def get_meta_data(video_id, source="gcs"):

with gr.Blocks(theme=gr.themes.Base(primary_hue=gr.themes.colors.orange, secondary_hue=gr.themes.colors.amber)) as demo:

password = gr.Textbox(label="Password", type="password", elem_id="password_input", visible=True)

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)

admin_update_visible

refactor

exit_ticket_exam_result = gr.Textbox(label="初次生成結果", show_copy_button=True, interactive=True, lines=40)

ai_content_json = ai_content_json[-1]

target_kvs = {

content_topic = gr.Dropdown(label="選擇主題", choices=["數學", "自然", "國文", "英文", "社會","物理", "化學", "生物", "地理", "歷史", "公民"], value="數學")

def get_ai_content(password, video_id, df_string, topic, grade, level, specific_feature, content_type, source="gcs"):

with gr.Accordion("微調", open=False):

"將结果轉成 word，完成後請點擊右下角 download 按鈕"

import uuid

def return_original_exam_result(exam_result_original):

worksheet_exam_result_retrun_original.click(

worksheet_content_btn.click(

worksheet_exam_result_fine_tune_btn.click(

update

update

update

update

update code

update

update

update

tab

gr.Markdown("## GROQ 模式")

respond_with_jutor_chat

groq

pw

img

# print("===確認其他衍生文件===")

first_image = "https://www.nameslook.com/names/dfsadf-nameslook.png"

print(f"mind_map_json: {mind_map_json}")

# 處理截圖

no comment

delete useless code

no 截圖

gr.Markdown("## 教育評量饗宴")

gr.Markdown("## 教育評量饗宴")

no comment

gr.Markdown("## 教育评量饗宴")

debug

gr.Markdown("## 教育评量饗宴")

languages = ['zh-TW', 'zh-Hant', 'zh', 'en'] # 優先順序列表

if transcript:

trascript_text = json.dumps(trascript_json, ensure_ascii=False, indent=2)

逐字稿資料：{trascript}

如果 file 內有找到 file.content["{youtube_id}"] 為資料文本，自行判斷資料的種類，