GitLab

* docs: add docs for v1/responses and rework openai compat section

I reworked the examples to be separated by topic and to be fully
runnable (i.e., they now log output instead of just suggesting how a
call might be made).

We now use `<CodeGroup>`s so that each example has a dropdown on the
docs site for users to choose, which makes the examples a lot more
digestible (since you only see approx 1/3 of the code you used to).

I also added a new tool to extract code examples into files so that it's
easier to actually run them and check that they work.

## Example

```shell
go run docs/tools/extract-examples/main.go docs/api/openai-compatibility.mdx
```

Output:

```
Extracting code examples to: /var/folders/vq/wfm2g6k917d3ldzpjdxc8ph00000gn/T/mdx-examples-3271754368

  - 01_basic.py
  - 01_basic.js
  - 01_basic.sh
  - 02_responses.py
  - 02_responses.js
  - 02_responses.sh
  - 03_vision.py
  - 03_vision.js
  - 03_vision.sh

Extracted 9 file(s) to /var/folders/vq/wfm2g6k917d3ldzpjdxc8ph00000gn/T/mdx-examples-3271754368

To run examples:

  cd /var/folders/vq/wfm2g6k917d3ldzpjdxc8ph00000gn/T/mdx-examples-3271754368
  npm install   # for JS examples

then run individual files with `node file.js`, `python file.py`, `bash file.sh`
```

In the future we should consider actually running the examples in CI and
having some sort of acceptance test so we can automatically detect when
our examples break. So this is just a start in that direction.

* Update docs/api/openai-compatibility.mdx
Co-authored-by: Parth Sareen <parth.sareen@ollama.com>

* Update docs/api/openai-compatibility.mdx
Co-authored-by: Parth Sareen <parth.sareen@ollama.com>

---------
Co-authored-by: Parth Sareen <parth.sareen@ollama.com>

Added Vulkan SDK installation instructions and environment variable setup for building with Vulkan support.

There were a few Markdown typos in one FAQ answer. It now renders as a proper ascii table.

* docs: vulkan information

* Revert "CI: Set up temporary opt-out Vulkan support (#12614)"

This reverts commit 8b6e5bae.

* vulkan: temporary opt-in for Vulkan support

Revert this once we're ready to enable by default.

* win: add vulkan CI build

Some route endpoints return an empty response with a 200 OK. These should be documented in the OpenAPI doc. Note that the previous deletion response was not correct.

* doc: re-add login autostart faq

This appears to have been accidentally dropped during the doc migration.

* docs: GPU updates lost on the doc update

* review comments: improve windows login disable instructions

Co-authored-by: A-Akhil <akhilrahul70@gmail.com>

This PR introduces a new ollama embed command that allows users to generate embeddings directly from the command line.

Added ollama embed MODEL [TEXT...] command for generating text embeddings
Supports both direct text arguments and stdin piping for scripted workflows

Outputs embeddings as JSON arrays (one per line)

This reverts commit 934dd9e1.

8.7 is Jetpack only, so no need on x86 builds
10.3 covers [G]B300

* Bring back escape valve for llm libraries

If the new discovery logic picks the wrong library, this gives users the
ability to force a specific one using the same pattern as before. This
can also potentially speed up bootstrap discovery if one of the libraries
takes a long time to load and ultimately bind to no devices.  For example
unsupported AMD iGPUS can sometimes take a while to discover and rule out.

* Bypass extra discovery on jetpack systems

On at least Jetpack6, cuda_v12 appears to expose the iGPU, but crashes later on in
cublasInit so if we detect a Jetpack, short-circuit and use that variant.

Notable EOLs with this change:
- MacOS v12 and v13 are no longer supported (v14+ required)
- AMD gfx900 and gfx906 are no longer supported

This revamps how we discover GPUs in the system by leveraging the Ollama
runner.  This should eliminate inconsistency between our GPU discovery and the
runners capabilities at runtime, particularly for cases where we try to filter
out unsupported GPUs.  Now the runner does that implicitly based on the actual
device list.  In some cases free VRAM reporting can be unreliable which can
leaad to scheduling mistakes, so this also includes a patch to leverage more
reliable VRAM reporting libraries if available.

Automatic workarounds have been removed as only one GPU leveraged this, which
is now documented. This GPU will soon fall off the support matrix with the next
ROCm bump.

Additional cleanup of the scheduler and discovery packages can be done in the
future once we have switched on the new memory management code, and removed
support for the llama runner.

* feat: add field to truncate embeddings

* add openai embeddings for dimensions