Profanity Detection API

Profanity Detection API

Profanity Detection API is a tool for identifying and flagging offensive language in user-generated content. It can detect a range of profanities, toxicities, and hate speech, including insults, threats, and identity-based hate. It uses advanced language understanding technology to accurately identify and classify potentially harmful language.

API description

About the API:

The Profanity Detection API is a powerful tool for identifying and flagging offensive language in user-generated content. It utilizes advanced language understanding technology to accurately detect a wide range of profanities and toxicities, including severe toxicities, obscene texts, insults, threats, and identity-based hate. This API is designed to help organizations and businesses manage user-generated content on their platforms, by identifying and removing potentially harmful language.

The API is easy to use and can be integrated into any application or platform that allows user-generated content. Once integrated, the API can automatically detect and flag offensive language, making it easy for moderators to review and take appropriate action. Additionally, the API can be configured to automatically remove or censor offensive language, providing an additional level of protection for users and organizations.

The Profanity Detection API can also be used to train machine learning models, by providing a large dataset of labeled offensive language. This can help organizations improve the accuracy of their own models for detecting offensive language.

Overall, the Profanity Detection API is a valuable tool for any organization or business that needs to manage user-generated content. It helps to protect users and businesses from the negative effects of offensive language and makes it easy to identify and remove harmful content. With its advanced language understanding technology, it provides a high level of accuracy and reliability, making it a reliable tool for managing user-generated content.

 

API Documentation

Endpoints


This endpoint detects profanities, toxicities, severe toxicities, obscene texts, insults, threats, and identity hate in a given text.



                                                                            
POST https://zylalabs.com/api/1060/profanity+detection+api/930/profanity+analyzer
                                                                            
                                                                        

Profanity Analyzer - Endpoint Features
Object Description
text [Required]
Test Endpoint

API EXAMPLE RESPONSE

       
                                                                                                        
                                                                                                                                                                                                                            {"Example Response":"No response example available for now."}
                                                                                                                                                                                                                    
                                                                                                    

Profanity Analyzer - CODE SNIPPETS


curl --location --request POST 'https://zylalabs.com/api/1060/profanity+detection+api/930/profanity+analyzer?text=You idiot! I will find where you live and kick you ass!' --header 'Authorization: Bearer YOUR_API_KEY' 

    

API Access Key & Authentication

After signing up, every developer is assigned a personal API access key, a unique combination of letters and digits provided to access to our API endpoint. To authenticate with the Profanity Detection API REST API, simply include your bearer token in the Authorization header.

Headers

Header Description
Authorization [Required] Should be Bearer access_key. See "Your API Access Key" above when you are subscribed.


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 Service Level
100%
 Response Time
254ms

Category:

NLP

Tags:


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