Update sentiment_analysis.py

sentiment_analysis.py

@@ -13,30 +13,30 @@ class SentimentAnalysisTool:
     def __call__(self, inputs: str): 
         return SentimentAnalysisTool.predicto(str)
         
-model_id_1 = "nlptown/bert-base-multilingual-uncased-sentiment"
-model_id_2 = "microsoft/deberta-xlarge-mnli"
-model_id_3 = "distilbert-base-uncased-finetuned-sst-2-english"
-model_id_4 = "lordtt13/emo-mobilebert"
-model_id_5 = "juliensimon/reviews-sentiment-analysis"
-model_id_6 = "sbcBI/sentiment_analysis_model"
-model_id_7 = "models/oliverguhr/german-sentiment-bert"
-
-def parse_output(output_json):  
-    list_pred=[]
-    for i in range(len(output_json[0])):
-        label = output_json[0][i]['label']
-        score = output_json[0][i]['score']
-        list_pred.append((label, score))
-    return list_pred
-
-def get_prediction(model_id):
-    classifier = pipeline("text-classification", model=model_id, return_all_scores=True)
-             
-def predicto(review):
-        classifier = SentimentAnalysisTool.get_prediction(SentimentAnalysisTool.model_id_7)
-        prediction = classifier(review)
-        print(prediction)
-        return SentimentAnalysisTool.parse_output(prediction)
+    model_id_1 = "nlptown/bert-base-multilingual-uncased-sentiment"
+    model_id_2 = "microsoft/deberta-xlarge-mnli"
+    model_id_3 = "distilbert-base-uncased-finetuned-sst-2-english"
+    model_id_4 = "lordtt13/emo-mobilebert"
+    model_id_5 = "juliensimon/reviews-sentiment-analysis"
+    model_id_6 = "sbcBI/sentiment_analysis_model"
+    model_id_7 = "models/oliverguhr/german-sentiment-bert"
+    
+    def parse_output(output_json):  
+        list_pred=[]
+        for i in range(len(output_json[0])):
+            label = output_json[0][i]['label']
+            score = output_json[0][i]['score']
+            list_pred.append((label, score))
+        return list_pred
+    
+    def get_prediction(model_id):
+        classifier = pipeline("text-classification", model=model_id, return_all_scores=True)
+                 
+    def predicto(review):
+            classifier = SentimentAnalysisTool.get_prediction(SentimentAnalysisTool.model_id_7)
+            prediction = classifier(review)
+            print(prediction)
+            return SentimentAnalysisTool.parse_output(prediction)