refine

app.py

@@ -3,10 +3,10 @@ import gradio as gr
 import pandas as pd
 
 # Load the uc_result.csv file
-uc_result_df = pd.read_csv('assets/uc_result.csv')
+uc_result_df = pd.read_csv('uc_result.csv')
 
 # Convert percentage columns to float for sorting
-percentage_columns = [col for col in uc_result_df.columns if uc_result_df[col].dtype == 'object' and '%' in uc_result_df[col].iloc[0]]
+percentage_columns = [col for col in uc_result_df.columns if '%' in str(uc_result_df[col].iloc[0])]
 for col in percentage_columns:
     uc_result_df[col] = uc_result_df[col].str.rstrip('%').astype('float') / 100
 
@@ -14,21 +14,21 @@ for col in percentage_columns:
 def filter_and_sort(method=None, sort_by=None, ascending=True):
     filtered_df = uc_result_df
     if method:
-        filtered_df = filtered_df[filtered_df['Method'].str.contains(method)]
+        filtered_df = filtered_df[filtered_df['Method'].str.contains(method, case=False, na=False)]
     if sort_by:
         filtered_df = filtered_df.sort_values(by=sort_by, ascending=ascending)
     return filtered_df
 
 # Create Gradio interface components
-method_input = gr.inputs.Textbox(label="Filter by Method", placeholder="Enter method name...")
-sort_by_dropdown = gr.inputs.Dropdown(label="Sort by", choices=uc_result_df.columns.tolist(), default=None)
-ascending_checkbox = gr.inputs.Checkbox(label="Ascending Order", value=True)
+method_input = gr.Textbox(label="Filter by Method", placeholder="Enter method name...")
+sort_by_dropdown = gr.Dropdown(label="Sort by", choices=uc_result_df.columns.tolist(), default=None)
+ascending_checkbox = gr.Checkbox(label="Ascending Order", value=True)
 
 # Create a Gradio interface to display the data
 iface = gr.Interface(
     fn=filter_and_sort,
     inputs=[method_input, sort_by_dropdown, ascending_checkbox],
-    outputs=gr.outputs.DataFrame(type="pandas"),
+    outputs=gr.DataFrame(),
     title="Enhanced UC Results Display",
     description="This interface allows filtering and sorting of the results from uc_result.csv"
 )