Update app.py

app.py

@@ -1,22 +1,35 @@
+
 import streamlit as st
-from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
+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)
 
-# Load the model and tokenizer from Hugging Face Model Hub
-model_name = "ASaboor/Saboors_Bart_samsum"
-tokenizer = AutoTokenizer.from_pretrained(model_name)
-model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
+# Initialize the summarization pipeline
+summarizer = pipeline('summarization', model=model,tokenizer=tokenizer)
 
-# Streamlit App
-st.title("Summarization App")
-st.write("This app uses a fine-tuned model to summarize text.")
+# Streamlit app layout
+st.title("Text Summarization App")
 
-# Text input
-text = st.text_area("Enter text to summarize")
+# User input
+text_input = st.text_area("Enter text to summarize", height=300)
 
-# Summarize button
+# Summarize the text
 if st.button("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)
+    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.")