import gradio as gr
import random
import requests
from bs4 import BeautifulSoup
import os

NEWS_API_KEY = os.environ['NEWS_API_KEY']
HF_TOKEN = os.environ['HF_TOKEN']

def summarize(model_name, article):
    API_URL = f"https://api-inference.huggingface.co/models/{model_name}"
    headers = {"Authorization": f"Bearer {HF_TOKEN}"}

    payload = {"inputs": article}
    response = requests.post(API_URL, headers=headers, json=payload)

    if response.status_code == 200:
        return format(response.json())
    else:
        if response.status_code == 401:
            return "Error: Unauthorized. Check your API token."
        elif response.status_code == 503:
            return "Error: Service unavailable or model is currently loading."
        else:
            return f"{response} - Error: Encountered an issue (status code: {response.status_code}). Please try again."
    return format(response.json())

def format(response):
    return response[0]['generated_text']

def get_news_article(search_query):
    if search_query.strip():
        url = 'https://newsapi.org/v2/everything'
        params = {
            'apiKey': NEWS_API_KEY,
            'q': search_query,
            'pageSize': 100,
            'language': 'en'
        }
    else:
        url = 'https://newsapi.org/v2/top-headlines'
        params = {
            'apiKey': NEWS_API_KEY,
            'country': 'us',
            'pageSize': 100
        }

    response = requests.get(url, params=params)
    articles = response.json().get('articles', [])
    if articles:
        random_article = random.choice(articles)
        news_url = random_article.get('url')
    else:
        return None

    if news_url:
        full_article, title = scrape_article(news_url)
        return full_article, title
    else:
        return "No news article found.", ""

def scrape_article(url):
    try:
        response = requests.get(url)
        soup = BeautifulSoup(response.content, 'html.parser')
        
        title = soup.title.string if soup.title else "No Title Available"

        article_content = soup.find_all('p')
        
        text = ' '.join([p.get_text() for p in article_content])
        words = text.split()
        truncated_text = ' '.join(words[:512])
    
        return truncated_text, title
    except Exception as e:
        return "Error scraping article: " + str(e), ""

with gr.Blocks() as demo:
    gr.Markdown("# News Summary App")
    gr.Markdown("Enter a news text, search for news articles, or load a random article.")
    
    with gr.Row():
        with gr.Column():
            search_query_input = gr.Textbox(label="Search for News", placeholder="Enter a topic to search...")
            load_news_article_button = gr.Button("Search News Article")
            article_title = gr.Label()
            input_text = gr.Textbox(lines=10, label="Input Text", placeholder="Enter article text, load a random article, or search for news...")
        with gr.Column():
            model_name = gr.Dropdown(label="Model Name", choices=["liamvbetts/bart-news-summary-v1", "liamvbetts/bart-base-cnn-v1", "liamvbetts/bart-large-cnn-v2", "liamvbetts/bart-large-cnn-v4"], value="liamvbetts/bart-news-summary-v1")
            summarize_button = gr.Button("Summarize")
            output_text = gr.Textbox(label="Summary", placeholder="Summary will appear here...")

    load_news_article_button.click(fn=get_news_article, inputs=[search_query_input], outputs=[input_text, article_title])
    summarize_button.click(fn=summarize, inputs=[model_name, input_text], outputs=output_text)

demo.launch()