1 month ago - The Google Gen AI SDK provides a unified interface to Gemini models through both the Gemini Developer API and the Gemini API on Gemini Enterprise Agent Platform.

1 month ago - Google Gen AI Python SDK provides an interface for developers to integrate Google's generative models into their Python applications. - googleapis/python-genai

April 28, 2026 - When building with the Gemini API, we recommend using the Google GenAI SDK. These are the official, production-ready libraries that we develop and maintain for the most popular languages.

With Gemini 2.0, we took the chance to create a single unified SDK for all developers who want to use Google's GenAI models (Gemini, Veo, Imagen, etc).

October 24, 2025 - This blog post introduces the new Google Gen AI .NET SDK, enabling C#/.NET developers to use Gemini from Google AI or Vertex AI with a single, unified library. Learn how to install the SDK, create a client, and generate text and images with configurable settings.

import google.genai from google.genai import types import os if os.environ.get('GOOGLE_GENAI_USE_ENTERPRISE'): MODEL_NAME = 'gemini-2.0-flash-live-preview-04-09' else: MODEL_NAME = 'gemini-live-2.5-flash-preview'; client = genai.Client() async with client.aio.live.connect( model=MODEL_NAME, config={"response_modalities": ["TEXT"]} ) as session: await session.send_client_content( turns=types.Content( role='user', parts=[types.Part(text="Hello world!")])) async for msg in session.receive(): if msg.text: print(msg.text)

3 weeks ago - The Google Gen AI Go SDK enables developers to use Google's state-of-the-art generative AI models (like Gemini) to build AI-powered features and applications. This SDK supports use cases like: ... For example, with just a few lines of code, you can access Gemini's multimodal capabilities to ...

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March 16, 2025 - Let’s dive in and see how this unified SDK simplifies working with Google’s generative AI capabilities. ... If you’re using Google Colab, you can find your API key under the secrets section by clicking on “Import key from AI Studio.” If you’re not using Colab, you can generate a free API key at aistudio.google.com. from google import genai from google.colab import userdata from IPython.display import Markdown, display GOOGLE_API_KEY = userdata.get('GOOGLE_API_KEY') # Create a client instance using Google Gemini API Key client = genai.Client(api_key=GOOGLE_API_KEY) response = client.models.generate_content( model='gemini-2.0-flash', contents='Create a short bedtime story for a 7 year old using unicorn and rainbows' ) display(Markdown(response.text))

April 25, 2026 - Documentation: https://googleapis.github.io/js-genai/ The Google Gen AI JavaScript SDK is designed for TypeScript and JavaScript developers to build applications powered by Gemini.

using Google.GenAI; // only run this block for Gemini Enterprise Agent Platform API client = new Client( project: project, location: location, enterprise: true )

Vertex AI's services are now part of Gemini Enterprise Agent Platform. See the most up-to-date information in the Agent Platform documentation · This page contains code samples for Generative AI on Vertex AI. To search and filter code samples for other Google Cloud products, see the Google ...

Documentation and resources for building and implementing generative AI applications with Google Cloud tools and productss.

April 8, 2026 - This SDK (@google/genai) is Google Deepmind’s "vanilla" SDK for its generative AI offerings, and is where Google Deepmind adds new AI features.

Use GoogleAI, OpenAI, Claude, and Ollama through one SDK.

from google import genai from google.genai import types as genai_types # Create a Client in the Gen AI SDK genai_client = genai.Client(vertexai=True, project="your-project", location="your-location") # Call generate_content() with the prompt response = genai_client.models.generate_content( model=retrieved_prompt.prompt_data.model, contents=retrieved_prompt.assemble_contents(), )

1 week ago - This SDK (@google/genai) is Google Deepmind’s "vanilla" SDK for its generative AI offerings, and is where Google Deepmind adds new AI features.

This API reference describes the unary, streaming, and real-time APIs you can use to interact with the Gemini models. You can use the REST APIs in any environment that supports HTTP requests.

April 24, 2026 - ctx := context.Background() client, err := genai.NewClient(ctx, &genai.ClientConfig{ APIKey: os.Getenv("GEMINI_API_KEY"), Backend: genai.BackendGeminiAPI, }) if err != nil { log.Fatal(err) } modelInfo, err := client.Models.Get(ctx, "gemini-3.5-flash", nil) if err != nil { log.Fatal(err) } fmt.Println(modelInfo)