Update app.py

app.py

@@ -250,7 +250,6 @@
 import streamlit as st
 import pandas as pd
 import altair as alt
-from st_aggrid import AgGrid, GridOptionsBuilder
 
 # Set page layout to wide mode
 st.set_page_config(
@@ -293,27 +292,25 @@ filtered_df = df[
     (df['Method'].str.contains(search_query, case=False, na=False))
 ]
 
-# Main Leaderboard Section
+# Manual Pagination Section
 st.subheader("Leaderboard Table")
 if filtered_df.empty:
     st.warning("No results found. Try adjusting the filters.")
 else:
-    # Interactive table with AgGrid
-    records_per_page = st.selectbox("Records per Page", [10, 20, 50, 100], index=0)
-    gb = GridOptionsBuilder.from_dataframe(filtered_df)
-    gb.configure_pagination(paginationAutoPageSize=False, paginationPageSize=records_per_page)
-    gb.configure_default_column(editable=False, groupable=True)
-    grid_options = gb.build()
-    
-    st.markdown("### Interactive Table")
-    AgGrid(
-        filtered_df,
-        gridOptions=grid_options,
-        enable_enterprise_modules=False,
-        theme='streamlit',
-        height=400,  # Adjust as needed
-        fit_columns_on_grid_load=True
+    # Pagination controls
+    page_size = st.sidebar.selectbox("Rows per page", [10, 20, 50], index=0)
+    page_number = st.sidebar.number_input(
+        "Page number",
+        min_value=1,
+        max_value=(len(filtered_df) // page_size) + 1,
+        step=1,
+        value=1
     )
+    start_index = (page_number - 1) * page_size
+    end_index = start_index + page_size
+
+    # Paginated table
+    st.dataframe(filtered_df.iloc[start_index:end_index], use_container_width=True)
 
     # Visualization of selected metric
     st.subheader("Performance Metrics Visualization")
@@ -331,7 +328,7 @@ else:
     )
     st.altair_chart(chart, use_container_width=True)
 
-    # Interactive Bubble Plot: Metric vs. Model Size
+    # Bubble Plot: Metric vs. Model Size
     st.subheader("Interactive Bubble Plot: Metric vs. Model Size")
     bubble_metric = st.selectbox("Select Metric for Bubble Plot", options=filtered_df.columns[5:], index=0)