mirror of
https://github.com/mudler/LocalAI.git
synced 2026-02-03 11:13:31 -05:00
Compare commits
1 Commits
| Author | SHA1 | Date | |
|---|---|---|---|
|
eb137c8a84 |
@@ -1,2 +1 @@
|
||||
models
|
||||
examples/chatbot-ui/models
|
||||
9
.github/bump_deps.sh
vendored
9
.github/bump_deps.sh
vendored
@@ -1,9 +0,0 @@
|
||||
#!/bin/bash
|
||||
set -xe
|
||||
REPO=$1
|
||||
BRANCH=$2
|
||||
VAR=$3
|
||||
|
||||
LAST_COMMIT=$(curl -s -H "Accept: application/vnd.github.VERSION.sha" "https://api.github.com/repos/$REPO/commits/$BRANCH")
|
||||
|
||||
sed -i Makefile -e "s/$VAR?=.*/$VAR?=$LAST_COMMIT/"
|
||||
42
.github/workflows/bump_deps.yaml
vendored
42
.github/workflows/bump_deps.yaml
vendored
@@ -1,42 +0,0 @@
|
||||
name: Bump dependencies
|
||||
on:
|
||||
schedule:
|
||||
- cron: 0 20 * * *
|
||||
workflow_dispatch:
|
||||
jobs:
|
||||
bump:
|
||||
strategy:
|
||||
fail-fast: false
|
||||
matrix:
|
||||
include:
|
||||
- repository: "go-skynet/go-gpt4all-j.cpp"
|
||||
variable: "GOGPT4ALLJ_VERSION"
|
||||
branch: "master"
|
||||
- repository: "go-skynet/go-llama.cpp"
|
||||
variable: "GOLLAMA_VERSION"
|
||||
branch: "master"
|
||||
- repository: "go-skynet/go-gpt2.cpp"
|
||||
variable: "GOGPT2_VERSION"
|
||||
branch: "master"
|
||||
- repository: "donomii/go-rwkv.cpp"
|
||||
variable: "RWKV_VERSION"
|
||||
branch: "main"
|
||||
runs-on: ubuntu-latest
|
||||
steps:
|
||||
- uses: actions/checkout@v3
|
||||
- name: Bump dependencies 🔧
|
||||
run: |
|
||||
bash .github/bump_deps.sh ${{ matrix.repository }} ${{ matrix.branch }} ${{ matrix.variable }}
|
||||
- name: Create Pull Request
|
||||
uses: peter-evans/create-pull-request@v5
|
||||
with:
|
||||
token: ${{ secrets.UPDATE_BOT_TOKEN }}
|
||||
push-to-fork: ci-forks/LocalAI
|
||||
commit-message: ':arrow_up: Update ${{ matrix.repository }}'
|
||||
title: ':arrow_up: Update ${{ matrix.repository }}'
|
||||
branch: "update/${{ matrix.variable }}"
|
||||
body: Bump of ${{ matrix.repository }} version
|
||||
signoff: true
|
||||
|
||||
|
||||
|
||||
4
.github/workflows/image.yml
vendored
4
.github/workflows/image.yml
vendored
@@ -54,8 +54,8 @@ jobs:
|
||||
uses: docker/login-action@v2
|
||||
with:
|
||||
registry: quay.io
|
||||
username: ${{ secrets.LOCALAI_REGISTRY_USERNAME }}
|
||||
password: ${{ secrets.LOCALAI_REGISTRY_PASSWORD }}
|
||||
username: ${{ secrets.QUAY_USERNAME }}
|
||||
password: ${{ secrets.QUAY_PASSWORD }}
|
||||
- name: Build
|
||||
if: github.event_name != 'pull_request'
|
||||
uses: docker/build-push-action@v4
|
||||
|
||||
4
.gitignore
vendored
4
.gitignore
vendored
@@ -2,7 +2,6 @@
|
||||
go-llama
|
||||
go-gpt4all-j
|
||||
go-gpt2
|
||||
go-rwkv
|
||||
|
||||
# LocalAI build binary
|
||||
LocalAI
|
||||
@@ -11,5 +10,6 @@ local-ai
|
||||
!charts/*
|
||||
|
||||
# Ignore models
|
||||
models/*
|
||||
models/*.bin
|
||||
models/ggml-*
|
||||
test-models/
|
||||
@@ -1,9 +0,0 @@
|
||||
ARG GO_VERSION=1.20
|
||||
ARG BUILD_TYPE=
|
||||
FROM golang:$GO_VERSION
|
||||
WORKDIR /build
|
||||
RUN apt-get update && apt-get install -y cmake
|
||||
COPY . .
|
||||
RUN make prepare-sources
|
||||
EXPOSE 8080
|
||||
ENTRYPOINT [ "/build/entrypoint.sh" ]
|
||||
@@ -1,14 +0,0 @@
|
||||
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" ]
|
||||
@@ -1,5 +0,0 @@
|
||||
VERSION 0.7
|
||||
|
||||
build:
|
||||
FROM DOCKERFILE -f Dockerfile .
|
||||
SAVE ARTIFACT /usr/bin/local-ai AS LOCAL local-ai
|
||||
21
LICENSE
21
LICENSE
@@ -1,21 +0,0 @@
|
||||
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.
|
||||
145
Makefile
145
Makefile
@@ -1,145 +0,0 @@
|
||||
GOCMD=go
|
||||
GOTEST=$(GOCMD) test
|
||||
GOVET=$(GOCMD) vet
|
||||
BINARY_NAME=local-ai
|
||||
|
||||
GOLLAMA_VERSION?=cf9b522db63898dcc5eb86e37c979ab85cbd583e
|
||||
GOGPT4ALLJ_VERSION?=1f7bff57f66cb7062e40d0ac3abd2217815e5109
|
||||
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
|
||||
@find ./go-rwkv -type f -name "*.c" -exec sed -i'' -e 's/ggml_/ggml_rwkv_/g' {} +
|
||||
@find ./go-rwkv -type f -name "*.cpp" -exec sed -i'' -e 's/ggml_/ggml_rwkv_/g' {} +
|
||||
@find ./go-rwkv -type f -name "*.h" -exec sed -i'' -e 's/ggml_/ggml_rwkv_/g' {} +
|
||||
|
||||
go-rwkv/librwkv.a: go-rwkv
|
||||
cd go-rwkv && cd rwkv.cpp && cmake . -DRWKV_BUILD_SHARED_LIBRARY=OFF && cmake --build . && cp librwkv.a .. && cp ggml/src/libggml.a ..
|
||||
|
||||
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 --recurse-submodules https://github.com/go-skynet/go-llama.cpp go-llama
|
||||
cd go-llama && git checkout -b build $(GOLLAMA_VERSION) && git submodule update --init --recursive --depth 1
|
||||
|
||||
go-llama/libbinding.a: go-llama
|
||||
$(MAKE) -C go-llama $(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) run github.com/onsi/ginkgo/v2/ginkgo -v -r ./...
|
||||
|
||||
## 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)
|
||||
637
README.md
637
README.md
@@ -1,637 +0,0 @@
|
||||
<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>
|
||||
|
||||
[](https://github.com/go-skynet/LocalAI/actions/workflows/test.yml) [](https://github.com/go-skynet/LocalAI/actions/workflows/image.yml)
|
||||
|
||||
[](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).
|
||||
|
||||
See [examples on how to integrate LocalAI](https://github.com/go-skynet/LocalAI/tree/master/examples/).
|
||||
|
||||
## 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 )
|
||||
|
||||
Twitter: [@LocalAI_API](https://twitter.com/LocalAI_API) and [@mudler_it](https://twitter.com/mudler_it)
|
||||
|
||||
### Blogs and articles
|
||||
|
||||
- [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.
|
||||
|
||||
## Contribute and help
|
||||
|
||||
To help the project you can:
|
||||
|
||||
- Upvote the [Reddit post](https://www.reddit.com/r/selfhosted/comments/12w4p2f/localai_openai_compatible_api_to_run_llm_models/) about LocalAI.
|
||||
|
||||
- [Hacker news post](https://news.ycombinator.com/item?id=35726934) - help us out by voting if you like this project.
|
||||
|
||||
- If you have technological skills and want to contribute to development, have a look at the open issues. If you are new you can have a look at the [good-first-issue](https://github.com/go-skynet/LocalAI/issues?q=is%3Aissue+is%3Aopen+label%3A%22good+first+issue%22) and [help-wanted](https://github.com/go-skynet/LocalAI/issues?q=is%3Aissue+is%3Aopen+label%3A%22help+wanted%22) labels.
|
||||
|
||||
- If you don't have technological skills you can still help improving documentation or add examples or share your user-stories with our community, any help and contribution is welcome!
|
||||
|
||||
## Model compatibility
|
||||
|
||||
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) (changes required, see below)
|
||||
- [GPT4ALL-J](https://gpt4all.io/models/ggml-gpt4all-j.bin) (no changes required)
|
||||
- Koala
|
||||
- [cerebras-GPT with ggml](https://huggingface.co/lxe/Cerebras-GPT-2.7B-Alpaca-SP-ggml)
|
||||
- WizardLM
|
||||
- [RWKV](https://github.com/BlinkDL/RWKV-LM) models with [rwkv.cpp](https://github.com/saharNooby/rwkv.cpp)
|
||||
|
||||
### GPT4ALL
|
||||
|
||||
Note: You might need to convert older models to the new format, see [here](https://github.com/ggerganov/llama.cpp#using-gpt4all) for instance to run `gpt4all`.
|
||||
|
||||
### RWKV
|
||||
|
||||
<details>
|
||||
|
||||
A full example on how to run a rwkv model is in the [examples](https://github.com/go-skynet/LocalAI/tree/master/examples/rwkv).
|
||||
|
||||
Note: rwkv models have an associated tokenizer along that needs to be provided with it:
|
||||
|
||||
```
|
||||
36464540 -rw-r--r-- 1 mudler mudler 1.2G May 3 10:51 rwkv_small
|
||||
36464543 -rw-r--r-- 1 mudler mudler 2.4M May 3 10:51 rwkv_small.tokenizer.json
|
||||
```
|
||||
|
||||
</details>
|
||||
|
||||
### Others
|
||||
|
||||
It should also be compatible with StableLM and GPTNeoX ggml models (untested).
|
||||
|
||||
### Hardware requirements
|
||||
|
||||
Depending on the model you are attempting to run might need more RAM or CPU resources. Check out also [here](https://github.com/ggerganov/llama.cpp#memorydisk-requirements) for `ggml` based backends. `rwkv` is less expensive on resources.
|
||||
|
||||
|
||||
## 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
|
||||
|
||||
To see other examples on how to integrate with other projects for instance for question answering or for using it with chatbot-ui, see: [examples](https://github.com/go-skynet/LocalAI/tree/master/examples/).
|
||||
|
||||
|
||||
### Advanced configuration
|
||||
|
||||
LocalAI can be configured to serve user-defined models with a set of default parameters and templates.
|
||||
|
||||
<details>
|
||||
|
||||
You can create multiple `yaml` files in the models path or either specify a single YAML configuration file.
|
||||
Consider the following `models` folder in the `example/chatbot-ui`:
|
||||
|
||||
```
|
||||
base ❯ ls -liah examples/chatbot-ui/models
|
||||
36487587 drwxr-xr-x 2 mudler mudler 4.0K May 3 12:27 .
|
||||
36487586 drwxr-xr-x 3 mudler mudler 4.0K May 3 10:42 ..
|
||||
36465214 -rw-r--r-- 1 mudler mudler 10 Apr 27 07:46 completion.tmpl
|
||||
36464855 -rw-r--r-- 1 mudler mudler 3.6G Apr 27 00:08 ggml-gpt4all-j
|
||||
36464537 -rw-r--r-- 1 mudler mudler 245 May 3 10:42 gpt-3.5-turbo.yaml
|
||||
36467388 -rw-r--r-- 1 mudler mudler 180 Apr 27 07:46 gpt4all.tmpl
|
||||
```
|
||||
|
||||
In the `gpt-3.5-turbo.yaml` file it is defined the `gpt-3.5-turbo` model which is an alias to use `gpt4all-j` with pre-defined options.
|
||||
|
||||
For instance, consider the following that declares `gpt-3.5-turbo` backed by the `ggml-gpt4all-j` model:
|
||||
|
||||
```yaml
|
||||
name: gpt-3.5-turbo
|
||||
# Default model parameters
|
||||
parameters:
|
||||
# Relative to the models path
|
||||
model: ggml-gpt4all-j
|
||||
# temperature
|
||||
temperature: 0.3
|
||||
# all the OpenAI request options here..
|
||||
|
||||
# Default context size
|
||||
context_size: 512
|
||||
threads: 10
|
||||
# Define a backend (optional). By default it will try to guess the backend the first time the model is interacted with.
|
||||
backend: gptj # available: llama, stablelm, gpt2, gptj rwkv
|
||||
# stopwords (if supported by the backend)
|
||||
stopwords:
|
||||
- "HUMAN:"
|
||||
- "### Response:"
|
||||
# define chat roles
|
||||
roles:
|
||||
user: "HUMAN:"
|
||||
system: "GPT:"
|
||||
template:
|
||||
# template file ".tmpl" with the prompt template to use by default on the endpoint call. Note there is no extension in the files
|
||||
completion: completion
|
||||
chat: ggml-gpt4all-j
|
||||
```
|
||||
|
||||
Specifying a `config-file` via CLI allows to declare models in a single file as a list, for instance:
|
||||
|
||||
```yaml
|
||||
- name: list1
|
||||
parameters:
|
||||
model: testmodel
|
||||
context_size: 512
|
||||
threads: 10
|
||||
stopwords:
|
||||
- "HUMAN:"
|
||||
- "### Response:"
|
||||
roles:
|
||||
user: "HUMAN:"
|
||||
system: "GPT:"
|
||||
template:
|
||||
completion: completion
|
||||
chat: ggml-gpt4all-j
|
||||
- name: list2
|
||||
parameters:
|
||||
model: testmodel
|
||||
context_size: 512
|
||||
threads: 10
|
||||
stopwords:
|
||||
- "HUMAN:"
|
||||
- "### Response:"
|
||||
roles:
|
||||
user: "HUMAN:"
|
||||
system: "GPT:"
|
||||
template:
|
||||
completion: completion
|
||||
chat: ggml-gpt4all-j
|
||||
```
|
||||
|
||||
See also [chatbot-ui](https://github.com/go-skynet/LocalAI/tree/master/examples/chatbot-ui) as an example on how to use config files.
|
||||
|
||||
</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>
|
||||
There is the availability of localai-webui and chatbot-ui in the examples section and can be setup as per the instructions. However as LocalAI is an API you can already plug it into existing projects that provides are UI interfaces to OpenAI's APIs. There are several already on github, and should be compatible with LocalAI already (as it mimics the OpenAI API)
|
||||
|
||||
</details>
|
||||
|
||||
### 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
|
||||
|
||||
[](https://star-history.com/#go-skynet/LocalAI&Date)
|
||||
|
||||
## License
|
||||
|
||||
LocalAI is a community-driven project. It was initially created by [Ettore Di Giacinto](https://github.com/mudler/) at the [SpectroCloud OSS Office](https://github.com/spectrocloud).
|
||||
|
||||
MIT
|
||||
|
||||
## Golang bindings used
|
||||
|
||||
- [go-skynet/go-llama.cpp](https://github.com/go-skynet/go-llama.cpp)
|
||||
- [go-skynet/go-gpt4all-j.cpp](https://github.com/go-skynet/go-gpt4all-j.cpp)
|
||||
- [go-skynet/go-gpt2.cpp](https://github.com/go-skynet/go-gpt2.cpp)
|
||||
- [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>
|
||||
91
api/api.go
91
api/api.go
@@ -1,91 +0,0 @@
|
||||
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/logger"
|
||||
"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},
|
||||
},
|
||||
)
|
||||
},
|
||||
})
|
||||
|
||||
if debug {
|
||||
app.Use(logger.New(logger.Config{
|
||||
Format: "[${ip}]:${port} ${status} - ${method} ${path}\n",
|
||||
}))
|
||||
}
|
||||
|
||||
cm := make(ConfigMerger)
|
||||
if err := cm.LoadConfigs(loader.ModelPath); err != nil {
|
||||
log.Error().Msgf("error loading config files: %s", err.Error())
|
||||
}
|
||||
|
||||
if configFile != "" {
|
||||
if err := cm.LoadConfigFile(configFile); err != nil {
|
||||
log.Error().Msgf("error loading config file: %s", err.Error())
|
||||
}
|
||||
}
|
||||
|
||||
if debug {
|
||||
for k, v := range cm {
|
||||
log.Debug().Msgf("Model: %s (config: %+v)", k, v)
|
||||
}
|
||||
}
|
||||
// Default middleware config
|
||||
app.Use(recover.New())
|
||||
app.Use(cors.New())
|
||||
|
||||
// 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.Post("/v1/embeddings", embeddingsEndpoint(cm, debug, loader, threads, ctxSize, f16))
|
||||
app.Post("/embeddings", embeddingsEndpoint(cm, debug, loader, threads, ctxSize, f16))
|
||||
|
||||
// /v1/engines/{engine_id}/embeddings
|
||||
|
||||
app.Post("/v1/engines/:model/embeddings", embeddingsEndpoint(cm, debug, loader, threads, ctxSize, f16))
|
||||
|
||||
app.Get("/v1/models", listModels(loader, cm))
|
||||
app.Get("/models", listModels(loader, cm))
|
||||
|
||||
return app
|
||||
}
|
||||
138
api/api_test.go
138
api/api_test.go
@@ -1,138 +0,0 @@
|
||||
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())
|
||||
})
|
||||
})
|
||||
})
|
||||
@@ -1,13 +0,0 @@
|
||||
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")
|
||||
}
|
||||
281
api/config.go
281
api/config.go
@@ -1,281 +0,0 @@
|
||||
package api
|
||||
|
||||
import (
|
||||
"encoding/json"
|
||||
"fmt"
|
||||
"io/ioutil"
|
||||
"os"
|
||||
"path/filepath"
|
||||
"strings"
|
||||
|
||||
model "github.com/go-skynet/LocalAI/pkg/model"
|
||||
"github.com/gofiber/fiber/v2"
|
||||
"github.com/rs/zerolog/log"
|
||||
"gopkg.in/yaml.v3"
|
||||
)
|
||||
|
||||
type Config struct {
|
||||
OpenAIRequest `yaml:"parameters"`
|
||||
Name string `yaml:"name"`
|
||||
StopWords []string `yaml:"stopwords"`
|
||||
Cutstrings []string `yaml:"cutstrings"`
|
||||
TrimSpace []string `yaml:"trimspace"`
|
||||
ContextSize int `yaml:"context_size"`
|
||||
F16 bool `yaml:"f16"`
|
||||
Threads int `yaml:"threads"`
|
||||
Debug bool `yaml:"debug"`
|
||||
Roles map[string]string `yaml:"roles"`
|
||||
Embeddings bool `yaml:"embeddings"`
|
||||
Backend string `yaml:"backend"`
|
||||
TemplateConfig TemplateConfig `yaml:"template"`
|
||||
MirostatETA float64 `yaml:"mirostat_eta"`
|
||||
MirostatTAU float64 `yaml:"mirostat_tau"`
|
||||
Mirostat int `yaml:"mirostat"`
|
||||
|
||||
PromptStrings, InputStrings []string
|
||||
}
|
||||
|
||||
type TemplateConfig struct {
|
||||
Completion string `yaml:"completion"`
|
||||
Chat string `yaml:"chat"`
|
||||
Edit string `yaml:"edit"`
|
||||
}
|
||||
|
||||
type ConfigMerger map[string]Config
|
||||
|
||||
func ReadConfigFile(file string) ([]*Config, error) {
|
||||
c := &[]*Config{}
|
||||
f, err := os.ReadFile(file)
|
||||
if err != nil {
|
||||
return nil, fmt.Errorf("cannot read config file: %w", err)
|
||||
}
|
||||
if err := yaml.Unmarshal(f, c); err != nil {
|
||||
return nil, fmt.Errorf("cannot unmarshal config file: %w", err)
|
||||
}
|
||||
|
||||
return *c, nil
|
||||
}
|
||||
|
||||
func ReadConfig(file string) (*Config, error) {
|
||||
c := &Config{}
|
||||
f, err := os.ReadFile(file)
|
||||
if err != nil {
|
||||
return nil, fmt.Errorf("cannot read config file: %w", err)
|
||||
}
|
||||
if err := yaml.Unmarshal(f, c); err != nil {
|
||||
return nil, fmt.Errorf("cannot unmarshal config file: %w", err)
|
||||
}
|
||||
|
||||
return c, nil
|
||||
}
|
||||
|
||||
func (cm ConfigMerger) LoadConfigFile(file string) error {
|
||||
c, err := ReadConfigFile(file)
|
||||
if err != nil {
|
||||
return fmt.Errorf("cannot load config file: %w", err)
|
||||
}
|
||||
|
||||
for _, cc := range c {
|
||||
cm[cc.Name] = *cc
|
||||
}
|
||||
return nil
|
||||
}
|
||||
|
||||
func (cm ConfigMerger) LoadConfig(file string) error {
|
||||
c, err := ReadConfig(file)
|
||||
if err != nil {
|
||||
return fmt.Errorf("cannot read config file: %w", err)
|
||||
}
|
||||
|
||||
cm[c.Name] = *c
|
||||
return nil
|
||||
}
|
||||
|
||||
func (cm ConfigMerger) LoadConfigs(path string) error {
|
||||
files, err := ioutil.ReadDir(path)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
|
||||
for _, file := range files {
|
||||
// Skip templates, YAML and .keep files
|
||||
if !strings.Contains(file.Name(), ".yaml") {
|
||||
continue
|
||||
}
|
||||
c, err := ReadConfig(filepath.Join(path, file.Name()))
|
||||
if err == nil {
|
||||
cm[c.Name] = *c
|
||||
}
|
||||
}
|
||||
|
||||
return nil
|
||||
}
|
||||
|
||||
func updateConfig(config *Config, input *OpenAIRequest) {
|
||||
if input.Echo {
|
||||
config.Echo = input.Echo
|
||||
}
|
||||
if input.TopK != 0 {
|
||||
config.TopK = input.TopK
|
||||
}
|
||||
if input.TopP != 0 {
|
||||
config.TopP = input.TopP
|
||||
}
|
||||
|
||||
if input.Temperature != 0 {
|
||||
config.Temperature = input.Temperature
|
||||
}
|
||||
|
||||
if input.Maxtokens != 0 {
|
||||
config.Maxtokens = input.Maxtokens
|
||||
}
|
||||
|
||||
switch stop := input.Stop.(type) {
|
||||
case string:
|
||||
if stop != "" {
|
||||
config.StopWords = append(config.StopWords, stop)
|
||||
}
|
||||
case []interface{}:
|
||||
for _, pp := range stop {
|
||||
if s, ok := pp.(string); ok {
|
||||
config.StopWords = append(config.StopWords, s)
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
if input.RepeatPenalty != 0 {
|
||||
config.RepeatPenalty = input.RepeatPenalty
|
||||
}
|
||||
|
||||
if input.Keep != 0 {
|
||||
config.Keep = input.Keep
|
||||
}
|
||||
|
||||
if input.Batch != 0 {
|
||||
config.Batch = input.Batch
|
||||
}
|
||||
|
||||
if input.F16 {
|
||||
config.F16 = input.F16
|
||||
}
|
||||
|
||||
if input.IgnoreEOS {
|
||||
config.IgnoreEOS = input.IgnoreEOS
|
||||
}
|
||||
|
||||
if input.Seed != 0 {
|
||||
config.Seed = input.Seed
|
||||
}
|
||||
|
||||
if input.Mirostat != 0 {
|
||||
config.Mirostat = input.Mirostat
|
||||
}
|
||||
|
||||
if input.MirostatETA != 0 {
|
||||
config.MirostatETA = input.MirostatETA
|
||||
}
|
||||
|
||||
if input.MirostatTAU != 0 {
|
||||
config.MirostatTAU = input.MirostatTAU
|
||||
}
|
||||
|
||||
switch inputs := input.Input.(type) {
|
||||
case string:
|
||||
if inputs != "" {
|
||||
config.InputStrings = append(config.InputStrings, inputs)
|
||||
}
|
||||
case []interface{}:
|
||||
for _, pp := range inputs {
|
||||
if s, ok := pp.(string); ok {
|
||||
config.InputStrings = append(config.InputStrings, s)
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
switch p := input.Prompt.(type) {
|
||||
case string:
|
||||
config.PromptStrings = append(config.PromptStrings, p)
|
||||
case []interface{}:
|
||||
for _, pp := range p {
|
||||
if s, ok := pp.(string); ok {
|
||||
config.PromptStrings = append(config.PromptStrings, s)
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
func readConfig(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
|
||||
|
||||
if c.Params("model") != "" {
|
||||
modelFile = c.Params("model")
|
||||
}
|
||||
|
||||
received, _ := json.Marshal(input)
|
||||
|
||||
log.Debug().Msgf("Request received: %s", string(received))
|
||||
|
||||
// Set model from bearer token, if available
|
||||
bearer := strings.TrimLeft(c.Get("authorization"), "Bearer ")
|
||||
bearerExists := bearer != "" && loader.ExistsInModelPath(bearer)
|
||||
|
||||
// If no model was specified, take the first available
|
||||
if modelFile == "" && !bearerExists {
|
||||
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),
|
||||
ContextSize: ctx,
|
||||
Threads: threads,
|
||||
F16: f16,
|
||||
Debug: debug,
|
||||
}
|
||||
} else {
|
||||
config = &cfg
|
||||
}
|
||||
|
||||
// Set the parameters for the language model prediction
|
||||
updateConfig(config, input)
|
||||
|
||||
// Don't allow 0 as setting
|
||||
if config.Threads == 0 {
|
||||
if threads != 0 {
|
||||
config.Threads = threads
|
||||
} else {
|
||||
config.Threads = 4
|
||||
}
|
||||
}
|
||||
|
||||
return config, input, nil
|
||||
}
|
||||
403
api/openai.go
403
api/openai.go
@@ -1,403 +0,0 @@
|
||||
package api
|
||||
|
||||
import (
|
||||
"bufio"
|
||||
"bytes"
|
||||
"encoding/json"
|
||||
"fmt"
|
||||
"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 Item struct {
|
||||
Embedding []float32 `json:"embedding"`
|
||||
Index int `json:"index"`
|
||||
Object string `json:"object,omitempty"`
|
||||
}
|
||||
|
||||
type OpenAIResponse struct {
|
||||
Created int `json:"created,omitempty"`
|
||||
Object string `json:"object,omitempty"`
|
||||
ID string `json:"id,omitempty"`
|
||||
Model string `json:"model,omitempty"`
|
||||
Choices []Choice `json:"choices,omitempty"`
|
||||
Data []Item `json:"data,omitempty"`
|
||||
|
||||
Usage OpenAIUsage `json:"usage"`
|
||||
}
|
||||
|
||||
type Choice struct {
|
||||
Index int `json:"index,omitempty"`
|
||||
FinishReason string `json:"finish_reason,omitempty"`
|
||||
Message *Message `json:"message,omitempty"`
|
||||
Delta *Message `json:"delta,omitempty"`
|
||||
Text string `json:"text,omitempty"`
|
||||
}
|
||||
|
||||
type Message struct {
|
||||
Role string `json:"role,omitempty" yaml:"role"`
|
||||
Content string `json:"content,omitempty" yaml:"content"`
|
||||
}
|
||||
|
||||
type OpenAIModel struct {
|
||||
ID string `json:"id"`
|
||||
Object string `json:"object"`
|
||||
}
|
||||
|
||||
type OpenAIRequest struct {
|
||||
Model string `json:"model" yaml:"model"`
|
||||
|
||||
// Prompt is read only by completion API calls
|
||||
Prompt interface{} `json:"prompt" yaml:"prompt"`
|
||||
|
||||
// Edit endpoint
|
||||
Instruction string `json:"instruction" yaml:"instruction"`
|
||||
Input interface{} `json:"input" yaml:"input"`
|
||||
|
||||
Stop interface{} `json:"stop" yaml:"stop"`
|
||||
|
||||
// Messages is read only by chat/completion API calls
|
||||
Messages []Message `json:"messages" yaml:"messages"`
|
||||
|
||||
Stream bool `json:"stream"`
|
||||
Echo bool `json:"echo"`
|
||||
// Common options between all the API calls
|
||||
TopP float64 `json:"top_p" yaml:"top_p"`
|
||||
TopK int `json:"top_k" yaml:"top_k"`
|
||||
Temperature float64 `json:"temperature" yaml:"temperature"`
|
||||
Maxtokens int `json:"max_tokens" yaml:"max_tokens"`
|
||||
|
||||
N int `json:"n"`
|
||||
|
||||
// Custom parameters - not present in the OpenAI API
|
||||
Batch int `json:"batch" yaml:"batch"`
|
||||
F16 bool `json:"f16" yaml:"f16"`
|
||||
IgnoreEOS bool `json:"ignore_eos" yaml:"ignore_eos"`
|
||||
RepeatPenalty float64 `json:"repeat_penalty" yaml:"repeat_penalty"`
|
||||
Keep int `json:"n_keep" yaml:"n_keep"`
|
||||
|
||||
MirostatETA float64 `json:"mirostat_eta" yaml:"mirostat_eta"`
|
||||
MirostatTAU float64 `json:"mirostat_tau" yaml:"mirostat_tau"`
|
||||
Mirostat int `json:"mirostat" yaml:"mirostat"`
|
||||
|
||||
Seed int `json:"seed" yaml:"seed"`
|
||||
}
|
||||
|
||||
func defaultRequest(modelFile string) OpenAIRequest {
|
||||
return OpenAIRequest{
|
||||
TopP: 0.7,
|
||||
TopK: 80,
|
||||
Maxtokens: 512,
|
||||
Temperature: 0.9,
|
||||
Model: modelFile,
|
||||
}
|
||||
}
|
||||
|
||||
// https://platform.openai.com/docs/api-reference/completions
|
||||
func completionEndpoint(cm ConfigMerger, debug bool, loader *model.ModelLoader, threads, ctx int, f16 bool) func(c *fiber.Ctx) error {
|
||||
return func(c *fiber.Ctx) error {
|
||||
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)
|
||||
|
||||
templateFile := config.Model
|
||||
|
||||
if config.TemplateConfig.Completion != "" {
|
||||
templateFile = config.TemplateConfig.Completion
|
||||
}
|
||||
|
||||
var result []Choice
|
||||
for _, i := range config.PromptStrings {
|
||||
// A model can have a "file.bin.tmpl" file associated with a prompt template prefix
|
||||
templatedInput, err := loader.TemplatePrefix(templateFile, struct {
|
||||
Input string
|
||||
}{Input: i})
|
||||
if err == nil {
|
||||
i = templatedInput
|
||||
log.Debug().Msgf("Template found, input modified to: %s", i)
|
||||
}
|
||||
|
||||
r, err := ComputeChoices(i, input, config, loader, func(s string, c *[]Choice) {
|
||||
*c = append(*c, Choice{Text: s})
|
||||
}, nil)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
|
||||
result = append(result, r...)
|
||||
}
|
||||
|
||||
resp := &OpenAIResponse{
|
||||
Model: input.Model, // we have to return what the user sent here, due to OpenAI spec.
|
||||
Choices: result,
|
||||
Object: "text_completion",
|
||||
}
|
||||
|
||||
jsonResult, _ := json.Marshal(resp)
|
||||
log.Debug().Msgf("Response: %s", jsonResult)
|
||||
|
||||
// Return the prediction in the response body
|
||||
return c.JSON(resp)
|
||||
}
|
||||
}
|
||||
|
||||
// https://platform.openai.com/docs/api-reference/embeddings
|
||||
func embeddingsEndpoint(cm ConfigMerger, debug bool, loader *model.ModelLoader, threads, ctx int, f16 bool) func(c *fiber.Ctx) error {
|
||||
return func(c *fiber.Ctx) error {
|
||||
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)
|
||||
items := []Item{}
|
||||
|
||||
for i, s := range config.InputStrings {
|
||||
|
||||
// get the model function to call for the result
|
||||
embedFn, err := ModelEmbedding(s, loader, *config)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
|
||||
embeddings, err := embedFn()
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
items = append(items, Item{Embedding: embeddings, Index: i, Object: "embedding"})
|
||||
}
|
||||
|
||||
resp := &OpenAIResponse{
|
||||
Model: input.Model, // we have to return what the user sent here, due to OpenAI spec.
|
||||
Data: items,
|
||||
Object: "list",
|
||||
}
|
||||
|
||||
jsonResult, _ := json.Marshal(resp)
|
||||
log.Debug().Msgf("Response: %s", jsonResult)
|
||||
|
||||
// Return the prediction in the response body
|
||||
return c.JSON(resp)
|
||||
}
|
||||
}
|
||||
|
||||
func chatEndpoint(cm ConfigMerger, debug bool, loader *model.ModelLoader, threads, ctx int, f16 bool) func(c *fiber.Ctx) error {
|
||||
|
||||
process := func(s string, req *OpenAIRequest, config *Config, loader *model.ModelLoader, responses chan OpenAIResponse) {
|
||||
ComputeChoices(s, req, config, loader, func(s string, c *[]Choice) {}, func(s string) bool {
|
||||
resp := OpenAIResponse{
|
||||
Model: req.Model, // we have to return what the user sent here, due to OpenAI spec.
|
||||
Choices: []Choice{{Delta: &Message{Role: "assistant", Content: s}}},
|
||||
Object: "chat.completion.chunk",
|
||||
}
|
||||
log.Debug().Msgf("Sending goroutine: %s", s)
|
||||
|
||||
responses <- resp
|
||||
return true
|
||||
})
|
||||
close(responses)
|
||||
}
|
||||
return func(c *fiber.Ctx) error {
|
||||
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 process(predInput, input, config, loader, responses)
|
||||
|
||||
c.Context().SetBodyStreamWriter(fasthttp.StreamWriter(func(w *bufio.Writer) {
|
||||
|
||||
for ev := range responses {
|
||||
var buf bytes.Buffer
|
||||
enc := json.NewEncoder(&buf)
|
||||
enc.Encode(ev)
|
||||
|
||||
fmt.Fprintf(w, "event: data\n\n")
|
||||
fmt.Fprintf(w, "data: %v\n\n", buf.String())
|
||||
log.Debug().Msgf("Sending chunk: %s", buf.String())
|
||||
w.Flush()
|
||||
}
|
||||
|
||||
w.WriteString("event: data\n\n")
|
||||
resp := &OpenAIResponse{
|
||||
Model: input.Model, // we have to return what the user sent here, due to OpenAI spec.
|
||||
Choices: []Choice{{FinishReason: "stop"}},
|
||||
}
|
||||
respData, _ := json.Marshal(resp)
|
||||
|
||||
w.WriteString(fmt.Sprintf("data: %s\n\n", respData))
|
||||
w.Flush()
|
||||
}))
|
||||
return nil
|
||||
}
|
||||
|
||||
result, err := ComputeChoices(predInput, input, config, loader, func(s string, c *[]Choice) {
|
||||
*c = append(*c, Choice{Message: &Message{Role: "assistant", Content: s}})
|
||||
}, nil)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
|
||||
resp := &OpenAIResponse{
|
||||
Model: input.Model, // we have to return what the user sent here, due to OpenAI spec.
|
||||
Choices: result,
|
||||
Object: "chat.completion",
|
||||
}
|
||||
respData, _ := json.Marshal(resp)
|
||||
log.Debug().Msgf("Response: %s", respData)
|
||||
|
||||
// Return the prediction in the response body
|
||||
return c.JSON(resp)
|
||||
}
|
||||
}
|
||||
|
||||
func editEndpoint(cm ConfigMerger, debug bool, loader *model.ModelLoader, threads, ctx int, f16 bool) func(c *fiber.Ctx) error {
|
||||
return func(c *fiber.Ctx) error {
|
||||
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)
|
||||
|
||||
templateFile := config.Model
|
||||
|
||||
if config.TemplateConfig.Edit != "" {
|
||||
templateFile = config.TemplateConfig.Edit
|
||||
}
|
||||
|
||||
var result []Choice
|
||||
for _, i := range config.InputStrings {
|
||||
// A model can have a "file.bin.tmpl" file associated with a prompt template prefix
|
||||
templatedInput, err := loader.TemplatePrefix(templateFile, struct {
|
||||
Input string
|
||||
Instruction string
|
||||
}{Input: i})
|
||||
if err == nil {
|
||||
i = templatedInput
|
||||
log.Debug().Msgf("Template found, input modified to: %s", i)
|
||||
}
|
||||
|
||||
r, err := ComputeChoices(i, input, config, loader, func(s string, c *[]Choice) {
|
||||
*c = append(*c, Choice{Text: s})
|
||||
}, nil)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
|
||||
result = append(result, r...)
|
||||
}
|
||||
|
||||
resp := &OpenAIResponse{
|
||||
Model: input.Model, // we have to return what the user sent here, due to OpenAI spec.
|
||||
Choices: result,
|
||||
Object: "edit",
|
||||
}
|
||||
|
||||
jsonResult, _ := json.Marshal(resp)
|
||||
log.Debug().Msgf("Response: %s", jsonResult)
|
||||
|
||||
// Return the prediction in the response body
|
||||
return c.JSON(resp)
|
||||
}
|
||||
}
|
||||
|
||||
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,
|
||||
})
|
||||
}
|
||||
}
|
||||
@@ -1,358 +0,0 @@
|
||||
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"
|
||||
)
|
||||
|
||||
// mutex still needed, see: https://github.com/ggerganov/llama.cpp/discussions/784
|
||||
var mutexMap sync.Mutex
|
||||
var mutexes map[string]*sync.Mutex = make(map[string]*sync.Mutex)
|
||||
|
||||
func defaultLLamaOpts(c Config) []llama.ModelOption {
|
||||
llamaOpts := []llama.ModelOption{}
|
||||
if c.ContextSize != 0 {
|
||||
llamaOpts = append(llamaOpts, llama.SetContext(c.ContextSize))
|
||||
}
|
||||
if c.F16 {
|
||||
llamaOpts = append(llamaOpts, llama.EnableF16Memory)
|
||||
}
|
||||
if c.Embeddings {
|
||||
llamaOpts = append(llamaOpts, llama.EnableEmbeddings)
|
||||
}
|
||||
|
||||
return llamaOpts
|
||||
}
|
||||
|
||||
func ModelEmbedding(s string, loader *model.ModelLoader, c Config) (func() ([]float32, error), error) {
|
||||
if !c.Embeddings {
|
||||
return nil, fmt.Errorf("endpoint disabled for this model by API configuration")
|
||||
}
|
||||
|
||||
modelFile := c.Model
|
||||
|
||||
llamaOpts := defaultLLamaOpts(c)
|
||||
|
||||
var inferenceModel interface{}
|
||||
var err error
|
||||
if c.Backend == "" {
|
||||
inferenceModel, err = loader.GreedyLoader(modelFile, llamaOpts, uint32(c.Threads))
|
||||
} else {
|
||||
inferenceModel, err = loader.BackendLoader(c.Backend, modelFile, llamaOpts, uint32(c.Threads))
|
||||
}
|
||||
if err != nil {
|
||||
return nil, err
|
||||
}
|
||||
|
||||
var fn func() ([]float32, error)
|
||||
switch model := inferenceModel.(type) {
|
||||
case *llama.LLama:
|
||||
fn = func() ([]float32, error) {
|
||||
predictOptions := buildLLamaPredictOptions(c)
|
||||
return model.Embeddings(s, predictOptions...)
|
||||
}
|
||||
default:
|
||||
fn = func() ([]float32, error) {
|
||||
return nil, fmt.Errorf("embeddings not supported by the backend")
|
||||
}
|
||||
}
|
||||
|
||||
return func() ([]float32, error) {
|
||||
// This is still needed, see: https://github.com/ggerganov/llama.cpp/discussions/784
|
||||
mutexMap.Lock()
|
||||
l, ok := mutexes[modelFile]
|
||||
if !ok {
|
||||
m := &sync.Mutex{}
|
||||
mutexes[modelFile] = m
|
||||
l = m
|
||||
}
|
||||
mutexMap.Unlock()
|
||||
l.Lock()
|
||||
defer l.Unlock()
|
||||
|
||||
embeds, err := fn()
|
||||
if err != nil {
|
||||
return embeds, err
|
||||
}
|
||||
// Remove trailing 0s
|
||||
for i := len(embeds) - 1; i >= 0; i-- {
|
||||
if embeds[i] == 0.0 {
|
||||
embeds = embeds[:i]
|
||||
} else {
|
||||
break
|
||||
}
|
||||
}
|
||||
return embeds, nil
|
||||
}, nil
|
||||
}
|
||||
|
||||
func buildLLamaPredictOptions(c Config) []llama.PredictOption {
|
||||
// Generate the prediction using the language model
|
||||
predictOptions := []llama.PredictOption{
|
||||
llama.SetTemperature(c.Temperature),
|
||||
llama.SetTopP(c.TopP),
|
||||
llama.SetTopK(c.TopK),
|
||||
llama.SetTokens(c.Maxtokens),
|
||||
llama.SetThreads(c.Threads),
|
||||
}
|
||||
|
||||
if c.Mirostat != 0 {
|
||||
predictOptions = append(predictOptions, llama.SetMirostat(c.Mirostat))
|
||||
}
|
||||
|
||||
if c.MirostatETA != 0 {
|
||||
predictOptions = append(predictOptions, llama.SetMirostatETA(c.MirostatETA))
|
||||
}
|
||||
|
||||
if c.MirostatTAU != 0 {
|
||||
predictOptions = append(predictOptions, llama.SetMirostatTAU(c.MirostatTAU))
|
||||
}
|
||||
|
||||
if c.Debug {
|
||||
predictOptions = append(predictOptions, llama.Debug)
|
||||
}
|
||||
|
||||
predictOptions = append(predictOptions, llama.SetStopWords(c.StopWords...))
|
||||
|
||||
if c.RepeatPenalty != 0 {
|
||||
predictOptions = append(predictOptions, llama.SetPenalty(c.RepeatPenalty))
|
||||
}
|
||||
|
||||
if c.Keep != 0 {
|
||||
predictOptions = append(predictOptions, llama.SetNKeep(c.Keep))
|
||||
}
|
||||
|
||||
if c.Batch != 0 {
|
||||
predictOptions = append(predictOptions, llama.SetBatch(c.Batch))
|
||||
}
|
||||
|
||||
if c.F16 {
|
||||
predictOptions = append(predictOptions, llama.EnableF16KV)
|
||||
}
|
||||
|
||||
if c.IgnoreEOS {
|
||||
predictOptions = append(predictOptions, llama.IgnoreEOS)
|
||||
}
|
||||
|
||||
if c.Seed != 0 {
|
||||
predictOptions = append(predictOptions, llama.SetSeed(c.Seed))
|
||||
}
|
||||
|
||||
return predictOptions
|
||||
}
|
||||
|
||||
func ModelInference(s string, loader *model.ModelLoader, c Config, tokenCallback func(string) bool) (func() (string, error), error) {
|
||||
supportStreams := false
|
||||
modelFile := c.Model
|
||||
|
||||
llamaOpts := defaultLLamaOpts(c)
|
||||
|
||||
var inferenceModel interface{}
|
||||
var err error
|
||||
if c.Backend == "" {
|
||||
inferenceModel, err = loader.GreedyLoader(modelFile, llamaOpts, uint32(c.Threads))
|
||||
} else {
|
||||
inferenceModel, err = loader.BackendLoader(c.Backend, modelFile, llamaOpts, uint32(c.Threads))
|
||||
}
|
||||
if err != nil {
|
||||
return nil, err
|
||||
}
|
||||
|
||||
var fn func() (string, error)
|
||||
|
||||
switch model := inferenceModel.(type) {
|
||||
case *rwkv.RwkvState:
|
||||
supportStreams = true
|
||||
|
||||
fn = func() (string, error) {
|
||||
stopWord := "\n"
|
||||
if len(c.StopWords) > 0 {
|
||||
stopWord = c.StopWords[0]
|
||||
}
|
||||
|
||||
if err := model.ProcessInput(s); err != nil {
|
||||
return "", err
|
||||
}
|
||||
|
||||
response := model.GenerateResponse(c.Maxtokens, stopWord, float32(c.Temperature), float32(c.TopP), tokenCallback)
|
||||
|
||||
return response, nil
|
||||
}
|
||||
case *gpt2.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)
|
||||
}
|
||||
|
||||
predictOptions := buildLLamaPredictOptions(c)
|
||||
|
||||
str, er := model.Predict(
|
||||
s,
|
||||
predictOptions...,
|
||||
)
|
||||
// Seems that if we don't free the callback explicitly we leave functions registered (that might try to send on closed channels)
|
||||
// For instance otherwise the API returns: {"error":{"code":500,"message":"send on closed channel","type":""}}
|
||||
// after a stream event has occurred
|
||||
model.SetTokenCallback(nil)
|
||||
return str, er
|
||||
}
|
||||
}
|
||||
|
||||
return func() (string, error) {
|
||||
// This is still needed, see: https://github.com/ggerganov/llama.cpp/discussions/784
|
||||
mutexMap.Lock()
|
||||
l, ok := mutexes[modelFile]
|
||||
if !ok {
|
||||
m := &sync.Mutex{}
|
||||
mutexes[modelFile] = m
|
||||
l = m
|
||||
}
|
||||
mutexMap.Unlock()
|
||||
l.Lock()
|
||||
defer l.Unlock()
|
||||
|
||||
res, err := fn()
|
||||
if tokenCallback != nil && !supportStreams {
|
||||
tokenCallback(res)
|
||||
}
|
||||
return res, err
|
||||
}, nil
|
||||
}
|
||||
|
||||
func ComputeChoices(predInput string, input *OpenAIRequest, config *Config, loader *model.ModelLoader, cb func(string, *[]Choice), tokenCallback func(string) bool) ([]Choice, error) {
|
||||
result := []Choice{}
|
||||
|
||||
n := input.N
|
||||
|
||||
if input.N == 0 {
|
||||
n = 1
|
||||
}
|
||||
|
||||
// get the model function to call for the result
|
||||
predFunc, err := ModelInference(predInput, loader, *config, tokenCallback)
|
||||
if err != nil {
|
||||
return result, err
|
||||
}
|
||||
|
||||
for i := 0; i < n; i++ {
|
||||
prediction, err := predFunc()
|
||||
if err != nil {
|
||||
return result, err
|
||||
}
|
||||
|
||||
prediction = Finetune(*config, predInput, prediction)
|
||||
cb(prediction, &result)
|
||||
|
||||
//result = append(result, Choice{Text: prediction})
|
||||
|
||||
}
|
||||
return result, err
|
||||
}
|
||||
|
||||
var cutstrings map[string]*regexp.Regexp = make(map[string]*regexp.Regexp)
|
||||
var mu sync.Mutex = sync.Mutex{}
|
||||
|
||||
func Finetune(config Config, input, prediction string) string {
|
||||
if config.Echo {
|
||||
prediction = input + prediction
|
||||
}
|
||||
|
||||
for _, c := range config.Cutstrings {
|
||||
mu.Lock()
|
||||
reg, ok := cutstrings[c]
|
||||
if !ok {
|
||||
cutstrings[c] = regexp.MustCompile(c)
|
||||
reg = cutstrings[c]
|
||||
}
|
||||
mu.Unlock()
|
||||
prediction = reg.ReplaceAllString(prediction, "")
|
||||
}
|
||||
|
||||
for _, c := range config.TrimSpace {
|
||||
prediction = strings.TrimSpace(strings.TrimPrefix(prediction, c))
|
||||
}
|
||||
return prediction
|
||||
|
||||
}
|
||||
@@ -1,15 +0,0 @@
|
||||
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" ]
|
||||
@@ -1,7 +0,0 @@
|
||||
#!/bin/bash
|
||||
|
||||
cd /build
|
||||
|
||||
make build
|
||||
|
||||
./local-ai "$@"
|
||||
@@ -1,78 +0,0 @@
|
||||
# Examples
|
||||
|
||||
Here is a list of projects that can easily be integrated with the LocalAI backend.
|
||||
|
||||
### Projects
|
||||
|
||||
|
||||
### Chatbot-UI
|
||||
|
||||
_by [@mkellerman](https://github.com/mkellerman)_
|
||||
|
||||
|
||||
|
||||
This integration shows how to use LocalAI with [mckaywrigley/chatbot-ui](https://github.com/mckaywrigley/chatbot-ui).
|
||||
|
||||
[Check it out here](https://github.com/go-skynet/LocalAI/tree/master/examples/chatbot-ui/)
|
||||
|
||||
### Discord bot
|
||||
|
||||
_by [@mudler](https://github.com/mudler)_
|
||||
|
||||
Run a discord bot which lets you talk directly with a model
|
||||
|
||||
[Check it out here](https://github.com/go-skynet/LocalAI/tree/master/examples/discord-bot/), or for a live demo you can talk with our bot in #random-bot in our discord server.
|
||||
|
||||
### Langchain
|
||||
|
||||
_by [@dave-gray101](https://github.com/dave-gray101)_
|
||||
|
||||
A ready to use example to show e2e how to integrate LocalAI with langchain
|
||||
|
||||
[Check it out here](https://github.com/go-skynet/LocalAI/tree/master/examples/langchain/)
|
||||
|
||||
### Langchain Python
|
||||
|
||||
_by [@mudler](https://github.com/mudler)_
|
||||
|
||||
A ready to use example to show e2e how to integrate LocalAI with langchain
|
||||
|
||||
[Check it out here](https://github.com/go-skynet/LocalAI/tree/master/examples/langchain-python/)
|
||||
|
||||
### LocalAI WebUI
|
||||
|
||||
_by [@dhruvgera](https://github.com/dhruvgera)_
|
||||
|
||||
|
||||
|
||||
A light, community-maintained web interface for LocalAI
|
||||
|
||||
[Check it out here](https://github.com/go-skynet/LocalAI/tree/master/examples/localai-webui/)
|
||||
|
||||
### How to run rwkv models
|
||||
|
||||
_by [@mudler](https://github.com/mudler)_
|
||||
|
||||
A full example on how to run RWKV models with LocalAI
|
||||
|
||||
[Check it out here](https://github.com/go-skynet/LocalAI/tree/master/examples/rwkv/)
|
||||
|
||||
### Slack bot
|
||||
|
||||
_by [@mudler](https://github.com/mudler)_
|
||||
|
||||
Run a slack bot which lets you talk directly with a model
|
||||
|
||||
[Check it out here](https://github.com/go-skynet/LocalAI/tree/master/examples/slack-bot/)
|
||||
|
||||
### Question answering on documents
|
||||
|
||||
_by [@mudler](https://github.com/mudler)_
|
||||
|
||||
Shows how to integrate with [Llama-Index](https://gpt-index.readthedocs.io/en/stable/getting_started/installation.html) to enable question answering on a set of documents.
|
||||
|
||||
[Check it out here](https://github.com/go-skynet/LocalAI/tree/master/examples/query_data/)
|
||||
|
||||
## Want to contribute?
|
||||
|
||||
Create an issue, and put `Example: <description>` in the title! We will post your examples here.
|
||||
@@ -1,46 +0,0 @@
|
||||
# chatbot-ui
|
||||
|
||||
Example of integration with [mckaywrigley/chatbot-ui](https://github.com/mckaywrigley/chatbot-ui).
|
||||
|
||||
|
||||
|
||||
## 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.
|
||||
|
||||
@@ -1,24 +0,0 @@
|
||||
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'
|
||||
@@ -1 +0,0 @@
|
||||
{{.Input}}
|
||||
@@ -1,17 +0,0 @@
|
||||
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
|
||||
@@ -1,4 +0,0 @@
|
||||
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:
|
||||
@@ -1,6 +0,0 @@
|
||||
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
|
||||
@@ -1,76 +0,0 @@
|
||||
# discord-bot
|
||||
|
||||
|
||||
|
||||
## 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
|
||||
```
|
||||
@@ -1,21 +0,0 @@
|
||||
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 +0,0 @@
|
||||
../chatbot-ui/models/
|
||||
@@ -1,47 +0,0 @@
|
||||
## Loosely based from https://gist.github.com/wiseman/4a706428eaabf4af1002a07a114f61d6
|
||||
|
||||
from io import StringIO
|
||||
import sys
|
||||
import os
|
||||
from typing import Dict, Optional
|
||||
|
||||
from langchain.agents import load_tools
|
||||
from langchain.agents import initialize_agent
|
||||
from langchain.agents.tools import Tool
|
||||
from langchain.llms import OpenAI
|
||||
|
||||
base_path = os.environ.get('OPENAI_API_BASE', 'http://api:8080/v1')
|
||||
model_name = os.environ.get('MODEL_NAME', 'gpt-3.5-turbo')
|
||||
|
||||
class PythonREPL:
|
||||
"""Simulates a standalone Python REPL."""
|
||||
|
||||
def __init__(self):
|
||||
pass
|
||||
|
||||
def run(self, command: str) -> str:
|
||||
"""Run command and returns anything printed."""
|
||||
# sys.stderr.write("EXECUTING PYTHON CODE:\n---\n" + command + "\n---\n")
|
||||
old_stdout = sys.stdout
|
||||
sys.stdout = mystdout = StringIO()
|
||||
try:
|
||||
exec(command, globals())
|
||||
sys.stdout = old_stdout
|
||||
output = mystdout.getvalue()
|
||||
except Exception as e:
|
||||
sys.stdout = old_stdout
|
||||
output = str(e)
|
||||
# sys.stderr.write("PYTHON OUTPUT: \"" + output + "\"\n")
|
||||
return output
|
||||
|
||||
llm = OpenAI(temperature=0.0, openai_api_base=base_path, model_name=model_name)
|
||||
python_repl = Tool(
|
||||
"Python REPL",
|
||||
PythonREPL().run,
|
||||
"""A Python shell. Use this to execute python commands. Input should be a valid python command.
|
||||
If you expect output it should be printed out.""",
|
||||
)
|
||||
tools = [python_repl]
|
||||
agent = initialize_agent(tools, llm, agent="zero-shot-react-description", verbose=True)
|
||||
agent.run("What is the 10th fibonacci number?")
|
||||
|
||||
@@ -1,33 +0,0 @@
|
||||
## 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".
|
||||
```
|
||||
@@ -1,16 +0,0 @@
|
||||
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" ]
|
||||
@@ -1 +0,0 @@
|
||||
../chatbot-ui/models
|
||||
@@ -1,6 +0,0 @@
|
||||
|
||||
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
2
examples/langchain/.gitignore
vendored
@@ -1,2 +0,0 @@
|
||||
models/ggml-koala-13B-4bit-128g
|
||||
models/ggml-gpt4all-j
|
||||
@@ -1,6 +0,0 @@
|
||||
FROM node:latest
|
||||
COPY ./langchainjs-localai-example /app
|
||||
WORKDIR /app
|
||||
RUN npm install
|
||||
RUN npm run build
|
||||
ENTRYPOINT [ "npm", "run", "start" ]
|
||||
@@ -1,5 +0,0 @@
|
||||
FROM python:3.10-bullseye
|
||||
COPY ./langchainpy-localai-example /app
|
||||
WORKDIR /app
|
||||
RUN pip install --no-cache-dir -r requirements.txt
|
||||
ENTRYPOINT [ "python", "./full_demo.py" ];
|
||||
@@ -1,30 +0,0 @@
|
||||
# langchain
|
||||
|
||||
Example of using langchain, with the standard OpenAI llm module, and LocalAI. Has docker compose profiles for both the Typescript and Python versions.
|
||||
|
||||
**Please Note** - This is a tech demo example at this time. ggml-gpt4all-j has pretty terrible results for most langchain applications with the settings used in this example.
|
||||
|
||||
## Setup
|
||||
|
||||
```bash
|
||||
# Clone LocalAI
|
||||
git clone https://github.com/go-skynet/LocalAI
|
||||
|
||||
cd LocalAI/examples/langchain
|
||||
|
||||
# (optional) - Edit the example code in typescript.
|
||||
# vi ./langchainjs-localai-example/index.ts
|
||||
|
||||
# Download gpt4all-j to models/
|
||||
wget https://gpt4all.io/models/ggml-gpt4all-j.bin -O models/ggml-gpt4all-j
|
||||
|
||||
# start with docker-compose for typescript!
|
||||
docker-compose --profile ts up --build
|
||||
|
||||
# or start with docker-compose for python!
|
||||
docker-compose --profile py up --build
|
||||
```
|
||||
|
||||
## Copyright
|
||||
|
||||
Some of the example code in index.mts and full_demo.py is adapted from the langchainjs project and is Copyright (c) Harrison Chase. Used under the terms of the MIT license, as is the remainder of this code.
|
||||
@@ -1,43 +0,0 @@
|
||||
version: '3.6'
|
||||
|
||||
services:
|
||||
api:
|
||||
image: quay.io/go-skynet/local-ai:latest
|
||||
build:
|
||||
context: ../../
|
||||
dockerfile: Dockerfile.dev
|
||||
ports:
|
||||
- 8080:8080
|
||||
environment:
|
||||
- DEBUG=true
|
||||
- MODELS_PATH=/models
|
||||
volumes:
|
||||
- ./models:/models:cached
|
||||
command: ["/usr/bin/local-ai" ]
|
||||
|
||||
js:
|
||||
build:
|
||||
context: .
|
||||
dockerfile: JS.Dockerfile
|
||||
profiles:
|
||||
- js
|
||||
- ts
|
||||
depends_on:
|
||||
- "api"
|
||||
environment:
|
||||
- 'OPENAI_API_KEY=sk-XXXXXXXXXXXXXXXXXXXX'
|
||||
- 'OPENAI_API_BASE=http://api:8080/v1'
|
||||
- 'MODEL_NAME=gpt-3.5-turbo' #gpt-3.5-turbo' # ggml-gpt4all-j' # ggml-koala-13B-4bit-128g'
|
||||
|
||||
py:
|
||||
build:
|
||||
context: .
|
||||
dockerfile: PY.Dockerfile
|
||||
profiles:
|
||||
- py
|
||||
depends_on:
|
||||
- "api"
|
||||
environment:
|
||||
- 'OPENAI_API_KEY=sk-XXXXXXXXXXXXXXXXXXXX'
|
||||
- 'OPENAI_API_BASE=http://api:8080/v1'
|
||||
- 'MODEL_NAME=gpt-3.5-turbo' #gpt-3.5-turbo' # ggml-gpt4all-j' # ggml-koala-13B-4bit-128g'
|
||||
@@ -1,2 +0,0 @@
|
||||
node_modules/
|
||||
dist/
|
||||
@@ -1,20 +0,0 @@
|
||||
{
|
||||
// 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"
|
||||
]
|
||||
}
|
||||
]
|
||||
}
|
||||
File diff suppressed because it is too large
Load Diff
@@ -1,21 +0,0 @@
|
||||
{
|
||||
"name": "langchainjs-localai-example",
|
||||
"version": "0.1.0",
|
||||
"description": "Trivial Example of using langchain + the OpenAI API + LocalAI together",
|
||||
"main": "index.mjs",
|
||||
"scripts": {
|
||||
"build": "tsc --build",
|
||||
"clean": "tsc --build --clean",
|
||||
"start": "node --trace-warnings dist/index.mjs"
|
||||
},
|
||||
"author": "dave@gray101.com",
|
||||
"license": "MIT",
|
||||
"devDependencies": {
|
||||
"@types/node": "^18.16.4",
|
||||
"typescript": "^5.0.4"
|
||||
},
|
||||
"dependencies": {
|
||||
"langchain": "^0.0.67",
|
||||
"typeorm": "^0.3.15"
|
||||
}
|
||||
}
|
||||
@@ -1,79 +0,0 @@
|
||||
import { OpenAIChat } from "langchain/llms/openai";
|
||||
import { loadQAStuffChain } from "langchain/chains";
|
||||
import { Document } from "langchain/document";
|
||||
import { initializeAgentExecutorWithOptions } from "langchain/agents";
|
||||
import {Calculator} from "langchain/tools/calculator";
|
||||
|
||||
const pathToLocalAi = process.env['OPENAI_API_BASE'] || 'http://api:8080/v1';
|
||||
const fakeApiKey = process.env['OPENAI_API_KEY'] || '-';
|
||||
const modelName = process.env['MODEL_NAME'] || 'gpt-3.5-turbo';
|
||||
|
||||
function getModel(): OpenAIChat {
|
||||
return new OpenAIChat({
|
||||
prefixMessages: [
|
||||
{
|
||||
role: "system",
|
||||
content: "You are a helpful assistant that answers in pirate language",
|
||||
},
|
||||
],
|
||||
modelName: modelName,
|
||||
maxTokens: 50,
|
||||
openAIApiKey: fakeApiKey,
|
||||
maxRetries: 2
|
||||
}, {
|
||||
basePath: pathToLocalAi,
|
||||
apiKey: fakeApiKey,
|
||||
});
|
||||
}
|
||||
|
||||
// Minimal example.
|
||||
export const run = async () => {
|
||||
const model = getModel();
|
||||
console.log(`about to model.call at ${new Date().toUTCString()}`);
|
||||
const res = await model.call(
|
||||
"What would be a good company name a company that makes colorful socks?"
|
||||
);
|
||||
console.log(`${new Date().toUTCString()}`);
|
||||
console.log({ res });
|
||||
};
|
||||
|
||||
await run();
|
||||
|
||||
// This example uses the `StuffDocumentsChain`
|
||||
export const run2 = async () => {
|
||||
const model = getModel();
|
||||
const chainA = loadQAStuffChain(model);
|
||||
const docs = [
|
||||
new Document({ pageContent: "Harrison went to Harvard." }),
|
||||
new Document({ pageContent: "Ankush went to Princeton." }),
|
||||
];
|
||||
const resA = await chainA.call({
|
||||
input_documents: docs,
|
||||
question: "Where did Harrison go to college?",
|
||||
});
|
||||
console.log({ resA });
|
||||
};
|
||||
|
||||
await run2();
|
||||
|
||||
// Quickly thrown together example of using tools + agents.
|
||||
// This seems like it should work, but it doesn't yet.
|
||||
export const temporarilyBrokenToolTest = async () => {
|
||||
const model = getModel();
|
||||
|
||||
const executor = await initializeAgentExecutorWithOptions([new Calculator(true)], model, {
|
||||
agentType: "zero-shot-react-description",
|
||||
});
|
||||
|
||||
console.log("Loaded agent.");
|
||||
|
||||
const input = `What is the value of (500 *2) + 350 - 13?`;
|
||||
|
||||
console.log(`Executing with input "${input}"...`);
|
||||
|
||||
const result = await executor.call({ input });
|
||||
|
||||
console.log(`Got output ${result.output}`);
|
||||
}
|
||||
|
||||
await temporarilyBrokenToolTest();
|
||||
@@ -1,15 +0,0 @@
|
||||
{
|
||||
"compilerOptions": {
|
||||
"target": "es2022",
|
||||
"lib": ["ES2022", "DOM"],
|
||||
"module": "ES2022",
|
||||
"moduleResolution": "node",
|
||||
"strict": true,
|
||||
"esModuleInterop": true,
|
||||
"allowSyntheticDefaultImports": true,
|
||||
"isolatedModules": true,
|
||||
"outDir": "./dist"
|
||||
},
|
||||
"include": ["src", "test"],
|
||||
"exclude": ["node_modules", "dist"]
|
||||
}
|
||||
@@ -1,24 +0,0 @@
|
||||
{
|
||||
"version": "0.2.0",
|
||||
"configurations": [
|
||||
{
|
||||
"name": "Python: Current File",
|
||||
"type": "python",
|
||||
"request": "launch",
|
||||
"program": "${file}",
|
||||
"console": "integratedTerminal",
|
||||
"redirectOutput": true,
|
||||
"justMyCode": false
|
||||
},
|
||||
{
|
||||
"name": "Python: Attach to Port 5678",
|
||||
"type": "python",
|
||||
"request": "attach",
|
||||
"connect": {
|
||||
"host": "localhost",
|
||||
"port": 5678
|
||||
},
|
||||
"justMyCode": false
|
||||
}
|
||||
]
|
||||
}
|
||||
@@ -1,3 +0,0 @@
|
||||
{
|
||||
"python.defaultInterpreterPath": "${workspaceFolder}/.venv/Scripts/python"
|
||||
}
|
||||
@@ -1,46 +0,0 @@
|
||||
import os
|
||||
import logging
|
||||
|
||||
from langchain.chat_models import ChatOpenAI
|
||||
from langchain import PromptTemplate, LLMChain
|
||||
from langchain.prompts.chat import (
|
||||
ChatPromptTemplate,
|
||||
SystemMessagePromptTemplate,
|
||||
AIMessagePromptTemplate,
|
||||
HumanMessagePromptTemplate,
|
||||
)
|
||||
from langchain.schema import (
|
||||
AIMessage,
|
||||
HumanMessage,
|
||||
SystemMessage
|
||||
)
|
||||
|
||||
# This logging incantation makes it easy to see that you're actually reaching your LocalAI instance rather than OpenAI.
|
||||
logging.basicConfig(level=logging.DEBUG)
|
||||
|
||||
print('Langchain + LocalAI PYTHON Tests')
|
||||
|
||||
base_path = os.environ.get('OPENAI_API_BASE', 'http://api:8080/v1')
|
||||
key = os.environ.get('OPENAI_API_KEY', '-')
|
||||
model_name = os.environ.get('MODEL_NAME', 'gpt-3.5-turbo')
|
||||
|
||||
|
||||
chat = ChatOpenAI(temperature=0, openai_api_base=base_path, openai_api_key=key, model_name=model_name, max_tokens=100)
|
||||
|
||||
print("Created ChatOpenAI for ", chat.model_name)
|
||||
|
||||
template = "You are a helpful assistant that translates {input_language} to {output_language}. The next message will be a sentence in {input_language}. Respond ONLY with the translation in {output_language}. Do not respond in {input_language}!"
|
||||
system_message_prompt = SystemMessagePromptTemplate.from_template(template)
|
||||
human_template = "{text}"
|
||||
human_message_prompt = HumanMessagePromptTemplate.from_template(human_template)
|
||||
|
||||
chat_prompt = ChatPromptTemplate.from_messages([system_message_prompt, human_message_prompt])
|
||||
|
||||
print("ABOUT to execute")
|
||||
|
||||
# get a chat completion from the formatted messages
|
||||
response = chat(chat_prompt.format_prompt(input_language="English", output_language="French", text="I love programming.").to_messages())
|
||||
|
||||
print(response)
|
||||
|
||||
print(".");
|
||||
@@ -1,32 +0,0 @@
|
||||
aiohttp==3.8.4
|
||||
aiosignal==1.3.1
|
||||
async-timeout==4.0.2
|
||||
attrs==23.1.0
|
||||
certifi==2022.12.7
|
||||
charset-normalizer==3.1.0
|
||||
colorama==0.4.6
|
||||
dataclasses-json==0.5.7
|
||||
debugpy==1.6.7
|
||||
frozenlist==1.3.3
|
||||
greenlet==2.0.2
|
||||
idna==3.4
|
||||
langchain==0.0.159
|
||||
marshmallow==3.19.0
|
||||
marshmallow-enum==1.5.1
|
||||
multidict==6.0.4
|
||||
mypy-extensions==1.0.0
|
||||
numexpr==2.8.4
|
||||
numpy==1.24.3
|
||||
openai==0.27.6
|
||||
openapi-schema-pydantic==1.2.4
|
||||
packaging==23.1
|
||||
pydantic==1.10.7
|
||||
PyYAML==6.0
|
||||
requests==2.29.0
|
||||
SQLAlchemy==2.0.12
|
||||
tenacity==8.2.2
|
||||
tqdm==4.65.0
|
||||
typing-inspect==0.8.0
|
||||
typing_extensions==4.5.0
|
||||
urllib3==1.26.15
|
||||
yarl==1.9.2
|
||||
@@ -1,6 +0,0 @@
|
||||
|
||||
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))
|
||||
@@ -1 +0,0 @@
|
||||
{{.Input}}
|
||||
@@ -1,18 +0,0 @@
|
||||
name: gpt-3.5-turbo
|
||||
parameters:
|
||||
model: ggml-gpt4all-j # ggml-koala-13B-4bit-128g
|
||||
top_k: 80
|
||||
temperature: 0.2
|
||||
top_p: 0.7
|
||||
context_size: 1024
|
||||
threads: 4
|
||||
stopwords:
|
||||
- "HUMAN:"
|
||||
- "GPT:"
|
||||
roles:
|
||||
user: " "
|
||||
system: " "
|
||||
backend: "gptj"
|
||||
template:
|
||||
completion: completion
|
||||
chat: gpt4all
|
||||
@@ -1,4 +0,0 @@
|
||||
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:
|
||||
@@ -1,26 +0,0 @@
|
||||
# localai-webui
|
||||
|
||||
Example of integration with [dhruvgera/localai-frontend](https://github.com/Dhruvgera/LocalAI-frontend).
|
||||
|
||||
|
||||
|
||||
## Setup
|
||||
|
||||
```bash
|
||||
# Clone LocalAI
|
||||
git clone https://github.com/go-skynet/LocalAI
|
||||
|
||||
cd LocalAI/examples/localai-webui
|
||||
|
||||
# (optional) Checkout a specific LocalAI tag
|
||||
# git checkout -b build <TAG>
|
||||
|
||||
# Download any desired models to models/ in the parent LocalAI project dir
|
||||
# For example: wget https://gpt4all.io/models/ggml-gpt4all-j.bin
|
||||
|
||||
# start with docker-compose
|
||||
docker-compose up -d --build
|
||||
```
|
||||
|
||||
Open http://localhost:3000 for the Web UI.
|
||||
|
||||
@@ -1,20 +0,0 @@
|
||||
version: '3.6'
|
||||
|
||||
services:
|
||||
api:
|
||||
image: quay.io/go-skynet/local-ai:latest
|
||||
build:
|
||||
context: .
|
||||
dockerfile: Dockerfile
|
||||
ports:
|
||||
- 8080:8080
|
||||
env_file:
|
||||
- .env
|
||||
volumes:
|
||||
- ./models:/models:cached
|
||||
command: ["/usr/bin/local-ai"]
|
||||
|
||||
frontend:
|
||||
image: quay.io/go-skynet/localai-frontend:master
|
||||
ports:
|
||||
- 3000:3000
|
||||
1
examples/query_data/.gitignore
vendored
1
examples/query_data/.gitignore
vendored
@@ -1 +0,0 @@
|
||||
storage/
|
||||
@@ -1,49 +0,0 @@
|
||||
# Data query example
|
||||
|
||||
This example makes use of [Llama-Index](https://gpt-index.readthedocs.io/en/stable/getting_started/installation.html) to enable question answering on a set of documents.
|
||||
|
||||
It loosely follows [the quickstart](https://gpt-index.readthedocs.io/en/stable/guides/primer/usage_pattern.html).
|
||||
|
||||
## Requirements
|
||||
|
||||
For this in order to work, you will need a model compatible with the `llama.cpp` backend. This is will not work with gpt4all.
|
||||
|
||||
The example uses `WizardLM`. Edit the config files in `models/` accordingly to specify the model you use (change `HERE`).
|
||||
|
||||
You will also need a training data set. Copy that over `data`.
|
||||
|
||||
## Setup
|
||||
|
||||
Start the API:
|
||||
|
||||
```bash
|
||||
# Clone LocalAI
|
||||
git clone https://github.com/go-skynet/LocalAI
|
||||
|
||||
cd LocalAI/examples/query_data
|
||||
|
||||
# Copy your models, edit config files accordingly
|
||||
|
||||
# start with docker-compose
|
||||
docker-compose up -d --build
|
||||
```
|
||||
|
||||
### Create a storage:
|
||||
|
||||
```bash
|
||||
export OPENAI_API_BASE=http://localhost:8080/v1
|
||||
export OPENAI_API_KEY=sk-
|
||||
|
||||
python store.py
|
||||
```
|
||||
|
||||
After it finishes, a directory "storage" will be created with the vector index database.
|
||||
|
||||
## Query
|
||||
|
||||
```bash
|
||||
export OPENAI_API_BASE=http://localhost:8080/v1
|
||||
export OPENAI_API_KEY=sk-
|
||||
|
||||
python query.py
|
||||
```
|
||||
@@ -1,15 +0,0 @@
|
||||
version: '3.6'
|
||||
|
||||
services:
|
||||
api:
|
||||
image: quay.io/go-skynet/local-ai:latest
|
||||
build:
|
||||
context: .
|
||||
dockerfile: Dockerfile
|
||||
ports:
|
||||
- 8080:8080
|
||||
env_file:
|
||||
- .env
|
||||
volumes:
|
||||
- ./models:/models:cached
|
||||
command: ["/usr/bin/local-ai"]
|
||||
@@ -1 +0,0 @@
|
||||
{{.Input}}
|
||||
@@ -1,18 +0,0 @@
|
||||
name: text-embedding-ada-002
|
||||
parameters:
|
||||
model: HERE
|
||||
top_k: 80
|
||||
temperature: 0.2
|
||||
top_p: 0.7
|
||||
context_size: 1024
|
||||
threads: 14
|
||||
stopwords:
|
||||
- "HUMAN:"
|
||||
- "GPT:"
|
||||
roles:
|
||||
user: " "
|
||||
system: " "
|
||||
embeddings: true
|
||||
template:
|
||||
completion: completion
|
||||
chat: gpt4all
|
||||
@@ -1,18 +0,0 @@
|
||||
name: gpt-3.5-turbo
|
||||
parameters:
|
||||
model: HERE
|
||||
top_k: 80
|
||||
temperature: 0.2
|
||||
top_p: 0.7
|
||||
context_size: 1024
|
||||
threads: 14
|
||||
embeddings: true
|
||||
stopwords:
|
||||
- "HUMAN:"
|
||||
- "GPT:"
|
||||
roles:
|
||||
user: " "
|
||||
system: " "
|
||||
template:
|
||||
completion: completion
|
||||
chat: wizardlm
|
||||
@@ -1,3 +0,0 @@
|
||||
{{.Input}}
|
||||
|
||||
### Response:
|
||||
@@ -1,33 +0,0 @@
|
||||
import os
|
||||
|
||||
# Uncomment to specify your OpenAI API key here (local testing only, not in production!), or add corresponding environment variable (recommended)
|
||||
# os.environ['OPENAI_API_KEY']= ""
|
||||
|
||||
from llama_index import LLMPredictor, PromptHelper, ServiceContext
|
||||
from langchain.llms.openai import OpenAI
|
||||
from llama_index import StorageContext, load_index_from_storage
|
||||
|
||||
base_path = os.environ.get('OPENAI_API_BASE', 'http://localhost:8080/v1')
|
||||
|
||||
# This example uses text-davinci-003 by default; feel free to change if desired
|
||||
llm_predictor = LLMPredictor(llm=OpenAI(temperature=0, model_name="gpt-3.5-turbo",openai_api_base=base_path))
|
||||
|
||||
# Configure prompt parameters and initialise helper
|
||||
max_input_size = 1024
|
||||
num_output = 256
|
||||
max_chunk_overlap = 20
|
||||
|
||||
prompt_helper = PromptHelper(max_input_size, num_output, max_chunk_overlap)
|
||||
|
||||
# Load documents from the 'data' directory
|
||||
service_context = ServiceContext.from_defaults(llm_predictor=llm_predictor, prompt_helper=prompt_helper)
|
||||
|
||||
# rebuild storage context
|
||||
storage_context = StorageContext.from_defaults(persist_dir='./storage')
|
||||
|
||||
# load index
|
||||
index = load_index_from_storage(storage_context, service_context=service_context, )
|
||||
|
||||
query_engine = index.as_query_engine()
|
||||
response = query_engine.query("XXXXXX your question here XXXXX")
|
||||
print(response)
|
||||
@@ -1,27 +0,0 @@
|
||||
import os
|
||||
|
||||
# Uncomment to specify your OpenAI API key here (local testing only, not in production!), or add corresponding environment variable (recommended)
|
||||
# os.environ['OPENAI_API_KEY']= ""
|
||||
|
||||
from llama_index import GPTVectorStoreIndex, SimpleDirectoryReader, LLMPredictor, PromptHelper, ServiceContext
|
||||
from langchain.llms.openai import OpenAI
|
||||
from llama_index import StorageContext, load_index_from_storage
|
||||
|
||||
base_path = os.environ.get('OPENAI_API_BASE', 'http://localhost:8080/v1')
|
||||
|
||||
# This example uses text-davinci-003 by default; feel free to change if desired
|
||||
llm_predictor = LLMPredictor(llm=OpenAI(temperature=0, model_name="gpt-3.5-turbo", openai_api_base=base_path))
|
||||
|
||||
# Configure prompt parameters and initialise helper
|
||||
max_input_size = 256
|
||||
num_output = 256
|
||||
max_chunk_overlap = 10
|
||||
|
||||
prompt_helper = PromptHelper(max_input_size, num_output, max_chunk_overlap)
|
||||
|
||||
# Load documents from the 'data' directory
|
||||
documents = SimpleDirectoryReader('data').load_data()
|
||||
service_context = ServiceContext.from_defaults(llm_predictor=llm_predictor, prompt_helper=prompt_helper, chunk_size_limit = 257)
|
||||
index = GPTVectorStoreIndex.from_documents(documents, service_context=service_context)
|
||||
index.storage_context.persist(persist_dir="./storage")
|
||||
|
||||
@@ -1,10 +0,0 @@
|
||||
FROM python
|
||||
|
||||
# convert the model (one-off)
|
||||
RUN pip3 install torch numpy
|
||||
|
||||
WORKDIR /build
|
||||
COPY ./scripts/ .
|
||||
|
||||
RUN git clone --recurse-submodules https://github.com/saharNooby/rwkv.cpp && cd rwkv.cpp && cmake . && cmake --build . --config Release
|
||||
ENTRYPOINT [ "/build/build.sh" ]
|
||||
@@ -1,59 +0,0 @@
|
||||
# rwkv
|
||||
|
||||
Example of how to run rwkv models.
|
||||
|
||||
## Run models
|
||||
|
||||
Setup:
|
||||
|
||||
```bash
|
||||
# Clone LocalAI
|
||||
git clone https://github.com/go-skynet/LocalAI
|
||||
|
||||
cd LocalAI/examples/rwkv
|
||||
|
||||
# (optional) Checkout a specific LocalAI tag
|
||||
# git checkout -b build <TAG>
|
||||
|
||||
# build the tooling image to convert an rwkv model locally:
|
||||
docker build -t rwkv-converter -f Dockerfile.build .
|
||||
|
||||
# download and convert a model (one-off) - it's going to be fast on CPU too!
|
||||
docker run -ti --name converter -v $PWD:/data rwkv-converter https://huggingface.co/BlinkDL/rwkv-4-raven/resolve/main/RWKV-4-Raven-1B5-v11-Eng99%25-Other1%25-20230425-ctx4096.pth /data/models/rwkv
|
||||
|
||||
# Get the tokenizer
|
||||
wget https://raw.githubusercontent.com/saharNooby/rwkv.cpp/5eb8f09c146ea8124633ab041d9ea0b1f1db4459/rwkv/20B_tokenizer.json -O models/rwkv.tokenizer.json
|
||||
|
||||
# start with docker-compose
|
||||
docker-compose up -d --build
|
||||
```
|
||||
|
||||
Test it out:
|
||||
|
||||
```bash
|
||||
curl http://localhost:8080/v1/completions -H "Content-Type: application/json" -d '{
|
||||
"model": "gpt-3.5-turbo",
|
||||
"prompt": "A long time ago, in a galaxy far away",
|
||||
"max_tokens": 100,
|
||||
"temperature": 0.9, "top_p": 0.8, "top_k": 80
|
||||
}'
|
||||
|
||||
# {"object":"text_completion","model":"gpt-3.5-turbo","choices":[{"text":", there was a small group of five friends: Annie, Bryan, Charlie, Emily, and Jesse."}],"usage":{"prompt_tokens":0,"completion_tokens":0,"total_tokens":0}}
|
||||
|
||||
curl http://localhost:8080/v1/chat/completions -H "Content-Type: application/json" -d '{
|
||||
"model": "gpt-3.5-turbo",
|
||||
"messages": [{"role": "user", "content": "How are you?"}],
|
||||
"temperature": 0.9, "top_p": 0.8, "top_k": 80
|
||||
}'
|
||||
|
||||
# {"object":"chat.completion","model":"gpt-3.5-turbo","choices":[{"message":{"role":"assistant","content":" Good, thanks. I am about to go to bed. I' ll talk to you later.Bye."}}],"usage":{"prompt_tokens":0,"completion_tokens":0,"total_tokens":0}}
|
||||
```
|
||||
|
||||
### Fine tuning
|
||||
|
||||
See [RWKV-LM](https://github.com/BlinkDL/RWKV-LM#training--fine-tuning). There is also a Google [colab](https://colab.research.google.com/github/resloved/RWKV-notebooks/blob/master/RWKV_v4_RNN_Pile_Fine_Tuning.ipynb).
|
||||
|
||||
## See also
|
||||
|
||||
- [RWKV-LM](https://github.com/BlinkDL/RWKV-LM)
|
||||
- [rwkv.cpp](https://github.com/saharNooby/rwkv.cpp)
|
||||
@@ -1,16 +0,0 @@
|
||||
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" ]
|
||||
@@ -1,19 +0,0 @@
|
||||
name: gpt-3.5-turbo
|
||||
parameters:
|
||||
model: rwkv
|
||||
top_k: 80
|
||||
temperature: 0.9
|
||||
max_tokens: 100
|
||||
top_p: 0.8
|
||||
context_size: 1024
|
||||
threads: 14
|
||||
backend: "rwkv"
|
||||
cutwords:
|
||||
- "Bob:.*"
|
||||
roles:
|
||||
user: "Bob:"
|
||||
system: "Alice:"
|
||||
assistant: "Alice:"
|
||||
template:
|
||||
completion: rwkv_completion
|
||||
chat: rwkv_chat
|
||||
@@ -1,13 +0,0 @@
|
||||
The following is a verbose detailed conversation between Bob and a woman, Alice. Alice is intelligent, friendly and likeable. Alice is likely to agree with Bob.
|
||||
|
||||
Bob: Hello Alice, how are you doing?
|
||||
|
||||
Alice: Hi Bob! Thanks, I'm fine. What about you?
|
||||
|
||||
Bob: I am very good! It's nice to see you. Would you mind me chatting with you for a while?
|
||||
|
||||
Alice: Not at all! I'm listening.
|
||||
|
||||
{{.Input}}
|
||||
|
||||
Alice:
|
||||
@@ -1 +0,0 @@
|
||||
Complete the following sentence: {{.Input}}
|
||||
@@ -1,11 +0,0 @@
|
||||
#!/bin/bash
|
||||
set -ex
|
||||
|
||||
URL=$1
|
||||
OUT=$2
|
||||
FILENAME=$(basename $URL)
|
||||
|
||||
wget -nc $URL -O /build/$FILENAME
|
||||
|
||||
python3 /build/rwkv.cpp/rwkv/convert_pytorch_to_ggml.py /build/$FILENAME /build/float-model float16
|
||||
python3 /build/rwkv.cpp/rwkv/quantize.py /build/float-model $OUT Q4_2
|
||||
@@ -1,11 +0,0 @@
|
||||
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
|
||||
@@ -1,27 +0,0 @@
|
||||
# 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
|
||||
```
|
||||
@@ -1,23 +0,0 @@
|
||||
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 +0,0 @@
|
||||
../chatbot-ui/models
|
||||
59
go.mod
59
go.mod
@@ -1,59 +0,0 @@
|
||||
module github.com/go-skynet/LocalAI
|
||||
|
||||
go 1.19
|
||||
|
||||
require (
|
||||
github.com/donomii/go-rwkv.cpp v0.0.0-20230503112711-af62fcc432be
|
||||
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 v0.0.0-20230505100647-691d479d3675
|
||||
github.com/gofiber/fiber/v2 v2.44.0
|
||||
github.com/hashicorp/go-multierror v1.1.1
|
||||
github.com/onsi/ginkgo/v2 v2.9.4
|
||||
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 v1.9.3
|
||||
github.com/swaggo/swag v1.16.1
|
||||
github.com/urfave/cli/v2 v2.25.3
|
||||
github.com/valyala/fasthttp v1.47.0
|
||||
gopkg.in/yaml.v3 v3.0.1
|
||||
)
|
||||
|
||||
require (
|
||||
github.com/KyleBanks/depth v1.2.1 // indirect
|
||||
github.com/PuerkitoBio/purell v1.1.1 // indirect
|
||||
github.com/PuerkitoBio/urlesc v0.0.0-20170810143723-de5bf2ad4578 // indirect
|
||||
github.com/andybalholm/brotli v1.0.5 // indirect
|
||||
github.com/cpuguy83/go-md2man/v2 v2.0.2 // indirect
|
||||
github.com/go-logr/logr v1.2.4 // indirect
|
||||
github.com/go-openapi/jsonpointer v0.19.5 // indirect
|
||||
github.com/go-openapi/jsonreference v0.19.6 // indirect
|
||||
github.com/go-openapi/spec v0.20.4 // indirect
|
||||
github.com/go-openapi/swag v0.19.15 // indirect
|
||||
github.com/go-task/slim-sprig v0.0.0-20230315185526-52ccab3ef572 // indirect
|
||||
github.com/google/go-cmp v0.5.9 // indirect
|
||||
github.com/google/pprof v0.0.0-20210407192527-94a9f03dee38 // indirect
|
||||
github.com/google/uuid v1.3.0 // indirect
|
||||
github.com/hashicorp/errwrap v1.0.0 // indirect
|
||||
github.com/josharian/intern v1.0.0 // indirect
|
||||
github.com/klauspost/compress v1.16.3 // indirect
|
||||
github.com/mailru/easyjson v0.7.6 // indirect
|
||||
github.com/mattn/go-colorable v0.1.13 // indirect
|
||||
github.com/mattn/go-isatty v0.0.18 // indirect
|
||||
github.com/mattn/go-runewidth v0.0.14 // indirect
|
||||
github.com/philhofer/fwd v1.1.2 // 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
|
||||
)
|
||||
197
go.sum
197
go.sum
@@ -1,197 +0,0 @@
|
||||
github.com/KyleBanks/depth v1.2.1 h1:5h8fQADFrWtarTdtDudMmGsC7GPbOAu6RVB3ffsVFHc=
|
||||
github.com/KyleBanks/depth v1.2.1/go.mod h1:jzSb9d0L43HxTQfT+oSA1EEp2q+ne2uh6XgeJcm8brE=
|
||||
github.com/PuerkitoBio/purell v1.1.1 h1:WEQqlqaGbrPkxLJWfBwQmfEAE1Z7ONdDLqrN38tNFfI=
|
||||
github.com/PuerkitoBio/purell v1.1.1/go.mod h1:c11w/QuzBsJSee3cPx9rAFu61PvFxuPbtSwDGJws/X0=
|
||||
github.com/PuerkitoBio/urlesc v0.0.0-20170810143723-de5bf2ad4578 h1:d+Bc7a5rLufV/sSk/8dngufqelfh6jnri85riMAaF/M=
|
||||
github.com/PuerkitoBio/urlesc v0.0.0-20170810143723-de5bf2ad4578/go.mod h1:uGdkoq3SwY9Y+13GIhn11/XLaGBb4BfwItxLd5jeuXE=
|
||||
github.com/andybalholm/brotli v1.0.5 h1:8uQZIdzKmjc/iuPu7O2ioW48L81FgatrcpfFmiq/cCs=
|
||||
github.com/andybalholm/brotli v1.0.5/go.mod h1:fO7iG3H7G2nSZ7m0zPUDn85XEX2GTukHGRSepvi9Eig=
|
||||
github.com/chzyer/logex v1.1.10/go.mod h1:+Ywpsq7O8HXn0nuIou7OrIPyXbp3wmkHB+jjWRnGsAI=
|
||||
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 v0.0.0-20230503112711-af62fcc432be h1:3Hic97PY6hcw/SY44RuR7kyONkxd744RFeRrqckzwNQ=
|
||||
github.com/donomii/go-rwkv.cpp v0.0.0-20230503112711-af62fcc432be/go.mod h1:gWy7FIWioqYmYxkaoFyBnaKApeZVrUkHhv9EV9pz4dM=
|
||||
github.com/go-logr/logr v1.2.4 h1:g01GSCwiDw2xSZfjJ2/T9M+S6pFdcNtFYsp+Y43HYDQ=
|
||||
github.com/go-logr/logr v1.2.4/go.mod h1:jdQByPbusPIv2/zmleS9BjJVeZ6kBagPoEUsqbVz/1A=
|
||||
github.com/go-openapi/jsonpointer v0.19.3/go.mod h1:Pl9vOtqEWErmShwVjC8pYs9cog34VGT37dQOVbmoatg=
|
||||
github.com/go-openapi/jsonpointer v0.19.5 h1:gZr+CIYByUqjcgeLXnQu2gHYQC9o73G2XUeOFYEICuY=
|
||||
github.com/go-openapi/jsonpointer v0.19.5/go.mod h1:Pl9vOtqEWErmShwVjC8pYs9cog34VGT37dQOVbmoatg=
|
||||
github.com/go-openapi/jsonreference v0.19.6 h1:UBIxjkht+AWIgYzCDSv2GN+E/togfwXUJFRTWhl2Jjs=
|
||||
github.com/go-openapi/jsonreference v0.19.6/go.mod h1:diGHMEHg2IqXZGKxqyvWdfWU/aim5Dprw5bqpKkTvns=
|
||||
github.com/go-openapi/spec v0.20.4 h1:O8hJrt0UMnhHcluhIdUgCLRWyM2x7QkBXRvOs7m+O1M=
|
||||
github.com/go-openapi/spec v0.20.4/go.mod h1:faYFR1CvsJZ0mNsmsphTMSoRrNV3TEDoAM7FOEWeq8I=
|
||||
github.com/go-openapi/swag v0.19.5/go.mod h1:POnQmlKehdgb5mhVOsnJFsivZCEZ/vjK9gh66Z9tfKk=
|
||||
github.com/go-openapi/swag v0.19.15 h1:D2NRCBzS9/pEY3gP9Nl8aDqGUcPFrwG2p+CNFrLyrCM=
|
||||
github.com/go-openapi/swag v0.19.15/go.mod h1:QYRuS/SOXUCsnplDa677K7+DxSOj6IPNl/eQntq43wQ=
|
||||
github.com/go-skynet/go-gpt2.cpp v0.0.0-20230422085954-245a5bfe6708 h1:cfOi4TWvQ6JsAm9Q1A8I8j9YfNy10bmIfwOiyGyU5wQ=
|
||||
github.com/go-skynet/go-gpt2.cpp v0.0.0-20230422085954-245a5bfe6708/go.mod h1:1Wj/xbkMfwQSOrhNYK178IzqQHstZbRfhx4s8p1M5VM=
|
||||
github.com/go-skynet/go-gpt4all-j.cpp v0.0.0-20230422090028-1f7bff57f66c h1:48I7jpLNGiQeBmF0SFVVbREh8vlG0zN13v9LH5ctXis=
|
||||
github.com/go-skynet/go-gpt4all-j.cpp v0.0.0-20230422090028-1f7bff57f66c/go.mod h1:5VZ9XbcINI0XcHhkcX8GPK8TplFGAzu1Hrg4tNiMCtI=
|
||||
github.com/go-skynet/go-llama.cpp v0.0.0-20230504223241-67ff6a4db244/go.mod h1:LvSQx5QAYBAMpWkbyVFFDiM1Tzj8LP55DvmUM3hbRMY=
|
||||
github.com/go-skynet/go-llama.cpp v0.0.0-20230505100647-691d479d3675 h1:plXywr95RghidIHPHl+O/zpcNXenEeS6w/6WftFNr9E=
|
||||
github.com/go-skynet/go-llama.cpp v0.0.0-20230505100647-691d479d3675/go.mod h1:LvSQx5QAYBAMpWkbyVFFDiM1Tzj8LP55DvmUM3hbRMY=
|
||||
github.com/go-task/slim-sprig v0.0.0-20230315185526-52ccab3ef572 h1:tfuBGBXKqDEevZMzYi5KSi8KkcZtzBcTgAUUtapy0OI=
|
||||
github.com/go-task/slim-sprig v0.0.0-20230315185526-52ccab3ef572/go.mod h1:9Pwr4B2jHnOSGXyyzV8ROjYa2ojvAY6HCGYYfMoC3Ls=
|
||||
github.com/godbus/dbus/v5 v5.0.4/go.mod h1:xhWf0FNVPg57R7Z0UbKHbJfkEywrmjJnf7w5xrFpKfA=
|
||||
github.com/gofiber/fiber/v2 v2.44.0 h1:Z90bEvPcJM5GFJnu1py0E1ojoerkyew3iiNJ78MQCM8=
|
||||
github.com/gofiber/fiber/v2 v2.44.0/go.mod h1:VTMtb/au8g01iqvHyaCzftuM/xmZgKOZCtFzz6CdV9w=
|
||||
github.com/golang/protobuf v1.5.3 h1:KhyjKVUg7Usr/dYsdSqoFveMYd5ko72D+zANwlG1mmg=
|
||||
github.com/google/go-cmp v0.5.9 h1:O2Tfq5qg4qc4AmwVlvv0oLiVAGB7enBSJ2x2DqQFi38=
|
||||
github.com/google/go-cmp v0.5.9/go.mod h1:17dUlkBOakJ0+DkrSSNjCkIjxS6bF9zb3elmeNGIjoY=
|
||||
github.com/google/pprof v0.0.0-20210407192527-94a9f03dee38 h1:yAJXTCF9TqKcTiHJAE8dj7HMvPfh66eeA2JYW7eFpSE=
|
||||
github.com/google/pprof v0.0.0-20210407192527-94a9f03dee38/go.mod h1:kpwsk12EmLew5upagYY7GY0pfYCcupk39gWOCRROcvE=
|
||||
github.com/google/uuid v1.3.0 h1:t6JiXgmwXMjEs8VusXIJk2BXHsn+wx8BZdTaoZ5fu7I=
|
||||
github.com/google/uuid v1.3.0/go.mod h1:TIyPZe4MgqvfeYDBFedMoGGpEw/LqOeaOT+nhxU+yHo=
|
||||
github.com/hashicorp/errwrap v1.0.0 h1:hLrqtEDnRye3+sgx6z4qVLNuviH3MR5aQ0ykNJa/UYA=
|
||||
github.com/hashicorp/errwrap v1.0.0/go.mod h1:YH+1FKiLXxHSkmPseP+kNlulaMuP3n2brvKWEqk/Jc4=
|
||||
github.com/hashicorp/go-multierror v1.1.1 h1:H5DkEtf6CXdFp0N0Em5UCwQpXMWke8IA0+lD48awMYo=
|
||||
github.com/hashicorp/go-multierror v1.1.1/go.mod h1:iw975J/qwKPdAO1clOe2L8331t/9/fmwbPZ6JB6eMoM=
|
||||
github.com/ianlancetaylor/demangle v0.0.0-20200824232613-28f6c0f3b639/go.mod h1:aSSvb/t6k1mPoxDqO4vJh6VOCGPwU4O0C2/Eqndh1Sc=
|
||||
github.com/josharian/intern v1.0.0 h1:vlS4z54oSdjm0bgjRigI+G1HpF+tI+9rE5LLzOg8HmY=
|
||||
github.com/josharian/intern v1.0.0/go.mod h1:5DoeVV0s6jJacbCEi61lwdGj/aVlrQvzHFFd8Hwg//Y=
|
||||
github.com/klauspost/compress v1.16.3 h1:XuJt9zzcnaz6a16/OU53ZjWp/v7/42WcR5t2a0PcNQY=
|
||||
github.com/klauspost/compress v1.16.3/go.mod h1:ntbaceVETuRiXiv4DpjP66DpAtAGkEQskQzEyD//IeE=
|
||||
github.com/kr/pretty v0.1.0/go.mod h1:dAy3ld7l9f0ibDNOQOHHMYYIIbhfbHSm3C4ZsoJORNo=
|
||||
github.com/kr/pty v1.1.1/go.mod h1:pFQYn66WHrOpPYNljwOMqo10TkYh1fy3cYio2l3bCsQ=
|
||||
github.com/kr/text v0.1.0/go.mod h1:4Jbv+DJW3UT/LiOwJeYQe1efqtUx/iVham/4vfdArNI=
|
||||
github.com/kr/text v0.2.0 h1:5Nx0Ya0ZqY2ygV366QzturHI13Jq95ApcVaJBhpS+AY=
|
||||
github.com/kr/text v0.2.0/go.mod h1:eLer722TekiGuMkidMxC/pM04lWEeraHUUmBw8l2grE=
|
||||
github.com/mailru/easyjson v0.0.0-20190614124828-94de47d64c63/go.mod h1:C1wdFJiN94OJF2b5HbByQZoLdCWB1Yqtg26g4irojpc=
|
||||
github.com/mailru/easyjson v0.0.0-20190626092158-b2ccc519800e/go.mod h1:C1wdFJiN94OJF2b5HbByQZoLdCWB1Yqtg26g4irojpc=
|
||||
github.com/mailru/easyjson v0.7.6 h1:8yTIVnZgCoiM1TgqoeTl+LfU5Jg6/xL3QhGQnimLYnA=
|
||||
github.com/mailru/easyjson v0.7.6/go.mod h1:xzfreul335JAWq5oZzymOObrkdz5UnU4kGfJJLY9Nlc=
|
||||
github.com/mattn/go-colorable v0.1.12/go.mod h1:u5H1YNBxpqRaxsYJYSkiCWKzEfiAb1Gb520KVy5xxl4=
|
||||
github.com/mattn/go-colorable v0.1.13 h1:fFA4WZxdEF4tXPZVKMLwD8oUnCTTo08duU7wxecdEvA=
|
||||
github.com/mattn/go-colorable v0.1.13/go.mod h1:7S9/ev0klgBDR4GtXTXX8a3vIGJpMovkB8vQcUbaXHg=
|
||||
github.com/mattn/go-isatty v0.0.14/go.mod h1:7GGIvUiUoEMVVmxf/4nioHXj79iQHKdU27kJ6hsGG94=
|
||||
github.com/mattn/go-isatty v0.0.16/go.mod h1:kYGgaQfpe5nmfYZH+SKPsOc2e4SrIfOl2e/yFXSvRLM=
|
||||
github.com/mattn/go-isatty v0.0.18 h1:DOKFKCQ7FNG2L1rbrmstDN4QVRdS89Nkh85u68Uwp98=
|
||||
github.com/mattn/go-isatty v0.0.18/go.mod h1:W+V8PltTTMOvKvAeJH7IuucS94S2C6jfK/D7dTCTo3Y=
|
||||
github.com/mattn/go-runewidth v0.0.14 h1:+xnbZSEeDbOIg5/mE6JF0w6n9duR1l3/WmbinWVwUuU=
|
||||
github.com/mattn/go-runewidth v0.0.14/go.mod h1:Jdepj2loyihRzMpdS35Xk/zdY8IAYHsh153qUoGf23w=
|
||||
github.com/niemeyer/pretty v0.0.0-20200227124842-a10e7caefd8e h1:fD57ERR4JtEqsWbfPhv4DMiApHyliiK5xCTNVSPiaAs=
|
||||
github.com/niemeyer/pretty v0.0.0-20200227124842-a10e7caefd8e/go.mod h1:zD1mROLANZcx1PVRCS0qkT7pwLkGfwJo4zjcN/Tysno=
|
||||
github.com/onsi/ginkgo/v2 v2.9.4 h1:xR7vG4IXt5RWx6FfIjyAtsoMAtnc3C/rFXBBd2AjZwE=
|
||||
github.com/onsi/ginkgo/v2 v2.9.4/go.mod h1:gCQYp2Q+kSoIj7ykSVb9nskRSsR6PUj4AiLywzIhbKM=
|
||||
github.com/onsi/gomega v1.27.6 h1:ENqfyGeS5AX/rlXDd/ETokDz93u0YufY1Pgxuy/PvWE=
|
||||
github.com/onsi/gomega v1.27.6/go.mod h1:PIQNjfQwkP3aQAH7lf7j87O/5FiNr+ZR8+ipb+qQlhg=
|
||||
github.com/otiai10/mint v1.4.1 h1:HOVBfKP1oXIc0wWo9hZ8JLdZtyCPWqjvmFDuVZ0yv2Y=
|
||||
github.com/otiai10/openaigo v1.1.0 h1:zRvGBqZUW5PCMgdkJNsPVTBd8tOLCMTipXE5wD2pdTg=
|
||||
github.com/otiai10/openaigo v1.1.0/go.mod h1:792bx6AWTS61weDi2EzKpHHnTF4eDMAlJ5GvAk/mgPg=
|
||||
github.com/philhofer/fwd v1.1.1/go.mod h1:gk3iGcWd9+svBvR0sR+KPcfE+RNWozjowpeBVG3ZVNU=
|
||||
github.com/philhofer/fwd v1.1.2 h1:bnDivRJ1EWPjUIRXV5KfORO897HTbpFAQddBdE8t7Gw=
|
||||
github.com/philhofer/fwd v1.1.2/go.mod h1:qkPdfjR2SIEbspLqpe1tO4n5yICnr2DY7mqEx2tUTP0=
|
||||
github.com/pkg/errors v0.9.1/go.mod h1:bwawxfHBFNV+L2hUp1rHADufV3IMtnDRdf1r5NINEl0=
|
||||
github.com/pmezard/go-difflib v1.0.0 h1:4DBwDE0NGyQoBHbLQYPwSUPoCMWR5BEzIk/f1lZbAQM=
|
||||
github.com/pmezard/go-difflib v1.0.0/go.mod h1:iKH77koFhYxTK1pcRnkKkqfTogsbg7gZNVY4sRDYZ/4=
|
||||
github.com/rivo/uniseg v0.2.0 h1:S1pD9weZBuJdFmowNwbpi7BJ8TNftyUImj/0WQi72jY=
|
||||
github.com/rivo/uniseg v0.2.0/go.mod h1:J6wj4VEh+S6ZtnVlnTBMWIodfgj8LQOQFoIToxlJtxc=
|
||||
github.com/rs/xid v1.4.0/go.mod h1:trrq9SKmegXys3aeAKXMUTdJsYXVwGY3RLcfgqegfbg=
|
||||
github.com/rs/zerolog v1.29.1 h1:cO+d60CHkknCbvzEWxP0S9K6KqyTjrCNUy1LdQLCGPc=
|
||||
github.com/rs/zerolog v1.29.1/go.mod h1:Le6ESbR7hc+DP6Lt1THiV8CQSdkkNrd3R0XbEgp3ZBU=
|
||||
github.com/russross/blackfriday/v2 v2.1.0 h1:JIOH55/0cWyOuilr9/qlrm0BSXldqnqwMsf35Ld67mk=
|
||||
github.com/russross/blackfriday/v2 v2.1.0/go.mod h1:+Rmxgy9KzJVeS9/2gXHxylqXiyQDYRxCVz55jmeOWTM=
|
||||
github.com/sashabaranov/go-openai v1.9.3 h1:uNak3Rn5pPsKRs9bdT7RqRZEyej/zdZOEI2/8wvrFtM=
|
||||
github.com/sashabaranov/go-openai v1.9.3/go.mod h1:lj5b/K+zjTSFxVLijLSTDZuP7adOgerWeFyZLUhAKRg=
|
||||
github.com/savsgio/dictpool v0.0.0-20221023140959-7bf2e61cea94 h1:rmMl4fXJhKMNWl+K+r/fq4FbbKI+Ia2m9hYBLm2h4G4=
|
||||
github.com/savsgio/dictpool v0.0.0-20221023140959-7bf2e61cea94/go.mod h1:90zrgN3D/WJsDd1iXHT96alCoN2KJo6/4x1DZC3wZs8=
|
||||
github.com/savsgio/gotils v0.0.0-20220530130905-52f3993e8d6d/go.mod h1:Gy+0tqhJvgGlqnTF8CVGP0AaGRjwBtXs/a5PA0Y3+A4=
|
||||
github.com/savsgio/gotils v0.0.0-20230208104028-c358bd845dee h1:8Iv5m6xEo1NR1AvpV+7XmhI4r39LGNzwUL4YpMuL5vk=
|
||||
github.com/savsgio/gotils v0.0.0-20230208104028-c358bd845dee/go.mod h1:qwtSXrKuJh/zsFQ12yEE89xfCrGKK63Rr7ctU/uCo4g=
|
||||
github.com/stretchr/objx v0.1.0/go.mod h1:HFkY916IF+rwdDfMAkV7OtwuqBVzrE8GR6GFx+wExME=
|
||||
github.com/stretchr/testify v1.3.0/go.mod h1:M5WIy9Dh21IEIfnGCwXGc5bZfKNJtfHm1UVUgZn+9EI=
|
||||
github.com/stretchr/testify v1.6.1/go.mod h1:6Fq8oRcR53rry900zMqJjRRixrwX3KX962/h/Wwjteg=
|
||||
github.com/stretchr/testify v1.7.0 h1:nwc3DEeHmmLAfoZucVR881uASk0Mfjw8xYJ99tb5CcY=
|
||||
github.com/swaggo/swag v1.16.1 h1:fTNRhKstPKxcnoKsytm4sahr8FaYzUcT7i1/3nd/fBg=
|
||||
github.com/swaggo/swag v1.16.1/go.mod h1:9/LMvHycG3NFHfR6LwvikHv5iFvmPADQ359cKikGxto=
|
||||
github.com/tinylib/msgp v1.1.6/go.mod h1:75BAfg2hauQhs3qedfdDZmWAPcFMAvJE5b9rGOMufyw=
|
||||
github.com/tinylib/msgp v1.1.8 h1:FCXC1xanKO4I8plpHGH2P7koL/RzZs12l/+r7vakfm0=
|
||||
github.com/tinylib/msgp v1.1.8/go.mod h1:qkpG+2ldGg4xRFmx+jfTvZPxfGFhi64BcnL9vkCm/Tw=
|
||||
github.com/urfave/cli/v2 v2.25.3 h1:VJkt6wvEBOoSjPFQvOkv6iWIrsJyCrKGtCtxXWwmGeY=
|
||||
github.com/urfave/cli/v2 v2.25.3/go.mod h1:GHupkWPMM0M/sj1a2b4wUrWBPzazNrIjouW6fmdJLxc=
|
||||
github.com/valyala/bytebufferpool v1.0.0 h1:GqA5TC/0021Y/b9FG4Oi9Mr3q7XYx6KllzawFIhcdPw=
|
||||
github.com/valyala/bytebufferpool v1.0.0/go.mod h1:6bBcMArwyJ5K/AmCkWv1jt77kVWyCJ6HpOuEn7z0Csc=
|
||||
github.com/valyala/fasthttp v1.47.0 h1:y7moDoxYzMooFpT5aHgNgVOQDrS3qlkfiP9mDtGGK9c=
|
||||
github.com/valyala/fasthttp v1.47.0/go.mod h1:k2zXd82h/7UZc3VOdJ2WaUqt1uZ/XpXAfE9i+HBC3lA=
|
||||
github.com/valyala/tcplisten v1.0.0 h1:rBHj/Xf+E1tRGZyWIWwJDiRY0zc1Js+CV5DqwacVSA8=
|
||||
github.com/valyala/tcplisten v1.0.0/go.mod h1:T0xQ8SeCZGxckz9qRXTfG43PvQ/mcWh7FwZEA7Ioqkc=
|
||||
github.com/xrash/smetrics v0.0.0-20201216005158-039620a65673 h1:bAn7/zixMGCfxrRTfdpNzjtPYqr8smhKouy9mxVdGPU=
|
||||
github.com/xrash/smetrics v0.0.0-20201216005158-039620a65673/go.mod h1:N3UwUGtsrSj3ccvlPHLoLsHnpR27oXr4ZE984MbSER8=
|
||||
github.com/yuin/goldmark v1.2.1/go.mod h1:3hX8gzYuyVAZsxl0MRgGTJEmQBFcNTphYh9decYSb74=
|
||||
github.com/yuin/goldmark v1.4.13/go.mod h1:6yULJ656Px+3vBD8DxQVa3kxgyrAnzto9xy5taEt/CY=
|
||||
golang.org/x/crypto v0.0.0-20190308221718-c2843e01d9a2/go.mod h1:djNgcEr1/C05ACkg1iLfiJU5Ep61QUkGW8qpdssI0+w=
|
||||
golang.org/x/crypto v0.0.0-20191011191535-87dc89f01550/go.mod h1:yigFU9vqHzYiE8UmvKecakEJjdnWj3jj499lnFckfCI=
|
||||
golang.org/x/crypto v0.0.0-20200622213623-75b288015ac9/go.mod h1:LzIPMQfyMNhhGPhUkYOs5KpL4U8rLKemX1yGLhDgUto=
|
||||
golang.org/x/crypto v0.0.0-20210921155107-089bfa567519/go.mod h1:GvvjBRRGRdwPK5ydBHafDWAxML/pGHZbMvKqRZ5+Abc=
|
||||
golang.org/x/mod v0.3.0/go.mod h1:s0Qsj1ACt9ePp/hMypM3fl4fZqREWJwdYDEqhRiZZUA=
|
||||
golang.org/x/mod v0.6.0-dev.0.20220419223038-86c51ed26bb4/go.mod h1:jJ57K6gSWd91VN4djpZkiMVwK6gcyfeH4XE8wZrZaV4=
|
||||
golang.org/x/mod v0.7.0/go.mod h1:iBbtSCu2XBx23ZKBPSOrRkjjQPZFPuis4dIYUhu/chs=
|
||||
golang.org/x/mod v0.10.0 h1:lFO9qtOdlre5W1jxS3r/4szv2/6iXxScdzjoBMXNhYk=
|
||||
golang.org/x/net v0.0.0-20190404232315-eb5bcb51f2a3/go.mod h1:t9HGtf8HONx5eT2rtn7q6eTqICYqUVnKs3thJo3Qplg=
|
||||
golang.org/x/net v0.0.0-20190620200207-3b0461eec859/go.mod h1:z5CRVTTTmAJ677TzLLGU+0bjPO0LkuOLi4/5GtJWs/s=
|
||||
golang.org/x/net v0.0.0-20201021035429-f5854403a974/go.mod h1:sp8m0HH+o8qH0wwXwYZr8TS3Oi6o0r6Gce1SSxlDquU=
|
||||
golang.org/x/net v0.0.0-20210226172049-e18ecbb05110/go.mod h1:m0MpNAwzfU5UDzcl9v0D8zg8gWTRqZa9RBIspLL5mdg=
|
||||
golang.org/x/net v0.0.0-20210421230115-4e50805a0758/go.mod h1:72T/g9IO56b78aLF+1Kcs5dz7/ng1VjMUvfKvpfy+jM=
|
||||
golang.org/x/net v0.0.0-20220722155237-a158d28d115b/go.mod h1:XRhObCWvk6IyKnWLug+ECip1KBveYUHfp+8e9klMJ9c=
|
||||
golang.org/x/net v0.3.0/go.mod h1:MBQ8lrhLObU/6UmLb4fmbmk5OcyYmqtbGd/9yIeKjEE=
|
||||
golang.org/x/net v0.9.0 h1:aWJ/m6xSmxWBx+V0XRHTlrYrPG56jKsLdTFmsSsCzOM=
|
||||
golang.org/x/net v0.9.0/go.mod h1:d48xBJpPfHeWQsugry2m+kC02ZBRGRgulfHnEXEuWns=
|
||||
golang.org/x/sync v0.0.0-20190423024810-112230192c58/go.mod h1:RxMgew5VJxzue5/jJTE5uejpjVlOe/izrB70Jof72aM=
|
||||
golang.org/x/sync v0.0.0-20201020160332-67f06af15bc9/go.mod h1:RxMgew5VJxzue5/jJTE5uejpjVlOe/izrB70Jof72aM=
|
||||
golang.org/x/sync v0.0.0-20220722155255-886fb9371eb4/go.mod h1:RxMgew5VJxzue5/jJTE5uejpjVlOe/izrB70Jof72aM=
|
||||
golang.org/x/sync v0.1.0/go.mod h1:RxMgew5VJxzue5/jJTE5uejpjVlOe/izrB70Jof72aM=
|
||||
golang.org/x/sys v0.0.0-20190215142949-d0b11bdaac8a/go.mod h1:STP8DvDyc/dI5b8T5hshtkjS+E42TnysNCUPdjciGhY=
|
||||
golang.org/x/sys v0.0.0-20190412213103-97732733099d/go.mod h1:h1NjWce9XRLGQEsW7wpKNCjG9DtNlClVuFLEZdDNbEs=
|
||||
golang.org/x/sys v0.0.0-20191204072324-ce4227a45e2e/go.mod h1:h1NjWce9XRLGQEsW7wpKNCjG9DtNlClVuFLEZdDNbEs=
|
||||
golang.org/x/sys v0.0.0-20200930185726-fdedc70b468f/go.mod h1:h1NjWce9XRLGQEsW7wpKNCjG9DtNlClVuFLEZdDNbEs=
|
||||
golang.org/x/sys v0.0.0-20201119102817-f84b799fce68/go.mod h1:h1NjWce9XRLGQEsW7wpKNCjG9DtNlClVuFLEZdDNbEs=
|
||||
golang.org/x/sys v0.0.0-20210420072515-93ed5bcd2bfe/go.mod h1:h1NjWce9XRLGQEsW7wpKNCjG9DtNlClVuFLEZdDNbEs=
|
||||
golang.org/x/sys v0.0.0-20210615035016-665e8c7367d1/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 v0.3.6/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 v0.9.0 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 v0.8.0 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/go.mod h1:Co6ibVJAznAaIkqp8huTwlJQCZ016jof/cbN4VW5Yz0=
|
||||
gopkg.in/check.v1 v1.0.0-20200227125254-8fa46927fb4f h1:BLraFXnmrev5lT+xlilqcH8XK9/i0At2xKjWk4p6zsU=
|
||||
gopkg.in/check.v1 v1.0.0-20200227125254-8fa46927fb4f/go.mod h1:Co6ibVJAznAaIkqp8huTwlJQCZ016jof/cbN4VW5Yz0=
|
||||
gopkg.in/yaml.v2 v2.2.2/go.mod h1:hI93XBmqTisBFMUTm0b8Fm+jr3Dg1NNxqwp+5A1VGuI=
|
||||
gopkg.in/yaml.v2 v2.4.0 h1:D8xgwECY7CYvx+Y2n4sBz93Jn9JRvxdiyyo8CTfuKaY=
|
||||
gopkg.in/yaml.v2 v2.4.0/go.mod h1:RDklbk79AGWmwhnvt/jBztapEOGDOx6ZbXqjP6csGnQ=
|
||||
gopkg.in/yaml.v3 v3.0.0-20200313102051-9f266ea9e77c/go.mod h1:K4uyk7z7BCEPqu6E+C64Yfv1cQ7kz7rIZviUmN+EgEM=
|
||||
gopkg.in/yaml.v3 v3.0.0-20200615113413-eeeca48fe776/go.mod h1:K4uyk7z7BCEPqu6E+C64Yfv1cQ7kz7rIZviUmN+EgEM=
|
||||
gopkg.in/yaml.v3 v3.0.1 h1:fxVm/GzAzEWqLHuvctI91KS9hhNmmWOoWu0XTYJS7CA=
|
||||
gopkg.in/yaml.v3 v3.0.1/go.mod h1:K4uyk7z7BCEPqu6E+C64Yfv1cQ7kz7rIZviUmN+EgEM=
|
||||
93
main.go
93
main.go
@@ -1,93 +0,0 @@
|
||||
package main
|
||||
|
||||
import (
|
||||
"fmt"
|
||||
"os"
|
||||
"path/filepath"
|
||||
|
||||
api "github.com/go-skynet/LocalAI/api"
|
||||
model "github.com/go-skynet/LocalAI/pkg/model"
|
||||
"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)
|
||||
}
|
||||
|
||||
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: 4,
|
||||
},
|
||||
&cli.StringFlag{
|
||||
Name: "models-path",
|
||||
DefaultText: "Path containing models used for inferencing",
|
||||
EnvVars: []string{"MODELS_PATH"},
|
||||
Value: filepath.Join(path, "models"),
|
||||
},
|
||||
&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 {
|
||||
fmt.Printf("Starting LocalAI using %d threads, with models path: %s\n", ctx.Int("threads"), ctx.String("models-path"))
|
||||
return api.App(ctx.String("config-file"), model.NewModelLoader(ctx.String("models-path")), ctx.Int("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)
|
||||
}
|
||||
}
|
||||
@@ -1,365 +0,0 @@
|
||||
package model
|
||||
|
||||
import (
|
||||
"bytes"
|
||||
"fmt"
|
||||
"io/ioutil"
|
||||
"os"
|
||||
"path/filepath"
|
||||
"strings"
|
||||
"sync"
|
||||
"text/template"
|
||||
|
||||
"github.com/hashicorp/go-multierror"
|
||||
"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 "", fmt.Errorf("failed loading any template")
|
||||
}
|
||||
|
||||
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
|
||||
}
|
||||
|
||||
const tokenizerSuffix = ".tokenizer.json"
|
||||
|
||||
var loadedModels map[string]interface{} = map[string]interface{}{}
|
||||
var muModels sync.Mutex
|
||||
|
||||
func (ml *ModelLoader) BackendLoader(backendString string, modelFile string, llamaOpts []llama.ModelOption, threads uint32) (model interface{}, err error) {
|
||||
switch strings.ToLower(backendString) {
|
||||
case "llama":
|
||||
return ml.LoadLLaMAModel(modelFile, llamaOpts...)
|
||||
case "stablelm":
|
||||
return ml.LoadStableLMModel(modelFile)
|
||||
case "gpt2":
|
||||
return ml.LoadGPT2Model(modelFile)
|
||||
case "gptj":
|
||||
return ml.LoadGPTJModel(modelFile)
|
||||
case "rwkv":
|
||||
return ml.LoadRWKV(modelFile, modelFile+tokenizerSuffix, threads)
|
||||
default:
|
||||
return nil, fmt.Errorf("backend unsupported: %s", backendString)
|
||||
}
|
||||
}
|
||||
|
||||
func (ml *ModelLoader) GreedyLoader(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 := ml.LoadLLaMAModel(modelFile, llamaOpts...)
|
||||
if modelerr == nil {
|
||||
updateModels(model)
|
||||
return model, nil
|
||||
} else {
|
||||
err = multierror.Append(err, modelerr)
|
||||
}
|
||||
|
||||
model, modelerr = ml.LoadGPTJModel(modelFile)
|
||||
if modelerr == nil {
|
||||
updateModels(model)
|
||||
return model, nil
|
||||
} else {
|
||||
err = multierror.Append(err, modelerr)
|
||||
}
|
||||
|
||||
model, modelerr = ml.LoadGPT2Model(modelFile)
|
||||
if modelerr == nil {
|
||||
updateModels(model)
|
||||
return model, nil
|
||||
} else {
|
||||
err = multierror.Append(err, modelerr)
|
||||
}
|
||||
|
||||
model, modelerr = ml.LoadStableLMModel(modelFile)
|
||||
if modelerr == nil {
|
||||
updateModels(model)
|
||||
return model, nil
|
||||
} else {
|
||||
err = multierror.Append(err, modelerr)
|
||||
}
|
||||
|
||||
model, modelerr = ml.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())
|
||||
}
|
||||
@@ -1,6 +0,0 @@
|
||||
Below is an instruction that describes a task. Write a response that appropriately completes the request.
|
||||
|
||||
### Instruction:
|
||||
{{.Input}}
|
||||
|
||||
### Response:
|
||||
@@ -1,4 +0,0 @@
|
||||
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:
|
||||
@@ -1 +0,0 @@
|
||||
BEGINNING OF CONVERSATION: USER: {{.Input}} GPT:
|
||||
@@ -1,6 +0,0 @@
|
||||
Below is an instruction that describes a task. Write a response that appropriately completes the request.
|
||||
|
||||
### Instruction:
|
||||
{{.Input}}
|
||||
|
||||
### Response:
|
||||
@@ -1,3 +0,0 @@
|
||||
{{.Input}}
|
||||
|
||||
### Response:
|
||||
@@ -1,4 +0,0 @@
|
||||
{
|
||||
"$schema": "https://docs.renovatebot.com/renovate-schema.json",
|
||||
"extends": ["config:base"]
|
||||
}
|
||||
1
tests/fixtures/completion.tmpl
vendored
1
tests/fixtures/completion.tmpl
vendored
@@ -1 +0,0 @@
|
||||
{{.Input}}
|
||||
32
tests/fixtures/config.yaml
vendored
32
tests/fixtures/config.yaml
vendored
@@ -1,32 +0,0 @@
|
||||
- name: list1
|
||||
parameters:
|
||||
model: testmodel
|
||||
top_p: 80
|
||||
top_k: 0.9
|
||||
temperature: 0.1
|
||||
context_size: 10
|
||||
stopwords:
|
||||
- "HUMAN:"
|
||||
- "### Response:"
|
||||
roles:
|
||||
user: "HUMAN:"
|
||||
system: "GPT:"
|
||||
template:
|
||||
completion: completion
|
||||
chat: ggml-gpt4all-j
|
||||
- name: list2
|
||||
parameters:
|
||||
top_p: 80
|
||||
top_k: 0.9
|
||||
temperature: 0.1
|
||||
model: testmodel
|
||||
context_size: 10
|
||||
stopwords:
|
||||
- "HUMAN:"
|
||||
- "### Response:"
|
||||
roles:
|
||||
user: "HUMAN:"
|
||||
system: "GPT:"
|
||||
template:
|
||||
completion: completion
|
||||
chat: ggml-gpt4all-j
|
||||
4
tests/fixtures/ggml-gpt4all-j.tmpl
vendored
4
tests/fixtures/ggml-gpt4all-j.tmpl
vendored
@@ -1,4 +0,0 @@
|
||||
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:
|
||||
16
tests/fixtures/gpt4.yaml
vendored
16
tests/fixtures/gpt4.yaml
vendored
@@ -1,16 +0,0 @@
|
||||
name: gpt4all
|
||||
parameters:
|
||||
model: testmodel
|
||||
top_p: 80
|
||||
top_k: 0.9
|
||||
temperature: 0.1
|
||||
context_size: 10
|
||||
stopwords:
|
||||
- "HUMAN:"
|
||||
- "### Response:"
|
||||
roles:
|
||||
user: "HUMAN:"
|
||||
system: "GPT:"
|
||||
template:
|
||||
completion: completion
|
||||
chat: ggml-gpt4all-j
|
||||
16
tests/fixtures/gpt4_2.yaml
vendored
16
tests/fixtures/gpt4_2.yaml
vendored
@@ -1,16 +0,0 @@
|
||||
name: gpt4all-2
|
||||
parameters:
|
||||
model: testmodel
|
||||
top_p: 80
|
||||
top_k: 0.9
|
||||
temperature: 0.1
|
||||
context_size: 10
|
||||
stopwords:
|
||||
- "HUMAN:"
|
||||
- "### Response:"
|
||||
roles:
|
||||
user: "HUMAN:"
|
||||
system: "GPT:"
|
||||
template:
|
||||
completion: completion
|
||||
chat: ggml-gpt4all-j
|
||||
Reference in New Issue
Block a user