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Update app.py
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app.py
CHANGED
@@ -53,6 +53,10 @@ STYLE = """
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#search_input > label > span {
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display: none;
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}
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"""
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dataset_repo_id = "chansung/auto-paper-qa2"
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@@ -146,10 +150,19 @@ def set_paper(date, paper_title):
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gr.Markdown(f"βͺ **(Technical)** {selected_paper['2_additional_breath_q:answers:expert']}"),
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)
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def
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if
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return
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def search(search_in, max_results=3):
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results = []
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@@ -272,55 +285,59 @@ with gr.Blocks(css=STYLE) as demo:
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title = gr.Markdown(f"# {selected_paper['title']}")
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summary = gr.Markdown(f"{selected_paper['summary']}", elem_classes=["small-font"])
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gr.
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# 1
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with gr.Column(elem_classes=["group"], visible=True) as q_0:
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basic_q_0 = gr.Markdown(f"## π {selected_paper['0_question']}")
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basic_q_eli5_0 = gr.Markdown(f"βͺ **(ELI5)** {selected_paper['0_answers:eli5']}", elem_classes=["small-font"])
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basic_q_expert_0 = gr.Markdown(f"βͺ **(Technical)** {selected_paper['0_answers:expert']}", elem_classes=["small-font"])
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with gr.Accordion("Additional question #1", open=False, elem_classes=["accordion"]) as aq_0_0:
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depth_q_0 = gr.Markdown(f"## ππ {selected_paper['0_additional_depth_q:follow up question']}")
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depth_q_eli5_0 = gr.Markdown(f"βͺ **(ELI5)** {selected_paper['0_additional_depth_q:answers:eli5']}", elem_classes=["small-font"])
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depth_q_expert_0 = gr.Markdown(f"βͺ **(Technical)** {selected_paper['0_additional_depth_q:answers:expert']}", elem_classes=["small-font"])
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with gr.Accordion("Additional question #2", open=False, elem_classes=["accordion"]) as aq_0_1:
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breath_q_0 = gr.Markdown(f"## ππ {selected_paper['0_additional_breath_q:follow up question']}")
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breath_q_eli5_0 = gr.Markdown(f"βͺ **(ELI5)** {selected_paper['0_additional_breath_q:answers:eli5']}", elem_classes=["small-font"])
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breath_q_expert_0 = gr.Markdown(f"βͺ **(Technical)** {selected_paper['0_additional_breath_q:answers:expert']}", elem_classes=["small-font"])
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# 2
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with gr.Column(elem_classes=["group"], visible=True) as q_1:
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basic_q_1 = gr.Markdown(f"## π {selected_paper['1_question']}")
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basic_q_eli5_1 = gr.Markdown(f"βͺ **(ELI5)** {selected_paper['1_answers:eli5']}", elem_classes=["small-font"])
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basic_q_expert_1 = gr.Markdown(f"βͺ **(Technical)** {selected_paper['1_answers:expert']}", elem_classes=["small-font"])
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with gr.Accordion("Additional question #1", open=False, elem_classes=["accordion"]) as aq_1_0:
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depth_q_1 = gr.Markdown(f"## ππ {selected_paper['1_additional_depth_q:follow up question']}")
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depth_q_eli5_1 = gr.Markdown(f"βͺ **(ELI5)** {selected_paper['1_additional_depth_q:answers:eli5']}", elem_classes=["small-font"])
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depth_q_expert_1 = gr.Markdown(f"βͺ **(Technical)** {selected_paper['1_additional_depth_q:answers:expert']}", elem_classes=["small-font"])
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with gr.Accordion("Additional question #2", open=False, elem_classes=["accordion"]) as aq_1_1:
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breath_q_1 = gr.Markdown(f"## ππ {selected_paper['1_additional_breath_q:follow up question']}")
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breath_q_eli5_1 = gr.Markdown(f"βͺ **(ELI5)** {selected_paper['1_additional_breath_q:answers:eli5']}", elem_classes=["small-font"])
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breath_q_expert_1 = gr.Markdown(f"βͺ **(Technical)** {selected_paper['1_additional_breath_q:answers:expert']}", elem_classes=["small-font"])
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# 3
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with gr.Column(elem_classes=["group"], visible=True) as q_2:
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basic_q_2 = gr.Markdown(f"## π {selected_paper['2_question']}")
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basic_q_eli5_2 = gr.Markdown(f"βͺ **(ELI5)** {selected_paper['2_answers:eli5']}", elem_classes=["small-font"])
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basic_q_expert_2 = gr.Markdown(f"βͺ **(Technical)** {selected_paper['2_answers:expert']}", elem_classes=["small-font"])
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with gr.Accordion("Additional question #1", open=False, elem_classes=["accordion"]) as aq_2_0:
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depth_q_2 = gr.Markdown(f"## ππ {selected_paper['2_additional_depth_q:follow up question']}")
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depth_q_eli5_2 = gr.Markdown(f"βͺ **(ELI5)** {selected_paper['2_additional_depth_q:answers:eli5']}", elem_classes=["small-font"])
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depth_q_expert_2 = gr.Markdown(f"βͺ **(Technical)** {selected_paper['2_additional_depth_q:answers:expert']}", elem_classes=["small-font"])
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with gr.Accordion("Additional question #2", open=False, elem_classes=["accordion"]) as aq_2_1:
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breath_q_2 = gr.Markdown(f"## ππ {selected_paper['2_additional_breath_q:follow up question']}")
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breath_q_eli5_2 = gr.Markdown(f"βͺ **(ELI5)** {selected_paper['2_additional_breath_q:answers:eli5']}", elem_classes=["small-font"])
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breath_q_expert_2 = gr.Markdown(f"βͺ **(Technical)** {selected_paper['2_additional_breath_q:answers:expert']}", elem_classes=["small-font"])
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search_r1.click(
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set_date,
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@@ -401,4 +418,14 @@ with gr.Blocks(css=STYLE) as demo:
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fn=None
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)
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demo.launch(share=True)
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#search_input > label > span {
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display: none;
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}
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#exp-type > span {
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display: none;
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}
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"""
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dataset_repo_id = "chansung/auto-paper-qa2"
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gr.Markdown(f"βͺ **(Technical)** {selected_paper['2_additional_breath_q:answers:expert']}"),
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)
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def change_exp_type(exp_type):
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if exp_type == "ELI5":
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return (
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gr.Markdown(visible=True), gr.Markdown(visible=False), gr.Markdown(visible=True), gr.Markdown(visible=False), gr.Markdown(visible=True), gr.Markdown(visible=False),
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gr.Markdown(visible=True), gr.Markdown(visible=False), gr.Markdown(visible=True), gr.Markdown(visible=False), gr.Markdown(visible=True), gr.Markdown(visible=False),
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gr.Markdown(visible=True), gr.Markdown(visible=False), gr.Markdown(visible=True), gr.Markdown(visible=False), gr.Markdown(visible=True), gr.Markdown(visible=False),
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)
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else:
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return (
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gr.Markdown(visible=False), gr.Markdown(visible=True), gr.Markdown(visible=False), gr.Markdown(visible=True), gr.Markdown(visible=False), gr.Markdown(visible=True),
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gr.Markdown(visible=False), gr.Markdown(visible=True), gr.Markdown(visible=False), gr.Markdown(visible=True), gr.Markdown(visible=False), gr.Markdown(visible=True),
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gr.Markdown(visible=False), gr.Markdown(visible=True), gr.Markdown(visible=False), gr.Markdown(visible=True), gr.Markdown(visible=False), gr.Markdown(visible=True),
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)
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def search(search_in, max_results=3):
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results = []
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title = gr.Markdown(f"# {selected_paper['title']}")
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summary = gr.Markdown(f"{selected_paper['summary']}", elem_classes=["small-font"])
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with gr.Row():
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with gr.Column(scale=7):
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gr.Markdown("## Auto generated Questions & Answers")
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exp_type = gr.Radio(choices=["ELI5", "Technical"], value="ELI5", elem_id="exp-type", scale=3)
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# 1
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with gr.Column(elem_classes=["group"], visible=True) as q_0:
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basic_q_0 = gr.Markdown(f"## π {selected_paper['0_question']}")
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basic_q_eli5_0 = gr.Markdown(f"βͺ **(ELI5)** {selected_paper['0_answers:eli5']}", elem_classes=["small-font"])
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basic_q_expert_0 = gr.Markdown(f"βͺ **(Technical)** {selected_paper['0_answers:expert']}", visible=False, elem_classes=["small-font"])
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with gr.Accordion("Additional question #1", open=False, elem_classes=["accordion"]) as aq_0_0:
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depth_q_0 = gr.Markdown(f"## ππ {selected_paper['0_additional_depth_q:follow up question']}")
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depth_q_eli5_0 = gr.Markdown(f"βͺ **(ELI5)** {selected_paper['0_additional_depth_q:answers:eli5']}", elem_classes=["small-font"])
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depth_q_expert_0 = gr.Markdown(f"βͺ **(Technical)** {selected_paper['0_additional_depth_q:answers:expert']}", visible=False, elem_classes=["small-font"])
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with gr.Accordion("Additional question #2", open=False, elem_classes=["accordion"]) as aq_0_1:
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breath_q_0 = gr.Markdown(f"## ππ {selected_paper['0_additional_breath_q:follow up question']}")
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breath_q_eli5_0 = gr.Markdown(f"βͺ **(ELI5)** {selected_paper['0_additional_breath_q:answers:eli5']}", elem_classes=["small-font"])
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breath_q_expert_0 = gr.Markdown(f"βͺ **(Technical)** {selected_paper['0_additional_breath_q:answers:expert']}", visible=False, elem_classes=["small-font"])
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# 2
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with gr.Column(elem_classes=["group"], visible=True) as q_1:
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basic_q_1 = gr.Markdown(f"## π {selected_paper['1_question']}")
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basic_q_eli5_1 = gr.Markdown(f"βͺ **(ELI5)** {selected_paper['1_answers:eli5']}", elem_classes=["small-font"])
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basic_q_expert_1 = gr.Markdown(f"βͺ **(Technical)** {selected_paper['1_answers:expert']}", visible=False, elem_classes=["small-font"])
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with gr.Accordion("Additional question #1", open=False, elem_classes=["accordion"]) as aq_1_0:
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depth_q_1 = gr.Markdown(f"## ππ {selected_paper['1_additional_depth_q:follow up question']}")
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depth_q_eli5_1 = gr.Markdown(f"βͺ **(ELI5)** {selected_paper['1_additional_depth_q:answers:eli5']}", elem_classes=["small-font"])
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depth_q_expert_1 = gr.Markdown(f"βͺ **(Technical)** {selected_paper['1_additional_depth_q:answers:expert']}", visible=False, elem_classes=["small-font"])
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with gr.Accordion("Additional question #2", open=False, elem_classes=["accordion"]) as aq_1_1:
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breath_q_1 = gr.Markdown(f"## ππ {selected_paper['1_additional_breath_q:follow up question']}")
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breath_q_eli5_1 = gr.Markdown(f"βͺ **(ELI5)** {selected_paper['1_additional_breath_q:answers:eli5']}", elem_classes=["small-font"])
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breath_q_expert_1 = gr.Markdown(f"βͺ **(Technical)** {selected_paper['1_additional_breath_q:answers:expert']}", visible=False, elem_classes=["small-font"])
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# 3
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with gr.Column(elem_classes=["group"], visible=True) as q_2:
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basic_q_2 = gr.Markdown(f"## π {selected_paper['2_question']}")
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basic_q_eli5_2 = gr.Markdown(f"βͺ **(ELI5)** {selected_paper['2_answers:eli5']}", elem_classes=["small-font"])
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basic_q_expert_2 = gr.Markdown(f"βͺ **(Technical)** {selected_paper['2_answers:expert']}", visible=False, elem_classes=["small-font"])
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with gr.Accordion("Additional question #1", open=False, elem_classes=["accordion"]) as aq_2_0:
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depth_q_2 = gr.Markdown(f"## ππ {selected_paper['2_additional_depth_q:follow up question']}")
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depth_q_eli5_2 = gr.Markdown(f"βͺ **(ELI5)** {selected_paper['2_additional_depth_q:answers:eli5']}", elem_classes=["small-font"])
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depth_q_expert_2 = gr.Markdown(f"βͺ **(Technical)** {selected_paper['2_additional_depth_q:answers:expert']}", visible=False, elem_classes=["small-font"])
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with gr.Accordion("Additional question #2", open=False, elem_classes=["accordion"]) as aq_2_1:
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breath_q_2 = gr.Markdown(f"## ππ {selected_paper['2_additional_breath_q:follow up question']}")
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breath_q_eli5_2 = gr.Markdown(f"βͺ **(ELI5)** {selected_paper['2_additional_breath_q:answers:eli5']}", elem_classes=["small-font"])
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breath_q_expert_2 = gr.Markdown(f"βͺ **(Technical)** {selected_paper['2_additional_breath_q:answers:expert']}", visible=False, elem_classes=["small-font"])
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search_r1.click(
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set_date,
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fn=None
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)
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exp_type.select(
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change_exp_type,
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exp_type,
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[
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basic_q_eli5_0, basic_q_expert_0, depth_q_eli5_0, depth_q_expert_0, breath_q_eli5_0, breath_q_expert_0,
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basic_q_eli5_1, basic_q_expert_1, depth_q_eli5_1, depth_q_expert_1, breath_q_eli5_1, breath_q_expert_1,
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basic_q_eli5_2, basic_q_expert_2, depth_q_eli5_2, depth_q_expert_2, breath_q_eli5_2, breath_q_expert_2
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]
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)
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demo.launch(share=True)
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