Setting up AI Developer Edition on

Prerequisites

Mon, 01 Jan 0001 00:00:00 +0000

AP Python

Hardware requirements

For the local docker deployment mode, a machine with the following specifications will enable you to experiment with the main features:

Optional - Obtaining access to the AI Developer Edition API Service

Mon, 01 Jan 0001 00:00:00 +0000

Registration is only required for running the APIs to protect, unprotect, and reprotect data. The find and redact that uses Data Discovery and Semantic Guardrail features can be used without registration. Skip this section if find and protect that uses the tokenization and encryption feature is not required.

Registering for access

Setting up the packages

Mon, 01 Jan 0001 00:00:00 +0000

Obtaining the package

Navigate to the Protegrity AI Developer Edition repository.
Clone or download the repositories on your local system.
- protegrity-developer-edition: Contains the files to launch the required containers. It also contains the sample applications and files.
```
git clone https://github.com/Protegrity-Developer-Edition/protegrity-developer-edition.git
```
To customize the Python modules, clone and use the source from the protegrity-developer-python repository.

Verifying the files in the Protegrity AI Developer Edition package

Mon, 01 Jan 0001 00:00:00 +0000

protegrity-developer-edition repository

The repository for the obtaining and running the sample application.

docker-compose.yml: This file contains the configuration for deploying the Data Discovery and Semantic Guardrail containers.
README.md: The readme file specifying the steps to set up the product.
samples: The directory with the sample application and scripts for the Python module.
- sample-app-find-and-redact.py: The sample application Python file for detecting and redacting sensitive information in the source file.
- sample-app-find-and-protect.py: The sample application Python file for detecting and protecting sensitive information in the source file using tokenization and encryption.
- sample-app-find-and-unprotect.py: The sample application Python file for unprotecting sensitive information in the source file. The source is generated by sample-app-find-and-protect.py.
- sample-app-protection.py: The sample application Python file for protecting and unprotecting data.
- sample-app-find.py: The sample application Python file for detecting and listing sensitive information in the source file.
- config.json: The configuration file for the Python application.
- sample-data: The directory with the sample file.
  - input.txt: The sample file that is processed.
  - output-redact.txt: The output file created by the find and redact application.
  - output-protect.txt: The output file created by the find and protect application.
data-discovery: The directory with the sample application and scripts for Data Discovery.
- sample-classification-commands.sh: A file with the sample curl command for identifying sensitive data.
- sample-classification-python.py: A sample Python module for identifying sensitive data.
semantic-guardrail: The directory with the sample application and scripts for Semantic Guardrail.
- sample-guardrail-python.py: A sample Python module for submitting multi-turn conversation with semantic and PII processors.

protegrity-developer-python repository

The repository with the source files for customizing and compiling the Python file.