feat: `gRPC`-based backends (#743)

renovate/github.com-imdario-mergo-1.x
Ettore Di Giacinto 1 year ago committed by GitHub
commit e3cabb555d
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  1. 22
      .github/workflows/test.yml
  2. 13
      .gitignore
  3. 218
      Makefile
  4. 114
      api/api.go
  5. 245
      api/api_test.go
  6. 105
      api/backend/embeddings.go
  7. 60
      api/backend/image.go
  8. 98
      api/backend/llm.go
  9. 22
      api/backend/lock.go
  10. 72
      api/backend/options.go
  11. 401
      api/config.go
  12. 209
      api/config/config.go
  13. 24
      api/config/config_test.go
  14. 37
      api/config/prediction.go
  15. 78
      api/localai.go
  16. 21
      api/localai/gallery.go
  17. 84
      api/localai/localai.go
  18. 961
      api/openai.go
  19. 105
      api/openai/api.go
  20. 320
      api/openai/chat.go
  21. 159
      api/openai/completion.go
  22. 67
      api/openai/edit.go
  23. 70
      api/openai/embeddings.go
  24. 158
      api/openai/image.go
  25. 36
      api/openai/inference.go
  26. 37
      api/openai/list.go
  27. 234
      api/openai/request.go
  28. 91
      api/openai/transcription.go
  29. 84
      api/options/options.go
  30. 649
      api/prediction.go
  31. 22
      cmd/grpc/bert-embeddings/main.go
  32. 23
      cmd/grpc/bloomz/main.go
  33. 23
      cmd/grpc/dolly/main.go
  34. 23
      cmd/grpc/falcon-ggml/main.go
  35. 25
      cmd/grpc/falcon/main.go
  36. 23
      cmd/grpc/gpt2/main.go
  37. 23
      cmd/grpc/gpt4all/main.go
  38. 23
      cmd/grpc/gptj/main.go
  39. 23
      cmd/grpc/gptneox/main.go
  40. 23
      cmd/grpc/langchain-huggingface/main.go
  41. 25
      cmd/grpc/llama/main.go
  42. 23
      cmd/grpc/mpt/main.go
  43. 23
      cmd/grpc/piper/main.go
  44. 23
      cmd/grpc/replit/main.go
  45. 23
      cmd/grpc/rwkv/main.go
  46. 23
      cmd/grpc/stablediffusion/main.go
  47. 23
      cmd/grpc/starcoder/main.go
  48. 23
      cmd/grpc/whisper/main.go
  49. 23
      go.mod
  50. 162
      go.sum
  51. 44
      main.go
  52. 42
      pkg/grpc/base/base.go
  53. 160
      pkg/grpc/client.go
  54. 33
      pkg/grpc/image/stablediffusion.go
  55. 16
      pkg/grpc/interface.go
  56. 33
      pkg/grpc/llm/bert/bert.go
  57. 59
      pkg/grpc/llm/bloomz/bloomz.go
  58. 144
      pkg/grpc/llm/falcon/falcon.go
  59. 62
      pkg/grpc/llm/gpt4all/gpt4all.go
  60. 58
      pkg/grpc/llm/langchain/langchain.go
  61. 170
      pkg/grpc/llm/llama/llama.go
  62. 71
      pkg/grpc/llm/rwkv/rwkv.go
  63. 43
      pkg/grpc/llm/transformers/dolly.go
  64. 43
      pkg/grpc/llm/transformers/falcon.go
  65. 42
      pkg/grpc/llm/transformers/gpt2.go
  66. 42
      pkg/grpc/llm/transformers/gptj.go
  67. 42
      pkg/grpc/llm/transformers/gptneox.go
  68. 42
      pkg/grpc/llm/transformers/mpt.go
  69. 26
      pkg/grpc/llm/transformers/predict.go
  70. 42
      pkg/grpc/llm/transformers/replit.go
  71. 43
      pkg/grpc/llm/transformers/starcoder.go
  72. 1458
      pkg/grpc/proto/backend.pb.go
  73. 129
      pkg/grpc/proto/backend.proto
  74. 385
      pkg/grpc/proto/backend_grpc.pb.go
  75. 126
      pkg/grpc/server.go
  76. 27
      pkg/grpc/transcribe/whisper.go
  77. 44
      pkg/grpc/tts/piper.go
  78. 16
      pkg/grpc/whisper/api/api.go
  79. 23
      pkg/grpc/whisper/whisper.go
  80. 284
      pkg/model/initializers.go
  81. 37
      pkg/model/loader.go
  82. 66
      pkg/model/options.go
  83. 12
      pkg/tts/generate.go
  84. 10
      pkg/tts/generate_unsupported.go
  85. 20
      pkg/tts/piper.go

@ -26,9 +26,29 @@ jobs:
run: |
sudo apt-get update
sudo apt-get install build-essential ffmpeg
sudo apt-get install -y ca-certificates cmake curl patch
sudo apt-get install -y libopencv-dev && sudo ln -s /usr/include/opencv4/opencv2 /usr/include/opencv2
sudo mkdir /build && sudo chmod -R 777 /build && cd /build && \
curl -L "https://github.com/gabime/spdlog/archive/refs/tags/v1.11.0.tar.gz" | \
tar -xzvf - && \
mkdir -p "spdlog-1.11.0/build" && \
cd "spdlog-1.11.0/build" && \
cmake .. && \
make -j8 && \
sudo cmake --install . --prefix /usr && mkdir -p "lib/Linux-$(uname -m)" && \
cd /build && \
mkdir -p "lib/Linux-$(uname -m)/piper_phonemize" && \
curl -L "https://github.com/rhasspy/piper-phonemize/releases/download/v1.0.0/libpiper_phonemize-amd64.tar.gz" | \
tar -C "lib/Linux-$(uname -m)/piper_phonemize" -xzvf - && ls -liah /build/lib/Linux-$(uname -m)/piper_phonemize/ && \
sudo cp -rfv /build/lib/Linux-$(uname -m)/piper_phonemize/lib/. /lib64/ && \
sudo cp -rfv /build/lib/Linux-$(uname -m)/piper_phonemize/lib/. /usr/lib/ && \
sudo cp -rfv /build/lib/Linux-$(uname -m)/piper_phonemize/include/. /usr/include/
- name: Test
run: |
make test
ESPEAK_DATA="/build/lib/Linux-$(uname -m)/piper_phonemize/lib/espeak-ng-data" GO_TAGS="tts stablediffusion" make test
macOS-latest:
runs-on: macOS-latest

13
.gitignore vendored

@ -1,12 +1,19 @@
# go-llama build artifacts
go-llama
gpt4all
/gpt4all
go-stable-diffusion
go-piper
go-ggllm
/piper
*.a
get-sources
go-ggml-transformers
go-gpt2
go-rwkv
whisper.cpp
bloomz
/bloomz
go-bert
# LocalAI build binary
@ -29,4 +36,4 @@ release/
# Generated during build
backend-assets/
/ggml-metal.metal
/ggml-metal.metal

@ -41,6 +41,9 @@ BLOOMZ_VERSION?=1834e77b83faafe912ad4092ccf7f77937349e2f
# stablediffusion version
STABLEDIFFUSION_VERSION?=d89260f598afb809279bc72aa0107b4292587632
# Go-ggllm
GOGGLLM_VERSION?=862477d16eefb0805261c19c9b0d053e3b2b684b
export BUILD_TYPE?=
CGO_LDFLAGS?=
CUDA_LIBPATH?=/usr/local/cuda/lib64/
@ -64,8 +67,14 @@ WHITE := $(shell tput -Txterm setaf 7)
CYAN := $(shell tput -Txterm setaf 6)
RESET := $(shell tput -Txterm sgr0)
C_INCLUDE_PATH=$(shell pwd)/go-llama:$(shell pwd)/go-stable-diffusion/:$(shell pwd)/gpt4all/gpt4all-bindings/golang/:$(shell pwd)/go-ggml-transformers:$(shell pwd)/go-rwkv:$(shell pwd)/whisper.cpp:$(shell pwd)/go-bert:$(shell pwd)/bloomz
LIBRARY_PATH=$(shell pwd)/go-piper:$(shell pwd)/go-llama:$(shell pwd)/go-stable-diffusion/:$(shell pwd)/gpt4all/gpt4all-bindings/golang/:$(shell pwd)/go-ggml-transformers:$(shell pwd)/go-rwkv:$(shell pwd)/whisper.cpp:$(shell pwd)/go-bert:$(shell pwd)/bloomz
ifndef UNAME_S
UNAME_S := $(shell uname -s)
endif
# workaround for rwkv.cpp
ifeq ($(UNAME_S),Darwin)
CGO_LDFLAGS += -lcblas -framework Accelerate
endif
ifeq ($(BUILD_TYPE),openblas)
CGO_LDFLAGS+=-lopenblas
@ -91,12 +100,14 @@ ifeq ($(STATIC),true)
endif
ifeq ($(findstring stablediffusion,$(GO_TAGS)),stablediffusion)
OPTIONAL_TARGETS+=go-stable-diffusion/libstablediffusion.a
# OPTIONAL_TARGETS+=go-stable-diffusion/libstablediffusion.a
OPTIONAL_GRPC+=backend-assets/grpc/stablediffusion
endif
ifeq ($(findstring tts,$(GO_TAGS)),tts)
OPTIONAL_TARGETS+=go-piper/libpiper_binding.a
OPTIONAL_TARGETS+=backend-assets/espeak-ng-data
# OPTIONAL_TARGETS+=go-piper/libpiper_binding.a
# OPTIONAL_TARGETS+=backend-assets/espeak-ng-data
OPTIONAL_GRPC+=backend-assets/grpc/piper
endif
.PHONY: all test build vendor
@ -107,24 +118,14 @@ all: help
gpt4all:
git clone --recurse-submodules $(GPT4ALL_REPO) gpt4all
cd gpt4all && git checkout -b build $(GPT4ALL_VERSION) && git submodule update --init --recursive --depth 1
# This is hackish, but needed as both go-llama and go-gpt4allj have their own version of ggml..
@find ./gpt4all -type f -name "*.c" -exec sed -i'' -e 's/ggml_/ggml_gpt4all_/g' {} +
@find ./gpt4all -type f -name "*.cpp" -exec sed -i'' -e 's/ggml_/ggml_gpt4all_/g' {} +
@find ./gpt4all -type f -name "*.m" -exec sed -i'' -e 's/ggml_/ggml_gpt4all_/g' {} +
@find ./gpt4all -type f -name "*.h" -exec sed -i'' -e 's/ggml_/ggml_gpt4all_/g' {} +
@find ./gpt4all -type f -name "*.c" -exec sed -i'' -e 's/llama_/llama_gpt4all_/g' {} +
@find ./gpt4all -type f -name "*.cpp" -exec sed -i'' -e 's/llama_/llama_gpt4all_/g' {} +
@find ./gpt4all -type f -name "*.h" -exec sed -i'' -e 's/llama_/llama_gpt4all_/g' {} +
@find ./gpt4all/gpt4all-backend -type f -name "llama_util.h" -execdir mv {} "llama_gpt4all_util.h" \;
@find ./gpt4all -type f -name "*.cmake" -exec sed -i'' -e 's/llama_util/llama_gpt4all_util/g' {} +
@find ./gpt4all -type f -name "*.txt" -exec sed -i'' -e 's/llama_util/llama_gpt4all_util/g' {} +
@find ./gpt4all/gpt4all-bindings/golang -type f -name "*.cpp" -exec sed -i'' -e 's/load_model/load_gpt4all_model/g' {} +
@find ./gpt4all/gpt4all-bindings/golang -type f -name "*.go" -exec sed -i'' -e 's/load_model/load_gpt4all_model/g' {} +
@find ./gpt4all/gpt4all-bindings/golang -type f -name "*.h" -exec sed -i'' -e 's/load_model/load_gpt4all_model/g' {} +
@find ./gpt4all/gpt4all-bindings/golang -type f -name "*.h" -exec sed -i'' -e 's/set_numa_thread_affinity/gpt4all_set_numa_thread_affinity/g' {} +
@find ./gpt4all/gpt4all-bindings/golang -type f -name "*.c" -exec sed -i'' -e 's/set_numa_thread_affinity/gpt4all__set_numa_thread_affinity/g' {} +
@find ./gpt4all/gpt4all-bindings/golang -type f -name "*.c" -exec sed -i'' -e 's/clear_numa_thread_affinity/gpt4all__clear_numa_thread_affinity/g' {} +
@find ./gpt4all/gpt4all-bindings/golang -type f -name "*.h" -exec sed -i'' -e 's/clear_numa_thread_affinity/gpt4all__clear_numa_thread_affinity/g' {} +
## go-ggllm
go-ggllm:
git clone --recurse-submodules https://github.com/mudler/go-ggllm.cpp go-ggllm
cd go-ggllm && git checkout -b build $(GOGGLLM_VERSION) && git submodule update --init --recursive --depth 1
go-ggllm/libggllm.a: go-ggllm
$(MAKE) -C go-ggllm BUILD_TYPE=$(BUILD_TYPE) libggllm.a
## go-piper
go-piper:
@ -135,9 +136,6 @@ go-piper:
go-bert:
git clone --recurse-submodules https://github.com/go-skynet/go-bert.cpp go-bert
cd go-bert && git checkout -b build $(BERT_VERSION) && git submodule update --init --recursive --depth 1
@find ./go-bert -type f -name "*.c" -exec sed -i'' -e 's/ggml_/ggml_bert_/g' {} +
@find ./go-bert -type f -name "*.cpp" -exec sed -i'' -e 's/ggml_/ggml_bert_/g' {} +
@find ./go-bert -type f -name "*.h" -exec sed -i'' -e 's/ggml_/ggml_bert_/g' {} +
## stable diffusion
go-stable-diffusion:
@ -151,9 +149,6 @@ go-stable-diffusion/libstablediffusion.a:
go-rwkv:
git clone --recurse-submodules $(RWKV_REPO) go-rwkv
cd go-rwkv && git checkout -b build $(RWKV_VERSION) && git submodule update --init --recursive --depth 1
@find ./go-rwkv -type f -name "*.c" -exec sed -i'' -e 's/ggml_/ggml_rwkv_/g' {} +
@find ./go-rwkv -type f -name "*.cpp" -exec sed -i'' -e 's/ggml_/ggml_rwkv_/g' {} +
@find ./go-rwkv -type f -name "*.h" -exec sed -i'' -e 's/ggml_/ggml_rwkv_/g' {} +
go-rwkv/librwkv.a: go-rwkv
cd go-rwkv && cd rwkv.cpp && cmake . -DRWKV_BUILD_SHARED_LIBRARY=OFF && cmake --build . && cp librwkv.a ..
@ -161,13 +156,7 @@ go-rwkv/librwkv.a: go-rwkv
## bloomz
bloomz:
git clone --recurse-submodules https://github.com/go-skynet/bloomz.cpp bloomz
@find ./bloomz -type f -name "*.c" -exec sed -i'' -e 's/ggml_/ggml_bloomz_/g' {} +
@find ./bloomz -type f -name "*.cpp" -exec sed -i'' -e 's/ggml_/ggml_bloomz_/g' {} +
@find ./bloomz -type f -name "*.h" -exec sed -i'' -e 's/ggml_/ggml_bloomz_/g' {} +
@find ./bloomz -type f -name "*.cpp" -exec sed -i'' -e 's/gpt_/gpt_bloomz_/g' {} +
@find ./bloomz -type f -name "*.h" -exec sed -i'' -e 's/gpt_/gpt_bloomz_/g' {} +
@find ./bloomz -type f -name "*.cpp" -exec sed -i'' -e 's/void replace/void json_bloomz_replace/g' {} +
@find ./bloomz -type f -name "*.cpp" -exec sed -i'' -e 's/::replace/::json_bloomz_replace/g' {} +
cd bloomz && git checkout -b build $(BLOOMZ_VERSION) && git submodule update --init --recursive --depth 1
bloomz/libbloomz.a: bloomz
cd bloomz && make libbloomz.a
@ -186,6 +175,7 @@ backend-assets/espeak-ng-data:
ifdef ESPEAK_DATA
@cp -rf $(ESPEAK_DATA)/. backend-assets/espeak-ng-data
else
@echo "ESPEAK_DATA not set, skipping tts. Note that this will break the tts functionality."
@touch backend-assets/espeak-ng-data/keep
endif
@ -196,21 +186,6 @@ gpt4all/gpt4all-bindings/golang/libgpt4all.a: gpt4all
go-ggml-transformers:
git clone --recurse-submodules https://github.com/go-skynet/go-ggml-transformers.cpp go-ggml-transformers
cd go-ggml-transformers && git checkout -b build $(GOGPT2_VERSION) && git submodule update --init --recursive --depth 1
# This is hackish, but needed as both go-llama and go-gpt4allj have their own version of ggml..
@find ./go-ggml-transformers -type f -name "*.c" -exec sed -i'' -e 's/ggml_/ggml_gpt2_/g' {} +
@find ./go-ggml-transformers -type f -name "*.cpp" -exec sed -i'' -e 's/ggml_/ggml_gpt2_/g' {} +
@find ./go-ggml-transformers -type f -name "*.h" -exec sed -i'' -e 's/ggml_/ggml_gpt2_/g' {} +
@find ./go-ggml-transformers -type f -name "*.cpp" -exec sed -i'' -e 's/gpt_print_usage/gpt2_print_usage/g' {} +
@find ./go-ggml-transformers -type f -name "*.h" -exec sed -i'' -e 's/gpt_print_usage/gpt2_print_usage/g' {} +
@find ./go-ggml-transformers -type f -name "*.cpp" -exec sed -i'' -e 's/gpt_params_parse/gpt2_params_parse/g' {} +
@find ./go-ggml-transformers -type f -name "*.h" -exec sed -i'' -e 's/gpt_params_parse/gpt2_params_parse/g' {} +
@find ./go-ggml-transformers -type f -name "*.cpp" -exec sed -i'' -e 's/gpt_random_prompt/gpt2_random_prompt/g' {} +
@find ./go-ggml-transformers -type f -name "*.h" -exec sed -i'' -e 's/gpt_random_prompt/gpt2_random_prompt/g' {} +
@find ./go-ggml-transformers -type f -name "*.cpp" -exec sed -i'' -e 's/json_/json_gpt2_/g' {} +
@find ./go-ggml-transformers -type f -name "*.h" -exec sed -i'' -e 's/set_numa_thread_affinity/transformers_set_numa_thread_affinity/g' {} +
@find ./go-ggml-transformers -type f -name "*.c" -exec sed -i'' -e 's/set_numa_thread_affinity/transformers_set_numa_thread_affinity/g' {} +
@find ./go-ggml-transformers -type f -name "*.c" -exec sed -i'' -e 's/clear_numa_thread_affinity/transformers_clear_numa_thread_affinity/g' {} +
@find ./go-ggml-transformers -type f -name "*.h" -exec sed -i'' -e 's/clear_numa_thread_affinity/transformers_clear_numa_thread_affinity/g' {} +
go-ggml-transformers/libtransformers.a: go-ggml-transformers
$(MAKE) -C go-ggml-transformers libtransformers.a
@ -218,9 +193,6 @@ go-ggml-transformers/libtransformers.a: go-ggml-transformers
whisper.cpp:
git clone https://github.com/ggerganov/whisper.cpp.git
cd whisper.cpp && git checkout -b build $(WHISPER_CPP_VERSION) && git submodule update --init --recursive --depth 1
@find ./whisper.cpp -type f -name "*.c" -exec sed -i'' -e 's/ggml_/ggml_whisper_/g' {} +
@find ./whisper.cpp -type f -name "*.cpp" -exec sed -i'' -e 's/ggml_/ggml_whisper_/g' {} +
@find ./whisper.cpp -type f -name "*.h" -exec sed -i'' -e 's/ggml_/ggml_whisper_/g' {} +
whisper.cpp/libwhisper.a: whisper.cpp
cd whisper.cpp && make libwhisper.a
@ -238,7 +210,7 @@ go-llama/libbinding.a: go-llama
go-piper/libpiper_binding.a:
$(MAKE) -C go-piper libpiper_binding.a example/main
get-sources: go-llama go-ggml-transformers gpt4all go-piper go-rwkv whisper.cpp go-bert bloomz go-stable-diffusion
get-sources: go-llama go-ggllm go-ggml-transformers gpt4all go-piper go-rwkv whisper.cpp go-bert bloomz go-stable-diffusion
touch $@
replace:
@ -251,6 +223,7 @@ replace:
$(GOCMD) mod edit -replace github.com/go-skynet/bloomz.cpp=$(shell pwd)/bloomz
$(GOCMD) mod edit -replace github.com/mudler/go-stable-diffusion=$(shell pwd)/go-stable-diffusion
$(GOCMD) mod edit -replace github.com/mudler/go-piper=$(shell pwd)/go-piper
$(GOCMD) mod edit -replace github.com/mudler/go-ggllm.cpp=$(shell pwd)/go-ggllm
prepare-sources: get-sources replace
$(GOCMD) mod download
@ -267,9 +240,10 @@ rebuild: ## Rebuilds the project
$(MAKE) -C go-bert clean
$(MAKE) -C bloomz clean
$(MAKE) -C go-piper clean
$(MAKE) -C go-ggllm clean
$(MAKE) build
prepare: prepare-sources backend-assets/gpt4all $(OPTIONAL_TARGETS) go-llama/libbinding.a go-bert/libgobert.a go-ggml-transformers/libtransformers.a go-rwkv/librwkv.a whisper.cpp/libwhisper.a bloomz/libbloomz.a ## Prepares for building
prepare: prepare-sources $(OPTIONAL_TARGETS)
touch $@
clean: ## Remove build related file
@ -285,18 +259,19 @@ clean: ## Remove build related file
rm -rf ./bloomz
rm -rf ./whisper.cpp
rm -rf ./go-piper
rm -rf ./go-ggllm
rm -rf $(BINARY_NAME)
rm -rf release/
## Build:
build: prepare ## Build the project
build: grpcs prepare ## Build the project
$(info ${GREEN}I local-ai build info:${RESET})
$(info ${GREEN}I BUILD_TYPE: ${YELLOW}$(BUILD_TYPE)${RESET})
$(info ${GREEN}I GO_TAGS: ${YELLOW}$(GO_TAGS)${RESET})
$(info ${GREEN}I LD_FLAGS: ${YELLOW}$(LD_FLAGS)${RESET})
CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=${C_INCLUDE_PATH} LIBRARY_PATH=${LIBRARY_PATH} $(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o $(BINARY_NAME) ./
CGO_LDFLAGS="$(CGO_LDFLAGS)" $(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o $(BINARY_NAME) ./
ifeq ($(BUILD_TYPE),metal)
cp go-llama/build/bin/ggml-metal.metal .
endif
@ -305,12 +280,9 @@ dist: build
mkdir -p release
cp $(BINARY_NAME) release/$(BINARY_NAME)-$(BUILD_ID)-$(OS)-$(ARCH)
generic-build: ## Build the project using generic
BUILD_TYPE="generic" $(MAKE) build
## Run
run: prepare ## run local-ai
CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=${C_INCLUDE_PATH} LIBRARY_PATH=${LIBRARY_PATH} $(GOCMD) run ./
CGO_LDFLAGS="$(CGO_LDFLAGS)" $(GOCMD) run ./
test-models/testmodel:
mkdir test-models
@ -323,12 +295,42 @@ test-models/testmodel:
wget https://raw.githubusercontent.com/saharNooby/rwkv.cpp/5eb8f09c146ea8124633ab041d9ea0b1f1db4459/rwkv/20B_tokenizer.json -O test-models/rwkv.tokenizer.json
cp tests/models_fixtures/* test-models
test: prepare test-models/testmodel
cp -r backend-assets api
prepare-test: grpcs
cp -rf backend-assets api
cp tests/models_fixtures/* test-models
C_INCLUDE_PATH=${C_INCLUDE_PATH} LIBRARY_PATH=${LIBRARY_PATH} TEST_DIR=$(abspath ./)/test-dir/ FIXTURES=$(abspath ./)/tests/fixtures CONFIG_FILE=$(abspath ./)/test-models/config.yaml MODELS_PATH=$(abspath ./)/test-models $(GOCMD) run github.com/onsi/ginkgo/v2/ginkgo --label-filter="!gpt4all && !llama" --flake-attempts 5 -v -r ./api ./pkg
C_INCLUDE_PATH=${C_INCLUDE_PATH} LIBRARY_PATH=${LIBRARY_PATH} TEST_DIR=$(abspath ./)/test-dir/ FIXTURES=$(abspath ./)/tests/fixtures CONFIG_FILE=$(abspath ./)/test-models/config.yaml MODELS_PATH=$(abspath ./)/test-models $(GOCMD) run github.com/onsi/ginkgo/v2/ginkgo --label-filter="gpt4all" --flake-attempts 5 -v -r ./api ./pkg
C_INCLUDE_PATH=${C_INCLUDE_PATH} LIBRARY_PATH=${LIBRARY_PATH} TEST_DIR=$(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 5 -v -r ./api ./pkg
test: prepare test-models/testmodel grpcs
@echo 'Running tests'
export GO_TAGS="tts stablediffusion"
$(MAKE) prepare-test
TEST_DIR=$(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="!gpt4all && !llama" --flake-attempts 5 -v -r ./api ./pkg
$(MAKE) test-gpt4all
$(MAKE) test-llama
$(MAKE) test-tts
$(MAKE) test-stablediffusion
test-gpt4all: prepare-test
TEST_DIR=$(abspath ./)/test-dir/ FIXTURES=$(abspath ./)/tests/fixtures CONFIG_FILE=$(abspath ./)/test-models/config.yaml MODELS_PATH=$(abspath ./)/test-models \
$(GOCMD) run github.com/onsi/ginkgo/v2/ginkgo --label-filter="gpt4all" --flake-attempts 5 -v -r ./api ./pkg
test-llama: prepare-test
TEST_DIR=$(abspath ./)/test-dir/ FIXTURES=$(abspath ./)/tests/fixtures CONFIG_FILE=$(abspath ./)/test-models/config.yaml MODELS_PATH=$(abspath ./)/test-models \
$(GOCMD) run github.com/onsi/ginkgo/v2/ginkgo --label-filter="llama" --flake-attempts 5 -v -r ./api ./pkg
test-tts: prepare-test
TEST_DIR=$(abspath ./)/test-dir/ FIXTURES=$(abspath ./)/tests/fixtures CONFIG_FILE=$(abspath ./)/test-models/config.yaml MODELS_PATH=$(abspath ./)/test-models \
$(GOCMD) run github.com/onsi/ginkgo/v2/ginkgo --label-filter="tts" --flake-attempts 1 -v -r ./api ./pkg
test-stablediffusion: prepare-test
TEST_DIR=$(abspath ./)/test-dir/ FIXTURES=$(abspath ./)/tests/fixtures CONFIG_FILE=$(abspath ./)/test-models/config.yaml MODELS_PATH=$(abspath ./)/test-models \
$(GOCMD) run github.com/onsi/ginkgo/v2/ginkgo --label-filter="stablediffusion" --flake-attempts 1 -v -r ./api ./pkg
test-container:
docker build --target requirements -t local-ai-test-container .
docker run --name localai-tests -e GO_TAGS=$(GO_TAGS) -ti -v $(abspath ./):/build local-ai-test-container make test
docker rm localai-tests
docker rmi local-ai-test-container
## Help:
help: ## Show this help.
@ -341,3 +343,85 @@ help: ## Show this help.
if (/^[a-zA-Z_-]+:.*?##.*$$/) {printf " ${YELLOW}%-20s${GREEN}%s${RESET}\n", $$1, $$2} \
else if (/^## .*$$/) {printf " ${CYAN}%s${RESET}\n", substr($$1,4)} \
}' $(MAKEFILE_LIST)
protogen:
protoc --go_out=. --go_opt=paths=source_relative --go-grpc_out=. --go-grpc_opt=paths=source_relative \
pkg/grpc/proto/backend.proto
## GRPC
backend-assets/grpc:
mkdir -p backend-assets/grpc
backend-assets/grpc/falcon: backend-assets/grpc go-ggllm/libggllm.a
CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(shell pwd)/go-ggllm LIBRARY_PATH=$(shell pwd)/go-ggllm \
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/falcon ./cmd/grpc/falcon/
backend-assets/grpc/llama: backend-assets/grpc go-llama/libbinding.a
CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(shell pwd)/go-llama LIBRARY_PATH=$(shell pwd)/go-llama \
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/llama ./cmd/grpc/llama/
backend-assets/grpc/gpt4all: backend-assets/grpc backend-assets/gpt4all gpt4all/gpt4all-bindings/golang/libgpt4all.a
CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(shell pwd)/gpt4all/gpt4all-bindings/golang/ LIBRARY_PATH=$(shell pwd)/gpt4all/gpt4all-bindings/golang/ \
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/gpt4all ./cmd/grpc/gpt4all/
backend-assets/grpc/dolly: backend-assets/grpc go-ggml-transformers/libtransformers.a
CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(shell pwd)/go-ggml-transformers LIBRARY_PATH=$(shell pwd)/go-ggml-transformers \
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/dolly ./cmd/grpc/dolly/
backend-assets/grpc/gpt2: backend-assets/grpc go-ggml-transformers/libtransformers.a
CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(shell pwd)/go-ggml-transformers LIBRARY_PATH=$(shell pwd)/go-ggml-transformers \
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/gpt2 ./cmd/grpc/gpt2/
backend-assets/grpc/gptj: backend-assets/grpc go-ggml-transformers/libtransformers.a
CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(shell pwd)/go-ggml-transformers LIBRARY_PATH=$(shell pwd)/go-ggml-transformers \
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/gptj ./cmd/grpc/gptj/
backend-assets/grpc/gptneox: backend-assets/grpc go-ggml-transformers/libtransformers.a
CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(shell pwd)/go-ggml-transformers LIBRARY_PATH=$(shell pwd)/go-ggml-transformers \
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/gptneox ./cmd/grpc/gptneox/
backend-assets/grpc/mpt: backend-assets/grpc go-ggml-transformers/libtransformers.a
CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(shell pwd)/go-ggml-transformers LIBRARY_PATH=$(shell pwd)/go-ggml-transformers \
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/mpt ./cmd/grpc/mpt/
backend-assets/grpc/replit: backend-assets/grpc go-ggml-transformers/libtransformers.a
CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(shell pwd)/go-ggml-transformers LIBRARY_PATH=$(shell pwd)/go-ggml-transformers \
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/replit ./cmd/grpc/replit/
backend-assets/grpc/falcon-ggml: backend-assets/grpc go-ggml-transformers/libtransformers.a
CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(shell pwd)/go-ggml-transformers LIBRARY_PATH=$(shell pwd)/go-ggml-transformers \
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/falcon-ggml ./cmd/grpc/falcon-ggml/
backend-assets/grpc/starcoder: backend-assets/grpc go-ggml-transformers/libtransformers.a
CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(shell pwd)/go-ggml-transformers LIBRARY_PATH=$(shell pwd)/go-ggml-transformers \
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/starcoder ./cmd/grpc/starcoder/
backend-assets/grpc/rwkv: backend-assets/grpc go-rwkv/librwkv.a
CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(shell pwd)/go-rwkv LIBRARY_PATH=$(shell pwd)/go-rwkv \
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/rwkv ./cmd/grpc/rwkv/
backend-assets/grpc/bloomz: backend-assets/grpc bloomz/libbloomz.a
CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(shell pwd)/bloomz LIBRARY_PATH=$(shell pwd)/bloomz \
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/bloomz ./cmd/grpc/bloomz/
backend-assets/grpc/bert-embeddings: backend-assets/grpc go-bert/libgobert.a
CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(shell pwd)/go-bert LIBRARY_PATH=$(shell pwd)/go-bert \
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/bert-embeddings ./cmd/grpc/bert-embeddings/
backend-assets/grpc/langchain-huggingface: backend-assets/grpc
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/langchain-huggingface ./cmd/grpc/langchain-huggingface/
backend-assets/grpc/stablediffusion: backend-assets/grpc go-stable-diffusion/libstablediffusion.a
CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(shell pwd)/go-stable-diffusion/ LIBRARY_PATH=$(shell pwd)/go-stable-diffusion/ \
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/stablediffusion ./cmd/grpc/stablediffusion/
backend-assets/grpc/piper: backend-assets/grpc backend-assets/espeak-ng-data go-piper/libpiper_binding.a
CGO_LDFLAGS="$(CGO_LDFLAGS)" LIBRARY_PATH=$(shell pwd)/go-piper \
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/piper ./cmd/grpc/piper/
backend-assets/grpc/whisper: backend-assets/grpc whisper.cpp/libwhisper.a
CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(shell pwd)/whisper.cpp LIBRARY_PATH=$(shell pwd)/whisper.cpp \
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/whisper ./cmd/grpc/whisper/
grpcs: prepare backend-assets/grpc/langchain-huggingface backend-assets/grpc/falcon-ggml backend-assets/grpc/bert-embeddings backend-assets/grpc/falcon backend-assets/grpc/bloomz backend-assets/grpc/llama backend-assets/grpc/gpt4all backend-assets/grpc/dolly backend-assets/grpc/gpt2 backend-assets/grpc/gptj backend-assets/grpc/gptneox backend-assets/grpc/mpt backend-assets/grpc/replit backend-assets/grpc/starcoder backend-assets/grpc/rwkv backend-assets/grpc/whisper $(OPTIONAL_GRPC)

@ -3,8 +3,13 @@ package api
import (
"errors"
config "github.com/go-skynet/LocalAI/api/config"
"github.com/go-skynet/LocalAI/api/localai"
"github.com/go-skynet/LocalAI/api/openai"
"github.com/go-skynet/LocalAI/api/options"
"github.com/go-skynet/LocalAI/internal"
"github.com/go-skynet/LocalAI/pkg/assets"
"github.com/gofiber/fiber/v2"
"github.com/gofiber/fiber/v2/middleware/cors"
"github.com/gofiber/fiber/v2/middleware/logger"
@ -13,18 +18,18 @@ import (
"github.com/rs/zerolog/log"
)
func App(opts ...AppOption) (*fiber.App, error) {
options := newOptions(opts...)
func App(opts ...options.AppOption) (*fiber.App, error) {
options := options.NewOptions(opts...)
zerolog.SetGlobalLevel(zerolog.InfoLevel)
if options.debug {
if options.Debug {
zerolog.SetGlobalLevel(zerolog.DebugLevel)
}
// Return errors as JSON responses
app := fiber.New(fiber.Config{
BodyLimit: options.uploadLimitMB * 1024 * 1024, // this is the default limit of 4MB
DisableStartupMessage: options.disableMessage,
BodyLimit: options.UploadLimitMB * 1024 * 1024, // this is the default limit of 4MB
DisableStartupMessage: options.DisableMessage,
// Override default error handler
ErrorHandler: func(ctx *fiber.Ctx, err error) error {
// Status code defaults to 500
@ -38,43 +43,44 @@ func App(opts ...AppOption) (*fiber.App, error) {
// Send custom error page
return ctx.Status(code).JSON(
ErrorResponse{
Error: &APIError{Message: err.Error(), Code: code},
openai.ErrorResponse{
Error: &openai.APIError{Message: err.Error(), Code: code},
},
)
},
})
if options.debug {
if options.Debug {
app.Use(logger.New(logger.Config{
Format: "[${ip}]:${port} ${status} - ${method} ${path}\n",
}))
}
log.Info().Msgf("Starting LocalAI using %d threads, with models path: %s", options.threads, options.loader.ModelPath)
log.Info().Msgf("Starting LocalAI using %d threads, with models path: %s", options.Threads, options.Loader.ModelPath)
log.Info().Msgf("LocalAI version: %s", internal.PrintableVersion())
cm := NewConfigMerger()
if err := cm.LoadConfigs(options.loader.ModelPath); err != nil {
cm := config.NewConfigLoader()
if err := cm.LoadConfigs(options.Loader.ModelPath); err != nil {
log.Error().Msgf("error loading config files: %s", err.Error())
}
if options.configFile != "" {
if err := cm.LoadConfigFile(options.configFile); err != nil {
if options.ConfigFile != "" {
if err := cm.LoadConfigFile(options.ConfigFile); err != nil {
log.Error().Msgf("error loading config file: %s", err.Error())
}
}
if options.debug {
if options.Debug {
for _, v := range cm.ListConfigs() {
cfg, _ := cm.GetConfig(v)
log.Debug().Msgf("Model: %s (config: %+v)", v, cfg)
}
}
if options.assetsDestination != "" {
if options.AssetsDestination != "" {
// Extract files from the embedded FS
err := assets.ExtractFiles(options.backendAssets, options.assetsDestination)
err := assets.ExtractFiles(options.BackendAssets, options.AssetsDestination)
log.Debug().Msgf("Extracting backend assets files to %s", options.AssetsDestination)
if err != nil {
log.Warn().Msgf("Failed extracting backend assets files: %s (might be required for some backends to work properly, like gpt4all)", err)
}
@ -83,31 +89,32 @@ func App(opts ...AppOption) (*fiber.App, error) {
// Default middleware config
app.Use(recover.New())
if options.preloadJSONModels != "" {
if err := ApplyGalleryFromString(options.loader.ModelPath, options.preloadJSONModels, cm, options.galleries); err != nil {
if options.PreloadJSONModels != "" {
if err := localai.ApplyGalleryFromString(options.Loader.ModelPath, options.PreloadJSONModels, cm, options.Galleries); err != nil {
return nil, err
}
}
if options.preloadModelsFromPath != "" {
if err := ApplyGalleryFromFile(options.loader.ModelPath, options.preloadModelsFromPath, cm, options.galleries); err != nil {
if options.PreloadModelsFromPath != "" {
if err := localai.ApplyGalleryFromFile(options.Loader.ModelPath, options.PreloadModelsFromPath, cm, options.Galleries); err != nil {
return nil, err
}
}
if options.cors {
if options.corsAllowOrigins == "" {
app.Use(cors.New())
if options.CORS {
var c func(ctx *fiber.Ctx) error
if options.CORSAllowOrigins == "" {
c = cors.New()
} else {
app.Use(cors.New(cors.Config{
AllowOrigins: options.corsAllowOrigins,
}))
c = cors.New(cors.Config{AllowOrigins: options.CORSAllowOrigins})
}
app.Use(c)
}
// LocalAI API endpoints
applier := newGalleryApplier(options.loader.ModelPath)
applier.start(options.context, cm)
galleryService := localai.NewGalleryService(options.Loader.ModelPath)
galleryService.Start(options.Context, cm)
app.Get("/version", func(c *fiber.Ctx) error {
return c.JSON(struct {
@ -115,43 +122,43 @@ func App(opts ...AppOption) (*fiber.App, error) {
}{Version: internal.PrintableVersion()})
})
app.Post("/models/apply", applyModelGallery(options.loader.ModelPath, cm, applier.C, options.galleries))
app.Get("/models/available", listModelFromGallery(options.galleries, options.loader.ModelPath))
app.Get("/models/jobs/:uuid", getOpStatus(applier))
app.Post("/models/apply", localai.ApplyModelGalleryEndpoint(options.Loader.ModelPath, cm, galleryService.C, options.Galleries))
app.Get("/models/available", localai.ListModelFromGalleryEndpoint(options.Galleries, options.Loader.ModelPath))
app.Get("/models/jobs/:uuid", localai.GetOpStatusEndpoint(galleryService))
// openAI compatible API endpoint
// chat
app.Post("/v1/chat/completions", chatEndpoint(cm, options))
app.Post("/chat/completions", chatEndpoint(cm, options))
app.Post("/v1/chat/completions", openai.ChatEndpoint(cm, options))
app.Post("/chat/completions", openai.ChatEndpoint(cm, options))
// edit
app.Post("/v1/edits", editEndpoint(cm, options))
app.Post("/edits", editEndpoint(cm, options))
app.Post("/v1/edits", openai.EditEndpoint(cm, options))
app.Post("/edits", openai.EditEndpoint(cm, options))
// completion
app.Post("/v1/completions", completionEndpoint(cm, options))
app.Post("/completions", completionEndpoint(cm, options))
app.Post("/v1/engines/:model/completions", completionEndpoint(cm, options))
app.Post("/v1/completions", openai.CompletionEndpoint(cm, options))
app.Post("/completions", openai.CompletionEndpoint(cm, options))
app.Post("/v1/engines/:model/completions", openai.CompletionEndpoint(cm, options))
// embeddings
app.Post("/v1/embeddings", embeddingsEndpoint(cm, options))
app.Post("/embeddings", embeddingsEndpoint(cm, options))
app.Post("/v1/engines/:model/embeddings", embeddingsEndpoint(cm, options))
app.Post("/v1/embeddings", openai.EmbeddingsEndpoint(cm, options))
app.Post("/embeddings", openai.EmbeddingsEndpoint(cm, options))
app.Post("/v1/engines/:model/embeddings", openai.EmbeddingsEndpoint(cm, options))
// audio
app.Post("/v1/audio/transcriptions", transcriptEndpoint(cm, options))
app.Post("/tts", ttsEndpoint(cm, options))
app.Post("/v1/audio/transcriptions", openai.TranscriptEndpoint(cm, options))
app.Post("/tts", localai.TTSEndpoint(cm, options))
// images
app.Post("/v1/images/generations", imageEndpoint(cm, options))
app.Post("/v1/images/generations", openai.ImageEndpoint(cm, options))
if options.imageDir != "" {
app.Static("/generated-images", options.imageDir)
if options.ImageDir != "" {
app.Static("/generated-images", options.ImageDir)
}
if options.audioDir != "" {
app.Static("/generated-audio", options.audioDir)
if options.AudioDir != "" {
app.Static("/generated-audio", options.AudioDir)
}
ok := func(c *fiber.Ctx) error {
@ -163,8 +170,15 @@ func App(opts ...AppOption) (*fiber.App, error) {
app.Get("/readyz", ok)
// models
app.Get("/v1/models", listModels(options.loader, cm))
app.Get("/models", listModels(options.loader, cm))
app.Get("/v1/models", openai.ListModelsEndpoint(options.Loader, cm))
app.Get("/models", openai.ListModelsEndpoint(options.Loader, cm))
// turn off any process that was started by GRPC if the context is canceled
go func() {
<-options.Context.Done()
log.Debug().Msgf("Context canceled, shutting down")
options.Loader.StopGRPC()
}()
return app, nil
}

@ -5,7 +5,9 @@ import (
"context"
"embed"
"encoding/json"
"errors"
"fmt"
"io"
"io/ioutil"
"net/http"
"os"
@ -13,6 +15,7 @@ import (
"runtime"
. "github.com/go-skynet/LocalAI/api"
"github.com/go-skynet/LocalAI/api/options"
"github.com/go-skynet/LocalAI/pkg/gallery"
"github.com/go-skynet/LocalAI/pkg/model"
"github.com/go-skynet/LocalAI/pkg/utils"
@ -23,6 +26,7 @@ import (
openaigo "github.com/otiai10/openaigo"
"github.com/sashabaranov/go-openai"
"github.com/sashabaranov/go-openai/jsonschema"
)
type modelApplyRequest struct {
@ -154,9 +158,10 @@ var _ = Describe("API test", func() {
},
}
app, err = App(WithContext(c),
WithGalleries(galleries),
WithModelLoader(modelLoader), WithBackendAssets(backendAssets), WithBackendAssetsOutput(tmpdir))
app, err = App(
options.WithContext(c),
options.WithGalleries(galleries),
options.WithModelLoader(modelLoader), options.WithBackendAssets(backendAssets), options.WithBackendAssetsOutput(tmpdir))
Expect(err).ToNot(HaveOccurred())
go app.Listen("127.0.0.1:9090")
@ -201,7 +206,7 @@ var _ = Describe("API test", func() {
fmt.Println(response)
resp = response
return response["processed"].(bool)
}, "360s").Should(Equal(true))
}, "360s", "10s").Should(Equal(true))
Expect(resp["message"]).ToNot(ContainSubstring("error"))
dat, err := os.ReadFile(filepath.Join(tmpdir, "bert2.yaml"))
@ -243,9 +248,8 @@ var _ = Describe("API test", func() {
Eventually(func() bool {
response := getModelStatus("http://127.0.0.1:9090/models/jobs/" + uuid)
fmt.Println(response)
return response["processed"].(bool)
}, "360s").Should(Equal(true))
}, "360s", "10s").Should(Equal(true))
dat, err := os.ReadFile(filepath.Join(tmpdir, "bert.yaml"))
Expect(err).ToNot(HaveOccurred())
@ -268,9 +272,8 @@ var _ = Describe("API test", func() {
Eventually(func() bool {
response := getModelStatus("http://127.0.0.1:9090/models/jobs/" + uuid)
fmt.Println(response)
return response["processed"].(bool)
}, "360s").Should(Equal(true))
}, "360s", "10s").Should(Equal(true))
dat, err := os.ReadFile(filepath.Join(tmpdir, "bert.yaml"))
Expect(err).ToNot(HaveOccurred())
@ -297,14 +300,58 @@ var _ = Describe("API test", func() {
Eventually(func() bool {
response := getModelStatus("http://127.0.0.1:9090/models/jobs/" + uuid)
fmt.Println(response)
return response["processed"].(bool)
}, "360s").Should(Equal(true))
}, "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(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))
})
It("runs gpt4all", Label("gpt4all"), func() {
@ -324,15 +371,126 @@ var _ = Describe("API test", func() {
Eventually(func() bool {
response := getModelStatus("http://127.0.0.1:9090/models/jobs/" + uuid)
fmt.Println(response)
return response["processed"].(bool)
}, "360s").Should(Equal(true))
}, "360s", "10s").Should(Equal(true))
resp, err := client.CreateChatCompletion(context.TODO(), openai.ChatCompletionRequest{Model: "gpt4all-j", Messages: []openai.ChatCompletionMessage{openai.ChatCompletionMessage{Role: "user", Content: "How are you?"}}})
Expect(err).ToNot(HaveOccurred())
Expect(len(resp.Choices)).To(Equal(1))
Expect(resp.Choices[0].Message.Content).To(ContainSubstring("well"))
})
})
})
Context("Model gallery", func() {
BeforeEach(func() {
var err error
tmpdir, err = os.MkdirTemp("", "")
Expect(err).ToNot(HaveOccurred())
modelLoader = model.NewModelLoader(tmpdir)
c, cancel = context.WithCancel(context.Background())
galleries := []gallery.Gallery{
{
Name: "model-gallery",
URL: "https://raw.githubusercontent.com/go-skynet/model-gallery/main/index.yaml",
},
}
app, err = App(
options.WithContext(c),
options.WithAudioDir(tmpdir),
options.WithImageDir(tmpdir),
options.WithGalleries(galleries),
options.WithModelLoader(modelLoader),
options.WithBackendAssets(backendAssets),
options.WithBackendAssetsOutput(tmpdir),
)
Expect(err).ToNot(HaveOccurred())
go app.Listen("127.0.0.1:9090")
defaultConfig := openai.DefaultConfig("")
defaultConfig.BaseURL = "http://127.0.0.1:9090/v1"
client2 = openaigo.NewClient("")
client2.BaseURL = defaultConfig.BaseURL
// Wait for API to be ready
client = openai.NewClientWithConfig(defaultConfig)
Eventually(func() error {
_, err := client.ListModels(context.TODO())
return err
}, "2m").ShouldNot(HaveOccurred())
})
AfterEach(func() {
cancel()
app.Shutdown()
os.RemoveAll(tmpdir)
})
It("installs and is capable to run tts", Label("tts"), func() {
if runtime.GOOS != "linux" {
Skip("test supported only on linux")
}
response := postModelApplyRequest("http://127.0.0.1:9090/models/apply", modelApplyRequest{
ID: "model-gallery@voice-en-us-kathleen-low",
})
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)
fmt.Println(response)
return response["processed"].(bool)
}, "360s", "10s").Should(Equal(true))
// An HTTP Post to the /tts endpoint should return a wav audio file
resp, err := http.Post("http://127.0.0.1:9090/tts", "application/json", bytes.NewBuffer([]byte(`{"input": "Hello world", "model": "en-us-kathleen-low.onnx"}`)))
Expect(err).ToNot(HaveOccurred(), fmt.Sprint(resp))
dat, err := io.ReadAll(resp.Body)
Expect(err).ToNot(HaveOccurred(), fmt.Sprint(resp))
Expect(resp.StatusCode).To(Equal(200), fmt.Sprint(string(dat)))
Expect(resp.Header.Get("Content-Type")).To(Equal("audio/x-wav"))
})
It("installs and is capable to generate images", Label("stablediffusion"), func() {
if runtime.GOOS != "linux" {
Skip("test supported only on linux")
}
response := postModelApplyRequest("http://127.0.0.1:9090/models/apply", modelApplyRequest{
ID: "model-gallery@stablediffusion",
})
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)
fmt.Println(response)
return response["processed"].(bool)
}, "360s", "10s").Should(Equal(true))
resp, err := http.Post(
"http://127.0.0.1:9090/v1/images/generations",
"application/json",
bytes.NewBuffer([]byte(`{
"prompt": "floating hair, portrait, ((loli)), ((one girl)), cute face, hidden hands, asymmetrical bangs, beautiful detailed eyes, eye shadow, hair ornament, ribbons, bowties, buttons, pleated skirt, (((masterpiece))), ((best quality)), colorful|((part of the head)), ((((mutated hands and fingers)))), deformed, blurry, bad anatomy, disfigured, poorly drawn face, mutation, mutated, extra limb, ugly, poorly drawn hands, missing limb, blurry, floating limbs, disconnected limbs, malformed hands, blur, out of focus, long neck, long body, Octane renderer, lowres, bad anatomy, bad hands, text",
"mode": 2, "seed":9000,
"size": "256x256", "n":2}`)))
// The response should contain an URL
Expect(err).ToNot(HaveOccurred(), fmt.Sprint(resp))
dat, err := io.ReadAll(resp.Body)
Expect(err).ToNot(HaveOccurred(), string(dat))
Expect(string(dat)).To(ContainSubstring("http://127.0.0.1:9090/"), string(dat))
Expect(string(dat)).To(ContainSubstring(".png"), string(dat))
})
})
@ -342,7 +500,7 @@ var _ = Describe("API test", func() {
c, cancel = context.WithCancel(context.Background())
var err error
app, err = App(WithContext(c), WithModelLoader(modelLoader))
app, err = App(options.WithContext(c), options.WithModelLoader(modelLoader))
Expect(err).ToNot(HaveOccurred())
go app.Listen("127.0.0.1:9090")
@ -399,7 +557,7 @@ var _ = Describe("API test", func() {
It("returns errors", func() {
_, err := client.CreateCompletion(context.TODO(), openai.CompletionRequest{Model: "foomodel", Prompt: "abcdedfghikl"})
Expect(err).To(HaveOccurred())
Expect(err.Error()).To(ContainSubstring("error, status code: 500, message: could not load model - all backends returned error: 11 errors occurred:"))
Expect(err.Error()).To(ContainSubstring("error, status code: 500, message: could not load model - all backends returned error: 12 errors occurred:"))
})
It("transcribes audio", func() {
if runtime.GOOS != "linux" {
@ -444,14 +602,67 @@ var _ = Describe("API test", func() {
})
Context("backends", func() {
It("runs rwkv", 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(Equal(" five."))
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(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(text).To(Or(ContainSubstring("Sure"), ContainSubstring("five")))
Expect(tokens).ToNot(Or(Equal(1), Equal(0)))
})
})
})
@ -462,7 +673,7 @@ var _ = Describe("API test", func() {
c, cancel = context.WithCancel(context.Background())
var err error
app, err = App(WithContext(c), WithModelLoader(modelLoader), WithConfigFile(os.Getenv("CONFIG_FILE")))
app, err = App(options.WithContext(c), options.WithModelLoader(modelLoader), options.WithConfigFile(os.Getenv("CONFIG_FILE")))
Expect(err).ToNot(HaveOccurred())
go app.Listen("127.0.0.1:9090")

@ -0,0 +1,105 @@
package backend
import (
"fmt"
"sync"
config "github.com/go-skynet/LocalAI/api/config"
"github.com/go-skynet/LocalAI/api/options"
"github.com/go-skynet/LocalAI/pkg/grpc"
model "github.com/go-skynet/LocalAI/pkg/model"
)
func ModelEmbedding(s string, tokens []int, loader *model.ModelLoader, c config.Config, o *options.Option) (func() ([]float32, error), error) {
if !c.Embeddings {
return nil, fmt.Errorf("endpoint disabled for this model by API configuration")
}
modelFile := c.Model
grpcOpts := gRPCModelOpts(c)
var inferenceModel interface{}
var err error
opts := []model.Option{
model.WithLoadGRPCLLMModelOpts(grpcOpts),
model.WithThreads(uint32(c.Threads)),
model.WithAssetDir(o.AssetsDestination),
model.WithModelFile(modelFile),
model.WithContext(o.Context),
}
if c.Backend == "" {
inferenceModel, err = loader.GreedyLoader(opts...)
} else {
opts = append(opts, model.WithBackendString(c.Backend))
inferenceModel, err = loader.BackendLoader(opts...)
}
if err != nil {
return nil, err
}
var fn func() ([]float32, error)
switch model := inferenceModel.(type) {
case *grpc.Client:
fn = func() ([]float32, error) {
predictOptions := gRPCPredictOpts(c, loader.ModelPath)
if len(tokens) > 0 {
embeds := []int32{}
for _, t := range tokens {
embeds = append(embeds, int32(t))
}
predictOptions.EmbeddingTokens = embeds
res, err := model.Embeddings(o.Context, predictOptions)
if err != nil {
return nil, err
}
return res.Embeddings, nil
}
predictOptions.Embeddings = s
res, err := model.Embeddings(o.Context, predictOptions)
if err != nil {
return nil, err
}
return res.Embeddings, nil
}
default:
fn = func() ([]float32, error) {
return nil, fmt.Errorf("embeddings not supported by the backend")
}
}
return func() ([]float32, error) {
// This is still needed, see: https://github.com/ggerganov/llama.cpp/discussions/784
mutexMap.Lock()
l, ok := mutexes[modelFile]
if !ok {
m := &sync.Mutex{}
mutexes[modelFile] = m
l = m
}
mutexMap.Unlock()
l.Lock()
defer l.Unlock()
embeds, err := fn()
if err != nil {
return embeds, err
}
// Remove trailing 0s
for i := len(embeds) - 1; i >= 0; i-- {
if embeds[i] == 0.0 {
embeds = embeds[:i]
} else {
break
}
}
return embeds, nil
}, nil
}

@ -0,0 +1,60 @@
package backend
import (
"fmt"
"sync"
config "github.com/go-skynet/LocalAI/api/config"
"github.com/go-skynet/LocalAI/api/options"
"github.com/go-skynet/LocalAI/pkg/grpc/proto"
model "github.com/go-skynet/LocalAI/pkg/model"
)
func ImageGeneration(height, width, mode, step, seed int, positive_prompt, negative_prompt, dst string, loader *model.ModelLoader, c config.Config, o *options.Option) (func() error, error) {
if c.Backend != model.StableDiffusionBackend {
return nil, fmt.Errorf("endpoint only working with stablediffusion models")
}
inferenceModel, err := loader.BackendLoader(
model.WithBackendString(c.Backend),
model.WithAssetDir(o.AssetsDestination),
model.WithThreads(uint32(c.Threads)),
model.WithContext(o.Context),
model.WithModelFile(c.ImageGenerationAssets),
)
if err != nil {
return nil, err
}
fn := func() error {
_, err := inferenceModel.GenerateImage(
o.Context,
&proto.GenerateImageRequest{
Height: int32(height),
Width: int32(width),
Mode: int32(mode),
Step: int32(step),
Seed: int32(seed),
PositivePrompt: positive_prompt,
NegativePrompt: negative_prompt,
Dst: dst,
})
return err
}
return func() error {
// This is still needed, see: https://github.com/ggerganov/llama.cpp/discussions/784
mutexMap.Lock()
l, ok := mutexes[c.Backend]
if !ok {
m := &sync.Mutex{}
mutexes[c.Backend] = m
l = m
}
mutexMap.Unlock()
l.Lock()
defer l.Unlock()
return fn()
}, nil
}

@ -0,0 +1,98 @@
package backend
import (
"regexp"
"strings"
"sync"
config "github.com/go-skynet/LocalAI/api/config"
"github.com/go-skynet/LocalAI/api/options"
"github.com/go-skynet/LocalAI/pkg/grpc"
model "github.com/go-skynet/LocalAI/pkg/model"
)
func ModelInference(s string, loader *model.ModelLoader, c config.Config, o *options.Option, tokenCallback func(string) bool) (func() (string, error), error) {
modelFile := c.Model
grpcOpts := gRPCModelOpts(c)
var inferenceModel *grpc.Client
var err error
opts := []model.Option{
model.WithLoadGRPCLLMModelOpts(grpcOpts),
model.WithThreads(uint32(c.Threads)), // some models uses this to allocate threads during startup
model.WithAssetDir(o.AssetsDestination),
model.WithModelFile(modelFile),
model.WithContext(o.Context),
}
if c.Backend == "" {
inferenceModel, err = loader.GreedyLoader(opts...)
} else {
opts = append(opts, model.WithBackendString(c.Backend))
inferenceModel, err = loader.BackendLoader(opts...)
}
if err != nil {
return nil, err
}
// in GRPC, the backend is supposed to answer to 1 single token if stream is not supported
fn := func() (string, error) {
opts := gRPCPredictOpts(c, loader.ModelPath)
opts.Prompt = s
if tokenCallback != nil {
ss := ""
err := inferenceModel.PredictStream(o.Context, opts, func(s string) {
tokenCallback(s)
ss += s
})
return ss, err
} else {
reply, err := inferenceModel.Predict(o.Context, opts)
return reply.Message, err
}
}
return func() (string, error) {
// This is still needed, see: https://github.com/ggerganov/llama.cpp/discussions/784
mutexMap.Lock()
l, ok := mutexes[modelFile]
if !ok {
m := &sync.Mutex{}
mutexes[modelFile] = m
l = m
}
mutexMap.Unlock()
l.Lock()
defer l.Unlock()
return fn()
}, nil
}
var cutstrings map[string]*regexp.Regexp = make(map[string]*regexp.Regexp)
var mu sync.Mutex = sync.Mutex{}
func Finetune(config config.Config, input, prediction string) string {
if config.Echo {
prediction = input + prediction
}
for _, c := range config.Cutstrings {
mu.Lock()
reg, ok := cutstrings[c]
if !ok {
cutstrings[c] = regexp.MustCompile(c)
reg = cutstrings[c]
}
mu.Unlock()
prediction = reg.ReplaceAllString(prediction, "")
}
for _, c := range config.TrimSpace {
prediction = strings.TrimSpace(strings.TrimPrefix(prediction, c))
}
return prediction
}

@ -0,0 +1,22 @@
package backend
import "sync"
// mutex still needed, see: https://github.com/ggerganov/llama.cpp/discussions/784
var mutexMap sync.Mutex
var mutexes map[string]*sync.Mutex = make(map[string]*sync.Mutex)
func Lock(s string) *sync.Mutex {
// This is still needed, see: https://github.com/ggerganov/llama.cpp/discussions/784
mutexMap.Lock()
l, ok := mutexes[s]
if !ok {
m := &sync.Mutex{}
mutexes[s] = m
l = m
}
mutexMap.Unlock()
l.Lock()
return l
}

@ -0,0 +1,72 @@
package backend
import (
"os"
"path/filepath"
pb "github.com/go-skynet/LocalAI/pkg/grpc/proto"
config "github.com/go-skynet/LocalAI/api/config"
)
func gRPCModelOpts(c config.Config) *pb.ModelOptions {
b := 512
if c.Batch != 0 {
b = c.Batch
}
return &pb.ModelOptions{
ContextSize: int32(c.ContextSize),
Seed: int32(c.Seed),
NBatch: int32(b),
F16Memory: c.F16,
MLock: c.MMlock,
NUMA: c.NUMA,
Embeddings: c.Embeddings,
LowVRAM: c.LowVRAM,
NGPULayers: int32(c.NGPULayers),
MMap: c.MMap,
MainGPU: c.MainGPU,
Threads: int32(c.Threads),
TensorSplit: c.TensorSplit,
}
}
func gRPCPredictOpts(c config.Config, modelPath string) *pb.PredictOptions {
promptCachePath := ""
if c.PromptCachePath != "" {
p := filepath.Join(modelPath, c.PromptCachePath)
os.MkdirAll(filepath.Dir(p), 0755)
promptCachePath = p
}
return &pb.PredictOptions{
Temperature: float32(c.Temperature),
TopP: float32(c.TopP),
TopK: int32(c.TopK),
Tokens: int32(c.Maxtokens),
Threads: int32(c.Threads),
PromptCacheAll: c.PromptCacheAll,
PromptCacheRO: c.PromptCacheRO,
PromptCachePath: promptCachePath,
F16KV: c.F16,
DebugMode: c.Debug,
Grammar: c.Grammar,
Mirostat: int32(c.Mirostat),
MirostatETA: float32(c.MirostatETA),
MirostatTAU: float32(c.MirostatTAU),
Debug: c.Debug,
StopPrompts: c.StopWords,
Repeat: int32(c.RepeatPenalty),
NKeep: int32(c.Keep),
Batch: int32(c.Batch),
IgnoreEOS: c.IgnoreEOS,
Seed: int32(c.Seed),
FrequencyPenalty: float32(c.FrequencyPenalty),
MLock: c.MMlock,
MMap: c.MMap,
MainGPU: c.MainGPU,
TensorSplit: c.TensorSplit,
TailFreeSamplingZ: float32(c.TFZ),
TypicalP: float32(c.TypicalP),
}
}

@ -1,401 +0,0 @@
package api
import (
"encoding/json"
"fmt"
"io/fs"
"os"
"path/filepath"
"strings"
"sync"
model "github.com/go-skynet/LocalAI/pkg/model"
"github.com/gofiber/fiber/v2"
"github.com/rs/zerolog/log"
"gopkg.in/yaml.v3"
)
type Config struct {
OpenAIRequest `yaml:"parameters"`
Name string `yaml:"name"`
StopWords []string `yaml:"stopwords"`
Cutstrings []string `yaml:"cutstrings"`
TrimSpace []string `yaml:"trimspace"`
ContextSize int `yaml:"context_size"`
F16 bool `yaml:"f16"`
NUMA bool `yaml:"numa"`
Threads int `yaml:"threads"`
Debug bool `yaml:"debug"`
Roles map[string]string `yaml:"roles"`
Embeddings bool `yaml:"embeddings"`
Backend string `yaml:"backend"`
TemplateConfig TemplateConfig `yaml:"template"`
MirostatETA float64 `yaml:"mirostat_eta"`
MirostatTAU float64 `yaml:"mirostat_tau"`
Mirostat int `yaml:"mirostat"`
NGPULayers int `yaml:"gpu_layers"`
MMap bool `yaml:"mmap"`
MMlock bool `yaml:"mmlock"`
LowVRAM bool `yaml:"low_vram"`
TensorSplit string `yaml:"tensor_split"`
MainGPU string `yaml:"main_gpu"`
ImageGenerationAssets string `yaml:"asset_dir"`
PromptCachePath string `yaml:"prompt_cache_path"`
PromptCacheAll bool `yaml:"prompt_cache_all"`
PromptCacheRO bool `yaml:"prompt_cache_ro"`
Grammar string `yaml:"grammar"`
FunctionsConfig Functions `yaml:"function"`
PromptStrings, InputStrings []string
InputToken [][]int
functionCallString, functionCallNameString string
}
type Functions struct {
DisableNoAction bool `yaml:"disable_no_action"`
NoActionFunctionName string `yaml:"no_action_function_name"`
NoActionDescriptionName string `yaml:"no_action_description_name"`
}
type TemplateConfig struct {
Completion string `yaml:"completion"`
Functions string `yaml:"function"`
Chat string `yaml:"chat"`
Edit string `yaml:"edit"`
}
type ConfigMerger struct {
configs map[string]Config
sync.Mutex
}
func defaultConfig(modelFile string) *Config {
return &Config{
OpenAIRequest: defaultRequest(modelFile),
}
}
func NewConfigMerger() *ConfigMerger {
return &ConfigMerger{
configs: make(map[string]Config),
}
}
func ReadConfigFile(file string) ([]*Config, error) {
c := &[]*Config{}
f, err := os.ReadFile(file)
if err != nil {
return nil, fmt.Errorf("cannot read config file: %w", err)
}
if err := yaml.Unmarshal(f, c); err != nil {
return nil, fmt.Errorf("cannot unmarshal config file: %w", err)
}
return *c, nil
}
func ReadConfig(file string) (*Config, error) {
c := &Config{}
f, err := os.ReadFile(file)
if err != nil {
return nil, fmt.Errorf("cannot read config file: %w", err)
}
if err := yaml.Unmarshal(f, c); err != nil {
return nil, fmt.Errorf("cannot unmarshal config file: %w", err)
}
return c, nil
}
func (cm *ConfigMerger) LoadConfigFile(file string) error {
cm.Lock()
defer cm.Unlock()
c, err := ReadConfigFile(file)
if err != nil {
return fmt.Errorf("cannot load config file: %w", err)
}
for _, cc := range c {
cm.configs[cc.Name] = *cc
}
return nil
}
func (cm *ConfigMerger) LoadConfig(file string) error {
cm.Lock()
defer cm.Unlock()
c, err := ReadConfig(file)
if err != nil {
return fmt.Errorf("cannot read config file: %w", err)
}
cm.configs[c.Name] = *c
return nil
}
func (cm *ConfigMerger) GetConfig(m string) (Config, bool) {
cm.Lock()
defer cm.Unlock()
v, exists := cm.configs[m]
return v, exists
}
func (cm *ConfigMerger) ListConfigs() []string {
cm.Lock()
defer cm.Unlock()
var res []string
for k := range cm.configs {
res = append(res, k)
}
return res
}
func (cm *ConfigMerger) LoadConfigs(path string) error {
cm.Lock()
defer cm.Unlock()
entries, err := os.ReadDir(path)
if err != nil {
return err
}
files := make([]fs.FileInfo, 0, len(entries))
for _, entry := range entries {
info, err := entry.Info()
if err != nil {
return err
}
files = append(files, info)
}
for _, file := range files {
// Skip templates, YAML and .keep files
if !strings.Contains(file.Name(), ".yaml") {
continue
}
c, err := ReadConfig(filepath.Join(path, file.Name()))
if err == nil {
cm.configs[c.Name] = *c
}
}
return nil
}
func updateConfig(config *Config, input *OpenAIRequest) {
if input.Echo {
config.Echo = input.Echo
}
if input.TopK != 0 {
config.TopK = input.TopK
}
if input.TopP != 0 {
config.TopP = input.TopP
}
if input.Grammar != "" {
config.Grammar = input.Grammar
}
if input.Temperature != 0 {
config.Temperature = input.Temperature
}
if input.Maxtokens != 0 {
config.Maxtokens = input.Maxtokens
}
switch stop := input.Stop.(type) {
case string:
if stop != "" {
config.StopWords = append(config.StopWords, stop)
}
case []interface{}:
for _, pp := range stop {
if s, ok := pp.(string); ok {
config.StopWords = append(config.StopWords, s)
}
}
}
if input.RepeatPenalty != 0 {
config.RepeatPenalty = input.RepeatPenalty
}
if input.Keep != 0 {
config.Keep = input.Keep
}
if input.Batch != 0 {
config.Batch = input.Batch
}
if input.F16 {
config.F16 = input.F16
}
if input.IgnoreEOS {
config.IgnoreEOS = input.IgnoreEOS
}
if input.Seed != 0 {
config.Seed = input.Seed
}
if input.Mirostat != 0 {
config.Mirostat = input.Mirostat
}
if input.MirostatETA != 0 {
config.MirostatETA = input.MirostatETA
}
if input.MirostatTAU != 0 {
config.MirostatTAU = input.MirostatTAU
}
if input.TypicalP != 0 {
config.TypicalP = input.TypicalP
}
switch inputs := input.Input.(type) {
case string:
if inputs != "" {
config.InputStrings = append(config.InputStrings, inputs)
}
case []interface{}:
for _, pp := range inputs {
switch i := pp.(type) {
case string:
config.InputStrings = append(config.InputStrings, i)
case []interface{}:
tokens := []int{}
for _, ii := range i {
tokens = append(tokens, int(ii.(float64)))
}
config.InputToken = append(config.InputToken, tokens)
}
}
}
// Can be either a string or an object
switch fnc := input.FunctionCall.(type) {
case string:
if fnc != "" {
config.functionCallString = fnc
}
case map[string]interface{}:
var name string
n, exists := fnc["name"]
if exists {
nn, e := n.(string)
if e {
name = nn
}
}
config.functionCallNameString = name
}
switch p := input.Prompt.(type) {
case string:
config.PromptStrings = append(config.PromptStrings, p)
case []interface{}:
for _, pp := range p {
if s, ok := pp.(string); ok {
config.PromptStrings = append(config.PromptStrings, s)
}
}
}
}
func readInput(c *fiber.Ctx, loader *model.ModelLoader, randomModel bool) (string, *OpenAIRequest, error) {
input := new(OpenAIRequest)
// Get input data from the request body
if err := c.BodyParser(input); err != nil {
return "", nil, err
}
modelFile := input.Model
if c.Params("model") != "" {
modelFile = c.Params("model")
}
received, _ := json.Marshal(input)
log.Debug().Msgf("Request received: %s", string(received))
// Set model from bearer token, if available
bearer := strings.TrimLeft(c.Get("authorization"), "Bearer ")
bearerExists := bearer != "" && loader.ExistsInModelPath(bearer)
// If no model was specified, take the first available
if modelFile == "" && !bearerExists && randomModel {
models, _ := loader.ListModels()
if len(models) > 0 {
modelFile = models[0]
log.Debug().Msgf("No model specified, using: %s", modelFile)
} else {
log.Debug().Msgf("No model specified, returning error")
return "", nil, fmt.Errorf("no model specified")
}
}
// If a model is found in bearer token takes precedence
if bearerExists {
log.Debug().Msgf("Using model from bearer token: %s", bearer)
modelFile = bearer
}
return modelFile, input, nil
}
func readConfig(modelFile string, input *OpenAIRequest, cm *ConfigMerger, loader *model.ModelLoader, debug bool, threads, ctx int, f16 bool) (*Config, *OpenAIRequest, error) {
// Load a config file if present after the model name
modelConfig := filepath.Join(loader.ModelPath, modelFile+".yaml")
var config *Config
defaults := func() {
config = defaultConfig(modelFile)
config.ContextSize = ctx
config.Threads = threads
config.F16 = f16
config.Debug = debug
}
cfg, exists := cm.GetConfig(modelFile)
if !exists {
if _, err := os.Stat(modelConfig); err == nil {
if err := cm.LoadConfig(modelConfig); err != nil {
return nil, nil, fmt.Errorf("failed loading model config (%s) %s", modelConfig, err.Error())
}
cfg, exists = cm.GetConfig(modelFile)
if exists {
config = &cfg
} else {
defaults()
}
} else {
defaults()
}
} else {
config = &cfg
}
// Set the parameters for the language model prediction
updateConfig(config, input)
// Don't allow 0 as setting
if config.Threads == 0 {
if threads != 0 {
config.Threads = threads
} else {
config.Threads = 4
}
}
// Enforce debug flag if passed from CLI
if debug {
config.Debug = true
}
return config, input, nil
}

@ -0,0 +1,209 @@
package api_config
import (
"fmt"
"io/fs"
"os"
"path/filepath"
"strings"
"sync"
"gopkg.in/yaml.v3"
)
type Config struct {
PredictionOptions `yaml:"parameters"`
Name string `yaml:"name"`
StopWords []string `yaml:"stopwords"`
Cutstrings []string `yaml:"cutstrings"`
TrimSpace []string `yaml:"trimspace"`
ContextSize int `yaml:"context_size"`
F16 bool `yaml:"f16"`
NUMA bool `yaml:"numa"`
Threads int `yaml:"threads"`
Debug bool `yaml:"debug"`
Roles map[string]string `yaml:"roles"`
Embeddings bool `yaml:"embeddings"`
Backend string `yaml:"backend"`
TemplateConfig TemplateConfig `yaml:"template"`
MirostatETA float64 `yaml:"mirostat_eta"`
MirostatTAU float64 `yaml:"mirostat_tau"`
Mirostat int `yaml:"mirostat"`
NGPULayers int `yaml:"gpu_layers"`
MMap bool `yaml:"mmap"`
MMlock bool `yaml:"mmlock"`
LowVRAM bool `yaml:"low_vram"`
TensorSplit string `yaml:"tensor_split"`
MainGPU string `yaml:"main_gpu"`
ImageGenerationAssets string `yaml:"asset_dir"`
PromptCachePath string `yaml:"prompt_cache_path"`
PromptCacheAll bool `yaml:"prompt_cache_all"`
PromptCacheRO bool `yaml:"prompt_cache_ro"`
Grammar string `yaml:"grammar"`
PromptStrings, InputStrings []string
InputToken [][]int
functionCallString, functionCallNameString string
FunctionsConfig Functions `yaml:"function"`
}
type Functions struct {
DisableNoAction bool `yaml:"disable_no_action"`
NoActionFunctionName string `yaml:"no_action_function_name"`
NoActionDescriptionName string `yaml:"no_action_description_name"`
}
type TemplateConfig struct {
Completion string `yaml:"completion"`
Functions string `yaml:"function"`
Chat string `yaml:"chat"`
Edit string `yaml:"edit"`
}
type ConfigLoader struct {
configs map[string]Config
sync.Mutex
}
func (c *Config) SetFunctionCallString(s string) {
c.functionCallString = s
}
func (c *Config) SetFunctionCallNameString(s string) {
c.functionCallNameString = s
}
func (c *Config) ShouldUseFunctions() bool {
return ((c.functionCallString != "none" || c.functionCallString == "") || c.ShouldCallSpecificFunction())
}
func (c *Config) ShouldCallSpecificFunction() bool {
return len(c.functionCallNameString) > 0
}
func (c *Config) FunctionToCall() string {
return c.functionCallNameString
}
func defaultPredictOptions(modelFile string) PredictionOptions {
return PredictionOptions{
TopP: 0.7,
TopK: 80,
Maxtokens: 512,
Temperature: 0.9,
Model: modelFile,
}
}
func DefaultConfig(modelFile string) *Config {
return &Config{
PredictionOptions: defaultPredictOptions(modelFile),
}
}
func NewConfigLoader() *ConfigLoader {
return &ConfigLoader{
configs: make(map[string]Config),
}
}
func ReadConfigFile(file string) ([]*Config, error) {
c := &[]*Config{}
f, err := os.ReadFile(file)
if err != nil {
return nil, fmt.Errorf("cannot read config file: %w", err)
}
if err := yaml.Unmarshal(f, c); err != nil {
return nil, fmt.Errorf("cannot unmarshal config file: %w", err)
}
return *c, nil
}
func ReadConfig(file string) (*Config, error) {
c := &Config{}
f, err := os.ReadFile(file)
if err != nil {
return nil, fmt.Errorf("cannot read config file: %w", err)
}
if err := yaml.Unmarshal(f, c); err != nil {
return nil, fmt.Errorf("cannot unmarshal config file: %w", err)
}
return c, nil
}
func (cm *ConfigLoader) LoadConfigFile(file string) error {
cm.Lock()
defer cm.Unlock()
c, err := ReadConfigFile(file)
if err != nil {
return fmt.Errorf("cannot load config file: %w", err)
}
for _, cc := range c {
cm.configs[cc.Name] = *cc
}
return nil
}
func (cm *ConfigLoader) LoadConfig(file string) error {
cm.Lock()
defer cm.Unlock()
c, err := ReadConfig(file)
if err != nil {
return fmt.Errorf("cannot read config file: %w", err)
}
cm.configs[c.Name] = *c
return nil
}
func (cm *ConfigLoader) GetConfig(m string) (Config, bool) {
cm.Lock()
defer cm.Unlock()
v, exists := cm.configs[m]
return v, exists
}
func (cm *ConfigLoader) ListConfigs() []string {
cm.Lock()
defer cm.Unlock()
var res []string
for k := range cm.configs {
res = append(res, k)
}
return res
}
func (cm *ConfigLoader) LoadConfigs(path string) error {
cm.Lock()
defer cm.Unlock()
entries, err := os.ReadDir(path)
if err != nil {
return err
}
files := make([]fs.FileInfo, 0, len(entries))
for _, entry := range entries {
info, err := entry.Info()
if err != nil {
return err
}
files = append(files, info)
}
for _, file := range files {
// Skip templates, YAML and .keep files
if !strings.Contains(file.Name(), ".yaml") {
continue
}
c, err := ReadConfig(filepath.Join(path, file.Name()))
if err == nil {
cm.configs[c.Name] = *c
}
}
return nil
}

@ -1,8 +1,10 @@
package api
package api_config_test
import (
"os"
. "github.com/go-skynet/LocalAI/api/config"
"github.com/go-skynet/LocalAI/api/options"
"github.com/go-skynet/LocalAI/pkg/model"
. "github.com/onsi/ginkgo/v2"
. "github.com/onsi/gomega"
@ -26,29 +28,29 @@ var _ = Describe("Test cases for config related functions", func() {
})
It("Test LoadConfigs", func() {
cm := NewConfigMerger()
options := newOptions()
cm := NewConfigLoader()
opts := options.NewOptions()
modelLoader := model.NewModelLoader(os.Getenv("MODELS_PATH"))
WithModelLoader(modelLoader)(options)
options.WithModelLoader(modelLoader)(opts)
err := cm.LoadConfigs(options.loader.ModelPath)
err := cm.LoadConfigs(opts.Loader.ModelPath)
Expect(err).To(BeNil())
Expect(cm.configs).ToNot(BeNil())
Expect(cm.ListConfigs()).ToNot(BeNil())
// config should includes gpt4all models's api.config
Expect(cm.configs).To(HaveKey("gpt4all"))
Expect(cm.ListConfigs()).To(ContainElements("gpt4all"))
// config should includes gpt2 models's api.config
Expect(cm.configs).To(HaveKey("gpt4all-2"))
Expect(cm.ListConfigs()).To(ContainElements("gpt4all-2"))
// config should includes text-embedding-ada-002 models's api.config
Expect(cm.configs).To(HaveKey("text-embedding-ada-002"))
Expect(cm.ListConfigs()).To(ContainElements("text-embedding-ada-002"))
// config should includes rwkv_test models's api.config
Expect(cm.configs).To(HaveKey("rwkv_test"))
Expect(cm.ListConfigs()).To(ContainElements("rwkv_test"))
// config should includes whisper-1 models's api.config
Expect(cm.configs).To(HaveKey("whisper-1"))
Expect(cm.ListConfigs()).To(ContainElements("whisper-1"))
})
})
})

@ -0,0 +1,37 @@
package api_config
type PredictionOptions struct {
// Also part of the OpenAI official spec
Model string `json:"model" yaml:"model"`
// Also part of the OpenAI official spec
Language string `json:"language"`
// Also part of the OpenAI official spec. use it for returning multiple results
N int `json:"n"`
// Common options between all the API calls, part of the OpenAI spec
TopP float64 `json:"top_p" yaml:"top_p"`
TopK int `json:"top_k" yaml:"top_k"`
Temperature float64 `json:"temperature" yaml:"temperature"`
Maxtokens int `json:"max_tokens" yaml:"max_tokens"`
Echo bool `json:"echo"`
// Custom parameters - not present in the OpenAI API
Batch int `json:"batch" yaml:"batch"`
F16 bool `json:"f16" yaml:"f16"`
IgnoreEOS bool `json:"ignore_eos" yaml:"ignore_eos"`
RepeatPenalty float64 `json:"repeat_penalty" yaml:"repeat_penalty"`
Keep int `json:"n_keep" yaml:"n_keep"`
MirostatETA float64 `json:"mirostat_eta" yaml:"mirostat_eta"`
MirostatTAU float64 `json:"mirostat_tau" yaml:"mirostat_tau"`
Mirostat int `json:"mirostat" yaml:"mirostat"`
FrequencyPenalty float64 `json:"frequency_penalty" yaml:"frequency_penalty"`
TFZ float64 `json:"tfz" yaml:"tfz"`
TypicalP float64 `json:"typical_p" yaml:"typical_p"`
Seed int `json:"seed" yaml:"seed"`
}

@ -1,78 +0,0 @@
package api
import (
"fmt"
"os"
"path/filepath"
model "github.com/go-skynet/LocalAI/pkg/model"
"github.com/go-skynet/LocalAI/pkg/tts"
"github.com/go-skynet/LocalAI/pkg/utils"
llama "github.com/go-skynet/go-llama.cpp"
"github.com/gofiber/fiber/v2"
)
type TTSRequest struct {
Model string `json:"model" yaml:"model"`
Input string `json:"input" yaml:"input"`
}
func generateUniqueFileName(dir, baseName, ext string) string {
counter := 1
fileName := baseName + ext
for {
filePath := filepath.Join(dir, fileName)
_, err := os.Stat(filePath)
if os.IsNotExist(err) {
return fileName
}
counter++
fileName = fmt.Sprintf("%s_%d%s", baseName, counter, ext)
}
}
func ttsEndpoint(cm *ConfigMerger, o *Option) func(c *fiber.Ctx) error {
return func(c *fiber.Ctx) error {
input := new(TTSRequest)
// Get input data from the request body
if err := c.BodyParser(input); err != nil {
return err
}
piperModel, err := o.loader.BackendLoader(model.PiperBackend, input.Model, []llama.ModelOption{}, uint32(0), o.assetsDestination)
if err != nil {
return err
}
if piperModel == nil {
return fmt.Errorf("could not load piper model")
}
w, ok := piperModel.(*tts.Piper)
if !ok {
return fmt.Errorf("loader returned non-piper object %+v", w)
}
if err := os.MkdirAll(o.audioDir, 0755); err != nil {
return err
}
fileName := generateUniqueFileName(o.audioDir, "piper", ".wav")
filePath := filepath.Join(o.audioDir, fileName)
modelPath := filepath.Join(o.loader.ModelPath, input.Model)
if err := utils.VerifyPath(modelPath, o.loader.ModelPath); err != nil {
return err
}
if err := w.TTS(input.Input, modelPath, filePath); err != nil {
return err
}
return c.Download(filePath)
}
}

@ -1,4 +1,4 @@
package api
package localai
import (
"context"
@ -9,6 +9,7 @@ import (
json "github.com/json-iterator/go"
config "github.com/go-skynet/LocalAI/api/config"
"github.com/go-skynet/LocalAI/pkg/gallery"
"github.com/gofiber/fiber/v2"
"github.com/google/uuid"
@ -38,7 +39,7 @@ type galleryApplier struct {
statuses map[string]*galleryOpStatus
}
func newGalleryApplier(modelPath string) *galleryApplier {
func NewGalleryService(modelPath string) *galleryApplier {
return &galleryApplier{
modelPath: modelPath,
C: make(chan galleryOp),
@ -47,7 +48,7 @@ func newGalleryApplier(modelPath string) *galleryApplier {
}
// prepareModel applies a
func prepareModel(modelPath string, req gallery.GalleryModel, cm *ConfigMerger, downloadStatus func(string, string, string, float64)) error {
func prepareModel(modelPath string, req gallery.GalleryModel, cm *config.ConfigLoader, downloadStatus func(string, string, string, float64)) error {
config, err := gallery.GetGalleryConfigFromURL(req.URL)
if err != nil {
@ -72,7 +73,7 @@ func (g *galleryApplier) getStatus(s string) *galleryOpStatus {
return g.statuses[s]
}
func (g *galleryApplier) start(c context.Context, cm *ConfigMerger) {
func (g *galleryApplier) Start(c context.Context, cm *config.ConfigLoader) {
go func() {
for {
select {
@ -148,7 +149,7 @@ type galleryModel struct {
ID string `json:"id"`
}
func ApplyGalleryFromFile(modelPath, s string, cm *ConfigMerger, galleries []gallery.Gallery) error {
func ApplyGalleryFromFile(modelPath, s string, cm *config.ConfigLoader, galleries []gallery.Gallery) error {
dat, err := os.ReadFile(s)
if err != nil {
return err
@ -156,7 +157,7 @@ func ApplyGalleryFromFile(modelPath, s string, cm *ConfigMerger, galleries []gal
return ApplyGalleryFromString(modelPath, string(dat), cm, galleries)
}
func ApplyGalleryFromString(modelPath, s string, cm *ConfigMerger, galleries []gallery.Gallery) error {
func ApplyGalleryFromString(modelPath, s string, cm *config.ConfigLoader, galleries []gallery.Gallery) error {
var requests []galleryModel
err := json.Unmarshal([]byte(s), &requests)
if err != nil {
@ -174,7 +175,9 @@ func ApplyGalleryFromString(modelPath, s string, cm *ConfigMerger, galleries []g
return err
}
func getOpStatus(g *galleryApplier) func(c *fiber.Ctx) error {
/// Endpoints
func GetOpStatusEndpoint(g *galleryApplier) func(c *fiber.Ctx) error {
return func(c *fiber.Ctx) error {
status := g.getStatus(c.Params("uuid"))
@ -191,7 +194,7 @@ type GalleryModel struct {
gallery.GalleryModel
}
func applyModelGallery(modelPath string, cm *ConfigMerger, g chan galleryOp, galleries []gallery.Gallery) func(c *fiber.Ctx) error {
func ApplyModelGalleryEndpoint(modelPath string, cm *config.ConfigLoader, g chan galleryOp, galleries []gallery.Gallery) func(c *fiber.Ctx) error {
return func(c *fiber.Ctx) error {
input := new(GalleryModel)
// Get input data from the request body
@ -216,7 +219,7 @@ func applyModelGallery(modelPath string, cm *ConfigMerger, g chan galleryOp, gal
}
}
func listModelFromGallery(galleries []gallery.Gallery, basePath string) func(c *fiber.Ctx) error {
func ListModelFromGalleryEndpoint(galleries []gallery.Gallery, basePath string) func(c *fiber.Ctx) error {
return func(c *fiber.Ctx) error {
log.Debug().Msgf("Listing models from galleries: %+v", galleries)

@ -0,0 +1,84 @@
package localai
import (
"context"
"fmt"
"os"
"path/filepath"
config "github.com/go-skynet/LocalAI/api/config"
"github.com/go-skynet/LocalAI/api/options"
"github.com/go-skynet/LocalAI/pkg/grpc/proto"
model "github.com/go-skynet/LocalAI/pkg/model"
"github.com/go-skynet/LocalAI/pkg/utils"
"github.com/gofiber/fiber/v2"
)
type TTSRequest struct {
Model string `json:"model" yaml:"model"`
Input string `json:"input" yaml:"input"`
}
func generateUniqueFileName(dir, baseName, ext string) string {
counter := 1
fileName := baseName + ext
for {
filePath := filepath.Join(dir, fileName)
_, err := os.Stat(filePath)
if os.IsNotExist(err) {
return fileName
}
counter++
fileName = fmt.Sprintf("%s_%d%s", baseName, counter, ext)
}
}
func TTSEndpoint(cm *config.ConfigLoader, o *options.Option) func(c *fiber.Ctx) error {
return func(c *fiber.Ctx) error {
input := new(TTSRequest)
// Get input data from the request body
if err := c.BodyParser(input); err != nil {
return err
}
piperModel, err := o.Loader.BackendLoader(
model.WithBackendString(model.PiperBackend),
model.WithModelFile(input.Model),
model.WithContext(o.Context),
model.WithAssetDir(o.AssetsDestination))
if err != nil {
return err
}
if piperModel == nil {
return fmt.Errorf("could not load piper model")
}
if err := os.MkdirAll(o.AudioDir, 0755); err != nil {
return fmt.Errorf("failed creating audio directory: %s", err)
}
fileName := generateUniqueFileName(o.AudioDir, "piper", ".wav")
filePath := filepath.Join(o.AudioDir, fileName)
modelPath := filepath.Join(o.Loader.ModelPath, input.Model)
if err := utils.VerifyPath(modelPath, o.Loader.ModelPath); err != nil {
return err
}
if _, err := piperModel.TTS(context.Background(), &proto.TTSRequest{
Text: input.Input,
Model: modelPath,
Dst: filePath,
}); err != nil {
return err
}
return c.Download(filePath)
}
}

@ -1,961 +0,0 @@
package api
import (
"bufio"
"bytes"
"encoding/base64"
"encoding/json"
"errors"
"fmt"
"io"
"io/ioutil"
"net/http"
"os"
"path"
"path/filepath"
"strconv"
"strings"
"github.com/ggerganov/whisper.cpp/bindings/go/pkg/whisper"
"github.com/go-skynet/LocalAI/pkg/grammar"
model "github.com/go-skynet/LocalAI/pkg/model"
whisperutil "github.com/go-skynet/LocalAI/pkg/whisper"
llama "github.com/go-skynet/go-llama.cpp"
"github.com/gofiber/fiber/v2"
"github.com/rs/zerolog/log"
"github.com/valyala/fasthttp"
)
// APIError provides error information returned by the OpenAI API.
type APIError struct {
Code any `json:"code,omitempty"`
Message string `json:"message"`
Param *string `json:"param,omitempty"`
Type string `json:"type"`
}
type ErrorResponse struct {
Error *APIError `json:"error,omitempty"`
}
type OpenAIUsage struct {
PromptTokens int `json:"prompt_tokens"`
CompletionTokens int `json:"completion_tokens"`
TotalTokens int `json:"total_tokens"`
}
type Item struct {
Embedding []float32 `json:"embedding"`
Index int `json:"index"`
Object string `json:"object,omitempty"`
// Images
URL string `json:"url,omitempty"`
B64JSON string `json:"b64_json,omitempty"`
}
type OpenAIResponse struct {
Created int `json:"created,omitempty"`
Object string `json:"object,omitempty"`
ID string `json:"id,omitempty"`
Model string `json:"model,omitempty"`
Choices []Choice `json:"choices,omitempty"`
Data []Item `json:"data,omitempty"`
Usage OpenAIUsage `json:"usage"`
}
type Choice struct {
Index int `json:"index,omitempty"`
FinishReason string `json:"finish_reason,omitempty"`
Message *Message `json:"message,omitempty"`
Delta *Message `json:"delta,omitempty"`
Text string `json:"text,omitempty"`
}
type Message struct {
// The message role
Role string `json:"role,omitempty" yaml:"role"`
// The message content
Content *string `json:"content" yaml:"content"`
// A result of a function call
FunctionCall interface{} `json:"function_call,omitempty" yaml:"function_call,omitempty"`
}
type OpenAIModel struct {
ID string `json:"id"`
Object string `json:"object"`
}
type OpenAIRequest struct {
Model string `json:"model" yaml:"model"`
// whisper
File string `json:"file" validate:"required"`
Language string `json:"language"`
//whisper/image
ResponseFormat string `json:"response_format"`
// image
Size string `json:"size"`
// Prompt is read only by completion/image API calls
Prompt interface{} `json:"prompt" yaml:"prompt"`
// Edit endpoint
Instruction string `json:"instruction" yaml:"instruction"`
Input interface{} `json:"input" yaml:"input"`
Stop interface{} `json:"stop" yaml:"stop"`
// Messages is read only by chat/completion API calls
Messages []Message `json:"messages" yaml:"messages"`
// A list of available functions to call
Functions []grammar.Function `json:"functions" yaml:"functions"`
FunctionCall interface{} `json:"function_call" yaml:"function_call"` // might be a string or an object
Stream bool `json:"stream"`
Echo bool `json:"echo"`
// Common options between all the API calls
TopP float64 `json:"top_p" yaml:"top_p"`
TopK int `json:"top_k" yaml:"top_k"`
Temperature float64 `json:"temperature" yaml:"temperature"`
Maxtokens int `json:"max_tokens" yaml:"max_tokens"`
N int `json:"n"`
// Custom parameters - not present in the OpenAI API
Batch int `json:"batch" yaml:"batch"`
F16 bool `json:"f16" yaml:"f16"`
IgnoreEOS bool `json:"ignore_eos" yaml:"ignore_eos"`
RepeatPenalty float64 `json:"repeat_penalty" yaml:"repeat_penalty"`
Keep int `json:"n_keep" yaml:"n_keep"`
MirostatETA float64 `json:"mirostat_eta" yaml:"mirostat_eta"`
MirostatTAU float64 `json:"mirostat_tau" yaml:"mirostat_tau"`
Mirostat int `json:"mirostat" yaml:"mirostat"`
FrequencyPenalty float64 `json:"frequency_penalty" yaml:"frequency_penalty"`
TFZ float64 `json:"tfz" yaml:"tfz"`
Seed int `json:"seed" yaml:"seed"`
// Image (not supported by OpenAI)
Mode int `json:"mode"`
Step int `json:"step"`
// A grammar to constrain the LLM output
Grammar string `json:"grammar" yaml:"grammar"`
// A grammar object
JSONFunctionGrammarObject *grammar.JSONFunctionStructure `json:"grammar_json_functions" yaml:"grammar_json_functions"`
TypicalP float64 `json:"typical_p" yaml:"typical_p"`
}
func defaultRequest(modelFile string) OpenAIRequest {
return OpenAIRequest{
TopP: 0.7,
TopK: 80,
Maxtokens: 512,
Temperature: 0.9,
Model: modelFile,
}
}
// https://platform.openai.com/docs/api-reference/completions
func completionEndpoint(cm *ConfigMerger, o *Option) func(c *fiber.Ctx) error {
process := func(s string, req *OpenAIRequest, config *Config, loader *model.ModelLoader, responses chan OpenAIResponse) {
ComputeChoices(s, req, config, o, loader, func(s string, c *[]Choice) {}, func(s string) bool {
resp := OpenAIResponse{
Model: req.Model, // we have to return what the user sent here, due to OpenAI spec.
Choices: []Choice{
{
Index: 0,
Text: s,
},
},
Object: "text_completion",
}
log.Debug().Msgf("Sending goroutine: %s", s)
responses <- resp
return true
})
close(responses)
}
return func(c *fiber.Ctx) error {
model, input, err := readInput(c, o.loader, true)
if err != nil {
return fmt.Errorf("failed reading parameters from request:%w", err)
}
log.Debug().Msgf("`input`: %+v", input)
config, input, err := readConfig(model, input, cm, o.loader, o.debug, o.threads, o.ctxSize, o.f16)
if err != nil {
return fmt.Errorf("failed reading parameters from request:%w", err)
}
log.Debug().Msgf("Parameter Config: %+v", config)
if input.Stream {
log.Debug().Msgf("Stream request received")
c.Context().SetContentType("text/event-stream")
//c.Response().Header.SetContentType(fiber.MIMETextHTMLCharsetUTF8)
//c.Set("Content-Type", "text/event-stream")
c.Set("Cache-Control", "no-cache")
c.Set("Connection", "keep-alive")
c.Set("Transfer-Encoding", "chunked")
}
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")
}
predInput := config.PromptStrings[0]
// A model can have a "file.bin.tmpl" file associated with a prompt template prefix
templatedInput, err := o.loader.TemplatePrefix(templateFile, struct {
Input string
}{
Input: predInput,
})
if err == nil {
predInput = templatedInput
log.Debug().Msgf("Template found, input modified to: %s", predInput)
}
responses := make(chan OpenAIResponse)
go process(predInput, input, config, o.loader, responses)
c.Context().SetBodyStreamWriter(fasthttp.StreamWriter(func(w *bufio.Writer) {
for ev := range responses {
var buf bytes.Buffer
enc := json.NewEncoder(&buf)
enc.Encode(ev)
log.Debug().Msgf("Sending chunk: %s", buf.String())
fmt.Fprintf(w, "data: %v\n", buf.String())
w.Flush()
}
resp := &OpenAIResponse{
Model: input.Model, // we have to return what the user sent here, due to OpenAI spec.
Choices: []Choice{
{
Index: 0,
FinishReason: "stop",
},
},
Object: "text_completion",
}
respData, _ := json.Marshal(resp)
w.WriteString(fmt.Sprintf("data: %s\n\n", respData))
w.WriteString("data: [DONE]\n\n")
w.Flush()
}))
return nil
}
var result []Choice
for _, i := range config.PromptStrings {
// A model can have a "file.bin.tmpl" file associated with a prompt template prefix
templatedInput, err := o.loader.TemplatePrefix(templateFile, struct {
Input string
}{
Input: i,
})
if err == nil {
i = templatedInput
log.Debug().Msgf("Template found, input modified to: %s", i)
}
r, err := ComputeChoices(i, input, config, o, o.loader, func(s string, c *[]Choice) {
*c = append(*c, Choice{Text: s})
}, nil)
if err != nil {
return err
}
result = append(result, r...)
}
resp := &OpenAIResponse{
Model: input.Model, // we have to return what the user sent here, due to OpenAI spec.
Choices: result,
Object: "text_completion",
}
jsonResult, _ := json.Marshal(resp)
log.Debug().Msgf("Response: %s", jsonResult)
// Return the prediction in the response body
return c.JSON(resp)
}
}
// https://platform.openai.com/docs/api-reference/embeddings
func embeddingsEndpoint(cm *ConfigMerger, o *Option) func(c *fiber.Ctx) error {
return func(c *fiber.Ctx) error {
model, input, err := readInput(c, o.loader, true)
if err != nil {
return fmt.Errorf("failed reading parameters from request:%w", err)
}
config, input, err := readConfig(model, input, cm, o.loader, o.debug, o.threads, o.ctxSize, o.f16)
if err != nil {
return fmt.Errorf("failed reading parameters from request:%w", err)
}
log.Debug().Msgf("Parameter Config: %+v", config)
items := []Item{}
for i, s := range config.InputToken {
// get the model function to call for the result
embedFn, err := ModelEmbedding("", s, o.loader, *config, o)
if err != nil {
return err
}
embeddings, err := embedFn()
if err != nil {
return err
}
items = append(items, Item{Embedding: embeddings, Index: i, Object: "embedding"})
}
for i, s := range config.InputStrings {
// get the model function to call for the result
embedFn, err := ModelEmbedding(s, []int{}, o.loader, *config, o)
if err != nil {
return err
}
embeddings, err := embedFn()
if err != nil {
return err
}
items = append(items, Item{Embedding: embeddings, Index: i, Object: "embedding"})
}
resp := &OpenAIResponse{
Model: input.Model, // we have to return what the user sent here, due to OpenAI spec.
Data: items,
Object: "list",
}
jsonResult, _ := json.Marshal(resp)
log.Debug().Msgf("Response: %s", jsonResult)
// Return the prediction in the response body
return c.JSON(resp)
}
}
func chatEndpoint(cm *ConfigMerger, o *Option) func(c *fiber.Ctx) error {
process := func(s string, req *OpenAIRequest, config *Config, loader *model.ModelLoader, responses chan OpenAIResponse) {
initialMessage := OpenAIResponse{
Model: req.Model, // we have to return what the user sent here, due to OpenAI spec.
Choices: []Choice{{Delta: &Message{Role: "assistant"}}},
Object: "chat.completion.chunk",
}
responses <- initialMessage
ComputeChoices(s, req, config, o, loader, func(s string, c *[]Choice) {}, func(s string) bool {
resp := OpenAIResponse{
Model: req.Model, // we have to return what the user sent here, due to OpenAI spec.
Choices: []Choice{{Delta: &Message{Content: &s}, Index: 0}},
Object: "chat.completion.chunk",
}
log.Debug().Msgf("Sending goroutine: %s", s)
responses <- resp
return true
})
close(responses)
}
return func(c *fiber.Ctx) error {
processFunctions := false
funcs := grammar.Functions{}
model, input, err := readInput(c, o.loader, true)
if err != nil {
return fmt.Errorf("failed reading parameters from request:%w", err)
}
config, input, err := readConfig(model, input, cm, o.loader, o.debug, o.threads, o.ctxSize, o.f16)
if err != nil {
return fmt.Errorf("failed reading parameters from request:%w", err)
}
log.Debug().Msgf("Configuration read: %+v", config)
// Allow the user to set custom actions via config file
// to be "embedded" in each model
noActionName := "answer"
noActionDescription := "use this action to answer without performing any action"
if config.FunctionsConfig.NoActionFunctionName != "" {
noActionName = config.FunctionsConfig.NoActionFunctionName
}
if config.FunctionsConfig.NoActionDescriptionName != "" {
noActionDescription = config.FunctionsConfig.NoActionDescriptionName
}
// process functions if we have any defined or if we have a function call string
if len(input.Functions) > 0 &&
((config.functionCallString != "none" || config.functionCallString == "") || len(config.functionCallNameString) > 0) {
log.Debug().Msgf("Response needs to process functions")
processFunctions = true
noActionGrammar := grammar.Function{
Name: noActionName,
Description: noActionDescription,
Parameters: map[string]interface{}{
"properties": map[string]interface{}{
"message": map[string]interface{}{
"type": "string",
"description": "The message to reply the user with",
}},
},
}
// Append the no action function
funcs = append(funcs, input.Functions...)
if !config.FunctionsConfig.DisableNoAction {
funcs = append(funcs, noActionGrammar)
}
// Force picking one of the functions by the request
if config.functionCallNameString != "" {
funcs = funcs.Select(config.functionCallNameString)
}
// Update input grammar
jsStruct := funcs.ToJSONStructure()
config.Grammar = jsStruct.Grammar("")
} else if input.JSONFunctionGrammarObject != nil {
config.Grammar = input.JSONFunctionGrammarObject.Grammar("")
}
// functions are not supported in stream mode (yet?)
toStream := input.Stream && !processFunctions
log.Debug().Msgf("Parameters: %+v", config)
var predInput string
mess := []string{}
for _, 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.Role == "assistant" {
roleFn := "assistant_function_call"
r := config.Roles[roleFn]
if r != "" {
role = roleFn
}
}
r := config.Roles[role]
contentExists := i.Content != nil && *i.Content != ""
if r != "" {
if contentExists {
content = fmt.Sprint(r, " ", *i.Content)
}
if i.FunctionCall != nil {
j, err := json.Marshal(i.FunctionCall)
if err == nil {
if contentExists {
content += "\n" + fmt.Sprint(r, " ", string(j))
} else {
content = fmt.Sprint(r, " ", string(j))
}
}
}
} else {
if contentExists {
content = fmt.Sprint(*i.Content)
}
if i.FunctionCall != nil {
j, err := json.Marshal(i.FunctionCall)
if err == nil {
if contentExists {
content += "\n" + string(j)
} else {
content = string(j)
}
}
}
}
mess = append(mess, content)
}
predInput = strings.Join(mess, "\n")
log.Debug().Msgf("Prompt (before templating): %s", predInput)
if toStream {
log.Debug().Msgf("Stream request received")
c.Context().SetContentType("text/event-stream")
//c.Response().Header.SetContentType(fiber.MIMETextHTMLCharsetUTF8)
// c.Set("Content-Type", "text/event-stream")
c.Set("Cache-Control", "no-cache")
c.Set("Connection", "keep-alive")
c.Set("Transfer-Encoding", "chunked")
}
templateFile := config.Model
if config.TemplateConfig.Chat != "" && !processFunctions {
templateFile = config.TemplateConfig.Chat
}
if config.TemplateConfig.Functions != "" && processFunctions {
templateFile = config.TemplateConfig.Functions
}
// A model can have a "file.bin.tmpl" file associated with a prompt template prefix
templatedInput, err := o.loader.TemplatePrefix(templateFile, struct {
Input string
Functions []grammar.Function
}{
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 processFunctions {
log.Debug().Msgf("Grammar: %+v", config.Grammar)
}
if toStream {
responses := make(chan OpenAIResponse)
go process(predInput, input, config, o.loader, responses)
c.Context().SetBodyStreamWriter(fasthttp.StreamWriter(func(w *bufio.Writer) {
for ev := range responses {
var buf bytes.Buffer
enc := json.NewEncoder(&buf)
enc.Encode(ev)
log.Debug().Msgf("Sending chunk: %s", buf.String())
fmt.Fprintf(w, "data: %v\n", buf.String())
w.Flush()
}
resp := &OpenAIResponse{
Model: input.Model, // we have to return what the user sent here, due to OpenAI spec.
Choices: []Choice{
{
FinishReason: "stop",
Index: 0,
Delta: &Message{},
}},
Object: "chat.completion.chunk",
}
respData, _ := json.Marshal(resp)
w.WriteString(fmt.Sprintf("data: %s\n\n", respData))
w.WriteString("data: [DONE]\n\n")
w.Flush()
}))
return nil
}
result, err := ComputeChoices(predInput, input, config, o, o.loader, func(s string, c *[]Choice) {
if processFunctions {
// As we have to change the result before processing, we can't stream the answer (yet?)
ss := map[string]interface{}{}
json.Unmarshal([]byte(s), &ss)
log.Debug().Msgf("Function return: %s %+v", s, ss)
// The grammar defines the function name as "function", while OpenAI returns "name"
func_name := ss["function"]
// Similarly, while here arguments is a map[string]interface{}, OpenAI actually want a stringified object
args := ss["arguments"] // arguments needs to be a string, but we return an object from the grammar result (TODO: fix)
d, _ := json.Marshal(args)
ss["arguments"] = string(d)
ss["name"] = func_name
// if do nothing, reply with a message
if func_name == noActionName {
log.Debug().Msgf("nothing to do, computing a reply")
// If there is a message that the LLM already sends as part of the JSON reply, use it
arguments := map[string]interface{}{}
json.Unmarshal([]byte(d), &arguments)
m, exists := arguments["message"]
if exists {
switch message := m.(type) {
case string:
if message != "" {
log.Debug().Msgf("Reply received from LLM: %s", message)
message = Finetune(*config, predInput, message)
log.Debug().Msgf("Reply received from LLM(finetuned): %s", message)
*c = append(*c, Choice{Message: &Message{Role: "assistant", Content: &message}})
return
}
}
}
log.Debug().Msgf("No action received from LLM, without a message, computing a reply")
// Otherwise ask the LLM to understand the JSON output and the context, and return a message
// Note: This costs (in term of CPU) another computation
config.Grammar = ""
predFunc, err := ModelInference(predInput, o.loader, *config, o, nil)
if err != nil {
log.Error().Msgf("inference error: %s", err.Error())
return
}
prediction, err := predFunc()
if err != nil {
log.Error().Msgf("inference error: %s", err.Error())
return
}
prediction = Finetune(*config, predInput, prediction)
*c = append(*c, Choice{Message: &Message{Role: "assistant", Content: &prediction}})
} else {
// otherwise reply with the function call
*c = append(*c, Choice{
FinishReason: "function_call",
Message: &Message{Role: "assistant", FunctionCall: ss},
})
}
return
}
*c = append(*c, Choice{Message: &Message{Role: "assistant", Content: &s}})
}, nil)
if err != nil {
return err
}
resp := &OpenAIResponse{
Model: input.Model, // we have to return what the user sent here, due to OpenAI spec.
Choices: result,
Object: "chat.completion",
}
respData, _ := json.Marshal(resp)
log.Debug().Msgf("Response: %s", respData)
// Return the prediction in the response body
return c.JSON(resp)
}
}
func editEndpoint(cm *ConfigMerger, o *Option) func(c *fiber.Ctx) error {
return func(c *fiber.Ctx) error {
model, input, err := readInput(c, o.loader, true)
if err != nil {
return fmt.Errorf("failed reading parameters from request:%w", err)
}
config, input, err := readConfig(model, input, cm, o.loader, o.debug, o.threads, o.ctxSize, o.f16)
if err != nil {
return fmt.Errorf("failed reading parameters from request:%w", err)
}
log.Debug().Msgf("Parameter Config: %+v", config)
templateFile := config.Model
if config.TemplateConfig.Edit != "" {
templateFile = config.TemplateConfig.Edit
}
var result []Choice
for _, i := range config.InputStrings {
// A model can have a "file.bin.tmpl" file associated with a prompt template prefix
templatedInput, err := o.loader.TemplatePrefix(templateFile, struct {
Input string
Instruction string
}{Input: i})
if err == nil {
i = templatedInput
log.Debug().Msgf("Template found, input modified to: %s", i)
}
r, err := ComputeChoices(i, input, config, o, o.loader, func(s string, c *[]Choice) {
*c = append(*c, Choice{Text: s})
}, nil)
if err != nil {
return err
}
result = append(result, r...)
}
resp := &OpenAIResponse{
Model: input.Model, // we have to return what the user sent here, due to OpenAI spec.
Choices: result,
Object: "edit",
}
jsonResult, _ := json.Marshal(resp)
log.Debug().Msgf("Response: %s", jsonResult)
// Return the prediction in the response body
return c.JSON(resp)
}
}
// https://platform.openai.com/docs/api-reference/images/create
/*
*
curl http://localhost:8080/v1/images/generations \
-H "Content-Type: application/json" \
-d '{
"prompt": "A cute baby sea otter",
"n": 1,
"size": "512x512"
}'
*
*/
func imageEndpoint(cm *ConfigMerger, o *Option) func(c *fiber.Ctx) error {
return func(c *fiber.Ctx) error {
m, input, err := readInput(c, o.loader, false)
if err != nil {
return fmt.Errorf("failed reading parameters from request:%w", err)
}
if m == "" {
m = model.StableDiffusionBackend
}
log.Debug().Msgf("Loading model: %+v", m)
config, input, err := readConfig(m, input, cm, o.loader, o.debug, 0, 0, false)
if err != nil {
return fmt.Errorf("failed reading parameters from request:%w", err)
}
log.Debug().Msgf("Parameter Config: %+v", config)
// XXX: Only stablediffusion is supported for now
if config.Backend == "" {
config.Backend = model.StableDiffusionBackend
}
sizeParts := strings.Split(input.Size, "x")
if len(sizeParts) != 2 {
return fmt.Errorf("Invalid value for 'size'")
}
width, err := strconv.Atoi(sizeParts[0])
if err != nil {
return fmt.Errorf("Invalid value for 'size'")
}
height, err := strconv.Atoi(sizeParts[1])
if err != nil {
return fmt.Errorf("Invalid value for 'size'")
}
b64JSON := false
if input.ResponseFormat == "b64_json" {
b64JSON = true
}
var result []Item
for _, i := range config.PromptStrings {
n := input.N
if input.N == 0 {
n = 1
}
for j := 0; j < n; j++ {
prompts := strings.Split(i, "|")
positive_prompt := prompts[0]
negative_prompt := ""
if len(prompts) > 1 {
negative_prompt = prompts[1]
}
mode := 0
step := 15
if input.Mode != 0 {
mode = input.Mode
}
if input.Step != 0 {
step = input.Step
}
tempDir := ""
if !b64JSON {
tempDir = o.imageDir
}
// Create a temporary file
outputFile, err := ioutil.TempFile(tempDir, "b64")
if err != nil {
return err
}
outputFile.Close()
output := outputFile.Name() + ".png"
// Rename the temporary file
err = os.Rename(outputFile.Name(), output)
if err != nil {
return err
}
baseURL := c.BaseURL()
fn, err := ImageGeneration(height, width, mode, step, input.Seed, positive_prompt, negative_prompt, output, o.loader, *config, o)
if err != nil {
return err
}
if err := fn(); err != nil {
return err
}
item := &Item{}
if b64JSON {
defer os.RemoveAll(output)
data, err := os.ReadFile(output)
if err != nil {
return err
}
item.B64JSON = base64.StdEncoding.EncodeToString(data)
} else {
base := filepath.Base(output)
item.URL = baseURL + "/generated-images/" + base
}
result = append(result, *item)
}
}
resp := &OpenAIResponse{
Data: result,
}
jsonResult, _ := json.Marshal(resp)
log.Debug().Msgf("Response: %s", jsonResult)
// Return the prediction in the response body
return c.JSON(resp)
}
}
// https://platform.openai.com/docs/api-reference/audio/create
func transcriptEndpoint(cm *ConfigMerger, o *Option) func(c *fiber.Ctx) error {
return func(c *fiber.Ctx) error {
m, input, err := readInput(c, o.loader, false)
if err != nil {
return fmt.Errorf("failed reading parameters from request:%w", err)
}
config, input, err := readConfig(m, input, cm, o.loader, o.debug, o.threads, o.ctxSize, o.f16)
if err != nil {
return fmt.Errorf("failed reading parameters from request:%w", err)
}
// retrieve the file data from the request
file, err := c.FormFile("file")
if err != nil {
return err
}
f, err := file.Open()
if err != nil {
return err
}
defer f.Close()
dir, err := os.MkdirTemp("", "whisper")
if err != nil {
return err
}
defer os.RemoveAll(dir)
dst := filepath.Join(dir, path.Base(file.Filename))
dstFile, err := os.Create(dst)
if err != nil {
return err
}
if _, err := io.Copy(dstFile, f); err != nil {
log.Debug().Msgf("Audio file copying error %+v - %+v - err %+v", file.Filename, dst, err)
return err
}
log.Debug().Msgf("Audio file copied to: %+v", dst)
whisperModel, err := o.loader.BackendLoader(model.WhisperBackend, config.Model, []llama.ModelOption{}, uint32(config.Threads), o.assetsDestination)
if err != nil {
return err
}
if whisperModel == nil {
return fmt.Errorf("could not load whisper model")
}
w, ok := whisperModel.(whisper.Model)
if !ok {
return fmt.Errorf("loader returned non-whisper object")
}
tr, err := whisperutil.Transcript(w, dst, input.Language, uint(config.Threads))
if err != nil {
return err
}
log.Debug().Msgf("Trascribed: %+v", tr)
// TODO: handle different outputs here
return c.Status(http.StatusOK).JSON(tr)
}
}
func listModels(loader *model.ModelLoader, cm *ConfigMerger) func(ctx *fiber.Ctx) error {
return func(c *fiber.Ctx) error {
models, err := loader.ListModels()
if err != nil {
return err
}
var mm map[string]interface{} = map[string]interface{}{}
dataModels := []OpenAIModel{}
for _, m := range models {
mm[m] = nil
dataModels = append(dataModels, OpenAIModel{ID: m, Object: "model"})
}
for _, k := range cm.ListConfigs() {
if _, exists := mm[k]; !exists {
dataModels = append(dataModels, OpenAIModel{ID: k, Object: "model"})
}
}
return c.JSON(struct {
Object string `json:"object"`
Data []OpenAIModel `json:"data"`
}{
Object: "list",
Data: dataModels,
})
}
}

@ -0,0 +1,105 @@
package openai
import (
config "github.com/go-skynet/LocalAI/api/config"
"github.com/go-skynet/LocalAI/pkg/grammar"
)
// APIError provides error information returned by the OpenAI API.
type APIError struct {
Code any `json:"code,omitempty"`
Message string `json:"message"`
Param *string `json:"param,omitempty"`
Type string `json:"type"`
}
type ErrorResponse struct {
Error *APIError `json:"error,omitempty"`
}
type OpenAIUsage struct {
PromptTokens int `json:"prompt_tokens"`
CompletionTokens int `json:"completion_tokens"`
TotalTokens int `json:"total_tokens"`
}
type Item struct {
Embedding []float32 `json:"embedding"`
Index int `json:"index"`
Object string `json:"object,omitempty"`
// Images
URL string `json:"url,omitempty"`
B64JSON string `json:"b64_json,omitempty"`
}
type OpenAIResponse struct {
Created int `json:"created,omitempty"`
Object string `json:"object,omitempty"`
ID string `json:"id,omitempty"`
Model string `json:"model,omitempty"`
Choices []Choice `json:"choices,omitempty"`
Data []Item `json:"data,omitempty"`
Usage OpenAIUsage `json:"usage"`
}
type Choice struct {
Index int `json:"index,omitempty"`
FinishReason string `json:"finish_reason,omitempty"`
Message *Message `json:"message,omitempty"`
Delta *Message `json:"delta,omitempty"`
Text string `json:"text,omitempty"`
}
type Message struct {
// The message role
Role string `json:"role,omitempty" yaml:"role"`
// The message content
Content *string `json:"content" yaml:"content"`
// A result of a function call
FunctionCall interface{} `json:"function_call,omitempty" yaml:"function_call,omitempty"`
}
type OpenAIModel struct {
ID string `json:"id"`
Object string `json:"object"`
}
type OpenAIRequest struct {
config.PredictionOptions
// whisper
File string `json:"file" validate:"required"`
//whisper/image
ResponseFormat string `json:"response_format"`
// image
Size string `json:"size"`
// Prompt is read only by completion/image API calls
Prompt interface{} `json:"prompt" yaml:"prompt"`
// Edit endpoint
Instruction string `json:"instruction" yaml:"instruction"`
Input interface{} `json:"input" yaml:"input"`
Stop interface{} `json:"stop" yaml:"stop"`
// Messages is read only by chat/completion API calls
Messages []Message `json:"messages" yaml:"messages"`
// A list of available functions to call
Functions []grammar.Function `json:"functions" yaml:"functions"`
FunctionCall interface{} `json:"function_call" yaml:"function_call"` // might be a string or an object
Stream bool `json:"stream"`
// Image (not supported by OpenAI)
Mode int `json:"mode"`
Step int `json:"step"`
// A grammar to constrain the LLM output
Grammar string `json:"grammar" yaml:"grammar"`
JSONFunctionGrammarObject *grammar.JSONFunctionStructure `json:"grammar_json_functions" yaml:"grammar_json_functions"`
}

@ -0,0 +1,320 @@
package openai
import (
"bufio"
"bytes"
"encoding/json"
"fmt"
"strings"
"github.com/go-skynet/LocalAI/api/backend"
config "github.com/go-skynet/LocalAI/api/config"
"github.com/go-skynet/LocalAI/api/options"
"github.com/go-skynet/LocalAI/pkg/grammar"
model "github.com/go-skynet/LocalAI/pkg/model"
"github.com/gofiber/fiber/v2"
"github.com/rs/zerolog/log"
"github.com/valyala/fasthttp"
)
func ChatEndpoint(cm *config.ConfigLoader, o *options.Option) func(c *fiber.Ctx) error {
process := func(s string, req *OpenAIRequest, config *config.Config, loader *model.ModelLoader, responses chan OpenAIResponse) {
initialMessage := OpenAIResponse{
Model: req.Model, // we have to return what the user sent here, due to OpenAI spec.
Choices: []Choice{{Delta: &Message{Role: "assistant"}}},
Object: "chat.completion.chunk",
}
responses <- initialMessage
ComputeChoices(s, req.N, config, o, loader, func(s string, c *[]Choice) {}, func(s string) bool {
resp := OpenAIResponse{
Model: req.Model, // we have to return what the user sent here, due to OpenAI spec.
Choices: []Choice{{Delta: &Message{Content: &s}, Index: 0}},
Object: "chat.completion.chunk",
}
responses <- resp
return true
})
close(responses)
}
return func(c *fiber.Ctx) error {
processFunctions := false
funcs := grammar.Functions{}
model, input, err := readInput(c, o.Loader, true)
if err != nil {
return fmt.Errorf("failed reading parameters from request:%w", err)
}
config, input, err := readConfig(model, input, cm, o.Loader, o.Debug, o.Threads, o.ContextSize, o.F16)
if err != nil {
return fmt.Errorf("failed reading parameters from request:%w", err)
}
log.Debug().Msgf("Configuration read: %+v", config)
// Allow the user to set custom actions via config file
// to be "embedded" in each model
noActionName := "answer"
noActionDescription := "use this action to answer without performing any action"
if config.FunctionsConfig.NoActionFunctionName != "" {
noActionName = config.FunctionsConfig.NoActionFunctionName
}
if config.FunctionsConfig.NoActionDescriptionName != "" {
noActionDescription = config.FunctionsConfig.NoActionDescriptionName
}
// process functions if we have any defined or if we have a function call string
if len(input.Functions) > 0 && config.ShouldUseFunctions() {
log.Debug().Msgf("Response needs to process functions")
processFunctions = true
noActionGrammar := grammar.Function{
Name: noActionName,
Description: noActionDescription,
Parameters: map[string]interface{}{
"properties": map[string]interface{}{
"message": map[string]interface{}{
"type": "string",
"description": "The message to reply the user with",
}},
},
}
// Append the no action function
funcs = append(funcs, input.Functions...)
if !config.FunctionsConfig.DisableNoAction {
funcs = append(funcs, noActionGrammar)
}
// Force picking one of the functions by the request
if config.FunctionToCall() != "" {
funcs = funcs.Select(config.FunctionToCall())
}
// Update input grammar
jsStruct := funcs.ToJSONStructure()
config.Grammar = jsStruct.Grammar("")
} else if input.JSONFunctionGrammarObject != nil {
config.Grammar = input.JSONFunctionGrammarObject.Grammar("")
}
// functions are not supported in stream mode (yet?)
toStream := input.Stream && !processFunctions
log.Debug().Msgf("Parameters: %+v", config)
var predInput string
mess := []string{}
for _, 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.Role == "assistant" {
roleFn := "assistant_function_call"
r := config.Roles[roleFn]
if r != "" {
role = roleFn
}
}
r := config.Roles[role]
contentExists := i.Content != nil && *i.Content != ""
if r != "" {
if contentExists {
content = fmt.Sprint(r, " ", *i.Content)
}
if i.FunctionCall != nil {
j, err := json.Marshal(i.FunctionCall)
if err == nil {
if contentExists {
content += "\n" + fmt.Sprint(r, " ", string(j))
} else {
content = fmt.Sprint(r, " ", string(j))
}
}
}
} else {
if contentExists {
content = fmt.Sprint(*i.Content)
}
if i.FunctionCall != nil {
j, err := json.Marshal(i.FunctionCall)
if err == nil {
if contentExists {
content += "\n" + string(j)
} else {
content = string(j)
}
}
}
}
mess = append(mess, content)
}
predInput = strings.Join(mess, "\n")
log.Debug().Msgf("Prompt (before templating): %s", predInput)
if toStream {
log.Debug().Msgf("Stream request received")
c.Context().SetContentType("text/event-stream")
//c.Response().Header.SetContentType(fiber.MIMETextHTMLCharsetUTF8)
// c.Set("Content-Type", "text/event-stream")
c.Set("Cache-Control", "no-cache")
c.Set("Connection", "keep-alive")
c.Set("Transfer-Encoding", "chunked")
}
templateFile := config.Model
if config.TemplateConfig.Chat != "" && !processFunctions {
templateFile = config.TemplateConfig.Chat
}
if config.TemplateConfig.Functions != "" && processFunctions {
templateFile = config.TemplateConfig.Functions
}
// A model can have a "file.bin.tmpl" file associated with a prompt template prefix
templatedInput, err := o.Loader.TemplatePrefix(templateFile, struct {
Input string
Functions []grammar.Function
}{
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 processFunctions {
log.Debug().Msgf("Grammar: %+v", config.Grammar)
}
if toStream {
responses := make(chan OpenAIResponse)
go process(predInput, input, config, o.Loader, responses)
c.Context().SetBodyStreamWriter(fasthttp.StreamWriter(func(w *bufio.Writer) {
for ev := range responses {
var buf bytes.Buffer
enc := json.NewEncoder(&buf)
enc.Encode(ev)
log.Debug().Msgf("Sending chunk: %s", buf.String())
fmt.Fprintf(w, "data: %v\n", buf.String())
w.Flush()
}
resp := &OpenAIResponse{
Model: input.Model, // we have to return what the user sent here, due to OpenAI spec.
Choices: []Choice{
{
FinishReason: "stop",
Index: 0,
Delta: &Message{},
}},
Object: "chat.completion.chunk",
}
respData, _ := json.Marshal(resp)
w.WriteString(fmt.Sprintf("data: %s\n\n", respData))
w.WriteString("data: [DONE]\n\n")
w.Flush()
}))
return nil
}
result, err := ComputeChoices(predInput, input.N, config, o, o.Loader, func(s string, c *[]Choice) {
if processFunctions {
// As we have to change the result before processing, we can't stream the answer (yet?)
ss := map[string]interface{}{}
json.Unmarshal([]byte(s), &ss)
log.Debug().Msgf("Function return: %s %+v", s, ss)
// The grammar defines the function name as "function", while OpenAI returns "name"
func_name := ss["function"]
// Similarly, while here arguments is a map[string]interface{}, OpenAI actually want a stringified object
args := ss["arguments"] // arguments needs to be a string, but we return an object from the grammar result (TODO: fix)
d, _ := json.Marshal(args)
ss["arguments"] = string(d)
ss["name"] = func_name
// if do nothing, reply with a message
if func_name == noActionName {
log.Debug().Msgf("nothing to do, computing a reply")
// If there is a message that the LLM already sends as part of the JSON reply, use it
arguments := map[string]interface{}{}
json.Unmarshal([]byte(d), &arguments)
m, exists := arguments["message"]
if exists {
switch message := m.(type) {
case string:
if message != "" {
log.Debug().Msgf("Reply received from LLM: %s", message)
message = backend.Finetune(*config, predInput, message)
log.Debug().Msgf("Reply received from LLM(finetuned): %s", message)
*c = append(*c, Choice{Message: &Message{Role: "assistant", Content: &message}})
return
}
}
}
log.Debug().Msgf("No action received from LLM, without a message, computing a reply")
// Otherwise ask the LLM to understand the JSON output and the context, and return a message
// Note: This costs (in term of CPU) another computation
config.Grammar = ""
predFunc, err := backend.ModelInference(predInput, o.Loader, *config, o, nil)
if err != nil {
log.Error().Msgf("inference error: %s", err.Error())
return
}
prediction, err := predFunc()
if err != nil {
log.Error().Msgf("inference error: %s", err.Error())
return
}
prediction = backend.Finetune(*config, predInput, prediction)
*c = append(*c, Choice{Message: &Message{Role: "assistant", Content: &prediction}})
} else {
// otherwise reply with the function call
*c = append(*c, Choice{
FinishReason: "function_call",
Message: &Message{Role: "assistant", FunctionCall: ss},
})
}
return
}
*c = append(*c, Choice{Message: &Message{Role: "assistant", Content: &s}})
}, nil)
if err != nil {
return err
}
resp := &OpenAIResponse{
Model: input.Model, // we have to return what the user sent here, due to OpenAI spec.
Choices: result,
Object: "chat.completion",
}
respData, _ := json.Marshal(resp)
log.Debug().Msgf("Response: %s", respData)
// Return the prediction in the response body
return c.JSON(resp)
}
}

@ -0,0 +1,159 @@
package openai
import (
"bufio"
"bytes"
"encoding/json"
"errors"
"fmt"
config "github.com/go-skynet/LocalAI/api/config"
"github.com/go-skynet/LocalAI/api/options"
model "github.com/go-skynet/LocalAI/pkg/model"
"github.com/gofiber/fiber/v2"
"github.com/rs/zerolog/log"
"github.com/valyala/fasthttp"
)
// https://platform.openai.com/docs/api-reference/completions
func CompletionEndpoint(cm *config.ConfigLoader, o *options.Option) func(c *fiber.Ctx) error {
process := func(s string, req *OpenAIRequest, config *config.Config, loader *model.ModelLoader, responses chan OpenAIResponse) {
ComputeChoices(s, req.N, config, o, loader, func(s string, c *[]Choice) {}, func(s string) bool {
resp := OpenAIResponse{
Model: req.Model, // we have to return what the user sent here, due to OpenAI spec.
Choices: []Choice{
{
Index: 0,
Text: s,
},
},
Object: "text_completion",
}
log.Debug().Msgf("Sending goroutine: %s", s)
responses <- resp
return true
})
close(responses)
}
return func(c *fiber.Ctx) error {
model, input, err := readInput(c, o.Loader, true)
if err != nil {
return fmt.Errorf("failed reading parameters from request:%w", err)
}
log.Debug().Msgf("`input`: %+v", input)
config, input, err := readConfig(model, input, cm, o.Loader, o.Debug, o.Threads, o.ContextSize, o.F16)
if err != nil {
return fmt.Errorf("failed reading parameters from request:%w", err)
}
log.Debug().Msgf("Parameter Config: %+v", config)
if input.Stream {
log.Debug().Msgf("Stream request received")
c.Context().SetContentType("text/event-stream")
//c.Response().Header.SetContentType(fiber.MIMETextHTMLCharsetUTF8)
//c.Set("Content-Type", "text/event-stream")
c.Set("Cache-Control", "no-cache")
c.Set("Connection", "keep-alive")
c.Set("Transfer-Encoding", "chunked")
}
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")
}
predInput := config.PromptStrings[0]
// A model can have a "file.bin.tmpl" file associated with a prompt template prefix
templatedInput, err := o.Loader.TemplatePrefix(templateFile, struct {
Input string
}{
Input: predInput,
})
if err == nil {
predInput = templatedInput
log.Debug().Msgf("Template found, input modified to: %s", predInput)
}
responses := make(chan OpenAIResponse)
go process(predInput, input, config, o.Loader, responses)
c.Context().SetBodyStreamWriter(fasthttp.StreamWriter(func(w *bufio.Writer) {
for ev := range responses {
var buf bytes.Buffer
enc := json.NewEncoder(&buf)
enc.Encode(ev)
log.Debug().Msgf("Sending chunk: %s", buf.String())
fmt.Fprintf(w, "data: %v\n", buf.String())
w.Flush()
}
resp := &OpenAIResponse{
Model: input.Model, // we have to return what the user sent here, due to OpenAI spec.
Choices: []Choice{
{
Index: 0,
FinishReason: "stop",
},
},
Object: "text_completion",
}
respData, _ := json.Marshal(resp)
w.WriteString(fmt.Sprintf("data: %s\n\n", respData))
w.WriteString("data: [DONE]\n\n")
w.Flush()
}))
return nil
}
var result []Choice
for _, i := range config.PromptStrings {
// A model can have a "file.bin.tmpl" file associated with a prompt template prefix
templatedInput, err := o.Loader.TemplatePrefix(templateFile, struct {
Input string
}{
Input: i,
})
if err == nil {
i = templatedInput
log.Debug().Msgf("Template found, input modified to: %s", i)
}
r, err := ComputeChoices(i, input.N, config, o, o.Loader, func(s string, c *[]Choice) {
*c = append(*c, Choice{Text: s})
}, nil)
if err != nil {
return err
}
result = append(result, r...)
}
resp := &OpenAIResponse{
Model: input.Model, // we have to return what the user sent here, due to OpenAI spec.
Choices: result,
Object: "text_completion",
}
jsonResult, _ := json.Marshal(resp)
log.Debug().Msgf("Response: %s", jsonResult)
// Return the prediction in the response body
return c.JSON(resp)
}
}

@ -0,0 +1,67 @@
package openai
import (
"encoding/json"
"fmt"
config "github.com/go-skynet/LocalAI/api/config"
"github.com/go-skynet/LocalAI/api/options"
"github.com/gofiber/fiber/v2"
"github.com/rs/zerolog/log"
)
func EditEndpoint(cm *config.ConfigLoader, o *options.Option) func(c *fiber.Ctx) error {
return func(c *fiber.Ctx) error {
model, input, err := readInput(c, o.Loader, true)
if err != nil {
return fmt.Errorf("failed reading parameters from request:%w", err)
}
config, input, err := readConfig(model, input, cm, o.Loader, o.Debug, o.Threads, o.ContextSize, o.F16)
if err != nil {
return fmt.Errorf("failed reading parameters from request:%w", err)
}
log.Debug().Msgf("Parameter Config: %+v", config)
templateFile := config.Model
if config.TemplateConfig.Edit != "" {
templateFile = config.TemplateConfig.Edit
}
var result []Choice
for _, i := range config.InputStrings {
// A model can have a "file.bin.tmpl" file associated with a prompt template prefix
templatedInput, err := o.Loader.TemplatePrefix(templateFile, struct {
Input string
Instruction string
}{Input: i})
if err == nil {
i = templatedInput
log.Debug().Msgf("Template found, input modified to: %s", i)
}
r, err := ComputeChoices(i, input.N, config, o, o.Loader, func(s string, c *[]Choice) {
*c = append(*c, Choice{Text: s})
}, nil)
if err != nil {
return err
}
result = append(result, r...)
}
resp := &OpenAIResponse{
Model: input.Model, // we have to return what the user sent here, due to OpenAI spec.
Choices: result,
Object: "edit",
}
jsonResult, _ := json.Marshal(resp)
log.Debug().Msgf("Response: %s", jsonResult)
// Return the prediction in the response body
return c.JSON(resp)
}
}

@ -0,0 +1,70 @@
package openai
import (
"encoding/json"
"fmt"
"github.com/go-skynet/LocalAI/api/backend"
config "github.com/go-skynet/LocalAI/api/config"
"github.com/go-skynet/LocalAI/api/options"
"github.com/gofiber/fiber/v2"
"github.com/rs/zerolog/log"
)
// https://platform.openai.com/docs/api-reference/embeddings
func EmbeddingsEndpoint(cm *config.ConfigLoader, o *options.Option) func(c *fiber.Ctx) error {
return func(c *fiber.Ctx) error {
model, input, err := readInput(c, o.Loader, true)
if err != nil {
return fmt.Errorf("failed reading parameters from request:%w", err)
}
config, input, err := readConfig(model, input, cm, o.Loader, o.Debug, o.Threads, o.ContextSize, o.F16)
if err != nil {
return fmt.Errorf("failed reading parameters from request:%w", err)
}
log.Debug().Msgf("Parameter Config: %+v", config)
items := []Item{}
for i, s := range config.InputToken {
// get the model function to call for the result
embedFn, err := backend.ModelEmbedding("", s, o.Loader, *config, o)
if err != nil {
return err
}
embeddings, err := embedFn()
if err != nil {
return err
}
items = append(items, Item{Embedding: embeddings, Index: i, Object: "embedding"})
}
for i, s := range config.InputStrings {
// get the model function to call for the result
embedFn, err := backend.ModelEmbedding(s, []int{}, o.Loader, *config, o)
if err != nil {
return err
}
embeddings, err := embedFn()
if err != nil {
return err
}
items = append(items, Item{Embedding: embeddings, Index: i, Object: "embedding"})
}
resp := &OpenAIResponse{
Model: input.Model, // we have to return what the user sent here, due to OpenAI spec.
Data: items,
Object: "list",
}
jsonResult, _ := json.Marshal(resp)
log.Debug().Msgf("Response: %s", jsonResult)
// Return the prediction in the response body
return c.JSON(resp)
}
}

@ -0,0 +1,158 @@
package openai
import (
"encoding/base64"
"encoding/json"
"fmt"
"io/ioutil"
"os"
"path/filepath"
"strconv"
"strings"
"github.com/go-skynet/LocalAI/api/backend"
config "github.com/go-skynet/LocalAI/api/config"
"github.com/go-skynet/LocalAI/api/options"
model "github.com/go-skynet/LocalAI/pkg/model"
"github.com/gofiber/fiber/v2"
"github.com/rs/zerolog/log"
)
// https://platform.openai.com/docs/api-reference/images/create
/*
*
curl http://localhost:8080/v1/images/generations \
-H "Content-Type: application/json" \
-d '{
"prompt": "A cute baby sea otter",
"n": 1,
"size": "512x512"
}'
*
*/
func ImageEndpoint(cm *config.ConfigLoader, o *options.Option) func(c *fiber.Ctx) error {
return func(c *fiber.Ctx) error {
m, input, err := readInput(c, o.Loader, false)
if err != nil {
return fmt.Errorf("failed reading parameters from request:%w", err)
}
if m == "" {
m = model.StableDiffusionBackend
}
log.Debug().Msgf("Loading model: %+v", m)
config, input, err := readConfig(m, input, cm, o.Loader, o.Debug, 0, 0, false)
if err != nil {
return fmt.Errorf("failed reading parameters from request:%w", err)
}
log.Debug().Msgf("Parameter Config: %+v", config)
// XXX: Only stablediffusion is supported for now
if config.Backend == "" {
config.Backend = model.StableDiffusionBackend
}
sizeParts := strings.Split(input.Size, "x")
if len(sizeParts) != 2 {
return fmt.Errorf("Invalid value for 'size'")
}
width, err := strconv.Atoi(sizeParts[0])
if err != nil {
return fmt.Errorf("Invalid value for 'size'")
}
height, err := strconv.Atoi(sizeParts[1])
if err != nil {
return fmt.Errorf("Invalid value for 'size'")
}
b64JSON := false
if input.ResponseFormat == "b64_json" {
b64JSON = true
}
var result []Item
for _, i := range config.PromptStrings {
n := input.N
if input.N == 0 {
n = 1
}
for j := 0; j < n; j++ {
prompts := strings.Split(i, "|")
positive_prompt := prompts[0]
negative_prompt := ""
if len(prompts) > 1 {
negative_prompt = prompts[1]
}
mode := 0
step := 15
if input.Mode != 0 {
mode = input.Mode
}
if input.Step != 0 {
step = input.Step
}
tempDir := ""
if !b64JSON {
tempDir = o.ImageDir
}
// Create a temporary file
outputFile, err := ioutil.TempFile(tempDir, "b64")
if err != nil {
return err
}
outputFile.Close()
output := outputFile.Name() + ".png"
// Rename the temporary file
err = os.Rename(outputFile.Name(), output)
if err != nil {
return err
}
baseURL := c.BaseURL()
fn, err := backend.ImageGeneration(height, width, mode, step, input.Seed, positive_prompt, negative_prompt, output, o.Loader, *config, o)
if err != nil {
return err
}
if err := fn(); err != nil {
return err
}
item := &Item{}
if b64JSON {
defer os.RemoveAll(output)
data, err := os.ReadFile(output)
if err != nil {
return err
}
item.B64JSON = base64.StdEncoding.EncodeToString(data)
} else {
base := filepath.Base(output)
item.URL = baseURL + "/generated-images/" + base
}
result = append(result, *item)
}
}
resp := &OpenAIResponse{
Data: result,
}
jsonResult, _ := json.Marshal(resp)
log.Debug().Msgf("Response: %s", jsonResult)
// Return the prediction in the response body
return c.JSON(resp)
}
}

@ -0,0 +1,36 @@
package openai
import (
"github.com/go-skynet/LocalAI/api/backend"
config "github.com/go-skynet/LocalAI/api/config"
"github.com/go-skynet/LocalAI/api/options"
model "github.com/go-skynet/LocalAI/pkg/model"
)
func ComputeChoices(predInput string, n int, config *config.Config, o *options.Option, loader *model.ModelLoader, cb func(string, *[]Choice), tokenCallback func(string) bool) ([]Choice, error) {
result := []Choice{}
if n == 0 {
n = 1
}
// get the model function to call for the result
predFunc, err := backend.ModelInference(predInput, loader, *config, o, tokenCallback)
if err != nil {
return result, err
}
for i := 0; i < n; i++ {
prediction, err := predFunc()
if err != nil {
return result, err
}
prediction = backend.Finetune(*config, predInput, prediction)
cb(prediction, &result)
//result = append(result, Choice{Text: prediction})
}
return result, err
}

@ -0,0 +1,37 @@
package openai
import (
config "github.com/go-skynet/LocalAI/api/config"
model "github.com/go-skynet/LocalAI/pkg/model"
"github.com/gofiber/fiber/v2"
)
func ListModelsEndpoint(loader *model.ModelLoader, cm *config.ConfigLoader) func(ctx *fiber.Ctx) error {
return func(c *fiber.Ctx) error {
models, err := loader.ListModels()
if err != nil {
return err
}
var mm map[string]interface{} = map[string]interface{}{}
dataModels := []OpenAIModel{}
for _, m := range models {
mm[m] = nil
dataModels = append(dataModels, OpenAIModel{ID: m, Object: "model"})
}
for _, k := range cm.ListConfigs() {
if _, exists := mm[k]; !exists {
dataModels = append(dataModels, OpenAIModel{ID: k, Object: "model"})
}
}
return c.JSON(struct {
Object string `json:"object"`
Data []OpenAIModel `json:"data"`
}{
Object: "list",
Data: dataModels,
})
}
}

@ -0,0 +1,234 @@
package openai
import (
"encoding/json"
"fmt"
"os"
"path/filepath"
"strings"
config "github.com/go-skynet/LocalAI/api/config"
model "github.com/go-skynet/LocalAI/pkg/model"
"github.com/gofiber/fiber/v2"
"github.com/rs/zerolog/log"
)
func readInput(c *fiber.Ctx, loader *model.ModelLoader, randomModel bool) (string, *OpenAIRequest, error) {
input := new(OpenAIRequest)
// Get input data from the request body
if err := c.BodyParser(input); err != nil {
return "", nil, err
}
modelFile := input.Model
if c.Params("model") != "" {
modelFile = c.Params("model")
}
received, _ := json.Marshal(input)
log.Debug().Msgf("Request received: %s", string(received))
// Set model from bearer token, if available
bearer := strings.TrimLeft(c.Get("authorization"), "Bearer ")
bearerExists := bearer != "" && loader.ExistsInModelPath(bearer)
// If no model was specified, take the first available
if modelFile == "" && !bearerExists && randomModel {
models, _ := loader.ListModels()
if len(models) > 0 {
modelFile = models[0]
log.Debug().Msgf("No model specified, using: %s", modelFile)
} else {
log.Debug().Msgf("No model specified, returning error")
return "", nil, fmt.Errorf("no model specified")
}
}
// If a model is found in bearer token takes precedence
if bearerExists {
log.Debug().Msgf("Using model from bearer token: %s", bearer)
modelFile = bearer
}
return modelFile, input, nil
}
func updateConfig(config *config.Config, input *OpenAIRequest) {
if input.Echo {
config.Echo = input.Echo
}
if input.TopK != 0 {
config.TopK = input.TopK
}
if input.TopP != 0 {
config.TopP = input.TopP
}
if input.Grammar != "" {
config.Grammar = input.Grammar
}
if input.Temperature != 0 {
config.Temperature = input.Temperature
}
if input.Maxtokens != 0 {
config.Maxtokens = input.Maxtokens
}
switch stop := input.Stop.(type) {
case string:
if stop != "" {
config.StopWords = append(config.StopWords, stop)
}
case []interface{}:
for _, pp := range stop {
if s, ok := pp.(string); ok {
config.StopWords = append(config.StopWords, s)
}
}
}
if input.RepeatPenalty != 0 {
config.RepeatPenalty = input.RepeatPenalty
}
if input.Keep != 0 {
config.Keep = input.Keep
}
if input.Batch != 0 {
config.Batch = input.Batch
}
if input.F16 {
config.F16 = input.F16
}
if input.IgnoreEOS {
config.IgnoreEOS = input.IgnoreEOS
}
if input.Seed != 0 {
config.Seed = input.Seed
}
if input.Mirostat != 0 {
config.Mirostat = input.Mirostat
}
if input.MirostatETA != 0 {
config.MirostatETA = input.MirostatETA
}
if input.MirostatTAU != 0 {
config.MirostatTAU = input.MirostatTAU
}
if input.TypicalP != 0 {
config.TypicalP = input.TypicalP
}
switch inputs := input.Input.(type) {
case string:
if inputs != "" {
config.InputStrings = append(config.InputStrings, inputs)
}
case []interface{}:
for _, pp := range inputs {
switch i := pp.(type) {
case string:
config.InputStrings = append(config.InputStrings, i)
case []interface{}:
tokens := []int{}
for _, ii := range i {
tokens = append(tokens, int(ii.(float64)))
}
config.InputToken = append(config.InputToken, tokens)
}
}
}
// Can be either a string or an object
switch fnc := input.FunctionCall.(type) {
case string:
if fnc != "" {
config.SetFunctionCallString(fnc)
}
case map[string]interface{}:
var name string
n, exists := fnc["name"]
if exists {
nn, e := n.(string)
if !e {
name = nn
}
}
config.SetFunctionCallNameString(name)
}
switch p := input.Prompt.(type) {
case string:
config.PromptStrings = append(config.PromptStrings, p)
case []interface{}:
for _, pp := range p {
if s, ok := pp.(string); ok {
config.PromptStrings = append(config.PromptStrings, s)
}
}
}
}
func readConfig(modelFile string, input *OpenAIRequest, cm *config.ConfigLoader, loader *model.ModelLoader, debug bool, threads, ctx int, f16 bool) (*config.Config, *OpenAIRequest, error) {
// Load a config file if present after the model name
modelConfig := filepath.Join(loader.ModelPath, modelFile+".yaml")
var cfg *config.Config
defaults := func() {
cfg = config.DefaultConfig(modelFile)
cfg.ContextSize = ctx
cfg.Threads = threads
cfg.F16 = f16
cfg.Debug = debug
}
cfgExisting, exists := cm.GetConfig(modelFile)
if !exists {
if _, err := os.Stat(modelConfig); err == nil {
if err := cm.LoadConfig(modelConfig); err != nil {
return nil, nil, fmt.Errorf("failed loading model config (%s) %s", modelConfig, err.Error())
}
cfgExisting, exists = cm.GetConfig(modelFile)
if exists {
cfg = &cfgExisting
} else {
defaults()
}
} else {
defaults()
}
} else {
cfg = &cfgExisting
}
// Set the parameters for the language model prediction
updateConfig(cfg, input)
// Don't allow 0 as setting
if cfg.Threads == 0 {
if threads != 0 {
cfg.Threads = threads
} else {
cfg.Threads = 4
}
}
// Enforce debug flag if passed from CLI
if debug {
cfg.Debug = true
}
return cfg, input, nil
}

@ -0,0 +1,91 @@
package openai
import (
"context"
"fmt"
"io"
"net/http"
"os"
"path"
"path/filepath"
config "github.com/go-skynet/LocalAI/api/config"
"github.com/go-skynet/LocalAI/api/options"
"github.com/go-skynet/LocalAI/pkg/grpc/proto"
model "github.com/go-skynet/LocalAI/pkg/model"
"github.com/gofiber/fiber/v2"
"github.com/rs/zerolog/log"
)
// https://platform.openai.com/docs/api-reference/audio/create
func TranscriptEndpoint(cm *config.ConfigLoader, o *options.Option) func(c *fiber.Ctx) error {
return func(c *fiber.Ctx) error {
m, input, err := readInput(c, o.Loader, false)
if err != nil {
return fmt.Errorf("failed reading parameters from request:%w", err)
}
config, input, err := readConfig(m, input, cm, o.Loader, o.Debug, o.Threads, o.ContextSize, o.F16)
if err != nil {
return fmt.Errorf("failed reading parameters from request:%w", err)
}
// retrieve the file data from the request
file, err := c.FormFile("file")
if err != nil {
return err
}
f, err := file.Open()
if err != nil {
return err
}
defer f.Close()
dir, err := os.MkdirTemp("", "whisper")
if err != nil {
return err
}
defer os.RemoveAll(dir)
dst := filepath.Join(dir, path.Base(file.Filename))
dstFile, err := os.Create(dst)
if err != nil {
return err
}
if _, err := io.Copy(dstFile, f); err != nil {
log.Debug().Msgf("Audio file copying error %+v - %+v - err %+v", file.Filename, dst, err)
return err
}
log.Debug().Msgf("Audio file copied to: %+v", dst)
whisperModel, err := o.Loader.BackendLoader(
model.WithBackendString(model.WhisperBackend),
model.WithModelFile(config.Model),
model.WithContext(o.Context),
model.WithThreads(uint32(config.Threads)),
model.WithAssetDir(o.AssetsDestination))
if err != nil {
return err
}
if whisperModel == nil {
return fmt.Errorf("could not load whisper model")
}
tr, err := whisperModel.AudioTranscription(context.Background(), &proto.TranscriptRequest{
Dst: dst,
Language: input.Language,
Threads: uint32(config.Threads),
})
if err != nil {
return err
}
log.Debug().Msgf("Trascribed: %+v", tr)
// TODO: handle different outputs here
return c.Status(http.StatusOK).JSON(tr)
}
}

@ -1,4 +1,4 @@
package api
package options
import (
"context"
@ -11,35 +11,35 @@ import (
)
type Option struct {
context context.Context
configFile string
loader *model.ModelLoader
uploadLimitMB, threads, ctxSize int
f16 bool
debug, disableMessage bool
imageDir string
audioDir string
cors bool
preloadJSONModels string
preloadModelsFromPath string
corsAllowOrigins string
Context context.Context
ConfigFile string
Loader *model.ModelLoader
UploadLimitMB, Threads, ContextSize int
F16 bool
Debug, DisableMessage bool
ImageDir string
AudioDir string
CORS bool
PreloadJSONModels string
PreloadModelsFromPath string
CORSAllowOrigins string
galleries []gallery.Gallery
Galleries []gallery.Gallery
backendAssets embed.FS
assetsDestination string
BackendAssets embed.FS
AssetsDestination string
}
type AppOption func(*Option)
func newOptions(o ...AppOption) *Option {
func NewOptions(o ...AppOption) *Option {
opt := &Option{
context: context.Background(),
uploadLimitMB: 15,
threads: 1,
ctxSize: 512,
debug: true,
disableMessage: true,
Context: context.Background(),
UploadLimitMB: 15,
Threads: 1,
ContextSize: 512,
Debug: true,
DisableMessage: true,
}
for _, oo := range o {
oo(opt)
@ -49,25 +49,25 @@ func newOptions(o ...AppOption) *Option {
func WithCors(b bool) AppOption {
return func(o *Option) {
o.cors = b
o.CORS = b
}
}
func WithCorsAllowOrigins(b string) AppOption {
return func(o *Option) {
o.corsAllowOrigins = b
o.CORSAllowOrigins = b
}
}
func WithBackendAssetsOutput(out string) AppOption {
return func(o *Option) {
o.assetsDestination = out
o.AssetsDestination = out
}
}
func WithBackendAssets(f embed.FS) AppOption {
return func(o *Option) {
o.backendAssets = f
o.BackendAssets = f
}
}
@ -81,89 +81,89 @@ func WithStringGalleries(galls string) AppOption {
if err := json.Unmarshal([]byte(galls), &galleries); err != nil {
log.Error().Msgf("failed loading galleries: %s", err.Error())
}
o.galleries = append(o.galleries, galleries...)
o.Galleries = append(o.Galleries, galleries...)
}
}
func WithGalleries(galleries []gallery.Gallery) AppOption {
return func(o *Option) {
o.galleries = append(o.galleries, galleries...)
o.Galleries = append(o.Galleries, galleries...)
}
}
func WithContext(ctx context.Context) AppOption {
return func(o *Option) {
o.context = ctx
o.Context = ctx
}
}
func WithYAMLConfigPreload(configFile string) AppOption {
return func(o *Option) {
o.preloadModelsFromPath = configFile
o.PreloadModelsFromPath = configFile
}
}
func WithJSONStringPreload(configFile string) AppOption {
return func(o *Option) {
o.preloadJSONModels = configFile
o.PreloadJSONModels = configFile
}
}
func WithConfigFile(configFile string) AppOption {
return func(o *Option) {
o.configFile = configFile
o.ConfigFile = configFile
}
}
func WithModelLoader(loader *model.ModelLoader) AppOption {
return func(o *Option) {
o.loader = loader
o.Loader = loader
}
}
func WithUploadLimitMB(limit int) AppOption {
return func(o *Option) {
o.uploadLimitMB = limit
o.UploadLimitMB = limit
}
}
func WithThreads(threads int) AppOption {
return func(o *Option) {
o.threads = threads
o.Threads = threads
}
}
func WithContextSize(ctxSize int) AppOption {
return func(o *Option) {
o.ctxSize = ctxSize
o.ContextSize = ctxSize
}
}
func WithF16(f16 bool) AppOption {
return func(o *Option) {
o.f16 = f16
o.F16 = f16
}
}
func WithDebug(debug bool) AppOption {
return func(o *Option) {
o.debug = debug
o.Debug = debug
}
}
func WithDisableMessage(disableMessage bool) AppOption {
return func(o *Option) {
o.disableMessage = disableMessage
o.DisableMessage = disableMessage
}
}
func WithAudioDir(audioDir string) AppOption {
return func(o *Option) {
o.audioDir = audioDir
o.AudioDir = audioDir
}
}
func WithImageDir(imageDir string) AppOption {
return func(o *Option) {
o.imageDir = imageDir
o.ImageDir = imageDir
}
}

@ -1,649 +0,0 @@
package api
import (
"fmt"
"os"
"path/filepath"
"regexp"
"strings"
"sync"
"github.com/donomii/go-rwkv.cpp"
"github.com/go-skynet/LocalAI/pkg/langchain"
model "github.com/go-skynet/LocalAI/pkg/model"
"github.com/go-skynet/LocalAI/pkg/stablediffusion"
"github.com/go-skynet/bloomz.cpp"
bert "github.com/go-skynet/go-bert.cpp"
transformers "github.com/go-skynet/go-ggml-transformers.cpp"
llama "github.com/go-skynet/go-llama.cpp"
gpt4all "github.com/nomic-ai/gpt4all/gpt4all-bindings/golang"
)
// mutex still needed, see: https://github.com/ggerganov/llama.cpp/discussions/784
var mutexMap sync.Mutex
var mutexes map[string]*sync.Mutex = make(map[string]*sync.Mutex)
func defaultLLamaOpts(c Config) []llama.ModelOption {
llamaOpts := []llama.ModelOption{}
if c.ContextSize != 0 {
llamaOpts = append(llamaOpts, llama.SetContext(c.ContextSize))
}
if c.F16 {
llamaOpts = append(llamaOpts, llama.EnableF16Memory)
}
if c.Embeddings {
llamaOpts = append(llamaOpts, llama.EnableEmbeddings)
}
if c.NGPULayers != 0 {
llamaOpts = append(llamaOpts, llama.SetGPULayers(c.NGPULayers))
}
llamaOpts = append(llamaOpts, llama.SetMMap(c.MMap))
llamaOpts = append(llamaOpts, llama.SetMainGPU(c.MainGPU))
llamaOpts = append(llamaOpts, llama.SetTensorSplit(c.TensorSplit))
if c.Batch != 0 {
llamaOpts = append(llamaOpts, llama.SetNBatch(c.Batch))
} else {
llamaOpts = append(llamaOpts, llama.SetNBatch(512))
}
if c.NUMA {
llamaOpts = append(llamaOpts, llama.EnableNUMA)
}
if c.LowVRAM {
llamaOpts = append(llamaOpts, llama.EnabelLowVRAM)
}
return llamaOpts
}
func ImageGeneration(height, width, mode, step, seed int, positive_prompt, negative_prompt, dst string, loader *model.ModelLoader, c Config, o *Option) (func() error, error) {
if c.Backend != model.StableDiffusionBackend {
return nil, fmt.Errorf("endpoint only working with stablediffusion models")
}
inferenceModel, err := loader.BackendLoader(c.Backend, c.ImageGenerationAssets, []llama.ModelOption{}, uint32(c.Threads), o.assetsDestination)
if err != nil {
return nil, err
}
var fn func() error
switch model := inferenceModel.(type) {
case *stablediffusion.StableDiffusion:
fn = func() error {
return model.GenerateImage(height, width, mode, step, seed, positive_prompt, negative_prompt, dst)
}
default:
fn = func() error {
return fmt.Errorf("creation of images not supported by the backend")
}
}
return func() error {
// This is still needed, see: https://github.com/ggerganov/llama.cpp/discussions/784
mutexMap.Lock()
l, ok := mutexes[c.Backend]
if !ok {
m := &sync.Mutex{}
mutexes[c.Backend] = m
l = m
}
mutexMap.Unlock()
l.Lock()
defer l.Unlock()
return fn()
}, nil
}
func ModelEmbedding(s string, tokens []int, loader *model.ModelLoader, c Config, o *Option) (func() ([]float32, error), error) {
if !c.Embeddings {
return nil, fmt.Errorf("endpoint disabled for this model by API configuration")
}
modelFile := c.Model
llamaOpts := defaultLLamaOpts(c)
var inferenceModel interface{}
var err error
if c.Backend == "" {
inferenceModel, err = loader.GreedyLoader(modelFile, llamaOpts, uint32(c.Threads), o.assetsDestination)
} else {
inferenceModel, err = loader.BackendLoader(c.Backend, modelFile, llamaOpts, uint32(c.Threads), o.assetsDestination)
}
if err != nil {
return nil, err
}
var fn func() ([]float32, error)
switch model := inferenceModel.(type) {
case *llama.LLama:
fn = func() ([]float32, error) {
predictOptions := buildLLamaPredictOptions(c, loader.ModelPath)
if len(tokens) > 0 {
return model.TokenEmbeddings(tokens, predictOptions...)
}
return model.Embeddings(s, predictOptions...)
}
// bert embeddings
case *bert.Bert:
fn = func() ([]float32, error) {
if len(tokens) > 0 {
return model.TokenEmbeddings(tokens, bert.SetThreads(c.Threads))
}
return model.Embeddings(s, bert.SetThreads(c.Threads))
}
default:
fn = func() ([]float32, error) {
return nil, fmt.Errorf("embeddings not supported by the backend")
}
}
return func() ([]float32, error) {
// This is still needed, see: https://github.com/ggerganov/llama.cpp/discussions/784
mutexMap.Lock()
l, ok := mutexes[modelFile]
if !ok {
m := &sync.Mutex{}
mutexes[modelFile] = m
l = m
}
mutexMap.Unlock()
l.Lock()
defer l.Unlock()
embeds, err := fn()
if err != nil {
return embeds, err
}
// Remove trailing 0s
for i := len(embeds) - 1; i >= 0; i-- {
if embeds[i] == 0.0 {
embeds = embeds[:i]
} else {
break
}
}
return embeds, nil
}, nil
}
func buildLLamaPredictOptions(c Config, modelPath string) []llama.PredictOption {
// Generate the prediction using the language model
predictOptions := []llama.PredictOption{
llama.SetTemperature(c.Temperature),
llama.SetTopP(c.TopP),
llama.SetTopK(c.TopK),
llama.SetTokens(c.Maxtokens),
llama.SetThreads(c.Threads),
}
if c.PromptCacheAll {
predictOptions = append(predictOptions, llama.EnablePromptCacheAll)
}
if c.PromptCacheRO {
predictOptions = append(predictOptions, llama.EnablePromptCacheRO)
}
predictOptions = append(predictOptions, llama.WithGrammar(c.Grammar))
if c.PromptCachePath != "" {
// Create parent directory
p := filepath.Join(modelPath, c.PromptCachePath)
os.MkdirAll(filepath.Dir(p), 0755)
predictOptions = append(predictOptions, llama.SetPathPromptCache(p))
}
if c.Mirostat != 0 {
predictOptions = append(predictOptions, llama.SetMirostat(c.Mirostat))
}
if c.MirostatETA != 0 {
predictOptions = append(predictOptions, llama.SetMirostatETA(c.MirostatETA))
}
if c.MirostatTAU != 0 {
predictOptions = append(predictOptions, llama.SetMirostatTAU(c.MirostatTAU))
}
if c.Debug {
predictOptions = append(predictOptions, llama.Debug)
}
predictOptions = append(predictOptions, llama.SetStopWords(c.StopWords...))
if c.RepeatPenalty != 0 {
predictOptions = append(predictOptions, llama.SetPenalty(c.RepeatPenalty))
}
if c.Keep != 0 {
predictOptions = append(predictOptions, llama.SetNKeep(c.Keep))
}
if c.Batch != 0 {
predictOptions = append(predictOptions, llama.SetBatch(c.Batch))
}
if c.F16 {
predictOptions = append(predictOptions, llama.EnableF16KV)
}
if c.IgnoreEOS {
predictOptions = append(predictOptions, llama.IgnoreEOS)
}
if c.Seed != 0 {
predictOptions = append(predictOptions, llama.SetSeed(c.Seed))
}
//predictOptions = append(predictOptions, llama.SetLogitBias(c.Seed))
predictOptions = append(predictOptions, llama.SetFrequencyPenalty(c.FrequencyPenalty))
predictOptions = append(predictOptions, llama.SetMlock(c.MMlock))
predictOptions = append(predictOptions, llama.SetMemoryMap(c.MMap))
predictOptions = append(predictOptions, llama.SetPredictionMainGPU(c.MainGPU))
predictOptions = append(predictOptions, llama.SetPredictionTensorSplit(c.TensorSplit))
predictOptions = append(predictOptions, llama.SetTailFreeSamplingZ(c.TFZ))
predictOptions = append(predictOptions, llama.SetTypicalP(c.TypicalP))
return predictOptions
}
func ModelInference(s string, loader *model.ModelLoader, c Config, o *Option, tokenCallback func(string) bool) (func() (string, error), error) {
supportStreams := false
modelFile := c.Model
llamaOpts := defaultLLamaOpts(c)
var inferenceModel interface{}
var err error
if c.Backend == "" {
inferenceModel, err = loader.GreedyLoader(modelFile, llamaOpts, uint32(c.Threads), o.assetsDestination)
} else {
inferenceModel, err = loader.BackendLoader(c.Backend, modelFile, llamaOpts, uint32(c.Threads), o.assetsDestination)
}
if err != nil {
return nil, err
}
var fn func() (string, error)
switch model := inferenceModel.(type) {
case *rwkv.RwkvState:
supportStreams = true
fn = func() (string, error) {
stopWord := "\n"
if len(c.StopWords) > 0 {
stopWord = c.StopWords[0]
}
if err := model.ProcessInput(s); err != nil {
return "", err
}
response := model.GenerateResponse(c.Maxtokens, stopWord, float32(c.Temperature), float32(c.TopP), tokenCallback)
return response, nil
}
case *transformers.GPTNeoX:
fn = func() (string, error) {
// Generate the prediction using the language model
predictOptions := []transformers.PredictOption{
transformers.SetTemperature(c.Temperature),
transformers.SetTopP(c.TopP),
transformers.SetTopK(c.TopK),
transformers.SetTokens(c.Maxtokens),
transformers.SetThreads(c.Threads),
}
if c.Batch != 0 {
predictOptions = append(predictOptions, transformers.SetBatch(c.Batch))
}
if c.Seed != 0 {
predictOptions = append(predictOptions, transformers.SetSeed(c.Seed))
}
return model.Predict(
s,
predictOptions...,
)
}
case *transformers.Replit:
fn = func() (string, error) {
// Generate the prediction using the language model
predictOptions := []transformers.PredictOption{
transformers.SetTemperature(c.Temperature),
transformers.SetTopP(c.TopP),
transformers.SetTopK(c.TopK),
transformers.SetTokens(c.Maxtokens),
transformers.SetThreads(c.Threads),
}
if c.Batch != 0 {
predictOptions = append(predictOptions, transformers.SetBatch(c.Batch))
}
if c.Seed != 0 {
predictOptions = append(predictOptions, transformers.SetSeed(c.Seed))
}
return model.Predict(
s,
predictOptions...,
)
}
case *transformers.Starcoder:
fn = func() (string, error) {
// Generate the prediction using the language model
predictOptions := []transformers.PredictOption{
transformers.SetTemperature(c.Temperature),
transformers.SetTopP(c.TopP),
transformers.SetTopK(c.TopK),
transformers.SetTokens(c.Maxtokens),
transformers.SetThreads(c.Threads),
}
if c.Batch != 0 {
predictOptions = append(predictOptions, transformers.SetBatch(c.Batch))
}
if c.Seed != 0 {
predictOptions = append(predictOptions, transformers.SetSeed(c.Seed))
}
return model.Predict(
s,
predictOptions...,
)
}
case *transformers.MPT:
fn = func() (string, error) {
// Generate the prediction using the language model
predictOptions := []transformers.PredictOption{
transformers.SetTemperature(c.Temperature),
transformers.SetTopP(c.TopP),
transformers.SetTopK(c.TopK),
transformers.SetTokens(c.Maxtokens),
transformers.SetThreads(c.Threads),
}
if c.Batch != 0 {
predictOptions = append(predictOptions, transformers.SetBatch(c.Batch))
}
if c.Seed != 0 {
predictOptions = append(predictOptions, transformers.SetSeed(c.Seed))
}
return model.Predict(
s,
predictOptions...,
)
}
case *bloomz.Bloomz:
fn = func() (string, error) {
// Generate the prediction using the language model
predictOptions := []bloomz.PredictOption{
bloomz.SetTemperature(c.Temperature),
bloomz.SetTopP(c.TopP),
bloomz.SetTopK(c.TopK),
bloomz.SetTokens(c.Maxtokens),
bloomz.SetThreads(c.Threads),
}
if c.Seed != 0 {
predictOptions = append(predictOptions, bloomz.SetSeed(c.Seed))
}
return model.Predict(
s,
predictOptions...,
)
}
case *transformers.Falcon:
fn = func() (string, error) {
// Generate the prediction using the language model
predictOptions := []transformers.PredictOption{
transformers.SetTemperature(c.Temperature),
transformers.SetTopP(c.TopP),
transformers.SetTopK(c.TopK),
transformers.SetTokens(c.Maxtokens),
transformers.SetThreads(c.Threads),
}
if c.Batch != 0 {
predictOptions = append(predictOptions, transformers.SetBatch(c.Batch))
}
if c.Seed != 0 {
predictOptions = append(predictOptions, transformers.SetSeed(c.Seed))
}
return model.Predict(
s,
predictOptions...,
)
}
case *transformers.GPTJ:
fn = func() (string, error) {
// Generate the prediction using the language model
predictOptions := []transformers.PredictOption{
transformers.SetTemperature(c.Temperature),
transformers.SetTopP(c.TopP),
transformers.SetTopK(c.TopK),
transformers.SetTokens(c.Maxtokens),
transformers.SetThreads(c.Threads),
}
if c.Batch != 0 {
predictOptions = append(predictOptions, transformers.SetBatch(c.Batch))
}
if c.Seed != 0 {
predictOptions = append(predictOptions, transformers.SetSeed(c.Seed))
}
return model.Predict(
s,
predictOptions...,
)
}
case *transformers.Dolly:
fn = func() (string, error) {
// Generate the prediction using the language model
predictOptions := []transformers.PredictOption{
transformers.SetTemperature(c.Temperature),
transformers.SetTopP(c.TopP),
transformers.SetTopK(c.TopK),
transformers.SetTokens(c.Maxtokens),
transformers.SetThreads(c.Threads),
}
if c.Batch != 0 {
predictOptions = append(predictOptions, transformers.SetBatch(c.Batch))
}
if c.Seed != 0 {
predictOptions = append(predictOptions, transformers.SetSeed(c.Seed))
}
return model.Predict(
s,
predictOptions...,
)
}
case *transformers.GPT2:
fn = func() (string, error) {
// Generate the prediction using the language model
predictOptions := []transformers.PredictOption{
transformers.SetTemperature(c.Temperature),
transformers.SetTopP(c.TopP),
transformers.SetTopK(c.TopK),
transformers.SetTokens(c.Maxtokens),
transformers.SetThreads(c.Threads),
}
if c.Batch != 0 {
predictOptions = append(predictOptions, transformers.SetBatch(c.Batch))
}
if c.Seed != 0 {
predictOptions = append(predictOptions, transformers.SetSeed(c.Seed))
}
return model.Predict(
s,
predictOptions...,
)
}
case *gpt4all.Model:
supportStreams = true
fn = func() (string, error) {
if tokenCallback != nil {
model.SetTokenCallback(tokenCallback)
}
// Generate the prediction using the language model
predictOptions := []gpt4all.PredictOption{
gpt4all.SetTemperature(c.Temperature),
gpt4all.SetTopP(c.TopP),
gpt4all.SetTopK(c.TopK),
gpt4all.SetTokens(c.Maxtokens),
}
if c.Batch != 0 {
predictOptions = append(predictOptions, gpt4all.SetBatch(c.Batch))
}
str, er := model.Predict(
s,
predictOptions...,
)
// Seems that if we don't free the callback explicitly we leave functions registered (that might try to send on closed channels)
// For instance otherwise the API returns: {"error":{"code":500,"message":"send on closed channel","type":""}}
// after a stream event has occurred
model.SetTokenCallback(nil)
return str, er
}
case *llama.LLama:
supportStreams = true
fn = func() (string, error) {
if tokenCallback != nil {
model.SetTokenCallback(tokenCallback)
}
predictOptions := buildLLamaPredictOptions(c, loader.ModelPath)
str, er := model.Predict(
s,
predictOptions...,
)
// Seems that if we don't free the callback explicitly we leave functions registered (that might try to send on closed channels)
// For instance otherwise the API returns: {"error":{"code":500,"message":"send on closed channel","type":""}}
// after a stream event has occurred
model.SetTokenCallback(nil)
return str, er
}
case *langchain.HuggingFace:
fn = func() (string, error) {
// Generate the prediction using the language model
predictOptions := []langchain.PredictOption{
langchain.SetModel(c.Model),
langchain.SetMaxTokens(c.Maxtokens),
langchain.SetTemperature(c.Temperature),
langchain.SetStopWords(c.StopWords),
}
pred, er := model.PredictHuggingFace(s, predictOptions...)
if er != nil {
return "", er
}
return pred.Completion, nil
}
}
return func() (string, error) {
// This is still needed, see: https://github.com/ggerganov/llama.cpp/discussions/784
mutexMap.Lock()
l, ok := mutexes[modelFile]
if !ok {
m := &sync.Mutex{}
mutexes[modelFile] = m
l = m
}
mutexMap.Unlock()
l.Lock()
defer l.Unlock()
res, err := fn()
if tokenCallback != nil && !supportStreams {
tokenCallback(res)
}
return res, err
}, nil
}
func ComputeChoices(predInput string, input *OpenAIRequest, config *Config, o *Option, loader *model.ModelLoader, cb func(string, *[]Choice), tokenCallback func(string) bool) ([]Choice, error) {
result := []Choice{}
n := input.N
if input.N == 0 {
n = 1
}
// get the model function to call for the result
predFunc, err := ModelInference(predInput, loader, *config, o, tokenCallback)
if err != nil {
return result, err
}
for i := 0; i < n; i++ {
prediction, err := predFunc()
if err != nil {
return result, err
}
prediction = Finetune(*config, predInput, prediction)
cb(prediction, &result)
//result = append(result, Choice{Text: prediction})
}
return result, err
}
var cutstrings map[string]*regexp.Regexp = make(map[string]*regexp.Regexp)
var mu sync.Mutex = sync.Mutex{}
func Finetune(config Config, input, prediction string) string {
if config.Echo {
prediction = input + prediction
}
for _, c := range config.Cutstrings {
mu.Lock()
reg, ok := cutstrings[c]
if !ok {
cutstrings[c] = regexp.MustCompile(c)
reg = cutstrings[c]
}
mu.Unlock()
prediction = reg.ReplaceAllString(prediction, "")
}
for _, c := range config.TrimSpace {
prediction = strings.TrimSpace(strings.TrimPrefix(prediction, c))
}
return prediction
}

@ -0,0 +1,22 @@
package main
// Note: this is started internally by LocalAI and a server is allocated for each model
import (
"flag"
grpc "github.com/go-skynet/LocalAI/pkg/grpc"
bert "github.com/go-skynet/LocalAI/pkg/grpc/llm/bert"
)
var (
addr = flag.String("addr", "localhost:50051", "the address to connect to")
)
func main() {
flag.Parse()
if err := grpc.StartServer(*addr, &bert.Embeddings{}); err != nil {
panic(err)
}
}

@ -0,0 +1,23 @@
package main
// Note: this is started internally by LocalAI and a server is allocated for each model
import (
"flag"
bloomz "github.com/go-skynet/LocalAI/pkg/grpc/llm/bloomz"
grpc "github.com/go-skynet/LocalAI/pkg/grpc"
)
var (
addr = flag.String("addr", "localhost:50051", "the address to connect to")
)
func main() {
flag.Parse()
if err := grpc.StartServer(*addr, &bloomz.LLM{}); err != nil {
panic(err)
}
}

@ -0,0 +1,23 @@
package main
// Note: this is started internally by LocalAI and a server is allocated for each model
import (
"flag"
transformers "github.com/go-skynet/LocalAI/pkg/grpc/llm/transformers"
grpc "github.com/go-skynet/LocalAI/pkg/grpc"
)
var (
addr = flag.String("addr", "localhost:50051", "the address to connect to")
)
func main() {
flag.Parse()
if err := grpc.StartServer(*addr, &transformers.Dolly{}); err != nil {
panic(err)
}
}

@ -0,0 +1,23 @@
package main
// Note: this is started internally by LocalAI and a server is allocated for each model
import (
"flag"
transformers "github.com/go-skynet/LocalAI/pkg/grpc/llm/transformers"
grpc "github.com/go-skynet/LocalAI/pkg/grpc"
)
var (
addr = flag.String("addr", "localhost:50051", "the address to connect to")
)
func main() {
flag.Parse()
if err := grpc.StartServer(*addr, &transformers.Falcon{}); err != nil {
panic(err)
}
}

@ -0,0 +1,25 @@
package main
// GRPC Falcon server
// Note: this is started internally by LocalAI and a server is allocated for each model
import (
"flag"
falcon "github.com/go-skynet/LocalAI/pkg/grpc/llm/falcon"
grpc "github.com/go-skynet/LocalAI/pkg/grpc"
)
var (
addr = flag.String("addr", "localhost:50051", "the address to connect to")
)
func main() {
flag.Parse()
if err := grpc.StartServer(*addr, &falcon.LLM{}); err != nil {
panic(err)
}
}

@ -0,0 +1,23 @@
package main
// Note: this is started internally by LocalAI and a server is allocated for each model
import (
"flag"
transformers "github.com/go-skynet/LocalAI/pkg/grpc/llm/transformers"
grpc "github.com/go-skynet/LocalAI/pkg/grpc"
)
var (
addr = flag.String("addr", "localhost:50051", "the address to connect to")
)
func main() {
flag.Parse()
if err := grpc.StartServer(*addr, &transformers.GPT2{}); err != nil {
panic(err)
}
}

@ -0,0 +1,23 @@
package main
// Note: this is started internally by LocalAI and a server is allocated for each model
import (
"flag"
gpt4all "github.com/go-skynet/LocalAI/pkg/grpc/llm/gpt4all"
grpc "github.com/go-skynet/LocalAI/pkg/grpc"
)
var (
addr = flag.String("addr", "localhost:50051", "the address to connect to")
)
func main() {
flag.Parse()
if err := grpc.StartServer(*addr, &gpt4all.LLM{}); err != nil {
panic(err)
}
}

@ -0,0 +1,23 @@
package main
// Note: this is started internally by LocalAI and a server is allocated for each model
import (
"flag"
transformers "github.com/go-skynet/LocalAI/pkg/grpc/llm/transformers"
grpc "github.com/go-skynet/LocalAI/pkg/grpc"
)
var (
addr = flag.String("addr", "localhost:50051", "the address to connect to")
)
func main() {
flag.Parse()
if err := grpc.StartServer(*addr, &transformers.GPTJ{}); err != nil {
panic(err)
}
}

@ -0,0 +1,23 @@
package main
// Note: this is started internally by LocalAI and a server is allocated for each model
import (
"flag"
transformers "github.com/go-skynet/LocalAI/pkg/grpc/llm/transformers"
grpc "github.com/go-skynet/LocalAI/pkg/grpc"
)
var (
addr = flag.String("addr", "localhost:50051", "the address to connect to")
)
func main() {
flag.Parse()
if err := grpc.StartServer(*addr, &transformers.GPTNeoX{}); err != nil {
panic(err)
}
}

@ -0,0 +1,23 @@
package main
// Note: this is started internally by LocalAI and a server is allocated for each model
import (
"flag"
langchain "github.com/go-skynet/LocalAI/pkg/grpc/llm/langchain"
grpc "github.com/go-skynet/LocalAI/pkg/grpc"
)
var (
addr = flag.String("addr", "localhost:50051", "the address to connect to")
)
func main() {
flag.Parse()
if err := grpc.StartServer(*addr, &langchain.LLM{}); err != nil {
panic(err)
}
}

@ -0,0 +1,25 @@
package main
// GRPC Falcon server
// Note: this is started internally by LocalAI and a server is allocated for each model
import (
"flag"
llama "github.com/go-skynet/LocalAI/pkg/grpc/llm/llama"
grpc "github.com/go-skynet/LocalAI/pkg/grpc"
)
var (
addr = flag.String("addr", "localhost:50051", "the address to connect to")
)
func main() {
flag.Parse()
if err := grpc.StartServer(*addr, &llama.LLM{}); err != nil {
panic(err)
}
}

@ -0,0 +1,23 @@
package main
// Note: this is started internally by LocalAI and a server is allocated for each model
import (
"flag"
transformers "github.com/go-skynet/LocalAI/pkg/grpc/llm/transformers"
grpc "github.com/go-skynet/LocalAI/pkg/grpc"
)
var (
addr = flag.String("addr", "localhost:50051", "the address to connect to")
)
func main() {
flag.Parse()
if err := grpc.StartServer(*addr, &transformers.MPT{}); err != nil {
panic(err)
}
}

@ -0,0 +1,23 @@
package main
// Note: this is started internally by LocalAI and a server is allocated for each model
import (
"flag"
tts "github.com/go-skynet/LocalAI/pkg/grpc/tts"
grpc "github.com/go-skynet/LocalAI/pkg/grpc"
)
var (
addr = flag.String("addr", "localhost:50051", "the address to connect to")
)
func main() {
flag.Parse()
if err := grpc.StartServer(*addr, &tts.Piper{}); err != nil {
panic(err)
}
}

@ -0,0 +1,23 @@
package main
// Note: this is started internally by LocalAI and a server is allocated for each model
import (
"flag"
transformers "github.com/go-skynet/LocalAI/pkg/grpc/llm/transformers"
grpc "github.com/go-skynet/LocalAI/pkg/grpc"
)
var (
addr = flag.String("addr", "localhost:50051", "the address to connect to")
)
func main() {
flag.Parse()
if err := grpc.StartServer(*addr, &transformers.Replit{}); err != nil {
panic(err)
}
}

@ -0,0 +1,23 @@
package main
// Note: this is started internally by LocalAI and a server is allocated for each model
import (
"flag"
rwkv "github.com/go-skynet/LocalAI/pkg/grpc/llm/rwkv"
grpc "github.com/go-skynet/LocalAI/pkg/grpc"
)
var (
addr = flag.String("addr", "localhost:50051", "the address to connect to")
)
func main() {
flag.Parse()
if err := grpc.StartServer(*addr, &rwkv.LLM{}); err != nil {
panic(err)
}
}

@ -0,0 +1,23 @@
package main
// Note: this is started internally by LocalAI and a server is allocated for each model
import (
"flag"
image "github.com/go-skynet/LocalAI/pkg/grpc/image"
grpc "github.com/go-skynet/LocalAI/pkg/grpc"
)
var (
addr = flag.String("addr", "localhost:50051", "the address to connect to")
)
func main() {
flag.Parse()
if err := grpc.StartServer(*addr, &image.StableDiffusion{}); err != nil {
panic(err)
}
}

@ -0,0 +1,23 @@
package main
// Note: this is started internally by LocalAI and a server is allocated for each model
import (
"flag"
transformers "github.com/go-skynet/LocalAI/pkg/grpc/llm/transformers"
grpc "github.com/go-skynet/LocalAI/pkg/grpc"
)
var (
addr = flag.String("addr", "localhost:50051", "the address to connect to")
)
func main() {
flag.Parse()
if err := grpc.StartServer(*addr, &transformers.Starcoder{}); err != nil {
panic(err)
}
}

@ -0,0 +1,23 @@
package main
// Note: this is started internally by LocalAI and a server is allocated for each model
import (
"flag"
transcribe "github.com/go-skynet/LocalAI/pkg/grpc/transcribe"
grpc "github.com/go-skynet/LocalAI/pkg/grpc"
)
var (
addr = flag.String("addr", "localhost:50051", "the address to connect to")
)
func main() {
flag.Parse()
if err := grpc.StartServer(*addr, &transcribe.Whisper{}); err != nil {
panic(err)
}
}

@ -13,20 +13,25 @@ require (
github.com/gofiber/fiber/v2 v2.47.0
github.com/google/uuid v1.3.0
github.com/hashicorp/go-multierror v1.1.1
github.com/hpcloud/tail v1.0.0
github.com/imdario/mergo v0.3.16
github.com/json-iterator/go v1.1.12
github.com/mholt/archiver/v3 v3.5.1
github.com/mudler/go-ggllm.cpp v0.0.0-20230708215552-a6504d5bc137
github.com/mudler/go-processmanager v0.0.0-20220724164624-c45b5c61312d
github.com/mudler/go-stable-diffusion v0.0.0-20230605122230-d89260f598af
github.com/nomic-ai/gpt4all/gpt4all-bindings/golang v0.0.0-20230708212935-d611d107479f
github.com/onsi/ginkgo/v2 v2.11.0
github.com/onsi/gomega v1.27.8
github.com/otiai10/openaigo v1.5.2
github.com/phayes/freeport v0.0.0-20220201140144-74d24b5ae9f5
github.com/rs/zerolog v1.29.1
github.com/sashabaranov/go-openai v1.13.0
github.com/swaggo/swag v1.16.1
github.com/tmc/langchaingo v0.0.0-20230709010448-a875e6bc0c54
github.com/urfave/cli/v2 v2.25.7
github.com/valyala/fasthttp v1.48.0
google.golang.org/grpc v1.56.2
google.golang.org/protobuf v1.30.0
gopkg.in/yaml.v2 v2.4.0
gopkg.in/yaml.v3 v3.0.1
)
@ -34,8 +39,10 @@ require (
require (
github.com/dlclark/regexp2 v1.8.1 // indirect
github.com/dsnet/compress v0.0.2-0.20210315054119-f66993602bf5 // indirect
github.com/golang/protobuf v1.5.3 // indirect
github.com/golang/snappy v0.0.2 // indirect
github.com/klauspost/pgzip v1.2.5 // indirect
github.com/kr/text v0.2.0 // indirect
github.com/modern-go/concurrent v0.0.0-20180228061459-e0a39a4cb421 // indirect
github.com/modern-go/reflect2 v1.0.2 // indirect
github.com/nwaples/rardecode v1.1.0 // indirect
@ -43,33 +50,27 @@ require (
github.com/pkoukk/tiktoken-go v0.1.2 // indirect
github.com/ulikunitz/xz v0.5.9 // indirect
github.com/xi2/xz v0.0.0-20171230120015-48954b6210f8 // indirect
google.golang.org/genproto v0.0.0-20230410155749-daa745c078e1 // indirect
gopkg.in/check.v1 v1.0.0-20201130134442-10cb98267c6c // indirect
gopkg.in/fsnotify.v1 v1.4.7 // indirect
gopkg.in/tomb.v1 v1.0.0-20141024135613-dd632973f1e7 // indirect
)
require (
github.com/KyleBanks/depth v1.2.1 // indirect
github.com/PuerkitoBio/purell v1.1.1 // indirect
github.com/PuerkitoBio/urlesc v0.0.0-20170810143723-de5bf2ad4578 // indirect
github.com/andybalholm/brotli v1.0.5 // indirect
github.com/cpuguy83/go-md2man/v2 v2.0.2 // indirect
github.com/go-audio/audio v1.0.0 // indirect
github.com/go-audio/riff v1.0.0 // indirect
github.com/go-logr/logr v1.2.4 // indirect
github.com/go-openapi/jsonpointer v0.19.5 // indirect
github.com/go-openapi/jsonreference v0.19.6 // indirect
github.com/go-openapi/spec v0.20.4 // indirect
github.com/go-openapi/swag v0.22.3 // indirect
github.com/go-task/slim-sprig v0.0.0-20230315185526-52ccab3ef572 // indirect
github.com/google/go-cmp v0.5.9 // indirect
github.com/google/pprof v0.0.0-20210407192527-94a9f03dee38 // indirect
github.com/hashicorp/errwrap v1.0.0 // indirect
github.com/josharian/intern v1.0.0 // indirect
github.com/klauspost/compress v1.16.3 // indirect
github.com/mailru/easyjson v0.7.7 // indirect
github.com/mattn/go-colorable v0.1.13 // indirect
github.com/mattn/go-isatty v0.0.19 // indirect
github.com/mattn/go-runewidth v0.0.14 // indirect
github.com/mudler/go-piper v0.0.0-20230621222733-56b8a81b4760
github.com/otiai10/mint v1.6.1 // indirect
github.com/philhofer/fwd v1.1.2 // indirect
github.com/rivo/uniseg v0.2.0 // indirect
github.com/russross/blackfriday/v2 v2.1.0 // indirect

162
go.sum

@ -1,9 +1,3 @@
github.com/KyleBanks/depth v1.2.1 h1:5h8fQADFrWtarTdtDudMmGsC7GPbOAu6RVB3ffsVFHc=
github.com/KyleBanks/depth v1.2.1/go.mod h1:jzSb9d0L43HxTQfT+oSA1EEp2q+ne2uh6XgeJcm8brE=
github.com/PuerkitoBio/purell v1.1.1 h1:WEQqlqaGbrPkxLJWfBwQmfEAE1Z7ONdDLqrN38tNFfI=
github.com/PuerkitoBio/purell v1.1.1/go.mod h1:c11w/QuzBsJSee3cPx9rAFu61PvFxuPbtSwDGJws/X0=
github.com/PuerkitoBio/urlesc v0.0.0-20170810143723-de5bf2ad4578 h1:d+Bc7a5rLufV/sSk/8dngufqelfh6jnri85riMAaF/M=
github.com/PuerkitoBio/urlesc v0.0.0-20170810143723-de5bf2ad4578/go.mod h1:uGdkoq3SwY9Y+13GIhn11/XLaGBb4BfwItxLd5jeuXE=
github.com/andybalholm/brotli v1.0.1/go.mod h1:loMXtMfwqflxFJPmdbJO0a3KNoPuLBgiu3qAvBg8x/Y=
github.com/andybalholm/brotli v1.0.5 h1:8uQZIdzKmjc/iuPu7O2ioW48L81FgatrcpfFmiq/cCs=
github.com/andybalholm/brotli v1.0.5/go.mod h1:fO7iG3H7G2nSZ7m0zPUDn85XEX2GTukHGRSepvi9Eig=
@ -19,13 +13,12 @@ github.com/davecgh/go-spew v1.1.1 h1:vj9j/u1bqnvCEfJOwUhtlOARqs3+rkHYY13jYWTU97c
github.com/davecgh/go-spew v1.1.1/go.mod h1:J7Y8YcW2NihsgmVo/mv3lAwl/skON4iLHjSsI+c5H38=
github.com/dlclark/regexp2 v1.8.1 h1:6Lcdwya6GjPUNsBct8Lg/yRPwMhABj269AAzdGSiR+0=
github.com/dlclark/regexp2 v1.8.1/go.mod h1:DHkYz0B9wPfa6wondMfaivmHpzrQ3v9q8cnmRbL6yW8=
github.com/donomii/go-rwkv.cpp v0.0.0-20230619005719-f5a8c4539674 h1:G70Yf/QOCEL1v24idWnGd6rJsbqiGkJAJnMaWaolzEg=
github.com/donomii/go-rwkv.cpp v0.0.0-20230619005719-f5a8c4539674/go.mod h1:gWy7FIWioqYmYxkaoFyBnaKApeZVrUkHhv9EV9pz4dM=
github.com/dsnet/compress v0.0.2-0.20210315054119-f66993602bf5 h1:iFaUwBSo5Svw6L7HYpRu/0lE3e0BaElwnNO1qkNQxBY=
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/ggerganov/whisper.cpp/bindings/go v0.0.0-20230606002726-57543c169e27 h1:boeMTUUBtnLU8JElZJHXrsUzROJar9/t6vGOFjkrhhI=
github.com/ggerganov/whisper.cpp/bindings/go v0.0.0-20230606002726-57543c169e27/go.mod h1:QIjZ9OktHFG7p+/m3sMvrAJKKdWrr1fZIK0rM6HZlyo=
github.com/fsnotify/fsnotify v1.4.7/go.mod h1:jwhsz4b93w/PPRr/qN1Yymfu8t87LnFCMoQvtojpjFo=
github.com/fsnotify/fsnotify v1.4.9 h1:hsms1Qyu0jgnwNXIxa+/V/PDsU6CfLf6CNO8H7IWoS4=
github.com/fsnotify/fsnotify v1.4.9/go.mod h1:znqG4EE+3YCdAaPaxE2ZRY/06pZUdp0tY4IgpuI1SZQ=
github.com/ggerganov/whisper.cpp/bindings/go v0.0.0-20230628193450-85ed71aaec8e h1:KtbU2JR3lJuXFASHG2+sVLucfMPBjWKUUKByX6C81mQ=
github.com/ggerganov/whisper.cpp/bindings/go v0.0.0-20230628193450-85ed71aaec8e/go.mod h1:QIjZ9OktHFG7p+/m3sMvrAJKKdWrr1fZIK0rM6HZlyo=
github.com/go-audio/audio v1.0.0 h1:zS9vebldgbQqktK4H0lUqWrG8P0NxCJVqcj7ZpNnwd4=
@ -36,47 +29,28 @@ github.com/go-audio/wav v1.1.0 h1:jQgLtbqBzY7G+BM8fXF7AHUk1uHUviWS4X39d5rsL2g=
github.com/go-audio/wav v1.1.0/go.mod h1:mpe9qfwbScEbkd8uybLuIpTgHyrISw/OTuvjUW2iGtE=
github.com/go-logr/logr v1.2.4 h1:g01GSCwiDw2xSZfjJ2/T9M+S6pFdcNtFYsp+Y43HYDQ=
github.com/go-logr/logr v1.2.4/go.mod h1:jdQByPbusPIv2/zmleS9BjJVeZ6kBagPoEUsqbVz/1A=
github.com/go-openapi/jsonpointer v0.19.3/go.mod h1:Pl9vOtqEWErmShwVjC8pYs9cog34VGT37dQOVbmoatg=
github.com/go-openapi/jsonpointer v0.19.5 h1:gZr+CIYByUqjcgeLXnQu2gHYQC9o73G2XUeOFYEICuY=
github.com/go-openapi/jsonpointer v0.19.5/go.mod h1:Pl9vOtqEWErmShwVjC8pYs9cog34VGT37dQOVbmoatg=
github.com/go-openapi/jsonreference v0.19.6 h1:UBIxjkht+AWIgYzCDSv2GN+E/togfwXUJFRTWhl2Jjs=
github.com/go-openapi/jsonreference v0.19.6/go.mod h1:diGHMEHg2IqXZGKxqyvWdfWU/aim5Dprw5bqpKkTvns=
github.com/go-openapi/spec v0.20.4 h1:O8hJrt0UMnhHcluhIdUgCLRWyM2x7QkBXRvOs7m+O1M=
github.com/go-openapi/spec v0.20.4/go.mod h1:faYFR1CvsJZ0mNsmsphTMSoRrNV3TEDoAM7FOEWeq8I=
github.com/go-openapi/swag v0.19.5/go.mod h1:POnQmlKehdgb5mhVOsnJFsivZCEZ/vjK9gh66Z9tfKk=
github.com/go-openapi/swag v0.19.15 h1:D2NRCBzS9/pEY3gP9Nl8aDqGUcPFrwG2p+CNFrLyrCM=
github.com/go-openapi/swag v0.19.15/go.mod h1:QYRuS/SOXUCsnplDa677K7+DxSOj6IPNl/eQntq43wQ=
github.com/go-openapi/swag v0.22.3/go.mod h1:UzaqsxGiab7freDnrUUra0MwWfN/q7tE4j+VcZ0yl14=
github.com/go-skynet/bloomz.cpp v0.0.0-20230529155654-1834e77b83fa h1:gxr68r/6EWroay4iI81jxqGCDbKotY4+CiwdUkBz2NQ=
github.com/go-skynet/bloomz.cpp v0.0.0-20230529155654-1834e77b83fa/go.mod h1:wc0fJ9V04yiYTfgKvE5RUUSRQ5Kzi0Bo4I+U3nNOUuA=
github.com/go-skynet/go-bert.cpp v0.0.0-20230607105116-6069103f54b9 h1:wRGbDwNwPmSzoXVw/HLzXY4blpRvPWg7QW2OA0WKezA=
github.com/go-skynet/go-bert.cpp v0.0.0-20230607105116-6069103f54b9/go.mod h1:pXKCpYYXujMeAvgJHU6WoMfvYbr84563+J8+Ebkyr5U=
github.com/go-skynet/go-ggml-transformers.cpp v0.0.0-20230617123349-32b9223ccdb1 h1:jVGgzDSfpjD/0jl/ChpGI+O4EHSAeeU6DK7IyhH8PK8=
github.com/go-skynet/go-ggml-transformers.cpp v0.0.0-20230617123349-32b9223ccdb1/go.mod h1:31j1odgFXP8hDSUVfH0zErKI5aYVP18ddYnPkwCso2A=
github.com/go-skynet/go-ggml-transformers.cpp v0.0.0-20230620192816-a459d2726792 h1:rozZ9gWGzq0ZhBsNCWqfLTRCebaxwTsxLMnflwe6rDU=
github.com/go-skynet/go-ggml-transformers.cpp v0.0.0-20230620192816-a459d2726792/go.mod h1:31j1odgFXP8hDSUVfH0zErKI5aYVP18ddYnPkwCso2A=
github.com/go-skynet/go-ggml-transformers.cpp v0.0.0-20230626202628-8e31841dcddc h1:SrNxH4U8W6cqurbxpXxm9rzifeDsCgecRT73kT0BRq0=
github.com/go-skynet/go-ggml-transformers.cpp v0.0.0-20230626202628-8e31841dcddc/go.mod h1:31j1odgFXP8hDSUVfH0zErKI5aYVP18ddYnPkwCso2A=
github.com/go-skynet/go-ggml-transformers.cpp v0.0.0-20230630204211-3fec197a1dc4 h1:LScGc8yWTS9wbS2RTOq6s+waeHElLIQDJg2SUCwrO3E=
github.com/go-skynet/go-ggml-transformers.cpp v0.0.0-20230630204211-3fec197a1dc4/go.mod h1:31j1odgFXP8hDSUVfH0zErKI5aYVP18ddYnPkwCso2A=
github.com/go-skynet/go-llama.cpp v0.0.0-20230616223721-7ad833b67070 h1:T771FjB1yQw8j4P5x4ayFrUPNTglzxRIqDjaNkMVIME=
github.com/go-skynet/go-llama.cpp v0.0.0-20230616223721-7ad833b67070/go.mod h1:tzi97YvT1bVQ+iTG39LvpDkKG1WbizgtljC+orSoM40=
github.com/go-skynet/go-llama.cpp v0.0.0-20230626215901-f104111358e8 h1:Knh5QUvI/68erb/yWtrVa/3hvoQdENF2dH0hL2HNPrI=
github.com/go-skynet/go-llama.cpp v0.0.0-20230626215901-f104111358e8/go.mod h1:tzi97YvT1bVQ+iTG39LvpDkKG1WbizgtljC+orSoM40=
github.com/go-skynet/go-llama.cpp v0.0.0-20230627195533-582753605210 h1:9bm+vsiR3UI7xlU0G0cMU2Swq78RysoFVkSONvrujF8=
github.com/go-skynet/go-llama.cpp v0.0.0-20230627195533-582753605210/go.mod h1:tzi97YvT1bVQ+iTG39LvpDkKG1WbizgtljC+orSoM40=
github.com/go-skynet/go-llama.cpp v0.0.0-20230628194133-42ba44838369 h1:lSX1NWzRvRS2MlACvyvVVUnqXhKiuMAoN3DO5TbCe8M=
github.com/go-skynet/go-llama.cpp v0.0.0-20230628194133-42ba44838369/go.mod h1:tzi97YvT1bVQ+iTG39LvpDkKG1WbizgtljC+orSoM40=
github.com/go-skynet/go-llama.cpp v0.0.0-20230703203849-ffa57fbc3a12 h1:cfGZiZana0gPD0i8nmyOGTUQGb4N8PYqaBqhhukREPc=
github.com/go-skynet/go-llama.cpp v0.0.0-20230703203849-ffa57fbc3a12/go.mod h1:tzi97YvT1bVQ+iTG39LvpDkKG1WbizgtljC+orSoM40=
github.com/go-task/slim-sprig v0.0.0-20210107165309-348f09dbbbc0/go.mod h1:fyg7847qk6SyHyPtNmDHnmrv/HOrqktSC+C9fM+CJOE=
github.com/go-task/slim-sprig v0.0.0-20230315185526-52ccab3ef572 h1:tfuBGBXKqDEevZMzYi5KSi8KkcZtzBcTgAUUtapy0OI=
github.com/go-task/slim-sprig v0.0.0-20230315185526-52ccab3ef572/go.mod h1:9Pwr4B2jHnOSGXyyzV8ROjYa2ojvAY6HCGYYfMoC3Ls=
github.com/godbus/dbus/v5 v5.0.4/go.mod h1:xhWf0FNVPg57R7Z0UbKHbJfkEywrmjJnf7w5xrFpKfA=
github.com/gofiber/fiber/v2 v2.47.0 h1:EN5lHVCc+Pyqh5OEsk8fzRiifgwpbrP0rulQ4iNf3fs=
github.com/gofiber/fiber/v2 v2.47.0/go.mod h1:mbFMVN1lQuzziTkkakgtKKdjfsXSw9BKR5lmcNksUoU=
github.com/golang/protobuf v1.2.0/go.mod h1:6lQm79b+lXiMfvg/cZm0SGofjICqVBUtrP5yJMmIC1U=
github.com/golang/protobuf v1.4.0-rc.1/go.mod h1:ceaxUfeHdC40wWswd/P6IGgMaK3YpKi5j83Wpe3EHw8=
github.com/golang/protobuf v1.4.0-rc.1.0.20200221234624-67d41d38c208/go.mod h1:xKAWHe0F5eneWXFV3EuXVDTCmh+JuBKY0li0aMyXATA=
github.com/golang/protobuf v1.4.0-rc.2/go.mod h1:LlEzMj4AhA7rCAGe4KMBDvJI+AwstrUpVNzEA03Pprs=
github.com/golang/protobuf v1.4.0-rc.4.0.20200313231945-b860323f09d0/go.mod h1:WU3c8KckQ9AFe+yFwt9sWVRKCVIyN9cPHBJSNnbL67w=
github.com/golang/protobuf v1.4.0/go.mod h1:jodUvKwWbYaEsadDk5Fwe5c77LiNKVO9IDvqG2KuDX0=
github.com/golang/protobuf v1.4.2/go.mod h1:oDoupMAO8OvCJWAcko0GGGIgR6R6ocIYbsSw735rRwI=
github.com/golang/protobuf v1.5.0/go.mod h1:FsONVRAS9T7sI+LIUmWTfcYkHO4aIWwzhcaSAoJOfIk=
github.com/golang/protobuf v1.5.2/go.mod h1:XVQd3VNwM+JqD3oG2Ue2ip4fOMUkwXdXDdiuN0vRsmY=
github.com/golang/protobuf v1.5.3 h1:KhyjKVUg7Usr/dYsdSqoFveMYd5ko72D+zANwlG1mmg=
github.com/golang/protobuf v1.5.3/go.mod h1:XVQd3VNwM+JqD3oG2Ue2ip4fOMUkwXdXDdiuN0vRsmY=
github.com/golang/snappy v0.0.2 h1:aeE13tS0IiQgFjYdoL8qN3K1N2bXXtI6Vi51/y7BpMw=
github.com/golang/snappy v0.0.2/go.mod h1:/XxbfmMg8lxefKM7IXC3fBNl/7bRcc72aCRzEWrmP2Q=
github.com/google/go-cmp v0.3.0/go.mod h1:8QqcDgzrUqlUb/G2PQTWiueGozuR1884gddMywk6iLU=
github.com/google/go-cmp v0.3.1/go.mod h1:8QqcDgzrUqlUb/G2PQTWiueGozuR1884gddMywk6iLU=
github.com/google/go-cmp v0.4.0/go.mod h1:v8dTdLbMG2kIc/vJvl+f65V22dbkXbowE6jgT/gNBxE=
github.com/google/go-cmp v0.5.5/go.mod h1:v8dTdLbMG2kIc/vJvl+f65V22dbkXbowE6jgT/gNBxE=
github.com/google/go-cmp v0.5.9 h1:O2Tfq5qg4qc4AmwVlvv0oLiVAGB7enBSJ2x2DqQFi38=
github.com/google/go-cmp v0.5.9/go.mod h1:17dUlkBOakJ0+DkrSSNjCkIjxS6bF9zb3elmeNGIjoY=
@ -89,11 +63,11 @@ github.com/hashicorp/errwrap v1.0.0 h1:hLrqtEDnRye3+sgx6z4qVLNuviH3MR5aQ0ykNJa/U
github.com/hashicorp/errwrap v1.0.0/go.mod h1:YH+1FKiLXxHSkmPseP+kNlulaMuP3n2brvKWEqk/Jc4=
github.com/hashicorp/go-multierror v1.1.1 h1:H5DkEtf6CXdFp0N0Em5UCwQpXMWke8IA0+lD48awMYo=
github.com/hashicorp/go-multierror v1.1.1/go.mod h1:iw975J/qwKPdAO1clOe2L8331t/9/fmwbPZ6JB6eMoM=
github.com/hpcloud/tail v1.0.0 h1:nfCOvKYfkgYP8hkirhJocXT2+zOD8yUNjXaWfTlyFKI=
github.com/hpcloud/tail v1.0.0/go.mod h1:ab1qPbhIpdTxEkNHXyeSf5vhxWSCs/tWer42PpOxQnU=
github.com/ianlancetaylor/demangle v0.0.0-20200824232613-28f6c0f3b639/go.mod h1:aSSvb/t6k1mPoxDqO4vJh6VOCGPwU4O0C2/Eqndh1Sc=
github.com/imdario/mergo v0.3.16 h1:wwQJbIsHYGMUyLSPrEq1CT16AhnhNJQ51+4fdHUnCl4=
github.com/imdario/mergo v0.3.16/go.mod h1:WBLT9ZmE3lPoWsEzCh9LPo3TiwVN+ZKEjmz+hD27ysY=
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 v1.1.12 h1:PV8peI4a0ysnczrg+LtxykD8LfKY9ML6u2jnxaEnrnM=
github.com/json-iterator/go v1.1.12/go.mod h1:e30LSqwooZae/UwlEbR2852Gd8hjQvJoHmT4TnhNGBo=
github.com/klauspost/compress v1.4.1/go.mod h1:RyIbtBH6LamlWaDj8nUwkbUhJ87Yi3uG0guNDohfE1A=
@ -103,16 +77,12 @@ github.com/klauspost/compress v1.16.3/go.mod h1:ntbaceVETuRiXiv4DpjP66DpAtAGkEQs
github.com/klauspost/cpuid v1.2.0/go.mod h1:Pj4uuM528wm8OyEC2QMXAi2YiTZ96dNQPGgoMS4s3ek=
github.com/klauspost/pgzip v1.2.5 h1:qnWYvvKqedOF2ulHpMG72XQol4ILEJ8k2wwRl/Km8oE=
github.com/klauspost/pgzip v1.2.5/go.mod h1:Ch1tH69qFZu15pkjo5kYi6mth2Zzwzt50oCQKQE9RUs=
github.com/kr/pretty v0.1.0/go.mod h1:dAy3ld7l9f0ibDNOQOHHMYYIIbhfbHSm3C4ZsoJORNo=
github.com/kr/pretty v0.2.1 h1:Fmg33tUaq4/8ym9TJN1x7sLJnHVwhP33CNkpYV/7rwI=
github.com/kr/pretty v0.2.1/go.mod h1:ipq/a2n7PKx3OHsz4KJII5eveXtPO4qwEXGdVfWzfnI=
github.com/kr/pty v1.1.1/go.mod h1:pFQYn66WHrOpPYNljwOMqo10TkYh1fy3cYio2l3bCsQ=
github.com/kr/text v0.1.0/go.mod h1:4Jbv+DJW3UT/LiOwJeYQe1efqtUx/iVham/4vfdArNI=
github.com/kr/text v0.2.0 h1:5Nx0Ya0ZqY2ygV366QzturHI13Jq95ApcVaJBhpS+AY=
github.com/kr/text v0.2.0/go.mod h1:eLer722TekiGuMkidMxC/pM04lWEeraHUUmBw8l2grE=
github.com/mailru/easyjson v0.0.0-20190614124828-94de47d64c63/go.mod h1:C1wdFJiN94OJF2b5HbByQZoLdCWB1Yqtg26g4irojpc=
github.com/mailru/easyjson v0.0.0-20190626092158-b2ccc519800e/go.mod h1:C1wdFJiN94OJF2b5HbByQZoLdCWB1Yqtg26g4irojpc=
github.com/mailru/easyjson v0.7.6 h1:8yTIVnZgCoiM1TgqoeTl+LfU5Jg6/xL3QhGQnimLYnA=
github.com/mailru/easyjson v0.7.6/go.mod h1:xzfreul335JAWq5oZzymOObrkdz5UnU4kGfJJLY9Nlc=
github.com/mailru/easyjson v0.7.7/go.mod h1:xzfreul335JAWq5oZzymOObrkdz5UnU4kGfJJLY9Nlc=
github.com/mattn/go-colorable v0.1.12/go.mod h1:u5H1YNBxpqRaxsYJYSkiCWKzEfiAb1Gb520KVy5xxl4=
github.com/mattn/go-colorable v0.1.13 h1:fFA4WZxdEF4tXPZVKMLwD8oUnCTTo08duU7wxecdEvA=
github.com/mattn/go-colorable v0.1.13/go.mod h1:7S9/ev0klgBDR4GtXTXX8a3vIGJpMovkB8vQcUbaXHg=
@ -128,33 +98,29 @@ github.com/modern-go/concurrent v0.0.0-20180228061459-e0a39a4cb421 h1:ZqeYNhU3OH
github.com/modern-go/concurrent v0.0.0-20180228061459-e0a39a4cb421/go.mod h1:6dJC0mAP4ikYIbvyc7fijjWJddQyLn8Ig3JB5CqoB9Q=
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/mudler/go-piper v0.0.0-20230621222733-56b8a81b4760 h1:OFVkSxR7CRSRSNm5dvpMRZwmSwWa8EMMnHbc84fW5tU=
github.com/mudler/go-piper v0.0.0-20230621222733-56b8a81b4760/go.mod h1:O7SwdSWMilAWhBZMK9N9Y/oBDyMMzshE3ju8Xkexwig=
github.com/mudler/go-stable-diffusion v0.0.0-20230605122230-d89260f598af h1:XFq6OUqsWQam0OrEr05okXsJK/TQur3zoZTHbiZD3Ks=
github.com/mudler/go-stable-diffusion v0.0.0-20230605122230-d89260f598af/go.mod h1:8ufRkpz/S/9ahkaxzZ5i4WMgO9w4InEhuRoT7vK5Rnw=
github.com/niemeyer/pretty v0.0.0-20200227124842-a10e7caefd8e h1:fD57ERR4JtEqsWbfPhv4DMiApHyliiK5xCTNVSPiaAs=
github.com/niemeyer/pretty v0.0.0-20200227124842-a10e7caefd8e/go.mod h1:zD1mROLANZcx1PVRCS0qkT7pwLkGfwJo4zjcN/Tysno=
github.com/nomic-ai/gpt4all/gpt4all-bindings/golang v0.0.0-20230620230702-09ae04cee90c h1:axNtjd5k6Xs4Ck7B7VRRQu6q5lQzTsjdWmaJkDADopU=
github.com/nomic-ai/gpt4all/gpt4all-bindings/golang v0.0.0-20230620230702-09ae04cee90c/go.mod h1:4T3CHXyrt+7FQHXaxULZfPjHbD8/99WuDDJa0YVZARI=
github.com/nomic-ai/gpt4all/gpt4all-bindings/golang v0.0.0-20230628182915-a67f8132e165 h1:zcnIdoSeLueTDxUD2A1qnyaSp8uh0Ay7OgHeBwpxSeg=
github.com/nomic-ai/gpt4all/gpt4all-bindings/golang v0.0.0-20230628182915-a67f8132e165/go.mod h1:4T3CHXyrt+7FQHXaxULZfPjHbD8/99WuDDJa0YVZARI=
github.com/nomic-ai/gpt4all/gpt4all-bindings/golang v0.0.0-20230708212935-d611d107479f h1:FtXRIjsBvoBQ5xmA26QbzyG4RjV2U5lOpUgP4npITOM=
github.com/nomic-ai/gpt4all/gpt4all-bindings/golang v0.0.0-20230708212935-d611d107479f/go.mod h1:4T3CHXyrt+7FQHXaxULZfPjHbD8/99WuDDJa0YVZARI=
github.com/mudler/go-processmanager v0.0.0-20220724164624-c45b5c61312d h1:/lAg9vPAAU+s35cDMCx1IyeMn+4OYfCBPqi08Q8vXDg=
github.com/mudler/go-processmanager v0.0.0-20220724164624-c45b5c61312d/go.mod h1:HGGAOJhipApckwNV8ZTliRJqxctUv3xRY+zbQEwuytc=
github.com/nwaples/rardecode v1.1.0 h1:vSxaY8vQhOcVr4mm5e8XllHWTiM4JF507A0Katqw7MQ=
github.com/nwaples/rardecode v1.1.0/go.mod h1:5DzqNKiOdpKKBH87u8VlvAnPZMXcGRhxWkRpHbbfGS0=
github.com/nxadm/tail v1.4.4/go.mod h1:kenIhsEOeOJmVchQTgglprH7qJGnHDVpk1VPCcaMI8A=
github.com/nxadm/tail v1.4.8 h1:nPr65rt6Y5JFSKQO7qToXr7pePgD6Gwiw05lkbyAQTE=
github.com/nxadm/tail v1.4.8/go.mod h1:+ncqLTQzXmGhMZNUePPaPqPvBxHAIsmXswZKocGu+AU=
github.com/onsi/ginkgo v1.6.0/go.mod h1:lLunBs/Ym6LB5Z9jYTR76FiuTmxDTDusOGeTQH+WWjE=
github.com/onsi/ginkgo v1.12.1/go.mod h1:zj2OWP4+oCPe1qIXoGWkgMRwljMUYCdkwsT2108oapk=
github.com/onsi/ginkgo v1.16.4 h1:29JGrr5oVBm5ulCWet69zQkzWipVXIol6ygQUe/EzNc=
github.com/onsi/ginkgo v1.16.4/go.mod h1:dX+/inL/fNMqNlz0e9LfyB9TswhZpCVdJM/Z6Vvnwo0=
github.com/onsi/ginkgo/v2 v2.11.0 h1:WgqUCUt/lT6yXoQ8Wef0fsNn5cAuMK7+KT9UFRz2tcU=
github.com/onsi/ginkgo/v2 v2.11.0/go.mod h1:ZhrRA5XmEE3x3rhlzamx/JJvujdZoJ2uvgI7kR0iZvM=
github.com/onsi/gomega v1.7.1/go.mod h1:XdKZgCCFLUoM/7CFJVPcG8C1xQ1AJ0vpAezJrB7JYyY=
github.com/onsi/gomega v1.10.1/go.mod h1:iN09h71vgCQne3DLsj+A5owkum+a2tYe+TOCB1ybHNo=
github.com/onsi/gomega v1.16.0/go.mod h1:HnhC7FXeEQY45zxNK3PPoIUhzk/80Xly9PcubAlGdZY=
github.com/onsi/gomega v1.27.8 h1:gegWiwZjBsf2DgiSbf5hpokZ98JVDMcWkUiigk6/KXc=
github.com/onsi/gomega v1.27.8/go.mod h1:2J8vzI/s+2shY9XHRApDkdgPo1TKT7P2u6fXeJKFnNQ=
github.com/otiai10/mint v1.5.1 h1:XaPLeE+9vGbuyEHem1JNk3bYc7KKqyI/na0/mLd/Kks=
github.com/otiai10/mint v1.5.1/go.mod h1:MJm72SBthJjz8qhefc4z1PYEieWmy8Bku7CjcAqyUSM=
github.com/otiai10/mint v1.6.1/go.mod h1:MJm72SBthJjz8qhefc4z1PYEieWmy8Bku7CjcAqyUSM=
github.com/otiai10/openaigo v1.2.0 h1:Whq+uvgqw8NdIsVdixtBKCAI6OdfCJiGPlhUnYJQ6Ag=
github.com/otiai10/openaigo v1.2.0/go.mod h1:792bx6AWTS61weDi2EzKpHHnTF4eDMAlJ5GvAk/mgPg=
github.com/otiai10/openaigo v1.4.0 h1:BeacKb2Q5bVejjOKHFJxL2WFYal3QxwkrKtKuoU5LNU=
github.com/otiai10/openaigo v1.4.0/go.mod h1:kIaXc3V+Xy5JLplcBxehVyGYDtufHp3PFPy04jOwOAI=
github.com/otiai10/mint v1.6.1 h1:kgbTJmOpp/0ce7hk3H8jiSuR0MXmpwWRfqUdKww17qg=
github.com/otiai10/openaigo v1.5.2 h1:YnNDisZmA4syArF3IxMCIrfgZOq30PLV219gPY7n2z8=
github.com/otiai10/openaigo v1.5.2/go.mod h1:kIaXc3V+Xy5JLplcBxehVyGYDtufHp3PFPy04jOwOAI=
github.com/phayes/freeport v0.0.0-20220201140144-74d24b5ae9f5 h1:Ii+DKncOVM8Cu1Hc+ETb5K+23HdAMvESYE3ZJ5b5cMI=
github.com/phayes/freeport v0.0.0-20220201140144-74d24b5ae9f5/go.mod h1:iIss55rKnNBTvrwdmkUpLnDpZoAHvWaiq5+iMmen4AE=
github.com/philhofer/fwd v1.1.1/go.mod h1:gk3iGcWd9+svBvR0sR+KPcfE+RNWozjowpeBVG3ZVNU=
github.com/philhofer/fwd v1.1.2 h1:bnDivRJ1EWPjUIRXV5KfORO897HTbpFAQddBdE8t7Gw=
github.com/philhofer/fwd v1.1.2/go.mod h1:qkPdfjR2SIEbspLqpe1tO4n5yICnr2DY7mqEx2tUTP0=
@ -172,8 +138,6 @@ github.com/rs/zerolog v1.29.1 h1:cO+d60CHkknCbvzEWxP0S9K6KqyTjrCNUy1LdQLCGPc=
github.com/rs/zerolog v1.29.1/go.mod h1:Le6ESbR7hc+DP6Lt1THiV8CQSdkkNrd3R0XbEgp3ZBU=
github.com/russross/blackfriday/v2 v2.1.0 h1:JIOH55/0cWyOuilr9/qlrm0BSXldqnqwMsf35Ld67mk=
github.com/russross/blackfriday/v2 v2.1.0/go.mod h1:+Rmxgy9KzJVeS9/2gXHxylqXiyQDYRxCVz55jmeOWTM=
github.com/sashabaranov/go-openai v1.11.3 h1:bvwWF8hj4UhPlswBdL9/IfOpaHXfzGCJO8WY8ml9sGc=
github.com/sashabaranov/go-openai v1.11.3/go.mod h1:lj5b/K+zjTSFxVLijLSTDZuP7adOgerWeFyZLUhAKRg=
github.com/sashabaranov/go-openai v1.13.0 h1:EAusFfnhaMaaUspUZ2+MbB/ZcVeD4epJmTOlZ+8AcAE=
github.com/sashabaranov/go-openai v1.13.0/go.mod h1:lj5b/K+zjTSFxVLijLSTDZuP7adOgerWeFyZLUhAKRg=
github.com/savsgio/dictpool v0.0.0-20221023140959-7bf2e61cea94 h1:rmMl4fXJhKMNWl+K+r/fq4FbbKI+Ia2m9hYBLm2h4G4=
@ -181,26 +145,14 @@ github.com/savsgio/dictpool v0.0.0-20221023140959-7bf2e61cea94/go.mod h1:90zrgN3
github.com/savsgio/gotils v0.0.0-20220530130905-52f3993e8d6d/go.mod h1:Gy+0tqhJvgGlqnTF8CVGP0AaGRjwBtXs/a5PA0Y3+A4=
github.com/savsgio/gotils v0.0.0-20230208104028-c358bd845dee h1:8Iv5m6xEo1NR1AvpV+7XmhI4r39LGNzwUL4YpMuL5vk=
github.com/savsgio/gotils v0.0.0-20230208104028-c358bd845dee/go.mod h1:qwtSXrKuJh/zsFQ12yEE89xfCrGKK63Rr7ctU/uCo4g=
github.com/shurcooL/sanitized_anchor_name v1.0.0/go.mod h1:1NzhyTcUVG4SuEtjjoZeVRXNmyL/1OwPU0+IJeTBvfc=
github.com/stretchr/objx v0.1.0/go.mod h1:HFkY916IF+rwdDfMAkV7OtwuqBVzrE8GR6GFx+wExME=
github.com/stretchr/testify v1.3.0/go.mod h1:M5WIy9Dh21IEIfnGCwXGc5bZfKNJtfHm1UVUgZn+9EI=
github.com/stretchr/testify v1.5.1/go.mod h1:5W2xD1RspED5o8YsWQXVCued0rvSQ+mT+I5cxcmMvtA=
github.com/stretchr/testify v1.6.1/go.mod h1:6Fq8oRcR53rry900zMqJjRRixrwX3KX962/h/Wwjteg=
github.com/stretchr/testify v1.8.2 h1:+h33VjcLVPDHtOdpUCuF+7gSuG3yGIftsP1YvFihtJ8=
github.com/swaggo/swag v1.16.1 h1:fTNRhKstPKxcnoKsytm4sahr8FaYzUcT7i1/3nd/fBg=
github.com/swaggo/swag v1.16.1/go.mod h1:9/LMvHycG3NFHfR6LwvikHv5iFvmPADQ359cKikGxto=
github.com/tinylib/msgp v1.1.6/go.mod h1:75BAfg2hauQhs3qedfdDZmWAPcFMAvJE5b9rGOMufyw=
github.com/tinylib/msgp v1.1.8 h1:FCXC1xanKO4I8plpHGH2P7koL/RzZs12l/+r7vakfm0=
github.com/tinylib/msgp v1.1.8/go.mod h1:qkpG+2ldGg4xRFmx+jfTvZPxfGFhi64BcnL9vkCm/Tw=
github.com/tmc/langchaingo v0.0.0-20230616220619-1b3da4433944 h1:EE9fvNENTdRc/yI/1zAs7VFbmDk6JZ7EbBIFl+TsCm0=
github.com/tmc/langchaingo v0.0.0-20230616220619-1b3da4433944/go.mod h1:6l1WoyqVDwkv7cFlY3gfcTv8yVowVyuutKv8PGlQCWI=
github.com/tmc/langchaingo v0.0.0-20230625081011-4d9d55dbcaba h1:NpAI9C0y9T4jwP7XFShwYJKGf/ggyCgZEtL/7lLRPwE=
github.com/tmc/langchaingo v0.0.0-20230625081011-4d9d55dbcaba/go.mod h1:tz9cjA9BW8/lWx/T5njr3ZLHK/dfPyr/0ICSMThmY2g=
github.com/tmc/langchaingo v0.0.0-20230625234550-7ea734523e39 h1:SpOEFXx5xXLypFnwNRQj7yOC3rMvSylGA5BQW/FAwYc=
github.com/tmc/langchaingo v0.0.0-20230625234550-7ea734523e39/go.mod h1:tz9cjA9BW8/lWx/T5njr3ZLHK/dfPyr/0ICSMThmY2g=
github.com/tmc/langchaingo v0.0.0-20230627220614-633853b5ac3b h1:xUxtya/3KRDn1rcCVZucp2KhjdqSZat9j0hOshSVh2Q=
github.com/tmc/langchaingo v0.0.0-20230627220614-633853b5ac3b/go.mod h1:F1k7uRBLM8jMMEPV3dVtWVNc+W91nxOBRKbJWM/LwpM=
github.com/tmc/langchaingo v0.0.0-20230628165432-e510561c17f9 h1:BooyHg3f058lrPcTLdfC7HTfjO5OGZAgwciQJ5e85l0=
github.com/tmc/langchaingo v0.0.0-20230628165432-e510561c17f9/go.mod h1:F1k7uRBLM8jMMEPV3dVtWVNc+W91nxOBRKbJWM/LwpM=
github.com/tmc/langchaingo v0.0.0-20230709010448-a875e6bc0c54 h1:MZSC3/pdBzkoPG49uTRvtEepOQKdbdgaT1aLtaEwxx4=
github.com/tmc/langchaingo v0.0.0-20230709010448-a875e6bc0c54/go.mod h1:RsMJqgUynOtr2jWNhUF41R3j6SDkKq9c8UfE0nJYBb4=
github.com/ulikunitz/xz v0.5.8/go.mod h1:nbz6k7qbPmH4IRqmfOplQw/tblSgqTqBwxkY0oWt/14=
@ -228,25 +180,34 @@ golang.org/x/mod v0.3.0/go.mod h1:s0Qsj1ACt9ePp/hMypM3fl4fZqREWJwdYDEqhRiZZUA=
golang.org/x/mod v0.6.0-dev.0.20220419223038-86c51ed26bb4/go.mod h1:jJ57K6gSWd91VN4djpZkiMVwK6gcyfeH4XE8wZrZaV4=
golang.org/x/mod v0.7.0/go.mod h1:iBbtSCu2XBx23ZKBPSOrRkjjQPZFPuis4dIYUhu/chs=
golang.org/x/mod v0.10.0 h1:lFO9qtOdlre5W1jxS3r/4szv2/6iXxScdzjoBMXNhYk=
golang.org/x/net v0.0.0-20180906233101-161cd47e91fd/go.mod h1:mL1N/T3taQHkDXs73rZJwtUhF3w3ftmwwsq0BUmARs4=
golang.org/x/net v0.0.0-20190404232315-eb5bcb51f2a3/go.mod h1:t9HGtf8HONx5eT2rtn7q6eTqICYqUVnKs3thJo3Qplg=
golang.org/x/net v0.0.0-20190620200207-3b0461eec859/go.mod h1:z5CRVTTTmAJ677TzLLGU+0bjPO0LkuOLi4/5GtJWs/s=
golang.org/x/net v0.0.0-20200520004742-59133d7f0dd7/go.mod h1:qpuaurCH72eLCgpAm/N6yyVIVM9cpaDIP3A8BGJEC5A=
golang.org/x/net v0.0.0-20201021035429-f5854403a974/go.mod h1:sp8m0HH+o8qH0wwXwYZr8TS3Oi6o0r6Gce1SSxlDquU=
golang.org/x/net v0.0.0-20210226172049-e18ecbb05110/go.mod h1:m0MpNAwzfU5UDzcl9v0D8zg8gWTRqZa9RBIspLL5mdg=
golang.org/x/net v0.0.0-20210421230115-4e50805a0758/go.mod h1:72T/g9IO56b78aLF+1Kcs5dz7/ng1VjMUvfKvpfy+jM=
golang.org/x/net v0.0.0-20210428140749-89ef3d95e781/go.mod h1:OJAsFXCWl8Ukc7SiCT/9KSuxbyM7479/AVlXFRxuMCk=
golang.org/x/net v0.0.0-20220722155237-a158d28d115b/go.mod h1:XRhObCWvk6IyKnWLug+ECip1KBveYUHfp+8e9klMJ9c=
golang.org/x/net v0.3.0/go.mod h1:MBQ8lrhLObU/6UmLb4fmbmk5OcyYmqtbGd/9yIeKjEE=
golang.org/x/net v0.10.0 h1:X2//UzNDwYmtCLn7To6G58Wr6f5ahEAQgKNzv9Y951M=
golang.org/x/net v0.10.0/go.mod h1:0qNGK6F8kojg2nk9dLZ2mShWaEBan6FAoqfSigmmuDg=
golang.org/x/sync v0.0.0-20180314180146-1d60e4601c6f/go.mod h1:RxMgew5VJxzue5/jJTE5uejpjVlOe/izrB70Jof72aM=
golang.org/x/sync v0.0.0-20190423024810-112230192c58/go.mod h1:RxMgew5VJxzue5/jJTE5uejpjVlOe/izrB70Jof72aM=
golang.org/x/sync v0.0.0-20201020160332-67f06af15bc9/go.mod h1:RxMgew5VJxzue5/jJTE5uejpjVlOe/izrB70Jof72aM=
golang.org/x/sync v0.0.0-20220722155255-886fb9371eb4/go.mod h1:RxMgew5VJxzue5/jJTE5uejpjVlOe/izrB70Jof72aM=
golang.org/x/sync v0.1.0/go.mod h1:RxMgew5VJxzue5/jJTE5uejpjVlOe/izrB70Jof72aM=
golang.org/x/sys v0.0.0-20180909124046-d0be0721c37e/go.mod h1:STP8DvDyc/dI5b8T5hshtkjS+E42TnysNCUPdjciGhY=
golang.org/x/sys v0.0.0-20190215142949-d0b11bdaac8a/go.mod h1:STP8DvDyc/dI5b8T5hshtkjS+E42TnysNCUPdjciGhY=
golang.org/x/sys v0.0.0-20190412213103-97732733099d/go.mod h1:h1NjWce9XRLGQEsW7wpKNCjG9DtNlClVuFLEZdDNbEs=
golang.org/x/sys v0.0.0-20190904154756-749cb33beabd/go.mod h1:h1NjWce9XRLGQEsW7wpKNCjG9DtNlClVuFLEZdDNbEs=
golang.org/x/sys v0.0.0-20191005200804-aed5e4c7ecf9/go.mod h1:h1NjWce9XRLGQEsW7wpKNCjG9DtNlClVuFLEZdDNbEs=
golang.org/x/sys v0.0.0-20191120155948-bd437916bb0e/go.mod h1:h1NjWce9XRLGQEsW7wpKNCjG9DtNlClVuFLEZdDNbEs=
golang.org/x/sys v0.0.0-20191204072324-ce4227a45e2e/go.mod h1:h1NjWce9XRLGQEsW7wpKNCjG9DtNlClVuFLEZdDNbEs=
golang.org/x/sys v0.0.0-20200323222414-85ca7c5b95cd/go.mod h1:h1NjWce9XRLGQEsW7wpKNCjG9DtNlClVuFLEZdDNbEs=
golang.org/x/sys v0.0.0-20200930185726-fdedc70b468f/go.mod h1:h1NjWce9XRLGQEsW7wpKNCjG9DtNlClVuFLEZdDNbEs=
golang.org/x/sys v0.0.0-20201119102817-f84b799fce68/go.mod h1:h1NjWce9XRLGQEsW7wpKNCjG9DtNlClVuFLEZdDNbEs=
golang.org/x/sys v0.0.0-20210420072515-93ed5bcd2bfe/go.mod h1:h1NjWce9XRLGQEsW7wpKNCjG9DtNlClVuFLEZdDNbEs=
golang.org/x/sys v0.0.0-20210112080510-489259a85091/go.mod h1:h1NjWce9XRLGQEsW7wpKNCjG9DtNlClVuFLEZdDNbEs=
golang.org/x/sys v0.0.0-20210423082822-04245dca01da/go.mod h1:h1NjWce9XRLGQEsW7wpKNCjG9DtNlClVuFLEZdDNbEs=
golang.org/x/sys v0.0.0-20210615035016-665e8c7367d1/go.mod h1:oPkhp1MJrh7nUepCBck5+mAzfO9JrbApNNgaTdGDITg=
golang.org/x/sys v0.0.0-20210630005230-0f9fa26af87c/go.mod h1:oPkhp1MJrh7nUepCBck5+mAzfO9JrbApNNgaTdGDITg=
golang.org/x/sys v0.0.0-20210927094055-39ccf1dd6fa6/go.mod h1:oPkhp1MJrh7nUepCBck5+mAzfO9JrbApNNgaTdGDITg=
@ -270,6 +231,7 @@ golang.org/x/text v0.9.0/go.mod h1:e1OnstbJyHTd6l/uOt8jFFHp6TRDWZR/bV3emEE/zU8=
golang.org/x/tools v0.0.0-20180917221912-90fa682c2a6e/go.mod h1:n7NCudcB/nEzxVGmLbDWY5pfWTLqBcC2KZ6jyYvM4mQ=
golang.org/x/tools v0.0.0-20191119224855-298f0cb1881e/go.mod h1:b+2E5dAYhXwXZwtnZ6UAqBI28+e2cm9otk0dWdXHAEo=
golang.org/x/tools v0.0.0-20201022035929-9cf592e881e9/go.mod h1:emZCQorbCU4vsT4fOWvOPXz4eW1wZW4PmDk9uLelYpA=
golang.org/x/tools v0.0.0-20201224043029-2b0845dc783e/go.mod h1:emZCQorbCU4vsT4fOWvOPXz4eW1wZW4PmDk9uLelYpA=
golang.org/x/tools v0.1.12/go.mod h1:hNGJHUnrk76NpqgfD5Aqm5Crs+Hm0VOH/i9J2+nxYbc=
golang.org/x/tools v0.4.0/go.mod h1:UE5sM2OK9E/d67R0ANs2xJizIymRP5gJU295PvKXxjQ=
golang.org/x/tools v0.9.3 h1:Gn1I8+64MsuTb/HpH+LmQtNas23LhUVr3rYZ0eKuaMM=
@ -278,15 +240,33 @@ golang.org/x/xerrors v0.0.0-20190717185122-a985d3407aa7/go.mod h1:I/5z698sn9Ka8T
golang.org/x/xerrors v0.0.0-20191011141410-1b5146add898/go.mod h1:I/5z698sn9Ka8TeJc9MKroUUfqBBauWjQqLJ2OPfmY0=
golang.org/x/xerrors v0.0.0-20191204190536-9bdfabe68543/go.mod h1:I/5z698sn9Ka8TeJc9MKroUUfqBBauWjQqLJ2OPfmY0=
golang.org/x/xerrors v0.0.0-20200804184101-5ec99f83aff1/go.mod h1:I/5z698sn9Ka8TeJc9MKroUUfqBBauWjQqLJ2OPfmY0=
google.golang.org/genproto v0.0.0-20230410155749-daa745c078e1 h1:KpwkzHKEF7B9Zxg18WzOa7djJ+Ha5DzthMyZYQfEn2A=
google.golang.org/genproto v0.0.0-20230410155749-daa745c078e1/go.mod h1:nKE/iIaLqn2bQwXBg8f1g2Ylh6r5MN5CmZvuzZCgsCU=
google.golang.org/grpc v1.56.2 h1:fVRFRnXvU+x6C4IlHZewvJOVHoOv1TUuQyoRsYnB4bI=
google.golang.org/grpc v1.56.2/go.mod h1:I9bI3vqKfayGqPUAwGdOSu7kt6oIJLixfffKrpXqQ9s=
google.golang.org/protobuf v0.0.0-20200109180630-ec00e32a8dfd/go.mod h1:DFci5gLYBciE7Vtevhsrf46CRTquxDuWsQurQQe4oz8=
google.golang.org/protobuf v0.0.0-20200221191635-4d8936d0db64/go.mod h1:kwYJMbMJ01Woi6D6+Kah6886xMZcty6N08ah7+eCXa0=
google.golang.org/protobuf v0.0.0-20200228230310-ab0ca4ff8a60/go.mod h1:cfTl7dwQJ+fmap5saPgwCLgHXTUD7jkjRqWcaiX5VyM=
google.golang.org/protobuf v1.20.1-0.20200309200217-e05f789c0967/go.mod h1:A+miEFZTKqfCUM6K7xSMQL9OKL/b6hQv+e19PK+JZNE=
google.golang.org/protobuf v1.21.0/go.mod h1:47Nbq4nVaFHyn7ilMalzfO3qCViNmqZ2kzikPIcrTAo=
google.golang.org/protobuf v1.23.0/go.mod h1:EGpADcykh3NcUnDUJcl1+ZksZNG86OlYog2l/sGQquU=
google.golang.org/protobuf v1.26.0-rc.1/go.mod h1:jlhhOSvTdKEhbULTjvd4ARK9grFBp09yW+WbY/TyQbw=
google.golang.org/protobuf v1.26.0/go.mod h1:9q0QmTI4eRPtz6boOQmLYwt+qCgq0jsYwAQnmE0givc=
google.golang.org/protobuf v1.30.0 h1:kPPoIgf3TsEvrm0PFe15JQ+570QVxYzEvvHqChK+cng=
google.golang.org/protobuf v1.30.0/go.mod h1:HV8QOd/L58Z+nl8r43ehVNZIU/HEI6OcFqwMG9pJV4I=
gopkg.in/check.v1 v0.0.0-20161208181325-20d25e280405/go.mod h1:Co6ibVJAznAaIkqp8huTwlJQCZ016jof/cbN4VW5Yz0=
gopkg.in/check.v1 v1.0.0-20180628173108-788fd7840127/go.mod h1:Co6ibVJAznAaIkqp8huTwlJQCZ016jof/cbN4VW5Yz0=
gopkg.in/check.v1 v1.0.0-20200227125254-8fa46927fb4f h1:BLraFXnmrev5lT+xlilqcH8XK9/i0At2xKjWk4p6zsU=
gopkg.in/check.v1 v1.0.0-20200227125254-8fa46927fb4f/go.mod h1:Co6ibVJAznAaIkqp8huTwlJQCZ016jof/cbN4VW5Yz0=
gopkg.in/check.v1 v1.0.0-20201130134442-10cb98267c6c h1:Hei/4ADfdWqJk1ZMxUNpqntNwaWcugrBjAiHlqqRiVk=
gopkg.in/check.v1 v1.0.0-20201130134442-10cb98267c6c/go.mod h1:JHkPIbrfpd72SG/EVd6muEfDQjcINNoR0C8j2r3qZ4Q=
gopkg.in/fsnotify.v1 v1.4.7 h1:xOHLXZwVvI9hhs+cLKq5+I5onOuwQLhQwiu63xxlHs4=
gopkg.in/fsnotify.v1 v1.4.7/go.mod h1:Tz8NjZHkW78fSQdbUxIjBTcgA1z1m8ZHf0WmKUhAMys=
gopkg.in/op/go-logging.v1 v1.0.0-20160211212156-b2cb9fa56473/go.mod h1:N1eN2tsCx0Ydtgjl4cqmbRCsY4/+z4cYDeqwZTk6zog=
gopkg.in/tomb.v1 v1.0.0-20141024135613-dd632973f1e7 h1:uRGJdciOHaEIrze2W8Q3AKkepLTh2hOroT7a+7czfdQ=
gopkg.in/tomb.v1 v1.0.0-20141024135613-dd632973f1e7/go.mod h1:dt/ZhP58zS4L8KSrWDmTeBkI65Dw0HsyUHuEVlX15mw=
gopkg.in/yaml.v2 v2.2.2/go.mod h1:hI93XBmqTisBFMUTm0b8Fm+jr3Dg1NNxqwp+5A1VGuI=
gopkg.in/yaml.v2 v2.2.4/go.mod h1:hI93XBmqTisBFMUTm0b8Fm+jr3Dg1NNxqwp+5A1VGuI=
gopkg.in/yaml.v2 v2.3.0/go.mod h1:hI93XBmqTisBFMUTm0b8Fm+jr3Dg1NNxqwp+5A1VGuI=
gopkg.in/yaml.v2 v2.4.0 h1:D8xgwECY7CYvx+Y2n4sBz93Jn9JRvxdiyyo8CTfuKaY=
gopkg.in/yaml.v2 v2.4.0/go.mod h1:RDklbk79AGWmwhnvt/jBztapEOGDOx6ZbXqjP6csGnQ=
gopkg.in/yaml.v3 v3.0.0-20200313102051-9f266ea9e77c/go.mod h1:K4uyk7z7BCEPqu6E+C64Yfv1cQ7kz7rIZviUmN+EgEM=
gopkg.in/yaml.v3 v3.0.0-20200615113413-eeeca48fe776/go.mod h1:K4uyk7z7BCEPqu6E+C64Yfv1cQ7kz7rIZviUmN+EgEM=
gopkg.in/yaml.v3 v3.0.1 h1:fxVm/GzAzEWqLHuvctI91KS9hhNmmWOoWu0XTYJS7CA=
gopkg.in/yaml.v3 v3.0.1/go.mod h1:K4uyk7z7BCEPqu6E+C64Yfv1cQ7kz7rIZviUmN+EgEM=

@ -2,9 +2,12 @@ package main
import (
"os"
"os/signal"
"path/filepath"
"syscall"
api "github.com/go-skynet/LocalAI/api"
"github.com/go-skynet/LocalAI/api/options"
"github.com/go-skynet/LocalAI/internal"
model "github.com/go-skynet/LocalAI/pkg/model"
"github.com/rs/zerolog"
@ -14,6 +17,13 @@ import (
func main() {
log.Logger = log.Output(zerolog.ConsoleWriter{Out: os.Stderr})
// clean up process
go func() {
c := make(chan os.Signal, 1) // we need to reserve to buffer size 1, so the notifier are not blocked
signal.Notify(c, os.Interrupt, syscall.SIGTERM)
<-c
os.Exit(1)
}()
path, err := os.Getwd()
if err != nil {
@ -129,23 +139,23 @@ For a list of compatible model, check out: https://localai.io/model-compatibilit
Copyright: "Ettore Di Giacinto",
Action: func(ctx *cli.Context) error {
app, err := api.App(
api.WithConfigFile(ctx.String("config-file")),
api.WithJSONStringPreload(ctx.String("preload-models")),
api.WithYAMLConfigPreload(ctx.String("preload-models-config")),
api.WithModelLoader(model.NewModelLoader(ctx.String("models-path"))),
api.WithContextSize(ctx.Int("context-size")),
api.WithDebug(ctx.Bool("debug")),
api.WithImageDir(ctx.String("image-path")),
api.WithAudioDir(ctx.String("audio-path")),
api.WithF16(ctx.Bool("f16")),
api.WithStringGalleries(ctx.String("galleries")),
api.WithDisableMessage(false),
api.WithCors(ctx.Bool("cors")),
api.WithCorsAllowOrigins(ctx.String("cors-allow-origins")),
api.WithThreads(ctx.Int("threads")),
api.WithBackendAssets(backendAssets),
api.WithBackendAssetsOutput(ctx.String("backend-assets-path")),
api.WithUploadLimitMB(ctx.Int("upload-limit")))
options.WithConfigFile(ctx.String("config-file")),
options.WithJSONStringPreload(ctx.String("preload-models")),
options.WithYAMLConfigPreload(ctx.String("preload-models-config")),
options.WithModelLoader(model.NewModelLoader(ctx.String("models-path"))),
options.WithContextSize(ctx.Int("context-size")),
options.WithDebug(ctx.Bool("debug")),
options.WithImageDir(ctx.String("image-path")),
options.WithAudioDir(ctx.String("audio-path")),
options.WithF16(ctx.Bool("f16")),
options.WithStringGalleries(ctx.String("galleries")),
options.WithDisableMessage(false),
options.WithCors(ctx.Bool("cors")),
options.WithCorsAllowOrigins(ctx.String("cors-allow-origins")),
options.WithThreads(ctx.Int("threads")),
options.WithBackendAssets(backendAssets),
options.WithBackendAssetsOutput(ctx.String("backend-assets-path")),
options.WithUploadLimitMB(ctx.Int("upload-limit")))
if err != nil {
return err
}

@ -0,0 +1,42 @@
package base
// 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"
pb "github.com/go-skynet/LocalAI/pkg/grpc/proto"
"github.com/go-skynet/LocalAI/pkg/grpc/whisper/api"
)
type Base struct {
}
func (llm *Base) Load(opts *pb.ModelOptions) error {
return fmt.Errorf("unimplemented")
}
func (llm *Base) Predict(opts *pb.PredictOptions) (string, error) {
return "", fmt.Errorf("unimplemented")
}
func (llm *Base) PredictStream(opts *pb.PredictOptions, results chan string) error {
return fmt.Errorf("unimplemented")
}
func (llm *Base) Embeddings(opts *pb.PredictOptions) ([]float32, error) {
return []float32{}, fmt.Errorf("unimplemented")
}
func (llm *Base) GenerateImage(*pb.GenerateImageRequest) error {
return fmt.Errorf("unimplemented")
}
func (llm *Base) AudioTranscription(*pb.TranscriptRequest) (api.Result, error) {
return api.Result{}, fmt.Errorf("unimplemented")
}
func (llm *Base) TTS(*pb.TTSRequest) error {
return fmt.Errorf("unimplemented")
}

@ -0,0 +1,160 @@
package grpc
import (
"context"
"fmt"
"io"
"time"
pb "github.com/go-skynet/LocalAI/pkg/grpc/proto"
"github.com/go-skynet/LocalAI/pkg/grpc/whisper/api"
"google.golang.org/grpc"
"google.golang.org/grpc/credentials/insecure"
)
type Client struct {
address string
}
func NewClient(address string) *Client {
return &Client{
address: address,
}
}
func (c *Client) HealthCheck(ctx context.Context) bool {
conn, err := grpc.Dial(c.address, grpc.WithTransportCredentials(insecure.NewCredentials()))
if err != nil {
fmt.Println(err)
return false
}
defer conn.Close()
client := pb.NewBackendClient(conn)
// The healthcheck call shouldn't take long time
ctx, cancel := context.WithTimeout(ctx, 10*time.Second)
defer cancel()
res, err := client.Health(ctx, &pb.HealthMessage{})
if err != nil {
fmt.Println(err)
return false
}
if res.Message == "OK" {
return true
}
return false
}
func (c *Client) Embeddings(ctx context.Context, in *pb.PredictOptions, opts ...grpc.CallOption) (*pb.EmbeddingResult, error) {
conn, err := grpc.Dial(c.address, grpc.WithTransportCredentials(insecure.NewCredentials()))
if err != nil {
return nil, err
}
defer conn.Close()
client := pb.NewBackendClient(conn)
return client.Embedding(ctx, in, opts...)
}
func (c *Client) Predict(ctx context.Context, in *pb.PredictOptions, opts ...grpc.CallOption) (*pb.Reply, error) {
conn, err := grpc.Dial(c.address, grpc.WithTransportCredentials(insecure.NewCredentials()))
if err != nil {
return nil, err
}
defer conn.Close()
client := pb.NewBackendClient(conn)
return client.Predict(ctx, in, opts...)
}
func (c *Client) LoadModel(ctx context.Context, in *pb.ModelOptions, opts ...grpc.CallOption) (*pb.Result, error) {
conn, err := grpc.Dial(c.address, grpc.WithTransportCredentials(insecure.NewCredentials()))
if err != nil {
return nil, err
}
defer conn.Close()
client := pb.NewBackendClient(conn)
return client.LoadModel(ctx, in, opts...)
}
func (c *Client) PredictStream(ctx context.Context, in *pb.PredictOptions, f func(s string), opts ...grpc.CallOption) error {
conn, err := grpc.Dial(c.address, grpc.WithTransportCredentials(insecure.NewCredentials()))
if err != nil {
return err
}
defer conn.Close()
client := pb.NewBackendClient(conn)
stream, err := client.PredictStream(ctx, in, opts...)
if err != nil {
return err
}
for {
feature, err := stream.Recv()
if err == io.EOF {
break
}
if err != nil {
fmt.Println("Error", err)
return err
}
f(feature.GetMessage())
}
return nil
}
func (c *Client) GenerateImage(ctx context.Context, in *pb.GenerateImageRequest, opts ...grpc.CallOption) (*pb.Result, error) {
conn, err := grpc.Dial(c.address, grpc.WithTransportCredentials(insecure.NewCredentials()))
if err != nil {
return nil, err
}
defer conn.Close()
client := pb.NewBackendClient(conn)
return client.GenerateImage(ctx, in, opts...)
}
func (c *Client) TTS(ctx context.Context, in *pb.TTSRequest, opts ...grpc.CallOption) (*pb.Result, error) {
conn, err := grpc.Dial(c.address, grpc.WithTransportCredentials(insecure.NewCredentials()))
if err != nil {
return nil, err
}
defer conn.Close()
client := pb.NewBackendClient(conn)
return client.TTS(ctx, in, opts...)
}
func (c *Client) AudioTranscription(ctx context.Context, in *pb.TranscriptRequest, opts ...grpc.CallOption) (*api.Result, error) {
conn, err := grpc.Dial(c.address, grpc.WithTransportCredentials(insecure.NewCredentials()))
if err != nil {
return nil, err
}
defer conn.Close()
client := pb.NewBackendClient(conn)
res, err := client.AudioTranscription(ctx, in, opts...)
if err != nil {
return nil, err
}
tresult := &api.Result{}
for _, s := range res.Segments {
tks := []int{}
for _, t := range s.Tokens {
tks = append(tks, int(t))
}
tresult.Segments = append(tresult.Segments,
api.Segment{
Text: s.Text,
Id: int(s.Id),
Start: time.Duration(s.Start),
End: time.Duration(s.End),
Tokens: tks,
})
}
tresult.Text = res.Text
return tresult, err
}

@ -0,0 +1,33 @@
package image
// 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 (
"github.com/go-skynet/LocalAI/pkg/grpc/base"
pb "github.com/go-skynet/LocalAI/pkg/grpc/proto"
"github.com/go-skynet/LocalAI/pkg/stablediffusion"
)
type StableDiffusion struct {
base.Base
stablediffusion *stablediffusion.StableDiffusion
}
func (sd *StableDiffusion) Load(opts *pb.ModelOptions) error {
var err error
// Note: the Model here is a path to a directory containing the model files
sd.stablediffusion, err = stablediffusion.New(opts.Model)
return err
}
func (sd *StableDiffusion) GenerateImage(opts *pb.GenerateImageRequest) error {
return sd.stablediffusion.GenerateImage(
int(opts.Height),
int(opts.Width),
int(opts.Mode),
int(opts.Step),
int(opts.Seed),
opts.PositivePrompt,
opts.NegativePrompt,
opts.Dst)
}

@ -0,0 +1,16 @@
package grpc
import (
pb "github.com/go-skynet/LocalAI/pkg/grpc/proto"
"github.com/go-skynet/LocalAI/pkg/grpc/whisper/api"
)
type LLM interface {
Predict(*pb.PredictOptions) (string, error)
PredictStream(*pb.PredictOptions, chan string) error
Load(*pb.ModelOptions) error
Embeddings(*pb.PredictOptions) ([]float32, error)
GenerateImage(*pb.GenerateImageRequest) error
AudioTranscription(*pb.TranscriptRequest) (api.Result, error)
TTS(*pb.TTSRequest) error
}

@ -0,0 +1,33 @@
package bert
// 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/go-skynet/LocalAI/pkg/grpc/base"
pb "github.com/go-skynet/LocalAI/pkg/grpc/proto"
)
type Embeddings struct {
base.Base
bert *bert.Bert
}
func (llm *Embeddings) Load(opts *pb.ModelOptions) error {
model, err := bert.New(opts.Model)
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)))
}

@ -0,0 +1,59 @@
package bloomz
// 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/LocalAI/pkg/grpc/base"
pb "github.com/go-skynet/LocalAI/pkg/grpc/proto"
"github.com/go-skynet/bloomz.cpp"
)
type LLM struct {
base.Base
bloomz *bloomz.Bloomz
}
func (llm *LLM) Load(opts *pb.ModelOptions) error {
model, err := bloomz.New(opts.Model)
llm.bloomz = model
return err
}
func buildPredictOptions(opts *pb.PredictOptions) []bloomz.PredictOption {
predictOptions := []bloomz.PredictOption{
bloomz.SetTemperature(float64(opts.Temperature)),
bloomz.SetTopP(float64(opts.TopP)),
bloomz.SetTopK(int(opts.TopK)),
bloomz.SetTokens(int(opts.Tokens)),
bloomz.SetThreads(int(opts.Threads)),
}
if opts.Seed != 0 {
predictOptions = append(predictOptions, bloomz.SetSeed(int(opts.Seed)))
}
return predictOptions
}
func (llm *LLM) Predict(opts *pb.PredictOptions) (string, error) {
return llm.bloomz.Predict(opts.Prompt, buildPredictOptions(opts)...)
}
// fallback to Predict
func (llm *LLM) PredictStream(opts *pb.PredictOptions, results chan string) error {
go func() {
res, err := llm.bloomz.Predict(opts.Prompt, buildPredictOptions(opts)...)
if err != nil {
fmt.Println("err: ", err)
}
results <- res
close(results)
}()
return nil
}

@ -0,0 +1,144 @@
package falcon
// 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/LocalAI/pkg/grpc/base"
pb "github.com/go-skynet/LocalAI/pkg/grpc/proto"
ggllm "github.com/mudler/go-ggllm.cpp"
)
type LLM struct {
base.Base
falcon *ggllm.Falcon
}
func (llm *LLM) Load(opts *pb.ModelOptions) error {
ggllmOpts := []ggllm.ModelOption{}
if opts.ContextSize != 0 {
ggllmOpts = append(ggllmOpts, ggllm.SetContext(int(opts.ContextSize)))
}
// F16 doesn't seem to produce good output at all!
//if c.F16 {
// llamaOpts = append(llamaOpts, llama.EnableF16Memory)
//}
if opts.NGPULayers != 0 {
ggllmOpts = append(ggllmOpts, ggllm.SetGPULayers(int(opts.NGPULayers)))
}
ggllmOpts = append(ggllmOpts, ggllm.SetMMap(opts.MMap))
ggllmOpts = append(ggllmOpts, ggllm.SetMainGPU(opts.MainGPU))
ggllmOpts = append(ggllmOpts, ggllm.SetTensorSplit(opts.TensorSplit))
if opts.NBatch != 0 {
ggllmOpts = append(ggllmOpts, ggllm.SetNBatch(int(opts.NBatch)))
} else {
ggllmOpts = append(ggllmOpts, ggllm.SetNBatch(512))
}
model, err := ggllm.New(opts.Model, ggllmOpts...)
llm.falcon = model
return err
}
func buildPredictOptions(opts *pb.PredictOptions) []ggllm.PredictOption {
predictOptions := []ggllm.PredictOption{
ggllm.SetTemperature(float64(opts.Temperature)),
ggllm.SetTopP(float64(opts.TopP)),
ggllm.SetTopK(int(opts.TopK)),
ggllm.SetTokens(int(opts.Tokens)),
ggllm.SetThreads(int(opts.Threads)),
}
if opts.PromptCacheAll {
predictOptions = append(predictOptions, ggllm.EnablePromptCacheAll)
}
if opts.PromptCacheRO {
predictOptions = append(predictOptions, ggllm.EnablePromptCacheRO)
}
// Expected absolute path
if opts.PromptCachePath != "" {
predictOptions = append(predictOptions, ggllm.SetPathPromptCache(opts.PromptCachePath))
}
if opts.Mirostat != 0 {
predictOptions = append(predictOptions, ggllm.SetMirostat(int(opts.Mirostat)))
}
if opts.MirostatETA != 0 {
predictOptions = append(predictOptions, ggllm.SetMirostatETA(float64(opts.MirostatETA)))
}
if opts.MirostatTAU != 0 {
predictOptions = append(predictOptions, ggllm.SetMirostatTAU(float64(opts.MirostatTAU)))
}
if opts.Debug {
predictOptions = append(predictOptions, ggllm.Debug)
}
predictOptions = append(predictOptions, ggllm.SetStopWords(opts.StopPrompts...))
if opts.PresencePenalty != 0 {
predictOptions = append(predictOptions, ggllm.SetPenalty(float64(opts.PresencePenalty)))
}
if opts.NKeep != 0 {
predictOptions = append(predictOptions, ggllm.SetNKeep(int(opts.NKeep)))
}
if opts.Batch != 0 {
predictOptions = append(predictOptions, ggllm.SetBatch(int(opts.Batch)))
}
if opts.IgnoreEOS {
predictOptions = append(predictOptions, ggllm.IgnoreEOS)
}
if opts.Seed != 0 {
predictOptions = append(predictOptions, ggllm.SetSeed(int(opts.Seed)))
}
//predictOptions = append(predictOptions, llama.SetLogitBias(c.Seed))
predictOptions = append(predictOptions, ggllm.SetFrequencyPenalty(float64(opts.FrequencyPenalty)))
predictOptions = append(predictOptions, ggllm.SetMlock(opts.MLock))
predictOptions = append(predictOptions, ggllm.SetMemoryMap(opts.MMap))
predictOptions = append(predictOptions, ggllm.SetPredictionMainGPU(opts.MainGPU))
predictOptions = append(predictOptions, ggllm.SetPredictionTensorSplit(opts.TensorSplit))
predictOptions = append(predictOptions, ggllm.SetTailFreeSamplingZ(float64(opts.TailFreeSamplingZ)))
predictOptions = append(predictOptions, ggllm.SetTypicalP(float64(opts.TypicalP)))
return predictOptions
}
func (llm *LLM) Predict(opts *pb.PredictOptions) (string, error) {
return llm.falcon.Predict(opts.Prompt, buildPredictOptions(opts)...)
}
func (llm *LLM) PredictStream(opts *pb.PredictOptions, results chan string) error {
predictOptions := buildPredictOptions(opts)
predictOptions = append(predictOptions, ggllm.SetTokenCallback(func(token string) bool {
if token == "<|endoftext|>" {
return true
}
results <- token
return true
}))
go func() {
_, err := llm.falcon.Predict(opts.Prompt, predictOptions...)
if err != nil {
fmt.Println("err: ", err)
}
close(results)
}()
return nil
}

@ -0,0 +1,62 @@
package gpt4all
// 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/LocalAI/pkg/grpc/base"
pb "github.com/go-skynet/LocalAI/pkg/grpc/proto"
gpt4all "github.com/nomic-ai/gpt4all/gpt4all-bindings/golang"
)
type LLM struct {
base.Base
gpt4all *gpt4all.Model
}
func (llm *LLM) Load(opts *pb.ModelOptions) error {
model, err := gpt4all.New(opts.Model,
gpt4all.SetThreads(int(opts.Threads)),
gpt4all.SetLibrarySearchPath(opts.LibrarySearchPath))
llm.gpt4all = model
return err
}
func buildPredictOptions(opts *pb.PredictOptions) []gpt4all.PredictOption {
predictOptions := []gpt4all.PredictOption{
gpt4all.SetTemperature(float64(opts.Temperature)),
gpt4all.SetTopP(float64(opts.TopP)),
gpt4all.SetTopK(int(opts.TopK)),
gpt4all.SetTokens(int(opts.Tokens)),
}
if opts.Batch != 0 {
predictOptions = append(predictOptions, gpt4all.SetBatch(int(opts.Batch)))
}
return predictOptions
}
func (llm *LLM) Predict(opts *pb.PredictOptions) (string, error) {
return llm.gpt4all.Predict(opts.Prompt, buildPredictOptions(opts)...)
}
func (llm *LLM) PredictStream(opts *pb.PredictOptions, results chan string) error {
predictOptions := buildPredictOptions(opts)
go func() {
llm.gpt4all.SetTokenCallback(func(token string) bool {
results <- token
return true
})
_, err := llm.gpt4all.Predict(opts.Prompt, predictOptions...)
if err != nil {
fmt.Println("err: ", err)
}
llm.gpt4all.SetTokenCallback(nil)
close(results)
}()
return nil
}

@ -0,0 +1,58 @@
package langchain
// 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/LocalAI/pkg/grpc/base"
pb "github.com/go-skynet/LocalAI/pkg/grpc/proto"
"github.com/go-skynet/LocalAI/pkg/langchain"
)
type LLM struct {
base.Base
langchain *langchain.HuggingFace
model string
}
func (llm *LLM) Load(opts *pb.ModelOptions) error {
llm.langchain, _ = langchain.NewHuggingFace(opts.Model)
llm.model = opts.Model
return nil
}
func (llm *LLM) Predict(opts *pb.PredictOptions) (string, error) {
o := []langchain.PredictOption{
langchain.SetModel(llm.model),
langchain.SetMaxTokens(int(opts.Tokens)),
langchain.SetTemperature(float64(opts.Temperature)),
langchain.SetStopWords(opts.StopPrompts),
}
pred, err := llm.langchain.PredictHuggingFace(opts.Prompt, o...)
if err != nil {
return "", err
}
return pred.Completion, nil
}
func (llm *LLM) PredictStream(opts *pb.PredictOptions, results chan string) error {
o := []langchain.PredictOption{
langchain.SetModel(llm.model),
langchain.SetMaxTokens(int(opts.Tokens)),
langchain.SetTemperature(float64(opts.Temperature)),
langchain.SetStopWords(opts.StopPrompts),
}
go func() {
res, err := llm.langchain.PredictHuggingFace(opts.Prompt, o...)
if err != nil {
fmt.Println("err: ", err)
}
results <- res.Completion
close(results)
}()
return nil
}

@ -0,0 +1,170 @@
package llama
// 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/LocalAI/pkg/grpc/base"
pb "github.com/go-skynet/LocalAI/pkg/grpc/proto"
"github.com/go-skynet/go-llama.cpp"
)
type LLM struct {
base.Base
llama *llama.LLama
}
func (llm *LLM) Load(opts *pb.ModelOptions) error {
llamaOpts := []llama.ModelOption{}
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.Model, llamaOpts...)
llm.llama = model
return err
}
func buildPredictOptions(opts *pb.PredictOptions) []llama.PredictOption {
predictOptions := []llama.PredictOption{
llama.SetTemperature(float64(opts.Temperature)),
llama.SetTopP(float64(opts.TopP)),
llama.SetTopK(int(opts.TopK)),
llama.SetTokens(int(opts.Tokens)),
llama.SetThreads(int(opts.Threads)),
}
if opts.PromptCacheAll {
predictOptions = append(predictOptions, llama.EnablePromptCacheAll)
}
if opts.PromptCacheRO {
predictOptions = append(predictOptions, llama.EnablePromptCacheRO)
}
predictOptions = append(predictOptions, llama.WithGrammar(opts.Grammar))
// 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(float64(opts.MirostatETA)))
}
if opts.MirostatTAU != 0 {
predictOptions = append(predictOptions, llama.SetMirostatTAU(float64(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(float64(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(float64(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(float64(opts.TailFreeSamplingZ)))
predictOptions = append(predictOptions, llama.SetTypicalP(float64(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...)
}

@ -0,0 +1,71 @@
package rwkv
// 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"
"path/filepath"
"github.com/donomii/go-rwkv.cpp"
"github.com/go-skynet/LocalAI/pkg/grpc/base"
pb "github.com/go-skynet/LocalAI/pkg/grpc/proto"
)
const tokenizerSuffix = ".tokenizer.json"
type LLM struct {
base.Base
rwkv *rwkv.RwkvState
}
func (llm *LLM) Load(opts *pb.ModelOptions) error {
modelPath := filepath.Dir(opts.Model)
modelFile := filepath.Base(opts.Model)
model := rwkv.LoadFiles(opts.Model, filepath.Join(modelPath, modelFile+tokenizerSuffix), uint32(opts.GetThreads()))
if model == nil {
return fmt.Errorf("could not load model")
}
llm.rwkv = model
return nil
}
func (llm *LLM) Predict(opts *pb.PredictOptions) (string, error) {
stopWord := "\n"
if len(opts.StopPrompts) > 0 {
stopWord = opts.StopPrompts[0]
}
if err := llm.rwkv.ProcessInput(opts.Prompt); err != nil {
return "", err
}
response := llm.rwkv.GenerateResponse(int(opts.Tokens), stopWord, float32(opts.Temperature), float32(opts.TopP), nil)
return response, nil
}
func (llm *LLM) PredictStream(opts *pb.PredictOptions, results chan string) error {
go func() {
stopWord := "\n"
if len(opts.StopPrompts) > 0 {
stopWord = opts.StopPrompts[0]
}
if err := llm.rwkv.ProcessInput(opts.Prompt); err != nil {
fmt.Println("Error processing input: ", err)
return
}
llm.rwkv.GenerateResponse(int(opts.Tokens), stopWord, float32(opts.Temperature), float32(opts.TopP), func(s string) bool {
results <- s
return true
})
close(results)
}()
return nil
}

@ -0,0 +1,43 @@
package transformers
// 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/LocalAI/pkg/grpc/base"
pb "github.com/go-skynet/LocalAI/pkg/grpc/proto"
transformers "github.com/go-skynet/go-ggml-transformers.cpp"
)
type Dolly struct {
base.Base
dolly *transformers.Dolly
}
func (llm *Dolly) Load(opts *pb.ModelOptions) error {
model, err := transformers.NewDolly(opts.Model)
llm.dolly = model
return err
}
func (llm *Dolly) Predict(opts *pb.PredictOptions) (string, error) {
return llm.dolly.Predict(opts.Prompt, buildPredictOptions(opts)...)
}
// fallback to Predict
func (llm *Dolly) PredictStream(opts *pb.PredictOptions, results chan string) error {
go func() {
res, err := llm.dolly.Predict(opts.Prompt, buildPredictOptions(opts)...)
if err != nil {
fmt.Println("err: ", err)
}
results <- res
close(results)
}()
return nil
}

@ -0,0 +1,43 @@
package transformers
// 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/LocalAI/pkg/grpc/base"
pb "github.com/go-skynet/LocalAI/pkg/grpc/proto"
transformers "github.com/go-skynet/go-ggml-transformers.cpp"
)
type Falcon struct {
base.Base
falcon *transformers.Falcon
}
func (llm *Falcon) Load(opts *pb.ModelOptions) error {
model, err := transformers.NewFalcon(opts.Model)
llm.falcon = model
return err
}
func (llm *Falcon) Predict(opts *pb.PredictOptions) (string, error) {
return llm.falcon.Predict(opts.Prompt, buildPredictOptions(opts)...)
}
// fallback to Predict
func (llm *Falcon) PredictStream(opts *pb.PredictOptions, results chan string) error {
go func() {
res, err := llm.falcon.Predict(opts.Prompt, buildPredictOptions(opts)...)
if err != nil {
fmt.Println("err: ", err)
}
results <- res
close(results)
}()
return nil
}

@ -0,0 +1,42 @@
package transformers
// 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/LocalAI/pkg/grpc/base"
pb "github.com/go-skynet/LocalAI/pkg/grpc/proto"
transformers "github.com/go-skynet/go-ggml-transformers.cpp"
)
type GPT2 struct {
base.Base
gpt2 *transformers.GPT2
}
func (llm *GPT2) Load(opts *pb.ModelOptions) error {
model, err := transformers.New(opts.Model)
llm.gpt2 = model
return err
}
func (llm *GPT2) Predict(opts *pb.PredictOptions) (string, error) {
return llm.gpt2.Predict(opts.Prompt, buildPredictOptions(opts)...)
}
// fallback to Predict
func (llm *GPT2) PredictStream(opts *pb.PredictOptions, results chan string) error {
go func() {
res, err := llm.gpt2.Predict(opts.Prompt, buildPredictOptions(opts)...)
if err != nil {
fmt.Println("err: ", err)
}
results <- res
close(results)
}()
return nil
}

@ -0,0 +1,42 @@
package transformers
// 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/LocalAI/pkg/grpc/base"
pb "github.com/go-skynet/LocalAI/pkg/grpc/proto"
transformers "github.com/go-skynet/go-ggml-transformers.cpp"
)
type GPTJ struct {
base.Base
gptj *transformers.GPTJ
}
func (llm *GPTJ) Load(opts *pb.ModelOptions) error {
model, err := transformers.NewGPTJ(opts.Model)
llm.gptj = model
return err
}
func (llm *GPTJ) Predict(opts *pb.PredictOptions) (string, error) {
return llm.gptj.Predict(opts.Prompt, buildPredictOptions(opts)...)
}
// fallback to Predict
func (llm *GPTJ) PredictStream(opts *pb.PredictOptions, results chan string) error {
go func() {
res, err := llm.gptj.Predict(opts.Prompt, buildPredictOptions(opts)...)
if err != nil {
fmt.Println("err: ", err)
}
results <- res
close(results)
}()
return nil
}

@ -0,0 +1,42 @@
package transformers
// 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/LocalAI/pkg/grpc/base"
pb "github.com/go-skynet/LocalAI/pkg/grpc/proto"
transformers "github.com/go-skynet/go-ggml-transformers.cpp"
)
type GPTNeoX struct {
base.Base
gptneox *transformers.GPTNeoX
}
func (llm *GPTNeoX) Load(opts *pb.ModelOptions) error {
model, err := transformers.NewGPTNeoX(opts.Model)
llm.gptneox = model
return err
}
func (llm *GPTNeoX) Predict(opts *pb.PredictOptions) (string, error) {
return llm.gptneox.Predict(opts.Prompt, buildPredictOptions(opts)...)
}
// fallback to Predict
func (llm *GPTNeoX) PredictStream(opts *pb.PredictOptions, results chan string) error {
go func() {
res, err := llm.gptneox.Predict(opts.Prompt, buildPredictOptions(opts)...)
if err != nil {
fmt.Println("err: ", err)
}
results <- res
close(results)
}()
return nil
}

@ -0,0 +1,42 @@
package transformers
// 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/LocalAI/pkg/grpc/base"
pb "github.com/go-skynet/LocalAI/pkg/grpc/proto"
transformers "github.com/go-skynet/go-ggml-transformers.cpp"
)
type MPT struct {
base.Base
mpt *transformers.MPT
}
func (llm *MPT) Load(opts *pb.ModelOptions) error {
model, err := transformers.NewMPT(opts.Model)
llm.mpt = model
return err
}
func (llm *MPT) Predict(opts *pb.PredictOptions) (string, error) {
return llm.mpt.Predict(opts.Prompt, buildPredictOptions(opts)...)
}
// fallback to Predict
func (llm *MPT) PredictStream(opts *pb.PredictOptions, results chan string) error {
go func() {
res, err := llm.mpt.Predict(opts.Prompt, buildPredictOptions(opts)...)
if err != nil {
fmt.Println("err: ", err)
}
results <- res
close(results)
}()
return nil
}

@ -0,0 +1,26 @@
package transformers
import (
pb "github.com/go-skynet/LocalAI/pkg/grpc/proto"
transformers "github.com/go-skynet/go-ggml-transformers.cpp"
)
func buildPredictOptions(opts *pb.PredictOptions) []transformers.PredictOption {
predictOptions := []transformers.PredictOption{
transformers.SetTemperature(float64(opts.Temperature)),
transformers.SetTopP(float64(opts.TopP)),
transformers.SetTopK(int(opts.TopK)),
transformers.SetTokens(int(opts.Tokens)),
transformers.SetThreads(int(opts.Threads)),
}
if opts.Batch != 0 {
predictOptions = append(predictOptions, transformers.SetBatch(int(opts.Batch)))
}
if opts.Seed != 0 {
predictOptions = append(predictOptions, transformers.SetSeed(int(opts.Seed)))
}
return predictOptions
}

@ -0,0 +1,42 @@
package transformers
// 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/LocalAI/pkg/grpc/base"
pb "github.com/go-skynet/LocalAI/pkg/grpc/proto"
transformers "github.com/go-skynet/go-ggml-transformers.cpp"
)
type Replit struct {
base.Base
replit *transformers.Replit
}
func (llm *Replit) Load(opts *pb.ModelOptions) error {
model, err := transformers.NewReplit(opts.Model)
llm.replit = model
return err
}
func (llm *Replit) Predict(opts *pb.PredictOptions) (string, error) {
return llm.replit.Predict(opts.Prompt, buildPredictOptions(opts)...)
}
// fallback to Predict
func (llm *Replit) PredictStream(opts *pb.PredictOptions, results chan string) error {
go func() {
res, err := llm.replit.Predict(opts.Prompt, buildPredictOptions(opts)...)
if err != nil {
fmt.Println("err: ", err)
}
results <- res
close(results)
}()
return nil
}

@ -0,0 +1,43 @@
package transformers
// 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/LocalAI/pkg/grpc/base"
pb "github.com/go-skynet/LocalAI/pkg/grpc/proto"
transformers "github.com/go-skynet/go-ggml-transformers.cpp"
)
type Starcoder struct {
base.Base
starcoder *transformers.Starcoder
}
func (llm *Starcoder) Load(opts *pb.ModelOptions) error {
model, err := transformers.NewStarcoder(opts.Model)
llm.starcoder = model
return err
}
func (llm *Starcoder) Predict(opts *pb.PredictOptions) (string, error) {
return llm.starcoder.Predict(opts.Prompt, buildPredictOptions(opts)...)
}
// fallback to Predict
func (llm *Starcoder) PredictStream(opts *pb.PredictOptions, results chan string) error {
go func() {
res, err := llm.starcoder.Predict(opts.Prompt, buildPredictOptions(opts)...)
if err != nil {
fmt.Println("err: ", err)
}
results <- res
close(results)
}()
return nil
}

File diff suppressed because it is too large Load Diff

@ -0,0 +1,129 @@
syntax = "proto3";
option go_package = "github.com/go-skynet/LocalAI/pkg/grpc/proto";
option java_multiple_files = true;
option java_package = "io.skynet.localai.backend";
option java_outer_classname = "LocalAIBackend";
package backend;
service Backend {
rpc Health(HealthMessage) returns (Reply) {}
rpc Predict(PredictOptions) returns (Reply) {}
rpc LoadModel(ModelOptions) returns (Result) {}
rpc PredictStream(PredictOptions) returns (stream Reply) {}
rpc Embedding(PredictOptions) returns (EmbeddingResult) {}
rpc GenerateImage(GenerateImageRequest) returns (Result) {}
rpc AudioTranscription(TranscriptRequest) returns (TranscriptResult) {}
rpc TTS(TTSRequest) returns (Result) {}
}
message HealthMessage {}
// The request message containing the user's name.
message PredictOptions {
string Prompt = 1;
int32 Seed = 2;
int32 Threads = 3;
int32 Tokens = 4;
int32 TopK = 5;
int32 Repeat = 6;
int32 Batch = 7;
int32 NKeep = 8;
float Temperature = 9;
float Penalty = 10;
bool F16KV = 11;
bool DebugMode = 12;
repeated string StopPrompts = 13;
bool IgnoreEOS = 14;
float TailFreeSamplingZ = 15;
float TypicalP = 16;
float FrequencyPenalty = 17;
float PresencePenalty = 18;
int32 Mirostat = 19;
float MirostatETA = 20;
float MirostatTAU = 21;
bool PenalizeNL = 22;
string LogitBias = 23;
bool MLock = 25;
bool MMap = 26;
bool PromptCacheAll = 27;
bool PromptCacheRO = 28;
string Grammar = 29;
string MainGPU = 30;
string TensorSplit = 31;
float TopP = 32;
string PromptCachePath = 33;
bool Debug = 34;
repeated int32 EmbeddingTokens = 35;
string Embeddings = 36;
}
// The response message containing the result
message Reply {
string message = 1;
}
message ModelOptions {
string Model = 1;
int32 ContextSize = 2;
int32 Seed = 3;
int32 NBatch = 4;
bool F16Memory = 5;
bool MLock = 6;
bool MMap = 7;
bool VocabOnly = 8;
bool LowVRAM = 9;
bool Embeddings = 10;
bool NUMA = 11;
int32 NGPULayers = 12;
string MainGPU = 13;
string TensorSplit = 14;
int32 Threads = 15;
string LibrarySearchPath = 16;
}
message Result {
string message = 1;
bool success = 2;
}
message EmbeddingResult {
repeated float embeddings = 1;
}
message TranscriptRequest {
string dst = 2;
string language = 3;
uint32 threads = 4;
}
message TranscriptResult {
repeated TranscriptSegment segments = 1;
string text = 2;
}
message TranscriptSegment {
int32 id = 1;
int64 start = 2;
int64 end = 3;
string text = 4;
repeated int32 tokens = 5;
}
message GenerateImageRequest {
int32 height = 1;
int32 width = 2;
int32 mode = 3;
int32 step = 4;
int32 seed = 5;
string positive_prompt = 6;
string negative_prompt = 7;
string dst = 8;
}
message TTSRequest {
string text = 1;
string model = 2;
string dst = 3;
}

@ -0,0 +1,385 @@
// Code generated by protoc-gen-go-grpc. DO NOT EDIT.
// versions:
// - protoc-gen-go-grpc v1.2.0
// - protoc v3.15.8
// source: pkg/grpc/proto/backend.proto
package proto
import (
context "context"
grpc "google.golang.org/grpc"
codes "google.golang.org/grpc/codes"
status "google.golang.org/grpc/status"
)
// This is a compile-time assertion to ensure that this generated file
// is compatible with the grpc package it is being compiled against.
// Requires gRPC-Go v1.32.0 or later.
const _ = grpc.SupportPackageIsVersion7
// BackendClient is the client API for Backend service.
//
// For semantics around ctx use and closing/ending streaming RPCs, please refer to https://pkg.go.dev/google.golang.org/grpc/?tab=doc#ClientConn.NewStream.
type BackendClient interface {
Health(ctx context.Context, in *HealthMessage, opts ...grpc.CallOption) (*Reply, error)
Predict(ctx context.Context, in *PredictOptions, opts ...grpc.CallOption) (*Reply, error)
LoadModel(ctx context.Context, in *ModelOptions, opts ...grpc.CallOption) (*Result, error)
PredictStream(ctx context.Context, in *PredictOptions, opts ...grpc.CallOption) (Backend_PredictStreamClient, error)
Embedding(ctx context.Context, in *PredictOptions, opts ...grpc.CallOption) (*EmbeddingResult, error)
GenerateImage(ctx context.Context, in *GenerateImageRequest, opts ...grpc.CallOption) (*Result, error)
AudioTranscription(ctx context.Context, in *TranscriptRequest, opts ...grpc.CallOption) (*TranscriptResult, error)
TTS(ctx context.Context, in *TTSRequest, opts ...grpc.CallOption) (*Result, error)
}
type backendClient struct {
cc grpc.ClientConnInterface
}
func NewBackendClient(cc grpc.ClientConnInterface) BackendClient {
return &backendClient{cc}
}
func (c *backendClient) Health(ctx context.Context, in *HealthMessage, opts ...grpc.CallOption) (*Reply, error) {
out := new(Reply)
err := c.cc.Invoke(ctx, "/backend.Backend/Health", in, out, opts...)
if err != nil {
return nil, err
}
return out, nil
}
func (c *backendClient) Predict(ctx context.Context, in *PredictOptions, opts ...grpc.CallOption) (*Reply, error) {
out := new(Reply)
err := c.cc.Invoke(ctx, "/backend.Backend/Predict", in, out, opts...)
if err != nil {
return nil, err
}
return out, nil
}
func (c *backendClient) LoadModel(ctx context.Context, in *ModelOptions, opts ...grpc.CallOption) (*Result, error) {
out := new(Result)
err := c.cc.Invoke(ctx, "/backend.Backend/LoadModel", in, out, opts...)
if err != nil {
return nil, err
}
return out, nil
}
func (c *backendClient) PredictStream(ctx context.Context, in *PredictOptions, opts ...grpc.CallOption) (Backend_PredictStreamClient, error) {
stream, err := c.cc.NewStream(ctx, &Backend_ServiceDesc.Streams[0], "/backend.Backend/PredictStream", opts...)
if err != nil {
return nil, err
}
x := &backendPredictStreamClient{stream}
if err := x.ClientStream.SendMsg(in); err != nil {
return nil, err
}
if err := x.ClientStream.CloseSend(); err != nil {
return nil, err
}
return x, nil
}
type Backend_PredictStreamClient interface {
Recv() (*Reply, error)
grpc.ClientStream
}
type backendPredictStreamClient struct {
grpc.ClientStream
}
func (x *backendPredictStreamClient) Recv() (*Reply, error) {
m := new(Reply)
if err := x.ClientStream.RecvMsg(m); err != nil {
return nil, err
}
return m, nil
}
func (c *backendClient) Embedding(ctx context.Context, in *PredictOptions, opts ...grpc.CallOption) (*EmbeddingResult, error) {
out := new(EmbeddingResult)
err := c.cc.Invoke(ctx, "/backend.Backend/Embedding", in, out, opts...)
if err != nil {
return nil, err
}
return out, nil
}
func (c *backendClient) GenerateImage(ctx context.Context, in *GenerateImageRequest, opts ...grpc.CallOption) (*Result, error) {
out := new(Result)
err := c.cc.Invoke(ctx, "/backend.Backend/GenerateImage", in, out, opts...)
if err != nil {
return nil, err
}
return out, nil
}
func (c *backendClient) AudioTranscription(ctx context.Context, in *TranscriptRequest, opts ...grpc.CallOption) (*TranscriptResult, error) {
out := new(TranscriptResult)
err := c.cc.Invoke(ctx, "/backend.Backend/AudioTranscription", in, out, opts...)
if err != nil {
return nil, err
}
return out, nil
}
func (c *backendClient) TTS(ctx context.Context, in *TTSRequest, opts ...grpc.CallOption) (*Result, error) {
out := new(Result)
err := c.cc.Invoke(ctx, "/backend.Backend/TTS", in, out, opts...)
if err != nil {
return nil, err
}
return out, nil
}
// BackendServer is the server API for Backend service.
// All implementations must embed UnimplementedBackendServer
// for forward compatibility
type BackendServer interface {
Health(context.Context, *HealthMessage) (*Reply, error)
Predict(context.Context, *PredictOptions) (*Reply, error)
LoadModel(context.Context, *ModelOptions) (*Result, error)
PredictStream(*PredictOptions, Backend_PredictStreamServer) error
Embedding(context.Context, *PredictOptions) (*EmbeddingResult, error)
GenerateImage(context.Context, *GenerateImageRequest) (*Result, error)
AudioTranscription(context.Context, *TranscriptRequest) (*TranscriptResult, error)
TTS(context.Context, *TTSRequest) (*Result, error)
mustEmbedUnimplementedBackendServer()
}
// UnimplementedBackendServer must be embedded to have forward compatible implementations.
type UnimplementedBackendServer struct {
}
func (UnimplementedBackendServer) Health(context.Context, *HealthMessage) (*Reply, error) {
return nil, status.Errorf(codes.Unimplemented, "method Health not implemented")
}
func (UnimplementedBackendServer) Predict(context.Context, *PredictOptions) (*Reply, error) {
return nil, status.Errorf(codes.Unimplemented, "method Predict not implemented")
}
func (UnimplementedBackendServer) LoadModel(context.Context, *ModelOptions) (*Result, error) {
return nil, status.Errorf(codes.Unimplemented, "method LoadModel not implemented")
}
func (UnimplementedBackendServer) PredictStream(*PredictOptions, Backend_PredictStreamServer) error {
return status.Errorf(codes.Unimplemented, "method PredictStream not implemented")
}
func (UnimplementedBackendServer) Embedding(context.Context, *PredictOptions) (*EmbeddingResult, error) {
return nil, status.Errorf(codes.Unimplemented, "method Embedding not implemented")
}
func (UnimplementedBackendServer) GenerateImage(context.Context, *GenerateImageRequest) (*Result, error) {
return nil, status.Errorf(codes.Unimplemented, "method GenerateImage not implemented")
}
func (UnimplementedBackendServer) AudioTranscription(context.Context, *TranscriptRequest) (*TranscriptResult, error) {
return nil, status.Errorf(codes.Unimplemented, "method AudioTranscription not implemented")
}
func (UnimplementedBackendServer) TTS(context.Context, *TTSRequest) (*Result, error) {
return nil, status.Errorf(codes.Unimplemented, "method TTS not implemented")
}
func (UnimplementedBackendServer) mustEmbedUnimplementedBackendServer() {}
// UnsafeBackendServer may be embedded to opt out of forward compatibility for this service.
// Use of this interface is not recommended, as added methods to BackendServer will
// result in compilation errors.
type UnsafeBackendServer interface {
mustEmbedUnimplementedBackendServer()
}
func RegisterBackendServer(s grpc.ServiceRegistrar, srv BackendServer) {
s.RegisterService(&Backend_ServiceDesc, srv)
}
func _Backend_Health_Handler(srv interface{}, ctx context.Context, dec func(interface{}) error, interceptor grpc.UnaryServerInterceptor) (interface{}, error) {
in := new(HealthMessage)
if err := dec(in); err != nil {
return nil, err
}
if interceptor == nil {
return srv.(BackendServer).Health(ctx, in)
}
info := &grpc.UnaryServerInfo{
Server: srv,
FullMethod: "/backend.Backend/Health",
}
handler := func(ctx context.Context, req interface{}) (interface{}, error) {
return srv.(BackendServer).Health(ctx, req.(*HealthMessage))
}
return interceptor(ctx, in, info, handler)
}
func _Backend_Predict_Handler(srv interface{}, ctx context.Context, dec func(interface{}) error, interceptor grpc.UnaryServerInterceptor) (interface{}, error) {
in := new(PredictOptions)
if err := dec(in); err != nil {
return nil, err
}
if interceptor == nil {
return srv.(BackendServer).Predict(ctx, in)
}
info := &grpc.UnaryServerInfo{
Server: srv,
FullMethod: "/backend.Backend/Predict",
}
handler := func(ctx context.Context, req interface{}) (interface{}, error) {
return srv.(BackendServer).Predict(ctx, req.(*PredictOptions))
}
return interceptor(ctx, in, info, handler)
}
func _Backend_LoadModel_Handler(srv interface{}, ctx context.Context, dec func(interface{}) error, interceptor grpc.UnaryServerInterceptor) (interface{}, error) {
in := new(ModelOptions)
if err := dec(in); err != nil {
return nil, err
}
if interceptor == nil {
return srv.(BackendServer).LoadModel(ctx, in)
}
info := &grpc.UnaryServerInfo{
Server: srv,
FullMethod: "/backend.Backend/LoadModel",
}
handler := func(ctx context.Context, req interface{}) (interface{}, error) {
return srv.(BackendServer).LoadModel(ctx, req.(*ModelOptions))
}
return interceptor(ctx, in, info, handler)
}
func _Backend_PredictStream_Handler(srv interface{}, stream grpc.ServerStream) error {
m := new(PredictOptions)
if err := stream.RecvMsg(m); err != nil {
return err
}
return srv.(BackendServer).PredictStream(m, &backendPredictStreamServer{stream})
}
type Backend_PredictStreamServer interface {
Send(*Reply) error
grpc.ServerStream
}
type backendPredictStreamServer struct {
grpc.ServerStream
}
func (x *backendPredictStreamServer) Send(m *Reply) error {
return x.ServerStream.SendMsg(m)
}
func _Backend_Embedding_Handler(srv interface{}, ctx context.Context, dec func(interface{}) error, interceptor grpc.UnaryServerInterceptor) (interface{}, error) {
in := new(PredictOptions)
if err := dec(in); err != nil {
return nil, err
}
if interceptor == nil {
return srv.(BackendServer).Embedding(ctx, in)
}
info := &grpc.UnaryServerInfo{
Server: srv,
FullMethod: "/backend.Backend/Embedding",
}
handler := func(ctx context.Context, req interface{}) (interface{}, error) {
return srv.(BackendServer).Embedding(ctx, req.(*PredictOptions))
}
return interceptor(ctx, in, info, handler)
}
func _Backend_GenerateImage_Handler(srv interface{}, ctx context.Context, dec func(interface{}) error, interceptor grpc.UnaryServerInterceptor) (interface{}, error) {
in := new(GenerateImageRequest)
if err := dec(in); err != nil {
return nil, err
}
if interceptor == nil {
return srv.(BackendServer).GenerateImage(ctx, in)
}
info := &grpc.UnaryServerInfo{
Server: srv,
FullMethod: "/backend.Backend/GenerateImage",
}
handler := func(ctx context.Context, req interface{}) (interface{}, error) {
return srv.(BackendServer).GenerateImage(ctx, req.(*GenerateImageRequest))
}
return interceptor(ctx, in, info, handler)
}
func _Backend_AudioTranscription_Handler(srv interface{}, ctx context.Context, dec func(interface{}) error, interceptor grpc.UnaryServerInterceptor) (interface{}, error) {
in := new(TranscriptRequest)
if err := dec(in); err != nil {
return nil, err
}
if interceptor == nil {
return srv.(BackendServer).AudioTranscription(ctx, in)
}
info := &grpc.UnaryServerInfo{
Server: srv,
FullMethod: "/backend.Backend/AudioTranscription",
}
handler := func(ctx context.Context, req interface{}) (interface{}, error) {
return srv.(BackendServer).AudioTranscription(ctx, req.(*TranscriptRequest))
}
return interceptor(ctx, in, info, handler)
}
func _Backend_TTS_Handler(srv interface{}, ctx context.Context, dec func(interface{}) error, interceptor grpc.UnaryServerInterceptor) (interface{}, error) {
in := new(TTSRequest)
if err := dec(in); err != nil {
return nil, err
}
if interceptor == nil {
return srv.(BackendServer).TTS(ctx, in)
}
info := &grpc.UnaryServerInfo{
Server: srv,
FullMethod: "/backend.Backend/TTS",
}
handler := func(ctx context.Context, req interface{}) (interface{}, error) {
return srv.(BackendServer).TTS(ctx, req.(*TTSRequest))
}
return interceptor(ctx, in, info, handler)
}
// Backend_ServiceDesc is the grpc.ServiceDesc for Backend service.
// It's only intended for direct use with grpc.RegisterService,
// and not to be introspected or modified (even as a copy)
var Backend_ServiceDesc = grpc.ServiceDesc{
ServiceName: "backend.Backend",
HandlerType: (*BackendServer)(nil),
Methods: []grpc.MethodDesc{
{
MethodName: "Health",
Handler: _Backend_Health_Handler,
},
{
MethodName: "Predict",
Handler: _Backend_Predict_Handler,
},
{
MethodName: "LoadModel",
Handler: _Backend_LoadModel_Handler,
},
{
MethodName: "Embedding",
Handler: _Backend_Embedding_Handler,
},
{
MethodName: "GenerateImage",
Handler: _Backend_GenerateImage_Handler,
},
{
MethodName: "AudioTranscription",
Handler: _Backend_AudioTranscription_Handler,
},
{
MethodName: "TTS",
Handler: _Backend_TTS_Handler,
},
},
Streams: []grpc.StreamDesc{
{
StreamName: "PredictStream",
Handler: _Backend_PredictStream_Handler,
ServerStreams: true,
},
},
Metadata: "pkg/grpc/proto/backend.proto",
}

@ -0,0 +1,126 @@
package grpc
import (
"context"
"fmt"
"log"
"net"
pb "github.com/go-skynet/LocalAI/pkg/grpc/proto"
"google.golang.org/grpc"
)
// A GRPC Server that allows to run LLM inference.
// It is used by the LLMServices to expose the LLM functionalities that are called by the client.
// The GRPC Service is general, trying to encompass all the possible LLM options models.
// It depends on the real implementer then what can be done or not.
//
// The server is implemented as a GRPC service, with the following methods:
// - Predict: to run the inference with options
// - PredictStream: to run the inference with options and stream the results
// server is used to implement helloworld.GreeterServer.
type server struct {
pb.UnimplementedBackendServer
llm LLM
}
func (s *server) Health(ctx context.Context, in *pb.HealthMessage) (*pb.Reply, error) {
return &pb.Reply{Message: "OK"}, nil
}
func (s *server) Embedding(ctx context.Context, in *pb.PredictOptions) (*pb.EmbeddingResult, error) {
embeds, err := s.llm.Embeddings(in)
if err != nil {
return nil, err
}
return &pb.EmbeddingResult{Embeddings: embeds}, nil
}
func (s *server) LoadModel(ctx context.Context, in *pb.ModelOptions) (*pb.Result, error) {
err := s.llm.Load(in)
if err != nil {
return &pb.Result{Message: fmt.Sprintf("Error loading model: %s", err.Error()), Success: false}, err
}
return &pb.Result{Message: "Loading succeeded", Success: true}, nil
}
func (s *server) Predict(ctx context.Context, in *pb.PredictOptions) (*pb.Reply, error) {
result, err := s.llm.Predict(in)
return &pb.Reply{Message: result}, err
}
func (s *server) GenerateImage(ctx context.Context, in *pb.GenerateImageRequest) (*pb.Result, error) {
err := s.llm.GenerateImage(in)
if err != nil {
return &pb.Result{Message: fmt.Sprintf("Error generating image: %s", err.Error()), Success: false}, err
}
return &pb.Result{Message: "Image generated", Success: true}, nil
}
func (s *server) TTS(ctx context.Context, in *pb.TTSRequest) (*pb.Result, error) {
err := s.llm.TTS(in)
if err != nil {
return &pb.Result{Message: fmt.Sprintf("Error generating audio: %s", err.Error()), Success: false}, err
}
return &pb.Result{Message: "Audio generated", Success: true}, nil
}
func (s *server) AudioTranscription(ctx context.Context, in *pb.TranscriptRequest) (*pb.TranscriptResult, error) {
result, err := s.llm.AudioTranscription(in)
if err != nil {
return nil, err
}
tresult := &pb.TranscriptResult{}
for _, s := range result.Segments {
tks := []int32{}
for _, t := range s.Tokens {
tks = append(tks, int32(t))
}
tresult.Segments = append(tresult.Segments,
&pb.TranscriptSegment{
Text: s.Text,
Id: int32(s.Id),
Start: int64(s.Start),
End: int64(s.End),
Tokens: tks,
})
}
tresult.Text = result.Text
return tresult, nil
}
func (s *server) PredictStream(in *pb.PredictOptions, stream pb.Backend_PredictStreamServer) error {
resultChan := make(chan string)
done := make(chan bool)
go func() {
for result := range resultChan {
stream.Send(&pb.Reply{Message: result})
}
done <- true
}()
s.llm.PredictStream(in, resultChan)
<-done
return nil
}
func StartServer(address string, model LLM) error {
lis, err := net.Listen("tcp", address)
if err != nil {
return err
}
s := grpc.NewServer()
pb.RegisterBackendServer(s, &server{llm: model})
log.Printf("gRPC Server listening at %v", lis.Addr())
if err := s.Serve(lis); err != nil {
return err
}
return nil
}

@ -0,0 +1,27 @@
package transcribe
// 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 (
"github.com/ggerganov/whisper.cpp/bindings/go/pkg/whisper"
"github.com/go-skynet/LocalAI/pkg/grpc/base"
pb "github.com/go-skynet/LocalAI/pkg/grpc/proto"
whisperutil "github.com/go-skynet/LocalAI/pkg/grpc/whisper"
"github.com/go-skynet/LocalAI/pkg/grpc/whisper/api"
)
type Whisper struct {
base.Base
whisper whisper.Model
}
func (sd *Whisper) Load(opts *pb.ModelOptions) error {
// Note: the Model here is a path to a directory containing the model files
w, err := whisper.New(opts.Model)
sd.whisper = w
return err
}
func (sd *Whisper) AudioTranscription(opts *pb.TranscriptRequest) (api.Result, error) {
return whisperutil.Transcript(sd.whisper, opts.Dst, opts.Language, uint(opts.Threads))
}

@ -0,0 +1,44 @@
package tts
// 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 (
"os"
"github.com/go-skynet/LocalAI/pkg/grpc/base"
pb "github.com/go-skynet/LocalAI/pkg/grpc/proto"
piper "github.com/mudler/go-piper"
)
type Piper struct {
base.Base
piper *PiperB
}
func (sd *Piper) Load(opts *pb.ModelOptions) error {
var err error
// Note: the Model here is a path to a directory containing the model files
sd.piper, err = New(opts.LibrarySearchPath)
return err
}
func (sd *Piper) TTS(opts *pb.TTSRequest) error {
return sd.piper.TTS(opts.Text, opts.Model, opts.Dst)
}
type PiperB struct {
assetDir string
}
func New(assetDir string) (*PiperB, error) {
if _, err := os.Stat(assetDir); err != nil {
return nil, err
}
return &PiperB{
assetDir: assetDir,
}, nil
}
func (s *PiperB) TTS(text, model, dst string) error {
return piper.TextToWav(text, model, s.assetDir, "", dst)
}

@ -0,0 +1,16 @@
package api
import "time"
type Segment struct {
Id int `json:"id"`
Start time.Duration `json:"start"`
End time.Duration `json:"end"`
Text string `json:"text"`
Tokens []int `json:"tokens"`
}
type Result struct {
Segments []Segment `json:"segments"`
Text string `json:"text"`
}

@ -5,25 +5,12 @@ import (
"os"
"os/exec"
"path/filepath"
"time"
"github.com/ggerganov/whisper.cpp/bindings/go/pkg/whisper"
wav "github.com/go-audio/wav"
"github.com/go-skynet/LocalAI/pkg/grpc/whisper/api"
)
type Segment struct {
Id int `json:"id"`
Start time.Duration `json:"start"`
End time.Duration `json:"end"`
Text string `json:"text"`
Tokens []int `json:"tokens"`
}
type Result struct {
Segments []Segment `json:"segments"`
Text string `json:"text"`
}
func sh(c string) (string, error) {
cmd := exec.Command("/bin/sh", "-c", c)
cmd.Env = os.Environ()
@ -42,8 +29,8 @@ func audioToWav(src, dst string) error {
return nil
}
func Transcript(model whisper.Model, audiopath, language string, threads uint) (Result, error) {
res := Result{}
func Transcript(model whisper.Model, audiopath, language string, threads uint) (api.Result, error) {
res := api.Result{}
dir, err := os.MkdirTemp("", "whisper")
if err != nil {
@ -99,11 +86,11 @@ func Transcript(model whisper.Model, audiopath, language string, threads uint) (
}
var tokens []int
for _, t := range(s.Tokens) {
for _, t := range s.Tokens {
tokens = append(tokens, t.Id)
}
segment := Segment{Id: s.Num, Text: s.Text, Start:s.Start, End: s.End, Tokens: tokens}
segment := api.Segment{Id: s.Num, Text: s.Text, Start: s.Start, End: s.End, Tokens: tokens}
res.Segments = append(res.Segments, segment)
res.Text += s.Text

@ -1,197 +1,216 @@
package model
import (
"context"
"fmt"
"os"
"os/signal"
"path/filepath"
"strings"
"syscall"
"time"
rwkv "github.com/donomii/go-rwkv.cpp"
whisper "github.com/ggerganov/whisper.cpp/bindings/go/pkg/whisper"
"github.com/go-skynet/LocalAI/pkg/langchain"
"github.com/go-skynet/LocalAI/pkg/stablediffusion"
"github.com/go-skynet/LocalAI/pkg/tts"
bloomz "github.com/go-skynet/bloomz.cpp"
bert "github.com/go-skynet/go-bert.cpp"
transformers "github.com/go-skynet/go-ggml-transformers.cpp"
llama "github.com/go-skynet/go-llama.cpp"
grpc "github.com/go-skynet/LocalAI/pkg/grpc"
"github.com/hashicorp/go-multierror"
gpt4all "github.com/nomic-ai/gpt4all/gpt4all-bindings/golang"
"github.com/hpcloud/tail"
"github.com/phayes/freeport"
"github.com/rs/zerolog/log"
process "github.com/mudler/go-processmanager"
)
const tokenizerSuffix = ".tokenizer.json"
const (
LlamaBackend = "llama"
BloomzBackend = "bloomz"
StarcoderBackend = "starcoder"
GPTJBackend = "gptj"
DollyBackend = "dolly"
MPTBackend = "mpt"
GPTNeoXBackend = "gptneox"
ReplitBackend = "replit"
Gpt2Backend = "gpt2"
Gpt4AllLlamaBackend = "gpt4all-llama"
Gpt4AllMptBackend = "gpt4all-mpt"
Gpt4AllJBackend = "gpt4all-j"
Gpt4All = "gpt4all"
FalconBackend = "falcon"
LlamaBackend = "llama"
BloomzBackend = "bloomz"
StarcoderBackend = "starcoder"
GPTJBackend = "gptj"
DollyBackend = "dolly"
MPTBackend = "mpt"
GPTNeoXBackend = "gptneox"
ReplitBackend = "replit"
Gpt2Backend = "gpt2"
Gpt4AllLlamaBackend = "gpt4all-llama"
Gpt4AllMptBackend = "gpt4all-mpt"
Gpt4AllJBackend = "gpt4all-j"
Gpt4All = "gpt4all"
FalconBackend = "falcon"
FalconGGMLBackend = "falcon-ggml"
BertEmbeddingsBackend = "bert-embeddings"
RwkvBackend = "rwkv"
WhisperBackend = "whisper"
StableDiffusionBackend = "stablediffusion"
PiperBackend = "piper"
LCHuggingFaceBackend = "langchain-huggingface"
//GGLLMFalconBackend = "falcon"
)
var autoLoadBackends []string = []string{
LlamaBackend,
Gpt4All,
RwkvBackend,
GPTNeoXBackend,
FalconBackend,
WhisperBackend,
GPTNeoXBackend,
BertEmbeddingsBackend,
FalconGGMLBackend,
GPTJBackend,
Gpt2Backend,
DollyBackend,
FalconBackend,
MPTBackend,
ReplitBackend,
StarcoderBackend,
BloomzBackend,
}
var starCoder = func(modelFile string) (interface{}, error) {
return transformers.NewStarcoder(modelFile)
func (ml *ModelLoader) StopGRPC() {
for _, p := range ml.grpcProcesses {
p.Stop()
}
}
var mpt = func(modelFile string) (interface{}, error) {
return transformers.NewMPT(modelFile)
}
// starts the grpcModelProcess for the backend, and returns a grpc client
// It also loads the model
func (ml *ModelLoader) grpcModel(backend string, o *Options) func(string) (*grpc.Client, error) {
return func(s string) (*grpc.Client, error) {
log.Debug().Msgf("Loading GRPC Model", backend, *o)
var dolly = func(modelFile string) (interface{}, error) {
return transformers.NewDolly(modelFile)
}
grpcProcess := filepath.Join(o.assetDir, "backend-assets", "grpc", backend)
var gptNeoX = func(modelFile string) (interface{}, error) {
return transformers.NewGPTNeoX(modelFile)
}
// Check if the file exists
if _, err := os.Stat(grpcProcess); os.IsNotExist(err) {
return nil, fmt.Errorf("grpc process not found: %s. some backends(stablediffusion, tts) require LocalAI compiled with GO_TAGS", grpcProcess)
}
var replit = func(modelFile string) (interface{}, error) {
return transformers.NewReplit(modelFile)
}
// Make sure the process is executable
if err := os.Chmod(grpcProcess, 0755); err != nil {
return nil, err
}
var gptJ = func(modelFile string) (interface{}, error) {
return transformers.NewGPTJ(modelFile)
}
log.Debug().Msgf("Loading GRPC Process", grpcProcess)
port, err := freeport.GetFreePort()
if err != nil {
return nil, err
}
var falcon = func(modelFile string) (interface{}, error) {
return transformers.NewFalcon(modelFile)
}
serverAddress := fmt.Sprintf("localhost:%d", port)
var bertEmbeddings = func(modelFile string) (interface{}, error) {
return bert.New(modelFile)
}
log.Debug().Msgf("GRPC Service for '%s' (%s) will be running at: '%s'", backend, o.modelFile, serverAddress)
var bloomzLM = func(modelFile string) (interface{}, error) {
return bloomz.New(modelFile)
}
grpcControlProcess := process.New(
process.WithTemporaryStateDir(),
process.WithName(grpcProcess),
process.WithArgs("--addr", serverAddress))
var transformersLM = func(modelFile string) (interface{}, error) {
return transformers.New(modelFile)
}
ml.grpcProcesses[o.modelFile] = grpcControlProcess
var stableDiffusion = func(assetDir string) (interface{}, error) {
return stablediffusion.New(assetDir)
}
if err := grpcControlProcess.Run(); err != nil {
return nil, err
}
func piperTTS(assetDir string) func(s string) (interface{}, error) {
return func(s string) (interface{}, error) {
return tts.New(assetDir)
}
}
// clean up process
go func() {
c := make(chan os.Signal, 1)
signal.Notify(c, os.Interrupt, syscall.SIGTERM)
<-c
grpcControlProcess.Stop()
}()
go func() {
t, err := tail.TailFile(grpcControlProcess.StderrPath(), tail.Config{Follow: true})
if err != nil {
log.Debug().Msgf("Could not tail stderr")
}
for line := range t.Lines {
log.Debug().Msgf("GRPC(%s): stderr %s", strings.Join([]string{backend, o.modelFile, serverAddress}, "-"), line.Text)
}
}()
go func() {
t, err := tail.TailFile(grpcControlProcess.StdoutPath(), tail.Config{Follow: true})
if err != nil {
log.Debug().Msgf("Could not tail stdout")
}
for line := range t.Lines {
log.Debug().Msgf("GRPC(%s): stderr %s", strings.Join([]string{backend, o.modelFile, serverAddress}, "-"), line.Text)
}
}()
log.Debug().Msgf("GRPC Service Started")
client := grpc.NewClient(serverAddress)
// Wait for the service to start up
ready := false
for i := 0; i < 10; i++ {
if client.HealthCheck(context.Background()) {
log.Debug().Msgf("GRPC Service Ready")
ready = true
break
}
time.Sleep(1 * time.Second)
}
var whisperModel = func(modelFile string) (interface{}, error) {
return whisper.New(modelFile)
}
if !ready {
log.Debug().Msgf("GRPC Service NOT ready")
log.Debug().Msgf("Alive: ", grpcControlProcess.IsAlive())
log.Debug().Msgf(fmt.Sprintf("GRPC Service Exitcode:"))
var lcHuggingFace = func(repoId string) (interface{}, error) {
return langchain.NewHuggingFace(repoId)
}
log.Debug().Msgf(grpcControlProcess.ExitCode())
func llamaLM(opts ...llama.ModelOption) func(string) (interface{}, error) {
return func(s string) (interface{}, error) {
return llama.New(s, opts...)
}
}
return nil, fmt.Errorf("grpc service not ready")
}
func gpt4allLM(opts ...gpt4all.ModelOption) func(string) (interface{}, error) {
return func(s string) (interface{}, error) {
return gpt4all.New(s, opts...)
}
}
options := *o.gRPCOptions
options.Model = s
func rwkvLM(tokenFile string, threads uint32) func(string) (interface{}, error) {
return func(s string) (interface{}, error) {
log.Debug().Msgf("Loading RWKV", s, tokenFile)
log.Debug().Msgf("GRPC: Loading model with options: %+v", options)
model := rwkv.LoadFiles(s, tokenFile, threads)
if model == nil {
return nil, fmt.Errorf("could not load model")
res, err := client.LoadModel(o.context, &options)
if err != nil {
return nil, err
}
if !res.Success {
return nil, fmt.Errorf("could not load model: %s", res.Message)
}
return model, nil
return client, nil
}
}
func (ml *ModelLoader) BackendLoader(backendString string, modelFile string, llamaOpts []llama.ModelOption, threads uint32, assetDir string) (model interface{}, err error) {
log.Debug().Msgf("Loading model %s from %s", backendString, modelFile)
switch strings.ToLower(backendString) {
case LlamaBackend:
return ml.LoadModel(modelFile, llamaLM(llamaOpts...))
case BloomzBackend:
return ml.LoadModel(modelFile, bloomzLM)
case GPTJBackend:
return ml.LoadModel(modelFile, gptJ)
case DollyBackend:
return ml.LoadModel(modelFile, dolly)
case MPTBackend:
return ml.LoadModel(modelFile, mpt)
case Gpt2Backend:
return ml.LoadModel(modelFile, transformersLM)
case FalconBackend:
return ml.LoadModel(modelFile, falcon)
case GPTNeoXBackend:
return ml.LoadModel(modelFile, gptNeoX)
case ReplitBackend:
return ml.LoadModel(modelFile, replit)
case StableDiffusionBackend:
return ml.LoadModel(modelFile, stableDiffusion)
case PiperBackend:
return ml.LoadModel(modelFile, piperTTS(filepath.Join(assetDir, "backend-assets", "espeak-ng-data")))
case StarcoderBackend:
return ml.LoadModel(modelFile, starCoder)
func (ml *ModelLoader) BackendLoader(opts ...Option) (model *grpc.Client, err error) {
o := NewOptions(opts...)
log.Debug().Msgf("Loading model %s from %s", o.backendString, o.modelFile)
backend := strings.ToLower(o.backendString)
switch backend {
case LlamaBackend, GPTJBackend, DollyBackend,
MPTBackend, Gpt2Backend, FalconBackend,
GPTNeoXBackend, ReplitBackend, StarcoderBackend, BloomzBackend,
RwkvBackend, LCHuggingFaceBackend, BertEmbeddingsBackend, FalconGGMLBackend, StableDiffusionBackend, WhisperBackend:
return ml.LoadModel(o.modelFile, ml.grpcModel(backend, o))
case Gpt4AllLlamaBackend, Gpt4AllMptBackend, Gpt4AllJBackend, Gpt4All:
return ml.LoadModel(modelFile, gpt4allLM(gpt4all.SetThreads(int(threads)), gpt4all.SetLibrarySearchPath(filepath.Join(assetDir, "backend-assets", "gpt4all"))))
case BertEmbeddingsBackend:
return ml.LoadModel(modelFile, bertEmbeddings)
case RwkvBackend:
return ml.LoadModel(modelFile, rwkvLM(filepath.Join(ml.ModelPath, modelFile+tokenizerSuffix), threads))
case WhisperBackend:
return ml.LoadModel(modelFile, whisperModel)
case LCHuggingFaceBackend:
return ml.LoadModel(modelFile, lcHuggingFace)
o.gRPCOptions.LibrarySearchPath = filepath.Join(o.assetDir, "backend-assets", "gpt4all")
return ml.LoadModel(o.modelFile, ml.grpcModel(Gpt4All, o))
case PiperBackend:
o.gRPCOptions.LibrarySearchPath = filepath.Join(o.assetDir, "backend-assets", "espeak-ng-data")
return ml.LoadModel(o.modelFile, ml.grpcModel(PiperBackend, o))
default:
return nil, fmt.Errorf("backend unsupported: %s", backendString)
return nil, fmt.Errorf("backend unsupported: %s", o.backendString)
}
}
func (ml *ModelLoader) GreedyLoader(modelFile string, llamaOpts []llama.ModelOption, threads uint32, assetDir string) (interface{}, error) {
log.Debug().Msgf("Loading model '%s' greedly", modelFile)
func (ml *ModelLoader) GreedyLoader(opts ...Option) (*grpc.Client, error) {
o := NewOptions(opts...)
log.Debug().Msgf("Loading model '%s' greedly", o.modelFile)
// Is this really needed? BackendLoader already does this
ml.mu.Lock()
m, exists := ml.models[modelFile]
if exists {
log.Debug().Msgf("Model '%s' already loaded", modelFile)
if m := ml.checkIsLoaded(o.modelFile); m != nil {
log.Debug().Msgf("Model '%s' already loaded", o.modelFile)
ml.mu.Unlock()
return m, nil
}
@ -203,7 +222,14 @@ func (ml *ModelLoader) GreedyLoader(modelFile string, llamaOpts []llama.ModelOpt
continue
}
log.Debug().Msgf("[%s] Attempting to load", b)
model, modelerr := ml.BackendLoader(b, modelFile, llamaOpts, threads, assetDir)
model, modelerr := ml.BackendLoader(
WithBackendString(b),
WithModelFile(o.modelFile),
WithLoadGRPCLLMModelOpts(o.gRPCOptions),
WithThreads(o.threads),
WithAssetDir(o.assetDir),
)
if modelerr == nil && model != nil {
log.Debug().Msgf("[%s] Loads OK", b)
return model, nil

@ -2,6 +2,7 @@ package model
import (
"bytes"
"context"
"fmt"
"io/ioutil"
"os"
@ -10,6 +11,8 @@ import (
"sync"
"text/template"
"github.com/go-skynet/LocalAI/pkg/grpc"
process "github.com/mudler/go-processmanager"
"github.com/rs/zerolog/log"
)
@ -17,15 +20,17 @@ type ModelLoader struct {
ModelPath string
mu sync.Mutex
// TODO: this needs generics
models map[string]interface{}
models map[string]*grpc.Client
grpcProcesses map[string]*process.Process
promptsTemplates map[string]*template.Template
}
func NewModelLoader(modelPath string) *ModelLoader {
return &ModelLoader{
ModelPath: modelPath,
models: make(map[string]interface{}),
models: make(map[string]*grpc.Client),
promptsTemplates: make(map[string]*template.Template),
grpcProcesses: make(map[string]*process.Process),
}
}
@ -110,14 +115,14 @@ func (ml *ModelLoader) loadTemplateIfExists(modelName, modelFile string) error {
return nil
}
func (ml *ModelLoader) LoadModel(modelName string, loader func(string) (interface{}, error)) (interface{}, error) {
func (ml *ModelLoader) LoadModel(modelName string, loader func(string) (*grpc.Client, error)) (*grpc.Client, error) {
ml.mu.Lock()
defer ml.mu.Unlock()
// Check if we already have a loaded model
if m, ok := ml.models[modelName]; ok {
if model := ml.checkIsLoaded(modelName); model != nil {
log.Debug().Msgf("Model already loaded in memory: %s", modelName)
return m, nil
return model, nil
}
// Load the model and keep it in memory for later use
@ -137,3 +142,25 @@ func (ml *ModelLoader) LoadModel(modelName string, loader func(string) (interfac
ml.models[modelName] = model
return model, nil
}
func (ml *ModelLoader) checkIsLoaded(s string) *grpc.Client {
if m, ok := ml.models[s]; ok {
log.Debug().Msgf("Model already loaded in memory: %s", s)
if !m.HealthCheck(context.Background()) {
log.Debug().Msgf("GRPC Model not responding", s)
if !ml.grpcProcesses[s].IsAlive() {
log.Debug().Msgf("GRPC Process is not responding", s)
// stop and delete the process, this forces to re-load the model and re-create again the service
ml.grpcProcesses[s].Stop()
delete(ml.grpcProcesses, s)
delete(ml.models, s)
return nil
}
}
return m
}
return nil
}

@ -0,0 +1,66 @@
package model
import (
"context"
pb "github.com/go-skynet/LocalAI/pkg/grpc/proto"
)
type Options struct {
backendString string
modelFile string
threads uint32
assetDir string
context context.Context
gRPCOptions *pb.ModelOptions
}
type Option func(*Options)
func WithBackendString(backend string) Option {
return func(o *Options) {
o.backendString = backend
}
}
func WithModelFile(modelFile string) Option {
return func(o *Options) {
o.modelFile = modelFile
}
}
func WithLoadGRPCLLMModelOpts(opts *pb.ModelOptions) Option {
return func(o *Options) {
o.gRPCOptions = opts
}
}
func WithThreads(threads uint32) Option {
return func(o *Options) {
o.threads = threads
}
}
func WithAssetDir(assetDir string) Option {
return func(o *Options) {
o.assetDir = assetDir
}
}
func WithContext(ctx context.Context) Option {
return func(o *Options) {
o.context = ctx
}
}
func NewOptions(opts ...Option) *Options {
o := &Options{
gRPCOptions: &pb.ModelOptions{},
context: context.Background(),
}
for _, opt := range opts {
opt(o)
}
return o
}

@ -1,12 +0,0 @@
//go:build tts
// +build tts
package tts
import (
piper "github.com/mudler/go-piper"
)
func tts(text, model, assetDir, arLib, dst string) error {
return piper.TextToWav(text, model, assetDir, arLib, dst)
}

@ -1,10 +0,0 @@
//go:build !tts
// +build !tts
package tts
import "fmt"
func tts(text, model, assetDir, arLib, dst string) error {
return fmt.Errorf("this version of LocalAI was built without the tts tag")
}

@ -1,20 +0,0 @@
package tts
import "os"
type Piper struct {
assetDir string
}
func New(assetDir string) (*Piper, error) {
if _, err := os.Stat(assetDir); err != nil {
return nil, err
}
return &Piper{
assetDir: assetDir,
}, nil
}
func (s *Piper) TTS(text, model, dst string) error {
return tts(text, model, s.assetDir, "", dst)
}
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