Update app.py

app.py

@@ -4,7 +4,8 @@ import requests
 import nltk
 from transformers import pipeline
 import gradio as gr
-from newsapi import NewsApiClient  # Import NewsApiClient from newsapi library
+from newsapi import NewsApiClient
+import asyncio
 
 # Configure logging
 logging.basicConfig(level=logging.DEBUG)
@@ -31,7 +32,7 @@ def fetch_article_content(url):
         return ""
 
 # Function to summarize news articles based on a query
-def summarize_news(query, num_results=3):
+async def summarize_news(query, num_results=3):
     logging.debug(f"Query received: {query}")
     logging.debug(f"Number of results requested: {num_results}")
 
@@ -54,26 +55,24 @@ def summarize_news(query, num_results=3):
 
     # Summarize the aggregated content
     try:
-        # Chunk the aggregated content into meaningful segments
+        # Chunk the aggregated content into chunks
         sentences = nltk.sent_tokenize(aggregated_content)
-        
-        # Summarize each sentence individually if it's meaningful
-        summaries = []
-        for sentence in sentences:
-            if len(sentence) > 10:  # Adjust minimum length as needed
-                summary = summarizer(sentence, max_length=120, min_length=30, do_sample=False)
-                summaries.append(summary[0]['summary_text'])
-        
-        # Join all summaries to form final output
-        final_summary = " ".join(summaries)
-        
+        chunk_size = 500  # Adjust chunk size as needed
+        chunks = [sentences[i:i + chunk_size] for i in range(0, len(sentences), chunk_size)]
+
+        # Summarize chunks concurrently
+        summaries = await asyncio.gather(*[summarizer(' '.join(chunk), max_length=120, min_length=30, do_sample=False) for chunk in chunks])
+
+        # Combine all summaries
+        final_summary = ' '.join([summary[0]['summary_text'] for summary in summaries])
+
         logging.debug(f"Final summarized text: {final_summary}")
         return final_summary
     
     except Exception as e:
         logging.error(f"Error during summarization: {e}")
         return "An error occurred during summarization."
-        
+
 # Setting up Gradio interface
 iface = gr.Interface(
     fn=summarize_news,