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Using the SDK

The Reveal SDK AI Client is a TypeScript/JavaScript library that provides AI capabilities for your web applications. It exposes two main APIs — Insights for generating data analysis, and Chat for conversational analytics — both accessible through a single client instance.

Initialization​

Before using any AI features, initialize the client with your server URL:

import { RevealSdkClient } from '@revealbi/api';

RevealSdkClient.initialize({
  hostUrl: 'https://your-server.com'
});

For UMD/CDN usage:

rv.RevealSdkClient.initialize({
  hostUrl: 'https://your-server.com'
});
info

The client SDK requires the AI Server SDK to be installed and running. All AI requests are processed server-side by the configured LLM provider.

If your AI server requires authentication or additional request headers, see Request Configuration.

Getting the Client Instance​

Once initialized, get the shared client instance anywhere in your application:

const client = RevealSdkClient.getInstance();

API Surface​

The client exposes AI features through the client.ai namespace:

Insights​

Generate summaries, analyses, and forecasts from your dashboards and visualizations:

const insight = await client.ai.insights.get({
  dashboardId: 'sales-dashboard',
  type: 'summary',
});

console.log(insight.explanation);

Learn more in Insights.

Chat​

Build conversational interfaces where users interact with data using natural language:

const response = await client.ai.chat.sendMessage({
  message: 'Show me sales by region for Q4',
  datasourceId: 'my-datasource',
});

console.log(response.explanation);

Learn more in Chat.

Streaming vs Non-Streaming​

Both APIs support two response modes:

  • Non-streaming (default): Wait for the complete response. Simple and straightforward.
  • Streaming: Receive text in real-time as it's generated, providing a ChatGPT-like experience.

Add stream: true to any request to enable streaming:

const stream = await client.ai.insights.get({
  dashboardId: 'sales-dashboard',
  type: 'summary',
  stream: true,
});

stream.on('text', (content) => {
  console.log(content); // Text arrives in chunks
});

const result = await stream.finalResponse();

Learn more in Streaming Responses.