Update app.py

app.py

@@ -1,7 +1,7 @@
 import streamlit as st
 import pandas as pd
 import plotly.express as px
-from transformers import pipeline
+from transformers import pipeline, AutoTokenizer
 
 def main():
     st.set_page_config(page_title="Sentiment Analysis App")
@@ -12,8 +12,10 @@ def main():
 
     if st.button("Analyze"):
         if text_input:
+            tokenizer = AutoTokenizer.from_pretrained(model_name)
+            encoded_input = tokenizer(text_input, return_tensors='pt', padding=True, truncation=True)
             sentiment_classifier = pipeline("sentiment-analysis", model=model_name)
-            result = sentiment_classifier(text_input)[0]
+            result = sentiment_classifier(encoded_input)[0]
             st.write(f"Sentiment: {result['label']}")
             st.write(f"Score: {round(result['score'], 4)}")
             
@@ -21,7 +23,7 @@ def main():
             df_sentiments = pd.DataFrame({"sentiment": ["Positive", "Negative", "Neutral"], "count": [0, 0, 0]})
             
             # get the sentiment distribution of the text using the selected model
-            results = sentiment_classifier(text_input, task="sentiment-analysis")
+            results = sentiment_classifier(encoded_input)
             for r in results:
                 if r["label"] == "POSITIVE":
                     df_sentiments.loc[0, "count"] = r["score"]
@@ -38,4 +40,4 @@ def main():
             st.warning("Please enter some text for sentiment analysis")
 
 if __name__ == "__main__":
-    main()
+    main()