OpenUI

System Prompts

Generate and customize prompt instructions from your OpenUI library.

The system prompt tells the LLM how to output valid OpenUI Lang. Generate a serialized library spec at build time, then pass that spec to generateSystemPrompt in your backend.

Where the prompt is built

WhereUse it whenCode
CLIThe prompt is the same for every request.npx @openuidev/cli@latest generate ./src/library.ts --out system-prompt.txt, then send the file's text.
Your backendThe prompt needs tools, editMode, inlineMode, or other per-request options.generateSystemPrompt({ library: librarySpec, promptOptions })
GatewayYour backend calls models through Gateway. Gateway builds the prompt.generateSystemPrompt({ cloud: true, library: librarySpec })

Gateway accepts only preamble, examples, and additionalRules in promptOptions. It drops every other option: tools, toolExamples, toolCalls, bindings, builtinFunctions, editMode, and inlineMode. For Query, Mutation, or edit mode, build the prompt in your backend.

The sections below cover each path.

openui generate emits two outputs from the same library: a prebuilt prompt and a serialized library spec. Use the spec with generateSystemPrompt; retain the prompt only for static or legacy integrations.

pnpx @openuidev/cli@latest generate ./src/library.ts

Write to a file:

pnpx @openuidev/cli@latest generate ./src/library.ts --out system-prompt.txt

This writes the prompt to system-prompt.txt and the spec to system-prompt.spec.json. The .spec.json file is the input to generateSystemPrompt; --json-schema produces a JSON Schema for other tooling, not the library spec used to build the prompt.

The CLI auto-detects exported PromptOptions (examples, rules) alongside your library. Use --prompt-options <name> to pick a specific export.

For backends that build the prompt per request, with different tools, preambles, or feature flags, use generateSystemPrompt from @openuidev/lang-core. It has no React dependency, so it works in any Node, Edge, or serverless backend. Import the spec emitted by the command above and build the prompt at runtime:

import { generateSystemPrompt, type LibrarySpec } from "@openuidev/lang-core";
import librarySpec from "./generated/system-prompt.spec.json";

const systemPrompt = generateSystemPrompt({
  library: librarySpec as LibrarySpec,

  promptOptions: {
    // Tool descriptions, so the LLM knows what tools exist
    tools: myToolSpecs,

    // Examples showing how to use your tools with Query/Mutation
    toolExamples: [`tickets = Query("list_tickets", {}, {rows: []})\n...`],

    // Feature flags
    toolCalls: true, // Enable Query(), Mutation(), @Run (default: true if tools provided)
    bindings: true, // Enable $variables, @Set, @Reset (default: true if toolCalls)
    editMode: true, // Enable incremental editing (LLM outputs patches, not full regen)
    inlineMode: true, // Enable text + code responses (LLM can answer questions without code)

    // Preamble and extra rules
    preamble: "You build dashboards using openui-lang.",
    additionalRules: ['Use @Reset after form submit, not @Set($var, "")'],
  },
});
FlagWhat it enablesDefault
toolCallsQuery(), Mutation(), @Run, built-in functions, tool workflow rulestrue if tools provided
bindings$variables, @Set, @Reset, built-in functions, reactive filterstrue if toolCalls is true
editModeIncremental editing: the LLM outputs only changed statementsfalse
inlineModeText and fenced code: the LLM can answer without generating UIfalse
builtinFunctionsLists the built-in functions (@Count, @Sum, ...) without toolCalls or bindingstrue if toolCalls or bindings

Gateway and Autofix

Pass cloud: true with the generated library specification to emit a configuration block for Gateway or Autofix. Gateway uses it to build the system prompt. Autofix uses it to validate and repair generated OpenUI Lang against your component library. The option name is kept for compatibility.

For Gateway requests, instructions adds extra prose after the configuration block.

import { generateSystemPrompt } from "@openuidev/lang-core";
import librarySpec from "./generated/system-prompt.spec.json";

const instructions = generateSystemPrompt({
  cloud: true,
  library: librarySpec,
});

Gateway accepts preamble, examples, and additionalRules:

const instructions = generateSystemPrompt({
  cloud: true,
  library: librarySpec,
  promptOptions: { preamble: "You build dashboards for Acme." },
});

See the Generative UI Quickstart for the Gateway workflow, or the Autofix API to repair output from your existing model integration.

The prompt lists the built-in functions (@Count, @Filter, @Sort, @Each, and the rest) when either toolCalls or bindings is enabled. For static UI libraries without data fetching, they are omitted to keep the prompt concise. Set builtinFunctions: true to include them anyway. A library's own custom functions are always listed.

library.prompt() (frontend shorthand)

If you're generating prompts client-side or in a Next.js route that already imports your library:

import { openuiLibrary, openuiPromptOptions } from "@openuidev/react-ui";

const systemPrompt = openuiLibrary.prompt(openuiPromptOptions);

This is convenient but imports React components. Prefer the generated spec plus generateSystemPrompt for backend routes.

What gets generated

The generated prompt includes:

  • Syntax rules and expression types
  • Component signatures (from your registered components)
  • Built-in function reference (@Count, @Filter, @Sort, etc.), only when toolCalls, bindings, or builtinFunctions is enabled
  • Your custom functions, when the library has any
  • The Action section with the available actions, including your custom actions, when a component has an action prop or the library has custom actions
  • Query/Mutation/Action workflow (if toolCalls enabled)
  • $variable and reactive binding rules (if bindings enabled)
  • Tool descriptions and tool examples (if tools provided)
  • Edit mode instructions (if editMode enabled)
  • Inline mode instructions (if inlineMode enabled)
  • Hoisting/streaming rules
  • Your optional examples and rules

Backend usage example

import OpenAI from "openai";
import { generateSystemPrompt, type LibrarySpec } from "@openuidev/lang-core";
import librarySpec from "./generated/system-prompt.spec.json";

const client = new OpenAI({ apiKey: process.env.OPENAI_API_KEY });
const systemPrompt = generateSystemPrompt({
  library: librarySpec as LibrarySpec,
  promptOptions: { preamble: "You are a helpful assistant." },
});

export async function POST(req: Request) {
  const { messages } = await req.json();

  const completion = await client.chat.completions.create({
    model: "gpt-5.4-mini",
    stream: true,
    messages: [{ role: "system", content: systemPrompt }, ...messages],
  });

  return new Response(completion.toReadableStream(), {
    headers: { "Content-Type": "text/event-stream" },
  });
}

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