LLM-Hub

LLM-Hub

Local AI Assistant on Android

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LLM Hub is an open-source Android app optimized for mobile usage, supporting multiple model formats for on-device LLM chat and image generation. It offers six AI tools including chat, writing aid, image generator, translator, transcriber, and scam detector. Privacy-first with on-device processing and zero data collection. Advanced capabilities include GPU/NPU acceleration, text-to-speech, RAG with global memory, and custom model import. Developed using Kotlin + Jetpack Compose, LLM Runtime, and various model runtimes.

README:

LLM Hub 🤖

LLM Hub is an open-source Android app for on-device LLM chat and image generation. It's optimized for mobile usage (CPU/GPU/NPU acceleration) and supports multiple model formats so you can run powerful models locally and privately.

📸 Screenshots

AI Models AI Features Chat Interface

🚀 Features

🛠️ Six AI Tools

Tool Description
💬 Chat Multi-turn conversations with RAG memory, web search, TTS auto-readout, and multimodal input (text, images, audio)
✍️ Writing Aid Summarize, expand, rewrite, improve grammar, or generate code from descriptions
🎨 Image Generator Create images from text prompts using Stable Diffusion 1.5 with swipeable gallery for variations
🌍 Translator Translate text, images (OCR), and audio across 50+ languages - works offline
🎙️ Transcriber Convert speech to text with on-device processing
🛡️ Scam Detector Analyze messages and images for phishing with risk assessment

🔐 Privacy First

  • 100% on-device processing - no internet required for inference
  • Zero data collection - conversations never leave your device
  • No accounts, no tracking - completely private
  • Open-source - fully transparent

⚡ Advanced Capabilities

  • GPU/NPU acceleration for fast performance
  • Text-to-Speech with auto-readout
  • RAG with global memory for enhanced responses
  • Import custom models (.task, .litertlm, .mnn, .gguf)
  • Direct downloads from HuggingFace
  • 16 language interfaces

Quick Start

  1. Download from Google Play or build from source
  2. Open Settings → Download Models → Download or Import a model
  3. Select a model and start chatting or generating images

Supported Model Families (summary)

  • Gemma (LiteRT Task)
  • Llama (Task + GGUF variants)
  • Phi (LiteRT LM)
  • LiquidAI LFM (LFM 2.5 1.2B + LFM VL 1.6B vision-enabled)
  • Ministral / Mistral family (GGUF / ONNX)
  • IBM Granite (GGUF)

Model Formats

  • Task / LiteRT (.task): MediaPipe/LiteRT optimized models (GPU/NPU capable)
  • LiteRT LM (.litertlm): LiteRT language models
  • GGUF (.gguf): Quantized models — CPU inference powered by Nexa SDK; some vision-capable GGUF models require an additional mmproj vision project file
  • ONNX (.onnx): Cross-platform model runtime

GGUF Compatibility Notes

  • Not all Android devices can load GGUF models in this app.
  • GGUF loading/runtime depends on Nexa SDK native libraries and device/ABI support; on unsupported devices, GGUF model loading can fail even if the model file is valid.
  • In this app, the GGUF NPU option is intentionally shown only for Snapdragon 8 Gen 4-class devices.

Importing models

  • Settings → Download Models → Import Model → choose .task, .litertlm, .mnn, .gguf, or .onnx
  • The full model list and download links live in app/src/.../data/ModelData.kt (do not exhaustively list variants in the README)

Technology

  • Kotlin + Jetpack Compose (Material 3)
  • LLM Runtime: MediaPipe, LiteRT, Nexa SDK
  • Image Gen: MNN / Qualcomm QNN
  • Quantization: INT4/INT8

Acknowledgments

  • Nexa SDK — GGUF model inference support (credit shown in-app About) ⚡
  • Google, Meta, Microsoft, IBM, LiquidAI, Mistral, HuggingFace — model and tooling contributions

Development Setup

Building from source

git clone https://github.com/timmyy123/LLM-Hub.git
cd LLM-Hub
./gradlew assembleDebug
./gradlew installDebug

Setting up Hugging Face Token for Development

To use private or gated models, add your HuggingFace token to local.properties (do NOT commit this file):

HF_TOKEN=hf_xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx

Save and sync Gradle in Android Studio; the app will read BuildConfig.HF_TOKEN at build time.

Contributing

  • Fork → branch → PR. See CONTRIBUTING.md (or open an issue/discussion if unsure).

License

  • MIT (see LICENSE)

Support

Notes

  • This README is intentionally concise — consult ModelData.kt for exact model variants, sizes, and format details.

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