helliun commited on
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97d975e
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Create app.py

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  1. app.py +143 -0
app.py ADDED
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+ import gradio as gr
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+ import pandas as pd
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+ import csv
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+
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+ def update_scores(winner_score, loser_score, k_factor=100):
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+ score_difference = k_factor / (winner_score / loser_score)
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+ return winner_score + score_difference, loser_score - score_difference
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+
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+ def prepare_dataframe(opponents_df, criteria_df, additional_columns=None):
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+ columns = ["descriptor", "opponent"] + [f"{c}_score" for c in criteria_df["criteria"]] + ["overall_score"]
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+ if additional_columns:
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+ columns += additional_columns
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+ return opponents_df[columns] if not opponents_df.empty else pd.DataFrame(columns=columns)
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+
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+ def clean_string(s):
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+ return " ".join(word.capitalize() for word in s.strip().replace(" ", " ").lower().split())
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+
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+ def display_dataframe(df, sort_column, file_name):
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+ df = df.sort_values(by=sort_column, ascending=False)
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+ df.to_csv(file_name, index=False)
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+ return df
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+
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+ def update_criteria_ratings(first, second, criteria_df, is_positive):
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+ winner, loser = (first, second) if is_positive else (second, first)
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+ winner_score, loser_score = update_scores(
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+ criteria_df.at[winner, 'score'], criteria_df.at[loser, 'score']
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+ )
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+ criteria_df.at[winner, 'score'], criteria_df.at[loser, 'score'] = winner_score, loser_score
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+ return criteria_df
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+
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+ def update_opponent_ratings(first, second, criterion, opponents_df, criteria_df, is_positive):
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+ winner, loser = (first, second) if is_positive else (second, first)
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+ winner_score, loser_score = update_scores(
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+ opponents_df.at[winner, f"{criterion}_score"], opponents_df.at[loser, f"{criterion}_score"]
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+ )
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+ opponents_df.at[winner, f"{criterion}_score"], opponents_df.at[loser, f"{criterion}_score"] = winner_score, loser_score
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+ return calculate_overall_scores(opponents_df, criteria_df)
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+
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+ def calculate_overall_scores(opponents_df, criteria_df):
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+ criteria_scores = criteria_df.set_index("criteria")["score"]
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+ criteria_list = criteria_df["criteria"]
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+
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+ def compute_score(row):
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+ total_score = sum(row[f"{c}_score"] * criteria_scores[c] for c in criteria_list)
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+ total_weight = sum(criteria_scores[c] for c in criteria_list)
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+ return total_score / total_weight if total_weight else 0
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+
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+ opponents_df["overall_score"] = opponents_df.apply(compute_score, axis=1)
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+ return opponents_df
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+
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+ def handle_vote(first, second, criteria, opponents_df, criteria_df, is_symbolic_func, data_file):
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+ data_frame = is_symbolic_func(first, second, criteria, opponents_df, criteria_df)
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+ data_frame = display_dataframe(data_frame, 'overall_score', data_file)
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+ return get_vote_start_data(opponents_df, criteria_df)
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+
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+ def get_vote_start_data(opponents_df, criteria_df):
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+ if len(opponents_df) > 1 and len(criteria_df) > 0:
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+ sample = opponents_df.sample(n=2)
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+ first_string = sample.iloc[0]["descriptor"] + " - " + sample.iloc[0]["opponent"]
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+ second_string = sample.iloc[1]["descriptor"] + " - " + sample.iloc[1]["opponent"]
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+ criterion = criteria_df.sample(n=1)["criteria"].values[0]
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+ return f"Which better reflects '{criterion}': '{first_string}' or '{second_string}'?", first_string, second_string, criterion
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+ return "Add more options and criteria to start voting!", "", "", ""
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+
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+ def handle_criteria_vote(first, second, criteria_df, is_positive):
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+ criteria_df = update_criteria_ratings(first, second, criteria_df, is_positive)
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+ criteria_df = display_dataframe(criteria_df, 'score', 'criteria_df.csv')
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+ return get_criteria_vote_start(criteria_df)
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+
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+ def get_criteria_vote_start(criteria_df):
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+ if len(criteria_df) > 1:
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+ sample = criteria_df.sample(n=2)
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+ first_string, second_string = sample.iloc[0]["criteria"], sample.iloc[1]["criteria"]
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+ return f"Is '{first_string}' more important than '{second_string}'?", first_string, second_string
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+ return "Add more criteria to start ranking!", "", ""
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+
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+ theme = gr.themes.Soft(primary_hue="red", secondary_hue="blue")
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+
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+ with gr.Blocks(theme=theme) as app:
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+ gr.Markdown("""## Preference-based Elo Ranker""")
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+
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+ with gr.Tab("Criteria Ranking"):
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+ gr.Markdown("### Rank Criteria")
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+ criteria_input = gr.Textbox(label="Criteria")
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+ add_criteria_button = gr.Button("Add Criteria")
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+ remove_criteria_button = gr.Button("Remove Criteria")
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+
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+ criteria_df = pd.DataFrame(columns=['score', 'criteria'])
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+ criteria_rankings = gr.DataFrame(value=criteria_df, interactive=False, headers=["Score", "Criteria"])
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+ criteria_compare_output = gr.Textbox("Add some criteria to start ranking!", label="Comparison", interactive=False)
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+
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+ criteria_yes_button = gr.Button("Yes", variant="secondary")
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+ criteria_no_button = gr.Button("No", variant="primary")
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+ criteria_new_vote = gr.Button("New Vote")
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+
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+ add_criteria_button.click(lambda _: add_criteria(criteria_input, criteria_rankings),
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+ inputs=[criteria_input, criteria_rankings], outputs=[criteria_input, criteria_rankings])
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+ remove_criteria_button.click(lambda _: remove_criteria(clean_string(remove_criteria_input.value), criteria_rankings),
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+ inputs=[remove_criteria_input, criteria_rankings], outputs=criteria_rankings)
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+
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+ criteria_yes_button.click(lambda first, second: handle_criteria_vote(first, second, criteria_rankings, True),
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+ inputs=[criteria_input, criteria_input], outputs=[criteria_compare_output, criteria_input, criteria_input])
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+ criteria_no_button.click(lambda first, second: handle_criteria_vote(first, second, criteria_rankings, False),
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+ inputs=[criteria_input, criteria_input], outputs=[criteria_compare_output, criteria_input, criteria_input])
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+ criteria_new_vote.click(lambda data_frame: get_criteria_vote_start(data_frame),
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+ inputs=[criteria_rankings], outputs=[criteria_compare_output, criteria_input, criteria_input])
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+
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+ with gr.Tab("Opponent Ranking"):
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+ opponents_df = pd.DataFrame(columns=["descriptor", "opponent"] + [f"{c}_score" for c in criteria_df["criteria"]] + ["overall_score"])
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+ rankings = gr.DataFrame(value=opponents_df, interactive=False,
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+ headers=["Descriptor", "Opponent"] + [f"{c} Score" for c in criteria_df["criteria"]] + ["Overall Score"])
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+
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+ compare_output = gr.Textbox("Add some options to start voting!", label="Comparison", interactive=False)
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+ yes_button = gr.Button("1", variant="secondary")
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+ no_button = gr.Button("2", variant="primary")
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+ criteria_output = gr.Textbox(label="Criteria", interactive=False)
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+
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+ new_vote = gr.Button("New Vote")
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+ descriptor_input = gr.Textbox(label="Descriptor")
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+ opponent_input = gr.Textbox(label="Opponent")
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+ add_button = gr.Button("Add Opponent")
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+
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+ add_button.click(lambda: add_and_compare(clean_string(descriptor_input.value), clean_string(opponent_input.value), rankings, criteria_rankings),
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+ inputs=[descriptor_input, opponent_input, rankings, criteria_rankings], outputs=[descriptor_input, opponent_input, rankings])
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+
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+ remove_descriptor_input = gr.Textbox(label="Descriptor")
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+ remove_opponent_input = gr.Textbox(label="Opponent")
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+ remove_button = gr.Button("Remove Opponent")
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+
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+ remove_button.click(lambda _, __: remove_opponent(remove_descriptor_input, remove_opponent_input, rankings),
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+ inputs=[remove_descriptor_input, remove_opponent_input, rankings], outputs=rankings)
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+
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+ 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"),
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+ inputs=[compare_output, compare_output, criteria_output, rankings, criteria_rankings],
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+ outputs=[compare_output, compare_output, compare_output, criteria_output, rankings])
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+ 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"),
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+ inputs=[compare_output, compare_output, criteria_output, rankings, criteria_rankings],
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+ outputs=[compare_output, compare_output, compare_output, criteria_output, rankings])
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+
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+ new_vote.click(lambda opp_df, crit_df: get_vote_start_data(opp_df, crit_df),
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+ inputs=[rankings, criteria_rankings], outputs=[compare_output, compare_output, compare_output, criteria_output, rankings])
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+
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+ app.launch(share=False)