from newspaper import Article
from langchain.chat_models import ChatGooglePalm
from langchain.schema import HumanMessage
# from dotenv import load_dotenv
import requests
import os
import gradio as gr

# load_dotenv()


chat = ChatGooglePalm(google_api_key=os.getenv("GOOGLE_API_KEY"), temperature=0)

headers = {
    "User-agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/89.0.4389.82 Safari/537.36"
}

article_url = input("URL: ")
print("\n")

session = requests.Session()

try:
    response = session.get(article_url, headers=headers, timeout=10)

    if response.status_code == 200:
        arts = Article(article_url)
        arts.download()
        arts.parse()

        print(f"Title: {arts.title}")
        # print(f"Text: {article.text}")

    else:
        print(f"Failed to fetch article at {article_url}")

except Exception as e:
    print(f"Error occured while fetching article at {article_url}: {e}")

    # article_title = article.title
    # article_text = article.text

template = """You are a very good assistant that summarizes online articles.

Here's the article you want to summarize.

==================
Title: {article_title}

{article_text}
==================

Now, provide a summarized version of the article in serialwise list.
"""


def art_sums(url):
    prompt = template.format(article_title=arts.title, article_text=arts.text)
    url = [HumanMessage(content=prompt)]
    print("\n")
    summary = chat(url)
    sum = summary.content
    sum = sum.replace("*", "")
    return sum

# art_sums(messages)

demo = gr.Interface(fn=art_sums, inputs="textbox", outputs="textbox",
                     title="Summarize news with me")
if __name__ == "__main__":
    demo.launch(share=True)