app.py

import os
import json
import pandas as pd
from collections import defaultdict, Counter
import altair as alt
import panel as pn


def choices_to_df(choices, hue):
    df = pd.DataFrame(choices, columns=['choices'])
    df['hue'] = hue
    df['hue'] = df['hue'].astype(str)
    return df

def arrange_data():
    
    # Human Data
    
    df = pd.read_csv('Project/2_scientific/ChatGPT-Behavioral-main/data/bomb_risk.csv')
    df = df[df['Role'] == 'player']
    df = df[df['gameType'] == 'bomb_risk']
    df.sort_values(by=['UserID', 'Round'])

    prefix_to_choices_human = defaultdict(list)
    prefix_to_IPW = defaultdict(list)
    prev_user = None
    prev_move = None
    prefix = ''
    bad_user = False
    for _, row in df.iterrows():
        if bad_user: continue
        if row['UserID'] != prev_user:
            prev_user = row['UserID']
            prefix = ''
            bad_user = False

        move = row['move']
        if move < 0 or move > 100:
            bad_users = True
            continue
        prefix_to_choices_human[prefix].append(move)

        if len(prefix) == 0:
            prefix_to_IPW[prefix].append(1)
        elif prefix[-1] == '1':
            prev_move = min(prev_move, 98)
            prefix_to_IPW[prefix].append(1./(100 - prev_move))
        elif prefix[-1] == '0':
            prev_move = max(prev_move, 1)
            prefix_to_IPW[prefix].append(1./(prev_move))
        else: assert False
        
        prev_move = move

        prefix += '1' if row['roundResult'] == 'SAFE' else '0'


    # Model Data
        
    prefix_to_choices_model = defaultdict(lambda : defaultdict(list))
    for model in ['ChatGPT-4', 'ChatGPT-3']:
        if model == 'ChatGPT-4':
            file_names = [
                'bomb_gpt4_2023_05_15-12_13_51_AM.json'
            ]
        elif model == 'ChatGPT-3':
            file_names = [
                'bomb_turbo_2023_05_14-10_45_50_PM.json'
            ]

        choices = []
        scenarios = []
        for file_name in file_names:
            with open(os.path.join('Project/2_scientific/ChatGPT-Behavioral-main/records', file_name), 'r') as f:
                records = json.load(f)
                choices += records['choices']
                scenarios += records['scenarios']

        assert len(scenarios) == len(choices)
        print('loaded %i valid records' % len(scenarios))

        prefix_to_choice = defaultdict(list)
        prefix_to_result = defaultdict(list)
        prefix_to_pattern = defaultdict(Counter)
        wrong_sum = 0
        for scenarios_tmp, choices_tmp in zip(scenarios, choices):

            result = 0
            for i, scenario in enumerate(scenarios_tmp):
                prefix = tuple(scenarios_tmp[:i])
                prefix = ''.join([str(x) for x in prefix])
                choice = choices_tmp[i]
                
                prefix_to_choice[prefix].append(choice)
                prefix_to_pattern[prefix][tuple(choices_tmp[:-1])] += 1

                prefix = tuple(scenarios_tmp[:i+1])
                if scenario == 1:
                    result += choice
                prefix_to_result[prefix].append(result)

        print('# of wrong sum:', wrong_sum)
        print('# of correct sum:', len(scenarios) - wrong_sum)

        prefix_to_choices_model[model] = prefix_to_choice


    # Arrange Data

    round_dict = {'': [1, -1, -1],
                '0': [2, 0, -1],
                '1': [2, 1, -1],
                '00': [3, 0, 0],
                '01': [3, 0, 1],
                '10': [3, 1, 0],
                '11': [3, 1, 1]}

    df_bomb_all = pd.DataFrame()

    for prefix in round_dict:
        
        df_bomb_human = choices_to_df(prefix_to_choices_human[prefix], hue='Human')
        df_bomb_human['weight'] = prefix_to_IPW[prefix]
        
        df_bomb_models = pd.concat([choices_to_df(
                prefix_to_choices_model[model][prefix], hue=model
            ) for model in prefix_to_choices_model]
        )
        df_bomb_models['weight'] = 1    
        
        df_bomb_temp = pd.concat([df_bomb_human, df_bomb_models])
        df_bomb_temp['prefix'] = prefix

        df_bomb_all = pd.concat([df_bomb_all, df_bomb_temp])

    df_density = df_bomb_all.groupby(['hue', 'prefix'])['choices'].value_counts(normalize=True).unstack(fill_value=0).stack().reset_index()
    df_density = df_density.rename(columns={'hue': 'Subject', 'choices': 'Boxes', 0: 'Density'})
    df_density['Round'] = df_density['prefix'].apply(lambda x: round_dict[x][0])
    
    return df_density


df_density = arrange_data()
alt.data_transformers.disable_max_rows()

# Enable Panel extensions
pn.extension(design='bootstrap')
pn.extension('vega')
template = pn.template.BootstrapTemplate(
    title='Nan-Hsin Lin | SI649 Scientific Viz Project',
)

# Define a function to create and return a plot
def create_plot(bomb_1, bomb_2):

    bomb_1 = int(not bomb_1)
    bomb_2 = int(not bomb_2)

    selection = alt.selection_single(encodings=['color'], empty='none', value=3)
    opacityCondition = alt.condition(selection, alt.value(1), alt.value(0.3))
    range_ = ['#009FB7', '#FED766', '#FE4A49']

    plot = alt.Chart(df_density).transform_filter(
        (alt.datum.prefix == '') | (alt.datum.prefix == str(bomb_1)) | (alt.datum.prefix == str(bomb_1) + str(bomb_2))
    ).mark_bar(opacity=0.5).encode(
        x=alt.X('Boxes:Q', 
                bin=alt.Bin(maxbins=10), 
                title='Number of boxes opened',
                axis=alt.Axis(ticks=False,
                            labelFontSize=11,
                            labelColor='#AAA7AD',
                            titleFontSize=12, 
                            titleColor='#AAA7AD',
                            domain=False)),
        y=alt.Y('Density:Q', 
                stack=None, 
                scale=alt.Scale(domain=[0, 1]), 
                axis=alt.Axis(format='.0%', 
                            ticks=False, 
                            tickCount=5,
                            labelFontSize=11,
                            labelColor='#AAA7AD',
                            titleFontSize=12, 
                            titleColor='#AAA7AD',
                            domain=False,
                            grid=False)),
        color=alt.Color('Round:N', 
                        scale=alt.Scale(domain=[1, 2, 3], range=range_)),
        row=alt.Row('Subject:N', 
                    header=alt.Header(title=None, orient='top', labelFontSize=16),
                    sort='descending'),
        tooltip=['Subject:N', 'Round:N', 'Boxes:Q', alt.Tooltip('Density:Q', format='.0%')]
    ).properties(width=400, height=150
    ).configure_view(strokeWidth=3, stroke='lightgrey'
    ).configure_legend(
        titleFontSize=12, 
        titleColor='#AAA7AD',
        titleAnchor='middle',
        titlePadding=8,
        labelFontSize=12,
        labelColor='#AAA7AD',
        labelFontWeight='bold',
        symbolOffset=20,
        orient='none',
        direction='horizontal',
        legendX=120,
        legendY=-90,
        symbolSize=200
    ).add_selection(selection).encode(
        opacity=opacityCondition
    )

    return plot

# Create widgets
switch_1 = pn.widgets.Switch(name='Bomb in Round 1', value=True)
switch_2 = pn.widgets.Switch(name='Bomb in Round 2', value=True)

plot_widgets = pn.bind(create_plot, switch_1, switch_2)

# Combine everything in a Panel Column to create an app
maincol = pn.Column()
maincol.append(pn.Row(pn.layout.HSpacer(),
                      "### A Turing test of whether AI chatbots are behaviorally similar to humans", 
                      pn.layout.HSpacer()))
maincol.append(pn.Row(pn.Spacer(width=100)))
maincol.append(pn.Row(pn.layout.HSpacer(),
                      "#### Bomb Risk Game: Human vs. ChatGPT-4 vs. ChatGPT-3", 
                      pn.layout.HSpacer()))
maincol.append(pn.Row(pn.layout.HSpacer(), 
                      "Bomb in Round 1", switch_1,
                      pn.Spacer(width=50),
                      "Bomb in Round 2", switch_2, 
                      pn.layout.HSpacer()))
maincol.append(pn.Row(pn.layout.HSpacer(), 
                      plot_widgets,
                      pn.layout.HSpacer()))
maincol.append(pn.Row(pn.layout.HSpacer(),
                      "**Fig 5.** ChatGPT-4 and ChatGPT-3 act as if they have particular risk preferences. Both have the same mode as human distribution in the first round or when experiencing favorable outcomes in the Bomb Risk Game. When experiencing negative outcomes, ChatGPT-4 remains consistent and risk-neutral, while ChatGPT-3 acts as if it becomes more risk-averse.",
                      pn.layout.HSpacer()))
template.main.append(maincol)

# set the app to be servable
template.servable(title="SI649 Scientific Viz Project")