Update app.py

app.py

@@ -443,27 +443,34 @@ def predict(message, history):
     mode = user_profile.get("mode") or ""
 
     # ~~~~~~~~~ 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):
-                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)
-                    
-                    # 先生成职业详情
-                    career_detail_prompt = f"""
+if mode == "是":
+    if in_backward_flow and not backward_done:
+        # 更新状态变量：保存用户的回答到对应的键
+        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()
+
+        # 如果还有问题要问，继续问
+        if backward_index < len(backward_additional_questions):
+            k, prompt_text = backward_additional_questions[backward_index]
+            backward_index += 1
+            return prompt_text
+        
+        # 问完了所有问题后，提供职业详情和A/B/C选项
+        else:
+            # 打印调试信息确认我们进入了这个分支
+            print("进入Backward模式的详情生成分支")
+            print(f"职业方向: {user_profile.get('specific_career')}")
+            print(f"背景信息: {user_profile.get('bg_info')}")
+            
+            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)
+                
+                # 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'}
@@ -476,83 +483,9 @@ def predict(message, history):
 6. 行业前景
 用分段Markdown格式，字数不少于300字。
 """
-                    msgs = [
-                        {"role": "system", "content": "你是一位专业职业顾问，会为用户的目标职业提供详细分析。"},
-                        {"role": "user", "content": career_detail_prompt}
-                    ]
-                    resp = client.chat.completions.create(
-                        model=model_default,
-                        messages=msgs,
-                        max_tokens=token_default,
-                        temperature=temp_default,
-                        top_p=top_p_default,
-                        stream=False
-                    )
-                    detail_msg = resp.choices[0].message.content
-                    
-                    # 设置状态，与Forward模式保持一致
-                    user_profile["final_choice"] = user_profile.get("specific_career")
-                    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'。"
-                    
-                except Exception as e:
-                    return f"生成职业详情时出错: {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["bg_info"],
-                    wv=user_profile.get("work_value") or "未提供",
-                    ps=user_profile.get("personality_summary") or "未提供",
-                    dd=user_profile.get("dream_day") or "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"}
+                    {"role": "system", "content": "你是一位专业职业顾问，会为用户的目标职业提供详细分析。"},
+                    {"role": "user", "content": career_detail_prompt}
                 ]
                 resp = client.chat.completions.create(
                     model=model_default,
@@ -562,9 +495,83 @@ def predict(message, history):
                     top_p=top_p_default,
                     stream=False
                 )
-                return resp.choices[0].message.content
+                detail_msg = resp.choices[0].message.content
+                
+                # 设置状态，与Forward模式保持一致
+                user_profile["final_choice"] = user_profile.get("specific_career")
+                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'。"
+                
             except Exception as e:
-                return f"发生错误: {str(e)}"
+                return f"生成职业详情时出错: {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 ~~~~~~~~~
     else: