import requests
import gradio as gr
import pandas as pd

from newsapi import NewsApiClient
from datetime import date, timedelta
from transformers import pipeline

# Model 2: Sentence Transformer
#API_URL = "https://api-inference.huggingface.co/models/sentence-transformers/msmarco-distilbert-base-tas-b"
HF_TOKEN = os.environ["newsapi"]
#headers = {"Authorization": f"Bearer {HF_TOKEN}"}

classifier = pipeline(model="cardiffnlp/twitter-roberta-base-sentiment") 
sentiment = ['Negative' if classifier(entry['content'])[0]['label'] == 'LABEL_0' else 'Neutral' if classifier(entry['content'])[0]['label'] == 'LABEL_1' else 'Positive' for entry in all_articles['articles']]
# Initialization
newsapi = NewsApiClient(api_key=HF_TOKEN)

# /v2/everything
all_articles = newsapi.get_everything(#q='bitcoin',
                                      sources='the-times-of-india',
                                      domains='timesofindia.indiatimes.com',
                                      from_param='2022-10-30',
                                      to='2022-10-30',
                                      language='en',
                                      sort_by='relevancy',)
                                      #page=2)
all_articles['articles']