The Text Similarity API computes the similarity score between two pieces of text. It uses state-of-the-art NLP machine learning models to first embed (see our Embddings API) the texts into 768-dimension vectors, and then computes the cosine similarity between the two vectors.
https://api.api-ninjas.com/v1/textsimilarity
Returns a similarity score between 0 and 1 (1 is similar and 0 is dissimilar) of two given texts.
text_1 requiredFirst input text. Maximum 5000 characters.
text_2 requiredSecond input text. Maximum 5000 characters.
X-Api-Key requiredAPI Key associated with your account.
https://api.api-ninjas.com/v1/textsimilarityHeaders
X-Api-KeyLog in or sign up to get your API Key1
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{
"similarity": 0.7749438285827637
}1
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import requests
body = { 'text_1': 'This is an example sentence.', 'text_2': 'This is just another example sentence.' }
api_url = 'https://api.api-ninjas.com/v1/textsimilarity'
response = requests.post(api_url, headers={'X-Api-Key': 'YOUR_API_KEY'}, json=body)
if response.status_code == requests.codes.ok:
print(response.text)
else:
print("Error:", response.status_code, response.text)If your programming language is not listed in the Code Example above, you can still make API calls by using a HTTP request library written in your programming language and following the above documentation.