Update app.py

app.py

@@ -31,7 +31,7 @@ from syllabus_utils import extract_course_topics_from_file
 HANBRIDGE_LOGO_PATH = "hanbridge_logo.png"
 CLARE_LOGO_PATH = "clare_mascot.png" 
 CLARE_RUN_PATH = "Clare_Run.png"
-CLARE_READING_PATH = "Clare_reading.png" # 请确保上传了这张图片
+CLARE_READING_PATH = "Clare_reading.png"  # 请确保上传了这张图片
 
 # ================== Base64 Helper ==================
 def image_to_base64(image_path):
@@ -190,7 +190,7 @@ CUSTOM_CSS = """
 
 /* --- Sidebar Login Panel --- */
 .login-panel {
-    background-color: #e5e7eb; /* 浅灰色背景 */
+    background-color: #e5e7eb;
     padding: 15px;
     border-radius: 8px;
     text-align: center;
@@ -199,7 +199,7 @@ CUSTOM_CSS = """
 .login-panel img {
     display: block;
     margin: 0 auto 10px auto;
-    height: 80px; /* 调整图片高度 */
+    height: 80px;
     object-fit: contain;
 }
 .login-main-btn {
@@ -209,7 +209,7 @@ CUSTOM_CSS = """
     font-weight: bold !important;
 }
 .logout-btn {
-    background-color: #6b2828 !important; /* 深红色背景 */
+    background-color: #6b2828 !important;
     color: #fff !important;
     border: none !important;
     font-weight: bold !important;
@@ -242,6 +242,31 @@ CUSTOM_CSS = """
 @keyframes fadeIn { to { opacity: 1; } }
 """
 
+# ===== log ====
+import time
+import requests
+
+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:
@@ -252,7 +277,7 @@ with gr.Blocks(title="Clare – Hanbridge AI Teaching Assistant", css=CUSTOM_CSS
     cognitive_state_state = gr.State({"confusion": 0, "mastery": 0})
     rag_chunks_state = gr.State([])
     
-    # 用户状态
+    # 用户状态（登录）
     user_name_state = gr.State("")
     user_id_state = gr.State("")
 
@@ -307,16 +332,26 @@ with gr.Blocks(title="Clare – Hanbridge AI Teaching Assistant", css=CUSTOM_CSS
 
             # 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"])
+                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")
@@ -336,7 +371,7 @@ with gr.Blocks(title="Clare – Hanbridge AI Teaching Assistant", css=CUSTOM_CSS
             with gr.Row():
                 # Upload Box
                 with gr.Column(scale=2):
-                     syllabus_file = gr.File(
+                    syllabus_file = gr.File(
                         file_types=[".docx", ".pdf", ".pptx"], 
                         file_count="single", 
                         height=160, 
@@ -344,9 +379,9 @@ with gr.Blocks(title="Clare – Hanbridge AI Teaching Assistant", css=CUSTOM_CSS
                     )
                 # Controls
                 with gr.Column(scale=1):
-                     doc_type = gr.Dropdown(choices=DOC_TYPES, value="Syllabus", label="File type", container=True)
-                     gr.HTML("<div style='height:5px'></div>")
-                     docs_btn = gr.Button("📂 Loaded Docs", size="sm", variant="secondary")
+                    doc_type = gr.Dropdown(choices=DOC_TYPES, value="Syllabus", label="File type", container=True)
+                    gr.HTML("<div style='height:5px'></div>")
+                    docs_btn = gr.Button("📂 Loaded Docs", size="sm", variant="secondary")
                 # Memory Line
                 with gr.Column(scale=2): 
                     with gr.Group(elem_classes="memory-line-box"):
@@ -378,18 +413,29 @@ with gr.Blocks(title="Clare – Hanbridge AI Teaching Assistant", css=CUSTOM_CSS
                 </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="Ask about a concept, your assignment, or let Clare test you...", show_label=False, container=True, autofocus=True)
+            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="Ask about a concept, your assignment, or let Clare test you...",
+                show_label=False,
+                container=True,
+                autofocus=True
+            )
 
         # === Right Sidebar ===
         with gr.Column(scale=1, min_width=180):
             
-            # --- New Login Panel (占用原来的 Spacer 空间) ---
+            # --- New Login Panel ---
             with gr.Group(elem_classes="login-panel"):
-                # 图片始终显示
                 gr.HTML(f"<img src='{image_to_base64(CLARE_READING_PATH)}'>")
                 
-                # 状态 1: 未登录 (显示 Login 按钮)
+                # 状态 1: 未登录
                 with gr.Group(visible=True) as login_state_1:
                     login_start_btn = gr.Button("Student Login", elem_classes="login-main-btn")
                 
@@ -399,9 +445,8 @@ with gr.Blocks(title="Clare – Hanbridge AI Teaching Assistant", css=CUSTOM_CSS
                     id_input = gr.Textbox(label="Email/ID", placeholder="ID", container=True)
                     login_confirm_btn = gr.Button("Enter", variant="primary", size="sm")
                 
-                # 状态 3: 已登录 (显示信息 + Logout)
+                # 状态 3: 已登录
                 with gr.Group(visible=False) as login_state_3:
-                    # 使用 HTML 显示居中的加粗名字
                     student_info_html = gr.HTML() 
                     logout_btn = gr.Button("Log out", elem_classes="logout-btn", size="sm")
 
@@ -414,7 +459,10 @@ with gr.Blocks(title="Clare – Hanbridge AI Teaching Assistant", css=CUSTOM_CSS
             # Results
             gr.Markdown("### Results")
             with gr.Group(elem_classes="result-box"):
-                result_display = gr.Markdown(value="Results will appear here...", label="Generated Content")
+                result_display = gr.Markdown(
+                    value="Results will appear here...",
+                    label="Generated Content"
+                )
 
     # ================== Logic: Sidebar Login Flow ==================
 
@@ -423,18 +471,27 @@ with gr.Blocks(title="Clare – Hanbridge AI Teaching Assistant", css=CUSTOM_CSS
         return {
             login_state_1: gr.update(visible=False),
             login_state_2: gr.update(visible=True),
-            login_state_3: gr.update(visible=False)
+            login_state_3: gr.update(visible=False),
         }
     
-    login_start_btn.click(show_inputs, outputs=[login_state_1, login_state_2, login_state_3])
+    login_start_btn.click(
+        show_inputs,
+        outputs=[login_state_1, login_state_2, login_state_3]
+    )
 
-    # 2. Confirm Login -> Show Profile
+    # 2. Confirm Login -> Show Profile & 更新 user_*_state
     def confirm_login(name, id_val):
         if not name or not id_val:
             # 简单验证，若为空则不跳转
-            return gr.update(), gr.update(), gr.update(), gr.update(), gr.update(), gr.update()
+            return {
+                login_state_1: gr.update(),
+                login_state_2: gr.update(),
+                login_state_3: gr.update(),
+                student_info_html: gr.update(),
+                user_name_state: gr.update(),
+                user_id_state: gr.update(),
+            }
         
-        # 构建居中的 HTML 信息
         info_html = f"""
         <div style="margin-bottom:10px;">
             <div style="font-weight:bold; font-size:16px;">{name}</div>
@@ -448,13 +505,20 @@ with gr.Blocks(title="Clare – Hanbridge AI Teaching Assistant", css=CUSTOM_CSS
             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_id_state: id_val,
         }
 
     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]
+        outputs=[
+            login_state_1,
+            login_state_2,
+            login_state_3,
+            student_info_html,
+            user_name_state,
+            user_id_state,
+        ]
     )
 
     # 3. Logout -> Reset
@@ -466,10 +530,21 @@ with gr.Blocks(title="Clare – Hanbridge AI Teaching Assistant", css=CUSTOM_CSS
             name_input: gr.update(value=""),
             id_input: gr.update(value=""),
             user_name_state: "",
-            user_id_state: ""
+            user_id_state: "",
         }
 
-    logout_btn.click(logout, outputs=[login_state_1, login_state_2, login_state_3, name_input, id_input, user_name_state, user_id_state])
+    logout_btn.click(
+        logout,
+        outputs=[
+            login_state_1,
+            login_state_2,
+            login_state_3,
+            name_input,
+            id_input,
+            user_name_state,
+            user_id_state,
+        ]
+    )
 
     # ================== Main App Logic ==================
 
@@ -479,32 +554,140 @@ with gr.Blocks(title="Clare – Hanbridge AI Teaching Assistant", css=CUSTOM_CSS
         status_md = f"✅ **File Loaded:** {doc_type_val}\n\nAnalyzing content for Memory Line..."
         return topics, rag_chunks, status_md
 
-    syllabus_file.change(update_course_and_rag, [syllabus_file, doc_type], [course_outline_state, rag_chunks_state, session_status])
-    docs_btn.click(lambda: gr.Info("Current Context: Syllabus.pdf (Uploaded), Course_Intro.docx (System)", title="Loaded Documents"))
+    syllabus_file.change(
+        update_course_and_rag,
+        [syllabus_file, doc_type],
+        [course_outline_state, rag_chunks_state, session_status],
+    )
+    docs_btn.click(
+        lambda: gr.Info(
+            "Current Context: Syllabus.pdf (Uploaded), Course_Intro.docx (System)",
+            title="Loaded Documents",
+        )
+    )
+
+    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,
+    ):
+        # 语言决策
+        resolved_lang = detect_language(message or "", lang_pref)
 
-    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
+            # 空输入，直接返回，不更新状态
+            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_context = retrieve_relevant_chunks(message, rag_chunks or [])
-        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)
+            
+        # 调用 Clare 并记录时间
+        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
+    
+        # 日志所用的 student_id（来自登录；未登录则为 ANON）
+        student_id = user_id_val or "ANON"
+        experiment_id = "RESP_AI_W10"  # 你定义一个本次实验的ID
+    
+        # 发送日志到 Google Sheet
+        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)
+            
+        # 更新 session_status
+        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_input, chatbot, weakness_state, cognitive_state_state, session_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,   # ✅ 把登录的 ID 作为 respond 的输入
+        ],
+        [user_input, chatbot, weakness_state, cognitive_state_state, session_status],
+    )
 
-    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])
+    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],
+    )
     
     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)
+
+    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()
-