Update aggregator.py

aggregator.py

@@ -76,7 +76,9 @@ def get_articles_sentiment(ticker, model):
                 dict["label"] = 2
             else:
                 dict["label"] = 1
-            
+    
+    total_articles = len(bezinga_results) + len(finhub_results) + len(marketaux_results) + len(newsapi_results) + len(newsdata_results) + len(vantage_results)
+
     try:
         replace_values(bezinga_results)
 
@@ -205,6 +207,9 @@ def get_articles_sentiment(ticker, model):
         if len(vantage_negatives) > 0:
             vantage_negative_score_mean = float(sum(d['score'] for d in vantage_negatives)) / len(vantage_negatives)
 
+    total_positives = len(bezinga_positives) + len(finhub_positives) + len(marketaux_positives) + len(newsapi_positives) + len(newsdata_positives) + len(vantage_positives)
+    total_negatives = len(bezinga_negatives) + len(finhub_negatives) + len(marketaux_negatives) + len(newsapi_negatives) + len(newsdata_negatives) + len(vantage_negatives)
+
     results_dict = {
         "bezinga": {
             "bezinga_articles": len(bezinga_results) if bezinga_results else 0,
@@ -253,7 +258,10 @@ def get_articles_sentiment(ticker, model):
             "vantage_sentiment_mean": vantage_label_mean if vantage_results else 0,
             "vantage_positive_score_mean": vantage_positive_score_mean if vantage_results else 0,
             "vantage_negative_score_mean": vantage_negative_score_mean if vantage_results else 0
-        }
+        },
+        "total_articles": total_articles,
+        "total_positives": total_positives,
+        "total_negatives": total_negatives
     }
 
     return results_dict