Adds eight curated vllm-cpp entries to the model gallery. Until now the backend had gallery coverage only for MiniMax-H3 video, so serving text on it meant hand-writing engine_args. The flagship tier is what vllm.cpp gates its correctness and speed claims on: Qwen3.6-27B and Qwen3.6-35B-A3B in NVFP4, each with a speculative sibling (MTP on both, DFlash on the 27B). Qwen3-Coder-30B-A3B covers agentic tool use, and Qwen3-4B / Qwen3-0.6B in bf16 are the entries that run where NVFP4 cannot, CPU included. Three details are load-bearing rather than incidental: - The 27B entries pin revision 890bdef7. That repository was later re-quantized in place from NVFP4 to FP8 W8A8 under the same name, so an unpinned entry resolves to different weights and reports nothing. - Qwen3-Coder names tool_parser: qwen3_coder explicitly. Its dialect is byte-identical on the wire to step3p5's, so chat-template sniffing cannot separate them and auto-detection picks wrong. - enable_prefix_caching is deliberately left unset everywhere. It defaults on for dense models and off for the GDN hybrids, and that per-model default is the right answer. num_blocks is sized per model from its real KV footprint rather than copied between entries, which ranges from 20 KiB/token on the 35B to 144 KiB/token on the 4B. Docs: adds features/vllm-cpp.md covering installation, the model table, the pinning rationale and how to choose between the speculative variants, and cross-links it from the existing engine_args reference. It also records that the CUDA images are built for Blackwell only, which is narrower than vllm.cpp's own ten-architecture release and makes an otherwise cryptic "no kernel image is available" failure legible. Verified: gallery suite green; all eight decode and validate as a ModelConfig. qwen3-0.6b-vllm-cpp confirmed end to end on a real cluster, chat plus engine-parsed tool_calls. The NVFP4 entries are not yet runtime-verified: no available node has kernels for them. Assisted-by: Claude Code:claude-opus-5[1m] [Read] [Bash] [Edit] Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
LocalAI website
LocalAI documentation website
Requirement
In this project, the Docsy theme component is pulled in as a Hugo module, together with other module dependencies:
$ hugo mod graph
hugo: collected modules in 566 ms
hugo: collected modules in 578 ms
github.com/google/docsy-example github.com/google/docsy@v0.5.1-0.20221017155306-99eacb09ffb0
github.com/google/docsy-example github.com/google/docsy/dependencies@v0.5.1-0.20221014161617-be5da07ecff1
github.com/google/docsy/dependencies@v0.5.1-0.20221014161617-be5da07ecff1 github.com/twbs/bootstrap@v4.6.2+incompatible
github.com/google/docsy/dependencies@v0.5.1-0.20221014161617-be5da07ecff1 github.com/FortAwesome/Font-Awesome@v0.0.0-20220831210243-d3a7818c253f
If you want to do SCSS edits and want to publish these, you need to install PostCSS
npm install
Running the website locally
Building and running the site locally requires a recent extended version of Hugo.
You can find out more about how to install Hugo for your environment in our
Getting started guide.
From the LocalAI repository root, run:
make docs
The Hugo configuration lives in the docs directory. To invoke Hugo
directly instead, run:
cd docs
hugo server
Running a container locally
You can run docsy-example inside a Docker
container, the container runs with a volume bound to the docsy-example
folder. This approach doesn't require you to install any dependencies other
than Docker Desktop on
Windows and Mac, and Docker Compose
on Linux.
-
Build the docker image
docker-compose build -
Run the built image
docker-compose upNOTE: You can run both commands at once with
docker-compose up --build. -
Verify that the service is working.
Open your web browser and type
http://localhost:1313in your navigation bar, This opens a local instance of the docsy-example homepage. You can now make changes to the docsy example and those changes will immediately show up in your browser after you save.
Cleanup
To stop Docker Compose, on your terminal window, press Ctrl + C.
To remove the produced images run:
docker-compose rm
For more information see the Docker Compose documentation.
Troubleshooting
As you run the website locally, you may run into the following error:
➜ hugo server
INFO 2021/01/21 21:07:55 Using config file:
Building sites … INFO 2021/01/21 21:07:55 syncing static files to /
Built in 288 ms
Error: Error building site: TOCSS: failed to transform "scss/main.scss" (text/x-scss): resource "scss/scss/main.scss_9fadf33d895a46083cdd64396b57ef68" not found in file cache
This error occurs if you have not installed the extended version of Hugo. See this section of the user guide for instructions on how to install Hugo.
Or you may encounter the following error:
➜ hugo server
Error: failed to download modules: binary with name "go" not found
This error occurs if you have not installed the go programming language on your system.
See this section of the user guide for instructions on how to install go.