Create app.py

app.py

@@ -0,0 +1,125 @@
+import gradio as gr
+import pandas as pd
+
+
+SHEET_ID = '1eaqWOSqNAY64E8jce5R8APAe12WFGga7f0xK3Ygt9HY'
+SHEET_NAME = 'Sheet1'
+csv_url = f'https://docs.google.com/spreadsheets/d/{SHEET_ID}/gviz/tq?tqx=out:csv&sheet={SHEET_NAME}'
+
+class DataList:
+    def __init__(self):
+        self.table = pd.read_csv(csv_url)
+        self._preprocess_table()
+
+        self.table_header = '''
+            <tr>
+                <td width="12%">Name</td>
+                <td width="52%">Description</td>
+                <td width="12%">Module</td>
+                <td width="12%">Type</td>
+                <td width="12%">Alignment with Key Guidance</td>
+            </tr>'''
+
+    def _preprocess_table(self) -> None:
+        self.table['name_lowercase'] = self.table['Name'].str.lower()
+
+        rows = []
+        for row in self.table.itertuples():
+            source = f'<a href="{row.URL}" target="_parent">{row.Name}</a>' if isinstance(
+                row.URL, str) else '{row.Name}'
+            row = f'''
+                <tr>
+                    <td>{source}</td>
+                    <td>{row.Description}</td>
+                    <td>{row.Module}</td>
+                    <td>{row.Type}</td>
+                    <td>{row.Alignment}</td>
+                </tr>'''
+            rows.append(row)
+        self.table['html_table_content'] = rows
+
+    def render(self, search_query: str,
+            filter_names: list[str],
+            filter_names2: list[str],
+            filter_names3: list[str]
+            ) -> tuple[int, str]:
+        self.table = pd.read_csv(csv_url)
+        self._preprocess_table()
+
+        self.table_header = '''
+            <tr>
+                <td width="12%">Name</td>
+                <td width="52%">Description</td>
+                <td width="12%">Module</td>
+                <td width="12%">Type</td>
+                <td width="12%">Alignment with Key Guidance</td>
+            </tr>'''
+        df = self.table
+        if search_query:
+                df = df[df.name_lowercase.str.contains(search_query.lower())]
+        df = self.filter_table(df, filter_names,filter_names2,filter_names3)
+        result = self.to_html(df, self.table_header)
+        return result
+
+    @staticmethod
+    def filter_table(df: pd.DataFrame, filter_names: list[str], filter_names2: list[str], filter_name3: list[str],) -> pd.DataFrame:
+        df = df.loc[df.Type.isin(set(filter_names))]
+        print(filter_name3)
+        vals= filter_names3
+        df = df.loc[df.Module.isin(vals)]
+        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
+
+
+data_list = DataList()
+
+css = """
+button.svelte-kqij2n{font-weight: bold !important;
+background-color: #ebecf0;
+color: black;
+margin-left: 5px;}
+#tlsnlbs{}
+#mtcs{}
+#mdls{}
+#dts{}
+.svelte-kqij2n .selected {
+    background-color: black;
+    color: white;
+}
+.app.svelte-182fdeq.svelte-182fdeq {
+padding: 0 !important;
+}
+span.svelte-s1r2yt{font-weight: bold !important;
+}
+"""
+with gr.Blocks(css=css) as demo:
+    with gr.Row():
+        search_box = gr.Textbox( label='Search Name', placeholder='You can search for titles with regular expressions. e.g. (?<!sur)face',max_lines=1, scale = 5)  
+    with gr.Row():
+        with gr.Column(scale=1):
+            filter_names = gr.CheckboxGroup(choices=['Guidebook','Assessment Tool','Training and Education',], value=['Guidebook','Assessment Tool','Training and Education',], label='Type')
+        with gr.Column(scale=1):
+            filter_names2 = gr.CheckboxGroup(choices=['NIST AI RMF MAP','NIST AI RMF GOVERN','ISO 42001 A.8',], value=['NIST AI RMF MAP','NIST AI RMF GOVERN','ISO 42001 A.8',], label='Alignment with Key Guidance')
+    with gr.Row():
+        filter_names3 = gr.CheckboxGroup(choices=['Compliance and Regulatory Guidance', 'Generative AI', 'Suppliers and Procurement', 'Policy and Governance', 'Assessing AI Systems',], value=['Compliance and Regulatory Guidance', 'Generative AI', 'Suppliers and Procurement', 'Policy and Governance', 'Assessing AI Systems',], label='Modules', interactive = True)
+    with gr.Row():
+        search_button = gr.Button('Search', size = 'sm', scale =1)
+
+    with gr.Row():
+        table = gr.HTML(show_label=False)
+        
+    demo.load(fn=data_list.render, inputs=[search_box, filter_names,filter_names2,filter_names3,],outputs=[table,])
+    search_box.submit(fn=data_list.render, inputs=[search_box, filter_names,filter_names2,filter_names3,], outputs=[table,])
+    search_button.click(fn=data_list.render, inputs=[search_box, filter_names,filter_names2,filter_names3,], outputs=[table,])    
+
+demo.queue()
+demo.launch(share=False)