mobile_rag_engine library

Mobile RAG Engine

A high-performance, on-device RAG (Retrieval-Augmented Generation) engine for Flutter. Run semantic search completely offline on iOS and Android.

Quick Start (Recommended)

import 'package:mobile_rag_engine/mobile_rag_engine.dart';

```dart
import 'package:mobile_rag_engine/mobile_rag_engine.dart';

void main() async {
  WidgetsFlutterBinding.ensureInitialized();

  // Initialize (just 1 line!)
  await MobileRag.initialize(
    tokenizerAsset: 'assets/tokenizer.json',
    modelAsset: 'assets/model.onnx',
  );

  runApp(const MyApp());
}

// Add documents
await MobileRag.instance.addDocument('Your long document text here');
await MobileRag.instance.rebuildIndex();

// Search with LLM context assembly
final result = await MobileRag.instance.search('query', tokenBudget: 2000);
final prompt = MobileRag.instance.formatPrompt('query', result);
// Send prompt to LLM

Advanced Usage (Low-Level API)

For fine-grained control, use the individual services directly:

await initTokenizer(tokenizerPath: 'path/to/tokenizer.json');
await EmbeddingService.init(modelBytes);
final rag = SourceRagService(dbPath: 'path/to/rag.db');
await rag.init();

Classes

AssembledContext

Assembled context ready for LLM consumption.

ContextBuilder

Builds optimized context for LLM prompts.

EmbeddingService

Dart-based embedding service Rust tokenizer + Flutter ONNX Runtime combination

MobileRag

Singleton facade for Mobile RAG Engine.

RagConfig

Configuration options for RagEngine initialization.

RagEngine