LLM Hub 🤖

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

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📸 Demo & Screenshots

Vibe Coder Demo on iOS	Image Generation on Android
Vibe Coder using Gemma 4 model on iPhone (HTML preview)	Stable Diffusion image generation on Android

🚀 Features

🛠️ AI Tools Suite

Tool	Description
💬 Chat	Multi-turn conversations with RAG memory, web search, TTS auto-readout, and multimodal input
🤖 creAItor	[NEW] Design custom AI personas with specialized system prompts (PCTF) in seconds
💻 Vibe Coder	[NEW] Explain your app idea and watch it be built in real-time with live HTML/JS preview
✍️ 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
🌍 Translator	Translate text, images (OCR), and audio across 50+ languages - offline
🎙️ Transcriber	Convert speech to text with on-device processing
🛡️ Scam Detector	Analyze messages and images for phishing with risk assessment
🗣️ VibeVoice	[NEW] Hands-free AI voice chat

🔐 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, qnn,.mnn, .gguf)
• Direct downloads from HuggingFace
• 16 language interfaces

Quick Start

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

Technology

• Android: Kotlin + Jetpack Compose (Material 3), Nexa SDK
• iOS: Swift + SwiftUI, Run Anywhere SDK, Apple Foundation Model
• LLM Runtime: MediaPipe, LiteRT, Llama.cpp (via Run Anywhere SDK)
• Image Gen: Qualcomm QNN

Acknowledgments

• Nexa SDK — GGUF model inference support (credit shown in-app About) ⚡
• Run Anywhere SDK — iOS model runtime and LLM execution framework 🚀
• Google, OpenAI, Meta, Microsoft, IBM, LiquidAI, Mistral, Primsm ML, HuggingFace — model and tooling contributions

Development Setup

Android local development (Android Studio + Gradle)

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

Android-only local configuration

Setting up Hugging Face Token for Development

To use private or gated models, add your HuggingFace token to android/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.

Dev Premium Flag

To skip ads and unlock all premium features locally without a real IAP purchase, add this to android/local.properties:

DEBUG_PREMIUM=true

Set it back to false before making a production build.

Model License Acceptance

Some models on HuggingFace (especially from Google and Meta) require explicit license acceptance before downloading. When building the app locally:

1. Ensure you have a valid HuggingFace read token in local.properties (see above)
2. For each model you want to download:
   • Visit the model's HuggingFace page (e.g., https://huggingface.co/google/gemma-3n-E2B-it-litert-lm)
   • Click the "Access repository" or license acceptance button
   • Grant consent to the model's license terms
   • Try downloading the model in the app again

Note: This is only required for local development builds. The Play Store version uses different authentication and does not require manual license acceptance for each model.

iOS local development (macOS + Xcode)

Prerequisites

• macOS with Xcode installed (use a version that matches your iOS device version)
• An Apple ID signed into Xcode (free Personal Team works for local device testing)
• iPhone with Developer Mode enabled if you run on real hardware

Build and run on iPhone

1. Clone the repo and open the iOS project:

git clone https://github.com/timmyy123/LLM-Hub.git
cd LLM-Hub
open ios/LLMHub/LLMHub.xcodeproj

2. In Xcode, select target LLMHub → Signing & Capabilities:
   • Set your Team
   • Set a unique Bundle Identifier (for example: com.yourname.llmhub)
   • Keep Automatically manage signing enabled
3. Select your iPhone as the run destination and press Run.

If you use Xcode beta

If your phone is on a newer iOS build and requires Xcode beta support, switch CLI tools:

sudo xcode-select -s /Applications/Xcode-beta.app/Contents/Developer
xcodebuild -version

Useful iOS dev troubleshooting

• If signing fails, re-check Team + Bundle Identifier in target settings.
• If build cache acts stale, clean DerivedData:

rm -rf ~/Library/Developer/Xcode/DerivedData/LLMHub-*

• Build logs: Report Navigator (Cmd+9)
• Runtime logs: Debug Console (Cmd+Shift+Y)

Contributing

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

License

• Source code is licensed under the PolyForm Noncommercial License 1.0.0.
• You are free to use, study, and build on this project for non-commercial purposes.
• Commercial use — including distributing the app, charging for it, or monetizing it with ads or IAP — is not permitted without explicit written permission from the author.
• Contact timmy@llm-hub.app for commercial licensing enquiries.

Support

• Email: timmyboy0623@gmail.com
• Issues & Discussions: GitHub

Notes

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

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