### Install PyTorch for CPU

Source: https://github.com/ashish-patnaik/kokoclone/blob/main/README.md

Install PyTorch and torchaudio for CPU-only environments. This is necessary for users without Nvidia GPUs.

```bash
pip install torch torchaudio --index-url [https://download.pytorch.org/whl/cpu](https://download.pytorch.org/whl/cpu)
pip install -r requirements.txt

```

--------------------------------

### Install Koko-ONNX for GPU

Source: https://github.com/ashish-patnaik/kokoclone/blob/main/README.md

Install project dependencies and the 'kokoro-onnx' package with GPU support for Nvidia GPUs. Ensure you have the necessary CUDA drivers installed.

```bash
pip install -r requirements.txt
pip install kokoro-onnx[gpu]

```

--------------------------------

### Clone Repository and Navigate

Source: https://github.com/ashish-patnaik/kokoclone/blob/main/README.md

Clone the KokoClone repository from GitHub and change the directory to the project root. This is the initial step for setting up the project locally.

```bash
git clone https://github.com/Ashish-Patnaik/kokoclone.git
cd kokoclone

```

--------------------------------

### Launch KokoClone Web Interface

Source: https://github.com/ashish-patnaik/kokoclone/blob/main/README.md

Run the main application script to launch the Gradio-based web interface. This provides an interactive UI for KokoClone functionalities.

```bash
python app.py

```

--------------------------------

### Sync Dependencies with uv (GPU)

Source: https://github.com/ashish-patnaik/kokoclone/blob/main/README.md

Synchronize project dependencies using uv with GPU support for Nvidia GPUs. This command assumes a GPU environment is available.

```bash
# For GPU Users (Nvidia)
uv sync --extra gpu

```

--------------------------------

### Sync Dependencies with uv (CPU)

Source: https://github.com/ashish-patnaik/kokoclone/blob/main/README.md

Synchronize project dependencies using uv for a CPU environment. This is an alternative to Conda for package management.

```bash
# For CPU Users
uv sync

```

--------------------------------

### Activate uv Environment

Source: https://github.com/ashish-patnaik/kokoclone/blob/main/README.md

Activate the virtual environment created by uv. The command differs for Linux/macOS and Windows.

```bash
# Activate the environment
source .venv/bin/activate  # Linux/macOS
.venv\Scripts\activate     # Windows

```

--------------------------------

### Python API: Audio-to-Audio Voice Conversion

Source: https://github.com/ashish-patnaik/kokoclone/blob/main/README.md

Performs audio-to-audio voice conversion using Python. Loads audio, initializes KokoClone, and uses `chunked_voice_conversion`.

```APIDOC
## Python API: Audio-to-Audio Voice Conversion

### Description
Performs audio-to-audio voice conversion using Python. Loads audio, initializes KokoClone, and uses `chunked_voice_conversion`.

### Usage
```python
import soundfile as sf
from kanade_tokenizer import load_audio
from core.cloner import KokoClone
from core.chunked_convert import chunked_voice_conversion

cloner = KokoClone()

# Load audio tensors
source_wav = load_audio("source_speech.wav", sample_rate=cloner.sample_rate).to(cloner.device)
ref_wav = load_audio("target_voice.wav", sample_rate=cloner.sample_rate).to(cloner.device)

# Convert using VRAM-aware chunking
converted = chunked_voice_conversion(
    kanade=cloner.kanade,
    vocoder_model=cloner.vocoder,
    source_wav=source_wav,
    ref_wav=ref_wav,
    sample_rate=cloner.sample_rate,
)

sf.write("revoiced_output.wav", converted.numpy(), cloner.sample_rate)
```

### Parameters for `chunked_voice_conversion` function
- `kanade` - Required - The Kanade model instance.
- `vocoder_model` - Required - The vocoder model instance.
- `source_wav` (Tensor) - Required - The source audio tensor.
- `ref_wav` (Tensor) - Required - The reference voice audio tensor.
- `sample_rate` (int) - Required - The sample rate of the audio.
```

--------------------------------

### Create and Activate Conda Environment

Source: https://github.com/ashish-patnaik/kokoclone/blob/main/README.md

Create a new Conda environment named 'kokoclone' with a specific Python version and activate it. This isolates project dependencies.

```bash
conda create -n kokoclone python=3.12.12 -y
conda activate kokoclone

```

--------------------------------

### Python API: Text to Cloned Speech

Source: https://github.com/ashish-patnaik/kokoclone/blob/main/README.md

Integrates text-to-speech cloning into Python applications. Initializes KokoClone and uses the `generate` method.

```APIDOC
## Python API: Text to Cloned Speech

### Description
Integrates text-to-speech cloning into Python applications. Initializes KokoClone and uses the `generate` method.

### Usage
```python
from core.cloner import KokoClone

cloner = KokoClone()
cloner.generate(
    text="This voice is cloned using KokoClone.",
    lang="en",
    reference_audio="reference.wav",
    output_path="output.wav"
)
```

### Parameters for `generate` method
- `text` (string) - Required - The text to synthesize.
- `lang` (string) - Required - Language code (e.g., `en`, `hi`, `fr`, `ja`, `zh`, `it`, `es`, `pt`).
- `reference_audio` (string) - Required - Path to the reference voice audio file.
- `output_path` (string) - Required - Path to save the generated audio file.
```

--------------------------------

### Python API: Audio-to-Audio Voice Conversion

Source: https://github.com/ashish-patnaik/kokoclone/blob/main/README.md

Perform audio-to-audio voice conversion using the KokoClone Python API with VRAM-aware chunking. Load audio, perform conversion, and save the output.

```python
import soundfile as sf
from kanade_tokenizer import load_audio
from core.cloner import KokoClone
from core.chunked_convert import chunked_voice_conversion

cloner = KokoClone()

# Load audio tensors
source_wav = load_audio("source_speech.wav", sample_rate=cloner.sample_rate).to(cloner.device)
ref_wav = load_audio("target_voice.wav", sample_rate=cloner.sample_rate).to(cloner.device)

# Convert using VRAM-aware chunking
converted = chunked_voice_conversion(
    kanade=cloner.kanade,
    vocoder_model=cloner.vocoder,
    source_wav=source_wav,
    ref_wav=ref_wav,
    sample_rate=cloner.sample_rate,
)

sf.write("revoiced_output.wav", converted.numpy(), cloner.sample_rate)

```

--------------------------------

### CLI: Audio to Re-voiced Speech

Source: https://github.com/ashish-patnaik/kokoclone/blob/main/README.md

Perform audio-to-audio voice conversion using the CLI. Provide the source audio, target voice reference, and output file path.

```bash
python cli.py --mode convert --source original_speech.wav --ref target_voice.wav --out revoiced.wav

```

--------------------------------

### CLI: Text to Cloned Speech

Source: https://github.com/ashish-patnaik/kokoclone/blob/main/README.md

Generate speech from text using the command-line interface. Specify the text, language, reference audio, and output file.

```bash
python cli.py --text "Hello from KokoClone" --lang en --ref reference.wav --out output.wav

```

--------------------------------

### CLI: Text to Cloned Speech

Source: https://github.com/ashish-patnaik/kokoclone/blob/main/README.md

Generates speech from text using a reference voice. Requires text, a reference audio file, and an output path.

```APIDOC
## CLI: Text to Cloned Speech

### Description
Generates speech from text using a reference voice. Requires text, a reference audio file, and an output path.

### Command
```bash
python cli.py --text "Hello from KokoClone" --lang en --ref reference.wav --out output.wav
```

### Arguments
- `--text` (string) - Required - The text to synthesize.
- `--lang` (string) - Optional (default: `en`) - Language code (e.g., `en`, `hi`, `fr`, `ja`, `zh`, `it`, `es`, `pt`).
- `--ref` (string) - Required - Path to the reference voice audio file.
- `--out` (string) - Optional (default: `output.wav`) - Output file path for the generated speech.
```

--------------------------------

### CLI: Audio to Re-voiced Speech

Source: https://github.com/ashish-patnaik/kokoclone/blob/main/README.md

Converts source audio to re-voiced speech using a target voice reference. Requires source audio, a reference audio file, and an output path.

```APIDOC
## CLI: Audio to Re-voiced Speech

### Description
Converts source audio to re-voiced speech using a target voice reference. Requires source audio, a reference audio file, and an output path.

### Command
```bash
python cli.py --mode convert --source original_speech.wav --ref target_voice.wav --out revoiced.wav
```

### Arguments
- `--mode` (string) - Required - Set to `convert` for audio-to-audio conversion.
- `--source` (string) - Required - Path to the source audio file.
- `--ref` (string) - Required - Path to the target voice reference audio file.
- `--out` (string) - Optional (default: `output.wav`) - Output file path for the re-voiced audio.
```

--------------------------------

### Python API: Text to Cloned Speech

Source: https://github.com/ashish-patnaik/kokoclone/blob/main/README.md

Generate speech from text using the KokoClone Python API. Instantiate the cloner and call the generate method with required parameters.

```python
from core.cloner import KokoClone

cloner = KokoClone()
cloner.generate(
    text="This voice is cloned using KokoClone.",
    lang="en",
    reference_audio="reference.wav",
    output_path="output.wav"
)

```

--------------------------------

### Kokoclone Project Structure

Source: https://github.com/ashish-patnaik/kokoclone/blob/main/README.md

Overview of the directory structure for the Kokoclone project, detailing the purpose of key files and directories.

```text
app.py                → Gradio Web Interface (two-tab UI)
cli.py                → Command-line tool (tts and convert modes)
inference.py          → Example API usage script
core/
 ├── cloner.py        → Core TTS + voice cloning engine
 └── chunked_convert.py → VRAM-aware chunked audio conversion
model/                → Downloaded Kokoro model weights (Auto-populates)
voice/                → Downloaded Kokoro voice bins (Auto-populates)


```

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