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app.py

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+import streamlit as st
+import json
+import requests
+from newspaper import Article
+
+st.set_page_config(page_title='Short News App',
+layout = 'wide',
+initial_sidebar_state = 'expanded',
+menu_items={
+    'About':'This is a demo application with One AI',
+    'Get help':'https://studio.oneai.com/docs',
+    'Report a Bug':'https://discord.com/channels/941458663493746698/941458828187287603'
+})
+st.title('Short Summary News Application Demo with OneAI')
+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.')
+st.sidebar.image('logo.jpg')
+st.sidebar.title('ONE AI')
+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.')
+st.sidebar.markdown('''It can perform several tasks like
+- Sentiment Analysis
+- Named Entity Recognition
+- Topic Analysis
+- Text Summarization
+- Keyword Extraction
+There are several more tasks that One AI can do. Please find the below links to explore more about this:''')
+st.sidebar.markdown('[About us](https://www.oneai.com/about-us)')
+st.sidebar.markdown('[Documentation](https://studio.oneai.com/docs)')
+st.sidebar.markdown('[Contact](https://www.oneai.com/contact-us)')
+st.sidebar.markdown('[Community](https://discord.com/channels/941458663493746698/942326235722309642)')
+st.sidebar.markdown('© 2022 Logo rights reserved to One AI')
+
+
+
+def run():
+    
+    @st.cache()
+    def summary(text1):
+        api_key = "1c93487c-695c-4089-adfc-5e4b7623718c"
+        url = "https://api.oneai.com/api/v0/pipeline"
+        text = text1
+        headers = {'api-key':api_key, 'content-type':'application/json'}
+        payload = {'input':text, 'input_type':'article', 'steps':[{'skill':'summarize'}]}
+        r = requests.post(url, json=payload, headers=headers)
+        data = r.json()
+        return data['output'][0]['text']
+
+    def get_links(text2):
+        url = "https://free-news.p.rapidapi.com/v1/search"
+        querystring = {"q":text2,"lang":"en", "page":1, "page_size":5}
+        headers = {'x-rapidapi-host': "free-news.p.rapidapi.com",'x-rapidapi-key': "375ffbaab0mshb442ffb69d6f025p117ba0jsn01e8146148e3"}
+        response = requests.request("GET", url, headers=headers, params=querystring)
+        response_dict = json.loads(response.text)
+        links = [response_dict['articles'][i]['link'] for i in range(len(response_dict['articles']))]
+        return links
+    
+    input_text = st.text_input('Search your favorite topic:')
+    submitted = st.button('Submit')
+    
+    if submitted:
+        links = get_links(input_text)
+        for link in links:
+            try:
+                news_article = Article(link, language='en')
+                news_article.download()
+                news_article.parse()
+                st.image(news_article.top_image)
+                st.header(news_article.title)
+                st.markdown('*Summary of the Article:*')
+                st.markdown(summary(news_article.text))
+                with st.expander('Full Article'):
+                    st.markdown(news_article.text)
+            except:
+                print('No Results!! Please try with new search!!')
+if __name__ == '__main__':
+    run()

config.toml

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+[theme]
+primaryColor="#0c0c0c"
+backgroundColor="#f9f9f2"
+secondaryBackgroundColor="#b7565c"
+textColor="#0a0a0a"

requirements.txt

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+newspaper3k