margin-bottom: 10px;'>
           <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;'>🎓 AI职业规划助手（升级版）</h1>
+            <h1 style='color:white; font-size: 36px; margin-bottom: 6px;'>🎓 AI职业规划助手（修正版）</h1>
             <p style='font-size: 18px; font-weight:bold; color:#ec4899; margin-top: 0;margin-left: 150px'>让梦想照进现实 💖</p>
           </div>
         </div>
         """)
 
     gr.Markdown("""
-    **📝 Forward / Backward 多轮交互：新增“自动职业方向推荐”功能**  
-    - 若已确定方向：回答“是”（Backward）
-    - 若还在探索：回答“否”（Forward）
-    - Forward模式会在你回答完四大问题后，自动给出一个简短“学生画像”+3个大方向供你选择
+    **📝 修正版：确保Forward / Backward问题回答也存入 user_profile**  
+    - 逐题逐答，不要一次性粘贴所有回答
+    - 这样每个回答都会写进 user_profile，再进行下一题
     """)
 
-    chatbot = gr.Chatbot(height=500, show_label=False, show_copy_button=True, type="messages")
+    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="请在这里输入你的回答...", show_label=False, container=False)
+            msg = gr.Textbox(
+                placeholder="请在这里输入你的回答...",
+                show_label=False,
+                container=False
+            )
         with gr.Column(scale=1):
             submit_btn = gr.Button("🚀 发送", elem_id="custom-send")
 
@@ -348,11 +374,25 @@ footer {
         history.append({"role": "assistant", "content": bot_message})
         return history
 
-    submit_btn.click(fn=add_message, inputs=[msg, chatbot], outputs=[msg, chatbot]) \
-              .then(fn=bot_response, inputs=[chatbot], outputs=[chatbot])
-
-    msg.submit(fn=add_message, inputs=[msg, chatbot], outputs=[msg, chatbot]) \
-       .then(fn=bot_response, inputs=[chatbot], outputs=[chatbot])
+    submit_btn.click(
+        fn=add_message,
+        inputs=[msg, chatbot],
+        outputs=[msg, chatbot]
+    ).then(
+        fn=bot_response,
+        inputs=[chatbot],
+        outputs=[chatbot]
+    )
+
+    msg.submit(
+        fn=add_message,
+        inputs=[msg, chatbot],
+        outputs=[msg, chatbot]
+    ).then(
+        fn=bot_response,
+        inputs=[chatbot],
+        outputs=[chatbot]
+    )
 
     def reset_conversation():
         global current_q_index, questions
@@ -375,7 +415,12 @@ footer {
         forward_recommendation_given = False
         return []
 
-    reset_btn.click(fn=reset_conversation, inputs=None, outputs=chatbot, queue=False)
+    reset_btn.click(
+        fn=reset_conversation,
+        inputs=None,
+        outputs=chatbot,
+        queue=False
+    )
 
     def auto_first_question():
         return [{"role": "assistant", "content": questions[0][1]}]