Update app.py

app.py

@@ -1,29 +1,33 @@
 import streamlit as st
 from transformers import pipeline, set_seed
 
-def generate_text(prompt):
-    # Load the GPT-2 model
-    generator = pipeline('text-generation', model='gpt2')
+def generate_summary(text):
+    # Load the summarization model
+    summarizer = pipeline("summarization", model="t5-base", max_length=1024, min_length=40)
 
     # Set a random seed for reproducibility
     set_seed(1)
 
-    # Generate text
-    generated_text = generator(prompt, max_length=1000, num_return_sequences=1)[0]['generated_text']
+    # Generate summary
+    summary = summarizer(text, num_beams=4, no_repeat_ngram_size=2, length_penalty=2.0, early_stopping=True)[0]['summary_text']
 
-    return generated_text
+    return summary
 
 def main():
     # Set the app title
-    st.title("GPT-2 Text Generation")
-
-    # Get user input
-    prompt = st.text_input("Enter a prompt", "")
-
-    # Generate text based on the prompt
-    if prompt:
-        generated_text = generate_text(prompt)
-        st.write(generated_text)
+    st.title("Text Summarizer")
+
+    # Create a text box for user input
+    input_text = st.text_area("Enter text to summarize", "")
+
+    # Create a button to generate the summary
+    if st.button("Summarize"):
+        # Generate summary based on user input
+        if input_text:
+            summary = generate_summary(input_text)
+            st.write(summary)
+        else:
+            st.warning("Please enter some text to summarize.")
 
 if __name__ == "__main__":
     main()