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{
"data": {
"isML": true,
"text": "This is just a normal text",
"totalBadWords": null,
"riskScore": 0,
"isSafe": true,
"status": "success",
"executionTime": 120
}
}
Profanity Detection
curl --request GET \
--url https://greipapi.com/scoring/profanity \
--header 'Authorization: Bearer <token>'{
"data": {
"isML": true,
"text": "This is just a normal text",
"totalBadWords": null,
"riskScore": 0,
"isSafe": true,
"status": "success",
"executionTime": 120
}
}
Risk Scoring
Profanity Detection
This method helps safeguard your website or app by detecting offensive or inappropriate language in user inputs. By screening for profanity and other harmful content before it’s made public, you can maintain a positive user environment, protect your brand, and prevent abusive behavior on your platform.
This method uses Machine Learning (ML) to analyze text and determine whether it contains profanity. It returns a score for the text you pass, classifying it as safe or risky.
Want to skip the docs? Use the MCP Server
Endpoint availability: Free and aboveLearn more
{
"data": {
"isML": true,
"text": "This is just a normal text",
"totalBadWords": null,
"riskScore": 0,
"isSafe": true,
"status": "success",
"executionTime": 120
}
}
GET
/
scoring
/
profanity
Profanity Detection
curl --request GET \
--url https://greipapi.com/scoring/profanity \
--header 'Authorization: Bearer <token>'{
"data": {
"isML": true,
"text": "This is just a normal text",
"totalBadWords": null,
"riskScore": 0,
"isSafe": true,
"status": "success",
"executionTime": 120
}
}
Documentation Index
Fetch the complete documentation index at: https://docs.greip.io/llms.txt
Use this file to discover all available pages before exploring further.
Query Parameters
The text you want to filterSample value:
This is a sample text without profanity!Returns only the score of the text and whether it’s safe or not.Expected values:
yes, or no.Used to list the bad words in an array.Expected values:
yes, or no.The format command is used to get a response in a specific format.Expected values:
JSON, XML, or CSVFor more information please refer to Response Format.The mode command is used to in the development stage to simulate the integration process before releasing it to the production environment.Expected values:
live, or test.For more information please refer to Development Environment.The callback command can help you make the response as a JSONP format.Expected values: any name that can be used as a function name in Javascript, e.g:
myFunctionName.For more information please refer to JSONP Callback.Response properties
Hide properties
Hide properties
A boolean value that indicates whether the detection is done by Machine Learning or not.
The text you passed to the API.
The total number of profane words found in the text.Note: This field is only available when
isML is true, otherwise you’ll get null.The risk score of the text you passed.
A boolean value that indicates whether the text is safe or not.
The response status.Expected values:
success, or error.Time spent in milliseconds to process the data.
This method returns a score for the text you pass.We classify profanity into 4 different level. The first level contains the most risky words and phrases (risky). The second level contains the medium-risk words and phrases. Whereas, the third level contains the low-risk words.When you use the API, the response will the determine the score of the text you passed as follows:
riskScore = 0means that this text is completely safe.riskScode = 1means that this is a high-risk text.riskScode = 2means that this is a medium-risk text.riskScode = 3means that this is a low-risk text.
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