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Genkit

Google Generative AI plugin

The Google Generative AI plugin provides interfaces to Google’s Gemini models through the Gemini API.

Configuration

Section titled “Configuration”

To use this plugin, import the googlegenai package and pass googlegenai.GoogleAI to WithPlugins() in the Genkit initializer:

import "github.com/firebase/genkit/go/plugins/googlegenai"
g := genkit.Init(context.Background(), genkit.WithPlugins(&googlegenai.GoogleAI{}))

The plugin requires an API key for the Gemini API, which you can get from Google AI Studio.

Configure the plugin to use your API key by doing one of the following:

  • Set the GEMINI_API_KEY environment variable to your API key.

  • Specify the API key when you initialize the plugin:

  genkit.WithPlugins(&googlegenai.GoogleAI{APIKey: "YOUR_API_KEY"})

However, don’t embed your API key directly in code! Use this feature only in conjunction with a service like Cloud Secret Manager or similar.

Usage

Section titled “Usage”

Generative models

Section titled “Generative models”

To get a reference to a supported model, specify its identifier to googlegenai.GoogleAIModel:

model := googlegenai.GoogleAIModel(g, "gemini-2.5-flash")

Alternatively, you may create a ModelRef which pairs the model name with its config:

modelRef := googlegenai.GoogleAIModelRef("gemini-2.5-flash", &genai.GenerateContentConfig{
    Temperature: genai.Ptr[float32](0.5),
    MaxOutputTokens: genai.Ptr[int32](500),
    // Other configuration...
})

Model references have a Generate() method that calls the Google API:

resp, err := genkit.Generate(ctx, g, ai.WithModel(modelRef), ai.WithPrompt("Tell me a joke."))
if err != nil {
    return err
}


log.Println(resp.Text())

See Generating content with AI models for more information.

Embedding models

Section titled “Embedding models”

To get a reference to a supported embedding model, specify its identifier to googlegenai.GoogleAIEmbedder:

embeddingModel := googlegenai.GoogleAIEmbedder(g, "text-embedding-004")

Embedder references have an Embed() method that calls the Google AI API:

resp, err := genkit.Embed(ctx, g, ai.WithEmbedder(embeddingModel), ai.WithTextDocs(userInput))
if err != nil {
    return err
}

See Retrieval-augmented generation (RAG) for more information.

Next Steps

Section titled “Next Steps”