mirror of
https://github.com/mudler/LocalAI.git
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feat(llama.cpp): add distributed llama.cpp inferencing (#2324)
* feat(llama.cpp): support distributed llama.cpp Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat: let tweak how chat messages are merged together Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * refactor Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Makefile: register to ALL_GRPC_BACKENDS Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * refactoring, allow disable auto-detection of backends Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * minor fixups Signed-off-by: mudler <mudler@localai.io> * feat: add cmd to start rpc-server from llama.cpp Signed-off-by: mudler <mudler@localai.io> * ci: add ccache Signed-off-by: mudler <mudler@localai.io> --------- Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Signed-off-by: mudler <mudler@localai.io>
This commit is contained in:
parent
29909666c3
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5
.env
5
.env
@ -71,6 +71,11 @@
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### Define the number of parallel LLAMA.cpp workers (Defaults to 1)
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# LLAMACPP_PARALLEL=1
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### Define a list of GRPC Servers for llama-cpp workers to distribute the load
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# https://github.com/ggerganov/llama.cpp/pull/6829
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# https://github.com/ggerganov/llama.cpp/blob/master/examples/rpc/README.md
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# LLAMACPP_GRPC_SERVERS=""
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### Enable to run parallel requests
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# LOCALAI_PARALLEL_REQUESTS=true
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4
.github/workflows/release.yaml
vendored
4
.github/workflows/release.yaml
vendored
@ -29,7 +29,7 @@ jobs:
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- name: Dependencies
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run: |
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sudo apt-get update
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sudo apt-get install build-essential ffmpeg protobuf-compiler
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sudo apt-get install build-essential ffmpeg protobuf-compiler ccache
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- name: Install CUDA Dependencies
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run: |
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curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64/cuda-keyring_1.1-1_all.deb
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@ -86,7 +86,7 @@ jobs:
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cache: false
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- name: Dependencies
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run: |
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sudo apt-get install -y --no-install-recommends libopencv-dev protobuf-compiler
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sudo apt-get install -y --no-install-recommends libopencv-dev protobuf-compiler ccache
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go install google.golang.org/grpc/cmd/protoc-gen-go-grpc@latest
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go install google.golang.org/protobuf/cmd/protoc-gen-go@latest
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- name: Build stablediffusion
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@ -19,6 +19,7 @@ ARG GO_TAGS="stablediffusion tinydream tts"
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RUN apt-get update && \
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apt-get install -y --no-install-recommends \
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build-essential \
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ccache \
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ca-certificates \
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cmake \
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curl \
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17
Makefile
17
Makefile
@ -5,7 +5,7 @@ BINARY_NAME=local-ai
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# llama.cpp versions
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GOLLAMA_STABLE_VERSION?=2b57a8ae43e4699d3dc5d1496a1ccd42922993be
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CPPLLAMA_VERSION?=dc685be46622a8fabfd57cfa804237c8f15679b8
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CPPLLAMA_VERSION?=4f0263633b40e94e8b69fd6e7e4395cfedfd5c12
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# gpt4all version
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GPT4ALL_REPO?=https://github.com/nomic-ai/gpt4all
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@ -158,6 +158,8 @@ ALL_GRPC_BACKENDS+=backend-assets/grpc/llama-cpp-avx
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ALL_GRPC_BACKENDS+=backend-assets/grpc/llama-cpp-avx2
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ALL_GRPC_BACKENDS+=backend-assets/grpc/llama-cpp-fallback
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ALL_GRPC_BACKENDS+=backend-assets/grpc/llama-ggml
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ALL_GRPC_BACKENDS+=backend-assets/grpc/llama-cpp-grpc
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ALL_GRPC_BACKENDS+=backend-assets/util/llama-cpp-rpc-server
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ALL_GRPC_BACKENDS+=backend-assets/grpc/gpt4all
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ALL_GRPC_BACKENDS+=backend-assets/grpc/rwkv
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ALL_GRPC_BACKENDS+=backend-assets/grpc/whisper
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@ -314,7 +316,7 @@ build: prepare backend-assets grpcs ## Build the project
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CGO_LDFLAGS="$(CGO_LDFLAGS)" $(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o $(BINARY_NAME) ./
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build-minimal:
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BUILD_GRPC_FOR_BACKEND_LLAMA=true GRPC_BACKENDS="backend-assets/grpc/llama-cpp" GO_TAGS=none $(MAKE) build
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BUILD_GRPC_FOR_BACKEND_LLAMA=true GRPC_BACKENDS="backend-assets/grpc/llama-cpp-avx2" GO_TAGS=none $(MAKE) build
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build-api:
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BUILD_GRPC_FOR_BACKEND_LLAMA=true BUILD_API_ONLY=true GO_TAGS=none $(MAKE) build
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@ -691,6 +693,17 @@ backend-assets/grpc/llama-cpp-cuda: backend-assets/grpc
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CMAKE_ARGS="$(CMAKE_ARGS) -DLLAMA_AVX=on -DLLAMA_AVX2=off -DLLAMA_AVX512=off -DLLAMA_FMA=off -DLLAMA_F16C=off -DLLAMA_CUDA=ON" $(MAKE) VARIANT="llama-cuda" build-llama-cpp-grpc-server
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cp -rfv backend/cpp/llama-cuda/grpc-server backend-assets/grpc/llama-cpp-cuda
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backend-assets/grpc/llama-cpp-grpc: backend-assets/grpc
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cp -rf backend/cpp/llama backend/cpp/llama-grpc
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$(MAKE) -C backend/cpp/llama-grpc purge
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$(info ${GREEN}I llama-cpp build info:grpc${RESET})
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CMAKE_ARGS="$(CMAKE_ARGS) -DLLAMA_RPC=ON -DLLAMA_AVX=off -DLLAMA_AVX2=off -DLLAMA_AVX512=off -DLLAMA_FMA=off -DLLAMA_F16C=off" $(MAKE) VARIANT="llama-grpc" build-llama-cpp-grpc-server
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cp -rfv backend/cpp/llama-grpc/grpc-server backend-assets/grpc/llama-cpp-grpc
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backend-assets/util/llama-cpp-rpc-server: backend-assets/grpc/llama-cpp-grpc
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mkdir -p backend-assets/util/
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cp -rf backend/cpp/llama-grpc/llama.cpp/build/bin/rpc-server backend-assets/util/llama-cpp-rpc-server
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backend-assets/grpc/llama-ggml: sources/go-llama.cpp sources/go-llama.cpp/libbinding.a backend-assets/grpc
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CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(CURDIR)/sources/go-llama.cpp LIBRARY_PATH=$(CURDIR)/sources/go-llama.cpp \
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$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/llama-ggml ./backend/go/llm/llama-ggml/
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@ -2217,6 +2217,12 @@ static void params_parse(const backend::ModelOptions* request,
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} else {
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params.n_parallel = 1;
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}
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const char *llama_grpc_servers = std::getenv("LLAMACPP_GRPC_SERVERS");
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if (llama_grpc_servers != NULL) {
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params.rpc_servers = std::string(llama_grpc_servers);
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}
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// TODO: Add yarn
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if (!request->tensorsplit().empty()) {
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@ -17,4 +17,5 @@ var CLI struct {
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Models ModelsCMD `cmd:"" help:"Manage LocalAI models and definitions"`
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TTS TTSCMD `cmd:"" help:"Convert text to speech"`
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Transcript TranscriptCMD `cmd:"" help:"Convert audio to text"`
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LLAMACPPWorker LLAMACPPWorkerCMD `cmd:"" help:"Run workers to distribute workload (llama.cpp-only)"`
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}
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37
core/cli/llamacppworker.go
Normal file
37
core/cli/llamacppworker.go
Normal file
@ -0,0 +1,37 @@
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package cli
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import (
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"os"
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"syscall"
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"github.com/go-skynet/LocalAI/pkg/assets"
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"github.com/rs/zerolog/log"
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)
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type LLAMACPPWorkerCMD struct {
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Args []string `arg:"" optional:"" name:"models" help:"Worker arguments: host port"`
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BackendAssetsPath string `env:"LOCALAI_BACKEND_ASSETS_PATH,BACKEND_ASSETS_PATH" type:"path" default:"/tmp/localai/backend_data" help:"Path used to extract libraries that are required by some of the backends in runtime" group:"storage"`
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}
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func (r *LLAMACPPWorkerCMD) Run(ctx *Context) error {
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// Extract files from the embedded FS
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err := assets.ExtractFiles(ctx.BackendAssets, r.BackendAssetsPath)
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log.Debug().Msgf("Extracting backend assets files to %s", r.BackendAssetsPath)
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if err != nil {
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log.Warn().Msgf("Failed extracting backend assets files: %s (might be required for some backends to work properly, like gpt4all)", err)
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}
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return syscall.Exec(
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assets.ResolvePath(
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r.BackendAssetsPath,
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"util",
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"llama-cpp-rpc-server",
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),
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append([]string{
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assets.ResolvePath(
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r.BackendAssetsPath,
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"util",
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"llama-cpp-rpc-server",
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)}, r.Args...),
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os.Environ())
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}
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@ -93,6 +93,8 @@ type Diffusers struct {
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ControlNet string `yaml:"control_net"`
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}
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// LLMConfig is a struct that holds the configuration that are
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// generic for most of the LLM backends.
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type LLMConfig struct {
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SystemPrompt string `yaml:"system_prompt"`
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TensorSplit string `yaml:"tensor_split"`
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@ -144,6 +146,7 @@ type LLMConfig struct {
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YarnBetaSlow float32 `yaml:"yarn_beta_slow"`
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}
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// AutoGPTQ is a struct that holds the configuration specific to the AutoGPTQ backend
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type AutoGPTQ struct {
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ModelBaseName string `yaml:"model_base_name"`
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Device string `yaml:"device"`
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@ -151,13 +154,31 @@ type AutoGPTQ struct {
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UseFastTokenizer bool `yaml:"use_fast_tokenizer"`
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}
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// TemplateConfig is a struct that holds the configuration of the templating system
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type TemplateConfig struct {
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// Chat is the template used in the chat completion endpoint
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Chat string `yaml:"chat"`
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// ChatMessage is the template used for chat messages
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ChatMessage string `yaml:"chat_message"`
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// Completion is the template used for completion requests
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Completion string `yaml:"completion"`
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// Edit is the template used for edit completion requests
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Edit string `yaml:"edit"`
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// Functions is the template used when tools are present in the client requests
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Functions string `yaml:"function"`
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// UseTokenizerTemplate is a flag that indicates if the tokenizer template should be used.
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// Note: this is mostly consumed for backends such as vllm and transformers
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// that can use the tokenizers specified in the JSON config files of the models
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UseTokenizerTemplate bool `yaml:"use_tokenizer_template"`
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// JoinChatMessagesByCharacter is a string that will be used to join chat messages together.
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// It defaults to \n
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JoinChatMessagesByCharacter *string `yaml:"join_chat_messages_by_character"`
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}
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func (c *BackendConfig) SetFunctionCallString(s string) {
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@ -349,7 +349,12 @@ func ChatEndpoint(cl *config.BackendConfigLoader, ml *model.ModelLoader, startup
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mess = append(mess, content)
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}
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predInput = strings.Join(mess, "\n")
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joinCharacter := "\n"
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if config.TemplateConfig.JoinChatMessagesByCharacter != nil {
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joinCharacter = *config.TemplateConfig.JoinChatMessagesByCharacter
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}
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predInput = strings.Join(mess, joinCharacter)
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log.Debug().Msgf("Prompt (before templating): %s", predInput)
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templateFile := ""
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@ -8,6 +8,10 @@ import (
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"path/filepath"
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)
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func ResolvePath(dir string, paths ...string) string {
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return filepath.Join(append([]string{dir, "backend-assets"}, paths...)...)
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}
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func ExtractFiles(content embed.FS, extractDir string) error {
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// Create the target directory if it doesn't exist
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err := os.MkdirAll(extractDir, 0750)
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@ -39,7 +43,7 @@ func ExtractFiles(content embed.FS, extractDir string) error {
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}
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// Create the file in the target directory
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err = os.WriteFile(targetFile, fileData, 0600)
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err = os.WriteFile(targetFile, fileData, 0700)
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if err != nil {
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return fmt.Errorf("failed to write file: %v", err)
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}
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@ -12,9 +12,9 @@ import (
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grpc "github.com/go-skynet/LocalAI/pkg/grpc"
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"github.com/go-skynet/LocalAI/pkg/xsysinfo"
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"github.com/klauspost/cpuid/v2"
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"github.com/phayes/freeport"
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"github.com/rs/zerolog/log"
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"golang.org/x/sys/cpu"
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"github.com/elliotchance/orderedmap/v2"
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)
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@ -26,16 +26,18 @@ var Aliases map[string]string = map[string]string{
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"langchain-huggingface": LCHuggingFaceBackend,
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}
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var autoDetect = os.Getenv("DISABLE_AUTODETECT") != "true"
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const (
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LlamaGGML = "llama-ggml"
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LLamaCPP = "llama-cpp"
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LLamaCPPCUDA12 = "llama-cpp-cuda12"
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LLamaCPPAVX2 = "llama-cpp-avx2"
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LLamaCPPAVX = "llama-cpp-avx"
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LLamaCPPFallback = "llama-cpp-fallback"
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LLamaCPPCUDA = "llama-cpp-cuda"
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LLamaCPPGRPC = "llama-cpp-grpc"
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Gpt4AllLlamaBackend = "gpt4all-llama"
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Gpt4AllMptBackend = "gpt4all-mpt"
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@ -59,7 +61,7 @@ func backendPath(assetDir, backend string) string {
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// backendsInAssetDir returns the list of backends in the asset directory
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// that should be loaded
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func backendsInAssetDir(assetDir string) (*orderedmap.OrderedMap[string, any], error) {
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func backendsInAssetDir(assetDir string) ([]string, error) {
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// Exclude backends from automatic loading
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excludeBackends := []string{LocalStoreBackend}
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entry, err := os.ReadDir(backendPath(assetDir, ""))
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@ -74,14 +76,24 @@ ENTRY:
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continue ENTRY
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}
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}
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if !e.IsDir() {
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if !strings.Contains(e.Name(), LLamaCPP) || strings.Contains(e.Name(), LLamaCPPFallback) {
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backends[e.Name()] = []string{}
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}
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}
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if e.IsDir() {
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continue
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}
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foundLCPPAVX, foundLCPPAVX2, foundLCPPFallback := false, false, false
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// Skip the llama.cpp variants if we are autoDetecting
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// But we always load the fallback variant if it exists
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if strings.Contains(e.Name(), LLamaCPP) && !strings.Contains(e.Name(), LLamaCPPFallback) && autoDetect {
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continue
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}
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backends[e.Name()] = []string{}
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}
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// if we are autoDetecting, we want to show the llama.cpp variants as a single backend
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if autoDetect {
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// if we find the llama.cpp variants, show them of as a single backend (llama-cpp) as later we are going to pick that up
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// when starting the service
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foundLCPPAVX, foundLCPPAVX2, foundLCPPFallback, foundLCPPGRPC, foundLCPPCuda := false, false, false, false, false
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if _, ok := backends[LLamaCPP]; !ok {
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for _, e := range entry {
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if strings.Contains(e.Name(), LLamaCPPAVX2) && !foundLCPPAVX2 {
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@ -96,16 +108,28 @@ ENTRY:
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backends[LLamaCPP] = append(backends[LLamaCPP], LLamaCPPFallback)
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foundLCPPFallback = true
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}
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if strings.Contains(e.Name(), LLamaCPPGRPC) && !foundLCPPGRPC {
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backends[LLamaCPP] = append(backends[LLamaCPP], LLamaCPPGRPC)
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foundLCPPGRPC = true
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}
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if strings.Contains(e.Name(), LLamaCPPCUDA) && !foundLCPPCuda {
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backends[LLamaCPP] = append(backends[LLamaCPP], LLamaCPPCUDA)
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foundLCPPCuda = true
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}
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}
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}
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}
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// order backends from the asset directory.
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// as we scan for backends, we want to keep some order which backends are tried of.
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// for example, llama.cpp should be tried first, and we want to keep the huggingface backend at the last.
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// sets a priority list
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// First has more priority
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// sets a priority list - first has more priority
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priorityList := []string{
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// First llama.cpp and llama-ggml
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// First llama.cpp(variants) and llama-ggml to follow.
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// We keep the fallback to prevent that if the llama.cpp variants
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// that depends on shared libs if breaks have still a safety net.
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LLamaCPP, LlamaGGML, Gpt4All, LLamaCPPFallback,
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}
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@ -139,7 +163,57 @@ ENTRY:
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}
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}
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return orderedBackends, nil
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return orderedBackends.Keys(), nil
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}
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// selectGRPCProcess selects the GRPC process to start based on system capabilities
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func selectGRPCProcess(backend, assetDir string) string {
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foundCUDA := false
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var grpcProcess string
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// Select backend now just for llama.cpp
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if backend != LLamaCPP {
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return ""
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}
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// Note: This environment variable is read by the LocalAI's llama.cpp grpc-server
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if os.Getenv("LLAMACPP_GRPC_SERVERS") != "" {
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log.Info().Msgf("[%s] attempting to load with GRPC variant", LLamaCPPGRPC)
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return backendPath(assetDir, LLamaCPPGRPC)
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}
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gpus, err := xsysinfo.GPUs()
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if err == nil {
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for _, gpu := range gpus {
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if strings.Contains(gpu.String(), "nvidia") {
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p := backendPath(assetDir, LLamaCPPCUDA)
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if _, err := os.Stat(p); err == nil {
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log.Info().Msgf("[%s] attempting to load with CUDA variant", backend)
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grpcProcess = p
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foundCUDA = true
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} else {
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log.Info().Msgf("GPU device found but no CUDA backend present")
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}
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}
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}
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}
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if foundCUDA {
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return grpcProcess
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}
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if xsysinfo.HasCPUCaps(cpuid.AVX2) {
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log.Info().Msgf("[%s] attempting to load with AVX2 variant", backend)
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grpcProcess = backendPath(assetDir, LLamaCPPAVX2)
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} else if xsysinfo.HasCPUCaps(cpuid.AVX) {
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log.Info().Msgf("[%s] attempting to load with AVX variant", backend)
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grpcProcess = backendPath(assetDir, LLamaCPPAVX)
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} else {
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log.Info().Msgf("[%s] attempting to load with fallback variant", backend)
|
||||
grpcProcess = backendPath(assetDir, LLamaCPPFallback)
|
||||
}
|
||||
|
||||
return grpcProcess
|
||||
}
|
||||
|
||||
// starts the grpcModelProcess for the backend, and returns a grpc client
|
||||
@ -192,33 +266,10 @@ func (ml *ModelLoader) grpcModel(backend string, o *Options) func(string, string
|
||||
} else {
|
||||
grpcProcess := backendPath(o.assetDir, backend)
|
||||
|
||||
foundCUDA := false
|
||||
// for llama-cpp, check CPU capabilities and load the appropriate variant
|
||||
if backend == LLamaCPP {
|
||||
gpus, err := xsysinfo.GPUs()
|
||||
if err == nil {
|
||||
for _, gpu := range gpus {
|
||||
if strings.Contains(gpu.String(), "nvidia") {
|
||||
log.Info().Msgf("[%s] attempting to load with CUDA variant", backend)
|
||||
grpcProcess = backendPath(o.assetDir, LLamaCPPCUDA)
|
||||
if _, err := os.Stat(grpcProcess); err == nil {
|
||||
foundCUDA = true
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
if !foundCUDA {
|
||||
if cpu.X86.HasAVX2 {
|
||||
log.Info().Msgf("[%s] attempting to load with AVX2 variant", backend)
|
||||
grpcProcess = backendPath(o.assetDir, LLamaCPPAVX2)
|
||||
} else if cpu.X86.HasAVX {
|
||||
log.Info().Msgf("[%s] attempting to load with AVX variant", backend)
|
||||
grpcProcess = backendPath(o.assetDir, LLamaCPPAVX)
|
||||
} else {
|
||||
log.Info().Msgf("[%s] attempting to load with fallback variant", backend)
|
||||
grpcProcess = backendPath(o.assetDir, LLamaCPPFallback)
|
||||
}
|
||||
if autoDetect {
|
||||
// autoDetect GRPC process to start based on system capabilities
|
||||
if selectedProcess := selectGRPCProcess(backend, o.assetDir); selectedProcess != "" {
|
||||
grpcProcess = selectedProcess
|
||||
}
|
||||
}
|
||||
|
||||
@ -363,28 +414,24 @@ func (ml *ModelLoader) GreedyLoader(opts ...Option) (grpc.Backend, error) {
|
||||
|
||||
var err error
|
||||
|
||||
// autoload also external backends
|
||||
allBackendsToAutoLoad := orderedmap.NewOrderedMap[string, any]()
|
||||
// get backends embedded in the binary
|
||||
autoLoadBackends, err := backendsInAssetDir(o.assetDir)
|
||||
if err != nil {
|
||||
return nil, err
|
||||
}
|
||||
|
||||
// append externalBackends supplied by the user via the CLI
|
||||
for _, b := range o.externalBackends {
|
||||
autoLoadBackends = append(autoLoadBackends, b)
|
||||
}
|
||||
|
||||
log.Debug().Msgf("Loading from the following backends (in order): %+v", autoLoadBackends)
|
||||
|
||||
for _, k := range autoLoadBackends.Keys() {
|
||||
v, _ := autoLoadBackends.Get(k)
|
||||
allBackendsToAutoLoad.Set(k, v)
|
||||
}
|
||||
|
||||
for _, b := range o.externalBackends {
|
||||
allBackendsToAutoLoad.Set(b, []string{})
|
||||
}
|
||||
|
||||
if o.model != "" {
|
||||
log.Info().Msgf("Trying to load the model '%s' with the backend '%s'", o.model, allBackendsToAutoLoad.Keys())
|
||||
log.Info().Msgf("Trying to load the model '%s' with the backend '%s'", o.model, autoLoadBackends)
|
||||
}
|
||||
|
||||
for _, key := range allBackendsToAutoLoad.Keys() {
|
||||
for _, key := range autoLoadBackends {
|
||||
log.Info().Msgf("[%s] Attempting to load", key)
|
||||
options := []Option{
|
||||
WithBackendString(key),
|
||||
|
Loading…
Reference in New Issue
Block a user