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@@ -1,3 +0,0 @@
|
||||
ARG GO_VERSION=1.20
|
||||
FROM mcr.microsoft.com/devcontainers/go:0-$GO_VERSION-bullseye
|
||||
RUN apt-get update && apt-get install -y cmake
|
||||
@@ -1,46 +0,0 @@
|
||||
// For format details, see https://aka.ms/devcontainer.json. For config options, see the
|
||||
// README at: https://github.com/devcontainers/templates/tree/main/src/docker-existing-docker-compose
|
||||
{
|
||||
"name": "Existing Docker Compose (Extend)",
|
||||
|
||||
// Update the 'dockerComposeFile' list if you have more compose files or use different names.
|
||||
// The .devcontainer/docker-compose.yml file contains any overrides you need/want to make.
|
||||
"dockerComposeFile": [
|
||||
"../docker-compose.yaml",
|
||||
"docker-compose.yml"
|
||||
],
|
||||
|
||||
// The 'service' property is the name of the service for the container that VS Code should
|
||||
// use. Update this value and .devcontainer/docker-compose.yml to the real service name.
|
||||
"service": "api",
|
||||
|
||||
// The optional 'workspaceFolder' property is the path VS Code should open by default when
|
||||
// connected. This is typically a file mount in .devcontainer/docker-compose.yml
|
||||
"workspaceFolder": "/workspace",
|
||||
|
||||
"features": {
|
||||
"ghcr.io/devcontainers/features/go:1": {},
|
||||
"ghcr.io/azutake/devcontainer-features/go-packages-install:0": {}
|
||||
},
|
||||
|
||||
// Features to add to the dev container. More info: https://containers.dev/features.
|
||||
// "features": {},
|
||||
|
||||
// Use 'forwardPorts' to make a list of ports inside the container available locally.
|
||||
// "forwardPorts": [],
|
||||
|
||||
// Uncomment the next line if you want start specific services in your Docker Compose config.
|
||||
// "runServices": [],
|
||||
|
||||
// Uncomment the next line if you want to keep your containers running after VS Code shuts down.
|
||||
// "shutdownAction": "none",
|
||||
|
||||
// Uncomment the next line to run commands after the container is created.
|
||||
"postCreateCommand": "make prepare"
|
||||
|
||||
// Configure tool-specific properties.
|
||||
// "customizations": {},
|
||||
|
||||
// Uncomment to connect as an existing user other than the container default. More info: https://aka.ms/dev-containers-non-root.
|
||||
// "remoteUser": "devcontainer"
|
||||
}
|
||||
@@ -1,26 +0,0 @@
|
||||
version: '3.6'
|
||||
services:
|
||||
# Update this to the name of the service you want to work with in your docker-compose.yml file
|
||||
api:
|
||||
# Uncomment if you want to override the service's Dockerfile to one in the .devcontainer
|
||||
# folder. Note that the path of the Dockerfile and context is relative to the *primary*
|
||||
# docker-compose.yml file (the first in the devcontainer.json "dockerComposeFile"
|
||||
# array). The sample below assumes your primary file is in the root of your project.
|
||||
#
|
||||
build:
|
||||
context: .
|
||||
dockerfile: .devcontainer/Dockerfile
|
||||
|
||||
volumes:
|
||||
# Update this to wherever you want VS Code to mount the folder of your project
|
||||
- .:/workspace:cached
|
||||
|
||||
# Uncomment the next four lines if you will use a ptrace-based debugger like C++, Go, and Rust.
|
||||
# cap_add:
|
||||
# - SYS_PTRACE
|
||||
# security_opt:
|
||||
# - seccomp:unconfined
|
||||
|
||||
# Overrides default command so things don't shut down after the process ends.
|
||||
command: /bin/sh -c "while sleep 1000; do :; done"
|
||||
|
||||
@@ -1,3 +1,4 @@
|
||||
.idea
|
||||
models
|
||||
examples/chatbot-ui/models
|
||||
examples/rwkv/models
|
||||
|
||||
26
.env
26
.env
@@ -7,24 +7,40 @@
|
||||
|
||||
## Default models context size
|
||||
# CONTEXT_SIZE=512
|
||||
#
|
||||
## Define galleries.
|
||||
## models will to install will be visible in `/models/available`
|
||||
# GALLERIES=[{"name":"model-gallery", "url":"github:go-skynet/model-gallery/index.yaml"}]
|
||||
|
||||
## CORS settings
|
||||
# CORS=true
|
||||
# CORS_ALLOW_ORIGINS=*
|
||||
|
||||
## Default path for models
|
||||
#
|
||||
MODELS_PATH=/models
|
||||
|
||||
## Enable debug mode
|
||||
# DEBUG=true
|
||||
|
||||
## Specify a build type. Available: cublas, openblas.
|
||||
## Specify a build type. Available: cublas, openblas, clblas.
|
||||
## cuBLAS: This is a GPU-accelerated version of the complete standard BLAS (Basic Linear Algebra Subprograms) library. It's provided by Nvidia and is part of their CUDA toolkit.
|
||||
## OpenBLAS: This is an open-source implementation of the BLAS library that aims to provide highly optimized code for various platforms. It includes support for multi-threading and can be compiled to use hardware-specific features for additional performance. OpenBLAS can run on many kinds of hardware, including CPUs from Intel, AMD, and ARM.
|
||||
## clBLAS: This is an open-source implementation of the BLAS library that uses OpenCL, a framework for writing programs that execute across heterogeneous platforms consisting of CPUs, GPUs, and other processors. clBLAS is designed to take advantage of the parallel computing power of GPUs but can also run on any hardware that supports OpenCL. This includes hardware from different vendors like Nvidia, AMD, and Intel.
|
||||
# BUILD_TYPE=openblas
|
||||
|
||||
## Uncomment and set to false to disable rebuilding from source
|
||||
# REBUILD=false
|
||||
## Uncomment and set to true to enable rebuilding from source
|
||||
# REBUILD=true
|
||||
|
||||
## Enable image generation with stablediffusion (requires REBUILD=true)
|
||||
## Enable go tags, available: stablediffusion, tts
|
||||
## stablediffusion: image generation with stablediffusion
|
||||
## tts: enables text-to-speech with go-piper
|
||||
## (requires REBUILD=true)
|
||||
#
|
||||
# GO_TAGS=stablediffusion
|
||||
|
||||
## Path where to store generated images
|
||||
# IMAGE_PATH=/tmp
|
||||
|
||||
## Specify a default upload limit in MB (whisper)
|
||||
# UPLOAD_LIMIT
|
||||
# UPLOAD_LIMIT
|
||||
|
||||
1
.gitattributes
vendored
Normal file
1
.gitattributes
vendored
Normal file
@@ -0,0 +1 @@
|
||||
*.sh text eol=lf
|
||||
5
.github/FUNDING.yml
vendored
Normal file
5
.github/FUNDING.yml
vendored
Normal file
@@ -0,0 +1,5 @@
|
||||
# These are supported funding model platforms
|
||||
|
||||
github: [mudler]
|
||||
custom:
|
||||
- https://www.buymeacoffee.com/mudler
|
||||
9
.github/workflows/bump_deps.yaml
vendored
9
.github/workflows/bump_deps.yaml
vendored
@@ -30,6 +30,15 @@ jobs:
|
||||
- repository: "nomic-ai/gpt4all"
|
||||
variable: "GPT4ALL_VERSION"
|
||||
branch: "main"
|
||||
- repository: "mudler/go-ggllm.cpp"
|
||||
variable: "GOGGLLM_VERSION"
|
||||
branch: "master"
|
||||
- repository: "mudler/go-stable-diffusion"
|
||||
variable: "STABLEDIFFUSION_VERSION"
|
||||
branch: "master"
|
||||
- repository: "mudler/go-piper"
|
||||
variable: "PIPER_VERSION"
|
||||
branch: "master"
|
||||
runs-on: ubuntu-latest
|
||||
steps:
|
||||
- uses: actions/checkout@v3
|
||||
|
||||
135
.github/workflows/image.yml
vendored
135
.github/workflows/image.yml
vendored
@@ -15,34 +15,97 @@ concurrency:
|
||||
|
||||
jobs:
|
||||
docker:
|
||||
strategy:
|
||||
matrix:
|
||||
include:
|
||||
- build-type: ''
|
||||
platforms: 'linux/amd64,linux/arm64'
|
||||
tag-latest: 'auto'
|
||||
tag-suffix: ''
|
||||
ffmpeg: ''
|
||||
- build-type: 'cublas'
|
||||
cuda-major-version: 11
|
||||
cuda-minor-version: 7
|
||||
platforms: 'linux/amd64'
|
||||
tag-latest: 'false'
|
||||
tag-suffix: '-cublas-cuda11'
|
||||
ffmpeg: ''
|
||||
- build-type: 'cublas'
|
||||
cuda-major-version: 12
|
||||
cuda-minor-version: 1
|
||||
platforms: 'linux/amd64'
|
||||
tag-latest: 'false'
|
||||
tag-suffix: '-cublas-cuda12'
|
||||
ffmpeg: ''
|
||||
- build-type: ''
|
||||
platforms: 'linux/amd64,linux/arm64'
|
||||
tag-latest: 'false'
|
||||
tag-suffix: '-ffmpeg'
|
||||
ffmpeg: 'true'
|
||||
- build-type: 'cublas'
|
||||
cuda-major-version: 11
|
||||
cuda-minor-version: 7
|
||||
platforms: 'linux/amd64'
|
||||
tag-latest: 'false'
|
||||
tag-suffix: '-cublas-cuda11-ffmpeg'
|
||||
ffmpeg: 'true'
|
||||
- build-type: 'cublas'
|
||||
cuda-major-version: 12
|
||||
cuda-minor-version: 1
|
||||
platforms: 'linux/amd64'
|
||||
tag-latest: 'false'
|
||||
tag-suffix: '-cublas-cuda12-ffmpeg'
|
||||
ffmpeg: 'true'
|
||||
|
||||
runs-on: ubuntu-latest
|
||||
steps:
|
||||
- name: Release space from worker
|
||||
run: |
|
||||
echo "Listing top largest packages"
|
||||
pkgs=$(dpkg-query -Wf '${Installed-Size}\t${Package}\t${Status}\n' | awk '$NF == "installed"{print $1 "\t" $2}' | sort -nr)
|
||||
head -n 30 <<< "${pkgs}"
|
||||
echo
|
||||
df -h
|
||||
echo
|
||||
sudo apt-get remove -y '^llvm-.*|^libllvm.*' || true
|
||||
sudo apt-get remove --auto-remove android-sdk-platform-tools || true
|
||||
sudo apt-get purge --auto-remove android-sdk-platform-tools || true
|
||||
sudo rm -rf /usr/local/lib/android
|
||||
sudo apt-get remove -y '^dotnet-.*|^aspnetcore-.*' || true
|
||||
sudo rm -rf /usr/share/dotnet
|
||||
sudo apt-get remove -y '^mono-.*' || true
|
||||
sudo apt-get remove -y '^ghc-.*' || true
|
||||
sudo apt-get remove -y '.*jdk.*|.*jre.*' || true
|
||||
sudo apt-get remove -y 'php.*' || true
|
||||
sudo apt-get remove -y hhvm powershell firefox monodoc-manual msbuild || true
|
||||
sudo apt-get remove -y '^google-.*' || true
|
||||
sudo apt-get remove -y azure-cli || true
|
||||
sudo apt-get remove -y '^mongo.*-.*|^postgresql-.*|^mysql-.*|^mssql-.*' || true
|
||||
sudo apt-get remove -y '^gfortran-.*' || true
|
||||
sudo apt-get autoremove -y
|
||||
sudo apt-get clean
|
||||
echo
|
||||
echo "Listing top largest packages"
|
||||
pkgs=$(dpkg-query -Wf '${Installed-Size}\t${Package}\t${Status}\n' | awk '$NF == "installed"{print $1 "\t" $2}' | sort -nr)
|
||||
head -n 30 <<< "${pkgs}"
|
||||
echo
|
||||
sudo rm -rfv build || true
|
||||
df -h
|
||||
- name: Checkout
|
||||
uses: actions/checkout@v3
|
||||
|
||||
- name: Prepare
|
||||
id: prep
|
||||
run: |
|
||||
DOCKER_IMAGE=quay.io/go-skynet/local-ai
|
||||
VERSION=master
|
||||
SHORTREF=${GITHUB_SHA::8}
|
||||
|
||||
# If this is git tag, use the tag name as a docker tag
|
||||
if [[ $GITHUB_REF == refs/tags/* ]]; then
|
||||
VERSION=${GITHUB_REF#refs/tags/}
|
||||
fi
|
||||
TAGS="${DOCKER_IMAGE}:${VERSION},${DOCKER_IMAGE}:${SHORTREF}"
|
||||
|
||||
# If the VERSION looks like a version number, assume that
|
||||
# this is the most recent version of the image and also
|
||||
# tag it 'latest'.
|
||||
if [[ $VERSION =~ ^v[0-9]{1,3}\.[0-9]{1,3}\.[0-9]{1,3}$ ]]; then
|
||||
TAGS="$TAGS,${DOCKER_IMAGE}:latest"
|
||||
fi
|
||||
|
||||
# Set output parameters.
|
||||
echo ::set-output name=tags::${TAGS}
|
||||
echo ::set-output name=docker_image::${DOCKER_IMAGE}
|
||||
- name: Docker meta
|
||||
id: meta
|
||||
uses: docker/metadata-action@v4
|
||||
with:
|
||||
images: quay.io/go-skynet/local-ai
|
||||
tags: |
|
||||
type=ref,event=branch
|
||||
type=semver,pattern={{raw}}
|
||||
type=sha
|
||||
flavor: |
|
||||
latest=${{ matrix.tag-latest }}
|
||||
suffix=${{ matrix.tag-suffix }}
|
||||
|
||||
- name: Set up QEMU
|
||||
uses: docker/setup-qemu-action@master
|
||||
@@ -60,23 +123,19 @@ jobs:
|
||||
registry: quay.io
|
||||
username: ${{ secrets.LOCALAI_REGISTRY_USERNAME }}
|
||||
password: ${{ secrets.LOCALAI_REGISTRY_PASSWORD }}
|
||||
- name: Build
|
||||
if: github.event_name != 'pull_request'
|
||||
|
||||
- name: Build and push
|
||||
uses: docker/build-push-action@v4
|
||||
with:
|
||||
builder: ${{ steps.buildx.outputs.name }}
|
||||
build-args: |
|
||||
BUILD_TYPE=${{ matrix.build-type }}
|
||||
CUDA_MAJOR_VERSION=${{ matrix.cuda-major-version }}
|
||||
CUDA_MINOR_VERSION=${{ matrix.cuda-minor-version }}
|
||||
FFMPEG=${{ matrix.ffmpeg }}
|
||||
context: .
|
||||
file: ./Dockerfile
|
||||
platforms: linux/amd64,linux/arm64
|
||||
push: true
|
||||
tags: ${{ steps.prep.outputs.tags }}
|
||||
- name: Build PRs
|
||||
if: github.event_name == 'pull_request'
|
||||
uses: docker/build-push-action@v4
|
||||
with:
|
||||
builder: ${{ steps.buildx.outputs.name }}
|
||||
context: .
|
||||
file: ./Dockerfile
|
||||
platforms: linux/amd64
|
||||
push: false
|
||||
tags: ${{ steps.prep.outputs.tags }}
|
||||
platforms: ${{ matrix.platforms }}
|
||||
push: ${{ github.event_name != 'pull_request' }}
|
||||
tags: ${{ steps.meta.outputs.tags }}
|
||||
labels: ${{ steps.meta.outputs.labels }}
|
||||
|
||||
21
.github/workflows/release.yaml
vendored
21
.github/workflows/release.yaml
vendored
@@ -20,8 +20,11 @@ jobs:
|
||||
steps:
|
||||
- name: Clone
|
||||
uses: actions/checkout@v3
|
||||
with:
|
||||
with:
|
||||
submodules: true
|
||||
- uses: actions/setup-go@v4
|
||||
with:
|
||||
go-version: '>=1.21.0'
|
||||
- name: Dependencies
|
||||
run: |
|
||||
sudo apt-get update
|
||||
@@ -29,10 +32,10 @@ jobs:
|
||||
- name: Build
|
||||
id: build
|
||||
env:
|
||||
CMAKE_ARGS: "${{ matrix.define }}"
|
||||
CMAKE_ARGS: "${{ matrix.defines }}"
|
||||
BUILD_ID: "${{ matrix.build }}"
|
||||
run: |
|
||||
make dist
|
||||
STATIC=true make dist
|
||||
- uses: actions/upload-artifact@v3
|
||||
with:
|
||||
name: ${{ matrix.build }}
|
||||
@@ -58,17 +61,15 @@ jobs:
|
||||
steps:
|
||||
- name: Clone
|
||||
uses: actions/checkout@v3
|
||||
with:
|
||||
with:
|
||||
submodules: true
|
||||
|
||||
- name: Dependencies
|
||||
run: |
|
||||
brew update
|
||||
brew install sdl2 ffmpeg
|
||||
- uses: actions/setup-go@v4
|
||||
with:
|
||||
go-version: '>=1.21.0'
|
||||
- name: Build
|
||||
id: build
|
||||
env:
|
||||
CMAKE_ARGS: "${{ matrix.define }}"
|
||||
CMAKE_ARGS: "${{ matrix.defines }}"
|
||||
BUILD_ID: "${{ matrix.build }}"
|
||||
run: |
|
||||
make dist
|
||||
|
||||
51
.github/workflows/test.yml
vendored
51
.github/workflows/test.yml
vendored
@@ -16,33 +16,66 @@ concurrency:
|
||||
jobs:
|
||||
ubuntu-latest:
|
||||
runs-on: ubuntu-latest
|
||||
|
||||
strategy:
|
||||
matrix:
|
||||
go-version: ['1.21.x']
|
||||
steps:
|
||||
- name: Clone
|
||||
uses: actions/checkout@v3
|
||||
with:
|
||||
submodules: true
|
||||
- name: Setup Go ${{ matrix.go-version }}
|
||||
uses: actions/setup-go@v4
|
||||
with:
|
||||
go-version: ${{ matrix.go-version }}
|
||||
# You can test your matrix by printing the current Go version
|
||||
- name: Display Go version
|
||||
run: go version
|
||||
- name: Dependencies
|
||||
run: |
|
||||
sudo apt-get update
|
||||
sudo apt-get install build-essential ffmpeg
|
||||
|
||||
sudo apt-get install -y ca-certificates cmake curl patch
|
||||
sudo apt-get install -y libopencv-dev && sudo ln -s /usr/include/opencv4/opencv2 /usr/include/opencv2
|
||||
sudo pip install -r extra/requirements.txt
|
||||
|
||||
sudo mkdir /build && sudo chmod -R 777 /build && cd /build && \
|
||||
curl -L "https://github.com/gabime/spdlog/archive/refs/tags/v1.11.0.tar.gz" | \
|
||||
tar -xzvf - && \
|
||||
mkdir -p "spdlog-1.11.0/build" && \
|
||||
cd "spdlog-1.11.0/build" && \
|
||||
cmake .. && \
|
||||
make -j8 && \
|
||||
sudo cmake --install . --prefix /usr && mkdir -p "lib/Linux-$(uname -m)" && \
|
||||
cd /build && \
|
||||
mkdir -p "lib/Linux-$(uname -m)/piper_phonemize" && \
|
||||
curl -L "https://github.com/rhasspy/piper-phonemize/releases/download/v1.0.0/libpiper_phonemize-amd64.tar.gz" | \
|
||||
tar -C "lib/Linux-$(uname -m)/piper_phonemize" -xzvf - && ls -liah /build/lib/Linux-$(uname -m)/piper_phonemize/ && \
|
||||
sudo cp -rfv /build/lib/Linux-$(uname -m)/piper_phonemize/lib/. /usr/lib/ && \
|
||||
sudo ln -s /usr/lib/libpiper_phonemize.so /usr/lib/libpiper_phonemize.so.1 && \
|
||||
sudo cp -rfv /build/lib/Linux-$(uname -m)/piper_phonemize/include/. /usr/include/
|
||||
- name: Test
|
||||
run: |
|
||||
make test
|
||||
ESPEAK_DATA="/build/lib/Linux-$(uname -m)/piper_phonemize/lib/espeak-ng-data" GO_TAGS="tts stablediffusion" make test
|
||||
|
||||
macOS-latest:
|
||||
runs-on: macOS-latest
|
||||
|
||||
strategy:
|
||||
matrix:
|
||||
go-version: ['1.21.x']
|
||||
steps:
|
||||
- name: Clone
|
||||
uses: actions/checkout@v3
|
||||
with:
|
||||
submodules: true
|
||||
|
||||
- name: Dependencies
|
||||
run: |
|
||||
brew update
|
||||
brew install sdl2 ffmpeg
|
||||
- name: Setup Go ${{ matrix.go-version }}
|
||||
uses: actions/setup-go@v4
|
||||
with:
|
||||
go-version: ${{ matrix.go-version }}
|
||||
# You can test your matrix by printing the current Go version
|
||||
- name: Display Go version
|
||||
run: go version
|
||||
- name: Test
|
||||
run: |
|
||||
make test
|
||||
CMAKE_ARGS="-DLLAMA_F16C=OFF -DLLAMA_AVX512=OFF -DLLAMA_AVX2=OFF -DLLAMA_FMA=OFF" make test
|
||||
23
.gitignore
vendored
23
.gitignore
vendored
@@ -1,22 +1,43 @@
|
||||
# go-llama build artifacts
|
||||
go-llama
|
||||
gpt4all
|
||||
go-llama-stable
|
||||
/gpt4all
|
||||
go-stable-diffusion
|
||||
go-piper
|
||||
/go-bert
|
||||
go-ggllm
|
||||
/piper
|
||||
__pycache__/
|
||||
*.a
|
||||
get-sources
|
||||
|
||||
go-ggml-transformers
|
||||
go-gpt2
|
||||
go-rwkv
|
||||
whisper.cpp
|
||||
/bloomz
|
||||
go-bert
|
||||
|
||||
# LocalAI build binary
|
||||
LocalAI
|
||||
local-ai
|
||||
# prevent above rules from omitting the helm chart
|
||||
!charts/*
|
||||
# prevent above rules from omitting the api/localai folder
|
||||
!api/localai
|
||||
|
||||
# Ignore models
|
||||
models/*
|
||||
test-models/
|
||||
test-dir/
|
||||
|
||||
release/
|
||||
|
||||
# just in case
|
||||
.DS_Store
|
||||
.idea
|
||||
|
||||
# Generated during build
|
||||
backend-assets/
|
||||
prepare
|
||||
/ggml-metal.metal
|
||||
|
||||
2
.vscode/launch.json
vendored
2
.vscode/launch.json
vendored
@@ -25,7 +25,7 @@
|
||||
],
|
||||
"env": {
|
||||
"C_INCLUDE_PATH": "${workspaceFolder}/go-llama:${workspaceFolder}/go-stable-diffusion/:${workspaceFolder}/gpt4all/gpt4all-bindings/golang/:${workspaceFolder}/go-gpt2:${workspaceFolder}/go-rwkv:${workspaceFolder}/whisper.cpp:${workspaceFolder}/go-bert:${workspaceFolder}/bloomz",
|
||||
"LIBRARY_PATH": "$${workspaceFolder}/go-llama:${workspaceFolder}/go-stable-diffusion/:${workspaceFolder}/gpt4all/gpt4all-bindings/golang/:${workspaceFolder}/go-gpt2:${workspaceFolder}/go-rwkv:${workspaceFolder}/whisper.cpp:${workspaceFolder}/go-bert:${workspaceFolder}/bloomz",
|
||||
"LIBRARY_PATH": "${workspaceFolder}/go-llama:${workspaceFolder}/go-stable-diffusion/:${workspaceFolder}/gpt4all/gpt4all-bindings/golang/:${workspaceFolder}/go-gpt2:${workspaceFolder}/go-rwkv:${workspaceFolder}/whisper.cpp:${workspaceFolder}/go-bert:${workspaceFolder}/bloomz",
|
||||
"DEBUG": "true"
|
||||
}
|
||||
}
|
||||
|
||||
143
Dockerfile
143
Dockerfile
@@ -1,15 +1,142 @@
|
||||
ARG GO_VERSION=1.20
|
||||
ARG BUILD_TYPE=
|
||||
FROM golang:$GO_VERSION
|
||||
ENV REBUILD=true
|
||||
ARG GO_VERSION=1.21-bullseye
|
||||
|
||||
FROM golang:$GO_VERSION as requirements
|
||||
|
||||
ARG BUILD_TYPE
|
||||
ARG CUDA_MAJOR_VERSION=11
|
||||
ARG CUDA_MINOR_VERSION=7
|
||||
ARG SPDLOG_VERSION="1.11.0"
|
||||
ARG PIPER_PHONEMIZE_VERSION='1.0.0'
|
||||
ARG TARGETARCH
|
||||
ARG TARGETVARIANT
|
||||
|
||||
ENV BUILD_TYPE=${BUILD_TYPE}
|
||||
ENV EXTERNAL_GRPC_BACKENDS="huggingface-embeddings:/build/extra/grpc/huggingface/huggingface.py,autogptq:/build/extra/grpc/autogptq/autogptq.py,bark:/build/extra/grpc/bark/ttsbark.py,diffusers:/build/extra/grpc/diffusers/backend_diffusers.py,exllama:/build/extra/grpc/exllama/exllama.py"
|
||||
ENV GALLERIES='[{"name":"model-gallery", "url":"github:go-skynet/model-gallery/index.yaml"}, {"url": "github:go-skynet/model-gallery/huggingface.yaml","name":"huggingface"}]'
|
||||
ARG GO_TAGS="stablediffusion tts"
|
||||
|
||||
RUN apt-get update && \
|
||||
apt-get install -y ca-certificates cmake curl patch pip
|
||||
|
||||
# Use the variables in subsequent instructions
|
||||
RUN echo "Target Architecture: $TARGETARCH"
|
||||
RUN echo "Target Variant: $TARGETVARIANT"
|
||||
|
||||
# CuBLAS requirements
|
||||
RUN if [ "${BUILD_TYPE}" = "cublas" ]; then \
|
||||
apt-get install -y software-properties-common && \
|
||||
apt-add-repository contrib && \
|
||||
curl -O https://developer.download.nvidia.com/compute/cuda/repos/debian11/x86_64/cuda-keyring_1.0-1_all.deb && \
|
||||
dpkg -i cuda-keyring_1.0-1_all.deb && \
|
||||
rm -f cuda-keyring_1.0-1_all.deb && \
|
||||
apt-get update && \
|
||||
apt-get install -y cuda-nvcc-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} libcublas-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} libcusparse-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} libcusolver-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
|
||||
; fi
|
||||
ENV PATH /usr/local/cuda/bin:${PATH}
|
||||
|
||||
# Extras requirements
|
||||
COPY extra/requirements.txt /build/extra/requirements.txt
|
||||
ENV PATH="/root/.cargo/bin:${PATH}"
|
||||
RUN pip install --upgrade pip
|
||||
RUN curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh -s -- -y
|
||||
RUN if [ "${TARGETARCH}" = "amd64" ]; then \
|
||||
pip install git+https://github.com/suno-ai/bark.git diffusers invisible_watermark transformers accelerate safetensors;\
|
||||
fi
|
||||
RUN if [ "${BUILD_TYPE}" = "cublas" ] && [ "${TARGETARCH}" = "amd64" ]; then \
|
||||
pip install torch && pip install auto-gptq https://github.com/jllllll/exllama/releases/download/0.0.10/exllama-0.0.10+cu${CUDA_MAJOR_VERSION}${CUDA_MINOR_VERSION}-cp39-cp39-linux_x86_64.whl;\
|
||||
fi
|
||||
RUN pip install -r /build/extra/requirements.txt && rm -rf /build/extra/requirements.txt
|
||||
|
||||
WORKDIR /build
|
||||
RUN apt-get update && apt-get install -y cmake curl libgomp1 libopenblas-dev libopenblas-base libopencv-dev libopencv-core-dev libopencv-core4.5 ca-certificates
|
||||
|
||||
# OpenBLAS requirements
|
||||
RUN apt-get install -y libopenblas-dev
|
||||
|
||||
# Stable Diffusion requirements
|
||||
RUN apt-get install -y libopencv-dev && \
|
||||
ln -s /usr/include/opencv4/opencv2 /usr/include/opencv2
|
||||
|
||||
|
||||
# piper requirements
|
||||
# Use pre-compiled Piper phonemization library (includes onnxruntime)
|
||||
#RUN if echo "${GO_TAGS}" | grep -q "tts"; then \
|
||||
RUN test -n "$TARGETARCH" \
|
||||
|| (echo 'warn: missing $TARGETARCH, either set this `ARG` manually, or run using `docker buildkit`')
|
||||
|
||||
RUN curl -L "https://github.com/gabime/spdlog/archive/refs/tags/v${SPDLOG_VERSION}.tar.gz" | \
|
||||
tar -xzvf - && \
|
||||
mkdir -p "spdlog-${SPDLOG_VERSION}/build" && \
|
||||
cd "spdlog-${SPDLOG_VERSION}/build" && \
|
||||
cmake .. && \
|
||||
make -j8 && \
|
||||
cmake --install . --prefix /usr && mkdir -p "lib/Linux-$(uname -m)" && \
|
||||
cd /build && \
|
||||
mkdir -p "lib/Linux-$(uname -m)/piper_phonemize" && \
|
||||
curl -L "https://github.com/rhasspy/piper-phonemize/releases/download/v${PIPER_PHONEMIZE_VERSION}/libpiper_phonemize-${TARGETARCH:-$(go env GOARCH)}${TARGETVARIANT}.tar.gz" | \
|
||||
tar -C "lib/Linux-$(uname -m)/piper_phonemize" -xzvf - && ls -liah /build/lib/Linux-$(uname -m)/piper_phonemize/ && \
|
||||
cp -rfv /build/lib/Linux-$(uname -m)/piper_phonemize/lib/. /usr/lib/ && \
|
||||
ln -s /usr/lib/libpiper_phonemize.so /usr/lib/libpiper_phonemize.so.1 && \
|
||||
cp -rfv /build/lib/Linux-$(uname -m)/piper_phonemize/include/. /usr/include/
|
||||
# \
|
||||
# ; fi
|
||||
|
||||
###################################
|
||||
###################################
|
||||
|
||||
FROM requirements as builder
|
||||
|
||||
ARG GO_TAGS="stablediffusion tts"
|
||||
|
||||
ENV GO_TAGS=${GO_TAGS}
|
||||
ENV NVIDIA_DRIVER_CAPABILITIES=compute,utility
|
||||
ENV NVIDIA_REQUIRE_CUDA="cuda>=${CUDA_MAJOR_VERSION}.0"
|
||||
ENV NVIDIA_VISIBLE_DEVICES=all
|
||||
|
||||
WORKDIR /build
|
||||
|
||||
COPY Makefile .
|
||||
RUN make get-sources
|
||||
COPY go.mod .
|
||||
RUN make prepare
|
||||
COPY . .
|
||||
RUN ln -s /usr/include/opencv4/opencv2/ /usr/include/opencv2
|
||||
RUN make build
|
||||
COPY .git .
|
||||
|
||||
RUN ESPEAK_DATA=/build/lib/Linux-$(uname -m)/piper_phonemize/lib/espeak-ng-data make build
|
||||
|
||||
###################################
|
||||
###################################
|
||||
|
||||
FROM requirements
|
||||
|
||||
ARG FFMPEG
|
||||
ARG BUILD_TYPE
|
||||
ARG TARGETARCH
|
||||
|
||||
ENV BUILD_TYPE=${BUILD_TYPE}
|
||||
ENV REBUILD=false
|
||||
ENV HEALTHCHECK_ENDPOINT=http://localhost:8080/readyz
|
||||
|
||||
# Add FFmpeg
|
||||
RUN if [ "${FFMPEG}" = "true" ]; then \
|
||||
apt-get install -y ffmpeg \
|
||||
; fi
|
||||
|
||||
WORKDIR /build
|
||||
|
||||
# we start fresh & re-copy all assets because `make build` does not clean up nicely after itself
|
||||
# so when `entrypoint.sh` runs `make build` again (which it does by default), the build would fail
|
||||
# see https://github.com/go-skynet/LocalAI/pull/658#discussion_r1241971626 and
|
||||
# https://github.com/go-skynet/LocalAI/pull/434
|
||||
COPY . .
|
||||
RUN make prepare-sources
|
||||
COPY --from=builder /build/local-ai ./
|
||||
# To resolve exllama import error
|
||||
RUN if [ "${BUILD_TYPE}" = "cublas" ] && [ "${TARGETARCH:-$(go env GOARCH)}" = "amd64" ]; then \
|
||||
cp -rfv /usr/local/lib/python3.9/dist-packages/exllama extra/grpc/exllama/;\
|
||||
fi
|
||||
# Define the health check command
|
||||
HEALTHCHECK --interval=30s --timeout=360s --retries=10 \
|
||||
HEALTHCHECK --interval=1m --timeout=10m --retries=10 \
|
||||
CMD curl -f $HEALTHCHECK_ENDPOINT || exit 1
|
||||
|
||||
EXPOSE 8080
|
||||
ENTRYPOINT [ "/build/entrypoint.sh" ]
|
||||
|
||||
@@ -1,20 +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 libgomp1 libopenblas-dev libopenblas-base libopencv-dev libopencv-core-dev libopencv-core4.5
|
||||
RUN ln -s /usr/include/opencv4/opencv2/ /usr/include/opencv2
|
||||
COPY . .
|
||||
RUN make build
|
||||
|
||||
FROM debian:$DEBIAN_VERSION
|
||||
COPY --from=builder /build/local-ai /usr/bin/local-ai
|
||||
RUN apt-get update && apt-get install -y ca-certificates curl
|
||||
ENV HEALTHCHECK_ENDPOINT=http://localhost:8080/readyz
|
||||
# Define the health check command
|
||||
HEALTHCHECK --interval=30s --timeout=360s --retries=10 \
|
||||
CMD curl -f $HEALTHCHECK_ENDPOINT || exit 1
|
||||
EXPOSE 8080
|
||||
ENTRYPOINT [ "/usr/bin/local-ai" ]
|
||||
2
LICENSE
2
LICENSE
@@ -1,6 +1,6 @@
|
||||
MIT License
|
||||
|
||||
Copyright (c) 2023 go-skynet authors
|
||||
Copyright (c) 2023 Ettore Di Giacinto
|
||||
|
||||
Permission is hereby granted, free of charge, to any person obtaining a copy
|
||||
of this software and associated documentation files (the "Software"), to deal
|
||||
|
||||
352
Makefile
352
Makefile
@@ -3,23 +3,54 @@ GOTEST=$(GOCMD) test
|
||||
GOVET=$(GOCMD) vet
|
||||
BINARY_NAME=local-ai
|
||||
|
||||
GOLLAMA_VERSION?=fbec625895ba0c458f783b62c8569135c5e80d79
|
||||
# llama.cpp versions
|
||||
GOLLAMA_VERSION?=bf63302a2be787674e6ca4227a8aaeb95a8eb6b1
|
||||
|
||||
GOLLAMA_STABLE_VERSION?=50cee7712066d9e38306eccadcfbb44ea87df4b7
|
||||
|
||||
# gpt4all version
|
||||
GPT4ALL_REPO?=https://github.com/nomic-ai/gpt4all
|
||||
GPT4ALL_VERSION?=73db20ba85fbbdc66a56e2619394c0eea40dc72b
|
||||
GOGGMLTRANSFORMERS_VERSION?=4f18e5eb75089dc1fc8f1c955bb8f73d18520a46
|
||||
GPT4ALL_VERSION?=27a8b020c36b0df8f8b82a252d261cda47cf44b8
|
||||
|
||||
# go-ggml-transformers version
|
||||
GOGGMLTRANSFORMERS_VERSION?=ffb09d7dd71e2cbc6c5d7d05357d230eea6f369a
|
||||
|
||||
# go-rwkv version
|
||||
RWKV_REPO?=https://github.com/donomii/go-rwkv.cpp
|
||||
RWKV_VERSION?=07166da10cb2a9e8854395a4f210464dcea76e47
|
||||
WHISPER_CPP_VERSION?=9b926844e3ae0ca6a0d13573b2e0349be1a4b573
|
||||
BERT_VERSION?=cea1ed76a7f48ef386a8e369f6c82c48cdf2d551
|
||||
BLOOMZ_VERSION?=e9366e82abdfe70565644fbfae9651976714efd1
|
||||
BUILD_TYPE?=
|
||||
RWKV_VERSION?=c898cd0f62df8f2a7830e53d1d513bef4f6f792b
|
||||
|
||||
# whisper.cpp version
|
||||
WHISPER_CPP_VERSION?=85ed71aaec8e0612a84c0b67804bde75aa75a273
|
||||
|
||||
# bert.cpp version
|
||||
BERT_VERSION?=6abe312cded14042f6b7c3cd8edf082713334a4d
|
||||
|
||||
# go-piper version
|
||||
PIPER_VERSION?=56b8a81b4760a6fbee1a82e62f007ae7e8f010a7
|
||||
|
||||
# go-bloomz version
|
||||
BLOOMZ_VERSION?=1834e77b83faafe912ad4092ccf7f77937349e2f
|
||||
|
||||
# stablediffusion version
|
||||
STABLEDIFFUSION_VERSION?=d89260f598afb809279bc72aa0107b4292587632
|
||||
|
||||
# Go-ggllm
|
||||
GOGGLLM_VERSION?=862477d16eefb0805261c19c9b0d053e3b2b684b
|
||||
|
||||
export BUILD_TYPE?=
|
||||
CGO_LDFLAGS?=
|
||||
CUDA_LIBPATH?=/usr/local/cuda/lib64/
|
||||
STABLEDIFFUSION_VERSION?=c0748eca3642d58bcf9521108bcee46959c647dc
|
||||
GO_TAGS?=
|
||||
BUILD_ID?=git
|
||||
LD_FLAGS=?=
|
||||
|
||||
VERSION?=$(shell git describe --always --tags || echo "dev" )
|
||||
# go tool nm ./local-ai | grep Commit
|
||||
LD_FLAGS?=
|
||||
override LD_FLAGS += -X "github.com/go-skynet/LocalAI/internal.Version=$(VERSION)"
|
||||
override LD_FLAGS += -X "github.com/go-skynet/LocalAI/internal.Commit=$(shell git rev-parse HEAD)"
|
||||
|
||||
OPTIONAL_TARGETS?=
|
||||
ESPEAK_DATA?=
|
||||
|
||||
OS := $(shell uname -s)
|
||||
ARCH := $(shell uname -m)
|
||||
@@ -29,8 +60,14 @@ WHITE := $(shell tput -Txterm setaf 7)
|
||||
CYAN := $(shell tput -Txterm setaf 6)
|
||||
RESET := $(shell tput -Txterm sgr0)
|
||||
|
||||
C_INCLUDE_PATH=$(shell pwd)/go-llama:$(shell pwd)/go-stable-diffusion/:$(shell pwd)/gpt4all/gpt4all-bindings/golang/:$(shell pwd)/go-ggml-transformers:$(shell pwd)/go-rwkv:$(shell pwd)/whisper.cpp:$(shell pwd)/go-bert:$(shell pwd)/bloomz
|
||||
LIBRARY_PATH=$(shell pwd)/go-llama:$(shell pwd)/go-stable-diffusion/:$(shell pwd)/gpt4all/gpt4all-bindings/golang/:$(shell pwd)/go-ggml-transformers:$(shell pwd)/go-rwkv:$(shell pwd)/whisper.cpp:$(shell pwd)/go-bert:$(shell pwd)/bloomz
|
||||
ifndef UNAME_S
|
||||
UNAME_S := $(shell uname -s)
|
||||
endif
|
||||
|
||||
# workaround for rwkv.cpp
|
||||
ifeq ($(UNAME_S),Darwin)
|
||||
CGO_LDFLAGS += -lcblas -framework Accelerate
|
||||
endif
|
||||
|
||||
ifeq ($(BUILD_TYPE),openblas)
|
||||
CGO_LDFLAGS+=-lopenblas
|
||||
@@ -41,15 +78,33 @@ ifeq ($(BUILD_TYPE),cublas)
|
||||
export LLAMA_CUBLAS=1
|
||||
endif
|
||||
|
||||
ifeq ($(BUILD_TYPE),metal)
|
||||
CGO_LDFLAGS+=-framework Foundation -framework Metal -framework MetalKit -framework MetalPerformanceShaders
|
||||
export LLAMA_METAL=1
|
||||
endif
|
||||
|
||||
ifeq ($(BUILD_TYPE),clblas)
|
||||
CGO_LDFLAGS+=-lOpenCL -lclblast
|
||||
endif
|
||||
|
||||
# glibc-static or glibc-devel-static required
|
||||
ifeq ($(STATIC),true)
|
||||
LD_FLAGS=-linkmode external -extldflags -static
|
||||
endif
|
||||
|
||||
ifeq ($(GO_TAGS),stablediffusion)
|
||||
OPTIONAL_TARGETS+=go-stable-diffusion/libstablediffusion.a
|
||||
ifeq ($(findstring stablediffusion,$(GO_TAGS)),stablediffusion)
|
||||
# OPTIONAL_TARGETS+=go-stable-diffusion/libstablediffusion.a
|
||||
OPTIONAL_GRPC+=backend-assets/grpc/stablediffusion
|
||||
endif
|
||||
|
||||
ifeq ($(findstring tts,$(GO_TAGS)),tts)
|
||||
# OPTIONAL_TARGETS+=go-piper/libpiper_binding.a
|
||||
# OPTIONAL_TARGETS+=backend-assets/espeak-ng-data
|
||||
OPTIONAL_GRPC+=backend-assets/grpc/piper
|
||||
endif
|
||||
|
||||
GRPC_BACKENDS?=backend-assets/grpc/langchain-huggingface backend-assets/grpc/falcon-ggml backend-assets/grpc/bert-embeddings backend-assets/grpc/falcon backend-assets/grpc/bloomz backend-assets/grpc/llama backend-assets/grpc/llama-stable backend-assets/grpc/gpt4all backend-assets/grpc/dolly backend-assets/grpc/gpt2 backend-assets/grpc/gptj backend-assets/grpc/gptneox backend-assets/grpc/mpt backend-assets/grpc/replit backend-assets/grpc/starcoder backend-assets/grpc/rwkv backend-assets/grpc/whisper $(OPTIONAL_GRPC)
|
||||
|
||||
.PHONY: all test build vendor
|
||||
|
||||
all: help
|
||||
@@ -58,31 +113,24 @@ all: help
|
||||
gpt4all:
|
||||
git clone --recurse-submodules $(GPT4ALL_REPO) gpt4all
|
||||
cd gpt4all && git checkout -b build $(GPT4ALL_VERSION) && git submodule update --init --recursive --depth 1
|
||||
# This is hackish, but needed as both go-llama and go-gpt4allj have their own version of ggml..
|
||||
@find ./gpt4all -type f -name "*.c" -exec sed -i'' -e 's/ggml_/ggml_gptj_/g' {} +
|
||||
@find ./gpt4all -type f -name "*.cpp" -exec sed -i'' -e 's/ggml_/ggml_gptj_/g' {} +
|
||||
@find ./gpt4all -type f -name "*.h" -exec sed -i'' -e 's/ggml_/ggml_gptj_/g' {} +
|
||||
@find ./gpt4all -type f -name "*.cpp" -exec sed -i'' -e 's/gpt_/gptj_/g' {} +
|
||||
@find ./gpt4all -type f -name "*.h" -exec sed -i'' -e 's/gpt_/gptj_/g' {} +
|
||||
@find ./gpt4all -type f -name "*.h" -exec sed -i'' -e 's/set_console_color/set_gptj_console_color/g' {} +
|
||||
@find ./gpt4all -type f -name "*.cpp" -exec sed -i'' -e 's/set_console_color/set_gptj_console_color/g' {} +
|
||||
@find ./gpt4all -type f -name "*.cpp" -exec sed -i'' -e 's/llama_/gptjllama_/g' {} +
|
||||
@find ./gpt4all -type f -name "*.go" -exec sed -i'' -e 's/llama_/gptjllama_/g' {} +
|
||||
@find ./gpt4all -type f -name "*.h" -exec sed -i'' -e 's/llama_/gptjllama_/g' {} +
|
||||
@find ./gpt4all -type f -name "*.txt" -exec sed -i'' -e 's/llama_/gptjllama_/g' {} +
|
||||
@find ./gpt4all -type f -name "*.cpp" -exec sed -i'' -e 's/json_/json_gptj_/g' {} +
|
||||
@find ./gpt4all -type f -name "*.cpp" -exec sed -i'' -e 's/void replace/void json_gptj_replace/g' {} +
|
||||
@find ./gpt4all -type f -name "*.cpp" -exec sed -i'' -e 's/::replace/::json_gptj_replace/g' {} +
|
||||
@find ./gpt4all -type f -name "*.cpp" -exec sed -i'' -e 's/regex_escape/gpt4allregex_escape/g' {} +
|
||||
mv ./gpt4all/gpt4all-backend/llama.cpp/llama_util.h ./gpt4all/gpt4all-backend/llama.cpp/gptjllama_util.h
|
||||
|
||||
## go-ggllm
|
||||
go-ggllm:
|
||||
git clone --recurse-submodules https://github.com/mudler/go-ggllm.cpp go-ggllm
|
||||
cd go-ggllm && git checkout -b build $(GOGGLLM_VERSION) && git submodule update --init --recursive --depth 1
|
||||
|
||||
go-ggllm/libggllm.a: go-ggllm
|
||||
$(MAKE) -C go-ggllm BUILD_TYPE=$(BUILD_TYPE) libggllm.a
|
||||
|
||||
## go-piper
|
||||
go-piper:
|
||||
git clone --recurse-submodules https://github.com/mudler/go-piper go-piper
|
||||
cd go-piper && git checkout -b build $(PIPER_VERSION) && git submodule update --init --recursive --depth 1
|
||||
|
||||
## BERT embeddings
|
||||
go-bert:
|
||||
git clone --recurse-submodules https://github.com/go-skynet/go-bert.cpp go-bert
|
||||
cd go-bert && git checkout -b build $(BERT_VERSION) && git submodule update --init --recursive --depth 1
|
||||
@find ./go-bert -type f -name "*.c" -exec sed -i'' -e 's/ggml_/ggml_bert_/g' {} +
|
||||
@find ./go-bert -type f -name "*.cpp" -exec sed -i'' -e 's/ggml_/ggml_bert_/g' {} +
|
||||
@find ./go-bert -type f -name "*.h" -exec sed -i'' -e 's/ggml_/ggml_bert_/g' {} +
|
||||
|
||||
## stable diffusion
|
||||
go-stable-diffusion:
|
||||
@@ -96,21 +144,14 @@ go-stable-diffusion/libstablediffusion.a:
|
||||
go-rwkv:
|
||||
git clone --recurse-submodules $(RWKV_REPO) go-rwkv
|
||||
cd go-rwkv && git checkout -b build $(RWKV_VERSION) && git submodule update --init --recursive --depth 1
|
||||
@find ./go-rwkv -type f -name "*.c" -exec sed -i'' -e 's/ggml_/ggml_rwkv_/g' {} +
|
||||
@find ./go-rwkv -type f -name "*.cpp" -exec sed -i'' -e 's/ggml_/ggml_rwkv_/g' {} +
|
||||
@find ./go-rwkv -type f -name "*.h" -exec sed -i'' -e 's/ggml_/ggml_rwkv_/g' {} +
|
||||
|
||||
go-rwkv/librwkv.a: go-rwkv
|
||||
cd go-rwkv && cd rwkv.cpp && cmake . -DRWKV_BUILD_SHARED_LIBRARY=OFF && cmake --build . && cp librwkv.a .. && cp ggml/src/libggml.a ..
|
||||
cd go-rwkv && cd rwkv.cpp && cmake . -DRWKV_BUILD_SHARED_LIBRARY=OFF && cmake --build . && cp librwkv.a ..
|
||||
|
||||
## bloomz
|
||||
bloomz:
|
||||
git clone --recurse-submodules https://github.com/go-skynet/bloomz.cpp bloomz
|
||||
@find ./bloomz -type f -name "*.c" -exec sed -i'' -e 's/ggml_/ggml_bloomz_/g' {} +
|
||||
@find ./bloomz -type f -name "*.cpp" -exec sed -i'' -e 's/ggml_/ggml_bloomz_/g' {} +
|
||||
@find ./bloomz -type f -name "*.h" -exec sed -i'' -e 's/ggml_/ggml_bloomz_/g' {} +
|
||||
@find ./bloomz -type f -name "*.cpp" -exec sed -i'' -e 's/gpt_/gpt_bloomz_/g' {} +
|
||||
@find ./bloomz -type f -name "*.h" -exec sed -i'' -e 's/gpt_/gpt_bloomz_/g' {} +
|
||||
cd bloomz && git checkout -b build $(BLOOMZ_VERSION) && git submodule update --init --recursive --depth 1
|
||||
|
||||
bloomz/libbloomz.a: bloomz
|
||||
cd bloomz && make libbloomz.a
|
||||
@@ -118,34 +159,35 @@ bloomz/libbloomz.a: bloomz
|
||||
go-bert/libgobert.a: go-bert
|
||||
$(MAKE) -C go-bert libgobert.a
|
||||
|
||||
backend-assets/gpt4all: gpt4all/gpt4all-bindings/golang/libgpt4all.a
|
||||
mkdir -p backend-assets/gpt4all
|
||||
@cp gpt4all/gpt4all-bindings/golang/buildllm/*.so backend-assets/gpt4all/ || true
|
||||
@cp gpt4all/gpt4all-bindings/golang/buildllm/*.dylib backend-assets/gpt4all/ || true
|
||||
@cp gpt4all/gpt4all-bindings/golang/buildllm/*.dll backend-assets/gpt4all/ || true
|
||||
|
||||
backend-assets/espeak-ng-data:
|
||||
mkdir -p backend-assets/espeak-ng-data
|
||||
ifdef ESPEAK_DATA
|
||||
@cp -rf $(ESPEAK_DATA)/. backend-assets/espeak-ng-data
|
||||
else
|
||||
@echo "ESPEAK_DATA not set, skipping tts. Note that this will break the tts functionality."
|
||||
@touch backend-assets/espeak-ng-data/keep
|
||||
endif
|
||||
|
||||
gpt4all/gpt4all-bindings/golang/libgpt4all.a: gpt4all
|
||||
$(MAKE) -C gpt4all/gpt4all-bindings/golang/ libgpt4all.a
|
||||
|
||||
## CEREBRAS GPT
|
||||
go-ggml-transformers:
|
||||
go-ggml-transformers:
|
||||
git clone --recurse-submodules https://github.com/go-skynet/go-ggml-transformers.cpp go-ggml-transformers
|
||||
cd go-ggml-transformers && git checkout -b build $(GOGPT2_VERSION) && git submodule update --init --recursive --depth 1
|
||||
# This is hackish, but needed as both go-llama and go-gpt4allj have their own version of ggml..
|
||||
@find ./go-ggml-transformers -type f -name "*.c" -exec sed -i'' -e 's/ggml_/ggml_gpt2_/g' {} +
|
||||
@find ./go-ggml-transformers -type f -name "*.cpp" -exec sed -i'' -e 's/ggml_/ggml_gpt2_/g' {} +
|
||||
@find ./go-ggml-transformers -type f -name "*.h" -exec sed -i'' -e 's/ggml_/ggml_gpt2_/g' {} +
|
||||
@find ./go-ggml-transformers -type f -name "*.cpp" -exec sed -i'' -e 's/gpt_print_usage/gpt2_print_usage/g' {} +
|
||||
@find ./go-ggml-transformers -type f -name "*.h" -exec sed -i'' -e 's/gpt_print_usage/gpt2_print_usage/g' {} +
|
||||
@find ./go-ggml-transformers -type f -name "*.cpp" -exec sed -i'' -e 's/gpt_params_parse/gpt2_params_parse/g' {} +
|
||||
@find ./go-ggml-transformers -type f -name "*.h" -exec sed -i'' -e 's/gpt_params_parse/gpt2_params_parse/g' {} +
|
||||
@find ./go-ggml-transformers -type f -name "*.cpp" -exec sed -i'' -e 's/gpt_random_prompt/gpt2_random_prompt/g' {} +
|
||||
@find ./go-ggml-transformers -type f -name "*.h" -exec sed -i'' -e 's/gpt_random_prompt/gpt2_random_prompt/g' {} +
|
||||
@find ./go-ggml-transformers -type f -name "*.cpp" -exec sed -i'' -e 's/json_/json_gpt2_/g' {} +
|
||||
|
||||
go-ggml-transformers/libtransformers.a: go-ggml-transformers
|
||||
$(MAKE) -C go-ggml-transformers libtransformers.a
|
||||
$(MAKE) -C go-ggml-transformers BUILD_TYPE=$(BUILD_TYPE) libtransformers.a
|
||||
|
||||
whisper.cpp:
|
||||
git clone https://github.com/ggerganov/whisper.cpp.git
|
||||
cd whisper.cpp && git checkout -b build $(WHISPER_CPP_VERSION) && git submodule update --init --recursive --depth 1
|
||||
@find ./whisper.cpp -type f -name "*.c" -exec sed -i'' -e 's/ggml_/ggml_whisper_/g' {} +
|
||||
@find ./whisper.cpp -type f -name "*.cpp" -exec sed -i'' -e 's/ggml_/ggml_whisper_/g' {} +
|
||||
@find ./whisper.cpp -type f -name "*.h" -exec sed -i'' -e 's/ggml_/ggml_whisper_/g' {} +
|
||||
|
||||
whisper.cpp/libwhisper.a: whisper.cpp
|
||||
cd whisper.cpp && make libwhisper.a
|
||||
@@ -154,11 +196,23 @@ 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
|
||||
go-llama-stable:
|
||||
git clone --recurse-submodules https://github.com/go-skynet/go-llama.cpp go-llama-stable
|
||||
cd go-llama-stable && git checkout -b build $(GOLLAMA_STABLE_VERSION) && git submodule update --init --recursive --depth 1
|
||||
|
||||
go-llama/libbinding.a: go-llama
|
||||
$(MAKE) -C go-llama BUILD_TYPE=$(BUILD_TYPE) libbinding.a
|
||||
|
||||
go-llama-stable/libbinding.a: go-llama-stable
|
||||
$(MAKE) -C go-llama-stable BUILD_TYPE=$(BUILD_TYPE) libbinding.a
|
||||
|
||||
go-piper/libpiper_binding.a:
|
||||
$(MAKE) -C go-piper libpiper_binding.a example/main
|
||||
|
||||
get-sources: go-llama go-llama-stable go-ggllm go-ggml-transformers gpt4all go-piper go-rwkv whisper.cpp go-bert bloomz go-stable-diffusion
|
||||
touch $@
|
||||
|
||||
replace:
|
||||
$(GOCMD) mod edit -replace github.com/go-skynet/go-llama.cpp=$(shell pwd)/go-llama
|
||||
$(GOCMD) mod edit -replace github.com/nomic-ai/gpt4all/gpt4all-bindings/golang=$(shell pwd)/gpt4all/gpt4all-bindings/golang
|
||||
$(GOCMD) mod edit -replace github.com/go-skynet/go-ggml-transformers.cpp=$(shell pwd)/go-ggml-transformers
|
||||
$(GOCMD) mod edit -replace github.com/donomii/go-rwkv.cpp=$(shell pwd)/go-rwkv
|
||||
@@ -166,13 +220,17 @@ replace:
|
||||
$(GOCMD) mod edit -replace github.com/go-skynet/go-bert.cpp=$(shell pwd)/go-bert
|
||||
$(GOCMD) mod edit -replace github.com/go-skynet/bloomz.cpp=$(shell pwd)/bloomz
|
||||
$(GOCMD) mod edit -replace github.com/mudler/go-stable-diffusion=$(shell pwd)/go-stable-diffusion
|
||||
$(GOCMD) mod edit -replace github.com/mudler/go-piper=$(shell pwd)/go-piper
|
||||
$(GOCMD) mod edit -replace github.com/mudler/go-ggllm.cpp=$(shell pwd)/go-ggllm
|
||||
|
||||
prepare-sources: go-llama go-ggml-transformers gpt4all go-rwkv whisper.cpp go-bert bloomz go-stable-diffusion replace
|
||||
prepare-sources: get-sources replace
|
||||
$(GOCMD) mod download
|
||||
|
||||
## GENERIC
|
||||
rebuild: ## Rebuilds the project
|
||||
$(GOCMD) clean -cache
|
||||
$(MAKE) -C go-llama clean
|
||||
$(MAKE) -C go-llama-stable clean
|
||||
$(MAKE) -C gpt4all/gpt4all-bindings/golang/ clean
|
||||
$(MAKE) -C go-ggml-transformers clean
|
||||
$(MAKE) -C go-rwkv clean
|
||||
@@ -180,40 +238,49 @@ rebuild: ## Rebuilds the project
|
||||
$(MAKE) -C go-stable-diffusion clean
|
||||
$(MAKE) -C go-bert clean
|
||||
$(MAKE) -C bloomz clean
|
||||
$(MAKE) -C go-piper clean
|
||||
$(MAKE) -C go-ggllm clean
|
||||
$(MAKE) build
|
||||
|
||||
prepare: prepare-sources gpt4all/gpt4all-bindings/golang/libgpt4all.a $(OPTIONAL_TARGETS) go-llama/libbinding.a go-bert/libgobert.a go-ggml-transformers/libtransformers.a go-rwkv/librwkv.a whisper.cpp/libwhisper.a bloomz/libbloomz.a ## Prepares for building
|
||||
prepare: prepare-sources $(OPTIONAL_TARGETS)
|
||||
touch $@
|
||||
|
||||
clean: ## Remove build related file
|
||||
rm -fr ./go-llama
|
||||
rm -rf ./gpt4all
|
||||
$(GOCMD) clean -cache
|
||||
rm -f prepare
|
||||
rm -rf ./go-llama
|
||||
rm -rf ./gpt4all
|
||||
rm -rf ./go-llama-stable
|
||||
rm -rf ./go-gpt2
|
||||
rm -rf ./go-stable-diffusion
|
||||
rm -rf ./go-ggml-transformers
|
||||
rm -rf ./backend-assets
|
||||
rm -rf ./go-rwkv
|
||||
rm -rf ./go-bert
|
||||
rm -rf ./bloomz
|
||||
rm -rf ./whisper.cpp
|
||||
rm -rf ./go-piper
|
||||
rm -rf ./go-ggllm
|
||||
rm -rf $(BINARY_NAME)
|
||||
rm -rf release/
|
||||
|
||||
## Build:
|
||||
|
||||
build: prepare ## Build the project
|
||||
build: grpcs prepare ## Build the project
|
||||
$(info ${GREEN}I local-ai build info:${RESET})
|
||||
$(info ${GREEN}I BUILD_TYPE: ${YELLOW}$(BUILD_TYPE)${RESET})
|
||||
$(info ${GREEN}I GO_TAGS: ${YELLOW}$(GO_TAGS)${RESET})
|
||||
CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=${C_INCLUDE_PATH} LIBRARY_PATH=${LIBRARY_PATH} $(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -x -o $(BINARY_NAME) ./
|
||||
$(info ${GREEN}I LD_FLAGS: ${YELLOW}$(LD_FLAGS)${RESET})
|
||||
|
||||
CGO_LDFLAGS="$(CGO_LDFLAGS)" $(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o $(BINARY_NAME) ./
|
||||
|
||||
dist: build
|
||||
mkdir -p release
|
||||
cp $(BINARY_NAME) release/$(BINARY_NAME)-$(BUILD_ID)-$(OS)-$(ARCH)
|
||||
|
||||
generic-build: ## Build the project using generic
|
||||
BUILD_TYPE="generic" $(MAKE) build
|
||||
|
||||
## Run
|
||||
run: prepare ## run local-ai
|
||||
CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=${C_INCLUDE_PATH} LIBRARY_PATH=${LIBRARY_PATH} $(GOCMD) run ./main.go
|
||||
CGO_LDFLAGS="$(CGO_LDFLAGS)" $(GOCMD) run ./
|
||||
|
||||
test-models/testmodel:
|
||||
mkdir test-models
|
||||
@@ -222,13 +289,49 @@ test-models/testmodel:
|
||||
wget https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-base.en.bin -O test-models/whisper-en
|
||||
wget https://huggingface.co/skeskinen/ggml/resolve/main/all-MiniLM-L6-v2/ggml-model-q4_0.bin -O test-models/bert
|
||||
wget https://cdn.openai.com/whisper/draft-20220913a/micro-machines.wav -O test-dir/audio.wav
|
||||
wget https://huggingface.co/imxcstar/rwkv-4-raven-ggml/resolve/main/RWKV-4-Raven-1B5-v11-Eng99%25-Other1%25-20230425-ctx4096-16_Q4_2.bin -O test-models/rwkv
|
||||
wget https://huggingface.co/mudler/rwkv-4-raven-1.5B-ggml/resolve/main/RWKV-4-Raven-1B5-v11-Eng99%2525-Other1%2525-20230425-ctx4096_Q4_0.bin -O test-models/rwkv
|
||||
wget https://raw.githubusercontent.com/saharNooby/rwkv.cpp/5eb8f09c146ea8124633ab041d9ea0b1f1db4459/rwkv/20B_tokenizer.json -O test-models/rwkv.tokenizer.json
|
||||
cp tests/models_fixtures/* test-models
|
||||
|
||||
test: prepare test-models/testmodel
|
||||
prepare-test: grpcs
|
||||
cp -rf backend-assets api
|
||||
cp tests/models_fixtures/* test-models
|
||||
C_INCLUDE_PATH=${C_INCLUDE_PATH} LIBRARY_PATH=${LIBRARY_PATH} TEST_DIR=$(abspath ./)/test-dir/ FIXTURES=$(abspath ./)/tests/fixtures CONFIG_FILE=$(abspath ./)/test-models/config.yaml MODELS_PATH=$(abspath ./)/test-models $(GOCMD) run github.com/onsi/ginkgo/v2/ginkgo --flakeAttempts 5 -v -r ./api ./pkg
|
||||
|
||||
test: prepare test-models/testmodel grpcs
|
||||
@echo 'Running tests'
|
||||
export GO_TAGS="tts stablediffusion"
|
||||
$(MAKE) prepare-test
|
||||
HUGGINGFACE_GRPC=$(abspath ./)/extra/grpc/huggingface/huggingface.py TEST_DIR=$(abspath ./)/test-dir/ FIXTURES=$(abspath ./)/tests/fixtures CONFIG_FILE=$(abspath ./)/test-models/config.yaml MODELS_PATH=$(abspath ./)/test-models \
|
||||
$(GOCMD) run github.com/onsi/ginkgo/v2/ginkgo --label-filter="!gpt4all && !llama && !llama-gguf" --flake-attempts 5 -v -r ./api ./pkg
|
||||
$(MAKE) test-gpt4all
|
||||
$(MAKE) test-llama
|
||||
$(MAKE) test-llama-gguf
|
||||
$(MAKE) test-tts
|
||||
$(MAKE) test-stablediffusion
|
||||
|
||||
test-gpt4all: prepare-test
|
||||
TEST_DIR=$(abspath ./)/test-dir/ FIXTURES=$(abspath ./)/tests/fixtures CONFIG_FILE=$(abspath ./)/test-models/config.yaml MODELS_PATH=$(abspath ./)/test-models \
|
||||
$(GOCMD) run github.com/onsi/ginkgo/v2/ginkgo --label-filter="gpt4all" --flake-attempts 5 -v -r ./api ./pkg
|
||||
|
||||
test-llama: prepare-test
|
||||
TEST_DIR=$(abspath ./)/test-dir/ FIXTURES=$(abspath ./)/tests/fixtures CONFIG_FILE=$(abspath ./)/test-models/config.yaml MODELS_PATH=$(abspath ./)/test-models \
|
||||
$(GOCMD) run github.com/onsi/ginkgo/v2/ginkgo --label-filter="llama" --flake-attempts 5 -v -r ./api ./pkg
|
||||
|
||||
test-llama-gguf: prepare-test
|
||||
TEST_DIR=$(abspath ./)/test-dir/ FIXTURES=$(abspath ./)/tests/fixtures CONFIG_FILE=$(abspath ./)/test-models/config.yaml MODELS_PATH=$(abspath ./)/test-models \
|
||||
$(GOCMD) run github.com/onsi/ginkgo/v2/ginkgo --label-filter="llama-gguf" --flake-attempts 5 -v -r ./api ./pkg
|
||||
|
||||
test-tts: prepare-test
|
||||
TEST_DIR=$(abspath ./)/test-dir/ FIXTURES=$(abspath ./)/tests/fixtures CONFIG_FILE=$(abspath ./)/test-models/config.yaml MODELS_PATH=$(abspath ./)/test-models \
|
||||
$(GOCMD) run github.com/onsi/ginkgo/v2/ginkgo --label-filter="tts" --flake-attempts 1 -v -r ./api ./pkg
|
||||
|
||||
test-stablediffusion: prepare-test
|
||||
TEST_DIR=$(abspath ./)/test-dir/ FIXTURES=$(abspath ./)/tests/fixtures CONFIG_FILE=$(abspath ./)/test-models/config.yaml MODELS_PATH=$(abspath ./)/test-models \
|
||||
$(GOCMD) run github.com/onsi/ginkgo/v2/ginkgo --label-filter="stablediffusion" --flake-attempts 1 -v -r ./api ./pkg
|
||||
|
||||
test-container:
|
||||
docker build --target requirements -t local-ai-test-container .
|
||||
docker run -ti --rm --entrypoint /bin/bash -ti -v $(abspath ./):/build local-ai-test-container
|
||||
|
||||
## Help:
|
||||
help: ## Show this help.
|
||||
@@ -241,3 +344,104 @@ help: ## Show this help.
|
||||
if (/^[a-zA-Z_-]+:.*?##.*$$/) {printf " ${YELLOW}%-20s${GREEN}%s${RESET}\n", $$1, $$2} \
|
||||
else if (/^## .*$$/) {printf " ${CYAN}%s${RESET}\n", substr($$1,4)} \
|
||||
}' $(MAKEFILE_LIST)
|
||||
|
||||
protogen: protogen-go protogen-python
|
||||
|
||||
protogen-go:
|
||||
protoc --go_out=. --go_opt=paths=source_relative --go-grpc_out=. --go-grpc_opt=paths=source_relative \
|
||||
pkg/grpc/proto/backend.proto
|
||||
|
||||
protogen-python:
|
||||
python3 -m grpc_tools.protoc -Ipkg/grpc/proto/ --python_out=extra/grpc/huggingface/ --grpc_python_out=extra/grpc/huggingface/ pkg/grpc/proto/backend.proto
|
||||
python3 -m grpc_tools.protoc -Ipkg/grpc/proto/ --python_out=extra/grpc/autogptq/ --grpc_python_out=extra/grpc/autogptq/ pkg/grpc/proto/backend.proto
|
||||
python3 -m grpc_tools.protoc -Ipkg/grpc/proto/ --python_out=extra/grpc/exllama/ --grpc_python_out=extra/grpc/exllama/ pkg/grpc/proto/backend.proto
|
||||
python3 -m grpc_tools.protoc -Ipkg/grpc/proto/ --python_out=extra/grpc/bark/ --grpc_python_out=extra/grpc/bark/ pkg/grpc/proto/backend.proto
|
||||
python3 -m grpc_tools.protoc -Ipkg/grpc/proto/ --python_out=extra/grpc/diffusers/ --grpc_python_out=extra/grpc/diffusers/ pkg/grpc/proto/backend.proto
|
||||
|
||||
## GRPC
|
||||
|
||||
backend-assets/grpc:
|
||||
mkdir -p backend-assets/grpc
|
||||
|
||||
backend-assets/grpc/falcon: backend-assets/grpc go-ggllm/libggllm.a
|
||||
CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(shell pwd)/go-ggllm LIBRARY_PATH=$(shell pwd)/go-ggllm \
|
||||
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/falcon ./cmd/grpc/falcon/
|
||||
|
||||
backend-assets/grpc/llama: backend-assets/grpc go-llama/libbinding.a
|
||||
$(GOCMD) mod edit -replace github.com/go-skynet/go-llama.cpp=$(shell pwd)/go-llama
|
||||
CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(shell pwd)/go-llama LIBRARY_PATH=$(shell pwd)/go-llama \
|
||||
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/llama ./cmd/grpc/llama/
|
||||
# TODO: every binary should have its own folder instead, so can have different metal implementations
|
||||
ifeq ($(BUILD_TYPE),metal)
|
||||
cp go-llama/build/bin/ggml-metal.metal backend-assets/grpc/
|
||||
endif
|
||||
|
||||
backend-assets/grpc/llama-stable: backend-assets/grpc go-llama-stable/libbinding.a
|
||||
$(GOCMD) mod edit -replace github.com/go-skynet/go-llama.cpp=$(shell pwd)/go-llama-stable
|
||||
CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(shell pwd)/go-llama-stable LIBRARY_PATH=$(shell pwd)/go-llama \
|
||||
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/llama-stable ./cmd/grpc/llama-stable/
|
||||
|
||||
backend-assets/grpc/gpt4all: backend-assets/grpc backend-assets/gpt4all gpt4all/gpt4all-bindings/golang/libgpt4all.a
|
||||
CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(shell pwd)/gpt4all/gpt4all-bindings/golang/ LIBRARY_PATH=$(shell pwd)/gpt4all/gpt4all-bindings/golang/ \
|
||||
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/gpt4all ./cmd/grpc/gpt4all/
|
||||
|
||||
backend-assets/grpc/dolly: backend-assets/grpc go-ggml-transformers/libtransformers.a
|
||||
CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(shell pwd)/go-ggml-transformers LIBRARY_PATH=$(shell pwd)/go-ggml-transformers \
|
||||
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/dolly ./cmd/grpc/dolly/
|
||||
|
||||
backend-assets/grpc/gpt2: backend-assets/grpc go-ggml-transformers/libtransformers.a
|
||||
CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(shell pwd)/go-ggml-transformers LIBRARY_PATH=$(shell pwd)/go-ggml-transformers \
|
||||
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/gpt2 ./cmd/grpc/gpt2/
|
||||
|
||||
backend-assets/grpc/gptj: backend-assets/grpc go-ggml-transformers/libtransformers.a
|
||||
CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(shell pwd)/go-ggml-transformers LIBRARY_PATH=$(shell pwd)/go-ggml-transformers \
|
||||
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/gptj ./cmd/grpc/gptj/
|
||||
|
||||
backend-assets/grpc/gptneox: backend-assets/grpc go-ggml-transformers/libtransformers.a
|
||||
CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(shell pwd)/go-ggml-transformers LIBRARY_PATH=$(shell pwd)/go-ggml-transformers \
|
||||
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/gptneox ./cmd/grpc/gptneox/
|
||||
|
||||
backend-assets/grpc/mpt: backend-assets/grpc go-ggml-transformers/libtransformers.a
|
||||
CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(shell pwd)/go-ggml-transformers LIBRARY_PATH=$(shell pwd)/go-ggml-transformers \
|
||||
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/mpt ./cmd/grpc/mpt/
|
||||
|
||||
backend-assets/grpc/replit: backend-assets/grpc go-ggml-transformers/libtransformers.a
|
||||
CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(shell pwd)/go-ggml-transformers LIBRARY_PATH=$(shell pwd)/go-ggml-transformers \
|
||||
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/replit ./cmd/grpc/replit/
|
||||
|
||||
backend-assets/grpc/falcon-ggml: backend-assets/grpc go-ggml-transformers/libtransformers.a
|
||||
CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(shell pwd)/go-ggml-transformers LIBRARY_PATH=$(shell pwd)/go-ggml-transformers \
|
||||
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/falcon-ggml ./cmd/grpc/falcon-ggml/
|
||||
|
||||
backend-assets/grpc/starcoder: backend-assets/grpc go-ggml-transformers/libtransformers.a
|
||||
CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(shell pwd)/go-ggml-transformers LIBRARY_PATH=$(shell pwd)/go-ggml-transformers \
|
||||
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/starcoder ./cmd/grpc/starcoder/
|
||||
|
||||
backend-assets/grpc/rwkv: backend-assets/grpc go-rwkv/librwkv.a
|
||||
CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(shell pwd)/go-rwkv LIBRARY_PATH=$(shell pwd)/go-rwkv \
|
||||
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/rwkv ./cmd/grpc/rwkv/
|
||||
|
||||
backend-assets/grpc/bloomz: backend-assets/grpc bloomz/libbloomz.a
|
||||
CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(shell pwd)/bloomz LIBRARY_PATH=$(shell pwd)/bloomz \
|
||||
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/bloomz ./cmd/grpc/bloomz/
|
||||
|
||||
backend-assets/grpc/bert-embeddings: backend-assets/grpc go-bert/libgobert.a
|
||||
CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(shell pwd)/go-bert LIBRARY_PATH=$(shell pwd)/go-bert \
|
||||
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/bert-embeddings ./cmd/grpc/bert-embeddings/
|
||||
|
||||
backend-assets/grpc/langchain-huggingface: backend-assets/grpc
|
||||
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/langchain-huggingface ./cmd/grpc/langchain-huggingface/
|
||||
|
||||
backend-assets/grpc/stablediffusion: backend-assets/grpc go-stable-diffusion/libstablediffusion.a
|
||||
CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(shell pwd)/go-stable-diffusion/ LIBRARY_PATH=$(shell pwd)/go-stable-diffusion/ \
|
||||
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/stablediffusion ./cmd/grpc/stablediffusion/
|
||||
|
||||
backend-assets/grpc/piper: backend-assets/grpc backend-assets/espeak-ng-data go-piper/libpiper_binding.a
|
||||
CGO_LDFLAGS="$(CGO_LDFLAGS)" LIBRARY_PATH=$(shell pwd)/go-piper \
|
||||
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/piper ./cmd/grpc/piper/
|
||||
|
||||
backend-assets/grpc/whisper: backend-assets/grpc whisper.cpp/libwhisper.a
|
||||
CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(shell pwd)/whisper.cpp LIBRARY_PATH=$(shell pwd)/whisper.cpp \
|
||||
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/whisper ./cmd/grpc/whisper/
|
||||
|
||||
grpcs: prepare $(GRPC_BACKENDS)
|
||||
|
||||
208
api/api.go
208
api/api.go
@@ -2,6 +2,16 @@ package api
|
||||
|
||||
import (
|
||||
"errors"
|
||||
"fmt"
|
||||
"strings"
|
||||
|
||||
config "github.com/go-skynet/LocalAI/api/config"
|
||||
"github.com/go-skynet/LocalAI/api/localai"
|
||||
"github.com/go-skynet/LocalAI/api/openai"
|
||||
"github.com/go-skynet/LocalAI/api/options"
|
||||
"github.com/go-skynet/LocalAI/api/schema"
|
||||
"github.com/go-skynet/LocalAI/internal"
|
||||
"github.com/go-skynet/LocalAI/pkg/assets"
|
||||
|
||||
"github.com/gofiber/fiber/v2"
|
||||
"github.com/gofiber/fiber/v2/middleware/cors"
|
||||
@@ -11,18 +21,77 @@ import (
|
||||
"github.com/rs/zerolog/log"
|
||||
)
|
||||
|
||||
func App(opts ...AppOption) *fiber.App {
|
||||
options := newOptions(opts...)
|
||||
func Startup(opts ...options.AppOption) (*options.Option, *config.ConfigLoader, error) {
|
||||
options := options.NewOptions(opts...)
|
||||
|
||||
zerolog.SetGlobalLevel(zerolog.InfoLevel)
|
||||
if options.debug {
|
||||
if options.Debug {
|
||||
zerolog.SetGlobalLevel(zerolog.DebugLevel)
|
||||
}
|
||||
|
||||
log.Info().Msgf("Starting LocalAI using %d threads, with models path: %s", options.Threads, options.Loader.ModelPath)
|
||||
log.Info().Msgf("LocalAI version: %s", internal.PrintableVersion())
|
||||
|
||||
cl := config.NewConfigLoader()
|
||||
if err := cl.LoadConfigs(options.Loader.ModelPath); err != nil {
|
||||
log.Error().Msgf("error loading config files: %s", err.Error())
|
||||
}
|
||||
|
||||
if options.ConfigFile != "" {
|
||||
if err := cl.LoadConfigFile(options.ConfigFile); err != nil {
|
||||
log.Error().Msgf("error loading config file: %s", err.Error())
|
||||
}
|
||||
}
|
||||
|
||||
if options.Debug {
|
||||
for _, v := range cl.ListConfigs() {
|
||||
cfg, _ := cl.GetConfig(v)
|
||||
log.Debug().Msgf("Model: %s (config: %+v)", v, cfg)
|
||||
}
|
||||
}
|
||||
|
||||
if options.AssetsDestination != "" {
|
||||
// Extract files from the embedded FS
|
||||
err := assets.ExtractFiles(options.BackendAssets, options.AssetsDestination)
|
||||
log.Debug().Msgf("Extracting backend assets files to %s", options.AssetsDestination)
|
||||
if err != nil {
|
||||
log.Warn().Msgf("Failed extracting backend assets files: %s (might be required for some backends to work properly, like gpt4all)", err)
|
||||
}
|
||||
}
|
||||
|
||||
if options.PreloadJSONModels != "" {
|
||||
if err := localai.ApplyGalleryFromString(options.Loader.ModelPath, options.PreloadJSONModels, cl, options.Galleries); err != nil {
|
||||
return nil, nil, err
|
||||
}
|
||||
}
|
||||
|
||||
if options.PreloadModelsFromPath != "" {
|
||||
if err := localai.ApplyGalleryFromFile(options.Loader.ModelPath, options.PreloadModelsFromPath, cl, options.Galleries); err != nil {
|
||||
return nil, nil, err
|
||||
}
|
||||
}
|
||||
|
||||
// turn off any process that was started by GRPC if the context is canceled
|
||||
go func() {
|
||||
<-options.Context.Done()
|
||||
log.Debug().Msgf("Context canceled, shutting down")
|
||||
options.Loader.StopAllGRPC()
|
||||
}()
|
||||
|
||||
return options, cl, nil
|
||||
}
|
||||
|
||||
func App(opts ...options.AppOption) (*fiber.App, error) {
|
||||
|
||||
options, cl, err := Startup(opts...)
|
||||
if err != nil {
|
||||
return nil, fmt.Errorf("failed basic startup tasks with error %s", err.Error())
|
||||
}
|
||||
|
||||
// Return errors as JSON responses
|
||||
app := fiber.New(fiber.Config{
|
||||
BodyLimit: options.uploadLimitMB * 1024 * 1024, // this is the default limit of 4MB
|
||||
DisableStartupMessage: options.disableMessage,
|
||||
BodyLimit: options.UploadLimitMB * 1024 * 1024, // this is the default limit of 4MB
|
||||
DisableStartupMessage: options.DisableMessage,
|
||||
// Override default error handler
|
||||
ErrorHandler: func(ctx *fiber.Ctx, err error) error {
|
||||
// Status code defaults to 500
|
||||
@@ -36,94 +105,106 @@ func App(opts ...AppOption) *fiber.App {
|
||||
|
||||
// Send custom error page
|
||||
return ctx.Status(code).JSON(
|
||||
ErrorResponse{
|
||||
Error: &APIError{Message: err.Error(), Code: code},
|
||||
schema.ErrorResponse{
|
||||
Error: &schema.APIError{Message: err.Error(), Code: code},
|
||||
},
|
||||
)
|
||||
},
|
||||
})
|
||||
|
||||
if options.debug {
|
||||
if options.Debug {
|
||||
app.Use(logger.New(logger.Config{
|
||||
Format: "[${ip}]:${port} ${status} - ${method} ${path}\n",
|
||||
}))
|
||||
}
|
||||
|
||||
cm := NewConfigMerger()
|
||||
if err := cm.LoadConfigs(options.loader.ModelPath); err != nil {
|
||||
log.Error().Msgf("error loading config files: %s", err.Error())
|
||||
}
|
||||
|
||||
if options.configFile != "" {
|
||||
if err := cm.LoadConfigFile(options.configFile); err != nil {
|
||||
log.Error().Msgf("error loading config file: %s", err.Error())
|
||||
}
|
||||
}
|
||||
|
||||
if options.debug {
|
||||
for _, v := range cm.ListConfigs() {
|
||||
cfg, _ := cm.GetConfig(v)
|
||||
log.Debug().Msgf("Model: %s (config: %+v)", v, cfg)
|
||||
}
|
||||
}
|
||||
// Default middleware config
|
||||
app.Use(recover.New())
|
||||
|
||||
if options.preloadJSONModels != "" {
|
||||
if err := ApplyGalleryFromString(options.loader.ModelPath, options.preloadJSONModels, cm); err != nil {
|
||||
return nil
|
||||
// Auth middleware checking if API key is valid. If no API key is set, no auth is required.
|
||||
auth := func(c *fiber.Ctx) error {
|
||||
if len(options.ApiKeys) > 0 {
|
||||
authHeader := c.Get("Authorization")
|
||||
if authHeader == "" {
|
||||
return c.Status(fiber.StatusUnauthorized).JSON(fiber.Map{"message": "Authorization header missing"})
|
||||
}
|
||||
authHeaderParts := strings.Split(authHeader, " ")
|
||||
if len(authHeaderParts) != 2 || authHeaderParts[0] != "Bearer" {
|
||||
return c.Status(fiber.StatusUnauthorized).JSON(fiber.Map{"message": "Invalid Authorization header format"})
|
||||
}
|
||||
|
||||
apiKey := authHeaderParts[1]
|
||||
validApiKey := false
|
||||
for _, key := range options.ApiKeys {
|
||||
if apiKey == key {
|
||||
validApiKey = true
|
||||
}
|
||||
}
|
||||
if !validApiKey {
|
||||
return c.Status(fiber.StatusUnauthorized).JSON(fiber.Map{"message": "Invalid API key"})
|
||||
}
|
||||
}
|
||||
return c.Next()
|
||||
}
|
||||
|
||||
if options.preloadModelsFromPath != "" {
|
||||
if err := ApplyGalleryFromFile(options.loader.ModelPath, options.preloadModelsFromPath, cm); err != nil {
|
||||
return nil
|
||||
}
|
||||
}
|
||||
|
||||
if options.cors {
|
||||
if options.corsAllowOrigins == "" {
|
||||
app.Use(cors.New())
|
||||
if options.CORS {
|
||||
var c func(ctx *fiber.Ctx) error
|
||||
if options.CORSAllowOrigins == "" {
|
||||
c = cors.New()
|
||||
} else {
|
||||
app.Use(cors.New(cors.Config{
|
||||
AllowOrigins: options.corsAllowOrigins,
|
||||
}))
|
||||
c = cors.New(cors.Config{AllowOrigins: options.CORSAllowOrigins})
|
||||
}
|
||||
|
||||
app.Use(c)
|
||||
}
|
||||
|
||||
// LocalAI API endpoints
|
||||
applier := newGalleryApplier(options.loader.ModelPath)
|
||||
applier.start(options.context, cm)
|
||||
app.Post("/models/apply", applyModelGallery(options.loader.ModelPath, cm, applier.C))
|
||||
app.Get("/models/jobs/:uuid", getOpStatus(applier))
|
||||
galleryService := localai.NewGalleryService(options.Loader.ModelPath)
|
||||
galleryService.Start(options.Context, cl)
|
||||
|
||||
app.Get("/version", auth, func(c *fiber.Ctx) error {
|
||||
return c.JSON(struct {
|
||||
Version string `json:"version"`
|
||||
}{Version: internal.PrintableVersion()})
|
||||
})
|
||||
|
||||
app.Post("/models/apply", auth, localai.ApplyModelGalleryEndpoint(options.Loader.ModelPath, cl, galleryService.C, options.Galleries))
|
||||
app.Get("/models/available", auth, localai.ListModelFromGalleryEndpoint(options.Galleries, options.Loader.ModelPath))
|
||||
app.Get("/models/jobs/:uuid", auth, localai.GetOpStatusEndpoint(galleryService))
|
||||
|
||||
// openAI compatible API endpoint
|
||||
|
||||
// chat
|
||||
app.Post("/v1/chat/completions", chatEndpoint(cm, options))
|
||||
app.Post("/chat/completions", chatEndpoint(cm, options))
|
||||
app.Post("/v1/chat/completions", auth, openai.ChatEndpoint(cl, options))
|
||||
app.Post("/chat/completions", auth, openai.ChatEndpoint(cl, options))
|
||||
|
||||
// edit
|
||||
app.Post("/v1/edits", editEndpoint(cm, options))
|
||||
app.Post("/edits", editEndpoint(cm, options))
|
||||
app.Post("/v1/edits", auth, openai.EditEndpoint(cl, options))
|
||||
app.Post("/edits", auth, openai.EditEndpoint(cl, options))
|
||||
|
||||
// completion
|
||||
app.Post("/v1/completions", completionEndpoint(cm, options))
|
||||
app.Post("/completions", completionEndpoint(cm, options))
|
||||
app.Post("/v1/completions", auth, openai.CompletionEndpoint(cl, options))
|
||||
app.Post("/completions", auth, openai.CompletionEndpoint(cl, options))
|
||||
app.Post("/v1/engines/:model/completions", auth, openai.CompletionEndpoint(cl, options))
|
||||
|
||||
// embeddings
|
||||
app.Post("/v1/embeddings", embeddingsEndpoint(cm, options))
|
||||
app.Post("/embeddings", embeddingsEndpoint(cm, options))
|
||||
app.Post("/v1/engines/:model/embeddings", embeddingsEndpoint(cm, options))
|
||||
app.Post("/v1/embeddings", auth, openai.EmbeddingsEndpoint(cl, options))
|
||||
app.Post("/embeddings", auth, openai.EmbeddingsEndpoint(cl, options))
|
||||
app.Post("/v1/engines/:model/embeddings", auth, openai.EmbeddingsEndpoint(cl, options))
|
||||
|
||||
// audio
|
||||
app.Post("/v1/audio/transcriptions", transcriptEndpoint(cm, options))
|
||||
app.Post("/v1/audio/transcriptions", auth, openai.TranscriptEndpoint(cl, options))
|
||||
app.Post("/tts", auth, localai.TTSEndpoint(cl, options))
|
||||
|
||||
// images
|
||||
app.Post("/v1/images/generations", imageEndpoint(cm, options))
|
||||
app.Post("/v1/images/generations", auth, openai.ImageEndpoint(cl, options))
|
||||
|
||||
if options.imageDir != "" {
|
||||
app.Static("/generated-images", options.imageDir)
|
||||
if options.ImageDir != "" {
|
||||
app.Static("/generated-images", options.ImageDir)
|
||||
}
|
||||
|
||||
if options.AudioDir != "" {
|
||||
app.Static("/generated-audio", options.AudioDir)
|
||||
}
|
||||
|
||||
ok := func(c *fiber.Ctx) error {
|
||||
@@ -134,9 +215,14 @@ func App(opts ...AppOption) *fiber.App {
|
||||
app.Get("/healthz", ok)
|
||||
app.Get("/readyz", ok)
|
||||
|
||||
// models
|
||||
app.Get("/v1/models", listModels(options.loader, cm))
|
||||
app.Get("/models", listModels(options.loader, cm))
|
||||
// Experimental Backend Statistics Module
|
||||
backendMonitor := localai.NewBackendMonitor(cl, options) // Split out for now
|
||||
app.Get("/backend/monitor", localai.BackendMonitorEndpoint(backendMonitor))
|
||||
app.Post("/backend/shutdown", localai.BackendShutdownEndpoint(backendMonitor))
|
||||
|
||||
return app
|
||||
// models
|
||||
app.Get("/v1/models", auth, openai.ListModelsEndpoint(options.Loader, cl))
|
||||
app.Get("/models", auth, openai.ListModelsEndpoint(options.Loader, cl))
|
||||
|
||||
return app, nil
|
||||
}
|
||||
|
||||
528
api/api_test.go
528
api/api_test.go
@@ -3,16 +3,21 @@ package api_test
|
||||
import (
|
||||
"bytes"
|
||||
"context"
|
||||
"embed"
|
||||
"encoding/json"
|
||||
"errors"
|
||||
"fmt"
|
||||
"io/ioutil"
|
||||
"io"
|
||||
"net/http"
|
||||
"os"
|
||||
"path/filepath"
|
||||
"runtime"
|
||||
|
||||
. "github.com/go-skynet/LocalAI/api"
|
||||
"github.com/go-skynet/LocalAI/api/options"
|
||||
"github.com/go-skynet/LocalAI/pkg/gallery"
|
||||
"github.com/go-skynet/LocalAI/pkg/model"
|
||||
"github.com/go-skynet/LocalAI/pkg/utils"
|
||||
"github.com/gofiber/fiber/v2"
|
||||
. "github.com/onsi/ginkgo/v2"
|
||||
. "github.com/onsi/gomega"
|
||||
@@ -20,12 +25,14 @@ import (
|
||||
|
||||
openaigo "github.com/otiai10/openaigo"
|
||||
"github.com/sashabaranov/go-openai"
|
||||
"github.com/sashabaranov/go-openai/jsonschema"
|
||||
)
|
||||
|
||||
type modelApplyRequest struct {
|
||||
URL string `json:"url"`
|
||||
Name string `json:"name"`
|
||||
Overrides map[string]string `json:"overrides"`
|
||||
ID string `json:"id"`
|
||||
URL string `json:"url"`
|
||||
Name string `json:"name"`
|
||||
Overrides map[string]interface{} `json:"overrides"`
|
||||
}
|
||||
|
||||
func getModelStatus(url string) (response map[string]interface{}) {
|
||||
@@ -37,7 +44,7 @@ func getModelStatus(url string) (response map[string]interface{}) {
|
||||
}
|
||||
defer resp.Body.Close()
|
||||
|
||||
body, err := ioutil.ReadAll(resp.Body)
|
||||
body, err := io.ReadAll(resp.Body)
|
||||
if err != nil {
|
||||
fmt.Println("Error reading response body:", err)
|
||||
return
|
||||
@@ -51,6 +58,15 @@ func getModelStatus(url string) (response map[string]interface{}) {
|
||||
}
|
||||
return
|
||||
}
|
||||
|
||||
func getModels(url string) (response []gallery.GalleryModel) {
|
||||
utils.GetURI(url, func(url string, i []byte) error {
|
||||
// Unmarshal YAML data into a struct
|
||||
return json.Unmarshal(i, &response)
|
||||
})
|
||||
return
|
||||
}
|
||||
|
||||
func postModelApplyRequest(url string, request modelApplyRequest) (response map[string]interface{}) {
|
||||
|
||||
//url := "http://localhost:AI/models/apply"
|
||||
@@ -80,7 +96,7 @@ func postModelApplyRequest(url string, request modelApplyRequest) (response map[
|
||||
}
|
||||
defer resp.Body.Close()
|
||||
|
||||
body, err := ioutil.ReadAll(resp.Body)
|
||||
body, err := io.ReadAll(resp.Body)
|
||||
if err != nil {
|
||||
fmt.Println("Error reading response body:", err)
|
||||
return
|
||||
@@ -95,6 +111,9 @@ func postModelApplyRequest(url string, request modelApplyRequest) (response map[
|
||||
return
|
||||
}
|
||||
|
||||
//go:embed backend-assets/*
|
||||
var backendAssets embed.FS
|
||||
|
||||
var _ = Describe("API test", func() {
|
||||
|
||||
var app *fiber.App
|
||||
@@ -105,6 +124,11 @@ var _ = Describe("API test", func() {
|
||||
var cancel context.CancelFunc
|
||||
var tmpdir string
|
||||
|
||||
commonOpts := []options.AppOption{
|
||||
options.WithDebug(true),
|
||||
options.WithDisableMessage(true),
|
||||
}
|
||||
|
||||
Context("API with ephemeral models", func() {
|
||||
BeforeEach(func() {
|
||||
var err error
|
||||
@@ -114,7 +138,36 @@ var _ = Describe("API test", func() {
|
||||
modelLoader = model.NewModelLoader(tmpdir)
|
||||
c, cancel = context.WithCancel(context.Background())
|
||||
|
||||
app = App(WithContext(c), WithModelLoader(modelLoader))
|
||||
g := []gallery.GalleryModel{
|
||||
{
|
||||
Name: "bert",
|
||||
URL: "https://raw.githubusercontent.com/go-skynet/model-gallery/main/bert-embeddings.yaml",
|
||||
},
|
||||
{
|
||||
Name: "bert2",
|
||||
URL: "https://raw.githubusercontent.com/go-skynet/model-gallery/main/bert-embeddings.yaml",
|
||||
Overrides: map[string]interface{}{"foo": "bar"},
|
||||
AdditionalFiles: []gallery.File{{Filename: "foo.yaml", URI: "https://raw.githubusercontent.com/go-skynet/model-gallery/main/bert-embeddings.yaml"}},
|
||||
},
|
||||
}
|
||||
out, err := yaml.Marshal(g)
|
||||
Expect(err).ToNot(HaveOccurred())
|
||||
err = os.WriteFile(filepath.Join(tmpdir, "gallery_simple.yaml"), out, 0644)
|
||||
Expect(err).ToNot(HaveOccurred())
|
||||
|
||||
galleries := []gallery.Gallery{
|
||||
{
|
||||
Name: "test",
|
||||
URL: "file://" + filepath.Join(tmpdir, "gallery_simple.yaml"),
|
||||
},
|
||||
}
|
||||
|
||||
app, err = App(
|
||||
append(commonOpts,
|
||||
options.WithContext(c),
|
||||
options.WithGalleries(galleries),
|
||||
options.WithModelLoader(modelLoader), options.WithBackendAssets(backendAssets), options.WithBackendAssetsOutput(tmpdir))...)
|
||||
Expect(err).ToNot(HaveOccurred())
|
||||
go app.Listen("127.0.0.1:9090")
|
||||
|
||||
defaultConfig := openai.DefaultConfig("")
|
||||
@@ -138,11 +191,58 @@ var _ = Describe("API test", func() {
|
||||
})
|
||||
|
||||
Context("Applying models", func() {
|
||||
It("applies models from a gallery", func() {
|
||||
|
||||
models := getModels("http://127.0.0.1:9090/models/available")
|
||||
Expect(len(models)).To(Equal(2), fmt.Sprint(models))
|
||||
Expect(models[0].Installed).To(BeFalse(), fmt.Sprint(models))
|
||||
Expect(models[1].Installed).To(BeFalse(), fmt.Sprint(models))
|
||||
|
||||
response := postModelApplyRequest("http://127.0.0.1:9090/models/apply", modelApplyRequest{
|
||||
ID: "test@bert2",
|
||||
})
|
||||
|
||||
Expect(response["uuid"]).ToNot(BeEmpty(), fmt.Sprint(response))
|
||||
|
||||
uuid := response["uuid"].(string)
|
||||
resp := map[string]interface{}{}
|
||||
Eventually(func() bool {
|
||||
response := getModelStatus("http://127.0.0.1:9090/models/jobs/" + uuid)
|
||||
fmt.Println(response)
|
||||
resp = response
|
||||
return response["processed"].(bool)
|
||||
}, "360s", "10s").Should(Equal(true))
|
||||
Expect(resp["message"]).ToNot(ContainSubstring("error"))
|
||||
|
||||
dat, err := os.ReadFile(filepath.Join(tmpdir, "bert2.yaml"))
|
||||
Expect(err).ToNot(HaveOccurred())
|
||||
|
||||
_, err = os.ReadFile(filepath.Join(tmpdir, "foo.yaml"))
|
||||
Expect(err).ToNot(HaveOccurred())
|
||||
|
||||
content := map[string]interface{}{}
|
||||
err = yaml.Unmarshal(dat, &content)
|
||||
Expect(err).ToNot(HaveOccurred())
|
||||
Expect(content["backend"]).To(Equal("bert-embeddings"))
|
||||
Expect(content["foo"]).To(Equal("bar"))
|
||||
|
||||
models = getModels("http://127.0.0.1:9090/models/available")
|
||||
Expect(len(models)).To(Equal(2), fmt.Sprint(models))
|
||||
Expect(models[0].Name).To(Or(Equal("bert"), Equal("bert2")))
|
||||
Expect(models[1].Name).To(Or(Equal("bert"), Equal("bert2")))
|
||||
for _, m := range models {
|
||||
if m.Name == "bert2" {
|
||||
Expect(m.Installed).To(BeTrue())
|
||||
} else {
|
||||
Expect(m.Installed).To(BeFalse())
|
||||
}
|
||||
}
|
||||
})
|
||||
It("overrides models", func() {
|
||||
response := postModelApplyRequest("http://127.0.0.1:9090/models/apply", modelApplyRequest{
|
||||
URL: "https://raw.githubusercontent.com/go-skynet/model-gallery/main/bert-embeddings.yaml",
|
||||
Name: "bert",
|
||||
Overrides: map[string]string{
|
||||
Overrides: map[string]interface{}{
|
||||
"backend": "llama",
|
||||
},
|
||||
})
|
||||
@@ -153,9 +253,8 @@ var _ = Describe("API test", func() {
|
||||
|
||||
Eventually(func() bool {
|
||||
response := getModelStatus("http://127.0.0.1:9090/models/jobs/" + uuid)
|
||||
fmt.Println(response)
|
||||
return response["processed"].(bool)
|
||||
}, "360s").Should(Equal(true))
|
||||
}, "360s", "10s").Should(Equal(true))
|
||||
|
||||
dat, err := os.ReadFile(filepath.Join(tmpdir, "bert.yaml"))
|
||||
Expect(err).ToNot(HaveOccurred())
|
||||
@@ -169,7 +268,7 @@ var _ = Describe("API test", func() {
|
||||
response := postModelApplyRequest("http://127.0.0.1:9090/models/apply", modelApplyRequest{
|
||||
URL: "https://raw.githubusercontent.com/go-skynet/model-gallery/main/bert-embeddings.yaml",
|
||||
Name: "bert",
|
||||
Overrides: map[string]string{},
|
||||
Overrides: map[string]interface{}{},
|
||||
})
|
||||
|
||||
Expect(response["uuid"]).ToNot(BeEmpty(), fmt.Sprint(response))
|
||||
@@ -178,9 +277,8 @@ var _ = Describe("API test", func() {
|
||||
|
||||
Eventually(func() bool {
|
||||
response := getModelStatus("http://127.0.0.1:9090/models/jobs/" + uuid)
|
||||
fmt.Println(response)
|
||||
return response["processed"].(bool)
|
||||
}, "360s").Should(Equal(true))
|
||||
}, "360s", "10s").Should(Equal(true))
|
||||
|
||||
dat, err := os.ReadFile(filepath.Join(tmpdir, "bert.yaml"))
|
||||
Expect(err).ToNot(HaveOccurred())
|
||||
@@ -190,6 +288,287 @@ var _ = Describe("API test", func() {
|
||||
Expect(err).ToNot(HaveOccurred())
|
||||
Expect(content["backend"]).To(Equal("bert-embeddings"))
|
||||
})
|
||||
|
||||
It("runs openllama", Label("llama"), func() {
|
||||
if runtime.GOOS != "linux" {
|
||||
Skip("test supported only on linux")
|
||||
}
|
||||
response := postModelApplyRequest("http://127.0.0.1:9090/models/apply", modelApplyRequest{
|
||||
URL: "github:go-skynet/model-gallery/openllama_3b.yaml",
|
||||
Name: "openllama_3b",
|
||||
Overrides: map[string]interface{}{"backend": "llama-stable", "mmap": true, "f16": true, "context_size": 128},
|
||||
})
|
||||
|
||||
Expect(response["uuid"]).ToNot(BeEmpty(), fmt.Sprint(response))
|
||||
|
||||
uuid := response["uuid"].(string)
|
||||
|
||||
Eventually(func() bool {
|
||||
response := getModelStatus("http://127.0.0.1:9090/models/jobs/" + uuid)
|
||||
return response["processed"].(bool)
|
||||
}, "360s", "10s").Should(Equal(true))
|
||||
|
||||
By("testing completion")
|
||||
resp, err := client.CreateCompletion(context.TODO(), openai.CompletionRequest{Model: "openllama_3b", Prompt: "Count up to five: one, two, three, four, "})
|
||||
Expect(err).ToNot(HaveOccurred())
|
||||
Expect(len(resp.Choices)).To(Equal(1))
|
||||
Expect(resp.Choices[0].Text).To(ContainSubstring("five"))
|
||||
|
||||
By("testing functions")
|
||||
resp2, err := client.CreateChatCompletion(
|
||||
context.TODO(),
|
||||
openai.ChatCompletionRequest{
|
||||
Model: "openllama_3b",
|
||||
Messages: []openai.ChatCompletionMessage{
|
||||
{
|
||||
Role: "user",
|
||||
Content: "What is the weather like in San Francisco (celsius)?",
|
||||
},
|
||||
},
|
||||
Functions: []openai.FunctionDefinition{
|
||||
openai.FunctionDefinition{
|
||||
Name: "get_current_weather",
|
||||
Description: "Get the current weather",
|
||||
Parameters: jsonschema.Definition{
|
||||
Type: jsonschema.Object,
|
||||
Properties: map[string]jsonschema.Definition{
|
||||
"location": {
|
||||
Type: jsonschema.String,
|
||||
Description: "The city and state, e.g. San Francisco, CA",
|
||||
},
|
||||
"unit": {
|
||||
Type: jsonschema.String,
|
||||
Enum: []string{"celcius", "fahrenheit"},
|
||||
},
|
||||
},
|
||||
Required: []string{"location"},
|
||||
},
|
||||
},
|
||||
},
|
||||
})
|
||||
Expect(err).ToNot(HaveOccurred())
|
||||
Expect(len(resp2.Choices)).To(Equal(1))
|
||||
Expect(resp2.Choices[0].Message.FunctionCall).ToNot(BeNil())
|
||||
Expect(resp2.Choices[0].Message.FunctionCall.Name).To(Equal("get_current_weather"), resp2.Choices[0].Message.FunctionCall.Name)
|
||||
|
||||
var res map[string]string
|
||||
err = json.Unmarshal([]byte(resp2.Choices[0].Message.FunctionCall.Arguments), &res)
|
||||
Expect(err).ToNot(HaveOccurred())
|
||||
Expect(res["location"]).To(Equal("San Francisco, California, United States"), fmt.Sprint(res))
|
||||
Expect(res["unit"]).To(Equal("celcius"), fmt.Sprint(res))
|
||||
Expect(string(resp2.Choices[0].FinishReason)).To(Equal("function_call"), fmt.Sprint(resp2.Choices[0].FinishReason))
|
||||
})
|
||||
|
||||
It("runs openllama gguf", Label("llama-gguf"), func() {
|
||||
if runtime.GOOS != "linux" {
|
||||
Skip("test supported only on linux")
|
||||
}
|
||||
response := postModelApplyRequest("http://127.0.0.1:9090/models/apply", modelApplyRequest{
|
||||
URL: "github:go-skynet/model-gallery/openllama-3b-gguf.yaml",
|
||||
Name: "openllama_3b_gguf",
|
||||
Overrides: map[string]interface{}{"backend": "llama", "mmap": true, "f16": true, "context_size": 128},
|
||||
})
|
||||
|
||||
Expect(response["uuid"]).ToNot(BeEmpty(), fmt.Sprint(response))
|
||||
|
||||
uuid := response["uuid"].(string)
|
||||
|
||||
Eventually(func() bool {
|
||||
response := getModelStatus("http://127.0.0.1:9090/models/jobs/" + uuid)
|
||||
return response["processed"].(bool)
|
||||
}, "360s", "10s").Should(Equal(true))
|
||||
|
||||
By("testing completion")
|
||||
resp, err := client.CreateCompletion(context.TODO(), openai.CompletionRequest{Model: "openllama_3b_gguf", Prompt: "Count up to five: one, two, three, four, "})
|
||||
Expect(err).ToNot(HaveOccurred())
|
||||
Expect(len(resp.Choices)).To(Equal(1))
|
||||
Expect(resp.Choices[0].Text).To(ContainSubstring("five"))
|
||||
|
||||
By("testing functions")
|
||||
resp2, err := client.CreateChatCompletion(
|
||||
context.TODO(),
|
||||
openai.ChatCompletionRequest{
|
||||
Model: "openllama_3b_gguf",
|
||||
Messages: []openai.ChatCompletionMessage{
|
||||
{
|
||||
Role: "user",
|
||||
Content: "What is the weather like in San Francisco (celsius)?",
|
||||
},
|
||||
},
|
||||
Functions: []openai.FunctionDefinition{
|
||||
openai.FunctionDefinition{
|
||||
Name: "get_current_weather",
|
||||
Description: "Get the current weather",
|
||||
Parameters: jsonschema.Definition{
|
||||
Type: jsonschema.Object,
|
||||
Properties: map[string]jsonschema.Definition{
|
||||
"location": {
|
||||
Type: jsonschema.String,
|
||||
Description: "The city and state, e.g. San Francisco, CA",
|
||||
},
|
||||
"unit": {
|
||||
Type: jsonschema.String,
|
||||
Enum: []string{"celcius", "fahrenheit"},
|
||||
},
|
||||
},
|
||||
Required: []string{"location"},
|
||||
},
|
||||
},
|
||||
},
|
||||
})
|
||||
Expect(err).ToNot(HaveOccurred())
|
||||
Expect(len(resp2.Choices)).To(Equal(1))
|
||||
Expect(resp2.Choices[0].Message.FunctionCall).ToNot(BeNil())
|
||||
Expect(resp2.Choices[0].Message.FunctionCall.Name).To(Equal("get_current_weather"), resp2.Choices[0].Message.FunctionCall.Name)
|
||||
|
||||
var res map[string]string
|
||||
err = json.Unmarshal([]byte(resp2.Choices[0].Message.FunctionCall.Arguments), &res)
|
||||
Expect(err).ToNot(HaveOccurred())
|
||||
Expect(res["location"]).To(Equal("San Francisco, California"), fmt.Sprint(res))
|
||||
Expect(res["unit"]).To(Equal("celcius"), fmt.Sprint(res))
|
||||
Expect(string(resp2.Choices[0].FinishReason)).To(Equal("function_call"), fmt.Sprint(resp2.Choices[0].FinishReason))
|
||||
})
|
||||
|
||||
It("runs gpt4all", Label("gpt4all"), func() {
|
||||
if runtime.GOOS != "linux" {
|
||||
Skip("test supported only on linux")
|
||||
}
|
||||
|
||||
response := postModelApplyRequest("http://127.0.0.1:9090/models/apply", modelApplyRequest{
|
||||
URL: "github:go-skynet/model-gallery/gpt4all-j.yaml",
|
||||
Name: "gpt4all-j",
|
||||
})
|
||||
|
||||
Expect(response["uuid"]).ToNot(BeEmpty(), fmt.Sprint(response))
|
||||
|
||||
uuid := response["uuid"].(string)
|
||||
|
||||
Eventually(func() bool {
|
||||
response := getModelStatus("http://127.0.0.1:9090/models/jobs/" + uuid)
|
||||
return response["processed"].(bool)
|
||||
}, "360s", "10s").Should(Equal(true))
|
||||
|
||||
resp, err := client.CreateChatCompletion(context.TODO(), openai.ChatCompletionRequest{Model: "gpt4all-j", Messages: []openai.ChatCompletionMessage{openai.ChatCompletionMessage{Role: "user", Content: "How are you?"}}})
|
||||
Expect(err).ToNot(HaveOccurred())
|
||||
Expect(len(resp.Choices)).To(Equal(1))
|
||||
Expect(resp.Choices[0].Message.Content).To(ContainSubstring("well"))
|
||||
})
|
||||
|
||||
})
|
||||
})
|
||||
|
||||
Context("Model gallery", func() {
|
||||
BeforeEach(func() {
|
||||
var err error
|
||||
tmpdir, err = os.MkdirTemp("", "")
|
||||
Expect(err).ToNot(HaveOccurred())
|
||||
|
||||
modelLoader = model.NewModelLoader(tmpdir)
|
||||
c, cancel = context.WithCancel(context.Background())
|
||||
|
||||
galleries := []gallery.Gallery{
|
||||
{
|
||||
Name: "model-gallery",
|
||||
URL: "https://raw.githubusercontent.com/go-skynet/model-gallery/main/index.yaml",
|
||||
},
|
||||
}
|
||||
|
||||
app, err = App(
|
||||
append(commonOpts,
|
||||
options.WithContext(c),
|
||||
options.WithAudioDir(tmpdir),
|
||||
options.WithImageDir(tmpdir),
|
||||
options.WithGalleries(galleries),
|
||||
options.WithModelLoader(modelLoader),
|
||||
options.WithBackendAssets(backendAssets),
|
||||
options.WithBackendAssetsOutput(tmpdir))...,
|
||||
)
|
||||
Expect(err).ToNot(HaveOccurred())
|
||||
go app.Listen("127.0.0.1:9090")
|
||||
|
||||
defaultConfig := openai.DefaultConfig("")
|
||||
defaultConfig.BaseURL = "http://127.0.0.1:9090/v1"
|
||||
|
||||
client2 = openaigo.NewClient("")
|
||||
client2.BaseURL = defaultConfig.BaseURL
|
||||
|
||||
// Wait for API to be ready
|
||||
client = openai.NewClientWithConfig(defaultConfig)
|
||||
Eventually(func() error {
|
||||
_, err := client.ListModels(context.TODO())
|
||||
return err
|
||||
}, "2m").ShouldNot(HaveOccurred())
|
||||
})
|
||||
|
||||
AfterEach(func() {
|
||||
cancel()
|
||||
app.Shutdown()
|
||||
os.RemoveAll(tmpdir)
|
||||
})
|
||||
It("installs and is capable to run tts", Label("tts"), func() {
|
||||
if runtime.GOOS != "linux" {
|
||||
Skip("test supported only on linux")
|
||||
}
|
||||
|
||||
response := postModelApplyRequest("http://127.0.0.1:9090/models/apply", modelApplyRequest{
|
||||
ID: "model-gallery@voice-en-us-kathleen-low",
|
||||
})
|
||||
|
||||
Expect(response["uuid"]).ToNot(BeEmpty(), fmt.Sprint(response))
|
||||
|
||||
uuid := response["uuid"].(string)
|
||||
|
||||
Eventually(func() bool {
|
||||
response := getModelStatus("http://127.0.0.1:9090/models/jobs/" + uuid)
|
||||
fmt.Println(response)
|
||||
return response["processed"].(bool)
|
||||
}, "360s", "10s").Should(Equal(true))
|
||||
|
||||
// An HTTP Post to the /tts endpoint should return a wav audio file
|
||||
resp, err := http.Post("http://127.0.0.1:9090/tts", "application/json", bytes.NewBuffer([]byte(`{"input": "Hello world", "model": "en-us-kathleen-low.onnx"}`)))
|
||||
Expect(err).ToNot(HaveOccurred(), fmt.Sprint(resp))
|
||||
dat, err := io.ReadAll(resp.Body)
|
||||
Expect(err).ToNot(HaveOccurred(), fmt.Sprint(resp))
|
||||
|
||||
Expect(resp.StatusCode).To(Equal(200), fmt.Sprint(string(dat)))
|
||||
Expect(resp.Header.Get("Content-Type")).To(Equal("audio/x-wav"))
|
||||
})
|
||||
It("installs and is capable to generate images", Label("stablediffusion"), func() {
|
||||
if runtime.GOOS != "linux" {
|
||||
Skip("test supported only on linux")
|
||||
}
|
||||
|
||||
response := postModelApplyRequest("http://127.0.0.1:9090/models/apply", modelApplyRequest{
|
||||
ID: "model-gallery@stablediffusion",
|
||||
Overrides: map[string]interface{}{
|
||||
"parameters": map[string]interface{}{"model": "stablediffusion_assets"},
|
||||
},
|
||||
})
|
||||
|
||||
Expect(response["uuid"]).ToNot(BeEmpty(), fmt.Sprint(response))
|
||||
|
||||
uuid := response["uuid"].(string)
|
||||
|
||||
Eventually(func() bool {
|
||||
response := getModelStatus("http://127.0.0.1:9090/models/jobs/" + uuid)
|
||||
fmt.Println(response)
|
||||
return response["processed"].(bool)
|
||||
}, "360s", "10s").Should(Equal(true))
|
||||
|
||||
resp, err := http.Post(
|
||||
"http://127.0.0.1:9090/v1/images/generations",
|
||||
"application/json",
|
||||
bytes.NewBuffer([]byte(`{
|
||||
"prompt": "floating hair, portrait, ((loli)), ((one girl)), cute face, hidden hands, asymmetrical bangs, beautiful detailed eyes, eye shadow, hair ornament, ribbons, bowties, buttons, pleated skirt, (((masterpiece))), ((best quality)), colorful|((part of the head)), ((((mutated hands and fingers)))), deformed, blurry, bad anatomy, disfigured, poorly drawn face, mutation, mutated, extra limb, ugly, poorly drawn hands, missing limb, blurry, floating limbs, disconnected limbs, malformed hands, blur, out of focus, long neck, long body, Octane renderer, lowres, bad anatomy, bad hands, text",
|
||||
"mode": 2, "seed":9000,
|
||||
"size": "256x256", "n":2}`)))
|
||||
// The response should contain an URL
|
||||
Expect(err).ToNot(HaveOccurred(), fmt.Sprint(resp))
|
||||
dat, err := io.ReadAll(resp.Body)
|
||||
Expect(err).ToNot(HaveOccurred(), string(dat))
|
||||
Expect(string(dat)).To(ContainSubstring("http://127.0.0.1:9090/"), string(dat))
|
||||
Expect(string(dat)).To(ContainSubstring(".png"), string(dat))
|
||||
|
||||
})
|
||||
})
|
||||
|
||||
@@ -198,7 +577,14 @@ var _ = Describe("API test", func() {
|
||||
modelLoader = model.NewModelLoader(os.Getenv("MODELS_PATH"))
|
||||
c, cancel = context.WithCancel(context.Background())
|
||||
|
||||
app = App(WithContext(c), WithModelLoader(modelLoader))
|
||||
var err error
|
||||
app, err = App(
|
||||
append(commonOpts,
|
||||
options.WithExternalBackend("huggingface", os.Getenv("HUGGINGFACE_GRPC")),
|
||||
options.WithContext(c),
|
||||
options.WithModelLoader(modelLoader),
|
||||
)...)
|
||||
Expect(err).ToNot(HaveOccurred())
|
||||
go app.Listen("127.0.0.1:9090")
|
||||
|
||||
defaultConfig := openai.DefaultConfig("")
|
||||
@@ -221,7 +607,7 @@ var _ = Describe("API test", func() {
|
||||
It("returns the models list", func() {
|
||||
models, err := client.ListModels(context.TODO())
|
||||
Expect(err).ToNot(HaveOccurred())
|
||||
Expect(len(models.Models)).To(Equal(10))
|
||||
Expect(len(models.Models)).To(Equal(6)) // If "config.yaml" should be included, this should be 8?
|
||||
})
|
||||
It("can generate completions", func() {
|
||||
resp, err := client.CreateCompletion(context.TODO(), openai.CompletionRequest{Model: "testmodel", Prompt: "abcdedfghikl"})
|
||||
@@ -252,9 +638,10 @@ var _ = Describe("API test", func() {
|
||||
})
|
||||
|
||||
It("returns errors", func() {
|
||||
backends := len(model.AutoLoadBackends) + 1 // +1 for huggingface
|
||||
_, 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: 12 errors occurred:"))
|
||||
Expect(err.Error()).To(ContainSubstring(fmt.Sprintf("error, status code: 500, message: could not load model - all backends returned error: %d errors occurred:", backends)))
|
||||
})
|
||||
It("transcribes audio", func() {
|
||||
if runtime.GOOS != "linux" {
|
||||
@@ -298,15 +685,98 @@ var _ = Describe("API test", func() {
|
||||
Expect(resp2.Data[0].Embedding).To(Equal(sunEmbedding))
|
||||
})
|
||||
|
||||
Context("External gRPC calls", func() {
|
||||
It("calculate embeddings with huggingface", func() {
|
||||
if runtime.GOOS != "linux" {
|
||||
Skip("test supported only on linux")
|
||||
}
|
||||
resp, err := client.CreateEmbeddings(
|
||||
context.Background(),
|
||||
openai.EmbeddingRequest{
|
||||
Model: openai.AdaCodeSearchCode,
|
||||
Input: []string{"sun", "cat"},
|
||||
},
|
||||
)
|
||||
Expect(err).ToNot(HaveOccurred())
|
||||
Expect(len(resp.Data[0].Embedding)).To(BeNumerically("==", 384))
|
||||
Expect(len(resp.Data[1].Embedding)).To(BeNumerically("==", 384))
|
||||
|
||||
sunEmbedding := resp.Data[0].Embedding
|
||||
resp2, err := client.CreateEmbeddings(
|
||||
context.Background(),
|
||||
openai.EmbeddingRequest{
|
||||
Model: openai.AdaCodeSearchCode,
|
||||
Input: []string{"sun"},
|
||||
},
|
||||
)
|
||||
Expect(err).ToNot(HaveOccurred())
|
||||
Expect(resp2.Data[0].Embedding).To(Equal(sunEmbedding))
|
||||
Expect(resp2.Data[0].Embedding).ToNot(Equal(resp.Data[1].Embedding))
|
||||
})
|
||||
})
|
||||
|
||||
Context("backends", func() {
|
||||
It("runs rwkv", func() {
|
||||
It("runs rwkv completion", func() {
|
||||
if runtime.GOOS != "linux" {
|
||||
Skip("test supported only on linux")
|
||||
}
|
||||
resp, err := client.CreateCompletion(context.TODO(), openai.CompletionRequest{Model: "rwkv_test", Prompt: "Count up to five: one, two, three, four,"})
|
||||
Expect(err).ToNot(HaveOccurred())
|
||||
Expect(len(resp.Choices) > 0).To(BeTrue())
|
||||
Expect(resp.Choices[0].Text).To(Equal(" five."))
|
||||
Expect(resp.Choices[0].Text).To(ContainSubstring("five"))
|
||||
|
||||
stream, err := client.CreateCompletionStream(context.TODO(), openai.CompletionRequest{
|
||||
Model: "rwkv_test", Prompt: "Count up to five: one, two, three, four,", Stream: true,
|
||||
})
|
||||
Expect(err).ToNot(HaveOccurred())
|
||||
defer stream.Close()
|
||||
|
||||
tokens := 0
|
||||
text := ""
|
||||
for {
|
||||
response, err := stream.Recv()
|
||||
if errors.Is(err, io.EOF) {
|
||||
break
|
||||
}
|
||||
|
||||
Expect(err).ToNot(HaveOccurred())
|
||||
text += response.Choices[0].Text
|
||||
tokens++
|
||||
}
|
||||
Expect(text).ToNot(BeEmpty())
|
||||
Expect(text).To(ContainSubstring("five"))
|
||||
Expect(tokens).ToNot(Or(Equal(1), Equal(0)))
|
||||
})
|
||||
It("runs rwkv chat completion", func() {
|
||||
if runtime.GOOS != "linux" {
|
||||
Skip("test supported only on linux")
|
||||
}
|
||||
resp, err := client.CreateChatCompletion(context.TODO(),
|
||||
openai.ChatCompletionRequest{Model: "rwkv_test", Messages: []openai.ChatCompletionMessage{{Content: "Can you count up to five?", Role: "user"}}})
|
||||
Expect(err).ToNot(HaveOccurred())
|
||||
Expect(len(resp.Choices) > 0).To(BeTrue())
|
||||
Expect(resp.Choices[0].Message.Content).To(Or(ContainSubstring("Sure"), ContainSubstring("five")))
|
||||
|
||||
stream, err := client.CreateChatCompletionStream(context.TODO(), openai.ChatCompletionRequest{Model: "rwkv_test", Messages: []openai.ChatCompletionMessage{{Content: "Can you count up to five?", Role: "user"}}})
|
||||
Expect(err).ToNot(HaveOccurred())
|
||||
defer stream.Close()
|
||||
|
||||
tokens := 0
|
||||
text := ""
|
||||
for {
|
||||
response, err := stream.Recv()
|
||||
if errors.Is(err, io.EOF) {
|
||||
break
|
||||
}
|
||||
|
||||
Expect(err).ToNot(HaveOccurred())
|
||||
text += response.Choices[0].Delta.Content
|
||||
tokens++
|
||||
}
|
||||
Expect(text).ToNot(BeEmpty())
|
||||
Expect(text).To(Or(ContainSubstring("Sure"), ContainSubstring("five")))
|
||||
|
||||
Expect(tokens).ToNot(Or(Equal(1), Equal(0)))
|
||||
})
|
||||
})
|
||||
})
|
||||
@@ -316,7 +786,14 @@ var _ = Describe("API test", func() {
|
||||
modelLoader = model.NewModelLoader(os.Getenv("MODELS_PATH"))
|
||||
c, cancel = context.WithCancel(context.Background())
|
||||
|
||||
app = App(WithContext(c), WithModelLoader(modelLoader), WithConfigFile(os.Getenv("CONFIG_FILE")))
|
||||
var err error
|
||||
app, err = App(
|
||||
append(commonOpts,
|
||||
options.WithContext(c),
|
||||
options.WithModelLoader(modelLoader),
|
||||
options.WithConfigFile(os.Getenv("CONFIG_FILE")))...,
|
||||
)
|
||||
Expect(err).ToNot(HaveOccurred())
|
||||
go app.Listen("127.0.0.1:9090")
|
||||
|
||||
defaultConfig := openai.DefaultConfig("")
|
||||
@@ -334,19 +811,14 @@ var _ = Describe("API test", func() {
|
||||
cancel()
|
||||
app.Shutdown()
|
||||
})
|
||||
It("can generate chat completions from config file", func() {
|
||||
models, err := client.ListModels(context.TODO())
|
||||
Expect(err).ToNot(HaveOccurred())
|
||||
Expect(len(models.Models)).To(Equal(12))
|
||||
})
|
||||
It("can generate chat completions from config file", func() {
|
||||
resp, err := client.CreateChatCompletion(context.TODO(), openai.ChatCompletionRequest{Model: "list1", Messages: []openai.ChatCompletionMessage{openai.ChatCompletionMessage{Role: "user", Content: "abcdedfghikl"}}})
|
||||
It("can generate chat completions from config file (list1)", func() {
|
||||
resp, err := client.CreateChatCompletion(context.TODO(), openai.ChatCompletionRequest{Model: "list1", Messages: []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"}}})
|
||||
It("can generate chat completions from config file (list2)", func() {
|
||||
resp, err := client.CreateChatCompletion(context.TODO(), openai.ChatCompletionRequest{Model: "list2", Messages: []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())
|
||||
|
||||
92
api/backend/embeddings.go
Normal file
92
api/backend/embeddings.go
Normal file
@@ -0,0 +1,92 @@
|
||||
package backend
|
||||
|
||||
import (
|
||||
"fmt"
|
||||
|
||||
config "github.com/go-skynet/LocalAI/api/config"
|
||||
"github.com/go-skynet/LocalAI/api/options"
|
||||
"github.com/go-skynet/LocalAI/pkg/grpc"
|
||||
model "github.com/go-skynet/LocalAI/pkg/model"
|
||||
)
|
||||
|
||||
func ModelEmbedding(s string, tokens []int, loader *model.ModelLoader, c config.Config, o *options.Option) (func() ([]float32, error), error) {
|
||||
if !c.Embeddings {
|
||||
return nil, fmt.Errorf("endpoint disabled for this model by API configuration")
|
||||
}
|
||||
|
||||
modelFile := c.Model
|
||||
|
||||
grpcOpts := gRPCModelOpts(c)
|
||||
|
||||
var inferenceModel interface{}
|
||||
var err error
|
||||
|
||||
opts := modelOpts(c, o, []model.Option{
|
||||
model.WithLoadGRPCLoadModelOpts(grpcOpts),
|
||||
model.WithThreads(uint32(c.Threads)),
|
||||
model.WithAssetDir(o.AssetsDestination),
|
||||
model.WithModel(modelFile),
|
||||
model.WithContext(o.Context),
|
||||
})
|
||||
|
||||
if c.Backend == "" {
|
||||
inferenceModel, err = loader.GreedyLoader(opts...)
|
||||
} else {
|
||||
opts = append(opts, model.WithBackendString(c.Backend))
|
||||
inferenceModel, err = loader.BackendLoader(opts...)
|
||||
}
|
||||
if err != nil {
|
||||
return nil, err
|
||||
}
|
||||
|
||||
var fn func() ([]float32, error)
|
||||
switch model := inferenceModel.(type) {
|
||||
case *grpc.Client:
|
||||
fn = func() ([]float32, error) {
|
||||
predictOptions := gRPCPredictOpts(c, loader.ModelPath)
|
||||
if len(tokens) > 0 {
|
||||
embeds := []int32{}
|
||||
|
||||
for _, t := range tokens {
|
||||
embeds = append(embeds, int32(t))
|
||||
}
|
||||
predictOptions.EmbeddingTokens = embeds
|
||||
|
||||
res, err := model.Embeddings(o.Context, predictOptions)
|
||||
if err != nil {
|
||||
return nil, err
|
||||
}
|
||||
|
||||
return res.Embeddings, nil
|
||||
}
|
||||
predictOptions.Embeddings = s
|
||||
|
||||
res, err := model.Embeddings(o.Context, predictOptions)
|
||||
if err != nil {
|
||||
return nil, err
|
||||
}
|
||||
|
||||
return res.Embeddings, nil
|
||||
}
|
||||
default:
|
||||
fn = func() ([]float32, error) {
|
||||
return nil, fmt.Errorf("embeddings not supported by the backend")
|
||||
}
|
||||
}
|
||||
|
||||
return func() ([]float32, error) {
|
||||
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
|
||||
}
|
||||
57
api/backend/image.go
Normal file
57
api/backend/image.go
Normal file
@@ -0,0 +1,57 @@
|
||||
package backend
|
||||
|
||||
import (
|
||||
config "github.com/go-skynet/LocalAI/api/config"
|
||||
"github.com/go-skynet/LocalAI/api/options"
|
||||
"github.com/go-skynet/LocalAI/pkg/grpc/proto"
|
||||
model "github.com/go-skynet/LocalAI/pkg/model"
|
||||
)
|
||||
|
||||
func ImageGeneration(height, width, mode, step, seed int, positive_prompt, negative_prompt, src, dst string, loader *model.ModelLoader, c config.Config, o *options.Option) (func() error, error) {
|
||||
|
||||
opts := modelOpts(c, o, []model.Option{
|
||||
model.WithBackendString(c.Backend),
|
||||
model.WithAssetDir(o.AssetsDestination),
|
||||
model.WithThreads(uint32(c.Threads)),
|
||||
model.WithContext(o.Context),
|
||||
model.WithModel(c.Model),
|
||||
model.WithLoadGRPCLoadModelOpts(&proto.ModelOptions{
|
||||
CUDA: c.Diffusers.CUDA,
|
||||
SchedulerType: c.Diffusers.SchedulerType,
|
||||
PipelineType: c.Diffusers.PipelineType,
|
||||
CFGScale: c.Diffusers.CFGScale,
|
||||
IMG2IMG: c.Diffusers.IMG2IMG,
|
||||
CLIPModel: c.Diffusers.ClipModel,
|
||||
CLIPSubfolder: c.Diffusers.ClipSubFolder,
|
||||
CLIPSkip: int32(c.Diffusers.ClipSkip),
|
||||
}),
|
||||
})
|
||||
|
||||
inferenceModel, err := loader.BackendLoader(
|
||||
opts...,
|
||||
)
|
||||
if err != nil {
|
||||
return nil, err
|
||||
}
|
||||
|
||||
fn := func() error {
|
||||
_, err := inferenceModel.GenerateImage(
|
||||
o.Context,
|
||||
&proto.GenerateImageRequest{
|
||||
Height: int32(height),
|
||||
Width: int32(width),
|
||||
Mode: int32(mode),
|
||||
Step: int32(step),
|
||||
Seed: int32(seed),
|
||||
CLIPSkip: int32(c.Diffusers.ClipSkip),
|
||||
PositivePrompt: positive_prompt,
|
||||
NegativePrompt: negative_prompt,
|
||||
Dst: dst,
|
||||
Src: src,
|
||||
EnableParameters: c.Diffusers.EnableParameters,
|
||||
})
|
||||
return err
|
||||
}
|
||||
|
||||
return fn, nil
|
||||
}
|
||||
148
api/backend/llm.go
Normal file
148
api/backend/llm.go
Normal file
@@ -0,0 +1,148 @@
|
||||
package backend
|
||||
|
||||
import (
|
||||
"context"
|
||||
"os"
|
||||
"regexp"
|
||||
"strings"
|
||||
"sync"
|
||||
|
||||
config "github.com/go-skynet/LocalAI/api/config"
|
||||
"github.com/go-skynet/LocalAI/api/options"
|
||||
"github.com/go-skynet/LocalAI/pkg/gallery"
|
||||
"github.com/go-skynet/LocalAI/pkg/grpc"
|
||||
model "github.com/go-skynet/LocalAI/pkg/model"
|
||||
"github.com/go-skynet/LocalAI/pkg/utils"
|
||||
)
|
||||
|
||||
type LLMResponse struct {
|
||||
Response string // should this be []byte?
|
||||
Usage TokenUsage
|
||||
}
|
||||
|
||||
type TokenUsage struct {
|
||||
Prompt int
|
||||
Completion int
|
||||
}
|
||||
|
||||
func ModelInference(ctx context.Context, s string, loader *model.ModelLoader, c config.Config, o *options.Option, tokenCallback func(string, TokenUsage) bool) (func() (LLMResponse, error), error) {
|
||||
modelFile := c.Model
|
||||
|
||||
grpcOpts := gRPCModelOpts(c)
|
||||
|
||||
var inferenceModel *grpc.Client
|
||||
var err error
|
||||
|
||||
opts := modelOpts(c, o, []model.Option{
|
||||
model.WithLoadGRPCLoadModelOpts(grpcOpts),
|
||||
model.WithThreads(uint32(c.Threads)), // some models uses this to allocate threads during startup
|
||||
model.WithAssetDir(o.AssetsDestination),
|
||||
model.WithModel(modelFile),
|
||||
model.WithContext(o.Context),
|
||||
})
|
||||
|
||||
if c.Backend != "" {
|
||||
opts = append(opts, model.WithBackendString(c.Backend))
|
||||
}
|
||||
|
||||
// Check if the modelFile exists, if it doesn't try to load it from the gallery
|
||||
if o.AutoloadGalleries { // experimental
|
||||
if _, err := os.Stat(modelFile); os.IsNotExist(err) {
|
||||
utils.ResetDownloadTimers()
|
||||
// if we failed to load the model, we try to download it
|
||||
err := gallery.InstallModelFromGalleryByName(o.Galleries, modelFile, loader.ModelPath, gallery.GalleryModel{}, utils.DisplayDownloadFunction)
|
||||
if err != nil {
|
||||
return nil, err
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
if c.Backend == "" {
|
||||
inferenceModel, err = loader.GreedyLoader(opts...)
|
||||
} else {
|
||||
inferenceModel, err = loader.BackendLoader(opts...)
|
||||
}
|
||||
|
||||
if err != nil {
|
||||
return nil, err
|
||||
}
|
||||
|
||||
// in GRPC, the backend is supposed to answer to 1 single token if stream is not supported
|
||||
fn := func() (LLMResponse, error) {
|
||||
opts := gRPCPredictOpts(c, loader.ModelPath)
|
||||
opts.Prompt = s
|
||||
|
||||
tokenUsage := TokenUsage{}
|
||||
|
||||
// check the per-model feature flag for usage, since tokenCallback may have a cost.
|
||||
// Defaults to off as for now it is still experimental
|
||||
if c.FeatureFlag.Enabled("usage") {
|
||||
userTokenCallback := tokenCallback
|
||||
if userTokenCallback == nil {
|
||||
userTokenCallback = func(token string, usage TokenUsage) bool {
|
||||
return true
|
||||
}
|
||||
}
|
||||
|
||||
promptInfo, pErr := inferenceModel.TokenizeString(ctx, opts)
|
||||
if pErr == nil && promptInfo.Length > 0 {
|
||||
tokenUsage.Prompt = int(promptInfo.Length)
|
||||
}
|
||||
|
||||
tokenCallback = func(token string, usage TokenUsage) bool {
|
||||
tokenUsage.Completion++
|
||||
return userTokenCallback(token, tokenUsage)
|
||||
}
|
||||
}
|
||||
|
||||
if tokenCallback != nil {
|
||||
ss := ""
|
||||
err := inferenceModel.PredictStream(ctx, opts, func(s []byte) {
|
||||
tokenCallback(string(s), tokenUsage)
|
||||
ss += string(s)
|
||||
})
|
||||
return LLMResponse{
|
||||
Response: ss,
|
||||
Usage: tokenUsage,
|
||||
}, err
|
||||
} else {
|
||||
// TODO: Is the chicken bit the only way to get here? is that acceptable?
|
||||
reply, err := inferenceModel.Predict(ctx, opts)
|
||||
if err != nil {
|
||||
return LLMResponse{}, err
|
||||
}
|
||||
return LLMResponse{
|
||||
Response: string(reply.Message),
|
||||
Usage: tokenUsage,
|
||||
}, err
|
||||
}
|
||||
}
|
||||
|
||||
return fn, nil
|
||||
}
|
||||
|
||||
var cutstrings map[string]*regexp.Regexp = make(map[string]*regexp.Regexp)
|
||||
var mu sync.Mutex = sync.Mutex{}
|
||||
|
||||
func Finetune(config config.Config, input, prediction string) string {
|
||||
if config.Echo {
|
||||
prediction = input + prediction
|
||||
}
|
||||
|
||||
for _, c := range config.Cutstrings {
|
||||
mu.Lock()
|
||||
reg, ok := cutstrings[c]
|
||||
if !ok {
|
||||
cutstrings[c] = regexp.MustCompile(c)
|
||||
reg = cutstrings[c]
|
||||
}
|
||||
mu.Unlock()
|
||||
prediction = reg.ReplaceAllString(prediction, "")
|
||||
}
|
||||
|
||||
for _, c := range config.TrimSpace {
|
||||
prediction = strings.TrimSpace(strings.TrimPrefix(prediction, c))
|
||||
}
|
||||
return prediction
|
||||
|
||||
}
|
||||
112
api/backend/options.go
Normal file
112
api/backend/options.go
Normal file
@@ -0,0 +1,112 @@
|
||||
package backend
|
||||
|
||||
import (
|
||||
"os"
|
||||
"path/filepath"
|
||||
|
||||
pb "github.com/go-skynet/LocalAI/pkg/grpc/proto"
|
||||
model "github.com/go-skynet/LocalAI/pkg/model"
|
||||
|
||||
config "github.com/go-skynet/LocalAI/api/config"
|
||||
"github.com/go-skynet/LocalAI/api/options"
|
||||
)
|
||||
|
||||
func modelOpts(c config.Config, o *options.Option, opts []model.Option) []model.Option {
|
||||
if o.SingleBackend {
|
||||
opts = append(opts, model.WithSingleActiveBackend())
|
||||
}
|
||||
|
||||
if c.GRPC.Attempts != 0 {
|
||||
opts = append(opts, model.WithGRPCAttempts(c.GRPC.Attempts))
|
||||
}
|
||||
|
||||
if c.GRPC.AttemptsSleepTime != 0 {
|
||||
opts = append(opts, model.WithGRPCAttemptsDelay(c.GRPC.AttemptsSleepTime))
|
||||
}
|
||||
|
||||
for k, v := range o.ExternalGRPCBackends {
|
||||
opts = append(opts, model.WithExternalBackend(k, v))
|
||||
}
|
||||
|
||||
return opts
|
||||
}
|
||||
|
||||
func gRPCModelOpts(c config.Config) *pb.ModelOptions {
|
||||
b := 512
|
||||
if c.Batch != 0 {
|
||||
b = c.Batch
|
||||
}
|
||||
|
||||
return &pb.ModelOptions{
|
||||
ContextSize: int32(c.ContextSize),
|
||||
Seed: int32(c.Seed),
|
||||
NBatch: int32(b),
|
||||
NoMulMatQ: c.NoMulMatQ,
|
||||
LoraAdapter: c.LoraAdapter,
|
||||
LoraBase: c.LoraBase,
|
||||
NGQA: c.NGQA,
|
||||
RMSNormEps: c.RMSNormEps,
|
||||
F16Memory: c.F16,
|
||||
MLock: c.MMlock,
|
||||
RopeFreqBase: c.RopeFreqBase,
|
||||
RopeFreqScale: c.RopeFreqScale,
|
||||
NUMA: c.NUMA,
|
||||
Embeddings: c.Embeddings,
|
||||
LowVRAM: c.LowVRAM,
|
||||
NGPULayers: int32(c.NGPULayers),
|
||||
MMap: c.MMap,
|
||||
MainGPU: c.MainGPU,
|
||||
Threads: int32(c.Threads),
|
||||
TensorSplit: c.TensorSplit,
|
||||
// AutoGPTQ
|
||||
ModelBaseName: c.AutoGPTQ.ModelBaseName,
|
||||
Device: c.AutoGPTQ.Device,
|
||||
UseTriton: c.AutoGPTQ.Triton,
|
||||
UseFastTokenizer: c.AutoGPTQ.UseFastTokenizer,
|
||||
// RWKV
|
||||
Tokenizer: c.Tokenizer,
|
||||
}
|
||||
}
|
||||
|
||||
func gRPCPredictOpts(c config.Config, modelPath string) *pb.PredictOptions {
|
||||
promptCachePath := ""
|
||||
if c.PromptCachePath != "" {
|
||||
p := filepath.Join(modelPath, c.PromptCachePath)
|
||||
os.MkdirAll(filepath.Dir(p), 0755)
|
||||
promptCachePath = p
|
||||
}
|
||||
return &pb.PredictOptions{
|
||||
Temperature: float32(c.Temperature),
|
||||
TopP: float32(c.TopP),
|
||||
TopK: int32(c.TopK),
|
||||
Tokens: int32(c.Maxtokens),
|
||||
Threads: int32(c.Threads),
|
||||
PromptCacheAll: c.PromptCacheAll,
|
||||
PromptCacheRO: c.PromptCacheRO,
|
||||
PromptCachePath: promptCachePath,
|
||||
F16KV: c.F16,
|
||||
DebugMode: c.Debug,
|
||||
Grammar: c.Grammar,
|
||||
NegativePromptScale: c.NegativePromptScale,
|
||||
RopeFreqBase: c.RopeFreqBase,
|
||||
RopeFreqScale: c.RopeFreqScale,
|
||||
NegativePrompt: c.NegativePrompt,
|
||||
Mirostat: int32(c.LLMConfig.Mirostat),
|
||||
MirostatETA: float32(c.LLMConfig.MirostatETA),
|
||||
MirostatTAU: float32(c.LLMConfig.MirostatTAU),
|
||||
Debug: c.Debug,
|
||||
StopPrompts: c.StopWords,
|
||||
Repeat: int32(c.RepeatPenalty),
|
||||
NKeep: int32(c.Keep),
|
||||
Batch: int32(c.Batch),
|
||||
IgnoreEOS: c.IgnoreEOS,
|
||||
Seed: int32(c.Seed),
|
||||
FrequencyPenalty: float32(c.FrequencyPenalty),
|
||||
MLock: c.MMlock,
|
||||
MMap: c.MMap,
|
||||
MainGPU: c.MainGPU,
|
||||
TensorSplit: c.TensorSplit,
|
||||
TailFreeSamplingZ: float32(c.TFZ),
|
||||
TypicalP: float32(c.TypicalP),
|
||||
}
|
||||
}
|
||||
39
api/backend/transcript.go
Normal file
39
api/backend/transcript.go
Normal file
@@ -0,0 +1,39 @@
|
||||
package backend
|
||||
|
||||
import (
|
||||
"context"
|
||||
"fmt"
|
||||
|
||||
config "github.com/go-skynet/LocalAI/api/config"
|
||||
"github.com/go-skynet/LocalAI/api/schema"
|
||||
|
||||
"github.com/go-skynet/LocalAI/api/options"
|
||||
"github.com/go-skynet/LocalAI/pkg/grpc/proto"
|
||||
model "github.com/go-skynet/LocalAI/pkg/model"
|
||||
)
|
||||
|
||||
func ModelTranscription(audio, language string, loader *model.ModelLoader, c config.Config, o *options.Option) (*schema.Result, error) {
|
||||
|
||||
opts := modelOpts(c, o, []model.Option{
|
||||
model.WithBackendString(model.WhisperBackend),
|
||||
model.WithModel(c.Model),
|
||||
model.WithContext(o.Context),
|
||||
model.WithThreads(uint32(c.Threads)),
|
||||
model.WithAssetDir(o.AssetsDestination),
|
||||
})
|
||||
|
||||
whisperModel, err := o.Loader.BackendLoader(opts...)
|
||||
if err != nil {
|
||||
return nil, err
|
||||
}
|
||||
|
||||
if whisperModel == nil {
|
||||
return nil, fmt.Errorf("could not load whisper model")
|
||||
}
|
||||
|
||||
return whisperModel.AudioTranscription(context.Background(), &proto.TranscriptRequest{
|
||||
Dst: audio,
|
||||
Language: language,
|
||||
Threads: uint32(c.Threads),
|
||||
})
|
||||
}
|
||||
75
api/backend/tts.go
Normal file
75
api/backend/tts.go
Normal file
@@ -0,0 +1,75 @@
|
||||
package backend
|
||||
|
||||
import (
|
||||
"context"
|
||||
"fmt"
|
||||
"os"
|
||||
"path/filepath"
|
||||
|
||||
api_config "github.com/go-skynet/LocalAI/api/config"
|
||||
"github.com/go-skynet/LocalAI/api/options"
|
||||
"github.com/go-skynet/LocalAI/pkg/grpc/proto"
|
||||
model "github.com/go-skynet/LocalAI/pkg/model"
|
||||
"github.com/go-skynet/LocalAI/pkg/utils"
|
||||
)
|
||||
|
||||
func generateUniqueFileName(dir, baseName, ext string) string {
|
||||
counter := 1
|
||||
fileName := baseName + ext
|
||||
|
||||
for {
|
||||
filePath := filepath.Join(dir, fileName)
|
||||
_, err := os.Stat(filePath)
|
||||
if os.IsNotExist(err) {
|
||||
return fileName
|
||||
}
|
||||
|
||||
counter++
|
||||
fileName = fmt.Sprintf("%s_%d%s", baseName, counter, ext)
|
||||
}
|
||||
}
|
||||
|
||||
func ModelTTS(backend, text, modelFile string, loader *model.ModelLoader, o *options.Option) (string, *proto.Result, error) {
|
||||
bb := backend
|
||||
if bb == "" {
|
||||
bb = model.PiperBackend
|
||||
}
|
||||
opts := modelOpts(api_config.Config{}, o, []model.Option{
|
||||
model.WithBackendString(bb),
|
||||
model.WithModel(modelFile),
|
||||
model.WithContext(o.Context),
|
||||
model.WithAssetDir(o.AssetsDestination),
|
||||
})
|
||||
piperModel, err := o.Loader.BackendLoader(opts...)
|
||||
if err != nil {
|
||||
return "", nil, err
|
||||
}
|
||||
|
||||
if piperModel == nil {
|
||||
return "", nil, fmt.Errorf("could not load piper model")
|
||||
}
|
||||
|
||||
if err := os.MkdirAll(o.AudioDir, 0755); err != nil {
|
||||
return "", nil, fmt.Errorf("failed creating audio directory: %s", err)
|
||||
}
|
||||
|
||||
fileName := generateUniqueFileName(o.AudioDir, "piper", ".wav")
|
||||
filePath := filepath.Join(o.AudioDir, fileName)
|
||||
|
||||
// If the model file is not empty, we pass it joined with the model path
|
||||
modelPath := ""
|
||||
if modelFile != "" {
|
||||
modelPath = filepath.Join(o.Loader.ModelPath, modelFile)
|
||||
if err := utils.VerifyPath(modelPath, o.Loader.ModelPath); err != nil {
|
||||
return "", nil, err
|
||||
}
|
||||
}
|
||||
|
||||
res, err := piperModel.TTS(context.Background(), &proto.TTSRequest{
|
||||
Text: text,
|
||||
Model: modelPath,
|
||||
Dst: filePath,
|
||||
})
|
||||
|
||||
return filePath, res, err
|
||||
}
|
||||
333
api/config.go
333
api/config.go
@@ -1,333 +0,0 @@
|
||||
package api
|
||||
|
||||
import (
|
||||
"encoding/json"
|
||||
"fmt"
|
||||
"io/ioutil"
|
||||
"os"
|
||||
"path/filepath"
|
||||
"strings"
|
||||
"sync"
|
||||
|
||||
model "github.com/go-skynet/LocalAI/pkg/model"
|
||||
"github.com/gofiber/fiber/v2"
|
||||
"github.com/rs/zerolog/log"
|
||||
"gopkg.in/yaml.v3"
|
||||
)
|
||||
|
||||
type Config struct {
|
||||
OpenAIRequest `yaml:"parameters"`
|
||||
Name string `yaml:"name"`
|
||||
StopWords []string `yaml:"stopwords"`
|
||||
Cutstrings []string `yaml:"cutstrings"`
|
||||
TrimSpace []string `yaml:"trimspace"`
|
||||
ContextSize int `yaml:"context_size"`
|
||||
F16 bool `yaml:"f16"`
|
||||
Threads int `yaml:"threads"`
|
||||
Debug bool `yaml:"debug"`
|
||||
Roles map[string]string `yaml:"roles"`
|
||||
Embeddings bool `yaml:"embeddings"`
|
||||
Backend string `yaml:"backend"`
|
||||
TemplateConfig TemplateConfig `yaml:"template"`
|
||||
MirostatETA float64 `yaml:"mirostat_eta"`
|
||||
MirostatTAU float64 `yaml:"mirostat_tau"`
|
||||
Mirostat int `yaml:"mirostat"`
|
||||
NGPULayers int `yaml:"gpu_layers"`
|
||||
ImageGenerationAssets string `yaml:"asset_dir"`
|
||||
|
||||
PromptCachePath string `yaml:"prompt_cache_path"`
|
||||
PromptCacheAll bool `yaml:"prompt_cache_all"`
|
||||
|
||||
PromptStrings, InputStrings []string
|
||||
InputToken [][]int
|
||||
}
|
||||
|
||||
type TemplateConfig struct {
|
||||
Completion string `yaml:"completion"`
|
||||
Chat string `yaml:"chat"`
|
||||
Edit string `yaml:"edit"`
|
||||
}
|
||||
|
||||
type ConfigMerger struct {
|
||||
configs map[string]Config
|
||||
sync.Mutex
|
||||
}
|
||||
|
||||
func NewConfigMerger() *ConfigMerger {
|
||||
return &ConfigMerger{
|
||||
configs: make(map[string]Config),
|
||||
}
|
||||
}
|
||||
func ReadConfigFile(file string) ([]*Config, error) {
|
||||
c := &[]*Config{}
|
||||
f, err := os.ReadFile(file)
|
||||
if err != nil {
|
||||
return nil, fmt.Errorf("cannot read config file: %w", err)
|
||||
}
|
||||
if err := yaml.Unmarshal(f, c); err != nil {
|
||||
return nil, fmt.Errorf("cannot unmarshal config file: %w", err)
|
||||
}
|
||||
|
||||
return *c, nil
|
||||
}
|
||||
|
||||
func ReadConfig(file string) (*Config, error) {
|
||||
c := &Config{}
|
||||
f, err := os.ReadFile(file)
|
||||
if err != nil {
|
||||
return nil, fmt.Errorf("cannot read config file: %w", err)
|
||||
}
|
||||
if err := yaml.Unmarshal(f, c); err != nil {
|
||||
return nil, fmt.Errorf("cannot unmarshal config file: %w", err)
|
||||
}
|
||||
|
||||
return c, nil
|
||||
}
|
||||
|
||||
func (cm ConfigMerger) LoadConfigFile(file string) error {
|
||||
cm.Lock()
|
||||
defer cm.Unlock()
|
||||
c, err := ReadConfigFile(file)
|
||||
if err != nil {
|
||||
return fmt.Errorf("cannot load config file: %w", err)
|
||||
}
|
||||
|
||||
for _, cc := range c {
|
||||
cm.configs[cc.Name] = *cc
|
||||
}
|
||||
return nil
|
||||
}
|
||||
|
||||
func (cm ConfigMerger) LoadConfig(file string) error {
|
||||
cm.Lock()
|
||||
defer cm.Unlock()
|
||||
c, err := ReadConfig(file)
|
||||
if err != nil {
|
||||
return fmt.Errorf("cannot read config file: %w", err)
|
||||
}
|
||||
|
||||
cm.configs[c.Name] = *c
|
||||
return nil
|
||||
}
|
||||
|
||||
func (cm ConfigMerger) GetConfig(m string) (Config, bool) {
|
||||
cm.Lock()
|
||||
defer cm.Unlock()
|
||||
v, exists := cm.configs[m]
|
||||
return v, exists
|
||||
}
|
||||
|
||||
func (cm ConfigMerger) ListConfigs() []string {
|
||||
cm.Lock()
|
||||
defer cm.Unlock()
|
||||
var res []string
|
||||
for k := range cm.configs {
|
||||
res = append(res, k)
|
||||
}
|
||||
return res
|
||||
}
|
||||
|
||||
func (cm ConfigMerger) LoadConfigs(path string) error {
|
||||
cm.Lock()
|
||||
defer cm.Unlock()
|
||||
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.configs[c.Name] = *c
|
||||
}
|
||||
}
|
||||
|
||||
return nil
|
||||
}
|
||||
|
||||
func updateConfig(config *Config, input *OpenAIRequest) {
|
||||
if input.Echo {
|
||||
config.Echo = input.Echo
|
||||
}
|
||||
if input.TopK != 0 {
|
||||
config.TopK = input.TopK
|
||||
}
|
||||
if input.TopP != 0 {
|
||||
config.TopP = input.TopP
|
||||
}
|
||||
|
||||
if input.Temperature != 0 {
|
||||
config.Temperature = input.Temperature
|
||||
}
|
||||
|
||||
if input.Maxtokens != 0 {
|
||||
config.Maxtokens = input.Maxtokens
|
||||
}
|
||||
|
||||
switch stop := input.Stop.(type) {
|
||||
case string:
|
||||
if stop != "" {
|
||||
config.StopWords = append(config.StopWords, stop)
|
||||
}
|
||||
case []interface{}:
|
||||
for _, pp := range stop {
|
||||
if s, ok := pp.(string); ok {
|
||||
config.StopWords = append(config.StopWords, s)
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
if input.RepeatPenalty != 0 {
|
||||
config.RepeatPenalty = input.RepeatPenalty
|
||||
}
|
||||
|
||||
if input.Keep != 0 {
|
||||
config.Keep = input.Keep
|
||||
}
|
||||
|
||||
if input.Batch != 0 {
|
||||
config.Batch = input.Batch
|
||||
}
|
||||
|
||||
if input.F16 {
|
||||
config.F16 = input.F16
|
||||
}
|
||||
|
||||
if input.IgnoreEOS {
|
||||
config.IgnoreEOS = input.IgnoreEOS
|
||||
}
|
||||
|
||||
if input.Seed != 0 {
|
||||
config.Seed = input.Seed
|
||||
}
|
||||
|
||||
if input.Mirostat != 0 {
|
||||
config.Mirostat = input.Mirostat
|
||||
}
|
||||
|
||||
if input.MirostatETA != 0 {
|
||||
config.MirostatETA = input.MirostatETA
|
||||
}
|
||||
|
||||
if input.MirostatTAU != 0 {
|
||||
config.MirostatTAU = input.MirostatTAU
|
||||
}
|
||||
|
||||
switch inputs := input.Input.(type) {
|
||||
case string:
|
||||
if inputs != "" {
|
||||
config.InputStrings = append(config.InputStrings, inputs)
|
||||
}
|
||||
case []interface{}:
|
||||
for _, pp := range inputs {
|
||||
switch i := pp.(type) {
|
||||
case string:
|
||||
config.InputStrings = append(config.InputStrings, i)
|
||||
case []interface{}:
|
||||
tokens := []int{}
|
||||
for _, ii := range i {
|
||||
tokens = append(tokens, int(ii.(float64)))
|
||||
}
|
||||
config.InputToken = append(config.InputToken, tokens)
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
switch p := input.Prompt.(type) {
|
||||
case string:
|
||||
config.PromptStrings = append(config.PromptStrings, p)
|
||||
case []interface{}:
|
||||
for _, pp := range p {
|
||||
if s, ok := pp.(string); ok {
|
||||
config.PromptStrings = append(config.PromptStrings, s)
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
func readInput(c *fiber.Ctx, loader *model.ModelLoader, randomModel bool) (string, *OpenAIRequest, error) {
|
||||
input := new(OpenAIRequest)
|
||||
// Get input data from the request body
|
||||
if err := c.BodyParser(input); err != nil {
|
||||
return "", nil, err
|
||||
}
|
||||
|
||||
modelFile := input.Model
|
||||
|
||||
if c.Params("model") != "" {
|
||||
modelFile = c.Params("model")
|
||||
}
|
||||
|
||||
received, _ := json.Marshal(input)
|
||||
|
||||
log.Debug().Msgf("Request received: %s", string(received))
|
||||
|
||||
// Set model from bearer token, if available
|
||||
bearer := strings.TrimLeft(c.Get("authorization"), "Bearer ")
|
||||
bearerExists := bearer != "" && loader.ExistsInModelPath(bearer)
|
||||
|
||||
// If no model was specified, take the first available
|
||||
if modelFile == "" && !bearerExists && randomModel {
|
||||
models, _ := loader.ListModels()
|
||||
if len(models) > 0 {
|
||||
modelFile = models[0]
|
||||
log.Debug().Msgf("No model specified, using: %s", modelFile)
|
||||
} else {
|
||||
log.Debug().Msgf("No model specified, returning error")
|
||||
return "", nil, fmt.Errorf("no model specified")
|
||||
}
|
||||
}
|
||||
|
||||
// If a model is found in bearer token takes precedence
|
||||
if bearerExists {
|
||||
log.Debug().Msgf("Using model from bearer token: %s", bearer)
|
||||
modelFile = bearer
|
||||
}
|
||||
return modelFile, input, nil
|
||||
}
|
||||
|
||||
func readConfig(modelFile string, input *OpenAIRequest, cm *ConfigMerger, loader *model.ModelLoader, debug bool, threads, ctx int, f16 bool) (*Config, *OpenAIRequest, error) {
|
||||
// Load a config file if present after the model name
|
||||
modelConfig := filepath.Join(loader.ModelPath, modelFile+".yaml")
|
||||
if _, err := os.Stat(modelConfig); err == nil {
|
||||
if err := cm.LoadConfig(modelConfig); err != nil {
|
||||
return nil, nil, fmt.Errorf("failed loading model config (%s) %s", modelConfig, err.Error())
|
||||
}
|
||||
}
|
||||
|
||||
var config *Config
|
||||
cfg, exists := cm.GetConfig(modelFile)
|
||||
if !exists {
|
||||
config = &Config{
|
||||
OpenAIRequest: defaultRequest(modelFile),
|
||||
ContextSize: ctx,
|
||||
Threads: threads,
|
||||
F16: f16,
|
||||
Debug: debug,
|
||||
}
|
||||
} else {
|
||||
config = &cfg
|
||||
}
|
||||
|
||||
// Set the parameters for the language model prediction
|
||||
updateConfig(config, input)
|
||||
|
||||
// Don't allow 0 as setting
|
||||
if config.Threads == 0 {
|
||||
if threads != 0 {
|
||||
config.Threads = threads
|
||||
} else {
|
||||
config.Threads = 4
|
||||
}
|
||||
}
|
||||
|
||||
// Enforce debug flag if passed from CLI
|
||||
if debug {
|
||||
config.Debug = true
|
||||
}
|
||||
|
||||
return config, input, nil
|
||||
}
|
||||
272
api/config/config.go
Normal file
272
api/config/config.go
Normal file
@@ -0,0 +1,272 @@
|
||||
package api_config
|
||||
|
||||
import (
|
||||
"fmt"
|
||||
"io/fs"
|
||||
"os"
|
||||
"path/filepath"
|
||||
"strings"
|
||||
"sync"
|
||||
|
||||
"gopkg.in/yaml.v3"
|
||||
)
|
||||
|
||||
type Config struct {
|
||||
PredictionOptions `yaml:"parameters"`
|
||||
Name string `yaml:"name"`
|
||||
|
||||
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"`
|
||||
|
||||
PromptStrings, InputStrings []string `yaml:"-"`
|
||||
InputToken [][]int `yaml:"-"`
|
||||
functionCallString, functionCallNameString string `yaml:"-"`
|
||||
|
||||
FunctionsConfig Functions `yaml:"function"`
|
||||
|
||||
FeatureFlag FeatureFlag `yaml:"feature_flags"` // Feature Flag registry. We move fast, and features may break on a per model/backend basis. Registry for (usually temporary) flags that indicate aborting something early.
|
||||
// LLM configs (GPT4ALL, Llama.cpp, ...)
|
||||
LLMConfig `yaml:",inline"`
|
||||
|
||||
// AutoGPTQ specifics
|
||||
AutoGPTQ AutoGPTQ `yaml:"autogptq"`
|
||||
|
||||
// Diffusers
|
||||
Diffusers Diffusers `yaml:"diffusers"`
|
||||
|
||||
Step int `yaml:"step"`
|
||||
|
||||
// GRPC Options
|
||||
GRPC GRPC `yaml:"grpc"`
|
||||
}
|
||||
|
||||
type FeatureFlag map[string]*bool
|
||||
|
||||
func (ff FeatureFlag) Enabled(s string) bool {
|
||||
v, exist := ff[s]
|
||||
return exist && v != nil && *v
|
||||
}
|
||||
|
||||
type GRPC struct {
|
||||
Attempts int `yaml:"attempts"`
|
||||
AttemptsSleepTime int `yaml:"attempts_sleep_time"`
|
||||
}
|
||||
|
||||
type Diffusers struct {
|
||||
PipelineType string `yaml:"pipeline_type"`
|
||||
SchedulerType string `yaml:"scheduler_type"`
|
||||
CUDA bool `yaml:"cuda"`
|
||||
EnableParameters string `yaml:"enable_parameters"` // A list of comma separated parameters to specify
|
||||
CFGScale float32 `yaml:"cfg_scale"` // Classifier-Free Guidance Scale
|
||||
IMG2IMG bool `yaml:"img2img"` // Image to Image Diffuser
|
||||
ClipSkip int `yaml:"clip_skip"` // Skip every N frames
|
||||
ClipModel string `yaml:"clip_model"` // Clip model to use
|
||||
ClipSubFolder string `yaml:"clip_subfolder"` // Subfolder to use for clip model
|
||||
}
|
||||
|
||||
type LLMConfig struct {
|
||||
SystemPrompt string `yaml:"system_prompt"`
|
||||
TensorSplit string `yaml:"tensor_split"`
|
||||
MainGPU string `yaml:"main_gpu"`
|
||||
RMSNormEps float32 `yaml:"rms_norm_eps"`
|
||||
NGQA int32 `yaml:"ngqa"`
|
||||
PromptCachePath string `yaml:"prompt_cache_path"`
|
||||
PromptCacheAll bool `yaml:"prompt_cache_all"`
|
||||
PromptCacheRO bool `yaml:"prompt_cache_ro"`
|
||||
MirostatETA float64 `yaml:"mirostat_eta"`
|
||||
MirostatTAU float64 `yaml:"mirostat_tau"`
|
||||
Mirostat int `yaml:"mirostat"`
|
||||
NGPULayers int `yaml:"gpu_layers"`
|
||||
MMap bool `yaml:"mmap"`
|
||||
MMlock bool `yaml:"mmlock"`
|
||||
LowVRAM bool `yaml:"low_vram"`
|
||||
Grammar string `yaml:"grammar"`
|
||||
StopWords []string `yaml:"stopwords"`
|
||||
Cutstrings []string `yaml:"cutstrings"`
|
||||
TrimSpace []string `yaml:"trimspace"`
|
||||
ContextSize int `yaml:"context_size"`
|
||||
NUMA bool `yaml:"numa"`
|
||||
LoraAdapter string `yaml:"lora_adapter"`
|
||||
LoraBase string `yaml:"lora_base"`
|
||||
NoMulMatQ bool `yaml:"no_mulmatq"`
|
||||
}
|
||||
|
||||
type AutoGPTQ struct {
|
||||
ModelBaseName string `yaml:"model_base_name"`
|
||||
Device string `yaml:"device"`
|
||||
Triton bool `yaml:"triton"`
|
||||
UseFastTokenizer bool `yaml:"use_fast_tokenizer"`
|
||||
}
|
||||
|
||||
type Functions struct {
|
||||
DisableNoAction bool `yaml:"disable_no_action"`
|
||||
NoActionFunctionName string `yaml:"no_action_function_name"`
|
||||
NoActionDescriptionName string `yaml:"no_action_description_name"`
|
||||
}
|
||||
|
||||
type TemplateConfig struct {
|
||||
Chat string `yaml:"chat"`
|
||||
ChatMessage string `yaml:"chat_message"`
|
||||
Completion string `yaml:"completion"`
|
||||
Edit string `yaml:"edit"`
|
||||
Functions string `yaml:"function"`
|
||||
}
|
||||
|
||||
type ConfigLoader struct {
|
||||
configs map[string]Config
|
||||
sync.Mutex
|
||||
}
|
||||
|
||||
func (c *Config) SetFunctionCallString(s string) {
|
||||
c.functionCallString = s
|
||||
}
|
||||
|
||||
func (c *Config) SetFunctionCallNameString(s string) {
|
||||
c.functionCallNameString = s
|
||||
}
|
||||
|
||||
func (c *Config) ShouldUseFunctions() bool {
|
||||
return ((c.functionCallString != "none" || c.functionCallString == "") || c.ShouldCallSpecificFunction())
|
||||
}
|
||||
|
||||
func (c *Config) ShouldCallSpecificFunction() bool {
|
||||
return len(c.functionCallNameString) > 0
|
||||
}
|
||||
|
||||
func (c *Config) FunctionToCall() string {
|
||||
return c.functionCallNameString
|
||||
}
|
||||
|
||||
func defaultPredictOptions(modelFile string) PredictionOptions {
|
||||
return PredictionOptions{
|
||||
TopP: 0.7,
|
||||
TopK: 80,
|
||||
Maxtokens: 512,
|
||||
Temperature: 0.9,
|
||||
Model: modelFile,
|
||||
}
|
||||
}
|
||||
|
||||
func DefaultConfig(modelFile string) *Config {
|
||||
return &Config{
|
||||
PredictionOptions: defaultPredictOptions(modelFile),
|
||||
}
|
||||
}
|
||||
|
||||
func NewConfigLoader() *ConfigLoader {
|
||||
return &ConfigLoader{
|
||||
configs: make(map[string]Config),
|
||||
}
|
||||
}
|
||||
func ReadConfigFile(file string) ([]*Config, error) {
|
||||
c := &[]*Config{}
|
||||
f, err := os.ReadFile(file)
|
||||
if err != nil {
|
||||
return nil, fmt.Errorf("cannot read config file: %w", err)
|
||||
}
|
||||
if err := yaml.Unmarshal(f, c); err != nil {
|
||||
return nil, fmt.Errorf("cannot unmarshal config file: %w", err)
|
||||
}
|
||||
|
||||
return *c, nil
|
||||
}
|
||||
|
||||
func ReadConfig(file string) (*Config, error) {
|
||||
c := &Config{}
|
||||
f, err := os.ReadFile(file)
|
||||
if err != nil {
|
||||
return nil, fmt.Errorf("cannot read config file: %w", err)
|
||||
}
|
||||
if err := yaml.Unmarshal(f, c); err != nil {
|
||||
return nil, fmt.Errorf("cannot unmarshal config file: %w", err)
|
||||
}
|
||||
|
||||
return c, nil
|
||||
}
|
||||
|
||||
func (cm *ConfigLoader) LoadConfigFile(file string) error {
|
||||
cm.Lock()
|
||||
defer cm.Unlock()
|
||||
c, err := ReadConfigFile(file)
|
||||
if err != nil {
|
||||
return fmt.Errorf("cannot load config file: %w", err)
|
||||
}
|
||||
|
||||
for _, cc := range c {
|
||||
cm.configs[cc.Name] = *cc
|
||||
}
|
||||
return nil
|
||||
}
|
||||
|
||||
func (cm *ConfigLoader) LoadConfig(file string) error {
|
||||
cm.Lock()
|
||||
defer cm.Unlock()
|
||||
c, err := ReadConfig(file)
|
||||
if err != nil {
|
||||
return fmt.Errorf("cannot read config file: %w", err)
|
||||
}
|
||||
|
||||
cm.configs[c.Name] = *c
|
||||
return nil
|
||||
}
|
||||
|
||||
func (cm *ConfigLoader) GetConfig(m string) (Config, bool) {
|
||||
cm.Lock()
|
||||
defer cm.Unlock()
|
||||
v, exists := cm.configs[m]
|
||||
return v, exists
|
||||
}
|
||||
|
||||
func (cm *ConfigLoader) GetAllConfigs() []Config {
|
||||
cm.Lock()
|
||||
defer cm.Unlock()
|
||||
var res []Config
|
||||
for _, v := range cm.configs {
|
||||
res = append(res, v)
|
||||
}
|
||||
return res
|
||||
}
|
||||
|
||||
func (cm *ConfigLoader) ListConfigs() []string {
|
||||
cm.Lock()
|
||||
defer cm.Unlock()
|
||||
var res []string
|
||||
for k := range cm.configs {
|
||||
res = append(res, k)
|
||||
}
|
||||
return res
|
||||
}
|
||||
|
||||
func (cm *ConfigLoader) LoadConfigs(path string) error {
|
||||
cm.Lock()
|
||||
defer cm.Unlock()
|
||||
entries, err := os.ReadDir(path)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
files := make([]fs.FileInfo, 0, len(entries))
|
||||
for _, entry := range entries {
|
||||
info, err := entry.Info()
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
files = append(files, info)
|
||||
}
|
||||
for _, file := range files {
|
||||
// Skip templates, YAML and .keep files
|
||||
if !strings.Contains(file.Name(), ".yaml") {
|
||||
continue
|
||||
}
|
||||
c, err := ReadConfig(filepath.Join(path, file.Name()))
|
||||
if err == nil {
|
||||
cm.configs[c.Name] = *c
|
||||
}
|
||||
}
|
||||
|
||||
return nil
|
||||
}
|
||||
56
api/config/config_test.go
Normal file
56
api/config/config_test.go
Normal file
@@ -0,0 +1,56 @@
|
||||
package api_config_test
|
||||
|
||||
import (
|
||||
"os"
|
||||
|
||||
. "github.com/go-skynet/LocalAI/api/config"
|
||||
"github.com/go-skynet/LocalAI/api/options"
|
||||
"github.com/go-skynet/LocalAI/pkg/model"
|
||||
. "github.com/onsi/ginkgo/v2"
|
||||
. "github.com/onsi/gomega"
|
||||
)
|
||||
|
||||
var _ = Describe("Test cases for config related functions", func() {
|
||||
|
||||
var (
|
||||
configFile string
|
||||
)
|
||||
|
||||
Context("Test Read configuration functions", func() {
|
||||
configFile = os.Getenv("CONFIG_FILE")
|
||||
It("Test ReadConfigFile", func() {
|
||||
config, err := ReadConfigFile(configFile)
|
||||
Expect(err).To(BeNil())
|
||||
Expect(config).ToNot(BeNil())
|
||||
// two configs in config.yaml
|
||||
Expect(config[0].Name).To(Equal("list1"))
|
||||
Expect(config[1].Name).To(Equal("list2"))
|
||||
})
|
||||
|
||||
It("Test LoadConfigs", func() {
|
||||
cm := NewConfigLoader()
|
||||
opts := options.NewOptions()
|
||||
modelLoader := model.NewModelLoader(os.Getenv("MODELS_PATH"))
|
||||
options.WithModelLoader(modelLoader)(opts)
|
||||
|
||||
err := cm.LoadConfigs(opts.Loader.ModelPath)
|
||||
Expect(err).To(BeNil())
|
||||
Expect(cm.ListConfigs()).ToNot(BeNil())
|
||||
|
||||
// config should includes gpt4all models's api.config
|
||||
Expect(cm.ListConfigs()).To(ContainElements("gpt4all"))
|
||||
|
||||
// config should includes gpt2 models's api.config
|
||||
Expect(cm.ListConfigs()).To(ContainElements("gpt4all-2"))
|
||||
|
||||
// config should includes text-embedding-ada-002 models's api.config
|
||||
Expect(cm.ListConfigs()).To(ContainElements("text-embedding-ada-002"))
|
||||
|
||||
// config should includes rwkv_test models's api.config
|
||||
Expect(cm.ListConfigs()).To(ContainElements("rwkv_test"))
|
||||
|
||||
// config should includes whisper-1 models's api.config
|
||||
Expect(cm.ListConfigs()).To(ContainElements("whisper-1"))
|
||||
})
|
||||
})
|
||||
})
|
||||
50
api/config/prediction.go
Normal file
50
api/config/prediction.go
Normal file
@@ -0,0 +1,50 @@
|
||||
package api_config
|
||||
|
||||
type PredictionOptions struct {
|
||||
|
||||
// Also part of the OpenAI official spec
|
||||
Model string `json:"model" yaml:"model"`
|
||||
|
||||
// Also part of the OpenAI official spec
|
||||
Language string `json:"language"`
|
||||
|
||||
// Also part of the OpenAI official spec. use it for returning multiple results
|
||||
N int `json:"n"`
|
||||
|
||||
// Common options between all the API calls, part of the OpenAI spec
|
||||
TopP float64 `json:"top_p" yaml:"top_p"`
|
||||
TopK int `json:"top_k" yaml:"top_k"`
|
||||
Temperature float64 `json:"temperature" yaml:"temperature"`
|
||||
Maxtokens int `json:"max_tokens" yaml:"max_tokens"`
|
||||
Echo bool `json:"echo"`
|
||||
|
||||
// Custom parameters - not present in the OpenAI API
|
||||
Batch int `json:"batch" yaml:"batch"`
|
||||
F16 bool `json:"f16" yaml:"f16"`
|
||||
IgnoreEOS bool `json:"ignore_eos" yaml:"ignore_eos"`
|
||||
RepeatPenalty float64 `json:"repeat_penalty" yaml:"repeat_penalty"`
|
||||
Keep int `json:"n_keep" yaml:"n_keep"`
|
||||
|
||||
MirostatETA float64 `json:"mirostat_eta" yaml:"mirostat_eta"`
|
||||
MirostatTAU float64 `json:"mirostat_tau" yaml:"mirostat_tau"`
|
||||
Mirostat int `json:"mirostat" yaml:"mirostat"`
|
||||
|
||||
FrequencyPenalty float64 `json:"frequency_penalty" yaml:"frequency_penalty"`
|
||||
TFZ float64 `json:"tfz" yaml:"tfz"`
|
||||
|
||||
TypicalP float64 `json:"typical_p" yaml:"typical_p"`
|
||||
Seed int `json:"seed" yaml:"seed"`
|
||||
|
||||
NegativePrompt string `json:"negative_prompt" yaml:"negative_prompt"`
|
||||
RopeFreqBase float32 `json:"rope_freq_base" yaml:"rope_freq_base"`
|
||||
RopeFreqScale float32 `json:"rope_freq_scale" yaml:"rope_freq_scale"`
|
||||
NegativePromptScale float32 `json:"negative_prompt_scale" yaml:"negative_prompt_scale"`
|
||||
// AutoGPTQ
|
||||
UseFastTokenizer bool `json:"use_fast_tokenizer" yaml:"use_fast_tokenizer"`
|
||||
|
||||
// Diffusers
|
||||
ClipSkip int `json:"clip_skip" yaml:"clip_skip"`
|
||||
|
||||
// RWKV (?)
|
||||
Tokenizer string `json:"tokenizer" yaml:"tokenizer"`
|
||||
}
|
||||
233
api/gallery.go
233
api/gallery.go
@@ -1,233 +0,0 @@
|
||||
package api
|
||||
|
||||
import (
|
||||
"context"
|
||||
"encoding/json"
|
||||
"fmt"
|
||||
"io/ioutil"
|
||||
"net/http"
|
||||
"net/url"
|
||||
"os"
|
||||
"strings"
|
||||
"sync"
|
||||
|
||||
"github.com/go-skynet/LocalAI/pkg/gallery"
|
||||
"github.com/gofiber/fiber/v2"
|
||||
"github.com/google/uuid"
|
||||
"gopkg.in/yaml.v3"
|
||||
)
|
||||
|
||||
type galleryOp struct {
|
||||
req ApplyGalleryModelRequest
|
||||
id string
|
||||
}
|
||||
|
||||
type galleryOpStatus struct {
|
||||
Error error `json:"error"`
|
||||
Processed bool `json:"processed"`
|
||||
Message string `json:"message"`
|
||||
}
|
||||
|
||||
type galleryApplier struct {
|
||||
modelPath string
|
||||
sync.Mutex
|
||||
C chan galleryOp
|
||||
statuses map[string]*galleryOpStatus
|
||||
}
|
||||
|
||||
func newGalleryApplier(modelPath string) *galleryApplier {
|
||||
return &galleryApplier{
|
||||
modelPath: modelPath,
|
||||
C: make(chan galleryOp),
|
||||
statuses: make(map[string]*galleryOpStatus),
|
||||
}
|
||||
}
|
||||
|
||||
func applyGallery(modelPath string, req ApplyGalleryModelRequest, cm *ConfigMerger) error {
|
||||
url, err := req.DecodeURL()
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
|
||||
// Send a GET request to the URL
|
||||
response, err := http.Get(url)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
defer response.Body.Close()
|
||||
|
||||
// Read the response body
|
||||
body, err := ioutil.ReadAll(response.Body)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
|
||||
// Unmarshal YAML data into a Config struct
|
||||
var config gallery.Config
|
||||
err = yaml.Unmarshal(body, &config)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
|
||||
config.Files = append(config.Files, req.AdditionalFiles...)
|
||||
|
||||
if err := gallery.Apply(modelPath, req.Name, &config, req.Overrides); err != nil {
|
||||
return err
|
||||
}
|
||||
|
||||
// Reload models
|
||||
return cm.LoadConfigs(modelPath)
|
||||
}
|
||||
|
||||
func (g *galleryApplier) updatestatus(s string, op *galleryOpStatus) {
|
||||
g.Lock()
|
||||
defer g.Unlock()
|
||||
g.statuses[s] = op
|
||||
}
|
||||
|
||||
func (g *galleryApplier) getstatus(s string) *galleryOpStatus {
|
||||
g.Lock()
|
||||
defer g.Unlock()
|
||||
|
||||
return g.statuses[s]
|
||||
}
|
||||
|
||||
func (g *galleryApplier) start(c context.Context, cm *ConfigMerger) {
|
||||
go func() {
|
||||
for {
|
||||
select {
|
||||
case <-c.Done():
|
||||
return
|
||||
case op := <-g.C:
|
||||
g.updatestatus(op.id, &galleryOpStatus{Message: "processing"})
|
||||
|
||||
updateError := func(e error) {
|
||||
g.updatestatus(op.id, &galleryOpStatus{Error: e, Processed: true})
|
||||
}
|
||||
|
||||
if err := applyGallery(g.modelPath, op.req, cm); err != nil {
|
||||
updateError(err)
|
||||
continue
|
||||
}
|
||||
|
||||
g.updatestatus(op.id, &galleryOpStatus{Processed: true, Message: "completed"})
|
||||
}
|
||||
}
|
||||
}()
|
||||
}
|
||||
|
||||
func ApplyGalleryFromFile(modelPath, s string, cm *ConfigMerger) error {
|
||||
dat, err := os.ReadFile(s)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
var requests []ApplyGalleryModelRequest
|
||||
err = json.Unmarshal(dat, &requests)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
|
||||
for _, r := range requests {
|
||||
if err := applyGallery(modelPath, r, cm); err != nil {
|
||||
return err
|
||||
}
|
||||
}
|
||||
|
||||
return nil
|
||||
}
|
||||
func ApplyGalleryFromString(modelPath, s string, cm *ConfigMerger) error {
|
||||
var requests []ApplyGalleryModelRequest
|
||||
err := json.Unmarshal([]byte(s), &requests)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
|
||||
for _, r := range requests {
|
||||
if err := applyGallery(modelPath, r, cm); err != nil {
|
||||
return err
|
||||
}
|
||||
}
|
||||
|
||||
return nil
|
||||
}
|
||||
|
||||
// endpoints
|
||||
|
||||
type ApplyGalleryModelRequest struct {
|
||||
URL string `json:"url"`
|
||||
Name string `json:"name"`
|
||||
Overrides map[string]interface{} `json:"overrides"`
|
||||
AdditionalFiles []gallery.File `json:"files"`
|
||||
}
|
||||
|
||||
const (
|
||||
githubURI = "github:"
|
||||
)
|
||||
|
||||
func (request ApplyGalleryModelRequest) DecodeURL() (string, error) {
|
||||
input := request.URL
|
||||
var rawURL string
|
||||
|
||||
if strings.HasPrefix(input, githubURI) {
|
||||
parts := strings.Split(input, ":")
|
||||
repoParts := strings.Split(parts[1], "@")
|
||||
branch := "main"
|
||||
|
||||
if len(repoParts) > 1 {
|
||||
branch = repoParts[1]
|
||||
}
|
||||
|
||||
repoPath := strings.Split(repoParts[0], "/")
|
||||
org := repoPath[0]
|
||||
project := repoPath[1]
|
||||
projectPath := strings.Join(repoPath[2:], "/")
|
||||
|
||||
rawURL = fmt.Sprintf("https://raw.githubusercontent.com/%s/%s/%s/%s", org, project, branch, projectPath)
|
||||
} else if strings.HasPrefix(input, "http://") || strings.HasPrefix(input, "https://") {
|
||||
// Handle regular URLs
|
||||
u, err := url.Parse(input)
|
||||
if err != nil {
|
||||
return "", fmt.Errorf("invalid URL: %w", err)
|
||||
}
|
||||
rawURL = u.String()
|
||||
} else {
|
||||
return "", fmt.Errorf("invalid URL format")
|
||||
}
|
||||
|
||||
return rawURL, nil
|
||||
}
|
||||
|
||||
func getOpStatus(g *galleryApplier) func(c *fiber.Ctx) error {
|
||||
return func(c *fiber.Ctx) error {
|
||||
|
||||
status := g.getstatus(c.Params("uuid"))
|
||||
if status == nil {
|
||||
return fmt.Errorf("could not find any status for ID")
|
||||
}
|
||||
|
||||
return c.JSON(status)
|
||||
}
|
||||
}
|
||||
|
||||
func applyModelGallery(modelPath string, cm *ConfigMerger, g chan galleryOp) func(c *fiber.Ctx) error {
|
||||
return func(c *fiber.Ctx) error {
|
||||
input := new(ApplyGalleryModelRequest)
|
||||
// Get input data from the request body
|
||||
if err := c.BodyParser(input); err != nil {
|
||||
return err
|
||||
}
|
||||
|
||||
uuid, err := uuid.NewUUID()
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
g <- galleryOp{
|
||||
req: *input,
|
||||
id: uuid.String(),
|
||||
}
|
||||
return c.JSON(struct {
|
||||
ID string `json:"uuid"`
|
||||
StatusURL string `json:"status"`
|
||||
}{ID: uuid.String(), StatusURL: c.BaseURL() + "/models/jobs/" + uuid.String()})
|
||||
}
|
||||
}
|
||||
@@ -1,30 +0,0 @@
|
||||
package api_test
|
||||
|
||||
import (
|
||||
. "github.com/go-skynet/LocalAI/api"
|
||||
. "github.com/onsi/ginkgo/v2"
|
||||
. "github.com/onsi/gomega"
|
||||
)
|
||||
|
||||
var _ = Describe("Gallery API tests", func() {
|
||||
Context("requests", func() {
|
||||
It("parses github with a branch", func() {
|
||||
req := ApplyGalleryModelRequest{URL: "github:go-skynet/model-gallery/gpt4all-j.yaml@main"}
|
||||
str, err := req.DecodeURL()
|
||||
Expect(err).ToNot(HaveOccurred())
|
||||
Expect(str).To(Equal("https://raw.githubusercontent.com/go-skynet/model-gallery/main/gpt4all-j.yaml"))
|
||||
})
|
||||
It("parses github without a branch", func() {
|
||||
req := ApplyGalleryModelRequest{URL: "github:go-skynet/model-gallery/gpt4all-j.yaml"}
|
||||
str, err := req.DecodeURL()
|
||||
Expect(err).ToNot(HaveOccurred())
|
||||
Expect(str).To(Equal("https://raw.githubusercontent.com/go-skynet/model-gallery/main/gpt4all-j.yaml"))
|
||||
})
|
||||
It("parses URLS", func() {
|
||||
req := ApplyGalleryModelRequest{URL: "https://raw.githubusercontent.com/go-skynet/model-gallery/main/gpt4all-j.yaml"}
|
||||
str, err := req.DecodeURL()
|
||||
Expect(err).ToNot(HaveOccurred())
|
||||
Expect(str).To(Equal("https://raw.githubusercontent.com/go-skynet/model-gallery/main/gpt4all-j.yaml"))
|
||||
})
|
||||
})
|
||||
})
|
||||
163
api/localai/backend_monitor.go
Normal file
163
api/localai/backend_monitor.go
Normal file
@@ -0,0 +1,163 @@
|
||||
package localai
|
||||
|
||||
import (
|
||||
"context"
|
||||
"fmt"
|
||||
"strings"
|
||||
|
||||
config "github.com/go-skynet/LocalAI/api/config"
|
||||
"github.com/go-skynet/LocalAI/pkg/grpc/proto"
|
||||
|
||||
"github.com/go-skynet/LocalAI/api/options"
|
||||
"github.com/gofiber/fiber/v2"
|
||||
"github.com/rs/zerolog/log"
|
||||
|
||||
gopsutil "github.com/shirou/gopsutil/v3/process"
|
||||
)
|
||||
|
||||
type BackendMonitorRequest struct {
|
||||
Model string `json:"model" yaml:"model"`
|
||||
}
|
||||
|
||||
type BackendMonitorResponse struct {
|
||||
MemoryInfo *gopsutil.MemoryInfoStat
|
||||
MemoryPercent float32
|
||||
CPUPercent float64
|
||||
}
|
||||
|
||||
type BackendMonitor struct {
|
||||
configLoader *config.ConfigLoader
|
||||
options *options.Option // Taking options in case we need to inspect ExternalGRPCBackends, though that's out of scope for now, hence the name.
|
||||
}
|
||||
|
||||
func NewBackendMonitor(configLoader *config.ConfigLoader, options *options.Option) BackendMonitor {
|
||||
return BackendMonitor{
|
||||
configLoader: configLoader,
|
||||
options: options,
|
||||
}
|
||||
}
|
||||
|
||||
func (bm *BackendMonitor) SampleLocalBackendProcess(model string) (*BackendMonitorResponse, error) {
|
||||
config, exists := bm.configLoader.GetConfig(model)
|
||||
var backend string
|
||||
if exists {
|
||||
backend = config.Model
|
||||
} else {
|
||||
// Last ditch effort: use it raw, see if a backend happens to match.
|
||||
backend = model
|
||||
}
|
||||
|
||||
if !strings.HasSuffix(backend, ".bin") {
|
||||
backend = fmt.Sprintf("%s.bin", backend)
|
||||
}
|
||||
|
||||
pid, err := bm.options.Loader.GetGRPCPID(backend)
|
||||
|
||||
if err != nil {
|
||||
log.Error().Msgf("model %s : failed to find pid %+v", model, err)
|
||||
return nil, err
|
||||
}
|
||||
|
||||
// Name is slightly frightening but this does _not_ create a new process, rather it looks up an existing process by PID.
|
||||
backendProcess, err := gopsutil.NewProcess(int32(pid))
|
||||
|
||||
if err != nil {
|
||||
log.Error().Msgf("model %s [PID %d] : error getting process info %+v", model, pid, err)
|
||||
return nil, err
|
||||
}
|
||||
|
||||
memInfo, err := backendProcess.MemoryInfo()
|
||||
|
||||
if err != nil {
|
||||
log.Error().Msgf("model %s [PID %d] : error getting memory info %+v", model, pid, err)
|
||||
return nil, err
|
||||
}
|
||||
|
||||
memPercent, err := backendProcess.MemoryPercent()
|
||||
if err != nil {
|
||||
log.Error().Msgf("model %s [PID %d] : error getting memory percent %+v", model, pid, err)
|
||||
return nil, err
|
||||
}
|
||||
|
||||
cpuPercent, err := backendProcess.CPUPercent()
|
||||
if err != nil {
|
||||
log.Error().Msgf("model %s [PID %d] : error getting cpu percent %+v", model, pid, err)
|
||||
return nil, err
|
||||
}
|
||||
|
||||
return &BackendMonitorResponse{
|
||||
MemoryInfo: memInfo,
|
||||
MemoryPercent: memPercent,
|
||||
CPUPercent: cpuPercent,
|
||||
}, nil
|
||||
}
|
||||
|
||||
func (bm BackendMonitor) getModelLoaderIDFromCtx(c *fiber.Ctx) (string, error) {
|
||||
input := new(BackendMonitorRequest)
|
||||
// Get input data from the request body
|
||||
if err := c.BodyParser(input); err != nil {
|
||||
return "", err
|
||||
}
|
||||
|
||||
config, exists := bm.configLoader.GetConfig(input.Model)
|
||||
var backendId string
|
||||
if exists {
|
||||
backendId = config.Model
|
||||
} else {
|
||||
// Last ditch effort: use it raw, see if a backend happens to match.
|
||||
backendId = input.Model
|
||||
}
|
||||
|
||||
if !strings.HasSuffix(backendId, ".bin") {
|
||||
backendId = fmt.Sprintf("%s.bin", backendId)
|
||||
}
|
||||
|
||||
return backendId, nil
|
||||
}
|
||||
|
||||
func BackendMonitorEndpoint(bm BackendMonitor) func(c *fiber.Ctx) error {
|
||||
return func(c *fiber.Ctx) error {
|
||||
|
||||
backendId, err := bm.getModelLoaderIDFromCtx(c)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
|
||||
client := bm.options.Loader.CheckIsLoaded(backendId)
|
||||
|
||||
if client == nil {
|
||||
return fmt.Errorf("backend %s is not currently loaded", backendId)
|
||||
}
|
||||
|
||||
status, rpcErr := client.Status(context.TODO())
|
||||
if rpcErr != nil {
|
||||
log.Warn().Msgf("backend %s experienced an error retrieving status info: %s", backendId, rpcErr.Error())
|
||||
val, slbErr := bm.SampleLocalBackendProcess(backendId)
|
||||
if slbErr != nil {
|
||||
return fmt.Errorf("backend %s experienced an error retrieving status info via rpc: %s, then failed local node process sample: %s", backendId, rpcErr.Error(), slbErr.Error())
|
||||
}
|
||||
return c.JSON(proto.StatusResponse{
|
||||
State: proto.StatusResponse_ERROR,
|
||||
Memory: &proto.MemoryUsageData{
|
||||
Total: val.MemoryInfo.VMS,
|
||||
Breakdown: map[string]uint64{
|
||||
"gopsutil-RSS": val.MemoryInfo.RSS,
|
||||
},
|
||||
},
|
||||
})
|
||||
}
|
||||
|
||||
return c.JSON(status)
|
||||
}
|
||||
}
|
||||
|
||||
func BackendShutdownEndpoint(bm BackendMonitor) func(c *fiber.Ctx) error {
|
||||
return func(c *fiber.Ctx) error {
|
||||
backendId, err := bm.getModelLoaderIDFromCtx(c)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
|
||||
return bm.options.Loader.ShutdownModel(backendId)
|
||||
}
|
||||
}
|
||||
241
api/localai/gallery.go
Normal file
241
api/localai/gallery.go
Normal file
@@ -0,0 +1,241 @@
|
||||
package localai
|
||||
|
||||
import (
|
||||
"context"
|
||||
"fmt"
|
||||
"os"
|
||||
"strings"
|
||||
"sync"
|
||||
|
||||
json "github.com/json-iterator/go"
|
||||
"gopkg.in/yaml.v3"
|
||||
|
||||
config "github.com/go-skynet/LocalAI/api/config"
|
||||
"github.com/go-skynet/LocalAI/pkg/gallery"
|
||||
"github.com/go-skynet/LocalAI/pkg/utils"
|
||||
|
||||
"github.com/gofiber/fiber/v2"
|
||||
"github.com/google/uuid"
|
||||
"github.com/rs/zerolog/log"
|
||||
)
|
||||
|
||||
type galleryOp struct {
|
||||
req gallery.GalleryModel
|
||||
id string
|
||||
galleries []gallery.Gallery
|
||||
galleryName string
|
||||
}
|
||||
|
||||
type galleryOpStatus struct {
|
||||
Error error `json:"error"`
|
||||
Processed bool `json:"processed"`
|
||||
Message string `json:"message"`
|
||||
Progress float64 `json:"progress"`
|
||||
TotalFileSize string `json:"file_size"`
|
||||
DownloadedFileSize string `json:"downloaded_size"`
|
||||
}
|
||||
|
||||
type galleryApplier struct {
|
||||
modelPath string
|
||||
sync.Mutex
|
||||
C chan galleryOp
|
||||
statuses map[string]*galleryOpStatus
|
||||
}
|
||||
|
||||
func NewGalleryService(modelPath string) *galleryApplier {
|
||||
return &galleryApplier{
|
||||
modelPath: modelPath,
|
||||
C: make(chan galleryOp),
|
||||
statuses: make(map[string]*galleryOpStatus),
|
||||
}
|
||||
}
|
||||
|
||||
// prepareModel applies a
|
||||
func prepareModel(modelPath string, req gallery.GalleryModel, cm *config.ConfigLoader, downloadStatus func(string, string, string, float64)) error {
|
||||
|
||||
config, err := gallery.GetGalleryConfigFromURL(req.URL)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
|
||||
config.Files = append(config.Files, req.AdditionalFiles...)
|
||||
|
||||
return gallery.InstallModel(modelPath, req.Name, &config, req.Overrides, downloadStatus)
|
||||
}
|
||||
|
||||
func (g *galleryApplier) updateStatus(s string, op *galleryOpStatus) {
|
||||
g.Lock()
|
||||
defer g.Unlock()
|
||||
g.statuses[s] = op
|
||||
}
|
||||
|
||||
func (g *galleryApplier) getStatus(s string) *galleryOpStatus {
|
||||
g.Lock()
|
||||
defer g.Unlock()
|
||||
|
||||
return g.statuses[s]
|
||||
}
|
||||
|
||||
func (g *galleryApplier) Start(c context.Context, cm *config.ConfigLoader) {
|
||||
go func() {
|
||||
for {
|
||||
select {
|
||||
case <-c.Done():
|
||||
return
|
||||
case op := <-g.C:
|
||||
utils.ResetDownloadTimers()
|
||||
|
||||
g.updateStatus(op.id, &galleryOpStatus{Message: "processing", Progress: 0})
|
||||
|
||||
// updates the status with an error
|
||||
updateError := func(e error) {
|
||||
g.updateStatus(op.id, &galleryOpStatus{Error: e, Processed: true, Message: "error: " + e.Error()})
|
||||
}
|
||||
|
||||
// displayDownload displays the download progress
|
||||
progressCallback := func(fileName string, current string, total string, percentage float64) {
|
||||
g.updateStatus(op.id, &galleryOpStatus{Message: "processing", Progress: percentage, TotalFileSize: total, DownloadedFileSize: current})
|
||||
utils.DisplayDownloadFunction(fileName, current, total, percentage)
|
||||
}
|
||||
|
||||
var err error
|
||||
// if the request contains a gallery name, we apply the gallery from the gallery list
|
||||
if op.galleryName != "" {
|
||||
if strings.Contains(op.galleryName, "@") {
|
||||
err = gallery.InstallModelFromGallery(op.galleries, op.galleryName, g.modelPath, op.req, progressCallback)
|
||||
} else {
|
||||
err = gallery.InstallModelFromGalleryByName(op.galleries, op.galleryName, g.modelPath, op.req, progressCallback)
|
||||
}
|
||||
} else {
|
||||
err = prepareModel(g.modelPath, op.req, cm, progressCallback)
|
||||
}
|
||||
|
||||
if err != nil {
|
||||
updateError(err)
|
||||
continue
|
||||
}
|
||||
|
||||
// Reload models
|
||||
err = cm.LoadConfigs(g.modelPath)
|
||||
if err != nil {
|
||||
updateError(err)
|
||||
continue
|
||||
}
|
||||
|
||||
g.updateStatus(op.id, &galleryOpStatus{Processed: true, Message: "completed", Progress: 100})
|
||||
}
|
||||
}
|
||||
}()
|
||||
}
|
||||
|
||||
type galleryModel struct {
|
||||
gallery.GalleryModel `yaml:",inline"` // https://github.com/go-yaml/yaml/issues/63
|
||||
ID string `json:"id"`
|
||||
}
|
||||
|
||||
func processRequests(modelPath, s string, cm *config.ConfigLoader, galleries []gallery.Gallery, requests []galleryModel) error {
|
||||
var err error
|
||||
for _, r := range requests {
|
||||
utils.ResetDownloadTimers()
|
||||
if r.ID == "" {
|
||||
err = prepareModel(modelPath, r.GalleryModel, cm, utils.DisplayDownloadFunction)
|
||||
} else {
|
||||
if strings.Contains(r.ID, "@") {
|
||||
err = gallery.InstallModelFromGallery(
|
||||
galleries, r.ID, modelPath, r.GalleryModel, utils.DisplayDownloadFunction)
|
||||
} else {
|
||||
err = gallery.InstallModelFromGalleryByName(
|
||||
galleries, r.ID, modelPath, r.GalleryModel, utils.DisplayDownloadFunction)
|
||||
}
|
||||
}
|
||||
}
|
||||
return err
|
||||
}
|
||||
|
||||
func ApplyGalleryFromFile(modelPath, s string, cm *config.ConfigLoader, galleries []gallery.Gallery) error {
|
||||
dat, err := os.ReadFile(s)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
var requests []galleryModel
|
||||
|
||||
if err := yaml.Unmarshal(dat, &requests); err != nil {
|
||||
return err
|
||||
}
|
||||
|
||||
return processRequests(modelPath, s, cm, galleries, requests)
|
||||
}
|
||||
|
||||
func ApplyGalleryFromString(modelPath, s string, cm *config.ConfigLoader, galleries []gallery.Gallery) error {
|
||||
var requests []galleryModel
|
||||
err := json.Unmarshal([]byte(s), &requests)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
|
||||
return processRequests(modelPath, s, cm, galleries, requests)
|
||||
}
|
||||
|
||||
/// Endpoints
|
||||
|
||||
func GetOpStatusEndpoint(g *galleryApplier) func(c *fiber.Ctx) error {
|
||||
return func(c *fiber.Ctx) error {
|
||||
|
||||
status := g.getStatus(c.Params("uuid"))
|
||||
if status == nil {
|
||||
return fmt.Errorf("could not find any status for ID")
|
||||
}
|
||||
|
||||
return c.JSON(status)
|
||||
}
|
||||
}
|
||||
|
||||
type GalleryModel struct {
|
||||
ID string `json:"id"`
|
||||
gallery.GalleryModel
|
||||
}
|
||||
|
||||
func ApplyModelGalleryEndpoint(modelPath string, cm *config.ConfigLoader, g chan galleryOp, galleries []gallery.Gallery) func(c *fiber.Ctx) error {
|
||||
return func(c *fiber.Ctx) error {
|
||||
input := new(GalleryModel)
|
||||
// Get input data from the request body
|
||||
if err := c.BodyParser(input); err != nil {
|
||||
return err
|
||||
}
|
||||
|
||||
uuid, err := uuid.NewUUID()
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
g <- galleryOp{
|
||||
req: input.GalleryModel,
|
||||
id: uuid.String(),
|
||||
galleryName: input.ID,
|
||||
galleries: galleries,
|
||||
}
|
||||
return c.JSON(struct {
|
||||
ID string `json:"uuid"`
|
||||
StatusURL string `json:"status"`
|
||||
}{ID: uuid.String(), StatusURL: c.BaseURL() + "/models/jobs/" + uuid.String()})
|
||||
}
|
||||
}
|
||||
|
||||
func ListModelFromGalleryEndpoint(galleries []gallery.Gallery, basePath string) func(c *fiber.Ctx) error {
|
||||
return func(c *fiber.Ctx) error {
|
||||
log.Debug().Msgf("Listing models from galleries: %+v", galleries)
|
||||
|
||||
models, err := gallery.AvailableGalleryModels(galleries, basePath)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
log.Debug().Msgf("Models found from galleries: %+v", models)
|
||||
for _, m := range models {
|
||||
log.Debug().Msgf("Model found from galleries: %+v", m)
|
||||
}
|
||||
dat, err := json.Marshal(models)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
return c.Send(dat)
|
||||
}
|
||||
}
|
||||
32
api/localai/localai.go
Normal file
32
api/localai/localai.go
Normal file
@@ -0,0 +1,32 @@
|
||||
package localai
|
||||
|
||||
import (
|
||||
"github.com/go-skynet/LocalAI/api/backend"
|
||||
config "github.com/go-skynet/LocalAI/api/config"
|
||||
|
||||
"github.com/go-skynet/LocalAI/api/options"
|
||||
"github.com/gofiber/fiber/v2"
|
||||
)
|
||||
|
||||
type TTSRequest struct {
|
||||
Model string `json:"model" yaml:"model"`
|
||||
Input string `json:"input" yaml:"input"`
|
||||
Backend string `json:"backend" yaml:"backend"`
|
||||
}
|
||||
|
||||
func TTSEndpoint(cm *config.ConfigLoader, o *options.Option) func(c *fiber.Ctx) error {
|
||||
return func(c *fiber.Ctx) error {
|
||||
|
||||
input := new(TTSRequest)
|
||||
// Get input data from the request body
|
||||
if err := c.BodyParser(input); err != nil {
|
||||
return err
|
||||
}
|
||||
|
||||
filePath, _, err := backend.ModelTTS(input.Backend, input.Input, input.Model, o.Loader, o)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
return c.Download(filePath)
|
||||
}
|
||||
}
|
||||
678
api/openai.go
678
api/openai.go
@@ -1,678 +0,0 @@
|
||||
package api
|
||||
|
||||
import (
|
||||
"bufio"
|
||||
"bytes"
|
||||
"encoding/base64"
|
||||
"encoding/json"
|
||||
"fmt"
|
||||
"io"
|
||||
"io/ioutil"
|
||||
"net/http"
|
||||
"os"
|
||||
"path"
|
||||
"path/filepath"
|
||||
"strconv"
|
||||
"strings"
|
||||
|
||||
"github.com/ggerganov/whisper.cpp/bindings/go/pkg/whisper"
|
||||
model "github.com/go-skynet/LocalAI/pkg/model"
|
||||
whisperutil "github.com/go-skynet/LocalAI/pkg/whisper"
|
||||
llama "github.com/go-skynet/go-llama.cpp"
|
||||
"github.com/gofiber/fiber/v2"
|
||||
"github.com/rs/zerolog/log"
|
||||
"github.com/valyala/fasthttp"
|
||||
)
|
||||
|
||||
// APIError provides error information returned by the OpenAI API.
|
||||
type APIError struct {
|
||||
Code any `json:"code,omitempty"`
|
||||
Message string `json:"message"`
|
||||
Param *string `json:"param,omitempty"`
|
||||
Type string `json:"type"`
|
||||
}
|
||||
|
||||
type ErrorResponse struct {
|
||||
Error *APIError `json:"error,omitempty"`
|
||||
}
|
||||
|
||||
type OpenAIUsage struct {
|
||||
PromptTokens int `json:"prompt_tokens"`
|
||||
CompletionTokens int `json:"completion_tokens"`
|
||||
TotalTokens int `json:"total_tokens"`
|
||||
}
|
||||
|
||||
type Item struct {
|
||||
Embedding []float32 `json:"embedding"`
|
||||
Index int `json:"index"`
|
||||
Object string `json:"object,omitempty"`
|
||||
|
||||
// Images
|
||||
URL string `json:"url,omitempty"`
|
||||
B64JSON string `json:"b64_json,omitempty"`
|
||||
}
|
||||
|
||||
type OpenAIResponse struct {
|
||||
Created int `json:"created,omitempty"`
|
||||
Object string `json:"object,omitempty"`
|
||||
ID string `json:"id,omitempty"`
|
||||
Model string `json:"model,omitempty"`
|
||||
Choices []Choice `json:"choices,omitempty"`
|
||||
Data []Item `json:"data,omitempty"`
|
||||
|
||||
Usage OpenAIUsage `json:"usage"`
|
||||
}
|
||||
|
||||
type Choice struct {
|
||||
Index int `json:"index,omitempty"`
|
||||
FinishReason string `json:"finish_reason,omitempty"`
|
||||
Message *Message `json:"message,omitempty"`
|
||||
Delta *Message `json:"delta,omitempty"`
|
||||
Text string `json:"text,omitempty"`
|
||||
}
|
||||
|
||||
type Message struct {
|
||||
Role string `json:"role,omitempty" yaml:"role"`
|
||||
Content string `json:"content,omitempty" yaml:"content"`
|
||||
}
|
||||
|
||||
type OpenAIModel struct {
|
||||
ID string `json:"id"`
|
||||
Object string `json:"object"`
|
||||
}
|
||||
|
||||
type OpenAIRequest struct {
|
||||
Model string `json:"model" yaml:"model"`
|
||||
|
||||
// whisper
|
||||
File string `json:"file" validate:"required"`
|
||||
Language string `json:"language"`
|
||||
//whisper/image
|
||||
ResponseFormat string `json:"response_format"`
|
||||
// image
|
||||
Size string `json:"size"`
|
||||
// Prompt is read only by completion/image API calls
|
||||
Prompt interface{} `json:"prompt" yaml:"prompt"`
|
||||
|
||||
// Edit endpoint
|
||||
Instruction string `json:"instruction" yaml:"instruction"`
|
||||
Input interface{} `json:"input" yaml:"input"`
|
||||
|
||||
Stop interface{} `json:"stop" yaml:"stop"`
|
||||
|
||||
// Messages is read only by chat/completion API calls
|
||||
Messages []Message `json:"messages" yaml:"messages"`
|
||||
|
||||
Stream bool `json:"stream"`
|
||||
Echo bool `json:"echo"`
|
||||
// Common options between all the API calls
|
||||
TopP float64 `json:"top_p" yaml:"top_p"`
|
||||
TopK int `json:"top_k" yaml:"top_k"`
|
||||
Temperature float64 `json:"temperature" yaml:"temperature"`
|
||||
Maxtokens int `json:"max_tokens" yaml:"max_tokens"`
|
||||
|
||||
N int `json:"n"`
|
||||
|
||||
// Custom parameters - not present in the OpenAI API
|
||||
Batch int `json:"batch" yaml:"batch"`
|
||||
F16 bool `json:"f16" yaml:"f16"`
|
||||
IgnoreEOS bool `json:"ignore_eos" yaml:"ignore_eos"`
|
||||
RepeatPenalty float64 `json:"repeat_penalty" yaml:"repeat_penalty"`
|
||||
Keep int `json:"n_keep" yaml:"n_keep"`
|
||||
|
||||
MirostatETA float64 `json:"mirostat_eta" yaml:"mirostat_eta"`
|
||||
MirostatTAU float64 `json:"mirostat_tau" yaml:"mirostat_tau"`
|
||||
Mirostat int `json:"mirostat" yaml:"mirostat"`
|
||||
|
||||
Seed int `json:"seed" yaml:"seed"`
|
||||
|
||||
// Image (not supported by OpenAI)
|
||||
Mode int `json:"mode"`
|
||||
Step int `json:"step"`
|
||||
}
|
||||
|
||||
func defaultRequest(modelFile string) OpenAIRequest {
|
||||
return OpenAIRequest{
|
||||
TopP: 0.7,
|
||||
TopK: 80,
|
||||
Maxtokens: 512,
|
||||
Temperature: 0.9,
|
||||
Model: modelFile,
|
||||
}
|
||||
}
|
||||
|
||||
// https://platform.openai.com/docs/api-reference/completions
|
||||
func completionEndpoint(cm *ConfigMerger, o *Option) func(c *fiber.Ctx) error {
|
||||
return func(c *fiber.Ctx) error {
|
||||
|
||||
model, input, err := readInput(c, o.loader, true)
|
||||
if err != nil {
|
||||
return fmt.Errorf("failed reading parameters from request:%w", err)
|
||||
}
|
||||
|
||||
config, input, err := readConfig(model, input, cm, o.loader, o.debug, o.threads, o.ctxSize, o.f16)
|
||||
if err != nil {
|
||||
return fmt.Errorf("failed reading parameters from request:%w", err)
|
||||
}
|
||||
|
||||
log.Debug().Msgf("Parameter Config: %+v", config)
|
||||
|
||||
templateFile := config.Model
|
||||
|
||||
if config.TemplateConfig.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 := o.loader.TemplatePrefix(templateFile, struct {
|
||||
Input string
|
||||
}{Input: i})
|
||||
if err == nil {
|
||||
i = templatedInput
|
||||
log.Debug().Msgf("Template found, input modified to: %s", i)
|
||||
}
|
||||
|
||||
r, err := ComputeChoices(i, input, config, o.loader, func(s string, c *[]Choice) {
|
||||
*c = append(*c, Choice{Text: s})
|
||||
}, nil)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
|
||||
result = append(result, r...)
|
||||
}
|
||||
|
||||
resp := &OpenAIResponse{
|
||||
Model: input.Model, // we have to return what the user sent here, due to OpenAI spec.
|
||||
Choices: result,
|
||||
Object: "text_completion",
|
||||
}
|
||||
|
||||
jsonResult, _ := json.Marshal(resp)
|
||||
log.Debug().Msgf("Response: %s", jsonResult)
|
||||
|
||||
// Return the prediction in the response body
|
||||
return c.JSON(resp)
|
||||
}
|
||||
}
|
||||
|
||||
// https://platform.openai.com/docs/api-reference/embeddings
|
||||
func embeddingsEndpoint(cm *ConfigMerger, o *Option) func(c *fiber.Ctx) error {
|
||||
return func(c *fiber.Ctx) error {
|
||||
model, input, err := readInput(c, o.loader, true)
|
||||
if err != nil {
|
||||
return fmt.Errorf("failed reading parameters from request:%w", err)
|
||||
}
|
||||
|
||||
config, input, err := readConfig(model, input, cm, o.loader, o.debug, o.threads, o.ctxSize, o.f16)
|
||||
if err != nil {
|
||||
return fmt.Errorf("failed reading parameters from request:%w", err)
|
||||
}
|
||||
|
||||
log.Debug().Msgf("Parameter Config: %+v", config)
|
||||
items := []Item{}
|
||||
|
||||
for i, s := range config.InputToken {
|
||||
// get the model function to call for the result
|
||||
embedFn, err := ModelEmbedding("", s, o.loader, *config)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
|
||||
embeddings, err := embedFn()
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
items = append(items, Item{Embedding: embeddings, Index: i, Object: "embedding"})
|
||||
}
|
||||
|
||||
for i, s := range config.InputStrings {
|
||||
// get the model function to call for the result
|
||||
embedFn, err := ModelEmbedding(s, []int{}, o.loader, *config)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
|
||||
embeddings, err := embedFn()
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
items = append(items, Item{Embedding: embeddings, Index: i, Object: "embedding"})
|
||||
}
|
||||
|
||||
resp := &OpenAIResponse{
|
||||
Model: input.Model, // we have to return what the user sent here, due to OpenAI spec.
|
||||
Data: items,
|
||||
Object: "list",
|
||||
}
|
||||
|
||||
jsonResult, _ := json.Marshal(resp)
|
||||
log.Debug().Msgf("Response: %s", jsonResult)
|
||||
|
||||
// Return the prediction in the response body
|
||||
return c.JSON(resp)
|
||||
}
|
||||
}
|
||||
|
||||
func chatEndpoint(cm *ConfigMerger, o *Option) func(c *fiber.Ctx) error {
|
||||
|
||||
process := func(s string, req *OpenAIRequest, config *Config, loader *model.ModelLoader, responses chan OpenAIResponse) {
|
||||
initialMessage := OpenAIResponse{
|
||||
Model: req.Model, // we have to return what the user sent here, due to OpenAI spec.
|
||||
Choices: []Choice{{Delta: &Message{Role: "assistant"}}},
|
||||
Object: "chat.completion.chunk",
|
||||
}
|
||||
responses <- initialMessage
|
||||
|
||||
ComputeChoices(s, req, config, loader, func(s string, c *[]Choice) {}, func(s string) bool {
|
||||
resp := OpenAIResponse{
|
||||
Model: req.Model, // we have to return what the user sent here, due to OpenAI spec.
|
||||
Choices: []Choice{{Delta: &Message{Content: s}}},
|
||||
Object: "chat.completion.chunk",
|
||||
}
|
||||
log.Debug().Msgf("Sending goroutine: %s", s)
|
||||
|
||||
responses <- resp
|
||||
return true
|
||||
})
|
||||
close(responses)
|
||||
}
|
||||
return func(c *fiber.Ctx) error {
|
||||
model, input, err := readInput(c, o.loader, true)
|
||||
if err != nil {
|
||||
return fmt.Errorf("failed reading parameters from request:%w", err)
|
||||
}
|
||||
|
||||
config, input, err := readConfig(model, input, cm, o.loader, o.debug, o.threads, o.ctxSize, o.f16)
|
||||
if err != nil {
|
||||
return fmt.Errorf("failed reading parameters from request:%w", err)
|
||||
}
|
||||
|
||||
log.Debug().Msgf("Parameter Config: %+v", config)
|
||||
|
||||
var predInput string
|
||||
|
||||
mess := []string{}
|
||||
for _, i := range input.Messages {
|
||||
var content string
|
||||
r := config.Roles[i.Role]
|
||||
if r != "" {
|
||||
content = fmt.Sprint(r, " ", i.Content)
|
||||
} else {
|
||||
content = i.Content
|
||||
}
|
||||
|
||||
mess = append(mess, content)
|
||||
}
|
||||
|
||||
predInput = strings.Join(mess, "\n")
|
||||
|
||||
if input.Stream {
|
||||
log.Debug().Msgf("Stream request received")
|
||||
c.Context().SetContentType("text/event-stream")
|
||||
//c.Response().Header.SetContentType(fiber.MIMETextHTMLCharsetUTF8)
|
||||
// c.Set("Content-Type", "text/event-stream")
|
||||
c.Set("Cache-Control", "no-cache")
|
||||
c.Set("Connection", "keep-alive")
|
||||
c.Set("Transfer-Encoding", "chunked")
|
||||
}
|
||||
|
||||
templateFile := config.Model
|
||||
|
||||
if config.TemplateConfig.Chat != "" {
|
||||
templateFile = config.TemplateConfig.Chat
|
||||
}
|
||||
|
||||
// A model can have a "file.bin.tmpl" file associated with a prompt template prefix
|
||||
templatedInput, err := o.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, o.loader, responses)
|
||||
|
||||
c.Context().SetBodyStreamWriter(fasthttp.StreamWriter(func(w *bufio.Writer) {
|
||||
|
||||
for ev := range responses {
|
||||
var buf bytes.Buffer
|
||||
enc := json.NewEncoder(&buf)
|
||||
enc.Encode(ev)
|
||||
|
||||
log.Debug().Msgf("Sending chunk: %s", buf.String())
|
||||
fmt.Fprintf(w, "data: %v\n", buf.String())
|
||||
w.Flush()
|
||||
}
|
||||
|
||||
resp := &OpenAIResponse{
|
||||
Model: input.Model, // we have to return what the user sent here, due to OpenAI spec.
|
||||
Choices: []Choice{{FinishReason: "stop"}},
|
||||
}
|
||||
respData, _ := json.Marshal(resp)
|
||||
|
||||
w.WriteString(fmt.Sprintf("data: %s\n\n", respData))
|
||||
w.WriteString("data: [DONE]\n\n")
|
||||
w.Flush()
|
||||
}))
|
||||
return nil
|
||||
}
|
||||
|
||||
result, err := ComputeChoices(predInput, input, config, o.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, o *Option) func(c *fiber.Ctx) error {
|
||||
return func(c *fiber.Ctx) error {
|
||||
model, input, err := readInput(c, o.loader, true)
|
||||
if err != nil {
|
||||
return fmt.Errorf("failed reading parameters from request:%w", err)
|
||||
}
|
||||
|
||||
config, input, err := readConfig(model, input, cm, o.loader, o.debug, o.threads, o.ctxSize, o.f16)
|
||||
if err != nil {
|
||||
return fmt.Errorf("failed reading parameters from request:%w", err)
|
||||
}
|
||||
|
||||
log.Debug().Msgf("Parameter Config: %+v", config)
|
||||
|
||||
templateFile := config.Model
|
||||
|
||||
if config.TemplateConfig.Edit != "" {
|
||||
templateFile = config.TemplateConfig.Edit
|
||||
}
|
||||
|
||||
var result []Choice
|
||||
for _, i := range config.InputStrings {
|
||||
// A model can have a "file.bin.tmpl" file associated with a prompt template prefix
|
||||
templatedInput, err := o.loader.TemplatePrefix(templateFile, struct {
|
||||
Input string
|
||||
Instruction string
|
||||
}{Input: i})
|
||||
if err == nil {
|
||||
i = templatedInput
|
||||
log.Debug().Msgf("Template found, input modified to: %s", i)
|
||||
}
|
||||
|
||||
r, err := ComputeChoices(i, input, config, o.loader, func(s string, c *[]Choice) {
|
||||
*c = append(*c, Choice{Text: s})
|
||||
}, nil)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
|
||||
result = append(result, r...)
|
||||
}
|
||||
|
||||
resp := &OpenAIResponse{
|
||||
Model: input.Model, // we have to return what the user sent here, due to OpenAI spec.
|
||||
Choices: result,
|
||||
Object: "edit",
|
||||
}
|
||||
|
||||
jsonResult, _ := json.Marshal(resp)
|
||||
log.Debug().Msgf("Response: %s", jsonResult)
|
||||
|
||||
// Return the prediction in the response body
|
||||
return c.JSON(resp)
|
||||
}
|
||||
}
|
||||
|
||||
// https://platform.openai.com/docs/api-reference/images/create
|
||||
|
||||
/*
|
||||
*
|
||||
|
||||
curl http://localhost:8080/v1/images/generations \
|
||||
-H "Content-Type: application/json" \
|
||||
-d '{
|
||||
"prompt": "A cute baby sea otter",
|
||||
"n": 1,
|
||||
"size": "512x512"
|
||||
}'
|
||||
|
||||
*
|
||||
*/
|
||||
func imageEndpoint(cm *ConfigMerger, o *Option) func(c *fiber.Ctx) error {
|
||||
return func(c *fiber.Ctx) error {
|
||||
m, input, err := readInput(c, o.loader, false)
|
||||
if err != nil {
|
||||
return fmt.Errorf("failed reading parameters from request:%w", err)
|
||||
}
|
||||
|
||||
if m == "" {
|
||||
m = model.StableDiffusionBackend
|
||||
}
|
||||
log.Debug().Msgf("Loading model: %+v", m)
|
||||
|
||||
config, input, err := readConfig(m, input, cm, o.loader, o.debug, 0, 0, false)
|
||||
if err != nil {
|
||||
return fmt.Errorf("failed reading parameters from request:%w", err)
|
||||
}
|
||||
|
||||
log.Debug().Msgf("Parameter Config: %+v", config)
|
||||
|
||||
// XXX: Only stablediffusion is supported for now
|
||||
if config.Backend == "" {
|
||||
config.Backend = model.StableDiffusionBackend
|
||||
}
|
||||
|
||||
sizeParts := strings.Split(input.Size, "x")
|
||||
if len(sizeParts) != 2 {
|
||||
return fmt.Errorf("Invalid value for 'size'")
|
||||
}
|
||||
width, err := strconv.Atoi(sizeParts[0])
|
||||
if err != nil {
|
||||
return fmt.Errorf("Invalid value for 'size'")
|
||||
}
|
||||
height, err := strconv.Atoi(sizeParts[1])
|
||||
if err != nil {
|
||||
return fmt.Errorf("Invalid value for 'size'")
|
||||
}
|
||||
|
||||
b64JSON := false
|
||||
if input.ResponseFormat == "b64_json" {
|
||||
b64JSON = true
|
||||
}
|
||||
|
||||
var result []Item
|
||||
for _, i := range config.PromptStrings {
|
||||
n := input.N
|
||||
if input.N == 0 {
|
||||
n = 1
|
||||
}
|
||||
for j := 0; j < n; j++ {
|
||||
prompts := strings.Split(i, "|")
|
||||
positive_prompt := prompts[0]
|
||||
negative_prompt := ""
|
||||
if len(prompts) > 1 {
|
||||
negative_prompt = prompts[1]
|
||||
}
|
||||
|
||||
mode := 0
|
||||
step := 15
|
||||
|
||||
if input.Mode != 0 {
|
||||
mode = input.Mode
|
||||
}
|
||||
|
||||
if input.Step != 0 {
|
||||
step = input.Step
|
||||
}
|
||||
|
||||
tempDir := ""
|
||||
if !b64JSON {
|
||||
tempDir = o.imageDir
|
||||
}
|
||||
// Create a temporary file
|
||||
outputFile, err := ioutil.TempFile(tempDir, "b64")
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
outputFile.Close()
|
||||
output := outputFile.Name() + ".png"
|
||||
// Rename the temporary file
|
||||
err = os.Rename(outputFile.Name(), output)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
|
||||
baseURL := c.BaseURL()
|
||||
|
||||
fn, err := ImageGeneration(height, width, mode, step, input.Seed, positive_prompt, negative_prompt, output, o.loader, *config)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
if err := fn(); err != nil {
|
||||
return err
|
||||
}
|
||||
|
||||
item := &Item{}
|
||||
|
||||
if b64JSON {
|
||||
defer os.RemoveAll(output)
|
||||
data, err := os.ReadFile(output)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
item.B64JSON = base64.StdEncoding.EncodeToString(data)
|
||||
} else {
|
||||
base := filepath.Base(output)
|
||||
item.URL = baseURL + "/generated-images/" + base
|
||||
}
|
||||
|
||||
result = append(result, *item)
|
||||
}
|
||||
}
|
||||
|
||||
resp := &OpenAIResponse{
|
||||
Data: result,
|
||||
}
|
||||
|
||||
jsonResult, _ := json.Marshal(resp)
|
||||
log.Debug().Msgf("Response: %s", jsonResult)
|
||||
|
||||
// Return the prediction in the response body
|
||||
return c.JSON(resp)
|
||||
}
|
||||
}
|
||||
|
||||
// https://platform.openai.com/docs/api-reference/audio/create
|
||||
func transcriptEndpoint(cm *ConfigMerger, o *Option) func(c *fiber.Ctx) error {
|
||||
return func(c *fiber.Ctx) error {
|
||||
m, input, err := readInput(c, o.loader, false)
|
||||
if err != nil {
|
||||
return fmt.Errorf("failed reading parameters from request:%w", err)
|
||||
}
|
||||
|
||||
config, input, err := readConfig(m, input, cm, o.loader, o.debug, o.threads, o.ctxSize, o.f16)
|
||||
if err != nil {
|
||||
return fmt.Errorf("failed reading parameters from request:%w", err)
|
||||
}
|
||||
// retrieve the file data from the request
|
||||
file, err := c.FormFile("file")
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
f, err := file.Open()
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
defer f.Close()
|
||||
|
||||
dir, err := os.MkdirTemp("", "whisper")
|
||||
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
defer os.RemoveAll(dir)
|
||||
|
||||
dst := filepath.Join(dir, path.Base(file.Filename))
|
||||
dstFile, err := os.Create(dst)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
|
||||
if _, err := io.Copy(dstFile, f); err != nil {
|
||||
log.Debug().Msgf("Audio file copying error %+v - %+v - err %+v", file.Filename, dst, err)
|
||||
return err
|
||||
}
|
||||
|
||||
log.Debug().Msgf("Audio file copied to: %+v", dst)
|
||||
|
||||
whisperModel, err := o.loader.BackendLoader(model.WhisperBackend, config.Model, []llama.ModelOption{}, uint32(config.Threads))
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
|
||||
if whisperModel == nil {
|
||||
return fmt.Errorf("could not load whisper model")
|
||||
}
|
||||
|
||||
w, ok := whisperModel.(whisper.Model)
|
||||
if !ok {
|
||||
return fmt.Errorf("loader returned non-whisper object")
|
||||
}
|
||||
|
||||
tr, err := whisperutil.Transcript(w, dst, input.Language, uint(config.Threads))
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
|
||||
log.Debug().Msgf("Trascribed: %+v", tr)
|
||||
// TODO: handle different outputs here
|
||||
return c.Status(http.StatusOK).JSON(fiber.Map{"text": tr})
|
||||
}
|
||||
}
|
||||
|
||||
func listModels(loader *model.ModelLoader, cm *ConfigMerger) func(ctx *fiber.Ctx) error {
|
||||
return func(c *fiber.Ctx) error {
|
||||
models, err := loader.ListModels()
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
var mm map[string]interface{} = map[string]interface{}{}
|
||||
|
||||
dataModels := []OpenAIModel{}
|
||||
for _, m := range models {
|
||||
mm[m] = nil
|
||||
dataModels = append(dataModels, OpenAIModel{ID: m, Object: "model"})
|
||||
}
|
||||
|
||||
for _, k := range cm.ListConfigs() {
|
||||
if _, exists := mm[k]; !exists {
|
||||
dataModels = append(dataModels, OpenAIModel{ID: k, Object: "model"})
|
||||
}
|
||||
}
|
||||
|
||||
return c.JSON(struct {
|
||||
Object string `json:"object"`
|
||||
Data []OpenAIModel `json:"data"`
|
||||
}{
|
||||
Object: "list",
|
||||
Data: dataModels,
|
||||
})
|
||||
}
|
||||
}
|
||||
373
api/openai/chat.go
Normal file
373
api/openai/chat.go
Normal file
@@ -0,0 +1,373 @@
|
||||
package openai
|
||||
|
||||
import (
|
||||
"bufio"
|
||||
"bytes"
|
||||
"encoding/json"
|
||||
"fmt"
|
||||
"strings"
|
||||
|
||||
"github.com/go-skynet/LocalAI/api/backend"
|
||||
config "github.com/go-skynet/LocalAI/api/config"
|
||||
"github.com/go-skynet/LocalAI/api/options"
|
||||
"github.com/go-skynet/LocalAI/api/schema"
|
||||
"github.com/go-skynet/LocalAI/pkg/grammar"
|
||||
model "github.com/go-skynet/LocalAI/pkg/model"
|
||||
"github.com/go-skynet/LocalAI/pkg/utils"
|
||||
"github.com/gofiber/fiber/v2"
|
||||
"github.com/rs/zerolog/log"
|
||||
"github.com/valyala/fasthttp"
|
||||
)
|
||||
|
||||
func ChatEndpoint(cm *config.ConfigLoader, o *options.Option) func(c *fiber.Ctx) error {
|
||||
emptyMessage := ""
|
||||
|
||||
process := func(s string, req *schema.OpenAIRequest, config *config.Config, loader *model.ModelLoader, responses chan schema.OpenAIResponse) {
|
||||
initialMessage := schema.OpenAIResponse{
|
||||
Model: req.Model, // we have to return what the user sent here, due to OpenAI spec.
|
||||
Choices: []schema.Choice{{Delta: &schema.Message{Role: "assistant", Content: &emptyMessage}}},
|
||||
Object: "chat.completion.chunk",
|
||||
}
|
||||
responses <- initialMessage
|
||||
|
||||
ComputeChoices(req, s, config, o, loader, func(s string, c *[]schema.Choice) {}, func(s string, usage backend.TokenUsage) bool {
|
||||
resp := schema.OpenAIResponse{
|
||||
Model: req.Model, // we have to return what the user sent here, due to OpenAI spec.
|
||||
Choices: []schema.Choice{{Delta: &schema.Message{Content: &s}, Index: 0}},
|
||||
Object: "chat.completion.chunk",
|
||||
Usage: schema.OpenAIUsage{
|
||||
PromptTokens: usage.Prompt,
|
||||
CompletionTokens: usage.Completion,
|
||||
TotalTokens: usage.Prompt + usage.Completion,
|
||||
},
|
||||
}
|
||||
|
||||
responses <- resp
|
||||
return true
|
||||
})
|
||||
close(responses)
|
||||
}
|
||||
return func(c *fiber.Ctx) error {
|
||||
processFunctions := false
|
||||
funcs := grammar.Functions{}
|
||||
modelFile, input, err := readInput(c, o, true)
|
||||
if err != nil {
|
||||
return fmt.Errorf("failed reading parameters from request:%w", err)
|
||||
}
|
||||
|
||||
config, input, err := readConfig(modelFile, input, cm, o.Loader, o.Debug, o.Threads, o.ContextSize, o.F16)
|
||||
if err != nil {
|
||||
return fmt.Errorf("failed reading parameters from request:%w", err)
|
||||
}
|
||||
log.Debug().Msgf("Configuration read: %+v", config)
|
||||
|
||||
// Allow the user to set custom actions via config file
|
||||
// to be "embedded" in each model
|
||||
noActionName := "answer"
|
||||
noActionDescription := "use this action to answer without performing any action"
|
||||
|
||||
if config.FunctionsConfig.NoActionFunctionName != "" {
|
||||
noActionName = config.FunctionsConfig.NoActionFunctionName
|
||||
}
|
||||
if config.FunctionsConfig.NoActionDescriptionName != "" {
|
||||
noActionDescription = config.FunctionsConfig.NoActionDescriptionName
|
||||
}
|
||||
|
||||
// process functions if we have any defined or if we have a function call string
|
||||
if len(input.Functions) > 0 && config.ShouldUseFunctions() {
|
||||
log.Debug().Msgf("Response needs to process functions")
|
||||
|
||||
processFunctions = true
|
||||
|
||||
noActionGrammar := grammar.Function{
|
||||
Name: noActionName,
|
||||
Description: noActionDescription,
|
||||
Parameters: map[string]interface{}{
|
||||
"properties": map[string]interface{}{
|
||||
"message": map[string]interface{}{
|
||||
"type": "string",
|
||||
"description": "The message to reply the user with",
|
||||
}},
|
||||
},
|
||||
}
|
||||
|
||||
// Append the no action function
|
||||
funcs = append(funcs, input.Functions...)
|
||||
if !config.FunctionsConfig.DisableNoAction {
|
||||
funcs = append(funcs, noActionGrammar)
|
||||
}
|
||||
|
||||
// Force picking one of the functions by the request
|
||||
if config.FunctionToCall() != "" {
|
||||
funcs = funcs.Select(config.FunctionToCall())
|
||||
}
|
||||
|
||||
// Update input grammar
|
||||
jsStruct := funcs.ToJSONStructure()
|
||||
config.Grammar = jsStruct.Grammar("")
|
||||
} else if input.JSONFunctionGrammarObject != nil {
|
||||
config.Grammar = input.JSONFunctionGrammarObject.Grammar("")
|
||||
}
|
||||
|
||||
// functions are not supported in stream mode (yet?)
|
||||
toStream := input.Stream && !processFunctions
|
||||
|
||||
log.Debug().Msgf("Parameters: %+v", config)
|
||||
|
||||
var predInput string
|
||||
|
||||
suppressConfigSystemPrompt := false
|
||||
mess := []string{}
|
||||
for messageIndex, i := range input.Messages {
|
||||
var content string
|
||||
role := i.Role
|
||||
|
||||
// if function call, we might want to customize the role so we can display better that the "assistant called a json action"
|
||||
// if an "assistant_function_call" role is defined, we use it, otherwise we use the role that is passed by in the request
|
||||
if i.FunctionCall != nil && i.Role == "assistant" {
|
||||
roleFn := "assistant_function_call"
|
||||
r := config.Roles[roleFn]
|
||||
if r != "" {
|
||||
role = roleFn
|
||||
}
|
||||
}
|
||||
r := config.Roles[role]
|
||||
contentExists := i.Content != nil && *i.Content != ""
|
||||
// First attempt to populate content via a chat message specific template
|
||||
if config.TemplateConfig.ChatMessage != "" {
|
||||
chatMessageData := model.ChatMessageTemplateData{
|
||||
SystemPrompt: config.SystemPrompt,
|
||||
Role: r,
|
||||
RoleName: role,
|
||||
Content: *i.Content,
|
||||
MessageIndex: messageIndex,
|
||||
}
|
||||
templatedChatMessage, err := o.Loader.EvaluateTemplateForChatMessage(config.TemplateConfig.ChatMessage, chatMessageData)
|
||||
if err != nil {
|
||||
log.Error().Msgf("error processing message %+v using template \"%s\": %v. Skipping!", chatMessageData, config.TemplateConfig.ChatMessage, err)
|
||||
} else {
|
||||
if templatedChatMessage == "" {
|
||||
log.Warn().Msgf("template \"%s\" produced blank output for %+v. Skipping!", config.TemplateConfig.ChatMessage, chatMessageData)
|
||||
continue // TODO: This continue is here intentionally to skip over the line `mess = append(mess, content)` below, and to prevent the sprintf
|
||||
}
|
||||
log.Debug().Msgf("templated message for chat: %s", templatedChatMessage)
|
||||
content = templatedChatMessage
|
||||
}
|
||||
}
|
||||
// If this model doesn't have such a template, or if that template fails to return a value, template at the message level.
|
||||
if content == "" {
|
||||
if r != "" {
|
||||
if contentExists {
|
||||
content = fmt.Sprint(r, " ", *i.Content)
|
||||
}
|
||||
if i.FunctionCall != nil {
|
||||
j, err := json.Marshal(i.FunctionCall)
|
||||
if err == nil {
|
||||
if contentExists {
|
||||
content += "\n" + fmt.Sprint(r, " ", string(j))
|
||||
} else {
|
||||
content = fmt.Sprint(r, " ", string(j))
|
||||
}
|
||||
}
|
||||
}
|
||||
} else {
|
||||
if contentExists {
|
||||
content = fmt.Sprint(*i.Content)
|
||||
}
|
||||
if i.FunctionCall != nil {
|
||||
j, err := json.Marshal(i.FunctionCall)
|
||||
if err == nil {
|
||||
if contentExists {
|
||||
content += "\n" + string(j)
|
||||
} else {
|
||||
content = string(j)
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
// Special Handling: System. We care if it was printed at all, not the r branch, so check seperately
|
||||
if contentExists && role == "system" {
|
||||
suppressConfigSystemPrompt = true
|
||||
}
|
||||
}
|
||||
|
||||
mess = append(mess, content)
|
||||
}
|
||||
|
||||
predInput = strings.Join(mess, "\n")
|
||||
log.Debug().Msgf("Prompt (before templating): %s", predInput)
|
||||
|
||||
if toStream {
|
||||
log.Debug().Msgf("Stream request received")
|
||||
c.Context().SetContentType("text/event-stream")
|
||||
//c.Response().Header.SetContentType(fiber.MIMETextHTMLCharsetUTF8)
|
||||
// c.Set("Content-Type", "text/event-stream")
|
||||
c.Set("Cache-Control", "no-cache")
|
||||
c.Set("Connection", "keep-alive")
|
||||
c.Set("Transfer-Encoding", "chunked")
|
||||
}
|
||||
|
||||
templateFile := config.Model
|
||||
|
||||
if config.TemplateConfig.Chat != "" && !processFunctions {
|
||||
templateFile = config.TemplateConfig.Chat
|
||||
}
|
||||
|
||||
if config.TemplateConfig.Functions != "" && processFunctions {
|
||||
templateFile = config.TemplateConfig.Functions
|
||||
}
|
||||
|
||||
// A model can have a "file.bin.tmpl" file associated with a prompt template prefix
|
||||
templatedInput, err := o.Loader.EvaluateTemplateForPrompt(model.ChatPromptTemplate, templateFile, model.PromptTemplateData{
|
||||
SystemPrompt: config.SystemPrompt,
|
||||
SuppressSystemPrompt: suppressConfigSystemPrompt,
|
||||
Input: predInput,
|
||||
Functions: funcs,
|
||||
})
|
||||
if err == nil {
|
||||
predInput = templatedInput
|
||||
log.Debug().Msgf("Template found, input modified to: %s", predInput)
|
||||
} else {
|
||||
log.Debug().Msgf("Template failed loading: %s", err.Error())
|
||||
}
|
||||
|
||||
log.Debug().Msgf("Prompt (after templating): %s", predInput)
|
||||
if processFunctions {
|
||||
log.Debug().Msgf("Grammar: %+v", config.Grammar)
|
||||
}
|
||||
|
||||
if toStream {
|
||||
responses := make(chan schema.OpenAIResponse)
|
||||
|
||||
go process(predInput, input, config, o.Loader, responses)
|
||||
|
||||
c.Context().SetBodyStreamWriter(fasthttp.StreamWriter(func(w *bufio.Writer) {
|
||||
|
||||
usage := &schema.OpenAIUsage{}
|
||||
|
||||
for ev := range responses {
|
||||
usage = &ev.Usage // Copy a pointer to the latest usage chunk so that the stop message can reference it
|
||||
var buf bytes.Buffer
|
||||
enc := json.NewEncoder(&buf)
|
||||
enc.Encode(ev)
|
||||
log.Debug().Msgf("Sending chunk: %s", buf.String())
|
||||
_, err := fmt.Fprintf(w, "data: %v\n", buf.String())
|
||||
if err != nil {
|
||||
log.Debug().Msgf("Sending chunk failed: %v", err)
|
||||
input.Cancel()
|
||||
break
|
||||
}
|
||||
w.Flush()
|
||||
}
|
||||
|
||||
resp := &schema.OpenAIResponse{
|
||||
Model: input.Model, // we have to return what the user sent here, due to OpenAI spec.
|
||||
Choices: []schema.Choice{
|
||||
{
|
||||
FinishReason: "stop",
|
||||
Index: 0,
|
||||
Delta: &schema.Message{Content: &emptyMessage},
|
||||
}},
|
||||
Object: "chat.completion.chunk",
|
||||
Usage: *usage,
|
||||
}
|
||||
respData, _ := json.Marshal(resp)
|
||||
|
||||
w.WriteString(fmt.Sprintf("data: %s\n\n", respData))
|
||||
w.WriteString("data: [DONE]\n\n")
|
||||
w.Flush()
|
||||
}))
|
||||
return nil
|
||||
}
|
||||
|
||||
result, tokenUsage, err := ComputeChoices(input, predInput, config, o, o.Loader, func(s string, c *[]schema.Choice) {
|
||||
if processFunctions {
|
||||
// As we have to change the result before processing, we can't stream the answer (yet?)
|
||||
ss := map[string]interface{}{}
|
||||
// This prevent newlines to break JSON parsing for clients
|
||||
s = utils.EscapeNewLines(s)
|
||||
json.Unmarshal([]byte(s), &ss)
|
||||
log.Debug().Msgf("Function return: %s %+v", s, ss)
|
||||
|
||||
// The grammar defines the function name as "function", while OpenAI returns "name"
|
||||
func_name := ss["function"]
|
||||
// Similarly, while here arguments is a map[string]interface{}, OpenAI actually want a stringified object
|
||||
args := ss["arguments"] // arguments needs to be a string, but we return an object from the grammar result (TODO: fix)
|
||||
d, _ := json.Marshal(args)
|
||||
|
||||
ss["arguments"] = string(d)
|
||||
ss["name"] = func_name
|
||||
|
||||
// if do nothing, reply with a message
|
||||
if func_name == noActionName {
|
||||
log.Debug().Msgf("nothing to do, computing a reply")
|
||||
|
||||
// If there is a message that the LLM already sends as part of the JSON reply, use it
|
||||
arguments := map[string]interface{}{}
|
||||
json.Unmarshal([]byte(d), &arguments)
|
||||
m, exists := arguments["message"]
|
||||
if exists {
|
||||
switch message := m.(type) {
|
||||
case string:
|
||||
if message != "" {
|
||||
log.Debug().Msgf("Reply received from LLM: %s", message)
|
||||
message = backend.Finetune(*config, predInput, message)
|
||||
log.Debug().Msgf("Reply received from LLM(finetuned): %s", message)
|
||||
|
||||
*c = append(*c, schema.Choice{Message: &schema.Message{Role: "assistant", Content: &message}})
|
||||
return
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
log.Debug().Msgf("No action received from LLM, without a message, computing a reply")
|
||||
// Otherwise ask the LLM to understand the JSON output and the context, and return a message
|
||||
// Note: This costs (in term of CPU) another computation
|
||||
config.Grammar = ""
|
||||
predFunc, err := backend.ModelInference(input.Context, predInput, o.Loader, *config, o, nil)
|
||||
if err != nil {
|
||||
log.Error().Msgf("inference error: %s", err.Error())
|
||||
return
|
||||
}
|
||||
|
||||
prediction, err := predFunc()
|
||||
if err != nil {
|
||||
log.Error().Msgf("inference error: %s", err.Error())
|
||||
return
|
||||
}
|
||||
|
||||
fineTunedResponse := backend.Finetune(*config, predInput, prediction.Response)
|
||||
*c = append(*c, schema.Choice{Message: &schema.Message{Role: "assistant", Content: &fineTunedResponse}})
|
||||
} else {
|
||||
// otherwise reply with the function call
|
||||
*c = append(*c, schema.Choice{
|
||||
FinishReason: "function_call",
|
||||
Message: &schema.Message{Role: "assistant", FunctionCall: ss},
|
||||
})
|
||||
}
|
||||
|
||||
return
|
||||
}
|
||||
*c = append(*c, schema.Choice{FinishReason: "stop", Index: 0, Message: &schema.Message{Role: "assistant", Content: &s}})
|
||||
}, nil)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
|
||||
resp := &schema.OpenAIResponse{
|
||||
Model: input.Model, // we have to return what the user sent here, due to OpenAI spec.
|
||||
Choices: result,
|
||||
Object: "chat.completion",
|
||||
Usage: schema.OpenAIUsage{
|
||||
PromptTokens: tokenUsage.Prompt,
|
||||
CompletionTokens: tokenUsage.Completion,
|
||||
TotalTokens: tokenUsage.Prompt + tokenUsage.Completion,
|
||||
},
|
||||
}
|
||||
respData, _ := json.Marshal(resp)
|
||||
log.Debug().Msgf("Response: %s", respData)
|
||||
|
||||
// Return the prediction in the response body
|
||||
return c.JSON(resp)
|
||||
}
|
||||
}
|
||||
175
api/openai/completion.go
Normal file
175
api/openai/completion.go
Normal file
@@ -0,0 +1,175 @@
|
||||
package openai
|
||||
|
||||
import (
|
||||
"bufio"
|
||||
"bytes"
|
||||
"encoding/json"
|
||||
"errors"
|
||||
"fmt"
|
||||
|
||||
"github.com/go-skynet/LocalAI/api/backend"
|
||||
config "github.com/go-skynet/LocalAI/api/config"
|
||||
"github.com/go-skynet/LocalAI/api/options"
|
||||
"github.com/go-skynet/LocalAI/api/schema"
|
||||
model "github.com/go-skynet/LocalAI/pkg/model"
|
||||
"github.com/gofiber/fiber/v2"
|
||||
"github.com/rs/zerolog/log"
|
||||
"github.com/valyala/fasthttp"
|
||||
)
|
||||
|
||||
// https://platform.openai.com/docs/api-reference/completions
|
||||
func CompletionEndpoint(cm *config.ConfigLoader, o *options.Option) func(c *fiber.Ctx) error {
|
||||
process := func(s string, req *schema.OpenAIRequest, config *config.Config, loader *model.ModelLoader, responses chan schema.OpenAIResponse) {
|
||||
ComputeChoices(req, s, config, o, loader, func(s string, c *[]schema.Choice) {}, func(s string, usage backend.TokenUsage) bool {
|
||||
resp := schema.OpenAIResponse{
|
||||
Model: req.Model, // we have to return what the user sent here, due to OpenAI spec.
|
||||
Choices: []schema.Choice{
|
||||
{
|
||||
Index: 0,
|
||||
Text: s,
|
||||
},
|
||||
},
|
||||
Object: "text_completion",
|
||||
Usage: schema.OpenAIUsage{
|
||||
PromptTokens: usage.Prompt,
|
||||
CompletionTokens: usage.Completion,
|
||||
TotalTokens: usage.Prompt + usage.Completion,
|
||||
},
|
||||
}
|
||||
log.Debug().Msgf("Sending goroutine: %s", s)
|
||||
|
||||
responses <- resp
|
||||
return true
|
||||
})
|
||||
close(responses)
|
||||
}
|
||||
|
||||
return func(c *fiber.Ctx) error {
|
||||
modelFile, input, err := readInput(c, o, true)
|
||||
if err != nil {
|
||||
return fmt.Errorf("failed reading parameters from request:%w", err)
|
||||
}
|
||||
|
||||
log.Debug().Msgf("`input`: %+v", input)
|
||||
|
||||
config, input, err := readConfig(modelFile, input, cm, o.Loader, o.Debug, o.Threads, o.ContextSize, o.F16)
|
||||
if err != nil {
|
||||
return fmt.Errorf("failed reading parameters from request:%w", err)
|
||||
}
|
||||
|
||||
log.Debug().Msgf("Parameter Config: %+v", config)
|
||||
|
||||
if input.Stream {
|
||||
log.Debug().Msgf("Stream request received")
|
||||
c.Context().SetContentType("text/event-stream")
|
||||
//c.Response().Header.SetContentType(fiber.MIMETextHTMLCharsetUTF8)
|
||||
//c.Set("Content-Type", "text/event-stream")
|
||||
c.Set("Cache-Control", "no-cache")
|
||||
c.Set("Connection", "keep-alive")
|
||||
c.Set("Transfer-Encoding", "chunked")
|
||||
}
|
||||
|
||||
templateFile := config.Model
|
||||
|
||||
if config.TemplateConfig.Completion != "" {
|
||||
templateFile = config.TemplateConfig.Completion
|
||||
}
|
||||
|
||||
if input.Stream {
|
||||
if len(config.PromptStrings) > 1 {
|
||||
return errors.New("cannot handle more than 1 `PromptStrings` when Streaming")
|
||||
}
|
||||
|
||||
predInput := config.PromptStrings[0]
|
||||
|
||||
// A model can have a "file.bin.tmpl" file associated with a prompt template prefix
|
||||
templatedInput, err := o.Loader.EvaluateTemplateForPrompt(model.CompletionPromptTemplate, templateFile, model.PromptTemplateData{
|
||||
Input: predInput,
|
||||
})
|
||||
if err == nil {
|
||||
predInput = templatedInput
|
||||
log.Debug().Msgf("Template found, input modified to: %s", predInput)
|
||||
}
|
||||
|
||||
responses := make(chan schema.OpenAIResponse)
|
||||
|
||||
go process(predInput, input, config, o.Loader, responses)
|
||||
|
||||
c.Context().SetBodyStreamWriter(fasthttp.StreamWriter(func(w *bufio.Writer) {
|
||||
|
||||
for ev := range responses {
|
||||
var buf bytes.Buffer
|
||||
enc := json.NewEncoder(&buf)
|
||||
enc.Encode(ev)
|
||||
|
||||
log.Debug().Msgf("Sending chunk: %s", buf.String())
|
||||
fmt.Fprintf(w, "data: %v\n", buf.String())
|
||||
w.Flush()
|
||||
}
|
||||
|
||||
resp := &schema.OpenAIResponse{
|
||||
Model: input.Model, // we have to return what the user sent here, due to OpenAI spec.
|
||||
Choices: []schema.Choice{
|
||||
{
|
||||
Index: 0,
|
||||
FinishReason: "stop",
|
||||
},
|
||||
},
|
||||
Object: "text_completion",
|
||||
}
|
||||
respData, _ := json.Marshal(resp)
|
||||
|
||||
w.WriteString(fmt.Sprintf("data: %s\n\n", respData))
|
||||
w.WriteString("data: [DONE]\n\n")
|
||||
w.Flush()
|
||||
}))
|
||||
return nil
|
||||
}
|
||||
|
||||
var result []schema.Choice
|
||||
|
||||
totalTokenUsage := backend.TokenUsage{}
|
||||
|
||||
for k, i := range config.PromptStrings {
|
||||
// A model can have a "file.bin.tmpl" file associated with a prompt template prefix
|
||||
templatedInput, err := o.Loader.EvaluateTemplateForPrompt(model.CompletionPromptTemplate, templateFile, model.PromptTemplateData{
|
||||
SystemPrompt: config.SystemPrompt,
|
||||
Input: i,
|
||||
})
|
||||
if err == nil {
|
||||
i = templatedInput
|
||||
log.Debug().Msgf("Template found, input modified to: %s", i)
|
||||
}
|
||||
|
||||
r, tokenUsage, err := ComputeChoices(
|
||||
input, i, config, o, o.Loader, func(s string, c *[]schema.Choice) {
|
||||
*c = append(*c, schema.Choice{Text: s, FinishReason: "stop", Index: k})
|
||||
}, nil)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
|
||||
totalTokenUsage.Prompt += tokenUsage.Prompt
|
||||
totalTokenUsage.Completion += tokenUsage.Completion
|
||||
|
||||
result = append(result, r...)
|
||||
}
|
||||
|
||||
resp := &schema.OpenAIResponse{
|
||||
Model: input.Model, // we have to return what the user sent here, due to OpenAI spec.
|
||||
Choices: result,
|
||||
Object: "text_completion",
|
||||
Usage: schema.OpenAIUsage{
|
||||
PromptTokens: totalTokenUsage.Prompt,
|
||||
CompletionTokens: totalTokenUsage.Completion,
|
||||
TotalTokens: totalTokenUsage.Prompt + totalTokenUsage.Completion,
|
||||
},
|
||||
}
|
||||
|
||||
jsonResult, _ := json.Marshal(resp)
|
||||
log.Debug().Msgf("Response: %s", jsonResult)
|
||||
|
||||
// Return the prediction in the response body
|
||||
return c.JSON(resp)
|
||||
}
|
||||
}
|
||||
82
api/openai/edit.go
Normal file
82
api/openai/edit.go
Normal file
@@ -0,0 +1,82 @@
|
||||
package openai
|
||||
|
||||
import (
|
||||
"encoding/json"
|
||||
"fmt"
|
||||
|
||||
"github.com/go-skynet/LocalAI/api/backend"
|
||||
config "github.com/go-skynet/LocalAI/api/config"
|
||||
"github.com/go-skynet/LocalAI/api/options"
|
||||
"github.com/go-skynet/LocalAI/api/schema"
|
||||
model "github.com/go-skynet/LocalAI/pkg/model"
|
||||
"github.com/gofiber/fiber/v2"
|
||||
|
||||
"github.com/rs/zerolog/log"
|
||||
)
|
||||
|
||||
func EditEndpoint(cm *config.ConfigLoader, o *options.Option) func(c *fiber.Ctx) error {
|
||||
return func(c *fiber.Ctx) error {
|
||||
modelFile, input, err := readInput(c, o, true)
|
||||
if err != nil {
|
||||
return fmt.Errorf("failed reading parameters from request:%w", err)
|
||||
}
|
||||
|
||||
config, input, err := readConfig(modelFile, input, cm, o.Loader, o.Debug, o.Threads, o.ContextSize, o.F16)
|
||||
if err != nil {
|
||||
return fmt.Errorf("failed reading parameters from request:%w", err)
|
||||
}
|
||||
|
||||
log.Debug().Msgf("Parameter Config: %+v", config)
|
||||
|
||||
templateFile := config.Model
|
||||
|
||||
if config.TemplateConfig.Edit != "" {
|
||||
templateFile = config.TemplateConfig.Edit
|
||||
}
|
||||
|
||||
var result []schema.Choice
|
||||
totalTokenUsage := backend.TokenUsage{}
|
||||
|
||||
for _, i := range config.InputStrings {
|
||||
// A model can have a "file.bin.tmpl" file associated with a prompt template prefix
|
||||
templatedInput, err := o.Loader.EvaluateTemplateForPrompt(model.EditPromptTemplate, templateFile, model.PromptTemplateData{
|
||||
Input: i,
|
||||
Instruction: input.Instruction,
|
||||
SystemPrompt: config.SystemPrompt,
|
||||
})
|
||||
if err == nil {
|
||||
i = templatedInput
|
||||
log.Debug().Msgf("Template found, input modified to: %s", i)
|
||||
}
|
||||
|
||||
r, tokenUsage, err := ComputeChoices(input, i, config, o, o.Loader, func(s string, c *[]schema.Choice) {
|
||||
*c = append(*c, schema.Choice{Text: s})
|
||||
}, nil)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
|
||||
totalTokenUsage.Prompt += tokenUsage.Prompt
|
||||
totalTokenUsage.Completion += tokenUsage.Completion
|
||||
|
||||
result = append(result, r...)
|
||||
}
|
||||
|
||||
resp := &schema.OpenAIResponse{
|
||||
Model: input.Model, // we have to return what the user sent here, due to OpenAI spec.
|
||||
Choices: result,
|
||||
Object: "edit",
|
||||
Usage: schema.OpenAIUsage{
|
||||
PromptTokens: totalTokenUsage.Prompt,
|
||||
CompletionTokens: totalTokenUsage.Completion,
|
||||
TotalTokens: totalTokenUsage.Prompt + totalTokenUsage.Completion,
|
||||
},
|
||||
}
|
||||
|
||||
jsonResult, _ := json.Marshal(resp)
|
||||
log.Debug().Msgf("Response: %s", jsonResult)
|
||||
|
||||
// Return the prediction in the response body
|
||||
return c.JSON(resp)
|
||||
}
|
||||
}
|
||||
72
api/openai/embeddings.go
Normal file
72
api/openai/embeddings.go
Normal file
@@ -0,0 +1,72 @@
|
||||
package openai
|
||||
|
||||
import (
|
||||
"encoding/json"
|
||||
"fmt"
|
||||
|
||||
"github.com/go-skynet/LocalAI/api/backend"
|
||||
config "github.com/go-skynet/LocalAI/api/config"
|
||||
"github.com/go-skynet/LocalAI/api/schema"
|
||||
|
||||
"github.com/go-skynet/LocalAI/api/options"
|
||||
"github.com/gofiber/fiber/v2"
|
||||
"github.com/rs/zerolog/log"
|
||||
)
|
||||
|
||||
// https://platform.openai.com/docs/api-reference/embeddings
|
||||
func EmbeddingsEndpoint(cm *config.ConfigLoader, o *options.Option) func(c *fiber.Ctx) error {
|
||||
return func(c *fiber.Ctx) error {
|
||||
model, input, err := readInput(c, o, true)
|
||||
if err != nil {
|
||||
return fmt.Errorf("failed reading parameters from request:%w", err)
|
||||
}
|
||||
|
||||
config, input, err := readConfig(model, input, cm, o.Loader, o.Debug, o.Threads, o.ContextSize, o.F16)
|
||||
if err != nil {
|
||||
return fmt.Errorf("failed reading parameters from request:%w", err)
|
||||
}
|
||||
|
||||
log.Debug().Msgf("Parameter Config: %+v", config)
|
||||
items := []schema.Item{}
|
||||
|
||||
for i, s := range config.InputToken {
|
||||
// get the model function to call for the result
|
||||
embedFn, err := backend.ModelEmbedding("", s, o.Loader, *config, o)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
|
||||
embeddings, err := embedFn()
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
items = append(items, schema.Item{Embedding: embeddings, Index: i, Object: "embedding"})
|
||||
}
|
||||
|
||||
for i, s := range config.InputStrings {
|
||||
// get the model function to call for the result
|
||||
embedFn, err := backend.ModelEmbedding(s, []int{}, o.Loader, *config, o)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
|
||||
embeddings, err := embedFn()
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
items = append(items, schema.Item{Embedding: embeddings, Index: i, Object: "embedding"})
|
||||
}
|
||||
|
||||
resp := &schema.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)
|
||||
}
|
||||
}
|
||||
187
api/openai/image.go
Normal file
187
api/openai/image.go
Normal file
@@ -0,0 +1,187 @@
|
||||
package openai
|
||||
|
||||
import (
|
||||
"bufio"
|
||||
"encoding/base64"
|
||||
"encoding/json"
|
||||
"fmt"
|
||||
"github.com/go-skynet/LocalAI/api/schema"
|
||||
"os"
|
||||
"path/filepath"
|
||||
"strconv"
|
||||
"strings"
|
||||
|
||||
"github.com/go-skynet/LocalAI/api/backend"
|
||||
config "github.com/go-skynet/LocalAI/api/config"
|
||||
"github.com/go-skynet/LocalAI/api/options"
|
||||
model "github.com/go-skynet/LocalAI/pkg/model"
|
||||
"github.com/gofiber/fiber/v2"
|
||||
"github.com/rs/zerolog/log"
|
||||
)
|
||||
|
||||
// https://platform.openai.com/docs/api-reference/images/create
|
||||
|
||||
/*
|
||||
*
|
||||
|
||||
curl http://localhost:8080/v1/images/generations \
|
||||
-H "Content-Type: application/json" \
|
||||
-d '{
|
||||
"prompt": "A cute baby sea otter",
|
||||
"n": 1,
|
||||
"size": "512x512"
|
||||
}'
|
||||
|
||||
*
|
||||
*/
|
||||
func ImageEndpoint(cm *config.ConfigLoader, o *options.Option) func(c *fiber.Ctx) error {
|
||||
return func(c *fiber.Ctx) error {
|
||||
m, input, err := readInput(c, o, false)
|
||||
if err != nil {
|
||||
return fmt.Errorf("failed reading parameters from request:%w", err)
|
||||
}
|
||||
|
||||
if m == "" {
|
||||
m = model.StableDiffusionBackend
|
||||
}
|
||||
log.Debug().Msgf("Loading model: %+v", m)
|
||||
|
||||
config, input, err := readConfig(m, input, cm, o.Loader, o.Debug, 0, 0, false)
|
||||
if err != nil {
|
||||
return fmt.Errorf("failed reading parameters from request:%w", err)
|
||||
}
|
||||
|
||||
src := ""
|
||||
if input.File != "" {
|
||||
//base 64 decode the file and write it somewhere
|
||||
// that we will cleanup
|
||||
decoded, err := base64.StdEncoding.DecodeString(input.File)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
// Create a temporary file
|
||||
outputFile, err := os.CreateTemp(o.ImageDir, "b64")
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
// write the base64 result
|
||||
writer := bufio.NewWriter(outputFile)
|
||||
_, err = writer.Write(decoded)
|
||||
if err != nil {
|
||||
outputFile.Close()
|
||||
return err
|
||||
}
|
||||
outputFile.Close()
|
||||
src = outputFile.Name()
|
||||
defer os.RemoveAll(src)
|
||||
}
|
||||
|
||||
log.Debug().Msgf("Parameter Config: %+v", config)
|
||||
|
||||
// XXX: Only stablediffusion is supported for now
|
||||
if config.Backend == "" {
|
||||
config.Backend = model.StableDiffusionBackend
|
||||
}
|
||||
|
||||
sizeParts := strings.Split(input.Size, "x")
|
||||
if len(sizeParts) != 2 {
|
||||
return fmt.Errorf("Invalid value for 'size'")
|
||||
}
|
||||
width, err := strconv.Atoi(sizeParts[0])
|
||||
if err != nil {
|
||||
return fmt.Errorf("Invalid value for 'size'")
|
||||
}
|
||||
height, err := strconv.Atoi(sizeParts[1])
|
||||
if err != nil {
|
||||
return fmt.Errorf("Invalid value for 'size'")
|
||||
}
|
||||
|
||||
b64JSON := false
|
||||
if input.ResponseFormat == "b64_json" {
|
||||
b64JSON = true
|
||||
}
|
||||
// src and clip_skip
|
||||
var result []schema.Item
|
||||
for _, i := range config.PromptStrings {
|
||||
n := input.N
|
||||
if input.N == 0 {
|
||||
n = 1
|
||||
}
|
||||
for j := 0; j < n; j++ {
|
||||
prompts := strings.Split(i, "|")
|
||||
positive_prompt := prompts[0]
|
||||
negative_prompt := ""
|
||||
if len(prompts) > 1 {
|
||||
negative_prompt = prompts[1]
|
||||
}
|
||||
|
||||
mode := 0
|
||||
step := config.Step
|
||||
if step == 0 {
|
||||
step = 15
|
||||
}
|
||||
|
||||
if input.Mode != 0 {
|
||||
mode = input.Mode
|
||||
}
|
||||
|
||||
if input.Step != 0 {
|
||||
step = input.Step
|
||||
}
|
||||
|
||||
tempDir := ""
|
||||
if !b64JSON {
|
||||
tempDir = o.ImageDir
|
||||
}
|
||||
// Create a temporary file
|
||||
outputFile, err := os.CreateTemp(tempDir, "b64")
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
outputFile.Close()
|
||||
output := outputFile.Name() + ".png"
|
||||
// Rename the temporary file
|
||||
err = os.Rename(outputFile.Name(), output)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
|
||||
baseURL := c.BaseURL()
|
||||
|
||||
fn, err := backend.ImageGeneration(height, width, mode, step, input.Seed, positive_prompt, negative_prompt, src, output, o.Loader, *config, o)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
if err := fn(); err != nil {
|
||||
return err
|
||||
}
|
||||
|
||||
item := &schema.Item{}
|
||||
|
||||
if b64JSON {
|
||||
defer os.RemoveAll(output)
|
||||
data, err := os.ReadFile(output)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
item.B64JSON = base64.StdEncoding.EncodeToString(data)
|
||||
} else {
|
||||
base := filepath.Base(output)
|
||||
item.URL = baseURL + "/generated-images/" + base
|
||||
}
|
||||
|
||||
result = append(result, *item)
|
||||
}
|
||||
}
|
||||
|
||||
resp := &schema.OpenAIResponse{
|
||||
Data: result,
|
||||
}
|
||||
|
||||
jsonResult, _ := json.Marshal(resp)
|
||||
log.Debug().Msgf("Response: %s", jsonResult)
|
||||
|
||||
// Return the prediction in the response body
|
||||
return c.JSON(resp)
|
||||
}
|
||||
}
|
||||
50
api/openai/inference.go
Normal file
50
api/openai/inference.go
Normal file
@@ -0,0 +1,50 @@
|
||||
package openai
|
||||
|
||||
import (
|
||||
"github.com/go-skynet/LocalAI/api/backend"
|
||||
config "github.com/go-skynet/LocalAI/api/config"
|
||||
"github.com/go-skynet/LocalAI/api/options"
|
||||
"github.com/go-skynet/LocalAI/api/schema"
|
||||
model "github.com/go-skynet/LocalAI/pkg/model"
|
||||
)
|
||||
|
||||
func ComputeChoices(
|
||||
req *schema.OpenAIRequest,
|
||||
predInput string,
|
||||
config *config.Config,
|
||||
o *options.Option,
|
||||
loader *model.ModelLoader,
|
||||
cb func(string, *[]schema.Choice),
|
||||
tokenCallback func(string, backend.TokenUsage) bool) ([]schema.Choice, backend.TokenUsage, error) {
|
||||
n := req.N // number of completions to return
|
||||
result := []schema.Choice{}
|
||||
|
||||
if n == 0 {
|
||||
n = 1
|
||||
}
|
||||
|
||||
// get the model function to call for the result
|
||||
predFunc, err := backend.ModelInference(req.Context, predInput, loader, *config, o, tokenCallback)
|
||||
if err != nil {
|
||||
return result, backend.TokenUsage{}, err
|
||||
}
|
||||
|
||||
tokenUsage := backend.TokenUsage{}
|
||||
|
||||
for i := 0; i < n; i++ {
|
||||
prediction, err := predFunc()
|
||||
if err != nil {
|
||||
return result, backend.TokenUsage{}, err
|
||||
}
|
||||
|
||||
tokenUsage.Prompt += prediction.Usage.Prompt
|
||||
tokenUsage.Completion += prediction.Usage.Completion
|
||||
|
||||
finetunedResponse := backend.Finetune(*config, predInput, prediction.Response)
|
||||
cb(finetunedResponse, &result)
|
||||
|
||||
//result = append(result, Choice{Text: prediction})
|
||||
|
||||
}
|
||||
return result, tokenUsage, err
|
||||
}
|
||||
69
api/openai/list.go
Normal file
69
api/openai/list.go
Normal file
@@ -0,0 +1,69 @@
|
||||
package openai
|
||||
|
||||
import (
|
||||
"regexp"
|
||||
|
||||
config "github.com/go-skynet/LocalAI/api/config"
|
||||
"github.com/go-skynet/LocalAI/api/schema"
|
||||
model "github.com/go-skynet/LocalAI/pkg/model"
|
||||
"github.com/gofiber/fiber/v2"
|
||||
)
|
||||
|
||||
func ListModelsEndpoint(loader *model.ModelLoader, cm *config.ConfigLoader) func(ctx *fiber.Ctx) error {
|
||||
return func(c *fiber.Ctx) error {
|
||||
models, err := loader.ListModels()
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
var mm map[string]interface{} = map[string]interface{}{}
|
||||
|
||||
dataModels := []schema.OpenAIModel{}
|
||||
|
||||
var filterFn func(name string) bool
|
||||
filter := c.Query("filter")
|
||||
|
||||
// If filter is not specified, do not filter the list by model name
|
||||
if filter == "" {
|
||||
filterFn = func(_ string) bool { return true }
|
||||
} else {
|
||||
// If filter _IS_ specified, we compile it to a regex which is used to create the filterFn
|
||||
rxp, err := regexp.Compile(filter)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
filterFn = func(name string) bool {
|
||||
return rxp.MatchString(name)
|
||||
}
|
||||
}
|
||||
|
||||
// By default, exclude any loose files that are already referenced by a configuration file.
|
||||
excludeConfigured := c.QueryBool("excludeConfigured", true)
|
||||
|
||||
// Start with the known configurations
|
||||
for _, c := range cm.GetAllConfigs() {
|
||||
if excludeConfigured {
|
||||
mm[c.Model] = nil
|
||||
}
|
||||
|
||||
if filterFn(c.Name) {
|
||||
dataModels = append(dataModels, schema.OpenAIModel{ID: c.Name, Object: "model"})
|
||||
}
|
||||
}
|
||||
|
||||
// Then iterate through the loose files:
|
||||
for _, m := range models {
|
||||
// And only adds them if they shouldn't be skipped.
|
||||
if _, exists := mm[m]; !exists && filterFn(m) {
|
||||
dataModels = append(dataModels, schema.OpenAIModel{ID: m, Object: "model"})
|
||||
}
|
||||
}
|
||||
|
||||
return c.JSON(struct {
|
||||
Object string `json:"object"`
|
||||
Data []schema.OpenAIModel `json:"data"`
|
||||
}{
|
||||
Object: "list",
|
||||
Data: dataModels,
|
||||
})
|
||||
}
|
||||
}
|
||||
273
api/openai/request.go
Normal file
273
api/openai/request.go
Normal file
@@ -0,0 +1,273 @@
|
||||
package openai
|
||||
|
||||
import (
|
||||
"context"
|
||||
"encoding/json"
|
||||
"fmt"
|
||||
"os"
|
||||
"path/filepath"
|
||||
"strings"
|
||||
|
||||
config "github.com/go-skynet/LocalAI/api/config"
|
||||
options "github.com/go-skynet/LocalAI/api/options"
|
||||
"github.com/go-skynet/LocalAI/api/schema"
|
||||
model "github.com/go-skynet/LocalAI/pkg/model"
|
||||
"github.com/gofiber/fiber/v2"
|
||||
"github.com/rs/zerolog/log"
|
||||
)
|
||||
|
||||
func readInput(c *fiber.Ctx, o *options.Option, randomModel bool) (string, *schema.OpenAIRequest, error) {
|
||||
loader := o.Loader
|
||||
input := new(schema.OpenAIRequest)
|
||||
ctx, cancel := context.WithCancel(o.Context)
|
||||
input.Context = ctx
|
||||
input.Cancel = cancel
|
||||
// Get input data from the request body
|
||||
if err := c.BodyParser(input); err != nil {
|
||||
return "", nil, err
|
||||
}
|
||||
|
||||
modelFile := input.Model
|
||||
|
||||
if c.Params("model") != "" {
|
||||
modelFile = c.Params("model")
|
||||
}
|
||||
|
||||
received, _ := json.Marshal(input)
|
||||
|
||||
log.Debug().Msgf("Request received: %s", string(received))
|
||||
|
||||
// Set model from bearer token, if available
|
||||
bearer := strings.TrimLeft(c.Get("authorization"), "Bearer ")
|
||||
bearerExists := bearer != "" && loader.ExistsInModelPath(bearer)
|
||||
|
||||
// If no model was specified, take the first available
|
||||
if modelFile == "" && !bearerExists && randomModel {
|
||||
models, _ := loader.ListModels()
|
||||
if len(models) > 0 {
|
||||
modelFile = models[0]
|
||||
log.Debug().Msgf("No model specified, using: %s", modelFile)
|
||||
} else {
|
||||
log.Debug().Msgf("No model specified, returning error")
|
||||
return "", nil, fmt.Errorf("no model specified")
|
||||
}
|
||||
}
|
||||
|
||||
// If a model is found in bearer token takes precedence
|
||||
if bearerExists {
|
||||
log.Debug().Msgf("Using model from bearer token: %s", bearer)
|
||||
modelFile = bearer
|
||||
}
|
||||
return modelFile, input, nil
|
||||
}
|
||||
|
||||
func updateConfig(config *config.Config, input *schema.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.Backend != "" {
|
||||
config.Backend = input.Backend
|
||||
}
|
||||
|
||||
if input.ClipSkip != 0 {
|
||||
config.Diffusers.ClipSkip = input.ClipSkip
|
||||
}
|
||||
|
||||
if input.ModelBaseName != "" {
|
||||
config.AutoGPTQ.ModelBaseName = input.ModelBaseName
|
||||
}
|
||||
|
||||
if input.NegativePromptScale != 0 {
|
||||
config.NegativePromptScale = input.NegativePromptScale
|
||||
}
|
||||
|
||||
if input.UseFastTokenizer {
|
||||
config.UseFastTokenizer = input.UseFastTokenizer
|
||||
}
|
||||
|
||||
if input.NegativePrompt != "" {
|
||||
config.NegativePrompt = input.NegativePrompt
|
||||
}
|
||||
|
||||
if input.RopeFreqBase != 0 {
|
||||
config.RopeFreqBase = input.RopeFreqBase
|
||||
}
|
||||
|
||||
if input.RopeFreqScale != 0 {
|
||||
config.RopeFreqScale = input.RopeFreqScale
|
||||
}
|
||||
|
||||
if input.Grammar != "" {
|
||||
config.Grammar = input.Grammar
|
||||
}
|
||||
|
||||
if input.Temperature != 0 {
|
||||
config.Temperature = input.Temperature
|
||||
}
|
||||
|
||||
if input.Maxtokens != 0 {
|
||||
config.Maxtokens = input.Maxtokens
|
||||
}
|
||||
|
||||
switch stop := input.Stop.(type) {
|
||||
case string:
|
||||
if stop != "" {
|
||||
config.StopWords = append(config.StopWords, stop)
|
||||
}
|
||||
case []interface{}:
|
||||
for _, pp := range stop {
|
||||
if s, ok := pp.(string); ok {
|
||||
config.StopWords = append(config.StopWords, s)
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
if input.RepeatPenalty != 0 {
|
||||
config.RepeatPenalty = input.RepeatPenalty
|
||||
}
|
||||
|
||||
if input.Keep != 0 {
|
||||
config.Keep = input.Keep
|
||||
}
|
||||
|
||||
if input.Batch != 0 {
|
||||
config.Batch = input.Batch
|
||||
}
|
||||
|
||||
if input.F16 {
|
||||
config.F16 = input.F16
|
||||
}
|
||||
|
||||
if input.IgnoreEOS {
|
||||
config.IgnoreEOS = input.IgnoreEOS
|
||||
}
|
||||
|
||||
if input.Seed != 0 {
|
||||
config.Seed = input.Seed
|
||||
}
|
||||
|
||||
if input.Mirostat != 0 {
|
||||
config.LLMConfig.Mirostat = input.Mirostat
|
||||
}
|
||||
|
||||
if input.MirostatETA != 0 {
|
||||
config.LLMConfig.MirostatETA = input.MirostatETA
|
||||
}
|
||||
|
||||
if input.MirostatTAU != 0 {
|
||||
config.LLMConfig.MirostatTAU = input.MirostatTAU
|
||||
}
|
||||
|
||||
if input.TypicalP != 0 {
|
||||
config.TypicalP = input.TypicalP
|
||||
}
|
||||
|
||||
switch inputs := input.Input.(type) {
|
||||
case string:
|
||||
if inputs != "" {
|
||||
config.InputStrings = append(config.InputStrings, inputs)
|
||||
}
|
||||
case []interface{}:
|
||||
for _, pp := range inputs {
|
||||
switch i := pp.(type) {
|
||||
case string:
|
||||
config.InputStrings = append(config.InputStrings, i)
|
||||
case []interface{}:
|
||||
tokens := []int{}
|
||||
for _, ii := range i {
|
||||
tokens = append(tokens, int(ii.(float64)))
|
||||
}
|
||||
config.InputToken = append(config.InputToken, tokens)
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// Can be either a string or an object
|
||||
switch fnc := input.FunctionCall.(type) {
|
||||
case string:
|
||||
if fnc != "" {
|
||||
config.SetFunctionCallString(fnc)
|
||||
}
|
||||
case map[string]interface{}:
|
||||
var name string
|
||||
n, exists := fnc["name"]
|
||||
if exists {
|
||||
nn, e := n.(string)
|
||||
if e {
|
||||
name = nn
|
||||
}
|
||||
}
|
||||
config.SetFunctionCallNameString(name)
|
||||
}
|
||||
|
||||
switch p := input.Prompt.(type) {
|
||||
case string:
|
||||
config.PromptStrings = append(config.PromptStrings, p)
|
||||
case []interface{}:
|
||||
for _, pp := range p {
|
||||
if s, ok := pp.(string); ok {
|
||||
config.PromptStrings = append(config.PromptStrings, s)
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
func readConfig(modelFile string, input *schema.OpenAIRequest, cm *config.ConfigLoader, loader *model.ModelLoader, debug bool, threads, ctx int, f16 bool) (*config.Config, *schema.OpenAIRequest, error) {
|
||||
// Load a config file if present after the model name
|
||||
modelConfig := filepath.Join(loader.ModelPath, modelFile+".yaml")
|
||||
|
||||
var cfg *config.Config
|
||||
|
||||
defaults := func() {
|
||||
cfg = config.DefaultConfig(modelFile)
|
||||
cfg.ContextSize = ctx
|
||||
cfg.Threads = threads
|
||||
cfg.F16 = f16
|
||||
cfg.Debug = debug
|
||||
}
|
||||
|
||||
cfgExisting, exists := cm.GetConfig(modelFile)
|
||||
if !exists {
|
||||
if _, err := os.Stat(modelConfig); err == nil {
|
||||
if err := cm.LoadConfig(modelConfig); err != nil {
|
||||
return nil, nil, fmt.Errorf("failed loading model config (%s) %s", modelConfig, err.Error())
|
||||
}
|
||||
cfgExisting, exists = cm.GetConfig(modelFile)
|
||||
if exists {
|
||||
cfg = &cfgExisting
|
||||
} else {
|
||||
defaults()
|
||||
}
|
||||
} else {
|
||||
defaults()
|
||||
}
|
||||
} else {
|
||||
cfg = &cfgExisting
|
||||
}
|
||||
|
||||
// Set the parameters for the language model prediction
|
||||
updateConfig(cfg, input)
|
||||
|
||||
// Don't allow 0 as setting
|
||||
if cfg.Threads == 0 {
|
||||
if threads != 0 {
|
||||
cfg.Threads = threads
|
||||
} else {
|
||||
cfg.Threads = 4
|
||||
}
|
||||
}
|
||||
|
||||
// Enforce debug flag if passed from CLI
|
||||
if debug {
|
||||
cfg.Debug = true
|
||||
}
|
||||
|
||||
return cfg, input, nil
|
||||
}
|
||||
71
api/openai/transcription.go
Normal file
71
api/openai/transcription.go
Normal file
@@ -0,0 +1,71 @@
|
||||
package openai
|
||||
|
||||
import (
|
||||
"fmt"
|
||||
"io"
|
||||
"net/http"
|
||||
"os"
|
||||
"path"
|
||||
"path/filepath"
|
||||
|
||||
"github.com/go-skynet/LocalAI/api/backend"
|
||||
config "github.com/go-skynet/LocalAI/api/config"
|
||||
"github.com/go-skynet/LocalAI/api/options"
|
||||
|
||||
"github.com/gofiber/fiber/v2"
|
||||
"github.com/rs/zerolog/log"
|
||||
)
|
||||
|
||||
// https://platform.openai.com/docs/api-reference/audio/create
|
||||
func TranscriptEndpoint(cm *config.ConfigLoader, o *options.Option) func(c *fiber.Ctx) error {
|
||||
return func(c *fiber.Ctx) error {
|
||||
m, input, err := readInput(c, o, false)
|
||||
if err != nil {
|
||||
return fmt.Errorf("failed reading parameters from request:%w", err)
|
||||
}
|
||||
|
||||
config, input, err := readConfig(m, input, cm, o.Loader, o.Debug, o.Threads, o.ContextSize, o.F16)
|
||||
if err != nil {
|
||||
return fmt.Errorf("failed reading parameters from request:%w", err)
|
||||
}
|
||||
// retrieve the file data from the request
|
||||
file, err := c.FormFile("file")
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
f, err := file.Open()
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
defer f.Close()
|
||||
|
||||
dir, err := os.MkdirTemp("", "whisper")
|
||||
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
defer os.RemoveAll(dir)
|
||||
|
||||
dst := filepath.Join(dir, path.Base(file.Filename))
|
||||
dstFile, err := os.Create(dst)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
|
||||
if _, err := io.Copy(dstFile, f); err != nil {
|
||||
log.Debug().Msgf("Audio file copying error %+v - %+v - err %+v", file.Filename, dst, err)
|
||||
return err
|
||||
}
|
||||
|
||||
log.Debug().Msgf("Audio file copied to: %+v", dst)
|
||||
|
||||
tr, err := backend.ModelTranscription(dst, input.Language, o.Loader, *config, o)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
|
||||
log.Debug().Msgf("Trascribed: %+v", tr)
|
||||
// TODO: handle different outputs here
|
||||
return c.Status(http.StatusOK).JSON(tr)
|
||||
}
|
||||
}
|
||||
121
api/options.go
121
api/options.go
@@ -1,121 +0,0 @@
|
||||
package api
|
||||
|
||||
import (
|
||||
"context"
|
||||
|
||||
model "github.com/go-skynet/LocalAI/pkg/model"
|
||||
)
|
||||
|
||||
type Option struct {
|
||||
context context.Context
|
||||
configFile string
|
||||
loader *model.ModelLoader
|
||||
uploadLimitMB, threads, ctxSize int
|
||||
f16 bool
|
||||
debug, disableMessage bool
|
||||
imageDir string
|
||||
cors bool
|
||||
preloadJSONModels string
|
||||
preloadModelsFromPath string
|
||||
corsAllowOrigins string
|
||||
}
|
||||
|
||||
type AppOption func(*Option)
|
||||
|
||||
func newOptions(o ...AppOption) *Option {
|
||||
opt := &Option{
|
||||
context: context.Background(),
|
||||
uploadLimitMB: 15,
|
||||
threads: 1,
|
||||
ctxSize: 512,
|
||||
debug: true,
|
||||
disableMessage: true,
|
||||
}
|
||||
for _, oo := range o {
|
||||
oo(opt)
|
||||
}
|
||||
return opt
|
||||
}
|
||||
|
||||
func WithCors(b bool) AppOption {
|
||||
return func(o *Option) {
|
||||
o.cors = b
|
||||
}
|
||||
}
|
||||
|
||||
func WithCorsAllowOrigins(b string) AppOption {
|
||||
return func(o *Option) {
|
||||
o.corsAllowOrigins = b
|
||||
}
|
||||
}
|
||||
|
||||
func WithContext(ctx context.Context) AppOption {
|
||||
return func(o *Option) {
|
||||
o.context = ctx
|
||||
}
|
||||
}
|
||||
|
||||
func WithYAMLConfigPreload(configFile string) AppOption {
|
||||
return func(o *Option) {
|
||||
o.preloadModelsFromPath = configFile
|
||||
}
|
||||
}
|
||||
|
||||
func WithJSONStringPreload(configFile string) AppOption {
|
||||
return func(o *Option) {
|
||||
o.preloadJSONModels = configFile
|
||||
}
|
||||
}
|
||||
func WithConfigFile(configFile string) AppOption {
|
||||
return func(o *Option) {
|
||||
o.configFile = configFile
|
||||
}
|
||||
}
|
||||
|
||||
func WithModelLoader(loader *model.ModelLoader) AppOption {
|
||||
return func(o *Option) {
|
||||
o.loader = loader
|
||||
}
|
||||
}
|
||||
|
||||
func WithUploadLimitMB(limit int) AppOption {
|
||||
return func(o *Option) {
|
||||
o.uploadLimitMB = limit
|
||||
}
|
||||
}
|
||||
|
||||
func WithThreads(threads int) AppOption {
|
||||
return func(o *Option) {
|
||||
o.threads = threads
|
||||
}
|
||||
}
|
||||
|
||||
func WithContextSize(ctxSize int) AppOption {
|
||||
return func(o *Option) {
|
||||
o.ctxSize = ctxSize
|
||||
}
|
||||
}
|
||||
|
||||
func WithF16(f16 bool) AppOption {
|
||||
return func(o *Option) {
|
||||
o.f16 = f16
|
||||
}
|
||||
}
|
||||
|
||||
func WithDebug(debug bool) AppOption {
|
||||
return func(o *Option) {
|
||||
o.debug = debug
|
||||
}
|
||||
}
|
||||
|
||||
func WithDisableMessage(disableMessage bool) AppOption {
|
||||
return func(o *Option) {
|
||||
o.disableMessage = disableMessage
|
||||
}
|
||||
}
|
||||
|
||||
func WithImageDir(imageDir string) AppOption {
|
||||
return func(o *Option) {
|
||||
o.imageDir = imageDir
|
||||
}
|
||||
}
|
||||
199
api/options/options.go
Normal file
199
api/options/options.go
Normal file
@@ -0,0 +1,199 @@
|
||||
package options
|
||||
|
||||
import (
|
||||
"context"
|
||||
"embed"
|
||||
"encoding/json"
|
||||
|
||||
"github.com/go-skynet/LocalAI/pkg/gallery"
|
||||
model "github.com/go-skynet/LocalAI/pkg/model"
|
||||
"github.com/rs/zerolog/log"
|
||||
)
|
||||
|
||||
type Option struct {
|
||||
Context context.Context
|
||||
ConfigFile string
|
||||
Loader *model.ModelLoader
|
||||
UploadLimitMB, Threads, ContextSize int
|
||||
F16 bool
|
||||
Debug, DisableMessage bool
|
||||
ImageDir string
|
||||
AudioDir string
|
||||
CORS bool
|
||||
PreloadJSONModels string
|
||||
PreloadModelsFromPath string
|
||||
CORSAllowOrigins string
|
||||
ApiKeys []string
|
||||
|
||||
Galleries []gallery.Gallery
|
||||
|
||||
BackendAssets embed.FS
|
||||
AssetsDestination string
|
||||
|
||||
ExternalGRPCBackends map[string]string
|
||||
|
||||
AutoloadGalleries bool
|
||||
|
||||
SingleBackend bool
|
||||
}
|
||||
|
||||
type AppOption func(*Option)
|
||||
|
||||
func NewOptions(o ...AppOption) *Option {
|
||||
opt := &Option{
|
||||
Context: context.Background(),
|
||||
UploadLimitMB: 15,
|
||||
Threads: 1,
|
||||
ContextSize: 512,
|
||||
Debug: true,
|
||||
DisableMessage: true,
|
||||
}
|
||||
for _, oo := range o {
|
||||
oo(opt)
|
||||
}
|
||||
return opt
|
||||
}
|
||||
|
||||
func WithCors(b bool) AppOption {
|
||||
return func(o *Option) {
|
||||
o.CORS = b
|
||||
}
|
||||
}
|
||||
|
||||
var EnableSingleBackend = func(o *Option) {
|
||||
o.SingleBackend = true
|
||||
}
|
||||
|
||||
var EnableGalleriesAutoload = func(o *Option) {
|
||||
o.AutoloadGalleries = true
|
||||
}
|
||||
|
||||
func WithExternalBackend(name string, uri string) AppOption {
|
||||
return func(o *Option) {
|
||||
if o.ExternalGRPCBackends == nil {
|
||||
o.ExternalGRPCBackends = make(map[string]string)
|
||||
}
|
||||
o.ExternalGRPCBackends[name] = uri
|
||||
}
|
||||
}
|
||||
|
||||
func WithCorsAllowOrigins(b string) AppOption {
|
||||
return func(o *Option) {
|
||||
o.CORSAllowOrigins = b
|
||||
}
|
||||
}
|
||||
|
||||
func WithBackendAssetsOutput(out string) AppOption {
|
||||
return func(o *Option) {
|
||||
o.AssetsDestination = out
|
||||
}
|
||||
}
|
||||
|
||||
func WithBackendAssets(f embed.FS) AppOption {
|
||||
return func(o *Option) {
|
||||
o.BackendAssets = f
|
||||
}
|
||||
}
|
||||
|
||||
func WithStringGalleries(galls string) AppOption {
|
||||
return func(o *Option) {
|
||||
if galls == "" {
|
||||
log.Debug().Msgf("no galleries to load")
|
||||
return
|
||||
}
|
||||
var galleries []gallery.Gallery
|
||||
if err := json.Unmarshal([]byte(galls), &galleries); err != nil {
|
||||
log.Error().Msgf("failed loading galleries: %s", err.Error())
|
||||
}
|
||||
o.Galleries = append(o.Galleries, galleries...)
|
||||
}
|
||||
}
|
||||
|
||||
func WithGalleries(galleries []gallery.Gallery) AppOption {
|
||||
return func(o *Option) {
|
||||
o.Galleries = append(o.Galleries, galleries...)
|
||||
}
|
||||
}
|
||||
|
||||
func WithContext(ctx context.Context) AppOption {
|
||||
return func(o *Option) {
|
||||
o.Context = ctx
|
||||
}
|
||||
}
|
||||
|
||||
func WithYAMLConfigPreload(configFile string) AppOption {
|
||||
return func(o *Option) {
|
||||
o.PreloadModelsFromPath = configFile
|
||||
}
|
||||
}
|
||||
|
||||
func WithJSONStringPreload(configFile string) AppOption {
|
||||
return func(o *Option) {
|
||||
o.PreloadJSONModels = configFile
|
||||
}
|
||||
}
|
||||
func WithConfigFile(configFile string) AppOption {
|
||||
return func(o *Option) {
|
||||
o.ConfigFile = configFile
|
||||
}
|
||||
}
|
||||
|
||||
func WithModelLoader(loader *model.ModelLoader) AppOption {
|
||||
return func(o *Option) {
|
||||
o.Loader = loader
|
||||
}
|
||||
}
|
||||
|
||||
func WithUploadLimitMB(limit int) AppOption {
|
||||
return func(o *Option) {
|
||||
o.UploadLimitMB = limit
|
||||
}
|
||||
}
|
||||
|
||||
func WithThreads(threads int) AppOption {
|
||||
return func(o *Option) {
|
||||
o.Threads = threads
|
||||
}
|
||||
}
|
||||
|
||||
func WithContextSize(ctxSize int) AppOption {
|
||||
return func(o *Option) {
|
||||
o.ContextSize = ctxSize
|
||||
}
|
||||
}
|
||||
|
||||
func WithF16(f16 bool) AppOption {
|
||||
return func(o *Option) {
|
||||
o.F16 = f16
|
||||
}
|
||||
}
|
||||
|
||||
func WithDebug(debug bool) AppOption {
|
||||
return func(o *Option) {
|
||||
o.Debug = debug
|
||||
}
|
||||
}
|
||||
|
||||
func WithDisableMessage(disableMessage bool) AppOption {
|
||||
return func(o *Option) {
|
||||
o.DisableMessage = disableMessage
|
||||
}
|
||||
}
|
||||
|
||||
func WithAudioDir(audioDir string) AppOption {
|
||||
return func(o *Option) {
|
||||
o.AudioDir = audioDir
|
||||
}
|
||||
}
|
||||
|
||||
func WithImageDir(imageDir string) AppOption {
|
||||
return func(o *Option) {
|
||||
o.ImageDir = imageDir
|
||||
}
|
||||
}
|
||||
|
||||
func WithApiKeys(apiKeys []string) AppOption {
|
||||
return func(o *Option) {
|
||||
o.ApiKeys = apiKeys
|
||||
}
|
||||
}
|
||||
@@ -1,574 +0,0 @@
|
||||
package api
|
||||
|
||||
import (
|
||||
"fmt"
|
||||
"os"
|
||||
"path/filepath"
|
||||
"regexp"
|
||||
"strings"
|
||||
"sync"
|
||||
|
||||
"github.com/donomii/go-rwkv.cpp"
|
||||
model "github.com/go-skynet/LocalAI/pkg/model"
|
||||
"github.com/go-skynet/LocalAI/pkg/stablediffusion"
|
||||
"github.com/go-skynet/bloomz.cpp"
|
||||
bert "github.com/go-skynet/go-bert.cpp"
|
||||
transformers "github.com/go-skynet/go-ggml-transformers.cpp"
|
||||
llama "github.com/go-skynet/go-llama.cpp"
|
||||
gpt4all "github.com/nomic-ai/gpt4all/gpt4all-bindings/golang"
|
||||
)
|
||||
|
||||
// mutex still needed, see: https://github.com/ggerganov/llama.cpp/discussions/784
|
||||
var mutexMap sync.Mutex
|
||||
var mutexes map[string]*sync.Mutex = make(map[string]*sync.Mutex)
|
||||
|
||||
func defaultLLamaOpts(c Config) []llama.ModelOption {
|
||||
llamaOpts := []llama.ModelOption{}
|
||||
if c.ContextSize != 0 {
|
||||
llamaOpts = append(llamaOpts, llama.SetContext(c.ContextSize))
|
||||
}
|
||||
if c.F16 {
|
||||
llamaOpts = append(llamaOpts, llama.EnableF16Memory)
|
||||
}
|
||||
if c.Embeddings {
|
||||
llamaOpts = append(llamaOpts, llama.EnableEmbeddings)
|
||||
}
|
||||
|
||||
if c.NGPULayers != 0 {
|
||||
llamaOpts = append(llamaOpts, llama.SetGPULayers(c.NGPULayers))
|
||||
}
|
||||
|
||||
return llamaOpts
|
||||
}
|
||||
|
||||
func ImageGeneration(height, width, mode, step, seed int, positive_prompt, negative_prompt, dst string, loader *model.ModelLoader, c Config) (func() error, error) {
|
||||
if c.Backend != model.StableDiffusionBackend {
|
||||
return nil, fmt.Errorf("endpoint only working with stablediffusion models")
|
||||
}
|
||||
inferenceModel, err := loader.BackendLoader(c.Backend, c.ImageGenerationAssets, []llama.ModelOption{}, uint32(c.Threads))
|
||||
if err != nil {
|
||||
return nil, err
|
||||
}
|
||||
|
||||
var fn func() error
|
||||
switch model := inferenceModel.(type) {
|
||||
case *stablediffusion.StableDiffusion:
|
||||
fn = func() error {
|
||||
return model.GenerateImage(height, width, mode, step, seed, positive_prompt, negative_prompt, dst)
|
||||
}
|
||||
|
||||
default:
|
||||
fn = func() error {
|
||||
return fmt.Errorf("creation of images not supported by the backend")
|
||||
}
|
||||
}
|
||||
|
||||
return func() error {
|
||||
// This is still needed, see: https://github.com/ggerganov/llama.cpp/discussions/784
|
||||
mutexMap.Lock()
|
||||
l, ok := mutexes[c.Backend]
|
||||
if !ok {
|
||||
m := &sync.Mutex{}
|
||||
mutexes[c.Backend] = m
|
||||
l = m
|
||||
}
|
||||
mutexMap.Unlock()
|
||||
l.Lock()
|
||||
defer l.Unlock()
|
||||
|
||||
return fn()
|
||||
}, nil
|
||||
}
|
||||
|
||||
func ModelEmbedding(s string, tokens []int, loader *model.ModelLoader, c Config) (func() ([]float32, error), error) {
|
||||
if !c.Embeddings {
|
||||
return nil, fmt.Errorf("endpoint disabled for this model by API configuration")
|
||||
}
|
||||
|
||||
modelFile := c.Model
|
||||
|
||||
llamaOpts := defaultLLamaOpts(c)
|
||||
|
||||
var inferenceModel interface{}
|
||||
var err error
|
||||
if c.Backend == "" {
|
||||
inferenceModel, err = loader.GreedyLoader(modelFile, llamaOpts, uint32(c.Threads))
|
||||
} else {
|
||||
inferenceModel, err = loader.BackendLoader(c.Backend, modelFile, llamaOpts, uint32(c.Threads))
|
||||
}
|
||||
if err != nil {
|
||||
return nil, err
|
||||
}
|
||||
|
||||
var fn func() ([]float32, error)
|
||||
switch model := inferenceModel.(type) {
|
||||
case *llama.LLama:
|
||||
fn = func() ([]float32, error) {
|
||||
predictOptions := buildLLamaPredictOptions(c, loader.ModelPath)
|
||||
if len(tokens) > 0 {
|
||||
return model.TokenEmbeddings(tokens, predictOptions...)
|
||||
}
|
||||
return model.Embeddings(s, predictOptions...)
|
||||
}
|
||||
// bert embeddings
|
||||
case *bert.Bert:
|
||||
fn = func() ([]float32, error) {
|
||||
if len(tokens) > 0 {
|
||||
return model.TokenEmbeddings(tokens, bert.SetThreads(c.Threads))
|
||||
}
|
||||
return model.Embeddings(s, bert.SetThreads(c.Threads))
|
||||
}
|
||||
default:
|
||||
fn = func() ([]float32, error) {
|
||||
return nil, fmt.Errorf("embeddings not supported by the backend")
|
||||
}
|
||||
}
|
||||
|
||||
return func() ([]float32, error) {
|
||||
// This is still needed, see: https://github.com/ggerganov/llama.cpp/discussions/784
|
||||
mutexMap.Lock()
|
||||
l, ok := mutexes[modelFile]
|
||||
if !ok {
|
||||
m := &sync.Mutex{}
|
||||
mutexes[modelFile] = m
|
||||
l = m
|
||||
}
|
||||
mutexMap.Unlock()
|
||||
l.Lock()
|
||||
defer l.Unlock()
|
||||
|
||||
embeds, err := fn()
|
||||
if err != nil {
|
||||
return embeds, err
|
||||
}
|
||||
// Remove trailing 0s
|
||||
for i := len(embeds) - 1; i >= 0; i-- {
|
||||
if embeds[i] == 0.0 {
|
||||
embeds = embeds[:i]
|
||||
} else {
|
||||
break
|
||||
}
|
||||
}
|
||||
return embeds, nil
|
||||
}, nil
|
||||
}
|
||||
|
||||
func buildLLamaPredictOptions(c Config, modelPath string) []llama.PredictOption {
|
||||
// Generate the prediction using the language model
|
||||
predictOptions := []llama.PredictOption{
|
||||
llama.SetTemperature(c.Temperature),
|
||||
llama.SetTopP(c.TopP),
|
||||
llama.SetTopK(c.TopK),
|
||||
llama.SetTokens(c.Maxtokens),
|
||||
llama.SetThreads(c.Threads),
|
||||
}
|
||||
|
||||
if c.PromptCacheAll {
|
||||
predictOptions = append(predictOptions, llama.EnablePromptCacheAll)
|
||||
}
|
||||
|
||||
if c.PromptCachePath != "" {
|
||||
// Create parent directory
|
||||
p := filepath.Join(modelPath, c.PromptCachePath)
|
||||
os.MkdirAll(filepath.Dir(p), 0755)
|
||||
predictOptions = append(predictOptions, llama.SetPathPromptCache(p))
|
||||
}
|
||||
|
||||
if c.Mirostat != 0 {
|
||||
predictOptions = append(predictOptions, llama.SetMirostat(c.Mirostat))
|
||||
}
|
||||
|
||||
if c.MirostatETA != 0 {
|
||||
predictOptions = append(predictOptions, llama.SetMirostatETA(c.MirostatETA))
|
||||
}
|
||||
|
||||
if c.MirostatTAU != 0 {
|
||||
predictOptions = append(predictOptions, llama.SetMirostatTAU(c.MirostatTAU))
|
||||
}
|
||||
|
||||
if c.Debug {
|
||||
predictOptions = append(predictOptions, llama.Debug)
|
||||
}
|
||||
|
||||
predictOptions = append(predictOptions, llama.SetStopWords(c.StopWords...))
|
||||
|
||||
if c.RepeatPenalty != 0 {
|
||||
predictOptions = append(predictOptions, llama.SetPenalty(c.RepeatPenalty))
|
||||
}
|
||||
|
||||
if c.Keep != 0 {
|
||||
predictOptions = append(predictOptions, llama.SetNKeep(c.Keep))
|
||||
}
|
||||
|
||||
if c.Batch != 0 {
|
||||
predictOptions = append(predictOptions, llama.SetBatch(c.Batch))
|
||||
}
|
||||
|
||||
if c.F16 {
|
||||
predictOptions = append(predictOptions, llama.EnableF16KV)
|
||||
}
|
||||
|
||||
if c.IgnoreEOS {
|
||||
predictOptions = append(predictOptions, llama.IgnoreEOS)
|
||||
}
|
||||
|
||||
if c.Seed != 0 {
|
||||
predictOptions = append(predictOptions, llama.SetSeed(c.Seed))
|
||||
}
|
||||
|
||||
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 *transformers.GPTNeoX:
|
||||
fn = func() (string, error) {
|
||||
// Generate the prediction using the language model
|
||||
predictOptions := []transformers.PredictOption{
|
||||
transformers.SetTemperature(c.Temperature),
|
||||
transformers.SetTopP(c.TopP),
|
||||
transformers.SetTopK(c.TopK),
|
||||
transformers.SetTokens(c.Maxtokens),
|
||||
transformers.SetThreads(c.Threads),
|
||||
}
|
||||
|
||||
if c.Batch != 0 {
|
||||
predictOptions = append(predictOptions, transformers.SetBatch(c.Batch))
|
||||
}
|
||||
|
||||
if c.Seed != 0 {
|
||||
predictOptions = append(predictOptions, transformers.SetSeed(c.Seed))
|
||||
}
|
||||
|
||||
return model.Predict(
|
||||
s,
|
||||
predictOptions...,
|
||||
)
|
||||
}
|
||||
case *transformers.Replit:
|
||||
fn = func() (string, error) {
|
||||
// Generate the prediction using the language model
|
||||
predictOptions := []transformers.PredictOption{
|
||||
transformers.SetTemperature(c.Temperature),
|
||||
transformers.SetTopP(c.TopP),
|
||||
transformers.SetTopK(c.TopK),
|
||||
transformers.SetTokens(c.Maxtokens),
|
||||
transformers.SetThreads(c.Threads),
|
||||
}
|
||||
|
||||
if c.Batch != 0 {
|
||||
predictOptions = append(predictOptions, transformers.SetBatch(c.Batch))
|
||||
}
|
||||
|
||||
if c.Seed != 0 {
|
||||
predictOptions = append(predictOptions, transformers.SetSeed(c.Seed))
|
||||
}
|
||||
|
||||
return model.Predict(
|
||||
s,
|
||||
predictOptions...,
|
||||
)
|
||||
}
|
||||
case *transformers.Starcoder:
|
||||
fn = func() (string, error) {
|
||||
// Generate the prediction using the language model
|
||||
predictOptions := []transformers.PredictOption{
|
||||
transformers.SetTemperature(c.Temperature),
|
||||
transformers.SetTopP(c.TopP),
|
||||
transformers.SetTopK(c.TopK),
|
||||
transformers.SetTokens(c.Maxtokens),
|
||||
transformers.SetThreads(c.Threads),
|
||||
}
|
||||
|
||||
if c.Batch != 0 {
|
||||
predictOptions = append(predictOptions, transformers.SetBatch(c.Batch))
|
||||
}
|
||||
|
||||
if c.Seed != 0 {
|
||||
predictOptions = append(predictOptions, transformers.SetSeed(c.Seed))
|
||||
}
|
||||
|
||||
return model.Predict(
|
||||
s,
|
||||
predictOptions...,
|
||||
)
|
||||
}
|
||||
case *transformers.MPT:
|
||||
fn = func() (string, error) {
|
||||
// Generate the prediction using the language model
|
||||
predictOptions := []transformers.PredictOption{
|
||||
transformers.SetTemperature(c.Temperature),
|
||||
transformers.SetTopP(c.TopP),
|
||||
transformers.SetTopK(c.TopK),
|
||||
transformers.SetTokens(c.Maxtokens),
|
||||
transformers.SetThreads(c.Threads),
|
||||
}
|
||||
|
||||
if c.Batch != 0 {
|
||||
predictOptions = append(predictOptions, transformers.SetBatch(c.Batch))
|
||||
}
|
||||
|
||||
if c.Seed != 0 {
|
||||
predictOptions = append(predictOptions, transformers.SetSeed(c.Seed))
|
||||
}
|
||||
|
||||
return model.Predict(
|
||||
s,
|
||||
predictOptions...,
|
||||
)
|
||||
}
|
||||
case *bloomz.Bloomz:
|
||||
fn = func() (string, error) {
|
||||
// Generate the prediction using the language model
|
||||
predictOptions := []bloomz.PredictOption{
|
||||
bloomz.SetTemperature(c.Temperature),
|
||||
bloomz.SetTopP(c.TopP),
|
||||
bloomz.SetTopK(c.TopK),
|
||||
bloomz.SetTokens(c.Maxtokens),
|
||||
bloomz.SetThreads(c.Threads),
|
||||
}
|
||||
|
||||
if c.Seed != 0 {
|
||||
predictOptions = append(predictOptions, bloomz.SetSeed(c.Seed))
|
||||
}
|
||||
|
||||
return model.Predict(
|
||||
s,
|
||||
predictOptions...,
|
||||
)
|
||||
}
|
||||
case *transformers.GPTJ:
|
||||
fn = func() (string, error) {
|
||||
// Generate the prediction using the language model
|
||||
predictOptions := []transformers.PredictOption{
|
||||
transformers.SetTemperature(c.Temperature),
|
||||
transformers.SetTopP(c.TopP),
|
||||
transformers.SetTopK(c.TopK),
|
||||
transformers.SetTokens(c.Maxtokens),
|
||||
transformers.SetThreads(c.Threads),
|
||||
}
|
||||
|
||||
if c.Batch != 0 {
|
||||
predictOptions = append(predictOptions, transformers.SetBatch(c.Batch))
|
||||
}
|
||||
|
||||
if c.Seed != 0 {
|
||||
predictOptions = append(predictOptions, transformers.SetSeed(c.Seed))
|
||||
}
|
||||
|
||||
return model.Predict(
|
||||
s,
|
||||
predictOptions...,
|
||||
)
|
||||
}
|
||||
case *transformers.Dolly:
|
||||
fn = func() (string, error) {
|
||||
// Generate the prediction using the language model
|
||||
predictOptions := []transformers.PredictOption{
|
||||
transformers.SetTemperature(c.Temperature),
|
||||
transformers.SetTopP(c.TopP),
|
||||
transformers.SetTopK(c.TopK),
|
||||
transformers.SetTokens(c.Maxtokens),
|
||||
transformers.SetThreads(c.Threads),
|
||||
}
|
||||
|
||||
if c.Batch != 0 {
|
||||
predictOptions = append(predictOptions, transformers.SetBatch(c.Batch))
|
||||
}
|
||||
|
||||
if c.Seed != 0 {
|
||||
predictOptions = append(predictOptions, transformers.SetSeed(c.Seed))
|
||||
}
|
||||
|
||||
return model.Predict(
|
||||
s,
|
||||
predictOptions...,
|
||||
)
|
||||
}
|
||||
case *transformers.GPT2:
|
||||
fn = func() (string, error) {
|
||||
// Generate the prediction using the language model
|
||||
predictOptions := []transformers.PredictOption{
|
||||
transformers.SetTemperature(c.Temperature),
|
||||
transformers.SetTopP(c.TopP),
|
||||
transformers.SetTopK(c.TopK),
|
||||
transformers.SetTokens(c.Maxtokens),
|
||||
transformers.SetThreads(c.Threads),
|
||||
}
|
||||
|
||||
if c.Batch != 0 {
|
||||
predictOptions = append(predictOptions, transformers.SetBatch(c.Batch))
|
||||
}
|
||||
|
||||
if c.Seed != 0 {
|
||||
predictOptions = append(predictOptions, transformers.SetSeed(c.Seed))
|
||||
}
|
||||
|
||||
return model.Predict(
|
||||
s,
|
||||
predictOptions...,
|
||||
)
|
||||
}
|
||||
case *gpt4all.Model:
|
||||
supportStreams = true
|
||||
|
||||
fn = func() (string, error) {
|
||||
if tokenCallback != nil {
|
||||
model.SetTokenCallback(tokenCallback)
|
||||
}
|
||||
|
||||
// Generate the prediction using the language model
|
||||
predictOptions := []gpt4all.PredictOption{
|
||||
gpt4all.SetTemperature(c.Temperature),
|
||||
gpt4all.SetTopP(c.TopP),
|
||||
gpt4all.SetTopK(c.TopK),
|
||||
gpt4all.SetTokens(c.Maxtokens),
|
||||
}
|
||||
|
||||
if c.Batch != 0 {
|
||||
predictOptions = append(predictOptions, gpt4all.SetBatch(c.Batch))
|
||||
}
|
||||
|
||||
str, er := model.Predict(
|
||||
s,
|
||||
predictOptions...,
|
||||
)
|
||||
// Seems that if we don't free the callback explicitly we leave functions registered (that might try to send on closed channels)
|
||||
// For instance otherwise the API returns: {"error":{"code":500,"message":"send on closed channel","type":""}}
|
||||
// after a stream event has occurred
|
||||
model.SetTokenCallback(nil)
|
||||
return str, er
|
||||
}
|
||||
case *llama.LLama:
|
||||
supportStreams = true
|
||||
fn = func() (string, error) {
|
||||
|
||||
if tokenCallback != nil {
|
||||
model.SetTokenCallback(tokenCallback)
|
||||
}
|
||||
|
||||
predictOptions := buildLLamaPredictOptions(c, loader.ModelPath)
|
||||
|
||||
str, er := model.Predict(
|
||||
s,
|
||||
predictOptions...,
|
||||
)
|
||||
// Seems that if we don't free the callback explicitly we leave functions registered (that might try to send on closed channels)
|
||||
// For instance otherwise the API returns: {"error":{"code":500,"message":"send on closed channel","type":""}}
|
||||
// after a stream event has occurred
|
||||
model.SetTokenCallback(nil)
|
||||
return str, er
|
||||
}
|
||||
}
|
||||
|
||||
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
|
||||
|
||||
}
|
||||
115
api/schema/openai.go
Normal file
115
api/schema/openai.go
Normal file
@@ -0,0 +1,115 @@
|
||||
package schema
|
||||
|
||||
import (
|
||||
"context"
|
||||
|
||||
config "github.com/go-skynet/LocalAI/api/config"
|
||||
|
||||
"github.com/go-skynet/LocalAI/pkg/grammar"
|
||||
)
|
||||
|
||||
// APIError provides error information returned by the OpenAI API.
|
||||
type APIError struct {
|
||||
Code any `json:"code,omitempty"`
|
||||
Message string `json:"message"`
|
||||
Param *string `json:"param,omitempty"`
|
||||
Type string `json:"type"`
|
||||
}
|
||||
|
||||
type ErrorResponse struct {
|
||||
Error *APIError `json:"error,omitempty"`
|
||||
}
|
||||
|
||||
type OpenAIUsage struct {
|
||||
PromptTokens int `json:"prompt_tokens"`
|
||||
CompletionTokens int `json:"completion_tokens"`
|
||||
TotalTokens int `json:"total_tokens"`
|
||||
}
|
||||
|
||||
type Item struct {
|
||||
Embedding []float32 `json:"embedding"`
|
||||
Index int `json:"index"`
|
||||
Object string `json:"object,omitempty"`
|
||||
|
||||
// Images
|
||||
URL string `json:"url,omitempty"`
|
||||
B64JSON string `json:"b64_json,omitempty"`
|
||||
}
|
||||
|
||||
type OpenAIResponse struct {
|
||||
Created int `json:"created,omitempty"`
|
||||
Object string `json:"object,omitempty"`
|
||||
ID string `json:"id,omitempty"`
|
||||
Model string `json:"model,omitempty"`
|
||||
Choices []Choice `json:"choices,omitempty"`
|
||||
Data []Item `json:"data,omitempty"`
|
||||
|
||||
Usage OpenAIUsage `json:"usage"`
|
||||
}
|
||||
|
||||
type Choice struct {
|
||||
Index int `json:"index"`
|
||||
FinishReason string `json:"finish_reason,omitempty"`
|
||||
Message *Message `json:"message,omitempty"`
|
||||
Delta *Message `json:"delta,omitempty"`
|
||||
Text string `json:"text,omitempty"`
|
||||
}
|
||||
|
||||
type Message struct {
|
||||
// The message role
|
||||
Role string `json:"role,omitempty" yaml:"role"`
|
||||
// The message content
|
||||
Content *string `json:"content" yaml:"content"`
|
||||
// A result of a function call
|
||||
FunctionCall interface{} `json:"function_call,omitempty" yaml:"function_call,omitempty"`
|
||||
}
|
||||
|
||||
type OpenAIModel struct {
|
||||
ID string `json:"id"`
|
||||
Object string `json:"object"`
|
||||
}
|
||||
|
||||
type OpenAIRequest struct {
|
||||
config.PredictionOptions
|
||||
|
||||
Context context.Context
|
||||
Cancel context.CancelFunc
|
||||
|
||||
// whisper
|
||||
File string `json:"file" validate:"required"`
|
||||
//whisper/image
|
||||
ResponseFormat string `json:"response_format"`
|
||||
// image
|
||||
Size string `json:"size"`
|
||||
// Prompt is read only by completion/image API calls
|
||||
Prompt interface{} `json:"prompt" yaml:"prompt"`
|
||||
|
||||
// Edit endpoint
|
||||
Instruction string `json:"instruction" yaml:"instruction"`
|
||||
Input interface{} `json:"input" yaml:"input"`
|
||||
|
||||
Stop interface{} `json:"stop" yaml:"stop"`
|
||||
|
||||
// Messages is read only by chat/completion API calls
|
||||
Messages []Message `json:"messages" yaml:"messages"`
|
||||
|
||||
// A list of available functions to call
|
||||
Functions []grammar.Function `json:"functions" yaml:"functions"`
|
||||
FunctionCall interface{} `json:"function_call" yaml:"function_call"` // might be a string or an object
|
||||
|
||||
Stream bool `json:"stream"`
|
||||
|
||||
// Image (not supported by OpenAI)
|
||||
Mode int `json:"mode"`
|
||||
Step int `json:"step"`
|
||||
|
||||
// A grammar to constrain the LLM output
|
||||
Grammar string `json:"grammar" yaml:"grammar"`
|
||||
|
||||
JSONFunctionGrammarObject *grammar.JSONFunctionStructure `json:"grammar_json_functions" yaml:"grammar_json_functions"`
|
||||
|
||||
Backend string `json:"backend" yaml:"backend"`
|
||||
|
||||
// AutoGPTQ
|
||||
ModelBaseName string `json:"model_base_name" yaml:"model_base_name"`
|
||||
}
|
||||
16
api/schema/whisper.go
Normal file
16
api/schema/whisper.go
Normal file
@@ -0,0 +1,16 @@
|
||||
package schema
|
||||
|
||||
import "time"
|
||||
|
||||
type Segment struct {
|
||||
Id int `json:"id"`
|
||||
Start time.Duration `json:"start"`
|
||||
End time.Duration `json:"end"`
|
||||
Text string `json:"text"`
|
||||
Tokens []int `json:"tokens"`
|
||||
}
|
||||
|
||||
type Result struct {
|
||||
Segments []Segment `json:"segments"`
|
||||
Text string `json:"text"`
|
||||
}
|
||||
6
assets.go
Normal file
6
assets.go
Normal file
@@ -0,0 +1,6 @@
|
||||
package main
|
||||
|
||||
import "embed"
|
||||
|
||||
//go:embed backend-assets/*
|
||||
var backendAssets embed.FS
|
||||
22
cmd/grpc/bert-embeddings/main.go
Normal file
22
cmd/grpc/bert-embeddings/main.go
Normal file
@@ -0,0 +1,22 @@
|
||||
package main
|
||||
|
||||
// Note: this is started internally by LocalAI and a server is allocated for each model
|
||||
|
||||
import (
|
||||
"flag"
|
||||
|
||||
bert "github.com/go-skynet/LocalAI/pkg/backend/llm/bert"
|
||||
grpc "github.com/go-skynet/LocalAI/pkg/grpc"
|
||||
)
|
||||
|
||||
var (
|
||||
addr = flag.String("addr", "localhost:50051", "the address to connect to")
|
||||
)
|
||||
|
||||
func main() {
|
||||
flag.Parse()
|
||||
|
||||
if err := grpc.StartServer(*addr, &bert.Embeddings{}); err != nil {
|
||||
panic(err)
|
||||
}
|
||||
}
|
||||
23
cmd/grpc/bloomz/main.go
Normal file
23
cmd/grpc/bloomz/main.go
Normal file
@@ -0,0 +1,23 @@
|
||||
package main
|
||||
|
||||
// Note: this is started internally by LocalAI and a server is allocated for each model
|
||||
|
||||
import (
|
||||
"flag"
|
||||
|
||||
bloomz "github.com/go-skynet/LocalAI/pkg/backend/llm/bloomz"
|
||||
|
||||
grpc "github.com/go-skynet/LocalAI/pkg/grpc"
|
||||
)
|
||||
|
||||
var (
|
||||
addr = flag.String("addr", "localhost:50051", "the address to connect to")
|
||||
)
|
||||
|
||||
func main() {
|
||||
flag.Parse()
|
||||
|
||||
if err := grpc.StartServer(*addr, &bloomz.LLM{}); err != nil {
|
||||
panic(err)
|
||||
}
|
||||
}
|
||||
23
cmd/grpc/dolly/main.go
Normal file
23
cmd/grpc/dolly/main.go
Normal file
@@ -0,0 +1,23 @@
|
||||
package main
|
||||
|
||||
// Note: this is started internally by LocalAI and a server is allocated for each model
|
||||
|
||||
import (
|
||||
"flag"
|
||||
|
||||
transformers "github.com/go-skynet/LocalAI/pkg/backend/llm/transformers"
|
||||
|
||||
grpc "github.com/go-skynet/LocalAI/pkg/grpc"
|
||||
)
|
||||
|
||||
var (
|
||||
addr = flag.String("addr", "localhost:50051", "the address to connect to")
|
||||
)
|
||||
|
||||
func main() {
|
||||
flag.Parse()
|
||||
|
||||
if err := grpc.StartServer(*addr, &transformers.Dolly{}); err != nil {
|
||||
panic(err)
|
||||
}
|
||||
}
|
||||
23
cmd/grpc/falcon-ggml/main.go
Normal file
23
cmd/grpc/falcon-ggml/main.go
Normal file
@@ -0,0 +1,23 @@
|
||||
package main
|
||||
|
||||
// Note: this is started internally by LocalAI and a server is allocated for each model
|
||||
|
||||
import (
|
||||
"flag"
|
||||
|
||||
transformers "github.com/go-skynet/LocalAI/pkg/backend/llm/transformers"
|
||||
|
||||
grpc "github.com/go-skynet/LocalAI/pkg/grpc"
|
||||
)
|
||||
|
||||
var (
|
||||
addr = flag.String("addr", "localhost:50051", "the address to connect to")
|
||||
)
|
||||
|
||||
func main() {
|
||||
flag.Parse()
|
||||
|
||||
if err := grpc.StartServer(*addr, &transformers.Falcon{}); err != nil {
|
||||
panic(err)
|
||||
}
|
||||
}
|
||||
25
cmd/grpc/falcon/main.go
Normal file
25
cmd/grpc/falcon/main.go
Normal file
@@ -0,0 +1,25 @@
|
||||
package main
|
||||
|
||||
// GRPC Falcon server
|
||||
|
||||
// Note: this is started internally by LocalAI and a server is allocated for each model
|
||||
|
||||
import (
|
||||
"flag"
|
||||
|
||||
falcon "github.com/go-skynet/LocalAI/pkg/backend/llm/falcon"
|
||||
|
||||
grpc "github.com/go-skynet/LocalAI/pkg/grpc"
|
||||
)
|
||||
|
||||
var (
|
||||
addr = flag.String("addr", "localhost:50051", "the address to connect to")
|
||||
)
|
||||
|
||||
func main() {
|
||||
flag.Parse()
|
||||
|
||||
if err := grpc.StartServer(*addr, &falcon.LLM{}); err != nil {
|
||||
panic(err)
|
||||
}
|
||||
}
|
||||
23
cmd/grpc/gpt2/main.go
Normal file
23
cmd/grpc/gpt2/main.go
Normal file
@@ -0,0 +1,23 @@
|
||||
package main
|
||||
|
||||
// Note: this is started internally by LocalAI and a server is allocated for each model
|
||||
|
||||
import (
|
||||
"flag"
|
||||
|
||||
transformers "github.com/go-skynet/LocalAI/pkg/backend/llm/transformers"
|
||||
|
||||
grpc "github.com/go-skynet/LocalAI/pkg/grpc"
|
||||
)
|
||||
|
||||
var (
|
||||
addr = flag.String("addr", "localhost:50051", "the address to connect to")
|
||||
)
|
||||
|
||||
func main() {
|
||||
flag.Parse()
|
||||
|
||||
if err := grpc.StartServer(*addr, &transformers.GPT2{}); err != nil {
|
||||
panic(err)
|
||||
}
|
||||
}
|
||||
23
cmd/grpc/gpt4all/main.go
Normal file
23
cmd/grpc/gpt4all/main.go
Normal file
@@ -0,0 +1,23 @@
|
||||
package main
|
||||
|
||||
// Note: this is started internally by LocalAI and a server is allocated for each model
|
||||
|
||||
import (
|
||||
"flag"
|
||||
|
||||
gpt4all "github.com/go-skynet/LocalAI/pkg/backend/llm/gpt4all"
|
||||
|
||||
grpc "github.com/go-skynet/LocalAI/pkg/grpc"
|
||||
)
|
||||
|
||||
var (
|
||||
addr = flag.String("addr", "localhost:50051", "the address to connect to")
|
||||
)
|
||||
|
||||
func main() {
|
||||
flag.Parse()
|
||||
|
||||
if err := grpc.StartServer(*addr, &gpt4all.LLM{}); err != nil {
|
||||
panic(err)
|
||||
}
|
||||
}
|
||||
23
cmd/grpc/gptj/main.go
Normal file
23
cmd/grpc/gptj/main.go
Normal file
@@ -0,0 +1,23 @@
|
||||
package main
|
||||
|
||||
// Note: this is started internally by LocalAI and a server is allocated for each model
|
||||
|
||||
import (
|
||||
"flag"
|
||||
|
||||
transformers "github.com/go-skynet/LocalAI/pkg/backend/llm/transformers"
|
||||
|
||||
grpc "github.com/go-skynet/LocalAI/pkg/grpc"
|
||||
)
|
||||
|
||||
var (
|
||||
addr = flag.String("addr", "localhost:50051", "the address to connect to")
|
||||
)
|
||||
|
||||
func main() {
|
||||
flag.Parse()
|
||||
|
||||
if err := grpc.StartServer(*addr, &transformers.GPTJ{}); err != nil {
|
||||
panic(err)
|
||||
}
|
||||
}
|
||||
23
cmd/grpc/gptneox/main.go
Normal file
23
cmd/grpc/gptneox/main.go
Normal file
@@ -0,0 +1,23 @@
|
||||
package main
|
||||
|
||||
// Note: this is started internally by LocalAI and a server is allocated for each model
|
||||
|
||||
import (
|
||||
"flag"
|
||||
|
||||
transformers "github.com/go-skynet/LocalAI/pkg/backend/llm/transformers"
|
||||
|
||||
grpc "github.com/go-skynet/LocalAI/pkg/grpc"
|
||||
)
|
||||
|
||||
var (
|
||||
addr = flag.String("addr", "localhost:50051", "the address to connect to")
|
||||
)
|
||||
|
||||
func main() {
|
||||
flag.Parse()
|
||||
|
||||
if err := grpc.StartServer(*addr, &transformers.GPTNeoX{}); err != nil {
|
||||
panic(err)
|
||||
}
|
||||
}
|
||||
23
cmd/grpc/langchain-huggingface/main.go
Normal file
23
cmd/grpc/langchain-huggingface/main.go
Normal file
@@ -0,0 +1,23 @@
|
||||
package main
|
||||
|
||||
// Note: this is started internally by LocalAI and a server is allocated for each model
|
||||
|
||||
import (
|
||||
"flag"
|
||||
|
||||
langchain "github.com/go-skynet/LocalAI/pkg/backend/llm/langchain"
|
||||
|
||||
grpc "github.com/go-skynet/LocalAI/pkg/grpc"
|
||||
)
|
||||
|
||||
var (
|
||||
addr = flag.String("addr", "localhost:50051", "the address to connect to")
|
||||
)
|
||||
|
||||
func main() {
|
||||
flag.Parse()
|
||||
|
||||
if err := grpc.StartServer(*addr, &langchain.LLM{}); err != nil {
|
||||
panic(err)
|
||||
}
|
||||
}
|
||||
21
cmd/grpc/llama-stable/main.go
Normal file
21
cmd/grpc/llama-stable/main.go
Normal file
@@ -0,0 +1,21 @@
|
||||
package main
|
||||
|
||||
import (
|
||||
"flag"
|
||||
|
||||
llama "github.com/go-skynet/LocalAI/pkg/backend/llm/llama-stable"
|
||||
|
||||
grpc "github.com/go-skynet/LocalAI/pkg/grpc"
|
||||
)
|
||||
|
||||
var (
|
||||
addr = flag.String("addr", "localhost:50051", "the address to connect to")
|
||||
)
|
||||
|
||||
func main() {
|
||||
flag.Parse()
|
||||
|
||||
if err := grpc.StartServer(*addr, &llama.LLM{}); err != nil {
|
||||
panic(err)
|
||||
}
|
||||
}
|
||||
25
cmd/grpc/llama/main.go
Normal file
25
cmd/grpc/llama/main.go
Normal file
@@ -0,0 +1,25 @@
|
||||
package main
|
||||
|
||||
// GRPC Falcon server
|
||||
|
||||
// Note: this is started internally by LocalAI and a server is allocated for each model
|
||||
|
||||
import (
|
||||
"flag"
|
||||
|
||||
llama "github.com/go-skynet/LocalAI/pkg/backend/llm/llama"
|
||||
|
||||
grpc "github.com/go-skynet/LocalAI/pkg/grpc"
|
||||
)
|
||||
|
||||
var (
|
||||
addr = flag.String("addr", "localhost:50051", "the address to connect to")
|
||||
)
|
||||
|
||||
func main() {
|
||||
flag.Parse()
|
||||
|
||||
if err := grpc.StartServer(*addr, &llama.LLM{}); err != nil {
|
||||
panic(err)
|
||||
}
|
||||
}
|
||||
23
cmd/grpc/mpt/main.go
Normal file
23
cmd/grpc/mpt/main.go
Normal file
@@ -0,0 +1,23 @@
|
||||
package main
|
||||
|
||||
// Note: this is started internally by LocalAI and a server is allocated for each model
|
||||
|
||||
import (
|
||||
"flag"
|
||||
|
||||
transformers "github.com/go-skynet/LocalAI/pkg/backend/llm/transformers"
|
||||
|
||||
grpc "github.com/go-skynet/LocalAI/pkg/grpc"
|
||||
)
|
||||
|
||||
var (
|
||||
addr = flag.String("addr", "localhost:50051", "the address to connect to")
|
||||
)
|
||||
|
||||
func main() {
|
||||
flag.Parse()
|
||||
|
||||
if err := grpc.StartServer(*addr, &transformers.MPT{}); err != nil {
|
||||
panic(err)
|
||||
}
|
||||
}
|
||||
23
cmd/grpc/piper/main.go
Normal file
23
cmd/grpc/piper/main.go
Normal file
@@ -0,0 +1,23 @@
|
||||
package main
|
||||
|
||||
// Note: this is started internally by LocalAI and a server is allocated for each model
|
||||
|
||||
import (
|
||||
"flag"
|
||||
|
||||
tts "github.com/go-skynet/LocalAI/pkg/backend/tts"
|
||||
|
||||
grpc "github.com/go-skynet/LocalAI/pkg/grpc"
|
||||
)
|
||||
|
||||
var (
|
||||
addr = flag.String("addr", "localhost:50051", "the address to connect to")
|
||||
)
|
||||
|
||||
func main() {
|
||||
flag.Parse()
|
||||
|
||||
if err := grpc.StartServer(*addr, &tts.Piper{}); err != nil {
|
||||
panic(err)
|
||||
}
|
||||
}
|
||||
23
cmd/grpc/replit/main.go
Normal file
23
cmd/grpc/replit/main.go
Normal file
@@ -0,0 +1,23 @@
|
||||
package main
|
||||
|
||||
// Note: this is started internally by LocalAI and a server is allocated for each model
|
||||
|
||||
import (
|
||||
"flag"
|
||||
|
||||
transformers "github.com/go-skynet/LocalAI/pkg/backend/llm/transformers"
|
||||
|
||||
grpc "github.com/go-skynet/LocalAI/pkg/grpc"
|
||||
)
|
||||
|
||||
var (
|
||||
addr = flag.String("addr", "localhost:50051", "the address to connect to")
|
||||
)
|
||||
|
||||
func main() {
|
||||
flag.Parse()
|
||||
|
||||
if err := grpc.StartServer(*addr, &transformers.Replit{}); err != nil {
|
||||
panic(err)
|
||||
}
|
||||
}
|
||||
23
cmd/grpc/rwkv/main.go
Normal file
23
cmd/grpc/rwkv/main.go
Normal file
@@ -0,0 +1,23 @@
|
||||
package main
|
||||
|
||||
// Note: this is started internally by LocalAI and a server is allocated for each model
|
||||
|
||||
import (
|
||||
"flag"
|
||||
|
||||
rwkv "github.com/go-skynet/LocalAI/pkg/backend/llm/rwkv"
|
||||
|
||||
grpc "github.com/go-skynet/LocalAI/pkg/grpc"
|
||||
)
|
||||
|
||||
var (
|
||||
addr = flag.String("addr", "localhost:50051", "the address to connect to")
|
||||
)
|
||||
|
||||
func main() {
|
||||
flag.Parse()
|
||||
|
||||
if err := grpc.StartServer(*addr, &rwkv.LLM{}); err != nil {
|
||||
panic(err)
|
||||
}
|
||||
}
|
||||
23
cmd/grpc/stablediffusion/main.go
Normal file
23
cmd/grpc/stablediffusion/main.go
Normal file
@@ -0,0 +1,23 @@
|
||||
package main
|
||||
|
||||
// Note: this is started internally by LocalAI and a server is allocated for each model
|
||||
|
||||
import (
|
||||
"flag"
|
||||
|
||||
image "github.com/go-skynet/LocalAI/pkg/backend/image"
|
||||
|
||||
grpc "github.com/go-skynet/LocalAI/pkg/grpc"
|
||||
)
|
||||
|
||||
var (
|
||||
addr = flag.String("addr", "localhost:50051", "the address to connect to")
|
||||
)
|
||||
|
||||
func main() {
|
||||
flag.Parse()
|
||||
|
||||
if err := grpc.StartServer(*addr, &image.StableDiffusion{}); err != nil {
|
||||
panic(err)
|
||||
}
|
||||
}
|
||||
23
cmd/grpc/starcoder/main.go
Normal file
23
cmd/grpc/starcoder/main.go
Normal file
@@ -0,0 +1,23 @@
|
||||
package main
|
||||
|
||||
// Note: this is started internally by LocalAI and a server is allocated for each model
|
||||
|
||||
import (
|
||||
"flag"
|
||||
|
||||
transformers "github.com/go-skynet/LocalAI/pkg/backend/llm/transformers"
|
||||
|
||||
grpc "github.com/go-skynet/LocalAI/pkg/grpc"
|
||||
)
|
||||
|
||||
var (
|
||||
addr = flag.String("addr", "localhost:50051", "the address to connect to")
|
||||
)
|
||||
|
||||
func main() {
|
||||
flag.Parse()
|
||||
|
||||
if err := grpc.StartServer(*addr, &transformers.Starcoder{}); err != nil {
|
||||
panic(err)
|
||||
}
|
||||
}
|
||||
23
cmd/grpc/whisper/main.go
Normal file
23
cmd/grpc/whisper/main.go
Normal file
@@ -0,0 +1,23 @@
|
||||
package main
|
||||
|
||||
// Note: this is started internally by LocalAI and a server is allocated for each model
|
||||
|
||||
import (
|
||||
"flag"
|
||||
|
||||
transcribe "github.com/go-skynet/LocalAI/pkg/backend/transcribe"
|
||||
|
||||
grpc "github.com/go-skynet/LocalAI/pkg/grpc"
|
||||
)
|
||||
|
||||
var (
|
||||
addr = flag.String("addr", "localhost:50051", "the address to connect to")
|
||||
)
|
||||
|
||||
func main() {
|
||||
flag.Parse()
|
||||
|
||||
if err := grpc.StartServer(*addr, &transcribe.Whisper{}); err != nil {
|
||||
panic(err)
|
||||
}
|
||||
}
|
||||
@@ -5,7 +5,7 @@ services:
|
||||
image: quay.io/go-skynet/local-ai:latest
|
||||
build:
|
||||
context: .
|
||||
dockerfile: Dockerfile.dev
|
||||
dockerfile: Dockerfile
|
||||
ports:
|
||||
- 8080:8080
|
||||
env_file:
|
||||
|
||||
@@ -1,9 +1,40 @@
|
||||
#!/bin/bash
|
||||
set -e
|
||||
|
||||
cd /build
|
||||
|
||||
if [ "$REBUILD" != "false" ]; then
|
||||
make rebuild
|
||||
rm -rf ./local-ai
|
||||
ESPEAK_DATA=/build/lib/Linux-$(uname -m)/piper_phonemize/lib/espeak-ng-data make build -j${BUILD_PARALLELISM:-1}
|
||||
else
|
||||
echo "@@@@@"
|
||||
echo "Skipping rebuild"
|
||||
echo "@@@@@"
|
||||
echo "If you are experiencing issues with the pre-compiled builds, try setting REBUILD=true"
|
||||
echo "If you are still experiencing issues with the build, try setting CMAKE_ARGS and disable the instructions set as needed:"
|
||||
echo 'CMAKE_ARGS="-DLLAMA_F16C=OFF -DLLAMA_AVX512=OFF -DLLAMA_AVX2=OFF -DLLAMA_FMA=OFF"'
|
||||
echo "see the documentation at: https://localai.io/basics/build/index.html"
|
||||
echo "Note: See also https://github.com/go-skynet/LocalAI/issues/288"
|
||||
echo "@@@@@"
|
||||
echo "CPU info:"
|
||||
grep -e "model\sname" /proc/cpuinfo | head -1
|
||||
grep -e "flags" /proc/cpuinfo | head -1
|
||||
if grep -q -e "\savx\s" /proc/cpuinfo ; then
|
||||
echo "CPU: AVX found OK"
|
||||
else
|
||||
echo "CPU: no AVX found"
|
||||
fi
|
||||
if grep -q -e "\savx2\s" /proc/cpuinfo ; then
|
||||
echo "CPU: AVX2 found OK"
|
||||
else
|
||||
echo "CPU: no AVX2 found"
|
||||
fi
|
||||
if grep -q -e "\savx512" /proc/cpuinfo ; then
|
||||
echo "CPU: AVX512 found OK"
|
||||
else
|
||||
echo "CPU: no AVX512 found"
|
||||
fi
|
||||
echo "@@@@@"
|
||||
fi
|
||||
|
||||
./local-ai "$@"
|
||||
./local-ai "$@"
|
||||
|
||||
@@ -1,7 +1,16 @@
|
||||
# Examples
|
||||
|
||||
| [ChatGPT OSS alternative](https://github.com/go-skynet/LocalAI/tree/master/examples/chatbot-ui) | [Image generation](https://localai.io/api-endpoints/index.html#image-generation) |
|
||||
|------------------------------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------------|
|
||||
|  |  |
|
||||
|
||||
| [Telegram bot](https://github.com/go-skynet/LocalAI/tree/master/examples/telegram-bot) | [Flowise](https://github.com/go-skynet/LocalAI/tree/master/examples/flowise) |
|
||||
|------------------------------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------------|
|
||||
 | | |
|
||||
|
||||
Here is a list of projects that can easily be integrated with the LocalAI backend.
|
||||
|
||||
|
||||
### Projects
|
||||
|
||||
### AutoGPT
|
||||
@@ -22,6 +31,24 @@ This integration shows how to use LocalAI with [mckaywrigley/chatbot-ui](https:/
|
||||
|
||||
[Check it out here](https://github.com/go-skynet/LocalAI/tree/master/examples/chatbot-ui/)
|
||||
|
||||
There is also a separate example to show how to manually setup a model: [example](https://github.com/go-skynet/LocalAI/tree/master/examples/chatbot-ui-manual/)
|
||||
|
||||
### K8sGPT
|
||||
|
||||
_by [@mudler](https://github.com/mudler)_
|
||||
|
||||
This example show how to use LocalAI inside Kubernetes with [k8sgpt](https://k8sgpt.ai).
|
||||
|
||||

|
||||
|
||||
### Flowise
|
||||
|
||||
_by [@mudler](https://github.com/mudler)_
|
||||
|
||||
This example shows how to use [FlowiseAI/Flowise](https://github.com/FlowiseAI/Flowise) with LocalAI.
|
||||
|
||||
[Check it out here](https://github.com/go-skynet/LocalAI/tree/master/examples/flowise/)
|
||||
|
||||
### Discord bot
|
||||
|
||||
_by [@mudler](https://github.com/mudler)_
|
||||
@@ -46,6 +73,14 @@ 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 functions
|
||||
|
||||
_by [@mudler](https://github.com/mudler)_
|
||||
|
||||
A ready to use example to show how to use OpenAI functions with LocalAI
|
||||
|
||||
[Check it out here](https://github.com/go-skynet/LocalAI/tree/master/examples/functions/)
|
||||
|
||||
### LocalAI WebUI
|
||||
|
||||
_by [@dhruvgera](https://github.com/dhruvgera)_
|
||||
@@ -80,6 +115,14 @@ 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/)
|
||||
|
||||
### Slack bot (Question answering)
|
||||
|
||||
_by [@mudler](https://github.com/mudler)_
|
||||
|
||||
Run a slack bot, ideally for teams, which lets you ask questions on a documentation website, or a github repository.
|
||||
|
||||
[Check it out here](https://github.com/go-skynet/LocalAI/tree/master/examples/slack-qa-bot/)
|
||||
|
||||
### Question answering on documents with llama-index
|
||||
|
||||
_by [@mudler](https://github.com/mudler)_
|
||||
@@ -96,6 +139,16 @@ Shows how to integrate with `Langchain` and `Chroma` to enable question answerin
|
||||
|
||||
[Check it out here](https://github.com/go-skynet/LocalAI/tree/master/examples/langchain-chroma/)
|
||||
|
||||
### Telegram bot
|
||||
|
||||
_by [@mudler](https://github.com/mudler)
|
||||
|
||||

|
||||
|
||||
Use LocalAI to power a Telegram bot assistant, with Image generation and audio support!
|
||||
|
||||
[Check it out here](https://github.com/go-skynet/LocalAI/tree/master/examples/telegram-bot/)
|
||||
|
||||
### Template for Runpod.io
|
||||
|
||||
_by [@fHachenberg](https://github.com/fHachenberg)_
|
||||
@@ -104,6 +157,16 @@ Allows to run any LocalAI-compatible model as a backend on the servers of https:
|
||||
|
||||
[Check it out here](https://runpod.io/gsc?template=uv9mtqnrd0&ref=984wlcra)
|
||||
|
||||
### Continue
|
||||
|
||||
<img src="continue/img/screen.png" width="600" height="200" alt="Screenshot">
|
||||
|
||||
_by [@gruberdev](https://github.com/gruberdev)_
|
||||
|
||||
Demonstrates how to integrate an open-source copilot alternative that enhances code analysis, completion, and improvements. This approach seamlessly integrates with any LocalAI model, offering a more user-friendly experience.
|
||||
|
||||
[Check it out here](https://github.com/go-skynet/LocalAI/tree/master/examples/continue/)
|
||||
|
||||
## Want to contribute?
|
||||
|
||||
Create an issue, and put `Example: <description>` in the title! We will post your examples here.
|
||||
|
||||
48
examples/chatbot-ui-manual/README.md
Normal file
48
examples/chatbot-ui-manual/README.md
Normal file
@@ -0,0 +1,48 @@
|
||||
# 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 --pull always
|
||||
# or you can build the images with:
|
||||
# docker-compose up -d --build
|
||||
```
|
||||
|
||||
## Pointing chatbot-ui to a separately managed LocalAI service
|
||||
|
||||
If you want to use the [chatbot-ui example](https://github.com/go-skynet/LocalAI/tree/master/examples/chatbot-ui) with an externally managed LocalAI service, you can alter the `docker-compose` file so that it looks like the below. You will notice the file is smaller, because we have removed the section that would normally start the LocalAI service. Take care to update the IP address (or FQDN) that the chatbot-ui service tries to access (marked `<<LOCALAI_IP>>` below):
|
||||
```
|
||||
version: '3.6'
|
||||
|
||||
services:
|
||||
chatgpt:
|
||||
image: ghcr.io/mckaywrigley/chatbot-ui:main
|
||||
ports:
|
||||
- 3000:3000
|
||||
environment:
|
||||
- 'OPENAI_API_KEY=sk-XXXXXXXXXXXXXXXXXXXX'
|
||||
- 'OPENAI_API_HOST=http://<<LOCALAI_IP>>:8080'
|
||||
```
|
||||
|
||||
Once you've edited the Dockerfile, you can start it with `docker compose up`, then browse to `http://localhost:3000`.
|
||||
|
||||
## Accessing chatbot-ui
|
||||
|
||||
Open http://localhost:3000 for the Web UI.
|
||||
|
||||
24
examples/chatbot-ui-manual/docker-compose.yaml
Normal file
24
examples/chatbot-ui-manual/docker-compose.yaml
Normal file
@@ -0,0 +1,24 @@
|
||||
version: '3.6'
|
||||
|
||||
services:
|
||||
api:
|
||||
image: quay.io/go-skynet/local-ai:latest
|
||||
build:
|
||||
context: ../../
|
||||
dockerfile: Dockerfile
|
||||
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'
|
||||
@@ -4,22 +4,18 @@ Example of integration with [mckaywrigley/chatbot-ui](https://github.com/mckaywr
|
||||
|
||||

|
||||
|
||||
## Setup
|
||||
## Run
|
||||
|
||||
In this example LocalAI will download the gpt4all model and set it up as "gpt-3.5-turbo". See the `docker-compose.yaml`
|
||||
```bash
|
||||
# Clone LocalAI
|
||||
git clone https://github.com/go-skynet/LocalAI
|
||||
|
||||
cd LocalAI/examples/chatbot-ui
|
||||
|
||||
# (optional) Checkout a specific LocalAI tag
|
||||
# git checkout -b build <TAG>
|
||||
|
||||
# Download gpt4all-j to models/
|
||||
wget https://gpt4all.io/models/ggml-gpt4all-j.bin -O models/ggml-gpt4all-j
|
||||
|
||||
# start with docker-compose
|
||||
docker-compose up -d --pull always
|
||||
docker-compose up --pull always
|
||||
|
||||
# or you can build the images with:
|
||||
# docker-compose up -d --build
|
||||
```
|
||||
|
||||
@@ -3,19 +3,32 @@ version: '3.6'
|
||||
services:
|
||||
api:
|
||||
image: quay.io/go-skynet/local-ai:latest
|
||||
# As initially LocalAI will download the models defined in PRELOAD_MODELS
|
||||
# you might need to tweak the healthcheck values here according to your network connection.
|
||||
# Here we give a timespan of 20m to download all the required files.
|
||||
healthcheck:
|
||||
test: ["CMD", "curl", "-f", "http://localhost:8080/readyz"]
|
||||
interval: 1m
|
||||
timeout: 20m
|
||||
retries: 20
|
||||
build:
|
||||
context: ../../
|
||||
dockerfile: Dockerfile.dev
|
||||
dockerfile: Dockerfile
|
||||
ports:
|
||||
- 8080:8080
|
||||
environment:
|
||||
- DEBUG=true
|
||||
- MODELS_PATH=/models
|
||||
# You can preload different models here as well.
|
||||
# See: https://github.com/go-skynet/model-gallery
|
||||
- 'PRELOAD_MODELS=[{"url": "github:go-skynet/model-gallery/gpt4all-j.yaml", "name": "gpt-3.5-turbo"}]'
|
||||
volumes:
|
||||
- ./models:/models:cached
|
||||
command: ["/usr/bin/local-ai" ]
|
||||
|
||||
chatgpt:
|
||||
depends_on:
|
||||
api:
|
||||
condition: service_healthy
|
||||
image: ghcr.io/mckaywrigley/chatbot-ui:main
|
||||
ports:
|
||||
- 3000:3000
|
||||
|
||||
56
examples/continue/README.md
Normal file
56
examples/continue/README.md
Normal file
@@ -0,0 +1,56 @@
|
||||
# Continue
|
||||
|
||||

|
||||
|
||||
This document presents an example of integration with [continuedev/continue](https://github.com/continuedev/continue).
|
||||
|
||||

|
||||
|
||||
For a live demonstration, please click on the link below:
|
||||
|
||||
- [How it works (Video demonstration)](https://www.youtube.com/watch?v=3Ocrc-WX4iQ)
|
||||
|
||||
## Integration Setup Walkthrough
|
||||
|
||||
1. [As outlined in `continue`'s documentation](https://continue.dev/docs/getting-started), install the [Visual Studio Code extension from the marketplace](https://marketplace.visualstudio.com/items?itemName=Continue.continue) and open it.
|
||||
2. In this example, LocalAI will download the gpt4all model and set it up as "gpt-3.5-turbo". Refer to the `docker-compose.yaml` file for details.
|
||||
|
||||
```bash
|
||||
# Clone LocalAI
|
||||
git clone https://github.com/go-skynet/LocalAI
|
||||
|
||||
cd LocalAI/examples/continue
|
||||
|
||||
# Start with docker-compose
|
||||
docker-compose up --build -d
|
||||
```
|
||||
|
||||
3. Type `/config` within Continue's VSCode extension, or edit the file located at `~/.continue/config.py` on your system with the following configuration:
|
||||
|
||||
```py
|
||||
from continuedev.src.continuedev.libs.llm.openai import OpenAI, OpenAIServerInfo
|
||||
|
||||
config = ContinueConfig(
|
||||
...
|
||||
models=Models(
|
||||
default=OpenAI(
|
||||
api_key="my-api-key",
|
||||
model="gpt-3.5-turbo",
|
||||
openai_server_info=OpenAIServerInfo(
|
||||
api_base="http://localhost:8080",
|
||||
model="gpt-3.5-turbo"
|
||||
)
|
||||
)
|
||||
),
|
||||
)
|
||||
```
|
||||
|
||||
This setup enables you to make queries directly to your model running in the Docker container. Note that the `api_key` does not need to be properly set up; it is included here as a placeholder.
|
||||
|
||||
If editing the configuration seems confusing, you may copy and paste the provided default `config.py` file over the existing one in `~/.continue/config.py` after initializing the extension in the VSCode IDE.
|
||||
|
||||
## Additional Resources
|
||||
|
||||
- [Official Continue documentation](https://continue.dev/docs/intro)
|
||||
- [Documentation page on using self-hosted models](https://continue.dev/docs/customization#self-hosting-an-open-source-model)
|
||||
- [Official extension link](https://marketplace.visualstudio.com/items?itemName=Continue.continue)
|
||||
148
examples/continue/config.py
Normal file
148
examples/continue/config.py
Normal file
@@ -0,0 +1,148 @@
|
||||
"""
|
||||
This is the Continue configuration file.
|
||||
|
||||
See https://continue.dev/docs/customization to learn more.
|
||||
"""
|
||||
|
||||
import subprocess
|
||||
|
||||
from continuedev.src.continuedev.core.main import Step
|
||||
from continuedev.src.continuedev.core.sdk import ContinueSDK
|
||||
from continuedev.src.continuedev.core.models import Models
|
||||
from continuedev.src.continuedev.core.config import CustomCommand, SlashCommand, ContinueConfig
|
||||
from continuedev.src.continuedev.plugins.context_providers.github import GitHubIssuesContextProvider
|
||||
from continuedev.src.continuedev.plugins.context_providers.google import GoogleContextProvider
|
||||
from continuedev.src.continuedev.plugins.policies.default import DefaultPolicy
|
||||
from continuedev.src.continuedev.libs.llm.openai import OpenAI, OpenAIServerInfo
|
||||
from continuedev.src.continuedev.libs.llm.ggml import GGML
|
||||
|
||||
from continuedev.src.continuedev.plugins.steps.open_config import OpenConfigStep
|
||||
from continuedev.src.continuedev.plugins.steps.clear_history import ClearHistoryStep
|
||||
from continuedev.src.continuedev.plugins.steps.feedback import FeedbackStep
|
||||
from continuedev.src.continuedev.plugins.steps.comment_code import CommentCodeStep
|
||||
from continuedev.src.continuedev.plugins.steps.share_session import ShareSessionStep
|
||||
from continuedev.src.continuedev.plugins.steps.main import EditHighlightedCodeStep
|
||||
from continuedev.src.continuedev.plugins.context_providers.search import SearchContextProvider
|
||||
from continuedev.src.continuedev.plugins.context_providers.diff import DiffContextProvider
|
||||
from continuedev.src.continuedev.plugins.context_providers.url import URLContextProvider
|
||||
|
||||
class CommitMessageStep(Step):
|
||||
"""
|
||||
This is a Step, the building block of Continue.
|
||||
It can be used below as a slash command, so that
|
||||
run will be called when you type '/commit'.
|
||||
"""
|
||||
async def run(self, sdk: ContinueSDK):
|
||||
|
||||
# Get the root directory of the workspace
|
||||
dir = sdk.ide.workspace_directory
|
||||
|
||||
# Run git diff in that directory
|
||||
diff = subprocess.check_output(
|
||||
["git", "diff"], cwd=dir).decode("utf-8")
|
||||
|
||||
# Ask the LLM to write a commit message,
|
||||
# and set it as the description of this step
|
||||
self.description = await sdk.models.default.complete(
|
||||
f"{diff}\n\nWrite a short, specific (less than 50 chars) commit message about the above changes:")
|
||||
|
||||
|
||||
config = ContinueConfig(
|
||||
|
||||
# If set to False, we will not collect any usage data
|
||||
# See here to learn what anonymous data we collect: https://continue.dev/docs/telemetry
|
||||
allow_anonymous_telemetry=True,
|
||||
|
||||
models = Models(
|
||||
default = OpenAI(
|
||||
api_key = "my-api-key",
|
||||
model = "gpt-3.5-turbo",
|
||||
openai_server_info = OpenAIServerInfo(
|
||||
api_base = "http://localhost:8080",
|
||||
model = "gpt-3.5-turbo"
|
||||
)
|
||||
)
|
||||
),
|
||||
# Set a system message with information that the LLM should always keep in mind
|
||||
# E.g. "Please give concise answers. Always respond in Spanish."
|
||||
system_message=None,
|
||||
|
||||
# Set temperature to any value between 0 and 1. Higher values will make the LLM
|
||||
# more creative, while lower values will make it more predictable.
|
||||
temperature=0.5,
|
||||
|
||||
# Custom commands let you map a prompt to a shortened slash command
|
||||
# They are like slash commands, but more easily defined - write just a prompt instead of a Step class
|
||||
# Their output will always be in chat form
|
||||
custom_commands=[
|
||||
# CustomCommand(
|
||||
# name="test",
|
||||
# description="Write unit tests for the higlighted code",
|
||||
# prompt="Write a comprehensive set of unit tests for the selected code. It should setup, run tests that check for correctness including important edge cases, and teardown. Ensure that the tests are complete and sophisticated. Give the tests just as chat output, don't edit any file.",
|
||||
# )
|
||||
],
|
||||
|
||||
# Slash commands let you run a Step from a slash command
|
||||
slash_commands=[
|
||||
# SlashCommand(
|
||||
# name="commit",
|
||||
# description="This is an example slash command. Use /config to edit it and create more",
|
||||
# step=CommitMessageStep,
|
||||
# )
|
||||
SlashCommand(
|
||||
name="edit",
|
||||
description="Edit code in the current file or the highlighted code",
|
||||
step=EditHighlightedCodeStep,
|
||||
),
|
||||
SlashCommand(
|
||||
name="config",
|
||||
description="Customize Continue - slash commands, LLMs, system message, etc.",
|
||||
step=OpenConfigStep,
|
||||
),
|
||||
SlashCommand(
|
||||
name="comment",
|
||||
description="Write comments for the current file or highlighted code",
|
||||
step=CommentCodeStep,
|
||||
),
|
||||
SlashCommand(
|
||||
name="feedback",
|
||||
description="Send feedback to improve Continue",
|
||||
step=FeedbackStep,
|
||||
),
|
||||
SlashCommand(
|
||||
name="clear",
|
||||
description="Clear step history",
|
||||
step=ClearHistoryStep,
|
||||
),
|
||||
SlashCommand(
|
||||
name="share",
|
||||
description="Download and share the session transcript",
|
||||
step=ShareSessionStep,
|
||||
)
|
||||
],
|
||||
|
||||
# Context providers let you quickly select context by typing '@'
|
||||
# Uncomment the following to
|
||||
# - quickly reference GitHub issues
|
||||
# - show Google search results to the LLM
|
||||
context_providers=[
|
||||
# GitHubIssuesContextProvider(
|
||||
# repo_name="<your github username or organization>/<your repo name>",
|
||||
# auth_token="<your github auth token>"
|
||||
# ),
|
||||
# GoogleContextProvider(
|
||||
# serper_api_key="<your serper.dev api key>"
|
||||
# )
|
||||
SearchContextProvider(),
|
||||
DiffContextProvider(),
|
||||
URLContextProvider(
|
||||
preset_urls = [
|
||||
# Add any common urls you reference here so they appear in autocomplete
|
||||
]
|
||||
)
|
||||
],
|
||||
|
||||
# Policies hold the main logic that decides which Step to take next
|
||||
# You can use them to design agents, or deeply customize Continue
|
||||
policy=DefaultPolicy()
|
||||
)
|
||||
27
examples/continue/docker-compose.yml
Normal file
27
examples/continue/docker-compose.yml
Normal file
@@ -0,0 +1,27 @@
|
||||
version: '3.6'
|
||||
|
||||
services:
|
||||
api:
|
||||
image: quay.io/go-skynet/local-ai:latest
|
||||
# As initially LocalAI will download the models defined in PRELOAD_MODELS
|
||||
# you might need to tweak the healthcheck values here according to your network connection.
|
||||
# Here we give a timespan of 20m to download all the required files.
|
||||
healthcheck:
|
||||
test: ["CMD", "curl", "-f", "http://localhost:8080/readyz"]
|
||||
interval: 1m
|
||||
timeout: 20m
|
||||
retries: 20
|
||||
build:
|
||||
context: ../../
|
||||
dockerfile: Dockerfile
|
||||
ports:
|
||||
- 8080:8080
|
||||
environment:
|
||||
- DEBUG=true
|
||||
- MODELS_PATH=/models
|
||||
# You can preload different models here as well.
|
||||
# See: https://github.com/go-skynet/model-gallery
|
||||
- 'PRELOAD_MODELS=[{"url": "github:go-skynet/model-gallery/gpt4all-j.yaml", "name": "gpt-3.5-turbo"}]'
|
||||
volumes:
|
||||
- ./models:/models:cached
|
||||
command: ["/usr/bin/local-ai" ]
|
||||
BIN
examples/continue/img/screen.png
Executable file
BIN
examples/continue/img/screen.png
Executable file
Binary file not shown.
|
After Width: | Height: | Size: 196 KiB |
@@ -5,7 +5,7 @@ services:
|
||||
image: quay.io/go-skynet/local-ai:latest
|
||||
build:
|
||||
context: ../../
|
||||
dockerfile: Dockerfile.dev
|
||||
dockerfile: Dockerfile
|
||||
ports:
|
||||
- 8080:8080
|
||||
environment:
|
||||
|
||||
30
examples/flowise/README.md
Normal file
30
examples/flowise/README.md
Normal file
@@ -0,0 +1,30 @@
|
||||
# flowise
|
||||
|
||||
Example of integration with [FlowiseAI/Flowise](https://github.com/FlowiseAI/Flowise).
|
||||
|
||||

|
||||
|
||||
You can check a demo video in the Flowise PR: https://github.com/FlowiseAI/Flowise/pull/123
|
||||
|
||||
## Run
|
||||
|
||||
In this example LocalAI will download the gpt4all model and set it up as "gpt-3.5-turbo". See the `docker-compose.yaml`
|
||||
```bash
|
||||
# Clone LocalAI
|
||||
git clone https://github.com/go-skynet/LocalAI
|
||||
|
||||
cd LocalAI/examples/flowise
|
||||
|
||||
# start with docker-compose
|
||||
docker-compose up --pull always
|
||||
|
||||
```
|
||||
|
||||
## Accessing flowise
|
||||
|
||||
Open http://localhost:3000.
|
||||
|
||||
## Using LocalAI
|
||||
|
||||
Search for LocalAI in the integration, and use the `http://api:8080/` as URL.
|
||||
|
||||
37
examples/flowise/docker-compose.yaml
Normal file
37
examples/flowise/docker-compose.yaml
Normal file
@@ -0,0 +1,37 @@
|
||||
version: '3.6'
|
||||
|
||||
services:
|
||||
api:
|
||||
image: quay.io/go-skynet/local-ai:latest
|
||||
# As initially LocalAI will download the models defined in PRELOAD_MODELS
|
||||
# you might need to tweak the healthcheck values here according to your network connection.
|
||||
# Here we give a timespan of 20m to download all the required files.
|
||||
healthcheck:
|
||||
test: ["CMD", "curl", "-f", "http://localhost:8080/readyz"]
|
||||
interval: 1m
|
||||
timeout: 20m
|
||||
retries: 20
|
||||
build:
|
||||
context: ../../
|
||||
dockerfile: Dockerfile
|
||||
ports:
|
||||
- 8080:8080
|
||||
environment:
|
||||
- DEBUG=true
|
||||
- MODELS_PATH=/models
|
||||
# You can preload different models here as well.
|
||||
# See: https://github.com/go-skynet/model-gallery
|
||||
- 'PRELOAD_MODELS=[{"url": "github:go-skynet/model-gallery/gpt4all-j.yaml", "name": "gpt-3.5-turbo"}]'
|
||||
volumes:
|
||||
- ./models:/models:cached
|
||||
command: ["/usr/bin/local-ai" ]
|
||||
flowise:
|
||||
depends_on:
|
||||
api:
|
||||
condition: service_healthy
|
||||
image: flowiseai/flowise
|
||||
ports:
|
||||
- 3000:3000
|
||||
volumes:
|
||||
- ~/.flowise:/root/.flowise
|
||||
command: /bin/sh -c "sleep 3; flowise start"
|
||||
9
examples/functions/.env
Normal file
9
examples/functions/.env
Normal file
@@ -0,0 +1,9 @@
|
||||
OPENAI_API_KEY=sk---anystringhere
|
||||
OPENAI_API_BASE=http://api:8080/v1
|
||||
# Models to preload at start
|
||||
# Here we configure gpt4all as gpt-3.5-turbo and bert as embeddings
|
||||
PRELOAD_MODELS=[{"url": "github:go-skynet/model-gallery/openllama-7b-open-instruct.yaml", "name": "gpt-3.5-turbo"}]
|
||||
|
||||
## Change the default number of threads
|
||||
#THREADS=14
|
||||
|
||||
5
examples/functions/Dockerfile
Normal file
5
examples/functions/Dockerfile
Normal file
@@ -0,0 +1,5 @@
|
||||
FROM python:3.10-bullseye
|
||||
COPY . /app
|
||||
WORKDIR /app
|
||||
RUN pip install --no-cache-dir -r requirements.txt
|
||||
ENTRYPOINT [ "python", "./functions-openai.py" ];
|
||||
18
examples/functions/README.md
Normal file
18
examples/functions/README.md
Normal file
@@ -0,0 +1,18 @@
|
||||
# LocalAI functions
|
||||
|
||||
Example of using LocalAI functions, see the [OpenAI](https://openai.com/blog/function-calling-and-other-api-updates) blog post.
|
||||
|
||||
## Run
|
||||
|
||||
```bash
|
||||
# Clone LocalAI
|
||||
git clone https://github.com/go-skynet/LocalAI
|
||||
|
||||
cd LocalAI/examples/functions
|
||||
|
||||
docker-compose run --rm functions
|
||||
```
|
||||
|
||||
Note: The example automatically downloads the `openllama` model as it is under a permissive license.
|
||||
|
||||
See the `.env` configuration file to set a different model with the [model-gallery](https://github.com/go-skynet/model-gallery) by editing `PRELOAD_MODELS`.
|
||||
23
examples/functions/docker-compose.yaml
Normal file
23
examples/functions/docker-compose.yaml
Normal file
@@ -0,0 +1,23 @@
|
||||
version: "3.9"
|
||||
services:
|
||||
api:
|
||||
image: quay.io/go-skynet/local-ai:master
|
||||
ports:
|
||||
- 8080:8080
|
||||
env_file:
|
||||
- .env
|
||||
environment:
|
||||
- DEBUG=true
|
||||
- MODELS_PATH=/models
|
||||
volumes:
|
||||
- ./models:/models:cached
|
||||
command: ["/usr/bin/local-ai" ]
|
||||
functions:
|
||||
build:
|
||||
context: .
|
||||
dockerfile: Dockerfile
|
||||
depends_on:
|
||||
api:
|
||||
condition: service_healthy
|
||||
env_file:
|
||||
- .env
|
||||
76
examples/functions/functions-openai.py
Normal file
76
examples/functions/functions-openai.py
Normal file
@@ -0,0 +1,76 @@
|
||||
import openai
|
||||
import json
|
||||
|
||||
# Example dummy function hard coded to return the same weather
|
||||
# In production, this could be your backend API or an external API
|
||||
def get_current_weather(location, unit="fahrenheit"):
|
||||
"""Get the current weather in a given location"""
|
||||
weather_info = {
|
||||
"location": location,
|
||||
"temperature": "72",
|
||||
"unit": unit,
|
||||
"forecast": ["sunny", "windy"],
|
||||
}
|
||||
return json.dumps(weather_info)
|
||||
|
||||
|
||||
def run_conversation():
|
||||
# Step 1: send the conversation and available functions to GPT
|
||||
messages = [{"role": "user", "content": "What's the weather like in Boston?"}]
|
||||
functions = [
|
||||
{
|
||||
"name": "get_current_weather",
|
||||
"description": "Get the current weather in a given location",
|
||||
"parameters": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"location": {
|
||||
"type": "string",
|
||||
"description": "The city and state, e.g. San Francisco, CA",
|
||||
},
|
||||
"unit": {"type": "string", "enum": ["celsius", "fahrenheit"]},
|
||||
},
|
||||
"required": ["location"],
|
||||
},
|
||||
}
|
||||
]
|
||||
response = openai.ChatCompletion.create(
|
||||
model="gpt-3.5-turbo",
|
||||
messages=messages,
|
||||
functions=functions,
|
||||
function_call="auto", # auto is default, but we'll be explicit
|
||||
)
|
||||
response_message = response["choices"][0]["message"]
|
||||
|
||||
# Step 2: check if GPT wanted to call a function
|
||||
if response_message.get("function_call"):
|
||||
# Step 3: call the function
|
||||
# Note: the JSON response may not always be valid; be sure to handle errors
|
||||
available_functions = {
|
||||
"get_current_weather": get_current_weather,
|
||||
} # only one function in this example, but you can have multiple
|
||||
function_name = response_message["function_call"]["name"]
|
||||
fuction_to_call = available_functions[function_name]
|
||||
function_args = json.loads(response_message["function_call"]["arguments"])
|
||||
function_response = fuction_to_call(
|
||||
location=function_args.get("location"),
|
||||
unit=function_args.get("unit"),
|
||||
)
|
||||
|
||||
# Step 4: send the info on the function call and function response to GPT
|
||||
messages.append(response_message) # extend conversation with assistant's reply
|
||||
messages.append(
|
||||
{
|
||||
"role": "function",
|
||||
"name": function_name,
|
||||
"content": function_response,
|
||||
}
|
||||
) # extend conversation with function response
|
||||
second_response = openai.ChatCompletion.create(
|
||||
model="gpt-3.5-turbo",
|
||||
messages=messages,
|
||||
) # get a new response from GPT where it can see the function response
|
||||
return second_response
|
||||
|
||||
|
||||
print(run_conversation())
|
||||
2
examples/functions/requirements.txt
Normal file
2
examples/functions/requirements.txt
Normal file
@@ -0,0 +1,2 @@
|
||||
langchain==0.0.234
|
||||
openai==0.27.8
|
||||
1
examples/insomnia/Insomnia_LocalAI.json
Normal file
1
examples/insomnia/Insomnia_LocalAI.json
Normal file
File diff suppressed because one or more lines are too long
17
examples/insomnia/README.md
Normal file
17
examples/insomnia/README.md
Normal file
@@ -0,0 +1,17 @@
|
||||
# Insomnia
|
||||
|
||||
Developer Testing Request Collection for [Insomnia](https://insomnia.rest/), an open-source REST client
|
||||
|
||||
## Instructions
|
||||
|
||||
* Install Insomnia as normal
|
||||
* [Import](https://docs.insomnia.rest/insomnia/import-export-data) `Insomnia_LocalAI.json`
|
||||
* Control + E opens the environment settings -
|
||||
|
||||
| **Parameter Name** | **Default Value** | **Description** |
|
||||
|--------------------|-------------------|------------------------------------------|
|
||||
| HOST | localhost | LocalAI base URL |
|
||||
| PORT | 8080 | LocalAI port |
|
||||
| DEFAULT_MODEL | gpt-3.5-turbo | Name of the model used on most requests. |
|
||||
|
||||
** you may want to duplicate localhost into a "Private" environment to avoid saving private settings back to this file **
|
||||
72
examples/k8sgpt/README.md
Normal file
72
examples/k8sgpt/README.md
Normal file
@@ -0,0 +1,72 @@
|
||||
# k8sgpt example
|
||||
|
||||
This example show how to use LocalAI with k8sgpt
|
||||
|
||||

|
||||
|
||||
## Create the cluster locally with Kind (optional)
|
||||
|
||||
If you want to test this locally without a remote Kubernetes cluster, you can use kind.
|
||||
|
||||
Install [kind](https://kind.sigs.k8s.io/) and create a cluster:
|
||||
|
||||
```
|
||||
kind create cluster
|
||||
```
|
||||
|
||||
## Setup LocalAI
|
||||
|
||||
We will use [helm](https://helm.sh/docs/intro/install/):
|
||||
|
||||
```
|
||||
helm repo add go-skynet https://go-skynet.github.io/helm-charts/
|
||||
helm repo update
|
||||
|
||||
# Clone LocalAI
|
||||
git clone https://github.com/go-skynet/LocalAI
|
||||
|
||||
cd LocalAI/examples/k8sgpt
|
||||
|
||||
# modify values.yaml preload_models with the models you want to install.
|
||||
# CHANGE the URL to a model in huggingface.
|
||||
helm install local-ai go-skynet/local-ai --create-namespace --namespace local-ai --values values.yaml
|
||||
```
|
||||
|
||||
## Setup K8sGPT
|
||||
|
||||
```
|
||||
# Install k8sgpt
|
||||
helm repo add k8sgpt https://charts.k8sgpt.ai/
|
||||
helm repo update
|
||||
helm install release k8sgpt/k8sgpt-operator -n k8sgpt-operator-system --create-namespace --version 0.0.17
|
||||
```
|
||||
|
||||
Apply the k8sgpt-operator configuration:
|
||||
|
||||
```
|
||||
kubectl apply -f - << EOF
|
||||
apiVersion: core.k8sgpt.ai/v1alpha1
|
||||
kind: K8sGPT
|
||||
metadata:
|
||||
name: k8sgpt-local-ai
|
||||
namespace: default
|
||||
spec:
|
||||
backend: localai
|
||||
baseUrl: http://local-ai.local-ai.svc.cluster.local:8080/v1
|
||||
noCache: false
|
||||
model: gpt-3.5-turbo
|
||||
version: v0.3.0
|
||||
enableAI: true
|
||||
EOF
|
||||
```
|
||||
|
||||
## Test
|
||||
|
||||
Apply a broken pod:
|
||||
|
||||
```
|
||||
kubectl apply -f broken-pod.yaml
|
||||
```
|
||||
|
||||
## ArgoCD Deployment Example
|
||||
[Deploy K8sgpt + localai with Argocd](https://github.com/tyler-harpool/gitops/tree/main/infra/k8gpt)
|
||||
14
examples/k8sgpt/broken-pod.yaml
Normal file
14
examples/k8sgpt/broken-pod.yaml
Normal file
@@ -0,0 +1,14 @@
|
||||
apiVersion: v1
|
||||
kind: Pod
|
||||
metadata:
|
||||
name: broken-pod
|
||||
spec:
|
||||
containers:
|
||||
- name: broken-pod
|
||||
image: nginx:1.a.b.c
|
||||
livenessProbe:
|
||||
httpGet:
|
||||
path: /
|
||||
port: 90
|
||||
initialDelaySeconds: 3
|
||||
periodSeconds: 3
|
||||
96
examples/k8sgpt/values.yaml
Normal file
96
examples/k8sgpt/values.yaml
Normal file
@@ -0,0 +1,96 @@
|
||||
replicaCount: 1
|
||||
|
||||
deployment:
|
||||
# https://quay.io/repository/go-skynet/local-ai?tab=tags
|
||||
image: quay.io/go-skynet/local-ai:v1.23.0
|
||||
env:
|
||||
threads: 4
|
||||
debug: "true"
|
||||
context_size: 512
|
||||
galleries: '[{"name":"model-gallery", "url":"github:go-skynet/model-gallery/index.yaml"}, {"url": "github:go-skynet/model-gallery/huggingface.yaml","name":"huggingface"}]'
|
||||
preload_models: '[{ "id": "huggingface@thebloke__open-llama-13b-open-instruct-ggml__open-llama-13b-open-instruct.ggmlv3.q3_k_m.bin", "name": "gpt-3.5-turbo", "overrides": { "f16": true, "mmap": true }}]'
|
||||
modelsPath: "/models"
|
||||
|
||||
resources:
|
||||
{}
|
||||
# We usually recommend not to specify default resources and to leave this as a conscious
|
||||
# choice for the user. This also increases chances charts run on environments with little
|
||||
# resources, such as Minikube. If you do want to specify resources, uncomment the following
|
||||
# lines, adjust them as necessary, and remove the curly braces after 'resources:'.
|
||||
# limits:
|
||||
# cpu: 100m
|
||||
# memory: 128Mi
|
||||
# requests:
|
||||
# cpu: 100m
|
||||
# memory: 128Mi
|
||||
|
||||
# Prompt templates to include
|
||||
# Note: the keys of this map will be the names of the prompt template files
|
||||
promptTemplates:
|
||||
{}
|
||||
# ggml-gpt4all-j.tmpl: |
|
||||
# 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:
|
||||
|
||||
# Models to download at runtime
|
||||
models:
|
||||
# Whether to force download models even if they already exist
|
||||
forceDownload: false
|
||||
|
||||
# The list of URLs to download models from
|
||||
# Note: the name of the file will be the name of the loaded model
|
||||
list:
|
||||
#- url: "https://gpt4all.io/models/ggml-gpt4all-j.bin"
|
||||
# basicAuth: base64EncodedCredentials
|
||||
|
||||
# Persistent storage for models and prompt templates.
|
||||
# PVC and HostPath are mutually exclusive. If both are enabled,
|
||||
# PVC configuration takes precedence. If neither are enabled, ephemeral
|
||||
# storage is used.
|
||||
persistence:
|
||||
pvc:
|
||||
enabled: false
|
||||
size: 6Gi
|
||||
accessModes:
|
||||
- ReadWriteOnce
|
||||
|
||||
annotations: {}
|
||||
|
||||
# Optional
|
||||
storageClass: ~
|
||||
|
||||
hostPath:
|
||||
enabled: false
|
||||
path: "/models"
|
||||
|
||||
service:
|
||||
type: ClusterIP
|
||||
port: 8080
|
||||
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"
|
||||
|
||||
ingress:
|
||||
enabled: false
|
||||
className: ""
|
||||
annotations:
|
||||
{}
|
||||
# kubernetes.io/ingress.class: nginx
|
||||
# kubernetes.io/tls-acme: "true"
|
||||
hosts:
|
||||
- host: chart-example.local
|
||||
paths:
|
||||
- path: /
|
||||
pathType: ImplementationSpecific
|
||||
tls: []
|
||||
# - secretName: chart-example-tls
|
||||
# hosts:
|
||||
# - chart-example.local
|
||||
|
||||
nodeSelector: {}
|
||||
|
||||
tolerations: []
|
||||
|
||||
affinity: {}
|
||||
@@ -9,7 +9,7 @@ from langchain.vectorstores.base import VectorStoreRetriever
|
||||
base_path = os.environ.get('OPENAI_API_BASE', 'http://localhost:8080/v1')
|
||||
|
||||
# Load and process the text
|
||||
embedding = OpenAIEmbeddings()
|
||||
embedding = OpenAIEmbeddings(model="text-embedding-ada-002", openai_api_base=base_path)
|
||||
persist_directory = 'db'
|
||||
|
||||
# Now we can load the persisted database from disk, and use it as normal.
|
||||
|
||||
@@ -18,8 +18,8 @@ texts = text_splitter.split_documents(documents)
|
||||
# Supplying a persist_directory will store the embeddings on disk
|
||||
persist_directory = 'db'
|
||||
|
||||
embedding = OpenAIEmbeddings(model="text-embedding-ada-002")
|
||||
embedding = OpenAIEmbeddings(model="text-embedding-ada-002", openai_api_base=base_path)
|
||||
vectordb = Chroma.from_documents(documents=texts, embedding=embedding, persist_directory=persist_directory)
|
||||
|
||||
vectordb.persist()
|
||||
vectordb = None
|
||||
vectordb = None
|
||||
|
||||
Some files were not shown because too many files have changed in this diff Show More
Reference in New Issue
Block a user