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

Signed-off-by: Gaohan123 <gaohan19@huawei.com>

docs/getting_started/installation/.nav.yml

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+nav:
+  - README.md
+  - gpu.md
+  - npu.md

docs/getting_started/installation/README.md

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+# Installation
+
+vLLM supports the following hardware platforms:
+
+- [GPU](gpu.md)
+    - [NVIDIA CUDA](gpu.md#nvidia-cuda)
+- [Ascend NPU](npu.md)

docs/getting_started/installation/gpu.md

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+# GPU
+
+vLLM-Omni is a Python library that supports the following GPU variants. Select your GPU type to see vendor specific instructions:
+
+[](){ #nvidia-cuda }
+
+=== "NVIDIA CUDA"
+
+    --8<-- "docs/getting_started/installation/gpu/cuda.inc.md:installation"
+
+## Requirements
+
+- OS: Linux
+- Python: 3.12
+
+!!! note
+    vLLM-Omni does not support Windows natively.
+
+=== "NVIDIA CUDA"
+
+    --8<-- "docs/getting_started/installation/gpu/cuda.inc.md:requirements"
+
+## Set up using Python
+
+### Create a new Python environment
+
+--8<-- "docs/getting_started/installation/python_env_setup.inc.md"
+
+=== "NVIDIA CUDA"
+
+    --8<-- "docs/getting_started/installation/gpu/cuda.inc.md:set-up-using-python"
+
+### Pre-built wheels
+
+=== "NVIDIA CUDA"
+
+    --8<-- "docs/getting_started/installation/gpu/cuda.inc.md:pre-built-wheels"
+
+[](){ #build-from-source }
+
+### Build wheel from source
+
+=== "NVIDIA CUDA"
+
+    --8<-- "docs/getting_started/installation/gpu/cuda.inc.md:build-wheel-from-source"
+
+## Set up using Docker
+
+### Pre-built images

docs/getting_started/installation/gpu/cuda.inc.md

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+# --8<-- [start:installation]
+
+vLLM-Omni mainly contains python implementations for framework and models.
+
+# --8<-- [end:installation]
+# --8<-- [start:requirements]
+
+- GPU: compute capability 7.0 or higher (e.g., V100, T4, RTX20xx, A100, L4, H100, etc.)
+
+# --8<-- [end:requirements]
+# --8<-- [start:set-up-using-python]
+
+vLLM-Omni depends vLLM. So please follow instructions below mainly for vLLM.
+
+!!! note
+    PyTorch installed via `conda` will statically link `NCCL` library, which can cause issues when vLLM tries to use `NCCL`. See <gh-issue:8420> for more details.
+
+In order to be performant, vLLM has to compile many cuda kernels. The compilation unfortunately introduces binary incompatibility with other CUDA versions and PyTorch versions, even for the same PyTorch version with different building configurations.
+
+Therefore, it is recommended to install vLLM and vLLM-Omni with a **fresh new** environment. If either you have a different CUDA version or you want to use an existing PyTorch installation, you need to build vLLM from source. See [build-from-source-vllm](https://docs.vllm.ai/en/stable/getting_started/installation/gpu/#build-wheel-from-source) for more details.
+
+# --8<-- [start:pre-built-wheels]
+
+## Installation of vLLM
+
+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-Omni
+
+```bash
+uv pip install vllm-omni
+```
+
+# --8<-- [end:pre-built-wheels]
+
+# --8<-- [start:build-wheel-from-source]
+
+## Installation of vLLM
+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 .
+```
+
+## 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 .
+```
+
+# --8<-- [end:build-wheel-from-source]

docs/getting_started/installation/npu.md

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+# Ascend-NPU
+
+vLLM-Omni is a Python library that supports the following NPU variants. Select your NPU type to see vendor specific instructions:

docs/getting_started/installation/npu/npu.inc.md

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+# --8<-- [start:installation]
+
+vLLM-Omni mainly contains python implementations for framework and models.
+
+# --8<-- [end:installation]

docs/getting_started/installation/python_env_setup.inc.md

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+It's recommended to use [uv](https://docs.astral.sh/uv/), a very fast Python environment manager, to create and manage Python environments. Please follow the [documentation](https://docs.astral.sh/uv/#getting-started) to install `uv`. After installing `uv`, you can create a new Python environment using the following commands:
+
+```bash
+uv venv --python 3.12 --seed
+source .venv/bin/activate
+```

docs/getting_started/quickstart.md

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+# Quickstart
+
+This guide will help you quickly get started with vLLM-Omni to perform:
+
+- Offline batched inference
+- Online serving using OpenAI-compatible server
+
+## Prerequisites
+
+- OS: Linux
+- Python: 3.12
+
+## Installation
+
+Please refer to [installation](installation/README.md)
+
+## Offline Inference
+
+Please refer to [offline inference](../user_guide/examples/offline_inference/qwen2_5_omni.md)
+
+## Online Serving with OpenAI-Completions API
+
+Please refer to [online serving](../user_guide/examples/online_serving/README.md)