Update app.py

app.py

@@ -429,10 +429,8 @@ def predict(message, history):
             user_profile["mode"] = ans
             if "是" in ans:
                 in_backward_flow = True
-                in_forward_flow = False  # 确保互斥
             else:
                 in_forward_flow = True
-                in_backward_flow = False  # 确保互斥
         else:
             user_profile[key] = message.strip()
 
@@ -441,38 +439,35 @@ def predict(message, history):
         current_q_index += 1
         return nxt
 
-    # 打印调试信息
-    # print(f"Mode: {user_profile.get('mode')}, Backward: {in_backward_flow}, Forward: {in_forward_flow}")
-    # print(f"Current indexes - Backward: {backward_index}, Forward: {forward_index}")
-
     # ======================== 分模式处理 =========================
+    mode = user_profile.get("mode") or ""
+
     # ~~~~~~~~~ Backward模式 ~~~~~~~~~
-    if in_backward_flow:
-        # 处理上一个问题的回答
-        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()
-
-        # 提出下一个问题
-        if backward_index < len(backward_additional_questions):
-            k, prompt_text = backward_additional_questions[backward_index]
-            backward_index += 1
-            return prompt_text
-        else:
-            # 所有问题都已回答完毕
-            if not post_career_detail_asked:
+    if mode == "是":
+        if in_backward_flow and not backward_done:
+            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()
+
+            if backward_index < len(backward_additional_questions):
+                k, prompt_text = backward_additional_questions[backward_index]
+                backward_index += 1
+                return prompt_text
+            else:
+                # 修改这里，不要直接设置backward_done为True
+                # 而是需要生成职业详情并询问是否需要A/B/C专项信息
                 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)
                     
-                    # 生成职业详情
+                    # 先生成职业详情
                     career_detail_prompt = f"""
 你是一位专业的职业规划顾问。
 学生目标职业: {user_profile.get('specific_career') or '未知'}
 学生背景: {user_profile.get('bg_info') or '未知'}
-请为这位想要从事 {user_profile.get('specific_career')} 职业的学生写一份详细的职业说明，至少包含：
+请写一份详细的职业说明，至少包含：
 1. 行业平均薪资（初级/中级/高级）
 2. 工作环境（远程/混合/办公室，团队规模等）
 3. 晋升难度（需要什么资历或条件）
@@ -495,81 +490,86 @@ def predict(message, history):
                     )
                     detail_msg = resp.choices[0].message.content
                     
-                    # 设置状态
+                    # 设置状态，与Forward模式保持一致
                     user_profile["final_choice"] = user_profile.get("specific_career")
-                    job_chosen = True  # 直接标记为已选择职业
+                    job_chosen = True
+                    forward_deep_dive_done = True
                     post_career_detail_asked = True
                     
                     # 返回职业详情并询问A/B/C
                     return detail_msg + "\n\n我还可以针对以下三方面提供更深入的分析建议：" \
-                           "\n- A：专业/选课 & 求职方向" \
-                           "\n- B：本校资源利用建议" \
-                           "\n- C：实习 & networking 积累" \
-                           "\n如果你想查看其中一个或多个，请输入 A / B / C / AB / BC / AC / ABC" \
-                           "\n如果都不需要，请回复'不需要'。"
+                        "\n- A：专业/选课 & 求职方向" \
+                        "\n- B：本校资源利用建议" \
+                        "\n- C：实习 & networking 积累" \
+                        "\n如果你想查看其中一个或多个，请输入 A / B / C / AB / BC / AC / ABC" \
+                        "\n如果都不需要，请回复'不需要'。"
                     
                 except Exception as e:
                     return f"生成职业详情时出错: {str(e)}"
-            
-            # 处理 A/B/C 答疑
-            elif post_career_detail_asked and not post_career_detail_done:
-                user_choice = message.strip().lower()
-                if user_choice in ["不需要", "no", "n"]:
-                    post_career_detail_done = True
-                    roadmap_offered = True
-                    return "好的，不查看这三个专项。那需要一个时间轴式职业路线图吗？如需，则回复【要】，否则回复【不要】。"
-                else:
-                    abc_text = answer_abc_questions(
-                        selected=user_choice,
-                        bg_info=user_profile.get("bg_info", ""),
-                        wv=user_profile.get("work_value", "未提供"),
-                        ps=user_profile.get("personality_summary", "未提供"),
-                        dd=user_profile.get("dream_day", "未提供")
-                    )
-                    post_career_detail_done = True
-                    roadmap_offered = True
-                    return abc_text + "\n\n以上是你所选的A/B/C专项信息。需要一个时间轴式职业路线图吗？如需，则回复【要】，否则回复【不要】。"
-            
-            # 处理是否需要时间轴路线图
-            elif roadmap_offered and not roadmap_done:
-                ans = message.strip().lower()
-                if ans in ["要", "yes", "y"]:
-                    roadmap_done = True
-                    backward_done = True
-                    return do_time_roadmap()
-                else:
-                    roadmap_done = True
-                    backward_done = True
-                    return "好的，不生成时间轴，本次规划结束。"
-            
-            # 最终收尾 (仅在所有流程都完成时才会触发)
-            if backward_done:
-                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"以下是资料: {user_profile}. 若需要更多咨询可再次输入"}
-                    ]
-                    resp = client.chat.completions.create(
-                        model=model_default,
-                        messages=msgs,
-                        max_tokens=token_default,
-                        temperature=temp_default,
-                        top_p=top_p_default,
-                        stream=False
-                    )
-                    return resp.choices[0].message.content
-                except Exception as e:
-                    return f"发生错误: {str(e)}"
+        
+        # 处理 A/B/C 答疑 (复用Forward模式的逻辑)
+        elif post_career_detail_asked and not post_career_detail_done:
+            user_choice = message.strip().lower()
+            if user_choice in ["不需要", "no", "n"]:
+                post_career_detail_done = True
+                roadmap_offered = True
+                return "好的，不查看这三个专项。那需要一个时间轴式职业路线图吗？如需，则回复【要】，否则回复【不要】。"
+            else:
+                abc_text = answer_abc_questions(
+                    selected=user_choice,
+                    bg_info=user_profile.get("bg_info", ""),
+                    wv=user_profile.get("work_value", "未提供"),
+                    ps=user_profile.get("personality_summary", "未提供"),
+                    dd=user_profile.get("dream_day", "未提供")
+                )
+                post_career_detail_done = True
+                roadmap_offered = True
+                return abc_text + "\n\n以上是你所选的A/B/C专项信息。需要一个时间轴式职业路线图吗？如需，则回复【要】，否则回复【不要】。"
+        
+        # 处理是否需要时间轴路线图 (复用Forward模式的逻辑)
+        elif job_chosen and not roadmap_offered and not roadmap_done:
+            roadmap_offered = True
+            return "需要一个时间轴式职业路线图吗？如需，则回复【要】，否则回复【不要】。"
+        
+        elif roadmap_offered and not roadmap_done:
+            ans = message.strip().lower()
+            if ans in ["要", "yes", "y"]:
+                roadmap_done = True
+                backward_done = True
+                return do_time_roadmap()
+            else:
+                roadmap_done = True
+                backward_done = True
+                return "好的，不生成时间轴，本次规划结束。"
+        
+        # 最终收尾 (仅在所有流程都完成时才会触发)
+        if backward_done:
+            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"以下是资料: {user_profile}. 若需要更多咨询可再次输入"}
+                ]
+                resp = client.chat.completions.create(
+                    model=model_default,
+                    messages=msgs,
+                    max_tokens=token_default,
+                    temperature=temp_default,
+                    top_p=top_p_default,
+                    stream=False
+                )
+                return resp.choices[0].message.content
+            except Exception as e:
+                return f"发生错误: {str(e)}"
 
     # ~~~~~~~~~ Forward模式 ~~~~~~~~~
-    elif in_forward_flow:
+    else:
         # 前期处理：收集信息和推荐大方向
-        if not direction_chosen:
+        if in_forward_flow and not direction_chosen:
             # 收集 4个基础问题
             if forward_index > 0 and forward_index <= len(forward_additional_questions):
                 prev_key = forward_additional_questions[forward_index - 1][0]