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()