app.py

!pip install ipynb
from ipynb.fs.full.sentimental_analysis_training_pipeline import DepressionClassifier


import gradio as gr
import numpy as np
#from PIL import Image
#import requests

import hopsworks
import joblib

project = hopsworks.login(project='liangc40')
#fs = project.get_feature_store()


mr = project.get_model_registry()
model = mr.get_model("sentimental_analysis_model", version=1)
model_dir = model.download()
model = joblib.load(model_dir + "/sentimental_analysis_model.pkl")

def analyse(text):
    label = model(text)
    return label

with gr.Blocks() as demo:
    gr.Markdown("<h1><center>Sentiment Analysis with Fine-tuned BERT Model")

    inputs_text=gr.Textbox(placeholder='Type your text for which you want know the sentiment', label='Text')
    text_button = gr.Button('Analyse Sentiment')
    output_text_sentiment = gr.Textbox(placeholder='Sentiment of the text.', label='Sentiment')
    text_button.click(analyse, inputs = inputs_text, outputs = output_text_sentiment)

    
if __name__ == "__main__":
    demo.launch()