Create app.py

app.py

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+from __future__ import annotations
+import gradio as gr
+import numpy as np
+import pandas as pd
+import requests
+from huggingface_hub.hf_api import SpaceInfo
+
+SHEET_ID = '1J_AEBo7l0gtfKSbMLlblY69IXp70UmfBLGW2ZtR_z_c'
+SHEET_NAME = 'model'
+csv_url = f'https://docs.google.com/spreadsheets/d/{SHEET_ID}/gviz/tq?tqx=out:csv&sheet={SHEET_NAME}'
+
+class ModelList:
+    def __init__(self):
+        self.table = pd.read_csv(csv_url)
+        self.table = self.table.astype({'Year':'string'})
+        self._preprocess_table()
+
+        self.table_header = '''
+            <tr>
+                <td width="20%">Title</td>
+                <td width="10%">Link</td>
+                <td width="10%">Tags</td>
+            </tr>'''
+
+    def _preprocess_table(self) -> None:
+        self.table['name_lowercase'] = self.table['Title'].str.lower()
+
+        rows = []
+        for row in self.table.itertuples():
+            source = f'<a href="{row.Link}" target="_blank">Link</a>' if isinstance(
+                row.Source, str) else ''
+            row = f'''
+                <tr>
+                    <td>{row.Title}</td>
+                    <td>{source}</td>
+                    <td>{row.Tags}</td>
+                </tr>'''
+            rows.append(row)
+        self.table['html_table_content'] = rows
+
+    def render(self, search_query: str, 
+            case_sensitive: bool,
+            filter_names: list[str],
+           ) -> tuple[int, str]:
+        df = self.table
+        if search_query:
+            if case_sensitive:
+                df = df[df.Title.str.contains(search_query)]
+            else:
+                df = df[df.name_lowercase.str.contains(search_query.lower())]
+        df = self.filter_table(df, filter_names)
+        result = self.to_html(df, self.table_header)
+        return result
+
+    @staticmethod
+    def filter_table(df: pd.DataFrame, filter_names: list[str]) -> pd.DataFrame:
+        df = df[df.Tags.str.contains(filter_names)]
+        return df
+
+    @staticmethod
+    def to_html(df: pd.DataFrame, table_header: str) -> str:
+        table_data = ''.join(df.html_table_content)
+        html = f'''
+        <table>
+            {table_header}
+            {table_data}
+        </table>'''
+        return html
+model_list = ModelList()
+with gr.Blocks() as demo:   
+            search_box = gr.Textbox(label='Search Title',placeholder='You can search for titles with regular expressions. e.g. (?<!sur)face',max_lines=1)
+            case_sensitive = gr.Checkbox(label='Case Sensitive')
+            filter_names1 = gr.CheckboxGroup(choices=['Filter A','Filter B ', 'Filer C'], value=['Filter A','Filter B ', 'Filer C'], label='Filter Tags')
+            search_button = gr.Button('Search')
+            table = gr.HTML(show_label=False)
+            demo.load(fn=model_list.render, inputs=[search_box, case_sensitive, filter_names1, data_types1,],outputs=[table,])
+            search_box.submit(fn=model_list.render, inputs=[search_box, case_sensitive, filter_names1, data_types1,], outputs=[table,])
+            search_button.click(fn=model_list.render, inputs=[search_box, case_sensitive, filter_names1, data_types1,], outputs=[table,])
+demo.queue()
+demo.launch(share=False)