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Basic config examples for AI Proxy Advanced

By Kong Inc.

Basic configuration examples

The following examples provide some typical configurations for enabling the ai-proxy-advanced plugin on a service.

Make the following request:

curl -X POST http://localhost:8001/services/{serviceName|Id}/plugins \
    --header "accept: application/json" \
    --header "Content-Type: application/json" \
    --data '
    {
  "name": "ai-proxy-advanced",
  "config": {
    "targets": [
      {
        "route_type": "llm/v1/chat",
        "auth": {
          "header_name": "Authorization",
          "header_value": "Bearer token"
        },
        "model": {
          "provider": "openai"
        }
      },
      {
        "route_type": "llm/v1/chat",
        "model": {
          "provider": "llama2",
          "options": {
            "llama2_format": "openai",
            "upstream_url": "http://httpbin"
          }
        }
      }
    ]
  }
}
    '

Replace SERVICE_NAME|ID with the id or name of the service that this plugin configuration will target.

Make the following request, substituting your own access token, region, control plane ID, and service ID:

curl -X POST \
https://{us|eu}.api.konghq.com/v2/control-planes/{controlPlaneId}/core-entities/services/{serviceId}/plugins \
    --header "accept: application/json" \
    --header "Content-Type: application/json" \
    --header "Authorization: Bearer TOKEN" \
    --data '{"name":"ai-proxy-advanced","config":{"targets":[{"route_type":"llm/v1/chat","auth":{"header_name":"Authorization","header_value":"Bearer token"},"model":{"provider":"openai"}},{"route_type":"llm/v1/chat","model":{"provider":"llama2","options":{"llama2_format":"openai","upstream_url":"http://httpbin"}}}]}}'

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

First, create a KongPlugin resource:

echo "
apiVersion: configuration.konghq.com/v1
kind: KongPlugin
metadata:
  name: ai-proxy-advanced-example
plugin: ai-proxy-advanced
config:
  targets:
  - route_type: llm/v1/chat
    auth:
      header_name: Authorization
      header_value: Bearer token
    model:
      provider: openai
  - route_type: llm/v1/chat
    model:
      provider: llama2
      options:
        llama2_format: openai
        upstream_url: http://httpbin
" | kubectl apply -f -

Next, apply the KongPlugin resource to an ingress by annotating the service as follows:

kubectl annotate service SERVICE_NAME konghq.com/plugins=ai-proxy-advanced-example

Replace SERVICE_NAME with the name of the service that this plugin configuration will target. You can see your available ingresses by running kubectl get service.

Note: The KongPlugin resource only needs to be defined once and can be applied to any service, consumer, or route in the namespace. If you want the plugin to be available cluster-wide, create the resource as a KongClusterPlugin instead of KongPlugin.

Add this section to your declarative configuration file:

plugins:
- name: ai-proxy-advanced
  service: SERVICE_NAME|ID
  config:
    targets:
    - route_type: llm/v1/chat
      auth:
        header_name: Authorization
        header_value: Bearer token
      model:
        provider: openai
    - route_type: llm/v1/chat
      model:
        provider: llama2
        options:
          llama2_format: openai
          upstream_url: http://httpbin

Replace SERVICE_NAME|ID with the id or name of the service that this plugin configuration will target.

Prerequisite: Configure your Personal Access Token 
terraform {
  required_providers {
    konnect = {
      source  = "kong/konnect"
    }
  }
}

provider "konnect" {
  personal_access_token = "kpat_YOUR_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_proxy_advanced" "my_ai_proxy_advanced" {
  enabled = true

  config = {
    targets = [
      {
        route_type = "llm/v1/chat"

        auth = {
          header_name = "Authorization"
          header_value = "Bearer token"
        }

        model = {
          provider = "openai"
        }
      }, 

      {
        route_type = "llm/v1/chat"

        model = {
          provider = "llama2"
          options = {
            llama2_format = "openai"
            upstream_url = "http://httpbin"
          }
        }
      }    ]
  }

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

The following examples provide some typical configurations for enabling the ai-proxy-advanced plugin on a route.

Make the following request:

curl -X POST http://localhost:8001/routes/{routeName|Id}/plugins \
    --header "accept: application/json" \
    --header "Content-Type: application/json" \
    --data '
    {
  "name": "ai-proxy-advanced",
  "config": {
    "targets": [
      {
        "route_type": "llm/v1/chat",
        "auth": {
          "header_name": "Authorization",
          "header_value": "Bearer token"
        },
        "model": {
          "provider": "openai"
        }
      },
      {
        "route_type": "llm/v1/chat",
        "model": {
          "provider": "llama2",
          "options": {
            "llama2_format": "openai",
            "upstream_url": "http://httpbin"
          }
        }
      }
    ]
  }
}
    '

Replace ROUTE_NAME|ID with the id or name of the route that this plugin configuration will target.

Make the following request, substituting your own access token, region, control plane ID, and route ID:

curl -X POST \
https://{us|eu}.api.konghq.com/v2/control-planes/{controlPlaneId}/core-entities/routes/{routeId}/plugins \
    --header "accept: application/json" \
    --header "Content-Type: application/json" \
    --header "Authorization: Bearer TOKEN" \
    --data '{"name":"ai-proxy-advanced","config":{"targets":[{"route_type":"llm/v1/chat","auth":{"header_name":"Authorization","header_value":"Bearer token"},"model":{"provider":"openai"}},{"route_type":"llm/v1/chat","model":{"provider":"llama2","options":{"llama2_format":"openai","upstream_url":"http://httpbin"}}}]}}'

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

First, create a KongPlugin resource:

echo "
apiVersion: configuration.konghq.com/v1
kind: KongPlugin
metadata:
  name: ai-proxy-advanced-example
plugin: ai-proxy-advanced
config:
  targets:
  - route_type: llm/v1/chat
    auth:
      header_name: Authorization
      header_value: Bearer token
    model:
      provider: openai
  - route_type: llm/v1/chat
    model:
      provider: llama2
      options:
        llama2_format: openai
        upstream_url: http://httpbin
" | kubectl apply -f -

Next, apply the KongPlugin resource to an ingress by annotating the ingress as follows:

kubectl annotate ingress INGRESS_NAME konghq.com/plugins=ai-proxy-advanced-example

Replace INGRESS_NAME with the name of the ingress that this plugin configuration will target. You can see your available ingresses by running kubectl get ingress.

Note: The KongPlugin resource only needs to be defined once and can be applied to any service, consumer, or route in the namespace. If you want the plugin to be available cluster-wide, create the resource as a KongClusterPlugin instead of KongPlugin.

Add this section to your declarative configuration file:

plugins:
- name: ai-proxy-advanced
  route: ROUTE_NAME|ID
  config:
    targets:
    - route_type: llm/v1/chat
      auth:
        header_name: Authorization
        header_value: Bearer token
      model:
        provider: openai
    - route_type: llm/v1/chat
      model:
        provider: llama2
        options:
          llama2_format: openai
          upstream_url: http://httpbin

Replace ROUTE_NAME|ID with the id or name of the route that this plugin configuration will target.

Prerequisite: Configure your Personal Access Token 
terraform {
  required_providers {
    konnect = {
      source  = "kong/konnect"
    }
  }
}

provider "konnect" {
  personal_access_token = "kpat_YOUR_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_proxy_advanced" "my_ai_proxy_advanced" {
  enabled = true

  config = {
    targets = [
      {
        route_type = "llm/v1/chat"

        auth = {
          header_name = "Authorization"
          header_value = "Bearer token"
        }

        model = {
          provider = "openai"
        }
      }, 

      {
        route_type = "llm/v1/chat"

        model = {
          provider = "llama2"
          options = {
            llama2_format = "openai"
            upstream_url = "http://httpbin"
          }
        }
      }    ]
  }

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

The following examples provide some typical configurations for enabling the ai-proxy-advanced plugin on a consumer.

Make the following request:

curl -X POST http://localhost:8001/consumers/{consumerName|Id}/plugins \
    --header "accept: application/json" \
    --header "Content-Type: application/json" \
    --data '
    {
  "name": "ai-proxy-advanced",
  "config": {
    "targets": [
      {
        "route_type": "llm/v1/chat",
        "auth": {
          "header_name": "Authorization",
          "header_value": "Bearer token"
        },
        "model": {
          "provider": "openai"
        }
      },
      {
        "route_type": "llm/v1/chat",
        "model": {
          "provider": "llama2",
          "options": {
            "llama2_format": "openai",
            "upstream_url": "http://httpbin"
          }
        }
      }
    ]
  }
}
    '

Replace CONSUMER_NAME|ID with the id or name of the consumer that this plugin configuration will target.

Make the following request, substituting your own access token, region, control plane ID, and consumer ID:

curl -X POST \
https://{us|eu}.api.konghq.com/v2/control-planes/{controlPlaneId}/core-entities/consumers/{consumerId}/plugins \
    --header "accept: application/json" \
    --header "Content-Type: application/json" \
    --header "Authorization: Bearer TOKEN" \
    --data '{"name":"ai-proxy-advanced","config":{"targets":[{"route_type":"llm/v1/chat","auth":{"header_name":"Authorization","header_value":"Bearer token"},"model":{"provider":"openai"}},{"route_type":"llm/v1/chat","model":{"provider":"llama2","options":{"llama2_format":"openai","upstream_url":"http://httpbin"}}}]}}'

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

First, create a KongPlugin resource:

echo "
apiVersion: configuration.konghq.com/v1
kind: KongPlugin
metadata:
  name: ai-proxy-advanced-example
plugin: ai-proxy-advanced
config:
  targets:
  - route_type: llm/v1/chat
    auth:
      header_name: Authorization
      header_value: Bearer token
    model:
      provider: openai
  - route_type: llm/v1/chat
    model:
      provider: llama2
      options:
        llama2_format: openai
        upstream_url: http://httpbin
" | kubectl apply -f -

Next, apply the KongPlugin resource to an ingress by annotating the KongConsumer object as follows:

kubectl annotate KongConsumer CONSUMER_NAME konghq.com/plugins=ai-proxy-advanced-example

Replace CONSUMER_NAME with the name of the consumer that this plugin configuration will target. You can see your available consumers by running kubectl get KongConsumer.

To learn more about KongConsumer objects, see Provisioning Consumers and Credentials.

Note: The KongPlugin resource only needs to be defined once and can be applied to any service, consumer, or route in the namespace. If you want the plugin to be available cluster-wide, create the resource as a KongClusterPlugin instead of KongPlugin.

Add this section to your declarative configuration file:

plugins:
- name: ai-proxy-advanced
  consumer: CONSUMER_NAME|ID
  config:
    targets:
    - route_type: llm/v1/chat
      auth:
        header_name: Authorization
        header_value: Bearer token
      model:
        provider: openai
    - route_type: llm/v1/chat
      model:
        provider: llama2
        options:
          llama2_format: openai
          upstream_url: http://httpbin

Replace CONSUMER_NAME|ID with the id or name of the consumer that this plugin configuration will target.

Prerequisite: Configure your Personal Access Token 
terraform {
  required_providers {
    konnect = {
      source  = "kong/konnect"
    }
  }
}

provider "konnect" {
  personal_access_token = "kpat_YOUR_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_proxy_advanced" "my_ai_proxy_advanced" {
  enabled = true

  config = {
    targets = [
      {
        route_type = "llm/v1/chat"

        auth = {
          header_name = "Authorization"
          header_value = "Bearer token"
        }

        model = {
          provider = "openai"
        }
      }, 

      {
        route_type = "llm/v1/chat"

        model = {
          provider = "llama2"
          options = {
            llama2_format = "openai"
            upstream_url = "http://httpbin"
          }
        }
      }    ]
  }

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

The following examples provide some typical configurations for enabling the ai-proxy-advanced plugin on a consumer group.

Make the following request:

curl -X POST http://localhost:8001/consumer_groups/{consumerGroupName|Id}/plugins \
    --header "accept: application/json" \
    --header "Content-Type: application/json" \
    --data '
    {
  "name": "ai-proxy-advanced",
  "config": {
    "targets": [
      {
        "route_type": "llm/v1/chat",
        "auth": {
          "header_name": "Authorization",
          "header_value": "Bearer token"
        },
        "model": {
          "provider": "openai"
        }
      },
      {
        "route_type": "llm/v1/chat",
        "model": {
          "provider": "llama2",
          "options": {
            "llama2_format": "openai",
            "upstream_url": "http://httpbin"
          }
        }
      }
    ]
  }
}
    '

Replace CONSUMER_GROUP_NAME|ID with the id or name of the consumer group that this plugin configuration will target.

Make the following request, substituting your own access token, region, control plane ID, and consumer group ID:

curl -X POST \
https://{us|eu}.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 TOKEN" \
    --data '{"name":"ai-proxy-advanced","config":{"targets":[{"route_type":"llm/v1/chat","auth":{"header_name":"Authorization","header_value":"Bearer token"},"model":{"provider":"openai"}},{"route_type":"llm/v1/chat","model":{"provider":"llama2","options":{"llama2_format":"openai","upstream_url":"http://httpbin"}}}]}}'

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

First, create a KongPlugin resource:

echo "
apiVersion: configuration.konghq.com/v1
kind: KongPlugin
metadata:
  name: ai-proxy-advanced-example
plugin: ai-proxy-advanced
config:
  targets:
  - route_type: llm/v1/chat
    auth:
      header_name: Authorization
      header_value: Bearer token
    model:
      provider: openai
  - route_type: llm/v1/chat
    model:
      provider: llama2
      options:
        llama2_format: openai
        upstream_url: http://httpbin
" | kubectl apply -f -

Next, apply the KongPlugin resource to an ingress by annotating the KongConsumerGroup object as follows:

kubectl annotate KongConsumerGroup CONSUMER_GROUP_NAME konghq.com/plugins=ai-proxy-advanced-example

Replace CONSUMER_GROUP_NAME with the name of the consumer group that this plugin configuration will target. You can see your available consumer groups by running kubectl get KongConsumerGroup.

Note: The KongPlugin resource only needs to be defined once and can be applied to any service, consumer, consumer group, or route in the namespace. If you want the plugin to be available cluster-wide, create the resource as a KongClusterPlugin instead of KongPlugin.

Add this section to your declarative configuration file:

plugins:
- name: ai-proxy-advanced
  consumer_group: CONSUMER_GROUP_NAME|ID
  config:
    targets:
    - route_type: llm/v1/chat
      auth:
        header_name: Authorization
        header_value: Bearer token
      model:
        provider: openai
    - route_type: llm/v1/chat
      model:
        provider: llama2
        options:
          llama2_format: openai
          upstream_url: http://httpbin

Replace CONSUMER_GROUP_NAME|ID with the id or name of the consumer group that this plugin configuration will target.

Prerequisite: Configure your Personal Access Token 
terraform {
  required_providers {
    konnect = {
      source  = "kong/konnect"
    }
  }
}

provider "konnect" {
  personal_access_token = "kpat_YOUR_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_proxy_advanced" "my_ai_proxy_advanced" {
  enabled = true

  config = {
    targets = [
      {
        route_type = "llm/v1/chat"

        auth = {
          header_name = "Authorization"
          header_value = "Bearer token"
        }

        model = {
          provider = "openai"
        }
      }, 

      {
        route_type = "llm/v1/chat"

        model = {
          provider = "llama2"
          options = {
            llama2_format = "openai"
            upstream_url = "http://httpbin"
          }
        }
      }    ]
  }

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

A plugin which is not associated to any service, route, consumer, or consumer group is considered global, and will be run on every request.

  • In self-managed Kong Gateway Enterprise, the plugin applies to every entity in a given workspace.
  • In self-managed Kong Gateway (OSS), the plugin applies to your entire environment.
  • In Konnect, the plugin applies to every entity in a given control plane.

Read the Plugin Reference and the Plugin Precedence sections for more information.

The following examples provide some typical configurations for enabling the AI Proxy Advanced plugin globally.

Make the following request:

curl -X POST http://localhost:8001/plugins/ \
    --header "accept: application/json" \
    --header "Content-Type: application/json" \
    --data '
    {
  "name": "ai-proxy-advanced",
  "config": {
    "targets": [
      {
        "route_type": "llm/v1/chat",
        "auth": {
          "header_name": "Authorization",
          "header_value": "Bearer token"
        },
        "model": {
          "provider": "openai"
        }
      },
      {
        "route_type": "llm/v1/chat",
        "model": {
          "provider": "llama2",
          "options": {
            "llama2_format": "openai",
            "upstream_url": "http://httpbin"
          }
        }
      }
    ]
  }
}
    '

Make the following request, substituting your own access token, region, and control plane ID:

curl -X POST \
https://{us|eu}.api.konghq.com/v2/control-planes/{controlPlaneId}/core-entities/plugins/ \
    --header "accept: application/json" \
    --header "Content-Type: application/json" \
    --header "Authorization: Bearer TOKEN" \
    --data '{"name":"ai-proxy-advanced","config":{"targets":[{"route_type":"llm/v1/chat","auth":{"header_name":"Authorization","header_value":"Bearer token"},"model":{"provider":"openai"}},{"route_type":"llm/v1/chat","model":{"provider":"llama2","options":{"llama2_format":"openai","upstream_url":"http://httpbin"}}}]}}'

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

Create a KongClusterPlugin resource and label it as global:

apiVersion: configuration.konghq.com/v1
kind: KongClusterPlugin
metadata:
  name: <global-ai-proxy-advanced>
  annotations:
    kubernetes.io/ingress.class: kong
  labels:
    global: "true"
config:
  targets:
  - route_type: llm/v1/chat
    auth:
      header_name: Authorization
      header_value: Bearer token
    model:
      provider: openai
  - route_type: llm/v1/chat
    model:
      provider: llama2
      options:
        llama2_format: openai
        upstream_url: http://httpbin
plugin: ai-proxy-advanced

Add a plugins entry in the declarative configuration file:

plugins:
- name: ai-proxy-advanced
  config:
    targets:
    - route_type: llm/v1/chat
      auth:
        header_name: Authorization
        header_value: Bearer token
      model:
        provider: openai
    - route_type: llm/v1/chat
      model:
        provider: llama2
        options:
          llama2_format: openai
          upstream_url: http://httpbin
Prerequisite: Configure your Personal Access Token 
terraform {
  required_providers {
    konnect = {
      source  = "kong/konnect"
    }
  }
}

provider "konnect" {
  personal_access_token = "kpat_YOUR_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_proxy_advanced" "my_ai_proxy_advanced" {
  enabled = true

  config = {
    targets = [
      {
        route_type = "llm/v1/chat"

        auth = {
          header_name = "Authorization"
          header_value = "Bearer token"
        }

        model = {
          provider = "openai"
        }
      }, 

      {
        route_type = "llm/v1/chat"

        model = {
          provider = "llama2"
          options = {
            llama2_format = "openai"
            upstream_url = "http://httpbin"
          }
        }
      }    ]
  }

  control_plane_id = konnect_gateway_control_plane.my_konnect_cp.id
}