build-with-dhiraj AI Chat Response Rendering
You are an expert in rendering AI SDK v6 chat responses — UIMessage parts, tool call results, streaming states, and structured data display in React applications.
The Problem
When building chat interfaces with AI SDK v6, the raw message format includes multiple part types (text, tool calls, reasoning, images). Without proper rendering, responses appear as raw JSON or malformed output.
AI SDK v6 Message Format
In v6, messages use the UIMessage type with a parts array:
interface UIMessage {
id: string
role: 'user' | 'assistant'
parts: UIMessagePart[]
}
// Part types:
// - { type: 'text', text: string }
// - { type: 'tool-<toolName>', toolCallId: string, state: string, input?: unknown, output?: unknown }
// state values: 'partial-call' | 'call' | 'output-available' | 'approval-requested' | 'approval-responded' | 'output-denied'
// - { type: 'reasoning', text: string }
// - { type: 'step-start' } // internal, skip in rendering
Recommended: Use AI Elements
The simplest approach is to use AI Elements, which handles all part types automatically:
import { Message } from '@/components/ai-elements/message'
import { Conversation } from '@/components/ai-elements/conversation'
{messages.map((message) => (
<Message key={message.id} message={message} />
))}
⤳ skill: ai-elements — Full component library for AI interfaces
Manual Rendering Pattern
If you need custom rendering without AI Elements, follow this pattern:
'use client'
import { useChat } from '@ai-sdk/react'
import { DefaultChatTransport } from 'ai'
export function Chat() {
const { messages, sendMessage, status } = useChat({
transport: new DefaultChatTransport({ api: '/api/chat' }),
})
const isLoading = status === 'streaming' || status === 'submitted'
return (
<div>
{messages.map((message) => (
<div key={message.id}>
{message.parts?.map((part, i) => {
// 1. Text parts — render as formatted text
if (part.type === 'text' && part.text.trim()) {
return (
<div key={i} className={
message.role === 'user'
? 'bg-primary text-primary-foreground rounded-lg px-3 py-2'
: 'bg-muted rounded-lg px-3 py-2'
}>
{part.text}
</div>
)
}
// 2. Tool parts — type is "tool-<toolName>"
if (part.type.startsWith('tool-')) {
const toolPart = part as {
type: string
toolCallId: string
state: string
input?: unknown
output?: unknown
}
const toolName = toolPart.type.replace('tool-', '')
if (toolPart.state === 'output-available' && toolPart.output) {
return <ToolResultCard key={i} name={toolName} output={toolPart.output} />
}
if (toolPart.state === 'output-denied') {
return (
<div key={i} className="text-sm text-muted-foreground">
{toolName} was denied
</div>
)
}
if (toolPart.state === 'approval-requested') {
return (
<div key={i} className="text-sm text-yellow-500">
{toolName} requires approval
</div>
)
}
return (
<div key={i} className="text-sm text-muted-foreground animate-pulse">
Running {toolName}...
</div>
)
}
// 3. Reasoning parts
if (part.type === 'reasoning') {
return (
<details key={i} className="text-xs text-muted-foreground">
<summary>Thinking...</summary>
<p className="whitespace-pre-wrap">{(part as { text: string }).text}</p>
</details>
)
}
// 4. Skip unknown types (step-start, etc.)
return null
})}
</div>
))}
</div>
)
}
Rendering Tool Results as Cards
Instead of dumping raw JSON, render structured tool output as human-readable cards:
function ToolResultCard({ name, output }: { name: string; output: unknown }) {
const data = output as Record<string, unknown>
// Pattern: Check for known result shapes and render accordingly
if (data?.success && data?.issue) {
const issue = data.issue as { identifier?: string; title?: string }
return (
<div className="rounded border border-border bg-card p-2 text-sm">
<span className="font-medium text-green-400">
{name === 'createIssue' ? 'Created' : 'Updated'} {issue.identifier}
</span>
<p className="text-muted-foreground">{issue.title}</p>
</div>
)
}
if (data?.items && Array.isArray(data.items)) {
return (
<div className="rounded border border-border bg-card p-2 text-sm">
<p className="font-medium">{data.items.length} results</p>
{data.items.slice(0, 5).map((item: Record<string, unknown>, i: number) => (
<p key={i} className="text-muted-foreground">{String(item.name || item.title || item.id)}</p>
))}
</div>
)
}
if (data?.error) {
return (
<div className="rounded border border-destructive/30 bg-destructive/10 p-2 text-sm text-destructive">
{String(data.error)}
</div>
)
}
// Fallback: simple completion message (not raw JSON)
return (
<div className="rounded border border-border bg-card p-2 text-xs text-muted-foreground">
{name} completed
</div>
)
}
Server-Side Requirements
The server route must use the correct v6 response format:
// app/api/chat/route.ts
import { streamText, convertToModelMessages, gateway } from 'ai'
export async function POST(req: Request) {
const { messages } = await req.json()
// IMPORTANT: convertToModelMessages is async in v6
const modelMessages = await convertToModelMessages(messages)
const result = streamText({
model: gateway('anthropic/claude-sonnet-4.6'),
messages: modelMessages,
})
// Use toUIMessageStreamResponse for chat UIs (not toDataStreamResponse)
return result.toUIMessageStreamResponse()
}
Client-Side Requirements
import { useChat } from '@ai-sdk/react'
import { DefaultChatTransport } from 'ai'
const { messages, sendMessage, status } = useChat({
// v6 uses transport instead of api
transport: new DefaultChatTransport({ api: '/api/chat' }),
})
// v6 uses sendMessage instead of handleSubmit
sendMessage({ text: inputValue })
// Status values: 'ready' | 'submitted' | 'streaming'
const isLoading = status === 'streaming' || status === 'submitted'
Common Mistakes
1. Raw JSON in chat responses
Cause: Rendering message.content instead of iterating message.parts.
Fix: Always iterate message.parts and handle each type:
// WRONG — shows raw JSON
<div>{message.content}</div>
// RIGHT — renders each part type
{message.parts?.map((part, i) => {
if (part.type === 'text') return <span key={i}>{part.text}</span>
// ... handle other types
})}
2. Tool results showing as JSON blobs
Cause: Using JSON.stringify(output) as the display.
Fix: Create structured card components for known tool output shapes.
3. "Invalid prompt: messages do not contain..." error
Cause: Not converting UI messages to model messages on the server.
Fix: Use await convertToModelMessages(messages) — it's async in v6.
4. Messages not appearing / empty responses
Cause: Using toDataStreamResponse() instead of toUIMessageStreamResponse().
Fix: Use toUIMessageStreamResponse() when the client uses useChat with DefaultChatTransport.
5. useChat not working with v6
Cause: Using the v5 useChat({ api: '/api/chat' }) pattern.
Fix: Use DefaultChatTransport:
// v5 (old)
const { messages, handleSubmit, input } = useChat({ api: '/api/chat' })
// v6 (current)
const { messages, sendMessage, status } = useChat({
transport: new DefaultChatTransport({ api: '/api/chat' }),
})
Decision Tree
Building a chat UI with AI SDK v6?
└─ Want pre-built components?
└─ Yes → Use AI Elements (⤳ skill: ai-elements)
└─ No → Manual rendering with parts iteration
└─ Tool results look like JSON?
└─ Create ToolResultCard components for each tool's output shape
└─ Text not rendering?
└─ Check part.type === 'text' and use part.text
└─ Server errors?
└─ Check: await convertToModelMessages(), toUIMessageStreamResponse()
Server-Side Message Validation
Use validateUIMessages to validate incoming messages before processing:
import { validateUIMessages, convertToModelMessages, streamText, gateway } from 'ai'
export async function POST(req: Request) {
const { messages } = await req.json()
const validatedMessages = validateUIMessages(messages)
const modelMessages = await convertToModelMessages(validatedMessages)
// ...
}