import gradio as gr import pandas as pd import re import csv def update_scores(winner, loser, k_factor=100): score_difference = int(k_factor / (winner / loser)) winner += score_difference loser -= score_difference return winner, loser def vote_startup_criteria(criteria_df): if len(criteria_df) > 1: sample = criteria_df.sample(n=2) first_string = sample.iloc[0]["criteria"] second_string = sample.iloc[1]["criteria"] return f"Is '{first_string}' more important than '{second_string}'?", first_string, second_string, display_criteria_rankings(criteria_df) else: return "Add more criteria to start ranking!", "", "", display_criteria_rankings(criteria_df) def vote_startup_opponents(opponents_df, criteria_df): try: opponents_df = opponents_df[["descriptor", "opponent"] + [f"{c}_score" for c in criteria_df["criteria"]] + ["overall_score"]] except: opponents_df = pd.DataFrame(columns=["descriptor", "opponent"] + [f"{c}_score" for c in criteria_df["criteria"]] + ["overall_score"]) if len(opponents_df) > 0: if len(opponents_df) > 10: slice_size = 4 slice = int(len(opponents_df) / slice_size) sample = opponents_df[slice:(slice_size - 1) * slice].sample(frac=1).iloc[0] opponent, descriptor = sample["opponent"], sample["descriptor"] else: sample = opponents_df.sample(frac=1).iloc[0] opponent, descriptor = sample["opponent"], sample["descriptor"] if len(opponents_df) > 1: sample = opponents_df.sample(frac=1) comparison_opponent = sample.iloc[0] if comparison_opponent['opponent'] == opponent and comparison_opponent['descriptor'] == descriptor: comparison_opponent = sample.iloc[1] first_df = opponents_df[opponents_df["opponent"] == opponent][opponents_df["descriptor"] == descriptor] first_string = first_df["opponent"].tolist()[0] + " - " + first_df["descriptor"].tolist()[0] second_df = comparison_opponent second_string = second_df["opponent"] + " - " + second_df["descriptor"] criteria = criteria_df.sample(n=1)["criteria"].values[0] return f"Which opponent better represents '{criteria}': '{descriptor} - {opponent}' or '{comparison_opponent['descriptor']} - {comparison_opponent['opponent']}'?", first_string, second_string, criteria, display_rankings(opponents_df, criteria_df) else: return "Add some opponents to start voting!", "", "", "", display_rankings(opponents_df, criteria_df) def clean_string(string): string = string.strip().replace(" ", " ").lower() string = " ".join([x[0].upper() + x[1:] for x in string.split()]) return string def add_and_compare(descriptor, opponent, opponents_df, criteria_df): try: opponents_df = opponents_df[["descriptor", "opponent"] + [f"{c}_score" for c in criteria_df["criteria"]] + ["overall_score"]] except: opponents_df = pd.DataFrame(columns=["descriptor", "opponent"] + [f"{c}_score" for c in criteria_df["criteria"]] + ["overall_score"]) if descriptor != "" and opponent != "": descriptor = clean_string(descriptor) opponent = clean_string(opponent) new_opponent = pd.DataFrame({'descriptor': [descriptor], 'opponent': [opponent]}) for c in criteria_df["criteria"]: new_opponent[f"{c}_score"] = 1000 new_opponent["overall_score"] = 1000 opponents_df = pd.concat([opponents_df, new_opponent], ignore_index=True) opponents_df.to_csv("opponents_df.csv") opponents_df = opponents_df[["descriptor", "opponent"] + [f"{c}_score" for c in criteria_df["criteria"]] + ["overall_score"]] return "", "", display_rankings(opponents_df, criteria_df) def update_ratings_pos(first_string, second_string, criteria, opponents_df, criteria_df): try: opponents_df = opponents_df[["descriptor", "opponent"] + [f"{c}_score" for c in criteria_df["criteria"]] + ["overall_score"]] except: opponents_df = pd.DataFrame(columns=["descriptor", "opponent"] + [f"{c}_score" for c in criteria_df["criteria"]] + ["overall_score"]) if len(opponents_df) == 0: return "Add some opponents to start voting!", "", "", "", display_rankings(opponents_df, criteria_df) if first_string != "": opponents_df["combined"] = opponents_df["opponent"] + " - " + opponents_df["descriptor"] loser = opponents_df[opponents_df["combined"] == second_string] winner = opponents_df[opponents_df["combined"] == first_string] winner_score, loser_score = update_scores(winner[f"{criteria}_score"].values[0], loser[f"{criteria}_score"].values[0]) opponents_df.at[winner.index[0], f"{criteria}_score"] = winner_score opponents_df.at[loser.index[0], f"{criteria}_score"] = loser_score opponents_df = calculate_overall_scores(opponents_df, criteria_df) opponents_df.to_csv("opponents_df.csv") return vote_startup_opponents(opponents_df, criteria_df) def update_ratings_neg(first_string, second_string, criteria, opponents_df, criteria_df): try: opponents_df = opponents_df[["descriptor", "opponent"] + [f"{c}_score" for c in criteria_df["criteria"]] + ["overall_score"]] except: opponents_df = pd.DataFrame(columns=["descriptor", "opponent"] + [f"{c}_score" for c in criteria_df["criteria"]] + ["overall_score"]) if len(opponents_df) == 0: return "Add some opponents to start voting!", "", "", "", display_rankings(opponents_df, criteria_df) if first_string != "": opponents_df["combined"] = opponents_df["opponent"] + " - " + opponents_df["descriptor"] loser = opponents_df[opponents_df["combined"] == first_string] winner = opponents_df[opponents_df["combined"] == second_string] winner_score, loser_score = update_scores(winner[f"{criteria}_score"].values[0], loser[f"{criteria}_score"].values[0]) opponents_df.at[winner.index[0], f"{criteria}_score"] = winner_score opponents_df.at[loser.index[0], f"{criteria}_score"] = loser_score opponents_df = calculate_overall_scores(opponents_df, criteria_df) opponents_df.to_csv("opponents_df.csv") return vote_startup_opponents(opponents_df, criteria_df) def display_rankings(opponents_df, criteria_df): opponents_df = opponents_df.sort_values(by='overall_score', ascending=False) opponents_df = opponents_df[["descriptor", "opponent"] + [f"{c}_score" for c in criteria_df["criteria"]] + ["overall_score"]] opponents_df.to_csv("opponents_df.csv") return opponents_df def export_csv(opponents_df): save_df = opponents_df save_df.to_csv("opponents_df.csv") return "opponents_df.csv" def import_csv(file, opponents_df, criteria_df): if file is not None: new_df = pd.read_csv(file) try: opponents_df = opponents_df[["descriptor", "opponent"] + [f"{c}_score" for c in criteria_df["criteria"]] + ["overall_score"]] except: opponents_df = pd.DataFrame(columns=["descriptor", "opponent"] + [f"{c}_score" for c in criteria_df["criteria"]] + ["overall_score"]) new_df = new_df[["descriptor", "opponent"] + [f"{c}_score" for c in criteria_df["criteria"]] + ["overall_score"]] opponents_df = pd.concat([opponents_df, new_df]) opponents_df = opponents_df.drop_duplicates(subset=['descriptor', 'opponent']) return opponents_df def remove_opponent(descriptor, opponent, opponents_df): descriptor = clean_string(descriptor) opponent = clean_string(opponent) opponents_df = opponents_df[~((opponents_df["descriptor"] == descriptor) & (opponents_df["opponent"] == opponent))] return opponents_df[["descriptor", "opponent"] + [f"{c}_score" for c in criteria_df["criteria"]] + ["overall_score"]] def reset_rankings(opponents_df, criteria_df): for c in criteria_df["criteria"]: opponents_df[f"{c}_score"] = 1000 opponents_df["overall_score"] = 1000 opponents_df = opponents_df[["descriptor", "opponent"] + [f"{c}_score" for c in criteria_df["criteria"]] + ["overall_score"]] return display_rankings(opponents_df, criteria_df) def clear_rankings(opponents_df, criteria_df): opponents_df = pd.DataFrame(columns=["descriptor", "opponent"] + [f"{c}_score" for c in criteria_df["criteria"]] + ["overall_score"]) return display_rankings(opponents_df, criteria_df) def add_criteria(criteria, criteria_df): if criteria != "": criteria = clean_string(criteria) new_criteria = pd.DataFrame({'criteria': [criteria], 'score': [1000]}) criteria_df = pd.concat([criteria_df, new_criteria], ignore_index=True) criteria_df.to_csv("criteria_df.csv") criteria_df = criteria_df[["score", "criteria"]] criteria_df = criteria_df.dropna() return "", display_criteria_rankings(criteria_df) def remove_criteria(criteria, criteria_df): criteria = clean_string(criteria) criteria_df = criteria_df[criteria_df["criteria"] != criteria] return display_criteria_rankings(criteria_df) def update_criteria_ratings_pos(first_string, second_string, criteria_df): if len(criteria_df) == 0: return "Add some criteria to start ranking!", "", "", display_criteria_rankings(criteria_df) if first_string != "": loser = criteria_df[criteria_df["criteria"] == second_string] winner = criteria_df[criteria_df["criteria"] == first_string] winner_score, loser_score = update_scores(winner['score'].values[0], loser['score'].values[0]) criteria_df.at[winner.index[0], 'score'] = winner_score criteria_df.at[loser.index[0], 'score'] = loser_score criteria_df = criteria_df.sort_values(by='score', ascending=False) criteria_df.to_csv("criteria_df.csv") return vote_startup_criteria(criteria_df) def update_criteria_ratings_neg(first_string, second_string, criteria_df): if len(criteria_df) == 0: return "Add some criteria to start ranking!", "", "", display_criteria_rankings(criteria_df) if first_string != "": loser = criteria_df[criteria_df["criteria"] == first_string] winner = criteria_df[criteria_df["criteria"] == second_string] winner_score, loser_score = update_scores(winner['score'].values[0], loser['score'].values[0]) criteria_df.at[winner.index[0], 'score'] = winner_score criteria_df.at[loser.index[0], 'score'] = loser_score criteria_df = criteria_df.sort_values(by='score', ascending=False) criteria_df.to_csv("criteria_df.csv") return vote_startup_criteria(criteria_df) def display_criteria_rankings(criteria_df): criteria_df = criteria_df.sort_values(by='score', ascending=False) criteria_df = criteria_df[["score", "criteria"]] criteria_df.to_csv("criteria_df.csv") return criteria_df def calculate_overall_scores(opponents_df, criteria_df): criteria_scores = criteria_df.set_index("criteria")["score"] new_scores = [] for _, row in opponents_df.iterrows(): overall_score = 0 total_weight = 0 for c in criteria_df["criteria"]: weight = criteria_scores[c] score = row[f"{c}_score"] overall_score += weight * score total_weight += weight # opponents_df.at[row.name, "overall_score"] = overall_score / total_weight score = overall_score / total_weight new_scores.append(score) opponents_df["overall_score"] = new_scores return opponents_df theme = gr.themes.Soft(primary_hue="red", secondary_hue="blue") with gr.Blocks(theme=theme) as app: gr.Markdown( """## Preference-based Elo Ranker This tool helps you create **accurate rankings** of things based on your personal preferences. It does this by asking you questions comparing a random pair of your inputs, and then using your answers to calculate Elo scores for ranking. """ ) with gr.Tab("Criteria Ranking"): gr.Markdown( """### Rank Criteria Add and rank the criteria that will be used to evaluate the opponents. """ ) with gr.Row(): criteria_input = gr.Textbox(label="Criteria") add_criteria_button = gr.Button("Add Criteria") with gr.Row(): 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"]) with gr.Row(): criteria_compare_output = gr.Textbox("Add some criteria to start ranking!", label="Comparison", interactive=False) with gr.Row(): criteria_yes_button = gr.Button("Yes", variant="secondary") criteria_no_button = gr.Button("No", variant="primary") with gr.Row(): with gr.Column(): criteria_compare_index_1 = gr.Textbox(label="", interactive=False, visible=False) with gr.Column(): criteria_compare_index_2 = gr.Textbox(label="", interactive=False, visible=False) criteria_new_vote = gr.Button("New Vote") add_criteria_button.click(add_criteria, inputs=[criteria_input, criteria_rankings], outputs=[criteria_input, criteria_rankings]) remove_criteria_button.click(remove_criteria, inputs=[remove_criteria_input, criteria_rankings], outputs=criteria_rankings) criteria_yes_button.click(update_criteria_ratings_pos, inputs=[criteria_compare_index_1, criteria_compare_index_2, criteria_rankings], outputs=[criteria_compare_output, criteria_compare_index_1, criteria_compare_index_2, criteria_rankings]) criteria_no_button.click(update_criteria_ratings_neg, inputs=[criteria_compare_index_1, criteria_compare_index_2, criteria_rankings], outputs=[criteria_compare_output, criteria_compare_index_1, criteria_compare_index_2, criteria_rankings]) criteria_new_vote.click(vote_startup_criteria, inputs=[criteria_rankings], outputs=[criteria_compare_output, criteria_compare_index_1, criteria_compare_index_2, criteria_rankings]) with gr.Tab("Opponent Ranking"): with gr.Row(): previews_df = pd.DataFrame(columns=["descriptor", "opponent"] + [f"{c}_score" for c in criteria_df["criteria"]] + ["overall_score"]) previews = gr.DataFrame(value=previews_df, interactive=False, visible=False) with gr.Column(): gr.Markdown( """### Vote to Rank """ ) with gr.Row(): compare_output = gr.Textbox("Add some options to start voting!", label="Comparison", interactive=False) with gr.Row(): yes_button = gr.Button("1", variant="secondary") no_button = gr.Button("2", variant="primary") with gr.Row(): criteria_output = gr.Textbox(label="Criteria", interactive=False) new_vote = gr.Button("New Vote") with gr.Row(): with gr.Column(): compare_index_1 = gr.Textbox(label="", interactive=False, visible=False) with gr.Column(): compare_index_2 = gr.Textbox(label="", interactive=False, visible=False) with gr.Column(): gr.Markdown( """### Rankings """ ) 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"]) gr.Markdown( """### Add Opponents """ ) with gr.Row(): descriptor_input = gr.Textbox(label="Descriptor") opponent_input = gr.Textbox(label="Opponent") add_button = gr.Button("Add Opponent") add_button.click(add_and_compare, inputs=[descriptor_input, opponent_input, rankings, criteria_rankings], outputs=[descriptor_input, opponent_input, rankings]) gr.Markdown( """### Remove Opponents """ ) with gr.Row(): remove_descriptor_input = gr.Textbox(label="Descriptor") remove_opponent_input = gr.Textbox(label="Opponent") remove_button = gr.Button("Remove Opponent") remove_button.click(remove_opponent, inputs=[remove_descriptor_input, remove_opponent_input, rankings], outputs=rankings) gr.Markdown( """### Import and Export Rankings """ ) with gr.Row(): import_button = gr.File(label="Import CSV", file_count="single") import_button.change(fn=import_csv, inputs=[import_button, rankings, criteria_rankings], outputs=[rankings]) with gr.Column(): export_link = gr.File(label="Download CSV", file_count="single") export_button = gr.Button("Export as CSV") export_button.click(fn=export_csv, inputs=[rankings], outputs=export_link) gr.Markdown("### Reset Data") with gr.Row(): reset_button = gr.Button("Reset Scores") reset_button.click(reset_rankings, inputs=[rankings, criteria_rankings], outputs=rankings) clear_button = gr.Button("Clear Table", variant="primary") clear_button.click(clear_rankings, inputs=[rankings, criteria_rankings], outputs=rankings) yes_button.click(update_ratings_pos, inputs=[compare_index_1, compare_index_2, criteria_output, rankings, criteria_rankings], outputs=[compare_output, compare_index_1, compare_index_2, criteria_output, rankings]) no_button.click(update_ratings_neg, inputs=[compare_index_1, compare_index_2, criteria_output, rankings, criteria_rankings], outputs=[compare_output, compare_index_1, compare_index_2, criteria_output, rankings]) new_vote.click(vote_startup_opponents, inputs=[rankings, criteria_rankings], outputs=[compare_output, compare_index_1, compare_index_2, criteria_output, rankings]) app.launch(share=False)