Update app.py

app.py

@@ -15,11 +15,29 @@ sentiment = pipeline("sentiment-analysis", model=finbert, tokenizer=tokenizer)
 
 #defining a function to give us the sentiment of the article
 def return_sentiment(text):
+  text = re.sub(r'Photo by.+', '', text)
+  text = re.sub(r"\n", " ", text)
+  text = re.sub(r"\n\n", " ", text)
+  text = re.sub(r"\t", " ", text)
+  text = text.strip(" ")
+  text = re.sub(
+      " +", " ", text
+      ).strip()  # get rid of multiple spaces and replace with a single
+      
   results = sentiment(text[:512])
   return (f"{results[0]['label']} ---> {results[0]['score']}")
   
 #defining a function to return the names of the organization present in the article
 def show_org(text):
+  text = re.sub(r'Photo by.+', '', text)
+  text = re.sub(r"\n", " ", text)
+  text = re.sub(r"\n\n", " ", text)
+  text = re.sub(r"\t", " ", text)
+  text = text.strip(" ")
+  text = re.sub(
+          " +", " ", text
+      ).strip()  # get rid of multiple spaces and replace with a single
+      
   org = []
   doc = nlp(text)
   if doc.ents: