mrfirdauss/JobClassification

1from sentence_transformers import SentenceTransformer2from sklearn.metrics.pairwise import cosine_similarity3import gradio as gr4 5 6st = SentenceTransformer('all-mpnet-base-v2')7 8def predict(exp, listOfPosition, major_applicant, skills_applicant, yoe, jobdesc, rolename, major_vacancy, skills_vacancy, minimumYoe):9  diffYoe = yoe - minimumYoe10  results = {}11  results['score'] = 0.612  results['is_accepted'] = True13  return results14 15with gr.Blocks() as app:16    with gr.Row():17        with gr.Column():18            gr.Markdown("### Applicant Details")19            exp = gr.Textbox(label="Experience")20            listOfPosition = gr.Textbox(label="List of Positions")21            major_applicant = gr.Textbox(label="Major")22            skills_applicant = gr.Textbox(label="Skills")23            yoe = gr.Number(label="Years of Experience", precision=0)24        25        with gr.Column():26            gr.Markdown("### Vacancy Details")27            jobdesc = gr.Textbox(label="Job Description")28            rolename = gr.Textbox(label="Role Name")29            major_vacancy = gr.Textbox(label="Major Required")30            skills_vacancy = gr.Textbox(label="Skills Required")31            minimumYoe = gr.Number(label="Minimum Years of Experience", precision=0)32    gr.Button("Submit Application").click(33      predict,34      inputs=[exp, listOfPosition, major_applicant, skills_applicant, yoe, jobdesc, rolename, major_vacancy, skills_vacancy, minimumYoe],35      outputs=gr.JSON(label="Result")36    )37 38if __name__ == "__main__":39    app.launch(debug=True)40