1 week ago - Learn more in the Interactions API Overview. The fastest path from prompt to production with Gemini, Veo, Nano Banana, and more. from google import genai client = genai.Client() interaction = client.interactions.create( model="gemini-3.5-flash", input="Explain how AI works in a few words" ) print(interaction.output_text) 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); curl -X POST "https://generativelanguage.googleapis.com/v1beta/interactions" \ -H "x-goog-api-key: $GEMINI_API_KEY" \ -H 'Content-Type: application/json' \ -d '{ "model": "gemini-3.5-flash", "input": "Explain how AI works in a few words" }' Start building ·

1 month ago - client.tunings contains tuning job APIs and supports supervised fine tuning through tune. Only supported in Vertex AI. See the 'Create a client' section above to initialize a client. Vertex AI supports tuning from GCS source or from a Vertex AI Multimodal Dataset · from google.genai import types model = 'gemini-3.5-flash' training_dataset = types.TuningDataset( # or gcs_uri=my_vertex_multimodal_dataset gcs_uri='gs://your-gcs-bucket/your-tuning-data.jsonl', )

The ML Kit GenAI APIs are built on top of AICore, an Android system service that enables on-device execution of GenAI foundation models to facilitate features such as enhanced app functionality and improved user privacy by processing data locally.

from google import genai # Only run this block for Vertex AI API client = genai.Client( vertexai=True, project='your-project-id', location='us-central1' )

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.

Enable the Vertex AI API. Configure authentication for your project. Install the gcloud CLI. Initialize the gcloud CLI. Create local authentication credentials for your user account: ... A list of accepted authentication options are listed in GoogleAuthOptions interface of google-auth-library-node.js GitHub repo. ... import {GoogleGenAI} from '@google/genai'; const GEMINI_API_KEY = process.env.GEMINI_API_KEY; const ai = new GoogleGenAI({apiKey: GEMINI_API_KEY}); async function main() { const response = await ai.models.generateContent({ model: 'gemini-2.5-flash', contents: 'Why is the sky blue?', }); console.log(response.text); } main(); Copy

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.

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...

For the model parameter, supported formats for Gemini API include: - The Gemini model ID, for example: ‘gemini-2.0-flash’ - The model name starts with ‘models/’, for example: ... For tuned models, the model name starts with ‘tunedModels/’, for example: ‘tunedModels/1234567890123456789’ · Some models support multimodal input and output. Built-in MCP support is an experimental feature. ... from google.genai import types from google import genai client = genai.Client( vertexai=True, project='my-project-id', location='us-central1' ) async for chunk in await client.aio.models.gener

Google Generative AI High level API client library and tools. ... 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).

May 22, 2026 - It supports the Gemini Developer API and Gemini Enterprise Agent Platform APIs. 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.

1 week ago - Manage API keys and monitor resource usage in one place Start · GenAI SDKs · Official SDKs for Python, JavaScript, Go, Java, and C++ Start · Interactions API · Build stateful, multi-turn agents with managed tool execution and history Start · Tools · Extensible function calling and native tool support, including Search and Maps grounding Start ·

5 days ago - "Show me the Google Gen AI SDK code for Node.js to call the Gemini API for summarizing a long document. What are the best practices for chunking input, according to the official documentation?" "I'm encountering an authentication error with the Java Gen AI SDK when running on Cloud Run. What are the common causes and how can I troubleshoot?" "Draft a Python function using the google-genai library to stream responses from Gemini for a chat application."

2 weeks 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); curl -X POST "https://generativelanguage.googleapis.com/v1beta/interactions" \ -H "x-goog-api-key: $GEMINI_API_KEY" \ -H 'Content-Type: application/json' \ -H "Api-Revision: 2026-05-20" \ -d '{ "model": "gemini-3.5-flash", "input": "Explain how AI works in a few words" }'

The Google GenAI API allows developers to build generative AI applications using Google’s Gemini models through either the Gemini Developer API or Vertex AI. The Google GenAI API supports multimodal prompts as input and outputs text or code. A multimodal model is capable of processing information ...

Integrate AI models like Gemini Nano into web apps with Chrome's built-in web platform APIs. AI on Chrome · Build trusted and secure AI with guidance for responsible design, development, and deployment of models and applications. Build Responsible AI · Tools and guidance to design, build, and evaluate open AI models responsibly. Responsible GenAI Toolkit ·

Learn how to use Google's Generative AI models through the Gemini Developer API, including text generation, embeddings, image generation, video generation, and text-to-speech.

Learn how to use the Gemini API and the Google Gen AI SDK for JavaScript and TypeScript to prototype generative AI for web apps. Use the Google Gen AI SDK to make your first generative AI call using the Gemini API in your client-side web application.

April 25, 2026 - Enable the Vertex AI API. Configure authentication for your project. Install the gcloud CLI. Initialize the gcloud CLI. Create local authentication credentials for your user account: ... A list of accepted authentication options are listed in GoogleAuthOptions interface of google-auth-library-node.js GitHub repo. ... import {GoogleGenAI} from '@google/genai'; const GEMINI_API_KEY = process.env.GEMINI_API_KEY; const ai = new GoogleGenAI({apiKey: GEMINI_API_KEY}); async function main() { const response = await ai.models.generateContent({ model: 'gemini-2.5-flash', contents: 'Why is the sky blue?', }); console.log(response.text); } main();