Update app.py

app.py

@@ -32,18 +32,9 @@ def chunk_text(text, chunk_size=1000):
 
 # Function to classify text as law-related or not using zero-shot classification
 def classify_text(text):
-    # Load the zero-shot classification pipeline
     classifier = pipeline("zero-shot-classification", model="facebook/bart-large-mnli")
-    
-    # Define the candidate labels
     candidate_labels = ["law-related", "not law-related"]
-    
-    # Run the classifier with the candidate labels
     result = classifier(text[:512], candidate_labels=candidate_labels)
-    
-    st.write(f"Classification result: {result}")
-    
-    # Check if the highest-scoring label is "law-related"
     return result['labels'][0] == "law-related"
 
 # Main area - Display content and perform tasks
@@ -56,11 +47,12 @@ if uploaded_file is not None:
 
         uploaded_file.seek(0)  # Reset file pointer to the beginning
         text = uploaded_file.read().decode(encoding)
-        st.write("File content loaded successfully!")  # Debugging: Confirm file loading
 
-        # Classify the text
+        # Classify the text before proceeding with summarization or NER
         if classify_text(text):
-            st.write("This document is classified as law-related.")  # Debugging: Confirm classification
+            st.write("This document is classified as law-related.")
+            
+            # Chunk the text if it is too long
             chunks = chunk_text(text, chunk_size=1000)
 
             if task == "Summarization":