How to use Vercel AI's SDK to give context to your LLM.
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When building AI applications, you often need to provide context or instructions to your language model through system prompts. Here's how to pass system prompts from your client-side code to your server-side API route using the Vercel AI SDK.
On the client side, you can pass additional data like system prompts through the
bodysendMessageconst systemText: string = "Be as sycophantic as possible." sendMessage({ text: "Am i absolutely right?", }, { body: { systemText }, });
The
systemTextOn the server side (in your API route), extract the system prompt from the request body and use it in your
streamTextconst { messages, systemText } = await req.json(); const result = streamText({ model: openai("gpt-5"), system: systemText, messages: convertToModelMessages(messages), });
This pattern allows you to dynamically provide context to your language model based on client-side state or user interactions, making your AI applications more flexible and context-aware.
With the React SDK, you can handle system prompts entirely on the client side without needing a server API route. This is useful for simpler applications or when you want to keep everything client-side.
const handleGen = async (name: string) => { const systemText = `Be as sycophantic as possible for ${name}.`; const { text } = await generateText({ model: openai('gpt-5'), system: systemText, prompt: 'Am i absolutely right?' }); setResult(text); };