Update app.py

app.py

@@ -153,7 +153,18 @@ nltk.download('averaged_perceptron_tagger')
 #     return outputs.last_hidden_state.mean(dim=1).squeeze().numpy()
 
 
-def text_processing_for_domain(text):
+
+from transformers import pipeline
+# Load a summarization model
+summarizer = pipeline("summarization")
+
+
+
+def text_processing_for_domain(unsummarized_text):
+
+    # Summarization
+    text = summarizer(unsummarized_text, max_length=70, min_length=30, do_sample=False)[0]['summary_text']
+    
     
     # Text Cleaning
     text = re.sub(r'[^\w\s]', '', text)