fix: more places where we are installing grpc that need a version specified
fix: attempt to fix metal tests
fix: metal/brew is forcing an update, they don't have 1.58 available anymore
Signed-off-by: Chris Jowett <421501+cryptk@users.noreply.github.com>
* start breaking up the giant channel refactor now that it's better understood - easier to merge bites
Signed-off-by: Dave Lee <dave@gray101.com>
* add concurrency and base64 back in, along with new base64 tests.
Signed-off-by: Dave Lee <dave@gray101.com>
* Automatic rename of whisper.go's Result to TranscriptResult
Signed-off-by: Dave Lee <dave@gray101.com>
* remove pkg/concurrency - significant changes coming in split 2
Signed-off-by: Dave Lee <dave@gray101.com>
* fix comments
Signed-off-by: Dave Lee <dave@gray101.com>
* add list_model service as another low-risk service to get it out of the way
Signed-off-by: Dave Lee <dave@gray101.com>
* split backend config loader into seperate file from the actual config struct. No changes yet, just reduce cognative load with smaller files of logical blocks
Signed-off-by: Dave Lee <dave@gray101.com>
* rename state.go ==> application.go
Signed-off-by: Dave Lee <dave@gray101.com>
* fix lost import?
Signed-off-by: Dave Lee <dave@gray101.com>
---------
Signed-off-by: Dave Lee <dave@gray101.com>
* Bump oneapi-basekit, optimum and openvino
* Changed PERFORMANCE HINT to CUMULATIVE_THROUGHPUT
Minor latency change for first token but about 10-15% speedup on token generation.
runCommand ==> ffmpegCommand. No functional changes, but makes it clear to the security scanner and future developers that this function cannot run arbitrary commands
Signed-off-by: Dave Lee <dave@gray101.com>
* fix regression #1971
fixes regression #1971 introduced by intel_extension_for_transformers==1.4
* UseTokenizerTemplate and StopPrompt
Implementation of use_tokenizer_template and stopwords options
* feat(parler-tts): Add new backend
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* feat(parler-tts): try downgrade protobuf
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* feat(parler-tts): add parler conda env
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Revert "feat(parler-tts): try downgrade protobuf"
This reverts commit bd5941d5cfc00676b45a99f71debf3c34249cf3c.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* deps: add grpc
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix: try to gen proto with same environment
* workaround
* Revert "fix: try to gen proto with same environment"
This reverts commit 998c745e2f.
* Workaround fixup
---------
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Dave <dave@gray101.com>
* Enhance autogptq backend to support VL models
* update dependencies for autogptq
* remove redundant auto-gptq dependency
* Convert base64 to image_url for Qwen-VL model
* implemented model inference for qwen-vl
* remove user prompt from generated answer
* fixed write image error
* fixed use_triton issue when loading Qwen-VL model
---------
Co-authored-by: Binghua Wu <bingwu@estee.com>
* Streaming working
* Small fix for regression on CUDA and XPU
* use pip version of optimum[openvino]
* Update backend/python/transformers/transformers_server.py
Signed-off-by: Ettore Di Giacinto <mudler@users.noreply.github.com>
* Token streaming support
fix optimum[openvino] package in install.sh
* Token Streaming support
---------
Signed-off-by: Ettore Di Giacinto <mudler@users.noreply.github.com>
Co-authored-by: Ettore Di Giacinto <mudler@users.noreply.github.com>
* fixes#1775 and #1774
Add BitsAndBytes Quantization and fixes embedding on CUDA devices
* Manage 4bit and 8 bit quantization
Manage different BitsAndBytes options with the quantization: parameter in yaml
* fix compilation errors on non CUDA environment
* OpenVINO draft
First draft of OpenVINO integration in transformer backend
* first working implementation
* Streaming working
* Small fix for regression on CUDA and XPU
* use pip version of optimum[openvino]
* Update backend/python/transformers/transformers_server.py
Signed-off-by: Ettore Di Giacinto <mudler@users.noreply.github.com>
---------
Signed-off-by: Ettore Di Giacinto <mudler@users.noreply.github.com>
Co-authored-by: Ettore Di Giacinto <mudler@users.noreply.github.com>
* Enhance autogptq backend to support VL models
* update dependencies for autogptq
* remove redundant auto-gptq dependency
* Convert base64 to image_url for Qwen-VL model
* implemented model inference for qwen-vl
* remove user prompt from generated answer
* fixed write image error
---------
Co-authored-by: Binghua Wu <bingwu@estee.com>
* test with gguf instead of ggml. Updates testPrompt to match? Adds debugging line to Dockerfile that I've found helpful recently.
* fix testPrompt slightly
* Sad Experiment: Test GH runner without metal?
* break apart CGO_LDFLAGS
* switch runner
* upstream llama.cpp disables Metal on Github CI!
* missed a dir from clean-tests
* CGO_LDFLAGS
* tmate failure + NO_ACCELERATE
* whisper.cpp has a metal fix
* do the exact opposite of the name of this branch, but keep it around for unrelated fixes?
* add back newlines
* add tmate to linux for testing
* update fixtures
* timeout for tmate
* fix: clean up Makefile dependencies to allow for parallel builds
* refactor: remove old unused backend from Makefile
* fix: finish removing legacy backend, update piper
* fix: I broke llama... I fixed llama
* feat: give the tests and builds a few threads
* fix: ensure libraries are replaced before build, add dropreplace target
* Fix image build workflows
* feat(elevenlabs): map elevenlabs API support to TTS
This allows elevenlabs Clients to work automatically with LocalAI by
supporting the elevenlabs API.
The elevenlabs server endpoint is implemented such as it is wired to the
TTS endpoints.
Fixes: https://github.com/mudler/LocalAI/issues/1809
* feat(openai/tts): compat layer with openai tts
Fixes: #1276
* fix: adapt tts CLI
* fixes#1775 and #1774
Add BitsAndBytes Quantization and fixes embedding on CUDA devices
* Manage 4bit and 8 bit quantization
Manage different BitsAndBytes options with the quantization: parameter in yaml
* fix compilation errors on non CUDA environment
* 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
* fix: use vllm AsyncLLMEngine to bring true stream
Current vLLM implementation uses the LLMEngine, which was designed for offline batch inference, which results in the streaming mode outputing all blobs at once at the end of the inference.
This PR reworks the gRPC server to use asyncio and gRPC.aio, in combination with vLLM's AsyncLLMEngine to bring true stream mode.
This PR also passes more parameters to vLLM during inference (presence_penalty, frequency_penalty, stop, ignore_eos, seed, ...).
* Remove unused import
This PR specifically introduces a `core` folder and moves the following packages over, without any other changes:
- `api/backend`
- `api/config`
- `api/options`
- `api/schema`
Once this is merged and we confirm there's no regressions, I can migrate over the remaining changes piece by piece to split up application startup, backend services, http, and mqtt as was the goal of the earlier PRs!
* Dockerfile changes to build for ROCm
* Adjust linker flags for ROCm
* Update conda env for diffusers and transformers to use ROCm pytorch
* Update transformers conda env for ROCm
* ci: build hipblas images
* fixup rebase
* use self-hosted
Signed-off-by: mudler <mudler@localai.io>
* specify LD_LIBRARY_PATH only when BUILD_TYPE=hipblas
---------
Signed-off-by: mudler <mudler@localai.io>
Co-authored-by: mudler <mudler@localai.io>
Infinite context loop might as well trigger an infinite loop of context
shifting if the model hallucinates and does not stop answering.
This has the unpleasant effect that the predicion never terminates,
which is the case especially on small models which tends to hallucinate.
Workarounds https://github.com/mudler/LocalAI/issues/1333 by removing
context-shifting.
See also upstream issue: https://github.com/ggerganov/llama.cpp/issues/3969
