Update app.py

app.py

@@ -1,37 +1,991 @@
-rag_context = retrieve_relevant_chunks(message, rag_chunks or [])
+import os
+import time
+import base64
+import requests
+from typing import List, Dict, Tuple, Optional
 
-# 如果完全检索不到任何与 Module 10 文档相关的内容，就认定为 out-of-scope
-if (not rag_context) and doc_type_val in ["Syllabus", "Reading", "Module 10"]:
-    out_msg = (
-        "For this experiment, I'm only allowed to discuss **Module 10 – "
-        "Responsible AI (Alto, 2024, Chapter 12)** and the uploaded Module 10 materials.\n\n"
-        "Your question seems to be outside this scope. Could you please rephrase it "
-        "to focus on Responsible AI topics (risks, mitigation layers, regulations, etc.)?"
-    )
-    new_history = (chat_history or []) + [[message, out_msg]]
+import gradio as gr
+
+from config import (
+    DEFAULT_MODEL,
+    DEFAULT_COURSE_TOPICS,
+    LEARNING_MODES,
+    DOC_TYPES,
+)
+from clare_core import (
+    update_weaknesses_from_message,
+    update_cognitive_state_from_message,
+    render_session_status,
+    find_similar_past_question,
+    detect_language,
+    chat_with_clare,
+    export_conversation,
+    generate_quiz_from_history,
+    get_empty_input_prompt,
+    summarize_conversation,
+)
+from rag_engine import (
+    build_rag_chunks_from_file,
+    retrieve_relevant_chunks,
+)
+from syllabus_utils import extract_course_topics_from_file
+
+# ================== Assets ==================
+HANBRIDGE_LOGO_PATH = "hanbridge_logo.png"
+CLARE_LOGO_PATH = "clare_mascot.png"
+CLARE_RUN_PATH = "Clare_Run.png"
+CLARE_READING_PATH = "Clare_reading.png"  # 确保存在
+
+# ================== Base64 Helper ==================
+def image_to_base64(image_path: str) -> str:
+    if not os.path.exists(image_path):
+        return ""
+    with open(image_path, "rb") as img_file:
+        encoded_string = base64.b64encode(img_file.read()).decode("utf-8")
+    if image_path.lower().endswith(".png"):
+        mime = "image/png"
+    elif image_path.lower().endswith((".jpg", ".jpeg")):
+        mime = "image/jpeg"
+    else:
+        mime = "image/png"
+    return f"data:{mime};base64,{encoded_string}"
+
+# ================== User Guide Content ==================
+USER_GUIDE_SECTIONS = {
+    "getting_started": """
+Welcome to **Clare — Your Personalized AI Tutor**.
+
+For this controlled experiment, Clare is already pre-loaded with:
+
+📘 **Module 10 Reading – Responsible AI (Alto, 2024, Chapter 12)**
+
+You do **NOT** need to upload any materials.  
+You may optionally upload extra files, but Clare will always include the Module 10 reading as core context.
+
+**To begin:**
+1. Log in with your **Student Name + Email/ID** on the right.
+2. Select your **Learning Mode** on the left.
+3. (Optional) Upload additional Module 10 slides / notes at the top.
+4. Ask Clare any question about **Module 10 – Responsible AI**.
+""",
+    "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": """
+Clare combines **course context + learning science + AI reasoning** to generate answers.
+
+For this experiment, Clare always includes:
+
+- Module 10 Reading – Responsible AI (Alto, 2024, Chapter 12)
+- Any additional Module 10 files you upload
+
+Clare uses:
+- **Learning Mode**: tone, depth, and interaction style.
+- **Reinforcement model**: may prioritize concepts you’re likely to forget.
+- **Responsible AI principles**: avoids harmful output and preserves academic integrity.
+""",
+    "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
+
+In this experiment, Memory Line should be interpreted as your **Module 10** reinforcement status.
+""",
+    "learning_progress": """
+The Learning Progress Report highlights:
+- **Concepts mastered**
+- **Concepts in progress**
+- **Concepts due for review**
+- Your recent **micro-quiz results**
+- Suggested **next-step topics**
+""",
+    "how_files": """
+Your uploaded materials help Clare:
+
+- Align explanations with your exact course (here: **Module 10 – Responsible AI**)
+- Use terminology consistent with your professor
+- Improve factual accuracy
+
+🔒 **Privacy**
+- Files are used only within your session
+- They are not kept as permanent training data
+
+Accepted formats: **.docx / .pdf / .pptx**
+
+For this experiment, Clare is **already pre-loaded** with the Module 10 reading. Uploads are optional.
+""",
+    "micro_quiz": """
+The **Micro-Quiz** function provides a:
+
+- 1-minute self-check
+- 1–3 questions about **Module 10 – Responsible AI**
+- Instant feedback inside the main chat
+
+**How it works:**
+1. Click “Let’s Try (Micro-Quiz)” on the right.
+2. Clare will send the **first quiz question** in the main chat.
+3. Type your answer in the chat box.
+4. Clare will:
+   - Judge correctness
+   - Give a brief explanation
+   - Ask if you want another question
+5. You can continue or say “stop” at any time.
+""",
+    "summarization": """
+Clare can summarize:
+
+- Module 10 reading
+- Uploaded slides / notes
+- Long conversation threads
+""",
+    "export_conversation": """
+You can export your chat session for:
+
+- Study review
+- Exam preparation
+- Saving important explanations
+
+Export format: **Markdown / plain text**.
+""",
+    "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: What languages does Clare support?**
+Currently: English & 简体中文.
+"""
+}
+
+# ================== CSS 样式表 ==================
+CUSTOM_CSS = """
+/* --- Main Header --- */
+.header-container { padding: 10px 20px; background-color: #ffffff; border-bottom: 2px solid #f3f4f6; margin-bottom: 15px; display: flex; align-items: center; }
 
-    # 也可以顺便记一条“out_of_scope”日志
+/* --- Sidebar Login Panel --- */
+.login-panel {
+    background-color: #e5e7eb;
+    padding: 15px;
+    border-radius: 8px;
+    text-align: center;
+    margin-bottom: 20px;
+}
+.login-panel img {
+    display: block;
+    margin: 0 auto 10px auto;
+    height: 80px;
+    object-fit: contain;
+}
+.login-main-btn {
+    background-color: #ffffff !important;
+    color: #000 !important;
+    border: 1px solid #000 !important;
+    font-weight: bold !important;
+}
+.logout-btn {
+    background-color: #6b2828 !important;
+    color: #fff !important;
+    border: none !important;
+    font-weight: bold !important;
+}
+
+/* User Guide */
+.main-user-guide { border: none !important; background: transparent !important; box-shadow: none !important; }
+.main-user-guide > .label-wrap { border: none !important; background: transparent !important; padding: 10px 0 !important; }
+.main-user-guide > .label-wrap span { font-size: 1.3rem !important; font-weight: 800 !important; color: #111827 !important; }
+
+.clean-accordion { border: none !important; background: transparent !important; box-shadow: none !important; margin-bottom: 0px !important; padding: 0 !important; border-radius: 0 !important; }
+.clean-accordion > .label-wrap { padding: 8px 5px !important; border: none !important; background: transparent !important; border-bottom: 1px solid #e5e7eb !important; }
+.clean-accordion > .label-wrap span { font-size: 0.9rem !important; font-weight: 500 !important; color: #374151 !important; }
+.clean-accordion > .label-wrap:hover { background-color: #f9fafb !important; }
+
+/* Action Buttons */
+.action-btn { font-weight: bold !important; font-size: 0.9rem !important; position: relative; overflow: visible !important; }
+.action-btn:hover::before { content: "See User Guide for details"; position: absolute; bottom: 110%; left: 50%; transform: translateX(-50%); background-color: #333; color: #fff; padding: 5px 10px; border-radius: 5px; font-size: 12px; white-space: nowrap; z-index: 1000; pointer-events: none; opacity: 0; animation: fadeIn 0.2s forwards; }
+.action-btn:hover::after { content: ""; position: absolute; bottom: 100%; left: 50%; margin-left: -5px; border-width: 5px; border-style: solid; border-color: #333 transparent transparent transparent; opacity: 0; animation: fadeIn 0.2s forwards; }
+
+/* Tooltips & Memory Line */
+.html-tooltip { border-bottom: 1px dashed #999; cursor: help; position: relative; }
+.html-tooltip:hover::before { content: attr(data-tooltip); position: absolute; bottom: 120%; left: 0; background-color: #333; color: #fff; padding: 5px 8px; border-radius: 4px; font-size: 11px; white-space: nowrap; z-index: 100; pointer-events: none; }
+.memory-line-box { border: 1px solid #e5e7eb; padding: 12px; border-radius: 8px; background-color: #f9fafb; height: 100%; display: flex; flex-direction: column; justify-content: space-between; }
+
+/* Results Box Style */
+.result-box { border: 1px solid #e5e7eb; background: #ffffff; padding: 10px; border-radius: 8px; height: 100%; }
+.result-box .prose { font-size: 0.9rem; }
+
+@keyframes fadeIn { to { opacity: 1; } }
+"""
+
+# ========== Preload Module 10 PDF ==========
+MODULE10_PATH = "module10_responsible_ai.pdf"
+MODULE10_DOC_TYPE = "Reading"
+
+preloaded_topics: List[str] = []
+preloaded_chunks: List[Dict] = []
+
+if os.path.exists(MODULE10_PATH):
     try:
-        log_event(
-            {
-                "experiment_id": "RESP_AI_W10",
-                "student_id": user_id_val or "ANON",
-                "event_type": "out_of_scope",
-                "timestamp": time.time(),
-                "latency_ms": 0,
-                "question": message,
-                "answer": out_msg,
-                "model_name": model_name_val,
-                "language": resolved_lang,
-                "learning_mode": mode_val,
-            }
+        preloaded_topics = extract_course_topics_from_file(
+            MODULE10_PATH, MODULE10_DOC_TYPE
         )
+        preloaded_chunks = build_rag_chunks_from_file(
+            MODULE10_PATH, MODULE10_DOC_TYPE
+        )
+        print("Module 10 PDF preloaded successfully.")
     except Exception as e:
-        print("log_event error:", e)
+        print("Module 10 preload failed:", e)
+else:
+    print("Module 10 PDF not found at path:", MODULE10_PATH)
+
+# ===== Google Sheet logging ====
+GSHEET_WEBHOOK_URL = os.getenv("GSHEET_WEBHOOK_URL")
+GSHEET_API_KEY = os.getenv("GSHEET_API_KEY")
+
+
+def log_event(data: Dict):
+    """
+    把日志发到 Google Sheet（通过 Apps Script Webhook）
+    """
+    if not GSHEET_WEBHOOK_URL:
+        print("Google Sheet webhook not configured, skip logging")
+        return
+
+    payload = data.copy()
+    payload["api_key"] = GSHEET_API_KEY or ""
+
+    try:
+        resp = requests.post(GSHEET_WEBHOOK_URL, json=payload, timeout=3)
+        if not resp.ok:
+            print("GSheet log failed:", resp.status_code, resp.text)
+    except Exception as e:
+        print("GSheet log exception:", e)
+
+
+# ================== Gradio App ==================
+with gr.Blocks(
+    title="Clare – Hanbridge AI Teaching Assistant", css=CUSTOM_CSS
+) as demo:
+
+    # 全局状态（预加载 Module 10 作为基础）
+    course_outline_state = gr.State(preloaded_topics or DEFAULT_COURSE_TOPICS)
+    weakness_state = gr.State([])
+    cognitive_state_state = gr.State({"confusion": 0, "mastery": 0})
+    rag_chunks_state = gr.State(preloaded_chunks or [])
+
+    # 用户状态（登录）
+    user_name_state = gr.State("")
+    user_id_state = gr.State("")
+
+    # --- Header ---
+    with gr.Row(elem_classes="header-container"):
+        with gr.Column(scale=2):
+            gr.HTML(
+                f"""
+                <div style="display:flex; align-items:center; gap: 20px;">
+                    <img src="{image_to_base64(CLARE_LOGO_PATH)}" style="height: 75px; object-fit: contain;">
+                    <div style="display:flex; flex-direction:column;">
+                        <div style="font-size: 32px; font-weight: 800; line-height: 1.1; color: #000;">
+                            Clare
+                            <span style="font-size: 18px; font-weight: 600; margin-left: 10px;">Your Personalized AI Tutor</span>
+                        </div>
+                        <div style="font-size: 14px; font-style: italic; color: #333; margin-top: 4px;">
+                            Personalized guidance, review, and intelligent reinforcement
+                        </div>
+                    </div>
+                </div>
+                """
+            )
+
+        with gr.Column(scale=1):
+            gr.HTML(
+                f"""
+                <div style="display:flex; justify-content:flex-end; margin-bottom: 5px;">
+                    <img src="{image_to_base64(HANBRIDGE_LOGO_PATH)}" style="height: 55px; object-fit: contain;">
+                </div>
+                """
+            )
+
+    # --- Main Layout ---
+    with gr.Row():
+
+        # === Left Sidebar ===
+        with gr.Column(scale=1, min_width=200):
+            clear_btn = gr.Button(
+                "Reset Conversation", variant="stop", interactive=False
+            )
+
+            gr.Markdown("### Model Settings")
+            model_name = gr.Textbox(
+                label="Model",
+                value="gpt-4.1-mini",
+                interactive=False,
+                lines=1,
+            )
+            language_preference = gr.Radio(
+                choices=["Auto", "English", "简体中文"],
+                value="Auto",
+                label="Language",
+                interactive=False,
+            )
+
+            learning_mode = gr.Radio(
+                choices=LEARNING_MODES,
+                value="Concept Explainer",
+                label="Learning Mode",
+                info="See User Guide for mode definition details.",
+                interactive=False,
+            )
+
+            # User Guide
+            with gr.Accordion(
+                "User Guide", open=True, elem_classes="main-user-guide"
+            ):
+                with gr.Accordion(
+                    "Getting Started",
+                    open=False,
+                    elem_classes="clean-accordion",
+                ):
+                    gr.Markdown(USER_GUIDE_SECTIONS["getting_started"])
+                with gr.Accordion(
+                    "Mode Definition",
+                    open=False,
+                    elem_classes="clean-accordion",
+                ):
+                    gr.Markdown(USER_GUIDE_SECTIONS["mode_definition"])
+                with gr.Accordion(
+                    "How Clare Works",
+                    open=False,
+                    elem_classes="clean-accordion",
+                ):
+                    gr.Markdown(USER_GUIDE_SECTIONS["how_clare_works"])
+                with gr.Accordion(
+                    "What is Memory Line",
+                    open=False,
+                    elem_classes="clean-accordion",
+                ):
+                    gr.Markdown(USER_GUIDE_SECTIONS["memory_line"])
+                with gr.Accordion(
+                    "Learning Progress Report",
+                    open=False,
+                    elem_classes="clean-accordion",
+                ):
+                    gr.Markdown(USER_GUIDE_SECTIONS["learning_progress"])
+                with gr.Accordion(
+                    "How Clare Uses Your Files",
+                    open=False,
+                    elem_classes="clean-accordion",
+                ):
+                    gr.Markdown(USER_GUIDE_SECTIONS["how_files"])
+                with gr.Accordion(
+                    "Micro-Quiz", open=False, elem_classes="clean-accordion"
+                ):
+                    gr.Markdown(USER_GUIDE_SECTIONS["micro_quiz"])
+                with gr.Accordion(
+                    "Summarization",
+                    open=False,
+                    elem_classes="clean-accordion",
+                ):
+                    gr.Markdown(USER_GUIDE_SECTIONS["summarization"])
+                with gr.Accordion(
+                    "Export Conversation",
+                    open=False,
+                    elem_classes="clean-accordion",
+                ):
+                    gr.Markdown(USER_GUIDE_SECTIONS["export_conversation"])
+                with gr.Accordion(
+                    "FAQ", open=False, elem_classes="clean-accordion"
+                ):
+                    gr.Markdown(USER_GUIDE_SECTIONS["faq"])
+
+            gr.Markdown("---")
+            gr.Button("System Settings", size="sm", variant="secondary", interactive=False)
+
+            gr.HTML(
+                """
+                <div style="font-size: 11px; color: #9ca3af; margin-top: 15px; text-align: left;">
+                    © 2025 Made by <a href="https://www.linkedin.com/in/qinghua-xia-479199252/" target="_blank" style="color: #6b7280; text-decoration: underline;">Sarah Xia</a>
+                </div>
+                """
+            )
 
-    new_status = render_session_status(
-        mode_val or "Concept Explainer",
-        weaknesses or [],
-        cognitive_state or {"confusion": 0, "mastery": 0},
+        # === Center Main ===
+        with gr.Column(scale=3):
+
+            # --- Top Control Row ---
+            with gr.Row():
+                with gr.Column(scale=2):
+                    syllabus_file = gr.File(
+                        file_types=[".docx", ".pdf", ".pptx"],
+                        file_count="single",
+                        height=160,
+                        label="Upload additional Module 10 file (.docx/.pdf/.pptx) — optional",
+                        interactive=False,
+                    )
+                with gr.Column(scale=1):
+                    doc_type = gr.Dropdown(
+                        choices=DOC_TYPES,
+                        value="Reading",
+                        label="File type",
+                        container=True,
+                        interactive=False,
+                    )
+                    gr.HTML("<div style='height:5px'></div>")
+                    docs_btn = gr.Button(
+                        "📂 Loaded Docs", size="sm", variant="secondary", interactive=False
+                    )
+                with gr.Column(scale=2):
+                    with gr.Group(elem_classes="memory-line-box"):
+                        gr.HTML(
+                            f"""
+                            <div style="font-weight:bold; font-size:14px; margin-bottom:5px;">
+                                <span class="html-tooltip" data-tooltip="See User Guide for explanation">Memory Line</span>
+                            </div>
+                            <div style="position: relative; height: 35px; margin-top: 10px; 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;">
+                                <div style="font-size: 12px; color: #666;">Next Review: T+7</div>
+                                <div style="font-size: 12px; color: #004a99; text-decoration:underline; cursor:pointer;">Report ⬇️</div>
+                            </div>
+                            """
+                        )
+                        review_btn = gr.Button(
+                            "Review Now", size="sm", variant="primary", interactive=False
+                        )
+                        session_status = gr.Markdown(visible=False)
+
+            # Chat instruction（主聊天框上方提示 Module10 已预加载）
+            gr.Markdown(
+                """
+                <div style="background-color:#f9fafb; padding:10px; border-radius:5px; margin-top:10px; font-size:0.9em; color:#555;">
+                ✦ <b>Instruction:</b> This prototype is <b>pre-loaded</b> with <b>Module 10 – Responsible AI (Alto, 2024, Chapter 12)</b>.<br>
+                ✦ You do <b>not</b> need to upload files (uploads are optional).<br>
+                ✦ Please log in on the right before chatting with Clare.
+                </div>
+                """
+            )
+            chatbot = gr.Chatbot(
+                label="",
+                height=450,
+                avatar_images=(None, CLARE_LOGO_PATH),
+                show_label=False,
+                bubble_full_width=False,
+            )
+            user_input = gr.Textbox(
+                label="Your Input",
+                placeholder="Please log in on the right before asking Clare anything...",
+                show_label=False,
+                container=True,
+                autofocus=False,
+                interactive=False,
+            )
+
+        # === Right Sidebar ===
+        with gr.Column(scale=1, min_width=180):
+            with gr.Group(elem_classes="login-panel"):
+                gr.HTML(f"<img src='{image_to_base64(CLARE_READING_PATH)}'>")
+
+                with gr.Group(visible=True) as login_state_1:
+                    login_start_btn = gr.Button(
+                        "Student Login", elem_classes="login-main-btn"
+                    )
+
+                with gr.Group(visible=False) as login_state_2:
+                    name_input = gr.Textbox(
+                        label="Student Name", placeholder="Name", container=True
+                    )
+                    id_input = gr.Textbox(
+                        label="Email/ID", placeholder="ID", container=True
+                    )
+                    login_confirm_btn = gr.Button(
+                        "Enter", variant="primary", size="sm"
+                    )
+
+                with gr.Group(visible=False) as login_state_3:
+                    student_info_html = gr.HTML()
+                    logout_btn = gr.Button(
+                        "Log out", elem_classes="logout-btn", size="sm"
+                    )
+
+            gr.Markdown("### Actions")
+            export_btn = gr.Button(
+                "Export Conversation", size="sm", elem_classes="action-btn", interactive=False
+            )
+            quiz_btn = gr.Button(
+                "Let's Try (Micro-Quiz)", size="sm", elem_classes="action-btn", interactive=False
+            )
+            summary_btn = gr.Button(
+                "Summarization", size="sm", elem_classes="action-btn", interactive=False
+            )
+
+            gr.Markdown("### Results")
+            with gr.Group(elem_classes="result-box"):
+                result_display = gr.Markdown(
+                    value="Results (export / summary) will appear here...",
+                    label="Generated Content",
+                )
+
+    # ================== Login Flow ==================
+
+    def show_inputs():
+        return {
+            login_state_1: gr.update(visible=False),
+            login_state_2: gr.update(visible=True),
+            login_state_3: gr.update(visible=False),
+        }
+
+    login_start_btn.click(
+        show_inputs, outputs=[login_state_1, login_state_2, login_state_3]
+    )
+
+    def confirm_login(name, id_val):
+        if not name or not id_val:
+            return {
+                login_state_1: gr.update(),
+                login_state_2: gr.update(),
+                login_state_3: gr.update(),
+                student_info_html: gr.update(
+                    value="<p style='color:red; font-size:12px;'>Please enter both Name and Email/ID to start.</p>"
+                ),
+                user_name_state: gr.update(),
+                user_id_state: gr.update(),
+                user_input: gr.update(interactive=False),
+                clear_btn: gr.update(interactive=False),
+                export_btn: gr.update(interactive=False),
+                quiz_btn: gr.update(interactive=False),
+                summary_btn: gr.update(interactive=False),
+                syllabus_file: gr.update(interactive=False),
+                doc_type: gr.update(interactive=False),
+                review_btn: gr.update(interactive=False),
+                language_preference: gr.update(interactive=False),
+                learning_mode: gr.update(interactive=False),
+                model_name: gr.update(interactive=False),
+                docs_btn: gr.update(interactive=False),
+            }
+
+        info_html = f"""
+        <div style="margin-bottom:10px;">
+            <div style="font-weight:bold; font-size:16px;">{name}</div>
+            <div style="color:#666; font-size:12px;">{id_val}</div>
+        </div>
+        """
+        return {
+            login_state_1: gr.update(visible=False),
+            login_state_2: gr.update(visible=False),
+            login_state_3: gr.update(visible=True),
+            student_info_html: gr.update(value=info_html),
+            user_name_state: name,
+            user_id_state: id_val,
+            user_input: gr.update(
+                interactive=True,
+                placeholder="Ask about Module 10 concepts, Responsible AI, or let Clare test you...",
+            ),
+            clear_btn: gr.update(interactive=True),
+            export_btn: gr.update(interactive=True),
+            quiz_btn: gr.update(interactive=True),
+            summary_btn: gr.update(interactive=True),
+            syllabus_file: gr.update(interactive=True),
+            doc_type: gr.update(interactive=True),
+            review_btn: gr.update(interactive=True),
+            language_preference: gr.update(interactive=True),
+            learning_mode: gr.update(interactive=True),
+            model_name: gr.update(interactive=False),
+            docs_btn: gr.update(interactive=True),
+        }
+
+    login_confirm_btn.click(
+        confirm_login,
+        inputs=[name_input, id_input],
+        outputs=[
+            login_state_1,
+            login_state_2,
+            login_state_3,
+            student_info_html,
+            user_name_state,
+            user_id_state,
+            user_input,
+            clear_btn,
+            export_btn,
+            quiz_btn,
+            summary_btn,
+            syllabus_file,
+            doc_type,
+            review_btn,
+            language_preference,
+            learning_mode,
+            model_name,
+            docs_btn,
+        ],
     )
-    return "", new_history, weaknesses, cognitive_state, new_status
+
+    def logout():
+        return {
+            login_state_1: gr.update(visible=True),
+            login_state_2: gr.update(visible=False),
+            login_state_3: gr.update(visible=False),
+            name_input: gr.update(value=""),
+            id_input: gr.update(value=""),
+            user_name_state: "",
+            user_id_state: "",
+            student_info_html: gr.update(value=""),
+            user_input: gr.update(
+                value="",
+                interactive=False,
+                placeholder="Please log in on the right before asking Clare anything...",
+            ),
+            clear_btn: gr.update(interactive=False),
+            export_btn: gr.update(interactive=False),
+            quiz_btn: gr.update(interactive=False),
+            summary_btn: gr.update(interactive=False),
+            syllabus_file: gr.update(interactive=False),
+            doc_type: gr.update(interactive=False),
+            review_btn: gr.update(interactive=False),
+            language_preference: gr.update(interactive=False),
+            learning_mode: gr.update(interactive=False),
+            docs_btn: gr.update(interactive=False),
+        }
+
+    logout_btn.click(
+        logout,
+        outputs=[
+            login_state_1,
+            login_state_2,
+            login_state_3,
+            name_input,
+            id_input,
+            user_name_state,
+            user_id_state,
+            student_info_html,
+            user_input,
+            clear_btn,
+            export_btn,
+            quiz_btn,
+            summary_btn,
+            syllabus_file,
+            doc_type,
+            review_btn,
+            language_preference,
+            learning_mode,
+            docs_btn,
+        ],
+    )
+
+    # ================== Main Logic ==================
+
+    def update_course_and_rag(file, doc_type_val):
+        """
+        上传的文件会在 Module10 预加载的基础上「追加」，而不是替换。
+        """
+        local_topics = preloaded_topics or []
+        local_chunks = preloaded_chunks or []
+
+        if file is not None:
+            try:
+                topics = extract_course_topics_from_file(file, doc_type_val)
+            except Exception:
+                topics = []
+            try:
+                chunks = build_rag_chunks_from_file(file, doc_type_val)
+            except Exception:
+                chunks = []
+
+            local_topics = (preloaded_topics or []) + (topics or [])
+            local_chunks = (preloaded_chunks or []) + (chunks or [])
+
+            status_md = (
+                f"✅ **Loaded Module 10 base reading + uploaded {doc_type_val} file.**\n\n"
+                "Both will be used for explanations and quizzes."
+            )
+        else:
+            status_md = (
+                "�� **Using pre-loaded Module 10 reading only.**\n\n"
+                "You may optionally upload additional Module 10 materials."
+            )
+
+        return local_topics, local_chunks, status_md
+
+    syllabus_file.change(
+        update_course_and_rag,
+        [syllabus_file, doc_type],
+        [course_outline_state, rag_chunks_state, session_status],
+    )
+
+    def show_loaded_docs(doc_type_val):
+        gr.Info(
+            f"For this experiment, Clare always includes the pre-loaded Module 10 reading.\n"
+            f"Additional uploaded {doc_type_val} files will be used as supplementary context.",
+            title="Loaded Documents",
+        )
+
+    docs_btn.click(show_loaded_docs, inputs=[doc_type])
+
+    def respond(
+        message,
+        chat_history,
+        course_outline,
+        weaknesses,
+        cognitive_state,
+        rag_chunks,
+        model_name_val,
+        lang_pref,
+        mode_val,
+        doc_type_val,
+        user_id_val,
+    ):
+        # 双保险：没登录就提示
+        if not user_id_val:
+            out_msg = (
+                "🔒 Please log in with your Student Name and Email/ID on the right "
+                "before using Clare."
+            )
+            new_history = (chat_history or []) + [[message, out_msg]]
+            new_status = render_session_status(
+                mode_val or "Concept Explainer",
+                weaknesses or [],
+                cognitive_state or {"confusion": 0, "mastery": 0},
+            )
+            return "", new_history, weaknesses, cognitive_state, new_status
+
+        resolved_lang = detect_language(message or "", lang_pref)
+
+        if not message or not message.strip():
+            new_status = render_session_status(
+                mode_val or "Concept Explainer",
+                weaknesses or [],
+                cognitive_state or {"confusion": 0, "mastery": 0},
+            )
+            return "", chat_history, weaknesses, cognitive_state, new_status
+
+        weaknesses = update_weaknesses_from_message(message, weaknesses or [])
+        cognitive_state = update_cognitive_state_from_message(message, cognitive_state)
+
+        # RAG 始终基于 (预加载 Module10 + 可选上传)
+        rag_context = retrieve_relevant_chunks(message, rag_chunks or [])
+
+        start_ts = time.time()
+        answer, new_history = chat_with_clare(
+            message=message,
+            history=chat_history,
+            model_name=model_name_val,
+            language_preference=resolved_lang,
+            learning_mode=mode_val,
+            doc_type=doc_type_val,
+            course_outline=course_outline,
+            weaknesses=weaknesses,
+            cognitive_state=cognitive_state,
+            rag_context=rag_context,
+        )
+        end_ts = time.time()
+        latency_ms = (end_ts - start_ts) * 1000.0
+
+        student_id = user_id_val or "ANON"
+        experiment_id = "RESP_AI_W10"
+
+        try:
+            log_event(
+                {
+                    "experiment_id": experiment_id,
+                    "student_id": student_id,
+                    "event_type": "chat_turn",
+                    "timestamp": end_ts,
+                    "latency_ms": latency_ms,
+                    "question": message,
+                    "answer": answer,
+                    "model_name": model_name_val,
+                    "language": resolved_lang,
+                    "learning_mode": mode_val,
+                }
+            )
+        except Exception as e:
+            print("log_event error:", e)
+
+        new_status = render_session_status(mode_val, 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_id_state,
+        ],
+        [user_input, chatbot, weakness_state, cognitive_state_state, session_status],
+    )
+
+    # ===== Micro-Quiz: 直接在主 Chatbot 里进行 =====
+    def start_micro_quiz(
+        chat_history,
+        course_outline,
+        weaknesses,
+        cognitive_state,
+        rag_chunks,
+        model_name_val,
+        lang_pref,
+        mode_val,
+        doc_type_val,
+        user_id_val,
+    ):
+        if not user_id_val:
+            gr.Info("Please log in first to start a micro-quiz.", title="Login required")
+            return (
+                chat_history,
+                weaknesses,
+                cognitive_state,
+                render_session_status(
+                    mode_val or "Concept Explainer",
+                    weaknesses or [],
+                    cognitive_state or {"confusion": 0, "mastery": 0},
+                ),
+            )
+
+        quiz_instruction = (
+            "We are running a short micro-quiz session based ONLY on **Module 10 – "
+            "Responsible AI (Alto, 2024, Chapter 12)** and the pre-loaded materials.\n\n"
+            "From now on, please:\n"
+            "1) Ask me ONE quiz question at a time, based on Module 10 concepts "
+            "(Responsible AI definition, risk types, mitigation layers, EU AI Act, etc.).\n"
+            "2) Do NOT reveal the answer when you ask the question.\n"
+            "3) When I reply, grade my answer, explain briefly, and then ask if I want another question.\n"
+            "4) Continue this pattern until I explicitly say to stop.\n\n"
+            "Please now send the FIRST quiz question only."
+        )
+
+        resolved_lang = lang_pref
+
+        start_ts = time.time()
+        answer, new_history = chat_with_clare(
+            message=quiz_instruction,
+            history=chat_history,
+            model_name=model_name_val,
+            language_preference=resolved_lang,
+            learning_mode=mode_val,
+            doc_type=doc_type_val,
+            course_outline=course_outline,
+            weaknesses=weaknesses,
+            cognitive_state=cognitive_state,
+            rag_context=retrieve_relevant_chunks(
+                "Module 10 quiz", rag_chunks or []
+            ),
+        )
+        end_ts = time.time()
+        latency_ms = (end_ts - start_ts) * 1000.0
+
+        student_id = user_id_val or "ANON"
+        experiment_id = "RESP_AI_W10"
+
+        try:
+            log_event(
+                {
+                    "experiment_id": experiment_id,
+                    "student_id": student_id,
+                    "event_type": "micro_quiz_start",
+                    "timestamp": end_ts,
+                    "latency_ms": latency_ms,
+                    "question": quiz_instruction,
+                    "answer": answer,
+                    "model_name": model_name_val,
+                    "language": resolved_lang,
+                    "learning_mode": mode_val,
+                }
+            )
+        except Exception as e:
+            print("log_event error:", e)
+
+        new_status = render_session_status(mode_val, weaknesses, cognitive_state)
+        return new_history, weaknesses, cognitive_state, new_status
+
+    quiz_btn.click(
+        start_micro_quiz,
+        [
+            chatbot,
+            course_outline_state,
+            weakness_state,
+            cognitive_state_state,
+            rag_chunks_state,
+            model_name,
+            language_preference,
+            learning_mode,
+            doc_type,
+            user_id_state,
+        ],
+        [chatbot, weakness_state, cognitive_state_state, session_status],
+    )
+
+    # ===== Export / Summary =====
+    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],
+    )
+
+    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 Conversation =====
+    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,
+    )
+
+if __name__ == "__main__":
+    demo.launch()