import gradio as gr import pandas as pd import csv def update_scores(winner_score, loser_score, k_factor=100): score_difference = k_factor / (winner_score / loser_score) return winner_score + score_difference, loser_score - score_difference def prepare_dataframe(opponents_df, criteria_df, additional_columns=None): columns = ["descriptor", "opponent"] + [f"{c}_score" for c in criteria_df["criteria"]] + ["overall_score"] if additional_columns: columns += additional_columns return opponents_df[columns] if not opponents_df.empty else pd.DataFrame(columns=columns) def clean_string(s): return " ".join(word.capitalize() for word in s.strip().replace(" ", " ").lower().split()) def display_dataframe(df, sort_column, file_name): df = df.sort_values(by=sort_column, ascending=False) df.to_csv(file_name, index=False) return df def update_criteria_ratings(first, second, criteria_df, is_positive): winner, loser = (first, second) if is_positive else (second, first) winner_score, loser_score = update_scores( criteria_df.at[winner, 'score'], criteria_df.at[loser, 'score'] ) criteria_df.at[winner, 'score'], criteria_df.at[loser, 'score'] = winner_score, loser_score return criteria_df def update_opponent_ratings(first, second, criterion, opponents_df, criteria_df, is_positive): winner, loser = (first, second) if is_positive else (second, first) winner_score, loser_score = update_scores( opponents_df.at[winner, f"{criterion}_score"], opponents_df.at[loser, f"{criterion}_score"] ) opponents_df.at[winner, f"{criterion}_score"], opponents_df.at[loser, f"{criterion}_score"] = winner_score, loser_score return calculate_overall_scores(opponents_df, criteria_df) def calculate_overall_scores(opponents_df, criteria_df): criteria_scores = criteria_df.set_index("criteria")["score"] criteria_list = criteria_df["criteria"] def compute_score(row): total_score = sum(row[f"{c}_score"] * criteria_scores[c] for c in criteria_list) total_weight = sum(criteria_scores[c] for c in criteria_list) return total_score / total_weight if total_weight else 0 opponents_df["overall_score"] = opponents_df.apply(compute_score, axis=1) return opponents_df def handle_vote(first, second, criteria, opponents_df, criteria_df, is_symbolic_func, data_file): data_frame = is_symbolic_func(first, second, criteria, opponents_df, criteria_df) data_frame = display_dataframe(data_frame, 'overall_score', data_file) return get_vote_start_data(opponents_df, criteria_df) def get_vote_start_data(opponents_df, criteria_df): if len(opponents_df) > 1 and len(criteria_df) > 0: sample = opponents_df.sample(n=2) first_string = sample.iloc[0]["descriptor"] + " - " + sample.iloc[0]["opponent"] second_string = sample.iloc[1]["descriptor"] + " - " + sample.iloc[1]["opponent"] criterion = criteria_df.sample(n=1)["criteria"].values[0] return f"Which better reflects '{criterion}': '{first_string}' or '{second_string}'?", first_string, second_string, criterion return "Add more options and criteria to start voting!", "", "", "" def handle_criteria_vote(first, second, criteria_df, is_positive): criteria_df = update_criteria_ratings(first, second, criteria_df, is_positive) criteria_df = display_dataframe(criteria_df, 'score', 'criteria_df.csv') return get_criteria_vote_start(criteria_df) def get_criteria_vote_start(criteria_df): if len(criteria_df) > 1: sample = criteria_df.sample(n=2) first_string, second_string = sample.iloc[0]["criteria"], sample.iloc[1]["criteria"] return f"Is '{first_string}' more important than '{second_string}'?", first_string, second_string return "Add more criteria to start ranking!", "", "" theme = gr.themes.Soft(primary_hue="red", secondary_hue="blue") with gr.Blocks(theme=theme) as app: gr.Markdown("""## Preference-based Elo Ranker""") with gr.Tab("Criteria Ranking"): gr.Markdown("### Rank Criteria") criteria_input = gr.Textbox(label="Criteria") add_criteria_button = gr.Button("Add Criteria") remove_criteria_button = gr.Button("Remove Criteria") criteria_df = pd.DataFrame(columns=['score', 'criteria']) criteria_rankings = gr.DataFrame(value=criteria_df, interactive=False, headers=["Score", "Criteria"]) criteria_compare_output = gr.Textbox("Add some criteria to start ranking!", label="Comparison", interactive=False) criteria_yes_button = gr.Button("Yes", variant="secondary") criteria_no_button = gr.Button("No", variant="primary") criteria_new_vote = gr.Button("New Vote") add_criteria_button.click(lambda _: add_criteria(criteria_input, criteria_rankings), inputs=[criteria_input, criteria_rankings], outputs=[criteria_input, criteria_rankings]) remove_criteria_button.click(lambda _: remove_criteria(clean_string(remove_criteria_input.value), criteria_rankings), inputs=[remove_criteria_input, criteria_rankings], outputs=criteria_rankings) criteria_yes_button.click(lambda first, second: handle_criteria_vote(first, second, criteria_rankings, True), inputs=[criteria_input, criteria_input], outputs=[criteria_compare_output, criteria_input, criteria_input]) criteria_no_button.click(lambda first, second: handle_criteria_vote(first, second, criteria_rankings, False), inputs=[criteria_input, criteria_input], outputs=[criteria_compare_output, criteria_input, criteria_input]) criteria_new_vote.click(lambda data_frame: get_criteria_vote_start(data_frame), inputs=[criteria_rankings], outputs=[criteria_compare_output, criteria_input, criteria_input]) with gr.Tab("Opponent Ranking"): opponents_df = pd.DataFrame(columns=["descriptor", "opponent"] + [f"{c}_score" for c in criteria_df["criteria"]] + ["overall_score"]) rankings = gr.DataFrame(value=opponents_df, interactive=False, headers=["Descriptor", "Opponent"] + [f"{c} Score" for c in criteria_df["criteria"]] + ["Overall Score"]) compare_output = gr.Textbox("Add some options to start voting!", label="Comparison", interactive=False) yes_button = gr.Button("1", variant="secondary") no_button = gr.Button("2", variant="primary") criteria_output = gr.Textbox(label="Criteria", interactive=False) new_vote = gr.Button("New Vote") descriptor_input = gr.Textbox(label="Descriptor") opponent_input = gr.Textbox(label="Opponent") add_button = gr.Button("Add Opponent") add_button.click(lambda: add_and_compare(clean_string(descriptor_input.value), clean_string(opponent_input.value), rankings, criteria_rankings), inputs=[descriptor_input, opponent_input, rankings, criteria_rankings], outputs=[descriptor_input, opponent_input, rankings]) remove_descriptor_input = gr.Textbox(label="Descriptor") remove_opponent_input = gr.Textbox(label="Opponent") remove_button = gr.Button("Remove Opponent") remove_button.click(lambda _, __: remove_opponent(remove_descriptor_input, remove_opponent_input, rankings), inputs=[remove_descriptor_input, remove_opponent_input, rankings], outputs=rankings) yes_button.click(lambda first, second, crit, opp_df, crit_df: handle_vote(first, second, crit, opp_df, crit_df, update_opponent_ratings, True, "opponents_df.csv"), inputs=[compare_output, compare_output, criteria_output, rankings, criteria_rankings], outputs=[compare_output, compare_output, compare_output, criteria_output, rankings]) no_button.click(lambda first, second, crit, opp_df, crit_df: handle_vote(first, second, crit, opp_df, crit_df, update_opponent_ratings, False, "opponents_df.csv"), inputs=[compare_output, compare_output, criteria_output, rankings, criteria_rankings], outputs=[compare_output, compare_output, compare_output, criteria_output, rankings]) new_vote.click(lambda opp_df, crit_df: get_vote_start_data(opp_df, crit_df), inputs=[rankings, criteria_rankings], outputs=[compare_output, compare_output, compare_output, criteria_output, rankings]) app.launch(share=False)