Create app.py

app.py

@@ -0,0 +1,143 @@
+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)