Text Recommendation

4min

The below input parameters are for different attack types. To start working with the APIs, see Text Recommendation (Alpha-release)﻿﻿
Text Recommendation is an early access with limited functionality. It is not available  in AIShield pypi package. For early access, kindly contact [email protected]﻿
File upload format
Data: The processed data, ready to be passed to the model for prediction, should be saved in a folder.
﻿Download sample data﻿
Model: The model should be saved in either .h5 or TensorFlow format.
﻿Download sample model﻿
Common parameters
The below table parameters are common for Extraction Attack type. 
Parameter
Data type
Description
Remark
model_Id
String
Model_id received during model registration. 
We need to provide this model ID in query parameter in URL.
You have to do model registration only once for a model to perform model analysis. This will help you track the no of api call made, and it's success metric.
Request Body (Json format)
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model_api_details
String
If use_model_api is Yes, then provide API 
details of hosted model as encrypted JSON 
string is mandatory
provide this only if use_model_api is "yes". 
use_model_api 
String
Use model API to train your model instead of uploading the model as a zip file.
when this parameter is yes, you don't have to upload model as zip. You can pass api url along with other verification credential in json file. 
model_framework
String
Original model is built with tensorflow framework. 
curretly supported framework are: tensorflow, scikit-learn, keras. (Option:[tensorflow])
title
string
movie title for the recommendation
movie title for which the recommendation is requested from model
encryption_strategy
Int
Choose a encryption strategy for you model. if model is uploaded directly as a 
zip pick 0, 1 if model is encryted as .pyc and 
uploaded as a zip. Ignore if use_model_api is 
Yes
select 0: pass tensorflow model as it is, select 1: pass encrypted model. It could be .pyc file 
﻿
To access all sample artifacts, please visit Artifacts﻿. 
For specific artifact details,  refer 
Vulnerability Report : Vulnerability Report﻿     
Note: For Text recommendation, supported attack types are - Extraction
﻿

Parameter	Data type	Description	Remark
model_Id	String	Model_id received during model registration. We need to provide this model ID in query parameter in URL.	You have to do model registration only once for a model to perform model analysis. This will help you track the no of api call made, and it's success metric.
Request Body (Json format)
model_api_details	String	If use_model_api is Yes, then provide API details of hosted model as encrypted JSON string is mandatory	provide this only if use_model_api is "yes".
use_model_api	String	Use model API to train your model instead of uploading the model as a zip file.	when this parameter is yes, you don't have to upload model as zip. You can pass api url along with other verification credential in json file.
model_framework	String	Original model is built with tensorflow framework.	curretly supported framework are: tensorflow, scikit-learn, keras. (Option:[tensorflow])
title	string	movie title for the recommendation	movie title for which the recommendation is requested from model
encryption_strategy	Int	Choose a encryption strategy for you model. if model is uploaded directly as a zip pick 0, 1 if model is encryted as .pyc and uploaded as a zip. Ignore if use_model_api is Yes	select 0: pass tensorflow model as it is, select 1: pass encrypted model. It could be .pyc file

Updated 03 Oct 2024

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