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Off Grid

calendar_todayAdded Apr 23, 2026
categoryAgent & Tooling
codeOpen Source
JavaScript大语言模型Knowledge BaseReactMultimodalRAGAgent & ToolingOtherKnowledge Management, Retrieval & RAGComputer Vision & MultimodalSecurity & Privacy

The Swiss Army Knife of On-Device AI — an offline-first mobile AI suite covering text generation, image generation, vision Q&A, and speech-to-text, with on-device RAG knowledge base and tool calling support.

Off Grid is a cross-platform (iOS / Android / Mac Catalyst) mobile offline AI application built with React Native. All inference runs locally on-device with zero data leaving the device.

Text Generation#

Supports any GGUF model (Qwen 3, Llama 3.2, Gemma 3, Phi-4, etc.) with streaming output, thinking mode, and Markdown rendering, achieving 15–30 tok/s on flagship devices, and supports user-supplied .gguf files.

Image Generation#

Integrates on-device Stable Diffusion with Snapdragon NPU acceleration on Android (5–10s/image) and Core ML acceleration on iOS, bundling 20+ models (Absolute Reality, DreamShaper, Anything V5, etc.) with AI Prompt enhancement.

Vision AI#

Supports real-time camera VQA with SmolVLM / Qwen3-VL / Gemma 3n for document analysis, scene description, and receipt recognition, with ~7s response on flagship devices.

Speech Input#

On-device Whisper for press-and-hold voice-to-text; audio never leaves the device.

Tool Calling#

Models supporting function calling can invoke built-in tools: web search, calculator, date/time, device info, knowledge base search, with auto tool loops and overflow protection.

On-Device RAG Knowledge Base#

Upload PDF/text documents, with MiniLM on-device Embedding, SQLite storage, and cosine similarity retrieval.

Document Analysis#

Attach PDFs, code files, CSVs in conversations with native PDF text extraction on both platforms.

Remote LLM Server Connection#

Connect to LAN OpenAI-compatible servers (Ollama, LM Studio, LocalAI) with auto model discovery, SSE streaming, Keychain-secured API key storage, and seamless local/remote model switching.

Architecture Highlights#

  • Frontend: React Native (TypeScript 93.5%)
  • Android Native Layer: Kotlin — llama.cpp / whisper.cpp / Stable Diffusion native module integration
  • iOS Native Layer: Swift — CoreML Diffusion, PDFExtractor, DownloadManager, etc.
  • RN Bridges: llama.rn, whisper.rn, op-sqlite
  • Image Generation Backends: local-dream, ml-stable-diffusion, MNN
  • Hardware Acceleration: Snapdragon NPU (Android), Core ML (iOS)
  • CI/CD: GitHub Actions + SonarQube + Codecov
  • E2E Testing: Maestro

Installation#

  • Android: Google Play Store or GitHub Releases APK
  • iOS: App Store (also runs on Apple Silicon Mac via Mac Catalyst)
  • Build from Source: Node.js 20+, JDK 17 / Android SDK 36, Xcode 15+

MIT-licensed with 7 contributors, 79 releases, and 1,489+ commits.

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