The Hugo relearn theme does not provide an "alert" shortcode, so the
docs deploy failed at the Build site step:
failed to extract shortcode: template for shortcode "alert" not found
docs/content/features/image-generation.md:106
Convert the vae_decode_only note to the theme-supported notice shortcode
used everywhere else in the docs.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
* ⬆️ Update leejet/stable-diffusion.cpp
Signed-off-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
* fix(stablediffusion-ggml): adapt gosd.cpp to upstream sd_ctx_params_t API
The bump to 5a34bc7 restructured sd_ctx_params_t: the boolean CPU-offload
knobs (offload_params_to_cpu, keep_clip_on_cpu, keep_vae_on_cpu,
keep_control_net_on_cpu) were replaced by backend assignment specs
(backend/params_backend), and vae_decode_only / free_params_immediately
were dropped entirely. The build broke with "no member named ..." on
every arch.
Translate the legacy options we still accept from gallery configs into
the new backend assignment specs, mirroring prepare_backend_assignments()
in the upstream CLI, so offload_params_to_cpu / keep_*_on_cpu keep
working. vae_decode_only is parsed and ignored for config compatibility.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-4-8 [Claude Code]
* feat(stablediffusion-ggml): expose backend/params placement options
The upstream bump introduced new sd_ctx_params_t fields for device and
memory placement (backend, params_backend, rpc_servers, max_vram,
stream_layers) plus PuLID-Flux weights (pulid_weights_path). Wire them up
as backend options so models can be split across CPU/GPU/disk/RPC:
- backend: per-component compute placement (e.g. clip=cpu,vae=cuda0)
- params_backend: per-component weight storage incl. disk mmap
- max_vram / stream_layers: graph-cut segmented parameter offload budget
- rpc_servers: offload compute to remote RPC servers
- pulid_weights_path: PuLID-Flux identity injection
The legacy keep_*_on_cpu / offload_params_to_cpu booleans now seed and
compose with the explicit backend/params_backend specs, matching upstream
prepare_backend_assignments(). Option values are taken as everything after
the first ':' so colon-bearing values (rpc_servers host:port) survive
parsing. Documented the new options in the image-generation guide.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-4-8 [Claude Code]
* feat(stablediffusion-ggml): distributed RPC across ggml workers
Enable the ggml RPC backend (-DSD_RPC=ON) so image generation can be
sharded across remote rpc-server workers. The ggml rpc-server is
backend-agnostic, so this reuses the exact same worker pool as the
llama.cpp backend - one set of `local-ai worker llama-cpp-rpc` /
`p2p-llama-cpp-rpc` workers accelerates both text and image generation.
RPC servers are selected by precedence:
- the explicit `rpc_servers` option, else
- the LLAMACPP_GRPC_SERVERS env var, which LocalAI's p2p worker mode
populates automatically with discovered workers (the backend inherits
it from the parent process env), so distributed image generation needs
no per-model configuration.
Documented manual and p2p setup in the image-generation guide.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-4-8 [Claude Code]
---------
Signed-off-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: mudler <2420543+mudler@users.noreply.github.com>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
* feat(img2vid): Initial support for img2vid
* doc(SD): fix SDXL Example
* Minor fixups for img2vid
* docs(img2img): fix example curl call
* feat(txt2vid): initial support
Signed-off-by: Ettore Di Giacinto <mudler@users.noreply.github.com>
* diffusers: be retro-compatible with CUDA settings
* docs(img2vid, txt2vid): examples
* Add notice on docs
---------
Signed-off-by: Ettore Di Giacinto <mudler@users.noreply.github.com>