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import streamlit as st | |
from data_loader import ( | |
resutls, | |
metric_ud, | |
tasks, | |
settings, | |
task_w_settings, | |
datasets | |
) | |
if __name__ == "__main__": | |
st.set_page_config( | |
page_title="URA-LLaMa Evaluation Dashboard", | |
page_icon="π§", | |
layout="wide", | |
initial_sidebar_state="expanded", | |
) | |
st.image(["Logo BK.png", "Logo VNU-HCM.png", | |
"Logo Stanford.png"], width=120) | |
st.title("URA-LLaMa Evaluation Dashboard") | |
st.write( | |
"This dashboard is used to visualize the results of the URA-LLaMa evaluation.") | |
task = st.sidebar.selectbox( | |
"Select Task", | |
list(tasks.keys()) | |
) | |
setting = st.sidebar.selectbox( | |
"Select Setting", | |
task_w_settings[task] | |
) | |
task_id = tasks[task] | |
dataset = st.sidebar.selectbox( | |
"Select Dataset", | |
list(datasets[task_id].values()) | |
) | |
result_id = f"{task_id}-{settings[setting]}" | |
result_sheet = resutls[result_id][dataset] | |
# Visualize the data stored as a pandas dataframe | |
st.dataframe(result_sheet) | |