Update app.py

app.py

@@ -4,7 +4,7 @@ import os
 
 # ============================ 用户信息结构 ============================
 user_profile = {
-    "mode": None,                # 只在回答第一个问题时设置
+    "mode": None,  # 只在回答第一个问题时设置（是/否）
     "specific_career": None,
     "bg_info": None,
     "work_value": None,
@@ -43,13 +43,14 @@ forward_done = False
 backward_done = False
 forward_recommendation_given = False
 
+# 允许多次换方向、深度分析、路线图
 recommendation_round = 0
 forward_deep_dive_done = False
 roadmap_offered = False
 roadmap_done = False
 
 # ============================ 模型设置 ============================
-model_default = "gpt-4o"
+model_default = "gpt-4o"  # 你可改成 "gpt-3.5-turbo" 等
 token_default = 2000
 temp_default = 0.7
 top_p_default = 0.95
@@ -86,8 +87,8 @@ def do_time_roadmap():
         client = OpenAI(api_key=api_key)
 
         msgs = [
-            {"role":"system","content":"你是一位专业的职业规划顾问，会生成时间轴式路线图"},
-            {"role":"user","content": prompt_roadmap}
+            {"role": "system", "content": "你是一位专业的职业规划顾问，会生成时间轴式路线图"},
+            {"role": "user", "content": prompt_roadmap}
         ]
         resp = client.chat.completions.create(
             model=model_default,
@@ -101,7 +102,7 @@ def do_time_roadmap():
     except Exception as e:
         return f"生成路线图时出错: {str(e)}"
 
-# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 深度分析函数 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 深度分析函数（3个具体职业） ~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 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"
@@ -132,8 +133,8 @@ def do_deep_analysis():
             return "错误：API_TOKEN 未设置"
         client = OpenAI(api_key=api_key)
         msgs = [
-            {"role":"system","content":"你是一位专业职业顾问，会深度分析并列出3个具体职业。"},
-            {"role":"user","content":deep_prompt}
+            {"role": "system", "content": "你是一位专业职业顾问，会深度分析并列出3个具体职业。"},
+            {"role": "user", "content": deep_prompt}
         ]
         resp = client.chat.completions.create(
             model=model_default,
@@ -175,8 +176,8 @@ def recommend_3directions():
             return "错误：API_TOKEN 未设置"
         client = OpenAI(api_key=api_key)
         msgs = [
-            {"role":"system","content":"你是一位职业顾问，擅长根据用户资料推荐3大方向"},
-            {"role":"user","content": rec_prompt}
+            {"role": "system", "content": "你是一位职业顾问，擅长根据用户资料推荐3大方向"},
+            {"role": "user", "content": rec_prompt}
         ]
         resp = client.chat.completions.create(
             model=model_default,
@@ -241,7 +242,6 @@ def predict(message, history):
     global forward_deep_dive_done
     global roadmap_offered, roadmap_done
 
-    # 若是第一次
     if not history:
         current_q_index = 0
         questions = base_questions[:]
@@ -250,7 +250,8 @@ def predict(message, history):
 
         in_forward_flow = False
         in_backward_flow = False
-        forward_index = backward_index = 0
+        forward_index = 0
+        backward_index = 0
         forward_done = backward_done = False
         forward_recommendation_given = False
         recommendation_round = 0
@@ -258,11 +259,17 @@ def predict(message, history):
         roadmap_offered = False
         roadmap_done = False
 
-    # ===== 如果在base_questions环节 =====
+    # ========== 如果还在问 base_questions ==========
     if 0 < current_q_index <= len(questions):
         key = questions[current_q_index - 1][0]
         if key == "mode" and current_q_index == 1:
-            user_profile["mode"] = message.strip()   # 只这里写 mode
+            # 只有回答第一个问题时 => mode
+            ans = message.strip()
+            user_profile["mode"] = ans
+            if "是" in ans:
+                in_backward_flow = True
+            else:
+                in_forward_flow = True
         else:
             user_profile[key] = message.strip()
 
@@ -273,13 +280,12 @@ def predict(message, history):
 
     mode = user_profile.get("mode") or ""
 
-    # ~~~~~~~~~~~~ Backward模式 ~~~~~~~~~~~~
+    # ========== Backward ==========
     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
@@ -295,8 +301,8 @@ def predict(message, history):
                 client = OpenAI(api_key=api_key)
                 sprompt = generate_system_prompt()
                 msgs = [
-                    {"role":"system","content": sprompt},
-                    {"role":"user","content": f"请根据{user_profile}给出最终规划"}
+                    {"role":"system","content":sprompt},
+                    {"role":"user","content": f"请根据{user_profile}给出完整规划"}
                 ]
                 resp = client.chat.completions.create(
                     model=model_default,
@@ -310,7 +316,7 @@ def predict(message, history):
             except Exception as e:
                 return f"发生错误: {str(e)}"
 
-    # ~~~~~~~~~~~~ Forward模式 ~~~~~~~~~~~~
+    # ========== Forward ==========
     else:
         if in_forward_flow and not forward_done and not forward_deep_dive_done and not roadmap_done:
             if forward_index > 0 and forward_index <= len(forward_additional_questions):
@@ -334,13 +340,14 @@ def predict(message, history):
                     recommendation_round += 1
                     if recommendation_round > 2:
                         forward_done = True
-                        return "已多次换方向，结束推荐了~"
+                        return "已多次换方向，结束推荐。"
                     else:
                         return recommend_3directions()
                 else:
-                    return "请回复1/2/3选择方向，或输入'换'来重选"
+                    return "请回复1/2/3选择方向，或输入'换'来重新推荐"
 
         elif forward_deep_dive_done and not roadmap_offered:
+            # 深度分析结束 -> 问路线图
             roadmap_offered = True
             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”。"
 
@@ -353,7 +360,7 @@ def predict(message, history):
             else:
                 roadmap_done = True
                 forward_done = True
-                return "好的，不生成时间轴，本次就到这里。"
+                return "好的，不生成时间轴，本次规划结束。"
 
         if forward_done:
             try:
@@ -364,7 +371,7 @@ def predict(message, history):
                 sprompt = generate_system_prompt()
                 msgs = [
                     {"role":"system","content":sprompt},
-                    {"role":"user","content": f"这是最终资料: {user_profile}, 如果还需要帮助请提问。"}
+                    {"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,
@@ -378,105 +385,108 @@ def predict(message, history):
             except Exception as e:
                 return f"发生错误: {str(e)}"
 
-    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。"
+    return "信息收集完毕，如还未得到最终回复，请再输入任意文字继续。"
 
-# ============================ Gradio UI ============================
-with gr.Blocks(css="""
-body {
-    background-color: #1e1e1e;
-    color: #ffffff;
-}
-.gradio-container {
-    font-family: 'Segoe UI', sans-serif;
-}
-.message.user {
-    background-color: #cce6ff !important;
-    color: #000000 !important;
+    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;   /* Very light blue */
+    color: #000000 !important;              /* <-- Black text */
     border-radius: 10px !important;
     padding: 10px;
     margin: 6px;
-}
-.message.bot {
-    background-color: #5599ff !important;
-    color: #000000 !important;
+    }
+
+     .message.bot {
+    background-color: #99ccff !important;   /* Light blue */
+    color: #000000 !important;              /* <-- Black text */
     border-radius: 10px !important;
     padding: 10px;
     margin: 6px;
-}
-.gradio-container .chat-msg.bot-msg .message.bot p {
-    color: #000000 !important;
-}
-.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:
+    }
+
+    .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;'>
-          <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</p>
-          </div>
-        </div>
+        <!-- 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:Black; 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("""
-**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")
-
-    with gr.Row():
-        reset_btn = gr.Button("🔄 重新开始")
-
-    def add_message(m, hist):
+    gr.Markdown("**Let's chat! 💬** Ask me anything you want")
+    
+    chatbot = gr.Chatbot(height=500, show_label=False, show_copy_button=True, type="messages")
+    msg = gr.Textbox(placeholder="请输入你的回答...")
+    send = gr.Button("发送 🚀", elem_id="custom-send")
+    reset = gr.Button("🔄 重新开始")
+
+    def add_user_message(m, hist):
         hist = hist or []
         hist.append({"role":"user","content":m})
         return "", hist
 
-    def bot_response(hist):
-        hist = hist or []
+    def add_bot_response(hist):
         user_m = hist[-1]["content"]
         bot_m = predict(user_m, hist[:-1])
         hist.append({"role":"assistant","content":bot_m})
         return hist
 
-    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)
+    send.click(add_user_message, [msg, chatbot], [msg, chatbot]) \
+        .then(add_bot_response, chatbot, chatbot)
+
+    msg.submit(add_user_message, [msg, chatbot], [msg, chatbot]) \
+       .then(add_bot_response, chatbot, chatbot)
 
     def reset_state():
         global current_q_index, questions
@@ -490,15 +500,14 @@ footer {
 
         current_q_index = 0
         questions = base_questions[:]
-        for k in user_profile:
-            user_profile[k] = None
+        for key in user_profile:
+            user_profile[key] = None
 
         in_forward_flow = False
         in_backward_flow = False
         forward_index = 0
         backward_index = 0
-        forward_done = False
-        backward_done = False
+        forward_done = backward_done = False
         forward_recommendation_given = False
         recommendation_round = 0
         forward_deep_dive_done = False
@@ -506,10 +515,11 @@ footer {
         roadmap_done = False
 
         return []
-    reset_btn.click(reset_state, outputs=chatbot)
 
-    def auto_first():
-        return [{"role": "assistant", "content": questions[0][1]}]
+    reset.click(reset_state, outputs=chatbot)
+
+    def first_q():
+        return [{"role":"assistant","content": questions[0][1]}]
 
-    demo.load(auto_first, outputs=chatbot)
+    demo.load(first_q, outputs=chatbot)
     demo.launch()