update

app.py

@@ -381,7 +381,7 @@ def extract_youtube_id(url):
         return None
 
 def get_transcript_by_yt_api(video_id):
-    languages = ['zh-TW', 'zh-Hant', 'zh', 'en']  # 優先順序列表
+    languages = ['zh-TW', 'zh-Hant', 'zh', 'en-US']  # 優先順序列表
     for language in languages:
         try:
             transcript = YouTubeTranscriptApi.get_transcript(video_id, languages=[language])
@@ -582,8 +582,8 @@ def process_youtube_link(password, link):
 
     # 基于逐字稿生成其他所需的输出
     source = "gcs"
-    questions = get_questions(video_id, formatted_simple_transcript, source)
-    questions_json = json.dumps(questions, ensure_ascii=False, indent=2)
+    questions_answers = get_questions_answers(video_id, formatted_simple_transcript, source)
+    questions_answers_json = json.dumps(questions_answers, 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"]
@@ -608,10 +608,7 @@ def process_youtube_link(password, link):
 
     # 确保返回与 UI 组件预期匹配的输出
     return video_id, \
-        questions_json, \
-        questions[0] if len(questions) > 0 else "", \
-        questions[1] if len(questions) > 1 else "", \
-        questions[2] if len(questions) > 2 else "", \
+        questions_answers_json, \
         original_transcript, \
         summary_text, \
         summary, \
@@ -888,7 +885,8 @@ def get_video_id_summary(video_id, df_string, source):
         # 检查 summary_file 是否存在
         is_summary_file_exists = GCS_SERVICE.check_file_exists(bucket_name, summary_file_blob_name)
         if not is_summary_file_exists:
-            summary = generate_summarise(df_string)
+            meta_data = get_meta_data(video_id)
+            summary = generate_summarise(df_string, meta_data)
             summary_json = {"summary": str(summary)}
             summary_text = json.dumps(summary_json, ensure_ascii=False, indent=2)
             upload_file_to_gcs_with_json_string(gcs_client, bucket_name, summary_file_blob_name, summary_text)
@@ -909,7 +907,8 @@ def get_video_id_summary(video_id, df_string, source):
         # 检查逐字稿是否存在
         exists, file_id = check_file_exists(service, folder_id, file_name)
         if not exists:
-            summary = generate_summarise(df_string)
+            meta_data = get_meta_data(video_id)
+            summary = generate_summarise(df_string, meta_data)
             summary_json = {"summary": str(summary)}
             summary_text = json.dumps(summary_json, ensure_ascii=False, indent=2)
             
@@ -930,12 +929,27 @@ def get_video_id_summary(video_id, df_string, source):
         
     return summary_json
     
-def generate_summarise(df_string):
+def generate_summarise(df_string, metadata=None):
     # 使用 OpenAI 生成基于上传数据的问题
+    if metadata:
+        title = metadata.get("title", "")
+        subject = metadata.get("subject", "")
+        grade = metadata.get("grade", "")
+    else:
+        title = ""
+        subject = ""
+        grade = ""
+
     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
+        課程名稱：{title}
+        科目：{subject}
+        年級：{grade}
+
+        請根據內文： {df_string}
+        
         格式為 Markdown
+        如果有課程名稱，請圍繞「課程名稱」為學習重點，進行重點整理，不要整理跟情境故事相關的問題
         整體摘要在一百字以內
         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
@@ -943,6 +957,7 @@ def generate_summarise(df_string):
         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：
+        ## 🌟 主題：{{title}} (如果沒有 title 就省略)
         ## 📚 整體摘要
             - (一個 bullet point....)
 
@@ -955,7 +970,7 @@ def generate_summarise(df_string):
             - (一個 bullet point....)
         
         ## ❓ 延伸小問題
-            - (一個 bullet point....)
+            - (一個 bullet point....請圍繞「課程名稱」為學習重點，進行重點整理，不要整理跟情境故事相關的問題)
     """
 
     # 🗂️ 1. 內容類型：？
@@ -1075,6 +1090,90 @@ def generate_questions(df_string):
 
     return questions
 
+def get_questions_answers(video_id, df_string, source="gcs"):
+    if source == "gcs":
+        try:
+            print("===get_questions_answers on gcs===")
+            gcs_client = GCS_CLIENT
+            bucket_name = 'video_ai_assistant'
+            file_name = f'{video_id}_questions_answers.json'
+            blob_name = f"{video_id}/{file_name}"
+            # 检查檔案是否存在
+            is_questions_answers_exists = GCS_SERVICE.check_file_exists(bucket_name, blob_name)
+            if not is_questions_answers_exists:
+                questions_answers = generate_questions_answers(df_string)
+                questions_answers_text = json.dumps(questions_answers, ensure_ascii=False, indent=2)
+                upload_file_to_gcs_with_json_string(gcs_client, bucket_name, blob_name, questions_answers_text)
+                print("questions_answers已上傳到GCS")
+            else:
+                # questions_answers已存在，下载内容
+                print("questions_answers已存在于GCS中")
+                questions_answers_text = download_blob_to_string(gcs_client, bucket_name, blob_name)
+                questions_answers = json.loads(questions_answers_text)
+        except:
+            questions = get_questions(video_id, df_string, source)
+            questions_answers = [{"question": q, "answer": ""} for q in questions]
+
+    return questions_answers
+
+def generate_questions_answers(df_string):
+    content_text = str(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，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 {content_text} 生成三個問題跟答案，主要與學科有關，不要問跟情節故事相關的問題
+        答案要在最後標示出處【參考：00:01:05】，請根據時間軸 start_time 來標示
+        請確保問題跟答案都是繁體中文 zh-TW
+        答案不用是標準答案，而是帶有啟發性的蘇格拉底式問答，讓學生思考本來的問題，以及該去參考的時間點
+        並用 JSON 格式返回 questions_answers: [{{question: q1的敘述text, answer: q1的答案text}}, ...]
+        k-v pair 的 key 是 question, value 是 answer
+    """
+
+    try:
+        # OPENAI
+        messages = [
+            {"role": "system", "content": sys_content},
+            {"role": "user", "content": user_content}
+        ]
+        response_format = { "type": "json_object" }
+        request_payload = {
+            "model": "gpt-4-turbo",
+            "messages": messages,
+            "max_tokens": 4000,
+            "response_format": response_format
+        }
+
+        response = OPEN_AI_CLIENT.chat.completions.create(**request_payload)
+        questions_answers = json.loads(response.choices[0].message.content)["questions_answers"]
+    except:
+        # REDROCK_CLIENT        
+        messages = [
+            {"role": "user", "content": user_content}
+        ]
+        model_id = "anthropic.claude-3-sonnet-20240229-v1:0"
+        # model_id = "anthropic.claude-3-haiku-20240307-v1:0"
+        kwargs = {
+            "modelId": model_id,
+            "contentType": "application/json",
+            "accept": "application/json",
+            "body": json.dumps({
+                "anthropic_version": "bedrock-2023-05-31",
+                "max_tokens": 4000,
+                "system": sys_content,
+                "messages": messages
+            })
+        }
+        response = BEDROCK_CLIENT.invoke_model(**kwargs)
+        response_body = json.loads(response.get('body').read())
+        response_completion = response_body.get('content')[0].get('text')
+        questions_answers = json.loads(response_completion)["questions_answers"]
+
+    print("=====json_response=====")
+    print(questions_answers)
+    print("=====json_response=====")
+
+    return questions_answers
+
+
 def change_questions(password, df_string):
     verify_password(password)
 
@@ -1527,6 +1626,16 @@ def update_LLM_content(video_id, new_content, kind):
         questions_text = json.dumps(questions_json, ensure_ascii=False, indent=2)
         upload_file_to_gcs_with_json_string(gcs_client, bucket_name, blob_name, questions_text)
         updated_content = questions_text
+    elif kind == "questions_answers":
+        # from update_LLM_btn  -> new_content is a string
+        # create_LLM_content -> new_content is a list
+        if isinstance(new_content, str):
+            questions_answers_json = json.loads(new_content)
+        else:
+            questions_answers_json = new_content
+        questions_answers_text = json.dumps(questions_answers_json, ensure_ascii=False, indent=2)
+        upload_file_to_gcs_with_json_string(gcs_client, bucket_name, blob_name, questions_answers_text)
+        updated_content = questions_answers_text
 
     print(f"{kind} 已更新到GCS")
     return gr.update(value=updated_content, interactive=False)
@@ -1539,7 +1648,8 @@ def create_LLM_content(video_id, df_string, kind):
         content = generate_reading_passage(df_string)
         update_LLM_content(video_id, content, kind)
     elif kind == "summary_markdown":
-        content = generate_summarise(df_string)
+        meta_data = get_meta_data(video_id)
+        content = generate_summarise(df_string, meta_data)
         update_LLM_content(video_id, content, kind)
     elif kind == "mind_map":
         content = generate_mind_map(df_string)
@@ -1551,17 +1661,26 @@ def create_LLM_content(video_id, df_string, kind):
             transcript = df_string
         formatted_simple_transcript = create_formatted_simple_transcript(transcript)
         formatted_transcript = create_formatted_transcript(video_id, transcript)
-        content = generate_key_moments(formatted_simple_transcript, formatted_transcript)
-        update_LLM_content(video_id, content, kind)
-        content = json.dumps(content, ensure_ascii=False, indent=2)
+        gen_content = generate_key_moments(formatted_simple_transcript, formatted_transcript)
+        update_LLM_content(video_id, gen_content, kind)
+        content = json.dumps(gen_content, ensure_ascii=False, indent=2)
     elif kind == "transcript":
-        content = process_transcript_and_screenshots_on_gcs(video_id)
-        update_LLM_content(video_id, content, kind)
-        content = json.dumps(content, ensure_ascii=False, indent=2)
+        gen_content = process_transcript_and_screenshots_on_gcs(video_id)
+        update_LLM_content(video_id, gen_content, kind)
+        content = json.dumps(gen_content, ensure_ascii=False, indent=2)
     elif kind == "questions":
-        content = generate_questions(df_string)
-        update_LLM_content(video_id, content, kind)
-        content = json.dumps(content, ensure_ascii=False, indent=2)
+        gen_content = generate_questions(df_string)
+        update_LLM_content(video_id, gen_content, kind)
+        content = json.dumps(gen_content, ensure_ascii=False, indent=2)
+    elif kind == "questions_answers":
+        if isinstance(df_string, str):
+            transcript = json.loads(df_string)
+        else:
+            transcript = df_string
+        formatted_simple_transcript = create_formatted_simple_transcript(transcript)
+        gen_content = generate_questions_answers(formatted_simple_transcript)
+        update_LLM_content(video_id, gen_content, kind)
+        content = json.dumps(gen_content, ensure_ascii=False, indent=2)
 
     return gr.update(value=content, interactive=False)
 
@@ -1688,8 +1807,6 @@ def summary_add_markdown_version(video_id):
 
     return new_summary
 
-    
-
 
 # AI 生成教學素材
 def get_meta_data(video_id, source="gcs"):
@@ -1838,11 +1955,12 @@ def get_instructions(content_subject, content_grade, key_moments):
         subject: {content_subject}
         grade: {content_grade}
         context: {key_moments}
-        Assistant Role: you are a {content_subject} teacher
+        Assistant Role: you are a {content_subject} assistant. you can call yourself as  {content_subject} 學伴
         User Role: {content_grade} th-grade student.
         Method: Socratic style, guide thinking, no direct answers. this is very important, please be seriously following.
         Language: Traditional Chinese ZH-TW (it's very important), suitable for {content_grade} th-grade level.
         Response: 
+        - if user say hi or hello or any greeting, just say hi back and introduce yourself. Then ask user to ask question in context.
         - Single question, under 100 characters
         - include math symbols (use LaTeX $ to cover before and after, ex: $x^2$)
         - hint with video timestamp which format 【參考：00:00:00】. 
@@ -1853,12 +1971,32 @@ def get_instructions(content_subject, content_grade, key_moments):
     """
     return instructions
 
-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):
+def chat_with_ai(ai_name, password, video_id, user_data, trascript_state, key_moments, user_message, chat_history, content_subject, content_grade, questions_answers_json, socratic_mode=False):
     verify_password(password)
 
     print("=====user_data=====")
     print(f"user_data: {user_data}")
 
+    questions_answers_json = json.loads(questions_answers_json)
+    for qa in questions_answers_json:
+        question = qa["question"]
+        answer = qa["answer"]
+        if user_message == question and answer != "":
+            print("=== in questions_answers_json==")
+            print(f"question: {question}")
+            print(f"answer: {answer}")
+            # 更新聊天历史
+            new_chat_history = (user_message, answer)
+            if chat_history is None:
+                chat_history = [new_chat_history]
+            else:
+                chat_history.append(new_chat_history)
+
+            # 等待 3 秒
+            time.sleep(3)
+
+            return "", chat_history
+
     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)
@@ -1927,7 +2065,7 @@ def chat_with_ai(ai_name, password, video_id, user_data, trascript_state, key_mo
         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, user_data, 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, questions_answers_json, socratic_mode=False):
     verify_password(password)
 
     print("=====user_data=====")
@@ -1938,6 +2076,28 @@ def chat_with_opan_ai_assistant(password, youtube_id, user_data, thread_id, tras
         error_msg = "你的訊息太長了，請縮短訊息長度至五百字以內"
         raise gr.Error(error_msg)
     
+    questions_answers_json = json.loads(questions_answers_json)
+    for qa in questions_answers_json:
+        question = qa["question"]
+        answer = qa["answer"]
+        if user_message == question and answer != "":
+            print("=== in questions_answers_json==")
+            print(f"question: {question}")
+            print(f"answer: {answer}")
+            print(f"thread_id: {thread_id}")
+            # 更新聊天历史
+            new_chat_history = (user_message, answer)
+            if chat_history is None:
+                chat_history = [new_chat_history]
+            else:
+                chat_history.append(new_chat_history)
+
+            # 等待 3 秒
+            time.sleep(3)
+
+            return "", chat_history, thread_id
+
+    
     # 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（對話一輪10次）"
@@ -2000,7 +2160,7 @@ def chat_with_opan_ai_assistant(password, youtube_id, user_data, thread_id, tras
         client.beta.threads.messages.create(
             thread_id=thread.id,
             role="user",
-            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: $x^2$)"
+            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，回答時如果講到數學專有名詞，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
@@ -2104,13 +2264,13 @@ 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, video_id, user_data, thread_id, trascript, key_moments, content_subject, content_grade):
+def chat_with_opan_ai_assistant_streaming(user_message, chat_history, password, video_id, 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("===chat_with_opan_ai_assistant_streaming===")
     print(thread_id)
     
     # 先計算 user_message 是否超過 500 個字
@@ -2288,7 +2448,7 @@ def init_params(text, request: gr.Request):
         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):
+def update_state(content_subject, content_grade, trascript, key_moments, questions_answers):
     # inputs=[content_subject, content_grade, df_string_output],
     # outputs=[content_subject_state, content_grade_state, trascript_state]
     content_subject_state = content_subject
@@ -2297,13 +2457,22 @@ def update_state(content_subject, content_grade, trascript, key_moments, questio
     formatted_simple_transcript = create_formatted_simple_transcript(trascript_json)
     trascript_state = formatted_simple_transcript
     key_moments_state = key_moments
-    streaming_chat_thread_id_state = create_thread_id()
+
+    streaming_chat_thread_id_state = ""
+    questions_answers_json = json.loads(questions_answers)
+    question_1 = questions_answers_json[0]["question"]
+    question_2 = questions_answers_json[1]["question"]
+    question_3 = questions_answers_json[2]["question"]
+    btn_1 = question_1
+    btn_2 = question_2
+    btn_3 = question_3
     ai_chatbot_question_1 = question_1
     ai_chatbot_question_2 = question_2
     ai_chatbot_question_3 = question_3
 
     return content_subject_state, content_grade_state, trascript_state, key_moments_state, \
         streaming_chat_thread_id_state, \
+        btn_1, btn_2, btn_3, \
         ai_chatbot_question_1, ai_chatbot_question_2, ai_chatbot_question_3
 
 
@@ -2389,7 +2558,7 @@ with gr.Blocks(theme=gr.themes.Base(primary_hue=gr.themes.colors.orange, seconda
     with gr.Tab("AI小精靈"):
         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"):
+                with gr.Column(scale=1, variant="panel", visible=False):
                     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
@@ -2403,7 +2572,7 @@ with gr.Blocks(theme=gr.themes.Base(primary_hue=gr.themes.colors.orange, seconda
                     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"):
+                with gr.Column(scale=1, variant="panel", visible=False):
                     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
@@ -2435,7 +2604,7 @@ with gr.Blocks(theme=gr.themes.Base(primary_hue=gr.themes.colors.orange, seconda
                 bot_avatar = "https://junyitopicimg.s3.amazonaws.com/s4byy--icon.jpe?v=20200513013523726"
                 latex_delimiters = [{"left": "$", "right": "$", "display": False}]
                 chatbot_greeting = [[
-                    None,
+                    "請問你是誰？",
                     """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！
@@ -2470,7 +2639,7 @@ with gr.Blocks(theme=gr.themes.Base(primary_hue=gr.themes.colors.orange, seconda
                     """
                 additional_inputs = [password, video_id, 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,
+                    fn=chat_with_opan_ai_assistant_streaming,
                     additional_inputs=additional_inputs,
                     submit_btn="送出",
                     retry_btn=None,
@@ -2482,7 +2651,7 @@ with gr.Blocks(theme=gr.themes.Base(primary_hue=gr.themes.colors.orange, seconda
         with gr.Row("其他精靈") as chatbot_jutor:   
             with gr.Column():
                 ai_chatbot_greeting = [[
-                    None,
+                    "請問你是誰？",
                     """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！
@@ -2491,7 +2660,12 @@ with gr.Blocks(theme=gr.themes.Base(primary_hue=gr.themes.colors.orange, seconda
                     """,
                 ]]
                 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_name = gr.Dropdown(label="選擇 AI 助理", choices=[
+                    # ("梨梨","jutor"), 
+                    ("麥麥","claude3"), 
+                    ("狐狸貓","groq")], 
+                        value="claude3"
+                )
                 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():
@@ -2526,7 +2700,7 @@ with gr.Blocks(theme=gr.themes.Base(primary_hue=gr.themes.colors.orange, seconda
                         with gr.Row():
                             worksheet_content_type_name = gr.Textbox(value="worksheet", visible=False)
                             worksheet_algorithm = gr.Dropdown(label="選擇教學策略或理論", choices=["Bloom認知階層理論", "Polya數學解題法", "CRA教學法"], value="Bloom認知階層理論", visible=False)
-                            worksheet_content_btn = gr.Button("生成學習單 📄", variant="primary")
+                            worksheet_content_btn = gr.Button("生成學習單 📄", variant="primary", visible=False)
                         with gr.Accordion("微調", open=False):
                             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")
@@ -2541,13 +2715,13 @@ with gr.Blocks(theme=gr.themes.Base(primary_hue=gr.themes.colors.orange, seconda
                         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.Tab("教案"):
                 with gr.Row():
                     with gr.Column(scale=1):
                         with gr.Row():
                             lesson_plan_content_type_name = gr.Textbox(value="lesson_plan", visible=False)                    
                             lesson_plan_time = gr.Slider(label="選擇課程時間(分鐘)", minimum=10, maximum=120, step=5, value=40)
-                            lesson_plan_btn = gr.Button("生成課程計畫 📕", variant="primary")
+                            lesson_plan_btn = gr.Button("生成教案 📕", variant="primary", visible=False)
                         with gr.Accordion("微調", open=False):
                             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")
@@ -2568,7 +2742,7 @@ with gr.Blocks(theme=gr.themes.Base(primary_hue=gr.themes.colors.orange, seconda
                         with gr.Row():
                             exit_ticket_content_type_name = gr.Textbox(value="exit_ticket", visible=False)
                             exit_ticket_time = gr.Slider(label="選擇出場券時間(分鐘)", minimum=5, maximum=10, step=1, value=8)
-                            exit_ticket_btn = gr.Button("生成出場券 🎟️", variant="primary")
+                            exit_ticket_btn = gr.Button("生成出場券 🎟️", variant="primary", visible=False)
                         with gr.Accordion("微調", open=False):
                             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")
@@ -2655,9 +2829,19 @@ with gr.Blocks(theme=gr.themes.Base(primary_hue=gr.themes.colors.orange, seconda
                 questions_edit_button = gr.Button("編輯", 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")
+                questions_create_button = gr.Button("重建", size="sm", variant="primary")
             with gr.Row():
                 questions_json = gr.Textbox(label="Questions", lines=40, interactive=False, show_copy_button=True)
+        with gr.Tab("問題答案本文"):
+            with gr.Row() as questions_answers_admin:
+                questions_answers_kind = gr.Textbox(value="questions_answers", show_label=False)
+                questions_answers_get_button = gr.Button("取得", size="sm", variant="primary")
+                questions_answers_edit_button = gr.Button("編輯", size="sm", variant="primary")
+                questions_answers_update_button = gr.Button("儲存", size="sm", variant="primary")
+                questions_answers_delete_button = gr.Button("刪除", size="sm", variant="primary")
+                questions_answers_create_button = gr.Button("重建", size="sm", variant="primary")
+            with gr.Row():
+                questions_answers_json = gr.Textbox(label="Questions Answers", lines=40, interactive=False, show_copy_button=True)
         with gr.Tab("逐字稿"):
             simple_html_content = gr.HTML(label="Simple Transcript")
         with gr.Tab("圖文"):
@@ -2687,6 +2871,10 @@ with gr.Blocks(theme=gr.themes.Base(primary_hue=gr.themes.colors.orange, seconda
         chatbot_select,
         inputs=[chatbot_open_ai_streaming_name],
         outputs=[chatbot_select_accordion, chatbot_open_ai, chatbot_open_ai_streaming, chatbot_jutor]
+    ).then(
+        create_thread_id,
+        inputs=[],
+        outputs=[streaming_chat_thread_id_state]
     )
     chatbot_jutor_select_btn.click(
         chatbot_select,
@@ -2697,7 +2885,7 @@ with gr.Blocks(theme=gr.themes.Base(primary_hue=gr.themes.colors.orange, seconda
     # OPENAI ASSISTANT CHATBOT 模式
     send_button.click(
         chat_with_opan_ai_assistant,
-        inputs=[password, video_id, user_data, thread_id, trascript_state, key_moments, msg, chatbot, content_subject, content_grade, socratic_mode_btn],
+        inputs=[password, video_id, user_data, thread_id, trascript_state, key_moments, msg, chatbot, content_subject, content_grade, questions_answers_json, socratic_mode_btn],
         outputs=[msg, chatbot, thread_id],
         scroll_to_output=True
     )
@@ -2707,9 +2895,9 @@ 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, 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_chat_with_opan_ai_assistant_input =[password, video_id, user_data, thread_id, trascript_state, key_moments, btn_1, chatbot, content_subject, content_grade, questions_answers_json, 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, questions_answers_json, 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, questions_answers_json, ai_chatbot_socratic_mode_btn]
     btn_1.click(
         chat_with_opan_ai_assistant,
         inputs=btn_1_chat_with_opan_ai_assistant_input, 
@@ -2737,14 +2925,14 @@ with gr.Blocks(theme=gr.themes.Base(primary_hue=gr.themes.colors.orange, seconda
     # 其他精靈 ai_chatbot 模式
     ai_send_button.click(
         chat_with_ai,
-        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],
+        inputs=[ai_name, password, video_id, user_data, trascript_state, key_moments, ai_msg, ai_chatbot, content_subject, content_grade, questions_answers_json, ai_chatbot_socratic_mode_btn],
         outputs=[ai_msg, ai_chatbot],
         scroll_to_output=True
     )
     # 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_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, questions_answers_json, 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, questions_answers_json, 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, questions_answers_json, ai_chatbot_socratic_mode_btn]
     ai_chatbot_question_1.click(
         chat_with_ai,
         inputs=ai_chatbot_question_1_chat_with_ai_input,
@@ -2771,10 +2959,7 @@ with gr.Blocks(theme=gr.themes.Base(primary_hue=gr.themes.colors.orange, seconda
     process_youtube_link_inputs = [password, youtube_link]
     process_youtube_link_outputs = [
         video_id,
-        questions_json,
-        btn_1, 
-        btn_2, 
-        btn_3, 
+        questions_answers_json,
         df_string_output, 
         summary_text,
         df_summarise,
@@ -2796,9 +2981,7 @@ with gr.Blocks(theme=gr.themes.Base(primary_hue=gr.themes.colors.orange, seconda
         content_grade,
         df_string_output,
         key_moments,
-        btn_1, 
-        btn_2, 
-        btn_3
+        questions_answers_json,
     ]
     update_state_outputs = [
         content_subject_state, 
@@ -2806,6 +2989,9 @@ with gr.Blocks(theme=gr.themes.Base(primary_hue=gr.themes.colors.orange, seconda
         trascript_state,
         key_moments_state,
         streaming_chat_thread_id_state,
+        btn_1, 
+        btn_2, 
+        btn_3,
         ai_chatbot_question_1,
         ai_chatbot_question_2,
         ai_chatbot_question_3
@@ -2979,6 +3165,33 @@ with gr.Blocks(theme=gr.themes.Base(primary_hue=gr.themes.colors.orange, seconda
         inputs=[video_id, questions_json, questions_kind],
         outputs=[questions_json]
     ) 
+    # questions_answers event
+    questions_answers_get_button.click(
+        get_LLM_content,
+        inputs=[video_id, questions_answers_kind],
+        outputs=[questions_answers_json]
+    )
+    questions_answers_create_button.click(
+        create_LLM_content,
+        inputs=[video_id, df_string_output, questions_answers_kind],
+        outputs=[questions_answers_json]
+    )
+    questions_answers_delete_button.click(
+        delete_LLM_content,
+        inputs=[video_id, questions_answers_kind],
+        outputs=[questions_answers_json]
+    )
+    questions_answers_edit_button.click(
+        enable_edit_mode,
+        inputs=[],
+        outputs=[questions_answers_json]
+    )
+    questions_answers_update_button.click(
+        update_LLM_content,
+        inputs=[video_id, questions_answers_json, questions_answers_kind],
+        outputs=[questions_answers_json]
+    )
+
 
     # 教師版
     worksheet_content_btn.click(

chatbot.py

@@ -61,7 +61,7 @@ class Chatbot:
                     messages.append({"role": "assistant", "content": assistant_msg})
                 
         if user_message:
-            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)，回答時請用數學符號代替文字（Latex 用 $ 字號 render)"
+            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)，回答時如果有用到數學式，請用數學符號代替純文字（Latex 用 $ 字號 render)"
             messages.append({"role": "user", "content": user_message})
         return messages