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Update app.py

7814964 verified 3 months ago

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	#Import streamlit and pipeline
	import streamlit as st
	from transformers import pipeline


	pipe_sent = pipeline("text-classification", model="ProsusAI/finbert")
	pipe_tran = pipeline("translation", model="Helsinki-NLP/opus-mt-mul-en")

	# Streamlit application title
	st.title("FinSentinel-Portuguese Financial Sentiment Analysis")
	st.write("Classification for 3 attitudes: positive, netural, negative")

	# Text input for user to enter the text to classify
	text = st.text_area("Enter the text to classify", "")

	# Perform text classification when the user clicks the "Classify" button
	if st.button("Classify"):
	# Perform text classification on the input text
	translated_text = pipe_tran(text)[0]['translation_text']
	results = pipe_sent(translated_text)[0]

	# Display the classification result
	max_score = float('-inf')
	max_label = ''
	max_score = round(results['score'], 4)
	max_label = results['label']

	st.write("Text:", text)
	st.write("Label:", max_label)
	st.write("Score:", max_score)