fixed keywords

app.py

@@ -38,12 +38,7 @@ client = tweepy.Client(bearer_token=bearer_token)
 nlp = spacy.load('en_core_web_lg')
 print('hi')
 
-def scrape(keyword_list):
-    if len(keyword_list) > 1:
-        keywords = '(' + ' OR '.join(keyword_list) + ')'
-    else:
-        keywords = keyword_list[0]
-    
+def scrape(keywords):
     query = keywords + ' (lang:en OR lang:tl) -is:retweet'
     max_results = 100
     tweet_fields=['geo', 'id', 'lang', 'created_at']
@@ -513,9 +508,12 @@ def main(dataset, model):
         "taft"
     ]
     keyword_list = dataset.split(',')
-    keyword_list = ' OR '.join(keyword_list)
+    if len(keyword_list) > 1:
+        keywords = '(' + ' OR '.join(keyword_list) + ')'
+    else:
+        keywords = keyword_list[0]
     if dataset in examples:
-        df = get_example(keyword_list)
+        df = get_example(keywords)
         place_data = 'test'
     else:
         print(dataset)