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50 Commits

Author SHA1 Message Date
Ettore Di Giacinto
c974dad799 Return usage in the API responses (#166) 2023-05-03 17:29:18 +02:00
Ettore Di Giacinto
4eae570ef5 Update docs (#163) 2023-05-03 15:51:54 +02:00
Ettore Di Giacinto
67992a7d99 feat: support slices or strings in the prompt completion endpoint (#162)
Signed-off-by: mudler <mudler@mocaccino.org>
2023-05-03 13:13:31 +02:00
renovate[bot]
0a4899f366 fix(deps): update github.com/go-skynet/go-llama.cpp digest to 8ceb616 (#150)
Co-authored-by: renovate[bot] <29139614+renovate[bot]@users.noreply.github.com>
2023-05-03 11:48:06 +02:00
renovate[bot]
1eb02f6c91 fix(deps): update module github.com/onsi/ginkgo/v2 to v2.9.3 (#161)
Co-authored-by: renovate[bot] <29139614+renovate[bot]@users.noreply.github.com>
2023-05-03 11:47:54 +02:00
mudler
575874e4fb readme: minor update 2023-05-03 11:46:29 +02:00
Ettore Di Giacinto
751b7eca62 feat: add rwkv support (#158)
Signed-off-by: mudler <mudler@mocaccino.org>
2023-05-03 11:45:22 +02:00
Ettore Di Giacinto
1ae7150810 feat: allow to specify default backend for model (#156)
Signed-off-by: mudler <mudler@c3os.io>
2023-05-03 00:31:28 +02:00
Ettore Di Giacinto
70caf9bf8c feat: support stopwords both string and arrays (#154) 2023-05-02 23:30:00 +02:00
Dave
0b226ac027 Stop parameter of OpenAIRequest changed to String Array (#153) 2023-05-02 22:02:45 +02:00
Ettore Di Giacinto
220d6fd59b feat: add stream events (#152) 2023-05-02 20:03:35 +02:00
antongisli
0a00a4b58e adding mac build and example (#151)
Co-authored-by: Ettore Di Giacinto <mudler@users.noreply.github.com>
2023-05-02 19:24:45 +02:00
Ettore Di Giacinto
156e15a4fa Bump llama.cpp, downgrade gpt4all-j (#149) 2023-05-02 16:07:18 +02:00
renovate[bot]
271d3f6673 fix(deps): update module github.com/valyala/fasthttp to v1.47.0 (#143)
Co-authored-by: renovate[bot] <29139614+renovate[bot]@users.noreply.github.com>
2023-05-01 23:36:58 +02:00
Ettore Di Giacinto
fec4ab93c5 docs: Add langchain to the example index (#147)
Signed-off-by: mudler <mudler@mocaccino.org>
2023-05-01 23:21:07 +02:00
renovate[bot]
38a7a7a54d fix(deps): update github.com/go-skynet/go-gpt4all-j.cpp digest to 77bf8c1 (#141)
Co-authored-by: renovate[bot] <29139614+renovate[bot]@users.noreply.github.com>
Co-authored-by: Ettore Di Giacinto <mudler@users.noreply.github.com>
2023-05-01 23:18:41 +02:00
Ettore Di Giacinto
0db0704e2c docs: Add slack-bot example (#145)
Signed-off-by: mudler <mudler@mocaccino.org>
2023-05-01 23:18:24 +02:00
Dave
88f472e5d2 Add LangchainJS Examples (#146) 2023-05-01 23:18:14 +02:00
Ettore Di Giacinto
92452d46da feat: add new gpt4all-j binding (#142) 2023-05-01 20:00:15 +02:00
Ettore Di Giacinto
ac70252d70 drop: remove helm charts, now in separate repo (#134)
Signed-off-by: mudler <mudler@mocaccino.org>
2023-05-01 18:07:41 +02:00
renovate[bot]
f6451d2518 fix(deps): update module github.com/urfave/cli/v2 to v2.25.3 (#140)
Co-authored-by: renovate[bot] <29139614+renovate[bot]@users.noreply.github.com>
2023-05-01 18:07:29 +02:00
Ettore Di Giacinto
2473f9d19b docs: add discord-bot preview (#137) 2023-05-01 11:03:34 +02:00
renovate[bot]
bc583385a9 fix(deps): update module github.com/urfave/cli/v2 to v2.25.2 (#136)
Co-authored-by: renovate[bot] <29139614+renovate[bot]@users.noreply.github.com>
2023-05-01 07:53:48 +02:00
renovate[bot]
8286bfbab7 fix(deps): update module github.com/sashabaranov/go-openai to v1.9.1 (#135)
Co-authored-by: renovate[bot] <29139614+renovate[bot]@users.noreply.github.com>
2023-05-01 07:52:20 +02:00
Ettore Di Giacinto
d129fabe3b docs: enhancements (#133) 2023-04-30 23:27:02 +02:00
renovate[bot]
2539867247 fix(deps): update github.com/go-skynet/go-llama.cpp digest to 377fd24 (#129)
Co-authored-by: renovate[bot] <29139614+renovate[bot]@users.noreply.github.com>
2023-04-30 11:09:48 +02:00
renovate[bot]
69fedb92d9 fix(deps): update github.com/go-skynet/go-llama.cpp digest to 361b9f8 (#127)
Co-authored-by: renovate[bot] <29139614+renovate[bot]@users.noreply.github.com>
2023-04-30 08:47:27 +02:00
Ettore Di Giacinto
54b5eadcc4 docs: add discord-bot example (#126) 2023-04-30 00:31:28 +02:00
Ettore Di Giacinto
16773e2a35 feat: make images to build sources on start (#124)
Signed-off-by: mudler <mudler@mocaccino.org>
2023-04-29 20:38:37 +02:00
renovate[bot]
78503c62b7 fix(deps): update github.com/go-skynet/go-llama.cpp digest to 9bf702f (#125)
Co-authored-by: renovate[bot] <29139614+renovate[bot]@users.noreply.github.com>
2023-04-29 16:53:39 +02:00
Ettore Di Giacinto
a330c9cee5 update: bump llama.cpp to 7f15c5c (#122)
Signed-off-by: mudler <mudler@mocaccino.org>
2023-04-29 15:20:50 +02:00
Ettore Di Giacinto
ff0867996e tests: increase timeout (#121) 2023-04-29 14:56:00 +02:00
Ettore Di Giacinto
1bf8f996d1 docs: clarify GPT4ALL-J licensing (#120) 2023-04-29 14:50:22 +02:00
Ettore Di Giacinto
52f4d993c1 feat: add /edit endpoint (#119) 2023-04-29 09:22:09 +02:00
renovate[bot]
d0ceebc5d7 fix(deps): update module github.com/valyala/fasthttp to v1.46.0 (#118)
Co-authored-by: renovate[bot] <29139614+renovate[bot]@users.noreply.github.com>
2023-04-28 22:44:29 +02:00
renovate[bot]
9122af3ae1 fix(deps): update github.com/go-skynet/go-llama.cpp digest to 3d084e4 (#108)
Co-authored-by: renovate[bot] <29139614+renovate[bot]@users.noreply.github.com>
2023-04-28 19:24:49 +02:00
Ettore Di Giacinto
b8533428bc bump: update llama.cpp (#117)
Signed-off-by: mudler <mudler@mocaccino.org>
2023-04-28 19:24:28 +02:00
Ettore Di Giacinto
677905334c docs: reorder section (#116) 2023-04-28 13:55:23 +02:00
Mauro Morales
d1d55d29a0 Add Kairos LocalAI example to the links (#115) 2023-04-28 13:52:17 +02:00
Ettore Di Giacinto
e07dba7ad6 docs: Add contributors (#113)
Signed-off-by: mudler <mudler@mocaccino.org>
2023-04-28 10:54:39 +02:00
Matthieu Talbot
062f832510 Add EXPOSE to Dockerfile (#107) 2023-04-27 16:45:24 +00:00
Ettore Di Giacinto
d0330bb64b docs: update example README.md (#104) 2023-04-27 17:46:14 +02:00
antongisli
91a23ec6ec Anton readme (#99)
Co-authored-by: Ettore Di Giacinto <mudler@users.noreply.github.com>
2023-04-27 17:17:03 +02:00
Ron Evans
0b000dd043 examples: correct typo in README (#103)
Signed-off-by: deadprogram <ron@hybridgroup.com>
2023-04-27 17:14:38 +02:00
Ettore Di Giacinto
c73ba91a66 docs: update README 2023-04-27 15:39:48 +02:00
Ettore Di Giacinto
dfc00f8bc1 docs: update README.md (#98) 2023-04-27 15:06:55 +02:00
Ettore Di Giacinto
a18ff9c9b3 docs: move api docs (#96) 2023-04-27 10:42:50 +02:00
Ettore Di Giacinto
d0199279ad docs: update, add config docs (#94) 2023-04-27 10:39:01 +02:00
Ettore Di Giacinto
9ede1e12d8 few typos and clarity changes (#91) (#92)
Co-authored-by: antongisli <anton@huge.geek.nz>
2023-04-27 07:47:39 +02:00
Ettore Di Giacinto
c806eae0de feat: config files and SSE (#83)
Signed-off-by: mudler <mudler@mocaccino.org>
Signed-off-by: Tyler Gillson <tyler.gillson@gmail.com>
Co-authored-by: Tyler Gillson <tyler.gillson@gmail.com>
2023-04-26 21:18:18 -07:00
64 changed files with 5589 additions and 4 deletions

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models
examples/chatbot-ui/models

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@@ -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

3
.gitignore vendored
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@@ -10,6 +10,5 @@ local-ai
!charts/*
# Ignore models
models/*.bin
models/ggml-*
models/*
test-models/

9
Dockerfile Normal file
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ARG GO_VERSION=1.20
ARG BUILD_TYPE=
FROM golang:$GO_VERSION
WORKDIR /build
RUN apt-get update && apt-get install -y cmake
COPY . .
RUN make prepare-sources
EXPOSE 8080
ENTRYPOINT [ "/build/entrypoint.sh" ]

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Dockerfile.dev Normal file
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ARG GO_VERSION=1.20
ARG DEBIAN_VERSION=11
ARG BUILD_TYPE=
FROM golang:$GO_VERSION as builder
WORKDIR /build
RUN apt-get update && apt-get install -y cmake
COPY . .
RUN make build
FROM debian:$DEBIAN_VERSION
COPY --from=builder /build/local-ai /usr/bin/local-ai
EXPOSE 8080
ENTRYPOINT [ "/usr/bin/local-ai" ]

5
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VERSION 0.7
build:
FROM DOCKERFILE -f Dockerfile .
SAVE ARTIFACT /usr/bin/local-ai AS LOCAL local-ai

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LICENSE Normal file
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MIT License
Copyright (c) 2023 go-skynet authors
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.

144
Makefile Normal file
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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-f4cef87
# 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
RWKV_REPO?=https://github.com/donomii/go-rwkv.cpp
RWKV_VERSION?=af62fcc432be2847acb6e0688b2c2491d6588d58
GREEN := $(shell tput -Txterm setaf 2)
YELLOW := $(shell tput -Txterm setaf 3)
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:$(shell pwd)/go-rwkv
LIBRARY_PATH=$(shell pwd)/go-llama:$(shell pwd)/go-gpt4all-j:$(shell pwd)/go-gpt2:$(shell pwd)/go-rwkv
# Use this if you want to set the default behavior
ifndef BUILD_TYPE
BUILD_TYPE:=default
endif
ifeq ($(BUILD_TYPE), "generic")
GENERIC_PREFIX:=generic-
else
GENERIC_PREFIX:=
endif
.PHONY: all test build vendor
all: help
## 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) && 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-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' {} +
## 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
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 ..
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) && 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_/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
$(GOCMD) mod edit -replace github.com/donomii/go-rwkv.cpp=$(shell pwd)/go-rwkv
prepare-sources: go-llama go-gpt2 go-gpt4all-j go-rwkv
$(GOCMD) mod download
## GENERIC
rebuild: ## Rebuilds the project
$(MAKE) -C go-llama clean
$(MAKE) -C go-gpt4all-j clean
$(MAKE) -C go-gpt2 clean
$(MAKE) -C go-rwkv clean
$(MAKE) build
prepare: prepare-sources go-llama/libbinding.a go-gpt4all-j/libgptj.a go-gpt2/libgpt2.a go-rwkv/librwkv.a replace ## Prepares for building
clean: ## Remove build related file
rm -fr ./go-llama
rm -rf ./go-gpt4all-j
rm -rf ./go-gpt2
rm -rf ./go-rwkv
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) ./
generic-build: ## Build the project using generic
BUILD_TYPE="generic" $(MAKE) build
## Run
run: prepare ## run local-ai
C_INCLUDE_PATH=${C_INCLUDE_PATH} LIBRARY_PATH=${LIBRARY_PATH} $(GOCMD) run ./main.go
test-models/testmodel:
mkdir test-models
wget https://huggingface.co/concedo/cerebras-111M-ggml/resolve/main/cerberas-111m-q4_0.bin -O test-models/testmodel
cp tests/fixtures/* test-models
test: prepare test-models/testmodel
cp tests/fixtures/* test-models
@C_INCLUDE_PATH=${C_INCLUDE_PATH} LIBRARY_PATH=${LIBRARY_PATH} CONFIG_FILE=$(abspath ./)/test-models/config.yaml MODELS_PATH=$(abspath ./)/test-models $(GOCMD) test -v -timeout 30m ./...
## Help:
help: ## Show this help.
@echo ''
@echo 'Usage:'
@echo ' ${YELLOW}make${RESET} ${GREEN}<target>${RESET}'
@echo ''
@echo 'Targets:'
@awk 'BEGIN {FS = ":.*?## "} { \
if (/^[a-zA-Z_-]+:.*?##.*$$/) {printf " ${YELLOW}%-20s${GREEN}%s${RESET}\n", $$1, $$2} \
else if (/^## .*$$/) {printf " ${CYAN}%s${RESET}\n", substr($$1,4)} \
}' $(MAKEFILE_LIST)

618
README.md Normal file
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<h1 align="center">
<br>
<img height="300" src="https://user-images.githubusercontent.com/2420543/233147843-88697415-6dbf-4368-a862-ab217f9f7342.jpeg"> <br>
LocalAI
<br>
</h1>
[![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 drop-in replacement REST API compatible with OpenAI for local CPU inferencing. It allows to run models locally or on-prem with consumer grade hardware. 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) and [ggml](https://github.com/ggerganov/ggml), including support GPT4ALL-J which is licensed under Apache 2.0.
- OpenAI compatible API
- Supports multiple-models
- 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.
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).
### News
- 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 )
### Socials and community chatter
- Follow [@LocalAI_API](https://twitter.com/LocalAI_API) on twitter.
- [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.
- [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.
## Model compatibility
It is compatible with the models supported by [llama.cpp](https://github.com/ggerganov/llama.cpp) supports also [GPT4ALL-J](https://github.com/nomic-ai/gpt4all) and [cerebras-GPT with ggml](https://huggingface.co/lxe/Cerebras-GPT-2.7B-Alpaca-SP-ggml).
Tested with:
- Vicuna
- Alpaca
- [GPT4ALL](https://github.com/nomic-ai/gpt4all)
- [GPT4ALL-J](https://gpt4all.io/models/ggml-gpt4all-j.bin)
- Koala
- [cerebras-GPT with ggml](https://huggingface.co/lxe/Cerebras-GPT-2.7B-Alpaca-SP-ggml)
- [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 older models to the new format, see [here](https://github.com/ggerganov/llama.cpp#using-gpt4all) for instance to run `gpt4all`.
### RWKV
<details>
For `rwkv` models, you need to put also the associated tokenizer along with the ggml model:
```
ls models
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>
## Usage
> `LocalAI` comes by default as a container image. You can check out all the available images with corresponding tags [here](https://quay.io/repository/go-skynet/local-ai?tab=tags&tag=latest).
The easiest way to run LocalAI is by using `docker-compose`:
```bash
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/
# (optional) Edit the .env file to set things like context size and threads
# vim .env
# start with docker-compose
docker-compose up -d --build
# Now API is accessible at localhost:8080
curl http://localhost:8080/v1/models
# {"object":"list","data":[{"id":"your-model.bin","object":"model"}]}
curl http://localhost:8080/v1/completions -H "Content-Type: application/json" -d '{
"model": "your-model.bin",
"prompt": "A long time ago in a galaxy far, far away",
"temperature": 0.7
}'
```
### Example: Use GPT4ALL-J model
<details>
```bash
# Clone LocalAI
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
# Use a template from the examples
cp -rf prompt-templates/ggml-gpt4all-j.tmpl models/
# (optional) Edit the .env file to set things like context size and threads
# vim .env
# start with docker-compose
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"}]}
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
}'
# {"model":"ggml-gpt4all-j","choices":[{"message":{"role":"assistant","content":"I'm doing well, thanks. How about you?"}}]}
```
</details>
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 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.
</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 sibling file, `foo.bin.tmpl` which will be used as a default prompt and can be used with alpaca:
```
The below instruction describes a task. Write a response that appropriately completes the request.
### Instruction:
{{.Input}}
### Response:
```
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>
### CLI
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. |
</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`:
```bash
docker run -p 8080:8080 -ti --rm quay.io/go-skynet/local-ai:latest --models-path /path/to/models --context-size 700 --threads 4
```
You should see:
```
┌───────────────────────────────────────────────────┐
│ Fiber v2.42.0 │
│ http://127.0.0.1:8080 │
│ (bound on host 0.0.0.0 and port 8080) │
│ │
│ Handlers ............. 1 Processes ........... 1 │
│ Prefork ....... Disabled PID ................. 1 │
└───────────────────────────────────────────────────┘
```
</details>
### Build locally
<details>
In order to build the `LocalAI` container image locally you can use `docker`:
```
# build the image
docker build -t LocalAI .
docker run LocalAI
```
Or you can build the binary with `make`:
```
make build
```
</details>
### 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>
### 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).
Following the list of endpoints/parameters supported.
Note:
- 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
<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:
```
curl http://localhost:8080/v1/chat/completions -H "Content-Type: application/json" -d '{
"model": "ggml-koala-7b-model-q4_0-r2.bin",
"messages": [{"role": "user", "content": "Say this is a test!"}],
"temperature": 0.7
}'
```
Available additional parameters: `top_p`, `top_k`, `max_tokens`
</details>
### Edit completions
<details>
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",
"prompt": "A long time ago in a galaxy far, far away",
"temperature": 0.7
}'
```
Available additional parameters: `top_p`, `top_k`, `max_tokens`
</details>
### List models
<details>
You can list all the models available with:
```
curl http://localhost:8080/v1/models
```
</details>
## Frequently asked questions
Here are answers to some of the most common questions.
### How do I get models?
<details>
Most ggml-based models should work, but newer models may require additions to the API. If a model doesn't work, please feel free to open up issues. However, be cautious about downloading models from the internet and directly onto your machine, as there may be security vulnerabilities in lama.cpp or ggml that could be maliciously exploited. Some models can be found on Hugging Face: https://huggingface.co/models?search=ggml, or models from gpt4all should also work: https://github.com/nomic-ai/gpt4all.
</details>
### What's the difference with Serge, or XXX?
<details>
LocalAI is a multi-model solution that doesn't focus on a specific model type (e.g., llama.cpp or alpaca.cpp), and it handles all of these internally for faster inference, easy to set up locally and deploy to Kubernetes.
</details>
### Can I use it with a Discord bot, or XXX?
<details>
Yes! If the client uses OpenAI and supports setting a different base URL to send requests to, you can use the LocalAI endpoint. This allows to use this with every application that was supposed to work with OpenAI, but without changing the application!
</details>
### Can this leverage GPUs?
<details>
Not currently, as ggml doesn't support GPUs yet: https://github.com/ggerganov/llama.cpp/discussions/915.
</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)
</details>
### Does it work with AutoGPT?
<details>
AutoGPT currently doesn't allow to set a different API URL, but there is a PR open for it, so this should be possible soon!
</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)
## 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) and [gpt4all](https://github.com/go-skynet/LocalAI/issues/85)
- [x] Multi-model support
- [x] Have a webUI!
- [x] Allow configuration of defaults for models.
- [ ] 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 [mudler](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)
- [donomii/go-rwkv.cpp](https://github.com/donomii/go-rwkv.cpp)
## Acknowledgements
- [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!)
## Contributors
<a href="https://github.com/go-skynet/LocalAI/graphs/contributors">
<img src="https://contrib.rocks/image?repo=go-skynet/LocalAI" />
</a>

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api/api.go Normal file
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package api
import (
"errors"
model "github.com/go-skynet/LocalAI/pkg/model"
"github.com/gofiber/fiber/v2"
"github.com/gofiber/fiber/v2/middleware/cors"
"github.com/gofiber/fiber/v2/middleware/recover"
"github.com/rs/zerolog"
"github.com/rs/zerolog/log"
)
func App(configFile string, loader *model.ModelLoader, threads, ctxSize int, f16 bool, debug, disableMessage bool) *fiber.App {
zerolog.SetGlobalLevel(zerolog.InfoLevel)
if debug {
zerolog.SetGlobalLevel(zerolog.DebugLevel)
}
// Return errors as JSON responses
app := fiber.New(fiber.Config{
DisableStartupMessage: disableMessage,
// Override default error handler
ErrorHandler: func(ctx *fiber.Ctx, err error) error {
// Status code defaults to 500
code := fiber.StatusInternalServerError
// Retrieve the custom status code if it's a *fiber.Error
var e *fiber.Error
if errors.As(err, &e) {
code = e.Code
}
// Send custom error page
return ctx.Status(code).JSON(
ErrorResponse{
Error: &APIError{Message: err.Error(), Code: code},
},
)
},
})
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())
// openAI compatible API endpoint
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/edits", editEndpoint(cm, debug, loader, threads, ctxSize, f16))
app.Post("/edits", editEndpoint(cm, debug, loader, threads, ctxSize, f16))
app.Post("/v1/completions", completionEndpoint(cm, debug, loader, threads, ctxSize, f16))
app.Post("/completions", completionEndpoint(cm, debug, loader, threads, ctxSize, f16))
app.Get("/v1/models", listModels(loader, cm))
app.Get("/models", listModels(loader, cm))
return app
}

138
api/api_test.go Normal file
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package api_test
import (
"context"
"os"
. "github.com/go-skynet/LocalAI/api"
"github.com/go-skynet/LocalAI/pkg/model"
"github.com/gofiber/fiber/v2"
. "github.com/onsi/ginkgo/v2"
. "github.com/onsi/gomega"
openaigo "github.com/otiai10/openaigo"
"github.com/sashabaranov/go-openai"
)
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, 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("returns the models list", func() {
models, err := client.ListModels(context.TODO())
Expect(err).ToNot(HaveOccurred())
Expect(len(models.Models)).To(Equal(3))
Expect(models.Models[0].ID).To(Equal("testmodel"))
})
It("can generate completions", func() {
resp, err := client.CreateCompletion(context.TODO(), openai.CompletionRequest{Model: "testmodel", 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 ", 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: could not load model - all backends returned error: 5 errors occurred:"))
})
})
Context("Config file", func() {
BeforeEach(func() {
modelLoader = model.NewModelLoader(os.Getenv("MODELS_PATH"))
app = App(os.Getenv("CONFIG_FILE"), modelLoader, 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(5))
Expect(models.Models[0].ID).To(Equal("testmodel"))
})
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())
})
})
})

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package api_test
import (
"testing"
. "github.com/onsi/ginkgo/v2"
. "github.com/onsi/gomega"
)
func TestLocalAI(t *testing.T) {
RegisterFailHandler(Fail)
RunSpecs(t, "LocalAI test suite")
}

102
api/config.go Normal file
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package api
import (
"fmt"
"io/ioutil"
"os"
"path/filepath"
"strings"
"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"`
Backend string `yaml:"backend"`
TemplateConfig TemplateConfig `yaml:"template"`
}
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
}

486
api/openai.go Normal file
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package api
import (
"bufio"
"bytes"
"encoding/json"
"fmt"
"os"
"path/filepath"
"strings"
model "github.com/go-skynet/LocalAI/pkg/model"
"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 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"`
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"`
// Prompt is read only by completion API calls
Prompt interface{} `json:"prompt" yaml:"prompt"`
// Edit endpoint
Instruction string `json:"instruction" yaml:"instruction"`
Input string `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"`
Seed int `json:"seed" yaml:"seed"`
}
func defaultRequest(modelFile string) OpenAIRequest {
return OpenAIRequest{
TopP: 0.7,
TopK: 80,
Maxtokens: 512,
Temperature: 0.9,
Model: modelFile,
}
}
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
}
}
func readConfig(cm ConfigMerger, c *fiber.Ctx, loader *model.ModelLoader, debug bool, threads, ctx int, f16 bool) (*Config, *OpenAIRequest, error) {
input := new(OpenAIRequest)
// Get input data from the request body
if err := c.BodyParser(input); err != nil {
return nil, nil, 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 == "" && !bearerExists {
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, 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
}
// 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),
}
} else {
config = &cfg
}
// Set the parameters for the language model prediction
updateConfig(config, input)
if threads != 0 {
config.Threads = threads
}
if ctx != 0 {
config.ContextSize = ctx
}
if f16 {
config.F16 = true
}
if debug {
config.Debug = true
}
return config, input, nil
}
// 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 {
config, input, err := readConfig(cm, c, 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)
predInput := []string{}
switch p := input.Prompt.(type) {
case string:
predInput = append(predInput, p)
case []interface{}:
for _, pp := range p {
if s, ok := pp.(string); ok {
predInput = append(predInput, s)
}
}
}
templateFile := config.Model
if config.TemplateConfig.Completion != "" {
templateFile = config.TemplateConfig.Completion
}
var result []Choice
for _, i := range predInput {
// 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)
}
}
func chatEndpoint(cm ConfigMerger, debug bool, loader *model.ModelLoader, threads, ctx int, f16 bool) func(c *fiber.Ctx) error {
return func(c *fiber.Ctx) error {
config, input, err := readConfig(cm, c, 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 {
r := config.Roles[i.Role]
if r == "" {
r = i.Role
}
content := fmt.Sprint(r, " ", 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 func() {
ComputeChoices(predInput, input, config, loader, func(s string, c *[]Choice) {}, func(s string) bool {
resp := OpenAIResponse{
Model: input.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",
}
responses <- resp
return true
})
close(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",
}
// 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 {
config, input, err := readConfig(cm, c, 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)
predInput := input.Input
templateFile := config.Model
if config.TemplateConfig.Edit != "" {
templateFile = config.TemplateConfig.Edit
}
// 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: predInput, Instruction: input.Instruction})
if err == nil {
predInput = templatedInput
log.Debug().Msgf("Template found, input modified to: %s", predInput)
}
result, err := ComputeChoices(predInput, input, config, loader, func(s string, c *[]Choice) {
*c = append(*c, Choice{Text: 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: "edit",
}
jsonResult, _ := json.Marshal(resp)
log.Debug().Msgf("Response: %s", jsonResult)
// Return the prediction in the response body
return c.JSON(resp)
}
}
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,
})
}
}

343
api/prediction.go Normal file
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package api
import (
"fmt"
"regexp"
"strings"
"sync"
"github.com/donomii/go-rwkv.cpp"
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/hashicorp/go-multierror"
)
const tokenizerSuffix = ".tokenizer.json"
// 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)
var loadedModels map[string]interface{} = map[string]interface{}{}
var muModels sync.Mutex
func backendLoader(backendString string, loader *model.ModelLoader, modelFile string, llamaOpts []llama.ModelOption, threads uint32) (model interface{}, err error) {
switch strings.ToLower(backendString) {
case "llama":
return loader.LoadLLaMAModel(modelFile, llamaOpts...)
case "stablelm":
return loader.LoadStableLMModel(modelFile)
case "gpt2":
return loader.LoadGPT2Model(modelFile)
case "gptj":
return loader.LoadGPTJModel(modelFile)
case "rwkv":
return loader.LoadRWKV(modelFile, modelFile+tokenizerSuffix, threads)
default:
return nil, fmt.Errorf("backend unsupported: %s", backendString)
}
}
func greedyLoader(loader *model.ModelLoader, modelFile string, llamaOpts []llama.ModelOption, threads uint32) (model interface{}, err error) {
updateModels := func(model interface{}) {
muModels.Lock()
defer muModels.Unlock()
loadedModels[modelFile] = model
}
muModels.Lock()
m, exists := loadedModels[modelFile]
if exists {
muModels.Unlock()
return m, nil
}
muModels.Unlock()
model, modelerr := loader.LoadLLaMAModel(modelFile, llamaOpts...)
if modelerr == nil {
updateModels(model)
return model, nil
} else {
err = multierror.Append(err, modelerr)
}
model, modelerr = loader.LoadGPTJModel(modelFile)
if modelerr == nil {
updateModels(model)
return model, nil
} else {
err = multierror.Append(err, modelerr)
}
model, modelerr = loader.LoadGPT2Model(modelFile)
if modelerr == nil {
updateModels(model)
return model, nil
} else {
err = multierror.Append(err, modelerr)
}
model, modelerr = loader.LoadStableLMModel(modelFile)
if modelerr == nil {
updateModels(model)
return model, nil
} else {
err = multierror.Append(err, modelerr)
}
model, modelerr = loader.LoadRWKV(modelFile, modelFile+tokenizerSuffix, threads)
if modelerr == nil {
updateModels(model)
return model, nil
} else {
err = multierror.Append(err, modelerr)
}
return nil, fmt.Errorf("could not load model - all backends returned error: %s", err.Error())
}
func ModelInference(s string, loader *model.ModelLoader, c Config, tokenCallback func(string) bool) (func() (string, error), error) {
supportStreams := false
modelFile := c.Model
// Try to load the model
llamaOpts := []llama.ModelOption{}
if c.ContextSize != 0 {
llamaOpts = append(llamaOpts, llama.SetContext(c.ContextSize))
}
if c.F16 {
llamaOpts = append(llamaOpts, llama.EnableF16Memory)
}
var inferenceModel interface{}
var err error
if c.Backend == "" {
inferenceModel, err = greedyLoader(loader, modelFile, llamaOpts, uint32(c.Threads))
} else {
inferenceModel, err = backendLoader(c.Backend, loader, 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) {
//model.ProcessInput("You are a chatbot that is very good at chatting. blah blah blah")
stopWord := "\n"
if len(c.StopWords) > 0 {
stopWord = c.StopWords[0]
}
response := model.GenerateResponse(c.Maxtokens, stopWord, float32(c.Temperature), float32(c.TopP), tokenCallback)
return response, nil
}
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.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 *gptj.GPTJ:
fn = func() (string, error) {
// Generate the prediction using the language model
predictOptions := []gptj.PredictOption{
gptj.SetTemperature(c.Temperature),
gptj.SetTopP(c.TopP),
gptj.SetTopK(c.TopK),
gptj.SetTokens(c.Maxtokens),
gptj.SetThreads(c.Threads),
}
if c.Batch != 0 {
predictOptions = append(predictOptions, gptj.SetBatch(c.Batch))
}
if c.Seed != 0 {
predictOptions = append(predictOptions, gptj.SetSeed(c.Seed))
}
return model.Predict(
s,
predictOptions...,
)
}
case *llama.LLama:
supportStreams = true
fn = func() (string, error) {
if tokenCallback != nil {
model.SetTokenCallback(tokenCallback)
}
// 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.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 model.Predict(
s,
predictOptions...,
)
}
}
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
}

15
docker-compose.yaml Normal file
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version: '3.6'
services:
api:
image: quay.io/go-skynet/local-ai:latest
build:
context: .
dockerfile: Dockerfile.dev
ports:
- 8080:8080
env_file:
- .env
volumes:
- ./models:/models:cached
command: ["/usr/bin/local-ai" ]

7
entrypoint.sh Executable file
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#!/bin/bash
cd /build
make build
./local-ai "$@"

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examples/README.md Normal file
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# Examples
Here is a list of projects that can easily be integrated with the LocalAI backend.
## Projects
- [chatbot-ui](https://github.com/go-skynet/LocalAI/tree/master/examples/chatbot-ui/) (by [@mkellerman](https://github.com/mkellerman))
- [discord-bot](https://github.com/go-skynet/LocalAI/tree/master/examples/discord-bot/) (by [@mudler](https://github.com/mudler))
- [langchain](https://github.com/go-skynet/LocalAI/tree/master/examples/langchain/) (by [@dave-gray101](https://github.com/dave-gray101))
- [langchain-python](https://github.com/go-skynet/LocalAI/tree/master/examples/langchain-python/) (by [@mudler](https://github.com/mudler))
- [slack-bot](https://github.com/go-skynet/LocalAI/tree/master/examples/slack-bot/) (by [@mudler](https://github.com/mudler))
## Want to contribute?
Create an issue, and put `Example: <description>` in the title! We will post your examples here.

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# 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 --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.

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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'

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{{.Input}}

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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

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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:

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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

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# 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
```

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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

1
examples/discord-bot/models Symbolic link
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@@ -0,0 +1 @@
../chatbot-ui/models/

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@@ -0,0 +1,33 @@
## 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".
```

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@@ -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" ]

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../chatbot-ui/models

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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))

2
examples/langchain/.gitignore vendored Normal file
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@@ -0,0 +1,2 @@
models/ggml-koala-13B-4bit-128g
models/ggml-gpt4all-j

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@@ -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" ]

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@@ -0,0 +1,31 @@
# langchain
Example of using langchain in TypeScript, with the standard OpenAI llm module, and LocalAI.
Example for python langchain to follow at a later date
Set up to make it easy to modify the `index.mts` file to look like any langchain example file.
**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
docker-compose up --build
```
## Copyright
Some of the example code in index.mts 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.

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@@ -0,0 +1,25 @@
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" ]
langchainjs:
build:
context: .
dockerfile: JS.Dockerfile
environment:
- 'OPENAI_API_KEY=sk-XXXXXXXXXXXXXXXXXXXX'
- 'OPENAI_API_HOST=http://api:8080/v1'
- 'MODEL_NAME=gpt-3.5-turbo' #gpt-3.5-turbo' # ggml-gpt4all-j' # ggml-koala-13B-4bit-128g'

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

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@@ -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"
]
}
]
}

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{
"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": "^18.16.3",
"typescript": "^5.0.4"
},
"dependencies": {
"langchain": "^0.0.67",
"typeorm": "^0.3.15"
}
}

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@@ -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_HOST'] || '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();

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@@ -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"]
}

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{{.Input}}

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@@ -0,0 +1,17 @@
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: " "
template:
completion: completion
chat: completion # gpt4all

View File

@@ -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:

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@@ -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

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@@ -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
```

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@@ -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

1
examples/slack-bot/models Symbolic link
View File

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

58
go.mod Normal file
View File

@@ -0,0 +1,58 @@
module github.com/go-skynet/LocalAI
go 1.19
require (
github.com/go-skynet/go-gpt2.cpp v0.0.0-20230422085954-245a5bfe6708
github.com/go-skynet/go-gpt4all-j.cpp v0.0.0-20230422090028-1f7bff57f66c
github.com/go-skynet/go-llama.cpp v0.0.0-20230502121737-8ceb6167e405
github.com/gofiber/fiber/v2 v2.44.0
github.com/hashicorp/go-multierror v1.1.1
github.com/jaypipes/ghw v0.10.0
github.com/onsi/ginkgo/v2 v2.9.3
github.com/onsi/gomega v1.27.6
github.com/otiai10/openaigo v1.1.0
github.com/rs/zerolog v1.29.1
github.com/sashabaranov/go-openai v1.9.1
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/andybalholm/brotli v1.0.5 // indirect
github.com/cpuguy83/go-md2man/v2 v2.0.2 // indirect
github.com/donomii/go-rwkv.cpp v0.0.0-20230502223004-0a3db3d72e7d // indirect
github.com/ghodss/yaml v1.0.0 // indirect
github.com/go-logr/logr v1.2.4 // indirect
github.com/go-ole/go-ole v1.2.6 // 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/hashicorp/errwrap v1.0.0 // indirect
github.com/jaypipes/pcidb v1.0.0 // indirect
github.com/klauspost/compress v1.16.3 // indirect
github.com/kr/text v0.2.0 // 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/tcplisten v1.0.0 // indirect
github.com/xrash/smetrics v0.0.0-20201216005158-039620a65673 // indirect
golang.org/x/net v0.9.0 // indirect
golang.org/x/sys v0.7.0 // indirect
golang.org/x/text v0.9.0 // indirect
golang.org/x/tools v0.8.0 // indirect
gopkg.in/yaml.v2 v2.4.0 // indirect
howett.net/plist v1.0.0 // indirect
)

190
go.sum Normal file
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@@ -0,0 +1,190 @@
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 v1.0.5 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=
github.com/chzyer/readline v0.0.0-20180603132655-2972be24d48e/go.mod h1:nSuG5e5PlCu98SY8svDHJxuZscDgtXS6KTTbou5AhLI=
github.com/chzyer/test v0.0.0-20180213035817-a1ea475d72b1/go.mod h1:Q3SI9o4m/ZMnBNeIyt5eFwwo7qiLfzFZmjNmxjkiQlU=
github.com/coreos/go-systemd/v22 v22.5.0/go.mod h1:Y58oyj3AT4RCenI/lSvhwexgC+NSVTIJ3seZv2GcEnc=
github.com/cpuguy83/go-md2man/v2 v2.0.2 h1:p1EgwI/C7NhT0JmVkwCD2ZBK8j4aeHQX2pMHHBfMQ6w=
github.com/cpuguy83/go-md2man/v2 v2.0.2/go.mod h1:tgQtvFlXSQOSOSIRvRPT7W67SCa46tRHOmNcaadrF8o=
github.com/creack/pty v1.1.9/go.mod h1:oKZEueFk5CKHvIhNR5MUki03XCEU+Q6VDXinZuGJ33E=
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/donomii/go-rwkv.cpp v0.0.0-20230502223004-0a3db3d72e7d h1:lSHwlYf1H4WAWYgf7rjEVTGen1qmigUq2Egpu8mnQiY=
github.com/donomii/go-rwkv.cpp v0.0.0-20230502223004-0a3db3d72e7d/go.mod h1:H6QBF7/Tz6DAEBDXQged4H1BvsmqY/K5FG9wQRGa01g=
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golang.org/x/sys v0.0.0-20200930185726-fdedc70b468f/go.mod h1:h1NjWce9XRLGQEsW7wpKNCjG9DtNlClVuFLEZdDNbEs=
golang.org/x/sys v0.0.0-20201119102817-f84b799fce68/go.mod h1:h1NjWce9XRLGQEsW7wpKNCjG9DtNlClVuFLEZdDNbEs=
golang.org/x/sys v0.0.0-20210615035016-665e8c7367d1/go.mod h1:oPkhp1MJrh7nUepCBck5+mAzfO9JrbApNNgaTdGDITg=
golang.org/x/sys v0.0.0-20210630005230-0f9fa26af87c/go.mod h1:oPkhp1MJrh7nUepCBck5+mAzfO9JrbApNNgaTdGDITg=
golang.org/x/sys v0.0.0-20210927094055-39ccf1dd6fa6/go.mod h1:oPkhp1MJrh7nUepCBck5+mAzfO9JrbApNNgaTdGDITg=
golang.org/x/sys v0.0.0-20220520151302-bc2c85ada10a/go.mod h1:oPkhp1MJrh7nUepCBck5+mAzfO9JrbApNNgaTdGDITg=
golang.org/x/sys v0.0.0-20220722155257-8c9f86f7a55f/go.mod h1:oPkhp1MJrh7nUepCBck5+mAzfO9JrbApNNgaTdGDITg=
golang.org/x/sys v0.0.0-20220811171246-fbc7d0a398ab/go.mod h1:oPkhp1MJrh7nUepCBck5+mAzfO9JrbApNNgaTdGDITg=
golang.org/x/sys v0.3.0/go.mod h1:oPkhp1MJrh7nUepCBck5+mAzfO9JrbApNNgaTdGDITg=
golang.org/x/sys v0.6.0/go.mod h1:oPkhp1MJrh7nUepCBck5+mAzfO9JrbApNNgaTdGDITg=
golang.org/x/sys v0.7.0 h1:3jlCCIQZPdOYu1h8BkNvLz8Kgwtae2cagcG/VamtZRU=
golang.org/x/sys v0.7.0/go.mod h1:oPkhp1MJrh7nUepCBck5+mAzfO9JrbApNNgaTdGDITg=
golang.org/x/term v0.0.0-20201126162022-7de9c90e9dd1/go.mod h1:bj7SfCRtBDWHUb9snDiAeCFNEtKQo2Wmx5Cou7ajbmo=
golang.org/x/term v0.0.0-20210927222741-03fcf44c2211/go.mod h1:jbD1KX2456YbFQfuXm/mYQcufACuNUgVhRMnK/tPxf8=
golang.org/x/term v0.3.0/go.mod h1:q750SLmJuPmVoN1blW3UFBPREJfb1KmY3vwxfr+nFDA=
golang.org/x/text v0.3.0/go.mod h1:NqM8EUOU14njkJ3fqMW+pc6Ldnwhi/IjpwHt7yyuwOQ=
golang.org/x/text v0.3.3/go.mod h1:5Zoc/QRtKVWzQhOtBMvqHzDpF6irO9z98xDceosuGiQ=
golang.org/x/text v0.3.7/go.mod h1:u+2+/6zg+i71rQMx5EYifcz6MCKuco9NR6JIITiCfzQ=
golang.org/x/text v0.5.0/go.mod h1:mrYo+phRRbMaCq/xk9113O4dZlRixOauAjOtrjsXDZ8=
golang.org/x/text v0.8.0 h1:57P1ETyNKtuIjB4SRd15iJxuhj8Gc416Y78H3qgMh68=
golang.org/x/text v0.8.0/go.mod h1:e1OnstbJyHTd6l/uOt8jFFHp6TRDWZR/bV3emEE/zU8=
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/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/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 v3.0.1 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=

97
main.go Normal file
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package main
import (
"os"
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"
)
func main() {
log.Logger = log.Output(zerolog.ConsoleWriter{Out: os.Stderr})
path, err := os.Getwd()
if err != nil {
log.Error().Msgf("error: %s", err.Error())
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.",
Flags: []cli.Flag{
&cli.BoolFlag{
Name: "f16",
EnvVars: []string{"F16"},
},
&cli.BoolFlag{
Name: "debug",
EnvVars: []string{"DEBUG"},
},
&cli.IntFlag{
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,
},
&cli.StringFlag{
Name: "models-path",
DefaultText: "Path containing models used for inferencing",
EnvVars: []string{"MODELS_PATH"},
Value: path,
},
&cli.StringFlag{
Name: "config-file",
DefaultText: "Config file",
EnvVars: []string{"CONFIG_FILE"},
},
&cli.StringFlag{
Name: "address",
DefaultText: "Bind address for the API server.",
EnvVars: []string{"ADDRESS"},
Value: ":8080",
},
&cli.IntFlag{
Name: "context-size",
DefaultText: "Default context size of the model",
EnvVars: []string{"CONTEXT_SIZE"},
Value: 512,
},
},
Description: `
LocalAI is a drop-in replacement OpenAI API which runs inference locally.
Some of the models compatible are:
- Vicuna
- Koala
- GPT4ALL
- GPT4ALL-J
- Cerebras
- Alpaca
- StableLM (ggml quantized)
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(ctx.String("config-file"), model.NewModelLoader(ctx.String("models-path")), ctx.Int("threads"), ctx.Int("context-size"), ctx.Bool("f16"), ctx.Bool("debug"), false).Listen(ctx.String("address"))
},
}
err = app.Run(os.Args)
if err != nil {
log.Error().Msgf("error: %s", err.Error())
os.Exit(1)
}
}

0
models/.keep Normal file
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285
pkg/model/loader.go Normal file
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package model
import (
"bytes"
"fmt"
"io/ioutil"
"os"
"path/filepath"
"strings"
"sync"
"text/template"
"github.com/rs/zerolog/log"
rwkv "github.com/donomii/go-rwkv.cpp"
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
mu sync.Mutex
models map[string]*llama.LLama
gptmodels map[string]*gptj.GPTJ
gpt2models map[string]*gpt2.GPT2
gptstablelmmodels map[string]*gpt2.StableLM
rwkv map[string]*rwkv.RwkvState
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),
rwkv: make(map[string]*rwkv.RwkvState),
promptsTemplates: make(map[string]*template.Template),
}
}
func (ml *ModelLoader) ExistsInModelPath(s string) bool {
_, err := os.Stat(filepath.Join(ml.ModelPath, s))
return err == nil
}
func (ml *ModelLoader) ListModels() ([]string, error) {
files, err := ioutil.ReadDir(ml.ModelPath)
if err != nil {
return []string{}, err
}
models := []string{}
for _, file := range files {
// Skip templates, YAML and .keep files
if strings.HasSuffix(file.Name(), ".tmpl") || strings.HasSuffix(file.Name(), ".keep") || strings.HasSuffix(file.Name(), ".yaml") || strings.HasSuffix(file.Name(), ".yml") {
continue
}
models = append(models, file.Name())
}
return models, nil
}
func (ml *ModelLoader) TemplatePrefix(modelName string, in interface{}) (string, error) {
ml.mu.Lock()
defer ml.mu.Unlock()
m, ok := ml.promptsTemplates[modelName]
if !ok {
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 "", nil
}
var buf bytes.Buffer
if err := m.Execute(&buf, in); err != nil {
return "", err
}
return buf.String(), nil
}
func (ml *ModelLoader) loadTemplateIfExists(modelName, modelFile string) error {
// Check if the template was already loaded
if _, ok := ml.promptsTemplates[modelName]; ok {
return nil
}
// Check if the model path exists
// skip any error here - we run anyway if a template does not exist
modelTemplateFile := fmt.Sprintf("%s.tmpl", modelName)
if !ml.ExistsInModelPath(modelTemplateFile) {
return nil
}
dat, err := os.ReadFile(filepath.Join(ml.ModelPath, modelTemplateFile))
if err != nil {
return err
}
// Parse the template
tmpl, err := template.New("prompt").Parse(string(dat))
if err != nil {
return err
}
ml.promptsTemplates[modelName] = tmpl
return nil
}
func (ml *ModelLoader) LoadStableLMModel(modelName string) (*gpt2.StableLM, 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
}
// 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
}
// 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) LoadRWKV(modelName, tokenFile string, threads uint32) (*rwkv.RwkvState, 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.rwkv[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)
tokenPath := filepath.Join(ml.ModelPath, tokenFile)
log.Debug().Msgf("Loading model in memory from file: %s", modelFile)
model := rwkv.LoadFiles(modelFile, tokenPath, threads)
if model == nil {
return nil, fmt.Errorf("could not load model")
}
ml.rwkv[modelName] = model
return model, nil
}
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
}
// 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 := llama.New(modelFile, opts...)
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.models[modelName] = model
return model, err
}

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@@ -0,0 +1,6 @@
Below is an instruction that describes a task. Write a response that appropriately completes the request.
### Instruction:
{{.Input}}
### Response:

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@@ -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:

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@@ -0,0 +1 @@
BEGINNING OF CONVERSATION: USER: {{.Input}} GPT:

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@@ -0,0 +1,6 @@
Below is an instruction that describes a task. Write a response that appropriately completes the request.
### Instruction:
{{.Input}}
### Response:

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

17
renovate.json Normal file
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@@ -0,0 +1,17 @@
{
"$schema": "https://docs.renovatebot.com/renovate-schema.json",
"extends": [
"config:base"
],
"regexManagers": [
{
"fileMatch": [
"^Makefile$"
],
"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}}"
}
]
}

1
tests/fixtures/completion.tmpl vendored Normal file
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{{.Input}}

28
tests/fixtures/config.yaml vendored Normal file
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- 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

4
tests/fixtures/ggml-gpt4all-j.tmpl vendored Normal file
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@@ -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:

14
tests/fixtures/gpt4.yaml vendored Normal file
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@@ -0,0 +1,14 @@
name: gpt4all
parameters:
model: testmodel
context_size: 512
threads: 10
stopwords:
- "HUMAN:"
- "### Response:"
roles:
user: "HUMAN:"
system: "GPT:"
template:
completion: completion
chat: ggml-gpt4all-j

14
tests/fixtures/gpt4_2.yaml vendored Normal file
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@@ -0,0 +1,14 @@
name: gpt4all-2
parameters:
model: testmodel
context_size: 1024
threads: 5
stopwords:
- "HUMAN:"
- "### Response:"
roles:
user: "HUMAN:"
system: "GPT:"
template:
completion: completion
chat: ggml-gpt4all-j