update

app.py

@@ -13,23 +13,44 @@ newsapi = NewsApiClient(api_key=HF_TOKEN)
 
 classifier = pipeline(model="cardiffnlp/twitter-roberta-base-sentiment") 
 today = str(date.today())
+
+#times of india
 all_articles = newsapi.get_everything(sources='the-times-of-india',
                                     domains='timesofindia.indiatimes.com',
                                     from_param=today,
                                     to=today,
                                     language='en',
                                     sort_by='relevancy',)
-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']]
+sentiment_toi = ['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']]
+
+#the hindu
+all_articles = newsapi.get_everything(sources='the-hindu',
+                                    domains='thehindu.com',
+                                    from_param=today,
+                                    to=today,
+                                    language='en',
+                                    sort_by='relevancy',)
+sentiment_hindu = ['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']]
+
+#google news
+all_articles = newsapi.get_everything(sources='google-news-in',
+                                    domains='news.google.com',
+                                    from_param=today,
+                                    to=today,
+                                    language='en',
+                                    sort_by='relevancy',)
+sentiment_google = ['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']]
 
 #Driver 
 def inference(newssource): #, date):
-  #today = str(date.today())
-  #all_articles = newsapi.get_everything(sources='the-times-of-india',
-  #                                    domains='timesofindia.indiatimes.com',
-  #                                    from_param=today,
-  #                                    to=today,
-  #                                    language='en',
-  #                                    sort_by='relevancy',)
+  
+  if newssource == "Times Of India":
+    sentiment = sentiment_toi
+  elif newssource == "The Hindu":
+    sentiment = sentiment_hindu
+  elif newssource == "Google News":
+    sentiment = sentiment_google
+  
   dictnews = { 'description' : [entry['description'] for entry in all_articles['articles']],
             'content' : [entry['content'] for entry in all_articles['articles']],
             'url' : [entry['url'] for entry in all_articles['articles']],