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import gradio as gr
from description import *
from reference_string_parsing import *
from summarization import *
with gr.Blocks(css="#htext span {white-space: pre-line}") as demo:
gr.Markdown("# Gradio Demo for SciAssist")
with gr.Tabs():
# Reference String Parsing
with gr.TabItem("Reference String Parsing"):
with gr.Box():
gr.Markdown(rsp_str_md)
with gr.Row():
with gr.Column():
rsp_str = gr.Textbox(label="Input String")
with gr.Column():
rsp_str_dehyphen = gr.Checkbox(label="dehyphen")
with gr.Row():
rsp_str_btn = gr.Button("Parse")
rsp_str_output = gr.HighlightedText(
elem_id="htext",
label="The Result of Parsing",
combine_adjacent=True,
adjacent_separator=" ",
)
rsp_str_examples = gr.Examples(examples=[[
"Waleed Ammar, Matthew E. Peters, Chandra Bhagavat- ula, and Russell Power. 2017. The ai2 system at semeval-2017 task 10 (scienceie): semi-supervised end-to-end entity and relation extraction. In ACL workshop (SemEval).",
True],
[
"Isabelle Augenstein, Mrinal Das, Sebastian Riedel, Lakshmi Vikraman, and Andrew D. McCallum. 2017. Semeval-2017 task 10 (scienceie): Extracting keyphrases and relations from scientific publications. In ACL workshop (SemEval).",
False]], inputs=[rsp_str, rsp_str_dehyphen])
with gr.Box():
gr.Markdown(rsp_file_md)
with gr.Row():
with gr.Column():
rsp_file = gr.File(label="Input File")
rsp_file_dehyphen = gr.Checkbox(label="dehyphen")
with gr.Row():
rsp_file_btn = gr.Button("Parse")
rsp_file_output = gr.HighlightedText(
elem_id="htext",
label="The Result of Parsing",
combine_adjacent=True,
adjacent_separator=" ",
)
rsp_file_examples = gr.Examples(examples=[["examples/N18-3011_ref.txt", False],["examples/BERT_paper.pdf", True]], inputs=[rsp_file, rsp_file_dehyphen])
rsp_file_btn.click(
fn=rsp_for_file,
inputs=[rsp_file, rsp_file_dehyphen],
outputs=rsp_file_output
)
rsp_str_btn.click(
fn=rsp_for_str,
inputs=[rsp_str, rsp_str_dehyphen],
outputs=rsp_str_output
)
# Single Document Summarization
with gr.TabItem("Single Document Summarization"):
with gr.Box():
gr.Markdown(ssum_str_md)
with gr.Row():
with gr.Column():
ssum_str = gr.Textbox(label="Input String")
with gr.Column():
ssum_str_beams = gr.Number(label="Number of beams for beam search", value=1, precision=0)
ssum_str_sequences = gr.Number(label="Number of generated summaries", value=1, precision=0)
with gr.Row():
ssum_str_btn = gr.Button("Generate")
ssum_str_output = gr.Textbox(
elem_id="htext",
label="Summary",
)
ssum_str_examples = gr.Examples(examples=[[ssum_str_example, 1, 1], ],
inputs=[ssum_str, ssum_str_beams, ssum_str_sequences])
with gr.Box():
gr.Markdown(ssum_file_md)
with gr.Row():
with gr.Column():
ssum_file = gr.File(label="Input File")
with gr.Column():
ssum_file_beams = gr.Number(label="Number of beams for beam search", value=1, precision=0)
ssum_file_sequences = gr.Number(label="Number of generated summaries", value=1, precision=0)
with gr.Row():
ssum_file_btn = gr.Button("Generate")
ssum_file_output = gr.Textbox(
elem_id="htext",
label="Summary",
)
ssum_file_examples = gr.Examples(examples=[["examples/BERT_body.txt", 10, 2],["examples/BERT_paper.pdf", 1, 1]],
inputs=[ssum_file, ssum_file_beams, ssum_file_sequences])
ssum_file_btn.click(
fn=ssum_for_file,
inputs=[ssum_file, ssum_file_beams, ssum_file_sequences],
outputs=ssum_file_output
)
ssum_str_btn.click(
fn=ssum_for_str,
inputs=[ssum_str, ssum_str_beams, ssum_str_sequences],
outputs=ssum_str_output
)
demo.launch() |