update

app.py

@@ -367,7 +367,7 @@ def extract_youtube_id(url):
     else:
         return None
 
-def get_transcript(video_id):
+def get_transcript_by_yt_api(video_id):
     languages = ['zh-TW', 'zh-Hant', 'zh', 'en']  # 優先順序列表
     for language in languages:
         try:
@@ -380,7 +380,7 @@ def get_transcript(video_id):
             continue  # 當前語言的字幕沒有找到，繼續嘗試下一個語言
     return None  # 所有嘗試都失敗，返回None
 
-def generate_transcription(video_id):
+def generate_transcription_by_whisper(video_id):
     youtube_url = f'https://www.youtube.com/watch?v={video_id}'
     codec_name = "mp3"
     outtmpl = f"{OUTPUT_PATH}/{video_id}.%(ext)s"
@@ -457,17 +457,17 @@ def process_transcript_and_screenshots_on_gcs(video_id):
         print("逐字稿文件不存在于GCS中，重新建立")
         # 从YouTube获取逐字稿并上传
         try:
-            transcript = get_transcript(video_id)
+            transcript = get_transcript_by_yt_api(video_id)
         except:
             # call open ai whisper
             print("===call open ai whisper===")
-            transcript = generate_transcription(video_id)
+            transcript = generate_transcription_by_whisper(video_id)
 
         if transcript:
             print("成功獲取字幕")
         else:
             print("沒有找到字幕")
-            transcript = generate_transcription(video_id)
+            transcript = generate_transcription_by_whisper(video_id)
 
         transcript_text = json.dumps(transcript, ensure_ascii=False, indent=2)
         upload_file_to_gcs_with_json_string(gcs_client, bucket_name, transcript_blob_name, transcript_text)
@@ -572,6 +572,7 @@ def process_youtube_link(password, link):
     questions = get_questions(video_id, formatted_simple_transcript, source)
     questions_json = json.dumps(questions, ensure_ascii=False, indent=2)
     summary_json = get_video_id_summary(video_id, formatted_simple_transcript, source)
+    summary_text = summary_json["summary"]
     summary = summary_json["summary"]
     key_moments_json = get_key_moments(video_id, formatted_simple_transcript, formatted_transcript, source)
     key_moments = key_moments_json["key_moments"]
@@ -586,6 +587,7 @@ def process_youtube_link(password, link):
     mind_map = mind_map_json["mind_map"]
     mind_map_html = get_mind_map_html(mind_map)
     reading_passage_json = get_reading_passage(video_id, formatted_simple_transcript, source)
+    reading_passage_text = reading_passage_json["reading_passage"]
     reading_passage = reading_passage_json["reading_passage"]
     meta_data = get_meta_data(video_id)
     subject = meta_data["subject"]
@@ -598,6 +600,7 @@ def process_youtube_link(password, link):
         questions[1] if len(questions) > 1 else "", \
         questions[2] if len(questions) > 2 else "", \
         original_transcript, \
+        summary_text, \
         summary, \
         key_moments_text, \
         key_moments_html, \
@@ -607,6 +610,7 @@ def process_youtube_link(password, link):
         simple_html_content, \
         first_image, \
         first_text, \
+        reading_passage_text, \
         reading_passage, \
         subject, \
         grade
@@ -750,6 +754,8 @@ def generate_reading_passage(df_string):
         請一定要使用繁體中文 zh-TW，並用台灣人的口語
         產生的結果不要前後文解釋，也不要敘述這篇文章怎麼產生的
         只需要專注提供 Reading Passage，字數在 500 字以內
+        敘述中，請把數學或是專業術語，用 Latex 包覆（$...$），並且不要去改原本的文章
+        加減乘除、根號、次方等等的運算式口語也換成 LATEX 數學符號
     """
     messages = [
         {"role": "system", "content": sys_content},
@@ -757,7 +763,7 @@ def generate_reading_passage(df_string):
     ]
 
     request_payload = {
-        "model": "gpt-4-1106-preview",
+        "model": "gpt-4-turbo",
         "messages": messages,
         "max_tokens": 4000,
     }
@@ -834,7 +840,7 @@ def generate_mind_map(df_string):
     ]
 
     request_payload = {
-        "model": "gpt-4-1106-preview",
+        "model": "gpt-4-turbo",
         "messages": messages,
         "max_tokens": 4000,
     }
@@ -916,22 +922,27 @@ def generate_summarise(df_string):
     sys_content = "你是一個擅長資料分析跟影片教學的老師，user 為學生，請精讀資料文本，自行判斷資料的種類，使用 zh-TW"
     user_content = f"""
         請根據 {df_string}，判斷這份文本
-        如果是資料類型，請提估欄位敘述、資料樣態與資料分析，告訴學生這張表的意義，以及可能的結論與對應方式
-        
-        如果是影片類型，請提估影片內容，告訴學生這部影片的意義，
+        格式為 Markdown
         整體摘要在一百字以內
-        小範圍切出不同段落的相對應時間軸的重點摘要，最多不超過五段
-        注意不要遺漏任何一段時間軸的內容
-        格式為 【start - end】: 摘要
+        重點概念列出 bullet points，至少三個，最多五個
         以及可能的結論與結尾延伸小問題提供學生作反思
+        敘述中，請把數學或是專業術語，用 Latex 包覆（$...$）
+        加減乘除、根號、次方等等的運算式口語也換成 LATEX 數學符號
 
         整體格式為：
-        🗂️ 1. 內容類型：？
-        📚 2. 整體摘要
-        🔖 3. 重點概念
-        🔑 4. 關鍵時刻
-        💡 5. 為什麼我們要學這個？
-        ❓ 6. 延伸小問題
+        ## 📚 整體摘要
+            - (一個 bullet point....)
+
+        ## 🔖 重點概念
+            - xxx
+            - xxx
+            - xxx
+        
+        ## 💡 為什麼我們要學這個？
+            - (一個 bullet point....)
+        
+        ## ❓ 延伸小問題
+            - (一個 bullet point....)
     """
 
     # 🗂️ 1. 內容類型：？
@@ -947,7 +958,7 @@ def generate_summarise(df_string):
     ]
 
     request_payload = {
-        "model": "gpt-4-turbo-preview",
+        "model": "gpt-4-turbo",
         "messages": messages,
         "max_tokens": 4000,
     }
@@ -1014,9 +1025,17 @@ def get_questions(video_id, df_string, source="gcs"):
 
 def generate_questions(df_string):
     # 使用 OpenAI 生成基于上传数据的问题
+    if isinstance(df_string, str):
+        df_string_json = json.loads(df_string)
+    else:
+        df_string_json = df_string
+    content_text = ""
+
+    for entry in df_string_json:
+        content_text += entry["text"] + "，"
 
     sys_content = "你是一個擅長資料分析跟影片教學的老師，user 為學生，請精讀資料文本，自行判斷資料的種類，並用既有資料為本質猜測用戶可能會問的問題，使用 zh-TW"
-    user_content = f"請根據 {df_string} 生成三個問題，並用 JSON 格式返回 questions:[q1的敘述text, q2的敘述text, q3的敘述text]"
+    user_content = f"請根據 {content_text} 生成三個問題，並用 JSON 格式返回 questions:[q1的敘述text, q2的敘述text, q3的敘述text]"
     messages = [
         {"role": "system", "content": sys_content},
         {"role": "user", "content": user_content}
@@ -1029,7 +1048,7 @@ def generate_questions(df_string):
 
 
     request_payload = {
-        "model": "gpt-4-1106-preview",
+        "model": "gpt-4-turbo",
         "messages": messages,
         "max_tokens": 4000,
         "response_format": response_format
@@ -1147,7 +1166,7 @@ def generate_key_moments(formatted_simple_transcript, formatted_transcript):
     response_format = { "type": "json_object" }
 
     request_payload = {
-        "model": "gpt-4-1106-preview",
+        "model": "gpt-4-turbo",
         "messages": messages,
         "max_tokens": 4096,
         "response_format": response_format
@@ -1189,7 +1208,7 @@ def generate_key_moments_keywords(transcript):
         {"role": "user", "content": user_content}
     ]
     request_payload = {
-        "model": "gpt-4-1106-preview",
+        "model": "gpt-4-turbo",
         "messages": messages,
         "max_tokens": 100,
     }
@@ -1402,6 +1421,27 @@ def get_key_moments_html(key_moments):
     return key_moments_html
 
 # ---- LLM CRUD ----
+def get_LLM_content(video_id, kind):
+    print(f"===get_{kind}===")
+    gcs_client = GCS_CLIENT
+    bucket_name = 'video_ai_assistant'
+    file_name = f'{video_id}_{kind}.json'
+    blob_name = f"{video_id}/{file_name}"
+    # 检查 file 是否存在
+    is_file_exists = GCS_SERVICE.check_file_exists(bucket_name, blob_name)
+    if is_file_exists:
+        content = download_blob_to_string(gcs_client, bucket_name, blob_name)
+        content_json = json.loads(content)
+        if kind == "reading_passage":
+            content_text = content_json["reading_passage"]
+        elif kind == "summary":
+            content_text = content_json["summary"]
+        else:
+            content_text = json.dumps(content_json, ensure_ascii=False, indent=2)
+    else:
+        content_text = ""
+    return content_text
+
 def enable_edit_mode():
     return gr.update(interactive=True)
 
@@ -1426,15 +1466,17 @@ def update_LLM_content(video_id, new_content, kind):
     blob_name = f"{video_id}/{file_name}"
 
     if kind == "reading_passage":
+        print("=========reading_passage=======")
+        print(new_content)
         reading_passage_json = {"reading_passage": str(new_content)}
         reading_passage_text = json.dumps(reading_passage_json, ensure_ascii=False, indent=2)
         upload_file_to_gcs_with_json_string(gcs_client, bucket_name, blob_name, reading_passage_text)
-        updated_content = reading_passage_text
+        updated_content = new_content
     elif kind == "summary":
         summary_json = {"summary": str(new_content)}
         summary_text = json.dumps(summary_json, ensure_ascii=False, indent=2)
         upload_file_to_gcs_with_json_string(gcs_client, bucket_name, blob_name, summary_text)
-        updated_content = summary_text
+        updated_content = new_content
     elif kind == "mind_map":
         mind_map_json = {"mind_map": str(new_content)}
         mind_map_text = json.dumps(mind_map_json, ensure_ascii=False, indent=2)
@@ -1507,7 +1549,6 @@ def create_LLM_content(video_id, df_string, kind):
 
     return gr.update(value=content, interactive=False)
 
-
 # AI 生成教學素材
 def get_meta_data(video_id, source="gcs"):
     if source == "gcs":
@@ -1611,7 +1652,7 @@ def generate_ai_content(password, df_string, topic, grade, level, specific_featu
     prompt = material.generate_content_prompt()
     user_content = material.build_user_content()
     messages = material.build_messages(user_content)
-    ai_model_name = "gpt-4-1106-preview"
+    ai_model_name = "gpt-4-turbo"
     request_payload = {
         "model": ai_model_name,
         "messages": messages,
@@ -1625,7 +1666,7 @@ def generate_exam_fine_tune_result(password, exam_result_prompt , df_string_outp
     material = EducationalMaterial(df_string_output, "", "", "", "", "")
     user_content = material.build_fine_tune_user_content(exam_result_prompt, exam_result, exam_result_fine_tune_prompt)
     messages = material.build_messages(user_content)
-    ai_model_name = "gpt-4-1106-preview"
+    ai_model_name = "gpt-4-turbo"
     request_payload = {
         "model": ai_model_name,
         "messages": messages,
@@ -1661,7 +1702,7 @@ def get_instructions(content_subject, content_grade, key_moments):
         Language: Traditional Chinese ZH-TW (it's very important), suitable for {content_grade} th-grade level.
         Response: 
         - Single question, under 100 characters
-        - include math symbols (use LaTeX $ to cover before and after)
+        - include math symbols (use LaTeX $ to cover before and after, ex: $x^2$)
         - hint with video timestamp which format 【參考：00:00:00】. 
         - Sometimes encourage user by Taiwanese style with relaxing atmosphere.
         - if user ask questions not include in context, 
@@ -1670,19 +1711,28 @@ def get_instructions(content_subject, content_grade, key_moments):
     """
     return instructions
 
-def chat_with_ai(ai_name, password, video_id, trascript_state, key_moments, user_message, chat_history, content_subject, content_grade, socratic_mode=False):
+def chat_with_ai(ai_name, password, video_id, user_data, trascript_state, key_moments, user_message, chat_history, content_subject, content_grade, socratic_mode=False):
     verify_password(password)
 
-    if chat_history is not None and len(chat_history) > 10:
-        error_msg = "此次對話超過上限"
+    print("=====user_data=====")
+    print(f"user_data: {user_data}")
+
+    if chat_history is not None and len(chat_history) > 11:
+        error_msg = "此次對話超過上限（對話一輪10次）"
         raise gr.Error(error_msg)
 
+    if not ai_name in ["jutor", "claude3", "groq"]:
+        ai_name = "jutor"
+
     if ai_name == "jutor":
         ai_client = ""
     elif ai_name == "claude3":
         ai_client = BEDROCK_CLIENT
     elif ai_name == "groq":
         ai_client = GROQ_CLIENT
+    else:
+        ai_client = ""
+
     if isinstance(trascript_state, str):
         simple_transcript = json.loads(trascript_state)
     else:
@@ -1696,7 +1746,7 @@ def chat_with_ai(ai_name, password, video_id, trascript_state, key_moments, user
     for moment in key_moments_json:
         moment.pop('images', None)
         moment.pop('end', None)
-        moment.pop('text', None)
+        moment.pop('transcript', None)
     key_moments_text = json.dumps(key_moments_json, ensure_ascii=False)
 
     instructions = get_instructions(content_subject, content_grade, key_moments_text)
@@ -1735,9 +1785,12 @@ def chat_with_ai(ai_name, password, video_id, trascript_state, key_moments, user
         print(f"Error: {e}")
         return "请求失败，请稍后再试！", chat_history
 
-def chat_with_opan_ai_assistant(password, youtube_id, thread_id, trascript_state, key_moments, user_message, chat_history, content_subject, content_grade, socratic_mode=False):
+def chat_with_opan_ai_assistant(password, youtube_id, user_data, thread_id, trascript_state, key_moments, user_message, chat_history, content_subject, content_grade, socratic_mode=False):
     verify_password(password)
 
+    print("=====user_data=====")
+    print(f"user_data: {user_data}")
+
     # 先計算 user_message 是否超過 500 個字
     if len(user_message) > 1500:
         error_msg = "你的訊息太長了，請縮短訊息長度至五百字以內"
@@ -1745,7 +1798,7 @@ def chat_with_opan_ai_assistant(password, youtube_id, thread_id, trascript_state
     
     # 如果 chat_history 超過 10 則訊息，直接 return "對話超過上限"
     if chat_history is not None and len(chat_history) > 10:
-        error_msg = "此次對話超過上限"
+        error_msg = "此次對話超過上限（對話一輪10次）"
         raise gr.Error(error_msg)
 
     try:
@@ -1754,14 +1807,14 @@ def chat_with_opan_ai_assistant(password, youtube_id, thread_id, trascript_state
 
         client = OPEN_AI_CLIENT
         # 直接安排逐字稿資料 in instructions
-        if isinstance(trascript_state, str):
-            trascript_json = json.loads(trascript_state)
-        else:
-            trascript_json = trascript_state
-        # 移除 embed_url, screenshot_path
-        for entry in trascript_json:
-            entry.pop('end_time', None)
-        trascript_text = json.dumps(trascript_json, ensure_ascii=False)
+        # if isinstance(trascript_state, str):
+        #     trascript_json = json.loads(trascript_state)
+        # else:
+        #     trascript_json = trascript_state
+        # # 移除 embed_url, screenshot_path
+        # for entry in trascript_json:
+        #     entry.pop('end_time', None)
+        # trascript_text = json.dumps(trascript_json, ensure_ascii=False)
 
         if isinstance(key_moments, str):
             key_moments_json = json.loads(key_moments)
@@ -1771,7 +1824,7 @@ def chat_with_opan_ai_assistant(password, youtube_id, thread_id, trascript_state
         for moment in key_moments_json:
             moment.pop('images', None)
             moment.pop('end', None)
-            moment.pop('text', None)
+            moment.pop('transcript', None)
         key_moments_text = json.dumps(key_moments_json, ensure_ascii=False)
         
         instructions = get_instructions(content_subject, content_grade, key_moments_text)
@@ -1785,18 +1838,11 @@ def chat_with_opan_ai_assistant(password, youtube_id, thread_id, trascript_state
         else:
             thread = client.beta.threads.retrieve(thread_id)
         
-        user_msg_note = """\n (請一定要用繁體中文回答 zh-TW，
-            請嚴格遵循instructions，擔任一位蘇格拉底家教，
-            並用台灣人的禮貌口語表達，回答時不要特別說明這是台灣人的語氣，
-            不用提到「逐字稿」這個詞，用「內容」代替)，
-            回答時請用數學符號代替文字（Latex 用 $ 字號 render)
-        """
-        user_msg_note = user_msg_note.replace(" ","").replace("\n","")
         # 向线程添加用户的消息
         client.beta.threads.messages.create(
             thread_id=thread.id,
             role="user",
-            content=user_message + user_msg_note
+            content=user_message + "/n 請嚴格遵循instructions，擔任一位蘇格拉底家教，絕對不要重複 user 的問句，請用引導的方式指引方向，請一定要用繁體中文回答 zh-TW，並用台灣人的禮貌口語表達，回答時不要特別說明這是台灣人的語氣，請在回答的最後標註【參考：（時）:（分）:（秒）】，（如果是反問學生，就只問一個問題，請幫助學生更好的理解資料，字數在100字以內，回答時請用數學符號代替文字（Latex 用 $ 字號 render, ex: $x^2$)"
         )
 
         # 运行助手，生成响应
@@ -1900,9 +1946,12 @@ def poll_run_status(run_id, thread_id, timeout=600, poll_interval=5):
     
     return run.status
 
-def streaming_chat_with_open_ai(user_message, chat_history, password, thread_id, trascript, key_moments, content_subject, content_grade):
+def streaming_chat_with_open_ai(user_message, chat_history, password, user_data, thread_id, trascript, key_moments, content_subject, content_grade):
     verify_password(password)
 
+    print("=====user_data=====")
+    print(f"user_data: {user_data}")
+
     print("===streaming_chat_with_open_ai===")
     print(thread_id)
     
@@ -1912,8 +1961,8 @@ def streaming_chat_with_open_ai(user_message, chat_history, password, thread_id,
         raise gr.Error(error_msg)
     
     # 如果 chat_history 超過 10 則訊息，直接 return "對話超過上限"
-    if chat_history is not None and len(chat_history) > 10:
-        error_msg = "此次對話超過上限"
+    if chat_history is not None and len(chat_history) > 11:
+        error_msg = "此次對話超過上限（對話一輪10次）"
         raise gr.Error(error_msg)
 
     try:
@@ -1921,13 +1970,13 @@ def streaming_chat_with_open_ai(user_message, chat_history, password, thread_id,
         # assistant_id = "asst_5SaUElqvL3U0ybSi9PRM8x3P" #GPT 3.5 turbo
         client = OPEN_AI_CLIENT
         # 直接安排逐字稿資料 in instructions
-        if isinstance(trascript, str):
-            trascript_json = json.loads(trascript)
-        else:
-            trascript_json = trascript
-        trascript_text = json.dumps(trascript_json, ensure_ascii=False)
-        # trascript_text 移除 \n, 空白
-        trascript_text = trascript_text.replace("\n", "").replace(" ", "")
+        # if isinstance(trascript, str):
+        #     trascript_json = json.loads(trascript)
+        # else:
+        #     trascript_json = trascript
+        # trascript_text = json.dumps(trascript_json, ensure_ascii=False)
+        # # trascript_text 移除 \n, 空白
+        # trascript_text = trascript_text.replace("\n", "").replace(" ", "")
 
         if isinstance(key_moments, str):
             key_moments_json = json.loads(key_moments)
@@ -1952,7 +2001,7 @@ def streaming_chat_with_open_ai(user_message, chat_history, password, thread_id,
         client.beta.threads.messages.create(
             thread_id=thread.id,
             role="user",
-            content=user_message + "/n (請一定要用繁體中文回答 zh-TW，並用台灣人的禮貌口語表達，回答時不要特別說明這是台灣人的語氣，不用提到「逐字稿」這個詞，用「內容」代替))，請在回答的最後標註【參考資料：（時）:（分）:（秒）】，（如果是反問學生，就只問一個問題，請幫助學生更好的理解資料，字數在100字以內）"
+            content=user_message + "/n 請嚴格遵循instructions，擔任一位蘇格拉底家教，請一定要用繁體中文回答 zh-TW，並用台灣人的禮貌口語表達，回答時不要特別說明這是台灣人的語氣，不用提到「逐字稿」這個詞，用「內容」代替))，請在回答的最後標註【參考資料：（時）:（分）:（秒）】，（如果是反問學生，就只問一個問題，請幫助學生更好的理解資料，字數在100字以內）"
         )
 
         with client.beta.threads.runs.stream(
@@ -1977,6 +2026,21 @@ def create_thread_id():
     print(f"create new thread_id: {thread_id}")
     return thread_id
 
+def chatbot_select(chatbot_name):
+    chatbot_select_accordion_visible = gr.update(open=False)
+    chatbot_open_ai_visible = gr.update(visible=False)
+    chatbot_open_ai_streaming_visible = gr.update(visible=False)
+    chatbot_jutor_visible = gr.update(visible=False)
+
+    if chatbot_name == "chatbot_open_ai":
+        chatbot_open_ai_visible = gr.update(visible=True)
+    elif chatbot_name == "chatbot_open_ai_streaming":
+        chatbot_open_ai_streaming_visible = gr.update(visible=True)
+    elif chatbot_name == "chatbot_jutor":
+        chatbot_jutor_visible = gr.update(visible=True)
+        
+    return chatbot_select_accordion_visible, chatbot_open_ai_visible, chatbot_open_ai_streaming_visible, chatbot_jutor_visible
+
 # --- Slide mode ---
 def update_slide(direction):
     global TRANSCRIPTS
@@ -2021,6 +2085,13 @@ def init_params(text, request: gr.Request):
         reading_passage_admin = gr.update(visible=True)
         summary_admin = gr.update(visible=True)
         see_detail = gr.update(visible=True)
+        worksheet_accordion = gr.update(visible=True)
+        lesson_plan_accordion = gr.update(visible=True)
+        exit_ticket_accordion = gr.update(visible=True)
+
+        chatbot_open_ai = gr.update(visible=False)
+        chatbot_open_ai_streaming = gr.update(visible=False)
+        chatbot_jutor = gr.update(visible=False)
 
         # if youtube_link in query_params
         if "youtube_id" in request.query_params:
@@ -2036,8 +2107,14 @@ def init_params(text, request: gr.Request):
             reading_passage_admin = gr.update(visible=False)
             summary_admin = gr.update(visible=False)
             see_detail = gr.update(visible=False)
+            worksheet_accordion = gr.update(visible=False)
+            lesson_plan_accordion = gr.update(visible=False)
+            exit_ticket_accordion = gr.update(visible=False)
 
-    return admin, reading_passage_admin, summary_admin, see_detail, password_text, youtube_link
+    return admin, reading_passage_admin, summary_admin, see_detail, \
+        worksheet_accordion, lesson_plan_accordion, exit_ticket_accordion, \
+        password_text, youtube_link, \
+        chatbot_open_ai, chatbot_open_ai_streaming, chatbot_jutor
 
 def update_state(content_subject, content_grade, trascript, key_moments, question_1, question_2, question_3):
     # inputs=[content_subject, content_grade, df_string_output],
@@ -2138,14 +2215,68 @@ with gr.Blocks(theme=gr.themes.Base(primary_hue=gr.themes.colors.orange, seconda
         key_moments_state = gr.State()  # 使用 gr.State 存储 key_moments
         streaming_chat_thread_id_state = gr.State()  # 使用 gr.State 存储 streaming_chat_thread_id
     with gr.Tab("AI小精靈"):
-        with gr.Row():
-            with gr.Tab("飛特精靈"):
-                bot_avatar = "https://junyi-avatar.s3.ap-northeast-1.amazonaws.com/live/%20%20foxcat-star-18.png?v=20231113095823614"
-                user_avatar = "https://junyitopicimg.s3.amazonaws.com/s4byy--icon.jpe?v=20200513013523726"
+        with gr.Accordion("選擇 AI 小精靈", open=True) as chatbot_select_accordion:
+            with gr.Row():
+                with gr.Column(scale=1, variant="panel"):
+                    chatbot_avatar_url = "https://junyitopicimg.s3.amazonaws.com/s4byy--icon.jpe?v=20200513013523726"
+                    chatbot_description = """Hi，我是你的AI學伴【飛特精靈】，\n
+                    我可以陪你一起學習本次的內容，有什麼問題都可以問我喔！\n
+                    🤔 如果你不知道怎麼發問，可以點擊左下方的問題一、問題二、問題三，我會幫你生成問題！\n
+                    🗣️ 也可以點擊右下方用語音輸入，我會幫你轉換成文字，厲害吧！\n
+                    🔠 或是直接鍵盤輸入你的問題，我會盡力回答你的問題喔！\n
+                    💤 但我還在成長，體力有限，每一次學習只能回答十個問題，請讓我休息一下再問問題喔！\n
+                    🦄 如果達到上限，或是遇到精靈很累，請問問其他朋友，像是飛特音速說話的速度比較快，你是否跟得上呢？你也可以和其他精靈互動看看喔！\n
+                    """
+                    chatbot_open_ai_name = gr.State("chatbot_open_ai")
+                    gr.Image(value=chatbot_avatar_url, height=100, width=100, show_label=False, show_download_button=False)
+                    chatbot_open_ai_select_btn = gr.Button("👆選擇【飛特精靈】", elem_id="chatbot_btn", visible=True, variant="primary")
+                    gr.Markdown(value=chatbot_description, visible=True)
+                with gr.Column(scale=1, variant="panel"):
+                    streaming_chatbot_avatar_url = "https://storage.googleapis.com/wpassets.junyiacademy.org/1/2020/11/1-%E6%98%9F%E7%A9%BA%E9%A0%AD%E8%B2%BC-%E5%A4%AA%E7%A9%BA%E7%8B%90%E7%8B%B8%E8%B2%93-150x150.png"
+                    streaming_chatbot_description = """Hi，我是【飛特音速】， \n
+                    說話比較快，但有什麼問題都可以問我喔！ \n
+                    🚀 我沒有預設問題、也沒有語音輸入，適合快問快答，一起練習問出好問題吧 \n
+                    🔠 擅長用文字表達的你，可以用鍵盤輸入你的問題，我會盡力回答你的問題喔\n
+                    💤 我還在成長，體力有限，每一次學習只能回答十個問題，請讓我休息一下再問問題喔～
+                    """
+                    chatbot_open_ai_streaming_name = gr.State("chatbot_open_ai_streaming")
+                    gr.Image(value=streaming_chatbot_avatar_url, height=100, width=100, show_label=False, show_download_button=False)
+                    chatbot_open_ai_streaming_select_btn = gr.Button("👆選擇【飛特音速】", elem_id="streaming_chatbot_btn", visible=True, variant="primary")
+                    gr.Markdown(value=streaming_chatbot_description, visible=True)
+                with gr.Column(scale=1, variant="panel"):
+                    jutor_chatbot_avatar_url = "https://storage.googleapis.com/wpassets.junyiacademy.org/1/2019/11/%E5%9B%9B%E6%A0%BC%E6%95%85%E4%BA%8B-04.jpg"
+                    jutor_chatbot_description = """Hi，我們是【梨梨、麥麥、狐狸貓】，\n
+                    也可以陪你一起學習本次的內容，有什麼問題都可以問我喔！\n
+                    🤔 如果你不知道怎麼發問，可以點擊左下方的問題一、問題二、問題三，我會幫你生成問題！\n
+                    🗣️ 也可以點擊右下方用語音輸入，我會幫你轉換成文字，厲害吧！\n
+                    🔠 或是直接鍵盤輸入你的問題，我會盡力回答你的問題喔！\n
+                    💤 精靈們體力都有限，每一次學習只能回答十個問題，請讓我休息一下再問問題喔！\n
+                    """
+                    chatbot_jutor_name = gr.State("chatbot_jutor")
+                    gr.Image(value=jutor_chatbot_avatar_url, height=100, width=100, show_label=False, show_download_button=False)
+                    chatbot_jutor_select_btn = gr.Button("👆選擇【梨梨、麥麥、狐狸貓】", elem_id="jutor_chatbot_btn", visible=True, variant="primary")
+                    gr.Markdown(value=jutor_chatbot_description, visible=True)
+                    
+        with gr.Row("飛特精靈") as chatbot_open_ai:
+            with gr.Column():
+                user_avatar = "https://em-content.zobj.net/source/google/263/flushed-face_1f633.png"
+                bot_avatar = "https://junyitopicimg.s3.amazonaws.com/s4byy--icon.jpe?v=20200513013523726"
                 latex_delimiters = [{"left": "$", "right": "$", "display": False}]
-                chatbot = gr.Chatbot(avatar_images=[bot_avatar, user_avatar], label="OPEN AI", show_share_button=False, likeable=True, show_label=False, latex_delimiters=latex_delimiters)
-                thread_id = gr.Textbox(label="thread_id", visible=False)
-                socratic_mode_btn = gr.Checkbox(label="蘇格拉底家教助理模式", value=True, visible=False)
+                chatbot_greeting = [[
+                    None,
+                    """Hi，我是你的AI學伴【飛特精靈】，我可以陪你一起學習本次的內容，有什麼問題都可以問我喔！
+                    🤔 如果你不知道怎麼發問，可以點擊左下方的問題一、問題二、問題三，我會幫你生成問題！
+                    🗣️ 也可以點擊右下方用語音輸入，我會幫你轉換成文字，厲害吧！
+                    🔠 或是直接鍵盤輸入你的問題，我會盡力回答你的問題喔！
+                    💤 但我還在成長，體力有限，每一次學習只能回答十個問題，請讓我休息一下再問問題喔！
+                    🦄 如果達到上限，或是��到精靈很累，請問問其他朋友，像是飛特音速說話的速度比較快，你是否跟得上呢？你也可以和其他精靈互動看看喔！
+                    """,
+                ]]
+                with gr.Row():
+                    chatbot = gr.Chatbot(avatar_images=[user_avatar, bot_avatar], label="OPEN AI", show_share_button=False, likeable=True, show_label=False, latex_delimiters=latex_delimiters,value=chatbot_greeting)
+                with gr.Row():
+                    thread_id = gr.Textbox(label="thread_id", visible=False)
+                    socratic_mode_btn = gr.Checkbox(label="蘇格拉底家教助理模式", value=True, visible=False)
                 with gr.Row():
                     with gr.Accordion("你也有類似的問題想問嗎？", open=False) as ask_questions_accordion:
                         btn_1 = gr.Button("問題一")
@@ -2153,12 +2284,19 @@ with gr.Blocks(theme=gr.themes.Base(primary_hue=gr.themes.colors.orange, seconda
                         btn_3 = gr.Button("問題一")
                         gr.Markdown("### 重新生成問題")
                         btn_create_question = gr.Button("生成其他問題", variant="primary")
-                    openai_chatbot_audio_input = gr.Audio(sources=["microphone"], type="filepath", max_length=60)
+                    openai_chatbot_audio_input = gr.Audio(sources=["microphone"], type="filepath", max_length=60, label="語音輸入")
                 with gr.Row():
                     msg = gr.Textbox(label="訊息",scale=3)
                     send_button = gr.Button("送出", variant="primary", scale=1)
-            with gr.Tab("飛特音速"):
-                additional_inputs = [password, streaming_chat_thread_id_state, trascript_state, key_moments_state, content_subject_state, content_grade_state]
+        with gr.Row("飛特音速") as chatbot_open_ai_streaming:
+            with gr.Column():
+                streaming_chat_greeting = """
+                Hi，我是【飛特音速】，說話比較快，但有什麼問題都可以問我喔！ \n
+                    🚀 我沒有預設問題、也沒有語音輸入，適合快問快答的你 \n
+                    🔠 鍵盤輸入你的問題，我會盡力回答你的問題喔！\n
+                    💤 我還在成長，體力有限，每一次學習只能回答十個問題，請讓我休息一下再問問題喔！
+                    """
+                additional_inputs = [password, user_data, streaming_chat_thread_id_state, trascript_state, key_moments_state, content_subject_state, content_grade_state]
                 streaming_chat = gr.ChatInterface(
                     fn=streaming_chat_with_open_ai,
                     additional_inputs=additional_inputs,
@@ -2166,41 +2304,41 @@ with gr.Blocks(theme=gr.themes.Base(primary_hue=gr.themes.colors.orange, seconda
                     retry_btn=None,
                     undo_btn="⏪ 上一步",
                     clear_btn="🗑️ 清除全部",
-                    stop_btn="🛑 停止",
+                    stop_btn=None,
+                    description=streaming_chat_greeting
                 )
-            with gr.Tab("其他精靈"):
-                ai_name = gr.Dropdown(label="選擇 AI 助理", choices=["jutor", "claude3", "groq"], value="jutor")
-                ai_chatbot = gr.Chatbot(avatar_images=[bot_avatar, user_avatar], label="ai_chatbot", show_share_button=False, likeable=True, show_label=False, latex_delimiters=latex_delimiters)
+        with gr.Row("其他精靈") as chatbot_jutor:   
+            with gr.Column():
+                ai_chatbot_greeting = [[
+                    None,
+                    """Hi，我是飛特精靈的朋友們【梨梨、麥麥、狐狸貓】，也可以陪你一起學習本次的內容，有什麼問題都可以問我喔！
+                    🤔 如果你不知道怎麼發問，可以點擊左下方的問題一、問題二、問題三，我會幫你生成問題！
+                    🗣️ 也可以點擊右下方用語音輸入，我會幫你轉換成文字，厲害吧！
+                    🔠 或是直接鍵盤輸入你的問題，我會盡力回答你的問題喔！
+                    💤 精靈們體力都有限，每一次學習只能回答十個問題，請讓我休息一下再問問題喔！
+                    """,
+                ]]
+                ai_chatbot_bot_avatar = "https://storage.googleapis.com/wpassets.junyiacademy.org/1/2019/11/%E5%9B%9B%E6%A0%BC%E6%95%85%E4%BA%8B-04.jpg"
+                ai_name = gr.Dropdown(label="選擇 AI 助理", choices=[("梨梨","jutor"), ("麥麥","claude3"), ("狐狸貓","groq")], value="jutor")
+                ai_chatbot = gr.Chatbot(avatar_images=[user_avatar, ai_chatbot_bot_avatar], label="ai_chatbot", show_share_button=False, likeable=True, show_label=False, latex_delimiters=latex_delimiters, value=ai_chatbot_greeting)
                 ai_chatbot_socratic_mode_btn = gr.Checkbox(label="蘇格拉底家教助理模式", value=True, visible=False)
                 with gr.Row():
                     with gr.Accordion("你也有類似的問題想問嗎？", open=False) as ask_questions_accordion_2:
                         ai_chatbot_question_1 = gr.Button("問題一")
                         ai_chatbot_question_2 = gr.Button("問題一")
                         ai_chatbot_question_3 = gr.Button("問題一")
-                    ai_chatbot_audio_input = gr.Audio(sources=["microphone"], type="filepath", max_length=60)
+                    ai_chatbot_audio_input = gr.Audio(sources=["microphone"], type="filepath", max_length=60, label="語音輸入")
                 with gr.Row():
                     ai_msg = gr.Textbox(label="訊息輸入",scale=3)
                     ai_send_button = gr.Button("送出", variant="primary",scale=1)              
     with gr.Tab("文章模式"):
-        with gr.Row() as reading_passage_admin:
-            reading_passage_kind = gr.Textbox(value="reading_passage", show_label=False)
-            reading_passage_edit_button = gr.Button("編輯", size="sm", variant="primary")
-            reading_passage_update_button = gr.Button("更新", size="sm", variant="primary")
-            reading_passage_delete_button = gr.Button("刪除", size="sm", variant="primary")
-            reading_passage_create_button = gr.Button("建立", size="sm", variant="primary")
         with gr.Row():
-            reading_passage = gr.Textbox(label="Reading Passage", lines=40, show_label=False)
+            reading_passage = gr.Markdown(show_label=False, latex_delimiters = [{"left": "$", "right": "$", "display": False}])
             reading_passage_speak_button = gr.Button("Speak", visible=False)
             reading_passage_audio_output = gr.Audio(label="Audio Output", visible=False) 
     with gr.Tab("重點摘要"):
-        with gr.Row() as summary_admmin:
-            summary_kind = gr.Textbox(value="summary", show_label=False)
-            summary_edit_button = gr.Button("編輯", size="sm", variant="primary")
-            summary_update_button = gr.Button("更新", size="sm", variant="primary")
-            summary_delete_button = gr.Button("刪除", size="sm", variant="primary")
-            summary_create_button = gr.Button("建立", size="sm", variant="primary")
         with gr.Row():
-            df_summarise = gr.Textbox(container=True, show_copy_button=True, lines=40, show_label=False)
+            df_summarise = gr.Markdown(show_label=False, latex_delimiters = [{"left": "$", "right": "$", "display": False}])
     with gr.Tab("關鍵時刻"):
         with gr.Row():
             key_moments_html = gr.HTML(value="")
@@ -2221,16 +2359,16 @@ with gr.Blocks(theme=gr.themes.Base(primary_hue=gr.themes.colors.orange, seconda
                             worksheet_exam_result_fine_tune_prompt = gr.Textbox(label="根據結果，輸入你想更改的想法")
                             worksheet_exam_result_fine_tune_btn = gr.Button("微調結果", variant="primary")
                             worksheet_exam_result_retrun_original = gr.Button("返回原始結果")
-                        with gr.Accordion("prompt", open=False):
+                        with gr.Accordion("prompt", open=False) as worksheet_accordion:
                             worksheet_prompt = gr.Textbox(label="worksheet_prompt", show_copy_button=True, lines=40)
                     with gr.Column(scale=2):
                         # 生成對應不同模式的結果
                         worksheet_exam_result_prompt = gr.Textbox(visible=False)
                         worksheet_exam_result_original = gr.Textbox(visible=False)
-                        worksheet_exam_result = gr.Textbox(label="初次生成結果", show_copy_button=True, interactive=True, lines=40)
+                        # worksheet_exam_result = gr.Textbox(label="初次生成結果", show_copy_button=True, interactive=True, lines=40)
+                        worksheet_exam_result = gr.Markdown(label="初次生成結果", latex_delimiters = [{"left": "$", "right": "$", "display": False}])
                         worksheet_download_exam_result_button = gr.Button("轉成 word，完成後請點擊右下角 download 按鈕", variant="primary")
                         worksheet_exam_result_word_link = gr.File(label="Download Word")
-
             with gr.Tab("課程計畫"):
                 with gr.Row():
                     with gr.Column(scale=1):
@@ -2242,17 +2380,16 @@ with gr.Blocks(theme=gr.themes.Base(primary_hue=gr.themes.colors.orange, seconda
                             lesson_plan_exam_result_fine_tune_prompt = gr.Textbox(label="根據結果，輸入你想更改的想法")
                             lesson_plan_exam_result_fine_tune_btn = gr.Button("微調結果", variant="primary")
                             lesson_plan_exam_result_retrun_original = gr.Button("返回原始結果")
-                        with gr.Accordion("prompt", open=False):
+                        with gr.Accordion("prompt", open=False) as lesson_plan_accordion:
                             lesson_plan_prompt = gr.Textbox(label="worksheet_prompt", show_copy_button=True, lines=40)
                     with gr.Column(scale=2):
                         # 生成對應不同模式的結果
                         lesson_plan_exam_result_prompt = gr.Textbox(visible=False)
                         lesson_plan_exam_result_original = gr.Textbox(visible=False)
-                        lesson_plan_exam_result = gr.Textbox(label="初次生成結果", show_copy_button=True, interactive=True, lines=40)
+                        lesson_plan_exam_result = gr.Markdown(label="初次生成結果", latex_delimiters = [{"left": "$", "right": "$", "display": False}])
                         
                         lesson_plan_download_exam_result_button = gr.Button("轉成 word，完成後請點擊右下角 download 按鈕", variant="primary")
                         lesson_plan_exam_result_word_link = gr.File(label="Download Word")
-            
             with gr.Tab("出場券"):
                 with gr.Row():
                     with gr.Column(scale=1):
@@ -2264,13 +2401,13 @@ with gr.Blocks(theme=gr.themes.Base(primary_hue=gr.themes.colors.orange, seconda
                             exit_ticket_exam_result_fine_tune_prompt = gr.Textbox(label="根據結果，輸入你想更改的想法")
                             exit_ticket_exam_result_fine_tune_btn = gr.Button("微調結果", variant="primary")
                             exit_ticket_exam_result_retrun_original = gr.Button("返回原始結果")
-                        with gr.Accordion("prompt", open=False):
+                        with gr.Accordion("prompt", open=False) as exit_ticket_accordion:
                             exit_ticket_prompt = gr.Textbox(label="worksheet_prompt", show_copy_button=True, lines=40)
                     with gr.Column(scale=2):
                         # 生成對應不同模式的結果
                         exit_ticket_exam_result_prompt = gr.Textbox(visible=False)
                         exit_ticket_exam_result_original = gr.Textbox(visible=False)
-                        exit_ticket_exam_result = gr.Textbox(label="初次生成結果", show_copy_button=True, interactive=True, lines=40)
+                        exit_ticket_exam_result = gr.Markdown(label="初次生成結果", latex_delimiters = [{"left": "$", "right": "$", "display": False}])
                         
                         exit_ticket_download_exam_result_button = gr.Button("轉成 word，完成後請點擊右下角 download 按鈕", variant="primary")
                         exit_ticket_exam_result_word_link = gr.File(label="Download Word")
@@ -2294,17 +2431,39 @@ with gr.Blocks(theme=gr.themes.Base(primary_hue=gr.themes.colors.orange, seconda
         with gr.Tab("逐字稿本文"):
             with gr.Row() as transcript_admmin:
                 transcript_kind = gr.Textbox(value="transcript", show_label=False)
+                transcript_get_button = gr.Button("取得", size="sm", variant="primary")
                 transcript_edit_button = gr.Button("編輯", size="sm", variant="primary")
-                transcript_update_button = gr.Button("更新", size="sm", variant="primary")
+                transcript_update_button = gr.Button("儲存", size="sm", variant="primary")
                 transcript_delete_button = gr.Button("刪除", size="sm", variant="primary")
                 transcript_create_button = gr.Button("建立", size="sm", variant="primary")
             with gr.Row():
                 df_string_output = gr.Textbox(lines=40, label="Data Text", interactive=False, show_copy_button=True)
+        with gr.Tab("文章本文"):
+            with gr.Row() as reading_passage_admin:
+                reading_passage_kind = gr.Textbox(value="reading_passage", show_label=False)
+                reading_passage_get_button = gr.Button("取得", size="sm", variant="primary")
+                reading_passage_edit_button = gr.Button("編輯", size="sm", variant="primary")
+                reading_passage_update_button = gr.Button("更新", size="sm", variant="primary")
+                reading_passage_delete_button = gr.Button("刪除", size="sm", variant="primary")
+                reading_passage_create_button = gr.Button("建立", size="sm", variant="primary")
+            with gr.Row():
+                reading_passage_text = gr.Textbox(label="reading_passage", lines=40, interactive=False, show_copy_button=True)
+        with gr.Tab("重點摘要本文"):
+            with gr.Row() as summary_admmin:
+                summary_kind = gr.Textbox(value="summary", show_label=False)
+                summary_get_button = gr.Button("取得", size="sm", variant="primary")
+                summary_edit_button = gr.Button("編輯", size="sm", variant="primary")
+                summary_update_button = gr.Button("更新", size="sm", variant="primary")
+                summary_delete_button = gr.Button("刪除", size="sm", variant="primary")
+                summary_create_button = gr.Button("建立", size="sm", variant="primary")
+            with gr.Row():
+                summary_text = gr.Textbox(label="Summary", lines=40, interactive=False, show_copy_button=True)
         with gr.Tab("關鍵時刻本文"):
             with gr.Row() as key_moments_admin:
                 key_moments_kind = gr.Textbox(value="key_moments", show_label=False)
+                key_moments_get_button = gr.Button("取得", size="sm", variant="primary")
                 key_moments_edit_button = gr.Button("編輯", size="sm", variant="primary")
-                key_moments_update_button = gr.Button("更新", size="sm", variant="primary")
+                key_moments_update_button = gr.Button("儲存", size="sm", variant="primary")
                 key_moments_delete_button = gr.Button("刪除", size="sm", variant="primary")
                 key_moments_create_button = gr.Button("建立", size="sm", variant="primary")
             with gr.Row():
@@ -2312,8 +2471,9 @@ with gr.Blocks(theme=gr.themes.Base(primary_hue=gr.themes.colors.orange, seconda
         with gr.Tab("問題本文"):
             with gr.Row() as question_list_admin:
                 questions_kind = gr.Textbox(value="questions", show_label=False)
+                questions_get_button = gr.Button("取得", size="sm", variant="primary")
                 questions_edit_button = gr.Button("編輯", size="sm", variant="primary")
-                questions_update_button = gr.Button("更新", size="sm", variant="primary")
+                questions_update_button = gr.Button("儲存", size="sm", variant="primary")
                 questions_delete_button = gr.Button("刪除", size="sm", variant="primary")
                 questions_create_button = gr.Button("建立", size="sm", variant="primary")
             with gr.Row():
@@ -2337,11 +2497,29 @@ with gr.Blocks(theme=gr.themes.Base(primary_hue=gr.themes.colors.orange, seconda
             mind_map_html = gr.HTML()
        
     # --- Event ---
+    # CHATBOT SELECT
+    chatbot_open_ai_select_btn.click(
+        chatbot_select,
+        inputs=[chatbot_open_ai_name],
+        outputs=[chatbot_select_accordion, chatbot_open_ai, chatbot_open_ai_streaming, chatbot_jutor]
+    )
+    chatbot_open_ai_streaming_select_btn.click(
+        chatbot_select,
+        inputs=[chatbot_open_ai_streaming_name],
+        outputs=[chatbot_select_accordion, chatbot_open_ai, chatbot_open_ai_streaming, chatbot_jutor]
+    )
+    chatbot_jutor_select_btn.click(
+        chatbot_select,
+        inputs=[chatbot_jutor_name],
+        outputs=[chatbot_select_accordion, chatbot_open_ai, chatbot_open_ai_streaming, chatbot_jutor]
+    )
+
     # OPENAI ASSISTANT CHATBOT 模式
     send_button.click(
         chat_with_opan_ai_assistant,
-        inputs=[password, video_id, thread_id, trascript_state, key_moments, msg, chatbot, content_subject, content_grade, socratic_mode_btn],
-        outputs=[msg, chatbot, thread_id]
+        inputs=[password, video_id, user_data, thread_id, trascript_state, key_moments, msg, chatbot, content_subject, content_grade, socratic_mode_btn],
+        outputs=[msg, chatbot, thread_id],
+        scroll_to_output=True
     )
     openai_chatbot_audio_input.change(
         process_open_ai_audio_to_chatbot,
@@ -2349,23 +2527,26 @@ with gr.Blocks(theme=gr.themes.Base(primary_hue=gr.themes.colors.orange, seconda
         outputs=[msg]
     )
     # OPENAI ASSISTANT CHATBOT 連接按鈕點擊事件
-    btn_1_chat_with_opan_ai_assistant_input =[password, video_id, thread_id, trascript_state, key_moments, btn_1, chatbot, content_subject, content_grade, ai_chatbot_socratic_mode_btn]
-    btn_2_chat_with_opan_ai_assistant_input =[password, video_id, thread_id, trascript_state, key_moments, btn_2, chatbot, content_subject, content_grade, ai_chatbot_socratic_mode_btn]
-    btn_3_chat_with_opan_ai_assistant_input =[password, video_id, thread_id, trascript_state, key_moments, btn_3, chatbot, content_subject, content_grade, ai_chatbot_socratic_mode_btn]
+    btn_1_chat_with_opan_ai_assistant_input =[password, video_id, user_data, thread_id, trascript_state, key_moments, btn_1, chatbot, content_subject, content_grade, ai_chatbot_socratic_mode_btn]
+    btn_2_chat_with_opan_ai_assistant_input =[password, video_id, user_data, thread_id, trascript_state, key_moments, btn_2, chatbot, content_subject, content_grade, ai_chatbot_socratic_mode_btn]
+    btn_3_chat_with_opan_ai_assistant_input =[password, video_id, user_data, thread_id, trascript_state, key_moments, btn_3, chatbot, content_subject, content_grade, ai_chatbot_socratic_mode_btn]
     btn_1.click(
         chat_with_opan_ai_assistant,
         inputs=btn_1_chat_with_opan_ai_assistant_input, 
-        outputs=[msg, chatbot, thread_id]
+        outputs=[msg, chatbot, thread_id],
+        scroll_to_output=True
     )
     btn_2.click(
         chat_with_opan_ai_assistant,
         inputs=btn_2_chat_with_opan_ai_assistant_input, 
-        outputs=[msg, chatbot, thread_id]
+        outputs=[msg, chatbot, thread_id],
+        scroll_to_output=True
     )
     btn_3.click(
         chat_with_opan_ai_assistant,
         inputs=btn_3_chat_with_opan_ai_assistant_input, 
-        outputs=[msg, chatbot, thread_id]
+        outputs=[msg, chatbot, thread_id],
+        scroll_to_output=True
     )
     btn_create_question.click(
         change_questions, 
@@ -2373,30 +2554,34 @@ with gr.Blocks(theme=gr.themes.Base(primary_hue=gr.themes.colors.orange, seconda
         outputs = [btn_1, btn_2, btn_3]
     )
 
-    # ai_chatbot 模式
+    # 其他精靈 ai_chatbot 模式
     ai_send_button.click(
         chat_with_ai,
-        inputs=[ai_name, password, video_id, trascript_state, key_moments, ai_msg, ai_chatbot, content_subject, content_grade, ai_chatbot_socratic_mode_btn],
-        outputs=[ai_msg, ai_chatbot]
+        inputs=[ai_name, password, video_id, user_data, trascript_state, key_moments, ai_msg, ai_chatbot, content_subject, content_grade, ai_chatbot_socratic_mode_btn],
+        outputs=[ai_msg, ai_chatbot],
+        scroll_to_output=True
     )
-    # ai_chatbot 连接按钮点击事件
-    ai_chatbot_question_1_chat_with_ai_input =[ai_name, password, video_id, trascript_state, key_moments, ai_chatbot_question_1, ai_chatbot, content_subject, content_grade, ai_chatbot_socratic_mode_btn]
-    ai_chatbot_question_2_chat_with_ai_input =[ai_name, password, video_id, trascript_state, key_moments, ai_chatbot_question_2, ai_chatbot, content_subject, content_grade, ai_chatbot_socratic_mode_btn]
-    ai_chatbot_question_3_chat_with_ai_input =[ai_name, password, video_id, trascript_state, key_moments, ai_chatbot_question_3, ai_chatbot, content_subject, content_grade, ai_chatbot_socratic_mode_btn]
+    # 其他精靈 ai_chatbot 连接按钮点击事件
+    ai_chatbot_question_1_chat_with_ai_input =[ai_name, password, video_id, user_data, trascript_state, key_moments, ai_chatbot_question_1, ai_chatbot, content_subject, content_grade, ai_chatbot_socratic_mode_btn]
+    ai_chatbot_question_2_chat_with_ai_input =[ai_name, password, video_id, user_data, trascript_state, key_moments, ai_chatbot_question_2, ai_chatbot, content_subject, content_grade, ai_chatbot_socratic_mode_btn]
+    ai_chatbot_question_3_chat_with_ai_input =[ai_name, password, video_id, user_data, trascript_state, key_moments, ai_chatbot_question_3, ai_chatbot, content_subject, content_grade, ai_chatbot_socratic_mode_btn]
     ai_chatbot_question_1.click(
         chat_with_ai,
         inputs=ai_chatbot_question_1_chat_with_ai_input,
-        outputs=[ai_msg, ai_chatbot]
+        outputs=[ai_msg, ai_chatbot],
+        scroll_to_output=True
     )
     ai_chatbot_question_2.click(
         chat_with_ai,
         inputs=ai_chatbot_question_2_chat_with_ai_input,
-        outputs=[ai_msg, ai_chatbot]
+        outputs=[ai_msg, ai_chatbot],
+        scroll_to_output=True
     )
     ai_chatbot_question_3.click(
         chat_with_ai,
         inputs=ai_chatbot_question_3_chat_with_ai_input,
-        outputs=[ai_msg, ai_chatbot]
+        outputs=[ai_msg, ai_chatbot],
+        scroll_to_output=True
     )
 
     # file_upload.change(process_file, inputs=file_upload, outputs=df_string_output)
@@ -2411,6 +2596,7 @@ with gr.Blocks(theme=gr.themes.Base(primary_hue=gr.themes.colors.orange, seconda
         btn_2, 
         btn_3, 
         df_string_output, 
+        summary_text,
         df_summarise,
         key_moments,
         key_moments_html,
@@ -2420,6 +2606,7 @@ with gr.Blocks(theme=gr.themes.Base(primary_hue=gr.themes.colors.orange, seconda
         simple_html_content, 
         slide_image, 
         slide_text,
+        reading_passage_text,
         reading_passage,
         content_subject,
         content_grade,
@@ -2469,50 +2656,65 @@ with gr.Blocks(theme=gr.themes.Base(primary_hue=gr.themes.colors.orange, seconda
     # web_link.change(process_web_link, inputs=web_link, outputs=[btn_1, btn_2, btn_3, df_summarise, df_string_output])
 
     # reading_passage event
+    reading_passage_get_button.click(
+        get_LLM_content,
+        inputs=[video_id, reading_passage_kind],
+        outputs=[reading_passage_text]
+    )
     reading_passage_create_button.click(
         create_LLM_content,
         inputs=[video_id, df_string_output, reading_passage_kind],
-        outputs=[reading_passage]
+        outputs=[reading_passage_text]
     )
     reading_passage_delete_button.click(
         delete_LLM_content,
         inputs=[video_id, reading_passage_kind],
-        outputs=[reading_passage]
+        outputs=[reading_passage_text]
     )
     reading_passage_edit_button.click(
         enable_edit_mode,
         inputs=[],
-        outputs=[reading_passage]
+        outputs=[reading_passage_text]
     )
     reading_passage_update_button.click(
         update_LLM_content,
-        inputs=[video_id, reading_passage, reading_passage_kind],
-        outputs=[reading_passage]
+        inputs=[video_id, reading_passage_text, reading_passage_kind],
+        outputs=[reading_passage_text]
     )
 
     # summary event
+    summary_get_button.click(
+        get_LLM_content,
+        inputs=[video_id, summary_kind],
+        outputs=[summary_text]
+    )
     summary_create_button.click(
         create_LLM_content,
         inputs=[video_id, df_string_output, summary_kind],
-        outputs=[df_summarise]
+        outputs=[summary_text]
     )
     summary_delete_button.click(
         delete_LLM_content,
         inputs=[video_id, summary_kind],
-        outputs=[df_summarise]
+        outputs=[summary_text]
     )
     summary_edit_button.click(
         enable_edit_mode,
         inputs=[],
-        outputs=[df_summarise]
+        outputs=[summary_text]
     )
     summary_update_button.click(
         update_LLM_content,
-        inputs=[video_id, df_summarise, summary_kind],
-        outputs=[df_summarise]
+        inputs=[video_id, summary_text, summary_kind],
+        outputs=[summary_text]
     )
 
     # transcript event
+    transcript_get_button.click(
+        get_LLM_content,
+        inputs=[video_id, transcript_kind],
+        outputs=[df_string_output]
+    )
     transcript_create_button.click(
         create_LLM_content,
         inputs=[video_id, df_string_output, transcript_kind],
@@ -2535,6 +2737,11 @@ with gr.Blocks(theme=gr.themes.Base(primary_hue=gr.themes.colors.orange, seconda
     )
     
     # key_moments event
+    key_moments_get_button.click(
+        get_LLM_content,
+        inputs=[video_id, key_moments_kind],
+        outputs=[key_moments]
+    )
     key_moments_create_button.click(
         create_LLM_content,
         inputs=[video_id, df_string_output, key_moments_kind],
@@ -2557,6 +2764,11 @@ with gr.Blocks(theme=gr.themes.Base(primary_hue=gr.themes.colors.orange, seconda
     )
     
     # question_list event
+    questions_get_button.click(
+        get_LLM_content,
+        inputs=[video_id, questions_kind],
+        outputs=[questions_json]
+    )
     questions_create_button.click(
         create_LLM_content,
         inputs=[video_id, df_string_output, questions_kind],
@@ -2643,10 +2855,24 @@ with gr.Blocks(theme=gr.themes.Base(primary_hue=gr.themes.colors.orange, seconda
     )
 
     # init_params
+    init_outputs = [
+        admin, 
+        reading_passage_admin, 
+        summary_admmin, 
+        see_details,
+        worksheet_accordion, 
+        lesson_plan_accordion, 
+        exit_ticket_accordion,
+        password, 
+        youtube_link,
+        chatbot_open_ai,
+        chatbot_open_ai_streaming,
+        chatbot_jutor
+    ]
     demo.load(
         init_params, 
         inputs =[youtube_link],
-        outputs = [admin, reading_passage_admin, summary_admmin, see_details, password , youtube_link]
+        outputs = init_outputs
     )
 
 demo.launch(allowed_paths=["videos"])

chatbot.py

@@ -82,7 +82,7 @@ class Chatbot:
             "Content-Type": "application/json",
             "x-api-key": self.jutor_chat_key,
         }
-        model = "gpt-4-1106-preview"
+        model = "gpt-4-turbo"
         # model = "gpt-3.5-turbo-0125"
         data = {
             "data": {

educational_material.py

@@ -30,14 +30,13 @@ class EducationalMaterial:
         self.level = level
         self.specific_feature = specific_feature
         self.content_type = content_type  # 'worksheet' or 'lesson_plan'
-        self.system_content = "你是一個擅長資料分析跟影片教學備課的老師，請精讀資料文本，自行判斷資料的種類，使用 zh-TW"
+        self.system_content = "你是一個擅長資料分析跟影片教學備課的老師，請精讀資料文本，自行判斷資料的種類，使用 zh-TW，遇到數學符號或是敘述請用 Latex 語法($...$)，例如：$x^2$。"
 
     def _prepare_context(self, context):
         context_json = json.loads(context)
+        processed_context = ""
         for entry in context_json:
-            entry.pop('embed_url', None)
-            entry.pop('screenshot_path', None)
-        processed_context = json.dumps(context_json, ensure_ascii=False, indent=2)
+            processed_context += entry.get('text', '') + "\n"
         return processed_context
 
     def generate_content_prompt(self):
@@ -50,7 +49,8 @@ class EducationalMaterial:
 
     def _generate_worksheet_prompt(self):
         bloom_worksheet_prompt = """
-        你是個專業的教師，熟悉布魯姆(Benjamin Bloom, 1964) 的認知理論。布魯姆認為人類的能力，大致可分為三個領域(domains)，即認知領域(cognitive domain)、情意領域(affective domain)、技能領域 (psychomotor domain)。
+        你是個專業的教師，，遇到數學符號或是敘述請用 Latex 語法($...$)，例如：$x^2$。
+        熟悉布魯姆(Benjamin Bloom, 1964) 的認知理論。布魯姆認為人類的能力，大致可分為三個領域(domains)，即認知領域(cognitive domain)、情意領域(affective domain)、技能領域 (psychomotor domain)。
         
         【認知領域】涉及知能及其運作，著重心智、學習以及問題解決的工作。認知目標從簡單的認識或記憶能力到複雜的評鑑能力。大部分的教育目標都屬於這個領域。認知領域的目標分為六個層次，每個層次代表不同的心智功能。
         - 📖 知識：在認知目標中知識是最低層次的能力，包括名詞、事實、規則和原理原則等的認識和記憶。用來表示此種能力的行為動詞有：指出、寫出、界定、說明、舉例、命名、認明等。例：能在地圖上指出長江流經的省分。
@@ -74,12 +74,12 @@ class EducationalMaterial:
         🌐【主題】：認識公里
 
         🎓【對象】 
-        科目： 數學
-        年級： 三年級
-        難度： 基礎
+        - 科目： 數學
+        - 年級： 三年級
+        - 難度： 基礎
 
         🏞️【情境描述】
-        狐狸貓和家人出遊，過程中認識測量較長距離的單位「公里」。
+        - 狐狸貓和家人出遊，過程中認識測量較長距離的單位「公里」。
 
         🔑【影片重點】
         - 公里是用來測量長距離的單位，通常用於測量很遠的距離。
@@ -101,7 +101,8 @@ class EducationalMaterial:
         """
 
         Polya_worksheet_prompt = """
-        你是個專業的教師，熟悉 George Polya(1945) 的數學問題解決策略。
+        你是個專業的教師，遇到數學符號或是敘述請用 Latex 語法($...$)，例如：$x^2$。
+        熟悉 George Polya(1945) 的數學問題解決策略。
         Polya提出了一個四步驟的數學問題解決策略，在他影響深遠的經典著作 How to solve it《如何解題》中指出解難過程可分為四個階段：
         (1) 理解問題 (understanding the problem)
         (2) 設計解題策略 (devising a plan)
@@ -115,9 +116,9 @@ class EducationalMaterial:
         🌐 主題：【概念】認識公里
 
         🎓【對象】
-        科目： 數學
-        年級： 三年級
-        難度： 基礎
+        - 科目： 數學
+        - 年級： 三年級
+        - 難度： 基礎
 
         🏞️【情境描述】
         狐狸貓和家人出遊，過程中認識測量較長距離的單位「公里」。
@@ -148,7 +149,8 @@ class EducationalMaterial:
         
         # CRA教學法
         cra_worksheet_prompt = """
-        你是個專業的教師，熟悉CRA教學法，CRA教學法是一種教學策略，
+        你是個專業的教師，，遇到數學符號或是敘述請用 Latex 語法($...$)，例如：$x^2$。
+        熟悉CRA教學法，CRA教學法是一種教學策略，
         CRA正是一種用來促進學生學習和記憶數學的三步教學法，它闡明瞭用這種方式進行教學的具體步驟。
         CRA的三個步驟互相依賴，運用CRA能建立起一種概念結構，從而形成知識的意義關聯。
         CRA策略的第一個階段， 即實例(C)階段，是一個“做”的階段。在這一階段，教師用加工材料建模，這些材料包括彩色圓片、立方體、十進位積木、六形六色積木，以及分數積木，等等。在使用這些材料時，必須考���到兒童的視覺、觸覺及動感經驗。
@@ -160,9 +162,9 @@ class EducationalMaterial:
         🌐 主題：【概念】認識公里
 
         🎓【對象】
-        科目： 數學
-        年級： 三年級
-        難度： 基礎
+        - 科目： 數學
+        - 年級： 三年級
+        - 難度： 基礎
 
         【實例(C)階段】
         1. 用彩色圓片來解釋什麼是分數？