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vaitor2

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def get_ai_content(password, video_id, df_string, topic, grade, level, specific_feature, content_type, source="gcs"):
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with gr.Accordion("微調", open=False):
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"將结果轉成 word，完成後請點擊右下角 download 按鈕"
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import uuid
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def return_original_exam_result(exam_result_original):
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worksheet_exam_result_retrun_original.click(
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worksheet_content_btn.click(
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worksheet_exam_result_fine_tune_btn.click(
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update
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update
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update
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update
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update code
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update
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gr.Markdown("## GROQ 模式")
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respond_with_jutor_chat
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# print("===確認其他衍生文件===")
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first_image = "https://www.nameslook.com/names/dfsadf-nameslook.png"
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print(f"mind_map_json: {mind_map_json}")
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# 處理截圖
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no comment
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delete useless code
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no 截圖
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gr.Markdown("## 教育評量饗宴")
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gr.Markdown("## 教育評量饗宴")
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no comment
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gr.Markdown("## 教育评量饗宴")
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gr.Markdown("## 教育评量饗宴")
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languages = ['zh-TW', 'zh-Hant', 'zh', 'en'] # 優先順序列表
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if transcript:
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trascript_text = json.dumps(trascript_json, ensure_ascii=False, indent=2)
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逐字稿資料：{trascript}
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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，
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error_msg = "你的訊息太長了，請縮短訊息長度至五百字以內"
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raise gr.Error(error_msg)
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raise ValueError("user_message 長度超過 500 個字")
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msg = gr.Textbox(label="Message")
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# msg limit to 1000 characters
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thread_id = gr.Textbox(label="thread_id", visible=False)
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最後只要是參考逐字稿資料，請在回答的最後標註【參考資料：（分）：（秒）】
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if file.filename == f"{youtube_id}_transcript.txt":
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file_list = client.beta.assistants.files.list(assistant_id=assistant_id)
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