Get started with Genkit using Go

This guide shows you how to get started with Genkit in a Go app.

If you discover issues with the libraries or this documentation please report them in our GitHub repository.

Make your first request

  1. Install Go 1.24 or later. See Download and install in the official Go docs.

  2. Initialize a new Go project directory with the Genkit package:

    mkdir genkit-intro && cd genkit-intro
go mod init example/genkit-intro
go get github.com/firebase/genkit/go

  3. Create a main.go file with the following sample code:

    package main

import (
    "context"
    "log"

    "github.com/firebase/genkit/go/ai"
    "github.com/firebase/genkit/go/genkit"
    "github.com/firebase/genkit/go/plugins/googlegenai"
)

func main() {
    ctx := context.Background()

    // Initialize Genkit with the Google AI plugin and Gemini 2.0 Flash.
    g, err := genkit.Init(ctx,
        genkit.WithPlugins(&googlegenai.GoogleAI{}),
        genkit.WithDefaultModel("googleai/gemini-2.0-flash"),
    )
    if err != nil {
        log.Fatalf("could not initialize Genkit: %w", err)
    }

    resp, err := genkit.Generate(ctx, g, ai.WithPrompt("What is the meaning of life?"))
    if err != nil {
        log.Fatal("could not generate model response: %w", err)
    }

    log.Println(resp.Text())
}

  4. Configure your Gemini API key by setting the GEMINI_API_KEY environment variable:

    export GEMINI_API_KEY=<your API key>

    If you don't already have one, create a key in Google AI Studio. Google AI provides a generous free-of-charge tier and does not require a credit card to get started.

  5. Run the app to see the model response:

    go run .
There is no single universally agreed-upon meaning of life; it's a deeply
personal question. Many find meaning through connection, growth,
contribution, happiness, or discovering their own purpose.

Next steps

Now that you're set up to make model requests with Genkit, learn how to use more Genkit capabilities to build your AI-powered apps and workflows. To get started with additional Genkit capabilities, see the following guides:

  • Developer tools: Learn how to set up and use Genkit's CLI and developer UI to help you locally test and debug your app.
  • Generating content: Learn how to use Genkit's unified generation API to generate text and structured data from any supported model.
  • Creating flows: Learn how to use special Genkit functions, called flows, that provide end-to-end observability for workflows and rich debugging from Genkit tooling.
  • Managing prompts: Learn how Genkit helps you manage your prompts and configuration together as code.