Google Gen AI Python SDK provides an interface for developers to integrate Google’s generative models into their Python applications. It supports the Gemini Developer API and Vertex AI APIs. ... Please run one of the following code blocks to create a client for different services (Gemini Developer API or Vertex AI). from google import genai # Only run this block for Gemini Developer API client = genai.Client(api_key='GEMINI_API_KEY')

from google import genai # TODO(developer): Update below line API_KEY = "YOUR_API_KEY" client = genai.Client(vertexai=True, api_key=API_KEY) response = client.models.generate_content( model="gemini-3.5-flash", contents="Explain bubble sort to me.", ) print(response.text) # Example response: # Bubble Sort is a simple sorting algorithm that repeatedly steps through the list · The Google Gen AI SDK for Go is available on go.dev and GitHub:

April 28, 2026 - The Google GenAI SDK is available for the Python, JavaScript/TypeScript, Go and Java languages. You can install each language's library using package managers, or visit their GitHub repos for further engagement: ... <dependencies> <dependency> ...

April 28, 2026 - You would directly instantiate and interact with GenerativeModel objects. import google.generativeai as genai # Directly create and use model objects model = genai.GenerativeModel('gemini-3.5-flash') response = ...

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.

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.

4 weeks ago - To make a model more deterministic, lowering the temperature parameter reduces randomness, with values near 0 minimizing variability. Capabilities and parameter defaults for each model is shown in the Vertex AI docs and Gemini API docs respectively. Note that all API methods support Pydantic types and dictionaries, which you can access from google.genai.types.

May 5, 2026 - The Google Gen AI Java SDK provides ... switch between the 2 backends without rewriting your code. import com.google.genai.Client; // Use Builder class for instantiation....

May 22, 2026 - 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, ...

1 week ago - import { GoogleGenAI } from "@google/genai"; const ai = new GoogleGenAI({}); 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);

Budget Controls: Set spending limits and track costs across all SDK usage · Logging & Observability: Track all requests with cost tracking, logging, and analytics ... model_list: - model_name: gemini-2.5-flash litellm_params: model: gemini/gemini-2.5-flash api_key: os.environ/GEMINI_API_KEY ... const { GoogleGenAI } = require("@google/genai"); const ai = new GoogleGenAI({ apiKey: "sk-1234", // LiteLLM virtual key (not a Google key) httpOptions: { baseUrl: "http://localhost:4000/gemini", // LiteLLM proxy URL }, }); async function main() { const response = await ai.models.generateContent({ model: "gemini-2.5-flash", contents: "Explain how AI works", }); console.log(response.text); } main();

Google Generative AI High level API client library and tools.

Fetch the complete documentation index at: /llms.txt · Use this file to discover all available pages before exploring further. ... Google’s GenAI SDK is a framework designed to help you interact with Gemini models and models run through VertexAI. ...

March 11, 2025 - By default, the SDK uses a set of standard configurations. However, you can modify these to suit your needs: from google import genai from google.genai import types PROJECT_ID = userdata.get('PROJECT_ID') LOCATION = userdata.get('LOCATION') # Create a client instance using Vertex AI in Google Cloud client = genai.Client(vertexai=True, project=PROJECT_ID, location=LOCATION) response = client.models.generate_content( model='gemini-2.0-flash', contents='Create a short bedtime story for a 3 year old using unicorns and rainbows', config = types.GenerateContentConfig( max_output_tokens=200, temperature = 0.1) ) display(Markdown(response.text))

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

1 month ago - import { GoogleGenAI, Modality } from '@google/genai'; const ai = new GoogleGenAI({ apiKey: "YOUR_API_KEY"}); const model = 'gemini-3.1-flash-live-preview'; const config = { responseModalities: [Modality.AUDIO] }; async function main() { const session = await ai.live.connect({ model: model, callbacks: { onopen: function () { console.debug('Opened'); }, onmessage: function (message) { console.debug(message); }, onerror: function (e) { console.debug('Error:', e.message); }, onclose: function (e) { console.debug('Close:', e.reason); }, }, config: config, }); console.debug("Session started"); // Send content...

March 24, 2026 - The Google Gen AI SDK provides a unified interface to Google's generative AI API services. This SDK simplifies the process of integrating generative AI capabilities into applications and services, enabling developers to leverage Google's advanced ...