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],], 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],], 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()