Text Classification

Fetch local news using geolocation coordinates (latitude, longitude) as input

The topics for the base level text classifier taxonomy are:

“arts and entertainment”, “automotive”, “business”, “careers”, “education”, “family and parenting”, “food and drink”, “health and fitness”, “hobbies and interests”, “home and garden”, “illegal content”, “law and government and politics”, “non standard content”, “personal finance”, “pets”, “real estate”, “religion and spirituality”, “science”, “shopping”, “society”, “sports”, “style and fashion”, “technology and computing”, “travel”

Input

• Languages:
• Python
• HTTP

import requests

url = "https://specrom-news-api.p.rapidapi.com/"

payload = {
  "api_type": "topic_detection_base_classifier",
  "input_text": "Top 20 Berkshire Hathaway holdings: What's in Warren Buffett portfolio going into 2023?"
}
headers = {
  "content-type": "application/json",
  "X-RapidAPI-Key": "API_key",
  "X-RapidAPI-Host": "specrom-news-api.p.rapidapi.com"
}

response = requests.request("POST", url, json=payload, headers=headers)

print(response.text)

	
	POST / HTTP/1.1
Content-Type: application/json
X-Rapidapi-Key: API_key
X-Rapidapi-Host: specrom-news-api.p.rapidapi.com
Host: specrom-news-api.p.rapidapi.com
Content-Length: 96

{
    "api_type": "topic_detection_base_classifier",
    "input_text": "Top 20 Berkshire Hathaway holdings: What's in Warren Buffett portfolio going into 2023?"
}
	
	

Output

• Languages:
• JSON

{"Topic":"business"}