Update app.py

app.py

@@ -32,14 +32,12 @@ HANBRIDGE_LOGO_PATH = "hanbridge_logo.png"
 CLARE_LOGO_PATH = "clare_mascot.png"
 CLARE_RUN_PATH = "Clare_Run.png"
 
-# ================== 【核心修改】Base64 图片转换函数 ==================
+# ================== Base64 图片转换 ==================
 def image_to_base64(image_path):
-    """将本地图片转换为 Base64 字符串，直接嵌入 HTML，避免路径错误"""
     if not os.path.exists(image_path):
-        return "" # 如果文件不存在，返回空
+        return "" 
     with open(image_path, "rb") as img_file:
         encoded_string = base64.b64encode(img_file.read()).decode('utf-8')
-    # 根据文件扩展名决定 MIME type
     if image_path.lower().endswith(".png"):
         mime = "image/png"
     elif image_path.lower().endswith(".jpg") or image_path.lower().endswith(".jpeg"):
@@ -48,65 +46,192 @@ def image_to_base64(image_path):
         mime = "image/png"
     return f"data:{mime};base64,{encoded_string}"
 
-# ================== CSS (样式调整) ==================
+# ================== User Guide Content ==================
+USER_GUIDE_SECTIONS = {
+    "getting_started": """
+## Getting started
+
+Welcome to **Clare — Your Personalized AI Tutor**.
+
+Clare is designed to support your learning through:
+- Clear explanations of course concepts  
+- Socratic-style reasoning guidance  
+- Personalized reinforcement based on learning science  
+- Course-aligned answers using your uploaded materials  
+- Micro-quizzes & summaries to strengthen understanding  
+
+**To begin:**
+1. Select your **Learning Mode** on the left  
+2. (Optional) Upload your **syllabus / slides / notes** at the top  
+3. Ask Clare any question about your course, assignment, or study plan.
+""",
+    "mode_definition": """
+## Mode Definition
+
+Clare offers different teaching modes to match how you prefer to learn.
+
+### Concept Explainer
+Clear, structured explanations with examples — ideal for learning new topics.
+
+### Socratic Tutor
+Clare asks guiding questions instead of giving direct answers.  
+Helps you build reasoning and problem-solving skills.
+
+### Exam Prep / Quiz
+Generates short practice questions aligned with your course week.  
+Useful for self-testing and preparing for exams.
+
+### Assignment Helper
+Helps you interpret assignment prompts, plan structure, and understand requirements.  
+❗ Clare does **not** produce full assignment answers (academic integrity).
+
+### Quick Summary
+Gives brief summaries of slides, reading materials, or long questions.
+""",
+    "how_clare_works": """
+## How Clare Works
+
+Clare combines **course context + learning science + AI reasoning** to generate answers.
+
+Clare uses:
+- **Your selected Learning Mode** Determines tone, depth, and interaction style.
+
+- **Your uploaded course files** Syllabus, slides, or papers help align answers with your specific course.
+
+- **Reinforcement learning cycle** Answers may prioritize key concepts you’re likely to forget (based on the forgetting curve).
+
+- **Adaptive explanation depth** Clare can adjust complexity depending on your previous interactions.
+
+- **Responsible AI principles** Avoids harmful output and preserves academic integrity.
+""",
+    "memory_line": """
+## What is Memory Line?
+
+**Memory Line** is a visualization of your *learning reinforcement cycle*.
+
+Based on the **forgetting-curve model**, Clare organizes your review topics into:
+- **T+0 (Current Week)** – new concepts  
+- **T+7** – first spaced review  
+- **T+14** – reinforcement review  
+- **T+30** – long-term consolidation  
+
+Clare uses these cycles to decide:
+- Which concepts to reinforce today  
+- Which explanations to prioritize  
+- When to introduce quick review questions  
+
+**Review Now** will generate a small set of concepts that are due for spaced repetition.
+""",
+    "learning_progress": """
+## Learning Progress Report
+
+The Learning Progress Report highlights:
+- **Concepts mastered** - **Concepts in progress** - **Concepts due for review** - Your recent **micro-quiz results** - Suggested **next-step topics**
+
+You can download a **summary** at any time to use as study notes.
+""",
+    "how_files": """
+## How Clare Uses Your Files
+
+Your uploaded syllabus / slides / notes help Clare:
+
+- Align explanations with your exact course  
+- Use terminology consistent with your professor  
+- Improve factual accuracy  
+- Generate personalized reinforcement content  
+- 🔒 **Privacy**: Files are used only within your session.
+
+Accepted formats: **.docx / .pdf / .pptx**
+""",
+    "micro_quiz": """
+## Micro-Quiz
+
+The **Micro-Quiz** function provides a:
+
+- 1-minute self-check  
+- 1–3 questions based on your recent topics  
+- Instant feedback
+
+Micro-quizzes strengthen your memory and are part of Clare’s reinforcement system.
+""",
+    "summarization": """
+## Summarization
+
+Clare can summarize:
+
+- Lecture notes  
+- Uploaded PDFs  
+- Long conversation threads  
+- Complex concepts  
+
+Summary styles can include: Bullet points, Key ideas, Study notes, Comparison-style highlights.
+""",
+    "export_conversation": """
+## Export Conversation
+
+You can export your chat session for:
+
+- Study review  
+- Exam preparation  
+- Documentation for tutoring help  
+- Saving important explanations  
+
+Export format: **Markdown / plain text**.
+""",
+    "faq": """
+## FAQ
+
+**Q: Does Clare give assignment answers?** No. Clare assists with understanding and planning but does **not** generate full solutions.
+
+**Q: Does Clare replace lectures or TA office hours?** No. Clare supplements your learning by providing on-demand guidance.
+
+**Q: Can Clare explain my professor’s slides?** Yes — upload your slides so Clare can align explanations with your course.
+
+**Q: What languages does Clare support?** Currently: English & 简体中文.
+"""
+}
+
+# ================== CSS ==================
 CUSTOM_CSS = """
-/* 顶部 Header 容器样式 */
+/* Header */
 .header-container {
-    display: flex;
-    align-items: center;
-    justify-content: space-between;
-    padding: 10px 20px;
-    background-color: #ffffff;
-    border-bottom: 2px solid #f3f4f6;
-    margin-bottom: 15px;
+    display: flex; align-items: center; justify-content: space-between;
+    padding: 10px 20px; background-color: #ffffff;
+    border-bottom: 2px solid #f3f4f6; margin-bottom: 15px;
 }
 
-/* User Guide 链接样式 */
-#user-guide-links button {
-    background: transparent !important; border: none !important; box-shadow: none !important;
-    padding: 2px 0 !important; margin: 1px 0 !important; text-align: left !important;
-    color: #004a99 !important; text-decoration: underline; font-size: 0.8rem;
+/* 问号按钮样式 (? Buttons) */
+.help-btn {
+    min-width: 25px !important; width: 25px !important; height: 25px !important;
+    padding: 0 !important; border-radius: 50% !important;
+    font-size: 12px !important; font-weight: bold !important;
+    background: transparent !important; color: #666 !important; border: 1px solid #ccc !important;
+    box-shadow: none !important; margin-left: 5px !important;
+    display: inline-flex !important; align-items: center !important; justify-content: center !important;
 }
-#user-guide-links button:hover { color: #002b66 !important; }
+.help-btn:hover { background: #eee !important; color: #333 !important; border-color: #999 !important; }
 
-/* Memory Line 区域样式 */
+/* Memory Line */
 .memory-line-box {
-    border: 1px solid #e5e7eb;
-    padding: 12px;
-    border-radius: 8px;
-    background-color: #f9fafb;
-    height: 100%; 
-}
-"""
-
-# ========= Clare User Guide Content (保持原样) =========
-USER_GUIDE_SECTIONS = {
-    "getting_started": "## Getting started\n\nWelcome to **Clare**...",
-    "mode_definition": "## Mode Definition\n\nClare offers different teaching modes...",
-    "how_clare_works": "## How Clare Works\n\nClare combines course context...",
-    "memory_line": "## What is Memory Line?\n\nMemory Line is a visualization...",
-    "learning_progress": "## Learning Progress Report\n\nThe Learning Progress Report highlights...",
-    "how_files": "## How Clare Uses Your Files\n\nYour uploaded syllabus / slides...",
-    "micro_quiz": "## Micro-Quiz\n\nThe Micro-Quiz function provides...",
-    "summarization": "## Summarization\n\nClare can summarize...",
-    "export_conversation": "## Export Conversation\n\nYou can export your chat session...",
-    "faq": "## FAQ\n\n**Q: Does Clare give assignment answers?**..."
+    border: 1px solid #e5e7eb; padding: 12px; border-radius: 8px;
+    background-color: #f9fafb; height: 100%;
 }
 
-def get_user_guide_section(section_key: str) -> str:
-    return USER_GUIDE_SECTIONS.get(section_key, "Section not found.")
+/* User Guide Accordion specific tweaking */
+.user-guide-item { margin-bottom: 5px; }
+"""
 
 # ================== Gradio App ==================
 
 with gr.Blocks(title="Clare – Hanbridge AI Teaching Assistant", css=CUSTOM_CSS) as demo:
     
-    # 状态变量
+    # State variables
     course_outline_state = gr.State(DEFAULT_COURSE_TOPICS)
     weakness_state = gr.State([])
     cognitive_state_state = gr.State({"confusion": 0, "mastery": 0})
     rag_chunks_state = gr.State([]) 
 
-    # ============ 1. 顶部 Header (使用 Base64 嵌入图片) ============
+    # 1. Header
     gr.HTML(
         f"""
         <div class="header-container">
@@ -122,7 +247,6 @@ with gr.Blocks(title="Clare – Hanbridge AI Teaching Assistant", css=CUSTOM_CSS
                     </div>
                 </div>
             </div>
-
             <div style="text-align: right;">
                 <img src="{image_to_base64(HANBRIDGE_LOGO_PATH)}" style="height: 55px; object-fit: contain; margin-bottom: 5px;">
                 <div style="font-size: 12px; color: #666;">
@@ -133,13 +257,14 @@ with gr.Blocks(title="Clare – Hanbridge AI Teaching Assistant", css=CUSTOM_CSS
         """
     )
 
-    # ============ 2. 主体分栏布局 ============
+    # 2. Main Layout
     with gr.Row():
         
-        # ============ [左侧] 控制面板 Sidebar ============
+        # === [Left Sidebar] ===
         with gr.Column(scale=1, min_width=200):
             clear_btn = gr.Button("Reset Conversation", variant="stop")
             
+            # Model Settings
             gr.Markdown("### Model Settings")
             model_name = gr.Textbox(label="Model", value=DEFAULT_MODEL, lines=1)
             language_preference = gr.Radio(
@@ -148,36 +273,72 @@ with gr.Blocks(title="Clare – Hanbridge AI Teaching Assistant", css=CUSTOM_CSS
                 label="Language"
             )
             
+            # Learning Mode with Help Button
+            with gr.Row(variant="compact", elem_classes="no-gap"):
+                gr.Markdown("**Learning Mode**")
+                mode_help_btn = gr.Button("?", elem_classes="help-btn") # ? Button
+
             learning_mode = gr.Radio(
                 choices=LEARNING_MODES,
                 value="Concept Explainer",
-                label="Learning Mode",
-                info="Select style"
+                label=None, # Hide default label to use custom header above
+                info="Select style",
+                show_label=False
             )
 
-            with gr.Accordion("User Guide", open=False):
-                with gr.Column(elem_id="user-guide-links"):
-                    ug_getting_started = gr.Button("Getting started")
-                    ug_mode_def = gr.Button("Mode Definition")
-                    ug_how_works = gr.Button("How Clare Works")
-                    ug_memory_line = gr.Button("What is Memory Line")
+            # --- User Guide (New Design: Nested Accordions) ---
+            with gr.Accordion("User Guide", open=True):
+                # 这里实现了“点击一个展开一个”的效果
+                with gr.Accordion("Getting Started", open=False, elem_classes="user-guide-item"):
+                    gr.Markdown(USER_GUIDE_SECTIONS["getting_started"])
+                
+                with gr.Accordion("Mode Definition", open=False, elem_classes="user-guide-item"):
+                    gr.Markdown(USER_GUIDE_SECTIONS["mode_definition"])
+                
+                with gr.Accordion("How Clare Works", open=False, elem_classes="user-guide-item"):
+                    gr.Markdown(USER_GUIDE_SECTIONS["how_clare_works"])
+                
+                with gr.Accordion("What is Memory Line", open=False, elem_classes="user-guide-item"):
+                    gr.Markdown(USER_GUIDE_SECTIONS["memory_line"])
+
+                with gr.Accordion("Learning Progress Report", open=False, elem_classes="user-guide-item"):
+                    gr.Markdown(USER_GUIDE_SECTIONS["learning_progress"])
+
+                with gr.Accordion("How Clare Uses Your Files", open=False, elem_classes="user-guide-item"):
+                    gr.Markdown(USER_GUIDE_SECTIONS["how_files"])
+
+                with gr.Accordion("Micro-Quiz", open=False, elem_classes="user-guide-item"):
+                    gr.Markdown(USER_GUIDE_SECTIONS["micro_quiz"])
+                
+                with gr.Accordion("Summarization", open=False, elem_classes="user-guide-item"):
+                    gr.Markdown(USER_GUIDE_SECTIONS["summarization"])
+
+                with gr.Accordion("Export Conversation", open=False, elem_classes="user-guide-item"):
+                    gr.Markdown(USER_GUIDE_SECTIONS["export_conversation"])
+
+                with gr.Accordion("FAQ", open=False, elem_classes="user-guide-item"):
+                    gr.Markdown(USER_GUIDE_SECTIONS["faq"])
             
             with gr.Group():
                 gr.Button("System Settings", variant="secondary")
                 gr.Button("Log Out", variant="secondary")
 
-        # ============ [中间] 主内容区 Center Main ============
+        # === [Center Main] ===
         with gr.Column(scale=3):
             
-            # 上半部分：上传区 + Memory Line
+            # Upload & Memory Line
             with gr.Row():
-                # --- Upload File ---
+                # Upload
                 with gr.Column(scale=1):
+                    with gr.Row():
+                        gr.Markdown("**Upload Course File**")
+                        file_help_btn = gr.Button("?", elem_classes="help-btn") # ? Button
+                    
                     syllabus_file = gr.File(
-                        label="Upload file (.docx/.pdf/.pptx)",
                         file_types=[".docx", ".pdf", ".pptx"],
                         file_count="single",
-                        height=100
+                        height=100,
+                        show_label=False
                     )
                     doc_type = gr.Dropdown(
                         choices=DOC_TYPES, 
@@ -186,34 +347,33 @@ with gr.Blocks(title="Clare – Hanbridge AI Teaching Assistant", css=CUSTOM_CSS
                         container=False 
                     )
                 
-                # --- Memory Line (使用 Base64 嵌入奔跑图片) ---
+                # Memory Line
                 with gr.Column(scale=1):
                     gr.HTML(
                         f"""
                         <div class="memory-line-box">
-                            <div style="display:flex; justify-content:space-between; font-size:14px; margin-bottom:5px; font-weight:bold;">
-                                <span>Memory Line <span style="font-weight:normal; color:#999; cursor:help;" title="Visualizes your spaced repetition progress">?</span></span>
-                            </div>
-                            
+                            <div style="display:flex; justify-content:space-between; align-items:center; margin-bottom:5px;">
+                                <div style="font-weight:bold; font-size:14px;">Memory Line</div>
+                                </div>
                             <div style="position: relative; height: 35px; margin-top: 15px; margin-bottom: 5px;">
                                 <div style="position: absolute; bottom: 5px; left: 0; width: 100%; height: 8px; background-color: #e5e7eb; border-radius: 4px;"></div>
                                 <div style="position: absolute; bottom: 5px; left: 0; width: 40%; height: 8px; background-color: #8B1A1A; border-radius: 4px 0 0 4px;"></div>
                                 <img src="{image_to_base64(CLARE_RUN_PATH)}" style="position: absolute; left: 36%; bottom: 8px; height: 35px; z-index: 10;">
                             </div>
-
                             <div style="display:flex; justify-content:space-between; align-items:center; margin-top:8px;">
                                 <div style="font-size: 12px; color: #666;">Next Review: T+7</div>
-                                <div style="font-size: 12px; color: #004a99; text-decoration:underline; cursor:pointer;">
-                                    Learning Progress Report ⬇️
-                                </div>
+                                <div style="font-size: 12px; color: #004a99; text-decoration:underline;">Learning Progress Report ⬇️</div>
                             </div>
                         </div>
                         """
                     )
-                    review_btn = gr.Button("Review Now", size="sm", variant="primary")
+                    # Memory Line 的问号按钮 (放在 HTML 下方紧凑的一行里)
+                    with gr.Row(elem_classes="no-gap"):
+                         ml_help_btn = gr.Button("What is Memory Line?", size="sm", variant="secondary")
+                         review_btn = gr.Button("Review Now", size="sm", variant="primary")
                     session_status = gr.Markdown(visible=False)
 
-            # --- Chat Interface ---
+            # Chat
             gr.Markdown(
                 """
                 <div style="background-color:#f9fafb; padding:10px; border-radius:5px; margin-top:10px; font-size:0.9em; color:#555;">
@@ -222,134 +382,81 @@ with gr.Blocks(title="Clare – Hanbridge AI Teaching Assistant", css=CUSTOM_CSS
                 </div>
                 """
             )
-
             chatbot = gr.Chatbot(
-                label="",
-                height=450,
-                # 聊天框内的头像也可以使用 Base64，但 Gradio 的 avatar_images 
-                # 通常直接接受路径即可（因为它内部会处理）。
-                # 如果这里头像也不显示，请告诉我，我再改这里。目前保持路径。
+                label="", height=450,
                 avatar_images=(None, CLARE_LOGO_PATH), 
-                show_label=False,
-                bubble_full_width=False
+                show_label=False, bubble_full_width=False
             )
-            
             user_input = gr.Textbox(
-                label="Your Input",
-                placeholder="Ask about a concept, your assignment, or let Clare test you...",
-                show_label=False,
-                container=True,
-                autofocus=True
+                label="Your Input", placeholder="Ask about a concept, your assignment, or let Clare test you...",
+                show_label=False, container=True, autofocus=True
             )
 
-        # ============ [右侧] 功能栏 Right Sidebar ============
+        # === [Right Sidebar] ===
         with gr.Column(scale=1, min_width=180):
             gr.Markdown("### Actions")
-            export_btn = gr.Button("Export Conversation", size="sm")
-            quiz_btn = gr.Button("Let's Try (Micro-Quiz)", size="sm")
-            summary_btn = gr.Button("Summarization", size="sm")
+            
+            with gr.Row():
+                export_btn = gr.Button("Export Conversation", size="sm", scale=4)
+                export_help_btn = gr.Button("?", elem_classes="help-btn", scale=1)
+            
+            with gr.Row():
+                quiz_btn = gr.Button("Let's Try (Micro-Quiz)", size="sm", scale=4)
+                quiz_help_btn = gr.Button("?", elem_classes="help-btn", scale=1)
+
+            with gr.Row():
+                summary_btn = gr.Button("Summarization", size="sm", scale=4)
+                summary_help_btn = gr.Button("?", elem_classes="help-btn", scale=1)
             
             gr.Markdown("### Results")
             result_display = gr.Textbox(
-                label="Generated Content",
-                lines=15,
+                label="Generated Content", lines=15,
                 placeholder="Results from Export, Quiz, or Summary will appear here...",
                 show_label=False
             )
 
-    # ================== Logic Bindings (逻辑部分保持不变) ==================
+    # ================== 问号按钮逻辑 (Pop-up Info) ==================
+    # 当点击问号时，弹出对应的信息
+    mode_help_btn.click(lambda: gr.Info(USER_GUIDE_SECTIONS["mode_definition"], title="Mode Definition"))
+    file_help_btn.click(lambda: gr.Info(USER_GUIDE_SECTIONS["how_files"], title="How Files Work"))
+    ml_help_btn.click(lambda: gr.Info(USER_GUIDE_SECTIONS["memory_line"], title="Memory Line"))
+    export_help_btn.click(lambda: gr.Info(USER_GUIDE_SECTIONS["export_conversation"], title="Export"))
+    quiz_help_btn.click(lambda: gr.Info(USER_GUIDE_SECTIONS["micro_quiz"], title="Micro-Quiz"))
+    summary_help_btn.click(lambda: gr.Info(USER_GUIDE_SECTIONS["summarization"], title="Summarization"))
 
+    # ================== Main Logic (保持原有逻辑) ==================
     def update_course_and_rag(file, doc_type_val):
         topics = extract_course_topics_from_file(file, doc_type_val)
         rag_chunks = build_rag_chunks_from_file(file, doc_type_val)
         status_md = f"✅ **File Loaded:** {doc_type_val}\n\nAnalyzing content for Memory Line..."
         return topics, rag_chunks, status_md
 
-    syllabus_file.change(
-        fn=update_course_and_rag,
-        inputs=[syllabus_file, doc_type],
-        outputs=[course_outline_state, rag_chunks_state, session_status],
-    )
+    syllabus_file.change(update_course_and_rag, [syllabus_file, doc_type], [course_outline_state, rag_chunks_state, session_status])
 
     def respond(message, chat_history, course_outline, weaknesses, cognitive_state, rag_chunks, model, lang, mode, doc_type_val):
         resolved_lang = detect_language(message or "", lang)
-        
         if not message or not message.strip():
              return "", chat_history, weaknesses, cognitive_state, session_status.value
-
         weaknesses = update_weaknesses_from_message(message, weaknesses or [])
         cognitive_state = update_cognitive_state_from_message(message, cognitive_state)
         rag_context = retrieve_relevant_chunks(message, rag_chunks or [])
-
-        answer, new_history = chat_with_clare(
-            message=message,
-            history=chat_history,
-            model_name=model,
-            language_preference=resolved_lang,
-            learning_mode=mode,
-            doc_type=doc_type_val,
-            course_outline=course_outline,
-            weaknesses=weaknesses,
-            cognitive_state=cognitive_state,
-            rag_context=rag_context
-        )
-        
+        answer, new_history = chat_with_clare(message, chat_history, model, resolved_lang, mode, doc_type_val, course_outline, weaknesses, cognitive_state, rag_context)
         new_status = render_session_status(mode, weaknesses, cognitive_state)
         return "", new_history, weaknesses, cognitive_state, new_status
 
-    user_input.submit(
-        respond,
-        [user_input, chatbot, course_outline_state, weakness_state, cognitive_state_state, rag_chunks_state, model_name, language_preference, learning_mode, doc_type],
-        [user_input, chatbot, weakness_state, cognitive_state_state, session_status]
-    )
-
-    def on_export(chat_history, course_outline, mode, weaknesses, cognitive_state):
-        return export_conversation(chat_history, course_outline, mode, weaknesses, cognitive_state)
-
-    export_btn.click(
-        on_export,
-        [chatbot, course_outline_state, learning_mode, weakness_state, cognitive_state_state],
-        [result_display]
-    )
-
-    def on_quiz(chat_history, course_outline, weaknesses, cognitive_state, model, lang):
-        return generate_quiz_from_history(chat_history, course_outline, weaknesses, cognitive_state, model, lang)
-
-    quiz_btn.click(
-        on_quiz,
-        [chatbot, course_outline_state, weakness_state, cognitive_state_state, model_name, language_preference],
-        [result_display]
-    )
-
-    def on_summary(chat_history, course_outline, weaknesses, cognitive_state, model, lang):
-        return summarize_conversation(chat_history, course_outline, weaknesses, cognitive_state, model, lang)
-
-    summary_btn.click(
-        on_summary,
-        [chatbot, course_outline_state, weakness_state, cognitive_state_state, model_name, language_preference],
-        [result_display]
-    )
+    user_input.submit(respond, [user_input, chatbot, course_outline_state, weakness_state, cognitive_state_state, rag_chunks_state, model_name, language_preference, learning_mode, doc_type], [user_input, chatbot, weakness_state, cognitive_state_state, session_status])
 
+    # Button Actions
+    export_btn.click(lambda h, c, m, w, cog: export_conversation(h, c, m, w, cog), [chatbot, course_outline_state, learning_mode, weakness_state, cognitive_state_state], [result_display])
+    quiz_btn.click(lambda h, c, w, cog, m, l: generate_quiz_from_history(h, c, w, cog, m, l), [chatbot, course_outline_state, weakness_state, cognitive_state_state, model_name, language_preference], [result_display])
+    summary_btn.click(lambda h, c, w, cog, m, l: summarize_conversation(h, c, w, cog, m, l), [chatbot, course_outline_state, weakness_state, cognitive_state_state, model_name, language_preference], [result_display])
+    
+    # Reset
     def clear_all():
         empty_state = {"confusion": 0, "mastery": 0}
         default_status = render_session_status("Concept Explainer", [], empty_state)
         return [], [], empty_state, [], "", default_status
-
-    clear_btn.click(
-        clear_all,
-        None,
-        [chatbot, weakness_state, cognitive_state_state, rag_chunks_state, result_display, session_status],
-        queue=False
-    )
-    
-    def show_guide(section):
-        return get_user_guide_section(section)
-
-    ug_getting_started.click(lambda: show_guide("getting_started"), outputs=result_display)
-    ug_mode_def.click(lambda: show_guide("mode_definition"), outputs=result_display)
-    ug_how_works.click(lambda: show_guide("how_clare_works"), outputs=result_display)
-    ug_memory_line.click(lambda: show_guide("memory_line"), outputs=result_display)
+    clear_btn.click(clear_all, None, [chatbot, weakness_state, cognitive_state_state, rag_chunks_state, result_display, session_status], queue=False)
 
 if __name__ == "__main__":
-    # 移除 allowed_paths，因为 Base64 不需要它
     demo.launch()