Spaces:
Running
Running
v0.8.0
#8
by
DmitryRyumin
- opened
- app.css +46 -0
- app.py +18 -2
- app/authors.py +59 -12
- app/description.py +1 -1
- app/description_steps.py +3 -3
- app/event_handlers/calculate_practical_tasks.py +130 -2
- app/event_handlers/calculate_pt_scores_blocks.py +30 -83
- app/event_handlers/clear_blocks.py +5 -0
- app/event_handlers/event_handlers.py +33 -0
- app/event_handlers/languages.py +39 -0
- app/event_handlers/practical_subtasks.py +57 -3
- app/mbti_description.py +29 -0
- app/tabs.py +48 -3
- config.toml +35 -2
- images/AA.jpg +0 -0
- practical_tasks.yaml +3 -1
- requirements.txt +1 -1
app.css
CHANGED
@@ -10,6 +10,11 @@ div.video-container {
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max-height: 350px;
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}
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div.files-container {
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height: 350px;
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max-height: 350px;
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@@ -95,6 +100,47 @@ div.files-container label[data-testid="block-label"] {
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max-width: fit-content;
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}
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.dropdown-container > div > span[data-testid="block-info"] + div {
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min-width: max-content;
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}
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max-height: 350px;
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}
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+
div.video-sorted-container {
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max-width: 640px;
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max-height: 350px;
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}
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div.files-container {
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height: 350px;
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max-height: 350px;
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max-width: fit-content;
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}
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+
.dropdown-language-container {
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display: contents;
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}
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.dropdown-container > div > span[data-testid="block-info"] + div {
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min-width: max-content;
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}
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div.gradio-container > div.main > div.wrap > div.contain > #component-0 > div.form {
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display: flex;
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width: fit-content;
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float: left;
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right: 0px;
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position: absolute;
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z-index: 2;
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}
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div.gradio-container > div.main > div.wrap > div.contain > #component-0 > div.tabs {
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margin-top: 20px;
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}
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div.dataframe span.wrapper_mbti {
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display: inline-block;
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border-radius: 2px;
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overflow: hidden;
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}
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div.dataframe span.wrapper_mbti > span.true, div.dataframe span.wrapper_mbti > span.err {
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color: #FFFFFF;
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display: inline-block;
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padding: 2px;
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}
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div.dataframe span.wrapper_mbti > span.true {
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background-color: #006900;
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}
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div.dataframe span.wrapper_mbti > span.err {
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background-color: #B42E2C;
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}
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div.mbti-dataframe div.table-wrap {
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--cell-width-0: 260px !important;
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}
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app.py
CHANGED
@@ -11,11 +11,24 @@ import gradio as gr
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from app.config import CONFIG_NAME, config_data, load_tab_creators
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from app.event_handlers.event_handlers import setup_app_event_handlers
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from app import tabs
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def create_gradio_app() -> gr.Blocks:
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with gr.Blocks(css=config_data.AppSettings_CSS_PATH) as gradio_app:
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tab_results = {}
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available_functions = {
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attr: getattr(tabs, attr)
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@@ -26,11 +39,14 @@ def create_gradio_app() -> gr.Blocks:
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tab_creators = load_tab_creators(CONFIG_NAME, available_functions)
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for tab_name, create_tab_function in tab_creators.items():
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-
with gr.Tab(tab_name):
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app_instance = create_tab_function()
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tab_results[tab_name] = app_instance
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-
setup_app_event_handlers(
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return gradio_app
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from app.config import CONFIG_NAME, config_data, load_tab_creators
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from app.event_handlers.event_handlers import setup_app_event_handlers
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from app import tabs
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from app.components import dropdown_create_ui
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def create_gradio_app() -> gr.Blocks:
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with gr.Blocks(css=config_data.AppSettings_CSS_PATH) as gradio_app:
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languages = dropdown_create_ui(
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label=None,
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info=None,
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choices=config_data.Settings_LANGUAGES_EN,
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value=config_data.Settings_LANGUAGES_EN[0],
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visible=True,
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show_label=False,
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elem_classes="dropdown-language-container",
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interactive=False,
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)
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tab_results = {}
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ts = []
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available_functions = {
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attr: getattr(tabs, attr)
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tab_creators = load_tab_creators(CONFIG_NAME, available_functions)
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for tab_name, create_tab_function in tab_creators.items():
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with gr.Tab(tab_name) as tab:
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app_instance = create_tab_function()
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tab_results[tab_name] = app_instance
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ts.append(tab)
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setup_app_event_handlers(
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*tab_results[list(tab_results.keys())[0]], *ts, languages
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)
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return gradio_app
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app/authors.py
CHANGED
@@ -12,16 +12,27 @@ AUTHORS = """
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<img src="https://readme-typing-svg.demolab.com?font=Roboto&duration=1500&pause=100&color=3081F7&vCenter=true&multiline=true&width=435&height=70&lines=Elena+Ryumina;Artificial+Intelligence+Researcher" alt="ElenaRyumina" />
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</a>
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<div style="display: flex; margin-bottom: 6px;">
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<a href="https://www.
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<img src="https://img.shields.io/badge/
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</a>
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<a href="https://
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<img src="https://img.shields.io/badge/
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</a>
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<a href="https://orcid.org/0000-0002-4135-6949">
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<img src="https://img.shields.io/badge/ORCID-0000--0002--4135--6949-green.svg?&style=flat-square&logo=orcid&logoColor=white" alt="" />
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</a>
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</div>
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<a href="https://github.com/ElenaRyumina" style="display: inline-block;">
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<img src="https://github-stats-alpha.vercel.app/api?username=ElenaRyumina&cc=3081F7&tc=FFFFFF&ic=FFFFFF&bc=FFFFFF" alt="" />
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</a>
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@@ -35,20 +46,31 @@ AUTHORS = """
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<img src="https://readme-typing-svg.demolab.com?font=Roboto&duration=1500&pause=100&color=3081F7&vCenter=true&multiline=true&width=435&height=70&lines=Dr.+Dmitry+Ryumin;Artificial+Intelligence+Researcher" alt="DmitryRyumin" />
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</a>
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<div style="display: flex; margin-bottom: 6px;">
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<a href="https://dmitryryumin.github.io">
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<img src="https://img.shields.io/badge/Website-blue??&style=flat-square&logo=opsgenie&logoColor=white" alt=""
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</a>
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<a href="https://www.
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-
<img src="https://img.shields.io/badge/
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</a>
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-
<a href="https://
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<img src="https://img.shields.io/badge/
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</a>
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<a href="https://orcid.org/0000-0002-7935-0569">
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<img src="https://img.shields.io/badge/ORCID-0000--0002--7935--0569-green.svg?&style=flat-square&logo=orcid&logoColor=white" alt=""
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</a>
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<a href="mailto:neweraairesearch@gmail.com">
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-
<img src="https://img.shields.io/badge/-Email-red?style=flat-square&logo=gmail&logoColor=white" alt=""
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</a>
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</div>
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<a href="https://github.com/DmitryRyumin" style="display: inline-block;">
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@@ -60,4 +82,29 @@ AUTHORS = """
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</div>
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</div>
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</div>
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"""
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<img src="https://readme-typing-svg.demolab.com?font=Roboto&duration=1500&pause=100&color=3081F7&vCenter=true&multiline=true&width=435&height=70&lines=Elena+Ryumina;Artificial+Intelligence+Researcher" alt="ElenaRyumina" />
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</a>
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<div style="display: flex; margin-bottom: 6px;">
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+
<a href="https://www.webofscience.com/wos/author/record/ABY-9103-2022" style="margin-right: 6px;">
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<img src="https://img.shields.io/badge/Web%20of%20Science-5D34BF??&style=flat-square&logo=clarivate&logoColor=white" alt="" />
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</a>
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+
<a href="https://www.scopus.com/authid/detail.uri?authorId=57220572427" style="margin-right: 6px;">
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<img src="https://img.shields.io/badge/Scopus-%23E9711C.svg?&style=flat-square&logo=scopus&logoColor=white" alt="" />
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</a>
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<a href="https://scholar.google.com/citations?user=DOBkQssAAAAJ" style="margin-right: 6px;">
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<img src="https://img.shields.io/badge/Google%20Scholar-%234285F4.svg?&style=flat-square&logo=google-scholar&logoColor=white" alt="" />
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</a>
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<a href="https://orcid.org/0000-0002-4135-6949">
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<img src="https://img.shields.io/badge/ORCID-0000--0002--4135--6949-green.svg?&style=flat-square&logo=orcid&logoColor=white" alt="" />
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</a>
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</div>
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<div style="display: flex; margin-bottom: 6px;">
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<a href="https://huggingface.co/ElenaRyumina" style="margin-right: 6px;">
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<img src="https://img.shields.io/badge/🤗-Hugging%20Face-FFD21F.svg?style=flat-square&&logoColor=white" alt="" />
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</a>
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<a href="mailto:ryumina_ev@mail.ru">
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<img src="https://img.shields.io/badge/-Email-red?style=flat-square&logo=gmail&logoColor=white" alt="" />
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</a>
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</div>
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<a href="https://github.com/ElenaRyumina" style="display: inline-block;">
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<img src="https://github-stats-alpha.vercel.app/api?username=ElenaRyumina&cc=3081F7&tc=FFFFFF&ic=FFFFFF&bc=FFFFFF" alt="" />
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</a>
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<img src="https://readme-typing-svg.demolab.com?font=Roboto&duration=1500&pause=100&color=3081F7&vCenter=true&multiline=true&width=435&height=70&lines=Dr.+Dmitry+Ryumin;Artificial+Intelligence+Researcher" alt="DmitryRyumin" />
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</a>
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<div style="display: flex; margin-bottom: 6px;">
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<a href="https://dmitryryumin.github.io" style="margin-right: 6px;">
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<img src="https://img.shields.io/badge/Website-blue??&style=flat-square&logo=opsgenie&logoColor=white" alt="" />
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</a>
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+
<a href="https://www.webofscience.com/wos/author/record/K-7989-2018" style="margin-right: 6px;">
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<img src="https://img.shields.io/badge/Web%20of%20Science-5D34BF??&style=flat-square&logo=clarivate&logoColor=white" alt="" />
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</a>
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+
<a href="https://www.scopus.com/authid/detail.uri?authorId=57191960214" style="margin-right: 6px;">
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<img src="https://img.shields.io/badge/Scopus-%23E9711C.svg?&style=flat-square&logo=scopus&logoColor=white" alt="" />
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</a>
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<a href="https://scholar.google.com/citations?user=LrTIp5IAAAAJ" style="margin-right: 6px;">
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<img src="https://img.shields.io/badge/Google%20Scholar-%234285F4.svg?&style=flat-square&logo=google-scholar&logoColor=white" alt="" />
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</a>
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<a href="https://orcid.org/0000-0002-7935-0569">
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<img src="https://img.shields.io/badge/ORCID-0000--0002--7935--0569-green.svg?&style=flat-square&logo=orcid&logoColor=white" alt="" />
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</a>
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</div>
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<div style="display: flex; margin-bottom: 6px;">
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<a href="https://huggingface.co/DmitryRyumin" style="margin-right: 6px;">
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<img src="https://img.shields.io/badge/🤗-Hugging%20Face-FFD21F.svg?style=flat-square&&logoColor=white" alt="" />
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</a>
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<a href="https://t.me/dmitry_ryumin" style="margin-right: 6px;">
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<img src="https://img.shields.io/badge/Telegram-2CA5E0?style=flat-square&logo=telegram&logoColor=white" alt="" />
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</a>
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<a href="mailto:neweraairesearch@gmail.com">
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<img src="https://img.shields.io/badge/-Email-red?style=flat-square&logo=gmail&logoColor=white" alt=""/>
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</a>
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</div>
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<a href="https://github.com/DmitryRyumin" style="display: inline-block;">
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</div>
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</div>
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</div>
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+
<div style="display: flex; justify-content: center; align-items: center; margin-top: 10px;">
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<img src="https://hci.nw.ru/storage/employees/first/Karpov.jpg" alt="Professor Alexey Karpov" style="margin-right: 20px; border-radius: 50%; width: 80px; height: 80px; object-fit: cover;">
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<div style="flex-basis: 40%;">
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<a href="https://hci.nw.ru/en/employees/1" style="display: inline-block;">
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<img src="https://readme-typing-svg.demolab.com?font=Roboto&duration=1500&pause=100&color=3081F7&vCenter=true&multiline=true&width=435&height=70&lines=Dr.Sc.+Alexey+Karpov;Supervisor" alt="AlexeyKarpov" />
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</a>
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<div style="display: flex; margin-bottom: 6px;">
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<a href="https://www.webofscience.com/wos/author/record/A-8905-2012" style="margin-right: 6px;">
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<img src="https://img.shields.io/badge/Web%20of%20Science-5D34BF??&style=flat-square&logo=clarivate&logoColor=white" alt="" />
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</a>
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<a href="https://www.scopus.com/authid/detail.uri?authorId=57219469958" style="margin-right: 6px;">
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<img src="https://img.shields.io/badge/Scopus-%23E9711C.svg?&style=flat-square&logo=scopus&logoColor=white" alt="" />
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</a>
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<a href="https://scholar.google.com/citations?user=Q0C3f1oAAAAJ" style="margin-right: 6px;">
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<img src="https://img.shields.io/badge/Google%20Scholar-%234285F4.svg?&style=flat-square&logo=google-scholar&logoColor=white" alt="" />
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</a>
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<a href="https://orcid.org/0000-0003-3424-652X" style="margin-right: 6px;">
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<img src="https://img.shields.io/badge/ORCID-0000--0003--3424--652X-green.svg?&style=flat-square&logo=orcid&logoColor=white" alt="" />
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</a>
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<a href="mailto:karpov@iias.spb.su">
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<img src="https://img.shields.io/badge/-Email-red?style=flat-square&logo=gmail&logoColor=white" alt="" />
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</a>
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</div>
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</div>
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</div>
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"""
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app/description.py
CHANGED
@@ -1,6 +1,6 @@
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"""
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File: description.py
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-
Author: Dmitry Ryumin
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Description: Project description for the Gradio app.
|
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License: MIT License
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"""
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"""
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File: description.py
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+
Author: Elena Ryumina and Dmitry Ryumin
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Description: Project description for the Gradio app.
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License: MIT License
|
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"""
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app/description_steps.py
CHANGED
@@ -1,7 +1,7 @@
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"""
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-
File:
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-
Author: Dmitry Ryumin
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-
Description: Project description for the Gradio app.
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License: MIT License
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"""
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"""
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File: description_steps.py
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Author: Elena Ryumina and Dmitry Ryumin
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Description: Project steps description for the Gradio app.
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License: MIT License
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"""
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app/event_handlers/calculate_practical_tasks.py
CHANGED
@@ -6,11 +6,13 @@ License: MIT License
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"""
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|
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from app.oceanai_init import b5
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import gradio as gr
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from pathlib import Path
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# Importing necessary components for the Gradio app
|
13 |
from app.config import config_data
|
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|
14 |
from app.utils import (
|
15 |
read_csv_file,
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16 |
apply_rounding_and_rename_columns,
|
@@ -31,10 +33,39 @@ def consumer_preferences(subtask):
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31 |
)
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32 |
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33 |
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34 |
def event_handler_calculate_practical_task_blocks(
|
35 |
files,
|
36 |
practical_subtasks,
|
37 |
pt_scores,
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|
|
38 |
threshold_professional_skills,
|
39 |
dropdown_professional_skills,
|
40 |
target_score_ope,
|
@@ -52,7 +83,79 @@ def event_handler_calculate_practical_task_blocks(
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52 |
number_agreeableness,
|
53 |
number_non_neuroticism,
|
54 |
):
|
55 |
-
if practical_subtasks.lower() == "
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|
56 |
sum_weights = sum(
|
57 |
[
|
58 |
number_openness,
|
@@ -80,6 +183,9 @@ def event_handler_calculate_practical_task_blocks(
|
|
80 |
False,
|
81 |
"csv-container",
|
82 |
),
|
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|
83 |
video_create_ui(visible=False),
|
84 |
html_message(
|
85 |
config_data.InformationMessages_SUM_WEIGHTS.format(sum_weights),
|
@@ -126,11 +232,15 @@ def event_handler_calculate_practical_task_blocks(
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|
126 |
True,
|
127 |
"csv-container",
|
128 |
),
|
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|
129 |
video_create_ui(
|
130 |
value=files[person_id],
|
131 |
file_name=Path(files[person_id]).name,
|
132 |
label="Best Person ID - " + str(person_id + 1),
|
133 |
visible=True,
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|
134 |
),
|
135 |
html_message(config_data.InformationMessages_NOTI_IN_DEV, False, False),
|
136 |
)
|
@@ -185,11 +295,15 @@ def event_handler_calculate_practical_task_blocks(
|
|
185 |
True,
|
186 |
"csv-container",
|
187 |
),
|
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|
188 |
video_create_ui(
|
189 |
value=files[person_id],
|
190 |
file_name=Path(files[person_id]).name,
|
191 |
label="Best Person ID - " + str(person_id + 1),
|
192 |
visible=True,
|
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|
193 |
),
|
194 |
html_message(config_data.InformationMessages_NOTI_IN_DEV, False, False),
|
195 |
)
|
@@ -247,27 +361,34 @@ def event_handler_calculate_practical_task_blocks(
|
|
247 |
True,
|
248 |
"csv-container",
|
249 |
),
|
|
|
|
|
|
|
250 |
video_create_ui(
|
251 |
value=files[person_id],
|
252 |
file_name=Path(files[person_id]).name,
|
253 |
label="Best Person ID - " + str(person_id + 1),
|
254 |
visible=True,
|
|
|
255 |
),
|
256 |
html_message(config_data.InformationMessages_NOTI_IN_DEV, False, False),
|
257 |
)
|
258 |
elif (
|
259 |
practical_subtasks.lower() == "car characteristics"
|
260 |
or practical_subtasks.lower() == "mobile device application categories"
|
|
|
261 |
):
|
262 |
if practical_subtasks.lower() == "car characteristics":
|
263 |
df_correlation_coefficients = read_csv_file(
|
264 |
config_data.Links_CAR_CHARACTERISTICS,
|
265 |
["Style and performance", "Safety and practicality"],
|
266 |
)
|
267 |
-
|
268 |
df_correlation_coefficients = read_csv_file(
|
269 |
config_data.Links_MDA_CATEGORIES
|
270 |
)
|
|
|
|
|
271 |
|
272 |
pt_scores_copy = pt_scores.iloc[:, 1:].copy()
|
273 |
|
@@ -316,11 +437,15 @@ def event_handler_calculate_practical_task_blocks(
|
|
316 |
True,
|
317 |
"csv-container",
|
318 |
),
|
|
|
|
|
|
|
319 |
video_create_ui(
|
320 |
value=files[person_id],
|
321 |
file_name=Path(files[person_id]).name,
|
322 |
label="Best Person ID - " + str(person_id + 1),
|
323 |
visible=True,
|
|
|
324 |
),
|
325 |
html_message(config_data.InformationMessages_NOTI_IN_DEV, False, False),
|
326 |
)
|
@@ -341,6 +466,9 @@ def event_handler_calculate_practical_task_blocks(
|
|
341 |
False,
|
342 |
"csv-container",
|
343 |
),
|
|
|
|
|
|
|
344 |
video_create_ui(visible=False),
|
345 |
html_message(config_data.InformationMessages_NOTI_IN_DEV, False, True),
|
346 |
)
|
|
|
6 |
"""
|
7 |
|
8 |
from app.oceanai_init import b5
|
9 |
+
import re
|
10 |
import gradio as gr
|
11 |
from pathlib import Path
|
12 |
|
13 |
# Importing necessary components for the Gradio app
|
14 |
from app.config import config_data
|
15 |
+
from app.mbti_description import MBTI_DESCRIPTION, MBTI_DATA
|
16 |
from app.utils import (
|
17 |
read_csv_file,
|
18 |
apply_rounding_and_rename_columns,
|
|
|
33 |
)
|
34 |
|
35 |
|
36 |
+
def remove_parentheses(s):
|
37 |
+
return re.sub(r"\s*\([^)]*\)", "", s)
|
38 |
+
|
39 |
+
|
40 |
+
def extract_text_in_parentheses(s):
|
41 |
+
result = re.search(r"\(([^)]+)\)", s)
|
42 |
+
if result:
|
43 |
+
return result.group(1)
|
44 |
+
else:
|
45 |
+
return None
|
46 |
+
|
47 |
+
|
48 |
+
def compare_strings(original, comparison):
|
49 |
+
result = []
|
50 |
+
prev_class = None
|
51 |
+
|
52 |
+
for orig_char, comp_char in zip(original, comparison):
|
53 |
+
curr_class = "true" if orig_char == comp_char else "err"
|
54 |
+
if curr_class != prev_class:
|
55 |
+
result.append("</span>" if prev_class else "")
|
56 |
+
result.append(f"<span class='{curr_class}'>")
|
57 |
+
prev_class = curr_class
|
58 |
+
result.append(comp_char)
|
59 |
+
|
60 |
+
return f"<span class='wrapper_mbti'>{''.join(result + [f'</span>' if prev_class else ''])}</span>"
|
61 |
+
|
62 |
+
|
63 |
def event_handler_calculate_practical_task_blocks(
|
64 |
files,
|
65 |
practical_subtasks,
|
66 |
pt_scores,
|
67 |
+
dropdown_mbti,
|
68 |
+
threshold_mbti,
|
69 |
threshold_professional_skills,
|
70 |
dropdown_professional_skills,
|
71 |
target_score_ope,
|
|
|
83 |
number_agreeableness,
|
84 |
number_non_neuroticism,
|
85 |
):
|
86 |
+
if practical_subtasks.lower() == "sixteen myers-briggs personality type indicators":
|
87 |
+
df_correlation_coefficients = read_csv_file(config_data.Links_MBTI)
|
88 |
+
|
89 |
+
pt_scores_copy = pt_scores.iloc[:, 1:].copy()
|
90 |
+
|
91 |
+
preprocess_scores_df(pt_scores_copy, "Person ID")
|
92 |
+
|
93 |
+
b5._professional_match(
|
94 |
+
df_files=pt_scores_copy,
|
95 |
+
correlation_coefficients=df_correlation_coefficients,
|
96 |
+
personality_type=remove_parentheses(dropdown_mbti),
|
97 |
+
threshold=threshold_mbti,
|
98 |
+
out=False,
|
99 |
+
)
|
100 |
+
|
101 |
+
df = apply_rounding_and_rename_columns(b5.df_files_MBTI_job_match_)
|
102 |
+
|
103 |
+
df_hidden = df.drop(
|
104 |
+
columns=config_data.Settings_SHORT_PROFESSIONAL_SKILLS
|
105 |
+
+ config_data.Settings_DROPDOWN_MBTI_DEL_COLS
|
106 |
+
)
|
107 |
+
|
108 |
+
df_hidden.to_csv(config_data.Filenames_MBTI_JOB)
|
109 |
+
|
110 |
+
df_hidden.reset_index(inplace=True)
|
111 |
+
|
112 |
+
person_id = int(df_hidden.iloc[0]["Person ID"]) - 1
|
113 |
+
|
114 |
+
short_mbti = extract_text_in_parentheses(dropdown_mbti)
|
115 |
+
mbti_values = df_hidden["MBTI"].tolist()
|
116 |
+
|
117 |
+
df_hidden["MBTI"] = [compare_strings(short_mbti, mbti) for mbti in mbti_values]
|
118 |
+
|
119 |
+
return (
|
120 |
+
gr.Row(visible=True),
|
121 |
+
gr.Column(visible=True),
|
122 |
+
dataframe(
|
123 |
+
headers=df_hidden.columns.tolist(),
|
124 |
+
values=df_hidden.values.tolist(),
|
125 |
+
visible=True,
|
126 |
+
),
|
127 |
+
files_create_ui(
|
128 |
+
config_data.Filenames_MBTI_JOB,
|
129 |
+
"single",
|
130 |
+
[".csv"],
|
131 |
+
config_data.OtherMessages_EXPORT_MBTI,
|
132 |
+
True,
|
133 |
+
False,
|
134 |
+
True,
|
135 |
+
"csv-container",
|
136 |
+
),
|
137 |
+
gr.Accordion(
|
138 |
+
label=config_data.Labels_NOTE_MBTI_LABEL,
|
139 |
+
open=False,
|
140 |
+
visible=True,
|
141 |
+
),
|
142 |
+
gr.HTML(value=MBTI_DESCRIPTION, visible=True),
|
143 |
+
dataframe(
|
144 |
+
headers=MBTI_DATA.columns.tolist(),
|
145 |
+
values=MBTI_DATA.values.tolist(),
|
146 |
+
visible=True,
|
147 |
+
elem_classes="mbti-dataframe",
|
148 |
+
),
|
149 |
+
video_create_ui(
|
150 |
+
value=files[person_id],
|
151 |
+
file_name=Path(files[person_id]).name,
|
152 |
+
label="Best Person ID - " + str(person_id + 1),
|
153 |
+
visible=True,
|
154 |
+
elem_classes="video-sorted-container",
|
155 |
+
),
|
156 |
+
html_message(config_data.InformationMessages_NOTI_IN_DEV, False, False),
|
157 |
+
)
|
158 |
+
elif practical_subtasks.lower() == "professional groups":
|
159 |
sum_weights = sum(
|
160 |
[
|
161 |
number_openness,
|
|
|
183 |
False,
|
184 |
"csv-container",
|
185 |
),
|
186 |
+
gr.Accordion(visible=False),
|
187 |
+
gr.HTML(visible=False),
|
188 |
+
dataframe(visible=False),
|
189 |
video_create_ui(visible=False),
|
190 |
html_message(
|
191 |
config_data.InformationMessages_SUM_WEIGHTS.format(sum_weights),
|
|
|
232 |
True,
|
233 |
"csv-container",
|
234 |
),
|
235 |
+
gr.Accordion(visible=False),
|
236 |
+
gr.HTML(visible=False),
|
237 |
+
dataframe(visible=False),
|
238 |
video_create_ui(
|
239 |
value=files[person_id],
|
240 |
file_name=Path(files[person_id]).name,
|
241 |
label="Best Person ID - " + str(person_id + 1),
|
242 |
visible=True,
|
243 |
+
elem_classes="video-sorted-container",
|
244 |
),
|
245 |
html_message(config_data.InformationMessages_NOTI_IN_DEV, False, False),
|
246 |
)
|
|
|
295 |
True,
|
296 |
"csv-container",
|
297 |
),
|
298 |
+
gr.Accordion(visible=False),
|
299 |
+
gr.HTML(visible=False),
|
300 |
+
dataframe(visible=False),
|
301 |
video_create_ui(
|
302 |
value=files[person_id],
|
303 |
file_name=Path(files[person_id]).name,
|
304 |
label="Best Person ID - " + str(person_id + 1),
|
305 |
visible=True,
|
306 |
+
elem_classes="video-sorted-container",
|
307 |
),
|
308 |
html_message(config_data.InformationMessages_NOTI_IN_DEV, False, False),
|
309 |
)
|
|
|
361 |
True,
|
362 |
"csv-container",
|
363 |
),
|
364 |
+
gr.Accordion(visible=False),
|
365 |
+
gr.HTML(visible=False),
|
366 |
+
dataframe(visible=False),
|
367 |
video_create_ui(
|
368 |
value=files[person_id],
|
369 |
file_name=Path(files[person_id]).name,
|
370 |
label="Best Person ID - " + str(person_id + 1),
|
371 |
visible=True,
|
372 |
+
elem_classes="video-sorted-container",
|
373 |
),
|
374 |
html_message(config_data.InformationMessages_NOTI_IN_DEV, False, False),
|
375 |
)
|
376 |
elif (
|
377 |
practical_subtasks.lower() == "car characteristics"
|
378 |
or practical_subtasks.lower() == "mobile device application categories"
|
379 |
+
or practical_subtasks.lower() == "clothing style correlation"
|
380 |
):
|
381 |
if practical_subtasks.lower() == "car characteristics":
|
382 |
df_correlation_coefficients = read_csv_file(
|
383 |
config_data.Links_CAR_CHARACTERISTICS,
|
384 |
["Style and performance", "Safety and practicality"],
|
385 |
)
|
386 |
+
elif practical_subtasks.lower() == "mobile device application categories":
|
387 |
df_correlation_coefficients = read_csv_file(
|
388 |
config_data.Links_MDA_CATEGORIES
|
389 |
)
|
390 |
+
elif practical_subtasks.lower() == "clothing style correlation":
|
391 |
+
df_correlation_coefficients = read_csv_file(config_data.Links_CLOTHING_SC)
|
392 |
|
393 |
pt_scores_copy = pt_scores.iloc[:, 1:].copy()
|
394 |
|
|
|
437 |
True,
|
438 |
"csv-container",
|
439 |
),
|
440 |
+
gr.Accordion(visible=False),
|
441 |
+
gr.HTML(visible=False),
|
442 |
+
dataframe(visible=False),
|
443 |
video_create_ui(
|
444 |
value=files[person_id],
|
445 |
file_name=Path(files[person_id]).name,
|
446 |
label="Best Person ID - " + str(person_id + 1),
|
447 |
visible=True,
|
448 |
+
elem_classes="video-sorted-container",
|
449 |
),
|
450 |
html_message(config_data.InformationMessages_NOTI_IN_DEV, False, False),
|
451 |
)
|
|
|
466 |
False,
|
467 |
"csv-container",
|
468 |
),
|
469 |
+
gr.Accordion(visible=False),
|
470 |
+
gr.HTML(visible=False),
|
471 |
+
dataframe(visible=False),
|
472 |
video_create_ui(visible=False),
|
473 |
html_message(config_data.InformationMessages_NOTI_IN_DEV, False, True),
|
474 |
)
|
app/event_handlers/calculate_pt_scores_blocks.py
CHANGED
@@ -90,6 +90,27 @@ def event_handler_calculate_pt_scores_blocks(files, evt_data: gr.EventData):
|
|
90 |
render=True,
|
91 |
),
|
92 |
gr.Column(visible=True),
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
93 |
number_create_ui(visible=False),
|
94 |
dropdown_create_ui(visible=False),
|
95 |
number_create_ui(visible=False),
|
@@ -101,89 +122,12 @@ def event_handler_calculate_pt_scores_blocks(files, evt_data: gr.EventData):
|
|
101 |
number_create_ui(visible=False),
|
102 |
number_create_ui(visible=False),
|
103 |
number_create_ui(visible=False),
|
104 |
-
dropdown_create_ui(
|
105 |
-
|
106 |
-
|
107 |
-
|
108 |
-
|
109 |
-
|
110 |
-
elem_classes="dropdown-container",
|
111 |
-
),
|
112 |
-
number_create_ui(
|
113 |
-
value=weights_professions[0],
|
114 |
-
minimum=config_data.Values_0_100[0],
|
115 |
-
maximum=config_data.Values_0_100[1],
|
116 |
-
step=1,
|
117 |
-
label=config_data.Labels_NUMBER_IMPORTANCE_OPE_LABEL,
|
118 |
-
info=config_data.InformationMessages_VALUE_FROM_TO_INFO.format(
|
119 |
-
config_data.Values_0_100[0], config_data.Values_0_100[1]
|
120 |
-
),
|
121 |
-
show_label=True,
|
122 |
-
interactive=interactive_professions,
|
123 |
-
visible=True,
|
124 |
-
render=True,
|
125 |
-
elem_classes="number-container",
|
126 |
-
),
|
127 |
-
number_create_ui(
|
128 |
-
value=weights_professions[1],
|
129 |
-
minimum=config_data.Values_0_100[0],
|
130 |
-
maximum=config_data.Values_0_100[1],
|
131 |
-
step=1,
|
132 |
-
label=config_data.Labels_NUMBER_IMPORTANCE_CON_LABEL,
|
133 |
-
info=config_data.InformationMessages_VALUE_FROM_TO_INFO.format(
|
134 |
-
config_data.Values_0_100[0], config_data.Values_0_100[1]
|
135 |
-
),
|
136 |
-
show_label=True,
|
137 |
-
interactive=interactive_professions,
|
138 |
-
visible=True,
|
139 |
-
render=True,
|
140 |
-
elem_classes="number-container",
|
141 |
-
),
|
142 |
-
number_create_ui(
|
143 |
-
value=weights_professions[2],
|
144 |
-
minimum=config_data.Values_0_100[0],
|
145 |
-
maximum=config_data.Values_0_100[1],
|
146 |
-
step=1,
|
147 |
-
label=config_data.Labels_NUMBER_IMPORTANCE_EXT_LABEL,
|
148 |
-
info=config_data.InformationMessages_VALUE_FROM_TO_INFO.format(
|
149 |
-
config_data.Values_0_100[0], config_data.Values_0_100[1]
|
150 |
-
),
|
151 |
-
show_label=True,
|
152 |
-
interactive=interactive_professions,
|
153 |
-
visible=True,
|
154 |
-
render=True,
|
155 |
-
elem_classes="number-container",
|
156 |
-
),
|
157 |
-
number_create_ui(
|
158 |
-
value=weights_professions[3],
|
159 |
-
minimum=config_data.Values_0_100[0],
|
160 |
-
maximum=config_data.Values_0_100[1],
|
161 |
-
step=1,
|
162 |
-
label=config_data.Labels_NUMBER_IMPORTANCE_AGR_LABEL,
|
163 |
-
info=config_data.InformationMessages_VALUE_FROM_TO_INFO.format(
|
164 |
-
config_data.Values_0_100[0], config_data.Values_0_100[1]
|
165 |
-
),
|
166 |
-
show_label=True,
|
167 |
-
interactive=interactive_professions,
|
168 |
-
visible=True,
|
169 |
-
render=True,
|
170 |
-
elem_classes="number-container",
|
171 |
-
),
|
172 |
-
number_create_ui(
|
173 |
-
value=weights_professions[4],
|
174 |
-
minimum=config_data.Values_0_100[0],
|
175 |
-
maximum=config_data.Values_0_100[1],
|
176 |
-
step=1,
|
177 |
-
label=config_data.Labels_NUMBER_IMPORTANCE_NNEU_LABEL,
|
178 |
-
info=config_data.InformationMessages_VALUE_FROM_TO_INFO.format(
|
179 |
-
config_data.Values_0_100[0], config_data.Values_0_100[1]
|
180 |
-
),
|
181 |
-
show_label=True,
|
182 |
-
interactive=interactive_professions,
|
183 |
-
visible=True,
|
184 |
-
render=True,
|
185 |
-
elem_classes="number-container",
|
186 |
-
),
|
187 |
button(
|
188 |
config_data.OtherMessages_CALCULATE_PRACTICAL_TASK,
|
189 |
True,
|
@@ -204,6 +148,9 @@ def event_handler_calculate_pt_scores_blocks(files, evt_data: gr.EventData):
|
|
204 |
False,
|
205 |
"csv-container",
|
206 |
),
|
|
|
|
|
|
|
207 |
video_create_ui(visible=False),
|
208 |
html_message(config_data.InformationMessages_NOTI_IN_DEV, False, False),
|
209 |
)
|
|
|
90 |
render=True,
|
91 |
),
|
92 |
gr.Column(visible=True),
|
93 |
+
dropdown_create_ui(
|
94 |
+
label=f"Potential candidates by Myers-Briggs Personality Type Indicators ({len(config_data.Settings_DROPDOWN_MBTI)})",
|
95 |
+
info=config_data.InformationMessages_DROPDOWN_MBTI_INFO,
|
96 |
+
choices=config_data.Settings_DROPDOWN_MBTI,
|
97 |
+
value=config_data.Settings_DROPDOWN_MBTI[0],
|
98 |
+
visible=True,
|
99 |
+
elem_classes="dropdown-container",
|
100 |
+
),
|
101 |
+
number_create_ui(
|
102 |
+
value=0.5,
|
103 |
+
minimum=0.0,
|
104 |
+
maximum=1.0,
|
105 |
+
step=0.01,
|
106 |
+
label=config_data.Labels_THRESHOLD_MBTI_LABEL,
|
107 |
+
info=config_data.InformationMessages_VALUE_FROM_TO_INFO.format(0, 1.0),
|
108 |
+
show_label=True,
|
109 |
+
interactive=True,
|
110 |
+
visible=True,
|
111 |
+
render=True,
|
112 |
+
elem_classes="number-container",
|
113 |
+
),
|
114 |
number_create_ui(visible=False),
|
115 |
dropdown_create_ui(visible=False),
|
116 |
number_create_ui(visible=False),
|
|
|
122 |
number_create_ui(visible=False),
|
123 |
number_create_ui(visible=False),
|
124 |
number_create_ui(visible=False),
|
125 |
+
dropdown_create_ui(visible=False),
|
126 |
+
number_create_ui(visible=False),
|
127 |
+
number_create_ui(visible=False),
|
128 |
+
number_create_ui(visible=False),
|
129 |
+
number_create_ui(visible=False),
|
130 |
+
number_create_ui(visible=False),
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
131 |
button(
|
132 |
config_data.OtherMessages_CALCULATE_PRACTICAL_TASK,
|
133 |
True,
|
|
|
148 |
False,
|
149 |
"csv-container",
|
150 |
),
|
151 |
+
gr.Accordion(visible=False),
|
152 |
+
gr.HTML(visible=False),
|
153 |
+
dataframe(visible=False),
|
154 |
video_create_ui(visible=False),
|
155 |
html_message(config_data.InformationMessages_NOTI_IN_DEV, False, False),
|
156 |
)
|
app/event_handlers/clear_blocks.py
CHANGED
@@ -76,6 +76,8 @@ def event_handler_clear_blocks():
|
|
76 |
render=True,
|
77 |
),
|
78 |
gr.Column(visible=False),
|
|
|
|
|
79 |
number_create_ui(visible=False),
|
80 |
dropdown_create_ui(visible=False),
|
81 |
number_create_ui(visible=False),
|
@@ -106,6 +108,9 @@ def event_handler_clear_blocks():
|
|
106 |
False,
|
107 |
"csv-container",
|
108 |
),
|
|
|
|
|
|
|
109 |
video_create_ui(visible=False),
|
110 |
html_message(config_data.InformationMessages_NOTI_IN_DEV, False, False),
|
111 |
)
|
|
|
76 |
render=True,
|
77 |
),
|
78 |
gr.Column(visible=False),
|
79 |
+
dropdown_create_ui(visible=False),
|
80 |
+
number_create_ui(visible=False),
|
81 |
number_create_ui(visible=False),
|
82 |
dropdown_create_ui(visible=False),
|
83 |
number_create_ui(visible=False),
|
|
|
108 |
False,
|
109 |
"csv-container",
|
110 |
),
|
111 |
+
gr.Accordion(visible=False),
|
112 |
+
gr.HTML(visible=False),
|
113 |
+
dataframe(visible=False),
|
114 |
video_create_ui(visible=False),
|
115 |
html_message(config_data.InformationMessages_NOTI_IN_DEV, False, False),
|
116 |
)
|
app/event_handlers/event_handlers.py
CHANGED
@@ -8,6 +8,7 @@ License: MIT License
|
|
8 |
import gradio as gr
|
9 |
|
10 |
# Importing necessary components for the Gradio app
|
|
|
11 |
from app.event_handlers.files import (
|
12 |
event_handler_files,
|
13 |
event_handler_files_select,
|
@@ -39,6 +40,8 @@ def setup_app_event_handlers(
|
|
39 |
practical_tasks,
|
40 |
practical_subtasks,
|
41 |
settings_practical_tasks,
|
|
|
|
|
42 |
threshold_professional_skills,
|
43 |
dropdown_professional_skills,
|
44 |
target_score_ope,
|
@@ -63,10 +66,23 @@ def setup_app_event_handlers(
|
|
63 |
sorted_videos_column,
|
64 |
practical_task_sorted,
|
65 |
csv_practical_task_sorted,
|
|
|
|
|
|
|
66 |
video_sorted,
|
67 |
in_development,
|
|
|
|
|
|
|
|
|
68 |
):
|
69 |
# Events
|
|
|
|
|
|
|
|
|
|
|
|
|
70 |
files.change(
|
71 |
event_handler_files,
|
72 |
[files],
|
@@ -95,6 +111,8 @@ def setup_app_event_handlers(
|
|
95 |
practical_subtasks,
|
96 |
practical_subtasks_selected,
|
97 |
settings_practical_tasks,
|
|
|
|
|
98 |
threshold_professional_skills,
|
99 |
dropdown_professional_skills,
|
100 |
target_score_ope,
|
@@ -117,6 +135,9 @@ def setup_app_event_handlers(
|
|
117 |
sorted_videos_column,
|
118 |
practical_task_sorted,
|
119 |
csv_practical_task_sorted,
|
|
|
|
|
|
|
120 |
video_sorted,
|
121 |
in_development,
|
122 |
],
|
@@ -147,6 +168,8 @@ def setup_app_event_handlers(
|
|
147 |
practical_subtasks,
|
148 |
practical_subtasks_selected,
|
149 |
settings_practical_tasks,
|
|
|
|
|
150 |
threshold_professional_skills,
|
151 |
dropdown_professional_skills,
|
152 |
target_score_ope,
|
@@ -168,6 +191,9 @@ def setup_app_event_handlers(
|
|
168 |
sorted_videos_column,
|
169 |
practical_task_sorted,
|
170 |
csv_practical_task_sorted,
|
|
|
|
|
|
|
171 |
video_sorted,
|
172 |
in_development,
|
173 |
],
|
@@ -185,6 +211,8 @@ def setup_app_event_handlers(
|
|
185 |
[
|
186 |
practical_subtasks_selected,
|
187 |
settings_practical_tasks,
|
|
|
|
|
188 |
threshold_professional_skills,
|
189 |
dropdown_professional_skills,
|
190 |
target_score_ope,
|
@@ -223,6 +251,8 @@ def setup_app_event_handlers(
|
|
223 |
files,
|
224 |
practical_subtasks,
|
225 |
pt_scores,
|
|
|
|
|
226 |
threshold_professional_skills,
|
227 |
dropdown_professional_skills,
|
228 |
target_score_ope,
|
@@ -245,6 +275,9 @@ def setup_app_event_handlers(
|
|
245 |
sorted_videos_column,
|
246 |
practical_task_sorted,
|
247 |
csv_practical_task_sorted,
|
|
|
|
|
|
|
248 |
video_sorted,
|
249 |
in_development,
|
250 |
],
|
|
|
8 |
import gradio as gr
|
9 |
|
10 |
# Importing necessary components for the Gradio app
|
11 |
+
from app.event_handlers.languages import event_handler_languages
|
12 |
from app.event_handlers.files import (
|
13 |
event_handler_files,
|
14 |
event_handler_files_select,
|
|
|
40 |
practical_tasks,
|
41 |
practical_subtasks,
|
42 |
settings_practical_tasks,
|
43 |
+
dropdown_mbti,
|
44 |
+
threshold_mbti,
|
45 |
threshold_professional_skills,
|
46 |
dropdown_professional_skills,
|
47 |
target_score_ope,
|
|
|
66 |
sorted_videos_column,
|
67 |
practical_task_sorted,
|
68 |
csv_practical_task_sorted,
|
69 |
+
mbti_accordion,
|
70 |
+
mbti_description,
|
71 |
+
mbti_description_data,
|
72 |
video_sorted,
|
73 |
in_development,
|
74 |
+
tab1,
|
75 |
+
tab2,
|
76 |
+
tab3,
|
77 |
+
languages,
|
78 |
):
|
79 |
# Events
|
80 |
+
languages.select(
|
81 |
+
fn=event_handler_languages,
|
82 |
+
inputs=[languages],
|
83 |
+
outputs=[languages, tab1, tab2, tab3],
|
84 |
+
queue=True,
|
85 |
+
)
|
86 |
files.change(
|
87 |
event_handler_files,
|
88 |
[files],
|
|
|
111 |
practical_subtasks,
|
112 |
practical_subtasks_selected,
|
113 |
settings_practical_tasks,
|
114 |
+
dropdown_mbti,
|
115 |
+
threshold_mbti,
|
116 |
threshold_professional_skills,
|
117 |
dropdown_professional_skills,
|
118 |
target_score_ope,
|
|
|
135 |
sorted_videos_column,
|
136 |
practical_task_sorted,
|
137 |
csv_practical_task_sorted,
|
138 |
+
mbti_accordion,
|
139 |
+
mbti_description,
|
140 |
+
mbti_description_data,
|
141 |
video_sorted,
|
142 |
in_development,
|
143 |
],
|
|
|
168 |
practical_subtasks,
|
169 |
practical_subtasks_selected,
|
170 |
settings_practical_tasks,
|
171 |
+
dropdown_mbti,
|
172 |
+
threshold_mbti,
|
173 |
threshold_professional_skills,
|
174 |
dropdown_professional_skills,
|
175 |
target_score_ope,
|
|
|
191 |
sorted_videos_column,
|
192 |
practical_task_sorted,
|
193 |
csv_practical_task_sorted,
|
194 |
+
mbti_accordion,
|
195 |
+
mbti_description,
|
196 |
+
mbti_description_data,
|
197 |
video_sorted,
|
198 |
in_development,
|
199 |
],
|
|
|
211 |
[
|
212 |
practical_subtasks_selected,
|
213 |
settings_practical_tasks,
|
214 |
+
dropdown_mbti,
|
215 |
+
threshold_mbti,
|
216 |
threshold_professional_skills,
|
217 |
dropdown_professional_skills,
|
218 |
target_score_ope,
|
|
|
251 |
files,
|
252 |
practical_subtasks,
|
253 |
pt_scores,
|
254 |
+
dropdown_mbti,
|
255 |
+
threshold_mbti,
|
256 |
threshold_professional_skills,
|
257 |
dropdown_professional_skills,
|
258 |
target_score_ope,
|
|
|
275 |
sorted_videos_column,
|
276 |
practical_task_sorted,
|
277 |
csv_practical_task_sorted,
|
278 |
+
mbti_accordion,
|
279 |
+
mbti_description,
|
280 |
+
mbti_description_data,
|
281 |
video_sorted,
|
282 |
in_development,
|
283 |
],
|
app/event_handlers/languages.py
ADDED
@@ -0,0 +1,39 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
"""
|
2 |
+
File: languages.py
|
3 |
+
Author: Elena Ryumina and Dmitry Ryumin
|
4 |
+
Description: Selected language event handlers for Gradio app.
|
5 |
+
License: MIT License
|
6 |
+
"""
|
7 |
+
|
8 |
+
import gradio as gr
|
9 |
+
|
10 |
+
# Importing necessary components for the Gradio app
|
11 |
+
from app.config import config_data
|
12 |
+
from app.components import dropdown_create_ui
|
13 |
+
|
14 |
+
|
15 |
+
def event_handler_languages(languages):
|
16 |
+
if languages.lower() == "english":
|
17 |
+
lang_id = 0
|
18 |
+
choices = config_data.Settings_LANGUAGES_EN
|
19 |
+
elif languages.lower() == "russian":
|
20 |
+
lang_id = 1
|
21 |
+
choices = config_data.Settings_LANGUAGES_RU
|
22 |
+
else:
|
23 |
+
lang_id = 0
|
24 |
+
choices = config_data.Settings_LANGUAGES_EN
|
25 |
+
|
26 |
+
return (
|
27 |
+
dropdown_create_ui(
|
28 |
+
label=None,
|
29 |
+
info=None,
|
30 |
+
choices=choices,
|
31 |
+
value=choices[lang_id],
|
32 |
+
visible=True,
|
33 |
+
show_label=False,
|
34 |
+
elem_classes="dropdown-language-container",
|
35 |
+
),
|
36 |
+
gr.Tab(config_data.Labels_APP_LABEL[lang_id]),
|
37 |
+
gr.Tab(config_data.Labels_ABOUT_APP_LABEL[lang_id]),
|
38 |
+
gr.Tab(config_data.Labels_ABOUT_AUTHORS_LABEL[lang_id]),
|
39 |
+
)
|
app/event_handlers/practical_subtasks.py
CHANGED
@@ -18,7 +18,50 @@ def event_handler_practical_subtasks(
|
|
18 |
):
|
19 |
practical_subtasks_selected[practical_tasks] = practical_subtasks
|
20 |
|
21 |
-
if practical_subtasks.lower() == "
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
22 |
df_traits_priority_for_professions = read_csv_file(
|
23 |
config_data.Links_PROFESSIONS
|
24 |
)
|
@@ -30,6 +73,8 @@ def event_handler_practical_subtasks(
|
|
30 |
return (
|
31 |
practical_subtasks_selected,
|
32 |
gr.Column(visible=True),
|
|
|
|
|
33 |
number_create_ui(visible=False),
|
34 |
dropdown_create_ui(visible=False),
|
35 |
number_create_ui(visible=False),
|
@@ -129,6 +174,8 @@ def event_handler_practical_subtasks(
|
|
129 |
return (
|
130 |
practical_subtasks_selected,
|
131 |
gr.Column(visible=True),
|
|
|
|
|
132 |
number_create_ui(
|
133 |
value=0.5,
|
134 |
minimum=0.0,
|
@@ -173,6 +220,8 @@ def event_handler_practical_subtasks(
|
|
173 |
return (
|
174 |
practical_subtasks_selected,
|
175 |
gr.Column(visible=True),
|
|
|
|
|
176 |
number_create_ui(visible=False),
|
177 |
dropdown_create_ui(visible=False),
|
178 |
number_create_ui(
|
@@ -266,6 +315,7 @@ def event_handler_practical_subtasks(
|
|
266 |
elif (
|
267 |
practical_subtasks.lower() == "car characteristics"
|
268 |
or practical_subtasks.lower() == "mobile device application categories"
|
|
|
269 |
):
|
270 |
df_correlation_coefficients = read_csv_file(
|
271 |
config_data.Links_CAR_CHARACTERISTICS,
|
@@ -275,6 +325,8 @@ def event_handler_practical_subtasks(
|
|
275 |
return (
|
276 |
practical_subtasks_selected,
|
277 |
gr.Column(visible=True),
|
|
|
|
|
278 |
number_create_ui(visible=False),
|
279 |
dropdown_create_ui(visible=False),
|
280 |
number_create_ui(visible=False),
|
@@ -284,7 +336,7 @@ def event_handler_practical_subtasks(
|
|
284 |
number_create_ui(visible=False),
|
285 |
number_create_ui(visible=False),
|
286 |
number_create_ui(
|
287 |
-
value=
|
288 |
minimum=1,
|
289 |
maximum=df_correlation_coefficients.columns.size,
|
290 |
step=1,
|
@@ -299,7 +351,7 @@ def event_handler_practical_subtasks(
|
|
299 |
elem_classes="number-container",
|
300 |
),
|
301 |
number_create_ui(
|
302 |
-
value=
|
303 |
minimum=1,
|
304 |
maximum=5,
|
305 |
step=1,
|
@@ -335,6 +387,8 @@ def event_handler_practical_subtasks(
|
|
335 |
return (
|
336 |
practical_subtasks_selected,
|
337 |
gr.Column(visible=False),
|
|
|
|
|
338 |
number_create_ui(visible=False),
|
339 |
dropdown_create_ui(visible=False),
|
340 |
number_create_ui(visible=False),
|
|
|
18 |
):
|
19 |
practical_subtasks_selected[practical_tasks] = practical_subtasks
|
20 |
|
21 |
+
if practical_subtasks.lower() == "sixteen myers-briggs personality type indicators":
|
22 |
+
return (
|
23 |
+
practical_subtasks_selected,
|
24 |
+
gr.Column(visible=True),
|
25 |
+
dropdown_create_ui(
|
26 |
+
label=f"Potential candidates by Myers-Briggs Personality Type Indicators ({len(config_data.Settings_DROPDOWN_MBTI)})",
|
27 |
+
info=config_data.InformationMessages_DROPDOWN_MBTI_INFO,
|
28 |
+
choices=config_data.Settings_DROPDOWN_MBTI,
|
29 |
+
value=config_data.Settings_DROPDOWN_MBTI[0],
|
30 |
+
visible=True,
|
31 |
+
elem_classes="dropdown-container",
|
32 |
+
),
|
33 |
+
number_create_ui(
|
34 |
+
value=0.5,
|
35 |
+
minimum=0.0,
|
36 |
+
maximum=1.0,
|
37 |
+
step=0.01,
|
38 |
+
label=config_data.Labels_THRESHOLD_MBTI_LABEL,
|
39 |
+
info=config_data.InformationMessages_VALUE_FROM_TO_INFO.format(0, 1.0),
|
40 |
+
show_label=True,
|
41 |
+
interactive=True,
|
42 |
+
visible=True,
|
43 |
+
render=True,
|
44 |
+
elem_classes="number-container",
|
45 |
+
),
|
46 |
+
number_create_ui(visible=False),
|
47 |
+
dropdown_create_ui(visible=False),
|
48 |
+
number_create_ui(visible=False),
|
49 |
+
number_create_ui(visible=False),
|
50 |
+
number_create_ui(visible=False),
|
51 |
+
number_create_ui(visible=False),
|
52 |
+
number_create_ui(visible=False),
|
53 |
+
number_create_ui(visible=False),
|
54 |
+
number_create_ui(visible=False),
|
55 |
+
number_create_ui(visible=False),
|
56 |
+
number_create_ui(visible=False),
|
57 |
+
dropdown_create_ui(visible=False),
|
58 |
+
number_create_ui(visible=False),
|
59 |
+
number_create_ui(visible=False),
|
60 |
+
number_create_ui(visible=False),
|
61 |
+
number_create_ui(visible=False),
|
62 |
+
number_create_ui(visible=False),
|
63 |
+
)
|
64 |
+
elif practical_subtasks.lower() == "professional groups":
|
65 |
df_traits_priority_for_professions = read_csv_file(
|
66 |
config_data.Links_PROFESSIONS
|
67 |
)
|
|
|
73 |
return (
|
74 |
practical_subtasks_selected,
|
75 |
gr.Column(visible=True),
|
76 |
+
dropdown_create_ui(visible=False),
|
77 |
+
number_create_ui(visible=False),
|
78 |
number_create_ui(visible=False),
|
79 |
dropdown_create_ui(visible=False),
|
80 |
number_create_ui(visible=False),
|
|
|
174 |
return (
|
175 |
practical_subtasks_selected,
|
176 |
gr.Column(visible=True),
|
177 |
+
dropdown_create_ui(visible=False),
|
178 |
+
number_create_ui(visible=False),
|
179 |
number_create_ui(
|
180 |
value=0.5,
|
181 |
minimum=0.0,
|
|
|
220 |
return (
|
221 |
practical_subtasks_selected,
|
222 |
gr.Column(visible=True),
|
223 |
+
dropdown_create_ui(visible=False),
|
224 |
+
number_create_ui(visible=False),
|
225 |
number_create_ui(visible=False),
|
226 |
dropdown_create_ui(visible=False),
|
227 |
number_create_ui(
|
|
|
315 |
elif (
|
316 |
practical_subtasks.lower() == "car characteristics"
|
317 |
or practical_subtasks.lower() == "mobile device application categories"
|
318 |
+
or practical_subtasks.lower() == "clothing style correlation"
|
319 |
):
|
320 |
df_correlation_coefficients = read_csv_file(
|
321 |
config_data.Links_CAR_CHARACTERISTICS,
|
|
|
325 |
return (
|
326 |
practical_subtasks_selected,
|
327 |
gr.Column(visible=True),
|
328 |
+
dropdown_create_ui(visible=False),
|
329 |
+
number_create_ui(visible=False),
|
330 |
number_create_ui(visible=False),
|
331 |
dropdown_create_ui(visible=False),
|
332 |
number_create_ui(visible=False),
|
|
|
336 |
number_create_ui(visible=False),
|
337 |
number_create_ui(visible=False),
|
338 |
number_create_ui(
|
339 |
+
value=1,
|
340 |
minimum=1,
|
341 |
maximum=df_correlation_coefficients.columns.size,
|
342 |
step=1,
|
|
|
351 |
elem_classes="number-container",
|
352 |
),
|
353 |
number_create_ui(
|
354 |
+
value=1,
|
355 |
minimum=1,
|
356 |
maximum=5,
|
357 |
step=1,
|
|
|
387 |
return (
|
388 |
practical_subtasks_selected,
|
389 |
gr.Column(visible=False),
|
390 |
+
dropdown_create_ui(visible=False),
|
391 |
+
number_create_ui(visible=False),
|
392 |
number_create_ui(visible=False),
|
393 |
dropdown_create_ui(visible=False),
|
394 |
number_create_ui(visible=False),
|
app/mbti_description.py
ADDED
@@ -0,0 +1,29 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
"""
|
2 |
+
File: mbti_description.py
|
3 |
+
Author: Elena Ryumina and Dmitry Ryumin
|
4 |
+
Description: Personality dimensions description.
|
5 |
+
License: MIT License
|
6 |
+
"""
|
7 |
+
|
8 |
+
import pandas as pd
|
9 |
+
|
10 |
+
# Importing necessary components for the Gradio app
|
11 |
+
|
12 |
+
MBTI_DATA = pd.DataFrame(
|
13 |
+
{
|
14 |
+
"Dimension description": [
|
15 |
+
"How we interact with the world and where we direct our energy",
|
16 |
+
"The kind of information we naturally notice",
|
17 |
+
"How we make decisions",
|
18 |
+
"Whether we prefer to live in a more structured way (making decisions) or in a more spontaneous way (taking in information)",
|
19 |
+
],
|
20 |
+
"Dimension": [
|
21 |
+
"(E) Extraversion - Introversion (I)",
|
22 |
+
"(S) Sensing - Intuition (N)",
|
23 |
+
"(T) Thinking - Feeling (F)",
|
24 |
+
"(J) Judging - Perceiving (P)",
|
25 |
+
],
|
26 |
+
}
|
27 |
+
)
|
28 |
+
|
29 |
+
MBTI_DESCRIPTION = "<h4>The four human Personality Dimensions</h4>"
|
app/tabs.py
CHANGED
@@ -10,6 +10,7 @@ import gradio as gr
|
|
10 |
# Importing necessary components for the Gradio app
|
11 |
from app.description import DESCRIPTION
|
12 |
from app.description_steps import STEP_1, STEP_2
|
|
|
13 |
from app.app import APP
|
14 |
from app.authors import AUTHORS
|
15 |
from app.config import config_data
|
@@ -96,6 +97,29 @@ def app_tab():
|
|
96 |
variant="default",
|
97 |
elem_classes="settings-container",
|
98 |
) as settings_practical_tasks:
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
99 |
threshold_professional_skills = number_create_ui(
|
100 |
value=0.5,
|
101 |
minimum=0.0,
|
@@ -209,7 +233,7 @@ def app_tab():
|
|
209 |
)
|
210 |
|
211 |
number_priority = number_create_ui(
|
212 |
-
value=
|
213 |
minimum=1,
|
214 |
maximum=df_correlation_coefficients.columns.size,
|
215 |
step=1,
|
@@ -225,7 +249,7 @@ def app_tab():
|
|
225 |
)
|
226 |
|
227 |
number_importance_traits = number_create_ui(
|
228 |
-
value=
|
229 |
minimum=1,
|
230 |
maximum=5,
|
231 |
step=1,
|
@@ -365,6 +389,20 @@ def app_tab():
|
|
365 |
with gr.Column(scale=1, visible=False, render=True) as sorted_videos_column:
|
366 |
practical_task_sorted = dataframe(visible=False)
|
367 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
368 |
csv_practical_task_sorted = files_create_ui(
|
369 |
None,
|
370 |
"single",
|
@@ -376,7 +414,9 @@ def app_tab():
|
|
376 |
"csv-container",
|
377 |
)
|
378 |
|
379 |
-
video_sorted = video_create_ui(
|
|
|
|
|
380 |
|
381 |
practical_subtasks_selected = gr.JSON(
|
382 |
value={
|
@@ -404,6 +444,8 @@ def app_tab():
|
|
404 |
practical_tasks,
|
405 |
practical_subtasks,
|
406 |
settings_practical_tasks,
|
|
|
|
|
407 |
threshold_professional_skills,
|
408 |
dropdown_professional_skills,
|
409 |
target_score_ope,
|
@@ -428,6 +470,9 @@ def app_tab():
|
|
428 |
sorted_videos_column,
|
429 |
practical_task_sorted,
|
430 |
csv_practical_task_sorted,
|
|
|
|
|
|
|
431 |
video_sorted,
|
432 |
in_development,
|
433 |
)
|
|
|
10 |
# Importing necessary components for the Gradio app
|
11 |
from app.description import DESCRIPTION
|
12 |
from app.description_steps import STEP_1, STEP_2
|
13 |
+
from app.mbti_description import MBTI_DESCRIPTION, MBTI_DATA
|
14 |
from app.app import APP
|
15 |
from app.authors import AUTHORS
|
16 |
from app.config import config_data
|
|
|
97 |
variant="default",
|
98 |
elem_classes="settings-container",
|
99 |
) as settings_practical_tasks:
|
100 |
+
dropdown_mbti = dropdown_create_ui(
|
101 |
+
label=f"Potential candidates by Myers-Briggs Personality Type Indicators ({len(config_data.Settings_DROPDOWN_MBTI)})",
|
102 |
+
info=config_data.InformationMessages_DROPDOWN_MBTI_INFO,
|
103 |
+
choices=config_data.Settings_DROPDOWN_MBTI,
|
104 |
+
value=config_data.Settings_DROPDOWN_MBTI[0],
|
105 |
+
visible=False,
|
106 |
+
elem_classes="dropdown-container",
|
107 |
+
)
|
108 |
+
|
109 |
+
threshold_mbti = number_create_ui(
|
110 |
+
value=0.5,
|
111 |
+
minimum=0.0,
|
112 |
+
maximum=1.0,
|
113 |
+
step=0.01,
|
114 |
+
label=config_data.Labels_THRESHOLD_MBTI_LABEL,
|
115 |
+
info=config_data.InformationMessages_VALUE_FROM_TO_INFO.format(0, 1.0),
|
116 |
+
show_label=True,
|
117 |
+
interactive=True,
|
118 |
+
visible=False,
|
119 |
+
render=True,
|
120 |
+
elem_classes="number-container",
|
121 |
+
)
|
122 |
+
|
123 |
threshold_professional_skills = number_create_ui(
|
124 |
value=0.5,
|
125 |
minimum=0.0,
|
|
|
233 |
)
|
234 |
|
235 |
number_priority = number_create_ui(
|
236 |
+
value=1,
|
237 |
minimum=1,
|
238 |
maximum=df_correlation_coefficients.columns.size,
|
239 |
step=1,
|
|
|
249 |
)
|
250 |
|
251 |
number_importance_traits = number_create_ui(
|
252 |
+
value=1,
|
253 |
minimum=1,
|
254 |
maximum=5,
|
255 |
step=1,
|
|
|
389 |
with gr.Column(scale=1, visible=False, render=True) as sorted_videos_column:
|
390 |
practical_task_sorted = dataframe(visible=False)
|
391 |
|
392 |
+
with gr.Accordion(
|
393 |
+
label=config_data.Labels_NOTE_MBTI_LABEL,
|
394 |
+
open=False,
|
395 |
+
visible=False,
|
396 |
+
) as mbti_accordion:
|
397 |
+
mbti_description = gr.HTML(value=MBTI_DESCRIPTION, visible=False)
|
398 |
+
|
399 |
+
mbti_description_data = dataframe(
|
400 |
+
headers=MBTI_DATA.columns.tolist(),
|
401 |
+
values=MBTI_DATA.values.tolist(),
|
402 |
+
visible=False,
|
403 |
+
elem_classes="mbti-dataframe",
|
404 |
+
)
|
405 |
+
|
406 |
csv_practical_task_sorted = files_create_ui(
|
407 |
None,
|
408 |
"single",
|
|
|
414 |
"csv-container",
|
415 |
)
|
416 |
|
417 |
+
video_sorted = video_create_ui(
|
418 |
+
visible=False, elem_classes="video-sorted-container"
|
419 |
+
)
|
420 |
|
421 |
practical_subtasks_selected = gr.JSON(
|
422 |
value={
|
|
|
444 |
practical_tasks,
|
445 |
practical_subtasks,
|
446 |
settings_practical_tasks,
|
447 |
+
dropdown_mbti,
|
448 |
+
threshold_mbti,
|
449 |
threshold_professional_skills,
|
450 |
dropdown_professional_skills,
|
451 |
target_score_ope,
|
|
|
470 |
sorted_videos_column,
|
471 |
practical_task_sorted,
|
472 |
csv_practical_task_sorted,
|
473 |
+
mbti_accordion,
|
474 |
+
mbti_description,
|
475 |
+
mbti_description_data,
|
476 |
video_sorted,
|
477 |
in_development,
|
478 |
)
|
config.toml
CHANGED
@@ -1,5 +1,5 @@
|
|
1 |
[AppSettings]
|
2 |
-
APP_VERSION = "0.
|
3 |
CSS_PATH = "app.css"
|
4 |
|
5 |
[InformationMessages]
|
@@ -7,9 +7,11 @@ NOTI_VIDEOS = "Select the video(s)"
|
|
7 |
PRACTICAL_TASKS_INFO = "Choose a practical task"
|
8 |
PRACTICAL_SUBTASKS_INFO = "Choose a practical subtask"
|
9 |
NOTI_IN_DEV = "In development"
|
|
|
10 |
DROPDOWN_PROFESSIONAL_SKILLS_INFO = "What professional skill are you interested in?"
|
11 |
DROPDOWN_DROPDOWN_COLLEAGUES_INFO = "What colleague are you interested in?"
|
12 |
DROPDOWN_CANDIDATES_INFO = "What profession are you interested in?"
|
|
|
13 |
VALUE_FROM_TO_INFO = "Set value from {} to {}"
|
14 |
SUM_WEIGHTS = "The sum of the weights of the personality traits should be 100, not {}"
|
15 |
STEP_1 = "Step 1: Calculation of personality traits scores"
|
@@ -25,11 +27,16 @@ EXPORT_PG = "Export ranking professional groups results to a CSV file"
|
|
25 |
EXPORT_PS = "Export ranking professional skill results to a CSV file"
|
26 |
EXPORT_WT = "Export ranking effective work teams results to a CSV file"
|
27 |
EXPORT_CP = "Export consumer preferences for industrial goods results to a CSV file"
|
|
|
28 |
NOTI_CALCULATE = "You can calculate Big Five personality traits scores"
|
29 |
|
30 |
[Labels]
|
|
|
|
|
|
|
31 |
PRACTICAL_TASKS_LABEL = "Practical tasks"
|
32 |
PRACTICAL_SUBTASKS_LABEL = "Practical subtasks"
|
|
|
33 |
THRESHOLD_PROFESSIONAL_SKILLS_LABEL = "Polarity traits threshold"
|
34 |
TARGET_SCORE_OPE_LABEL = "Openness target score"
|
35 |
TARGET_SCORE_CON_LABEL = "Conscientiousness target score"
|
@@ -45,6 +52,8 @@ NUMBER_IMPORTANCE_EXT_LABEL = "Extraversion weight"
|
|
45 |
NUMBER_IMPORTANCE_AGR_LABEL = "Agreeableness weight"
|
46 |
NUMBER_IMPORTANCE_NNEU_LABEL = "Non-Neuroticism weight"
|
47 |
THRESHOLD_CONSUMER_PREFERENCES_LABEL = "Polarity traits threshold"
|
|
|
|
|
48 |
|
49 |
[TabCreators]
|
50 |
"App" = "app_tab"
|
@@ -58,12 +67,34 @@ COLLEAGUE_RANKING = "_colleague_ranking.csv"
|
|
58 |
CAR_CHARACTERISTICS = "auto_characteristics_priorities.csv"
|
59 |
MDA_CATEGORIES = "divice_characteristics_priorities.csv"
|
60 |
POTENTIAL_CANDIDATES = "potential_candidates.csv"
|
|
|
61 |
|
62 |
[Settings]
|
|
|
|
|
63 |
SHORT_PROFESSIONAL_SKILLS = ["OPE", "CON", "EXT", "AGR", "NNEU"]
|
64 |
DROPDOWN_PROFESSIONAL_SKILLS = ["Analytical", "Interactive", "Routine", "Non-Routine"]
|
65 |
DROPDOWN_COLLEAGUES = ["major", "minor"]
|
66 |
DROPDOWN_CANDIDATES = ["Managers/executives", "Entrepreneurship", "Social/Non profit making professions", "Public sector professions", "Scientists/researchers, and engineers", "Custom"]
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
67 |
|
68 |
[Values]
|
69 |
TARGET_SCORES = [0.527886, 0.522337, 0.458468, 0.51761, 0.444649]
|
@@ -74,4 +105,6 @@ PROFESSIONAL_SKILLS = "https://download.sberdisk.ru/download/file/478678231?toke
|
|
74 |
FINDING_COLLEAGUE = "https://download.sberdisk.ru/download/file/478675819?token=LuB7L1QsEY0UuSs&filename=colleague_ranking.csv"
|
75 |
CAR_CHARACTERISTICS = "https://download.sberdisk.ru/download/file/478675818?token=EjfLMqOeK8cfnOu&filename=auto_characteristics.csv"
|
76 |
MDA_CATEGORIES = "https://download.sberdisk.ru/download/file/478676690?token=7KcAxPqMpWiYQnx&filename=divice_characteristics.csv"
|
77 |
-
|
|
|
|
|
|
1 |
[AppSettings]
|
2 |
+
APP_VERSION = "0.8.0"
|
3 |
CSS_PATH = "app.css"
|
4 |
|
5 |
[InformationMessages]
|
|
|
7 |
PRACTICAL_TASKS_INFO = "Choose a practical task"
|
8 |
PRACTICAL_SUBTASKS_INFO = "Choose a practical subtask"
|
9 |
NOTI_IN_DEV = "In development"
|
10 |
+
DROPDOWN_MBTI_INFO = "What personality type indicator are you interested in?"
|
11 |
DROPDOWN_PROFESSIONAL_SKILLS_INFO = "What professional skill are you interested in?"
|
12 |
DROPDOWN_DROPDOWN_COLLEAGUES_INFO = "What colleague are you interested in?"
|
13 |
DROPDOWN_CANDIDATES_INFO = "What profession are you interested in?"
|
14 |
+
DROPDOWN_LANGUAGES_INFO = "Select the language of the app"
|
15 |
VALUE_FROM_TO_INFO = "Set value from {} to {}"
|
16 |
SUM_WEIGHTS = "The sum of the weights of the personality traits should be 100, not {}"
|
17 |
STEP_1 = "Step 1: Calculation of personality traits scores"
|
|
|
27 |
EXPORT_PS = "Export ranking professional skill results to a CSV file"
|
28 |
EXPORT_WT = "Export ranking effective work teams results to a CSV file"
|
29 |
EXPORT_CP = "Export consumer preferences for industrial goods results to a CSV file"
|
30 |
+
EXPORT_MBTI = "Export ranking personality type results to a CSV file"
|
31 |
NOTI_CALCULATE = "You can calculate Big Five personality traits scores"
|
32 |
|
33 |
[Labels]
|
34 |
+
APP_LABEL = ["App", "Приложение"]
|
35 |
+
ABOUT_APP_LABEL = ["About the App", "О приложении"]
|
36 |
+
ABOUT_AUTHORS_LABEL = ["About the Authors", "Об авторах"]
|
37 |
PRACTICAL_TASKS_LABEL = "Practical tasks"
|
38 |
PRACTICAL_SUBTASKS_LABEL = "Practical subtasks"
|
39 |
+
THRESHOLD_MBTI_LABEL = "Personality type indicator threshold"
|
40 |
THRESHOLD_PROFESSIONAL_SKILLS_LABEL = "Polarity traits threshold"
|
41 |
TARGET_SCORE_OPE_LABEL = "Openness target score"
|
42 |
TARGET_SCORE_CON_LABEL = "Conscientiousness target score"
|
|
|
52 |
NUMBER_IMPORTANCE_AGR_LABEL = "Agreeableness weight"
|
53 |
NUMBER_IMPORTANCE_NNEU_LABEL = "Non-Neuroticism weight"
|
54 |
THRESHOLD_CONSUMER_PREFERENCES_LABEL = "Polarity traits threshold"
|
55 |
+
LANGUAGES_LABEL = "Languages"
|
56 |
+
NOTE_MBTI_LABEL = "Note: What is MBTI?"
|
57 |
|
58 |
[TabCreators]
|
59 |
"App" = "app_tab"
|
|
|
67 |
CAR_CHARACTERISTICS = "auto_characteristics_priorities.csv"
|
68 |
MDA_CATEGORIES = "divice_characteristics_priorities.csv"
|
69 |
POTENTIAL_CANDIDATES = "potential_candidates.csv"
|
70 |
+
MBTI_JOB = "mbti_job_match.csv"
|
71 |
|
72 |
[Settings]
|
73 |
+
LANGUAGES_EN = ["English", "Russian"]
|
74 |
+
LANGUAGES_RU = ["Английский", "Русский"]
|
75 |
SHORT_PROFESSIONAL_SKILLS = ["OPE", "CON", "EXT", "AGR", "NNEU"]
|
76 |
DROPDOWN_PROFESSIONAL_SKILLS = ["Analytical", "Interactive", "Routine", "Non-Routine"]
|
77 |
DROPDOWN_COLLEAGUES = ["major", "minor"]
|
78 |
DROPDOWN_CANDIDATES = ["Managers/executives", "Entrepreneurship", "Social/Non profit making professions", "Public sector professions", "Scientists/researchers, and engineers", "Custom"]
|
79 |
+
DROPDOWN_MBTI = [
|
80 |
+
"The Inspector (ISTJ): Accountant, Auditor, Budget Analyst, Financial Manager, Developer, Systems Analyst, Librarian etc.",
|
81 |
+
"The Protector (ISFJ): Nurse, Doctor, Veterinarian or Veterinary Nurse/Assistant, Social Worker, Agricultural or Food Scientist, Secretary, Driver, etc.",
|
82 |
+
"The Counselor (INFJ): Psychologist, Human Resources Professional, Office Manager, Training Specialist, Graphic Designer, etc.",
|
83 |
+
"The Mastermind (INTJ): Animator, Architect, Content Writer, Photographer, TV Journalist, Video Editor, Business Development, Executive, Professor, etc.",
|
84 |
+
"The Crafter (ISTP): Engineer, Technician, Construction Worker, Inspector, Forensic Scientist, Software Engineer, Computer Programmer, etc.",
|
85 |
+
"The Composer (ISFP): Marketing Assistant, Dancer, Chef, Office Administrator, Artist, Interior Designer, Legal Secretary, Nurse, etc.",
|
86 |
+
"The Healer (INFP): Writer, Multimedia Designer, Customer Relations Manager, Special Education Teacher, Coach, Editor, Fashion Designer, etc.",
|
87 |
+
"The Architect (INTP): Technical Writer, Web Developer, Information Security Analyst, Researcher, Scientist, Lawyer, etc.",
|
88 |
+
"The Promoter (ESTP): Customer Care Specialist, Actor, Personal Trainer, Brand Ambassador, Manager, Entrepreneur, Creative Director, Police Officer, Marketing Officer, Manufacturer, etc.",
|
89 |
+
"The Performer (ESFP): Flight Attendant, Entertainer, Teacher, Public Relations Manager, Sales Representative, Event Planner, etc.",
|
90 |
+
"The Champion (ENFP): Healthcare Professional, Producer, Retail Sales Associate, Customer Service; Screenwriter; TV/Radio Host, etc.",
|
91 |
+
"The Visionary (ENTP): Engineer, Market Researcher, Social Media Manager, Management Analyst, Digital Marketing Executive, Business Consultant, Game Designer/Developer, Sales Manager, etc.",
|
92 |
+
"The Supervisor (ESTJ): Managing Director, Hotel Manager, Finance Officer, Judge, Real Estate Agent, Chief Executive Officer, Chef, Business Development Manager, Telemarketer, etc.",
|
93 |
+
"The Provider (ESFJ): Technical Support Specialist, Account Manager, College Professor, Medical Researcher, Bookkeeper, Photojournalist, etc.",
|
94 |
+
"The Teacher (ENFJ): Public Relations Manager, Sales Manager, Human Resource Director, Art Director, Counselor, etc.",
|
95 |
+
"The Commander (ENTJ): Construction Supervisor, Health Services Administrator, Financial Accountant, Auditor, Lawyer, School Principal, Chemical Engineer, Database Manager, etc.",
|
96 |
+
]
|
97 |
+
DROPDOWN_MBTI_DEL_COLS = ["EI", "SN", "TF", "JP", "Match"]
|
98 |
|
99 |
[Values]
|
100 |
TARGET_SCORES = [0.527886, 0.522337, 0.458468, 0.51761, 0.444649]
|
|
|
105 |
FINDING_COLLEAGUE = "https://download.sberdisk.ru/download/file/478675819?token=LuB7L1QsEY0UuSs&filename=colleague_ranking.csv"
|
106 |
CAR_CHARACTERISTICS = "https://download.sberdisk.ru/download/file/478675818?token=EjfLMqOeK8cfnOu&filename=auto_characteristics.csv"
|
107 |
MDA_CATEGORIES = "https://download.sberdisk.ru/download/file/478676690?token=7KcAxPqMpWiYQnx&filename=divice_characteristics.csv"
|
108 |
+
CLOTHING_SC = "https://download.sberdisk.ru/download/file/493644097?token=KGtSGMxjZtWXmBz&filename=df_%D1%81lothing_style_correlation.csv"
|
109 |
+
PROFESSIONS = "https://download.sberdisk.ru/download/file/478675798?token=fF5fNZVpthQlEV0&filename=traits_priority_for_professions.csv"
|
110 |
+
MBTI = "https://download.sberdisk.ru/download/file/493644095?token=EX7hFxNJhMoLumI&filename=df_mbti_correlation.csv"
|
images/AA.jpg
ADDED
practical_tasks.yaml
CHANGED
@@ -1,5 +1,6 @@
|
|
1 |
- task: "Ranking potential candidates by professional responsibilities"
|
2 |
subtasks:
|
|
|
3 |
- "Professional groups"
|
4 |
- "Professional skills"
|
5 |
- task: "Forming effective work teams"
|
@@ -9,4 +10,5 @@
|
|
9 |
- task: "Predicting consumer preferences for industrial goods"
|
10 |
subtasks:
|
11 |
- "Car characteristics"
|
12 |
-
- "Mobile device application categories"
|
|
|
|
1 |
- task: "Ranking potential candidates by professional responsibilities"
|
2 |
subtasks:
|
3 |
+
- "Sixteen Myers-Briggs Personality Type Indicators"
|
4 |
- "Professional groups"
|
5 |
- "Professional skills"
|
6 |
- task: "Forming effective work teams"
|
|
|
10 |
- task: "Predicting consumer preferences for industrial goods"
|
11 |
subtasks:
|
12 |
- "Car characteristics"
|
13 |
+
- "Mobile device application categories"
|
14 |
+
- "Clothing style correlation"
|
requirements.txt
CHANGED
@@ -2,6 +2,6 @@ gradio==4.23.0
|
|
2 |
requests==2.31.0
|
3 |
PyYAML==6.0.1
|
4 |
toml==0.10.2
|
5 |
-
oceanai==1.0.
|
6 |
tf-keras==2.16.0
|
7 |
pandas==2.2.1
|
|
|
2 |
requests==2.31.0
|
3 |
PyYAML==6.0.1
|
4 |
toml==0.10.2
|
5 |
+
oceanai==1.0.0a28
|
6 |
tf-keras==2.16.0
|
7 |
pandas==2.2.1
|