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import asyncio
import streamlit as st
import pandas as pd
from typing import Optional, List, Set, Tuple
from .components.filters import render_table_filters
from .components.visualizations import (
render_leaderboard_table,
render_performance_plots,
)
from .components.header import render_header, render_contribution_guide
from .services.firebase import fetch_leaderboard_data
from .core.styles import CUSTOM_CSS
def get_filter_values(
df: pd.DataFrame,
) -> tuple[
List[str],
List[str],
List[str],
List[str],
List[str],
Tuple[int, int],
Tuple[int, int],
Tuple[int, int],
List[str],
int,
]:
"""Get unique values for filters"""
models = sorted(df["Model ID"].unique().tolist())
platforms = sorted(df["Platform"].unique().tolist())
devices = sorted(df["Device"].unique().tolist())
cache_type_v = sorted(df["cache_type_v"].unique().tolist())
cache_type_k = sorted(df["cache_type_k"].unique().tolist())
n_threads = (df["n_threads"].min(), df["n_threads"].max())
max_n_gpu_layers = (0, max(df["n_gpu_layers"].unique().tolist()))
pp_range = (df["PP Config"].min(), df["PP Config"].max())
tg_range = (df["TG Config"].min(), df["TG Config"].max())
versions = sorted(df["Version"].unique().tolist())
return (
models,
platforms,
devices,
cache_type_v,
cache_type_k,
pp_range,
tg_range,
n_threads,
versions,
max_n_gpu_layers,
)
async def main():
"""Main application entry point"""
st.set_page_config(
page_title="AI Phone Benchmark Leaderboard",
page_icon="📱",
layout="wide",
)
# Apply custom styles
st.markdown(CUSTOM_CSS, unsafe_allow_html=True)
# Fetch initial data
df = await fetch_leaderboard_data()
if df.empty:
st.error("No data available. Please check your connection and try again.")
return
# Render header
render_header()
# Get unique values for filters
(
models,
platforms,
devices,
cache_type_v,
cache_type_k,
pp_range,
tg_range,
n_threads,
versions,
max_n_gpu_layers,
) = get_filter_values(df)
# Create main layout with sidebar for contribution guide
# Adjust column ratio based on guide visibility
if "show_guide" not in st.session_state:
st.session_state.show_guide = True
main_col, guide_col = st.columns(
[
0.9 if not st.session_state.show_guide else 0.8,
0.1 if not st.session_state.show_guide else 0.2,
]
)
with main_col:
# Render filters
table_filters = render_table_filters(
models,
platforms,
devices,
cache_type_v,
cache_type_k,
pp_range,
tg_range,
n_threads,
versions,
max_n_gpu_layers,
)
# Render the main leaderboard table
render_leaderboard_table(df, table_filters)
# Render plot section
st.markdown("---")
st.title("📊 Performance Comparison")
# Plot specific selectors in a row
plot_col1, plot_col2, plot_col3 = st.columns(3)
with plot_col1:
plot_model = st.selectbox(
"Select Model for Comparison", options=models, key="plot_model_selector"
)
with plot_col2:
plot_pp = st.selectbox(
"Select PP Config for Comparison",
options=sorted([int(x) for x in df["PP Config"].unique()]),
key="plot_pp_selector",
)
with plot_col3:
plot_tg = st.selectbox(
"Select TG Config for Comparison",
options=sorted([int(x) for x in df["TG Config"].unique()]),
key="plot_tg_selector",
)
# Create plot filters based on table filters but override the model and configs
plot_filters = table_filters.copy()
plot_filters["model"] = plot_model
plot_filters["pp_range"] = (plot_pp, plot_pp) # Set exact PP value
plot_filters["tg_range"] = (plot_tg, plot_tg) # Set exact TG value
render_performance_plots(df, plot_filters)
with guide_col:
render_contribution_guide()
if __name__ == "__main__":
asyncio.run(main())
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