Gemini provider

You can proxy requests to Gemini AI models through AI Gateway using the AI Proxy and AI Proxy Advanced plugins. This reference documents all supported AI capabilities, configuration requirements, and provider-specific details needed for proper integration.

AI Gateway automatically routes requests to the appropriate Gemini API endpoints. The following table shows the upstream paths used for each capability.

The following tables show the AI capabilities supported by Gemini provider when used with the AI Proxy or the AI Proxy Advanced plugin.

Set the plugin’s route_type based on the capability you want to use. See the tables below for supported route types.

Text generation

Support for Gemini basic text generation capabilities including chat, completions, and embeddings:

Advanced text generation

Support for Gemini function calling to allow Gemini models to use external tools and APIs:

Processing

Support for Gemini file operations, batch operations, assistants, and response handling:

¹ Files processing for Gemini is supported in the native format from SDK only

² Batches processing for Gemini is supported in the native format from SDK only

Image

Support for Gemini image generation and editing capabilities:

For requests with large payloads, consider increasing config.max_request_body_size to three times the raw binary size.

Supported image sizes and formats vary by model. Refer to your provider’s documentation for allowed dimensions and requirements.

Video

Support for Gemini video generation capabilities:

For requests with large payloads (video generation), consider increasing config.max_request_body_size to three times the raw binary size.

Realtime

Support for Gemini’s bidirectional streaming for realtime applications:

Realtime processing requires the AI Proxy Advanced plugin and uses WebSocket protocol.

To use the realtime route, you must configure the protocols ws and/or wss on both the Service and on the Route where the plugin is associated.

³ Realtime processing for Gemini is supported in the native format from SDK only

The base URL is https://generativelanguage.googleapis.com, where {route_type_path} is determined by the capability.

AI Gateway uses this URL automatically. You only need to configure a URL if you’re using a self-hosted or Gemini-compatible endpoint, in which case set the upstream_url plugin option.

By default, the AI Proxy plugin uses OpenAI-compatible request formats. Set config.llm_format to a native format to use Gemini-specific APIs and features.

The following native Gemini APIs are supported:

Provider-specific limitations for native formats

• Gemini only supports auth.allow_override = false

To use Gemini with AI Gateway, configure the AI Proxy or AI Proxy Advanced.

Here’s a minimal configuration for chat completions:

_format_version: "3.0"
plugins:
  - name: ai-proxy
    config:
      route_type: llm/v1/chat
      auth:
        param_name: key
        param_value: ${{ env "DECK_GEMINI_API_KEY" }}
        param_location: query
      model:
        provider: gemini
        name: gemini-2.5-flash

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",
        "auth": {
          "param_name": "key",
          "param_value": "'$GEMINI_API_KEY'",
          "param_location": "query"
        },
        "model": {
          "provider": "gemini",
          "name": "gemini-2.5-flash"
        }
      }
    }
    '

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 $KONNECT_TOKEN" \
    --data '
    {
      "name": "ai-proxy",
      "config": {
        "route_type": "llm/v1/chat",
        "auth": {
          "param_name": "key",
          "param_value": "'$GEMINI_API_KEY'",
          "param_location": "query"
        },
        "model": {
          "provider": "gemini",
          "name": "gemini-2.5-flash"
        }
      }
    }
    '

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
  auth:
    param_name: key
    param_value: '$GEMINI_API_KEY'
    param_location: query
  model:
    provider: gemini
    name: gemini-2.5-flash
plugin: ai-proxy
" | kubectl apply -f -

resource "konnect_gateway_plugin_ai_proxy" "my_ai_proxy" {
  enabled = true

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

    auth = {
      param_name = "key"
      param_value = var.gemini_api_key
      param_location = "query"
    }

    model = {
      provider = "gemini"
      name = "gemini-2.5-flash"
    }
  }

  control_plane_id = konnect_gateway_control_plane.my_konnect_cp.id
}

variable "gemini_api_key" {
  type = string
}

For more configuration options and examples, see:

• AI Proxy examples
• AI Proxy Advanced examples

• Set up AI Proxy Advanced with Gemini in Kong Gateway View →
• Set up AI Proxy with Gemini in Kong Gateway View →
• Route Claude CLI traffic through AI Gateway and Gemini View →
• Use Gemini's googleSearch tool with AI Proxy Advanced in AI Gateway View →
• Use Gemini's imageConfig with AI Proxy in AI Gateway View →
• Use Gemini's thinkingConfig with AI Proxy Advanced in AI Gateway View →
• Use Google Generative AI SDK for Gemini AI service chats with AI Gateway View →