Devika Nair M
commited on
Update Briefly.py
Browse files- Briefly.py +17 -14
Briefly.py
CHANGED
@@ -1,20 +1,24 @@
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import streamlit as st #Web App
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from gnewsclient import gnewsclient # for fetching google news
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from newspaper import Article # to obtain text from news articles
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from transformers import pipeline # to summarize text
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import spacy # to obtain keyword
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from annotated_text import annotated_text # to display keywords
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# Load sshleifer/distilbart-cnn-12-6 model
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model = pipeline('summarization')
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return model
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data = gnewsclient.NewsClient(max_results=0)
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# obtain urls and it's content
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def getNews(topic,location):
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count=0
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@@ -46,11 +50,11 @@ def getNews(topic,location):
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# Summarizes the content- minimum word limit 30 and maximum 60
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def getNewsSummary(contents
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summaries=[]
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for content in contents:
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summaries.append(
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return summaries
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@@ -98,8 +102,7 @@ def DisplaySummary(titles,authors,summaries,keywords,urls):
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st.text("")
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def main():
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summarizer=load_model()
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st.title('Briefly')
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with st.expander('Read trending news in less than 60 words...', expanded=True):
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with st.form(key='form1'):
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if submit_button:
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with st.spinner('Fetching news...'):
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contents,titles,authors,urls=getNews(topic,location)
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summaries=getNewsSummary(contents
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keywords=generateKeyword(contents)
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DisplaySummary(titles,authors,summaries,keywords,urls)
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if __name__ == '__main__':
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main()
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import streamlit as st #Web App
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from gnewsclient import gnewsclient # for fetching google news
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from newspaper import Article # to obtain text from news articles
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import spacy # to obtain keyword
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from annotated_text import annotated_text # to display keywords
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import requests
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# Load sshleifer/distilbart-cnn-12-6 model using Accelerated Inference API
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API_URL = "https://api-inference.huggingface.co/models/sshleifer/distilbart-cnn-12-6"
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headers = {"Authorization": "Bearer api_GWvAcWrXIkIVYvBeyDyzJBOfGXhekPhFID"}
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def query(payload):
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response = requests.post(API_URL, headers=headers, json=payload)
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return response.json()
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data = gnewsclient.NewsClient(max_results=0)
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st.cache(allow_output_mutation=True)
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# obtain urls and it's content
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def getNews(topic,location):
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count=0
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# Summarizes the content- minimum word limit 30 and maximum 60
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def getNewsSummary(contents):
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summaries=[]
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for content in contents:
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summary = query({"inputs":content})[0]["summary_text"]
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summaries.append(summary)
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return summaries
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st.text("")
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def main():
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st.title('Briefly')
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with st.expander('Read trending news in less than 60 words...', expanded=True):
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with st.form(key='form1'):
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if submit_button:
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with st.spinner('Fetching news...'):
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contents,titles,authors,urls=getNews(topic,location)
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summaries=getNewsSummary(contents)
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keywords=generateKeyword(contents)
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DisplaySummary(titles,authors,summaries,keywords,urls)
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if __name__ == '__main__':
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main()
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