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0447659 2932768 0447659 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 | from sentence_transformers import SentenceTransformer
from sklearn.metrics.pairwise import cosine_similarity
import gradio as gr
st = SentenceTransformer('all-mpnet-base-v2')
def predict(exp, listOfPosition, major_applicant, skills_applicant, yoe, jobdesc, rolename, major_vacancy, skills_vacancy, minimumYoe):
diffYoe = yoe - minimumYoe
results = {}
results['score'] = 0.6
results['is_accepted'] = True
return results
with gr.Blocks() as app:
with gr.Row():
with gr.Column():
gr.Markdown("### Applicant Details")
exp = gr.Textbox(label="Experience")
listOfPosition = gr.Textbox(label="List of Positions")
major_applicant = gr.Textbox(label="Major")
skills_applicant = gr.Textbox(label="Skills")
yoe = gr.Number(label="Years of Experience", precision=0)
with gr.Column():
gr.Markdown("### Vacancy Details")
jobdesc = gr.Textbox(label="Job Description")
rolename = gr.Textbox(label="Role Name")
major_vacancy = gr.Textbox(label="Major Required")
skills_vacancy = gr.Textbox(label="Skills Required")
minimumYoe = gr.Number(label="Minimum Years of Experience", precision=0)
gr.Button("Submit Application").click(
predict,
inputs=[exp, listOfPosition, major_applicant, skills_applicant, yoe, jobdesc, rolename, major_vacancy, skills_vacancy, minimumYoe],
outputs=gr.JSON(label="Result")
)
if __name__ == "__main__":
app.launch(debug=True)
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