Minor fixes (#285)

Signed-off-by: GitHub <noreply@github.com>
Co-authored-by: mudler <mudler@users.noreply.github.com>

.dockerignore

@@ -1 +1,4 @@
 models
+examples/chatbot-ui/models
+examples/rwkv/models
+examples/**/models

.github/bump_deps.sh

@@ -0,0 +1,9 @@
+#!/bin/bash
+set -xe
+REPO=$1
+BRANCH=$2
+VAR=$3
+
+LAST_COMMIT=$(curl -s -H "Accept: application/vnd.github.VERSION.sha" "https://api.github.com/repos/$REPO/commits/$BRANCH")
+
+sed -i Makefile -e "s/$VAR?=.*/$VAR?=$LAST_COMMIT/"

.github/workflows/bump_deps.yaml

@@ -0,0 +1,51 @@
+name: Bump dependencies
+on:
+  schedule:
+    - cron: 0 20 * * *
+  workflow_dispatch:
+jobs:
+  bump:
+    strategy:
+      fail-fast: false
+      matrix:
+        include:
+          - repository: "go-skynet/go-llama.cpp"
+            variable: "GOLLAMA_VERSION"
+            branch: "master"
+          - repository: "go-skynet/go-gpt2.cpp"
+            variable: "GOGPT2_VERSION"
+            branch: "master"
+          - repository: "donomii/go-rwkv.cpp"
+            variable: "RWKV_VERSION"
+            branch: "main"
+          - repository: "ggerganov/whisper.cpp"
+            variable: "WHISPER_CPP_VERSION"
+            branch: "master"
+          - repository: "go-skynet/go-bert.cpp"
+            variable: "BERT_VERSION"
+            branch: "master"
+          - repository: "go-skynet/bloomz.cpp"
+            variable: "BLOOMZ_VERSION"
+            branch: "main"
+          - repository: "nomic-ai/gpt4all"
+            variable: "GPT4ALL_VERSION"
+            branch: "main"
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v3
+      - name: Bump dependencies 🔧
+        run: |
+          bash .github/bump_deps.sh ${{ matrix.repository }} ${{ matrix.branch }} ${{ matrix.variable }}
+      - name: Create Pull Request
+        uses: peter-evans/create-pull-request@v5
+        with:
+          token: ${{ secrets.UPDATE_BOT_TOKEN }}
+          push-to-fork: ci-forks/LocalAI
+          commit-message: ':arrow_up: Update ${{ matrix.repository }}'
+          title: ':arrow_up: Update ${{ matrix.repository }}'
+          branch: "update/${{ matrix.variable }}"
+          body: Bump of ${{ matrix.repository }} version
+          signoff: true
+
+
+

.github/workflows/image.yml

@@ -54,8 +54,8 @@ jobs:
         uses: docker/login-action@v2
         with:
           registry: quay.io
-          username: ${{ secrets.QUAY_USERNAME }}
-          password: ${{ secrets.QUAY_PASSWORD }}
+          username: ${{ secrets.LOCALAI_REGISTRY_USERNAME }}
+          password: ${{ secrets.LOCALAI_REGISTRY_PASSWORD }}
       - name: Build
         if: github.event_name != 'pull_request'
         uses: docker/build-push-action@v4

.github/workflows/test.yml

@@ -21,7 +21,7 @@ jobs:
       - name: Dependencies
         run: |
           sudo apt-get update
-          sudo apt-get install build-essential
+          sudo apt-get install build-essential ffmpeg
       - name: Test
         run: |
           make test
@@ -38,7 +38,7 @@ jobs:
       - name: Dependencies
         run: |
           brew update
-          brew install sdl2
+          brew install sdl2 ffmpeg
       - name: Test
         run: |
           make test

.gitignore

@@ -1,7 +1,10 @@
 # go-llama build artifacts
 go-llama
-go-gpt4all-j
+gpt4all
+go-stable-diffusion
 go-gpt2
+go-rwkv
+whisper.cpp
 
 # LocalAI build binary
 LocalAI
@@ -10,6 +13,8 @@ local-ai
 !charts/*
 
 # Ignore models
-models/*.bin
-models/ggml-*
-test-models/
+models/*
+test-models/
+
+# just in case
+.DS_Store

Dockerfile

@@ -1,13 +1,10 @@
 ARG GO_VERSION=1.20
-ARG DEBIAN_VERSION=11
 ARG BUILD_TYPE=
-
-FROM golang:$GO_VERSION as builder
+FROM golang:$GO_VERSION
 WORKDIR /build
-RUN apt-get update && apt-get install -y cmake
+RUN apt-get update && apt-get install -y cmake libgomp1 libopenblas-dev libopenblas-base libopencv-dev libopencv-core-dev libopencv-core4.5 
 COPY . .
-RUN make build
-
-FROM debian:$DEBIAN_VERSION
-COPY --from=builder /build/local-ai /usr/bin/local-ai
-ENTRYPOINT [ "/usr/bin/local-ai" ]
+RUN ln -s /usr/include/opencv4/opencv2/ /usr/include/opencv2
+RUN make prepare-sources
+EXPOSE 8080
+ENTRYPOINT [ "/build/entrypoint.sh" ]

Dockerfile.dev

@@ -0,0 +1,15 @@
+ARG GO_VERSION=1.20
+ARG DEBIAN_VERSION=11
+ARG BUILD_TYPE=
+
+FROM golang:$GO_VERSION as builder
+WORKDIR /build
+RUN apt-get update && apt-get install -y cmake libgomp1 libopenblas-dev libopenblas-base libopencv-dev libopencv-core-dev libopencv-core4.5 
+RUN ln -s /usr/include/opencv4/opencv2/ /usr/include/opencv2
+COPY . .
+RUN make build
+
+FROM debian:$DEBIAN_VERSION
+COPY --from=builder /build/local-ai /usr/bin/local-ai
+EXPOSE 8080
+ENTRYPOINT [ "/usr/bin/local-ai" ]

Makefile

@@ -2,12 +2,24 @@ GOCMD=go
 GOTEST=$(GOCMD) test
 GOVET=$(GOCMD) vet
 BINARY_NAME=local-ai
-# renovate: datasource=github-tags depName=go-skynet/go-llama.cpp
-GOLLAMA_VERSION?=llama.cpp-25d7abb
-# renovate: datasource=git-refs packageNameTemplate=https://github.com/go-skynet/go-gpt4all-j.cpp currentValueTemplate=master depNameTemplate=go-gpt4all-j.cpp
-GOGPT4ALLJ_VERSION?=1f7bff57f66cb7062e40d0ac3abd2217815e5109
-# renovate: datasource=git-refs packageNameTemplate=https://github.com/go-skynet/go-gpt2.cpp currentValueTemplate=master depNameTemplate=go-gpt2.cpp
-GOGPT2_VERSION?=245a5bfe6708ab80dc5c733dcdbfbe3cfd2acdaa
+
+GOLLAMA_VERSION?=7f9ae4246088f0c08ed322acbae21d69cd2eb547
+GPT4ALL_REPO?=https://github.com/nomic-ai/gpt4all
+GPT4ALL_VERSION?=a07237e54fcdfdb351913587052ac061a2a7bdff
+GOGPT2_VERSION?=7bff56f0224502c1c9ed6258d2a17e8084628827
+RWKV_REPO?=https://github.com/donomii/go-rwkv.cpp
+RWKV_VERSION?=07166da10cb2a9e8854395a4f210464dcea76e47
+WHISPER_CPP_VERSION?=95b02d76b04d18e4ce37ed8353a1f0797f1717ea
+BERT_VERSION?=cea1ed76a7f48ef386a8e369f6c82c48cdf2d551
+BLOOMZ_VERSION?=e9366e82abdfe70565644fbfae9651976714efd1
+BUILD_TYPE?=
+CGO_LDFLAGS?=
+CUDA_LIBPATH?=/usr/local/cuda/lib64/
+STABLEDIFFUSION_VERSION?=c0748eca3642d58bcf9521108bcee46959c647dc
+
+GO_TAGS?=
+
+OPTIONAL_TARGETS?=
 
 GREEN  := $(shell tput -Txterm setaf 2)
 YELLOW := $(shell tput -Txterm setaf 3)
@@ -15,96 +27,195 @@ 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-gpt4all-j:$(shell pwd)/go-gpt2
-LIBRARY_PATH=$(shell pwd)/go-llama:$(shell pwd)/go-gpt4all-j:$(shell pwd)/go-gpt2
+C_INCLUDE_PATH=$(shell pwd)/go-llama:$(shell pwd)/go-stable-diffusion/:$(shell pwd)/gpt4all/gpt4all-bindings/golang/:$(shell pwd)/go-gpt2:$(shell pwd)/go-rwkv:$(shell pwd)/whisper.cpp:$(shell pwd)/go-bert:$(shell pwd)/bloomz
+LIBRARY_PATH=$(shell pwd)/go-llama:$(shell pwd)/go-stable-diffusion/:$(shell pwd)/gpt4all/gpt4all-bindings/golang/:$(shell pwd)/go-gpt2:$(shell pwd)/go-rwkv:$(shell pwd)/whisper.cpp:$(shell pwd)/go-bert:$(shell pwd)/bloomz
 
-# Use this if you want to set the default behavior
-ifndef BUILD_TYPE
-	BUILD_TYPE:=default
+ifeq ($(BUILD_TYPE),openblas)
+	CGO_LDFLAGS+=-lopenblas
 endif
 
-ifeq ($(BUILD_TYPE), "generic")
-	GENERIC_PREFIX:=generic-
-else
-	GENERIC_PREFIX:=
+ifeq ($(BUILD_TYPE),cublas)
+	CGO_LDFLAGS+=-lcublas -lcudart -L$(CUDA_LIBPATH)
+endif
+
+
+ifeq ($(GO_TAGS),stablediffusion)
+	OPTIONAL_TARGETS+=go-stable-diffusion/libstablediffusion.a
 endif
 
 .PHONY: all test build vendor
 
 all: help
 
+## GPT4ALL
+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_gptj_/g' {} +
+	@find ./gpt4all -type f -name "*.cpp" -exec sed -i'' -e 's/ggml_/ggml_gptj_/g' {} +
+	@find ./gpt4all -type f -name "*.h" -exec sed -i'' -e 's/ggml_/ggml_gptj_/g' {} +
+	@find ./gpt4all -type f -name "*.cpp" -exec sed -i'' -e 's/gpt_/gptj_/g' {} +
+	@find ./gpt4all -type f -name "*.h" -exec sed -i'' -e 's/gpt_/gptj_/g' {} +
+	@find ./gpt4all -type f -name "*.h" -exec sed -i'' -e 's/set_console_color/set_gptj_console_color/g' {} +
+	@find ./gpt4all -type f -name "*.cpp" -exec sed -i'' -e 's/set_console_color/set_gptj_console_color/g' {} +
+	@find ./gpt4all -type f -name "*.cpp" -exec sed -i'' -e 's/llama_/gptjllama_/g' {} +
+	@find ./gpt4all -type f -name "*.go" -exec sed -i'' -e 's/llama_/gptjllama_/g' {} +
+	@find ./gpt4all -type f -name "*.h" -exec sed -i'' -e 's/llama_/gptjllama_/g' {} +
+	@find ./gpt4all -type f -name "*.txt" -exec sed -i'' -e 's/llama_/gptjllama_/g' {} +
+	@find ./gpt4all -type f -name "*.cpp" -exec sed -i'' -e 's/json_/json_gptj_/g' {} +
+	@find ./gpt4all -type f -name "*.cpp" -exec sed -i'' -e 's/void replace/void json_gptj_replace/g' {} +
+	@find ./gpt4all -type f -name "*.cpp" -exec sed -i'' -e 's/::replace/::json_gptj_replace/g' {} +
+	mv ./gpt4all/gpt4all-backend/llama.cpp/llama_util.h ./gpt4all/gpt4all-backend/llama.cpp/gptjllama_util.h
+
+## BERT embeddings
+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:
+	git clone --recurse-submodules https://github.com/mudler/go-stable-diffusion go-stable-diffusion
+	cd go-stable-diffusion && git checkout -b build $(STABLEDIFFUSION_VERSION) && git submodule update --init --recursive --depth 1
+
+go-stable-diffusion/libstablediffusion.a:
+	$(MAKE) -C go-stable-diffusion libstablediffusion.a
+
+## RWKV
+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 .. && cp ggml/src/libggml.a ..
+
+## 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' {} +
+
+bloomz/libbloomz.a: bloomz
+	cd bloomz && make libbloomz.a
+
+go-bert/libgobert.a: go-bert
+	$(MAKE) -C go-bert libgobert.a
+
+gpt4all/gpt4all-bindings/golang/libgpt4all.a: gpt4all
+	$(MAKE) -C gpt4all/gpt4all-bindings/golang/ libgpt4all.a
+
+## CEREBRAS GPT
+go-gpt2: 
+	git clone --recurse-submodules https://github.com/go-skynet/go-gpt2.cpp go-gpt2
+	cd go-gpt2 && 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-gpt2 -type f -name "*.c" -exec sed -i'' -e 's/ggml_/ggml_gpt2_/g' {} +
+	@find ./go-gpt2 -type f -name "*.cpp" -exec sed -i'' -e 's/ggml_/ggml_gpt2_/g' {} +
+	@find ./go-gpt2 -type f -name "*.h" -exec sed -i'' -e 's/ggml_/ggml_gpt2_/g' {} +
+	@find ./go-gpt2 -type f -name "*.cpp" -exec sed -i'' -e 's/gpt_print_usage/gpt2_print_usage/g' {} +
+	@find ./go-gpt2 -type f -name "*.h" -exec sed -i'' -e 's/gpt_print_usage/gpt2_print_usage/g' {} +
+	@find ./go-gpt2 -type f -name "*.cpp" -exec sed -i'' -e 's/gpt_params_parse/gpt2_params_parse/g' {} +
+	@find ./go-gpt2 -type f -name "*.h" -exec sed -i'' -e 's/gpt_params_parse/gpt2_params_parse/g' {} +
+	@find ./go-gpt2 -type f -name "*.cpp" -exec sed -i'' -e 's/gpt_random_prompt/gpt2_random_prompt/g' {} +
+	@find ./go-gpt2 -type f -name "*.h" -exec sed -i'' -e 's/gpt_random_prompt/gpt2_random_prompt/g' {} +
+	@find ./go-gpt2 -type f -name "*.cpp" -exec sed -i'' -e 's/json_/json_gpt2_/g' {} +
+
+go-gpt2/libgpt2.a: go-gpt2
+	$(MAKE) -C go-gpt2 libgpt2.a
+
+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
+
+go-llama:
+	git clone --recurse-submodules https://github.com/go-skynet/go-llama.cpp go-llama
+	cd go-llama && git checkout -b build $(GOLLAMA_VERSION) && git submodule update --init --recursive --depth 1
+
+go-llama/libbinding.a: go-llama 
+	$(MAKE) -C go-llama BUILD_TYPE=$(BUILD_TYPE) libbinding.a
+
+replace:
+	$(GOCMD) mod edit -replace github.com/go-skynet/go-llama.cpp=$(shell pwd)/go-llama
+	$(GOCMD) mod edit -replace github.com/nomic-ai/gpt4all/gpt4all-bindings/golang=$(shell pwd)/gpt4all/gpt4all-bindings/golang
+	$(GOCMD) mod edit -replace github.com/go-skynet/go-gpt2.cpp=$(shell pwd)/go-gpt2
+	$(GOCMD) mod edit -replace github.com/donomii/go-rwkv.cpp=$(shell pwd)/go-rwkv
+	$(GOCMD) mod edit -replace github.com/ggerganov/whisper.cpp=$(shell pwd)/whisper.cpp
+	$(GOCMD) mod edit -replace github.com/go-skynet/go-bert.cpp=$(shell pwd)/go-bert
+	$(GOCMD) mod edit -replace github.com/go-skynet/bloomz.cpp=$(shell pwd)/bloomz
+	$(GOCMD) mod edit -replace github.com/mudler/go-stable-diffusion=$(shell pwd)/go-stable-diffusion
+
+prepare-sources: go-llama go-gpt2 gpt4all go-rwkv whisper.cpp go-bert bloomz go-stable-diffusion replace
+	$(GOCMD) mod download
+
+## GENERIC
+rebuild: ## Rebuilds the project
+	$(MAKE) -C go-llama clean
+	$(MAKE) -C gpt4all/gpt4all-bindings/golang/ clean
+	$(MAKE) -C go-gpt2 clean
+	$(MAKE) -C go-rwkv clean
+	$(MAKE) -C whisper.cpp clean
+	$(MAKE) -C go-stable-diffusion clean
+	$(MAKE) -C go-bert clean
+	$(MAKE) -C bloomz clean
+	$(MAKE) build
+
+prepare: prepare-sources gpt4all/gpt4all-bindings/golang/libgpt4all.a $(OPTIONAL_TARGETS) go-llama/libbinding.a go-bert/libgobert.a go-gpt2/libgpt2.a go-rwkv/librwkv.a whisper.cpp/libwhisper.a bloomz/libbloomz.a  ## Prepares for building
+
+clean: ## Remove build related file
+	rm -fr ./go-llama
+	rm -rf ./gpt4all
+	rm -rf ./go-stable-diffusion
+	rm -rf ./go-gpt2
+	rm -rf ./go-rwkv
+	rm -rf ./go-bert
+	rm -rf ./bloomz
+	rm -rf ./whisper.cpp
+	rm -rf $(BINARY_NAME)
+
 ## Build:
 
 build: prepare ## Build the project
 	$(info ${GREEN}I local-ai build info:${RESET})
 	$(info ${GREEN}I BUILD_TYPE: ${YELLOW}$(BUILD_TYPE)${RESET})
-	C_INCLUDE_PATH=${C_INCLUDE_PATH} LIBRARY_PATH=${LIBRARY_PATH} $(GOCMD) build -o $(BINARY_NAME) ./
+	$(info ${GREEN}I GO_TAGS: ${YELLOW}$(GO_TAGS)${RESET})
+	CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=${C_INCLUDE_PATH} LIBRARY_PATH=${LIBRARY_PATH} $(GOCMD) build -tags "$(GO_TAGS)" -x -o $(BINARY_NAME) ./
 
 generic-build: ## Build the project using generic
 	BUILD_TYPE="generic" $(MAKE) build
 
-## GPT4ALL-J
-go-gpt4all-j:
-	git clone --recurse-submodules https://github.com/go-skynet/go-gpt4all-j.cpp go-gpt4all-j
-	cd go-gpt4all-j && git checkout -b build $(GOGPT4ALLJ_VERSION)
-	# This is hackish, but needed as both go-llama and go-gpt4allj have their own version of ggml..
-	@find ./go-gpt4all-j -type f -name "*.c" -exec sed -i'' -e 's/ggml_/ggml_gptj_/g' {} +
-	@find ./go-gpt4all-j -type f -name "*.cpp" -exec sed -i'' -e 's/ggml_/ggml_gptj_/g' {} +
-	@find ./go-gpt4all-j -type f -name "*.h" -exec sed -i'' -e 's/ggml_/ggml_gptj_/g' {} +
-	@find ./go-gpt4all-j -type f -name "*.cpp" -exec sed -i'' -e 's/gpt_/gptj_/g' {} +
-	@find ./go-gpt4all-j -type f -name "*.h" -exec sed -i'' -e 's/gpt_/gptj_/g' {} +
-	@find ./go-gpt4all-j -type f -name "*.cpp" -exec sed -i'' -e 's/json_/json_gptj_/g' {} +
-	@find ./go-gpt4all-j -type f -name "*.cpp" -exec sed -i'' -e 's/void replace/void json_gptj_replace/g' {} +
-	@find ./go-gpt4all-j -type f -name "*.cpp" -exec sed -i'' -e 's/::replace/::json_gptj_replace/g' {} +
-
-go-gpt4all-j/libgptj.a: go-gpt4all-j
-	$(MAKE) -C go-gpt4all-j $(GENERIC_PREFIX)libgptj.a
-
-# CEREBRAS GPT
-go-gpt2:
-	git clone --recurse-submodules https://github.com/go-skynet/go-gpt2.cpp go-gpt2
-	cd go-gpt2 && git checkout -b build $(GOGPT2_VERSION)
-	# This is hackish, but needed as both go-llama and go-gpt4allj have their own version of ggml..
-	@find ./go-gpt2 -type f -name "*.c" -exec sed -i'' -e 's/ggml_/ggml_gpt2_/g' {} +
-	@find ./go-gpt2 -type f -name "*.cpp" -exec sed -i'' -e 's/ggml_/ggml_gpt2_/g' {} +
-	@find ./go-gpt2 -type f -name "*.h" -exec sed -i'' -e 's/ggml_/ggml_gpt2_/g' {} +
-	@find ./go-gpt2 -type f -name "*.cpp" -exec sed -i'' -e 's/gpt_/gpt2_/g' {} +
-	@find ./go-gpt2 -type f -name "*.h" -exec sed -i'' -e 's/gpt_/gpt2_/g' {} +
-	@find ./go-gpt2 -type f -name "*.cpp" -exec sed -i'' -e 's/json_/json_gpt2_/g' {} +
-
-go-gpt2/libgpt2.a: go-gpt2
-	$(MAKE) -C go-gpt2 $(GENERIC_PREFIX)libgpt2.a
-	
-
-go-llama:
-	git clone -b $(GOLLAMA_VERSION) --recurse-submodules https://github.com/go-skynet/go-llama.cpp go-llama
-
-go-llama/libbinding.a: go-llama
-	$(MAKE) -C go-llama $(GENERIC_PREFIX)libbinding.a
-
-replace:
-	$(GOCMD) mod edit -replace github.com/go-skynet/go-llama.cpp=$(shell pwd)/go-llama
-	$(GOCMD) mod edit -replace github.com/go-skynet/go-gpt4all-j.cpp=$(shell pwd)/go-gpt4all-j
-	$(GOCMD) mod edit -replace github.com/go-skynet/go-gpt2.cpp=$(shell pwd)/go-gpt2
-
-prepare: go-llama/libbinding.a go-gpt4all-j/libgptj.a go-gpt2/libgpt2.a replace
-
-clean: ## Remove build related file
-	rm -fr ./go-llama
-	rm -rf ./go-gpt4all-j
-	rm -rf ./go-gpt2
-	rm -rf $(BINARY_NAME)
-
-## Run:
-run: prepare
-	C_INCLUDE_PATH=${C_INCLUDE_PATH} LIBRARY_PATH=${LIBRARY_PATH} $(GOCMD) run ./main.go
+## Run
+run: prepare ## run local-ai
+	CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=${C_INCLUDE_PATH} LIBRARY_PATH=${LIBRARY_PATH} $(GOCMD) run ./main.go
 
 test-models/testmodel:
 	mkdir test-models
+	mkdir test-dir
 	wget https://huggingface.co/concedo/cerebras-111M-ggml/resolve/main/cerberas-111m-q4_0.bin -O test-models/testmodel
+	wget https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-base.en.bin -O test-models/whisper-en
+	wget https://huggingface.co/skeskinen/ggml/resolve/main/all-MiniLM-L6-v2/ggml-model-q4_0.bin -O test-models/bert
+	wget https://cdn.openai.com/whisper/draft-20220913a/micro-machines.wav -O test-dir/audio.wav
+	wget https://huggingface.co/imxcstar/rwkv-4-raven-ggml/resolve/main/RWKV-4-Raven-1B5-v11-Eng99%25-Other1%25-20230425-ctx4096-16_Q4_2.bin -O test-models/rwkv
+	wget https://raw.githubusercontent.com/saharNooby/rwkv.cpp/5eb8f09c146ea8124633ab041d9ea0b1f1db4459/rwkv/20B_tokenizer.json -O test-models/rwkv.tokenizer.json
+	cp tests/fixtures/* test-models
 
 test: prepare test-models/testmodel
-	@C_INCLUDE_PATH=${C_INCLUDE_PATH} LIBRARY_PATH=${LIBRARY_PATH} MODELS_PATH=$(abspath ./)/test-models $(GOCMD) test -v ./...
+	cp tests/fixtures/* test-models
+	@C_INCLUDE_PATH=${C_INCLUDE_PATH} LIBRARY_PATH=${LIBRARY_PATH} TEST_DIR=$(abspath ./)/test-dir/ CONFIG_FILE=$(abspath ./)/test-models/config.yaml MODELS_PATH=$(abspath ./)/test-models $(GOCMD) run github.com/onsi/ginkgo/v2/ginkgo -v -r ./api
 
 ## Help:
 help: ## Show this help.

README.md

@@ -5,22 +5,71 @@
 <br>
 </h1>
 
-> :warning: This project has been renamed from `llama-cli` to `LocalAI` to reflect the fact that we are focusing on a fast drop-in OpenAI API rather on the CLI interface. We think that there are already many projects that can be used as a CLI interface already, for instance  [llama.cpp](https://github.com/ggerganov/llama.cpp) and [gpt4all](https://github.com/nomic-ai/gpt4all). If you are were using `llama-cli` for CLI interactions and want to keep using it, use older versions or please open up an issue - contributions are welcome!
-
-
 [![tests](https://github.com/go-skynet/LocalAI/actions/workflows/test.yml/badge.svg)](https://github.com/go-skynet/LocalAI/actions/workflows/test.yml) [![build container images](https://github.com/go-skynet/LocalAI/actions/workflows/image.yml/badge.svg)](https://github.com/go-skynet/LocalAI/actions/workflows/image.yml)
 
 [![](https://dcbadge.vercel.app/api/server/uJAeKSAGDy?style=flat-square&theme=default-inverted)](https://discord.gg/uJAeKSAGDy) 
 
-**LocalAI** is a straightforward, drop-in replacement API compatible with OpenAI for local CPU inferencing, based on [llama.cpp](https://github.com/ggerganov/llama.cpp), [gpt4all](https://github.com/nomic-ai/gpt4all) and [ggml](https://github.com/ggerganov/ggml), including support GPT4ALL-J which is Apache 2.0 Licensed and can be used for commercial purposes.
+**LocalAI** is a drop-in replacement REST API compatible with OpenAI API specifications for local inferencing. It allows to run models locally or on-prem with consumer grade hardware, supporting multiple models families compatible with the `ggml` format. For a list of the supported model families, see [the model compatibility table below](https://github.com/go-skynet/LocalAI#model-compatibility-table).
 
-- OpenAI compatible API
-- Supports multiple-models
+- OpenAI drop-in alternative REST API
+- Supports multiple models, Audio transcription, Text generation with GPTs, Image generation with stable diffusion (experimental)
 - Once loaded the first time, it keep models loaded in memory for faster inference
 - Support for prompt templates
-- Doesn't shell-out, but uses C bindings for a faster inference and better performance. Uses [go-llama.cpp](https://github.com/go-skynet/go-llama.cpp) and [go-gpt4all-j.cpp](https://github.com/go-skynet/go-gpt4all-j.cpp).
+- Doesn't shell-out, but uses C++ bindings for a faster inference and better performance. 
 
-Reddit post: https://www.reddit.com/r/selfhosted/comments/12w4p2f/localai_openai_compatible_api_to_run_llm_models/
+LocalAI is a community-driven project, focused on making the AI accessible to anyone. Any contribution, feedback and PR is welcome! It was initially created by [mudler](https://github.com/mudler/) at the [SpectroCloud OSS Office](https://github.com/spectrocloud).
+
+LocalAI uses C++ bindings for optimizing speed. It is based on [llama.cpp](https://github.com/ggerganov/llama.cpp), [gpt4all](https://github.com/nomic-ai/gpt4all), [rwkv.cpp](https://github.com/saharNooby/rwkv.cpp), [ggml](https://github.com/ggerganov/ggml), [whisper.cpp](https://github.com/ggerganov/whisper.cpp) for audio transcriptions, and [bert.cpp](https://github.com/skeskinen/bert.cpp) for embedding.
+
+See [examples on how to integrate LocalAI](https://github.com/go-skynet/LocalAI/tree/master/examples/).
+
+
+### How does it work?  
+
+<details>
+  
+![LocalAI](https://github.com/go-skynet/LocalAI/assets/2420543/38de3a9b-3866-48cd-9234-662f9571064a)
+
+</details>
+
+## News
+
+- 16-05-2023: 🔥🔥🔥 Experimental support for CUDA (https://github.com/go-skynet/LocalAI/pull/258) in the `llama.cpp` backend and Stable diffusion CPU image generation (https://github.com/go-skynet/LocalAI/pull/272) in `master`.
+
+Now LocalAI can generate images too:
+
+| mode=0                                                                                                                | mode=1 (winograd/sgemm)                                                                                                                |
+|------------------------------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------------|
+| ![b6441997879](https://github.com/go-skynet/LocalAI/assets/2420543/d50af51c-51b7-4f39-b6c2-bf04c403894c)              | ![winograd2](https://github.com/go-skynet/LocalAI/assets/2420543/1935a69a-ecce-4afc-a099-1ac28cb649b3)                |
+
+- 14-05-2023: __v1.11.1__ released! `rwkv` backend patch release
+- 13-05-2023: __v1.11.0__ released! 🔥 Updated `llama.cpp` bindings: This update includes a breaking change in the model files ( https://github.com/ggerganov/llama.cpp/pull/1405 ) - old models should still work with the `gpt4all-llama` backend.
+- 12-05-2023: __v1.10.0__ released! 🔥🔥 Updated `gpt4all` bindings. Added support for GPTNeox (experimental), RedPajama (experimental), Starcoder (experimental), Replit (experimental), MosaicML MPT. Also now `embeddings` endpoint supports tokens arrays. See the [langchain-chroma](https://github.com/go-skynet/LocalAI/tree/master/examples/langchain-chroma) example! Note - this update does NOT include https://github.com/ggerganov/llama.cpp/pull/1405 which makes models incompatible.
+- 11-05-2023: __v1.9.0__ released! 🔥 Important whisper updates ( https://github.com/go-skynet/LocalAI/pull/233 https://github.com/go-skynet/LocalAI/pull/229 ) and extended gpt4all model families support ( https://github.com/go-skynet/LocalAI/pull/232 ). Redpajama/dolly experimental ( https://github.com/go-skynet/LocalAI/pull/214 )
+- 10-05-2023: __v1.8.0__ released! 🔥 Added support for fast and accurate embeddings with `bert.cpp` ( https://github.com/go-skynet/LocalAI/pull/222 )
+- 09-05-2023: Added experimental support for transcriptions endpoint ( https://github.com/go-skynet/LocalAI/pull/211 )
+- 08-05-2023: Support for embeddings with models using the `llama.cpp` backend ( https://github.com/go-skynet/LocalAI/pull/207 )
+- 02-05-2023: Support for `rwkv.cpp` models ( https://github.com/go-skynet/LocalAI/pull/158 ) and for `/edits` endpoint
+- 01-05-2023: Support for SSE stream of tokens in `llama.cpp` backends ( https://github.com/go-skynet/LocalAI/pull/152 )
+
+Twitter: [@LocalAI_API](https://twitter.com/LocalAI_API) and [@mudler_it](https://twitter.com/mudler_it)
+
+### Blogs and articles
+
+- [Question Answering on Documents locally with LangChain, LocalAI, Chroma, and GPT4All](https://mudler.pm/posts/localai-question-answering/) by Ettore Di Giacinto
+- [Tutorial to use k8sgpt with LocalAI](https://medium.com/@tyler_97636/k8sgpt-localai-unlock-kubernetes-superpowers-for-free-584790de9b65) - excellent usecase for localAI, using AI to analyse Kubernetes clusters. by Tyller Gillson
+
+## Contribute and help
+
+To help the project you can:
+
+- Upvote the [Reddit post](https://www.reddit.com/r/selfhosted/comments/12w4p2f/localai_openai_compatible_api_to_run_llm_models/) about LocalAI.
+
+- [Hacker news post](https://news.ycombinator.com/item?id=35726934) - help us out by voting if you like this project.
+
+- If you have technological skills and want to contribute to development, have a look at the open issues. If you are new you can have a look at the [good-first-issue](https://github.com/go-skynet/LocalAI/issues?q=is%3Aissue+is%3Aopen+label%3A%22good+first+issue%22) and [help-wanted](https://github.com/go-skynet/LocalAI/issues?q=is%3Aissue+is%3Aopen+label%3A%22help+wanted%22) labels.
+
+- If you don't have technological skills you can still help improving documentation or add examples or share your user-stories with our community, any help and contribution is welcome!
 
 ## Model compatibility
 
@@ -29,14 +78,62 @@ It is compatible with the models supported by [llama.cpp](https://github.com/gge
 Tested with:
 - Vicuna
 - Alpaca
-- [GPT4ALL](https://github.com/nomic-ai/gpt4all)
-- [GPT4ALL-J](https://gpt4all.io/models/ggml-gpt4all-j.bin)
+- [GPT4ALL](https://gpt4all.io)
+- [GPT4ALL-J](https://gpt4all.io/models/ggml-gpt4all-j.bin) (no changes required)
 - Koala
 - [cerebras-GPT with ggml](https://huggingface.co/lxe/Cerebras-GPT-2.7B-Alpaca-SP-ggml)
+- WizardLM
+- [RWKV](https://github.com/BlinkDL/RWKV-LM) models with [rwkv.cpp](https://github.com/saharNooby/rwkv.cpp)
 
-It should also be compatible with StableLM and GPTNeoX ggml models (untested)
+Note: You might need to convert some models from older models to the new format, for indications, see [the README in llama.cpp](https://github.com/ggerganov/llama.cpp#using-gpt4all) for instance to run `gpt4all`.
 
-Note: You might need to convert older models to the new format, see [here](https://github.com/ggerganov/llama.cpp#using-gpt4all) for instance to run `gpt4all`.
+### RWKV
+
+<details>
+
+A full example on how to run a rwkv model is in the [examples](https://github.com/go-skynet/LocalAI/tree/master/examples/rwkv).
+
+Note: rwkv models needs to specify the backend `rwkv` in the YAML config files and have an associated tokenizer along that needs to be provided with it:
+
+```
+36464540 -rw-r--r--  1 mudler mudler 1.2G May  3 10:51 rwkv_small
+36464543 -rw-r--r--  1 mudler mudler 2.4M May  3 10:51 rwkv_small.tokenizer.json
+```
+
+</details>
+
+### Others
+
+It should also be compatible with StableLM and GPTNeoX ggml models (untested).
+
+### Hardware requirements
+
+Depending on the model you are attempting to run might need more RAM or CPU resources. Check out also [here](https://github.com/ggerganov/llama.cpp#memorydisk-requirements) for `ggml` based backends. `rwkv` is less expensive on resources.
+
+
+### Model compatibility table
+
+<details>
+
+| Backend         | Compatible models     | Completion/Chat endpoint | Audio transcription/Image | Embeddings support                | Token stream support | Github                                     | Bindings                                  |
+|-----------------|-----------------------|--------------------------|---------------------|-----------------------------------|----------------------|--------------------------------------------|-------------------------------------------|
+| llama           | Vicuna, Alpaca, LLaMa | yes                      | no                  | yes (doesn't seem to be accurate) | yes                  | https://github.com/ggerganov/llama.cpp     | https://github.com/go-skynet/go-llama.cpp |
+| gpt4all-llama   | Vicuna, Alpaca, LLaMa | yes                      | no                  | no                                | yes                  | https://github.com/nomic-ai/gpt4all        | https://github.com/go-skynet/gpt4all      |
+| gpt4all-mpt     | MPT                   | yes                      | no                  | no                                | yes                  | https://github.com/nomic-ai/gpt4all        | https://github.com/go-skynet/gpt4all      |
+| gpt4all-j       | GPT4ALL-J             | yes                      | no                  | no                                | yes                  | https://github.com/nomic-ai/gpt4all        | https://github.com/go-skynet/gpt4all      |
+| gpt2            | GPT/NeoX, Cerebras    | yes                      | no                  | no                                | no                   | https://github.com/ggerganov/ggml          | https://github.com/go-skynet/go-gpt2.cpp  |
+| dolly           | Dolly                 | yes                      | no                  | no                                | no                   | https://github.com/ggerganov/ggml          | https://github.com/go-skynet/go-gpt2.cpp  |
+| redpajama       | RedPajama             | yes                      | no                  | no                                | no                   | https://github.com/ggerganov/ggml          | https://github.com/go-skynet/go-gpt2.cpp  |
+| stableLM        | StableLM GPT/NeoX     | yes                      | no                  | no                                | no                   | https://github.com/ggerganov/ggml          | https://github.com/go-skynet/go-gpt2.cpp  |
+| replit       | Replit             | yes                      | no                  | no                                | no                   | https://github.com/ggerganov/ggml          | https://github.com/go-skynet/go-gpt2.cpp  |
+| gptneox       | GPT NeoX             | yes                      | no                  | no                                | no                   | https://github.com/ggerganov/ggml          | https://github.com/go-skynet/go-gpt2.cpp  |
+| starcoder       | Starcoder             | yes                      | no                  | no                                | no                   | https://github.com/ggerganov/ggml          | https://github.com/go-skynet/go-gpt2.cpp  |
+| bloomz          | Bloom                 | yes                      | no                  | no                                | no                   | https://github.com/NouamaneTazi/bloomz.cpp | https://github.com/go-skynet/bloomz.cpp   |
+| rwkv            | RWKV                  | yes                      | no                  | no                                | yes                  | https://github.com/saharNooby/rwkv.cpp     | https://github.com/donomii/go-rwkv.cpp    |
+| bert-embeddings | bert                  | no                       | no                  | yes                               | no                   | https://github.com/skeskinen/bert.cpp      | https://github.com/go-skynet/go-bert.cpp  |
+| whisper         | whisper               | no                       | Audio                 | no                                | no                   | https://github.com/ggerganov/whisper.cpp   | https://github.com/ggerganov/whisper.cpp  |
+| stablediffusion         | stablediffusion               | no                       | Image                 | no                                | no                   | https://github.com/EdVince/Stable-Diffusion-NCNN   | https://github.com/mudler/go-stable-diffusion  |
+</details>
 
 ## Usage
 
@@ -50,6 +147,9 @@ git clone https://github.com/go-skynet/LocalAI
 
 cd LocalAI
 
+# (optional) Checkout a specific LocalAI tag
+# git checkout -b build <TAG>
+
 # copy your models to models/
 cp your-model.bin models/
 
@@ -57,7 +157,9 @@ cp your-model.bin models/
 # vim .env
 
 # start with docker-compose
-docker-compose up -d --build
+docker-compose up -d --pull always
+# or you can build the images with:
+# docker-compose up -d --build
 
 # Now API is accessible at localhost:8080
 curl http://localhost:8080/v1/models
@@ -80,6 +182,9 @@ git clone https://github.com/go-skynet/LocalAI
 
 cd LocalAI
 
+# (optional) Checkout a specific LocalAI tag
+# git checkout -b build <TAG>
+
 # Download gpt4all-j to models/
 wget https://gpt4all.io/models/ggml-gpt4all-j.bin -O models/ggml-gpt4all-j
 
@@ -90,8 +195,9 @@ cp -rf prompt-templates/ggml-gpt4all-j.tmpl models/
 # vim .env
 
 # start with docker-compose
-docker-compose up -d --build
-
+docker-compose up -d --pull always
+# or you can build the images with:
+# docker-compose up -d --build
 # Now API is accessible at localhost:8080
 curl http://localhost:8080/v1/models
 # {"object":"list","data":[{"id":"ggml-gpt4all-j","object":"model"}]}
@@ -106,15 +212,180 @@ curl http://localhost:8080/v1/chat/completions -H "Content-Type: application/jso
 ```
 </details>
 
-## Prompt templates 
+To build locally, run `make build` (see below).
+
+### Other examples
+
+![Screenshot from 2023-04-26 23-59-55](https://user-images.githubusercontent.com/2420543/234715439-98d12e03-d3ce-4f94-ab54-2b256808e05e.png)
+
+To see other examples on how to integrate with other projects for instance for question answering or for using it with chatbot-ui, see: [examples](https://github.com/go-skynet/LocalAI/tree/master/examples/).
+
+
+### Advanced configuration
+
+LocalAI can be configured to serve user-defined models with a set of default parameters and templates.
+
+<details>
+
+You can create multiple `yaml` files in the models path or either specify a single YAML configuration file. 
+Consider the following `models` folder in the `example/chatbot-ui`:
+
+```
+base ❯ ls -liah examples/chatbot-ui/models 
+36487587 drwxr-xr-x 2 mudler mudler 4.0K May  3 12:27 .
+36487586 drwxr-xr-x 3 mudler mudler 4.0K May  3 10:42 ..
+36465214 -rw-r--r-- 1 mudler mudler   10 Apr 27 07:46 completion.tmpl
+36464855 -rw-r--r-- 1 mudler mudler 3.6G Apr 27 00:08 ggml-gpt4all-j
+36464537 -rw-r--r-- 1 mudler mudler  245 May  3 10:42 gpt-3.5-turbo.yaml
+36467388 -rw-r--r-- 1 mudler mudler  180 Apr 27 07:46 gpt4all.tmpl
+```
+
+In the `gpt-3.5-turbo.yaml` file it is defined the `gpt-3.5-turbo` model which is an alias to use `gpt4all-j` with pre-defined options.
+
+For instance, consider the following that declares `gpt-3.5-turbo` backed by the `ggml-gpt4all-j` model:
+
+```yaml
+name: gpt-3.5-turbo
+# Default model parameters
+parameters:
+  # Relative to the models path
+  model: ggml-gpt4all-j
+  # temperature
+  temperature: 0.3
+  # all the OpenAI request options here..
+
+# Default context size
+context_size: 512
+threads: 10
+# Define a backend (optional). By default it will try to guess the backend the first time the model is interacted with.
+backend: gptj # available: llama, stablelm, gpt2, gptj rwkv
+# stopwords (if supported by the backend)
+stopwords:
+- "HUMAN:"
+- "### Response:"
+# define chat roles
+roles:
+  user: "HUMAN:"
+  system: "GPT:"
+template:
+  # template file ".tmpl" with the prompt template to use by default on the endpoint call. Note there is no extension in the files
+  completion: completion
+  chat: ggml-gpt4all-j
+```
+
+Specifying a `config-file` via CLI allows to declare models in a single file as a list, for instance:
+
+```yaml
+- name: list1
+  parameters:
+    model: testmodel
+  context_size: 512
+  threads: 10
+  stopwords:
+  - "HUMAN:"
+  - "### Response:"
+  roles:
+    user: "HUMAN:"
+    system: "GPT:"
+  template:
+    completion: completion
+    chat: ggml-gpt4all-j
+- name: list2
+  parameters:
+    model: testmodel
+  context_size: 512
+  threads: 10
+  stopwords:
+  - "HUMAN:"
+  - "### Response:"
+  roles:
+    user: "HUMAN:"
+    system: "GPT:"
+  template:
+    completion: completion
+   chat: ggml-gpt4all-j
+```
+
+See also [chatbot-ui](https://github.com/go-skynet/LocalAI/tree/master/examples/chatbot-ui) as an example on how to use config files.
+
+### Full config model file reference
+
+```yaml
+name: gpt-3.5-turbo
+
+# Default model parameters
+parameters:
+  # Relative to the models path
+  model: ggml-gpt4all-j
+  # temperature
+  temperature: 0.3
+  # all the OpenAI request options here..
+  top_k: 
+  top_p: 
+  max_tokens:
+  batch:
+  f16: true
+  ignore_eos: true
+  n_keep: 10
+  seed: 
+  mode: 
+  step: 
+
+# Default context size
+context_size: 512
+# Default number of threads
+threads: 10
+# Define a backend (optional). By default it will try to guess the backend the first time the model is interacted with.
+backend: gptj # available: llama, stablelm, gpt2, gptj rwkv
+# stopwords (if supported by the backend)
+stopwords:
+- "HUMAN:"
+- "### Response:"
+# string to trim space to
+trimspace:
+- string
+# Strings to cut from the response
+cutstrings:
+- "string"
+# define chat roles
+roles:
+  user: "HUMAN:"
+  system: "GPT:"
+  assistant: "ASSISTANT:"
+template:
+  # template file ".tmpl" with the prompt template to use by default on the endpoint call. Note there is no extension in the files
+  completion: completion
+  chat: ggml-gpt4all-j
+  edit: edit_template
+
+# Enable F16 if backend supports it
+f16: true
+# Enable debugging
+debug: true
+# Enable embeddings
+embeddings: true
+# Mirostat configuration (llama.cpp only)
+mirostat_eta: 0.8
+mirostat_tau: 0.9
+mirostat: 1
+
+# GPU Layers (only used when built with cublas)
+gpu_layers: 22
+
+# Directory used to store additional assets (used for stablediffusion)
+asset_dir: ""
+```
+</details>
+
+### Prompt templates 
 
 The API doesn't inject a default prompt for talking to the model. You have to use a prompt similar to what's described in the standford-alpaca docs: https://github.com/tatsu-lab/stanford_alpaca#data-release.
 
 <details>
-You can use a default template for every model present in your model path, by creating a corresponding file with the `.tmpl` suffix next to your model. For instance, if the model is called `foo.bin`, you can create a sibiling file, `foo.bin.tmpl` which will be used as a default prompt, for instance this can be used with alpaca:
+You can use a default template for every model present in your model path, by creating a corresponding file with the `.tmpl` suffix next to your model. For instance, if the model is called `foo.bin`, you can create a sibling file, `foo.bin.tmpl` which will be used as a default prompt and can be used with alpaca:
 
 ```
-Below is an instruction that describes a task. Write a response that appropriately completes the request.
+The below instruction describes a task. Write a response that appropriately completes the request.
 
 ### Instruction:
 {{.Input}}
@@ -122,13 +393,55 @@ Below is an instruction that describes a task. Write a response that appropriate
 ### Response:
 ```
 
-See the [prompt-templates](https://github.com/go-skynet/LocalAI/tree/master/prompt-templates) directory in this repository for templates for most popular models.
+See the [prompt-templates](https://github.com/go-skynet/LocalAI/tree/master/prompt-templates) directory in this repository for templates for some of the most popular models.
+
+
+For the edit endpoint, an example template for alpaca-based models can be:
+
+```yaml
+Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request.
+
+### Instruction:
+{{.Instruction}}
+
+### Input:
+{{.Input}}
+
+### Response:
+```
 
 </details>
 
-## API
+### CLI
 
-`LocalAI` provides an API for running text generation as a service, that follows the OpenAI reference and can be used as a drop-in. The models once loaded the first time will be kept in memory.
+You can control LocalAI with command line arguments, to specify a binding address, or the number of threads.
+
+<details>
+
+Usage:
+
+```
+local-ai --models-path <model_path> [--address <address>] [--threads <num_threads>]
+```
+
+| Parameter    | Environment Variable | Default Value | Description                            |
+| ------------ | -------------------- | ------------- | -------------------------------------- |
+| models-path        | MODELS_PATH           |               | The path where you have models (ending with `.bin`).      |
+| threads      | THREADS              | Number of Physical cores     | The number of threads to use for text generation. |
+| address      | ADDRESS              | :8080         | The address and port to listen on. |
+| context-size | CONTEXT_SIZE         | 512           | Default token context size. |
+| debug | DEBUG         | false           | Enable debug mode. |
+| config-file | CONFIG_FILE         | empty           | Path to a LocalAI config file. |
+| upload_limit | UPLOAD_LIMIT         | 5MB           | Upload limit for whisper. |
+| image-dir | CONFIG_FILE         | empty           | Image directory to store and serve processed images. |
+
+</details>
+
+## Setup
+
+Currently LocalAI comes as a container image and can be used with docker or a container engine of choice. You can check out all the available images with corresponding tags [here](https://quay.io/repository/go-skynet/local-ai?tab=tags&tag=latest).
+
+### Docker
 
 <details>
 Example of starting the API with `docker`:
@@ -137,7 +450,7 @@ Example of starting the API with `docker`:
 docker run -p 8080:8080 -ti --rm quay.io/go-skynet/local-ai:latest --models-path /path/to/models --context-size 700 --threads 4
 ```
 
-And you'll see:
+You should see:
 ```
 ┌───────────────────────────────────────────────────┐ 
 │                   Fiber v2.42.0                   │ 
@@ -149,27 +462,165 @@ And you'll see:
 └───────────────────────────────────────────────────┘ 
 ```
 
-You can control the API server options with command line arguments:
+</details>
+
+### Build locally
+
+<details>
+
+In order to build the `LocalAI` container image locally you can use `docker`:
 
 ```
-local-api --models-path <model_path> [--address <address>] [--threads <num_threads>]
+# build the image
+docker build -t LocalAI .
+docker run LocalAI
 ```
 
-The API takes takes the following parameters:
+Or you can build the binary with `make`:
 
-| Parameter    | Environment Variable | Default Value | Description                            |
-| ------------ | -------------------- | ------------- | -------------------------------------- |
-| models-path        | MODELS_PATH           |               | The path where you have models (ending with `.bin`).      |
-| threads      | THREADS              | Number of Physical cores     | The number of threads to use for text generation. |
-| address      | ADDRESS              | :8080         | The address and port to listen on. |
-| context-size | CONTEXT_SIZE         | 512           | Default token context size. |
-| debug | DEBUG         | false           | Enable debug mode. |
-
-Once the server is running, you can start making requests to it using HTTP, using the OpenAI API. 
+```
+make build
+```
 
 </details>
 
-### Supported OpenAI API endpoints
+### Build on mac
+
+Building on Mac (M1 or M2) works, but you may need to install some prerequisites using `brew`. 
+
+<details>
+
+The below has been tested by one mac user and found to work. Note that this doesn't use docker to run the server:
+
+```
+# install build dependencies
+brew install cmake
+brew install go
+
+# clone the repo
+git clone https://github.com/go-skynet/LocalAI.git
+
+cd LocalAI
+
+# build the binary
+make build
+
+# Download gpt4all-j to models/
+wget https://gpt4all.io/models/ggml-gpt4all-j.bin -O models/ggml-gpt4all-j
+
+# Use a template from the examples
+cp -rf prompt-templates/ggml-gpt4all-j.tmpl models/
+
+# Run LocalAI
+./local-ai --models-path ./models/ --debug
+
+# Now API is accessible at localhost:8080
+curl http://localhost:8080/v1/models
+
+curl http://localhost:8080/v1/chat/completions -H "Content-Type: application/json" -d '{
+     "model": "ggml-gpt4all-j",
+     "messages": [{"role": "user", "content": "How are you?"}],
+     "temperature": 0.9 
+   }'
+```
+
+</details>
+
+### Build with Image generation support
+
+<details>
+
+**Requirements**: OpenCV, Gomp
+
+Image generation is experimental and requires `GO_TAGS=stablediffusion` to be set during build:
+
+```
+make GO_TAGS=stablediffusion rebuild
+```
+
+</details>
+
+### Accelleration
+
+#### OpenBLAS
+
+<details>
+
+Requirements: OpenBLAS
+
+```
+make BUILD_TYPE=openblas build
+```
+
+</details>
+
+#### CuBLAS
+
+<details>
+
+Requirement: Nvidia CUDA toolkit
+
+Note: CuBLAS support is experimental, and has not been tested on real HW. please report any issues you find!
+
+```
+make BUILD_TYPE=cublas build
+```
+
+</details>
+
+### Windows compatibility
+
+It should work, however you need to make sure you give enough resources to the container. See https://github.com/go-skynet/LocalAI/issues/2
+
+### Run LocalAI in Kubernetes
+
+LocalAI can be installed inside Kubernetes with helm.
+
+<details>
+
+1. Add the helm repo
+    ```bash
+    helm repo add go-skynet https://go-skynet.github.io/helm-charts/
+    ```
+1. Create a values files with your settings:
+```bash
+cat <<EOF > values.yaml
+deployment:
+  image: quay.io/go-skynet/local-ai:latest
+  env:
+    threads: 4
+    contextSize: 1024
+    modelsPath: "/models"
+# Optionally create a PVC, mount the PV to the LocalAI Deployment,
+# and download a model to prepopulate the models directory
+modelsVolume:
+  enabled: true
+  url: "https://gpt4all.io/models/ggml-gpt4all-j.bin"
+  pvc:
+    size: 6Gi
+    accessModes:
+    - ReadWriteOnce
+  auth:
+    # Optional value for HTTP basic access authentication header
+    basic: "" # 'username:password' base64 encoded
+service:
+  type: ClusterIP
+  annotations: {}
+  # If using an AWS load balancer, you'll need to override the default 60s load balancer idle timeout
+  # service.beta.kubernetes.io/aws-load-balancer-connection-idle-timeout: "1200"
+EOF
+```
+3. Install the helm chart:
+```bash
+helm repo update
+helm install local-ai go-skynet/local-ai -f values.yaml
+```
+
+Check out also the [helm chart repository on GitHub](https://github.com/go-skynet/helm-charts).
+
+</details>
+
+## Supported OpenAI API endpoints
 
 You can check out the [OpenAI API reference](https://platform.openai.com/docs/api-reference/chat/create). 
 
@@ -177,10 +628,10 @@ Following the list of endpoints/parameters supported.
 
 Note:
 
-- You can also specify the model a part of the OpenAI token.
+- You can also specify the model as part of the OpenAI token.
 - If only one model is available, the API will use it for all the requests.
 
-#### Chat completions
+### Chat completions
 
 <details>
 For example, to generate a chat completion, you can send a POST request to the `/v1/chat/completions` endpoint with the instruction as the request body:
@@ -196,10 +647,30 @@ curl http://localhost:8080/v1/chat/completions -H "Content-Type: application/jso
 Available additional parameters: `top_p`, `top_k`, `max_tokens`
 </details>
 
-#### Completions
+### Edit completions
 
 <details>
-For example, to generate a completion, you can send a POST request to the `/v1/completions` endpoint with the instruction as the request body:
+To generate an edit completion you can send a POST request to the `/v1/edits` endpoint with the instruction as the request body:
+
+```
+curl http://localhost:8080/v1/edits -H "Content-Type: application/json" -d '{
+     "model": "ggml-koala-7b-model-q4_0-r2.bin",
+     "instruction": "rephrase",
+     "input": "Black cat jumped out of the window",
+     "temperature": 0.7
+   }'
+```
+
+Available additional parameters: `top_p`, `top_k`, `max_tokens`.
+
+</details>
+
+### Completions
+
+<details>
+
+To generate a completion, you can send a POST request to the `/v1/completions` endpoint with the instruction as per the request body:
+
 ```
 curl http://localhost:8080/v1/completions -H "Content-Type: application/json" -d '{
      "model": "ggml-koala-7b-model-q4_0-r2.bin",
@@ -212,7 +683,7 @@ Available additional parameters: `top_p`, `top_k`, `max_tokens`
 
 </details>
 
-#### List models
+### List models
 
 <details>
 You can list all the models available with:
@@ -223,63 +694,129 @@ curl http://localhost:8080/v1/models
 
 </details>
 
-## Using other models
+### Embeddings
 
-gpt4all (https://github.com/nomic-ai/gpt4all) works as well, however the original model needs to be converted (same applies for old alpaca models, too):
+OpenAI docs: https://platform.openai.com/docs/api-reference/embeddings
+
+<details>
+
+The embedding endpoint is experimental and enabled only if the model is configured with `embeddings: true` in its `yaml` file, for example:
+
+```yaml
+name: text-embedding-ada-002
+parameters:
+  model: bert
+embeddings: true
+backend: "bert-embeddings"
+```
+
+There is an example available [here](https://github.com/go-skynet/LocalAI/tree/master/examples/query_data/).
+
+Note: embeddings is supported only with `llama.cpp` compatible models and `bert` models. bert is more performant and available independently of the LLM model.
+
+</details>
+
+### Transcriptions endpoint
+
+<details>
+
+Note: requires ffmpeg in the container image, which is currently not shipped due to licensing issues. We will prepare separated images with ffmpeg. (stay tuned!)
+
+Download one of the models from https://huggingface.co/ggerganov/whisper.cpp/tree/main in the `models` folder, and create a YAML file for your model:
+
+```yaml
+name: whisper-1
+backend: whisper
+parameters:
+  model: whisper-en
+```
+
+The transcriptions endpoint then can be tested like so:
+```
+wget --quiet --show-progress -O gb1.ogg https://upload.wikimedia.org/wikipedia/commons/1/1f/George_W_Bush_Columbia_FINAL.ogg
+
+curl http://localhost:8080/v1/audio/transcriptions -H "Content-Type: multipart/form-data" -F file="@$PWD/gb1.ogg" -F model="whisper-1"                                                     
+
+{"text":"My fellow Americans, this day has brought terrible news and great sadness to our country.At nine o'clock this morning, Mission Control in Houston lost contact with our Space ShuttleColumbia.A short time later, debris was seen falling from the skies above Texas.The Columbia's lost.There are no survivors.One board was a crew of seven.Colonel Rick Husband, Lieutenant Colonel Michael Anderson, Commander Laurel Clark, Captain DavidBrown, Commander William McCool, Dr. Kultna Shavla, and Elon Ramon, a colonel in the IsraeliAir Force.These men and women assumed great risk in the service to all humanity.In an age when spaceflight has come to seem almost routine, it is easy to overlook thedangers of travel by rocket and the difficulties of navigating the fierce outer atmosphere ofthe Earth.These astronauts knew the dangers, and they faced them willingly, knowing they had a highand noble purpose in life.Because of their courage and daring and idealism, we will miss them all the more.All Americans today are thinking as well of the families of these men and women who havebeen given this sudden shock and grief.You're not alone.Our entire nation agrees with you, and those you loved will always have the respect andgratitude of this country.The cause in which they died will continue.Mankind has led into the darkness beyond our world by the inspiration of discovery andthe longing to understand.Our journey into space will go on.In the skies today, we saw destruction and tragedy.As farther than we can see, there is comfort and hope.In the words of the prophet Isaiah, \"Lift your eyes and look to the heavens who createdall these, he who brings out the starry hosts one by one and calls them each by name.\"Because of his great power and mighty strength, not one of them is missing.The same creator who names the stars also knows the names of the seven souls we mourntoday.The crew of the shuttle Columbia did not return safely to Earth yet we can pray that all aresafely home.May God bless the grieving families and may God continue to bless America.[BLANK_AUDIO]"}
+```
+
+</details>
+  
+### Image generation
+
+OpenAI docs: https://platform.openai.com/docs/api-reference/images/create
+
+LocalAI supports generating images with Stable diffusion, running on CPU.
+
+| mode=0                                                                                                                | mode=1 (winograd/sgemm)                                                                                                                |
+|------------------------------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------------|
+| ![test](https://github.com/go-skynet/LocalAI/assets/2420543/7145bdee-4134-45bb-84d4-f11cb08a5638)                      | ![b643343452981](https://github.com/go-skynet/LocalAI/assets/2420543/abf14de1-4f50-4715-aaa4-411d703a942a)          |
+| ![b6441997879](https://github.com/go-skynet/LocalAI/assets/2420543/d50af51c-51b7-4f39-b6c2-bf04c403894c)              | ![winograd2](https://github.com/go-skynet/LocalAI/assets/2420543/1935a69a-ecce-4afc-a099-1ac28cb649b3)                |
+| ![winograd](https://github.com/go-skynet/LocalAI/assets/2420543/1979a8c4-a70d-4602-95ed-642f382f6c6a)                | ![winograd3](https://github.com/go-skynet/LocalAI/assets/2420543/e6d184d4-5002-408f-b564-163986e1bdfb)                |
+
+<details>
+
+To generate an image you can send a POST request to the `/v1/images/generations` endpoint with the instruction as the request body:
 
 ```bash
-wget -O tokenizer.model https://huggingface.co/decapoda-research/llama-30b-hf/resolve/main/tokenizer.model
-mkdir models
-cp gpt4all.. models/
-git clone https://gist.github.com/eiz/828bddec6162a023114ce19146cb2b82
-pip install sentencepiece
-python 828bddec6162a023114ce19146cb2b82/gistfile1.txt models tokenizer.model
-# There will be a new model with the ".tmp" extension, you have to use that one!
+# 512x512 is supported too
+curl http://localhost:8080/v1/images/generations -H "Content-Type: application/json" -d '{
+            "prompt": "A cute baby sea otter",
+            "size": "256x256" 
+          }'
 ```
 
+Available additional parameters: `mode`, `step`.
 
-## Helm Chart Installation (run LocalAI in Kubernetes)
-The local-ai Helm chart supports two options for the LocalAI server's models directory:
-1. Basic deployment with no persistent volume. You must manually update the Deployment to configure your own models directory.
+Note: To set a negative prompt, you can split the prompt with `|`, for instance: `a cute baby sea otter|malformed`.
 
-    Install the chart with `.Values.deployment.volumes.enabled == false` and `.Values.dataVolume.enabled == false`.
-
-2. Advanced, two-phase deployment to provision the models directory using a DataVolume. Requires [Containerized Data Importer CDI](https://github.com/kubevirt/containerized-data-importer) to be pre-installed in your cluster.
-
-    First, install the chart with `.Values.deployment.volumes.enabled == false` and `.Values.dataVolume.enabled == true`:
-    ```bash
-    helm install local-ai charts/local-ai -n local-ai --create-namespace
-    ```
-    Wait for CDI to create an importer Pod for the DataVolume and for the importer pod to finish provisioning the model archive inside the PV.
-
-    Once the PV is provisioned and the importer Pod removed, set `.Values.deployment.volumes.enabled == true` and `.Values.dataVolume.enabled == false` and upgrade the chart:
-    ```bash
-    helm upgrade local-ai -n local-ai charts/local-ai
-    ```
-    This will update the local-ai Deployment to mount the PV that was provisioned by the DataVolume.
-
-## Windows compatibility
-
-It should work, however you need to make sure you give enough resources to the container. See https://github.com/go-skynet/LocalAI/issues/2
-
-## Build locally
-
-Pre-built images might fit well for most of the modern hardware, however you can and might need to build the images manually.
-
-In order to build the `LocalAI` container image locally you can use `docker`:
-
-```
-# build the image
-docker build -t LocalAI .
-docker run LocalAI
+```bash
+curl http://localhost:8080/v1/images/generations -H "Content-Type: application/json" -d '{
+            "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",
+            "size": "256x256"
+          }'
 ```
 
-Or build the binary with `make`:
+Note: image generator supports images up to 512x512. You can use other tools however to upscale the image, for instance: https://github.com/upscayl/upscayl.
+
+#### Setup
+
+Note: In order to use the `images/generation` endpoint, you need to build LocalAI with `GO_TAGS=stablediffusion`.
+
+1. Create a model file `stablediffusion.yaml` in the models folder:
+
+```yaml
+name: stablediffusion
+backend: stablediffusion
+asset_dir: stablediffusion_assets
+```
+2. Create a `stablediffusion_assets` directory inside your `models` directory
+3. Download the ncnn assets from https://github.com/EdVince/Stable-Diffusion-NCNN#out-of-box and place them in `stablediffusion_assets`.
+
+The models directory should look like the following:
 
 ```
-make build
+models
+├── stablediffusion_assets
+│   ├── AutoencoderKL-256-256-fp16-opt.param
+│   ├── AutoencoderKL-512-512-fp16-opt.param
+│   ├── AutoencoderKL-base-fp16.param
+│   ├── AutoencoderKL-encoder-512-512-fp16.bin
+│   ├── AutoencoderKL-fp16.bin
+│   ├── FrozenCLIPEmbedder-fp16.bin
+│   ├── FrozenCLIPEmbedder-fp16.param
+│   ├── log_sigmas.bin
+│   ├── tmp-AutoencoderKL-encoder-256-256-fp16.param
+│   ├── UNetModel-256-256-MHA-fp16-opt.param
+│   ├── UNetModel-512-512-MHA-fp16-opt.param
+│   ├── UNetModel-base-MHA-fp16.param
+│   ├── UNetModel-MHA-fp16.bin
+│   └── vocab.txt
+└── stablediffusion.yaml
 ```
 
+</details>
+
 ## Frequently asked questions
 
 Here are answers to some of the most common questions.
@@ -316,14 +853,14 @@ Yes! If the client uses OpenAI and supports setting a different base URL to send
 
 <details>
 
-Not currently, as ggml doesn't support GPUs yet: https://github.com/ggerganov/llama.cpp/discussions/915.
+There is partial GPU support, see build instructions above.
 
 </details>
 
 ### Where is the webUI? 
 
 <details> 
-We are working on to have a good out of the box experience - however as LocalAI is an API you can already plug it into existing projects that provides are UI interfaces to OpenAI's APIs. There are several already on github, and should be compatible with LocalAI already (as it mimics the OpenAI API)
+There is the availability of localai-webui and chatbot-ui in the examples section and can be setup as per the instructions. However as LocalAI is an API you can already plug it into existing projects that provides are UI interfaces to OpenAI's APIs. There are several already on github, and should be compatible with LocalAI already (as it mimics the OpenAI API)
 
 </details>
 
@@ -335,24 +872,64 @@ AutoGPT currently doesn't allow to set a different API URL, but there is a PR op
 
 </details>
 
+## Projects already using LocalAI to run local models
+
+Feel free to open up a PR to get your project listed!
+
+- [Kairos](https://github.com/kairos-io/kairos)
+- [k8sgpt](https://github.com/k8sgpt-ai/k8sgpt#running-local-models)
+- [Spark](https://github.com/cedriking/spark)
+
+## Blog posts and other articles
+
+- https://medium.com/@tyler_97636/k8sgpt-localai-unlock-kubernetes-superpowers-for-free-584790de9b65
+- https://kairos.io/docs/examples/localai/
 
 ## Short-term roadmap
 
 - [x] Mimic OpenAI API (https://github.com/go-skynet/LocalAI/issues/10)
 - [ ] Binary releases (https://github.com/go-skynet/LocalAI/issues/6)
-- [ ] Upstream our golang bindings to llama.cpp (https://github.com/ggerganov/llama.cpp/issues/351)
+- [ ] Upstream our golang bindings to llama.cpp (https://github.com/ggerganov/llama.cpp/issues/351) and [gpt4all](https://github.com/go-skynet/LocalAI/issues/85)
 - [x] Multi-model support
-- [ ] Have a webUI!
-- [ ] Allow configuration of defaults for models.
-- [ ] Enable automatic downloading of models from a curated gallery, with only free-licensed models.
+- [x] Have a webUI!
+- [x] Allow configuration of defaults for models.
+- [x] Support for embeddings
+- [x] Support for audio transcription with https://github.com/ggerganov/whisper.cpp
+- [ ] GPU/CUDA support ( https://github.com/go-skynet/LocalAI/issues/69 )
+- [ ] Enable automatic downloading of models from a curated gallery, with only free-licensed models, directly from the webui.
+
+## Star history
+
+[![LocalAI Star history Chart](https://api.star-history.com/svg?repos=go-skynet/LocalAI&type=Date)](https://star-history.com/#go-skynet/LocalAI&Date)
 
 ## License
 
+LocalAI is a community-driven project. It was initially created by [Ettore Di Giacinto](https://github.com/mudler/) at the [SpectroCloud OSS Office](https://github.com/spectrocloud).
+
 MIT
 
+## Golang bindings used
+
+- [go-skynet/go-llama.cpp](https://github.com/go-skynet/go-llama.cpp)
+- [go-skynet/go-gpt4all-j.cpp](https://github.com/go-skynet/go-gpt4all-j.cpp)
+- [go-skynet/go-gpt2.cpp](https://github.com/go-skynet/go-gpt2.cpp)
+- [go-skynet/go-bert.cpp](https://github.com/go-skynet/go-bert.cpp)
+- [donomii/go-rwkv.cpp](https://github.com/donomii/go-rwkv.cpp)
+
 ## Acknowledgements
 
+LocalAI couldn't have been built without the help of great software already available from the community. Thank you!
+
 - [llama.cpp](https://github.com/ggerganov/llama.cpp)
 - https://github.com/tatsu-lab/stanford_alpaca
 - https://github.com/cornelk/llama-go for the initial ideas
-- https://github.com/antimatter15/alpaca.cpp for the light model version (this is compatible and tested only with that checkpoint model!)
+- https://github.com/antimatter15/alpaca.cpp
+- https://github.com/EdVince/Stable-Diffusion-NCNN
+- https://github.com/ggerganov/whisper.cpp
+- https://github.com/saharNooby/rwkv.cpp
+
+## Contributors
+
+<a href="https://github.com/go-skynet/LocalAI/graphs/contributors">
+  <img src="https://contrib.rocks/image?repo=go-skynet/LocalAI" />
+</a>

api/api.go

@@ -1,392 +1,18 @@
 package api
 
 import (
-	"encoding/json"
 	"errors"
-	"fmt"
-	"strings"
-	"sync"
 
 	model "github.com/go-skynet/LocalAI/pkg/model"
-	gpt2 "github.com/go-skynet/go-gpt2.cpp"
-	gptj "github.com/go-skynet/go-gpt4all-j.cpp"
-	llama "github.com/go-skynet/go-llama.cpp"
 	"github.com/gofiber/fiber/v2"
 	"github.com/gofiber/fiber/v2/middleware/cors"
+	"github.com/gofiber/fiber/v2/middleware/logger"
 	"github.com/gofiber/fiber/v2/middleware/recover"
 	"github.com/rs/zerolog"
 	"github.com/rs/zerolog/log"
 )
 
-// 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 OpenAIResponse struct {
-	Created int      `json:"created,omitempty"`
-	Object  string   `json:"chat.completion,omitempty"`
-	ID      string   `json:"id,omitempty"`
-	Model   string   `json:"model,omitempty"`
-	Choices []Choice `json:"choices,omitempty"`
-}
-
-type Choice struct {
-	Index        int      `json:"index,omitempty"`
-	FinishReason string   `json:"finish_reason,omitempty"`
-	Message      *Message `json:"message,omitempty"`
-	Text         string   `json:"text,omitempty"`
-}
-
-type Message struct {
-	Role    string `json:"role,omitempty"`
-	Content string `json:"content,omitempty"`
-}
-
-type OpenAIModel struct {
-	ID     string `json:"id"`
-	Object string `json:"object"`
-}
-
-type OpenAIRequest struct {
-	Model string `json:"model"`
-
-	// Prompt is read only by completion API calls
-	Prompt string `json:"prompt"`
-
-	Stop string `json:"stop"`
-
-	// Messages is read only by chat/completion API calls
-	Messages []Message `json:"messages"`
-
-	Echo bool `json:"echo"`
-	// Common options between all the API calls
-	TopP        float64 `json:"top_p"`
-	TopK        int     `json:"top_k"`
-	Temperature float64 `json:"temperature"`
-	Maxtokens   int     `json:"max_tokens"`
-
-	N int `json:"n"`
-
-	// Custom parameters - not present in the OpenAI API
-	Batch         int     `json:"batch"`
-	F16           bool    `json:"f16kv"`
-	IgnoreEOS     bool    `json:"ignore_eos"`
-	RepeatPenalty float64 `json:"repeat_penalty"`
-	Keep          int     `json:"n_keep"`
-
-	Seed int `json:"seed"`
-}
-
-// https://platform.openai.com/docs/api-reference/completions
-func openAIEndpoint(chat, debug bool, loader *model.ModelLoader, threads, ctx int, f16 bool, mutexMap *sync.Mutex, mutexes map[string]*sync.Mutex) func(c *fiber.Ctx) error {
-	return func(c *fiber.Ctx) error {
-		var err error
-		var model *llama.LLama
-		var gptModel *gptj.GPTJ
-		var gpt2Model *gpt2.GPT2
-		var stableLMModel *gpt2.StableLM
-
-		input := new(OpenAIRequest)
-		// Get input data from the request body
-		if err := c.BodyParser(input); err != nil {
-			return err
-		}
-		modelFile := input.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 == "" {
-			models, _ := loader.ListModels()
-			if len(models) > 0 {
-				modelFile = models[0]
-				log.Debug().Msgf("No model specified, using: %s", modelFile)
-			}
-		}
-
-		// If no model is found or specified, we bail out
-		if modelFile == "" && !bearerExists {
-			return 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
-		}
-
-		// Try to load the model
-		var llamaerr, gpt2err, gptjerr, stableerr error
-		llamaOpts := []llama.ModelOption{}
-		if ctx != 0 {
-			llamaOpts = append(llamaOpts, llama.SetContext(ctx))
-		}
-		if f16 {
-			llamaOpts = append(llamaOpts, llama.EnableF16Memory)
-		}
-
-		// TODO: this is ugly, better identifying the model somehow! however, it is a good stab for a first implementation..
-		model, llamaerr = loader.LoadLLaMAModel(modelFile, llamaOpts...)
-		if llamaerr != nil {
-			gptModel, gptjerr = loader.LoadGPTJModel(modelFile)
-			if gptjerr != nil {
-				gpt2Model, gpt2err = loader.LoadGPT2Model(modelFile)
-				if gpt2err != nil {
-					stableLMModel, stableerr = loader.LoadStableLMModel(modelFile)
-					if stableerr != nil {
-						return fmt.Errorf("llama: %s gpt: %s gpt2: %s stableLM: %s", llamaerr.Error(), gptjerr.Error(), gpt2err.Error(), stableerr.Error()) // llama failed first, so we want to catch both errors
-					}
-				}
-			}
-		}
-
-		// 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()
-
-		// Set the parameters for the language model prediction
-		topP := input.TopP
-		if topP == 0 {
-			topP = 0.7
-		}
-		topK := input.TopK
-		if topK == 0 {
-			topK = 80
-		}
-
-		temperature := input.Temperature
-		if temperature == 0 {
-			temperature = 0.9
-		}
-
-		tokens := input.Maxtokens
-		if tokens == 0 {
-			tokens = 512
-		}
-
-		predInput := input.Prompt
-		if chat {
-			mess := []string{}
-			// TODO: encode roles
-			for _, i := range input.Messages {
-				mess = append(mess, i.Content)
-			}
-
-			predInput = strings.Join(mess, "\n")
-		}
-
-		// A model can have a "file.bin.tmpl" file associated with a prompt template prefix
-		templatedInput, err := loader.TemplatePrefix(modelFile, struct {
-			Input string
-		}{Input: predInput})
-		if err == nil {
-			predInput = templatedInput
-			log.Debug().Msgf("Template found, input modified to: %s", predInput)
-		}
-
-		result := []Choice{}
-
-		n := input.N
-
-		if input.N == 0 {
-			n = 1
-		}
-
-		var predFunc func() (string, error)
-		switch {
-		case stableLMModel != nil:
-			predFunc = func() (string, error) {
-				// Generate the prediction using the language model
-				predictOptions := []gpt2.PredictOption{
-					gpt2.SetTemperature(temperature),
-					gpt2.SetTopP(topP),
-					gpt2.SetTopK(topK),
-					gpt2.SetTokens(tokens),
-					gpt2.SetThreads(threads),
-				}
-
-				if input.Batch != 0 {
-					predictOptions = append(predictOptions, gpt2.SetBatch(input.Batch))
-				}
-
-				if input.Seed != 0 {
-					predictOptions = append(predictOptions, gpt2.SetSeed(input.Seed))
-				}
-
-				return stableLMModel.Predict(
-					predInput,
-					predictOptions...,
-				)
-			}
-		case gpt2Model != nil:
-			predFunc = func() (string, error) {
-				// Generate the prediction using the language model
-				predictOptions := []gpt2.PredictOption{
-					gpt2.SetTemperature(temperature),
-					gpt2.SetTopP(topP),
-					gpt2.SetTopK(topK),
-					gpt2.SetTokens(tokens),
-					gpt2.SetThreads(threads),
-				}
-
-				if input.Batch != 0 {
-					predictOptions = append(predictOptions, gpt2.SetBatch(input.Batch))
-				}
-
-				if input.Seed != 0 {
-					predictOptions = append(predictOptions, gpt2.SetSeed(input.Seed))
-				}
-
-				return gpt2Model.Predict(
-					predInput,
-					predictOptions...,
-				)
-			}
-		case gptModel != nil:
-			predFunc = func() (string, error) {
-				// Generate the prediction using the language model
-				predictOptions := []gptj.PredictOption{
-					gptj.SetTemperature(temperature),
-					gptj.SetTopP(topP),
-					gptj.SetTopK(topK),
-					gptj.SetTokens(tokens),
-					gptj.SetThreads(threads),
-				}
-
-				if input.Batch != 0 {
-					predictOptions = append(predictOptions, gptj.SetBatch(input.Batch))
-				}
-
-				if input.Seed != 0 {
-					predictOptions = append(predictOptions, gptj.SetSeed(input.Seed))
-				}
-
-				return gptModel.Predict(
-					predInput,
-					predictOptions...,
-				)
-			}
-		case model != nil:
-			predFunc = func() (string, error) {
-				// Generate the prediction using the language model
-				predictOptions := []llama.PredictOption{
-					llama.SetTemperature(temperature),
-					llama.SetTopP(topP),
-					llama.SetTopK(topK),
-					llama.SetTokens(tokens),
-					llama.SetThreads(threads),
-				}
-
-				if debug {
-					predictOptions = append(predictOptions, llama.Debug)
-				}
-
-				if input.Stop != "" {
-					predictOptions = append(predictOptions, llama.SetStopWords(input.Stop))
-				}
-
-				if input.RepeatPenalty != 0 {
-					predictOptions = append(predictOptions, llama.SetPenalty(input.RepeatPenalty))
-				}
-
-				if input.Keep != 0 {
-					predictOptions = append(predictOptions, llama.SetNKeep(input.Keep))
-				}
-
-				if input.Batch != 0 {
-					predictOptions = append(predictOptions, llama.SetBatch(input.Batch))
-				}
-
-				if input.F16 {
-					predictOptions = append(predictOptions, llama.EnableF16KV)
-				}
-
-				if input.IgnoreEOS {
-					predictOptions = append(predictOptions, llama.IgnoreEOS)
-				}
-
-				if input.Seed != 0 {
-					predictOptions = append(predictOptions, llama.SetSeed(input.Seed))
-				}
-
-				return model.Predict(
-					predInput,
-					predictOptions...,
-				)
-			}
-		}
-
-		for i := 0; i < n; i++ {
-			prediction, err := predFunc()
-			if err != nil {
-				return err
-			}
-
-			if input.Echo {
-				prediction = predInput + prediction
-			}
-
-			if chat {
-				result = append(result, Choice{Message: &Message{Role: "assistant", Content: prediction}})
-			} else {
-				result = append(result, Choice{Text: prediction})
-			}
-		}
-
-		jsonResult, _ := json.Marshal(result)
-		log.Debug().Msgf("Response: %s", jsonResult)
-
-		// Return the prediction in the response body
-		return c.JSON(OpenAIResponse{
-			Model:   input.Model, // we have to return what the user sent here, due to OpenAI spec.
-			Choices: result,
-		})
-	}
-}
-
-func listModels(loader *model.ModelLoader) func(ctx *fiber.Ctx) error {
-	return func(c *fiber.Ctx) error {
-		models, err := loader.ListModels()
-		if err != nil {
-			return err
-		}
-
-		dataModels := []OpenAIModel{}
-		for _, m := range models {
-			dataModels = append(dataModels, OpenAIModel{ID: m, Object: "model"})
-		}
-		return c.JSON(struct {
-			Object string        `json:"object"`
-			Data   []OpenAIModel `json:"data"`
-		}{
-			Object: "list",
-			Data:   dataModels,
-		})
-	}
-}
-
-func App(loader *model.ModelLoader, threads, ctxSize int, f16 bool, debug, disableMessage bool) *fiber.App {
+func App(configFile string, loader *model.ModelLoader, uploadLimitMB, threads, ctxSize int, f16 bool, debug, disableMessage bool, imageDir string) *fiber.App {
 	zerolog.SetGlobalLevel(zerolog.InfoLevel)
 	if debug {
 		zerolog.SetGlobalLevel(zerolog.DebugLevel)
@@ -394,6 +20,7 @@ func App(loader *model.ModelLoader, threads, ctxSize int, f16 bool, debug, disab
 
 	// Return errors as JSON responses
 	app := fiber.New(fiber.Config{
+		BodyLimit:             uploadLimitMB * 1024 * 1024, // this is the default limit of 4MB
 		DisableStartupMessage: disableMessage,
 		// Override default error handler
 		ErrorHandler: func(ctx *fiber.Ctx, err error) error {
@@ -415,23 +42,59 @@ func App(loader *model.ModelLoader, threads, ctxSize int, f16 bool, debug, disab
 		},
 	})
 
+	if debug {
+		app.Use(logger.New(logger.Config{
+			Format: "[${ip}]:${port} ${status} - ${method} ${path}\n",
+		}))
+	}
+
+	cm := make(ConfigMerger)
+	if err := cm.LoadConfigs(loader.ModelPath); err != nil {
+		log.Error().Msgf("error loading config files: %s", err.Error())
+	}
+
+	if configFile != "" {
+		if err := cm.LoadConfigFile(configFile); err != nil {
+			log.Error().Msgf("error loading config file: %s", err.Error())
+		}
+	}
+
+	if debug {
+		for k, v := range cm {
+			log.Debug().Msgf("Model: %s (config: %+v)", k, v)
+		}
+	}
 	// Default middleware config
 	app.Use(recover.New())
 	app.Use(cors.New())
 
-	// This is still needed, see: https://github.com/ggerganov/llama.cpp/discussions/784
-	mu := map[string]*sync.Mutex{}
-	var mumutex = &sync.Mutex{}
-
 	// openAI compatible API endpoint
-	app.Post("/v1/chat/completions", openAIEndpoint(true, debug, loader, threads, ctxSize, f16, mumutex, mu))
-	app.Post("/chat/completions", openAIEndpoint(true, debug, loader, threads, ctxSize, f16, mumutex, mu))
+	app.Post("/v1/chat/completions", chatEndpoint(cm, debug, loader, threads, ctxSize, f16))
+	app.Post("/chat/completions", chatEndpoint(cm, debug, loader, threads, ctxSize, f16))
 
-	app.Post("/v1/completions", openAIEndpoint(false, debug, loader, threads, ctxSize, f16, mumutex, mu))
-	app.Post("/completions", openAIEndpoint(false, debug, loader, threads, ctxSize, f16, mumutex, mu))
+	app.Post("/v1/edits", editEndpoint(cm, debug, loader, threads, ctxSize, f16))
+	app.Post("/edits", editEndpoint(cm, debug, loader, threads, ctxSize, f16))
 
-	app.Get("/v1/models", listModels(loader))
-	app.Get("/models", listModels(loader))
+	app.Post("/v1/completions", completionEndpoint(cm, debug, loader, threads, ctxSize, f16))
+	app.Post("/completions", completionEndpoint(cm, debug, loader, threads, ctxSize, f16))
+
+	app.Post("/v1/embeddings", embeddingsEndpoint(cm, debug, loader, threads, ctxSize, f16))
+	app.Post("/embeddings", embeddingsEndpoint(cm, debug, loader, threads, ctxSize, f16))
+
+	// /v1/engines/{engine_id}/embeddings
+
+	app.Post("/v1/engines/:model/embeddings", embeddingsEndpoint(cm, debug, loader, threads, ctxSize, f16))
+
+	app.Post("/v1/audio/transcriptions", transcriptEndpoint(cm, debug, loader, threads, ctxSize, f16))
+
+	app.Post("/v1/images/generations", imageEndpoint(cm, debug, loader, imageDir))
+
+	if imageDir != "" {
+		app.Static("/generated-images", imageDir)
+	}
+
+	app.Get("/v1/models", listModels(loader, cm))
+	app.Get("/models", listModels(loader, cm))
 
 	return app
 }

api/api_test.go

@@ -3,6 +3,8 @@ package api_test
 import (
 	"context"
 	"os"
+	"path/filepath"
+	"runtime"
 
 	. "github.com/go-skynet/LocalAI/api"
 	"github.com/go-skynet/LocalAI/pkg/model"
@@ -10,6 +12,7 @@ import (
 	. "github.com/onsi/ginkgo/v2"
 	. "github.com/onsi/gomega"
 
+	openaigo "github.com/otiai10/openaigo"
 	"github.com/sashabaranov/go-openai"
 )
 
@@ -18,15 +21,19 @@ var _ = Describe("API test", func() {
 	var app *fiber.App
 	var modelLoader *model.ModelLoader
 	var client *openai.Client
+	var client2 *openaigo.Client
 	Context("API query", func() {
 		BeforeEach(func() {
 			modelLoader = model.NewModelLoader(os.Getenv("MODELS_PATH"))
-			app = App(modelLoader, 1, 512, false, false, true)
+			app = App("", modelLoader, 15, 1, 512, false, true, true, "")
 			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 {
@@ -40,8 +47,7 @@ var _ = Describe("API test", func() {
 		It("returns the models list", func() {
 			models, err := client.ListModels(context.TODO())
 			Expect(err).ToNot(HaveOccurred())
-			Expect(len(models.Models)).To(Equal(1))
-			Expect(models.Models[0].ID).To(Equal("testmodel"))
+			Expect(len(models.Models)).To(Equal(10))
 		})
 		It("can generate completions", func() {
 			resp, err := client.CreateCompletion(context.TODO(), openai.CompletionRequest{Model: "testmodel", Prompt: "abcdedfghikl"})
@@ -49,10 +55,137 @@ var _ = Describe("API test", func() {
 			Expect(len(resp.Choices)).To(Equal(1))
 			Expect(resp.Choices[0].Text).ToNot(BeEmpty())
 		})
+
+		It("can generate chat completions ", func() {
+			resp, err := client.CreateChatCompletion(context.TODO(), openai.ChatCompletionRequest{Model: "testmodel", Messages: []openai.ChatCompletionMessage{openai.ChatCompletionMessage{Role: "user", Content: "abcdedfghikl"}}})
+			Expect(err).ToNot(HaveOccurred())
+			Expect(len(resp.Choices)).To(Equal(1))
+			Expect(resp.Choices[0].Message.Content).ToNot(BeEmpty())
+		})
+
+		It("can generate completions from model configs", func() {
+			resp, err := client.CreateCompletion(context.TODO(), openai.CompletionRequest{Model: "gpt4all", Prompt: "abcdedfghikl"})
+			Expect(err).ToNot(HaveOccurred())
+			Expect(len(resp.Choices)).To(Equal(1))
+			Expect(resp.Choices[0].Text).ToNot(BeEmpty())
+		})
+
+		It("can generate chat completions from model configs", func() {
+			resp, err := client.CreateChatCompletion(context.TODO(), openai.ChatCompletionRequest{Model: "gpt4all-2", Messages: []openai.ChatCompletionMessage{openai.ChatCompletionMessage{Role: "user", Content: "abcdedfghikl"}}})
+			Expect(err).ToNot(HaveOccurred())
+			Expect(len(resp.Choices)).To(Equal(1))
+			Expect(resp.Choices[0].Message.Content).ToNot(BeEmpty())
+		})
+
 		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: llama: model does not exist"))
+			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" {
+				Skip("test supported only on linux")
+			}
+			resp, err := client.CreateTranscription(
+				context.Background(),
+				openai.AudioRequest{
+					Model:    openai.Whisper1,
+					FilePath: filepath.Join(os.Getenv("TEST_DIR"), "audio.wav"),
+				},
+			)
+			Expect(err).ToNot(HaveOccurred())
+			Expect(resp.Text).To(ContainSubstring("This is the Micro Machine Man presenting"))
+		})
+
+		It("calculate embeddings", func() {
+			if runtime.GOOS != "linux" {
+				Skip("test supported only on linux")
+			}
+			resp, err := client.CreateEmbeddings(
+				context.Background(),
+				openai.EmbeddingRequest{
+					Model: openai.AdaEmbeddingV2,
+					Input: []string{"sun", "cat"},
+				},
+			)
+			Expect(err).ToNot(HaveOccurred())
+			Expect(len(resp.Data[0].Embedding)).To(BeNumerically("==", 384))
+			Expect(len(resp.Data[1].Embedding)).To(BeNumerically("==", 384))
+
+			sunEmbedding := resp.Data[0].Embedding
+			resp2, err := client.CreateEmbeddings(
+				context.Background(),
+				openai.EmbeddingRequest{
+					Model: openai.AdaEmbeddingV2,
+					Input: []string{"sun"},
+				},
+			)
+			Expect(err).ToNot(HaveOccurred())
+			Expect(resp2.Data[0].Embedding).To(Equal(sunEmbedding))
+		})
+
+		Context("backends", func() {
+			It("runs rwkv", 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."))
+			})
 		})
 	})
+
+	Context("Config file", func() {
+		BeforeEach(func() {
+			modelLoader = model.NewModelLoader(os.Getenv("MODELS_PATH"))
+			app = App(os.Getenv("CONFIG_FILE"), modelLoader, 5, 1, 512, false, true, true, "")
+			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() {
+			app.Shutdown()
+		})
+		It("can generate chat completions from config file", func() {
+
+			models, err := client.ListModels(context.TODO())
+			Expect(err).ToNot(HaveOccurred())
+			Expect(len(models.Models)).To(Equal(12))
+		})
+		It("can generate chat completions from config file", func() {
+			resp, err := client.CreateChatCompletion(context.TODO(), openai.ChatCompletionRequest{Model: "list1", Messages: []openai.ChatCompletionMessage{openai.ChatCompletionMessage{Role: "user", Content: "abcdedfghikl"}}})
+			Expect(err).ToNot(HaveOccurred())
+			Expect(len(resp.Choices)).To(Equal(1))
+			Expect(resp.Choices[0].Message.Content).ToNot(BeEmpty())
+		})
+		It("can generate chat completions from config file", func() {
+			resp, err := client.CreateChatCompletion(context.TODO(), openai.ChatCompletionRequest{Model: "list2", Messages: []openai.ChatCompletionMessage{openai.ChatCompletionMessage{Role: "user", Content: "abcdedfghikl"}}})
+			Expect(err).ToNot(HaveOccurred())
+			Expect(len(resp.Choices)).To(Equal(1))
+			Expect(resp.Choices[0].Message.Content).ToNot(BeEmpty())
+		})
+		It("can generate edit completions from config file", func() {
+			request := openaigo.EditCreateRequestBody{
+				Model:       "list2",
+				Instruction: "foo",
+				Input:       "bar",
+			}
+			resp, err := client2.CreateEdit(context.Background(), request)
+			Expect(err).ToNot(HaveOccurred())
+			Expect(len(resp.Choices)).To(Equal(1))
+			Expect(resp.Choices[0].Text).ToNot(BeEmpty())
+		})
+
+	})
 })

api/config.go

@@ -0,0 +1,297 @@
+package api
+
+import (
+	"encoding/json"
+	"fmt"
+	"io/ioutil"
+	"os"
+	"path/filepath"
+	"strings"
+
+	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"`
+	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"`
+	ImageGenerationAssets       string            `yaml:"asset_dir"`
+	PromptStrings, InputStrings []string
+	InputToken                  [][]int
+}
+
+type TemplateConfig struct {
+	Completion string `yaml:"completion"`
+	Chat       string `yaml:"chat"`
+	Edit       string `yaml:"edit"`
+}
+
+type ConfigMerger 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 {
+	c, err := ReadConfigFile(file)
+	if err != nil {
+		return fmt.Errorf("cannot load config file: %w", err)
+	}
+
+	for _, cc := range c {
+		cm[cc.Name] = *cc
+	}
+	return nil
+}
+
+func (cm ConfigMerger) LoadConfig(file string) error {
+	c, err := ReadConfig(file)
+	if err != nil {
+		return fmt.Errorf("cannot read config file: %w", err)
+	}
+
+	cm[c.Name] = *c
+	return nil
+}
+
+func (cm ConfigMerger) LoadConfigs(path string) error {
+	files, err := ioutil.ReadDir(path)
+	if err != nil {
+		return err
+	}
+
+	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[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.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
+	}
+
+	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)
+			}
+		}
+	}
+
+	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")
+	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())
+		}
+	}
+
+	var config *Config
+	cfg, exists := cm[modelFile]
+	if !exists {
+		config = &Config{
+			OpenAIRequest: defaultRequest(modelFile),
+			ContextSize:   ctx,
+			Threads:       threads,
+			F16:           f16,
+			Debug:         debug,
+		}
+	} 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
+}

api/openai.go

@@ -0,0 +1,672 @@
+package api
+
+import (
+	"bufio"
+	"bytes"
+	"encoding/base64"
+	"encoding/json"
+	"fmt"
+	"io"
+	"io/ioutil"
+	"net/http"
+	"os"
+	"path"
+	"path/filepath"
+	"strconv"
+	"strings"
+
+	"github.com/ggerganov/whisper.cpp/bindings/go/pkg/whisper"
+	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 {
+	Role    string `json:"role,omitempty" yaml:"role"`
+	Content string `json:"content,omitempty" yaml:"content"`
+}
+
+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"`
+
+	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"`
+
+	Seed int `json:"seed" yaml:"seed"`
+
+	// Image (not supported by OpenAI)
+	Mode int `json:"mode"`
+	Step int `json:"step"`
+}
+
+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, debug bool, loader *model.ModelLoader, threads, ctx int, f16 bool) func(c *fiber.Ctx) error {
+	return func(c *fiber.Ctx) error {
+
+		model, input, err := readInput(c, loader, true)
+		if err != nil {
+			return fmt.Errorf("failed reading parameters from request:%w", err)
+		}
+
+		config, input, err := readConfig(model, input, cm, loader, debug, threads, ctx, 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.Completion != "" {
+			templateFile = config.TemplateConfig.Completion
+		}
+
+		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 := 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, 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, debug bool, loader *model.ModelLoader, threads, ctx int, f16 bool) func(c *fiber.Ctx) error {
+	return func(c *fiber.Ctx) error {
+		model, input, err := readInput(c, loader, true)
+		if err != nil {
+			return fmt.Errorf("failed reading parameters from request:%w", err)
+		}
+
+		config, input, err := readConfig(model, input, cm, loader, debug, threads, ctx, 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, loader, *config)
+			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{}, loader, *config)
+			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, debug bool, loader *model.ModelLoader, threads, ctx int, f16 bool) func(c *fiber.Ctx) error {
+
+	process := func(s string, req *OpenAIRequest, config *Config, loader *model.ModelLoader, responses chan OpenAIResponse) {
+		ComputeChoices(s, req, config, 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{Role: "assistant", Content: s}}},
+				Object:  "chat.completion.chunk",
+			}
+			log.Debug().Msgf("Sending goroutine: %s", s)
+
+			responses <- resp
+			return true
+		})
+		close(responses)
+	}
+	return func(c *fiber.Ctx) error {
+		model, input, err := readInput(c, loader, true)
+		if err != nil {
+			return fmt.Errorf("failed reading parameters from request:%w", err)
+		}
+
+		config, input, err := readConfig(model, input, cm, loader, debug, threads, ctx, f16)
+		if err != nil {
+			return fmt.Errorf("failed reading parameters from request:%w", err)
+		}
+
+		log.Debug().Msgf("Parameter Config: %+v", config)
+
+		var predInput string
+
+		mess := []string{}
+		for _, i := range input.Messages {
+			var content string
+			r := config.Roles[i.Role]
+			if r != "" {
+				content = fmt.Sprint(r, " ", i.Content)
+			} else {
+				content = i.Content
+			}
+
+			mess = append(mess, content)
+		}
+
+		predInput = strings.Join(mess, "\n")
+
+		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.Chat != "" {
+			templateFile = config.TemplateConfig.Chat
+		}
+
+		// A model can have a "file.bin.tmpl" file associated with a prompt template prefix
+		templatedInput, err := loader.TemplatePrefix(templateFile, struct {
+			Input string
+		}{Input: predInput})
+		if err == nil {
+			predInput = templatedInput
+			log.Debug().Msgf("Template found, input modified to: %s", predInput)
+		}
+
+		if input.Stream {
+			responses := make(chan OpenAIResponse)
+
+			go process(predInput, input, config, 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)
+
+					fmt.Fprintf(w, "event: data\n\n")
+					fmt.Fprintf(w, "data: %v\n\n", buf.String())
+					log.Debug().Msgf("Sending chunk: %s", buf.String())
+					w.Flush()
+				}
+
+				w.WriteString("event: data\n\n")
+				resp := &OpenAIResponse{
+					Model:   input.Model, // we have to return what the user sent here, due to OpenAI spec.
+					Choices: []Choice{{FinishReason: "stop"}},
+				}
+				respData, _ := json.Marshal(resp)
+
+				w.WriteString(fmt.Sprintf("data: %s\n\n", respData))
+				w.Flush()
+			}))
+			return nil
+		}
+
+		result, err := ComputeChoices(predInput, input, config, loader, func(s string, c *[]Choice) {
+			*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, debug bool, loader *model.ModelLoader, threads, ctx int, f16 bool) func(c *fiber.Ctx) error {
+	return func(c *fiber.Ctx) error {
+		model, input, err := readInput(c, loader, true)
+		if err != nil {
+			return fmt.Errorf("failed reading parameters from request:%w", err)
+		}
+
+		config, input, err := readConfig(model, input, cm, loader, debug, threads, ctx, 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 := 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, 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, debug bool, loader *model.ModelLoader, imageDir string) func(c *fiber.Ctx) error {
+	return func(c *fiber.Ctx) error {
+		m, input, err := readInput(c, 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, loader, 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 = 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, loader, *config)
+				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, debug bool, loader *model.ModelLoader, threads, ctx int, f16 bool) func(c *fiber.Ctx) error {
+	return func(c *fiber.Ctx) error {
+		m, input, err := readInput(c, loader, false)
+		if err != nil {
+			return fmt.Errorf("failed reading parameters from request:%w", err)
+		}
+
+		config, input, err := readConfig(m, input, cm, loader, debug, threads, ctx, 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 := loader.BackendLoader(model.WhisperBackend, config.Model, []llama.ModelOption{}, uint32(config.Threads))
+		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(fiber.Map{"text": 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 {
+			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,
+		})
+	}
+}

api/prediction.go

@@ -0,0 +1,561 @@
+package api
+
+import (
+	"fmt"
+	"regexp"
+	"strings"
+	"sync"
+
+	"github.com/donomii/go-rwkv.cpp"
+	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"
+	gpt2 "github.com/go-skynet/go-gpt2.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))
+	}
+
+	return llamaOpts
+}
+
+func ImageGeneration(height, width, mode, step, seed int, positive_prompt, negative_prompt, dst string, loader *model.ModelLoader, c Config) (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))
+	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) (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))
+	} else {
+		inferenceModel, err = loader.BackendLoader(c.Backend, modelFile, llamaOpts, uint32(c.Threads))
+	}
+	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)
+			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) []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.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))
+	}
+
+	return predictOptions
+}
+
+func ModelInference(s string, loader *model.ModelLoader, c Config, 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))
+	} else {
+		inferenceModel, err = loader.BackendLoader(c.Backend, modelFile, llamaOpts, uint32(c.Threads))
+	}
+	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 *gpt2.GPTNeoX:
+		fn = func() (string, error) {
+			// Generate the prediction using the language model
+			predictOptions := []gpt2.PredictOption{
+				gpt2.SetTemperature(c.Temperature),
+				gpt2.SetTopP(c.TopP),
+				gpt2.SetTopK(c.TopK),
+				gpt2.SetTokens(c.Maxtokens),
+				gpt2.SetThreads(c.Threads),
+			}
+
+			if c.Batch != 0 {
+				predictOptions = append(predictOptions, gpt2.SetBatch(c.Batch))
+			}
+
+			if c.Seed != 0 {
+				predictOptions = append(predictOptions, gpt2.SetSeed(c.Seed))
+			}
+
+			return model.Predict(
+				s,
+				predictOptions...,
+			)
+		}
+	case *gpt2.Replit:
+		fn = func() (string, error) {
+			// Generate the prediction using the language model
+			predictOptions := []gpt2.PredictOption{
+				gpt2.SetTemperature(c.Temperature),
+				gpt2.SetTopP(c.TopP),
+				gpt2.SetTopK(c.TopK),
+				gpt2.SetTokens(c.Maxtokens),
+				gpt2.SetThreads(c.Threads),
+			}
+
+			if c.Batch != 0 {
+				predictOptions = append(predictOptions, gpt2.SetBatch(c.Batch))
+			}
+
+			if c.Seed != 0 {
+				predictOptions = append(predictOptions, gpt2.SetSeed(c.Seed))
+			}
+
+			return model.Predict(
+				s,
+				predictOptions...,
+			)
+		}
+	case *gpt2.Starcoder:
+		fn = func() (string, error) {
+			// Generate the prediction using the language model
+			predictOptions := []gpt2.PredictOption{
+				gpt2.SetTemperature(c.Temperature),
+				gpt2.SetTopP(c.TopP),
+				gpt2.SetTopK(c.TopK),
+				gpt2.SetTokens(c.Maxtokens),
+				gpt2.SetThreads(c.Threads),
+			}
+
+			if c.Batch != 0 {
+				predictOptions = append(predictOptions, gpt2.SetBatch(c.Batch))
+			}
+
+			if c.Seed != 0 {
+				predictOptions = append(predictOptions, gpt2.SetSeed(c.Seed))
+			}
+
+			return model.Predict(
+				s,
+				predictOptions...,
+			)
+		}
+	case *gpt2.RedPajama:
+		fn = func() (string, error) {
+			// Generate the prediction using the language model
+			predictOptions := []gpt2.PredictOption{
+				gpt2.SetTemperature(c.Temperature),
+				gpt2.SetTopP(c.TopP),
+				gpt2.SetTopK(c.TopK),
+				gpt2.SetTokens(c.Maxtokens),
+				gpt2.SetThreads(c.Threads),
+			}
+
+			if c.Batch != 0 {
+				predictOptions = append(predictOptions, gpt2.SetBatch(c.Batch))
+			}
+
+			if c.Seed != 0 {
+				predictOptions = append(predictOptions, gpt2.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 *gpt2.StableLM:
+		fn = func() (string, error) {
+			// Generate the prediction using the language model
+			predictOptions := []gpt2.PredictOption{
+				gpt2.SetTemperature(c.Temperature),
+				gpt2.SetTopP(c.TopP),
+				gpt2.SetTopK(c.TopK),
+				gpt2.SetTokens(c.Maxtokens),
+				gpt2.SetThreads(c.Threads),
+			}
+
+			if c.Batch != 0 {
+				predictOptions = append(predictOptions, gpt2.SetBatch(c.Batch))
+			}
+
+			if c.Seed != 0 {
+				predictOptions = append(predictOptions, gpt2.SetSeed(c.Seed))
+			}
+
+			return model.Predict(
+				s,
+				predictOptions...,
+			)
+		}
+	case *gpt2.Dolly:
+		fn = func() (string, error) {
+			// Generate the prediction using the language model
+			predictOptions := []gpt2.PredictOption{
+				gpt2.SetTemperature(c.Temperature),
+				gpt2.SetTopP(c.TopP),
+				gpt2.SetTopK(c.TopK),
+				gpt2.SetTokens(c.Maxtokens),
+				gpt2.SetThreads(c.Threads),
+			}
+
+			if c.Batch != 0 {
+				predictOptions = append(predictOptions, gpt2.SetBatch(c.Batch))
+			}
+
+			if c.Seed != 0 {
+				predictOptions = append(predictOptions, gpt2.SetSeed(c.Seed))
+			}
+
+			return model.Predict(
+				s,
+				predictOptions...,
+			)
+		}
+	case *gpt2.GPT2:
+		fn = func() (string, error) {
+			// Generate the prediction using the language model
+			predictOptions := []gpt2.PredictOption{
+				gpt2.SetTemperature(c.Temperature),
+				gpt2.SetTopP(c.TopP),
+				gpt2.SetTopK(c.TopK),
+				gpt2.SetTokens(c.Maxtokens),
+				gpt2.SetThreads(c.Threads),
+			}
+
+			if c.Batch != 0 {
+				predictOptions = append(predictOptions, gpt2.SetBatch(c.Batch))
+			}
+
+			if c.Seed != 0 {
+				predictOptions = append(predictOptions, gpt2.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)
+
+			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
+		}
+	}
+
+	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, 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, 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
+
+}

charts/local-ai/Chart.yaml

@@ -1,6 +0,0 @@
-apiVersion: v2
-appVersion: 0.1.0
-description: A Helm chart for LocalAI
-name: local-ai
-type: application
-version: 1.0.0

charts/local-ai/templates/_helpers.tpl

@@ -1,44 +0,0 @@
-{{/*
-Expand the name of the chart.
-*/}}
-{{- define "local-ai.name" -}}
-{{- default .Chart.Name .Values.nameOverride | trunc 63 | trimSuffix "-" }}
-{{- end }}
-
-{{/*
-Create a default fully qualified app name.
-We truncate at 63 chars because some Kubernetes name fields are limited to this (by the DNS naming spec).
-If release name contains chart name it will be used as a full name.
-*/}}
-{{- define "local-ai.fullname" -}}
-{{- if .Values.fullnameOverride }}
-{{- .Values.fullnameOverride | trunc 63 | trimSuffix "-" }}
-{{- else }}
-{{- $name := default .Chart.Name .Values.nameOverride }}
-{{- if contains $name .Release.Name }}
-{{- .Release.Name | trunc 63 | trimSuffix "-" }}
-{{- else }}
-{{- printf "%s-%s" .Release.Name $name | trunc 63 | trimSuffix "-" }}
-{{- end }}
-{{- end }}
-{{- end }}
-
-{{/*
-Create chart name and version as used by the chart label.
-*/}}
-{{- define "local-ai.chart" -}}
-{{- printf "%s-%s" .Chart.Name .Chart.Version | replace "+" "_" | trunc 63 | trimSuffix "-" }}
-{{- end }}
-
-{{/*
-Common labels
-*/}}
-{{- define "local-ai.labels" -}}
-helm.sh/chart: {{ include "local-ai.chart" . }}
-app.kubernetes.io/name: {{ include "local-ai.name" . }}
-app.kubernetes.io/instance: "{{ .Release.Name }}"
-app.kubernetes.io/managed-by: {{ .Release.Service }}
-{{- if .Chart.AppVersion }}
-app.kubernetes.io/version: {{ .Chart.AppVersion | quote }}
-{{- end }}
-{{- end }}

charts/local-ai/templates/data-volume.yaml

@@ -1,39 +0,0 @@
-{{- if .Values.dataVolume.enabled }}
-apiVersion: cdi.kubevirt.io/v1beta1
-kind: DataVolume
-metadata:
-  name: {{ template "local-ai.fullname" . }}
-  namespace: {{ .Release.Namespace | quote }}
-  labels:
-    {{- include "local-ai.labels" . | nindent 4 }}
-spec:
-  contentType: archive
-  source:
-    {{ .Values.dataVolume.source.type }}:
-      url: {{ .Values.dataVolume.source.url }}
-      secretRef: {{ template "local-ai.fullname" . }}
-      {{- if and (eq .Values.dataVolume.source.type "http") .Values.dataVolume.source.secretExtraHeaders }}
-      secretExtraHeaders: {{ .Values.dataVolume.source.secretExtraHeaders }}
-      {{- end }}
-      {{- if .Values.dataVolume.source.caCertConfigMap }}
-      caCertConfigMap: {{ .Values.dataVolume.source.caCertConfigMap }}
-      {{- end }}
-  pvc:
-    accessModes: {{ .Values.dataVolume.pvc.accessModes }}
-    resources:
-      requests:
-        storage: {{ .Values.dataVolume.pvc.size }}
----
-{{- if .Values.dataVolume.secret.enabled }}
-apiVersion: v1
-kind: Secret
-metadata:
-  name: {{ template "local-ai.fullname" . }}
-  namespace: {{ .Release.Namespace | quote }}
-  labels:
-    {{- include "local-ai.labels" . | nindent 4 }}
-data:
-  accessKeyId: {{ .Values.dataVolume.secret.username }}
-  secretKey: {{ .Values.dataVolume.secret.password }}
-{{- end }}
-{{- end }}

charts/local-ai/templates/deployment.yaml

@@ -1,39 +0,0 @@
-apiVersion: apps/v1
-kind: Deployment
-metadata:
-  name: {{ template "local-ai.fullname" . }}
-  namespace: {{ .Release.Namespace | quote }}
-  labels:
-    {{- include "local-ai.labels" . | nindent 4 }}
-spec:
-  selector:
-    matchLabels:
-      app.kubernetes.io/name: {{ include "local-ai.name" . }}
-      app.kubernetes.io/instance: {{ .Release.Name }}
-  replicas: 1
-  template:
-    metadata:
-      name: {{ template "local-ai.fullname" . }}
-      labels:
-        app.kubernetes.io/name: {{ include "local-ai.name" . }}
-        app.kubernetes.io/instance: {{ .Release.Name }}
-    spec:
-      containers:
-        - name: {{ template "local-ai.fullname" . }}
-          image: {{ .Values.deployment.image }}
-          env:
-          - name: THREADS
-            value: {{ .Values.deployment.env.threads | quote }}
-          - name: CONTEXT_SIZE
-            value: {{ .Values.deployment.env.contextSize | quote }}
-          - name: MODELS_PATH
-            value: {{ .Values.deployment.env.modelsPath }}
-{{- if .Values.deployment.volume.enabled }}
-          volumeMounts:
-          - mountPath: {{ .Values.deployment.env.modelsPath }}
-            name: models
-      volumes:
-      - name: models
-        persistentVolumeClaim:
-          claimName: {{ template "local-ai.fullname" . }}
-{{- end }}

charts/local-ai/templates/service.yaml

@@ -1,19 +0,0 @@
-apiVersion: v1
-kind: Service
-metadata:
-  name: {{ template "local-ai.fullname" . }}
-  namespace: {{ .Release.Namespace | quote }}
-  labels:
-    {{- include "local-ai.labels" . | nindent 4 }}
-{{- if .Values.service.annotations }}
-  annotations:
-  {{ toYaml .Values.service.annotations | indent 4 }}
-{{- end }}
-spec:
-  selector:
-    app.kubernetes.io/name: {{ include "local-ai.name" . }}
-  type: "{{ .Values.service.type }}"
-  ports:
-    - protocol: TCP
-      port: 8080
-      targetPort: 8080

charts/local-ai/values.yaml

@@ -1,38 +0,0 @@
-deployment:
-  image: quay.io/go-skynet/local-ai:latest
-  env:
-    threads: 14
-    contextSize: 512
-    modelsPath: "/models"
-  volume:
-    enabled: false
-
-service:
-  type: ClusterIP
-  annotations: {}
-  # If using an AWS load balancer, you'll need to override the default 60s load balancer idle timeout
-  # service.beta.kubernetes.io/aws-load-balancer-connection-idle-timeout: "1200"
-
-# Optionally create a PVC containing a model binary, sourced from an arbitrary HTTP server or S3 bucket
-# (requires https://github.com/kubevirt/containerized-data-importer)
-dataVolume:
-  enabled: false
-  source:
-    type: "http" # Source type. One of: [ http | s3 ]
-    url: "http://<model_server>/<model_archive>" # e.g. koala-7B-4bit-128g.GGML.tar
-
-    # CertConfigMap is an optional ConfigMap reference, containing a Certificate Authority (CA) public key
-    # and a base64 encoded pem certificate
-    caCertConfigMap: ""
-
-    # SecretExtraHeaders is an optional list of Secret references, each containing an extra HTTP header
-    # that may include sensitive information. Only applicable for the http source type.
-    secretExtraHeaders: []
-  pvc:
-    accessModes:
-    - ReadWriteOnce
-    size: 5Gi
-  secret:
-    enabled: false
-    username: "" # base64 encoded
-    password: "" # base64 encoded

docker-compose.yaml

@@ -5,11 +5,11 @@ services:
     image: quay.io/go-skynet/local-ai:latest
     build:
       context: .
-      dockerfile: Dockerfile
+      dockerfile: Dockerfile.dev
     ports:
       - 8080:8080
     env_file:
       - .env
     volumes:
       - ./models:/models:cached
-    command: ["/usr/bin/local-ai" ]
+    command: ["/usr/bin/local-ai" ]

entrypoint.sh

@@ -0,0 +1,7 @@
+#!/bin/bash
+
+cd /build
+
+make build
+
+./local-ai "$@"

examples/README.md

@@ -0,0 +1,94 @@
+# Examples
+
+Here is a list of projects that can easily be integrated with the LocalAI backend. 
+
+### Projects
+
+
+### Chatbot-UI
+
+_by [@mkellerman](https://github.com/mkellerman)_
+
+![Screenshot from 2023-04-26 23-59-55](https://user-images.githubusercontent.com/2420543/234715439-98d12e03-d3ce-4f94-ab54-2b256808e05e.png)
+
+This integration shows how to use LocalAI with [mckaywrigley/chatbot-ui](https://github.com/mckaywrigley/chatbot-ui).
+
+[Check it out here](https://github.com/go-skynet/LocalAI/tree/master/examples/chatbot-ui/)
+
+### Discord bot
+
+_by [@mudler](https://github.com/mudler)_
+
+Run a discord bot which lets you talk directly with a model
+
+[Check it out here](https://github.com/go-skynet/LocalAI/tree/master/examples/discord-bot/), or for a live demo you can talk with our bot in #random-bot in our discord server.
+
+### Langchain
+
+_by [@dave-gray101](https://github.com/dave-gray101)_
+
+A ready to use example to show e2e how to integrate LocalAI with langchain
+
+[Check it out here](https://github.com/go-skynet/LocalAI/tree/master/examples/langchain/)
+
+### Langchain Python
+
+_by [@mudler](https://github.com/mudler)_
+
+A ready to use example to show e2e how to integrate LocalAI with langchain
+
+[Check it out here](https://github.com/go-skynet/LocalAI/tree/master/examples/langchain-python/)
+
+### LocalAI WebUI
+
+_by [@dhruvgera](https://github.com/dhruvgera)_
+
+![image](https://user-images.githubusercontent.com/42107491/235344183-44b5967d-ba22-4331-804c-8da7004a5d35.png)
+
+A light, community-maintained web interface for LocalAI
+
+[Check it out here](https://github.com/go-skynet/LocalAI/tree/master/examples/localai-webui/)
+
+### How to run rwkv models
+
+_by [@mudler](https://github.com/mudler)_
+
+A full example on how to run RWKV models with LocalAI
+
+[Check it out here](https://github.com/go-skynet/LocalAI/tree/master/examples/rwkv/)
+
+### Slack bot
+
+_by [@mudler](https://github.com/mudler)_
+
+Run a slack bot which lets you talk directly with a model
+
+[Check it out here](https://github.com/go-skynet/LocalAI/tree/master/examples/slack-bot/)
+
+### Question answering on documents with llama-index
+
+_by [@mudler](https://github.com/mudler)_
+
+Shows how to integrate with [Llama-Index](https://gpt-index.readthedocs.io/en/stable/getting_started/installation.html) to enable question answering on a set of documents.
+
+[Check it out here](https://github.com/go-skynet/LocalAI/tree/master/examples/query_data/)
+
+### Question answering on documents with langchain and chroma
+
+_by [@mudler](https://github.com/mudler)_
+
+Shows how to integrate with `Langchain` and `Chroma` to enable question answering on a set of documents.
+
+[Check it out here](https://github.com/go-skynet/LocalAI/tree/master/examples/langchain-chroma/)
+
+### Template for Runpod.io
+
+_by [@fHachenberg](https://github.com/fHachenberg)_
+
+Allows to run any LocalAI-compatible model as a backend on the servers of https://runpod.io
+
+[Check it out here](https://runpod.io/gsc?template=uv9mtqnrd0&ref=984wlcra)
+
+## Want to contribute?
+
+Create an issue, and put `Example: <description>` in the title! We will post your examples here.

examples/chatbot-ui/README.md

@@ -0,0 +1,48 @@
+# chatbot-ui
+
+Example of integration with [mckaywrigley/chatbot-ui](https://github.com/mckaywrigley/chatbot-ui).
+
+![Screenshot from 2023-04-26 23-59-55](https://user-images.githubusercontent.com/2420543/234715439-98d12e03-d3ce-4f94-ab54-2b256808e05e.png)
+
+## Setup
+
+```bash
+# Clone LocalAI
+git clone https://github.com/go-skynet/LocalAI
+
+cd LocalAI/examples/chatbot-ui
+
+# (optional) Checkout a specific LocalAI tag
+# git checkout -b build <TAG>
+
+# Download gpt4all-j to models/
+wget https://gpt4all.io/models/ggml-gpt4all-j.bin -O models/ggml-gpt4all-j
+
+# start with docker-compose
+docker-compose up -d --pull always
+# or you can build the images with:
+# docker-compose up -d --build
+```
+
+## Pointing chatbot-ui to a separately managed LocalAI service
+
+If you want to use the [chatbot-ui example](https://github.com/go-skynet/LocalAI/tree/master/examples/chatbot-ui) with an externally managed LocalAI service, you can alter the `docker-compose` file so that it looks like the below. You will notice the file is smaller, because we have removed the section that would normally start the LocalAI service. Take care to update the IP address (or FQDN) that the chatbot-ui service tries to access (marked `<<LOCALAI_IP>>` below):
+```
+version: '3.6'
+
+services:
+  chatgpt:
+    image: ghcr.io/mckaywrigley/chatbot-ui:main
+    ports:
+      - 3000:3000
+    environment:
+      - 'OPENAI_API_KEY=sk-XXXXXXXXXXXXXXXXXXXX'
+      - 'OPENAI_API_HOST=http://<<LOCALAI_IP>>:8080'
+```
+
+Once you've edited the Dockerfile, you can start it with `docker compose up`, then browse to `http://localhost:3000`.
+
+## Accessing chatbot-ui
+
+Open http://localhost:3000 for the Web UI.
+

examples/chatbot-ui/docker-compose.yaml

@@ -0,0 +1,24 @@
+version: '3.6'
+
+services:
+  api:
+    image: quay.io/go-skynet/local-ai:latest
+    build:
+      context: ../../
+      dockerfile: Dockerfile.dev
+    ports:
+      - 8080:8080
+    environment:
+      - DEBUG=true
+      - MODELS_PATH=/models
+    volumes:
+      - ./models:/models:cached
+    command: ["/usr/bin/local-ai" ]
+
+  chatgpt:
+    image: ghcr.io/mckaywrigley/chatbot-ui:main
+    ports:
+      - 3000:3000
+    environment:
+      - 'OPENAI_API_KEY=sk-XXXXXXXXXXXXXXXXXXXX'
+      - 'OPENAI_API_HOST=http://api:8080'

examples/chatbot-ui/models/completion.tmpl

@@ -0,0 +1 @@
+{{.Input}}

examples/chatbot-ui/models/gpt-3.5-turbo.yaml

@@ -0,0 +1,17 @@
+name: gpt-3.5-turbo
+parameters:
+  model: ggml-gpt4all-j
+  top_k: 80
+  temperature: 0.2
+  top_p: 0.7
+context_size: 1024
+threads: 14
+stopwords:
+- "HUMAN:"
+- "GPT:"
+roles:
+  user: " "
+  system: " "
+template:
+  completion: completion
+  chat: gpt4all

examples/chatbot-ui/models/gpt4all.tmpl

@@ -0,0 +1,4 @@
+The prompt below is a question to answer, a task to complete, or a conversation to respond to; decide which and write an appropriate response.
+### Prompt:
+{{.Input}}
+### Response:

examples/discord-bot/.env.example

@@ -0,0 +1,6 @@
+OPENAI_API_KEY=x
+DISCORD_BOT_TOKEN=x
+DISCORD_CLIENT_ID=x
+OPENAI_API_BASE=http://api:8080
+ALLOWED_SERVER_IDS=x
+SERVER_TO_MODERATION_CHANNEL=1:1

examples/discord-bot/README.md

@@ -0,0 +1,76 @@
+# discord-bot
+
+![Screenshot from 2023-05-01 07-58-19](https://user-images.githubusercontent.com/2420543/235413924-0cb2e75b-f2d6-4119-8610-44386e44afb8.png)
+
+## Setup
+
+```bash
+# Clone LocalAI
+git clone https://github.com/go-skynet/LocalAI
+
+cd LocalAI/examples/discord-bot
+
+# (optional) Checkout a specific LocalAI tag
+# git checkout -b build <TAG>
+
+# Download gpt4all-j to models/
+wget https://gpt4all.io/models/ggml-gpt4all-j.bin -O models/ggml-gpt4all-j
+
+# Set the discord bot options (see: https://github.com/go-skynet/gpt-discord-bot#setup)
+cp -rfv .env.example .env
+vim .env
+
+# start with docker-compose
+docker-compose up -d --build
+```
+
+Note: see setup options here: https://github.com/go-skynet/gpt-discord-bot#setup
+
+Open up the URL in the console and give permission to the bot in your server. Start a thread with `/chat ..`
+
+## Kubernetes
+
+- install the local-ai chart first
+- change OPENAI_API_BASE to point to the API address and apply the discord-bot manifest:
+
+```yaml
+apiVersion: v1
+kind: Namespace
+metadata:
+  name: discord-bot
+---
+apiVersion: apps/v1
+kind: Deployment
+metadata:
+  name: localai
+  namespace: discord-bot
+  labels:
+    app: localai
+spec:
+  selector:
+    matchLabels:
+      app: localai
+  replicas: 1
+  template:
+    metadata:
+      labels:
+        app: localai
+      name: localai
+    spec:
+      containers:
+        - name: localai-discord
+          env:
+          - name: OPENAI_API_KEY
+            value: "x"
+          - name: DISCORD_BOT_TOKEN
+            value: ""
+          - name: DISCORD_CLIENT_ID
+            value: ""
+          - name: OPENAI_API_BASE
+            value: "http://local-ai.default.svc.cluster.local:8080"
+          - name: ALLOWED_SERVER_IDS
+            value: "xx"
+          - name: SERVER_TO_MODERATION_CHANNEL
+            value: "1:1"
+          image: quay.io/go-skynet/gpt-discord-bot:main
+```

examples/discord-bot/docker-compose.yaml

@@ -0,0 +1,21 @@
+version: '3.6'
+
+services:
+  api:
+    image: quay.io/go-skynet/local-ai:latest
+    build:
+      context: ../../
+      dockerfile: Dockerfile.dev
+    ports:
+      - 8080:8080
+    environment:
+      - DEBUG=true
+      - MODELS_PATH=/models
+    volumes:
+      - ./models:/models:cached
+    command: ["/usr/bin/local-ai" ]
+
+  bot:
+    image: quay.io/go-skynet/gpt-discord-bot:main
+    env_file:
+    - .env

examples/discord-bot/models

@@ -0,0 +1 @@
+../chatbot-ui/models/

examples/langchain-chroma/README.md

@@ -0,0 +1,54 @@
+# Data query example
+
+This example makes use of [langchain and chroma](https://blog.langchain.dev/langchain-chroma/) to enable question answering on a set of documents.
+
+## Setup
+
+Download the models and start the API:
+
+```bash
+# Clone LocalAI
+git clone https://github.com/go-skynet/LocalAI
+
+cd LocalAI/examples/query_data
+
+wget https://huggingface.co/skeskinen/ggml/resolve/main/all-MiniLM-L6-v2/ggml-model-q4_0.bin -O models/bert
+wget https://gpt4all.io/models/ggml-gpt4all-j.bin -O models/ggml-gpt4all-j
+
+# start with docker-compose
+docker-compose up -d --build
+```
+
+### Python requirements
+
+```
+pip install -r requirements.txt
+```
+
+### Create a storage
+
+In this step we will create a local vector database from our document set, so later we can ask questions on it with the LLM.
+
+```bash
+export OPENAI_API_BASE=http://localhost:8080/v1
+export OPENAI_API_KEY=sk-
+
+wget https://raw.githubusercontent.com/hwchase17/chat-your-data/master/state_of_the_union.txt
+python store.py
+```
+
+After it finishes, a directory "storage" will be created with the vector index database.
+
+## Query
+
+We can now query the dataset. 
+
+```bash
+export OPENAI_API_BASE=http://localhost:8080/v1
+export OPENAI_API_KEY=sk-
+
+python query.py
+# President Trump recently stated during a press conference regarding tax reform legislation that "we're getting rid of all these loopholes." He also mentioned that he wants to simplify the system further through changes such as increasing the standard deduction amount and making other adjustments aimed at reducing taxpayers' overall burden.    
+```
+
+Keep in mind now things are hit or miss!

examples/langchain-chroma/models/completion.tmpl

@@ -0,0 +1 @@
+{{.Input}}

examples/langchain-chroma/models/embeddings.yaml

@@ -0,0 +1,5 @@
+name: text-embedding-ada-002
+parameters:
+  model: bert
+backend: bert-embeddings
+embeddings: true

examples/langchain-chroma/models/gpt-3.5-turbo.yaml

@@ -0,0 +1,16 @@
+name: gpt-3.5-turbo
+parameters:
+  model: ggml-gpt4all-j
+  top_k: 80
+  temperature: 0.2
+  top_p: 0.7
+context_size: 1024
+stopwords:
+- "HUMAN:"
+- "GPT:"
+roles:
+  user: " "
+  system: " "
+template:
+  completion: completion
+  chat: gpt4all

examples/langchain-chroma/models/gpt4all.tmpl

@@ -0,0 +1,4 @@
+The prompt below is a question to answer, a task to complete, or a conversation to respond to; decide which and write an appropriate response.
+### Prompt:
+{{.Input}}
+### Response:

examples/langchain-chroma/query.py

@@ -0,0 +1,20 @@
+
+import os
+from langchain.vectorstores import Chroma
+from langchain.embeddings import OpenAIEmbeddings
+from langchain.llms import OpenAI
+from langchain.chains import VectorDBQA
+
+base_path = os.environ.get('OPENAI_API_BASE', 'http://localhost:8080/v1')
+
+# Load and process the text
+embedding = OpenAIEmbeddings()
+persist_directory = 'db'
+
+# Now we can load the persisted database from disk, and use it as normal. 
+vectordb = Chroma(persist_directory=persist_directory, embedding_function=embedding)
+qa = VectorDBQA.from_chain_type(llm=OpenAI(temperature=0, model_name="gpt-3.5-turbo", openai_api_base=base_path), chain_type="stuff", vectorstore=vectordb)
+
+query = "What the president said about taxes ?"
+print(qa.run(query))
+

examples/langchain-chroma/requirements.txt

@@ -0,0 +1,4 @@
+langchain==0.0.160
+openai==0.27.6
+chromadb==0.3.21
+llama-index==0.6.2

examples/langchain-chroma/store.py

@@ -0,0 +1,28 @@
+
+import os
+from langchain.vectorstores import Chroma
+from langchain.embeddings import OpenAIEmbeddings
+from langchain.text_splitter import RecursiveCharacterTextSplitter,TokenTextSplitter,CharacterTextSplitter
+from langchain.llms import OpenAI
+from langchain.chains import VectorDBQA
+from langchain.document_loaders import TextLoader
+
+base_path = os.environ.get('OPENAI_API_BASE', 'http://localhost:8080/v1')
+
+# Load and process the text
+loader = TextLoader('state_of_the_union.txt')
+documents = loader.load()
+
+text_splitter = CharacterTextSplitter(chunk_size=300, chunk_overlap=70)
+#text_splitter = TokenTextSplitter()
+texts = text_splitter.split_documents(documents)
+
+# Embed and store the texts
+# Supplying a persist_directory will store the embeddings on disk
+persist_directory = 'db'
+
+embedding = OpenAIEmbeddings(model="text-embedding-ada-002")
+vectordb = Chroma.from_documents(documents=texts, embedding=embedding, persist_directory=persist_directory)
+
+vectordb.persist()
+vectordb = None

examples/langchain-python/README.md

@@ -0,0 +1,35 @@
+## Langchain-python
+
+Langchain example from [quickstart](https://python.langchain.com/en/latest/getting_started/getting_started.html).
+
+To interact with langchain, you can just set the `OPENAI_API_BASE` URL and provide a token with a random string.
+
+See the example below:
+
+```
+# Clone LocalAI
+git clone https://github.com/go-skynet/LocalAI
+
+cd LocalAI/examples/langchain-python
+
+# (optional) Checkout a specific LocalAI tag
+# git checkout -b build <TAG>
+
+# Download gpt4all-j to models/
+wget https://gpt4all.io/models/ggml-gpt4all-j.bin -O models/ggml-gpt4all-j
+
+# start with docker-compose
+docker-compose up -d --build
+
+
+pip install langchain
+pip install openai
+
+export OPENAI_API_BASE=http://localhost:8080
+export OPENAI_API_KEY=sk-
+
+python test.py
+# A good company name for a company that makes colorful socks would be "Colorsocks".
+
+python agent.py
+```

examples/langchain-python/agent.py

@@ -0,0 +1,44 @@
+## This is a fork/based from https://gist.github.com/wiseman/4a706428eaabf4af1002a07a114f61d6
+
+from io import StringIO
+import sys
+import os
+from typing import Dict, Optional
+
+from langchain.agents import load_tools
+from langchain.agents import initialize_agent
+from langchain.agents.tools import Tool
+from langchain.llms import OpenAI
+
+base_path = os.environ.get('OPENAI_API_BASE', 'http://localhost:8080/v1')
+model_name = os.environ.get('MODEL_NAME', 'gpt-3.5-turbo')
+
+class PythonREPL:
+    """Simulates a standalone Python REPL."""
+
+    def __init__(self):
+        pass        
+
+    def run(self, command: str) -> str:
+        """Run command and returns anything printed."""
+        old_stdout = sys.stdout
+        sys.stdout = mystdout = StringIO()
+        try:
+            exec(command, globals())
+            sys.stdout = old_stdout
+            output = mystdout.getvalue()
+        except Exception as e:
+            sys.stdout = old_stdout
+            output = str(e)
+        return output
+
+llm = OpenAI(temperature=0.0, openai_api_base=base_path, model_name=model_name)
+python_repl = Tool(
+        "Python REPL",
+        PythonREPL().run,
+        """A Python shell. Use this to execute python commands. Input should be a valid python command.
+        If you expect output it should be printed out.""",
+    )
+tools = [python_repl]
+agent = initialize_agent(tools, llm, agent="zero-shot-react-description", verbose=True)
+agent.run("What is the 10th fibonacci number?")

examples/langchain-python/docker-compose.yaml

@@ -0,0 +1,16 @@
+version: '3.6'
+
+services:
+  api:
+    image: quay.io/go-skynet/local-ai:latest
+    build:
+      context: ../../
+      dockerfile: Dockerfile.dev
+    ports:
+      - 8080:8080
+    environment:
+      - DEBUG=true
+      - MODELS_PATH=/models
+    volumes:
+      - ./models:/models:cached
+    command: ["/usr/bin/local-ai" ]

examples/langchain-python/models

@@ -0,0 +1 @@
+../chatbot-ui/models

examples/langchain-python/test.py

@@ -0,0 +1,6 @@
+
+from langchain.llms import OpenAI
+
+llm = OpenAI(temperature=0.9,model_name="gpt-3.5-turbo")
+text = "What would be a good company name for a company that makes colorful socks?"
+print(llm(text))

examples/langchain/.gitignore

@@ -0,0 +1,2 @@
+models/ggml-koala-13B-4bit-128g
+models/ggml-gpt4all-j

examples/langchain/JS.Dockerfile

@@ -0,0 +1,6 @@
+FROM node:latest
+COPY ./langchainjs-localai-example /app
+WORKDIR /app
+RUN npm install
+RUN npm run build
+ENTRYPOINT [ "npm", "run", "start" ]

examples/langchain/PY.Dockerfile

@@ -0,0 +1,5 @@
+FROM python:3.10-bullseye
+COPY ./langchainpy-localai-example /app
+WORKDIR /app
+RUN pip install --no-cache-dir -r requirements.txt
+ENTRYPOINT [ "python", "./full_demo.py" ];

examples/langchain/README.md

@@ -0,0 +1,30 @@
+# langchain
+
+Example of using langchain, with the standard OpenAI llm module, and LocalAI. Has docker compose profiles for both the Typescript and Python versions.
+
+**Please Note** - This is a tech demo example at this time. ggml-gpt4all-j has pretty terrible results for most langchain applications with the settings used in this example.
+
+## Setup
+
+```bash
+# Clone LocalAI
+git clone https://github.com/go-skynet/LocalAI
+
+cd LocalAI/examples/langchain
+
+# (optional) - Edit the example code in typescript.
+# vi ./langchainjs-localai-example/index.ts
+
+# Download gpt4all-j to models/
+wget https://gpt4all.io/models/ggml-gpt4all-j.bin -O models/ggml-gpt4all-j
+
+# start with docker-compose for typescript!
+docker-compose --profile ts up --build
+
+# or start with docker-compose for python!
+docker-compose --profile py up --build
+```
+
+## Copyright
+
+Some of the example code in index.mts and full_demo.py is adapted from the langchainjs project and is Copyright (c) Harrison Chase. Used under the terms of the MIT license, as is the remainder of this code.

examples/langchain/docker-compose.yaml

@@ -0,0 +1,43 @@
+version: '3.6'
+
+services:
+  api:
+    image: quay.io/go-skynet/local-ai:latest
+    build:
+      context: ../../
+      dockerfile: Dockerfile.dev
+    ports:
+      - 8080:8080
+    environment:
+      - DEBUG=true
+      - MODELS_PATH=/models
+    volumes:
+      - ./models:/models:cached
+    command: ["/usr/bin/local-ai" ]
+
+  js:
+    build:
+      context: .
+      dockerfile: JS.Dockerfile
+    profiles:
+      - js
+      - ts
+    depends_on:
+    - "api"
+    environment:
+      - 'OPENAI_API_KEY=sk-XXXXXXXXXXXXXXXXXXXX'
+      - 'OPENAI_API_BASE=http://api:8080/v1'
+      - 'MODEL_NAME=gpt-3.5-turbo' #gpt-3.5-turbo' # ggml-gpt4all-j' # ggml-koala-13B-4bit-128g'
+
+  py:
+    build:
+      context: .
+      dockerfile: PY.Dockerfile
+    profiles:
+      - py
+    depends_on:
+    - "api"
+    environment:
+      - 'OPENAI_API_KEY=sk-XXXXXXXXXXXXXXXXXXXX'
+      - 'OPENAI_API_BASE=http://api:8080/v1'
+      - 'MODEL_NAME=gpt-3.5-turbo' #gpt-3.5-turbo' # ggml-gpt4all-j' # ggml-koala-13B-4bit-128g'

examples/langchain/langchainjs-localai-example/.gitignore

@@ -0,0 +1,2 @@
+node_modules/
+dist/

examples/langchain/langchainjs-localai-example/.vscode/launch.json

@@ -0,0 +1,20 @@
+{
+    // Use IntelliSense to learn about possible attributes.
+    // Hover to view descriptions of existing attributes.
+    // For more information, visit: https://go.microsoft.com/fwlink/?linkid=830387
+    "version": "0.2.0",
+    "configurations": [
+        {
+            "type": "node",
+            "request": "launch",
+            "name": "Launch Program",
+            // "skipFiles": [
+            //     "<node_internals>/**"
+            // ],
+            "program": "${workspaceFolder}\\dist\\index.mjs",
+            "outFiles": [
+                "${workspaceFolder}/**/*.js"
+            ]
+        }
+    ]
+}

examples/langchain/langchainjs-localai-example/package.json

@@ -0,0 +1,21 @@
+{
+  "name": "langchainjs-localai-example",
+  "version": "0.1.0",
+  "description": "Trivial Example of using langchain + the OpenAI API + LocalAI together",
+  "main": "index.mjs",
+  "scripts": {
+    "build": "tsc --build",
+    "clean": "tsc --build --clean",
+    "start": "node --trace-warnings dist/index.mjs"
+  },
+  "author": "dave@gray101.com",
+  "license": "MIT",
+  "devDependencies": {
+    "@types/node": "^18.16.4",
+    "typescript": "^5.0.4"
+  },
+  "dependencies": {
+    "langchain": "^0.0.67",
+    "typeorm": "^0.3.15"
+  }
+}

examples/langchain/langchainjs-localai-example/src/index.mts

@@ -0,0 +1,79 @@
+import { OpenAIChat } from "langchain/llms/openai";
+import { loadQAStuffChain } from "langchain/chains";
+import { Document } from "langchain/document";
+import { initializeAgentExecutorWithOptions } from "langchain/agents";
+import {Calculator} from "langchain/tools/calculator";
+
+const pathToLocalAi = process.env['OPENAI_API_BASE'] || 'http://api:8080/v1';
+const fakeApiKey = process.env['OPENAI_API_KEY'] || '-';
+const modelName = process.env['MODEL_NAME'] || 'gpt-3.5-turbo';
+
+function getModel(): OpenAIChat {
+  return new OpenAIChat({
+    prefixMessages: [
+      {
+        role: "system",
+        content: "You are a helpful assistant that answers in pirate language",
+      },
+    ],
+    modelName: modelName,
+    maxTokens: 50,
+    openAIApiKey: fakeApiKey,
+    maxRetries: 2
+  }, {
+    basePath: pathToLocalAi,
+    apiKey: fakeApiKey,
+  });
+}
+
+// Minimal example.
+export const run = async () => {
+  const model = getModel();
+  console.log(`about to model.call at ${new Date().toUTCString()}`);
+  const res = await model.call(
+    "What would be a good company name a company that makes colorful socks?"
+  );
+  console.log(`${new Date().toUTCString()}`);
+  console.log({ res });
+};
+
+await run();
+
+// This example uses the `StuffDocumentsChain`
+export const run2 = async () => {
+  const model = getModel();
+  const chainA = loadQAStuffChain(model);
+  const docs = [
+    new Document({ pageContent: "Harrison went to Harvard." }),
+    new Document({ pageContent: "Ankush went to Princeton." }),
+  ];
+  const resA = await chainA.call({
+    input_documents: docs,
+    question: "Where did Harrison go to college?",
+  });
+  console.log({ resA });
+};
+
+await run2();
+
+// Quickly thrown together example of using tools + agents.
+// This seems like it should work, but it doesn't yet.
+export const temporarilyBrokenToolTest = async () => {
+  const model = getModel();
+
+  const executor = await initializeAgentExecutorWithOptions([new Calculator(true)], model, {
+    agentType: "zero-shot-react-description",
+  });
+
+  console.log("Loaded agent.");
+
+  const input = `What is the value of (500 *2) + 350 - 13?`;
+
+  console.log(`Executing with input "${input}"...`);
+
+  const result = await executor.call({ input });
+
+  console.log(`Got output ${result.output}`);
+}
+
+await temporarilyBrokenToolTest();

examples/langchain/langchainjs-localai-example/tsconfig.json

@@ -0,0 +1,15 @@
+{
+  "compilerOptions": {
+    "target": "es2022",
+    "lib": ["ES2022", "DOM"],
+    "module": "ES2022",
+    "moduleResolution": "node",
+    "strict": true,
+    "esModuleInterop": true,
+    "allowSyntheticDefaultImports": true,
+    "isolatedModules": true,
+    "outDir": "./dist"
+  },
+  "include": ["src", "test"],
+  "exclude": ["node_modules", "dist"]
+}

examples/langchain/langchainpy-localai-example/.vscode/launch.json

@@ -0,0 +1,24 @@
+{
+    "version": "0.2.0",
+    "configurations": [
+        {
+            "name": "Python: Current File",
+            "type": "python",
+            "request": "launch",
+            "program": "${file}",
+            "console": "integratedTerminal",
+            "redirectOutput": true,
+            "justMyCode": false
+        },
+        {
+            "name": "Python: Attach to Port 5678",
+            "type": "python",
+            "request": "attach",
+            "connect": {
+                "host": "localhost",
+                "port": 5678
+              },
+            "justMyCode": false
+        }
+    ]
+}

examples/langchain/langchainpy-localai-example/.vscode/settings.json

@@ -0,0 +1,3 @@
+{
+    "python.defaultInterpreterPath": "${workspaceFolder}/.venv/Scripts/python"
+}

examples/langchain/langchainpy-localai-example/full_demo.py

@@ -0,0 +1,46 @@
+import os
+import logging
+
+from langchain.chat_models import ChatOpenAI
+from langchain import PromptTemplate, LLMChain
+from langchain.prompts.chat import (
+    ChatPromptTemplate,
+    SystemMessagePromptTemplate,
+    AIMessagePromptTemplate,
+    HumanMessagePromptTemplate,
+)
+from langchain.schema import (
+    AIMessage,
+    HumanMessage,
+    SystemMessage
+)
+
+# This logging incantation makes it easy to see that you're actually reaching your LocalAI instance rather than OpenAI.
+logging.basicConfig(level=logging.DEBUG)
+
+print('Langchain + LocalAI PYTHON Tests')
+
+base_path = os.environ.get('OPENAI_API_BASE', 'http://api:8080/v1')
+key = os.environ.get('OPENAI_API_KEY', '-')
+model_name = os.environ.get('MODEL_NAME', 'gpt-3.5-turbo')
+
+
+chat = ChatOpenAI(temperature=0, openai_api_base=base_path, openai_api_key=key, model_name=model_name, max_tokens=100)
+
+print("Created ChatOpenAI for ", chat.model_name)
+
+template = "You are a helpful assistant that translates {input_language} to {output_language}. The next message will be a sentence in {input_language}. Respond ONLY with the translation in {output_language}. Do not respond in {input_language}!"
+system_message_prompt = SystemMessagePromptTemplate.from_template(template)
+human_template = "{text}"
+human_message_prompt = HumanMessagePromptTemplate.from_template(human_template)
+
+chat_prompt = ChatPromptTemplate.from_messages([system_message_prompt, human_message_prompt])
+
+print("ABOUT to execute")
+
+# get a chat completion from the formatted messages
+response = chat(chat_prompt.format_prompt(input_language="English", output_language="French", text="I love programming.").to_messages())
+
+print(response)
+
+print(".");

examples/langchain/langchainpy-localai-example/requirements.txt

@@ -0,0 +1,32 @@
+aiohttp==3.8.4
+aiosignal==1.3.1
+async-timeout==4.0.2
+attrs==23.1.0
+certifi==2022.12.7
+charset-normalizer==3.1.0
+colorama==0.4.6
+dataclasses-json==0.5.7
+debugpy==1.6.7
+frozenlist==1.3.3
+greenlet==2.0.2
+idna==3.4
+langchain==0.0.159
+marshmallow==3.19.0
+marshmallow-enum==1.5.1
+multidict==6.0.4
+mypy-extensions==1.0.0
+numexpr==2.8.4
+numpy==1.24.3
+openai==0.27.6
+openapi-schema-pydantic==1.2.4
+packaging==23.1
+pydantic==1.10.7
+PyYAML==6.0
+requests==2.29.0
+SQLAlchemy==2.0.12
+tenacity==8.2.2
+tqdm==4.65.0
+typing-inspect==0.8.0
+typing_extensions==4.5.0
+urllib3==1.26.15
+yarl==1.9.2

examples/langchain/langchainpy-localai-example/simple_demo.py

@@ -0,0 +1,6 @@
+
+from langchain.llms import OpenAI
+
+llm = OpenAI(temperature=0.9,model_name="gpt-3.5-turbo")
+text = "What would be a good company name for a company that makes colorful socks?"
+print(llm(text))

examples/langchain/models/completion.tmpl

@@ -0,0 +1 @@
+{{.Input}}

examples/langchain/models/gpt-3.5-turbo.yaml

@@ -0,0 +1,18 @@
+name: gpt-3.5-turbo
+parameters:
+  model: ggml-gpt4all-j # ggml-koala-13B-4bit-128g
+  top_k: 80
+  temperature: 0.2
+  top_p: 0.7
+context_size: 1024
+threads: 4
+stopwords:
+- "HUMAN:"
+- "GPT:"
+roles:
+  user: " "
+  system: " "
+backend: "gptj"
+template:
+  completion: completion
+  chat: gpt4all

examples/langchain/models/gpt4all.tmpl

@@ -0,0 +1,4 @@
+The prompt below is a question to answer, a task to complete, or a conversation to respond to; decide which and write an appropriate response.
+### Prompt:
+{{.Input}}
+### Response:

examples/localai-webui/README.md

@@ -0,0 +1,26 @@
+# localai-webui
+
+Example of integration with [dhruvgera/localai-frontend](https://github.com/Dhruvgera/LocalAI-frontend).
+
+![image](https://user-images.githubusercontent.com/42107491/235344183-44b5967d-ba22-4331-804c-8da7004a5d35.png)
+
+## Setup
+
+```bash
+# Clone LocalAI
+git clone https://github.com/go-skynet/LocalAI
+
+cd LocalAI/examples/localai-webui
+
+# (optional) Checkout a specific LocalAI tag
+# git checkout -b build <TAG>
+
+# Download any desired models to models/ in the parent LocalAI project dir
+# For example: wget https://gpt4all.io/models/ggml-gpt4all-j.bin
+
+# start with docker-compose
+docker-compose up -d --build
+```
+
+Open http://localhost:3000 for the Web UI.
+

examples/localai-webui/docker-compose.yml

@@ -0,0 +1,20 @@
+version: '3.6'
+
+services:
+  api:
+    image: quay.io/go-skynet/local-ai:latest
+    build:
+      context: .
+      dockerfile: Dockerfile
+    ports:
+      - 8080:8080
+    env_file:
+      - .env
+    volumes:
+      - ./models:/models:cached
+    command: ["/usr/bin/local-ai"]
+
+  frontend:
+    image: quay.io/go-skynet/localai-frontend:master
+    ports:
+      - 3000:3000

examples/query_data/.gitignore

@@ -0,0 +1 @@
+storage/

examples/query_data/README.md

@@ -0,0 +1,67 @@
+# Data query example
+
+This example makes use of [Llama-Index](https://gpt-index.readthedocs.io/en/stable/getting_started/installation.html) to enable question answering on a set of documents.
+
+It loosely follows [the quickstart](https://gpt-index.readthedocs.io/en/stable/guides/primer/usage_pattern.html).
+
+Summary of the steps:
+
+- prepare the dataset (and store it into `data`)
+- prepare a vector index database to run queries on
+- run queries
+
+## Requirements
+
+You will need a training data set. Copy that over `data`.
+
+## Setup
+
+Start the API:
+
+```bash
+# Clone LocalAI
+git clone https://github.com/go-skynet/LocalAI
+
+cd LocalAI/examples/query_data
+
+wget https://huggingface.co/skeskinen/ggml/resolve/main/all-MiniLM-L6-v2/ggml-model-q4_0.bin -O models/bert
+wget https://gpt4all.io/models/ggml-gpt4all-j.bin -O models/ggml-gpt4all-j
+
+# start with docker-compose
+docker-compose up -d --build
+```
+
+### Create a storage
+
+In this step we will create a local vector database from our document set, so later we can ask questions on it with the LLM.
+
+```bash
+export OPENAI_API_BASE=http://localhost:8080/v1
+export OPENAI_API_KEY=sk-
+
+python store.py
+```
+
+After it finishes, a directory "storage" will be created with the vector index database.
+
+## Query
+
+We can now query the dataset. 
+
+```bash
+export OPENAI_API_BASE=http://localhost:8080/v1
+export OPENAI_API_KEY=sk-
+
+python query.py
+```
+
+## Update
+
+To update our vector database, run `update.py`
+
+```bash
+export OPENAI_API_BASE=http://localhost:8080/v1
+export OPENAI_API_KEY=sk-
+
+python update.py
+```

examples/query_data/docker-compose.yml

@@ -0,0 +1,15 @@
+version: '3.6'
+
+services:
+  api:
+    image: quay.io/go-skynet/local-ai:latest
+    build:
+      context: .
+      dockerfile: Dockerfile
+    ports:
+      - 8080:8080
+    env_file:
+      - .env
+    volumes:
+      - ./models:/models:cached
+    command: ["/usr/bin/local-ai"]

examples/query_data/models/completion.tmpl

@@ -0,0 +1 @@
+{{.Input}}

examples/query_data/models/embeddings.yaml

@@ -0,0 +1,6 @@
+name: text-embedding-ada-002
+parameters:
+  model: bert
+threads: 14
+backend: bert-embeddings
+embeddings: true

examples/query_data/models/gpt-3.5-turbo.yaml

@@ -0,0 +1,17 @@
+name: gpt-3.5-turbo
+parameters:
+  model: ggml-gpt4all-j
+  top_k: 80
+  temperature: 0.2
+  top_p: 0.7
+context_size: 1024
+threads: 14
+stopwords:
+- "HUMAN:"
+- "GPT:"
+roles:
+  user: " "
+  system: " "
+template:
+  completion: completion
+  chat: gpt4all

examples/query_data/query.py

@@ -0,0 +1,35 @@
+import os
+
+# Uncomment to specify your OpenAI API key here (local testing only, not in production!), or add corresponding environment variable (recommended)
+# os.environ['OPENAI_API_KEY']= ""
+
+from llama_index import   LLMPredictor, PromptHelper, ServiceContext
+from langchain.llms.openai import OpenAI
+from llama_index import StorageContext, load_index_from_storage
+
+base_path = os.environ.get('OPENAI_API_BASE', 'http://localhost:8080/v1')
+
+# This example uses text-davinci-003 by default; feel free to change if desired
+llm_predictor = LLMPredictor(llm=OpenAI(temperature=0, model_name="gpt-3.5-turbo", openai_api_base=base_path))
+
+# Configure prompt parameters and initialise helper
+max_input_size = 500
+num_output = 256
+max_chunk_overlap = 20
+
+prompt_helper = PromptHelper(max_input_size, num_output, max_chunk_overlap)
+
+# Load documents from the 'data' directory
+service_context = ServiceContext.from_defaults(llm_predictor=llm_predictor, prompt_helper=prompt_helper)
+
+# rebuild storage context
+storage_context = StorageContext.from_defaults(persist_dir='./storage')
+
+# load index
+index = load_index_from_storage(storage_context,     service_context=service_context,    )
+
+query_engine = index.as_query_engine()
+
+data = input("Question: ")
+response = query_engine.query(data)
+print(response)

examples/query_data/store.py

@@ -0,0 +1,27 @@
+import os
+
+# Uncomment to specify your OpenAI API key here (local testing only, not in production!), or add corresponding environment variable (recommended)
+# os.environ['OPENAI_API_KEY']= ""
+
+from llama_index import GPTVectorStoreIndex, SimpleDirectoryReader, LLMPredictor, PromptHelper, ServiceContext
+from langchain.llms.openai import OpenAI
+from llama_index import StorageContext, load_index_from_storage
+
+base_path = os.environ.get('OPENAI_API_BASE', 'http://localhost:8080/v1')
+
+# This example uses text-davinci-003 by default; feel free to change if desired
+llm_predictor = LLMPredictor(llm=OpenAI(temperature=0, model_name="gpt-3.5-turbo", openai_api_base=base_path))
+
+# Configure prompt parameters and initialise helper
+max_input_size = 400
+num_output = 400
+max_chunk_overlap = 30
+
+prompt_helper = PromptHelper(max_input_size, num_output, max_chunk_overlap)
+
+# Load documents from the 'data' directory
+documents = SimpleDirectoryReader('data').load_data()
+service_context = ServiceContext.from_defaults(llm_predictor=llm_predictor, prompt_helper=prompt_helper, chunk_size_limit = 400)
+index = GPTVectorStoreIndex.from_documents(documents, service_context=service_context)
+index.storage_context.persist(persist_dir="./storage")
+

examples/query_data/update.py

@@ -0,0 +1,32 @@
+import os
+
+# Uncomment to specify your OpenAI API key here (local testing only, not in production!), or add corresponding environment variable (recommended)
+# os.environ['OPENAI_API_KEY']= ""
+
+from llama_index import   LLMPredictor, PromptHelper, SimpleDirectoryReader, ServiceContext
+from langchain.llms.openai import OpenAI
+from llama_index import StorageContext, load_index_from_storage
+
+base_path = os.environ.get('OPENAI_API_BASE', 'http://localhost:8080/v1')
+
+# This example uses text-davinci-003 by default; feel free to change if desired
+llm_predictor = LLMPredictor(llm=OpenAI(temperature=0, model_name="gpt-3.5-turbo", openai_api_base=base_path))
+
+# Configure prompt parameters and initialise helper
+max_input_size = 512
+num_output = 256
+max_chunk_overlap = 20
+
+prompt_helper = PromptHelper(max_input_size, num_output, max_chunk_overlap)
+
+# Load documents from the 'data' directory
+service_context = ServiceContext.from_defaults(llm_predictor=llm_predictor, prompt_helper=prompt_helper)
+
+# rebuild storage context
+storage_context = StorageContext.from_defaults(persist_dir='./storage')
+
+# load index
+index = load_index_from_storage(storage_context,     service_context=service_context,    )
+documents = SimpleDirectoryReader('data').load_data()
+index.refresh(documents)
+index.storage_context.persist(persist_dir="./storage")

examples/rwkv/Dockerfile.build

@@ -0,0 +1,10 @@
+FROM python
+
+# convert the model (one-off)
+RUN pip3 install torch numpy
+
+WORKDIR /build
+COPY ./scripts/ .
+
+RUN git clone --recurse-submodules https://github.com/saharNooby/rwkv.cpp && cd rwkv.cpp && cmake . && cmake --build . --config Release
+ENTRYPOINT [ "/build/build.sh" ]

examples/rwkv/README.md

@@ -0,0 +1,59 @@
+# rwkv
+
+Example of how to run rwkv models.
+
+## Run models
+
+Setup:
+
+```bash
+# Clone LocalAI
+git clone https://github.com/go-skynet/LocalAI
+
+cd LocalAI/examples/rwkv
+
+# (optional) Checkout a specific LocalAI tag
+# git checkout -b build <TAG>
+
+# build the tooling image to convert an rwkv model locally:
+docker build -t rwkv-converter -f Dockerfile.build .
+
+# download and convert a model (one-off) - it's going to be fast on CPU too!
+docker run -ti --name converter -v $PWD:/data rwkv-converter https://huggingface.co/BlinkDL/rwkv-4-raven/resolve/main/RWKV-4-Raven-1B5-v11-Eng99%25-Other1%25-20230425-ctx4096.pth /data/models/rwkv
+
+# Get the tokenizer
+wget https://raw.githubusercontent.com/saharNooby/rwkv.cpp/5eb8f09c146ea8124633ab041d9ea0b1f1db4459/rwkv/20B_tokenizer.json -O models/rwkv.tokenizer.json
+
+# start with docker-compose
+docker-compose up -d --build
+```
+
+Test it out:
+
+```bash
+curl http://localhost:8080/v1/completions -H "Content-Type: application/json" -d '{
+    "model": "gpt-3.5-turbo",
+    "prompt": "A long time ago, in a galaxy far away",
+    "max_tokens": 100,
+    "temperature": 0.9, "top_p": 0.8, "top_k": 80
+  }'
+
+# {"object":"text_completion","model":"gpt-3.5-turbo","choices":[{"text":", there was a small group of five friends: Annie, Bryan, Charlie, Emily, and Jesse."}],"usage":{"prompt_tokens":0,"completion_tokens":0,"total_tokens":0}}
+
+curl http://localhost:8080/v1/chat/completions -H "Content-Type: application/json" -d '{
+     "model": "gpt-3.5-turbo",            
+     "messages": [{"role": "user", "content": "How are you?"}],
+     "temperature": 0.9, "top_p": 0.8, "top_k": 80
+   }'
+
+# {"object":"chat.completion","model":"gpt-3.5-turbo","choices":[{"message":{"role":"assistant","content":" Good, thanks. I am about to go to bed. I' ll talk to you later.Bye."}}],"usage":{"prompt_tokens":0,"completion_tokens":0,"total_tokens":0}}
+```
+
+### Fine tuning
+
+See [RWKV-LM](https://github.com/BlinkDL/RWKV-LM#training--fine-tuning). There is also a Google [colab](https://colab.research.google.com/github/resloved/RWKV-notebooks/blob/master/RWKV_v4_RNN_Pile_Fine_Tuning.ipynb).
+
+## See also
+
+- [RWKV-LM](https://github.com/BlinkDL/RWKV-LM)
+- [rwkv.cpp](https://github.com/saharNooby/rwkv.cpp)

examples/rwkv/docker-compose.yaml

@@ -0,0 +1,16 @@
+version: '3.6'
+
+services:
+  api:
+    image: quay.io/go-skynet/local-ai:latest
+    build:
+      context: ../../
+      dockerfile: Dockerfile.dev
+    ports:
+      - 8080:8080
+    environment:
+      - DEBUG=true
+      - MODELS_PATH=/models
+    volumes:
+      - ./models:/models:cached
+    command: ["/usr/bin/local-ai" ]

examples/rwkv/models/gpt-3.5-turbo.yaml

@@ -0,0 +1,19 @@
+name: gpt-3.5-turbo
+parameters:
+  model: rwkv
+  top_k: 80
+  temperature: 0.9
+  max_tokens: 100
+  top_p: 0.8
+context_size: 1024
+threads: 14
+backend: "rwkv"
+cutwords:
+- "Bob:.*"
+roles:
+  user: "Bob:"
+  system: "Alice:"
+  assistant: "Alice:"
+template:
+  completion: rwkv_completion
+  chat: rwkv_chat

examples/rwkv/models/rwkv_chat.tmpl

@@ -0,0 +1,13 @@
+The following is a verbose detailed conversation between Bob and a woman, Alice. Alice is intelligent, friendly and likeable. Alice is likely to agree with Bob.
+
+Bob: Hello Alice, how are you doing?
+
+Alice: Hi Bob! Thanks, I'm fine. What about you?
+
+Bob: I am very good! It's nice to see you. Would you mind me chatting with you for a while?
+
+Alice: Not at all! I'm listening.
+
+{{.Input}}
+
+Alice: 

examples/rwkv/models/rwkv_completion.tmpl

@@ -0,0 +1 @@
+Complete the following sentence: {{.Input}} 

examples/rwkv/scripts/build.sh

@@ -0,0 +1,11 @@
+#!/bin/bash
+set -ex
+
+URL=$1
+OUT=$2
+FILENAME=$(basename $URL)
+
+wget -nc $URL -O /build/$FILENAME
+
+python3 /build/rwkv.cpp/rwkv/convert_pytorch_to_ggml.py /build/$FILENAME /build/float-model float16
+python3 /build/rwkv.cpp/rwkv/quantize.py /build/float-model $OUT Q4_2

examples/slack-bot/.env.example

@@ -0,0 +1,11 @@
+SLACK_APP_TOKEN=xapp-1-...
+SLACK_BOT_TOKEN=xoxb-...
+OPENAI_API_KEY=sk-...
+OPENAI_API_BASE=http://api:8080
+OPENAI_MODEL=gpt-3.5-turbo
+OPENAI_TIMEOUT_SECONDS=60
+#OPENAI_SYSTEM_TEXT="You proofread text. When you receive a message, you will check
+#for mistakes and make suggestion to improve the language of the given text"
+USE_SLACK_LANGUAGE=true
+SLACK_APP_LOG_LEVEL=INFO
+TRANSLATE_MARKDOWN=true

examples/slack-bot/README.md

@@ -0,0 +1,27 @@
+# Slack bot
+
+Slackbot using: https://github.com/seratch/ChatGPT-in-Slack
+
+## Setup
+
+```bash
+# Clone LocalAI
+git clone https://github.com/go-skynet/LocalAI
+
+cd LocalAI/examples/slack-bot
+
+git clone https://github.com/seratch/ChatGPT-in-Slack
+
+# (optional) Checkout a specific LocalAI tag
+# git checkout -b build <TAG>
+
+# Download gpt4all-j to models/
+wget https://gpt4all.io/models/ggml-gpt4all-j.bin -O models/ggml-gpt4all-j
+
+# Set the discord bot options (see: https://github.com/seratch/ChatGPT-in-Slack)
+cp -rfv .env.example .env
+vim .env
+
+# start with docker-compose
+docker-compose up -d --build
+```

examples/slack-bot/docker-compose.yaml

@@ -0,0 +1,23 @@
+version: '3.6'
+
+services:
+  api:
+    image: quay.io/go-skynet/local-ai:latest
+    build:
+      context: ../../
+      dockerfile: Dockerfile.dev
+    ports:
+      - 8080:8080
+    environment:
+      - DEBUG=true
+      - MODELS_PATH=/models
+    volumes:
+      - ./models:/models:cached
+    command: ["/usr/bin/local-ai" ]
+
+  bot:
+    build:
+     context: ./ChatGPT-in-Slack
+     dockerfile: Dockerfile
+    env_file:
+    - .env

examples/slack-bot/models

@@ -0,0 +1 @@
+../chatbot-ui/models

go.mod

@@ -3,52 +3,66 @@ module github.com/go-skynet/LocalAI
 go 1.19
 
 require (
-	github.com/go-skynet/go-gpt2.cpp v0.0.0-20230422085954-245a5bfe6708
+	github.com/donomii/go-rwkv.cpp v0.0.0-20230515123100-6fdd0c338e56
+	github.com/ggerganov/whisper.cpp/bindings/go v0.0.0-20230515153606-95b02d76b04d
+	github.com/go-audio/wav v1.1.0
+	github.com/go-skynet/bloomz.cpp v0.0.0-20230510223001-e9366e82abdf
+	github.com/go-skynet/go-bert.cpp v0.0.0-20230516063724-cea1ed76a7f4
+	github.com/go-skynet/go-gpt2.cpp v0.0.0-20230512145559-7bff56f02245
 	github.com/go-skynet/go-gpt4all-j.cpp v0.0.0-20230422090028-1f7bff57f66c
-	github.com/go-skynet/go-llama.cpp v0.0.0-20230424120713-e45cebe33c04
-	github.com/gofiber/fiber/v2 v2.44.0
-	github.com/jaypipes/ghw v0.10.0
-	github.com/onsi/ginkgo/v2 v2.9.2
+	github.com/go-skynet/go-llama.cpp v0.0.0-20230516230554-b7bbefbe0b84
+	github.com/gofiber/fiber/v2 v2.45.0
+	github.com/hashicorp/go-multierror v1.1.1
+	github.com/mudler/go-stable-diffusion v0.0.0-20230516152536-c0748eca3642
+	github.com/nomic-ai/gpt4all/gpt4all-bindings/golang v0.0.0-20230516143155-79d6243fe1bc
+	github.com/onsi/ginkgo/v2 v2.9.5
 	github.com/onsi/gomega v1.27.6
+	github.com/otiai10/copy v1.11.0
+	github.com/otiai10/openaigo v1.1.0
 	github.com/rs/zerolog v1.29.1
-	github.com/sashabaranov/go-openai v1.9.0
-	github.com/urfave/cli/v2 v2.25.1
+	github.com/sashabaranov/go-openai v1.9.4
+	github.com/swaggo/swag v1.16.1
+	github.com/urfave/cli/v2 v2.25.3
+	github.com/valyala/fasthttp v1.47.0
+	gopkg.in/yaml.v3 v3.0.1
 )
 
 require (
-	github.com/StackExchange/wmi v1.2.1 // indirect
+	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/ghodss/yaml v1.0.0 // indirect
-	github.com/go-logr/logr v1.2.3 // indirect
-	github.com/go-ole/go-ole v1.2.6 // 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 v0.19.15 // 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/google/uuid v1.3.0 // indirect
-	github.com/jaypipes/pcidb v1.0.0 // 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/kr/text v0.2.0 // indirect
+	github.com/mailru/easyjson v0.7.6 // indirect
 	github.com/mattn/go-colorable v0.1.13 // indirect
 	github.com/mattn/go-isatty v0.0.18 // indirect
 	github.com/mattn/go-runewidth v0.0.14 // indirect
-	github.com/mitchellh/go-homedir v1.1.0 // indirect
 	github.com/philhofer/fwd v1.1.2 // indirect
-	github.com/pkg/errors v0.9.1 // indirect
 	github.com/rivo/uniseg v0.2.0 // indirect
 	github.com/russross/blackfriday/v2 v2.1.0 // indirect
 	github.com/savsgio/dictpool v0.0.0-20221023140959-7bf2e61cea94 // indirect
 	github.com/savsgio/gotils v0.0.0-20230208104028-c358bd845dee // indirect
 	github.com/tinylib/msgp v1.1.8 // indirect
 	github.com/valyala/bytebufferpool v1.0.0 // indirect
-	github.com/valyala/fasthttp v1.45.0 // indirect
 	github.com/valyala/tcplisten v1.0.0 // indirect
 	github.com/xrash/smetrics v0.0.0-20201216005158-039620a65673 // indirect
-	golang.org/x/net v0.8.0 // indirect
-	golang.org/x/sys v0.7.0 // indirect
-	golang.org/x/text v0.8.0 // indirect
-	golang.org/x/tools v0.7.0 // indirect
+	golang.org/x/net v0.10.0 // indirect
+	golang.org/x/sys v0.8.0 // indirect
+	golang.org/x/text v0.9.0 // indirect
+	golang.org/x/tools v0.9.1 // indirect
 	gopkg.in/yaml.v2 v2.4.0 // indirect
-	gopkg.in/yaml.v3 v3.0.1 // indirect
-	howett.net/plist v1.0.0 // indirect
 )

go.sum

@@ -1,7 +1,9 @@
-github.com/StackExchange/wmi v1.2.1 h1:VIkavFPXSjcnS+O8yTq7NI32k0R5Aj+v39y29VYDOSA=
-github.com/StackExchange/wmi v1.2.1/go.mod h1:rcmrprowKIVzvc+NUiLncP2uuArMWLCbu9SBzvHz7e8=
-github.com/andybalholm/brotli v1.0.4 h1:V7DdXeJtZscaqfNuAdSRuRFzuiKlHSC/Zh3zl9qY3JY=
-github.com/andybalholm/brotli v1.0.4/go.mod h1:fO7iG3H7G2nSZ7m0zPUDn85XEX2GTukHGRSepvi9Eig=
+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 v1.0.5 h1:8uQZIdzKmjc/iuPu7O2ioW48L81FgatrcpfFmiq/cCs=
 github.com/andybalholm/brotli v1.0.5/go.mod h1:fO7iG3H7G2nSZ7m0zPUDn85XEX2GTukHGRSepvi9Eig=
 github.com/chzyer/logex v1.1.10/go.mod h1:+Ywpsq7O8HXn0nuIou7OrIPyXbp3wmkHB+jjWRnGsAI=
@@ -14,32 +16,61 @@ github.com/creack/pty v1.1.9/go.mod h1:oKZEueFk5CKHvIhNR5MUki03XCEU+Q6VDXinZuGJ3
 github.com/davecgh/go-spew v1.1.0/go.mod h1:J7Y8YcW2NihsgmVo/mv3lAwl/skON4iLHjSsI+c5H38=
 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/ghodss/yaml v1.0.0 h1:wQHKEahhL6wmXdzwWG11gIVCkOv05bNOh+Rxn0yngAk=
-github.com/ghodss/yaml v1.0.0/go.mod h1:4dBDuWmgqj2HViK6kFavaiC9ZROes6MMH2rRYeMEF04=
-github.com/go-logr/logr v1.2.3 h1:2DntVwHkVopvECVRSlL5PSo9eG+cAkDCuckLubN+rq0=
-github.com/go-logr/logr v1.2.3/go.mod h1:jdQByPbusPIv2/zmleS9BjJVeZ6kBagPoEUsqbVz/1A=
-github.com/go-ole/go-ole v1.2.5/go.mod h1:pprOEPIfldk/42T2oK7lQ4v4JSDwmV0As9GaiUsvbm0=
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@@ -172,26 +214,29 @@ golang.org/x/text v0.3.3/go.mod h1:5Zoc/QRtKVWzQhOtBMvqHzDpF6irO9z98xDceosuGiQ=
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+golang.org/x/text v0.9.0 h1:2sjJmO8cDvYveuX97RDLsxlyUxLl+GHoLxBiRdHllBE=
+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 v0.1.12/go.mod h1:hNGJHUnrk76NpqgfD5Aqm5Crs+Hm0VOH/i9J2+nxYbc=
 golang.org/x/tools v0.4.0/go.mod h1:UE5sM2OK9E/d67R0ANs2xJizIymRP5gJU295PvKXxjQ=
-golang.org/x/tools v0.7.0 h1:W4OVu8VVOaIO0yzWMNdepAulS7YfoS3Zabrm8DOXXU4=
-golang.org/x/tools v0.7.0/go.mod h1:4pg6aUX35JBAogB10C9AtvVL+qowtN4pT3CGSQex14s=
+golang.org/x/tools v0.8.0 h1:vSDcovVPld282ceKgDimkRSC8kpaH1dgyc9UMzlt84Y=
+golang.org/x/tools v0.8.0/go.mod h1:JxBZ99ISMI5ViVkT1tr6tdNmXeTrcpVSD3vZ1RsRdN4=
+golang.org/x/tools v0.9.1 h1:8WMNJAz3zrtPmnYC7ISf5dEn3MT0gY7jBJfw27yrrLo=
+golang.org/x/tools v0.9.1/go.mod h1:owI94Op576fPu3cIGQeHs3joujW/2Oc6MtlxbF5dfNc=
 golang.org/x/xerrors v0.0.0-20190717185122-a985d3407aa7/go.mod h1:I/5z698sn9Ka8TeJc9MKroUUfqBBauWjQqLJ2OPfmY0=
 golang.org/x/xerrors v0.0.0-20191011141410-1b5146add898/go.mod h1:I/5z698sn9Ka8TeJc9MKroUUfqBBauWjQqLJ2OPfmY0=
 golang.org/x/xerrors v0.0.0-20200804184101-5ec99f83aff1/go.mod h1:I/5z698sn9Ka8TeJc9MKroUUfqBBauWjQqLJ2OPfmY0=
 google.golang.org/protobuf v1.28.0 h1:w43yiav+6bVFTBQFZX0r7ipe9JQ1QsbMgHwbBziscLw=
 gopkg.in/check.v1 v0.0.0-20161208181325-20d25e280405/go.mod h1:Co6ibVJAznAaIkqp8huTwlJQCZ016jof/cbN4VW5Yz0=
-gopkg.in/check.v1 v1.0.0-20180628173108-788fd7840127 h1:qIbj1fsPNlZgppZ+VLlY7N33q108Sa+fhmuc+sWQYwY=
-gopkg.in/yaml.v1 v1.0.0-20140924161607-9f9df34309c0/go.mod h1:WDnlLJ4WF5VGsH/HVa3CI79GS0ol3YnhVnKP89i0kNg=
+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/yaml.v2 v2.2.2/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=
-howett.net/plist v1.0.0 h1:7CrbWYbPPO/PyNy38b2EB/+gYbjCe2DXBxgtOOZbSQM=
-howett.net/plist v1.0.0/go.mod h1:lqaXoTrLY4hg8tnEzNru53gicrbv7rrk+2xJA/7hw9g=

main.go

@@ -1,11 +1,12 @@
 package main
 
 import (
+	"fmt"
 	"os"
+	"path/filepath"
 
 	api "github.com/go-skynet/LocalAI/api"
 	model "github.com/go-skynet/LocalAI/pkg/model"
-	"github.com/jaypipes/ghw"
 	"github.com/rs/zerolog"
 	"github.com/rs/zerolog/log"
 	"github.com/urfave/cli/v2"
@@ -20,12 +21,6 @@ func main() {
 		os.Exit(1)
 	}
 
-	threads := 4
-	cpu, err := ghw.CPU()
-	if err == nil {
-		threads = int(cpu.TotalCores)
-	}
-
 	app := &cli.App{
 		Name:  "LocalAI",
 		Usage: "OpenAI compatible API for running LLaMA/GPT models locally on CPU with consumer grade hardware.",
@@ -42,13 +37,18 @@ func main() {
 				Name:        "threads",
 				DefaultText: "Number of threads used for parallel computation. Usage of the number of physical cores in the system is suggested.",
 				EnvVars:     []string{"THREADS"},
-				Value:       threads,
+				Value:       4,
 			},
 			&cli.StringFlag{
 				Name:        "models-path",
 				DefaultText: "Path containing models used for inferencing",
 				EnvVars:     []string{"MODELS_PATH"},
-				Value:       path,
+				Value:       filepath.Join(path, "models"),
+			},
+			&cli.StringFlag{
+				Name:        "config-file",
+				DefaultText: "Config file",
+				EnvVars:     []string{"CONFIG_FILE"},
 			},
 			&cli.StringFlag{
 				Name:        "address",
@@ -56,12 +56,24 @@ func main() {
 				EnvVars:     []string{"ADDRESS"},
 				Value:       ":8080",
 			},
+			&cli.StringFlag{
+				Name:        "image-dir",
+				DefaultText: "Image directory",
+				EnvVars:     []string{"IMAGE_DIR"},
+				Value:       "",
+			},
 			&cli.IntFlag{
 				Name:        "context-size",
 				DefaultText: "Default context size of the model",
 				EnvVars:     []string{"CONTEXT_SIZE"},
 				Value:       512,
 			},
+			&cli.IntFlag{
+				Name:        "upload-limit",
+				DefaultText: "Default upload-limit. MB",
+				EnvVars:     []string{"UPLOAD_LIMIT"},
+				Value:       15,
+			},
 		},
 		Description: `
 LocalAI is a drop-in replacement OpenAI API which runs inference locally.
@@ -80,7 +92,8 @@ It uses llama.cpp, ggml and gpt4all as backend with golang c bindings.
 		UsageText: `local-ai [options]`,
 		Copyright: "go-skynet authors",
 		Action: func(ctx *cli.Context) error {
-			return api.App(model.NewModelLoader(ctx.String("models-path")), ctx.Int("threads"), ctx.Int("context-size"), ctx.Bool("f16"), ctx.Bool("debug"), false).Listen(ctx.String("address"))
+			fmt.Printf("Starting LocalAI using %d threads, with models path: %s\n", ctx.Int("threads"), ctx.String("models-path"))
+			return api.App(ctx.String("config-file"), model.NewModelLoader(ctx.String("models-path")), ctx.Int("upload-limit"), ctx.Int("threads"), ctx.Int("context-size"), ctx.Bool("f16"), ctx.Bool("debug"), false, ctx.String("image-dir")).Listen(ctx.String("address"))
 		},
 	}
 

pkg/model/initializers.go

@@ -0,0 +1,194 @@
+package model
+
+import (
+	"fmt"
+	"path/filepath"
+	"strings"
+
+	rwkv "github.com/donomii/go-rwkv.cpp"
+	whisper "github.com/ggerganov/whisper.cpp/bindings/go/pkg/whisper"
+	"github.com/go-skynet/LocalAI/pkg/stablediffusion"
+	bloomz "github.com/go-skynet/bloomz.cpp"
+	bert "github.com/go-skynet/go-bert.cpp"
+	gpt2 "github.com/go-skynet/go-gpt2.cpp"
+	llama "github.com/go-skynet/go-llama.cpp"
+	"github.com/hashicorp/go-multierror"
+	gpt4all "github.com/nomic-ai/gpt4all/gpt4all-bindings/golang"
+	"github.com/rs/zerolog/log"
+)
+
+const tokenizerSuffix = ".tokenizer.json"
+
+const (
+	LlamaBackend           = "llama"
+	BloomzBackend          = "bloomz"
+	StarcoderBackend       = "starcoder"
+	StableLMBackend        = "stablelm"
+	DollyBackend           = "dolly"
+	RedPajamaBackend       = "redpajama"
+	GPTNeoXBackend         = "gptneox"
+	ReplitBackend          = "replit"
+	Gpt2Backend            = "gpt2"
+	Gpt4AllLlamaBackend    = "gpt4all-llama"
+	Gpt4AllMptBackend      = "gpt4all-mpt"
+	Gpt4AllJBackend        = "gpt4all-j"
+	BertEmbeddingsBackend  = "bert-embeddings"
+	RwkvBackend            = "rwkv"
+	WhisperBackend         = "whisper"
+	StableDiffusionBackend = "stablediffusion"
+)
+
+var backends []string = []string{
+	LlamaBackend,
+	Gpt4AllLlamaBackend,
+	Gpt4AllMptBackend,
+	Gpt4AllJBackend,
+	Gpt2Backend,
+	WhisperBackend,
+	RwkvBackend,
+	BloomzBackend,
+	StableLMBackend,
+	DollyBackend,
+	RedPajamaBackend,
+	ReplitBackend,
+	GPTNeoXBackend,
+	BertEmbeddingsBackend,
+	StarcoderBackend,
+}
+
+var starCoder = func(modelFile string) (interface{}, error) {
+	return gpt2.NewStarcoder(modelFile)
+}
+
+var redPajama = func(modelFile string) (interface{}, error) {
+	return gpt2.NewRedPajama(modelFile)
+}
+
+var dolly = func(modelFile string) (interface{}, error) {
+	return gpt2.NewDolly(modelFile)
+}
+
+var gptNeoX = func(modelFile string) (interface{}, error) {
+	return gpt2.NewGPTNeoX(modelFile)
+}
+
+var replit = func(modelFile string) (interface{}, error) {
+	return gpt2.NewReplit(modelFile)
+}
+
+var stableLM = func(modelFile string) (interface{}, error) {
+	return gpt2.NewStableLM(modelFile)
+}
+
+var bertEmbeddings = func(modelFile string) (interface{}, error) {
+	return bert.New(modelFile)
+}
+
+var bloomzLM = func(modelFile string) (interface{}, error) {
+	return bloomz.New(modelFile)
+}
+var gpt2LM = func(modelFile string) (interface{}, error) {
+	return gpt2.New(modelFile)
+}
+
+var stableDiffusion = func(assetDir string) (interface{}, error) {
+	return stablediffusion.New(assetDir)
+}
+
+var whisperModel = func(modelFile string) (interface{}, error) {
+	return whisper.New(modelFile)
+}
+
+func llamaLM(opts ...llama.ModelOption) func(string) (interface{}, error) {
+	return func(s string) (interface{}, error) {
+		return llama.New(s, opts...)
+	}
+}
+
+func gpt4allLM(opts ...gpt4all.ModelOption) func(string) (interface{}, error) {
+	return func(s string) (interface{}, error) {
+		return gpt4all.New(s, opts...)
+	}
+}
+
+func rwkvLM(tokenFile string, threads uint32) func(string) (interface{}, error) {
+	return func(s string) (interface{}, error) {
+		log.Debug().Msgf("Loading RWKV", s, tokenFile)
+
+		model := rwkv.LoadFiles(s, tokenFile, threads)
+		if model == nil {
+			return nil, fmt.Errorf("could not load model")
+		}
+		return model, nil
+	}
+}
+
+func (ml *ModelLoader) BackendLoader(backendString string, modelFile string, llamaOpts []llama.ModelOption, threads uint32) (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 StableLMBackend:
+		return ml.LoadModel(modelFile, stableLM)
+	case DollyBackend:
+		return ml.LoadModel(modelFile, dolly)
+	case RedPajamaBackend:
+		return ml.LoadModel(modelFile, redPajama)
+	case Gpt2Backend:
+		return ml.LoadModel(modelFile, gpt2LM)
+	case GPTNeoXBackend:
+		return ml.LoadModel(modelFile, gptNeoX)
+	case ReplitBackend:
+		return ml.LoadModel(modelFile, replit)
+	case StableDiffusionBackend:
+		return ml.LoadModel(modelFile, stableDiffusion)
+	case StarcoderBackend:
+		return ml.LoadModel(modelFile, starCoder)
+	case Gpt4AllLlamaBackend:
+		return ml.LoadModel(modelFile, gpt4allLM(gpt4all.SetThreads(int(threads)), gpt4all.SetModelType(gpt4all.LLaMAType)))
+	case Gpt4AllMptBackend:
+		return ml.LoadModel(modelFile, gpt4allLM(gpt4all.SetThreads(int(threads)), gpt4all.SetModelType(gpt4all.MPTType)))
+	case Gpt4AllJBackend:
+		return ml.LoadModel(modelFile, gpt4allLM(gpt4all.SetThreads(int(threads)), gpt4all.SetModelType(gpt4all.GPTJType)))
+	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)
+	default:
+		return nil, fmt.Errorf("backend unsupported: %s", backendString)
+	}
+}
+
+func (ml *ModelLoader) GreedyLoader(modelFile string, llamaOpts []llama.ModelOption, threads uint32) (interface{}, error) {
+	log.Debug().Msgf("Loading models greedly")
+
+	ml.mu.Lock()
+	m, exists := ml.models[modelFile]
+	if exists {
+		ml.mu.Unlock()
+		return m, nil
+	}
+	ml.mu.Unlock()
+	var err error
+
+	for _, b := range backends {
+		if b == BloomzBackend || b == WhisperBackend || b == RwkvBackend { // do not autoload bloomz/whisper/rwkv
+			continue
+		}
+		log.Debug().Msgf("[%s] Attempting to load", b)
+		model, modelerr := ml.BackendLoader(b, modelFile, llamaOpts, threads)
+		if modelerr == nil && model != nil {
+			log.Debug().Msgf("[%s] Loads OK", b)
+			return model, nil
+		} else if modelerr != nil {
+			err = multierror.Append(err, modelerr)
+			log.Debug().Msgf("[%s] Fails: %s", b, modelerr.Error())
+		}
+	}
+
+	return nil, fmt.Errorf("could not load model - all backends returned error: %s", err.Error())
+}

pkg/model/loader.go

@@ -11,42 +11,31 @@ import (
 	"text/template"
 
 	"github.com/rs/zerolog/log"
-
-	gpt2 "github.com/go-skynet/go-gpt2.cpp"
-	gptj "github.com/go-skynet/go-gpt4all-j.cpp"
-	llama "github.com/go-skynet/go-llama.cpp"
 )
 
 type ModelLoader struct {
-	modelPath string
+	ModelPath string
 	mu        sync.Mutex
-
-	models            map[string]*llama.LLama
-	gptmodels         map[string]*gptj.GPTJ
-	gpt2models        map[string]*gpt2.GPT2
-	gptstablelmmodels map[string]*gpt2.StableLM
-
+	// TODO: this needs generics
+	models           map[string]interface{}
 	promptsTemplates map[string]*template.Template
 }
 
 func NewModelLoader(modelPath string) *ModelLoader {
 	return &ModelLoader{
-		modelPath:         modelPath,
-		gpt2models:        make(map[string]*gpt2.GPT2),
-		gptmodels:         make(map[string]*gptj.GPTJ),
-		gptstablelmmodels: make(map[string]*gpt2.StableLM),
-		models:            make(map[string]*llama.LLama),
-		promptsTemplates:  make(map[string]*template.Template),
+		ModelPath:        modelPath,
+		models:           make(map[string]interface{}),
+		promptsTemplates: make(map[string]*template.Template),
 	}
 }
 
 func (ml *ModelLoader) ExistsInModelPath(s string) bool {
-	_, err := os.Stat(filepath.Join(ml.modelPath, s))
+	_, err := os.Stat(filepath.Join(ml.ModelPath, s))
 	return err == nil
 }
 
 func (ml *ModelLoader) ListModels() ([]string, error) {
-	files, err := ioutil.ReadDir(ml.modelPath)
+	files, err := ioutil.ReadDir(ml.ModelPath)
 	if err != nil {
 		return []string{}, err
 	}
@@ -70,7 +59,18 @@ func (ml *ModelLoader) TemplatePrefix(modelName string, in interface{}) (string,
 
 	m, ok := ml.promptsTemplates[modelName]
 	if !ok {
-		return "", fmt.Errorf("no prompt template available")
+		modelFile := filepath.Join(ml.ModelPath, modelName)
+		if err := ml.loadTemplateIfExists(modelName, modelFile); err != nil {
+			return "", err
+		}
+
+		t, exists := ml.promptsTemplates[modelName]
+		if exists {
+			m = t
+		}
+	}
+	if m == nil {
+		return "", fmt.Errorf("failed loading any template")
 	}
 
 	var buf bytes.Buffer
@@ -88,14 +88,14 @@ func (ml *ModelLoader) loadTemplateIfExists(modelName, modelFile string) error {
 	}
 
 	// Check if the model path exists
-	// skip any error here - we run anyway if a template is not exist
+	// skip any error here - we run anyway if a template does not exist
 	modelTemplateFile := fmt.Sprintf("%s.tmpl", modelName)
 
 	if !ml.ExistsInModelPath(modelTemplateFile) {
 		return nil
 	}
 
-	dat, err := os.ReadFile(filepath.Join(ml.modelPath, modelTemplateFile))
+	dat, err := os.ReadFile(filepath.Join(ml.ModelPath, modelTemplateFile))
 	if err != nil {
 		return err
 	}
@@ -110,156 +110,21 @@ func (ml *ModelLoader) loadTemplateIfExists(modelName, modelFile string) error {
 	return nil
 }
 
-func (ml *ModelLoader) LoadStableLMModel(modelName string) (*gpt2.StableLM, error) {
+func (ml *ModelLoader) LoadModel(modelName string, loader func(string) (interface{}, error)) (interface{}, error) {
 	ml.mu.Lock()
 	defer ml.mu.Unlock()
 
 	// Check if we already have a loaded model
-	if !ml.ExistsInModelPath(modelName) {
-		return nil, fmt.Errorf("model does not exist")
-	}
-
-	if m, ok := ml.gptstablelmmodels[modelName]; ok {
-		log.Debug().Msgf("Model already loaded in memory: %s", modelName)
-		return m, nil
-	}
-
-	// Load the model and keep it in memory for later use
-	modelFile := filepath.Join(ml.modelPath, modelName)
-	log.Debug().Msgf("Loading model in memory from file: %s", modelFile)
-
-	model, err := gpt2.NewStableLM(modelFile)
-	if err != nil {
-		return nil, err
-	}
-
-	// If there is a prompt template, load it
-	if err := ml.loadTemplateIfExists(modelName, modelFile); err != nil {
-		return nil, err
-	}
-
-	ml.gptstablelmmodels[modelName] = model
-	return model, err
-}
-
-func (ml *ModelLoader) LoadGPT2Model(modelName string) (*gpt2.GPT2, error) {
-	ml.mu.Lock()
-	defer ml.mu.Unlock()
-
-	// Check if we already have a loaded model
-	if !ml.ExistsInModelPath(modelName) {
-		return nil, fmt.Errorf("model does not exist")
-	}
-
-	if m, ok := ml.gpt2models[modelName]; ok {
-		log.Debug().Msgf("Model already loaded in memory: %s", modelName)
-		return m, nil
-	}
-
-	// TODO: This needs refactoring, it's really bad to have it in here
-	// Check if we have a GPTStable model loaded instead - if we do we return an error so the API tries with StableLM
-	if _, ok := ml.gptstablelmmodels[modelName]; ok {
-		log.Debug().Msgf("Model is GPTStableLM: %s", modelName)
-		return nil, fmt.Errorf("this model is a GPTStableLM one")
-	}
-
-	// Load the model and keep it in memory for later use
-	modelFile := filepath.Join(ml.modelPath, modelName)
-	log.Debug().Msgf("Loading model in memory from file: %s", modelFile)
-
-	model, err := gpt2.New(modelFile)
-	if err != nil {
-		return nil, err
-	}
-
-	// If there is a prompt template, load it
-	if err := ml.loadTemplateIfExists(modelName, modelFile); err != nil {
-		return nil, err
-	}
-
-	ml.gpt2models[modelName] = model
-	return model, err
-}
-
-func (ml *ModelLoader) LoadGPTJModel(modelName string) (*gptj.GPTJ, error) {
-	ml.mu.Lock()
-	defer ml.mu.Unlock()
-
-	// Check if we already have a loaded model
-	if !ml.ExistsInModelPath(modelName) {
-		return nil, fmt.Errorf("model does not exist")
-	}
-
-	if m, ok := ml.gptmodels[modelName]; ok {
-		log.Debug().Msgf("Model already loaded in memory: %s", modelName)
-		return m, nil
-	}
-
-	// TODO: This needs refactoring, it's really bad to have it in here
-	// Check if we have a GPT2 model loaded instead - if we do we return an error so the API tries with GPT2
-	if _, ok := ml.gpt2models[modelName]; ok {
-		log.Debug().Msgf("Model is GPT2: %s", modelName)
-		return nil, fmt.Errorf("this model is a GPT2 one")
-	}
-	if _, ok := ml.gptstablelmmodels[modelName]; ok {
-		log.Debug().Msgf("Model is GPTStableLM: %s", modelName)
-		return nil, fmt.Errorf("this model is a GPTStableLM one")
-	}
-
-	// Load the model and keep it in memory for later use
-	modelFile := filepath.Join(ml.modelPath, modelName)
-	log.Debug().Msgf("Loading model in memory from file: %s", modelFile)
-
-	model, err := gptj.New(modelFile)
-	if err != nil {
-		return nil, err
-	}
-
-	// If there is a prompt template, load it
-	if err := ml.loadTemplateIfExists(modelName, modelFile); err != nil {
-		return nil, err
-	}
-
-	ml.gptmodels[modelName] = model
-	return model, err
-}
-
-func (ml *ModelLoader) LoadLLaMAModel(modelName string, opts ...llama.ModelOption) (*llama.LLama, error) {
-	ml.mu.Lock()
-	defer ml.mu.Unlock()
-
-	log.Debug().Msgf("Loading model name: %s", modelName)
-
-	// Check if we already have a loaded model
-	if !ml.ExistsInModelPath(modelName) {
-		return nil, fmt.Errorf("model does not exist")
-	}
-
 	if m, ok := ml.models[modelName]; ok {
 		log.Debug().Msgf("Model already loaded in memory: %s", modelName)
 		return m, nil
 	}
 
-	// TODO: This needs refactoring, it's really bad to have it in here
-	// Check if we have a GPTJ model loaded instead - if we do we return an error so the API tries with GPTJ
-	if _, ok := ml.gptmodels[modelName]; ok {
-		log.Debug().Msgf("Model is GPTJ: %s", modelName)
-		return nil, fmt.Errorf("this model is a GPTJ one")
-	}
-	if _, ok := ml.gpt2models[modelName]; ok {
-		log.Debug().Msgf("Model is GPT2: %s", modelName)
-		return nil, fmt.Errorf("this model is a GPT2 one")
-	}
-	if _, ok := ml.gptstablelmmodels[modelName]; ok {
-		log.Debug().Msgf("Model is GPTStableLM: %s", modelName)
-		return nil, fmt.Errorf("this model is a GPTStableLM one")
-	}
-
 	// Load the model and keep it in memory for later use
-	modelFile := filepath.Join(ml.modelPath, modelName)
+	modelFile := filepath.Join(ml.ModelPath, modelName)
 	log.Debug().Msgf("Loading model in memory from file: %s", modelFile)
 
-	model, err := llama.New(modelFile, opts...)
+	model, err := loader(modelFile)
 	if err != nil {
 		return nil, err
 	}
@@ -270,5 +135,5 @@ func (ml *ModelLoader) LoadLLaMAModel(modelName string, opts ...llama.ModelOptio
 	}
 
 	ml.models[modelName] = model
-	return model, err
+	return model, nil
 }

pkg/stablediffusion/generate.go

@@ -0,0 +1,23 @@
+//go:build stablediffusion
+// +build stablediffusion
+
+package stablediffusion
+
+import (
+	stableDiffusion "github.com/mudler/go-stable-diffusion"
+)
+
+func GenerateImage(height, width, mode, step, seed int, positive_prompt, negative_prompt, dst, asset_dir string) error {
+	return stableDiffusion.GenerateImage(
+		height,
+		width,
+		mode,
+		step,
+		seed,
+		positive_prompt,
+		negative_prompt,
+		dst,
+		"",
+		asset_dir,
+	)
+}

pkg/stablediffusion/generate_unsupported.go

@@ -0,0 +1,10 @@
+//go:build !stablediffusion
+// +build !stablediffusion
+
+package stablediffusion
+
+import "fmt"
+
+func GenerateImage(height, width, mode, step, seed int, positive_prompt, negative_prompt, dst, asset_dir string) error {
+	return fmt.Errorf("This version of LocalAI was built without the stablediffusion tag")
+}

pkg/stablediffusion/stablediffusion.go

@@ -0,0 +1,20 @@
+package stablediffusion
+
+import "os"
+
+type StableDiffusion struct {
+	assetDir string
+}
+
+func New(assetDir string) (*StableDiffusion, error) {
+	if _, err := os.Stat(assetDir); err != nil {
+		return nil, err
+	}
+	return &StableDiffusion{
+		assetDir: assetDir,
+	}, nil
+}
+
+func (s *StableDiffusion) GenerateImage(height, width, mode, step, seed int, positive_prompt, negative_prompt, dst string) error {
+	return GenerateImage(height, width, mode, step, seed, positive_prompt, negative_prompt, dst, s.assetDir)
+}

pkg/whisper/whisper.go

@@ -0,0 +1,90 @@
+package whisper
+
+import (
+	"fmt"
+	"os"
+	"os/exec"
+	"path/filepath"
+
+	"github.com/ggerganov/whisper.cpp/bindings/go/pkg/whisper"
+	wav "github.com/go-audio/wav"
+)
+
+func sh(c string) (string, error) {
+	cmd := exec.Command("/bin/sh", "-c", c)
+	cmd.Env = os.Environ()
+	o, err := cmd.CombinedOutput()
+	return string(o), err
+}
+
+// AudioToWav converts audio to wav for transcribe. It bashes out to ffmpeg
+// TODO: use https://github.com/mccoyst/ogg?
+func audioToWav(src, dst string) error {
+	out, err := sh(fmt.Sprintf("ffmpeg -i %s -format s16le -ar 16000 -ac 1 -acodec pcm_s16le %s", src, dst))
+	if err != nil {
+		return fmt.Errorf("error: %w out: %s", err, out)
+	}
+
+	return nil
+}
+
+func Transcript(model whisper.Model, audiopath, language string, threads uint) (string, error) {
+
+	dir, err := os.MkdirTemp("", "whisper")
+	if err != nil {
+		return "", err
+	}
+	defer os.RemoveAll(dir)
+
+	convertedPath := filepath.Join(dir, "converted.wav")
+
+	if err := audioToWav(audiopath, convertedPath); err != nil {
+		return "", err
+	}
+
+	// Open samples
+	fh, err := os.Open(convertedPath)
+	if err != nil {
+		return "", err
+	}
+	defer fh.Close()
+
+	// Read samples
+	d := wav.NewDecoder(fh)
+	buf, err := d.FullPCMBuffer()
+	if err != nil {
+		return "", err
+	}
+
+	data := buf.AsFloat32Buffer().Data
+
+	// Process samples
+	context, err := model.NewContext()
+	if err != nil {
+		return "", err
+
+	}
+
+	context.SetThreads(threads)
+
+	if language != "" {
+		context.SetLanguage(language)
+	} else {
+		context.SetLanguage("auto")
+	}
+
+	if err := context.Process(data, nil); err != nil {
+		return "", err
+	}
+
+	text := ""
+	for {
+		segment, err := context.NextSegment()
+		if err != nil {
+			break
+		}
+		text += segment.Text
+	}
+
+	return text, nil
+}

prompt-templates/wizardlm.tmpl

@@ -0,0 +1,3 @@
+{{.Input}}
+
+### Response:

renovate.json

@@ -1,17 +1,4 @@
 {
   "$schema": "https://docs.renovatebot.com/renovate-schema.json",
-  "extends": [
-    "config:base"
-  ],
-  "regexManagers": [
-    {
-      "fileMatch": [
-        "^Makefile$"
-      ],
-      "matchStrings": [
-        "#\\s*renovate:\\s*datasource=(?<datasource>.*?) depName=(?<depName>.*?)( datasourceTemplate=(?<datasourceTemplate>.*?))?( packageNameTemplate=(?<packageNameTemplate>.*?))?( depNameTemplate=(?<depNameTemplate>.*?))?( valueTemplate=(?<currentValueTemplate>.*?))?( versioning=(?<versioning>.*?))?\\s+.+_VERSION=(?<currentValue>.*?)\\s"
-      ],
-      "versioningTemplate": "{{#if versioning}}{{versioning}}{{/if}}"
-    }
-  ]
+  "extends": ["config:base"]
 }

tests/fixtures/completion.tmpl

@@ -0,0 +1 @@
+{{.Input}}