* chore: drop double call to stop all backends, refactors
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix: do lock when cycling to models to delete
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
---------
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
The GGML format is now dead, since in the next version of LocalAI we
already bring many breaking compatibility changes, taking the occasion
also to drop ggml support (pre-gguf).
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* chore(stablediffusion-ncn): drop in favor of ggml implementation
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* chore(ci): drop stablediffusion build
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* chore(tests): add
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* chore(tests): try to fixup current tests
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Try to fix tests
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Tests improvements
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* chore(tests): use quality to specify step
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* chore(tests): switch to sd-1.5
also increase prep time for downloading models
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
---------
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* merge sentencetransformers
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Add alias to silently redirect sentencetransformers to transformers
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Add alias also for transformers-musicgen
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Drop from makefile
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Move tests from sentencetransformers
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Remove sentencetransformers
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Remove tests from CI (part of transformers)
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Do not always try to load the tokenizer
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Adapt tests
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Fix typo
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Tiny adjustments
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
---------
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* feat(backends): Drop bert.cpp
use llama.cpp 3.2 as a drop-in replacement for bert.cpp
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* chore(tests): make test more robust
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
---------
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Instead of trying to derive it from the model file. In backends that
specify HF url this results in a fragile logic.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
This is in order to identify also builds which are not using
alternatives based on capabilities.
For instance, there are cases when we build the backend only natively in
the host.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix(llama-cpp): consistently select fallback
We didn't took in consideration the case where the host has the CPU
flagset, but the binaries were not actually present in the asset dir.
This made possible for instance for models that specified the llama-cpp
backend directly in the config to not eventually pick-up the fallback
binary in case the optimized binaries were not present.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* chore: adjust and simplify selection
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix: move failure recovery to BackendLoader()
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* comments
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* minor fixups
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
---------
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* chore(refactor): track internally started models by ID
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Just extend options, no need to copy
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Improve debugging for rerankers failures
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Simplify model loading with rerankers
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Be more consistent when generating model options
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Uncommitted code
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Make deleteProcess more idiomatic
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Adapt CLI for sound generation
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Fixup threads definition
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Handle corner case where c.Seed is nil
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Consistently use ModelOptions
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Adapt new code to refactoring
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
---------
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Dave <dave@gray101.com>
* chore(refactor): track grpcProcess in the model structure
This avoids to have to handle in two parts the data relative to the same
model. It makes it easier to track and use mutex with.
This also fixes races conditions while accessing to the model.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* chore(tests): run protogen-go before starting aio tests
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* chore(tests): install protoc in aio tests
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
---------
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* chore(refactor): drop duplicated shutdown logics
- Handle locking in Shutdown and CheckModelIsLoaded in a more go-idiomatic way
- Drop duplicated code and re-organize shutdown code
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix: drop leftover
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* chore: improve logging and add missing locks
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
---------
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* feat: add endpoint to list system informations
For now, it lists the available backends, but can be expanded later on
to include more system informations (such as GPU devices detected, RAM,
threads configured, and so on so forth).
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* show also external backends
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* add test
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
---------
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Due to a previous refactor we moved the client constructor tight to the
model address, however that was just a string which we would use to
build the client each time.
With this change we make the loader to return a *Model which carries a
constructor for the client and stores the client on the first
connection.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* specify workdir when launching external backend for safety / relative paths, bump version, logs
Signed-off-by: Dave Lee <dave@gray101.com>
* sneak in a devcontainer fix
Signed-off-by: Dave Lee <dave@gray101.com>
---------
Signed-off-by: Dave Lee <dave@gray101.com>
chore: drop gpt4all
gpt4all is already supported in llama.cpp - the backend was kept for
keeping compatibility with old gpt4all models (prior to gguf format).
It is good time now to clean up and remove it to slim the compilation
process.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix(cuda): downgrade to 12.0 to increase compatibility range
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* improve messaging
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
---------
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* refactor(gallery): move under core/
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix(unarchive): do not allow symlinks
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
---------
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* feat(amdgpu): try to build in single binary
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Release space from worker
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
---------
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* auto select cpu variant
Signed-off-by: Sertac Ozercan <sozercan@gmail.com>
* remove cuda target for now
Signed-off-by: Sertac Ozercan <sozercan@gmail.com>
* fix metal
Signed-off-by: Sertac Ozercan <sozercan@gmail.com>
* fix path
Signed-off-by: Sertac Ozercan <sozercan@gmail.com>
* cuda
Signed-off-by: Sertac Ozercan <sozercan@gmail.com>
* auto select cuda
Signed-off-by: Sertac Ozercan <sozercan@gmail.com>
* update test
Signed-off-by: Sertac Ozercan <sozercan@gmail.com>
* select CUDA backend only if present
Signed-off-by: mudler <mudler@localai.io>
* ci: keep cuda bin in path
Signed-off-by: mudler <mudler@localai.io>
* Makefile: make dist now builds also cuda
Signed-off-by: mudler <mudler@localai.io>
* Keep pushing fallback in case auto-flagset/nvidia fails
There could be other reasons for which the default binary may fail. For example we might have detected an Nvidia GPU,
however the user might not have the drivers/cuda libraries installed in the system, and so it would fail to start.
We keep the fallback of llama.cpp at the end of the llama.cpp backends to try to fallback loading in case things go wrong
Signed-off-by: mudler <mudler@localai.io>
* Do not build cuda on MacOS
Signed-off-by: mudler <mudler@localai.io>
* cleanup
Signed-off-by: Sertac Ozercan <sozercan@gmail.com>
* Apply suggestions from code review
Signed-off-by: Ettore Di Giacinto <mudler@users.noreply.github.com>
---------
Signed-off-by: Sertac Ozercan <sozercan@gmail.com>
Signed-off-by: Ettore Di Giacinto <mudler@users.noreply.github.com>
Signed-off-by: mudler <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@users.noreply.github.com>
Co-authored-by: mudler <mudler@localai.io>
* feat(initializer): do not specify backends to autoload
We can simply try to autoload the backends extracted in the asset dir.
This will allow to build variants of the same backend (for e.g. with different instructions sets),
so to have a single binary for all the variants.
Signed-off-by: mudler <mudler@localai.io>
* refactor(prepare): refactor out llama.cpp prepare steps
Make it so are idempotent and that we can re-build
Signed-off-by: mudler <mudler@localai.io>
* [TEST] feat(build): build noavx version along
Signed-off-by: mudler <mudler@localai.io>
* build: make build parallel
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* build: do not override CMAKE_ARGS
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* build: add fallback variant
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Fixups
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix(huggingface-langchain): fail if no token is set
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix(huggingface-langchain): rename
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix: do not autoload local-store
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix: give priority between the listed backends
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
---------
Signed-off-by: mudler <mudler@localai.io>
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* feat(intel): add diffusers support
* try to consume upstream container image
* Debug
* Manually install deps
* Map transformers/hf cache dir to modelpath if not specified
* fix(compel): update initialization, pass by all gRPC options
* fix: add dependencies, implement transformers for xpu
* base it from the oneapi image
* Add pillow
* set threads if specified when launching the API
* Skip conda install if intel
* defaults to non-intel
* ci: add to pipelines
* prepare compel only if enabled
* Skip conda install if intel
* fix cleanup
* Disable compel by default
* Install torch 2.1.0 with Intel
* Skip conda on some setups
* Detect python
* Quiet output
* Do not override system python with conda
* Prefer python3
* Fixups
* exllama2: do not install without conda (overrides pytorch version)
* exllama/exllama2: do not install if not using cuda
* Add missing dataset dependency
* Small fixups, symlink to python, add requirements
* Add neural_speed to the deps
* correctly handle model offloading
* fix: device_map == xpu
* go back at calling python, fixed at dockerfile level
* Exllama2 restricted to only nvidia gpus
* Tokenizer to xpu
