Request prompt function
Protect your LLM services with rate limiting. The AI Rate Limiting Advanced Policy analyzes query costs and token responses to provide an enterprise-grade rate limiting strategy.
The following example uses request prompt rate limiting, which lets you rate limit requests based on a custom token.
Prerequisites
ai_gateway_policies:
- ref: request-prompt-count-function
ai_gateway: !lookup {id: !env AI_GATEWAY_ID}
name: request-prompt-count-function
display_name: Request prompt function
type: ai-rate-limiting-advanced
enabled: true
config:
strategy: redis
redis:
host: host.docker.internal
port: 16379
sync_rate: 0
policies:
- match:
- type: provider
partition_by: true
values:
- cohere
limits:
- limit: 100
window_size: 60
- limit: 1000
window_size: 3600
request_prompt_count_function: |
local header_count = tonumber(kong.request.get_header("x-prompt-count"))
if header_count then
return header_count
end
return 0
global: falseMake sure to replace the following placeholders with your own values:
AI_GATEWAY_ID: Theidof your AI Gateway.
curl -X POST https://{region}.api.konghq.com/v1/ai-gateways/{AIGatewayId}/policies \
--header "accept: application/json" \
--header "Content-Type: application/json" \
--header "Authorization: Bearer $KONNECT_TOKEN" \
--data '
{
"name": "request-prompt-count-function",
"display_name": "Request prompt function",
"type": "ai-rate-limiting-advanced",
"enabled": true,
"config": {
"strategy": "redis",
"redis": {
"host": "host.docker.internal",
"port": 16379
},
"sync_rate": 0,
"policies": [
{
"match": [
{
"type": "provider",
"partition_by": true,
"values": [
"cohere"
]
}
],
"limits": [
{
"limit": 100,
"window_size": 60
},
{
"limit": 1000,
"window_size": 3600
}
]
}
],
"request_prompt_count_function": "local header_count = tonumber(kong.request.get_header(\"x-prompt-count\"))\nif header_count then\n return header_count\nend\nreturn 0\n"
},
"global": false
}
'Make sure to replace the following placeholders with your own values:
-
region: Geographic region where your Kong Konnect is hosted and operates. -
KONNECT_TOKEN: Your Personal Access Token (PAT) associated with your Konnect account. -
AIGatewayId: Theidof the AI Gateway.
See the Konnect AI Gateway API reference to learn about region-specific URLs and personal access tokens.
Prerequisite: Configure your Personal Access Token
terraform {
required_providers {
konnect = {
source = "kong/konnect"
}
}
}
provider "konnect" {
personal_access_token = "$KONNECT_TOKEN"
server_url = "https://us.api.konghq.com/"
}Add the following to your Terraform configuration:
resource "konnect_ai_gateway_policy" "my_policy" {
name = "request-prompt-count-function"
display_name = "Request prompt function"
type = "ai-rate-limiting-advanced"
enabled = true
global = false
config = jsonencode({
strategy = "redis"
redis = {
host = "host.docker.internal"
port = 16379
}
sync_rate = 0
policies = [
{
match = [
{
type = "provider"
partition_by = true
values = ["cohere"]
} ]
limits = [
{
limit = 100
window_size = 60
},
{
limit = 1000
window_size = 3600
} ]
} ]
request_prompt_count_function = <<EOF
local header_count = tonumber(kong.request.get_header("x-prompt-count"))
if header_count then
return header_count
end
return 0
EOF
})
gateway_id = konnect_ai_gateway.my_ai_gateway.id
}ai_gateway_policies:
- ref: request-prompt-count-function
ai_gateway: !lookup {id: !env AI_GATEWAY_ID}
name: request-prompt-count-function
display_name: Request prompt function
type: ai-rate-limiting-advanced
enabled: true
config:
strategy: redis
redis:
host: host.docker.internal
port: 16379
sync_rate: 0
policies:
- match:
- type: provider
partition_by: true
values:
- cohere
limits:
- limit: 100
window_size: 60
- limit: 1000
window_size: 3600
request_prompt_count_function: |
local header_count = tonumber(kong.request.get_header("x-prompt-count"))
if header_count then
return header_count
end
return 0
global: falseMake sure to replace the following placeholders with your own values:
AI_GATEWAY_ID: Theidof your AI Gateway.
curl -X POST https://{region}.api.konghq.com/v1/ai-gateways/{AIGatewayId}/policies \
--header "accept: application/json" \
--header "Content-Type: application/json" \
--header "Authorization: Bearer $KONNECT_TOKEN" \
--data '
{
"name": "request-prompt-count-function",
"display_name": "Request prompt function",
"type": "ai-rate-limiting-advanced",
"enabled": true,
"config": {
"strategy": "redis",
"redis": {
"host": "host.docker.internal",
"port": 16379
},
"sync_rate": 0,
"policies": [
{
"match": [
{
"type": "provider",
"partition_by": true,
"values": [
"cohere"
]
}
],
"limits": [
{
"limit": 100,
"window_size": 60
},
{
"limit": 1000,
"window_size": 3600
}
]
}
],
"request_prompt_count_function": "local header_count = tonumber(kong.request.get_header(\"x-prompt-count\"))\nif header_count then\n return header_count\nend\nreturn 0\n"
},
"global": false
}
'Make sure to replace the following placeholders with your own values:
-
region: Geographic region where your Kong Konnect is hosted and operates. -
KONNECT_TOKEN: Your Personal Access Token (PAT) associated with your Konnect account. -
AIGatewayId: Theidof the AI Gateway.
See the Konnect AI Gateway API reference to learn about region-specific URLs and personal access tokens.
Prerequisite: Configure your Personal Access Token
terraform {
required_providers {
konnect = {
source = "kong/konnect"
}
}
}
provider "konnect" {
personal_access_token = "$KONNECT_TOKEN"
server_url = "https://us.api.konghq.com/"
}Add the following to your Terraform configuration:
resource "konnect_ai_gateway_policy" "my_policy" {
name = "request-prompt-count-function"
display_name = "Request prompt function"
type = "ai-rate-limiting-advanced"
enabled = true
global = false
config = jsonencode({
strategy = "redis"
redis = {
host = "host.docker.internal"
port = 16379
}
sync_rate = 0
policies = [
{
match = [
{
type = "provider"
partition_by = true
values = ["cohere"]
} ]
limits = [
{
limit = 100
window_size = 60
},
{
limit = 1000
window_size = 3600
} ]
} ]
request_prompt_count_function = <<EOF
local header_count = tonumber(kong.request.get_header("x-prompt-count"))
if header_count then
return header_count
end
return 0
EOF
})
gateway_id = konnect_ai_gateway.my_ai_gateway.id
}ai_gateway_policies:
- ref: request-prompt-count-function
ai_gateway: !lookup {id: !env AI_GATEWAY_ID}
name: request-prompt-count-function
display_name: Request prompt function
type: ai-rate-limiting-advanced
enabled: true
config:
strategy: redis
redis:
host: host.docker.internal
port: 16379
sync_rate: 0
policies:
- match:
- type: provider
partition_by: true
values:
- cohere
limits:
- limit: 100
window_size: 60
- limit: 1000
window_size: 3600
request_prompt_count_function: |
local header_count = tonumber(kong.request.get_header("x-prompt-count"))
if header_count then
return header_count
end
return 0
global: falseMake sure to replace the following placeholders with your own values:
AI_GATEWAY_ID: Theidof your AI Gateway.
curl -X POST https://{region}.api.konghq.com/v1/ai-gateways/{AIGatewayId}/policies \
--header "accept: application/json" \
--header "Content-Type: application/json" \
--header "Authorization: Bearer $KONNECT_TOKEN" \
--data '
{
"name": "request-prompt-count-function",
"display_name": "Request prompt function",
"type": "ai-rate-limiting-advanced",
"enabled": true,
"config": {
"strategy": "redis",
"redis": {
"host": "host.docker.internal",
"port": 16379
},
"sync_rate": 0,
"policies": [
{
"match": [
{
"type": "provider",
"partition_by": true,
"values": [
"cohere"
]
}
],
"limits": [
{
"limit": 100,
"window_size": 60
},
{
"limit": 1000,
"window_size": 3600
}
]
}
],
"request_prompt_count_function": "local header_count = tonumber(kong.request.get_header(\"x-prompt-count\"))\nif header_count then\n return header_count\nend\nreturn 0\n"
},
"global": false
}
'Make sure to replace the following placeholders with your own values:
-
region: Geographic region where your Kong Konnect is hosted and operates. -
KONNECT_TOKEN: Your Personal Access Token (PAT) associated with your Konnect account. -
AIGatewayId: Theidof the AI Gateway.
See the Konnect AI Gateway API reference to learn about region-specific URLs and personal access tokens.
Prerequisite: Configure your Personal Access Token
terraform {
required_providers {
konnect = {
source = "kong/konnect"
}
}
}
provider "konnect" {
personal_access_token = "$KONNECT_TOKEN"
server_url = "https://us.api.konghq.com/"
}Add the following to your Terraform configuration:
resource "konnect_ai_gateway_policy" "my_policy" {
name = "request-prompt-count-function"
display_name = "Request prompt function"
type = "ai-rate-limiting-advanced"
enabled = true
global = false
config = jsonencode({
strategy = "redis"
redis = {
host = "host.docker.internal"
port = 16379
}
sync_rate = 0
policies = [
{
match = [
{
type = "provider"
partition_by = true
values = ["cohere"]
} ]
limits = [
{
limit = 100
window_size = 60
},
{
limit = 1000
window_size = 3600
} ]
} ]
request_prompt_count_function = <<EOF
local header_count = tonumber(kong.request.get_header("x-prompt-count"))
if header_count then
return header_count
end
return 0
EOF
})
gateway_id = konnect_ai_gateway.my_ai_gateway.id
}ai_gateway_policies:
- ref: request-prompt-count-function
ai_gateway: !lookup {id: !env AI_GATEWAY_ID}
name: request-prompt-count-function
display_name: Request prompt function
type: ai-rate-limiting-advanced
enabled: true
config:
strategy: redis
redis:
host: host.docker.internal
port: 16379
sync_rate: 0
policies:
- match:
- type: provider
partition_by: true
values:
- cohere
limits:
- limit: 100
window_size: 60
- limit: 1000
window_size: 3600
request_prompt_count_function: |
local header_count = tonumber(kong.request.get_header("x-prompt-count"))
if header_count then
return header_count
end
return 0
global: trueMake sure to replace the following placeholders with your own values:
AI_GATEWAY_ID: Theidof your AI Gateway.
curl -X POST https://{region}.api.konghq.com/v1/ai-gateways/{AIGatewayId}/policies \
--header "accept: application/json" \
--header "Content-Type: application/json" \
--header "Authorization: Bearer $KONNECT_TOKEN" \
--data '
{
"name": "request-prompt-count-function",
"display_name": "Request prompt function",
"type": "ai-rate-limiting-advanced",
"enabled": true,
"config": {
"strategy": "redis",
"redis": {
"host": "host.docker.internal",
"port": 16379
},
"sync_rate": 0,
"policies": [
{
"match": [
{
"type": "provider",
"partition_by": true,
"values": [
"cohere"
]
}
],
"limits": [
{
"limit": 100,
"window_size": 60
},
{
"limit": 1000,
"window_size": 3600
}
]
}
],
"request_prompt_count_function": "local header_count = tonumber(kong.request.get_header(\"x-prompt-count\"))\nif header_count then\n return header_count\nend\nreturn 0\n"
},
"global": true
}
'Make sure to replace the following placeholders with your own values:
-
region: Geographic region where your Kong Konnect is hosted and operates. -
KONNECT_TOKEN: Your Personal Access Token (PAT) associated with your Konnect account. -
AIGatewayId: Theidof the AI Gateway.
See the Konnect AI Gateway API reference to learn about region-specific URLs and personal access tokens.
Prerequisite: Configure your Personal Access Token
terraform {
required_providers {
konnect = {
source = "kong/konnect"
}
}
}
provider "konnect" {
personal_access_token = "$KONNECT_TOKEN"
server_url = "https://us.api.konghq.com/"
}Add the following to your Terraform configuration:
resource "konnect_ai_gateway_policy" "my_policy" {
name = "request-prompt-count-function"
display_name = "Request prompt function"
type = "ai-rate-limiting-advanced"
enabled = true
global = true
config = jsonencode({
strategy = "redis"
redis = {
host = "host.docker.internal"
port = 16379
}
sync_rate = 0
policies = [
{
match = [
{
type = "provider"
partition_by = true
values = ["cohere"]
} ]
limits = [
{
limit = 100
window_size = 60
},
{
limit = 1000
window_size = 3600
} ]
} ]
request_prompt_count_function = <<EOF
local header_count = tonumber(kong.request.get_header("x-prompt-count"))
if header_count then
return header_count
end
return 0
EOF
})
gateway_id = konnect_ai_gateway.my_ai_gateway.id
}After creating the policy, add request-prompt-count-function to the policies array of your AI Model. The tool examples update an existing AI Model with the policy attached: replace the entity configuration in the example with your own, as the update replaces the entire AI Model.
ai_gateway_models:
- ref: my-gpt-4o
ai_gateway: !lookup {id: !env AI_GATEWAY_ID}
display_name: my-gpt-4o
name: my-gpt-4o
type: model
capabilities:
- generate
formats:
- type: openai
targets:
- name: gpt-4o
provider: my-openai-account
config:
type: openai
config:
route:
paths:
- "/v1"
model:
body_param: model
values:
- my-gpt-4o
logging:
payloads: false
policies:
- !ref request-prompt-count-function#nameAfter creating the policy, add request-prompt-count-function to the policies array of your AI Model. The tool examples update an existing AI Model with the policy attached: replace the entity configuration in the example with your own, as the update replaces the entire AI Model.
curl -X PUT https://{region}.api.konghq.com/v1/ai-gateways/{AIGatewayId}/models/my-gpt-4o \
--header "accept: application/json" \
--header "Content-Type: application/json" \
--header "Authorization: Bearer $KONNECT_TOKEN" \
--data '
{
"display_name": "my-gpt-4o",
"name": "my-gpt-4o",
"type": "model",
"capabilities": [
"generate"
],
"formats": [
{
"type": "openai"
}
],
"policies": [
"request-prompt-count-function"
],
"targets": [
{
"name": "gpt-4o",
"provider": "my-openai-account",
"config": {
"type": "openai"
}
}
],
"config": {
"route": {
"paths": [
"/v1"
],
"model": {
"body_param": "model",
"values": [
"my-gpt-4o"
]
}
},
"logging": {
"payloads": false
}
}
}
'After creating the policy, add request-prompt-count-function to the policies array of your AI Model. The tool examples update an existing AI Model with the policy attached: replace the entity configuration in the example with your own, as the update replaces the entire AI Model.
resource "konnect_ai_gateway_model" "my_model" {
display_name = "my-gpt-4o"
name = "my-gpt-4o"
type = "model"
capabilities = ["generate"]
formats = [
{
type = "openai"
} ]
targets = [
{
name = "gpt-4o"
provider = "my-openai-account"
config = {
type = "openai"
}
} ]
config = jsonencode({
route = {
paths = ["/v1"]
model = {
body_param = "model"
values = ["my-gpt-4o"]
}
}
logging = {
payloads = false
}
})
policies = [konnect_ai_gateway_policy.my_policy.name]
gateway_id = konnect_ai_gateway.my_ai_gateway.id
}After creating the policy, add request-prompt-count-function to the policies array of your AI Consumer. The tool examples update an existing AI Consumer with the policy attached: replace the entity configuration in the example with your own, as the update replaces the entire AI Consumer.
ai_gateway_consumers:
- ref: mobile-app-production
ai_gateway: !lookup {id: !env AI_GATEWAY_ID}
display_name: Mobile App - Production
name: mobile-app-production
type: api-key
policies:
- !ref request-prompt-count-function#nameAfter creating the policy, add request-prompt-count-function to the policies array of your AI Consumer. The tool examples update an existing AI Consumer with the policy attached: replace the entity configuration in the example with your own, as the update replaces the entire AI Consumer.
curl -X PUT https://{region}.api.konghq.com/v1/ai-gateways/{AIGatewayId}/consumers/mobile-app-production \
--header "accept: application/json" \
--header "Content-Type: application/json" \
--header "Authorization: Bearer $KONNECT_TOKEN" \
--data '
{
"display_name": "Mobile App - Production",
"name": "mobile-app-production",
"type": "api-key",
"policies": [
"request-prompt-count-function"
]
}
'After creating the policy, add request-prompt-count-function to the policies array of your AI Consumer. The tool examples update an existing AI Consumer with the policy attached: replace the entity configuration in the example with your own, as the update replaces the entire AI Consumer.
resource "konnect_ai_gateway_consumer" "my_consumer" {
display_name = "Mobile App - Production"
name = "mobile-app-production"
type = "api-key"
policies = [konnect_ai_gateway_policy.my_policy.name]
gateway_id = konnect_ai_gateway.my_ai_gateway.id
}After creating the policy, add request-prompt-count-function to the policies array of your AI Consumer Group. The tool examples update an existing AI Consumer Group with the policy attached: replace the entity configuration in the example with your own, as the update replaces the entire AI Consumer Group.
ai_gateway_consumer_groups:
- ref: internal-teams
ai_gateway: !lookup {id: !env AI_GATEWAY_ID}
display_name: Internal Teams
name: internal-teams
policies:
- !ref request-prompt-count-function#nameAfter creating the policy, add request-prompt-count-function to the policies array of your AI Consumer Group. The tool examples update an existing AI Consumer Group with the policy attached: replace the entity configuration in the example with your own, as the update replaces the entire AI Consumer Group.
curl -X PUT https://{region}.api.konghq.com/v1/ai-gateways/{AIGatewayId}/consumer-groups/internal-teams \
--header "accept: application/json" \
--header "Content-Type: application/json" \
--header "Authorization: Bearer $KONNECT_TOKEN" \
--data '
{
"display_name": "Internal Teams",
"name": "internal-teams",
"policies": [
"request-prompt-count-function"
]
}
'After creating the policy, add request-prompt-count-function to the policies array of your AI Consumer Group. The tool examples update an existing AI Consumer Group with the policy attached: replace the entity configuration in the example with your own, as the update replaces the entire AI Consumer Group.
resource "konnect_ai_gateway_consumer_group" "my_consumer_group" {
display_name = "Internal Teams"
name = "internal-teams"
policies = [konnect_ai_gateway_policy.my_policy.name]
gateway_id = konnect_ai_gateway.my_ai_gateway.id
}