JavaScript / TypeScript quickstart

Get up and running with Genkit in JavaScript or TypeScript in under five minutes using Gemini models via the Google AI plugin.

This guide walks you through installing Genkit, writing your first AI-powered function, and exploring it with the local Developer UI.

1. Get a Google AI API key

   Genkit’s Google AI plugin uses the Gemini API. Get a free API key from Google AI Studio.

   Set the key as an environment variable before running any Genkit code:

   export GOOGLE_GENAI_API_KEY="your-api-key"
   

   The plugin also accepts GEMINI_API_KEY and GOOGLE_API_KEY. You can alternatively pass the key directly as googleAI({ apiKey: '...' }), but using an environment variable is recommended so credentials are never committed to source control.

2. Install dependencies

   Create a new Node.js project (or open an existing one), then install Genkit and the Google AI plugin:

   npm

   npm install genkit @genkit-ai/google-genai
   

   Install the Genkit CLI globally so you can use the Developer UI:

   npm install -g genkit-cli
   
3. Write your first Genkit app

   Create src/index.ts with the following content:

   import { genkit } from 'genkit';
   import { googleAI } from '@genkit-ai/google-genai';
   
   // Initialize Genkit with the Google AI plugin.
   // The plugin reads GOOGLE_GENAI_API_KEY (or GEMINI_API_KEY) from the environment.
   const ai = genkit({
     plugins: [googleAI()],
   });
   
   // Define a flow — a traced, deployable AI function.
   const jokeFlow = ai.defineFlow('tellJoke', async (topic: string) => {
     const { text } = await ai.generate({
       model: googleAI.model('gemini-2.5-flash'),
       prompt: `Tell me a short joke about ${topic}.`,
     });
     return text;
   });
   
   // Run the flow directly when executed as a script.
   const joke = await jokeFlow('software engineers');
   console.log(joke);
   

   Run it with tsx (or compile with tsc first):

   npx tsx src/index.ts
   
4. Explore with the Developer UI

   The Genkit CLI wraps your app with tracing and launches a local Developer UI where you can run flows, inspect execution traces, and compare model outputs interactively.

   genkit start -- npx tsx src/index.ts
   

   The CLI starts your app, then opens the Developer UI at http://localhost:4000. In the UI you can:

   • Run the tellJoke flow against any input without touching your code.
   • Inspect traces to see exactly what was sent to and received from the model.
   • Tweak prompts and compare outputs across different Gemini model variants.

   Set GENKIT_ENV=dev in your environment to keep the reflection server running even outside the genkit start command, which is useful during active development.

5. Add structured output (optional)

   Genkit can validate model responses against a Zod schema and return typed objects:

   import { z } from 'genkit';
   
   const RecipeSchema = z.object({
     title: z.string(),
     ingredients: z.array(z.string()),
     steps: z.array(z.string()),
   });
   
   const recipeFlow = ai.defineFlow(
     { name: 'generateRecipe', outputSchema: RecipeSchema },
     async (dish: string) => {
       const { output } = await ai.generate({
         model: googleAI.model('gemini-2.5-flash'),
         prompt: `Create a recipe for ${dish}.`,
         output: { schema: RecipeSchema },
       });
       return output!;
     }
   );
   
   const recipe = await recipeFlow('chocolate chip cookies');
   console.log(recipe.title, recipe.ingredients);
   

Next steps

Concepts: Flows

Learn how flows add observability, retries, and HTTP exposure to any AI function.

Concepts: Models

Understand model references, config options, multimodal inputs, and streaming.

Guides: Structured output

Return validated, type-safe JSON from any model call using Zod schemas.

Guides: Streaming

Stream tokens to the client as they are generated for a faster perceived response.

Guides: Agents

Build multi-step agentic workflows with tool calling and looping.

Plugins: Google AI

Full reference for the @genkit-ai/google-genai plugin including Vertex AI, Imagen, and embeddings.

Plugins overview

Browse all available plugins: Vertex AI, Ollama, Firebase, and community providers.

Developer tools

Deep dive into the Genkit CLI and Developer UI.