This package provides Vertex AI integrations for Genkit, including Model Garden, Rerankers, Evaluation, and Vector Search.
⚠️ Deprecation notice: The main
vertexAIplugin export (Gemini, Imagen, and embedder models) is deprecated. Please migrate to@genkit-ai/google-genai:// Before (deprecated)
import { vertexAI } from '@genkit-ai/vertexai';
// After
import { vertexAI } from '@genkit-ai/google-genai';
npm i --save @genkit-ai/vertexai
This package provides the following sub-package imports:
| Import | Description |
|---|---|
@genkit-ai/vertexai/modelgarden |
Third-party models (Claude, Mistral, Llama) via Vertex AI Model Garden |
@genkit-ai/vertexai/rerankers |
Vertex AI Rerankers API |
@genkit-ai/vertexai/evaluation |
Vertex AI evaluation metrics (BLEU, ROUGE, SAFETY, etc.) |
@genkit-ai/vertexai/vectorsearch |
Vertex AI Vector Search with BigQuery and Firestore backends |
Access third-party models (Anthropic Claude, Mistral, Llama) hosted on Vertex AI Model Garden:
import { genkit } from 'genkit';
import { vertexModelGarden } from '@genkit-ai/vertexai/modelgarden';
const ai = genkit({
plugins: [
vertexModelGarden({ projectId: 'my-project', location: 'us-central1' }),
],
});
const { text } = await ai.generate({
model: vertexModelGarden.model('claude-sonnet-4'),
prompt: 'Write a haiku about cloud computing',
});
console.log(text);
Use Vertex AI's reranking API to reorder documents by relevance:
import { genkit } from 'genkit';
import { vertexRerankers } from '@genkit-ai/vertexai/rerankers';
const ai = genkit({
plugins: [
vertexRerankers({ projectId: 'my-project', location: 'us-central1' }),
],
});
Evaluate AI output quality using Vertex AI's built-in metrics:
import { vertexAIEvaluation } from '@genkit-ai/vertexai/evaluation';
import { VertexAIEvaluationMetricType } from '@genkit-ai/vertexai/evaluation';
const ai = genkit({
plugins: [
vertexAIEvaluation({
projectId: 'my-project',
location: 'us-central1',
metrics: [
VertexAIEvaluationMetricType.BLEU,
VertexAIEvaluationMetricType.ROUGE,
VertexAIEvaluationMetricType.SAFETY,
VertexAIEvaluationMetricType.GROUNDEDNESS,
],
}),
],
});
Use Vertex AI Vector Search for retrieval-augmented generation (RAG) with BigQuery or Firestore document stores:
import { vertexAIVectorSearch } from '@genkit-ai/vertexai/vectorsearch';
const ai = genkit({
plugins: [
vertexAIVectorSearch({
projectId: 'my-project',
location: 'us-central1',
vectorSearchOptions: [
{
publicDomainName: 'my-public-endpoint.vdb.vertexai.goog',
indexEndpointId: 'my-index-endpoint-id',
indexId: 'my-index-id',
deployedIndexId: 'my-deployed-index-id',
documentRetriever: myDocRetriever,
documentIndexer: myDocIndexer,
embedder: myEmbedder,
},
],
}),
],
});
The sources for this package are in the main Genkit repo. Please file issues and pull requests against that repo.
Usage information and reference details can be found in official Genkit documentation.
License: Apache 2.0