diff --git a/application/functions/sentiment.py b/application/functions/sentiment.py
index 5b1a088..5166186 100644
--- a/application/functions/sentiment.py
+++ b/application/functions/sentiment.py
@@ -8,4 +8,25 @@ tokenizer = AutoTokenizer.from_pretrained('application/tokenizers/sentiment_toke
 def sentiment_prediction(data):
     pipe = pipeline('text-classification', model=model, tokenizer = tokenizer)
     result = pipe(data)
-    return result
\ No newline at end of file
+    
+    return result
+
+def count_predictions(predictions):
+    l0 = 0
+    l1 = 0
+    l2 = 0
+    all = {}
+
+    for i in predictions:
+        if i['label'] == 'LABEL_0':
+            l0 += 1
+        if i['label'] == 'LABEL_1':
+            l1 += 1
+        if i['label'] == 'LABEL_2':
+            l2 += 1
+
+    all['positive'] = l1
+    all['negative'] = l0
+    all['neutral'] = l2
+
+    return all
\ No newline at end of file
diff --git a/application/services/sentiment_service.py b/application/services/sentiment_service.py
index d85f1d5..26b82c0 100644
--- a/application/services/sentiment_service.py
+++ b/application/services/sentiment_service.py
@@ -3,12 +3,14 @@ from flask import(
     jsonify, 
     Blueprint,
     )
-from application.functions.sentiment import sentiment_prediction
+from application.functions.sentiment import sentiment_prediction, count_predictions
 
 sentiment_service = Blueprint("sentiment_service", __name__)    
 
 @sentiment_service.route("/get_sentiment_data", methods=['GET'])
 def get_data():
     data = request.get_json()
-    result = sentiment_prediction(data['sentences'])
-    return result
\ No newline at end of file
+    predicitons = sentiment_prediction(data['sentences']) #predykcje
+    count_labels = count_predictions(predicitons) #dane do wykresu
+
+    return jsonify({"predictions": predicitons, "count_labels": count_labels})
\ No newline at end of file