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Documentation Index

Fetch the complete documentation index at: https://mintlify.com/tambo-ai/tambo/llms.txt

Use this file to discover all available pages before exploring further.

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Overview

Components are React components that the AI can dynamically render in response to user messages. Each component is registered with a name, description, and props schema that defines what data it can accept.

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TamboComponent Type

The TamboComponent interface defines how components are registered: 
interface TamboComponent {
  /** The React component to render */
  component: ComponentType<any>;
  
  /** Name used by the AI to identify this component */
  name: string;
  
  /** Description explaining the component's purpose and functionality */
  description: string;
  
  /** Zod schema defining the component's props */
  propsSchema: SupportedSchema;
  
  /** Optional loading component shown while props stream */
  loadingComponent?: ComponentType<any>;
}

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Component Field

The actual React component to render. Pass the component itself, not an instance: 
// ✅ Correct - Pass the component
const components = [{ component: MyComponent, ... }];

// ❌ Wrong - Don't instantiate
const components = [{ component: <MyComponent />, ... }];

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Name Field

A unique identifier for the component. Should be:
  • Descriptive - Indicates what the component does
  • CamelCase or PascalCase - Follows React naming conventions
  • Unique - No two components should share the same name
name: "WeatherCard"      // Good
name: "weather-card"     // Okay but not conventional
name: "Card"             // Too generic

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Description Field

Explains to the AI when and how to use this component. Should include:
  • Purpose - What the component displays or does
  • Use cases - When it should be selected
  • Data requirements - What kind of data it expects
description: "Displays current weather information including temperature, conditions, and 5-day forecast. Use when the user asks about weather or climate."

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Props Schema

Defines the component’s props using Zod or another supported schema library. The schema:
  • Validates incoming props
  • Documents available props for the AI
  • Provides types for TypeScript inference
import { z } from 'zod';

propsSchema: z.object({
  location: z.string().describe("City name or location"),
  temperature: z.number().describe("Temperature in degrees"),
  unit: z.enum(["celsius", "fahrenheit"]).default("celsius"),
  forecast: z.array(z.object({
    day: z.string(),
    high: z.number(),
    low: z.number(),
    condition: z.string(),
  })).optional(),
})

​
Loading Component

Optional component shown while props stream in from the AI: 
function WeatherCardSkeleton() {
  return (
    <div className="animate-pulse">
      <div className="h-8 bg-gray-200 rounded w-1/2 mb-4" />
      <div className="h-4 bg-gray-200 rounded w-full mb-2" />
      <div className="h-4 bg-gray-200 rounded w-3/4" />
    </div>
  );
}

const components: TamboComponent[] = [
  {
    name: "WeatherCard",
    component: WeatherCard,
    loadingComponent: WeatherCardSkeleton,
    propsSchema: weatherSchema,
    description: "Weather information display",
  },
];

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Registering Components

Components are registered by passing them to TamboProvider: 
import { TamboProvider } from '@tambo-ai/react';

const components: TamboComponent[] = [
  {
    name: "WeatherCard",
    description: "Shows weather forecast",
    component: WeatherCard,
    propsSchema: weatherSchema,
  },
  {
    name: "StockChart",
    description: "Displays stock price history",
    component: StockChart,
    propsSchema: stockSchema,
  },
];

function App() {
  return (
    <TamboProvider
      apiKey={process.env.NEXT_PUBLIC_TAMBO_API_KEY!}
      userKey="user-123"
      components={components}
    >
      <YourApp />
    </TamboProvider>
  );
}

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Component Lifecycle

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1. Registration

When TamboProvider mounts, components are registered with the internal registry and converted to tool definitions for the AI.

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2. Selection

When a user sends a message, the AI analyzes it and decides which component(s) to render based on:
  • Component descriptions
  • Available props schemas
  • Conversation context

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3. Streaming

The AI streams props to the selected component:
  1. Component renders with initial/empty props
  2. Props update as they stream in
  3. Component re-renders with new prop values
  4. Stream completes when all props are delivered

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4. Rendering

The component renders in the message thread as an assistant message with type "component".

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Component Props

Props your component receives come from two sources:

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1. Schema-defined Props

Props defined in your Zod schema, streamed from the AI: 
function WeatherCard({ location, temperature, condition }: WeatherCardProps) {
  return (
    <div>
      <h2>{location}</h2>
      <p>{temperature}°</p>
      <p>{condition}</p>
    </div>
  );
}

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2. Handling Partial Props

During streaming, props may be incomplete. Handle gracefully: 
function DataTable({ data, columns }: DataTableProps) {
  // data and columns stream in gradually
  if (!data || !columns) {
    return <Skeleton />;
  }
  
  return (
    <table>
      <thead>
        <tr>
          {columns.map(col => <th key={col}>{col}</th>)}
        </tr>
      </thead>
      <tbody>
        {data.map((row, i) => (
          <tr key={i}>
            {columns.map(col => <td key={col}>{row[col]}</td>)}
          </tr>
        ))}
      </tbody>
    </table>
  );
}

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Best Practices

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Write Clear Descriptions

Descriptions help the AI choose the right component: 
// ✅ Good - Specific and actionable
description: "Displays a list of tasks with checkboxes, due dates, and priority indicators. Use when the user wants to view or manage their task list."

// ❌ Bad - Too vague
description: "A component for tasks"

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Use Descriptive Schema Fields

Add .describe() to schema fields to help the AI understand what data to provide: 
propsSchema: z.object({
  tasks: z.array(z.object({
    title: z.string().describe("Task title or description"),
    completed: z.boolean().describe("Whether the task is completed"),
    dueDate: z.string().describe("ISO date string for when task is due"),
    priority: z.enum(["low", "medium", "high"]).describe("Task priority level"),
  })),
})

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Handle Loading States

Show something meaningful while props stream: 
function ProductGrid({ products }: { products: Product[] }) {
  if (products.length === 0) {
    return <ProductGridSkeleton />;
  }
  
  return (
    <div className="grid grid-cols-3 gap-4">
      {products.map(product => (
        <ProductCard key={product.id} product={product} />
      ))}
    </div>
  );
}

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Avoid Props Not in Schema

Only use props defined in your schema. The AI won’t provide props outside the schema: 
// ✅ Good - All props in schema
propsSchema: z.object({
  title: z.string(),
  items: z.array(z.string()),
})

function MyComponent({ title, items }: { title: string; items: string[] }) {
  return <div>...</div>;
}

// ❌ Bad - extraProp not in schema
function MyComponent({ title, items, extraProp }: { ... }) {
  // extraProp will always be undefined
}

​
TypeScript Integration

Infer prop types from your schema: 
import { z } from 'zod';

const weatherSchema = z.object({
  location: z.string(),
  temperature: z.number(),
  condition: z.string(),
});

type WeatherCardProps = z.infer<typeof weatherSchema>;

function WeatherCard({ location, temperature, condition }: WeatherCardProps) {
  return (
    <div>
      <h2>{location}</h2>
      <p>{temperature}°</p>
      <p>{condition}</p>
    </div>
  );
}

const components: TamboComponent[] = [
  {
    name: "WeatherCard",
    description: "Weather display",
    component: WeatherCard,
    propsSchema: weatherSchema,
  },
];

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Next Steps

  • Learn about Interactable Components for persistent, updatable components
  • Explore Tools to understand how components relate to the tool system
  • See Streaming for details on handling real-time prop updates
  • Check Generative UI for the high-level concept

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