Update app.py

app.py

@@ -2,10 +2,10 @@ from transformers import pipeline
 import gradio as gr
 import requests
 
-# Initialize the summarization pipeline (global initialization for efficiency)
-summarizer = pipeline("summarization", model="facebook/bart-large-cnn")
+# Initialize the summarization pipeline
+summarizer = pipeline("summarization", model="facebook/bart-large-cnn", device=-1)
 
-# Function to fetch content from Wikipedia with a limit on length
+# Function to fetch content from Wikipedia with a length cap
 def fetch_wikipedia_content(search_term, max_chars=10000):
     url = "https://en.wikipedia.org/w/api.php"
     params = {
@@ -17,7 +17,7 @@ def fetch_wikipedia_content(search_term, max_chars=10000):
         "redirects": 1  # Follow redirects
     }
     try:
-        response = requests.get(url, headers=headers, params=params)
+        response = requests.get(url, params=params)
         response.raise_for_status()
         data = response.json()
         page = next(iter(data["query"]["pages"].values()))
@@ -38,7 +38,7 @@ def summarize_text(text):
     for i, chunk in enumerate(chunks):
         try:
             chunk_word_count = len(chunk.split())
-            max_summary_length = min(120, max(40, chunk_word_count // 2))  # Optimized for smaller summaries
+            max_summary_length = min(120, max(50, chunk_word_count // 2))  # Adjust summary length
             summary = summarizer(chunk, max_length=max_summary_length, min_length=30, do_sample=False)[0]['summary_text']
             summaries.append(summary)
         except Exception as e:
@@ -57,11 +57,10 @@ iface = gr.Interface(
     fn=fetch_and_summarize,
     inputs=gr.Textbox(lines=1, placeholder="Enter a Wikipedia topic", label="Wikipedia Topic"),
     outputs=gr.Textbox(label="Summarized Content"),
-    title="Optimized Wikipedia Article Summarizer",
-    description="Fetch and summarize Wikipedia articles efficiently. Optimized for lightweight summarization.",
-    allow_flagging="never"  # Disable flagging for a lightweight deployment
+    title="Wikipedia Article Summarizer",
+    description="Fetch and summarize Wikipedia articles efficiently. Just enter a topic to get started!",
 )
 
-# Launch Gradio with queuing for handling concurrent requests
+# Launch Gradio
 if __name__ == "__main__":
-    iface.queue(concurrency_count=4).launch(debug=False)
+    iface.launch(debug=True)