Update app.py

app.py

@@ -1,35 +1,22 @@
-
 import streamlit as st
-import requests
-import torch
-from transformers import pipeline
-from transformers import BartTokenizer, BartForConditionalGeneration
-
-# Replace with your Hugging Face model repository path
-model_repo_path = 'ASaboor/Saboors_Bart_samsum'
-
-# Load the model and tokenizer
-model = BartForConditionalGeneration.from_pretrained(model_repo_path)
-tokenizer = BartTokenizer.from_pretrained(model_repo_path)
+from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
 
-# Initialize the summarization pipeline
-summarizer = pipeline('summarization', model=model,tokenizer=tokenizer)
+# Load the model and tokenizer from Hugging Face Model Hub
+model_name = "ASaboor/Saboors_Bart_samsum"  # Ensure this is correct
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
 
-# Streamlit app layout
-st.title("Text Summarization App")
+# Streamlit App
+st.title("Summarization App")
+st.write("This app uses a fine-tuned model to summarize text.")
 
-# User input
-text_input = st.text_area("Enter text to summarize", height=300)
+# Text input
+text = st.text_area("Enter text to summarize")
 
-# Summarize the text
+# Summarize button
 if st.button("Summarize"):
-    if text_input:
-        with st.spinner("Generating summary..."):
-            try:
-                summary = summarizer(text_input, max_length=150, min_length=30, do_sample=False)
-                st.subheader("Summary")
-                st.write(summary[0]['summary_text'])
-            except Exception as e:
-                st.error(f"Error during summarization: {e}")
-    else:
-        st.warning("Please enter some text to summarize.")
+    inputs = tokenizer.encode("summarize: " + text, return_tensors="pt", max_length=512, truncation=True)
+    summary_ids = model.generate(inputs, max_length=150, min_length=40, length_penalty=2.0, num_beams=4, early_stopping=True)
+    summary = tokenizer.decode(summary_ids[0], skip_special_tokens=True)
+    st.write("Summary:")
+    st.write(summary)