Python code for running sentiment analysis on Zapier

gistfile1.txt

import requests

API_URL = "https://api-inference.huggingface.co/models/cardiffnlp/twitter-roberta-base-sentiment"
headers = {"Authorization": "Bearer <YOUR HUGGINGFACE API KEY>"}

def query(payload):
	response = requests.post(API_URL, headers=headers, json=payload)
	return response.json()

result = query({"inputs": str(input_data['input_data'])})

negative = result[0][0]['score']
neutral = result[0][1]['score']
positive = result[0][2]['score']

scores = [{'label': 'negative', 'score': negative}, {'label': 'neutral', 'score': neutral}, {'label': 'positive', 'score': positive}]
          
top_score = max(item['score'] for item in scores)
      
top_sentiment = next(item for item in scores if item["score"] == top_score)['label']

output = [{'sentiment_label': top_sentiment, 'sentiment_score': top_score}]