Create app.py

app.py

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+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
+  return diffYoe
+
+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)