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README.md

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----
-title: News Article Summarization
-emoji: 😻
-colorFrom: blue
-colorTo: indigo
-sdk: gradio
-sdk_version: 5.9.1
-app_file: app.py
-pinned: false
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# News Article Summarizer
+
+This is a Gradio app that summarizes news articles using the BART-large-CNN model. Simply input a news article URL, and the app will provide a clean, concise, and accurate summary of the article.
+
+## Features
+
+- URL-based article extraction
+- Automatic text summarization using state-of-the-art transformer model
+- Clean and user-friendly interface
+- Handles long articles by splitting them into chunks
+
+## How to Use
+
+1. Enter a news article URL in the input box
+2. Click submit
+3. Get your summarized article instantly
+
+## Local Development
+
+To run this app locally:
+
+1. Install the requirements:
+```bash
+pip install -r requirements.txt
+```
+
+2. Run the app:
+```bash
+python app.py
+```
+
+## Deployment
+
+This app is ready to be deployed on Hugging Face Spaces.

app.py

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+import gradio as gr
+from transformers import pipeline
+from newspaper import Article
+import torch
+
+# Initialize the summarization pipeline
+summarizer = pipeline("summarization", model="facebook/bart-large-cnn")
+
+# Define system prompt
+SYSTEM_PROMPT = """Summarize the given news article in a clear, concise, and accurate manner. Focus on:
+1. Key facts and main points
+2. Important details and context
+3. Maintain objectivity
+4. Preserve accuracy of information
+Avoid: opinions, redundancy, and unnecessary details."""
+
+def summarize_article(url):
+    try:
+        # Download and parse the article
+        article = Article(url)
+        article.download()
+        article.parse()
+        
+        # Get the text content
+        text = article.text
+        
+        # Prepend system prompt to the text
+        text_with_prompt = SYSTEM_PROMPT + "\n\nArticle:\n" + text
+        
+        # If the text is too long, split it into chunks
+        max_chunk_length = 1024
+        chunks = [text_with_prompt[i:i + max_chunk_length] for i in range(0, len(text_with_prompt), max_chunk_length)]
+        
+        summaries = []
+        for chunk in chunks:
+            # Skip empty chunks
+            if not chunk.strip():
+                continue
+                
+            summary = summarizer(chunk, max_length=130, min_length=30, do_sample=False)
+            summaries.append(summary[0]['summary_text'])
+        
+        # Combine all summaries
+        final_summary = " ".join(summaries)
+        return final_summary
+        
+    except Exception as e:
+        return f"Error processing the article: {str(e)}"
+
+# Create Gradio interface
+iface = gr.Interface(
+    fn=summarize_article,
+    inputs=gr.Textbox(label="Enter News Article URL", placeholder="https://..."),
+    outputs=gr.Textbox(label="Summary"),
+    title="News Article Summarizer",
+    description="Enter a news article URL to get a concise summary. The summary will be clean, accurate, and focused on the main points.",
+    examples=[
+        ["https://www.bbc.com/news/world-us-canada-67841980"],
+    ],
+    theme=gr.themes.Soft()
+)
+
+if __name__ == "__main__":
+    iface.launch()

requirements.txt

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+gradio>=4.0.0
+transformers>=4.30.0
+torch>=2.0.0
+newspaper3k>=0.2.8