streamlit_app.py

import os
import requests

import openai
import streamlit as st
from retry import retry
from newspaper import Article

import nltk
nltk.download('punkt')


# TODO: Add summary and description to the story

if "OPENAI_API_KEY" in os.environ:
    openai.api_key = os.getenv("OPENAI_API_KEY")
else:
    openai.api_key = st.secrets['OPENAI_API_KEY']

# Function to fetch Hacker News stories through the official API
def fetch_hacker_news_stories():
    url = "https://hacker-news.firebaseio.com/v0/topstories.json?print=pretty"
    response = requests.get(url)
    top_story_ids = response.json()[:5]
    return top_story_ids

@retry(exceptions=openai.error.RateLimitError, tries=3, delay=15, backoff=2)
def generate_summary(text):
    # Geneate summary of the article using GPT-3
    response = openai.ChatCompletion.create(
        model="gpt-3.5-turbo-16k-0613",
        messages=[
            {"role": "system", "content": f"You're a great research article writer! and very skillful in summarizing articles. I have a task for you."},
            {"role": "user", "content": f"summarize the followning article briefly and use markdown formatting wherever needed like code snippets  and use bold *headers* instead of #headers: {text}"}])
    summary = response["choices"][0]["message"]["content"]
    return summary


@st.cache_data()
def get_story(story_id):
    url = f"https://hacker-news.firebaseio.com/v0/item/{story_id}.json?print=pretty"
    response = requests.get(url)
    story = response.json()

    article = Article(story["url"])

    # Download and parse the article
    article.download()
    article.parse()

    # Perform natural language processing on the article
    article.nlp()

    # Print the article title
    story["title"] = article.title
    story["summary"] = generate_summary(article.text)

    return story

# Streamlit app
def main():
    st.title("Hacker News Top Stories")
    hide_streamlit_style = """
                <style>
                #MainMenu {visibility: hidden;}
                footer {visibility: hidden;}
                footer:after {
                    content:"Made with 💓 by Chandra Sekhar Mullu"; 
                    visibility: visible;
                    display: block;
                    position: relative;
                    #background-color: red;
                    padding: 5px;
                    top: 2px;
                }
                </style>
                """
    st.markdown(hide_streamlit_style, unsafe_allow_html=True)
    stories = fetch_hacker_news_stories()

    for story_id in stories:
        with st.container():
            story = get_story(story_id)
            st.subheader(f"[{story['title']}]({story['url']})")
            st.write(f"*Author:* {story['by']}")
            st.write(f"{story['summary']}")
            st.write("---")

if __name__ == "__main__":
    main()