Spaces:
Sleeping
Sleeping
video_id = gr.Textbox(label="video_id")
Browse files
app.py
CHANGED
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@@ -532,17 +532,19 @@ def process_youtube_link(link):
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mind_map_html = get_mind_map_html(mind_map)
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# 确保返回与 UI 组件预期匹配的输出
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return
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def format_transcript_to_html(formatted_transcript):
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@@ -774,7 +776,6 @@ def get_video_id_summary(video_id, df_string, source):
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return summary_json
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def generate_summarise(df_string):
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# 使用 OpenAI 生成基于上传数据的问题
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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"
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return df_summarise
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def generate_questions(df_string):
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# 使用 OpenAI 生成基于上传数据的问题
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def next_slide():
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return update_slide(1)
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return VIDEO_ID
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HEAD = """
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<meta charset="UTF-8">
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with gr.Column(scale=2):
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file_upload = gr.File(label="Upload your CSV or Word file", visible=False)
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youtube_link = gr.Textbox(label="Enter YouTube Link")
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youtube_link_btn = gr.Button("Submit_YouTube_Link")
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web_link = gr.Textbox(label="Enter Web Page Link", visible=False)
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chatbot = gr.Chatbot()
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# chat_with_youtube_transcript
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send_button.click(
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chat_with_youtube_transcript,
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inputs=[
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outputs=[msg, chatbot, thread_id]
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)
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# 连接按钮点击事件
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btn_1.click(
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chat_with_youtube_transcript,
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inputs=[
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outputs=[msg, chatbot, thread_id]
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)
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btn_2.click(
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chat_with_youtube_transcript,
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inputs=[
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outputs=[msg, chatbot, thread_id]
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)
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btn_3.click(
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chat_with_youtube_transcript,
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inputs=[
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outputs=[msg, chatbot, thread_id]
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)
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process_youtube_link,
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inputs=youtube_link,
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outputs=[
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btn_1,
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btn_2,
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btn_3,
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process_youtube_link,
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inputs=youtube_link,
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outputs=[
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btn_1,
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btn_2,
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btn_3,
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mind_map_html = get_mind_map_html(mind_map)
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# 确保返回与 UI 组件预期匹配的输出
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return video_id, \
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questions[0] if len(questions) > 0 else "", \
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questions[1] if len(questions) > 1 else "", \
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questions[2] if len(questions) > 2 else "", \
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formatted_transcript_json, \
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summary, \
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mind_map, \
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mind_map_html, \
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html_content, \
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simple_html_content, \
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first_image, \
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first_text,
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def format_transcript_to_html(formatted_transcript):
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return summary_json
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def generate_summarise(df_string):
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# 使用 OpenAI 生成基于上传数据的问题
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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"
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return df_summarise
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def generate_questions(df_string):
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# 使用 OpenAI 生成基于上传数据的问题
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def next_slide():
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return update_slide(1)
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HEAD = """
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<meta charset="UTF-8">
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with gr.Column(scale=2):
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file_upload = gr.File(label="Upload your CSV or Word file", visible=False)
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youtube_link = gr.Textbox(label="Enter YouTube Link")
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video_id = gr.Textbox(label="video_id")
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youtube_link_btn = gr.Button("Submit_YouTube_Link")
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web_link = gr.Textbox(label="Enter Web Page Link", visible=False)
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chatbot = gr.Chatbot()
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# chat_with_youtube_transcript
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send_button.click(
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chat_with_youtube_transcript,
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inputs=[video_id, thread_id, msg, chatbot, socratic_mode_btn],
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outputs=[msg, chatbot, thread_id]
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)
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# 连接按钮点击事件
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btn_1.click(
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chat_with_youtube_transcript,
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inputs=[video_id, thread_id, btn_1, chatbot, socratic_mode_btn],
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outputs=[msg, chatbot, thread_id]
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)
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btn_2.click(
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chat_with_youtube_transcript,
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inputs=[video_id, thread_id, btn_2, chatbot, socratic_mode_btn],
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outputs=[msg, chatbot, thread_id]
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)
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btn_3.click(
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chat_with_youtube_transcript,
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inputs=[video_id, thread_id, btn_3, chatbot, socratic_mode_btn],
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outputs=[msg, chatbot, thread_id]
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)
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process_youtube_link,
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inputs=youtube_link,
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outputs=[
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video_id,
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btn_1,
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btn_2,
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btn_3,
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process_youtube_link,
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inputs=youtube_link,
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outputs=[
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video_id,
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btn_1,
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btn_2,
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btn_3,
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