AI Proxy Advanced: Batches route with Azure OpenAI Service - Plugin

Batches route with Azure OpenAI Service

Configure a batch route using Azure OpenAI Service.

To connect to Azure AI, you’ll need three values from your Azure OpenAI resource:

Make sure to use a globalbatch or datazonebatch deployment for files and batch operations. Standard deployments (GlobalStandard) cannot process batch and file operations.

Deployment ID — The unique name of your deployed model.
- In the Azure AI Foundry Portal sidebar, select a resource and go to: Shared Resources > Deployments > Model deployments, then click the deployment name.
- You can also see the deployment ID in the Azure OpenAI URL when calling the API, for example: https://{AZURE_INSTANCE_NAME}.openai.azure.com/openai/deployments/{AZURE_DEPLOYMENT_ID}/...
Instance name — The name of your Azure OpenAI resource.
- This is the prefix in your API endpoint URL, for example: https://{AZURE_INSTANCE_NAME}.openai.azure.com
API Key — The key used to authenticate requests to your Azure OpenAI deployment in Azure AI Foundry.
- In the Azure AI Foundry Portal sidebar, select a resource and go to: Shared Resources > Deployments > Model deployments, then click the deployment name.
- The API key is visible in the Endpoint tile.

Check the Send batch requests to Azure OpenAI LLMs tutorial for a step-by-step walkthrough.

Environment variables

AZURE_OPENAI_API_KEY
AZURE_INSTANCE_NAME
AZURE_DEPLOYMENT_ID

Set up the plugin

Add this section to your kong.yaml configuration file:

kong.yaml

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_format_version: "3.0"
plugins:
  - name: ai-proxy-advanced
    config:
      model_name_header: false
      targets:
      - route_type: llm/v1/batches
        auth:
          header_name: Authorization
          header_value: Bearer ${{ env "DECK_AZURE_OPENAI_API_KEY" }}
        model:
          provider: azure
          options:
            azure_api_version: 2025-01-01-preview
            azure_instance: ${{ env "DECK_AZURE_INSTANCE_NAME" }}
            azure_deployment_id: ${{ env "DECK_AZURE_DEPLOYMENT_ID" }}

Make the following request:

curl -i -X POST http://localhost:8001/plugins/ \
    --header "Accept: application/json" \
    --header "Content-Type: application/json" \
    --data '
    {
      "name": "ai-proxy-advanced",
      "config": {
        "model_name_header": false,
        "targets": [
          {
            "route_type": "llm/v1/batches",
            "auth": {
              "header_name": "Authorization",
              "header_value": "Bearer '$AZURE_OPENAI_API_KEY'"
            },
            "model": {
              "provider": "azure",
              "options": {
                "azure_api_version": "2025-01-01-preview",
                "azure_instance": "'$AZURE_INSTANCE_NAME'",
                "azure_deployment_id": "'$AZURE_DEPLOYMENT_ID'"
              }
            }
          }
        ]
      },
      "tags": []
    }
    '

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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 $KONNECT_TOKEN" \
    --data '
    {
      "name": "ai-proxy-advanced",
      "config": {
        "model_name_header": false,
        "targets": [
          {
            "route_type": "llm/v1/batches",
            "auth": {
              "header_name": "Authorization",
              "header_value": "Bearer '$AZURE_OPENAI_API_KEY'"
            },
            "model": {
              "provider": "azure",
              "options": {
                "azure_api_version": "2025-01-01-preview",
                "azure_instance": "'$AZURE_INSTANCE_NAME'",
                "azure_deployment_id": "'$AZURE_DEPLOYMENT_ID'"
              }
            }
          }
        ]
      },
      "tags": []
    }
    '

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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.
controlPlaneId: The id of the control plane.

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-proxy-advanced
  namespace: kong
  annotations:
    kubernetes.io/ingress.class: kong
    konghq.com/tags: ''
  labels:
    global: 'true'
config:
  model_name_header: false
  targets:
  - route_type: llm/v1/batches
    auth:
      header_name: Authorization
      header_value: Bearer $AZURE_OPENAI_API_KEY
    model:
      provider: azure
      options:
        azure_api_version: 2025-01-01-preview
        azure_instance: '$AZURE_INSTANCE_NAME'
        azure_deployment_id: '$AZURE_DEPLOYMENT_ID'
plugin: ai-proxy-advanced
" | kubectl apply -f -

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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 to create a Konnect Gateway Plugin:

resource "konnect_gateway_plugin_ai_proxy_advanced" "my_ai_proxy_advanced" {
  enabled = true

  config = {
    model_name_header = false
    targets = [
      {
        route_type = "llm/v1/batches"

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

        model = {
          provider = "azure"

          options = {
            azure_api_version = "2025-01-01-preview"
            azure_instance = var.azure_instance_name
            azure_deployment_id = var.azure_deployment_id
          }
        }
      }    ]
  }
  tags = []

  control_plane_id = konnect_gateway_control_plane.my_konnect_cp.id
}

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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 "azure_deployment_id" {
  type = string
}

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Add this section to your kong.yaml configuration file:

kong.yaml

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_format_version: "3.0"
plugins:
  - name: ai-proxy-advanced
    service: serviceName|Id
    config:
      model_name_header: false
      targets:
      - route_type: llm/v1/batches
        auth:
          header_name: Authorization
          header_value: Bearer ${{ env "DECK_AZURE_OPENAI_API_KEY" }}
        model:
          provider: azure
          options:
            azure_api_version: 2025-01-01-preview
            azure_instance: ${{ env "DECK_AZURE_INSTANCE_NAME" }}
            azure_deployment_id: ${{ env "DECK_AZURE_DEPLOYMENT_ID" }}

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-proxy-advanced",
      "config": {
        "model_name_header": false,
        "targets": [
          {
            "route_type": "llm/v1/batches",
            "auth": {
              "header_name": "Authorization",
              "header_value": "Bearer '$AZURE_OPENAI_API_KEY'"
            },
            "model": {
              "provider": "azure",
              "options": {
                "azure_api_version": "2025-01-01-preview",
                "azure_instance": "'$AZURE_INSTANCE_NAME'",
                "azure_deployment_id": "'$AZURE_DEPLOYMENT_ID'"
              }
            }
          }
        ]
      },
      "tags": []
    }
    '

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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 $KONNECT_TOKEN" \
    --data '
    {
      "name": "ai-proxy-advanced",
      "config": {
        "model_name_header": false,
        "targets": [
          {
            "route_type": "llm/v1/batches",
            "auth": {
              "header_name": "Authorization",
              "header_value": "Bearer '$AZURE_OPENAI_API_KEY'"
            },
            "model": {
              "provider": "azure",
              "options": {
                "azure_api_version": "2025-01-01-preview",
                "azure_instance": "'$AZURE_INSTANCE_NAME'",
                "azure_deployment_id": "'$AZURE_DEPLOYMENT_ID'"
              }
            }
          }
        ]
      },
      "tags": []
    }
    '

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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.
controlPlaneId: The id of the control plane.
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-proxy-advanced
  namespace: kong
  annotations:
    kubernetes.io/ingress.class: kong
    konghq.com/tags: ''
config:
  model_name_header: false
  targets:
  - route_type: llm/v1/batches
    auth:
      header_name: Authorization
      header_value: Bearer $AZURE_OPENAI_API_KEY
    model:
      provider: azure
      options:
        azure_api_version: 2025-01-01-preview
        azure_instance: '$AZURE_INSTANCE_NAME'
        azure_deployment_id: '$AZURE_DEPLOYMENT_ID'
plugin: ai-proxy-advanced
" | kubectl apply -f -

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

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

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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 to create a Konnect Gateway Plugin:

resource "konnect_gateway_plugin_ai_proxy_advanced" "my_ai_proxy_advanced" {
  enabled = true

  config = {
    model_name_header = false
    targets = [
      {
        route_type = "llm/v1/batches"

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

        model = {
          provider = "azure"

          options = {
            azure_api_version = "2025-01-01-preview"
            azure_instance = var.azure_instance_name
            azure_deployment_id = var.azure_deployment_id
          }
        }
      }    ]
  }
  tags = []

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

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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 "azure_deployment_id" {
  type = string
}

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Add this section to your kong.yaml configuration file:

kong.yaml

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_format_version: "3.0"
plugins:
  - name: ai-proxy-advanced
    route: routeName|Id
    config:
      model_name_header: false
      targets:
      - route_type: llm/v1/batches
        auth:
          header_name: Authorization
          header_value: Bearer ${{ env "DECK_AZURE_OPENAI_API_KEY" }}
        model:
          provider: azure
          options:
            azure_api_version: 2025-01-01-preview
            azure_instance: ${{ env "DECK_AZURE_INSTANCE_NAME" }}
            azure_deployment_id: ${{ env "DECK_AZURE_DEPLOYMENT_ID" }}

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-proxy-advanced",
      "config": {
        "model_name_header": false,
        "targets": [
          {
            "route_type": "llm/v1/batches",
            "auth": {
              "header_name": "Authorization",
              "header_value": "Bearer '$AZURE_OPENAI_API_KEY'"
            },
            "model": {
              "provider": "azure",
              "options": {
                "azure_api_version": "2025-01-01-preview",
                "azure_instance": "'$AZURE_INSTANCE_NAME'",
                "azure_deployment_id": "'$AZURE_DEPLOYMENT_ID'"
              }
            }
          }
        ]
      },
      "tags": []
    }
    '

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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 $KONNECT_TOKEN" \
    --data '
    {
      "name": "ai-proxy-advanced",
      "config": {
        "model_name_header": false,
        "targets": [
          {
            "route_type": "llm/v1/batches",
            "auth": {
              "header_name": "Authorization",
              "header_value": "Bearer '$AZURE_OPENAI_API_KEY'"
            },
            "model": {
              "provider": "azure",
              "options": {
                "azure_api_version": "2025-01-01-preview",
                "azure_instance": "'$AZURE_INSTANCE_NAME'",
                "azure_deployment_id": "'$AZURE_DEPLOYMENT_ID'"
              }
            }
          }
        ]
      },
      "tags": []
    }
    '

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.
controlPlaneId: The id of the control plane.
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-proxy-advanced
  namespace: kong
  annotations:
    kubernetes.io/ingress.class: kong
    konghq.com/tags: ''
config:
  model_name_header: false
  targets:
  - route_type: llm/v1/batches
    auth:
      header_name: Authorization
      header_value: Bearer $AZURE_OPENAI_API_KEY
    model:
      provider: azure
      options:
        azure_api_version: 2025-01-01-preview
        azure_instance: '$AZURE_INSTANCE_NAME'
        azure_deployment_id: '$AZURE_DEPLOYMENT_ID'
plugin: ai-proxy-advanced
" | kubectl apply -f -

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

kubectl annotate -n kong httproute  konghq.com/plugins=ai-proxy-advanced

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kubectl annotate -n kong ingress  konghq.com/plugins=ai-proxy-advanced

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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 to create a Konnect Gateway Plugin:

resource "konnect_gateway_plugin_ai_proxy_advanced" "my_ai_proxy_advanced" {
  enabled = true

  config = {
    model_name_header = false
    targets = [
      {
        route_type = "llm/v1/batches"

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

        model = {
          provider = "azure"

          options = {
            azure_api_version = "2025-01-01-preview"
            azure_instance = var.azure_instance_name
            azure_deployment_id = var.azure_deployment_id
          }
        }
      }    ]
  }
  tags = []

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

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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 "azure_deployment_id" {
  type = string
}

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Add this section to your kong.yaml configuration file:

kong.yaml

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_format_version: "3.0"
plugins:
  - name: ai-proxy-advanced
    consumer: consumerName|Id
    config:
      model_name_header: false
      targets:
      - route_type: llm/v1/batches
        auth:
          header_name: Authorization
          header_value: Bearer ${{ env "DECK_AZURE_OPENAI_API_KEY" }}
        model:
          provider: azure
          options:
            azure_api_version: 2025-01-01-preview
            azure_instance: ${{ env "DECK_AZURE_INSTANCE_NAME" }}
            azure_deployment_id: ${{ env "DECK_AZURE_DEPLOYMENT_ID" }}

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-proxy-advanced",
      "config": {
        "model_name_header": false,
        "targets": [
          {
            "route_type": "llm/v1/batches",
            "auth": {
              "header_name": "Authorization",
              "header_value": "Bearer '$AZURE_OPENAI_API_KEY'"
            },
            "model": {
              "provider": "azure",
              "options": {
                "azure_api_version": "2025-01-01-preview",
                "azure_instance": "'$AZURE_INSTANCE_NAME'",
                "azure_deployment_id": "'$AZURE_DEPLOYMENT_ID'"
              }
            }
          }
        ]
      },
      "tags": []
    }
    '

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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 $KONNECT_TOKEN" \
    --data '
    {
      "name": "ai-proxy-advanced",
      "config": {
        "model_name_header": false,
        "targets": [
          {
            "route_type": "llm/v1/batches",
            "auth": {
              "header_name": "Authorization",
              "header_value": "Bearer '$AZURE_OPENAI_API_KEY'"
            },
            "model": {
              "provider": "azure",
              "options": {
                "azure_api_version": "2025-01-01-preview",
                "azure_instance": "'$AZURE_INSTANCE_NAME'",
                "azure_deployment_id": "'$AZURE_DEPLOYMENT_ID'"
              }
            }
          }
        ]
      },
      "tags": []
    }
    '

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.
controlPlaneId: The id of the control plane.
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-proxy-advanced
  namespace: kong
  annotations:
    kubernetes.io/ingress.class: kong
    konghq.com/tags: ''
config:
  model_name_header: false
  targets:
  - route_type: llm/v1/batches
    auth:
      header_name: Authorization
      header_value: Bearer $AZURE_OPENAI_API_KEY
    model:
      provider: azure
      options:
        azure_api_version: 2025-01-01-preview
        azure_instance: '$AZURE_INSTANCE_NAME'
        azure_deployment_id: '$AZURE_DEPLOYMENT_ID'
plugin: ai-proxy-advanced
" | kubectl apply -f -

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

kubectl annotate -n kong  CONSUMER_NAME konghq.com/plugins=ai-proxy-advanced

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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 to create a Konnect Gateway Plugin:

resource "konnect_gateway_plugin_ai_proxy_advanced" "my_ai_proxy_advanced" {
  enabled = true

  config = {
    model_name_header = false
    targets = [
      {
        route_type = "llm/v1/batches"

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

        model = {
          provider = "azure"

          options = {
            azure_api_version = "2025-01-01-preview"
            azure_instance = var.azure_instance_name
            azure_deployment_id = var.azure_deployment_id
          }
        }
      }    ]
  }
  tags = []

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

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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 "azure_deployment_id" {
  type = string
}

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Add this section to your kong.yaml configuration file:

kong.yaml

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_format_version: "3.0"
plugins:
  - name: ai-proxy-advanced
    consumer_group: consumerGroupName|Id
    config:
      model_name_header: false
      targets:
      - route_type: llm/v1/batches
        auth:
          header_name: Authorization
          header_value: Bearer ${{ env "DECK_AZURE_OPENAI_API_KEY" }}
        model:
          provider: azure
          options:
            azure_api_version: 2025-01-01-preview
            azure_instance: ${{ env "DECK_AZURE_INSTANCE_NAME" }}
            azure_deployment_id: ${{ env "DECK_AZURE_DEPLOYMENT_ID" }}

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-proxy-advanced",
      "config": {
        "model_name_header": false,
        "targets": [
          {
            "route_type": "llm/v1/batches",
            "auth": {
              "header_name": "Authorization",
              "header_value": "Bearer '$AZURE_OPENAI_API_KEY'"
            },
            "model": {
              "provider": "azure",
              "options": {
                "azure_api_version": "2025-01-01-preview",
                "azure_instance": "'$AZURE_INSTANCE_NAME'",
                "azure_deployment_id": "'$AZURE_DEPLOYMENT_ID'"
              }
            }
          }
        ]
      },
      "tags": []
    }
    '

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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 $KONNECT_TOKEN" \
    --data '
    {
      "name": "ai-proxy-advanced",
      "config": {
        "model_name_header": false,
        "targets": [
          {
            "route_type": "llm/v1/batches",
            "auth": {
              "header_name": "Authorization",
              "header_value": "Bearer '$AZURE_OPENAI_API_KEY'"
            },
            "model": {
              "provider": "azure",
              "options": {
                "azure_api_version": "2025-01-01-preview",
                "azure_instance": "'$AZURE_INSTANCE_NAME'",
                "azure_deployment_id": "'$AZURE_DEPLOYMENT_ID'"
              }
            }
          }
        ]
      },
      "tags": []
    }
    '

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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.
controlPlaneId: The id of the control plane.
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-proxy-advanced
  namespace: kong
  annotations:
    kubernetes.io/ingress.class: kong
    konghq.com/tags: ''
config:
  model_name_header: false
  targets:
  - route_type: llm/v1/batches
    auth:
      header_name: Authorization
      header_value: Bearer $AZURE_OPENAI_API_KEY
    model:
      provider: azure
      options:
        azure_api_version: 2025-01-01-preview
        azure_instance: '$AZURE_INSTANCE_NAME'
        azure_deployment_id: '$AZURE_DEPLOYMENT_ID'
plugin: ai-proxy-advanced
" | kubectl apply -f -

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

kubectl annotate -n kong  CONSUMERGROUP_NAME konghq.com/plugins=ai-proxy-advanced

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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 to create a Konnect Gateway Plugin:

resource "konnect_gateway_plugin_ai_proxy_advanced" "my_ai_proxy_advanced" {
  enabled = true

  config = {
    model_name_header = false
    targets = [
      {
        route_type = "llm/v1/batches"

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

        model = {
          provider = "azure"

          options = {
            azure_api_version = "2025-01-01-preview"
            azure_instance = var.azure_instance_name
            azure_deployment_id = var.azure_deployment_id
          }
        }
      }    ]
  }
  tags = []

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

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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 "azure_deployment_id" {
  type = string
}

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AI Proxy Advanced

Batches route with Azure OpenAI Service

Environment variables

Set up the plugin

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