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319 Commits
v1.20.0
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@@ -1,4 +1,3 @@
|
||||
.git
|
||||
.idea
|
||||
models
|
||||
examples/chatbot-ui/models
|
||||
|
||||
30
.env
30
.env
@@ -23,11 +23,20 @@ MODELS_PATH=/models
|
||||
## Enable debug mode
|
||||
# DEBUG=true
|
||||
|
||||
## 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 go tags, available: stablediffusion, tts
|
||||
## stablediffusion: image generation with stablediffusion
|
||||
@@ -41,3 +50,20 @@ MODELS_PATH=/models
|
||||
|
||||
## Specify a default upload limit in MB (whisper)
|
||||
# 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
|
||||
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.
|
||||
-->
|
||||
9
.github/workflows/bump_deps.yaml
vendored
9
.github/workflows/bump_deps.yaml
vendored
@@ -30,6 +30,15 @@ jobs:
|
||||
- repository: "nomic-ai/gpt4all"
|
||||
variable: "GPT4ALL_VERSION"
|
||||
branch: "main"
|
||||
- repository: "mudler/go-ggllm.cpp"
|
||||
variable: "GOGGLLM_VERSION"
|
||||
branch: "master"
|
||||
- repository: "mudler/go-stable-diffusion"
|
||||
variable: "STABLEDIFFUSION_VERSION"
|
||||
branch: "master"
|
||||
- repository: "mudler/go-piper"
|
||||
variable: "PIPER_VERSION"
|
||||
branch: "master"
|
||||
runs-on: ubuntu-latest
|
||||
steps:
|
||||
- uses: actions/checkout@v3
|
||||
|
||||
38
.github/workflows/image.yml
vendored
38
.github/workflows/image.yml
vendored
@@ -59,12 +59,44 @@ jobs:
|
||||
|
||||
runs-on: ubuntu-latest
|
||||
steps:
|
||||
- name: Release space from worker
|
||||
run: |
|
||||
echo "Listing top largest packages"
|
||||
pkgs=$(dpkg-query -Wf '${Installed-Size}\t${Package}\t${Status}\n' | awk '$NF == "installed"{print $1 "\t" $2}' | sort -nr)
|
||||
head -n 30 <<< "${pkgs}"
|
||||
echo
|
||||
df -h
|
||||
echo
|
||||
sudo apt-get remove -y '^llvm-.*|^libllvm.*' || true
|
||||
sudo apt-get remove --auto-remove android-sdk-platform-tools || true
|
||||
sudo apt-get purge --auto-remove android-sdk-platform-tools || true
|
||||
sudo rm -rf /usr/local/lib/android
|
||||
sudo apt-get remove -y '^dotnet-.*|^aspnetcore-.*' || true
|
||||
sudo rm -rf /usr/share/dotnet
|
||||
sudo apt-get remove -y '^mono-.*' || true
|
||||
sudo apt-get remove -y '^ghc-.*' || true
|
||||
sudo apt-get remove -y '.*jdk.*|.*jre.*' || true
|
||||
sudo apt-get remove -y 'php.*' || true
|
||||
sudo apt-get remove -y hhvm powershell firefox monodoc-manual msbuild || true
|
||||
sudo apt-get remove -y '^google-.*' || true
|
||||
sudo apt-get remove -y azure-cli || true
|
||||
sudo apt-get remove -y '^mongo.*-.*|^postgresql-.*|^mysql-.*|^mssql-.*' || true
|
||||
sudo apt-get remove -y '^gfortran-.*' || true
|
||||
sudo apt-get autoremove -y
|
||||
sudo apt-get clean
|
||||
echo
|
||||
echo "Listing top largest packages"
|
||||
pkgs=$(dpkg-query -Wf '${Installed-Size}\t${Package}\t${Status}\n' | awk '$NF == "installed"{print $1 "\t" $2}' | sort -nr)
|
||||
head -n 30 <<< "${pkgs}"
|
||||
echo
|
||||
sudo rm -rfv build || true
|
||||
df -h
|
||||
- name: Checkout
|
||||
uses: actions/checkout@v3
|
||||
|
||||
- name: Docker meta
|
||||
id: meta
|
||||
uses: docker/metadata-action@v4
|
||||
uses: docker/metadata-action@v5
|
||||
with:
|
||||
images: quay.io/go-skynet/local-ai
|
||||
tags: |
|
||||
@@ -86,14 +118,14 @@ jobs:
|
||||
|
||||
- name: Login to DockerHub
|
||||
if: github.event_name != 'pull_request'
|
||||
uses: docker/login-action@v2
|
||||
uses: docker/login-action@v3
|
||||
with:
|
||||
registry: quay.io
|
||||
username: ${{ secrets.LOCALAI_REGISTRY_USERNAME }}
|
||||
password: ${{ secrets.LOCALAI_REGISTRY_PASSWORD }}
|
||||
|
||||
- name: Build and push
|
||||
uses: docker/build-push-action@v4
|
||||
uses: docker/build-push-action@v5
|
||||
with:
|
||||
builder: ${{ steps.buildx.outputs.name }}
|
||||
build-args: |
|
||||
|
||||
6
.github/workflows/release.yaml
vendored
6
.github/workflows/release.yaml
vendored
@@ -22,6 +22,9 @@ jobs:
|
||||
uses: actions/checkout@v3
|
||||
with:
|
||||
submodules: true
|
||||
- uses: actions/setup-go@v4
|
||||
with:
|
||||
go-version: '>=1.21.0'
|
||||
- name: Dependencies
|
||||
run: |
|
||||
sudo apt-get update
|
||||
@@ -60,6 +63,9 @@ jobs:
|
||||
uses: actions/checkout@v3
|
||||
with:
|
||||
submodules: true
|
||||
- uses: actions/setup-go@v4
|
||||
with:
|
||||
go-version: '>=1.21.0'
|
||||
- name: Build
|
||||
id: build
|
||||
env:
|
||||
|
||||
77
.github/workflows/test.yml
vendored
77
.github/workflows/test.yml
vendored
@@ -16,29 +16,98 @@ concurrency:
|
||||
jobs:
|
||||
ubuntu-latest:
|
||||
runs-on: ubuntu-latest
|
||||
|
||||
strategy:
|
||||
matrix:
|
||||
go-version: ['1.21.x']
|
||||
steps:
|
||||
- name: Release space from worker
|
||||
run: |
|
||||
echo "Listing top largest packages"
|
||||
pkgs=$(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
|
||||
with:
|
||||
submodules: true
|
||||
- name: Setup Go ${{ matrix.go-version }}
|
||||
uses: actions/setup-go@v4
|
||||
with:
|
||||
go-version: ${{ matrix.go-version }}
|
||||
# You can test your matrix by printing the current Go version
|
||||
- name: Display Go version
|
||||
run: go version
|
||||
- name: Dependencies
|
||||
run: |
|
||||
sudo apt-get update
|
||||
sudo apt-get install build-essential ffmpeg
|
||||
|
||||
sudo apt-get install -y ca-certificates cmake curl patch
|
||||
sudo apt-get install -y libopencv-dev && sudo ln -s /usr/include/opencv4/opencv2 /usr/include/opencv2
|
||||
sudo pip install -r extra/requirements.txt
|
||||
|
||||
sudo mkdir /build && sudo chmod -R 777 /build && cd /build && \
|
||||
curl -L "https://github.com/gabime/spdlog/archive/refs/tags/v1.11.0.tar.gz" | \
|
||||
tar -xzvf - && \
|
||||
mkdir -p "spdlog-1.11.0/build" && \
|
||||
cd "spdlog-1.11.0/build" && \
|
||||
cmake .. && \
|
||||
make -j8 && \
|
||||
sudo cmake --install . --prefix /usr && mkdir -p "lib/Linux-$(uname -m)" && \
|
||||
cd /build && \
|
||||
mkdir -p "lib/Linux-$(uname -m)/piper_phonemize" && \
|
||||
curl -L "https://github.com/rhasspy/piper-phonemize/releases/download/v1.0.0/libpiper_phonemize-amd64.tar.gz" | \
|
||||
tar -C "lib/Linux-$(uname -m)/piper_phonemize" -xzvf - && ls -liah /build/lib/Linux-$(uname -m)/piper_phonemize/ && \
|
||||
sudo cp -rfv /build/lib/Linux-$(uname -m)/piper_phonemize/lib/. /usr/lib/ && \
|
||||
sudo ln -s /usr/lib/libpiper_phonemize.so /usr/lib/libpiper_phonemize.so.1 && \
|
||||
sudo cp -rfv /build/lib/Linux-$(uname -m)/piper_phonemize/include/. /usr/include/
|
||||
- name: Test
|
||||
run: |
|
||||
make test
|
||||
ESPEAK_DATA="/build/lib/Linux-$(uname -m)/piper_phonemize/lib/espeak-ng-data" GO_TAGS="tts stablediffusion" make test
|
||||
|
||||
macOS-latest:
|
||||
runs-on: macOS-latest
|
||||
|
||||
strategy:
|
||||
matrix:
|
||||
go-version: ['1.21.x']
|
||||
steps:
|
||||
- name: Clone
|
||||
uses: actions/checkout@v3
|
||||
with:
|
||||
submodules: true
|
||||
|
||||
- name: Setup Go ${{ matrix.go-version }}
|
||||
uses: actions/setup-go@v4
|
||||
with:
|
||||
go-version: ${{ matrix.go-version }}
|
||||
# You can test your matrix by printing the current Go version
|
||||
- name: Display Go version
|
||||
run: go version
|
||||
- name: Test
|
||||
run: |
|
||||
CMAKE_ARGS="-DLLAMA_F16C=OFF -DLLAMA_AVX512=OFF -DLLAMA_AVX2=OFF -DLLAMA_FMA=OFF" make test
|
||||
19
.gitignore
vendored
19
.gitignore
vendored
@@ -1,12 +1,21 @@
|
||||
# go-llama build artifacts
|
||||
go-llama
|
||||
gpt4all
|
||||
go-llama-stable
|
||||
/gpt4all
|
||||
go-stable-diffusion
|
||||
go-piper
|
||||
/go-bert
|
||||
go-ggllm
|
||||
/piper
|
||||
__pycache__/
|
||||
*.a
|
||||
get-sources
|
||||
|
||||
go-ggml-transformers
|
||||
go-gpt2
|
||||
go-rwkv
|
||||
whisper.cpp
|
||||
bloomz
|
||||
/bloomz
|
||||
go-bert
|
||||
|
||||
# LocalAI build binary
|
||||
@@ -14,6 +23,8 @@ 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 +39,5 @@ release/
|
||||
|
||||
# Generated during build
|
||||
backend-assets/
|
||||
|
||||
/ggml-metal.metal
|
||||
prepare
|
||||
/ggml-metal.metal
|
||||
|
||||
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)
|
||||
|
||||
---
|
||||
47
Dockerfile
47
Dockerfile
@@ -1,4 +1,4 @@
|
||||
ARG GO_VERSION=1.20-bullseye
|
||||
ARG GO_VERSION=1.21-bullseye
|
||||
|
||||
FROM golang:$GO_VERSION as requirements
|
||||
|
||||
@@ -11,10 +11,16 @@ ARG TARGETARCH
|
||||
ARG TARGETVARIANT
|
||||
|
||||
ENV BUILD_TYPE=${BUILD_TYPE}
|
||||
ENV EXTERNAL_GRPC_BACKENDS="huggingface-embeddings:/build/extra/grpc/huggingface/huggingface.py,autogptq:/build/extra/grpc/autogptq/autogptq.py,bark:/build/extra/grpc/bark/ttsbark.py,diffusers:/build/extra/grpc/diffusers/backend_diffusers.py,exllama:/build/extra/grpc/exllama/exllama.py,vall-e-x:/build/extra/grpc/vall-e-x/ttsvalle.py,vllm:/build/extra/grpc/vllm/backend_vllm.py"
|
||||
ENV GALLERIES='[{"name":"model-gallery", "url":"github:go-skynet/model-gallery/index.yaml"}, {"url": "github:go-skynet/model-gallery/huggingface.yaml","name":"huggingface"}]'
|
||||
ARG GO_TAGS="stablediffusion tts"
|
||||
|
||||
RUN apt-get update && \
|
||||
apt-get install -y ca-certificates cmake curl patch
|
||||
apt-get install -y ca-certificates cmake curl patch pip
|
||||
|
||||
# Use the variables in subsequent instructions
|
||||
RUN echo "Target Architecture: $TARGETARCH"
|
||||
RUN echo "Target Variant: $TARGETVARIANT"
|
||||
|
||||
# CuBLAS requirements
|
||||
RUN if [ "${BUILD_TYPE}" = "cublas" ]; then \
|
||||
@@ -24,10 +30,26 @@ 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}-${CUDA_MINOR_VERSION} \
|
||||
; fi
|
||||
ENV PATH /usr/local/cuda/bin:${PATH}
|
||||
|
||||
# Extras requirements
|
||||
COPY extra/requirements.txt /build/extra/requirements.txt
|
||||
ENV PATH="/root/.cargo/bin:${PATH}"
|
||||
RUN pip install --upgrade pip
|
||||
RUN curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh -s -- -y
|
||||
RUN if [ "${TARGETARCH}" = "amd64" ]; then \
|
||||
pip install git+https://github.com/suno-ai/bark.git diffusers invisible_watermark transformers accelerate safetensors;\
|
||||
fi
|
||||
RUN if [ "${BUILD_TYPE}" = "cublas" ] && [ "${TARGETARCH}" = "amd64" ]; then \
|
||||
pip install torch vllm && pip install auto-gptq https://github.com/jllllll/exllama/releases/download/0.0.10/exllama-0.0.10+cu${CUDA_MAJOR_VERSION}${CUDA_MINOR_VERSION}-cp39-cp39-linux_x86_64.whl;\
|
||||
fi
|
||||
RUN pip install -r /build/extra/requirements.txt && rm -rf /build/extra/requirements.txt
|
||||
|
||||
# Vall-e-X
|
||||
RUN git clone https://github.com/Plachtaa/VALL-E-X.git /usr/lib/vall-e-x && cd /usr/lib/vall-e-x && pip install -r requirements.txt
|
||||
|
||||
WORKDIR /build
|
||||
|
||||
# OpenBLAS requirements
|
||||
@@ -37,9 +59,6 @@ RUN apt-get install -y libopenblas-dev
|
||||
RUN apt-get install -y libopencv-dev && \
|
||||
ln -s /usr/include/opencv4/opencv2 /usr/include/opencv2
|
||||
|
||||
# Use the variables in subsequent instructions
|
||||
RUN echo "Target Architecture: $TARGETARCH"
|
||||
RUN echo "Target Variant: $TARGETVARIANT"
|
||||
|
||||
# piper requirements
|
||||
# Use pre-compiled Piper phonemization library (includes onnxruntime)
|
||||
@@ -58,8 +77,8 @@ RUN curl -L "https://github.com/gabime/spdlog/archive/refs/tags/v${SPDLOG_VERSIO
|
||||
mkdir -p "lib/Linux-$(uname -m)/piper_phonemize" && \
|
||||
curl -L "https://github.com/rhasspy/piper-phonemize/releases/download/v${PIPER_PHONEMIZE_VERSION}/libpiper_phonemize-${TARGETARCH:-$(go env GOARCH)}${TARGETVARIANT}.tar.gz" | \
|
||||
tar -C "lib/Linux-$(uname -m)/piper_phonemize" -xzvf - && ls -liah /build/lib/Linux-$(uname -m)/piper_phonemize/ && \
|
||||
cp -rfv /build/lib/Linux-$(uname -m)/piper_phonemize/lib/. /lib64/ && \
|
||||
cp -rfv /build/lib/Linux-$(uname -m)/piper_phonemize/lib/. /usr/lib/ && \
|
||||
ln -s /usr/lib/libpiper_phonemize.so /usr/lib/libpiper_phonemize.so.1 && \
|
||||
cp -rfv /build/lib/Linux-$(uname -m)/piper_phonemize/include/. /usr/include/
|
||||
# \
|
||||
# ; fi
|
||||
@@ -83,6 +102,8 @@ RUN make get-sources
|
||||
COPY go.mod .
|
||||
RUN make prepare
|
||||
COPY . .
|
||||
COPY .git .
|
||||
|
||||
RUN ESPEAK_DATA=/build/lib/Linux-$(uname -m)/piper_phonemize/lib/espeak-ng-data make build
|
||||
|
||||
###################################
|
||||
@@ -91,8 +112,11 @@ RUN ESPEAK_DATA=/build/lib/Linux-$(uname -m)/piper_phonemize/lib/espeak-ng-data
|
||||
FROM requirements
|
||||
|
||||
ARG FFMPEG
|
||||
ARG BUILD_TYPE
|
||||
ARG TARGETARCH
|
||||
|
||||
ENV REBUILD=true
|
||||
ENV BUILD_TYPE=${BUILD_TYPE}
|
||||
ENV REBUILD=false
|
||||
ENV HEALTHCHECK_ENDPOINT=http://localhost:8080/readyz
|
||||
|
||||
# Add FFmpeg
|
||||
@@ -110,6 +134,13 @@ COPY . .
|
||||
RUN make prepare-sources
|
||||
COPY --from=builder /build/local-ai ./
|
||||
|
||||
# Copy VALLE-X as it's not a real "lib"
|
||||
RUN cp -rfv /usr/lib/vall-e-x/* ./
|
||||
|
||||
# To resolve exllama import error
|
||||
RUN if [ "${BUILD_TYPE}" = "cublas" ] && [ "${TARGETARCH:-$(go env GOARCH)}" = "amd64" ]; then \
|
||||
cp -rfv /usr/local/lib/python3.9/dist-packages/exllama extra/grpc/exllama/;\
|
||||
fi
|
||||
# Define the health check command
|
||||
HEALTHCHECK --interval=1m --timeout=10m --retries=10 \
|
||||
CMD curl -f $HEALTHCHECK_ENDPOINT || exit 1
|
||||
|
||||
309
Makefile
309
Makefile
@@ -3,24 +3,49 @@ GOTEST=$(GOCMD) test
|
||||
GOVET=$(GOCMD) vet
|
||||
BINARY_NAME=local-ai
|
||||
|
||||
GOLLAMA_VERSION?=582753605210844a21871df05837bd3d4876b91f
|
||||
# llama.cpp versions
|
||||
GOLLAMA_VERSION?=1676dcd7a139b6cdfbaea5fd67f46dc25d9d8bcf
|
||||
|
||||
GOLLAMA_STABLE_VERSION?=50cee7712066d9e38306eccadcfbb44ea87df4b7
|
||||
|
||||
# gpt4all version
|
||||
GPT4ALL_REPO?=https://github.com/nomic-ai/gpt4all
|
||||
GPT4ALL_VERSION?=c1794597a7559d5616567e280b722231c624a57b
|
||||
GOGGMLTRANSFORMERS_VERSION?=8e31841dcddca16468c11b2e7809f279fa76a832
|
||||
GPT4ALL_VERSION?=27a8b020c36b0df8f8b82a252d261cda47cf44b8
|
||||
|
||||
# go-ggml-transformers version
|
||||
GOGGMLTRANSFORMERS_VERSION?=ffb09d7dd71e2cbc6c5d7d05357d230eea6f369a
|
||||
|
||||
# go-rwkv version
|
||||
RWKV_REPO?=https://github.com/donomii/go-rwkv.cpp
|
||||
RWKV_VERSION?=f5a8c45396741470583f59b916a2a7641e63bcd0
|
||||
WHISPER_CPP_VERSION?=72deb41eb26300f71c50febe29db8ffcce09256c
|
||||
BERT_VERSION?=6069103f54b9969c02e789d0fb12a23bd614285f
|
||||
RWKV_VERSION?=c898cd0f62df8f2a7830e53d1d513bef4f6f792b
|
||||
|
||||
# whisper.cpp version
|
||||
WHISPER_CPP_VERSION?=85ed71aaec8e0612a84c0b67804bde75aa75a273
|
||||
|
||||
# bert.cpp version
|
||||
BERT_VERSION?=6abe312cded14042f6b7c3cd8edf082713334a4d
|
||||
|
||||
# go-piper version
|
||||
PIPER_VERSION?=56b8a81b4760a6fbee1a82e62f007ae7e8f010a7
|
||||
|
||||
# go-bloomz version
|
||||
BLOOMZ_VERSION?=1834e77b83faafe912ad4092ccf7f77937349e2f
|
||||
|
||||
# stablediffusion version
|
||||
STABLEDIFFUSION_VERSION?=d89260f598afb809279bc72aa0107b4292587632
|
||||
|
||||
# Go-ggllm
|
||||
GOGGLLM_VERSION?=862477d16eefb0805261c19c9b0d053e3b2b684b
|
||||
|
||||
export BUILD_TYPE?=
|
||||
export STABLE_BUILD_TYPE?=$(BUILD_TYPE)
|
||||
export CMAKE_ARGS?=
|
||||
CGO_LDFLAGS?=
|
||||
CUDA_LIBPATH?=/usr/local/cuda/lib64/
|
||||
STABLEDIFFUSION_VERSION?=d89260f598afb809279bc72aa0107b4292587632
|
||||
GO_TAGS?=
|
||||
BUILD_ID?=git
|
||||
|
||||
VERSION?=$(shell git describe --always --tags --dirty || echo "dev" )
|
||||
VERSION?=$(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)"
|
||||
@@ -37,8 +62,17 @@ 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-piper:$(shell pwd)/go-llama:$(shell pwd)/go-stable-diffusion/:$(shell pwd)/gpt4all/gpt4all-bindings/golang/:$(shell pwd)/go-ggml-transformers:$(shell pwd)/go-rwkv:$(shell pwd)/whisper.cpp:$(shell pwd)/go-bert:$(shell pwd)/bloomz
|
||||
ifndef UNAME_S
|
||||
UNAME_S := $(shell uname -s)
|
||||
endif
|
||||
|
||||
ifeq ($(UNAME_S),Darwin)
|
||||
CGO_LDFLAGS += -lcblas -framework Accelerate
|
||||
ifneq ($(BUILD_TYPE),metal)
|
||||
# explicit disable metal if on Darwin and metal is disabled
|
||||
CMAKE_ARGS+=-DLLAMA_METAL=OFF
|
||||
endif
|
||||
endif
|
||||
|
||||
ifeq ($(BUILD_TYPE),openblas)
|
||||
CGO_LDFLAGS+=-lopenblas
|
||||
@@ -49,6 +83,18 @@ ifeq ($(BUILD_TYPE),cublas)
|
||||
export LLAMA_CUBLAS=1
|
||||
endif
|
||||
|
||||
ifeq ($(BUILD_TYPE),hipblas)
|
||||
ROCM_HOME ?= /opt/rocm
|
||||
export CXX=$(ROCM_HOME)/llvm/bin/clang++
|
||||
export CC=$(ROCM_HOME)/llvm/bin/clang
|
||||
# Llama-stable has no hipblas support, so override it here.
|
||||
export STABLE_BUILD_TYPE=
|
||||
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
|
||||
@@ -64,14 +110,18 @@ ifeq ($(STATIC),true)
|
||||
endif
|
||||
|
||||
ifeq ($(findstring stablediffusion,$(GO_TAGS)),stablediffusion)
|
||||
OPTIONAL_TARGETS+=go-stable-diffusion/libstablediffusion.a
|
||||
# OPTIONAL_TARGETS+=go-stable-diffusion/libstablediffusion.a
|
||||
OPTIONAL_GRPC+=backend-assets/grpc/stablediffusion
|
||||
endif
|
||||
|
||||
ifeq ($(findstring tts,$(GO_TAGS)),tts)
|
||||
OPTIONAL_TARGETS+=go-piper/libpiper_binding.a
|
||||
OPTIONAL_TARGETS+=backend-assets/espeak-ng-data
|
||||
# OPTIONAL_TARGETS+=go-piper/libpiper_binding.a
|
||||
# OPTIONAL_TARGETS+=backend-assets/espeak-ng-data
|
||||
OPTIONAL_GRPC+=backend-assets/grpc/piper
|
||||
endif
|
||||
|
||||
GRPC_BACKENDS?=backend-assets/grpc/langchain-huggingface backend-assets/grpc/falcon-ggml backend-assets/grpc/bert-embeddings backend-assets/grpc/falcon backend-assets/grpc/bloomz backend-assets/grpc/llama backend-assets/grpc/llama-stable backend-assets/grpc/gpt4all backend-assets/grpc/dolly backend-assets/grpc/gpt2 backend-assets/grpc/gptj backend-assets/grpc/gptneox backend-assets/grpc/mpt backend-assets/grpc/replit backend-assets/grpc/starcoder backend-assets/grpc/rwkv backend-assets/grpc/whisper $(OPTIONAL_GRPC)
|
||||
|
||||
.PHONY: all test build vendor
|
||||
|
||||
all: help
|
||||
@@ -80,20 +130,14 @@ all: help
|
||||
gpt4all:
|
||||
git clone --recurse-submodules $(GPT4ALL_REPO) gpt4all
|
||||
cd gpt4all && git checkout -b build $(GPT4ALL_VERSION) && git submodule update --init --recursive --depth 1
|
||||
# This is hackish, but needed as both go-llama and go-gpt4allj have their own version of ggml..
|
||||
@find ./gpt4all -type f -name "*.c" -exec sed -i'' -e 's/ggml_/ggml_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' {} +
|
||||
|
||||
## go-ggllm
|
||||
go-ggllm:
|
||||
git clone --recurse-submodules https://github.com/mudler/go-ggllm.cpp go-ggllm
|
||||
cd go-ggllm && git checkout -b build $(GOGGLLM_VERSION) && git submodule update --init --recursive --depth 1
|
||||
|
||||
go-ggllm/libggllm.a: go-ggllm
|
||||
$(MAKE) -C go-ggllm BUILD_TYPE=$(BUILD_TYPE) libggllm.a
|
||||
|
||||
## go-piper
|
||||
go-piper:
|
||||
@@ -104,9 +148,6 @@ go-piper:
|
||||
go-bert:
|
||||
git clone --recurse-submodules https://github.com/go-skynet/go-bert.cpp go-bert
|
||||
cd go-bert && git checkout -b build $(BERT_VERSION) && git submodule update --init --recursive --depth 1
|
||||
@find ./go-bert -type f -name "*.c" -exec sed -i'' -e 's/ggml_/ggml_bert_/g' {} +
|
||||
@find ./go-bert -type f -name "*.cpp" -exec sed -i'' -e 's/ggml_/ggml_bert_/g' {} +
|
||||
@find ./go-bert -type f -name "*.h" -exec sed -i'' -e 's/ggml_/ggml_bert_/g' {} +
|
||||
|
||||
## stable diffusion
|
||||
go-stable-diffusion:
|
||||
@@ -120,9 +161,6 @@ go-stable-diffusion/libstablediffusion.a:
|
||||
go-rwkv:
|
||||
git clone --recurse-submodules $(RWKV_REPO) go-rwkv
|
||||
cd go-rwkv && git checkout -b build $(RWKV_VERSION) && git submodule update --init --recursive --depth 1
|
||||
@find ./go-rwkv -type f -name "*.c" -exec sed -i'' -e 's/ggml_/ggml_rwkv_/g' {} +
|
||||
@find ./go-rwkv -type f -name "*.cpp" -exec sed -i'' -e 's/ggml_/ggml_rwkv_/g' {} +
|
||||
@find ./go-rwkv -type f -name "*.h" -exec sed -i'' -e 's/ggml_/ggml_rwkv_/g' {} +
|
||||
|
||||
go-rwkv/librwkv.a: go-rwkv
|
||||
cd go-rwkv && cd rwkv.cpp && cmake . -DRWKV_BUILD_SHARED_LIBRARY=OFF && cmake --build . && cp librwkv.a ..
|
||||
@@ -130,13 +168,7 @@ go-rwkv/librwkv.a: go-rwkv
|
||||
## 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' {} +
|
||||
cd bloomz && git checkout -b build $(BLOOMZ_VERSION) && git submodule update --init --recursive --depth 1
|
||||
|
||||
bloomz/libbloomz.a: bloomz
|
||||
cd bloomz && make libbloomz.a
|
||||
@@ -155,6 +187,7 @@ backend-assets/espeak-ng-data:
|
||||
ifdef ESPEAK_DATA
|
||||
@cp -rf $(ESPEAK_DATA)/. backend-assets/espeak-ng-data
|
||||
else
|
||||
@echo "ESPEAK_DATA not set, skipping tts. Note that this will break the tts functionality."
|
||||
@touch backend-assets/espeak-ng-data/keep
|
||||
endif
|
||||
|
||||
@@ -165,27 +198,13 @@ gpt4all/gpt4all-bindings/golang/libgpt4all.a: gpt4all
|
||||
go-ggml-transformers:
|
||||
git clone --recurse-submodules https://github.com/go-skynet/go-ggml-transformers.cpp go-ggml-transformers
|
||||
cd go-ggml-transformers && git checkout -b build $(GOGPT2_VERSION) && git submodule update --init --recursive --depth 1
|
||||
# This is hackish, but needed as both go-llama and go-gpt4allj have their own version of ggml..
|
||||
@find ./go-ggml-transformers -type f -name "*.c" -exec sed -i'' -e 's/ggml_/ggml_gpt2_/g' {} +
|
||||
@find ./go-ggml-transformers -type f -name "*.cpp" -exec sed -i'' -e 's/ggml_/ggml_gpt2_/g' {} +
|
||||
@find ./go-ggml-transformers -type f -name "*.h" -exec sed -i'' -e 's/ggml_/ggml_gpt2_/g' {} +
|
||||
@find ./go-ggml-transformers -type f -name "*.cpp" -exec sed -i'' -e 's/gpt_print_usage/gpt2_print_usage/g' {} +
|
||||
@find ./go-ggml-transformers -type f -name "*.h" -exec sed -i'' -e 's/gpt_print_usage/gpt2_print_usage/g' {} +
|
||||
@find ./go-ggml-transformers -type f -name "*.cpp" -exec sed -i'' -e 's/gpt_params_parse/gpt2_params_parse/g' {} +
|
||||
@find ./go-ggml-transformers -type f -name "*.h" -exec sed -i'' -e 's/gpt_params_parse/gpt2_params_parse/g' {} +
|
||||
@find ./go-ggml-transformers -type f -name "*.cpp" -exec sed -i'' -e 's/gpt_random_prompt/gpt2_random_prompt/g' {} +
|
||||
@find ./go-ggml-transformers -type f -name "*.h" -exec sed -i'' -e 's/gpt_random_prompt/gpt2_random_prompt/g' {} +
|
||||
@find ./go-ggml-transformers -type f -name "*.cpp" -exec sed -i'' -e 's/json_/json_gpt2_/g' {} +
|
||||
|
||||
go-ggml-transformers/libtransformers.a: go-ggml-transformers
|
||||
$(MAKE) -C go-ggml-transformers libtransformers.a
|
||||
$(MAKE) -C go-ggml-transformers BUILD_TYPE=$(BUILD_TYPE) libtransformers.a
|
||||
|
||||
whisper.cpp:
|
||||
git clone https://github.com/ggerganov/whisper.cpp.git
|
||||
cd whisper.cpp && git checkout -b build $(WHISPER_CPP_VERSION) && git submodule update --init --recursive --depth 1
|
||||
@find ./whisper.cpp -type f -name "*.c" -exec sed -i'' -e 's/ggml_/ggml_whisper_/g' {} +
|
||||
@find ./whisper.cpp -type f -name "*.cpp" -exec sed -i'' -e 's/ggml_/ggml_whisper_/g' {} +
|
||||
@find ./whisper.cpp -type f -name "*.h" -exec sed -i'' -e 's/ggml_/ggml_whisper_/g' {} +
|
||||
|
||||
whisper.cpp/libwhisper.a: whisper.cpp
|
||||
cd whisper.cpp && make libwhisper.a
|
||||
@@ -194,17 +213,23 @@ go-llama:
|
||||
git clone --recurse-submodules https://github.com/go-skynet/go-llama.cpp go-llama
|
||||
cd go-llama && git checkout -b build $(GOLLAMA_VERSION) && git submodule update --init --recursive --depth 1
|
||||
|
||||
go-llama-stable:
|
||||
git clone --recurse-submodules https://github.com/go-skynet/go-llama.cpp go-llama-stable
|
||||
cd go-llama-stable && git checkout -b build $(GOLLAMA_STABLE_VERSION) && git submodule update --init --recursive --depth 1
|
||||
|
||||
go-llama/libbinding.a: go-llama
|
||||
$(MAKE) -C go-llama BUILD_TYPE=$(BUILD_TYPE) libbinding.a
|
||||
|
||||
go-llama-stable/libbinding.a: go-llama-stable
|
||||
$(MAKE) -C go-llama-stable BUILD_TYPE=$(STABLE_BUILD_TYPE) libbinding.a
|
||||
|
||||
go-piper/libpiper_binding.a:
|
||||
$(MAKE) -C go-piper libpiper_binding.a example/main
|
||||
|
||||
get-sources: go-llama go-ggml-transformers gpt4all go-piper go-rwkv whisper.cpp go-bert bloomz go-stable-diffusion
|
||||
get-sources: go-llama go-llama-stable go-ggllm go-ggml-transformers gpt4all go-piper go-rwkv whisper.cpp go-bert bloomz go-stable-diffusion
|
||||
touch $@
|
||||
|
||||
replace:
|
||||
$(GOCMD) mod edit -replace github.com/go-skynet/go-llama.cpp=$(shell pwd)/go-llama
|
||||
$(GOCMD) mod edit -replace github.com/nomic-ai/gpt4all/gpt4all-bindings/golang=$(shell pwd)/gpt4all/gpt4all-bindings/golang
|
||||
$(GOCMD) mod edit -replace github.com/go-skynet/go-ggml-transformers.cpp=$(shell pwd)/go-ggml-transformers
|
||||
$(GOCMD) mod edit -replace github.com/donomii/go-rwkv.cpp=$(shell pwd)/go-rwkv
|
||||
@@ -213,13 +238,16 @@ replace:
|
||||
$(GOCMD) mod edit -replace github.com/go-skynet/bloomz.cpp=$(shell pwd)/bloomz
|
||||
$(GOCMD) mod edit -replace github.com/mudler/go-stable-diffusion=$(shell pwd)/go-stable-diffusion
|
||||
$(GOCMD) mod edit -replace github.com/mudler/go-piper=$(shell pwd)/go-piper
|
||||
$(GOCMD) mod edit -replace github.com/mudler/go-ggllm.cpp=$(shell pwd)/go-ggllm
|
||||
|
||||
prepare-sources: get-sources replace
|
||||
$(GOCMD) mod download
|
||||
|
||||
## GENERIC
|
||||
rebuild: ## Rebuilds the project
|
||||
$(GOCMD) clean -cache
|
||||
$(MAKE) -C go-llama clean
|
||||
$(MAKE) -C go-llama-stable clean
|
||||
$(MAKE) -C gpt4all/gpt4all-bindings/golang/ clean
|
||||
$(MAKE) -C go-ggml-transformers clean
|
||||
$(MAKE) -C go-rwkv clean
|
||||
@@ -228,14 +256,18 @@ rebuild: ## Rebuilds the project
|
||||
$(MAKE) -C go-bert clean
|
||||
$(MAKE) -C bloomz clean
|
||||
$(MAKE) -C go-piper clean
|
||||
$(MAKE) -C go-ggllm 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
|
||||
$(GOCMD) clean -cache
|
||||
rm -f prepare
|
||||
rm -rf ./go-llama
|
||||
rm -rf ./gpt4all
|
||||
rm -rf ./go-llama-stable
|
||||
rm -rf ./go-gpt2
|
||||
rm -rf ./go-stable-diffusion
|
||||
rm -rf ./go-ggml-transformers
|
||||
@@ -245,32 +277,27 @@ clean: ## Remove build related file
|
||||
rm -rf ./bloomz
|
||||
rm -rf ./whisper.cpp
|
||||
rm -rf ./go-piper
|
||||
rm -rf ./go-ggllm
|
||||
rm -rf $(BINARY_NAME)
|
||||
rm -rf release/
|
||||
|
||||
## Build:
|
||||
|
||||
build: prepare ## Build the project
|
||||
build: grpcs prepare ## Build the project
|
||||
$(info ${GREEN}I local-ai build info:${RESET})
|
||||
$(info ${GREEN}I BUILD_TYPE: ${YELLOW}$(BUILD_TYPE)${RESET})
|
||||
$(info ${GREEN}I GO_TAGS: ${YELLOW}$(GO_TAGS)${RESET})
|
||||
$(info ${GREEN}I LD_FLAGS: ${YELLOW}$(LD_FLAGS)${RESET})
|
||||
|
||||
CGO_LDFLAGS="$(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
|
||||
CGO_LDFLAGS="$(CGO_LDFLAGS)" $(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o $(BINARY_NAME) ./
|
||||
|
||||
dist: build
|
||||
mkdir -p release
|
||||
cp $(BINARY_NAME) release/$(BINARY_NAME)-$(BUILD_ID)-$(OS)-$(ARCH)
|
||||
|
||||
generic-build: ## Build the project using generic
|
||||
BUILD_TYPE="generic" $(MAKE) build
|
||||
|
||||
## Run
|
||||
run: prepare ## run local-ai
|
||||
CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=${C_INCLUDE_PATH} LIBRARY_PATH=${LIBRARY_PATH} $(GOCMD) run ./
|
||||
CGO_LDFLAGS="$(CGO_LDFLAGS)" $(GOCMD) run ./
|
||||
|
||||
test-models/testmodel:
|
||||
mkdir test-models
|
||||
@@ -283,12 +310,45 @@ test-models/testmodel:
|
||||
wget https://raw.githubusercontent.com/saharNooby/rwkv.cpp/5eb8f09c146ea8124633ab041d9ea0b1f1db4459/rwkv/20B_tokenizer.json -O test-models/rwkv.tokenizer.json
|
||||
cp tests/models_fixtures/* test-models
|
||||
|
||||
test: prepare test-models/testmodel
|
||||
cp -r backend-assets api
|
||||
prepare-test: grpcs
|
||||
cp -rf backend-assets api
|
||||
cp tests/models_fixtures/* test-models
|
||||
C_INCLUDE_PATH=${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 ./)/extra/grpc/huggingface/huggingface.py TEST_DIR=$(abspath ./)/test-dir/ FIXTURES=$(abspath ./)/tests/fixtures CONFIG_FILE=$(abspath ./)/test-models/config.yaml MODELS_PATH=$(abspath ./)/test-models \
|
||||
$(GOCMD) run github.com/onsi/ginkgo/v2/ginkgo --label-filter="!gpt4all && !llama && !llama-gguf" --flake-attempts 5 -v -r ./api ./pkg
|
||||
$(MAKE) test-gpt4all
|
||||
$(MAKE) test-llama
|
||||
$(MAKE) test-llama-gguf
|
||||
$(MAKE) test-tts
|
||||
$(MAKE) test-stablediffusion
|
||||
|
||||
test-gpt4all: prepare-test
|
||||
TEST_DIR=$(abspath ./)/test-dir/ FIXTURES=$(abspath ./)/tests/fixtures CONFIG_FILE=$(abspath ./)/test-models/config.yaml MODELS_PATH=$(abspath ./)/test-models \
|
||||
$(GOCMD) run github.com/onsi/ginkgo/v2/ginkgo --label-filter="gpt4all" --flake-attempts 5 -v -r ./api ./pkg
|
||||
|
||||
test-llama: prepare-test
|
||||
TEST_DIR=$(abspath ./)/test-dir/ FIXTURES=$(abspath ./)/tests/fixtures CONFIG_FILE=$(abspath ./)/test-models/config.yaml MODELS_PATH=$(abspath ./)/test-models \
|
||||
$(GOCMD) run github.com/onsi/ginkgo/v2/ginkgo --label-filter="llama" --flake-attempts 5 -v -r ./api ./pkg
|
||||
|
||||
test-llama-gguf: prepare-test
|
||||
TEST_DIR=$(abspath ./)/test-dir/ FIXTURES=$(abspath ./)/tests/fixtures CONFIG_FILE=$(abspath ./)/test-models/config.yaml MODELS_PATH=$(abspath ./)/test-models \
|
||||
$(GOCMD) run github.com/onsi/ginkgo/v2/ginkgo --label-filter="llama-gguf" --flake-attempts 5 -v -r ./api ./pkg
|
||||
|
||||
test-tts: prepare-test
|
||||
TEST_DIR=$(abspath ./)/test-dir/ FIXTURES=$(abspath ./)/tests/fixtures CONFIG_FILE=$(abspath ./)/test-models/config.yaml MODELS_PATH=$(abspath ./)/test-models \
|
||||
$(GOCMD) run github.com/onsi/ginkgo/v2/ginkgo --label-filter="tts" --flake-attempts 1 -v -r ./api ./pkg
|
||||
|
||||
test-stablediffusion: prepare-test
|
||||
TEST_DIR=$(abspath ./)/test-dir/ FIXTURES=$(abspath ./)/tests/fixtures CONFIG_FILE=$(abspath ./)/test-models/config.yaml MODELS_PATH=$(abspath ./)/test-models \
|
||||
$(GOCMD) run github.com/onsi/ginkgo/v2/ginkgo --label-filter="stablediffusion" --flake-attempts 1 -v -r ./api ./pkg
|
||||
|
||||
test-container:
|
||||
docker build --target requirements -t local-ai-test-container .
|
||||
docker run -ti --rm --entrypoint /bin/bash -ti -v $(abspath ./):/build local-ai-test-container
|
||||
|
||||
## Help:
|
||||
help: ## Show this help.
|
||||
@@ -301,3 +361,106 @@ help: ## Show this help.
|
||||
if (/^[a-zA-Z_-]+:.*?##.*$$/) {printf " ${YELLOW}%-20s${GREEN}%s${RESET}\n", $$1, $$2} \
|
||||
else if (/^## .*$$/) {printf " ${CYAN}%s${RESET}\n", substr($$1,4)} \
|
||||
}' $(MAKEFILE_LIST)
|
||||
|
||||
protogen: protogen-go protogen-python
|
||||
|
||||
protogen-go:
|
||||
protoc --go_out=. --go_opt=paths=source_relative --go-grpc_out=. --go-grpc_opt=paths=source_relative \
|
||||
pkg/grpc/proto/backend.proto
|
||||
|
||||
protogen-python:
|
||||
python3 -m grpc_tools.protoc -Ipkg/grpc/proto/ --python_out=extra/grpc/huggingface/ --grpc_python_out=extra/grpc/huggingface/ pkg/grpc/proto/backend.proto
|
||||
python3 -m grpc_tools.protoc -Ipkg/grpc/proto/ --python_out=extra/grpc/autogptq/ --grpc_python_out=extra/grpc/autogptq/ pkg/grpc/proto/backend.proto
|
||||
python3 -m grpc_tools.protoc -Ipkg/grpc/proto/ --python_out=extra/grpc/exllama/ --grpc_python_out=extra/grpc/exllama/ pkg/grpc/proto/backend.proto
|
||||
python3 -m grpc_tools.protoc -Ipkg/grpc/proto/ --python_out=extra/grpc/bark/ --grpc_python_out=extra/grpc/bark/ pkg/grpc/proto/backend.proto
|
||||
python3 -m grpc_tools.protoc -Ipkg/grpc/proto/ --python_out=extra/grpc/diffusers/ --grpc_python_out=extra/grpc/diffusers/ pkg/grpc/proto/backend.proto
|
||||
python3 -m grpc_tools.protoc -Ipkg/grpc/proto/ --python_out=extra/grpc/vall-e-x/ --grpc_python_out=extra/grpc/vall-e-x/ pkg/grpc/proto/backend.proto
|
||||
python3 -m grpc_tools.protoc -Ipkg/grpc/proto/ --python_out=extra/grpc/vllm/ --grpc_python_out=extra/grpc/vllm/ pkg/grpc/proto/backend.proto
|
||||
|
||||
## GRPC
|
||||
|
||||
backend-assets/grpc:
|
||||
mkdir -p backend-assets/grpc
|
||||
|
||||
backend-assets/grpc/falcon: backend-assets/grpc go-ggllm/libggllm.a
|
||||
CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(shell pwd)/go-ggllm LIBRARY_PATH=$(shell pwd)/go-ggllm \
|
||||
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/falcon ./cmd/grpc/falcon/
|
||||
|
||||
backend-assets/grpc/llama: backend-assets/grpc go-llama/libbinding.a
|
||||
$(GOCMD) mod edit -replace github.com/go-skynet/go-llama.cpp=$(shell pwd)/go-llama
|
||||
CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(shell pwd)/go-llama LIBRARY_PATH=$(shell pwd)/go-llama \
|
||||
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/llama ./cmd/grpc/llama/
|
||||
# TODO: every binary should have its own folder instead, so can have different metal implementations
|
||||
ifeq ($(BUILD_TYPE),metal)
|
||||
cp go-llama/build/bin/ggml-metal.metal backend-assets/grpc/
|
||||
endif
|
||||
|
||||
backend-assets/grpc/llama-stable: backend-assets/grpc go-llama-stable/libbinding.a
|
||||
$(GOCMD) mod edit -replace github.com/go-skynet/go-llama.cpp=$(shell pwd)/go-llama-stable
|
||||
CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(shell pwd)/go-llama-stable LIBRARY_PATH=$(shell pwd)/go-llama \
|
||||
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/llama-stable ./cmd/grpc/llama-stable/
|
||||
|
||||
backend-assets/grpc/gpt4all: backend-assets/grpc backend-assets/gpt4all gpt4all/gpt4all-bindings/golang/libgpt4all.a
|
||||
CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(shell pwd)/gpt4all/gpt4all-bindings/golang/ LIBRARY_PATH=$(shell pwd)/gpt4all/gpt4all-bindings/golang/ \
|
||||
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/gpt4all ./cmd/grpc/gpt4all/
|
||||
|
||||
backend-assets/grpc/dolly: backend-assets/grpc go-ggml-transformers/libtransformers.a
|
||||
CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(shell pwd)/go-ggml-transformers LIBRARY_PATH=$(shell pwd)/go-ggml-transformers \
|
||||
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/dolly ./cmd/grpc/dolly/
|
||||
|
||||
backend-assets/grpc/gpt2: backend-assets/grpc go-ggml-transformers/libtransformers.a
|
||||
CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(shell pwd)/go-ggml-transformers LIBRARY_PATH=$(shell pwd)/go-ggml-transformers \
|
||||
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/gpt2 ./cmd/grpc/gpt2/
|
||||
|
||||
backend-assets/grpc/gptj: backend-assets/grpc go-ggml-transformers/libtransformers.a
|
||||
CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(shell pwd)/go-ggml-transformers LIBRARY_PATH=$(shell pwd)/go-ggml-transformers \
|
||||
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/gptj ./cmd/grpc/gptj/
|
||||
|
||||
backend-assets/grpc/gptneox: backend-assets/grpc go-ggml-transformers/libtransformers.a
|
||||
CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(shell pwd)/go-ggml-transformers LIBRARY_PATH=$(shell pwd)/go-ggml-transformers \
|
||||
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/gptneox ./cmd/grpc/gptneox/
|
||||
|
||||
backend-assets/grpc/mpt: backend-assets/grpc go-ggml-transformers/libtransformers.a
|
||||
CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(shell pwd)/go-ggml-transformers LIBRARY_PATH=$(shell pwd)/go-ggml-transformers \
|
||||
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/mpt ./cmd/grpc/mpt/
|
||||
|
||||
backend-assets/grpc/replit: backend-assets/grpc go-ggml-transformers/libtransformers.a
|
||||
CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(shell pwd)/go-ggml-transformers LIBRARY_PATH=$(shell pwd)/go-ggml-transformers \
|
||||
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/replit ./cmd/grpc/replit/
|
||||
|
||||
backend-assets/grpc/falcon-ggml: backend-assets/grpc go-ggml-transformers/libtransformers.a
|
||||
CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(shell pwd)/go-ggml-transformers LIBRARY_PATH=$(shell pwd)/go-ggml-transformers \
|
||||
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/falcon-ggml ./cmd/grpc/falcon-ggml/
|
||||
|
||||
backend-assets/grpc/starcoder: backend-assets/grpc go-ggml-transformers/libtransformers.a
|
||||
CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(shell pwd)/go-ggml-transformers LIBRARY_PATH=$(shell pwd)/go-ggml-transformers \
|
||||
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/starcoder ./cmd/grpc/starcoder/
|
||||
|
||||
backend-assets/grpc/rwkv: backend-assets/grpc go-rwkv/librwkv.a
|
||||
CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(shell pwd)/go-rwkv LIBRARY_PATH=$(shell pwd)/go-rwkv \
|
||||
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/rwkv ./cmd/grpc/rwkv/
|
||||
|
||||
backend-assets/grpc/bloomz: backend-assets/grpc bloomz/libbloomz.a
|
||||
CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(shell pwd)/bloomz LIBRARY_PATH=$(shell pwd)/bloomz \
|
||||
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/bloomz ./cmd/grpc/bloomz/
|
||||
|
||||
backend-assets/grpc/bert-embeddings: backend-assets/grpc go-bert/libgobert.a
|
||||
CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(shell pwd)/go-bert LIBRARY_PATH=$(shell pwd)/go-bert \
|
||||
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/bert-embeddings ./cmd/grpc/bert-embeddings/
|
||||
|
||||
backend-assets/grpc/langchain-huggingface: backend-assets/grpc
|
||||
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/langchain-huggingface ./cmd/grpc/langchain-huggingface/
|
||||
|
||||
backend-assets/grpc/stablediffusion: backend-assets/grpc go-stable-diffusion/libstablediffusion.a
|
||||
CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(shell pwd)/go-stable-diffusion/ LIBRARY_PATH=$(shell pwd)/go-stable-diffusion/ \
|
||||
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/stablediffusion ./cmd/grpc/stablediffusion/
|
||||
|
||||
backend-assets/grpc/piper: backend-assets/grpc backend-assets/espeak-ng-data go-piper/libpiper_binding.a
|
||||
CGO_LDFLAGS="$(CGO_LDFLAGS)" LIBRARY_PATH=$(shell pwd)/go-piper \
|
||||
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/piper ./cmd/grpc/piper/
|
||||
|
||||
backend-assets/grpc/whisper: backend-assets/grpc whisper.cpp/libwhisper.a
|
||||
CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(shell pwd)/whisper.cpp LIBRARY_PATH=$(shell pwd)/whisper.cpp \
|
||||
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/whisper ./cmd/grpc/whisper/
|
||||
|
||||
grpcs: prepare $(GRPC_BACKENDS)
|
||||
|
||||
292
README.md
292
README.md
@@ -1,210 +1,163 @@
|
||||
<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/)
|
||||
|
||||
**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.
|
||||
|
||||
For a list of the supported model families, please see [the model compatibility table](https://localai.io/model-compatibility/index.html#model-compatibility-table).
|
||||
[](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)
|
||||
|
||||
**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, pytorch and more. Does not require GPU.
|
||||
|
||||
<p align="center"><b>Follow LocalAI </b></p>
|
||||
|
||||
<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>
|
||||
|
||||
<p align="center"><b>Connect with the Creator </b></p>
|
||||
|
||||
<p align="center">
|
||||
<a href="https://twitter.com/mudler_it" target="blank">
|
||||
<img src="https://img.shields.io/twitter/follow/mudler_it?label=Follow: mudler_it&style=social" alt="Follow mudler_it"/>
|
||||
</a>
|
||||
<a href='https://github.com/mudler'>
|
||||
<img alt="Follow on Github" src="https://img.shields.io/badge/Follow-mudler-black?logo=github&link=https%3A%2F%2Fgithub.com%2Fmudler">
|
||||
</a>
|
||||
</p>
|
||||
|
||||
<p align="center"><b>Share LocalAI Repository</b></p>
|
||||
|
||||
<p align="center">
|
||||
|
||||
<a href="https://twitter.com/intent/tweet?text=Check%20this%20GitHub%20repository%20out.%20LocalAI%20-%20Let%27s%20you%20easily%20run%20LLM%20locally.&url=https://github.com/go-skynet/LocalAI&hashtags=LocalAI,AI" target="blank">
|
||||
<img src="https://img.shields.io/twitter/follow/_LocalAI?label=Share Repo on Twitter&style=social" alt="Follow _LocalAI"/></a>
|
||||
<a href="https://t.me/share/url?text=Check%20this%20GitHub%20repository%20out.%20LocalAI%20-%20Let%27s%20you%20easily%20run%20LLM%20locally.&url=https://github.com/go-skynet/LocalAI" target="_blank"><img src="https://img.shields.io/twitter/url?label=Telegram&logo=Telegram&style=social&url=https://github.com/go-skynet/LocalAI" alt="Share on Telegram"/></a>
|
||||
<a href="https://api.whatsapp.com/send?text=Check%20this%20GitHub%20repository%20out.%20LocalAI%20-%20Let%27s%20you%20easily%20run%20LLM%20locally.%20https://github.com/go-skynet/LocalAI"><img src="https://img.shields.io/twitter/url?label=whatsapp&logo=whatsapp&style=social&url=https://github.com/go-skynet/LocalAI" /></a> <a href="https://www.reddit.com/submit?url=https://github.com/go-skynet/LocalAI&title=Check%20this%20GitHub%20repository%20out.%20LocalAI%20-%20Let%27s%20you%20easily%20run%20LLM%20locally.
|
||||
" target="blank">
|
||||
<img src="https://img.shields.io/twitter/url?label=Reddit&logo=Reddit&style=social&url=https://github.com/go-skynet/LocalAI" alt="Share on Reddit"/>
|
||||
</a> <a href="mailto:?subject=Check%20this%20GitHub%20repository%20out.%20LocalAI%20-%20Let%27s%20you%20easily%20run%20LLM%20locally.%3A%0Ahttps://github.com/go-skynet/LocalAI" target="_blank"><img src="https://img.shields.io/twitter/url?label=Gmail&logo=Gmail&style=social&url=https://github.com/go-skynet/LocalAI"/></a> <a href="https://www.buymeacoffee.com/mudler" target="_blank"><img src="https://cdn.buymeacoffee.com/buttons/default-orange.png" alt="Buy Me A Coffee" height="23" width="100" style="border-radius:1px"></a>
|
||||
|
||||
</p>
|
||||
|
||||
<hr>
|
||||
|
||||
In a nutshell:
|
||||
|
||||
- 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.
|
||||
- NO GPU required. NO Internet access is required either
|
||||
- Optional, GPU Acceleration is available in `llama.cpp`-compatible LLMs. See also the [build section](https://localai.io/basics/build/index.html).
|
||||
- Supports multiple models
|
||||
- 🏃 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.
|
||||
|
||||
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!
|
||||
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!
|
||||
|
||||
See the [examples](https://github.com/go-skynet/LocalAI/tree/master/examples/) on how to integrate LocalAI with other popular projects:
|
||||
Note that this started just as a [fun weekend project](https://localai.io/#backstory) in order to try to create the necessary pieces for a full AI assistant like `ChatGPT`: the community is growing fast and we are working hard to make it better and more stable. If you want to help, please consider contributing (see below)!
|
||||
|
||||
| [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) |
|
||||
|------------------------------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------------|
|
||||
|  |  |
|
||||
## 🔥🔥 [Hot topics / Roadmap](https://localai.io/#-hot-topics--roadmap)
|
||||
|
||||
| [Telegram bot](https://github.com/go-skynet/LocalAI/tree/master/examples/telegram-bot) | [Flowise](https://github.com/go-skynet/LocalAI/tree/master/examples/flowise) |
|
||||
|------------------------------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------------|
|
||||
 | | |
|
||||
## 🚀 [Features](https://localai.io/features/)
|
||||
|
||||
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/).
|
||||
|
||||
## News
|
||||
|
||||
- 🔥🔥🔥 19-06-2023: **v1.19.0**: CUDA support! [Release notes](https://localai.io/basics/news/index.html#-19-06-2023-__v1190__-) [Changelog](https://github.com/go-skynet/LocalAI/releases/tag/v1.19.0)
|
||||
- 🔥🔥🔥 06-06-2023: **v1.18.0**: Many updates, new features, and much more 🚀, check out the [Release notes](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)!
|
||||
|
||||
For latest news, follow also on Twitter [@LocalAI_API](https://twitter.com/LocalAI_API) and [@mudler_it](https://twitter.com/mudler_it)
|
||||
|
||||
## Contribute and help
|
||||
|
||||
To help the project you can:
|
||||
|
||||
- [Hacker news post](https://news.ycombinator.com/item?id=35726934) - help us out by voting if you like this project.
|
||||
|
||||
- If you have technological skills and want to contribute to development, have a look at the open issues. If you are new you can have a look at the [good-first-issue](https://github.com/go-skynet/LocalAI/issues?q=is%3Aissue+is%3Aopen+label%3A%22good+first+issue%22) and [help-wanted](https://github.com/go-skynet/LocalAI/issues?q=is%3Aissue+is%3Aopen+label%3A%22help+wanted%22) labels.
|
||||
|
||||
- If you don't have technological skills you can still help improving documentation or add examples or share your user-stories with our community, any help and contribution is welcome!
|
||||
|
||||
## Usage
|
||||
|
||||
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.
|
||||
|
||||
The easiest way to run LocalAI is by using `docker-compose` (to build locally, see [building LocalAI](https://localai.io/basics/build/index.html)):
|
||||
|
||||
```bash
|
||||
|
||||
git clone https://github.com/go-skynet/LocalAI
|
||||
|
||||
cd LocalAI
|
||||
|
||||
# (optional) Checkout a specific LocalAI tag
|
||||
# git checkout -b build <TAG>
|
||||
|
||||
# copy your models to models/
|
||||
cp your-model.bin models/
|
||||
|
||||
# (optional) Edit the .env file to set things like context size and threads
|
||||
# vim .env
|
||||
|
||||
# start with docker-compose
|
||||
docker-compose up -d --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>
|
||||
- 📖 [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/)
|
||||
|
||||
|
||||
### Build locally
|
||||
## :book: 🎥 [Media, Blogs, Social](https://localai.io/basics/news/#media-blogs-social)
|
||||
|
||||
<details>
|
||||
- [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)
|
||||
|
||||
In order to build the `LocalAI` container image locally you can use `docker`:
|
||||
## 💻 Usage
|
||||
|
||||
Check out the [Getting started](https://localai.io/basics/getting_started/index.html) section in our documentation.
|
||||
|
||||
### 💡 Example: Use Luna-AI Llama model
|
||||
|
||||
See the [documentation](https://localai.io/basics/getting_started)
|
||||
|
||||
### 🔗 Resources
|
||||
|
||||
- [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)
|
||||
|
||||
## Citation
|
||||
|
||||
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)
|
||||
- [x] 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)
|
||||
- [x] Upstream [gpt4all](https://github.com/go-skynet/LocalAI/issues/85) bindings
|
||||
- [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
|
||||
- [x] 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!
|
||||
|
||||
@@ -215,9 +168,12 @@ 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>
|
||||
|
||||
214
api/api.go
214
api/api.go
@@ -2,9 +2,17 @@ package api
|
||||
|
||||
import (
|
||||
"errors"
|
||||
"fmt"
|
||||
"strings"
|
||||
|
||||
config "github.com/go-skynet/LocalAI/api/config"
|
||||
"github.com/go-skynet/LocalAI/api/localai"
|
||||
"github.com/go-skynet/LocalAI/api/openai"
|
||||
"github.com/go-skynet/LocalAI/api/options"
|
||||
"github.com/go-skynet/LocalAI/api/schema"
|
||||
"github.com/go-skynet/LocalAI/internal"
|
||||
"github.com/go-skynet/LocalAI/pkg/assets"
|
||||
|
||||
"github.com/gofiber/fiber/v2"
|
||||
"github.com/gofiber/fiber/v2/middleware/cors"
|
||||
"github.com/gofiber/fiber/v2/middleware/logger"
|
||||
@@ -13,18 +21,77 @@ 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 options.Debug {
|
||||
for _, v := range cl.ListConfigs() {
|
||||
cfg, _ := cl.GetConfig(v)
|
||||
log.Debug().Msgf("Model: %s (config: %+v)", v, cfg)
|
||||
}
|
||||
}
|
||||
|
||||
if options.AssetsDestination != "" {
|
||||
// Extract files from the embedded FS
|
||||
err := assets.ExtractFiles(options.BackendAssets, options.AssetsDestination)
|
||||
log.Debug().Msgf("Extracting backend assets files to %s", options.AssetsDestination)
|
||||
if err != nil {
|
||||
log.Warn().Msgf("Failed extracting backend assets files: %s (might be required for some backends to work properly, like gpt4all)", err)
|
||||
}
|
||||
}
|
||||
|
||||
if options.PreloadJSONModels != "" {
|
||||
if err := localai.ApplyGalleryFromString(options.Loader.ModelPath, options.PreloadJSONModels, cl, options.Galleries); err != nil {
|
||||
return nil, nil, err
|
||||
}
|
||||
}
|
||||
|
||||
if options.PreloadModelsFromPath != "" {
|
||||
if err := localai.ApplyGalleryFromFile(options.Loader.ModelPath, options.PreloadModelsFromPath, cl, options.Galleries); err != nil {
|
||||
return nil, nil, err
|
||||
}
|
||||
}
|
||||
|
||||
// turn off any process that was started by GRPC if the context is canceled
|
||||
go func() {
|
||||
<-options.Context.Done()
|
||||
log.Debug().Msgf("Context canceled, shutting down")
|
||||
options.Loader.StopAllGRPC()
|
||||
}()
|
||||
|
||||
return options, cl, nil
|
||||
}
|
||||
|
||||
func App(opts ...options.AppOption) (*fiber.App, error) {
|
||||
|
||||
options, cl, err := Startup(opts...)
|
||||
if err != nil {
|
||||
return nil, fmt.Errorf("failed basic startup tasks with error %s", err.Error())
|
||||
}
|
||||
|
||||
// Return errors as JSON responses
|
||||
app := fiber.New(fiber.Config{
|
||||
BodyLimit: options.uploadLimitMB * 1024 * 1024, // this is the default limit of 4MB
|
||||
DisableStartupMessage: options.disableMessage,
|
||||
BodyLimit: options.UploadLimitMB * 1024 * 1024, // this is the default limit of 4MB
|
||||
DisableStartupMessage: options.DisableMessage,
|
||||
// Override default error handler
|
||||
ErrorHandler: func(ctx *fiber.Ctx, err error) error {
|
||||
// Status code defaults to 500
|
||||
@@ -38,117 +105,111 @@ 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, options.galleries); 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 {
|
||||
authHeader := c.Get("Authorization")
|
||||
if authHeader == "" {
|
||||
return c.Status(fiber.StatusUnauthorized).JSON(fiber.Map{"message": "Authorization header missing"})
|
||||
}
|
||||
authHeaderParts := strings.Split(authHeader, " ")
|
||||
if len(authHeaderParts) != 2 || authHeaderParts[0] != "Bearer" {
|
||||
return c.Status(fiber.StatusUnauthorized).JSON(fiber.Map{"message": "Invalid Authorization header format"})
|
||||
}
|
||||
|
||||
apiKey := authHeaderParts[1]
|
||||
validApiKey := false
|
||||
for _, key := range options.ApiKeys {
|
||||
if apiKey == key {
|
||||
validApiKey = true
|
||||
}
|
||||
}
|
||||
if !validApiKey {
|
||||
return c.Status(fiber.StatusUnauthorized).JSON(fiber.Map{"message": "Invalid API key"})
|
||||
}
|
||||
}
|
||||
return c.Next()
|
||||
}
|
||||
|
||||
if options.preloadModelsFromPath != "" {
|
||||
if err := ApplyGalleryFromFile(options.loader.ModelPath, options.preloadModelsFromPath, cm, options.galleries); err != nil {
|
||||
return nil, err
|
||||
}
|
||||
}
|
||||
|
||||
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)
|
||||
galleryService := localai.NewGalleryService(options.Loader.ModelPath)
|
||||
galleryService.Start(options.Context, cl)
|
||||
|
||||
app.Get("/version", func(c *fiber.Ctx) error {
|
||||
app.Get("/version", auth, func(c *fiber.Ctx) error {
|
||||
return c.JSON(struct {
|
||||
Version string `json:"version"`
|
||||
}{Version: internal.PrintableVersion()})
|
||||
})
|
||||
|
||||
app.Post("/models/apply", applyModelGallery(options.loader.ModelPath, cm, applier.C, options.galleries))
|
||||
app.Get("/models/available", listModelFromGallery(options.galleries, options.loader.ModelPath))
|
||||
app.Get("/models/jobs/:uuid", getOpStatus(applier))
|
||||
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/engines/:model/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("/tts", ttsEndpoint(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)
|
||||
if options.AudioDir != "" {
|
||||
app.Static("/generated-audio", options.AudioDir)
|
||||
}
|
||||
|
||||
ok := func(c *fiber.Ctx) error {
|
||||
@@ -159,9 +220,14 @@ 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))
|
||||
|
||||
return app, nil
|
||||
}
|
||||
|
||||
415
api/api_test.go
415
api/api_test.go
@@ -5,14 +5,16 @@ 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/pkg/gallery"
|
||||
"github.com/go-skynet/LocalAI/pkg/model"
|
||||
"github.com/go-skynet/LocalAI/pkg/utils"
|
||||
@@ -23,13 +25,14 @@ import (
|
||||
|
||||
openaigo "github.com/otiai10/openaigo"
|
||||
"github.com/sashabaranov/go-openai"
|
||||
"github.com/sashabaranov/go-openai/jsonschema"
|
||||
)
|
||||
|
||||
type modelApplyRequest struct {
|
||||
ID string `json:"id"`
|
||||
URL string `json:"url"`
|
||||
Name string `json:"name"`
|
||||
Overrides map[string]string `json:"overrides"`
|
||||
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{}) {
|
||||
@@ -41,7 +44,7 @@ func getModelStatus(url string) (response map[string]interface{}) {
|
||||
}
|
||||
defer resp.Body.Close()
|
||||
|
||||
body, err := ioutil.ReadAll(resp.Body)
|
||||
body, err := io.ReadAll(resp.Body)
|
||||
if err != nil {
|
||||
fmt.Println("Error reading response body:", err)
|
||||
return
|
||||
@@ -93,7 +96,7 @@ func postModelApplyRequest(url string, request modelApplyRequest) (response map[
|
||||
}
|
||||
defer resp.Body.Close()
|
||||
|
||||
body, err := ioutil.ReadAll(resp.Body)
|
||||
body, err := io.ReadAll(resp.Body)
|
||||
if err != nil {
|
||||
fmt.Println("Error reading response body:", err)
|
||||
return
|
||||
@@ -121,6 +124,11 @@ var _ = Describe("API test", func() {
|
||||
var cancel context.CancelFunc
|
||||
var tmpdir string
|
||||
|
||||
commonOpts := []options.AppOption{
|
||||
options.WithDebug(true),
|
||||
options.WithDisableMessage(true),
|
||||
}
|
||||
|
||||
Context("API with ephemeral models", func() {
|
||||
BeforeEach(func() {
|
||||
var err error
|
||||
@@ -139,12 +147,12 @@ var _ = Describe("API test", func() {
|
||||
Name: "bert2",
|
||||
URL: "https://raw.githubusercontent.com/go-skynet/model-gallery/main/bert-embeddings.yaml",
|
||||
Overrides: map[string]interface{}{"foo": "bar"},
|
||||
AdditionalFiles: []gallery.File{gallery.File{Filename: "foo.yaml", URI: "https://raw.githubusercontent.com/go-skynet/model-gallery/main/bert-embeddings.yaml"}},
|
||||
AdditionalFiles: []gallery.File{{Filename: "foo.yaml", URI: "https://raw.githubusercontent.com/go-skynet/model-gallery/main/bert-embeddings.yaml"}},
|
||||
},
|
||||
}
|
||||
out, err := yaml.Marshal(g)
|
||||
Expect(err).ToNot(HaveOccurred())
|
||||
err = ioutil.WriteFile(filepath.Join(tmpdir, "gallery_simple.yaml"), out, 0644)
|
||||
err = os.WriteFile(filepath.Join(tmpdir, "gallery_simple.yaml"), out, 0644)
|
||||
Expect(err).ToNot(HaveOccurred())
|
||||
|
||||
galleries := []gallery.Gallery{
|
||||
@@ -154,9 +162,11 @@ var _ = Describe("API test", func() {
|
||||
},
|
||||
}
|
||||
|
||||
app, err = App(WithContext(c),
|
||||
WithGalleries(galleries),
|
||||
WithModelLoader(modelLoader), WithBackendAssets(backendAssets), WithBackendAssetsOutput(tmpdir))
|
||||
app, err = App(
|
||||
append(commonOpts,
|
||||
options.WithContext(c),
|
||||
options.WithGalleries(galleries),
|
||||
options.WithModelLoader(modelLoader), options.WithBackendAssets(backendAssets), options.WithBackendAssetsOutput(tmpdir))...)
|
||||
Expect(err).ToNot(HaveOccurred())
|
||||
go app.Listen("127.0.0.1:9090")
|
||||
|
||||
@@ -201,7 +211,7 @@ var _ = Describe("API test", func() {
|
||||
fmt.Println(response)
|
||||
resp = response
|
||||
return response["processed"].(bool)
|
||||
}, "360s").Should(Equal(true))
|
||||
}, "360s", "10s").Should(Equal(true))
|
||||
Expect(resp["message"]).ToNot(ContainSubstring("error"))
|
||||
|
||||
dat, err := os.ReadFile(filepath.Join(tmpdir, "bert2.yaml"))
|
||||
@@ -232,7 +242,7 @@ 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{}{
|
||||
"backend": "llama",
|
||||
},
|
||||
})
|
||||
@@ -243,9 +253,8 @@ var _ = Describe("API test", func() {
|
||||
|
||||
Eventually(func() bool {
|
||||
response := getModelStatus("http://127.0.0.1:9090/models/jobs/" + uuid)
|
||||
fmt.Println(response)
|
||||
return response["processed"].(bool)
|
||||
}, "360s").Should(Equal(true))
|
||||
}, "360s", "10s").Should(Equal(true))
|
||||
|
||||
dat, err := os.ReadFile(filepath.Join(tmpdir, "bert.yaml"))
|
||||
Expect(err).ToNot(HaveOccurred())
|
||||
@@ -259,7 +268,7 @@ var _ = Describe("API test", func() {
|
||||
response := postModelApplyRequest("http://127.0.0.1:9090/models/apply", modelApplyRequest{
|
||||
URL: "https://raw.githubusercontent.com/go-skynet/model-gallery/main/bert-embeddings.yaml",
|
||||
Name: "bert",
|
||||
Overrides: map[string]string{},
|
||||
Overrides: map[string]interface{}{},
|
||||
})
|
||||
|
||||
Expect(response["uuid"]).ToNot(BeEmpty(), fmt.Sprint(response))
|
||||
@@ -268,9 +277,8 @@ var _ = Describe("API test", func() {
|
||||
|
||||
Eventually(func() bool {
|
||||
response := getModelStatus("http://127.0.0.1:9090/models/jobs/" + uuid)
|
||||
fmt.Println(response)
|
||||
return response["processed"].(bool)
|
||||
}, "360s").Should(Equal(true))
|
||||
}, "360s", "10s").Should(Equal(true))
|
||||
|
||||
dat, err := os.ReadFile(filepath.Join(tmpdir, "bert.yaml"))
|
||||
Expect(err).ToNot(HaveOccurred())
|
||||
@@ -288,7 +296,7 @@ var _ = Describe("API test", func() {
|
||||
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-stable", "mmap": true, "f16": true, "context_size": 128},
|
||||
})
|
||||
|
||||
Expect(response["uuid"]).ToNot(BeEmpty(), fmt.Sprint(response))
|
||||
@@ -297,14 +305,134 @@ 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))
|
||||
}, "360s", "10s").Should(Equal(true))
|
||||
|
||||
By("testing completion")
|
||||
resp, err := client.CreateCompletion(context.TODO(), openai.CompletionRequest{Model: "openllama_3b", Prompt: "Count up to five: one, two, three, four, "})
|
||||
Expect(err).ToNot(HaveOccurred())
|
||||
Expect(len(resp.Choices)).To(Equal(1))
|
||||
Expect(resp.Choices[0].Text).To(ContainSubstring("five"))
|
||||
|
||||
By("testing functions")
|
||||
resp2, err := client.CreateChatCompletion(
|
||||
context.TODO(),
|
||||
openai.ChatCompletionRequest{
|
||||
Model: "openllama_3b",
|
||||
Messages: []openai.ChatCompletionMessage{
|
||||
{
|
||||
Role: "user",
|
||||
Content: "What is the weather like in San Francisco (celsius)?",
|
||||
},
|
||||
},
|
||||
Functions: []openai.FunctionDefinition{
|
||||
openai.FunctionDefinition{
|
||||
Name: "get_current_weather",
|
||||
Description: "Get the current weather",
|
||||
Parameters: jsonschema.Definition{
|
||||
Type: jsonschema.Object,
|
||||
Properties: map[string]jsonschema.Definition{
|
||||
"location": {
|
||||
Type: jsonschema.String,
|
||||
Description: "The city and state, e.g. San Francisco, CA",
|
||||
},
|
||||
"unit": {
|
||||
Type: jsonschema.String,
|
||||
Enum: []string{"celcius", "fahrenheit"},
|
||||
},
|
||||
},
|
||||
Required: []string{"location"},
|
||||
},
|
||||
},
|
||||
},
|
||||
})
|
||||
Expect(err).ToNot(HaveOccurred())
|
||||
Expect(len(resp2.Choices)).To(Equal(1))
|
||||
Expect(resp2.Choices[0].Message.FunctionCall).ToNot(BeNil())
|
||||
Expect(resp2.Choices[0].Message.FunctionCall.Name).To(Equal("get_current_weather"), resp2.Choices[0].Message.FunctionCall.Name)
|
||||
|
||||
var res map[string]string
|
||||
err = json.Unmarshal([]byte(resp2.Choices[0].Message.FunctionCall.Arguments), &res)
|
||||
Expect(err).ToNot(HaveOccurred())
|
||||
Expect(res["location"]).To(Equal("San Francisco, California, United States"), fmt.Sprint(res))
|
||||
Expect(res["unit"]).To(Equal("celcius"), fmt.Sprint(res))
|
||||
Expect(string(resp2.Choices[0].FinishReason)).To(Equal("function_call"), fmt.Sprint(resp2.Choices[0].FinishReason))
|
||||
})
|
||||
|
||||
It("runs openllama gguf", Label("llama-gguf"), func() {
|
||||
if runtime.GOOS != "linux" {
|
||||
Skip("test supported only on linux")
|
||||
}
|
||||
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() {
|
||||
@@ -313,9 +441,8 @@ 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))
|
||||
@@ -324,15 +451,130 @@ 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))
|
||||
|
||||
resp, err := client.CreateChatCompletion(context.TODO(), openai.ChatCompletionRequest{Model: "gpt4all-j", Messages: []openai.ChatCompletionMessage{openai.ChatCompletionMessage{Role: "user", Content: "How are you?"}}})
|
||||
Expect(err).ToNot(HaveOccurred())
|
||||
Expect(len(resp.Choices)).To(Equal(1))
|
||||
Expect(resp.Choices[0].Message.Content).To(ContainSubstring("well"))
|
||||
})
|
||||
|
||||
})
|
||||
})
|
||||
|
||||
Context("Model gallery", func() {
|
||||
BeforeEach(func() {
|
||||
var err error
|
||||
tmpdir, err = os.MkdirTemp("", "")
|
||||
Expect(err).ToNot(HaveOccurred())
|
||||
|
||||
modelLoader = model.NewModelLoader(tmpdir)
|
||||
c, cancel = context.WithCancel(context.Background())
|
||||
|
||||
galleries := []gallery.Gallery{
|
||||
{
|
||||
Name: "model-gallery",
|
||||
URL: "https://raw.githubusercontent.com/go-skynet/model-gallery/main/index.yaml",
|
||||
},
|
||||
}
|
||||
|
||||
app, err = App(
|
||||
append(commonOpts,
|
||||
options.WithContext(c),
|
||||
options.WithAudioDir(tmpdir),
|
||||
options.WithImageDir(tmpdir),
|
||||
options.WithGalleries(galleries),
|
||||
options.WithModelLoader(modelLoader),
|
||||
options.WithBackendAssets(backendAssets),
|
||||
options.WithBackendAssetsOutput(tmpdir))...,
|
||||
)
|
||||
Expect(err).ToNot(HaveOccurred())
|
||||
go app.Listen("127.0.0.1:9090")
|
||||
|
||||
defaultConfig := openai.DefaultConfig("")
|
||||
defaultConfig.BaseURL = "http://127.0.0.1:9090/v1"
|
||||
|
||||
client2 = openaigo.NewClient("")
|
||||
client2.BaseURL = defaultConfig.BaseURL
|
||||
|
||||
// Wait for API to be ready
|
||||
client = openai.NewClientWithConfig(defaultConfig)
|
||||
Eventually(func() error {
|
||||
_, err := client.ListModels(context.TODO())
|
||||
return err
|
||||
}, "2m").ShouldNot(HaveOccurred())
|
||||
})
|
||||
|
||||
AfterEach(func() {
|
||||
cancel()
|
||||
app.Shutdown()
|
||||
os.RemoveAll(tmpdir)
|
||||
})
|
||||
It("installs and is capable to run tts", Label("tts"), func() {
|
||||
if runtime.GOOS != "linux" {
|
||||
Skip("test supported only on linux")
|
||||
}
|
||||
|
||||
response := postModelApplyRequest("http://127.0.0.1:9090/models/apply", modelApplyRequest{
|
||||
ID: "model-gallery@voice-en-us-kathleen-low",
|
||||
})
|
||||
|
||||
Expect(response["uuid"]).ToNot(BeEmpty(), fmt.Sprint(response))
|
||||
|
||||
uuid := response["uuid"].(string)
|
||||
|
||||
Eventually(func() bool {
|
||||
response := getModelStatus("http://127.0.0.1:9090/models/jobs/" + uuid)
|
||||
fmt.Println(response)
|
||||
return response["processed"].(bool)
|
||||
}, "360s", "10s").Should(Equal(true))
|
||||
|
||||
// An HTTP Post to the /tts endpoint should return a wav audio file
|
||||
resp, err := http.Post("http://127.0.0.1:9090/tts", "application/json", bytes.NewBuffer([]byte(`{"input": "Hello world", "model": "en-us-kathleen-low.onnx"}`)))
|
||||
Expect(err).ToNot(HaveOccurred(), fmt.Sprint(resp))
|
||||
dat, err := io.ReadAll(resp.Body)
|
||||
Expect(err).ToNot(HaveOccurred(), fmt.Sprint(resp))
|
||||
|
||||
Expect(resp.StatusCode).To(Equal(200), fmt.Sprint(string(dat)))
|
||||
Expect(resp.Header.Get("Content-Type")).To(Equal("audio/x-wav"))
|
||||
})
|
||||
It("installs and is capable to generate images", Label("stablediffusion"), func() {
|
||||
if runtime.GOOS != "linux" {
|
||||
Skip("test supported only on linux")
|
||||
}
|
||||
|
||||
response := postModelApplyRequest("http://127.0.0.1:9090/models/apply", modelApplyRequest{
|
||||
ID: "model-gallery@stablediffusion",
|
||||
Overrides: map[string]interface{}{
|
||||
"parameters": map[string]interface{}{"model": "stablediffusion_assets"},
|
||||
},
|
||||
})
|
||||
|
||||
Expect(response["uuid"]).ToNot(BeEmpty(), fmt.Sprint(response))
|
||||
|
||||
uuid := response["uuid"].(string)
|
||||
|
||||
Eventually(func() bool {
|
||||
response := getModelStatus("http://127.0.0.1:9090/models/jobs/" + uuid)
|
||||
fmt.Println(response)
|
||||
return response["processed"].(bool)
|
||||
}, "360s", "10s").Should(Equal(true))
|
||||
|
||||
resp, err := http.Post(
|
||||
"http://127.0.0.1:9090/v1/images/generations",
|
||||
"application/json",
|
||||
bytes.NewBuffer([]byte(`{
|
||||
"prompt": "floating hair, portrait, ((loli)), ((one girl)), cute face, hidden hands, asymmetrical bangs, beautiful detailed eyes, eye shadow, hair ornament, ribbons, bowties, buttons, pleated skirt, (((masterpiece))), ((best quality)), colorful|((part of the head)), ((((mutated hands and fingers)))), deformed, blurry, bad anatomy, disfigured, poorly drawn face, mutation, mutated, extra limb, ugly, poorly drawn hands, missing limb, blurry, floating limbs, disconnected limbs, malformed hands, blur, out of focus, long neck, long body, Octane renderer, lowres, bad anatomy, bad hands, text",
|
||||
"mode": 2, "seed":9000,
|
||||
"size": "256x256", "n":2}`)))
|
||||
// The response should contain an URL
|
||||
Expect(err).ToNot(HaveOccurred(), fmt.Sprint(resp))
|
||||
dat, err := io.ReadAll(resp.Body)
|
||||
Expect(err).ToNot(HaveOccurred(), string(dat))
|
||||
Expect(string(dat)).To(ContainSubstring("http://127.0.0.1:9090/"), string(dat))
|
||||
Expect(string(dat)).To(ContainSubstring(".png"), string(dat))
|
||||
|
||||
})
|
||||
})
|
||||
|
||||
@@ -342,7 +584,12 @@ var _ = Describe("API test", func() {
|
||||
c, cancel = context.WithCancel(context.Background())
|
||||
|
||||
var err error
|
||||
app, err = App(WithContext(c), WithModelLoader(modelLoader))
|
||||
app, err = App(
|
||||
append(commonOpts,
|
||||
options.WithExternalBackend("huggingface", os.Getenv("HUGGINGFACE_GRPC")),
|
||||
options.WithContext(c),
|
||||
options.WithModelLoader(modelLoader),
|
||||
)...)
|
||||
Expect(err).ToNot(HaveOccurred())
|
||||
go app.Listen("127.0.0.1:9090")
|
||||
|
||||
@@ -366,7 +613,7 @@ 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"})
|
||||
@@ -397,9 +644,10 @@ 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" {
|
||||
@@ -443,15 +691,98 @@ var _ = Describe("API test", func() {
|
||||
Expect(resp2.Data[0].Embedding).To(Equal(sunEmbedding))
|
||||
})
|
||||
|
||||
Context("External gRPC calls", func() {
|
||||
It("calculate embeddings with huggingface", func() {
|
||||
if runtime.GOOS != "linux" {
|
||||
Skip("test supported only on linux")
|
||||
}
|
||||
resp, err := client.CreateEmbeddings(
|
||||
context.Background(),
|
||||
openai.EmbeddingRequest{
|
||||
Model: openai.AdaCodeSearchCode,
|
||||
Input: []string{"sun", "cat"},
|
||||
},
|
||||
)
|
||||
Expect(err).ToNot(HaveOccurred())
|
||||
Expect(len(resp.Data[0].Embedding)).To(BeNumerically("==", 384))
|
||||
Expect(len(resp.Data[1].Embedding)).To(BeNumerically("==", 384))
|
||||
|
||||
sunEmbedding := resp.Data[0].Embedding
|
||||
resp2, err := client.CreateEmbeddings(
|
||||
context.Background(),
|
||||
openai.EmbeddingRequest{
|
||||
Model: openai.AdaCodeSearchCode,
|
||||
Input: []string{"sun"},
|
||||
},
|
||||
)
|
||||
Expect(err).ToNot(HaveOccurred())
|
||||
Expect(resp2.Data[0].Embedding).To(Equal(sunEmbedding))
|
||||
Expect(resp2.Data[0].Embedding).ToNot(Equal(resp.Data[1].Embedding))
|
||||
})
|
||||
})
|
||||
|
||||
Context("backends", func() {
|
||||
It("runs rwkv", func() {
|
||||
It("runs rwkv completion", func() {
|
||||
if runtime.GOOS != "linux" {
|
||||
Skip("test supported only on linux")
|
||||
}
|
||||
resp, err := client.CreateCompletion(context.TODO(), openai.CompletionRequest{Model: "rwkv_test", Prompt: "Count up to five: one, two, three, four,"})
|
||||
Expect(err).ToNot(HaveOccurred())
|
||||
Expect(len(resp.Choices) > 0).To(BeTrue())
|
||||
Expect(resp.Choices[0].Text).To(Equal(" five."))
|
||||
Expect(resp.Choices[0].Text).To(ContainSubstring("five"))
|
||||
|
||||
stream, err := client.CreateCompletionStream(context.TODO(), openai.CompletionRequest{
|
||||
Model: "rwkv_test", Prompt: "Count up to five: one, two, three, four,", Stream: true,
|
||||
})
|
||||
Expect(err).ToNot(HaveOccurred())
|
||||
defer stream.Close()
|
||||
|
||||
tokens := 0
|
||||
text := ""
|
||||
for {
|
||||
response, err := stream.Recv()
|
||||
if errors.Is(err, io.EOF) {
|
||||
break
|
||||
}
|
||||
|
||||
Expect(err).ToNot(HaveOccurred())
|
||||
text += response.Choices[0].Text
|
||||
tokens++
|
||||
}
|
||||
Expect(text).ToNot(BeEmpty())
|
||||
Expect(text).To(ContainSubstring("five"))
|
||||
Expect(tokens).ToNot(Or(Equal(1), Equal(0)))
|
||||
})
|
||||
It("runs rwkv chat completion", func() {
|
||||
if runtime.GOOS != "linux" {
|
||||
Skip("test supported only on linux")
|
||||
}
|
||||
resp, err := client.CreateChatCompletion(context.TODO(),
|
||||
openai.ChatCompletionRequest{Model: "rwkv_test", Messages: []openai.ChatCompletionMessage{{Content: "Can you count up to five?", Role: "user"}}})
|
||||
Expect(err).ToNot(HaveOccurred())
|
||||
Expect(len(resp.Choices) > 0).To(BeTrue())
|
||||
Expect(resp.Choices[0].Message.Content).To(Or(ContainSubstring("Sure"), ContainSubstring("five")))
|
||||
|
||||
stream, err := client.CreateChatCompletionStream(context.TODO(), openai.ChatCompletionRequest{Model: "rwkv_test", Messages: []openai.ChatCompletionMessage{{Content: "Can you count up to five?", Role: "user"}}})
|
||||
Expect(err).ToNot(HaveOccurred())
|
||||
defer stream.Close()
|
||||
|
||||
tokens := 0
|
||||
text := ""
|
||||
for {
|
||||
response, err := stream.Recv()
|
||||
if errors.Is(err, io.EOF) {
|
||||
break
|
||||
}
|
||||
|
||||
Expect(err).ToNot(HaveOccurred())
|
||||
text += response.Choices[0].Delta.Content
|
||||
tokens++
|
||||
}
|
||||
Expect(text).ToNot(BeEmpty())
|
||||
Expect(text).To(Or(ContainSubstring("Sure"), ContainSubstring("five")))
|
||||
|
||||
Expect(tokens).ToNot(Or(Equal(1), Equal(0)))
|
||||
})
|
||||
})
|
||||
})
|
||||
@@ -462,7 +793,12 @@ var _ = Describe("API test", func() {
|
||||
c, cancel = context.WithCancel(context.Background())
|
||||
|
||||
var err error
|
||||
app, err = App(WithContext(c), WithModelLoader(modelLoader), WithConfigFile(os.Getenv("CONFIG_FILE")))
|
||||
app, err = App(
|
||||
append(commonOpts,
|
||||
options.WithContext(c),
|
||||
options.WithModelLoader(modelLoader),
|
||||
options.WithConfigFile(os.Getenv("CONFIG_FILE")))...,
|
||||
)
|
||||
Expect(err).ToNot(HaveOccurred())
|
||||
go app.Listen("127.0.0.1:9090")
|
||||
|
||||
@@ -481,19 +817,14 @@ 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
|
||||
}
|
||||
59
api/backend/image.go
Normal file
59
api/backend/image.go
Normal file
@@ -0,0 +1,59 @@
|
||||
package backend
|
||||
|
||||
import (
|
||||
config "github.com/go-skynet/LocalAI/api/config"
|
||||
"github.com/go-skynet/LocalAI/api/options"
|
||||
"github.com/go-skynet/LocalAI/pkg/grpc/proto"
|
||||
model "github.com/go-skynet/LocalAI/pkg/model"
|
||||
)
|
||||
|
||||
func ImageGeneration(height, width, mode, step, seed int, positive_prompt, negative_prompt, src, dst string, loader *model.ModelLoader, c config.Config, o *options.Option) (func() error, error) {
|
||||
|
||||
opts := modelOpts(c, o, []model.Option{
|
||||
model.WithBackendString(c.Backend),
|
||||
model.WithAssetDir(o.AssetsDestination),
|
||||
model.WithThreads(uint32(c.Threads)),
|
||||
model.WithContext(o.Context),
|
||||
model.WithModel(c.Model),
|
||||
model.WithLoadGRPCLoadModelOpts(&proto.ModelOptions{
|
||||
CUDA: c.Diffusers.CUDA,
|
||||
SchedulerType: c.Diffusers.SchedulerType,
|
||||
PipelineType: c.Diffusers.PipelineType,
|
||||
CFGScale: c.Diffusers.CFGScale,
|
||||
LoraAdapter: c.LoraAdapter,
|
||||
LoraBase: c.LoraBase,
|
||||
IMG2IMG: c.Diffusers.IMG2IMG,
|
||||
CLIPModel: c.Diffusers.ClipModel,
|
||||
CLIPSubfolder: c.Diffusers.ClipSubFolder,
|
||||
CLIPSkip: int32(c.Diffusers.ClipSkip),
|
||||
}),
|
||||
})
|
||||
|
||||
inferenceModel, err := loader.BackendLoader(
|
||||
opts...,
|
||||
)
|
||||
if err != nil {
|
||||
return nil, err
|
||||
}
|
||||
|
||||
fn := func() error {
|
||||
_, err := inferenceModel.GenerateImage(
|
||||
o.Context,
|
||||
&proto.GenerateImageRequest{
|
||||
Height: int32(height),
|
||||
Width: int32(width),
|
||||
Mode: int32(mode),
|
||||
Step: int32(step),
|
||||
Seed: int32(seed),
|
||||
CLIPSkip: int32(c.Diffusers.ClipSkip),
|
||||
PositivePrompt: positive_prompt,
|
||||
NegativePrompt: negative_prompt,
|
||||
Dst: dst,
|
||||
Src: src,
|
||||
EnableParameters: c.Diffusers.EnableParameters,
|
||||
})
|
||||
return err
|
||||
}
|
||||
|
||||
return fn, nil
|
||||
}
|
||||
163
api/backend/llm.go
Normal file
163
api/backend/llm.go
Normal file
@@ -0,0 +1,163 @@
|
||||
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, loader *model.ModelLoader, c config.Config, o *options.Option, tokenCallback func(string, TokenUsage) bool) (func() (LLMResponse, error), error) {
|
||||
modelFile := c.Model
|
||||
|
||||
grpcOpts := gRPCModelOpts(c)
|
||||
|
||||
var inferenceModel *grpc.Client
|
||||
var err error
|
||||
|
||||
opts := modelOpts(c, o, []model.Option{
|
||||
model.WithLoadGRPCLoadModelOpts(grpcOpts),
|
||||
model.WithThreads(uint32(c.Threads)), // some models uses this to allocate threads during startup
|
||||
model.WithAssetDir(o.AssetsDestination),
|
||||
model.WithModel(modelFile),
|
||||
model.WithContext(o.Context),
|
||||
})
|
||||
|
||||
if c.Backend != "" {
|
||||
opts = append(opts, model.WithBackendString(c.Backend))
|
||||
}
|
||||
|
||||
// Check if the modelFile exists, if it doesn't try to load it from the gallery
|
||||
if o.AutoloadGalleries { // experimental
|
||||
if _, err := os.Stat(modelFile); os.IsNotExist(err) {
|
||||
utils.ResetDownloadTimers()
|
||||
// if we failed to load the model, we try to download it
|
||||
err := gallery.InstallModelFromGalleryByName(o.Galleries, modelFile, loader.ModelPath, gallery.GalleryModel{}, utils.DisplayDownloadFunction)
|
||||
if err != nil {
|
||||
return nil, err
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
if c.Backend == "" {
|
||||
inferenceModel, err = loader.GreedyLoader(opts...)
|
||||
} else {
|
||||
inferenceModel, err = loader.BackendLoader(opts...)
|
||||
}
|
||||
|
||||
if err != nil {
|
||||
return nil, err
|
||||
}
|
||||
|
||||
// in GRPC, the backend is supposed to answer to 1 single token if stream is not supported
|
||||
fn := func() (LLMResponse, error) {
|
||||
opts := gRPCPredictOpts(c, loader.ModelPath)
|
||||
opts.Prompt = s
|
||||
|
||||
tokenUsage := TokenUsage{}
|
||||
|
||||
// check the per-model feature flag for usage, since tokenCallback may have a cost.
|
||||
// Defaults to off as for now it is still experimental
|
||||
if c.FeatureFlag.Enabled("usage") {
|
||||
userTokenCallback := tokenCallback
|
||||
if userTokenCallback == nil {
|
||||
userTokenCallback = func(token string, usage TokenUsage) bool {
|
||||
return true
|
||||
}
|
||||
}
|
||||
|
||||
promptInfo, pErr := inferenceModel.TokenizeString(ctx, opts)
|
||||
if pErr == nil && promptInfo.Length > 0 {
|
||||
tokenUsage.Prompt = int(promptInfo.Length)
|
||||
}
|
||||
|
||||
tokenCallback = func(token string, usage TokenUsage) bool {
|
||||
tokenUsage.Completion++
|
||||
return userTokenCallback(token, tokenUsage)
|
||||
}
|
||||
}
|
||||
|
||||
if tokenCallback != nil {
|
||||
ss := ""
|
||||
|
||||
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
|
||||
|
||||
}
|
||||
116
api/backend/options.go
Normal file
116
api/backend/options.go
Normal file
@@ -0,0 +1,116 @@
|
||||
package backend
|
||||
|
||||
import (
|
||||
"os"
|
||||
"path/filepath"
|
||||
|
||||
pb "github.com/go-skynet/LocalAI/pkg/grpc/proto"
|
||||
model "github.com/go-skynet/LocalAI/pkg/model"
|
||||
|
||||
config "github.com/go-skynet/LocalAI/api/config"
|
||||
"github.com/go-skynet/LocalAI/api/options"
|
||||
)
|
||||
|
||||
func modelOpts(c config.Config, o *options.Option, opts []model.Option) []model.Option {
|
||||
if o.SingleBackend {
|
||||
opts = append(opts, model.WithSingleActiveBackend())
|
||||
}
|
||||
|
||||
if c.GRPC.Attempts != 0 {
|
||||
opts = append(opts, model.WithGRPCAttempts(c.GRPC.Attempts))
|
||||
}
|
||||
|
||||
if c.GRPC.AttemptsSleepTime != 0 {
|
||||
opts = append(opts, model.WithGRPCAttemptsDelay(c.GRPC.AttemptsSleepTime))
|
||||
}
|
||||
|
||||
for k, v := range o.ExternalGRPCBackends {
|
||||
opts = append(opts, model.WithExternalBackend(k, v))
|
||||
}
|
||||
|
||||
return opts
|
||||
}
|
||||
|
||||
func gRPCModelOpts(c config.Config) *pb.ModelOptions {
|
||||
b := 512
|
||||
if c.Batch != 0 {
|
||||
b = c.Batch
|
||||
}
|
||||
|
||||
return &pb.ModelOptions{
|
||||
ContextSize: int32(c.ContextSize),
|
||||
Seed: int32(c.Seed),
|
||||
NBatch: int32(b),
|
||||
NoMulMatQ: c.NoMulMatQ,
|
||||
DraftModel: c.DraftModel,
|
||||
AudioPath: c.VallE.AudioPath,
|
||||
Quantization: c.Quantization,
|
||||
LoraAdapter: c.LoraAdapter,
|
||||
LoraBase: c.LoraBase,
|
||||
NGQA: c.NGQA,
|
||||
RMSNormEps: c.RMSNormEps,
|
||||
F16Memory: c.F16,
|
||||
MLock: c.MMlock,
|
||||
RopeFreqBase: c.RopeFreqBase,
|
||||
RopeFreqScale: c.RopeFreqScale,
|
||||
NUMA: c.NUMA,
|
||||
Embeddings: c.Embeddings,
|
||||
LowVRAM: c.LowVRAM,
|
||||
NGPULayers: int32(c.NGPULayers),
|
||||
MMap: c.MMap,
|
||||
MainGPU: c.MainGPU,
|
||||
Threads: int32(c.Threads),
|
||||
TensorSplit: c.TensorSplit,
|
||||
// AutoGPTQ
|
||||
ModelBaseName: c.AutoGPTQ.ModelBaseName,
|
||||
Device: c.AutoGPTQ.Device,
|
||||
UseTriton: c.AutoGPTQ.Triton,
|
||||
UseFastTokenizer: c.AutoGPTQ.UseFastTokenizer,
|
||||
// RWKV
|
||||
Tokenizer: c.Tokenizer,
|
||||
}
|
||||
}
|
||||
|
||||
func gRPCPredictOpts(c config.Config, modelPath string) *pb.PredictOptions {
|
||||
promptCachePath := ""
|
||||
if c.PromptCachePath != "" {
|
||||
p := filepath.Join(modelPath, c.PromptCachePath)
|
||||
os.MkdirAll(filepath.Dir(p), 0755)
|
||||
promptCachePath = p
|
||||
}
|
||||
return &pb.PredictOptions{
|
||||
Temperature: float32(c.Temperature),
|
||||
TopP: float32(c.TopP),
|
||||
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),
|
||||
})
|
||||
}
|
||||
75
api/backend/tts.go
Normal file
75
api/backend/tts.go
Normal file
@@ -0,0 +1,75 @@
|
||||
package backend
|
||||
|
||||
import (
|
||||
"context"
|
||||
"fmt"
|
||||
"os"
|
||||
"path/filepath"
|
||||
|
||||
api_config "github.com/go-skynet/LocalAI/api/config"
|
||||
"github.com/go-skynet/LocalAI/api/options"
|
||||
"github.com/go-skynet/LocalAI/pkg/grpc/proto"
|
||||
model "github.com/go-skynet/LocalAI/pkg/model"
|
||||
"github.com/go-skynet/LocalAI/pkg/utils"
|
||||
)
|
||||
|
||||
func generateUniqueFileName(dir, baseName, ext string) string {
|
||||
counter := 1
|
||||
fileName := baseName + ext
|
||||
|
||||
for {
|
||||
filePath := filepath.Join(dir, fileName)
|
||||
_, err := os.Stat(filePath)
|
||||
if os.IsNotExist(err) {
|
||||
return fileName
|
||||
}
|
||||
|
||||
counter++
|
||||
fileName = fmt.Sprintf("%s_%d%s", baseName, counter, ext)
|
||||
}
|
||||
}
|
||||
|
||||
func ModelTTS(backend, text, modelFile string, loader *model.ModelLoader, o *options.Option) (string, *proto.Result, error) {
|
||||
bb := backend
|
||||
if bb == "" {
|
||||
bb = model.PiperBackend
|
||||
}
|
||||
opts := modelOpts(api_config.Config{}, o, []model.Option{
|
||||
model.WithBackendString(bb),
|
||||
model.WithModel(modelFile),
|
||||
model.WithContext(o.Context),
|
||||
model.WithAssetDir(o.AssetsDestination),
|
||||
})
|
||||
piperModel, err := o.Loader.BackendLoader(opts...)
|
||||
if err != nil {
|
||||
return "", nil, err
|
||||
}
|
||||
|
||||
if piperModel == nil {
|
||||
return "", nil, fmt.Errorf("could not load piper model")
|
||||
}
|
||||
|
||||
if err := os.MkdirAll(o.AudioDir, 0755); err != nil {
|
||||
return "", nil, fmt.Errorf("failed creating audio directory: %s", err)
|
||||
}
|
||||
|
||||
fileName := generateUniqueFileName(o.AudioDir, "piper", ".wav")
|
||||
filePath := filepath.Join(o.AudioDir, fileName)
|
||||
|
||||
// If the model file is not empty, we pass it joined with the model path
|
||||
modelPath := ""
|
||||
if modelFile != "" {
|
||||
modelPath = filepath.Join(o.Loader.ModelPath, modelFile)
|
||||
if err := utils.VerifyPath(modelPath, o.Loader.ModelPath); err != nil {
|
||||
return "", nil, err
|
||||
}
|
||||
}
|
||||
|
||||
res, err := piperModel.TTS(context.Background(), &proto.TTSRequest{
|
||||
Text: text,
|
||||
Model: modelPath,
|
||||
Dst: filePath,
|
||||
})
|
||||
|
||||
return filePath, res, err
|
||||
}
|
||||
368
api/config.go
368
api/config.go
@@ -1,368 +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"`
|
||||
NUMA bool `yaml:"numa"`
|
||||
Threads int `yaml:"threads"`
|
||||
Debug bool `yaml:"debug"`
|
||||
Roles map[string]string `yaml:"roles"`
|
||||
Embeddings bool `yaml:"embeddings"`
|
||||
Backend string `yaml:"backend"`
|
||||
TemplateConfig TemplateConfig `yaml:"template"`
|
||||
MirostatETA float64 `yaml:"mirostat_eta"`
|
||||
MirostatTAU float64 `yaml:"mirostat_tau"`
|
||||
Mirostat int `yaml:"mirostat"`
|
||||
NGPULayers int `yaml:"gpu_layers"`
|
||||
MMap bool `yaml:"mmap"`
|
||||
MMlock bool `yaml:"mmlock"`
|
||||
LowVRAM bool `yaml:"low_vram"`
|
||||
|
||||
TensorSplit string `yaml:"tensor_split"`
|
||||
MainGPU string `yaml:"main_gpu"`
|
||||
ImageGenerationAssets string `yaml:"asset_dir"`
|
||||
|
||||
PromptCachePath string `yaml:"prompt_cache_path"`
|
||||
PromptCacheAll bool `yaml:"prompt_cache_all"`
|
||||
PromptCacheRO bool `yaml:"prompt_cache_ro"`
|
||||
|
||||
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")
|
||||
|
||||
var config *Config
|
||||
|
||||
defaults := func() {
|
||||
config = defaultConfig(modelFile)
|
||||
config.ContextSize = ctx
|
||||
config.Threads = threads
|
||||
config.F16 = f16
|
||||
config.Debug = debug
|
||||
}
|
||||
|
||||
cfg, 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())
|
||||
}
|
||||
cfg, exists = cm.GetConfig(modelFile)
|
||||
if exists {
|
||||
config = &cfg
|
||||
} else {
|
||||
defaults()
|
||||
}
|
||||
} else {
|
||||
defaults()
|
||||
}
|
||||
} 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
|
||||
}
|
||||
282
api/config/config.go
Normal file
282
api/config/config.go
Normal file
@@ -0,0 +1,282 @@
|
||||
package api_config
|
||||
|
||||
import (
|
||||
"fmt"
|
||||
"io/fs"
|
||||
"os"
|
||||
"path/filepath"
|
||||
"strings"
|
||||
"sync"
|
||||
|
||||
"gopkg.in/yaml.v3"
|
||||
)
|
||||
|
||||
type Config struct {
|
||||
PredictionOptions `yaml:"parameters"`
|
||||
Name string `yaml:"name"`
|
||||
|
||||
F16 bool `yaml:"f16"`
|
||||
Threads int `yaml:"threads"`
|
||||
Debug bool `yaml:"debug"`
|
||||
Roles map[string]string `yaml:"roles"`
|
||||
Embeddings bool `yaml:"embeddings"`
|
||||
Backend string `yaml:"backend"`
|
||||
TemplateConfig TemplateConfig `yaml:"template"`
|
||||
|
||||
PromptStrings, InputStrings []string `yaml:"-"`
|
||||
InputToken [][]int `yaml:"-"`
|
||||
functionCallString, functionCallNameString string `yaml:"-"`
|
||||
|
||||
FunctionsConfig Functions `yaml:"function"`
|
||||
|
||||
FeatureFlag FeatureFlag `yaml:"feature_flags"` // Feature Flag registry. We move fast, and features may break on a per model/backend basis. Registry for (usually temporary) flags that indicate aborting something early.
|
||||
// LLM configs (GPT4ALL, Llama.cpp, ...)
|
||||
LLMConfig `yaml:",inline"`
|
||||
|
||||
// AutoGPTQ specifics
|
||||
AutoGPTQ AutoGPTQ `yaml:"autogptq"`
|
||||
|
||||
// Diffusers
|
||||
Diffusers Diffusers `yaml:"diffusers"`
|
||||
|
||||
Step int `yaml:"step"`
|
||||
|
||||
// GRPC Options
|
||||
GRPC GRPC `yaml:"grpc"`
|
||||
|
||||
// Vall-e-x
|
||||
VallE VallE `yaml:"vall-e"`
|
||||
}
|
||||
|
||||
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 {
|
||||
PipelineType string `yaml:"pipeline_type"`
|
||||
SchedulerType string `yaml:"scheduler_type"`
|
||||
CUDA bool `yaml:"cuda"`
|
||||
EnableParameters string `yaml:"enable_parameters"` // A list of comma separated parameters to specify
|
||||
CFGScale float32 `yaml:"cfg_scale"` // Classifier-Free Guidance Scale
|
||||
IMG2IMG bool `yaml:"img2img"` // Image to Image Diffuser
|
||||
ClipSkip int `yaml:"clip_skip"` // Skip every N frames
|
||||
ClipModel string `yaml:"clip_model"` // Clip model to use
|
||||
ClipSubFolder string `yaml:"clip_subfolder"` // Subfolder to use for clip model
|
||||
}
|
||||
|
||||
type LLMConfig struct {
|
||||
SystemPrompt string `yaml:"system_prompt"`
|
||||
TensorSplit string `yaml:"tensor_split"`
|
||||
MainGPU string `yaml:"main_gpu"`
|
||||
RMSNormEps float32 `yaml:"rms_norm_eps"`
|
||||
NGQA int32 `yaml:"ngqa"`
|
||||
PromptCachePath string `yaml:"prompt_cache_path"`
|
||||
PromptCacheAll bool `yaml:"prompt_cache_all"`
|
||||
PromptCacheRO bool `yaml:"prompt_cache_ro"`
|
||||
MirostatETA float64 `yaml:"mirostat_eta"`
|
||||
MirostatTAU float64 `yaml:"mirostat_tau"`
|
||||
Mirostat int `yaml:"mirostat"`
|
||||
NGPULayers int `yaml:"gpu_layers"`
|
||||
MMap bool `yaml:"mmap"`
|
||||
MMlock bool `yaml:"mmlock"`
|
||||
LowVRAM bool `yaml:"low_vram"`
|
||||
Grammar string `yaml:"grammar"`
|
||||
StopWords []string `yaml:"stopwords"`
|
||||
Cutstrings []string `yaml:"cutstrings"`
|
||||
TrimSpace []string `yaml:"trimspace"`
|
||||
ContextSize int `yaml:"context_size"`
|
||||
NUMA bool `yaml:"numa"`
|
||||
LoraAdapter string `yaml:"lora_adapter"`
|
||||
LoraBase string `yaml:"lora_base"`
|
||||
NoMulMatQ bool `yaml:"no_mulmatq"`
|
||||
DraftModel string `yaml:"draft_model"`
|
||||
NDraft int32 `yaml:"n_draft"`
|
||||
Quantization string `yaml:"quantization"`
|
||||
}
|
||||
|
||||
type AutoGPTQ struct {
|
||||
ModelBaseName string `yaml:"model_base_name"`
|
||||
Device string `yaml:"device"`
|
||||
Triton bool `yaml:"triton"`
|
||||
UseFastTokenizer bool `yaml:"use_fast_tokenizer"`
|
||||
}
|
||||
|
||||
type Functions struct {
|
||||
DisableNoAction bool `yaml:"disable_no_action"`
|
||||
NoActionFunctionName string `yaml:"no_action_function_name"`
|
||||
NoActionDescriptionName string `yaml:"no_action_description_name"`
|
||||
}
|
||||
|
||||
type TemplateConfig struct {
|
||||
Chat string `yaml:"chat"`
|
||||
ChatMessage string `yaml:"chat_message"`
|
||||
Completion string `yaml:"completion"`
|
||||
Edit string `yaml:"edit"`
|
||||
Functions string `yaml:"function"`
|
||||
}
|
||||
|
||||
type ConfigLoader struct {
|
||||
configs map[string]Config
|
||||
sync.Mutex
|
||||
}
|
||||
|
||||
func (c *Config) SetFunctionCallString(s string) {
|
||||
c.functionCallString = s
|
||||
}
|
||||
|
||||
func (c *Config) SetFunctionCallNameString(s string) {
|
||||
c.functionCallNameString = s
|
||||
}
|
||||
|
||||
func (c *Config) ShouldUseFunctions() bool {
|
||||
return ((c.functionCallString != "none" || c.functionCallString == "") || c.ShouldCallSpecificFunction())
|
||||
}
|
||||
|
||||
func (c *Config) ShouldCallSpecificFunction() bool {
|
||||
return len(c.functionCallNameString) > 0
|
||||
}
|
||||
|
||||
func (c *Config) FunctionToCall() string {
|
||||
return c.functionCallNameString
|
||||
}
|
||||
|
||||
func defaultPredictOptions(modelFile string) PredictionOptions {
|
||||
return PredictionOptions{
|
||||
TopP: 0.7,
|
||||
TopK: 80,
|
||||
Maxtokens: 512,
|
||||
Temperature: 0.9,
|
||||
Model: modelFile,
|
||||
}
|
||||
}
|
||||
|
||||
func DefaultConfig(modelFile string) *Config {
|
||||
return &Config{
|
||||
PredictionOptions: defaultPredictOptions(modelFile),
|
||||
}
|
||||
}
|
||||
|
||||
func NewConfigLoader() *ConfigLoader {
|
||||
return &ConfigLoader{
|
||||
configs: make(map[string]Config),
|
||||
}
|
||||
}
|
||||
func ReadConfigFile(file string) ([]*Config, error) {
|
||||
c := &[]*Config{}
|
||||
f, err := os.ReadFile(file)
|
||||
if err != nil {
|
||||
return nil, fmt.Errorf("cannot read config file: %w", err)
|
||||
}
|
||||
if err := yaml.Unmarshal(f, c); err != nil {
|
||||
return nil, fmt.Errorf("cannot unmarshal config file: %w", err)
|
||||
}
|
||||
|
||||
return *c, nil
|
||||
}
|
||||
|
||||
func ReadConfig(file string) (*Config, error) {
|
||||
c := &Config{}
|
||||
f, err := os.ReadFile(file)
|
||||
if err != nil {
|
||||
return nil, fmt.Errorf("cannot read config file: %w", err)
|
||||
}
|
||||
if err := yaml.Unmarshal(f, c); err != nil {
|
||||
return nil, fmt.Errorf("cannot unmarshal config file: %w", err)
|
||||
}
|
||||
|
||||
return c, nil
|
||||
}
|
||||
|
||||
func (cm *ConfigLoader) LoadConfigFile(file string) error {
|
||||
cm.Lock()
|
||||
defer cm.Unlock()
|
||||
c, err := ReadConfigFile(file)
|
||||
if err != nil {
|
||||
return fmt.Errorf("cannot load config file: %w", err)
|
||||
}
|
||||
|
||||
for _, cc := range c {
|
||||
cm.configs[cc.Name] = *cc
|
||||
}
|
||||
return nil
|
||||
}
|
||||
|
||||
func (cm *ConfigLoader) LoadConfig(file string) error {
|
||||
cm.Lock()
|
||||
defer cm.Unlock()
|
||||
c, err := ReadConfig(file)
|
||||
if err != nil {
|
||||
return fmt.Errorf("cannot read config file: %w", err)
|
||||
}
|
||||
|
||||
cm.configs[c.Name] = *c
|
||||
return nil
|
||||
}
|
||||
|
||||
func (cm *ConfigLoader) GetConfig(m string) (Config, bool) {
|
||||
cm.Lock()
|
||||
defer cm.Unlock()
|
||||
v, exists := cm.configs[m]
|
||||
return v, exists
|
||||
}
|
||||
|
||||
func (cm *ConfigLoader) GetAllConfigs() []Config {
|
||||
cm.Lock()
|
||||
defer cm.Unlock()
|
||||
var res []Config
|
||||
for _, v := range cm.configs {
|
||||
res = append(res, v)
|
||||
}
|
||||
return res
|
||||
}
|
||||
|
||||
func (cm *ConfigLoader) ListConfigs() []string {
|
||||
cm.Lock()
|
||||
defer cm.Unlock()
|
||||
var res []string
|
||||
for k := range cm.configs {
|
||||
res = append(res, k)
|
||||
}
|
||||
return res
|
||||
}
|
||||
|
||||
func (cm *ConfigLoader) LoadConfigs(path string) error {
|
||||
cm.Lock()
|
||||
defer cm.Unlock()
|
||||
entries, err := os.ReadDir(path)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
files := make([]fs.FileInfo, 0, len(entries))
|
||||
for _, entry := range entries {
|
||||
info, err := entry.Info()
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
files = append(files, info)
|
||||
}
|
||||
for _, file := range files {
|
||||
// Skip templates, YAML and .keep files
|
||||
if !strings.Contains(file.Name(), ".yaml") {
|
||||
continue
|
||||
}
|
||||
c, err := ReadConfig(filepath.Join(path, file.Name()))
|
||||
if err == nil {
|
||||
cm.configs[c.Name] = *c
|
||||
}
|
||||
}
|
||||
|
||||
return nil
|
||||
}
|
||||
@@ -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"`
|
||||
}
|
||||
237
api/gallery.go
237
api/gallery.go
@@ -1,237 +0,0 @@
|
||||
package api
|
||||
|
||||
import (
|
||||
"context"
|
||||
"fmt"
|
||||
"os"
|
||||
"sync"
|
||||
"time"
|
||||
|
||||
json "github.com/json-iterator/go"
|
||||
|
||||
"github.com/go-skynet/LocalAI/pkg/gallery"
|
||||
"github.com/gofiber/fiber/v2"
|
||||
"github.com/google/uuid"
|
||||
"github.com/rs/zerolog/log"
|
||||
)
|
||||
|
||||
type galleryOp struct {
|
||||
req gallery.GalleryModel
|
||||
id string
|
||||
galleries []gallery.Gallery
|
||||
galleryName string
|
||||
}
|
||||
|
||||
type galleryOpStatus struct {
|
||||
Error error `json:"error"`
|
||||
Processed bool `json:"processed"`
|
||||
Message string `json:"message"`
|
||||
Progress float64 `json:"progress"`
|
||||
TotalFileSize string `json:"file_size"`
|
||||
DownloadedFileSize string `json:"downloaded_size"`
|
||||
}
|
||||
|
||||
type galleryApplier struct {
|
||||
modelPath string
|
||||
sync.Mutex
|
||||
C chan galleryOp
|
||||
statuses map[string]*galleryOpStatus
|
||||
}
|
||||
|
||||
func newGalleryApplier(modelPath string) *galleryApplier {
|
||||
return &galleryApplier{
|
||||
modelPath: modelPath,
|
||||
C: make(chan galleryOp),
|
||||
statuses: make(map[string]*galleryOpStatus),
|
||||
}
|
||||
}
|
||||
|
||||
// prepareModel applies a
|
||||
func prepareModel(modelPath string, req gallery.GalleryModel, cm *ConfigMerger, downloadStatus func(string, string, string, float64)) error {
|
||||
|
||||
config, err := gallery.GetGalleryConfigFromURL(req.URL)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
|
||||
config.Files = append(config.Files, req.AdditionalFiles...)
|
||||
|
||||
return gallery.InstallModel(modelPath, req.Name, &config, req.Overrides, downloadStatus)
|
||||
}
|
||||
|
||||
func (g *galleryApplier) updateStatus(s string, op *galleryOpStatus) {
|
||||
g.Lock()
|
||||
defer g.Unlock()
|
||||
g.statuses[s] = op
|
||||
}
|
||||
|
||||
func (g *galleryApplier) getStatus(s string) *galleryOpStatus {
|
||||
g.Lock()
|
||||
defer g.Unlock()
|
||||
|
||||
return g.statuses[s]
|
||||
}
|
||||
|
||||
func (g *galleryApplier) start(c context.Context, cm *ConfigMerger) {
|
||||
go func() {
|
||||
for {
|
||||
select {
|
||||
case <-c.Done():
|
||||
return
|
||||
case op := <-g.C:
|
||||
g.updateStatus(op.id, &galleryOpStatus{Message: "processing", Progress: 0})
|
||||
|
||||
// updates the status with an error
|
||||
updateError := func(e error) {
|
||||
g.updateStatus(op.id, &galleryOpStatus{Error: e, Processed: true, Message: "error: " + e.Error()})
|
||||
}
|
||||
|
||||
// displayDownload displays the download progress
|
||||
progressCallback := func(fileName string, current string, total string, percentage float64) {
|
||||
g.updateStatus(op.id, &galleryOpStatus{Message: "processing", Progress: percentage, TotalFileSize: total, DownloadedFileSize: current})
|
||||
displayDownload(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 != "" {
|
||||
err = gallery.InstallModelFromGallery(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})
|
||||
}
|
||||
}
|
||||
}()
|
||||
}
|
||||
|
||||
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)
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
type galleryModel struct {
|
||||
gallery.GalleryModel
|
||||
ID string `json:"id"`
|
||||
}
|
||||
|
||||
func ApplyGalleryFromFile(modelPath, s string, cm *ConfigMerger, galleries []gallery.Gallery) error {
|
||||
dat, err := os.ReadFile(s)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
return ApplyGalleryFromString(modelPath, string(dat), cm, galleries)
|
||||
}
|
||||
|
||||
func ApplyGalleryFromString(modelPath, s string, cm *ConfigMerger, galleries []gallery.Gallery) error {
|
||||
var requests []galleryModel
|
||||
err := json.Unmarshal([]byte(s), &requests)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
|
||||
for _, r := range requests {
|
||||
if r.ID == "" {
|
||||
err = prepareModel(modelPath, r.GalleryModel, cm, displayDownload)
|
||||
} else {
|
||||
err = gallery.InstallModelFromGallery(galleries, r.ID, modelPath, r.GalleryModel, displayDownload)
|
||||
}
|
||||
}
|
||||
|
||||
return err
|
||||
}
|
||||
|
||||
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)
|
||||
}
|
||||
}
|
||||
|
||||
type GalleryModel struct {
|
||||
ID string `json:"id"`
|
||||
gallery.GalleryModel
|
||||
}
|
||||
|
||||
func applyModelGallery(modelPath string, cm *ConfigMerger, g chan galleryOp, galleries []gallery.Gallery) func(c *fiber.Ctx) error {
|
||||
return func(c *fiber.Ctx) error {
|
||||
input := new(GalleryModel)
|
||||
// Get input data from the request body
|
||||
if err := c.BodyParser(input); err != nil {
|
||||
return err
|
||||
}
|
||||
|
||||
uuid, err := uuid.NewUUID()
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
g <- galleryOp{
|
||||
req: input.GalleryModel,
|
||||
id: uuid.String(),
|
||||
galleryName: input.ID,
|
||||
galleries: galleries,
|
||||
}
|
||||
return c.JSON(struct {
|
||||
ID string `json:"uuid"`
|
||||
StatusURL string `json:"status"`
|
||||
}{ID: uuid.String(), StatusURL: c.BaseURL() + "/models/jobs/" + uuid.String()})
|
||||
}
|
||||
}
|
||||
|
||||
func listModelFromGallery(galleries []gallery.Gallery, basePath string) func(c *fiber.Ctx) error {
|
||||
return func(c *fiber.Ctx) error {
|
||||
log.Debug().Msgf("Listing models from galleries: %+v", galleries)
|
||||
|
||||
models, err := gallery.AvailableGalleryModels(galleries, basePath)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
log.Debug().Msgf("Models found from galleries: %+v", models)
|
||||
for _, m := range models {
|
||||
log.Debug().Msgf("Model found from galleries: %+v", m)
|
||||
}
|
||||
dat, err := json.Marshal(models)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
return c.Send(dat)
|
||||
}
|
||||
}
|
||||
@@ -1,78 +0,0 @@
|
||||
package api
|
||||
|
||||
import (
|
||||
"fmt"
|
||||
"os"
|
||||
"path/filepath"
|
||||
|
||||
model "github.com/go-skynet/LocalAI/pkg/model"
|
||||
"github.com/go-skynet/LocalAI/pkg/tts"
|
||||
"github.com/go-skynet/LocalAI/pkg/utils"
|
||||
llama "github.com/go-skynet/go-llama.cpp"
|
||||
"github.com/gofiber/fiber/v2"
|
||||
)
|
||||
|
||||
type TTSRequest struct {
|
||||
Model string `json:"model" yaml:"model"`
|
||||
Input string `json:"input" yaml:"input"`
|
||||
}
|
||||
|
||||
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 ttsEndpoint(cm *ConfigMerger, o *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
|
||||
}
|
||||
|
||||
piperModel, err := o.loader.BackendLoader(model.PiperBackend, input.Model, []llama.ModelOption{}, uint32(0), o.assetsDestination)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
|
||||
if piperModel == nil {
|
||||
return fmt.Errorf("could not load piper model")
|
||||
}
|
||||
|
||||
w, ok := piperModel.(*tts.Piper)
|
||||
if !ok {
|
||||
return fmt.Errorf("loader returned non-piper object %+v", w)
|
||||
}
|
||||
|
||||
if err := os.MkdirAll(o.audioDir, 0755); err != nil {
|
||||
return err
|
||||
}
|
||||
|
||||
fileName := generateUniqueFileName(o.audioDir, "piper", ".wav")
|
||||
filePath := filepath.Join(o.audioDir, fileName)
|
||||
|
||||
modelPath := filepath.Join(o.loader.ModelPath, input.Model)
|
||||
|
||||
if err := utils.VerifyPath(modelPath, o.loader.ModelPath); err != nil {
|
||||
return err
|
||||
}
|
||||
|
||||
if err := w.TTS(input.Input, modelPath, filePath); err != nil {
|
||||
return err
|
||||
}
|
||||
|
||||
return c.Download(filePath)
|
||||
}
|
||||
}
|
||||
163
api/localai/backend_monitor.go
Normal file
163
api/localai/backend_monitor.go
Normal file
@@ -0,0 +1,163 @@
|
||||
package localai
|
||||
|
||||
import (
|
||||
"context"
|
||||
"fmt"
|
||||
"strings"
|
||||
|
||||
config "github.com/go-skynet/LocalAI/api/config"
|
||||
"github.com/go-skynet/LocalAI/pkg/grpc/proto"
|
||||
|
||||
"github.com/go-skynet/LocalAI/api/options"
|
||||
"github.com/gofiber/fiber/v2"
|
||||
"github.com/rs/zerolog/log"
|
||||
|
||||
gopsutil "github.com/shirou/gopsutil/v3/process"
|
||||
)
|
||||
|
||||
type BackendMonitorRequest struct {
|
||||
Model string `json:"model" yaml:"model"`
|
||||
}
|
||||
|
||||
type BackendMonitorResponse struct {
|
||||
MemoryInfo *gopsutil.MemoryInfoStat
|
||||
MemoryPercent float32
|
||||
CPUPercent float64
|
||||
}
|
||||
|
||||
type BackendMonitor struct {
|
||||
configLoader *config.ConfigLoader
|
||||
options *options.Option // Taking options in case we need to inspect ExternalGRPCBackends, though that's out of scope for now, hence the name.
|
||||
}
|
||||
|
||||
func NewBackendMonitor(configLoader *config.ConfigLoader, options *options.Option) BackendMonitor {
|
||||
return BackendMonitor{
|
||||
configLoader: configLoader,
|
||||
options: options,
|
||||
}
|
||||
}
|
||||
|
||||
func (bm *BackendMonitor) SampleLocalBackendProcess(model string) (*BackendMonitorResponse, error) {
|
||||
config, exists := bm.configLoader.GetConfig(model)
|
||||
var backend string
|
||||
if exists {
|
||||
backend = config.Model
|
||||
} else {
|
||||
// Last ditch effort: use it raw, see if a backend happens to match.
|
||||
backend = model
|
||||
}
|
||||
|
||||
if !strings.HasSuffix(backend, ".bin") {
|
||||
backend = fmt.Sprintf("%s.bin", backend)
|
||||
}
|
||||
|
||||
pid, err := bm.options.Loader.GetGRPCPID(backend)
|
||||
|
||||
if err != nil {
|
||||
log.Error().Msgf("model %s : failed to find pid %+v", model, err)
|
||||
return nil, err
|
||||
}
|
||||
|
||||
// Name is slightly frightening but this does _not_ create a new process, rather it looks up an existing process by PID.
|
||||
backendProcess, err := gopsutil.NewProcess(int32(pid))
|
||||
|
||||
if err != nil {
|
||||
log.Error().Msgf("model %s [PID %d] : error getting process info %+v", model, pid, err)
|
||||
return nil, err
|
||||
}
|
||||
|
||||
memInfo, err := backendProcess.MemoryInfo()
|
||||
|
||||
if err != nil {
|
||||
log.Error().Msgf("model %s [PID %d] : error getting memory info %+v", model, pid, err)
|
||||
return nil, err
|
||||
}
|
||||
|
||||
memPercent, err := backendProcess.MemoryPercent()
|
||||
if err != nil {
|
||||
log.Error().Msgf("model %s [PID %d] : error getting memory percent %+v", model, pid, err)
|
||||
return nil, err
|
||||
}
|
||||
|
||||
cpuPercent, err := backendProcess.CPUPercent()
|
||||
if err != nil {
|
||||
log.Error().Msgf("model %s [PID %d] : error getting cpu percent %+v", model, pid, err)
|
||||
return nil, err
|
||||
}
|
||||
|
||||
return &BackendMonitorResponse{
|
||||
MemoryInfo: memInfo,
|
||||
MemoryPercent: memPercent,
|
||||
CPUPercent: cpuPercent,
|
||||
}, nil
|
||||
}
|
||||
|
||||
func (bm BackendMonitor) getModelLoaderIDFromCtx(c *fiber.Ctx) (string, error) {
|
||||
input := new(BackendMonitorRequest)
|
||||
// Get input data from the request body
|
||||
if err := c.BodyParser(input); err != nil {
|
||||
return "", err
|
||||
}
|
||||
|
||||
config, exists := bm.configLoader.GetConfig(input.Model)
|
||||
var backendId string
|
||||
if exists {
|
||||
backendId = config.Model
|
||||
} else {
|
||||
// Last ditch effort: use it raw, see if a backend happens to match.
|
||||
backendId = input.Model
|
||||
}
|
||||
|
||||
if !strings.HasSuffix(backendId, ".bin") {
|
||||
backendId = fmt.Sprintf("%s.bin", backendId)
|
||||
}
|
||||
|
||||
return backendId, nil
|
||||
}
|
||||
|
||||
func BackendMonitorEndpoint(bm BackendMonitor) func(c *fiber.Ctx) error {
|
||||
return func(c *fiber.Ctx) error {
|
||||
|
||||
backendId, err := bm.getModelLoaderIDFromCtx(c)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
|
||||
client := bm.options.Loader.CheckIsLoaded(backendId)
|
||||
|
||||
if client == nil {
|
||||
return fmt.Errorf("backend %s is not currently loaded", backendId)
|
||||
}
|
||||
|
||||
status, rpcErr := client.Status(context.TODO())
|
||||
if rpcErr != nil {
|
||||
log.Warn().Msgf("backend %s experienced an error retrieving status info: %s", backendId, rpcErr.Error())
|
||||
val, slbErr := bm.SampleLocalBackendProcess(backendId)
|
||||
if slbErr != nil {
|
||||
return fmt.Errorf("backend %s experienced an error retrieving status info via rpc: %s, then failed local node process sample: %s", backendId, rpcErr.Error(), slbErr.Error())
|
||||
}
|
||||
return c.JSON(proto.StatusResponse{
|
||||
State: proto.StatusResponse_ERROR,
|
||||
Memory: &proto.MemoryUsageData{
|
||||
Total: val.MemoryInfo.VMS,
|
||||
Breakdown: map[string]uint64{
|
||||
"gopsutil-RSS": val.MemoryInfo.RSS,
|
||||
},
|
||||
},
|
||||
})
|
||||
}
|
||||
|
||||
return c.JSON(status)
|
||||
}
|
||||
}
|
||||
|
||||
func BackendShutdownEndpoint(bm BackendMonitor) func(c *fiber.Ctx) error {
|
||||
return func(c *fiber.Ctx) error {
|
||||
backendId, err := bm.getModelLoaderIDFromCtx(c)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
|
||||
return bm.options.Loader.ShutdownModel(backendId)
|
||||
}
|
||||
}
|
||||
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)
|
||||
}
|
||||
}
|
||||
772
api/openai.go
772
api/openai.go
@@ -1,772 +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{
|
||||
{
|
||||
Index: 0,
|
||||
Text: s,
|
||||
},
|
||||
},
|
||||
Object: "text_completion",
|
||||
}
|
||||
log.Debug().Msgf("Sending goroutine: %s", s)
|
||||
|
||||
responses <- resp
|
||||
return true
|
||||
})
|
||||
close(responses)
|
||||
}
|
||||
|
||||
return func(c *fiber.Ctx) error {
|
||||
model, input, err := readInput(c, o.loader, true)
|
||||
if err != nil {
|
||||
return fmt.Errorf("failed reading parameters from request:%w", err)
|
||||
}
|
||||
|
||||
log.Debug().Msgf("`input`: %+v", input)
|
||||
|
||||
config, input, err := readConfig(model, input, cm, o.loader, o.debug, o.threads, o.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{
|
||||
{
|
||||
Index: 0,
|
||||
FinishReason: "stop",
|
||||
},
|
||||
},
|
||||
Object: "text_completion",
|
||||
}
|
||||
respData, _ := json.Marshal(resp)
|
||||
|
||||
w.WriteString(fmt.Sprintf("data: %s\n\n", respData))
|
||||
w.WriteString("data: [DONE]\n\n")
|
||||
w.Flush()
|
||||
}))
|
||||
return nil
|
||||
}
|
||||
|
||||
var result []Choice
|
||||
for _, 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}, Index: 0}},
|
||||
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",
|
||||
Index: 0,
|
||||
Delta: &Message{},
|
||||
}},
|
||||
Object: "chat.completion.chunk",
|
||||
}
|
||||
respData, _ := json.Marshal(resp)
|
||||
|
||||
w.WriteString(fmt.Sprintf("data: %s\n\n", respData))
|
||||
w.WriteString("data: [DONE]\n\n")
|
||||
w.Flush()
|
||||
}))
|
||||
return nil
|
||||
}
|
||||
|
||||
result, err := ComputeChoices(predInput, input, 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,
|
||||
})
|
||||
}
|
||||
}
|
||||
385
api/openai/chat.go
Normal file
385
api/openai/chat.go
Normal file
@@ -0,0 +1,385 @@
|
||||
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
|
||||
}
|
||||
|
||||
// process functions if we have any defined or if we have a function call string
|
||||
if len(input.Functions) > 0 && config.ShouldUseFunctions() {
|
||||
log.Debug().Msgf("Response needs to process functions")
|
||||
|
||||
processFunctions = true
|
||||
|
||||
noActionGrammar := grammar.Function{
|
||||
Name: noActionName,
|
||||
Description: noActionDescription,
|
||||
Parameters: map[string]interface{}{
|
||||
"properties": map[string]interface{}{
|
||||
"message": map[string]interface{}{
|
||||
"type": "string",
|
||||
"description": "The message to reply the user with",
|
||||
}},
|
||||
},
|
||||
}
|
||||
|
||||
// Append the no action function
|
||||
funcs = append(funcs, input.Functions...)
|
||||
if !config.FunctionsConfig.DisableNoAction {
|
||||
funcs = append(funcs, noActionGrammar)
|
||||
}
|
||||
|
||||
// Force picking one of the functions by the request
|
||||
if config.FunctionToCall() != "" {
|
||||
funcs = funcs.Select(config.FunctionToCall())
|
||||
}
|
||||
|
||||
// Update input grammar
|
||||
jsStruct := funcs.ToJSONStructure()
|
||||
config.Grammar = jsStruct.Grammar("")
|
||||
} else if input.JSONFunctionGrammarObject != nil {
|
||||
config.Grammar = input.JSONFunctionGrammarObject.Grammar("")
|
||||
}
|
||||
|
||||
// functions are not supported in stream mode (yet?)
|
||||
toStream := input.Stream && !processFunctions
|
||||
|
||||
log.Debug().Msgf("Parameters: %+v", config)
|
||||
|
||||
var predInput string
|
||||
|
||||
suppressConfigSystemPrompt := false
|
||||
mess := []string{}
|
||||
for messageIndex, i := range input.Messages {
|
||||
var content string
|
||||
role := i.Role
|
||||
|
||||
// if function call, we might want to customize the role so we can display better that the "assistant called a json action"
|
||||
// if an "assistant_function_call" role is defined, we use it, otherwise we use the role that is passed by in the request
|
||||
if i.FunctionCall != nil && i.Role == "assistant" {
|
||||
roleFn := "assistant_function_call"
|
||||
r := config.Roles[roleFn]
|
||||
if r != "" {
|
||||
role = roleFn
|
||||
}
|
||||
}
|
||||
r := config.Roles[role]
|
||||
contentExists := i.Content != nil && *i.Content != ""
|
||||
// First attempt to populate content via a chat message specific template
|
||||
if config.TemplateConfig.ChatMessage != "" {
|
||||
chatMessageData := model.ChatMessageTemplateData{
|
||||
SystemPrompt: config.SystemPrompt,
|
||||
Role: r,
|
||||
RoleName: role,
|
||||
Content: *i.Content,
|
||||
MessageIndex: messageIndex,
|
||||
}
|
||||
templatedChatMessage, err := o.Loader.EvaluateTemplateForChatMessage(config.TemplateConfig.ChatMessage, chatMessageData)
|
||||
if err != nil {
|
||||
log.Error().Msgf("error processing message %+v using template \"%s\": %v. Skipping!", chatMessageData, config.TemplateConfig.ChatMessage, err)
|
||||
} else {
|
||||
if templatedChatMessage == "" {
|
||||
log.Warn().Msgf("template \"%s\" produced blank output for %+v. Skipping!", config.TemplateConfig.ChatMessage, chatMessageData)
|
||||
continue // TODO: This continue is here intentionally to skip over the line `mess = append(mess, content)` below, and to prevent the sprintf
|
||||
}
|
||||
log.Debug().Msgf("templated message for chat: %s", templatedChatMessage)
|
||||
content = templatedChatMessage
|
||||
}
|
||||
}
|
||||
// If this model doesn't have such a template, or if that template fails to return a value, template at the message level.
|
||||
if content == "" {
|
||||
if r != "" {
|
||||
if contentExists {
|
||||
content = fmt.Sprint(r, " ", *i.Content)
|
||||
}
|
||||
if i.FunctionCall != nil {
|
||||
j, err := json.Marshal(i.FunctionCall)
|
||||
if err == nil {
|
||||
if contentExists {
|
||||
content += "\n" + fmt.Sprint(r, " ", string(j))
|
||||
} else {
|
||||
content = fmt.Sprint(r, " ", string(j))
|
||||
}
|
||||
}
|
||||
}
|
||||
} else {
|
||||
if contentExists {
|
||||
content = fmt.Sprint(*i.Content)
|
||||
}
|
||||
if i.FunctionCall != nil {
|
||||
j, err := json.Marshal(i.FunctionCall)
|
||||
if err == nil {
|
||||
if contentExists {
|
||||
content += "\n" + string(j)
|
||||
} else {
|
||||
content = string(j)
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
// Special Handling: System. We care if it was printed at all, not the r branch, so check seperately
|
||||
if contentExists && role == "system" {
|
||||
suppressConfigSystemPrompt = true
|
||||
}
|
||||
}
|
||||
|
||||
mess = append(mess, content)
|
||||
}
|
||||
|
||||
predInput = strings.Join(mess, "\n")
|
||||
log.Debug().Msgf("Prompt (before templating): %s", predInput)
|
||||
|
||||
if toStream {
|
||||
log.Debug().Msgf("Stream request received")
|
||||
c.Context().SetContentType("text/event-stream")
|
||||
//c.Response().Header.SetContentType(fiber.MIMETextHTMLCharsetUTF8)
|
||||
// c.Set("Content-Type", "text/event-stream")
|
||||
c.Set("Cache-Control", "no-cache")
|
||||
c.Set("Connection", "keep-alive")
|
||||
c.Set("Transfer-Encoding", "chunked")
|
||||
}
|
||||
|
||||
templateFile := config.Model
|
||||
|
||||
if config.TemplateConfig.Chat != "" && !processFunctions {
|
||||
templateFile = config.TemplateConfig.Chat
|
||||
}
|
||||
|
||||
if config.TemplateConfig.Functions != "" && processFunctions {
|
||||
templateFile = config.TemplateConfig.Functions
|
||||
}
|
||||
|
||||
// A model can have a "file.bin.tmpl" file associated with a prompt template prefix
|
||||
templatedInput, err := o.Loader.EvaluateTemplateForPrompt(model.ChatPromptTemplate, templateFile, model.PromptTemplateData{
|
||||
SystemPrompt: config.SystemPrompt,
|
||||
SuppressSystemPrompt: suppressConfigSystemPrompt,
|
||||
Input: predInput,
|
||||
Functions: funcs,
|
||||
})
|
||||
if err == nil {
|
||||
predInput = templatedInput
|
||||
log.Debug().Msgf("Template found, input modified to: %s", predInput)
|
||||
} else {
|
||||
log.Debug().Msgf("Template failed loading: %s", err.Error())
|
||||
}
|
||||
|
||||
log.Debug().Msgf("Prompt (after templating): %s", predInput)
|
||||
if processFunctions {
|
||||
log.Debug().Msgf("Grammar: %+v", config.Grammar)
|
||||
}
|
||||
|
||||
if toStream {
|
||||
responses := make(chan schema.OpenAIResponse)
|
||||
|
||||
go process(predInput, input, config, o.Loader, responses)
|
||||
|
||||
c.Context().SetBodyStreamWriter(fasthttp.StreamWriter(func(w *bufio.Writer) {
|
||||
|
||||
usage := &schema.OpenAIUsage{}
|
||||
|
||||
for ev := range responses {
|
||||
usage = &ev.Usage // Copy a pointer to the latest usage chunk so that the stop message can reference it
|
||||
var buf bytes.Buffer
|
||||
enc := json.NewEncoder(&buf)
|
||||
enc.Encode(ev)
|
||||
log.Debug().Msgf("Sending chunk: %s", buf.String())
|
||||
_, err := fmt.Fprintf(w, "data: %v\n", buf.String())
|
||||
if err != nil {
|
||||
log.Debug().Msgf("Sending chunk failed: %v", err)
|
||||
input.Cancel()
|
||||
break
|
||||
}
|
||||
w.Flush()
|
||||
}
|
||||
|
||||
resp := &schema.OpenAIResponse{
|
||||
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 = ""
|
||||
predFunc, err := backend.ModelInference(input.Context, predInput, o.Loader, *config, o, nil)
|
||||
if err != nil {
|
||||
log.Error().Msgf("inference error: %s", err.Error())
|
||||
return
|
||||
}
|
||||
|
||||
prediction, err := predFunc()
|
||||
if err != nil {
|
||||
log.Error().Msgf("inference error: %s", err.Error())
|
||||
return
|
||||
}
|
||||
|
||||
fineTunedResponse := backend.Finetune(*config, predInput, prediction.Response)
|
||||
*c = append(*c, schema.Choice{Message: &schema.Message{Role: "assistant", Content: &fineTunedResponse}})
|
||||
} else {
|
||||
// otherwise reply with the function call
|
||||
*c = append(*c, schema.Choice{
|
||||
FinishReason: "function_call",
|
||||
Message: &schema.Message{Role: "assistant", FunctionCall: ss},
|
||||
})
|
||||
}
|
||||
|
||||
return
|
||||
}
|
||||
*c = append(*c, schema.Choice{FinishReason: "stop", Index: 0, Message: &schema.Message{Role: "assistant", Content: &s}})
|
||||
}, nil)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
|
||||
resp := &schema.OpenAIResponse{
|
||||
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)
|
||||
}
|
||||
}
|
||||
186
api/openai/completion.go
Normal file
186
api/openai/completion.go
Normal file
@@ -0,0 +1,186 @@
|
||||
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"
|
||||
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)
|
||||
}
|
||||
|
||||
log.Debug().Msgf("Parameter Config: %+v", config)
|
||||
|
||||
if input.Stream {
|
||||
log.Debug().Msgf("Stream request received")
|
||||
c.Context().SetContentType("text/event-stream")
|
||||
//c.Response().Header.SetContentType(fiber.MIMETextHTMLCharsetUTF8)
|
||||
//c.Set("Content-Type", "text/event-stream")
|
||||
c.Set("Cache-Control", "no-cache")
|
||||
c.Set("Connection", "keep-alive")
|
||||
c.Set("Transfer-Encoding", "chunked")
|
||||
}
|
||||
|
||||
templateFile := config.Model
|
||||
|
||||
if config.TemplateConfig.Completion != "" {
|
||||
templateFile = config.TemplateConfig.Completion
|
||||
}
|
||||
|
||||
if input.Stream {
|
||||
if len(config.PromptStrings) > 1 {
|
||||
return errors.New("cannot handle more than 1 `PromptStrings` when Streaming")
|
||||
}
|
||||
|
||||
predInput := config.PromptStrings[0]
|
||||
|
||||
// A model can have a "file.bin.tmpl" file associated with a prompt template prefix
|
||||
templatedInput, err := o.Loader.EvaluateTemplateForPrompt(model.CompletionPromptTemplate, templateFile, model.PromptTemplateData{
|
||||
Input: predInput,
|
||||
})
|
||||
if err == nil {
|
||||
predInput = templatedInput
|
||||
log.Debug().Msgf("Template found, input modified to: %s", predInput)
|
||||
}
|
||||
|
||||
responses := make(chan schema.OpenAIResponse)
|
||||
|
||||
go process(predInput, input, config, o.Loader, responses)
|
||||
|
||||
c.Context().SetBodyStreamWriter(fasthttp.StreamWriter(func(w *bufio.Writer) {
|
||||
|
||||
for ev := range responses {
|
||||
var buf bytes.Buffer
|
||||
enc := json.NewEncoder(&buf)
|
||||
enc.Encode(ev)
|
||||
|
||||
log.Debug().Msgf("Sending chunk: %s", buf.String())
|
||||
fmt.Fprintf(w, "data: %v\n", buf.String())
|
||||
w.Flush()
|
||||
}
|
||||
|
||||
resp := &schema.OpenAIResponse{
|
||||
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 {
|
||||
// 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)
|
||||
}
|
||||
}
|
||||
88
api/openai/edit.go
Normal file
88
api/openai/edit.go
Normal file
@@ -0,0 +1,88 @@
|
||||
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 := config.Model
|
||||
|
||||
if config.TemplateConfig.Edit != "" {
|
||||
templateFile = config.TemplateConfig.Edit
|
||||
}
|
||||
|
||||
var result []schema.Choice
|
||||
totalTokenUsage := backend.TokenUsage{}
|
||||
|
||||
for _, i := range config.InputStrings {
|
||||
// A model can have a "file.bin.tmpl" file associated with a prompt template prefix
|
||||
templatedInput, err := o.Loader.EvaluateTemplateForPrompt(model.EditPromptTemplate, templateFile, model.PromptTemplateData{
|
||||
Input: i,
|
||||
Instruction: input.Instruction,
|
||||
SystemPrompt: config.SystemPrompt,
|
||||
})
|
||||
if err == nil {
|
||||
i = templatedInput
|
||||
log.Debug().Msgf("Template found, input modified to: %s", i)
|
||||
}
|
||||
|
||||
r, tokenUsage, err := ComputeChoices(input, i, config, o, o.Loader, func(s string, c *[]schema.Choice) {
|
||||
*c = append(*c, schema.Choice{Text: s})
|
||||
}, nil)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
|
||||
totalTokenUsage.Prompt += tokenUsage.Prompt
|
||||
totalTokenUsage.Completion += tokenUsage.Completion
|
||||
|
||||
result = append(result, r...)
|
||||
}
|
||||
|
||||
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)
|
||||
}
|
||||
}
|
||||
194
api/openai/image.go
Normal file
194
api/openai/image.go
Normal file
@@ -0,0 +1,194 @@
|
||||
package openai
|
||||
|
||||
import (
|
||||
"bufio"
|
||||
"encoding/base64"
|
||||
"encoding/json"
|
||||
"fmt"
|
||||
"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"
|
||||
)
|
||||
|
||||
// https://platform.openai.com/docs/api-reference/images/create
|
||||
|
||||
/*
|
||||
*
|
||||
|
||||
curl http://localhost:8080/v1/images/generations \
|
||||
-H "Content-Type: application/json" \
|
||||
-d '{
|
||||
"prompt": "A cute baby sea otter",
|
||||
"n": 1,
|
||||
"size": "512x512"
|
||||
}'
|
||||
|
||||
*
|
||||
*/
|
||||
func ImageEndpoint(cm *config.ConfigLoader, o *options.Option) func(c *fiber.Ctx) error {
|
||||
return func(c *fiber.Ctx) error {
|
||||
m, input, err := readInput(c, o, false)
|
||||
if err != nil {
|
||||
return fmt.Errorf("failed reading parameters from request:%w", err)
|
||||
}
|
||||
|
||||
if m == "" {
|
||||
m = model.StableDiffusionBackend
|
||||
}
|
||||
log.Debug().Msgf("Loading model: %+v", m)
|
||||
|
||||
config, input, err := readConfig(m, input, cm, o.Loader, o.Debug, 0, 0, false)
|
||||
if err != nil {
|
||||
return fmt.Errorf("failed reading parameters from request:%w", err)
|
||||
}
|
||||
|
||||
src := ""
|
||||
if input.File != "" {
|
||||
//base 64 decode the file and write it somewhere
|
||||
// that we will cleanup
|
||||
decoded, err := base64.StdEncoding.DecodeString(input.File)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
// Create a temporary file
|
||||
outputFile, err := os.CreateTemp(o.ImageDir, "b64")
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
// write the base64 result
|
||||
writer := bufio.NewWriter(outputFile)
|
||||
_, err = writer.Write(decoded)
|
||||
if err != nil {
|
||||
outputFile.Close()
|
||||
return err
|
||||
}
|
||||
outputFile.Close()
|
||||
src = outputFile.Name()
|
||||
defer os.RemoveAll(src)
|
||||
}
|
||||
|
||||
log.Debug().Msgf("Parameter Config: %+v", config)
|
||||
|
||||
// XXX: Only stablediffusion is supported for now
|
||||
if config.Backend == "" {
|
||||
config.Backend = model.StableDiffusionBackend
|
||||
}
|
||||
|
||||
sizeParts := strings.Split(input.Size, "x")
|
||||
if len(sizeParts) != 2 {
|
||||
return fmt.Errorf("Invalid value for 'size'")
|
||||
}
|
||||
width, err := strconv.Atoi(sizeParts[0])
|
||||
if err != nil {
|
||||
return fmt.Errorf("Invalid value for 'size'")
|
||||
}
|
||||
height, err := strconv.Atoi(sizeParts[1])
|
||||
if err != nil {
|
||||
return fmt.Errorf("Invalid value for 'size'")
|
||||
}
|
||||
|
||||
b64JSON := false
|
||||
if input.ResponseFormat == "b64_json" {
|
||||
b64JSON = true
|
||||
}
|
||||
// src and clip_skip
|
||||
var result []schema.Item
|
||||
for _, i := range config.PromptStrings {
|
||||
n := input.N
|
||||
if input.N == 0 {
|
||||
n = 1
|
||||
}
|
||||
for j := 0; j < n; j++ {
|
||||
prompts := strings.Split(i, "|")
|
||||
positive_prompt := prompts[0]
|
||||
negative_prompt := ""
|
||||
if len(prompts) > 1 {
|
||||
negative_prompt = prompts[1]
|
||||
}
|
||||
|
||||
mode := 0
|
||||
step := config.Step
|
||||
if step == 0 {
|
||||
step = 15
|
||||
}
|
||||
|
||||
if input.Mode != 0 {
|
||||
mode = input.Mode
|
||||
}
|
||||
|
||||
if input.Step != 0 {
|
||||
step = input.Step
|
||||
}
|
||||
|
||||
tempDir := ""
|
||||
if !b64JSON {
|
||||
tempDir = o.ImageDir
|
||||
}
|
||||
// Create a temporary file
|
||||
outputFile, err := os.CreateTemp(tempDir, "b64")
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
outputFile.Close()
|
||||
output := outputFile.Name() + ".png"
|
||||
// Rename the temporary file
|
||||
err = os.Rename(outputFile.Name(), output)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
|
||||
baseURL := c.BaseURL()
|
||||
|
||||
fn, err := backend.ImageGeneration(height, width, mode, step, input.Seed, positive_prompt, negative_prompt, src, output, o.Loader, *config, o)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
if err := fn(); err != nil {
|
||||
return err
|
||||
}
|
||||
|
||||
item := &schema.Item{}
|
||||
|
||||
if b64JSON {
|
||||
defer os.RemoveAll(output)
|
||||
data, err := os.ReadFile(output)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
item.B64JSON = base64.StdEncoding.EncodeToString(data)
|
||||
} else {
|
||||
base := filepath.Base(output)
|
||||
item.URL = baseURL + "/generated-images/" + base
|
||||
}
|
||||
|
||||
result = append(result, *item)
|
||||
}
|
||||
}
|
||||
|
||||
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)
|
||||
}
|
||||
}
|
||||
50
api/openai/inference.go
Normal file
50
api/openai/inference.go
Normal file
@@ -0,0 +1,50 @@
|
||||
package openai
|
||||
|
||||
import (
|
||||
"github.com/go-skynet/LocalAI/api/backend"
|
||||
config "github.com/go-skynet/LocalAI/api/config"
|
||||
"github.com/go-skynet/LocalAI/api/options"
|
||||
"github.com/go-skynet/LocalAI/api/schema"
|
||||
model "github.com/go-skynet/LocalAI/pkg/model"
|
||||
)
|
||||
|
||||
func ComputeChoices(
|
||||
req *schema.OpenAIRequest,
|
||||
predInput string,
|
||||
config *config.Config,
|
||||
o *options.Option,
|
||||
loader *model.ModelLoader,
|
||||
cb func(string, *[]schema.Choice),
|
||||
tokenCallback func(string, backend.TokenUsage) bool) ([]schema.Choice, backend.TokenUsage, error) {
|
||||
n := req.N // number of completions to return
|
||||
result := []schema.Choice{}
|
||||
|
||||
if n == 0 {
|
||||
n = 1
|
||||
}
|
||||
|
||||
// get the model function to call for the result
|
||||
predFunc, err := backend.ModelInference(req.Context, predInput, loader, *config, o, tokenCallback)
|
||||
if err != nil {
|
||||
return result, backend.TokenUsage{}, err
|
||||
}
|
||||
|
||||
tokenUsage := backend.TokenUsage{}
|
||||
|
||||
for i := 0; i < n; i++ {
|
||||
prediction, err := predFunc()
|
||||
if err != nil {
|
||||
return result, backend.TokenUsage{}, err
|
||||
}
|
||||
|
||||
tokenUsage.Prompt += prediction.Usage.Prompt
|
||||
tokenUsage.Completion += prediction.Usage.Completion
|
||||
|
||||
finetunedResponse := backend.Finetune(*config, predInput, prediction.Response)
|
||||
cb(finetunedResponse, &result)
|
||||
|
||||
//result = append(result, Choice{Text: prediction})
|
||||
|
||||
}
|
||||
return result, tokenUsage, err
|
||||
}
|
||||
69
api/openai/list.go
Normal file
69
api/openai/list.go
Normal file
@@ -0,0 +1,69 @@
|
||||
package openai
|
||||
|
||||
import (
|
||||
"regexp"
|
||||
|
||||
config "github.com/go-skynet/LocalAI/api/config"
|
||||
"github.com/go-skynet/LocalAI/api/schema"
|
||||
model "github.com/go-skynet/LocalAI/pkg/model"
|
||||
"github.com/gofiber/fiber/v2"
|
||||
)
|
||||
|
||||
func ListModelsEndpoint(loader *model.ModelLoader, cm *config.ConfigLoader) func(ctx *fiber.Ctx) error {
|
||||
return func(c *fiber.Ctx) error {
|
||||
models, err := loader.ListModels()
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
var mm map[string]interface{} = map[string]interface{}{}
|
||||
|
||||
dataModels := []schema.OpenAIModel{}
|
||||
|
||||
var filterFn func(name string) bool
|
||||
filter := c.Query("filter")
|
||||
|
||||
// If filter is not specified, do not filter the list by model name
|
||||
if filter == "" {
|
||||
filterFn = func(_ string) bool { return true }
|
||||
} else {
|
||||
// If filter _IS_ specified, we compile it to a regex which is used to create the filterFn
|
||||
rxp, err := regexp.Compile(filter)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
filterFn = func(name string) bool {
|
||||
return rxp.MatchString(name)
|
||||
}
|
||||
}
|
||||
|
||||
// By default, exclude any loose files that are already referenced by a configuration file.
|
||||
excludeConfigured := c.QueryBool("excludeConfigured", true)
|
||||
|
||||
// Start with the known configurations
|
||||
for _, c := range cm.GetAllConfigs() {
|
||||
if excludeConfigured {
|
||||
mm[c.Model] = nil
|
||||
}
|
||||
|
||||
if filterFn(c.Name) {
|
||||
dataModels = append(dataModels, schema.OpenAIModel{ID: c.Name, Object: "model"})
|
||||
}
|
||||
}
|
||||
|
||||
// Then iterate through the loose files:
|
||||
for _, m := range models {
|
||||
// And only adds them if they shouldn't be skipped.
|
||||
if _, exists := mm[m]; !exists && filterFn(m) {
|
||||
dataModels = append(dataModels, schema.OpenAIModel{ID: m, Object: "model"})
|
||||
}
|
||||
}
|
||||
|
||||
return c.JSON(struct {
|
||||
Object string `json:"object"`
|
||||
Data []schema.OpenAIModel `json:"data"`
|
||||
}{
|
||||
Object: "list",
|
||||
Data: dataModels,
|
||||
})
|
||||
}
|
||||
}
|
||||
273
api/openai/request.go
Normal file
273
api/openai/request.go
Normal file
@@ -0,0 +1,273 @@
|
||||
package openai
|
||||
|
||||
import (
|
||||
"context"
|
||||
"encoding/json"
|
||||
"fmt"
|
||||
"os"
|
||||
"path/filepath"
|
||||
"strings"
|
||||
|
||||
config "github.com/go-skynet/LocalAI/api/config"
|
||||
options "github.com/go-skynet/LocalAI/api/options"
|
||||
"github.com/go-skynet/LocalAI/api/schema"
|
||||
model "github.com/go-skynet/LocalAI/pkg/model"
|
||||
"github.com/gofiber/fiber/v2"
|
||||
"github.com/rs/zerolog/log"
|
||||
)
|
||||
|
||||
func readInput(c *fiber.Ctx, o *options.Option, randomModel bool) (string, *schema.OpenAIRequest, error) {
|
||||
loader := o.Loader
|
||||
input := new(schema.OpenAIRequest)
|
||||
ctx, cancel := context.WithCancel(o.Context)
|
||||
input.Context = ctx
|
||||
input.Cancel = cancel
|
||||
// Get input data from the request body
|
||||
if err := c.BodyParser(input); err != nil {
|
||||
return "", nil, err
|
||||
}
|
||||
|
||||
modelFile := input.Model
|
||||
|
||||
if c.Params("model") != "" {
|
||||
modelFile = c.Params("model")
|
||||
}
|
||||
|
||||
received, _ := json.Marshal(input)
|
||||
|
||||
log.Debug().Msgf("Request received: %s", string(received))
|
||||
|
||||
// Set model from bearer token, if available
|
||||
bearer := strings.TrimLeft(c.Get("authorization"), "Bearer ")
|
||||
bearerExists := bearer != "" && loader.ExistsInModelPath(bearer)
|
||||
|
||||
// If no model was specified, take the first available
|
||||
if modelFile == "" && !bearerExists && randomModel {
|
||||
models, _ := loader.ListModels()
|
||||
if len(models) > 0 {
|
||||
modelFile = models[0]
|
||||
log.Debug().Msgf("No model specified, using: %s", modelFile)
|
||||
} else {
|
||||
log.Debug().Msgf("No model specified, returning error")
|
||||
return "", nil, fmt.Errorf("no model specified")
|
||||
}
|
||||
}
|
||||
|
||||
// If a model is found in bearer token takes precedence
|
||||
if bearerExists {
|
||||
log.Debug().Msgf("Using model from bearer token: %s", bearer)
|
||||
modelFile = bearer
|
||||
}
|
||||
return modelFile, input, nil
|
||||
}
|
||||
|
||||
func updateConfig(config *config.Config, input *schema.OpenAIRequest) {
|
||||
if input.Echo {
|
||||
config.Echo = input.Echo
|
||||
}
|
||||
if input.TopK != 0 {
|
||||
config.TopK = input.TopK
|
||||
}
|
||||
if input.TopP != 0 {
|
||||
config.TopP = input.TopP
|
||||
}
|
||||
|
||||
if input.Backend != "" {
|
||||
config.Backend = input.Backend
|
||||
}
|
||||
|
||||
if input.ClipSkip != 0 {
|
||||
config.Diffusers.ClipSkip = input.ClipSkip
|
||||
}
|
||||
|
||||
if input.ModelBaseName != "" {
|
||||
config.AutoGPTQ.ModelBaseName = input.ModelBaseName
|
||||
}
|
||||
|
||||
if input.NegativePromptScale != 0 {
|
||||
config.NegativePromptScale = input.NegativePromptScale
|
||||
}
|
||||
|
||||
if input.UseFastTokenizer {
|
||||
config.UseFastTokenizer = input.UseFastTokenizer
|
||||
}
|
||||
|
||||
if input.NegativePrompt != "" {
|
||||
config.NegativePrompt = input.NegativePrompt
|
||||
}
|
||||
|
||||
if input.RopeFreqBase != 0 {
|
||||
config.RopeFreqBase = input.RopeFreqBase
|
||||
}
|
||||
|
||||
if input.RopeFreqScale != 0 {
|
||||
config.RopeFreqScale = input.RopeFreqScale
|
||||
}
|
||||
|
||||
if input.Grammar != "" {
|
||||
config.Grammar = input.Grammar
|
||||
}
|
||||
|
||||
if input.Temperature != 0 {
|
||||
config.Temperature = input.Temperature
|
||||
}
|
||||
|
||||
if input.Maxtokens != 0 {
|
||||
config.Maxtokens = input.Maxtokens
|
||||
}
|
||||
|
||||
switch stop := input.Stop.(type) {
|
||||
case string:
|
||||
if stop != "" {
|
||||
config.StopWords = append(config.StopWords, stop)
|
||||
}
|
||||
case []interface{}:
|
||||
for _, pp := range stop {
|
||||
if s, ok := pp.(string); ok {
|
||||
config.StopWords = append(config.StopWords, s)
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
if input.RepeatPenalty != 0 {
|
||||
config.RepeatPenalty = input.RepeatPenalty
|
||||
}
|
||||
|
||||
if input.Keep != 0 {
|
||||
config.Keep = input.Keep
|
||||
}
|
||||
|
||||
if input.Batch != 0 {
|
||||
config.Batch = input.Batch
|
||||
}
|
||||
|
||||
if input.F16 {
|
||||
config.F16 = input.F16
|
||||
}
|
||||
|
||||
if input.IgnoreEOS {
|
||||
config.IgnoreEOS = input.IgnoreEOS
|
||||
}
|
||||
|
||||
if input.Seed != 0 {
|
||||
config.Seed = input.Seed
|
||||
}
|
||||
|
||||
if input.Mirostat != 0 {
|
||||
config.LLMConfig.Mirostat = input.Mirostat
|
||||
}
|
||||
|
||||
if input.MirostatETA != 0 {
|
||||
config.LLMConfig.MirostatETA = input.MirostatETA
|
||||
}
|
||||
|
||||
if input.MirostatTAU != 0 {
|
||||
config.LLMConfig.MirostatTAU = input.MirostatTAU
|
||||
}
|
||||
|
||||
if input.TypicalP != 0 {
|
||||
config.TypicalP = input.TypicalP
|
||||
}
|
||||
|
||||
switch inputs := input.Input.(type) {
|
||||
case string:
|
||||
if inputs != "" {
|
||||
config.InputStrings = append(config.InputStrings, inputs)
|
||||
}
|
||||
case []interface{}:
|
||||
for _, pp := range inputs {
|
||||
switch i := pp.(type) {
|
||||
case string:
|
||||
config.InputStrings = append(config.InputStrings, i)
|
||||
case []interface{}:
|
||||
tokens := []int{}
|
||||
for _, ii := range i {
|
||||
tokens = append(tokens, int(ii.(float64)))
|
||||
}
|
||||
config.InputToken = append(config.InputToken, tokens)
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// Can be either a string or an object
|
||||
switch fnc := input.FunctionCall.(type) {
|
||||
case string:
|
||||
if fnc != "" {
|
||||
config.SetFunctionCallString(fnc)
|
||||
}
|
||||
case map[string]interface{}:
|
||||
var name string
|
||||
n, exists := fnc["name"]
|
||||
if exists {
|
||||
nn, e := n.(string)
|
||||
if e {
|
||||
name = nn
|
||||
}
|
||||
}
|
||||
config.SetFunctionCallNameString(name)
|
||||
}
|
||||
|
||||
switch p := input.Prompt.(type) {
|
||||
case string:
|
||||
config.PromptStrings = append(config.PromptStrings, p)
|
||||
case []interface{}:
|
||||
for _, pp := range p {
|
||||
if s, ok := pp.(string); ok {
|
||||
config.PromptStrings = append(config.PromptStrings, s)
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
func readConfig(modelFile string, input *schema.OpenAIRequest, cm *config.ConfigLoader, loader *model.ModelLoader, debug bool, threads, ctx int, f16 bool) (*config.Config, *schema.OpenAIRequest, error) {
|
||||
// Load a config file if present after the model name
|
||||
modelConfig := filepath.Join(loader.ModelPath, modelFile+".yaml")
|
||||
|
||||
var cfg *config.Config
|
||||
|
||||
defaults := func() {
|
||||
cfg = config.DefaultConfig(modelFile)
|
||||
cfg.ContextSize = ctx
|
||||
cfg.Threads = threads
|
||||
cfg.F16 = f16
|
||||
cfg.Debug = debug
|
||||
}
|
||||
|
||||
cfgExisting, exists := cm.GetConfig(modelFile)
|
||||
if !exists {
|
||||
if _, err := os.Stat(modelConfig); err == nil {
|
||||
if err := cm.LoadConfig(modelConfig); err != nil {
|
||||
return nil, nil, fmt.Errorf("failed loading model config (%s) %s", modelConfig, err.Error())
|
||||
}
|
||||
cfgExisting, exists = cm.GetConfig(modelFile)
|
||||
if exists {
|
||||
cfg = &cfgExisting
|
||||
} else {
|
||||
defaults()
|
||||
}
|
||||
} else {
|
||||
defaults()
|
||||
}
|
||||
} else {
|
||||
cfg = &cfgExisting
|
||||
}
|
||||
|
||||
// Set the parameters for the language model prediction
|
||||
updateConfig(cfg, input)
|
||||
|
||||
// Don't allow 0 as setting
|
||||
if cfg.Threads == 0 {
|
||||
if threads != 0 {
|
||||
cfg.Threads = threads
|
||||
} else {
|
||||
cfg.Threads = 4
|
||||
}
|
||||
}
|
||||
|
||||
// Enforce debug flag if passed from CLI
|
||||
if debug {
|
||||
cfg.Debug = true
|
||||
}
|
||||
|
||||
return cfg, input, nil
|
||||
}
|
||||
71
api/openai/transcription.go
Normal file
71
api/openai/transcription.go
Normal file
@@ -0,0 +1,71 @@
|
||||
package openai
|
||||
|
||||
import (
|
||||
"fmt"
|
||||
"io"
|
||||
"net/http"
|
||||
"os"
|
||||
"path"
|
||||
"path/filepath"
|
||||
|
||||
"github.com/go-skynet/LocalAI/api/backend"
|
||||
config "github.com/go-skynet/LocalAI/api/config"
|
||||
"github.com/go-skynet/LocalAI/api/options"
|
||||
|
||||
"github.com/gofiber/fiber/v2"
|
||||
"github.com/rs/zerolog/log"
|
||||
)
|
||||
|
||||
// https://platform.openai.com/docs/api-reference/audio/create
|
||||
func TranscriptEndpoint(cm *config.ConfigLoader, o *options.Option) func(c *fiber.Ctx) error {
|
||||
return func(c *fiber.Ctx) error {
|
||||
m, input, err := readInput(c, o, false)
|
||||
if err != nil {
|
||||
return fmt.Errorf("failed reading parameters from request:%w", err)
|
||||
}
|
||||
|
||||
config, input, err := readConfig(m, input, cm, o.Loader, o.Debug, o.Threads, o.ContextSize, o.F16)
|
||||
if err != nil {
|
||||
return fmt.Errorf("failed reading parameters from request:%w", err)
|
||||
}
|
||||
// retrieve the file data from the request
|
||||
file, err := c.FormFile("file")
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
f, err := file.Open()
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
defer f.Close()
|
||||
|
||||
dir, err := os.MkdirTemp("", "whisper")
|
||||
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
defer os.RemoveAll(dir)
|
||||
|
||||
dst := filepath.Join(dir, path.Base(file.Filename))
|
||||
dstFile, err := os.Create(dst)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
|
||||
if _, err := io.Copy(dstFile, f); err != nil {
|
||||
log.Debug().Msgf("Audio file copying error %+v - %+v - err %+v", file.Filename, dst, err)
|
||||
return err
|
||||
}
|
||||
|
||||
log.Debug().Msgf("Audio file copied to: %+v", dst)
|
||||
|
||||
tr, err := backend.ModelTranscription(dst, input.Language, o.Loader, *config, o)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
|
||||
log.Debug().Msgf("Trascribed: %+v", tr)
|
||||
// TODO: handle different outputs here
|
||||
return c.Status(http.StatusOK).JSON(tr)
|
||||
}
|
||||
}
|
||||
153
api/options.go
153
api/options.go
@@ -1,153 +0,0 @@
|
||||
package api
|
||||
|
||||
import (
|
||||
"context"
|
||||
"embed"
|
||||
|
||||
"github.com/go-skynet/LocalAI/pkg/gallery"
|
||||
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
|
||||
audioDir string
|
||||
cors bool
|
||||
preloadJSONModels string
|
||||
preloadModelsFromPath string
|
||||
corsAllowOrigins string
|
||||
|
||||
galleries []gallery.Gallery
|
||||
|
||||
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 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.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 WithAudioDir(audioDir string) AppOption {
|
||||
return func(o *Option) {
|
||||
o.audioDir = audioDir
|
||||
}
|
||||
}
|
||||
|
||||
func WithImageDir(imageDir string) AppOption {
|
||||
return func(o *Option) {
|
||||
o.imageDir = imageDir
|
||||
}
|
||||
}
|
||||
200
api/options/options.go
Normal file
200
api/options/options.go
Normal file
@@ -0,0 +1,200 @@
|
||||
package options
|
||||
|
||||
import (
|
||||
"context"
|
||||
"embed"
|
||||
"encoding/json"
|
||||
|
||||
"github.com/go-skynet/LocalAI/pkg/gallery"
|
||||
model "github.com/go-skynet/LocalAI/pkg/model"
|
||||
"github.com/rs/zerolog/log"
|
||||
)
|
||||
|
||||
type Option struct {
|
||||
Context context.Context
|
||||
ConfigFile string
|
||||
Loader *model.ModelLoader
|
||||
UploadLimitMB, Threads, ContextSize int
|
||||
F16 bool
|
||||
Debug, DisableMessage bool
|
||||
ImageDir string
|
||||
AudioDir string
|
||||
CORS bool
|
||||
PreloadJSONModels string
|
||||
PreloadModelsFromPath string
|
||||
CORSAllowOrigins string
|
||||
ApiKeys []string
|
||||
|
||||
Galleries []gallery.Gallery
|
||||
|
||||
BackendAssets embed.FS
|
||||
AssetsDestination string
|
||||
|
||||
ExternalGRPCBackends map[string]string
|
||||
|
||||
AutoloadGalleries bool
|
||||
|
||||
SingleBackend bool
|
||||
}
|
||||
|
||||
type AppOption func(*Option)
|
||||
|
||||
func NewOptions(o ...AppOption) *Option {
|
||||
opt := &Option{
|
||||
Context: context.Background(),
|
||||
UploadLimitMB: 15,
|
||||
Threads: 1,
|
||||
ContextSize: 512,
|
||||
Debug: true,
|
||||
DisableMessage: true,
|
||||
}
|
||||
for _, oo := range o {
|
||||
oo(opt)
|
||||
}
|
||||
return opt
|
||||
}
|
||||
|
||||
func WithCors(b bool) AppOption {
|
||||
return func(o *Option) {
|
||||
o.CORS = b
|
||||
}
|
||||
}
|
||||
|
||||
var EnableSingleBackend = func(o *Option) {
|
||||
o.SingleBackend = true
|
||||
}
|
||||
|
||||
var EnableGalleriesAutoload = func(o *Option) {
|
||||
o.AutoloadGalleries = true
|
||||
}
|
||||
|
||||
func WithExternalBackend(name string, uri string) AppOption {
|
||||
return func(o *Option) {
|
||||
if o.ExternalGRPCBackends == nil {
|
||||
o.ExternalGRPCBackends = make(map[string]string)
|
||||
}
|
||||
o.ExternalGRPCBackends[name] = uri
|
||||
}
|
||||
}
|
||||
|
||||
func WithCorsAllowOrigins(b string) AppOption {
|
||||
return func(o *Option) {
|
||||
o.CORSAllowOrigins = b
|
||||
}
|
||||
}
|
||||
|
||||
func WithBackendAssetsOutput(out string) AppOption {
|
||||
return func(o *Option) {
|
||||
o.AssetsDestination = out
|
||||
}
|
||||
}
|
||||
|
||||
func WithBackendAssets(f embed.FS) AppOption {
|
||||
return func(o *Option) {
|
||||
o.BackendAssets = f
|
||||
}
|
||||
}
|
||||
|
||||
func WithStringGalleries(galls string) AppOption {
|
||||
return func(o *Option) {
|
||||
if galls == "" {
|
||||
log.Debug().Msgf("no galleries to load")
|
||||
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
|
||||
}
|
||||
}
|
||||
@@ -1,647 +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.NUMA {
|
||||
llamaOpts = append(llamaOpts, llama.EnableNUMA)
|
||||
}
|
||||
|
||||
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
|
||||
|
||||
}
|
||||
115
api/schema/openai.go
Normal file
115
api/schema/openai.go
Normal file
@@ -0,0 +1,115 @@
|
||||
package schema
|
||||
|
||||
import (
|
||||
"context"
|
||||
|
||||
config "github.com/go-skynet/LocalAI/api/config"
|
||||
|
||||
"github.com/go-skynet/LocalAI/pkg/grammar"
|
||||
)
|
||||
|
||||
// APIError provides error information returned by the OpenAI API.
|
||||
type APIError struct {
|
||||
Code any `json:"code,omitempty"`
|
||||
Message string `json:"message"`
|
||||
Param *string `json:"param,omitempty"`
|
||||
Type string `json:"type"`
|
||||
}
|
||||
|
||||
type ErrorResponse struct {
|
||||
Error *APIError `json:"error,omitempty"`
|
||||
}
|
||||
|
||||
type OpenAIUsage struct {
|
||||
PromptTokens int `json:"prompt_tokens"`
|
||||
CompletionTokens int `json:"completion_tokens"`
|
||||
TotalTokens int `json:"total_tokens"`
|
||||
}
|
||||
|
||||
type Item struct {
|
||||
Embedding []float32 `json:"embedding"`
|
||||
Index int `json:"index"`
|
||||
Object string `json:"object,omitempty"`
|
||||
|
||||
// Images
|
||||
URL string `json:"url,omitempty"`
|
||||
B64JSON string `json:"b64_json,omitempty"`
|
||||
}
|
||||
|
||||
type OpenAIResponse struct {
|
||||
Created int `json:"created,omitempty"`
|
||||
Object string `json:"object,omitempty"`
|
||||
ID string `json:"id,omitempty"`
|
||||
Model string `json:"model,omitempty"`
|
||||
Choices []Choice `json:"choices,omitempty"`
|
||||
Data []Item `json:"data,omitempty"`
|
||||
|
||||
Usage OpenAIUsage `json:"usage"`
|
||||
}
|
||||
|
||||
type Choice struct {
|
||||
Index int `json:"index"`
|
||||
FinishReason string `json:"finish_reason,omitempty"`
|
||||
Message *Message `json:"message,omitempty"`
|
||||
Delta *Message `json:"delta,omitempty"`
|
||||
Text string `json:"text,omitempty"`
|
||||
}
|
||||
|
||||
type Message struct {
|
||||
// The message role
|
||||
Role string `json:"role,omitempty" yaml:"role"`
|
||||
// The message content
|
||||
Content *string `json:"content" yaml:"content"`
|
||||
// A result of a function call
|
||||
FunctionCall interface{} `json:"function_call,omitempty" yaml:"function_call,omitempty"`
|
||||
}
|
||||
|
||||
type OpenAIModel struct {
|
||||
ID string `json:"id"`
|
||||
Object string `json:"object"`
|
||||
}
|
||||
|
||||
type OpenAIRequest struct {
|
||||
config.PredictionOptions
|
||||
|
||||
Context context.Context
|
||||
Cancel context.CancelFunc
|
||||
|
||||
// whisper
|
||||
File string `json:"file" validate:"required"`
|
||||
//whisper/image
|
||||
ResponseFormat string `json:"response_format"`
|
||||
// image
|
||||
Size string `json:"size"`
|
||||
// Prompt is read only by completion/image API calls
|
||||
Prompt interface{} `json:"prompt" yaml:"prompt"`
|
||||
|
||||
// Edit endpoint
|
||||
Instruction string `json:"instruction" yaml:"instruction"`
|
||||
Input interface{} `json:"input" yaml:"input"`
|
||||
|
||||
Stop interface{} `json:"stop" yaml:"stop"`
|
||||
|
||||
// Messages is read only by chat/completion API calls
|
||||
Messages []Message `json:"messages" yaml:"messages"`
|
||||
|
||||
// A list of available functions to call
|
||||
Functions []grammar.Function `json:"functions" yaml:"functions"`
|
||||
FunctionCall interface{} `json:"function_call" yaml:"function_call"` // might be a string or an object
|
||||
|
||||
Stream bool `json:"stream"`
|
||||
|
||||
// Image (not supported by OpenAI)
|
||||
Mode int `json:"mode"`
|
||||
Step int `json:"step"`
|
||||
|
||||
// A grammar to constrain the LLM output
|
||||
Grammar string `json:"grammar" yaml:"grammar"`
|
||||
|
||||
JSONFunctionGrammarObject *grammar.JSONFunctionStructure `json:"grammar_json_functions" yaml:"grammar_json_functions"`
|
||||
|
||||
Backend string `json:"backend" yaml:"backend"`
|
||||
|
||||
// AutoGPTQ
|
||||
ModelBaseName string `json:"model_base_name" yaml:"model_base_name"`
|
||||
}
|
||||
16
api/schema/whisper.go
Normal file
16
api/schema/whisper.go
Normal file
@@ -0,0 +1,16 @@
|
||||
package schema
|
||||
|
||||
import "time"
|
||||
|
||||
type Segment struct {
|
||||
Id int `json:"id"`
|
||||
Start time.Duration `json:"start"`
|
||||
End time.Duration `json:"end"`
|
||||
Text string `json:"text"`
|
||||
Tokens []int `json:"tokens"`
|
||||
}
|
||||
|
||||
type Result struct {
|
||||
Segments []Segment `json:"segments"`
|
||||
Text string `json:"text"`
|
||||
}
|
||||
22
cmd/grpc/bert-embeddings/main.go
Normal file
22
cmd/grpc/bert-embeddings/main.go
Normal file
@@ -0,0 +1,22 @@
|
||||
package main
|
||||
|
||||
// Note: this is started internally by LocalAI and a server is allocated for each model
|
||||
|
||||
import (
|
||||
"flag"
|
||||
|
||||
bert "github.com/go-skynet/LocalAI/pkg/backend/llm/bert"
|
||||
grpc "github.com/go-skynet/LocalAI/pkg/grpc"
|
||||
)
|
||||
|
||||
var (
|
||||
addr = flag.String("addr", "localhost:50051", "the address to connect to")
|
||||
)
|
||||
|
||||
func main() {
|
||||
flag.Parse()
|
||||
|
||||
if err := grpc.StartServer(*addr, &bert.Embeddings{}); err != nil {
|
||||
panic(err)
|
||||
}
|
||||
}
|
||||
23
cmd/grpc/bloomz/main.go
Normal file
23
cmd/grpc/bloomz/main.go
Normal file
@@ -0,0 +1,23 @@
|
||||
package main
|
||||
|
||||
// Note: this is started internally by LocalAI and a server is allocated for each model
|
||||
|
||||
import (
|
||||
"flag"
|
||||
|
||||
bloomz "github.com/go-skynet/LocalAI/pkg/backend/llm/bloomz"
|
||||
|
||||
grpc "github.com/go-skynet/LocalAI/pkg/grpc"
|
||||
)
|
||||
|
||||
var (
|
||||
addr = flag.String("addr", "localhost:50051", "the address to connect to")
|
||||
)
|
||||
|
||||
func main() {
|
||||
flag.Parse()
|
||||
|
||||
if err := grpc.StartServer(*addr, &bloomz.LLM{}); err != nil {
|
||||
panic(err)
|
||||
}
|
||||
}
|
||||
23
cmd/grpc/dolly/main.go
Normal file
23
cmd/grpc/dolly/main.go
Normal file
@@ -0,0 +1,23 @@
|
||||
package main
|
||||
|
||||
// Note: this is started internally by LocalAI and a server is allocated for each model
|
||||
|
||||
import (
|
||||
"flag"
|
||||
|
||||
transformers "github.com/go-skynet/LocalAI/pkg/backend/llm/transformers"
|
||||
|
||||
grpc "github.com/go-skynet/LocalAI/pkg/grpc"
|
||||
)
|
||||
|
||||
var (
|
||||
addr = flag.String("addr", "localhost:50051", "the address to connect to")
|
||||
)
|
||||
|
||||
func main() {
|
||||
flag.Parse()
|
||||
|
||||
if err := grpc.StartServer(*addr, &transformers.Dolly{}); err != nil {
|
||||
panic(err)
|
||||
}
|
||||
}
|
||||
23
cmd/grpc/falcon-ggml/main.go
Normal file
23
cmd/grpc/falcon-ggml/main.go
Normal file
@@ -0,0 +1,23 @@
|
||||
package main
|
||||
|
||||
// Note: this is started internally by LocalAI and a server is allocated for each model
|
||||
|
||||
import (
|
||||
"flag"
|
||||
|
||||
transformers "github.com/go-skynet/LocalAI/pkg/backend/llm/transformers"
|
||||
|
||||
grpc "github.com/go-skynet/LocalAI/pkg/grpc"
|
||||
)
|
||||
|
||||
var (
|
||||
addr = flag.String("addr", "localhost:50051", "the address to connect to")
|
||||
)
|
||||
|
||||
func main() {
|
||||
flag.Parse()
|
||||
|
||||
if err := grpc.StartServer(*addr, &transformers.Falcon{}); err != nil {
|
||||
panic(err)
|
||||
}
|
||||
}
|
||||
25
cmd/grpc/falcon/main.go
Normal file
25
cmd/grpc/falcon/main.go
Normal file
@@ -0,0 +1,25 @@
|
||||
package main
|
||||
|
||||
// GRPC Falcon server
|
||||
|
||||
// Note: this is started internally by LocalAI and a server is allocated for each model
|
||||
|
||||
import (
|
||||
"flag"
|
||||
|
||||
falcon "github.com/go-skynet/LocalAI/pkg/backend/llm/falcon"
|
||||
|
||||
grpc "github.com/go-skynet/LocalAI/pkg/grpc"
|
||||
)
|
||||
|
||||
var (
|
||||
addr = flag.String("addr", "localhost:50051", "the address to connect to")
|
||||
)
|
||||
|
||||
func main() {
|
||||
flag.Parse()
|
||||
|
||||
if err := grpc.StartServer(*addr, &falcon.LLM{}); err != nil {
|
||||
panic(err)
|
||||
}
|
||||
}
|
||||
23
cmd/grpc/gpt2/main.go
Normal file
23
cmd/grpc/gpt2/main.go
Normal file
@@ -0,0 +1,23 @@
|
||||
package main
|
||||
|
||||
// Note: this is started internally by LocalAI and a server is allocated for each model
|
||||
|
||||
import (
|
||||
"flag"
|
||||
|
||||
transformers "github.com/go-skynet/LocalAI/pkg/backend/llm/transformers"
|
||||
|
||||
grpc "github.com/go-skynet/LocalAI/pkg/grpc"
|
||||
)
|
||||
|
||||
var (
|
||||
addr = flag.String("addr", "localhost:50051", "the address to connect to")
|
||||
)
|
||||
|
||||
func main() {
|
||||
flag.Parse()
|
||||
|
||||
if err := grpc.StartServer(*addr, &transformers.GPT2{}); err != nil {
|
||||
panic(err)
|
||||
}
|
||||
}
|
||||
23
cmd/grpc/gpt4all/main.go
Normal file
23
cmd/grpc/gpt4all/main.go
Normal file
@@ -0,0 +1,23 @@
|
||||
package main
|
||||
|
||||
// Note: this is started internally by LocalAI and a server is allocated for each model
|
||||
|
||||
import (
|
||||
"flag"
|
||||
|
||||
gpt4all "github.com/go-skynet/LocalAI/pkg/backend/llm/gpt4all"
|
||||
|
||||
grpc "github.com/go-skynet/LocalAI/pkg/grpc"
|
||||
)
|
||||
|
||||
var (
|
||||
addr = flag.String("addr", "localhost:50051", "the address to connect to")
|
||||
)
|
||||
|
||||
func main() {
|
||||
flag.Parse()
|
||||
|
||||
if err := grpc.StartServer(*addr, &gpt4all.LLM{}); err != nil {
|
||||
panic(err)
|
||||
}
|
||||
}
|
||||
23
cmd/grpc/gptj/main.go
Normal file
23
cmd/grpc/gptj/main.go
Normal file
@@ -0,0 +1,23 @@
|
||||
package main
|
||||
|
||||
// Note: this is started internally by LocalAI and a server is allocated for each model
|
||||
|
||||
import (
|
||||
"flag"
|
||||
|
||||
transformers "github.com/go-skynet/LocalAI/pkg/backend/llm/transformers"
|
||||
|
||||
grpc "github.com/go-skynet/LocalAI/pkg/grpc"
|
||||
)
|
||||
|
||||
var (
|
||||
addr = flag.String("addr", "localhost:50051", "the address to connect to")
|
||||
)
|
||||
|
||||
func main() {
|
||||
flag.Parse()
|
||||
|
||||
if err := grpc.StartServer(*addr, &transformers.GPTJ{}); err != nil {
|
||||
panic(err)
|
||||
}
|
||||
}
|
||||
23
cmd/grpc/gptneox/main.go
Normal file
23
cmd/grpc/gptneox/main.go
Normal file
@@ -0,0 +1,23 @@
|
||||
package main
|
||||
|
||||
// Note: this is started internally by LocalAI and a server is allocated for each model
|
||||
|
||||
import (
|
||||
"flag"
|
||||
|
||||
transformers "github.com/go-skynet/LocalAI/pkg/backend/llm/transformers"
|
||||
|
||||
grpc "github.com/go-skynet/LocalAI/pkg/grpc"
|
||||
)
|
||||
|
||||
var (
|
||||
addr = flag.String("addr", "localhost:50051", "the address to connect to")
|
||||
)
|
||||
|
||||
func main() {
|
||||
flag.Parse()
|
||||
|
||||
if err := grpc.StartServer(*addr, &transformers.GPTNeoX{}); err != nil {
|
||||
panic(err)
|
||||
}
|
||||
}
|
||||
23
cmd/grpc/langchain-huggingface/main.go
Normal file
23
cmd/grpc/langchain-huggingface/main.go
Normal file
@@ -0,0 +1,23 @@
|
||||
package main
|
||||
|
||||
// Note: this is started internally by LocalAI and a server is allocated for each model
|
||||
|
||||
import (
|
||||
"flag"
|
||||
|
||||
langchain "github.com/go-skynet/LocalAI/pkg/backend/llm/langchain"
|
||||
|
||||
grpc "github.com/go-skynet/LocalAI/pkg/grpc"
|
||||
)
|
||||
|
||||
var (
|
||||
addr = flag.String("addr", "localhost:50051", "the address to connect to")
|
||||
)
|
||||
|
||||
func main() {
|
||||
flag.Parse()
|
||||
|
||||
if err := grpc.StartServer(*addr, &langchain.LLM{}); err != nil {
|
||||
panic(err)
|
||||
}
|
||||
}
|
||||
21
cmd/grpc/llama-stable/main.go
Normal file
21
cmd/grpc/llama-stable/main.go
Normal file
@@ -0,0 +1,21 @@
|
||||
package main
|
||||
|
||||
import (
|
||||
"flag"
|
||||
|
||||
llama "github.com/go-skynet/LocalAI/pkg/backend/llm/llama-stable"
|
||||
|
||||
grpc "github.com/go-skynet/LocalAI/pkg/grpc"
|
||||
)
|
||||
|
||||
var (
|
||||
addr = flag.String("addr", "localhost:50051", "the address to connect to")
|
||||
)
|
||||
|
||||
func main() {
|
||||
flag.Parse()
|
||||
|
||||
if err := grpc.StartServer(*addr, &llama.LLM{}); err != nil {
|
||||
panic(err)
|
||||
}
|
||||
}
|
||||
25
cmd/grpc/llama/main.go
Normal file
25
cmd/grpc/llama/main.go
Normal file
@@ -0,0 +1,25 @@
|
||||
package main
|
||||
|
||||
// GRPC Falcon server
|
||||
|
||||
// Note: this is started internally by LocalAI and a server is allocated for each model
|
||||
|
||||
import (
|
||||
"flag"
|
||||
|
||||
llama "github.com/go-skynet/LocalAI/pkg/backend/llm/llama"
|
||||
|
||||
grpc "github.com/go-skynet/LocalAI/pkg/grpc"
|
||||
)
|
||||
|
||||
var (
|
||||
addr = flag.String("addr", "localhost:50051", "the address to connect to")
|
||||
)
|
||||
|
||||
func main() {
|
||||
flag.Parse()
|
||||
|
||||
if err := grpc.StartServer(*addr, &llama.LLM{}); err != nil {
|
||||
panic(err)
|
||||
}
|
||||
}
|
||||
23
cmd/grpc/mpt/main.go
Normal file
23
cmd/grpc/mpt/main.go
Normal file
@@ -0,0 +1,23 @@
|
||||
package main
|
||||
|
||||
// Note: this is started internally by LocalAI and a server is allocated for each model
|
||||
|
||||
import (
|
||||
"flag"
|
||||
|
||||
transformers "github.com/go-skynet/LocalAI/pkg/backend/llm/transformers"
|
||||
|
||||
grpc "github.com/go-skynet/LocalAI/pkg/grpc"
|
||||
)
|
||||
|
||||
var (
|
||||
addr = flag.String("addr", "localhost:50051", "the address to connect to")
|
||||
)
|
||||
|
||||
func main() {
|
||||
flag.Parse()
|
||||
|
||||
if err := grpc.StartServer(*addr, &transformers.MPT{}); err != nil {
|
||||
panic(err)
|
||||
}
|
||||
}
|
||||
23
cmd/grpc/piper/main.go
Normal file
23
cmd/grpc/piper/main.go
Normal file
@@ -0,0 +1,23 @@
|
||||
package main
|
||||
|
||||
// Note: this is started internally by LocalAI and a server is allocated for each model
|
||||
|
||||
import (
|
||||
"flag"
|
||||
|
||||
tts "github.com/go-skynet/LocalAI/pkg/backend/tts"
|
||||
|
||||
grpc "github.com/go-skynet/LocalAI/pkg/grpc"
|
||||
)
|
||||
|
||||
var (
|
||||
addr = flag.String("addr", "localhost:50051", "the address to connect to")
|
||||
)
|
||||
|
||||
func main() {
|
||||
flag.Parse()
|
||||
|
||||
if err := grpc.StartServer(*addr, &tts.Piper{}); err != nil {
|
||||
panic(err)
|
||||
}
|
||||
}
|
||||
23
cmd/grpc/replit/main.go
Normal file
23
cmd/grpc/replit/main.go
Normal file
@@ -0,0 +1,23 @@
|
||||
package main
|
||||
|
||||
// Note: this is started internally by LocalAI and a server is allocated for each model
|
||||
|
||||
import (
|
||||
"flag"
|
||||
|
||||
transformers "github.com/go-skynet/LocalAI/pkg/backend/llm/transformers"
|
||||
|
||||
grpc "github.com/go-skynet/LocalAI/pkg/grpc"
|
||||
)
|
||||
|
||||
var (
|
||||
addr = flag.String("addr", "localhost:50051", "the address to connect to")
|
||||
)
|
||||
|
||||
func main() {
|
||||
flag.Parse()
|
||||
|
||||
if err := grpc.StartServer(*addr, &transformers.Replit{}); err != nil {
|
||||
panic(err)
|
||||
}
|
||||
}
|
||||
23
cmd/grpc/rwkv/main.go
Normal file
23
cmd/grpc/rwkv/main.go
Normal file
@@ -0,0 +1,23 @@
|
||||
package main
|
||||
|
||||
// Note: this is started internally by LocalAI and a server is allocated for each model
|
||||
|
||||
import (
|
||||
"flag"
|
||||
|
||||
rwkv "github.com/go-skynet/LocalAI/pkg/backend/llm/rwkv"
|
||||
|
||||
grpc "github.com/go-skynet/LocalAI/pkg/grpc"
|
||||
)
|
||||
|
||||
var (
|
||||
addr = flag.String("addr", "localhost:50051", "the address to connect to")
|
||||
)
|
||||
|
||||
func main() {
|
||||
flag.Parse()
|
||||
|
||||
if err := grpc.StartServer(*addr, &rwkv.LLM{}); err != nil {
|
||||
panic(err)
|
||||
}
|
||||
}
|
||||
23
cmd/grpc/stablediffusion/main.go
Normal file
23
cmd/grpc/stablediffusion/main.go
Normal file
@@ -0,0 +1,23 @@
|
||||
package main
|
||||
|
||||
// Note: this is started internally by LocalAI and a server is allocated for each model
|
||||
|
||||
import (
|
||||
"flag"
|
||||
|
||||
image "github.com/go-skynet/LocalAI/pkg/backend/image"
|
||||
|
||||
grpc "github.com/go-skynet/LocalAI/pkg/grpc"
|
||||
)
|
||||
|
||||
var (
|
||||
addr = flag.String("addr", "localhost:50051", "the address to connect to")
|
||||
)
|
||||
|
||||
func main() {
|
||||
flag.Parse()
|
||||
|
||||
if err := grpc.StartServer(*addr, &image.StableDiffusion{}); err != nil {
|
||||
panic(err)
|
||||
}
|
||||
}
|
||||
23
cmd/grpc/starcoder/main.go
Normal file
23
cmd/grpc/starcoder/main.go
Normal file
@@ -0,0 +1,23 @@
|
||||
package main
|
||||
|
||||
// Note: this is started internally by LocalAI and a server is allocated for each model
|
||||
|
||||
import (
|
||||
"flag"
|
||||
|
||||
transformers "github.com/go-skynet/LocalAI/pkg/backend/llm/transformers"
|
||||
|
||||
grpc "github.com/go-skynet/LocalAI/pkg/grpc"
|
||||
)
|
||||
|
||||
var (
|
||||
addr = flag.String("addr", "localhost:50051", "the address to connect to")
|
||||
)
|
||||
|
||||
func main() {
|
||||
flag.Parse()
|
||||
|
||||
if err := grpc.StartServer(*addr, &transformers.Starcoder{}); err != nil {
|
||||
panic(err)
|
||||
}
|
||||
}
|
||||
23
cmd/grpc/whisper/main.go
Normal file
23
cmd/grpc/whisper/main.go
Normal file
@@ -0,0 +1,23 @@
|
||||
package main
|
||||
|
||||
// Note: this is started internally by LocalAI and a server is allocated for each model
|
||||
|
||||
import (
|
||||
"flag"
|
||||
|
||||
transcribe "github.com/go-skynet/LocalAI/pkg/backend/transcribe"
|
||||
|
||||
grpc "github.com/go-skynet/LocalAI/pkg/grpc"
|
||||
)
|
||||
|
||||
var (
|
||||
addr = flag.String("addr", "localhost:50051", "the address to connect to")
|
||||
)
|
||||
|
||||
func main() {
|
||||
flag.Parse()
|
||||
|
||||
if err := grpc.StartServer(*addr, &transcribe.Whisper{}); err != nil {
|
||||
panic(err)
|
||||
}
|
||||
}
|
||||
@@ -12,4 +12,5 @@ services:
|
||||
- .env
|
||||
volumes:
|
||||
- ./models:/models:cached
|
||||
- ./images/:/tmp/generated/images/
|
||||
command: ["/usr/bin/local-ai" ]
|
||||
|
||||
@@ -5,7 +5,36 @@ cd /build
|
||||
|
||||
if [ "$REBUILD" != "false" ]; then
|
||||
rm -rf ./local-ai
|
||||
ESPEAK_DATA=/build/lib/Linux-$(uname -m)/piper_phonemize/lib/espeak-ng-data make build -j${THREADS:-1}
|
||||
ESPEAK_DATA=/build/lib/Linux-$(uname -m)/piper_phonemize/lib/espeak-ng-data make build -j${BUILD_PARALLELISM:-1}
|
||||
else
|
||||
echo "@@@@@"
|
||||
echo "Skipping rebuild"
|
||||
echo "@@@@@"
|
||||
echo "If you are experiencing issues with the pre-compiled builds, try setting REBUILD=true"
|
||||
echo "If you are still experiencing issues with the build, try setting CMAKE_ARGS and disable the instructions set as needed:"
|
||||
echo 'CMAKE_ARGS="-DLLAMA_F16C=OFF -DLLAMA_AVX512=OFF -DLLAMA_AVX2=OFF -DLLAMA_FMA=OFF"'
|
||||
echo "see the documentation at: https://localai.io/basics/build/index.html"
|
||||
echo "Note: See also https://github.com/go-skynet/LocalAI/issues/288"
|
||||
echo "@@@@@"
|
||||
echo "CPU info:"
|
||||
grep -e "model\sname" /proc/cpuinfo | head -1
|
||||
grep -e "flags" /proc/cpuinfo | head -1
|
||||
if grep -q -e "\savx\s" /proc/cpuinfo ; then
|
||||
echo "CPU: AVX found OK"
|
||||
else
|
||||
echo "CPU: no AVX found"
|
||||
fi
|
||||
if grep -q -e "\savx2\s" /proc/cpuinfo ; then
|
||||
echo "CPU: AVX2 found OK"
|
||||
else
|
||||
echo "CPU: no AVX2 found"
|
||||
fi
|
||||
if grep -q -e "\savx512" /proc/cpuinfo ; then
|
||||
echo "CPU: AVX512 found OK"
|
||||
else
|
||||
echo "CPU: no AVX512 found"
|
||||
fi
|
||||
echo "@@@@@"
|
||||
fi
|
||||
|
||||
./local-ai "$@"
|
||||
|
||||
@@ -1,7 +1,16 @@
|
||||
# Examples
|
||||
|
||||
| [ChatGPT OSS alternative](https://github.com/go-skynet/LocalAI/tree/master/examples/chatbot-ui) | [Image generation](https://localai.io/api-endpoints/index.html#image-generation) |
|
||||
|------------------------------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------------|
|
||||
|  |  |
|
||||
|
||||
| [Telegram bot](https://github.com/go-skynet/LocalAI/tree/master/examples/telegram-bot) | [Flowise](https://github.com/go-skynet/LocalAI/tree/master/examples/flowise) |
|
||||
|------------------------------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------------|
|
||||
 | | |
|
||||
|
||||
Here is a list of projects that can easily be integrated with the LocalAI backend.
|
||||
|
||||
|
||||
### Projects
|
||||
|
||||
### AutoGPT
|
||||
@@ -64,6 +73,14 @@ A ready to use example to show e2e how to integrate LocalAI with langchain
|
||||
|
||||
[Check it out here](https://github.com/go-skynet/LocalAI/tree/master/examples/langchain-python/)
|
||||
|
||||
### LocalAI functions
|
||||
|
||||
_by [@mudler](https://github.com/mudler)_
|
||||
|
||||
A ready to use example to show how to use OpenAI functions with LocalAI
|
||||
|
||||
[Check it out here](https://github.com/go-skynet/LocalAI/tree/master/examples/functions/)
|
||||
|
||||
### LocalAI WebUI
|
||||
|
||||
_by [@dhruvgera](https://github.com/dhruvgera)_
|
||||
@@ -140,6 +157,26 @@ Allows to run any LocalAI-compatible model as a backend on the servers of https:
|
||||
|
||||
[Check it out here](https://runpod.io/gsc?template=uv9mtqnrd0&ref=984wlcra)
|
||||
|
||||
### Continue
|
||||
|
||||
_by [@gruberdev](https://github.com/gruberdev)_
|
||||
|
||||
<img src="continue/img/screen.png" width="600" height="200" alt="Screenshot">
|
||||
|
||||
Demonstrates how to integrate an open-source copilot alternative that enhances code analysis, completion, and improvements. This approach seamlessly integrates with any LocalAI model, offering a more user-friendly experience.
|
||||
|
||||
[Check it out here](https://github.com/go-skynet/LocalAI/tree/master/examples/continue/)
|
||||
|
||||
### Streamlit bot
|
||||
|
||||
_by [@majoshi1](https://github.com/majoshi1)_
|
||||
|
||||

|
||||
|
||||
A chat bot made using `Streamlit` & LocalAI.
|
||||
|
||||
[Check it out here](https://github.com/go-skynet/LocalAI/tree/master/examples/streamlit-bot/)
|
||||
|
||||
## Want to contribute?
|
||||
|
||||
Create an issue, and put `Example: <description>` in the title! We will post your examples here.
|
||||
|
||||
@@ -1,5 +1,9 @@
|
||||
# CPU .env docs: https://localai.io/howtos/easy-setup-docker-cpu/
|
||||
# GPU .env docs: https://localai.io/howtos/easy-setup-docker-gpu/
|
||||
|
||||
OPENAI_API_KEY=sk---anystringhere
|
||||
OPENAI_API_BASE=http://api:8080/v1
|
||||
# Models to preload at start
|
||||
# Here we configure gpt4all as gpt-3.5-turbo and bert as embeddings
|
||||
PRELOAD_MODELS=[{"url": "github:go-skynet/model-gallery/gpt4all-j.yaml", "name": "gpt-3.5-turbo"}, { "url": "github:go-skynet/model-gallery/bert-embeddings.yaml", "name": "text-embedding-ada-002"}]
|
||||
# Here we configure gpt4all as gpt-3.5-turbo and bert as embeddings,
|
||||
# see other options in the model gallery at https://github.com/go-skynet/model-gallery
|
||||
PRELOAD_MODELS=[{"url": "github:go-skynet/model-gallery/gpt4all-j.yaml", "name": "gpt-3.5-turbo"}, { "url": "github:go-skynet/model-gallery/bert-embeddings.yaml", "name": "text-embedding-ada-002"}]
|
||||
@@ -10,12 +10,16 @@ git clone https://github.com/go-skynet/LocalAI
|
||||
|
||||
cd LocalAI/examples/autoGPT
|
||||
|
||||
cp -rfv .env.example .env
|
||||
|
||||
# Edit the .env file to set a different model by editing `PRELOAD_MODELS`.
|
||||
vim .env
|
||||
|
||||
docker-compose run --rm auto-gpt
|
||||
```
|
||||
|
||||
Note: The example automatically downloads the `gpt4all` model as it is under a permissive license. The GPT4All model does not seem to be enough to run AutoGPT. WizardLM-7b-uncensored seems to perform better (with `f16: true`).
|
||||
|
||||
See the `.env` configuration file to set a different model with the [model-gallery](https://github.com/go-skynet/model-gallery) by editing `PRELOAD_MODELS`.
|
||||
|
||||
## Without docker
|
||||
|
||||
|
||||
@@ -0,0 +1,11 @@
|
||||
meta {
|
||||
name: backend monitor
|
||||
type: http
|
||||
seq: 4
|
||||
}
|
||||
|
||||
get {
|
||||
url: {{PROTOCOL}}{{HOST}}:{{PORT}}/backend/monitor
|
||||
body: none
|
||||
auth: none
|
||||
}
|
||||
@@ -0,0 +1,21 @@
|
||||
meta {
|
||||
name: backend-shutdown
|
||||
type: http
|
||||
seq: 3
|
||||
}
|
||||
|
||||
post {
|
||||
url: {{PROTOCOL}}{{HOST}}:{{PORT}}/backend/shutdown
|
||||
body: json
|
||||
auth: none
|
||||
}
|
||||
|
||||
headers {
|
||||
Content-Type: application/json
|
||||
}
|
||||
|
||||
body:json {
|
||||
{
|
||||
"model": "{{DEFAULT_MODEL}}"
|
||||
}
|
||||
}
|
||||
5
examples/bruno/LocalAI Test Requests/bruno.json
Normal file
5
examples/bruno/LocalAI Test Requests/bruno.json
Normal file
@@ -0,0 +1,5 @@
|
||||
{
|
||||
"version": "1",
|
||||
"name": "LocalAI Test Requests",
|
||||
"type": "collection"
|
||||
}
|
||||
@@ -0,0 +1,6 @@
|
||||
vars {
|
||||
HOST: localhost
|
||||
PORT: 8080
|
||||
DEFAULT_MODEL: gpt-3.5-turbo
|
||||
PROTOCOL: http://
|
||||
}
|
||||
11
examples/bruno/LocalAI Test Requests/get models list.bru
Normal file
11
examples/bruno/LocalAI Test Requests/get models list.bru
Normal file
@@ -0,0 +1,11 @@
|
||||
meta {
|
||||
name: get models list
|
||||
type: http
|
||||
seq: 2
|
||||
}
|
||||
|
||||
get {
|
||||
url: {{PROTOCOL}}{{HOST}}:{{PORT}}/models
|
||||
body: none
|
||||
auth: none
|
||||
}
|
||||
@@ -0,0 +1,24 @@
|
||||
meta {
|
||||
name: -completions
|
||||
type: http
|
||||
seq: 4
|
||||
}
|
||||
|
||||
post {
|
||||
url: {{PROTOCOL}}{{HOST}}:{{PORT}}/completions
|
||||
body: json
|
||||
auth: none
|
||||
}
|
||||
|
||||
headers {
|
||||
Content-Type: application/json
|
||||
}
|
||||
|
||||
body:json {
|
||||
{
|
||||
"model": "{{DEFAULT_MODEL}}",
|
||||
"prompt": "function downloadFile(string url, string outputPath) {",
|
||||
"max_tokens": 256,
|
||||
"temperature": 0.5
|
||||
}
|
||||
}
|
||||
23
examples/bruno/LocalAI Test Requests/llm text/-edits.bru
Normal file
23
examples/bruno/LocalAI Test Requests/llm text/-edits.bru
Normal file
@@ -0,0 +1,23 @@
|
||||
meta {
|
||||
name: -edits
|
||||
type: http
|
||||
seq: 5
|
||||
}
|
||||
|
||||
post {
|
||||
url: {{PROTOCOL}}{{HOST}}:{{PORT}}/edits
|
||||
body: json
|
||||
auth: none
|
||||
}
|
||||
|
||||
headers {
|
||||
Content-Type: application/json
|
||||
}
|
||||
|
||||
body:json {
|
||||
{
|
||||
"model": "{{DEFAULT_MODEL}}",
|
||||
"input": "What day of the wek is it?",
|
||||
"instruction": "Fix the spelling mistakes"
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,22 @@
|
||||
meta {
|
||||
name: -embeddings
|
||||
type: http
|
||||
seq: 6
|
||||
}
|
||||
|
||||
post {
|
||||
url: {{PROTOCOL}}{{HOST}}:{{PORT}}/embeddings
|
||||
body: json
|
||||
auth: none
|
||||
}
|
||||
|
||||
headers {
|
||||
Content-Type: application/json
|
||||
}
|
||||
|
||||
body:json {
|
||||
{
|
||||
"model": "{{DEFAULT_MODEL}}",
|
||||
"input": "A STRANGE GAME.\nTHE ONLY WINNING MOVE IS NOT TO PLAY.\n\nHOW ABOUT A NICE GAME OF CHESS?"
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,24 @@
|
||||
meta {
|
||||
name: chat completion -simple- 1 message-
|
||||
type: http
|
||||
seq: 4
|
||||
}
|
||||
|
||||
post {
|
||||
url: {{PROTOCOL}}{{HOST}}:{{PORT}}/chat/completions
|
||||
body: json
|
||||
auth: none
|
||||
}
|
||||
|
||||
headers {
|
||||
Content-Type: application/json
|
||||
}
|
||||
|
||||
body:json {
|
||||
{
|
||||
"model": "{{DEFAULT_MODEL}}",
|
||||
"messages": [{"role": "user", "content": "How could one use friction to cook an egg?"}],
|
||||
"max_tokens": 256,
|
||||
"temperature": 0.2
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,29 @@
|
||||
meta {
|
||||
name: chat-completions -long-
|
||||
type: http
|
||||
seq: 5
|
||||
}
|
||||
|
||||
post {
|
||||
url: {{PROTOCOL}}{{HOST}}:{{PORT}}/chat/completions
|
||||
body: json
|
||||
auth: none
|
||||
}
|
||||
|
||||
headers {
|
||||
Content-Type: application/json
|
||||
}
|
||||
|
||||
body:json {
|
||||
{
|
||||
"model": "{{DEFAULT_MODEL}}",
|
||||
"messages": [{"role": "system", "content": "You are a helpful, intelligent pirate assistant. Always answer as helpfully as possible, while being a pirate and using pirate language. If a question does not make any sense, or is not factually coherent, explain why instead of answering something not correct. If you don't know the answer to a question, please don't share false information."},
|
||||
{"role": "user", "content": "How could one use electricity to cook an egg?"},
|
||||
{"role": "assistant",
|
||||
"content": "Shiver me timbers! Using electricity to cook an egg? Well, matey, I reckon that be a right curious idea! *adjusts spectacles* Now, I ain't sure if this be possible, but I'll do me best to help ye out.\n\nFirst things first, ye gotta understand that electricity be a powerful force, and it can't just cook an egg on its own. Ye see, electricity be like a mighty wind that can make things happen, but it needs somethin' to work with. So, if ye want to use electricity to cook an egg, ye gotta find a way to harness that power and make it do the cookin'.\n\nNow, I know what ye might be thinkin': \"How do I harness the power of electricity to cook an egg?\" Well, matey, there be a few ways to do it. One way be to use a special device called an \"electric frying pan.\" This be a pan that has a built-in heating element that gets hot when ye plug it into a wall socket. When the element gets hot, ye can crack an egg into the pan and watch as it cook"
|
||||
},
|
||||
{"role": "user", "content": "I don't have one of those, just a raw wire and plenty of power! How do we get it done?"}],
|
||||
"max_tokens": 1024,
|
||||
"temperature": 0.5
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,25 @@
|
||||
meta {
|
||||
name: chat-completions -stream-
|
||||
type: http
|
||||
seq: 6
|
||||
}
|
||||
|
||||
post {
|
||||
url: {{PROTOCOL}}{{HOST}}:{{PORT}}/chat/completions
|
||||
body: json
|
||||
auth: none
|
||||
}
|
||||
|
||||
headers {
|
||||
Content-Type: application/json
|
||||
}
|
||||
|
||||
body:json {
|
||||
{
|
||||
"model": "{{DEFAULT_MODEL}}",
|
||||
"messages": [{"role": "user", "content": "Explain how I can set sail on the ocean using only power generated by seagulls?"}],
|
||||
"max_tokens": 256,
|
||||
"temperature": 0.9,
|
||||
"stream": true
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,22 @@
|
||||
meta {
|
||||
name: add model gallery
|
||||
type: http
|
||||
seq: 10
|
||||
}
|
||||
|
||||
post {
|
||||
url: {{PROTOCOL}}{{HOST}}:{{PORT}}/models/galleries
|
||||
body: json
|
||||
auth: none
|
||||
}
|
||||
|
||||
headers {
|
||||
Content-Type: application/json
|
||||
}
|
||||
|
||||
body:json {
|
||||
{
|
||||
"url": "file:///home/dave/projects/model-gallery/huggingface/TheBloke__CodeLlama-7B-Instruct-GGML.yaml",
|
||||
"name": "test"
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,21 @@
|
||||
meta {
|
||||
name: delete model gallery
|
||||
type: http
|
||||
seq: 11
|
||||
}
|
||||
|
||||
delete {
|
||||
url: {{PROTOCOL}}{{HOST}}:{{PORT}}/models/galleries
|
||||
body: json
|
||||
auth: none
|
||||
}
|
||||
|
||||
headers {
|
||||
Content-Type: application/json
|
||||
}
|
||||
|
||||
body:json {
|
||||
{
|
||||
"name": "test"
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,11 @@
|
||||
meta {
|
||||
name: list MODELS in galleries
|
||||
type: http
|
||||
seq: 7
|
||||
}
|
||||
|
||||
get {
|
||||
url: {{PROTOCOL}}{{HOST}}:{{PORT}}/models/available
|
||||
body: none
|
||||
auth: none
|
||||
}
|
||||
@@ -0,0 +1,11 @@
|
||||
meta {
|
||||
name: list model GALLERIES
|
||||
type: http
|
||||
seq: 8
|
||||
}
|
||||
|
||||
get {
|
||||
url: {{PROTOCOL}}{{HOST}}:{{PORT}}/models/galleries
|
||||
body: none
|
||||
auth: none
|
||||
}
|
||||
@@ -0,0 +1,21 @@
|
||||
meta {
|
||||
name: model gallery apply -gist-
|
||||
type: http
|
||||
seq: 12
|
||||
}
|
||||
|
||||
post {
|
||||
url: {{PROTOCOL}}{{HOST}}:{{PORT}}/models/apply
|
||||
body: json
|
||||
auth: none
|
||||
}
|
||||
|
||||
headers {
|
||||
Content-Type: application/json
|
||||
}
|
||||
|
||||
body:json {
|
||||
{
|
||||
"id": "TheBloke__CodeLlama-7B-Instruct-GGML__codellama-7b-instruct.ggmlv3.Q2_K.bin"
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,22 @@
|
||||
meta {
|
||||
name: model gallery apply
|
||||
type: http
|
||||
seq: 9
|
||||
}
|
||||
|
||||
post {
|
||||
url: {{PROTOCOL}}{{HOST}}:{{PORT}}/models/apply
|
||||
body: json
|
||||
auth: none
|
||||
}
|
||||
|
||||
headers {
|
||||
Content-Type: application/json
|
||||
}
|
||||
|
||||
body:json {
|
||||
{
|
||||
"id": "dave@TheBloke__CodeLlama-7B-Instruct-GGML__codellama-7b-instruct.ggmlv3.Q3_K_S.bin",
|
||||
"name": "codellama7b"
|
||||
}
|
||||
}
|
||||
22
examples/bruno/LocalAI Test Requests/tts/-tts.bru
Normal file
22
examples/bruno/LocalAI Test Requests/tts/-tts.bru
Normal file
@@ -0,0 +1,22 @@
|
||||
meta {
|
||||
name: -tts
|
||||
type: http
|
||||
seq: 2
|
||||
}
|
||||
|
||||
post {
|
||||
url: {{PROTOCOL}}{{HOST}}:{{PORT}}/tts
|
||||
body: json
|
||||
auth: none
|
||||
}
|
||||
|
||||
headers {
|
||||
Content-Type: application/json
|
||||
}
|
||||
|
||||
body:json {
|
||||
{
|
||||
"model": "{{DEFAULT_MODEL}}",
|
||||
"input": "A STRANGE GAME.\nTHE ONLY WINNING MOVE IS NOT TO PLAY.\n\nHOW ABOUT A NICE GAME OF CHESS?"
|
||||
}
|
||||
}
|
||||
@@ -24,10 +24,13 @@ docker-compose up -d --pull always
|
||||
# docker-compose up -d --build
|
||||
```
|
||||
|
||||
Then browse to `http://localhost:3000` to view the Web UI.
|
||||
|
||||
## Pointing chatbot-ui to a separately managed LocalAI service
|
||||
|
||||
If you want to use the [chatbot-ui example](https://github.com/go-skynet/LocalAI/tree/master/examples/chatbot-ui) with an externally managed LocalAI service, you can alter the `docker-compose` file so that it looks like the below. You will notice the file is smaller, because we have removed the section that would normally start the LocalAI service. Take care to update the IP address (or FQDN) that the chatbot-ui service tries to access (marked `<<LOCALAI_IP>>` below):
|
||||
```
|
||||
If you want to use the [chatbot-ui example](https://github.com/go-skynet/LocalAI/tree/master/examples/chatbot-ui) with an externally managed LocalAI service, you can alter the `docker-compose.yaml` file so that it looks like the below. You will notice the file is smaller, because we have removed the section that would normally start the LocalAI service. Take care to update the IP address (or FQDN) that the chatbot-ui service tries to access (marked `<<LOCALAI_IP>>` below):
|
||||
|
||||
```yaml
|
||||
version: '3.6'
|
||||
|
||||
services:
|
||||
@@ -40,9 +43,8 @@ services:
|
||||
- 'OPENAI_API_HOST=http://<<LOCALAI_IP>>:8080'
|
||||
```
|
||||
|
||||
Once you've edited the Dockerfile, you can start it with `docker compose up`, then browse to `http://localhost:3000`.
|
||||
Once you've edited the `docker-compose.yaml`, you can start it with `docker compose up`, then browse to `http://localhost:3000` to view the Web UI.
|
||||
|
||||
## Accessing chatbot-ui
|
||||
|
||||
Open http://localhost:3000 for the Web UI.
|
||||
|
||||
|
||||
1
examples/chatbot-ui-manual/models
Symbolic link
1
examples/chatbot-ui-manual/models
Symbolic link
@@ -0,0 +1 @@
|
||||
../models
|
||||
@@ -20,10 +20,13 @@ docker-compose up --pull always
|
||||
# docker-compose up -d --build
|
||||
```
|
||||
|
||||
Then browse to `http://localhost:3000` to view the Web UI.
|
||||
|
||||
## Pointing chatbot-ui to a separately managed LocalAI service
|
||||
|
||||
If you want to use the [chatbot-ui example](https://github.com/go-skynet/LocalAI/tree/master/examples/chatbot-ui) with an externally managed LocalAI service, you can alter the `docker-compose` file so that it looks like the below. You will notice the file is smaller, because we have removed the section that would normally start the LocalAI service. Take care to update the IP address (or FQDN) that the chatbot-ui service tries to access (marked `<<LOCALAI_IP>>` below):
|
||||
```
|
||||
If you want to use the [chatbot-ui example](https://github.com/go-skynet/LocalAI/tree/master/examples/chatbot-ui) with an externally managed LocalAI service, you can alter the `docker-compose.yaml` file so that it looks like the below. You will notice the file is smaller, because we have removed the section that would normally start the LocalAI service. Take care to update the IP address (or FQDN) that the chatbot-ui service tries to access (marked `<<LOCALAI_IP>>` below):
|
||||
|
||||
```yaml
|
||||
version: '3.6'
|
||||
|
||||
services:
|
||||
@@ -36,9 +39,8 @@ services:
|
||||
- 'OPENAI_API_HOST=http://<<LOCALAI_IP>>:8080'
|
||||
```
|
||||
|
||||
Once you've edited the Dockerfile, you can start it with `docker compose up`, then browse to `http://localhost:3000`.
|
||||
Once you've edited the `docker-compose.yaml`, you can start it with `docker compose up`, then browse to `http://localhost:3000` to view the Web UI.
|
||||
|
||||
## Accessing chatbot-ui
|
||||
|
||||
Open http://localhost:3000 for the Web UI.
|
||||
|
||||
|
||||
53
examples/continue/README.md
Normal file
53
examples/continue/README.md
Normal file
@@ -0,0 +1,53 @@
|
||||
# Continue
|
||||
|
||||

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

|
||||
|
||||
For a live demonstration, please click on the link below:
|
||||
|
||||
- [How it works (Video demonstration)](https://www.youtube.com/watch?v=3Ocrc-WX4iQ)
|
||||
|
||||
## Integration Setup Walkthrough
|
||||
|
||||
1. [As outlined in `continue`'s documentation](https://continue.dev/docs/getting-started), install the [Visual Studio Code extension from the marketplace](https://marketplace.visualstudio.com/items?itemName=Continue.continue) and open it.
|
||||
2. In this example, LocalAI will download the gpt4all model and set it up as "gpt-3.5-turbo". Refer to the `docker-compose.yaml` file for details.
|
||||
|
||||
```bash
|
||||
# Clone LocalAI
|
||||
git clone https://github.com/go-skynet/LocalAI
|
||||
|
||||
cd LocalAI/examples/continue
|
||||
|
||||
# Start with docker-compose
|
||||
docker-compose up --build -d
|
||||
```
|
||||
|
||||
3. Type `/config` within Continue's VSCode extension, or edit the file located at `~/.continue/config.py` on your system with the following configuration:
|
||||
|
||||
```py
|
||||
from continuedev.src.continuedev.libs.llm.openai import OpenAI
|
||||
|
||||
config = ContinueConfig(
|
||||
...
|
||||
models=Models(
|
||||
default=OpenAI(
|
||||
api_key="my-api-key",
|
||||
model="gpt-3.5-turbo",
|
||||
api_base="http://localhost:8080",
|
||||
)
|
||||
),
|
||||
)
|
||||
```
|
||||
|
||||
This setup enables you to make queries directly to your model running in the Docker container. Note that the `api_key` does not need to be properly set up; it is included here as a placeholder.
|
||||
|
||||
If editing the configuration seems confusing, you may copy and paste the provided default `config.py` file over the existing one in `~/.continue/config.py` after initializing the extension in the VSCode IDE.
|
||||
|
||||
## Additional Resources
|
||||
|
||||
- [Official Continue documentation](https://continue.dev/docs/intro)
|
||||
- [Documentation page on using self-hosted models](https://continue.dev/docs/customization#self-hosting-an-open-source-model)
|
||||
- [Official extension link](https://marketplace.visualstudio.com/items?itemName=Continue.continue)
|
||||
148
examples/continue/config.py
Normal file
148
examples/continue/config.py
Normal file
@@ -0,0 +1,148 @@
|
||||
"""
|
||||
This is the Continue configuration file.
|
||||
|
||||
See https://continue.dev/docs/customization to learn more.
|
||||
"""
|
||||
|
||||
import subprocess
|
||||
|
||||
from continuedev.src.continuedev.core.main import Step
|
||||
from continuedev.src.continuedev.core.sdk import ContinueSDK
|
||||
from continuedev.src.continuedev.core.models import Models
|
||||
from continuedev.src.continuedev.core.config import CustomCommand, SlashCommand, ContinueConfig
|
||||
from continuedev.src.continuedev.plugins.context_providers.github import GitHubIssuesContextProvider
|
||||
from continuedev.src.continuedev.plugins.context_providers.google import GoogleContextProvider
|
||||
from continuedev.src.continuedev.plugins.policies.default import DefaultPolicy
|
||||
from continuedev.src.continuedev.libs.llm.openai import OpenAI, OpenAIServerInfo
|
||||
from continuedev.src.continuedev.libs.llm.ggml import GGML
|
||||
|
||||
from continuedev.src.continuedev.plugins.steps.open_config import OpenConfigStep
|
||||
from continuedev.src.continuedev.plugins.steps.clear_history import ClearHistoryStep
|
||||
from continuedev.src.continuedev.plugins.steps.feedback import FeedbackStep
|
||||
from continuedev.src.continuedev.plugins.steps.comment_code import CommentCodeStep
|
||||
from continuedev.src.continuedev.plugins.steps.share_session import ShareSessionStep
|
||||
from continuedev.src.continuedev.plugins.steps.main import EditHighlightedCodeStep
|
||||
from continuedev.src.continuedev.plugins.context_providers.search import SearchContextProvider
|
||||
from continuedev.src.continuedev.plugins.context_providers.diff import DiffContextProvider
|
||||
from continuedev.src.continuedev.plugins.context_providers.url import URLContextProvider
|
||||
|
||||
class CommitMessageStep(Step):
|
||||
"""
|
||||
This is a Step, the building block of Continue.
|
||||
It can be used below as a slash command, so that
|
||||
run will be called when you type '/commit'.
|
||||
"""
|
||||
async def run(self, sdk: ContinueSDK):
|
||||
|
||||
# Get the root directory of the workspace
|
||||
dir = sdk.ide.workspace_directory
|
||||
|
||||
# Run git diff in that directory
|
||||
diff = subprocess.check_output(
|
||||
["git", "diff"], cwd=dir).decode("utf-8")
|
||||
|
||||
# Ask the LLM to write a commit message,
|
||||
# and set it as the description of this step
|
||||
self.description = await sdk.models.default.complete(
|
||||
f"{diff}\n\nWrite a short, specific (less than 50 chars) commit message about the above changes:")
|
||||
|
||||
|
||||
config = ContinueConfig(
|
||||
|
||||
# If set to False, we will not collect any usage data
|
||||
# See here to learn what anonymous data we collect: https://continue.dev/docs/telemetry
|
||||
allow_anonymous_telemetry=True,
|
||||
|
||||
models = Models(
|
||||
default = OpenAI(
|
||||
api_key = "my-api-key",
|
||||
model = "gpt-3.5-turbo",
|
||||
openai_server_info = OpenAIServerInfo(
|
||||
api_base = "http://localhost:8080",
|
||||
model = "gpt-3.5-turbo"
|
||||
)
|
||||
)
|
||||
),
|
||||
# Set a system message with information that the LLM should always keep in mind
|
||||
# E.g. "Please give concise answers. Always respond in Spanish."
|
||||
system_message=None,
|
||||
|
||||
# Set temperature to any value between 0 and 1. Higher values will make the LLM
|
||||
# more creative, while lower values will make it more predictable.
|
||||
temperature=0.5,
|
||||
|
||||
# Custom commands let you map a prompt to a shortened slash command
|
||||
# They are like slash commands, but more easily defined - write just a prompt instead of a Step class
|
||||
# Their output will always be in chat form
|
||||
custom_commands=[
|
||||
# CustomCommand(
|
||||
# name="test",
|
||||
# description="Write unit tests for the higlighted code",
|
||||
# prompt="Write a comprehensive set of unit tests for the selected code. It should setup, run tests that check for correctness including important edge cases, and teardown. Ensure that the tests are complete and sophisticated. Give the tests just as chat output, don't edit any file.",
|
||||
# )
|
||||
],
|
||||
|
||||
# Slash commands let you run a Step from a slash command
|
||||
slash_commands=[
|
||||
# SlashCommand(
|
||||
# name="commit",
|
||||
# description="This is an example slash command. Use /config to edit it and create more",
|
||||
# step=CommitMessageStep,
|
||||
# )
|
||||
SlashCommand(
|
||||
name="edit",
|
||||
description="Edit code in the current file or the highlighted code",
|
||||
step=EditHighlightedCodeStep,
|
||||
),
|
||||
SlashCommand(
|
||||
name="config",
|
||||
description="Customize Continue - slash commands, LLMs, system message, etc.",
|
||||
step=OpenConfigStep,
|
||||
),
|
||||
SlashCommand(
|
||||
name="comment",
|
||||
description="Write comments for the current file or highlighted code",
|
||||
step=CommentCodeStep,
|
||||
),
|
||||
SlashCommand(
|
||||
name="feedback",
|
||||
description="Send feedback to improve Continue",
|
||||
step=FeedbackStep,
|
||||
),
|
||||
SlashCommand(
|
||||
name="clear",
|
||||
description="Clear step history",
|
||||
step=ClearHistoryStep,
|
||||
),
|
||||
SlashCommand(
|
||||
name="share",
|
||||
description="Download and share the session transcript",
|
||||
step=ShareSessionStep,
|
||||
)
|
||||
],
|
||||
|
||||
# Context providers let you quickly select context by typing '@'
|
||||
# Uncomment the following to
|
||||
# - quickly reference GitHub issues
|
||||
# - show Google search results to the LLM
|
||||
context_providers=[
|
||||
# GitHubIssuesContextProvider(
|
||||
# repo_name="<your github username or organization>/<your repo name>",
|
||||
# auth_token="<your github auth token>"
|
||||
# ),
|
||||
# GoogleContextProvider(
|
||||
# serper_api_key="<your serper.dev api key>"
|
||||
# )
|
||||
SearchContextProvider(),
|
||||
DiffContextProvider(),
|
||||
URLContextProvider(
|
||||
preset_urls = [
|
||||
# Add any common urls you reference here so they appear in autocomplete
|
||||
]
|
||||
)
|
||||
],
|
||||
|
||||
# Policies hold the main logic that decides which Step to take next
|
||||
# You can use them to design agents, or deeply customize Continue
|
||||
policy=DefaultPolicy()
|
||||
)
|
||||
27
examples/continue/docker-compose.yml
Normal file
27
examples/continue/docker-compose.yml
Normal file
@@ -0,0 +1,27 @@
|
||||
version: '3.6'
|
||||
|
||||
services:
|
||||
api:
|
||||
image: quay.io/go-skynet/local-ai:latest
|
||||
# As initially LocalAI will download the models defined in PRELOAD_MODELS
|
||||
# you might need to tweak the healthcheck values here according to your network connection.
|
||||
# Here we give a timespan of 20m to download all the required files.
|
||||
healthcheck:
|
||||
test: ["CMD", "curl", "-f", "http://localhost:8080/readyz"]
|
||||
interval: 1m
|
||||
timeout: 20m
|
||||
retries: 20
|
||||
build:
|
||||
context: ../../
|
||||
dockerfile: Dockerfile
|
||||
ports:
|
||||
- 8080:8080
|
||||
environment:
|
||||
- DEBUG=true
|
||||
- MODELS_PATH=/models
|
||||
# You can preload different models here as well.
|
||||
# See: https://github.com/go-skynet/model-gallery
|
||||
- 'PRELOAD_MODELS=[{"url": "github:go-skynet/model-gallery/gpt4all-j.yaml", "name": "gpt-3.5-turbo"}]'
|
||||
volumes:
|
||||
- ./models:/models:cached
|
||||
command: ["/usr/bin/local-ai" ]
|
||||
BIN
examples/continue/img/screen.png
Executable file
BIN
examples/continue/img/screen.png
Executable file
Binary file not shown.
|
After Width: | Height: | Size: 196 KiB |
@@ -1,3 +1,6 @@
|
||||
# CPU .env docs: https://localai.io/howtos/easy-setup-docker-cpu/
|
||||
# GPU .env docs: https://localai.io/howtos/easy-setup-docker-gpu/
|
||||
|
||||
OPENAI_API_KEY=x
|
||||
DISCORD_BOT_TOKEN=x
|
||||
DISCORD_CLIENT_ID=x
|
||||
|
||||
@@ -1 +1 @@
|
||||
../chatbot-ui/models/
|
||||
../models
|
||||
13
examples/functions/.env.example
Normal file
13
examples/functions/.env.example
Normal file
@@ -0,0 +1,13 @@
|
||||
# CPU .env docs: https://localai.io/howtos/easy-setup-docker-cpu/
|
||||
# GPU .env docs: https://localai.io/howtos/easy-setup-docker-gpu/
|
||||
|
||||
OPENAI_API_KEY=sk---anystringhere
|
||||
OPENAI_API_BASE=http://api:8080/v1
|
||||
# Models to preload at start
|
||||
# Here we configure gpt4all as gpt-3.5-turbo and bert as embeddings,
|
||||
# see other options in the model gallery at https://github.com/go-skynet/model-gallery
|
||||
PRELOAD_MODELS=[{"url": "github:go-skynet/model-gallery/openllama-7b-open-instruct.yaml", "name": "gpt-3.5-turbo"}]
|
||||
|
||||
## Change the default number of threads
|
||||
#THREADS=14
|
||||
|
||||
5
examples/functions/Dockerfile
Normal file
5
examples/functions/Dockerfile
Normal file
@@ -0,0 +1,5 @@
|
||||
FROM python:3.10-bullseye
|
||||
COPY . /app
|
||||
WORKDIR /app
|
||||
RUN pip install --no-cache-dir -r requirements.txt
|
||||
ENTRYPOINT [ "python", "./functions-openai.py" ];
|
||||
21
examples/functions/README.md
Normal file
21
examples/functions/README.md
Normal file
@@ -0,0 +1,21 @@
|
||||
# LocalAI functions
|
||||
|
||||
Example of using LocalAI functions, see the [OpenAI](https://openai.com/blog/function-calling-and-other-api-updates) blog post.
|
||||
|
||||
## Run
|
||||
|
||||
```bash
|
||||
# Clone LocalAI
|
||||
git clone https://github.com/go-skynet/LocalAI
|
||||
|
||||
cd LocalAI/examples/functions
|
||||
|
||||
cp -rfv .env.example .env
|
||||
|
||||
# Edit the .env file to set a different model by editing `PRELOAD_MODELS`.
|
||||
vim .env
|
||||
|
||||
docker-compose run --rm functions
|
||||
```
|
||||
|
||||
Note: The example automatically downloads the `openllama` model as it is under a permissive license.
|
||||
Some files were not shown because too many files have changed in this diff Show More
Reference in New Issue
Block a user