docs: update README.md with download links and setup tutorials

README.md

@@ -1,12 +1,14 @@
-# 🎙️ Standalone ONNX Real-Time Voice Changer Service
+# 🎙️ ONNX VC - Standalone Real-Time Voice Changer
 
-A high-performance, low-latency, real-time voice conversion system powered by **ONNX Runtime** and **Retrieval-based Voice Conversion (RVC)**. This application enables real-time voice conversion from a microphone/browser source to a designated target character model with minimal processing latency.
+A high-performance, low-latency, real-time AI voice conversion system powered by **ONNX Runtime** and **Retrieval-based Voice Conversion (RVC)**. Features a premium dashboard built with **Next.js App Router**, **TypeScript**, and **Tailwind CSS**, supporting full internationalization.
 
 ---
 
 ## ✨ Key Features
 * **🚀 WebSocket Audio Pipeline:** Streaming audio transfer using binary WebSocket connections (raw PCM float32) for minimal overhead.
 * **⚡ Multi-Backend ONNX Acceleration:** Supports execution providers including NVIDIA `CUDA`, AMD/Intel `DirectML`, and fallback `CPU`.
+* **🌐 Universal Localisation:** Fully translatable interface supporting English, Indonesian, Japanese, Chinese, and Spanish.
+* **🎨 Premium Dashboard**: Fully responsive workspace built using React 19, Radix UI, Framer Motion, and Tailwind CSS.
 * **🎼 High-Fidelity DSP Pipeline:**
   * **Low-Cut Filter:** Active 1st order Butterworth high-pass filter at 80Hz to eliminate AC hum and rumble.
   * **Noise Gate:** Threshold-based noise suppression to bypass inference during silence (saving CPU/GPU cycles).
@@ -38,44 +40,101 @@ graph TD
 * [server.py](file:///M:/Users/ahmad/project/onnx-voice-changer/server.py) — The main WebSocket backend and static HTTP server managing connection loops, audio resampling, and model execution.
 * [start.bat](file:///M:/Users/ahmad/project/onnx-voice-changer/start.bat) — Windows launcher batch file that automatically resolves the Python virtual environment and executes the server.
 * [requirements.txt](file:///M:/Users/ahmad/project/onnx-voice-changer/requirements.txt) — Python dependencies list.
-* [frontend/](file:///M:/Users/ahmad/project/onnx-voice-changer/frontend) — Contains client-side Web UI files:
+* [frontend-next/](file:///M:/Users/ahmad/project/onnx-voice-changer/frontend-next) — The development workspace for the frontend client (Next.js, TypeScript).
-  * [frontend/index.html](file:///M:/Users/ahmad/project/onnx-voice-changer/frontend/index.html) — Control interface layout.
+* [frontend/](file:///M:/Users/ahmad/project/onnx-voice-changer/frontend) — Statically exported and optimized assets served by [server.py](file:///M:/Users/ahmad/project/onnx-voice-changer/server.py) backend.
-  * [frontend/app.js](file:///M:/Users/ahmad/project/onnx-voice-changer/frontend/app.js) — WebSocket communication and client-side audio rendering.
+* [lib/](file:///M:/Users/ahmad/project/onnx-voice-changer/lib) — Core package containing inference models, ONNX conversion scripts, and prediction tools.
-  * [frontend/styles.css](file:///M:/Users/ahmad/project/onnx-voice-changer/frontend/styles.css) — Custom dashboard styling.
+* [weights/](file:///M:/Users/ahmad/project/onnx-voice-changer/weights) — Directory for character voice model weights (e.g. `weights/HuTao/`).
-* [lib/](file:///M:/Users/ahmad/project/onnx-voice-changer/lib) — core package containing inference models and prediction tools.
+* [pretrained/](file:///M:/Users/ahmad/project/onnx-voice-changer/pretrained) — Directory containing base pre-trained models.
-* [weights/](file:///M:/Users/ahmad/project/onnx-voice-changer/weights) — Directory for voice model weights. Place your custom `.onnx` and `.pth` model sub-directories here.
-* [pretrained/](file:///M:/Users/ahmad/project/onnx-voice-changer/pretrained) — Directory containing base pre-trained models such as `vec-768-layer-12.onnx` or `vec-256-layer-12.onnx`.
 
 ---
 
-## 🚀 Getting Started
+## 🚀 Installation & Setup
 
 ### 📋 Prerequisites
-* **Python 3.10+** (Recommended)
+* **Python 3.10+**
 * **FFmpeg** installed and added to the system PATH (Required for audio processing utilities).
+* **Node.js 18+** & **npm** (Only required if you want to modify and compile the frontend workspace).
 * (Optional) **NVIDIA CUDA Toolkit** (v11.x/12.x) and **cuDNN** for GPU execution acceleration.
 
-### 📦 Installation
+---
+
+### 📦 1. Python Backend Installation
 1. Clone this repository to your local directory.
-2. Initialize and activate a virtual environment (optional but recommended):
+2. Initialize and activate a virtual environment:
    ```bash
    python -m venv venv
+   # On Windows:
    .\venv\Scripts\activate
+   # On Linux/macOS:
+   source venv/bin/activate
    ```
 3. Install the required dependencies:
    ```bash
    pip install -r requirements.txt
    ```
-4. Place your ContentVec base model (`vec-768-layer-12.onnx` or `vec-256-layer-12.onnx`) inside the [pretrained/](file:///M:/Users/ahmad/project/onnx-voice-changer/pretrained) directory.
-5. Place your character models in [weights/](file:///M:/Users/ahmad/project/onnx-voice-changer/weights) in structured folders (e.g., `weights/HuTao/` containing `HuTao.onnx` and `HuTao.pth`).
 
-### 🏃 Running the Server
+---
 
-#### Option A: Quick Launch (Windows)
+### 📥 2. Download Pre-trained ContentVec (Required)
-Simply double-click the [start.bat](file:///M:/Users/ahmad/project/onnx-voice-changer/start.bat) file. It will automatically detect Python, set up the directory paths, and launch the service.
+The model requires a ContentVec base model to generate speaker features from voice chunks.
+1. Download the `vec-768-layer-12.onnx` model from Hugging Face:
+   👉 **[Download vec-768-layer-12.onnx](https://huggingface.co/DogManTC/test-rvc-onnx/blob/main/vec-768-layer-12.onnx)**
+2. Save the downloaded file inside the [pretrained/](file:///M:/Users/ahmad/project/onnx-voice-changer/pretrained) directory:
+   ```
+   pretrained/
+   └── vec-768-layer-12.onnx
+   ```
 
-#### Option B: Manual CLI execution
+---
-Execute the server using your terminal:
+
+### 🔄 3. Setup & Export RVC Models to ONNX
+To run character models on ONNX Runtime, you must place your standard PyTorch RVC models (`.pth`) under the [weights/](file:///M:/Users/ahmad/project/onnx-voice-changer/weights) directory and convert them.
+
+1. Create a sub-folder under `weights/` named after your character (e.g. `HuTao`):
+   ```
+   weights/
+   └── HuTao/
+       └── HuTao.pth
+   ```
+2. Run the ONNX conversion script by passing the folder name of the model:
+   ```bash
+   python lib/export_onnx.py --model_name HuTao
+   ```
+3. The script will automatically search for the `.pth` file inside `weights/HuTao/` and export a corresponding `HuTao.onnx` file inside the same directory:
+   ```
+   weights/
+   └── HuTao/
+       ├── HuTao.pth
+       └── HuTao.onnx
+   ```
+
+---
+
+### 🖥️ 4. Build the Frontend (Optional)
+*Note: Statically built files are already pre-compiled under `/frontend`. You only need to run this step if you have modified the Next.js workspace source files inside `/frontend-next`.*
+
+1. Navigate to the frontend directory:
+   ```bash
+   cd frontend-next
+   ```
+2. Install npm dependencies:
+   ```bash
+   npm install
+   ```
+3. Build and export static assets (this will automatically compile files and synchronize them to the `/frontend` directory via `copy-build.js`):
+   ```bash
+   npm run build
+   ```
+
+---
+
+## 🏃 Running the Voice Changer
+
+### Option A: Quick Launch (Windows)
+Double-click the [start.bat](file:///M:/Users/ahmad/project/onnx-voice-changer/start.bat) file at the root. It automatically activates the Python virtual environment and fires up the server.
+
+### Option B: Manual CLI Execution
+Run the server using your terminal:
 ```bash
 python server.py --host 127.0.0.1 --port 8765 --http_port 8000 --device cuda
 ```
@@ -89,7 +148,7 @@ python server.py --host 127.0.0.1 --port 8765 --http_port 8000 --device cuda
 | `--device` | The ONNX Runtime execution device (`cpu`, `cuda`, `dml`). | `cuda` |
 | `--model` | Target folder name in `weights/` to load directly upon startup. | `None` |
 
-Once the server begins execution, it will spin up the local server, and your Web UI should open automatically at `http://localhost:8000`.
+Once started, the application will automatically launch your browser and direct you to the premium audio dashboard at `http://localhost:8000`.
 
 ---