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chore(llama-ggml): drop deprecated backend (#4775)

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The GGML format is now dead, since in the next version of LocalAI we
already bring many breaking compatibility changes, taking the occasion
also to drop ggml support (pre-gguf).

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
This commit is contained in:
Ettore Di Giacinto 2025-02-06 18:36:23 +01:00 committed by GitHub
parent 8d45670e41
commit 7f90ff7aec
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GPG Key ID: B5690EEEBB952194
6 changed files with 7 additions and 348 deletions
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38
Makefile
View File

@ -6,8 +6,6 @@ BINARY_NAME=local-ai
DETECT_LIBS?=true
# llama.cpp versions
GOLLAMA_REPO?=https://github.com/go-skynet/go-llama.cpp
GOLLAMA_VERSION?=2b57a8ae43e4699d3dc5d1496a1ccd42922993be
CPPLLAMA_VERSION?=d774ab3acc4fee41fbed6dbfc192b57d5f79f34b
# whisper.cpp version
@ -151,7 +149,6 @@ ifeq ($(BUILD_TYPE),hipblas)
LD_LIBRARY_PATH ?= /opt/rocm/lib:/opt/rocm/llvm/lib
export CXX=$(ROCM_HOME)/llvm/bin/clang++
export CC=$(ROCM_HOME)/llvm/bin/clang
# llama-ggml has no hipblas support, so override it here.
export STABLE_BUILD_TYPE=
export GGML_HIP=1
GPU_TARGETS ?= gfx900,gfx906,gfx908,gfx940,gfx941,gfx942,gfx90a,gfx1030,gfx1031,gfx1100,gfx1101
@ -188,7 +185,6 @@ 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-avx512
ALL_GRPC_BACKENDS+=backend-assets/grpc/llama-cpp-fallback
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
@ -222,19 +218,6 @@ endif
all: help
## go-llama.cpp
sources/go-llama.cpp:
mkdir -p sources/go-llama.cpp
cd sources/go-llama.cpp && \
git init && \
git remote add origin $(GOLLAMA_REPO) && \
git fetch origin && \
git checkout $(GOLLAMA_VERSION) && \
git submodule update --init --recursive --depth 1 --single-branch
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 && \
@ -310,19 +293,17 @@ 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 backend/cpp/llama/llama.cpp
get-sources: sources/go-piper sources/stablediffusion-ggml.cpp sources/bark.cpp sources/whisper.cpp 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
$(GOCMD) mod edit -replace github.com/mudler/go-piper=$(CURDIR)/sources/go-piper
$(GOCMD) mod edit -replace github.com/go-skynet/go-llama.cpp=$(CURDIR)/sources/go-llama.cpp
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/mudler/go-piper
$(GOCMD) mod edit -dropreplace github.com/go-skynet/go-llama.cpp
prepare-sources: get-sources replace
$(GOCMD) mod download
@ -330,7 +311,6 @@ prepare-sources: get-sources replace
## GENERIC
rebuild: ## Rebuilds the project
$(GOCMD) clean -cache
$(MAKE) -C sources/go-llama.cpp clean
$(MAKE) -C sources/whisper.cpp clean
$(MAKE) -C sources/go-piper clean
$(MAKE) build
@ -434,7 +414,7 @@ run: prepare ## run local-ai
test-models/testmodel.ggml:
mkdir test-models
mkdir test-dir
wget -q https://huggingface.co/TheBloke/orca_mini_3B-GGML/resolve/main/orca-mini-3b.ggmlv3.q4_0.bin -O test-models/testmodel.ggml
wget -q https://huggingface.co/RichardErkhov/Qwen_-_Qwen2-1.5B-Instruct-gguf/resolve/main/Qwen2-1.5B-Instruct.Q2_K.gguf -O test-models/testmodel.ggml
wget -q https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-base.en.bin -O test-models/whisper-en
wget -q https://huggingface.co/mudler/all-MiniLM-L6-v2/resolve/main/ggml-model-q4_0.bin -O test-models/bert
wget -q https://cdn.openai.com/whisper/draft-20220913a/micro-machines.wav -O test-dir/audio.wav
@ -449,8 +429,7 @@ test: prepare test-models/testmodel.ggml grpcs
export GO_TAGS="tts debug"
$(MAKE) prepare-test
HUGGINGFACE_GRPC=$(abspath ./)/backend/python/transformers/run.sh TEST_DIR=$(abspath ./)/test-dir/ FIXTURES=$(abspath ./)/tests/fixtures CONFIG_FILE=$(abspath ./)/test-models/config.yaml MODELS_PATH=$(abspath ./)/test-models \
$(GOCMD) run github.com/onsi/ginkgo/v2/ginkgo --label-filter="!llama && !llama-gguf" --flake-attempts $(TEST_FLAKES) --fail-fast -v -r $(TEST_PATHS)
$(MAKE) test-llama
$(GOCMD) run github.com/onsi/ginkgo/v2/ginkgo --label-filter="!llama-gguf" --flake-attempts $(TEST_FLAKES) --fail-fast -v -r $(TEST_PATHS)
$(MAKE) test-llama-gguf
$(MAKE) test-tts
$(MAKE) test-stablediffusion
@ -479,10 +458,6 @@ teardown-e2e:
rm -rf $(TEST_DIR) || true
docker stop $$(docker ps -q --filter ancestor=localai-tests)
test-llama: prepare-test
TEST_DIR=$(abspath ./)/test-dir/ FIXTURES=$(abspath ./)/tests/fixtures CONFIG_FILE=$(abspath ./)/test-models/config.yaml MODELS_PATH=$(abspath ./)/test-models \
$(GOCMD) run github.com/onsi/ginkgo/v2/ginkgo --label-filter="llama" --flake-attempts $(TEST_FLAKES) -v -r $(TEST_PATHS)
test-llama-gguf: prepare-test
TEST_DIR=$(abspath ./)/test-dir/ FIXTURES=$(abspath ./)/tests/fixtures CONFIG_FILE=$(abspath ./)/test-models/config.yaml MODELS_PATH=$(abspath ./)/test-models \
$(GOCMD) run github.com/onsi/ginkgo/v2/ginkgo --label-filter="llama-gguf" --flake-attempts $(TEST_FLAKES) -v -r $(TEST_PATHS)
@ -760,13 +735,6 @@ backend-assets/util/llama-cpp-rpc-server: backend-assets/grpc/llama-cpp-grpc
mkdir -p backend-assets/util/
cp -rf backend/cpp/llama-grpc/llama.cpp/build/bin/rpc-server backend-assets/util/llama-cpp-rpc-server
backend-assets/grpc/llama-ggml: sources/go-llama.cpp sources/go-llama.cpp/libbinding.a backend-assets/grpc
CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(CURDIR)/sources/go-llama.cpp LIBRARY_PATH=$(CURDIR)/sources/go-llama.cpp \
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/llama-ggml ./backend/go/llm/llama-ggml/
ifneq ($(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/

204
backend/go/llm/llama-ggml/llama.go
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@ -1,204 +0,0 @@
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 (
"fmt"
"github.com/go-skynet/go-llama.cpp"
"github.com/mudler/LocalAI/pkg/grpc/base"
pb "github.com/mudler/LocalAI/pkg/grpc/proto"
)
type LLM struct {
base.SingleThread
llama *llama.LLama
}
func (llm *LLM) Load(opts *pb.ModelOptions) error {
ropeFreqBase := float32(10000)
ropeFreqScale := float32(1)
if opts.RopeFreqBase != 0 {
ropeFreqBase = opts.RopeFreqBase
}
if opts.RopeFreqScale != 0 {
ropeFreqScale = opts.RopeFreqScale
}
llamaOpts := []llama.ModelOption{
llama.WithRopeFreqBase(ropeFreqBase),
llama.WithRopeFreqScale(ropeFreqScale),
}
if opts.NGQA != 0 {
llamaOpts = append(llamaOpts, llama.WithGQA(int(opts.NGQA)))
}
if opts.RMSNormEps != 0 {
llamaOpts = append(llamaOpts, llama.WithRMSNormEPS(opts.RMSNormEps))
}
if opts.ContextSize != 0 {
llamaOpts = append(llamaOpts, llama.SetContext(int(opts.ContextSize)))
}
if opts.F16Memory {
llamaOpts = append(llamaOpts, llama.EnableF16Memory)
}
if opts.Embeddings {
llamaOpts = append(llamaOpts, llama.EnableEmbeddings)
}
if opts.NGPULayers != 0 {
llamaOpts = append(llamaOpts, llama.SetGPULayers(int(opts.NGPULayers)))
}
llamaOpts = append(llamaOpts, llama.SetMMap(opts.MMap))
llamaOpts = append(llamaOpts, llama.SetMainGPU(opts.MainGPU))
llamaOpts = append(llamaOpts, llama.SetTensorSplit(opts.TensorSplit))
if opts.NBatch != 0 {
llamaOpts = append(llamaOpts, llama.SetNBatch(int(opts.NBatch)))
} else {
llamaOpts = append(llamaOpts, llama.SetNBatch(512))
}
if opts.NUMA {
llamaOpts = append(llamaOpts, llama.EnableNUMA)
}
if opts.LowVRAM {
llamaOpts = append(llamaOpts, llama.EnabelLowVRAM)
}
model, err := llama.New(opts.ModelFile, llamaOpts...)
llm.llama = model
return err
}
func buildPredictOptions(opts *pb.PredictOptions) []llama.PredictOption {
ropeFreqBase := float32(10000)
ropeFreqScale := float32(1)
if opts.RopeFreqBase != 0 {
ropeFreqBase = opts.RopeFreqBase
}
if opts.RopeFreqScale != 0 {
ropeFreqScale = opts.RopeFreqScale
}
predictOptions := []llama.PredictOption{
llama.SetTemperature(opts.Temperature),
llama.SetTopP(opts.TopP),
llama.SetTopK(int(opts.TopK)),
llama.SetTokens(int(opts.Tokens)),
llama.SetThreads(int(opts.Threads)),
llama.WithGrammar(opts.Grammar),
llama.SetRopeFreqBase(ropeFreqBase),
llama.SetRopeFreqScale(ropeFreqScale),
llama.SetNegativePromptScale(opts.NegativePromptScale),
llama.SetNegativePrompt(opts.NegativePrompt),
}
if opts.PromptCacheAll {
predictOptions = append(predictOptions, llama.EnablePromptCacheAll)
}
if opts.PromptCacheRO {
predictOptions = append(predictOptions, llama.EnablePromptCacheRO)
}
// Expected absolute path
if opts.PromptCachePath != "" {
predictOptions = append(predictOptions, llama.SetPathPromptCache(opts.PromptCachePath))
}
if opts.Mirostat != 0 {
predictOptions = append(predictOptions, llama.SetMirostat(int(opts.Mirostat)))
}
if opts.MirostatETA != 0 {
predictOptions = append(predictOptions, llama.SetMirostatETA(opts.MirostatETA))
}
if opts.MirostatTAU != 0 {
predictOptions = append(predictOptions, llama.SetMirostatTAU(opts.MirostatTAU))
}
if opts.Debug {
predictOptions = append(predictOptions, llama.Debug)
}
predictOptions = append(predictOptions, llama.SetStopWords(opts.StopPrompts...))
if opts.PresencePenalty != 0 {
predictOptions = append(predictOptions, llama.SetPenalty(opts.PresencePenalty))
}
if opts.NKeep != 0 {
predictOptions = append(predictOptions, llama.SetNKeep(int(opts.NKeep)))
}
if opts.Batch != 0 {
predictOptions = append(predictOptions, llama.SetBatch(int(opts.Batch)))
}
if opts.F16KV {
predictOptions = append(predictOptions, llama.EnableF16KV)
}
if opts.IgnoreEOS {
predictOptions = append(predictOptions, llama.IgnoreEOS)
}
if opts.Seed != 0 {
predictOptions = append(predictOptions, llama.SetSeed(int(opts.Seed)))
}
//predictOptions = append(predictOptions, llama.SetLogitBias(c.Seed))
predictOptions = append(predictOptions, llama.SetFrequencyPenalty(opts.FrequencyPenalty))
predictOptions = append(predictOptions, llama.SetMlock(opts.MLock))
predictOptions = append(predictOptions, llama.SetMemoryMap(opts.MMap))
predictOptions = append(predictOptions, llama.SetPredictionMainGPU(opts.MainGPU))
predictOptions = append(predictOptions, llama.SetPredictionTensorSplit(opts.TensorSplit))
predictOptions = append(predictOptions, llama.SetTailFreeSamplingZ(opts.TailFreeSamplingZ))
predictOptions = append(predictOptions, llama.SetTypicalP(opts.TypicalP))
return predictOptions
}
func (llm *LLM) Predict(opts *pb.PredictOptions) (string, error) {
return llm.llama.Predict(opts.Prompt, buildPredictOptions(opts)...)
}
func (llm *LLM) PredictStream(opts *pb.PredictOptions, results chan string) error {
predictOptions := buildPredictOptions(opts)
predictOptions = append(predictOptions, llama.SetTokenCallback(func(token string) bool {
results <- token
return true
}))
go func() {
_, err := llm.llama.Predict(opts.Prompt, predictOptions...)
if err != nil {
fmt.Println("err: ", err)
}
close(results)
}()
return nil
}
func (llm *LLM) Embeddings(opts *pb.PredictOptions) ([]float32, error) {
predictOptions := buildPredictOptions(opts)
if len(opts.EmbeddingTokens) > 0 {
tokens := []int{}
for _, t := range opts.EmbeddingTokens {
tokens = append(tokens, int(t))
}
return llm.llama.TokenEmbeddings(tokens, predictOptions...)
}
return llm.llama.Embeddings(opts.Embeddings, predictOptions...)
}

19
backend/go/llm/llama-ggml/main.go
View File

@ -1,19 +0,0 @@
package main
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, &LLM{}); err != nil {
panic(err)
}
}

71
core/http/app_test.go
View File

@ -526,77 +526,6 @@ var _ = Describe("API test", func() {
Expect(content["usage"]).To(ContainSubstring("You can test this model with curl like this"))
})
It("runs openllama(llama-ggml backend)", Label("llama"), func() {
if runtime.GOOS != "linux" {
Skip("test supported only on linux")
}
response := postModelApplyRequest("http://127.0.0.1:9090/models/apply", modelApplyRequest{
URL: "github:go-skynet/model-gallery/openllama_3b.yaml",
Name: "openllama_3b",
Overrides: map[string]interface{}{"backend": "llama-ggml", "mmap": true, "f16": true, "context_size": 128},
})
Expect(response["uuid"]).ToNot(BeEmpty(), fmt.Sprint(response))
uuid := response["uuid"].(string)
Eventually(func() bool {
response := getModelStatus("http://127.0.0.1:9090/models/jobs/" + uuid)
return response["processed"].(bool)
}, "360s", "10s").Should(Equal(true))
By("testing completion")
resp, err := client.CreateCompletion(context.TODO(), openai.CompletionRequest{Model: "openllama_3b", Prompt: "Count up to five: one, two, three, four, "})
Expect(err).ToNot(HaveOccurred())
Expect(len(resp.Choices)).To(Equal(1))
Expect(resp.Choices[0].Text).To(ContainSubstring("five"))
By("testing functions")
resp2, err := client.CreateChatCompletion(
context.TODO(),
openai.ChatCompletionRequest{
Model: "openllama_3b",
Messages: []openai.ChatCompletionMessage{
{
Role: "user",
Content: "What is the weather like in San Francisco (celsius)?",
},
},
Functions: []openai.FunctionDefinition{
openai.FunctionDefinition{
Name: "get_current_weather",
Description: "Get the current weather",
Parameters: jsonschema.Definition{
Type: jsonschema.Object,
Properties: map[string]jsonschema.Definition{
"location": {
Type: jsonschema.String,
Description: "The city and state, e.g. San Francisco, CA",
},
"unit": {
Type: jsonschema.String,
Enum: []string{"celcius", "fahrenheit"},
},
},
Required: []string{"location"},
},
},
},
})
Expect(err).ToNot(HaveOccurred())
Expect(len(resp2.Choices)).To(Equal(1))
Expect(resp2.Choices[0].Message.FunctionCall).ToNot(BeNil())
Expect(resp2.Choices[0].Message.FunctionCall.Name).To(Equal("get_current_weather"), resp2.Choices[0].Message.FunctionCall.Name)
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["unit"]).To(Equal("celcius"), fmt.Sprint(res))
Expect(string(resp2.Choices[0].FinishReason)).To(Equal("function_call"), fmt.Sprint(resp2.Choices[0].FinishReason))
})
It("runs openllama gguf(llama-cpp)", Label("llama-gguf"), func() {
if runtime.GOOS != "linux" {
Skip("test supported only on linux")

17
docs/content/docs/features/text-generation.md
View File

@ -124,7 +124,7 @@ Note: rwkv models needs to specify the backend `rwkv` in the YAML config files a
{{% alert note %}}
The `ggml` file format has been deprecated. If you are using `ggml` models and you are configuring your model with a YAML file, specify, use the `llama-ggml` backend instead. If you are relying in automatic detection of the model, you should be fine. For `gguf` models, use the `llama` backend. The go backend is deprecated as well but still available as `go-llama`. The go backend supports still features not available in the mainline: speculative sampling and embeddings.
The `ggml` file format has been deprecated. If you are using `ggml` models and you are configuring your model with a YAML file, specify, use a LocalAI version older than v2.25.0. For `gguf` models, use the `llama` backend. The go backend is deprecated as well but still available as `go-llama`.
{{% /alert %}}
@ -175,25 +175,12 @@ name: llama
backend: llama
parameters:
# Relative to the models path
model: file.gguf.bin
```
In the example above we specify `llama` as the backend to restrict loading `gguf` models only.
For instance, to use the `llama-ggml` backend for `ggml` models:
```yaml
name: llama
backend: llama-ggml
parameters:
# Relative to the models path
model: file.ggml.bin
model: file.gguf
```
#### Reference
- [llama](https://github.com/ggerganov/llama.cpp)
- [binding](https://github.com/go-skynet/go-llama.cpp)
### exllama/2

6
pkg/model/initializers.go
View File

@ -43,8 +43,6 @@ var TypeAlias map[string]string = map[string]string{
var AutoDetect = os.Getenv("DISABLE_AUTODETECT") != "true"
const (
LlamaGGML = "llama-ggml"
LLamaCPP = "llama-cpp"
LLamaCPPAVX2 = "llama-cpp-avx2"
@ -143,10 +141,10 @@ func orderBackends(backends map[string][]string) ([]string, error) {
// sets a priority list - first has more priority
priorityList := []string{
// First llama.cpp(variants) and llama-ggml to follow.
// First llama.cpp(variants)
// We keep the fallback to prevent that if the llama.cpp variants
// that depends on shared libs if breaks have still a safety net.
LLamaCPP, LlamaGGML, LLamaCPPFallback,
LLamaCPP, LLamaCPPFallback,
}
toTheEnd := []string{