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import streamlit as st
from aggregator import get_articles_sentiment
st.title("Real time financial news fast sentiment")
st.subheader("Using finTinyBert")
with st.form("my_form"):
ticker = st.text_input("Insert the company ticker")
submitted = st.form_submit_button("Submit")
col1, col2 = st.columns(2)
if submitted:
st.write("You chose", ticker)
with st.spinner("Waiting for APIs"):
results = get_articles_sentiment(ticker, "Andreagus/fin_tinyBert_32")
with col1:
st.text("Benzinga news provider")
if results['bezinga']['bezinga_articles'] == 0:
st.text('Benzinga returned 0 articles')
else:
st.json(results['benzinga'], expanded=False)
st.text("finhub news provider")
if results['finhub']['finhub_articles'] == 0:
st.text('finhub returned 0 articles')
else:
st.json(results['finhub'], expanded=False)
st.text("Newsapi news provider")
if results['newsapi']['newsapi_articles'] == 0:
st.text('newsapi returned 0 articles')
else:
st.json(results['newsapi'], expanded=False)
st.text('Newsdata news provider')
if results['newsdata']['newsdata_articles'] == 0:
st.text('newsdata returned 0 articles')
else:
st.json(results['newsdata'], expanded=False)
st.text("Vantage news provider")
if results['vantage']['vantage_articles'] == 0:
st.text('vantage returned 0 articles')
else:
st.json(results['vantage'], expanded=False)
with col2:
st.text("Summary results")
st.metric("Total articles", results['total_articles'])
st.metric("Total positive articles", results['total_positives'])
st.metric("Total negative articles", results['total_negatives'])
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