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Build a Chatbot with Next.js and Kyma API in 5 Minutes

April 12, 20262 min read

Update, 2026-09-21. gemini-2.5-flash, which this post suggested for long context, retires on 2026-10-20 and is no longer listed on Kyma. Use gemini-3-flash, which the long-context alias resolves to; the model list below now names it.

Chatbot in 5 min

What You'll Build

A streaming chatbot with:

  • •Real-time token streaming
  • •Switch between 6 AI models
  • •Dark navy + gold theme
  • •Deploy to Vercel in one click

Total code: under 100 lines. Total cost: free (Kyma gives you $0.50 on signup, spendable on the free tier).

Prerequisites

Step 1: Create the Project

npx create-next-app@latest my-chatbot
cd my-chatbot
npm install kyma-ai

Step 2: Add Your API Key

cp .env.example .env.local

Edit .env.local:

KYMA_API_KEY=kyma-your-actual-key

Step 3: Run

npm run dev

Open http://localhost:3000. You're chatting with qwen-3.6-plus — the most popular model on Kyma.

How It Works

The API Route (15 lines)

// app/api/chat/route.ts
import { streamText } from "ai";
import { kyma } from "@kyma-api/ai-sdk";

export async function POST(req: Request) {
  const { messages, model } = await req.json();
  const result = streamText({
    model: kyma(model || "qwen-3.6-plus"),
    messages,
    system: "You are a helpful assistant.",
  });
  return result.toUIMessageStreamResponse();
}

The kyma() function wraps the Vercel AI SDK's OpenAI-compatible provider. It reads KYMA_API_KEY from your environment automatically.

The Chat UI

The frontend uses useChat from ai/react — it handles streaming, message state, and the input form. The model selector passes the selected model via the body option.

const { messages, sendMessage, status } = useChat({
  body: { model }, // passed to the API route
});

Switch Models

The dropdown lets you switch between:

  • •qwen-3.6-plus — best overall quality
  • •deepseek-v3 — GPT-5 class, best value
  • •deepseek-r1 — chain-of-thought reasoning
  • •llama-3.3-70b — fast, all-around
  • •gemini-3-flash — 1M context window
  • •qwen-3-32b — ultra-fast coding

Each model has different strengths. Try asking the same question to different models to see the difference.

Deploy to Vercel

Deploy your chatbot to Vercel — add KYMA_API_KEY as an environment variable and you're live.

Click the button, paste your KYMA_API_KEY, and you're live.

What's Next

Cost

With $0.50 free credit on the free tier, you get roughly 500-3,000 chat messages depending on the model. A typical conversation (500 input + 200 output tokens) costs about $0.0008 with qwen-3.6-plus.