Compare commits

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1 Commits

Author SHA1 Message Date
mudler cfba345021 wip: swagger 2 years ago
  1. 3
      .devcontainer/Dockerfile
  2. 46
      .devcontainer/devcontainer.json
  3. 26
      .devcontainer/docker-compose.yml
  4. 3
      .dockerignore
  5. 40
      .env
  6. 5
      .github/FUNDING.yml
  7. 31
      .github/ISSUE_TEMPLATE/bug_report.md
  8. 8
      .github/ISSUE_TEMPLATE/config.yml
  9. 22
      .github/ISSUE_TEMPLATE/feature_request.md
  10. 23
      .github/PULL_REQUEST_TEMPLATE.md
  11. 9
      .github/bump_deps.sh
  12. 24
      .github/release.yml
  13. 18
      .github/stale.yml
  14. 63
      .github/workflows/bump_deps.yaml
  15. 139
      .github/workflows/image.yml
  16. 79
      .github/workflows/release.yaml
  17. 26
      .github/workflows/release.yml.disabled
  18. 34
      .github/workflows/test.yml
  19. 28
      .gitignore
  20. 15
      .goreleaser.yaml
  21. 19
      .vscode/launch.json
  22. 124
      Dockerfile
  23. 14
      Dockerfile.dev
  24. 2
      LICENSE
  25. 430
      Makefile
  26. 592
      README.md
  27. 169
      api/api.go
  28. 651
      api/api_test.go
  29. 109
      api/backend/embeddings.go
  30. 68
      api/backend/image.go
  31. 124
      api/backend/llm.go
  32. 22
      api/backend/lock.go
  33. 72
      api/backend/options.go
  34. 42
      api/backend/transcript.go
  35. 72
      api/backend/tts.go
  36. 102
      api/config.go
  37. 209
      api/config/config.go
  38. 56
      api/config/config_test.go
  39. 37
      api/config/prediction.go
  40. 224
      api/localai/gallery.go
  41. 31
      api/localai/localai.go
  42. 518
      api/openai.go
  43. 105
      api/openai/api.go
  44. 322
      api/openai/chat.go
  45. 159
      api/openai/completion.go
  46. 67
      api/openai/edit.go
  47. 70
      api/openai/embeddings.go
  48. 158
      api/openai/image.go
  49. 36
      api/openai/inference.go
  50. 37
      api/openai/list.go
  51. 234
      api/openai/request.go
  52. 71
      api/openai/transcription.go
  53. 186
      api/options/options.go
  54. 343
      api/prediction.go
  55. 6
      assets.go
  56. 22
      cmd/grpc/bert-embeddings/main.go
  57. 23
      cmd/grpc/bloomz/main.go
  58. 23
      cmd/grpc/dolly/main.go
  59. 23
      cmd/grpc/falcon-ggml/main.go
  60. 25
      cmd/grpc/falcon/main.go
  61. 23
      cmd/grpc/gpt2/main.go
  62. 23
      cmd/grpc/gpt4all/main.go
  63. 23
      cmd/grpc/gptj/main.go
  64. 23
      cmd/grpc/gptneox/main.go
  65. 23
      cmd/grpc/langchain-huggingface/main.go
  66. 25
      cmd/grpc/llama-grammar/main.go
  67. 25
      cmd/grpc/llama/main.go
  68. 23
      cmd/grpc/mpt/main.go
  69. 23
      cmd/grpc/piper/main.go
  70. 23
      cmd/grpc/replit/main.go
  71. 23
      cmd/grpc/rwkv/main.go
  72. 23
      cmd/grpc/stablediffusion/main.go
  73. 23
      cmd/grpc/starcoder/main.go
  74. 23
      cmd/grpc/whisper/main.go
  75. 2
      docker-compose.yaml
  76. 16
      entrypoint.sh
  77. 150
      examples/README.md
  78. 5
      examples/autoGPT/.env
  79. 32
      examples/autoGPT/README.md
  80. 42
      examples/autoGPT/docker-compose.yaml
  81. 48
      examples/chatbot-ui-manual/README.md
  82. 24
      examples/chatbot-ui-manual/docker-compose.yaml
  83. 14
      examples/chatbot-ui/README.md
  84. 17
      examples/chatbot-ui/docker-compose.yaml
  85. 0
      examples/chatbot-ui/models/completion.tmpl
  86. 1
      examples/chatbot-ui/models/gpt-3.5-turbo.yaml
  87. 0
      examples/chatbot-ui/models/gpt4all.tmpl
  88. 2
      examples/discord-bot/docker-compose.yaml
  89. 30
      examples/flowise/README.md
  90. 37
      examples/flowise/docker-compose.yaml
  91. 9
      examples/functions/.env
  92. 5
      examples/functions/Dockerfile
  93. 18
      examples/functions/README.md
  94. 23
      examples/functions/docker-compose.yaml
  95. 76
      examples/functions/functions-openai.py
  96. 2
      examples/functions/requirements.txt
  97. 70
      examples/k8sgpt/README.md
  98. 14
      examples/k8sgpt/broken-pod.yaml
  99. 95
      examples/k8sgpt/values.yaml
  100. 5
      examples/langchain-chroma/.env.example
  101. Some files were not shown because too many files have changed in this diff Show More

@ -0,0 +1,3 @@
ARG GO_VERSION=1.20
FROM mcr.microsoft.com/devcontainers/go:0-$GO_VERSION-bullseye
RUN apt-get update && apt-get install -y cmake

@ -0,0 +1,46 @@
// 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"
}

@ -0,0 +1,26 @@
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"

@ -1,5 +1,2 @@
.idea
models
examples/chatbot-ui/models
examples/rwkv/models
examples/**/models

40
.env

@ -1,43 +1,5 @@
## Set number of threads.
## Note: prefer the number of physical cores. Overbooking the CPU degrades performance notably.
# THREADS=14
## Specify a different bind address (defaults to ":8080")
# ADDRESS=127.0.0.1:8080
## 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, clblas.
# BUILD_TYPE=openblas
## Uncomment and set to true to enable rebuilding from source
# 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
# BUILD_TYPE=generic

@ -1,5 +0,0 @@
# These are supported funding model platforms
github: [mudler]
custom:
- https://www.buymeacoffee.com/mudler

@ -1,31 +0,0 @@
---
name: Bug report
about: Create a report to help us improve
title: ''
labels: bug
assignees: mudler
---
<!-- Thanks for helping us to improve LocalAI! We welcome all bug reports. Please fill out each area of the template so we can better help you. Comments like this will be hidden when you post but you can delete them if you wish. -->
**LocalAI version:**
<!-- Container Image or LocalAI tag/commit -->
**Environment, CPU architecture, OS, and Version:**
<!-- Provide the output from "uname -a", HW specs, if it's a VM -->
**Describe the bug**
<!-- A clear and concise description of what the bug is. -->
**To Reproduce**
<!-- Steps to reproduce the behavior, including the LocalAI command used, if any -->
**Expected behavior**
<!-- A clear and concise description of what you expected to happen. -->
**Logs**
<!-- If applicable, add logs while running LocalAI in debug mode (`--debug` or `DEBUG=true`) to help explain your problem. -->
**Additional context**
<!-- Add any other context about the problem here. -->

@ -1,8 +0,0 @@
blank_issues_enabled: false
contact_links:
- name: Community Support
url: https://github.com/go-skynet/LocalAI/discussions
about: Please ask and answer questions here.
- name: Discord
url: https://discord.gg/uJAeKSAGDy
about: Join our community on Discord!

@ -1,22 +0,0 @@
---
name: Feature request
about: Suggest an idea for this project
title: ''
labels: enhancement
assignees: mudler
---
<!-- Thanks for helping us to improve LocalAI! We welcome all feature requests. Please fill out each area of the template so we can better help you. Comments like this will be hidden when you post but you can delete them if you wish. -->
**Is your feature request related to a problem? Please describe.**
<!-- A clear and concise description of what the problem is. Ex. I'm always frustrated when [...] -->
**Describe the solution you'd like**
<!-- A clear and concise description of what you want to happen. -->
**Describe alternatives you've considered**
<!-- A clear and concise description of any alternative solutions or features you've considered. -->
**Additional context**
<!-- Add any other context or screenshots about the feature request here. -->

@ -1,23 +0,0 @@
**Description**
This PR fixes #
**Notes for Reviewers**
**[Signed commits](../CONTRIBUTING.md#signing-off-on-commits-developer-certificate-of-origin)**
- [ ] Yes, I signed my commits.
<!--
Thank you for contributing to LocalAI!
Contributing Conventions:
1. Include descriptive PR titles with [<component-name>] prepended.
2. Build and test your changes before submitting a PR.
3. Sign your commits
By following the community's contribution conventions upfront, the review process will
be accelerated and your PR merged more quickly.
-->

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

@ -1,24 +0,0 @@
# .github/release.yml
changelog:
exclude:
labels:
- ignore-for-release
categories:
- title: Breaking Changes 🛠
labels:
- Semver-Major
- breaking-change
- title: "Bug fixes :bug:"
labels:
- bug
- title: Exciting New Features 🎉
labels:
- Semver-Minor
- enhancement
- title: 👒 Dependencies
labels:
- dependencies
- title: Other Changes
labels:
- "*"

@ -1,18 +0,0 @@
# Number of days of inactivity before an issue becomes stale
daysUntilStale: 45
# Number of days of inactivity before a stale issue is closed
daysUntilClose: 10
# Issues with these labels will never be considered stale
exemptLabels:
- issue/willfix
# Label to use when marking an issue as stale
staleLabel: issue/stale
# Comment to post when marking an issue as stale. Set to `false` to disable
markComment: >
This issue has been automatically marked as stale because it has not had
recent activity. It will be closed if no further activity occurs. Thank you
for your contributions.
# Comment to post when closing a stale issue. Set to `false` to disable
closeComment: >
This issue is being automatically closed due to inactivity.
However, you may choose to reopen this issue.

@ -1,63 +0,0 @@
name: Bump dependencies
on:
schedule:
- cron: 0 20 * * *
workflow_dispatch:
jobs:
bump:
strategy:
fail-fast: false
matrix:
include:
- repository: "go-skynet/go-llama.cpp"
variable: "GOLLAMA_VERSION"
branch: "master"
- repository: "go-skynet/go-llama.cpp"
variable: "GOLLAMA_GRAMMAR_VERSION"
branch: "master"
- repository: "go-skynet/go-ggml-transformers.cpp"
variable: "GOGGMLTRANSFORMERS_VERSION"
branch: "master"
- repository: "donomii/go-rwkv.cpp"
variable: "RWKV_VERSION"
branch: "main"
- repository: "ggerganov/whisper.cpp"
variable: "WHISPER_CPP_VERSION"
branch: "master"
- repository: "go-skynet/go-bert.cpp"
variable: "BERT_VERSION"
branch: "master"
- repository: "go-skynet/bloomz.cpp"
variable: "BLOOMZ_VERSION"
branch: "main"
- repository: "nomic-ai/gpt4all"
variable: "GPT4ALL_VERSION"
branch: "main"
- 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
- name: Bump dependencies 🔧
run: |
bash .github/bump_deps.sh ${{ matrix.repository }} ${{ matrix.branch }} ${{ matrix.variable }}
- name: Create Pull Request
uses: peter-evans/create-pull-request@v5
with:
token: ${{ secrets.UPDATE_BOT_TOKEN }}
push-to-fork: ci-forks/LocalAI
commit-message: ':arrow_up: Update ${{ matrix.repository }}'
title: ':arrow_up: Update ${{ matrix.repository }}'
branch: "update/${{ matrix.variable }}"
body: Bump of ${{ matrix.repository }} version
signoff: true

@ -9,103 +9,36 @@ on:
tags:
- '*'
concurrency:
group: ci-${{ github.head_ref || github.ref }}-${{ github.repository }}
cancel-in-progress: true
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: 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: 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: Set up QEMU
uses: docker/setup-qemu-action@master
@ -123,19 +56,23 @@ jobs:
registry: quay.io
username: ${{ secrets.LOCALAI_REGISTRY_USERNAME }}
password: ${{ secrets.LOCALAI_REGISTRY_PASSWORD }}
- name: Build and push
- name: Build
if: github.event_name != 'pull_request'
uses: docker/build-push-action@v4
with:
builder: ${{ steps.buildx.outputs.name }}
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: ${{ steps.buildx.outputs.name }}
build-args: |
BUILD_TYPE=${{ matrix.build-type }}
CUDA_MAJOR_VERSION=${{ matrix.cuda-major-version }}
CUDA_MINOR_VERSION=${{ matrix.cuda-minor-version }}
FFMPEG=${{ matrix.ffmpeg }}
context: .
file: ./Dockerfile
platforms: ${{ matrix.platforms }}
push: ${{ github.event_name != 'pull_request' }}
tags: ${{ steps.meta.outputs.tags }}
labels: ${{ steps.meta.outputs.labels }}
platforms: linux/amd64
push: false
tags: ${{ steps.prep.outputs.tags }}

@ -1,79 +0,0 @@
name: Build and Release
on: push
permissions:
contents: write
jobs:
build-linux:
strategy:
matrix:
include:
- build: 'avx2'
defines: ''
- build: 'avx'
defines: '-DLLAMA_AVX2=OFF'
- build: 'avx512'
defines: '-DLLAMA_AVX512=ON'
runs-on: ubuntu-latest
steps:
- name: Clone
uses: actions/checkout@v3
with:
submodules: true
- name: Dependencies
run: |
sudo apt-get update
sudo apt-get install build-essential ffmpeg
- name: Build
id: build
env:
CMAKE_ARGS: "${{ matrix.defines }}"
BUILD_ID: "${{ matrix.build }}"
run: |
STATIC=true make dist
- uses: actions/upload-artifact@v3
with:
name: ${{ matrix.build }}
path: release/
- name: Release
uses: softprops/action-gh-release@v1
if: startsWith(github.ref, 'refs/tags/')
with:
files: |
release/*
build-macOS:
strategy:
matrix:
include:
- build: 'avx2'
defines: ''
- build: 'avx'
defines: '-DLLAMA_AVX2=OFF'
- build: 'avx512'
defines: '-DLLAMA_AVX512=ON'
runs-on: macOS-latest
steps:
- name: Clone
uses: actions/checkout@v3
with:
submodules: true
- name: Build
id: build
env:
CMAKE_ARGS: "${{ matrix.defines }}"
BUILD_ID: "${{ matrix.build }}"
run: |
make dist
- uses: actions/upload-artifact@v3
with:
name: ${{ matrix.build }}
path: release/
- name: Release
uses: softprops/action-gh-release@v1
if: startsWith(github.ref, 'refs/tags/')
with:
files: |
release/*

@ -0,0 +1,26 @@
name: goreleaser
on:
push:
tags:
- 'v*'
jobs:
goreleaser:
runs-on: ubuntu-latest
steps:
- name: Checkout
uses: actions/checkout@v3
with:
fetch-depth: 0
- name: Set up Go
uses: actions/setup-go@v3
with:
go-version: 1.18
- name: Run GoReleaser
uses: goreleaser/goreleaser-action@v4
with:
version: latest
args: release --clean
env:
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}

@ -9,10 +9,6 @@ on:
tags:
- '*'
concurrency:
group: ci-tests-${{ github.head_ref || github.ref }}-${{ github.repository }}
cancel-in-progress: true
jobs:
ubuntu-latest:
runs-on: ubuntu-latest
@ -25,30 +21,10 @@ jobs:
- 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-$(uname -m)/piper_phonemize/lib/. /lib64/ && \
sudo cp -rfv /build/lib/Linux-$(uname -m)/piper_phonemize/lib/. /usr/lib/ && \
sudo cp -rfv /build/lib/Linux-$(uname -m)/piper_phonemize/include/. /usr/include/
sudo apt-get install build-essential
- name: Test
run: |
ESPEAK_DATA="/build/lib/Linux-$(uname -m)/piper_phonemize/lib/espeak-ng-data" GO_TAGS="tts stablediffusion" make test
make test
macOS-latest:
runs-on: macOS-latest
@ -59,6 +35,10 @@ jobs:
with:
submodules: true
- name: Dependencies
run: |
brew update
brew install sdl2
- name: Test
run: |
CMAKE_ARGS="-DLLAMA_F16C=OFF -DLLAMA_AVX512=OFF -DLLAMA_AVX2=OFF -DLLAMA_FMA=OFF" make test
make test

28
.gitignore vendored

@ -1,21 +1,7 @@
# go-llama build artifacts
go-llama
/gpt4all
go-stable-diffusion
go-piper
/go-bert
go-ggllm
/piper
__pycache__/
*.a
get-sources
go-ggml-transformers
go-gpt4all-j
go-gpt2
go-rwkv
whisper.cpp
/bloomz
go-bert
# LocalAI build binary
LocalAI
@ -26,15 +12,3 @@ local-ai
# Ignore models
models/*
test-models/
test-dir/
release/
# just in case
.DS_Store
.idea
# Generated during build
backend-assets/
/ggml-metal.metal

@ -0,0 +1,15 @@
# Make sure to check the documentation at http://goreleaser.com
project_name: local-ai
builds:
- ldflags:
- -w -s
env:
- CGO_ENABLED=0
goos:
- linux
- darwin
- windows
goarch:
- amd64
- arm64
binary: '{{ .ProjectName }}'

@ -2,20 +2,7 @@
"version": "0.2.0",
"configurations": [
{
"name": "Python: Current File",
"type": "python",
"request": "launch",
"program": "${file}",
"console": "integratedTerminal",
"justMyCode": false,
"cwd": "${workspaceFolder}/examples/langchain-chroma",
"env": {
"OPENAI_API_BASE": "http://localhost:8080/v1",
"OPENAI_API_KEY": "abc"
}
},
{
"name": "Launch LocalAI API",
"name": "Launch Go",
"type": "go",
"request": "launch",
"mode": "debug",
@ -24,8 +11,8 @@
"api"
],
"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",
"C_INCLUDE_PATH": "/workspace/go-llama:/workspace/go-gpt4all-j:/workspace/go-gpt2",
"LIBRARY_PATH": "/workspace/go-llama:/workspace/go-gpt4all-j:/workspace/go-gpt2",
"DEBUG": "true"
}
}

@ -1,125 +1,9 @@
ARG GO_VERSION=1.20-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"
ARG GO_TAGS="stablediffusion tts"
RUN apt-get update && \
apt-get install -y ca-certificates cmake curl patch pip
# Extras requirements
COPY extra/requirements.txt /build/extra/requirements.txt
RUN pip install -r /build/extra/requirements.txt && rm -rf /build/extra/requirements.txt
# 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}-${CUDA_MINOR_VERSION} \
; fi
ENV PATH /usr/local/cuda/bin:${PATH}
ARG GO_VERSION=1.20
ARG BUILD_TYPE=
FROM golang:$GO_VERSION
WORKDIR /build
# 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
# Use the variables in subsequent instructions
RUN echo "Target Architecture: $TARGETARCH"
RUN echo "Target Variant: $TARGETVARIANT"
# piper requirements
# Use pre-compiled Piper phonemization library (includes onnxruntime)
#RUN if echo "${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-$(uname -m)/piper_phonemize/lib/. /lib64/ && \
cp -rfv /build/lib/Linux-$(uname -m)/piper_phonemize/lib/. /usr/lib/ && \
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>=${CUDA_MAJOR_VERSION}.0"
ENV NVIDIA_VISIBLE_DEVICES=all
WORKDIR /build
COPY Makefile .
RUN make get-sources
COPY go.mod .
RUN make prepare
COPY . .
COPY .git .
RUN ESPEAK_DATA=/build/lib/Linux-$(uname -m)/piper_phonemize/lib/espeak-ng-data make build
###################################
###################################
FROM requirements
ARG FFMPEG
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
RUN apt-get update && apt-get install -y cmake
COPY . .
RUN make prepare-sources
COPY --from=builder /build/local-ai ./
# Define the health check command
HEALTHCHECK --interval=1m --timeout=10m --retries=10 \
CMD curl -f $HEALTHCHECK_ENDPOINT || exit 1
EXPOSE 8080
ENTRYPOINT [ "/build/entrypoint.sh" ]

@ -0,0 +1,14 @@
ARG GO_VERSION=1.20
ARG DEBIAN_VERSION=11
ARG BUILD_TYPE=
FROM golang:$GO_VERSION as builder
WORKDIR /build
RUN apt-get update && apt-get install -y cmake
COPY . .
RUN make build
FROM debian:$DEBIAN_VERSION
COPY --from=builder /build/local-ai /usr/bin/local-ai
EXPOSE 8080
ENTRYPOINT [ "/usr/bin/local-ai" ]

@ -1,6 +1,6 @@
MIT License
Copyright (c) 2023 Ettore Di Giacinto
Copyright (c) 2023 go-skynet authors
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal

@ -2,149 +2,53 @@ GOCMD=go
GOTEST=$(GOCMD) test
GOVET=$(GOCMD) vet
BINARY_NAME=local-ai
# renovate: datasource=github-tags depName=go-skynet/go-llama.cpp
GOLLAMA_VERSION?=llama.cpp-f4cef87
# renovate: datasource=git-refs packageNameTemplate=https://github.com/go-skynet/go-gpt4all-j.cpp currentValueTemplate=master depNameTemplate=go-gpt4all-j.cpp
GOGPT4ALLJ_VERSION?=1f7bff57f66cb7062e40d0ac3abd2217815e5109
# renovate: datasource=git-refs packageNameTemplate=https://github.com/go-skynet/go-gpt2.cpp currentValueTemplate=master depNameTemplate=go-gpt2.cpp
GOGPT2_VERSION?=245a5bfe6708ab80dc5c733dcdbfbe3cfd2acdaa
# llama.cpp versions
# Temporarly pinned to https://github.com/go-skynet/go-llama.cpp/pull/124
GOLLAMA_VERSION?=f3a6ee0ef53d667f110d28fcf9b808bdca741c07
GOLLAMA_GRAMMAR_VERSION?=cb8d7cd4cb95725a04504a9e3a26dd72a12b69ac
# Temporary set a specific version of llama.cpp
# containing: https://github.com/ggerganov/llama.cpp/pull/1773 and
# rebased on top of master.
# This pin can be dropped when the PR above is merged, and go-llama has merged changes as well
# Set empty to use the version pinned by go-llama
LLAMA_CPP_GRAMMAR_REPO?=https://github.com/mudler/llama.cpp
LLAMA_CPP_GRAMMAR_VERSION?=48ce8722a05a018681634af801fd0fd45b3a87cc
# gpt4all version
GPT4ALL_REPO?=https://github.com/nomic-ai/gpt4all
GPT4ALL_VERSION?=5f0aaf8bdb166ea3b5bfd578c2b19f61b583e6a9
# go-ggml-transformers version
GOGGMLTRANSFORMERS_VERSION?=ffb09d7dd71e2cbc6c5d7d05357d230eea6f369a
# go-rwkv version
RWKV_REPO?=https://github.com/donomii/go-rwkv.cpp
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
RWKV_VERSION?=af62fcc432be2847acb6e0688b2c2491d6588d58
export BUILD_TYPE?=
CGO_LDFLAGS?=
CUDA_LIBPATH?=/usr/local/cuda/lib64/
GO_TAGS?=
BUILD_ID?=git
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)
GREEN := $(shell tput -Txterm setaf 2)
YELLOW := $(shell tput -Txterm setaf 3)
WHITE := $(shell tput -Txterm setaf 7)
CYAN := $(shell tput -Txterm setaf 6)
RESET := $(shell tput -Txterm sgr0)
ifndef UNAME_S
UNAME_S := $(shell uname -s)
endif
# workaround for rwkv.cpp
ifeq ($(UNAME_S),Darwin)
CGO_LDFLAGS += -lcblas -framework Accelerate
endif
ifeq ($(BUILD_TYPE),openblas)
CGO_LDFLAGS+=-lopenblas
endif
ifeq ($(BUILD_TYPE),cublas)
CGO_LDFLAGS+=-lcublas -lcudart -L$(CUDA_LIBPATH)
export LLAMA_CUBLAS=1
endif
ifeq ($(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
C_INCLUDE_PATH=$(shell pwd)/go-llama:$(shell pwd)/go-gpt4all-j:$(shell pwd)/go-gpt2:$(shell pwd)/go-rwkv
LIBRARY_PATH=$(shell pwd)/go-llama:$(shell pwd)/go-gpt4all-j:$(shell pwd)/go-gpt2:$(shell pwd)/go-rwkv
ifeq ($(findstring stablediffusion,$(GO_TAGS)),stablediffusion)
# OPTIONAL_TARGETS+=go-stable-diffusion/libstablediffusion.a
OPTIONAL_GRPC+=backend-assets/grpc/stablediffusion
# Use this if you want to set the default behavior
ifndef BUILD_TYPE
BUILD_TYPE:=default
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
ifeq ($(BUILD_TYPE), "generic")
GENERIC_PREFIX:=generic-
else
GENERIC_PREFIX:=
endif
.PHONY: all test build vendor
all: help
## GPT4ALL
gpt4all:
git clone --recurse-submodules $(GPT4ALL_REPO) gpt4all
cd gpt4all && git checkout -b build $(GPT4ALL_VERSION) && git submodule update --init --recursive --depth 1
## 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
## stable diffusion
go-stable-diffusion:
git clone --recurse-submodules https://github.com/mudler/go-stable-diffusion go-stable-diffusion
cd go-stable-diffusion && git checkout -b build $(STABLEDIFFUSION_VERSION) && git submodule update --init --recursive --depth 1
go-stable-diffusion/libstablediffusion.a:
$(MAKE) -C go-stable-diffusion libstablediffusion.a
## GPT4ALL-J
go-gpt4all-j:
git clone --recurse-submodules https://github.com/go-skynet/go-gpt4all-j.cpp go-gpt4all-j
cd go-gpt4all-j && git checkout -b build $(GOGPT4ALLJ_VERSION) && git submodule update --init --recursive --depth 1
# This is hackish, but needed as both go-llama and go-gpt4allj have their own version of ggml..
@find ./go-gpt4all-j -type f -name "*.c" -exec sed -i'' -e 's/ggml_/ggml_gptj_/g' {} +
@find ./go-gpt4all-j -type f -name "*.cpp" -exec sed -i'' -e 's/ggml_/ggml_gptj_/g' {} +
@find ./go-gpt4all-j -type f -name "*.h" -exec sed -i'' -e 's/ggml_/ggml_gptj_/g' {} +
@find ./go-gpt4all-j -type f -name "*.cpp" -exec sed -i'' -e 's/gpt_/gptj_/g' {} +
@find ./go-gpt4all-j -type f -name "*.h" -exec sed -i'' -e 's/gpt_/gptj_/g' {} +
@find ./go-gpt4all-j -type f -name "*.cpp" -exec sed -i'' -e 's/json_/json_gptj_/g' {} +
@find ./go-gpt4all-j -type f -name "*.cpp" -exec sed -i'' -e 's/void replace/void json_gptj_replace/g' {} +
@find ./go-gpt4all-j -type f -name "*.cpp" -exec sed -i'' -e 's/::replace/::json_gptj_replace/g' {} +
## RWKV
go-rwkv:
@ -152,190 +56,83 @@ go-rwkv:
cd go-rwkv && git checkout -b build $(RWKV_VERSION) && git submodule update --init --recursive --depth 1
go-rwkv/librwkv.a: go-rwkv
cd go-rwkv && cd rwkv.cpp && cmake . -DRWKV_BUILD_SHARED_LIBRARY=OFF && cmake --build . && cp librwkv.a ..
## bloomz
bloomz:
git clone --recurse-submodules https://github.com/go-skynet/bloomz.cpp bloomz
cd bloomz && git checkout -b build $(BLOOMZ_VERSION) && git submodule update --init --recursive --depth 1
bloomz/libbloomz.a: bloomz
cd bloomz && make libbloomz.a
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
cd go-rwkv && cd rwkv.cpp && cmake . -DRWKV_BUILD_SHARED_LIBRARY=OFF && cmake --build . && cp librwkv.a .. && cp ggml/src/libggml.a ..
gpt4all/gpt4all-bindings/golang/libgpt4all.a: gpt4all
$(MAKE) -C gpt4all/gpt4all-bindings/golang/ libgpt4all.a
go-gpt4all-j/libgptj.a: go-gpt4all-j
$(MAKE) -C go-gpt4all-j $(GENERIC_PREFIX)libgptj.a
## CEREBRAS GPT
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
go-ggml-transformers/libtransformers.a: go-ggml-transformers
$(MAKE) -C go-ggml-transformers BUILD_TYPE=$(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
whisper.cpp/libwhisper.a: whisper.cpp
cd whisper.cpp && make libwhisper.a
go-gpt2:
git clone --recurse-submodules https://github.com/go-skynet/go-gpt2.cpp go-gpt2
cd go-gpt2 && git checkout -b build $(GOGPT2_VERSION) && git submodule update --init --recursive --depth 1
# This is hackish, but needed as both go-llama and go-gpt4allj have their own version of ggml..
@find ./go-gpt2 -type f -name "*.c" -exec sed -i'' -e 's/ggml_/ggml_gpt2_/g' {} +
@find ./go-gpt2 -type f -name "*.cpp" -exec sed -i'' -e 's/ggml_/ggml_gpt2_/g' {} +
@find ./go-gpt2 -type f -name "*.h" -exec sed -i'' -e 's/ggml_/ggml_gpt2_/g' {} +
@find ./go-gpt2 -type f -name "*.cpp" -exec sed -i'' -e 's/gpt_/gpt2_/g' {} +
@find ./go-gpt2 -type f -name "*.h" -exec sed -i'' -e 's/gpt_/gpt2_/g' {} +
@find ./go-gpt2 -type f -name "*.cpp" -exec sed -i'' -e 's/json_/json_gpt2_/g' {} +
go-gpt2/libgpt2.a: go-gpt2
$(MAKE) -C go-gpt2 $(GENERIC_PREFIX)libgpt2.a
go-llama:
git clone --recurse-submodules https://github.com/go-skynet/go-llama.cpp go-llama
cd go-llama && git checkout -b build $(GOLLAMA_VERSION) && git submodule update --init --recursive --depth 1
go-llama-grammar:
git clone --recurse-submodules https://github.com/go-skynet/go-llama.cpp go-llama-grammar
cd go-llama-grammar && git checkout -b build $(GOLLAMA_GRAMMAR_VERSION) && git submodule update --init --recursive --depth 1
ifneq ($(LLAMA_CPP_GRAMMAR_REPO),)
cd go-llama-grammar && rm -rf llama.cpp && git clone $(LLAMA_CPP_GRAMMAR_REPO) llama.cpp && cd llama.cpp && git checkout -b build $(LLAMA_CPP_GRAMMAR_VERSION) && git submodule update --init --recursive --depth 1
endif
git clone -b $(GOLLAMA_VERSION) --recurse-submodules https://github.com/go-skynet/go-llama.cpp go-llama
go-llama/libbinding.a: go-llama
$(MAKE) -C go-llama BUILD_TYPE=$(BUILD_TYPE) libbinding.a
go-llama-grammar/libbinding.a: go-llama-grammar
$(MAKE) -C go-llama-grammar BUILD_TYPE=$(BUILD_TYPE) libbinding.a
go-piper/libpiper_binding.a:
$(MAKE) -C go-piper libpiper_binding.a example/main
get-sources: go-llama go-ggllm go-llama-grammar go-ggml-transformers gpt4all go-piper go-rwkv whisper.cpp go-bert bloomz go-stable-diffusion
touch $@
$(MAKE) -C go-llama $(GENERIC_PREFIX)libbinding.a
replace:
$(GOCMD) mod edit -replace github.com/go-skynet/go-llama.cpp=$(shell pwd)/go-llama
$(GOCMD) mod edit -replace github.com/go-skynet/go-llama.cpp-grammar=$(shell pwd)/go-llama-grammar
$(GOCMD) mod edit -replace github.com/nomic-ai/gpt4all/gpt4all-bindings/golang=$(shell pwd)/gpt4all/gpt4all-bindings/golang
$(GOCMD) mod edit -replace github.com/go-skynet/go-ggml-transformers.cpp=$(shell pwd)/go-ggml-transformers
$(GOCMD) mod edit -replace github.com/go-skynet/go-gpt4all-j.cpp=$(shell pwd)/go-gpt4all-j
$(GOCMD) mod edit -replace github.com/go-skynet/go-gpt2.cpp=$(shell pwd)/go-gpt2
$(GOCMD) mod edit -replace github.com/donomii/go-rwkv.cpp=$(shell pwd)/go-rwkv
$(GOCMD) mod edit -replace github.com/ggerganov/whisper.cpp=$(shell pwd)/whisper.cpp
$(GOCMD) mod edit -replace github.com/go-skynet/go-bert.cpp=$(shell pwd)/go-bert
$(GOCMD) mod edit -replace github.com/go-skynet/bloomz.cpp=$(shell pwd)/bloomz
$(GOCMD) mod edit -replace github.com/mudler/go-stable-diffusion=$(shell pwd)/go-stable-diffusion
$(GOCMD) mod edit -replace github.com/mudler/go-piper=$(shell pwd)/go-piper
$(GOCMD) mod edit -replace github.com/mudler/go-ggllm.cpp=$(shell pwd)/go-ggllm
prepare-sources: get-sources replace
prepare-sources: go-llama go-gpt2 go-gpt4all-j go-rwkv
$(GOCMD) mod download
## GENERIC
rebuild: ## Rebuilds the project
$(GOCMD) clean -cache
$(MAKE) -C go-llama clean
$(MAKE) -C go-llama-grammar clean
$(MAKE) -C gpt4all/gpt4all-bindings/golang/ clean
$(MAKE) -C go-ggml-transformers clean
$(MAKE) -C go-gpt4all-j clean
$(MAKE) -C go-gpt2 clean
$(MAKE) -C go-rwkv clean
$(MAKE) -C whisper.cpp clean
$(MAKE) -C go-stable-diffusion clean
$(MAKE) -C go-bert clean
$(MAKE) -C bloomz clean
$(MAKE) -C go-piper clean
$(MAKE) -C go-ggllm clean
$(MAKE) build
prepare: prepare-sources $(OPTIONAL_TARGETS)
touch $@
prepare: prepare-sources go-llama/libbinding.a go-gpt4all-j/libgptj.a go-gpt2/libgpt2.a go-rwkv/librwkv.a replace ## Prepares for building
clean: ## Remove build related file
$(GOCMD) clean -cache
rm -fr ./go-llama
rm -rf ./gpt4all
rm -rf ./go-gpt4all-j
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: grpcs prepare ## Build the project
build: prepare ## Build the project
$(info ${GREEN}I local-ai build info:${RESET})
$(info ${GREEN}I BUILD_TYPE: ${YELLOW}$(BUILD_TYPE)${RESET})
$(info ${GREEN}I GO_TAGS: ${YELLOW}$(GO_TAGS)${RESET})
$(info ${GREEN}I LD_FLAGS: ${YELLOW}$(LD_FLAGS)${RESET})
C_INCLUDE_PATH=${C_INCLUDE_PATH} LIBRARY_PATH=${LIBRARY_PATH} $(GOCMD) build -o $(BINARY_NAME) ./
CGO_LDFLAGS="$(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)" $(GOCMD) run ./
C_INCLUDE_PATH=${C_INCLUDE_PATH} LIBRARY_PATH=${LIBRARY_PATH} $(GOCMD) run ./main.go
test-models/testmodel:
mkdir test-models
mkdir test-dir
wget https://huggingface.co/nnakasato/ggml-model-test/resolve/main/ggml-model-q4.bin -O test-models/testmodel
wget https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-base.en.bin -O test-models/whisper-en
wget https://huggingface.co/skeskinen/ggml/resolve/main/all-MiniLM-L6-v2/ggml-model-q4_0.bin -O test-models/bert
wget https://cdn.openai.com/whisper/draft-20220913a/micro-machines.wav -O test-dir/audio.wav
wget https://huggingface.co/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
prepare-test: grpcs
cp -rf backend-assets api
cp tests/models_fixtures/* test-models
wget https://huggingface.co/concedo/cerebras-111M-ggml/resolve/main/cerberas-111m-q4_0.bin -O test-models/testmodel
cp tests/fixtures/* test-models
test: prepare test-models/testmodel 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" --flake-attempts 5 -v -r ./api ./pkg
$(MAKE) test-gpt4all
$(MAKE) test-llama
$(MAKE) test-tts
$(MAKE) test-stablediffusion
test: prepare test-models/testmodel
cp tests/fixtures/* test-models
@C_INCLUDE_PATH=${C_INCLUDE_PATH} LIBRARY_PATH=${LIBRARY_PATH} CONFIG_FILE=$(abspath ./)/test-models/config.yaml MODELS_PATH=$(abspath ./)/test-models $(GOCMD) test -v -timeout 30m ./...
test-gpt4all: prepare-test
TEST_DIR=$(abspath ./)/test-dir/ FIXTURES=$(abspath ./)/tests/fixtures CONFIG_FILE=$(abspath ./)/test-models/config.yaml MODELS_PATH=$(abspath ./)/test-models \
$(GOCMD) run github.com/onsi/ginkgo/v2/ginkgo --label-filter="gpt4all" --flake-attempts 5 -v -r ./api ./pkg
test-llama: prepare-test
TEST_DIR=$(abspath ./)/test-dir/ FIXTURES=$(abspath ./)/tests/fixtures CONFIG_FILE=$(abspath ./)/test-models/config.yaml MODELS_PATH=$(abspath ./)/test-models \
$(GOCMD) run github.com/onsi/ginkgo/v2/ginkgo --label-filter="llama" --flake-attempts 5 -v -r ./api ./pkg
test-tts: prepare-test
TEST_DIR=$(abspath ./)/test-dir/ FIXTURES=$(abspath ./)/tests/fixtures CONFIG_FILE=$(abspath ./)/test-models/config.yaml MODELS_PATH=$(abspath ./)/test-models \
$(GOCMD) run github.com/onsi/ginkgo/v2/ginkgo --label-filter="tts" --flake-attempts 1 -v -r ./api ./pkg
test-stablediffusion: prepare-test
TEST_DIR=$(abspath ./)/test-dir/ FIXTURES=$(abspath ./)/tests/fixtures CONFIG_FILE=$(abspath ./)/test-models/config.yaml MODELS_PATH=$(abspath ./)/test-models \
$(GOCMD) run github.com/onsi/ginkgo/v2/ginkgo --label-filter="stablediffusion" --flake-attempts 1 -v -r ./api ./pkg
test-container:
docker build --target requirements -t local-ai-test-container .
docker run -ti --rm --entrypoint /bin/bash -ti -v $(abspath ./):/build local-ai-test-container
swagger:
swag init -g api/api.go --output docs/swagger
## Help:
help: ## Show this help.
@ -348,98 +145,3 @@ 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)} \
}' $(MAKEFILE_LIST)
protogen: protogen-go protogen-python
protogen-go:
protoc --go_out=. --go_opt=paths=source_relative --go-grpc_out=. --go-grpc_opt=paths=source_relative \
pkg/grpc/proto/backend.proto
protogen-python:
python -m grpc_tools.protoc -Ipkg/grpc/proto/ --python_out=extra/grpc/huggingface/ --grpc_python_out=extra/grpc/huggingface/ pkg/grpc/proto/backend.proto
## GRPC
backend-assets/grpc:
mkdir -p backend-assets/grpc
backend-assets/grpc/falcon: backend-assets/grpc go-ggllm/libggllm.a
CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(shell pwd)/go-ggllm LIBRARY_PATH=$(shell pwd)/go-ggllm \
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/falcon ./cmd/grpc/falcon/
backend-assets/grpc/llama: backend-assets/grpc go-llama/libbinding.a
CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(shell pwd)/go-llama LIBRARY_PATH=$(shell pwd)/go-llama \
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/llama ./cmd/grpc/llama/
# TODO: every binary should have its own folder instead, so can have different metal implementations
ifeq ($(BUILD_TYPE),metal)
cp go-llama/build/bin/ggml-metal.metal backend-assets/grpc/
endif
backend-assets/grpc/llama-grammar: backend-assets/grpc go-llama-grammar/libbinding.a
CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(shell pwd)/go-llama-grammar LIBRARY_PATH=$(shell pwd)/go-llama-grammar \
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/llama-grammar ./cmd/grpc/llama-grammar/
backend-assets/grpc/gpt4all: backend-assets/grpc backend-assets/gpt4all gpt4all/gpt4all-bindings/golang/libgpt4all.a
CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(shell pwd)/gpt4all/gpt4all-bindings/golang/ LIBRARY_PATH=$(shell pwd)/gpt4all/gpt4all-bindings/golang/ \
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/gpt4all ./cmd/grpc/gpt4all/
backend-assets/grpc/dolly: backend-assets/grpc go-ggml-transformers/libtransformers.a
CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(shell pwd)/go-ggml-transformers LIBRARY_PATH=$(shell pwd)/go-ggml-transformers \
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/dolly ./cmd/grpc/dolly/
backend-assets/grpc/gpt2: backend-assets/grpc go-ggml-transformers/libtransformers.a
CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(shell pwd)/go-ggml-transformers LIBRARY_PATH=$(shell pwd)/go-ggml-transformers \
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/gpt2 ./cmd/grpc/gpt2/
backend-assets/grpc/gptj: backend-assets/grpc go-ggml-transformers/libtransformers.a
CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(shell pwd)/go-ggml-transformers LIBRARY_PATH=$(shell pwd)/go-ggml-transformers \
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/gptj ./cmd/grpc/gptj/
backend-assets/grpc/gptneox: backend-assets/grpc go-ggml-transformers/libtransformers.a
CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(shell pwd)/go-ggml-transformers LIBRARY_PATH=$(shell pwd)/go-ggml-transformers \
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/gptneox ./cmd/grpc/gptneox/
backend-assets/grpc/mpt: backend-assets/grpc go-ggml-transformers/libtransformers.a
CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(shell pwd)/go-ggml-transformers LIBRARY_PATH=$(shell pwd)/go-ggml-transformers \
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/mpt ./cmd/grpc/mpt/
backend-assets/grpc/replit: backend-assets/grpc go-ggml-transformers/libtransformers.a
CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(shell pwd)/go-ggml-transformers LIBRARY_PATH=$(shell pwd)/go-ggml-transformers \
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/replit ./cmd/grpc/replit/
backend-assets/grpc/falcon-ggml: backend-assets/grpc go-ggml-transformers/libtransformers.a
CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(shell pwd)/go-ggml-transformers LIBRARY_PATH=$(shell pwd)/go-ggml-transformers \
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/falcon-ggml ./cmd/grpc/falcon-ggml/
backend-assets/grpc/starcoder: backend-assets/grpc go-ggml-transformers/libtransformers.a
CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(shell pwd)/go-ggml-transformers LIBRARY_PATH=$(shell pwd)/go-ggml-transformers \
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/starcoder ./cmd/grpc/starcoder/
backend-assets/grpc/rwkv: backend-assets/grpc go-rwkv/librwkv.a
CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(shell pwd)/go-rwkv LIBRARY_PATH=$(shell pwd)/go-rwkv \
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/rwkv ./cmd/grpc/rwkv/
backend-assets/grpc/bloomz: backend-assets/grpc bloomz/libbloomz.a
CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(shell pwd)/bloomz LIBRARY_PATH=$(shell pwd)/bloomz \
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/bloomz ./cmd/grpc/bloomz/
backend-assets/grpc/bert-embeddings: backend-assets/grpc go-bert/libgobert.a
CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(shell pwd)/go-bert LIBRARY_PATH=$(shell pwd)/go-bert \
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/bert-embeddings ./cmd/grpc/bert-embeddings/
backend-assets/grpc/langchain-huggingface: backend-assets/grpc
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/langchain-huggingface ./cmd/grpc/langchain-huggingface/
backend-assets/grpc/stablediffusion: backend-assets/grpc go-stable-diffusion/libstablediffusion.a
CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(shell pwd)/go-stable-diffusion/ LIBRARY_PATH=$(shell pwd)/go-stable-diffusion/ \
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/stablediffusion ./cmd/grpc/stablediffusion/
backend-assets/grpc/piper: backend-assets/grpc backend-assets/espeak-ng-data go-piper/libpiper_binding.a
CGO_LDFLAGS="$(CGO_LDFLAGS)" LIBRARY_PATH=$(shell pwd)/go-piper \
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/piper ./cmd/grpc/piper/
backend-assets/grpc/whisper: backend-assets/grpc whisper.cpp/libwhisper.a
CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(shell pwd)/whisper.cpp LIBRARY_PATH=$(shell pwd)/whisper.cpp \
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/whisper ./cmd/grpc/whisper/
grpcs: prepare backend-assets/grpc/langchain-huggingface backend-assets/grpc/llama-grammar backend-assets/grpc/falcon-ggml backend-assets/grpc/bert-embeddings backend-assets/grpc/falcon backend-assets/grpc/bloomz backend-assets/grpc/llama backend-assets/grpc/gpt4all backend-assets/grpc/dolly backend-assets/grpc/gpt2 backend-assets/grpc/gptj backend-assets/grpc/gptneox backend-assets/grpc/mpt backend-assets/grpc/replit backend-assets/grpc/starcoder backend-assets/grpc/rwkv backend-assets/grpc/whisper $(OPTIONAL_GRPC)

@ -1,8 +1,108 @@
# LOCAL AI
<h1 align="center">
<br>
<img height="300" src="https://user-images.githubusercontent.com/2420543/233147843-88697415-6dbf-4368-a862-ab217f9f7342.jpeg"> <br>
LocalAI
<br>
</h1>
## USAGE
[![tests](https://github.com/go-skynet/LocalAI/actions/workflows/test.yml/badge.svg)](https://github.com/go-skynet/LocalAI/actions/workflows/test.yml) [![build container images](https://github.com/go-skynet/LocalAI/actions/workflows/image.yml/badge.svg)](https://github.com/go-skynet/LocalAI/actions/workflows/image.yml)
- Installation et démarrage:
[![](https://dcbadge.vercel.app/api/server/uJAeKSAGDy?style=flat-square&theme=default-inverted)](https://discord.gg/uJAeKSAGDy)
**LocalAI** is a drop-in replacement REST API compatible with OpenAI for local CPU inferencing. It allows to run models locally or on-prem with consumer grade hardware. It is based on [llama.cpp](https://github.com/ggerganov/llama.cpp), [gpt4all](https://github.com/nomic-ai/gpt4all), [rwkv.cpp](https://github.com/saharNooby/rwkv.cpp) and [ggml](https://github.com/ggerganov/ggml), including support GPT4ALL-J which is licensed under Apache 2.0.
- OpenAI compatible API
- Supports multiple-models
- Once loaded the first time, it keep models loaded in memory for faster inference
- Support for prompt templates
- Doesn't shell-out, but uses C bindings for a faster inference and better performance.
LocalAI is a community-driven project, focused on making the AI accessible to anyone. Any contribution, feedback and PR is welcome! It was initially created by [mudler](https://github.com/mudler/) at the [SpectroCloud OSS Office](https://github.com/spectrocloud).
### News
- 02-05-2023: Support for `rwkv.cpp` models ( https://github.com/go-skynet/LocalAI/pull/158 ) and for `/edits` endpoint
- 01-05-2023: Support for SSE stream of tokens in `llama.cpp` backends ( https://github.com/go-skynet/LocalAI/pull/152 )
### Socials and community chatter
- Follow [@LocalAI_API](https://twitter.com/LocalAI_API) on twitter.
- [Reddit post](https://www.reddit.com/r/selfhosted/comments/12w4p2f/localai_openai_compatible_api_to_run_llm_models/) about LocalAI.
- [Hacker news post](https://news.ycombinator.com/item?id=35726934) - help us out by voting if you like this project.
- [Tutorial to use k8sgpt with LocalAI](https://medium.com/@tyler_97636/k8sgpt-localai-unlock-kubernetes-superpowers-for-free-584790de9b65) - excellent usecase for localAI, using AI to analyse Kubernetes clusters.
## Model compatibility
It is compatible with the models supported by [llama.cpp](https://github.com/ggerganov/llama.cpp) supports also [GPT4ALL-J](https://github.com/nomic-ai/gpt4all) and [cerebras-GPT with ggml](https://huggingface.co/lxe/Cerebras-GPT-2.7B-Alpaca-SP-ggml).
Tested with:
- Vicuna
- Alpaca
- [GPT4ALL](https://github.com/nomic-ai/gpt4all)
- [GPT4ALL-J](https://gpt4all.io/models/ggml-gpt4all-j.bin)
- Koala
- [cerebras-GPT with ggml](https://huggingface.co/lxe/Cerebras-GPT-2.7B-Alpaca-SP-ggml)
- [RWKV](https://github.com/BlinkDL/RWKV-LM) models with [rwkv.cpp](https://github.com/saharNooby/rwkv.cpp)
It should also be compatible with StableLM and GPTNeoX ggml models (untested)
Note: You might need to convert older models to the new format, see [here](https://github.com/ggerganov/llama.cpp#using-gpt4all) for instance to run `gpt4all`.
### RWKV
<details>
For `rwkv` models, you need to put also the associated tokenizer along with the ggml model:
```
ls models
36464540 -rw-r--r-- 1 mudler mudler 1.2G May 3 10:51 rwkv_small
36464543 -rw-r--r-- 1 mudler mudler 2.4M May 3 10:51 rwkv_small.tokenizer.json
```
</details>
## Usage
> `LocalAI` comes by default as a container image. You can check out all the available images with corresponding tags [here](https://quay.io/repository/go-skynet/local-ai?tab=tags&tag=latest).
The easiest way to run LocalAI is by using `docker-compose`:
```bash
git clone https://github.com/go-skynet/LocalAI
cd LocalAI
# (optional) Checkout a specific LocalAI tag
# git checkout -b build <TAG>
# copy your models to models/
cp your-model.bin models/
# (optional) Edit the .env file to set things like context size and threads
# vim .env
# start with docker-compose
docker-compose up -d --build
# Now API is accessible at localhost:8080
curl http://localhost:8080/v1/models
# {"object":"list","data":[{"id":"your-model.bin","object":"model"}]}
curl http://localhost:8080/v1/completions -H "Content-Type: application/json" -d '{
"model": "your-model.bin",
"prompt": "A long time ago in a galaxy far, far away",
"temperature": 0.7
}'
```
### Example: Use GPT4ALL-J model
<details>
```bash
# Clone LocalAI
@ -23,9 +123,8 @@ cp -rf prompt-templates/ggml-gpt4all-j.tmpl models/
# vim .env
# start with docker-compose
# docker-compose up -d --pull always
# or you can build the images with:
docker-compose up -d --build
# Now API is accessible at localhost:8080
curl http://localhost:8080/v1/models
# {"object":"list","data":[{"id":"ggml-gpt4all-j","object":"model"}]}
@ -38,23 +137,482 @@ curl http://localhost:8080/v1/chat/completions -H "Content-Type: application/jso
# {"model":"ggml-gpt4all-j","choices":[{"message":{"role":"assistant","content":"I'm doing well, thanks. How about you?"}}]}
```
</details>
To build locally, run `make build` (see below).
### Other examples
![Screenshot from 2023-04-26 23-59-55](https://user-images.githubusercontent.com/2420543/234715439-98d12e03-d3ce-4f94-ab54-2b256808e05e.png)
To see other examples on how to integrate with other projects for instance chatbot-ui, see: [examples](https://github.com/go-skynet/LocalAI/tree/master/examples/).
### Advanced configuration
LocalAI can be configured to serve user-defined models with a set of default parameters and templates.
<details>
You can create multiple `yaml` files in the models path or either specify a single YAML configuration file.
Consider the following `models` folder in the `example/chatbot-ui`:
```
base ❯ ls -liah examples/chatbot-ui/models
36487587 drwxr-xr-x 2 mudler mudler 4.0K May 3 12:27 .
36487586 drwxr-xr-x 3 mudler mudler 4.0K May 3 10:42 ..
36465214 -rw-r--r-- 1 mudler mudler 10 Apr 27 07:46 completion.tmpl
36464855 -rw-r--r-- 1 mudler mudler 3.6G Apr 27 00:08 ggml-gpt4all-j
36464537 -rw-r--r-- 1 mudler mudler 245 May 3 10:42 gpt-3.5-turbo.yaml
36467388 -rw-r--r-- 1 mudler mudler 180 Apr 27 07:46 gpt4all.tmpl
```
In the `gpt-3.5-turbo.yaml` file it is defined the `gpt-3.5-turbo` model which is an alias to use `gpt4all-j` with pre-defined options.
For instance, consider the following that declares `gpt-3.5-turbo` backed by the `ggml-gpt4all-j` model:
```yaml
name: gpt-3.5-turbo
# Default model parameters
parameters:
# Relative to the models path
model: ggml-gpt4all-j
# temperature
temperature: 0.3
# all the OpenAI request options here..
# Default context size
context_size: 512
threads: 10
# Define a backend (optional). By default it will try to guess the backend the first time the model is interacted with.
backend: gptj # available: llama, stablelm, gpt2, gptj rwkv
# stopwords (if supported by the backend)
stopwords:
- "HUMAN:"
- "### Response:"
# define chat roles
roles:
user: "HUMAN:"
system: "GPT:"
template:
# template file ".tmpl" with the prompt template to use by default on the endpoint call. Note there is no extension in the files
completion: completion
chat: ggml-gpt4all-j
```
Specifying a `config-file` via CLI allows to declare models in a single file as a list, for instance:
```yaml
- name: list1
parameters:
model: testmodel
context_size: 512
threads: 10
stopwords:
- "HUMAN:"
- "### Response:"
roles:
user: "HUMAN:"
system: "GPT:"
template:
completion: completion
chat: ggml-gpt4all-j
- name: list2
parameters:
model: testmodel
context_size: 512
threads: 10
stopwords:
- "HUMAN:"
- "### Response:"
roles:
user: "HUMAN:"
system: "GPT:"
template:
completion: completion
chat: ggml-gpt4all-j
```
See also [chatbot-ui](https://github.com/go-skynet/LocalAI/tree/master/examples/chatbot-ui) as an example on how to use config files.
</details>
### Prompt templates
The API doesn't inject a default prompt for talking to the model. You have to use a prompt similar to what's described in the standford-alpaca docs: https://github.com/tatsu-lab/stanford_alpaca#data-release.
<details>
You can use a default template for every model present in your model path, by creating a corresponding file with the `.tmpl` suffix next to your model. For instance, if the model is called `foo.bin`, you can create a sibling file, `foo.bin.tmpl` which will be used as a default prompt and can be used with alpaca:
```
The below instruction describes a task. Write a response that appropriately completes the request.
### Instruction:
{{.Input}}
### Response:
```
See the [prompt-templates](https://github.com/go-skynet/LocalAI/tree/master/prompt-templates) directory in this repository for templates for some of the most popular models.
For the edit endpoint, an example template for alpaca-based models can be:
```yaml
Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request.
### Instruction:
{{.Instruction}}
### Input:
{{.Input}}
### Response:
```
</details>
### CLI
You can control LocalAI with command line arguments, to specify a binding address, or the number of threads.
<details>
Usage:
```
local-ai --models-path <model_path> [--address <address>] [--threads <num_threads>]
```
| Parameter | Environment Variable | Default Value | Description |
| ------------ | -------------------- | ------------- | -------------------------------------- |
| models-path | MODELS_PATH | | The path where you have models (ending with `.bin`). |
| threads | THREADS | Number of Physical cores | The number of threads to use for text generation. |
| address | ADDRESS | :8080 | The address and port to listen on. |
| context-size | CONTEXT_SIZE | 512 | Default token context size. |
| debug | DEBUG | false | Enable debug mode. |
| config-file | CONFIG_FILE | empty | Path to a LocalAI config file. |
</details>
## Setup
Currently LocalAI comes as a container image and can be used with docker or a container engine of choice. You can check out all the available images with corresponding tags [here](https://quay.io/repository/go-skynet/local-ai?tab=tags&tag=latest).
### Docker
<details>
Example of starting the API with `docker`:
```bash
docker run -p 8080:8080 -ti --rm quay.io/go-skynet/local-ai:latest --models-path /path/to/models --context-size 700 --threads 4
```
You should see:
```
┌───────────────────────────────────────────────────┐
│ Fiber v2.42.0 │
│ http://127.0.0.1:8080 │
│ (bound on host 0.0.0.0 and port 8080) │
│ │
│ Handlers ............. 1 Processes ........... 1 │
│ Prefork ....... Disabled PID ................. 1 │
└───────────────────────────────────────────────────┘
```
</details>
### Build locally
<details>
In order to build the `LocalAI` container image locally you can use `docker`:
```
# build the image
docker build -t LocalAI .
docker run LocalAI
```
Or you can build the binary with `make`:
```
make build
```
- Python implementation:
</details>
```python
import openai
### Build on mac
openai.api_base = "http://localhost:8080/v1"
Building on Mac (M1 or M2) works, but you may need to install some prerequisites using `brew`.
# create a chat completion
chat_completion = openai.ChatCompletion.create(model="gpt-3.5-turbo", messages=[{"role": "user", "content": "Hello world"}])
<details>
# print the completion
print(completion.choices[0].message.content)
The below has been tested by one mac user and found to work. Note that this doesn't use docker to run the server:
```
# install build dependencies
brew install cmake
brew install go
# clone the repo
git clone https://github.com/go-skynet/LocalAI.git
cd LocalAI
# build the binary
make build
# Download gpt4all-j to models/
wget https://gpt4all.io/models/ggml-gpt4all-j.bin -O models/ggml-gpt4all-j
# Use a template from the examples
cp -rf prompt-templates/ggml-gpt4all-j.tmpl models/
# Run LocalAI
./local-ai --models-path ./models/ --debug
# Now API is accessible at localhost:8080
curl http://localhost:8080/v1/models
curl http://localhost:8080/v1/chat/completions -H "Content-Type: application/json" -d '{
"model": "ggml-gpt4all-j",
"messages": [{"role": "user", "content": "How are you?"}],
"temperature": 0.9
}'
```
</details>
### Windows compatibility
It should work, however you need to make sure you give enough resources to the container. See https://github.com/go-skynet/LocalAI/issues/2
### Run LocalAI in Kubernetes
LocalAI can be installed inside Kubernetes with helm.
<details>
1. Add the helm repo
```bash
helm repo add go-skynet https://go-skynet.github.io/helm-charts/
```
1. Create a values files with your settings:
```bash
cat <<EOF > values.yaml
deployment:
image: quay.io/go-skynet/local-ai:latest
env:
threads: 4
contextSize: 1024
modelsPath: "/models"
# Optionally create a PVC, mount the PV to the LocalAI Deployment,
# and download a model to prepopulate the models directory
modelsVolume:
enabled: true
url: "https://gpt4all.io/models/ggml-gpt4all-j.bin"
pvc:
size: 6Gi
accessModes:
- ReadWriteOnce
auth:
# Optional value for HTTP basic access authentication header
basic: "" # 'username:password' base64 encoded
service:
type: ClusterIP
annotations: {}
# If using an AWS load balancer, you'll need to override the default 60s load balancer idle timeout
# service.beta.kubernetes.io/aws-load-balancer-connection-idle-timeout: "1200"
EOF
```
3. Install the helm chart:
```bash
helm repo update
helm install local-ai go-skynet/local-ai -f values.yaml
```
Check out also the [helm chart repository on GitHub](https://github.com/go-skynet/helm-charts).
</details>
## Supported OpenAI API endpoints
You can check out the [OpenAI API reference](https://platform.openai.com/docs/api-reference/chat/create).
Following the list of endpoints/parameters supported.
Note:
- You can also specify the model as part of the OpenAI token.
- If only one model is available, the API will use it for all the requests.
### Chat completions
<details>
For example, to generate a chat completion, you can send a POST request to the `/v1/chat/completions` endpoint with the instruction as the request body:
```
curl http://localhost:8080/v1/chat/completions -H "Content-Type: application/json" -d '{
"model": "ggml-koala-7b-model-q4_0-r2.bin",
"messages": [{"role": "user", "content": "Say this is a test!"}],
"temperature": 0.7
}'
```
## TO DO
Available additional parameters: `top_p`, `top_k`, `max_tokens`
</details>
### Edit completions
<details>
To generate an edit completion you can send a POST request to the `/v1/edits` endpoint with the instruction as the request body:
```
curl http://localhost:8080/v1/edits -H "Content-Type: application/json" -d '{
"model": "ggml-koala-7b-model-q4_0-r2.bin",
"instruction": "rephrase",
"input": "Black cat jumped out of the window",
"temperature": 0.7
}'
```
Available additional parameters: `top_p`, `top_k`, `max_tokens`.
</details>
### Completions
<details>
To generate a completion, you can send a POST request to the `/v1/completions` endpoint with the instruction as per the request body:
```
curl http://localhost:8080/v1/completions -H "Content-Type: application/json" -d '{
"model": "ggml-koala-7b-model-q4_0-r2.bin",
"prompt": "A long time ago in a galaxy far, far away",
"temperature": 0.7
}'
```
Available additional parameters: `top_p`, `top_k`, `max_tokens`
</details>
### List models
<details>
You can list all the models available with:
```
curl http://localhost:8080/v1/models
```
</details>
## Frequently asked questions
Here are answers to some of the most common questions.
### How do I get models?
<details>
Most ggml-based models should work, but newer models may require additions to the API. If a model doesn't work, please feel free to open up issues. However, be cautious about downloading models from the internet and directly onto your machine, as there may be security vulnerabilities in lama.cpp or ggml that could be maliciously exploited. Some models can be found on Hugging Face: https://huggingface.co/models?search=ggml, or models from gpt4all should also work: https://github.com/nomic-ai/gpt4all.
</details>
### What's the difference with Serge, or XXX?
<details>
LocalAI is a multi-model solution that doesn't focus on a specific model type (e.g., llama.cpp or alpaca.cpp), and it handles all of these internally for faster inference, easy to set up locally and deploy to Kubernetes.
</details>
### Can I use it with a Discord bot, or XXX?
<details>
Yes! If the client uses OpenAI and supports setting a different base URL to send requests to, you can use the LocalAI endpoint. This allows to use this with every application that was supposed to work with OpenAI, but without changing the application!
</details>
### Can this leverage GPUs?
<details>
Not currently, as ggml doesn't support GPUs yet: https://github.com/ggerganov/llama.cpp/discussions/915.
</details>
### Where is the webUI?
<details>
We are working on to have a good out of the box experience - however as LocalAI is an API you can already plug it into existing projects that provides are UI interfaces to OpenAI's APIs. There are several already on github, and should be compatible with LocalAI already (as it mimics the OpenAI API)
</details>
### Does it work with AutoGPT?
<details>
AutoGPT currently doesn't allow to set a different API URL, but there is a PR open for it, so this should be possible soon!
</details>
## Projects already using LocalAI to run local models
Feel free to open up a PR to get your project listed!
- [Kairos](https://github.com/kairos-io/kairos)
- [k8sgpt](https://github.com/k8sgpt-ai/k8sgpt#running-local-models)
## Blog posts and other articles
- https://medium.com/@tyler_97636/k8sgpt-localai-unlock-kubernetes-superpowers-for-free-584790de9b65
- https://kairos.io/docs/examples/localai/
## Short-term roadmap
- [x] Mimic OpenAI API (https://github.com/go-skynet/LocalAI/issues/10)
- [ ] Binary releases (https://github.com/go-skynet/LocalAI/issues/6)
- [ ] Upstream our golang bindings to llama.cpp (https://github.com/ggerganov/llama.cpp/issues/351) and [gpt4all](https://github.com/go-skynet/LocalAI/issues/85)
- [x] Multi-model support
- [x] Have a webUI!
- [x] Allow configuration of defaults for models.
- [ ] Enable automatic downloading of models from a curated gallery, with only free-licensed models, directly from the webui.
## Star history
[![LocalAI Star history Chart](https://api.star-history.com/svg?repos=go-skynet/LocalAI&type=Date)](https://star-history.com/#go-skynet/LocalAI&Date)
## License
LocalAI is a community-driven project. It was initially created by [mudler](https://github.com/mudler/) at the [SpectroCloud OSS Office](https://github.com/spectrocloud).
MIT
## Golang bindings used
- [go-skynet/go-llama.cpp](https://github.com/go-skynet/go-llama.cpp)
- [go-skynet/go-gpt4all-j.cpp](https://github.com/go-skynet/go-gpt4all-j.cpp)
- [go-skynet/go-gpt2.cpp](https://github.com/go-skynet/go-gpt2.cpp)
- [donomii/go-rwkv.cpp](https://github.com/donomii/go-rwkv.cpp)
## Acknowledgements
- [llama.cpp](https://github.com/ggerganov/llama.cpp)
- https://github.com/tatsu-lab/stanford_alpaca
- https://github.com/cornelk/llama-go for the initial ideas
- https://github.com/antimatter15/alpaca.cpp for the light model version (this is compatible and tested only with that checkpoint model!)
## Contributors
- [ ] Flask app frontend
- [ ] Keycloak auth
- [ ] speech to text avec openVINO
<a href="https://github.com/go-skynet/LocalAI/graphs/contributors">
<img src="https://contrib.rocks/image?repo=go-skynet/LocalAI" />
</a>

@ -3,33 +3,40 @@ package api
import (
"errors"
config "github.com/go-skynet/LocalAI/api/config"
"github.com/go-skynet/LocalAI/api/localai"
"github.com/go-skynet/LocalAI/api/openai"
"github.com/go-skynet/LocalAI/api/options"
"github.com/go-skynet/LocalAI/internal"
"github.com/go-skynet/LocalAI/pkg/assets"
_ "github.com/go-skynet/LocalAI/docs/swagger"
model "github.com/go-skynet/LocalAI/pkg/model"
"github.com/gofiber/fiber/v2"
"github.com/gofiber/fiber/v2/middleware/cors"
"github.com/gofiber/fiber/v2/middleware/logger"
"github.com/gofiber/fiber/v2/middleware/recover"
swagger "github.com/gofiber/swagger"
"github.com/rs/zerolog"
"github.com/rs/zerolog/log"
)
func App(opts ...options.AppOption) (*fiber.App, error) {
options := options.NewOptions(opts...)
// @title LocalAI API
// @version 2.0
// @description LocalAI is a drop-in replacement for OpenAI to enable local models inferencing with ggml.
// @termsOfService xxx
// @contact.name API Support
// @contact.url xxx
// @contact.email xxx
// @license.name MIT
// @license.url xxx
// @host localhost:8080
// @BasePath /
// @schemes http
func App(configFile string, loader *model.ModelLoader, threads, ctxSize int, f16 bool, debug, disableMessage bool) *fiber.App {
zerolog.SetGlobalLevel(zerolog.InfoLevel)
if options.Debug {
if debug {
zerolog.SetGlobalLevel(zerolog.DebugLevel)
}
// Return errors as JSON responses
app := fiber.New(fiber.Config{
BodyLimit: options.UploadLimitMB * 1024 * 1024, // this is the default limit of 4MB
DisableStartupMessage: options.DisableMessage,
DisableStartupMessage: disableMessage,
// Override default error handler
ErrorHandler: func(ctx *fiber.Ctx, err error) error {
// Status code defaults to 500
@ -43,142 +50,46 @@ func App(opts ...options.AppOption) (*fiber.App, error) {
// Send custom error page
return ctx.Status(code).JSON(
openai.ErrorResponse{
Error: &openai.APIError{Message: err.Error(), Code: code},
ErrorResponse{
Error: &APIError{Message: err.Error(), Code: code},
},
)
},
})
if options.Debug {
app.Use(logger.New(logger.Config{
Format: "[${ip}]:${port} ${status} - ${method} ${path}\n",
}))
}
log.Info().Msgf("Starting LocalAI using %d threads, with models path: %s", options.Threads, options.Loader.ModelPath)
log.Info().Msgf("LocalAI version: %s", internal.PrintableVersion())
cm := config.NewConfigLoader()
if err := cm.LoadConfigs(options.Loader.ModelPath); err != nil {
cm := make(ConfigMerger)
if err := cm.LoadConfigs(loader.ModelPath); err != nil {
log.Error().Msgf("error loading config files: %s", err.Error())
}
if options.ConfigFile != "" {
if err := cm.LoadConfigFile(options.ConfigFile); err != nil {
if configFile != "" {
if err := cm.LoadConfigFile(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)
}
}
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 debug {
for k, v := range cm {
log.Debug().Msgf("Model: %s (config: %+v)", k, v)
}
}
// Default middleware config
app.Use(recover.New())
app.Use(cors.New())
if options.PreloadJSONModels != "" {
if err := localai.ApplyGalleryFromString(options.Loader.ModelPath, options.PreloadJSONModels, cm, options.Galleries); err != nil {
return nil, err
}
}
app.Get("/swagger/*", swagger.HandlerDefault) // default
if options.PreloadModelsFromPath != "" {
if err := localai.ApplyGalleryFromFile(options.Loader.ModelPath, options.PreloadModelsFromPath, cm, options.Galleries); err != nil {
return nil, err
}
}
if options.CORS {
var c func(ctx *fiber.Ctx) error
if options.CORSAllowOrigins == "" {
c = cors.New()
} else {
c = cors.New(cors.Config{AllowOrigins: options.CORSAllowOrigins})
}
app.Use(c)
}
// LocalAI API endpoints
galleryService := localai.NewGalleryService(options.Loader.ModelPath)
galleryService.Start(options.Context, cm)
app.Get("/version", func(c *fiber.Ctx) error {
return c.JSON(struct {
Version string `json:"version"`
}{Version: internal.PrintableVersion()})
})
app.Post("/models/apply", localai.ApplyModelGalleryEndpoint(options.Loader.ModelPath, cm, galleryService.C, options.Galleries))
app.Get("/models/available", localai.ListModelFromGalleryEndpoint(options.Galleries, options.Loader.ModelPath))
app.Get("/models/jobs/:uuid", localai.GetOpStatusEndpoint(galleryService))
// openAI compatible API endpoint
// chat
app.Post("/v1/chat/completions", openai.ChatEndpoint(cm, options))
app.Post("/chat/completions", openai.ChatEndpoint(cm, options))
// edit
app.Post("/v1/edits", openai.EditEndpoint(cm, options))
app.Post("/edits", openai.EditEndpoint(cm, options))
// completion
app.Post("/v1/completions", openai.CompletionEndpoint(cm, options))
app.Post("/completions", openai.CompletionEndpoint(cm, options))
app.Post("/v1/engines/:model/completions", openai.CompletionEndpoint(cm, options))
// embeddings
app.Post("/v1/embeddings", openai.EmbeddingsEndpoint(cm, options))
app.Post("/embeddings", openai.EmbeddingsEndpoint(cm, options))
app.Post("/v1/engines/:model/embeddings", openai.EmbeddingsEndpoint(cm, options))
// audio
app.Post("/v1/audio/transcriptions", openai.TranscriptEndpoint(cm, options))
app.Post("/tts", localai.TTSEndpoint(cm, options))
// images
app.Post("/v1/images/generations", openai.ImageEndpoint(cm, options))
if options.ImageDir != "" {
app.Static("/generated-images", options.ImageDir)
}
if options.AudioDir != "" {
app.Static("/generated-audio", options.AudioDir)
}
ok := func(c *fiber.Ctx) error {
return c.SendStatus(200)
}
app.Post("/v1/chat/completions", chatEndpoint(cm, debug, loader, threads, ctxSize, f16))
app.Post("/chat/completions", chatEndpoint(cm, debug, loader, threads, ctxSize, f16))
// Kubernetes health checks
app.Get("/healthz", ok)
app.Get("/readyz", ok)
app.Post("/v1/edits", editEndpoint(cm, debug, loader, threads, ctxSize, f16))
app.Post("/edits", editEndpoint(cm, debug, loader, threads, ctxSize, f16))
// models
app.Get("/v1/models", openai.ListModelsEndpoint(options.Loader, cm))
app.Get("/models", openai.ListModelsEndpoint(options.Loader, cm))
app.Post("/v1/completions", completionEndpoint(cm, debug, loader, threads, ctxSize, f16))
app.Post("/completions", completionEndpoint(cm, debug, loader, threads, ctxSize, f16))
// turn off any process that was started by GRPC if the context is canceled
go func() {
<-options.Context.Done()
log.Debug().Msgf("Context canceled, shutting down")
options.Loader.StopGRPC()
}()
app.Get("/v1/models", listModels(loader, cm))
app.Get("/models", listModels(loader, cm))
return app, nil
return app
}

@ -1,519 +1,29 @@
package api_test
import (
"bytes"
"context"
"embed"
"encoding/json"
"errors"
"fmt"
"io"
"io/ioutil"
"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"
"gopkg.in/yaml.v3"
openaigo "github.com/otiai10/openaigo"
"github.com/sashabaranov/go-openai"
"github.com/sashabaranov/go-openai/jsonschema"
)
type modelApplyRequest struct {
ID string `json:"id"`
URL string `json:"url"`
Name string `json:"name"`
Overrides map[string]string `json:"overrides"`
}
func getModelStatus(url string) (response map[string]interface{}) {
// Create the HTTP request
resp, err := http.Get(url)
if err != nil {
fmt.Println("Error creating request:", err)
return
}
defer resp.Body.Close()
body, err := ioutil.ReadAll(resp.Body)
if err != nil {
fmt.Println("Error reading response body:", err)
return
}
// Unmarshal the response into a map[string]interface{}
err = json.Unmarshal(body, &response)
if err != nil {
fmt.Println("Error unmarshaling JSON response:", err)
return
}
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"
// Create the request payload
payload, err := json.Marshal(request)
if err != nil {
fmt.Println("Error marshaling JSON:", err)
return
}
// Create the HTTP request
req, err := http.NewRequest("POST", url, bytes.NewBuffer(payload))
if err != nil {
fmt.Println("Error creating request:", err)
return
}
req.Header.Set("Content-Type", "application/json")
// Make the request
client := &http.Client{}
resp, err := client.Do(req)
if err != nil {
fmt.Println("Error making request:", err)
return
}
defer resp.Body.Close()
body, err := ioutil.ReadAll(resp.Body)
if err != nil {
fmt.Println("Error reading response body:", err)
return
}
// Unmarshal the response into a map[string]interface{}
err = json.Unmarshal(body, &response)
if err != nil {
fmt.Println("Error unmarshaling JSON response:", err)
return
}
return
}
//go:embed backend-assets/*
var backendAssets embed.FS
var _ = Describe("API test", func() {
var app *fiber.App
var modelLoader *model.ModelLoader
var client *openai.Client
var client2 *openaigo.Client
var c context.Context
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
tmpdir, err = os.MkdirTemp("", "")
Expect(err).ToNot(HaveOccurred())
modelLoader = model.NewModelLoader(tmpdir)
c, cancel = context.WithCancel(context.Background())
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 = ioutil.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("")
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)
})
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{
"backend": "llama",
},
})
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))
dat, err := os.ReadFile(filepath.Join(tmpdir, "bert.yaml"))
Expect(err).ToNot(HaveOccurred())
content := map[string]interface{}{}
err = yaml.Unmarshal(dat, &content)
Expect(err).ToNot(HaveOccurred())
Expect(content["backend"]).To(Equal("llama"))
})
It("apply models without overrides", 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{},
})
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))
dat, err := os.ReadFile(filepath.Join(tmpdir, "bert.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"))
})
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]string{"backend": "llama-grammar"},
})
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"), 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",
Overrides: map[string]string{},
})
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",
})
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))
})
})
Context("API query", func() {
BeforeEach(func() {
modelLoader = model.NewModelLoader(os.Getenv("MODELS_PATH"))
c, cancel = context.WithCancel(context.Background())
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())
app = App("", modelLoader, 1, 512, false, true, true)
go app.Listen("127.0.0.1:9090")
defaultConfig := openai.DefaultConfig("")
@ -530,13 +40,13 @@ var _ = Describe("API test", func() {
}, "2m").ShouldNot(HaveOccurred())
})
AfterEach(func() {
cancel()
app.Shutdown()
})
It("returns the models list", func() {
models, err := client.ListModels(context.TODO())
Expect(err).ToNot(HaveOccurred())
Expect(len(models.Models)).To(Equal(11))
Expect(len(models.Models)).To(Equal(3))
Expect(models.Models[0].ID).To(Equal("testmodel"))
})
It("can generate completions", func() {
resp, err := client.CreateCompletion(context.TODO(), openai.CompletionRequest{Model: "testmodel", Prompt: "abcdedfghikl"})
@ -567,162 +77,17 @@ 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(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" {
Skip("test supported only on linux")
}
resp, err := client.CreateTranscription(
context.Background(),
openai.AudioRequest{
Model: openai.Whisper1,
FilePath: filepath.Join(os.Getenv("TEST_DIR"), "audio.wav"),
},
)
Expect(err).ToNot(HaveOccurred())
Expect(resp.Text).To(ContainSubstring("This is the Micro Machine Man presenting"))
})
It("calculate embeddings", func() {
if runtime.GOOS != "linux" {
Skip("test supported only on linux")
}
resp, err := client.CreateEmbeddings(
context.Background(),
openai.EmbeddingRequest{
Model: openai.AdaEmbeddingV2,
Input: []string{"sun", "cat"},
},
)
Expect(err).ToNot(HaveOccurred())
Expect(len(resp.Data[0].Embedding)).To(BeNumerically("==", 384))
Expect(len(resp.Data[1].Embedding)).To(BeNumerically("==", 384))
sunEmbedding := resp.Data[0].Embedding
resp2, err := client.CreateEmbeddings(
context.Background(),
openai.EmbeddingRequest{
Model: openai.AdaEmbeddingV2,
Input: []string{"sun"},
},
)
Expect(err).ToNot(HaveOccurred())
Expect(resp2.Data[0].Embedding).To(Equal(sunEmbedding))
Expect(err.Error()).To(ContainSubstring("error, status code: 500, message: could not load model - all backends returned error: 5 errors occurred:"))
})
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 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(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)))
})
})
})
Context("Config file", func() {
BeforeEach(func() {
modelLoader = model.NewModelLoader(os.Getenv("MODELS_PATH"))
c, cancel = context.WithCancel(context.Background())
var err error
app, err = App(
append(commonOpts,
options.WithContext(c),
options.WithModelLoader(modelLoader),
options.WithConfigFile(os.Getenv("CONFIG_FILE")))...,
)
Expect(err).ToNot(HaveOccurred())
app = App(os.Getenv("CONFIG_FILE"), modelLoader, 1, 512, false, true, true)
go app.Listen("127.0.0.1:9090")
defaultConfig := openai.DefaultConfig("")
@ -737,13 +102,14 @@ var _ = Describe("API test", func() {
}, "2m").ShouldNot(HaveOccurred())
})
AfterEach(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(13))
Expect(len(models.Models)).To(Equal(5))
Expect(models.Models[0].ID).To(Equal("testmodel"))
})
It("can generate chat completions from config file", func() {
resp, err := client.CreateChatCompletion(context.TODO(), openai.ChatCompletionRequest{Model: "list1", Messages: []openai.ChatCompletionMessage{openai.ChatCompletionMessage{Role: "user", Content: "abcdedfghikl"}}})
@ -768,6 +134,5 @@ var _ = Describe("API test", func() {
Expect(len(resp.Choices)).To(Equal(1))
Expect(resp.Choices[0].Text).ToNot(BeEmpty())
})
})
})

@ -1,109 +0,0 @@
package backend
import (
"fmt"
"sync"
config "github.com/go-skynet/LocalAI/api/config"
"github.com/go-skynet/LocalAI/api/options"
"github.com/go-skynet/LocalAI/pkg/grpc"
model "github.com/go-skynet/LocalAI/pkg/model"
)
func ModelEmbedding(s string, tokens []int, loader *model.ModelLoader, c config.Config, o *options.Option) (func() ([]float32, error), error) {
if !c.Embeddings {
return nil, fmt.Errorf("endpoint disabled for this model by API configuration")
}
modelFile := c.Model
grpcOpts := gRPCModelOpts(c)
var inferenceModel interface{}
var err error
opts := []model.Option{
model.WithLoadGRPCLLMModelOpts(grpcOpts),
model.WithThreads(uint32(c.Threads)),
model.WithAssetDir(o.AssetsDestination),
model.WithModelFile(modelFile),
model.WithContext(o.Context),
}
for k, v := range o.ExternalGRPCBackends {
opts = append(opts, model.WithExternalBackend(k, v))
}
if c.Backend == "" {
inferenceModel, err = loader.GreedyLoader(opts...)
} else {
opts = append(opts, model.WithBackendString(c.Backend))
inferenceModel, err = loader.BackendLoader(opts...)
}
if err != nil {
return nil, err
}
var fn func() ([]float32, error)
switch model := inferenceModel.(type) {
case *grpc.Client:
fn = func() ([]float32, error) {
predictOptions := gRPCPredictOpts(c, loader.ModelPath)
if len(tokens) > 0 {
embeds := []int32{}
for _, t := range tokens {
embeds = append(embeds, int32(t))
}
predictOptions.EmbeddingTokens = embeds
res, err := model.Embeddings(o.Context, predictOptions)
if err != nil {
return nil, err
}
return res.Embeddings, nil
}
predictOptions.Embeddings = s
res, err := model.Embeddings(o.Context, predictOptions)
if err != nil {
return nil, err
}
return res.Embeddings, nil
}
default:
fn = func() ([]float32, error) {
return nil, fmt.Errorf("embeddings not supported by the backend")
}
}
return func() ([]float32, error) {
// This is still needed, see: https://github.com/ggerganov/llama.cpp/discussions/784
mutexMap.Lock()
l, ok := mutexes[modelFile]
if !ok {
m := &sync.Mutex{}
mutexes[modelFile] = m
l = m
}
mutexMap.Unlock()
l.Lock()
defer l.Unlock()
embeds, err := fn()
if err != nil {
return embeds, err
}
// Remove trailing 0s
for i := len(embeds) - 1; i >= 0; i-- {
if embeds[i] == 0.0 {
embeds = embeds[:i]
} else {
break
}
}
return embeds, nil
}, nil
}

@ -1,68 +0,0 @@
package backend
import (
"fmt"
"sync"
config "github.com/go-skynet/LocalAI/api/config"
"github.com/go-skynet/LocalAI/api/options"
"github.com/go-skynet/LocalAI/pkg/grpc/proto"
model "github.com/go-skynet/LocalAI/pkg/model"
)
func ImageGeneration(height, width, mode, step, seed int, positive_prompt, negative_prompt, dst string, loader *model.ModelLoader, c config.Config, o *options.Option) (func() error, error) {
if c.Backend != model.StableDiffusionBackend {
return nil, fmt.Errorf("endpoint only working with stablediffusion models")
}
opts := []model.Option{
model.WithBackendString(c.Backend),
model.WithAssetDir(o.AssetsDestination),
model.WithThreads(uint32(c.Threads)),
model.WithContext(o.Context),
model.WithModelFile(c.ImageGenerationAssets),
}
for k, v := range o.ExternalGRPCBackends {
opts = append(opts, model.WithExternalBackend(k, v))
}
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),
PositivePrompt: positive_prompt,
NegativePrompt: negative_prompt,
Dst: dst,
})
return err
}
return func() error {
// This is still needed, see: https://github.com/ggerganov/llama.cpp/discussions/784
mutexMap.Lock()
l, ok := mutexes[c.Backend]
if !ok {
m := &sync.Mutex{}
mutexes[c.Backend] = m
l = m
}
mutexMap.Unlock()
l.Lock()
defer l.Unlock()
return fn()
}, nil
}

@ -1,124 +0,0 @@
package backend
import (
"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"
)
func ModelInference(s string, loader *model.ModelLoader, c config.Config, o *options.Option, tokenCallback func(string) bool) (func() (string, error), error) {
modelFile := c.Model
grpcOpts := gRPCModelOpts(c)
var inferenceModel *grpc.Client
var err error
opts := []model.Option{
model.WithLoadGRPCLLMModelOpts(grpcOpts),
model.WithThreads(uint32(c.Threads)), // some models uses this to allocate threads during startup
model.WithAssetDir(o.AssetsDestination),
model.WithModelFile(modelFile),
model.WithContext(o.Context),
}
for k, v := range o.ExternalGRPCBackends {
opts = append(opts, model.WithExternalBackend(k, v))
}
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() (string, error) {
opts := gRPCPredictOpts(c, loader.ModelPath)
opts.Prompt = s
if tokenCallback != nil {
ss := ""
err := inferenceModel.PredictStream(o.Context, opts, func(s string) {
tokenCallback(s)
ss += s
})
return ss, err
} else {
reply, err := inferenceModel.Predict(o.Context, opts)
if err != nil {
return "", err
}
return reply.Message, err
}
}
return func() (string, error) {
// This is still needed, see: https://github.com/ggerganov/llama.cpp/discussions/784
mutexMap.Lock()
l, ok := mutexes[modelFile]
if !ok {
m := &sync.Mutex{}
mutexes[modelFile] = m
l = m
}
mutexMap.Unlock()
l.Lock()
defer l.Unlock()
return fn()
}, nil
}
var cutstrings map[string]*regexp.Regexp = make(map[string]*regexp.Regexp)
var mu sync.Mutex = sync.Mutex{}
func Finetune(config config.Config, input, prediction string) string {
if config.Echo {
prediction = input + prediction
}
for _, c := range config.Cutstrings {
mu.Lock()
reg, ok := cutstrings[c]
if !ok {
cutstrings[c] = regexp.MustCompile(c)
reg = cutstrings[c]
}
mu.Unlock()
prediction = reg.ReplaceAllString(prediction, "")
}
for _, c := range config.TrimSpace {
prediction = strings.TrimSpace(strings.TrimPrefix(prediction, c))
}
return prediction
}

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

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

@ -1,42 +0,0 @@
package backend
import (
"context"
"fmt"
config "github.com/go-skynet/LocalAI/api/config"
"github.com/go-skynet/LocalAI/api/options"
"github.com/go-skynet/LocalAI/pkg/grpc/proto"
"github.com/go-skynet/LocalAI/pkg/grpc/whisper/api"
model "github.com/go-skynet/LocalAI/pkg/model"
)
func ModelTranscription(audio, language string, loader *model.ModelLoader, c config.Config, o *options.Option) (*api.Result, error) {
opts := []model.Option{
model.WithBackendString(model.WhisperBackend),
model.WithModelFile(c.Model),
model.WithContext(o.Context),
model.WithThreads(uint32(c.Threads)),
model.WithAssetDir(o.AssetsDestination),
}
for k, v := range o.ExternalGRPCBackends {
opts = append(opts, model.WithExternalBackend(k, v))
}
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),
})
}

@ -1,72 +0,0 @@
package backend
import (
"context"
"fmt"
"os"
"path/filepath"
"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(text, modelFile string, loader *model.ModelLoader, o *options.Option) (string, *proto.Result, error) {
opts := []model.Option{
model.WithBackendString(model.PiperBackend),
model.WithModelFile(modelFile),
model.WithContext(o.Context),
model.WithAssetDir(o.AssetsDestination),
}
for k, v := range o.ExternalGRPCBackends {
opts = append(opts, model.WithExternalBackend(k, v))
}
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)
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
}

@ -0,0 +1,102 @@
package api
import (
"fmt"
"io/ioutil"
"os"
"path/filepath"
"strings"
"gopkg.in/yaml.v3"
)
type Config struct {
OpenAIRequest `yaml:"parameters"`
Name string `yaml:"name"`
StopWords []string `yaml:"stopwords"`
Cutstrings []string `yaml:"cutstrings"`
TrimSpace []string `yaml:"trimspace"`
ContextSize int `yaml:"context_size"`
F16 bool `yaml:"f16"`
Threads int `yaml:"threads"`
Debug bool `yaml:"debug"`
Roles map[string]string `yaml:"roles"`
Backend string `yaml:"backend"`
TemplateConfig TemplateConfig `yaml:"template"`
}
type TemplateConfig struct {
Completion string `yaml:"completion"`
Chat string `yaml:"chat"`
Edit string `yaml:"edit"`
}
type ConfigMerger map[string]Config
func ReadConfigFile(file string) ([]*Config, error) {
c := &[]*Config{}
f, err := os.ReadFile(file)
if err != nil {
return nil, fmt.Errorf("cannot read config file: %w", err)
}
if err := yaml.Unmarshal(f, c); err != nil {
return nil, fmt.Errorf("cannot unmarshal config file: %w", err)
}
return *c, nil
}
func ReadConfig(file string) (*Config, error) {
c := &Config{}
f, err := os.ReadFile(file)
if err != nil {
return nil, fmt.Errorf("cannot read config file: %w", err)
}
if err := yaml.Unmarshal(f, c); err != nil {
return nil, fmt.Errorf("cannot unmarshal config file: %w", err)
}
return c, nil
}
func (cm ConfigMerger) LoadConfigFile(file string) error {
c, err := ReadConfigFile(file)
if err != nil {
return fmt.Errorf("cannot load config file: %w", err)
}
for _, cc := range c {
cm[cc.Name] = *cc
}
return nil
}
func (cm ConfigMerger) LoadConfig(file string) error {
c, err := ReadConfig(file)
if err != nil {
return fmt.Errorf("cannot read config file: %w", err)
}
cm[c.Name] = *c
return nil
}
func (cm ConfigMerger) LoadConfigs(path string) error {
files, err := ioutil.ReadDir(path)
if err != nil {
return err
}
for _, file := range files {
// Skip templates, YAML and .keep files
if !strings.Contains(file.Name(), ".yaml") {
continue
}
c, err := ReadConfig(filepath.Join(path, file.Name()))
if err == nil {
cm[c.Name] = *c
}
}
return nil
}

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

@ -1,56 +0,0 @@
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"))
})
})
})

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

@ -1,224 +0,0 @@
package localai
import (
"context"
"fmt"
"os"
"strings"
"sync"
json "github.com/json-iterator/go"
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
ID string `json:"id"`
}
func ApplyGalleryFromFile(modelPath, s string, cm *config.ConfigLoader, galleries []gallery.Gallery) error {
dat, err := os.ReadFile(s)
if err != nil {
return err
}
return ApplyGalleryFromString(modelPath, string(dat), cm, galleries)
}
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
}
for _, r := range requests {
utils.ResetDownloadTimers()
if r.ID == "" {
err = prepareModel(modelPath, r.GalleryModel, cm, utils.DisplayDownloadFunction)
} else {
err = gallery.InstallModelFromGallery(galleries, r.ID, modelPath, r.GalleryModel, utils.DisplayDownloadFunction)
}
}
return err
}
/// 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)
}
}

@ -1,31 +0,0 @@
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"`
}
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.Input, input.Model, o.Loader, o)
if err != nil {
return err
}
return c.Download(filePath)
}
}

@ -0,0 +1,518 @@
package api
import (
"bufio"
"bytes"
"encoding/json"
"fmt"
"os"
"path/filepath"
"strings"
model "github.com/go-skynet/LocalAI/pkg/model"
"github.com/gofiber/fiber/v2"
"github.com/rs/zerolog/log"
"github.com/valyala/fasthttp"
)
// APIError provides error information returned by the OpenAI API.
// @Description Error returned by the API
type APIError struct {
Code any `json:"code,omitempty"`
Message string `json:"message"`
Param *string `json:"param,omitempty"`
Type string `json:"type"`
}
type ErrorResponse struct {
Error *APIError `json:"error,omitempty"`
}
type OpenAIUsage struct {
PromptTokens int `json:"prompt_tokens"`
CompletionTokens int `json:"completion_tokens"`
TotalTokens int `json:"total_tokens"`
}
type OpenAIResponse struct {
Created int `json:"created,omitempty"`
Object string `json:"object,omitempty"`
ID string `json:"id,omitempty"`
Model string `json:"model,omitempty"`
Choices []Choice `json:"choices,omitempty"`
Usage OpenAIUsage `json:"usage"`
}
type Choice struct {
Index int `json:"index,omitempty"`
FinishReason string `json:"finish_reason,omitempty"`
Message *Message `json:"message,omitempty"`
Delta *Message `json:"delta,omitempty"`
Text string `json:"text,omitempty"`
}
// Chat Message
// @Description Message with a content and a role
type Message struct {
Role string `json:"role,omitempty" yaml:"role"`
Content string `json:"content,omitempty" yaml:"content"`
}
type OpenAIModel struct {
ID string `json:"id"`
Object string `json:"object"`
}
type OpenAIRequest struct {
Model string `json:"model" yaml:"model"`
// Prompt is read only by completion API calls
Prompt interface{} `json:"prompt" yaml:"prompt"`
// Edit endpoint
Instruction string `json:"instruction" yaml:"instruction"`
Input string `json:"input" yaml:"input"`
Stop interface{} `json:"stop" yaml:"stop"`
// Messages is read only by chat/completion API calls
Messages []Message `json:"messages" yaml:"messages"`
Stream bool `json:"stream"`
Echo bool `json:"echo"`
// Common options between all the API calls
TopP float64 `json:"top_p" yaml:"top_p"`
TopK int `json:"top_k" yaml:"top_k"`
Temperature float64 `json:"temperature" yaml:"temperature"`
Maxtokens int `json:"max_tokens" yaml:"max_tokens"`
N int `json:"n"`
// Custom parameters - not present in the OpenAI API
Batch int `json:"batch" yaml:"batch"`
F16 bool `json:"f16" yaml:"f16"`
IgnoreEOS bool `json:"ignore_eos" yaml:"ignore_eos"`
RepeatPenalty float64 `json:"repeat_penalty" yaml:"repeat_penalty"`
Keep int `json:"n_keep" yaml:"n_keep"`
Seed int `json:"seed" yaml:"seed"`
}
func defaultRequest(modelFile string) OpenAIRequest {
return OpenAIRequest{
TopP: 0.7,
TopK: 80,
Maxtokens: 512,
Temperature: 0.9,
Model: modelFile,
}
}
func updateConfig(config *Config, input *OpenAIRequest) {
if input.Echo {
config.Echo = input.Echo
}
if input.TopK != 0 {
config.TopK = input.TopK
}
if input.TopP != 0 {
config.TopP = input.TopP
}
if input.Temperature != 0 {
config.Temperature = input.Temperature
}
if input.Maxtokens != 0 {
config.Maxtokens = input.Maxtokens
}
switch stop := input.Stop.(type) {
case string:
if stop != "" {
config.StopWords = append(config.StopWords, stop)
}
case []interface{}:
for _, pp := range stop {
if s, ok := pp.(string); ok {
config.StopWords = append(config.StopWords, s)
}
}
}
if input.RepeatPenalty != 0 {
config.RepeatPenalty = input.RepeatPenalty
}
if input.Keep != 0 {
config.Keep = input.Keep
}
if input.Batch != 0 {
config.Batch = input.Batch
}
if input.F16 {
config.F16 = input.F16
}
if input.IgnoreEOS {
config.IgnoreEOS = input.IgnoreEOS
}
if input.Seed != 0 {
config.Seed = input.Seed
}
}
func readConfig(cm ConfigMerger, c *fiber.Ctx, loader *model.ModelLoader, debug bool, threads, ctx int, f16 bool) (*Config, *OpenAIRequest, error) {
input := new(OpenAIRequest)
// Get input data from the request body
if err := c.BodyParser(input); err != nil {
return nil, nil, err
}
modelFile := input.Model
received, _ := json.Marshal(input)
log.Debug().Msgf("Request received: %s", string(received))
// Set model from bearer token, if available
bearer := strings.TrimLeft(c.Get("authorization"), "Bearer ")
bearerExists := bearer != "" && loader.ExistsInModelPath(bearer)
// If no model was specified, take the first available
if modelFile == "" && !bearerExists {
models, _ := loader.ListModels()
if len(models) > 0 {
modelFile = models[0]
log.Debug().Msgf("No model specified, using: %s", modelFile)
} else {
log.Debug().Msgf("No model specified, returning error")
return nil, nil, fmt.Errorf("no model specified")
}
}
// If a model is found in bearer token takes precedence
if bearerExists {
log.Debug().Msgf("Using model from bearer token: %s", bearer)
modelFile = bearer
}
// Load a config file if present after the model name
modelConfig := filepath.Join(loader.ModelPath, modelFile+".yaml")
if _, err := os.Stat(modelConfig); err == nil {
if err := cm.LoadConfig(modelConfig); err != nil {
return nil, nil, fmt.Errorf("failed loading model config (%s) %s", modelConfig, err.Error())
}
}
var config *Config
cfg, exists := cm[modelFile]
if !exists {
config = &Config{
OpenAIRequest: defaultRequest(modelFile),
}
} else {
config = &cfg
}
// Set the parameters for the language model prediction
updateConfig(config, input)
if threads != 0 {
config.Threads = threads
}
if ctx != 0 {
config.ContextSize = ctx
}
if f16 {
config.F16 = true
}
if debug {
config.Debug = true
}
return config, input, nil
}
// OpenAI Completion API endpoint https://platform.openai.com/docs/api-reference/completions
// chatEndpoint godoc
// @Summary Chat completions.
// @Description Allows to generate completions for a given prompt and model.
// @Tags root
// @Accept json
// @Produce json
// @Param prompt body string true "The prompt to generate completions for."
// @Param model body string true "The ID of the model to use."
// @Param max_tokens body integer false "The maximum number of tokens to generate in the completion."
// @Param n body integer false "How many completions to generate for each prompt."
// @Param temperature body float64 false "The sampling temperature to use when generating completions."
// @Param stop body string false "Sequence where the API will stop generating further tokens"
// @Success 200 {object} map[string]interface{}
// @Router /v1/completions [post]
func completionEndpoint(cm ConfigMerger, debug bool, loader *model.ModelLoader, threads, ctx int, f16 bool) func(c *fiber.Ctx) error {
return func(c *fiber.Ctx) error {
config, input, err := readConfig(cm, c, loader, debug, threads, ctx, f16)
if err != nil {
return fmt.Errorf("failed reading parameters from request:%w", err)
}
log.Debug().Msgf("Parameter Config: %+v", config)
predInput := []string{}
switch p := input.Prompt.(type) {
case string:
predInput = append(predInput, p)
case []interface{}:
for _, pp := range p {
if s, ok := pp.(string); ok {
predInput = append(predInput, s)
}
}
}
templateFile := config.Model
if config.TemplateConfig.Completion != "" {
templateFile = config.TemplateConfig.Completion
}
var result []Choice
for _, i := range predInput {
// A model can have a "file.bin.tmpl" file associated with a prompt template prefix
templatedInput, err := loader.TemplatePrefix(templateFile, struct {
Input string
}{Input: i})
if err == nil {
i = templatedInput
log.Debug().Msgf("Template found, input modified to: %s", i)
}
r, err := ComputeChoices(i, input, config, loader, func(s string, c *[]Choice) {
*c = append(*c, Choice{Text: s})
}, nil)
if err != nil {
return err
}
result = append(result, r...)
}
resp := &OpenAIResponse{
Model: input.Model, // we have to return what the user sent here, due to OpenAI spec.
Choices: result,
Object: "text_completion",
}
jsonResult, _ := json.Marshal(resp)
log.Debug().Msgf("Response: %s", jsonResult)
// Return the prediction in the response body
return c.JSON(resp)
}
}
// OpenAI CHAT API endpoint for generating model-based text completions
// chatEndpoint mimics the /chat/completions endpoint with local models
// @Summary Generate Model-based Text Completions
// @Description Generates text completions based on the provided prompt and previous messages, using a pre-trained language model.
// @Tags Chat
// @Accept json
// @Produce json
// @Param model body string true "The name of the pre-trained language model to use for generating text completions."
// @Param messages body []Message true "The list of previous messages exchanged with the language model, including the user's messages and the model's responses."
// @Param temperature body number false "The sampling temperature to use when generating text completions. Must be between 0 and 1. Higher values result in more diverse completions, while lower values result in more conservative completions." default(0.5)
// @Success 200 {object} OpenAIResponse
// @Failure 400 {object} APIError
// @Failure 401 {object} APIError
// @Failure 500 {object} APIError
// @Router /v1/chat/completions [post]
func chatEndpoint(cm ConfigMerger, debug bool, loader *model.ModelLoader, threads, ctx int, f16 bool) func(c *fiber.Ctx) error {
return func(c *fiber.Ctx) error {
config, input, err := readConfig(cm, c, loader, debug, threads, ctx, f16)
if err != nil {
return fmt.Errorf("failed reading parameters from request:%w", err)
}
log.Debug().Msgf("Parameter Config: %+v", config)
var predInput string
mess := []string{}
for _, i := range input.Messages {
r := config.Roles[i.Role]
if r == "" {
r = i.Role
}
content := fmt.Sprint(r, " ", i.Content)
mess = append(mess, content)
}
predInput = strings.Join(mess, "\n")
if input.Stream {
log.Debug().Msgf("Stream request received")
c.Context().SetContentType("text/event-stream")
//c.Response().Header.SetContentType(fiber.MIMETextHTMLCharsetUTF8)
// c.Set("Content-Type", "text/event-stream")
c.Set("Cache-Control", "no-cache")
c.Set("Connection", "keep-alive")
c.Set("Transfer-Encoding", "chunked")
}
templateFile := config.Model
if config.TemplateConfig.Chat != "" {
templateFile = config.TemplateConfig.Chat
}
// A model can have a "file.bin.tmpl" file associated with a prompt template prefix
templatedInput, err := loader.TemplatePrefix(templateFile, struct {
Input string
}{Input: predInput})
if err == nil {
predInput = templatedInput
log.Debug().Msgf("Template found, input modified to: %s", predInput)
}
if input.Stream {
responses := make(chan OpenAIResponse)
go func() {
ComputeChoices(predInput, input, config, loader, func(s string, c *[]Choice) {}, func(s string) bool {
resp := OpenAIResponse{
Model: input.Model, // we have to return what the user sent here, due to OpenAI spec.
Choices: []Choice{{Delta: &Message{Role: "assistant", Content: s}}},
Object: "chat.completion.chunk",
}
responses <- resp
return true
})
close(responses)
}()
c.Context().SetBodyStreamWriter(fasthttp.StreamWriter(func(w *bufio.Writer) {
for ev := range responses {
var buf bytes.Buffer
enc := json.NewEncoder(&buf)
enc.Encode(ev)
fmt.Fprintf(w, "event: data\n\n")
fmt.Fprintf(w, "data: %v\n\n", buf.String())
log.Debug().Msgf("Sending chunk: %s", buf.String())
w.Flush()
}
w.WriteString("event: data\n\n")
resp := &OpenAIResponse{
Model: input.Model, // we have to return what the user sent here, due to OpenAI spec.
Choices: []Choice{{FinishReason: "stop"}},
}
respData, _ := json.Marshal(resp)
w.WriteString(fmt.Sprintf("data: %s\n\n", respData))
w.Flush()
}))
return nil
}
result, err := ComputeChoices(predInput, input, config, loader, func(s string, c *[]Choice) {
*c = append(*c, Choice{Message: &Message{Role: "assistant", Content: s}})
}, nil)
if err != nil {
return err
}
resp := &OpenAIResponse{
Model: input.Model, // we have to return what the user sent here, due to OpenAI spec.
Choices: result,
Object: "chat.completion",
}
// Return the prediction in the response body
return c.JSON(resp)
}
}
func editEndpoint(cm ConfigMerger, debug bool, loader *model.ModelLoader, threads, ctx int, f16 bool) func(c *fiber.Ctx) error {
return func(c *fiber.Ctx) error {
config, input, err := readConfig(cm, c, loader, debug, threads, ctx, f16)
if err != nil {
return fmt.Errorf("failed reading parameters from request:%w", err)
}
log.Debug().Msgf("Parameter Config: %+v", config)
predInput := input.Input
templateFile := config.Model
if config.TemplateConfig.Edit != "" {
templateFile = config.TemplateConfig.Edit
}
// A model can have a "file.bin.tmpl" file associated with a prompt template prefix
templatedInput, err := loader.TemplatePrefix(templateFile, struct {
Input string
Instruction string
}{Input: predInput, Instruction: input.Instruction})
if err == nil {
predInput = templatedInput
log.Debug().Msgf("Template found, input modified to: %s", predInput)
}
result, err := ComputeChoices(predInput, input, config, loader, func(s string, c *[]Choice) {
*c = append(*c, Choice{Text: s})
}, nil)
if err != nil {
return err
}
resp := &OpenAIResponse{
Model: input.Model, // we have to return what the user sent here, due to OpenAI spec.
Choices: result,
Object: "edit",
}
jsonResult, _ := json.Marshal(resp)
log.Debug().Msgf("Response: %s", jsonResult)
// Return the prediction in the response body
return c.JSON(resp)
}
}
func listModels(loader *model.ModelLoader, cm ConfigMerger) func(ctx *fiber.Ctx) error {
return func(c *fiber.Ctx) error {
models, err := loader.ListModels()
if err != nil {
return err
}
var mm map[string]interface{} = map[string]interface{}{}
dataModels := []OpenAIModel{}
for _, m := range models {
mm[m] = nil
dataModels = append(dataModels, OpenAIModel{ID: m, Object: "model"})
}
for k := range cm {
if _, exists := mm[k]; !exists {
dataModels = append(dataModels, OpenAIModel{ID: k, Object: "model"})
}
}
return c.JSON(struct {
Object string `json:"object"`
Data []OpenAIModel `json:"data"`
}{
Object: "list",
Data: dataModels,
})
}
}

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

@ -1,322 +0,0 @@
package openai
import (
"bufio"
"bytes"
"encoding/json"
"fmt"
"strings"
"github.com/go-skynet/LocalAI/api/backend"
config "github.com/go-skynet/LocalAI/api/config"
"github.com/go-skynet/LocalAI/api/options"
"github.com/go-skynet/LocalAI/pkg/grammar"
model "github.com/go-skynet/LocalAI/pkg/model"
"github.com/gofiber/fiber/v2"
"github.com/rs/zerolog/log"
"github.com/valyala/fasthttp"
)
func ChatEndpoint(cm *config.ConfigLoader, o *options.Option) func(c *fiber.Ctx) error {
emptyMessage := ""
process := func(s string, req *OpenAIRequest, config *config.Config, loader *model.ModelLoader, responses chan OpenAIResponse) {
initialMessage := OpenAIResponse{
Model: req.Model, // we have to return what the user sent here, due to OpenAI spec.
Choices: []Choice{{Delta: &Message{Role: "assistant", Content: &emptyMessage}}},
Object: "chat.completion.chunk",
}
responses <- initialMessage
ComputeChoices(s, req.N, config, o, loader, func(s string, c *[]Choice) {}, func(s string) bool {
resp := OpenAIResponse{
Model: req.Model, // we have to return what the user sent here, due to OpenAI spec.
Choices: []Choice{{Delta: &Message{Content: &s}, Index: 0}},
Object: "chat.completion.chunk",
}
responses <- resp
return true
})
close(responses)
}
return func(c *fiber.Ctx) error {
processFunctions := false
funcs := grammar.Functions{}
model, input, err := readInput(c, o.Loader, true)
if err != nil {
return fmt.Errorf("failed reading parameters from request:%w", err)
}
config, input, err := readConfig(model, input, cm, o.Loader, o.Debug, o.Threads, o.ContextSize, o.F16)
if err != nil {
return fmt.Errorf("failed reading parameters from request:%w", err)
}
log.Debug().Msgf("Configuration read: %+v", config)
// Allow the user to set custom actions via config file
// to be "embedded" in each model
noActionName := "answer"
noActionDescription := "use this action to answer without performing any action"
if config.FunctionsConfig.NoActionFunctionName != "" {
noActionName = config.FunctionsConfig.NoActionFunctionName
}
if config.FunctionsConfig.NoActionDescriptionName != "" {
noActionDescription = config.FunctionsConfig.NoActionDescriptionName
}
// process functions if we have any defined or if we have a function call string
if len(input.Functions) > 0 && config.ShouldUseFunctions() {
log.Debug().Msgf("Response needs to process functions")
processFunctions = true
noActionGrammar := grammar.Function{
Name: noActionName,
Description: noActionDescription,
Parameters: map[string]interface{}{
"properties": map[string]interface{}{
"message": map[string]interface{}{
"type": "string",
"description": "The message to reply the user with",
}},
},
}
// Append the no action function
funcs = append(funcs, input.Functions...)
if !config.FunctionsConfig.DisableNoAction {
funcs = append(funcs, noActionGrammar)
}
// Force picking one of the functions by the request
if config.FunctionToCall() != "" {
funcs = funcs.Select(config.FunctionToCall())
}
// Update input grammar
jsStruct := funcs.ToJSONStructure()
config.Grammar = jsStruct.Grammar("")
} else if input.JSONFunctionGrammarObject != nil {
config.Grammar = input.JSONFunctionGrammarObject.Grammar("")
}
// functions are not supported in stream mode (yet?)
toStream := input.Stream && !processFunctions
log.Debug().Msgf("Parameters: %+v", config)
var predInput string
mess := []string{}
for _, i := range input.Messages {
var content string
role := i.Role
// if function call, we might want to customize the role so we can display better that the "assistant called a json action"
// if an "assistant_function_call" role is defined, we use it, otherwise we use the role that is passed by in the request
if i.FunctionCall != nil && i.Role == "assistant" {
roleFn := "assistant_function_call"
r := config.Roles[roleFn]
if r != "" {
role = roleFn
}
}
r := config.Roles[role]
contentExists := i.Content != nil && *i.Content != ""
if r != "" {
if contentExists {
content = fmt.Sprint(r, " ", *i.Content)
}
if i.FunctionCall != nil {
j, err := json.Marshal(i.FunctionCall)
if err == nil {
if contentExists {
content += "\n" + fmt.Sprint(r, " ", string(j))
} else {
content = fmt.Sprint(r, " ", string(j))
}
}
}
} else {
if contentExists {
content = fmt.Sprint(*i.Content)
}
if i.FunctionCall != nil {
j, err := json.Marshal(i.FunctionCall)
if err == nil {
if contentExists {
content += "\n" + string(j)
} else {
content = string(j)
}
}
}
}
mess = append(mess, content)
}
predInput = strings.Join(mess, "\n")
log.Debug().Msgf("Prompt (before templating): %s", predInput)
if toStream {
log.Debug().Msgf("Stream request received")
c.Context().SetContentType("text/event-stream")
//c.Response().Header.SetContentType(fiber.MIMETextHTMLCharsetUTF8)
// c.Set("Content-Type", "text/event-stream")
c.Set("Cache-Control", "no-cache")
c.Set("Connection", "keep-alive")
c.Set("Transfer-Encoding", "chunked")
}
templateFile := config.Model
if config.TemplateConfig.Chat != "" && !processFunctions {
templateFile = config.TemplateConfig.Chat
}
if config.TemplateConfig.Functions != "" && processFunctions {
templateFile = config.TemplateConfig.Functions
}
// A model can have a "file.bin.tmpl" file associated with a prompt template prefix
templatedInput, err := o.Loader.TemplatePrefix(templateFile, struct {
Input string
Functions []grammar.Function
}{
Input: predInput,
Functions: funcs,
})
if err == nil {
predInput = templatedInput
log.Debug().Msgf("Template found, input modified to: %s", predInput)
} else {
log.Debug().Msgf("Template failed loading: %s", err.Error())
}
log.Debug().Msgf("Prompt (after templating): %s", predInput)
if processFunctions {
log.Debug().Msgf("Grammar: %+v", config.Grammar)
}
if toStream {
responses := make(chan OpenAIResponse)
go process(predInput, input, config, o.Loader, responses)
c.Context().SetBodyStreamWriter(fasthttp.StreamWriter(func(w *bufio.Writer) {
for ev := range responses {
var buf bytes.Buffer
enc := json.NewEncoder(&buf)
enc.Encode(ev)
log.Debug().Msgf("Sending chunk: %s", buf.String())
fmt.Fprintf(w, "data: %v\n", buf.String())
w.Flush()
}
resp := &OpenAIResponse{
Model: input.Model, // we have to return what the user sent here, due to OpenAI spec.
Choices: []Choice{
{
FinishReason: "stop",
Index: 0,
Delta: &Message{Content: &emptyMessage},
}},
Object: "chat.completion.chunk",
}
respData, _ := json.Marshal(resp)
w.WriteString(fmt.Sprintf("data: %s\n\n", respData))
w.WriteString("data: [DONE]\n\n")
w.Flush()
}))
return nil
}
result, err := ComputeChoices(predInput, input.N, config, o, o.Loader, func(s string, c *[]Choice) {
if processFunctions {
// As we have to change the result before processing, we can't stream the answer (yet?)
ss := map[string]interface{}{}
json.Unmarshal([]byte(s), &ss)
log.Debug().Msgf("Function return: %s %+v", s, ss)
// The grammar defines the function name as "function", while OpenAI returns "name"
func_name := ss["function"]
// Similarly, while here arguments is a map[string]interface{}, OpenAI actually want a stringified object
args := ss["arguments"] // arguments needs to be a string, but we return an object from the grammar result (TODO: fix)
d, _ := json.Marshal(args)
ss["arguments"] = string(d)
ss["name"] = func_name
// if do nothing, reply with a message
if func_name == noActionName {
log.Debug().Msgf("nothing to do, computing a reply")
// If there is a message that the LLM already sends as part of the JSON reply, use it
arguments := map[string]interface{}{}
json.Unmarshal([]byte(d), &arguments)
m, exists := arguments["message"]
if exists {
switch message := m.(type) {
case string:
if message != "" {
log.Debug().Msgf("Reply received from LLM: %s", message)
message = backend.Finetune(*config, predInput, message)
log.Debug().Msgf("Reply received from LLM(finetuned): %s", message)
*c = append(*c, Choice{Message: &Message{Role: "assistant", Content: &message}})
return
}
}
}
log.Debug().Msgf("No action received from LLM, without a message, computing a reply")
// Otherwise ask the LLM to understand the JSON output and the context, and return a message
// Note: This costs (in term of CPU) another computation
config.Grammar = ""
predFunc, err := backend.ModelInference(predInput, o.Loader, *config, o, nil)
if err != nil {
log.Error().Msgf("inference error: %s", err.Error())
return
}
prediction, err := predFunc()
if err != nil {
log.Error().Msgf("inference error: %s", err.Error())
return
}
prediction = backend.Finetune(*config, predInput, prediction)
*c = append(*c, Choice{Message: &Message{Role: "assistant", Content: &prediction}})
} else {
// otherwise reply with the function call
*c = append(*c, Choice{
FinishReason: "function_call",
Message: &Message{Role: "assistant", FunctionCall: ss},
})
}
return
}
*c = append(*c, Choice{FinishReason: "stop", Index: 0, 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)
}
}

@ -1,159 +0,0 @@
package openai
import (
"bufio"
"bytes"
"encoding/json"
"errors"
"fmt"
config "github.com/go-skynet/LocalAI/api/config"
"github.com/go-skynet/LocalAI/api/options"
model "github.com/go-skynet/LocalAI/pkg/model"
"github.com/gofiber/fiber/v2"
"github.com/rs/zerolog/log"
"github.com/valyala/fasthttp"
)
// https://platform.openai.com/docs/api-reference/completions
func CompletionEndpoint(cm *config.ConfigLoader, o *options.Option) func(c *fiber.Ctx) error {
process := func(s string, req *OpenAIRequest, config *config.Config, loader *model.ModelLoader, responses chan OpenAIResponse) {
ComputeChoices(s, req.N, config, o, loader, func(s string, c *[]Choice) {}, func(s string) bool {
resp := OpenAIResponse{
Model: req.Model, // we have to return what the user sent here, due to OpenAI spec.
Choices: []Choice{
{
Index: 0,
Text: s,
},
},
Object: "text_completion",
}
log.Debug().Msgf("Sending goroutine: %s", s)
responses <- resp
return true
})
close(responses)
}
return func(c *fiber.Ctx) error {
model, input, err := readInput(c, o.Loader, true)
if err != nil {
return fmt.Errorf("failed reading parameters from request:%w", err)
}
log.Debug().Msgf("`input`: %+v", input)
config, input, err := readConfig(model, input, cm, o.Loader, o.Debug, o.Threads, o.ContextSize, o.F16)
if err != nil {
return fmt.Errorf("failed reading parameters from request:%w", err)
}
log.Debug().Msgf("Parameter Config: %+v", config)
if input.Stream {
log.Debug().Msgf("Stream request received")
c.Context().SetContentType("text/event-stream")
//c.Response().Header.SetContentType(fiber.MIMETextHTMLCharsetUTF8)
//c.Set("Content-Type", "text/event-stream")
c.Set("Cache-Control", "no-cache")
c.Set("Connection", "keep-alive")
c.Set("Transfer-Encoding", "chunked")
}
templateFile := config.Model
if config.TemplateConfig.Completion != "" {
templateFile = config.TemplateConfig.Completion
}
if input.Stream {
if len(config.PromptStrings) > 1 {
return errors.New("cannot handle more than 1 `PromptStrings` when Streaming")
}
predInput := config.PromptStrings[0]
// A model can have a "file.bin.tmpl" file associated with a prompt template prefix
templatedInput, err := o.Loader.TemplatePrefix(templateFile, struct {
Input string
}{
Input: predInput,
})
if err == nil {
predInput = templatedInput
log.Debug().Msgf("Template found, input modified to: %s", predInput)
}
responses := make(chan OpenAIResponse)
go process(predInput, input, config, o.Loader, responses)
c.Context().SetBodyStreamWriter(fasthttp.StreamWriter(func(w *bufio.Writer) {
for ev := range responses {
var buf bytes.Buffer
enc := json.NewEncoder(&buf)
enc.Encode(ev)
log.Debug().Msgf("Sending chunk: %s", buf.String())
fmt.Fprintf(w, "data: %v\n", buf.String())
w.Flush()
}
resp := &OpenAIResponse{
Model: input.Model, // we have to return what the user sent here, due to OpenAI spec.
Choices: []Choice{
{
Index: 0,
FinishReason: "stop",
},
},
Object: "text_completion",
}
respData, _ := json.Marshal(resp)
w.WriteString(fmt.Sprintf("data: %s\n\n", respData))
w.WriteString("data: [DONE]\n\n")
w.Flush()
}))
return nil
}
var result []Choice
for k, i := range config.PromptStrings {
// A model can have a "file.bin.tmpl" file associated with a prompt template prefix
templatedInput, err := o.Loader.TemplatePrefix(templateFile, struct {
Input string
}{
Input: i,
})
if err == nil {
i = templatedInput
log.Debug().Msgf("Template found, input modified to: %s", i)
}
r, err := ComputeChoices(i, input.N, config, o, o.Loader, func(s string, c *[]Choice) {
*c = append(*c, Choice{Text: s, FinishReason: "stop", Index: k})
}, 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)
}
}

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

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

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

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

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

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

@ -1,71 +0,0 @@
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.Loader, false)
if err != nil {
return fmt.Errorf("failed reading parameters from request:%w", err)
}
config, input, err := readConfig(m, input, cm, o.Loader, o.Debug, o.Threads, o.ContextSize, o.F16)
if err != nil {
return fmt.Errorf("failed reading parameters from request:%w", err)
}
// retrieve the file data from the request
file, err := c.FormFile("file")
if err != nil {
return err
}
f, err := file.Open()
if err != nil {
return err
}
defer f.Close()
dir, err := os.MkdirTemp("", "whisper")
if err != nil {
return err
}
defer os.RemoveAll(dir)
dst := filepath.Join(dir, path.Base(file.Filename))
dstFile, err := os.Create(dst)
if err != nil {
return err
}
if _, err := io.Copy(dstFile, f); err != nil {
log.Debug().Msgf("Audio file copying error %+v - %+v - err %+v", file.Filename, dst, err)
return err
}
log.Debug().Msgf("Audio file copied to: %+v", dst)
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)
}
}

@ -1,186 +0,0 @@
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
Galleries []gallery.Gallery
BackendAssets embed.FS
AssetsDestination string
ExternalGRPCBackends map[string]string
AutoloadGalleries 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 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
}
}

@ -0,0 +1,343 @@
package api
import (
"fmt"
"regexp"
"strings"
"sync"
"github.com/donomii/go-rwkv.cpp"
model "github.com/go-skynet/LocalAI/pkg/model"
gpt2 "github.com/go-skynet/go-gpt2.cpp"
gptj "github.com/go-skynet/go-gpt4all-j.cpp"
llama "github.com/go-skynet/go-llama.cpp"
"github.com/hashicorp/go-multierror"
)
const tokenizerSuffix = ".tokenizer.json"
// mutex still needed, see: https://github.com/ggerganov/llama.cpp/discussions/784
var mutexMap sync.Mutex
var mutexes map[string]*sync.Mutex = make(map[string]*sync.Mutex)
var loadedModels map[string]interface{} = map[string]interface{}{}
var muModels sync.Mutex
func backendLoader(backendString string, loader *model.ModelLoader, modelFile string, llamaOpts []llama.ModelOption, threads uint32) (model interface{}, err error) {
switch strings.ToLower(backendString) {
case "llama":
return loader.LoadLLaMAModel(modelFile, llamaOpts...)
case "stablelm":
return loader.LoadStableLMModel(modelFile)
case "gpt2":
return loader.LoadGPT2Model(modelFile)
case "gptj":
return loader.LoadGPTJModel(modelFile)
case "rwkv":
return loader.LoadRWKV(modelFile, modelFile+tokenizerSuffix, threads)
default:
return nil, fmt.Errorf("backend unsupported: %s", backendString)
}
}
func greedyLoader(loader *model.ModelLoader, modelFile string, llamaOpts []llama.ModelOption, threads uint32) (model interface{}, err error) {
updateModels := func(model interface{}) {
muModels.Lock()
defer muModels.Unlock()
loadedModels[modelFile] = model
}
muModels.Lock()
m, exists := loadedModels[modelFile]
if exists {
muModels.Unlock()
return m, nil
}
muModels.Unlock()
model, modelerr := loader.LoadLLaMAModel(modelFile, llamaOpts...)
if modelerr == nil {
updateModels(model)
return model, nil
} else {
err = multierror.Append(err, modelerr)
}
model, modelerr = loader.LoadGPTJModel(modelFile)
if modelerr == nil {
updateModels(model)
return model, nil
} else {
err = multierror.Append(err, modelerr)
}
model, modelerr = loader.LoadGPT2Model(modelFile)
if modelerr == nil {
updateModels(model)
return model, nil
} else {
err = multierror.Append(err, modelerr)
}
model, modelerr = loader.LoadStableLMModel(modelFile)
if modelerr == nil {
updateModels(model)
return model, nil
} else {
err = multierror.Append(err, modelerr)
}
model, modelerr = loader.LoadRWKV(modelFile, modelFile+tokenizerSuffix, threads)
if modelerr == nil {
updateModels(model)
return model, nil
} else {
err = multierror.Append(err, modelerr)
}
return nil, fmt.Errorf("could not load model - all backends returned error: %s", err.Error())
}
func ModelInference(s string, loader *model.ModelLoader, c Config, tokenCallback func(string) bool) (func() (string, error), error) {
supportStreams := false
modelFile := c.Model
// Try to load the model
llamaOpts := []llama.ModelOption{}
if c.ContextSize != 0 {
llamaOpts = append(llamaOpts, llama.SetContext(c.ContextSize))
}
if c.F16 {
llamaOpts = append(llamaOpts, llama.EnableF16Memory)
}
var inferenceModel interface{}
var err error
if c.Backend == "" {
inferenceModel, err = greedyLoader(loader, modelFile, llamaOpts, uint32(c.Threads))
} else {
inferenceModel, err = backendLoader(c.Backend, loader, modelFile, llamaOpts, uint32(c.Threads))
}
if err != nil {
return nil, err
}
var fn func() (string, error)
switch model := inferenceModel.(type) {
case *rwkv.RwkvState:
supportStreams = true
fn = func() (string, error) {
//model.ProcessInput("You are a chatbot that is very good at chatting. blah blah blah")
stopWord := "\n"
if len(c.StopWords) > 0 {
stopWord = c.StopWords[0]
}
response := model.GenerateResponse(c.Maxtokens, stopWord, float32(c.Temperature), float32(c.TopP), tokenCallback)
return response, nil
}
case *gpt2.StableLM:
fn = func() (string, error) {
// Generate the prediction using the language model
predictOptions := []gpt2.PredictOption{
gpt2.SetTemperature(c.Temperature),
gpt2.SetTopP(c.TopP),
gpt2.SetTopK(c.TopK),
gpt2.SetTokens(c.Maxtokens),
gpt2.SetThreads(c.Threads),
}
if c.Batch != 0 {
predictOptions = append(predictOptions, gpt2.SetBatch(c.Batch))
}
if c.Seed != 0 {
predictOptions = append(predictOptions, gpt2.SetSeed(c.Seed))
}
return model.Predict(
s,
predictOptions...,
)
}
case *gpt2.GPT2:
fn = func() (string, error) {
// Generate the prediction using the language model
predictOptions := []gpt2.PredictOption{
gpt2.SetTemperature(c.Temperature),
gpt2.SetTopP(c.TopP),
gpt2.SetTopK(c.TopK),
gpt2.SetTokens(c.Maxtokens),
gpt2.SetThreads(c.Threads),
}
if c.Batch != 0 {
predictOptions = append(predictOptions, gpt2.SetBatch(c.Batch))
}
if c.Seed != 0 {
predictOptions = append(predictOptions, gpt2.SetSeed(c.Seed))
}
return model.Predict(
s,
predictOptions...,
)
}
case *gptj.GPTJ:
fn = func() (string, error) {
// Generate the prediction using the language model
predictOptions := []gptj.PredictOption{
gptj.SetTemperature(c.Temperature),
gptj.SetTopP(c.TopP),
gptj.SetTopK(c.TopK),
gptj.SetTokens(c.Maxtokens),
gptj.SetThreads(c.Threads),
}
if c.Batch != 0 {
predictOptions = append(predictOptions, gptj.SetBatch(c.Batch))
}
if c.Seed != 0 {
predictOptions = append(predictOptions, gptj.SetSeed(c.Seed))
}
return model.Predict(
s,
predictOptions...,
)
}
case *llama.LLama:
supportStreams = true
fn = func() (string, error) {
if tokenCallback != nil {
model.SetTokenCallback(tokenCallback)
}
// Generate the prediction using the language model
predictOptions := []llama.PredictOption{
llama.SetTemperature(c.Temperature),
llama.SetTopP(c.TopP),
llama.SetTopK(c.TopK),
llama.SetTokens(c.Maxtokens),
llama.SetThreads(c.Threads),
}
if c.Debug {
predictOptions = append(predictOptions, llama.Debug)
}
predictOptions = append(predictOptions, llama.SetStopWords(c.StopWords...))
if c.RepeatPenalty != 0 {
predictOptions = append(predictOptions, llama.SetPenalty(c.RepeatPenalty))
}
if c.Keep != 0 {
predictOptions = append(predictOptions, llama.SetNKeep(c.Keep))
}
if c.Batch != 0 {
predictOptions = append(predictOptions, llama.SetBatch(c.Batch))
}
if c.F16 {
predictOptions = append(predictOptions, llama.EnableF16KV)
}
if c.IgnoreEOS {
predictOptions = append(predictOptions, llama.IgnoreEOS)
}
if c.Seed != 0 {
predictOptions = append(predictOptions, llama.SetSeed(c.Seed))
}
return model.Predict(
s,
predictOptions...,
)
}
}
return func() (string, error) {
// This is still needed, see: https://github.com/ggerganov/llama.cpp/discussions/784
mutexMap.Lock()
l, ok := mutexes[modelFile]
if !ok {
m := &sync.Mutex{}
mutexes[modelFile] = m
l = m
}
mutexMap.Unlock()
l.Lock()
defer l.Unlock()
res, err := fn()
if tokenCallback != nil && !supportStreams {
tokenCallback(res)
}
return res, err
}, nil
}
func ComputeChoices(predInput string, input *OpenAIRequest, config *Config, loader *model.ModelLoader, cb func(string, *[]Choice), tokenCallback func(string) bool) ([]Choice, error) {
result := []Choice{}
n := input.N
if input.N == 0 {
n = 1
}
// get the model function to call for the result
predFunc, err := ModelInference(predInput, loader, *config, tokenCallback)
if err != nil {
return result, err
}
for i := 0; i < n; i++ {
prediction, err := predFunc()
if err != nil {
return result, err
}
prediction = Finetune(*config, predInput, prediction)
cb(prediction, &result)
//result = append(result, Choice{Text: prediction})
}
return result, err
}
var cutstrings map[string]*regexp.Regexp = make(map[string]*regexp.Regexp)
var mu sync.Mutex = sync.Mutex{}
func Finetune(config Config, input, prediction string) string {
if config.Echo {
prediction = input + prediction
}
for _, c := range config.Cutstrings {
mu.Lock()
reg, ok := cutstrings[c]
if !ok {
cutstrings[c] = regexp.MustCompile(c)
reg = cutstrings[c]
}
mu.Unlock()
prediction = reg.ReplaceAllString(prediction, "")
}
for _, c := range config.TrimSpace {
prediction = strings.TrimSpace(strings.TrimPrefix(prediction, c))
}
return prediction
}

@ -1,6 +0,0 @@
package main
import "embed"
//go:embed backend-assets/*
var backendAssets embed.FS

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

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

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

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

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

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

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

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

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

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

@ -1,25 +0,0 @@
package main
// GRPC Falcon server
// Note: this is started internally by LocalAI and a server is allocated for each model
import (
"flag"
llama "github.com/go-skynet/LocalAI/pkg/grpc/llm/llama-grammar"
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)
}
}

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

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

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

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

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

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

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

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

@ -5,7 +5,7 @@ services:
image: quay.io/go-skynet/local-ai:latest
build:
context: .
dockerfile: Dockerfile
dockerfile: Dockerfile.dev
ports:
- 8080:8080
env_file:

@ -1,21 +1,7 @@
#!/bin/bash
set -e
cd /build
if [ "$REBUILD" != "false" ]; then
rm -rf ./local-ai
ESPEAK_DATA=/build/lib/Linux-$(uname -m)/piper_phonemize/lib/espeak-ng-data make build -j${BUILD_PARALLELISM:-1}
else
echo "@@@@@"
echo "Skipping rebuild"
echo "@@@@@"
echo "If you are experiencing issues with the pre-compiled builds, try setting REBUILD=true"
echo "If you are still experiencing issues with the build, try setting CMAKE_ARGS and disable the instructions set as needed:"
echo 'CMAKE_ARGS="-DLLAMA_F16C=OFF -DLLAMA_AVX512=OFF -DLLAMA_AVX2=OFF -DLLAMA_FMA=OFF"'
echo "see the documentation at: https://localai.io/basics/build/index.html"
echo "Note: See also https://github.com/go-skynet/LocalAI/issues/288"
echo "@@@@@"
fi
make build
./local-ai "$@"

@ -2,151 +2,13 @@
Here is a list of projects that can easily be integrated with the LocalAI backend.
### Projects
## Projects
### AutoGPT
_by [@mudler](https://github.com/mudler)_
This example shows how to use AutoGPT with LocalAI.
[Check it out here](https://github.com/go-skynet/LocalAI/tree/master/examples/autoGPT/)
### Chatbot-UI
_by [@mkellerman](https://github.com/mkellerman)_
![Screenshot from 2023-04-26 23-59-55](https://user-images.githubusercontent.com/2420543/234715439-98d12e03-d3ce-4f94-ab54-2b256808e05e.png)
This integration shows how to use LocalAI with [mckaywrigley/chatbot-ui](https://github.com/mckaywrigley/chatbot-ui).
[Check it out here](https://github.com/go-skynet/LocalAI/tree/master/examples/chatbot-ui/)
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).
![Screenshot from 2023-06-19 23-58-47](https://github.com/go-skynet/go-ggml-transformers.cpp/assets/2420543/cab87409-ee68-44ae-8d53-41627fb49509)
### 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)_
Run a discord bot which lets you talk directly with a model
[Check it out here](https://github.com/go-skynet/LocalAI/tree/master/examples/discord-bot/), or for a live demo you can talk with our bot in #random-bot in our discord server.
### Langchain
_by [@dave-gray101](https://github.com/dave-gray101)_
A ready to use example to show e2e how to integrate LocalAI with langchain
[Check it out here](https://github.com/go-skynet/LocalAI/tree/master/examples/langchain/)
### Langchain Python
_by [@mudler](https://github.com/mudler)_
A ready to use example to show e2e how to integrate LocalAI with langchain
[Check it out here](https://github.com/go-skynet/LocalAI/tree/master/examples/langchain-python/)
### LocalAI 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)_
![image](https://user-images.githubusercontent.com/42107491/235344183-44b5967d-ba22-4331-804c-8da7004a5d35.png)
A light, community-maintained web interface for LocalAI
[Check it out here](https://github.com/go-skynet/LocalAI/tree/master/examples/localai-webui/)
### How to run rwkv models
_by [@mudler](https://github.com/mudler)_
A full example on how to run RWKV models with LocalAI
[Check it out here](https://github.com/go-skynet/LocalAI/tree/master/examples/rwkv/)
### PrivateGPT
_by [@mudler](https://github.com/mudler)_
A full example on how to run PrivateGPT with LocalAI
[Check it out here](https://github.com/go-skynet/LocalAI/tree/master/examples/privateGPT/)
### Slack bot
_by [@mudler](https://github.com/mudler)_
Run a slack bot which lets you talk directly with a model
[Check it out here](https://github.com/go-skynet/LocalAI/tree/master/examples/slack-bot/)
### 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)_
Shows how to integrate with [Llama-Index](https://gpt-index.readthedocs.io/en/stable/getting_started/installation.html) to enable question answering on a set of documents.
[Check it out here](https://github.com/go-skynet/LocalAI/tree/master/examples/query_data/)
### Question answering on documents with langchain and chroma
_by [@mudler](https://github.com/mudler)_
Shows how to integrate with `Langchain` and `Chroma` to enable question answering on a set of documents.
[Check it out here](https://github.com/go-skynet/LocalAI/tree/master/examples/langchain-chroma/)
### Telegram bot
_by [@mudler](https://github.com/mudler)
![Screenshot from 2023-06-09 00-36-26](https://github.com/go-skynet/LocalAI/assets/2420543/e98b4305-fa2d-41cf-9d2f-1bb2d75ca902)
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)_
Allows to run any LocalAI-compatible model as a backend on the servers of https://runpod.io
[Check it out here](https://runpod.io/gsc?template=uv9mtqnrd0&ref=984wlcra)
- [chatbot-ui](https://github.com/go-skynet/LocalAI/tree/master/examples/chatbot-ui/) (by [@mkellerman](https://github.com/mkellerman))
- [discord-bot](https://github.com/go-skynet/LocalAI/tree/master/examples/discord-bot/) (by [@mudler](https://github.com/mudler))
- [langchain](https://github.com/go-skynet/LocalAI/tree/master/examples/langchain/) (by [@dave-gray101](https://github.com/dave-gray101))
- [langchain-python](https://github.com/go-skynet/LocalAI/tree/master/examples/langchain-python/) (by [@mudler](https://github.com/mudler))
- [slack-bot](https://github.com/go-skynet/LocalAI/tree/master/examples/slack-bot/) (by [@mudler](https://github.com/mudler))
## Want to contribute?

@ -1,5 +0,0 @@
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/gpt4all-j.yaml", "name": "gpt-3.5-turbo"}, { "url": "github:go-skynet/model-gallery/bert-embeddings.yaml", "name": "text-embedding-ada-002"}]

@ -1,32 +0,0 @@
# AutoGPT
Example of integration with [AutoGPT](https://github.com/Significant-Gravitas/Auto-GPT).
## Run
```bash
# Clone LocalAI
git clone https://github.com/go-skynet/LocalAI
cd LocalAI/examples/autoGPT
docker-compose run --rm auto-gpt
```
Note: The example automatically downloads the `gpt4all` model as it is under a permissive license. The GPT4All model does not seem to be enough to run AutoGPT. WizardLM-7b-uncensored seems to perform better (with `f16: true`).
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`.
## Without docker
Run AutoGPT with `OPENAI_API_BASE` pointing to the LocalAI endpoint. If you run it locally for instance:
```
OPENAI_API_BASE=http://localhost:8080 python ...
```
Note: you need a model named `gpt-3.5-turbo` and `text-embedding-ada-002`. You can preload those in LocalAI at start by setting in the env:
```
PRELOAD_MODELS=[{"url": "github:go-skynet/model-gallery/gpt4all-j.yaml", "name": "gpt-3.5-turbo"}, { "url": "github:go-skynet/model-gallery/bert-embeddings.yaml", "name": "text-embedding-ada-002"}]
```

@ -1,42 +0,0 @@
version: "3.9"
services:
api:
image: quay.io/go-skynet/local-ai:latest
ports:
- 8080:8080
env_file:
- .env
environment:
- DEBUG=true
- MODELS_PATH=/models
volumes:
- ./models:/models:cached
command: ["/usr/bin/local-ai" ]
auto-gpt:
image: significantgravitas/auto-gpt
depends_on:
api:
condition: service_healthy
redis:
condition: service_started
env_file:
- .env
environment:
MEMORY_BACKEND: ${MEMORY_BACKEND:-redis}
REDIS_HOST: ${REDIS_HOST:-redis}
profiles: ["exclude-from-up"]
volumes:
- ./auto_gpt_workspace:/app/autogpt/auto_gpt_workspace
- ./data:/app/data
## allow auto-gpt to write logs to disk
- ./logs:/app/logs
## uncomment following lines if you want to make use of these files
## you must have them existing in the same folder as this docker-compose.yml
#- type: bind
# source: ./azure.yaml
# target: /app/azure.yaml
#- type: bind
# source: ./ai_settings.yaml
# target: /app/ai_settings.yaml
redis:
image: "redis/redis-stack-server:latest"

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

@ -1,24 +0,0 @@
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'

@ -4,20 +4,22 @@ Example of integration with [mckaywrigley/chatbot-ui](https://github.com/mckaywr
![Screenshot from 2023-04-26 23-59-55](https://user-images.githubusercontent.com/2420543/234715439-98d12e03-d3ce-4f94-ab54-2b256808e05e.png)
## Run
## Setup
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
# start with docker-compose
docker-compose up --pull always
# (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
# or you can build the images with:
# docker-compose up -d --build
# start with docker-compose
docker-compose up -d --build
```
## Pointing chatbot-ui to a separately managed LocalAI service

@ -3,32 +3,19 @@ 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
dockerfile: Dockerfile.dev
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

@ -5,6 +5,7 @@ parameters:
temperature: 0.2
top_p: 0.7
context_size: 1024
threads: 14
stopwords:
- "HUMAN:"
- "GPT:"

@ -5,7 +5,7 @@ services:
image: quay.io/go-skynet/local-ai:latest
build:
context: ../../
dockerfile: Dockerfile
dockerfile: Dockerfile.dev
ports:
- 8080:8080
environment:

@ -1,30 +0,0 @@
# flowise
Example of integration with [FlowiseAI/Flowise](https://github.com/FlowiseAI/Flowise).
![Screenshot from 2023-05-30 18-01-03](https://github.com/go-skynet/LocalAI/assets/2420543/02458782-0549-4131-971c-95ee56ec1af8)
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.

@ -1,37 +0,0 @@
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"

@ -1,9 +0,0 @@
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

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

@ -1,18 +0,0 @@
# 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`.

@ -1,23 +0,0 @@
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

@ -1,76 +0,0 @@
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())

@ -1,2 +0,0 @@
langchain==0.0.234
openai==0.27.8

@ -1,70 +0,0 @@
# k8sgpt example
This example show how to use LocalAI with k8sgpt
![Screenshot from 2023-06-19 23-58-47](https://github.com/go-skynet/go-ggml-transformers.cpp/assets/2420543/cab87409-ee68-44ae-8d53-41627fb49509)
## 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
```
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
noCache: false
version: v0.3.0
enableAI: true
EOF
```
## Test
Apply a broken pod:
```
kubectl apply -f broken-pod.yaml
```

@ -1,14 +0,0 @@
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

@ -1,95 +0,0 @@
replicaCount: 1
deployment:
# https://quay.io/repository/go-skynet/local-ai?tab=tags
image: quay.io/go-skynet/local-ai:latest
env:
threads: 4
debug: "true"
context_size: 512
preload_models: '[{ "url": "github:go-skynet/model-gallery/wizard.yaml", "name": "gpt-3.5-turbo", "overrides": { "parameters": { "model": "WizardLM-7B-uncensored.ggmlv3.q5_1" }},"files": [ { "uri": "https://huggingface.co//WizardLM-7B-uncensored-GGML/resolve/main/WizardLM-7B-uncensored.ggmlv3.q5_1.bin", "sha256": "d92a509d83a8ea5e08ba4c2dbaf08f29015932dc2accd627ce0665ac72c2bb2b", "filename": "WizardLM-7B-uncensored.ggmlv3.q5_1" }]}]'
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: {}

@ -1,5 +0,0 @@
THREADS=4
CONTEXT_SIZE=512
MODELS_PATH=/models
DEBUG=true
# BUILD_TYPE=generic

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