August 27, 2024 - package cmd import ( "context" "fmt" "log" "os" "github.com/google/generative-ai-go/genai" "github.com/spf13/cobra" "google.golang.org/api/option" ) // searchCmd represents the search command var searchCmd = &cobra.Command{ Use: "search", Short: "A brief description of your command", // Added the getResponse() function Run: func(cmd *cobra.Command, args []string) { getResponse() }, } func init() { rootCmd.AddCommand(searchCmd) } func getResponse() { ctx := context.Background() client, err := genai.NewClient(ctx, option.WithAPIKey(os.Getenv("GEMINI_API_KEY"))) if err != nil { log.Fatal(err) } defer client.Close() model := client.GenerativeModel("gemini-1.5-flash") resp, err := model.GenerateContent(ctx, genai.Text("Write a story about a AI and magic")) if err != nil { log.Fatal(err) } fmt.Println(resp.Candidates[0].Content.Parts[0]) }

February 19, 2024 - Call client.Close() to close it proactively. Use a model specifically tailored to your use case (e.g., gemini-pro-vision for multimodal input, gemini-pro for text generation and continuous dialogue). import "github.com/google/generative-ai-go/genai" import "google.golang.org/api/option" ctx := context.Background() // Access your API key as an environment variable (see "Set up your API key" above) client, err := genai.NewClient(ctx, option.WithAPIKey(os.Getenv("API_KEY"))) if err != nil { log.Fatal(err) } defer client.Close() model := client.GenerativeModel("MODEL_NAME") When the prompt input i

December 4, 2025 - Learn step-by-step how to implement the Gemini AI model in Golang with our comprehensive guide. Build powerful AI applications efficiently - CloudZenia blog

December 15, 2024 - To connect and use Gemini with Go, Google's LLM, one can use their official Go SDK for doing this. In this post, we will just show a simple chat example to demonstrate how to make it work with Go.

The Gemini API docs are fully updated to show examples of the new Google Gen AI SDK: Get started.

May 22, 2026 - import "google.golang.org/genai" ... location, Backend: genai.BackendEnterprise, }) You can create a client by configuring the necessary environment variables....

Client and server library for the Gemini protocol, in Go. - makew0rld/go-gemini

Simple way to use Gemini from Go, including function calls / tools - xyproto/geminiclient

go-gemini is an implementation of the Gemini API (public and private) in Golang. Based off of https://github.com/toorop/go-bittrex/ import "github.com/jyap808/go-gemini" This library is more of a framework for some bots I use so it is expected ...

package main import ( "context" "encoding/json" "fmt" "log" "os" "github.com/google/generative-ai-go/genai" "google.golang.org/api/option" ) func main() { ctx := context.Background() client, err := genai.NewClient(ctx, option.WithAPIKey(os.Getenv("API_KEY"))) if err != nil { log.Fatal(err) } defer client.Close() model := client.GenerativeModel("gemini-pro-vision") imgData1, err := os.ReadFile("../images/turtle1.png") if err != nil { log.Fatal(err) } imgData2, err := os.ReadFile("../images/turtle2.png") if err != nil { log.Fatal(err) } prompt := []genai.Part{ genai.ImageData("png", imgData1), genai.ImageData("png", imgData2), genai.Text("Describe the difference between these two pictures, with scientific detail"), } resp, err := model.GenerateContent(ctx, prompt...) if err != nil { log.Fatal(err) } bs, _ := json.MarshalIndent(resp, "", " ") fmt.Println(string(bs)) }

February 17, 2026 - Here is a Cloud Function that takes a prompt and returns a Gemini response. package myfunction import ( "context" "encoding/json" "fmt" "log" "net/http" "os" "github.com/GoogleCloudPlatform/functions-framework-go/functions" "google.golang.org/genai" ) // init registers the Cloud Function entry point func init() { functions.HTTP("GenerateText", GenerateText) } // GenerateRequest represents the incoming request payload type GenerateRequest struct { Prompt string `json:"prompt"` MaxTokens int `json:"max_tokens,omitempty"` Temperature float32 `json:"temperature,omitempty"` } // GenerateResponse re

ErrorResponse create a response from the given error with the error string as the Meta field. If the error is of type gemini.Error, the status will be taken from the status field, otherwise it will default to StatusTemporaryFailure.

September 14, 2024 - In this blog post, we’ll explore how to create a chat application powered by Gemini PRO using the Go programming language. We’ll cover the integration of this model, handling user prompts, and implementing a apikey based caching system for a more personalized experience. To utilize this application, you’ll need an API key from ai.google.dev · Go (Golang): A statically typed, compiled language designed for simplicity and efficiency.

3 weeks ago - Gemini API on Gemini Enterprise Agent Platform: Set GOOGLE_GENAI_USE_ENTERPRISE, GOOGLE_CLOUD_PROJECT and GOOGLE_CLOUD_LOCATION, as shown below: export GOOGLE_GENAI_USE_ENTERPRISE=true export GOOGLE_CLOUD_PROJECT='your-project-id' export GOOGLE_CLOUD_LOCATION='us-central1' client, err := ...

May 2, 2025 - package main import ( "context" "fmt" "log" "os" "github.com/google/generative-ai-go/genai" "google.golang.org/api/option" ) func main() { ctx := context.Background() client, err := genai.NewClient(ctx, option.WithAPIKey(os.Getenv("GEMINI_API_KEY"))) if err != nil { log.Fatal(err) } defer client.Close() model := client.GenerativeModel("gemini-1.5-flash") cs := model.StartChat() cs.History = []*genai.Content{ { Parts: []genai.Part{ genai.Text("Hello, I have 2 dogs in my house."), }, Role: "user", }, { Parts: []genai.Part{ genai.Text("Great to meet you.

January 30, 2026 - func NewModel(ctx context.Context, modelName string, cfg *genai.ClientConfig) (model.LLM, error) NewModel returns model.LLM, backed by the Gemini API.

2 weeks ago - To use the Gemini API, you need an API key. Create one for free to get started: ... Install the SDK and generate text with a single API call. ... from google import genai client = genai.Client() interaction = client.interactions.create( ...

1 week ago - import { GoogleGenAI } from "@google/genai"; const ai = new GoogleGenAI({ apiKey: "YOUR_API_KEY" }); async function main() { const interaction = await ai.interactions.create({ model: "gemini-3.5-flash", input: "Explain how AI works in a few words", }); console.log(interaction.output_text); } main(); package main import ( "context" "fmt" "log" "google.golang.org/genai" "google.golang.org/genai/interactions" ) func main() { ctx := context.Background() client, err := genai.NewClient(ctx, &genai.ClientConfig{ APIKey: "YOUR_API_KEY", Backend: genai.BackendGeminiAPI, }) if err != nil { log.Fatal(err

February 12, 2026 - One of the key goals of this tutorial is to validate that a compiled language like Go can be used for AI software development beyond the traditional interpreted languages. Go, also known as Golang...