AI Proxy: Native Hugging Face API route - Plugin

Native Hugging Face API routev3.6+

Configure a route that uses native Hugging Face APIs with the Hugging Face SDK. This example uses the HuggingFaceTB/SmolVLM-Base model.

Supported native Hugging Face APIs include:

/generate
/generate_stream

Set llm_format: huggingface to enable compatibility with these APIs. Use default values for genai_category and route_type parameters (text/generation and llm/v1/chat).

Prerequisites

Hugging Face account

Environment variables

HUGGINGFACE_TOKEN: The token to use to connect to Hugging Face.

Set up the plugin

Add this section to your declarative configuration file:

_format_version: "3.0"
plugins:
  - name: ai-proxy
    config:
      route_type: llm/v1/chat
      genai_category: text/generation
      llm_format: huggingface
      auth:
        header_name: Authorization
        header_value: Bearer ${{ env "DECK_HUGGINGFACE_TOKEN" }}
      model:
        provider: huggingface
        name: HuggingFaceTB/SmolVLM-Base

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",
      "config": {
        "route_type": "llm/v1/chat",
        "genai_category": "text/generation",
        "llm_format": "huggingface",
        "auth": {
          "header_name": "Authorization",
          "header_value": "Bearer '$HUGGINGFACE_TOKEN'"
        },
        "model": {
          "provider": "huggingface",
          "name": "HuggingFaceTB/SmolVLM-Base"
        }
      }
    }
    '

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 $KONNECT_TOKEN" \
    --data '
    {
      "name": "ai-proxy",
      "config": {
        "route_type": "llm/v1/chat",
        "genai_category": "text/generation",
        "llm_format": "huggingface",
        "auth": {
          "header_name": "Authorization",
          "header_value": "Bearer '$HUGGINGFACE_TOKEN'"
        },
        "model": {
          "provider": "huggingface",
          "name": "HuggingFaceTB/SmolVLM-Base"
        }
      }
    }
    '

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-proxy
  namespace: kong
  annotations:
    kubernetes.io/ingress.class: kong
  labels:
    global: 'true'
config:
  route_type: llm/v1/chat
  genai_category: text/generation
  llm_format: huggingface
  auth:
    header_name: Authorization
    header_value: Bearer $HUGGINGFACE_TOKEN
  model:
    provider: huggingface
    name: HuggingFaceTB/SmolVLM-Base
plugin: ai-proxy
" | 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_proxy" "my_ai_proxy" {
  enabled = true

  config = {
    route_type = "llm/v1/chat"
    genai_category = "text/generation"
    llm_format = "huggingface"

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

    model = {
      provider = "huggingface"
      name = "HuggingFaceTB/SmolVLM-Base"
    }
  }

  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 "huggingface_token" {
  type = string
}

Add this section to your declarative configuration file:

_format_version: "3.0"
plugins:
  - name: ai-proxy
    service: serviceName|Id
    config:
      route_type: llm/v1/chat
      genai_category: text/generation
      llm_format: huggingface
      auth:
        header_name: Authorization
        header_value: Bearer ${{ env "DECK_HUGGINGFACE_TOKEN" }}
      model:
        provider: huggingface
        name: HuggingFaceTB/SmolVLM-Base

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",
      "config": {
        "route_type": "llm/v1/chat",
        "genai_category": "text/generation",
        "llm_format": "huggingface",
        "auth": {
          "header_name": "Authorization",
          "header_value": "Bearer '$HUGGINGFACE_TOKEN'"
        },
        "model": {
          "provider": "huggingface",
          "name": "HuggingFaceTB/SmolVLM-Base"
        }
      }
    }
    '

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 $KONNECT_TOKEN" \
    --data '
    {
      "name": "ai-proxy",
      "config": {
        "route_type": "llm/v1/chat",
        "genai_category": "text/generation",
        "llm_format": "huggingface",
        "auth": {
          "header_name": "Authorization",
          "header_value": "Bearer '$HUGGINGFACE_TOKEN'"
        },
        "model": {
          "provider": "huggingface",
          "name": "HuggingFaceTB/SmolVLM-Base"
        }
      }
    }
    '

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-proxy
  namespace: kong
  annotations:
    kubernetes.io/ingress.class: kong
config:
  route_type: llm/v1/chat
  genai_category: text/generation
  llm_format: huggingface
  auth:
    header_name: Authorization
    header_value: Bearer $HUGGINGFACE_TOKEN
  model:
    provider: huggingface
    name: HuggingFaceTB/SmolVLM-Base
plugin: ai-proxy
" | kubectl apply -f -

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

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

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_proxy" "my_ai_proxy" {
  enabled = true

  config = {
    route_type = "llm/v1/chat"
    genai_category = "text/generation"
    llm_format = "huggingface"

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

    model = {
      provider = "huggingface"
      name = "HuggingFaceTB/SmolVLM-Base"
    }
  }

  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 "huggingface_token" {
  type = string
}

Add this section to your declarative configuration file:

_format_version: "3.0"
plugins:
  - name: ai-proxy
    route: routeName|Id
    config:
      route_type: llm/v1/chat
      genai_category: text/generation
      llm_format: huggingface
      auth:
        header_name: Authorization
        header_value: Bearer ${{ env "DECK_HUGGINGFACE_TOKEN" }}
      model:
        provider: huggingface
        name: HuggingFaceTB/SmolVLM-Base

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",
      "config": {
        "route_type": "llm/v1/chat",
        "genai_category": "text/generation",
        "llm_format": "huggingface",
        "auth": {
          "header_name": "Authorization",
          "header_value": "Bearer '$HUGGINGFACE_TOKEN'"
        },
        "model": {
          "provider": "huggingface",
          "name": "HuggingFaceTB/SmolVLM-Base"
        }
      }
    }
    '

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 $KONNECT_TOKEN" \
    --data '
    {
      "name": "ai-proxy",
      "config": {
        "route_type": "llm/v1/chat",
        "genai_category": "text/generation",
        "llm_format": "huggingface",
        "auth": {
          "header_name": "Authorization",
          "header_value": "Bearer '$HUGGINGFACE_TOKEN'"
        },
        "model": {
          "provider": "huggingface",
          "name": "HuggingFaceTB/SmolVLM-Base"
        }
      }
    }
    '

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-proxy
  namespace: kong
  annotations:
    kubernetes.io/ingress.class: kong
config:
  route_type: llm/v1/chat
  genai_category: text/generation
  llm_format: huggingface
  auth:
    header_name: Authorization
    header_value: Bearer $HUGGINGFACE_TOKEN
  model:
    provider: huggingface
    name: HuggingFaceTB/SmolVLM-Base
plugin: ai-proxy
" | kubectl apply -f -

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

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

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

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_proxy" "my_ai_proxy" {
  enabled = true

  config = {
    route_type = "llm/v1/chat"
    genai_category = "text/generation"
    llm_format = "huggingface"

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

    model = {
      provider = "huggingface"
      name = "HuggingFaceTB/SmolVLM-Base"
    }
  }

  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 "huggingface_token" {
  type = string
}

Add this section to your declarative configuration file:

_format_version: "3.0"
plugins:
  - name: ai-proxy
    consumer: consumerName|Id
    config:
      route_type: llm/v1/chat
      genai_category: text/generation
      llm_format: huggingface
      auth:
        header_name: Authorization
        header_value: Bearer ${{ env "DECK_HUGGINGFACE_TOKEN" }}
      model:
        provider: huggingface
        name: HuggingFaceTB/SmolVLM-Base

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",
      "config": {
        "route_type": "llm/v1/chat",
        "genai_category": "text/generation",
        "llm_format": "huggingface",
        "auth": {
          "header_name": "Authorization",
          "header_value": "Bearer '$HUGGINGFACE_TOKEN'"
        },
        "model": {
          "provider": "huggingface",
          "name": "HuggingFaceTB/SmolVLM-Base"
        }
      }
    }
    '

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 $KONNECT_TOKEN" \
    --data '
    {
      "name": "ai-proxy",
      "config": {
        "route_type": "llm/v1/chat",
        "genai_category": "text/generation",
        "llm_format": "huggingface",
        "auth": {
          "header_name": "Authorization",
          "header_value": "Bearer '$HUGGINGFACE_TOKEN'"
        },
        "model": {
          "provider": "huggingface",
          "name": "HuggingFaceTB/SmolVLM-Base"
        }
      }
    }
    '

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-proxy
  namespace: kong
  annotations:
    kubernetes.io/ingress.class: kong
config:
  route_type: llm/v1/chat
  genai_category: text/generation
  llm_format: huggingface
  auth:
    header_name: Authorization
    header_value: Bearer $HUGGINGFACE_TOKEN
  model:
    provider: huggingface
    name: HuggingFaceTB/SmolVLM-Base
plugin: ai-proxy
" | kubectl apply -f -

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

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

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_proxy" "my_ai_proxy" {
  enabled = true

  config = {
    route_type = "llm/v1/chat"
    genai_category = "text/generation"
    llm_format = "huggingface"

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

    model = {
      provider = "huggingface"
      name = "HuggingFaceTB/SmolVLM-Base"
    }
  }

  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 "huggingface_token" {
  type = string
}

Add this section to your declarative configuration file:

_format_version: "3.0"
plugins:
  - name: ai-proxy
    consumer_group: consumerGroupName|Id
    config:
      route_type: llm/v1/chat
      genai_category: text/generation
      llm_format: huggingface
      auth:
        header_name: Authorization
        header_value: Bearer ${{ env "DECK_HUGGINGFACE_TOKEN" }}
      model:
        provider: huggingface
        name: HuggingFaceTB/SmolVLM-Base

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",
      "config": {
        "route_type": "llm/v1/chat",
        "genai_category": "text/generation",
        "llm_format": "huggingface",
        "auth": {
          "header_name": "Authorization",
          "header_value": "Bearer '$HUGGINGFACE_TOKEN'"
        },
        "model": {
          "provider": "huggingface",
          "name": "HuggingFaceTB/SmolVLM-Base"
        }
      }
    }
    '

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 $KONNECT_TOKEN" \
    --data '
    {
      "name": "ai-proxy",
      "config": {
        "route_type": "llm/v1/chat",
        "genai_category": "text/generation",
        "llm_format": "huggingface",
        "auth": {
          "header_name": "Authorization",
          "header_value": "Bearer '$HUGGINGFACE_TOKEN'"
        },
        "model": {
          "provider": "huggingface",
          "name": "HuggingFaceTB/SmolVLM-Base"
        }
      }
    }
    '

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-proxy
  namespace: kong
  annotations:
    kubernetes.io/ingress.class: kong
config:
  route_type: llm/v1/chat
  genai_category: text/generation
  llm_format: huggingface
  auth:
    header_name: Authorization
    header_value: Bearer $HUGGINGFACE_TOKEN
  model:
    provider: huggingface
    name: HuggingFaceTB/SmolVLM-Base
plugin: ai-proxy
" | kubectl apply -f -

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

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

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_proxy" "my_ai_proxy" {
  enabled = true

  config = {
    route_type = "llm/v1/chat"
    genai_category = "text/generation"
    llm_format = "huggingface"

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

    model = {
      provider = "huggingface"
      name = "HuggingFaceTB/SmolVLM-Base"
    }
  }

  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 "huggingface_token" {
  type = string
}

AI Proxy

Native Hugging Face API routev3.6+

Prerequisites

Environment variables

Set up the plugin

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