Compare commits

..

1 Commits

Author SHA1 Message Date
Ettore Di Giacinto
a00bbfe3eb chore(model): add silero-vad model config
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2024-11-26 14:28:41 +01:00
80 changed files with 1139 additions and 2604 deletions

5
.github/labeler.yml vendored
View File

@@ -1,11 +1,6 @@
enhancements:
- head-branch: ['^feature', 'feature']
dependencies:
- any:
- changed-files:
- any-glob-to-any-file: 'Makefile'
kind/documentation:
- any:
- changed-files:

View File

@@ -12,14 +12,23 @@ jobs:
- repository: "ggerganov/llama.cpp"
variable: "CPPLLAMA_VERSION"
branch: "master"
- repository: "go-skynet/go-ggml-transformers.cpp"
variable: "GOGGMLTRANSFORMERS_VERSION"
branch: "master"
- repository: "donomii/go-rwkv.cpp"
variable: "RWKV_VERSION"
branch: "main"
- repository: "ggerganov/whisper.cpp"
variable: "WHISPER_CPP_VERSION"
branch: "master"
- repository: "PABannier/bark.cpp"
variable: "BARKCPP_VERSION"
- repository: "go-skynet/go-bert.cpp"
variable: "BERT_VERSION"
branch: "master"
- repository: "go-skynet/bloomz.cpp"
variable: "BLOOMZ_VERSION"
branch: "main"
- repository: "leejet/stable-diffusion.cpp"
variable: "STABLEDIFFUSION_GGML_VERSION"
- repository: "mudler/go-ggllm.cpp"
variable: "GOGGLLM_VERSION"
branch: "master"
- repository: "mudler/go-stable-diffusion"
variable: "STABLEDIFFUSION_VERSION"

1
.gitignore vendored
View File

@@ -2,7 +2,6 @@
/sources/
__pycache__/
*.a
*.o
get-sources
prepare-sources
/backend/cpp/llama/grpc-server

153
Makefile
View File

@@ -8,12 +8,16 @@ DETECT_LIBS?=true
# llama.cpp versions
GOLLAMA_REPO?=https://github.com/go-skynet/go-llama.cpp
GOLLAMA_VERSION?=2b57a8ae43e4699d3dc5d1496a1ccd42922993be
CPPLLAMA_VERSION?=dafae66cc242eb766797194d3c85c5e502625623
CPPLLAMA_VERSION?=47f931c8f9a26c072d71224bc8013cc66ea9e445
# whisper.cpp version
WHISPER_REPO?=https://github.com/ggerganov/whisper.cpp
WHISPER_CPP_VERSION?=6266a9f9e56a5b925e9892acf650f3eb1245814d
# bert.cpp version
BERT_REPO?=https://github.com/go-skynet/go-bert.cpp
BERT_VERSION?=710044b124545415f555e4260d16b146c725a6e4
# go-piper version
PIPER_REPO?=https://github.com/mudler/go-piper
PIPER_VERSION?=e10ca041a885d4a8f3871d52924b47792d5e5aa0
@@ -26,21 +30,12 @@ STABLEDIFFUSION_VERSION?=4a3cd6aeae6f66ee57eae9a0075f8c58c3a6a38f
TINYDREAM_REPO?=https://github.com/M0Rf30/go-tiny-dream
TINYDREAM_VERSION?=c04fa463ace9d9a6464313aa5f9cd0f953b6c057
# bark.cpp
BARKCPP_REPO?=https://github.com/PABannier/bark.cpp.git
BARKCPP_VERSION?=v1.0.0
# stablediffusion.cpp (ggml)
STABLEDIFFUSION_GGML_REPO?=https://github.com/leejet/stable-diffusion.cpp
STABLEDIFFUSION_GGML_VERSION?=9578fdcc4632dc3de5565f28e2fb16b7c18f8d48
ONNX_VERSION?=1.20.0
ONNX_ARCH?=x64
ONNX_OS?=linux
export BUILD_TYPE?=
export STABLE_BUILD_TYPE?=$(BUILD_TYPE)
export GGML_CMAKE_ARGS?=
export CMAKE_ARGS?=
export BACKEND_LIBS?=
@@ -89,45 +84,9 @@ ifndef UNAME_S
UNAME_S := $(shell uname -s)
endif
# IF native is false, we add -DGGML_NATIVE=OFF to GGML_CMAKE_ARGS
# IF native is false, we add -DGGML_NATIVE=OFF to CMAKE_ARGS
ifeq ($(NATIVE),false)
GGML_CMAKE_ARGS+=-DGGML_NATIVE=OFF
endif
# Disable Shared libs as we are linking on static gRPC and we can't mix shared and static
GGML_CMAKE_ARGS+=-DBUILD_SHARED_LIBS=OFF
# If build type is cublas, then we set -DGGML_CUDA=ON to GGML_CMAKE_ARGS automatically
ifeq ($(BUILD_TYPE),cublas)
GGML_CMAKE_ARGS+=-DGGML_CUDA=ON
# If build type is openblas then we set -DGGML_BLAS=ON -DGGML_BLAS_VENDOR=OpenBLAS
# to GGML_CMAKE_ARGS automatically
else ifeq ($(BUILD_TYPE),openblas)
GGML_CMAKE_ARGS+=-DGGML_BLAS=ON -DGGML_BLAS_VENDOR=OpenBLAS
# If build type is clblas (openCL) we set -DGGML_CLBLAST=ON -DCLBlast_DIR=/some/path
else ifeq ($(BUILD_TYPE),clblas)
GGML_CMAKE_ARGS+=-DGGML_CLBLAST=ON -DCLBlast_DIR=/some/path
# If it's hipblas we do have also to set CC=/opt/rocm/llvm/bin/clang CXX=/opt/rocm/llvm/bin/clang++
else ifeq ($(BUILD_TYPE),hipblas)
GGML_CMAKE_ARGS+=-DGGML_HIP=ON
# If it's OSX, DO NOT embed the metal library - -DGGML_METAL_EMBED_LIBRARY=ON requires further investigation
# But if it's OSX without metal, disable it here
else ifeq ($(OS),Darwin)
ifneq ($(BUILD_TYPE),metal)
GGML_CMAKE_ARGS+=-DGGML_METAL=OFF
else
GGML_CMAKE_ARGS+=-DGGML_METAL=ON
GGML_CMAKE_ARGS+=-DGGML_METAL_EMBED_LIBRARY=ON
TARGET+=--target ggml-metal
endif
endif
ifeq ($(BUILD_TYPE),sycl_f16)
GGML_CMAKE_ARGS+=-DGGML_SYCL=ON -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx -DGGML_SYCL_F16=ON
endif
ifeq ($(BUILD_TYPE),sycl_f32)
GGML_CMAKE_ARGS+=-DGGML_SYCL=ON -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx
CMAKE_ARGS+=-DGGML_NATIVE=OFF
endif
# Detect if we are running on arm64
@@ -154,7 +113,7 @@ ifeq ($(OS),Darwin)
BUILD_TYPE=metal
# disable metal if on Darwin and any other value is explicitly passed.
else ifneq ($(BUILD_TYPE),metal)
GGML_CMAKE_ARGS+=-DGGML_METAL=OFF
CMAKE_ARGS+=-DGGML_METAL=OFF
export GGML_NO_ACCELERATE=1
export GGML_NO_METAL=1
endif
@@ -179,7 +138,7 @@ ifeq ($(BUILD_TYPE),cublas)
endif
ifeq ($(BUILD_TYPE),vulkan)
GGML_CMAKE_ARGS+=-DGGML_VULKAN=1
CMAKE_ARGS+=-DGGML_VULKAN=1
endif
ifneq (,$(findstring sycl,$(BUILD_TYPE)))
@@ -201,7 +160,7 @@ ifeq ($(BUILD_TYPE),hipblas)
export GGML_HIP=1
GPU_TARGETS ?= gfx900,gfx906,gfx908,gfx940,gfx941,gfx942,gfx90a,gfx1030,gfx1031,gfx1100,gfx1101
AMDGPU_TARGETS ?= "$(GPU_TARGETS)"
GGML_CMAKE_ARGS+=-DGGML_HIP=ON -DAMDGPU_TARGETS="$(AMDGPU_TARGETS)" -DGPU_TARGETS="$(GPU_TARGETS)"
CMAKE_ARGS+=-DGGML_HIP=ON -DAMDGPU_TARGETS="$(AMDGPU_TARGETS)" -DGPU_TARGETS="$(GPU_TARGETS)"
CGO_LDFLAGS += -O3 --rtlib=compiler-rt -unwindlib=libgcc -lhipblas -lrocblas --hip-link -L${ROCM_HOME}/lib/llvm/lib
endif
@@ -239,6 +198,7 @@ ifeq ($(findstring tts,$(GO_TAGS)),tts)
endif
ALL_GRPC_BACKENDS=backend-assets/grpc/huggingface
ALL_GRPC_BACKENDS+=backend-assets/grpc/bert-embeddings
ALL_GRPC_BACKENDS+=backend-assets/grpc/llama-cpp-avx
ALL_GRPC_BACKENDS+=backend-assets/grpc/llama-cpp-avx2
ALL_GRPC_BACKENDS+=backend-assets/grpc/llama-cpp-fallback
@@ -246,14 +206,6 @@ ALL_GRPC_BACKENDS+=backend-assets/grpc/llama-ggml
ALL_GRPC_BACKENDS+=backend-assets/grpc/llama-cpp-grpc
ALL_GRPC_BACKENDS+=backend-assets/util/llama-cpp-rpc-server
ALL_GRPC_BACKENDS+=backend-assets/grpc/whisper
ifeq ($(ONNX_OS),linux)
ifeq ($(ONNX_ARCH),x64)
ALL_GRPC_BACKENDS+=backend-assets/grpc/bark-cpp
ALL_GRPC_BACKENDS+=backend-assets/grpc/stablediffusion-ggml
endif
endif
ALL_GRPC_BACKENDS+=backend-assets/grpc/local-store
ALL_GRPC_BACKENDS+=backend-assets/grpc/silero-vad
ALL_GRPC_BACKENDS+=$(OPTIONAL_GRPC)
@@ -272,12 +224,23 @@ ifeq ($(BUILD_API_ONLY),true)
GRPC_BACKENDS=
endif
export CMAKE_ARGS?=$(GGML_CMAKE_ARGS)
.PHONY: all test build vendor get-sources prepare-sources prepare
all: help
## BERT embeddings
sources/go-bert.cpp:
mkdir -p sources/go-bert.cpp
cd sources/go-bert.cpp && \
git init && \
git remote add origin $(BERT_REPO) && \
git fetch origin && \
git checkout $(BERT_VERSION) && \
git submodule update --init --recursive --depth 1 --single-branch
sources/go-bert.cpp/libgobert.a: sources/go-bert.cpp
$(MAKE) -C sources/go-bert.cpp libgobert.a
## go-llama.cpp
sources/go-llama.cpp:
mkdir -p sources/go-llama.cpp
@@ -291,23 +254,6 @@ sources/go-llama.cpp:
sources/go-llama.cpp/libbinding.a: sources/go-llama.cpp
$(MAKE) -C sources/go-llama.cpp BUILD_TYPE=$(STABLE_BUILD_TYPE) libbinding.a
## bark.cpp
sources/bark.cpp:
git clone --recursive $(BARKCPP_REPO) sources/bark.cpp && \
cd sources/bark.cpp && \
git checkout $(BARKCPP_VERSION) && \
git submodule update --init --recursive --depth 1 --single-branch
sources/bark.cpp/build/libbark.a: sources/bark.cpp
cd sources/bark.cpp && \
mkdir -p build && \
cd build && \
cmake $(CMAKE_ARGS) .. && \
cmake --build . --config Release
backend/go/bark/libbark.a: sources/bark.cpp/build/libbark.a
$(MAKE) -C backend/go/bark libbark.a
## go-piper
sources/go-piper:
mkdir -p sources/go-piper
@@ -321,7 +267,7 @@ sources/go-piper:
sources/go-piper/libpiper_binding.a: sources/go-piper
$(MAKE) -C sources/go-piper libpiper_binding.a example/main piper.o
## stable diffusion (onnx)
## stable diffusion
sources/go-stable-diffusion:
mkdir -p sources/go-stable-diffusion
cd sources/go-stable-diffusion && \
@@ -334,30 +280,6 @@ sources/go-stable-diffusion:
sources/go-stable-diffusion/libstablediffusion.a: sources/go-stable-diffusion
CPATH="$(CPATH):/usr/include/opencv4" $(MAKE) -C sources/go-stable-diffusion libstablediffusion.a
## stablediffusion (ggml)
sources/stablediffusion-ggml.cpp:
git clone --recursive $(STABLEDIFFUSION_GGML_REPO) sources/stablediffusion-ggml.cpp && \
cd sources/stablediffusion-ggml.cpp && \
git checkout $(STABLEDIFFUSION_GGML_VERSION) && \
git submodule update --init --recursive --depth 1 --single-branch
sources/stablediffusion-ggml.cpp/build/libstable-diffusion.a: sources/stablediffusion-ggml.cpp
cd sources/stablediffusion-ggml.cpp && \
mkdir -p build && \
cd build && \
cmake $(CMAKE_ARGS) .. && \
cmake --build . --config Release
backend/go/image/stablediffusion-ggml/libsd.a: sources/stablediffusion-ggml.cpp/build/libstable-diffusion.a
$(MAKE) -C backend/go/image/stablediffusion-ggml libsd.a
backend-assets/grpc/stablediffusion-ggml: backend/go/image/stablediffusion-ggml/libsd.a backend-assets/grpc
CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(CURDIR)/backend/go/image/stablediffusion-ggml/ LIBRARY_PATH=$(CURDIR)/backend/go/image/stablediffusion-ggml/ \
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/stablediffusion-ggml ./backend/go/image/stablediffusion-ggml/
ifneq ($(UPX),)
$(UPX) backend-assets/grpc/stablediffusion-ggml
endif
sources/onnxruntime:
mkdir -p sources/onnxruntime
curl -L https://github.com/microsoft/onnxruntime/releases/download/v$(ONNX_VERSION)/onnxruntime-$(ONNX_OS)-$(ONNX_ARCH)-$(ONNX_VERSION).tgz -o sources/onnxruntime/onnxruntime-$(ONNX_OS)-$(ONNX_ARCH)-$(ONNX_VERSION).tgz
@@ -398,11 +320,12 @@ sources/whisper.cpp:
sources/whisper.cpp/libwhisper.a: sources/whisper.cpp
cd sources/whisper.cpp && $(MAKE) libwhisper.a libggml.a
get-sources: sources/go-llama.cpp sources/go-piper sources/stablediffusion-ggml.cpp sources/bark.cpp sources/whisper.cpp sources/go-stable-diffusion sources/go-tiny-dream backend/cpp/llama/llama.cpp
get-sources: sources/go-llama.cpp sources/go-piper sources/whisper.cpp sources/go-bert.cpp sources/go-stable-diffusion sources/go-tiny-dream backend/cpp/llama/llama.cpp
replace:
$(GOCMD) mod edit -replace github.com/ggerganov/whisper.cpp=$(CURDIR)/sources/whisper.cpp
$(GOCMD) mod edit -replace github.com/ggerganov/whisper.cpp/bindings/go=$(CURDIR)/sources/whisper.cpp/bindings/go
$(GOCMD) mod edit -replace github.com/go-skynet/go-bert.cpp=$(CURDIR)/sources/go-bert.cpp
$(GOCMD) mod edit -replace github.com/M0Rf30/go-tiny-dream=$(CURDIR)/sources/go-tiny-dream
$(GOCMD) mod edit -replace github.com/mudler/go-piper=$(CURDIR)/sources/go-piper
$(GOCMD) mod edit -replace github.com/mudler/go-stable-diffusion=$(CURDIR)/sources/go-stable-diffusion
@@ -411,6 +334,7 @@ replace:
dropreplace:
$(GOCMD) mod edit -dropreplace github.com/ggerganov/whisper.cpp
$(GOCMD) mod edit -dropreplace github.com/ggerganov/whisper.cpp/bindings/go
$(GOCMD) mod edit -dropreplace github.com/go-skynet/go-bert.cpp
$(GOCMD) mod edit -dropreplace github.com/M0Rf30/go-tiny-dream
$(GOCMD) mod edit -dropreplace github.com/mudler/go-piper
$(GOCMD) mod edit -dropreplace github.com/mudler/go-stable-diffusion
@@ -425,6 +349,7 @@ rebuild: ## Rebuilds the project
$(MAKE) -C sources/go-llama.cpp clean
$(MAKE) -C sources/whisper.cpp clean
$(MAKE) -C sources/go-stable-diffusion clean
$(MAKE) -C sources/go-bert.cpp clean
$(MAKE) -C sources/go-piper clean
$(MAKE) -C sources/go-tiny-dream clean
$(MAKE) build
@@ -439,9 +364,7 @@ clean: ## Remove build related file
rm -rf release/
rm -rf backend-assets/*
$(MAKE) -C backend/cpp/grpc clean
$(MAKE) -C backend/go/bark clean
$(MAKE) -C backend/cpp/llama clean
$(MAKE) -C backend/go/image/stablediffusion-ggml clean
rm -rf backend/cpp/llama-* || true
$(MAKE) dropreplace
$(MAKE) protogen-clean
@@ -784,6 +707,13 @@ backend-assets/espeak-ng-data: sources/go-piper sources/go-piper/libpiper_bindin
backend-assets/grpc: protogen-go replace
mkdir -p backend-assets/grpc
backend-assets/grpc/bert-embeddings: sources/go-bert.cpp sources/go-bert.cpp/libgobert.a backend-assets/grpc
CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(CURDIR)/sources/go-bert.cpp LIBRARY_PATH=$(CURDIR)/sources/go-bert.cpp \
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/bert-embeddings ./backend/go/llm/bert/
ifneq ($(UPX),)
$(UPX) backend-assets/grpc/bert-embeddings
endif
backend-assets/grpc/huggingface: backend-assets/grpc
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/huggingface ./backend/go/llm/langchain/
ifneq ($(UPX),)
@@ -843,6 +773,10 @@ backend-assets/grpc/llama-cpp-fallback: backend-assets/grpc backend/cpp/llama/ll
$(info ${GREEN}I llama-cpp build info:fallback${RESET})
CMAKE_ARGS="$(CMAKE_ARGS) -DGGML_AVX=off -DGGML_AVX2=off -DGGML_AVX512=off -DGGML_FMA=off -DGGML_F16C=off" $(MAKE) VARIANT="llama-fallback" build-llama-cpp-grpc-server
cp -rfv backend/cpp/llama-fallback/grpc-server backend-assets/grpc/llama-cpp-fallback
# TODO: every binary should have its own folder instead, so can have different metal implementations
ifeq ($(BUILD_TYPE),metal)
cp backend/cpp/llama-fallback/llama.cpp/build/bin/ggml-metal.metal backend-assets/grpc/
endif
backend-assets/grpc/llama-cpp-cuda: backend-assets/grpc backend/cpp/llama/llama.cpp
cp -rf backend/cpp/llama backend/cpp/llama-cuda
@@ -890,13 +824,6 @@ ifneq ($(UPX),)
$(UPX) backend-assets/grpc/llama-ggml
endif
backend-assets/grpc/bark-cpp: backend/go/bark/libbark.a backend-assets/grpc
CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(CURDIR)/backend/go/bark/ LIBRARY_PATH=$(CURDIR)/backend/go/bark/ \
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/bark-cpp ./backend/go/bark/
ifneq ($(UPX),)
$(UPX) backend-assets/grpc/bark-cpp
endif
backend-assets/grpc/piper: sources/go-piper sources/go-piper/libpiper_binding.a backend-assets/grpc backend-assets/espeak-ng-data
CGO_CXXFLAGS="$(PIPER_CGO_CXXFLAGS)" CGO_LDFLAGS="$(PIPER_CGO_LDFLAGS)" LIBRARY_PATH=$(CURDIR)/sources/go-piper \
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/piper ./backend/go/tts/

View File

@@ -92,8 +92,6 @@ local-ai run oci://localai/phi-2:latest
## 📰 Latest project news
- Dec 2024: stablediffusion.cpp backend (ggml) added ( https://github.com/mudler/LocalAI/pull/4289 )
- Nov 2024: Bark.cpp backend added ( https://github.com/mudler/LocalAI/pull/4287 )
- Nov 2024: Voice activity detection models (**VAD**) added to the API: https://github.com/mudler/LocalAI/pull/4204
- Oct 2024: examples moved to [LocalAI-examples](https://github.com/mudler/LocalAI-examples)
- Aug 2024: 🆕 FLUX-1, [P2P Explorer](https://explorer.localai.io)

View File

@@ -1,7 +1,7 @@
name: text-embedding-ada-002
embeddings: true
backend: bert-embeddings
parameters:
model: huggingface://hugging-quants/Llama-3.2-1B-Instruct-Q4_K_M-GGUF/llama-3.2-1b-instruct-q4_k_m.gguf
model: huggingface://mudler/all-MiniLM-L6-v2/ggml-model-q4_0.bin
usage: |
You can test this model with curl like this:

View File

@@ -240,11 +240,6 @@ message ModelOptions {
repeated string LoraAdapters = 60;
repeated float LoraScales = 61;
repeated string Options = 62;
string CacheTypeKey = 63;
string CacheTypeValue = 64;
}
message Result {

View File

@@ -7,6 +7,44 @@ BUILD_TYPE?=
ONEAPI_VARS?=/opt/intel/oneapi/setvars.sh
TARGET?=--target grpc-server
# Disable Shared libs as we are linking on static gRPC and we can't mix shared and static
CMAKE_ARGS+=-DBUILD_SHARED_LIBS=OFF
# If build type is cublas, then we set -DGGML_CUDA=ON to CMAKE_ARGS automatically
ifeq ($(BUILD_TYPE),cublas)
CMAKE_ARGS+=-DGGML_CUDA=ON
# If build type is openblas then we set -DGGML_BLAS=ON -DGGML_BLAS_VENDOR=OpenBLAS
# to CMAKE_ARGS automatically
else ifeq ($(BUILD_TYPE),openblas)
CMAKE_ARGS+=-DGGML_BLAS=ON -DGGML_BLAS_VENDOR=OpenBLAS
# If build type is clblas (openCL) we set -DGGML_CLBLAST=ON -DCLBlast_DIR=/some/path
else ifeq ($(BUILD_TYPE),clblas)
CMAKE_ARGS+=-DGGML_CLBLAST=ON -DCLBlast_DIR=/some/path
# If it's hipblas we do have also to set CC=/opt/rocm/llvm/bin/clang CXX=/opt/rocm/llvm/bin/clang++
else ifeq ($(BUILD_TYPE),hipblas)
CMAKE_ARGS+=-DGGML_HIP=ON
# If it's OSX, DO NOT embed the metal library - -DGGML_METAL_EMBED_LIBRARY=ON requires further investigation
# But if it's OSX without metal, disable it here
else ifeq ($(OS),Darwin)
ifneq ($(BUILD_TYPE),metal)
CMAKE_ARGS+=-DGGML_METAL=OFF
else
CMAKE_ARGS+=-DGGML_METAL=ON
# Until this is tested properly, we disable embedded metal file
# as we already embed it as part of the LocalAI assets
CMAKE_ARGS+=-DGGML_METAL_EMBED_LIBRARY=OFF
TARGET+=--target ggml-metal
endif
endif
ifeq ($(BUILD_TYPE),sycl_f16)
CMAKE_ARGS+=-DGGML_SYCL=ON -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx -DGGML_SYCL_F16=ON
endif
ifeq ($(BUILD_TYPE),sycl_f32)
CMAKE_ARGS+=-DGGML_SYCL=ON -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx
endif
llama.cpp:
mkdir -p llama.cpp
cd llama.cpp && \
@@ -34,7 +72,7 @@ clean: purge
rm -rf llama.cpp
grpc-server: llama.cpp llama.cpp/examples/grpc-server
@echo "Building grpc-server for llama.cpp with $(BUILD_TYPE) build type and $(CMAKE_ARGS)"
@echo "Building grpc-server with $(BUILD_TYPE) build type and $(CMAKE_ARGS)"
ifneq (,$(findstring sycl,$(BUILD_TYPE)))
+bash -c "source $(ONEAPI_VARS); \
cd llama.cpp && mkdir -p build && cd build && cmake .. $(CMAKE_ARGS) && cmake --build . --config Release $(TARGET)"

View File

@@ -2241,12 +2241,6 @@ static void params_parse(const backend::ModelOptions* request,
}
// params.model_alias ??
params.model_alias = request->modelfile();
if (!request->cachetypekey().empty()) {
params.cache_type_k = request->cachetypekey();
}
if (!request->cachetypevalue().empty()) {
params.cache_type_v = request->cachetypevalue();
}
params.n_ctx = request->contextsize();
//params.memory_f16 = request->f16memory();
params.cpuparams.n_threads = request->threads();

View File

@@ -1,25 +0,0 @@
INCLUDE_PATH := $(abspath ./)
LIBRARY_PATH := $(abspath ./)
AR?=ar
BUILD_TYPE?=
# keep standard at C11 and C++11
CXXFLAGS = -I. -I$(INCLUDE_PATH)/../../../sources/bark.cpp/examples -I$(INCLUDE_PATH)/../../../sources/bark.cpp/spm-headers -I$(INCLUDE_PATH)/../../../sources/bark.cpp -O3 -DNDEBUG -std=c++17 -fPIC
LDFLAGS = -L$(LIBRARY_PATH) -L$(LIBRARY_PATH)/../../../sources/bark.cpp/build/examples -lbark -lstdc++ -lm
# warnings
CXXFLAGS += -Wall -Wextra -Wpedantic -Wcast-qual -Wno-unused-function
gobark.o:
$(CXX) $(CXXFLAGS) gobark.cpp -o gobark.o -c $(LDFLAGS)
libbark.a: gobark.o
cp $(INCLUDE_PATH)/../../../sources/bark.cpp/build/libbark.a ./
$(AR) rcs libbark.a gobark.o
$(AR) rcs libbark.a $(LIBRARY_PATH)/../../../sources/bark.cpp/build/encodec.cpp/ggml/src/CMakeFiles/ggml.dir/ggml.c.o
$(AR) rcs libbark.a $(LIBRARY_PATH)/../../../sources/bark.cpp/build/encodec.cpp/ggml/src/CMakeFiles/ggml.dir/ggml-alloc.c.o
$(AR) rcs libbark.a $(LIBRARY_PATH)/../../../sources/bark.cpp/build/encodec.cpp/ggml/src/CMakeFiles/ggml.dir/ggml-backend.c.o
clean:
rm -f gobark.o libbark.a

View File

@@ -1,85 +0,0 @@
#include <iostream>
#include <tuple>
#include "bark.h"
#include "gobark.h"
#include "common.h"
#include "ggml.h"
struct bark_context *c;
void bark_print_progress_callback(struct bark_context *bctx, enum bark_encoding_step step, int progress, void *user_data) {
if (step == bark_encoding_step::SEMANTIC) {
printf("\rGenerating semantic tokens... %d%%", progress);
} else if (step == bark_encoding_step::COARSE) {
printf("\rGenerating coarse tokens... %d%%", progress);
} else if (step == bark_encoding_step::FINE) {
printf("\rGenerating fine tokens... %d%%", progress);
}
fflush(stdout);
}
int load_model(char *model) {
// initialize bark context
struct bark_context_params ctx_params = bark_context_default_params();
bark_params params;
params.model_path = model;
// ctx_params.verbosity = verbosity;
ctx_params.progress_callback = bark_print_progress_callback;
ctx_params.progress_callback_user_data = nullptr;
struct bark_context *bctx = bark_load_model(params.model_path.c_str(), ctx_params, params.seed);
if (!bctx) {
fprintf(stderr, "%s: Could not load model\n", __func__);
return 1;
}
c = bctx;
return 0;
}
int tts(char *text,int threads, char *dst ) {
ggml_time_init();
const int64_t t_main_start_us = ggml_time_us();
// generate audio
if (!bark_generate_audio(c, text, threads)) {
fprintf(stderr, "%s: An error occured. If the problem persists, feel free to open an issue to report it.\n", __func__);
return 1;
}
const float *audio_data = bark_get_audio_data(c);
if (audio_data == NULL) {
fprintf(stderr, "%s: Could not get audio data\n", __func__);
return 1;
}
const int audio_arr_size = bark_get_audio_data_size(c);
std::vector<float> audio_arr(audio_data, audio_data + audio_arr_size);
write_wav_on_disk(audio_arr, dst);
// report timing
{
const int64_t t_main_end_us = ggml_time_us();
const int64_t t_load_us = bark_get_load_time(c);
const int64_t t_eval_us = bark_get_eval_time(c);
printf("\n\n");
printf("%s: load time = %8.2f ms\n", __func__, t_load_us / 1000.0f);
printf("%s: eval time = %8.2f ms\n", __func__, t_eval_us / 1000.0f);
printf("%s: total time = %8.2f ms\n", __func__, (t_main_end_us - t_main_start_us) / 1000.0f);
}
return 0;
}
int unload() {
bark_free(c);
}

View File

@@ -1,52 +0,0 @@
package main
// #cgo CXXFLAGS: -I${SRCDIR}/../../../sources/bark.cpp/ -I${SRCDIR}/../../../sources/bark.cpp/encodec.cpp -I${SRCDIR}/../../../sources/bark.cpp/examples -I${SRCDIR}/../../../sources/bark.cpp/spm-headers
// #cgo LDFLAGS: -L${SRCDIR}/ -L${SRCDIR}/../../../sources/bark.cpp/build/examples -L${SRCDIR}/../../../sources/bark.cpp/build/encodec.cpp/ -lbark -lencodec -lcommon
// #include <gobark.h>
// #include <stdlib.h>
import "C"
import (
"fmt"
"unsafe"
"github.com/mudler/LocalAI/pkg/grpc/base"
pb "github.com/mudler/LocalAI/pkg/grpc/proto"
)
type Bark struct {
base.SingleThread
threads int
}
func (sd *Bark) Load(opts *pb.ModelOptions) error {
sd.threads = int(opts.Threads)
modelFile := C.CString(opts.ModelFile)
defer C.free(unsafe.Pointer(modelFile))
ret := C.load_model(modelFile)
if ret != 0 {
return fmt.Errorf("inference failed")
}
return nil
}
func (sd *Bark) TTS(opts *pb.TTSRequest) error {
t := C.CString(opts.Text)
defer C.free(unsafe.Pointer(t))
dst := C.CString(opts.Dst)
defer C.free(unsafe.Pointer(dst))
threads := C.int(sd.threads)
ret := C.tts(t, threads, dst)
if ret != 0 {
return fmt.Errorf("inference failed")
}
return nil
}

View File

@@ -1,8 +0,0 @@
#ifdef __cplusplus
extern "C" {
#endif
int load_model(char *model);
int tts(char *text,int threads, char *dst );
#ifdef __cplusplus
}
#endif

View File

@@ -1,21 +0,0 @@
INCLUDE_PATH := $(abspath ./)
LIBRARY_PATH := $(abspath ./)
AR?=ar
BUILD_TYPE?=
# keep standard at C11 and C++11
CXXFLAGS = -I. -I$(INCLUDE_PATH)/../../../../sources/stablediffusion-ggml.cpp/thirdparty -I$(INCLUDE_PATH)/../../../../sources/stablediffusion-ggml.cpp/ggml/include -I$(INCLUDE_PATH)/../../../../sources/stablediffusion-ggml.cpp -O3 -DNDEBUG -std=c++17 -fPIC
# warnings
CXXFLAGS += -Wall -Wextra -Wpedantic -Wcast-qual -Wno-unused-function
gosd.o:
$(CXX) $(CXXFLAGS) gosd.cpp -o gosd.o -c
libsd.a: gosd.o
cp $(INCLUDE_PATH)/../../../../sources/stablediffusion-ggml.cpp/build/libstable-diffusion.a ./libsd.a
$(AR) rcs libsd.a gosd.o
clean:
rm -f gosd.o libsd.a

View File

@@ -1,228 +0,0 @@
#include <stdio.h>
#include <string.h>
#include <time.h>
#include <iostream>
#include <random>
#include <string>
#include <vector>
#include "gosd.h"
// #include "preprocessing.hpp"
#include "flux.hpp"
#include "stable-diffusion.h"
#define STB_IMAGE_IMPLEMENTATION
#define STB_IMAGE_STATIC
#include "stb_image.h"
#define STB_IMAGE_WRITE_IMPLEMENTATION
#define STB_IMAGE_WRITE_STATIC
#include "stb_image_write.h"
#define STB_IMAGE_RESIZE_IMPLEMENTATION
#define STB_IMAGE_RESIZE_STATIC
#include "stb_image_resize.h"
// Names of the sampler method, same order as enum sample_method in stable-diffusion.h
const char* sample_method_str[] = {
"euler_a",
"euler",
"heun",
"dpm2",
"dpm++2s_a",
"dpm++2m",
"dpm++2mv2",
"ipndm",
"ipndm_v",
"lcm",
};
// Names of the sigma schedule overrides, same order as sample_schedule in stable-diffusion.h
const char* schedule_str[] = {
"default",
"discrete",
"karras",
"exponential",
"ays",
"gits",
};
sd_ctx_t* sd_c;
sample_method_t sample_method;
int load_model(char *model, char* options[], int threads, int diff) {
fprintf (stderr, "Loading model!\n");
char *stableDiffusionModel = "";
if (diff == 1 ) {
stableDiffusionModel = model;
model = "";
}
// decode options. Options are in form optname:optvale, or if booleans only optname.
char *clip_l_path = "";
char *clip_g_path = "";
char *t5xxl_path = "";
char *vae_path = "";
char *scheduler = "";
char *sampler = "";
// If options is not NULL, parse options
for (int i = 0; options[i] != NULL; i++) {
char *optname = strtok(options[i], ":");
char *optval = strtok(NULL, ":");
if (optval == NULL) {
optval = "true";
}
if (!strcmp(optname, "clip_l_path")) {
clip_l_path = optval;
}
if (!strcmp(optname, "clip_g_path")) {
clip_g_path = optval;
}
if (!strcmp(optname, "t5xxl_path")) {
t5xxl_path = optval;
}
if (!strcmp(optname, "vae_path")) {
vae_path = optval;
}
if (!strcmp(optname, "scheduler")) {
scheduler = optval;
}
if (!strcmp(optname, "sampler")) {
sampler = optval;
}
}
int sample_method_found = -1;
for (int m = 0; m < N_SAMPLE_METHODS; m++) {
if (!strcmp(sampler, sample_method_str[m])) {
sample_method_found = m;
}
}
if (sample_method_found == -1) {
fprintf(stderr, "Invalid sample method, default to EULER_A!\n");
sample_method_found = EULER_A;
}
sample_method = (sample_method_t)sample_method_found;
int schedule_found = -1;
for (int d = 0; d < N_SCHEDULES; d++) {
if (!strcmp(scheduler, schedule_str[d])) {
schedule_found = d;
fprintf (stderr, "Found scheduler: %s\n", scheduler);
}
}
if (schedule_found == -1) {
fprintf (stderr, "Invalid scheduler! using DEFAULT\n");
schedule_found = DEFAULT;
}
schedule_t schedule = (schedule_t)schedule_found;
fprintf (stderr, "Creating context\n");
sd_ctx_t* sd_ctx = new_sd_ctx(model,
clip_l_path,
clip_g_path,
t5xxl_path,
stableDiffusionModel,
vae_path,
"",
"",
"",
"",
"",
false,
false,
false,
threads,
SD_TYPE_COUNT,
STD_DEFAULT_RNG,
schedule,
false,
false,
false,
false);
if (sd_ctx == NULL) {
fprintf (stderr, "failed loading model (generic error)\n");
return 1;
}
fprintf (stderr, "Created context: OK\n");
sd_c = sd_ctx;
return 0;
}
int gen_image(char *text, char *negativeText, int width, int height, int steps, int seed , char *dst, float cfg_scale) {
sd_image_t* results;
std::vector<int> skip_layers = {7, 8, 9};
fprintf (stderr, "Generating image\n");
results = txt2img(sd_c,
text,
negativeText,
-1, //clip_skip
cfg_scale, // sfg_scale
3.5f,
width,
height,
sample_method,
steps,
seed,
1,
NULL,
0.9f,
20.f,
false,
"",
skip_layers.data(),
skip_layers.size(),
0,
0.01,
0.2);
if (results == NULL) {
fprintf (stderr, "NO results\n");
return 1;
}
if (results[0].data == NULL) {
fprintf (stderr, "Results with no data\n");
return 1;
}
fprintf (stderr, "Writing PNG\n");
fprintf (stderr, "DST: %s\n", dst);
fprintf (stderr, "Width: %d\n", results[0].width);
fprintf (stderr, "Height: %d\n", results[0].height);
fprintf (stderr, "Channel: %d\n", results[0].channel);
fprintf (stderr, "Data: %p\n", results[0].data);
stbi_write_png(dst, results[0].width, results[0].height, results[0].channel,
results[0].data, 0, NULL);
fprintf (stderr, "Saved resulting image to '%s'\n", dst);
// TODO: free results. Why does it crash?
free(results[0].data);
results[0].data = NULL;
free(results);
fprintf (stderr, "gen_image is done", dst);
return 0;
}
int unload() {
free_sd_ctx(sd_c);
}

View File

@@ -1,96 +0,0 @@
package main
// #cgo CXXFLAGS: -I${SRCDIR}/../../../../sources/stablediffusion-ggml.cpp/thirdparty -I${SRCDIR}/../../../../sources/stablediffusion-ggml.cpp -I${SRCDIR}/../../../../sources/stablediffusion-ggml.cpp/ggml/include
// #cgo LDFLAGS: -L${SRCDIR}/ -L${SRCDIR}/../../../../sources/stablediffusion-ggml.cpp/build/ggml/src/ggml-cpu -L${SRCDIR}/../../../../sources/stablediffusion-ggml.cpp/build/ggml/src -lsd -lstdc++ -lm -lggml -lggml-base -lggml-cpu -lgomp
// #include <gosd.h>
// #include <stdlib.h>
import "C"
import (
"fmt"
"os"
"path/filepath"
"strings"
"unsafe"
"github.com/mudler/LocalAI/pkg/grpc/base"
pb "github.com/mudler/LocalAI/pkg/grpc/proto"
"github.com/mudler/LocalAI/pkg/utils"
)
type SDGGML struct {
base.SingleThread
threads int
sampleMethod string
cfgScale float32
}
func (sd *SDGGML) Load(opts *pb.ModelOptions) error {
sd.threads = int(opts.Threads)
modelFile := C.CString(opts.ModelFile)
defer C.free(unsafe.Pointer(modelFile))
var options **C.char
// prepare the options array to pass to C
size := C.size_t(unsafe.Sizeof((*C.char)(nil)))
length := C.size_t(len(opts.Options))
options = (**C.char)(C.malloc(length * size))
view := (*[1 << 30]*C.char)(unsafe.Pointer(options))[0:len(opts.Options):len(opts.Options)]
var diffusionModel int
var oo []string
for _, op := range opts.Options {
if op == "diffusion_model" {
diffusionModel = 1
continue
}
// If it's an option path, we resolve absolute path from the model path
if strings.Contains(op, ":") && strings.Contains(op, "path") {
data := strings.Split(op, ":")
data[1] = filepath.Join(opts.ModelPath, data[1])
if err := utils.VerifyPath(data[1], opts.ModelPath); err == nil {
oo = append(oo, strings.Join(data, ":"))
}
} else {
oo = append(oo, op)
}
}
fmt.Fprintf(os.Stderr, "Options: %+v\n", oo)
for i, x := range oo {
view[i] = C.CString(x)
}
sd.cfgScale = opts.CFGScale
ret := C.load_model(modelFile, options, C.int(opts.Threads), C.int(diffusionModel))
if ret != 0 {
return fmt.Errorf("could not load model")
}
return nil
}
func (sd *SDGGML) GenerateImage(opts *pb.GenerateImageRequest) error {
t := C.CString(opts.PositivePrompt)
defer C.free(unsafe.Pointer(t))
dst := C.CString(opts.Dst)
defer C.free(unsafe.Pointer(dst))
negative := C.CString(opts.NegativePrompt)
defer C.free(unsafe.Pointer(negative))
ret := C.gen_image(t, negative, C.int(opts.Width), C.int(opts.Height), C.int(opts.Step), C.int(opts.Seed), dst, C.float(sd.cfgScale))
if ret != 0 {
return fmt.Errorf("inference failed")
}
return nil
}

View File

@@ -1,8 +0,0 @@
#ifdef __cplusplus
extern "C" {
#endif
int load_model(char *model, char* options[], int threads, int diffusionModel);
int gen_image(char *text, char *negativeText, int width, int height, int steps, int seed, char *dst, float cfg_scale);
#ifdef __cplusplus
}
#endif

View File

@@ -1,20 +0,0 @@
package main
// Note: this is started internally by LocalAI and a server is allocated for each model
import (
"flag"
grpc "github.com/mudler/LocalAI/pkg/grpc"
)
var (
addr = flag.String("addr", "localhost:50051", "the address to connect to")
)
func main() {
flag.Parse()
if err := grpc.StartServer(*addr, &SDGGML{}); err != nil {
panic(err)
}
}

View File

@@ -0,0 +1,34 @@
package main
// This is a wrapper to statisfy the GRPC service interface
// It is meant to be used by the main executable that is the server for the specific backend type (falcon, gpt3, etc)
import (
bert "github.com/go-skynet/go-bert.cpp"
"github.com/mudler/LocalAI/pkg/grpc/base"
pb "github.com/mudler/LocalAI/pkg/grpc/proto"
)
type Embeddings struct {
base.SingleThread
bert *bert.Bert
}
func (llm *Embeddings) Load(opts *pb.ModelOptions) error {
model, err := bert.New(opts.ModelFile)
llm.bert = model
return err
}
func (llm *Embeddings) Embeddings(opts *pb.PredictOptions) ([]float32, error) {
if len(opts.EmbeddingTokens) > 0 {
tokens := []int{}
for _, t := range opts.EmbeddingTokens {
tokens = append(tokens, int(t))
}
return llm.bert.TokenEmbeddings(tokens, bert.SetThreads(int(opts.Threads)))
}
return llm.bert.Embeddings(opts.Embeddings, bert.SetThreads(int(opts.Threads)))
}

View File

@@ -1,6 +1,7 @@
package main
// Note: this is started internally by LocalAI and a server is allocated for each model
import (
"flag"
@@ -14,7 +15,7 @@ var (
func main() {
flag.Parse()
if err := grpc.StartServer(*addr, &Bark{}); err != nil {
if err := grpc.StartServer(*addr, &Embeddings{}); err != nil {
panic(err)
}
}

View File

@@ -1,6 +1,6 @@
accelerate
auto-gptq==0.7.1
grpcio==1.68.1
grpcio==1.68.0
protobuf
certifi
transformers

View File

@@ -1,4 +1,4 @@
bark==0.1.5
grpcio==1.68.1
grpcio==1.68.0
protobuf
certifi

View File

@@ -1,3 +1,3 @@
grpcio==1.68.1
grpcio==1.68.0
protobuf
grpcio-tools

View File

@@ -1,4 +1,4 @@
grpcio==1.68.1
grpcio==1.68.0
protobuf
certifi
packaging==24.1

View File

@@ -1,5 +1,5 @@
setuptools
grpcio==1.68.1
grpcio==1.68.0
pillow
protobuf
certifi

View File

@@ -1,4 +1,4 @@
grpcio==1.68.1
grpcio==1.68.0
protobuf
certifi
wheel

View File

@@ -1,3 +1,3 @@
grpcio==1.68.1
grpcio==1.68.0
protobuf
certifi

View File

@@ -2,7 +2,7 @@
intel-extension-for-pytorch
torch
optimum[openvino]
grpcio==1.68.1
grpcio==1.68.0
protobuf
librosa==0.9.1
faster-whisper==0.9.0

View File

@@ -1,4 +1,4 @@
grpcio==1.68.1
grpcio==1.68.0
protobuf
librosa
faster-whisper

View File

@@ -1,3 +1,3 @@
grpcio==1.68.1
grpcio==1.68.0
certifi
llvmlite==0.43.0

View File

@@ -1,3 +1,3 @@
grpcio==1.68.1
grpcio==1.68.0
protobuf
certifi

View File

@@ -1,4 +1,4 @@
grpcio==1.68.1
grpcio==1.68.0
protobuf
certifi
datasets

View File

@@ -1,4 +1,4 @@
grpcio==1.68.1
grpcio==1.68.0
protobuf
scipy==1.14.0
certifi

View File

@@ -1,4 +1,4 @@
grpcio==1.68.1
grpcio==1.68.0
protobuf
certifi
setuptools==69.5.1 # https://github.com/mudler/LocalAI/issues/2406

View File

@@ -1,3 +1,3 @@
grpcio==1.68.1
grpcio==1.68.0
protobuf
certifi

View File

@@ -22,7 +22,7 @@ if [ "x${BUILD_TYPE}" == "x" ] && [ "x${FROM_SOURCE}" == "xtrue" ]; then
git clone https://github.com/vllm-project/vllm
fi
pushd vllm
uv pip install wheel packaging ninja "setuptools>=49.4.0" numpy typing-extensions pillow setuptools-scm grpcio==1.68.1 protobuf bitsandbytes
uv pip install wheel packaging ninja "setuptools>=49.4.0" numpy typing-extensions pillow setuptools-scm grpcio==1.68.0 protobuf bitsandbytes
uv pip install -v -r requirements-cpu.txt --extra-index-url https://download.pytorch.org/whl/cpu
VLLM_TARGET_DEVICE=cpu python setup.py install
popd

View File

@@ -1,4 +1,4 @@
grpcio==1.68.1
grpcio==1.68.0
protobuf
certifi
setuptools

38
core/application.go Normal file
View File

@@ -0,0 +1,38 @@
package core
import (
"github.com/mudler/LocalAI/core/config"
"github.com/mudler/LocalAI/core/services"
"github.com/mudler/LocalAI/pkg/model"
)
// The purpose of this structure is to hold pointers to all initialized services, to make plumbing easy
// Perhaps a proper DI system is worth it in the future, but for now keep things simple.
type Application struct {
// Application-Level Config
ApplicationConfig *config.ApplicationConfig
// ApplicationState *ApplicationState
// Core Low-Level Services
BackendConfigLoader *config.BackendConfigLoader
ModelLoader *model.ModelLoader
// Backend Services
// EmbeddingsBackendService *backend.EmbeddingsBackendService
// ImageGenerationBackendService *backend.ImageGenerationBackendService
// LLMBackendService *backend.LLMBackendService
// TranscriptionBackendService *backend.TranscriptionBackendService
// TextToSpeechBackendService *backend.TextToSpeechBackendService
// LocalAI System Services
BackendMonitorService *services.BackendMonitorService
GalleryService *services.GalleryService
LocalAIMetricsService *services.LocalAIMetricsService
// OpenAIService *services.OpenAIService
}
// TODO [NEXT PR?]: Break up ApplicationConfig.
// Migrate over stuff that is not set via config at all - especially runtime stuff
type ApplicationState struct {
}

View File

@@ -1,39 +0,0 @@
package application
import (
"github.com/mudler/LocalAI/core/config"
"github.com/mudler/LocalAI/pkg/model"
"github.com/mudler/LocalAI/pkg/templates"
)
type Application struct {
backendLoader *config.BackendConfigLoader
modelLoader *model.ModelLoader
applicationConfig *config.ApplicationConfig
templatesEvaluator *templates.Evaluator
}
func newApplication(appConfig *config.ApplicationConfig) *Application {
return &Application{
backendLoader: config.NewBackendConfigLoader(appConfig.ModelPath),
modelLoader: model.NewModelLoader(appConfig.ModelPath),
applicationConfig: appConfig,
templatesEvaluator: templates.NewEvaluator(appConfig.ModelPath),
}
}
func (a *Application) BackendLoader() *config.BackendConfigLoader {
return a.backendLoader
}
func (a *Application) ModelLoader() *model.ModelLoader {
return a.modelLoader
}
func (a *Application) ApplicationConfig() *config.ApplicationConfig {
return a.applicationConfig
}
func (a *Application) TemplatesEvaluator() *templates.Evaluator {
return a.templatesEvaluator
}

View File

@@ -122,7 +122,7 @@ func grpcModelOpts(c config.BackendConfig) *pb.ModelOptions {
CUDA: c.CUDA || c.Diffusers.CUDA,
SchedulerType: c.Diffusers.SchedulerType,
PipelineType: c.Diffusers.PipelineType,
CFGScale: c.CFGScale,
CFGScale: c.Diffusers.CFGScale,
LoraAdapter: c.LoraAdapter,
LoraScale: c.LoraScale,
LoraAdapters: c.LoraAdapters,
@@ -132,7 +132,6 @@ func grpcModelOpts(c config.BackendConfig) *pb.ModelOptions {
IMG2IMG: c.Diffusers.IMG2IMG,
CLIPModel: c.Diffusers.ClipModel,
CLIPSubfolder: c.Diffusers.ClipSubFolder,
Options: c.Options,
CLIPSkip: int32(c.Diffusers.ClipSkip),
ControlNet: c.Diffusers.ControlNet,
ContextSize: int32(ctxSize),
@@ -151,8 +150,6 @@ func grpcModelOpts(c config.BackendConfig) *pb.ModelOptions {
TensorParallelSize: int32(c.TensorParallelSize),
MMProj: c.MMProj,
FlashAttention: c.FlashAttention,
CacheTypeKey: c.CacheTypeK,
CacheTypeValue: c.CacheTypeV,
NoKVOffload: c.NoKVOffloading,
YarnExtFactor: c.YarnExtFactor,
YarnAttnFactor: c.YarnAttnFactor,

View File

@@ -6,12 +6,12 @@ import (
"strings"
"time"
"github.com/mudler/LocalAI/core/application"
cli_api "github.com/mudler/LocalAI/core/cli/api"
cliContext "github.com/mudler/LocalAI/core/cli/context"
"github.com/mudler/LocalAI/core/config"
"github.com/mudler/LocalAI/core/http"
"github.com/mudler/LocalAI/core/p2p"
"github.com/mudler/LocalAI/core/startup"
"github.com/rs/zerolog"
"github.com/rs/zerolog/log"
)
@@ -186,16 +186,16 @@ func (r *RunCMD) Run(ctx *cliContext.Context) error {
}
if r.PreloadBackendOnly {
_, err := application.New(opts...)
_, _, _, err := startup.Startup(opts...)
return err
}
app, err := application.New(opts...)
cl, ml, options, err := startup.Startup(opts...)
if err != nil {
return fmt.Errorf("failed basic startup tasks with error %s", err.Error())
}
appHTTP, err := http.API(app)
appHTTP, err := http.App(cl, ml, options)
if err != nil {
log.Error().Err(err).Msg("error during HTTP App construction")
return err

View File

@@ -72,8 +72,6 @@ type BackendConfig struct {
Description string `yaml:"description"`
Usage string `yaml:"usage"`
Options []string `yaml:"options"`
}
type File struct {
@@ -99,15 +97,16 @@ type GRPC struct {
}
type Diffusers struct {
CUDA bool `yaml:"cuda"`
PipelineType string `yaml:"pipeline_type"`
SchedulerType string `yaml:"scheduler_type"`
EnableParameters string `yaml:"enable_parameters"` // A list of comma separated parameters to specify
IMG2IMG bool `yaml:"img2img"` // Image to Image Diffuser
ClipSkip int `yaml:"clip_skip"` // Skip every N frames
ClipModel string `yaml:"clip_model"` // Clip model to use
ClipSubFolder string `yaml:"clip_subfolder"` // Subfolder to use for clip model
ControlNet string `yaml:"control_net"`
CUDA bool `yaml:"cuda"`
PipelineType string `yaml:"pipeline_type"`
SchedulerType string `yaml:"scheduler_type"`
EnableParameters string `yaml:"enable_parameters"` // A list of comma separated parameters to specify
CFGScale float32 `yaml:"cfg_scale"` // Classifier-Free Guidance Scale
IMG2IMG bool `yaml:"img2img"` // Image to Image Diffuser
ClipSkip int `yaml:"clip_skip"` // Skip every N frames
ClipModel string `yaml:"clip_model"` // Clip model to use
ClipSubFolder string `yaml:"clip_subfolder"` // Subfolder to use for clip model
ControlNet string `yaml:"control_net"`
}
// LLMConfig is a struct that holds the configuration that are
@@ -155,10 +154,8 @@ type LLMConfig struct {
TensorParallelSize int `yaml:"tensor_parallel_size"` // vLLM
MMProj string `yaml:"mmproj"`
FlashAttention bool `yaml:"flash_attention"`
NoKVOffloading bool `yaml:"no_kv_offloading"`
CacheTypeK string `yaml:"cache_type_k"`
CacheTypeV string `yaml:"cache_type_v"`
FlashAttention bool `yaml:"flash_attention"`
NoKVOffloading bool `yaml:"no_kv_offloading"`
RopeScaling string `yaml:"rope_scaling"`
ModelType string `yaml:"type"`
@@ -167,8 +164,6 @@ type LLMConfig struct {
YarnAttnFactor float32 `yaml:"yarn_attn_factor"`
YarnBetaFast float32 `yaml:"yarn_beta_fast"`
YarnBetaSlow float32 `yaml:"yarn_beta_slow"`
CFGScale float32 `yaml:"cfg_scale"` // Classifier-Free Guidance Scale
}
// AutoGPTQ is a struct that holds the configuration specific to the AutoGPTQ backend
@@ -206,8 +201,6 @@ type TemplateConfig struct {
JoinChatMessagesByCharacter *string `yaml:"join_chat_messages_by_character"`
Multimodal string `yaml:"multimodal"`
JinjaTemplate bool `yaml:"jinja_template"`
}
func (c *BackendConfig) UnmarshalYAML(value *yaml.Node) error {

View File

@@ -26,14 +26,14 @@ const (
type settingsConfig struct {
StopWords []string
TemplateConfig TemplateConfig
RepeatPenalty float64
RepeatPenalty float64
}
// default settings to adopt with a given model family
var defaultsSettings map[familyType]settingsConfig = map[familyType]settingsConfig{
Gemma: {
RepeatPenalty: 1.0,
StopWords: []string{"<|im_end|>", "<end_of_turn>", "<start_of_turn>"},
StopWords: []string{"<|im_end|>", "<end_of_turn>", "<start_of_turn>"},
TemplateConfig: TemplateConfig{
Chat: "{{.Input }}\n<start_of_turn>model\n",
ChatMessage: "<start_of_turn>{{if eq .RoleName \"assistant\" }}model{{else}}{{ .RoleName }}{{end}}\n{{ if .Content -}}\n{{.Content -}}\n{{ end -}}<end_of_turn>",
@@ -200,18 +200,6 @@ func guessDefaultsFromFile(cfg *BackendConfig, modelPath string) {
} else {
log.Debug().Any("family", family).Msgf("guessDefaultsFromFile: no template found for family")
}
if cfg.HasTemplate() {
return
}
// identify from well known templates first, otherwise use the raw jinja template
chatTemplate, found := f.Header.MetadataKV.Get("tokenizer.chat_template")
if found {
// try to use the jinja template
cfg.TemplateConfig.JinjaTemplate = true
cfg.TemplateConfig.ChatMessage = chatTemplate.ValueString()
}
}
func identifyFamily(f *gguf.GGUFFile) familyType {

View File

@@ -12,8 +12,6 @@ import (
"gopkg.in/yaml.v3"
)
const bertEmbeddingsURL = `https://gist.githubusercontent.com/mudler/0a080b166b87640e8644b09c2aee6e3b/raw/f0e8c26bb72edc16d9fbafbfd6638072126ff225/bert-embeddings-gallery.yaml`
var _ = Describe("Model test", func() {
Context("Downloading", func() {
@@ -49,7 +47,7 @@ var _ = Describe("Model test", func() {
gallery := []GalleryModel{{
Name: "bert",
URL: bertEmbeddingsURL,
URL: "https://raw.githubusercontent.com/go-skynet/model-gallery/main/bert-embeddings.yaml",
}}
out, err := yaml.Marshal(gallery)
Expect(err).ToNot(HaveOccurred())
@@ -68,7 +66,7 @@ var _ = Describe("Model test", func() {
Expect(err).ToNot(HaveOccurred())
Expect(len(models)).To(Equal(1))
Expect(models[0].Name).To(Equal("bert"))
Expect(models[0].URL).To(Equal(bertEmbeddingsURL))
Expect(models[0].URL).To(Equal("https://raw.githubusercontent.com/go-skynet/model-gallery/main/bert-embeddings.yaml"))
Expect(models[0].Installed).To(BeFalse())
err = InstallModelFromGallery(galleries, "test@bert", tempdir, GalleryModel{}, func(s1, s2, s3 string, f float64) {}, true)
@@ -80,7 +78,7 @@ var _ = Describe("Model test", func() {
content := map[string]interface{}{}
err = yaml.Unmarshal(dat, &content)
Expect(err).ToNot(HaveOccurred())
Expect(content["usage"]).To(ContainSubstring("You can test this model with curl like this"))
Expect(content["backend"]).To(Equal("bert-embeddings"))
models, err = AvailableGalleryModels(galleries, tempdir)
Expect(err).ToNot(HaveOccurred())

View File

@@ -14,9 +14,10 @@ import (
"github.com/mudler/LocalAI/core/http/middleware"
"github.com/mudler/LocalAI/core/http/routes"
"github.com/mudler/LocalAI/core/application"
"github.com/mudler/LocalAI/core/config"
"github.com/mudler/LocalAI/core/schema"
"github.com/mudler/LocalAI/core/services"
"github.com/mudler/LocalAI/pkg/model"
"github.com/gofiber/contrib/fiberzerolog"
"github.com/gofiber/fiber/v2"
@@ -48,18 +49,18 @@ var embedDirStatic embed.FS
// @in header
// @name Authorization
func API(application *application.Application) (*fiber.App, error) {
func App(cl *config.BackendConfigLoader, ml *model.ModelLoader, appConfig *config.ApplicationConfig) (*fiber.App, error) {
fiberCfg := fiber.Config{
Views: renderEngine(),
BodyLimit: application.ApplicationConfig().UploadLimitMB * 1024 * 1024, // this is the default limit of 4MB
BodyLimit: appConfig.UploadLimitMB * 1024 * 1024, // this is the default limit of 4MB
// We disable the Fiber startup message as it does not conform to structured logging.
// We register a startup log line with connection information in the OnListen hook to keep things user friendly though
DisableStartupMessage: true,
// Override default error handler
}
if !application.ApplicationConfig().OpaqueErrors {
if !appConfig.OpaqueErrors {
// Normally, return errors as JSON responses
fiberCfg.ErrorHandler = func(ctx *fiber.Ctx, err error) error {
// Status code defaults to 500
@@ -85,9 +86,9 @@ func API(application *application.Application) (*fiber.App, error) {
}
}
router := fiber.New(fiberCfg)
app := fiber.New(fiberCfg)
router.Hooks().OnListen(func(listenData fiber.ListenData) error {
app.Hooks().OnListen(func(listenData fiber.ListenData) error {
scheme := "http"
if listenData.TLS {
scheme = "https"
@@ -98,82 +99,82 @@ func API(application *application.Application) (*fiber.App, error) {
// Have Fiber use zerolog like the rest of the application rather than it's built-in logger
logger := log.Logger
router.Use(fiberzerolog.New(fiberzerolog.Config{
app.Use(fiberzerolog.New(fiberzerolog.Config{
Logger: &logger,
}))
// Default middleware config
if !application.ApplicationConfig().Debug {
router.Use(recover.New())
if !appConfig.Debug {
app.Use(recover.New())
}
if !application.ApplicationConfig().DisableMetrics {
if !appConfig.DisableMetrics {
metricsService, err := services.NewLocalAIMetricsService()
if err != nil {
return nil, err
}
if metricsService != nil {
router.Use(localai.LocalAIMetricsAPIMiddleware(metricsService))
router.Hooks().OnShutdown(func() error {
app.Use(localai.LocalAIMetricsAPIMiddleware(metricsService))
app.Hooks().OnShutdown(func() error {
return metricsService.Shutdown()
})
}
}
// Health Checks should always be exempt from auth, so register these first
routes.HealthRoutes(router)
routes.HealthRoutes(app)
kaConfig, err := middleware.GetKeyAuthConfig(application.ApplicationConfig())
kaConfig, err := middleware.GetKeyAuthConfig(appConfig)
if err != nil || kaConfig == nil {
return nil, fmt.Errorf("failed to create key auth config: %w", err)
}
// Auth is applied to _all_ endpoints. No exceptions. Filtering out endpoints to bypass is the role of the Filter property of the KeyAuth Configuration
router.Use(v2keyauth.New(*kaConfig))
app.Use(v2keyauth.New(*kaConfig))
if application.ApplicationConfig().CORS {
if appConfig.CORS {
var c func(ctx *fiber.Ctx) error
if application.ApplicationConfig().CORSAllowOrigins == "" {
if appConfig.CORSAllowOrigins == "" {
c = cors.New()
} else {
c = cors.New(cors.Config{AllowOrigins: application.ApplicationConfig().CORSAllowOrigins})
c = cors.New(cors.Config{AllowOrigins: appConfig.CORSAllowOrigins})
}
router.Use(c)
app.Use(c)
}
if application.ApplicationConfig().CSRF {
if appConfig.CSRF {
log.Debug().Msg("Enabling CSRF middleware. Tokens are now required for state-modifying requests")
router.Use(csrf.New())
app.Use(csrf.New())
}
// Load config jsons
utils.LoadConfig(application.ApplicationConfig().UploadDir, openai.UploadedFilesFile, &openai.UploadedFiles)
utils.LoadConfig(application.ApplicationConfig().ConfigsDir, openai.AssistantsConfigFile, &openai.Assistants)
utils.LoadConfig(application.ApplicationConfig().ConfigsDir, openai.AssistantsFileConfigFile, &openai.AssistantFiles)
utils.LoadConfig(appConfig.UploadDir, openai.UploadedFilesFile, &openai.UploadedFiles)
utils.LoadConfig(appConfig.ConfigsDir, openai.AssistantsConfigFile, &openai.Assistants)
utils.LoadConfig(appConfig.ConfigsDir, openai.AssistantsFileConfigFile, &openai.AssistantFiles)
galleryService := services.NewGalleryService(application.ApplicationConfig())
galleryService.Start(application.ApplicationConfig().Context, application.BackendLoader())
galleryService := services.NewGalleryService(appConfig)
galleryService.Start(appConfig.Context, cl)
routes.RegisterElevenLabsRoutes(router, application.BackendLoader(), application.ModelLoader(), application.ApplicationConfig())
routes.RegisterLocalAIRoutes(router, application.BackendLoader(), application.ModelLoader(), application.ApplicationConfig(), galleryService)
routes.RegisterOpenAIRoutes(router, application)
if !application.ApplicationConfig().DisableWebUI {
routes.RegisterUIRoutes(router, application.BackendLoader(), application.ModelLoader(), application.ApplicationConfig(), galleryService)
routes.RegisterElevenLabsRoutes(app, cl, ml, appConfig)
routes.RegisterLocalAIRoutes(app, cl, ml, appConfig, galleryService)
routes.RegisterOpenAIRoutes(app, cl, ml, appConfig)
if !appConfig.DisableWebUI {
routes.RegisterUIRoutes(app, cl, ml, appConfig, galleryService)
}
routes.RegisterJINARoutes(router, application.BackendLoader(), application.ModelLoader(), application.ApplicationConfig())
routes.RegisterJINARoutes(app, cl, ml, appConfig)
httpFS := http.FS(embedDirStatic)
router.Use(favicon.New(favicon.Config{
app.Use(favicon.New(favicon.Config{
URL: "/favicon.ico",
FileSystem: httpFS,
File: "static/favicon.ico",
}))
router.Use("/static", filesystem.New(filesystem.Config{
app.Use("/static", filesystem.New(filesystem.Config{
Root: httpFS,
PathPrefix: "static",
Browse: true,
@@ -181,7 +182,7 @@ func API(application *application.Application) (*fiber.App, error) {
// Define a custom 404 handler
// Note: keep this at the bottom!
router.Use(notFoundHandler)
app.Use(notFoundHandler)
return router, nil
return app, nil
}

View File

@@ -5,21 +5,24 @@ import (
"context"
"embed"
"encoding/json"
"errors"
"fmt"
"io"
"net/http"
"os"
"path/filepath"
"runtime"
"strings"
"github.com/mudler/LocalAI/core/application"
"github.com/mudler/LocalAI/core/config"
. "github.com/mudler/LocalAI/core/http"
"github.com/mudler/LocalAI/core/schema"
"github.com/mudler/LocalAI/core/startup"
"github.com/gofiber/fiber/v2"
"github.com/mudler/LocalAI/core/gallery"
"github.com/mudler/LocalAI/pkg/downloader"
"github.com/mudler/LocalAI/pkg/model"
. "github.com/onsi/ginkgo/v2"
. "github.com/onsi/gomega"
"gopkg.in/yaml.v3"
@@ -237,8 +240,6 @@ func postInvalidRequest(url string) (error, int) {
return nil, resp.StatusCode
}
const bertEmbeddingsURL = `https://gist.githubusercontent.com/mudler/0a080b166b87640e8644b09c2aee6e3b/raw/f0e8c26bb72edc16d9fbafbfd6638072126ff225/bert-embeddings-gallery.yaml`
//go:embed backend-assets/*
var backendAssets embed.FS
@@ -251,6 +252,9 @@ var _ = Describe("API test", func() {
var cancel context.CancelFunc
var tmpdir string
var modelDir string
var bcl *config.BackendConfigLoader
var ml *model.ModelLoader
var applicationConfig *config.ApplicationConfig
commonOpts := []config.AppOption{
config.WithDebug(true),
@@ -275,13 +279,13 @@ var _ = Describe("API test", func() {
g := []gallery.GalleryModel{
{
Name: "bert",
URL: bertEmbeddingsURL,
URL: "https://raw.githubusercontent.com/go-skynet/model-gallery/main/bert-embeddings.yaml",
},
{
Name: "bert2",
URL: bertEmbeddingsURL,
URL: "https://raw.githubusercontent.com/go-skynet/model-gallery/main/bert-embeddings.yaml",
Overrides: map[string]interface{}{"foo": "bar"},
AdditionalFiles: []gallery.File{{Filename: "foo.yaml", URI: bertEmbeddingsURL}},
AdditionalFiles: []gallery.File{{Filename: "foo.yaml", URI: "https://raw.githubusercontent.com/go-skynet/model-gallery/main/bert-embeddings.yaml"}},
},
}
out, err := yaml.Marshal(g)
@@ -296,7 +300,7 @@ var _ = Describe("API test", func() {
},
}
application, err := application.New(
bcl, ml, applicationConfig, err = startup.Startup(
append(commonOpts,
config.WithContext(c),
config.WithGalleries(galleries),
@@ -306,7 +310,7 @@ var _ = Describe("API test", func() {
config.WithBackendAssetsOutput(backendAssetsDir))...)
Expect(err).ToNot(HaveOccurred())
app, err = API(application)
app, err = App(bcl, ml, applicationConfig)
Expect(err).ToNot(HaveOccurred())
go app.Listen("127.0.0.1:9090")
@@ -379,7 +383,7 @@ var _ = Describe("API test", func() {
content := map[string]interface{}{}
err = yaml.Unmarshal(dat, &content)
Expect(err).ToNot(HaveOccurred())
Expect(content["usage"]).To(ContainSubstring("You can test this model with curl like this"))
Expect(content["backend"]).To(Equal("bert-embeddings"))
Expect(content["foo"]).To(Equal("bar"))
models, err = getModels("http://127.0.0.1:9090/models/available")
@@ -398,7 +402,7 @@ var _ = Describe("API test", func() {
It("overrides models", func() {
response := postModelApplyRequest("http://127.0.0.1:9090/models/apply", modelApplyRequest{
URL: bertEmbeddingsURL,
URL: "https://raw.githubusercontent.com/go-skynet/model-gallery/main/bert-embeddings.yaml",
Name: "bert",
Overrides: map[string]interface{}{
"backend": "llama",
@@ -447,7 +451,7 @@ var _ = Describe("API test", func() {
})
It("apply models without overrides", func() {
response := postModelApplyRequest("http://127.0.0.1:9090/models/apply", modelApplyRequest{
URL: bertEmbeddingsURL,
URL: "https://raw.githubusercontent.com/go-skynet/model-gallery/main/bert-embeddings.yaml",
Name: "bert",
Overrides: map[string]interface{}{},
})
@@ -467,7 +471,7 @@ var _ = Describe("API test", func() {
content := map[string]interface{}{}
err = yaml.Unmarshal(dat, &content)
Expect(err).ToNot(HaveOccurred())
Expect(content["usage"]).To(ContainSubstring("You can test this model with curl like this"))
Expect(content["backend"]).To(Equal("bert-embeddings"))
})
It("runs openllama(llama-ggml backend)", Label("llama"), func() {
@@ -535,7 +539,7 @@ var _ = Describe("API test", func() {
var res map[string]string
err = json.Unmarshal([]byte(resp2.Choices[0].Message.FunctionCall.Arguments), &res)
Expect(err).ToNot(HaveOccurred())
Expect(res["location"]).To(ContainSubstring("San Francisco"), fmt.Sprint(res))
Expect(res["location"]).To(Equal("San Francisco"), fmt.Sprint(res))
Expect(res["unit"]).To(Equal("celcius"), fmt.Sprint(res))
Expect(string(resp2.Choices[0].FinishReason)).To(Equal("function_call"), fmt.Sprint(resp2.Choices[0].FinishReason))
@@ -637,7 +641,7 @@ var _ = Describe("API test", func() {
},
}
application, err := application.New(
bcl, ml, applicationConfig, err = startup.Startup(
append(commonOpts,
config.WithContext(c),
config.WithAudioDir(tmpdir),
@@ -648,7 +652,7 @@ var _ = Describe("API test", func() {
config.WithBackendAssetsOutput(tmpdir))...,
)
Expect(err).ToNot(HaveOccurred())
app, err = API(application)
app, err = App(bcl, ml, applicationConfig)
Expect(err).ToNot(HaveOccurred())
go app.Listen("127.0.0.1:9090")
@@ -768,14 +772,14 @@ var _ = Describe("API test", func() {
var err error
application, err := application.New(
bcl, ml, applicationConfig, err = startup.Startup(
append(commonOpts,
config.WithExternalBackend("huggingface", os.Getenv("HUGGINGFACE_GRPC")),
config.WithContext(c),
config.WithModelPath(modelPath),
)...)
Expect(err).ToNot(HaveOccurred())
app, err = API(application)
app, err = App(bcl, ml, applicationConfig)
Expect(err).ToNot(HaveOccurred())
go app.Listen("127.0.0.1:9090")
@@ -802,7 +806,7 @@ var _ = Describe("API test", func() {
It("returns the models list", func() {
models, err := client.ListModels(context.TODO())
Expect(err).ToNot(HaveOccurred())
Expect(len(models.Models)).To(Equal(7)) // If "config.yaml" should be included, this should be 8?
Expect(len(models.Models)).To(Equal(6)) // If "config.yaml" should be included, this should be 8?
})
It("can generate completions via ggml", func() {
resp, err := client.CreateCompletion(context.TODO(), openai.CompletionRequest{Model: "testmodel.ggml", Prompt: testPrompt})
@@ -862,8 +866,8 @@ var _ = Describe("API test", func() {
},
)
Expect(err).ToNot(HaveOccurred(), err)
Expect(len(resp.Data[0].Embedding)).To(BeNumerically("==", 2048))
Expect(len(resp.Data[1].Embedding)).To(BeNumerically("==", 2048))
Expect(len(resp.Data[0].Embedding)).To(BeNumerically("==", 384))
Expect(len(resp.Data[1].Embedding)).To(BeNumerically("==", 384))
sunEmbedding := resp.Data[0].Embedding
resp2, err := client.CreateEmbeddings(
@@ -907,6 +911,71 @@ var _ = Describe("API test", func() {
})
})
Context("backends", func() {
It("runs rwkv completion", func() {
if runtime.GOOS != "linux" {
Skip("test supported only on linux")
}
resp, err := client.CreateCompletion(context.TODO(), openai.CompletionRequest{Model: "rwkv_test", Prompt: "Count up to five: one, two, three, four,"})
Expect(err).ToNot(HaveOccurred())
Expect(len(resp.Choices) > 0).To(BeTrue())
Expect(resp.Choices[0].Text).To(ContainSubstring("five"))
stream, err := client.CreateCompletionStream(context.TODO(), openai.CompletionRequest{
Model: "rwkv_test", Prompt: "Count up to five: one, two, three, four,", Stream: true,
})
Expect(err).ToNot(HaveOccurred())
defer stream.Close()
tokens := 0
text := ""
for {
response, err := stream.Recv()
if errors.Is(err, io.EOF) {
break
}
Expect(err).ToNot(HaveOccurred())
text += response.Choices[0].Text
tokens++
}
Expect(text).ToNot(BeEmpty())
Expect(text).To(ContainSubstring("five"))
Expect(tokens).ToNot(Or(Equal(1), Equal(0)))
})
It("runs rwkv chat completion", func() {
if runtime.GOOS != "linux" {
Skip("test supported only on linux")
}
resp, err := client.CreateChatCompletion(context.TODO(),
openai.ChatCompletionRequest{Model: "rwkv_test", Messages: []openai.ChatCompletionMessage{{Content: "Can you count up to five?", Role: "user"}}})
Expect(err).ToNot(HaveOccurred())
Expect(len(resp.Choices) > 0).To(BeTrue())
Expect(strings.ToLower(resp.Choices[0].Message.Content)).To(Or(ContainSubstring("sure"), ContainSubstring("five")))
stream, err := client.CreateChatCompletionStream(context.TODO(), openai.ChatCompletionRequest{Model: "rwkv_test", Messages: []openai.ChatCompletionMessage{{Content: "Can you count up to five?", Role: "user"}}})
Expect(err).ToNot(HaveOccurred())
defer stream.Close()
tokens := 0
text := ""
for {
response, err := stream.Recv()
if errors.Is(err, io.EOF) {
break
}
Expect(err).ToNot(HaveOccurred())
text += response.Choices[0].Delta.Content
tokens++
}
Expect(text).ToNot(BeEmpty())
Expect(strings.ToLower(text)).To(Or(ContainSubstring("sure"), ContainSubstring("five")))
Expect(tokens).ToNot(Or(Equal(1), Equal(0)))
})
})
// See tests/integration/stores_test
Context("Stores", Label("stores"), func() {
@@ -986,14 +1055,14 @@ var _ = Describe("API test", func() {
c, cancel = context.WithCancel(context.Background())
var err error
application, err := application.New(
bcl, ml, applicationConfig, err = startup.Startup(
append(commonOpts,
config.WithContext(c),
config.WithModelPath(modelPath),
config.WithConfigFile(os.Getenv("CONFIG_FILE")))...,
)
Expect(err).ToNot(HaveOccurred())
app, err = API(application)
app, err = App(bcl, ml, applicationConfig)
Expect(err).ToNot(HaveOccurred())
go app.Listen("127.0.0.1:9090")

View File

@@ -14,8 +14,6 @@ import (
"github.com/mudler/LocalAI/core/config"
"github.com/mudler/LocalAI/core/schema"
"github.com/mudler/LocalAI/pkg/functions"
"github.com/mudler/LocalAI/pkg/templates"
model "github.com/mudler/LocalAI/pkg/model"
"github.com/rs/zerolog/log"
"github.com/valyala/fasthttp"
@@ -26,7 +24,7 @@ import (
// @Param request body schema.OpenAIRequest true "query params"
// @Success 200 {object} schema.OpenAIResponse "Response"
// @Router /v1/chat/completions [post]
func ChatEndpoint(cl *config.BackendConfigLoader, ml *model.ModelLoader, evaluator *templates.Evaluator, startupOptions *config.ApplicationConfig) func(c *fiber.Ctx) error {
func ChatEndpoint(cl *config.BackendConfigLoader, ml *model.ModelLoader, startupOptions *config.ApplicationConfig) func(c *fiber.Ctx) error {
var id, textContentToReturn string
var created int
@@ -296,10 +294,148 @@ func ChatEndpoint(cl *config.BackendConfigLoader, ml *model.ModelLoader, evaluat
// If we are using the tokenizer template, we don't need to process the messages
// unless we are processing functions
if !config.TemplateConfig.UseTokenizerTemplate || shouldUseFn {
predInput = evaluator.TemplateMessages(input.Messages, config, funcs, shouldUseFn)
suppressConfigSystemPrompt := false
mess := []string{}
for messageIndex, i := range input.Messages {
var content string
role := i.Role
// if function call, we might want to customize the role so we can display better that the "assistant called a json action"
// if an "assistant_function_call" role is defined, we use it, otherwise we use the role that is passed by in the request
if (i.FunctionCall != nil || i.ToolCalls != nil) && i.Role == "assistant" {
roleFn := "assistant_function_call"
r := config.Roles[roleFn]
if r != "" {
role = roleFn
}
}
r := config.Roles[role]
contentExists := i.Content != nil && i.StringContent != ""
fcall := i.FunctionCall
if len(i.ToolCalls) > 0 {
fcall = i.ToolCalls
}
// First attempt to populate content via a chat message specific template
if config.TemplateConfig.ChatMessage != "" {
chatMessageData := model.ChatMessageTemplateData{
SystemPrompt: config.SystemPrompt,
Role: r,
RoleName: role,
Content: i.StringContent,
FunctionCall: fcall,
FunctionName: i.Name,
LastMessage: messageIndex == (len(input.Messages) - 1),
Function: config.Grammar != "" && (messageIndex == (len(input.Messages) - 1)),
MessageIndex: messageIndex,
}
templatedChatMessage, err := ml.EvaluateTemplateForChatMessage(config.TemplateConfig.ChatMessage, chatMessageData)
if err != nil {
log.Error().Err(err).Interface("message", chatMessageData).Str("template", config.TemplateConfig.ChatMessage).Msg("error processing message with template, skipping")
} else {
if templatedChatMessage == "" {
log.Warn().Msgf("template \"%s\" produced blank output for %+v. Skipping!", config.TemplateConfig.ChatMessage, chatMessageData)
continue // TODO: This continue is here intentionally to skip over the line `mess = append(mess, content)` below, and to prevent the sprintf
}
log.Debug().Msgf("templated message for chat: %s", templatedChatMessage)
content = templatedChatMessage
}
}
marshalAnyRole := func(f any) {
j, err := json.Marshal(f)
if err == nil {
if contentExists {
content += "\n" + fmt.Sprint(r, " ", string(j))
} else {
content = fmt.Sprint(r, " ", string(j))
}
}
}
marshalAny := func(f any) {
j, err := json.Marshal(f)
if err == nil {
if contentExists {
content += "\n" + string(j)
} else {
content = string(j)
}
}
}
// If this model doesn't have such a template, or if that template fails to return a value, template at the message level.
if content == "" {
if r != "" {
if contentExists {
content = fmt.Sprint(r, i.StringContent)
}
if i.FunctionCall != nil {
marshalAnyRole(i.FunctionCall)
}
if i.ToolCalls != nil {
marshalAnyRole(i.ToolCalls)
}
} else {
if contentExists {
content = fmt.Sprint(i.StringContent)
}
if i.FunctionCall != nil {
marshalAny(i.FunctionCall)
}
if i.ToolCalls != nil {
marshalAny(i.ToolCalls)
}
}
// Special Handling: System. We care if it was printed at all, not the r branch, so check seperately
if contentExists && role == "system" {
suppressConfigSystemPrompt = true
}
}
mess = append(mess, content)
}
joinCharacter := "\n"
if config.TemplateConfig.JoinChatMessagesByCharacter != nil {
joinCharacter = *config.TemplateConfig.JoinChatMessagesByCharacter
}
predInput = strings.Join(mess, joinCharacter)
log.Debug().Msgf("Prompt (before templating): %s", predInput)
templateFile := ""
// A model can have a "file.bin.tmpl" file associated with a prompt template prefix
if ml.ExistsInModelPath(fmt.Sprintf("%s.tmpl", config.Model)) {
templateFile = config.Model
}
if config.TemplateConfig.Chat != "" && !shouldUseFn {
templateFile = config.TemplateConfig.Chat
}
if config.TemplateConfig.Functions != "" && shouldUseFn {
templateFile = config.TemplateConfig.Functions
}
if templateFile != "" {
templatedInput, err := ml.EvaluateTemplateForPrompt(model.ChatPromptTemplate, templateFile, model.PromptTemplateData{
SystemPrompt: config.SystemPrompt,
SuppressSystemPrompt: suppressConfigSystemPrompt,
Input: predInput,
Functions: funcs,
})
if err == nil {
predInput = templatedInput
log.Debug().Msgf("Template found, input modified to: %s", predInput)
} else {
log.Debug().Msgf("Template failed loading: %s", err.Error())
}
}
log.Debug().Msgf("Prompt (after templating): %s", predInput)
if config.Grammar != "" {
if shouldUseFn && config.Grammar != "" {
log.Debug().Msgf("Grammar: %+v", config.Grammar)
}
}

View File

@@ -16,7 +16,6 @@ import (
"github.com/mudler/LocalAI/core/schema"
"github.com/mudler/LocalAI/pkg/functions"
model "github.com/mudler/LocalAI/pkg/model"
"github.com/mudler/LocalAI/pkg/templates"
"github.com/rs/zerolog/log"
"github.com/valyala/fasthttp"
)
@@ -26,7 +25,7 @@ import (
// @Param request body schema.OpenAIRequest true "query params"
// @Success 200 {object} schema.OpenAIResponse "Response"
// @Router /v1/completions [post]
func CompletionEndpoint(cl *config.BackendConfigLoader, ml *model.ModelLoader, evaluator *templates.Evaluator, appConfig *config.ApplicationConfig) func(c *fiber.Ctx) error {
func CompletionEndpoint(cl *config.BackendConfigLoader, ml *model.ModelLoader, appConfig *config.ApplicationConfig) func(c *fiber.Ctx) error {
id := uuid.New().String()
created := int(time.Now().Unix())
@@ -95,6 +94,17 @@ func CompletionEndpoint(cl *config.BackendConfigLoader, ml *model.ModelLoader, e
c.Set("Transfer-Encoding", "chunked")
}
templateFile := ""
// A model can have a "file.bin.tmpl" file associated with a prompt template prefix
if ml.ExistsInModelPath(fmt.Sprintf("%s.tmpl", config.Model)) {
templateFile = config.Model
}
if config.TemplateConfig.Completion != "" {
templateFile = config.TemplateConfig.Completion
}
if input.Stream {
if len(config.PromptStrings) > 1 {
return errors.New("cannot handle more than 1 `PromptStrings` when Streaming")
@@ -102,13 +112,15 @@ func CompletionEndpoint(cl *config.BackendConfigLoader, ml *model.ModelLoader, e
predInput := config.PromptStrings[0]
templatedInput, err := evaluator.EvaluateTemplateForPrompt(templates.CompletionPromptTemplate, *config, templates.PromptTemplateData{
Input: predInput,
SystemPrompt: config.SystemPrompt,
})
if err == nil {
predInput = templatedInput
log.Debug().Msgf("Template found, input modified to: %s", predInput)
if templateFile != "" {
templatedInput, err := ml.EvaluateTemplateForPrompt(model.CompletionPromptTemplate, templateFile, model.PromptTemplateData{
Input: predInput,
SystemPrompt: config.SystemPrompt,
})
if err == nil {
predInput = templatedInput
log.Debug().Msgf("Template found, input modified to: %s", predInput)
}
}
responses := make(chan schema.OpenAIResponse)
@@ -153,13 +165,16 @@ func CompletionEndpoint(cl *config.BackendConfigLoader, ml *model.ModelLoader, e
totalTokenUsage := backend.TokenUsage{}
for k, i := range config.PromptStrings {
templatedInput, err := evaluator.EvaluateTemplateForPrompt(templates.CompletionPromptTemplate, *config, templates.PromptTemplateData{
SystemPrompt: config.SystemPrompt,
Input: i,
})
if err == nil {
i = templatedInput
log.Debug().Msgf("Template found, input modified to: %s", i)
if templateFile != "" {
// A model can have a "file.bin.tmpl" file associated with a prompt template prefix
templatedInput, err := ml.EvaluateTemplateForPrompt(model.CompletionPromptTemplate, templateFile, model.PromptTemplateData{
SystemPrompt: config.SystemPrompt,
Input: i,
})
if err == nil {
i = templatedInput
log.Debug().Msgf("Template found, input modified to: %s", i)
}
}
r, tokenUsage, err := ComputeChoices(

View File

@@ -12,7 +12,6 @@ import (
"github.com/google/uuid"
"github.com/mudler/LocalAI/core/schema"
model "github.com/mudler/LocalAI/pkg/model"
"github.com/mudler/LocalAI/pkg/templates"
"github.com/rs/zerolog/log"
)
@@ -22,8 +21,7 @@ import (
// @Param request body schema.OpenAIRequest true "query params"
// @Success 200 {object} schema.OpenAIResponse "Response"
// @Router /v1/edits [post]
func EditEndpoint(cl *config.BackendConfigLoader, ml *model.ModelLoader, evaluator *templates.Evaluator, appConfig *config.ApplicationConfig) func(c *fiber.Ctx) error {
func EditEndpoint(cl *config.BackendConfigLoader, ml *model.ModelLoader, appConfig *config.ApplicationConfig) func(c *fiber.Ctx) error {
return func(c *fiber.Ctx) error {
modelFile, input, err := readRequest(c, cl, ml, appConfig, true)
if err != nil {
@@ -37,18 +35,31 @@ func EditEndpoint(cl *config.BackendConfigLoader, ml *model.ModelLoader, evaluat
log.Debug().Msgf("Parameter Config: %+v", config)
templateFile := ""
// A model can have a "file.bin.tmpl" file associated with a prompt template prefix
if ml.ExistsInModelPath(fmt.Sprintf("%s.tmpl", config.Model)) {
templateFile = config.Model
}
if config.TemplateConfig.Edit != "" {
templateFile = config.TemplateConfig.Edit
}
var result []schema.Choice
totalTokenUsage := backend.TokenUsage{}
for _, i := range config.InputStrings {
templatedInput, err := evaluator.EvaluateTemplateForPrompt(templates.EditPromptTemplate, *config, templates.PromptTemplateData{
Input: i,
Instruction: input.Instruction,
SystemPrompt: config.SystemPrompt,
})
if err == nil {
i = templatedInput
log.Debug().Msgf("Template found, input modified to: %s", i)
if templateFile != "" {
templatedInput, err := ml.EvaluateTemplateForPrompt(model.EditPromptTemplate, templateFile, model.PromptTemplateData{
Input: i,
Instruction: input.Instruction,
SystemPrompt: config.SystemPrompt,
})
if err == nil {
i = templatedInput
log.Debug().Msgf("Template found, input modified to: %s", i)
}
}
r, tokenUsage, err := ComputeChoices(input, i, config, appConfig, ml, func(s string, c *[]schema.Choice) {

View File

@@ -11,62 +11,62 @@ import (
"github.com/mudler/LocalAI/pkg/model"
)
func RegisterLocalAIRoutes(router *fiber.App,
func RegisterLocalAIRoutes(app *fiber.App,
cl *config.BackendConfigLoader,
ml *model.ModelLoader,
appConfig *config.ApplicationConfig,
galleryService *services.GalleryService) {
router.Get("/swagger/*", swagger.HandlerDefault) // default
app.Get("/swagger/*", swagger.HandlerDefault) // default
// LocalAI API endpoints
if !appConfig.DisableGalleryEndpoint {
modelGalleryEndpointService := localai.CreateModelGalleryEndpointService(appConfig.Galleries, appConfig.ModelPath, galleryService)
router.Post("/models/apply", modelGalleryEndpointService.ApplyModelGalleryEndpoint())
router.Post("/models/delete/:name", modelGalleryEndpointService.DeleteModelGalleryEndpoint())
app.Post("/models/apply", modelGalleryEndpointService.ApplyModelGalleryEndpoint())
app.Post("/models/delete/:name", modelGalleryEndpointService.DeleteModelGalleryEndpoint())
router.Get("/models/available", modelGalleryEndpointService.ListModelFromGalleryEndpoint())
router.Get("/models/galleries", modelGalleryEndpointService.ListModelGalleriesEndpoint())
router.Post("/models/galleries", modelGalleryEndpointService.AddModelGalleryEndpoint())
router.Delete("/models/galleries", modelGalleryEndpointService.RemoveModelGalleryEndpoint())
router.Get("/models/jobs/:uuid", modelGalleryEndpointService.GetOpStatusEndpoint())
router.Get("/models/jobs", modelGalleryEndpointService.GetAllStatusEndpoint())
app.Get("/models/available", modelGalleryEndpointService.ListModelFromGalleryEndpoint())
app.Get("/models/galleries", modelGalleryEndpointService.ListModelGalleriesEndpoint())
app.Post("/models/galleries", modelGalleryEndpointService.AddModelGalleryEndpoint())
app.Delete("/models/galleries", modelGalleryEndpointService.RemoveModelGalleryEndpoint())
app.Get("/models/jobs/:uuid", modelGalleryEndpointService.GetOpStatusEndpoint())
app.Get("/models/jobs", modelGalleryEndpointService.GetAllStatusEndpoint())
}
router.Post("/tts", localai.TTSEndpoint(cl, ml, appConfig))
router.Post("/vad", localai.VADEndpoint(cl, ml, appConfig))
app.Post("/tts", localai.TTSEndpoint(cl, ml, appConfig))
app.Post("/vad", localai.VADEndpoint(cl, ml, appConfig))
// Stores
sl := model.NewModelLoader("")
router.Post("/stores/set", localai.StoresSetEndpoint(sl, appConfig))
router.Post("/stores/delete", localai.StoresDeleteEndpoint(sl, appConfig))
router.Post("/stores/get", localai.StoresGetEndpoint(sl, appConfig))
router.Post("/stores/find", localai.StoresFindEndpoint(sl, appConfig))
app.Post("/stores/set", localai.StoresSetEndpoint(sl, appConfig))
app.Post("/stores/delete", localai.StoresDeleteEndpoint(sl, appConfig))
app.Post("/stores/get", localai.StoresGetEndpoint(sl, appConfig))
app.Post("/stores/find", localai.StoresFindEndpoint(sl, appConfig))
if !appConfig.DisableMetrics {
router.Get("/metrics", localai.LocalAIMetricsEndpoint())
app.Get("/metrics", localai.LocalAIMetricsEndpoint())
}
// Experimental Backend Statistics Module
backendMonitorService := services.NewBackendMonitorService(ml, cl, appConfig) // Split out for now
router.Get("/backend/monitor", localai.BackendMonitorEndpoint(backendMonitorService))
router.Post("/backend/shutdown", localai.BackendShutdownEndpoint(backendMonitorService))
app.Get("/backend/monitor", localai.BackendMonitorEndpoint(backendMonitorService))
app.Post("/backend/shutdown", localai.BackendShutdownEndpoint(backendMonitorService))
// p2p
if p2p.IsP2PEnabled() {
router.Get("/api/p2p", localai.ShowP2PNodes(appConfig))
router.Get("/api/p2p/token", localai.ShowP2PToken(appConfig))
app.Get("/api/p2p", localai.ShowP2PNodes(appConfig))
app.Get("/api/p2p/token", localai.ShowP2PToken(appConfig))
}
router.Get("/version", func(c *fiber.Ctx) error {
app.Get("/version", func(c *fiber.Ctx) error {
return c.JSON(struct {
Version string `json:"version"`
}{Version: internal.PrintableVersion()})
})
router.Get("/system", localai.SystemInformations(ml, appConfig))
app.Get("/system", localai.SystemInformations(ml, appConfig))
// misc
router.Post("/v1/tokenize", localai.TokenizeEndpoint(cl, ml, appConfig))
app.Post("/v1/tokenize", localai.TokenizeEndpoint(cl, ml, appConfig))
}

View File

@@ -2,134 +2,84 @@ package routes
import (
"github.com/gofiber/fiber/v2"
"github.com/mudler/LocalAI/core/application"
"github.com/mudler/LocalAI/core/config"
"github.com/mudler/LocalAI/core/http/endpoints/localai"
"github.com/mudler/LocalAI/core/http/endpoints/openai"
"github.com/mudler/LocalAI/pkg/model"
)
func RegisterOpenAIRoutes(app *fiber.App,
application *application.Application) {
cl *config.BackendConfigLoader,
ml *model.ModelLoader,
appConfig *config.ApplicationConfig) {
// openAI compatible API endpoint
// chat
app.Post("/v1/chat/completions",
openai.ChatEndpoint(
application.BackendLoader(),
application.ModelLoader(),
application.TemplatesEvaluator(),
application.ApplicationConfig(),
),
)
app.Post("/chat/completions",
openai.ChatEndpoint(
application.BackendLoader(),
application.ModelLoader(),
application.TemplatesEvaluator(),
application.ApplicationConfig(),
),
)
app.Post("/v1/chat/completions", openai.ChatEndpoint(cl, ml, appConfig))
app.Post("/chat/completions", openai.ChatEndpoint(cl, ml, appConfig))
// edit
app.Post("/v1/edits",
openai.EditEndpoint(
application.BackendLoader(),
application.ModelLoader(),
application.TemplatesEvaluator(),
application.ApplicationConfig(),
),
)
app.Post("/edits",
openai.EditEndpoint(
application.BackendLoader(),
application.ModelLoader(),
application.TemplatesEvaluator(),
application.ApplicationConfig(),
),
)
app.Post("/v1/edits", openai.EditEndpoint(cl, ml, appConfig))
app.Post("/edits", openai.EditEndpoint(cl, ml, appConfig))
// assistant
app.Get("/v1/assistants", openai.ListAssistantsEndpoint(application.BackendLoader(), application.ModelLoader(), application.ApplicationConfig()))
app.Get("/assistants", openai.ListAssistantsEndpoint(application.BackendLoader(), application.ModelLoader(), application.ApplicationConfig()))
app.Post("/v1/assistants", openai.CreateAssistantEndpoint(application.BackendLoader(), application.ModelLoader(), application.ApplicationConfig()))
app.Post("/assistants", openai.CreateAssistantEndpoint(application.BackendLoader(), application.ModelLoader(), application.ApplicationConfig()))
app.Delete("/v1/assistants/:assistant_id", openai.DeleteAssistantEndpoint(application.BackendLoader(), application.ModelLoader(), application.ApplicationConfig()))
app.Delete("/assistants/:assistant_id", openai.DeleteAssistantEndpoint(application.BackendLoader(), application.ModelLoader(), application.ApplicationConfig()))
app.Get("/v1/assistants/:assistant_id", openai.GetAssistantEndpoint(application.BackendLoader(), application.ModelLoader(), application.ApplicationConfig()))
app.Get("/assistants/:assistant_id", openai.GetAssistantEndpoint(application.BackendLoader(), application.ModelLoader(), application.ApplicationConfig()))
app.Post("/v1/assistants/:assistant_id", openai.ModifyAssistantEndpoint(application.BackendLoader(), application.ModelLoader(), application.ApplicationConfig()))
app.Post("/assistants/:assistant_id", openai.ModifyAssistantEndpoint(application.BackendLoader(), application.ModelLoader(), application.ApplicationConfig()))
app.Get("/v1/assistants/:assistant_id/files", openai.ListAssistantFilesEndpoint(application.BackendLoader(), application.ModelLoader(), application.ApplicationConfig()))
app.Get("/assistants/:assistant_id/files", openai.ListAssistantFilesEndpoint(application.BackendLoader(), application.ModelLoader(), application.ApplicationConfig()))
app.Post("/v1/assistants/:assistant_id/files", openai.CreateAssistantFileEndpoint(application.BackendLoader(), application.ModelLoader(), application.ApplicationConfig()))
app.Post("/assistants/:assistant_id/files", openai.CreateAssistantFileEndpoint(application.BackendLoader(), application.ModelLoader(), application.ApplicationConfig()))
app.Delete("/v1/assistants/:assistant_id/files/:file_id", openai.DeleteAssistantFileEndpoint(application.BackendLoader(), application.ModelLoader(), application.ApplicationConfig()))
app.Delete("/assistants/:assistant_id/files/:file_id", openai.DeleteAssistantFileEndpoint(application.BackendLoader(), application.ModelLoader(), application.ApplicationConfig()))
app.Get("/v1/assistants/:assistant_id/files/:file_id", openai.GetAssistantFileEndpoint(application.BackendLoader(), application.ModelLoader(), application.ApplicationConfig()))
app.Get("/assistants/:assistant_id/files/:file_id", openai.GetAssistantFileEndpoint(application.BackendLoader(), application.ModelLoader(), application.ApplicationConfig()))
app.Get("/v1/assistants", openai.ListAssistantsEndpoint(cl, ml, appConfig))
app.Get("/assistants", openai.ListAssistantsEndpoint(cl, ml, appConfig))
app.Post("/v1/assistants", openai.CreateAssistantEndpoint(cl, ml, appConfig))
app.Post("/assistants", openai.CreateAssistantEndpoint(cl, ml, appConfig))
app.Delete("/v1/assistants/:assistant_id", openai.DeleteAssistantEndpoint(cl, ml, appConfig))
app.Delete("/assistants/:assistant_id", openai.DeleteAssistantEndpoint(cl, ml, appConfig))
app.Get("/v1/assistants/:assistant_id", openai.GetAssistantEndpoint(cl, ml, appConfig))
app.Get("/assistants/:assistant_id", openai.GetAssistantEndpoint(cl, ml, appConfig))
app.Post("/v1/assistants/:assistant_id", openai.ModifyAssistantEndpoint(cl, ml, appConfig))
app.Post("/assistants/:assistant_id", openai.ModifyAssistantEndpoint(cl, ml, appConfig))
app.Get("/v1/assistants/:assistant_id/files", openai.ListAssistantFilesEndpoint(cl, ml, appConfig))
app.Get("/assistants/:assistant_id/files", openai.ListAssistantFilesEndpoint(cl, ml, appConfig))
app.Post("/v1/assistants/:assistant_id/files", openai.CreateAssistantFileEndpoint(cl, ml, appConfig))
app.Post("/assistants/:assistant_id/files", openai.CreateAssistantFileEndpoint(cl, ml, appConfig))
app.Delete("/v1/assistants/:assistant_id/files/:file_id", openai.DeleteAssistantFileEndpoint(cl, ml, appConfig))
app.Delete("/assistants/:assistant_id/files/:file_id", openai.DeleteAssistantFileEndpoint(cl, ml, appConfig))
app.Get("/v1/assistants/:assistant_id/files/:file_id", openai.GetAssistantFileEndpoint(cl, ml, appConfig))
app.Get("/assistants/:assistant_id/files/:file_id", openai.GetAssistantFileEndpoint(cl, ml, appConfig))
// files
app.Post("/v1/files", openai.UploadFilesEndpoint(application.BackendLoader(), application.ApplicationConfig()))
app.Post("/files", openai.UploadFilesEndpoint(application.BackendLoader(), application.ApplicationConfig()))
app.Get("/v1/files", openai.ListFilesEndpoint(application.BackendLoader(), application.ApplicationConfig()))
app.Get("/files", openai.ListFilesEndpoint(application.BackendLoader(), application.ApplicationConfig()))
app.Get("/v1/files/:file_id", openai.GetFilesEndpoint(application.BackendLoader(), application.ApplicationConfig()))
app.Get("/files/:file_id", openai.GetFilesEndpoint(application.BackendLoader(), application.ApplicationConfig()))
app.Delete("/v1/files/:file_id", openai.DeleteFilesEndpoint(application.BackendLoader(), application.ApplicationConfig()))
app.Delete("/files/:file_id", openai.DeleteFilesEndpoint(application.BackendLoader(), application.ApplicationConfig()))
app.Get("/v1/files/:file_id/content", openai.GetFilesContentsEndpoint(application.BackendLoader(), application.ApplicationConfig()))
app.Get("/files/:file_id/content", openai.GetFilesContentsEndpoint(application.BackendLoader(), application.ApplicationConfig()))
app.Post("/v1/files", openai.UploadFilesEndpoint(cl, appConfig))
app.Post("/files", openai.UploadFilesEndpoint(cl, appConfig))
app.Get("/v1/files", openai.ListFilesEndpoint(cl, appConfig))
app.Get("/files", openai.ListFilesEndpoint(cl, appConfig))
app.Get("/v1/files/:file_id", openai.GetFilesEndpoint(cl, appConfig))
app.Get("/files/:file_id", openai.GetFilesEndpoint(cl, appConfig))
app.Delete("/v1/files/:file_id", openai.DeleteFilesEndpoint(cl, appConfig))
app.Delete("/files/:file_id", openai.DeleteFilesEndpoint(cl, appConfig))
app.Get("/v1/files/:file_id/content", openai.GetFilesContentsEndpoint(cl, appConfig))
app.Get("/files/:file_id/content", openai.GetFilesContentsEndpoint(cl, appConfig))
// completion
app.Post("/v1/completions",
openai.CompletionEndpoint(
application.BackendLoader(),
application.ModelLoader(),
application.TemplatesEvaluator(),
application.ApplicationConfig(),
),
)
app.Post("/completions",
openai.CompletionEndpoint(
application.BackendLoader(),
application.ModelLoader(),
application.TemplatesEvaluator(),
application.ApplicationConfig(),
),
)
app.Post("/v1/engines/:model/completions",
openai.CompletionEndpoint(
application.BackendLoader(),
application.ModelLoader(),
application.TemplatesEvaluator(),
application.ApplicationConfig(),
),
)
app.Post("/v1/completions", openai.CompletionEndpoint(cl, ml, appConfig))
app.Post("/completions", openai.CompletionEndpoint(cl, ml, appConfig))
app.Post("/v1/engines/:model/completions", openai.CompletionEndpoint(cl, ml, appConfig))
// embeddings
app.Post("/v1/embeddings", openai.EmbeddingsEndpoint(application.BackendLoader(), application.ModelLoader(), application.ApplicationConfig()))
app.Post("/embeddings", openai.EmbeddingsEndpoint(application.BackendLoader(), application.ModelLoader(), application.ApplicationConfig()))
app.Post("/v1/engines/:model/embeddings", openai.EmbeddingsEndpoint(application.BackendLoader(), application.ModelLoader(), application.ApplicationConfig()))
app.Post("/v1/embeddings", openai.EmbeddingsEndpoint(cl, ml, appConfig))
app.Post("/embeddings", openai.EmbeddingsEndpoint(cl, ml, appConfig))
app.Post("/v1/engines/:model/embeddings", openai.EmbeddingsEndpoint(cl, ml, appConfig))
// audio
app.Post("/v1/audio/transcriptions", openai.TranscriptEndpoint(application.BackendLoader(), application.ModelLoader(), application.ApplicationConfig()))
app.Post("/v1/audio/speech", localai.TTSEndpoint(application.BackendLoader(), application.ModelLoader(), application.ApplicationConfig()))
app.Post("/v1/audio/transcriptions", openai.TranscriptEndpoint(cl, ml, appConfig))
app.Post("/v1/audio/speech", localai.TTSEndpoint(cl, ml, appConfig))
// images
app.Post("/v1/images/generations", openai.ImageEndpoint(application.BackendLoader(), application.ModelLoader(), application.ApplicationConfig()))
app.Post("/v1/images/generations", openai.ImageEndpoint(cl, ml, appConfig))
if application.ApplicationConfig().ImageDir != "" {
app.Static("/generated-images", application.ApplicationConfig().ImageDir)
if appConfig.ImageDir != "" {
app.Static("/generated-images", appConfig.ImageDir)
}
if application.ApplicationConfig().AudioDir != "" {
app.Static("/generated-audio", application.ApplicationConfig().AudioDir)
if appConfig.AudioDir != "" {
app.Static("/generated-audio", appConfig.AudioDir)
}
// List models
app.Get("/v1/models", openai.ListModelsEndpoint(application.BackendLoader(), application.ModelLoader()))
app.Get("/models", openai.ListModelsEndpoint(application.BackendLoader(), application.ModelLoader()))
app.Get("/v1/models", openai.ListModelsEndpoint(cl, ml))
app.Get("/models", openai.ListModelsEndpoint(cl, ml))
}

View File

@@ -1,4 +1,4 @@
package application
package startup
import (
"encoding/json"
@@ -8,8 +8,8 @@ import (
"path/filepath"
"time"
"dario.cat/mergo"
"github.com/fsnotify/fsnotify"
"dario.cat/mergo"
"github.com/mudler/LocalAI/core/config"
"github.com/rs/zerolog/log"
)

View File

@@ -1,15 +1,15 @@
package application
package startup
import (
"fmt"
"os"
"github.com/mudler/LocalAI/core"
"github.com/mudler/LocalAI/core/backend"
"github.com/mudler/LocalAI/core/config"
"github.com/mudler/LocalAI/core/services"
"github.com/mudler/LocalAI/internal"
"github.com/mudler/LocalAI/pkg/assets"
"github.com/mudler/LocalAI/pkg/library"
"github.com/mudler/LocalAI/pkg/model"
pkgStartup "github.com/mudler/LocalAI/pkg/startup"
@@ -17,9 +17,8 @@ import (
"github.com/rs/zerolog/log"
)
func New(opts ...config.AppOption) (*Application, error) {
func Startup(opts ...config.AppOption) (*config.BackendConfigLoader, *model.ModelLoader, *config.ApplicationConfig, error) {
options := config.NewApplicationConfig(opts...)
application := newApplication(options)
log.Info().Msgf("Starting LocalAI using %d threads, with models path: %s", options.Threads, options.ModelPath)
log.Info().Msgf("LocalAI version: %s", internal.PrintableVersion())
@@ -37,28 +36,28 @@ func New(opts ...config.AppOption) (*Application, error) {
// Make sure directories exists
if options.ModelPath == "" {
return nil, fmt.Errorf("options.ModelPath cannot be empty")
return nil, nil, nil, fmt.Errorf("options.ModelPath cannot be empty")
}
err = os.MkdirAll(options.ModelPath, 0750)
if err != nil {
return nil, fmt.Errorf("unable to create ModelPath: %q", err)
return nil, nil, nil, fmt.Errorf("unable to create ModelPath: %q", err)
}
if options.ImageDir != "" {
err := os.MkdirAll(options.ImageDir, 0750)
if err != nil {
return nil, fmt.Errorf("unable to create ImageDir: %q", err)
return nil, nil, nil, fmt.Errorf("unable to create ImageDir: %q", err)
}
}
if options.AudioDir != "" {
err := os.MkdirAll(options.AudioDir, 0750)
if err != nil {
return nil, fmt.Errorf("unable to create AudioDir: %q", err)
return nil, nil, nil, fmt.Errorf("unable to create AudioDir: %q", err)
}
}
if options.UploadDir != "" {
err := os.MkdirAll(options.UploadDir, 0750)
if err != nil {
return nil, fmt.Errorf("unable to create UploadDir: %q", err)
return nil, nil, nil, fmt.Errorf("unable to create UploadDir: %q", err)
}
}
@@ -66,36 +65,39 @@ func New(opts ...config.AppOption) (*Application, error) {
log.Error().Err(err).Msg("error installing models")
}
cl := config.NewBackendConfigLoader(options.ModelPath)
ml := model.NewModelLoader(options.ModelPath)
configLoaderOpts := options.ToConfigLoaderOptions()
if err := application.BackendLoader().LoadBackendConfigsFromPath(options.ModelPath, configLoaderOpts...); err != nil {
if err := cl.LoadBackendConfigsFromPath(options.ModelPath, configLoaderOpts...); err != nil {
log.Error().Err(err).Msg("error loading config files")
}
if options.ConfigFile != "" {
if err := application.BackendLoader().LoadMultipleBackendConfigsSingleFile(options.ConfigFile, configLoaderOpts...); err != nil {
if err := cl.LoadMultipleBackendConfigsSingleFile(options.ConfigFile, configLoaderOpts...); err != nil {
log.Error().Err(err).Msg("error loading config file")
}
}
if err := application.BackendLoader().Preload(options.ModelPath); err != nil {
if err := cl.Preload(options.ModelPath); err != nil {
log.Error().Err(err).Msg("error downloading models")
}
if options.PreloadJSONModels != "" {
if err := services.ApplyGalleryFromString(options.ModelPath, options.PreloadJSONModels, options.EnforcePredownloadScans, options.Galleries); err != nil {
return nil, err
return nil, nil, nil, err
}
}
if options.PreloadModelsFromPath != "" {
if err := services.ApplyGalleryFromFile(options.ModelPath, options.PreloadModelsFromPath, options.EnforcePredownloadScans, options.Galleries); err != nil {
return nil, err
return nil, nil, nil, err
}
}
if options.Debug {
for _, v := range application.BackendLoader().GetAllBackendConfigs() {
for _, v := range cl.GetAllBackendConfigs() {
log.Debug().Msgf("Model: %s (config: %+v)", v.Name, v)
}
}
@@ -121,7 +123,7 @@ func New(opts ...config.AppOption) (*Application, error) {
go func() {
<-options.Context.Done()
log.Debug().Msgf("Context canceled, shutting down")
err := application.ModelLoader().StopAllGRPC()
err := ml.StopAllGRPC()
if err != nil {
log.Error().Err(err).Msg("error while stopping all grpc backends")
}
@@ -129,12 +131,12 @@ func New(opts ...config.AppOption) (*Application, error) {
if options.WatchDog {
wd := model.NewWatchDog(
application.ModelLoader(),
ml,
options.WatchDogBusyTimeout,
options.WatchDogIdleTimeout,
options.WatchDogBusy,
options.WatchDogIdle)
application.ModelLoader().SetWatchDog(wd)
ml.SetWatchDog(wd)
go wd.Run()
go func() {
<-options.Context.Done()
@@ -145,7 +147,7 @@ func New(opts ...config.AppOption) (*Application, error) {
if options.LoadToMemory != nil {
for _, m := range options.LoadToMemory {
cfg, err := application.BackendLoader().LoadBackendConfigFileByName(m, options.ModelPath,
cfg, err := cl.LoadBackendConfigFileByName(m, options.ModelPath,
config.LoadOptionDebug(options.Debug),
config.LoadOptionThreads(options.Threads),
config.LoadOptionContextSize(options.ContextSize),
@@ -153,7 +155,7 @@ func New(opts ...config.AppOption) (*Application, error) {
config.ModelPath(options.ModelPath),
)
if err != nil {
return nil, err
return nil, nil, nil, err
}
log.Debug().Msgf("Auto loading model %s into memory from file: %s", m, cfg.Model)
@@ -161,9 +163,9 @@ func New(opts ...config.AppOption) (*Application, error) {
o := backend.ModelOptions(*cfg, options)
var backendErr error
_, backendErr = application.ModelLoader().Load(o...)
_, backendErr = ml.Load(o...)
if backendErr != nil {
return nil, err
return nil, nil, nil, err
}
}
}
@@ -172,7 +174,7 @@ func New(opts ...config.AppOption) (*Application, error) {
startWatcher(options)
log.Info().Msg("core/startup process completed!")
return application, nil
return cl, ml, options, nil
}
func startWatcher(options *config.ApplicationConfig) {
@@ -199,3 +201,32 @@ func startWatcher(options *config.ApplicationConfig) {
log.Error().Err(err).Msg("failed creating watcher")
}
}
// In Lieu of a proper DI framework, this function wires up the Application manually.
// This is in core/startup rather than core/state.go to keep package references clean!
func createApplication(appConfig *config.ApplicationConfig) *core.Application {
app := &core.Application{
ApplicationConfig: appConfig,
BackendConfigLoader: config.NewBackendConfigLoader(appConfig.ModelPath),
ModelLoader: model.NewModelLoader(appConfig.ModelPath),
}
var err error
// app.EmbeddingsBackendService = backend.NewEmbeddingsBackendService(app.ModelLoader, app.BackendConfigLoader, app.ApplicationConfig)
// app.ImageGenerationBackendService = backend.NewImageGenerationBackendService(app.ModelLoader, app.BackendConfigLoader, app.ApplicationConfig)
// app.LLMBackendService = backend.NewLLMBackendService(app.ModelLoader, app.BackendConfigLoader, app.ApplicationConfig)
// app.TranscriptionBackendService = backend.NewTranscriptionBackendService(app.ModelLoader, app.BackendConfigLoader, app.ApplicationConfig)
// app.TextToSpeechBackendService = backend.NewTextToSpeechBackendService(app.ModelLoader, app.BackendConfigLoader, app.ApplicationConfig)
app.BackendMonitorService = services.NewBackendMonitorService(app.ModelLoader, app.BackendConfigLoader, app.ApplicationConfig)
app.GalleryService = services.NewGalleryService(app.ApplicationConfig)
// app.OpenAIService = services.NewOpenAIService(app.ModelLoader, app.BackendConfigLoader, app.ApplicationConfig, app.LLMBackendService)
app.LocalAIMetricsService, err = services.NewLocalAIMetricsService()
if err != nil {
log.Error().Err(err).Msg("encountered an error initializing metrics service, startup will continue but metrics will not be tracked.")
}
return app
}

View File

@@ -27,6 +27,39 @@ embeddings: true
# .. other parameters
```
## Bert embeddings
To use `bert.cpp` models you can use the `bert` embedding backend.
An example model config file:
```yaml
name: text-embedding-ada-002
parameters:
model: bert
backend: bert-embeddings
embeddings: true
# .. other parameters
```
The `bert` backend uses [bert.cpp](https://github.com/skeskinen/bert.cpp) and uses `ggml` models.
For instance you can download the `ggml` quantized version of `all-MiniLM-L6-v2` from https://huggingface.co/skeskinen/ggml:
```bash
wget https://huggingface.co/skeskinen/ggml/resolve/main/all-MiniLM-L6-v2/ggml-model-q4_0.bin -O models/bert
```
To test locally (LocalAI server running on `localhost`),
you can use `curl` (and `jq` at the end to prettify):
```bash
curl http://localhost:8080/embeddings -X POST -H "Content-Type: application/json" -d '{
"input": "Your text string goes here",
"model": "text-embedding-ada-002"
}' | jq "."
```
## Huggingface embeddings
To use `sentence-transformers` and models in `huggingface` you can use the `sentencetransformers` embedding backend.
@@ -54,26 +87,17 @@ The `sentencetransformers` backend uses Python [sentence-transformers](https://g
## Llama.cpp embeddings
Embeddings with `llama.cpp` are supported with the `llama-cpp` backend, it needs to be enabled with `embeddings` set to `true`.
Embeddings with `llama.cpp` are supported with the `llama` backend.
```yaml
name: my-awesome-model
backend: llama-cpp
backend: llama
embeddings: true
parameters:
model: ggml-file.bin
# ...
```
Then you can use the API to generate embeddings:
```bash
curl http://localhost:8080/embeddings -X POST -H "Content-Type: application/json" -d '{
"input": "My text",
"model": "my-awesome-model"
}' | jq "."
```
## 💡 Examples
- Example that uses LLamaIndex and LocalAI as embedding: [here](https://github.com/go-skynet/LocalAI/tree/master/examples/query_data/).

View File

@@ -194,9 +194,8 @@ diffusers:
pipeline_type: StableDiffusionPipeline
enable_parameters: "negative_prompt,num_inference_steps,clip_skip"
scheduler_type: "k_dpmpp_sde"
cfg_scale: 8
clip_skip: 11
cfg_scale: 8
```
#### Configuration parameters
@@ -303,8 +302,7 @@ cuda: true
diffusers:
pipeline_type: StableDiffusionDepth2ImgPipeline
enable_parameters: "negative_prompt,num_inference_steps,image"
cfg_scale: 6
cfg_scale: 6
```
```bash

View File

@@ -300,7 +300,7 @@ curl $LOCALAI/models/apply -H "Content-Type: application/json" -d '{
```bash
curl $LOCALAI/models/apply -H "Content-Type: application/json" -d '{
"id": "bert-embeddings",
"url": "github:mudler/LocalAI/gallery/bert-embeddings.yaml",
"name": "text-embedding-ada-002"
}'
```

View File

@@ -10,13 +10,13 @@ ico = "rocket_launch"
For installing LocalAI in Kubernetes, the deployment file from the `examples` can be used and customized as prefered:
```
kubectl apply -f https://raw.githubusercontent.com/mudler/LocalAI-examples/refs/heads/main/kubernetes/deployment.yaml
kubectl apply -f https://raw.githubusercontent.com/mudler/LocalAI/master/examples/kubernetes/deployment.yaml
```
For Nvidia GPUs:
```
kubectl apply -f https://raw.githubusercontent.com/mudler/LocalAI-examples/refs/heads/main/kubernetes/deployment-nvidia.yaml
kubectl apply -f https://raw.githubusercontent.com/mudler/LocalAI/master/examples/kubernetes/deployment-nvidia.yaml
```
Alternatively, the [helm chart](https://github.com/go-skynet/helm-charts) can be used as well:

View File

@@ -6,7 +6,7 @@ weight = 24
url = "/model-compatibility/"
+++
Besides llama based models, LocalAI is compatible also with other architectures. The table below lists all the backends, compatible models families and the associated repository.
Besides llama based models, LocalAI is compatible also with other architectures. The table below lists all the compatible models families and the associated binding repository.
{{% alert note %}}
@@ -16,8 +16,19 @@ LocalAI will attempt to automatically load models which are not explicitly confi
| Backend and Bindings | Compatible models | Completion/Chat endpoint | Capability | Embeddings support | Token stream support | Acceleration |
|----------------------------------------------------------------------------------|-----------------------|--------------------------|---------------------------|-----------------------------------|----------------------|--------------|
| [llama.cpp]({{%relref "docs/features/text-generation#llama.cpp" %}}) | LLama, Mamba, RWKV, Falcon, Starcoder, GPT-2, [and many others](https://github.com/ggerganov/llama.cpp?tab=readme-ov-file#description) | yes | GPT and Functions | yes** | yes | CUDA, openCL, cuBLAS, Metal |
| [llama.cpp's ggml model (backward compatibility with old format, before GGUF)](https://github.com/ggerganov/llama.cpp) ([binding](https://github.com/go-skynet/go-llama.cpp)) | LLama, GPT-2, [and many others](https://github.com/ggerganov/llama.cpp?tab=readme-ov-file#description) | yes | GPT and Functions | yes** | yes | CUDA, openCL, cuBLAS, Metal |
| [llama.cpp]({{%relref "docs/features/text-generation#llama.cpp" %}}) | Vicuna, Alpaca, LLaMa, Falcon, Starcoder, GPT-2, [and many others](https://github.com/ggerganov/llama.cpp?tab=readme-ov-file#description) | yes | GPT and Functions | yes** | yes | CUDA, openCL, cuBLAS, Metal |
| [gpt4all-llama](https://github.com/nomic-ai/gpt4all) | Vicuna, Alpaca, LLaMa | yes | GPT | no | yes | N/A |
| [gpt4all-mpt](https://github.com/nomic-ai/gpt4all) | MPT | yes | GPT | no | yes | N/A |
| [gpt4all-j](https://github.com/nomic-ai/gpt4all) | GPT4ALL-J | yes | GPT | no | yes | N/A |
| [falcon-ggml](https://github.com/ggerganov/ggml) ([binding](https://github.com/go-skynet/go-ggml-transformers.cpp)) | Falcon (*) | yes | GPT | no | no | N/A |
| [dolly](https://github.com/ggerganov/ggml) ([binding](https://github.com/go-skynet/go-ggml-transformers.cpp)) | Dolly | yes | GPT | no | no | N/A |
| [gptj](https://github.com/ggerganov/ggml) ([binding](https://github.com/go-skynet/go-ggml-transformers.cpp)) | GPTJ | yes | GPT | no | no | N/A |
| [mpt](https://github.com/ggerganov/ggml) ([binding](https://github.com/go-skynet/go-ggml-transformers.cpp)) | MPT | yes | GPT | no | no | N/A |
| [replit](https://github.com/ggerganov/ggml) ([binding](https://github.com/go-skynet/go-ggml-transformers.cpp)) | Replit | yes | GPT | no | no | N/A |
| [gptneox](https://github.com/ggerganov/ggml) ([binding](https://github.com/go-skynet/go-ggml-transformers.cpp)) | GPT NeoX, RedPajama, StableLM | yes | GPT | no | no | N/A |
| [bloomz](https://github.com/NouamaneTazi/bloomz.cpp) ([binding](https://github.com/go-skynet/bloomz.cpp)) | Bloom | yes | GPT | no | no | N/A |
| [rwkv](https://github.com/saharNooby/rwkv.cpp) ([binding](https://github.com/donomii/go-rwkv.cpp)) | rwkv | yes | GPT | no | yes | N/A |
| [bert](https://github.com/skeskinen/bert.cpp) ([binding](https://github.com/go-skynet/go-bert.cpp)) | bert | no | Embeddings only | yes | no | N/A |
| [whisper](https://github.com/ggerganov/whisper.cpp) | whisper | no | Audio | no | no | N/A |
| [stablediffusion](https://github.com/EdVince/Stable-Diffusion-NCNN) ([binding](https://github.com/mudler/go-stable-diffusion)) | stablediffusion | no | Image | no | no | N/A |
| [langchain-huggingface](https://github.com/tmc/langchaingo) | Any text generators available on HuggingFace through API | yes | GPT | no | no | N/A |
@@ -29,18 +40,11 @@ LocalAI will attempt to automatically load models which are not explicitly confi
| `diffusers` | SD,... | no | Image generation | no | no | N/A |
| `vall-e-x` | Vall-E | no | Audio generation and Voice cloning | no | no | CPU/CUDA |
| `vllm` | Various GPTs and quantization formats | yes | GPT | no | no | CPU/CUDA |
| `mamba` | Mamba models architecture | yes | GPT | no | no | CPU/CUDA |
| `exllama2` | GPTQ | yes | GPT only | no | no | N/A |
| `transformers-musicgen` | | no | Audio generation | no | no | N/A |
| [tinydream](https://github.com/symisc/tiny-dream#tiny-dreaman-embedded-header-only-stable-diffusion-inference-c-librarypixlabiotiny-dream) | stablediffusion | no | Image | no | no | N/A |
| `coqui` | Coqui | no | Audio generation and Voice cloning | no | no | CPU/CUDA |
| `openvoice` | Open voice | no | Audio generation and Voice cloning | no | no | CPU/CUDA |
| `parler-tts` | Open voice | no | Audio generation and Voice cloning | no | no | CPU/CUDA |
| [rerankers](https://github.com/AnswerDotAI/rerankers) | Reranking API | no | Reranking | no | no | CPU/CUDA |
| `transformers` | Various GPTs and quantization formats | yes | GPT, embeddings | yes | yes**** | CPU/CUDA/XPU |
| [bark-cpp](https://github.com/PABannier/bark.cpp) | bark | no | Audio-Only | no | no | yes |
| [stablediffusion-cpp](https://github.com/leejet/stable-diffusion.cpp) | stablediffusion-1, stablediffusion-2, stablediffusion-3, flux, PhotoMaker | no | Image | no | no | N/A |
| [silero-vad](https://github.com/snakers4/silero-vad) with [Golang bindings](https://github.com/streamer45/silero-vad-go) | Silero VAD | no | Voice Activity Detection | no | no | CPU |
Note: any backend name listed above can be used in the `backend` field of the model configuration file (See [the advanced section]({{%relref "docs/advanced" %}})).

View File

@@ -1,3 +1,3 @@
{
"version": "v2.24.2"
"version": "v2.23.0"
}

View File

@@ -0,0 +1,23 @@
backend: bert-embeddings
embeddings: true
f16: true
gpu_layers: 90
mmap: true
name: bert-cpp-minilm-v6
parameters:
model: bert-MiniLM-L6-v2q4_0.bin
download_files:
- filename: "bert-MiniLM-L6-v2q4_0.bin"
sha256: "a5a174d8772c8a569faf9f3136c441f2c3855b5bf35ed32274294219533feaad"
uri: "https://huggingface.co/mudler/all-MiniLM-L6-v2/resolve/main/ggml-model-q4_0.bin"
usage: |
You can test this model with curl like this:
curl http://localhost:8080/embeddings -X POST -H "Content-Type: application/json" -d '{
"input": "Your text string goes here",
"model": "bert-cpp-minilm-v6"
}'

View File

@@ -0,0 +1,12 @@
---
name: "bert-embeddings"
config_file: |
parameters:
model: bert-MiniLM-L6-v2q4_0.bin
backend: bert-embeddings
embeddings: true
files:
- filename: "bert-MiniLM-L6-v2q4_0.bin"
sha256: "a5a174d8772c8a569faf9f3136c441f2c3855b5bf35ed32274294219533feaad"
uri: "https://huggingface.co/mudler/all-MiniLM-L6-v2/resolve/main/ggml-model-q4_0.bin"

View File

@@ -1,12 +0,0 @@
---
name: "flux-ggml"
config_file: |
backend: stablediffusion-ggml
step: 25
options:
- "diffusion_model"
- "clip_l_path:clip_l.safetensors"
- "t5xxl_path:t5xxl_fp16.safetensors"
- "vae_path:ae.safetensors"
- "sampler:euler"

View File

@@ -11,5 +11,4 @@ config_file: |
cuda: true
enable_parameters: num_inference_steps
pipeline_type: FluxPipeline
cfg_scale: 0
cfg_scale: 0

View File

@@ -1,75 +1,4 @@
---
- &intellect1
name: "intellect-1-instruct"
url: "github:mudler/LocalAI/gallery/llama3.1-instruct.yaml@master"
icon: https://huggingface.co/PrimeIntellect/INTELLECT-1-Instruct/resolve/main/intellect-1-map.png
urls:
- https://huggingface.co/PrimeIntellect/INTELLECT-1-Instruct
- https://huggingface.co/bartowski/INTELLECT-1-Instruct-GGUF
tags:
- llm
- gguf
- gpu
- cpu
- intellect
license: apache-2.0
description: |
INTELLECT-1 is the first collaboratively trained 10 billion parameter language model trained from scratch on 1 trillion tokens of English text and code.
This is an instruct model. The base model associated with it is INTELLECT-1.
INTELLECT-1 was trained on up to 14 concurrent nodes distributed across 3 continents, with contributions from 30 independent community contributors providing compute. The training code utilizes the prime framework, a scalable distributed training framework designed for fault-tolerant, dynamically scaling, high-perfomance training on unreliable, globally distributed workers. The key abstraction that allows dynamic scaling is the ElasticDeviceMesh which manages dynamic global process groups for fault-tolerant communication across the internet and local process groups for communication within a node. The model was trained using the DiLoCo algorithms with 100 inner steps. The global all-reduce was done with custom int8 all-reduce kernels to reduce the communication payload required, greatly reducing the communication overhead by a factor 400x.
overrides:
parameters:
model: INTELLECT-1-Instruct-Q4_K_M.gguf
files:
- filename: INTELLECT-1-Instruct-Q4_K_M.gguf
sha256: 5df236fe570e5998d07fb3207788eac811ef3b77dd2a0ad04a2ef5c6361f3030
uri: huggingface://bartowski/INTELLECT-1-Instruct-GGUF/INTELLECT-1-Instruct-Q4_K_M.gguf
- &llama33
url: "github:mudler/LocalAI/gallery/llama3.1-instruct.yaml@master"
icon: https://cdn-uploads.huggingface.co/production/uploads/642cc1c253e76b4c2286c58e/aJJxKus1wP5N-euvHEUq7.png
license: llama3.3
description: |
The Meta Llama 3.3 multilingual large language model (LLM) is a pretrained and instruction tuned generative model in 70B (text in/text out). The Llama 3.3 instruction tuned text only model is optimized for multilingual dialogue use cases and outperform many of the available open source and closed chat models on common industry benchmarks.
tags:
- llm
- gguf
- gpu
- cpu
- llama3.3
name: "llama-3.3-70b-instruct"
urls:
- https://huggingface.co/meta-llama/Llama-3.3-70B-Instruct
- https://huggingface.co/MaziyarPanahi/Llama-3.3-70B-Instruct-GGUF
overrides:
parameters:
model: Llama-3.3-70B-Instruct.Q4_K_M.gguf
files:
- filename: Llama-3.3-70B-Instruct.Q4_K_M.gguf
sha256: 4f3b04ecae278bdb0fd545b47c210bc5edf823e5ebf7d41e0b526c81d54b1ff3
uri: huggingface://MaziyarPanahi/Llama-3.3-70B-Instruct-GGUF/Llama-3.3-70B-Instruct.Q4_K_M.gguf
- &rwkv
url: "github:mudler/LocalAI/gallery/rwkv.yaml@master"
name: "rwkv-6-world-7b"
license: apache-2.0
urls:
- https://huggingface.co/RWKV/rwkv-6-world-7b
- https://huggingface.co/bartowski/rwkv-6-world-7b-GGUF
tags:
- llm
- rwkv
- cpu
- gpu
- rnn
description: |
RWKV (pronounced RwaKuv) is an RNN with GPT-level LLM performance, and can also be directly trained like a GPT transformer (parallelizable). We are at RWKV-7.
So it's combining the best of RNN and transformer - great performance, fast inference, fast training, saves VRAM, "infinite" ctxlen, and free text embedding. Moreover it's 100% attention-free, and a Linux Foundation AI project.
overrides:
parameters:
model: rwkv-6-world-7b-Q4_K_M.gguf
files:
- filename: rwkv-6-world-7b-Q4_K_M.gguf
sha256: f74574186fa4584f405e92198605680db6ad00fd77974ffa14bf02073bb90273
uri: huggingface://bartowski/rwkv-6-world-7b-GGUF/rwkv-6-world-7b-Q4_K_M.gguf
- &qwen25coder
name: "qwen2.5-coder-14b"
url: "github:mudler/LocalAI/gallery/chatml.yaml@master"
@@ -428,7 +357,6 @@
urls:
- https://huggingface.co/hugging-quants/Llama-3.2-1B-Instruct-Q4_K_M-GGUF
overrides:
embeddings: true
parameters:
model: llama-3.2-1b-instruct-q4_k_m.gguf
files:
@@ -752,31 +680,6 @@
- filename: Llama-Sentient-3.2-3B-Instruct.Q4_K_M.gguf
uri: huggingface://QuantFactory/Llama-Sentient-3.2-3B-Instruct-GGUF/Llama-Sentient-3.2-3B-Instruct.Q4_K_M.gguf
sha256: 3f855ce0522bfdc39fc826162ba6d89f15cc3740c5207da10e70baa3348b7812
- !!merge <<: *llama32
name: "llama-smoltalk-3.2-1b-instruct"
urls:
- https://huggingface.co/prithivMLmods/Llama-SmolTalk-3.2-1B-Instruct
- https://huggingface.co/mradermacher/Llama-SmolTalk-3.2-1B-Instruct-GGUF
description: |
The Llama-SmolTalk-3.2-1B-Instruct model is a lightweight, instruction-tuned model designed for efficient text generation and conversational AI tasks. With a 1B parameter architecture, this model strikes a balance between performance and resource efficiency, making it ideal for applications requiring concise, contextually relevant outputs. The model has been fine-tuned to deliver robust instruction-following capabilities, catering to both structured and open-ended queries.
Key Features:
Instruction-Tuned Performance: Optimized to understand and execute user-provided instructions across diverse domains.
Lightweight Architecture: With just 1 billion parameters, the model provides efficient computation and storage without compromising output quality.
Versatile Use Cases: Suitable for tasks like content generation, conversational interfaces, and basic problem-solving.
Intended Applications:
Conversational AI: Engage users with dynamic and contextually aware dialogue.
Content Generation: Produce summaries, explanations, or other creative text outputs efficiently.
Instruction Execution: Follow user commands to generate precise and relevant responses.
overrides:
parameters:
model: Llama-SmolTalk-3.2-1B-Instruct.Q4_K_M.gguf
files:
- filename: Llama-SmolTalk-3.2-1B-Instruct.Q4_K_M.gguf
sha256: 03d8d05e3821f4caa65defa82baaff658484d4405b66546431528153ceef4d9e
uri: huggingface://mradermacher/Llama-SmolTalk-3.2-1B-Instruct-GGUF/Llama-SmolTalk-3.2-1B-Instruct.Q4_K_M.gguf
- &qwen25
## Qwen2.5
name: "qwen2.5-14b-instruct"
@@ -1668,290 +1571,6 @@
- filename: SteyrCannon-0.2-Qwen2.5-72b.Q4_K_M.gguf
sha256: b34c08b77ffd25ccb0ca50b167f2215e784689205c93a0903fa9435b6cc187f0
uri: huggingface://mradermacher/SteyrCannon-0.2-Qwen2.5-72b-GGUF/SteyrCannon-0.2-Qwen2.5-72b.Q4_K_M.gguf
- !!merge <<: *qwen25
name: "q2.5-ms-mistoria-72b-v2"
icon: https://cdn-uploads.huggingface.co/production/uploads/64545af5ec40bbbd01242ca6/5LOvUFYiMMw6pcEsOhmo2.webp
urls:
- https://huggingface.co/Steelskull/Q2.5-MS-Mistoria-72b-v2
- https://huggingface.co/bartowski/Q2.5-MS-Mistoria-72b-v2-GGUF
description: |
This model is my second attempt at a 72b model, as usual, my goal is to merge the robust storytelling of mutiple models while attempting to maintain intelligence.
models:
- model: EVA-UNIT-01/EVA-Qwen2.5-72B-v0.2
- model: ZeusLabs/Chronos-Platinum-72B
- model: shuttleai/shuttle-3
overrides:
parameters:
model: Q2.5-MS-Mistoria-72b-v2-Q4_K_M.gguf
files:
- filename: Q2.5-MS-Mistoria-72b-v2-Q4_K_M.gguf
sha256: 33df8aac5a790d1c286fe0fc4f9d340311f282eca19b78db6f7abb845923425c
uri: huggingface://bartowski/Q2.5-MS-Mistoria-72b-v2-GGUF/Q2.5-MS-Mistoria-72b-v2-Q4_K_M.gguf
- !!merge <<: *qwen25
name: "eva-qwen2.5-72b-v0.2"
urls:
- https://huggingface.co/EVA-UNIT-01/EVA-Qwen2.5-72B-v0.2
- https://huggingface.co/bartowski/EVA-Qwen2.5-72B-v0.2-GGUF
description: |
A RP/storywriting specialist model, full-parameter finetune of Qwen2.5-72B on mixture of synthetic and natural data.
It uses Celeste 70B 0.1 data mixture, greatly expanding it to improve versatility, creativity and "flavor" of the resulting model.
Version notes for 0.2: Optimized training hyperparameters and increased sequence length. Better instruction following deeper into context and less repetition.
overrides:
parameters:
model: EVA-Qwen2.5-72B-v0.2-Q4_K_M.gguf
files:
- filename: EVA-Qwen2.5-72B-v0.2-Q4_K_M.gguf
sha256: 03ea0ecac3ee24a332ca43cf925b669c58714b9754be0f4bc232bd996681ef4b
uri: huggingface://bartowski/EVA-Qwen2.5-72B-v0.2-GGUF/EVA-Qwen2.5-72B-v0.2-Q4_K_M.gguf
- !!merge <<: *qwen25
name: "qwq-32b-preview"
urls:
- https://huggingface.co/Qwen/QwQ-32B-Preview
- https://huggingface.co/bartowski/QwQ-32B-Preview-GGUF
description: |
QwQ-32B-Preview is an experimental research model developed by the Qwen Team, focused on advancing AI reasoning capabilities. As a preview release, it demonstrates promising analytical abilities while having several important limitations:
Language Mixing and Code-Switching: The model may mix languages or switch between them unexpectedly, affecting response clarity.
Recursive Reasoning Loops: The model may enter circular reasoning patterns, leading to lengthy responses without a conclusive answer.
Safety and Ethical Considerations: The model requires enhanced safety measures to ensure reliable and secure performance, and users should exercise caution when deploying it.
Performance and Benchmark Limitations: The model excels in math and coding but has room for improvement in other areas, such as common sense reasoning and nuanced language understanding.
overrides:
parameters:
model: QwQ-32B-Preview-Q4_K_M.gguf
files:
- filename: QwQ-32B-Preview-Q4_K_M.gguf
sha256: c499801e682e2379528090c50e106837ca1d69dc3bf3ff3a9af830a0eb49cdf6
uri: huggingface://bartowski/QwQ-32B-Preview-GGUF/QwQ-32B-Preview-Q4_K_M.gguf
- !!merge <<: *qwen25
name: "q2.5-32b-slush-i1"
urls:
- https://huggingface.co/crestf411/Q2.5-32B-Slush
- https://huggingface.co/mradermacher/Q2.5-32B-Slush-i1-GGUF
description: |
Slush is a two-stage model trained with high LoRA dropout, where stage 1 is a pretraining continuation on the base model, aimed at boosting the model's creativity and writing capabilities. This is then merged into the instruction tune model, and stage 2 is a fine tuning step on top of this to further enhance its roleplaying capabilities and/or to repair any damage caused in the stage 1 merge.
This is still early stage. As always, feedback is welcome, and begone if you demand perfection.
The second stage, like the Sunfall series, follows the Silly Tavern preset (ChatML), so ymmv in particular if you use some other tool and/or preset.
overrides:
parameters:
model: Q2.5-32B-Slush.i1-Q4_K_M.gguf
files:
- filename: Q2.5-32B-Slush.i1-Q4_K_M.gguf
sha256: 95aecaf43077dabc72d3b556923ede2563325e1c89863800229cfa8b7f1c9659
uri: huggingface://mradermacher/Q2.5-32B-Slush-i1-GGUF/Q2.5-32B-Slush.i1-Q4_K_M.gguf
- !!merge <<: *qwen25
name: "qwestion-24b"
urls:
- https://huggingface.co/CultriX/Qwestion-14B
- https://huggingface.co/mradermacher/Qwestion-24B-GGUF
description: |
This model was merged using the DARE TIES merge method using Qwen/Qwen2.5-14B as a base.
The following models were included in the merge:
allknowingroger/Qwenslerp2-14B
rombodawg/Rombos-LLM-V2.6-Qwen-14b
VAGOsolutions/SauerkrautLM-v2-14b-DPO
CultriX/Qwen2.5-14B-Wernicke
overrides:
parameters:
model: Qwestion-24B.Q4_K_M.gguf
files:
- filename: Qwestion-24B.Q4_K_M.gguf
sha256: 5d493bd81cfeef66d80101260145ab1d1d0428ef2191edce62b58391bd0fff0e
uri: huggingface://mradermacher/Qwestion-24B-GGUF/Qwestion-24B.Q4_K_M.gguf
- !!merge <<: *qwen25
name: "teleut-7b"
icon: https://cdn-uploads.huggingface.co/production/uploads/634262af8d8089ebaefd410e/UqIi8eztdptvt52Mak_1K.png
urls:
- https://huggingface.co/allura-org/Teleut-7b
- https://huggingface.co/QuantFactory/Teleut-7b-GGUF
description: |
A replication attempt of Tulu 3 on the Qwen 2.5 base models.
overrides:
parameters:
model: Teleut-7b.Q4_K_M.gguf
files:
- filename: Teleut-7b.Q4_K_M.gguf
sha256: 844a633ea01d793c638e99f2e07413606b3812b759e9264fbaf69c8d94eaa093
uri: huggingface://QuantFactory/Teleut-7b-GGUF/Teleut-7b.Q4_K_M.gguf
- !!merge <<: *qwen25
name: "qwen2.5-7b-homercreative-mix"
urls:
- https://huggingface.co/ZeroXClem/Qwen2.5-7B-HomerCreative-Mix
- https://huggingface.co/QuantFactory/Qwen2.5-7B-HomerCreative-Mix-GGUF
description: |
ZeroXClem/Qwen2.5-7B-HomerCreative-Mix is an advanced language model meticulously crafted by merging four pre-trained models using the powerful mergekit framework. This fusion leverages the Model Stock merge method to combine the creative prowess of Qandora, the instructive capabilities of Qwen-Instruct-Fusion, the sophisticated blending of HomerSlerp1, and the foundational conversational strengths of Homer-v0.5-Qwen2.5-7B. The resulting model excels in creative text generation, contextual understanding, and dynamic conversational interactions.
🚀 Merged Models
This model merge incorporates the following:
bunnycore/Qandora-2.5-7B-Creative: Specializes in creative text generation, enhancing the model's ability to produce imaginative and diverse content.
bunnycore/Qwen2.5-7B-Instruct-Fusion: Focuses on instruction-following capabilities, improving the model's performance in understanding and executing user commands.
allknowingroger/HomerSlerp1-7B: Utilizes spherical linear interpolation (SLERP) to blend model weights smoothly, ensuring a harmonious integration of different model attributes.
newsbang/Homer-v0.5-Qwen2.5-7B: Acts as the foundational conversational model, providing robust language comprehension and generation capabilities.
overrides:
parameters:
model: Qwen2.5-7B-HomerCreative-Mix.Q4_K_M.gguf
files:
- filename: Qwen2.5-7B-HomerCreative-Mix.Q4_K_M.gguf
sha256: fc3fdb41e068646592f89a8ae62d7b330f2bd4e97bf615aef2977930977c8ba5
uri: huggingface://QuantFactory/Qwen2.5-7B-HomerCreative-Mix-GGUF/Qwen2.5-7B-HomerCreative-Mix.Q4_K_M.gguf
- !!merge <<: *qwen25
name: "cybercore-qwen-2.1-7b"
urls:
- https://huggingface.co/bunnycore/CyberCore-Qwen-2.1-7B
- https://huggingface.co/QuantFactory/CyberCore-Qwen-2.1-7B-GGUF
description: |
This model was merged using the TIES merge method using rombodawg/Rombos-LLM-V2.5-Qwen-7b as a base.
Models Merged
fblgit/cybertron-v4-qw7B-UNAMGS + bunnycore/Qwen-2.1-7b-Persona-lora_model
fblgit/cybertron-v4-qw7B-MGS + bunnycore/Qwen-2.1-7b-Persona-lora_model
overrides:
parameters:
model: CyberCore-Qwen-2.1-7B.Q4_K_M.gguf
files:
- filename: CyberCore-Qwen-2.1-7B.Q4_K_M.gguf
sha256: 726042707a4cec29ca0355b4dc7c53a807b307d08aa8a3d4a9e76aefbbbcaadf
uri: huggingface://QuantFactory/CyberCore-Qwen-2.1-7B-GGUF/CyberCore-Qwen-2.1-7B.Q4_K_M.gguf
- !!merge <<: *qwen25
name: "homercreativeanvita-mix-qw7b"
icon: https://huggingface.co/suayptalha/HomerCreativeAnvita-Mix-Qw7B/resolve/main/HomerCreativeAnvita.jpeg
urls:
- https://huggingface.co/suayptalha/HomerCreativeAnvita-Mix-Qw7B
- https://huggingface.co/QuantFactory/HomerCreativeAnvita-Mix-Qw7B-GGUF
description: |
This model is currently ranked #1 on the Open LLM Leaderboard among models up to 13B parameters!
Merge Method
This model was merged using the SLERP merge method.
Models Merged
The following models were included in the merge:
ZeroXClem/Qwen2.5-7B-HomerAnvita-NerdMix
ZeroXClem/Qwen2.5-7B-HomerCreative-Mix
overrides:
parameters:
model: HomerCreativeAnvita-Mix-Qw7B.Q4_K_M.gguf
files:
- filename: HomerCreativeAnvita-Mix-Qw7B.Q4_K_M.gguf
sha256: a356f279a104bff0bbc2ef7ec136c1e774153de8893bf988083e96fb7f4bc053
uri: huggingface://QuantFactory/HomerCreativeAnvita-Mix-Qw7B-GGUF/HomerCreativeAnvita-Mix-Qw7B.Q4_K_M.gguf
- !!merge <<: *qwen25
name: "math-iio-7b-instruct"
icon: https://cdn-uploads.huggingface.co/production/uploads/65bb837dbfb878f46c77de4c/faLfR-doaWP_BLUkOQrbq.png
urls:
- https://huggingface.co/prithivMLmods/Math-IIO-7B-Instruct
- https://huggingface.co/QuantFactory/Math-IIO-7B-Instruct-GGUF
description: |
The Math IIO 7B Instruct is a fine-tuned language model based on the robust Qwen2.5-7B-Instruct architecture. This model has been specifically trained to excel in single-shot mathematical reasoning and instruction-based tasks, making it a reliable choice for educational, analytical, and problem-solving applications.
Key Features:
Math-Optimized Capabilities:
The model is designed to handle complex mathematical problems, step-by-step calculations, and reasoning tasks.
Instruction-Tuned:
Fine-tuned for better adherence to structured queries and task-oriented prompts, enabling clear and concise outputs.
Large Vocabulary:
Equipped with an extensive tokenizer configuration and custom tokens to ensure precise mathematical notation support.
overrides:
parameters:
model: Math-IIO-7B-Instruct.Q4_K_M.gguf
files:
- filename: Math-IIO-7B-Instruct.Q4_K_M.gguf
sha256: 8ffda0b6a43eb9997dfd7db48fe3bd0970fd1b9b86fb68f082c38622a48b58f4
uri: huggingface://QuantFactory/Math-IIO-7B-Instruct-GGUF/Math-IIO-7B-Instruct.Q4_K_M.gguf
- !!merge <<: *qwen25
name: "virtuoso-small"
icon: https://i.ibb.co/pXD6Bcv/SW2-U-g-QQLSH1-ZAbxhs-Iu-A.webp
urls:
- https://huggingface.co/arcee-ai/Virtuoso-Small-GGUF
description: |
Virtuoso-Small is the debut public release of the Virtuoso series of models by Arcee.ai, designed to bring cutting-edge generative AI capabilities to organizations and developers in a compact, efficient form. With 14 billion parameters, Virtuoso-Small is an accessible entry point for high-quality instruction-following, complex reasoning, and business-oriented generative AI tasks.
overrides:
parameters:
model: Virtuoso-Small-Q4_K_M.gguf
files:
- filename: Virtuoso-Small-Q4_K_M.gguf
sha256: 07db215cdfcb05036567017fe20e50e60cb2da28d1f9a8251cc4f18c8caa247f
uri: huggingface://arcee-ai/Virtuoso-Small-GGUF/Virtuoso-Small-Q4_K_M.gguf
- !!merge <<: *qwen25
name: "qwen2.5-7b-homeranvita-nerdmix"
urls:
- https://huggingface.co/ZeroXClem/Qwen2.5-7B-HomerAnvita-NerdMix
- https://huggingface.co/QuantFactory/Qwen2.5-7B-HomerAnvita-NerdMix-GGUF
description: |
ZeroXClem/Qwen2.5-7B-HomerAnvita-NerdMix is an advanced language model meticulously crafted by merging five pre-trained models using the powerful mergekit framework. This fusion leverages the Model Stock merge method to combine the creative prowess of Qandora, the instructive capabilities of Qwen-Instruct-Fusion, the sophisticated blending of HomerSlerp1, the mathematical precision of Cybertron-MGS, and the uncensored expertise of Qwen-Nerd. The resulting model excels in creative text generation, contextual understanding, technical reasoning, and dynamic conversational interactions.
overrides:
parameters:
model: Qwen2.5-7B-HomerAnvita-NerdMix.Q4_K_M.gguf
files:
- filename: Qwen2.5-7B-HomerAnvita-NerdMix.Q4_K_M.gguf
sha256: 73db2ca3ab50e8627352078988cd173e7447c5e8199a7db9e554602da1362e5f
uri: huggingface://QuantFactory/Qwen2.5-7B-HomerAnvita-NerdMix-GGUF/Qwen2.5-7B-HomerAnvita-NerdMix.Q4_K_M.gguf
- !!merge <<: *qwen25
name: "qwen2.5-math-14b-instruct"
urls:
- https://huggingface.co/qingy2024/Qwen2.5-Math-14B-Instruct-Preview
- https://huggingface.co/QuantFactory/Qwen2.5-Math-14B-Instruct-GGUF
description: |
This Qwen 2.5 model was trained 2x faster with Unsloth and Huggingface's TRL library.
Fine-tuned it for 400 steps on garage-bAInd/Open-Platypus with a batch size of 3.
overrides:
parameters:
model: Qwen2.5-Math-14B-Instruct.Q4_K_M.gguf
files:
- filename: Qwen2.5-Math-14B-Instruct.Q4_K_M.gguf
sha256: 14e672394738a7d9f14a6cb16fd9a649b113a19a8b4934f9c18299fc4e286ab6
uri: huggingface://QuantFactory/Qwen2.5-Math-14B-Instruct-GGUF/Qwen2.5-Math-14B-Instruct.Q4_K_M.gguf
- !!merge <<: *qwen25
name: "sailor2-1b-chat"
icon: https://huggingface.co/sail/Sailor2-1B-Chat/resolve/main/sailor2_banner.jpg
urls:
- https://huggingface.co/sail/Sailor2-1B-Chat
- https://huggingface.co/bartowski/Sailor2-1B-Chat-GGUF
description: |
Sailor2 is a community-driven initiative that brings cutting-edge multilingual language models to South-East Asia (SEA). Our research highlights a strong demand for models in the 8B and 20B parameter range for production use, alongside 1B models for specialized applications, such as speculative decoding and research purposes. These models, released under the Apache 2.0 license, provide enhanced accessibility to advanced language technologies across the region.
Sailor2 builds upon the foundation of the awesome multilingual model Qwen 2.5 and is continuously pre-trained on 500B tokens to support 15 languages better with a unified model. These languages include English, Chinese, Burmese, Cebuano, Ilocano, Indonesian, Javanese, Khmer, Lao, Malay, Sundanese, Tagalog, Thai, Vietnamese, and Waray. By addressing the growing demand for diverse, robust, and accessible language models, Sailor2 seeks to serve the underserved in SEA areas with open, inclusive, and accessible multilingual LLMs. The Sailor2 model comes in three sizes, 1B, 8B, and 20B, which are expanded from the Qwen2.5 base models of 0.5B, 7B, and 14B, respectively.
overrides:
parameters:
model: Sailor2-1B-Chat-Q4_K_M.gguf
files:
- filename: Sailor2-1B-Chat-Q4_K_M.gguf
sha256: 782e8abed13d51a2083eadfb2f6d94c2cd77940532f612a99e6f6bec9b3501d4
uri: huggingface://bartowski/Sailor2-1B-Chat-GGUF/Sailor2-1B-Chat-Q4_K_M.gguf
- !!merge <<: *qwen25
icon: https://huggingface.co/sail/Sailor2-1B-Chat/resolve/main/sailor2_banner.jpg
name: "sailor2-8b-chat"
urls:
- https://huggingface.co/bartowski/Sailor2-8B-Chat-GGUF
description: |
Sailor2 is a community-driven initiative that brings cutting-edge multilingual language models to South-East Asia (SEA). Our research highlights a strong demand for models in the 8B and 20B parameter range for production use, alongside 1B models for specialized applications, such as speculative decoding and research purposes. These models, released under the Apache 2.0 license, provide enhanced accessibility to advanced language technologies across the region.
Sailor2 builds upon the foundation of the awesome multilingual model Qwen 2.5 and is continuously pre-trained on 500B tokens to support 15 languages better with a unified model. These languages include English, Chinese, Burmese, Cebuano, Ilocano, Indonesian, Javanese, Khmer, Lao, Malay, Sundanese, Tagalog, Thai, Vietnamese, and Waray. By addressing the growing demand for diverse, robust, and accessible language models, Sailor2 seeks to serve the underserved in SEA areas with open, inclusive, and accessible multilingual LLMs. The Sailor2 model comes in three sizes, 1B, 8B, and 20B, which are expanded from the Qwen2.5 base models of 0.5B, 7B, and 14B, respectively.
overrides:
parameters:
model: Sailor2-8B-Chat-Q4_K_M.gguf
files:
- filename: Sailor2-8B-Chat-Q4_K_M.gguf
sha256: 1a6aaadd6f6ef9c2290d66b348ebcbd6fdec542834cde622498fbd467d966103
uri: huggingface://bartowski/Sailor2-8B-Chat-GGUF/Sailor2-8B-Chat-Q4_K_M.gguf
- !!merge <<: *qwen25
name: "sailor2-20b-chat"
icon: https://huggingface.co/sail/Sailor2-1B-Chat/resolve/main/sailor2_banner.jpg
urls:
- https://huggingface.co/bartowski/Sailor2-20B-Chat-GGUF
description: |
Sailor2 is a community-driven initiative that brings cutting-edge multilingual language models to South-East Asia (SEA). Our research highlights a strong demand for models in the 8B and 20B parameter range for production use, alongside 1B models for specialized applications, such as speculative decoding and research purposes. These models, released under the Apache 2.0 license, provide enhanced accessibility to advanced language technologies across the region.
Sailor2 builds upon the foundation of the awesome multilingual model Qwen 2.5 and is continuously pre-trained on 500B tokens to support 15 languages better with a unified model. These languages include English, Chinese, Burmese, Cebuano, Ilocano, Indonesian, Javanese, Khmer, Lao, Malay, Sundanese, Tagalog, Thai, Vietnamese, and Waray. By addressing the growing demand for diverse, robust, and accessible language models, Sailor2 seeks to serve the underserved in SEA areas with open, inclusive, and accessible multilingual LLMs. The Sailor2 model comes in three sizes, 1B, 8B, and 20B, which are expanded from the Qwen2.5 base models of 0.5B, 7B, and 14B, respectively.
overrides:
parameters:
model: Sailor2-20B-Chat-Q4_K_M.gguf
files:
- filename: Sailor2-20B-Chat-Q4_K_M.gguf
sha256: 0cf8fcd367accee19702ef15ee964bddd5035bde034afddd838f818e7655534a
uri: huggingface://bartowski/Sailor2-20B-Chat-GGUF/Sailor2-20B-Chat-Q4_K_M.gguf
- &archfunct
license: apache-2.0
tags:
@@ -3514,253 +3133,6 @@
- filename: Tulu-3.1-8B-SuperNova.i1-Q4_K_M.gguf
sha256: c6cc2e1a4c3d2338973ca0050af1cf4462b3f62838f62b4c8a204f2a74eeb01f
uri: huggingface://mradermacher/Tulu-3.1-8B-SuperNova-i1-GGUF/Tulu-3.1-8B-SuperNova.i1-Q4_K_M.gguf
- !!merge <<: *llama31
name: "llama-3.1-tulu-3-70b-dpo"
icon: "https://huggingface.co/datasets/allenai/blog-images/resolve/main/tulu3/Tulu3-logo.png"
urls:
- https://huggingface.co/allenai/Llama-3.1-Tulu-3-70B-DPO
- https://huggingface.co/bartowski/Llama-3.1-Tulu-3-70B-DPO-GGUF
description: |
Tülu3 is a leading instruction following model family, offering fully open-source data, code, and recipes designed to serve as a comprehensive guide for modern post-training techniques. Tülu3 is designed for state-of-the-art performance on a diversity of tasks in addition to chat, such as MATH, GSM8K, and IFEval.
overrides:
parameters:
model: Llama-3.1-Tulu-3-70B-DPO-Q4_K_M.gguf
files:
- filename: Llama-3.1-Tulu-3-70B-DPO-Q4_K_M.gguf
sha256: e2d9c59736274f9dd94f30ef3edcee68fec1d6649eb01d6bad7e3e8a6024f77d
uri: huggingface://bartowski/Llama-3.1-Tulu-3-70B-DPO-GGUF/Llama-3.1-Tulu-3-70B-DPO-Q4_K_M.gguf
- !!merge <<: *llama31
name: "llama-3.1-tulu-3-8b-sft"
icon: "https://huggingface.co/datasets/allenai/blog-images/resolve/main/tulu3/Tulu3-logo.png"
urls:
- https://huggingface.co/allenai/Llama-3.1-Tulu-3-8B-SFT
- https://huggingface.co/bartowski/Llama-3.1-Tulu-3-8B-SFT-GGUF
description: |
Tülu3 is a leading instruction following model family, offering fully open-source data, code, and recipes designed to serve as a comprehensive guide for modern post-training techniques. Tülu3 is designed for state-of-the-art performance on a diversity of tasks in addition to chat, such as MATH, GSM8K, and IFEval.
overrides:
parameters:
model: Llama-3.1-Tulu-3-8B-SFT-Q4_K_M.gguf
files:
- filename: Llama-3.1-Tulu-3-8B-SFT-Q4_K_M.gguf
sha256: 3fad2c96aa9b9de19c2cda0f88a381c47ac768ca03a95059d9f6c439791f8592
uri: huggingface://bartowski/Llama-3.1-Tulu-3-8B-SFT-GGUF/Llama-3.1-Tulu-3-8B-SFT-Q4_K_M.gguf
- !!merge <<: *llama31
icon: https://huggingface.co/Skywork/Skywork-o1-Open-Llama-3.1-8B/resolve/main/misc/misc_fig.jpg
name: "skywork-o1-open-llama-3.1-8b"
urls:
- https://huggingface.co/Skywork/Skywork-o1-Open-Llama-3.1-8B
- https://huggingface.co/QuantFactory/Skywork-o1-Open-Llama-3.1-8B-GGUF
description: |
We are excited to announce the release of the Skywork o1 Open model series, developed by the Skywork team at Kunlun Inc. This groundbreaking release introduces a series of models that incorporate o1-like slow thinking and reasoning capabilities. The Skywork o1 Open model series includes three advanced models:
Skywork o1 Open-Llama-3.1-8B: A robust chat model trained on Llama-3.1-8B, enhanced significantly with "o1-style" data to improve reasoning skills.
Skywork o1 Open-PRM-Qwen-2.5-1.5B: A specialized model designed to enhance reasoning capability through incremental process rewards, ideal for complex problem solving at a smaller scale.
Skywork o1 Open-PRM-Qwen-2.5-7B: Extends the capabilities of the 1.5B model by scaling up to handle more demanding reasoning tasks, pushing the boundaries of AI reasoning.
Different from mere reproductions of the OpenAI o1 model, the Skywork o1 Open model series not only exhibits innate thinking, planning, and reflecting capabilities in its outputs, but also shows significant improvements in reasoning skills on standard benchmarks. This series represents a strategic advancement in AI capabilities, moving a previously weaker base model towards the state-of-the-art (SOTA) in reasoning tasks.
overrides:
parameters:
model: Skywork-o1-Open-Llama-3.1-8B.Q4_K_M.gguf
files:
- filename: Skywork-o1-Open-Llama-3.1-8B.Q4_K_M.gguf
sha256: ef6a203ba585aab14f5d2ec463917a45b3ac571abd89c39e9a96a5e395ea8eea
uri: huggingface://QuantFactory/Skywork-o1-Open-Llama-3.1-8B-GGUF/Skywork-o1-Open-Llama-3.1-8B.Q4_K_M.gguf
- !!merge <<: *llama31
name: "sparse-llama-3.1-8b-2of4"
urls:
- https://huggingface.co/QuantFactory/Sparse-Llama-3.1-8B-2of4-GGUF
- https://huggingface.co/QuantFactory/Sparse-Llama-3.1-8B-2of4-GGUF
description: |
This is the 2:4 sparse version of Llama-3.1-8B. On the OpenLLM benchmark (version 1), it achieves an average score of 62.16, compared to 63.19 for the dense model—demonstrating a 98.37% accuracy recovery. On the Mosaic Eval Gauntlet benchmark (version v0.3), it achieves an average score of 53.85, versus 55.34 for the dense model—representing a 97.3% accuracy recovery.
overrides:
parameters:
model: Sparse-Llama-3.1-8B-2of4.Q4_K_M.gguf
files:
- filename: Sparse-Llama-3.1-8B-2of4.Q4_K_M.gguf
sha256: c481e7089ffaedd5ae8c74dccc7fb45f6509640b661fa086ae979f6fefc3fdba
uri: huggingface://QuantFactory/Sparse-Llama-3.1-8B-2of4-GGUF/Sparse-Llama-3.1-8B-2of4.Q4_K_M.gguf
- !!merge <<: *llama31
name: "loki-v2.6-8b-1024k"
icon: https://cdn-uploads.huggingface.co/production/uploads/6472de046facfb01d8b1fb9d/uQPITKRS8XLTLyaiGwgh_.jpeg
urls:
- https://huggingface.co/QuantFactory/Loki-v2.6-8b-1024k-GGUF
description: |
The following models were included in the merge:
MrRobotoAI/Epic_Fiction-8b
MrRobotoAI/Unaligned-RP-Base-8b-1024k
MrRobotoAI/Loki-.Epic_Fiction.-8b
Casual-Autopsy/L3-Luna-8B
Casual-Autopsy/L3-Super-Nova-RP-8B
Casual-Autopsy/L3-Umbral-Mind-RP-v3.0-8B
Casual-Autopsy/Halu-L3-Stheno-BlackOasis-8B
Undi95/Llama-3-LewdPlay-8B
Undi95/Llama-3-LewdPlay-8B-evo
Undi95/Llama-3-Unholy-8B
ChaoticNeutrals/Hathor_Tahsin-L3-8B-v0.9
ChaoticNeutrals/Hathor_RP-v.01-L3-8B
ChaoticNeutrals/Domain-Fusion-L3-8B
ChaoticNeutrals/T-900-8B
ChaoticNeutrals/Poppy_Porpoise-1.4-L3-8B
ChaoticNeutrals/Templar_v1_8B
ChaoticNeutrals/Hathor_Respawn-L3-8B-v0.8
ChaoticNeutrals/Sekhmet_Gimmel-L3.1-8B-v0.3
zeroblu3/LewdPoppy-8B-RP
tohur/natsumura-storytelling-rp-1.0-llama-3.1-8b
jeiku/Chaos_RP_l3_8B
tannedbum/L3-Nymeria-Maid-8B
Nekochu/Luminia-8B-RP
vicgalle/Humanish-Roleplay-Llama-3.1-8B
saishf/SOVLish-Maid-L3-8B
Dogge/llama-3-8B-instruct-Bluemoon-Freedom-RP
MrRobotoAI/Epic_Fiction-8b-v4
maldv/badger-lambda-0-llama-3-8b
maldv/llama-3-fantasy-writer-8b
maldv/badger-kappa-llama-3-8b
maldv/badger-mu-llama-3-8b
maldv/badger-lambda-llama-3-8b
maldv/badger-iota-llama-3-8b
maldv/badger-writer-llama-3-8b
Magpie-Align/MagpieLM-8B-Chat-v0.1
nbeerbower/llama-3-gutenberg-8B
nothingiisreal/L3-8B-Stheno-Horny-v3.3-32K
nbeerbower/llama-3-spicy-abliterated-stella-8B
Magpie-Align/MagpieLM-8B-SFT-v0.1
NeverSleep/Llama-3-Lumimaid-8B-v0.1
mlabonne/NeuralDaredevil-8B-abliterated
mlabonne/Daredevil-8B-abliterated
NeverSleep/Llama-3-Lumimaid-8B-v0.1-OAS
nothingiisreal/L3-8B-Instruct-Abliterated-DWP
openchat/openchat-3.6-8b-20240522
turboderp/llama3-turbcat-instruct-8b
UCLA-AGI/Llama-3-Instruct-8B-SPPO-Iter3
Undi95/Llama-3-LewdPlay-8B
TIGER-Lab/MAmmoTH2-8B-Plus
OwenArli/Awanllm-Llama-3-8B-Cumulus-v1.0
refuelai/Llama-3-Refueled
SicariusSicariiStuff/LLAMA-3_8B_Unaligned_Alpha
NousResearch/Hermes-2-Theta-Llama-3-8B
ResplendentAI/Nymph_8B
grimjim/Llama-3-Oasis-v1-OAS-8B
flammenai/Mahou-1.3b-llama3-8B
lemon07r/Llama-3-RedMagic4-8B
grimjim/Llama-3.1-SuperNova-Lite-lorabilterated-8B
grimjim/Llama-Nephilim-Metamorphosis-v2-8B
lemon07r/Lllama-3-RedElixir-8B
grimjim/Llama-3-Perky-Pat-Instruct-8B
ChaoticNeutrals/Hathor_RP-v.01-L3-8B
grimjim/llama-3-Nephilim-v2.1-8B
ChaoticNeutrals/Hathor_Respawn-L3-8B-v0.8
migtissera/Llama-3-8B-Synthia-v3.5
Locutusque/Llama-3-Hercules-5.0-8B
WhiteRabbitNeo/Llama-3-WhiteRabbitNeo-8B-v2.0
VAGOsolutions/Llama-3-SauerkrautLM-8b-Instruct
iRyanBell/ARC1-II
HPAI-BSC/Llama3-Aloe-8B-Alpha
HaitameLaf/Llama-3-8B-StoryGenerator
failspy/Meta-Llama-3-8B-Instruct-abliterated-v3
Undi95/Llama-3-Unholy-8B
ajibawa-2023/Uncensored-Frank-Llama-3-8B
ajibawa-2023/SlimOrca-Llama-3-8B
ChaoticNeutrals/Templar_v1_8B
aifeifei798/llama3-8B-DarkIdol-2.2-Uncensored-1048K
ChaoticNeutrals/Hathor_Tahsin-L3-8B-v0.9
Blackroot/Llama-3-Gamma-Twist
FPHam/L3-8B-Everything-COT
Blackroot/Llama-3-LongStory
ChaoticNeutrals/Sekhmet_Gimmel-L3.1-8B-v0.3
abacusai/Llama-3-Smaug-8B
Khetterman/CursedMatrix-8B-v9
ajibawa-2023/Scarlett-Llama-3-8B-v1.0
MrRobotoAI/Unaligned-RP-Base-8b-1024k + surya-narayanan/physics_non_masked
MrRobotoAI/Unaligned-RP-Base-8b-1024k + surya-narayanan/electrical_engineering
MrRobotoAI/Unaligned-RP-Base-8b-1024k + surya-narayanan/college_chemistry
MrRobotoAI/Unaligned-RP-Base-8b-1024k + surya-narayanan/philosophy_non_masked
MrRobotoAI/Unaligned-RP-Base-8b-1024k + surya-narayanan/college_physics
MrRobotoAI/Unaligned-RP-Base-8b-1024k + surya-narayanan/philosophy
MrRobotoAI/Unaligned-RP-Base-8b-1024k + surya-narayanan/formal_logic
MrRobotoAI/Unaligned-RP-Base-8b-1024k + surya-narayanan/philosophy_100
MrRobotoAI/Unaligned-RP-Base-8b-1024k + surya-narayanan/conceptual_physics
MrRobotoAI/Unaligned-RP-Base-8b-1024k + surya-narayanan/college_computer_science
MrRobotoAI/Unaligned-RP-Base-8b-1024k + surya-narayanan/psychology_non_masked
MrRobotoAI/Unaligned-RP-Base-8b-1024k + surya-narayanan/psychology
MrRobotoAI/Unaligned-RP-Base-8b-1024k + Blackroot/Llama3-RP-Lora
MrRobotoAI/Unaligned-RP-Base-8b-1024k + Azazelle/Llama-3-LimaRP-Instruct-LoRA-8B
MrRobotoAI/Unaligned-RP-Base-8b-1024k + nothingiisreal/llama3-8B-DWP-lora
MrRobotoAI/Unaligned-RP-Base-8b-1024k + surya-narayanan/world_religions
MrRobotoAI/Unaligned-RP-Base-8b-1024k + surya-narayanan/high_school_european_history
MrRobotoAI/Unaligned-RP-Base-8b-1024k + surya-narayanan/electrical_engineering
MrRobotoAI/Unaligned-RP-Base-8b-1024k + Azazelle/Llama-3-8B-Abomination-LORA
MrRobotoAI/Unaligned-RP-Base-8b-1024k + Azazelle/Llama-3-LongStory-LORA
MrRobotoAI/Unaligned-RP-Base-8b-1024k + surya-narayanan/human_sexuality
MrRobotoAI/Unaligned-RP-Base-8b-1024k + surya-narayanan/sociology
MrRobotoAI/Unaligned-RP-Base-8b-1024k + ResplendentAI/Theory_of_Mind_Llama3
MrRobotoAI/Unaligned-RP-Base-8b-1024k + Azazelle/Smarts_Llama3
MrRobotoAI/Unaligned-RP-Base-8b-1024k + Azazelle/Llama-3-LongStory-LORA
MrRobotoAI/Unaligned-RP-Base-8b-1024k + Azazelle/Nimue-8B
MrRobotoAI/Unaligned-RP-Base-8b-1024k + vincentyandex/lora_llama3_chunked_novel_bs128
MrRobotoAI/Unaligned-RP-Base-8b-1024k + ResplendentAI/Aura_Llama3
MrRobotoAI/Unaligned-RP-Base-8b-1024k + Azazelle/L3-Daybreak-8b-lora
MrRobotoAI/Unaligned-RP-Base-8b-1024k + ResplendentAI/Luna_Llama3
MrRobotoAI/Unaligned-RP-Base-8b-1024k + nicce/story-mixtral-8x7b-lora
MrRobotoAI/Unaligned-RP-Base-8b-1024k + Blackroot/Llama-3-LongStory-LORA
MrRobotoAI/Unaligned-RP-Base-8b-1024k + ResplendentAI/NoWarning_Llama3
MrRobotoAI/Unaligned-RP-Base-8b-1024k + ResplendentAI/BlueMoon_Llama3
overrides:
parameters:
model: Loki-v2.6-8b-1024k.Q4_K_M.gguf
files:
- filename: Loki-v2.6-8b-1024k.Q4_K_M.gguf
sha256: 9b15c1fee0a0e6d6ed97df3d1b6fc8f774e6e1bd388328599e731c62e0f19d81
uri: huggingface://QuantFactory/Loki-v2.6-8b-1024k-GGUF/Loki-v2.6-8b-1024k.Q4_K_M.gguf
- !!merge <<: *llama31
name: "impish_mind_8b"
icon: https://huggingface.co/SicariusSicariiStuff/Impish_Mind_8B/resolve/main/Images/Impish_Mind.png
urls:
- https://huggingface.co/SicariusSicariiStuff/Impish_Mind_8B
- https://huggingface.co/bartowski/Impish_Mind_8B-GGUF
description: |
This model was trained with new data and a new approach (compared to my other models). While it may be a bit more censored, it is expected to be significantly smarter. The data used is quite unique, and is also featuring long and complex markdown datasets.
Regarding censorship: Whether uncensoring or enforcing strict censorship, the model tends to lose some of its intelligence. The use of toxic data was kept to a minimum with this model.
Consequently, the model is likely to refuse some requests, this is easly avoidable with a basic system prompt, or assistant impersonation ("Sure thing!..."). Unlike many RP models, this one is designed to excel at general assistant tasks as well.
overrides:
parameters:
model: Impish_Mind_8B-Q4_K_M.gguf
files:
- filename: Impish_Mind_8B-Q4_K_M.gguf
sha256: 918f82bcb893c75fa2e846156df7bd3ce359464b960e32ae9171035ee14e7c51
uri: huggingface://bartowski/Impish_Mind_8B-GGUF/Impish_Mind_8B-Q4_K_M.gguf
- !!merge <<: *llama31
name: "tulu-3.1-8b-supernova-smart"
urls:
- https://huggingface.co/bunnycore/Tulu-3.1-8B-SuperNova-Smart
- https://huggingface.co/QuantFactory/Tulu-3.1-8B-SuperNova-Smart-GGUF
description: |
This model was merged using the passthrough merge method using bunnycore/Tulu-3.1-8B-SuperNova + bunnycore/Llama-3.1-8b-smart-lora as a base.
overrides:
parameters:
model: Tulu-3.1-8B-SuperNova-Smart.Q4_K_M.gguf
files:
- filename: Tulu-3.1-8B-SuperNova-Smart.Q4_K_M.gguf
sha256: 4b8ba9e64f0667199eee2dcc769f1a90aa9c7730165d42f440fdf107c7585c63
uri: huggingface://QuantFactory/Tulu-3.1-8B-SuperNova-Smart-GGUF/Tulu-3.1-8B-SuperNova-Smart.Q4_K_M.gguf
- !!merge <<: *llama31
name: "b-nimita-l3-8b-v0.02"
urls:
- https://huggingface.co/Arkana08/B-NIMITA-L3-8B-v0.02
- https://huggingface.co/QuantFactory/B-NIMITA-L3-8B-v0.02-GGUF
description: |
B-NIMITA is an AI model designed to bring role-playing scenarios to life with emotional depth and rich storytelling. At its core is NIHAPPY, providing a solid narrative foundation and contextual consistency. This is enhanced by Mythorica, which adds vivid emotional arcs and expressive dialogue, and V-Blackroot, ensuring character consistency and subtle adaptability. This combination allows B-NIMITA to deliver dynamic, engaging interactions that feel natural and immersive.
overrides:
parameters:
model: B-NIMITA-L3-8B-v0.02.Q4_K_M.gguf
files:
- filename: B-NIMITA-L3-8B-v0.02.Q4_K_M.gguf
sha256: 625a54848dcd3f23bc06b639a7dfecae14142b5d177dd45acfe7724816bab4cd
uri: huggingface://QuantFactory/B-NIMITA-L3-8B-v0.02-GGUF/B-NIMITA-L3-8B-v0.02.Q4_K_M.gguf
- &deepseek
## Deepseek
url: "github:mudler/LocalAI/gallery/deepseek.yaml@master"
@@ -4554,47 +3926,6 @@
- filename: magnum-12b-v2.5-kto.i1-Q4_K_M.gguf
sha256: 07e91d2c6d4e42312e65a69c54f16be467575f7a596fe052993b388e38b90d76
uri: huggingface://mradermacher/magnum-12b-v2.5-kto-i1-GGUF/magnum-12b-v2.5-kto.i1-Q4_K_M.gguf
- !!merge <<: *mistral03
url: "github:mudler/LocalAI/gallery/chatml.yaml@master"
name: "chatty-harry_v3.0"
icon: https://cdn-uploads.huggingface.co/production/uploads/66c1cc08453a7ef6c5fe657a/0KzNTEtn2kJJQsw4lQeY0.png
urls:
- https://huggingface.co/Triangle104/Chatty-Harry_V3.0
- https://huggingface.co/QuantFactory/Chatty-Harry_V3.0-GGUF
description: |
This model was merged using the TIES merge method using Triangle104/ChatWaifu_Magnum_V0.2 as a base.
The following models were included in the merge: elinas/Chronos-Gold-12B-1.0
overrides:
parameters:
model: Chatty-Harry_V3.0.Q4_K_M.gguf
files:
- filename: Chatty-Harry_V3.0.Q4_K_M.gguf
sha256: 54b63bb74498576ca77b801ed096657a93cc2f6b71d707c3605fdb394bd3e622
uri: huggingface://QuantFactory/Chatty-Harry_V3.0-GGUF/Chatty-Harry_V3.0.Q4_K_M.gguf
- !!merge <<: *mistral03
url: "github:mudler/LocalAI/gallery/chatml.yaml@master"
name: "mn-chunky-lotus-12b"
icon: https://huggingface.co/FallenMerick/MN-Chunky-Lotus-12B/resolve/main/chunky-lotus.jpg
urls:
- https://huggingface.co/QuantFactory/MN-Chunky-Lotus-12B-GGUF
description: |
I had originally planned to use this model for future/further merges, but decided to go ahead and release it since it scored rather high on my local EQ Bench testing (79.58 w/ 100% parsed @ 8-bit).
Bear in mind that most models tend to score a bit higher on my own local tests as compared to their posted scores. Still, its the highest score I've personally seen from all the models I've tested.
Its a decent model, with great emotional intelligence and acceptable adherence to various character personalities. It does a good job at roleplaying despite being a bit bland at times.
Overall, I like the way it writes, but it has a few formatting issues that show up from time to time, and it has an uncommon tendency to paste walls of character feelings/intentions at the end of some outputs without any prompting. This is something I hope to correct with future iterations.
This is a merge of pre-trained language models created using mergekit.
The following models were included in the merge:
Epiculous/Violet_Twilight-v0.2
nbeerbower/mistral-nemo-gutenberg-12B-v4
flammenai/Mahou-1.5-mistral-nemo-12B
overrides:
parameters:
model: MN-Chunky-Lotus-12B.Q4_K_M.gguf
files:
- filename: MN-Chunky-Lotus-12B.Q4_K_M.gguf
sha256: 363defe0a769fdb715dab75517966a0a80bcdd981a610d4c759099b6c8ff143a
uri: huggingface://QuantFactory/MN-Chunky-Lotus-12B-GGUF/MN-Chunky-Lotus-12B.Q4_K_M.gguf
- &mudler
### START mudler's LocalAI specific-models
url: "github:mudler/LocalAI/gallery/mudler.yaml@master"
@@ -5350,39 +4681,6 @@
- filename: G2-9B-Sugarquill-v0.Q4_K_M.gguf
sha256: 790a2f1541011b2773e22aa863ef78c8662baaa7eca5875e9573007985120187
uri: huggingface://QuantFactory/G2-9B-Sugarquill-v0-GGUF/G2-9B-Sugarquill-v0.Q4_K_M.gguf
- !!merge <<: *gemma
name: "volare-i1"
urls:
- https://huggingface.co/MoxoffSpA/Volare
- https://huggingface.co/mradermacher/Volare-i1-GGUF
description: |
Volare is an updated version of Gemma7B, specifically fine-tuned with SFT and LoRA adjustments.
It's trained on publicly available datasets, like SQUAD-it, and datasets we've created in-house.
it's designed to understand and maintain context, making it ideal for Retrieval Augmented Generation (RAG) tasks and applications requiring contextual awareness.
Italian dataset.
overrides:
parameters:
model: Volare.i1-Q4_K_M.gguf
files:
- filename: Volare.i1-Q4_K_M.gguf
sha256: fa8fb9d4cb19fcb44be8d53561c9e2840f45aed738de545983ebb158ebba461b
uri: huggingface://mradermacher/Volare-i1-GGUF/Volare.i1-Q4_K_M.gguf
- !!merge <<: *gemma
name: "bggpt-gemma-2-2.6b-it-v1.0"
icon: https://cdn-uploads.huggingface.co/production/uploads/637e1f8cf7e01589cc17bf7e/p6d0YFHjWCQ3S12jWqO1m.png
urls:
- https://huggingface.co/QuantFactory/BgGPT-Gemma-2-2.6B-IT-v1.0-GGUF
- https://huggingface.co/QuantFactory/BgGPT-Gemma-2-2.6B-IT-v1.0-GGUF
description: |
INSAIT introduces BgGPT-Gemma-2-2.6B-IT-v1.0, a state-of-the-art Bulgarian language model based on google/gemma-2-2b and google/gemma-2-2b-it. BgGPT-Gemma-2-2.6B-IT-v1.0 is free to use and distributed under the Gemma Terms of Use. This model was created by INSAIT, part of Sofia University St. Kliment Ohridski, in Sofia, Bulgaria.
The model was built on top of Googles Gemma 2 2B open models. It was continuously pre-trained on around 100 billion tokens (85 billion in Bulgarian) using the Branch-and-Merge strategy INSAIT presented at EMNLP24, allowing the model to gain outstanding Bulgarian cultural and linguistic capabilities while retaining its English performance. During the pre-training stage, we use various datasets, including Bulgarian web crawl data, freely available datasets such as Wikipedia, a range of specialized Bulgarian datasets sourced by the INSAIT Institute, and machine translations of popular English datasets. The model was then instruction-fine-tuned on a newly constructed Bulgarian instruction dataset created using real-world conversations. For more information check our blogpost.
overrides:
parameters:
model: BgGPT-Gemma-2-2.6B-IT-v1.0.Q4_K_M.gguf
files:
- filename: BgGPT-Gemma-2-2.6B-IT-v1.0.Q4_K_M.gguf
sha256: 1e92fe80ccad80e97076ee26b002c2280f075dfe2507d534b46a4391a077f319
uri: huggingface://QuantFactory/BgGPT-Gemma-2-2.6B-IT-v1.0-GGUF/BgGPT-Gemma-2-2.6B-IT-v1.0.Q4_K_M.gguf
- &llama3
url: "github:mudler/LocalAI/gallery/llama3-instruct.yaml@master"
icon: https://cdn-uploads.huggingface.co/production/uploads/642cc1c253e76b4c2286c58e/aJJxKus1wP5N-euvHEUq7.png
@@ -8008,27 +7306,6 @@
- filename: LLAMA-3_8B_Unaligned_BETA-Q4_K_M.gguf
sha256: 5b88fb4537339996c04e4a1b6ef6a2d555c4103b6378e273ae9c6c5e77af67eb
uri: huggingface://bartowski/LLAMA-3_8B_Unaligned_BETA-GGUF/LLAMA-3_8B_Unaligned_BETA-Q4_K_M.gguf
- !!merge <<: *llama3
name: "freyja-v4.95-maldv-7b-non-fiction-i1"
urls:
- https://huggingface.co/MrRobotoAI/Freyja-v4.95-maldv-7b-NON-FICTION
- https://huggingface.co/mradermacher/Freyja-v4.95-maldv-7b-NON-FICTION-i1-GGUF
description: |
This model was merged using the Model Stock merge method using aifeifei798/llama3-8B-DarkIdol-2.2-Uncensored-1048K as a base.
The following models were included in the merge:
maldv/llama-3-fantasy-writer-8b
maldv/badger-iota-llama-3-8b
maldv/badger-lambda-llama-3-8b
maldv/badger-mu-llama-3-8b
maldv/badger-kappa-llama-3-8b
maldv/badger-writer-llama-3-8b
overrides:
parameters:
model: Freyja-v4.95-maldv-7b-NON-FICTION.i1-Q4_K_M.gguf
files:
- filename: Freyja-v4.95-maldv-7b-NON-FICTION.i1-Q4_K_M.gguf
sha256: cdc0f4de6df2ba120835fbd25c2a0ae2af8548f46d2c40c7a018c51c3d19e0c0
uri: huggingface://mradermacher/Freyja-v4.95-maldv-7b-NON-FICTION-i1-GGUF/Freyja-v4.95-maldv-7b-NON-FICTION.i1-Q4_K_M.gguf
- &chatml
### ChatML
url: "github:mudler/LocalAI/gallery/chatml.yaml@master"
@@ -8256,43 +7533,6 @@
- filename: Meta-Llama-3-8B-Instruct-exp5-11-Q4_K_M.gguf
sha256: 5dd81b8b809667d10036499affdd1461cf95af50b405cbc9f800b421a4b60e98
uri: huggingface://DavidAU/Meta-Llama-3-Instruct-8.9B-BRAINSTORM-5x-FORM-11-GGUF/Meta-Llama-3-8B-Instruct-exp5-11-Q4_K_M.gguf
- !!merge <<: *llama3
name: "rp-naughty-v1.0c-8b"
urls:
- https://huggingface.co/QuantFactory/RP-Naughty-v1.0c-8b-GGUF
description: |
This model was merged using the Model Stock merge method using aifeifei798/llama3-8B-DarkIdol-2.2-Uncensored-1048K as a base.
The following models were included in the merge:
underwoods/adventure-8b
Khetterman/Multilingual-SaigaSuzume-8B
underwoods/writer-8b
Khetterman/Kosmos-8B-v1
Khetterman/CursedMatrix-8B-v9
overrides:
parameters:
model: RP-Naughty-v1.0c-8b.Q4_K_M.gguf
files:
- filename: RP-Naughty-v1.0c-8b.Q4_K_M.gguf
sha256: c344564d26d0c3d244d31cfeb103666eab37f9dee6678a2dbaf5bfcf4109d789
uri: huggingface://QuantFactory/RP-Naughty-v1.0c-8b-GGUF/RP-Naughty-v1.0c-8b.Q4_K_M.gguf
- !!merge <<: *llama3
name: "bio-medical-llama-3-8b"
icon: https://cdn-uploads.huggingface.co/production/uploads/653f5b93cd52f288490edc83/zPMUugzfOiwTiRw88jm7T.jpeg
urls:
- https://huggingface.co/ContactDoctor/Bio-Medical-Llama-3-8B
- https://huggingface.co/QuantFactory/Bio-Medical-Llama-3-8B-GGUF
description: |
Bio-Medical-Llama-3-8B model is a specialized large language model designed for biomedical applications. It is finetuned from the meta-llama/Meta-Llama-3-8B-Instruct model using a custom dataset containing over 500,000 diverse entries. These entries include a mix of synthetic and manually curated data, ensuring high quality and broad coverage of biomedical topics.
The model is trained to understand and generate text related to various biomedical fields, making it a valuable tool for researchers, clinicians, and other professionals in the biomedical domain.
overrides:
parameters:
model: Bio-Medical-Llama-3-8B.Q4_K_M.gguf
files:
- filename: Bio-Medical-Llama-3-8B.Q4_K_M.gguf
sha256: 672939e0487d02c55734132c25a59f26e4deaac7cd49445a7028f2291139edcc
uri: huggingface://QuantFactory/Bio-Medical-Llama-3-8B-GGUF/Bio-Medical-Llama-3-8B.Q4_K_M.gguf
- &command-R
### START Command-r
url: "github:mudler/LocalAI/gallery/command-r.yaml@master"
@@ -9308,43 +8548,6 @@
overrides:
parameters:
model: black-forest-labs/FLUX.1-schnell
- name: flux.1-dev-ggml
license: flux-1-dev-non-commercial-license
url: "github:mudler/LocalAI/gallery/flux-ggml.yaml@master"
description: |
FLUX.1 [dev] is a 12 billion parameter rectified flow transformer capable of generating images from text descriptions. For more information, please read our blog post.
Key Features
Cutting-edge output quality, second only to our state-of-the-art model FLUX.1 [pro].
Competitive prompt following, matching the performance of closed source alternatives .
Trained using guidance distillation, making FLUX.1 [dev] more efficient.
Open weights to drive new scientific research, and empower artists to develop innovative workflows.
Generated outputs can be used for personal, scientific, and commercial purposes as described in the flux-1-dev-non-commercial-license.
This model is quantized with GGUF
urls:
- https://huggingface.co/black-forest-labs/FLUX.1-dev
- https://huggingface.co/city96/FLUX.1-dev-gguf
tags:
- text-to-image
- flux
- gpu
- cpu
icon: https://huggingface.co/black-forest-labs/FLUX.1-schnell/resolve/main/schnell_grid.jpeg
overrides:
parameters:
model: flux1-dev-Q2_K.gguf
files:
- filename: "flux1-dev-Q2_K.gguf"
sha256: "b8c464bc0f10076ef8f00ba040d220d90c7993f7c4245ae80227d857f65df105"
uri: "huggingface://city96/FLUX.1-dev-gguf/flux1-dev-Q2_K.gguf"
- filename: ae.safetensors
sha256: afc8e28272cd15db3919bacdb6918ce9c1ed22e96cb12c4d5ed0fba823529e38
uri: https://huggingface.co/ChuckMcSneed/FLUX.1-dev/resolve/main/ae.safetensors
- filename: clip_l.safetensors
sha256: 660c6f5b1abae9dc498ac2d21e1347d2abdb0cf6c0c0c8576cd796491d9a6cdd
uri: https://huggingface.co/comfyanonymous/flux_text_encoders/resolve/main/clip_l.safetensors
- filename: t5xxl_fp16.safetensors
sha256: 6e480b09fae049a72d2a8c5fbccb8d3e92febeb233bbe9dfe7256958a9167635
uri: https://huggingface.co/comfyanonymous/flux_text_encoders/resolve/main/t5xxl_fp16.safetensors
- &whisper
## Whisper
url: "github:mudler/LocalAI/gallery/whisper-base.yaml@master"
@@ -9506,13 +8709,16 @@
- filename: "ggml-model-whisper-tiny.en-q8_0.bin"
uri: "https://ggml.ggerganov.com/ggml-model-whisper-tiny.en-q8_0.bin"
sha256: 5bc2b3860aa151a4c6e7bb095e1fcce7cf12c7b020ca08dcec0c6d018bb7dd94
## Bert embeddings (llama3.2 drop-in)
- !!merge <<: *llama32
## Bert embeddings
- url: "github:mudler/LocalAI/gallery/bert-embeddings.yaml@master"
name: "bert-embeddings"
description: |
llama3.2 embeddings model. Using as drop-in replacement for bert-embeddings
license: "Apache 2.0"
urls:
- https://huggingface.co/skeskinen/ggml
tags:
- embeddings
description: |
Bert model that can be used for embeddings
## Stable Diffusion
- url: github:mudler/LocalAI/gallery/stablediffusion.yaml@master
license: "BSD-3"
@@ -10130,22 +9336,3 @@
- filename: silero-vad.onnx
uri: https://huggingface.co/onnx-community/silero-vad/resolve/main/onnx/model.onnx
sha256: a4a068cd6cf1ea8355b84327595838ca748ec29a25bc91fc82e6c299ccdc5808
- name: "bark-cpp-small"
url: github:mudler/LocalAI/gallery/virtual.yaml@master
license: mit
urls:
- https://huggingface.co/suno/bark
- https://huggingface.co/Green-Sky/bark-ggml
description: |
Bark is a transformer-based text-to-audio model created by Suno. Bark can generate highly realistic, multilingual speech as well as other audio - including music, background noise and simple sound effects. The model can also produce nonverbal communications like laughing, sighing and crying. To support the research community, we are providing access to pretrained model checkpoints ready for inference.
tags:
- tts
- cpu
overrides:
backend: bark-cpp
parameters:
model: bark-small_weights-f16.bin
files:
- filename: bark-small_weights-f16.bin
uri: https://huggingface.co/Green-Sky/bark-ggml/resolve/main/bark-small_weights-f16.bin
sha256: de1ece17e8319537b3a7909baebbd28affab23c942d5d57e648d622af4e2feaa

View File

@@ -1,24 +0,0 @@
---
name: "rwkv"
config_file: |
parameters:
top_k: 80
temperature: 0.9
max_tokens: 4098
top_p: 0.8
context_size: 4098
roles:
user: "User: "
system: "System: "
assistant: "Assistant: "
stopwords:
- 'Assistant:'
- '<s>'
template:
chat: "{{.Input}}\nAssistant: "
completion: |
{{.Input}}

8
gallery/silero-vad.yaml Normal file
View File

@@ -0,0 +1,8 @@
---
name: "silero-vad"
config_file: |
name: vad
backend: silero-vad
parameters:
model: silero_vad.onnx

5
go.mod
View File

@@ -76,7 +76,6 @@ require (
cloud.google.com/go/auth v0.4.1 // indirect
cloud.google.com/go/auth/oauth2adapt v0.2.2 // indirect
cloud.google.com/go/compute/metadata v0.3.0 // indirect
github.com/dustin/go-humanize v1.0.1 // indirect
github.com/envoyproxy/protoc-gen-validate v1.0.4 // indirect
github.com/fasthttp/websocket v1.5.3 // indirect
github.com/felixge/httpsnoop v1.0.4 // indirect
@@ -85,12 +84,8 @@ require (
github.com/google/s2a-go v0.1.7 // indirect
github.com/googleapis/enterprise-certificate-proxy v0.3.2 // indirect
github.com/googleapis/gax-go/v2 v2.12.4 // indirect
github.com/json-iterator/go v1.1.12 // indirect
github.com/moby/docker-image-spec v1.3.1 // indirect
github.com/modern-go/concurrent v0.0.0-20180306012644-bacd9c7ef1dd // indirect
github.com/modern-go/reflect2 v1.0.2 // indirect
github.com/munnerz/goautoneg v0.0.0-20191010083416-a7dc8b61c822 // indirect
github.com/nikolalohinski/gonja/v2 v2.3.2 // indirect
github.com/pion/datachannel v1.5.8 // indirect
github.com/pion/dtls/v2 v2.2.12 // indirect
github.com/pion/ice/v2 v2.3.34 // indirect

12
go.sum
View File

@@ -140,8 +140,6 @@ github.com/dsnet/compress v0.0.2-0.20210315054119-f66993602bf5 h1:iFaUwBSo5Svw6L
github.com/dsnet/compress v0.0.2-0.20210315054119-f66993602bf5/go.mod h1:qssHWj60/X5sZFNxpG4HBPDHVqxNm4DfnCKgrbZOT+s=
github.com/dsnet/golib v0.0.0-20171103203638-1ea166775780/go.mod h1:Lj+Z9rebOhdfkVLjJ8T6VcRQv3SXugXy999NBtR9aFY=
github.com/dustin/go-humanize v1.0.0/go.mod h1:HtrtbFcZ19U5GC7JDqmcUSB87Iq5E25KnS6fMYU6eOk=
github.com/dustin/go-humanize v1.0.1 h1:GzkhY7T5VNhEkwH0PVJgjz+fX1rhBrR7pRT3mDkpeCY=
github.com/dustin/go-humanize v1.0.1/go.mod h1:Mu1zIs6XwVuF/gI1OepvI0qD18qycQx+mFykh5fBlto=
github.com/elastic/gosigar v0.12.0/go.mod h1:iXRIGg2tLnu7LBdpqzyQfGDEidKCfWcCMS0WKyPWoMs=
github.com/elastic/gosigar v0.14.3 h1:xwkKwPia+hSfg9GqrCUKYdId102m9qTJIIr7egmK/uo=
github.com/elastic/gosigar v0.14.3/go.mod h1:iXRIGg2tLnu7LBdpqzyQfGDEidKCfWcCMS0WKyPWoMs=
@@ -270,7 +268,6 @@ github.com/google/go-containerregistry v0.19.2 h1:TannFKE1QSajsP6hPWb5oJNgKe1IKj
github.com/google/go-containerregistry v0.19.2/go.mod h1:YCMFNQeeXeLF+dnhhWkqDItx/JSkH01j1Kis4PsjzFI=
github.com/google/go-github v17.0.0+incompatible/go.mod h1:zLgOLi98H3fifZn+44m+umXrS52loVEgC2AApnigrVQ=
github.com/google/go-querystring v1.0.0/go.mod h1:odCYkC5MyYFN7vkCjXpyrEuKhc/BUO6wN/zVPAxq5ck=
github.com/google/gofuzz v1.0.0/go.mod h1:dBl0BpW6vV/+mYPU4Po3pmUjxk6FQPldtuIdl/M65Eg=
github.com/google/gopacket v1.1.19 h1:ves8RnFZPGiFnTS0uPQStjwru6uO6h+nlr9j6fL7kF8=
github.com/google/gopacket v1.1.19/go.mod h1:iJ8V8n6KS+z2U1A8pUwu8bW5SyEMkXJB8Yo/Vo+TKTo=
github.com/google/martian v2.1.0+incompatible/go.mod h1:9I4somxYTbIHy5NJKHRl3wXiIaQGbYVAs8BPL6v8lEs=
@@ -356,8 +353,6 @@ github.com/joho/godotenv v1.5.1/go.mod h1:f4LDr5Voq0i2e/R5DDNOoa2zzDfwtkZa6DnEwA
github.com/josharian/intern v1.0.0 h1:vlS4z54oSdjm0bgjRigI+G1HpF+tI+9rE5LLzOg8HmY=
github.com/josharian/intern v1.0.0/go.mod h1:5DoeVV0s6jJacbCEi61lwdGj/aVlrQvzHFFd8Hwg//Y=
github.com/json-iterator/go v1.1.6/go.mod h1:+SdeFBvtyEkXs7REEP0seUULqWtbJapLOCVDaaPEHmU=
github.com/json-iterator/go v1.1.12 h1:PV8peI4a0ysnczrg+LtxykD8LfKY9ML6u2jnxaEnrnM=
github.com/json-iterator/go v1.1.12/go.mod h1:e30LSqwooZae/UwlEbR2852Gd8hjQvJoHmT4TnhNGBo=
github.com/jstemmer/go-junit-report v0.0.0-20190106144839-af01ea7f8024/go.mod h1:6v2b51hI/fHJwM22ozAgKL4VKDeJcHhJFhtBdhmNjmU=
github.com/jtolds/gls v4.20.0+incompatible h1:xdiiI2gbIgH/gLH7ADydsJ1uDOEzR8yvV7C0MuV77Wo=
github.com/jtolds/gls v4.20.0+incompatible/go.mod h1:QJZ7F/aHp+rZTRtaJ1ow/lLfFfVYBRgL+9YlvaHOwJU=
@@ -479,12 +474,8 @@ github.com/moby/sys/sequential v0.5.0 h1:OPvI35Lzn9K04PBbCLW0g4LcFAJgHsvXsRyewg5
github.com/moby/sys/sequential v0.5.0/go.mod h1:tH2cOOs5V9MlPiXcQzRC+eEyab644PWKGRYaaV5ZZlo=
github.com/moby/term v0.5.0 h1:xt8Q1nalod/v7BqbG21f8mQPqH+xAaC9C3N3wfWbVP0=
github.com/moby/term v0.5.0/go.mod h1:8FzsFHVUBGZdbDsJw/ot+X+d5HLUbvklYLJ9uGfcI3Y=
github.com/modern-go/concurrent v0.0.0-20180228061459-e0a39a4cb421/go.mod h1:6dJC0mAP4ikYIbvyc7fijjWJddQyLn8Ig3JB5CqoB9Q=
github.com/modern-go/concurrent v0.0.0-20180306012644-bacd9c7ef1dd h1:TRLaZ9cD/w8PVh93nsPXa1VrQ6jlwL5oN8l14QlcNfg=
github.com/modern-go/concurrent v0.0.0-20180306012644-bacd9c7ef1dd/go.mod h1:6dJC0mAP4ikYIbvyc7fijjWJddQyLn8Ig3JB5CqoB9Q=
github.com/modern-go/reflect2 v1.0.1/go.mod h1:bx2lNnkwVCuqBIxFjflWJWanXIb3RllmbCylyMrvgv0=
github.com/modern-go/reflect2 v1.0.2 h1:xBagoLtFs94CBntxluKeaWgTMpvLxC4ur3nMaC9Gz0M=
github.com/modern-go/reflect2 v1.0.2/go.mod h1:yWuevngMOJpCy52FWWMvUC8ws7m/LJsjYzDa0/r8luk=
github.com/mr-tron/base58 v1.1.2/go.mod h1:BinMc/sQntlIE1frQmRFPUoPA1Zkr8VRgBdjWI2mNwc=
github.com/mr-tron/base58 v1.2.0 h1:T/HDJBh4ZCPbU39/+c3rRvE0uKBQlU27+QI8LJ4t64o=
github.com/mr-tron/base58 v1.2.0/go.mod h1:BinMc/sQntlIE1frQmRFPUoPA1Zkr8VRgBdjWI2mNwc=
@@ -528,9 +519,6 @@ github.com/munnerz/goautoneg v0.0.0-20191010083416-a7dc8b61c822 h1:C3w9PqII01/Oq
github.com/munnerz/goautoneg v0.0.0-20191010083416-a7dc8b61c822/go.mod h1:+n7T8mK8HuQTcFwEeznm/DIxMOiR9yIdICNftLE1DvQ=
github.com/neelance/astrewrite v0.0.0-20160511093645-99348263ae86/go.mod h1:kHJEU3ofeGjhHklVoIGuVj85JJwZ6kWPaJwCIxgnFmo=
github.com/neelance/sourcemap v0.0.0-20151028013722-8c68805598ab/go.mod h1:Qr6/a/Q4r9LP1IltGz7tA7iOK1WonHEYhu1HRBA7ZiM=
github.com/nikolalohinski/gonja v1.5.3 h1:GsA+EEaZDZPGJ8JtpeGN78jidhOlxeJROpqMT9fTj9c=
github.com/nikolalohinski/gonja/v2 v2.3.2 h1:UgLFfqi7L9XfX0PEcE4eUpvGojVQL5KhBfJJaBp7ZxY=
github.com/nikolalohinski/gonja/v2 v2.3.2/go.mod h1:1Wcc/5huTu6y36e0sOFR1XQoFlylw3c3H3L5WOz0RDg=
github.com/nwaples/rardecode v1.1.0 h1:vSxaY8vQhOcVr4mm5e8XllHWTiM4JF507A0Katqw7MQ=
github.com/nwaples/rardecode v1.1.0/go.mod h1:5DzqNKiOdpKKBH87u8VlvAnPZMXcGRhxWkRpHbbfGS0=
github.com/nxadm/tail v1.4.11 h1:8feyoE3OzPrcshW5/MJ4sGESc5cqmGkGCWlco4l0bqY=

View File

@@ -45,6 +45,7 @@ const (
LLamaCPPGRPC = "llama-cpp-grpc"
BertEmbeddingsBackend = "bert-embeddings"
WhisperBackend = "whisper"
StableDiffusionBackend = "stablediffusion"
TinyDreamBackend = "tinydream"
@@ -153,6 +154,8 @@ func orderBackends(backends map[string][]string) ([]string, error) {
toTheEnd := []string{
// last has to be huggingface
LCHuggingFaceBackend,
// then bert embeddings
BertEmbeddingsBackend,
}
// create an ordered map

View File

@@ -9,6 +9,8 @@ import (
"sync"
"time"
"github.com/mudler/LocalAI/pkg/templates"
"github.com/mudler/LocalAI/pkg/utils"
"github.com/rs/zerolog/log"
@@ -21,6 +23,7 @@ type ModelLoader struct {
ModelPath string
mu sync.Mutex
models map[string]*Model
templates *templates.TemplateCache
wd *WatchDog
}
@@ -28,6 +31,7 @@ func NewModelLoader(modelPath string) *ModelLoader {
nml := &ModelLoader{
ModelPath: modelPath,
models: make(map[string]*Model),
templates: templates.NewTemplateCache(modelPath),
}
return nml

52
pkg/model/template.go Normal file
View File

@@ -0,0 +1,52 @@
package model
import (
"fmt"
"github.com/mudler/LocalAI/pkg/functions"
"github.com/mudler/LocalAI/pkg/templates"
)
// Rather than pass an interface{} to the prompt template:
// These are the definitions of all possible variables LocalAI will currently populate for use in a prompt template file
// Please note: Not all of these are populated on every endpoint - your template should either be tested for each endpoint you map it to, or tolerant of zero values.
type PromptTemplateData struct {
SystemPrompt string
SuppressSystemPrompt bool // used by chat specifically to indicate that SystemPrompt above should be _ignored_
Input string
Instruction string
Functions []functions.Function
MessageIndex int
}
type ChatMessageTemplateData struct {
SystemPrompt string
Role string
RoleName string
FunctionName string
Content string
MessageIndex int
Function bool
FunctionCall interface{}
LastMessage bool
}
const (
ChatPromptTemplate templates.TemplateType = iota
ChatMessageTemplate
CompletionPromptTemplate
EditPromptTemplate
FunctionsPromptTemplate
)
func (ml *ModelLoader) EvaluateTemplateForPrompt(templateType templates.TemplateType, templateName string, in PromptTemplateData) (string, error) {
// TODO: should this check be improved?
if templateType == ChatMessageTemplate {
return "", fmt.Errorf("invalid templateType: ChatMessage")
}
return ml.templates.EvaluateTemplate(templateType, templateName, in)
}
func (ml *ModelLoader) EvaluateTemplateForChatMessage(templateName string, messageData ChatMessageTemplateData) (string, error) {
return ml.templates.EvaluateTemplate(ChatMessageTemplate, templateName, messageData)
}

197
pkg/model/template_test.go Normal file
View File

@@ -0,0 +1,197 @@
package model_test
import (
. "github.com/mudler/LocalAI/pkg/model"
. "github.com/onsi/ginkgo/v2"
. "github.com/onsi/gomega"
)
const chatML = `<|im_start|>{{if eq .RoleName "assistant"}}assistant{{else if eq .RoleName "system"}}system{{else if eq .RoleName "tool"}}tool{{else if eq .RoleName "user"}}user{{end}}
{{- if .FunctionCall }}
<tool_call>
{{- else if eq .RoleName "tool" }}
<tool_response>
{{- end }}
{{- if .Content}}
{{.Content }}
{{- end }}
{{- if .FunctionCall}}
{{toJson .FunctionCall}}
{{- end }}
{{- if .FunctionCall }}
</tool_call>
{{- else if eq .RoleName "tool" }}
</tool_response>
{{- end }}<|im_end|>`
const llama3 = `<|start_header_id|>{{if eq .RoleName "assistant"}}assistant{{else if eq .RoleName "system"}}system{{else if eq .RoleName "tool"}}tool{{else if eq .RoleName "user"}}user{{end}}<|end_header_id|>
{{ if .FunctionCall -}}
Function call:
{{ else if eq .RoleName "tool" -}}
Function response:
{{ end -}}
{{ if .Content -}}
{{.Content -}}
{{ else if .FunctionCall -}}
{{ toJson .FunctionCall -}}
{{ end -}}
<|eot_id|>`
var llama3TestMatch map[string]map[string]interface{} = map[string]map[string]interface{}{
"user": {
"template": llama3,
"expected": "<|start_header_id|>user<|end_header_id|>\n\nA long time ago in a galaxy far, far away...<|eot_id|>",
"data": ChatMessageTemplateData{
SystemPrompt: "",
Role: "user",
RoleName: "user",
Content: "A long time ago in a galaxy far, far away...",
FunctionCall: nil,
FunctionName: "",
LastMessage: false,
Function: false,
MessageIndex: 0,
},
},
"assistant": {
"template": llama3,
"expected": "<|start_header_id|>assistant<|end_header_id|>\n\nA long time ago in a galaxy far, far away...<|eot_id|>",
"data": ChatMessageTemplateData{
SystemPrompt: "",
Role: "assistant",
RoleName: "assistant",
Content: "A long time ago in a galaxy far, far away...",
FunctionCall: nil,
FunctionName: "",
LastMessage: false,
Function: false,
MessageIndex: 0,
},
},
"function_call": {
"template": llama3,
"expected": "<|start_header_id|>assistant<|end_header_id|>\n\nFunction call:\n{\"function\":\"test\"}<|eot_id|>",
"data": ChatMessageTemplateData{
SystemPrompt: "",
Role: "assistant",
RoleName: "assistant",
Content: "",
FunctionCall: map[string]string{"function": "test"},
FunctionName: "",
LastMessage: false,
Function: false,
MessageIndex: 0,
},
},
"function_response": {
"template": llama3,
"expected": "<|start_header_id|>tool<|end_header_id|>\n\nFunction response:\nResponse from tool<|eot_id|>",
"data": ChatMessageTemplateData{
SystemPrompt: "",
Role: "tool",
RoleName: "tool",
Content: "Response from tool",
FunctionCall: nil,
FunctionName: "",
LastMessage: false,
Function: false,
MessageIndex: 0,
},
},
}
var chatMLTestMatch map[string]map[string]interface{} = map[string]map[string]interface{}{
"user": {
"template": chatML,
"expected": "<|im_start|>user\nA long time ago in a galaxy far, far away...<|im_end|>",
"data": ChatMessageTemplateData{
SystemPrompt: "",
Role: "user",
RoleName: "user",
Content: "A long time ago in a galaxy far, far away...",
FunctionCall: nil,
FunctionName: "",
LastMessage: false,
Function: false,
MessageIndex: 0,
},
},
"assistant": {
"template": chatML,
"expected": "<|im_start|>assistant\nA long time ago in a galaxy far, far away...<|im_end|>",
"data": ChatMessageTemplateData{
SystemPrompt: "",
Role: "assistant",
RoleName: "assistant",
Content: "A long time ago in a galaxy far, far away...",
FunctionCall: nil,
FunctionName: "",
LastMessage: false,
Function: false,
MessageIndex: 0,
},
},
"function_call": {
"template": chatML,
"expected": "<|im_start|>assistant\n<tool_call>\n{\"function\":\"test\"}\n</tool_call><|im_end|>",
"data": ChatMessageTemplateData{
SystemPrompt: "",
Role: "assistant",
RoleName: "assistant",
Content: "",
FunctionCall: map[string]string{"function": "test"},
FunctionName: "",
LastMessage: false,
Function: false,
MessageIndex: 0,
},
},
"function_response": {
"template": chatML,
"expected": "<|im_start|>tool\n<tool_response>\nResponse from tool\n</tool_response><|im_end|>",
"data": ChatMessageTemplateData{
SystemPrompt: "",
Role: "tool",
RoleName: "tool",
Content: "Response from tool",
FunctionCall: nil,
FunctionName: "",
LastMessage: false,
Function: false,
MessageIndex: 0,
},
},
}
var _ = Describe("Templates", func() {
Context("chat message ChatML", func() {
var modelLoader *ModelLoader
BeforeEach(func() {
modelLoader = NewModelLoader("")
})
for key := range chatMLTestMatch {
foo := chatMLTestMatch[key]
It("renders correctly `"+key+"`", func() {
templated, err := modelLoader.EvaluateTemplateForChatMessage(foo["template"].(string), foo["data"].(ChatMessageTemplateData))
Expect(err).ToNot(HaveOccurred())
Expect(templated).To(Equal(foo["expected"]), templated)
})
}
})
Context("chat message llama3", func() {
var modelLoader *ModelLoader
BeforeEach(func() {
modelLoader = NewModelLoader("")
})
for key := range llama3TestMatch {
foo := llama3TestMatch[key]
It("renders correctly `"+key+"`", func() {
templated, err := modelLoader.EvaluateTemplateForChatMessage(foo["template"].(string), foo["data"].(ChatMessageTemplateData))
Expect(err).ToNot(HaveOccurred())
Expect(templated).To(Equal(foo["expected"]), templated)
})
}
})
})

View File

@@ -11,41 +11,59 @@ import (
"github.com/mudler/LocalAI/pkg/utils"
"github.com/Masterminds/sprig/v3"
"github.com/nikolalohinski/gonja/v2"
"github.com/nikolalohinski/gonja/v2/exec"
)
// Keep this in sync with config.TemplateConfig. Is there a more idiomatic way to accomplish this in go?
// Technically, order doesn't _really_ matter, but the count must stay in sync, see tests/integration/reflect_test.go
type TemplateType int
type templateCache struct {
mu sync.Mutex
templatesPath string
templates map[TemplateType]map[string]*template.Template
jinjaTemplates map[TemplateType]map[string]*exec.Template
type TemplateCache struct {
mu sync.Mutex
templatesPath string
templates map[TemplateType]map[string]*template.Template
}
func newTemplateCache(templatesPath string) *templateCache {
tc := &templateCache{
templatesPath: templatesPath,
templates: make(map[TemplateType]map[string]*template.Template),
jinjaTemplates: make(map[TemplateType]map[string]*exec.Template),
func NewTemplateCache(templatesPath string) *TemplateCache {
tc := &TemplateCache{
templatesPath: templatesPath,
templates: make(map[TemplateType]map[string]*template.Template),
}
return tc
}
func (tc *templateCache) initializeTemplateMapKey(tt TemplateType) {
func (tc *TemplateCache) initializeTemplateMapKey(tt TemplateType) {
if _, ok := tc.templates[tt]; !ok {
tc.templates[tt] = make(map[string]*template.Template)
}
}
func (tc *templateCache) existsInModelPath(s string) bool {
return utils.ExistsInPath(tc.templatesPath, s)
func (tc *TemplateCache) EvaluateTemplate(templateType TemplateType, templateName string, in interface{}) (string, error) {
tc.mu.Lock()
defer tc.mu.Unlock()
tc.initializeTemplateMapKey(templateType)
m, ok := tc.templates[templateType][templateName]
if !ok {
// return "", fmt.Errorf("template not loaded: %s", templateName)
loadErr := tc.loadTemplateIfExists(templateType, templateName)
if loadErr != nil {
return "", loadErr
}
m = tc.templates[templateType][templateName] // ok is not important since we check m on the next line, and wealready checked
}
if m == nil {
return "", fmt.Errorf("failed loading a template for %s", templateName)
}
var buf bytes.Buffer
if err := m.Execute(&buf, in); err != nil {
return "", err
}
return buf.String(), nil
}
func (tc *templateCache) loadTemplateIfExists(templateType TemplateType, templateName string) error {
func (tc *TemplateCache) loadTemplateIfExists(templateType TemplateType, templateName string) error {
// Check if the template was already loaded
if _, ok := tc.templates[templateType][templateName]; ok {
@@ -64,51 +82,6 @@ func (tc *templateCache) loadTemplateIfExists(templateType TemplateType, templat
return fmt.Errorf("template file outside path: %s", file)
}
// can either be a file in the system or a string with the template
if tc.existsInModelPath(modelTemplateFile) {
d, err := os.ReadFile(file)
if err != nil {
return err
}
dat = string(d)
} else {
dat = templateName
}
// Parse the template
tmpl, err := template.New("prompt").Funcs(sprig.FuncMap()).Parse(dat)
if err != nil {
return err
}
tc.templates[templateType][templateName] = tmpl
return nil
}
func (tc *templateCache) initializeJinjaTemplateMapKey(tt TemplateType) {
if _, ok := tc.jinjaTemplates[tt]; !ok {
tc.jinjaTemplates[tt] = make(map[string]*exec.Template)
}
}
func (tc *templateCache) loadJinjaTemplateIfExists(templateType TemplateType, templateName string) error {
// Check if the template was already loaded
if _, ok := tc.jinjaTemplates[templateType][templateName]; ok {
return nil
}
// Check if the model path exists
// skip any error here - we run anyway if a template does not exist
modelTemplateFile := fmt.Sprintf("%s.tmpl", templateName)
dat := ""
file := filepath.Join(tc.templatesPath, modelTemplateFile)
// Security check
if err := utils.VerifyPath(modelTemplateFile, tc.templatesPath); err != nil {
return fmt.Errorf("template file outside path: %s", file)
}
// can either be a file in the system or a string with the template
if utils.ExistsInPath(tc.templatesPath, modelTemplateFile) {
d, err := os.ReadFile(file)
@@ -120,65 +93,12 @@ func (tc *templateCache) loadJinjaTemplateIfExists(templateType TemplateType, te
dat = templateName
}
tmpl, err := gonja.FromString(dat)
// Parse the template
tmpl, err := template.New("prompt").Funcs(sprig.FuncMap()).Parse(dat)
if err != nil {
return err
}
tc.jinjaTemplates[templateType][templateName] = tmpl
tc.templates[templateType][templateName] = tmpl
return nil
}
func (tc *templateCache) evaluateJinjaTemplate(templateType TemplateType, templateNameOrContent string, in map[string]interface{}) (string, error) {
tc.mu.Lock()
defer tc.mu.Unlock()
tc.initializeJinjaTemplateMapKey(templateType)
m, ok := tc.jinjaTemplates[templateType][templateNameOrContent]
if !ok {
// return "", fmt.Errorf("template not loaded: %s", templateName)
loadErr := tc.loadJinjaTemplateIfExists(templateType, templateNameOrContent)
if loadErr != nil {
return "", loadErr
}
m = tc.jinjaTemplates[templateType][templateNameOrContent] // ok is not important since we check m on the next line, and wealready checked
}
if m == nil {
return "", fmt.Errorf("failed loading a template for %s", templateNameOrContent)
}
var buf bytes.Buffer
data := exec.NewContext(in)
if err := m.Execute(&buf, data); err != nil {
return "", err
}
return buf.String(), nil
}
func (tc *templateCache) evaluateTemplate(templateType TemplateType, templateNameOrContent string, in interface{}) (string, error) {
tc.mu.Lock()
defer tc.mu.Unlock()
tc.initializeTemplateMapKey(templateType)
m, ok := tc.templates[templateType][templateNameOrContent]
if !ok {
// return "", fmt.Errorf("template not loaded: %s", templateName)
loadErr := tc.loadTemplateIfExists(templateType, templateNameOrContent)
if loadErr != nil {
return "", loadErr
}
m = tc.templates[templateType][templateNameOrContent] // ok is not important since we check m on the next line, and wealready checked
}
if m == nil {
return "", fmt.Errorf("failed loading a template for %s", templateNameOrContent)
}
var buf bytes.Buffer
if err := m.Execute(&buf, in); err != nil {
return "", err
}
return buf.String(), nil
}

View File

@@ -0,0 +1,73 @@
package templates_test
import (
"os"
"path/filepath"
"github.com/mudler/LocalAI/pkg/templates" // Update with your module path
. "github.com/onsi/ginkgo/v2"
. "github.com/onsi/gomega"
)
var _ = Describe("TemplateCache", func() {
var (
templateCache *templates.TemplateCache
tempDir string
)
BeforeEach(func() {
var err error
tempDir, err = os.MkdirTemp("", "templates")
Expect(err).NotTo(HaveOccurred())
// Writing example template files
err = os.WriteFile(filepath.Join(tempDir, "example.tmpl"), []byte("Hello, {{.Name}}!"), 0600)
Expect(err).NotTo(HaveOccurred())
err = os.WriteFile(filepath.Join(tempDir, "empty.tmpl"), []byte(""), 0600)
Expect(err).NotTo(HaveOccurred())
templateCache = templates.NewTemplateCache(tempDir)
})
AfterEach(func() {
os.RemoveAll(tempDir) // Clean up
})
Describe("EvaluateTemplate", func() {
Context("when template is loaded successfully", func() {
It("should evaluate the template correctly", func() {
result, err := templateCache.EvaluateTemplate(1, "example", map[string]string{"Name": "Gopher"})
Expect(err).NotTo(HaveOccurred())
Expect(result).To(Equal("Hello, Gopher!"))
})
})
Context("when template isn't a file", func() {
It("should parse from string", func() {
result, err := templateCache.EvaluateTemplate(1, "{{.Name}}", map[string]string{"Name": "Gopher"})
Expect(err).ToNot(HaveOccurred())
Expect(result).To(Equal("Gopher"))
})
})
Context("when template is empty", func() {
It("should return an empty string", func() {
result, err := templateCache.EvaluateTemplate(1, "empty", nil)
Expect(err).NotTo(HaveOccurred())
Expect(result).To(Equal(""))
})
})
})
Describe("concurrency", func() {
It("should handle multiple concurrent accesses", func(done Done) {
go func() {
_, _ = templateCache.EvaluateTemplate(1, "example", map[string]string{"Name": "Gopher"})
}()
go func() {
_, _ = templateCache.EvaluateTemplate(1, "example", map[string]string{"Name": "Gopher"})
}()
close(done)
}, 0.1) // timeout in seconds
})
})

View File

@@ -1,295 +0,0 @@
package templates
import (
"encoding/json"
"fmt"
"strings"
"github.com/mudler/LocalAI/core/config"
"github.com/mudler/LocalAI/core/schema"
"github.com/mudler/LocalAI/pkg/functions"
"github.com/rs/zerolog/log"
)
// Rather than pass an interface{} to the prompt template:
// These are the definitions of all possible variables LocalAI will currently populate for use in a prompt template file
// Please note: Not all of these are populated on every endpoint - your template should either be tested for each endpoint you map it to, or tolerant of zero values.
type PromptTemplateData struct {
SystemPrompt string
SuppressSystemPrompt bool // used by chat specifically to indicate that SystemPrompt above should be _ignored_
Input string
Instruction string
Functions []functions.Function
MessageIndex int
}
type ChatMessageTemplateData struct {
SystemPrompt string
Role string
RoleName string
FunctionName string
Content string
MessageIndex int
Function bool
FunctionCall interface{}
LastMessage bool
}
const (
ChatPromptTemplate TemplateType = iota
ChatMessageTemplate
CompletionPromptTemplate
EditPromptTemplate
FunctionsPromptTemplate
)
type Evaluator struct {
cache *templateCache
}
func NewEvaluator(modelPath string) *Evaluator {
return &Evaluator{
cache: newTemplateCache(modelPath),
}
}
func (e *Evaluator) EvaluateTemplateForPrompt(templateType TemplateType, config config.BackendConfig, in PromptTemplateData) (string, error) {
template := ""
// A model can have a "file.bin.tmpl" file associated with a prompt template prefix
if e.cache.existsInModelPath(fmt.Sprintf("%s.tmpl", config.Model)) {
template = config.Model
}
switch templateType {
case CompletionPromptTemplate:
if config.TemplateConfig.Completion != "" {
template = config.TemplateConfig.Completion
}
case EditPromptTemplate:
if config.TemplateConfig.Edit != "" {
template = config.TemplateConfig.Edit
}
case ChatPromptTemplate:
if config.TemplateConfig.Chat != "" {
template = config.TemplateConfig.Chat
}
case FunctionsPromptTemplate:
if config.TemplateConfig.Functions != "" {
template = config.TemplateConfig.Functions
}
}
if template == "" {
return in.Input, nil
}
if config.TemplateConfig.JinjaTemplate {
return e.evaluateJinjaTemplateForPrompt(templateType, template, in)
}
return e.cache.evaluateTemplate(templateType, template, in)
}
func (e *Evaluator) evaluateTemplateForChatMessage(templateName string, messageData ChatMessageTemplateData) (string, error) {
return e.cache.evaluateTemplate(ChatMessageTemplate, templateName, messageData)
}
func (e *Evaluator) templateJinjaChat(templateName string, messageData []ChatMessageTemplateData, funcs []functions.Function) (string, error) {
conversation := make(map[string]interface{})
messages := make([]map[string]interface{}, len(messageData))
// convert from ChatMessageTemplateData to what the jinja template expects
for _, message := range messageData {
// TODO: this seems to cover minimum text templates. Can be expanded to cover more complex interactions
var data []byte
data, _ = json.Marshal(message.FunctionCall)
messages = append(messages, map[string]interface{}{
"role": message.RoleName,
"content": message.Content,
"tool_call": string(data),
})
}
conversation["messages"] = messages
// if tools are detected, add these
if len(funcs) > 0 {
conversation["tools"] = funcs
}
return e.cache.evaluateJinjaTemplate(ChatMessageTemplate, templateName, conversation)
}
func (e *Evaluator) evaluateJinjaTemplateForPrompt(templateType TemplateType, templateName string, in PromptTemplateData) (string, error) {
conversation := make(map[string]interface{})
conversation["system_prompt"] = in.SystemPrompt
conversation["content"] = in.Input
return e.cache.evaluateJinjaTemplate(templateType, templateName, conversation)
}
func (e *Evaluator) TemplateMessages(messages []schema.Message, config *config.BackendConfig, funcs []functions.Function, shouldUseFn bool) string {
if config.TemplateConfig.JinjaTemplate {
var messageData []ChatMessageTemplateData
for messageIndex, i := range messages {
fcall := i.FunctionCall
if len(i.ToolCalls) > 0 {
fcall = i.ToolCalls
}
messageData = append(messageData, ChatMessageTemplateData{
SystemPrompt: config.SystemPrompt,
Role: config.Roles[i.Role],
RoleName: i.Role,
Content: i.StringContent,
FunctionCall: fcall,
FunctionName: i.Name,
LastMessage: messageIndex == (len(messages) - 1),
Function: config.Grammar != "" && (messageIndex == (len(messages) - 1)),
MessageIndex: messageIndex,
})
}
templatedInput, err := e.templateJinjaChat(config.TemplateConfig.ChatMessage, messageData, funcs)
if err == nil {
return templatedInput
}
}
var predInput string
suppressConfigSystemPrompt := false
mess := []string{}
for messageIndex, i := range messages {
var content string
role := i.Role
// if function call, we might want to customize the role so we can display better that the "assistant called a json action"
// if an "assistant_function_call" role is defined, we use it, otherwise we use the role that is passed by in the request
if (i.FunctionCall != nil || i.ToolCalls != nil) && i.Role == "assistant" {
roleFn := "assistant_function_call"
r := config.Roles[roleFn]
if r != "" {
role = roleFn
}
}
r := config.Roles[role]
contentExists := i.Content != nil && i.StringContent != ""
fcall := i.FunctionCall
if len(i.ToolCalls) > 0 {
fcall = i.ToolCalls
}
// First attempt to populate content via a chat message specific template
if config.TemplateConfig.ChatMessage != "" {
chatMessageData := ChatMessageTemplateData{
SystemPrompt: config.SystemPrompt,
Role: r,
RoleName: role,
Content: i.StringContent,
FunctionCall: fcall,
FunctionName: i.Name,
LastMessage: messageIndex == (len(messages) - 1),
Function: config.Grammar != "" && (messageIndex == (len(messages) - 1)),
MessageIndex: messageIndex,
}
templatedChatMessage, err := e.evaluateTemplateForChatMessage(config.TemplateConfig.ChatMessage, chatMessageData)
if err != nil {
log.Error().Err(err).Interface("message", chatMessageData).Str("template", config.TemplateConfig.ChatMessage).Msg("error processing message with template, skipping")
} else {
if templatedChatMessage == "" {
log.Warn().Msgf("template \"%s\" produced blank output for %+v. Skipping!", config.TemplateConfig.ChatMessage, chatMessageData)
continue // TODO: This continue is here intentionally to skip over the line `mess = append(mess, content)` below, and to prevent the sprintf
}
log.Debug().Msgf("templated message for chat: %s", templatedChatMessage)
content = templatedChatMessage
}
}
marshalAnyRole := func(f any) {
j, err := json.Marshal(f)
if err == nil {
if contentExists {
content += "\n" + fmt.Sprint(r, " ", string(j))
} else {
content = fmt.Sprint(r, " ", string(j))
}
}
}
marshalAny := func(f any) {
j, err := json.Marshal(f)
if err == nil {
if contentExists {
content += "\n" + string(j)
} else {
content = string(j)
}
}
}
// If this model doesn't have such a template, or if that template fails to return a value, template at the message level.
if content == "" {
if r != "" {
if contentExists {
content = fmt.Sprint(r, i.StringContent)
}
if i.FunctionCall != nil {
marshalAnyRole(i.FunctionCall)
}
if i.ToolCalls != nil {
marshalAnyRole(i.ToolCalls)
}
} else {
if contentExists {
content = fmt.Sprint(i.StringContent)
}
if i.FunctionCall != nil {
marshalAny(i.FunctionCall)
}
if i.ToolCalls != nil {
marshalAny(i.ToolCalls)
}
}
// Special Handling: System. We care if it was printed at all, not the r branch, so check seperately
if contentExists && role == "system" {
suppressConfigSystemPrompt = true
}
}
mess = append(mess, content)
}
joinCharacter := "\n"
if config.TemplateConfig.JoinChatMessagesByCharacter != nil {
joinCharacter = *config.TemplateConfig.JoinChatMessagesByCharacter
}
predInput = strings.Join(mess, joinCharacter)
log.Debug().Msgf("Prompt (before templating): %s", predInput)
promptTemplate := ChatPromptTemplate
if config.TemplateConfig.Functions != "" && shouldUseFn {
promptTemplate = FunctionsPromptTemplate
}
templatedInput, err := e.EvaluateTemplateForPrompt(promptTemplate, *config, PromptTemplateData{
SystemPrompt: config.SystemPrompt,
SuppressSystemPrompt: suppressConfigSystemPrompt,
Input: predInput,
Functions: funcs,
})
if err == nil {
predInput = templatedInput
log.Debug().Msgf("Template found, input modified to: %s", predInput)
} else {
log.Debug().Msgf("Template failed loading: %s", err.Error())
}
return predInput
}

View File

@@ -1,253 +0,0 @@
package templates_test
import (
"github.com/mudler/LocalAI/core/config"
"github.com/mudler/LocalAI/core/schema"
"github.com/mudler/LocalAI/pkg/functions"
. "github.com/mudler/LocalAI/pkg/templates"
. "github.com/onsi/ginkgo/v2"
. "github.com/onsi/gomega"
)
const toolCallJinja = `{{ '<|begin_of_text|>' }}{% if messages[0]['role'] == 'system' %}{% set system_message = messages[0]['content'] %}{% endif %}{% if system_message is defined %}{{ '<|start_header_id|>system<|end_header_id|>
' + system_message + '<|eot_id|>' }}{% endif %}{% for message in messages %}{% set content = message['content'] %}{% if message['role'] == 'user' %}{{ '<|start_header_id|>user<|end_header_id|>
' + content + '<|eot_id|><|start_header_id|>assistant<|end_header_id|>
' }}{% elif message['role'] == 'assistant' %}{{ content + '<|eot_id|>' }}{% endif %}{% endfor %}`
const chatML = `<|im_start|>{{if eq .RoleName "assistant"}}assistant{{else if eq .RoleName "system"}}system{{else if eq .RoleName "tool"}}tool{{else if eq .RoleName "user"}}user{{end}}
{{- if .FunctionCall }}
<tool_call>
{{- else if eq .RoleName "tool" }}
<tool_response>
{{- end }}
{{- if .Content}}
{{.Content }}
{{- end }}
{{- if .FunctionCall}}
{{toJson .FunctionCall}}
{{- end }}
{{- if .FunctionCall }}
</tool_call>
{{- else if eq .RoleName "tool" }}
</tool_response>
{{- end }}<|im_end|>`
const llama3 = `<|start_header_id|>{{if eq .RoleName "assistant"}}assistant{{else if eq .RoleName "system"}}system{{else if eq .RoleName "tool"}}tool{{else if eq .RoleName "user"}}user{{end}}<|end_header_id|>
{{ if .FunctionCall -}}
Function call:
{{ else if eq .RoleName "tool" -}}
Function response:
{{ end -}}
{{ if .Content -}}
{{.Content -}}
{{ else if .FunctionCall -}}
{{ toJson .FunctionCall -}}
{{ end -}}
<|eot_id|>`
var llama3TestMatch map[string]map[string]interface{} = map[string]map[string]interface{}{
"user": {
"expected": "<|start_header_id|>user<|end_header_id|>\n\nA long time ago in a galaxy far, far away...<|eot_id|>",
"config": &config.BackendConfig{
TemplateConfig: config.TemplateConfig{
ChatMessage: llama3,
},
},
"functions": []functions.Function{},
"shouldUseFn": false,
"messages": []schema.Message{
{
Role: "user",
StringContent: "A long time ago in a galaxy far, far away...",
},
},
},
"assistant": {
"expected": "<|start_header_id|>assistant<|end_header_id|>\n\nA long time ago in a galaxy far, far away...<|eot_id|>",
"config": &config.BackendConfig{
TemplateConfig: config.TemplateConfig{
ChatMessage: llama3,
},
},
"functions": []functions.Function{},
"messages": []schema.Message{
{
Role: "assistant",
StringContent: "A long time ago in a galaxy far, far away...",
},
},
"shouldUseFn": false,
},
"function_call": {
"expected": "<|start_header_id|>assistant<|end_header_id|>\n\nFunction call:\n{\"function\":\"test\"}<|eot_id|>",
"config": &config.BackendConfig{
TemplateConfig: config.TemplateConfig{
ChatMessage: llama3,
},
},
"functions": []functions.Function{},
"messages": []schema.Message{
{
Role: "assistant",
FunctionCall: map[string]string{"function": "test"},
},
},
"shouldUseFn": false,
},
"function_response": {
"expected": "<|start_header_id|>tool<|end_header_id|>\n\nFunction response:\nResponse from tool<|eot_id|>",
"config": &config.BackendConfig{
TemplateConfig: config.TemplateConfig{
ChatMessage: llama3,
},
},
"functions": []functions.Function{},
"messages": []schema.Message{
{
Role: "tool",
StringContent: "Response from tool",
},
},
"shouldUseFn": false,
},
}
var chatMLTestMatch map[string]map[string]interface{} = map[string]map[string]interface{}{
"user": {
"expected": "<|im_start|>user\nA long time ago in a galaxy far, far away...<|im_end|>",
"config": &config.BackendConfig{
TemplateConfig: config.TemplateConfig{
ChatMessage: chatML,
},
},
"functions": []functions.Function{},
"shouldUseFn": false,
"messages": []schema.Message{
{
Role: "user",
StringContent: "A long time ago in a galaxy far, far away...",
},
},
},
"assistant": {
"expected": "<|im_start|>assistant\nA long time ago in a galaxy far, far away...<|im_end|>",
"config": &config.BackendConfig{
TemplateConfig: config.TemplateConfig{
ChatMessage: chatML,
},
},
"functions": []functions.Function{},
"messages": []schema.Message{
{
Role: "assistant",
StringContent: "A long time ago in a galaxy far, far away...",
},
},
"shouldUseFn": false,
},
"function_call": {
"expected": "<|im_start|>assistant\n<tool_call>\n{\"function\":\"test\"}\n</tool_call><|im_end|>",
"config": &config.BackendConfig{
TemplateConfig: config.TemplateConfig{
ChatMessage: chatML,
},
},
"functions": []functions.Function{
{
Name: "test",
Description: "test",
Parameters: nil,
},
},
"shouldUseFn": true,
"messages": []schema.Message{
{
Role: "assistant",
FunctionCall: map[string]string{"function": "test"},
},
},
},
"function_response": {
"expected": "<|im_start|>tool\n<tool_response>\nResponse from tool\n</tool_response><|im_end|>",
"config": &config.BackendConfig{
TemplateConfig: config.TemplateConfig{
ChatMessage: chatML,
},
},
"functions": []functions.Function{},
"shouldUseFn": false,
"messages": []schema.Message{
{
Role: "tool",
StringContent: "Response from tool",
},
},
},
}
var jinjaTest map[string]map[string]interface{} = map[string]map[string]interface{}{
"user": {
"expected": "<|begin_of_text|><|start_header_id|>user<|end_header_id|>\n\nA long time ago in a galaxy far, far away...<|eot_id|><|start_header_id|>assistant<|end_header_id|>\n\n",
"config": &config.BackendConfig{
TemplateConfig: config.TemplateConfig{
ChatMessage: toolCallJinja,
JinjaTemplate: true,
},
},
"functions": []functions.Function{},
"shouldUseFn": false,
"messages": []schema.Message{
{
Role: "user",
StringContent: "A long time ago in a galaxy far, far away...",
},
},
},
}
var _ = Describe("Templates", func() {
Context("chat message ChatML", func() {
var evaluator *Evaluator
BeforeEach(func() {
evaluator = NewEvaluator("")
})
for key := range chatMLTestMatch {
foo := chatMLTestMatch[key]
It("renders correctly `"+key+"`", func() {
templated := evaluator.TemplateMessages(foo["messages"].([]schema.Message), foo["config"].(*config.BackendConfig), foo["functions"].([]functions.Function), foo["shouldUseFn"].(bool))
Expect(templated).To(Equal(foo["expected"]), templated)
})
}
})
Context("chat message llama3", func() {
var evaluator *Evaluator
BeforeEach(func() {
evaluator = NewEvaluator("")
})
for key := range llama3TestMatch {
foo := llama3TestMatch[key]
It("renders correctly `"+key+"`", func() {
templated := evaluator.TemplateMessages(foo["messages"].([]schema.Message), foo["config"].(*config.BackendConfig), foo["functions"].([]functions.Function), foo["shouldUseFn"].(bool))
Expect(templated).To(Equal(foo["expected"]), templated)
})
}
})
Context("chat message jinja", func() {
var evaluator *Evaluator
BeforeEach(func() {
evaluator = NewEvaluator("")
})
for key := range jinjaTest {
foo := jinjaTest[key]
It("renders correctly `"+key+"`", func() {
templated := evaluator.TemplateMessages(foo["messages"].([]schema.Message), foo["config"].(*config.BackendConfig), foo["functions"].([]functions.Function), foo["shouldUseFn"].(bool))
Expect(templated).To(Equal(foo["expected"]), templated)
})
}
})
})

View File

@@ -103,10 +103,7 @@ if __name__ == "__main__":
if readmeFile:
# If there is a README file, read it
readme = fs.read_text(readmeFile)
try:
summarized_readme = summarize(readme)
except Exception as e:
print(f"Error summarizing the README: {str(e)}", file=sys.stderr)
summarized_readme = summarize(readme)
summarized_readme = format_description(summarized_readme)
print("Model correctly processed")

View File

@@ -1,4 +1,5 @@
name: text-embedding-ada-002
embeddings: true
parameters:
model: huggingface://hugging-quants/Llama-3.2-1B-Instruct-Q4_K_M-GGUF/llama-3.2-1b-instruct-q4_k_m.gguf
model: bert
backend: bert-embeddings
embeddings: true

View File

@@ -14,7 +14,6 @@ roles:
stopwords:
- 'Assistant:'
- '<s>'
template:
chat: |