cross-platform-llm-client

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cross-platform-llm-client

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A unified cross-platform AI client supporting seamless transitions between standard cloud APIs and on-device, offline execution of custom and uncensored language models.

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# PrivateLM

[![Live Web App](https://img.shields.io/badge/Live_Demo-Try_Web_App-02569B?style=for-the-badge&logo=flutter&logoColor=white)](https://ai-chat-orailnoor.web.app/)

A production-ready, cross-platform AI chat client built with Flutter. It unifies local on-device LLM inference (Android) with cloud API access, giving users full control over how their models run.

![Image generation tested on Moto G71 (Snapdragon), Oneplus 10r (Mediatek), Pixel 6A (Tensor), Poco F1 (Snapdragon), Samsung s23 (Snapdragon) 4 steps fast](https://raw.githubusercontent.com/orailnoor/cross-platform-llm-client/main/PrivateLM.png)
_Image generation tested on Moto G71 (Snapdragon), Oneplus 10r (Mediatek), Pixel 6A (Tensor), Poco F1 (Snapdragon), Samsung s23 (Snapdragon) 4 steps fast_

![Generated on pixel 6 with 20 step](https://raw.githubusercontent.com/orailnoor/cross-platform-llm-client/main/IMG_2390.png)
_Generated on pixel 6 with 20 step_

---

## What It Does

- **Local Inference on Android** — Download and run GGUF models directly on your phone using GPU-accelerated inference (Vulkan). No internet required after download.
- **Cloud API Fallback** — Seamlessly switch to OpenAI, Anthropic, Google Gemini, or Kimi (Moonshot AI) when you need more power or are on unsupported platforms.
- **Multimodal Chat** — Send text and images in conversations. Vision support works with both local models (Qwen2-VL) and cloud providers.
- **Persistent Sessions** — All chats, tasks, and settings are stored locally via Hive. Nothing leaves your device unless you explicitly choose cloud mode.
- **Background Services** — Firebase Cloud Messaging integration for push updates and background task handling.
- **Smart Auto-Configuration** — On first launch, the app detects your device's RAM and recommends optimal context size and token limits automatically.
- **Task Management** — A dedicated task view for structured AI-assisted workflows alongside free-form chat.

---

## Technical Architecture

### Stack

- **Framework:** Flutter 3.x (Dart >=3.3.0)
- **State Management:** GetX
- **Local Storage:** Hive
- **Networking:** Dio + `package:http`
- **Background Execution:** `flutter_background_service` + `flutter_local_notifications`
- **Push Notifications:** Firebase Core + Firebase Messaging

### Inference Pipeline

```
┌─────────────────────────────────────────────────────────────┐
│                        UI Layer                              │
│   ChatView / TaskView / ModelView / SettingsView            │
└──────────────────────────┬──────────────────────────────────┘
                           │
┌──────────────────────────▼──────────────────────────────────┐
│                    Controllers (GetX)                        │
│   ChatController · TaskController · ModelController         │
│   SettingsController · HomeController                       │
└──────────────────────────┬──────────────────────────────────┘
                           │
┌──────────────────────────▼──────────────────────────────────┐
│                      Services                                │
│  ┌─────────────────┐  ┌─────────────────┐  ┌─────────────┐ │
│  │ InferenceService│  │  CloudService   │  │DownloadSvc  │ │
│  │  (local GGUF)   │  │ (OpenAI/Claude/ │  │ (model dl)  │ │
│  │                 │  │  Gemini/Kimi)   │  │             │ │
│  └─────────────────┘  └─────────────────┘  └─────────────┘ │
│  ┌─────────────────┐  ┌─────────────────┐  ┌─────────────┐ │
│  │  HiveService    │  │ DeviceInfoSvc   │  │ExecutionSvc │ │
│  │  ( persistence) │  │  (RAM/GPU tier) │  │ (bg tasks)  │ │
│  └─────────────────┘  └─────────────────┘  └─────────────┘ │
└─────────────────────────────────────────────────────────────┘
```

### Local Inference (Android)

The app uses `llama_flutter_android`, a custom Flutter plugin wrapping `llama.cpp` for ARM64 devices. At runtime it:

1. **Detects GPU capabilities** via Vulkan to determine offload layers.
2. **Selects thread count** based on device tier (ultra / high / mid / low).
3. **Loads the GGUF model** with progress streaming.
4. **Generates tokens** via `generateChat()` with native chat-template support (ChatML, Llama-3, Gemma, Phi).
5. **Falls back** to manual prompt construction if native templates fail.

Idle detection (5s) and hard timeouts (180s) keep the UX responsive even on underpowered hardware.

### Cloud Inference

`CloudService` normalizes four different API shapes into a single interface:

- **OpenAI** — standard `/v1/chat/completions`
- **Anthropic** — Messages API with separate system param
- **Google Gemini** — `generateContent` with inline image base64
- **Kimi** — OpenAI-compatible endpoint from Moonshot AI

API keys are stored in Hive and never transmitted anywhere except to the provider's endpoint.

### Cross-Platform Abstraction

Local inference is conditionally compiled:

- **Android** → `inference_android.dart` (full llama.cpp engine)
- **Web** → `inference_stub.dart` (cloud-only, local coming soon)
- **iOS** → `inference_android.dart` (full llama.cpp engine via Metal GPU)

The `InferenceService` exposes `supportsLocalInference` so the UI can hide local-model UI on unsupported platforms.

---

## Supported Platforms

| Platform | Local Inference | Cloud APIs | Notes                           |
| -------- | --------------- | ---------- | ------------------------------- |
| Android  | ✅ Yes          | ✅ Yes     | CPU offload via NEON; minSdk 28 |
| iOS      | ✅ Yes          | ✅ Yes     | Metal GPU acceleration          |
| Web      | ❌ No           | ✅ Yes     | Cloud-only (local coming soon)  |

### iOS / iPad

The iPad release is distributed as a standalone ZIP package for sideloading. Download the latest `PrivateLM-iOS.zip` from the [Releases](https://github.com/orailnoor/cross-platform-llm-client/releases) page, extract it, and install the `.ipa` via AltStore, Sideloadly, or Xcode. iPhone support is experimental — iPad is the recommended iOS target due to RAM requirements for local models.

---

## Build Configuration

### Prerequisites

- Flutter SDK >=3.3.0
- Android SDK (API 26+)
- JDK 17
- NDK (bundled with Android SDK)

### Android

```bash
flutter pub get
flutter build apk --debug
```

Release APKs require a stable signing key. Copy
`android/key.properties.example` to `android/key.properties`, fill in the
keystore values, and keep both the key and its backup. Android accepts an APK
upgrade only when it is signed with the same key as the installed APK.

```bash
cp android/key.properties.example android/key.properties
flutter build apk --release --split-per-abi
```

Never rotate the signing key between GitHub releases. The per-ABI APKs must
also keep increasing the build number in `pubspec.yaml`.

### iOS

```bash
flutter pub get
cd ios
pod install
flutter build ios
```

### Web

```bash
flutter pub get
flutter build web --release
```

---

## License

MIT — see [LICENSE](./LICENSE) for details.

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