docs: add memoization recipe (#4116)

content/cookbook/01-next/25-markdown-chatbot-with-memoization.mdx

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+---
+title: Markdown Chatbot with Memoization
+description: Learn how to build a performant chatbot that renders Markdown responses and uses memoization for optimal performance with Next.js and the AI SDK.
+tags: ['next', 'streaming', 'chatbot', 'markdown']
+---
+
+# Markdown Chatbot with Memoization
+
+When building a chatbot with Next.js and the AI SDK, you'll likely want to render the model's responses in Markdown format using a library like `react-markdown`. However, this can have negative performance implications as the Markdown is re-rendered on each new token received from the streaming response.
+
+As conversations get longer and more complex, this performance impact becomes exponentially worse since the entire conversation history is re-rendered with each new token.
+
+This recipe uses memoization - a performance optimization technique where the results of expensive function calls are cached and reused to avoid unnecessary re-computation. In this case, parsed Markdown blocks are memoized to prevent them from being re-parsed and re-rendered on each token update, which means that once a block is fully parsed, it's cached and reused rather than being regenerated. This approach significantly improves rendering performance for long conversations by eliminating redundant parsing and rendering operations.
+
+## Server
+
+On the server, you use a simple route handler that streams the response from the language model.
+
+```tsx filename='app/api/chat/route.ts'
+import { openai } from '@ai-sdk/openai';
+import { streamText } from 'ai';
+
+export const maxDuration = 60;
+
+export async function POST(req: Request) {
+  const { messages } = await req.json();
+
+  const result = streamText({
+    system:
+      'You are a helpful assistant. Respond to the user in Markdown format.',
+    model: openai('gpt-4o'),
+    messages,
+  });
+
+  return result.toDataStreamResponse();
+}
+```
+
+## Memoized Markdown Component
+
+Next, create a memoized markdown component that will take in raw Markdown text into blocks and only updates when the content actually changes. This component splits Markdown content into blocks using the `marked` library to identify discrete Markdown elements, then uses React's memoization features to optimize re-rendering by only updating blocks that have actually changed.
+
+```tsx filename='components/memoized-markdown.tsx'
+import { marked } from 'marked';
+import { memo, useMemo } from 'react';
+import ReactMarkdown from 'react-markdown';
+
+function parseMarkdownIntoBlocks(markdown: string): string[] {
+  const tokens = marked.lexer(markdown);
+  return tokens.map(token => token.raw);
+}
+
+const MemoizedMarkdownBlock = memo(
+  ({ content }: { content: string }) => {
+    return <ReactMarkdown>{content}</ReactMarkdown>;
+  },
+  (prevProps, nextProps) => {
+    if (prevProps.content !== nextProps.content) return false;
+    return true;
+  },
+);
+
+MemoizedMarkdownBlock.displayName = 'MemoizedMarkdownBlock';
+
+export const MemoizedMarkdown = memo(
+  ({ content, id }: { content: string; id: string }) => {
+    const blocks = useMemo(() => parseMarkdownIntoBlocks(content), [content]);
+
+    return blocks.map((block, index) => (
+      <MemoizedMarkdownBlock content={block} key={`${id}-block_${index}`} />
+    ));
+  },
+);
+
+MemoizedMarkdown.displayName = 'MemoizedMarkdown';
+```
+
+## Client
+
+Finally, on the client, use the `useChat` hook to manage the chat state and render the chat interface. You can use the `MemoizedMarkdown` component to render the message contents in Markdown format without compromising on performance. Additionally, you can render the form in it's own component so as to not trigger unnecessary re-renders of the chat messages. You can also use the `experimental_throttle` option that will throttle data updates to a specified interval, helping to manage rendering performance.
+
+```typescript filename='app/page.tsx'
+'use client';
+
+import { useChat } from 'ai/react';
+import { MemoizedMarkdown } from '@/components/memoized-markdown';
+
+export default function Page() {
+  const { messages } = useChat({
+    id: 'chat',
+    // Throttle the messages and data updates to 50ms:
+    experimental_throttle: 50,
+  });
+
+  return (
+    <div className="flex flex-col w-full max-w-xl py-24 mx-auto stretch">
+      <div className="space-y-8 mb-4">
+        {messages.map(message => (
+          <div key={message.id}>
+            <div className="font-bold mb-2">
+              {message.role === 'user' ? 'You' : 'Assistant'}
+            </div>
+            <div className="prose space-y-2">
+              <MemoizedMarkdown id={message.id} content={message.content} />
+            </div>
+          </div>
+        ))}
+      </div>
+      <MessageInput />
+    </div>
+  );
+}
+
+const MessageInput = () => {
+  const { input, handleSubmit, handleInputChange } = useChat({ id: 'chat' });
+  return (
+    <form onSubmit={handleSubmit}>
+      <input
+        className="fixed bottom-0 w-full max-w-xl p-2 mb-8 dark:bg-zinc-900 border border-zinc-300 dark:border-zinc-800 rounded shadow-xl"
+        placeholder="Say something..."
+        value={input}
+        onChange={handleInputChange}
+      />
+    </form>
+  );
+};
+```
+
+<Note>
+  The chat state is shared between both components by using the same `id` value.
+  This allows you to split the form and chat messages into separate components
+  while maintaining synchronized state.
+</Note>