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import streamlit as st
import pandas as pd
import numpy as np
from streamlit_echarts import st_echarts
from streamlit.components.v1 import html
import pandas as pd
from model_information import get_dataframe
info_df = get_dataframe()
# path = "./style/Leaderboard-Rename-SeaEval.csv"
# info_df = pd.read_csv(path).dropna(axis=0)
#Model2Detail = {
# {'cross_mmlu': 'Cross-MMLU'}
#}
def draw(folder_name, category_one, category_two, sort, num_sort, model_size_range):
folder = f"./results/{folder_name}/"
data_path = f'{folder}/{category_one}/{category_two}.csv'
chart_data = pd.read_csv(data_path).dropna(axis='columns').round(3)
st.markdown("""
<style>
.stMultiSelect [data-baseweb=select] span {
max-width: 800px;
font-size: 0.9rem;
background-color: #3C6478 !important; /* Background color for selected items */
color: white; /* Change text color */
back
}
</style>
""", unsafe_allow_html=True)
# remap model names
display_model_names = {key.strip() :val.strip() for key, val in zip(info_df['Original Name'], info_df['Proper Display Name'])}
model2sizes = {key.strip() :val.strip() for key, val in zip(info_df['Original Name'], info_df['Model Size'])}
chart_data['model_show'] = chart_data['Model'].map(display_model_names)
chart_data['model_show'] = chart_data['model_show'].fillna(chart_data['Model'].apply(lambda x: x.replace('_', '-')))
chart_data['model_size'] = chart_data['Model'].map(model2sizes)
chart_data['model_size'] = chart_data['model_size'].fillna('99999')
# How to work on the model size range, filter the ones that are not in the range
if model_size_range != 'All':
if model_size_range == '<10B':
chart_data = chart_data[chart_data['model_size'].astype(float) < 10]
elif model_size_range == '10B-30B':
chart_data = chart_data[(chart_data['model_size'].astype(float) >= 10) & (chart_data['model_size'].astype(float) < 30)]
elif model_size_range == '>30B':
chart_data = chart_data[chart_data['model_size'].astype(float) >= 30]
chart_data.drop(columns=['model_size'], inplace=True)
models = st.multiselect("Please choose the model",
sorted(chart_data['model_show'].tolist()),
default = sorted(chart_data['model_show'].tolist()),
)
# if 'Select All' in st.session_state.models:
# st.session_state.models = chart_data['model_show'].tolist()
chart_data = chart_data[chart_data['model_show'].isin(models)]
if len(chart_data) == 0: return
min_value = round(min(chart_data.iloc[:, 1]) - 0.1*min(chart_data.iloc[:, 1]), 1)
max_value = round(max(chart_data.iloc[:, 1]) + 0.1*max(chart_data.iloc[:, 1]), 1)
display_names = {
'cross_mmlu' : 'Cross-MMLU',
'cross_logiqa' : 'Cross-LogiQA',
'cross_xquad' : 'Cross-XQUAD',
'sg_eval' : 'SG EVAL',
'sg_eval_v1_cleaned': 'SG EVAL V1 Cleaned',
'sg_eval_v2_mcq' : 'SG EVAL V2 MCQ',
'sg_eval_v2_open' : 'SG EVAL V2 Open Ended',
'us_eval' : 'US EVAL',
'cn_eval' : 'CN EVAL',
'ph_eval' : 'PH EVAL'
}
data_columns = [i for i in chart_data.columns if i not in ['Model', 'model_show']]
'''
Show table
'''
with st.container():
st.markdown('##### TABLE')
model_link = {key.strip(): val for key, val in zip(info_df['Proper Display Name'], info_df['Link'])}
chart_data['model_link'] = chart_data['model_show'].map(model_link)
chart_data_table = chart_data[['model_show', 'model_link'] + data_columns]
chart_data_table = chart_data_table.sort_values(
by=chart_data_table.columns[2],
ascending=False
).reset_index(drop=True)
styled_df = chart_data_table.style.highlight_max(
subset=[chart_data_table.columns[2]], color='yellow'
)
st.dataframe(
styled_df,
column_config={
'model_show': 'Model',
chart_data_table.columns[1]: {'alignment': 'center'},
"model_link": st.column_config.LinkColumn(
"Model Link",
),
},
hide_index=True,
use_container_width=True
)
# = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = =
# Initialize a session state variable for toggling the chart visibility
if "show_chart" not in st.session_state:
st.session_state.show_chart = False
# Create a button to toggle visibility
if st.button("Show Chart"):
st.session_state.show_chart = not st.session_state.show_chart
if st.session_state.show_chart:
with st.container():
st.markdown('##### CHART')
if num_sort == 'Ascending': ascend = True
else: ascend = False
chart_data = chart_data.sort_values(by=[sort], ascending=ascend).dropna(axis=0)
options = {
# "title": {"text": f"{display_names[category_two]}"},
"tooltip": {
"trigger": "axis",
"axisPointer": {"type": "cross", "label": {"backgroundColor": "#6a7985"}},
"triggerOn": 'mousemove',
},
"legend": {"data": data_columns},
"toolbox": {"feature": {"saveAsImage": {}}},
"grid": {"left": "3%", "right": "4%", "bottom": "3%", "containLabel": True},
"xAxis": [
{
"type": "category",
"boundaryGap": True,
"triggerEvent": True,
"data": chart_data['model_show'].tolist(),
}
],
"yAxis": [{"type": "value",
"min": min_value,
"max": max_value,
"boundaryGap": True
# "splitNumber": 10
}],
"series": [{
"name": f"{col}",
"type": "bar",
"data": chart_data[f'{col}'].tolist(),
} for col in data_columns],
}
events = {
"click": "function(params) { return params.value }"
}
value = st_echarts(options=options, events=events, height="500px") |