Native Amazon Bedrock API routev3.6+
Configure a route that uses native Amazon Bedrock APIs with the AWS SDK. This example uses the Meta Llama 3 70B Instruct model in the US East 1 AWS region.
Supported native Bedrock APIs include:
- /converse
- /converse-stream
- /retrieveAndGenerate
- /retrieveAndGenerateStream
- /rerank
Set llm_format: bedrock to enable compatibility with these APIs. Use default values for genai_category and route_type parameters (text/generation and llm/v1/chat).
Prerequisites
- AWS account with access to Bedrock
Environment variables
- 
    AWS_ACCESS_KEY_ID: The AWS access key ID to use to connect to Bedrock.
- 
    AWS_SECRET_ACCESS_KEY: The AWS secret access key to use to connect to Bedrock.
Add this section to your kong.yaml configuration file:
_format_version: "3.0"
plugins:
  - name: ai-proxy
    config:
      route_type: llm/v1/chat
      genai_category: text/generation
      llm_format: bedrock
      auth:
        allow_override: false
        aws_access_key_id: ${{ env "DECK_AWS_ACCESS_KEY_ID" }}
        aws_secret_access_key: ${{ env "DECK_AWS_SECRET_ACCESS_KEY" }}
      model:
        provider: bedrock
        name: meta.llama3-70b-instruct-v1:0
        options:
          bedrock:
            aws_region: us-east-1
Make the following request:
curl -i -X POST http://localhost:8001/plugins/ \
    --header "Accept: application/json" \
    --header "Content-Type: application/json" \
    --data '
    {
      "name": "ai-proxy",
      "config": {
        "route_type": "llm/v1/chat",
        "genai_category": "text/generation",
        "llm_format": "bedrock",
        "auth": {
          "allow_override": false,
          "aws_access_key_id": "'$AWS_ACCESS_KEY_ID'",
          "aws_secret_access_key": "'$AWS_SECRET_ACCESS_KEY'"
        },
        "model": {
          "provider": "bedrock",
          "name": "meta.llama3-70b-instruct-v1:0",
          "options": {
            "bedrock": {
              "aws_region": "us-east-1"
            }
          }
        }
      },
      "tags": []
    }
    '
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 $KONNECT_TOKEN" \
    --data '
    {
      "name": "ai-proxy",
      "config": {
        "route_type": "llm/v1/chat",
        "genai_category": "text/generation",
        "llm_format": "bedrock",
        "auth": {
          "allow_override": false,
          "aws_access_key_id": "'$AWS_ACCESS_KEY_ID'",
          "aws_secret_access_key": "'$AWS_SECRET_ACCESS_KEY'"
        },
        "model": {
          "provider": "bedrock",
          "name": "meta.llama3-70b-instruct-v1:0",
          "options": {
            "bedrock": {
              "aws_region": "us-east-1"
            }
          }
        }
      },
      "tags": []
    }
    '
Make sure to replace the following placeholders with your own values:
- 
    region: Geographic region where your Kong Konnect is hosted and operates.
- 
    controlPlaneId: Theidof the control plane.
- 
    KONNECT_TOKEN: Your Personal Access Token (PAT) associated with your Konnect account.
See the Konnect API reference to learn about region-specific URLs and personal access tokens.
echo "
apiVersion: configuration.konghq.com/v1
kind: KongClusterPlugin
metadata:
  name: ai-proxy
  namespace: kong
  annotations:
    kubernetes.io/ingress.class: kong
    konghq.com/tags: ''
  labels:
    global: 'true'
config:
  route_type: llm/v1/chat
  genai_category: text/generation
  llm_format: bedrock
  auth:
    allow_override: false
    aws_access_key_id: '$AWS_ACCESS_KEY_ID'
    aws_secret_access_key: '$AWS_SECRET_ACCESS_KEY'
  model:
    provider: bedrock
    name: meta.llama3-70b-instruct-v1:0
    options:
      bedrock:
        aws_region: us-east-1
plugin: ai-proxy
" | kubectl apply -f -
Prerequisite: Configure your Personal Access Token
terraform {
  required_providers {
    konnect = {
      source  = "kong/konnect"
    }
  }
}
provider "konnect" {
  personal_access_token = "$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 = "bedrock"
    auth = {
      allow_override = false
      aws_access_key_id = var.aws_access_key_id
      aws_secret_access_key = var.aws_secret_access_key
    }
    model = {
      provider = "bedrock"
      name = "meta.llama3-70b-instruct-v1:0"
      options = {
        bedrock = {
          aws_region = "us-east-1"
        }
      }
    }
  }
  tags = []
  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 "aws_secret_access_key" {
  type = string
}
Add this section to your kong.yaml 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: bedrock
      auth:
        allow_override: false
        aws_access_key_id: ${{ env "DECK_AWS_ACCESS_KEY_ID" }}
        aws_secret_access_key: ${{ env "DECK_AWS_SECRET_ACCESS_KEY" }}
      model:
        provider: bedrock
        name: meta.llama3-70b-instruct-v1:0
        options:
          bedrock:
            aws_region: us-east-1
Make sure to replace the following placeholders with your own values:
- 
serviceName|Id: Theidornameof the service the plugin configuration will target.
Make the following request:
curl -i -X POST http://localhost:8001/services/{serviceName|Id}/plugins/ \
    --header "Accept: application/json" \
    --header "Content-Type: application/json" \
    --data '
    {
      "name": "ai-proxy",
      "config": {
        "route_type": "llm/v1/chat",
        "genai_category": "text/generation",
        "llm_format": "bedrock",
        "auth": {
          "allow_override": false,
          "aws_access_key_id": "'$AWS_ACCESS_KEY_ID'",
          "aws_secret_access_key": "'$AWS_SECRET_ACCESS_KEY'"
        },
        "model": {
          "provider": "bedrock",
          "name": "meta.llama3-70b-instruct-v1:0",
          "options": {
            "bedrock": {
              "aws_region": "us-east-1"
            }
          }
        }
      },
      "tags": []
    }
    '
Make sure to replace the following placeholders with your own values:
- 
serviceName|Id: Theidornameof 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 $KONNECT_TOKEN" \
    --data '
    {
      "name": "ai-proxy",
      "config": {
        "route_type": "llm/v1/chat",
        "genai_category": "text/generation",
        "llm_format": "bedrock",
        "auth": {
          "allow_override": false,
          "aws_access_key_id": "'$AWS_ACCESS_KEY_ID'",
          "aws_secret_access_key": "'$AWS_SECRET_ACCESS_KEY'"
        },
        "model": {
          "provider": "bedrock",
          "name": "meta.llama3-70b-instruct-v1:0",
          "options": {
            "bedrock": {
              "aws_region": "us-east-1"
            }
          }
        }
      },
      "tags": []
    }
    '
Make sure to replace the following placeholders with your own values:
- 
    region: Geographic region where your Kong Konnect is hosted and operates.
- 
    controlPlaneId: Theidof the control plane.
- 
    KONNECT_TOKEN: Your Personal Access Token (PAT) associated with your Konnect account.
- 
    serviceId: Theidof the service the plugin configuration will target.
See the Konnect API reference to learn about region-specific URLs and personal access tokens.
echo "
apiVersion: configuration.konghq.com/v1
kind: KongPlugin
metadata:
  name: ai-proxy
  namespace: kong
  annotations:
    kubernetes.io/ingress.class: kong
    konghq.com/tags: ''
config:
  route_type: llm/v1/chat
  genai_category: text/generation
  llm_format: bedrock
  auth:
    allow_override: false
    aws_access_key_id: '$AWS_ACCESS_KEY_ID'
    aws_secret_access_key: '$AWS_SECRET_ACCESS_KEY'
  model:
    provider: bedrock
    name: meta.llama3-70b-instruct-v1:0
    options:
      bedrock:
        aws_region: us-east-1
plugin: ai-proxy
" | kubectl apply -f -
Next, apply the KongPlugin resource by annotating the service resource:
kubectl annotate -n kong service SERVICE_NAME konghq.com/plugins=ai-proxy
Prerequisite: Configure your Personal Access Token
terraform {
  required_providers {
    konnect = {
      source  = "kong/konnect"
    }
  }
}
provider "konnect" {
  personal_access_token = "$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 = "bedrock"
    auth = {
      allow_override = false
      aws_access_key_id = var.aws_access_key_id
      aws_secret_access_key = var.aws_secret_access_key
    }
    model = {
      provider = "bedrock"
      name = "meta.llama3-70b-instruct-v1:0"
      options = {
        bedrock = {
          aws_region = "us-east-1"
        }
      }
    }
  }
  tags = []
  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 "aws_secret_access_key" {
  type = string
}
Add this section to your kong.yaml 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: bedrock
      auth:
        allow_override: false
        aws_access_key_id: ${{ env "DECK_AWS_ACCESS_KEY_ID" }}
        aws_secret_access_key: ${{ env "DECK_AWS_SECRET_ACCESS_KEY" }}
      model:
        provider: bedrock
        name: meta.llama3-70b-instruct-v1:0
        options:
          bedrock:
            aws_region: us-east-1
Make sure to replace the following placeholders with your own values:
- 
routeName|Id: Theidornameof the route the plugin configuration will target.
Make the following request:
curl -i -X POST http://localhost:8001/routes/{routeName|Id}/plugins/ \
    --header "Accept: application/json" \
    --header "Content-Type: application/json" \
    --data '
    {
      "name": "ai-proxy",
      "config": {
        "route_type": "llm/v1/chat",
        "genai_category": "text/generation",
        "llm_format": "bedrock",
        "auth": {
          "allow_override": false,
          "aws_access_key_id": "'$AWS_ACCESS_KEY_ID'",
          "aws_secret_access_key": "'$AWS_SECRET_ACCESS_KEY'"
        },
        "model": {
          "provider": "bedrock",
          "name": "meta.llama3-70b-instruct-v1:0",
          "options": {
            "bedrock": {
              "aws_region": "us-east-1"
            }
          }
        }
      },
      "tags": []
    }
    '
Make sure to replace the following placeholders with your own values:
- 
routeName|Id: Theidornameof 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 $KONNECT_TOKEN" \
    --data '
    {
      "name": "ai-proxy",
      "config": {
        "route_type": "llm/v1/chat",
        "genai_category": "text/generation",
        "llm_format": "bedrock",
        "auth": {
          "allow_override": false,
          "aws_access_key_id": "'$AWS_ACCESS_KEY_ID'",
          "aws_secret_access_key": "'$AWS_SECRET_ACCESS_KEY'"
        },
        "model": {
          "provider": "bedrock",
          "name": "meta.llama3-70b-instruct-v1:0",
          "options": {
            "bedrock": {
              "aws_region": "us-east-1"
            }
          }
        }
      },
      "tags": []
    }
    '
Make sure to replace the following placeholders with your own values:
- 
    region: Geographic region where your Kong Konnect is hosted and operates.
- 
    controlPlaneId: Theidof the control plane.
- 
    KONNECT_TOKEN: Your Personal Access Token (PAT) associated with your Konnect account.
- 
    routeId: Theidof the route the plugin configuration will target.
See the Konnect API reference to learn about region-specific URLs and personal access tokens.
echo "
apiVersion: configuration.konghq.com/v1
kind: KongPlugin
metadata:
  name: ai-proxy
  namespace: kong
  annotations:
    kubernetes.io/ingress.class: kong
    konghq.com/tags: ''
config:
  route_type: llm/v1/chat
  genai_category: text/generation
  llm_format: bedrock
  auth:
    allow_override: false
    aws_access_key_id: '$AWS_ACCESS_KEY_ID'
    aws_secret_access_key: '$AWS_SECRET_ACCESS_KEY'
  model:
    provider: bedrock
    name: meta.llama3-70b-instruct-v1:0
    options:
      bedrock:
        aws_region: us-east-1
plugin: ai-proxy
" | kubectl apply -f -
Next, apply the KongPlugin resource by annotating the httproute or ingress resource:
kubectl annotate -n kong httproute  konghq.com/plugins=ai-proxy
kubectl annotate -n kong ingress  konghq.com/plugins=ai-proxy
Prerequisite: Configure your Personal Access Token
terraform {
  required_providers {
    konnect = {
      source  = "kong/konnect"
    }
  }
}
provider "konnect" {
  personal_access_token = "$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 = "bedrock"
    auth = {
      allow_override = false
      aws_access_key_id = var.aws_access_key_id
      aws_secret_access_key = var.aws_secret_access_key
    }
    model = {
      provider = "bedrock"
      name = "meta.llama3-70b-instruct-v1:0"
      options = {
        bedrock = {
          aws_region = "us-east-1"
        }
      }
    }
  }
  tags = []
  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 "aws_secret_access_key" {
  type = string
}
Add this section to your kong.yaml 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: bedrock
      auth:
        allow_override: false
        aws_access_key_id: ${{ env "DECK_AWS_ACCESS_KEY_ID" }}
        aws_secret_access_key: ${{ env "DECK_AWS_SECRET_ACCESS_KEY" }}
      model:
        provider: bedrock
        name: meta.llama3-70b-instruct-v1:0
        options:
          bedrock:
            aws_region: us-east-1
Make sure to replace the following placeholders with your own values:
- 
consumerName|Id: Theidornameof the consumer the plugin configuration will target.
Make the following request:
curl -i -X POST http://localhost:8001/consumers/{consumerName|Id}/plugins/ \
    --header "Accept: application/json" \
    --header "Content-Type: application/json" \
    --data '
    {
      "name": "ai-proxy",
      "config": {
        "route_type": "llm/v1/chat",
        "genai_category": "text/generation",
        "llm_format": "bedrock",
        "auth": {
          "allow_override": false,
          "aws_access_key_id": "'$AWS_ACCESS_KEY_ID'",
          "aws_secret_access_key": "'$AWS_SECRET_ACCESS_KEY'"
        },
        "model": {
          "provider": "bedrock",
          "name": "meta.llama3-70b-instruct-v1:0",
          "options": {
            "bedrock": {
              "aws_region": "us-east-1"
            }
          }
        }
      },
      "tags": []
    }
    '
Make sure to replace the following placeholders with your own values:
- 
consumerName|Id: Theidornameof 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 $KONNECT_TOKEN" \
    --data '
    {
      "name": "ai-proxy",
      "config": {
        "route_type": "llm/v1/chat",
        "genai_category": "text/generation",
        "llm_format": "bedrock",
        "auth": {
          "allow_override": false,
          "aws_access_key_id": "'$AWS_ACCESS_KEY_ID'",
          "aws_secret_access_key": "'$AWS_SECRET_ACCESS_KEY'"
        },
        "model": {
          "provider": "bedrock",
          "name": "meta.llama3-70b-instruct-v1:0",
          "options": {
            "bedrock": {
              "aws_region": "us-east-1"
            }
          }
        }
      },
      "tags": []
    }
    '
Make sure to replace the following placeholders with your own values:
- 
    region: Geographic region where your Kong Konnect is hosted and operates.
- 
    controlPlaneId: Theidof the control plane.
- 
    KONNECT_TOKEN: Your Personal Access Token (PAT) associated with your Konnect account.
- 
    consumerId: Theidof the consumer the plugin configuration will target.
See the Konnect API reference to learn about region-specific URLs and personal access tokens.
echo "
apiVersion: configuration.konghq.com/v1
kind: KongPlugin
metadata:
  name: ai-proxy
  namespace: kong
  annotations:
    kubernetes.io/ingress.class: kong
    konghq.com/tags: ''
config:
  route_type: llm/v1/chat
  genai_category: text/generation
  llm_format: bedrock
  auth:
    allow_override: false
    aws_access_key_id: '$AWS_ACCESS_KEY_ID'
    aws_secret_access_key: '$AWS_SECRET_ACCESS_KEY'
  model:
    provider: bedrock
    name: meta.llama3-70b-instruct-v1:0
    options:
      bedrock:
        aws_region: us-east-1
plugin: ai-proxy
" | kubectl apply -f -
Next, apply the KongPlugin resource by annotating the KongConsumer resource:
kubectl annotate -n kong  CONSUMER_NAME konghq.com/plugins=ai-proxy
Prerequisite: Configure your Personal Access Token
terraform {
  required_providers {
    konnect = {
      source  = "kong/konnect"
    }
  }
}
provider "konnect" {
  personal_access_token = "$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 = "bedrock"
    auth = {
      allow_override = false
      aws_access_key_id = var.aws_access_key_id
      aws_secret_access_key = var.aws_secret_access_key
    }
    model = {
      provider = "bedrock"
      name = "meta.llama3-70b-instruct-v1:0"
      options = {
        bedrock = {
          aws_region = "us-east-1"
        }
      }
    }
  }
  tags = []
  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 "aws_secret_access_key" {
  type = string
}
Add this section to your kong.yaml 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: bedrock
      auth:
        allow_override: false
        aws_access_key_id: ${{ env "DECK_AWS_ACCESS_KEY_ID" }}
        aws_secret_access_key: ${{ env "DECK_AWS_SECRET_ACCESS_KEY" }}
      model:
        provider: bedrock
        name: meta.llama3-70b-instruct-v1:0
        options:
          bedrock:
            aws_region: us-east-1
Make sure to replace the following placeholders with your own values:
- 
consumerGroupName|Id: Theidornameof the consumer group the plugin configuration will target.
Make the following request:
curl -i -X POST http://localhost:8001/consumer_groups/{consumerGroupName|Id}/plugins/ \
    --header "Accept: application/json" \
    --header "Content-Type: application/json" \
    --data '
    {
      "name": "ai-proxy",
      "config": {
        "route_type": "llm/v1/chat",
        "genai_category": "text/generation",
        "llm_format": "bedrock",
        "auth": {
          "allow_override": false,
          "aws_access_key_id": "'$AWS_ACCESS_KEY_ID'",
          "aws_secret_access_key": "'$AWS_SECRET_ACCESS_KEY'"
        },
        "model": {
          "provider": "bedrock",
          "name": "meta.llama3-70b-instruct-v1:0",
          "options": {
            "bedrock": {
              "aws_region": "us-east-1"
            }
          }
        }
      },
      "tags": []
    }
    '
Make sure to replace the following placeholders with your own values:
- 
consumerGroupName|Id: Theidornameof 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 $KONNECT_TOKEN" \
    --data '
    {
      "name": "ai-proxy",
      "config": {
        "route_type": "llm/v1/chat",
        "genai_category": "text/generation",
        "llm_format": "bedrock",
        "auth": {
          "allow_override": false,
          "aws_access_key_id": "'$AWS_ACCESS_KEY_ID'",
          "aws_secret_access_key": "'$AWS_SECRET_ACCESS_KEY'"
        },
        "model": {
          "provider": "bedrock",
          "name": "meta.llama3-70b-instruct-v1:0",
          "options": {
            "bedrock": {
              "aws_region": "us-east-1"
            }
          }
        }
      },
      "tags": []
    }
    '
Make sure to replace the following placeholders with your own values:
- 
    region: Geographic region where your Kong Konnect is hosted and operates.
- 
    controlPlaneId: Theidof the control plane.
- 
    KONNECT_TOKEN: Your Personal Access Token (PAT) associated with your Konnect account.
- 
    consumerGroupId: Theidof the consumer group the plugin configuration will target.
See the Konnect API reference to learn about region-specific URLs and personal access tokens.
echo "
apiVersion: configuration.konghq.com/v1
kind: KongPlugin
metadata:
  name: ai-proxy
  namespace: kong
  annotations:
    kubernetes.io/ingress.class: kong
    konghq.com/tags: ''
config:
  route_type: llm/v1/chat
  genai_category: text/generation
  llm_format: bedrock
  auth:
    allow_override: false
    aws_access_key_id: '$AWS_ACCESS_KEY_ID'
    aws_secret_access_key: '$AWS_SECRET_ACCESS_KEY'
  model:
    provider: bedrock
    name: meta.llama3-70b-instruct-v1:0
    options:
      bedrock:
        aws_region: us-east-1
plugin: ai-proxy
" | kubectl apply -f -
Next, apply the KongPlugin resource by annotating the KongConsumerGroup resource:
kubectl annotate -n kong  CONSUMERGROUP_NAME konghq.com/plugins=ai-proxy
Prerequisite: Configure your Personal Access Token
terraform {
  required_providers {
    konnect = {
      source  = "kong/konnect"
    }
  }
}
provider "konnect" {
  personal_access_token = "$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 = "bedrock"
    auth = {
      allow_override = false
      aws_access_key_id = var.aws_access_key_id
      aws_secret_access_key = var.aws_secret_access_key
    }
    model = {
      provider = "bedrock"
      name = "meta.llama3-70b-instruct-v1:0"
      options = {
        bedrock = {
          aws_region = "us-east-1"
        }
      }
    }
  }
  tags = []
  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 "aws_secret_access_key" {
  type = string
}
