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import streamlit as st |
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import json |
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import requests |
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from newspaper import Article |
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from newsapi import NewsApiClient |
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st.set_page_config(page_title='Short News App', |
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layout = 'wide', |
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initial_sidebar_state = 'expanded', |
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menu_items={ |
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'About':'This is a demo application with One AI', |
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'Get help':'https://studio.oneai.com/docs', |
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'Report a Bug':'https://discord.com/channels/941458663493746698/941458828187287603' |
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}) |
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st.title('Short Summary News Application Demo with OneAI') |
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st.markdown('This application takes an input from the user and displays upto five latest news articles along with their summary. This application uses the free quota api calls.') |
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st.sidebar.image('logo.jpg') |
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st.sidebar.title('ONE AI') |
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st.sidebar.markdown('[One AI](https://www.oneai.com/) is an API-first, language AI service built for developers. Embed your API to analyze, process, and transform text in your project.') |
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st.sidebar.markdown('''It can perform several tasks like |
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- Sentiment Analysis |
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- Named Entity Recognition |
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- Topic Analysis |
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- Text Summarization |
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- Keyword Extraction |
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There are several more tasks that One AI can do. Please find the below links to explore more about this:''') |
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st.sidebar.markdown('[About us](https://www.oneai.com/about-us)') |
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st.sidebar.markdown('[Documentation](https://studio.oneai.com/docs)') |
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st.sidebar.markdown('[Contact](https://www.oneai.com/contact-us)') |
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st.sidebar.markdown('[Community](https://discord.com/channels/941458663493746698/942326235722309642)') |
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st.sidebar.markdown('© 2022 Logo rights reserved to One AI') |
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def run(): |
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newsapi = NewsApiClient(api_key='e07356679fcb40e98d44a37b323e9dd6') |
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@st.cache() |
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def summary(text1): |
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try: |
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api_key = "1c93487c-695c-4089-adfc-5e4b7623718c" |
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url = "https://api.oneai.com/api/v0/pipeline" |
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headers = {'api-key': api_key, 'content-type': 'application/json'} |
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payload = { |
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'input': text1, |
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'input_type': 'article', |
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'steps': [{'skill': 'summarize'}] |
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} |
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r = requests.post(url, json=payload, headers=headers) |
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r.raise_for_status() |
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data = r.json() |
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return data['output'][0]['text'] |
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except requests.exceptions.RequestException as e: |
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st.error(f"Error calling One AI API: {str(e)}") |
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return None |
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except (KeyError, IndexError) as e: |
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st.error(f"Error processing One AI response: {str(e)}") |
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return None |
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def get_links(query): |
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try: |
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all_articles = newsapi.get_everything(q=query, |
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language='en', |
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sort_by='relevancy', |
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page_size=5, |
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page=1) |
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if all_articles['status'] != 'ok': |
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st.error(f"NewsAPI Error: {all_articles.get('message', 'Unknown error')}") |
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return [] |
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links = [article['url'] for article in all_articles['articles']] |
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return links |
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except Exception as e: |
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st.error(f"Error fetching news: {str(e)}") |
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return [] |
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input_text = st.text_input('Search your favorite topic:') |
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submitted = st.button('Submit') |
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if submitted and input_text: |
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with st.spinner('Fetching news articles...'): |
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links = get_links(input_text) |
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if not links: |
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st.warning("No articles found. Please try a different search term.") |
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return |
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for link in links: |
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try: |
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with st.spinner(f'Processing article from {link}...'): |
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news_article = Article(link, language='en') |
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news_article.download() |
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news_article.parse() |
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if news_article.top_image: |
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st.image(news_article.top_image) |
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st.header(news_article.title) |
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st.markdown('*Summary of the Article:*') |
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article_summary = summary(news_article.text) |
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if article_summary: |
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st.markdown(article_summary) |
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else: |
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st.warning("Could not generate summary for this article") |
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with st.expander('Full Article'): |
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st.markdown(news_article.text) |
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except Exception as e: |
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st.error(f"Error processing article from {link}: {str(e)}") |
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continue |
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elif submitted: |
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st.warning("Please enter a search term") |
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if __name__ == '__main__': |
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run() |
