# Qwen3-Omni

Source <https://github.com/vllm-project/vllm-omni/tree/main/examples/online_serving/qwen3_omni>.


## 🛠️ Installation

Please refer to [README.md](https://github.com/vllm-project/vllm-omni/tree/main/README.md)

## Run examples (Qwen3-Omni)

### Launch the Server

```bash
vllm serve Qwen/Qwen3-Omni-30B-A3B-Instruct --omni --port 8091
```

If you have custom stage configs file, launch the server with command below
```bash
vllm serve Qwen/Qwen3-Omni-30B-A3B-Instruct --omni --port 8091 --stage-configs-path /path/to/stage_configs_file
```

### Send Multi-modal Request

Get into the example folder
```bash
cd examples/online_serving/qwen3_omni
```

####  Send request via python

```bash
python openai_chat_completion_client_for_multimodal_generation.py --query-type use_image
```

The Python client supports the following command-line arguments:

- `--query-type` (or `-q`): Query type (default: `use_video`)
  - Options: `text`, `use_audio`, `use_image`, `use_video`
- `--model` (or `-m`): Model name/path (default: `Qwen/Qwen3-Omni-30B-A3B-Instruct`)
- `--video-path` (or `-v`): Path to local video file or URL
  - If not provided and query-type is `use_video`, uses default video URL
  - Supports local file paths (automatically encoded to base64) or HTTP/HTTPS URLs
  - Example: `--video-path /path/to/video.mp4` or `--video-path https://example.com/video.mp4`
- `--image-path` (or `-i`): Path to local image file or URL
  - If not provided and query-type is `use_image`, uses default image URL
  - Supports local file paths (automatically encoded to base64) or HTTP/HTTPS URLs
  - Supports common image formats: JPEG, PNG, GIF, WebP
  - Example: `--image-path /path/to/image.jpg` or `--image-path https://example.com/image.png`
- `--audio-path` (or `-a`): Path to local audio file or URL
  - If not provided and query-type is `use_audio`, uses default audio URL
  - Supports local file paths (automatically encoded to base64) or HTTP/HTTPS URLs
  - Supports common audio formats: MP3, WAV, OGG, FLAC, M4A
  - Example: `--audio-path /path/to/audio.wav` or `--audio-path https://example.com/audio.mp3`
- `--prompt` (or `-p`): Custom text prompt/question
  - If not provided, uses default prompt for the selected query type
  - Example: `--prompt "What are the main activities shown in this video?"`


For example, to use a local video file with custom prompt:

```bash
python openai_chat_completion_client_for_multimodal_generation.py \
    --query-type use_video \
    --video-path /path/to/your/video.mp4 \
    --prompt "What are the main activities shown in this video?"
```

####  Send request via curl

```bash
bash run_curl_multimodal_generation.sh use_image
```


### FAQ

If you encounter error about backend of librosa, try to install ffmpeg with command below.
```
sudo apt update
sudo apt install ffmpeg
```

## Modality control
If you want to control output modalities, e.g. only output text, you can run the command below:
```bash
python openai_chat_completion_client_for_multimodal_generation.py \
    --query-type use_image \
    --modalities text
```

## Run Local Web UI Demo

This Web UI demo allows users to interact with the model through a web browser.

### Running Gradio Demo

The Gradio demo connects to a vLLM API server. You have two options:

#### Option 1: One-step Launch Script (Recommended)

The convenience script launches both the vLLM server and Gradio demo together:

```bash
./run_gradio_demo.sh --model Qwen/Qwen3-Omni-30B-A3B-Instruct --server-port 8091 --gradio-port 7861
```

This script will:
1. Start the vLLM server in the background
2. Wait for the server to be ready
3. Launch the Gradio demo
4. Handle cleanup when you press Ctrl+C

The script supports the following arguments:
- `--model`: Model name/path (default: Qwen/Qwen3-Omni-30B-A3B-Instruct)
- `--server-port`: Port for vLLM server (default: 8091)
- `--gradio-port`: Port for Gradio demo (default: 7861)
- `--stage-configs-path`: Path to custom stage configs YAML file (optional)
- `--server-host`: Host for vLLM server (default: 0.0.0.0)
- `--gradio-ip`: IP for Gradio demo (default: 127.0.0.1)
- `--share`: Share Gradio demo publicly (creates a public link)

#### Option 2: Manual Launch (Two-Step Process)

**Step 1: Launch the vLLM API server**

```bash
vllm serve Qwen/Qwen3-Omni-30B-A3B-Instruct --omni --port 8091
```

If you have custom stage configs file:
```bash
vllm serve Qwen/Qwen3-Omni-30B-A3B-Instruct --omni --port 8091 --stage-configs-path /path/to/stage_configs_file
```

**Step 2: Run the Gradio demo**

In a separate terminal:

```bash
python gradio_demo.py --model Qwen/Qwen3-Omni-30B-A3B-Instruct --api-base http://localhost:8091/v1 --port 7861
```

Then open `http://localhost:7861/` on your local browser to interact with the web UI.

The gradio script supports the following arguments:

- `--model`: Model name/path (should match the server model)
- `--api-base`: Base URL for the vLLM API server (default: http://localhost:8091/v1)
- `--ip`: Host/IP for Gradio server (default: 127.0.0.1)
- `--port`: Port for Gradio server (default: 7861)
- `--share`: Share the Gradio demo publicly (creates a public link)

## Example materials

??? abstract "gradio_demo.py"
    ``````py
    --8<-- "examples/online_serving/qwen3_omni/gradio_demo.py"
    ``````
??? abstract "openai_chat_completion_client_for_multimodal_generation.py"
    ``````py
    --8<-- "examples/online_serving/qwen3_omni/openai_chat_completion_client_for_multimodal_generation.py"
    ``````
??? abstract "qwen3_omni_moe_thinking.yaml"
    ``````yaml
    --8<-- "examples/online_serving/qwen3_omni/qwen3_omni_moe_thinking.yaml"
    ``````
??? abstract "run_curl_multimodal_generation.sh"
    ``````sh
    --8<-- "examples/online_serving/qwen3_omni/run_curl_multimodal_generation.sh"
    ``````
??? abstract "run_gradio_demo.sh"
    ``````sh
    --8<-- "examples/online_serving/qwen3_omni/run_gradio_demo.sh"
    ``````