Request Termination: Echo response back to client - Policy

Echo response back to client

Block requests and echo the request back to the client with debugging information about the AI Gateway instance, such as the internal routing details it matched for the request. You can also combine the config.echo parameter with a header name specified in config.trigger to make the policy trigger only on specific requests and avoid disturbing real traffic. Because the echoed response exposes internal routing details, use a trigger and remove the policy when you finish debugging.

Set up the policy

kongctl

policy.yaml

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ai_gateway_policies:
  - ref: echo-response-to-client
    ai_gateway: !lookup {id: !env AI_GATEWAY_ID}
    name: echo-response-to-client
    display_name: Echo response back to client
    type: request-termination
    enabled: true
    config:
      status_code: 401
      message: Error - Authentication required
      echo: true
    global: false

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

AI_GATEWAY_ID: The id of your AI Gateway.

curl -X POST https://{region}.api.konghq.com/v1/ai-gateways/{AIGatewayId}/policies \
    --header "accept: application/json" \
    --header "Content-Type: application/json" \
    --header "Authorization: Bearer $KONNECT_TOKEN" \
    --data '
    {
      "name": "echo-response-to-client",
      "display_name": "Echo response back to client",
      "type": "request-termination",
      "enabled": true,
      "config": {
        "status_code": 401,
        "message": "Error - Authentication required",
        "echo": true
      },
      "global": false
    }
    '

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

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

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

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/"
}

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Add the following to your Terraform configuration:

resource "konnect_ai_gateway_policy" "my_policy" {
  name = "echo-response-to-client"
  display_name = "Echo response back to client"
  type = "request-termination"
  enabled = true
  global = false
  config = jsonencode({
    status_code = 401
    message = "Error - Authentication required"
    echo = true
  })


  gateway_id = konnect_ai_gateway.my_ai_gateway.id
}

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kongctl

policy.yaml

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ai_gateway_policies:
  - ref: echo-response-to-client
    ai_gateway: !lookup {id: !env AI_GATEWAY_ID}
    name: echo-response-to-client
    display_name: Echo response back to client
    type: request-termination
    enabled: true
    config:
      status_code: 401
      message: Error - Authentication required
      echo: true
    global: false

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

AI_GATEWAY_ID: The id of your AI Gateway.

curl -X POST https://{region}.api.konghq.com/v1/ai-gateways/{AIGatewayId}/policies \
    --header "accept: application/json" \
    --header "Content-Type: application/json" \
    --header "Authorization: Bearer $KONNECT_TOKEN" \
    --data '
    {
      "name": "echo-response-to-client",
      "display_name": "Echo response back to client",
      "type": "request-termination",
      "enabled": true,
      "config": {
        "status_code": 401,
        "message": "Error - Authentication required",
        "echo": true
      },
      "global": false
    }
    '

Copied!

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

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

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

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/"
}

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Add the following to your Terraform configuration:

resource "konnect_ai_gateway_policy" "my_policy" {
  name = "echo-response-to-client"
  display_name = "Echo response back to client"
  type = "request-termination"
  enabled = true
  global = false
  config = jsonencode({
    status_code = 401
    message = "Error - Authentication required"
    echo = true
  })


  gateway_id = konnect_ai_gateway.my_ai_gateway.id
}

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kongctl

policy.yaml

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ai_gateway_policies:
  - ref: echo-response-to-client
    ai_gateway: !lookup {id: !env AI_GATEWAY_ID}
    name: echo-response-to-client
    display_name: Echo response back to client
    type: request-termination
    enabled: true
    config:
      status_code: 401
      message: Error - Authentication required
      echo: true
    global: false

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

AI_GATEWAY_ID: The id of your AI Gateway.

curl -X POST https://{region}.api.konghq.com/v1/ai-gateways/{AIGatewayId}/policies \
    --header "accept: application/json" \
    --header "Content-Type: application/json" \
    --header "Authorization: Bearer $KONNECT_TOKEN" \
    --data '
    {
      "name": "echo-response-to-client",
      "display_name": "Echo response back to client",
      "type": "request-termination",
      "enabled": true,
      "config": {
        "status_code": 401,
        "message": "Error - Authentication required",
        "echo": true
      },
      "global": false
    }
    '

Copied!

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

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

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

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/"
}

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Add the following to your Terraform configuration:

resource "konnect_ai_gateway_policy" "my_policy" {
  name = "echo-response-to-client"
  display_name = "Echo response back to client"
  type = "request-termination"
  enabled = true
  global = false
  config = jsonencode({
    status_code = 401
    message = "Error - Authentication required"
    echo = true
  })


  gateway_id = konnect_ai_gateway.my_ai_gateway.id
}

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kongctl

policy.yaml

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ai_gateway_policies:
  - ref: echo-response-to-client
    ai_gateway: !lookup {id: !env AI_GATEWAY_ID}
    name: echo-response-to-client
    display_name: Echo response back to client
    type: request-termination
    enabled: true
    config:
      status_code: 401
      message: Error - Authentication required
      echo: true
    global: false

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

AI_GATEWAY_ID: The id of your AI Gateway.

curl -X POST https://{region}.api.konghq.com/v1/ai-gateways/{AIGatewayId}/policies \
    --header "accept: application/json" \
    --header "Content-Type: application/json" \
    --header "Authorization: Bearer $KONNECT_TOKEN" \
    --data '
    {
      "name": "echo-response-to-client",
      "display_name": "Echo response back to client",
      "type": "request-termination",
      "enabled": true,
      "config": {
        "status_code": 401,
        "message": "Error - Authentication required",
        "echo": true
      },
      "global": false
    }
    '

Copied!

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

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

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

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/"
}

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Add the following to your Terraform configuration:

resource "konnect_ai_gateway_policy" "my_policy" {
  name = "echo-response-to-client"
  display_name = "Echo response back to client"
  type = "request-termination"
  enabled = true
  global = false
  config = jsonencode({
    status_code = 401
    message = "Error - Authentication required"
    echo = true
  })


  gateway_id = konnect_ai_gateway.my_ai_gateway.id
}

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kongctl

policy.yaml

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ai_gateway_policies:
  - ref: echo-response-to-client
    ai_gateway: !lookup {id: !env AI_GATEWAY_ID}
    name: echo-response-to-client
    display_name: Echo response back to client
    type: request-termination
    enabled: true
    config:
      status_code: 401
      message: Error - Authentication required
      echo: true
    global: false

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

AI_GATEWAY_ID: The id of your AI Gateway.

curl -X POST https://{region}.api.konghq.com/v1/ai-gateways/{AIGatewayId}/policies \
    --header "accept: application/json" \
    --header "Content-Type: application/json" \
    --header "Authorization: Bearer $KONNECT_TOKEN" \
    --data '
    {
      "name": "echo-response-to-client",
      "display_name": "Echo response back to client",
      "type": "request-termination",
      "enabled": true,
      "config": {
        "status_code": 401,
        "message": "Error - Authentication required",
        "echo": true
      },
      "global": false
    }
    '

Copied!

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

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

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

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/"
}

Copied!

Add the following to your Terraform configuration:

resource "konnect_ai_gateway_policy" "my_policy" {
  name = "echo-response-to-client"
  display_name = "Echo response back to client"
  type = "request-termination"
  enabled = true
  global = false
  config = jsonencode({
    status_code = 401
    message = "Error - Authentication required"
    echo = true
  })


  gateway_id = konnect_ai_gateway.my_ai_gateway.id
}

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kongctl

policy.yaml

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ai_gateway_policies:
  - ref: echo-response-to-client
    ai_gateway: !lookup {id: !env AI_GATEWAY_ID}
    name: echo-response-to-client
    display_name: Echo response back to client
    type: request-termination
    enabled: true
    config:
      status_code: 401
      message: Error - Authentication required
      echo: true
    global: true

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

AI_GATEWAY_ID: The id of your AI Gateway.

curl -X POST https://{region}.api.konghq.com/v1/ai-gateways/{AIGatewayId}/policies \
    --header "accept: application/json" \
    --header "Content-Type: application/json" \
    --header "Authorization: Bearer $KONNECT_TOKEN" \
    --data '
    {
      "name": "echo-response-to-client",
      "display_name": "Echo response back to client",
      "type": "request-termination",
      "enabled": true,
      "config": {
        "status_code": 401,
        "message": "Error - Authentication required",
        "echo": true
      },
      "global": true
    }
    '

Copied!

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

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

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

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/"
}

Copied!

Add the following to your Terraform configuration:

resource "konnect_ai_gateway_policy" "my_policy" {
  name = "echo-response-to-client"
  display_name = "Echo response back to client"
  type = "request-termination"
  enabled = true
  global = true
  config = jsonencode({
    status_code = 401
    message = "Error - Authentication required"
    echo = true
  })


  gateway_id = konnect_ai_gateway.my_ai_gateway.id
}

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Attach the policy

After creating the policy, add echo-response-to-client to the policies array of your AI Model. The tool examples update an existing AI Model with the policy attached: replace the entity configuration in the example with your own, as the update replaces the entire AI Model.

kongctl

model.yaml

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ai_gateway_models:
  - ref: my-gpt-4o
    ai_gateway: !lookup {id: !env AI_GATEWAY_ID}
    display_name: my-gpt-4o
    name: my-gpt-4o
    type: model
    capabilities:
    - generate
    formats:
    - type: openai
    targets:
    - name: gpt-4o
      provider: my-openai-account
      config:
        type: openai
    config:
      route:
        paths:
        - "/v1"
        model:
          body_param: model
          values:
          - my-gpt-4o
      logging:
        payloads: false
    policies:
    - !ref echo-response-to-client#name

After creating the policy, add echo-response-to-client to the policies array of your AI Model. The tool examples update an existing AI Model with the policy attached: replace the entity configuration in the example with your own, as the update replaces the entire AI Model.

curl -X PUT https://{region}.api.konghq.com/v1/ai-gateways/{AIGatewayId}/models/my-gpt-4o \
    --header "accept: application/json" \
    --header "Content-Type: application/json" \
    --header "Authorization: Bearer $KONNECT_TOKEN" \
    --data '
    {
      "display_name": "my-gpt-4o",
      "name": "my-gpt-4o",
      "type": "model",
      "capabilities": [
        "generate"
      ],
      "formats": [
        {
          "type": "openai"
        }
      ],
      "policies": [
        "echo-response-to-client"
      ],
      "targets": [
        {
          "name": "gpt-4o",
          "provider": "my-openai-account",
          "config": {
            "type": "openai"
          }
        }
      ],
      "config": {
        "route": {
          "paths": [
            "/v1"
          ],
          "model": {
            "body_param": "model",
            "values": [
              "my-gpt-4o"
            ]
          }
        },
        "logging": {
          "payloads": false
        }
      }
    }
    '

Copied!

After creating the policy, add echo-response-to-client to the policies array of your AI Model. The tool examples update an existing AI Model with the policy attached: replace the entity configuration in the example with your own, as the update replaces the entire AI Model.

resource "konnect_ai_gateway_model" "my_model" {
  display_name = "my-gpt-4o"
  name = "my-gpt-4o"
  type = "model"
  capabilities = ["generate"]
  formats = [
    {
      type = "openai"
    }  ]
  targets = [
    {
      name = "gpt-4o"
      provider = "my-openai-account"

      config = {
        type = "openai"
      }
    }  ]
  config = jsonencode({

    route = {
      paths = ["/v1"]

      model = {
        body_param = "model"
        values = ["my-gpt-4o"]
      }
    }

    logging = {
      payloads = false
    }
  })
  policies = [konnect_ai_gateway_policy.my_policy.name]


  gateway_id = konnect_ai_gateway.my_ai_gateway.id
}

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After creating the policy, add echo-response-to-client to the policies array of your AI MCP Server. The tool examples update an existing AI MCP Server with the policy attached: replace the entity configuration in the example with your own, as the update replaces the entire AI MCP Server.

kongctl

mcp_server.yaml

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ai_gateway_mcp_servers:
  - ref: petstore-mcp
    ai_gateway: !lookup {id: !env AI_GATEWAY_ID}
    display_name: Petstore API
    name: petstore-mcp
    type: conversion-listener
    enabled: true
    access:
      acl_attribute_type: consumer
      acls:
        allow: []
      default_tool_acls:
        deny: []
    config:
      url: http://host.docker.internal:8080/api/v3
      route:
        paths:
        - "/petstore"
      logging:
        payloads: false
      server:
        timeout: 60000
    tools:
    - name: get-pets-by-status
      description: Find pets by status
      method: GET
      path: "/petstore/pet/findByStatus"
      parameters:
      - name: status
        in: query
        required: true
        schema:
          type: string
          enum:
          - available
          - pending
          - sold
        description: Status value to filter pets by
    - name: get-pet-by-id
      description: Get pet by ID
      method: GET
      path: "/petstore/pet/{petId}"
      parameters:
      - name: petId
        in: path
        required: true
        schema:
          type: integer
        description: ID of the pet to retrieve
    policies:
    - !ref echo-response-to-client#name

After creating the policy, add echo-response-to-client to the policies array of your AI MCP Server. The tool examples update an existing AI MCP Server with the policy attached: replace the entity configuration in the example with your own, as the update replaces the entire AI MCP Server.

curl -X PUT https://{region}.api.konghq.com/v1/ai-gateways/{AIGatewayId}/mcp-servers/petstore-mcp \
    --header "accept: application/json" \
    --header "Content-Type: application/json" \
    --header "Authorization: Bearer $KONNECT_TOKEN" \
    --data '
    {
      "display_name": "Petstore API",
      "name": "petstore-mcp",
      "type": "conversion-listener",
      "enabled": true,
      "policies": [
        "echo-response-to-client"
      ],
      "access": {
        "acl_attribute_type": "consumer",
        "acls": {
          "allow": []
        },
        "default_tool_acls": {
          "deny": []
        }
      },
      "config": {
        "url": "http://host.docker.internal:8080/api/v3",
        "route": {
          "paths": [
            "/petstore"
          ]
        },
        "logging": {
          "payloads": false
        },
        "server": {
          "timeout": 60000
        }
      },
      "tools": [
        {
          "name": "get-pets-by-status",
          "description": "Find pets by status",
          "method": "GET",
          "path": "/petstore/pet/findByStatus",
          "parameters": [
            {
              "name": "status",
              "in": "query",
              "required": true,
              "schema": {
                "type": "string",
                "enum": [
                  "available",
                  "pending",
                  "sold"
                ]
              },
              "description": "Status value to filter pets by"
            }
          ]
        },
        {
          "name": "get-pet-by-id",
          "description": "Get pet by ID",
          "method": "GET",
          "path": "/petstore/pet/{petId}",
          "parameters": [
            {
              "name": "petId",
              "in": "path",
              "required": true,
              "schema": {
                "type": "integer"
              },
              "description": "ID of the pet to retrieve"
            }
          ]
        }
      ]
    }
    '

Copied!

After creating the policy, add echo-response-to-client to the policies array of your AI MCP Server. The tool examples update an existing AI MCP Server with the policy attached: replace the entity configuration in the example with your own, as the update replaces the entire AI MCP Server.

resource "konnect_ai_gateway_mcp_server" "my_mcp_server" {
  display_name = "Petstore API"
  name = "petstore-mcp"
  type = "conversion-listener"
  enabled = true
  access = {
    acl_attribute_type = "consumer"

    acls = {
      allow = []
    }

    default_tool_acls = {
      deny = []
    }
  }
  tools = [
    {
      name = "get-pets-by-status"
      description = "Find pets by status"
      method = "GET"
      path = "/petstore/pet/findByStatus"
      parameters = [
        {
          name = "status"
          in = "query"
          required = true

          schema = {
            type = "string"
            enum = ["available", "pending", "sold"]
          }
          description = "Status value to filter pets by"
        }      ]
    }, 

    {
      name = "get-pet-by-id"
      description = "Get pet by ID"
      method = "GET"
      path = "/petstore/pet/{petId}"
      parameters = [
        {
          name = "petId"
          in = "path"
          required = true

          schema = {
            type = "integer"
          }
          description = "ID of the pet to retrieve"
        }      ]
    }  ]
  config = jsonencode({
    url = "http://host.docker.internal:8080/api/v3"

    route = {
      paths = ["/petstore"]
    }

    logging = {
      payloads = false
    }

    server = {
      timeout = 60000
    }
  })
  policies = [konnect_ai_gateway_policy.my_policy.name]


  gateway_id = konnect_ai_gateway.my_ai_gateway.id
}

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After creating the policy, add echo-response-to-client to the policies array of your AI Agent. The tool examples update an existing AI Agent with the policy attached: replace the entity configuration in the example with your own, as the update replaces the entire AI Agent.

kongctl

agent.yaml

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ai_gateway_agents:
  - ref: kongair-flight-booking-agent
    ai_gateway: !lookup {id: !env AI_GATEWAY_ID}
    display_name: KongAir Flight Booking Agent
    name: kongair-flight-booking-agent
    type: a2a
    access:
      acls:
        allow:
        - internal-teams
    config:
      url: https://booking-agent.internal.kongair.com
      route:
        paths:
        - "/kongair-flight-booking"
      logging:
        payloads: false
        max_payload_size: 1048576
    policies:
    - !ref echo-response-to-client#name

After creating the policy, add echo-response-to-client to the policies array of your AI Agent. The tool examples update an existing AI Agent with the policy attached: replace the entity configuration in the example with your own, as the update replaces the entire AI Agent.

curl -X PUT https://{region}.api.konghq.com/v1/ai-gateways/{AIGatewayId}/agents/kongair-flight-booking-agent \
    --header "accept: application/json" \
    --header "Content-Type: application/json" \
    --header "Authorization: Bearer $KONNECT_TOKEN" \
    --data '
    {
      "display_name": "KongAir Flight Booking Agent",
      "name": "kongair-flight-booking-agent",
      "type": "a2a",
      "access": {
        "acls": {
          "allow": [
            "internal-teams"
          ]
        }
      },
      "policies": [
        "echo-response-to-client"
      ],
      "config": {
        "url": "https://booking-agent.internal.kongair.com",
        "route": {
          "paths": [
            "/kongair-flight-booking"
          ]
        },
        "logging": {
          "payloads": false,
          "max_payload_size": 1048576
        }
      }
    }
    '

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After creating the policy, add echo-response-to-client to the policies array of your AI Agent. The tool examples update an existing AI Agent with the policy attached: replace the entity configuration in the example with your own, as the update replaces the entire AI Agent.

resource "konnect_ai_gateway_agent" "my_agent" {
  display_name = "KongAir Flight Booking Agent"
  name = "kongair-flight-booking-agent"
  type = "a2a"
  access = {

    acls = {
      allow = ["internal-teams"]
    }
  }
  config = jsonencode({
    url = "https://booking-agent.internal.kongair.com"

    route = {
      paths = ["/kongair-flight-booking"]
    }

    logging = {
      payloads = false
      max_payload_size = 1048576
    }
  })
  policies = [konnect_ai_gateway_policy.my_policy.name]


  gateway_id = konnect_ai_gateway.my_ai_gateway.id
}

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After creating the policy, add echo-response-to-client to the policies array of your AI Consumer. The tool examples update an existing AI Consumer with the policy attached: replace the entity configuration in the example with your own, as the update replaces the entire AI Consumer.

kongctl

consumer.yaml

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ai_gateway_consumers:
  - ref: mobile-app-production
    ai_gateway: !lookup {id: !env AI_GATEWAY_ID}
    display_name: Mobile App - Production
    name: mobile-app-production
    type: api-key
    policies:
    - !ref echo-response-to-client#name

After creating the policy, add echo-response-to-client to the policies array of your AI Consumer. The tool examples update an existing AI Consumer with the policy attached: replace the entity configuration in the example with your own, as the update replaces the entire AI Consumer.

curl -X PUT https://{region}.api.konghq.com/v1/ai-gateways/{AIGatewayId}/consumers/mobile-app-production \
    --header "accept: application/json" \
    --header "Content-Type: application/json" \
    --header "Authorization: Bearer $KONNECT_TOKEN" \
    --data '
    {
      "display_name": "Mobile App - Production",
      "name": "mobile-app-production",
      "type": "api-key",
      "policies": [
        "echo-response-to-client"
      ]
    }
    '

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After creating the policy, add echo-response-to-client to the policies array of your AI Consumer. The tool examples update an existing AI Consumer with the policy attached: replace the entity configuration in the example with your own, as the update replaces the entire AI Consumer.

resource "konnect_ai_gateway_consumer" "my_consumer" {
  display_name = "Mobile App - Production"
  name = "mobile-app-production"
  type = "api-key"
  policies = [konnect_ai_gateway_policy.my_policy.name]


  gateway_id = konnect_ai_gateway.my_ai_gateway.id
}

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After creating the policy, add echo-response-to-client to the policies array of your AI Consumer Group. The tool examples update an existing AI Consumer Group with the policy attached: replace the entity configuration in the example with your own, as the update replaces the entire AI Consumer Group.

kongctl

consumer_group.yaml

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ai_gateway_consumer_groups:
  - ref: internal-teams
    ai_gateway: !lookup {id: !env AI_GATEWAY_ID}
    display_name: Internal Teams
    name: internal-teams
    policies:
    - !ref echo-response-to-client#name

After creating the policy, add echo-response-to-client to the policies array of your AI Consumer Group. The tool examples update an existing AI Consumer Group with the policy attached: replace the entity configuration in the example with your own, as the update replaces the entire AI Consumer Group.

curl -X PUT https://{region}.api.konghq.com/v1/ai-gateways/{AIGatewayId}/consumer-groups/internal-teams \
    --header "accept: application/json" \
    --header "Content-Type: application/json" \
    --header "Authorization: Bearer $KONNECT_TOKEN" \
    --data '
    {
      "display_name": "Internal Teams",
      "name": "internal-teams",
      "policies": [
        "echo-response-to-client"
      ]
    }
    '

Copied!

After creating the policy, add echo-response-to-client to the policies array of your AI Consumer Group. The tool examples update an existing AI Consumer Group with the policy attached: replace the entity configuration in the example with your own, as the update replaces the entire AI Consumer Group.

resource "konnect_ai_gateway_consumer_group" "my_consumer_group" {
  display_name = "Internal Teams"
  name = "internal-teams"
  policies = [konnect_ai_gateway_policy.my_policy.name]


  gateway_id = konnect_ai_gateway.my_ai_gateway.id
}

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Request Termination Policy

Echo response back to client

Set up the policy

Attach the policy

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