Update app.py

app.py

@@ -1,3 +1,33 @@
-import gradio as gr
+import streamlit as st
+from transformers import BartForConditionalGeneration, BartTokenizer
+
+st.set_page_config(page_title="BART Text Summarization", layout="centered")
+
+@st.cache_resource
+def load_model():
+    model = BartForConditionalGeneration.from_pretrained("Arjun9/bart_samsum")
+    tokenizer = BartTokenizer.from_pretrained("Arjun9/bart_samsum")
+    return model, tokenizer
+
+model, tokenizer = load_model()
+
+def main():
+    st.title("Meeting summarization")
+
+    # Get user input
+    input_text = st.text_area("Enter text to summarize", height=200)
+
+    if st.button("Summarize"):
+        # Tokenize the input text
+        inputs = tokenizer(input_text, return_tensors="pt", truncation=True)
+
+        # Generate summary
+        summary_ids = model.generate(inputs["input_ids"], num_beams=4, max_length=100, early_stopping=True)
+        summary = tokenizer.decode(summary_ids[0], skip_special_tokens=True)
+
+        # Display the summary
+        st.write(f"Summary: {summary}")
+
+if __name__ == "__main__":
+    main()
 
-gr.load("models/Arjun9/bart_samsum").launch()