You have a Vue 3 app and want to add AI chat. By the end of this guide, you'll have a streaming chat component powered by TanStack AI and OpenAI.
Tip: If you'd prefer not to sign up with individual AI providers, OpenRouter gives you access to 300+ models with a single API key and is the easiest way to get started.
npm install @tanstack/ai @tanstack/ai-vue @tanstack/ai-openai
# or
pnpm add @tanstack/ai @tanstack/ai-vue @tanstack/ai-openai
# or
yarn add @tanstack/ai @tanstack/ai-vue @tanstack/ai-openai
Vue apps typically use a separate backend. Here's an Express server that streams chat responses:
import express from 'express'
import { chat, toServerSentEventsResponse } from '@tanstack/ai'
import { openaiText } from '@tanstack/ai-openai'
const app = express()
app.use(express.json())
app.post('/api/chat', async (req, res) => {
const { messages, conversationId } = req.body
if (!process.env.OPENAI_API_KEY) {
res.status(500).json({ error: 'OPENAI_API_KEY not configured' })
return
}
try {
const stream = chat({
adapter: openaiText('gpt-4o'),
messages,
conversationId,
})
const response = toServerSentEventsResponse(stream)
res.writeHead(response.status, Object.fromEntries(response.headers))
const body = response.body
if (body) {
const reader = body.getReader()
const pump = async () => {
const { done, value } = await reader.read()
if (done) {
res.end()
return
}
res.write(value)
await pump()
}
await pump()
}
} catch (error) {
res.status(500).json({
error: error instanceof Error ? error.message : 'An error occurred',
})
}
})
app.listen(3000, () => console.log('Server running on port 3000'))
Tip: Any backend that returns the TanStack AI SSE format works -- you can use Fastify, Hono, Nitro, or any other Node.js framework.
Create a Chat.vue component using the useChat composable:
<script setup lang="ts">
import { ref } from 'vue'
import { useChat, fetchServerSentEvents } from '@tanstack/ai-vue'
const input = ref('')
const { messages, sendMessage, isLoading } = useChat({
connection: fetchServerSentEvents('/api/chat'),
})
function handleSubmit() {
if (input.value.trim() && !isLoading.value) {
sendMessage(input.value)
input.value = ''
}
}
</script>
<template>
<div class="chat">
<div class="messages">
<div
v-for="message in messages.value"
:key="message.id"
:class="message.role"
>
<strong>{{ message.role === 'assistant' ? 'Assistant' : 'You' }}</strong>
<div v-for="(part, idx) in message.parts" :key="idx">
<p v-if="part.type === 'text'">{{ part.content }}</p>
</div>
</div>
</div>
<form @submit.prevent="handleSubmit">
<input
v-model="input"
placeholder="Type a message..."
:disabled="isLoading.value"
/>
<button type="submit" :disabled="!input.trim() || isLoading.value">
Send
</button>
</form>
</div>
</template>
Create a .env file (or .env.local depending on your setup) with your API key:
# OpenRouter (recommended — access 300+ models with one key)
OPENROUTER_API_KEY=sk-or-...
# OpenAI
OPENAI_API_KEY=your-openai-api-key
Your server reads this key at runtime. Never expose it to the browser.
Reactive state uses ShallowRef. The useChat composable returns state wrapped in DeepReadonly<ShallowRef<>>. Access values with .value in both <script> and <template>:
<script setup lang="ts">
// In script, use .value
if (isLoading.value) { /* ... */ }
const count = messages.value.length
</script>
<template>
<!-- In template, also use .value (these are ShallowRefs, not regular refs) -->
<span v-if="isLoading.value">Loading...</span>
<span>{{ messages.value.length }} messages</span>
</template>
Automatic cleanup. The composable calls onScopeDispose internally, so in-flight requests are stopped when the component unmounts. No manual cleanup needed.
Same API shape as React. If you're coming from @tanstack/ai-react, the Vue composable returns the same properties (messages, sendMessage, isLoading, error, status, stop, reload, clear). The only difference is the ShallowRef wrapper.
You now have a working Vue chat application. The useChat composable handles: