Revert "docs: add reference to docs.ollama.com (#12800)" (#12803)

This reverts commit 934dd9e1.

Revert "docs: add reference to docs.ollama.com (#12800)" (#12803)
This reverts commit 934dd9e1.
5483497d · Parth Sareen · GitHub · 934dd9e1 · 934dd9e1 · 934dd9e1
Unverified Commit 5483497d authored Oct 28, 2025 by Parth Sareen Committed by GitHub Oct 28, 2025
17 changed files
--- a/docs/integrations/vscode.mdx
+++ b/docs/integrations/vscode.mdx
---
-title: VS Code 
---
-## Install
-Install [VSCode](https://code.visualstudio.com/download). 
-## Usage with Ollama 
-1. Open Copilot side bar found in top right window
-<div style={{ display: 'flex', justifyContent: 'center' }}>
-  <img 
-    src="/images/vscode-sidebar.png" 
-    alt="VSCode chat Sidebar"
-    width="75%"
-  />
-</div>
-2. Select the model drowpdown > **Manage models**
-<div style={{ display: 'flex', justifyContent: 'center' }}>
-  <img 
-    src="/images/vscode-models.png" 
-    alt="VSCode model picker"
-    width="75%"
-  />
-</div>
-3. Enter **Ollama** under **Provider Dropdown** and select desired models (e.g `qwen3, qwen3-coder:480b-cloud`)
-<div style={{ display: 'flex', justifyContent: 'center' }}>
-  <img 
-    src="/images/vscode-model-options.png" 
-    alt="VSCode model options dropdown"
-    width="75%"
-  />
-</div>
--- a/docs/integrations/xcode.mdx
+++ b/docs/integrations/xcode.mdx
---
-title: Xcode 
---
-## Install
-Install [XCode](https://developer.apple.com/xcode/)
-## Usage with Ollama 
-<Note> Ensure Apple Intelligence is setup and the latest XCode version is v26.0 </Note>
-1. Click **XCode** in top left corner > **Settings** 
-<div style={{ display: 'flex', justifyContent: 'center' }}>
-  <img 
-    src="/images/xcode-intelligence-window.png" 
-    alt="Xcode Intelligence window"
-    width="50%"
-  />
-</div>
-2. Select **Locally Hosted**, enter port **11434** and click **Add**
-<div style={{ display: 'flex', justifyContent: 'center' }}>
-  <img 
-    src="/images/xcode-locally-hosted.png" 
-    alt="Xcode settings"
-    width="50%"
-  />
-</div>
-3. Select the **star icon** on the top left corner and click the **dropdown**
-<div style={{ display: 'flex', justifyContent: 'center' }}>
-  <img 
-    src="/images/xcode-chat-icon.png" 
-    alt="Xcode settings"
-    width="50%"
-  />
-</div>
-4. Click **My Account** and select your desired model
-## Connecting to ollama.com directly
-1. Create an [API key](https://ollama.com/settings/keys) from ollama.com 
-2. Select **Internet Hosted** and enter URL as `https://ollama.com`  
-3. Enter your **Ollama API Key** and click **Add** 
\ No newline at end of file
--- a/docs/integrations/zed.mdx
+++ b/docs/integrations/zed.mdx
---
-title: Zed
---
-## Install
-Install [Zed](https://zed.dev/download).
-## Usage with Ollama
-1. In Zed, click the **star icon** in the bottom-right corner, then select **Configure**.
-<div style={{ display: 'flex', justifyContent: 'center' }}>
-  <img 
-    src="/images/zed-settings.png" 
-    alt="Zed star icon in bottom right corner"
-    width="50%"
-  />
-</div>
-2. Under **LLM Providers**, choose **Ollama**
-3. Confirm the **Host URL** is `http://localhost:11434`, then click **Connect**
-4. Once connected, select a model under **Ollama**
-<div style={{ display: 'flex', justifyContent: 'center' }}>
-  <img 
-    src="/images/zed-ollama-dropdown.png" 
-    alt="Zed star icon in bottom right corner"
-    width="50%"
-  />
-</div>
-## Connecting to ollama.com
-1. Create an [API key](https://ollama.com/settings/keys) on **ollama.com**
-2. In Zed, open the **star icon** → **Configure**
-3. Under **LLM Providers**, select **Ollama**
-4. Set the **API URL** to `https://ollama.com`
--- a/docs/linux.mdx
+++ b/docs/linux.mdx
---
-title: Linux
---
-## Install
-To install Ollama, run the following command:
-```shell
-curl -fsSL https://ollama.com/install.sh | sh
-```
-## Manual install
-<Note>
-  If you are upgrading from a prior version, you should remove the old libraries
-  with `sudo rm -rf /usr/lib/ollama` first.
-</Note>
-Download and extract the package:
-```shell
-curl -fsSL https://ollama.com/download/ollama-linux-amd64.tgz \
-    | sudo tar zx -C /usr
-```
-Start Ollama:
-```shell
-ollama serve
-```
-In another terminal, verify that Ollama is running:
-```shell
-ollama -v
-```
-### AMD GPU install
-If you have an AMD GPU, also download and extract the additional ROCm package:
-```shell
-curl -fsSL https://ollama.com/download/ollama-linux-amd64-rocm.tgz \
-    | sudo tar zx -C /usr
-```
-### ARM64 install
-Download and extract the ARM64-specific package:
-```shell
-curl -fsSL https://ollama.com/download/ollama-linux-arm64.tgz \
-    | sudo tar zx -C /usr
-```
-### Adding Ollama as a startup service (recommended)
-Create a user and group for Ollama:
-```shell
-sudo useradd -r -s /bin/false -U -m -d /usr/share/ollama ollama
-sudo usermod -a -G ollama $(whoami)
-```
-Create a service file in `/etc/systemd/system/ollama.service`:
-```ini
-[Unit]
-Description=Ollama Service
-After=network-online.target
-[Service]
-ExecStart=/usr/bin/ollama serve
-User=ollama
-Group=ollama
-Restart=always
-RestartSec=3
-Environment="PATH=$PATH"
-[Install]
-WantedBy=multi-user.target
-```
-Then start the service:
-```shell
-sudo systemctl daemon-reload
-sudo systemctl enable ollama
-```
-### Install CUDA drivers (optional)
-[Download and install](https://developer.nvidia.com/cuda-downloads) CUDA.
-Verify that the drivers are installed by running the following command, which should print details about your GPU:
-```shell
-nvidia-smi
-```
-### Install AMD ROCm drivers (optional)
-[Download and Install](https://rocm.docs.amd.com/projects/install-on-linux/en/latest/tutorial/quick-start.html) ROCm v6.
-### Start Ollama
-Start Ollama and verify it is running:
-```shell
-sudo systemctl start ollama
-sudo systemctl status ollama
-```
-<Note>
-  While AMD has contributed the `amdgpu` driver upstream to the official linux
-  kernel source, the version is older and may not support all ROCm features. We
-  recommend you install the latest driver from
-  https://www.amd.com/en/support/linux-drivers for best support of your Radeon
-  GPU.
-</Note>
-## Customizing
-To customize the installation of Ollama, you can edit the systemd service file or the environment variables by running:
-```shell
-sudo systemctl edit ollama
-```
-Alternatively, create an override file manually in `/etc/systemd/system/ollama.service.d/override.conf`:
-```ini
-[Service]
-Environment="OLLAMA_DEBUG=1"
-```
-## Updating
-Update Ollama by running the install script again:
-```shell
-curl -fsSL https://ollama.com/install.sh | sh
-```
-Or by re-downloading Ollama:
-```shell
-curl -fsSL https://ollama.com/download/ollama-linux-amd64.tgz \
-    | sudo tar zx -C /usr
-```
-## Installing specific versions
-Use `OLLAMA_VERSION` environment variable with the install script to install a specific version of Ollama, including pre-releases. You can find the version numbers in the [releases page](https://github.com/ollama/ollama/releases).
-For example:
-```shell
-curl -fsSL https://ollama.com/install.sh | OLLAMA_VERSION=0.5.7 sh
-```
-## Viewing logs
-To view logs of Ollama running as a startup service, run:
-```shell
-journalctl -e -u ollama
-```
-## Uninstall
-Remove the ollama service:
-```shell
-sudo systemctl stop ollama
-sudo systemctl disable ollama
-sudo rm /etc/systemd/system/ollama.service
-```
-Remove ollama libraries from your lib directory (either `/usr/local/lib`, `/usr/lib`, or `/lib`):
-```shell
-sudo rm -r $(which ollama | tr 'bin' 'lib')
-```
-Remove the ollama binary from your bin directory (either `/usr/local/bin`, `/usr/bin`, or `/bin`):
-```shell
-sudo rm $(which ollama)
-```
-Remove the downloaded models and Ollama service user and group:
-```shell
-sudo userdel ollama
-sudo groupdel ollama
-sudo rm -r /usr/share/ollama
-```
--- a/docs/logo.svg
+++ b/docs/logo.svg
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--- a/docs/modelfile.mdx
+++ b/docs/modelfile.mdx
---
-title: Modelfile Reference
---
-A Modelfile is the blueprint to create and share customized models using Ollama.
-## Table of Contents
- [Format](#format)
- [Examples](#examples)
- [Instructions](#instructions)
-  - [FROM (Required)](#from-required)
-    - [Build from existing model](#build-from-existing-model)
-    - [Build from a Safetensors model](#build-from-a-safetensors-model)
-    - [Build from a GGUF file](#build-from-a-gguf-file)
-  - [PARAMETER](#parameter)
-    - [Valid Parameters and Values](#valid-parameters-and-values)
-  - [TEMPLATE](#template)
-    - [Template Variables](#template-variables)
-  - [SYSTEM](#system)
-  - [ADAPTER](#adapter)
-  - [LICENSE](#license)
-  - [MESSAGE](#message)
- [Notes](#notes)
-## Format
-The format of the `Modelfile`:
-```
-# comment
-INSTRUCTION arguments
-```
-| Instruction                         | Description                                                    |
-| ----------------------------------- | -------------------------------------------------------------- |
-| [`FROM`](#from-required) (required) | Defines the base model to use.                                 |
-| [`PARAMETER`](#parameter)           | Sets the parameters for how Ollama will run the model.         |
-| [`TEMPLATE`](#template)             | The full prompt template to be sent to the model.              |
-| [`SYSTEM`](#system)                 | Specifies the system message that will be set in the template. |
-| [`ADAPTER`](#adapter)               | Defines the (Q)LoRA adapters to apply to the model.            |
-| [`LICENSE`](#license)               | Specifies the legal license.                                   |
-| [`MESSAGE`](#message)               | Specify message history.                                       |
-## Examples
-### Basic `Modelfile`
-An example of a `Modelfile` creating a mario blueprint:
-```
-FROM llama3.2
-# sets the temperature to 1 [higher is more creative, lower is more coherent]
-PARAMETER temperature 1
-# sets the context window size to 4096, this controls how many tokens the LLM can use as context to generate the next token
-PARAMETER num_ctx 4096
-# sets a custom system message to specify the behavior of the chat assistant
-SYSTEM You are Mario from super mario bros, acting as an assistant.
-```
-To use this:
-1. Save it as a file (e.g. `Modelfile`)
-2. `ollama create choose-a-model-name -f <location of the file e.g. ./Modelfile>`
-3. `ollama run choose-a-model-name`
-4. Start using the model!
-To view the Modelfile of a given model, use the `ollama show --modelfile` command.
-```shell
-ollama show --modelfile llama3.2
-```
-```
-# Modelfile generated by "ollama show"
-# To build a new Modelfile based on this one, replace the FROM line with:
-# FROM llama3.2:latest
-FROM /Users/pdevine/.ollama/models/blobs/sha256-00e1317cbf74d901080d7100f57580ba8dd8de57203072dc6f668324ba545f29
-TEMPLATE """{{ if .System }}<|start_header_id|>system<|end_header_id|>
-{{ .System }}<|eot_id|>{{ end }}{{ if .Prompt }}<|start_header_id|>user<|end_header_id|>
-{{ .Prompt }}<|eot_id|>{{ end }}<|start_header_id|>assistant<|end_header_id|>
-{{ .Response }}<|eot_id|>"""
-PARAMETER stop "<|start_header_id|>"
-PARAMETER stop "<|end_header_id|>"
-PARAMETER stop "<|eot_id|>"
-PARAMETER stop "<|reserved_special_token"
-```
-## Instructions
-### FROM (Required)
-The `FROM` instruction defines the base model to use when creating a model.
-```
-FROM <model name>:<tag>
-```
-#### Build from existing model
-```
-FROM llama3.2
-```
-<Card title="Base Models" href="https://github.com/ollama/ollama#model-library">
-  A list of available base models
-</Card>
-<Card title="Base Models" href="https://ollama.com/library">
-  Additional models can be found at
-</Card>
-#### Build from a Safetensors model
-```
-FROM <model directory>
-```
-The model directory should contain the Safetensors weights for a supported architecture.
-Currently supported model architectures:
- Llama (including Llama 2, Llama 3, Llama 3.1, and Llama 3.2)
- Mistral (including Mistral 1, Mistral 2, and Mixtral)
- Gemma (including Gemma 1 and Gemma 2)
- Phi3
-#### Build from a GGUF file
-```
-FROM ./ollama-model.gguf
-```
-The GGUF file location should be specified as an absolute path or relative to the `Modelfile` location.
-### PARAMETER
-The `PARAMETER` instruction defines a parameter that can be set when the model is run.
-```
-PARAMETER <parameter> <parametervalue>
-```
-#### Valid Parameters and Values
-| Parameter      | Description                                                                                                                                                                                                                                                                                                                                                                     | Value Type | Example Usage        |
-| -------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ---------- | -------------------- |
-| mirostat       | Enable Mirostat sampling for controlling perplexity. (default: 0, 0 = disabled, 1 = Mirostat, 2 = Mirostat 2.0)                                                                                                                                                                                                                                                                 | int        | mirostat 0           |
-| mirostat_eta   | Influences how quickly the algorithm responds to feedback from the generated text. A lower learning rate will result in slower adjustments, while a higher learning rate will make the algorithm more responsive. (Default: 0.1)                                                                                                                                                | float      | mirostat_eta 0.1     |
-| mirostat_tau   | Controls the balance between coherence and diversity of the output. A lower value will result in more focused and coherent text. (Default: 5.0)                                                                                                                                                                                                                                 | float      | mirostat_tau 5.0     |
-| num_ctx        | Sets the size of the context window used to generate the next token. (Default: 2048)                                                                                                                                                                                                                                                                                            | int        | num_ctx 4096         |
-| repeat_last_n  | Sets how far back for the model to look back to prevent repetition. (Default: 64, 0 = disabled, -1 = num_ctx)                                                                                                                                                                                                                                                                   | int        | repeat_last_n 64     |
-| repeat_penalty | Sets how strongly to penalize repetitions. A higher value (e.g., 1.5) will penalize repetitions more strongly, while a lower value (e.g., 0.9) will be more lenient. (Default: 1.1)                                                                                                                                                                                             | float      | repeat_penalty 1.1   |
-| temperature    | The temperature of the model. Increasing the temperature will make the model answer more creatively. (Default: 0.8)                                                                                                                                                                                                                                                             | float      | temperature 0.7      |
-| seed           | Sets the random number seed to use for generation. Setting this to a specific number will make the model generate the same text for the same prompt. (Default: 0)                                                                                                                                                                                                               | int        | seed 42              |
-| stop           | Sets the stop sequences to use. When this pattern is encountered the LLM will stop generating text and return. Multiple stop patterns may be set by specifying multiple separate `stop` parameters in a modelfile.                                                                                                                                                              | string     | stop "AI assistant:" |
-| num_predict    | Maximum number of tokens to predict when generating text. (Default: -1, infinite generation)                                                                                                                                                                                                                                                                                    | int        | num_predict 42       |
-| top_k          | Reduces the probability of generating nonsense. A higher value (e.g. 100) will give more diverse answers, while a lower value (e.g. 10) will be more conservative. (Default: 40)                                                                                                                                                                                                | int        | top_k 40             |
-| top_p          | Works together with top-k. A higher value (e.g., 0.95) will lead to more diverse text, while a lower value (e.g., 0.5) will generate more focused and conservative text. (Default: 0.9)                                                                                                                                                                                         | float      | top_p 0.9            |
-| min_p          | Alternative to the top*p, and aims to ensure a balance of quality and variety. The parameter \_p* represents the minimum probability for a token to be considered, relative to the probability of the most likely token. For example, with _p_=0.05 and the most likely token having a probability of 0.9, logits with a value less than 0.045 are filtered out. (Default: 0.0) | float      | min_p 0.05           |
-### TEMPLATE
-`TEMPLATE` of the full prompt template to be passed into the model. It may include (optionally) a system message, a user's message and the response from the model. Note: syntax may be model specific. Templates use Go [template syntax](https://pkg.go.dev/text/template).
-#### Template Variables
-| Variable          | Description                                                                                   |
-| ----------------- | --------------------------------------------------------------------------------------------- |
-| `{{ .System }}`   | The system message used to specify custom behavior.                                           |
-| `{{ .Prompt }}`   | The user prompt message.                                                                      |
-| `{{ .Response }}` | The response from the model. When generating a response, text after this variable is omitted. |
-```
-TEMPLATE """{{ if .System }}<|im_start|>system
-{{ .System }}<|im_end|>
-{{ end }}{{ if .Prompt }}<|im_start|>user
-{{ .Prompt }}<|im_end|>
-{{ end }}<|im_start|>assistant
-"""
-```
-### SYSTEM
-The `SYSTEM` instruction specifies the system message to be used in the template, if applicable.
-```
-SYSTEM """<system message>"""
-```
-### ADAPTER
-The `ADAPTER` instruction specifies a fine tuned LoRA adapter that should apply to the base model. The value of the adapter should be an absolute path or a path relative to the Modelfile. The base model should be specified with a `FROM` instruction. If the base model is not the same as the base model that the adapter was tuned from the behaviour will be erratic.
-#### Safetensor adapter
-```
-ADAPTER <path to safetensor adapter>
-```
-Currently supported Safetensor adapters:
- Llama (including Llama 2, Llama 3, and Llama 3.1)
- Mistral (including Mistral 1, Mistral 2, and Mixtral)
- Gemma (including Gemma 1 and Gemma 2)
-#### GGUF adapter
-```
-ADAPTER ./ollama-lora.gguf
-```
-### LICENSE
-The `LICENSE` instruction allows you to specify the legal license under which the model used with this Modelfile is shared or distributed.
-```
-LICENSE """
-<license text>
-"""
-```
-### MESSAGE
-The `MESSAGE` instruction allows you to specify a message history for the model to use when responding. Use multiple iterations of the MESSAGE command to build up a conversation which will guide the model to answer in a similar way.
-```
-MESSAGE <role> <message>
-```
-#### Valid roles
-| Role      | Description                                                  |
-| --------- | ------------------------------------------------------------ |
-| system    | Alternate way of providing the SYSTEM message for the model. |
-| user      | An example message of what the user could have asked.        |
-| assistant | An example message of how the model should respond.          |
-#### Example conversation
-```
-MESSAGE user Is Toronto in Canada?
-MESSAGE assistant yes
-MESSAGE user Is Sacramento in Canada?
-MESSAGE assistant no
-MESSAGE user Is Ontario in Canada?
-MESSAGE assistant yes
-```
-## Notes
- the **`Modelfile` is not case sensitive**. In the examples, uppercase instructions are used to make it easier to distinguish it from arguments.
- Instructions can be in any order. In the examples, the `FROM` instruction is first to keep it easily readable.
-[1]: https://ollama.com/library
--- a/docs/n8n.mdx
+++ b/docs/n8n.mdx
---
-title: n8n
---
-## Install
-Install [n8n](https://docs.n8n.io/choose-n8n/).
-## Using Ollama Locally
-1. In the top right corner, click the dropdown and select **Create Credential**
-<div style={{ display: 'flex', justifyContent: 'center' }}>
-  <img 
-    src="/images/n8n-credential-creation.png" 
-    alt="Create a n8n Credential"
-    width="75%"
-  />
-</div>
-2. Under **Add new credential** select **Ollama**
-<div style={{ display: 'flex', justifyContent: 'center' }}>
-  <img 
-    src="/images/n8n-ollama-form.png" 
-    alt="Select Ollama under Credential"
-    width="75%"
-  />
-</div>
-3. Confirm Base URL is set to `http://localhost:11434` and click **Save**
-<Note> If connecting to `http://localhost:11434` fails, use `http://127.0.0.1:11434`</Note>
-4. When creating a new workflow, select **Add a first step** and select an **Ollama node** 
-<div style={{ display: 'flex', justifyContent: 'center' }}>
-  <img 
-    src="/images/n8n-chat-node.png" 
-    alt="Add a first step with Ollama node"
-    width="75%"
-  />
-</div>
-5. Select your model of choice (e.g. `qwen3-coder`) 
-<div style={{ display: 'flex', justifyContent: 'center' }}>
-  <img 
-    src="/images/n8n-models.png" 
-    alt="Set up Ollama credentials"
-    width="75%"
-  />
-</div>
-## Connecting to ollama.com
-1. Create an [API key](https://ollama.com/settings/keys) on **ollama.com**.  
-2. In n8n, click **Create Credential** and select **Ollama**
-4. Set the **API URL** to `https://ollama.com`
-5. Enter your **API Key** and click **Save**
--- a/docs/ollama-logo.svg
+++ b/docs/ollama-logo.svg
-<svg width="17" height="25" viewBox="0 0 17 25" fill="none" xmlns="http://www.w3.org/2000/svg">
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-</svg>
--- a/docs/ollama.png
+++ b/docs/ollama.png
--- a/docs/openapi.yaml
+++ b/docs/openapi.yaml
--- a/docs/quickstart.mdx
+++ b/docs/quickstart.mdx
---
-title: Quickstart
---
-This quickstart will walk your through running your first model with Ollama. To get started, download Ollama on macOS, Windows or Linux.
-<a
-  href="https://ollama.com/download"
-  target="_blank"
-  className="inline-block px-6 py-2 bg-black rounded-full dark:bg-neutral-700 text-white font-normal border-none"
->
-  Download Ollama
-</a>
-## Run a model
-<Tabs>
-  <Tab title="CLI">
-    Open a terminal and run the command:
-    ```
-    ollama run gemma3
-    ```
-  </Tab>
-  <Tab title="cURL">
-    ```
-    ollama pull gemma3
-    ```
-    Lastly, chat with the model:
-    ```shell
-    curl http://localhost:11434/api/chat -d '{
-      "model": "gemma3",
-      "messages": [{
-        "role": "user",
-        "content": "Hello there!"
-      }],
-      "stream": false
-    }'
-    ```
-  </Tab>
-  <Tab title="Python">
-    Start by downloading a model:
-    ```
-    ollama pull gemma3
-    ```
-    Then install Ollama's Python library:
-    ```
-    pip install ollama
-    ```
-    Lastly, chat with the model:
-    ```python
-    from ollama import chat
-    from ollama import ChatResponse
-    response: ChatResponse = chat(model='gemma3', messages=[
-      {
-        'role': 'user',
-        'content': 'Why is the sky blue?',
-      },
-    ])
-    print(response['message']['content'])
-    # or access fields directly from the response object
-    print(response.message.content)
-    ```
-  </Tab>
-  <Tab title="JavaScript">
-    Start by downloading a model:
-    ```
-    ollama pull gemma3
-    ```
-    Then install the Ollama JavaScript library:
-    ```
-    npm i ollama
-    ```
-    Lastly, chat with the model:
-    ```shell
-    import ollama from 'ollama'
-    const response = await ollama.chat({
-      model: 'gemma3',
-      messages: [{ role: 'user', content: 'Why is the sky blue?' }],
-    })
-    console.log(response.message.content)
-    ```
-  </Tab>
-</Tabs>
-See a full list of available models [here](https://ollama.com/models).
--- a/docs/styling.css
+++ b/docs/styling.css
-body {
-    font-family: ui-sans-serif, system-ui, sans-serif, Apple Color Emoji,Segoe UI Emoji,Segoe UI Symbol,Noto Color Emoji;
-}
-pre, code, .font-mono {
-    font-family: ui-monospace,SFMono-Regular,Menlo,Monaco,Consolas,monospace;
-}
-.nav-logo {
-    height: 44px;
-}
-.eyebrow {
-    color: #666;
-    font-weight: 400;
-}
--- a/docs/template.mdx
+++ b/docs/template.mdx
--- a/docs/text.mdx
+++ b/docs/text.mdx
---
-title: Text generation
---
--- a/docs/troubleshooting.mdx
+++ b/docs/troubleshooting.mdx
--- a/docs/vision.mdx
+++ b/docs/vision.mdx
---
-title: Vision
-description: Provide images to models
---
--- a/docs/windows.mdx
+++ b/docs/windows.mdx