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[Docs] optimize and supplement docs system (#86)

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Signed-off-by: Gaohan123 <gaohan19@huawei.com>
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Gao Han authored and GitHub committed 2025-11-28 11:03:52 +08:00
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docs/user_guide/examples/offline_inference/qwen2_5_omni.md
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# Offline Example of vLLM-omni for Qwen2.5-omni
Source <https://github.com/vllm-project/vllm-omni/tree/main/examples\offline_inference\qwen2_5_omni>.
Source <https://github.com/vllm-project/vllm-omni/tree/main/examples/offline_inference/qwen2_5_omni>.
## 🛠️ Installation
@@ -36,29 +36,29 @@ Then run the command below.
bash run_single_prompt.sh
```
### FAQ
If you encounter error about backend of librosa, try to install ffmpeg with command below.
```
sudo apt update
sudo apt install ffmpeg
```
## Example materials
??? abstract "end2end.py"
``````py
--8<-- "examples\offline_inference\qwen2_5_omni\end2end.py"
--8<-- "examples/offline_inference/qwen2_5_omni/end2end.py"
``````
??? abstract "extract_prompts.py"
``````py
--8<-- "examples\offline_inference\qwen2_5_omni\extract_prompts.py"
``````
??? abstract "processing_omni.py"
``````py
--8<-- "examples\offline_inference\qwen2_5_omni\processing_omni.py"
--8<-- "examples/offline_inference/qwen2_5_omni/extract_prompts.py"
``````
??? abstract "run_multiple_prompts.sh"
``````sh
--8<-- "examples\offline_inference\qwen2_5_omni\run_multiple_prompts.sh"
--8<-- "examples/offline_inference/qwen2_5_omni/run_multiple_prompts.sh"
``````
??? abstract "run_single_prompt.sh"
``````sh
--8<-- "examples\offline_inference\qwen2_5_omni\run_single_prompt.sh"
``````
??? abstract "utils.py"
``````py
--8<-- "examples\offline_inference\qwen2_5_omni\utils.py"
--8<-- "examples/offline_inference/qwen2_5_omni/run_single_prompt.sh"
``````
docs/user_guide/examples/offline_inference/qwen_2_5_omni.md
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# Offline Example of vLLM-omni for Qwen2.5-omni
Source <https://github.com/vllm-project/vllm-omni/tree/main/examples/offline_inference/qwen_2_5_omni>.
## 🛠️ Installation
### Environment setup
Use Docker to keep consistent basic environment (Optional, Recommended)
```bash
docker run --gpus all --ipc=host --network=host -v $source_dir:$container_dir --name $container_name -it nvcr.io/nvidia/pytorch:25.01-py3 bash
```
Set up basic uv environment
```bash
pip install uv
uv venv --python 3.12 --seed
source .venv/bin/activate
```
### Installation of vLLM (for users)
Now we build it based on vLLM v0.11.0. Please install it with command below.
```bash
uv pip install vllm==0.11.0 --torch-backend=auto
```
### Installation of vLLM (for developers)
If you want to check or debug with source code of vLLM, install stable release version of vllm with 0.11.0 from source with pre-built wheel file.
```bash
git clone https://github.com/vllm-project/vllm.git
cd vllm
git checkout v0.11.0
```
Set up environment variables to get pre-built wheels. If there are internet problems, just download the whl file manually. And set VLLM_PRECOMPILED_WHEEL_LOCATION as your local absolute path of whl file.
```bash
export VLLM_PRECOMPILED_WHEEL_LOCATION=https://github.com/vllm-project/vllm/releases/download/v0.11.0/vllm-0.11.0-cp38-abi3-manylinux1_x86_64.whl
```
Install vllm with command below (If you have no existing PyTorch).
```bash
uv pip install --editable .
```
Install vllm with command below (If you already have PyTorch).
```bash
python use_existing_torch.py
uv pip install -r requirements/build.txt
uv pip install --no-build-isolation --editable .
```
### Verification for successful installation of vLLM
Just run the command below. If no error, it demonstrates that the installation is successful.
```bash
python -c "import vllm._C"
```
### Installation of vLLM-omni
Install additional requirements for vllm-omni
```bash
git clone https://github.com/vllm-project/vllm-omni.git
cd vllm_omni
uv pip install -e .
```
## Run examples (Qwen2.5-omni)
Get into the example folder
```bash
cd examples/offline_inference/qwen_2_5_omni
```
Then run
```bash
bash run.sh
```
The output audio is saved in ./output_audio
## Example materials
??? abstract "end2end.py"
``````py
--8<-- "examples/offline_inference/qwen_2_5_omni/end2end.py"
``````
??? abstract "processing_omni.py"
``````py
--8<-- "examples/offline_inference/qwen_2_5_omni/processing_omni.py"
``````
??? abstract "run.sh"
``````sh
--8<-- "examples/offline_inference/qwen_2_5_omni/run.sh"
``````
??? abstract "utils.py"
``````py
--8<-- "examples/offline_inference/qwen_2_5_omni/utils.py"
``````