Update app.py

app.py

@@ -45,6 +45,19 @@ for uploaded_file in uploaded_files:
 
         result = result1.values.tolist()
         st.dataframe(result)
+
+        model = GLiNER.from_pretrained("urchade/gliner_base")
+        labels = ["person", "country", "organization", "time", "role"]
+        entities = model.predict_entities(text_data, labels)
+
+        entity_dict = {}
+        for label in labels:
+            entity_dict[label] = [entity["text"] for entity in entities if entity["label"] == label]
+
+    
+        data = {"Text": text_data, **entity_dict}
+        st.dataframe(data)
+            
         
         vectorizer = TfidfVectorizer()
         tfidf_matrix = vectorizer.fit_transform(result)