reboot-chat-app

name	reboot-chat-app
description	Use Reboot to build AI Chat Apps (MCP Apps) for ChatGPT, Claude, VSCode, Goose, and others.
argument-hint	["<app-description>"]
allowed-tools	Bash, Read, Write, Glob, Grep, Edit

/reboot-chat-app — Build Reboot AI Chat Apps

Build complete Reboot AI Chat Apps from a user description.

Installation

From GitHub

Add the Reboot skills marketplace and install the plugin:

# 1. Add the marketplace (one-time).
claude plugin marketplace add reboot-dev/reboot-skills

# 2. Install the plugin.
claude plugin install reboot-chat-app@reboot-skills

If you install the plugin within claude with /plugin you need to restart for the configuration and skill to load correctly.

Or add to your project's .claude/settings.json so teammates are automatically offered the plugin on first use:

{
  "extraKnownMarketplaces": {
    "reboot-skills": {
      "source": {
        "source": "github",
        "repo": "reboot-dev/reboot-skills"
      }
    }
  },
  "enabledPlugins": {
    "reboot-chat-app@reboot-skills": true
  }
}

Local (repo checked out)

If you have the reboot-skills repo cloned locally:

claude --plugin-dir /path/to/reboot-skills

When to Use

• Building a new Reboot AI Chat App from a description
• Adding features, state, or UI to an existing Reboot AI Chat App
• Modifying state model, methods, or React UI in a Reboot AI Chat App

Workflow: Plan First, Then Build

Always enter plan mode before writing code. The state model is the foundation — getting entities, field types, or method types wrong means regenerating everything across 12+ files.

Plan Phase

1. Analyze the user's description using the State Model Assessment below
2. Enter plan mode (EnterPlanMode)
3. Present the proposed design:
   • User type and its methods (as the MCP front door to the application types discussed below, creating new ones and locating existing ones)
   • Application types: state shape (fields, types, tags)
   • Method map: which operations, which method type (Reader/ Writer/Transaction/Workflow), which get UI()
   • Tool surface: what the AI will see as callable tools
4. Get user approval before writing any files
5. Then execute the Step-by-Step Build Flow

For updates to existing apps, still plan: read current state, propose changes, confirm, then modify.

State Model Assessment

Before writing code, analyze the user's request:

1. Application types: What primary things is the user managing? (counter, inventory, chat thread, etc.) Each becomes its own Type with its own state.
2. User methods: How does the AI create instances of application types? Each gets a Transaction on User that calls <Type>.create(context).
3. State shape: Fields, types — lists, nested objects, primitives. Each gets Field(tag=N). Nested Model subobjects (preferences, profile, config — owned 1:1 by a parent state) must be Optional[X] = Field(tag=N, default=None) and hydrated in the parent's factory create Writer; nested Models can't take default= or default_factory= (Gotcha #21). For collections, prefer list[Item] with default_factory=list over a single-nested wrapper.
4. Operations: Map to the right method type:
   • Reader — read-only queries
   • Writer — single-state mutations
   • Transaction — multi-state atomic operations (e.g., transfer between two accounts, or User creating an application type instance)
   • Workflow — long-running control flows with loops, scheduling, and idempotency helpers
5. Tool surface: Which operations need UIs (UI())? Which need explicit tool exposure (mcp=Tool())?
6. Identity: Single default instance vs multiple instances?
7. Cross-state coordination: Does any operation touch multiple state instances? If yes, use Transaction.

Key Framework Concepts

User and Application Types

Every AI Chat App has a User type and one or more application types:

• User is auto-constructed for each authenticated user. Its state is typically empty. Its methods are Transactions that create instances of application types, or Readers that find the IDs of existing application type instances in indexes that have well-known IDs of their own.
• Application types (e.g., Counter) hold the actual application state. They need a create Writer with factory=True for construction.

Tool Exposure Control

Every method must explicitly declare its MCP exposure:

• mcp=Tool(): Expose the method as an AI-callable tool. Required on every method — including User methods — that the AI should be able to call.
• mcp=None: Hide the method from the AI. Use for human-only actions or to reduce context bloat.
• Tool() options: Tool(name="custom_name", title="Title") to override the default tool name or add a human-readable title.

Method Types

• UI(): Opens a React UI in the AI chat interface. Takes request= (config type or None), path= (web dir relative to project root), title=, description=. No servicer implementation needed — the React app IS the implementation. When request= is a Model type, its fields are passed to the React component as props.
• Writer: Single-state mutations. Context: WriterContext. Use factory=True on the create method of application types.
• Reader: Read-only queries. Context: ReaderContext.
• Transaction: Multi-state atomic operations. Context: TransactionContext. Use when an operation must modify multiple state instances atomically, or when User creates application type instances.
• Workflow: Long-running control flows. Context: WorkflowContext. Implemented as @classmethod (not instance method). Support context.loop() for periodic/reactive loops, scheduling with timedelta, and idempotency helpers.

Declarative, Not Decorator

All MCP surface is defined in the API file. main.py is minimal. No @mcp.tool() decorators.

State is Durable

State survives restarts. Set dev run --application-name=<name> in .rbtrc to persist across dev restarts. Use uv run rbt dev expunge --application-name=<name> to reset.

Project Structure

<project>/
├── .python-version          # "3.10"
├── .rbtrc                   # Line-based config (NOT YAML!)
├── pyproject.toml           # Python deps (uv)
├── api/
│   └── <pkg>/v1/
│       └── <name>.py        # API definition
├── backend/
│   └── src/
│       ├── main.py          # Application entrypoint
│       └── servicers/
│           └── <name>.py    # Servicer implementation
└── web/
    ├── package.json
    ├── tsconfig.json
    ├── tsconfig.app.json
    ├── tsconfig.node.json
    ├── vite.config.ts
    ├── index.css            # Theme variables
    └── ui/
        └── <ui-name>/
            ├── index.html
            ├── main.tsx     # RebootClientProvider entry
            ├── App.tsx      # React component
            └── App.module.css

Step-by-Step Build Flow

Only execute after plan approval. All commands run from the application directory.

1. Create .python-version, pyproject.toml, .rbtrc

2. uv sync

3. Write API definition (api/<pkg>/v1/<name>.py)

4. uv run rbt generate

5. Write servicer (backend/src/servicers/<name>.py)

6. Write main.py

7. npm create @reboot-dev/ui

8. cd web && npm install

9. uv run rbt generate (React bindings need node_modules)

10. Customize React UIs: edit App.tsx files in web/ui/*/

11. cd web && npm run build

12. Create mcp_servers.json with {"mcpServers":{"<name>":{"url":"http://localhost:9991/mcp","useOAuth":true}}}

13. STOP. Do NOT run the app yourself. Print the following run instructions exactly, then wait:

    Project directory: <absolute path to the current working directory>
    
    To run (each in a separate terminal, from the project directory):
    
      uv run rbt dev run          # start backend
      cd web && npm run dev        # HMR frontend (separate terminal)
    
    To test with MCP inspector (separate terminal):
    
      npx @mcpjam/inspector@2.4.0 --config mcp_servers.json --server <name>
    

    Replace <name> with the actual server name from mcp_servers.json. Print the real absolute path of the project directory (not the literal placeholder). Then suggest a first prompt the user can try in the inspector (e.g., "Create a new todo list and show it to me").

Inline Patterns

All patterns below are complete and copy-paste-ready. Replace <project-name>, <pkg>, <name>, <ui-name> with actual values.

.python-version

3.10

.rbtrc

Line-based config. NOT YAML!

# Find API definitions in 'api/'.
generate api/

# Tell `rbt generate` where to put generated files.
generate --python=backend/api/

# Generate React bindings for web apps (into "web/api/").
generate --react=web/api
generate --react-extensions

# Watch if any source files are modified.
dev run --watch=backend/**/*.py

# Tell `rbt` that this is a Python application.
dev run --python

# Save state between restarts.
dev run --application-name=<project-name>

# Run the application!
dev run --application=backend/src/main.py

# Default to HMR mode when no --config is specified.
dev run --default-config=hmr

# Hot Module Replacement (HMR): Vite dev server proxied through Envoy.
# Run Vite in a separate terminal: cd web && npm run dev
# Envoy routes "/__/web/**" to Vite for HMR support.
dev run:hmr --mcp-frontend-host=http://localhost:4444

# Dist mode: serve pre-built artifacts from "web/dist/" (no Vite HMR).
# Usage: uv run rbt dev run --config=dist
# Requires: cd web && npm run build
dev run:dist --mcp-frontend-host=""

# When expunging, expunge that state we've saved.
dev expunge --application-name=<project-name>

pyproject.toml

[project]
name = "<project-name>"
version = "0.1.0"
requires-python = ">= 3.10"
dependencies = [
    "httpx>=0.27,<1.0",
    "uuid7>=0.1.0",
    "anyio>=4.0.0",
    "reboot>=1.0.4",
]

[tool.rye]
dev-dependencies = [
    "mypy==1.18.1",
    "types-protobuf>=4.24.0.20240129",
    "reboot>=1.0.4",
]

virtual = true
managed = true

API Definition (api/<pkg>/v1/<name>.py)

Rules:

• Import only the method types you use from reboot.api
• Helper Model types as standalone classes
• State model with Field(tag=N) on every field
• User type with empty state and Transaction methods that create application type instances
• Application types with their own state and methods
• All methods need explicit mcp=Tool() (AI-callable) or mcp=None (hidden from AI)
• Application types need a create Writer with factory=True
• api = API(User=Type(...), <AppType>=Type(...))

Simple Example (Counter)

from reboot.api import (
    API,
    UI,
    Field,
    Methods,
    Model,
    Reader,
    Tool,
    Transaction,
    Type,
    Writer,
)


# -- User models. --


class CreateCounterResponse(Model):
    counter_id: str = Field(tag=1)


class UserState(Model):
    pass


# -- Counter models. --


class CounterState(Model):
    value: int = Field(tag=1, default=0)
    description: str = Field(tag=2, default="")


class ValueResponse(Model):
    value: int = Field(tag=1)


class AmountRequest(Model):
    """Request with an amount parameter."""
    amount: int = Field(tag=1)


api = API(
    User=Type(
        state=UserState,
        methods=Methods(
            create_counter=Transaction(
                request=None,
                response=CreateCounterResponse,
                description="Create a new Counter. Returns "
                "the ID of the new counter. That ID is not "
                "human-readable; pass it to future tool "
                "calls where needed, but no need to tell "
                "the human what it is.",
                mcp=Tool(),
            ),
        ),
    ),
    Counter=Type(
        state=CounterState,
        methods=Methods(
            show_clicker=UI(
                request=None,
                path="web/ui/clicker",
                title="Counter Clicker",
                description="Interactive clicker UI for "
                "the counter.",
            ),
            create=Writer(
                request=None,
                response=None,
                factory=True,
                mcp=None,
            ),
            get=Reader(
                request=None,
                response=ValueResponse,
                description="Get the current counter value.",
                mcp=Tool(),
            ),
            increment=Writer(
                request=AmountRequest,
                response=None,
                description="Increment the counter by the "
                "specified amount.",
                mcp=Tool(),
            ),
            decrement=Writer(
                request=AmountRequest,
                response=None,
                description="Decrement the counter by the "
                "specified amount.",
                mcp=Tool(),
            ),
        ),
    ),
)

Parameterized UI Example

When the AI should pass parameters to a React UI (e.g., a personalized message or configuration), use request= with a Model type. The fields become React component props:

class DashboardConfig(Model):
    """Configuration passed by the AI."""
    personalized_message: str = Field(tag=1)


# In the application type's Methods():
show_dashboard=UI(
    # The AI provides a DashboardConfig when opening this UI.
    # The fields are passed to the React component as props.
    request=DashboardConfig,
    path="web/ui/dashboard",
    title="Counter Dashboard",
    description="Dashboard UI. Use `personalized_message` to "
    "impart wisdom on the topic of counting things.",
),

The React component receives the config fields as props:

import {
  type DashboardConfig,
  useCounter,
} from "@api/<pkg>/v1/<name>_rbt_react";

export const DashboardApp: FC<DashboardConfig> = ({ personalizedMessage }) => {
  const counter = useCounter();
  const { response } = counter.useGet();
  // personalizedMessage is available as a prop.
  return (
    <div>
      {personalizedMessage}: {response?.value ?? 0}
    </div>
  );
};

mcp=None Example

Hide a method from the AI (e.g., for human-only actions):

# In an application type's Methods():
# Only callable from the React UI, not by the AI.
confirm_dangerous_action=Writer(
    request=ConfirmRequest,
    response=None,
    description="Confirm a dangerous action.",
    mcp=None,
),

List State Patterns

For application types with list-based state (items, entries, messages, etc.):

• Define helper Model types as standalone classes (e.g., class Item(Model)) — NOT nested on the application type
• Use list[Item] in the state with default_factory=list
• Add CRUD Writers: add, remove, toggle, reorder as needed
• Each Writer validates indices before mutating
• The reorder pattern uses pop + insert
• In the servicer, import helpers standalone: from <pkg>.v1.<name> import Item

The counter example above shows the full User + application type pattern. Apply the same structure for any application type, adding whatever Writers and Readers your app needs.

Nested Model State Patterns

For application types that own a single nested Model sub-object (preferences blob, profile, config, etc.):

• Declare the field as Optional[Sub] = Field(tag=N, default=None). Nested non-Optional Model types reject both default= and default_factory= (Gotcha #21).
• Hydrate the sub-object in the parent's factory create Writer, so callers never observe the None:

from reboot.api import API, Field, Methods, Model, Transaction, Type, User as RbtUser, Writer
from typing import Optional

class GuestPreferences(Model):
    meal_type: str = Field(tag=1, default="")
    calorie_level: str = Field(tag=2, default="")
    dietary_restrictions: str = Field(tag=3, default="")

class Guest(Model):
    name: str = Field(tag=1, default="")
    # Single nested Model: Optional + default=None, populated
    # by the factory `create` below.
    preferences: Optional[GuestPreferences] = Field(tag=2, default=None)

class CreateRequest(Model):
    name: str = Field(tag=1)
    meal_type: str = Field(tag=2, default="")
    calorie_level: str = Field(tag=3, default="")
    dietary_restrictions: str = Field(tag=4, default="")

# Servicer side (in `backend/src/servicers/<name>.py`):
class GuestServicer(Guest.Servicer):
    async def create(self, context, *, name, meal_type, calorie_level, dietary_restrictions):
        self.state.name = name
        self.state.preferences = GuestPreferences(
            meal_type=meal_type,
            calorie_level=calorie_level,
            dietary_restrictions=dietary_restrictions,
        )

If the prompt suggests plural sub-objects ("each guest's preferences"), prefer list[GuestPreferences] with default_factory=list — lists are exempt from this rule.

Workflow Example (Long-Running)

Use Workflow for periodic or long-running operations:

from reboot.api import (
    API,
    Field,
    Methods,
    Model,
    Tool,
    Type,
    Workflow,
)


class DoPingPeriodicallyRequest(Model):
    num_pings: int = Field(tag=1)
    period_seconds: float = Field(tag=2)


class DoPingPeriodicallyResponse(Model):
    num_pings: int = Field(tag=1)


# In an application type's Methods():
do_ping_periodically=Workflow(
    request=DoPingPeriodicallyRequest,
    response=DoPingPeriodicallyResponse,
)

Servicer (backend/src/servicers/<name>.py)

Rules:

• Import helper types standalone: from <pkg>.v1.<name> import MyItem
• Import generated classes: from <pkg>.v1.<name>_rbt import User, Counter
• Each type gets its own servicer class (e.g., UserServicer, CounterServicer)
• User.Servicer / Counter.Servicer base
• Context types from reboot.aio.contexts:
  • ReaderContext — read-only
  • WriterContext — single-state mutation
  • TransactionContext — multi-state atomic
  • WorkflowContext — long-running (@classmethod)
• Access state via self.state.<field>
• Request types: Counter.XxxRequest, response: Counter.XxxResponse

Simple Servicer (Counter)

from ai_chat_counter.v1.counter_rbt import Counter, User
from reboot.aio.contexts import (
    ReaderContext,
    TransactionContext,
    WriterContext,
)


class UserServicer(User.Servicer):

    async def create_counter(
        self,
        context: TransactionContext,
    ) -> User.CreateCounterResponse:
        """Create a new Counter and return its ID."""
        # Factory create: pass request fields as keyword args
        # directly — do NOT wrap in a Request object.
        # No-args: Counter.create(context)
        # With args: Counter.create(context, title="...", count=0)
        counter, _ = await Counter.create(context)
        return User.CreateCounterResponse(
            counter_id=counter.state_id,
        )


class CounterServicer(Counter.Servicer):

    async def create(self, context) -> None:
        # State is initialized with defaults; nothing to do.
        pass

    async def increment(
        self,
        context: WriterContext,
        request: Counter.IncrementRequest,
    ) -> None:
        self.state.value += request.amount

    async def decrement(
        self,
        context: WriterContext,
        request: Counter.DecrementRequest,
    ) -> None:
        self.state.value -= request.amount

    async def get(
        self,
        context: ReaderContext,
    ) -> Counter.GetResponse:
        return Counter.GetResponse(value=self.state.value)

Workflow Servicer

Workflow methods are @classmethod — no self, no self.state. To call back into the current instance, use the state class imported from <name>_rbt (e.g. MyType.ref()), NOT cls. Inside a Workflow, calling <StateClass>.ref() with no arguments is special: it picks up the current state_id from WorkflowContext automatically, so MyType.ref() resolves to a ref to the running workflow's own instance.

from datetime import timedelta
from reboot.aio.contexts import WorkflowContext
# Import the state class — this is what `.ref()` is called on,
# NOT `cls`. `cls` inside the classmethod is `MyTypeBaseServicer`.
from <pkg>.v1.<name>_rbt import MyType


class MyTypeServicer(MyType.Servicer):

    @classmethod
    async def do_ping_periodically(
        cls,
        context: WorkflowContext,
        request: MyType.DoPingPeriodicallyRequest,
    ) -> MyType.DoPingPeriodicallyResponse:
        async for iteration in context.loop(
            "Ping periodically",
            interval=timedelta(seconds=request.period_seconds),
        ):
            # `MyType.ref()` with no args is Workflow-only magic:
            # it reads `state_id` from `WorkflowContext`, returning
            # a ref to this workflow's own instance. Do NOT write
            # `cls.ref()` or `self.ref()` here — see Critical
            # Gotcha #19.
            await MyType.ref().do_ping(context)
            pings_sent = iteration + 1  # iteration starts at 0.
            if pings_sent >= request.num_pings:
                break

        # `.read()` is only valid on the workflow's own no-arg
        # ref; a foreign-state read like
        # `OtherType.ref(id).read(context)` raises a "only
        # supported within workflows" RuntimeError. Call a Reader
        # method on the foreign type instead — see Gotcha #23.
        state = await MyType.ref().read(context)
        return MyType.DoPingPeriodicallyResponse(
            num_pings=state.num_pings,
        )

Use inline writers for workflow-only state changes. When the mutation is only ever performed by this workflow, do not add a separate store_xxx Writer to the API just so the workflow can call it. Pass an async (state) -> ... function to .idempotently("alias").write(context, fn):

async def increment_count(state):
    state.num_pings += 1

await MyType.ref().idempotently(
    "Increment ping count",
).write(context, increment_count)

The idempotency alias is a human-readable string that survives workflow restarts — the inline writer runs at most once per alias. Anti-pattern: defining a store_count Writer in the API just so the workflow can await MyType.ref().store_count(context) to bump a counter. That adds an unnecessary indirection. Reserve declared Writers for operations that are also called from outside the workflow.

For "run every time" (e.g., re-fetching a remote value on each loop iteration), use .always().write(context, fn) instead of .idempotently("...").write(...).

Scheduling a Workflow from a Transaction

A workflow can only be await-ed directly from an ExternalContext (e.g. a bootstrap script) or from another WorkflowContext. In any other context — most commonly a TransactionContext kicking off a workflow on a state it just created — the workflow must be scheduled, not awaited directly. Use .schedule() to fire-and-forget from a transaction:

# In a User's Transaction method that creates a Game and wants
# its autoplay workflow to start running:
class UserServicer(User.Servicer):

    async def create_game(
        self,
        context: TransactionContext,
        request: User.CreateGameRequest,
    ) -> User.CreateGameResponse:
        game, _ = await Game.create(context, ...)
        # GOOD — schedule the workflow from the transaction.
        # Request type is empty (`AutoplayRequest`), so just
        # pass `context`:
        await Game.ref(game.state_id).schedule().autoplay(context)
        # If the workflow request had fields (e.g.
        # `do_ping_periodically(num_pings, period_seconds)`),
        # pass them as keyword args:
        await Game.ref(game.state_id).schedule().do_ping_periodically(
            context,
            num_pings=10,
            period_seconds=1.0,
        )
        # BAD — wrapping in `request=` raises
        # `TypeError: ... got an unexpected keyword argument
        # 'request'` (Gotcha #9):
        # await Game.ref(game.state_id).schedule().autoplay(
        #     context, request=Game.AutoplayRequest()
        # )
        # BAD — awaiting a workflow directly from a Transaction
        # raises `TypeError: ... 'Autoplay' is a workflow and
        # must be scheduled from a 'TransactionContext' via
        # `await [...].schedule([...]).Autoplay(context, [...])`
        # (Gotcha #20):
        # await Game.ref(game.state_id).autoplay(context)
        return User.CreateGameResponse(game_id=game.state_id)

.schedule(when=timedelta(...)) delays the workflow by a duration. .schedule() with no argument starts it as soon as the transaction commits.

Same rule from a WriterContext or ReaderContext: use .schedule(). Only ExternalContext and WorkflowContext can await a workflow directly.

main.py

Register all servicers (User + application types):

import asyncio
import logging
from reboot.aio.applications import Application
from servicers.<name> import (
    CounterServicer,
    UserServicer,
)

logging.basicConfig(
    level=logging.INFO,
    format="%(asctime)s - %(name)s - %(levelname)s - %(message)s",
)


async def main() -> None:
    application = Application(
        servicers=[UserServicer, CounterServicer],
    )
    await application.run()


if __name__ == "__main__":
    asyncio.run(main())

web/package.json

Use explicit per-UI build scripts as shown below. Do NOT create a build.js or any auto-discovery wrapper — use npm run build:<name> scripts directly.

{
  "name": "<project-name>-web",
  "version": "0.1.0",
  "private": true,
  "type": "module",
  "scripts": {
    "dev": "vite",
    "build:<ui-name>": "vite build --mode <ui-name>",
    "build:watch:<ui-name>": "vite build --mode <ui-name> --watch",
    "build": "tsc --noEmit && npm run build:<ui-name>",
    "build:watch": "concurrently \"npm:build:watch:*\""
  },
  "dependencies": {
    "@modelcontextprotocol/ext-apps": "1.5.0",
    "@modelcontextprotocol/sdk": "1.29.0",
    "@reboot-dev/reboot-react": "1.0.4",
    "@reboot-dev/reboot-api": "1.0.4",
    "react": "^18.2.0",
    "react-dom": "^18.2.0",
    "zod": "^3.25.0"
  },
  "devDependencies": {
    "@types/react": "^18.2.67",
    "@types/react-dom": "^18.2.22",
    "@vitejs/plugin-react": "^4.7.0",
    "concurrently": "^9.1.2",
    "typescript": "^5.9.2",
    "vite": "^6.3.5",
    "vite-plugin-singlefile": "^2.0.3"
  }
}

For multiple UIs, add build:<name> and build:watch:<name> entries for each UI, and update the build script to chain them:

"build": "tsc --noEmit && npm run build:ui1 && npm run build:ui2"

web/vite.config.ts

CRITICAL: Copy this file EXACTLY. Do NOT refactor, generalize, or add recursive directory scanning. The flat outDir: "dist" and output: "${name}.html" pattern is required — nested output paths will break the MCP server's UI discovery.

// Vite configuration for Reboot UIs.
import fs from "fs";
import path from "path";
import react from "@vitejs/plugin-react";
import { defineConfig } from "vite";
import { viteSingleFile } from "vite-plugin-singlefile";

// Auto-discover UIs from ui/ directory.
const uiDir = path.resolve(__dirname, "ui");
const uis: Record<string, { input: string; output: string }> =
  Object.fromEntries(
    fs
      .readdirSync(uiDir)
      .filter((d) => fs.existsSync(path.join(uiDir, d, "index.html")))
      .map((name) => [
        name,
        { input: `ui/${name}/index.html`, output: `${name}.html` },
      ])
  );

export default defineConfig(({ command, mode }) => {
  // Path alias for API imports (@api/... -> ./api/...).
  const resolve = {
    alias: {
      "@api": path.resolve(__dirname, "./api"),
    },
    dedupe: ["react", "react-dom", "zod"],
  };

  // Dev server configuration.
  //
  // UIs use a double iframe architecture:
  //   MCP Host -> srcdoc (origin=null) -> iframe (origin=localhost:9991)
  //
  // The inner iframe loads from Envoy ("/__/web/**"), which proxies
  // to Vite. Because the inner iframe has a real origin, Vite's URLs
  // work normally. `base: "/__/web/"` ensures all paths route through
  // Envoy.
  //
  // Hot Module Replacement works automatically: Vite's client connects
  // to the page's origin, and Envoy proxies WebSocket upgrades to
  // Vite. This also works with tunnels (ngrok) since the tunnel
  // points to Envoy.
  if (command === "serve") {
    const port = parseInt(process.env.RBT_VITE_PORT || "4444", 10);

    return {
      plugins: [react()],
      root: ".",
      resolve,
      base: "/__/web/",
      server: {
        port,
        strictPort: true,
        // Listen on all interfaces since requests come through
        // Envoy (and tunnels).
        host: true,
        allowedHosts: true,
      },
    };
  }

  // Build mode: `vite build --mode <ui-name>`
  const ui = uis[mode];
  if (!ui) {
    const valid = Object.keys(uis).join(", ");
    throw new Error(`Unknown UI: ${mode}. Use --mode with: ${valid}`);
  }

  return {
    plugins: [react(), viteSingleFile()],
    build: {
      outDir: "dist",
      emptyOutDir: false,
      assetsInlineLimit: 100000000,
      cssCodeSplit: false,
      rollupOptions: {
        input: ui.input,
        output: {
          inlineDynamicImports: true,
          entryFileNames: ui.output.replace(".html", ".js"),
          assetFileNames: ui.output.replace(".html", ".[ext]"),
        },
      },
    },
    resolve,
  };
});

web/tsconfig.json

{
  "files": [],
  "references": [
    { "path": "./tsconfig.app.json" },
    { "path": "./tsconfig.node.json" }
  ]
}

web/tsconfig.app.json

{
  "compilerOptions": {
    "tsBuildInfoFile": "./node_modules/.tmp/tsconfig.app.tsbuildinfo",
    "target": "ES2022",
    "useDefineForClassFields": true,
    "lib": ["ES2022", "DOM", "DOM.Iterable"],
    "module": "ESNext",
    "skipLibCheck": true,
    "moduleResolution": "bundler",
    "allowImportingTsExtensions": true,
    "verbatimModuleSyntax": true,
    "moduleDetection": "force",
    "noEmit": true,
    "jsx": "react-jsx",
    "strict": true,
    "noUnusedLocals": true,
    "noUnusedParameters": true,
    "noFallthroughCasesInSwitch": true,
    "baseUrl": ".",
    "paths": {
      "@api/*": ["./api/*"]
    }
  },
  "include": ["ui"]
}

web/tsconfig.node.json

{
  "compilerOptions": {
    "tsBuildInfoFile": "./node_modules/.tmp/tsconfig.node.tsbuildinfo",
    "target": "ES2023",
    "lib": ["ES2023"],
    "module": "ESNext",
    "skipLibCheck": true,
    "moduleResolution": "bundler",
    "allowImportingTsExtensions": true,
    "verbatimModuleSyntax": true,
    "moduleDetection": "force",
    "noEmit": true,
    "strict": true,
    "noUnusedLocals": true,
    "noUnusedParameters": true,
    "noFallthroughCasesInSwitch": true
  },
  "include": ["vite.config.ts"]
}

web/index.css

:root {
  --color-bg: #1a1a2e;
  --color-bg-dark: #0f0f1a;
  --color-border: #2d2d4a;
  --color-text: #e0e0e0;
  --color-text-muted: #888899;
  --color-green: #4ade80;
  --color-blue: #60a5fa;
  --color-yellow: #fbbf24;
  --color-pink: #f472b6;
  --color-purple: #a78bfa;
  --color-orange: #fb923c;
  --font-mono: ui-monospace, SFMono-Regular, "SF Mono", Menlo, Consolas,
    monospace;
}

[data-theme="light"] {
  --color-bg: #f8f9fa;
  --color-bg-dark: #e9ecef;
  --color-border: #dee2e6;
  --color-text: #212529;
  --color-text-muted: #6c757d;
  --color-green: #16a34a;
  --color-blue: #2563eb;
  --color-yellow: #ca8a04;
  --color-pink: #db2777;
  --color-purple: #7c3aed;
  --color-orange: #ea580c;
}

* {
  box-sizing: border-box;
  margin: 0;
  padding: 0;
}

body {
  font-family: var(--font-mono);
  background: var(--color-bg);
  color: var(--color-text);
}

web/ui/<ui-name>/index.html

<!DOCTYPE html>
<html lang="en">
  <head>
    <meta charset="UTF-8" />
    <meta name="viewport" content="width=device-width, initial-scale=1.0" />
    <title><UI Title></title>
  </head>
  <body>
    <div id="root"></div>
    <script type="module" src="./main.tsx"></script>
  </body>
</html>

web/ui/<ui-name>/main.tsx

import { StrictMode } from "react";
import { createRoot } from "react-dom/client";
import { RebootClientProvider } from "@reboot-dev/reboot-react";
import { ClickerApp } from "./App";
import "../../index.css";

createRoot(document.getElementById("root")!).render(
  <StrictMode>
    <RebootClientProvider>
      <ClickerApp />
    </RebootClientProvider>
  </StrictMode>
);

web/ui/<ui-name>/App.tsx

Generated hook usage — use<Type>() returns reader hooks and mutation functions. Both reads and writes go directly to the Reboot backend:

import { useCounter } from "@api/<pkg>/v1/<name>_rbt_react";

// useCounter() connects to the Counter state instance.
const counter = useCounter();

// Reader (WebSocket subscription, auto-updates):
const { response, isLoading } = counter.useGet();
const value = response?.value ?? 0;

// Writer (direct call to Reboot backend):
await counter.increment({ amount: 1 });

For list state, the same pattern applies — use the generated hook for the application type and call its methods:

// Python from_index -> TypeScript fromIndex (camelCase)
await myType.reorderItem({ fromIndex: 0, toIndex: 1 });
await myType.addItem({ text: "New item" });

Full Counter App.tsx Example

import { useEffect, useRef, useState, type FC } from "react";
import { useCounter } from "@api/ai_chat_counter/v1/counter_rbt_react";
import css from "./App.module.css";

export const ClickerApp: FC = () => {
  const [isPending, setIsPending] = useState(false);
  const counter = useCounter();
  const { response, isLoading } = counter.useGet();

  const prevValueRef = useRef<number | null>(null);
  const [trend, setTrend] = useState<"up" | "down" | "same" | null>(null);

  const value = response?.value ?? 0;

  useEffect(() => {
    if (response?.value !== undefined) {
      if (prevValueRef.current !== null) {
        if (response.value > prevValueRef.current) {
          setTrend("up");
        } else if (response.value < prevValueRef.current) {
          setTrend("down");
        } else {
          setTrend("same");
        }
      }
      prevValueRef.current = response.value;
    }
  }, [response?.value]);

  const handleIncrement = async () => {
    setIsPending(true);
    try {
      await counter.increment({ amount: 1 });
    } finally {
      setIsPending(false);
    }
  };

  const handleDecrement = async () => {
    setIsPending(true);
    try {
      await counter.decrement({ amount: 1 });
    } finally {
      setIsPending(false);
    }
  };

  const trendIcon = trend === "up" ? "↑" : trend === "down" ? "↓" : "→";
  const trendClass =
    trend === "up" ? css.trendUp : trend === "down" ? css.trendDown : "";

  if (isLoading && response === undefined) {
    return (
      <div className={css.container}>
        <div className={css.loading}>loading...</div>
      </div>
    );
  }

  return (
    <div className={css.container}>
      <div className={css.row}>
        <button
          onClick={handleDecrement}
          disabled={isPending}
          className={css.buttonDecrement}
        >
          −
        </button>
        <div className={css.valueGroup}>
          <div
            className={`${css.counter} ${trendClass} ${
              isPending ? css.pending : ""
            }`}
          >
            {value}
          </div>
          {trend && (
            <span className={`${css.trend} ${trendClass}`}>{trendIcon}</span>
          )}
        </div>
        <button
          onClick={handleIncrement}
          disabled={isPending}
          className={css.buttonIncrement}
        >
          +
        </button>
      </div>
      <span className={`${css.syncStatus} ${isPending ? css.visible : ""}`}>
        syncing...
      </span>
    </div>
  );
};

web/ui/<ui-name>/App.module.css

.container {
  background: var(--color-bg);
  color: var(--color-text);
  font-family: var(--font-mono);
  display: flex;
  flex-direction: column;
  align-items: center;
  justify-content: center;
  padding: 24px 20px 16px;
  gap: 12px;
}

.row {
  display: flex;
  align-items: center;
  gap: 12px;
}

.valueGroup {
  display: flex;
  align-items: baseline;
  gap: 4px;
  min-width: 80px;
  justify-content: center;
}

.counter {
  font-size: 36px;
  font-weight: bold;
  color: var(--color-text);
  transition: color 0.15s ease, opacity 0.15s ease;
}

.counter.pending {
  opacity: 0.7;
}

.counter.trendUp {
  color: var(--color-green);
  text-shadow: 0 0 12px rgba(74, 222, 128, 0.25);
}

.counter.trendDown {
  color: var(--color-pink);
  text-shadow: 0 0 12px rgba(244, 114, 182, 0.25);
}

.trend {
  font-size: 18px;
  font-weight: bold;
  transition: color 0.15s ease;
}

.trendUp {
  color: var(--color-green);
}

.trendDown {
  color: var(--color-pink);
}

.button {
  width: 40px;
  height: 40px;
  font-size: 20px;
  font-family: var(--font-mono);
  border: none;
  border-radius: 6px;
  cursor: pointer;
  transition: all 0.15s ease;
  display: flex;
  align-items: center;
  justify-content: center;
}

.button:disabled {
  cursor: not-allowed;
  opacity: 0.6;
}

.buttonIncrement {
  composes: button;
  background: var(--color-green);
  color: var(--color-bg-dark);
}

.buttonDecrement {
  composes: button;
  background: var(--color-pink);
  color: var(--color-bg-dark);
}

.syncStatus {
  color: var(--color-yellow);
  font-size: 11px;
  height: 14px;
  opacity: 0;
  transition: opacity 0.15s ease;
}

.syncStatus.visible {
  opacity: 1;
}

.loading {
  color: var(--color-text-muted);
  font-size: 12px;
}

Adapt the CSS module to your app's needs. The CSS variables from index.css provide consistent theming.

Critical Gotchas

1. .rbtrc is line-based, NOT YAML. Each line is a command with flags. Comments start with #.

2. No __init__.py in api/ directories. The generator scans all .py files; __init__.py causes conflicts.

3. Field(tag=N) required on every field. Tags must be unique within each Model class. Start at 1. Defaults: State fields must use proto3 zero-value defaults: default=0 for int, default="" for str, default=False for bool, default_factory=list for lists. Non-zero defaults like default="red" or default=1 are NOT supported (protobuf limitation). Set initial values in a servicer method marked as a factory instead. Request/response fields need no default.

4. Helper Model types are standalone imports: from <pkg>.v1.<name> import MyItem — NOT Counter.MyItem (that doesn't exist).

5. Generated class only has: .State, .Servicer, .XxxRequest, .XxxResponse.

6. React bindings use camelCase: Python from_index becomes TypeScript fromIndex.

7. Every method requires explicit mcp=. Use mcp=Tool() to expose a method as an AI-callable tool (required on all types, including User). Use mcp=None to hide it from the AI.

8. Application types need factory=True on their create Writer method.

9. Method call signatures: pass request fields as kwargs, never wrap in a Request object. This applies to every call shape — factory constructors, regular Writers/Readers/ Transactions, and .schedule().method() for workflows. Right shapes:

   • Type.constructor_method(context, field=val, ...)
   • Type.ref(id).some_method(context, field=val, ...)
   • Type.ref(id).schedule().my_workflow(context, field=val, ...)
   • For empty request types, omit fields entirely: Type.ref(id).schedule().autoplay(context).

   Wrong:

   • Type.constructor_method(context, request=Type.ConstructorMethodRequest(...))
   • Type.ref(id).some_method(context, request=Type.SomeMethodRequest(...))

   The request= kwarg raises TypeError: ... got an unexpected keyword argument 'request' at runtime.

10. npm install before second rbt generate — React bindings need node_modules to exist.

11. Generated React hook: use<TypeName>() — e.g., useCounter(), useInventory(), etc.

12. Generated React import path: @api/<pkg>/v1/<name>_rbt_react

13. Generated Python import path: from <pkg>.v1.<name>_rbt import User, Counter

14. Use --default-config=hmr in .rbtrc (not --default=hmr).

15. UI(path="web/ui/<name>") — path is relative to project root.

16. UI(request=<ConfigType>) passes config as React component props. UI(request=None) passes no props.

17. Register all servicers in main.py: Application(servicers=[UserServicer, CounterServicer]).

18. The requests and responses on the frontend are always Zod types generated from the Python Models.

19. Inside a Workflow classmethod, cls is the servicer, not the state class. To call methods on the running instance, use the state class imported from <name>_rbt: await MyType.ref().some_method(context). A no-arg .ref() inside a Workflow picks up state_id from WorkflowContext automatically. Do NOT write cls.ref() — it fails with TypeError: <YourType>BaseServicer.ref() missing 1 required positional argument: 'self', because ref on the BaseServicer is an instance method, not the state-class factory. self.ref() is also wrong because there is no self in a classmethod.

20. Workflows must be scheduled, not awaited, from a TransactionContext/WriterContext/ReaderContext. Only ExternalContext and WorkflowContext can await a workflow directly. From a transaction that kicks off a workflow on a state it just created, use .schedule(): await MyType.ref(id).schedule().autoplay(context). Writing await MyType.ref(id).autoplay(context) from a transaction raises TypeError: ... '<Method>' is a workflow and must be scheduled from a 'TransactionContext' via await [...].schedule([...]).(context, [...])``. See the "Scheduling a Workflow from a Transaction" example in the Workflow Servicer section.

21. Nested Model fields can't take default_factory or default. Two related rules — both raise UserPydanticError at startup, not at field-construction time, so they look like runtime errors but are static schema problems:

    • default_factory= is only supported for list and dict. Field(tag=N, default_factory=MyModel) raises Field <X> in model <Y> uses default_factory which is not supported for type <T>. Only list, dict types can have a default_factory currently.
    • A non-Optional Model-typed field also can't take default=, even with an instance: Field <X> in model <Y> is a non-optional Model type and cannot have a default value. Use Optional for Model types with empty default.

    The fix is to declare the field optional and construct lazily, e.g. preferences: Optional[UserPreferences] = Field(tag=N, default=None), then materialize it inside the servicer (or in a factory create method) when the parent state is first written.

22. .per_workflow() is implicit; don't write it. Inside a workflow, MyType.ref().read(context) and MyType.ref().write(context, fn) already pick the right semantics: .always() inside an until block, .per_iteration() inside a context.loop, and .per_workflow() everywhere else. Only reach for an explicit .per_iteration() (override the default to per-iteration when not inside a loop) or .always() (re-run every time). A plain MyType.ref().per_workflow().some_method(context) adds nothing beyond MyType.ref().some_method(context).

23. .read(context) only works on the workflow's own no-argument MyType.ref(). Inside a workflow, MyType.ref().read(context) reads the workflow's own state via the no-argument ref() (picks up state_id from WorkflowContext). A foreign read like OtherType.ref(other_id).read(context) raises RuntimeError: read() is currently only supported within workflows — the constraint isn't actually "must be inside a workflow" (you are) but "must be the workflow's own no-argument ref." For cross-state reads, call a Reader method on the target type. The same rule applies to inline .write(context, fn).

    # GOOD — workflow's own state.
    state = await MyType.ref().read(context)
    
    # GOOD — cross-state read via a Reader method.
    response = await User.ref(user_id).get_history(context)
    
    # BAD — raises the "only supported within workflows"
    # RuntimeError despite being inside one. Use a Reader.
    # user_state = await User.ref(user_id).read(context)
    

Update Flow

When modifying an existing app:

1. Read .rbtrc, API definition, servicer, main.py
2. Assess state model changes
3. Update API definition -> re-run uv run rbt generate
4. Update servicer methods
5. Update React components
6. cd web && npm run build