Revert

Signed-off-by: Rafael Vasquez <[email protected]>

Author: rafvasq

.github/workflows/doc-lint.yml

@@ -0,0 +1,39 @@
+name: Lint documentation
+
+on:
+  push:
+    branches:
+      - main
+    paths:
+      - "docs/**"
+  pull_request:
+    branches:
+      - main
+    paths:
+      - "docs/**"
+
+jobs:
+  sphinx-lint:
+    runs-on: ubuntu-latest
+    strategy:
+      matrix:
+        python-version: ["3.12"]
+    steps:
+      - uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4.2.2
+      - name: Set up Python ${{ matrix.python-version }}
+        uses: actions/setup-python@0b93645e9fea7318ecaed2b359559ac225c90a2b # v5.3.0
+        with:
+          python-version: ${{ matrix.python-version }}
+      - name: Install dependencies
+        run: |
+          python -m pip install --upgrade pip
+          pip install -r requirements-lint.txt
+      - name: Linting docs
+        run: tools/sphinx-lint.sh
+  markdown-lint:
+    runs-on: ubuntu-latest
+    steps:
+    - uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683
+    - uses: DavidAnson/markdownlint-cli2-action@v19
+      with:
+        globs: "docs/**/*.md"

.github/workflows/sphinx-lint.yml

@@ -2,27 +2,72 @@
 
 # Multi-Modality
 
+```{eval-rst}
+.. currentmodule:: vllm.multimodal
+```
+
 vLLM provides experimental support for multi-modal models through the {mod}`vllm.multimodal` package.
 
 Multi-modal inputs can be passed alongside text and token prompts to [supported models](#supported-mm-models)
 via the `multi_modal_data` field in {class}`vllm.inputs.PromptType`.
 
 Looking to add your own multi-modal model? Please follow the instructions listed [here](#enabling-multimodal-inputs).
 
+
 ## Module Contents
 
+```{eval-rst}
+.. automodule:: vllm.multimodal
+```
+
+### Registry
+
 ```{eval-rst}
 .. autodata:: vllm.multimodal.MULTIMODAL_REGISTRY
 ```
 
-## Submodules
+```{eval-rst}
+.. autoclass:: vllm.multimodal.MultiModalRegistry
+    :members:
+    :show-inheritance:
+```
+
+### Base Classes
+
+```{eval-rst}
+.. automodule:: vllm.multimodal.base
+    :members:
+    :show-inheritance:
+```
 
-```{toctree}
-:maxdepth: 1
+### Input Classes
 
-inputs
-parse
-processing
-profiling
-registry
+```{eval-rst}
+.. automodule:: vllm.multimodal.inputs
+    :members:
+    :show-inheritance:
+```
+
+### Audio Classes
+
+```{eval-rst}
+.. automodule:: vllm.multimodal.audio
+    :members:
+    :show-inheritance:
+```
+
+### Image Classes
+
+```{eval-rst}
+.. automodule:: vllm.multimodal.image
+    :members:
+    :show-inheritance:
+```
+
+### Video Classes
+
+```{eval-rst}
+.. automodule:: vllm.multimodal.video
+    :members:
+    :show-inheritance:
 ```

.markdownlint-cli2.yaml

@@ -19,3 +19,4 @@ Optional parameters for vLLM APIs.
 .. autoclass:: vllm.PoolingParams
     :members:
 ```
+

docs/source/api/inference_params.md

@@ -21,7 +21,7 @@ This document describes how vLLM deals with these challenges.
 
 ## Multiprocessing Methods
 
-[Python multiprocessing methods](https://docs.python.org/3/library/multiprocessing.html#contexts-and-start-methods) include:
+[Python multiprocessing methods](https://docs.python.org/3/library/multiprocessing.html.md#contexts-and-start-methods) include:
 
 - `spawn` - spawn a new Python process. This will be the default as of Python
   3.14.

docs/source/api/model/adapters.md

@@ -15,19 +15,10 @@ This guide will help you quickly get started with vLLM to perform:
 ## Installation
 
 If you are using NVIDIA GPUs, you can install vLLM using [pip](https://pypi.org/project/vllm/) directly.
-
-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 and install vLLM using the following commands:
-
-```console
-$ uv venv myenv --python 3.12 --seed
-$ source myenv/bin/activate
-$ uv pip install vllm
-```
-
-You can also use [conda](https://docs.conda.io/projects/conda/en/latest/user-guide/getting-started.html) to create and manage Python environments.
+It's recommended to use [conda](https://docs.conda.io/projects/conda/en/latest/user-guide/getting-started.html) to create and manage Python environments.
 
 ```console
-$ conda create -n myenv python=3.12 -y
+$ conda create -n myenv python=3.10 -y
 $ conda activate myenv
 $ pip install vllm
 ```

docs/source/api/model/index.md

@@ -139,9 +139,8 @@ community/sponsors
 
 api/offline_inference/index
 api/engine/index
-api/inference_params
 api/multimodal/index
-api/model/index
+api/params
 ```
 
 % Design Documents: Details about vLLM internals