import os

import gradio as gr
from gradio_pdf import PDF

current_pdf_file = None

with gr.Blocks() as demo:
    with gr.Row():
        with gr.Column(scale=1):
            with gr.Row():
                # gr.Label("会议名称")
                conf_name = gr.Dropdown(choices=["ECCV2022", "ECCV2020", "CVPR2024"], value="ECCV2022", label="会议名称", show_label=True)
                conf_button = gr.Button("查看会议论文", variant='primary')
            dataframe = gr.Dataframe(headers=["论文名称"], col_count=(1, "fixed"), type='array', height=800)
            with gr.Row():
                look_input = gr.Textbox(placeholder="关键词检索", label="关键词过滤")
                filter_button = gr.Button("过滤")
            # up_button = gr.Button("加载")

        with gr.Column(scale=2):
            pdf = PDF(label="Upload a PDF", interactive=True, height=1000)


        # name = gr.Textbox(show_label=False)
        # pdf.upload(lambda f: f, pdf, name)

        def up_load():
            global current_pdf_file
            n = r"D:\py\keyan_qingbao\te_u\paper_down_load\ECCV_2022\main_paper\3d-siamese-transformer-network-for-single-object-tracking-on-point-clouds_ECCV_2022.pdf"
            current_pdf_file = n
            return n


        def load_conf_list(conf_name):
            if conf_name == "ECCV2022":
                root_dir = r"D:\py\keyan_qingbao\te_u\paper_down_load\ECCV_2022\main_paper"
                return [[i] for i in os.listdir(root_dir)]


        def look_dataframe(evt: gr.SelectData):
            global current_pdf_file
            if evt.value:
                root_dir = r"D:\py\keyan_qingbao\te_u\paper_down_load\ECCV_2022\main_paper"
                n = os.path.join(root_dir, evt.value)
                if os.path.exists(n):
                    current_pdf_file = n
            return PDF(value=current_pdf_file, label="Upload a PDF", interactive=True, height=1000)


        def filter_by_word(words, paper_list):
            word_list = words.strip().split()
            paper_list_filter = [p[0] for p in paper_list]
            for word in word_list:
                paper_list_filter = [p for p in paper_list_filter if word in p]
            return [[p] for p in paper_list_filter]


        filter_button.click(filter_by_word, inputs=[look_input, dataframe], outputs=[dataframe])
        dataframe.select(look_dataframe, inputs=None, outputs=[pdf])
        conf_button.click(load_conf_list, inputs=[conf_name], outputs=[dataframe])
        # up_button.click(up_load, inputs=None, outputs=[pdf])

demo.launch()