| import streamlit as st | |
| from aggregator import get_articles_sentiment | |
| st.title("Real time financial news fast sentiment") | |
| model_to_use = "" | |
| model_selected = st.radio("Choose your model", ["fin_distilBert", "fin_tinyBert", "fin_miniLM"]) | |
| ticker = st.text_input("Insert the company ticker") | |
| col1, col2 = st.columns(2) | |
| if model_selected and ticker is not None: | |
| if model_selected == "fin_distilBert": | |
| model_to_use = "Andreagus/fin_distilbert_16" | |
| if model_selected == "fin_tinyBert": | |
| model_to_use = "Andreagus/fin_tinyBert_32" | |
| if model_selected == "fin_miniLM12": | |
| model_to_use = "Andreagus/fin_miniLM_16" | |
| results = get_articles_sentiment(ticker, model_to_use) | |
| with col1: | |
| st.text("Bezinga news provider") | |
| if results['bezinga']['bezinga_articles'] == 0: | |
| st.text('Bezinga returned 0 articles') | |
| else: | |
| st.json(results['bezinga'], 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("marketaux news provider") | |
| if results['marketaux']['marketaux_articles'] == 0: | |
| st.text('marketaux returned 0 articles') | |
| else: | |
| st.json(results['marketaux'], 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']) | |