Fixed Schema A2UI

Pre-defined A2UI schema with dynamic data. The fastest approach — no LLM schema generation needed.

"""MS Agent Framework agent for the Declarative Generative UI (A2UI — Fixed Schema) demo.Fixed-schema A2UI: the component tree (schema) is authored ahead of time asJSON and loaded at startup. The agent only streams *data* into the data modelat runtime. The frontend registers a matching catalog (see`src/app/demos/a2ui-fixed-schema/a2ui/catalog.ts`) that pins the schema'scomponent names to real React implementations.Reference:    showcase/integrations/langgraph-python/src/agents/a2ui_fixed.py"""from __future__ import annotationsimport jsonfrom pathlib import Pathfrom textwrap import dedentfrom typing import Annotatedfrom agent_framework import Agent, BaseChatClient, toolfrom agent_framework_ag_ui import AgentFrameworkAgentfrom pydantic import FieldCATALOG_ID = "copilotkit://flight-fixed-catalog"SURFACE_ID = "flight-fixed-schema"_SCHEMAS_DIR = Path(__file__).parent / "a2ui_schemas"def _load_schema(path: Path) -> list[dict]:    """Thin JSON loader — mirrors `a2ui.load_schema` from the Python SDK."""    with open(path) as f:        return json.load(f)FLIGHT_SCHEMA = _load_schema(_SCHEMAS_DIR / "flight_schema.json")BOOKED_SCHEMA = _load_schema(_SCHEMAS_DIR / "booked_schema.json")  # noqa: F841 — kept for parity with LangGraph referencedef _build_a2ui_ops(*, origin: str, destination: str, airline: str, price: str) -> dict:    """Return the `a2ui_operations` payload for the flight card.    Mirrors `a2ui.render(operations=[create_surface, update_components,    update_data_model])` from the Python SDK. The A2UI middleware detects this    container in the tool result and forwards the ops to the frontend renderer.    """    ops = [        {            "version": "v0.9",            "createSurface": {                "surfaceId": SURFACE_ID,                "catalogId": CATALOG_ID,            },        },        {            "version": "v0.9",            "updateComponents": {                "surfaceId": SURFACE_ID,                "components": FLIGHT_SCHEMA,            },        },        {            "version": "v0.9",            "updateDataModel": {                "surfaceId": SURFACE_ID,                "path": "/",                "value": {                    "origin": origin,                    "destination": destination,                    "airline": airline,                    "price": price,                },            },        },    ]    return {"a2ui_operations": ops}@tool(    name="display_flight",    description=(        "Show a flight card for the given trip. Use short airport codes "        "(e.g. 'SFO', 'JFK') for origin/destination and a price string like '$289'."    ),)def display_flight(    origin: Annotated[        str, Field(description="3-letter origin airport code (e.g. 'SFO').")    ],    destination: Annotated[        str, Field(description="3-letter destination airport code (e.g. 'JFK').")    ],    airline: Annotated[str, Field(description="Airline name (e.g. 'United').")],    price: Annotated[        str, Field(description="Price string including currency, e.g. '$289'.")    ],) -> str:    """Emit an `a2ui_operations` container describing the flight card."""    return json.dumps(        _build_a2ui_ops(            origin=origin,            destination=destination,            airline=airline,            price=price,        )    )SYSTEM_PROMPT = dedent(    """    You help users find flights. When asked about a flight, call    `display_flight` with origin, destination, airline, and price.    Keep any chat reply to one short sentence.    """).strip()def create_agent(chat_client: BaseChatClient) -> AgentFrameworkAgent:    """Instantiate the MS-Agent-backed a2ui-fixed-schema agent."""    base_agent = Agent(        client=chat_client,        name="a2ui_fixed_agent",        instructions=SYSTEM_PROMPT,        tools=[display_flight],    )    return AgentFrameworkAgent(        agent=base_agent,        name="CopilotKitMicrosoftAgentFrameworkAgent",        description="Fixed-schema A2UI flight search demo.",        require_confirmation=False,    )

In the fixed-schema approach, you design the UI schema once (by hand, or using the A2UI Composer) and keep it on the agent side. The agent tool only provides the data; the surface appears instantly when the tool returns because nothing has to be generated at runtime.

How the schema is delivered to the runtime is the only thing that varies between integrations:

Schema-loading (langgraph-python, langgraph-typescript, langgraph-fastapi, llamaindex, crewai-crews, pydantic-ai, ms-agent-python, google-adk) — the schema is saved as a .json file next to the agent and loaded once at startup.
Schema-inline (spring-ai, ms-agent-dotnet) — the schema is declared inline as a typed literal in source. The host language doesn't ship a load_schema JSON loader, so the structure is compiled in directly.
LLM-driven (mastra, strands) — the agent runs a secondary LLM call to produce the operations container per-request. The catalog is still fixed; the schema is generated on demand.

Ask about a flight and the agent renders a fully structured card from a pre-defined schema:

How it works#

The schema is made available to the agent — either loaded from a JSON file at startup, declared inline, or generated per-request, depending on the integration.
The agent's display_flight tool receives data from the primary LLM (origin / destination / airline / price).
The tool returns a2ui.render(...) with createSurface + updateComponents + updateDataModel operations.
The A2UI middleware intercepts the tool result and the frontend renders the surface using the matching 5-component client catalog (Title, Airport, Arrow, AirlineBadge, PriceTag, plus the built-ins).

Compositional schemas#

The example below ships a flight card assembled compositionally from small sub-components rather than one monolithic FlightCard:

Card
 └─ Column
     ├─ Title        ("Flight Details")
     ├─ Row          (Airport → Arrow → Airport)
     ├─ Row          (AirlineBadge · PriceTag)
     └─ Button       (Book)

That tree lives backend-side — as a JSON file, an inline literal, or a per-request LLM output, depending on the integration. Components without data bindings (like Title or Arrow) carry their value inline; components bound to the LLM's data (like Airport) reference fields via JSON Pointer paths such as { "path": "/origin" }. The A2UI binder resolves those paths before the React renderer runs, so renderer props are typed as their resolved values (plain z.string(), not a path-or-literal union).

The 5-component custom catalog#

The frontend catalog declares just the domain-specific primitives (Title, Airport, Arrow, AirlineBadge, PriceTag) and merges in CopilotKit's basic catalog (Card, Column, Row, Text, Button, …) via includeBasicCatalog: true.

Declare the component definitions#

Each component declares its props as a Zod schema. Props are the resolved values, never the path expressions:

definitions.ts

import { z } from "zod";import type { CatalogDefinitions } from "@copilotkit/a2ui-renderer";/** * Dynamic string: literal OR a data-model path binding. The GenericBinder * resolves path bindings to the actual value at render time. */const DynString = z.union([z.string(), z.object({ path: z.string() })]);export const definitions = {  /**   * Card override: gives the outer flight-card container a ShadCN look   * (rounded-xl, neutral-200 border, soft shadow). The basic catalog's   * Card uses inline styles; overriding here lets the demo's renderer   * adopt the demo's Tailwind aesthetic without touching the schema JSON.   */  Card: {    description: "A container card with a single child.",    props: z.object({      child: z.string(),    }),  },  Title: {    description: "A prominent heading for the flight card.",    props: z.object({      text: DynString,    }),  },  Airport: {    description: "A 3-letter airport code, displayed large.",    props: z.object({      code: DynString,    }),  },  Arrow: {    description: "A right-pointing arrow used between airports.",    props: z.object({}),  },  AirlineBadge: {    description: "A pill-styled airline name tag.",    props: z.object({      name: DynString,    }),  },  PriceTag: {    description: "A stylized price display (e.g. '$289').",    props: z.object({      amount: DynString,    }),  },  /**   * Button override: swaps in an ActionButton renderer that tracks   * its own `done` state so clicking "Book flight" visually updates to   * a "Booked ✓" confirmation. The basic catalog's Button is stateless,   * so without this override the click fires the action but the button   * looks unchanged. Mirrors the pattern in beautiful-chat   * (src/app/demos/beautiful-chat/declarative-generative-ui/renderers.tsx).   */  Button: {    description:      "An interactive button with an action event. Use 'child' with a Text component ID for the label. After click, the button shows a confirmation state.",    props: z.object({      child: z        .string()        .describe(          "The ID of the child component (e.g. a Text component for the label).",        ),      variant: z.enum(["primary", "secondary", "ghost"]).optional(),      // Union with { event } so GenericBinder resolves this as ACTION → callable () => void.      action: z        .union([          z.object({            event: z.object({              name: z.string(),              context: z.record(z.any()).optional(),            }),          }),          z.null(),        ])        .optional(),    }),  },} satisfies CatalogDefinitions;

Implement the React renderers#

TypeScript enforces that the renderer map's keys and prop shapes match the definitions exactly, so refactors stay safe:

renderers.tsx

export const renderers: CatalogRenderers<Definitions> = {  /**   * Card override: ShadCN-style outer container. The basic catalog's Card   * uses inline styles; overriding here keeps the demo's tailwind aesthetic.   * The flight schema renders Card > Column > [Title, Row, …]; the inner   * Column adds the vertical spacing.   */  Card: ({ props, children }) => (    <Card className="w-full max-w-md p-5" data-testid="a2ui-fixed-card">      {props.child ? children(props.child) : null}    </Card>  ),  Title: ({ props }) => (    <div className="flex items-center justify-between">      <div className="space-y-1">        <p className="text-[11px] font-medium uppercase tracking-[0.14em] text-neutral-500">          Itinerary        </p>        <h3 className="text-base font-semibold leading-none tracking-tight text-neutral-900">          {s(props.text)}        </h3>      </div>      <Badge variant="outline" className="font-mono">        1-stop · economy      </Badge>    </div>  ),  Airport: ({ props }) => (    <div className="flex flex-col items-center">      <span className="font-mono text-2xl font-semibold tracking-wider text-neutral-900">        {s(props.code)}      </span>    </div>  ),  Arrow: () => (    <div className="flex flex-1 items-center px-3">      <Separator className="flex-1 bg-neutral-200" />      <svg        width="16"        height="16"        viewBox="0 0 24 24"        fill="none"        stroke="currentColor"        strokeWidth="2"        strokeLinecap="round"        strokeLinejoin="round"        className="mx-1 text-neutral-400"        aria-hidden      >        <line x1="5" y1="12" x2="19" y2="12" />        <polyline points="12 5 19 12 12 19" />      </svg>      <Separator className="flex-1 bg-neutral-200" />    </div>  ),  AirlineBadge: ({ props }) => (    <Badge variant="secondary" className="uppercase tracking-[0.08em]">      {s(props.name)}    </Badge>  ),  PriceTag: ({ props }) => (    <div className="flex items-baseline gap-1">      <span className="text-[11px] font-medium uppercase tracking-[0.14em] text-neutral-500">        Total      </span>      <span className="font-mono text-base font-semibold text-neutral-900">        {s(props.amount)}      </span>    </div>  ),  /**   * Button override: this is a pure-presentation demo, so the button just   * renders its label. The schema declares an `action` for visual fidelity,   * but the click handler is inert until the Python SDK exposes   * `action_handlers=` on `a2ui.render` (see `src/agents/a2ui_fixed.py`).   */  Button: ({ props, children }) => (    <UIButton className="w-full">      {props.child ? children(props.child) : null}    </UIButton>  ),};

Wire the catalog#

createCatalog(..., { includeBasicCatalog: true }) merges the custom renderers with CopilotKit's built-ins so the schema can reference Card, Column, Row, Button alongside the domain primitives:

catalog.ts

import { createCatalog } from "@copilotkit/a2ui-renderer";import { definitions } from "./definitions";import { renderers } from "./renderers";export const CATALOG_ID = "copilotkit://flight-fixed-catalog";export const catalog = createCatalog(definitions, renderers, {  catalogId: CATALOG_ID,  includeBasicCatalog: true,});

Load the schema JSON at startup#

a2ui.load_schema(path) (or the framework's equivalent thin json.load wrapper) parses the schema file once at module-import time. The sibling booked_schema.json is kept ready for the button-click "booked" optimistic swap (see the note on action handlers below):

a2ui_fixed.py

from __future__ import annotationsimport jsonfrom pathlib import Pathfrom textwrap import dedentfrom typing import Annotatedfrom agent_framework import Agent, BaseChatClient, toolfrom agent_framework_ag_ui import AgentFrameworkAgentfrom pydantic import FieldCATALOG_ID = "copilotkit://flight-fixed-catalog"SURFACE_ID = "flight-fixed-schema"_SCHEMAS_DIR = Path(__file__).parent / "a2ui_schemas"def _load_schema(path: Path) -> list[dict]:    """Thin JSON loader — mirrors `a2ui.load_schema` from the Python SDK."""    with open(path) as f:        return json.load(f)FLIGHT_SCHEMA = _load_schema(_SCHEMAS_DIR / "flight_schema.json")BOOKED_SCHEMA = _load_schema(_SCHEMAS_DIR / "booked_schema.json")  # noqa: F841 — kept for parity with LangGraph reference

Return render operations from the tool#

The agent tool returns a2ui.render(operations=[…]). The A2UI middleware detects the operations container in the tool result and forwards it to the frontend renderer. The LLM only generates the four data fields (origin, destination, airline, price); the schema does the rest:

a2ui_fixed.py

from __future__ import annotationsimport jsonfrom pathlib import Pathfrom textwrap import dedentfrom typing import Annotatedfrom agent_framework import Agent, BaseChatClient, toolfrom agent_framework_ag_ui import AgentFrameworkAgentfrom pydantic import FieldCATALOG_ID = "copilotkit://flight-fixed-catalog"SURFACE_ID = "flight-fixed-schema"_SCHEMAS_DIR = Path(__file__).parent / "a2ui_schemas"def _load_schema(path: Path) -> list[dict]:    """Thin JSON loader — mirrors `a2ui.load_schema` from the Python SDK."""    with open(path) as f:        return json.load(f)FLIGHT_SCHEMA = _load_schema(_SCHEMAS_DIR / "flight_schema.json")BOOKED_SCHEMA = _load_schema(_SCHEMAS_DIR / "booked_schema.json")  # noqa: F841 — kept for parity with LangGraph referencedef _build_a2ui_ops(*, origin: str, destination: str, airline: str, price: str) -> dict:    """Return the `a2ui_operations` payload for the flight card.    Mirrors `a2ui.render(operations=[create_surface, update_components,    update_data_model])` from the Python SDK. The A2UI middleware detects this    container in the tool result and forwards the ops to the frontend renderer.    """    ops = [        {            "version": "v0.9",            "createSurface": {                "surfaceId": SURFACE_ID,                "catalogId": CATALOG_ID,            },        },        {            "version": "v0.9",            "updateComponents": {                "surfaceId": SURFACE_ID,                "components": FLIGHT_SCHEMA,            },        },        {            "version": "v0.9",            "updateDataModel": {                "surfaceId": SURFACE_ID,                "path": "/",                "value": {                    "origin": origin,                    "destination": destination,                    "airline": airline,                    "price": price,                },            },        },    ]    return {"a2ui_operations": ops}

Why compositional beats monolithic#

A single big FlightCard component would be faster to write but would lock the design in place. Assembling the card from Card / Column / Row / Title / Airport / Arrow / AirlineBadge / PriceTag gives you:

Reusable primitives — the same Airport renderer works in search results, booking confirmations, and future seat maps.
Schema-level design iteration — re-arranging rows or swapping a badge requires only a JSON edit; the renderer code is untouched.
A2UI Composer compatibility — hand-written and Composer-built schemas share the same primitive vocabulary.

Registering the runtime#

On the TypeScript side, A2UI's middleware auto-detects the operations in any tool result, so even with a fixed schema, the minimum setup is a2ui: {}. The a2ui-fixed-schema cell happens to also keep injectA2UITool: true so the same agent can be pointed at dynamic-schema workflows later without re-configuring.

app/api/copilotkit/route.ts

const runtime = new CopilotRuntime({
  agents: { "a2ui-fixed-schema": agent },
  a2ui: { injectA2UITool: true, agents: ["a2ui-fixed-schema"] },
});

Action handlers (reference)#

The canonical reference pairs fixed schemas with action_handlers={...} to declare optimistic UI swaps (e.g. replacing the flight schema with BOOKED_SCHEMA when the user clicks "Book"). The Python SDK's a2ui.render does not yet accept action_handlers, so the cell omits them; the booked_schema.json sibling is retained so the swap can be wired up the moment the SDK exposes the handler kwarg.

When available, a button declares its action like this:

{
  "Button": {
    "label": "Book",
    "action": {
      "name": "book_flight",
      "context": [
        { "key": "flightNumber", "value": { "path": "/flightNumber" } },
        { "key": "price", "value": { "path": "/price" } }
      ]
    }
  }
}

And the Python tool matches it with a handler keyed by the action name (plus a "*" catch-all). Until the SDK lands, see the reference fixed-schema guide for the full pattern.

When should I use fixed schemas?#

The surface is well-known: flight cards, product tiles, order summaries, dashboards.
You want deterministic, designer-controlled UI. No LLM schema drift.
You want the fastest possible first paint; no secondary LLM call.

If the UI must adapt per prompt, reach for dynamic schemas instead.