maybe last

app.py

@@ -10,6 +10,19 @@ from pyphonetics import RefinedSoundex
 from bs4 import BeautifulSoup
 import re
 
+
+# Load sentiment analysis model and tokenizer
+tokenizer = AutoTokenizer.from_pretrained("Seethal/sentiment_analysis_generic_dataset")
+model = AutoModelForSequenceClassification.from_pretrained("Seethal/sentiment_analysis_generic_dataset")
+
+# Define a function to get the sentiment from the model
+def get_sentiment(text):
+    inputs = tokenizer(text, return_tensors='pt', truncation=True, padding=True)
+    outputs = model(**inputs)
+    sentiment = torch.argmax(outputs.logits, dim=1).item()
+    return 'Positive' if sentiment == 1 else 'Negative'
+
+
 def closest_match(word, vocabulary):
     best_match = None
     best_distance = float('inf')
@@ -191,5 +204,9 @@ def main():
             st.write("Hinglish -> Hindi Transliterated String:", conversion_list)
             st.write("Hindi -> English Translated String:", translated)
 
+            # Get the sentiment of the translated text
+            sentiment = get_sentiment(translated[0])
+            st.write("Sentiment of Translated Text:", sentiment)
+
 if __name__ == '__main__':
     main()