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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"https://ipip.ori.org/New_IPIP-50-item-scale.htm"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# gradio"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"#os.system('pip install openpyxl') #works for huggingface-spaces\n",
"#score of each latent variable ranges in [10, 50]\n",
"def correct_score(score, big_5_indicator):\n",
" big_5_sign = big_5_indicator[0]\n",
" big_5_num = int(big_5_indicator[1])\n",
" dict1 = {\n",
" 1 : 'Extraversion',\n",
" 2 : 'Agreeableness',\n",
" 3 : 'Conscientiousness',\n",
" 4 : 'Neuroticism',\n",
" 5 : 'Openness'\n",
" }\n",
" if big_5_sign=='+':\n",
" return [dict1[big_5_num], score]\n",
" elif big_5_sign =='-':\n",
" return [dict1[big_5_num], 6-score]\n",
"# correct_score(3, big_5_indicator='-2')\n",
"\n",
"def make_question(q):\n",
" q = gr.Radio(choices=[1, 2, 3, 4, 5], label=q, value=1) #, value=5\n",
" return q\n",
"\n",
"def calculate_personality_score(questions, list_questions):\n",
" personality = {\n",
" 'Extraversion': 0,\n",
" 'Agreeableness': 0,\n",
" 'Conscientiousness': 0,\n",
" 'Neuroticism': 0,\n",
" 'Openness': 0\n",
" }\n",
" for question in list_questions:\n",
" big_5_indicator = questions[question[0]]\n",
" score = correct_score(question[1], big_5_indicator=big_5_indicator)\n",
" personality[score[0]] += score[1]\n",
" return personality"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Running on local URL: http://127.0.0.1:7862\n",
"\n",
"To create a public link, set `share=True` in `launch()`.\n"
]
},
{
"data": {
"text/html": [
"<div><iframe src=\"http://127.0.0.1:7862/\" width=\"900\" height=\"500\" allow=\"autoplay; camera; microphone;\" frameborder=\"0\" allowfullscreen></iframe></div>"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/plain": [
"(<gradio.routes.App at 0x27427d923a0>, 'http://127.0.0.1:7862/', None)"
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"import gradio as gr\n",
"import pandas as pd\n",
"import numpy as np\n",
"import os\n",
"\n",
"#\n",
"df_big5_test = pd.read_csv('Big5.csv', sep=';', header=None)\n",
"df_big5_test = df_big5_test[[0, 6]]\n",
"df_big5_test.columns = ['question', 'score']\n",
"df_big5_test['score'] = df_big5_test['score'].apply(lambda x : x.replace('(', '').replace(')', '')[::-1])\n",
"# df.index = df.pop('question')\n",
"questions = dict()\n",
"for el in df_big5_test.values.tolist():\n",
" questions[el[0]] = el[1]\n",
"questions\n",
"\n",
"#the first module becomes text1, the second module file1\n",
"def greet(*args): \n",
" args_list = [item for item in args]\n",
"\n",
" #extract big5\n",
" q_list = list(questions)\n",
" a_list = args_list[:]\n",
" list_total = [[q_list[x], a_list[x]] for x in range(len(a_list))]\n",
" personality = calculate_personality_score(questions, list_total)\n",
" personality = { x : personality[x]/50 for x in personality}\n",
" # personality = [personality['Openness'], personality['Conscientiousness'], personality['Extraversion'], personality['Agreeableness'], personality['Neuroticism']]\n",
" # personality = [x/50 for x in personality]\n",
"\n",
" #to return a file:\n",
" #return 'new.xlsx'\n",
" return personality\n",
"\n",
"iface = gr.Interface(\n",
" fn=greet, \n",
" inputs=[make_question(q) for q in list(questions)], \n",
" outputs=[\"text\"]\n",
" )\n",
"iface.launch(share=False)"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3.9.0 64-bit",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.0"
},
"orig_nbformat": 4,
"vscode": {
"interpreter": {
"hash": "fdf377d643bc1cb065454f0ad2ceac75d834452ecf289e7ba92c6b3f59a7cee1"
}
}
},
"nbformat": 4,
"nbformat_minor": 2
}
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