Getting Started with Reveal AI Add-On

This guide will walk you through setting up the Reveal AI Add-On in your existing Reveal SDK application.

Time to Complete: 30-45 minutes

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Choose Your Platform

Platform	Package	Minimum Reveal Version
ASP.NET Core (C#)	Reveal.Sdk.AI.AspNetCore (NuGet)	1.8.4+
Node.js	reveal-sdk-node-ai (npm)	2.0.0+
Java	io.revealbi:reveal-sdk-ai (Maven)	2.0.0+

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ASP.NET Core (C#)

Prerequisites

• ✅ Reveal SDK v1.8.4+ installed and working in your ASP.NET Core app
• ✅ .NET 8.0 SDK installed
• ✅ LLM Provider account (OpenAI or Anthropic recommended)
• ✅ At least one datasource configured in Reveal SDK

Step 1a: Install NuGet Package

Using .NET CLI:

cd YourProject
dotnet add package Reveal.Sdk.AI.AspNetCore
dotnet build

Using Visual Studio:

1. Right-click on your project in Solution Explorer
2. Select "Manage NuGet Packages"
3. Select the "Browse" tab
4. Search for Reveal.Sdk.AI.AspNetCore
5. Click "Install"

1b. Optional: Install Client-Side Package

If using the JavaScript API:

npm install @revealbi/api

See the @revealbi/api npm package README for client-side usage.

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Step 2: Configure LLM Provider

Choose OpenAI (recommended for quick setup) or Anthropic Claude.

Option A: OpenAI (Recommended)

Get API Key:

1. Visit OpenAI Platform
2. Create an API key (starts with sk-)

Configure in appsettings.json:

{
  "RevealAI": {
    "DefaultClient": "openai",
    "OpenAI": {
      "ApiKey": "sk-your-api-key-here",
      "ModelId": "gpt-4.1"
    }
  }
}

Option B: Anthropic Claude

Get API Key:

1. Visit Anthropic Console
2. Create an API key (starts with sk-ant-)

Configure in appsettings.json:

{
  "RevealAI": {
    "DefaultClient": "anthropic",
    "Anthropic": {
      "ApiKey": "sk-ant-your-api-key-here",
      "ModelId": "claude-sonnet-4-5"
    }
  }
}

Tip: Store your API key in User Secrets rather than committing it to source control.

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Step 3: Register AI Services

Update your Program.cs:

using Reveal.Sdk.AI;

var builder = WebApplication.CreateBuilder(args);

// Your existing Reveal SDK setup
builder.Services.AddControllers()
    .AddReveal(revealBuilder =>
    {
        revealBuilder
            .AddAuthenticationProvider<AuthenticationProvider>()
            .AddDataSourceProvider<DataSourceProvider>()
            .AddUserContextProvider<UserContextProvider>();
    });

// Add Reveal AI services
builder.Services.AddRevealAI()
  .AddOpenAI()
  .UseMetadataCatalogFile("config/catalog.json");

var app = builder.Build();

app.UseHttpsRedirection();
app.UseAuthorization();
app.MapControllers();

app.Run();

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Step 4: Configure Metadata Generation

The AI needs metadata about your datasources. Add to appsettings.json:

{
  "RevealAI": {
    "OpenAI": {
      "ApiKey": "OPENAI_API_KEY",
      "ModelId": "gpt-4-turbo"
    },

    "MetadataService": {
      "GenerateOnStartup": true
    }
  }
}

Then list your configured datasources in your metadata catalog file (e.g. config/catalog.json):

{
  "Datasources": [
    {
      "id": "my-datasource-id",
      "provider": "SQLServer"
    }
  ]
}

Supported Providers: AmazonAthena, MySQL, Oracle, OracleSID, PostgreSQL, SSAS, SSASHTTP, Snowflake, SQLServer, WebService

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Step 5: Run and Verify

Start your application:

dotnet run

Watch console output for metadata generation:

MetadataGenerationHostedService starting
Triggering metadata initialization on startup
...
Generating metadata for datasource my-datasource-id
Enriching metadata for datasource my-datasource-id
...
Metadata initialization completed. Metadata is now ready.
Startup metadata initialization completed

Verify metadata files were created:

# Windows
dir %localappdata%\reveal\ai\metadata\

# Linux
ls ~/.local/share/reveal/ai/metadata/

# Mac
ls ~/Library/Application\ Support/reveal/ai/metadata

You should see files like:

• my-datasource-id_index.json
• my-datasource-id_MyDB_Orders.json
• etc.

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Step 6: Test Dashboard Generation (Server-Side)

curl -X GET http://localhost:5000/api/reveal/ai/metadata/status

Expected Response (once system is ready):

{
  "status": "Completed",
  "isInitialized": true
}

---

Node.js

Prerequisites

• ✅ Reveal 2.0.0+ (reveal-sdk-node) installed and working
• ✅ Node.js 16+
• ✅ LLM Provider account (OpenAI or Anthropic recommended)
• ✅ At least one datasource configured in Reveal SDK

Step 1: Install npm Package

npm install reveal-sdk-node-ai

Optional: Install Client-Side Package

npm install @revealbi/api

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Step 2: Configure LLM Provider

Pass your LLM provider settings via the settings option when registering the plugin (see Step 3). The settings object uses lowercase provider keys:

Option A: OpenAI (Recommended)

{
  "openai": {
    "ApiKey": "sk-your-api-key-here",
    "Model": "gpt-4.1"
  }
}

Option B: Anthropic Claude

{
  "anthropic": {
    "ApiKey": "sk-ant-your-api-key-here",
    "Model": "claude-sonnet-4-5"
  }
}

Tip: Load these settings from a secure source (environment variables, a secrets manager, or a local config file) and pass them at startup.

---

Step 3: Register the Plugin

Add the AI plugin to your RevealOptions, passing the settings object and a defaultProvider:

const reveal = require('reveal-sdk-node');
const revealAI = require('reveal-sdk-node-ai');
const path = require('path');
const os = require('os');

// Load your AI provider settings from your preferred config source
const aiSettings = {
  openai: { ApiKey: process.env.OPENAI_API_KEY, Model: 'gpt-4.1' }
};

const revealOptions = {
  // ... your existing Reveal options
  plugins: [
    revealAI.withOptions({
      defaultProvider: 'openai',
      settings: aiSettings,
      metadataCatalogFile: path.resolve(__dirname, 'Reveal', 'Metadata', 'catalog.json'),
      metadataManager: {
        outputPath: path.resolve(os.homedir(), 'AImetadata'),
      },
      callbacks: {
        contextManagerProvider: async (userContext, message) => {
          return '';
        },
        aiProvider: async (userContext, message) => {
          return '';
        }
      }
    })
  ]
};

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Step 4: Configure Metadata

Create a metadata catalog JSON file listing your datasources (same format as C#):

{
  "Datasources": [
    {
      "Id": "my-datasource-id",
      "Provider": "SQLServer"
    }
  ]
}

Supported Providers: AmazonAthena, MySQL, Oracle, OracleSID, PostgreSQL, SSAS, SSASHTTP, Snowflake, SQLServer, WebService

---

Step 5: Run and Verify

node server.js

Once running, verify the AI endpoint:

curl -X GET http://localhost:5111/api/reveal/ai/metadata/status

Expected Response:

{
  "status": "Completed",
  "isInitialized": true
}

---

Java

Prerequisites

• ✅ Reveal 2.0.0+ (io.revealbi:reveal-sdk-servlet or Spring equivalent) installed and working
• ✅ Java 17+
• ✅ Maven 3.6+
• ✅ LLM Provider account (OpenAI or Anthropic recommended)
• ✅ At least one datasource configured in Reveal SDK

Step 1: Add Maven Dependency

Add the Reveal Maven repository and dependency to your pom.xml:

<repositories>
  <repository>
    <id>reveal.snapshots</id>
    <url>https://maven.revealbi.io/repository/snapshots</url>
  </repository>
</repositories>

<dependencies>
  <dependency>
    <groupId>io.revealbi</groupId>
    <artifactId>reveal-sdk-ai</artifactId>
    <version>1.0.6-SNAPSHOT</version>
  </dependency>
</dependencies>

Then run:

mvn install

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Step 2: Configure LLM Provider

Pass your LLM provider settings via the additionalOptions map when creating RevealAIPluginOptions (see Step 3). The settings map uses lowercase provider keys:

Option A: OpenAI (Recommended)

{
  "openai": {
    "ApiKey": "sk-your-api-key-here",
    "Model": "gpt-4.1"
  }
}

Option B: Anthropic Claude

{
  "anthropic": {
    "ApiKey": "sk-ant-your-api-key-here",
    "Model": "claude-sonnet-4-5"
  }
}

Tip: Load these settings from a secure source (environment variables, a secrets manager, or a local config file) and pass them at startup.

---

Step 3: Register the Plugin

Add the AI plugin when building your RevealServer. The RevealAIPluginOptions constructor takes:

1. defaultProvider – the provider name (e.g. "openai" or "anthropic")
2. metadataCatalogFile – path to your catalog JSON
3. MetadataManagerOptions – output directory for generated metadata
4. ContextManagerOptions – (nullable) context manager config
5. additionalOptions – map containing "settings" with your provider config

The plugin also accepts an optional callbacks map as a second argument to withOptions():

import io.revealbi.ai.RevealAIPlugin;
import io.revealbi.ai.RevealAIPluginOptions;
import io.revealbi.core.IRevealServer;
import io.revealbi.core.RevealPluginCallback;
import io.revealbi.core.RevealServerBuilder;

import java.nio.file.Path;
import java.util.Map;
import java.util.concurrent.CompletableFuture;

// Load your AI provider settings from your preferred config source
Map<String, Object> aiSettings = Map.of(
    "openai", Map.of("ApiKey", System.getenv("OPENAI_API_KEY"), "Model", "gpt-4.1")
);

RevealAIPluginOptions aiPluginOptions = new RevealAIPluginOptions(
    "openai",
    Path.of("src", "main", "resources", "Reveal", "Metadata", "catalog.json")
        .toAbsolutePath().normalize().toString(),
    new RevealAIPluginOptions.MetadataManagerOptions(
        Path.of(System.getProperty("user.home"), "AImetadata").toString()),
    null,
    Map.of("settings", aiSettings));

// Optional callbacks
Map<String, RevealPluginCallback> callbacks = Map.of(
    "contextManagerProvider", (userContext, message) ->
        CompletableFuture.completedFuture(""),
    "aiProvider", (userContext, message) ->
        CompletableFuture.completedFuture("")
);

IRevealServer revealServer = new RevealServerBuilder()
    .setDataSourceProvider(dataSourceProvider)
    .addPlugin(RevealAIPlugin.withOptions(aiPluginOptions, callbacks))
    .build();

---

Step 4: Configure Metadata

Create a metadata catalog JSON file listing your datasources (same format as C#):

{
  "Datasources": [
    {
      "Id": "my-datasource-id",
      "Provider": "SQLServer"
    }
  ]
}

Supported Providers: AmazonAthena, MySQL, Oracle, OracleSID, PostgreSQL, SSAS, SSASHTTP, Snowflake, SQLServer, WebService

---

Step 5: Run and Verify

mvn spring-boot:run

Once running, verify the AI endpoint:

curl -X GET http://localhost:5111/api/reveal/ai/metadata/status

Expected Response:

{
  "status": "Completed",
  "isInitialized": true
}

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Set Up Client-Side API (Optional)

If you want to use the JavaScript/TypeScript API for insights and chat in your web application:

Install the Client Package

npm install @revealbi/api

Or use the CDN:

<script src="https://cdn.jsdelivr.net/npm/@revealbi/api/dist/index.umd.js"></script>

Initialize the Client

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

// Initialize once at app startup
RevealSdkClient.initialize({
  hostUrl: 'http://localhost:5000'
});

const client = RevealSdkClient.getInstance();

Use Chat Interface

// Non-streaming: send a message and wait for the complete response
const response = await client.ai.chat.sendMessage({
  message: 'Show me total sales by region',
  datasourceId: 'my-datasource-id',
});

console.log('AI Response:', response.explanation);
if (response.dashboard) {
  // Load the generated/modified dashboard
  loadDashboard(response.dashboard);
}

// Streaming: get real-time text chunks
const stream = await client.ai.chat.sendMessage({
  message: 'Create a dashboard showing revenue trends',
  datasourceId: 'my-datasource-id',
  stream: true,
});

stream.on('progress', (message) => console.log('Status:', message));
stream.on('text', (content) => appendToUI(content));
stream.on('error', (error) => console.error(error));

const result = await stream.finalResponse();
if (result.dashboard) {
  loadDashboard(result.dashboard);
}

// Editing an existing dashboard
const editResponse = await client.ai.chat.sendMessage({
  message: 'Add a date filter to this dashboard',
  datasourceId: 'my-datasource-id',
  dashboard: revealView.dashboard,
});

// Reset conversation context
await client.ai.chat.resetContext();

Get AI Insights

// Non-streaming: get a summary for a dashboard
const insight = await client.ai.insights.get({
  dashboardId: 'my-dashboard',
  type: 'summary',  // 'summary' | 'analysis' | 'forecast'
});

console.log('Insight:', insight.explanation);

// Streaming: get real-time text chunks
const stream = await client.ai.insights.get({
  dashboard: revealView.dashboard,
  type: 'analysis',
  stream: true,
});

stream.on('text', (content) => appendToUI(content));

const result = await stream.finalResponse();
console.log('Complete:', result.explanation);

// Visualization-level insight
const vizInsight = await client.ai.insights.get({
  dashboard: revealView.dashboard,
  visualizationId: 'sales-chart',
  type: 'analysis',
});

// Forecast with custom periods
const forecast = await client.ai.insights.get({
  dashboardId: 'my-dashboard',
  type: 'forecast',
  forecastPeriods: 12,
});

For complete API documentation and advanced usage, see the @revealbi/api npm package README.

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Success Checklist

ASP.NET Core (C#)

• NuGet package Reveal.Sdk.AI.AspNetCore installed
• LLM provider configured in appsettings.json (OpenAI or Anthropic)
• Metadata catalog configured (datasource list)
• AddRevealAI() registered in Program.cs
• Application builds without errors
• Metadata files generated in reveal/ai/metadata/
• GET /api/reveal/ai/metadata/status returns isInitialized: true

Node.js

• reveal-sdk-node-ai npm package installed
• LLM provider settings passed via settings option in withOptions() (lowercase provider keys)
• defaultProvider set in withOptions() (e.g. 'openai' or 'anthropic')
• Metadata catalog JSON file configured with datasource list
• revealAI.withOptions(...) added to RevealOptions.plugins
• Application starts without errors
• GET /api/reveal/ai/metadata/status returns isInitialized: true

Java

• io.revealbi:reveal-sdk-ai Maven dependency added (with Reveal Maven repositories)
• LLM provider settings passed via additionalOptions in RevealAIPluginOptions (lowercase provider keys)
• defaultProvider set as first argument to RevealAIPluginOptions constructor
• Metadata catalog JSON file configured with datasource list
• RevealAIPlugin.withOptions(aiPluginOptions, callbacks) added via RevealServerBuilder.addPlugin()
• Application builds and starts without errors
• GET /api/reveal/ai/metadata/status returns isInitialized: true

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