Use the AI GCP Model Armor plugin

This is a Konnect tutorial and requires a Konnect personal access token.

1. Create a new personal access token by opening the Konnect PAT page and selecting Generate Token.

2. Export your token to an environment variable:

    export KONNECT_TOKEN='YOUR_KONNECT_PAT'
   

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3. Run the quickstart script to automatically provision a Control Plane and Data Plane, and configure your environment:

    curl -Ls https://get.konghq.com/quickstart | bash -s -- -k $KONNECT_TOKEN --deck-output
   

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   This sets up a Konnect Control Plane named quickstart, provisions a local Data Plane, and prints out the following environment variable exports:

    export DECK_KONNECT_TOKEN=$KONNECT_TOKEN
    export DECK_KONNECT_CONTROL_PLANE_NAME=quickstart
    export KONNECT_CONTROL_PLANE_URL=https://us.api.konghq.com
    export KONNECT_PROXY_URL='http://localhost:8000'
   

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   Copy and paste these into your terminal to configure your session.

This tutorial requires Kong Gateway Enterprise. If you don’t have Kong Gateway set up yet, you can use the quickstart script with an enterprise license to get an instance of Kong Gateway running almost instantly.

1. Export your license to an environment variable:

    export KONG_LICENSE_DATA='LICENSE-CONTENTS-GO-HERE'
   

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2. Run the quickstart script:

   curl -Ls https://get.konghq.com/quickstart | bash -s -- -e KONG_LICENSE_DATA 
   

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   Once Kong Gateway is ready, you will see the following message:

    Kong Gateway Ready
   

decK is a CLI tool for managing Kong Gateway declaratively with state files. To complete this tutorial, install decK version 1.43 or later.

This guide uses deck gateway apply, which directly applies entity configuration to your Gateway instance. We recommend upgrading your decK installation to take advantage of this tool.

You can check your current decK version with deck version.

For this tutorial, you’ll need Kong Gateway entities, like Gateway Services and Routes, pre-configured. These entities are essential for Kong Gateway to function but installing them isn’t the focus of this guide. Follow these steps to pre-configure them:

1. Run the following command:

   echo '
   _format_version: "3.0"
   services:
     - name: example-service
       url: http://httpbin.konghq.com/anything
   routes:
     - name: example-route
       paths:
       - "/anything"
       service:
         name: example-service
   ' | deck gateway apply -
   

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To learn more about entities, you can read our entities documentation.

This tutorial uses OpenAI:

1. Create an OpenAI account.
2. Get an API key.
3. Create a decK variable with the API key:

export DECK_OPENAI_API_KEY="YOUR OPENAI API KEY"

export DECK_OPENAI_API_KEY="YOUR OPENAI API KEY"

To use the AI GCP Model Armor plugin, you need a service account with Model Armor Admin permissions and a configured Model Armor template:

1. **Check your IAM permissions:**
Your service account must have the [`roles/modelarmor.admin`](https://cloud.google.com/iam/docs/roles-permissions/modelarmor) IAM role.

2. Create the `modelarmor-admin` service account in your GCP by executing the following command in your terminal:

   
   ```bash
   gcloud iam service-accounts create modelarmor-admin \
       --description="Service account for Model Armor administration" \
       --display-name="Model Armor Admin" \
       --project=$DECK_GCP_PROJECT_ID
   ```
   

3. Create and activate a service account key file by executing the following commands:


   
   ```bash
   gcloud iam service-accounts keys create modelarmor-admin-key.json \
       --iam-account=modelarmor-admin@$DECK_GCP_PROJECT_ID.iam.gserviceaccount.com
   
   gcloud auth activate-service-account \
       --key-file=modelarmor-admin-key.json
   ```
   

   After creating the key, convert the contents of `modelarmor-admin-key.json` into a **single-line JSON string**.
   Escape all necessary characters — quotes (`"`) and newlines (`\n`) — so that it becomes a valid one-line JSON string.
   Then export it as an environment variable:

   ```bash
   export DECK_GCP_SERVICE_ACCOUNT_JSON="<single-line-escaped-json>"
   ```

4. Enable the Model Armor API:


   
   ```bash
   gcloud config set api_endpoint_overrides/modelarmor "https://modelarmor.$DECK_GCP_LOCATION_ID.rep.googleapis.com/"
   gcloud services enable modelarmor.googleapis.com --project=$DECK_GCP_PROJECT_ID
   ```
   

5. Create a Model Armor template with strict guardrails. This template blocks **hate speech, harassment, and sexually explicit content** at medium confidence or higher, enforces PI/jailbreak and malicious URI filters, and logs all inspection events. Execute the following command to create the template:

   
   ```bash
   gcloud model-armor templates create strict-guardrails \
       --project=$DECK_GCP_PROJECT_ID \
       --location=$DECK_GCP_LOCATION_ID \
       --rai-settings-filters='[
           { "filterType": "HATE_SPEECH", "confidenceLevel": "MEDIUM_AND_ABOVE" },
           { "filterType": "HARASSMENT", "confidenceLevel": "MEDIUM_AND_ABOVE" },
           { "filterType": "SEXUALLY_EXPLICIT", "confidenceLevel": "MEDIUM_AND_ABOVE" }
       ]' \
       --basic-config-filter-enforcement=enabled \
       --pi-and-jailbreak-filter-settings-enforcement=enabled \
       --pi-and-jailbreak-filter-settings-confidence-level=LOW_AND_ABOVE \
       --malicious-uri-filter-settings-enforcement=enabled \
       --template-metadata-log-operations \
       --template-metadata-log-sanitize-operations
   ```
   


6. Export the template ID:
    
   ```bash
   export DECK_GCP_TEMPLATE_ID="strict-guardrails"
   ```