Update app.py

app.py

@@ -1,39 +1,22 @@
 import streamlit as st
-from transformers import RagTokenizer, RagRetriever, RagSequenceForGeneration
+from transformers import pipeline
 
-# Function to generate response using RAG (Retrieval-Augmented Generation)
-def generate_response_with_rag(txt):
-    try:
-        # Initialize the RAG model and tokenizer
-        tokenizer = RagTokenizer.from_pretrained("facebook/rag-token-nq")
-        retriever = RagRetriever.from_pretrained(
-            "facebook/rag-token-nq",
-            index_name="exact",
-            use_dummy_dataset=True,
-            trust_remote_code=True  # Allows loading the required dataset script
-        )
-        model = RagSequenceForGeneration.from_pretrained("facebook/rag-token-nq")
-
-        # Tokenize the input text
-        inputs = tokenizer(txt, return_tensors="pt")
-
-        # Retrieve relevant documents using the retriever
-        retrieved_docs = retriever.retrieve(inputs["input_ids"])
+# Initialize summarization pipeline
+summarizer = pipeline("summarization", model="facebook/bart-large-cnn")
 
-        # Generate the output using RAG
-        generated = model.generate(input_ids=inputs["input_ids"], context_input_ids=retrieved_docs['context_input_ids'])
-
-        # Decode the generated text
-        summary = tokenizer.decode(generated[0], skip_special_tokens=True)
-
-        return summary
+# Function to generate response using the summarizer
+def generate_response_with_summarizer(txt):
+    try:
+        # Generate summary
+        summary = summarizer(txt, max_length=130, min_length=30, do_sample=False)
+        return summary[0]['summary_text']
     except Exception as e:
         st.error(f"An error occurred during summarization: {str(e)}")
         return None
 
 # Page title and layout
-st.set_page_config(page_title='🦜🔗 RAG Text Summarization App')
-st.title('🦜🔗 RAG Text Summarization App')
+st.set_page_config(page_title='🦜🔗 Text Summarization App')
+st.title('🦜🔗 Text Summarization App')
 
 # Text input area for user to input text
 txt_input = st.text_area('Enter your text', '', height=200)
@@ -43,16 +26,16 @@ response = None
 with st.form('summarize_form', clear_on_submit=True):
     submitted = st.form_submit_button('Submit')
     if submitted and txt_input:
-        with st.spinner('Summarizing with RAG...'):
-            response = generate_response_with_rag(txt_input)
+        with st.spinner('Summarizing...'):
+            response = generate_response_with_summarizer(txt_input)
 
 # Display the response if available
 if response:
     st.info(response)
 
-# Instructions for getting started with Hugging Face models
-st.subheader("Hugging Face RAG Summarization")
+# Instructions for using the summarization app
+st.subheader("Hugging Face Summarization")
 st.write("""
-This app uses Hugging Face's RAG model (Retrieval-Augmented Generation) to generate summaries with relevant external context.
-RAG retrieves information from a set of documents and combines that with a generative model to produce more accurate summaries.
+This app uses Hugging Face's `facebook/bart-large-cnn` model to summarize input text.
+The model provides concise summaries by capturing the main points of the text.
 """)