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Google GenAI Plugin

The @genkit-ai/google-genai plugin provides a unified interface to connect with Google’s generative AI models, offering access through both the Gemini Developer API and Vertex AI. It replaces the previous googleAI and vertexAI plugins.

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Installation

npm install @genkit-ai/google-genai

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Configuration

This unified plugin exports two main initializers:
  • googleAI: Access models via the Gemini Developer API using API key authentication
  • vertexAI: Access models via Google Cloud Vertex AI

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Using Gemini Developer API (googleAI)

Ideal for quick prototyping and access to models available in Google AI Studio. Authentication: Requires a Google AI API Key from Google AI Studio. Provide the key via GEMINI_API_KEY or GOOGLE_API_KEY environment variables, or pass it in the plugin configuration. 
import { genkit } from 'genkit';
import { googleAI } from '@genkit-ai/google-genai';

const ai = genkit({
  plugins: [
    googleAI(),
    // Or with an explicit API key:
    // googleAI({ apiKey: 'your-api-key' }),
  ],
});

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Using Vertex AI (vertexAI)

Suitable for applications leveraging Google Cloud’s AI infrastructure. Authentication Methods:
  • Application Default Credentials (ADC): Standard method for production. Uses credentials from the environment (service account on GCP, user credentials from gcloud auth application-default login locally). Requires a Google Cloud Project with billing and Vertex AI API enabled.
  • Vertex AI Express Mode: Streamlined way to try Vertex AI features using just an API key, without billing setup. Ideal for quick experimentation with generous free tier quotas. Learn more about Express Mode. 
import { genkit } from 'genkit';
import { vertexAI } from '@genkit-ai/google-genai';

const ai = genkit({
  plugins: [
    // Using Application Default Credentials (Recommended for full features)
    vertexAI({ location: 'us-central1' }), // Regional endpoint
    // vertexAI({ location: 'global' }),      // Global endpoint

    // OR

    // Using Vertex AI Express Mode (Easy to start, some limitations)
    // vertexAI({ apiKey: process.env.VERTEX_EXPRESS_API_KEY }),
  ],
});
Note: When using Express Mode, don’t provide projectId and location in the plugin config.

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Using Both Google AI and Vertex AI

You can configure both plugins to access models or features from both services: 
import { genkit } from 'genkit';
import { googleAI, vertexAI } from '@genkit-ai/google-genai';

const ai = genkit({
  plugins: [
    googleAI(),
    vertexAI(),
  ],
});

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Available Models

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Gemini Models

  • gemini-2.5-flash - Fast, efficient model for most tasks
  • gemini-2.5-pro - Advanced reasoning and complex tasks
  • gemini-1.5-flash - Previous generation fast model
  • gemini-1.5-pro - Previous generation advanced model

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Image Generation

  • imagen-3.0-generate-002 - High-quality image generation

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Embeddings

  • gemini-embedding-001 - Text embeddings (Google AI)
  • text-embedding-005 - Text embeddings (Vertex AI)

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Music Generation (Vertex AI Only)

  • lyria-002 - AI music generation

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Usage Examples

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Text Generation with Google AI

import { genkit } from 'genkit';
import { googleAI } from '@genkit-ai/google-genai';

const ai = genkit({
  plugins: [googleAI()],
});

const response = await ai.generate({
  model: googleAI.model('gemini-2.5-flash'),
  prompt: 'Tell me something interesting about Google AI.',
});

console.log(response.text());

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Text Generation with Vertex AI

import { genkit } from 'genkit';
import { vertexAI } from '@genkit-ai/google-genai';

const ai = genkit({
  plugins: [vertexAI()],
});

const response = await ai.generate({
  model: vertexAI.model('gemini-2.5-pro'),
  prompt: 'Explain Vertex AI in simple terms.',
});

console.log(response.text());

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Text Embedding

With Google AI: 
import { genkit } from 'genkit';
import { googleAI } from '@genkit-ai/google-genai';

const ai = genkit({
  plugins: [googleAI()],
});

const embeddings = await ai.embed({
  embedder: googleAI.embedder('gemini-embedding-001'),
  content: 'Embed this text.',
});
With Vertex AI: 
import { genkit } from 'genkit';
import { vertexAI } from '@genkit-ai/google-genai';

const ai = genkit({
  plugins: [vertexAI()],
});

const embeddings = await ai.embed({
  embedder: vertexAI.embedder('text-embedding-005'),
  content: 'Embed this text.',
});

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Image Generation (Imagen)

With Google AI: 
import { genkit } from 'genkit';
import { googleAI } from '@genkit-ai/google-genai';

const ai = genkit({
  plugins: [googleAI()],
});

const response = await ai.generate({
  model: googleAI.model('imagen-3.0-generate-002'),
  prompt: 'A beautiful watercolor painting of a castle in the mountains.',
});

const generatedImage = response.media();
With Vertex AI: 
import { genkit } from 'genkit';
import { vertexAI } from '@genkit-ai/google-genai';

const ai = genkit({
  plugins: [vertexAI()],
});

const response = await ai.generate({
  model: vertexAI.model('imagen-3.0-generate-002'),
  prompt: 'A beautiful watercolor painting of a castle in the mountains.',
});

const generatedImage = response.media();

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Music Generation (Lyria - Vertex AI Only)

import { genkit } from 'genkit';
import { vertexAI } from '@genkit-ai/google-genai';

const ai = genkit({
  plugins: [vertexAI()],
});

const response = await ai.generate({
  model: vertexAI.model('lyria-002'),
  prompt: 'A relaxing, instrumental piano track.',
});

const generatedAudio = response.media();

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Key Differences

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Google AI (googleAI)

  • Easier setup for smaller projects
  • Great for prototyping with Google AI Studio
  • Uses API keys for authentication
  • Access to Gemini and Imagen models

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Vertex AI (vertexAI)

  • Enterprise-ready with Google Cloud IAM
  • Integrates with other Vertex AI services
  • Broader range of models and features
  • Supports Lyria music generation
  • Fine-tuning capabilities
  • Robust governance and compliance
  • Express Mode for easy experimentation

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