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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
ed2344ab9b | ||
|
|
935bd51510 | ||
|
|
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|
|
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|
|
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|
|
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|
|
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|
|
c2dec387aa | ||
|
|
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|
|
ad81e37672 | ||
|
|
78f3c3da48 | ||
|
|
d18f85df46 | ||
|
|
6213da330a | ||
|
|
53f8d73101 | ||
|
|
2cfc9a2706 | ||
|
|
0ba94bf33f | ||
|
|
06570d1e41 | ||
|
|
be1667c387 | ||
|
|
eb39d908d0 | ||
|
|
60db5957d3 | ||
|
|
2a45a99737 | ||
|
|
91a67d5ee0 | ||
|
|
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|
|
a7bb029d23 | ||
|
|
cc31c58235 | ||
|
|
4e831307a8 | ||
|
|
445067f6ad | ||
|
|
11bfd0de76 | ||
|
|
dc7b8ad23b |
@@ -1,4 +1,3 @@
|
||||
.git
|
||||
.idea
|
||||
models
|
||||
examples/chatbot-ui/models
|
||||
|
||||
69
.env
69
.env
@@ -7,24 +7,83 @@
|
||||
|
||||
## 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.
|
||||
## Disables COMPEL (Diffusers)
|
||||
# COMPEL=0
|
||||
|
||||
## Enable/Disable single backend (useful if only one GPU is available)
|
||||
# SINGLE_ACTIVE_BACKEND=true
|
||||
|
||||
## Specify a build type. Available: cublas, openblas, clblas.
|
||||
## cuBLAS: This is a GPU-accelerated version of the complete standard BLAS (Basic Linear Algebra Subprograms) library. It's provided by Nvidia and is part of their CUDA toolkit.
|
||||
## OpenBLAS: This is an open-source implementation of the BLAS library that aims to provide highly optimized code for various platforms. It includes support for multi-threading and can be compiled to use hardware-specific features for additional performance. OpenBLAS can run on many kinds of hardware, including CPUs from Intel, AMD, and ARM.
|
||||
## clBLAS: This is an open-source implementation of the BLAS library that uses OpenCL, a framework for writing programs that execute across heterogeneous platforms consisting of CPUs, GPUs, and other processors. clBLAS is designed to take advantage of the parallel computing power of GPUs but can also run on any hardware that supports OpenCL. This includes hardware from different vendors like Nvidia, AMD, and Intel.
|
||||
# BUILD_TYPE=openblas
|
||||
|
||||
## Uncomment and set to false to disable rebuilding from source
|
||||
# REBUILD=false
|
||||
## Uncomment and set to true to enable rebuilding from source
|
||||
# REBUILD=true
|
||||
|
||||
## Enable image generation with stablediffusion (requires REBUILD=true)
|
||||
## Enable go tags, available: stablediffusion, tts
|
||||
## stablediffusion: image generation with stablediffusion
|
||||
## tts: enables text-to-speech with go-piper
|
||||
## (requires REBUILD=true)
|
||||
#
|
||||
# GO_TAGS=stablediffusion
|
||||
|
||||
## Path where to store generated images
|
||||
# IMAGE_PATH=/tmp
|
||||
|
||||
## Specify a default upload limit in MB (whisper)
|
||||
# UPLOAD_LIMIT
|
||||
# UPLOAD_LIMIT
|
||||
|
||||
## List of external GRPC backends (note on the container image this variable is already set to use extra backends available in extra/)
|
||||
# EXTERNAL_GRPC_BACKENDS=my-backend:127.0.0.1:9000,my-backend2:/usr/bin/backend.py
|
||||
|
||||
### Advanced settings ###
|
||||
### Those are not really used by LocalAI, but from components in the stack ###
|
||||
##
|
||||
### Preload libraries
|
||||
# LD_PRELOAD=
|
||||
|
||||
### Huggingface cache for models
|
||||
# HUGGINGFACE_HUB_CACHE=/usr/local/huggingface
|
||||
|
||||
### Python backends GRPC max workers
|
||||
### Default number of workers for GRPC Python backends.
|
||||
### This actually controls wether a backend can process multiple requests or not.
|
||||
# PYTHON_GRPC_MAX_WORKERS=1
|
||||
|
||||
### Define the number of parallel LLAMA.cpp workers (Defaults to 1)
|
||||
# LLAMACPP_PARALLEL=1
|
||||
|
||||
### Enable to run parallel requests
|
||||
# PARALLEL_REQUESTS=true
|
||||
|
||||
### Watchdog settings
|
||||
###
|
||||
# Enables watchdog to kill backends that are inactive for too much time
|
||||
# WATCHDOG_IDLE=true
|
||||
#
|
||||
# Enables watchdog to kill backends that are busy for too much time
|
||||
# WATCHDOG_BUSY=true
|
||||
#
|
||||
# Time in duration format (e.g. 1h30m) after which a backend is considered idle
|
||||
# WATCHDOG_IDLE_TIMEOUT=5m
|
||||
#
|
||||
# Time in duration format (e.g. 1h30m) after which a backend is considered busy
|
||||
# WATCHDOG_BUSY_TIMEOUT=5m
|
||||
1
.gitattributes
vendored
Normal file
1
.gitattributes
vendored
Normal file
@@ -0,0 +1 @@
|
||||
*.sh text eol=lf
|
||||
5
.github/FUNDING.yml
vendored
Normal file
5
.github/FUNDING.yml
vendored
Normal file
@@ -0,0 +1,5 @@
|
||||
# These are supported funding model platforms
|
||||
|
||||
github: [mudler]
|
||||
custom:
|
||||
- https://www.buymeacoffee.com/mudler
|
||||
16
.github/PULL_REQUEST_TEMPLATE.md
vendored
16
.github/PULL_REQUEST_TEMPLATE.md
vendored
@@ -8,16 +8,24 @@ This PR fixes #
|
||||
**[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:
|
||||
Contributing Conventions
|
||||
-------------------------
|
||||
|
||||
1. Include descriptive PR titles with [<component-name>] prepended.
|
||||
2. Build and test your changes before submitting a PR.
|
||||
The draft above helps to give a quick overview of your PR.
|
||||
|
||||
Remember to remove this comment and to at least:
|
||||
|
||||
1. Include descriptive PR titles with [<component-name>] prepended. We use [conventional commits](https://www.conventionalcommits.org/en/v1.0.0/).
|
||||
2. Build and test your changes before submitting a PR (`make build`).
|
||||
3. Sign your commits
|
||||
4. **Tag maintainer:** for a quicker response, tag the relevant maintainer (see below).
|
||||
5. **X/Twitter handle:** we announce bigger features on X/Twitter. If your PR gets announced, and you'd like a mention, we'll gladly shout you out!
|
||||
|
||||
By following the community's contribution conventions upfront, the review process will
|
||||
be accelerated and your PR merged more quickly.
|
||||
|
||||
If no one reviews your PR within a few days, please @-mention @mudler.
|
||||
-->
|
||||
7
.github/bump_docs.sh
vendored
Executable file
7
.github/bump_docs.sh
vendored
Executable file
@@ -0,0 +1,7 @@
|
||||
#!/bin/bash
|
||||
set -xe
|
||||
REPO=$1
|
||||
|
||||
LATEST_TAG=$(curl -s "https://api.github.com/repos/$REPO/releases/latest" | jq -r '.name')
|
||||
|
||||
cat <<< $(jq ".version = \"$LATEST_TAG\"" docs/data/version.json) > docs/data/version.json
|
||||
14
.github/workflows/bump_deps.yaml
vendored
14
.github/workflows/bump_deps.yaml
vendored
@@ -12,6 +12,9 @@ jobs:
|
||||
- repository: "go-skynet/go-llama.cpp"
|
||||
variable: "GOLLAMA_VERSION"
|
||||
branch: "master"
|
||||
- repository: "ggerganov/llama.cpp"
|
||||
variable: "CPPLLAMA_VERSION"
|
||||
branch: "master"
|
||||
- repository: "go-skynet/go-ggml-transformers.cpp"
|
||||
variable: "GOGGMLTRANSFORMERS_VERSION"
|
||||
branch: "master"
|
||||
@@ -30,9 +33,18 @@ jobs:
|
||||
- repository: "nomic-ai/gpt4all"
|
||||
variable: "GPT4ALL_VERSION"
|
||||
branch: "main"
|
||||
- repository: "mudler/go-ggllm.cpp"
|
||||
variable: "GOGGLLM_VERSION"
|
||||
branch: "master"
|
||||
- repository: "mudler/go-stable-diffusion"
|
||||
variable: "STABLEDIFFUSION_VERSION"
|
||||
branch: "master"
|
||||
- repository: "mudler/go-piper"
|
||||
variable: "PIPER_VERSION"
|
||||
branch: "master"
|
||||
runs-on: ubuntu-latest
|
||||
steps:
|
||||
- uses: actions/checkout@v3
|
||||
- uses: actions/checkout@v4
|
||||
- name: Bump dependencies 🔧
|
||||
run: |
|
||||
bash .github/bump_deps.sh ${{ matrix.repository }} ${{ matrix.branch }} ${{ matrix.variable }}
|
||||
|
||||
31
.github/workflows/bump_docs.yaml
vendored
Normal file
31
.github/workflows/bump_docs.yaml
vendored
Normal file
@@ -0,0 +1,31 @@
|
||||
name: Bump dependencies
|
||||
on:
|
||||
schedule:
|
||||
- cron: 0 20 * * *
|
||||
workflow_dispatch:
|
||||
jobs:
|
||||
bump:
|
||||
strategy:
|
||||
fail-fast: false
|
||||
matrix:
|
||||
include:
|
||||
- repository: "mudler/LocalAI"
|
||||
runs-on: ubuntu-latest
|
||||
steps:
|
||||
- uses: actions/checkout@v4
|
||||
- name: Bump dependencies 🔧
|
||||
run: |
|
||||
bash .github/bump_docs.sh ${{ matrix.repository }}
|
||||
- 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 docs version ${{ matrix.repository }}'
|
||||
title: ':arrow_up: Update docs version ${{ matrix.repository }}'
|
||||
branch: "update/docs"
|
||||
body: Bump of ${{ matrix.repository }} version inside docs
|
||||
signoff: true
|
||||
|
||||
|
||||
|
||||
63
.github/workflows/disabled/test-gpu.yml
vendored
Normal file
63
.github/workflows/disabled/test-gpu.yml
vendored
Normal file
@@ -0,0 +1,63 @@
|
||||
---
|
||||
name: 'GPU tests'
|
||||
|
||||
on:
|
||||
pull_request:
|
||||
push:
|
||||
branches:
|
||||
- master
|
||||
tags:
|
||||
- '*'
|
||||
|
||||
concurrency:
|
||||
group: ci-gpu-tests-${{ github.head_ref || github.ref }}-${{ github.repository }}
|
||||
cancel-in-progress: true
|
||||
|
||||
jobs:
|
||||
ubuntu-latest:
|
||||
runs-on: gpu
|
||||
strategy:
|
||||
matrix:
|
||||
go-version: ['1.21.x']
|
||||
steps:
|
||||
- name: Clone
|
||||
uses: actions/checkout@v4
|
||||
with:
|
||||
submodules: true
|
||||
- name: Setup Go ${{ matrix.go-version }}
|
||||
uses: actions/setup-go@v4
|
||||
with:
|
||||
go-version: ${{ matrix.go-version }}
|
||||
# You can test your matrix by printing the current Go version
|
||||
- name: Display Go version
|
||||
run: go version
|
||||
- name: Dependencies
|
||||
run: |
|
||||
sudo apt-get update
|
||||
sudo DEBIAN_FRONTEND=noninteractive apt-get install -y make wget
|
||||
- name: Build
|
||||
run: |
|
||||
if [ ! -e /run/systemd/system ]; then
|
||||
sudo mkdir /run/systemd/system
|
||||
fi
|
||||
sudo mkdir -p /host/tests/${{ github.head_ref || github.ref }}
|
||||
sudo chmod -R 777 /host/tests/${{ github.head_ref || github.ref }}
|
||||
make \
|
||||
TEST_DIR="/host/tests/${{ github.head_ref || github.ref }}" \
|
||||
BUILD_TYPE=cublas \
|
||||
prepare-e2e run-e2e-image test-e2e
|
||||
- name: Release space from worker ♻
|
||||
if: always()
|
||||
run: |
|
||||
sudo rm -rf build || true
|
||||
sudo rm -rf bin || true
|
||||
sudo rm -rf dist || true
|
||||
sudo docker logs $(sudo docker ps -q --filter ancestor=localai-tests) > logs.txt
|
||||
sudo cat logs.txt || true
|
||||
sudo rm -rf logs.txt
|
||||
make clean || true
|
||||
make \
|
||||
TEST_DIR="/host/tests/${{ github.head_ref || github.ref }}" \
|
||||
teardown-e2e || true
|
||||
sudo rm -rf /host/tests/${{ github.head_ref || github.ref }} || true
|
||||
docker system prune -f -a --volumes || true
|
||||
180
.github/workflows/image.yml
vendored
180
.github/workflows/image.yml
vendored
@@ -14,96 +14,144 @@ concurrency:
|
||||
cancel-in-progress: true
|
||||
|
||||
jobs:
|
||||
docker:
|
||||
extras-image-build:
|
||||
uses: ./.github/workflows/image_build.yml
|
||||
with:
|
||||
tag-latest: ${{ matrix.tag-latest }}
|
||||
tag-suffix: ${{ matrix.tag-suffix }}
|
||||
ffmpeg: ${{ matrix.ffmpeg }}
|
||||
image-type: ${{ matrix.image-type }}
|
||||
build-type: ${{ matrix.build-type }}
|
||||
cuda-major-version: ${{ matrix.cuda-major-version }}
|
||||
cuda-minor-version: ${{ matrix.cuda-minor-version }}
|
||||
platforms: ${{ matrix.platforms }}
|
||||
runs-on: ${{ matrix.runs-on }}
|
||||
secrets:
|
||||
dockerUsername: ${{ secrets.LOCALAI_REGISTRY_USERNAME }}
|
||||
dockerPassword: ${{ secrets.LOCALAI_REGISTRY_PASSWORD }}
|
||||
strategy:
|
||||
# Pushing with all jobs in parallel
|
||||
# eats the bandwidth of all the nodes
|
||||
max-parallel: ${{ github.event_name != 'pull_request' && 2 || 4 }}
|
||||
matrix:
|
||||
include:
|
||||
- build-type: ''
|
||||
platforms: 'linux/amd64,linux/arm64'
|
||||
#platforms: 'linux/amd64,linux/arm64'
|
||||
platforms: 'linux/amd64'
|
||||
tag-latest: 'auto'
|
||||
tag-suffix: ''
|
||||
ffmpeg: ''
|
||||
image-type: 'extras'
|
||||
runs-on: 'arc-runner-set'
|
||||
- build-type: ''
|
||||
platforms: 'linux/amd64'
|
||||
tag-latest: 'false'
|
||||
tag-suffix: '-ffmpeg'
|
||||
ffmpeg: 'true'
|
||||
image-type: 'extras'
|
||||
runs-on: 'arc-runner-set'
|
||||
- build-type: 'cublas'
|
||||
cuda-major-version: 11
|
||||
cuda-minor-version: 7
|
||||
cuda-major-version: "11"
|
||||
cuda-minor-version: "7"
|
||||
platforms: 'linux/amd64'
|
||||
tag-latest: 'false'
|
||||
tag-suffix: '-cublas-cuda11'
|
||||
ffmpeg: ''
|
||||
image-type: 'extras'
|
||||
runs-on: 'arc-runner-set'
|
||||
- build-type: 'cublas'
|
||||
cuda-major-version: 12
|
||||
cuda-minor-version: 1
|
||||
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'
|
||||
image-type: 'extras'
|
||||
runs-on: 'arc-runner-set'
|
||||
- build-type: 'cublas'
|
||||
cuda-major-version: 11
|
||||
cuda-minor-version: 7
|
||||
cuda-major-version: "11"
|
||||
cuda-minor-version: "7"
|
||||
platforms: 'linux/amd64'
|
||||
tag-latest: 'false'
|
||||
tag-suffix: '-cublas-cuda11-ffmpeg'
|
||||
ffmpeg: 'true'
|
||||
image-type: 'extras'
|
||||
runs-on: 'arc-runner-set'
|
||||
- build-type: 'cublas'
|
||||
cuda-major-version: 12
|
||||
cuda-minor-version: 1
|
||||
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: 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: Set up QEMU
|
||||
uses: docker/setup-qemu-action@master
|
||||
with:
|
||||
platforms: all
|
||||
|
||||
- name: Set up Docker Buildx
|
||||
id: buildx
|
||||
uses: docker/setup-buildx-action@master
|
||||
|
||||
- name: Login to DockerHub
|
||||
if: github.event_name != 'pull_request'
|
||||
uses: docker/login-action@v2
|
||||
with:
|
||||
registry: quay.io
|
||||
username: ${{ secrets.LOCALAI_REGISTRY_USERNAME }}
|
||||
password: ${{ secrets.LOCALAI_REGISTRY_PASSWORD }}
|
||||
|
||||
- name: Build and push
|
||||
uses: docker/build-push-action@v4
|
||||
with:
|
||||
builder: ${{ steps.buildx.outputs.name }}
|
||||
build-args: |
|
||||
BUILD_TYPE=${{ matrix.build-type }}
|
||||
CUDA_MAJOR_VERSION=${{ matrix.cuda-major-version }}
|
||||
CUDA_MINOR_VERSION=${{ matrix.cuda-minor-version }}
|
||||
FFMPEG=${{ matrix.ffmpeg }}
|
||||
context: .
|
||||
file: ./Dockerfile
|
||||
platforms: ${{ matrix.platforms }}
|
||||
push: ${{ github.event_name != 'pull_request' }}
|
||||
tags: ${{ steps.meta.outputs.tags }}
|
||||
labels: ${{ steps.meta.outputs.labels }}
|
||||
image-type: 'extras'
|
||||
runs-on: 'arc-runner-set'
|
||||
- build-type: ''
|
||||
#platforms: 'linux/amd64,linux/arm64'
|
||||
platforms: 'linux/amd64'
|
||||
tag-latest: 'auto'
|
||||
tag-suffix: ''
|
||||
ffmpeg: ''
|
||||
image-type: 'extras'
|
||||
runs-on: 'arc-runner-set'
|
||||
core-image-build:
|
||||
uses: ./.github/workflows/image_build.yml
|
||||
with:
|
||||
tag-latest: ${{ matrix.tag-latest }}
|
||||
tag-suffix: ${{ matrix.tag-suffix }}
|
||||
ffmpeg: ${{ matrix.ffmpeg }}
|
||||
image-type: ${{ matrix.image-type }}
|
||||
build-type: ${{ matrix.build-type }}
|
||||
cuda-major-version: ${{ matrix.cuda-major-version }}
|
||||
cuda-minor-version: ${{ matrix.cuda-minor-version }}
|
||||
platforms: ${{ matrix.platforms }}
|
||||
runs-on: ${{ matrix.runs-on }}
|
||||
secrets:
|
||||
dockerUsername: ${{ secrets.LOCALAI_REGISTRY_USERNAME }}
|
||||
dockerPassword: ${{ secrets.LOCALAI_REGISTRY_PASSWORD }}
|
||||
strategy:
|
||||
matrix:
|
||||
include:
|
||||
- build-type: ''
|
||||
platforms: 'linux/amd64'
|
||||
tag-latest: 'false'
|
||||
tag-suffix: '-ffmpeg-core'
|
||||
ffmpeg: 'true'
|
||||
image-type: 'core'
|
||||
runs-on: 'ubuntu-latest'
|
||||
- build-type: 'cublas'
|
||||
cuda-major-version: "11"
|
||||
cuda-minor-version: "7"
|
||||
platforms: 'linux/amd64'
|
||||
tag-latest: 'false'
|
||||
tag-suffix: '-cublas-cuda11-core'
|
||||
ffmpeg: ''
|
||||
image-type: 'core'
|
||||
runs-on: 'ubuntu-latest'
|
||||
- build-type: 'cublas'
|
||||
cuda-major-version: "12"
|
||||
cuda-minor-version: "1"
|
||||
platforms: 'linux/amd64'
|
||||
tag-latest: 'false'
|
||||
tag-suffix: '-cublas-cuda12-core'
|
||||
ffmpeg: ''
|
||||
image-type: 'core'
|
||||
runs-on: 'ubuntu-latest'
|
||||
- build-type: 'cublas'
|
||||
cuda-major-version: "11"
|
||||
cuda-minor-version: "7"
|
||||
platforms: 'linux/amd64'
|
||||
tag-latest: 'false'
|
||||
tag-suffix: '-cublas-cuda11-ffmpeg-core'
|
||||
ffmpeg: 'true'
|
||||
image-type: 'core'
|
||||
runs-on: 'ubuntu-latest'
|
||||
- build-type: 'cublas'
|
||||
cuda-major-version: "12"
|
||||
cuda-minor-version: "1"
|
||||
platforms: 'linux/amd64'
|
||||
tag-latest: 'false'
|
||||
tag-suffix: '-cublas-cuda12-ffmpeg-core'
|
||||
ffmpeg: 'true'
|
||||
image-type: 'core'
|
||||
runs-on: 'ubuntu-latest'
|
||||
|
||||
147
.github/workflows/image_build.yml
vendored
Normal file
147
.github/workflows/image_build.yml
vendored
Normal file
@@ -0,0 +1,147 @@
|
||||
---
|
||||
name: 'build container images (reusable)'
|
||||
|
||||
on:
|
||||
workflow_call:
|
||||
inputs:
|
||||
build-type:
|
||||
description: 'Build type'
|
||||
default: ''
|
||||
type: string
|
||||
cuda-major-version:
|
||||
description: 'CUDA major version'
|
||||
default: "11"
|
||||
type: string
|
||||
cuda-minor-version:
|
||||
description: 'CUDA minor version'
|
||||
default: "7"
|
||||
type: string
|
||||
platforms:
|
||||
description: 'Platforms'
|
||||
default: ''
|
||||
type: string
|
||||
tag-latest:
|
||||
description: 'Tag latest'
|
||||
default: ''
|
||||
type: string
|
||||
tag-suffix:
|
||||
description: 'Tag suffix'
|
||||
default: ''
|
||||
type: string
|
||||
ffmpeg:
|
||||
description: 'FFMPEG'
|
||||
default: ''
|
||||
type: string
|
||||
image-type:
|
||||
description: 'Image type'
|
||||
default: ''
|
||||
type: string
|
||||
runs-on:
|
||||
description: 'Runs on'
|
||||
required: true
|
||||
default: ''
|
||||
type: string
|
||||
secrets:
|
||||
dockerUsername:
|
||||
required: true
|
||||
dockerPassword:
|
||||
required: true
|
||||
jobs:
|
||||
reusable_image-build:
|
||||
runs-on: ${{ inputs.runs-on }}
|
||||
steps:
|
||||
- name: Force Install GIT latest
|
||||
run: |
|
||||
sudo apt-get update \
|
||||
&& sudo apt-get install -y software-properties-common \
|
||||
&& sudo apt-get update \
|
||||
&& sudo add-apt-repository -y ppa:git-core/ppa \
|
||||
&& sudo apt-get update \
|
||||
&& sudo apt-get install -y git
|
||||
- name: Checkout
|
||||
uses: actions/checkout@v4
|
||||
# - name: Release space from worker
|
||||
# run: |
|
||||
# echo "Listing top largest packages"
|
||||
# pkgs=$(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 remove -y microsoft-edge-stable || true
|
||||
# sudo apt-get remove -y firefox || true
|
||||
# sudo apt-get remove -y powershell || true
|
||||
# sudo apt-get remove -y r-base-core || 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: Docker meta
|
||||
id: meta
|
||||
uses: docker/metadata-action@v5
|
||||
with:
|
||||
images: quay.io/go-skynet/local-ai
|
||||
tags: |
|
||||
type=ref,event=branch
|
||||
type=semver,pattern={{raw}}
|
||||
type=sha
|
||||
flavor: |
|
||||
latest=${{ inputs.tag-latest }}
|
||||
suffix=${{ inputs.tag-suffix }}
|
||||
|
||||
- name: Set up QEMU
|
||||
uses: docker/setup-qemu-action@master
|
||||
with:
|
||||
platforms: all
|
||||
|
||||
- name: Set up Docker Buildx
|
||||
id: buildx
|
||||
uses: docker/setup-buildx-action@master
|
||||
|
||||
- name: Login to DockerHub
|
||||
if: github.event_name != 'pull_request'
|
||||
uses: docker/login-action@v3
|
||||
with:
|
||||
registry: quay.io
|
||||
username: ${{ secrets.dockerUsername }}
|
||||
password: ${{ secrets.dockerPassword }}
|
||||
|
||||
- name: Build and push
|
||||
uses: docker/build-push-action@v5
|
||||
with:
|
||||
builder: ${{ steps.buildx.outputs.name }}
|
||||
build-args: |
|
||||
BUILD_TYPE=${{ inputs.build-type }}
|
||||
CUDA_MAJOR_VERSION=${{ inputs.cuda-major-version }}
|
||||
CUDA_MINOR_VERSION=${{ inputs.cuda-minor-version }}
|
||||
FFMPEG=${{ inputs.ffmpeg }}
|
||||
IMAGE_TYPE=${{ inputs.image-type }}
|
||||
context: .
|
||||
file: ./Dockerfile
|
||||
platforms: ${{ inputs.platforms }}
|
||||
push: ${{ github.event_name != 'pull_request' }}
|
||||
tags: ${{ steps.meta.outputs.tags }}
|
||||
labels: ${{ steps.meta.outputs.labels }}
|
||||
- name: job summary
|
||||
run: |
|
||||
echo "Built image: ${{ steps.meta.outputs.labels }}" >> $GITHUB_STEP_SUMMARY
|
||||
25
.github/workflows/release.yaml
vendored
25
.github/workflows/release.yaml
vendored
@@ -5,6 +5,10 @@ on: push
|
||||
permissions:
|
||||
contents: write
|
||||
|
||||
concurrency:
|
||||
group: ci-releases-${{ github.head_ref || github.ref }}-${{ github.repository }}
|
||||
cancel-in-progress: true
|
||||
|
||||
jobs:
|
||||
build-linux:
|
||||
strategy:
|
||||
@@ -19,13 +23,22 @@ jobs:
|
||||
runs-on: ubuntu-latest
|
||||
steps:
|
||||
- name: Clone
|
||||
uses: actions/checkout@v3
|
||||
uses: actions/checkout@v4
|
||||
with:
|
||||
submodules: true
|
||||
- uses: actions/setup-go@v4
|
||||
with:
|
||||
go-version: '>=1.21.0'
|
||||
- name: Dependencies
|
||||
run: |
|
||||
sudo apt-get update
|
||||
sudo apt-get install build-essential ffmpeg
|
||||
|
||||
git clone --recurse-submodules -b v1.58.0 --depth 1 --shallow-submodules https://github.com/grpc/grpc && \
|
||||
cd grpc && mkdir -p cmake/build && cd cmake/build && cmake -DgRPC_INSTALL=ON \
|
||||
-DgRPC_BUILD_TESTS=OFF \
|
||||
../.. && sudo make -j12 install
|
||||
|
||||
- name: Build
|
||||
id: build
|
||||
env:
|
||||
@@ -57,15 +70,23 @@ jobs:
|
||||
runs-on: macOS-latest
|
||||
steps:
|
||||
- name: Clone
|
||||
uses: actions/checkout@v3
|
||||
uses: actions/checkout@v4
|
||||
with:
|
||||
submodules: true
|
||||
- uses: actions/setup-go@v4
|
||||
with:
|
||||
go-version: '>=1.21.0'
|
||||
- name: Dependencies
|
||||
run: |
|
||||
brew install protobuf grpc
|
||||
- name: Build
|
||||
id: build
|
||||
env:
|
||||
CMAKE_ARGS: "${{ matrix.defines }}"
|
||||
BUILD_ID: "${{ matrix.build }}"
|
||||
run: |
|
||||
export C_INCLUDE_PATH=/usr/local/include
|
||||
export CPLUS_INCLUDE_PATH=/usr/local/include
|
||||
make dist
|
||||
- uses: actions/upload-artifact@v3
|
||||
with:
|
||||
|
||||
277
.github/workflows/test-extra.yml
vendored
Normal file
277
.github/workflows/test-extra.yml
vendored
Normal file
@@ -0,0 +1,277 @@
|
||||
---
|
||||
name: 'Tests extras backends'
|
||||
|
||||
on:
|
||||
pull_request:
|
||||
push:
|
||||
branches:
|
||||
- master
|
||||
tags:
|
||||
- '*'
|
||||
|
||||
concurrency:
|
||||
group: ci-tests-extra-${{ github.head_ref || github.ref }}-${{ github.repository }}
|
||||
cancel-in-progress: true
|
||||
|
||||
jobs:
|
||||
tests-transformers:
|
||||
runs-on: ubuntu-latest
|
||||
steps:
|
||||
- name: Clone
|
||||
uses: actions/checkout@v4
|
||||
with:
|
||||
submodules: true
|
||||
- name: Dependencies
|
||||
run: |
|
||||
sudo apt-get update
|
||||
sudo apt-get install build-essential ffmpeg
|
||||
curl https://repo.anaconda.com/pkgs/misc/gpgkeys/anaconda.asc | gpg --dearmor > conda.gpg && \
|
||||
sudo install -o root -g root -m 644 conda.gpg /usr/share/keyrings/conda-archive-keyring.gpg && \
|
||||
gpg --keyring /usr/share/keyrings/conda-archive-keyring.gpg --no-default-keyring --fingerprint 34161F5BF5EB1D4BFBBB8F0A8AEB4F8B29D82806 && \
|
||||
sudo /bin/bash -c 'echo "deb [arch=amd64 signed-by=/usr/share/keyrings/conda-archive-keyring.gpg] https://repo.anaconda.com/pkgs/misc/debrepo/conda stable main" > /etc/apt/sources.list.d/conda.list' && \
|
||||
sudo /bin/bash -c 'echo "deb [arch=amd64 signed-by=/usr/share/keyrings/conda-archive-keyring.gpg] https://repo.anaconda.com/pkgs/misc/debrepo/conda stable main" | tee -a /etc/apt/sources.list.d/conda.list' && \
|
||||
sudo apt-get update && \
|
||||
sudo apt-get install -y conda
|
||||
sudo apt-get install -y ca-certificates cmake curl patch
|
||||
sudo apt-get install -y libopencv-dev && sudo ln -s /usr/include/opencv4/opencv2 /usr/include/opencv2
|
||||
|
||||
sudo rm -rfv /usr/bin/conda || true
|
||||
|
||||
- name: Test transformers
|
||||
run: |
|
||||
export PATH=$PATH:/opt/conda/bin
|
||||
make -C backend/python/transformers
|
||||
make -C backend/python/transformers test
|
||||
|
||||
tests-sentencetransformers:
|
||||
runs-on: ubuntu-latest
|
||||
steps:
|
||||
- name: Clone
|
||||
uses: actions/checkout@v4
|
||||
with:
|
||||
submodules: true
|
||||
- name: Dependencies
|
||||
run: |
|
||||
sudo apt-get update
|
||||
sudo apt-get install build-essential ffmpeg
|
||||
curl https://repo.anaconda.com/pkgs/misc/gpgkeys/anaconda.asc | gpg --dearmor > conda.gpg && \
|
||||
sudo install -o root -g root -m 644 conda.gpg /usr/share/keyrings/conda-archive-keyring.gpg && \
|
||||
gpg --keyring /usr/share/keyrings/conda-archive-keyring.gpg --no-default-keyring --fingerprint 34161F5BF5EB1D4BFBBB8F0A8AEB4F8B29D82806 && \
|
||||
sudo /bin/bash -c 'echo "deb [arch=amd64 signed-by=/usr/share/keyrings/conda-archive-keyring.gpg] https://repo.anaconda.com/pkgs/misc/debrepo/conda stable main" > /etc/apt/sources.list.d/conda.list' && \
|
||||
sudo /bin/bash -c 'echo "deb [arch=amd64 signed-by=/usr/share/keyrings/conda-archive-keyring.gpg] https://repo.anaconda.com/pkgs/misc/debrepo/conda stable main" | tee -a /etc/apt/sources.list.d/conda.list' && \
|
||||
sudo apt-get update && \
|
||||
sudo apt-get install -y conda
|
||||
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 rm -rfv /usr/bin/conda || true
|
||||
|
||||
- name: Test sentencetransformers
|
||||
run: |
|
||||
export PATH=$PATH:/opt/conda/bin
|
||||
make -C backend/python/sentencetransformers
|
||||
make -C backend/python/sentencetransformers test
|
||||
|
||||
tests-diffusers:
|
||||
runs-on: ubuntu-latest
|
||||
steps:
|
||||
- name: Clone
|
||||
uses: actions/checkout@v4
|
||||
with:
|
||||
submodules: true
|
||||
- name: Dependencies
|
||||
run: |
|
||||
sudo apt-get update
|
||||
sudo apt-get install build-essential ffmpeg
|
||||
curl https://repo.anaconda.com/pkgs/misc/gpgkeys/anaconda.asc | gpg --dearmor > conda.gpg && \
|
||||
sudo install -o root -g root -m 644 conda.gpg /usr/share/keyrings/conda-archive-keyring.gpg && \
|
||||
gpg --keyring /usr/share/keyrings/conda-archive-keyring.gpg --no-default-keyring --fingerprint 34161F5BF5EB1D4BFBBB8F0A8AEB4F8B29D82806 && \
|
||||
sudo /bin/bash -c 'echo "deb [arch=amd64 signed-by=/usr/share/keyrings/conda-archive-keyring.gpg] https://repo.anaconda.com/pkgs/misc/debrepo/conda stable main" > /etc/apt/sources.list.d/conda.list' && \
|
||||
sudo /bin/bash -c 'echo "deb [arch=amd64 signed-by=/usr/share/keyrings/conda-archive-keyring.gpg] https://repo.anaconda.com/pkgs/misc/debrepo/conda stable main" | tee -a /etc/apt/sources.list.d/conda.list' && \
|
||||
sudo apt-get update && \
|
||||
sudo apt-get install -y conda
|
||||
sudo apt-get install -y ca-certificates cmake curl patch
|
||||
sudo apt-get install -y libopencv-dev && sudo ln -s /usr/include/opencv4/opencv2 /usr/include/opencv2
|
||||
|
||||
sudo rm -rfv /usr/bin/conda || true
|
||||
|
||||
- name: Test diffusers
|
||||
run: |
|
||||
export PATH=$PATH:/opt/conda/bin
|
||||
make -C backend/python/diffusers
|
||||
make -C backend/python/diffusers test
|
||||
|
||||
|
||||
tests-transformers-musicgen:
|
||||
runs-on: ubuntu-latest
|
||||
steps:
|
||||
- name: Clone
|
||||
uses: actions/checkout@v4
|
||||
with:
|
||||
submodules: true
|
||||
- name: Dependencies
|
||||
run: |
|
||||
sudo apt-get update
|
||||
sudo apt-get install build-essential ffmpeg
|
||||
curl https://repo.anaconda.com/pkgs/misc/gpgkeys/anaconda.asc | gpg --dearmor > conda.gpg && \
|
||||
sudo install -o root -g root -m 644 conda.gpg /usr/share/keyrings/conda-archive-keyring.gpg && \
|
||||
gpg --keyring /usr/share/keyrings/conda-archive-keyring.gpg --no-default-keyring --fingerprint 34161F5BF5EB1D4BFBBB8F0A8AEB4F8B29D82806 && \
|
||||
sudo /bin/bash -c 'echo "deb [arch=amd64 signed-by=/usr/share/keyrings/conda-archive-keyring.gpg] https://repo.anaconda.com/pkgs/misc/debrepo/conda stable main" > /etc/apt/sources.list.d/conda.list' && \
|
||||
sudo /bin/bash -c 'echo "deb [arch=amd64 signed-by=/usr/share/keyrings/conda-archive-keyring.gpg] https://repo.anaconda.com/pkgs/misc/debrepo/conda stable main" | tee -a /etc/apt/sources.list.d/conda.list' && \
|
||||
sudo apt-get update && \
|
||||
sudo apt-get install -y conda
|
||||
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 rm -rfv /usr/bin/conda || true
|
||||
|
||||
- name: Test transformers-musicgen
|
||||
run: |
|
||||
export PATH=$PATH:/opt/conda/bin
|
||||
make -C backend/python/transformers-musicgen
|
||||
make -C backend/python/transformers-musicgen test
|
||||
|
||||
|
||||
|
||||
tests-petals:
|
||||
runs-on: ubuntu-latest
|
||||
steps:
|
||||
- name: Clone
|
||||
uses: actions/checkout@v4
|
||||
with:
|
||||
submodules: true
|
||||
- name: Dependencies
|
||||
run: |
|
||||
sudo apt-get update
|
||||
sudo apt-get install build-essential ffmpeg
|
||||
curl https://repo.anaconda.com/pkgs/misc/gpgkeys/anaconda.asc | gpg --dearmor > conda.gpg && \
|
||||
sudo install -o root -g root -m 644 conda.gpg /usr/share/keyrings/conda-archive-keyring.gpg && \
|
||||
gpg --keyring /usr/share/keyrings/conda-archive-keyring.gpg --no-default-keyring --fingerprint 34161F5BF5EB1D4BFBBB8F0A8AEB4F8B29D82806 && \
|
||||
sudo /bin/bash -c 'echo "deb [arch=amd64 signed-by=/usr/share/keyrings/conda-archive-keyring.gpg] https://repo.anaconda.com/pkgs/misc/debrepo/conda stable main" > /etc/apt/sources.list.d/conda.list' && \
|
||||
sudo /bin/bash -c 'echo "deb [arch=amd64 signed-by=/usr/share/keyrings/conda-archive-keyring.gpg] https://repo.anaconda.com/pkgs/misc/debrepo/conda stable main" | tee -a /etc/apt/sources.list.d/conda.list' && \
|
||||
sudo apt-get update && \
|
||||
sudo apt-get install -y conda
|
||||
sudo apt-get install -y ca-certificates cmake curl patch
|
||||
sudo apt-get install -y libopencv-dev && sudo ln -s /usr/include/opencv4/opencv2 /usr/include/opencv2
|
||||
|
||||
sudo rm -rfv /usr/bin/conda || true
|
||||
|
||||
- name: Test petals
|
||||
run: |
|
||||
export PATH=$PATH:/opt/conda/bin
|
||||
make -C backend/python/petals
|
||||
make -C backend/python/petals test
|
||||
|
||||
|
||||
|
||||
tests-bark:
|
||||
runs-on: ubuntu-latest
|
||||
steps:
|
||||
- name: Clone
|
||||
uses: actions/checkout@v4
|
||||
with:
|
||||
submodules: true
|
||||
- name: Dependencies
|
||||
run: |
|
||||
sudo apt-get update
|
||||
sudo apt-get install build-essential ffmpeg
|
||||
curl https://repo.anaconda.com/pkgs/misc/gpgkeys/anaconda.asc | gpg --dearmor > conda.gpg && \
|
||||
sudo install -o root -g root -m 644 conda.gpg /usr/share/keyrings/conda-archive-keyring.gpg && \
|
||||
gpg --keyring /usr/share/keyrings/conda-archive-keyring.gpg --no-default-keyring --fingerprint 34161F5BF5EB1D4BFBBB8F0A8AEB4F8B29D82806 && \
|
||||
sudo /bin/bash -c 'echo "deb [arch=amd64 signed-by=/usr/share/keyrings/conda-archive-keyring.gpg] https://repo.anaconda.com/pkgs/misc/debrepo/conda stable main" > /etc/apt/sources.list.d/conda.list' && \
|
||||
sudo /bin/bash -c 'echo "deb [arch=amd64 signed-by=/usr/share/keyrings/conda-archive-keyring.gpg] https://repo.anaconda.com/pkgs/misc/debrepo/conda stable main" | tee -a /etc/apt/sources.list.d/conda.list' && \
|
||||
sudo apt-get update && \
|
||||
sudo apt-get install -y conda
|
||||
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 rm -rfv /usr/bin/conda || true
|
||||
|
||||
- name: Test bark
|
||||
run: |
|
||||
export PATH=$PATH:/opt/conda/bin
|
||||
make -C backend/python/bark
|
||||
make -C backend/python/bark test
|
||||
|
||||
|
||||
# Below tests needs GPU. Commented out for now
|
||||
# TODO: Re-enable as soon as we have GPU nodes
|
||||
# tests-vllm:
|
||||
# runs-on: ubuntu-latest
|
||||
# steps:
|
||||
# - name: Clone
|
||||
# uses: actions/checkout@v4
|
||||
# with:
|
||||
# submodules: true
|
||||
# - name: Dependencies
|
||||
# run: |
|
||||
# sudo apt-get update
|
||||
# sudo apt-get install build-essential ffmpeg
|
||||
# curl https://repo.anaconda.com/pkgs/misc/gpgkeys/anaconda.asc | gpg --dearmor > conda.gpg && \
|
||||
# sudo install -o root -g root -m 644 conda.gpg /usr/share/keyrings/conda-archive-keyring.gpg && \
|
||||
# gpg --keyring /usr/share/keyrings/conda-archive-keyring.gpg --no-default-keyring --fingerprint 34161F5BF5EB1D4BFBBB8F0A8AEB4F8B29D82806 && \
|
||||
# sudo /bin/bash -c 'echo "deb [arch=amd64 signed-by=/usr/share/keyrings/conda-archive-keyring.gpg] https://repo.anaconda.com/pkgs/misc/debrepo/conda stable main" > /etc/apt/sources.list.d/conda.list' && \
|
||||
# sudo /bin/bash -c 'echo "deb [arch=amd64 signed-by=/usr/share/keyrings/conda-archive-keyring.gpg] https://repo.anaconda.com/pkgs/misc/debrepo/conda stable main" | tee -a /etc/apt/sources.list.d/conda.list' && \
|
||||
# sudo apt-get update && \
|
||||
# sudo apt-get install -y conda
|
||||
# sudo apt-get install -y ca-certificates cmake curl patch
|
||||
# sudo apt-get install -y libopencv-dev && sudo ln -s /usr/include/opencv4/opencv2 /usr/include/opencv2
|
||||
# sudo rm -rfv /usr/bin/conda || true
|
||||
# - name: Test vllm
|
||||
# run: |
|
||||
# export PATH=$PATH:/opt/conda/bin
|
||||
# make -C backend/python/vllm
|
||||
# make -C backend/python/vllm test
|
||||
tests-vallex:
|
||||
runs-on: ubuntu-latest
|
||||
steps:
|
||||
- name: Clone
|
||||
uses: actions/checkout@v4
|
||||
with:
|
||||
submodules: true
|
||||
- name: Dependencies
|
||||
run: |
|
||||
sudo apt-get update
|
||||
sudo apt-get install build-essential ffmpeg
|
||||
curl https://repo.anaconda.com/pkgs/misc/gpgkeys/anaconda.asc | gpg --dearmor > conda.gpg && \
|
||||
sudo install -o root -g root -m 644 conda.gpg /usr/share/keyrings/conda-archive-keyring.gpg && \
|
||||
gpg --keyring /usr/share/keyrings/conda-archive-keyring.gpg --no-default-keyring --fingerprint 34161F5BF5EB1D4BFBBB8F0A8AEB4F8B29D82806 && \
|
||||
sudo /bin/bash -c 'echo "deb [arch=amd64 signed-by=/usr/share/keyrings/conda-archive-keyring.gpg] https://repo.anaconda.com/pkgs/misc/debrepo/conda stable main" > /etc/apt/sources.list.d/conda.list' && \
|
||||
sudo /bin/bash -c 'echo "deb [arch=amd64 signed-by=/usr/share/keyrings/conda-archive-keyring.gpg] https://repo.anaconda.com/pkgs/misc/debrepo/conda stable main" | tee -a /etc/apt/sources.list.d/conda.list' && \
|
||||
sudo apt-get update && \
|
||||
sudo apt-get install -y conda
|
||||
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 rm -rfv /usr/bin/conda || true
|
||||
- name: Test vall-e-x
|
||||
run: |
|
||||
export PATH=$PATH:/opt/conda/bin
|
||||
make -C backend/python/vall-e-x
|
||||
make -C backend/python/vall-e-x test
|
||||
|
||||
tests-coqui:
|
||||
runs-on: ubuntu-latest
|
||||
steps:
|
||||
- name: Clone
|
||||
uses: actions/checkout@v4
|
||||
with:
|
||||
submodules: true
|
||||
- name: Dependencies
|
||||
run: |
|
||||
sudo apt-get update
|
||||
sudo apt-get install build-essential ffmpeg
|
||||
curl https://repo.anaconda.com/pkgs/misc/gpgkeys/anaconda.asc | gpg --dearmor > conda.gpg && \
|
||||
sudo install -o root -g root -m 644 conda.gpg /usr/share/keyrings/conda-archive-keyring.gpg && \
|
||||
gpg --keyring /usr/share/keyrings/conda-archive-keyring.gpg --no-default-keyring --fingerprint 34161F5BF5EB1D4BFBBB8F0A8AEB4F8B29D82806 && \
|
||||
sudo /bin/bash -c 'echo "deb [arch=amd64 signed-by=/usr/share/keyrings/conda-archive-keyring.gpg] https://repo.anaconda.com/pkgs/misc/debrepo/conda stable main" > /etc/apt/sources.list.d/conda.list' && \
|
||||
sudo /bin/bash -c 'echo "deb [arch=amd64 signed-by=/usr/share/keyrings/conda-archive-keyring.gpg] https://repo.anaconda.com/pkgs/misc/debrepo/conda stable main" | tee -a /etc/apt/sources.list.d/conda.list' && \
|
||||
sudo apt-get update && \
|
||||
sudo apt-get install -y conda
|
||||
sudo apt-get install -y ca-certificates cmake curl patch espeak espeak-ng
|
||||
sudo rm -rfv /usr/bin/conda || true
|
||||
|
||||
- name: Test coqui
|
||||
run: |
|
||||
export PATH=$PATH:/opt/conda/bin
|
||||
make -C backend/python/coqui
|
||||
make -C backend/python/coqui test
|
||||
94
.github/workflows/test.yml
vendored
94
.github/workflows/test.yml
vendored
@@ -14,31 +14,109 @@ concurrency:
|
||||
cancel-in-progress: true
|
||||
|
||||
jobs:
|
||||
ubuntu-latest:
|
||||
tests-linux:
|
||||
runs-on: ubuntu-latest
|
||||
|
||||
strategy:
|
||||
matrix:
|
||||
go-version: ['1.21.x']
|
||||
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: Clone
|
||||
uses: actions/checkout@v3
|
||||
uses: actions/checkout@v4
|
||||
with:
|
||||
submodules: true
|
||||
- name: Setup Go ${{ matrix.go-version }}
|
||||
uses: actions/setup-go@v4
|
||||
with:
|
||||
go-version: ${{ matrix.go-version }}
|
||||
# You can test your matrix by printing the current Go version
|
||||
- name: Display Go version
|
||||
run: go version
|
||||
- name: Dependencies
|
||||
run: |
|
||||
sudo apt-get update
|
||||
sudo apt-get install build-essential ffmpeg
|
||||
curl https://repo.anaconda.com/pkgs/misc/gpgkeys/anaconda.asc | gpg --dearmor > conda.gpg && \
|
||||
sudo install -o root -g root -m 644 conda.gpg /usr/share/keyrings/conda-archive-keyring.gpg && \
|
||||
gpg --keyring /usr/share/keyrings/conda-archive-keyring.gpg --no-default-keyring --fingerprint 34161F5BF5EB1D4BFBBB8F0A8AEB4F8B29D82806 && \
|
||||
sudo /bin/bash -c 'echo "deb [arch=amd64 signed-by=/usr/share/keyrings/conda-archive-keyring.gpg] https://repo.anaconda.com/pkgs/misc/debrepo/conda stable main" > /etc/apt/sources.list.d/conda.list' && \
|
||||
sudo /bin/bash -c 'echo "deb [arch=amd64 signed-by=/usr/share/keyrings/conda-archive-keyring.gpg] https://repo.anaconda.com/pkgs/misc/debrepo/conda stable main" | tee -a /etc/apt/sources.list.d/conda.list' && \
|
||||
sudo apt-get update && \
|
||||
sudo apt-get install -y conda
|
||||
sudo apt-get install -y ca-certificates cmake curl patch
|
||||
sudo apt-get install -y libopencv-dev && sudo ln -s /usr/include/opencv4/opencv2 /usr/include/opencv2
|
||||
|
||||
sudo rm -rfv /usr/bin/conda || true
|
||||
PATH=$PATH:/opt/conda/bin make -C backend/python/sentencetransformers
|
||||
|
||||
# Pre-build piper before we start tests in order to have shared libraries in place
|
||||
make sources/go-piper && \
|
||||
GO_TAGS="tts" make -C sources/go-piper piper.o && \
|
||||
sudo cp -rfv sources/go-piper/piper-phonemize/pi/lib/. /usr/lib/ && \
|
||||
# Pre-build stable diffusion before we install a newer version of abseil (not compatible with stablediffusion-ncn)
|
||||
GO_TAGS="stablediffusion tts" GRPC_BACKENDS=backend-assets/grpc/stablediffusion make build
|
||||
|
||||
git clone --recurse-submodules -b v1.58.0 --depth 1 --shallow-submodules https://github.com/grpc/grpc && \
|
||||
cd grpc && mkdir -p cmake/build && cd cmake/build && cmake -DgRPC_INSTALL=ON \
|
||||
-DgRPC_BUILD_TESTS=OFF \
|
||||
../.. && sudo make -j12 install
|
||||
- name: Test
|
||||
run: |
|
||||
make test
|
||||
GO_TAGS="stablediffusion tts" make test
|
||||
|
||||
macOS-latest:
|
||||
tests-apple:
|
||||
runs-on: macOS-latest
|
||||
|
||||
strategy:
|
||||
matrix:
|
||||
go-version: ['1.21.x']
|
||||
steps:
|
||||
- name: Clone
|
||||
uses: actions/checkout@v3
|
||||
uses: actions/checkout@v4
|
||||
with:
|
||||
submodules: true
|
||||
|
||||
- name: Setup Go ${{ matrix.go-version }}
|
||||
uses: actions/setup-go@v4
|
||||
with:
|
||||
go-version: ${{ matrix.go-version }}
|
||||
# You can test your matrix by printing the current Go version
|
||||
- name: Display Go version
|
||||
run: go version
|
||||
- name: Dependencies
|
||||
run: |
|
||||
brew install protobuf grpc
|
||||
- name: Test
|
||||
run: |
|
||||
export C_INCLUDE_PATH=/usr/local/include
|
||||
export CPLUS_INCLUDE_PATH=/usr/local/include
|
||||
CMAKE_ARGS="-DLLAMA_F16C=OFF -DLLAMA_AVX512=OFF -DLLAMA_AVX2=OFF -DLLAMA_FMA=OFF" make test
|
||||
19
.gitignore
vendored
19
.gitignore
vendored
@@ -1,12 +1,17 @@
|
||||
# go-llama build artifacts
|
||||
go-llama
|
||||
gpt4all
|
||||
go-stable-diffusion
|
||||
/sources/
|
||||
__pycache__/
|
||||
*.a
|
||||
get-sources
|
||||
prepare-sources
|
||||
/backend/cpp/llama/grpc-server
|
||||
/backend/cpp/llama/llama.cpp
|
||||
|
||||
go-ggml-transformers
|
||||
go-gpt2
|
||||
go-rwkv
|
||||
whisper.cpp
|
||||
bloomz
|
||||
/bloomz
|
||||
go-bert
|
||||
|
||||
# LocalAI build binary
|
||||
@@ -14,6 +19,8 @@ LocalAI
|
||||
local-ai
|
||||
# prevent above rules from omitting the helm chart
|
||||
!charts/*
|
||||
# prevent above rules from omitting the api/localai folder
|
||||
!api/localai
|
||||
|
||||
# Ignore models
|
||||
models/*
|
||||
@@ -28,5 +35,5 @@ release/
|
||||
|
||||
# Generated during build
|
||||
backend-assets/
|
||||
|
||||
/ggml-metal.metal
|
||||
prepare
|
||||
/ggml-metal.metal
|
||||
|
||||
3
.gitmodules
vendored
Normal file
3
.gitmodules
vendored
Normal file
@@ -0,0 +1,3 @@
|
||||
[submodule "docs/themes/hugo-theme-relearn"]
|
||||
path = docs/themes/hugo-theme-relearn
|
||||
url = https://github.com/McShelby/hugo-theme-relearn.git
|
||||
72
CONTRIBUTING.md
Normal file
72
CONTRIBUTING.md
Normal file
@@ -0,0 +1,72 @@
|
||||
# Contributing to localAI
|
||||
|
||||
Thank you for your interest in contributing to LocalAI! We appreciate your time and effort in helping to improve our project. Before you get started, please take a moment to review these guidelines.
|
||||
|
||||
## Table of Contents
|
||||
|
||||
- [Getting Started](#getting-started)
|
||||
- [Prerequisites](#prerequisites)
|
||||
- [Setting up the Development Environment](#setting-up-the-development-environment)
|
||||
- [Contributing](#contributing)
|
||||
- [Submitting an Issue](#submitting-an-issue)
|
||||
- [Creating a Pull Request (PR)](#creating-a-pull-request-pr)
|
||||
- [Coding Guidelines](#coding-guidelines)
|
||||
- [Testing](#testing)
|
||||
- [Documentation](#documentation)
|
||||
- [Community and Communication](#community-and-communication)
|
||||
|
||||
|
||||
|
||||
## Getting Started
|
||||
|
||||
### Prerequisites
|
||||
|
||||
- Golang [1.21]
|
||||
- Git
|
||||
- macOS/Linux
|
||||
|
||||
### Setting up the Development Environment and running localAI in the local environment
|
||||
|
||||
1. Clone the repository: `git clone https://github.com/go-skynet/LocalAI.git`
|
||||
2. Navigate to the project directory: `cd LocalAI`
|
||||
3. Install the required dependencies: `make prepare`
|
||||
4. Run LocalAI: `make run`
|
||||
|
||||
## Contributing
|
||||
|
||||
We welcome contributions from everyone! To get started, follow these steps:
|
||||
|
||||
### Submitting an Issue
|
||||
|
||||
If you find a bug, have a feature request, or encounter any issues, please check the [issue tracker](https://github.com/go-skynet/LocalAI/issues) to see if a similar issue has already been reported. If not, feel free to [create a new issue](https://github.com/go-skynet/LocalAI/issues/new) and provide as much detail as possible.
|
||||
|
||||
### Creating a Pull Request (PR)
|
||||
|
||||
1. Fork the repository.
|
||||
2. Create a new branch with a descriptive name: `git checkout -b [branch name]`
|
||||
3. Make your changes and commit them.
|
||||
4. Push the changes to your fork: `git push origin [branch name]`
|
||||
5. Create a new pull request from your branch to the main project's `main` or `master` branch.
|
||||
6. Provide a clear description of your changes in the pull request.
|
||||
7. Make any requested changes during the review process.
|
||||
8. Once your PR is approved, it will be merged into the main project.
|
||||
|
||||
## Coding Guidelines
|
||||
|
||||
- No specific coding guidelines at the moment. Please make sure the code can be tested. The most popular lint tools like []`golangci-lint`](https://golangci-lint.run) can help you here.
|
||||
|
||||
## Testing
|
||||
|
||||
`make test` cannot handle all the model now. Please be sure to add a test case for the new features or the part was changed.
|
||||
|
||||
## Documentation
|
||||
|
||||
- We are welcome the contribution of the documents, please open new PR in the official document repo [localai-website](https://github.com/go-skynet/localai-website)
|
||||
|
||||
## Community and Communication
|
||||
|
||||
- You can reach out via the Github issue tracker.
|
||||
- Open a new discussion at [Discussion](https://github.com/go-skynet/LocalAI/discussions)
|
||||
- Join the Discord channel [Discord](https://discord.gg/uJAeKSAGDy)
|
||||
|
||||
---
|
||||
161
Dockerfile
161
Dockerfile
@@ -1,15 +1,33 @@
|
||||
ARG GO_VERSION=1.20-bullseye
|
||||
ARG GO_VERSION=1.21-bullseye
|
||||
ARG IMAGE_TYPE=extras
|
||||
# extras or core
|
||||
|
||||
FROM golang:$GO_VERSION as requirements
|
||||
|
||||
FROM golang:$GO_VERSION as requirements-core
|
||||
|
||||
ARG BUILD_TYPE
|
||||
ARG CUDA_MAJOR_VERSION=11
|
||||
ARG CUDA_MINOR_VERSION=7
|
||||
ARG TARGETARCH
|
||||
ARG TARGETVARIANT
|
||||
|
||||
ENV BUILD_TYPE=${BUILD_TYPE}
|
||||
|
||||
ENV EXTERNAL_GRPC_BACKENDS="coqui:/build/backend/python/coqui/run.sh,huggingface-embeddings:/build/backend/python/sentencetransformers/run.sh,petals:/build/backend/python/petals/run.sh,transformers:/build/backend/python/transformers/run.sh,sentencetransformers:/build/backend/python/sentencetransformers/run.sh,autogptq:/build/backend/python/autogptq/run.sh,bark:/build/backend/python/bark/run.sh,diffusers:/build/backend/python/diffusers/run.sh,exllama:/build/backend/python/exllama/run.sh,vall-e-x:/build/backend/python/vall-e-x/run.sh,vllm:/build/backend/python/vllm/run.sh,exllama2:/build/backend/python/exllama2/run.sh,transformers-musicgen:/build/backend/python/transformers-musicgen/run.sh"
|
||||
|
||||
ENV GALLERIES='[{"name":"model-gallery", "url":"github:go-skynet/model-gallery/index.yaml"}, {"url": "github:go-skynet/model-gallery/huggingface.yaml","name":"huggingface"}]'
|
||||
ARG GO_TAGS="stablediffusion tinydream tts"
|
||||
|
||||
RUN apt-get update && \
|
||||
apt-get install -y ca-certificates cmake curl patch
|
||||
apt-get install -y ca-certificates curl patch pip cmake && apt-get clean
|
||||
|
||||
|
||||
COPY --chmod=644 custom-ca-certs/* /usr/local/share/ca-certificates/
|
||||
RUN update-ca-certificates
|
||||
|
||||
# Use the variables in subsequent instructions
|
||||
RUN echo "Target Architecture: $TARGETARCH"
|
||||
RUN echo "Target Variant: $TARGETVARIANT"
|
||||
|
||||
# CuBLAS requirements
|
||||
RUN if [ "${BUILD_TYPE}" = "cublas" ]; then \
|
||||
@@ -19,21 +37,49 @@ RUN if [ "${BUILD_TYPE}" = "cublas" ]; then \
|
||||
dpkg -i cuda-keyring_1.0-1_all.deb && \
|
||||
rm -f cuda-keyring_1.0-1_all.deb && \
|
||||
apt-get update && \
|
||||
apt-get install -y cuda-nvcc-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} libcublas-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
|
||||
apt-get install -y cuda-nvcc-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} libcublas-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} libcusparse-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} libcusolver-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} && apt-get clean \
|
||||
; fi
|
||||
ENV PATH /usr/local/cuda/bin:${PATH}
|
||||
|
||||
# OpenBLAS requirements
|
||||
RUN apt-get install -y libopenblas-dev
|
||||
# OpenBLAS requirements and stable diffusion
|
||||
RUN apt-get install -y \
|
||||
libopenblas-dev \
|
||||
libopencv-dev \
|
||||
&& apt-get clean
|
||||
|
||||
# Stable Diffusion requirements
|
||||
RUN apt-get install -y libopencv-dev && \
|
||||
ln -s /usr/include/opencv4/opencv2 /usr/include/opencv2
|
||||
# Set up OpenCV
|
||||
RUN ln -s /usr/include/opencv4/opencv2 /usr/include/opencv2
|
||||
|
||||
FROM requirements as builder
|
||||
WORKDIR /build
|
||||
|
||||
ARG GO_TAGS=stablediffusion
|
||||
RUN test -n "$TARGETARCH" \
|
||||
|| (echo 'warn: missing $TARGETARCH, either set this `ARG` manually, or run using `docker buildkit`')
|
||||
|
||||
# Extras requirements
|
||||
FROM requirements-core as requirements-extras
|
||||
|
||||
RUN curl https://repo.anaconda.com/pkgs/misc/gpgkeys/anaconda.asc | gpg --dearmor > conda.gpg && \
|
||||
install -o root -g root -m 644 conda.gpg /usr/share/keyrings/conda-archive-keyring.gpg && \
|
||||
gpg --keyring /usr/share/keyrings/conda-archive-keyring.gpg --no-default-keyring --fingerprint 34161F5BF5EB1D4BFBBB8F0A8AEB4F8B29D82806 && \
|
||||
echo "deb [arch=amd64 signed-by=/usr/share/keyrings/conda-archive-keyring.gpg] https://repo.anaconda.com/pkgs/misc/debrepo/conda stable main" > /etc/apt/sources.list.d/conda.list && \
|
||||
echo "deb [arch=amd64 signed-by=/usr/share/keyrings/conda-archive-keyring.gpg] https://repo.anaconda.com/pkgs/misc/debrepo/conda stable main" | tee -a /etc/apt/sources.list.d/conda.list && \
|
||||
apt-get update && \
|
||||
apt-get install -y conda
|
||||
|
||||
ENV PATH="/root/.cargo/bin:${PATH}"
|
||||
RUN pip install --upgrade pip
|
||||
RUN curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh -s -- -y
|
||||
RUN apt-get install -y espeak-ng espeak
|
||||
|
||||
###################################
|
||||
###################################
|
||||
|
||||
FROM requirements-${IMAGE_TYPE} as builder
|
||||
|
||||
ARG GO_TAGS="stablediffusion tts"
|
||||
ARG GRPC_BACKENDS
|
||||
ARG BUILD_GRPC=true
|
||||
ENV GRPC_BACKENDS=${GRPC_BACKENDS}
|
||||
ENV GO_TAGS=${GO_TAGS}
|
||||
ENV NVIDIA_DRIVER_CAPABILITIES=compute,utility
|
||||
ENV NVIDIA_REQUIRE_CUDA="cuda>=${CUDA_MAJOR_VERSION}.0"
|
||||
@@ -42,15 +88,46 @@ ENV NVIDIA_VISIBLE_DEVICES=all
|
||||
WORKDIR /build
|
||||
|
||||
COPY . .
|
||||
COPY .git .
|
||||
RUN make prepare
|
||||
|
||||
# stablediffusion does not tolerate a newer version of abseil, build it first
|
||||
RUN GRPC_BACKENDS=backend-assets/grpc/stablediffusion make build
|
||||
|
||||
RUN if [ "${BUILD_GRPC}" = "true" ]; then \
|
||||
git clone --recurse-submodules -b v1.58.0 --depth 1 --shallow-submodules https://github.com/grpc/grpc && \
|
||||
cd grpc && mkdir -p cmake/build && cd cmake/build && cmake -DgRPC_INSTALL=ON \
|
||||
-DgRPC_BUILD_TESTS=OFF \
|
||||
../.. && make -j12 install \
|
||||
; fi
|
||||
|
||||
# Rebuild with defaults backends
|
||||
RUN make build
|
||||
|
||||
FROM requirements
|
||||
RUN if [ ! -d "/build/sources/go-piper/piper-phonemize/pi/lib/" ]; then \
|
||||
mkdir -p /build/sources/go-piper/piper-phonemize/pi/lib/ \
|
||||
touch /build/sources/go-piper/piper-phonemize/pi/lib/keep \
|
||||
; fi
|
||||
|
||||
###################################
|
||||
###################################
|
||||
|
||||
FROM requirements-${IMAGE_TYPE}
|
||||
|
||||
ARG FFMPEG
|
||||
ARG BUILD_TYPE
|
||||
ARG TARGETARCH
|
||||
ARG IMAGE_TYPE=extras
|
||||
|
||||
ENV REBUILD=true
|
||||
ENV BUILD_TYPE=${BUILD_TYPE}
|
||||
ENV REBUILD=false
|
||||
ENV HEALTHCHECK_ENDPOINT=http://localhost:8080/readyz
|
||||
|
||||
ARG CUDA_MAJOR_VERSION=11
|
||||
ENV NVIDIA_DRIVER_CAPABILITIES=compute,utility
|
||||
ENV NVIDIA_REQUIRE_CUDA="cuda>=${CUDA_MAJOR_VERSION}.0"
|
||||
ENV NVIDIA_VISIBLE_DEVICES=all
|
||||
|
||||
# Add FFmpeg
|
||||
RUN if [ "${FFMPEG}" = "true" ]; then \
|
||||
apt-get install -y ffmpeg \
|
||||
@@ -58,13 +135,67 @@ RUN if [ "${FFMPEG}" = "true" ]; then \
|
||||
|
||||
WORKDIR /build
|
||||
|
||||
# we start fresh & re-copy all assets because `make build` does not clean up nicely after itself
|
||||
# so when `entrypoint.sh` runs `make build` again (which it does by default), the build would fail
|
||||
# see https://github.com/go-skynet/LocalAI/pull/658#discussion_r1241971626 and
|
||||
# https://github.com/go-skynet/LocalAI/pull/434
|
||||
COPY . .
|
||||
RUN make prepare-sources
|
||||
|
||||
COPY --from=builder /build/sources ./sources/
|
||||
COPY --from=builder /build/grpc ./grpc/
|
||||
|
||||
RUN make prepare-sources && cd /build/grpc/cmake/build && make install && rm -rf grpc
|
||||
|
||||
# Copy the binary
|
||||
COPY --from=builder /build/local-ai ./
|
||||
|
||||
# Copy shared libraries for piper
|
||||
COPY --from=builder /build/sources/go-piper/piper-phonemize/pi/lib/* /usr/lib/
|
||||
|
||||
# do not let stablediffusion rebuild (requires an older version of absl)
|
||||
COPY --from=builder /build/backend-assets/grpc/stablediffusion ./backend-assets/grpc/stablediffusion
|
||||
|
||||
## Duplicated from Makefile to avoid having a big layer that's hard to push
|
||||
RUN if [ "${IMAGE_TYPE}" = "extras" ]; then \
|
||||
PATH=$PATH:/opt/conda/bin make -C backend/python/autogptq \
|
||||
; fi
|
||||
RUN if [ "${IMAGE_TYPE}" = "extras" ]; then \
|
||||
PATH=$PATH:/opt/conda/bin make -C backend/python/bark \
|
||||
; fi
|
||||
RUN if [ "${IMAGE_TYPE}" = "extras" ]; then \
|
||||
PATH=$PATH:/opt/conda/bin make -C backend/python/diffusers \
|
||||
; fi
|
||||
RUN if [ "${IMAGE_TYPE}" = "extras" ]; then \
|
||||
PATH=$PATH:/opt/conda/bin make -C backend/python/vllm \
|
||||
; fi
|
||||
RUN if [ "${IMAGE_TYPE}" = "extras" ]; then \
|
||||
PATH=$PATH:/opt/conda/bin make -C backend/python/sentencetransformers \
|
||||
; fi
|
||||
RUN if [ "${IMAGE_TYPE}" = "extras" ]; then \
|
||||
PATH=$PATH:/opt/conda/bin make -C backend/python/transformers \
|
||||
; fi
|
||||
RUN if [ "${IMAGE_TYPE}" = "extras" ]; then \
|
||||
PATH=$PATH:/opt/conda/bin make -C backend/python/vall-e-x \
|
||||
; fi
|
||||
RUN if [ "${IMAGE_TYPE}" = "extras" ]; then \
|
||||
PATH=$PATH:/opt/conda/bin make -C backend/python/exllama \
|
||||
; fi
|
||||
RUN if [ "${IMAGE_TYPE}" = "extras" ]; then \
|
||||
PATH=$PATH:/opt/conda/bin make -C backend/python/exllama2 \
|
||||
; fi
|
||||
RUN if [ "${IMAGE_TYPE}" = "extras" ]; then \
|
||||
PATH=$PATH:/opt/conda/bin make -C backend/python/petals \
|
||||
; fi
|
||||
RUN if [ "${IMAGE_TYPE}" = "extras" ]; then \
|
||||
PATH=$PATH:/opt/conda/bin make -C backend/python/transformers-musicgen \
|
||||
; fi
|
||||
RUN if [ "${IMAGE_TYPE}" = "extras" ]; then \
|
||||
PATH=$PATH:/opt/conda/bin make -C backend/python/coqui \
|
||||
; fi
|
||||
|
||||
# Define the health check command
|
||||
HEALTHCHECK --interval=1m --timeout=10m --retries=10 \
|
||||
CMD curl -f $HEALTHCHECK_ENDPOINT || exit 1
|
||||
|
||||
EXPOSE 8080
|
||||
ENTRYPOINT [ "/build/entrypoint.sh" ]
|
||||
ENTRYPOINT [ "/build/entrypoint.sh" ]
|
||||
|
||||
10
Entitlements.plist
Normal file
10
Entitlements.plist
Normal file
@@ -0,0 +1,10 @@
|
||||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<!DOCTYPE plist PUBLIC "-//Apple//DTD PLIST 1.0//EN" "http://www.apple.com/DTDs/PropertyList-1.0.dtd">
|
||||
<plist version="1.0">
|
||||
<dict>
|
||||
<key>com.apple.security.network.client</key>
|
||||
<true/>
|
||||
<key>com.apple.security.network.server</key>
|
||||
<true/>
|
||||
</dict>
|
||||
</plist>
|
||||
588
Makefile
588
Makefile
@@ -3,22 +3,58 @@ GOTEST=$(GOCMD) test
|
||||
GOVET=$(GOCMD) vet
|
||||
BINARY_NAME=local-ai
|
||||
|
||||
GOLLAMA_VERSION?=7ad833b67070fd3ec46d838f5e38d21111013f98
|
||||
# llama.cpp versions
|
||||
GOLLAMA_VERSION?=aeba71ee842819da681ea537e78846dc75949ac0
|
||||
|
||||
GOLLAMA_STABLE_VERSION?=50cee7712066d9e38306eccadcfbb44ea87df4b7
|
||||
|
||||
CPPLLAMA_VERSION?=65e5f6dadbba4b496bba27f573e473c66b446496
|
||||
|
||||
# gpt4all version
|
||||
GPT4ALL_REPO?=https://github.com/nomic-ai/gpt4all
|
||||
GPT4ALL_VERSION?=2b6cc99a31a124f1f27f2dc6515b94b84d35b254
|
||||
GOGGMLTRANSFORMERS_VERSION?=661669258dd0a752f3f3607358b168bc1d928135
|
||||
GPT4ALL_VERSION?=27a8b020c36b0df8f8b82a252d261cda47cf44b8
|
||||
|
||||
# go-ggml-transformers version
|
||||
GOGGMLTRANSFORMERS_VERSION?=ffb09d7dd71e2cbc6c5d7d05357d230eea6f369a
|
||||
|
||||
# go-rwkv version
|
||||
RWKV_REPO?=https://github.com/donomii/go-rwkv.cpp
|
||||
RWKV_VERSION?=930a774fa0152426ed2279cb1005b3490bb0eba6
|
||||
WHISPER_CPP_VERSION?=57543c169e27312e7546d07ed0d8c6eb806ebc36
|
||||
BERT_VERSION?=6069103f54b9969c02e789d0fb12a23bd614285f
|
||||
BLOOMZ_VERSION?=1834e77b83faafe912ad4092ccf7f77937349e2f
|
||||
RWKV_VERSION?=633c5a3485c403cb2520693dc0991a25dace9f0f
|
||||
|
||||
# whisper.cpp version
|
||||
WHISPER_CPP_VERSION?=37a709f6558c6d9783199e2b8cbb136e1c41d346
|
||||
|
||||
# bert.cpp version
|
||||
BERT_VERSION?=6abe312cded14042f6b7c3cd8edf082713334a4d
|
||||
|
||||
# go-piper version
|
||||
PIPER_VERSION?=d6b6275ba037dabdba4a8b65dfdf6b2a73a67f07
|
||||
|
||||
# stablediffusion version
|
||||
STABLEDIFFUSION_VERSION?=902db5f066fd137697e3b69d0fa10d4782bd2c2f
|
||||
|
||||
# tinydream version
|
||||
TINYDREAM_VERSION?=772a9c0d9aaf768290e63cca3c904fe69faf677a
|
||||
|
||||
export BUILD_TYPE?=
|
||||
export STABLE_BUILD_TYPE?=$(BUILD_TYPE)
|
||||
export CMAKE_ARGS?=
|
||||
|
||||
CGO_LDFLAGS?=
|
||||
CUDA_LIBPATH?=/usr/local/cuda/lib64/
|
||||
STABLEDIFFUSION_VERSION?=d89260f598afb809279bc72aa0107b4292587632
|
||||
GO_TAGS?=
|
||||
BUILD_ID?=git
|
||||
LD_FLAGS=?=
|
||||
|
||||
TEST_DIR=/tmp/test
|
||||
|
||||
RANDOM := $(shell bash -c 'echo $$RANDOM')
|
||||
|
||||
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?=
|
||||
|
||||
OS := $(shell uname -s)
|
||||
@@ -29,25 +65,61 @@ WHITE := $(shell tput -Txterm setaf 7)
|
||||
CYAN := $(shell tput -Txterm setaf 6)
|
||||
RESET := $(shell tput -Txterm sgr0)
|
||||
|
||||
C_INCLUDE_PATH=$(shell pwd)/go-llama:$(shell pwd)/go-stable-diffusion/:$(shell pwd)/gpt4all/gpt4all-bindings/golang/:$(shell pwd)/go-ggml-transformers:$(shell pwd)/go-rwkv:$(shell pwd)/whisper.cpp:$(shell pwd)/go-bert:$(shell pwd)/bloomz
|
||||
LIBRARY_PATH=$(shell pwd)/go-llama:$(shell pwd)/go-stable-diffusion/:$(shell pwd)/gpt4all/gpt4all-bindings/golang/:$(shell pwd)/go-ggml-transformers:$(shell pwd)/go-rwkv:$(shell pwd)/whisper.cpp:$(shell pwd)/go-bert:$(shell pwd)/bloomz
|
||||
# Default Docker bridge IP
|
||||
E2E_BRIDGE_IP?=172.17.0.1
|
||||
|
||||
ifndef UNAME_S
|
||||
UNAME_S := $(shell uname -s)
|
||||
endif
|
||||
|
||||
ifeq ($(OS),Darwin)
|
||||
CGO_LDFLAGS += -lcblas -framework Accelerate
|
||||
ifeq ($(OSX_SIGNING_IDENTITY),)
|
||||
OSX_SIGNING_IDENTITY := $(shell security find-identity -v -p codesigning | grep '"' | head -n 1 | sed -E 's/.*"(.*)"/\1/')
|
||||
endif
|
||||
|
||||
# on OSX, if BUILD_TYPE is blank, we should default to use Metal
|
||||
ifeq ($(BUILD_TYPE),)
|
||||
BUILD_TYPE=metal
|
||||
# disable metal if on Darwin and any other value is explicitly passed.
|
||||
else ifneq ($(BUILD_TYPE),metal)
|
||||
CMAKE_ARGS+=-DLLAMA_METAL=OFF
|
||||
endif
|
||||
endif
|
||||
|
||||
ifeq ($(BUILD_TYPE),openblas)
|
||||
CGO_LDFLAGS+=-lopenblas
|
||||
export WHISPER_OPENBLAS=1
|
||||
endif
|
||||
|
||||
ifeq ($(BUILD_TYPE),cublas)
|
||||
CGO_LDFLAGS+=-lcublas -lcudart -L$(CUDA_LIBPATH)
|
||||
export LLAMA_CUBLAS=1
|
||||
export WHISPER_CUBLAS=1
|
||||
endif
|
||||
|
||||
ifeq ($(BUILD_TYPE),hipblas)
|
||||
ROCM_HOME ?= /opt/rocm
|
||||
export CXX=$(ROCM_HOME)/llvm/bin/clang++
|
||||
export CC=$(ROCM_HOME)/llvm/bin/clang
|
||||
# llama-ggml has no hipblas support, so override it here.
|
||||
export STABLE_BUILD_TYPE=
|
||||
export WHISPER_HIPBLAS=1
|
||||
GPU_TARGETS ?= gfx900,gfx90a,gfx1030,gfx1031,gfx1100
|
||||
AMDGPU_TARGETS ?= "$(GPU_TARGETS)"
|
||||
CMAKE_ARGS+=-DLLAMA_HIPBLAS=ON -DAMDGPU_TARGETS="$(AMDGPU_TARGETS)" -DGPU_TARGETS="$(GPU_TARGETS)"
|
||||
CGO_LDFLAGS += -O3 --rtlib=compiler-rt -unwindlib=libgcc -lhipblas -lrocblas --hip-link
|
||||
endif
|
||||
|
||||
ifeq ($(BUILD_TYPE),metal)
|
||||
CGO_LDFLAGS+=-framework Foundation -framework Metal -framework MetalKit -framework MetalPerformanceShaders
|
||||
export LLAMA_METAL=1
|
||||
export WHISPER_METAL=1
|
||||
endif
|
||||
|
||||
ifeq ($(BUILD_TYPE),clblas)
|
||||
CGO_LDFLAGS+=-lOpenCL -lclblast
|
||||
export WHISPER_CLBLAST=1
|
||||
endif
|
||||
|
||||
# glibc-static or glibc-devel-static required
|
||||
@@ -55,8 +127,30 @@ ifeq ($(STATIC),true)
|
||||
LD_FLAGS=-linkmode external -extldflags -static
|
||||
endif
|
||||
|
||||
ifeq ($(GO_TAGS),stablediffusion)
|
||||
OPTIONAL_TARGETS+=go-stable-diffusion/libstablediffusion.a
|
||||
ifeq ($(findstring stablediffusion,$(GO_TAGS)),stablediffusion)
|
||||
# OPTIONAL_TARGETS+=go-stable-diffusion/libstablediffusion.a
|
||||
OPTIONAL_GRPC+=backend-assets/grpc/stablediffusion
|
||||
endif
|
||||
|
||||
ifeq ($(findstring tinydream,$(GO_TAGS)),tinydream)
|
||||
# OPTIONAL_TARGETS+=go-tiny-dream/libtinydream.a
|
||||
OPTIONAL_GRPC+=backend-assets/grpc/tinydream
|
||||
endif
|
||||
|
||||
ifeq ($(findstring tts,$(GO_TAGS)),tts)
|
||||
# OPTIONAL_TARGETS+=go-piper/libpiper_binding.a
|
||||
# OPTIONAL_TARGETS+=backend-assets/espeak-ng-data
|
||||
PIPER_CGO_CXXFLAGS+=-I$(shell pwd)/sources/go-piper/piper/src/cpp -I$(shell pwd)/sources/go-piper/piper/build/fi/include -I$(shell pwd)/sources/go-piper/piper/build/pi/include -I$(shell pwd)/sources/go-piper/piper/build/si/include
|
||||
PIPER_CGO_LDFLAGS+=-L$(shell pwd)/sources/go-piper/piper/build/fi/lib -L$(shell pwd)/sources/go-piper/piper/build/pi/lib -L$(shell pwd)/sources/go-piper/piper/build/si/lib -lfmt -lspdlog -lucd
|
||||
OPTIONAL_GRPC+=backend-assets/grpc/piper
|
||||
endif
|
||||
|
||||
ALL_GRPC_BACKENDS=backend-assets/grpc/langchain-huggingface backend-assets/grpc/falcon-ggml backend-assets/grpc/bert-embeddings backend-assets/grpc/llama backend-assets/grpc/llama-cpp backend-assets/grpc/llama-ggml 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)
|
||||
GRPC_BACKENDS?=$(ALL_GRPC_BACKENDS) $(OPTIONAL_GRPC)
|
||||
|
||||
# If empty, then we build all
|
||||
ifeq ($(GRPC_BACKENDS),)
|
||||
GRPC_BACKENDS=$(ALL_GRPC_BACKENDS)
|
||||
endif
|
||||
|
||||
.PHONY: all test build vendor
|
||||
@@ -64,194 +158,234 @@ endif
|
||||
all: help
|
||||
|
||||
## GPT4ALL
|
||||
gpt4all:
|
||||
git clone --recurse-submodules $(GPT4ALL_REPO) gpt4all
|
||||
cd gpt4all && git checkout -b build $(GPT4ALL_VERSION) && git submodule update --init --recursive --depth 1
|
||||
# This is hackish, but needed as both go-llama and go-gpt4allj have their own version of ggml..
|
||||
@find ./gpt4all -type f -name "*.c" -exec sed -i'' -e 's/ggml_/ggml_gpt4all_/g' {} +
|
||||
@find ./gpt4all -type f -name "*.cpp" -exec sed -i'' -e 's/ggml_/ggml_gpt4all_/g' {} +
|
||||
@find ./gpt4all -type f -name "*.m" -exec sed -i'' -e 's/ggml_/ggml_gpt4all_/g' {} +
|
||||
@find ./gpt4all -type f -name "*.h" -exec sed -i'' -e 's/ggml_/ggml_gpt4all_/g' {} +
|
||||
@find ./gpt4all -type f -name "*.c" -exec sed -i'' -e 's/llama_/llama_gpt4all_/g' {} +
|
||||
@find ./gpt4all -type f -name "*.cpp" -exec sed -i'' -e 's/llama_/llama_gpt4all_/g' {} +
|
||||
@find ./gpt4all -type f -name "*.h" -exec sed -i'' -e 's/llama_/llama_gpt4all_/g' {} +
|
||||
@find ./gpt4all/gpt4all-backend -type f -name "llama_util.h" -execdir mv {} "llama_gpt4all_util.h" \;
|
||||
@find ./gpt4all -type f -name "*.cmake" -exec sed -i'' -e 's/llama_util/llama_gpt4all_util/g' {} +
|
||||
@find ./gpt4all -type f -name "*.txt" -exec sed -i'' -e 's/llama_util/llama_gpt4all_util/g' {} +
|
||||
@find ./gpt4all/gpt4all-bindings/golang -type f -name "*.cpp" -exec sed -i'' -e 's/load_model/load_gpt4all_model/g' {} +
|
||||
@find ./gpt4all/gpt4all-bindings/golang -type f -name "*.go" -exec sed -i'' -e 's/load_model/load_gpt4all_model/g' {} +
|
||||
@find ./gpt4all/gpt4all-bindings/golang -type f -name "*.h" -exec sed -i'' -e 's/load_model/load_gpt4all_model/g' {} +
|
||||
sources/gpt4all:
|
||||
git clone --recurse-submodules $(GPT4ALL_REPO) sources/gpt4all
|
||||
cd sources/gpt4all && git checkout -b build $(GPT4ALL_VERSION) && git submodule update --init --recursive --depth 1
|
||||
|
||||
## go-piper
|
||||
sources/go-piper:
|
||||
git clone --recurse-submodules https://github.com/mudler/go-piper sources/go-piper
|
||||
cd sources/go-piper && git checkout -b build $(PIPER_VERSION) && git submodule update --init --recursive --depth 1
|
||||
|
||||
## BERT embeddings
|
||||
go-bert:
|
||||
git clone --recurse-submodules https://github.com/go-skynet/go-bert.cpp go-bert
|
||||
cd go-bert && git checkout -b build $(BERT_VERSION) && git submodule update --init --recursive --depth 1
|
||||
@find ./go-bert -type f -name "*.c" -exec sed -i'' -e 's/ggml_/ggml_bert_/g' {} +
|
||||
@find ./go-bert -type f -name "*.cpp" -exec sed -i'' -e 's/ggml_/ggml_bert_/g' {} +
|
||||
@find ./go-bert -type f -name "*.h" -exec sed -i'' -e 's/ggml_/ggml_bert_/g' {} +
|
||||
sources/go-bert:
|
||||
git clone --recurse-submodules https://github.com/go-skynet/go-bert.cpp sources/go-bert
|
||||
cd sources/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
|
||||
sources/go-stable-diffusion:
|
||||
git clone --recurse-submodules https://github.com/mudler/go-stable-diffusion sources/go-stable-diffusion
|
||||
cd sources/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
|
||||
sources/go-stable-diffusion/libstablediffusion.a:
|
||||
$(MAKE) -C sources/go-stable-diffusion libstablediffusion.a
|
||||
|
||||
## tiny-dream
|
||||
sources/go-tiny-dream:
|
||||
git clone --recurse-submodules https://github.com/M0Rf30/go-tiny-dream sources/go-tiny-dream
|
||||
cd sources/go-tiny-dream && git checkout -b build $(TINYDREAM_VERSION) && git submodule update --init --recursive --depth 1
|
||||
|
||||
sources/go-tiny-dream/libtinydream.a:
|
||||
$(MAKE) -C sources/go-tiny-dream libtinydream.a
|
||||
|
||||
## RWKV
|
||||
go-rwkv:
|
||||
git clone --recurse-submodules $(RWKV_REPO) go-rwkv
|
||||
cd go-rwkv && git checkout -b build $(RWKV_VERSION) && git submodule update --init --recursive --depth 1
|
||||
@find ./go-rwkv -type f -name "*.c" -exec sed -i'' -e 's/ggml_/ggml_rwkv_/g' {} +
|
||||
@find ./go-rwkv -type f -name "*.cpp" -exec sed -i'' -e 's/ggml_/ggml_rwkv_/g' {} +
|
||||
@find ./go-rwkv -type f -name "*.h" -exec sed -i'' -e 's/ggml_/ggml_rwkv_/g' {} +
|
||||
sources/go-rwkv:
|
||||
git clone --recurse-submodules $(RWKV_REPO) sources/go-rwkv
|
||||
cd sources/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 ..
|
||||
sources/go-rwkv/librwkv.a: sources/go-rwkv
|
||||
cd sources/go-rwkv && cd rwkv.cpp && cmake . -DRWKV_BUILD_SHARED_LIBRARY=OFF && cmake --build . && cp librwkv.a ..
|
||||
|
||||
## bloomz
|
||||
bloomz:
|
||||
git clone --recurse-submodules https://github.com/go-skynet/bloomz.cpp bloomz
|
||||
@find ./bloomz -type f -name "*.c" -exec sed -i'' -e 's/ggml_/ggml_bloomz_/g' {} +
|
||||
@find ./bloomz -type f -name "*.cpp" -exec sed -i'' -e 's/ggml_/ggml_bloomz_/g' {} +
|
||||
@find ./bloomz -type f -name "*.h" -exec sed -i'' -e 's/ggml_/ggml_bloomz_/g' {} +
|
||||
@find ./bloomz -type f -name "*.cpp" -exec sed -i'' -e 's/gpt_/gpt_bloomz_/g' {} +
|
||||
@find ./bloomz -type f -name "*.h" -exec sed -i'' -e 's/gpt_/gpt_bloomz_/g' {} +
|
||||
@find ./bloomz -type f -name "*.cpp" -exec sed -i'' -e 's/void replace/void json_bloomz_replace/g' {} +
|
||||
@find ./bloomz -type f -name "*.cpp" -exec sed -i'' -e 's/::replace/::json_bloomz_replace/g' {} +
|
||||
sources/go-bert/libgobert.a: sources/go-bert
|
||||
$(MAKE) -C sources/go-bert libgobert.a
|
||||
|
||||
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
|
||||
backend-assets/gpt4all: sources/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
|
||||
@cp sources/gpt4all/gpt4all-bindings/golang/buildllm/*.so backend-assets/gpt4all/ || true
|
||||
@cp sources/gpt4all/gpt4all-bindings/golang/buildllm/*.dylib backend-assets/gpt4all/ || true
|
||||
@cp sources/gpt4all/gpt4all-bindings/golang/buildllm/*.dll backend-assets/gpt4all/ || true
|
||||
|
||||
gpt4all/gpt4all-bindings/golang/libgpt4all.a: gpt4all
|
||||
$(MAKE) -C gpt4all/gpt4all-bindings/golang/ libgpt4all.a
|
||||
backend-assets/espeak-ng-data: sources/go-piper
|
||||
mkdir -p backend-assets/espeak-ng-data
|
||||
$(MAKE) -C sources/go-piper piper.o
|
||||
@cp -rf sources/go-piper/piper-phonemize/pi/share/espeak-ng-data/. backend-assets/espeak-ng-data
|
||||
|
||||
sources/gpt4all/gpt4all-bindings/golang/libgpt4all.a: sources/gpt4all
|
||||
$(MAKE) -C sources/gpt4all/gpt4all-bindings/golang/ libgpt4all.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
|
||||
# This is hackish, but needed as both go-llama and go-gpt4allj have their own version of ggml..
|
||||
@find ./go-ggml-transformers -type f -name "*.c" -exec sed -i'' -e 's/ggml_/ggml_gpt2_/g' {} +
|
||||
@find ./go-ggml-transformers -type f -name "*.cpp" -exec sed -i'' -e 's/ggml_/ggml_gpt2_/g' {} +
|
||||
@find ./go-ggml-transformers -type f -name "*.h" -exec sed -i'' -e 's/ggml_/ggml_gpt2_/g' {} +
|
||||
@find ./go-ggml-transformers -type f -name "*.cpp" -exec sed -i'' -e 's/gpt_print_usage/gpt2_print_usage/g' {} +
|
||||
@find ./go-ggml-transformers -type f -name "*.h" -exec sed -i'' -e 's/gpt_print_usage/gpt2_print_usage/g' {} +
|
||||
@find ./go-ggml-transformers -type f -name "*.cpp" -exec sed -i'' -e 's/gpt_params_parse/gpt2_params_parse/g' {} +
|
||||
@find ./go-ggml-transformers -type f -name "*.h" -exec sed -i'' -e 's/gpt_params_parse/gpt2_params_parse/g' {} +
|
||||
@find ./go-ggml-transformers -type f -name "*.cpp" -exec sed -i'' -e 's/gpt_random_prompt/gpt2_random_prompt/g' {} +
|
||||
@find ./go-ggml-transformers -type f -name "*.h" -exec sed -i'' -e 's/gpt_random_prompt/gpt2_random_prompt/g' {} +
|
||||
@find ./go-ggml-transformers -type f -name "*.cpp" -exec sed -i'' -e 's/json_/json_gpt2_/g' {} +
|
||||
sources/go-ggml-transformers:
|
||||
git clone --recurse-submodules https://github.com/go-skynet/go-ggml-transformers.cpp sources/go-ggml-transformers
|
||||
cd sources/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 libtransformers.a
|
||||
sources/go-ggml-transformers/libtransformers.a: sources/go-ggml-transformers
|
||||
$(MAKE) -C sources/go-ggml-transformers BUILD_TYPE=$(BUILD_TYPE) libtransformers.a
|
||||
|
||||
whisper.cpp:
|
||||
git clone https://github.com/ggerganov/whisper.cpp.git
|
||||
cd whisper.cpp && git checkout -b build $(WHISPER_CPP_VERSION) && git submodule update --init --recursive --depth 1
|
||||
@find ./whisper.cpp -type f -name "*.c" -exec sed -i'' -e 's/ggml_/ggml_whisper_/g' {} +
|
||||
@find ./whisper.cpp -type f -name "*.cpp" -exec sed -i'' -e 's/ggml_/ggml_whisper_/g' {} +
|
||||
@find ./whisper.cpp -type f -name "*.h" -exec sed -i'' -e 's/ggml_/ggml_whisper_/g' {} +
|
||||
sources/whisper.cpp:
|
||||
git clone https://github.com/ggerganov/whisper.cpp.git sources/whisper.cpp
|
||||
cd sources/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
|
||||
sources/whisper.cpp/libwhisper.a: sources/whisper.cpp
|
||||
cd sources/whisper.cpp && make libwhisper.a
|
||||
|
||||
go-llama:
|
||||
git clone --recurse-submodules https://github.com/go-skynet/go-llama.cpp go-llama
|
||||
cd go-llama && git checkout -b build $(GOLLAMA_VERSION) && git submodule update --init --recursive --depth 1
|
||||
sources/go-llama:
|
||||
git clone --recurse-submodules https://github.com/go-skynet/go-llama.cpp sources/go-llama
|
||||
cd sources/go-llama && git checkout -b build $(GOLLAMA_VERSION) && git submodule update --init --recursive --depth 1
|
||||
|
||||
go-llama/libbinding.a: go-llama
|
||||
$(MAKE) -C go-llama BUILD_TYPE=$(BUILD_TYPE) libbinding.a
|
||||
sources/go-llama-ggml:
|
||||
git clone --recurse-submodules https://github.com/go-skynet/go-llama.cpp sources/go-llama-ggml
|
||||
cd sources/go-llama-ggml && git checkout -b build $(GOLLAMA_STABLE_VERSION) && git submodule update --init --recursive --depth 1
|
||||
|
||||
sources/go-llama/libbinding.a: sources/go-llama
|
||||
$(MAKE) -C sources/go-llama BUILD_TYPE=$(BUILD_TYPE) libbinding.a
|
||||
|
||||
sources/go-llama-ggml/libbinding.a: sources/go-llama-ggml
|
||||
$(MAKE) -C sources/go-llama-ggml BUILD_TYPE=$(STABLE_BUILD_TYPE) libbinding.a
|
||||
|
||||
sources/go-piper/libpiper_binding.a: sources/go-piper
|
||||
$(MAKE) -C sources/go-piper libpiper_binding.a example/main
|
||||
|
||||
backend/cpp/llama/llama.cpp:
|
||||
LLAMA_VERSION=$(CPPLLAMA_VERSION) $(MAKE) -C backend/cpp/llama llama.cpp
|
||||
|
||||
get-sources: backend/cpp/llama/llama.cpp sources/go-llama sources/go-llama-ggml sources/go-ggml-transformers sources/gpt4all sources/go-piper sources/go-rwkv sources/whisper.cpp sources/go-bert sources/go-stable-diffusion sources/go-tiny-dream
|
||||
touch $@
|
||||
|
||||
replace:
|
||||
$(GOCMD) mod edit -replace github.com/go-skynet/go-llama.cpp=$(shell pwd)/go-llama
|
||||
$(GOCMD) mod edit -replace github.com/nomic-ai/gpt4all/gpt4all-bindings/golang=$(shell pwd)/gpt4all/gpt4all-bindings/golang
|
||||
$(GOCMD) mod edit -replace github.com/go-skynet/go-ggml-transformers.cpp=$(shell pwd)/go-ggml-transformers
|
||||
$(GOCMD) mod edit -replace github.com/donomii/go-rwkv.cpp=$(shell pwd)/go-rwkv
|
||||
$(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/nomic-ai/gpt4all/gpt4all-bindings/golang=$(shell pwd)/sources/gpt4all/gpt4all-bindings/golang
|
||||
$(GOCMD) mod edit -replace github.com/go-skynet/go-ggml-transformers.cpp=$(shell pwd)/sources/go-ggml-transformers
|
||||
$(GOCMD) mod edit -replace github.com/donomii/go-rwkv.cpp=$(shell pwd)/sources/go-rwkv
|
||||
$(GOCMD) mod edit -replace github.com/ggerganov/whisper.cpp=$(shell pwd)/sources/whisper.cpp
|
||||
$(GOCMD) mod edit -replace github.com/ggerganov/whisper.cpp/bindings/go=$(shell pwd)/sources/whisper.cpp/bindings/go
|
||||
$(GOCMD) mod edit -replace github.com/go-skynet/go-bert.cpp=$(shell pwd)/sources/go-bert
|
||||
$(GOCMD) mod edit -replace github.com/mudler/go-stable-diffusion=$(shell pwd)/sources/go-stable-diffusion
|
||||
$(GOCMD) mod edit -replace github.com/M0Rf30/go-tiny-dream=$(shell pwd)/sources/go-tiny-dream
|
||||
$(GOCMD) mod edit -replace github.com/mudler/go-piper=$(shell pwd)/sources/go-piper
|
||||
|
||||
prepare-sources: go-llama go-ggml-transformers gpt4all go-rwkv whisper.cpp go-bert bloomz go-stable-diffusion replace
|
||||
prepare-sources: get-sources replace
|
||||
$(GOCMD) mod download
|
||||
touch $@
|
||||
|
||||
## GENERIC
|
||||
rebuild: ## Rebuilds the project
|
||||
$(MAKE) -C go-llama clean
|
||||
$(MAKE) -C gpt4all/gpt4all-bindings/golang/ clean
|
||||
$(MAKE) -C go-ggml-transformers 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
|
||||
$(GOCMD) clean -cache
|
||||
$(MAKE) -C sources/go-llama clean
|
||||
$(MAKE) -C sources/go-llama-ggml clean
|
||||
$(MAKE) -C sources/gpt4all/gpt4all-bindings/golang/ clean
|
||||
$(MAKE) -C sources/go-ggml-transformers clean
|
||||
$(MAKE) -C sources/go-rwkv clean
|
||||
$(MAKE) -C sources/whisper.cpp clean
|
||||
$(MAKE) -C sources/go-stable-diffusion clean
|
||||
$(MAKE) -C sources/go-bert clean
|
||||
$(MAKE) -C sources/go-piper clean
|
||||
$(MAKE) -C sources/go-tiny-dream clean
|
||||
$(MAKE) build
|
||||
|
||||
prepare: prepare-sources backend-assets/gpt4all $(OPTIONAL_TARGETS) go-llama/libbinding.a go-bert/libgobert.a go-ggml-transformers/libtransformers.a go-rwkv/librwkv.a whisper.cpp/libwhisper.a bloomz/libbloomz.a ## Prepares for building
|
||||
prepare: prepare-sources $(OPTIONAL_TARGETS)
|
||||
touch $@
|
||||
|
||||
clean: ## Remove build related file
|
||||
rm -fr ./go-llama
|
||||
rm -rf ./gpt4all
|
||||
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
|
||||
$(GOCMD) clean -cache
|
||||
rm -f prepare
|
||||
rm -rf ./sources
|
||||
rm -rf $(BINARY_NAME)
|
||||
rm -rf release/
|
||||
rm -rf ./backend/cpp/grpc/grpc_repo
|
||||
rm -rf ./backend/cpp/grpc/build
|
||||
rm -rf ./backend/cpp/grpc/installed_packages
|
||||
$(MAKE) -C backend/cpp/llama clean
|
||||
|
||||
## Build:
|
||||
|
||||
build: prepare ## Build the project
|
||||
build: grpcs prepare ## Build the project
|
||||
$(info ${GREEN}I local-ai build info:${RESET})
|
||||
$(info ${GREEN}I BUILD_TYPE: ${YELLOW}$(BUILD_TYPE)${RESET})
|
||||
$(info ${GREEN}I GO_TAGS: ${YELLOW}$(GO_TAGS)${RESET})
|
||||
CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=${C_INCLUDE_PATH} LIBRARY_PATH=${LIBRARY_PATH} $(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o $(BINARY_NAME) ./
|
||||
ifeq ($(BUILD_TYPE),metal)
|
||||
cp go-llama/build/bin/ggml-metal.metal .
|
||||
endif
|
||||
$(info ${GREEN}I LD_FLAGS: ${YELLOW}$(LD_FLAGS)${RESET})
|
||||
|
||||
CGO_LDFLAGS="$(CGO_LDFLAGS)" $(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o $(BINARY_NAME) ./
|
||||
|
||||
dist: build
|
||||
mkdir -p release
|
||||
cp $(BINARY_NAME) release/$(BINARY_NAME)-$(BUILD_ID)-$(OS)-$(ARCH)
|
||||
|
||||
generic-build: ## Build the project using generic
|
||||
BUILD_TYPE="generic" $(MAKE) build
|
||||
osx-signed: build
|
||||
codesign --deep --force --sign "$(OSX_SIGNING_IDENTITY)" --entitlements "./Entitlements.plist" "./$(BINARY_NAME)"
|
||||
|
||||
## Run
|
||||
run: prepare ## run local-ai
|
||||
CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=${C_INCLUDE_PATH} LIBRARY_PATH=${LIBRARY_PATH} $(GOCMD) run ./
|
||||
CGO_LDFLAGS="$(CGO_LDFLAGS)" $(GOCMD) run ./
|
||||
|
||||
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
|
||||
wget -q https://huggingface.co/nnakasato/ggml-model-test/resolve/main/ggml-model-q4.bin -O test-models/testmodel
|
||||
wget -q https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-base.en.bin -O test-models/whisper-en
|
||||
wget -q https://huggingface.co/mudler/all-MiniLM-L6-v2/resolve/main/ggml-model-q4_0.bin -O test-models/bert
|
||||
wget -q https://cdn.openai.com/whisper/draft-20220913a/micro-machines.wav -O test-dir/audio.wav
|
||||
wget -q 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 -q https://raw.githubusercontent.com/saharNooby/rwkv.cpp/5eb8f09c146ea8124633ab041d9ea0b1f1db4459/rwkv/20B_tokenizer.json -O test-models/rwkv.tokenizer.json
|
||||
cp tests/models_fixtures/* test-models
|
||||
|
||||
test: prepare test-models/testmodel
|
||||
cp -r backend-assets api
|
||||
prepare-test: grpcs
|
||||
cp -rf backend-assets api
|
||||
cp tests/models_fixtures/* test-models
|
||||
C_INCLUDE_PATH=${C_INCLUDE_PATH} LIBRARY_PATH=${LIBRARY_PATH} TEST_DIR=$(abspath ./)/test-dir/ FIXTURES=$(abspath ./)/tests/fixtures CONFIG_FILE=$(abspath ./)/test-models/config.yaml MODELS_PATH=$(abspath ./)/test-models $(GOCMD) run github.com/onsi/ginkgo/v2/ginkgo --label-filter="!gpt4all && !llama" --flake-attempts 5 -v -r ./api ./pkg
|
||||
C_INCLUDE_PATH=${C_INCLUDE_PATH} LIBRARY_PATH=${LIBRARY_PATH} TEST_DIR=$(abspath ./)/test-dir/ FIXTURES=$(abspath ./)/tests/fixtures CONFIG_FILE=$(abspath ./)/test-models/config.yaml MODELS_PATH=$(abspath ./)/test-models $(GOCMD) run github.com/onsi/ginkgo/v2/ginkgo --label-filter="gpt4all" --flake-attempts 5 -v -r ./api ./pkg
|
||||
C_INCLUDE_PATH=${C_INCLUDE_PATH} LIBRARY_PATH=${LIBRARY_PATH} TEST_DIR=$(abspath ./)/test-dir/ FIXTURES=$(abspath ./)/tests/fixtures CONFIG_FILE=$(abspath ./)/test-models/config.yaml MODELS_PATH=$(abspath ./)/test-models $(GOCMD) run github.com/onsi/ginkgo/v2/ginkgo --label-filter="llama" --flake-attempts 5 -v -r ./api ./pkg
|
||||
|
||||
test: prepare test-models/testmodel grpcs
|
||||
@echo 'Running tests'
|
||||
export GO_TAGS="tts stablediffusion"
|
||||
$(MAKE) prepare-test
|
||||
HUGGINGFACE_GRPC=$(abspath ./)/backend/python/sentencetransformers/run.sh TEST_DIR=$(abspath ./)/test-dir/ FIXTURES=$(abspath ./)/tests/fixtures CONFIG_FILE=$(abspath ./)/test-models/config.yaml MODELS_PATH=$(abspath ./)/test-models \
|
||||
$(GOCMD) run github.com/onsi/ginkgo/v2/ginkgo --label-filter="!gpt4all && !llama && !llama-gguf" --flake-attempts 5 --fail-fast -v -r ./api ./pkg
|
||||
$(MAKE) test-gpt4all
|
||||
$(MAKE) test-llama
|
||||
$(MAKE) test-llama-gguf
|
||||
$(MAKE) test-tts
|
||||
$(MAKE) test-stablediffusion
|
||||
|
||||
prepare-e2e:
|
||||
mkdir -p $(TEST_DIR)
|
||||
cp -rfv $(abspath ./tests/e2e-fixtures)/gpu.yaml $(TEST_DIR)/gpu.yaml
|
||||
test -e $(TEST_DIR)/ggllm-test-model.bin || wget -q https://huggingface.co/TheBloke/CodeLlama-7B-Instruct-GGUF/resolve/main/codellama-7b-instruct.Q2_K.gguf -O $(TEST_DIR)/ggllm-test-model.bin
|
||||
docker build --build-arg BUILD_GRPC=true --build-arg GRPC_BACKENDS="$(GRPC_BACKENDS)" --build-arg IMAGE_TYPE=core --build-arg BUILD_TYPE=$(BUILD_TYPE) --build-arg CUDA_MAJOR_VERSION=11 --build-arg CUDA_MINOR_VERSION=7 --build-arg FFMPEG=true -t localai-tests .
|
||||
|
||||
run-e2e-image:
|
||||
ls -liah $(abspath ./tests/e2e-fixtures)
|
||||
docker run -p 5390:8080 -e MODELS_PATH=/models -e THREADS=1 -e DEBUG=true -d --rm -v $(TEST_DIR):/models --gpus all --name e2e-tests-$(RANDOM) localai-tests
|
||||
|
||||
test-e2e:
|
||||
@echo 'Running e2e tests'
|
||||
BUILD_TYPE=$(BUILD_TYPE) \
|
||||
LOCALAI_API=http://$(E2E_BRIDGE_IP):5390/v1 \
|
||||
$(GOCMD) run github.com/onsi/ginkgo/v2/ginkgo --flake-attempts 5 -v -r ./tests/e2e
|
||||
|
||||
teardown-e2e:
|
||||
rm -rf $(TEST_DIR) || true
|
||||
docker stop $$(docker ps -q --filter ancestor=localai-tests)
|
||||
|
||||
test-gpt4all: prepare-test
|
||||
TEST_DIR=$(abspath ./)/test-dir/ FIXTURES=$(abspath ./)/tests/fixtures CONFIG_FILE=$(abspath ./)/test-models/config.yaml MODELS_PATH=$(abspath ./)/test-models \
|
||||
$(GOCMD) run github.com/onsi/ginkgo/v2/ginkgo --label-filter="gpt4all" --flake-attempts 5 -v -r ./api ./pkg
|
||||
|
||||
test-llama: prepare-test
|
||||
TEST_DIR=$(abspath ./)/test-dir/ FIXTURES=$(abspath ./)/tests/fixtures CONFIG_FILE=$(abspath ./)/test-models/config.yaml MODELS_PATH=$(abspath ./)/test-models \
|
||||
$(GOCMD) run github.com/onsi/ginkgo/v2/ginkgo --label-filter="llama" --flake-attempts 5 -v -r ./api ./pkg
|
||||
|
||||
test-llama-gguf: prepare-test
|
||||
TEST_DIR=$(abspath ./)/test-dir/ FIXTURES=$(abspath ./)/tests/fixtures CONFIG_FILE=$(abspath ./)/test-models/config.yaml MODELS_PATH=$(abspath ./)/test-models \
|
||||
$(GOCMD) run github.com/onsi/ginkgo/v2/ginkgo --label-filter="llama-gguf" --flake-attempts 5 -v -r ./api ./pkg
|
||||
|
||||
test-tts: prepare-test
|
||||
TEST_DIR=$(abspath ./)/test-dir/ FIXTURES=$(abspath ./)/tests/fixtures CONFIG_FILE=$(abspath ./)/test-models/config.yaml MODELS_PATH=$(abspath ./)/test-models \
|
||||
$(GOCMD) run github.com/onsi/ginkgo/v2/ginkgo --label-filter="tts" --flake-attempts 1 -v -r ./api ./pkg
|
||||
|
||||
test-stablediffusion: prepare-test
|
||||
TEST_DIR=$(abspath ./)/test-dir/ FIXTURES=$(abspath ./)/tests/fixtures CONFIG_FILE=$(abspath ./)/test-models/config.yaml MODELS_PATH=$(abspath ./)/test-models \
|
||||
$(GOCMD) run github.com/onsi/ginkgo/v2/ginkgo --label-filter="stablediffusion" --flake-attempts 1 -v -r ./api ./pkg
|
||||
|
||||
test-container:
|
||||
docker build --target requirements -t local-ai-test-container .
|
||||
docker run -ti --rm --entrypoint /bin/bash -ti -v $(abspath ./):/build local-ai-test-container
|
||||
|
||||
## Help:
|
||||
help: ## Show this help.
|
||||
@@ -264,3 +398,163 @@ 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 -Ibackend/ --go_out=pkg/grpc/proto/ --go_opt=paths=source_relative --go-grpc_out=pkg/grpc/proto/ --go-grpc_opt=paths=source_relative \
|
||||
backend/backend.proto
|
||||
|
||||
protogen-python:
|
||||
python3 -m grpc_tools.protoc -Ibackend/ --python_out=backend/python/sentencetransformers/ --grpc_python_out=backend/python/sentencetransformers/ backend/backend.proto
|
||||
python3 -m grpc_tools.protoc -Ibackend/ --python_out=backend/python/transformers/ --grpc_python_out=backend/python/transformers/ backend/backend.proto
|
||||
python3 -m grpc_tools.protoc -Ibackend/ --python_out=backend/python/transformers-musicgen/ --grpc_python_out=backend/python/transformers-musicgen/ backend/backend.proto
|
||||
python3 -m grpc_tools.protoc -Ibackend/ --python_out=backend/python/autogptq/ --grpc_python_out=backend/python/autogptq/ backend/backend.proto
|
||||
python3 -m grpc_tools.protoc -Ibackend/ --python_out=backend/python/exllama/ --grpc_python_out=backend/python/exllama/ backend/backend.proto
|
||||
python3 -m grpc_tools.protoc -Ibackend/ --python_out=backend/python/bark/ --grpc_python_out=backend/python/bark/ backend/backend.proto
|
||||
python3 -m grpc_tools.protoc -Ibackend/ --python_out=backend/python/diffusers/ --grpc_python_out=backend/python/diffusers/ backend/backend.proto
|
||||
python3 -m grpc_tools.protoc -Ibackend/ --python_out=backend/python/coqui/ --grpc_python_out=backend/python/coqui/ backend/backend.proto
|
||||
python3 -m grpc_tools.protoc -Ibackend/ --python_out=backend/python/vall-e-x/ --grpc_python_out=backend/python/vall-e-x/ backend/backend.proto
|
||||
python3 -m grpc_tools.protoc -Ibackend/ --python_out=backend/python/vllm/ --grpc_python_out=backend/python/vllm/ backend/backend.proto
|
||||
python3 -m grpc_tools.protoc -Ibackend/ --python_out=backend/python/petals/ --grpc_python_out=backend/python/petals/ backend/backend.proto
|
||||
python3 -m grpc_tools.protoc -Ibackend/ --python_out=backend/python/exllama2/ --grpc_python_out=backend/python/exllama2/ backend/backend.proto
|
||||
|
||||
## GRPC
|
||||
# Note: it is duplicated in the Dockerfile
|
||||
prepare-extra-conda-environments:
|
||||
$(MAKE) -C backend/python/autogptq
|
||||
$(MAKE) -C backend/python/bark
|
||||
$(MAKE) -C backend/python/coqui
|
||||
$(MAKE) -C backend/python/diffusers
|
||||
$(MAKE) -C backend/python/vllm
|
||||
$(MAKE) -C backend/python/sentencetransformers
|
||||
$(MAKE) -C backend/python/transformers
|
||||
$(MAKE) -C backend/python/transformers-musicgen
|
||||
$(MAKE) -C backend/python/vall-e-x
|
||||
$(MAKE) -C backend/python/exllama
|
||||
$(MAKE) -C backend/python/petals
|
||||
$(MAKE) -C backend/python/exllama2
|
||||
|
||||
prepare-test-extra:
|
||||
$(MAKE) -C backend/python/transformers
|
||||
$(MAKE) -C backend/python/diffusers
|
||||
|
||||
test-extra: prepare-test-extra
|
||||
$(MAKE) -C backend/python/transformers test
|
||||
$(MAKE) -C backend/python/diffusers test
|
||||
|
||||
backend-assets/grpc:
|
||||
mkdir -p backend-assets/grpc
|
||||
|
||||
backend-assets/grpc/llama: backend-assets/grpc sources/go-llama/libbinding.a
|
||||
$(GOCMD) mod edit -replace github.com/go-skynet/go-llama.cpp=$(shell pwd)/sources/go-llama
|
||||
CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(shell pwd)/sources/go-llama LIBRARY_PATH=$(shell pwd)/sources/go-llama \
|
||||
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/llama ./backend/go/llm/llama/
|
||||
# TODO: every binary should have its own folder instead, so can have different implementations
|
||||
ifeq ($(BUILD_TYPE),metal)
|
||||
cp backend/cpp/llama/llama.cpp/ggml-metal.metal backend-assets/grpc/
|
||||
endif
|
||||
|
||||
## BACKEND CPP LLAMA START
|
||||
# Sets the variables in case it has to build the gRPC locally.
|
||||
INSTALLED_PACKAGES=$(CURDIR)/backend/cpp/grpc/installed_packages
|
||||
INSTALLED_LIB_CMAKE=$(INSTALLED_PACKAGES)/lib/cmake
|
||||
ADDED_CMAKE_ARGS=-Dabsl_DIR=${INSTALLED_LIB_CMAKE}/absl \
|
||||
-DProtobuf_DIR=${INSTALLED_LIB_CMAKE}/protobuf \
|
||||
-Dutf8_range_DIR=${INSTALLED_LIB_CMAKE}/utf8_range \
|
||||
-DgRPC_DIR=${INSTALLED_LIB_CMAKE}/grpc \
|
||||
-DCMAKE_CXX_STANDARD_INCLUDE_DIRECTORIES=${INSTALLED_PACKAGES}/include
|
||||
|
||||
backend/cpp/llama/grpc-server:
|
||||
ifdef BUILD_GRPC_FOR_BACKEND_LLAMA
|
||||
backend/cpp/grpc/script/build_grpc.sh ${INSTALLED_PACKAGES}
|
||||
export _PROTOBUF_PROTOC=${INSTALLED_PACKAGES}/bin/proto && \
|
||||
export _GRPC_CPP_PLUGIN_EXECUTABLE=${INSTALLED_PACKAGES}/bin/grpc_cpp_plugin && \
|
||||
export PATH=${PATH}:${INSTALLED_PACKAGES}/bin && \
|
||||
CMAKE_ARGS="${CMAKE_ARGS} ${ADDED_CMAKE_ARGS}" LLAMA_VERSION=$(CPPLLAMA_VERSION) $(MAKE) -C backend/cpp/llama grpc-server
|
||||
else
|
||||
echo "BUILD_GRPC_FOR_BACKEND_LLAMA is not defined."
|
||||
LLAMA_VERSION=$(CPPLLAMA_VERSION) $(MAKE) -C backend/cpp/llama grpc-server
|
||||
endif
|
||||
## BACKEND CPP LLAMA END
|
||||
|
||||
##
|
||||
backend-assets/grpc/llama-cpp: backend-assets/grpc backend/cpp/llama/grpc-server
|
||||
cp -rfv backend/cpp/llama/grpc-server backend-assets/grpc/llama-cpp
|
||||
# TODO: every binary should have its own folder instead, so can have different metal implementations
|
||||
ifeq ($(BUILD_TYPE),metal)
|
||||
cp backend/cpp/llama/llama.cpp/build/bin/ggml-metal.metal backend-assets/grpc/
|
||||
endif
|
||||
|
||||
backend-assets/grpc/llama-ggml: backend-assets/grpc sources/go-llama-ggml/libbinding.a
|
||||
$(GOCMD) mod edit -replace github.com/go-skynet/go-llama.cpp=$(shell pwd)/sources/go-llama-ggml
|
||||
CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(shell pwd)/sources/go-llama-ggml LIBRARY_PATH=$(shell pwd)/sources/go-llama-ggml \
|
||||
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/llama-ggml ./backend/go/llm/llama-ggml/
|
||||
|
||||
backend-assets/grpc/gpt4all: backend-assets/grpc backend-assets/gpt4all sources/gpt4all/gpt4all-bindings/golang/libgpt4all.a
|
||||
CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(shell pwd)/sources/gpt4all/gpt4all-bindings/golang/ LIBRARY_PATH=$(shell pwd)/sources/gpt4all/gpt4all-bindings/golang/ \
|
||||
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/gpt4all ./backend/go/llm/gpt4all/
|
||||
|
||||
backend-assets/grpc/dolly: backend-assets/grpc sources/go-ggml-transformers/libtransformers.a
|
||||
CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(shell pwd)/sources/go-ggml-transformers LIBRARY_PATH=$(shell pwd)/sources/go-ggml-transformers \
|
||||
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/dolly ./backend/go/llm/dolly/
|
||||
|
||||
backend-assets/grpc/gpt2: backend-assets/grpc sources/go-ggml-transformers/libtransformers.a
|
||||
CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(shell pwd)/sources/go-ggml-transformers LIBRARY_PATH=$(shell pwd)/sources/go-ggml-transformers \
|
||||
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/gpt2 ./backend/go/llm/gpt2/
|
||||
|
||||
backend-assets/grpc/gptj: backend-assets/grpc sources/go-ggml-transformers/libtransformers.a
|
||||
CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(shell pwd)/sources/go-ggml-transformers LIBRARY_PATH=$(shell pwd)/sources/go-ggml-transformers \
|
||||
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/gptj ./backend/go/llm/gptj/
|
||||
|
||||
backend-assets/grpc/gptneox: backend-assets/grpc sources/go-ggml-transformers/libtransformers.a
|
||||
CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(shell pwd)/sources/go-ggml-transformers LIBRARY_PATH=$(shell pwd)/sources/go-ggml-transformers \
|
||||
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/gptneox ./backend/go/llm/gptneox/
|
||||
|
||||
backend-assets/grpc/mpt: backend-assets/grpc sources/go-ggml-transformers/libtransformers.a
|
||||
CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(shell pwd)/sources/go-ggml-transformers LIBRARY_PATH=$(shell pwd)/sources/go-ggml-transformers \
|
||||
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/mpt ./backend/go/llm/mpt/
|
||||
|
||||
backend-assets/grpc/replit: backend-assets/grpc sources/go-ggml-transformers/libtransformers.a
|
||||
CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(shell pwd)/sources/go-ggml-transformers LIBRARY_PATH=$(shell pwd)/sources/go-ggml-transformers \
|
||||
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/replit ./backend/go/llm/replit/
|
||||
|
||||
backend-assets/grpc/falcon-ggml: backend-assets/grpc sources/go-ggml-transformers/libtransformers.a
|
||||
CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(shell pwd)/sources/go-ggml-transformers LIBRARY_PATH=$(shell pwd)/sources/go-ggml-transformers \
|
||||
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/falcon-ggml ./backend/go/llm/falcon-ggml/
|
||||
|
||||
backend-assets/grpc/starcoder: backend-assets/grpc sources/go-ggml-transformers/libtransformers.a
|
||||
CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(shell pwd)/sources/go-ggml-transformers LIBRARY_PATH=$(shell pwd)/sources/go-ggml-transformers \
|
||||
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/starcoder ./backend/go/llm/starcoder/
|
||||
|
||||
backend-assets/grpc/rwkv: backend-assets/grpc sources/go-rwkv/librwkv.a
|
||||
CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(shell pwd)/sources/go-rwkv LIBRARY_PATH=$(shell pwd)/sources/go-rwkv \
|
||||
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/rwkv ./backend/go/llm/rwkv
|
||||
|
||||
backend-assets/grpc/bert-embeddings: backend-assets/grpc sources/go-bert/libgobert.a
|
||||
CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(shell pwd)/sources/go-bert LIBRARY_PATH=$(shell pwd)/sources/go-bert \
|
||||
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/bert-embeddings ./backend/go/llm/bert/
|
||||
|
||||
backend-assets/grpc/langchain-huggingface: backend-assets/grpc
|
||||
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/langchain-huggingface ./backend/go/llm/langchain/
|
||||
|
||||
backend-assets/grpc/stablediffusion: backend-assets/grpc
|
||||
if [ ! -f backend-assets/grpc/stablediffusion ]; then \
|
||||
$(MAKE) sources/go-stable-diffusion/libstablediffusion.a; \
|
||||
CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(shell pwd)/sources/go-stable-diffusion/ LIBRARY_PATH=$(shell pwd)/sources/go-stable-diffusion/ \
|
||||
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/stablediffusion ./backend/go/image/stablediffusion; \
|
||||
fi
|
||||
|
||||
backend-assets/grpc/tinydream: backend-assets/grpc sources/go-tiny-dream/libtinydream.a
|
||||
CGO_LDFLAGS="$(CGO_LDFLAGS)" LIBRARY_PATH=$(shell pwd)/go-tiny-dream \
|
||||
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/tinydream ./backend/go/image/tinydream
|
||||
|
||||
backend-assets/grpc/piper: backend-assets/grpc backend-assets/espeak-ng-data sources/go-piper/libpiper_binding.a
|
||||
CGO_CXXFLAGS="$(PIPER_CGO_CXXFLAGS)" CGO_LDFLAGS="$(PIPER_CGO_LDFLAGS)" LIBRARY_PATH=$(shell pwd)/sources/go-piper \
|
||||
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/piper ./backend/go/tts/
|
||||
|
||||
backend-assets/grpc/whisper: backend-assets/grpc sources/whisper.cpp/libwhisper.a
|
||||
CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(shell pwd)/sources/whisper.cpp LIBRARY_PATH=$(shell pwd)/sources/whisper.cpp \
|
||||
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/whisper ./backend/go/transcribe/
|
||||
|
||||
grpcs: prepare $(GRPC_BACKENDS)
|
||||
|
||||
261
README.md
261
README.md
@@ -1,205 +1,155 @@
|
||||
<h1 align="center">
|
||||
<br>
|
||||
<img height="300" src="https://user-images.githubusercontent.com/2420543/233147843-88697415-6dbf-4368-a862-ab217f9f7342.jpeg"> <br>
|
||||
<img height="300" src="https://github.com/go-skynet/LocalAI/assets/2420543/0966aa2a-166e-4f99-a3e5-6c915fc997dd"> <br>
|
||||
LocalAI
|
||||
<br>
|
||||
</h1>
|
||||
|
||||
[](https://github.com/go-skynet/LocalAI/actions/workflows/test.yml) [](https://github.com/go-skynet/LocalAI/actions/workflows/image.yml)
|
||||
<p align="center">
|
||||
<a href="https://github.com/go-skynet/LocalAI/fork" target="blank">
|
||||
<img src="https://img.shields.io/github/forks/go-skynet/LocalAI?style=for-the-badge" alt="LocalAI forks"/>
|
||||
</a>
|
||||
<a href="https://github.com/go-skynet/LocalAI/stargazers" target="blank">
|
||||
<img src="https://img.shields.io/github/stars/go-skynet/LocalAI?style=for-the-badge" alt="LocalAI stars"/>
|
||||
</a>
|
||||
<a href="https://github.com/go-skynet/LocalAI/pulls" target="blank">
|
||||
<img src="https://img.shields.io/github/issues-pr/go-skynet/LocalAI?style=for-the-badge" alt="LocalAI pull-requests"/>
|
||||
</a>
|
||||
<a href='https://github.com/go-skynet/LocalAI/releases'>
|
||||
<img src='https://img.shields.io/github/release/go-skynet/LocalAI?&label=Latest&style=for-the-badge'>
|
||||
</a>
|
||||
</p>
|
||||
|
||||
[](https://discord.gg/uJAeKSAGDy)
|
||||
> :bulb: Get help - [❓FAQ](https://localai.io/faq/) [💭Discussions](https://github.com/go-skynet/LocalAI/discussions) [:speech_balloon: Discord](https://discord.gg/uJAeKSAGDy) [:book: Documentation website](https://localai.io/)
|
||||
>
|
||||
> [💻 Quickstart](https://localai.io/basics/getting_started/) [📣 News](https://localai.io/basics/news/) [ 🛫 Examples ](https://github.com/go-skynet/LocalAI/tree/master/examples/) [ 🖼️ Models ](https://localai.io/models/) [ 🚀 Roadmap ](https://github.com/mudler/LocalAI/issues?q=is%3Aissue+is%3Aopen+label%3Aroadmap)
|
||||
|
||||
**LocalAI** is a drop-in replacement REST API that’s compatible with OpenAI API specifications for local inferencing. It allows you to run LLMs (and not only) locally or on-prem with consumer grade hardware, supporting multiple model families that are compatible with the ggml format. Does not require GPU.
|
||||
[](https://github.com/go-skynet/LocalAI/actions/workflows/test.yml)[](https://github.com/go-skynet/LocalAI/actions/workflows/release.yaml)[](https://github.com/go-skynet/LocalAI/actions/workflows/image.yml)[](https://github.com/go-skynet/LocalAI/actions/workflows/bump_deps.yaml)[](https://artifacthub.io/packages/search?repo=localai)
|
||||
|
||||
For a list of the supported model families, please see [the model compatibility table](https://localai.io/model-compatibility/index.html#model-compatibility-table).
|
||||
<p align="center">
|
||||
<a href="https://twitter.com/LocalAI_API" target="blank">
|
||||
<img src="https://img.shields.io/twitter/follow/LocalAI_API?label=Follow: LocalAI_API&style=social" alt="Follow LocalAI_API"/>
|
||||
</a>
|
||||
<a href="https://discord.gg/uJAeKSAGDy" target="blank">
|
||||
<img src="https://dcbadge.vercel.app/api/server/uJAeKSAGDy?style=flat-square&theme=default-inverted" alt="Join LocalAI Discord Community"/>
|
||||
</a>
|
||||
|
||||
In a nutshell:
|
||||
**LocalAI** is the free, Open Source OpenAI alternative. LocalAI act as a drop-in replacement REST API that’s compatible with OpenAI API specifications for local inferencing. It allows you to run LLMs, generate images, audio (and not only) locally or on-prem with consumer grade hardware, supporting multiple model families. Does not require GPU.
|
||||
|
||||
- Local, OpenAI drop-in alternative REST API. You own your data.
|
||||
- NO GPU required. NO Internet access is required either. Optional, GPU Acceleration is available in `llama.cpp`-compatible LLMs. [See building instructions](https://localai.io/basics/build/index.html).
|
||||
- Supports multiple models, Audio transcription, Text generation with GPTs, Image generation with stable diffusion (experimental)
|
||||
- Once loaded the first time, it keep models loaded in memory for faster inference
|
||||
- Doesn't shell-out, but uses C++ bindings for a faster inference and better performance.
|
||||
## 🔥🔥 Hot topics / Roadmap
|
||||
|
||||
LocalAI was created by [Ettore Di Giacinto](https://github.com/mudler/) and is a community-driven project, focused on making the AI accessible to anyone. Any contribution, feedback and PR is welcome!
|
||||
[Roadmap](https://github.com/mudler/LocalAI/issues?q=is%3Aissue+is%3Aopen+label%3Aroadmap)
|
||||
|
||||
| [ChatGPT OSS alternative](https://github.com/go-skynet/LocalAI/tree/master/examples/chatbot-ui) | [Image generation](https://localai.io/api-endpoints/index.html#image-generation) |
|
||||
|------------------------------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------------|
|
||||
|  |  |
|
||||
- 🐸 Coqui: https://github.com/mudler/LocalAI/pull/1489
|
||||
- Inline templates: https://github.com/mudler/LocalAI/pull/1452
|
||||
- Mixtral: https://github.com/mudler/LocalAI/pull/1449
|
||||
- Img2vid https://github.com/mudler/LocalAI/pull/1442
|
||||
- Musicgen https://github.com/mudler/LocalAI/pull/1387
|
||||
|
||||
Hot topics (looking for contributors):
|
||||
- Backends v2: https://github.com/mudler/LocalAI/issues/1126
|
||||
- Improving UX v2: https://github.com/mudler/LocalAI/issues/1373
|
||||
|
||||
See the [Getting started](https://localai.io/basics/getting_started/index.html) and [examples](https://github.com/go-skynet/LocalAI/tree/master/examples/) sections to learn how to use LocalAI. For a list of curated models check out the [model gallery](https://localai.io/models/).
|
||||
If you want to help and contribute, issues up for grabs: https://github.com/mudler/LocalAI/issues?q=is%3Aissue+is%3Aopen+label%3A%22up+for+grabs%22
|
||||
|
||||
## News
|
||||
## 💻 [Getting started](https://localai.io/basics/getting_started/index.html)
|
||||
|
||||
- 🔥🔥🔥 06-06-2023: **v1.18.0**: Many updates, new features, and much more 🚀, check out the [Changelog](https://localai.io/basics/news/index.html#-06-06-2023-__v1180__-)!
|
||||
- 29-05-2023: LocalAI now has a website, [https://localai.io](https://localai.io)! check the news in the [dedicated section](https://localai.io/basics/news/index.html)!
|
||||
## 🚀 [Features](https://localai.io/features/)
|
||||
|
||||
For latest news, follow also on Twitter [@LocalAI_API](https://twitter.com/LocalAI_API) and [@mudler_it](https://twitter.com/mudler_it)
|
||||
- 📖 [Text generation with GPTs](https://localai.io/features/text-generation/) (`llama.cpp`, `gpt4all.cpp`, ... [:book: and more](https://localai.io/model-compatibility/index.html#model-compatibility-table))
|
||||
- 🗣 [Text to Audio](https://localai.io/features/text-to-audio/)
|
||||
- 🔈 [Audio to Text](https://localai.io/features/audio-to-text/) (Audio transcription with `whisper.cpp`)
|
||||
- 🎨 [Image generation with stable diffusion](https://localai.io/features/image-generation)
|
||||
- 🔥 [OpenAI functions](https://localai.io/features/openai-functions/) 🆕
|
||||
- 🧠 [Embeddings generation for vector databases](https://localai.io/features/embeddings/)
|
||||
- ✍️ [Constrained grammars](https://localai.io/features/constrained_grammars/)
|
||||
- 🖼️ [Download Models directly from Huggingface ](https://localai.io/models/)
|
||||
- 🆕 [Vision API](https://localai.io/features/gpt-vision/)
|
||||
|
||||
## Contribute and help
|
||||
## 💻 Usage
|
||||
|
||||
To help the project you can:
|
||||
Check out the [Getting started](https://localai.io/basics/getting_started/index.html) section in our documentation.
|
||||
|
||||
- Upvote the [Reddit post](https://www.reddit.com/r/selfhosted/comments/12w4p2f/localai_openai_compatible_api_to_run_llm_models/) about LocalAI.
|
||||
### 🔗 Community and integrations
|
||||
|
||||
- [Hacker news post](https://news.ycombinator.com/item?id=35726934) - help us out by voting if you like this project.
|
||||
Build and deploy custom containers:
|
||||
- https://github.com/sozercan/aikit
|
||||
|
||||
- If you have technological skills and want to contribute to development, have a look at the open issues. If you are new you can have a look at the [good-first-issue](https://github.com/go-skynet/LocalAI/issues?q=is%3Aissue+is%3Aopen+label%3A%22good+first+issue%22) and [help-wanted](https://github.com/go-skynet/LocalAI/issues?q=is%3Aissue+is%3Aopen+label%3A%22help+wanted%22) labels.
|
||||
WebUIs:
|
||||
- https://github.com/Jirubizu/localai-admin
|
||||
- https://github.com/go-skynet/LocalAI-frontend
|
||||
|
||||
- If you don't have technological skills you can still help improving documentation or add examples or share your user-stories with our community, any help and contribution is welcome!
|
||||
Model galleries
|
||||
- https://github.com/go-skynet/model-gallery
|
||||
|
||||
## Usage
|
||||
Other:
|
||||
- Helm chart https://github.com/go-skynet/helm-charts
|
||||
- VSCode extension https://github.com/badgooooor/localai-vscode-plugin
|
||||
- Local Smart assistant https://github.com/mudler/LocalAGI
|
||||
- Home Assistant https://github.com/sammcj/homeassistant-localai / https://github.com/drndos/hass-openai-custom-conversation
|
||||
- Discord bot https://github.com/mudler/LocalAGI/tree/main/examples/discord
|
||||
- Slack bot https://github.com/mudler/LocalAGI/tree/main/examples/slack
|
||||
- Telegram bot https://github.com/mudler/LocalAI/tree/master/examples/telegram-bot
|
||||
- Examples: https://github.com/mudler/LocalAI/tree/master/examples/
|
||||
|
||||
Check out the [Getting started](https://localai.io/basics/getting_started/index.html) section. Here below you will find generic, quick instructions to get ready and use LocalAI.
|
||||
### 🔗 Resources
|
||||
|
||||
The easiest way to run LocalAI is by using `docker-compose` (to build locally, see [building LocalAI](https://localai.io/basics/build/index.html)):
|
||||
- 🆕 New! [LLM finetuning guide](https://localai.io/advanced/fine-tuning/)
|
||||
- [How to build locally](https://localai.io/basics/build/index.html)
|
||||
- [How to install in Kubernetes](https://localai.io/basics/getting_started/index.html#run-localai-in-kubernetes)
|
||||
- [Projects integrating LocalAI](https://localai.io/integrations/)
|
||||
- [How tos section](https://localai.io/howtos/) (curated by our community)
|
||||
|
||||
```bash
|
||||
## :book: 🎥 [Media, Blogs, Social](https://localai.io/basics/news/#media-blogs-social)
|
||||
|
||||
git clone https://github.com/go-skynet/LocalAI
|
||||
- [Create a slackbot for teams and OSS projects that answer to documentation](https://mudler.pm/posts/smart-slackbot-for-teams/)
|
||||
- [LocalAI meets k8sgpt](https://www.youtube.com/watch?v=PKrDNuJ_dfE)
|
||||
- [Question Answering on Documents locally with LangChain, LocalAI, Chroma, and GPT4All](https://mudler.pm/posts/localai-question-answering/)
|
||||
- [Tutorial to use k8sgpt with LocalAI](https://medium.com/@tyler_97636/k8sgpt-localai-unlock-kubernetes-superpowers-for-free-584790de9b65)
|
||||
|
||||
cd LocalAI
|
||||
## Citation
|
||||
|
||||
# (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 --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":"your-model.bin","object":"model"}]}
|
||||
|
||||
curl http://localhost:8080/v1/completions -H "Content-Type: application/json" -d '{
|
||||
"model": "your-model.bin",
|
||||
"prompt": "A long time ago in a galaxy far, far away",
|
||||
"temperature": 0.7
|
||||
}'
|
||||
```
|
||||
|
||||
### Example: Use GPT4ALL-J model
|
||||
|
||||
<details>
|
||||
|
||||
```bash
|
||||
# Clone LocalAI
|
||||
git clone https://github.com/go-skynet/LocalAI
|
||||
|
||||
cd LocalAI
|
||||
|
||||
# (optional) Checkout a specific LocalAI tag
|
||||
# git checkout -b build <TAG>
|
||||
|
||||
# Download gpt4all-j to models/
|
||||
wget https://gpt4all.io/models/ggml-gpt4all-j.bin -O models/ggml-gpt4all-j
|
||||
|
||||
# Use a template from the examples
|
||||
cp -rf prompt-templates/ggml-gpt4all-j.tmpl models/
|
||||
|
||||
# (optional) Edit the .env file to set things like context size and threads
|
||||
# vim .env
|
||||
|
||||
# start with docker-compose
|
||||
docker-compose up -d --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"}]}
|
||||
|
||||
curl http://localhost:8080/v1/chat/completions -H "Content-Type: application/json" -d '{
|
||||
"model": "ggml-gpt4all-j",
|
||||
"messages": [{"role": "user", "content": "How are you?"}],
|
||||
"temperature": 0.9
|
||||
}'
|
||||
|
||||
# {"model":"ggml-gpt4all-j","choices":[{"message":{"role":"assistant","content":"I'm doing well, thanks. How about you?"}}]}
|
||||
```
|
||||
</details>
|
||||
|
||||
|
||||
### Build locally
|
||||
|
||||
<details>
|
||||
|
||||
In order to build the `LocalAI` container image locally you can use `docker`:
|
||||
If you utilize this repository, data in a downstream project, please consider citing it with:
|
||||
|
||||
```
|
||||
# build the image
|
||||
docker build -t localai .
|
||||
docker run localai
|
||||
@misc{localai,
|
||||
author = {Ettore Di Giacinto},
|
||||
title = {LocalAI: The free, Open source OpenAI alternative},
|
||||
year = {2023},
|
||||
publisher = {GitHub},
|
||||
journal = {GitHub repository},
|
||||
howpublished = {\url{https://github.com/go-skynet/LocalAI}},
|
||||
```
|
||||
|
||||
Or you can build the binary with `make`:
|
||||
## ❤️ Sponsors
|
||||
|
||||
```
|
||||
make build
|
||||
```
|
||||
> Do you find LocalAI useful?
|
||||
|
||||
</details>
|
||||
Support the project by becoming [a backer or sponsor](https://github.com/sponsors/mudler). Your logo will show up here with a link to your website.
|
||||
|
||||
See the [build section](https://localai.io/basics/build/index.html) in our documentation for detailed instructions.
|
||||
A huge thank you to our generous sponsors who support this project:
|
||||
|
||||
### Run LocalAI in Kubernetes
|
||||
|  |
|
||||
|:-----------------------------------------------:|
|
||||
| [Spectro Cloud](https://www.spectrocloud.com/) |
|
||||
| Spectro Cloud kindly supports LocalAI by providing GPU and computing resources to run tests on lamdalabs! |
|
||||
|
||||
LocalAI can be installed inside Kubernetes with helm. See [installation instructions](https://localai.io/basics/getting_started/index.html#run-localai-in-kubernetes).
|
||||
And a huge shout-out to individuals sponsoring the project by donating hardware or backing the project.
|
||||
|
||||
## Supported API endpoints
|
||||
- [Sponsor list](https://github.com/sponsors/mudler)
|
||||
- JDAM00 (donating HW for the CI)
|
||||
|
||||
See the [list of the supported API endpoints](https://localai.io/api-endpoints/index.html) and how to configure image generation and audio transcription.
|
||||
|
||||
## Frequently asked questions
|
||||
|
||||
See [the FAQ](https://localai.io/faq/index.html) section for a list of common questions.
|
||||
|
||||
## Projects already using LocalAI to run local models
|
||||
|
||||
Feel free to open up a PR to get your project listed!
|
||||
|
||||
- [Kairos](https://github.com/kairos-io/kairos)
|
||||
- [k8sgpt](https://github.com/k8sgpt-ai/k8sgpt#running-local-models)
|
||||
- [Spark](https://github.com/cedriking/spark)
|
||||
- [autogpt4all](https://github.com/aorumbayev/autogpt4all)
|
||||
- [Mods](https://github.com/charmbracelet/mods)
|
||||
- [Flowise](https://github.com/FlowiseAI/Flowise)
|
||||
|
||||
## 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.
|
||||
- [x] Support for embeddings
|
||||
- [x] Support for audio transcription with https://github.com/ggerganov/whisper.cpp
|
||||
- [ ] GPU/CUDA support ( https://github.com/go-skynet/LocalAI/issues/69 )
|
||||
- [ ] Enable automatic downloading of models from a curated gallery, with only free-licensed models, directly from the webui.
|
||||
|
||||
## Star history
|
||||
## 🌟 Star history
|
||||
|
||||
[](https://star-history.com/#go-skynet/LocalAI&Date)
|
||||
|
||||
## License
|
||||
## 📖 License
|
||||
|
||||
LocalAI is a community-driven project created by [Ettore Di Giacinto](https://github.com/mudler/).
|
||||
|
||||
MIT
|
||||
MIT - Author Ettore Di Giacinto
|
||||
|
||||
## Author
|
||||
|
||||
Ettore Di Giacinto and others
|
||||
|
||||
## Acknowledgements
|
||||
## 🙇 Acknowledgements
|
||||
|
||||
LocalAI couldn't have been built without the help of great software already available from the community. Thank you!
|
||||
|
||||
@@ -210,9 +160,12 @@ LocalAI couldn't have been built without the help of great software already avai
|
||||
- https://github.com/EdVince/Stable-Diffusion-NCNN
|
||||
- https://github.com/ggerganov/whisper.cpp
|
||||
- https://github.com/saharNooby/rwkv.cpp
|
||||
- https://github.com/rhasspy/piper
|
||||
- https://github.com/cmp-nct/ggllm.cpp
|
||||
|
||||
## Contributors
|
||||
## 🤗 Contributors
|
||||
|
||||
This is a community project, a special thanks to our contributors! 🤗
|
||||
<a href="https://github.com/go-skynet/LocalAI/graphs/contributors">
|
||||
<img src="https://contrib.rocks/image?repo=go-skynet/LocalAI" />
|
||||
</a>
|
||||
|
||||
262
api/api.go
262
api/api.go
@@ -1,9 +1,22 @@
|
||||
package api
|
||||
|
||||
import (
|
||||
"encoding/json"
|
||||
"errors"
|
||||
"fmt"
|
||||
"os"
|
||||
"strings"
|
||||
|
||||
config "github.com/go-skynet/LocalAI/api/config"
|
||||
"github.com/go-skynet/LocalAI/api/localai"
|
||||
"github.com/go-skynet/LocalAI/api/openai"
|
||||
"github.com/go-skynet/LocalAI/api/options"
|
||||
"github.com/go-skynet/LocalAI/api/schema"
|
||||
"github.com/go-skynet/LocalAI/internal"
|
||||
"github.com/go-skynet/LocalAI/metrics"
|
||||
"github.com/go-skynet/LocalAI/pkg/assets"
|
||||
"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"
|
||||
@@ -12,18 +25,97 @@ import (
|
||||
"github.com/rs/zerolog/log"
|
||||
)
|
||||
|
||||
func App(opts ...AppOption) (*fiber.App, error) {
|
||||
options := newOptions(opts...)
|
||||
func Startup(opts ...options.AppOption) (*options.Option, *config.ConfigLoader, error) {
|
||||
options := options.NewOptions(opts...)
|
||||
|
||||
zerolog.SetGlobalLevel(zerolog.InfoLevel)
|
||||
if options.debug {
|
||||
if options.Debug {
|
||||
zerolog.SetGlobalLevel(zerolog.DebugLevel)
|
||||
}
|
||||
|
||||
log.Info().Msgf("Starting LocalAI using %d threads, with models path: %s", options.Threads, options.Loader.ModelPath)
|
||||
log.Info().Msgf("LocalAI version: %s", internal.PrintableVersion())
|
||||
|
||||
cl := config.NewConfigLoader()
|
||||
if err := cl.LoadConfigs(options.Loader.ModelPath); err != nil {
|
||||
log.Error().Msgf("error loading config files: %s", err.Error())
|
||||
}
|
||||
|
||||
if options.ConfigFile != "" {
|
||||
if err := cl.LoadConfigFile(options.ConfigFile); err != nil {
|
||||
log.Error().Msgf("error loading config file: %s", err.Error())
|
||||
}
|
||||
}
|
||||
|
||||
if err := cl.Preload(options.Loader.ModelPath); err != nil {
|
||||
log.Error().Msgf("error downloading models: %s", err.Error())
|
||||
}
|
||||
|
||||
if options.Debug {
|
||||
for _, v := range cl.ListConfigs() {
|
||||
cfg, _ := cl.GetConfig(v)
|
||||
log.Debug().Msgf("Model: %s (config: %+v)", v, cfg)
|
||||
}
|
||||
}
|
||||
|
||||
if options.AssetsDestination != "" {
|
||||
// Extract files from the embedded FS
|
||||
err := assets.ExtractFiles(options.BackendAssets, options.AssetsDestination)
|
||||
log.Debug().Msgf("Extracting backend assets files to %s", options.AssetsDestination)
|
||||
if err != nil {
|
||||
log.Warn().Msgf("Failed extracting backend assets files: %s (might be required for some backends to work properly, like gpt4all)", err)
|
||||
}
|
||||
}
|
||||
|
||||
if options.PreloadJSONModels != "" {
|
||||
if err := localai.ApplyGalleryFromString(options.Loader.ModelPath, options.PreloadJSONModels, cl, options.Galleries); err != nil {
|
||||
return nil, nil, err
|
||||
}
|
||||
}
|
||||
|
||||
if options.PreloadModelsFromPath != "" {
|
||||
if err := localai.ApplyGalleryFromFile(options.Loader.ModelPath, options.PreloadModelsFromPath, cl, options.Galleries); err != nil {
|
||||
return nil, nil, err
|
||||
}
|
||||
}
|
||||
|
||||
// turn off any process that was started by GRPC if the context is canceled
|
||||
go func() {
|
||||
<-options.Context.Done()
|
||||
log.Debug().Msgf("Context canceled, shutting down")
|
||||
options.Loader.StopAllGRPC()
|
||||
}()
|
||||
|
||||
if options.WatchDog {
|
||||
wd := model.NewWatchDog(
|
||||
options.Loader,
|
||||
options.WatchDogBusyTimeout,
|
||||
options.WatchDogIdleTimeout,
|
||||
options.WatchDogBusy,
|
||||
options.WatchDogIdle)
|
||||
options.Loader.SetWatchDog(wd)
|
||||
go wd.Run()
|
||||
go func() {
|
||||
<-options.Context.Done()
|
||||
log.Debug().Msgf("Context canceled, shutting down")
|
||||
wd.Shutdown()
|
||||
}()
|
||||
}
|
||||
|
||||
return options, cl, nil
|
||||
}
|
||||
|
||||
func App(opts ...options.AppOption) (*fiber.App, error) {
|
||||
|
||||
options, cl, err := Startup(opts...)
|
||||
if err != nil {
|
||||
return nil, fmt.Errorf("failed basic startup tasks with error %s", err.Error())
|
||||
}
|
||||
|
||||
// Return errors as JSON responses
|
||||
app := fiber.New(fiber.Config{
|
||||
BodyLimit: options.uploadLimitMB * 1024 * 1024, // this is the default limit of 4MB
|
||||
DisableStartupMessage: options.disableMessage,
|
||||
BodyLimit: options.UploadLimitMB * 1024 * 1024, // this is the default limit of 4MB
|
||||
DisableStartupMessage: options.DisableMessage,
|
||||
// Override default error handler
|
||||
ErrorHandler: func(ctx *fiber.Ctx, err error) error {
|
||||
// Status code defaults to 500
|
||||
@@ -37,103 +129,132 @@ func App(opts ...AppOption) (*fiber.App, error) {
|
||||
|
||||
// Send custom error page
|
||||
return ctx.Status(code).JSON(
|
||||
ErrorResponse{
|
||||
Error: &APIError{Message: err.Error(), Code: code},
|
||||
schema.ErrorResponse{
|
||||
Error: &schema.APIError{Message: err.Error(), Code: code},
|
||||
},
|
||||
)
|
||||
},
|
||||
})
|
||||
|
||||
if options.debug {
|
||||
if options.Debug {
|
||||
app.Use(logger.New(logger.Config{
|
||||
Format: "[${ip}]:${port} ${status} - ${method} ${path}\n",
|
||||
}))
|
||||
}
|
||||
|
||||
cm := NewConfigMerger()
|
||||
if err := cm.LoadConfigs(options.loader.ModelPath); err != nil {
|
||||
log.Error().Msgf("error loading config files: %s", err.Error())
|
||||
}
|
||||
|
||||
if options.configFile != "" {
|
||||
if err := cm.LoadConfigFile(options.configFile); err != nil {
|
||||
log.Error().Msgf("error loading config file: %s", err.Error())
|
||||
}
|
||||
}
|
||||
|
||||
if options.debug {
|
||||
for _, v := range cm.ListConfigs() {
|
||||
cfg, _ := cm.GetConfig(v)
|
||||
log.Debug().Msgf("Model: %s (config: %+v)", v, cfg)
|
||||
}
|
||||
}
|
||||
|
||||
if options.assetsDestination != "" {
|
||||
// Extract files from the embedded FS
|
||||
err := assets.ExtractFiles(options.backendAssets, 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)
|
||||
}
|
||||
}
|
||||
|
||||
// Default middleware config
|
||||
app.Use(recover.New())
|
||||
|
||||
if options.preloadJSONModels != "" {
|
||||
if err := ApplyGalleryFromString(options.loader.ModelPath, options.preloadJSONModels, cm); err != nil {
|
||||
return nil, err
|
||||
}
|
||||
if options.Metrics != nil {
|
||||
app.Use(metrics.APIMiddleware(options.Metrics))
|
||||
}
|
||||
|
||||
if options.preloadModelsFromPath != "" {
|
||||
if err := ApplyGalleryFromFile(options.loader.ModelPath, options.preloadModelsFromPath, cm); err != nil {
|
||||
return nil, err
|
||||
// Auth middleware checking if API key is valid. If no API key is set, no auth is required.
|
||||
auth := func(c *fiber.Ctx) error {
|
||||
if len(options.ApiKeys) == 0 {
|
||||
return c.Next()
|
||||
}
|
||||
|
||||
// Check for api_keys.json file
|
||||
fileContent, err := os.ReadFile("api_keys.json")
|
||||
if err == nil {
|
||||
// Parse JSON content from the file
|
||||
var fileKeys []string
|
||||
err := json.Unmarshal(fileContent, &fileKeys)
|
||||
if err != nil {
|
||||
return c.Status(fiber.StatusInternalServerError).JSON(fiber.Map{"message": "Error parsing api_keys.json"})
|
||||
}
|
||||
|
||||
// Add file keys to options.ApiKeys
|
||||
options.ApiKeys = append(options.ApiKeys, fileKeys...)
|
||||
}
|
||||
|
||||
if len(options.ApiKeys) == 0 {
|
||||
return c.Next()
|
||||
}
|
||||
|
||||
authHeader := c.Get("Authorization")
|
||||
if authHeader == "" {
|
||||
return c.Status(fiber.StatusUnauthorized).JSON(fiber.Map{"message": "Authorization header missing"})
|
||||
}
|
||||
authHeaderParts := strings.Split(authHeader, " ")
|
||||
if len(authHeaderParts) != 2 || authHeaderParts[0] != "Bearer" {
|
||||
return c.Status(fiber.StatusUnauthorized).JSON(fiber.Map{"message": "Invalid Authorization header format"})
|
||||
}
|
||||
|
||||
apiKey := authHeaderParts[1]
|
||||
for _, key := range options.ApiKeys {
|
||||
if apiKey == key {
|
||||
return c.Next()
|
||||
}
|
||||
}
|
||||
|
||||
return c.Status(fiber.StatusUnauthorized).JSON(fiber.Map{"message": "Invalid API key"})
|
||||
|
||||
}
|
||||
|
||||
if options.cors {
|
||||
if options.corsAllowOrigins == "" {
|
||||
app.Use(cors.New())
|
||||
if options.CORS {
|
||||
var c func(ctx *fiber.Ctx) error
|
||||
if options.CORSAllowOrigins == "" {
|
||||
c = cors.New()
|
||||
} else {
|
||||
app.Use(cors.New(cors.Config{
|
||||
AllowOrigins: options.corsAllowOrigins,
|
||||
}))
|
||||
c = cors.New(cors.Config{AllowOrigins: options.CORSAllowOrigins})
|
||||
}
|
||||
|
||||
app.Use(c)
|
||||
}
|
||||
|
||||
// LocalAI API endpoints
|
||||
applier := newGalleryApplier(options.loader.ModelPath)
|
||||
applier.start(options.context, cm)
|
||||
app.Post("/models/apply", applyModelGallery(options.loader.ModelPath, cm, applier.C))
|
||||
app.Get("/models/jobs/:uuid", getOpStatus(applier))
|
||||
galleryService := localai.NewGalleryService(options.Loader.ModelPath)
|
||||
galleryService.Start(options.Context, cl)
|
||||
|
||||
app.Get("/version", auth, func(c *fiber.Ctx) error {
|
||||
return c.JSON(struct {
|
||||
Version string `json:"version"`
|
||||
}{Version: internal.PrintableVersion()})
|
||||
})
|
||||
|
||||
modelGalleryService := localai.CreateModelGalleryService(options.Galleries, options.Loader.ModelPath, galleryService)
|
||||
app.Post("/models/apply", auth, modelGalleryService.ApplyModelGalleryEndpoint())
|
||||
app.Get("/models/available", auth, modelGalleryService.ListModelFromGalleryEndpoint())
|
||||
app.Get("/models/galleries", auth, modelGalleryService.ListModelGalleriesEndpoint())
|
||||
app.Post("/models/galleries", auth, modelGalleryService.AddModelGalleryEndpoint())
|
||||
app.Delete("/models/galleries", auth, modelGalleryService.RemoveModelGalleryEndpoint())
|
||||
app.Get("/models/jobs/:uuid", auth, modelGalleryService.GetOpStatusEndpoint())
|
||||
app.Get("/models/jobs", auth, modelGalleryService.GetAllStatusEndpoint())
|
||||
|
||||
// openAI compatible API endpoint
|
||||
|
||||
// chat
|
||||
app.Post("/v1/chat/completions", chatEndpoint(cm, options))
|
||||
app.Post("/chat/completions", chatEndpoint(cm, options))
|
||||
app.Post("/v1/chat/completions", auth, openai.ChatEndpoint(cl, options))
|
||||
app.Post("/chat/completions", auth, openai.ChatEndpoint(cl, options))
|
||||
|
||||
// edit
|
||||
app.Post("/v1/edits", editEndpoint(cm, options))
|
||||
app.Post("/edits", editEndpoint(cm, options))
|
||||
app.Post("/v1/edits", auth, openai.EditEndpoint(cl, options))
|
||||
app.Post("/edits", auth, openai.EditEndpoint(cl, options))
|
||||
|
||||
// completion
|
||||
app.Post("/v1/completions", completionEndpoint(cm, options))
|
||||
app.Post("/completions", completionEndpoint(cm, options))
|
||||
app.Post("/v1/completions", auth, openai.CompletionEndpoint(cl, options))
|
||||
app.Post("/completions", auth, openai.CompletionEndpoint(cl, options))
|
||||
app.Post("/v1/engines/:model/completions", auth, openai.CompletionEndpoint(cl, options))
|
||||
|
||||
// embeddings
|
||||
app.Post("/v1/embeddings", embeddingsEndpoint(cm, options))
|
||||
app.Post("/embeddings", embeddingsEndpoint(cm, options))
|
||||
app.Post("/v1/engines/:model/embeddings", embeddingsEndpoint(cm, options))
|
||||
app.Post("/v1/embeddings", auth, openai.EmbeddingsEndpoint(cl, options))
|
||||
app.Post("/embeddings", auth, openai.EmbeddingsEndpoint(cl, options))
|
||||
app.Post("/v1/engines/:model/embeddings", auth, openai.EmbeddingsEndpoint(cl, options))
|
||||
|
||||
// audio
|
||||
app.Post("/v1/audio/transcriptions", transcriptEndpoint(cm, options))
|
||||
app.Post("/v1/audio/transcriptions", auth, openai.TranscriptEndpoint(cl, options))
|
||||
app.Post("/tts", auth, localai.TTSEndpoint(cl, options))
|
||||
|
||||
// images
|
||||
app.Post("/v1/images/generations", imageEndpoint(cm, options))
|
||||
app.Post("/v1/images/generations", auth, openai.ImageEndpoint(cl, options))
|
||||
|
||||
if options.imageDir != "" {
|
||||
app.Static("/generated-images", options.imageDir)
|
||||
if options.ImageDir != "" {
|
||||
app.Static("/generated-images", options.ImageDir)
|
||||
}
|
||||
|
||||
if options.AudioDir != "" {
|
||||
app.Static("/generated-audio", options.AudioDir)
|
||||
}
|
||||
|
||||
ok := func(c *fiber.Ctx) error {
|
||||
@@ -144,9 +265,16 @@ func App(opts ...AppOption) (*fiber.App, error) {
|
||||
app.Get("/healthz", ok)
|
||||
app.Get("/readyz", ok)
|
||||
|
||||
// Experimental Backend Statistics Module
|
||||
backendMonitor := localai.NewBackendMonitor(cl, options) // Split out for now
|
||||
app.Get("/backend/monitor", localai.BackendMonitorEndpoint(backendMonitor))
|
||||
app.Post("/backend/shutdown", localai.BackendShutdownEndpoint(backendMonitor))
|
||||
|
||||
// models
|
||||
app.Get("/v1/models", listModels(options.loader, cm))
|
||||
app.Get("/models", listModels(options.loader, cm))
|
||||
app.Get("/v1/models", auth, openai.ListModelsEndpoint(options.Loader, cl))
|
||||
app.Get("/models", auth, openai.ListModelsEndpoint(options.Loader, cl))
|
||||
|
||||
app.Get("/metrics", metrics.MetricsHandler())
|
||||
|
||||
return app, nil
|
||||
}
|
||||
|
||||
512
api/api_test.go
512
api/api_test.go
@@ -5,15 +5,20 @@ import (
|
||||
"context"
|
||||
"embed"
|
||||
"encoding/json"
|
||||
"errors"
|
||||
"fmt"
|
||||
"io/ioutil"
|
||||
"io"
|
||||
"net/http"
|
||||
"os"
|
||||
"path/filepath"
|
||||
"runtime"
|
||||
|
||||
. "github.com/go-skynet/LocalAI/api"
|
||||
"github.com/go-skynet/LocalAI/api/options"
|
||||
"github.com/go-skynet/LocalAI/metrics"
|
||||
"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"
|
||||
@@ -21,12 +26,14 @@ import (
|
||||
|
||||
openaigo "github.com/otiai10/openaigo"
|
||||
"github.com/sashabaranov/go-openai"
|
||||
"github.com/sashabaranov/go-openai/jsonschema"
|
||||
)
|
||||
|
||||
type modelApplyRequest struct {
|
||||
URL string `json:"url"`
|
||||
Name string `json:"name"`
|
||||
Overrides map[string]string `json:"overrides"`
|
||||
ID string `json:"id"`
|
||||
URL string `json:"url"`
|
||||
Name string `json:"name"`
|
||||
Overrides map[string]interface{} `json:"overrides"`
|
||||
}
|
||||
|
||||
func getModelStatus(url string) (response map[string]interface{}) {
|
||||
@@ -38,7 +45,7 @@ func getModelStatus(url string) (response map[string]interface{}) {
|
||||
}
|
||||
defer resp.Body.Close()
|
||||
|
||||
body, err := ioutil.ReadAll(resp.Body)
|
||||
body, err := io.ReadAll(resp.Body)
|
||||
if err != nil {
|
||||
fmt.Println("Error reading response body:", err)
|
||||
return
|
||||
@@ -52,6 +59,15 @@ func getModelStatus(url string) (response map[string]interface{}) {
|
||||
}
|
||||
return
|
||||
}
|
||||
|
||||
func getModels(url string) (response []gallery.GalleryModel) {
|
||||
utils.GetURI(url, func(url string, i []byte) error {
|
||||
// Unmarshal YAML data into a struct
|
||||
return json.Unmarshal(i, &response)
|
||||
})
|
||||
return
|
||||
}
|
||||
|
||||
func postModelApplyRequest(url string, request modelApplyRequest) (response map[string]interface{}) {
|
||||
|
||||
//url := "http://localhost:AI/models/apply"
|
||||
@@ -81,7 +97,7 @@ func postModelApplyRequest(url string, request modelApplyRequest) (response map[
|
||||
}
|
||||
defer resp.Body.Close()
|
||||
|
||||
body, err := ioutil.ReadAll(resp.Body)
|
||||
body, err := io.ReadAll(resp.Body)
|
||||
if err != nil {
|
||||
fmt.Println("Error reading response body:", err)
|
||||
return
|
||||
@@ -109,6 +125,11 @@ var _ = Describe("API test", func() {
|
||||
var cancel context.CancelFunc
|
||||
var tmpdir string
|
||||
|
||||
commonOpts := []options.AppOption{
|
||||
options.WithDebug(true),
|
||||
options.WithDisableMessage(true),
|
||||
}
|
||||
|
||||
Context("API with ephemeral models", func() {
|
||||
BeforeEach(func() {
|
||||
var err error
|
||||
@@ -118,7 +139,39 @@ var _ = Describe("API test", func() {
|
||||
modelLoader = model.NewModelLoader(tmpdir)
|
||||
c, cancel = context.WithCancel(context.Background())
|
||||
|
||||
app, err = App(WithContext(c), WithModelLoader(modelLoader), WithBackendAssets(backendAssets), WithBackendAssetsOutput(tmpdir))
|
||||
g := []gallery.GalleryModel{
|
||||
{
|
||||
Name: "bert",
|
||||
URL: "https://raw.githubusercontent.com/go-skynet/model-gallery/main/bert-embeddings.yaml",
|
||||
},
|
||||
{
|
||||
Name: "bert2",
|
||||
URL: "https://raw.githubusercontent.com/go-skynet/model-gallery/main/bert-embeddings.yaml",
|
||||
Overrides: map[string]interface{}{"foo": "bar"},
|
||||
AdditionalFiles: []gallery.File{{Filename: "foo.yaml", URI: "https://raw.githubusercontent.com/go-skynet/model-gallery/main/bert-embeddings.yaml"}},
|
||||
},
|
||||
}
|
||||
out, err := yaml.Marshal(g)
|
||||
Expect(err).ToNot(HaveOccurred())
|
||||
err = os.WriteFile(filepath.Join(tmpdir, "gallery_simple.yaml"), out, 0644)
|
||||
Expect(err).ToNot(HaveOccurred())
|
||||
|
||||
galleries := []gallery.Gallery{
|
||||
{
|
||||
Name: "test",
|
||||
URL: "file://" + filepath.Join(tmpdir, "gallery_simple.yaml"),
|
||||
},
|
||||
}
|
||||
|
||||
metricsService, err := metrics.SetupMetrics()
|
||||
Expect(err).ToNot(HaveOccurred())
|
||||
|
||||
app, err = App(
|
||||
append(commonOpts,
|
||||
options.WithMetrics(metricsService),
|
||||
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")
|
||||
|
||||
@@ -143,11 +196,58 @@ var _ = Describe("API test", func() {
|
||||
})
|
||||
|
||||
Context("Applying models", func() {
|
||||
It("applies models from a gallery", func() {
|
||||
|
||||
models := getModels("http://127.0.0.1:9090/models/available")
|
||||
Expect(len(models)).To(Equal(2), fmt.Sprint(models))
|
||||
Expect(models[0].Installed).To(BeFalse(), fmt.Sprint(models))
|
||||
Expect(models[1].Installed).To(BeFalse(), fmt.Sprint(models))
|
||||
|
||||
response := postModelApplyRequest("http://127.0.0.1:9090/models/apply", modelApplyRequest{
|
||||
ID: "test@bert2",
|
||||
})
|
||||
|
||||
Expect(response["uuid"]).ToNot(BeEmpty(), fmt.Sprint(response))
|
||||
|
||||
uuid := response["uuid"].(string)
|
||||
resp := map[string]interface{}{}
|
||||
Eventually(func() bool {
|
||||
response := getModelStatus("http://127.0.0.1:9090/models/jobs/" + uuid)
|
||||
fmt.Println(response)
|
||||
resp = response
|
||||
return response["processed"].(bool)
|
||||
}, "360s", "10s").Should(Equal(true))
|
||||
Expect(resp["message"]).ToNot(ContainSubstring("error"))
|
||||
|
||||
dat, err := os.ReadFile(filepath.Join(tmpdir, "bert2.yaml"))
|
||||
Expect(err).ToNot(HaveOccurred())
|
||||
|
||||
_, err = os.ReadFile(filepath.Join(tmpdir, "foo.yaml"))
|
||||
Expect(err).ToNot(HaveOccurred())
|
||||
|
||||
content := map[string]interface{}{}
|
||||
err = yaml.Unmarshal(dat, &content)
|
||||
Expect(err).ToNot(HaveOccurred())
|
||||
Expect(content["backend"]).To(Equal("bert-embeddings"))
|
||||
Expect(content["foo"]).To(Equal("bar"))
|
||||
|
||||
models = getModels("http://127.0.0.1:9090/models/available")
|
||||
Expect(len(models)).To(Equal(2), fmt.Sprint(models))
|
||||
Expect(models[0].Name).To(Or(Equal("bert"), Equal("bert2")))
|
||||
Expect(models[1].Name).To(Or(Equal("bert"), Equal("bert2")))
|
||||
for _, m := range models {
|
||||
if m.Name == "bert2" {
|
||||
Expect(m.Installed).To(BeTrue())
|
||||
} else {
|
||||
Expect(m.Installed).To(BeFalse())
|
||||
}
|
||||
}
|
||||
})
|
||||
It("overrides models", func() {
|
||||
response := postModelApplyRequest("http://127.0.0.1:9090/models/apply", modelApplyRequest{
|
||||
URL: "https://raw.githubusercontent.com/go-skynet/model-gallery/main/bert-embeddings.yaml",
|
||||
Name: "bert",
|
||||
Overrides: map[string]string{
|
||||
Overrides: map[string]interface{}{
|
||||
"backend": "llama",
|
||||
},
|
||||
})
|
||||
@@ -158,9 +258,8 @@ var _ = Describe("API test", func() {
|
||||
|
||||
Eventually(func() bool {
|
||||
response := getModelStatus("http://127.0.0.1:9090/models/jobs/" + uuid)
|
||||
fmt.Println(response)
|
||||
return response["processed"].(bool)
|
||||
}, "360s").Should(Equal(true))
|
||||
}, "360s", "10s").Should(Equal(true))
|
||||
|
||||
dat, err := os.ReadFile(filepath.Join(tmpdir, "bert.yaml"))
|
||||
Expect(err).ToNot(HaveOccurred())
|
||||
@@ -174,7 +273,7 @@ var _ = Describe("API test", func() {
|
||||
response := postModelApplyRequest("http://127.0.0.1:9090/models/apply", modelApplyRequest{
|
||||
URL: "https://raw.githubusercontent.com/go-skynet/model-gallery/main/bert-embeddings.yaml",
|
||||
Name: "bert",
|
||||
Overrides: map[string]string{},
|
||||
Overrides: map[string]interface{}{},
|
||||
})
|
||||
|
||||
Expect(response["uuid"]).ToNot(BeEmpty(), fmt.Sprint(response))
|
||||
@@ -183,9 +282,8 @@ var _ = Describe("API test", func() {
|
||||
|
||||
Eventually(func() bool {
|
||||
response := getModelStatus("http://127.0.0.1:9090/models/jobs/" + uuid)
|
||||
fmt.Println(response)
|
||||
return response["processed"].(bool)
|
||||
}, "360s").Should(Equal(true))
|
||||
}, "360s", "10s").Should(Equal(true))
|
||||
|
||||
dat, err := os.ReadFile(filepath.Join(tmpdir, "bert.yaml"))
|
||||
Expect(err).ToNot(HaveOccurred())
|
||||
@@ -196,14 +294,14 @@ var _ = Describe("API test", func() {
|
||||
Expect(content["backend"]).To(Equal("bert-embeddings"))
|
||||
})
|
||||
|
||||
It("runs openllama", Label("llama"), func() {
|
||||
It("runs openllama(llama-ggml backend)", 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{},
|
||||
Overrides: map[string]interface{}{"backend": "llama-ggml", "mmap": true, "f16": true, "context_size": 128},
|
||||
})
|
||||
|
||||
Expect(response["uuid"]).ToNot(BeEmpty(), fmt.Sprint(response))
|
||||
@@ -212,14 +310,135 @@ var _ = Describe("API test", func() {
|
||||
|
||||
Eventually(func() bool {
|
||||
response := getModelStatus("http://127.0.0.1:9090/models/jobs/" + uuid)
|
||||
fmt.Println(response)
|
||||
return response["processed"].(bool)
|
||||
}, "360s").Should(Equal(true))
|
||||
}, "360s", "10s").Should(Equal(true))
|
||||
|
||||
By("testing completion")
|
||||
resp, err := client.CreateCompletion(context.TODO(), openai.CompletionRequest{Model: "openllama_3b", Prompt: "Count up to five: one, two, three, four, "})
|
||||
Expect(err).ToNot(HaveOccurred())
|
||||
Expect(len(resp.Choices)).To(Equal(1))
|
||||
Expect(resp.Choices[0].Text).To(ContainSubstring("five"))
|
||||
|
||||
By("testing functions")
|
||||
resp2, err := client.CreateChatCompletion(
|
||||
context.TODO(),
|
||||
openai.ChatCompletionRequest{
|
||||
Model: "openllama_3b",
|
||||
Messages: []openai.ChatCompletionMessage{
|
||||
{
|
||||
Role: "user",
|
||||
Content: "What is the weather like in San Francisco (celsius)?",
|
||||
},
|
||||
},
|
||||
Functions: []openai.FunctionDefinition{
|
||||
openai.FunctionDefinition{
|
||||
Name: "get_current_weather",
|
||||
Description: "Get the current weather",
|
||||
Parameters: jsonschema.Definition{
|
||||
Type: jsonschema.Object,
|
||||
Properties: map[string]jsonschema.Definition{
|
||||
"location": {
|
||||
Type: jsonschema.String,
|
||||
Description: "The city and state, e.g. San Francisco, CA",
|
||||
},
|
||||
"unit": {
|
||||
Type: jsonschema.String,
|
||||
Enum: []string{"celcius", "fahrenheit"},
|
||||
},
|
||||
},
|
||||
Required: []string{"location"},
|
||||
},
|
||||
},
|
||||
},
|
||||
})
|
||||
Expect(err).ToNot(HaveOccurred())
|
||||
Expect(len(resp2.Choices)).To(Equal(1))
|
||||
Expect(resp2.Choices[0].Message.FunctionCall).ToNot(BeNil())
|
||||
Expect(resp2.Choices[0].Message.FunctionCall.Name).To(Equal("get_current_weather"), resp2.Choices[0].Message.FunctionCall.Name)
|
||||
|
||||
var res map[string]string
|
||||
err = json.Unmarshal([]byte(resp2.Choices[0].Message.FunctionCall.Arguments), &res)
|
||||
Expect(err).ToNot(HaveOccurred())
|
||||
Expect(res["location"]).To(Equal("San Francisco, California, United States"), fmt.Sprint(res))
|
||||
Expect(res["unit"]).To(Equal("celcius"), fmt.Sprint(res))
|
||||
Expect(string(resp2.Choices[0].FinishReason)).To(Equal("function_call"), fmt.Sprint(resp2.Choices[0].FinishReason))
|
||||
|
||||
})
|
||||
|
||||
It("runs openllama gguf(llama-cpp)", Label("llama-gguf"), func() {
|
||||
if runtime.GOOS != "linux" {
|
||||
Skip("test supported only on linux")
|
||||
}
|
||||
modelName := "codellama"
|
||||
response := postModelApplyRequest("http://127.0.0.1:9090/models/apply", modelApplyRequest{
|
||||
URL: "github:go-skynet/model-gallery/codellama-7b-instruct.yaml",
|
||||
Name: modelName,
|
||||
Overrides: map[string]interface{}{"backend": "llama", "mmap": true, "f16": true, "context_size": 128},
|
||||
})
|
||||
|
||||
Expect(response["uuid"]).ToNot(BeEmpty(), fmt.Sprint(response))
|
||||
|
||||
uuid := response["uuid"].(string)
|
||||
|
||||
Eventually(func() bool {
|
||||
response := getModelStatus("http://127.0.0.1:9090/models/jobs/" + uuid)
|
||||
return response["processed"].(bool)
|
||||
}, "360s", "10s").Should(Equal(true))
|
||||
|
||||
By("testing chat")
|
||||
resp, err := client.CreateChatCompletion(context.TODO(), openai.ChatCompletionRequest{Model: modelName, Messages: []openai.ChatCompletionMessage{
|
||||
{
|
||||
Role: "user",
|
||||
Content: "How much is 2+2?",
|
||||
},
|
||||
}})
|
||||
Expect(err).ToNot(HaveOccurred())
|
||||
Expect(len(resp.Choices)).To(Equal(1))
|
||||
Expect(resp.Choices[0].Message.Content).To(Or(ContainSubstring("4"), ContainSubstring("four")))
|
||||
|
||||
By("testing functions")
|
||||
resp2, err := client.CreateChatCompletion(
|
||||
context.TODO(),
|
||||
openai.ChatCompletionRequest{
|
||||
Model: modelName,
|
||||
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() {
|
||||
@@ -228,9 +447,8 @@ var _ = Describe("API test", func() {
|
||||
}
|
||||
|
||||
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{},
|
||||
URL: "github:go-skynet/model-gallery/gpt4all-j.yaml",
|
||||
Name: "gpt4all-j",
|
||||
})
|
||||
|
||||
Expect(response["uuid"]).ToNot(BeEmpty(), fmt.Sprint(response))
|
||||
@@ -239,15 +457,134 @@ var _ = Describe("API test", func() {
|
||||
|
||||
Eventually(func() bool {
|
||||
response := getModelStatus("http://127.0.0.1:9090/models/jobs/" + uuid)
|
||||
fmt.Println(response)
|
||||
return response["processed"].(bool)
|
||||
}, "360s").Should(Equal(true))
|
||||
}, "960s", "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",
|
||||
},
|
||||
}
|
||||
|
||||
metricsService, err := metrics.SetupMetrics()
|
||||
Expect(err).ToNot(HaveOccurred())
|
||||
|
||||
app, err = App(
|
||||
append(commonOpts,
|
||||
options.WithContext(c),
|
||||
options.WithMetrics(metricsService),
|
||||
options.WithAudioDir(tmpdir),
|
||||
options.WithImageDir(tmpdir),
|
||||
options.WithGalleries(galleries),
|
||||
options.WithModelLoader(modelLoader),
|
||||
options.WithBackendAssets(backendAssets),
|
||||
options.WithBackendAssetsOutput(tmpdir))...,
|
||||
)
|
||||
Expect(err).ToNot(HaveOccurred())
|
||||
go app.Listen("127.0.0.1:9090")
|
||||
|
||||
defaultConfig := openai.DefaultConfig("")
|
||||
defaultConfig.BaseURL = "http://127.0.0.1:9090/v1"
|
||||
|
||||
client2 = openaigo.NewClient("")
|
||||
client2.BaseURL = defaultConfig.BaseURL
|
||||
|
||||
// Wait for API to be ready
|
||||
client = openai.NewClientWithConfig(defaultConfig)
|
||||
Eventually(func() error {
|
||||
_, err := client.ListModels(context.TODO())
|
||||
return err
|
||||
}, "2m").ShouldNot(HaveOccurred())
|
||||
})
|
||||
|
||||
AfterEach(func() {
|
||||
cancel()
|
||||
app.Shutdown()
|
||||
os.RemoveAll(tmpdir)
|
||||
})
|
||||
It("installs and is capable to run tts", Label("tts"), func() {
|
||||
if runtime.GOOS != "linux" {
|
||||
Skip("test supported only on linux")
|
||||
}
|
||||
|
||||
response := postModelApplyRequest("http://127.0.0.1:9090/models/apply", modelApplyRequest{
|
||||
ID: "model-gallery@voice-en-us-kathleen-low",
|
||||
})
|
||||
|
||||
Expect(response["uuid"]).ToNot(BeEmpty(), fmt.Sprint(response))
|
||||
|
||||
uuid := response["uuid"].(string)
|
||||
|
||||
Eventually(func() bool {
|
||||
response := getModelStatus("http://127.0.0.1:9090/models/jobs/" + uuid)
|
||||
fmt.Println(response)
|
||||
return response["processed"].(bool)
|
||||
}, "360s", "10s").Should(Equal(true))
|
||||
|
||||
// An HTTP Post to the /tts endpoint should return a wav audio file
|
||||
resp, err := http.Post("http://127.0.0.1:9090/tts", "application/json", bytes.NewBuffer([]byte(`{"input": "Hello world", "model": "en-us-kathleen-low.onnx"}`)))
|
||||
Expect(err).ToNot(HaveOccurred(), fmt.Sprint(resp))
|
||||
dat, err := io.ReadAll(resp.Body)
|
||||
Expect(err).ToNot(HaveOccurred(), fmt.Sprint(resp))
|
||||
|
||||
Expect(resp.StatusCode).To(Equal(200), fmt.Sprint(string(dat)))
|
||||
Expect(resp.Header.Get("Content-Type")).To(Equal("audio/x-wav"))
|
||||
})
|
||||
It("installs and is capable to generate images", Label("stablediffusion"), func() {
|
||||
if runtime.GOOS != "linux" {
|
||||
Skip("test supported only on linux")
|
||||
}
|
||||
|
||||
response := postModelApplyRequest("http://127.0.0.1:9090/models/apply", modelApplyRequest{
|
||||
ID: "model-gallery@stablediffusion",
|
||||
Overrides: map[string]interface{}{
|
||||
"parameters": map[string]interface{}{"model": "stablediffusion_assets"},
|
||||
},
|
||||
})
|
||||
|
||||
Expect(response["uuid"]).ToNot(BeEmpty(), fmt.Sprint(response))
|
||||
|
||||
uuid := response["uuid"].(string)
|
||||
|
||||
Eventually(func() bool {
|
||||
response := getModelStatus("http://127.0.0.1:9090/models/jobs/" + uuid)
|
||||
fmt.Println(response)
|
||||
return response["processed"].(bool)
|
||||
}, "360s", "10s").Should(Equal(true))
|
||||
|
||||
resp, err := http.Post(
|
||||
"http://127.0.0.1:9090/v1/images/generations",
|
||||
"application/json",
|
||||
bytes.NewBuffer([]byte(`{
|
||||
"prompt": "floating hair, portrait, ((loli)), ((one girl)), cute face, hidden hands, asymmetrical bangs, beautiful detailed eyes, eye shadow, hair ornament, ribbons, bowties, buttons, pleated skirt, (((masterpiece))), ((best quality)), colorful|((part of the head)), ((((mutated hands and fingers)))), deformed, blurry, bad anatomy, disfigured, poorly drawn face, mutation, mutated, extra limb, ugly, poorly drawn hands, missing limb, blurry, floating limbs, disconnected limbs, malformed hands, blur, out of focus, long neck, long body, Octane renderer, lowres, bad anatomy, bad hands, text",
|
||||
"mode": 2, "seed":9000,
|
||||
"size": "256x256", "n":2}`)))
|
||||
// The response should contain an URL
|
||||
Expect(err).ToNot(HaveOccurred(), fmt.Sprint(resp))
|
||||
dat, err := io.ReadAll(resp.Body)
|
||||
Expect(err).ToNot(HaveOccurred(), string(dat))
|
||||
Expect(string(dat)).To(ContainSubstring("http://127.0.0.1:9090/"), string(dat))
|
||||
Expect(string(dat)).To(ContainSubstring(".png"), string(dat))
|
||||
|
||||
})
|
||||
})
|
||||
|
||||
@@ -256,8 +593,16 @@ var _ = Describe("API test", func() {
|
||||
modelLoader = model.NewModelLoader(os.Getenv("MODELS_PATH"))
|
||||
c, cancel = context.WithCancel(context.Background())
|
||||
|
||||
var err error
|
||||
app, err = App(WithContext(c), WithModelLoader(modelLoader))
|
||||
metricsService, err := metrics.SetupMetrics()
|
||||
Expect(err).ToNot(HaveOccurred())
|
||||
|
||||
app, err = App(
|
||||
append(commonOpts,
|
||||
options.WithExternalBackend("huggingface", os.Getenv("HUGGINGFACE_GRPC")),
|
||||
options.WithContext(c),
|
||||
options.WithModelLoader(modelLoader),
|
||||
options.WithMetrics(metricsService),
|
||||
)...)
|
||||
Expect(err).ToNot(HaveOccurred())
|
||||
go app.Listen("127.0.0.1:9090")
|
||||
|
||||
@@ -281,7 +626,7 @@ var _ = Describe("API test", func() {
|
||||
It("returns the models list", func() {
|
||||
models, err := client.ListModels(context.TODO())
|
||||
Expect(err).ToNot(HaveOccurred())
|
||||
Expect(len(models.Models)).To(Equal(10))
|
||||
Expect(len(models.Models)).To(Equal(6)) // If "config.yaml" should be included, this should be 8?
|
||||
})
|
||||
It("can generate completions", func() {
|
||||
resp, err := client.CreateCompletion(context.TODO(), openai.CompletionRequest{Model: "testmodel", Prompt: "abcdedfghikl"})
|
||||
@@ -312,9 +657,10 @@ var _ = Describe("API test", func() {
|
||||
})
|
||||
|
||||
It("returns errors", func() {
|
||||
backends := len(model.AutoLoadBackends) + 1 // +1 for huggingface
|
||||
_, err := client.CreateCompletion(context.TODO(), openai.CompletionRequest{Model: "foomodel", Prompt: "abcdedfghikl"})
|
||||
Expect(err).To(HaveOccurred())
|
||||
Expect(err.Error()).To(ContainSubstring("error, status code: 500, message: could not load model - all backends returned error: 11 errors occurred:"))
|
||||
Expect(err.Error()).To(ContainSubstring(fmt.Sprintf("error, status code: 500, message: could not load model - all backends returned error: %d errors occurred:", backends)))
|
||||
})
|
||||
It("transcribes audio", func() {
|
||||
if runtime.GOOS != "linux" {
|
||||
@@ -342,7 +688,7 @@ var _ = Describe("API test", func() {
|
||||
Input: []string{"sun", "cat"},
|
||||
},
|
||||
)
|
||||
Expect(err).ToNot(HaveOccurred())
|
||||
Expect(err).ToNot(HaveOccurred(), err)
|
||||
Expect(len(resp.Data[0].Embedding)).To(BeNumerically("==", 384))
|
||||
Expect(len(resp.Data[1].Embedding)).To(BeNumerically("==", 384))
|
||||
|
||||
@@ -358,15 +704,98 @@ var _ = Describe("API test", func() {
|
||||
Expect(resp2.Data[0].Embedding).To(Equal(sunEmbedding))
|
||||
})
|
||||
|
||||
Context("External gRPC calls", func() {
|
||||
It("calculate embeddings with sentencetransformers", func() {
|
||||
if runtime.GOOS != "linux" {
|
||||
Skip("test supported only on linux")
|
||||
}
|
||||
resp, err := client.CreateEmbeddings(
|
||||
context.Background(),
|
||||
openai.EmbeddingRequest{
|
||||
Model: openai.AdaCodeSearchCode,
|
||||
Input: []string{"sun", "cat"},
|
||||
},
|
||||
)
|
||||
Expect(err).ToNot(HaveOccurred())
|
||||
Expect(len(resp.Data[0].Embedding)).To(BeNumerically("==", 384))
|
||||
Expect(len(resp.Data[1].Embedding)).To(BeNumerically("==", 384))
|
||||
|
||||
sunEmbedding := resp.Data[0].Embedding
|
||||
resp2, err := client.CreateEmbeddings(
|
||||
context.Background(),
|
||||
openai.EmbeddingRequest{
|
||||
Model: openai.AdaCodeSearchCode,
|
||||
Input: []string{"sun"},
|
||||
},
|
||||
)
|
||||
Expect(err).ToNot(HaveOccurred())
|
||||
Expect(resp2.Data[0].Embedding).To(Equal(sunEmbedding))
|
||||
Expect(resp2.Data[0].Embedding).ToNot(Equal(resp.Data[1].Embedding))
|
||||
})
|
||||
})
|
||||
|
||||
Context("backends", func() {
|
||||
It("runs rwkv", func() {
|
||||
It("runs rwkv completion", func() {
|
||||
if runtime.GOOS != "linux" {
|
||||
Skip("test supported only on linux")
|
||||
}
|
||||
resp, err := client.CreateCompletion(context.TODO(), openai.CompletionRequest{Model: "rwkv_test", Prompt: "Count up to five: one, two, three, four,"})
|
||||
Expect(err).ToNot(HaveOccurred())
|
||||
Expect(len(resp.Choices) > 0).To(BeTrue())
|
||||
Expect(resp.Choices[0].Text).To(Equal(" five."))
|
||||
Expect(resp.Choices[0].Text).To(ContainSubstring("five"))
|
||||
|
||||
stream, err := client.CreateCompletionStream(context.TODO(), openai.CompletionRequest{
|
||||
Model: "rwkv_test", Prompt: "Count up to five: one, two, three, four,", Stream: true,
|
||||
})
|
||||
Expect(err).ToNot(HaveOccurred())
|
||||
defer stream.Close()
|
||||
|
||||
tokens := 0
|
||||
text := ""
|
||||
for {
|
||||
response, err := stream.Recv()
|
||||
if errors.Is(err, io.EOF) {
|
||||
break
|
||||
}
|
||||
|
||||
Expect(err).ToNot(HaveOccurred())
|
||||
text += response.Choices[0].Text
|
||||
tokens++
|
||||
}
|
||||
Expect(text).ToNot(BeEmpty())
|
||||
Expect(text).To(ContainSubstring("five"))
|
||||
Expect(tokens).ToNot(Or(Equal(1), Equal(0)))
|
||||
})
|
||||
It("runs rwkv chat completion", func() {
|
||||
if runtime.GOOS != "linux" {
|
||||
Skip("test supported only on linux")
|
||||
}
|
||||
resp, err := client.CreateChatCompletion(context.TODO(),
|
||||
openai.ChatCompletionRequest{Model: "rwkv_test", Messages: []openai.ChatCompletionMessage{{Content: "Can you count up to five?", Role: "user"}}})
|
||||
Expect(err).ToNot(HaveOccurred())
|
||||
Expect(len(resp.Choices) > 0).To(BeTrue())
|
||||
Expect(resp.Choices[0].Message.Content).To(Or(ContainSubstring("Sure"), ContainSubstring("five")))
|
||||
|
||||
stream, err := client.CreateChatCompletionStream(context.TODO(), openai.ChatCompletionRequest{Model: "rwkv_test", Messages: []openai.ChatCompletionMessage{{Content: "Can you count up to five?", Role: "user"}}})
|
||||
Expect(err).ToNot(HaveOccurred())
|
||||
defer stream.Close()
|
||||
|
||||
tokens := 0
|
||||
text := ""
|
||||
for {
|
||||
response, err := stream.Recv()
|
||||
if errors.Is(err, io.EOF) {
|
||||
break
|
||||
}
|
||||
|
||||
Expect(err).ToNot(HaveOccurred())
|
||||
text += response.Choices[0].Delta.Content
|
||||
tokens++
|
||||
}
|
||||
Expect(text).ToNot(BeEmpty())
|
||||
Expect(text).To(Or(ContainSubstring("Sure"), ContainSubstring("five")))
|
||||
|
||||
Expect(tokens).ToNot(Or(Equal(1), Equal(0)))
|
||||
})
|
||||
})
|
||||
})
|
||||
@@ -376,8 +805,16 @@ var _ = Describe("API test", func() {
|
||||
modelLoader = model.NewModelLoader(os.Getenv("MODELS_PATH"))
|
||||
c, cancel = context.WithCancel(context.Background())
|
||||
|
||||
var err error
|
||||
app, err = App(WithContext(c), WithModelLoader(modelLoader), WithConfigFile(os.Getenv("CONFIG_FILE")))
|
||||
metricsService, err := metrics.SetupMetrics()
|
||||
Expect(err).ToNot(HaveOccurred())
|
||||
|
||||
app, err = App(
|
||||
append(commonOpts,
|
||||
options.WithContext(c),
|
||||
options.WithMetrics(metricsService),
|
||||
options.WithModelLoader(modelLoader),
|
||||
options.WithConfigFile(os.Getenv("CONFIG_FILE")))...,
|
||||
)
|
||||
Expect(err).ToNot(HaveOccurred())
|
||||
go app.Listen("127.0.0.1:9090")
|
||||
|
||||
@@ -396,19 +833,14 @@ var _ = Describe("API test", func() {
|
||||
cancel()
|
||||
app.Shutdown()
|
||||
})
|
||||
It("can generate chat completions from config file", func() {
|
||||
models, err := client.ListModels(context.TODO())
|
||||
Expect(err).ToNot(HaveOccurred())
|
||||
Expect(len(models.Models)).To(Equal(12))
|
||||
})
|
||||
It("can generate chat completions from config file", func() {
|
||||
resp, err := client.CreateChatCompletion(context.TODO(), openai.ChatCompletionRequest{Model: "list1", Messages: []openai.ChatCompletionMessage{openai.ChatCompletionMessage{Role: "user", Content: "abcdedfghikl"}}})
|
||||
It("can generate chat completions from config file (list1)", func() {
|
||||
resp, err := client.CreateChatCompletion(context.TODO(), openai.ChatCompletionRequest{Model: "list1", Messages: []openai.ChatCompletionMessage{{Role: "user", Content: "abcdedfghikl"}}})
|
||||
Expect(err).ToNot(HaveOccurred())
|
||||
Expect(len(resp.Choices)).To(Equal(1))
|
||||
Expect(resp.Choices[0].Message.Content).ToNot(BeEmpty())
|
||||
})
|
||||
It("can generate chat completions from config file", func() {
|
||||
resp, err := client.CreateChatCompletion(context.TODO(), openai.ChatCompletionRequest{Model: "list2", Messages: []openai.ChatCompletionMessage{openai.ChatCompletionMessage{Role: "user", Content: "abcdedfghikl"}}})
|
||||
It("can generate chat completions from config file (list2)", func() {
|
||||
resp, err := client.CreateChatCompletion(context.TODO(), openai.ChatCompletionRequest{Model: "list2", Messages: []openai.ChatCompletionMessage{{Role: "user", Content: "abcdedfghikl"}}})
|
||||
Expect(err).ToNot(HaveOccurred())
|
||||
Expect(len(resp.Choices)).To(Equal(1))
|
||||
Expect(resp.Choices[0].Message.Content).ToNot(BeEmpty())
|
||||
|
||||
92
api/backend/embeddings.go
Normal file
92
api/backend/embeddings.go
Normal file
@@ -0,0 +1,92 @@
|
||||
package backend
|
||||
|
||||
import (
|
||||
"fmt"
|
||||
|
||||
config "github.com/go-skynet/LocalAI/api/config"
|
||||
"github.com/go-skynet/LocalAI/api/options"
|
||||
"github.com/go-skynet/LocalAI/pkg/grpc"
|
||||
model "github.com/go-skynet/LocalAI/pkg/model"
|
||||
)
|
||||
|
||||
func ModelEmbedding(s string, tokens []int, loader *model.ModelLoader, c config.Config, o *options.Option) (func() ([]float32, error), error) {
|
||||
if !c.Embeddings {
|
||||
return nil, fmt.Errorf("endpoint disabled for this model by API configuration")
|
||||
}
|
||||
|
||||
modelFile := c.Model
|
||||
|
||||
grpcOpts := gRPCModelOpts(c)
|
||||
|
||||
var inferenceModel interface{}
|
||||
var err error
|
||||
|
||||
opts := modelOpts(c, o, []model.Option{
|
||||
model.WithLoadGRPCLoadModelOpts(grpcOpts),
|
||||
model.WithThreads(uint32(c.Threads)),
|
||||
model.WithAssetDir(o.AssetsDestination),
|
||||
model.WithModel(modelFile),
|
||||
model.WithContext(o.Context),
|
||||
})
|
||||
|
||||
if c.Backend == "" {
|
||||
inferenceModel, err = loader.GreedyLoader(opts...)
|
||||
} else {
|
||||
opts = append(opts, model.WithBackendString(c.Backend))
|
||||
inferenceModel, err = loader.BackendLoader(opts...)
|
||||
}
|
||||
if err != nil {
|
||||
return nil, err
|
||||
}
|
||||
|
||||
var fn func() ([]float32, error)
|
||||
switch model := inferenceModel.(type) {
|
||||
case *grpc.Client:
|
||||
fn = func() ([]float32, error) {
|
||||
predictOptions := gRPCPredictOpts(c, loader.ModelPath)
|
||||
if len(tokens) > 0 {
|
||||
embeds := []int32{}
|
||||
|
||||
for _, t := range tokens {
|
||||
embeds = append(embeds, int32(t))
|
||||
}
|
||||
predictOptions.EmbeddingTokens = embeds
|
||||
|
||||
res, err := model.Embeddings(o.Context, predictOptions)
|
||||
if err != nil {
|
||||
return nil, err
|
||||
}
|
||||
|
||||
return res.Embeddings, nil
|
||||
}
|
||||
predictOptions.Embeddings = s
|
||||
|
||||
res, err := model.Embeddings(o.Context, predictOptions)
|
||||
if err != nil {
|
||||
return nil, err
|
||||
}
|
||||
|
||||
return res.Embeddings, nil
|
||||
}
|
||||
default:
|
||||
fn = func() ([]float32, error) {
|
||||
return nil, fmt.Errorf("embeddings not supported by the backend")
|
||||
}
|
||||
}
|
||||
|
||||
return func() ([]float32, error) {
|
||||
embeds, err := fn()
|
||||
if err != nil {
|
||||
return embeds, err
|
||||
}
|
||||
// Remove trailing 0s
|
||||
for i := len(embeds) - 1; i >= 0; i-- {
|
||||
if embeds[i] == 0.0 {
|
||||
embeds = embeds[:i]
|
||||
} else {
|
||||
break
|
||||
}
|
||||
}
|
||||
return embeds, nil
|
||||
}, nil
|
||||
}
|
||||
61
api/backend/image.go
Normal file
61
api/backend/image.go
Normal file
@@ -0,0 +1,61 @@
|
||||
package backend
|
||||
|
||||
import (
|
||||
config "github.com/go-skynet/LocalAI/api/config"
|
||||
"github.com/go-skynet/LocalAI/api/options"
|
||||
"github.com/go-skynet/LocalAI/pkg/grpc/proto"
|
||||
model "github.com/go-skynet/LocalAI/pkg/model"
|
||||
)
|
||||
|
||||
func ImageGeneration(height, width, mode, step, seed int, positive_prompt, negative_prompt, src, dst string, loader *model.ModelLoader, c config.Config, o *options.Option) (func() error, error) {
|
||||
|
||||
opts := modelOpts(c, o, []model.Option{
|
||||
model.WithBackendString(c.Backend),
|
||||
model.WithAssetDir(o.AssetsDestination),
|
||||
model.WithThreads(uint32(c.Threads)),
|
||||
model.WithContext(o.Context),
|
||||
model.WithModel(c.Model),
|
||||
model.WithLoadGRPCLoadModelOpts(&proto.ModelOptions{
|
||||
CUDA: c.CUDA || c.Diffusers.CUDA,
|
||||
SchedulerType: c.Diffusers.SchedulerType,
|
||||
PipelineType: c.Diffusers.PipelineType,
|
||||
CFGScale: c.Diffusers.CFGScale,
|
||||
LoraAdapter: c.LoraAdapter,
|
||||
LoraScale: c.LoraScale,
|
||||
LoraBase: c.LoraBase,
|
||||
IMG2IMG: c.Diffusers.IMG2IMG,
|
||||
CLIPModel: c.Diffusers.ClipModel,
|
||||
CLIPSubfolder: c.Diffusers.ClipSubFolder,
|
||||
CLIPSkip: int32(c.Diffusers.ClipSkip),
|
||||
ControlNet: c.Diffusers.ControlNet,
|
||||
}),
|
||||
})
|
||||
|
||||
inferenceModel, err := loader.BackendLoader(
|
||||
opts...,
|
||||
)
|
||||
if err != nil {
|
||||
return nil, err
|
||||
}
|
||||
|
||||
fn := func() error {
|
||||
_, err := inferenceModel.GenerateImage(
|
||||
o.Context,
|
||||
&proto.GenerateImageRequest{
|
||||
Height: int32(height),
|
||||
Width: int32(width),
|
||||
Mode: int32(mode),
|
||||
Step: int32(step),
|
||||
Seed: int32(seed),
|
||||
CLIPSkip: int32(c.Diffusers.ClipSkip),
|
||||
PositivePrompt: positive_prompt,
|
||||
NegativePrompt: negative_prompt,
|
||||
Dst: dst,
|
||||
Src: src,
|
||||
EnableParameters: c.Diffusers.EnableParameters,
|
||||
})
|
||||
return err
|
||||
}
|
||||
|
||||
return fn, nil
|
||||
}
|
||||
164
api/backend/llm.go
Normal file
164
api/backend/llm.go
Normal file
@@ -0,0 +1,164 @@
|
||||
package backend
|
||||
|
||||
import (
|
||||
"context"
|
||||
"os"
|
||||
"regexp"
|
||||
"strings"
|
||||
"sync"
|
||||
"unicode/utf8"
|
||||
|
||||
config "github.com/go-skynet/LocalAI/api/config"
|
||||
"github.com/go-skynet/LocalAI/api/options"
|
||||
"github.com/go-skynet/LocalAI/pkg/gallery"
|
||||
"github.com/go-skynet/LocalAI/pkg/grpc"
|
||||
model "github.com/go-skynet/LocalAI/pkg/model"
|
||||
"github.com/go-skynet/LocalAI/pkg/utils"
|
||||
)
|
||||
|
||||
type LLMResponse struct {
|
||||
Response string // should this be []byte?
|
||||
Usage TokenUsage
|
||||
}
|
||||
|
||||
type TokenUsage struct {
|
||||
Prompt int
|
||||
Completion int
|
||||
}
|
||||
|
||||
func ModelInference(ctx context.Context, s string, images []string, loader *model.ModelLoader, c config.Config, o *options.Option, tokenCallback func(string, TokenUsage) bool) (func() (LLMResponse, error), error) {
|
||||
modelFile := c.Model
|
||||
|
||||
grpcOpts := gRPCModelOpts(c)
|
||||
|
||||
var inferenceModel *grpc.Client
|
||||
var err error
|
||||
|
||||
opts := modelOpts(c, o, []model.Option{
|
||||
model.WithLoadGRPCLoadModelOpts(grpcOpts),
|
||||
model.WithThreads(uint32(c.Threads)), // some models uses this to allocate threads during startup
|
||||
model.WithAssetDir(o.AssetsDestination),
|
||||
model.WithModel(modelFile),
|
||||
model.WithContext(o.Context),
|
||||
})
|
||||
|
||||
if c.Backend != "" {
|
||||
opts = append(opts, model.WithBackendString(c.Backend))
|
||||
}
|
||||
|
||||
// Check if the modelFile exists, if it doesn't try to load it from the gallery
|
||||
if o.AutoloadGalleries { // experimental
|
||||
if _, err := os.Stat(modelFile); os.IsNotExist(err) {
|
||||
utils.ResetDownloadTimers()
|
||||
// if we failed to load the model, we try to download it
|
||||
err := gallery.InstallModelFromGalleryByName(o.Galleries, modelFile, loader.ModelPath, gallery.GalleryModel{}, utils.DisplayDownloadFunction)
|
||||
if err != nil {
|
||||
return nil, err
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
if c.Backend == "" {
|
||||
inferenceModel, err = loader.GreedyLoader(opts...)
|
||||
} else {
|
||||
inferenceModel, err = loader.BackendLoader(opts...)
|
||||
}
|
||||
|
||||
if err != nil {
|
||||
return nil, err
|
||||
}
|
||||
|
||||
// in GRPC, the backend is supposed to answer to 1 single token if stream is not supported
|
||||
fn := func() (LLMResponse, error) {
|
||||
opts := gRPCPredictOpts(c, loader.ModelPath)
|
||||
opts.Prompt = s
|
||||
opts.Images = images
|
||||
|
||||
tokenUsage := TokenUsage{}
|
||||
|
||||
// check the per-model feature flag for usage, since tokenCallback may have a cost.
|
||||
// Defaults to off as for now it is still experimental
|
||||
if c.FeatureFlag.Enabled("usage") {
|
||||
userTokenCallback := tokenCallback
|
||||
if userTokenCallback == nil {
|
||||
userTokenCallback = func(token string, usage TokenUsage) bool {
|
||||
return true
|
||||
}
|
||||
}
|
||||
|
||||
promptInfo, pErr := inferenceModel.TokenizeString(ctx, opts)
|
||||
if pErr == nil && promptInfo.Length > 0 {
|
||||
tokenUsage.Prompt = int(promptInfo.Length)
|
||||
}
|
||||
|
||||
tokenCallback = func(token string, usage TokenUsage) bool {
|
||||
tokenUsage.Completion++
|
||||
return userTokenCallback(token, tokenUsage)
|
||||
}
|
||||
}
|
||||
|
||||
if tokenCallback != nil {
|
||||
ss := ""
|
||||
|
||||
var partialRune []byte
|
||||
err := inferenceModel.PredictStream(ctx, opts, func(chars []byte) {
|
||||
partialRune = append(partialRune, chars...)
|
||||
|
||||
for len(partialRune) > 0 {
|
||||
r, size := utf8.DecodeRune(partialRune)
|
||||
if r == utf8.RuneError {
|
||||
// incomplete rune, wait for more bytes
|
||||
break
|
||||
}
|
||||
|
||||
tokenCallback(string(r), tokenUsage)
|
||||
ss += string(r)
|
||||
|
||||
partialRune = partialRune[size:]
|
||||
}
|
||||
})
|
||||
return LLMResponse{
|
||||
Response: ss,
|
||||
Usage: tokenUsage,
|
||||
}, err
|
||||
} else {
|
||||
// TODO: Is the chicken bit the only way to get here? is that acceptable?
|
||||
reply, err := inferenceModel.Predict(ctx, opts)
|
||||
if err != nil {
|
||||
return LLMResponse{}, err
|
||||
}
|
||||
return LLMResponse{
|
||||
Response: string(reply.Message),
|
||||
Usage: tokenUsage,
|
||||
}, err
|
||||
}
|
||||
}
|
||||
|
||||
return fn, nil
|
||||
}
|
||||
|
||||
var cutstrings map[string]*regexp.Regexp = make(map[string]*regexp.Regexp)
|
||||
var mu sync.Mutex = sync.Mutex{}
|
||||
|
||||
func Finetune(config config.Config, input, prediction string) string {
|
||||
if config.Echo {
|
||||
prediction = input + prediction
|
||||
}
|
||||
|
||||
for _, c := range config.Cutstrings {
|
||||
mu.Lock()
|
||||
reg, ok := cutstrings[c]
|
||||
if !ok {
|
||||
cutstrings[c] = regexp.MustCompile(c)
|
||||
reg = cutstrings[c]
|
||||
}
|
||||
mu.Unlock()
|
||||
prediction = reg.ReplaceAllString(prediction, "")
|
||||
}
|
||||
|
||||
for _, c := range config.TrimSpace {
|
||||
prediction = strings.TrimSpace(strings.TrimPrefix(prediction, c))
|
||||
}
|
||||
return prediction
|
||||
|
||||
}
|
||||
127
api/backend/options.go
Normal file
127
api/backend/options.go
Normal file
@@ -0,0 +1,127 @@
|
||||
package backend
|
||||
|
||||
import (
|
||||
"os"
|
||||
"path/filepath"
|
||||
|
||||
pb "github.com/go-skynet/LocalAI/pkg/grpc/proto"
|
||||
model "github.com/go-skynet/LocalAI/pkg/model"
|
||||
|
||||
config "github.com/go-skynet/LocalAI/api/config"
|
||||
"github.com/go-skynet/LocalAI/api/options"
|
||||
)
|
||||
|
||||
func modelOpts(c config.Config, o *options.Option, opts []model.Option) []model.Option {
|
||||
if o.SingleBackend {
|
||||
opts = append(opts, model.WithSingleActiveBackend())
|
||||
}
|
||||
|
||||
if o.ParallelBackendRequests {
|
||||
opts = append(opts, model.EnableParallelRequests)
|
||||
}
|
||||
|
||||
if c.GRPC.Attempts != 0 {
|
||||
opts = append(opts, model.WithGRPCAttempts(c.GRPC.Attempts))
|
||||
}
|
||||
|
||||
if c.GRPC.AttemptsSleepTime != 0 {
|
||||
opts = append(opts, model.WithGRPCAttemptsDelay(c.GRPC.AttemptsSleepTime))
|
||||
}
|
||||
|
||||
for k, v := range o.ExternalGRPCBackends {
|
||||
opts = append(opts, model.WithExternalBackend(k, v))
|
||||
}
|
||||
|
||||
return opts
|
||||
}
|
||||
|
||||
func gRPCModelOpts(c config.Config) *pb.ModelOptions {
|
||||
b := 512
|
||||
if c.Batch != 0 {
|
||||
b = c.Batch
|
||||
}
|
||||
|
||||
return &pb.ModelOptions{
|
||||
ContextSize: int32(c.ContextSize),
|
||||
Seed: int32(c.Seed),
|
||||
NBatch: int32(b),
|
||||
NoMulMatQ: c.NoMulMatQ,
|
||||
CUDA: c.CUDA, // diffusers, transformers
|
||||
DraftModel: c.DraftModel,
|
||||
AudioPath: c.VallE.AudioPath,
|
||||
Quantization: c.Quantization,
|
||||
MMProj: c.MMProj,
|
||||
YarnExtFactor: c.YarnExtFactor,
|
||||
YarnAttnFactor: c.YarnAttnFactor,
|
||||
YarnBetaFast: c.YarnBetaFast,
|
||||
YarnBetaSlow: c.YarnBetaSlow,
|
||||
LoraAdapter: c.LoraAdapter,
|
||||
LoraBase: c.LoraBase,
|
||||
LoraScale: c.LoraScale,
|
||||
NGQA: c.NGQA,
|
||||
RMSNormEps: c.RMSNormEps,
|
||||
F16Memory: c.F16,
|
||||
MLock: c.MMlock,
|
||||
RopeFreqBase: c.RopeFreqBase,
|
||||
RopeFreqScale: c.RopeFreqScale,
|
||||
NUMA: c.NUMA,
|
||||
Embeddings: c.Embeddings,
|
||||
LowVRAM: c.LowVRAM,
|
||||
NGPULayers: int32(c.NGPULayers),
|
||||
MMap: c.MMap,
|
||||
MainGPU: c.MainGPU,
|
||||
Threads: int32(c.Threads),
|
||||
TensorSplit: c.TensorSplit,
|
||||
// AutoGPTQ
|
||||
ModelBaseName: c.AutoGPTQ.ModelBaseName,
|
||||
Device: c.AutoGPTQ.Device,
|
||||
UseTriton: c.AutoGPTQ.Triton,
|
||||
UseFastTokenizer: c.AutoGPTQ.UseFastTokenizer,
|
||||
// RWKV
|
||||
Tokenizer: c.Tokenizer,
|
||||
}
|
||||
}
|
||||
|
||||
func gRPCPredictOpts(c config.Config, modelPath string) *pb.PredictOptions {
|
||||
promptCachePath := ""
|
||||
if c.PromptCachePath != "" {
|
||||
p := filepath.Join(modelPath, c.PromptCachePath)
|
||||
os.MkdirAll(filepath.Dir(p), 0755)
|
||||
promptCachePath = p
|
||||
}
|
||||
return &pb.PredictOptions{
|
||||
Temperature: float32(c.Temperature),
|
||||
TopP: float32(c.TopP),
|
||||
NDraft: c.NDraft,
|
||||
TopK: int32(c.TopK),
|
||||
Tokens: int32(c.Maxtokens),
|
||||
Threads: int32(c.Threads),
|
||||
PromptCacheAll: c.PromptCacheAll,
|
||||
PromptCacheRO: c.PromptCacheRO,
|
||||
PromptCachePath: promptCachePath,
|
||||
F16KV: c.F16,
|
||||
DebugMode: c.Debug,
|
||||
Grammar: c.Grammar,
|
||||
NegativePromptScale: c.NegativePromptScale,
|
||||
RopeFreqBase: c.RopeFreqBase,
|
||||
RopeFreqScale: c.RopeFreqScale,
|
||||
NegativePrompt: c.NegativePrompt,
|
||||
Mirostat: int32(c.LLMConfig.Mirostat),
|
||||
MirostatETA: float32(c.LLMConfig.MirostatETA),
|
||||
MirostatTAU: float32(c.LLMConfig.MirostatTAU),
|
||||
Debug: c.Debug,
|
||||
StopPrompts: c.StopWords,
|
||||
Repeat: int32(c.RepeatPenalty),
|
||||
NKeep: int32(c.Keep),
|
||||
Batch: int32(c.Batch),
|
||||
IgnoreEOS: c.IgnoreEOS,
|
||||
Seed: int32(c.Seed),
|
||||
FrequencyPenalty: float32(c.FrequencyPenalty),
|
||||
MLock: c.MMlock,
|
||||
MMap: c.MMap,
|
||||
MainGPU: c.MainGPU,
|
||||
TensorSplit: c.TensorSplit,
|
||||
TailFreeSamplingZ: float32(c.TFZ),
|
||||
TypicalP: float32(c.TypicalP),
|
||||
}
|
||||
}
|
||||
39
api/backend/transcript.go
Normal file
39
api/backend/transcript.go
Normal file
@@ -0,0 +1,39 @@
|
||||
package backend
|
||||
|
||||
import (
|
||||
"context"
|
||||
"fmt"
|
||||
|
||||
config "github.com/go-skynet/LocalAI/api/config"
|
||||
"github.com/go-skynet/LocalAI/api/schema"
|
||||
|
||||
"github.com/go-skynet/LocalAI/api/options"
|
||||
"github.com/go-skynet/LocalAI/pkg/grpc/proto"
|
||||
model "github.com/go-skynet/LocalAI/pkg/model"
|
||||
)
|
||||
|
||||
func ModelTranscription(audio, language string, loader *model.ModelLoader, c config.Config, o *options.Option) (*schema.Result, error) {
|
||||
|
||||
opts := modelOpts(c, o, []model.Option{
|
||||
model.WithBackendString(model.WhisperBackend),
|
||||
model.WithModel(c.Model),
|
||||
model.WithContext(o.Context),
|
||||
model.WithThreads(uint32(c.Threads)),
|
||||
model.WithAssetDir(o.AssetsDestination),
|
||||
})
|
||||
|
||||
whisperModel, err := o.Loader.BackendLoader(opts...)
|
||||
if err != nil {
|
||||
return nil, err
|
||||
}
|
||||
|
||||
if whisperModel == nil {
|
||||
return nil, fmt.Errorf("could not load whisper model")
|
||||
}
|
||||
|
||||
return whisperModel.AudioTranscription(context.Background(), &proto.TranscriptRequest{
|
||||
Dst: audio,
|
||||
Language: language,
|
||||
Threads: uint32(c.Threads),
|
||||
})
|
||||
}
|
||||
79
api/backend/tts.go
Normal file
79
api/backend/tts.go
Normal file
@@ -0,0 +1,79 @@
|
||||
package backend
|
||||
|
||||
import (
|
||||
"context"
|
||||
"fmt"
|
||||
"os"
|
||||
"path/filepath"
|
||||
|
||||
api_config "github.com/go-skynet/LocalAI/api/config"
|
||||
"github.com/go-skynet/LocalAI/api/options"
|
||||
"github.com/go-skynet/LocalAI/pkg/grpc/proto"
|
||||
model "github.com/go-skynet/LocalAI/pkg/model"
|
||||
"github.com/go-skynet/LocalAI/pkg/utils"
|
||||
)
|
||||
|
||||
func generateUniqueFileName(dir, baseName, ext string) string {
|
||||
counter := 1
|
||||
fileName := baseName + ext
|
||||
|
||||
for {
|
||||
filePath := filepath.Join(dir, fileName)
|
||||
_, err := os.Stat(filePath)
|
||||
if os.IsNotExist(err) {
|
||||
return fileName
|
||||
}
|
||||
|
||||
counter++
|
||||
fileName = fmt.Sprintf("%s_%d%s", baseName, counter, ext)
|
||||
}
|
||||
}
|
||||
|
||||
func ModelTTS(backend, text, modelFile string, loader *model.ModelLoader, o *options.Option) (string, *proto.Result, error) {
|
||||
bb := backend
|
||||
if bb == "" {
|
||||
bb = model.PiperBackend
|
||||
}
|
||||
opts := modelOpts(api_config.Config{}, o, []model.Option{
|
||||
model.WithBackendString(bb),
|
||||
model.WithModel(modelFile),
|
||||
model.WithContext(o.Context),
|
||||
model.WithAssetDir(o.AssetsDestination),
|
||||
})
|
||||
piperModel, err := o.Loader.BackendLoader(opts...)
|
||||
if err != nil {
|
||||
return "", nil, err
|
||||
}
|
||||
|
||||
if piperModel == nil {
|
||||
return "", nil, fmt.Errorf("could not load piper model")
|
||||
}
|
||||
|
||||
if err := os.MkdirAll(o.AudioDir, 0755); err != nil {
|
||||
return "", nil, fmt.Errorf("failed creating audio directory: %s", err)
|
||||
}
|
||||
|
||||
fileName := generateUniqueFileName(o.AudioDir, "piper", ".wav")
|
||||
filePath := filepath.Join(o.AudioDir, fileName)
|
||||
|
||||
// If the model file is not empty, we pass it joined with the model path
|
||||
modelPath := ""
|
||||
if modelFile != "" {
|
||||
if bb != model.TransformersMusicGen {
|
||||
modelPath = filepath.Join(o.Loader.ModelPath, modelFile)
|
||||
if err := utils.VerifyPath(modelPath, o.Loader.ModelPath); err != nil {
|
||||
return "", nil, err
|
||||
}
|
||||
} else {
|
||||
modelPath = modelFile
|
||||
}
|
||||
}
|
||||
|
||||
res, err := piperModel.TTS(context.Background(), &proto.TTSRequest{
|
||||
Text: text,
|
||||
Model: modelPath,
|
||||
Dst: filePath,
|
||||
})
|
||||
|
||||
return filePath, res, err
|
||||
}
|
||||
355
api/config.go
355
api/config.go
@@ -1,355 +0,0 @@
|
||||
package api
|
||||
|
||||
import (
|
||||
"encoding/json"
|
||||
"fmt"
|
||||
"io/fs"
|
||||
"os"
|
||||
"path/filepath"
|
||||
"strings"
|
||||
"sync"
|
||||
|
||||
model "github.com/go-skynet/LocalAI/pkg/model"
|
||||
"github.com/gofiber/fiber/v2"
|
||||
"github.com/rs/zerolog/log"
|
||||
"gopkg.in/yaml.v3"
|
||||
)
|
||||
|
||||
type Config struct {
|
||||
OpenAIRequest `yaml:"parameters"`
|
||||
Name string `yaml:"name"`
|
||||
StopWords []string `yaml:"stopwords"`
|
||||
Cutstrings []string `yaml:"cutstrings"`
|
||||
TrimSpace []string `yaml:"trimspace"`
|
||||
ContextSize int `yaml:"context_size"`
|
||||
F16 bool `yaml:"f16"`
|
||||
Threads int `yaml:"threads"`
|
||||
Debug bool `yaml:"debug"`
|
||||
Roles map[string]string `yaml:"roles"`
|
||||
Embeddings bool `yaml:"embeddings"`
|
||||
Backend string `yaml:"backend"`
|
||||
TemplateConfig TemplateConfig `yaml:"template"`
|
||||
MirostatETA float64 `yaml:"mirostat_eta"`
|
||||
MirostatTAU float64 `yaml:"mirostat_tau"`
|
||||
Mirostat int `yaml:"mirostat"`
|
||||
NGPULayers int `yaml:"gpu_layers"`
|
||||
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"`
|
||||
|
||||
PromptStrings, InputStrings []string
|
||||
InputToken [][]int
|
||||
}
|
||||
|
||||
type TemplateConfig struct {
|
||||
Completion string `yaml:"completion"`
|
||||
Chat string `yaml:"chat"`
|
||||
Edit string `yaml:"edit"`
|
||||
}
|
||||
|
||||
type ConfigMerger struct {
|
||||
configs map[string]Config
|
||||
sync.Mutex
|
||||
}
|
||||
|
||||
func defaultConfig(modelFile string) *Config {
|
||||
return &Config{
|
||||
OpenAIRequest: defaultRequest(modelFile),
|
||||
}
|
||||
}
|
||||
|
||||
func NewConfigMerger() *ConfigMerger {
|
||||
return &ConfigMerger{
|
||||
configs: make(map[string]Config),
|
||||
}
|
||||
}
|
||||
func ReadConfigFile(file string) ([]*Config, error) {
|
||||
c := &[]*Config{}
|
||||
f, err := os.ReadFile(file)
|
||||
if err != nil {
|
||||
return nil, fmt.Errorf("cannot read config file: %w", err)
|
||||
}
|
||||
if err := yaml.Unmarshal(f, c); err != nil {
|
||||
return nil, fmt.Errorf("cannot unmarshal config file: %w", err)
|
||||
}
|
||||
|
||||
return *c, nil
|
||||
}
|
||||
|
||||
func ReadConfig(file string) (*Config, error) {
|
||||
c := &Config{}
|
||||
f, err := os.ReadFile(file)
|
||||
if err != nil {
|
||||
return nil, fmt.Errorf("cannot read config file: %w", err)
|
||||
}
|
||||
if err := yaml.Unmarshal(f, c); err != nil {
|
||||
return nil, fmt.Errorf("cannot unmarshal config file: %w", err)
|
||||
}
|
||||
|
||||
return c, nil
|
||||
}
|
||||
|
||||
func (cm ConfigMerger) LoadConfigFile(file string) error {
|
||||
cm.Lock()
|
||||
defer cm.Unlock()
|
||||
c, err := ReadConfigFile(file)
|
||||
if err != nil {
|
||||
return fmt.Errorf("cannot load config file: %w", err)
|
||||
}
|
||||
|
||||
for _, cc := range c {
|
||||
cm.configs[cc.Name] = *cc
|
||||
}
|
||||
return nil
|
||||
}
|
||||
|
||||
func (cm ConfigMerger) LoadConfig(file string) error {
|
||||
cm.Lock()
|
||||
defer cm.Unlock()
|
||||
c, err := ReadConfig(file)
|
||||
if err != nil {
|
||||
return fmt.Errorf("cannot read config file: %w", err)
|
||||
}
|
||||
|
||||
cm.configs[c.Name] = *c
|
||||
return nil
|
||||
}
|
||||
|
||||
func (cm ConfigMerger) GetConfig(m string) (Config, bool) {
|
||||
cm.Lock()
|
||||
defer cm.Unlock()
|
||||
v, exists := cm.configs[m]
|
||||
return v, exists
|
||||
}
|
||||
|
||||
func (cm ConfigMerger) ListConfigs() []string {
|
||||
cm.Lock()
|
||||
defer cm.Unlock()
|
||||
var res []string
|
||||
for k := range cm.configs {
|
||||
res = append(res, k)
|
||||
}
|
||||
return res
|
||||
}
|
||||
|
||||
func (cm ConfigMerger) LoadConfigs(path string) error {
|
||||
cm.Lock()
|
||||
defer cm.Unlock()
|
||||
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
|
||||
}
|
||||
|
||||
func updateConfig(config *Config, input *OpenAIRequest) {
|
||||
if input.Echo {
|
||||
config.Echo = input.Echo
|
||||
}
|
||||
if input.TopK != 0 {
|
||||
config.TopK = input.TopK
|
||||
}
|
||||
if input.TopP != 0 {
|
||||
config.TopP = input.TopP
|
||||
}
|
||||
|
||||
if input.Temperature != 0 {
|
||||
config.Temperature = input.Temperature
|
||||
}
|
||||
|
||||
if input.Maxtokens != 0 {
|
||||
config.Maxtokens = input.Maxtokens
|
||||
}
|
||||
|
||||
switch stop := input.Stop.(type) {
|
||||
case string:
|
||||
if stop != "" {
|
||||
config.StopWords = append(config.StopWords, stop)
|
||||
}
|
||||
case []interface{}:
|
||||
for _, pp := range stop {
|
||||
if s, ok := pp.(string); ok {
|
||||
config.StopWords = append(config.StopWords, s)
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
if input.RepeatPenalty != 0 {
|
||||
config.RepeatPenalty = input.RepeatPenalty
|
||||
}
|
||||
|
||||
if input.Keep != 0 {
|
||||
config.Keep = input.Keep
|
||||
}
|
||||
|
||||
if input.Batch != 0 {
|
||||
config.Batch = input.Batch
|
||||
}
|
||||
|
||||
if input.F16 {
|
||||
config.F16 = input.F16
|
||||
}
|
||||
|
||||
if input.IgnoreEOS {
|
||||
config.IgnoreEOS = input.IgnoreEOS
|
||||
}
|
||||
|
||||
if input.Seed != 0 {
|
||||
config.Seed = input.Seed
|
||||
}
|
||||
|
||||
if input.Mirostat != 0 {
|
||||
config.Mirostat = input.Mirostat
|
||||
}
|
||||
|
||||
if input.MirostatETA != 0 {
|
||||
config.MirostatETA = input.MirostatETA
|
||||
}
|
||||
|
||||
if input.MirostatTAU != 0 {
|
||||
config.MirostatTAU = input.MirostatTAU
|
||||
}
|
||||
|
||||
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)
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
switch p := input.Prompt.(type) {
|
||||
case string:
|
||||
config.PromptStrings = append(config.PromptStrings, p)
|
||||
case []interface{}:
|
||||
for _, pp := range p {
|
||||
if s, ok := pp.(string); ok {
|
||||
config.PromptStrings = append(config.PromptStrings, s)
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
func readInput(c *fiber.Ctx, loader *model.ModelLoader, randomModel bool) (string, *OpenAIRequest, error) {
|
||||
input := new(OpenAIRequest)
|
||||
// Get input data from the request body
|
||||
if err := c.BodyParser(input); err != nil {
|
||||
return "", nil, err
|
||||
}
|
||||
|
||||
modelFile := input.Model
|
||||
|
||||
if c.Params("model") != "" {
|
||||
modelFile = c.Params("model")
|
||||
}
|
||||
|
||||
received, _ := json.Marshal(input)
|
||||
|
||||
log.Debug().Msgf("Request received: %s", string(received))
|
||||
|
||||
// Set model from bearer token, if available
|
||||
bearer := strings.TrimLeft(c.Get("authorization"), "Bearer ")
|
||||
bearerExists := bearer != "" && loader.ExistsInModelPath(bearer)
|
||||
|
||||
// If no model was specified, take the first available
|
||||
if modelFile == "" && !bearerExists && randomModel {
|
||||
models, _ := loader.ListModels()
|
||||
if len(models) > 0 {
|
||||
modelFile = models[0]
|
||||
log.Debug().Msgf("No model specified, using: %s", modelFile)
|
||||
} else {
|
||||
log.Debug().Msgf("No model specified, returning error")
|
||||
return "", nil, fmt.Errorf("no model specified")
|
||||
}
|
||||
}
|
||||
|
||||
// If a model is found in bearer token takes precedence
|
||||
if bearerExists {
|
||||
log.Debug().Msgf("Using model from bearer token: %s", bearer)
|
||||
modelFile = bearer
|
||||
}
|
||||
return modelFile, input, nil
|
||||
}
|
||||
|
||||
func readConfig(modelFile string, input *OpenAIRequest, cm *ConfigMerger, loader *model.ModelLoader, debug bool, threads, ctx int, f16 bool) (*Config, *OpenAIRequest, error) {
|
||||
// Load a config file if present after the model name
|
||||
modelConfig := filepath.Join(loader.ModelPath, modelFile+".yaml")
|
||||
if _, err := os.Stat(modelConfig); err == nil {
|
||||
if err := cm.LoadConfig(modelConfig); err != nil {
|
||||
return nil, nil, fmt.Errorf("failed loading model config (%s) %s", modelConfig, err.Error())
|
||||
}
|
||||
}
|
||||
|
||||
var config *Config
|
||||
cfg, exists := cm.GetConfig(modelFile)
|
||||
if !exists {
|
||||
config = defaultConfig(modelFile)
|
||||
config.ContextSize = ctx
|
||||
config.Threads = threads
|
||||
config.F16 = f16
|
||||
config.Debug = debug
|
||||
} else {
|
||||
config = &cfg
|
||||
}
|
||||
|
||||
// Set the parameters for the language model prediction
|
||||
updateConfig(config, input)
|
||||
|
||||
// Don't allow 0 as setting
|
||||
if config.Threads == 0 {
|
||||
if threads != 0 {
|
||||
config.Threads = threads
|
||||
} else {
|
||||
config.Threads = 4
|
||||
}
|
||||
}
|
||||
|
||||
// Enforce debug flag if passed from CLI
|
||||
if debug {
|
||||
config.Debug = true
|
||||
}
|
||||
|
||||
return config, input, nil
|
||||
}
|
||||
326
api/config/config.go
Normal file
326
api/config/config.go
Normal file
@@ -0,0 +1,326 @@
|
||||
package api_config
|
||||
|
||||
import (
|
||||
"fmt"
|
||||
"io/fs"
|
||||
"os"
|
||||
"path/filepath"
|
||||
"strings"
|
||||
"sync"
|
||||
|
||||
"github.com/go-skynet/LocalAI/pkg/utils"
|
||||
"github.com/rs/zerolog/log"
|
||||
"gopkg.in/yaml.v3"
|
||||
)
|
||||
|
||||
type Config struct {
|
||||
PredictionOptions `yaml:"parameters"`
|
||||
Name string `yaml:"name"`
|
||||
|
||||
F16 bool `yaml:"f16"`
|
||||
Threads int `yaml:"threads"`
|
||||
Debug bool `yaml:"debug"`
|
||||
Roles map[string]string `yaml:"roles"`
|
||||
Embeddings bool `yaml:"embeddings"`
|
||||
Backend string `yaml:"backend"`
|
||||
TemplateConfig TemplateConfig `yaml:"template"`
|
||||
|
||||
PromptStrings, InputStrings []string `yaml:"-"`
|
||||
InputToken [][]int `yaml:"-"`
|
||||
functionCallString, functionCallNameString string `yaml:"-"`
|
||||
|
||||
FunctionsConfig Functions `yaml:"function"`
|
||||
|
||||
FeatureFlag FeatureFlag `yaml:"feature_flags"` // Feature Flag registry. We move fast, and features may break on a per model/backend basis. Registry for (usually temporary) flags that indicate aborting something early.
|
||||
// LLM configs (GPT4ALL, Llama.cpp, ...)
|
||||
LLMConfig `yaml:",inline"`
|
||||
|
||||
// AutoGPTQ specifics
|
||||
AutoGPTQ AutoGPTQ `yaml:"autogptq"`
|
||||
|
||||
// Diffusers
|
||||
Diffusers Diffusers `yaml:"diffusers"`
|
||||
Step int `yaml:"step"`
|
||||
|
||||
// GRPC Options
|
||||
GRPC GRPC `yaml:"grpc"`
|
||||
|
||||
// Vall-e-x
|
||||
VallE VallE `yaml:"vall-e"`
|
||||
|
||||
// CUDA
|
||||
// Explicitly enable CUDA or not (some backends might need it)
|
||||
CUDA bool `yaml:"cuda"`
|
||||
}
|
||||
|
||||
type VallE struct {
|
||||
AudioPath string `yaml:"audio_path"`
|
||||
}
|
||||
|
||||
type FeatureFlag map[string]*bool
|
||||
|
||||
func (ff FeatureFlag) Enabled(s string) bool {
|
||||
v, exist := ff[s]
|
||||
return exist && v != nil && *v
|
||||
}
|
||||
|
||||
type GRPC struct {
|
||||
Attempts int `yaml:"attempts"`
|
||||
AttemptsSleepTime int `yaml:"attempts_sleep_time"`
|
||||
}
|
||||
|
||||
type Diffusers struct {
|
||||
CUDA bool `yaml:"cuda"`
|
||||
PipelineType string `yaml:"pipeline_type"`
|
||||
SchedulerType string `yaml:"scheduler_type"`
|
||||
EnableParameters string `yaml:"enable_parameters"` // A list of comma separated parameters to specify
|
||||
CFGScale float32 `yaml:"cfg_scale"` // Classifier-Free Guidance Scale
|
||||
IMG2IMG bool `yaml:"img2img"` // Image to Image Diffuser
|
||||
ClipSkip int `yaml:"clip_skip"` // Skip every N frames
|
||||
ClipModel string `yaml:"clip_model"` // Clip model to use
|
||||
ClipSubFolder string `yaml:"clip_subfolder"` // Subfolder to use for clip model
|
||||
ControlNet string `yaml:"control_net"`
|
||||
}
|
||||
|
||||
type LLMConfig struct {
|
||||
SystemPrompt string `yaml:"system_prompt"`
|
||||
TensorSplit string `yaml:"tensor_split"`
|
||||
MainGPU string `yaml:"main_gpu"`
|
||||
RMSNormEps float32 `yaml:"rms_norm_eps"`
|
||||
NGQA int32 `yaml:"ngqa"`
|
||||
PromptCachePath string `yaml:"prompt_cache_path"`
|
||||
PromptCacheAll bool `yaml:"prompt_cache_all"`
|
||||
PromptCacheRO bool `yaml:"prompt_cache_ro"`
|
||||
MirostatETA float64 `yaml:"mirostat_eta"`
|
||||
MirostatTAU float64 `yaml:"mirostat_tau"`
|
||||
Mirostat int `yaml:"mirostat"`
|
||||
NGPULayers int `yaml:"gpu_layers"`
|
||||
MMap bool `yaml:"mmap"`
|
||||
MMlock bool `yaml:"mmlock"`
|
||||
LowVRAM bool `yaml:"low_vram"`
|
||||
Grammar string `yaml:"grammar"`
|
||||
StopWords []string `yaml:"stopwords"`
|
||||
Cutstrings []string `yaml:"cutstrings"`
|
||||
TrimSpace []string `yaml:"trimspace"`
|
||||
ContextSize int `yaml:"context_size"`
|
||||
NUMA bool `yaml:"numa"`
|
||||
LoraAdapter string `yaml:"lora_adapter"`
|
||||
LoraBase string `yaml:"lora_base"`
|
||||
LoraScale float32 `yaml:"lora_scale"`
|
||||
NoMulMatQ bool `yaml:"no_mulmatq"`
|
||||
DraftModel string `yaml:"draft_model"`
|
||||
NDraft int32 `yaml:"n_draft"`
|
||||
Quantization string `yaml:"quantization"`
|
||||
MMProj string `yaml:"mmproj"`
|
||||
|
||||
RopeScaling string `yaml:"rope_scaling"`
|
||||
YarnExtFactor float32 `yaml:"yarn_ext_factor"`
|
||||
YarnAttnFactor float32 `yaml:"yarn_attn_factor"`
|
||||
YarnBetaFast float32 `yaml:"yarn_beta_fast"`
|
||||
YarnBetaSlow float32 `yaml:"yarn_beta_slow"`
|
||||
}
|
||||
|
||||
type AutoGPTQ struct {
|
||||
ModelBaseName string `yaml:"model_base_name"`
|
||||
Device string `yaml:"device"`
|
||||
Triton bool `yaml:"triton"`
|
||||
UseFastTokenizer bool `yaml:"use_fast_tokenizer"`
|
||||
}
|
||||
|
||||
type Functions struct {
|
||||
DisableNoAction bool `yaml:"disable_no_action"`
|
||||
NoActionFunctionName string `yaml:"no_action_function_name"`
|
||||
NoActionDescriptionName string `yaml:"no_action_description_name"`
|
||||
}
|
||||
|
||||
type TemplateConfig struct {
|
||||
Chat string `yaml:"chat"`
|
||||
ChatMessage string `yaml:"chat_message"`
|
||||
Completion string `yaml:"completion"`
|
||||
Edit string `yaml:"edit"`
|
||||
Functions string `yaml:"function"`
|
||||
}
|
||||
|
||||
type ConfigLoader struct {
|
||||
configs map[string]Config
|
||||
sync.Mutex
|
||||
}
|
||||
|
||||
func (c *Config) SetFunctionCallString(s string) {
|
||||
c.functionCallString = s
|
||||
}
|
||||
|
||||
func (c *Config) SetFunctionCallNameString(s string) {
|
||||
c.functionCallNameString = s
|
||||
}
|
||||
|
||||
func (c *Config) ShouldUseFunctions() bool {
|
||||
return ((c.functionCallString != "none" || c.functionCallString == "") || c.ShouldCallSpecificFunction())
|
||||
}
|
||||
|
||||
func (c *Config) ShouldCallSpecificFunction() bool {
|
||||
return len(c.functionCallNameString) > 0
|
||||
}
|
||||
|
||||
func (c *Config) FunctionToCall() string {
|
||||
return c.functionCallNameString
|
||||
}
|
||||
|
||||
func defaultPredictOptions(modelFile string) PredictionOptions {
|
||||
return PredictionOptions{
|
||||
TopP: 0.7,
|
||||
TopK: 80,
|
||||
Maxtokens: 512,
|
||||
Temperature: 0.9,
|
||||
Model: modelFile,
|
||||
}
|
||||
}
|
||||
|
||||
func DefaultConfig(modelFile string) *Config {
|
||||
return &Config{
|
||||
PredictionOptions: defaultPredictOptions(modelFile),
|
||||
}
|
||||
}
|
||||
|
||||
func NewConfigLoader() *ConfigLoader {
|
||||
return &ConfigLoader{
|
||||
configs: make(map[string]Config),
|
||||
}
|
||||
}
|
||||
func ReadConfigFile(file string) ([]*Config, error) {
|
||||
c := &[]*Config{}
|
||||
f, err := os.ReadFile(file)
|
||||
if err != nil {
|
||||
return nil, fmt.Errorf("cannot read config file: %w", err)
|
||||
}
|
||||
if err := yaml.Unmarshal(f, c); err != nil {
|
||||
return nil, fmt.Errorf("cannot unmarshal config file: %w", err)
|
||||
}
|
||||
|
||||
return *c, nil
|
||||
}
|
||||
|
||||
func ReadConfig(file string) (*Config, error) {
|
||||
c := &Config{}
|
||||
f, err := os.ReadFile(file)
|
||||
if err != nil {
|
||||
return nil, fmt.Errorf("cannot read config file: %w", err)
|
||||
}
|
||||
if err := yaml.Unmarshal(f, c); err != nil {
|
||||
return nil, fmt.Errorf("cannot unmarshal config file: %w", err)
|
||||
}
|
||||
|
||||
return c, nil
|
||||
}
|
||||
|
||||
func (cm *ConfigLoader) LoadConfigFile(file string) error {
|
||||
cm.Lock()
|
||||
defer cm.Unlock()
|
||||
c, err := ReadConfigFile(file)
|
||||
if err != nil {
|
||||
return fmt.Errorf("cannot load config file: %w", err)
|
||||
}
|
||||
|
||||
for _, cc := range c {
|
||||
cm.configs[cc.Name] = *cc
|
||||
}
|
||||
return nil
|
||||
}
|
||||
|
||||
func (cm *ConfigLoader) LoadConfig(file string) error {
|
||||
cm.Lock()
|
||||
defer cm.Unlock()
|
||||
c, err := ReadConfig(file)
|
||||
if err != nil {
|
||||
return fmt.Errorf("cannot read config file: %w", err)
|
||||
}
|
||||
|
||||
cm.configs[c.Name] = *c
|
||||
return nil
|
||||
}
|
||||
|
||||
func (cm *ConfigLoader) GetConfig(m string) (Config, bool) {
|
||||
cm.Lock()
|
||||
defer cm.Unlock()
|
||||
v, exists := cm.configs[m]
|
||||
return v, exists
|
||||
}
|
||||
|
||||
func (cm *ConfigLoader) GetAllConfigs() []Config {
|
||||
cm.Lock()
|
||||
defer cm.Unlock()
|
||||
var res []Config
|
||||
for _, v := range cm.configs {
|
||||
res = append(res, v)
|
||||
}
|
||||
return res
|
||||
}
|
||||
|
||||
func (cm *ConfigLoader) ListConfigs() []string {
|
||||
cm.Lock()
|
||||
defer cm.Unlock()
|
||||
var res []string
|
||||
for k := range cm.configs {
|
||||
res = append(res, k)
|
||||
}
|
||||
return res
|
||||
}
|
||||
|
||||
func (cm *ConfigLoader) Preload(modelPath string) error {
|
||||
cm.Lock()
|
||||
defer cm.Unlock()
|
||||
|
||||
for i, config := range cm.configs {
|
||||
modelURL := config.PredictionOptions.Model
|
||||
modelURL = utils.ConvertURL(modelURL)
|
||||
if strings.HasPrefix(modelURL, "http://") || strings.HasPrefix(modelURL, "https://") {
|
||||
// md5 of model name
|
||||
md5Name := utils.MD5(modelURL)
|
||||
|
||||
// check if file exists
|
||||
if _, err := os.Stat(filepath.Join(modelPath, md5Name)); err == os.ErrNotExist {
|
||||
err := utils.DownloadFile(modelURL, filepath.Join(modelPath, md5Name), "", func(fileName, current, total string, percent float64) {
|
||||
log.Info().Msgf("Downloading %s: %s/%s (%.2f%%)", fileName, current, total, percent)
|
||||
})
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
}
|
||||
|
||||
cc := cm.configs[i]
|
||||
c := &cc
|
||||
c.PredictionOptions.Model = md5Name
|
||||
cm.configs[i] = *c
|
||||
}
|
||||
}
|
||||
return nil
|
||||
}
|
||||
|
||||
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") && !strings.Contains(file.Name(), ".yml") {
|
||||
continue
|
||||
}
|
||||
c, err := ReadConfig(filepath.Join(path, file.Name()))
|
||||
if err == nil {
|
||||
cm.configs[c.Name] = *c
|
||||
}
|
||||
}
|
||||
|
||||
return nil
|
||||
}
|
||||
@@ -1,8 +1,10 @@
|
||||
package api
|
||||
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"
|
||||
@@ -26,29 +28,29 @@ var _ = Describe("Test cases for config related functions", func() {
|
||||
})
|
||||
|
||||
It("Test LoadConfigs", func() {
|
||||
cm := NewConfigMerger()
|
||||
options := newOptions()
|
||||
cm := NewConfigLoader()
|
||||
opts := options.NewOptions()
|
||||
modelLoader := model.NewModelLoader(os.Getenv("MODELS_PATH"))
|
||||
WithModelLoader(modelLoader)(options)
|
||||
options.WithModelLoader(modelLoader)(opts)
|
||||
|
||||
err := cm.LoadConfigs(options.loader.ModelPath)
|
||||
err := cm.LoadConfigs(opts.Loader.ModelPath)
|
||||
Expect(err).To(BeNil())
|
||||
Expect(cm.configs).ToNot(BeNil())
|
||||
Expect(cm.ListConfigs()).ToNot(BeNil())
|
||||
|
||||
// config should includes gpt4all models's api.config
|
||||
Expect(cm.configs).To(HaveKey("gpt4all"))
|
||||
Expect(cm.ListConfigs()).To(ContainElements("gpt4all"))
|
||||
|
||||
// config should includes gpt2 models's api.config
|
||||
Expect(cm.configs).To(HaveKey("gpt4all-2"))
|
||||
Expect(cm.ListConfigs()).To(ContainElements("gpt4all-2"))
|
||||
|
||||
// config should includes text-embedding-ada-002 models's api.config
|
||||
Expect(cm.configs).To(HaveKey("text-embedding-ada-002"))
|
||||
Expect(cm.ListConfigs()).To(ContainElements("text-embedding-ada-002"))
|
||||
|
||||
// config should includes rwkv_test models's api.config
|
||||
Expect(cm.configs).To(HaveKey("rwkv_test"))
|
||||
Expect(cm.ListConfigs()).To(ContainElements("rwkv_test"))
|
||||
|
||||
// config should includes whisper-1 models's api.config
|
||||
Expect(cm.configs).To(HaveKey("whisper-1"))
|
||||
Expect(cm.ListConfigs()).To(ContainElements("whisper-1"))
|
||||
})
|
||||
})
|
||||
})
|
||||
50
api/config/prediction.go
Normal file
50
api/config/prediction.go
Normal file
@@ -0,0 +1,50 @@
|
||||
package api_config
|
||||
|
||||
type PredictionOptions struct {
|
||||
|
||||
// Also part of the OpenAI official spec
|
||||
Model string `json:"model" yaml:"model"`
|
||||
|
||||
// Also part of the OpenAI official spec
|
||||
Language string `json:"language"`
|
||||
|
||||
// Also part of the OpenAI official spec. use it for returning multiple results
|
||||
N int `json:"n"`
|
||||
|
||||
// Common options between all the API calls, part of the OpenAI spec
|
||||
TopP float64 `json:"top_p" yaml:"top_p"`
|
||||
TopK int `json:"top_k" yaml:"top_k"`
|
||||
Temperature float64 `json:"temperature" yaml:"temperature"`
|
||||
Maxtokens int `json:"max_tokens" yaml:"max_tokens"`
|
||||
Echo bool `json:"echo"`
|
||||
|
||||
// Custom parameters - not present in the OpenAI API
|
||||
Batch int `json:"batch" yaml:"batch"`
|
||||
F16 bool `json:"f16" yaml:"f16"`
|
||||
IgnoreEOS bool `json:"ignore_eos" yaml:"ignore_eos"`
|
||||
RepeatPenalty float64 `json:"repeat_penalty" yaml:"repeat_penalty"`
|
||||
Keep int `json:"n_keep" yaml:"n_keep"`
|
||||
|
||||
MirostatETA float64 `json:"mirostat_eta" yaml:"mirostat_eta"`
|
||||
MirostatTAU float64 `json:"mirostat_tau" yaml:"mirostat_tau"`
|
||||
Mirostat int `json:"mirostat" yaml:"mirostat"`
|
||||
|
||||
FrequencyPenalty float64 `json:"frequency_penalty" yaml:"frequency_penalty"`
|
||||
TFZ float64 `json:"tfz" yaml:"tfz"`
|
||||
|
||||
TypicalP float64 `json:"typical_p" yaml:"typical_p"`
|
||||
Seed int `json:"seed" yaml:"seed"`
|
||||
|
||||
NegativePrompt string `json:"negative_prompt" yaml:"negative_prompt"`
|
||||
RopeFreqBase float32 `json:"rope_freq_base" yaml:"rope_freq_base"`
|
||||
RopeFreqScale float32 `json:"rope_freq_scale" yaml:"rope_freq_scale"`
|
||||
NegativePromptScale float32 `json:"negative_prompt_scale" yaml:"negative_prompt_scale"`
|
||||
// AutoGPTQ
|
||||
UseFastTokenizer bool `json:"use_fast_tokenizer" yaml:"use_fast_tokenizer"`
|
||||
|
||||
// Diffusers
|
||||
ClipSkip int `json:"clip_skip" yaml:"clip_skip"`
|
||||
|
||||
// RWKV (?)
|
||||
Tokenizer string `json:"tokenizer" yaml:"tokenizer"`
|
||||
}
|
||||
267
api/gallery.go
267
api/gallery.go
@@ -1,267 +0,0 @@
|
||||
package api
|
||||
|
||||
import (
|
||||
"context"
|
||||
"encoding/json"
|
||||
"fmt"
|
||||
"io/ioutil"
|
||||
"net/http"
|
||||
"net/url"
|
||||
"os"
|
||||
"strings"
|
||||
"sync"
|
||||
"time"
|
||||
|
||||
"github.com/go-skynet/LocalAI/pkg/gallery"
|
||||
"github.com/gofiber/fiber/v2"
|
||||
"github.com/google/uuid"
|
||||
"github.com/rs/zerolog/log"
|
||||
"gopkg.in/yaml.v3"
|
||||
)
|
||||
|
||||
type galleryOp struct {
|
||||
req ApplyGalleryModelRequest
|
||||
id string
|
||||
}
|
||||
|
||||
type galleryOpStatus struct {
|
||||
Error error `json:"error"`
|
||||
Processed bool `json:"processed"`
|
||||
Message string `json:"message"`
|
||||
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 newGalleryApplier(modelPath string) *galleryApplier {
|
||||
return &galleryApplier{
|
||||
modelPath: modelPath,
|
||||
C: make(chan galleryOp),
|
||||
statuses: make(map[string]*galleryOpStatus),
|
||||
}
|
||||
}
|
||||
|
||||
func applyGallery(modelPath string, req ApplyGalleryModelRequest, cm *ConfigMerger, downloadStatus func(string, string, string, float64)) error {
|
||||
url, err := req.DecodeURL()
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
|
||||
// Send a GET request to the URL
|
||||
response, err := http.Get(url)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
defer response.Body.Close()
|
||||
|
||||
// Read the response body
|
||||
body, err := ioutil.ReadAll(response.Body)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
|
||||
// Unmarshal YAML data into a Config struct
|
||||
var config gallery.Config
|
||||
err = yaml.Unmarshal(body, &config)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
|
||||
config.Files = append(config.Files, req.AdditionalFiles...)
|
||||
|
||||
if err := gallery.Apply(modelPath, req.Name, &config, req.Overrides, downloadStatus); err != nil {
|
||||
return err
|
||||
}
|
||||
|
||||
// Reload models
|
||||
return cm.LoadConfigs(modelPath)
|
||||
}
|
||||
|
||||
func (g *galleryApplier) updatestatus(s string, op *galleryOpStatus) {
|
||||
g.Lock()
|
||||
defer g.Unlock()
|
||||
g.statuses[s] = op
|
||||
}
|
||||
|
||||
func (g *galleryApplier) getstatus(s string) *galleryOpStatus {
|
||||
g.Lock()
|
||||
defer g.Unlock()
|
||||
|
||||
return g.statuses[s]
|
||||
}
|
||||
|
||||
func (g *galleryApplier) start(c context.Context, cm *ConfigMerger) {
|
||||
go func() {
|
||||
for {
|
||||
select {
|
||||
case <-c.Done():
|
||||
return
|
||||
case op := <-g.C:
|
||||
g.updatestatus(op.id, &galleryOpStatus{Message: "processing", Progress: 0})
|
||||
|
||||
updateError := func(e error) {
|
||||
g.updatestatus(op.id, &galleryOpStatus{Error: e, Processed: true})
|
||||
}
|
||||
|
||||
if err := applyGallery(g.modelPath, op.req, cm, func(fileName string, current string, total string, percentage float64) {
|
||||
g.updatestatus(op.id, &galleryOpStatus{Message: "processing", Progress: percentage, TotalFileSize: total, DownloadedFileSize: current})
|
||||
displayDownload(fileName, current, total, percentage)
|
||||
}); err != nil {
|
||||
updateError(err)
|
||||
continue
|
||||
}
|
||||
|
||||
g.updatestatus(op.id, &galleryOpStatus{Processed: true, Message: "completed", Progress: 100})
|
||||
}
|
||||
}
|
||||
}()
|
||||
}
|
||||
|
||||
var lastProgress time.Time = time.Now()
|
||||
var startTime time.Time = time.Now()
|
||||
|
||||
func displayDownload(fileName string, current string, total string, percentage float64) {
|
||||
currentTime := time.Now()
|
||||
|
||||
if currentTime.Sub(lastProgress) >= 5*time.Second {
|
||||
|
||||
lastProgress = currentTime
|
||||
|
||||
// calculate ETA based on percentage and elapsed time
|
||||
var eta time.Duration
|
||||
if percentage > 0 {
|
||||
elapsed := currentTime.Sub(startTime)
|
||||
eta = time.Duration(float64(elapsed)*(100/percentage) - float64(elapsed))
|
||||
}
|
||||
|
||||
if total != "" {
|
||||
log.Debug().Msgf("Downloading %s: %s/%s (%.2f%%) ETA: %s", fileName, current, total, percentage, eta)
|
||||
} else {
|
||||
log.Debug().Msgf("Downloading: %s", current)
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
func ApplyGalleryFromFile(modelPath, s string, cm *ConfigMerger) error {
|
||||
dat, err := os.ReadFile(s)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
var requests []ApplyGalleryModelRequest
|
||||
err = json.Unmarshal(dat, &requests)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
|
||||
for _, r := range requests {
|
||||
if err := applyGallery(modelPath, r, cm, displayDownload); err != nil {
|
||||
return err
|
||||
}
|
||||
}
|
||||
|
||||
return nil
|
||||
}
|
||||
|
||||
func ApplyGalleryFromString(modelPath, s string, cm *ConfigMerger) error {
|
||||
var requests []ApplyGalleryModelRequest
|
||||
err := json.Unmarshal([]byte(s), &requests)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
|
||||
for _, r := range requests {
|
||||
if err := applyGallery(modelPath, r, cm, displayDownload); err != nil {
|
||||
return err
|
||||
}
|
||||
}
|
||||
|
||||
return nil
|
||||
}
|
||||
|
||||
// endpoints
|
||||
|
||||
type ApplyGalleryModelRequest struct {
|
||||
URL string `json:"url"`
|
||||
Name string `json:"name"`
|
||||
Overrides map[string]interface{} `json:"overrides"`
|
||||
AdditionalFiles []gallery.File `json:"files"`
|
||||
}
|
||||
|
||||
const (
|
||||
githubURI = "github:"
|
||||
)
|
||||
|
||||
func (request ApplyGalleryModelRequest) DecodeURL() (string, error) {
|
||||
input := request.URL
|
||||
var rawURL string
|
||||
|
||||
if strings.HasPrefix(input, githubURI) {
|
||||
parts := strings.Split(input, ":")
|
||||
repoParts := strings.Split(parts[1], "@")
|
||||
branch := "main"
|
||||
|
||||
if len(repoParts) > 1 {
|
||||
branch = repoParts[1]
|
||||
}
|
||||
|
||||
repoPath := strings.Split(repoParts[0], "/")
|
||||
org := repoPath[0]
|
||||
project := repoPath[1]
|
||||
projectPath := strings.Join(repoPath[2:], "/")
|
||||
|
||||
rawURL = fmt.Sprintf("https://raw.githubusercontent.com/%s/%s/%s/%s", org, project, branch, projectPath)
|
||||
} else if strings.HasPrefix(input, "http://") || strings.HasPrefix(input, "https://") {
|
||||
// Handle regular URLs
|
||||
u, err := url.Parse(input)
|
||||
if err != nil {
|
||||
return "", fmt.Errorf("invalid URL: %w", err)
|
||||
}
|
||||
rawURL = u.String()
|
||||
} else {
|
||||
return "", fmt.Errorf("invalid URL format")
|
||||
}
|
||||
|
||||
return rawURL, nil
|
||||
}
|
||||
|
||||
func getOpStatus(g *galleryApplier) func(c *fiber.Ctx) error {
|
||||
return func(c *fiber.Ctx) error {
|
||||
|
||||
status := g.getstatus(c.Params("uuid"))
|
||||
if status == nil {
|
||||
return fmt.Errorf("could not find any status for ID")
|
||||
}
|
||||
|
||||
return c.JSON(status)
|
||||
}
|
||||
}
|
||||
|
||||
func applyModelGallery(modelPath string, cm *ConfigMerger, g chan galleryOp) func(c *fiber.Ctx) error {
|
||||
return func(c *fiber.Ctx) error {
|
||||
input := new(ApplyGalleryModelRequest)
|
||||
// Get input data from the request body
|
||||
if err := c.BodyParser(input); err != nil {
|
||||
return err
|
||||
}
|
||||
|
||||
uuid, err := uuid.NewUUID()
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
g <- galleryOp{
|
||||
req: *input,
|
||||
id: uuid.String(),
|
||||
}
|
||||
return c.JSON(struct {
|
||||
ID string `json:"uuid"`
|
||||
StatusURL string `json:"status"`
|
||||
}{ID: uuid.String(), StatusURL: c.BaseURL() + "/models/jobs/" + uuid.String()})
|
||||
}
|
||||
}
|
||||
@@ -1,30 +0,0 @@
|
||||
package api_test
|
||||
|
||||
import (
|
||||
. "github.com/go-skynet/LocalAI/api"
|
||||
. "github.com/onsi/ginkgo/v2"
|
||||
. "github.com/onsi/gomega"
|
||||
)
|
||||
|
||||
var _ = Describe("Gallery API tests", func() {
|
||||
Context("requests", func() {
|
||||
It("parses github with a branch", func() {
|
||||
req := ApplyGalleryModelRequest{URL: "github:go-skynet/model-gallery/gpt4all-j.yaml@main"}
|
||||
str, err := req.DecodeURL()
|
||||
Expect(err).ToNot(HaveOccurred())
|
||||
Expect(str).To(Equal("https://raw.githubusercontent.com/go-skynet/model-gallery/main/gpt4all-j.yaml"))
|
||||
})
|
||||
It("parses github without a branch", func() {
|
||||
req := ApplyGalleryModelRequest{URL: "github:go-skynet/model-gallery/gpt4all-j.yaml"}
|
||||
str, err := req.DecodeURL()
|
||||
Expect(err).ToNot(HaveOccurred())
|
||||
Expect(str).To(Equal("https://raw.githubusercontent.com/go-skynet/model-gallery/main/gpt4all-j.yaml"))
|
||||
})
|
||||
It("parses URLS", func() {
|
||||
req := ApplyGalleryModelRequest{URL: "https://raw.githubusercontent.com/go-skynet/model-gallery/main/gpt4all-j.yaml"}
|
||||
str, err := req.DecodeURL()
|
||||
Expect(err).ToNot(HaveOccurred())
|
||||
Expect(str).To(Equal("https://raw.githubusercontent.com/go-skynet/model-gallery/main/gpt4all-j.yaml"))
|
||||
})
|
||||
})
|
||||
})
|
||||
162
api/localai/backend_monitor.go
Normal file
162
api/localai/backend_monitor.go
Normal file
@@ -0,0 +1,162 @@
|
||||
package localai
|
||||
|
||||
import (
|
||||
"context"
|
||||
"fmt"
|
||||
"strings"
|
||||
|
||||
config "github.com/go-skynet/LocalAI/api/config"
|
||||
"github.com/go-skynet/LocalAI/pkg/grpc/proto"
|
||||
|
||||
"github.com/go-skynet/LocalAI/api/options"
|
||||
"github.com/gofiber/fiber/v2"
|
||||
"github.com/rs/zerolog/log"
|
||||
|
||||
gopsutil "github.com/shirou/gopsutil/v3/process"
|
||||
)
|
||||
|
||||
type BackendMonitorRequest struct {
|
||||
Model string `json:"model" yaml:"model"`
|
||||
}
|
||||
|
||||
type BackendMonitorResponse struct {
|
||||
MemoryInfo *gopsutil.MemoryInfoStat
|
||||
MemoryPercent float32
|
||||
CPUPercent float64
|
||||
}
|
||||
|
||||
type BackendMonitor struct {
|
||||
configLoader *config.ConfigLoader
|
||||
options *options.Option // Taking options in case we need to inspect ExternalGRPCBackends, though that's out of scope for now, hence the name.
|
||||
}
|
||||
|
||||
func NewBackendMonitor(configLoader *config.ConfigLoader, options *options.Option) BackendMonitor {
|
||||
return BackendMonitor{
|
||||
configLoader: configLoader,
|
||||
options: options,
|
||||
}
|
||||
}
|
||||
|
||||
func (bm *BackendMonitor) SampleLocalBackendProcess(model string) (*BackendMonitorResponse, error) {
|
||||
config, exists := bm.configLoader.GetConfig(model)
|
||||
var backend string
|
||||
if exists {
|
||||
backend = config.Model
|
||||
} else {
|
||||
// Last ditch effort: use it raw, see if a backend happens to match.
|
||||
backend = model
|
||||
}
|
||||
|
||||
if !strings.HasSuffix(backend, ".bin") {
|
||||
backend = fmt.Sprintf("%s.bin", backend)
|
||||
}
|
||||
|
||||
pid, err := bm.options.Loader.GetGRPCPID(backend)
|
||||
|
||||
if err != nil {
|
||||
log.Error().Msgf("model %s : failed to find pid %+v", model, err)
|
||||
return nil, err
|
||||
}
|
||||
|
||||
// Name is slightly frightening but this does _not_ create a new process, rather it looks up an existing process by PID.
|
||||
backendProcess, err := gopsutil.NewProcess(int32(pid))
|
||||
|
||||
if err != nil {
|
||||
log.Error().Msgf("model %s [PID %d] : error getting process info %+v", model, pid, err)
|
||||
return nil, err
|
||||
}
|
||||
|
||||
memInfo, err := backendProcess.MemoryInfo()
|
||||
|
||||
if err != nil {
|
||||
log.Error().Msgf("model %s [PID %d] : error getting memory info %+v", model, pid, err)
|
||||
return nil, err
|
||||
}
|
||||
|
||||
memPercent, err := backendProcess.MemoryPercent()
|
||||
if err != nil {
|
||||
log.Error().Msgf("model %s [PID %d] : error getting memory percent %+v", model, pid, err)
|
||||
return nil, err
|
||||
}
|
||||
|
||||
cpuPercent, err := backendProcess.CPUPercent()
|
||||
if err != nil {
|
||||
log.Error().Msgf("model %s [PID %d] : error getting cpu percent %+v", model, pid, err)
|
||||
return nil, err
|
||||
}
|
||||
|
||||
return &BackendMonitorResponse{
|
||||
MemoryInfo: memInfo,
|
||||
MemoryPercent: memPercent,
|
||||
CPUPercent: cpuPercent,
|
||||
}, nil
|
||||
}
|
||||
|
||||
func (bm BackendMonitor) getModelLoaderIDFromCtx(c *fiber.Ctx) (string, error) {
|
||||
input := new(BackendMonitorRequest)
|
||||
// Get input data from the request body
|
||||
if err := c.BodyParser(input); err != nil {
|
||||
return "", err
|
||||
}
|
||||
|
||||
config, exists := bm.configLoader.GetConfig(input.Model)
|
||||
var backendId string
|
||||
if exists {
|
||||
backendId = config.Model
|
||||
} else {
|
||||
// Last ditch effort: use it raw, see if a backend happens to match.
|
||||
backendId = input.Model
|
||||
}
|
||||
|
||||
if !strings.HasSuffix(backendId, ".bin") {
|
||||
backendId = fmt.Sprintf("%s.bin", backendId)
|
||||
}
|
||||
|
||||
return backendId, nil
|
||||
}
|
||||
|
||||
func BackendMonitorEndpoint(bm BackendMonitor) func(c *fiber.Ctx) error {
|
||||
return func(c *fiber.Ctx) error {
|
||||
|
||||
backendId, err := bm.getModelLoaderIDFromCtx(c)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
|
||||
model := bm.options.Loader.CheckIsLoaded(backendId)
|
||||
if model == "" {
|
||||
return fmt.Errorf("backend %s is not currently loaded", backendId)
|
||||
}
|
||||
|
||||
status, rpcErr := model.GRPC(false, nil).Status(context.TODO())
|
||||
if rpcErr != nil {
|
||||
log.Warn().Msgf("backend %s experienced an error retrieving status info: %s", backendId, rpcErr.Error())
|
||||
val, slbErr := bm.SampleLocalBackendProcess(backendId)
|
||||
if slbErr != nil {
|
||||
return fmt.Errorf("backend %s experienced an error retrieving status info via rpc: %s, then failed local node process sample: %s", backendId, rpcErr.Error(), slbErr.Error())
|
||||
}
|
||||
return c.JSON(proto.StatusResponse{
|
||||
State: proto.StatusResponse_ERROR,
|
||||
Memory: &proto.MemoryUsageData{
|
||||
Total: val.MemoryInfo.VMS,
|
||||
Breakdown: map[string]uint64{
|
||||
"gopsutil-RSS": val.MemoryInfo.RSS,
|
||||
},
|
||||
},
|
||||
})
|
||||
}
|
||||
|
||||
return c.JSON(status)
|
||||
}
|
||||
}
|
||||
|
||||
func BackendShutdownEndpoint(bm BackendMonitor) func(c *fiber.Ctx) error {
|
||||
return func(c *fiber.Ctx) error {
|
||||
backendId, err := bm.getModelLoaderIDFromCtx(c)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
|
||||
return bm.options.Loader.ShutdownModel(backendId)
|
||||
}
|
||||
}
|
||||
320
api/localai/gallery.go
Normal file
320
api/localai/gallery.go
Normal file
@@ -0,0 +1,320 @@
|
||||
package localai
|
||||
|
||||
import (
|
||||
"context"
|
||||
"fmt"
|
||||
"os"
|
||||
"slices"
|
||||
"strings"
|
||||
"sync"
|
||||
|
||||
json "github.com/json-iterator/go"
|
||||
"gopkg.in/yaml.v3"
|
||||
|
||||
config "github.com/go-skynet/LocalAI/api/config"
|
||||
"github.com/go-skynet/LocalAI/pkg/gallery"
|
||||
"github.com/go-skynet/LocalAI/pkg/utils"
|
||||
|
||||
"github.com/gofiber/fiber/v2"
|
||||
"github.com/google/uuid"
|
||||
"github.com/rs/zerolog/log"
|
||||
)
|
||||
|
||||
type galleryOp struct {
|
||||
req gallery.GalleryModel
|
||||
id string
|
||||
galleries []gallery.Gallery
|
||||
galleryName string
|
||||
}
|
||||
|
||||
type galleryOpStatus struct {
|
||||
FileName string `json:"file_name"`
|
||||
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),
|
||||
}
|
||||
}
|
||||
|
||||
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) getAllStatus() map[string]*galleryOpStatus {
|
||||
g.Lock()
|
||||
defer g.Unlock()
|
||||
|
||||
return g.statuses
|
||||
}
|
||||
|
||||
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", FileName: fileName, Progress: percentage, TotalFileSize: total, DownloadedFileSize: current})
|
||||
utils.DisplayDownloadFunction(fileName, current, total, percentage)
|
||||
}
|
||||
|
||||
var err error
|
||||
// if the request contains a gallery name, we apply the gallery from the gallery list
|
||||
if op.galleryName != "" {
|
||||
if strings.Contains(op.galleryName, "@") {
|
||||
err = gallery.InstallModelFromGallery(op.galleries, op.galleryName, g.modelPath, op.req, progressCallback)
|
||||
} else {
|
||||
err = gallery.InstallModelFromGalleryByName(op.galleries, op.galleryName, g.modelPath, op.req, progressCallback)
|
||||
}
|
||||
} else {
|
||||
err = prepareModel(g.modelPath, op.req, cm, progressCallback)
|
||||
}
|
||||
|
||||
if err != nil {
|
||||
updateError(err)
|
||||
continue
|
||||
}
|
||||
|
||||
// Reload models
|
||||
err = cm.LoadConfigs(g.modelPath)
|
||||
if err != nil {
|
||||
updateError(err)
|
||||
continue
|
||||
}
|
||||
|
||||
g.updateStatus(op.id, &galleryOpStatus{Processed: true, Message: "completed", Progress: 100})
|
||||
}
|
||||
}
|
||||
}()
|
||||
}
|
||||
|
||||
type galleryModel struct {
|
||||
gallery.GalleryModel `yaml:",inline"` // https://github.com/go-yaml/yaml/issues/63
|
||||
ID string `json:"id"`
|
||||
}
|
||||
|
||||
func processRequests(modelPath, s string, cm *config.ConfigLoader, galleries []gallery.Gallery, requests []galleryModel) error {
|
||||
var err error
|
||||
for _, r := range requests {
|
||||
utils.ResetDownloadTimers()
|
||||
if r.ID == "" {
|
||||
err = prepareModel(modelPath, r.GalleryModel, cm, utils.DisplayDownloadFunction)
|
||||
} else {
|
||||
if strings.Contains(r.ID, "@") {
|
||||
err = gallery.InstallModelFromGallery(
|
||||
galleries, r.ID, modelPath, r.GalleryModel, utils.DisplayDownloadFunction)
|
||||
} else {
|
||||
err = gallery.InstallModelFromGalleryByName(
|
||||
galleries, r.ID, modelPath, r.GalleryModel, utils.DisplayDownloadFunction)
|
||||
}
|
||||
}
|
||||
}
|
||||
return err
|
||||
}
|
||||
|
||||
func ApplyGalleryFromFile(modelPath, s string, cm *config.ConfigLoader, galleries []gallery.Gallery) error {
|
||||
dat, err := os.ReadFile(s)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
var requests []galleryModel
|
||||
|
||||
if err := yaml.Unmarshal(dat, &requests); err != nil {
|
||||
return err
|
||||
}
|
||||
|
||||
return processRequests(modelPath, s, cm, galleries, requests)
|
||||
}
|
||||
|
||||
func ApplyGalleryFromString(modelPath, s string, cm *config.ConfigLoader, galleries []gallery.Gallery) error {
|
||||
var requests []galleryModel
|
||||
err := json.Unmarshal([]byte(s), &requests)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
|
||||
return processRequests(modelPath, s, cm, galleries, requests)
|
||||
}
|
||||
|
||||
/// Endpoint Service
|
||||
|
||||
type ModelGalleryService struct {
|
||||
galleries []gallery.Gallery
|
||||
modelPath string
|
||||
galleryApplier *galleryApplier
|
||||
}
|
||||
|
||||
type GalleryModel struct {
|
||||
ID string `json:"id"`
|
||||
gallery.GalleryModel
|
||||
}
|
||||
|
||||
func CreateModelGalleryService(galleries []gallery.Gallery, modelPath string, galleryApplier *galleryApplier) ModelGalleryService {
|
||||
return ModelGalleryService{
|
||||
galleries: galleries,
|
||||
modelPath: modelPath,
|
||||
galleryApplier: galleryApplier,
|
||||
}
|
||||
}
|
||||
|
||||
func (mgs *ModelGalleryService) GetOpStatusEndpoint() func(c *fiber.Ctx) error {
|
||||
return func(c *fiber.Ctx) error {
|
||||
status := mgs.galleryApplier.getStatus(c.Params("uuid"))
|
||||
if status == nil {
|
||||
return fmt.Errorf("could not find any status for ID")
|
||||
}
|
||||
return c.JSON(status)
|
||||
}
|
||||
}
|
||||
|
||||
func (mgs *ModelGalleryService) GetAllStatusEndpoint() func(c *fiber.Ctx) error {
|
||||
return func(c *fiber.Ctx) error {
|
||||
return c.JSON(mgs.galleryApplier.getAllStatus())
|
||||
}
|
||||
}
|
||||
|
||||
func (mgs *ModelGalleryService) ApplyModelGalleryEndpoint() 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
|
||||
}
|
||||
mgs.galleryApplier.C <- galleryOp{
|
||||
req: input.GalleryModel,
|
||||
id: uuid.String(),
|
||||
galleryName: input.ID,
|
||||
galleries: mgs.galleries,
|
||||
}
|
||||
return c.JSON(struct {
|
||||
ID string `json:"uuid"`
|
||||
StatusURL string `json:"status"`
|
||||
}{ID: uuid.String(), StatusURL: c.BaseURL() + "/models/jobs/" + uuid.String()})
|
||||
}
|
||||
}
|
||||
|
||||
func (mgs *ModelGalleryService) ListModelFromGalleryEndpoint() func(c *fiber.Ctx) error {
|
||||
return func(c *fiber.Ctx) error {
|
||||
log.Debug().Msgf("Listing models from galleries: %+v", mgs.galleries)
|
||||
|
||||
models, err := gallery.AvailableGalleryModels(mgs.galleries, mgs.modelPath)
|
||||
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)
|
||||
}
|
||||
}
|
||||
|
||||
// NOTE: This is different (and much simpler!) than above! This JUST lists the model galleries that have been loaded, not their contents!
|
||||
func (mgs *ModelGalleryService) ListModelGalleriesEndpoint() func(c *fiber.Ctx) error {
|
||||
return func(c *fiber.Ctx) error {
|
||||
log.Debug().Msgf("Listing model galleries %+v", mgs.galleries)
|
||||
dat, err := json.Marshal(mgs.galleries)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
return c.Send(dat)
|
||||
}
|
||||
}
|
||||
|
||||
func (mgs *ModelGalleryService) AddModelGalleryEndpoint() func(c *fiber.Ctx) error {
|
||||
return func(c *fiber.Ctx) error {
|
||||
input := new(gallery.Gallery)
|
||||
// Get input data from the request body
|
||||
if err := c.BodyParser(input); err != nil {
|
||||
return err
|
||||
}
|
||||
if slices.ContainsFunc(mgs.galleries, func(gallery gallery.Gallery) bool {
|
||||
return gallery.Name == input.Name
|
||||
}) {
|
||||
return fmt.Errorf("%s already exists", input.Name)
|
||||
}
|
||||
dat, err := json.Marshal(mgs.galleries)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
log.Debug().Msgf("Adding %+v to gallery list", *input)
|
||||
mgs.galleries = append(mgs.galleries, *input)
|
||||
return c.Send(dat)
|
||||
}
|
||||
}
|
||||
|
||||
func (mgs *ModelGalleryService) RemoveModelGalleryEndpoint() func(c *fiber.Ctx) error {
|
||||
return func(c *fiber.Ctx) error {
|
||||
input := new(gallery.Gallery)
|
||||
// Get input data from the request body
|
||||
if err := c.BodyParser(input); err != nil {
|
||||
return err
|
||||
}
|
||||
if !slices.ContainsFunc(mgs.galleries, func(gallery gallery.Gallery) bool {
|
||||
return gallery.Name == input.Name
|
||||
}) {
|
||||
return fmt.Errorf("%s is not currently registered", input.Name)
|
||||
}
|
||||
mgs.galleries = slices.DeleteFunc(mgs.galleries, func(gallery gallery.Gallery) bool {
|
||||
return gallery.Name == input.Name
|
||||
})
|
||||
return c.Send(nil)
|
||||
}
|
||||
}
|
||||
32
api/localai/localai.go
Normal file
32
api/localai/localai.go
Normal file
@@ -0,0 +1,32 @@
|
||||
package localai
|
||||
|
||||
import (
|
||||
"github.com/go-skynet/LocalAI/api/backend"
|
||||
config "github.com/go-skynet/LocalAI/api/config"
|
||||
|
||||
"github.com/go-skynet/LocalAI/api/options"
|
||||
"github.com/gofiber/fiber/v2"
|
||||
)
|
||||
|
||||
type TTSRequest struct {
|
||||
Model string `json:"model" yaml:"model"`
|
||||
Input string `json:"input" yaml:"input"`
|
||||
Backend string `json:"backend" yaml:"backend"`
|
||||
}
|
||||
|
||||
func TTSEndpoint(cm *config.ConfigLoader, o *options.Option) func(c *fiber.Ctx) error {
|
||||
return func(c *fiber.Ctx) error {
|
||||
|
||||
input := new(TTSRequest)
|
||||
// Get input data from the request body
|
||||
if err := c.BodyParser(input); err != nil {
|
||||
return err
|
||||
}
|
||||
|
||||
filePath, _, err := backend.ModelTTS(input.Backend, input.Input, input.Model, o.Loader, o)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
return c.Download(filePath)
|
||||
}
|
||||
}
|
||||
755
api/openai.go
755
api/openai.go
@@ -1,755 +0,0 @@
|
||||
package api
|
||||
|
||||
import (
|
||||
"bufio"
|
||||
"bytes"
|
||||
"encoding/base64"
|
||||
"encoding/json"
|
||||
"errors"
|
||||
"fmt"
|
||||
"io"
|
||||
"io/ioutil"
|
||||
"net/http"
|
||||
"os"
|
||||
"path"
|
||||
"path/filepath"
|
||||
"strconv"
|
||||
"strings"
|
||||
|
||||
"github.com/ggerganov/whisper.cpp/bindings/go/pkg/whisper"
|
||||
model "github.com/go-skynet/LocalAI/pkg/model"
|
||||
whisperutil "github.com/go-skynet/LocalAI/pkg/whisper"
|
||||
llama "github.com/go-skynet/go-llama.cpp"
|
||||
"github.com/gofiber/fiber/v2"
|
||||
"github.com/rs/zerolog/log"
|
||||
"github.com/valyala/fasthttp"
|
||||
)
|
||||
|
||||
// APIError provides error information returned by the OpenAI API.
|
||||
type APIError struct {
|
||||
Code any `json:"code,omitempty"`
|
||||
Message string `json:"message"`
|
||||
Param *string `json:"param,omitempty"`
|
||||
Type string `json:"type"`
|
||||
}
|
||||
|
||||
type ErrorResponse struct {
|
||||
Error *APIError `json:"error,omitempty"`
|
||||
}
|
||||
|
||||
type OpenAIUsage struct {
|
||||
PromptTokens int `json:"prompt_tokens"`
|
||||
CompletionTokens int `json:"completion_tokens"`
|
||||
TotalTokens int `json:"total_tokens"`
|
||||
}
|
||||
|
||||
type Item struct {
|
||||
Embedding []float32 `json:"embedding"`
|
||||
Index int `json:"index"`
|
||||
Object string `json:"object,omitempty"`
|
||||
|
||||
// Images
|
||||
URL string `json:"url,omitempty"`
|
||||
B64JSON string `json:"b64_json,omitempty"`
|
||||
}
|
||||
|
||||
type OpenAIResponse struct {
|
||||
Created int `json:"created,omitempty"`
|
||||
Object string `json:"object,omitempty"`
|
||||
ID string `json:"id,omitempty"`
|
||||
Model string `json:"model,omitempty"`
|
||||
Choices []Choice `json:"choices,omitempty"`
|
||||
Data []Item `json:"data,omitempty"`
|
||||
|
||||
Usage OpenAIUsage `json:"usage"`
|
||||
}
|
||||
|
||||
type Choice struct {
|
||||
Index int `json:"index,omitempty"`
|
||||
FinishReason string `json:"finish_reason,omitempty"`
|
||||
Message *Message `json:"message,omitempty"`
|
||||
Delta *Message `json:"delta,omitempty"`
|
||||
Text string `json:"text,omitempty"`
|
||||
}
|
||||
|
||||
type Message struct {
|
||||
Role string `json:"role,omitempty" yaml:"role"`
|
||||
Content string `json:"content,omitempty" yaml:"content"`
|
||||
}
|
||||
|
||||
type OpenAIModel struct {
|
||||
ID string `json:"id"`
|
||||
Object string `json:"object"`
|
||||
}
|
||||
|
||||
type OpenAIRequest struct {
|
||||
Model string `json:"model" yaml:"model"`
|
||||
|
||||
// whisper
|
||||
File string `json:"file" validate:"required"`
|
||||
Language string `json:"language"`
|
||||
//whisper/image
|
||||
ResponseFormat string `json:"response_format"`
|
||||
// image
|
||||
Size string `json:"size"`
|
||||
// Prompt is read only by completion/image API calls
|
||||
Prompt interface{} `json:"prompt" yaml:"prompt"`
|
||||
|
||||
// Edit endpoint
|
||||
Instruction string `json:"instruction" yaml:"instruction"`
|
||||
Input interface{} `json:"input" yaml:"input"`
|
||||
|
||||
Stop interface{} `json:"stop" yaml:"stop"`
|
||||
|
||||
// Messages is read only by chat/completion API calls
|
||||
Messages []Message `json:"messages" yaml:"messages"`
|
||||
|
||||
Stream bool `json:"stream"`
|
||||
Echo bool `json:"echo"`
|
||||
// Common options between all the API calls
|
||||
TopP float64 `json:"top_p" yaml:"top_p"`
|
||||
TopK int `json:"top_k" yaml:"top_k"`
|
||||
Temperature float64 `json:"temperature" yaml:"temperature"`
|
||||
Maxtokens int `json:"max_tokens" yaml:"max_tokens"`
|
||||
|
||||
N int `json:"n"`
|
||||
|
||||
// Custom parameters - not present in the OpenAI API
|
||||
Batch int `json:"batch" yaml:"batch"`
|
||||
F16 bool `json:"f16" yaml:"f16"`
|
||||
IgnoreEOS bool `json:"ignore_eos" yaml:"ignore_eos"`
|
||||
RepeatPenalty float64 `json:"repeat_penalty" yaml:"repeat_penalty"`
|
||||
Keep int `json:"n_keep" yaml:"n_keep"`
|
||||
|
||||
MirostatETA float64 `json:"mirostat_eta" yaml:"mirostat_eta"`
|
||||
MirostatTAU float64 `json:"mirostat_tau" yaml:"mirostat_tau"`
|
||||
Mirostat int `json:"mirostat" yaml:"mirostat"`
|
||||
|
||||
FrequencyPenalty float64 `json:"frequency_penalty" yaml:"frequency_penalty"`
|
||||
TFZ float64 `json:"tfz" yaml:"tfz"`
|
||||
|
||||
Seed int `json:"seed" yaml:"seed"`
|
||||
|
||||
// Image (not supported by OpenAI)
|
||||
Mode int `json:"mode"`
|
||||
Step int `json:"step"`
|
||||
|
||||
TypicalP float64 `json:"typical_p" yaml:"typical_p"`
|
||||
}
|
||||
|
||||
func defaultRequest(modelFile string) OpenAIRequest {
|
||||
return OpenAIRequest{
|
||||
TopP: 0.7,
|
||||
TopK: 80,
|
||||
Maxtokens: 512,
|
||||
Temperature: 0.9,
|
||||
Model: modelFile,
|
||||
}
|
||||
}
|
||||
|
||||
// https://platform.openai.com/docs/api-reference/completions
|
||||
func completionEndpoint(cm *ConfigMerger, o *Option) func(c *fiber.Ctx) error {
|
||||
process := func(s string, req *OpenAIRequest, config *Config, loader *model.ModelLoader, responses chan OpenAIResponse) {
|
||||
ComputeChoices(s, req, 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{{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.ctxSize, 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 `Stream`ing")
|
||||
}
|
||||
|
||||
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{{FinishReason: "stop"}},
|
||||
}
|
||||
respData, _ := json.Marshal(resp)
|
||||
|
||||
w.WriteString(fmt.Sprintf("data: %s\n\n", respData))
|
||||
w.WriteString("data: [DONE]\n\n")
|
||||
w.Flush()
|
||||
}))
|
||||
return nil
|
||||
}
|
||||
|
||||
var result []Choice
|
||||
for _, i := range config.PromptStrings {
|
||||
// A model can have a "file.bin.tmpl" file associated with a prompt template prefix
|
||||
templatedInput, err := o.loader.TemplatePrefix(templateFile, struct {
|
||||
Input string
|
||||
}{Input: i})
|
||||
if err == nil {
|
||||
i = templatedInput
|
||||
log.Debug().Msgf("Template found, input modified to: %s", i)
|
||||
}
|
||||
|
||||
r, err := ComputeChoices(i, input, config, o, o.loader, func(s string, c *[]Choice) {
|
||||
*c = append(*c, Choice{Text: s})
|
||||
}, nil)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
|
||||
result = append(result, r...)
|
||||
}
|
||||
|
||||
resp := &OpenAIResponse{
|
||||
Model: input.Model, // we have to return what the user sent here, due to OpenAI spec.
|
||||
Choices: result,
|
||||
Object: "text_completion",
|
||||
}
|
||||
|
||||
jsonResult, _ := json.Marshal(resp)
|
||||
log.Debug().Msgf("Response: %s", jsonResult)
|
||||
|
||||
// Return the prediction in the response body
|
||||
return c.JSON(resp)
|
||||
}
|
||||
}
|
||||
|
||||
// https://platform.openai.com/docs/api-reference/embeddings
|
||||
func embeddingsEndpoint(cm *ConfigMerger, o *Option) func(c *fiber.Ctx) error {
|
||||
return func(c *fiber.Ctx) error {
|
||||
model, input, err := readInput(c, o.loader, true)
|
||||
if err != nil {
|
||||
return fmt.Errorf("failed reading parameters from request:%w", err)
|
||||
}
|
||||
|
||||
config, input, err := readConfig(model, input, cm, o.loader, o.debug, o.threads, o.ctxSize, o.f16)
|
||||
if err != nil {
|
||||
return fmt.Errorf("failed reading parameters from request:%w", err)
|
||||
}
|
||||
|
||||
log.Debug().Msgf("Parameter Config: %+v", config)
|
||||
items := []Item{}
|
||||
|
||||
for i, s := range config.InputToken {
|
||||
// get the model function to call for the result
|
||||
embedFn, err := ModelEmbedding("", s, o.loader, *config, 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 := 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)
|
||||
}
|
||||
}
|
||||
|
||||
func chatEndpoint(cm *ConfigMerger, o *Option) func(c *fiber.Ctx) error {
|
||||
|
||||
process := func(s string, req *OpenAIRequest, config *Config, loader *model.ModelLoader, responses chan OpenAIResponse) {
|
||||
initialMessage := OpenAIResponse{
|
||||
Model: req.Model, // we have to return what the user sent here, due to OpenAI spec.
|
||||
Choices: []Choice{{Delta: &Message{Role: "assistant"}}},
|
||||
Object: "chat.completion.chunk",
|
||||
}
|
||||
responses <- initialMessage
|
||||
|
||||
ComputeChoices(s, req, config, 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}}},
|
||||
Object: "chat.completion.chunk",
|
||||
}
|
||||
log.Debug().Msgf("Sending goroutine: %s", s)
|
||||
|
||||
responses <- resp
|
||||
return true
|
||||
})
|
||||
close(responses)
|
||||
}
|
||||
return func(c *fiber.Ctx) error {
|
||||
model, input, err := readInput(c, o.loader, true)
|
||||
if err != nil {
|
||||
return fmt.Errorf("failed reading parameters from request:%w", err)
|
||||
}
|
||||
|
||||
config, input, err := readConfig(model, input, cm, o.loader, o.debug, o.threads, o.ctxSize, o.f16)
|
||||
if err != nil {
|
||||
return fmt.Errorf("failed reading parameters from request:%w", err)
|
||||
}
|
||||
|
||||
log.Debug().Msgf("Parameter Config: %+v", config)
|
||||
|
||||
var predInput string
|
||||
|
||||
mess := []string{}
|
||||
for _, i := range input.Messages {
|
||||
var content string
|
||||
r := config.Roles[i.Role]
|
||||
if r != "" {
|
||||
content = fmt.Sprint(r, " ", i.Content)
|
||||
} else {
|
||||
content = i.Content
|
||||
}
|
||||
|
||||
mess = append(mess, content)
|
||||
}
|
||||
|
||||
predInput = strings.Join(mess, "\n")
|
||||
|
||||
if input.Stream {
|
||||
log.Debug().Msgf("Stream request received")
|
||||
c.Context().SetContentType("text/event-stream")
|
||||
//c.Response().Header.SetContentType(fiber.MIMETextHTMLCharsetUTF8)
|
||||
// c.Set("Content-Type", "text/event-stream")
|
||||
c.Set("Cache-Control", "no-cache")
|
||||
c.Set("Connection", "keep-alive")
|
||||
c.Set("Transfer-Encoding", "chunked")
|
||||
}
|
||||
|
||||
templateFile := config.Model
|
||||
|
||||
if config.TemplateConfig.Chat != "" {
|
||||
templateFile = config.TemplateConfig.Chat
|
||||
}
|
||||
|
||||
// A model can have a "file.bin.tmpl" file associated with a prompt template prefix
|
||||
templatedInput, err := o.loader.TemplatePrefix(templateFile, struct {
|
||||
Input string
|
||||
}{Input: predInput})
|
||||
if err == nil {
|
||||
predInput = templatedInput
|
||||
log.Debug().Msgf("Template found, input modified to: %s", predInput)
|
||||
}
|
||||
|
||||
if input.Stream {
|
||||
responses := make(chan OpenAIResponse)
|
||||
|
||||
go process(predInput, input, config, o.loader, responses)
|
||||
|
||||
c.Context().SetBodyStreamWriter(fasthttp.StreamWriter(func(w *bufio.Writer) {
|
||||
|
||||
for ev := range responses {
|
||||
var buf bytes.Buffer
|
||||
enc := json.NewEncoder(&buf)
|
||||
enc.Encode(ev)
|
||||
|
||||
log.Debug().Msgf("Sending chunk: %s", buf.String())
|
||||
fmt.Fprintf(w, "data: %v\n", buf.String())
|
||||
w.Flush()
|
||||
}
|
||||
|
||||
resp := &OpenAIResponse{
|
||||
Model: input.Model, // we have to return what the user sent here, due to OpenAI spec.
|
||||
Choices: []Choice{{FinishReason: "stop"}},
|
||||
}
|
||||
respData, _ := json.Marshal(resp)
|
||||
|
||||
w.WriteString(fmt.Sprintf("data: %s\n\n", respData))
|
||||
w.WriteString("data: [DONE]\n\n")
|
||||
w.Flush()
|
||||
}))
|
||||
return nil
|
||||
}
|
||||
|
||||
result, err := ComputeChoices(predInput, input, config, o, o.loader, func(s string, c *[]Choice) {
|
||||
*c = append(*c, Choice{Message: &Message{Role: "assistant", Content: s}})
|
||||
}, nil)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
|
||||
resp := &OpenAIResponse{
|
||||
Model: input.Model, // we have to return what the user sent here, due to OpenAI spec.
|
||||
Choices: result,
|
||||
Object: "chat.completion",
|
||||
}
|
||||
respData, _ := json.Marshal(resp)
|
||||
log.Debug().Msgf("Response: %s", respData)
|
||||
|
||||
// Return the prediction in the response body
|
||||
return c.JSON(resp)
|
||||
}
|
||||
}
|
||||
|
||||
func editEndpoint(cm *ConfigMerger, o *Option) func(c *fiber.Ctx) error {
|
||||
return func(c *fiber.Ctx) error {
|
||||
model, input, err := readInput(c, o.loader, true)
|
||||
if err != nil {
|
||||
return fmt.Errorf("failed reading parameters from request:%w", err)
|
||||
}
|
||||
|
||||
config, input, err := readConfig(model, input, cm, o.loader, o.debug, o.threads, o.ctxSize, o.f16)
|
||||
if err != nil {
|
||||
return fmt.Errorf("failed reading parameters from request:%w", err)
|
||||
}
|
||||
|
||||
log.Debug().Msgf("Parameter Config: %+v", config)
|
||||
|
||||
templateFile := config.Model
|
||||
|
||||
if config.TemplateConfig.Edit != "" {
|
||||
templateFile = config.TemplateConfig.Edit
|
||||
}
|
||||
|
||||
var result []Choice
|
||||
for _, i := range config.InputStrings {
|
||||
// A model can have a "file.bin.tmpl" file associated with a prompt template prefix
|
||||
templatedInput, err := o.loader.TemplatePrefix(templateFile, struct {
|
||||
Input string
|
||||
Instruction string
|
||||
}{Input: i})
|
||||
if err == nil {
|
||||
i = templatedInput
|
||||
log.Debug().Msgf("Template found, input modified to: %s", i)
|
||||
}
|
||||
|
||||
r, err := ComputeChoices(i, input, config, o, o.loader, func(s string, c *[]Choice) {
|
||||
*c = append(*c, Choice{Text: s})
|
||||
}, nil)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
|
||||
result = append(result, r...)
|
||||
}
|
||||
|
||||
resp := &OpenAIResponse{
|
||||
Model: input.Model, // we have to return what the user sent here, due to OpenAI spec.
|
||||
Choices: result,
|
||||
Object: "edit",
|
||||
}
|
||||
|
||||
jsonResult, _ := json.Marshal(resp)
|
||||
log.Debug().Msgf("Response: %s", jsonResult)
|
||||
|
||||
// Return the prediction in the response body
|
||||
return c.JSON(resp)
|
||||
}
|
||||
}
|
||||
|
||||
// https://platform.openai.com/docs/api-reference/images/create
|
||||
|
||||
/*
|
||||
*
|
||||
|
||||
curl http://localhost:8080/v1/images/generations \
|
||||
-H "Content-Type: application/json" \
|
||||
-d '{
|
||||
"prompt": "A cute baby sea otter",
|
||||
"n": 1,
|
||||
"size": "512x512"
|
||||
}'
|
||||
|
||||
*
|
||||
*/
|
||||
func imageEndpoint(cm *ConfigMerger, o *Option) func(c *fiber.Ctx) error {
|
||||
return func(c *fiber.Ctx) error {
|
||||
m, input, err := readInput(c, o.loader, false)
|
||||
if err != nil {
|
||||
return fmt.Errorf("failed reading parameters from request:%w", err)
|
||||
}
|
||||
|
||||
if m == "" {
|
||||
m = model.StableDiffusionBackend
|
||||
}
|
||||
log.Debug().Msgf("Loading model: %+v", m)
|
||||
|
||||
config, input, err := readConfig(m, input, cm, o.loader, o.debug, 0, 0, false)
|
||||
if err != nil {
|
||||
return fmt.Errorf("failed reading parameters from request:%w", err)
|
||||
}
|
||||
|
||||
log.Debug().Msgf("Parameter Config: %+v", config)
|
||||
|
||||
// XXX: Only stablediffusion is supported for now
|
||||
if config.Backend == "" {
|
||||
config.Backend = model.StableDiffusionBackend
|
||||
}
|
||||
|
||||
sizeParts := strings.Split(input.Size, "x")
|
||||
if len(sizeParts) != 2 {
|
||||
return fmt.Errorf("Invalid value for 'size'")
|
||||
}
|
||||
width, err := strconv.Atoi(sizeParts[0])
|
||||
if err != nil {
|
||||
return fmt.Errorf("Invalid value for 'size'")
|
||||
}
|
||||
height, err := strconv.Atoi(sizeParts[1])
|
||||
if err != nil {
|
||||
return fmt.Errorf("Invalid value for 'size'")
|
||||
}
|
||||
|
||||
b64JSON := false
|
||||
if input.ResponseFormat == "b64_json" {
|
||||
b64JSON = true
|
||||
}
|
||||
|
||||
var result []Item
|
||||
for _, i := range config.PromptStrings {
|
||||
n := input.N
|
||||
if input.N == 0 {
|
||||
n = 1
|
||||
}
|
||||
for j := 0; j < n; j++ {
|
||||
prompts := strings.Split(i, "|")
|
||||
positive_prompt := prompts[0]
|
||||
negative_prompt := ""
|
||||
if len(prompts) > 1 {
|
||||
negative_prompt = prompts[1]
|
||||
}
|
||||
|
||||
mode := 0
|
||||
step := 15
|
||||
|
||||
if input.Mode != 0 {
|
||||
mode = input.Mode
|
||||
}
|
||||
|
||||
if input.Step != 0 {
|
||||
step = input.Step
|
||||
}
|
||||
|
||||
tempDir := ""
|
||||
if !b64JSON {
|
||||
tempDir = o.imageDir
|
||||
}
|
||||
// Create a temporary file
|
||||
outputFile, err := ioutil.TempFile(tempDir, "b64")
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
outputFile.Close()
|
||||
output := outputFile.Name() + ".png"
|
||||
// Rename the temporary file
|
||||
err = os.Rename(outputFile.Name(), output)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
|
||||
baseURL := c.BaseURL()
|
||||
|
||||
fn, err := ImageGeneration(height, width, mode, step, input.Seed, positive_prompt, negative_prompt, output, o.loader, *config, 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)
|
||||
}
|
||||
}
|
||||
|
||||
// https://platform.openai.com/docs/api-reference/audio/create
|
||||
func transcriptEndpoint(cm *ConfigMerger, o *Option) func(c *fiber.Ctx) error {
|
||||
return func(c *fiber.Ctx) error {
|
||||
m, input, err := readInput(c, o.loader, false)
|
||||
if err != nil {
|
||||
return fmt.Errorf("failed reading parameters from request:%w", err)
|
||||
}
|
||||
|
||||
config, input, err := readConfig(m, input, cm, o.loader, o.debug, o.threads, o.ctxSize, o.f16)
|
||||
if err != nil {
|
||||
return fmt.Errorf("failed reading parameters from request:%w", err)
|
||||
}
|
||||
// retrieve the file data from the request
|
||||
file, err := c.FormFile("file")
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
f, err := file.Open()
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
defer f.Close()
|
||||
|
||||
dir, err := os.MkdirTemp("", "whisper")
|
||||
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
defer os.RemoveAll(dir)
|
||||
|
||||
dst := filepath.Join(dir, path.Base(file.Filename))
|
||||
dstFile, err := os.Create(dst)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
|
||||
if _, err := io.Copy(dstFile, f); err != nil {
|
||||
log.Debug().Msgf("Audio file copying error %+v - %+v - err %+v", file.Filename, dst, err)
|
||||
return err
|
||||
}
|
||||
|
||||
log.Debug().Msgf("Audio file copied to: %+v", dst)
|
||||
|
||||
whisperModel, err := o.loader.BackendLoader(model.WhisperBackend, config.Model, []llama.ModelOption{}, uint32(config.Threads), o.assetsDestination)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
|
||||
if whisperModel == nil {
|
||||
return fmt.Errorf("could not load whisper model")
|
||||
}
|
||||
|
||||
w, ok := whisperModel.(whisper.Model)
|
||||
if !ok {
|
||||
return fmt.Errorf("loader returned non-whisper object")
|
||||
}
|
||||
|
||||
tr, err := whisperutil.Transcript(w, dst, input.Language, uint(config.Threads))
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
|
||||
log.Debug().Msgf("Trascribed: %+v", tr)
|
||||
// TODO: handle different outputs here
|
||||
return c.Status(http.StatusOK).JSON(fiber.Map{"text": tr})
|
||||
}
|
||||
}
|
||||
|
||||
func listModels(loader *model.ModelLoader, cm *ConfigMerger) func(ctx *fiber.Ctx) error {
|
||||
return func(c *fiber.Ctx) error {
|
||||
models, err := loader.ListModels()
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
var mm map[string]interface{} = map[string]interface{}{}
|
||||
|
||||
dataModels := []OpenAIModel{}
|
||||
for _, m := range models {
|
||||
mm[m] = nil
|
||||
dataModels = append(dataModels, OpenAIModel{ID: m, Object: "model"})
|
||||
}
|
||||
|
||||
for _, k := range cm.ListConfigs() {
|
||||
if _, exists := mm[k]; !exists {
|
||||
dataModels = append(dataModels, OpenAIModel{ID: k, Object: "model"})
|
||||
}
|
||||
}
|
||||
|
||||
return c.JSON(struct {
|
||||
Object string `json:"object"`
|
||||
Data []OpenAIModel `json:"data"`
|
||||
}{
|
||||
Object: "list",
|
||||
Data: dataModels,
|
||||
})
|
||||
}
|
||||
}
|
||||
399
api/openai/chat.go
Normal file
399
api/openai/chat.go
Normal file
@@ -0,0 +1,399 @@
|
||||
package openai
|
||||
|
||||
import (
|
||||
"bufio"
|
||||
"bytes"
|
||||
"encoding/json"
|
||||
"fmt"
|
||||
"strings"
|
||||
"time"
|
||||
|
||||
"github.com/go-skynet/LocalAI/api/backend"
|
||||
config "github.com/go-skynet/LocalAI/api/config"
|
||||
"github.com/go-skynet/LocalAI/api/options"
|
||||
"github.com/go-skynet/LocalAI/api/schema"
|
||||
"github.com/go-skynet/LocalAI/pkg/grammar"
|
||||
model "github.com/go-skynet/LocalAI/pkg/model"
|
||||
"github.com/go-skynet/LocalAI/pkg/utils"
|
||||
"github.com/gofiber/fiber/v2"
|
||||
"github.com/google/uuid"
|
||||
"github.com/rs/zerolog/log"
|
||||
"github.com/valyala/fasthttp"
|
||||
)
|
||||
|
||||
func ChatEndpoint(cm *config.ConfigLoader, o *options.Option) func(c *fiber.Ctx) error {
|
||||
emptyMessage := ""
|
||||
id := uuid.New().String()
|
||||
created := int(time.Now().Unix())
|
||||
|
||||
process := func(s string, req *schema.OpenAIRequest, config *config.Config, loader *model.ModelLoader, responses chan schema.OpenAIResponse) {
|
||||
initialMessage := schema.OpenAIResponse{
|
||||
ID: id,
|
||||
Created: created,
|
||||
Model: req.Model, // we have to return what the user sent here, due to OpenAI spec.
|
||||
Choices: []schema.Choice{{Delta: &schema.Message{Role: "assistant", Content: &emptyMessage}}},
|
||||
Object: "chat.completion.chunk",
|
||||
}
|
||||
responses <- initialMessage
|
||||
|
||||
ComputeChoices(req, s, config, o, loader, func(s string, c *[]schema.Choice) {}, func(s string, usage backend.TokenUsage) bool {
|
||||
resp := schema.OpenAIResponse{
|
||||
ID: id,
|
||||
Created: created,
|
||||
Model: req.Model, // we have to return what the user sent here, due to OpenAI spec.
|
||||
Choices: []schema.Choice{{Delta: &schema.Message{Content: &s}, Index: 0}},
|
||||
Object: "chat.completion.chunk",
|
||||
Usage: schema.OpenAIUsage{
|
||||
PromptTokens: usage.Prompt,
|
||||
CompletionTokens: usage.Completion,
|
||||
TotalTokens: usage.Prompt + usage.Completion,
|
||||
},
|
||||
}
|
||||
|
||||
responses <- resp
|
||||
return true
|
||||
})
|
||||
close(responses)
|
||||
}
|
||||
return func(c *fiber.Ctx) error {
|
||||
processFunctions := false
|
||||
funcs := grammar.Functions{}
|
||||
modelFile, input, err := readInput(c, o, true)
|
||||
if err != nil {
|
||||
return fmt.Errorf("failed reading parameters from request:%w", err)
|
||||
}
|
||||
|
||||
config, input, err := readConfig(modelFile, input, cm, o.Loader, o.Debug, o.Threads, o.ContextSize, o.F16)
|
||||
if err != nil {
|
||||
return fmt.Errorf("failed reading parameters from request:%w", err)
|
||||
}
|
||||
log.Debug().Msgf("Configuration read: %+v", config)
|
||||
|
||||
// Allow the user to set custom actions via config file
|
||||
// to be "embedded" in each model
|
||||
noActionName := "answer"
|
||||
noActionDescription := "use this action to answer without performing any action"
|
||||
|
||||
if config.FunctionsConfig.NoActionFunctionName != "" {
|
||||
noActionName = config.FunctionsConfig.NoActionFunctionName
|
||||
}
|
||||
if config.FunctionsConfig.NoActionDescriptionName != "" {
|
||||
noActionDescription = config.FunctionsConfig.NoActionDescriptionName
|
||||
}
|
||||
|
||||
if input.ResponseFormat.Type == "json_object" {
|
||||
input.Grammar = grammar.JSONBNF
|
||||
}
|
||||
|
||||
// process functions if we have any defined or if we have a function call string
|
||||
if len(input.Functions) > 0 && config.ShouldUseFunctions() {
|
||||
log.Debug().Msgf("Response needs to process functions")
|
||||
|
||||
processFunctions = true
|
||||
|
||||
noActionGrammar := grammar.Function{
|
||||
Name: noActionName,
|
||||
Description: noActionDescription,
|
||||
Parameters: map[string]interface{}{
|
||||
"properties": map[string]interface{}{
|
||||
"message": map[string]interface{}{
|
||||
"type": "string",
|
||||
"description": "The message to reply the user with",
|
||||
}},
|
||||
},
|
||||
}
|
||||
|
||||
// Append the no action function
|
||||
funcs = append(funcs, input.Functions...)
|
||||
if !config.FunctionsConfig.DisableNoAction {
|
||||
funcs = append(funcs, noActionGrammar)
|
||||
}
|
||||
|
||||
// Force picking one of the functions by the request
|
||||
if config.FunctionToCall() != "" {
|
||||
funcs = funcs.Select(config.FunctionToCall())
|
||||
}
|
||||
|
||||
// Update input grammar
|
||||
jsStruct := funcs.ToJSONStructure()
|
||||
config.Grammar = jsStruct.Grammar("")
|
||||
} else if input.JSONFunctionGrammarObject != nil {
|
||||
config.Grammar = input.JSONFunctionGrammarObject.Grammar("")
|
||||
}
|
||||
|
||||
// functions are not supported in stream mode (yet?)
|
||||
toStream := input.Stream && !processFunctions
|
||||
|
||||
log.Debug().Msgf("Parameters: %+v", config)
|
||||
|
||||
var predInput string
|
||||
|
||||
suppressConfigSystemPrompt := false
|
||||
mess := []string{}
|
||||
for messageIndex, i := range input.Messages {
|
||||
var content string
|
||||
role := i.Role
|
||||
|
||||
// if function call, we might want to customize the role so we can display better that the "assistant called a json action"
|
||||
// if an "assistant_function_call" role is defined, we use it, otherwise we use the role that is passed by in the request
|
||||
if i.FunctionCall != nil && i.Role == "assistant" {
|
||||
roleFn := "assistant_function_call"
|
||||
r := config.Roles[roleFn]
|
||||
if r != "" {
|
||||
role = roleFn
|
||||
}
|
||||
}
|
||||
r := config.Roles[role]
|
||||
contentExists := i.Content != nil && i.StringContent != ""
|
||||
// First attempt to populate content via a chat message specific template
|
||||
if config.TemplateConfig.ChatMessage != "" {
|
||||
chatMessageData := model.ChatMessageTemplateData{
|
||||
SystemPrompt: config.SystemPrompt,
|
||||
Role: r,
|
||||
RoleName: role,
|
||||
Content: i.StringContent,
|
||||
MessageIndex: messageIndex,
|
||||
}
|
||||
templatedChatMessage, err := o.Loader.EvaluateTemplateForChatMessage(config.TemplateConfig.ChatMessage, chatMessageData)
|
||||
if err != nil {
|
||||
log.Error().Msgf("error processing message %+v using template \"%s\": %v. Skipping!", chatMessageData, config.TemplateConfig.ChatMessage, err)
|
||||
} else {
|
||||
if templatedChatMessage == "" {
|
||||
log.Warn().Msgf("template \"%s\" produced blank output for %+v. Skipping!", config.TemplateConfig.ChatMessage, chatMessageData)
|
||||
continue // TODO: This continue is here intentionally to skip over the line `mess = append(mess, content)` below, and to prevent the sprintf
|
||||
}
|
||||
log.Debug().Msgf("templated message for chat: %s", templatedChatMessage)
|
||||
content = templatedChatMessage
|
||||
}
|
||||
}
|
||||
// If this model doesn't have such a template, or if that template fails to return a value, template at the message level.
|
||||
if content == "" {
|
||||
if r != "" {
|
||||
if contentExists {
|
||||
content = fmt.Sprint(r, i.StringContent)
|
||||
}
|
||||
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.StringContent)
|
||||
}
|
||||
if i.FunctionCall != nil {
|
||||
j, err := json.Marshal(i.FunctionCall)
|
||||
if err == nil {
|
||||
if contentExists {
|
||||
content += "\n" + string(j)
|
||||
} else {
|
||||
content = string(j)
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
// Special Handling: System. We care if it was printed at all, not the r branch, so check seperately
|
||||
if contentExists && role == "system" {
|
||||
suppressConfigSystemPrompt = true
|
||||
}
|
||||
}
|
||||
|
||||
mess = append(mess, content)
|
||||
}
|
||||
|
||||
predInput = strings.Join(mess, "\n")
|
||||
log.Debug().Msgf("Prompt (before templating): %s", predInput)
|
||||
|
||||
if toStream {
|
||||
log.Debug().Msgf("Stream request received")
|
||||
c.Context().SetContentType("text/event-stream")
|
||||
//c.Response().Header.SetContentType(fiber.MIMETextHTMLCharsetUTF8)
|
||||
// c.Set("Content-Type", "text/event-stream")
|
||||
c.Set("Cache-Control", "no-cache")
|
||||
c.Set("Connection", "keep-alive")
|
||||
c.Set("Transfer-Encoding", "chunked")
|
||||
}
|
||||
|
||||
templateFile := ""
|
||||
|
||||
// A model can have a "file.bin.tmpl" file associated with a prompt template prefix
|
||||
if o.Loader.ExistsInModelPath(fmt.Sprintf("%s.tmpl", config.Model)) {
|
||||
templateFile = config.Model
|
||||
}
|
||||
|
||||
if config.TemplateConfig.Chat != "" && !processFunctions {
|
||||
templateFile = config.TemplateConfig.Chat
|
||||
}
|
||||
|
||||
if config.TemplateConfig.Functions != "" && processFunctions {
|
||||
templateFile = config.TemplateConfig.Functions
|
||||
}
|
||||
|
||||
if templateFile != "" {
|
||||
templatedInput, err := o.Loader.EvaluateTemplateForPrompt(model.ChatPromptTemplate, templateFile, model.PromptTemplateData{
|
||||
SystemPrompt: config.SystemPrompt,
|
||||
SuppressSystemPrompt: suppressConfigSystemPrompt,
|
||||
Input: predInput,
|
||||
Functions: funcs,
|
||||
})
|
||||
if err == nil {
|
||||
predInput = templatedInput
|
||||
log.Debug().Msgf("Template found, input modified to: %s", predInput)
|
||||
} else {
|
||||
log.Debug().Msgf("Template failed loading: %s", err.Error())
|
||||
}
|
||||
}
|
||||
|
||||
log.Debug().Msgf("Prompt (after templating): %s", predInput)
|
||||
if processFunctions {
|
||||
log.Debug().Msgf("Grammar: %+v", config.Grammar)
|
||||
}
|
||||
|
||||
if toStream {
|
||||
responses := make(chan schema.OpenAIResponse)
|
||||
|
||||
go process(predInput, input, config, o.Loader, responses)
|
||||
|
||||
c.Context().SetBodyStreamWriter(fasthttp.StreamWriter(func(w *bufio.Writer) {
|
||||
|
||||
usage := &schema.OpenAIUsage{}
|
||||
|
||||
for ev := range responses {
|
||||
usage = &ev.Usage // Copy a pointer to the latest usage chunk so that the stop message can reference it
|
||||
var buf bytes.Buffer
|
||||
enc := json.NewEncoder(&buf)
|
||||
enc.Encode(ev)
|
||||
log.Debug().Msgf("Sending chunk: %s", buf.String())
|
||||
_, err := fmt.Fprintf(w, "data: %v\n", buf.String())
|
||||
if err != nil {
|
||||
log.Debug().Msgf("Sending chunk failed: %v", err)
|
||||
input.Cancel()
|
||||
break
|
||||
}
|
||||
w.Flush()
|
||||
}
|
||||
|
||||
resp := &schema.OpenAIResponse{
|
||||
ID: id,
|
||||
Created: created,
|
||||
Model: input.Model, // we have to return what the user sent here, due to OpenAI spec.
|
||||
Choices: []schema.Choice{
|
||||
{
|
||||
FinishReason: "stop",
|
||||
Index: 0,
|
||||
Delta: &schema.Message{Content: &emptyMessage},
|
||||
}},
|
||||
Object: "chat.completion.chunk",
|
||||
Usage: *usage,
|
||||
}
|
||||
respData, _ := json.Marshal(resp)
|
||||
|
||||
w.WriteString(fmt.Sprintf("data: %s\n\n", respData))
|
||||
w.WriteString("data: [DONE]\n\n")
|
||||
w.Flush()
|
||||
}))
|
||||
return nil
|
||||
}
|
||||
|
||||
result, tokenUsage, err := ComputeChoices(input, predInput, config, o, o.Loader, func(s string, c *[]schema.Choice) {
|
||||
if processFunctions {
|
||||
// As we have to change the result before processing, we can't stream the answer (yet?)
|
||||
ss := map[string]interface{}{}
|
||||
// This prevent newlines to break JSON parsing for clients
|
||||
s = utils.EscapeNewLines(s)
|
||||
json.Unmarshal([]byte(s), &ss)
|
||||
log.Debug().Msgf("Function return: %s %+v", s, ss)
|
||||
|
||||
// The grammar defines the function name as "function", while OpenAI returns "name"
|
||||
func_name := ss["function"]
|
||||
// Similarly, while here arguments is a map[string]interface{}, OpenAI actually want a stringified object
|
||||
args := ss["arguments"] // arguments needs to be a string, but we return an object from the grammar result (TODO: fix)
|
||||
d, _ := json.Marshal(args)
|
||||
|
||||
ss["arguments"] = string(d)
|
||||
ss["name"] = func_name
|
||||
|
||||
// if do nothing, reply with a message
|
||||
if func_name == noActionName {
|
||||
log.Debug().Msgf("nothing to do, computing a reply")
|
||||
|
||||
// If there is a message that the LLM already sends as part of the JSON reply, use it
|
||||
arguments := map[string]interface{}{}
|
||||
json.Unmarshal([]byte(d), &arguments)
|
||||
m, exists := arguments["message"]
|
||||
if exists {
|
||||
switch message := m.(type) {
|
||||
case string:
|
||||
if message != "" {
|
||||
log.Debug().Msgf("Reply received from LLM: %s", message)
|
||||
message = backend.Finetune(*config, predInput, message)
|
||||
log.Debug().Msgf("Reply received from LLM(finetuned): %s", message)
|
||||
|
||||
*c = append(*c, schema.Choice{Message: &schema.Message{Role: "assistant", Content: &message}})
|
||||
return
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
log.Debug().Msgf("No action received from LLM, without a message, computing a reply")
|
||||
// Otherwise ask the LLM to understand the JSON output and the context, and return a message
|
||||
// Note: This costs (in term of CPU) another computation
|
||||
config.Grammar = ""
|
||||
images := []string{}
|
||||
for _, m := range input.Messages {
|
||||
images = append(images, m.StringImages...)
|
||||
}
|
||||
predFunc, err := backend.ModelInference(input.Context, predInput, images, o.Loader, *config, o, nil)
|
||||
if err != nil {
|
||||
log.Error().Msgf("inference error: %s", err.Error())
|
||||
return
|
||||
}
|
||||
|
||||
prediction, err := predFunc()
|
||||
if err != nil {
|
||||
log.Error().Msgf("inference error: %s", err.Error())
|
||||
return
|
||||
}
|
||||
|
||||
fineTunedResponse := backend.Finetune(*config, predInput, prediction.Response)
|
||||
*c = append(*c, schema.Choice{Message: &schema.Message{Role: "assistant", Content: &fineTunedResponse}})
|
||||
} else {
|
||||
// otherwise reply with the function call
|
||||
*c = append(*c, schema.Choice{
|
||||
FinishReason: "function_call",
|
||||
Message: &schema.Message{Role: "assistant", FunctionCall: ss},
|
||||
})
|
||||
}
|
||||
|
||||
return
|
||||
}
|
||||
*c = append(*c, schema.Choice{FinishReason: "stop", Index: 0, Message: &schema.Message{Role: "assistant", Content: &s}})
|
||||
}, nil)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
|
||||
resp := &schema.OpenAIResponse{
|
||||
ID: id,
|
||||
Created: created,
|
||||
Model: input.Model, // we have to return what the user sent here, due to OpenAI spec.
|
||||
Choices: result,
|
||||
Object: "chat.completion",
|
||||
Usage: schema.OpenAIUsage{
|
||||
PromptTokens: tokenUsage.Prompt,
|
||||
CompletionTokens: tokenUsage.Completion,
|
||||
TotalTokens: tokenUsage.Prompt + tokenUsage.Completion,
|
||||
},
|
||||
}
|
||||
respData, _ := json.Marshal(resp)
|
||||
log.Debug().Msgf("Response: %s", respData)
|
||||
|
||||
// Return the prediction in the response body
|
||||
return c.JSON(resp)
|
||||
}
|
||||
}
|
||||
199
api/openai/completion.go
Normal file
199
api/openai/completion.go
Normal file
@@ -0,0 +1,199 @@
|
||||
package openai
|
||||
|
||||
import (
|
||||
"bufio"
|
||||
"bytes"
|
||||
"encoding/json"
|
||||
"errors"
|
||||
"fmt"
|
||||
"time"
|
||||
|
||||
"github.com/go-skynet/LocalAI/api/backend"
|
||||
config "github.com/go-skynet/LocalAI/api/config"
|
||||
"github.com/go-skynet/LocalAI/api/options"
|
||||
"github.com/go-skynet/LocalAI/api/schema"
|
||||
"github.com/go-skynet/LocalAI/pkg/grammar"
|
||||
model "github.com/go-skynet/LocalAI/pkg/model"
|
||||
"github.com/gofiber/fiber/v2"
|
||||
"github.com/google/uuid"
|
||||
"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 {
|
||||
id := uuid.New().String()
|
||||
created := int(time.Now().Unix())
|
||||
|
||||
process := func(s string, req *schema.OpenAIRequest, config *config.Config, loader *model.ModelLoader, responses chan schema.OpenAIResponse) {
|
||||
ComputeChoices(req, s, config, o, loader, func(s string, c *[]schema.Choice) {}, func(s string, usage backend.TokenUsage) bool {
|
||||
resp := schema.OpenAIResponse{
|
||||
ID: id,
|
||||
Created: created,
|
||||
Model: req.Model, // we have to return what the user sent here, due to OpenAI spec.
|
||||
Choices: []schema.Choice{
|
||||
{
|
||||
Index: 0,
|
||||
Text: s,
|
||||
},
|
||||
},
|
||||
Object: "text_completion",
|
||||
Usage: schema.OpenAIUsage{
|
||||
PromptTokens: usage.Prompt,
|
||||
CompletionTokens: usage.Completion,
|
||||
TotalTokens: usage.Prompt + usage.Completion,
|
||||
},
|
||||
}
|
||||
log.Debug().Msgf("Sending goroutine: %s", s)
|
||||
|
||||
responses <- resp
|
||||
return true
|
||||
})
|
||||
close(responses)
|
||||
}
|
||||
|
||||
return func(c *fiber.Ctx) error {
|
||||
modelFile, input, err := readInput(c, o, true)
|
||||
if err != nil {
|
||||
return fmt.Errorf("failed reading parameters from request:%w", err)
|
||||
}
|
||||
|
||||
log.Debug().Msgf("`input`: %+v", input)
|
||||
|
||||
config, input, err := readConfig(modelFile, input, cm, o.Loader, o.Debug, o.Threads, o.ContextSize, o.F16)
|
||||
if err != nil {
|
||||
return fmt.Errorf("failed reading parameters from request:%w", err)
|
||||
}
|
||||
|
||||
if input.ResponseFormat.Type == "json_object" {
|
||||
input.Grammar = grammar.JSONBNF
|
||||
}
|
||||
|
||||
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 := ""
|
||||
|
||||
// A model can have a "file.bin.tmpl" file associated with a prompt template prefix
|
||||
if o.Loader.ExistsInModelPath(fmt.Sprintf("%s.tmpl", config.Model)) {
|
||||
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]
|
||||
|
||||
if templateFile != "" {
|
||||
templatedInput, err := o.Loader.EvaluateTemplateForPrompt(model.CompletionPromptTemplate, templateFile, model.PromptTemplateData{
|
||||
Input: predInput,
|
||||
})
|
||||
if err == nil {
|
||||
predInput = templatedInput
|
||||
log.Debug().Msgf("Template found, input modified to: %s", predInput)
|
||||
}
|
||||
}
|
||||
|
||||
responses := make(chan schema.OpenAIResponse)
|
||||
|
||||
go process(predInput, input, config, o.Loader, responses)
|
||||
|
||||
c.Context().SetBodyStreamWriter(fasthttp.StreamWriter(func(w *bufio.Writer) {
|
||||
|
||||
for ev := range responses {
|
||||
var buf bytes.Buffer
|
||||
enc := json.NewEncoder(&buf)
|
||||
enc.Encode(ev)
|
||||
|
||||
log.Debug().Msgf("Sending chunk: %s", buf.String())
|
||||
fmt.Fprintf(w, "data: %v\n", buf.String())
|
||||
w.Flush()
|
||||
}
|
||||
|
||||
resp := &schema.OpenAIResponse{
|
||||
ID: id,
|
||||
Created: created,
|
||||
Model: input.Model, // we have to return what the user sent here, due to OpenAI spec.
|
||||
Choices: []schema.Choice{
|
||||
{
|
||||
Index: 0,
|
||||
FinishReason: "stop",
|
||||
},
|
||||
},
|
||||
Object: "text_completion",
|
||||
}
|
||||
respData, _ := json.Marshal(resp)
|
||||
|
||||
w.WriteString(fmt.Sprintf("data: %s\n\n", respData))
|
||||
w.WriteString("data: [DONE]\n\n")
|
||||
w.Flush()
|
||||
}))
|
||||
return nil
|
||||
}
|
||||
|
||||
var result []schema.Choice
|
||||
|
||||
totalTokenUsage := backend.TokenUsage{}
|
||||
|
||||
for k, i := range config.PromptStrings {
|
||||
if templateFile != "" {
|
||||
// A model can have a "file.bin.tmpl" file associated with a prompt template prefix
|
||||
templatedInput, err := o.Loader.EvaluateTemplateForPrompt(model.CompletionPromptTemplate, templateFile, model.PromptTemplateData{
|
||||
SystemPrompt: config.SystemPrompt,
|
||||
Input: i,
|
||||
})
|
||||
if err == nil {
|
||||
i = templatedInput
|
||||
log.Debug().Msgf("Template found, input modified to: %s", i)
|
||||
}
|
||||
}
|
||||
|
||||
r, tokenUsage, err := ComputeChoices(
|
||||
input, i, config, o, o.Loader, func(s string, c *[]schema.Choice) {
|
||||
*c = append(*c, schema.Choice{Text: s, FinishReason: "stop", Index: k})
|
||||
}, nil)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
|
||||
totalTokenUsage.Prompt += tokenUsage.Prompt
|
||||
totalTokenUsage.Completion += tokenUsage.Completion
|
||||
|
||||
result = append(result, r...)
|
||||
}
|
||||
|
||||
resp := &schema.OpenAIResponse{
|
||||
ID: id,
|
||||
Created: created,
|
||||
Model: input.Model, // we have to return what the user sent here, due to OpenAI spec.
|
||||
Choices: result,
|
||||
Object: "text_completion",
|
||||
Usage: schema.OpenAIUsage{
|
||||
PromptTokens: totalTokenUsage.Prompt,
|
||||
CompletionTokens: totalTokenUsage.Completion,
|
||||
TotalTokens: totalTokenUsage.Prompt + totalTokenUsage.Completion,
|
||||
},
|
||||
}
|
||||
|
||||
jsonResult, _ := json.Marshal(resp)
|
||||
log.Debug().Msgf("Response: %s", jsonResult)
|
||||
|
||||
// Return the prediction in the response body
|
||||
return c.JSON(resp)
|
||||
}
|
||||
}
|
||||
94
api/openai/edit.go
Normal file
94
api/openai/edit.go
Normal file
@@ -0,0 +1,94 @@
|
||||
package openai
|
||||
|
||||
import (
|
||||
"encoding/json"
|
||||
"fmt"
|
||||
"time"
|
||||
|
||||
"github.com/go-skynet/LocalAI/api/backend"
|
||||
config "github.com/go-skynet/LocalAI/api/config"
|
||||
"github.com/go-skynet/LocalAI/api/options"
|
||||
"github.com/go-skynet/LocalAI/api/schema"
|
||||
model "github.com/go-skynet/LocalAI/pkg/model"
|
||||
"github.com/gofiber/fiber/v2"
|
||||
"github.com/google/uuid"
|
||||
|
||||
"github.com/rs/zerolog/log"
|
||||
)
|
||||
|
||||
func EditEndpoint(cm *config.ConfigLoader, o *options.Option) func(c *fiber.Ctx) error {
|
||||
return func(c *fiber.Ctx) error {
|
||||
modelFile, input, err := readInput(c, o, true)
|
||||
if err != nil {
|
||||
return fmt.Errorf("failed reading parameters from request:%w", err)
|
||||
}
|
||||
|
||||
config, input, err := readConfig(modelFile, input, cm, o.Loader, o.Debug, o.Threads, o.ContextSize, o.F16)
|
||||
if err != nil {
|
||||
return fmt.Errorf("failed reading parameters from request:%w", err)
|
||||
}
|
||||
|
||||
log.Debug().Msgf("Parameter Config: %+v", config)
|
||||
|
||||
templateFile := ""
|
||||
|
||||
// A model can have a "file.bin.tmpl" file associated with a prompt template prefix
|
||||
if o.Loader.ExistsInModelPath(fmt.Sprintf("%s.tmpl", config.Model)) {
|
||||
templateFile = config.Model
|
||||
}
|
||||
|
||||
if config.TemplateConfig.Edit != "" {
|
||||
templateFile = config.TemplateConfig.Edit
|
||||
}
|
||||
|
||||
var result []schema.Choice
|
||||
totalTokenUsage := backend.TokenUsage{}
|
||||
|
||||
for _, i := range config.InputStrings {
|
||||
if templateFile != "" {
|
||||
templatedInput, err := o.Loader.EvaluateTemplateForPrompt(model.EditPromptTemplate, templateFile, model.PromptTemplateData{
|
||||
Input: i,
|
||||
Instruction: input.Instruction,
|
||||
SystemPrompt: config.SystemPrompt,
|
||||
})
|
||||
if err == nil {
|
||||
i = templatedInput
|
||||
log.Debug().Msgf("Template found, input modified to: %s", i)
|
||||
}
|
||||
}
|
||||
|
||||
r, tokenUsage, err := ComputeChoices(input, i, config, o, o.Loader, func(s string, c *[]schema.Choice) {
|
||||
*c = append(*c, schema.Choice{Text: s})
|
||||
}, nil)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
|
||||
totalTokenUsage.Prompt += tokenUsage.Prompt
|
||||
totalTokenUsage.Completion += tokenUsage.Completion
|
||||
|
||||
result = append(result, r...)
|
||||
}
|
||||
|
||||
id := uuid.New().String()
|
||||
created := int(time.Now().Unix())
|
||||
resp := &schema.OpenAIResponse{
|
||||
ID: id,
|
||||
Created: created,
|
||||
Model: input.Model, // we have to return what the user sent here, due to OpenAI spec.
|
||||
Choices: result,
|
||||
Object: "edit",
|
||||
Usage: schema.OpenAIUsage{
|
||||
PromptTokens: totalTokenUsage.Prompt,
|
||||
CompletionTokens: totalTokenUsage.Completion,
|
||||
TotalTokens: totalTokenUsage.Prompt + totalTokenUsage.Completion,
|
||||
},
|
||||
}
|
||||
|
||||
jsonResult, _ := json.Marshal(resp)
|
||||
log.Debug().Msgf("Response: %s", jsonResult)
|
||||
|
||||
// Return the prediction in the response body
|
||||
return c.JSON(resp)
|
||||
}
|
||||
}
|
||||
78
api/openai/embeddings.go
Normal file
78
api/openai/embeddings.go
Normal file
@@ -0,0 +1,78 @@
|
||||
package openai
|
||||
|
||||
import (
|
||||
"encoding/json"
|
||||
"fmt"
|
||||
"time"
|
||||
|
||||
"github.com/go-skynet/LocalAI/api/backend"
|
||||
config "github.com/go-skynet/LocalAI/api/config"
|
||||
"github.com/go-skynet/LocalAI/api/schema"
|
||||
"github.com/google/uuid"
|
||||
|
||||
"github.com/go-skynet/LocalAI/api/options"
|
||||
"github.com/gofiber/fiber/v2"
|
||||
"github.com/rs/zerolog/log"
|
||||
)
|
||||
|
||||
// https://platform.openai.com/docs/api-reference/embeddings
|
||||
func EmbeddingsEndpoint(cm *config.ConfigLoader, o *options.Option) func(c *fiber.Ctx) error {
|
||||
return func(c *fiber.Ctx) error {
|
||||
model, input, err := readInput(c, o, true)
|
||||
if err != nil {
|
||||
return fmt.Errorf("failed reading parameters from request:%w", err)
|
||||
}
|
||||
|
||||
config, input, err := readConfig(model, input, cm, o.Loader, o.Debug, o.Threads, o.ContextSize, o.F16)
|
||||
if err != nil {
|
||||
return fmt.Errorf("failed reading parameters from request:%w", err)
|
||||
}
|
||||
|
||||
log.Debug().Msgf("Parameter Config: %+v", config)
|
||||
items := []schema.Item{}
|
||||
|
||||
for i, s := range config.InputToken {
|
||||
// get the model function to call for the result
|
||||
embedFn, err := backend.ModelEmbedding("", s, o.Loader, *config, o)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
|
||||
embeddings, err := embedFn()
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
items = append(items, schema.Item{Embedding: embeddings, Index: i, Object: "embedding"})
|
||||
}
|
||||
|
||||
for i, s := range config.InputStrings {
|
||||
// get the model function to call for the result
|
||||
embedFn, err := backend.ModelEmbedding(s, []int{}, o.Loader, *config, o)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
|
||||
embeddings, err := embedFn()
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
items = append(items, schema.Item{Embedding: embeddings, Index: i, Object: "embedding"})
|
||||
}
|
||||
|
||||
id := uuid.New().String()
|
||||
created := int(time.Now().Unix())
|
||||
resp := &schema.OpenAIResponse{
|
||||
ID: id,
|
||||
Created: created,
|
||||
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)
|
||||
}
|
||||
}
|
||||
239
api/openai/image.go
Normal file
239
api/openai/image.go
Normal file
@@ -0,0 +1,239 @@
|
||||
package openai
|
||||
|
||||
import (
|
||||
"bufio"
|
||||
"encoding/base64"
|
||||
"encoding/json"
|
||||
"fmt"
|
||||
"io"
|
||||
"net/http"
|
||||
"os"
|
||||
"path/filepath"
|
||||
"strconv"
|
||||
"strings"
|
||||
"time"
|
||||
|
||||
"github.com/go-skynet/LocalAI/api/schema"
|
||||
"github.com/google/uuid"
|
||||
|
||||
"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"
|
||||
)
|
||||
|
||||
func downloadFile(url string) (string, error) {
|
||||
// Get the data
|
||||
resp, err := http.Get(url)
|
||||
if err != nil {
|
||||
return "", err
|
||||
}
|
||||
defer resp.Body.Close()
|
||||
|
||||
// Create the file
|
||||
out, err := os.CreateTemp("", "image")
|
||||
if err != nil {
|
||||
return "", err
|
||||
}
|
||||
defer out.Close()
|
||||
|
||||
// Write the body to file
|
||||
_, err = io.Copy(out, resp.Body)
|
||||
return out.Name(), err
|
||||
}
|
||||
|
||||
// https://platform.openai.com/docs/api-reference/images/create
|
||||
|
||||
/*
|
||||
*
|
||||
|
||||
curl http://localhost:8080/v1/images/generations \
|
||||
-H "Content-Type: application/json" \
|
||||
-d '{
|
||||
"prompt": "A cute baby sea otter",
|
||||
"n": 1,
|
||||
"size": "512x512"
|
||||
}'
|
||||
|
||||
*
|
||||
*/
|
||||
func ImageEndpoint(cm *config.ConfigLoader, o *options.Option) func(c *fiber.Ctx) error {
|
||||
return func(c *fiber.Ctx) error {
|
||||
m, input, err := readInput(c, o, false)
|
||||
if err != nil {
|
||||
return fmt.Errorf("failed reading parameters from request:%w", err)
|
||||
}
|
||||
|
||||
if m == "" {
|
||||
m = model.StableDiffusionBackend
|
||||
}
|
||||
log.Debug().Msgf("Loading model: %+v", m)
|
||||
|
||||
config, input, err := readConfig(m, input, cm, o.Loader, o.Debug, 0, 0, false)
|
||||
if err != nil {
|
||||
return fmt.Errorf("failed reading parameters from request:%w", err)
|
||||
}
|
||||
|
||||
src := ""
|
||||
if input.File != "" {
|
||||
|
||||
fileData := []byte{}
|
||||
// check if input.File is an URL, if so download it and save it
|
||||
// to a temporary file
|
||||
if strings.HasPrefix(input.File, "http://") || strings.HasPrefix(input.File, "https://") {
|
||||
out, err := downloadFile(input.File)
|
||||
if err != nil {
|
||||
return fmt.Errorf("failed downloading file:%w", err)
|
||||
}
|
||||
defer os.RemoveAll(out)
|
||||
|
||||
fileData, err = os.ReadFile(out)
|
||||
if err != nil {
|
||||
return fmt.Errorf("failed reading file:%w", err)
|
||||
}
|
||||
|
||||
} else {
|
||||
// base 64 decode the file and write it somewhere
|
||||
// that we will cleanup
|
||||
fileData, err = base64.StdEncoding.DecodeString(input.File)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
}
|
||||
|
||||
// Create a temporary file
|
||||
outputFile, err := os.CreateTemp(o.ImageDir, "b64")
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
// write the base64 result
|
||||
writer := bufio.NewWriter(outputFile)
|
||||
_, err = writer.Write(fileData)
|
||||
if err != nil {
|
||||
outputFile.Close()
|
||||
return err
|
||||
}
|
||||
outputFile.Close()
|
||||
src = outputFile.Name()
|
||||
defer os.RemoveAll(src)
|
||||
}
|
||||
|
||||
log.Debug().Msgf("Parameter Config: %+v", config)
|
||||
|
||||
switch config.Backend {
|
||||
case "stablediffusion":
|
||||
config.Backend = model.StableDiffusionBackend
|
||||
case "tinydream":
|
||||
config.Backend = model.TinyDreamBackend
|
||||
case "":
|
||||
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.Type == "b64_json" {
|
||||
b64JSON = true
|
||||
}
|
||||
// src and clip_skip
|
||||
var result []schema.Item
|
||||
for _, i := range config.PromptStrings {
|
||||
n := input.N
|
||||
if input.N == 0 {
|
||||
n = 1
|
||||
}
|
||||
for j := 0; j < n; j++ {
|
||||
prompts := strings.Split(i, "|")
|
||||
positive_prompt := prompts[0]
|
||||
negative_prompt := ""
|
||||
if len(prompts) > 1 {
|
||||
negative_prompt = prompts[1]
|
||||
}
|
||||
|
||||
mode := 0
|
||||
step := config.Step
|
||||
if step == 0 {
|
||||
step = 15
|
||||
}
|
||||
|
||||
if input.Mode != 0 {
|
||||
mode = input.Mode
|
||||
}
|
||||
|
||||
if input.Step != 0 {
|
||||
step = input.Step
|
||||
}
|
||||
|
||||
tempDir := ""
|
||||
if !b64JSON {
|
||||
tempDir = o.ImageDir
|
||||
}
|
||||
// Create a temporary file
|
||||
outputFile, err := os.CreateTemp(tempDir, "b64")
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
outputFile.Close()
|
||||
output := outputFile.Name() + ".png"
|
||||
// Rename the temporary file
|
||||
err = os.Rename(outputFile.Name(), output)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
|
||||
baseURL := c.BaseURL()
|
||||
|
||||
fn, err := backend.ImageGeneration(height, width, mode, step, input.Seed, positive_prompt, negative_prompt, src, output, o.Loader, *config, o)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
if err := fn(); err != nil {
|
||||
return err
|
||||
}
|
||||
|
||||
item := &schema.Item{}
|
||||
|
||||
if b64JSON {
|
||||
defer os.RemoveAll(output)
|
||||
data, err := os.ReadFile(output)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
item.B64JSON = base64.StdEncoding.EncodeToString(data)
|
||||
} else {
|
||||
base := filepath.Base(output)
|
||||
item.URL = baseURL + "/generated-images/" + base
|
||||
}
|
||||
|
||||
result = append(result, *item)
|
||||
}
|
||||
}
|
||||
|
||||
id := uuid.New().String()
|
||||
created := int(time.Now().Unix())
|
||||
resp := &schema.OpenAIResponse{
|
||||
ID: id,
|
||||
Created: created,
|
||||
Data: result,
|
||||
}
|
||||
|
||||
jsonResult, _ := json.Marshal(resp)
|
||||
log.Debug().Msgf("Response: %s", jsonResult)
|
||||
|
||||
// Return the prediction in the response body
|
||||
return c.JSON(resp)
|
||||
}
|
||||
}
|
||||
55
api/openai/inference.go
Normal file
55
api/openai/inference.go
Normal file
@@ -0,0 +1,55 @@
|
||||
package openai
|
||||
|
||||
import (
|
||||
"github.com/go-skynet/LocalAI/api/backend"
|
||||
config "github.com/go-skynet/LocalAI/api/config"
|
||||
"github.com/go-skynet/LocalAI/api/options"
|
||||
"github.com/go-skynet/LocalAI/api/schema"
|
||||
model "github.com/go-skynet/LocalAI/pkg/model"
|
||||
)
|
||||
|
||||
func ComputeChoices(
|
||||
req *schema.OpenAIRequest,
|
||||
predInput string,
|
||||
config *config.Config,
|
||||
o *options.Option,
|
||||
loader *model.ModelLoader,
|
||||
cb func(string, *[]schema.Choice),
|
||||
tokenCallback func(string, backend.TokenUsage) bool) ([]schema.Choice, backend.TokenUsage, error) {
|
||||
n := req.N // number of completions to return
|
||||
result := []schema.Choice{}
|
||||
|
||||
if n == 0 {
|
||||
n = 1
|
||||
}
|
||||
|
||||
images := []string{}
|
||||
for _, m := range req.Messages {
|
||||
images = append(images, m.StringImages...)
|
||||
}
|
||||
|
||||
// get the model function to call for the result
|
||||
predFunc, err := backend.ModelInference(req.Context, predInput, images, loader, *config, o, tokenCallback)
|
||||
if err != nil {
|
||||
return result, backend.TokenUsage{}, err
|
||||
}
|
||||
|
||||
tokenUsage := backend.TokenUsage{}
|
||||
|
||||
for i := 0; i < n; i++ {
|
||||
prediction, err := predFunc()
|
||||
if err != nil {
|
||||
return result, backend.TokenUsage{}, err
|
||||
}
|
||||
|
||||
tokenUsage.Prompt += prediction.Usage.Prompt
|
||||
tokenUsage.Completion += prediction.Usage.Completion
|
||||
|
||||
finetunedResponse := backend.Finetune(*config, predInput, prediction.Response)
|
||||
cb(finetunedResponse, &result)
|
||||
|
||||
//result = append(result, Choice{Text: prediction})
|
||||
|
||||
}
|
||||
return result, tokenUsage, err
|
||||
}
|
||||
69
api/openai/list.go
Normal file
69
api/openai/list.go
Normal file
@@ -0,0 +1,69 @@
|
||||
package openai
|
||||
|
||||
import (
|
||||
"regexp"
|
||||
|
||||
config "github.com/go-skynet/LocalAI/api/config"
|
||||
"github.com/go-skynet/LocalAI/api/schema"
|
||||
model "github.com/go-skynet/LocalAI/pkg/model"
|
||||
"github.com/gofiber/fiber/v2"
|
||||
)
|
||||
|
||||
func ListModelsEndpoint(loader *model.ModelLoader, cm *config.ConfigLoader) func(ctx *fiber.Ctx) error {
|
||||
return func(c *fiber.Ctx) error {
|
||||
models, err := loader.ListModels()
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
var mm map[string]interface{} = map[string]interface{}{}
|
||||
|
||||
dataModels := []schema.OpenAIModel{}
|
||||
|
||||
var filterFn func(name string) bool
|
||||
filter := c.Query("filter")
|
||||
|
||||
// If filter is not specified, do not filter the list by model name
|
||||
if filter == "" {
|
||||
filterFn = func(_ string) bool { return true }
|
||||
} else {
|
||||
// If filter _IS_ specified, we compile it to a regex which is used to create the filterFn
|
||||
rxp, err := regexp.Compile(filter)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
filterFn = func(name string) bool {
|
||||
return rxp.MatchString(name)
|
||||
}
|
||||
}
|
||||
|
||||
// By default, exclude any loose files that are already referenced by a configuration file.
|
||||
excludeConfigured := c.QueryBool("excludeConfigured", true)
|
||||
|
||||
// Start with the known configurations
|
||||
for _, c := range cm.GetAllConfigs() {
|
||||
if excludeConfigured {
|
||||
mm[c.Model] = nil
|
||||
}
|
||||
|
||||
if filterFn(c.Name) {
|
||||
dataModels = append(dataModels, schema.OpenAIModel{ID: c.Name, Object: "model"})
|
||||
}
|
||||
}
|
||||
|
||||
// Then iterate through the loose files:
|
||||
for _, m := range models {
|
||||
// And only adds them if they shouldn't be skipped.
|
||||
if _, exists := mm[m]; !exists && filterFn(m) {
|
||||
dataModels = append(dataModels, schema.OpenAIModel{ID: m, Object: "model"})
|
||||
}
|
||||
}
|
||||
|
||||
return c.JSON(struct {
|
||||
Object string `json:"object"`
|
||||
Data []schema.OpenAIModel `json:"data"`
|
||||
}{
|
||||
Object: "list",
|
||||
Data: dataModels,
|
||||
})
|
||||
}
|
||||
}
|
||||
336
api/openai/request.go
Normal file
336
api/openai/request.go
Normal file
@@ -0,0 +1,336 @@
|
||||
package openai
|
||||
|
||||
import (
|
||||
"context"
|
||||
"encoding/base64"
|
||||
"encoding/json"
|
||||
"fmt"
|
||||
"io/ioutil"
|
||||
"net/http"
|
||||
"os"
|
||||
"path/filepath"
|
||||
"strings"
|
||||
|
||||
config "github.com/go-skynet/LocalAI/api/config"
|
||||
options "github.com/go-skynet/LocalAI/api/options"
|
||||
"github.com/go-skynet/LocalAI/api/schema"
|
||||
model "github.com/go-skynet/LocalAI/pkg/model"
|
||||
"github.com/gofiber/fiber/v2"
|
||||
"github.com/rs/zerolog/log"
|
||||
)
|
||||
|
||||
func readInput(c *fiber.Ctx, o *options.Option, randomModel bool) (string, *schema.OpenAIRequest, error) {
|
||||
loader := o.Loader
|
||||
input := new(schema.OpenAIRequest)
|
||||
ctx, cancel := context.WithCancel(o.Context)
|
||||
input.Context = ctx
|
||||
input.Cancel = cancel
|
||||
// Get input data from the request body
|
||||
if err := c.BodyParser(input); err != nil {
|
||||
return "", nil, fmt.Errorf("failed parsing request body: %w", 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
|
||||
}
|
||||
|
||||
// this function check if the string is an URL, if it's an URL downloads the image in memory
|
||||
// encodes it in base64 and returns the base64 string
|
||||
func getBase64Image(s string) (string, error) {
|
||||
if strings.HasPrefix(s, "http") {
|
||||
// download the image
|
||||
resp, err := http.Get(s)
|
||||
if err != nil {
|
||||
return "", err
|
||||
}
|
||||
defer resp.Body.Close()
|
||||
|
||||
// read the image data into memory
|
||||
data, err := ioutil.ReadAll(resp.Body)
|
||||
if err != nil {
|
||||
return "", err
|
||||
}
|
||||
|
||||
// encode the image data in base64
|
||||
encoded := base64.StdEncoding.EncodeToString(data)
|
||||
|
||||
// return the base64 string
|
||||
return encoded, nil
|
||||
}
|
||||
|
||||
// if the string instead is prefixed with "data:image/jpeg;base64,", drop it
|
||||
if strings.HasPrefix(s, "data:image/jpeg;base64,") {
|
||||
return strings.ReplaceAll(s, "data:image/jpeg;base64,", ""), nil
|
||||
}
|
||||
return "", fmt.Errorf("not valid string")
|
||||
}
|
||||
|
||||
func updateConfig(config *config.Config, input *schema.OpenAIRequest) {
|
||||
if input.Echo {
|
||||
config.Echo = input.Echo
|
||||
}
|
||||
if input.TopK != 0 {
|
||||
config.TopK = input.TopK
|
||||
}
|
||||
if input.TopP != 0 {
|
||||
config.TopP = input.TopP
|
||||
}
|
||||
|
||||
if input.Backend != "" {
|
||||
config.Backend = input.Backend
|
||||
}
|
||||
|
||||
if input.ClipSkip != 0 {
|
||||
config.Diffusers.ClipSkip = input.ClipSkip
|
||||
}
|
||||
|
||||
if input.ModelBaseName != "" {
|
||||
config.AutoGPTQ.ModelBaseName = input.ModelBaseName
|
||||
}
|
||||
|
||||
if input.NegativePromptScale != 0 {
|
||||
config.NegativePromptScale = input.NegativePromptScale
|
||||
}
|
||||
|
||||
if input.UseFastTokenizer {
|
||||
config.UseFastTokenizer = input.UseFastTokenizer
|
||||
}
|
||||
|
||||
if input.NegativePrompt != "" {
|
||||
config.NegativePrompt = input.NegativePrompt
|
||||
}
|
||||
|
||||
if input.RopeFreqBase != 0 {
|
||||
config.RopeFreqBase = input.RopeFreqBase
|
||||
}
|
||||
|
||||
if input.RopeFreqScale != 0 {
|
||||
config.RopeFreqScale = input.RopeFreqScale
|
||||
}
|
||||
|
||||
if input.Grammar != "" {
|
||||
config.Grammar = input.Grammar
|
||||
}
|
||||
|
||||
if input.Temperature != 0 {
|
||||
config.Temperature = input.Temperature
|
||||
}
|
||||
|
||||
if input.Maxtokens != 0 {
|
||||
config.Maxtokens = input.Maxtokens
|
||||
}
|
||||
|
||||
switch stop := input.Stop.(type) {
|
||||
case string:
|
||||
if stop != "" {
|
||||
config.StopWords = append(config.StopWords, stop)
|
||||
}
|
||||
case []interface{}:
|
||||
for _, pp := range stop {
|
||||
if s, ok := pp.(string); ok {
|
||||
config.StopWords = append(config.StopWords, s)
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// Decode each request's message content
|
||||
index := 0
|
||||
for i, m := range input.Messages {
|
||||
switch content := m.Content.(type) {
|
||||
case string:
|
||||
input.Messages[i].StringContent = content
|
||||
case []interface{}:
|
||||
dat, _ := json.Marshal(content)
|
||||
c := []schema.Content{}
|
||||
json.Unmarshal(dat, &c)
|
||||
for _, pp := range c {
|
||||
if pp.Type == "text" {
|
||||
input.Messages[i].StringContent = pp.Text
|
||||
} else if pp.Type == "image_url" {
|
||||
// Detect if pp.ImageURL is an URL, if it is download the image and encode it in base64:
|
||||
base64, err := getBase64Image(pp.ImageURL.URL)
|
||||
if err == nil {
|
||||
input.Messages[i].StringImages = append(input.Messages[i].StringImages, base64) // TODO: make sure that we only return base64 stuff
|
||||
// set a placeholder for each image
|
||||
input.Messages[i].StringContent = fmt.Sprintf("[img-%d]", index) + input.Messages[i].StringContent
|
||||
index++
|
||||
} else {
|
||||
fmt.Print("Failed encoding image", err)
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
if input.RepeatPenalty != 0 {
|
||||
config.RepeatPenalty = input.RepeatPenalty
|
||||
}
|
||||
|
||||
if input.Keep != 0 {
|
||||
config.Keep = input.Keep
|
||||
}
|
||||
|
||||
if input.Batch != 0 {
|
||||
config.Batch = input.Batch
|
||||
}
|
||||
|
||||
if input.F16 {
|
||||
config.F16 = input.F16
|
||||
}
|
||||
|
||||
if input.IgnoreEOS {
|
||||
config.IgnoreEOS = input.IgnoreEOS
|
||||
}
|
||||
|
||||
if input.Seed != 0 {
|
||||
config.Seed = input.Seed
|
||||
}
|
||||
|
||||
if input.Mirostat != 0 {
|
||||
config.LLMConfig.Mirostat = input.Mirostat
|
||||
}
|
||||
|
||||
if input.MirostatETA != 0 {
|
||||
config.LLMConfig.MirostatETA = input.MirostatETA
|
||||
}
|
||||
|
||||
if input.MirostatTAU != 0 {
|
||||
config.LLMConfig.MirostatTAU = input.MirostatTAU
|
||||
}
|
||||
|
||||
if input.TypicalP != 0 {
|
||||
config.TypicalP = input.TypicalP
|
||||
}
|
||||
|
||||
switch inputs := input.Input.(type) {
|
||||
case string:
|
||||
if inputs != "" {
|
||||
config.InputStrings = append(config.InputStrings, inputs)
|
||||
}
|
||||
case []interface{}:
|
||||
for _, pp := range inputs {
|
||||
switch i := pp.(type) {
|
||||
case string:
|
||||
config.InputStrings = append(config.InputStrings, i)
|
||||
case []interface{}:
|
||||
tokens := []int{}
|
||||
for _, ii := range i {
|
||||
tokens = append(tokens, int(ii.(float64)))
|
||||
}
|
||||
config.InputToken = append(config.InputToken, tokens)
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// Can be either a string or an object
|
||||
switch fnc := input.FunctionCall.(type) {
|
||||
case string:
|
||||
if fnc != "" {
|
||||
config.SetFunctionCallString(fnc)
|
||||
}
|
||||
case map[string]interface{}:
|
||||
var name string
|
||||
n, exists := fnc["name"]
|
||||
if exists {
|
||||
nn, e := n.(string)
|
||||
if e {
|
||||
name = nn
|
||||
}
|
||||
}
|
||||
config.SetFunctionCallNameString(name)
|
||||
}
|
||||
|
||||
switch p := input.Prompt.(type) {
|
||||
case string:
|
||||
config.PromptStrings = append(config.PromptStrings, p)
|
||||
case []interface{}:
|
||||
for _, pp := range p {
|
||||
if s, ok := pp.(string); ok {
|
||||
config.PromptStrings = append(config.PromptStrings, s)
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
func readConfig(modelFile string, input *schema.OpenAIRequest, cm *config.ConfigLoader, loader *model.ModelLoader, debug bool, threads, ctx int, f16 bool) (*config.Config, *schema.OpenAIRequest, error) {
|
||||
// Load a config file if present after the model name
|
||||
modelConfig := filepath.Join(loader.ModelPath, modelFile+".yaml")
|
||||
|
||||
var cfg *config.Config
|
||||
|
||||
defaults := func() {
|
||||
cfg = config.DefaultConfig(modelFile)
|
||||
cfg.ContextSize = ctx
|
||||
cfg.Threads = threads
|
||||
cfg.F16 = f16
|
||||
cfg.Debug = debug
|
||||
}
|
||||
|
||||
cfgExisting, exists := cm.GetConfig(modelFile)
|
||||
if !exists {
|
||||
if _, err := os.Stat(modelConfig); err == nil {
|
||||
if err := cm.LoadConfig(modelConfig); err != nil {
|
||||
return nil, nil, fmt.Errorf("failed loading model config (%s) %s", modelConfig, err.Error())
|
||||
}
|
||||
cfgExisting, exists = cm.GetConfig(modelFile)
|
||||
if exists {
|
||||
cfg = &cfgExisting
|
||||
} else {
|
||||
defaults()
|
||||
}
|
||||
} else {
|
||||
defaults()
|
||||
}
|
||||
} else {
|
||||
cfg = &cfgExisting
|
||||
}
|
||||
|
||||
// Set the parameters for the language model prediction
|
||||
updateConfig(cfg, input)
|
||||
|
||||
// Don't allow 0 as setting
|
||||
if cfg.Threads == 0 {
|
||||
if threads != 0 {
|
||||
cfg.Threads = threads
|
||||
} else {
|
||||
cfg.Threads = 4
|
||||
}
|
||||
}
|
||||
|
||||
// Enforce debug flag if passed from CLI
|
||||
if debug {
|
||||
cfg.Debug = true
|
||||
}
|
||||
|
||||
return cfg, input, nil
|
||||
}
|
||||
71
api/openai/transcription.go
Normal file
71
api/openai/transcription.go
Normal file
@@ -0,0 +1,71 @@
|
||||
package openai
|
||||
|
||||
import (
|
||||
"fmt"
|
||||
"io"
|
||||
"net/http"
|
||||
"os"
|
||||
"path"
|
||||
"path/filepath"
|
||||
|
||||
"github.com/go-skynet/LocalAI/api/backend"
|
||||
config "github.com/go-skynet/LocalAI/api/config"
|
||||
"github.com/go-skynet/LocalAI/api/options"
|
||||
|
||||
"github.com/gofiber/fiber/v2"
|
||||
"github.com/rs/zerolog/log"
|
||||
)
|
||||
|
||||
// https://platform.openai.com/docs/api-reference/audio/create
|
||||
func TranscriptEndpoint(cm *config.ConfigLoader, o *options.Option) func(c *fiber.Ctx) error {
|
||||
return func(c *fiber.Ctx) error {
|
||||
m, input, err := readInput(c, o, false)
|
||||
if err != nil {
|
||||
return fmt.Errorf("failed reading parameters from request:%w", err)
|
||||
}
|
||||
|
||||
config, input, err := readConfig(m, input, cm, o.Loader, o.Debug, o.Threads, o.ContextSize, o.F16)
|
||||
if err != nil {
|
||||
return fmt.Errorf("failed reading parameters from request:%w", err)
|
||||
}
|
||||
// retrieve the file data from the request
|
||||
file, err := c.FormFile("file")
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
f, err := file.Open()
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
defer f.Close()
|
||||
|
||||
dir, err := os.MkdirTemp("", "whisper")
|
||||
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
defer os.RemoveAll(dir)
|
||||
|
||||
dst := filepath.Join(dir, path.Base(file.Filename))
|
||||
dstFile, err := os.Create(dst)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
|
||||
if _, err := io.Copy(dstFile, f); err != nil {
|
||||
log.Debug().Msgf("Audio file copying error %+v - %+v - err %+v", file.Filename, dst, err)
|
||||
return err
|
||||
}
|
||||
|
||||
log.Debug().Msgf("Audio file copied to: %+v", dst)
|
||||
|
||||
tr, err := backend.ModelTranscription(dst, input.Language, o.Loader, *config, o)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
|
||||
log.Debug().Msgf("Trascribed: %+v", tr)
|
||||
// TODO: handle different outputs here
|
||||
return c.Status(http.StatusOK).JSON(tr)
|
||||
}
|
||||
}
|
||||
137
api/options.go
137
api/options.go
@@ -1,137 +0,0 @@
|
||||
package api
|
||||
|
||||
import (
|
||||
"context"
|
||||
"embed"
|
||||
|
||||
model "github.com/go-skynet/LocalAI/pkg/model"
|
||||
)
|
||||
|
||||
type Option struct {
|
||||
context context.Context
|
||||
configFile string
|
||||
loader *model.ModelLoader
|
||||
uploadLimitMB, threads, ctxSize int
|
||||
f16 bool
|
||||
debug, disableMessage bool
|
||||
imageDir string
|
||||
cors bool
|
||||
preloadJSONModels string
|
||||
preloadModelsFromPath string
|
||||
corsAllowOrigins string
|
||||
|
||||
backendAssets embed.FS
|
||||
assetsDestination string
|
||||
}
|
||||
|
||||
type AppOption func(*Option)
|
||||
|
||||
func newOptions(o ...AppOption) *Option {
|
||||
opt := &Option{
|
||||
context: context.Background(),
|
||||
uploadLimitMB: 15,
|
||||
threads: 1,
|
||||
ctxSize: 512,
|
||||
debug: true,
|
||||
disableMessage: true,
|
||||
}
|
||||
for _, oo := range o {
|
||||
oo(opt)
|
||||
}
|
||||
return opt
|
||||
}
|
||||
|
||||
func WithCors(b bool) AppOption {
|
||||
return func(o *Option) {
|
||||
o.cors = b
|
||||
}
|
||||
}
|
||||
|
||||
func WithCorsAllowOrigins(b string) AppOption {
|
||||
return func(o *Option) {
|
||||
o.corsAllowOrigins = b
|
||||
}
|
||||
}
|
||||
|
||||
func 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 WithContext(ctx context.Context) AppOption {
|
||||
return func(o *Option) {
|
||||
o.context = ctx
|
||||
}
|
||||
}
|
||||
|
||||
func WithYAMLConfigPreload(configFile string) AppOption {
|
||||
return func(o *Option) {
|
||||
o.preloadModelsFromPath = configFile
|
||||
}
|
||||
}
|
||||
|
||||
func WithJSONStringPreload(configFile string) AppOption {
|
||||
return func(o *Option) {
|
||||
o.preloadJSONModels = configFile
|
||||
}
|
||||
}
|
||||
func WithConfigFile(configFile string) AppOption {
|
||||
return func(o *Option) {
|
||||
o.configFile = configFile
|
||||
}
|
||||
}
|
||||
|
||||
func WithModelLoader(loader *model.ModelLoader) AppOption {
|
||||
return func(o *Option) {
|
||||
o.loader = loader
|
||||
}
|
||||
}
|
||||
|
||||
func WithUploadLimitMB(limit int) AppOption {
|
||||
return func(o *Option) {
|
||||
o.uploadLimitMB = limit
|
||||
}
|
||||
}
|
||||
|
||||
func WithThreads(threads int) AppOption {
|
||||
return func(o *Option) {
|
||||
o.threads = threads
|
||||
}
|
||||
}
|
||||
|
||||
func WithContextSize(ctxSize int) AppOption {
|
||||
return func(o *Option) {
|
||||
o.ctxSize = ctxSize
|
||||
}
|
||||
}
|
||||
|
||||
func WithF16(f16 bool) AppOption {
|
||||
return func(o *Option) {
|
||||
o.f16 = f16
|
||||
}
|
||||
}
|
||||
|
||||
func WithDebug(debug bool) AppOption {
|
||||
return func(o *Option) {
|
||||
o.debug = debug
|
||||
}
|
||||
}
|
||||
|
||||
func WithDisableMessage(disableMessage bool) AppOption {
|
||||
return func(o *Option) {
|
||||
o.disableMessage = disableMessage
|
||||
}
|
||||
}
|
||||
|
||||
func WithImageDir(imageDir string) AppOption {
|
||||
return func(o *Option) {
|
||||
o.imageDir = imageDir
|
||||
}
|
||||
}
|
||||
245
api/options/options.go
Normal file
245
api/options/options.go
Normal file
@@ -0,0 +1,245 @@
|
||||
package options
|
||||
|
||||
import (
|
||||
"context"
|
||||
"embed"
|
||||
"encoding/json"
|
||||
"time"
|
||||
|
||||
"github.com/go-skynet/LocalAI/metrics"
|
||||
"github.com/go-skynet/LocalAI/pkg/gallery"
|
||||
model "github.com/go-skynet/LocalAI/pkg/model"
|
||||
"github.com/rs/zerolog/log"
|
||||
)
|
||||
|
||||
type Option struct {
|
||||
Context context.Context
|
||||
ConfigFile string
|
||||
Loader *model.ModelLoader
|
||||
UploadLimitMB, Threads, ContextSize int
|
||||
F16 bool
|
||||
Debug, DisableMessage bool
|
||||
ImageDir string
|
||||
AudioDir string
|
||||
CORS bool
|
||||
PreloadJSONModels string
|
||||
PreloadModelsFromPath string
|
||||
CORSAllowOrigins string
|
||||
ApiKeys []string
|
||||
Metrics *metrics.Metrics
|
||||
|
||||
Galleries []gallery.Gallery
|
||||
|
||||
BackendAssets embed.FS
|
||||
AssetsDestination string
|
||||
|
||||
ExternalGRPCBackends map[string]string
|
||||
|
||||
AutoloadGalleries bool
|
||||
|
||||
SingleBackend bool
|
||||
ParallelBackendRequests bool
|
||||
|
||||
WatchDogIdle bool
|
||||
WatchDogBusy bool
|
||||
WatchDog bool
|
||||
WatchDogBusyTimeout, WatchDogIdleTimeout time.Duration
|
||||
}
|
||||
|
||||
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 EnableWatchDog = func(o *Option) {
|
||||
o.WatchDog = true
|
||||
}
|
||||
|
||||
var EnableWatchDogIdleCheck = func(o *Option) {
|
||||
o.WatchDog = true
|
||||
o.WatchDogIdle = true
|
||||
}
|
||||
|
||||
var EnableWatchDogBusyCheck = func(o *Option) {
|
||||
o.WatchDog = true
|
||||
o.WatchDogBusy = true
|
||||
}
|
||||
|
||||
func SetWatchDogBusyTimeout(t time.Duration) AppOption {
|
||||
return func(o *Option) {
|
||||
o.WatchDogBusyTimeout = t
|
||||
}
|
||||
}
|
||||
|
||||
func SetWatchDogIdleTimeout(t time.Duration) AppOption {
|
||||
return func(o *Option) {
|
||||
o.WatchDogIdleTimeout = t
|
||||
}
|
||||
}
|
||||
|
||||
var EnableSingleBackend = func(o *Option) {
|
||||
o.SingleBackend = true
|
||||
}
|
||||
|
||||
var EnableParallelBackendRequests = func(o *Option) {
|
||||
o.ParallelBackendRequests = true
|
||||
}
|
||||
|
||||
var EnableGalleriesAutoload = func(o *Option) {
|
||||
o.AutoloadGalleries = true
|
||||
}
|
||||
|
||||
func WithExternalBackend(name string, uri string) AppOption {
|
||||
return func(o *Option) {
|
||||
if o.ExternalGRPCBackends == nil {
|
||||
o.ExternalGRPCBackends = make(map[string]string)
|
||||
}
|
||||
o.ExternalGRPCBackends[name] = uri
|
||||
}
|
||||
}
|
||||
|
||||
func WithCorsAllowOrigins(b string) AppOption {
|
||||
return func(o *Option) {
|
||||
o.CORSAllowOrigins = b
|
||||
}
|
||||
}
|
||||
|
||||
func WithBackendAssetsOutput(out string) AppOption {
|
||||
return func(o *Option) {
|
||||
o.AssetsDestination = out
|
||||
}
|
||||
}
|
||||
|
||||
func WithBackendAssets(f embed.FS) AppOption {
|
||||
return func(o *Option) {
|
||||
o.BackendAssets = f
|
||||
}
|
||||
}
|
||||
|
||||
func WithStringGalleries(galls string) AppOption {
|
||||
return func(o *Option) {
|
||||
if galls == "" {
|
||||
log.Debug().Msgf("no galleries to load")
|
||||
o.Galleries = []gallery.Gallery{}
|
||||
return
|
||||
}
|
||||
var galleries []gallery.Gallery
|
||||
if err := json.Unmarshal([]byte(galls), &galleries); err != nil {
|
||||
log.Error().Msgf("failed loading galleries: %s", err.Error())
|
||||
}
|
||||
o.Galleries = append(o.Galleries, galleries...)
|
||||
}
|
||||
}
|
||||
|
||||
func WithGalleries(galleries []gallery.Gallery) AppOption {
|
||||
return func(o *Option) {
|
||||
o.Galleries = append(o.Galleries, galleries...)
|
||||
}
|
||||
}
|
||||
|
||||
func WithContext(ctx context.Context) AppOption {
|
||||
return func(o *Option) {
|
||||
o.Context = ctx
|
||||
}
|
||||
}
|
||||
|
||||
func WithYAMLConfigPreload(configFile string) AppOption {
|
||||
return func(o *Option) {
|
||||
o.PreloadModelsFromPath = configFile
|
||||
}
|
||||
}
|
||||
|
||||
func WithJSONStringPreload(configFile string) AppOption {
|
||||
return func(o *Option) {
|
||||
o.PreloadJSONModels = configFile
|
||||
}
|
||||
}
|
||||
func WithConfigFile(configFile string) AppOption {
|
||||
return func(o *Option) {
|
||||
o.ConfigFile = configFile
|
||||
}
|
||||
}
|
||||
|
||||
func WithModelLoader(loader *model.ModelLoader) AppOption {
|
||||
return func(o *Option) {
|
||||
o.Loader = loader
|
||||
}
|
||||
}
|
||||
|
||||
func WithUploadLimitMB(limit int) AppOption {
|
||||
return func(o *Option) {
|
||||
o.UploadLimitMB = limit
|
||||
}
|
||||
}
|
||||
|
||||
func WithThreads(threads int) AppOption {
|
||||
return func(o *Option) {
|
||||
o.Threads = threads
|
||||
}
|
||||
}
|
||||
|
||||
func WithContextSize(ctxSize int) AppOption {
|
||||
return func(o *Option) {
|
||||
o.ContextSize = ctxSize
|
||||
}
|
||||
}
|
||||
|
||||
func WithF16(f16 bool) AppOption {
|
||||
return func(o *Option) {
|
||||
o.F16 = f16
|
||||
}
|
||||
}
|
||||
|
||||
func WithDebug(debug bool) AppOption {
|
||||
return func(o *Option) {
|
||||
o.Debug = debug
|
||||
}
|
||||
}
|
||||
|
||||
func WithDisableMessage(disableMessage bool) AppOption {
|
||||
return func(o *Option) {
|
||||
o.DisableMessage = disableMessage
|
||||
}
|
||||
}
|
||||
|
||||
func WithAudioDir(audioDir string) AppOption {
|
||||
return func(o *Option) {
|
||||
o.AudioDir = audioDir
|
||||
}
|
||||
}
|
||||
|
||||
func WithImageDir(imageDir string) AppOption {
|
||||
return func(o *Option) {
|
||||
o.ImageDir = imageDir
|
||||
}
|
||||
}
|
||||
|
||||
func WithApiKeys(apiKeys []string) AppOption {
|
||||
return func(o *Option) {
|
||||
o.ApiKeys = apiKeys
|
||||
}
|
||||
}
|
||||
|
||||
func WithMetrics(meter *metrics.Metrics) AppOption {
|
||||
return func(o *Option) {
|
||||
o.Metrics = meter
|
||||
}
|
||||
}
|
||||
@@ -1,643 +0,0 @@
|
||||
package api
|
||||
|
||||
import (
|
||||
"fmt"
|
||||
"os"
|
||||
"path/filepath"
|
||||
"regexp"
|
||||
"strings"
|
||||
"sync"
|
||||
|
||||
"github.com/donomii/go-rwkv.cpp"
|
||||
"github.com/go-skynet/LocalAI/pkg/langchain"
|
||||
model "github.com/go-skynet/LocalAI/pkg/model"
|
||||
"github.com/go-skynet/LocalAI/pkg/stablediffusion"
|
||||
"github.com/go-skynet/bloomz.cpp"
|
||||
bert "github.com/go-skynet/go-bert.cpp"
|
||||
transformers "github.com/go-skynet/go-ggml-transformers.cpp"
|
||||
llama "github.com/go-skynet/go-llama.cpp"
|
||||
gpt4all "github.com/nomic-ai/gpt4all/gpt4all-bindings/golang"
|
||||
)
|
||||
|
||||
// mutex still needed, see: https://github.com/ggerganov/llama.cpp/discussions/784
|
||||
var mutexMap sync.Mutex
|
||||
var mutexes map[string]*sync.Mutex = make(map[string]*sync.Mutex)
|
||||
|
||||
func defaultLLamaOpts(c Config) []llama.ModelOption {
|
||||
llamaOpts := []llama.ModelOption{}
|
||||
if c.ContextSize != 0 {
|
||||
llamaOpts = append(llamaOpts, llama.SetContext(c.ContextSize))
|
||||
}
|
||||
if c.F16 {
|
||||
llamaOpts = append(llamaOpts, llama.EnableF16Memory)
|
||||
}
|
||||
if c.Embeddings {
|
||||
llamaOpts = append(llamaOpts, llama.EnableEmbeddings)
|
||||
}
|
||||
|
||||
if c.NGPULayers != 0 {
|
||||
llamaOpts = append(llamaOpts, llama.SetGPULayers(c.NGPULayers))
|
||||
}
|
||||
|
||||
llamaOpts = append(llamaOpts, llama.SetMMap(c.MMap))
|
||||
llamaOpts = append(llamaOpts, llama.SetMainGPU(c.MainGPU))
|
||||
llamaOpts = append(llamaOpts, llama.SetTensorSplit(c.TensorSplit))
|
||||
if c.Batch != 0 {
|
||||
llamaOpts = append(llamaOpts, llama.SetNBatch(c.Batch))
|
||||
} else {
|
||||
llamaOpts = append(llamaOpts, llama.SetNBatch(512))
|
||||
}
|
||||
|
||||
if c.LowVRAM {
|
||||
llamaOpts = append(llamaOpts, llama.EnabelLowVRAM)
|
||||
}
|
||||
|
||||
return llamaOpts
|
||||
}
|
||||
|
||||
func ImageGeneration(height, width, mode, step, seed int, positive_prompt, negative_prompt, dst string, loader *model.ModelLoader, c Config, o *Option) (func() error, error) {
|
||||
if c.Backend != model.StableDiffusionBackend {
|
||||
return nil, fmt.Errorf("endpoint only working with stablediffusion models")
|
||||
}
|
||||
inferenceModel, err := loader.BackendLoader(c.Backend, c.ImageGenerationAssets, []llama.ModelOption{}, uint32(c.Threads), o.assetsDestination)
|
||||
if err != nil {
|
||||
return nil, err
|
||||
}
|
||||
|
||||
var fn func() error
|
||||
switch model := inferenceModel.(type) {
|
||||
case *stablediffusion.StableDiffusion:
|
||||
fn = func() error {
|
||||
return model.GenerateImage(height, width, mode, step, seed, positive_prompt, negative_prompt, dst)
|
||||
}
|
||||
|
||||
default:
|
||||
fn = func() error {
|
||||
return fmt.Errorf("creation of images not supported by the backend")
|
||||
}
|
||||
}
|
||||
|
||||
return func() error {
|
||||
// This is still needed, see: https://github.com/ggerganov/llama.cpp/discussions/784
|
||||
mutexMap.Lock()
|
||||
l, ok := mutexes[c.Backend]
|
||||
if !ok {
|
||||
m := &sync.Mutex{}
|
||||
mutexes[c.Backend] = m
|
||||
l = m
|
||||
}
|
||||
mutexMap.Unlock()
|
||||
l.Lock()
|
||||
defer l.Unlock()
|
||||
|
||||
return fn()
|
||||
}, nil
|
||||
}
|
||||
|
||||
func ModelEmbedding(s string, tokens []int, loader *model.ModelLoader, c Config, o *Option) (func() ([]float32, error), error) {
|
||||
if !c.Embeddings {
|
||||
return nil, fmt.Errorf("endpoint disabled for this model by API configuration")
|
||||
}
|
||||
|
||||
modelFile := c.Model
|
||||
|
||||
llamaOpts := defaultLLamaOpts(c)
|
||||
|
||||
var inferenceModel interface{}
|
||||
var err error
|
||||
if c.Backend == "" {
|
||||
inferenceModel, err = loader.GreedyLoader(modelFile, llamaOpts, uint32(c.Threads), o.assetsDestination)
|
||||
} else {
|
||||
inferenceModel, err = loader.BackendLoader(c.Backend, modelFile, llamaOpts, uint32(c.Threads), o.assetsDestination)
|
||||
}
|
||||
if err != nil {
|
||||
return nil, err
|
||||
}
|
||||
|
||||
var fn func() ([]float32, error)
|
||||
switch model := inferenceModel.(type) {
|
||||
case *llama.LLama:
|
||||
fn = func() ([]float32, error) {
|
||||
predictOptions := buildLLamaPredictOptions(c, loader.ModelPath)
|
||||
if len(tokens) > 0 {
|
||||
return model.TokenEmbeddings(tokens, predictOptions...)
|
||||
}
|
||||
return model.Embeddings(s, predictOptions...)
|
||||
}
|
||||
// bert embeddings
|
||||
case *bert.Bert:
|
||||
fn = func() ([]float32, error) {
|
||||
if len(tokens) > 0 {
|
||||
return model.TokenEmbeddings(tokens, bert.SetThreads(c.Threads))
|
||||
}
|
||||
return model.Embeddings(s, bert.SetThreads(c.Threads))
|
||||
}
|
||||
default:
|
||||
fn = func() ([]float32, error) {
|
||||
return nil, fmt.Errorf("embeddings not supported by the backend")
|
||||
}
|
||||
}
|
||||
|
||||
return func() ([]float32, error) {
|
||||
// This is still needed, see: https://github.com/ggerganov/llama.cpp/discussions/784
|
||||
mutexMap.Lock()
|
||||
l, ok := mutexes[modelFile]
|
||||
if !ok {
|
||||
m := &sync.Mutex{}
|
||||
mutexes[modelFile] = m
|
||||
l = m
|
||||
}
|
||||
mutexMap.Unlock()
|
||||
l.Lock()
|
||||
defer l.Unlock()
|
||||
|
||||
embeds, err := fn()
|
||||
if err != nil {
|
||||
return embeds, err
|
||||
}
|
||||
// Remove trailing 0s
|
||||
for i := len(embeds) - 1; i >= 0; i-- {
|
||||
if embeds[i] == 0.0 {
|
||||
embeds = embeds[:i]
|
||||
} else {
|
||||
break
|
||||
}
|
||||
}
|
||||
return embeds, nil
|
||||
}, nil
|
||||
}
|
||||
|
||||
func buildLLamaPredictOptions(c Config, modelPath string) []llama.PredictOption {
|
||||
// Generate the prediction using the language model
|
||||
predictOptions := []llama.PredictOption{
|
||||
llama.SetTemperature(c.Temperature),
|
||||
llama.SetTopP(c.TopP),
|
||||
llama.SetTopK(c.TopK),
|
||||
llama.SetTokens(c.Maxtokens),
|
||||
llama.SetThreads(c.Threads),
|
||||
}
|
||||
|
||||
if c.PromptCacheAll {
|
||||
predictOptions = append(predictOptions, llama.EnablePromptCacheAll)
|
||||
}
|
||||
|
||||
if c.PromptCacheRO {
|
||||
predictOptions = append(predictOptions, llama.EnablePromptCacheRO)
|
||||
}
|
||||
|
||||
if c.PromptCachePath != "" {
|
||||
// Create parent directory
|
||||
p := filepath.Join(modelPath, c.PromptCachePath)
|
||||
os.MkdirAll(filepath.Dir(p), 0755)
|
||||
predictOptions = append(predictOptions, llama.SetPathPromptCache(p))
|
||||
}
|
||||
|
||||
if c.Mirostat != 0 {
|
||||
predictOptions = append(predictOptions, llama.SetMirostat(c.Mirostat))
|
||||
}
|
||||
|
||||
if c.MirostatETA != 0 {
|
||||
predictOptions = append(predictOptions, llama.SetMirostatETA(c.MirostatETA))
|
||||
}
|
||||
|
||||
if c.MirostatTAU != 0 {
|
||||
predictOptions = append(predictOptions, llama.SetMirostatTAU(c.MirostatTAU))
|
||||
}
|
||||
|
||||
if c.Debug {
|
||||
predictOptions = append(predictOptions, llama.Debug)
|
||||
}
|
||||
|
||||
predictOptions = append(predictOptions, llama.SetStopWords(c.StopWords...))
|
||||
|
||||
if c.RepeatPenalty != 0 {
|
||||
predictOptions = append(predictOptions, llama.SetPenalty(c.RepeatPenalty))
|
||||
}
|
||||
|
||||
if c.Keep != 0 {
|
||||
predictOptions = append(predictOptions, llama.SetNKeep(c.Keep))
|
||||
}
|
||||
|
||||
if c.Batch != 0 {
|
||||
predictOptions = append(predictOptions, llama.SetBatch(c.Batch))
|
||||
}
|
||||
|
||||
if c.F16 {
|
||||
predictOptions = append(predictOptions, llama.EnableF16KV)
|
||||
}
|
||||
|
||||
if c.IgnoreEOS {
|
||||
predictOptions = append(predictOptions, llama.IgnoreEOS)
|
||||
}
|
||||
|
||||
if c.Seed != 0 {
|
||||
predictOptions = append(predictOptions, llama.SetSeed(c.Seed))
|
||||
}
|
||||
|
||||
//predictOptions = append(predictOptions, llama.SetLogitBias(c.Seed))
|
||||
|
||||
predictOptions = append(predictOptions, llama.SetFrequencyPenalty(c.FrequencyPenalty))
|
||||
predictOptions = append(predictOptions, llama.SetMlock(c.MMlock))
|
||||
predictOptions = append(predictOptions, llama.SetMemoryMap(c.MMap))
|
||||
predictOptions = append(predictOptions, llama.SetPredictionMainGPU(c.MainGPU))
|
||||
predictOptions = append(predictOptions, llama.SetPredictionTensorSplit(c.TensorSplit))
|
||||
predictOptions = append(predictOptions, llama.SetTailFreeSamplingZ(c.TFZ))
|
||||
predictOptions = append(predictOptions, llama.SetTypicalP(c.TypicalP))
|
||||
|
||||
return predictOptions
|
||||
}
|
||||
|
||||
func ModelInference(s string, loader *model.ModelLoader, c Config, o *Option, tokenCallback func(string) bool) (func() (string, error), error) {
|
||||
supportStreams := false
|
||||
modelFile := c.Model
|
||||
|
||||
llamaOpts := defaultLLamaOpts(c)
|
||||
|
||||
var inferenceModel interface{}
|
||||
var err error
|
||||
if c.Backend == "" {
|
||||
inferenceModel, err = loader.GreedyLoader(modelFile, llamaOpts, uint32(c.Threads), o.assetsDestination)
|
||||
} else {
|
||||
inferenceModel, err = loader.BackendLoader(c.Backend, modelFile, llamaOpts, uint32(c.Threads), o.assetsDestination)
|
||||
}
|
||||
if err != nil {
|
||||
return nil, err
|
||||
}
|
||||
|
||||
var fn func() (string, error)
|
||||
|
||||
switch model := inferenceModel.(type) {
|
||||
case *rwkv.RwkvState:
|
||||
supportStreams = true
|
||||
|
||||
fn = func() (string, error) {
|
||||
stopWord := "\n"
|
||||
if len(c.StopWords) > 0 {
|
||||
stopWord = c.StopWords[0]
|
||||
}
|
||||
|
||||
if err := model.ProcessInput(s); err != nil {
|
||||
return "", err
|
||||
}
|
||||
|
||||
response := model.GenerateResponse(c.Maxtokens, stopWord, float32(c.Temperature), float32(c.TopP), tokenCallback)
|
||||
|
||||
return response, nil
|
||||
}
|
||||
case *transformers.GPTNeoX:
|
||||
fn = func() (string, error) {
|
||||
// Generate the prediction using the language model
|
||||
predictOptions := []transformers.PredictOption{
|
||||
transformers.SetTemperature(c.Temperature),
|
||||
transformers.SetTopP(c.TopP),
|
||||
transformers.SetTopK(c.TopK),
|
||||
transformers.SetTokens(c.Maxtokens),
|
||||
transformers.SetThreads(c.Threads),
|
||||
}
|
||||
|
||||
if c.Batch != 0 {
|
||||
predictOptions = append(predictOptions, transformers.SetBatch(c.Batch))
|
||||
}
|
||||
|
||||
if c.Seed != 0 {
|
||||
predictOptions = append(predictOptions, transformers.SetSeed(c.Seed))
|
||||
}
|
||||
|
||||
return model.Predict(
|
||||
s,
|
||||
predictOptions...,
|
||||
)
|
||||
}
|
||||
case *transformers.Replit:
|
||||
fn = func() (string, error) {
|
||||
// Generate the prediction using the language model
|
||||
predictOptions := []transformers.PredictOption{
|
||||
transformers.SetTemperature(c.Temperature),
|
||||
transformers.SetTopP(c.TopP),
|
||||
transformers.SetTopK(c.TopK),
|
||||
transformers.SetTokens(c.Maxtokens),
|
||||
transformers.SetThreads(c.Threads),
|
||||
}
|
||||
|
||||
if c.Batch != 0 {
|
||||
predictOptions = append(predictOptions, transformers.SetBatch(c.Batch))
|
||||
}
|
||||
|
||||
if c.Seed != 0 {
|
||||
predictOptions = append(predictOptions, transformers.SetSeed(c.Seed))
|
||||
}
|
||||
|
||||
return model.Predict(
|
||||
s,
|
||||
predictOptions...,
|
||||
)
|
||||
}
|
||||
case *transformers.Starcoder:
|
||||
fn = func() (string, error) {
|
||||
// Generate the prediction using the language model
|
||||
predictOptions := []transformers.PredictOption{
|
||||
transformers.SetTemperature(c.Temperature),
|
||||
transformers.SetTopP(c.TopP),
|
||||
transformers.SetTopK(c.TopK),
|
||||
transformers.SetTokens(c.Maxtokens),
|
||||
transformers.SetThreads(c.Threads),
|
||||
}
|
||||
|
||||
if c.Batch != 0 {
|
||||
predictOptions = append(predictOptions, transformers.SetBatch(c.Batch))
|
||||
}
|
||||
|
||||
if c.Seed != 0 {
|
||||
predictOptions = append(predictOptions, transformers.SetSeed(c.Seed))
|
||||
}
|
||||
|
||||
return model.Predict(
|
||||
s,
|
||||
predictOptions...,
|
||||
)
|
||||
}
|
||||
case *transformers.MPT:
|
||||
fn = func() (string, error) {
|
||||
// Generate the prediction using the language model
|
||||
predictOptions := []transformers.PredictOption{
|
||||
transformers.SetTemperature(c.Temperature),
|
||||
transformers.SetTopP(c.TopP),
|
||||
transformers.SetTopK(c.TopK),
|
||||
transformers.SetTokens(c.Maxtokens),
|
||||
transformers.SetThreads(c.Threads),
|
||||
}
|
||||
|
||||
if c.Batch != 0 {
|
||||
predictOptions = append(predictOptions, transformers.SetBatch(c.Batch))
|
||||
}
|
||||
|
||||
if c.Seed != 0 {
|
||||
predictOptions = append(predictOptions, transformers.SetSeed(c.Seed))
|
||||
}
|
||||
|
||||
return model.Predict(
|
||||
s,
|
||||
predictOptions...,
|
||||
)
|
||||
}
|
||||
case *bloomz.Bloomz:
|
||||
fn = func() (string, error) {
|
||||
// Generate the prediction using the language model
|
||||
predictOptions := []bloomz.PredictOption{
|
||||
bloomz.SetTemperature(c.Temperature),
|
||||
bloomz.SetTopP(c.TopP),
|
||||
bloomz.SetTopK(c.TopK),
|
||||
bloomz.SetTokens(c.Maxtokens),
|
||||
bloomz.SetThreads(c.Threads),
|
||||
}
|
||||
|
||||
if c.Seed != 0 {
|
||||
predictOptions = append(predictOptions, bloomz.SetSeed(c.Seed))
|
||||
}
|
||||
|
||||
return model.Predict(
|
||||
s,
|
||||
predictOptions...,
|
||||
)
|
||||
}
|
||||
case *transformers.Falcon:
|
||||
fn = func() (string, error) {
|
||||
// Generate the prediction using the language model
|
||||
predictOptions := []transformers.PredictOption{
|
||||
transformers.SetTemperature(c.Temperature),
|
||||
transformers.SetTopP(c.TopP),
|
||||
transformers.SetTopK(c.TopK),
|
||||
transformers.SetTokens(c.Maxtokens),
|
||||
transformers.SetThreads(c.Threads),
|
||||
}
|
||||
|
||||
if c.Batch != 0 {
|
||||
predictOptions = append(predictOptions, transformers.SetBatch(c.Batch))
|
||||
}
|
||||
|
||||
if c.Seed != 0 {
|
||||
predictOptions = append(predictOptions, transformers.SetSeed(c.Seed))
|
||||
}
|
||||
|
||||
return model.Predict(
|
||||
s,
|
||||
predictOptions...,
|
||||
)
|
||||
}
|
||||
case *transformers.GPTJ:
|
||||
fn = func() (string, error) {
|
||||
// Generate the prediction using the language model
|
||||
predictOptions := []transformers.PredictOption{
|
||||
transformers.SetTemperature(c.Temperature),
|
||||
transformers.SetTopP(c.TopP),
|
||||
transformers.SetTopK(c.TopK),
|
||||
transformers.SetTokens(c.Maxtokens),
|
||||
transformers.SetThreads(c.Threads),
|
||||
}
|
||||
|
||||
if c.Batch != 0 {
|
||||
predictOptions = append(predictOptions, transformers.SetBatch(c.Batch))
|
||||
}
|
||||
|
||||
if c.Seed != 0 {
|
||||
predictOptions = append(predictOptions, transformers.SetSeed(c.Seed))
|
||||
}
|
||||
|
||||
return model.Predict(
|
||||
s,
|
||||
predictOptions...,
|
||||
)
|
||||
}
|
||||
case *transformers.Dolly:
|
||||
fn = func() (string, error) {
|
||||
// Generate the prediction using the language model
|
||||
predictOptions := []transformers.PredictOption{
|
||||
transformers.SetTemperature(c.Temperature),
|
||||
transformers.SetTopP(c.TopP),
|
||||
transformers.SetTopK(c.TopK),
|
||||
transformers.SetTokens(c.Maxtokens),
|
||||
transformers.SetThreads(c.Threads),
|
||||
}
|
||||
|
||||
if c.Batch != 0 {
|
||||
predictOptions = append(predictOptions, transformers.SetBatch(c.Batch))
|
||||
}
|
||||
|
||||
if c.Seed != 0 {
|
||||
predictOptions = append(predictOptions, transformers.SetSeed(c.Seed))
|
||||
}
|
||||
|
||||
return model.Predict(
|
||||
s,
|
||||
predictOptions...,
|
||||
)
|
||||
}
|
||||
case *transformers.GPT2:
|
||||
fn = func() (string, error) {
|
||||
// Generate the prediction using the language model
|
||||
predictOptions := []transformers.PredictOption{
|
||||
transformers.SetTemperature(c.Temperature),
|
||||
transformers.SetTopP(c.TopP),
|
||||
transformers.SetTopK(c.TopK),
|
||||
transformers.SetTokens(c.Maxtokens),
|
||||
transformers.SetThreads(c.Threads),
|
||||
}
|
||||
|
||||
if c.Batch != 0 {
|
||||
predictOptions = append(predictOptions, transformers.SetBatch(c.Batch))
|
||||
}
|
||||
|
||||
if c.Seed != 0 {
|
||||
predictOptions = append(predictOptions, transformers.SetSeed(c.Seed))
|
||||
}
|
||||
|
||||
return model.Predict(
|
||||
s,
|
||||
predictOptions...,
|
||||
)
|
||||
}
|
||||
case *gpt4all.Model:
|
||||
supportStreams = true
|
||||
|
||||
fn = func() (string, error) {
|
||||
if tokenCallback != nil {
|
||||
model.SetTokenCallback(tokenCallback)
|
||||
}
|
||||
|
||||
// Generate the prediction using the language model
|
||||
predictOptions := []gpt4all.PredictOption{
|
||||
gpt4all.SetTemperature(c.Temperature),
|
||||
gpt4all.SetTopP(c.TopP),
|
||||
gpt4all.SetTopK(c.TopK),
|
||||
gpt4all.SetTokens(c.Maxtokens),
|
||||
}
|
||||
|
||||
if c.Batch != 0 {
|
||||
predictOptions = append(predictOptions, gpt4all.SetBatch(c.Batch))
|
||||
}
|
||||
|
||||
str, er := model.Predict(
|
||||
s,
|
||||
predictOptions...,
|
||||
)
|
||||
// Seems that if we don't free the callback explicitly we leave functions registered (that might try to send on closed channels)
|
||||
// For instance otherwise the API returns: {"error":{"code":500,"message":"send on closed channel","type":""}}
|
||||
// after a stream event has occurred
|
||||
model.SetTokenCallback(nil)
|
||||
return str, er
|
||||
}
|
||||
case *llama.LLama:
|
||||
supportStreams = true
|
||||
fn = func() (string, error) {
|
||||
|
||||
if tokenCallback != nil {
|
||||
model.SetTokenCallback(tokenCallback)
|
||||
}
|
||||
|
||||
predictOptions := buildLLamaPredictOptions(c, loader.ModelPath)
|
||||
|
||||
str, er := model.Predict(
|
||||
s,
|
||||
predictOptions...,
|
||||
)
|
||||
// Seems that if we don't free the callback explicitly we leave functions registered (that might try to send on closed channels)
|
||||
// For instance otherwise the API returns: {"error":{"code":500,"message":"send on closed channel","type":""}}
|
||||
// after a stream event has occurred
|
||||
model.SetTokenCallback(nil)
|
||||
return str, er
|
||||
}
|
||||
case *langchain.HuggingFace:
|
||||
fn = func() (string, error) {
|
||||
|
||||
// Generate the prediction using the language model
|
||||
predictOptions := []langchain.PredictOption{
|
||||
langchain.SetModel(c.Model),
|
||||
langchain.SetMaxTokens(c.Maxtokens),
|
||||
langchain.SetTemperature(c.Temperature),
|
||||
langchain.SetStopWords(c.StopWords),
|
||||
}
|
||||
|
||||
pred, er := model.PredictHuggingFace(s, predictOptions...)
|
||||
if er != nil {
|
||||
return "", er
|
||||
}
|
||||
return pred.Completion, nil
|
||||
}
|
||||
}
|
||||
|
||||
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, o *Option, 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, o, 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
|
||||
|
||||
}
|
||||
135
api/schema/openai.go
Normal file
135
api/schema/openai.go
Normal file
@@ -0,0 +1,135 @@
|
||||
package schema
|
||||
|
||||
import (
|
||||
"context"
|
||||
|
||||
config "github.com/go-skynet/LocalAI/api/config"
|
||||
|
||||
"github.com/go-skynet/LocalAI/pkg/grammar"
|
||||
)
|
||||
|
||||
// APIError provides error information returned by the OpenAI API.
|
||||
type APIError struct {
|
||||
Code any `json:"code,omitempty"`
|
||||
Message string `json:"message"`
|
||||
Param *string `json:"param,omitempty"`
|
||||
Type string `json:"type"`
|
||||
}
|
||||
|
||||
type ErrorResponse struct {
|
||||
Error *APIError `json:"error,omitempty"`
|
||||
}
|
||||
|
||||
type OpenAIUsage struct {
|
||||
PromptTokens int `json:"prompt_tokens"`
|
||||
CompletionTokens int `json:"completion_tokens"`
|
||||
TotalTokens int `json:"total_tokens"`
|
||||
}
|
||||
|
||||
type Item struct {
|
||||
Embedding []float32 `json:"embedding"`
|
||||
Index int `json:"index"`
|
||||
Object string `json:"object,omitempty"`
|
||||
|
||||
// Images
|
||||
URL string `json:"url,omitempty"`
|
||||
B64JSON string `json:"b64_json,omitempty"`
|
||||
}
|
||||
|
||||
type OpenAIResponse struct {
|
||||
Created int `json:"created,omitempty"`
|
||||
Object string `json:"object,omitempty"`
|
||||
ID string `json:"id,omitempty"`
|
||||
Model string `json:"model,omitempty"`
|
||||
Choices []Choice `json:"choices,omitempty"`
|
||||
Data []Item `json:"data,omitempty"`
|
||||
|
||||
Usage OpenAIUsage `json:"usage"`
|
||||
}
|
||||
|
||||
type Choice struct {
|
||||
Index int `json:"index"`
|
||||
FinishReason string `json:"finish_reason,omitempty"`
|
||||
Message *Message `json:"message,omitempty"`
|
||||
Delta *Message `json:"delta,omitempty"`
|
||||
Text string `json:"text,omitempty"`
|
||||
}
|
||||
|
||||
type Content struct {
|
||||
Type string `json:"type" yaml:"type"`
|
||||
Text string `json:"text" yaml:"text"`
|
||||
ImageURL ContentURL `json:"image_url" yaml:"image_url"`
|
||||
}
|
||||
|
||||
type ContentURL struct {
|
||||
URL string `json:"url" yaml:"url"`
|
||||
}
|
||||
|
||||
type Message struct {
|
||||
// The message role
|
||||
Role string `json:"role,omitempty" yaml:"role"`
|
||||
// The message content
|
||||
Content interface{} `json:"content" yaml:"content"`
|
||||
|
||||
StringContent string `json:"string_content,omitempty" yaml:"string_content,omitempty"`
|
||||
StringImages []string `json:"string_images,omitempty" yaml:"string_images,omitempty"`
|
||||
|
||||
// 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 ChatCompletionResponseFormatType string
|
||||
|
||||
type ChatCompletionResponseFormat struct {
|
||||
Type ChatCompletionResponseFormatType `json:"type,omitempty"`
|
||||
}
|
||||
|
||||
type OpenAIRequest struct {
|
||||
config.PredictionOptions
|
||||
|
||||
Context context.Context
|
||||
Cancel context.CancelFunc
|
||||
|
||||
// whisper
|
||||
File string `json:"file" validate:"required"`
|
||||
//whisper/image
|
||||
ResponseFormat ChatCompletionResponseFormat `json:"response_format"`
|
||||
// image
|
||||
Size string `json:"size"`
|
||||
// Prompt is read only by completion/image API calls
|
||||
Prompt interface{} `json:"prompt" yaml:"prompt"`
|
||||
|
||||
// Edit endpoint
|
||||
Instruction string `json:"instruction" yaml:"instruction"`
|
||||
Input interface{} `json:"input" yaml:"input"`
|
||||
|
||||
Stop interface{} `json:"stop" yaml:"stop"`
|
||||
|
||||
// Messages is read only by chat/completion API calls
|
||||
Messages []Message `json:"messages" yaml:"messages"`
|
||||
|
||||
// A list of available functions to call
|
||||
Functions []grammar.Function `json:"functions" yaml:"functions"`
|
||||
FunctionCall interface{} `json:"function_call" yaml:"function_call"` // might be a string or an object
|
||||
|
||||
Stream bool `json:"stream"`
|
||||
|
||||
// Image (not supported by OpenAI)
|
||||
Mode int `json:"mode"`
|
||||
Step int `json:"step"`
|
||||
|
||||
// A grammar to constrain the LLM output
|
||||
Grammar string `json:"grammar" yaml:"grammar"`
|
||||
|
||||
JSONFunctionGrammarObject *grammar.JSONFunctionStructure `json:"grammar_json_functions" yaml:"grammar_json_functions"`
|
||||
|
||||
Backend string `json:"backend" yaml:"backend"`
|
||||
|
||||
// AutoGPTQ
|
||||
ModelBaseName string `json:"model_base_name" yaml:"model_base_name"`
|
||||
}
|
||||
16
api/schema/whisper.go
Normal file
16
api/schema/whisper.go
Normal file
@@ -0,0 +1,16 @@
|
||||
package schema
|
||||
|
||||
import "time"
|
||||
|
||||
type Segment struct {
|
||||
Id int `json:"id"`
|
||||
Start time.Duration `json:"start"`
|
||||
End time.Duration `json:"end"`
|
||||
Text string `json:"text"`
|
||||
Tokens []int `json:"tokens"`
|
||||
}
|
||||
|
||||
type Result struct {
|
||||
Segments []Segment `json:"segments"`
|
||||
Text string `json:"text"`
|
||||
}
|
||||
209
backend/backend.proto
Normal file
209
backend/backend.proto
Normal file
@@ -0,0 +1,209 @@
|
||||
syntax = "proto3";
|
||||
|
||||
option go_package = "github.com/go-skynet/LocalAI/pkg/grpc/proto";
|
||||
option java_multiple_files = true;
|
||||
option java_package = "io.skynet.localai.backend";
|
||||
option java_outer_classname = "LocalAIBackend";
|
||||
|
||||
package backend;
|
||||
|
||||
service Backend {
|
||||
rpc Health(HealthMessage) returns (Reply) {}
|
||||
rpc Predict(PredictOptions) returns (Reply) {}
|
||||
rpc LoadModel(ModelOptions) returns (Result) {}
|
||||
rpc PredictStream(PredictOptions) returns (stream Reply) {}
|
||||
rpc Embedding(PredictOptions) returns (EmbeddingResult) {}
|
||||
rpc GenerateImage(GenerateImageRequest) returns (Result) {}
|
||||
rpc AudioTranscription(TranscriptRequest) returns (TranscriptResult) {}
|
||||
rpc TTS(TTSRequest) returns (Result) {}
|
||||
rpc TokenizeString(PredictOptions) returns (TokenizationResponse) {}
|
||||
rpc Status(HealthMessage) returns (StatusResponse) {}
|
||||
}
|
||||
|
||||
message HealthMessage {}
|
||||
|
||||
// The request message containing the user's name.
|
||||
message PredictOptions {
|
||||
string Prompt = 1;
|
||||
int32 Seed = 2;
|
||||
int32 Threads = 3;
|
||||
int32 Tokens = 4;
|
||||
int32 TopK = 5;
|
||||
int32 Repeat = 6;
|
||||
int32 Batch = 7;
|
||||
int32 NKeep = 8;
|
||||
float Temperature = 9;
|
||||
float Penalty = 10;
|
||||
bool F16KV = 11;
|
||||
bool DebugMode = 12;
|
||||
repeated string StopPrompts = 13;
|
||||
bool IgnoreEOS = 14;
|
||||
float TailFreeSamplingZ = 15;
|
||||
float TypicalP = 16;
|
||||
float FrequencyPenalty = 17;
|
||||
float PresencePenalty = 18;
|
||||
int32 Mirostat = 19;
|
||||
float MirostatETA = 20;
|
||||
float MirostatTAU = 21;
|
||||
bool PenalizeNL = 22;
|
||||
string LogitBias = 23;
|
||||
bool MLock = 25;
|
||||
bool MMap = 26;
|
||||
bool PromptCacheAll = 27;
|
||||
bool PromptCacheRO = 28;
|
||||
string Grammar = 29;
|
||||
string MainGPU = 30;
|
||||
string TensorSplit = 31;
|
||||
float TopP = 32;
|
||||
string PromptCachePath = 33;
|
||||
bool Debug = 34;
|
||||
repeated int32 EmbeddingTokens = 35;
|
||||
string Embeddings = 36;
|
||||
float RopeFreqBase = 37;
|
||||
float RopeFreqScale = 38;
|
||||
float NegativePromptScale = 39;
|
||||
string NegativePrompt = 40;
|
||||
int32 NDraft = 41;
|
||||
repeated string Images = 42;
|
||||
}
|
||||
|
||||
// The response message containing the result
|
||||
message Reply {
|
||||
bytes message = 1;
|
||||
}
|
||||
|
||||
message ModelOptions {
|
||||
string Model = 1;
|
||||
int32 ContextSize = 2;
|
||||
int32 Seed = 3;
|
||||
int32 NBatch = 4;
|
||||
bool F16Memory = 5;
|
||||
bool MLock = 6;
|
||||
bool MMap = 7;
|
||||
bool VocabOnly = 8;
|
||||
bool LowVRAM = 9;
|
||||
bool Embeddings = 10;
|
||||
bool NUMA = 11;
|
||||
int32 NGPULayers = 12;
|
||||
string MainGPU = 13;
|
||||
string TensorSplit = 14;
|
||||
int32 Threads = 15;
|
||||
string LibrarySearchPath = 16;
|
||||
float RopeFreqBase = 17;
|
||||
float RopeFreqScale = 18;
|
||||
float RMSNormEps = 19;
|
||||
int32 NGQA = 20;
|
||||
string ModelFile = 21;
|
||||
|
||||
// AutoGPTQ
|
||||
string Device = 22;
|
||||
bool UseTriton = 23;
|
||||
string ModelBaseName = 24;
|
||||
bool UseFastTokenizer = 25;
|
||||
|
||||
// Diffusers
|
||||
string PipelineType = 26;
|
||||
string SchedulerType = 27;
|
||||
bool CUDA = 28;
|
||||
float CFGScale = 29;
|
||||
bool IMG2IMG = 30;
|
||||
string CLIPModel = 31;
|
||||
string CLIPSubfolder = 32;
|
||||
int32 CLIPSkip = 33;
|
||||
string ControlNet = 48;
|
||||
|
||||
// RWKV
|
||||
string Tokenizer = 34;
|
||||
|
||||
// LLM (llama.cpp)
|
||||
string LoraBase = 35;
|
||||
string LoraAdapter = 36;
|
||||
float LoraScale = 42;
|
||||
|
||||
bool NoMulMatQ = 37;
|
||||
string DraftModel = 39;
|
||||
|
||||
string AudioPath = 38;
|
||||
|
||||
// vllm
|
||||
string Quantization = 40;
|
||||
|
||||
string MMProj = 41;
|
||||
|
||||
string RopeScaling = 43;
|
||||
float YarnExtFactor = 44;
|
||||
float YarnAttnFactor = 45;
|
||||
float YarnBetaFast = 46;
|
||||
float YarnBetaSlow = 47;
|
||||
}
|
||||
|
||||
message Result {
|
||||
string message = 1;
|
||||
bool success = 2;
|
||||
}
|
||||
|
||||
message EmbeddingResult {
|
||||
repeated float embeddings = 1;
|
||||
}
|
||||
|
||||
message TranscriptRequest {
|
||||
string dst = 2;
|
||||
string language = 3;
|
||||
uint32 threads = 4;
|
||||
}
|
||||
|
||||
message TranscriptResult {
|
||||
repeated TranscriptSegment segments = 1;
|
||||
string text = 2;
|
||||
}
|
||||
|
||||
message TranscriptSegment {
|
||||
int32 id = 1;
|
||||
int64 start = 2;
|
||||
int64 end = 3;
|
||||
string text = 4;
|
||||
repeated int32 tokens = 5;
|
||||
}
|
||||
|
||||
message GenerateImageRequest {
|
||||
int32 height = 1;
|
||||
int32 width = 2;
|
||||
int32 mode = 3;
|
||||
int32 step = 4;
|
||||
int32 seed = 5;
|
||||
string positive_prompt = 6;
|
||||
string negative_prompt = 7;
|
||||
string dst = 8;
|
||||
string src = 9;
|
||||
|
||||
// Diffusers
|
||||
string EnableParameters = 10;
|
||||
int32 CLIPSkip = 11;
|
||||
}
|
||||
|
||||
message TTSRequest {
|
||||
string text = 1;
|
||||
string model = 2;
|
||||
string dst = 3;
|
||||
}
|
||||
|
||||
message TokenizationResponse {
|
||||
int32 length = 1;
|
||||
repeated int32 tokens = 2;
|
||||
}
|
||||
|
||||
message MemoryUsageData {
|
||||
uint64 total = 1;
|
||||
map<string, uint64> breakdown = 2;
|
||||
}
|
||||
|
||||
message StatusResponse {
|
||||
enum State {
|
||||
UNINITIALIZED = 0;
|
||||
BUSY = 1;
|
||||
READY = 2;
|
||||
ERROR = -1;
|
||||
}
|
||||
State state = 1;
|
||||
MemoryUsageData memory = 2;
|
||||
}
|
||||
3
backend/cpp/grpc/.gitignore
vendored
Normal file
3
backend/cpp/grpc/.gitignore
vendored
Normal file
@@ -0,0 +1,3 @@
|
||||
installed_packages/
|
||||
grpc_build/
|
||||
grpc_repo/
|
||||
81
backend/cpp/grpc/script/build_grpc.sh
Executable file
81
backend/cpp/grpc/script/build_grpc.sh
Executable file
@@ -0,0 +1,81 @@
|
||||
#!/bin/bash
|
||||
|
||||
# Builds locally from sources the packages needed by the llama cpp backend.
|
||||
|
||||
# Makes sure a few base packages exist.
|
||||
# sudo apt-get --no-upgrade -y install g++ gcc binutils cmake git build-essential autoconf libtool pkg-config
|
||||
|
||||
SCRIPT_DIR="$( cd "$( dirname "${BASH_SOURCE[0]}" )" &> /dev/null && pwd )"
|
||||
echo "Script directory: $SCRIPT_DIR"
|
||||
|
||||
CPP_INSTALLED_PACKAGES_DIR=$1
|
||||
if [ -z ${CPP_INSTALLED_PACKAGES_DIR} ]; then
|
||||
echo "CPP_INSTALLED_PACKAGES_DIR env variable not set. Don't know where to install: failed.";
|
||||
echo
|
||||
exit -1
|
||||
fi
|
||||
|
||||
if [ -d "${CPP_INSTALLED_PACKAGES_DIR}" ]; then
|
||||
echo "gRPC installation directory already exists. Nothing to do."
|
||||
exit 0
|
||||
fi
|
||||
|
||||
# The depth when cloning a git repo. 1 speeds up the clone when the repo history is not needed.
|
||||
GIT_CLONE_DEPTH=1
|
||||
|
||||
NUM_BUILD_THREADS=$(nproc --ignore=1)
|
||||
|
||||
# Google gRPC --------------------------------------------------------------------------------------
|
||||
TAG_LIB_GRPC="v1.59.0"
|
||||
GIT_REPO_LIB_GRPC="https://github.com/grpc/grpc.git"
|
||||
GRPC_REPO_DIR="${SCRIPT_DIR}/../grpc_repo"
|
||||
GRPC_BUILD_DIR="${SCRIPT_DIR}/../grpc_build"
|
||||
SRC_DIR_LIB_GRPC="${GRPC_REPO_DIR}/grpc"
|
||||
|
||||
echo "SRC_DIR_LIB_GRPC: ${SRC_DIR_LIB_GRPC}"
|
||||
echo "GRPC_REPO_DIR: ${GRPC_REPO_DIR}"
|
||||
echo "GRPC_BUILD_DIR: ${GRPC_BUILD_DIR}"
|
||||
|
||||
mkdir -pv ${GRPC_REPO_DIR}
|
||||
|
||||
rm -rf ${GRPC_BUILD_DIR}
|
||||
mkdir -pv ${GRPC_BUILD_DIR}
|
||||
|
||||
mkdir -pv ${CPP_INSTALLED_PACKAGES_DIR}
|
||||
|
||||
if [ -d "${SRC_DIR_LIB_GRPC}" ]; then
|
||||
echo "gRPC source already exists locally. Not cloned again."
|
||||
else
|
||||
( cd ${GRPC_REPO_DIR} && \
|
||||
git clone --depth ${GIT_CLONE_DEPTH} -b ${TAG_LIB_GRPC} ${GIT_REPO_LIB_GRPC} && \
|
||||
cd ${SRC_DIR_LIB_GRPC} && \
|
||||
git submodule update --init --recursive --depth ${GIT_CLONE_DEPTH}
|
||||
)
|
||||
fi
|
||||
|
||||
( cd ${GRPC_BUILD_DIR} && \
|
||||
cmake -G "Unix Makefiles" \
|
||||
-DCMAKE_BUILD_TYPE=Release \
|
||||
-DgRPC_INSTALL=ON \
|
||||
-DEXECUTABLE_OUTPUT_PATH=${CPP_INSTALLED_PACKAGES_DIR}/grpc/bin \
|
||||
-DLIBRARY_OUTPUT_PATH=${CPP_INSTALLED_PACKAGES_DIR}/grpc/lib \
|
||||
-DgRPC_BUILD_TESTS=OFF \
|
||||
-DgRPC_BUILD_CSHARP_EXT=OFF \
|
||||
-DgRPC_BUILD_GRPC_CPP_PLUGIN=ON \
|
||||
-DgRPC_BUILD_GRPC_CSHARP_PLUGIN=OFF \
|
||||
-DgRPC_BUILD_GRPC_NODE_PLUGIN=OFF \
|
||||
-DgRPC_BUILD_GRPC_OBJECTIVE_C_PLUGIN=OFF \
|
||||
-DgRPC_BUILD_GRPC_PHP_PLUGIN=OFF \
|
||||
-DgRPC_BUILD_GRPC_PYTHON_PLUGIN=ON \
|
||||
-DgRPC_BUILD_GRPC_RUBY_PLUGIN=OFF \
|
||||
-Dprotobuf_WITH_ZLIB=ON \
|
||||
-DRE2_BUILD_TESTING=OFF \
|
||||
-DCMAKE_INSTALL_PREFIX=${CPP_INSTALLED_PACKAGES_DIR}/ \
|
||||
${SRC_DIR_LIB_GRPC} && \
|
||||
cmake --build . -- -j ${NUM_BUILD_THREADS} && \
|
||||
cmake --build . --target install -- -j ${NUM_BUILD_THREADS}
|
||||
)
|
||||
|
||||
rm -rf ${GRPC_BUILD_DIR}
|
||||
rm -rf ${GRPC_REPO_DIR}
|
||||
|
||||
74
backend/cpp/llama/CMakeLists.txt
Normal file
74
backend/cpp/llama/CMakeLists.txt
Normal file
@@ -0,0 +1,74 @@
|
||||
|
||||
## XXX: In some versions of CMake clip wasn't being built before llama.
|
||||
## This is an hack for now, but it should be fixed in the future.
|
||||
set(TARGET myclip)
|
||||
add_library(${TARGET} clip.cpp clip.h)
|
||||
install(TARGETS ${TARGET} LIBRARY)
|
||||
target_link_libraries(${TARGET} PRIVATE common ggml ${CMAKE_THREAD_LIBS_INIT})
|
||||
target_compile_features(${TARGET} PRIVATE cxx_std_11)
|
||||
if (NOT MSVC)
|
||||
target_compile_options(${TARGET} PRIVATE -Wno-cast-qual) # stb_image.h
|
||||
endif()
|
||||
|
||||
set(TARGET grpc-server)
|
||||
# END CLIP hack
|
||||
set(CMAKE_CXX_STANDARD 17)
|
||||
cmake_minimum_required(VERSION 3.15)
|
||||
set(TARGET grpc-server)
|
||||
set(_PROTOBUF_LIBPROTOBUF libprotobuf)
|
||||
set(_REFLECTION grpc++_reflection)
|
||||
if (${CMAKE_SYSTEM_NAME} MATCHES "Darwin")
|
||||
link_directories("/opt/homebrew/lib")
|
||||
include_directories("/opt/homebrew/include")
|
||||
endif()
|
||||
|
||||
find_package(absl CONFIG REQUIRED)
|
||||
find_package(Protobuf CONFIG REQUIRED)
|
||||
find_package(gRPC CONFIG REQUIRED)
|
||||
|
||||
find_program(_PROTOBUF_PROTOC protoc)
|
||||
set(_GRPC_GRPCPP grpc++)
|
||||
find_program(_GRPC_CPP_PLUGIN_EXECUTABLE grpc_cpp_plugin)
|
||||
|
||||
include_directories(${CMAKE_CURRENT_BINARY_DIR})
|
||||
include_directories(${Protobuf_INCLUDE_DIRS})
|
||||
|
||||
message(STATUS "Using protobuf version ${Protobuf_VERSION} | Protobuf_INCLUDE_DIRS: ${Protobuf_INCLUDE_DIRS} | CMAKE_CURRENT_BINARY_DIR: ${CMAKE_CURRENT_BINARY_DIR}")
|
||||
|
||||
# Proto file
|
||||
get_filename_component(hw_proto "../../../../../../backend/backend.proto" ABSOLUTE)
|
||||
get_filename_component(hw_proto_path "${hw_proto}" PATH)
|
||||
|
||||
# Generated sources
|
||||
set(hw_proto_srcs "${CMAKE_CURRENT_BINARY_DIR}/backend.pb.cc")
|
||||
set(hw_proto_hdrs "${CMAKE_CURRENT_BINARY_DIR}/backend.pb.h")
|
||||
set(hw_grpc_srcs "${CMAKE_CURRENT_BINARY_DIR}/backend.grpc.pb.cc")
|
||||
set(hw_grpc_hdrs "${CMAKE_CURRENT_BINARY_DIR}/backend.grpc.pb.h")
|
||||
|
||||
add_custom_command(
|
||||
OUTPUT "${hw_proto_srcs}" "${hw_proto_hdrs}" "${hw_grpc_srcs}" "${hw_grpc_hdrs}"
|
||||
COMMAND ${_PROTOBUF_PROTOC}
|
||||
ARGS --grpc_out "${CMAKE_CURRENT_BINARY_DIR}"
|
||||
--cpp_out "${CMAKE_CURRENT_BINARY_DIR}"
|
||||
-I "${hw_proto_path}"
|
||||
--plugin=protoc-gen-grpc="${_GRPC_CPP_PLUGIN_EXECUTABLE}"
|
||||
"${hw_proto}"
|
||||
DEPENDS "${hw_proto}")
|
||||
|
||||
# hw_grpc_proto
|
||||
add_library(hw_grpc_proto
|
||||
${hw_grpc_srcs}
|
||||
${hw_grpc_hdrs}
|
||||
${hw_proto_srcs}
|
||||
${hw_proto_hdrs} )
|
||||
|
||||
add_executable(${TARGET} grpc-server.cpp json.hpp )
|
||||
target_link_libraries(${TARGET} PRIVATE common llama myclip ${CMAKE_THREAD_LIBS_INIT} absl::flags hw_grpc_proto
|
||||
absl::flags_parse
|
||||
gRPC::${_REFLECTION}
|
||||
gRPC::${_GRPC_GRPCPP}
|
||||
protobuf::${_PROTOBUF_LIBPROTOBUF})
|
||||
target_compile_features(${TARGET} PRIVATE cxx_std_11)
|
||||
if(TARGET BUILD_INFO)
|
||||
add_dependencies(${TARGET} BUILD_INFO)
|
||||
endif()
|
||||
53
backend/cpp/llama/Makefile
Normal file
53
backend/cpp/llama/Makefile
Normal file
@@ -0,0 +1,53 @@
|
||||
|
||||
LLAMA_VERSION?=
|
||||
|
||||
CMAKE_ARGS?=
|
||||
BUILD_TYPE?=
|
||||
|
||||
# If build type is cublas, then we set -DLLAMA_CUBLAS=ON to CMAKE_ARGS automatically
|
||||
ifeq ($(BUILD_TYPE),cublas)
|
||||
CMAKE_ARGS+=-DLLAMA_CUBLAS=ON
|
||||
# If build type is openblas then we set -DLLAMA_BLAS=ON -DLLAMA_BLAS_VENDOR=OpenBLAS
|
||||
# to CMAKE_ARGS automatically
|
||||
else ifeq ($(BUILD_TYPE),openblas)
|
||||
CMAKE_ARGS+=-DLLAMA_BLAS=ON -DLLAMA_BLAS_VENDOR=OpenBLAS
|
||||
# If build type is clblast (openCL) we set -DLLAMA_CLBLAST=ON -DCLBlast_DIR=/some/path
|
||||
else ifeq ($(BUILD_TYPE),clblast)
|
||||
CMAKE_ARGS+=-DLLAMA_CLBLAST=ON -DCLBlast_DIR=/some/path
|
||||
# If it's hipblas we do have also to set CC=/opt/rocm/llvm/bin/clang CXX=/opt/rocm/llvm/bin/clang++
|
||||
else ifeq ($(BUILD_TYPE),hipblas)
|
||||
CMAKE_ARGS+=-DLLAMA_HIPBLAS=ON
|
||||
endif
|
||||
|
||||
llama.cpp:
|
||||
git clone --recurse-submodules https://github.com/ggerganov/llama.cpp llama.cpp
|
||||
if [ -z "$(LLAMA_VERSION)" ]; then \
|
||||
exit 1; \
|
||||
fi
|
||||
cd llama.cpp && git checkout -b build $(LLAMA_VERSION) && git submodule update --init --recursive --depth 1
|
||||
|
||||
llama.cpp/examples/grpc-server:
|
||||
mkdir -p llama.cpp/examples/grpc-server
|
||||
cp -r $(abspath ./)/CMakeLists.txt llama.cpp/examples/grpc-server/
|
||||
cp -r $(abspath ./)/grpc-server.cpp llama.cpp/examples/grpc-server/
|
||||
cp -rfv $(abspath ./)/json.hpp llama.cpp/examples/grpc-server/
|
||||
echo "add_subdirectory(grpc-server)" >> llama.cpp/examples/CMakeLists.txt
|
||||
## XXX: In some versions of CMake clip wasn't being built before llama.
|
||||
## This is an hack for now, but it should be fixed in the future.
|
||||
cp -rfv llama.cpp/examples/llava/clip.h llama.cpp/examples/grpc-server/clip.h
|
||||
cp -rfv llama.cpp/examples/llava/clip.cpp llama.cpp/examples/grpc-server/clip.cpp
|
||||
|
||||
rebuild:
|
||||
cp -rfv $(abspath ./)/CMakeLists.txt llama.cpp/examples/grpc-server/
|
||||
cp -rfv $(abspath ./)/grpc-server.cpp llama.cpp/examples/grpc-server/
|
||||
cp -rfv $(abspath ./)/json.hpp llama.cpp/examples/grpc-server/
|
||||
rm -rf grpc-server
|
||||
$(MAKE) grpc-server
|
||||
|
||||
clean:
|
||||
rm -rf llama.cpp
|
||||
rm -rf grpc-server
|
||||
|
||||
grpc-server: llama.cpp llama.cpp/examples/grpc-server
|
||||
cd llama.cpp && mkdir -p build && cd build && cmake .. $(CMAKE_ARGS) && cmake --build . --config Release
|
||||
cp llama.cpp/build/bin/grpc-server .
|
||||
2579
backend/cpp/llama/grpc-server.cpp
Normal file
2579
backend/cpp/llama/grpc-server.cpp
Normal file
File diff suppressed because it is too large
Load Diff
24596
backend/cpp/llama/json.hpp
Normal file
24596
backend/cpp/llama/json.hpp
Normal file
File diff suppressed because it is too large
Load Diff
21
backend/go/image/stablediffusion/main.go
Normal file
21
backend/go/image/stablediffusion/main.go
Normal file
@@ -0,0 +1,21 @@
|
||||
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"
|
||||
)
|
||||
|
||||
var (
|
||||
addr = flag.String("addr", "localhost:50051", "the address to connect to")
|
||||
)
|
||||
|
||||
func main() {
|
||||
flag.Parse()
|
||||
|
||||
if err := grpc.StartServer(*addr, &Image{}); err != nil {
|
||||
panic(err)
|
||||
}
|
||||
}
|
||||
33
backend/go/image/stablediffusion/stablediffusion.go
Normal file
33
backend/go/image/stablediffusion/stablediffusion.go
Normal file
@@ -0,0 +1,33 @@
|
||||
package main
|
||||
|
||||
// This is a wrapper to statisfy the GRPC service interface
|
||||
// It is meant to be used by the main executable that is the server for the specific backend type (falcon, gpt3, etc)
|
||||
import (
|
||||
"github.com/go-skynet/LocalAI/pkg/grpc/base"
|
||||
pb "github.com/go-skynet/LocalAI/pkg/grpc/proto"
|
||||
"github.com/go-skynet/LocalAI/pkg/stablediffusion"
|
||||
)
|
||||
|
||||
type Image struct {
|
||||
base.SingleThread
|
||||
stablediffusion *stablediffusion.StableDiffusion
|
||||
}
|
||||
|
||||
func (image *Image) Load(opts *pb.ModelOptions) error {
|
||||
var err error
|
||||
// Note: the Model here is a path to a directory containing the model files
|
||||
image.stablediffusion, err = stablediffusion.New(opts.ModelFile)
|
||||
return err
|
||||
}
|
||||
|
||||
func (image *Image) GenerateImage(opts *pb.GenerateImageRequest) error {
|
||||
return image.stablediffusion.GenerateImage(
|
||||
int(opts.Height),
|
||||
int(opts.Width),
|
||||
int(opts.Mode),
|
||||
int(opts.Step),
|
||||
int(opts.Seed),
|
||||
opts.PositivePrompt,
|
||||
opts.NegativePrompt,
|
||||
opts.Dst)
|
||||
}
|
||||
21
backend/go/image/tinydream/main.go
Normal file
21
backend/go/image/tinydream/main.go
Normal file
@@ -0,0 +1,21 @@
|
||||
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"
|
||||
)
|
||||
|
||||
var (
|
||||
addr = flag.String("addr", "localhost:50051", "the address to connect to")
|
||||
)
|
||||
|
||||
func main() {
|
||||
flag.Parse()
|
||||
|
||||
if err := grpc.StartServer(*addr, &Image{}); err != nil {
|
||||
panic(err)
|
||||
}
|
||||
}
|
||||
32
backend/go/image/tinydream/tinydream.go
Normal file
32
backend/go/image/tinydream/tinydream.go
Normal file
@@ -0,0 +1,32 @@
|
||||
package main
|
||||
|
||||
// This is a wrapper to statisfy the GRPC service interface
|
||||
// It is meant to be used by the main executable that is the server for the specific backend type (falcon, gpt3, etc)
|
||||
import (
|
||||
"github.com/go-skynet/LocalAI/pkg/grpc/base"
|
||||
pb "github.com/go-skynet/LocalAI/pkg/grpc/proto"
|
||||
"github.com/go-skynet/LocalAI/pkg/tinydream"
|
||||
)
|
||||
|
||||
type Image struct {
|
||||
base.SingleThread
|
||||
tinydream *tinydream.TinyDream
|
||||
}
|
||||
|
||||
func (image *Image) Load(opts *pb.ModelOptions) error {
|
||||
var err error
|
||||
// Note: the Model here is a path to a directory containing the model files
|
||||
image.tinydream, err = tinydream.New(opts.ModelFile)
|
||||
return err
|
||||
}
|
||||
|
||||
func (image *Image) GenerateImage(opts *pb.GenerateImageRequest) error {
|
||||
return image.tinydream.GenerateImage(
|
||||
int(opts.Height),
|
||||
int(opts.Width),
|
||||
int(opts.Step),
|
||||
int(opts.Seed),
|
||||
opts.PositivePrompt,
|
||||
opts.NegativePrompt,
|
||||
opts.Dst)
|
||||
}
|
||||
34
backend/go/llm/bert/bert.go
Normal file
34
backend/go/llm/bert/bert.go
Normal file
@@ -0,0 +1,34 @@
|
||||
package main
|
||||
|
||||
// This is a wrapper to statisfy the GRPC service interface
|
||||
// It is meant to be used by the main executable that is the server for the specific backend type (falcon, gpt3, etc)
|
||||
import (
|
||||
bert "github.com/go-skynet/go-bert.cpp"
|
||||
|
||||
"github.com/go-skynet/LocalAI/pkg/grpc/base"
|
||||
pb "github.com/go-skynet/LocalAI/pkg/grpc/proto"
|
||||
)
|
||||
|
||||
type Embeddings struct {
|
||||
base.SingleThread
|
||||
bert *bert.Bert
|
||||
}
|
||||
|
||||
func (llm *Embeddings) Load(opts *pb.ModelOptions) error {
|
||||
model, err := bert.New(opts.ModelFile)
|
||||
llm.bert = model
|
||||
return err
|
||||
}
|
||||
|
||||
func (llm *Embeddings) Embeddings(opts *pb.PredictOptions) ([]float32, error) {
|
||||
|
||||
if len(opts.EmbeddingTokens) > 0 {
|
||||
tokens := []int{}
|
||||
for _, t := range opts.EmbeddingTokens {
|
||||
tokens = append(tokens, int(t))
|
||||
}
|
||||
return llm.bert.TokenEmbeddings(tokens, bert.SetThreads(int(opts.Threads)))
|
||||
}
|
||||
|
||||
return llm.bert.Embeddings(opts.Embeddings, bert.SetThreads(int(opts.Threads)))
|
||||
}
|
||||
21
backend/go/llm/bert/main.go
Normal file
21
backend/go/llm/bert/main.go
Normal file
@@ -0,0 +1,21 @@
|
||||
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"
|
||||
)
|
||||
|
||||
var (
|
||||
addr = flag.String("addr", "localhost:50051", "the address to connect to")
|
||||
)
|
||||
|
||||
func main() {
|
||||
flag.Parse()
|
||||
|
||||
if err := grpc.StartServer(*addr, &Embeddings{}); err != nil {
|
||||
panic(err)
|
||||
}
|
||||
}
|
||||
23
backend/go/llm/dolly/main.go
Normal file
23
backend/go/llm/dolly/main.go
Normal file
@@ -0,0 +1,23 @@
|
||||
package main
|
||||
|
||||
// Note: this is started internally by LocalAI and a server is allocated for each model
|
||||
|
||||
import (
|
||||
"flag"
|
||||
|
||||
transformers "github.com/go-skynet/LocalAI/backend/go/llm/transformers"
|
||||
|
||||
grpc "github.com/go-skynet/LocalAI/pkg/grpc"
|
||||
)
|
||||
|
||||
var (
|
||||
addr = flag.String("addr", "localhost:50051", "the address to connect to")
|
||||
)
|
||||
|
||||
func main() {
|
||||
flag.Parse()
|
||||
|
||||
if err := grpc.StartServer(*addr, &transformers.Dolly{}); err != nil {
|
||||
panic(err)
|
||||
}
|
||||
}
|
||||
23
backend/go/llm/falcon-ggml/main.go
Normal file
23
backend/go/llm/falcon-ggml/main.go
Normal file
@@ -0,0 +1,23 @@
|
||||
package main
|
||||
|
||||
// Note: this is started internally by LocalAI and a server is allocated for each model
|
||||
|
||||
import (
|
||||
"flag"
|
||||
|
||||
transformers "github.com/go-skynet/LocalAI/backend/go/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)
|
||||
}
|
||||
}
|
||||
23
backend/go/llm/gpt2/main.go
Normal file
23
backend/go/llm/gpt2/main.go
Normal file
@@ -0,0 +1,23 @@
|
||||
package main
|
||||
|
||||
// Note: this is started internally by LocalAI and a server is allocated for each model
|
||||
|
||||
import (
|
||||
"flag"
|
||||
|
||||
transformers "github.com/go-skynet/LocalAI/backend/go/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)
|
||||
}
|
||||
}
|
||||
62
backend/go/llm/gpt4all/gpt4all.go
Normal file
62
backend/go/llm/gpt4all/gpt4all.go
Normal file
@@ -0,0 +1,62 @@
|
||||
package main
|
||||
|
||||
// This is a wrapper to statisfy the GRPC service interface
|
||||
// It is meant to be used by the main executable that is the server for the specific backend type (falcon, gpt3, etc)
|
||||
import (
|
||||
"fmt"
|
||||
|
||||
"github.com/go-skynet/LocalAI/pkg/grpc/base"
|
||||
pb "github.com/go-skynet/LocalAI/pkg/grpc/proto"
|
||||
gpt4all "github.com/nomic-ai/gpt4all/gpt4all-bindings/golang"
|
||||
)
|
||||
|
||||
type LLM struct {
|
||||
base.SingleThread
|
||||
|
||||
gpt4all *gpt4all.Model
|
||||
}
|
||||
|
||||
func (llm *LLM) Load(opts *pb.ModelOptions) error {
|
||||
model, err := gpt4all.New(opts.ModelFile,
|
||||
gpt4all.SetThreads(int(opts.Threads)),
|
||||
gpt4all.SetLibrarySearchPath(opts.LibrarySearchPath))
|
||||
llm.gpt4all = model
|
||||
return err
|
||||
}
|
||||
|
||||
func buildPredictOptions(opts *pb.PredictOptions) []gpt4all.PredictOption {
|
||||
predictOptions := []gpt4all.PredictOption{
|
||||
gpt4all.SetTemperature(float64(opts.Temperature)),
|
||||
gpt4all.SetTopP(float64(opts.TopP)),
|
||||
gpt4all.SetTopK(int(opts.TopK)),
|
||||
gpt4all.SetTokens(int(opts.Tokens)),
|
||||
}
|
||||
|
||||
if opts.Batch != 0 {
|
||||
predictOptions = append(predictOptions, gpt4all.SetBatch(int(opts.Batch)))
|
||||
}
|
||||
return predictOptions
|
||||
}
|
||||
|
||||
func (llm *LLM) Predict(opts *pb.PredictOptions) (string, error) {
|
||||
return llm.gpt4all.Predict(opts.Prompt, buildPredictOptions(opts)...)
|
||||
}
|
||||
|
||||
func (llm *LLM) PredictStream(opts *pb.PredictOptions, results chan string) error {
|
||||
predictOptions := buildPredictOptions(opts)
|
||||
|
||||
go func() {
|
||||
llm.gpt4all.SetTokenCallback(func(token string) bool {
|
||||
results <- token
|
||||
return true
|
||||
})
|
||||
_, err := llm.gpt4all.Predict(opts.Prompt, predictOptions...)
|
||||
if err != nil {
|
||||
fmt.Println("err: ", err)
|
||||
}
|
||||
llm.gpt4all.SetTokenCallback(nil)
|
||||
close(results)
|
||||
}()
|
||||
|
||||
return nil
|
||||
}
|
||||
21
backend/go/llm/gpt4all/main.go
Normal file
21
backend/go/llm/gpt4all/main.go
Normal file
@@ -0,0 +1,21 @@
|
||||
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"
|
||||
)
|
||||
|
||||
var (
|
||||
addr = flag.String("addr", "localhost:50051", "the address to connect to")
|
||||
)
|
||||
|
||||
func main() {
|
||||
flag.Parse()
|
||||
|
||||
if err := grpc.StartServer(*addr, &LLM{}); err != nil {
|
||||
panic(err)
|
||||
}
|
||||
}
|
||||
23
backend/go/llm/gptj/main.go
Normal file
23
backend/go/llm/gptj/main.go
Normal file
@@ -0,0 +1,23 @@
|
||||
package main
|
||||
|
||||
// Note: this is started internally by LocalAI and a server is allocated for each model
|
||||
|
||||
import (
|
||||
"flag"
|
||||
|
||||
transformers "github.com/go-skynet/LocalAI/backend/go/llm/transformers"
|
||||
|
||||
grpc "github.com/go-skynet/LocalAI/pkg/grpc"
|
||||
)
|
||||
|
||||
var (
|
||||
addr = flag.String("addr", "localhost:50051", "the address to connect to")
|
||||
)
|
||||
|
||||
func main() {
|
||||
flag.Parse()
|
||||
|
||||
if err := grpc.StartServer(*addr, &transformers.GPTJ{}); err != nil {
|
||||
panic(err)
|
||||
}
|
||||
}
|
||||
23
backend/go/llm/gptneox/main.go
Normal file
23
backend/go/llm/gptneox/main.go
Normal file
@@ -0,0 +1,23 @@
|
||||
package main
|
||||
|
||||
// Note: this is started internally by LocalAI and a server is allocated for each model
|
||||
|
||||
import (
|
||||
"flag"
|
||||
|
||||
transformers "github.com/go-skynet/LocalAI/backend/go/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)
|
||||
}
|
||||
}
|
||||
58
backend/go/llm/langchain/langchain.go
Normal file
58
backend/go/llm/langchain/langchain.go
Normal file
@@ -0,0 +1,58 @@
|
||||
package main
|
||||
|
||||
// This is a wrapper to statisfy the GRPC service interface
|
||||
// It is meant to be used by the main executable that is the server for the specific backend type (falcon, gpt3, etc)
|
||||
import (
|
||||
"fmt"
|
||||
|
||||
"github.com/go-skynet/LocalAI/pkg/grpc/base"
|
||||
pb "github.com/go-skynet/LocalAI/pkg/grpc/proto"
|
||||
"github.com/go-skynet/LocalAI/pkg/langchain"
|
||||
)
|
||||
|
||||
type LLM struct {
|
||||
base.Base
|
||||
|
||||
langchain *langchain.HuggingFace
|
||||
model string
|
||||
}
|
||||
|
||||
func (llm *LLM) Load(opts *pb.ModelOptions) error {
|
||||
llm.langchain, _ = langchain.NewHuggingFace(opts.Model)
|
||||
llm.model = opts.Model
|
||||
return nil
|
||||
}
|
||||
|
||||
func (llm *LLM) Predict(opts *pb.PredictOptions) (string, error) {
|
||||
o := []langchain.PredictOption{
|
||||
langchain.SetModel(llm.model),
|
||||
langchain.SetMaxTokens(int(opts.Tokens)),
|
||||
langchain.SetTemperature(float64(opts.Temperature)),
|
||||
langchain.SetStopWords(opts.StopPrompts),
|
||||
}
|
||||
pred, err := llm.langchain.PredictHuggingFace(opts.Prompt, o...)
|
||||
if err != nil {
|
||||
return "", err
|
||||
}
|
||||
return pred.Completion, nil
|
||||
}
|
||||
|
||||
func (llm *LLM) PredictStream(opts *pb.PredictOptions, results chan string) error {
|
||||
o := []langchain.PredictOption{
|
||||
langchain.SetModel(llm.model),
|
||||
langchain.SetMaxTokens(int(opts.Tokens)),
|
||||
langchain.SetTemperature(float64(opts.Temperature)),
|
||||
langchain.SetStopWords(opts.StopPrompts),
|
||||
}
|
||||
go func() {
|
||||
res, err := llm.langchain.PredictHuggingFace(opts.Prompt, o...)
|
||||
|
||||
if err != nil {
|
||||
fmt.Println("err: ", err)
|
||||
}
|
||||
results <- res.Completion
|
||||
close(results)
|
||||
}()
|
||||
|
||||
return nil
|
||||
}
|
||||
21
backend/go/llm/langchain/main.go
Normal file
21
backend/go/llm/langchain/main.go
Normal file
@@ -0,0 +1,21 @@
|
||||
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"
|
||||
)
|
||||
|
||||
var (
|
||||
addr = flag.String("addr", "localhost:50051", "the address to connect to")
|
||||
)
|
||||
|
||||
func main() {
|
||||
flag.Parse()
|
||||
|
||||
if err := grpc.StartServer(*addr, &LLM{}); err != nil {
|
||||
panic(err)
|
||||
}
|
||||
}
|
||||
204
backend/go/llm/llama-ggml/llama.go
Normal file
204
backend/go/llm/llama-ggml/llama.go
Normal file
@@ -0,0 +1,204 @@
|
||||
package main
|
||||
|
||||
// This is a wrapper to statisfy the GRPC service interface
|
||||
// It is meant to be used by the main executable that is the server for the specific backend type (falcon, gpt3, etc)
|
||||
import (
|
||||
"fmt"
|
||||
|
||||
"github.com/go-skynet/LocalAI/pkg/grpc/base"
|
||||
pb "github.com/go-skynet/LocalAI/pkg/grpc/proto"
|
||||
"github.com/go-skynet/go-llama.cpp"
|
||||
)
|
||||
|
||||
type LLM struct {
|
||||
base.SingleThread
|
||||
|
||||
llama *llama.LLama
|
||||
}
|
||||
|
||||
func (llm *LLM) Load(opts *pb.ModelOptions) error {
|
||||
ropeFreqBase := float32(10000)
|
||||
ropeFreqScale := float32(1)
|
||||
|
||||
if opts.RopeFreqBase != 0 {
|
||||
ropeFreqBase = opts.RopeFreqBase
|
||||
}
|
||||
if opts.RopeFreqScale != 0 {
|
||||
ropeFreqScale = opts.RopeFreqScale
|
||||
}
|
||||
|
||||
llamaOpts := []llama.ModelOption{
|
||||
llama.WithRopeFreqBase(ropeFreqBase),
|
||||
llama.WithRopeFreqScale(ropeFreqScale),
|
||||
}
|
||||
|
||||
if opts.NGQA != 0 {
|
||||
llamaOpts = append(llamaOpts, llama.WithGQA(int(opts.NGQA)))
|
||||
}
|
||||
|
||||
if opts.RMSNormEps != 0 {
|
||||
llamaOpts = append(llamaOpts, llama.WithRMSNormEPS(opts.RMSNormEps))
|
||||
}
|
||||
|
||||
if opts.ContextSize != 0 {
|
||||
llamaOpts = append(llamaOpts, llama.SetContext(int(opts.ContextSize)))
|
||||
}
|
||||
if opts.F16Memory {
|
||||
llamaOpts = append(llamaOpts, llama.EnableF16Memory)
|
||||
}
|
||||
if opts.Embeddings {
|
||||
llamaOpts = append(llamaOpts, llama.EnableEmbeddings)
|
||||
}
|
||||
if opts.NGPULayers != 0 {
|
||||
llamaOpts = append(llamaOpts, llama.SetGPULayers(int(opts.NGPULayers)))
|
||||
}
|
||||
|
||||
llamaOpts = append(llamaOpts, llama.SetMMap(opts.MMap))
|
||||
llamaOpts = append(llamaOpts, llama.SetMainGPU(opts.MainGPU))
|
||||
llamaOpts = append(llamaOpts, llama.SetTensorSplit(opts.TensorSplit))
|
||||
if opts.NBatch != 0 {
|
||||
llamaOpts = append(llamaOpts, llama.SetNBatch(int(opts.NBatch)))
|
||||
} else {
|
||||
llamaOpts = append(llamaOpts, llama.SetNBatch(512))
|
||||
}
|
||||
|
||||
if opts.NUMA {
|
||||
llamaOpts = append(llamaOpts, llama.EnableNUMA)
|
||||
}
|
||||
|
||||
if opts.LowVRAM {
|
||||
llamaOpts = append(llamaOpts, llama.EnabelLowVRAM)
|
||||
}
|
||||
|
||||
model, err := llama.New(opts.ModelFile, llamaOpts...)
|
||||
llm.llama = model
|
||||
|
||||
return err
|
||||
}
|
||||
|
||||
func buildPredictOptions(opts *pb.PredictOptions) []llama.PredictOption {
|
||||
ropeFreqBase := float32(10000)
|
||||
ropeFreqScale := float32(1)
|
||||
|
||||
if opts.RopeFreqBase != 0 {
|
||||
ropeFreqBase = opts.RopeFreqBase
|
||||
}
|
||||
if opts.RopeFreqScale != 0 {
|
||||
ropeFreqScale = opts.RopeFreqScale
|
||||
}
|
||||
predictOptions := []llama.PredictOption{
|
||||
llama.SetTemperature(opts.Temperature),
|
||||
llama.SetTopP(opts.TopP),
|
||||
llama.SetTopK(int(opts.TopK)),
|
||||
llama.SetTokens(int(opts.Tokens)),
|
||||
llama.SetThreads(int(opts.Threads)),
|
||||
llama.WithGrammar(opts.Grammar),
|
||||
llama.SetRopeFreqBase(ropeFreqBase),
|
||||
llama.SetRopeFreqScale(ropeFreqScale),
|
||||
llama.SetNegativePromptScale(opts.NegativePromptScale),
|
||||
llama.SetNegativePrompt(opts.NegativePrompt),
|
||||
}
|
||||
|
||||
if opts.PromptCacheAll {
|
||||
predictOptions = append(predictOptions, llama.EnablePromptCacheAll)
|
||||
}
|
||||
|
||||
if opts.PromptCacheRO {
|
||||
predictOptions = append(predictOptions, llama.EnablePromptCacheRO)
|
||||
}
|
||||
|
||||
// Expected absolute path
|
||||
if opts.PromptCachePath != "" {
|
||||
predictOptions = append(predictOptions, llama.SetPathPromptCache(opts.PromptCachePath))
|
||||
}
|
||||
|
||||
if opts.Mirostat != 0 {
|
||||
predictOptions = append(predictOptions, llama.SetMirostat(int(opts.Mirostat)))
|
||||
}
|
||||
|
||||
if opts.MirostatETA != 0 {
|
||||
predictOptions = append(predictOptions, llama.SetMirostatETA(opts.MirostatETA))
|
||||
}
|
||||
|
||||
if opts.MirostatTAU != 0 {
|
||||
predictOptions = append(predictOptions, llama.SetMirostatTAU(opts.MirostatTAU))
|
||||
}
|
||||
|
||||
if opts.Debug {
|
||||
predictOptions = append(predictOptions, llama.Debug)
|
||||
}
|
||||
|
||||
predictOptions = append(predictOptions, llama.SetStopWords(opts.StopPrompts...))
|
||||
|
||||
if opts.PresencePenalty != 0 {
|
||||
predictOptions = append(predictOptions, llama.SetPenalty(opts.PresencePenalty))
|
||||
}
|
||||
|
||||
if opts.NKeep != 0 {
|
||||
predictOptions = append(predictOptions, llama.SetNKeep(int(opts.NKeep)))
|
||||
}
|
||||
|
||||
if opts.Batch != 0 {
|
||||
predictOptions = append(predictOptions, llama.SetBatch(int(opts.Batch)))
|
||||
}
|
||||
|
||||
if opts.F16KV {
|
||||
predictOptions = append(predictOptions, llama.EnableF16KV)
|
||||
}
|
||||
|
||||
if opts.IgnoreEOS {
|
||||
predictOptions = append(predictOptions, llama.IgnoreEOS)
|
||||
}
|
||||
|
||||
if opts.Seed != 0 {
|
||||
predictOptions = append(predictOptions, llama.SetSeed(int(opts.Seed)))
|
||||
}
|
||||
|
||||
//predictOptions = append(predictOptions, llama.SetLogitBias(c.Seed))
|
||||
|
||||
predictOptions = append(predictOptions, llama.SetFrequencyPenalty(opts.FrequencyPenalty))
|
||||
predictOptions = append(predictOptions, llama.SetMlock(opts.MLock))
|
||||
predictOptions = append(predictOptions, llama.SetMemoryMap(opts.MMap))
|
||||
predictOptions = append(predictOptions, llama.SetPredictionMainGPU(opts.MainGPU))
|
||||
predictOptions = append(predictOptions, llama.SetPredictionTensorSplit(opts.TensorSplit))
|
||||
predictOptions = append(predictOptions, llama.SetTailFreeSamplingZ(opts.TailFreeSamplingZ))
|
||||
predictOptions = append(predictOptions, llama.SetTypicalP(opts.TypicalP))
|
||||
return predictOptions
|
||||
}
|
||||
|
||||
func (llm *LLM) Predict(opts *pb.PredictOptions) (string, error) {
|
||||
return llm.llama.Predict(opts.Prompt, buildPredictOptions(opts)...)
|
||||
}
|
||||
|
||||
func (llm *LLM) PredictStream(opts *pb.PredictOptions, results chan string) error {
|
||||
predictOptions := buildPredictOptions(opts)
|
||||
|
||||
predictOptions = append(predictOptions, llama.SetTokenCallback(func(token string) bool {
|
||||
results <- token
|
||||
return true
|
||||
}))
|
||||
|
||||
go func() {
|
||||
_, err := llm.llama.Predict(opts.Prompt, predictOptions...)
|
||||
if err != nil {
|
||||
fmt.Println("err: ", err)
|
||||
}
|
||||
close(results)
|
||||
}()
|
||||
|
||||
return nil
|
||||
}
|
||||
|
||||
func (llm *LLM) Embeddings(opts *pb.PredictOptions) ([]float32, error) {
|
||||
predictOptions := buildPredictOptions(opts)
|
||||
|
||||
if len(opts.EmbeddingTokens) > 0 {
|
||||
tokens := []int{}
|
||||
for _, t := range opts.EmbeddingTokens {
|
||||
tokens = append(tokens, int(t))
|
||||
}
|
||||
return llm.llama.TokenEmbeddings(tokens, predictOptions...)
|
||||
}
|
||||
|
||||
return llm.llama.Embeddings(opts.Embeddings, predictOptions...)
|
||||
}
|
||||
19
backend/go/llm/llama-ggml/main.go
Normal file
19
backend/go/llm/llama-ggml/main.go
Normal file
@@ -0,0 +1,19 @@
|
||||
package main
|
||||
|
||||
import (
|
||||
"flag"
|
||||
|
||||
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, &LLM{}); err != nil {
|
||||
panic(err)
|
||||
}
|
||||
}
|
||||
257
backend/go/llm/llama/llama.go
Normal file
257
backend/go/llm/llama/llama.go
Normal file
@@ -0,0 +1,257 @@
|
||||
package main
|
||||
|
||||
// This is a wrapper to statisfy the GRPC service interface
|
||||
// It is meant to be used by the main executable that is the server for the specific backend type (falcon, gpt3, etc)
|
||||
import (
|
||||
"fmt"
|
||||
"path/filepath"
|
||||
|
||||
"github.com/go-skynet/LocalAI/pkg/grpc/base"
|
||||
pb "github.com/go-skynet/LocalAI/pkg/grpc/proto"
|
||||
"github.com/go-skynet/go-llama.cpp"
|
||||
)
|
||||
|
||||
type LLM struct {
|
||||
base.SingleThread
|
||||
|
||||
llama *llama.LLama
|
||||
draftModel *llama.LLama
|
||||
}
|
||||
|
||||
func (llm *LLM) Load(opts *pb.ModelOptions) error {
|
||||
ropeFreqBase := float32(10000)
|
||||
ropeFreqScale := float32(1)
|
||||
|
||||
if opts.RopeFreqBase != 0 {
|
||||
ropeFreqBase = opts.RopeFreqBase
|
||||
}
|
||||
if opts.RopeFreqScale != 0 {
|
||||
ropeFreqScale = opts.RopeFreqScale
|
||||
}
|
||||
|
||||
llamaOpts := []llama.ModelOption{
|
||||
llama.WithRopeFreqBase(ropeFreqBase),
|
||||
llama.WithRopeFreqScale(ropeFreqScale),
|
||||
}
|
||||
|
||||
if opts.NoMulMatQ {
|
||||
llamaOpts = append(llamaOpts, llama.SetMulMatQ(false))
|
||||
}
|
||||
|
||||
// Get base path of opts.ModelFile and use the same for lora (assume the same path)
|
||||
basePath := filepath.Dir(opts.ModelFile)
|
||||
|
||||
if opts.LoraAdapter != "" {
|
||||
llamaOpts = append(llamaOpts, llama.SetLoraAdapter(filepath.Join(basePath, opts.LoraAdapter)))
|
||||
}
|
||||
|
||||
if opts.LoraBase != "" {
|
||||
llamaOpts = append(llamaOpts, llama.SetLoraBase(filepath.Join(basePath, opts.LoraBase)))
|
||||
}
|
||||
|
||||
if opts.ContextSize != 0 {
|
||||
llamaOpts = append(llamaOpts, llama.SetContext(int(opts.ContextSize)))
|
||||
}
|
||||
if opts.F16Memory {
|
||||
llamaOpts = append(llamaOpts, llama.EnableF16Memory)
|
||||
}
|
||||
if opts.Embeddings {
|
||||
llamaOpts = append(llamaOpts, llama.EnableEmbeddings)
|
||||
}
|
||||
if opts.NGPULayers != 0 {
|
||||
llamaOpts = append(llamaOpts, llama.SetGPULayers(int(opts.NGPULayers)))
|
||||
}
|
||||
|
||||
llamaOpts = append(llamaOpts, llama.SetMMap(opts.MMap))
|
||||
llamaOpts = append(llamaOpts, llama.SetMainGPU(opts.MainGPU))
|
||||
llamaOpts = append(llamaOpts, llama.SetTensorSplit(opts.TensorSplit))
|
||||
if opts.NBatch != 0 {
|
||||
llamaOpts = append(llamaOpts, llama.SetNBatch(int(opts.NBatch)))
|
||||
} else {
|
||||
llamaOpts = append(llamaOpts, llama.SetNBatch(512))
|
||||
}
|
||||
|
||||
if opts.NUMA {
|
||||
llamaOpts = append(llamaOpts, llama.EnableNUMA)
|
||||
}
|
||||
|
||||
if opts.LowVRAM {
|
||||
llamaOpts = append(llamaOpts, llama.EnabelLowVRAM)
|
||||
}
|
||||
|
||||
if opts.DraftModel != "" {
|
||||
// https://github.com/ggerganov/llama.cpp/blob/71ca2fad7d6c0ef95ef9944fb3a1a843e481f314/examples/speculative/speculative.cpp#L40
|
||||
llamaOpts = append(llamaOpts, llama.SetPerplexity(true))
|
||||
}
|
||||
|
||||
model, err := llama.New(opts.ModelFile, llamaOpts...)
|
||||
|
||||
if opts.DraftModel != "" {
|
||||
// opts.DraftModel is relative to opts.ModelFile, so we need to get the basepath of opts.ModelFile
|
||||
if !filepath.IsAbs(opts.DraftModel) {
|
||||
dir := filepath.Dir(opts.ModelFile)
|
||||
opts.DraftModel = filepath.Join(dir, opts.DraftModel)
|
||||
}
|
||||
|
||||
draftModel, err := llama.New(opts.DraftModel, llamaOpts...)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
llm.draftModel = draftModel
|
||||
}
|
||||
|
||||
llm.llama = model
|
||||
|
||||
return err
|
||||
}
|
||||
|
||||
func buildPredictOptions(opts *pb.PredictOptions) []llama.PredictOption {
|
||||
ropeFreqBase := float32(10000)
|
||||
ropeFreqScale := float32(1)
|
||||
|
||||
if opts.RopeFreqBase != 0 {
|
||||
ropeFreqBase = opts.RopeFreqBase
|
||||
}
|
||||
if opts.RopeFreqScale != 0 {
|
||||
ropeFreqScale = opts.RopeFreqScale
|
||||
}
|
||||
predictOptions := []llama.PredictOption{
|
||||
llama.SetTemperature(opts.Temperature),
|
||||
llama.SetTopP(opts.TopP),
|
||||
llama.SetTopK(int(opts.TopK)),
|
||||
llama.SetTokens(int(opts.Tokens)),
|
||||
llama.SetThreads(int(opts.Threads)),
|
||||
llama.WithGrammar(opts.Grammar),
|
||||
llama.SetRopeFreqBase(ropeFreqBase),
|
||||
llama.SetRopeFreqScale(ropeFreqScale),
|
||||
llama.SetNegativePromptScale(opts.NegativePromptScale),
|
||||
llama.SetNegativePrompt(opts.NegativePrompt),
|
||||
}
|
||||
|
||||
if opts.PromptCacheAll {
|
||||
predictOptions = append(predictOptions, llama.EnablePromptCacheAll)
|
||||
}
|
||||
|
||||
if opts.PromptCacheRO {
|
||||
predictOptions = append(predictOptions, llama.EnablePromptCacheRO)
|
||||
}
|
||||
|
||||
// Expected absolute path
|
||||
if opts.PromptCachePath != "" {
|
||||
predictOptions = append(predictOptions, llama.SetPathPromptCache(opts.PromptCachePath))
|
||||
}
|
||||
|
||||
if opts.Mirostat != 0 {
|
||||
predictOptions = append(predictOptions, llama.SetMirostat(int(opts.Mirostat)))
|
||||
}
|
||||
|
||||
if opts.MirostatETA != 0 {
|
||||
predictOptions = append(predictOptions, llama.SetMirostatETA(opts.MirostatETA))
|
||||
}
|
||||
|
||||
if opts.MirostatTAU != 0 {
|
||||
predictOptions = append(predictOptions, llama.SetMirostatTAU(opts.MirostatTAU))
|
||||
}
|
||||
|
||||
if opts.Debug {
|
||||
predictOptions = append(predictOptions, llama.Debug)
|
||||
}
|
||||
|
||||
predictOptions = append(predictOptions, llama.SetStopWords(opts.StopPrompts...))
|
||||
|
||||
if opts.PresencePenalty != 0 {
|
||||
predictOptions = append(predictOptions, llama.SetPenalty(opts.PresencePenalty))
|
||||
}
|
||||
|
||||
if opts.NKeep != 0 {
|
||||
predictOptions = append(predictOptions, llama.SetNKeep(int(opts.NKeep)))
|
||||
}
|
||||
|
||||
if opts.Batch != 0 {
|
||||
predictOptions = append(predictOptions, llama.SetBatch(int(opts.Batch)))
|
||||
}
|
||||
|
||||
if opts.F16KV {
|
||||
predictOptions = append(predictOptions, llama.EnableF16KV)
|
||||
}
|
||||
|
||||
if opts.IgnoreEOS {
|
||||
predictOptions = append(predictOptions, llama.IgnoreEOS)
|
||||
}
|
||||
|
||||
if opts.Seed != 0 {
|
||||
predictOptions = append(predictOptions, llama.SetSeed(int(opts.Seed)))
|
||||
}
|
||||
|
||||
if opts.NDraft != 0 {
|
||||
predictOptions = append(predictOptions, llama.SetNDraft(int(opts.NDraft)))
|
||||
}
|
||||
//predictOptions = append(predictOptions, llama.SetLogitBias(c.Seed))
|
||||
|
||||
predictOptions = append(predictOptions, llama.SetFrequencyPenalty(opts.FrequencyPenalty))
|
||||
predictOptions = append(predictOptions, llama.SetMlock(opts.MLock))
|
||||
predictOptions = append(predictOptions, llama.SetMemoryMap(opts.MMap))
|
||||
predictOptions = append(predictOptions, llama.SetPredictionMainGPU(opts.MainGPU))
|
||||
predictOptions = append(predictOptions, llama.SetPredictionTensorSplit(opts.TensorSplit))
|
||||
predictOptions = append(predictOptions, llama.SetTailFreeSamplingZ(opts.TailFreeSamplingZ))
|
||||
predictOptions = append(predictOptions, llama.SetTypicalP(opts.TypicalP))
|
||||
return predictOptions
|
||||
}
|
||||
|
||||
func (llm *LLM) Predict(opts *pb.PredictOptions) (string, error) {
|
||||
if llm.draftModel != nil {
|
||||
return llm.llama.SpeculativeSampling(llm.draftModel, opts.Prompt, buildPredictOptions(opts)...)
|
||||
}
|
||||
return llm.llama.Predict(opts.Prompt, buildPredictOptions(opts)...)
|
||||
}
|
||||
|
||||
func (llm *LLM) PredictStream(opts *pb.PredictOptions, results chan string) error {
|
||||
predictOptions := buildPredictOptions(opts)
|
||||
|
||||
predictOptions = append(predictOptions, llama.SetTokenCallback(func(token string) bool {
|
||||
results <- token
|
||||
return true
|
||||
}))
|
||||
|
||||
go func() {
|
||||
var err error
|
||||
if llm.draftModel != nil {
|
||||
_, err = llm.llama.SpeculativeSampling(llm.draftModel, opts.Prompt, buildPredictOptions(opts)...)
|
||||
} else {
|
||||
_, err = llm.llama.Predict(opts.Prompt, predictOptions...)
|
||||
}
|
||||
|
||||
if err != nil {
|
||||
fmt.Println("err: ", err)
|
||||
}
|
||||
close(results)
|
||||
}()
|
||||
|
||||
return nil
|
||||
}
|
||||
|
||||
func (llm *LLM) Embeddings(opts *pb.PredictOptions) ([]float32, error) {
|
||||
predictOptions := buildPredictOptions(opts)
|
||||
|
||||
if len(opts.EmbeddingTokens) > 0 {
|
||||
tokens := []int{}
|
||||
for _, t := range opts.EmbeddingTokens {
|
||||
tokens = append(tokens, int(t))
|
||||
}
|
||||
return llm.llama.TokenEmbeddings(tokens, predictOptions...)
|
||||
}
|
||||
|
||||
return llm.llama.Embeddings(opts.Embeddings, predictOptions...)
|
||||
}
|
||||
|
||||
func (llm *LLM) TokenizeString(opts *pb.PredictOptions) (pb.TokenizationResponse, error) {
|
||||
predictOptions := buildPredictOptions(opts)
|
||||
l, tokens, err := llm.llama.TokenizeString(opts.Prompt, predictOptions...)
|
||||
if err != nil {
|
||||
return pb.TokenizationResponse{}, err
|
||||
}
|
||||
return pb.TokenizationResponse{
|
||||
Length: l,
|
||||
Tokens: tokens,
|
||||
}, nil
|
||||
}
|
||||
23
backend/go/llm/llama/main.go
Normal file
23
backend/go/llm/llama/main.go
Normal file
@@ -0,0 +1,23 @@
|
||||
package main
|
||||
|
||||
// GRPC Falcon server
|
||||
|
||||
// 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"
|
||||
)
|
||||
|
||||
var (
|
||||
addr = flag.String("addr", "localhost:50051", "the address to connect to")
|
||||
)
|
||||
|
||||
func main() {
|
||||
flag.Parse()
|
||||
|
||||
if err := grpc.StartServer(*addr, &LLM{}); err != nil {
|
||||
panic(err)
|
||||
}
|
||||
}
|
||||
23
backend/go/llm/mpt/main.go
Normal file
23
backend/go/llm/mpt/main.go
Normal file
@@ -0,0 +1,23 @@
|
||||
package main
|
||||
|
||||
// Note: this is started internally by LocalAI and a server is allocated for each model
|
||||
|
||||
import (
|
||||
"flag"
|
||||
|
||||
transformers "github.com/go-skynet/LocalAI/backend/go/llm/transformers"
|
||||
|
||||
grpc "github.com/go-skynet/LocalAI/pkg/grpc"
|
||||
)
|
||||
|
||||
var (
|
||||
addr = flag.String("addr", "localhost:50051", "the address to connect to")
|
||||
)
|
||||
|
||||
func main() {
|
||||
flag.Parse()
|
||||
|
||||
if err := grpc.StartServer(*addr, &transformers.MPT{}); err != nil {
|
||||
panic(err)
|
||||
}
|
||||
}
|
||||
23
backend/go/llm/replit/main.go
Normal file
23
backend/go/llm/replit/main.go
Normal file
@@ -0,0 +1,23 @@
|
||||
package main
|
||||
|
||||
// Note: this is started internally by LocalAI and a server is allocated for each model
|
||||
|
||||
import (
|
||||
"flag"
|
||||
|
||||
transformers "github.com/go-skynet/LocalAI/backend/go/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)
|
||||
}
|
||||
}
|
||||
21
backend/go/llm/rwkv/main.go
Normal file
21
backend/go/llm/rwkv/main.go
Normal file
@@ -0,0 +1,21 @@
|
||||
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"
|
||||
)
|
||||
|
||||
var (
|
||||
addr = flag.String("addr", "localhost:50051", "the address to connect to")
|
||||
)
|
||||
|
||||
func main() {
|
||||
flag.Parse()
|
||||
|
||||
if err := grpc.StartServer(*addr, &LLM{}); err != nil {
|
||||
panic(err)
|
||||
}
|
||||
}
|
||||
95
backend/go/llm/rwkv/rwkv.go
Normal file
95
backend/go/llm/rwkv/rwkv.go
Normal file
@@ -0,0 +1,95 @@
|
||||
package main
|
||||
|
||||
// This is a wrapper to statisfy the GRPC service interface
|
||||
// It is meant to be used by the main executable that is the server for the specific backend type (falcon, gpt3, etc)
|
||||
import (
|
||||
"fmt"
|
||||
"path/filepath"
|
||||
|
||||
"github.com/donomii/go-rwkv.cpp"
|
||||
"github.com/go-skynet/LocalAI/pkg/grpc/base"
|
||||
pb "github.com/go-skynet/LocalAI/pkg/grpc/proto"
|
||||
)
|
||||
|
||||
const tokenizerSuffix = ".tokenizer.json"
|
||||
|
||||
type LLM struct {
|
||||
base.SingleThread
|
||||
|
||||
rwkv *rwkv.RwkvState
|
||||
}
|
||||
|
||||
func (llm *LLM) Load(opts *pb.ModelOptions) error {
|
||||
tokenizerFile := opts.Tokenizer
|
||||
if tokenizerFile == "" {
|
||||
modelFile := filepath.Base(opts.ModelFile)
|
||||
tokenizerFile = modelFile + tokenizerSuffix
|
||||
}
|
||||
modelPath := filepath.Dir(opts.ModelFile)
|
||||
tokenizerPath := filepath.Join(modelPath, tokenizerFile)
|
||||
|
||||
model := rwkv.LoadFiles(opts.ModelFile, tokenizerPath, uint32(opts.GetThreads()))
|
||||
|
||||
if model == nil {
|
||||
return fmt.Errorf("could not load model")
|
||||
}
|
||||
llm.rwkv = model
|
||||
return nil
|
||||
}
|
||||
|
||||
func (llm *LLM) Predict(opts *pb.PredictOptions) (string, error) {
|
||||
stopWord := "\n"
|
||||
if len(opts.StopPrompts) > 0 {
|
||||
stopWord = opts.StopPrompts[0]
|
||||
}
|
||||
|
||||
if err := llm.rwkv.ProcessInput(opts.Prompt); err != nil {
|
||||
return "", err
|
||||
}
|
||||
|
||||
response := llm.rwkv.GenerateResponse(int(opts.Tokens), stopWord, float32(opts.Temperature), float32(opts.TopP), nil)
|
||||
|
||||
return response, nil
|
||||
}
|
||||
|
||||
func (llm *LLM) PredictStream(opts *pb.PredictOptions, results chan string) error {
|
||||
go func() {
|
||||
|
||||
stopWord := "\n"
|
||||
if len(opts.StopPrompts) > 0 {
|
||||
stopWord = opts.StopPrompts[0]
|
||||
}
|
||||
|
||||
if err := llm.rwkv.ProcessInput(opts.Prompt); err != nil {
|
||||
fmt.Println("Error processing input: ", err)
|
||||
return
|
||||
}
|
||||
|
||||
llm.rwkv.GenerateResponse(int(opts.Tokens), stopWord, float32(opts.Temperature), float32(opts.TopP), func(s string) bool {
|
||||
results <- s
|
||||
return true
|
||||
})
|
||||
close(results)
|
||||
}()
|
||||
|
||||
return nil
|
||||
}
|
||||
|
||||
func (llm *LLM) TokenizeString(opts *pb.PredictOptions) (pb.TokenizationResponse, error) {
|
||||
tokens, err := llm.rwkv.Tokenizer.Encode(opts.Prompt)
|
||||
if err != nil {
|
||||
return pb.TokenizationResponse{}, err
|
||||
}
|
||||
|
||||
l := len(tokens)
|
||||
i32Tokens := make([]int32, l)
|
||||
|
||||
for i, t := range tokens {
|
||||
i32Tokens[i] = int32(t.ID)
|
||||
}
|
||||
|
||||
return pb.TokenizationResponse{
|
||||
Length: int32(l),
|
||||
Tokens: i32Tokens,
|
||||
}, nil
|
||||
}
|
||||
23
backend/go/llm/starcoder/main.go
Normal file
23
backend/go/llm/starcoder/main.go
Normal file
@@ -0,0 +1,23 @@
|
||||
package main
|
||||
|
||||
// Note: this is started internally by LocalAI and a server is allocated for each model
|
||||
|
||||
import (
|
||||
"flag"
|
||||
|
||||
transformers "github.com/go-skynet/LocalAI/backend/go/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)
|
||||
}
|
||||
}
|
||||
44
backend/go/llm/transformers/dolly.go
Normal file
44
backend/go/llm/transformers/dolly.go
Normal file
@@ -0,0 +1,44 @@
|
||||
package transformers
|
||||
|
||||
// This is a wrapper to statisfy the GRPC service interface
|
||||
// It is meant to be used by the main executable that is the server for the specific backend type (falcon, gpt3, etc)
|
||||
import (
|
||||
"fmt"
|
||||
|
||||
"github.com/go-skynet/LocalAI/pkg/grpc/base"
|
||||
pb "github.com/go-skynet/LocalAI/pkg/grpc/proto"
|
||||
|
||||
transformers "github.com/go-skynet/go-ggml-transformers.cpp"
|
||||
)
|
||||
|
||||
type Dolly struct {
|
||||
base.SingleThread
|
||||
|
||||
dolly *transformers.Dolly
|
||||
}
|
||||
|
||||
func (llm *Dolly) Load(opts *pb.ModelOptions) error {
|
||||
model, err := transformers.NewDolly(opts.ModelFile)
|
||||
llm.dolly = model
|
||||
return err
|
||||
}
|
||||
|
||||
func (llm *Dolly) Predict(opts *pb.PredictOptions) (string, error) {
|
||||
return llm.dolly.Predict(opts.Prompt, buildPredictOptions(opts)...)
|
||||
}
|
||||
|
||||
// fallback to Predict
|
||||
func (llm *Dolly) PredictStream(opts *pb.PredictOptions, results chan string) error {
|
||||
|
||||
go func() {
|
||||
res, err := llm.dolly.Predict(opts.Prompt, buildPredictOptions(opts)...)
|
||||
|
||||
if err != nil {
|
||||
fmt.Println("err: ", err)
|
||||
}
|
||||
results <- res
|
||||
close(results)
|
||||
}()
|
||||
|
||||
return nil
|
||||
}
|
||||
43
backend/go/llm/transformers/falcon.go
Normal file
43
backend/go/llm/transformers/falcon.go
Normal file
@@ -0,0 +1,43 @@
|
||||
package transformers
|
||||
|
||||
// This is a wrapper to statisfy the GRPC service interface
|
||||
// It is meant to be used by the main executable that is the server for the specific backend type (falcon, gpt3, etc)
|
||||
import (
|
||||
"fmt"
|
||||
|
||||
"github.com/go-skynet/LocalAI/pkg/grpc/base"
|
||||
pb "github.com/go-skynet/LocalAI/pkg/grpc/proto"
|
||||
|
||||
transformers "github.com/go-skynet/go-ggml-transformers.cpp"
|
||||
)
|
||||
|
||||
type Falcon struct {
|
||||
base.SingleThread
|
||||
|
||||
falcon *transformers.Falcon
|
||||
}
|
||||
|
||||
func (llm *Falcon) Load(opts *pb.ModelOptions) error {
|
||||
model, err := transformers.NewFalcon(opts.ModelFile)
|
||||
llm.falcon = model
|
||||
return err
|
||||
}
|
||||
|
||||
func (llm *Falcon) Predict(opts *pb.PredictOptions) (string, error) {
|
||||
return llm.falcon.Predict(opts.Prompt, buildPredictOptions(opts)...)
|
||||
}
|
||||
|
||||
// fallback to Predict
|
||||
func (llm *Falcon) PredictStream(opts *pb.PredictOptions, results chan string) error {
|
||||
go func() {
|
||||
res, err := llm.falcon.Predict(opts.Prompt, buildPredictOptions(opts)...)
|
||||
|
||||
if err != nil {
|
||||
fmt.Println("err: ", err)
|
||||
}
|
||||
results <- res
|
||||
close(results)
|
||||
}()
|
||||
|
||||
return nil
|
||||
}
|
||||
42
backend/go/llm/transformers/gpt2.go
Normal file
42
backend/go/llm/transformers/gpt2.go
Normal file
@@ -0,0 +1,42 @@
|
||||
package transformers
|
||||
|
||||
// This is a wrapper to statisfy the GRPC service interface
|
||||
// It is meant to be used by the main executable that is the server for the specific backend type (falcon, gpt3, etc)
|
||||
import (
|
||||
"fmt"
|
||||
|
||||
"github.com/go-skynet/LocalAI/pkg/grpc/base"
|
||||
pb "github.com/go-skynet/LocalAI/pkg/grpc/proto"
|
||||
|
||||
transformers "github.com/go-skynet/go-ggml-transformers.cpp"
|
||||
)
|
||||
|
||||
type GPT2 struct {
|
||||
base.SingleThread
|
||||
|
||||
gpt2 *transformers.GPT2
|
||||
}
|
||||
|
||||
func (llm *GPT2) Load(opts *pb.ModelOptions) error {
|
||||
model, err := transformers.New(opts.ModelFile)
|
||||
llm.gpt2 = model
|
||||
return err
|
||||
}
|
||||
|
||||
func (llm *GPT2) Predict(opts *pb.PredictOptions) (string, error) {
|
||||
return llm.gpt2.Predict(opts.Prompt, buildPredictOptions(opts)...)
|
||||
}
|
||||
|
||||
// fallback to Predict
|
||||
func (llm *GPT2) PredictStream(opts *pb.PredictOptions, results chan string) error {
|
||||
go func() {
|
||||
res, err := llm.gpt2.Predict(opts.Prompt, buildPredictOptions(opts)...)
|
||||
|
||||
if err != nil {
|
||||
fmt.Println("err: ", err)
|
||||
}
|
||||
results <- res
|
||||
close(results)
|
||||
}()
|
||||
return nil
|
||||
}
|
||||
42
backend/go/llm/transformers/gptj.go
Normal file
42
backend/go/llm/transformers/gptj.go
Normal file
@@ -0,0 +1,42 @@
|
||||
package transformers
|
||||
|
||||
// This is a wrapper to statisfy the GRPC service interface
|
||||
// It is meant to be used by the main executable that is the server for the specific backend type (falcon, gpt3, etc)
|
||||
import (
|
||||
"fmt"
|
||||
|
||||
"github.com/go-skynet/LocalAI/pkg/grpc/base"
|
||||
pb "github.com/go-skynet/LocalAI/pkg/grpc/proto"
|
||||
|
||||
transformers "github.com/go-skynet/go-ggml-transformers.cpp"
|
||||
)
|
||||
|
||||
type GPTJ struct {
|
||||
base.SingleThread
|
||||
|
||||
gptj *transformers.GPTJ
|
||||
}
|
||||
|
||||
func (llm *GPTJ) Load(opts *pb.ModelOptions) error {
|
||||
model, err := transformers.NewGPTJ(opts.ModelFile)
|
||||
llm.gptj = model
|
||||
return err
|
||||
}
|
||||
|
||||
func (llm *GPTJ) Predict(opts *pb.PredictOptions) (string, error) {
|
||||
return llm.gptj.Predict(opts.Prompt, buildPredictOptions(opts)...)
|
||||
}
|
||||
|
||||
// fallback to Predict
|
||||
func (llm *GPTJ) PredictStream(opts *pb.PredictOptions, results chan string) error {
|
||||
go func() {
|
||||
res, err := llm.gptj.Predict(opts.Prompt, buildPredictOptions(opts)...)
|
||||
|
||||
if err != nil {
|
||||
fmt.Println("err: ", err)
|
||||
}
|
||||
results <- res
|
||||
close(results)
|
||||
}()
|
||||
return nil
|
||||
}
|
||||
42
backend/go/llm/transformers/gptneox.go
Normal file
42
backend/go/llm/transformers/gptneox.go
Normal file
@@ -0,0 +1,42 @@
|
||||
package transformers
|
||||
|
||||
// This is a wrapper to statisfy the GRPC service interface
|
||||
// It is meant to be used by the main executable that is the server for the specific backend type (falcon, gpt3, etc)
|
||||
import (
|
||||
"fmt"
|
||||
|
||||
"github.com/go-skynet/LocalAI/pkg/grpc/base"
|
||||
pb "github.com/go-skynet/LocalAI/pkg/grpc/proto"
|
||||
|
||||
transformers "github.com/go-skynet/go-ggml-transformers.cpp"
|
||||
)
|
||||
|
||||
type GPTNeoX struct {
|
||||
base.SingleThread
|
||||
|
||||
gptneox *transformers.GPTNeoX
|
||||
}
|
||||
|
||||
func (llm *GPTNeoX) Load(opts *pb.ModelOptions) error {
|
||||
model, err := transformers.NewGPTNeoX(opts.ModelFile)
|
||||
llm.gptneox = model
|
||||
return err
|
||||
}
|
||||
|
||||
func (llm *GPTNeoX) Predict(opts *pb.PredictOptions) (string, error) {
|
||||
return llm.gptneox.Predict(opts.Prompt, buildPredictOptions(opts)...)
|
||||
}
|
||||
|
||||
// fallback to Predict
|
||||
func (llm *GPTNeoX) PredictStream(opts *pb.PredictOptions, results chan string) error {
|
||||
go func() {
|
||||
res, err := llm.gptneox.Predict(opts.Prompt, buildPredictOptions(opts)...)
|
||||
|
||||
if err != nil {
|
||||
fmt.Println("err: ", err)
|
||||
}
|
||||
results <- res
|
||||
close(results)
|
||||
}()
|
||||
return nil
|
||||
}
|
||||
42
backend/go/llm/transformers/mpt.go
Normal file
42
backend/go/llm/transformers/mpt.go
Normal file
@@ -0,0 +1,42 @@
|
||||
package transformers
|
||||
|
||||
// This is a wrapper to statisfy the GRPC service interface
|
||||
// It is meant to be used by the main executable that is the server for the specific backend type (falcon, gpt3, etc)
|
||||
import (
|
||||
"fmt"
|
||||
|
||||
"github.com/go-skynet/LocalAI/pkg/grpc/base"
|
||||
pb "github.com/go-skynet/LocalAI/pkg/grpc/proto"
|
||||
|
||||
transformers "github.com/go-skynet/go-ggml-transformers.cpp"
|
||||
)
|
||||
|
||||
type MPT struct {
|
||||
base.SingleThread
|
||||
|
||||
mpt *transformers.MPT
|
||||
}
|
||||
|
||||
func (llm *MPT) Load(opts *pb.ModelOptions) error {
|
||||
model, err := transformers.NewMPT(opts.ModelFile)
|
||||
llm.mpt = model
|
||||
return err
|
||||
}
|
||||
|
||||
func (llm *MPT) Predict(opts *pb.PredictOptions) (string, error) {
|
||||
return llm.mpt.Predict(opts.Prompt, buildPredictOptions(opts)...)
|
||||
}
|
||||
|
||||
// fallback to Predict
|
||||
func (llm *MPT) PredictStream(opts *pb.PredictOptions, results chan string) error {
|
||||
go func() {
|
||||
res, err := llm.mpt.Predict(opts.Prompt, buildPredictOptions(opts)...)
|
||||
|
||||
if err != nil {
|
||||
fmt.Println("err: ", err)
|
||||
}
|
||||
results <- res
|
||||
close(results)
|
||||
}()
|
||||
return nil
|
||||
}
|
||||
26
backend/go/llm/transformers/predict.go
Normal file
26
backend/go/llm/transformers/predict.go
Normal file
@@ -0,0 +1,26 @@
|
||||
package transformers
|
||||
|
||||
import (
|
||||
pb "github.com/go-skynet/LocalAI/pkg/grpc/proto"
|
||||
transformers "github.com/go-skynet/go-ggml-transformers.cpp"
|
||||
)
|
||||
|
||||
func buildPredictOptions(opts *pb.PredictOptions) []transformers.PredictOption {
|
||||
predictOptions := []transformers.PredictOption{
|
||||
transformers.SetTemperature(float64(opts.Temperature)),
|
||||
transformers.SetTopP(float64(opts.TopP)),
|
||||
transformers.SetTopK(int(opts.TopK)),
|
||||
transformers.SetTokens(int(opts.Tokens)),
|
||||
transformers.SetThreads(int(opts.Threads)),
|
||||
}
|
||||
|
||||
if opts.Batch != 0 {
|
||||
predictOptions = append(predictOptions, transformers.SetBatch(int(opts.Batch)))
|
||||
}
|
||||
|
||||
if opts.Seed != 0 {
|
||||
predictOptions = append(predictOptions, transformers.SetSeed(int(opts.Seed)))
|
||||
}
|
||||
|
||||
return predictOptions
|
||||
}
|
||||
42
backend/go/llm/transformers/replit.go
Normal file
42
backend/go/llm/transformers/replit.go
Normal file
@@ -0,0 +1,42 @@
|
||||
package transformers
|
||||
|
||||
// This is a wrapper to statisfy the GRPC service interface
|
||||
// It is meant to be used by the main executable that is the server for the specific backend type (falcon, gpt3, etc)
|
||||
import (
|
||||
"fmt"
|
||||
|
||||
"github.com/go-skynet/LocalAI/pkg/grpc/base"
|
||||
pb "github.com/go-skynet/LocalAI/pkg/grpc/proto"
|
||||
|
||||
transformers "github.com/go-skynet/go-ggml-transformers.cpp"
|
||||
)
|
||||
|
||||
type Replit struct {
|
||||
base.SingleThread
|
||||
|
||||
replit *transformers.Replit
|
||||
}
|
||||
|
||||
func (llm *Replit) Load(opts *pb.ModelOptions) error {
|
||||
model, err := transformers.NewReplit(opts.ModelFile)
|
||||
llm.replit = model
|
||||
return err
|
||||
}
|
||||
|
||||
func (llm *Replit) Predict(opts *pb.PredictOptions) (string, error) {
|
||||
return llm.replit.Predict(opts.Prompt, buildPredictOptions(opts)...)
|
||||
}
|
||||
|
||||
// fallback to Predict
|
||||
func (llm *Replit) PredictStream(opts *pb.PredictOptions, results chan string) error {
|
||||
go func() {
|
||||
res, err := llm.replit.Predict(opts.Prompt, buildPredictOptions(opts)...)
|
||||
|
||||
if err != nil {
|
||||
fmt.Println("err: ", err)
|
||||
}
|
||||
results <- res
|
||||
close(results)
|
||||
}()
|
||||
return nil
|
||||
}
|
||||
43
backend/go/llm/transformers/starcoder.go
Normal file
43
backend/go/llm/transformers/starcoder.go
Normal file
@@ -0,0 +1,43 @@
|
||||
package transformers
|
||||
|
||||
// This is a wrapper to statisfy the GRPC service interface
|
||||
// It is meant to be used by the main executable that is the server for the specific backend type (falcon, gpt3, etc)
|
||||
import (
|
||||
"fmt"
|
||||
|
||||
"github.com/go-skynet/LocalAI/pkg/grpc/base"
|
||||
pb "github.com/go-skynet/LocalAI/pkg/grpc/proto"
|
||||
|
||||
transformers "github.com/go-skynet/go-ggml-transformers.cpp"
|
||||
)
|
||||
|
||||
type Starcoder struct {
|
||||
base.SingleThread
|
||||
|
||||
starcoder *transformers.Starcoder
|
||||
}
|
||||
|
||||
func (llm *Starcoder) Load(opts *pb.ModelOptions) error {
|
||||
model, err := transformers.NewStarcoder(opts.ModelFile)
|
||||
llm.starcoder = model
|
||||
return err
|
||||
}
|
||||
|
||||
func (llm *Starcoder) Predict(opts *pb.PredictOptions) (string, error) {
|
||||
return llm.starcoder.Predict(opts.Prompt, buildPredictOptions(opts)...)
|
||||
}
|
||||
|
||||
// fallback to Predict
|
||||
func (llm *Starcoder) PredictStream(opts *pb.PredictOptions, results chan string) error {
|
||||
go func() {
|
||||
res, err := llm.starcoder.Predict(opts.Prompt, buildPredictOptions(opts)...)
|
||||
|
||||
if err != nil {
|
||||
fmt.Println("err: ", err)
|
||||
}
|
||||
results <- res
|
||||
close(results)
|
||||
}()
|
||||
|
||||
return nil
|
||||
}
|
||||
21
backend/go/transcribe/main.go
Normal file
21
backend/go/transcribe/main.go
Normal file
@@ -0,0 +1,21 @@
|
||||
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"
|
||||
)
|
||||
|
||||
var (
|
||||
addr = flag.String("addr", "localhost:50051", "the address to connect to")
|
||||
)
|
||||
|
||||
func main() {
|
||||
flag.Parse()
|
||||
|
||||
if err := grpc.StartServer(*addr, &Whisper{}); err != nil {
|
||||
panic(err)
|
||||
}
|
||||
}
|
||||
@@ -1,4 +1,4 @@
|
||||
package whisper
|
||||
package main
|
||||
|
||||
import (
|
||||
"fmt"
|
||||
@@ -7,7 +7,8 @@ import (
|
||||
"path/filepath"
|
||||
|
||||
"github.com/ggerganov/whisper.cpp/bindings/go/pkg/whisper"
|
||||
wav "github.com/go-audio/wav"
|
||||
"github.com/go-audio/wav"
|
||||
"github.com/go-skynet/LocalAI/api/schema"
|
||||
)
|
||||
|
||||
func sh(c string) (string, error) {
|
||||
@@ -28,24 +29,25 @@ func audioToWav(src, dst string) error {
|
||||
return nil
|
||||
}
|
||||
|
||||
func Transcript(model whisper.Model, audiopath, language string, threads uint) (string, error) {
|
||||
func Transcript(model whisper.Model, audiopath, language string, threads uint) (schema.Result, error) {
|
||||
res := schema.Result{}
|
||||
|
||||
dir, err := os.MkdirTemp("", "whisper")
|
||||
if err != nil {
|
||||
return "", err
|
||||
return res, err
|
||||
}
|
||||
defer os.RemoveAll(dir)
|
||||
|
||||
convertedPath := filepath.Join(dir, "converted.wav")
|
||||
|
||||
if err := audioToWav(audiopath, convertedPath); err != nil {
|
||||
return "", err
|
||||
return res, err
|
||||
}
|
||||
|
||||
// Open samples
|
||||
fh, err := os.Open(convertedPath)
|
||||
if err != nil {
|
||||
return "", err
|
||||
return res, err
|
||||
}
|
||||
defer fh.Close()
|
||||
|
||||
@@ -53,7 +55,7 @@ func Transcript(model whisper.Model, audiopath, language string, threads uint) (
|
||||
d := wav.NewDecoder(fh)
|
||||
buf, err := d.FullPCMBuffer()
|
||||
if err != nil {
|
||||
return "", err
|
||||
return res, err
|
||||
}
|
||||
|
||||
data := buf.AsFloat32Buffer().Data
|
||||
@@ -61,7 +63,7 @@ func Transcript(model whisper.Model, audiopath, language string, threads uint) (
|
||||
// Process samples
|
||||
context, err := model.NewContext()
|
||||
if err != nil {
|
||||
return "", err
|
||||
return res, err
|
||||
|
||||
}
|
||||
|
||||
@@ -73,18 +75,26 @@ func Transcript(model whisper.Model, audiopath, language string, threads uint) (
|
||||
context.SetLanguage("auto")
|
||||
}
|
||||
|
||||
if err := context.Process(data, nil); err != nil {
|
||||
return "", err
|
||||
if err := context.Process(data, nil, nil); err != nil {
|
||||
return res, err
|
||||
}
|
||||
|
||||
text := ""
|
||||
for {
|
||||
segment, err := context.NextSegment()
|
||||
s, err := context.NextSegment()
|
||||
if err != nil {
|
||||
break
|
||||
}
|
||||
text += segment.Text
|
||||
|
||||
var tokens []int
|
||||
for _, t := range s.Tokens {
|
||||
tokens = append(tokens, t.Id)
|
||||
}
|
||||
|
||||
segment := schema.Segment{Id: s.Num, Text: s.Text, Start: s.Start, End: s.End, Tokens: tokens}
|
||||
res.Segments = append(res.Segments, segment)
|
||||
|
||||
res.Text += s.Text
|
||||
}
|
||||
|
||||
return text, nil
|
||||
return res, nil
|
||||
}
|
||||
26
backend/go/transcribe/whisper.go
Normal file
26
backend/go/transcribe/whisper.go
Normal file
@@ -0,0 +1,26 @@
|
||||
package main
|
||||
|
||||
// This is a wrapper to statisfy the GRPC service interface
|
||||
// It is meant to be used by the main executable that is the server for the specific backend type (falcon, gpt3, etc)
|
||||
import (
|
||||
"github.com/ggerganov/whisper.cpp/bindings/go/pkg/whisper"
|
||||
"github.com/go-skynet/LocalAI/api/schema"
|
||||
"github.com/go-skynet/LocalAI/pkg/grpc/base"
|
||||
pb "github.com/go-skynet/LocalAI/pkg/grpc/proto"
|
||||
)
|
||||
|
||||
type Whisper struct {
|
||||
base.SingleThread
|
||||
whisper whisper.Model
|
||||
}
|
||||
|
||||
func (sd *Whisper) Load(opts *pb.ModelOptions) error {
|
||||
// Note: the Model here is a path to a directory containing the model files
|
||||
w, err := whisper.New(opts.ModelFile)
|
||||
sd.whisper = w
|
||||
return err
|
||||
}
|
||||
|
||||
func (sd *Whisper) AudioTranscription(opts *pb.TranscriptRequest) (schema.Result, error) {
|
||||
return Transcript(sd.whisper, opts.Dst, opts.Language, uint(opts.Threads))
|
||||
}
|
||||
21
backend/go/tts/main.go
Normal file
21
backend/go/tts/main.go
Normal file
@@ -0,0 +1,21 @@
|
||||
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"
|
||||
)
|
||||
|
||||
var (
|
||||
addr = flag.String("addr", "localhost:50051", "the address to connect to")
|
||||
)
|
||||
|
||||
func main() {
|
||||
flag.Parse()
|
||||
|
||||
if err := grpc.StartServer(*addr, &Piper{}); err != nil {
|
||||
panic(err)
|
||||
}
|
||||
}
|
||||
49
backend/go/tts/piper.go
Normal file
49
backend/go/tts/piper.go
Normal file
@@ -0,0 +1,49 @@
|
||||
package main
|
||||
|
||||
// This is a wrapper to statisfy the GRPC service interface
|
||||
// It is meant to be used by the main executable that is the server for the specific backend type (falcon, gpt3, etc)
|
||||
import (
|
||||
"fmt"
|
||||
"os"
|
||||
"path/filepath"
|
||||
|
||||
"github.com/go-skynet/LocalAI/pkg/grpc/base"
|
||||
pb "github.com/go-skynet/LocalAI/pkg/grpc/proto"
|
||||
piper "github.com/mudler/go-piper"
|
||||
)
|
||||
|
||||
type Piper struct {
|
||||
base.SingleThread
|
||||
piper *PiperB
|
||||
}
|
||||
|
||||
func (sd *Piper) Load(opts *pb.ModelOptions) error {
|
||||
if filepath.Ext(opts.ModelFile) != ".onnx" {
|
||||
return fmt.Errorf("unsupported model type %s (should end with .onnx)", opts.ModelFile)
|
||||
}
|
||||
var err error
|
||||
// Note: the Model here is a path to a directory containing the model files
|
||||
sd.piper, err = New(opts.LibrarySearchPath)
|
||||
return err
|
||||
}
|
||||
|
||||
func (sd *Piper) TTS(opts *pb.TTSRequest) error {
|
||||
return sd.piper.TTS(opts.Text, opts.Model, opts.Dst)
|
||||
}
|
||||
|
||||
type PiperB struct {
|
||||
assetDir string
|
||||
}
|
||||
|
||||
func New(assetDir string) (*PiperB, error) {
|
||||
if _, err := os.Stat(assetDir); err != nil {
|
||||
return nil, err
|
||||
}
|
||||
return &PiperB{
|
||||
assetDir: assetDir,
|
||||
}, nil
|
||||
}
|
||||
|
||||
func (s *PiperB) TTS(text, model, dst string) error {
|
||||
return piper.TextToWav(text, model, s.assetDir, "", dst)
|
||||
}
|
||||
38
backend/python/README.md
Normal file
38
backend/python/README.md
Normal file
@@ -0,0 +1,38 @@
|
||||
# Common commands about conda environment
|
||||
|
||||
## Create a new empty conda environment
|
||||
|
||||
```
|
||||
conda create --name <env-name> python=<your version> -y
|
||||
|
||||
conda create --name autogptq python=3.11 -y
|
||||
```
|
||||
|
||||
## To activate the environment
|
||||
|
||||
As of conda 4.4
|
||||
```
|
||||
conda activate autogptq
|
||||
```
|
||||
|
||||
The conda version older than 4.4
|
||||
|
||||
```
|
||||
source activate autogptq
|
||||
```
|
||||
|
||||
## Install the packages to your environment
|
||||
|
||||
Sometimes you need to install the packages from the conda-forge channel
|
||||
|
||||
By using `conda`
|
||||
```
|
||||
conda install <your-package-name>
|
||||
|
||||
conda install -c conda-forge <your package-name>
|
||||
```
|
||||
|
||||
Or by using `pip`
|
||||
```
|
||||
pip install <your-package-name>
|
||||
```
|
||||
5
backend/python/autogptq/Makefile
Normal file
5
backend/python/autogptq/Makefile
Normal file
@@ -0,0 +1,5 @@
|
||||
.PHONY: autogptq
|
||||
autogptq:
|
||||
@echo "Creating virtual environment..."
|
||||
@conda env create --name autogptq --file autogptq.yml
|
||||
@echo "Virtual environment created."
|
||||
Some files were not shown because too many files have changed in this diff Show More
Reference in New Issue
Block a user