LLM table output React

LLM table output in React with validated Ace Grid results

LLM table output becomes more useful when it is structured, validated, and rendered as an interactive grid instead of a static markdown table.

Open AI output docs Open AI Schema docs

Parse a versioned result, not arbitrary JSX props

Ask the model for a constrained object with version, kind, view data, provenance, validation issues, and suggested commands. Validate the complete object or validated stream chunks before mapping allowed fields to Ace Grid props. Ace Grid schema documents use a version field; application wrappers may add their own result identifier and generation timestamp.

Render every state deliberately

Show progress while rows stream, preserve a text fallback, report schema errors without discarding raw output, and keep citations available beside the grid. Do not let partial columns or changing row IDs corrupt selection and editing.

Separate display from mutation

Rendering an answer can be automatic after validation. Applying commands should require policy checks, current authorization, user approval, and a server-side mutation. Return per-row outcomes so the grid can show partial success or failure.

Handle streaming without corrupting identity

If rows arrive incrementally, assign stable IDs and avoid replacing column definitions after users begin interacting. Buffer incomplete objects until they validate. Preserve selection and scroll when appending results. If the model revises an existing row, make that update explicit and retain provenance. Streaming convenience should not make the visible result internally inconsistent.

Test adversarial and malformed output

Send missing IDs, duplicate columns, unknown commands, oversized payloads, invalid values, stale citations, and prompt-injected instructions. Confirm validation rejects unsafe shapes and the UI falls back without applying actions. Limit row, column, text, and command sizes before rendering. Treat model output as untrusted external data even when the model is hosted internally.

Render validation errors as product states

Invalid model output should not crash the page or silently disappear. Show a readable fallback, preserve authorized diagnostics, and explain what failed. If citations are missing, display the limitation. If columns are partial, wait until a valid shape is available. Treat validation failure as a normal state in the React component, not an exceptional afterthought.

Never apply generated commands directly

An LLM result can suggest actions, but the application must map them to allow-listed commands, require user approval when needed, and send them to a server that rechecks authorization and row versions. The grid can display suggested actions and outcomes, but model output is not permission. This is the safety distinction that makes Ace Grid relevant for serious LLM table output.

Use stable row IDs from the model contract

React rendering needs stable keys, and grid interaction needs stable row identity. The model contract should require row IDs or provide enough source identity for the application to assign deterministic IDs. Without stable IDs, streaming updates can corrupt selection, focus, validation, and command targeting.

Limit what reaches the Grid component

Map validated data into known Ace Grid props. Do not spread model output into the grid. This prevents prompt-injected fields or unsupported options from changing UI behavior and creates a clear frontend security boundary for LLM table output in React.

Model the React state machine

Use explicit states for receiving, buffering, validating, invalid, ready, awaiting approval, applying, partially applied, complete, and failed. Buffer incomplete streamed objects until they validate. Keep stable column definitions and deterministic row IDs once interaction begins. Preserve a readable fallback and authorized diagnostics when validation fails instead of crashing or silently discarding the answer.

Test a streamed result fixture

Stream columns followed by rows with stable IDs, then send a corrected row, a duplicate ID, an unknown command, a missing citation, and an oversized value. Confirm invalid chunks do not enter the Grid component, valid appended rows preserve scroll and selection, revisions remain explicit, and suggested commands cannot execute without server authorization. This fixture covers the failures most likely to corrupt an interactive LLM table.

Return row-level command outcomes

When a user approves a suggested operation, send stable target IDs and the allow-listed command to the server. Return saved, rejected, conflicted, forbidden, or retryable outcomes for each row. Update the grid from authoritative responses and preserve failed rows for correction. This keeps partial execution visible and prevents a successful-looking assistant message from hiding rejected business changes.

Validate before rendering an LLM table result

import { Grid } from "@ace-grid/enterprise";
import { validateGridSchemaDocument } from "@ace-grid/schema-ai";

export function AssistantGridResult({ result }) {
  const validation = validateGridSchemaDocument(result);

  if (!validation.valid) {
    return (
      <section role="alert">
        <h3>The assistant result could not be rendered</h3>
        <pre>{JSON.stringify(validation.issues, null, 2)}</pre>
      </section>
    );
  }

  const view = validation.value.kind === "view"
    ? validation.value
    : validation.value.view;

  if (!view?.data?.rows || !view.data.columnDefs) {
    return <p>The assistant returned no table data.</p>;
  }

  return (
    <Grid
      data={{ rows: view.data.rows, columns: view.data.columnDefs }}
      layout={{ width: 1200, height: 420 }}
      columns={{ columnWidths: {}, fillWidth: true }}
    />
  );
}

Sources