Update app.py

app.py

@@ -3,6 +3,33 @@ from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
 import torch
 import sys
 
+st.title("Dialog Summarizer App")
+
+# User input
+user_input = st.text_area("Enter the dialog:")
+
+# Add "Summarize" and "Clear" buttons
+summarize_button = st.button("Summarize")
+clear_button = st.button("Clear")
+
+# If "Clear" button is clicked, clear the user input
+if clear_button:
+    user_input = ""
+
+# "Summarize" button and user input, generate and display summary
+if summarize_button and user_input:
+    # Load pre-trained Pegasus model and tokenizer
+    model_name = "ale-dp/pegasus-finetuned-dialog-summarizer"
+    tokenizer = AutoTokenizer.from_pretrained(model_name)
+    model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
+
+    # Generate summary
+    summary = generate_summary(model, tokenizer, user_input)
+
+    # Display the generated summary
+    st.subheader("Generated Summary:")
+    st.write(summary)
+
 def generate_summary(model, tokenizer, dialogue):
     # Tokenize input dialogue
     inputs = tokenizer(dialogue, return_tensors="pt", max_length=1024, truncation=True)
@@ -14,24 +41,3 @@ def generate_summary(model, tokenizer, dialogue):
     # Decode and return the summary
     summary = tokenizer.decode(summary_ids[0], skip_special_tokens=True, clean_up_tokenization_spaces=True)
     return summary
-
-
-st.title("Dialog Summarizer App")
-
-# User input
-user_input = st.text_area("Enter the dialog:")
-if not user_input:
-    st.info("Please enter a dialog.")
-    sys.exit()
-
-# Load pre-trained Pegasus model and tokenizer
-model_name = "ale-dp/pegasus-finetuned-dialog-summarizer"
-tokenizer = AutoTokenizer.from_pretrained(model_name)
-model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
-
-# Generate summary
-summary = generate_summary(model, tokenizer, user_input)
-
-# Display the generated summary
-st.subheader("Summary:")
-st.write(summary)