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| import gradio as gr | |
| import pandas as pd | |
| 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") | |
| # Define the remove_criteria_input TextBox | |
| remove_criteria_input = gr.Textbox(label="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) |