return json object

app.py

@@ -9,9 +9,9 @@ print('Loading Sentiment Analysis model')
 sa = Sentiment()
 
 app = Flask(__name__)
-bot = ChatBot('Chatterbot', storage_adapter="chatterbot.storage.SQLStorageAdapter")
-trainer = ChatterBotCorpusTrainer(bot)
-trainer.train('./chatterbot_training_dataset/ai.yml', './chatterbot_training_dataset/emotion.yml', './chatterbot_training_dataset/conversational.yml')
+# bot = ChatBot('Chatterbot', storage_adapter="chatterbot.storage.SQLStorageAdapter")
+# trainer = ChatterBotCorpusTrainer(bot)
+# trainer.train('./chatterbot_training_dataset/ai.yml', './chatterbot_training_dataset/emotion.yml', './chatterbot_training_dataset/conversational.yml')
 #trainer.train('./chatterbot_training_dataset/conversational.yml')
 #trainer.train('./chatterbot_training_dataset/emotion.yml')
 
@@ -22,10 +22,11 @@ def index_test():
 
     new_ma_val = max(pred.items(), key=operator.itemgetter(1))[0]
 
-    avg = json.dumps(str(pred))
+    #arr = [ {'emotion' : i, 'value' : pred[i]} for i in pred]
+    avg = json.dumps(pred)
 
     #response from chatbot
-    res = str(bot.get_response(js_text['text']))
-    return res
+    # res = str(bot.get_response(js_text['text']))
+    return avg
 
 app.run(debug=True, port=8080)
\ No newline at end of file

sentiment_analysis.py

@@ -168,7 +168,8 @@ class Sentiment:
         
         predictions={}
         for key , value in zip(encoded_dict.keys(),validation[0]):
-            predictions[key]=value
+            st_value = str(value)
+            predictions[key]=float(st_value)
         
         return predictions