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import gradio as gr
import requests
from bs4 import BeautifulSoup
import openai
import os
openai.api_key = os.getenv("OPENAI_API_KEY")
def fetch_text_from_url(url):
try:
response = requests.get(url, timeout=10)
soup = BeautifulSoup(response.text, 'html.parser')
paragraphs = soup.find_all('p')
content = ' '.join([p.get_text() for p in paragraphs])
return content[:4000] # trim for token limits
except Exception as e:
return f"Error fetching content: {str(e)}"
def summarize_with_takeaways(content):
prompt = f"""
You are a helpful AI agent. Summarize the article and extract 3–5 key takeaways.
Article:
\"\"\"
{content}
\"\"\"
Return in this format:
Summary:
<your summary>
Key Takeaways:
- ...
- ...
- ...
"""
response = openai.ChatCompletion.create(
model="gpt-4o",
messages=[{"role": "user", "content": prompt}]
)
return response.choices[0].message.content.strip()
def summarize_url(url):
content = fetch_text_from_url(url)
if content.startswith("Error"):
return content
return summarize_with_takeaways(content)
demo = gr.Interface(
fn=summarize_url,
inputs=gr.Textbox(label="Enter Weblink (URL)"),
outputs=gr.Textbox(label="Summary & Takeaways"),
title="🌐 Learning Agent: Weblink Summarizer",
description="Get a concise summary + key takeaways from any article."
)
demo.launch()
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