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import gradio as gr
import os
import shutil
import json
from ml import VacancyAnalyzer
class GlobalState:
"""
Class to store global variables
"""
result_file_path = os.path.join(os.path.dirname(__file__), 'result/archive.json')
result_dir = os.path.join(os.path.dirname(__file__), 'result')
bert_path = os.path.join(os.path.dirname(__file__), 'tiny.pt')
conv_classes = {0: 'low',
1: 'middle',
2: 'high'
}
default_data = {'id': 'a0000',
'emp_brand': '',
'mandatory': '',
'additional': '',
'comp_stages': '',
'work_conditions': '',
'conversion': 0,
'conversion_class': 'unknown'
}
data = None
def cid(txt):
GlobalState.data['id'] = txt
def cbrand(txt):
GlobalState.data['emp_brand'] = txt
def cmand(txt):
GlobalState.data['mandatory'] = txt
def cadd(txt):
GlobalState.data['additional'] = txt
def ccomp(txt):
GlobalState.data['comp_stages'] = txt
def ccond(txt):
GlobalState.data['work_conditions'] = txt
def submit(chk):
# print(GlobalState.data)
return gr.update("Run!", visible=True)
def append_to_json(_dict, path):
with open(path, 'ab+') as f:
f.seek(0, 2)
if f.tell() == 0:
f.write(json.dumps([_dict]).encode())
else:
f.seek(-1, 2)
f.truncate()
f.write(' , '.encode())
f.write(json.dumps(_dict).encode())
f.write(']'.encode())
def predict(btn):
analyzer = VacancyAnalyzer(GlobalState.bert_path, GlobalState.data)
status, result = analyzer.classify()
gr.Info(status)
if result != 'unknown':
result = GlobalState.conv_classes[int(result[0])]
out_2 = f'Predicted by vacancy description conversion - {result}'
GlobalState.data['conversion_class'] = result
fid = GlobalState.result_file_path
append_to_json(GlobalState.data, fid)
GlobalState.data = GlobalState.default_data
link = GlobalState.result_file_path
return gr.update(value=out_2), gr.update(link="/file=" + link, visible=True)
def save(btn):
link = GlobalState.result_file_path
return gr.update(link="/file=" + link)
def main():
# shutil.rmtree(os.path.join(os.path.dirname(__file__), 'result/'), ignore_errors=True)
try:
os.mkdir(os.path.join(os.path.dirname(__file__), 'result/'))
except FileExistsError:
pass
GlobalState.data = GlobalState.default_data
with gr.Blocks() as demo:
with gr.Tab("Load"):
with gr.Row():
gr.Markdown(
"""
# Input the text description of the position
# 👾👾👾 Then press **Run!** 👾👾👾
""")
with gr.Row():
with gr.Column():
with gr.Row():
brand = gr.Textbox(label='Company name', value=None)
with gr.Row():
vid = gr.Textbox(label='Position id', value=None)
with gr.Row():
req = gr.Textbox(label='Mandatory')
with gr.Column():
with gr.Row():
add = gr.Textbox(label='Additional')
with gr.Row():
comp = gr.Textbox(label='Competition stage')
with gr.Row():
cond = gr.Textbox(label='Work conditions')
with gr.Column():
with gr.Row():
with gr.Column():
ready = gr.Checkbox(label='Data Filled')
with gr.Column():
process_button = gr.Button("Run!", visible=False, interactive=True)
with gr.Row():
output_2 = gr.Textbox(label='LLM Result')
with gr.Row():
download_button = gr.Button("JSON Archive", visible=False)
brand.change(cbrand, inputs=[brand])
vid.change(cid, inputs=[vid])
req.change(cmand, inputs=[req])
add.change(cadd, inputs=[add])
comp.change(ccomp, inputs=[comp])
cond.change(ccond, inputs=[cond])
ready.change(submit, inputs=[ready], outputs=[process_button])
process_button.click(predict, inputs=[process_button], outputs=[output_2, download_button],
show_progress='full')
download_button.click(save, inputs=[download_button], outputs=[download_button])
demo.launch(allowed_paths=[GlobalState.result_dir])
if __name__ == "__main__":
main()
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