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Setting up AI Developer Edition

The steps to set up the product.

Complete the prerequisites, optionally register for access to AI Developer Edition API Service, set up, verify, and run the required files for using Protegrity AI Developer Edition.

1 - Prerequisites

Ensure that the following prerequisites are met.

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:

  • RAM: 16 GB
  • CPU: 8 core
  • Hard Disk: 30GB available

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

  • RAM: 16 GB
  • CPU: 8 core
  • Hard Disk: 30GB available

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

  • RAM: 16 GB
  • CPU: 4 core
  • Hard Disk: 30GB available

Software requirements

  • Python v3.12.11 and above is installed. For more information about installing Python, refer to the Python website. Ensure that the Python command points to a supported python3 version, for example, Python 3.12.11. Verify using the python --version command.
  • pip for installing packages.
  • Python Virtual Environment.
  • Docker CLI is installed to manage Docker containers.
  • Docker Compose is installed for local containerized deployments. This application supports Docker Compose V2. Ensure that your installation supports this version.
  • Git is installed for cloning the repository.
  • Python v3.12.11 and above is installed. For more information about installing Python, refer to the Python website. Ensure that the Python command points to a supported python3 version, for example, Python 3.12. Verify using the python --version command.
  • pip for installing packages.
  • Python Virtual Environment.
  • Docker CLI is installed to manage Docker containers.
  • Docker Compose is installed for local containerized deployments. This application supports Docker Compose V2. Ensure that your installation supports this version.
  • Git is installed for cloning the repository.
  • Python v3.12.11 and above is installed. For more information about installing Python, refer to the Python website. Ensure that the Python command points to a supported python3 version, for example, Python 3.12. Verify using the python --version command.
  • pip for installing packages.
  • Python Virtual Environment.
  • Docker Desktop or Colima is installed.
  • Docker Compose is installed for local containerized deployments. This application supports Docker Compose V2. Ensure that your installation supports this version.
  • Git is installed for cloning the repository.

Additional settings for macOS

macOS requires additional steps for Docker and for systems with Apple Silicon chips. Complete the following steps before using AI Developer Edition.

  1. Complete one of the following options to apply the settings.

    • For Colima:
      1. Open a command prompt.
      2. Run the following command.
        colima start --vm-type vz --vz-rosetta --memory 4
    • For Docker Desktop:
      1. Open Docker Desktop.
      2. Go to Settings > General.
      3. Enable the following check boxes:
        • Use Virtualization framework
        • Use Rosetta for x86_64/amd64 emulation on Apple Silicon
      4. Click Apply & restart.

  2. Update one of the following options for resolving certificate related errors.

    • For Colima:

      1. Open a command prompt.

      2. Navigate and open the following file.

        ~/.colima/default/colima.yaml

      3. Update the following configuration in colima.yaml to add the path for obtaining the required images.

        Before update:

        docker: {}

        After update:

        docker:
    insecure-registries:
        - ghcr.io

      4. Save and close the file.

      5. Stop colima.

        colima stop

      6. Close and start the command prompt.

      7. Start colima.

        colima start --vm-type vz --vz-rosetta --memory 4
    • For Docker Desktop:

      1. Open Docker Desktop.

      2. Click the gear or settings icon.

      3. Click Docker Engine from the sidebar. The editor opens the current Docker daemon configuration daemon.json.

      4. Locate and add the insecure-registries key in the root JSON object. Ensure that a comma is added after the last value in the existing configuration.

        After update:

        {
    .
    .
    <existing configuration>,
    "insecure-registries": [
        "ghcr.io",
        "githubusercontent.com"
    ]
}

      5. Click Apply & Restart to save the changes and restart Docker Desktop.

      6. Verify: After Docker restarts, run docker info in your terminal and confirm that the required registry is listed under Insecure Registries.

  3. Optional: If the The requested image’s platform (linux/amd64) does not match the detected host platform (linux/arm64/v8) and no specific platform was requested error is displayed.

    1. Start a command prompt.

    2. Navigate and open the following file.

      ~/.docker/config.json

    3. Add the following paramater.

      "default-platform": "linux/amd64"

    4. Save and close the file.

    5. Run docker compose up -d from the protegrity-developer-edition directory if already cloned, else continue with the setup.

2 - Optional - Obtaining access to the AI Developer Edition API Service

Creating a user account and completing the registration.

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

Sign up for access to the AI Developer Edition API Service. This is required for obtaining access to use the APIs.

  1. Open a web browser.
  2. Navigate to https://www.protegrity.com/developers/get-api-credentials.
  3. Specify the following details:
    • First Name
    • Last Name
    • Work Email
    • Job Title
    • Company Name
    • Country
  4. Click the Terms & Conditions link and read the terms and conditions.
  5. Select the check box to accept the terms and conditions.
  6. Click Get Started.

The request is analyzed. After the request is approved, a password and API key to access the AI Developer Edition API Service is sent to the Work Email specified. If the account already exists, then the details are re-sent to the email address. The email takes a minute or two to arrive. If you do not see the email in your inbox, check your spam or junk folder before retrying.

Specifying the authentication information

Add the login information provided by Protegrity to the environment to access the AI Developer Edition API Service.

It is recommended to add the details to the environment variables to avoid specifying the information every time the environment is initialized.

  1. Open a command prompt.
  2. Initialize a Python virtual environment.
  3. Add the email address of the user.
export DEV_EDITION_EMAIL='<Email_used_for_registration>'

$env:DEV_EDITION_EMAIL = '<Email_used_for_registration>' 

export DEV_EDITION_EMAIL='<Email_used_for_registration>'
  1. Specify the password provided in the registration email.
export DEV_EDITION_PASSWORD='<Password_provided_in_email>'

$env:DEV_EDITION_PASSWORD = '<Password_provided_in_email>' 

export DEV_EDITION_PASSWORD='<Password_provided_in_email>'
  1. Specify the API key for accessing the AI Developer Edition API Service.
export DEV_EDITION_API_KEY='<API_key_provided_in_email>'

$env:DEV_EDITION_API_KEY = '<API_key_provided_in_email>'  

export DEV_EDITION_API_KEY='<API_key_provided_in_email>'
  1. Verify that the variables are set.
test -n "$DEV_EDITION_EMAIL" && echo "EMAIL $DEV_EDITION_EMAIL set" || echo "EMAIL missing"
test -n "$DEV_EDITION_PASSWORD" && echo "PASSWORD $DEV_EDITION_PASSWORD set" || echo "PASSWORD missing"
test -n "$DEV_EDITION_API_KEY" && echo "API KEY $DEV_EDITION_API_KEY set" || echo "API KEY missing"

if ($env:DEV_EDITION_EMAIL) { Write-Output "EMAIL $env:DEV_EDITION_EMAIL set"} else { Write-Output "EMAIL missing"} 
if ($env:DEV_EDITION_PASSWORD) { Write-Output "PASSWORD $env:DEV_EDITION_PASSWORD set" } else { Write-Output "PASSWORD missing" } 
if ($env:DEV_EDITION_API_KEY) { Write-Output "API KEY $env:DEV_EDITION_API_KEY set" } else { Write-Output "API KEY missing" } 

test -n "$DEV_EDITION_EMAIL" && echo "EMAIL $DEV_EDITION_EMAIL set" || echo "EMAIL missing"
test -n "$DEV_EDITION_PASSWORD" && echo "PASSWORD $DEV_EDITION_PASSWORD set" || echo "PASSWORD missing"
test -n "$DEV_EDITION_API_KEY" && echo "API KEY $DEV_EDITION_API_KEY set" || echo "API KEY missing"

AI Developer Edition API Service usage guidelines

To ensure fair use of the API service, rate limits is enforced on API requests to the AI Developer Edition API Service.

These limits are:

  • Request rate: 50 per second
  • Burst: up to 100
  • Quota: 10,000 requests per user per day
  • Maximum payload size: 1MB

3 - Setting up the packages

Steps for obtaining and setting up the pacakges.

Obtaining the package

  1. Navigate to the Protegrity AI Developer Edition repository.

  2. Clone or download the repositories on your local system.

    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.

    git clone https://github.com/Protegrity-Developer-Edition/protegrity-developer-python.git

  3. Verify the files in the package. The list of files in the git package can be obtained from the files list.

  1. Back up the Protegrity AI Developer Edition repository if the Python and configuration files are updated.

  2. Navigate to the cloned repository location for protegrity-developer-edition.

  3. Run the following command to stop the containers.

    docker compose down

    Based on your configuration use the docker-compose down command.

  4. Sync to update the repositories on the local system using the git pull command.

  5. Verify the files in the package. The list of files in the git package can be obtained from the files list.

Setting up Data Discovery and Semantic Guardrail

The containers contain the Data Discovery and Semantic Guardrail components required for identifying sensitive data.

  1. Open a command prompt.

  2. Navigate to the cloned repository location for protegrity-developer-edition.

  3. Run the following command to download and start the containers. The dependent containers are large in size. Based on the network connection, the containers might take time to download and deploy.

    docker compose up -d

    Based on your configuration use the docker-compose up -d command.

  4. Verify that the containers started successfully.

    docker compose logs

  1. Open a command prompt.

  2. Navigate to the cloned repository location for protegrity-developer-edition.

  3. If the step to stop containers was missed earlier, then use the following commands to identify and remove the AI Developer Edition containers.

    docker compose down
docker compose down --remove-orphans

  4. Delete the docker network resources.

    docker network rm -f <network_name_or_id>

    For example,

    docker network rm -f protegrity-network

  5. Run the following command to download and start the containers. The dependent containers are large in size. Based on the network connection, the containers might take time to download and deploy.

    docker compose up -d

    Based on your configuration use the docker-compose up -d command.

  6. Verify that the containers started successfully.

    docker compose logs

Installing the protegrity-developer-python Module

The module has built-in functions to find, redact, mask, and protect data.

  1. Open a command prompt.

  2. Install the protegrity-developer-python module. It is recommended to install and activate the Python virtual environment before running this command.

    pip install protegrity-developer-python

    The installation completes and the success message is displayed. To compile and install the Python module from source, refer to Building the Python module.

  1. Open a command prompt.

  2. Upgrade the protegrity-developer-python module. It is recommended to install and activate the Python virtual environment before running the command.

    pip install --upgrade protegrity-developer-python

    The package is successfully upgraded.

4 - Verifying the files in the Protegrity AI Developer Edition package

The list of files available in the AI Developer Edition repositories.

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.

  • LICENSE: The license file with the terms and conditions for using the application.
  • README.md: The readme file for working with the Python file.
  • pyproject.toml: The configuration file for the script.
  • pytest.ini: The configuration file for the Pytest framework.
  • requirements.txt: The configuration file for the script.
  • appython: The directory for the source file.
    • init.py: The initializing script.
    • protector.py: The source file for the script.
  • protegrity-developer-python: The directory for the source file.
    • init.py: The initializing script.
    • securefind.py: The source file for the script.