import re import streamlit as st import requests import pandas as pd from io import StringIO import plotly.graph_objs as go from yall import create_yall def convert_markdown_table_to_dataframe(md_content): """ Converts markdown table to Pandas DataFrame, handling special characters and links, extracts Hugging Face URLs, and adds them to a new column. """ # Remove leading and trailing | characters cleaned_content = re.sub(r'\|\s*$', '', re.sub(r'^\|\s*', '', md_content, flags=re.MULTILINE), flags=re.MULTILINE) # Create DataFrame from cleaned content df = pd.read_csv(StringIO(cleaned_content), sep="\|", engine='python') # Remove the first row after the header df = df.drop(0, axis=0) # Strip whitespace from column names df.columns = df.columns.str.strip() # Extract Hugging Face URLs and add them to a new column model_link_pattern = r'\[(.*?)\]\((.*?)\)\s*\[.*?\]\(.*?\)' df['URL'] = df['Model'].apply(lambda x: re.search(model_link_pattern, x).group(2) if re.search(model_link_pattern, x) else None) # Clean Model column to have only the model link text df['Model'] = df['Model'].apply(lambda x: re.sub(model_link_pattern, r'\1', x)) return df def create_bar_chart(df, category): """Create and display a bar chart for a given category.""" st.write(f"### {category} Scores") # Sort the DataFrame based on the category score sorted_df = df[['Model', category]].sort_values(by=category, ascending=True) # Create the bar chart with color gradient fig = go.Figure(go.Bar( x=sorted_df[category], y=sorted_df['Model'], orientation='h', marker=dict(color=sorted_df[category], colorscale='Magma') )) # Update layout for better readability fig.update_layout( xaxis_title=category, yaxis_title="Model", margin=dict(l=20, r=20, t=20, b=20) ) st.plotly_chart(fig, use_container_width=True) def main(): st.set_page_config(page_title="YALL - Yet Another LLM Leaderboard", layout="wide") st.title("🏆 YALL - Yet Another LLM Leaderboard") st.markdown("Leaderboard made with [🧐 LLM AutoEval](https://github.com/mlabonne/llm-autoeval) using [Nous](https://huggingface.co/NousResearch) benchmark suite. It's a collection of my own evaluations.") content = create_yall() if content: try: score_columns = ['Average', 'AGIEval', 'GPT4All', 'TruthfulQA', 'Bigbench'] # Display dataframe df = convert_markdown_table_to_dataframe(content) for col in score_columns: df[col] = pd.to_numeric(df[col].str.strip(), errors='coerce') st.dataframe(df, use_container_width=True) # Full-width plot for the first category create_bar_chart(df, score_columns[0]) # Next two plots in two columns col1, col2 = st.columns(2) with col1: create_bar_chart(df, score_columns[1]) with col2: create_bar_chart(df, score_columns[2]) # Last two plots in two columns col3, col4 = st.columns(2) with col3: create_bar_chart(df, score_columns[3]) with col4: create_bar_chart(df, score_columns[4]) except Exception as e: st.error("An error occurred while processing the markdown table.") st.error(str(e)) else: st.error("Failed to download the content from the URL provided.") if __name__ == "__main__": main()