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Built-in Agent (TanStack AI)Agent Config

Agent Config

Forward typed configuration from your UI into the agent's reasoning loop.

You have a working agent and want the user to be able to tune how it behaves: tone, expertise level, response length, language, persona. By the end of this guide, your UI will own a typed config object that the agent reads on every run and rebuilds its system prompt from.

When to use this#

Reach for agent config whenever the agent's behaviour depends on user-controllable settings that don't fit naturally as chat input:

  • Tone, voice, persona: "playful", "formal", "casual"
  • Expertise level: "beginner", "intermediate", "expert"
  • Response shape: short / medium / long, structured / prose, language
  • Domain switches: which knowledge base to consult, which tool subset to enable

If the values are a channel the user occasionally tunes (a settings panel, a toolbar of selects), agent config is the right shape. If the values are content the agent should write back to (notes, a document, a plan), use Shared State instead.

Live Demo: Built-in Agent (TanStack AI) — agent-configOpen full demo →

How agent config flows from the UI into the agent's reasoning loop depends on your runtime architecture. Agents living behind a runtime read it from agent state on every run, while in-process agents receive the same object as forwarded properties on the provider — same UX, slightly different wiring on each side.

How it works#

The runtime owns the agent in-process, so config travels through the provider rather than agent state. There's no separate backend service to push state into, and no extra plumbing — the typed object you set on <CopilotKit> becomes the input to the agent factory directly.

The UI side passes the typed object as properties on the provider:

frontend/src/app/page.tsx — config flows through the provider
tsx
<CopilotKit
  runtimeUrl="/api/copilotkit"
  properties={{ tone, expertise, responseLength }}
  useSingleEndpoint
>
  <Demo />
</CopilotKit>

The runtime hands the same object to the agent factory on every call as input.forwardedProps. The factory uses those fields to build a system prompt before returning the agent for that turn:

backend/agent factory — synthesise the system prompt per turn
ts
export const agentConfigFactory = async (input: AgentFactoryInput) => {
  const { tone, expertise, responseLength } = input.forwardedProps ?? {};
  const systemPrompt = buildSystemPrompt(tone, expertise, responseLength);
  return makeAgent({ systemPrompt /* ... */ });
};
Supported by
Built-in Agent (TanStack AI)LangGraph (Python)LangGraph (TypeScript)LangGraph (FastAPI)Google ADKMastraCrewAI (Crews)PydanticAIClaude Agent SDK (Python)Claude Agent SDK (TypeScript)AgnoAG2LlamaIndexAWS StrandsLangroidMS Agent Framework (Python)MS Agent Framework (.NET)Spring AI
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When to use thisHow it works