Create app.py

app.py

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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_trans = 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
+    results = pipe_sent(pipe_trans(text))[0]
+
+    # Display the classification result
+    max_score = float('-inf')
+    max_label = ''
+    max_score = result['score']
+    max_label = result['label']
+
+    st.write("Text:", text)
+    st.write("Label:", max_label)
+    st.write("Score:", max_score)