Get started with Genkit using Go (beta)

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.

Requirements

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

• Node.js 20 or later (for the Genkit CLI and UI). See the next section for a brief guide on installing Node.

Install Genkit

1. If you don't already have Node 20 or newer on your system, install it now.

   Recommendation: The nvm and nvm-windows tools are a convenient way to install specific versions of Node if it's not already installed on your system. These tools install Node on a per-user basis, so you don't need to make system-wide changes.

   To install nvm:

   Linux, macOS, etc.Windows

   Run the following command:

   curl -o- https://raw.githubusercontent.com/nvm-sh/nvm/v0.39.7/install.sh | bash

   Download and run the installer as described in the nvm-windows docs.

   Then, to install Node and npm, open a new shell and run the following command:

   nvm install 20

2. Install the Genkit CLI by running the following command:

   npm i -g genkit-cli

   This command installs the Genkit CLI into your Node installation directory so that it can be used outside of a Node project.

Create and explore a sample project

1. Create a new project directory:

   mkdir genkit-intro && cd genkit-intro

2. Initialize the Go module and get the Genkit package:

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

Configure your model API key

For this guide, we'll show you how to use the Gemini API which provides a generous free-of-charge tier and does not require a credit card to get started. To use the Gemini API, you'll need an API key. If you don't already have one, create a key in Google AI Studio.

After you've created an API key, set the GEMINI_API_KEY environment variable to your key with the following command:

export GEMINI_API_KEY=<your API key>

Make your first request

Get started with Genkit in just a few lines of 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 a Genkit instance.
    g, err := genkit.Init(ctx,
        // Install the Google AI plugin which provides Gemini models.
        genkit.WithPlugins(&googlegenai.GoogleAI{}),
        // Set the default model to use for generate calls.
        genkit.WithDefaultModel("googleai/gemini-2.0-flash"),
    )
    if err != nil {
        log.Fatal(err)
    }

    // Generate a model response.
    resp, err := genkit.Generate(ctx, g, ai.WithPrompt("Hello, Gemini!"))
    if err != nil {
        log.Fatal(err)
    }

    log.Println(resp.Text())
}

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.