AI Response Transformer: Add a header to a response body - Plugin

Add a header to a response bodyv3.6+

Configure the plugin to use OpenAI GPT-4 to add a header to the response before returning it to the client. See Transform a response using OpenAI for a full how-to guide with this example.

Prerequisites

You have an OpenAI subscription.

Environment variables

OPENAI_API_KEY: An API key to connect to the OpenAI API.

Set up the plugin

Add this section to your declarative configuration file:

_format_version: "3.0"
plugins:
  - name: ai-response-transformer
    config:
      prompt: |
        Add a new header named "new-header" with the value "header-value" to the response. Format the JSON response as follows:
        {
          "headers":
            {
              "new-header": "header-value"
            },
          "status": 201,
          "body": "new response body"
        }
      transformation_extract_pattern: "{((.|\\n)*)}"
      parse_llm_response_json_instructions: true
      llm:
        route_type: llm/v1/chat
        auth:
          header_name: Authorization
          header_value: Bearer ${{ env "DECK_OPENAI_API_KEY" }}
        model:
          provider: openai
          name: gpt-4

Make the following request:

curl -i -X POST http://localhost:8001/plugins/ \
    --header "Accept: application/json" \
    --header "Content-Type: application/json" \
    --data '
    {
      "name": "ai-response-transformer",
      "config": {
        "prompt": "Add a new header named \"new-header\" with the value \"header-value\" to the response. Format the JSON response as follows:\n{\n  \"headers\":\n    {\n      \"new-header\": \"header-value\"\n    },\n  \"status\": 201,\n  \"body\": \"new response body\"\n}\n",
        "transformation_extract_pattern": "{((.|\\n)*)}",
        "parse_llm_response_json_instructions": true,
        "llm": {
          "route_type": "llm/v1/chat",
          "auth": {
            "header_name": "Authorization",
            "header_value": "Bearer '$OPENAI_API_KEY'"
          },
          "model": {
            "provider": "openai",
            "name": "gpt-4"
          }
        }
      }
    }
    '

Make the following request:

curl -X POST https://{region}.api.konghq.com/v2/control-planes/{controlPlaneId}/core-entities/plugins/ \
    --header "accept: application/json" \
    --header "Content-Type: application/json" \
    --header "Authorization: Bearer $KONNECT_TOKEN" \
    --data '
    {
      "name": "ai-response-transformer",
      "config": {
        "prompt": "Add a new header named \"new-header\" with the value \"header-value\" to the response. Format the JSON response as follows:\n{\n  \"headers\":\n    {\n      \"new-header\": \"header-value\"\n    },\n  \"status\": 201,\n  \"body\": \"new response body\"\n}\n",
        "transformation_extract_pattern": "{((.|\\n)*)}",
        "parse_llm_response_json_instructions": true,
        "llm": {
          "route_type": "llm/v1/chat",
          "auth": {
            "header_name": "Authorization",
            "header_value": "Bearer '$OPENAI_API_KEY'"
          },
          "model": {
            "provider": "openai",
            "name": "gpt-4"
          }
        }
      }
    }
    '

Make sure to replace the following placeholders with your own values:

region: Geographic region where your Kong Konnect is hosted and operates.
controlPlaneId: The id of the control plane.
KONNECT_TOKEN: Your Personal Access Token (PAT) associated with your Konnect account.

See the Konnect API reference to learn about region-specific URLs and personal access tokens.

echo "
apiVersion: configuration.konghq.com/v1
kind: KongClusterPlugin
metadata:
  name: ai-response-transformer
  namespace: kong
  annotations:
    kubernetes.io/ingress.class: kong
  labels:
    global: 'true'
config:
  prompt: |
    Add a new header named 'new-header' with the value 'header-value' to the response. Format the JSON response as follows:
    {
      'headers':
        {
          'new-header': 'header-value'
        },
      'status': 201,
      'body': 'new response body'
    }
  transformation_extract_pattern: '{((.|\\n)*)}'
  parse_llm_response_json_instructions: true
  llm:
    route_type: llm/v1/chat
    auth:
      header_name: Authorization
      header_value: Bearer $OPENAI_API_KEY
    model:
      provider: openai
      name: gpt-4
plugin: ai-response-transformer
" | kubectl apply -f -

Prerequisite: Configure your Personal Access Token

terraform {
  required_providers {
    konnect = {
      source  = "kong/konnect"
    }
  }
}

provider "konnect" {
  personal_access_token = "$KONNECT_TOKEN"
  server_url            = "https://us.api.konghq.com/"
}

Add the following to your Terraform configuration to create a Konnect Gateway Plugin:

resource "konnect_gateway_plugin_ai_response_transformer" "my_ai_response_transformer" {
  enabled = true

  config = {
    prompt = <<EOF
Add a new header named "new-header" with the value "header-value" to the response. Format the JSON response as follows:
{
  "headers":
    {
      "new-header": "header-value"
    },
  "status": 201,
  "body": "new response body"
}
EOF
    transformation_extract_pattern = "{((.|\n)*)}"
    parse_llm_response_json_instructions = true

    llm = {
      route_type = "llm/v1/chat"

      auth = {
        header_name = "Authorization"
        header_value = "Bearer var.openai_api_key"
      }

      model = {
        provider = "openai"
        name = "gpt-4"
      }
    }
  }

  control_plane_id = konnect_gateway_control_plane.my_konnect_cp.id
}

This example requires the following variables to be added to your manifest. You can specify values at runtime by setting TF_VAR_name=value.

variable "openai_api_key" {
  type = string
}

Add this section to your declarative configuration file:

_format_version: "3.0"
plugins:
  - name: ai-response-transformer
    service: serviceName|Id
    config:
      prompt: |
        Add a new header named "new-header" with the value "header-value" to the response. Format the JSON response as follows:
        {
          "headers":
            {
              "new-header": "header-value"
            },
          "status": 201,
          "body": "new response body"
        }
      transformation_extract_pattern: "{((.|\\n)*)}"
      parse_llm_response_json_instructions: true
      llm:
        route_type: llm/v1/chat
        auth:
          header_name: Authorization
          header_value: Bearer ${{ env "DECK_OPENAI_API_KEY" }}
        model:
          provider: openai
          name: gpt-4

Make sure to replace the following placeholders with your own values:

serviceName|Id: The id or name of the service the plugin configuration will target.

Make the following request:

curl -i -X POST http://localhost:8001/services/{serviceName|Id}/plugins/ \
    --header "Accept: application/json" \
    --header "Content-Type: application/json" \
    --data '
    {
      "name": "ai-response-transformer",
      "config": {
        "prompt": "Add a new header named \"new-header\" with the value \"header-value\" to the response. Format the JSON response as follows:\n{\n  \"headers\":\n    {\n      \"new-header\": \"header-value\"\n    },\n  \"status\": 201,\n  \"body\": \"new response body\"\n}\n",
        "transformation_extract_pattern": "{((.|\\n)*)}",
        "parse_llm_response_json_instructions": true,
        "llm": {
          "route_type": "llm/v1/chat",
          "auth": {
            "header_name": "Authorization",
            "header_value": "Bearer '$OPENAI_API_KEY'"
          },
          "model": {
            "provider": "openai",
            "name": "gpt-4"
          }
        }
      }
    }
    '

Make sure to replace the following placeholders with your own values:

serviceName|Id: The id or name of the service the plugin configuration will target.

Make the following request:

curl -X POST https://{region}.api.konghq.com/v2/control-planes/{controlPlaneId}/core-entities/services/{serviceId}/plugins/ \
    --header "accept: application/json" \
    --header "Content-Type: application/json" \
    --header "Authorization: Bearer $KONNECT_TOKEN" \
    --data '
    {
      "name": "ai-response-transformer",
      "config": {
        "prompt": "Add a new header named \"new-header\" with the value \"header-value\" to the response. Format the JSON response as follows:\n{\n  \"headers\":\n    {\n      \"new-header\": \"header-value\"\n    },\n  \"status\": 201,\n  \"body\": \"new response body\"\n}\n",
        "transformation_extract_pattern": "{((.|\\n)*)}",
        "parse_llm_response_json_instructions": true,
        "llm": {
          "route_type": "llm/v1/chat",
          "auth": {
            "header_name": "Authorization",
            "header_value": "Bearer '$OPENAI_API_KEY'"
          },
          "model": {
            "provider": "openai",
            "name": "gpt-4"
          }
        }
      }
    }
    '

Make sure to replace the following placeholders with your own values:

region: Geographic region where your Kong Konnect is hosted and operates.
controlPlaneId: The id of the control plane.
KONNECT_TOKEN: Your Personal Access Token (PAT) associated with your Konnect account.
serviceId: The id of the service the plugin configuration will target.

See the Konnect API reference to learn about region-specific URLs and personal access tokens.

echo "
apiVersion: configuration.konghq.com/v1
kind: KongPlugin
metadata:
  name: ai-response-transformer
  namespace: kong
  annotations:
    kubernetes.io/ingress.class: kong
config:
  prompt: |
    Add a new header named 'new-header' with the value 'header-value' to the response. Format the JSON response as follows:
    {
      'headers':
        {
          'new-header': 'header-value'
        },
      'status': 201,
      'body': 'new response body'
    }
  transformation_extract_pattern: '{((.|\\n)*)}'
  parse_llm_response_json_instructions: true
  llm:
    route_type: llm/v1/chat
    auth:
      header_name: Authorization
      header_value: Bearer $OPENAI_API_KEY
    model:
      provider: openai
      name: gpt-4
plugin: ai-response-transformer
" | kubectl apply -f -

Next, apply the KongPlugin resource by annotating the service resource:

kubectl annotate -n kong service SERVICE_NAME konghq.com/plugins=ai-response-transformer

Prerequisite: Configure your Personal Access Token

terraform {
  required_providers {
    konnect = {
      source  = "kong/konnect"
    }
  }
}

provider "konnect" {
  personal_access_token = "$KONNECT_TOKEN"
  server_url            = "https://us.api.konghq.com/"
}

Add the following to your Terraform configuration to create a Konnect Gateway Plugin:

resource "konnect_gateway_plugin_ai_response_transformer" "my_ai_response_transformer" {
  enabled = true

  config = {
    prompt = <<EOF
Add a new header named "new-header" with the value "header-value" to the response. Format the JSON response as follows:
{
  "headers":
    {
      "new-header": "header-value"
    },
  "status": 201,
  "body": "new response body"
}
EOF
    transformation_extract_pattern = "{((.|\n)*)}"
    parse_llm_response_json_instructions = true

    llm = {
      route_type = "llm/v1/chat"

      auth = {
        header_name = "Authorization"
        header_value = "Bearer var.openai_api_key"
      }

      model = {
        provider = "openai"
        name = "gpt-4"
      }
    }
  }

  control_plane_id = konnect_gateway_control_plane.my_konnect_cp.id
  service = {
    id = konnect_gateway_service.my_service.id
  }
}

This example requires the following variables to be added to your manifest. You can specify values at runtime by setting TF_VAR_name=value.

variable "openai_api_key" {
  type = string
}

Add this section to your declarative configuration file:

_format_version: "3.0"
plugins:
  - name: ai-response-transformer
    route: routeName|Id
    config:
      prompt: |
        Add a new header named "new-header" with the value "header-value" to the response. Format the JSON response as follows:
        {
          "headers":
            {
              "new-header": "header-value"
            },
          "status": 201,
          "body": "new response body"
        }
      transformation_extract_pattern: "{((.|\\n)*)}"
      parse_llm_response_json_instructions: true
      llm:
        route_type: llm/v1/chat
        auth:
          header_name: Authorization
          header_value: Bearer ${{ env "DECK_OPENAI_API_KEY" }}
        model:
          provider: openai
          name: gpt-4

Make sure to replace the following placeholders with your own values:

routeName|Id: The id or name of the route the plugin configuration will target.

Make the following request:

curl -i -X POST http://localhost:8001/routes/{routeName|Id}/plugins/ \
    --header "Accept: application/json" \
    --header "Content-Type: application/json" \
    --data '
    {
      "name": "ai-response-transformer",
      "config": {
        "prompt": "Add a new header named \"new-header\" with the value \"header-value\" to the response. Format the JSON response as follows:\n{\n  \"headers\":\n    {\n      \"new-header\": \"header-value\"\n    },\n  \"status\": 201,\n  \"body\": \"new response body\"\n}\n",
        "transformation_extract_pattern": "{((.|\\n)*)}",
        "parse_llm_response_json_instructions": true,
        "llm": {
          "route_type": "llm/v1/chat",
          "auth": {
            "header_name": "Authorization",
            "header_value": "Bearer '$OPENAI_API_KEY'"
          },
          "model": {
            "provider": "openai",
            "name": "gpt-4"
          }
        }
      }
    }
    '

Make sure to replace the following placeholders with your own values:

routeName|Id: The id or name of the route the plugin configuration will target.

Make the following request:

curl -X POST https://{region}.api.konghq.com/v2/control-planes/{controlPlaneId}/core-entities/routes/{routeId}/plugins/ \
    --header "accept: application/json" \
    --header "Content-Type: application/json" \
    --header "Authorization: Bearer $KONNECT_TOKEN" \
    --data '
    {
      "name": "ai-response-transformer",
      "config": {
        "prompt": "Add a new header named \"new-header\" with the value \"header-value\" to the response. Format the JSON response as follows:\n{\n  \"headers\":\n    {\n      \"new-header\": \"header-value\"\n    },\n  \"status\": 201,\n  \"body\": \"new response body\"\n}\n",
        "transformation_extract_pattern": "{((.|\\n)*)}",
        "parse_llm_response_json_instructions": true,
        "llm": {
          "route_type": "llm/v1/chat",
          "auth": {
            "header_name": "Authorization",
            "header_value": "Bearer '$OPENAI_API_KEY'"
          },
          "model": {
            "provider": "openai",
            "name": "gpt-4"
          }
        }
      }
    }
    '

Make sure to replace the following placeholders with your own values:

region: Geographic region where your Kong Konnect is hosted and operates.
controlPlaneId: The id of the control plane.
KONNECT_TOKEN: Your Personal Access Token (PAT) associated with your Konnect account.
routeId: The id of the route the plugin configuration will target.

See the Konnect API reference to learn about region-specific URLs and personal access tokens.

echo "
apiVersion: configuration.konghq.com/v1
kind: KongPlugin
metadata:
  name: ai-response-transformer
  namespace: kong
  annotations:
    kubernetes.io/ingress.class: kong
config:
  prompt: |
    Add a new header named 'new-header' with the value 'header-value' to the response. Format the JSON response as follows:
    {
      'headers':
        {
          'new-header': 'header-value'
        },
      'status': 201,
      'body': 'new response body'
    }
  transformation_extract_pattern: '{((.|\\n)*)}'
  parse_llm_response_json_instructions: true
  llm:
    route_type: llm/v1/chat
    auth:
      header_name: Authorization
      header_value: Bearer $OPENAI_API_KEY
    model:
      provider: openai
      name: gpt-4
plugin: ai-response-transformer
" | kubectl apply -f -

Next, apply the KongPlugin resource by annotating the httproute or ingress resource:

kubectl annotate -n kong httproute  konghq.com/plugins=ai-response-transformer

kubectl annotate -n kong ingress  konghq.com/plugins=ai-response-transformer

Prerequisite: Configure your Personal Access Token

terraform {
  required_providers {
    konnect = {
      source  = "kong/konnect"
    }
  }
}

provider "konnect" {
  personal_access_token = "$KONNECT_TOKEN"
  server_url            = "https://us.api.konghq.com/"
}

Add the following to your Terraform configuration to create a Konnect Gateway Plugin:

resource "konnect_gateway_plugin_ai_response_transformer" "my_ai_response_transformer" {
  enabled = true

  config = {
    prompt = <<EOF
Add a new header named "new-header" with the value "header-value" to the response. Format the JSON response as follows:
{
  "headers":
    {
      "new-header": "header-value"
    },
  "status": 201,
  "body": "new response body"
}
EOF
    transformation_extract_pattern = "{((.|\n)*)}"
    parse_llm_response_json_instructions = true

    llm = {
      route_type = "llm/v1/chat"

      auth = {
        header_name = "Authorization"
        header_value = "Bearer var.openai_api_key"
      }

      model = {
        provider = "openai"
        name = "gpt-4"
      }
    }
  }

  control_plane_id = konnect_gateway_control_plane.my_konnect_cp.id
  route = {
    id = konnect_gateway_route.my_route.id
  }
}

This example requires the following variables to be added to your manifest. You can specify values at runtime by setting TF_VAR_name=value.

variable "openai_api_key" {
  type = string
}

Add this section to your declarative configuration file:

_format_version: "3.0"
plugins:
  - name: ai-response-transformer
    consumer: consumerName|Id
    config:
      prompt: |
        Add a new header named "new-header" with the value "header-value" to the response. Format the JSON response as follows:
        {
          "headers":
            {
              "new-header": "header-value"
            },
          "status": 201,
          "body": "new response body"
        }
      transformation_extract_pattern: "{((.|\\n)*)}"
      parse_llm_response_json_instructions: true
      llm:
        route_type: llm/v1/chat
        auth:
          header_name: Authorization
          header_value: Bearer ${{ env "DECK_OPENAI_API_KEY" }}
        model:
          provider: openai
          name: gpt-4

Make sure to replace the following placeholders with your own values:

consumerName|Id: The id or name of the consumer the plugin configuration will target.

Make the following request:

curl -i -X POST http://localhost:8001/consumers/{consumerName|Id}/plugins/ \
    --header "Accept: application/json" \
    --header "Content-Type: application/json" \
    --data '
    {
      "name": "ai-response-transformer",
      "config": {
        "prompt": "Add a new header named \"new-header\" with the value \"header-value\" to the response. Format the JSON response as follows:\n{\n  \"headers\":\n    {\n      \"new-header\": \"header-value\"\n    },\n  \"status\": 201,\n  \"body\": \"new response body\"\n}\n",
        "transformation_extract_pattern": "{((.|\\n)*)}",
        "parse_llm_response_json_instructions": true,
        "llm": {
          "route_type": "llm/v1/chat",
          "auth": {
            "header_name": "Authorization",
            "header_value": "Bearer '$OPENAI_API_KEY'"
          },
          "model": {
            "provider": "openai",
            "name": "gpt-4"
          }
        }
      }
    }
    '

Make sure to replace the following placeholders with your own values:

consumerName|Id: The id or name of the consumer the plugin configuration will target.

Make the following request:

curl -X POST https://{region}.api.konghq.com/v2/control-planes/{controlPlaneId}/core-entities/consumers/{consumerId}/plugins/ \
    --header "accept: application/json" \
    --header "Content-Type: application/json" \
    --header "Authorization: Bearer $KONNECT_TOKEN" \
    --data '
    {
      "name": "ai-response-transformer",
      "config": {
        "prompt": "Add a new header named \"new-header\" with the value \"header-value\" to the response. Format the JSON response as follows:\n{\n  \"headers\":\n    {\n      \"new-header\": \"header-value\"\n    },\n  \"status\": 201,\n  \"body\": \"new response body\"\n}\n",
        "transformation_extract_pattern": "{((.|\\n)*)}",
        "parse_llm_response_json_instructions": true,
        "llm": {
          "route_type": "llm/v1/chat",
          "auth": {
            "header_name": "Authorization",
            "header_value": "Bearer '$OPENAI_API_KEY'"
          },
          "model": {
            "provider": "openai",
            "name": "gpt-4"
          }
        }
      }
    }
    '

Make sure to replace the following placeholders with your own values:

region: Geographic region where your Kong Konnect is hosted and operates.
controlPlaneId: The id of the control plane.
KONNECT_TOKEN: Your Personal Access Token (PAT) associated with your Konnect account.
consumerId: The id of the consumer the plugin configuration will target.

See the Konnect API reference to learn about region-specific URLs and personal access tokens.

echo "
apiVersion: configuration.konghq.com/v1
kind: KongPlugin
metadata:
  name: ai-response-transformer
  namespace: kong
  annotations:
    kubernetes.io/ingress.class: kong
config:
  prompt: |
    Add a new header named 'new-header' with the value 'header-value' to the response. Format the JSON response as follows:
    {
      'headers':
        {
          'new-header': 'header-value'
        },
      'status': 201,
      'body': 'new response body'
    }
  transformation_extract_pattern: '{((.|\\n)*)}'
  parse_llm_response_json_instructions: true
  llm:
    route_type: llm/v1/chat
    auth:
      header_name: Authorization
      header_value: Bearer $OPENAI_API_KEY
    model:
      provider: openai
      name: gpt-4
plugin: ai-response-transformer
" | kubectl apply -f -

Next, apply the KongPlugin resource by annotating the KongConsumer resource:

kubectl annotate -n kong  CONSUMER_NAME konghq.com/plugins=ai-response-transformer

Prerequisite: Configure your Personal Access Token

terraform {
  required_providers {
    konnect = {
      source  = "kong/konnect"
    }
  }
}

provider "konnect" {
  personal_access_token = "$KONNECT_TOKEN"
  server_url            = "https://us.api.konghq.com/"
}

Add the following to your Terraform configuration to create a Konnect Gateway Plugin:

resource "konnect_gateway_plugin_ai_response_transformer" "my_ai_response_transformer" {
  enabled = true

  config = {
    prompt = <<EOF
Add a new header named "new-header" with the value "header-value" to the response. Format the JSON response as follows:
{
  "headers":
    {
      "new-header": "header-value"
    },
  "status": 201,
  "body": "new response body"
}
EOF
    transformation_extract_pattern = "{((.|\n)*)}"
    parse_llm_response_json_instructions = true

    llm = {
      route_type = "llm/v1/chat"

      auth = {
        header_name = "Authorization"
        header_value = "Bearer var.openai_api_key"
      }

      model = {
        provider = "openai"
        name = "gpt-4"
      }
    }
  }

  control_plane_id = konnect_gateway_control_plane.my_konnect_cp.id
  consumer = {
    id = konnect_gateway_consumer.my_consumer.id
  }
}

This example requires the following variables to be added to your manifest. You can specify values at runtime by setting TF_VAR_name=value.

variable "openai_api_key" {
  type = string
}

Add this section to your declarative configuration file:

_format_version: "3.0"
plugins:
  - name: ai-response-transformer
    consumer_group: consumerGroupName|Id
    config:
      prompt: |
        Add a new header named "new-header" with the value "header-value" to the response. Format the JSON response as follows:
        {
          "headers":
            {
              "new-header": "header-value"
            },
          "status": 201,
          "body": "new response body"
        }
      transformation_extract_pattern: "{((.|\\n)*)}"
      parse_llm_response_json_instructions: true
      llm:
        route_type: llm/v1/chat
        auth:
          header_name: Authorization
          header_value: Bearer ${{ env "DECK_OPENAI_API_KEY" }}
        model:
          provider: openai
          name: gpt-4

Make sure to replace the following placeholders with your own values:

consumerGroupName|Id: The id or name of the consumer group the plugin configuration will target.

Make the following request:

curl -i -X POST http://localhost:8001/consumer_groups/{consumerGroupName|Id}/plugins/ \
    --header "Accept: application/json" \
    --header "Content-Type: application/json" \
    --data '
    {
      "name": "ai-response-transformer",
      "config": {
        "prompt": "Add a new header named \"new-header\" with the value \"header-value\" to the response. Format the JSON response as follows:\n{\n  \"headers\":\n    {\n      \"new-header\": \"header-value\"\n    },\n  \"status\": 201,\n  \"body\": \"new response body\"\n}\n",
        "transformation_extract_pattern": "{((.|\\n)*)}",
        "parse_llm_response_json_instructions": true,
        "llm": {
          "route_type": "llm/v1/chat",
          "auth": {
            "header_name": "Authorization",
            "header_value": "Bearer '$OPENAI_API_KEY'"
          },
          "model": {
            "provider": "openai",
            "name": "gpt-4"
          }
        }
      }
    }
    '

Make sure to replace the following placeholders with your own values:

consumerGroupName|Id: The id or name of the consumer group the plugin configuration will target.

Make the following request:

curl -X POST https://{region}.api.konghq.com/v2/control-planes/{controlPlaneId}/core-entities/consumer_groups/{consumerGroupId}/plugins/ \
    --header "accept: application/json" \
    --header "Content-Type: application/json" \
    --header "Authorization: Bearer $KONNECT_TOKEN" \
    --data '
    {
      "name": "ai-response-transformer",
      "config": {
        "prompt": "Add a new header named \"new-header\" with the value \"header-value\" to the response. Format the JSON response as follows:\n{\n  \"headers\":\n    {\n      \"new-header\": \"header-value\"\n    },\n  \"status\": 201,\n  \"body\": \"new response body\"\n}\n",
        "transformation_extract_pattern": "{((.|\\n)*)}",
        "parse_llm_response_json_instructions": true,
        "llm": {
          "route_type": "llm/v1/chat",
          "auth": {
            "header_name": "Authorization",
            "header_value": "Bearer '$OPENAI_API_KEY'"
          },
          "model": {
            "provider": "openai",
            "name": "gpt-4"
          }
        }
      }
    }
    '

Make sure to replace the following placeholders with your own values:

region: Geographic region where your Kong Konnect is hosted and operates.
controlPlaneId: The id of the control plane.
KONNECT_TOKEN: Your Personal Access Token (PAT) associated with your Konnect account.
consumerGroupId: The id of the consumer group the plugin configuration will target.

See the Konnect API reference to learn about region-specific URLs and personal access tokens.

echo "
apiVersion: configuration.konghq.com/v1
kind: KongPlugin
metadata:
  name: ai-response-transformer
  namespace: kong
  annotations:
    kubernetes.io/ingress.class: kong
config:
  prompt: |
    Add a new header named 'new-header' with the value 'header-value' to the response. Format the JSON response as follows:
    {
      'headers':
        {
          'new-header': 'header-value'
        },
      'status': 201,
      'body': 'new response body'
    }
  transformation_extract_pattern: '{((.|\\n)*)}'
  parse_llm_response_json_instructions: true
  llm:
    route_type: llm/v1/chat
    auth:
      header_name: Authorization
      header_value: Bearer $OPENAI_API_KEY
    model:
      provider: openai
      name: gpt-4
plugin: ai-response-transformer
" | kubectl apply -f -

Next, apply the KongPlugin resource by annotating the KongConsumerGroup resource:

kubectl annotate -n kong  CONSUMERGROUP_NAME konghq.com/plugins=ai-response-transformer

Prerequisite: Configure your Personal Access Token

terraform {
  required_providers {
    konnect = {
      source  = "kong/konnect"
    }
  }
}

provider "konnect" {
  personal_access_token = "$KONNECT_TOKEN"
  server_url            = "https://us.api.konghq.com/"
}

Add the following to your Terraform configuration to create a Konnect Gateway Plugin:

resource "konnect_gateway_plugin_ai_response_transformer" "my_ai_response_transformer" {
  enabled = true

  config = {
    prompt = <<EOF
Add a new header named "new-header" with the value "header-value" to the response. Format the JSON response as follows:
{
  "headers":
    {
      "new-header": "header-value"
    },
  "status": 201,
  "body": "new response body"
}
EOF
    transformation_extract_pattern = "{((.|\n)*)}"
    parse_llm_response_json_instructions = true

    llm = {
      route_type = "llm/v1/chat"

      auth = {
        header_name = "Authorization"
        header_value = "Bearer var.openai_api_key"
      }

      model = {
        provider = "openai"
        name = "gpt-4"
      }
    }
  }

  control_plane_id = konnect_gateway_control_plane.my_konnect_cp.id
  consumer_group = {
    id = konnect_gateway_consumer_group.my_consumer_group.id
  }
}

This example requires the following variables to be added to your manifest. You can specify values at runtime by setting TF_VAR_name=value.

variable "openai_api_key" {
  type = string
}

AI Response Transformer

Add a header to a response bodyv3.6+

Prerequisites

Environment variables

Set up the plugin

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