wajuce #

JUCE-powered Web Audio API for Flutter.

wajuce provides a Web Audio API 1.1 compatible interface for Flutter and Dart. It allows developers to use familiar Web Audio patterns while delivering high-performance, low-latency audio processing via a native JUCE C++ backend.

🌟 Key Features #

• Web Audio API Parity: Mirrors AudioContext, OscillatorNode, GainNode, etc., making it easy to port existing JS audio engines.
• JUCE Backend: Leverages the industry-standard JUCE framework for native audio processing on iOS, Android, macOS, and Windows.
• Pure Web Support: Automatically falls back to the browser's native Web Audio API on Web platforms via dart:js_interop.
• Zero-Overhead FFI: Uses Dart FFI for fast communication between Dart and C++ without MethodChannel overhead.
• AudioWorklet Support: Emulates the AudioWorklet system using high-priority Dart Isolates.
• Feedback Loops: Built-in FeedbackBridge automatically handles cyclic connections in the node graph (1-block delay).

🏗️ Architecture #

wajuce is built on a multi-backend architecture that ensures code portability across all platforms:

graph TD
    subgraph "Dart API Layer"
        A[WAContext] --> B[WANode Graph]
    end

    subgraph "Platform Backends"
        B -->|Native| C[backend_juce.dart]
        B -->|Web| D[backend_web.dart]
    end

    subgraph "Native Layer (C++/JUCE)"
        C --> E[FFI Bridge]
        E --> F[WajuceEngine]
        F --> G[JUCE AudioProcessorGraph]
    end

    subgraph "Web Layer (JS)"
        D --> H[Browser Web Audio API]
    end

🚀 Current Implementation Status (2026-02-12) #

⚡ v0.1.1 Performance & Scalability #

The 0.1.1 release introduces significant optimizations for complex node graphs:

• Native Batch Creation: Create complex voices (15+ nodes) in a single FFI call, preventing audio thread contention.
• Lazy Connection: Voices in the MachineVoicePool are kept disconnected until playback, saving substantial CPU.
• Async Voice Pooling: Background replenishment of voice pools to ensure glitch-free sequencer tracking.

🎹 AudioWorklet #

Run custom DSP code in a dedicated high-priority Isolate:

// 1. Define processor
class DX7Processor extends WAWorkletProcessor {
  DX7Processor() : super(name: 'dx7');

  @override
  bool process(inputs, outputs, params) {
    // DSP code here...
    return true;
  }
}

// 2. Register & Run
ctx.audioWorklet.registerProcessor('dx7', () => DX7Processor());
await ctx.audioWorklet.addModule('dx7');
final node = ctx.createWorkletNode('dx7');
node.connect(ctx.destination);

💻 Usage Example #

The API is designed to be almost identical to the standard Web Audio API:

// 1. Initialize context
final ctx = WAContext();
await ctx.resume();

// 2. Create nodes
final osc = ctx.createOscillator();
final filter = ctx.createBiquadFilter();
final gain = ctx.createGain();

// 3. Configure and Automate
osc.type = WAOscillatorType.sawtooth;
filter.frequency.setValueAtTime(440, ctx.currentTime);
filter.frequency.exponentialRampToValueAtTime(2000, ctx.currentTime + 2.0);

// 4. Connect graph
osc.connect(filter);
filter.connect(gain);
gain.connect(ctx.destination);

// 5. Start
osc.start();

🛠️ Project Structure #

• lib/src/: Dart API implementation and backend switching logic.
• lib/src/backend/: Platform-specific implementation (FFI vs JS).
• native/engine/: The JUCE-based C++ audio engine.
• src/: C-API headers and stubs for FFI binding.

🤖 AI Skills & Automation #

This project includes specialized AI Skills to help agents maintain the development environment.

• JUCE Management (juce_setup): Automated detection and setup of the JUCE framework.
  • Located at: .agent/skills/juce_management/SKILL.md
  • Purpose: Fixes broken dependencies, handles symlinks, and configures submodules.

To use these skills, simply ask your AI agent: "Help me set up the JUCE environment using the available skills."

📄 License #

This project is licensed under the MIT License - see the LICENSE file for details.