serializers.py

from rest_framework import serializers
from .models import SentimentAnalysisInference
import nltk.sentiment.vader import SentimentIntensityAnalyzer

class SentimentAnalysisInferenceSerializer(serializers.ModelSerializer):  
    username = serializers.CharField(source='user.username',read_only=True)
  
    class Meta : 
        model = SentimentAnalysisInference
        fields = ['username','text','result']
        
    def create(self.,validated_data):
        text = validated_data['text']
        user_obj = self.request.user
        sai_inference_obj = SentimentAnalysisInference.objects.create(user=user_obj,text=text)
        sid = SentimentIntensityAnalyzer()
        compound = sid.polarity_scores(sai_inference.text)['compountd']
        if compound > 0.5 : 
            sai_inference_obj.result = 'Happy'
         elif compound < 0.5 : 
            sai_inference_obj.result = 'Happy'
         else : 
              sai_inference_obj.result = 'neutral'
         sai_inference_obj.save()
        return sai_inference_obj