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import gradio as gr | |
from preprocessing import vectorizer | |
def predict_category(Issue, SubIssue): | |
model, vectorize, category_mapping = vectorizer() | |
example_text = Issue + " " + SubIssue | |
example_text_vecorized = vectorize.transform([example_text]) | |
predicted_category = model.predict(example_text_vecorized) | |
predicted_category_name = [category for category,index in category_mapping.items() if index == predicted_category[0]][0] | |
return predicted_category_name | |
gr.Interface(title="Predict the category", | |
description="Here we take issue and subissue of the user and predict different product categories", | |
fn=predict_category, | |
inputs = [gr.Textbox(lines=2,placeholder="Enter issue"), | |
gr.Textbox(lines=2,placeholder="Enter Subissue")], | |
allow_flagging="never", | |
outputs="text", | |
examples=[["i need money for my masters education","till now i haven't got it"], | |
["My money is debited from account and still now not transferred to respective bank account","It's been 3 hours"]]).launch() |