Update app.py

app.py

@@ -2,51 +2,68 @@ import gradio as gr
 from transformers import pipeline
 from bs4 import BeautifulSoup
 import requests
+from googlesearch import search
 
-def summarize_blog_post(url):
-    # Load summarization pipeline
+def summarize_news(query):
+    # Initialize summarization pipeline
     summarizer = pipeline("summarization")
 
-    # Get blog post content
-    r = requests.get(url)
-    soup = BeautifulSoup(r.text, 'html.parser')
-    results = soup.find_all(['h1', 'p'])
-    text = [result.text for result in results]
-    ARTICLE = ' '.join(text)
-
-    # Chunk text
-    max_chunk = 500
-    ARTICLE = ARTICLE.replace('.', '.<eos>')
-    ARTICLE = ARTICLE.replace('?', '?<eos>')
-    ARTICLE = ARTICLE.replace('!', '!<eos>')
-
-    sentences = ARTICLE.split('<eos>')
-    current_chunk = 0
-    chunks = []
-    for sentence in sentences:
-        if len(chunks) == current_chunk + 1:
-            if len(chunks[current_chunk]) + len(sentence.split(' ')) <= max_chunk:
-                chunks[current_chunk].extend(sentence.split(' '))
-            else:
-                current_chunk += 1
-                chunks.append(sentence.split(' '))
-        else:
-            chunks.append(sentence.split(' '))
-
-    for chunk_id in range(len(chunks)):
-        chunks[chunk_id] = ' '.join(chunks[chunk_id])
-
-    # Summarize text
-    summaries = summarizer(chunks, max_length=120, min_length=30, do_sample=False)
-    summary_text = " ".join([summary['summary_text'] for summary in summaries])
-    return summary_text
+    # Search for news articles
+    search_results = search(query, num_results=3)
+    articles = []
+    
+    for url in search_results:
+        try:
+            # Fetch the content of the news article
+            r = requests.get(url)
+            soup = BeautifulSoup(r.text, 'html.parser')
+            results = soup.find_all(['h1', 'p'])
+            text = [result.text for result in results]
+            ARTICLE = ' '.join(text)
+
+            # Chunk the article text
+            max_chunk = 500
+            ARTICLE = ARTICLE.replace('.', '.<eos>')
+            ARTICLE = ARTICLE.replace('?', '?<eos>')
+            ARTICLE = ARTICLE.replace('!', '!<eos>')
+
+            sentences = ARTICLE.split('<eos>')
+            current_chunk = 0
+            chunks = []
+            for sentence in sentences:
+                if len(chunks) == current_chunk + 1:
+                    if len(chunks[current_chunk]) + len(sentence.split(' ')) <= max_chunk:
+                        chunks[current_chunk].extend(sentence.split(' '))
+                    else:
+                        current_chunk += 1
+                        chunks.append(sentence.split(' '))
+                else:
+                    chunks.append(sentence.split(' '))
+
+            for chunk_id in range(len(chunks)):
+                chunks[chunk_id] = ' '.join(chunks[chunk_id])
+
+            # Summarize the chunks
+            summaries = summarizer(chunks, max_length=120, min_length=30, do_sample=False)
+            summary_text = " ".join([summary['summary_text'] for summary in summaries])
+            articles.append((url, summary_text))
+        except Exception as e:
+            continue
+
+    return articles
+
+def format_output(articles):
+    formatted_text = ""
+    for url, summary in articles:
+        formatted_text += f"URL: {url}\nSummary: {summary}\n\n"
+    return formatted_text
 
 iface = gr.Interface(
-    fn=summarize_blog_post, 
+    fn=lambda query: format_output(summarize_news(query)), 
     inputs="text", 
     outputs="text",
-    title="Medium Blog Post Summarizer",
-    description="Enter the URL of a Medium blog post to get a summarized version of the content."
+    title="News Summarizer",
+    description="Enter a query to get summarized versions of the top news articles."
 )
 
 iface.launch()