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2 Commits

Author SHA1 Message Date
mudler
b8161da27c docs: move api docs 2023-04-27 10:41:42 +02:00
mudler
4e9b1ab550 docs: update, add config docs 2023-04-27 10:38:15 +02:00
905 changed files with 2242 additions and 115880 deletions

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@@ -1,17 +0,0 @@
#!/bin/bash
cd /workspace
# Get the files into the volume without a bind mount
if [ ! -d ".git" ]; then
git clone https://github.com/mudler/LocalAI.git .
else
git fetch
fi
echo "Standard Post-Create script completed."
if [ -f "/devcontainer-customization/postcreate.sh" ]; then
echo "Launching customization postcreate.sh"
bash "/devcontainer-customization/postcreate.sh"
fi

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@@ -1,16 +0,0 @@
#!/bin/bash
cd /workspace
# Grab the pre-stashed backend assets to avoid build issues
cp -r /build/backend-assets /workspace/backend-assets
# Ensures generated source files are present upon load
make prepare
echo "Standard Post-Start script completed."
if [ -f "/devcontainer-customization/poststart.sh" ]; then
echo "Launching customization poststart.sh"
bash "/devcontainer-customization/poststart.sh"
fi

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@@ -1,49 +0,0 @@
#!/bin/bash
# This file contains some really simple functions that are useful when building up customization scripts.
# Checks if the git config has a user registered - and sets it up if not.
#
# Param 1: name
# Param 2: email
#
config_user() {
local gcn=$(git config --global user.name)
if [ -z "${gcn}" ]; then
echo "Setting up git user / remote"
git config --global user.name "$1"
git config --global user.email "$2"
fi
}
# Checks if the git remote is configured - and sets it up if not. Fetches either way.
#
# Param 1: remote name
# Param 2: remote url
#
config_remote() {
local gr=$(git remote -v | grep $1)
if [ -z "${gr}" ]; then
git remote add $1 $2
fi
git fetch $1
}
# Setup special .ssh files
#
# Param 1: bash array, filenames relative to the customization directory that should be copied to ~/.ssh
setup_ssh() {
local files=("$@")
for file in "${files[@]}"; then
local cfile="/devcontainer-customization/${file}"
local hfile="~/.ssh/${file}"
if [ ! -f "${hfile}" ]; then
echo "copying ${file}"
cp "${cfile}" "${hfile}"
chmod 600 "${hfile}"
fi
done
ls ~/.ssh
}

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

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@@ -1,25 +0,0 @@
Place any additional resources your environment requires in this directory
Script hooks are currently called for:
`postcreate.sh` and `poststart.sh`
If files with those names exist here, they will be called at the end of the normal script.
This is a good place to set things like `git config --global user.name` are set - and to handle any other files that are mounted via this directory.
To assist in doing so, `source /.devcontainer-scripts/utils.sh` will provide utility functions that may be useful - for example:
```
#!/bin/bash
source "/.devcontainer-scripts/utils.sh"
sshfiles=("config", "key.pub")
setup_ssh "${sshfiles[@]}"
config_user "YOUR NAME" "YOUR EMAIL"
config_remote "REMOTE NAME" "REMOTE URL"
```

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@@ -1,24 +1,46 @@
{
"$schema": "https://raw.githubusercontent.com/devcontainers/spec/main/schemas/devContainer.schema.json",
"name": "LocalAI",
"workspaceFolder": "/workspace",
"dockerComposeFile": [ "./docker-compose-devcontainer.yml" ],
"service": "api",
"shutdownAction": "stopCompose",
"customizations": {
"vscode": {
"extensions": [
"golang.go",
"ms-vscode.makefile-tools",
"ms-azuretools.vscode-docker",
"ms-python.python",
"ms-python.debugpy",
"wayou.vscode-todo-highlight",
"waderyan.gitblame"
]
}
},
"forwardPorts": [8080, 3000],
"postCreateCommand": "bash /.devcontainer-scripts/postcreate.sh",
"postStartCommand": "bash /.devcontainer-scripts/poststart.sh"
}
// For format details, see https://aka.ms/devcontainer.json. For config options, see the
// README at: https://github.com/devcontainers/templates/tree/main/src/docker-existing-docker-compose
{
"name": "Existing Docker Compose (Extend)",
// Update the 'dockerComposeFile' list if you have more compose files or use different names.
// The .devcontainer/docker-compose.yml file contains any overrides you need/want to make.
"dockerComposeFile": [
"../docker-compose.yaml",
"docker-compose.yml"
],
// The 'service' property is the name of the service for the container that VS Code should
// use. Update this value and .devcontainer/docker-compose.yml to the real service name.
"service": "api",
// The optional 'workspaceFolder' property is the path VS Code should open by default when
// connected. This is typically a file mount in .devcontainer/docker-compose.yml
"workspaceFolder": "/workspace",
"features": {
"ghcr.io/devcontainers/features/go:1": {},
"ghcr.io/azutake/devcontainer-features/go-packages-install:0": {}
},
// Features to add to the dev container. More info: https://containers.dev/features.
// "features": {},
// Use 'forwardPorts' to make a list of ports inside the container available locally.
// "forwardPorts": [],
// Uncomment the next line if you want start specific services in your Docker Compose config.
// "runServices": [],
// Uncomment the next line if you want to keep your containers running after VS Code shuts down.
// "shutdownAction": "none",
// Uncomment the next line to run commands after the container is created.
"postCreateCommand": "make prepare"
// Configure tool-specific properties.
// "customizations": {},
// Uncomment to connect as an existing user other than the container default. More info: https://aka.ms/dev-containers-non-root.
// "remoteUser": "devcontainer"
}

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@@ -1,48 +0,0 @@
services:
api:
build:
context: ..
dockerfile: Dockerfile
target: devcontainer
args:
- FFMPEG=true
- IMAGE_TYPE=extras
- GO_TAGS=stablediffusion p2p tts
env_file:
- ../.env
ports:
- 8080:8080
volumes:
- localai_workspace:/workspace
- ../models:/host-models
- ./customization:/devcontainer-customization
command: /bin/sh -c "while sleep 1000; do :; done"
cap_add:
- SYS_PTRACE
security_opt:
- seccomp:unconfined
prometheus:
image: prom/prometheus
container_name: prometheus
command:
- '--config.file=/etc/prometheus/prometheus.yml'
ports:
- 9090:9090
restart: unless-stopped
volumes:
- ./prometheus:/etc/prometheus
- prom_data:/prometheus
grafana:
image: grafana/grafana
container_name: grafana
ports:
- 3000:3000
restart: unless-stopped
environment:
- GF_SECURITY_ADMIN_USER=admin
- GF_SECURITY_ADMIN_PASSWORD=grafana
volumes:
- ./grafana:/etc/grafana/provisioning/datasources
volumes:
prom_data:
localai_workspace:

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@@ -0,0 +1,26 @@
version: '3.6'
services:
# Update this to the name of the service you want to work with in your docker-compose.yml file
api:
# Uncomment if you want to override the service's Dockerfile to one in the .devcontainer
# folder. Note that the path of the Dockerfile and context is relative to the *primary*
# docker-compose.yml file (the first in the devcontainer.json "dockerComposeFile"
# array). The sample below assumes your primary file is in the root of your project.
#
build:
context: .
dockerfile: .devcontainer/Dockerfile
volumes:
# Update this to wherever you want VS Code to mount the folder of your project
- .:/workspace:cached
# Uncomment the next four lines if you will use a ptrace-based debugger like C++, Go, and Rust.
# cap_add:
# - SYS_PTRACE
# security_opt:
# - seccomp:unconfined
# Overrides default command so things don't shut down after the process ends.
command: /bin/sh -c "while sleep 1000; do :; done"

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@@ -1,10 +0,0 @@
apiVersion: 1
datasources:
- name: Prometheus
type: prometheus
url: http://prometheus:9090
isDefault: true
access: proxy
editable: true

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@@ -1,21 +0,0 @@
global:
scrape_interval: 15s
scrape_timeout: 10s
evaluation_interval: 15s
alerting:
alertmanagers:
- static_configs:
- targets: []
scheme: http
timeout: 10s
api_version: v1
scrape_configs:
- job_name: prometheus
honor_timestamps: true
scrape_interval: 15s
scrape_timeout: 10s
metrics_path: /metrics
scheme: http
static_configs:
- targets:
- localhost:9090

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@@ -1,17 +1,2 @@
.idea
.github
.vscode
.devcontainer
models
examples/chatbot-ui/models
examples/rwkv/models
examples/**/models
Dockerfile*
__pycache__
# SonarQube
.scannerwork
# backend virtual environments
**/venv
backend/python/**/source
examples/chatbot-ui/models

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@@ -1,31 +0,0 @@
root = true
[*]
indent_style = space
indent_size = 2
end_of_line = lf
charset = utf-8
trim_trailing_whitespace = true
insert_final_newline = true
[*.go]
indent_style = tab
[Makefile]
indent_style = tab
[*.proto]
indent_size = 2
[*.py]
indent_size = 4
[*.js]
indent_size = 2
[*.yaml]
indent_size = 2
[*.md]
trim_trailing_whitespace = false

102
.env
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@@ -1,97 +1,5 @@
## Set number of threads.
## Note: prefer the number of physical cores. Overbooking the CPU degrades performance notably.
# LOCALAI_THREADS=14
## Specify a different bind address (defaults to ":8080")
# LOCALAI_ADDRESS=127.0.0.1:8080
## Default models context size
# LOCALAI_CONTEXT_SIZE=512
#
## Define galleries.
## models will to install will be visible in `/models/available`
# LOCALAI_GALLERIES=[{"name":"localai", "url":"github:mudler/LocalAI/gallery/index.yaml@master"}]
## CORS settings
# LOCALAI_CORS=true
# LOCALAI_CORS_ALLOW_ORIGINS=*
## Default path for models
#
# LOCALAI_MODELS_PATH=/models
## Enable debug mode
# LOCALAI_LOG_LEVEL=debug
## Disables COMPEL (Diffusers)
# COMPEL=0
## Enable/Disable single backend (useful if only one GPU is available)
# LOCALAI_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 true to enable rebuilding from source
# REBUILD=true
## Enable go tags, available: stablediffusion, tts
## stablediffusion: image generation with stablediffusion
## tts: enables text-to-speech with go-piper
## (requires REBUILD=true)
#
# GO_TAGS=stablediffusion
## Path where to store generated images
# LOCALAI_IMAGE_PATH=/tmp/generated/images
## Specify a default upload limit in MB (whisper)
# LOCALAI_UPLOAD_LIMIT=15
## List of external GRPC backends (note on the container image this variable is already set to use extra backends available in extra/)
# LOCALAI_EXTERNAL_GRPC_BACKENDS=my-backend:127.0.0.1:9000,my-backend2:/usr/bin/backend.py
### Advanced settings ###
### Those are not really used by LocalAI, but from components in the stack ###
##
### Preload libraries
# LD_PRELOAD=
### Huggingface cache for models
# HUGGINGFACE_HUB_CACHE=/usr/local/huggingface
### Python backends GRPC max workers
### Default number of workers for GRPC Python backends.
### This actually controls wether a backend can process multiple requests or not.
# PYTHON_GRPC_MAX_WORKERS=1
### Define the number of parallel LLAMA.cpp workers (Defaults to 1)
# LLAMACPP_PARALLEL=1
### Define a list of GRPC Servers for llama-cpp workers to distribute the load
# https://github.com/ggerganov/llama.cpp/pull/6829
# https://github.com/ggerganov/llama.cpp/blob/master/examples/rpc/README.md
# LLAMACPP_GRPC_SERVERS=""
### Enable to run parallel requests
# LOCALAI_PARALLEL_REQUESTS=true
# Enable to allow p2p mode
# LOCALAI_P2P=true
### Watchdog settings
###
# Enables watchdog to kill backends that are inactive for too much time
# LOCALAI_WATCHDOG_IDLE=true
#
# Time in duration format (e.g. 1h30m) after which a backend is considered idle
# LOCALAI_WATCHDOG_IDLE_TIMEOUT=5m
#
# Enables watchdog to kill backends that are busy for too much time
# LOCALAI_WATCHDOG_BUSY=true
#
# Time in duration format (e.g. 1h30m) after which a backend is considered busy
# LOCALAI_WATCHDOG_BUSY_TIMEOUT=5m
# THREADS=14
# CONTEXT_SIZE=512
MODELS_PATH=/models
# DEBUG=true
# BUILD_TYPE=generic

1
.gitattributes vendored
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@@ -1 +0,0 @@
*.sh text eol=lf

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

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@@ -1,29 +0,0 @@
---
name: Bug report
about: Create a report to help us improve
title: ''
labels: bug, unconfirmed, up-for-grabs
---
<!-- Thanks for helping us to improve LocalAI! We welcome all bug reports. Please fill out each area of the template so we can better help you. Comments like this will be hidden when you post but you can delete them if you wish. -->
**LocalAI version:**
<!-- Container Image or LocalAI tag/commit -->
**Environment, CPU architecture, OS, and Version:**
<!-- Provide the output from "uname -a", HW specs, if it's a VM -->
**Describe the bug**
<!-- A clear and concise description of what the bug is. -->
**To Reproduce**
<!-- Steps to reproduce the behavior, including the LocalAI command used, if any -->
**Expected behavior**
<!-- A clear and concise description of what you expected to happen. -->
**Logs**
<!-- If applicable, add logs while running LocalAI in debug mode (`--debug` or `DEBUG=true`) to help explain your problem. -->
**Additional context**
<!-- Add any other context about the problem here. -->

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

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@@ -1,20 +0,0 @@
---
name: Feature request
about: Suggest an idea for this project
title: ''
labels: enhancement, up-for-grabs
---
<!-- Thanks for helping us to improve LocalAI! We welcome all feature requests. Please fill out each area of the template so we can better help you. Comments like this will be hidden when you post but you can delete them if you wish. -->
**Is your feature request related to a problem? Please describe.**
<!-- A clear and concise description of what the problem is. Ex. I'm always frustrated when [...] -->
**Describe the solution you'd like**
<!-- A clear and concise description of what you want to happen. -->
**Describe alternatives you've considered**
<!-- A clear and concise description of any alternative solutions or features you've considered. -->
**Additional context**
<!-- Add any other context or screenshots about the feature request here. -->

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@@ -1,31 +0,0 @@
**Description**
This PR fixes #
**Notes for Reviewers**
**[Signed commits](../CONTRIBUTING.md#signing-off-on-commits-developer-certificate-of-origin)**
- [ ] Yes, I signed my commits.
<!--
Thank you for contributing to LocalAI!
Contributing Conventions
-------------------------
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.
-->

22
.github/bump_deps.sh vendored
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@@ -1,22 +0,0 @@
#!/bin/bash
set -xe
REPO=$1
BRANCH=$2
VAR=$3
LAST_COMMIT=$(curl -s -H "Accept: application/vnd.github.VERSION.sha" "https://api.github.com/repos/$REPO/commits/$BRANCH")
# Read $VAR from Makefile (only first match)
set +e
CURRENT_COMMIT="$(grep -m1 "^$VAR?=" Makefile | cut -d'=' -f2)"
set -e
sed -i Makefile -e "s/$VAR?=.*/$VAR?=$LAST_COMMIT/"
if [ -z "$CURRENT_COMMIT" ]; then
echo "Could not find $VAR in Makefile."
exit 0
fi
echo "Changes: https://github.com/$REPO/compare/${CURRENT_COMMIT}..${LAST_COMMIT}" >> "${VAR}_message.txt"
echo "${LAST_COMMIT}" >> "${VAR}_commit.txt"

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@@ -1,7 +0,0 @@
#!/bin/bash
set -xe
REPO=$1
LATEST_TAG=$(curl -s "https://api.github.com/repos/$REPO/releases/latest" | jq -r '.tag_name')
cat <<< $(jq ".version = \"$LATEST_TAG\"" docs/data/version.json) > docs/data/version.json

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@@ -1,80 +0,0 @@
import hashlib
from huggingface_hub import hf_hub_download, get_paths_info
import requests
import sys
import os
uri = sys.argv[1]
file_name = uri.split('/')[-1]
# Function to parse the URI and determine download method
def parse_uri(uri):
if uri.startswith('huggingface://'):
repo_id = uri.split('://')[1]
return 'huggingface', repo_id.rsplit('/', 1)[0]
elif 'huggingface.co' in uri:
parts = uri.split('/resolve/')
if len(parts) > 1:
repo_path = parts[0].split('https://huggingface.co/')[-1]
return 'huggingface', repo_path
return 'direct', uri
def calculate_sha256(file_path):
sha256_hash = hashlib.sha256()
with open(file_path, 'rb') as f:
for byte_block in iter(lambda: f.read(4096), b''):
sha256_hash.update(byte_block)
return sha256_hash.hexdigest()
def manual_safety_check_hf(repo_id):
scanResponse = requests.get('https://huggingface.co/api/models/' + repo_id + "/scan")
scan = scanResponse.json()
if scan['hasUnsafeFile']:
return scan
return None
download_type, repo_id_or_url = parse_uri(uri)
new_checksum = None
file_path = None
# Decide download method based on URI type
if download_type == 'huggingface':
# Check if the repo is flagged as dangerous by HF
hazard = manual_safety_check_hf(repo_id_or_url)
if hazard != None:
print(f'Error: HuggingFace has detected security problems for {repo_id_or_url}: {str(hazard)}', filename=file_name)
sys.exit(5)
# Use HF API to pull sha
for file in get_paths_info(repo_id_or_url, [file_name], repo_type='model'):
try:
new_checksum = file.lfs.sha256
break
except Exception as e:
print(f'Error from Hugging Face Hub: {str(e)}', file=sys.stderr)
sys.exit(2)
if new_checksum is None:
try:
file_path = hf_hub_download(repo_id=repo_id_or_url, filename=file_name)
except Exception as e:
print(f'Error from Hugging Face Hub: {str(e)}', file=sys.stderr)
sys.exit(2)
else:
response = requests.get(repo_id_or_url)
if response.status_code == 200:
with open(file_name, 'wb') as f:
f.write(response.content)
file_path = file_name
elif response.status_code == 404:
print(f'File not found: {response.status_code}', file=sys.stderr)
sys.exit(2)
else:
print(f'Error downloading file: {response.status_code}', file=sys.stderr)
sys.exit(1)
if new_checksum is None:
new_checksum = calculate_sha256(file_path)
print(new_checksum)
os.remove(file_path)
else:
print(new_checksum)

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@@ -1,63 +0,0 @@
#!/bin/bash
# This scripts needs yq and huggingface_hub to be installed
# to install hugingface_hub run pip install huggingface_hub
# Path to the input YAML file
input_yaml=$1
# Function to download file and check checksum using Python
function check_and_update_checksum() {
model_name="$1"
file_name="$2"
uri="$3"
old_checksum="$4"
idx="$5"
# Download the file and calculate new checksum using Python
new_checksum=$(python3 ./.github/check_and_update.py $uri)
result=$?
if [[ $result -eq 5 ]]; then
echo "Contaminated entry detected, deleting entry for $model_name..."
yq eval -i "del([$idx])" "$input_yaml"
return
fi
if [[ "$new_checksum" == "" ]]; then
echo "Error calculating checksum for $file_name. Skipping..."
return
fi
echo "Checksum for $file_name: $new_checksum"
# Compare and update the YAML file if checksums do not match
if [[ $result -eq 2 ]]; then
echo "File not found, deleting entry for $file_name..."
# yq eval -i "del(.[$idx].files[] | select(.filename == \"$file_name\"))" "$input_yaml"
elif [[ "$old_checksum" != "$new_checksum" ]]; then
echo "Checksum mismatch for $file_name. Updating..."
yq eval -i "del(.[$idx].files[] | select(.filename == \"$file_name\").sha256)" "$input_yaml"
yq eval -i "(.[$idx].files[] | select(.filename == \"$file_name\")).sha256 = \"$new_checksum\"" "$input_yaml"
elif [[ $result -ne 0 ]]; then
echo "Error downloading file $file_name. Skipping..."
else
echo "Checksum match for $file_name. No update needed."
fi
}
# Read the YAML and process each file
len=$(yq eval '. | length' "$input_yaml")
for ((i=0; i<$len; i++))
do
name=$(yq eval ".[$i].name" "$input_yaml")
files_len=$(yq eval ".[$i].files | length" "$input_yaml")
for ((j=0; j<$files_len; j++))
do
filename=$(yq eval ".[$i].files[$j].filename" "$input_yaml")
uri=$(yq eval ".[$i].files[$j].uri" "$input_yaml")
checksum=$(yq eval ".[$i].files[$j].sha256" "$input_yaml")
echo "Checking model $name, file $filename. URI = $uri, Checksum = $checksum"
check_and_update_checksum "$name" "$filename" "$uri" "$checksum" "$i"
done
done

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@@ -1,297 +0,0 @@
package main
import (
"fmt"
"html/template"
"io/ioutil"
"os"
"gopkg.in/yaml.v3"
)
var modelPageTemplate string = `
<!DOCTYPE html>
<html>
<head>
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<title>LocalAI models</title>
<link href="https://cdnjs.cloudflare.com/ajax/libs/flowbite/2.3.0/flowbite.min.css" rel="stylesheet" />
<script src="https://cdn.jsdelivr.net/npm/vanilla-lazyload@19.1.3/dist/lazyload.min.js"></script>
<link
rel="stylesheet"
href="https://cdn.jsdelivr.net/gh/highlightjs/cdn-release@11.8.0/build/styles/default.min.css"
/>
<script
defer
src="https://cdn.jsdelivr.net/gh/highlightjs/cdn-release@11.8.0/build/highlight.min.js"
></script>
<script
defer
src="https://cdn.jsdelivr.net/npm/alpinejs@3.x.x/dist/cdn.min.js"
></script>
<script
defer
src="https://cdn.jsdelivr.net/npm/marked/marked.min.js"
></script>
<script
defer
src="https://cdn.jsdelivr.net/npm/dompurify@3.0.6/dist/purify.min.js"
></script>
<link href="/static/general.css" rel="stylesheet" />
<link href="https://fonts.googleapis.com/css2?family=Inter:wght@400;600;700&family=Roboto:wght@400;500&display=swap" rel="stylesheet">
<link
href="https://fonts.googleapis.com/css?family=Roboto:300,400,500,700,900&display=swap"
rel="stylesheet" />
<link
rel="stylesheet"
href="https://cdn.jsdelivr.net/npm/tw-elements/css/tw-elements.min.css" />
<script src="https://cdn.tailwindcss.com/3.3.0"></script>
<script>
tailwind.config = {
darkMode: "class",
theme: {
fontFamily: {
sans: ["Roboto", "sans-serif"],
body: ["Roboto", "sans-serif"],
mono: ["ui-monospace", "monospace"],
},
},
corePlugins: {
preflight: false,
},
};
</script>
<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/6.1.1/css/all.min.css">
<script src="https://unpkg.com/htmx.org@1.9.12" integrity="sha384-ujb1lZYygJmzgSwoxRggbCHcjc0rB2XoQrxeTUQyRjrOnlCoYta87iKBWq3EsdM2" crossorigin="anonymous"></script>
</head>
<body class="bg-gray-900 text-gray-200">
<div class="flex flex-col min-h-screen">
<nav class="bg-gray-800 shadow-lg">
<div class="container mx-auto px-4 py-4">
<div class="flex items-center justify-between">
<div class="flex items-center">
<a href="/" class="text-white text-xl font-bold"><img src="https://github.com/mudler/LocalAI/assets/2420543/0966aa2a-166e-4f99-a3e5-6c915fc997dd" alt="LocalAI Logo" class="h-10 mr-3 border-2 border-gray-300 shadow rounded"></a>
<a href="/" class="text-white text-xl font-bold">LocalAI</a>
</div>
<!-- Menu button for small screens -->
<div class="lg:hidden">
<button id="menu-toggle" class="text-gray-400 hover:text-white focus:outline-none">
<i class="fas fa-bars fa-lg"></i>
</button>
</div>
<!-- Navigation links -->
<div class="hidden lg:flex lg:items-center lg:justify-end lg:flex-1 lg:w-0">
<a href="https://localai.io" class="text-gray-400 hover:text-white px-3 py-2 rounded" target="_blank" ><i class="fas fa-book-reader pr-2"></i> Documentation</a>
</div>
</div>
<!-- Collapsible menu for small screens -->
<div class="hidden lg:hidden" id="mobile-menu">
<div class="pt-4 pb-3 border-t border-gray-700">
<a href="https://localai.io" class="block text-gray-400 hover:text-white px-3 py-2 rounded mt-1" target="_blank" ><i class="fas fa-book-reader pr-2"></i> Documentation</a>
</div>
</div>
</div>
</nav>
<style>
.is-hidden {
display: none;
}
</style>
<div class="container mx-auto px-4 flex-grow">
<div class="models mt-12">
<h2 class="text-center text-3xl font-semibold text-gray-100">
LocalAI model gallery list </h2><br>
<h2 class="text-center text-3xl font-semibold text-gray-100">
🖼️ Available {{.AvailableModels}} models</i> <a href="https://localai.io/models/" target="_blank" >
<i class="fas fa-circle-info pr-2"></i>
</a></h2>
<h3>
Refer to the Model gallery <a href="https://localai.io/models/" target="_blank" ><i class="fas fa-circle-info pr-2"></i></a> for more information on how to use the models with LocalAI.<br>
You can install models with the CLI command <code>local-ai models install <model-name></code>. or by using the WebUI.
</h3>
<input class="form-control appearance-none block w-full mt-5 px-3 py-2 text-base font-normal text-gray-300 pb-2 mb-5 bg-gray-800 bg-clip-padding border border-solid border-gray-600 rounded transition ease-in-out m-0 focus:text-gray-300 focus:bg-gray-900 focus:border-blue-500 focus:outline-none" type="search"
id="searchbox" placeholder="Live search keyword..">
<div class="dark grid grid-cols-1 grid-rows-1 md:grid-cols-3 block rounded-lg shadow-secondary-1 dark:bg-surface-dark">
{{ range $_, $model := .Models }}
<div class="box me-4 mb-2 block rounded-lg bg-white shadow-secondary-1 dark:bg-gray-800 dark:bg-surface-dark dark:text-white text-surface pb-2">
<div>
{{ $icon := "https://upload.wikimedia.org/wikipedia/commons/6/65/No-Image-Placeholder.svg" }}
{{ if $model.Icon }}
{{ $icon = $model.Icon }}
{{ end }}
<div class="flex justify-center items-center">
<img data-src="{{ $icon }}" alt="{{$model.Name}}" class="rounded-t-lg max-h-48 max-w-96 object-cover mt-3 lazy">
</div>
<div class="p-6 text-surface dark:text-white">
<h5 class="mb-2 text-xl font-medium leading-tight">{{$model.Name}}</h5>
<p class="mb-4 text-base truncate">{{ $model.Description }}</p>
</div>
<div class="px-6 pt-4 pb-2">
<!-- Modal toggle -->
<button data-modal-target="{{ $model.Name}}-modal" data-modal-toggle="{{ $model.Name }}-modal" class="block text-white bg-blue-700 hover:bg-blue-800 focus:ring-4 focus:outline-none focus:ring-blue-300 font-medium rounded-lg text-sm px-5 py-2.5 text-center dark:bg-blue-600 dark:hover:bg-blue-700 dark:focus:ring-blue-800" type="button">
More info
</button>
<!-- Main modal -->
<div id="{{ $model.Name}}-modal" tabindex="-1" aria-hidden="true" class="hidden overflow-y-auto overflow-x-hidden fixed top-0 right-0 left-0 z-50 justify-center items-center w-full md:inset-0 h-[calc(100%-1rem)] max-h-full">
<div class="relative p-4 w-full max-w-2xl max-h-full">
<!-- Modal content -->
<div class="relative bg-white rounded-lg shadow dark:bg-gray-700">
<!-- Modal header -->
<div class="flex items-center justify-between p-4 md:p-5 border-b rounded-t dark:border-gray-600">
<h3 class="text-xl font-semibold text-gray-900 dark:text-white">
{{ $model.Name}}
</h3>
<button type="button" class="text-gray-400 bg-transparent hover:bg-gray-200 hover:text-gray-900 rounded-lg text-sm w-8 h-8 ms-auto inline-flex justify-center items-center dark:hover:bg-gray-600 dark:hover:text-white" data-modal-hide="{{$model.Name}}-modal">
<svg class="w-3 h-3" aria-hidden="true" xmlns="http://www.w3.org/2000/svg" fill="none" viewBox="0 0 14 14">
<path stroke="currentColor" stroke-linecap="round" stroke-linejoin="round" stroke-width="2" d="m1 1 6 6m0 0 6 6M7 7l6-6M7 7l-6 6"/>
</svg>
<span class="sr-only">Close modal</span>
</button>
</div>
<!-- Modal body -->
<div class="p-4 md:p-5 space-y-4">
<div class="flex justify-center items-center">
<img data-src="{{ $icon }}" alt="{{$model.Name}}" class="lazy rounded-t-lg max-h-48 max-w-96 object-cover mt-3">
</div>
<p class="text-base leading-relaxed text-gray-500 dark:text-gray-400">
{{ $model.Description }}
</p>
<p class="text-base leading-relaxed text-gray-500 dark:text-gray-400">
To install the model with the CLI, run: <br>
<code> local-ai models install {{$model.Name}} </code> <br>
<hr>
See also <a href="https://localai.io/models/" target="_blank" >
Installation <i class="fas fa-circle-info pr-2"></i>
</a> to see how to install models with the REST API.
</p>
<p class="text-base leading-relaxed text-gray-500 dark:text-gray-400">
<ul>
{{ range $_, $u := $model.URLs }}
<li><a href="{{ $u }}" target=_blank><i class="fa-solid fa-link"></i> {{ $u }}</a></li>
{{ end }}
</ul>
</p>
</div>
<!-- Modal footer -->
<div class="flex items-center p-4 md:p-5 border-t border-gray-200 rounded-b dark:border-gray-600">
<button data-modal-hide="{{ $model.Name}}-modal" type="button" class="py-2.5 px-5 ms-3 text-sm font-medium text-gray-900 focus:outline-none bg-white rounded-lg border border-gray-200 hover:bg-gray-100 hover:text-blue-700 focus:z-10 focus:ring-4 focus:ring-gray-100 dark:focus:ring-gray-700 dark:bg-gray-800 dark:text-gray-400 dark:border-gray-600 dark:hover:text-white dark:hover:bg-gray-700">Close</button>
</div>
</div>
</div>
</div>
</div>
</div>
</div>
{{ end }}
</div>
</div>
</div>
<script>
var lazyLoadInstance = new LazyLoad({
// Your custom settings go here
});
let cards = document.querySelectorAll('.box')
function liveSearch() {
let search_query = document.getElementById("searchbox").value;
//Use innerText if all contents are visible
//Use textContent for including hidden elements
for (var i = 0; i < cards.length; i++) {
if(cards[i].textContent.toLowerCase()
.includes(search_query.toLowerCase())) {
cards[i].classList.remove("is-hidden");
} else {
cards[i].classList.add("is-hidden");
}
}
}
//A little delay
let typingTimer;
let typeInterval = 500;
let searchInput = document.getElementById('searchbox');
searchInput.addEventListener('keyup', () => {
clearTimeout(typingTimer);
typingTimer = setTimeout(liveSearch, typeInterval);
});
</script>
</div>
<script src="https://cdnjs.cloudflare.com/ajax/libs/flowbite/2.3.0/flowbite.min.js"></script>
</body>
</html>
`
type GalleryModel struct {
Name string `json:"name" yaml:"name"`
URLs []string `json:"urls" yaml:"urls"`
Icon string `json:"icon" yaml:"icon"`
Description string `json:"description" yaml:"description"`
}
func main() {
// read the YAML file which contains the models
f, err := ioutil.ReadFile(os.Args[1])
if err != nil {
fmt.Println("Error reading file:", err)
return
}
models := []*GalleryModel{}
err = yaml.Unmarshal(f, &models)
if err != nil {
// write to stderr
os.Stderr.WriteString("Error unmarshaling YAML: " + err.Error() + "\n")
return
}
// render the template
data := struct {
Models []*GalleryModel
AvailableModels int
}{
Models: models,
AvailableModels: len(models),
}
tmpl := template.Must(template.New("modelPage").Parse(modelPageTemplate))
err = tmpl.Execute(os.Stdout, data)
if err != nil {
fmt.Println("Error executing template:", err)
return
}
}

133
.github/dependabot.yml vendored
View File

@@ -1,133 +0,0 @@
# https://docs.github.com/en/code-security/dependabot/dependabot-version-updates/configuration-options-for-the-dependabot.yml-file
version: 2
updates:
- package-ecosystem: "gitsubmodule"
directory: "/"
schedule:
interval: "weekly"
- package-ecosystem: "gomod"
directory: "/"
schedule:
interval: "weekly"
- package-ecosystem: "github-actions"
# Workflow files stored in the default location of `.github/workflows`. (You don't need to specify `/.github/workflows` for `directory`. You can use `directory: "/"`.)
directory: "/"
schedule:
# Check for updates to GitHub Actions every weekday
interval: "weekly"
- package-ecosystem: "pip"
# Workflow files stored in the default location of `.github/workflows`. (You don't need to specify `/.github/workflows` for `directory`. You can use `directory: "/"`.)
directory: "/"
schedule:
# Check for updates to GitHub Actions every weekday
interval: "weekly"
- package-ecosystem: "docker"
# Workflow files stored in the default location of `.github/workflows`. (You don't need to specify `/.github/workflows` for `directory`. You can use `directory: "/"`.)
directory: "/"
schedule:
# Check for updates to GitHub Actions every weekday
interval: "weekly"
- package-ecosystem: "pip"
directory: "/backend/python/autogptq"
schedule:
interval: "weekly"
- package-ecosystem: "pip"
directory: "/backend/python/bark"
schedule:
interval: "weekly"
- package-ecosystem: "pip"
directory: "/backend/python/common/template"
schedule:
interval: "weekly"
- package-ecosystem: "pip"
directory: "/backend/python/coqui"
schedule:
interval: "weekly"
- package-ecosystem: "pip"
directory: "/backend/python/diffusers"
schedule:
interval: "weekly"
- package-ecosystem: "pip"
directory: "/backend/python/exllama"
schedule:
interval: "weekly"
- package-ecosystem: "pip"
directory: "/backend/python/exllama2"
schedule:
interval: "weekly"
- package-ecosystem: "pip"
directory: "/backend/python/mamba"
schedule:
interval: "weekly"
- package-ecosystem: "pip"
directory: "/backend/python/openvoice"
schedule:
interval: "weekly"
- package-ecosystem: "pip"
directory: "/backend/python/parler-tts"
schedule:
interval: "weekly"
- package-ecosystem: "pip"
directory: "/backend/python/rerankers"
schedule:
interval: "weekly"
- package-ecosystem: "pip"
directory: "/backend/python/sentencetransformers"
schedule:
interval: "weekly"
- package-ecosystem: "pip"
directory: "/backend/python/transformers"
schedule:
interval: "weekly"
- package-ecosystem: "pip"
directory: "/backend/python/transformers-musicgen"
schedule:
interval: "weekly"
- package-ecosystem: "pip"
directory: "/backend/python/vall-e-x"
schedule:
interval: "weekly"
- package-ecosystem: "pip"
directory: "/backend/python/vllm"
schedule:
interval: "weekly"
- package-ecosystem: "pip"
directory: "/examples/chainlit"
schedule:
interval: "weekly"
- package-ecosystem: "pip"
directory: "/examples/functions"
schedule:
interval: "weekly"
- package-ecosystem: "pip"
directory: "/examples/langchain/langchainpy-localai-example"
schedule:
interval: "weekly"
- package-ecosystem: "pip"
directory: "/examples/langchain-chroma"
schedule:
interval: "weekly"
- package-ecosystem: "pip"
directory: "/examples/streamlit-bot"
schedule:
interval: "weekly"
- package-ecosystem: "docker"
directory: "/examples/k8sgpt"
schedule:
interval: "weekly"
- package-ecosystem: "docker"
directory: "/examples/kubernetes"
schedule:
interval: "weekly"
- package-ecosystem: "docker"
directory: "/examples/langchain"
schedule:
interval: "weekly"
- package-ecosystem: "gomod"
directory: "/examples/semantic-todo"
schedule:
interval: "weekly"
- package-ecosystem: "docker"
directory: "/examples/telegram-bot"
schedule:
interval: "weekly"

24
.github/labeler.yml vendored
View File

@@ -1,24 +0,0 @@
enhancements:
- head-branch: ['^feature', 'feature']
kind/documentation:
- any:
- changed-files:
- any-glob-to-any-file: 'docs/*'
- changed-files:
- any-glob-to-any-file: '*.md'
area/ai-model:
- any:
- changed-files:
- any-glob-to-any-file: 'gallery/*'
examples:
- any:
- changed-files:
- any-glob-to-any-file: 'examples/*'
ci:
- any:
- changed-files:
- any-glob-to-any-file: '.github/*'

37
.github/release.yml vendored
View File

@@ -1,37 +0,0 @@
# .github/release.yml
changelog:
exclude:
labels:
- ignore-for-release
categories:
- title: Breaking Changes 🛠
labels:
- Semver-Major
- breaking-change
- title: "Bug fixes :bug:"
labels:
- bug
- regression
- title: "🖧 P2P area"
labels:
- area/p2p
- title: Exciting New Features 🎉
labels:
- Semver-Minor
- enhancement
- ux
- roadmap
- title: 🧠 Models
labels:
- area/ai-model
- title: 📖 Documentation and examples
labels:
- kind/documentation
- examples
- title: 👒 Dependencies
labels:
- dependencies
- title: Other Changes
labels:
- "*"

18
.github/stale.yml vendored
View File

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

View File

@@ -1,70 +0,0 @@
name: Bump dependencies
on:
schedule:
- cron: 0 20 * * *
workflow_dispatch:
jobs:
bump:
strategy:
fail-fast: false
matrix:
include:
- repository: "ggerganov/llama.cpp"
variable: "CPPLLAMA_VERSION"
branch: "master"
- repository: "go-skynet/go-ggml-transformers.cpp"
variable: "GOGGMLTRANSFORMERS_VERSION"
branch: "master"
- repository: "donomii/go-rwkv.cpp"
variable: "RWKV_VERSION"
branch: "main"
- repository: "ggerganov/whisper.cpp"
variable: "WHISPER_CPP_VERSION"
branch: "master"
- repository: "go-skynet/go-bert.cpp"
variable: "BERT_VERSION"
branch: "master"
- repository: "go-skynet/bloomz.cpp"
variable: "BLOOMZ_VERSION"
branch: "main"
- repository: "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@v4
- name: Bump dependencies 🔧
id: bump
run: |
bash .github/bump_deps.sh ${{ matrix.repository }} ${{ matrix.branch }} ${{ matrix.variable }}
{
echo 'message<<EOF'
cat "${{ matrix.variable }}_message.txt"
echo EOF
} >> "$GITHUB_OUTPUT"
{
echo 'commit<<EOF'
cat "${{ matrix.variable }}_commit.txt"
echo EOF
} >> "$GITHUB_OUTPUT"
rm -rfv ${{ matrix.variable }}_message.txt
rm -rfv ${{ matrix.variable }}_commit.txt
- name: Create Pull Request
uses: peter-evans/create-pull-request@v6
with:
token: ${{ secrets.UPDATE_BOT_TOKEN }}
push-to-fork: ci-forks/LocalAI
commit-message: ':arrow_up: Update ${{ matrix.repository }}'
title: 'chore: :arrow_up: Update ${{ matrix.repository }} to `${{ steps.bump.outputs.commit }}`'
branch: "update/${{ matrix.variable }}"
body: ${{ steps.bump.outputs.message }}
signoff: true

View File

@@ -1,31 +0,0 @@
name: Bump dependencies
on:
schedule:
- cron: 0 20 * * *
workflow_dispatch:
jobs:
bump:
strategy:
fail-fast: false
matrix:
include:
- repository: "mudler/LocalAI"
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- name: Bump dependencies 🔧
run: |
bash .github/bump_docs.sh ${{ matrix.repository }}
- name: Create Pull Request
uses: peter-evans/create-pull-request@v6
with:
token: ${{ secrets.UPDATE_BOT_TOKEN }}
push-to-fork: ci-forks/LocalAI
commit-message: ':arrow_up: Update docs version ${{ matrix.repository }}'
title: 'docs: :arrow_up: update docs version ${{ matrix.repository }}'
branch: "update/docs"
body: Bump of ${{ matrix.repository }} version inside docs
signoff: true

View File

@@ -1,47 +0,0 @@
name: Check if checksums are up-to-date
on:
schedule:
- cron: 0 20 * * *
workflow_dispatch:
jobs:
checksum_check:
runs-on: arc-runner-set
steps:
- name: Force Install GIT latest
run: |
sudo apt-get update \
&& sudo apt-get install -y software-properties-common \
&& sudo apt-get update \
&& sudo add-apt-repository -y ppa:git-core/ppa \
&& sudo apt-get update \
&& sudo apt-get install -y git
- uses: actions/checkout@v4
- name: Install dependencies
run: |
sudo apt-get update
sudo apt-get install -y pip wget
sudo pip install --upgrade pip
pip install huggingface_hub
- name: 'Setup yq'
uses: dcarbone/install-yq-action@v1.1.1
with:
version: 'v4.44.2'
download-compressed: true
force: true
- name: Checksum checker 🔧
run: |
export HF_HOME=/hf_cache
sudo mkdir /hf_cache
sudo chmod 777 /hf_cache
bash .github/checksum_checker.sh gallery/index.yaml
- name: Create Pull Request
uses: peter-evans/create-pull-request@v6
with:
token: ${{ secrets.UPDATE_BOT_TOKEN }}
push-to-fork: ci-forks/LocalAI
commit-message: ':arrow_up: Checksum updates in gallery/index.yaml'
title: 'chore(model-gallery): :arrow_up: update checksum'
branch: "update/checksum"
body: Updating checksums in gallery/index.yaml
signoff: true

View File

@@ -1,43 +0,0 @@
name: Dependabot auto-merge
on:
- pull_request_target
permissions:
contents: write
pull-requests: write
packages: read
jobs:
dependabot:
runs-on: ubuntu-latest
if: ${{ github.actor == 'dependabot[bot]' }}
steps:
- name: Dependabot metadata
id: metadata
uses: dependabot/fetch-metadata@v2.2.0
with:
github-token: "${{ secrets.GITHUB_TOKEN }}"
skip-commit-verification: true
- name: Checkout repository
uses: actions/checkout@v4
- name: Approve a PR if not already approved
run: |
gh pr checkout "$PR_URL"
if [ "$(gh pr status --json reviewDecision -q .currentBranch.reviewDecision)" != "APPROVED" ];
then
gh pr review --approve "$PR_URL"
else
echo "PR already approved.";
fi
env:
PR_URL: ${{github.event.pull_request.html_url}}
GITHUB_TOKEN: ${{secrets.GITHUB_TOKEN}}
- name: Enable auto-merge for Dependabot PRs
if: ${{ contains(github.event.pull_request.title, 'bump')}}
run: gh pr merge --auto --squash "$PR_URL"
env:
PR_URL: ${{github.event.pull_request.html_url}}
GITHUB_TOKEN: ${{secrets.GITHUB_TOKEN}}

View File

@@ -1,64 +0,0 @@
name: Explorer deployment
on:
push:
branches:
- master
tags:
- 'v*'
concurrency:
group: ci-deploy-${{ github.head_ref || github.ref }}-${{ github.repository }}
jobs:
build-linux:
runs-on: ubuntu-latest
steps:
- name: Clone
uses: actions/checkout@v4
with:
submodules: true
- uses: actions/setup-go@v5
with:
go-version: '1.21.x'
cache: false
- name: Dependencies
run: |
sudo apt-get update
sudo apt-get install -y wget curl build-essential ffmpeg protobuf-compiler ccache upx-ucl gawk cmake libgmock-dev
go install google.golang.org/grpc/cmd/protoc-gen-go-grpc@1958fcbe2ca8bd93af633f11e97d44e567e945af
go install google.golang.org/protobuf/cmd/protoc-gen-go@v1.34.2
make protogen-go
- name: Build api
run: |
CGO_ENABLED=0 make build-api
- name: rm
uses: appleboy/ssh-action@v1.0.3
with:
host: ${{ secrets.EXPLORER_SSH_HOST }}
username: ${{ secrets.EXPLORER_SSH_USERNAME }}
key: ${{ secrets.EXPLORER_SSH_KEY }}
port: ${{ secrets.EXPLORER_SSH_PORT }}
script: |
sudo rm -rf local-ai/ || true
- name: copy file via ssh
uses: appleboy/scp-action@v0.1.7
with:
host: ${{ secrets.EXPLORER_SSH_HOST }}
username: ${{ secrets.EXPLORER_SSH_USERNAME }}
key: ${{ secrets.EXPLORER_SSH_KEY }}
port: ${{ secrets.EXPLORER_SSH_PORT }}
source: "local-ai"
overwrite: true
rm: true
target: ./local-ai
- name: restarting
uses: appleboy/ssh-action@v1.0.3
with:
host: ${{ secrets.EXPLORER_SSH_HOST }}
username: ${{ secrets.EXPLORER_SSH_USERNAME }}
key: ${{ secrets.EXPLORER_SSH_KEY }}
port: ${{ secrets.EXPLORER_SSH_PORT }}
script: |
sudo cp -rfv local-ai/local-ai /usr/bin/local-ai
sudo systemctl restart local-ai

View File

@@ -1,83 +0,0 @@
name: Comment PRs
on:
pull_request_target:
jobs:
comment-pr:
env:
MODEL_NAME: hermes-2-theta-llama-3-8b
runs-on: ubuntu-latest
steps:
- name: Checkout code
uses: actions/checkout@v3
with:
ref: "${{ github.event.pull_request.merge_commit_sha }}"
fetch-depth: 0 # needed to checkout all branches for this Action to work
- uses: mudler/localai-github-action@v1
with:
model: 'hermes-2-theta-llama-3-8b' # Any from models.localai.io, or from huggingface.com with: "huggingface://<repository>/file"
# Check the PR diff using the current branch and the base branch of the PR
- uses: GrantBirki/git-diff-action@v2.7.0
id: git-diff-action
with:
json_diff_file_output: diff.json
raw_diff_file_output: diff.txt
file_output_only: "true"
base_branch: ${{ github.event.pull_request.base.sha }}
- name: Show diff
env:
DIFF: ${{ steps.git-diff-action.outputs.raw-diff-path }}
run: |
cat $DIFF
- name: Summarize
env:
DIFF: ${{ steps.git-diff-action.outputs.raw-diff-path }}
id: summarize
run: |
input="$(cat $DIFF)"
# Define the LocalAI API endpoint
API_URL="http://localhost:8080/chat/completions"
# Create a JSON payload using jq to handle special characters
json_payload=$(jq -n --arg input "$input" '{
model: "'$MODEL_NAME'",
messages: [
{
role: "system",
content: "You are LocalAI-bot in Github that helps understanding PRs and assess complexity. Explain what has changed in this PR diff and why"
},
{
role: "user",
content: $input
}
]
}')
# Send the request to LocalAI
response=$(curl -s -X POST $API_URL \
-H "Content-Type: application/json" \
-d "$json_payload")
# Extract the summary from the response
summary="$(echo $response | jq -r '.choices[0].message.content')"
# Print the summary
# -H "Authorization: Bearer $API_KEY" \
echo "Summary:"
echo "$summary"
echo "payload sent"
echo "$json_payload"
{
echo 'message<<EOF'
echo "$summary"
echo EOF
} >> "$GITHUB_OUTPUT"
docker logs --tail 10 local-ai
- uses: mshick/add-pr-comment@v2
if: always()
with:
repo-token: ${{ secrets.UPDATE_BOT_TOKEN }}
message: ${{ steps.summarize.outputs.message }}
message-failure: |
Uh oh! Could not analyze this PR, maybe it's too big?

View File

@@ -1,63 +0,0 @@
---
name: 'GPU tests'
on:
pull_request:
push:
branches:
- master
tags:
- '*'
concurrency:
group: ci-gpu-tests-${{ github.head_ref || github.ref }}-${{ github.repository }}
cancel-in-progress: true
jobs:
ubuntu-latest:
runs-on: gpu
strategy:
matrix:
go-version: ['1.21.x']
steps:
- name: Clone
uses: actions/checkout@v4
with:
submodules: true
- name: Setup Go ${{ matrix.go-version }}
uses: actions/setup-go@v4
with:
go-version: ${{ matrix.go-version }}
# You can test your matrix by printing the current Go version
- name: Display Go version
run: go version
- name: Dependencies
run: |
sudo apt-get update
sudo DEBIAN_FRONTEND=noninteractive apt-get install -y make wget
- name: Build
run: |
if [ ! -e /run/systemd/system ]; then
sudo mkdir /run/systemd/system
fi
sudo mkdir -p /host/tests/${{ github.head_ref || github.ref }}
sudo chmod -R 777 /host/tests/${{ github.head_ref || github.ref }}
make \
TEST_DIR="/host/tests/${{ github.head_ref || github.ref }}" \
BUILD_TYPE=cublas \
prepare-e2e run-e2e-image test-e2e
- name: Release space from worker ♻
if: always()
run: |
sudo rm -rf build || true
sudo rm -rf bin || true
sudo rm -rf dist || true
sudo docker logs $(sudo docker ps -q --filter ancestor=localai-tests) > logs.txt
sudo cat logs.txt || true
sudo rm -rf logs.txt
make clean || true
make \
TEST_DIR="/host/tests/${{ github.head_ref || github.ref }}" \
teardown-e2e || true
sudo rm -rf /host/tests/${{ github.head_ref || github.ref }} || true
docker system prune -f -a --volumes || true

View File

@@ -1,94 +0,0 @@
name: 'generate and publish GRPC docker caches'
on:
workflow_dispatch:
push:
branches:
- master
concurrency:
group: grpc-cache-${{ github.head_ref || github.ref }}-${{ github.repository }}
cancel-in-progress: true
jobs:
generate_caches:
strategy:
matrix:
include:
- grpc-base-image: ubuntu:22.04
runs-on: 'ubuntu-latest'
platforms: 'linux/amd64,linux/arm64'
runs-on: ${{matrix.runs-on}}
steps:
- name: Release space from worker
if: matrix.runs-on == 'ubuntu-latest'
run: |
echo "Listing top largest packages"
pkgs=$(dpkg-query -Wf '${Installed-Size}\t${Package}\t${Status}\n' | awk '$NF == "installed"{print $1 "\t" $2}' | sort -nr)
head -n 30 <<< "${pkgs}"
echo
df -h
echo
sudo apt-get remove -y '^llvm-.*|^libllvm.*' || true
sudo apt-get remove --auto-remove android-sdk-platform-tools || true
sudo apt-get purge --auto-remove android-sdk-platform-tools || true
sudo rm -rf /usr/local/lib/android
sudo apt-get remove -y '^dotnet-.*|^aspnetcore-.*' || true
sudo rm -rf /usr/share/dotnet
sudo apt-get remove -y '^mono-.*' || true
sudo apt-get remove -y '^ghc-.*' || true
sudo apt-get remove -y '.*jdk.*|.*jre.*' || true
sudo apt-get remove -y 'php.*' || true
sudo apt-get remove -y hhvm powershell firefox monodoc-manual msbuild || true
sudo apt-get remove -y '^google-.*' || true
sudo apt-get remove -y azure-cli || true
sudo apt-get remove -y '^mongo.*-.*|^postgresql-.*|^mysql-.*|^mssql-.*' || true
sudo apt-get remove -y '^gfortran-.*' || true
sudo apt-get remove -y microsoft-edge-stable || true
sudo apt-get remove -y firefox || true
sudo apt-get remove -y powershell || true
sudo apt-get remove -y r-base-core || true
sudo apt-get autoremove -y
sudo apt-get clean
echo
echo "Listing top largest packages"
pkgs=$(dpkg-query -Wf '${Installed-Size}\t${Package}\t${Status}\n' | awk '$NF == "installed"{print $1 "\t" $2}' | sort -nr)
head -n 30 <<< "${pkgs}"
echo
sudo rm -rfv build || true
sudo rm -rf /usr/share/dotnet || true
sudo rm -rf /opt/ghc || true
sudo rm -rf "/usr/local/share/boost" || true
sudo rm -rf "$AGENT_TOOLSDIRECTORY" || true
df -h
- name: Set up QEMU
uses: docker/setup-qemu-action@master
with:
platforms: all
- name: Set up Docker Buildx
id: buildx
uses: docker/setup-buildx-action@master
- name: Checkout
uses: actions/checkout@v4
- name: Cache GRPC
uses: docker/build-push-action@v6
with:
builder: ${{ steps.buildx.outputs.name }}
# The build-args MUST be an EXACT match between the image cache and other workflow steps that want to use that cache.
# This means that even the MAKEFLAGS have to be an EXACT match.
# If the build-args are not an EXACT match, it will result in a cache miss, which will require GRPC to be built from scratch.
build-args: |
GRPC_BASE_IMAGE=${{ matrix.grpc-base-image }}
GRPC_MAKEFLAGS=--jobs=4 --output-sync=target
GRPC_VERSION=v1.65.0
context: .
file: ./Dockerfile
cache-to: type=gha,ignore-error=true
cache-from: type=gha
target: grpc
platforms: ${{ matrix.platforms }}
push: false

View File

@@ -1,59 +0,0 @@
name: 'generate and publish intel docker caches'
on:
workflow_dispatch:
push:
branches:
- master
concurrency:
group: intel-cache-${{ github.head_ref || github.ref }}-${{ github.repository }}
cancel-in-progress: true
jobs:
generate_caches:
strategy:
matrix:
include:
- base-image: intel/oneapi-basekit:2024.2.0-devel-ubuntu22.04
runs-on: 'ubuntu-latest'
platforms: 'linux/amd64'
runs-on: ${{matrix.runs-on}}
steps:
- name: Set up QEMU
uses: docker/setup-qemu-action@master
with:
platforms: all
- name: Login to DockerHub
if: github.event_name != 'pull_request'
uses: docker/login-action@v3
with:
username: ${{ secrets.DOCKERHUB_USERNAME }}
password: ${{ secrets.DOCKERHUB_PASSWORD }}
- name: Login to quay
if: github.event_name != 'pull_request'
uses: docker/login-action@v3
with:
registry: quay.io
username: ${{ secrets.LOCALAI_REGISTRY_USERNAME }}
password: ${{ secrets.LOCALAI_REGISTRY_PASSWORD }}
- name: Set up Docker Buildx
id: buildx
uses: docker/setup-buildx-action@master
- name: Checkout
uses: actions/checkout@v4
- name: Cache Intel images
uses: docker/build-push-action@v6
with:
builder: ${{ steps.buildx.outputs.name }}
build-args: |
BASE_IMAGE=${{ matrix.base-image }}
context: .
file: ./Dockerfile
tags: quay.io/go-skynet/intel-oneapi-base:latest
push: true
target: intel
platforms: ${{ matrix.platforms }}

View File

@@ -1,140 +0,0 @@
---
name: 'build container images tests'
on:
pull_request:
concurrency:
group: ci-${{ github.head_ref || github.ref }}-${{ github.repository }}
cancel-in-progress: true
jobs:
extras-image-build:
uses: ./.github/workflows/image_build.yml
with:
tag-latest: ${{ matrix.tag-latest }}
tag-suffix: ${{ matrix.tag-suffix }}
ffmpeg: ${{ matrix.ffmpeg }}
image-type: ${{ matrix.image-type }}
build-type: ${{ matrix.build-type }}
cuda-major-version: ${{ matrix.cuda-major-version }}
cuda-minor-version: ${{ matrix.cuda-minor-version }}
platforms: ${{ matrix.platforms }}
runs-on: ${{ matrix.runs-on }}
base-image: ${{ matrix.base-image }}
grpc-base-image: ${{ matrix.grpc-base-image }}
makeflags: ${{ matrix.makeflags }}
secrets:
dockerUsername: ${{ secrets.DOCKERHUB_USERNAME }}
dockerPassword: ${{ secrets.DOCKERHUB_PASSWORD }}
quayUsername: ${{ secrets.LOCALAI_REGISTRY_USERNAME }}
quayPassword: ${{ secrets.LOCALAI_REGISTRY_PASSWORD }}
strategy:
# Pushing with all jobs in parallel
# eats the bandwidth of all the nodes
max-parallel: ${{ github.event_name != 'pull_request' && 4 || 8 }}
matrix:
include:
# This is basically covered by the AIO test
# - build-type: ''
# platforms: 'linux/amd64'
# tag-latest: 'false'
# tag-suffix: '-ffmpeg'
# ffmpeg: 'true'
# image-type: 'extras'
# runs-on: 'arc-runner-set'
# base-image: "ubuntu:22.04"
# makeflags: "--jobs=3 --output-sync=target"
- build-type: 'cublas'
cuda-major-version: "12"
cuda-minor-version: "0"
platforms: 'linux/amd64'
tag-latest: 'false'
tag-suffix: '-cublas-cuda12-ffmpeg'
ffmpeg: 'true'
image-type: 'extras'
runs-on: 'arc-runner-set'
base-image: "ubuntu:22.04"
makeflags: "--jobs=3 --output-sync=target"
# - build-type: 'hipblas'
# platforms: 'linux/amd64'
# tag-latest: 'false'
# tag-suffix: '-hipblas'
# ffmpeg: 'false'
# image-type: 'extras'
# base-image: "rocm/dev-ubuntu-22.04:6.1"
# grpc-base-image: "ubuntu:22.04"
# runs-on: 'arc-runner-set'
# makeflags: "--jobs=3 --output-sync=target"
# - build-type: 'sycl_f16'
# platforms: 'linux/amd64'
# tag-latest: 'false'
# base-image: "quay.io/go-skynet/intel-oneapi-base:latest"
# grpc-base-image: "ubuntu:22.04"
# tag-suffix: 'sycl-f16-ffmpeg'
# ffmpeg: 'true'
# image-type: 'extras'
# runs-on: 'arc-runner-set'
# makeflags: "--jobs=3 --output-sync=target"
# core-image-build:
# uses: ./.github/workflows/image_build.yml
# with:
# tag-latest: ${{ matrix.tag-latest }}
# tag-suffix: ${{ matrix.tag-suffix }}
# ffmpeg: ${{ matrix.ffmpeg }}
# image-type: ${{ matrix.image-type }}
# build-type: ${{ matrix.build-type }}
# cuda-major-version: ${{ matrix.cuda-major-version }}
# cuda-minor-version: ${{ matrix.cuda-minor-version }}
# platforms: ${{ matrix.platforms }}
# runs-on: ${{ matrix.runs-on }}
# base-image: ${{ matrix.base-image }}
# grpc-base-image: ${{ matrix.grpc-base-image }}
# makeflags: ${{ matrix.makeflags }}
# secrets:
# dockerUsername: ${{ secrets.DOCKERHUB_USERNAME }}
# dockerPassword: ${{ secrets.DOCKERHUB_PASSWORD }}
# quayUsername: ${{ secrets.LOCALAI_REGISTRY_USERNAME }}
# quayPassword: ${{ secrets.LOCALAI_REGISTRY_PASSWORD }}
# strategy:
# matrix:
# include:
# - build-type: ''
# platforms: 'linux/amd64'
# tag-latest: 'false'
# tag-suffix: '-ffmpeg-core'
# ffmpeg: 'true'
# image-type: 'core'
# runs-on: 'ubuntu-latest'
# base-image: "ubuntu:22.04"
# makeflags: "--jobs=4 --output-sync=target"
# - build-type: 'sycl_f16'
# platforms: 'linux/amd64'
# tag-latest: 'false'
# base-image: "quay.io/go-skynet/intel-oneapi-base:latest"
# grpc-base-image: "ubuntu:22.04"
# tag-suffix: 'sycl-f16-ffmpeg-core'
# ffmpeg: 'true'
# image-type: 'core'
# runs-on: 'arc-runner-set'
# makeflags: "--jobs=3 --output-sync=target"
# - build-type: 'cublas'
# cuda-major-version: "12"
# cuda-minor-version: "0"
# platforms: 'linux/amd64'
# tag-latest: 'false'
# tag-suffix: '-cublas-cuda12-ffmpeg-core'
# ffmpeg: 'true'
# image-type: 'core'
# runs-on: 'ubuntu-latest'
# base-image: "ubuntu:22.04"
# makeflags: "--jobs=4 --output-sync=target"
# - build-type: 'vulkan'
# platforms: 'linux/amd64'
# tag-latest: 'false'
# tag-suffix: '-vulkan-ffmpeg-core'
# ffmpeg: 'true'
# image-type: 'core'
# runs-on: 'ubuntu-latest'
# base-image: "ubuntu:22.04"
# makeflags: "--jobs=4 --output-sync=target"

View File

@@ -2,327 +2,77 @@
name: 'build container images'
on:
pull_request:
push:
branches:
- master
tags:
- '*'
concurrency:
group: ci-${{ github.head_ref || github.ref }}-${{ github.repository }}
cancel-in-progress: true
jobs:
self-hosted-jobs:
uses: ./.github/workflows/image_build.yml
with:
tag-latest: ${{ matrix.tag-latest }}
tag-suffix: ${{ matrix.tag-suffix }}
ffmpeg: ${{ matrix.ffmpeg }}
image-type: ${{ matrix.image-type }}
build-type: ${{ matrix.build-type }}
cuda-major-version: ${{ matrix.cuda-major-version }}
cuda-minor-version: ${{ matrix.cuda-minor-version }}
platforms: ${{ matrix.platforms }}
runs-on: ${{ matrix.runs-on }}
base-image: ${{ matrix.base-image }}
grpc-base-image: ${{ matrix.grpc-base-image }}
aio: ${{ matrix.aio }}
makeflags: ${{ matrix.makeflags }}
latest-image: ${{ matrix.latest-image }}
latest-image-aio: ${{ matrix.latest-image-aio }}
secrets:
dockerUsername: ${{ secrets.DOCKERHUB_USERNAME }}
dockerPassword: ${{ secrets.DOCKERHUB_PASSWORD }}
quayUsername: ${{ secrets.LOCALAI_REGISTRY_USERNAME }}
quayPassword: ${{ secrets.LOCALAI_REGISTRY_PASSWORD }}
strategy:
# Pushing with all jobs in parallel
# eats the bandwidth of all the nodes
max-parallel: ${{ github.event_name != 'pull_request' && 6 || 10 }}
matrix:
include:
# Extra images
- build-type: ''
#platforms: 'linux/amd64,linux/arm64'
platforms: 'linux/amd64'
tag-latest: 'auto'
tag-suffix: ''
ffmpeg: ''
image-type: 'extras'
runs-on: 'arc-runner-set'
base-image: "ubuntu:22.04"
makeflags: "--jobs=3 --output-sync=target"
- build-type: ''
platforms: 'linux/amd64'
tag-latest: 'auto'
tag-suffix: '-ffmpeg'
ffmpeg: 'true'
image-type: 'extras'
runs-on: 'arc-runner-set'
base-image: "ubuntu:22.04"
makeflags: "--jobs=3 --output-sync=target"
- build-type: 'cublas'
cuda-major-version: "11"
cuda-minor-version: "7"
platforms: 'linux/amd64'
tag-latest: 'false'
tag-suffix: '-cublas-cuda11'
ffmpeg: ''
image-type: 'extras'
runs-on: 'arc-runner-set'
base-image: "ubuntu:22.04"
makeflags: "--jobs=3 --output-sync=target"
- build-type: 'cublas'
cuda-major-version: "12"
cuda-minor-version: "0"
platforms: 'linux/amd64'
tag-latest: 'false'
tag-suffix: '-cublas-cuda12'
ffmpeg: ''
image-type: 'extras'
runs-on: 'arc-runner-set'
base-image: "ubuntu:22.04"
makeflags: "--jobs=3 --output-sync=target"
- build-type: 'cublas'
cuda-major-version: "11"
cuda-minor-version: "7"
platforms: 'linux/amd64'
tag-latest: 'auto'
tag-suffix: '-cublas-cuda11-ffmpeg'
ffmpeg: 'true'
image-type: 'extras'
runs-on: 'arc-runner-set'
base-image: "ubuntu:22.04"
aio: "-aio-gpu-nvidia-cuda-11"
latest-image: 'latest-gpu-nvidia-cuda-11'
latest-image-aio: 'latest-aio-gpu-nvidia-cuda-11'
makeflags: "--jobs=3 --output-sync=target"
- build-type: 'cublas'
cuda-major-version: "12"
cuda-minor-version: "0"
platforms: 'linux/amd64'
tag-latest: 'auto'
tag-suffix: '-cublas-cuda12-ffmpeg'
ffmpeg: 'true'
image-type: 'extras'
runs-on: 'arc-runner-set'
base-image: "ubuntu:22.04"
aio: "-aio-gpu-nvidia-cuda-12"
latest-image: 'latest-gpu-nvidia-cuda-12'
latest-image-aio: 'latest-aio-gpu-nvidia-cuda-12'
makeflags: "--jobs=3 --output-sync=target"
- build-type: ''
#platforms: 'linux/amd64,linux/arm64'
platforms: 'linux/amd64'
tag-latest: 'auto'
tag-suffix: ''
ffmpeg: ''
image-type: 'extras'
base-image: "ubuntu:22.04"
runs-on: 'arc-runner-set'
makeflags: "--jobs=3 --output-sync=target"
- build-type: 'hipblas'
platforms: 'linux/amd64'
tag-latest: 'auto'
tag-suffix: '-hipblas-ffmpeg'
ffmpeg: 'true'
image-type: 'extras'
aio: "-aio-gpu-hipblas"
base-image: "rocm/dev-ubuntu-22.04:6.1"
grpc-base-image: "ubuntu:22.04"
latest-image: 'latest-gpu-hipblas'
latest-image-aio: 'latest-aio-gpu-hipblas'
runs-on: 'arc-runner-set'
makeflags: "--jobs=3 --output-sync=target"
- build-type: 'hipblas'
platforms: 'linux/amd64'
tag-latest: 'false'
tag-suffix: '-hipblas'
ffmpeg: 'false'
image-type: 'extras'
base-image: "rocm/dev-ubuntu-22.04:6.1"
grpc-base-image: "ubuntu:22.04"
runs-on: 'arc-runner-set'
makeflags: "--jobs=3 --output-sync=target"
- build-type: 'sycl_f16'
platforms: 'linux/amd64'
tag-latest: 'auto'
base-image: "quay.io/go-skynet/intel-oneapi-base:latest"
grpc-base-image: "ubuntu:22.04"
tag-suffix: '-sycl-f16-ffmpeg'
ffmpeg: 'true'
image-type: 'extras'
runs-on: 'arc-runner-set'
aio: "-aio-gpu-intel-f16"
latest-image: 'latest-gpu-intel-f16'
latest-image-aio: 'latest-aio-gpu-intel-f16'
makeflags: "--jobs=3 --output-sync=target"
- build-type: 'sycl_f32'
platforms: 'linux/amd64'
tag-latest: 'auto'
base-image: "quay.io/go-skynet/intel-oneapi-base:latest"
grpc-base-image: "ubuntu:22.04"
tag-suffix: '-sycl-f32-ffmpeg'
ffmpeg: 'true'
image-type: 'extras'
runs-on: 'arc-runner-set'
aio: "-aio-gpu-intel-f32"
latest-image: 'latest-gpu-intel-f32'
latest-image-aio: 'latest-aio-gpu-intel-f32'
makeflags: "--jobs=3 --output-sync=target"
# Core images
- build-type: 'sycl_f16'
platforms: 'linux/amd64'
tag-latest: 'false'
base-image: "quay.io/go-skynet/intel-oneapi-base:latest"
grpc-base-image: "ubuntu:22.04"
tag-suffix: '-sycl-f16-core'
ffmpeg: 'false'
image-type: 'core'
runs-on: 'arc-runner-set'
makeflags: "--jobs=3 --output-sync=target"
- build-type: 'sycl_f32'
platforms: 'linux/amd64'
tag-latest: 'false'
base-image: "quay.io/go-skynet/intel-oneapi-base:latest"
grpc-base-image: "ubuntu:22.04"
tag-suffix: '-sycl-f32-core'
ffmpeg: 'false'
image-type: 'core'
runs-on: 'arc-runner-set'
makeflags: "--jobs=3 --output-sync=target"
- build-type: 'sycl_f16'
platforms: 'linux/amd64'
tag-latest: 'false'
base-image: "quay.io/go-skynet/intel-oneapi-base:latest"
grpc-base-image: "ubuntu:22.04"
tag-suffix: '-sycl-f16-ffmpeg-core'
ffmpeg: 'true'
image-type: 'core'
runs-on: 'arc-runner-set'
makeflags: "--jobs=3 --output-sync=target"
- build-type: 'sycl_f32'
platforms: 'linux/amd64'
tag-latest: 'false'
base-image: "quay.io/go-skynet/intel-oneapi-base:latest"
grpc-base-image: "ubuntu:22.04"
tag-suffix: '-sycl-f32-ffmpeg-core'
ffmpeg: 'true'
image-type: 'core'
runs-on: 'arc-runner-set'
makeflags: "--jobs=3 --output-sync=target"
- build-type: 'hipblas'
platforms: 'linux/amd64'
tag-latest: 'false'
tag-suffix: '-hipblas-ffmpeg-core'
ffmpeg: 'true'
image-type: 'core'
base-image: "rocm/dev-ubuntu-22.04:6.1"
grpc-base-image: "ubuntu:22.04"
runs-on: 'arc-runner-set'
makeflags: "--jobs=3 --output-sync=target"
- build-type: 'hipblas'
platforms: 'linux/amd64'
tag-latest: 'false'
tag-suffix: '-hipblas-core'
ffmpeg: 'false'
image-type: 'core'
base-image: "rocm/dev-ubuntu-22.04:6.1"
grpc-base-image: "ubuntu:22.04"
runs-on: 'arc-runner-set'
makeflags: "--jobs=3 --output-sync=target"
docker:
runs-on: ubuntu-latest
steps:
- name: Checkout
uses: actions/checkout@v3
core-image-build:
uses: ./.github/workflows/image_build.yml
with:
tag-latest: ${{ matrix.tag-latest }}
tag-suffix: ${{ matrix.tag-suffix }}
ffmpeg: ${{ matrix.ffmpeg }}
image-type: ${{ matrix.image-type }}
build-type: ${{ matrix.build-type }}
cuda-major-version: ${{ matrix.cuda-major-version }}
cuda-minor-version: ${{ matrix.cuda-minor-version }}
platforms: ${{ matrix.platforms }}
runs-on: ${{ matrix.runs-on }}
aio: ${{ matrix.aio }}
base-image: ${{ matrix.base-image }}
grpc-base-image: ${{ matrix.grpc-base-image }}
makeflags: ${{ matrix.makeflags }}
latest-image: ${{ matrix.latest-image }}
latest-image-aio: ${{ matrix.latest-image-aio }}
secrets:
dockerUsername: ${{ secrets.DOCKERHUB_USERNAME }}
dockerPassword: ${{ secrets.DOCKERHUB_PASSWORD }}
quayUsername: ${{ secrets.LOCALAI_REGISTRY_USERNAME }}
quayPassword: ${{ secrets.LOCALAI_REGISTRY_PASSWORD }}
strategy:
max-parallel: ${{ github.event_name != 'pull_request' && 2 || 4 }}
matrix:
include:
- build-type: ''
platforms: 'linux/amd64,linux/arm64'
tag-latest: 'auto'
tag-suffix: '-ffmpeg-core'
ffmpeg: 'true'
image-type: 'core'
base-image: "ubuntu:22.04"
runs-on: 'arc-runner-set'
aio: "-aio-cpu"
latest-image: 'latest-cpu'
latest-image-aio: 'latest-aio-cpu'
makeflags: "--jobs=4 --output-sync=target"
- build-type: 'cublas'
cuda-major-version: "11"
cuda-minor-version: "7"
platforms: 'linux/amd64'
tag-latest: 'false'
tag-suffix: '-cublas-cuda11-core'
ffmpeg: ''
image-type: 'core'
base-image: "ubuntu:22.04"
runs-on: 'arc-runner-set'
makeflags: "--jobs=4 --output-sync=target"
- build-type: 'cublas'
cuda-major-version: "12"
cuda-minor-version: "0"
platforms: 'linux/amd64'
tag-latest: 'false'
tag-suffix: '-cublas-cuda12-core'
ffmpeg: ''
image-type: 'core'
base-image: "ubuntu:22.04"
runs-on: 'arc-runner-set'
makeflags: "--jobs=4 --output-sync=target"
- build-type: 'cublas'
cuda-major-version: "11"
cuda-minor-version: "7"
platforms: 'linux/amd64'
tag-latest: 'false'
tag-suffix: '-cublas-cuda11-ffmpeg-core'
ffmpeg: 'true'
image-type: 'core'
runs-on: 'arc-runner-set'
base-image: "ubuntu:22.04"
makeflags: "--jobs=4 --output-sync=target"
- build-type: 'cublas'
cuda-major-version: "12"
cuda-minor-version: "0"
platforms: 'linux/amd64'
tag-latest: 'false'
tag-suffix: '-cublas-cuda12-ffmpeg-core'
ffmpeg: 'true'
image-type: 'core'
runs-on: 'arc-runner-set'
base-image: "ubuntu:22.04"
makeflags: "--jobs=4 --output-sync=target"
- build-type: 'vulkan'
platforms: 'linux/amd64'
tag-latest: 'false'
tag-suffix: '-vulkan-ffmpeg-core'
latest-image: 'latest-vulkan-ffmpeg-core'
ffmpeg: 'true'
image-type: 'core'
runs-on: 'arc-runner-set'
base-image: "ubuntu:22.04"
makeflags: "--jobs=4 --output-sync=target"
- name: Prepare
id: prep
run: |
DOCKER_IMAGE=quay.io/go-skynet/local-ai
VERSION=master
SHORTREF=${GITHUB_SHA::8}
# If this is git tag, use the tag name as a docker tag
if [[ $GITHUB_REF == refs/tags/* ]]; then
VERSION=${GITHUB_REF#refs/tags/}
fi
TAGS="${DOCKER_IMAGE}:${VERSION},${DOCKER_IMAGE}:${SHORTREF}"
# If the VERSION looks like a version number, assume that
# this is the most recent version of the image and also
# tag it 'latest'.
if [[ $VERSION =~ ^v[0-9]{1,3}\.[0-9]{1,3}\.[0-9]{1,3}$ ]]; then
TAGS="$TAGS,${DOCKER_IMAGE}:latest"
fi
# Set output parameters.
echo ::set-output name=tags::${TAGS}
echo ::set-output name=docker_image::${DOCKER_IMAGE}
- name: Set up QEMU
uses: docker/setup-qemu-action@master
with:
platforms: all
- name: Set up Docker Buildx
id: buildx
uses: docker/setup-buildx-action@master
- name: Login to DockerHub
if: github.event_name != 'pull_request'
uses: docker/login-action@v2
with:
registry: quay.io
username: ${{ secrets.QUAY_USERNAME }}
password: ${{ secrets.QUAY_PASSWORD }}
- name: Build
if: github.event_name != 'pull_request'
uses: docker/build-push-action@v4
with:
builder: ${{ steps.buildx.outputs.name }}
context: .
file: ./Dockerfile
platforms: linux/amd64,linux/arm64
push: true
tags: ${{ steps.prep.outputs.tags }}
- name: Build PRs
if: github.event_name == 'pull_request'
uses: docker/build-push-action@v4
with:
builder: ${{ steps.buildx.outputs.name }}
context: .
file: ./Dockerfile
platforms: linux/amd64
push: false
tags: ${{ steps.prep.outputs.tags }}

View File

@@ -1,335 +0,0 @@
---
name: 'build container images (reusable)'
on:
workflow_call:
inputs:
base-image:
description: 'Base image'
required: true
type: string
grpc-base-image:
description: 'GRPC Base image, must be a compatible image with base-image'
required: false
default: ''
type: string
build-type:
description: 'Build type'
default: ''
type: string
cuda-major-version:
description: 'CUDA major version'
default: "12"
type: string
cuda-minor-version:
description: 'CUDA minor version'
default: "4"
type: string
platforms:
description: 'Platforms'
default: ''
type: string
tag-latest:
description: 'Tag latest'
default: ''
type: string
latest-image:
description: 'Tag latest'
default: ''
type: string
latest-image-aio:
description: 'Tag latest'
default: ''
type: string
tag-suffix:
description: 'Tag suffix'
default: ''
type: string
ffmpeg:
description: 'FFMPEG'
default: ''
type: string
image-type:
description: 'Image type'
default: ''
type: string
runs-on:
description: 'Runs on'
required: true
default: ''
type: string
makeflags:
description: 'Make Flags'
required: false
default: '--jobs=4 --output-sync=target'
type: string
aio:
description: 'AIO Image Name'
required: false
default: ''
type: string
secrets:
dockerUsername:
required: true
dockerPassword:
required: true
quayUsername:
required: true
quayPassword:
required: true
jobs:
reusable_image-build:
runs-on: ${{ inputs.runs-on }}
steps:
- name: Force Install GIT latest
run: |
sudo apt-get update \
&& sudo apt-get install -y software-properties-common \
&& sudo apt-get update \
&& sudo add-apt-repository -y ppa:git-core/ppa \
&& sudo apt-get update \
&& sudo apt-get install -y git
- name: Checkout
uses: actions/checkout@v4
- name: Release space from worker
if: inputs.runs-on == 'ubuntu-latest'
run: |
echo "Listing top largest packages"
pkgs=$(dpkg-query -Wf '${Installed-Size}\t${Package}\t${Status}\n' | awk '$NF == "installed"{print $1 "\t" $2}' | sort -nr)
head -n 30 <<< "${pkgs}"
echo
df -h
echo
sudo apt-get remove -y '^llvm-.*|^libllvm.*' || true
sudo apt-get remove --auto-remove android-sdk-platform-tools || true
sudo apt-get purge --auto-remove android-sdk-platform-tools || true
sudo rm -rf /usr/local/lib/android
sudo apt-get remove -y '^dotnet-.*|^aspnetcore-.*' || true
sudo rm -rf /usr/share/dotnet
sudo apt-get remove -y '^mono-.*' || true
sudo apt-get remove -y '^ghc-.*' || true
sudo apt-get remove -y '.*jdk.*|.*jre.*' || true
sudo apt-get remove -y 'php.*' || true
sudo apt-get remove -y hhvm powershell firefox monodoc-manual msbuild || true
sudo apt-get remove -y '^google-.*' || true
sudo apt-get remove -y azure-cli || true
sudo apt-get remove -y '^mongo.*-.*|^postgresql-.*|^mysql-.*|^mssql-.*' || true
sudo apt-get remove -y '^gfortran-.*' || true
sudo apt-get remove -y microsoft-edge-stable || true
sudo apt-get remove -y firefox || true
sudo apt-get remove -y powershell || true
sudo apt-get remove -y r-base-core || true
sudo apt-get autoremove -y
sudo apt-get clean
echo
echo "Listing top largest packages"
pkgs=$(dpkg-query -Wf '${Installed-Size}\t${Package}\t${Status}\n' | awk '$NF == "installed"{print $1 "\t" $2}' | sort -nr)
head -n 30 <<< "${pkgs}"
echo
sudo rm -rfv build || true
sudo rm -rf /usr/share/dotnet || true
sudo rm -rf /opt/ghc || true
sudo rm -rf "/usr/local/share/boost" || true
sudo rm -rf "$AGENT_TOOLSDIRECTORY" || true
df -h
- name: Docker meta
id: meta
if: github.event_name != 'pull_request'
uses: docker/metadata-action@v5
with:
images: |
quay.io/go-skynet/local-ai
localai/localai
tags: |
type=ref,event=branch
type=semver,pattern={{raw}}
type=sha
flavor: |
latest=${{ inputs.tag-latest }}
suffix=${{ inputs.tag-suffix }}
- name: Docker meta for PR
id: meta_pull_request
if: github.event_name == 'pull_request'
uses: docker/metadata-action@v5
with:
images: |
ttl.sh/localai-ci-pr-${{ github.event.number }}
tags: |
type=ref,event=branch
type=semver,pattern={{raw}}
type=sha
flavor: |
latest=${{ inputs.tag-latest }}
suffix=${{ inputs.tag-suffix }}
- name: Docker meta AIO (quay.io)
if: inputs.aio != ''
id: meta_aio
uses: docker/metadata-action@v5
with:
images: |
quay.io/go-skynet/local-ai
tags: |
type=ref,event=branch
type=semver,pattern={{raw}}
flavor: |
latest=${{ inputs.tag-latest }}
suffix=${{ inputs.aio }}
- name: Docker meta AIO (dockerhub)
if: inputs.aio != ''
id: meta_aio_dockerhub
uses: docker/metadata-action@v5
with:
images: |
localai/localai
tags: |
type=ref,event=branch
type=semver,pattern={{raw}}
flavor: |
suffix=${{ inputs.aio }}
- name: Set up QEMU
uses: docker/setup-qemu-action@master
with:
platforms: all
- name: Set up Docker Buildx
id: buildx
uses: docker/setup-buildx-action@master
- name: Login to DockerHub
if: github.event_name != 'pull_request'
uses: docker/login-action@v3
with:
username: ${{ secrets.dockerUsername }}
password: ${{ secrets.dockerPassword }}
- name: Login to DockerHub
if: github.event_name != 'pull_request'
uses: docker/login-action@v3
with:
registry: quay.io
username: ${{ secrets.quayUsername }}
password: ${{ secrets.quayPassword }}
- name: Build and push
uses: docker/build-push-action@v6
if: github.event_name != 'pull_request'
with:
builder: ${{ steps.buildx.outputs.name }}
# The build-args MUST be an EXACT match between the image cache and other workflow steps that want to use that cache.
# This means that even the MAKEFLAGS have to be an EXACT match.
# If the build-args are not an EXACT match, it will result in a cache miss, which will require GRPC to be built from scratch.
# This is why some build args like GRPC_VERSION and MAKEFLAGS are hardcoded
build-args: |
BUILD_TYPE=${{ inputs.build-type }}
CUDA_MAJOR_VERSION=${{ inputs.cuda-major-version }}
CUDA_MINOR_VERSION=${{ inputs.cuda-minor-version }}
FFMPEG=${{ inputs.ffmpeg }}
IMAGE_TYPE=${{ inputs.image-type }}
BASE_IMAGE=${{ inputs.base-image }}
GRPC_BASE_IMAGE=${{ inputs.grpc-base-image || inputs.base-image }}
GRPC_MAKEFLAGS=--jobs=4 --output-sync=target
GRPC_VERSION=v1.65.0
MAKEFLAGS=${{ inputs.makeflags }}
context: .
file: ./Dockerfile
cache-from: type=gha
platforms: ${{ inputs.platforms }}
push: ${{ github.event_name != 'pull_request' }}
tags: ${{ steps.meta.outputs.tags }}
labels: ${{ steps.meta.outputs.labels }}
### Start testing image
- name: Build and push
uses: docker/build-push-action@v6
if: github.event_name == 'pull_request'
with:
builder: ${{ steps.buildx.outputs.name }}
# The build-args MUST be an EXACT match between the image cache and other workflow steps that want to use that cache.
# This means that even the MAKEFLAGS have to be an EXACT match.
# If the build-args are not an EXACT match, it will result in a cache miss, which will require GRPC to be built from scratch.
# This is why some build args like GRPC_VERSION and MAKEFLAGS are hardcoded
build-args: |
BUILD_TYPE=${{ inputs.build-type }}
CUDA_MAJOR_VERSION=${{ inputs.cuda-major-version }}
CUDA_MINOR_VERSION=${{ inputs.cuda-minor-version }}
FFMPEG=${{ inputs.ffmpeg }}
IMAGE_TYPE=${{ inputs.image-type }}
BASE_IMAGE=${{ inputs.base-image }}
GRPC_BASE_IMAGE=${{ inputs.grpc-base-image || inputs.base-image }}
GRPC_MAKEFLAGS=--jobs=4 --output-sync=target
GRPC_VERSION=v1.65.0
MAKEFLAGS=${{ inputs.makeflags }}
context: .
file: ./Dockerfile
cache-from: type=gha
platforms: ${{ inputs.platforms }}
push: true
tags: ${{ steps.meta_pull_request.outputs.tags }}
labels: ${{ steps.meta_pull_request.outputs.labels }}
- name: Testing image
if: github.event_name == 'pull_request'
run: |
echo "Image is available at ttl.sh/localai-ci-pr-${{ github.event.number }}:${{ steps.meta_pull_request.outputs.version }}" >> $GITHUB_STEP_SUMMARY
## End testing image
- name: Build and push AIO image
if: inputs.aio != ''
uses: docker/build-push-action@v6
with:
builder: ${{ steps.buildx.outputs.name }}
build-args: |
BASE_IMAGE=quay.io/go-skynet/local-ai:${{ steps.meta.outputs.version }}
MAKEFLAGS=${{ inputs.makeflags }}
context: .
file: ./Dockerfile.aio
platforms: ${{ inputs.platforms }}
push: ${{ github.event_name != 'pull_request' }}
tags: ${{ steps.meta_aio.outputs.tags }}
labels: ${{ steps.meta_aio.outputs.labels }}
- name: Build and push AIO image (dockerhub)
if: inputs.aio != ''
uses: docker/build-push-action@v6
with:
builder: ${{ steps.buildx.outputs.name }}
build-args: |
BASE_IMAGE=localai/localai:${{ steps.meta.outputs.version }}
MAKEFLAGS=${{ inputs.makeflags }}
context: .
file: ./Dockerfile.aio
platforms: ${{ inputs.platforms }}
push: ${{ github.event_name != 'pull_request' }}
tags: ${{ steps.meta_aio_dockerhub.outputs.tags }}
labels: ${{ steps.meta_aio_dockerhub.outputs.labels }}
- name: Latest tag
# run this on branches, when it is a tag and there is a latest-image defined
if: github.event_name != 'pull_request' && inputs.latest-image != '' && github.ref_type == 'tag'
run: |
docker pull localai/localai:${{ steps.meta.outputs.version }}
docker tag localai/localai:${{ steps.meta.outputs.version }} localai/localai:${{ inputs.latest-image }}
docker push localai/localai:${{ inputs.latest-image }}
docker pull quay.io/go-skynet/local-ai:${{ steps.meta.outputs.version }}
docker tag quay.io/go-skynet/local-ai:${{ steps.meta.outputs.version }} quay.io/go-skynet/local-ai:${{ inputs.latest-image }}
docker push quay.io/go-skynet/local-ai:${{ inputs.latest-image }}
- name: Latest AIO tag
# run this on branches, when it is a tag and there is a latest-image defined
if: github.event_name != 'pull_request' && inputs.latest-image-aio != '' && github.ref_type == 'tag'
run: |
docker pull localai/localai:${{ steps.meta_aio_dockerhub.outputs.version }}
docker tag localai/localai:${{ steps.meta_aio_dockerhub.outputs.version }} localai/localai:${{ inputs.latest-image-aio }}
docker push localai/localai:${{ inputs.latest-image-aio }}
docker pull quay.io/go-skynet/local-ai:${{ steps.meta_aio.outputs.version }}
docker tag quay.io/go-skynet/local-ai:${{ steps.meta_aio.outputs.version }} quay.io/go-skynet/local-ai:${{ inputs.latest-image-aio }}
docker push quay.io/go-skynet/local-ai:${{ inputs.latest-image-aio }}
- name: job summary
run: |
echo "Built image: ${{ steps.meta.outputs.labels }}" >> $GITHUB_STEP_SUMMARY
- name: job summary(AIO)
if: inputs.aio != ''
run: |
echo "Built image: ${{ steps.meta_aio.outputs.labels }}" >> $GITHUB_STEP_SUMMARY

View File

@@ -1,12 +0,0 @@
name: "Pull Request Labeler"
on:
- pull_request_target
jobs:
labeler:
permissions:
contents: read
pull-requests: write
runs-on: ubuntu-latest
steps:
- uses: actions/labeler@v5

View File

@@ -1,35 +0,0 @@
name: LocalAI-bot auto-merge
on:
- pull_request_target
permissions:
contents: write
pull-requests: write
packages: read
jobs:
dependabot:
runs-on: ubuntu-latest
if: ${{ github.actor == 'localai-bot' }}
steps:
- name: Checkout repository
uses: actions/checkout@v4
- name: Approve a PR if not already approved
run: |
gh pr checkout "$PR_URL"
if [ "$(gh pr status --json reviewDecision -q .currentBranch.reviewDecision)" != "APPROVED" ];
then
gh pr review --approve "$PR_URL"
else
echo "PR already approved.";
fi
env:
PR_URL: ${{github.event.pull_request.html_url}}
GITHUB_TOKEN: ${{secrets.GITHUB_TOKEN}}
- name: Enable auto-merge for LocalAIBot PRs
run: gh pr merge --auto --squash "$PR_URL"
env:
PR_URL: ${{github.event.pull_request.html_url}}
GITHUB_TOKEN: ${{secrets.GITHUB_TOKEN}}

View File

@@ -1,168 +0,0 @@
name: Notifications for new models
on:
pull_request:
types:
- closed
jobs:
notify-discord:
if: ${{ (github.event.pull_request.merged == true) && (contains(github.event.pull_request.labels.*.name, 'area/ai-model')) }}
env:
MODEL_NAME: hermes-2-theta-llama-3-8b
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
with:
fetch-depth: 0 # needed to checkout all branches for this Action to work
- uses: mudler/localai-github-action@v1
with:
model: 'hermes-2-theta-llama-3-8b' # Any from models.localai.io, or from huggingface.com with: "huggingface://<repository>/file"
# Check the PR diff using the current branch and the base branch of the PR
- uses: GrantBirki/git-diff-action@v2.7.0
id: git-diff-action
with:
json_diff_file_output: diff.json
raw_diff_file_output: diff.txt
file_output_only: "true"
- name: Summarize
env:
DIFF: ${{ steps.git-diff-action.outputs.raw-diff-path }}
id: summarize
run: |
input="$(cat $DIFF)"
# Define the LocalAI API endpoint
API_URL="http://localhost:8080/chat/completions"
# Create a JSON payload using jq to handle special characters
json_payload=$(jq -n --arg input "$input" '{
model: "'$MODEL_NAME'",
messages: [
{
role: "system",
content: "You are LocalAI-bot. Write a discord message to notify everyone about the new model from the git diff. Make it informal. An example can include: the URL of the model, the name, and a brief description of the model if exists. Also add an hint on how to install it in LocalAI and that can be browsed over https://models.localai.io. For example: local-ai run model_name_here"
},
{
role: "user",
content: $input
}
]
}')
# Send the request to LocalAI
response=$(curl -s -X POST $API_URL \
-H "Content-Type: application/json" \
-d "$json_payload")
# Extract the summary from the response
summary="$(echo $response | jq -r '.choices[0].message.content')"
# Print the summary
# -H "Authorization: Bearer $API_KEY" \
echo "Summary:"
echo "$summary"
echo "payload sent"
echo "$json_payload"
{
echo 'message<<EOF'
echo "$summary"
echo EOF
} >> "$GITHUB_OUTPUT"
docker logs --tail 10 local-ai
- name: Discord notification
env:
DISCORD_WEBHOOK: ${{ secrets.DISCORD_WEBHOOK_URL }}
DISCORD_USERNAME: "LocalAI-Bot"
DISCORD_AVATAR: "https://avatars.githubusercontent.com/u/139863280?v=4"
uses: Ilshidur/action-discord@master
with:
args: ${{ steps.summarize.outputs.message }}
- name: Setup tmate session if fails
if: ${{ failure() }}
uses: mxschmitt/action-tmate@v3.18
with:
detached: true
connect-timeout-seconds: 180
limit-access-to-actor: true
notify-twitter:
if: ${{ (github.event.pull_request.merged == true) && (contains(github.event.pull_request.labels.*.name, 'area/ai-model')) }}
env:
MODEL_NAME: hermes-2-theta-llama-3-8b
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
with:
fetch-depth: 0 # needed to checkout all branches for this Action to work
- name: Start LocalAI
run: |
echo "Starting LocalAI..."
docker run -e -ti -d --name local-ai -p 8080:8080 localai/localai:master-ffmpeg-core run --debug $MODEL_NAME
until [ "`docker inspect -f {{.State.Health.Status}} local-ai`" == "healthy" ]; do echo "Waiting for container to be ready"; docker logs --tail 10 local-ai; sleep 2; done
# Check the PR diff using the current branch and the base branch of the PR
- uses: GrantBirki/git-diff-action@v2.7.0
id: git-diff-action
with:
json_diff_file_output: diff.json
raw_diff_file_output: diff.txt
file_output_only: "true"
- name: Summarize
env:
DIFF: ${{ steps.git-diff-action.outputs.raw-diff-path }}
id: summarize
run: |
input="$(cat $DIFF)"
# Define the LocalAI API endpoint
API_URL="http://localhost:8080/chat/completions"
# Create a JSON payload using jq to handle special characters
json_payload=$(jq -n --arg input "$input" '{
model: "'$MODEL_NAME'",
messages: [
{
role: "system",
content: "You are LocalAI-bot. Write a twitter message to notify everyone about the new model from the git diff. Make it informal and really short. An example can include: the name, and a brief description of the model if exists. Also add an hint on how to install it in LocalAI. For example: local-ai run model_name_here"
},
{
role: "user",
content: $input
}
]
}')
# Send the request to LocalAI
response=$(curl -s -X POST $API_URL \
-H "Content-Type: application/json" \
-d "$json_payload")
# Extract the summary from the response
summary="$(echo $response | jq -r '.choices[0].message.content')"
# Print the summary
# -H "Authorization: Bearer $API_KEY" \
echo "Summary:"
echo "$summary"
echo "payload sent"
echo "$json_payload"
{
echo 'message<<EOF'
echo "$summary"
echo EOF
} >> "$GITHUB_OUTPUT"
docker logs --tail 10 local-ai
- uses: Eomm/why-don-t-you-tweet@v2
with:
tweet-message: ${{ steps.summarize.outputs.message }}
env:
# Get your tokens from https://developer.twitter.com/apps
TWITTER_CONSUMER_API_KEY: ${{ secrets.TWITTER_APP_KEY }}
TWITTER_CONSUMER_API_SECRET: ${{ secrets.TWITTER_APP_SECRET }}
TWITTER_ACCESS_TOKEN: ${{ secrets.TWITTER_ACCESS_TOKEN }}
TWITTER_ACCESS_TOKEN_SECRET: ${{ secrets.TWITTER_ACCESS_TOKEN_SECRET }}
- name: Setup tmate session if fails
if: ${{ failure() }}
uses: mxschmitt/action-tmate@v3.18
with:
detached: true
connect-timeout-seconds: 180
limit-access-to-actor: true

View File

@@ -1,63 +0,0 @@
name: Release notifications
on:
release:
types:
- published
jobs:
notify-discord:
runs-on: ubuntu-latest
env:
RELEASE_BODY: ${{ github.event.release.body }}
RELEASE_TITLE: ${{ github.event.release.name }}
RELEASE_TAG_NAME: ${{ github.event.release.tag_name }}
steps:
- uses: mudler/localai-github-action@v1
with:
model: 'hermes-2-theta-llama-3-8b' # Any from models.localai.io, or from huggingface.com with: "huggingface://<repository>/file"
- name: Summarize
id: summarize
run: |
input="$RELEASE_TITLE\b$RELEASE_BODY"
# Define the LocalAI API endpoint
API_URL="http://localhost:8080/chat/completions"
# Create a JSON payload using jq to handle special characters
json_payload=$(jq -n --arg input "$input" '{
model: "'$MODEL_NAME'",
messages: [
{
role: "system",
content: "Write a discord message with a bullet point summary of the release notes."
},
{
role: "user",
content: $input
}
]
}')
# Send the request to LocalAI API
response=$(curl -s -X POST $API_URL \
-H "Content-Type: application/json" \
-d "$json_payload")
# Extract the summary from the response
summary=$(echo $response | jq -r '.choices[0].message.content')
# Print the summary
# -H "Authorization: Bearer $API_KEY" \
{
echo 'message<<EOF'
echo "$summary"
echo EOF
} >> "$GITHUB_OUTPUT"
- name: Discord notification
env:
DISCORD_WEBHOOK: ${{ secrets.DISCORD_WEBHOOK_URL_RELEASE }}
DISCORD_USERNAME: "LocalAI-Bot"
DISCORD_AVATAR: "https://avatars.githubusercontent.com/u/139863280?v=4"
uses: Ilshidur/action-discord@master
with:
args: ${{ steps.summarize.outputs.message }}

View File

@@ -1,28 +0,0 @@
name: Check PR style
on:
pull_request_target:
types:
- opened
- reopened
- edited
- synchronize
jobs:
title-lint:
runs-on: ubuntu-latest
permissions:
statuses: write
steps:
- uses: aslafy-z/conventional-pr-title-action@v3
env:
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
# check-pr-description:
# runs-on: ubuntu-latest
# steps:
# - uses: actions/checkout@v2
# - uses: jadrol/pr-description-checker-action@v1.0.0
# id: description-checker
# with:
# repo-token: ${{ secrets.GITHUB_TOKEN }}
# exempt-labels: no qa

View File

@@ -1,357 +0,0 @@
name: Build and Release
on:
push:
branches:
- master
tags:
- 'v*'
pull_request:
env:
GRPC_VERSION: v1.65.0
permissions:
contents: write
concurrency:
group: ci-releases-${{ github.head_ref || github.ref }}-${{ github.repository }}
cancel-in-progress: true
jobs:
build-linux-arm:
runs-on: ubuntu-latest
steps:
- name: Clone
uses: actions/checkout@v4
with:
submodules: true
- uses: actions/setup-go@v5
with:
go-version: '1.21.x'
cache: false
- name: Dependencies
run: |
sudo apt-get update
sudo apt-get install build-essential ffmpeg protobuf-compiler ccache upx-ucl gawk
sudo apt-get install -qy binutils-aarch64-linux-gnu gcc-aarch64-linux-gnu g++-aarch64-linux-gnu libgmock-dev
- name: Install CUDA Dependencies
run: |
curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/cross-linux-aarch64/cuda-keyring_1.1-1_all.deb
sudo dpkg -i cuda-keyring_1.1-1_all.deb
sudo apt-get update
sudo apt-get install -y cuda-cross-aarch64 cuda-nvcc-cross-aarch64-${CUDA_VERSION} libcublas-cross-aarch64-${CUDA_VERSION}
env:
CUDA_VERSION: 12-4
- name: Cache grpc
id: cache-grpc
uses: actions/cache@v4
with:
path: grpc
key: ${{ runner.os }}-arm-grpc-${{ env.GRPC_VERSION }}
- name: Build grpc
if: steps.cache-grpc.outputs.cache-hit != 'true'
run: |
git clone --recurse-submodules -b ${{ env.GRPC_VERSION }} --depth 1 --shallow-submodules https://github.com/grpc/grpc && \
cd grpc && sed -i "216i\ TESTONLY" "third_party/abseil-cpp/absl/container/CMakeLists.txt" && mkdir -p cmake/build && \
cd cmake/build && cmake -DgRPC_INSTALL=ON \
-DgRPC_BUILD_TESTS=OFF \
../.. && sudo make --jobs 5 --output-sync=target
- name: Install gRPC
run: |
GNU_HOST=aarch64-linux-gnu
C_COMPILER_ARM_LINUX=$GNU_HOST-gcc
CXX_COMPILER_ARM_LINUX=$GNU_HOST-g++
CROSS_TOOLCHAIN=/usr/$GNU_HOST
CROSS_STAGING_PREFIX=$CROSS_TOOLCHAIN/stage
CMAKE_CROSS_TOOLCHAIN=/tmp/arm.toolchain.cmake
# https://cmake.org/cmake/help/v3.13/manual/cmake-toolchains.7.html#cross-compiling-for-linux
echo "set(CMAKE_SYSTEM_NAME Linux)" >> $CMAKE_CROSS_TOOLCHAIN && \
echo "set(CMAKE_SYSTEM_PROCESSOR arm)" >> $CMAKE_CROSS_TOOLCHAIN && \
echo "set(CMAKE_STAGING_PREFIX $CROSS_STAGING_PREFIX)" >> $CMAKE_CROSS_TOOLCHAIN && \
echo "set(CMAKE_SYSROOT ${CROSS_TOOLCHAIN}/sysroot)" >> $CMAKE_CROSS_TOOLCHAIN && \
echo "set(CMAKE_C_COMPILER /usr/bin/$C_COMPILER_ARM_LINUX)" >> $CMAKE_CROSS_TOOLCHAIN && \
echo "set(CMAKE_CXX_COMPILER /usr/bin/$CXX_COMPILER_ARM_LINUX)" >> $CMAKE_CROSS_TOOLCHAIN && \
echo "set(CMAKE_FIND_ROOT_PATH_MODE_PROGRAM NEVER)" >> $CMAKE_CROSS_TOOLCHAIN && \
echo "set(CMAKE_FIND_ROOT_PATH_MODE_LIBRARY ONLY)" >> $CMAKE_CROSS_TOOLCHAIN && \
echo "set(CMAKE_FIND_ROOT_PATH_MODE_INCLUDE ONLY)" >> $CMAKE_CROSS_TOOLCHAIN && \
echo "set(CMAKE_FIND_ROOT_PATH_MODE_PACKAGE ONLY)" >> $CMAKE_CROSS_TOOLCHAIN
GRPC_DIR=$PWD/grpc
cd grpc && cd cmake/build && sudo make --jobs 5 --output-sync=target install && \
GRPC_CROSS_BUILD_DIR=$GRPC_DIR/cmake/cross_build && \
mkdir -p $GRPC_CROSS_BUILD_DIR && \
cd $GRPC_CROSS_BUILD_DIR && \
cmake -DCMAKE_TOOLCHAIN_FILE=$CMAKE_CROSS_TOOLCHAIN \
-DCMAKE_BUILD_TYPE=Release \
-DCMAKE_INSTALL_PREFIX=$CROSS_TOOLCHAIN/grpc_install \
../.. && \
sudo make -j`nproc` install
- name: Build
id: build
run: |
GNU_HOST=aarch64-linux-gnu
C_COMPILER_ARM_LINUX=$GNU_HOST-gcc
CXX_COMPILER_ARM_LINUX=$GNU_HOST-g++
CROSS_TOOLCHAIN=/usr/$GNU_HOST
CROSS_STAGING_PREFIX=$CROSS_TOOLCHAIN/stage
CMAKE_CROSS_TOOLCHAIN=/tmp/arm.toolchain.cmake
go install google.golang.org/grpc/cmd/protoc-gen-go-grpc@1958fcbe2ca8bd93af633f11e97d44e567e945af
go install google.golang.org/protobuf/cmd/protoc-gen-go@v1.34.2
export PATH=$PATH:$GOPATH/bin
export PATH=/usr/local/cuda/bin:$PATH
sudo rm -rf /usr/aarch64-linux-gnu/lib/libstdc++.so.6
sudo cp -rf /usr/aarch64-linux-gnu/lib/libstdc++.so* /usr/aarch64-linux-gnu/lib/libstdc++.so.6
sudo cp /usr/aarch64-linux-gnu/lib/ld-linux-aarch64.so.1 ld.so
BACKEND_LIBS="./grpc/cmake/cross_build/third_party/re2/libre2.a ./grpc/cmake/cross_build/libgrpc.a ./grpc/cmake/cross_build/libgrpc++.a ./grpc/cmake/cross_build/third_party/protobuf/libprotobuf.a /usr/aarch64-linux-gnu/lib/libc.so.6 /usr/aarch64-linux-gnu/lib/libstdc++.so.6 /usr/aarch64-linux-gnu/lib/libgomp.so.1 /usr/aarch64-linux-gnu/lib/libm.so.6 /usr/aarch64-linux-gnu/lib/libgcc_s.so.1 /usr/aarch64-linux-gnu/lib/libdl.so.2 /usr/aarch64-linux-gnu/lib/libpthread.so.0 ./ld.so" \
GOOS=linux \
GOARCH=arm64 \
CMAKE_ARGS="-DProtobuf_INCLUDE_DIRS=$CROSS_STAGING_PREFIX/include -DProtobuf_DIR=$CROSS_STAGING_PREFIX/lib/cmake/protobuf -DgRPC_DIR=$CROSS_STAGING_PREFIX/lib/cmake/grpc -DCMAKE_TOOLCHAIN_FILE=$CMAKE_CROSS_TOOLCHAIN -DCMAKE_C_COMPILER=aarch64-linux-gnu-gcc -DCMAKE_CXX_COMPILER=aarch64-linux-gnu-g++" make dist-cross-linux-arm64
- uses: actions/upload-artifact@v4
with:
name: LocalAI-linux-arm64
path: release/
- name: Release
uses: softprops/action-gh-release@v2
if: startsWith(github.ref, 'refs/tags/')
with:
files: |
release/*
- name: Setup tmate session if tests fail
if: ${{ failure() }}
uses: mxschmitt/action-tmate@v3.18
with:
detached: true
connect-timeout-seconds: 180
limit-access-to-actor: true
build-linux:
runs-on: arc-runner-set
steps:
- name: Force Install GIT latest
run: |
sudo apt-get update \
&& sudo apt-get install -y software-properties-common \
&& sudo apt-get update \
&& sudo add-apt-repository -y ppa:git-core/ppa \
&& sudo apt-get update \
&& sudo apt-get install -y git
- name: Clone
uses: actions/checkout@v4
with:
submodules: true
- uses: actions/setup-go@v5
with:
go-version: '1.21.x'
cache: false
- name: Dependencies
run: |
sudo apt-get update
sudo apt-get install -y wget curl build-essential ffmpeg protobuf-compiler ccache upx-ucl gawk cmake libgmock-dev
- name: Intel Dependencies
run: |
wget -O- https://apt.repos.intel.com/intel-gpg-keys/GPG-PUB-KEY-INTEL-SW-PRODUCTS.PUB | gpg --dearmor | sudo tee /usr/share/keyrings/oneapi-archive-keyring.gpg > /dev/null
echo "deb [signed-by=/usr/share/keyrings/oneapi-archive-keyring.gpg] https://apt.repos.intel.com/oneapi all main" | sudo tee /etc/apt/sources.list.d/oneAPI.list
sudo apt update
sudo apt install -y intel-basekit
- name: Install CUDA Dependencies
run: |
curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64/cuda-keyring_1.1-1_all.deb
sudo dpkg -i cuda-keyring_1.1-1_all.deb
sudo apt-get update
sudo apt-get install -y cuda-nvcc-${CUDA_VERSION} libcublas-dev-${CUDA_VERSION}
env:
CUDA_VERSION: 12-5
- name: "Install Hipblas"
env:
ROCM_VERSION: "6.1"
AMDGPU_VERSION: "6.1"
run: |
set -ex
sudo apt-get update
sudo DEBIAN_FRONTEND=noninteractive apt-get install -y --no-install-recommends ca-certificates curl libnuma-dev gnupg
curl -sL https://repo.radeon.com/rocm/rocm.gpg.key | sudo apt-key add -
printf "deb [arch=amd64] https://repo.radeon.com/rocm/apt/$ROCM_VERSION/ jammy main" | sudo tee /etc/apt/sources.list.d/rocm.list
printf "deb [arch=amd64] https://repo.radeon.com/amdgpu/$AMDGPU_VERSION/ubuntu jammy main" | sudo tee /etc/apt/sources.list.d/amdgpu.list
printf 'Package: *\nPin: release o=repo.radeon.com\nPin-Priority: 600' | sudo tee /etc/apt/preferences.d/rocm-pin-600
sudo apt-get update
sudo DEBIAN_FRONTEND=noninteractive apt-get install -y \
hipblas-dev rocm-dev \
rocblas-dev
sudo apt-get clean
sudo rm -rf /var/lib/apt/lists/*
sudo ldconfig
- name: Cache grpc
id: cache-grpc
uses: actions/cache@v4
with:
path: grpc
key: ${{ runner.os }}-grpc-${{ env.GRPC_VERSION }}
- name: Build grpc
if: steps.cache-grpc.outputs.cache-hit != 'true'
run: |
git clone --recurse-submodules -b ${{ env.GRPC_VERSION }} --depth 1 --shallow-submodules https://github.com/grpc/grpc && \
cd grpc && sed -i "216i\ TESTONLY" "third_party/abseil-cpp/absl/container/CMakeLists.txt" && mkdir -p cmake/build && \
cd cmake/build && cmake -DgRPC_INSTALL=ON \
-DgRPC_BUILD_TESTS=OFF \
../.. && sudo make --jobs 5 --output-sync=target
- name: Install gRPC
run: |
cd grpc && cd cmake/build && sudo make --jobs 5 --output-sync=target install
# BACKEND_LIBS needed for gpu-workload: /opt/intel/oneapi/*/lib/libiomp5.so /opt/intel/oneapi/*/lib/libmkl_core.so /opt/intel/oneapi/*/lib/libmkl_core.so.2 /opt/intel/oneapi/*/lib/libmkl_intel_ilp64.so /opt/intel/oneapi/*/lib/libmkl_intel_ilp64.so.2 /opt/intel/oneapi/*/lib/libmkl_sycl_blas.so /opt/intel/oneapi/*/lib/libmkl_sycl_blas.so.4 /opt/intel/oneapi/*/lib/libmkl_tbb_thread.so /opt/intel/oneapi/*/lib/libmkl_tbb_thread.so.2 /opt/intel/oneapi/*/lib/libsycl.so /opt/intel/oneapi/*/lib/libsycl.so.7 /opt/intel/oneapi/*/lib/libsycl.so.7.1.0 /opt/rocm-*/lib/libamdhip64.so /opt/rocm-*/lib/libamdhip64.so.5 /opt/rocm-*/lib/libamdhip64.so.6 /opt/rocm-*/lib/libamdhip64.so.6.1.60100 /opt/rocm-*/lib/libhipblas.so /opt/rocm-*/lib/libhipblas.so.2 /opt/rocm-*/lib/libhipblas.so.2.1.60100 /opt/rocm-*/lib/librocblas.so /opt/rocm-*/lib/librocblas.so.4 /opt/rocm-*/lib/librocblas.so.4.1.60100 /usr/lib/x86_64-linux-gnu/libstdc++.so.6 /usr/lib/x86_64-linux-gnu/libOpenCL.so.1 /usr/lib/x86_64-linux-gnu/libOpenCL.so.1.0.0 /usr/lib/x86_64-linux-gnu/libm.so.6 /usr/lib/x86_64-linux-gnu/libgcc_s.so.1 /usr/lib/x86_64-linux-gnu/libc.so.6 /usr/lib/x86_64-linux-gnu/librt.so.1 /usr/local/cuda-*/targets/x86_64-linux/lib/libcublas.so /usr/local/cuda-*/targets/x86_64-linux/lib/libcublasLt.so /usr/local/cuda-*/targets/x86_64-linux/lib/libcudart.so /usr/local/cuda-*/targets/x86_64-linux/lib/stubs/libcuda.so
- name: Build
id: build
run: |
go install google.golang.org/grpc/cmd/protoc-gen-go-grpc@1958fcbe2ca8bd93af633f11e97d44e567e945af
go install google.golang.org/protobuf/cmd/protoc-gen-go@v1.34.2
export PATH=$PATH:$GOPATH/bin
export PATH=/usr/local/cuda/bin:$PATH
export PATH=/opt/rocm/bin:$PATH
source /opt/intel/oneapi/setvars.sh
sudo cp /lib64/ld-linux-x86-64.so.2 ld.so
BACKEND_LIBS="./ld.so ./sources/go-piper/piper/build/fi/lib/libfmt.a ./sources/go-piper/piper-phonemize/pi/lib/libonnxruntime.so.1.14.1 ./sources/go-piper/piper-phonemize/pi/src/libespeak-ng/libespeak-ng.so /usr/lib/x86_64-linux-gnu/libdl.so.2 /usr/lib/x86_64-linux-gnu/librt.so.1 /usr/lib/x86_64-linux-gnu/libpthread.so.0 ./sources/go-piper/piper-phonemize/pi/lib/libpiper_phonemize.so.1 ./sources/go-piper/piper/build/si/lib/libspdlog.a ./sources/go-piper/espeak/ei/lib/libucd.so" \
make -j4 dist
- uses: actions/upload-artifact@v4
with:
name: LocalAI-linux
path: release/
- name: Release
uses: softprops/action-gh-release@v2
if: startsWith(github.ref, 'refs/tags/')
with:
files: |
release/*
- name: Setup tmate session if tests fail
if: ${{ failure() }}
uses: mxschmitt/action-tmate@v3.18
with:
detached: true
connect-timeout-seconds: 180
limit-access-to-actor: true
build-stablediffusion:
runs-on: ubuntu-latest
steps:
- name: Clone
uses: actions/checkout@v4
with:
submodules: true
- uses: actions/setup-go@v5
with:
go-version: '1.21.x'
cache: false
- name: Dependencies
run: |
sudo apt-get update
sudo apt-get install -y --no-install-recommends libopencv-dev protobuf-compiler ccache upx-ucl
go install google.golang.org/grpc/cmd/protoc-gen-go-grpc@1958fcbe2ca8bd93af633f11e97d44e567e945af
go install google.golang.org/protobuf/cmd/protoc-gen-go@v1.34.2
- name: Build stablediffusion
run: |
export PATH=$PATH:$GOPATH/bin
make backend-assets/grpc/stablediffusion
mkdir -p release && cp backend-assets/grpc/stablediffusion release
env:
GO_TAGS: stablediffusion
- uses: actions/upload-artifact@v4
with:
name: stablediffusion
path: release/
- name: Release
uses: softprops/action-gh-release@v2
if: startsWith(github.ref, 'refs/tags/')
with:
files: |
release/*
build-macOS-x86_64:
runs-on: macos-13
steps:
- name: Clone
uses: actions/checkout@v4
with:
submodules: true
- uses: actions/setup-go@v5
with:
go-version: '1.21.x'
cache: false
- name: Dependencies
run: |
brew install protobuf grpc
go install google.golang.org/grpc/cmd/protoc-gen-go-grpc@8ba23be9613c672d40ae261d2a1335d639bdd59b
go install google.golang.org/protobuf/cmd/protoc-gen-go@v1.34.0
- name: Build
id: build
run: |
export C_INCLUDE_PATH=/usr/local/include
export CPLUS_INCLUDE_PATH=/usr/local/include
export PATH=$PATH:$GOPATH/bin
make dist
- uses: actions/upload-artifact@v4
with:
name: LocalAI-MacOS-x86_64
path: release/
- name: Release
uses: softprops/action-gh-release@v2
if: startsWith(github.ref, 'refs/tags/')
with:
files: |
release/*
- name: Setup tmate session if tests fail
if: ${{ failure() }}
uses: mxschmitt/action-tmate@v3.18
with:
detached: true
connect-timeout-seconds: 180
limit-access-to-actor: true
build-macOS-arm64:
runs-on: macos-14
steps:
- name: Clone
uses: actions/checkout@v4
with:
submodules: true
- uses: actions/setup-go@v5
with:
go-version: '1.21.x'
cache: false
- name: Dependencies
run: |
brew install protobuf grpc
go install google.golang.org/grpc/cmd/protoc-gen-go-grpc@1958fcbe2ca8bd93af633f11e97d44e567e945af
go install google.golang.org/protobuf/cmd/protoc-gen-go@v1.34.2
- name: Build
id: build
run: |
export C_INCLUDE_PATH=/usr/local/include
export CPLUS_INCLUDE_PATH=/usr/local/include
export PATH=$PATH:$GOPATH/bin
make dist
- uses: actions/upload-artifact@v4
with:
name: LocalAI-MacOS-arm64
path: release/
- name: Release
uses: softprops/action-gh-release@v2
if: startsWith(github.ref, 'refs/tags/')
with:
files: |
release/*
- name: Setup tmate session if tests fail
if: ${{ failure() }}
uses: mxschmitt/action-tmate@v3.18
with:
detached: true
connect-timeout-seconds: 180
limit-access-to-actor: true

26
.github/workflows/release.yml.disabled vendored Normal file
View File

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

View File

@@ -1,30 +0,0 @@
name: "Security Scan"
# Run workflow each time code is pushed to your repository and on a schedule.
# The scheduled workflow runs every at 00:00 on Sunday UTC time.
on:
push:
schedule:
- cron: '0 0 * * 0'
jobs:
tests:
runs-on: ubuntu-latest
env:
GO111MODULE: on
steps:
- name: Checkout Source
uses: actions/checkout@v4
if: ${{ github.actor != 'dependabot[bot]' }}
- name: Run Gosec Security Scanner
if: ${{ github.actor != 'dependabot[bot]' }}
uses: securego/gosec@master
with:
# we let the report trigger content trigger a failure using the GitHub Security features.
args: '-no-fail -fmt sarif -out results.sarif ./...'
- name: Upload SARIF file
if: ${{ github.actor != 'dependabot[bot]' }}
uses: github/codeql-action/upload-sarif@v3
with:
# Path to SARIF file relative to the root of the repository
sarif_file: results.sarif

View File

@@ -1,295 +0,0 @@
---
name: 'Tests extras backends'
on:
pull_request:
push:
branches:
- master
tags:
- '*'
concurrency:
group: ci-tests-extra-${{ github.head_ref || github.ref }}-${{ github.repository }}
cancel-in-progress: true
jobs:
tests-transformers:
runs-on: ubuntu-latest
steps:
- name: Clone
uses: actions/checkout@v4
with:
submodules: true
- name: Dependencies
run: |
sudo apt-get update
sudo apt-get install build-essential ffmpeg
# Install UV
curl -LsSf https://astral.sh/uv/install.sh | sh
sudo apt-get install -y ca-certificates cmake curl patch python3-pip
sudo apt-get install -y libopencv-dev
pip install --user --no-cache-dir grpcio-tools==1.64.1
- name: Test transformers
run: |
make --jobs=5 --output-sync=target -C backend/python/transformers
make --jobs=5 --output-sync=target -C backend/python/transformers test
tests-sentencetransformers:
runs-on: ubuntu-latest
steps:
- name: Clone
uses: actions/checkout@v4
with:
submodules: true
- name: Dependencies
run: |
sudo apt-get update
sudo apt-get install build-essential ffmpeg
# Install UV
curl -LsSf https://astral.sh/uv/install.sh | sh
sudo apt-get install -y ca-certificates cmake curl patch python3-pip
sudo apt-get install -y libopencv-dev
pip install --user --no-cache-dir grpcio-tools==1.64.1
- name: Test sentencetransformers
run: |
make --jobs=5 --output-sync=target -C backend/python/sentencetransformers
make --jobs=5 --output-sync=target -C backend/python/sentencetransformers test
tests-rerankers:
runs-on: ubuntu-latest
steps:
- name: Clone
uses: actions/checkout@v4
with:
submodules: true
- name: Dependencies
run: |
sudo apt-get update
sudo apt-get install build-essential ffmpeg
# Install UV
curl -LsSf https://astral.sh/uv/install.sh | sh
sudo apt-get install -y ca-certificates cmake curl patch python3-pip
sudo apt-get install -y libopencv-dev
pip install --user --no-cache-dir grpcio-tools==1.64.1
- name: Test rerankers
run: |
make --jobs=5 --output-sync=target -C backend/python/rerankers
make --jobs=5 --output-sync=target -C backend/python/rerankers test
tests-diffusers:
runs-on: ubuntu-latest
steps:
- name: Clone
uses: actions/checkout@v4
with:
submodules: true
- name: Dependencies
run: |
sudo apt-get update
sudo apt-get install -y build-essential ffmpeg
sudo apt-get install -y ca-certificates cmake curl patch python3-pip
sudo apt-get install -y libopencv-dev
# Install UV
curl -LsSf https://astral.sh/uv/install.sh | sh
pip install --user --no-cache-dir grpcio-tools==1.64.1
- name: Test diffusers
run: |
make --jobs=5 --output-sync=target -C backend/python/diffusers
make --jobs=5 --output-sync=target -C backend/python/diffusers test
tests-parler-tts:
runs-on: ubuntu-latest
steps:
- name: Clone
uses: actions/checkout@v4
with:
submodules: true
- name: Dependencies
run: |
sudo apt-get update
sudo apt-get install build-essential ffmpeg
# Install UV
curl -LsSf https://astral.sh/uv/install.sh | sh
sudo apt-get install -y ca-certificates cmake curl patch python3-pip
sudo apt-get install -y libopencv-dev
pip install --user --no-cache-dir grpcio-tools==1.64.1
- name: Test parler-tts
run: |
make --jobs=5 --output-sync=target -C backend/python/parler-tts
make --jobs=5 --output-sync=target -C backend/python/parler-tts test
tests-openvoice:
runs-on: ubuntu-latest
steps:
- name: Clone
uses: actions/checkout@v4
with:
submodules: true
- name: Dependencies
run: |
sudo apt-get update
sudo apt-get install build-essential ffmpeg
# Install UV
curl -LsSf https://astral.sh/uv/install.sh | sh
sudo apt-get install -y ca-certificates cmake curl patch python3-pip
sudo apt-get install -y libopencv-dev
pip install --user --no-cache-dir grpcio-tools==1.64.1
- name: Test openvoice
run: |
make --jobs=5 --output-sync=target -C backend/python/openvoice
make --jobs=5 --output-sync=target -C backend/python/openvoice test
tests-transformers-musicgen:
runs-on: ubuntu-latest
steps:
- name: Clone
uses: actions/checkout@v4
with:
submodules: true
- name: Dependencies
run: |
sudo apt-get update
sudo apt-get install build-essential ffmpeg
# Install UV
curl -LsSf https://astral.sh/uv/install.sh | sh
sudo apt-get install -y ca-certificates cmake curl patch python3-pip
sudo apt-get install -y libopencv-dev
pip install --user --no-cache-dir grpcio-tools==1.64.1
- name: Test transformers-musicgen
run: |
make --jobs=5 --output-sync=target -C backend/python/transformers-musicgen
make --jobs=5 --output-sync=target -C backend/python/transformers-musicgen test
# tests-bark:
# 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 remove -y microsoft-edge-stable || true
# sudo apt-get remove -y firefox || true
# sudo apt-get remove -y powershell || true
# sudo apt-get remove -y r-base-core || true
# sudo apt-get autoremove -y
# sudo apt-get clean
# echo
# echo "Listing top largest packages"
# pkgs=$(dpkg-query -Wf '${Installed-Size}\t${Package}\t${Status}\n' | awk '$NF == "installed"{print $1 "\t" $2}' | sort -nr)
# head -n 30 <<< "${pkgs}"
# echo
# sudo rm -rfv build || true
# sudo rm -rf /usr/share/dotnet || true
# sudo rm -rf /opt/ghc || true
# sudo rm -rf "/usr/local/share/boost" || true
# sudo rm -rf "$AGENT_TOOLSDIRECTORY" || true
# df -h
# - name: Clone
# uses: actions/checkout@v4
# with:
# submodules: true
# - name: Dependencies
# run: |
# sudo apt-get update
# sudo apt-get install build-essential ffmpeg
# # Install UV
# curl -LsSf https://astral.sh/uv/install.sh | sh
# sudo apt-get install -y ca-certificates cmake curl patch python3-pip
# sudo apt-get install -y libopencv-dev
# pip install --user --no-cache-dir grpcio-tools==1.64.1
# - name: Test bark
# run: |
# make --jobs=5 --output-sync=target -C backend/python/bark
# make --jobs=5 --output-sync=target -C backend/python/bark test
# Below tests needs GPU. Commented out for now
# TODO: Re-enable as soon as we have GPU nodes
# tests-vllm:
# runs-on: ubuntu-latest
# steps:
# - name: Clone
# uses: actions/checkout@v4
# with:
# submodules: true
# - name: Dependencies
# run: |
# sudo apt-get update
# sudo apt-get install build-essential ffmpeg
# # Install UV
# curl -LsSf https://astral.sh/uv/install.sh | sh
# sudo apt-get install -y ca-certificates cmake curl patch python3-pip
# sudo apt-get install -y libopencv-dev
# pip install --user --no-cache-dir grpcio-tools==1.64.1
# - name: Test vllm
# run: |
# make --jobs=5 --output-sync=target -C backend/python/vllm
# make --jobs=5 --output-sync=target -C backend/python/vllm test
tests-vallex:
runs-on: ubuntu-latest
steps:
- name: Clone
uses: actions/checkout@v4
with:
submodules: true
- name: Dependencies
run: |
sudo apt-get update
sudo apt-get install build-essential ffmpeg
# Install UV
curl -LsSf https://astral.sh/uv/install.sh | sh
sudo apt-get install -y ca-certificates cmake curl patch python3-pip
sudo apt-get install -y libopencv-dev
pip install --user --no-cache-dir grpcio-tools==1.64.1
- name: Test vall-e-x
run: |
make --jobs=5 --output-sync=target -C backend/python/vall-e-x
make --jobs=5 --output-sync=target -C backend/python/vall-e-x test
tests-coqui:
runs-on: ubuntu-latest
steps:
- name: Clone
uses: actions/checkout@v4
with:
submodules: true
- name: Dependencies
run: |
sudo apt-get update
sudo apt-get install build-essential ffmpeg
sudo apt-get install -y ca-certificates cmake curl patch espeak espeak-ng python3-pip
# Install UV
curl -LsSf https://astral.sh/uv/install.sh | sh
pip install --user --no-cache-dir grpcio-tools==1.64.1
- name: Test coqui
run: |
make --jobs=5 --output-sync=target -C backend/python/coqui
make --jobs=5 --output-sync=target -C backend/python/coqui test

View File

@@ -9,224 +9,36 @@ on:
tags:
- '*'
env:
GRPC_VERSION: v1.65.0
concurrency:
group: ci-tests-${{ github.head_ref || github.ref }}-${{ github.repository }}
cancel-in-progress: true
jobs:
tests-linux:
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@v4
with:
uses: actions/checkout@v3
with:
submodules: true
- name: Setup Go ${{ matrix.go-version }}
uses: actions/setup-go@v5
with:
go-version: ${{ matrix.go-version }}
cache: false
# You can test your matrix by printing the current Go version
- name: Display Go version
run: go version
- name: Dependencies
run: |
sudo apt-get update
sudo apt-get install build-essential ccache upx-ucl curl ffmpeg
sudo apt-get install -y libgmock-dev
curl https://repo.anaconda.com/pkgs/misc/gpgkeys/anaconda.asc | gpg --dearmor > conda.gpg && \
sudo install -o root -g root -m 644 conda.gpg /usr/share/keyrings/conda-archive-keyring.gpg && \
gpg --keyring /usr/share/keyrings/conda-archive-keyring.gpg --no-default-keyring --fingerprint 34161F5BF5EB1D4BFBBB8F0A8AEB4F8B29D82806 && \
sudo /bin/bash -c 'echo "deb [arch=amd64 signed-by=/usr/share/keyrings/conda-archive-keyring.gpg] https://repo.anaconda.com/pkgs/misc/debrepo/conda stable main" > /etc/apt/sources.list.d/conda.list' && \
sudo /bin/bash -c 'echo "deb [arch=amd64 signed-by=/usr/share/keyrings/conda-archive-keyring.gpg] https://repo.anaconda.com/pkgs/misc/debrepo/conda stable main" | tee -a /etc/apt/sources.list.d/conda.list' && \
sudo apt-get update && \
sudo apt-get install -y conda
# Install UV
curl -LsSf https://astral.sh/uv/install.sh | sh
sudo apt-get install -y ca-certificates cmake patch python3-pip unzip
sudo apt-get install -y libopencv-dev
curl -L -s https://github.com/protocolbuffers/protobuf/releases/download/v26.1/protoc-26.1-linux-x86_64.zip -o protoc.zip && \
unzip -j -d /usr/local/bin protoc.zip bin/protoc && \
rm protoc.zip
curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64/cuda-keyring_1.1-1_all.deb
sudo dpkg -i cuda-keyring_1.1-1_all.deb
sudo apt-get update
sudo apt-get install -y cuda-nvcc-${CUDA_VERSION} libcublas-dev-${CUDA_VERSION}
export CUDACXX=/usr/local/cuda/bin/nvcc
go install google.golang.org/protobuf/cmd/protoc-gen-go@v1.34.2
go install google.golang.org/grpc/cmd/protoc-gen-go-grpc@1958fcbe2ca8bd93af633f11e97d44e567e945af
# The python3-grpc-tools package in 22.04 is too old
pip install --user grpcio-tools
sudo rm -rfv /usr/bin/conda || true
PATH=$PATH:/opt/conda/bin make -C backend/python/sentencetransformers
# Pre-build piper before we start tests in order to have shared libraries in place
make sources/go-piper && \
GO_TAGS="tts" make -C sources/go-piper piper.o && \
sudo cp -rfv sources/go-piper/piper-phonemize/pi/lib/. /usr/lib/ && \
# Pre-build stable diffusion before we install a newer version of abseil (not compatible with stablediffusion-ncn)
PATH="$PATH:/root/go/bin" GO_TAGS="stablediffusion tts" GRPC_BACKENDS=backend-assets/grpc/stablediffusion make build
env:
CUDA_VERSION: 12-4
- name: Cache grpc
id: cache-grpc
uses: actions/cache@v4
with:
path: grpc
key: ${{ runner.os }}-grpc-${{ env.GRPC_VERSION }}
- name: Build grpc
if: steps.cache-grpc.outputs.cache-hit != 'true'
run: |
git clone --recurse-submodules -b ${{ env.GRPC_VERSION }} --depth 1 --jobs 5 --shallow-submodules https://github.com/grpc/grpc && \
cd grpc && sed -i "216i\ TESTONLY" "third_party/abseil-cpp/absl/container/CMakeLists.txt" && mkdir -p cmake/build && cd cmake/build && \
cmake -DgRPC_INSTALL=ON \
-DgRPC_BUILD_TESTS=OFF \
../.. && sudo make --jobs 5
- name: Install gRPC
run: |
cd grpc && cd cmake/build && sudo make --jobs 5 install
sudo apt-get install build-essential
- name: Test
run: |
PATH="$PATH:/root/go/bin" GO_TAGS="stablediffusion tts" make --jobs 5 --output-sync=target test
- name: Setup tmate session if tests fail
if: ${{ failure() }}
uses: mxschmitt/action-tmate@v3.18
with:
detached: true
connect-timeout-seconds: 180
limit-access-to-actor: true
make test
tests-aio-container:
runs-on: ubuntu-latest
steps:
- name: Release space from worker
run: |
echo "Listing top largest packages"
pkgs=$(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: Clone
uses: actions/checkout@v4
with:
submodules: true
- name: Build images
run: |
docker build --build-arg FFMPEG=true --build-arg IMAGE_TYPE=extras --build-arg EXTRA_BACKENDS=rerankers --build-arg MAKEFLAGS="--jobs=5 --output-sync=target" -t local-ai:tests -f Dockerfile .
BASE_IMAGE=local-ai:tests DOCKER_AIO_IMAGE=local-ai-aio:test make docker-aio
- name: Test
run: |
LOCALAI_MODELS_DIR=$PWD/models LOCALAI_IMAGE_TAG=test LOCALAI_IMAGE=local-ai-aio \
make run-e2e-aio
- name: Setup tmate session if tests fail
if: ${{ failure() }}
uses: mxschmitt/action-tmate@v3.18
with:
detached: true
connect-timeout-seconds: 180
limit-access-to-actor: true
macOS-latest:
runs-on: macOS-latest
tests-apple:
runs-on: macOS-14
strategy:
matrix:
go-version: ['1.21.x']
steps:
- name: Clone
uses: actions/checkout@v4
with:
uses: actions/checkout@v3
with:
submodules: true
- name: Setup Go ${{ matrix.go-version }}
uses: actions/setup-go@v5
with:
go-version: ${{ matrix.go-version }}
cache: false
# You can test your matrix by printing the current Go version
- name: Display Go version
run: go version
- name: Dependencies
run: |
brew install protobuf grpc make protoc-gen-go protoc-gen-go-grpc
pip install --user --no-cache-dir grpcio-tools==1.64.1
brew update
brew install sdl2
- name: Test
run: |
export C_INCLUDE_PATH=/usr/local/include
export CPLUS_INCLUDE_PATH=/usr/local/include
# Used to run the newer GNUMake version from brew that supports --output-sync
export PATH="/opt/homebrew/opt/make/libexec/gnubin:$PATH"
BUILD_TYPE="GITHUB_CI_HAS_BROKEN_METAL" CMAKE_ARGS="-DGGML_F16C=OFF -DGGML_AVX512=OFF -DGGML_AVX2=OFF -DGGML_FMA=OFF" make --jobs 4 --output-sync=target test
- name: Setup tmate session if tests fail
if: ${{ failure() }}
uses: mxschmitt/action-tmate@v3.18
with:
detached: true
connect-timeout-seconds: 180
limit-access-to-actor: true
make test

View File

@@ -1,37 +0,0 @@
name: Update swagger
on:
schedule:
- cron: 0 20 * * *
workflow_dispatch:
jobs:
swagger:
strategy:
fail-fast: false
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- uses: actions/setup-go@v5
with:
go-version: 'stable'
- name: Dependencies
run: |
sudo apt-get update
sudo apt-get install protobuf-compiler
- run: |
go install github.com/swaggo/swag/cmd/swag@latest
go install google.golang.org/grpc/cmd/protoc-gen-go-grpc@1958fcbe2ca8bd93af633f11e97d44e567e945af
go install google.golang.org/protobuf/cmd/protoc-gen-go@v1.34.2
- name: Bump swagger 🔧
run: |
make protogen-go swagger
- name: Create Pull Request
uses: peter-evans/create-pull-request@v6
with:
token: ${{ secrets.UPDATE_BOT_TOKEN }}
push-to-fork: ci-forks/LocalAI
commit-message: 'feat(swagger): update swagger'
title: 'feat(swagger): update swagger'
branch: "update/swagger"
body: Update swagger
signoff: true

View File

@@ -1,18 +0,0 @@
name: 'Yamllint GitHub Actions'
on:
- pull_request
jobs:
yamllint:
name: 'Yamllint'
runs-on: ubuntu-latest
steps:
- name: 'Checkout'
uses: actions/checkout@master
- name: 'Yamllint'
uses: karancode/yamllint-github-action@master
with:
yamllint_file_or_dir: 'gallery'
yamllint_strict: false
yamllint_comment: true
env:
GITHUB_ACCESS_TOKEN: ${{ secrets.GITHUB_TOKEN }}

51
.gitignore vendored
View File

@@ -1,59 +1,14 @@
# go-llama build artifacts
/sources/
__pycache__/
*.a
get-sources
prepare-sources
/backend/cpp/llama/grpc-server
/backend/cpp/llama/llama.cpp
/backend/cpp/llama-*
*.log
go-ggml-transformers
go-llama
go-gpt4all-j
go-gpt2
go-rwkv
whisper.cpp
/bloomz
go-bert
# LocalAI build binary
LocalAI
local-ai
# prevent above rules from omitting the helm chart
!charts/*
# prevent above rules from omitting the api/localai folder
!api/localai
!core/**/localai
# Ignore models
models/*
test-models/
test-dir/
release/
# just in case
.DS_Store
.idea
# Generated during build
backend-assets/*
!backend-assets/.keep
prepare
/ggml-metal.metal
docs/static/gallery.html
# Protobuf generated files
*.pb.go
*pb2.py
*pb2_grpc.py
# SonarQube
.scannerwork
# backend virtual environments
**/venv
# per-developer customization files for the development container
.devcontainer/customization/*
test-models/

6
.gitmodules vendored
View File

@@ -1,6 +0,0 @@
[submodule "docs/themes/hugo-theme-relearn"]
path = docs/themes/hugo-theme-relearn
url = https://github.com/McShelby/hugo-theme-relearn.git
[submodule "docs/themes/lotusdocs"]
path = docs/themes/lotusdocs
url = https://github.com/colinwilson/lotusdocs

15
.goreleaser.yaml Normal file
View File

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

View File

@@ -1,5 +0,0 @@
{
"recommendations": [
"golang.go"
]
}

32
.vscode/launch.json vendored
View File

@@ -2,33 +2,19 @@
"version": "0.2.0",
"configurations": [
{
"name": "Python: Current File",
"type": "debugpy",
"request": "launch",
"program": "${file}",
"console": "integratedTerminal",
"justMyCode": false,
"cwd": "${fileDirname}",
"env": {
"OPENAI_API_BASE": "http://localhost:8080/v1",
"OPENAI_API_KEY": "abc"
}
},
{
"name": "Launch LocalAI API",
"name": "Launch Go",
"type": "go",
"request": "launch",
"mode": "debug",
"program": "${workspaceRoot}",
"args": [],
"program": "${workspaceFolder}/main.go",
"args": [
"api"
],
"env": {
"LOCALAI_LOG_LEVEL": "debug",
"LOCALAI_P2P": "true",
"LOCALAI_FEDERATED": "true"
},
"buildFlags": ["-tags", "stablediffusion p2p tts", "-v"],
"envFile": "${workspaceFolder}/.env",
"cwd": "${workspaceRoot}"
"C_INCLUDE_PATH": "/workspace/go-llama:/workspace/go-gpt4all-j:/workspace/go-gpt2",
"LIBRARY_PATH": "/workspace/go-llama:/workspace/go-gpt4all-j:/workspace/go-gpt2",
"DEBUG": "true"
}
}
]
}

View File

@@ -1,4 +0,0 @@
extends: default
rules:
line-length: disable

View File

@@ -1,88 +0,0 @@
# 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 ( see https://localai.io/basics/build/#build-localai-locally )
4. Build LocalAI: `make build`
5. Run LocalAI: `./local-ai`
## 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.
### Running AIO tests
All-In-One images has a set of tests that automatically verifies that most of the endpoints works correctly, a flow can be :
```bash
# Build the LocalAI docker image
make DOCKER_IMAGE=local-ai docker
# Build the corresponding AIO image
BASE_IMAGE=local-ai DOCKER_AIO_IMAGE=local-ai-aio:test make docker-aio
# Run the AIO e2e tests
LOCALAI_IMAGE_TAG=test LOCALAI_IMAGE=local-ai-aio make run-e2e-aio
```
## Documentation
We are welcome the contribution of the documents, please open new PR or create a new issue. The documentation is available under `docs/` https://github.com/mudler/LocalAI/tree/master/docs
## 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)
---

View File

@@ -1,449 +1,13 @@
ARG IMAGE_TYPE=extras
ARG BASE_IMAGE=ubuntu:22.04
ARG GRPC_BASE_IMAGE=${BASE_IMAGE}
ARG INTEL_BASE_IMAGE=${BASE_IMAGE}
# The requirements-core target is common to all images. It should not be placed in requirements-core unless every single build will use it.
FROM ${BASE_IMAGE} AS requirements-core
USER root
ARG GO_VERSION=1.22.6
ARG TARGETARCH
ARG TARGETVARIANT
ENV DEBIAN_FRONTEND=noninteractive
ENV EXTERNAL_GRPC_BACKENDS="coqui:/build/backend/python/coqui/run.sh,huggingface-embeddings:/build/backend/python/sentencetransformers/run.sh,transformers:/build/backend/python/transformers/run.sh,sentencetransformers:/build/backend/python/sentencetransformers/run.sh,rerankers:/build/backend/python/rerankers/run.sh,autogptq:/build/backend/python/autogptq/run.sh,bark:/build/backend/python/bark/run.sh,diffusers:/build/backend/python/diffusers/run.sh,exllama:/build/backend/python/exllama/run.sh,openvoice:/build/backend/python/openvoice/run.sh,vall-e-x:/build/backend/python/vall-e-x/run.sh,vllm:/build/backend/python/vllm/run.sh,mamba:/build/backend/python/mamba/run.sh,exllama2:/build/backend/python/exllama2/run.sh,transformers-musicgen:/build/backend/python/transformers-musicgen/run.sh,parler-tts:/build/backend/python/parler-tts/run.sh"
RUN apt-get update && \
apt-get install -y --no-install-recommends \
build-essential \
ccache \
ca-certificates \
cmake \
curl \
git \
unzip upx-ucl && \
apt-get clean && \
rm -rf /var/lib/apt/lists/*
# Install Go
RUN curl -L -s https://go.dev/dl/go${GO_VERSION}.linux-${TARGETARCH}.tar.gz | tar -C /usr/local -xz
ENV PATH=$PATH:/root/go/bin:/usr/local/go/bin
# Install grpc compilers
RUN go install google.golang.org/protobuf/cmd/protoc-gen-go@v1.34.2 && \
go install google.golang.org/grpc/cmd/protoc-gen-go-grpc@1958fcbe2ca8bd93af633f11e97d44e567e945af
COPY --chmod=644 custom-ca-certs/* /usr/local/share/ca-certificates/
RUN update-ca-certificates
RUN test -n "$TARGETARCH" \
|| (echo 'warn: missing $TARGETARCH, either set this `ARG` manually, or run using `docker buildkit`')
# Use the variables in subsequent instructions
RUN echo "Target Architecture: $TARGETARCH"
RUN echo "Target Variant: $TARGETVARIANT"
# Cuda
ENV PATH=/usr/local/cuda/bin:${PATH}
# HipBLAS requirements
ENV PATH=/opt/rocm/bin:${PATH}
# OpenBLAS requirements and stable diffusion
RUN apt-get update && \
apt-get install -y --no-install-recommends \
libopenblas-dev \
libopencv-dev && \
apt-get clean && \
rm -rf /var/lib/apt/lists/*
# Set up OpenCV
RUN ln -s /usr/include/opencv4/opencv2 /usr/include/opencv2
ARG GO_VERSION=1.20
ARG DEBIAN_VERSION=11
ARG BUILD_TYPE=
FROM golang:$GO_VERSION as builder
WORKDIR /build
###################################
###################################
# The requirements-extras target is for any builds with IMAGE_TYPE=extras. It should not be placed in this target unless every IMAGE_TYPE=extras build will use it
FROM requirements-core AS requirements-extras
RUN curl -LsSf https://astral.sh/uv/install.sh | sh
ENV PATH="/root/.cargo/bin:${PATH}"
RUN curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh -s -- -y
RUN apt-get update && \
apt-get install -y --no-install-recommends \
espeak-ng \
espeak \
python3-pip \
python-is-python3 \
python3-dev llvm \
python3-venv && \
apt-get clean && \
rm -rf /var/lib/apt/lists/* && \
pip install --upgrade pip
# Install grpcio-tools (the version in 22.04 is too old)
RUN pip install --user grpcio-tools
###################################
###################################
# The requirements-drivers target is for BUILD_TYPE specific items. If you need to install something specific to CUDA, or specific to ROCM, it goes here.
# This target will be built on top of requirements-core or requirements-extras as retermined by the IMAGE_TYPE build-arg
FROM requirements-${IMAGE_TYPE} AS requirements-drivers
ARG BUILD_TYPE
ARG CUDA_MAJOR_VERSION=12
ARG CUDA_MINOR_VERSION=0
ENV BUILD_TYPE=${BUILD_TYPE}
# Vulkan requirements
RUN <<EOT bash
if [ "${BUILD_TYPE}" = "vulkan" ]; then
apt-get update && \
apt-get install -y --no-install-recommends \
software-properties-common pciutils wget gpg-agent && \
wget -qO - https://packages.lunarg.com/lunarg-signing-key-pub.asc | apt-key add - && \
wget -qO /etc/apt/sources.list.d/lunarg-vulkan-jammy.list https://packages.lunarg.com/vulkan/lunarg-vulkan-jammy.list && \
apt-get update && \
apt-get install -y \
vulkan-sdk && \
apt-get clean && \
rm -rf /var/lib/apt/lists/*
fi
EOT
# CuBLAS requirements
RUN <<EOT bash
if [ "${BUILD_TYPE}" = "cublas" ]; then
apt-get update && \
apt-get install -y --no-install-recommends \
software-properties-common pciutils
if [ "amd64" = "$TARGETARCH" ]; then
curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64/cuda-keyring_1.1-1_all.deb
fi
if [ "arm64" = "$TARGETARCH" ]; then
curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/arm64/cuda-keyring_1.1-1_all.deb
fi
dpkg -i cuda-keyring_1.1-1_all.deb && \
rm -f cuda-keyring_1.1-1_all.deb && \
apt-get update && \
apt-get install -y --no-install-recommends \
cuda-nvcc-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
libcufft-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
libcurand-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
libcublas-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
libcusparse-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
libcusolver-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} && \
apt-get clean && \
rm -rf /var/lib/apt/lists/*
fi
EOT
# If we are building with clblas support, we need the libraries for the builds
RUN if [ "${BUILD_TYPE}" = "clblas" ]; then \
apt-get update && \
apt-get install -y --no-install-recommends \
libclblast-dev && \
apt-get clean && \
rm -rf /var/lib/apt/lists/* \
; fi
RUN if [ "${BUILD_TYPE}" = "hipblas" ]; then \
apt-get update && \
apt-get install -y --no-install-recommends \
hipblas-dev \
rocblas-dev && \
apt-get clean && \
rm -rf /var/lib/apt/lists/* && \
# I have no idea why, but the ROCM lib packages don't trigger ldconfig after they install, which results in local-ai and others not being able
# to locate the libraries. We run ldconfig ourselves to work around this packaging deficiency
ldconfig \
; fi
###################################
###################################
# Temporary workaround for Intel's repository to work correctly
# https://community.intel.com/t5/Intel-oneAPI-Math-Kernel-Library/APT-Repository-not-working-signatures-invalid/m-p/1599436/highlight/true#M36143
# This is a temporary workaround until Intel fixes their repository
FROM ${INTEL_BASE_IMAGE} AS intel
RUN wget -qO - https://repositories.intel.com/gpu/intel-graphics.key | \
gpg --yes --dearmor --output /usr/share/keyrings/intel-graphics.gpg
RUN echo "deb [arch=amd64 signed-by=/usr/share/keyrings/intel-graphics.gpg] https://repositories.intel.com/gpu/ubuntu jammy/lts/2350 unified" > /etc/apt/sources.list.d/intel-graphics.list
###################################
###################################
# The grpc target does one thing, it builds and installs GRPC. This is in it's own layer so that it can be effectively cached by CI.
# You probably don't need to change anything here, and if you do, make sure that CI is adjusted so that the cache continues to work.
FROM ${GRPC_BASE_IMAGE} AS grpc
# This is a bit of a hack, but it's required in order to be able to effectively cache this layer in CI
ARG GRPC_MAKEFLAGS="-j4 -Otarget"
ARG GRPC_VERSION=v1.65.0
ENV MAKEFLAGS=${GRPC_MAKEFLAGS}
WORKDIR /build
RUN apt-get update && \
apt-get install -y --no-install-recommends \
ca-certificates \
build-essential \
cmake \
git && \
apt-get clean && \
rm -rf /var/lib/apt/lists/*
# We install GRPC to a different prefix here so that we can copy in only the build artifacts later
# saves several hundred MB on the final docker image size vs copying in the entire GRPC source tree
# and running make install in the target container
RUN git clone --recurse-submodules --jobs 4 -b ${GRPC_VERSION} --depth 1 --shallow-submodules https://github.com/grpc/grpc && \
mkdir -p /build/grpc/cmake/build && \
cd /build/grpc/cmake/build && \
sed -i "216i\ TESTONLY" "../../third_party/abseil-cpp/absl/container/CMakeLists.txt" && \
cmake -DgRPC_INSTALL=ON -DgRPC_BUILD_TESTS=OFF -DCMAKE_INSTALL_PREFIX:PATH=/opt/grpc ../.. && \
make && \
make install && \
rm -rf /build
###################################
###################################
# The builder-base target has the arguments, variables, and copies shared between full builder images and the uncompiled devcontainer
FROM requirements-drivers AS builder-base
ARG GO_TAGS="stablediffusion tts p2p"
ARG GRPC_BACKENDS
ARG MAKEFLAGS
ARG LD_FLAGS="-s -w"
ENV GRPC_BACKENDS=${GRPC_BACKENDS}
ENV GO_TAGS=${GO_TAGS}
ENV MAKEFLAGS=${MAKEFLAGS}
ENV NVIDIA_DRIVER_CAPABILITIES=compute,utility
ENV NVIDIA_REQUIRE_CUDA="cuda>=${CUDA_MAJOR_VERSION}.0"
ENV NVIDIA_VISIBLE_DEVICES=all
ENV LD_FLAGS=${LD_FLAGS}
RUN echo "GO_TAGS: $GO_TAGS" && echo "TARGETARCH: $TARGETARCH"
WORKDIR /build
# We need protoc installed, and the version in 22.04 is too old. We will create one as part installing the GRPC build below
# but that will also being in a newer version of absl which stablediffusion cannot compile with. This version of protoc is only
# here so that we can generate the grpc code for the stablediffusion build
RUN <<EOT bash
if [ "amd64" = "$TARGETARCH" ]; then
curl -L -s https://github.com/protocolbuffers/protobuf/releases/download/v27.1/protoc-27.1-linux-x86_64.zip -o protoc.zip && \
unzip -j -d /usr/local/bin protoc.zip bin/protoc && \
rm protoc.zip
fi
if [ "arm64" = "$TARGETARCH" ]; then
curl -L -s https://github.com/protocolbuffers/protobuf/releases/download/v27.1/protoc-27.1-linux-aarch_64.zip -o protoc.zip && \
unzip -j -d /usr/local/bin protoc.zip bin/protoc && \
rm protoc.zip
fi
EOT
###################################
###################################
# This first portion of builder holds the layers specifically used to build backend-assets/grpc/stablediffusion
# In most cases, builder is the image you should be using - however, this can save build time if one just needs to copy backend-assets/grpc/stablediffusion and nothing else.
FROM builder-base AS builder-sd
RUN apt-get update && apt-get install -y cmake
COPY . .
COPY .git .
RUN make prepare
# stablediffusion does not tolerate a newer version of abseil, build it first
RUN GRPC_BACKENDS=backend-assets/grpc/stablediffusion make build
###################################
###################################
# The builder target compiles LocalAI. This target is not the target that will be uploaded to the registry.
# Adjustments to the build process should likely be made here.
FROM builder-sd AS builder
# Install the pre-built GRPC
COPY --from=grpc /opt/grpc /usr/local
# Rebuild with defaults backends
WORKDIR /build
## Build the binary
RUN make build
RUN if [ ! -d "/build/sources/go-piper/piper-phonemize/pi/lib/" ]; then \
mkdir -p /build/sources/go-piper/piper-phonemize/pi/lib/ \
touch /build/sources/go-piper/piper-phonemize/pi/lib/keep \
; fi
###################################
###################################
# The devcontainer target is not used on CI. It is a target for developers to use locally -
# rather than copying files it mounts them locally and leaves building to the developer
FROM builder-base AS devcontainer
ARG FFMPEG
COPY --from=grpc /opt/grpc /usr/local
COPY --from=builder-sd /build/backend-assets/grpc/stablediffusion /build/backend-assets/grpc/stablediffusion
COPY .devcontainer-scripts /.devcontainer-scripts
# Add FFmpeg
RUN if [ "${FFMPEG}" = "true" ]; then \
apt-get update && \
apt-get install -y --no-install-recommends \
ffmpeg && \
apt-get clean && \
rm -rf /var/lib/apt/lists/* \
; fi
RUN apt-get update && \
apt-get install -y --no-install-recommends \
ssh less && \
apt-get clean && \
rm -rf /var/lib/apt/lists/*
RUN go install github.com/go-delve/delve/cmd/dlv@latest
RUN go install github.com/mikefarah/yq/v4@latest
###################################
###################################
# This is the final target. The result of this target will be the image uploaded to the registry.
# If you cannot find a more suitable place for an addition, this layer is a suitable place for it.
FROM requirements-drivers
ARG FFMPEG
ARG BUILD_TYPE
ARG TARGETARCH
ARG IMAGE_TYPE=extras
ARG EXTRA_BACKENDS
ARG MAKEFLAGS
ENV BUILD_TYPE=${BUILD_TYPE}
ENV REBUILD=false
ENV HEALTHCHECK_ENDPOINT=http://localhost:8080/readyz
ENV MAKEFLAGS=${MAKEFLAGS}
ARG CUDA_MAJOR_VERSION=12
ENV NVIDIA_DRIVER_CAPABILITIES=compute,utility
ENV NVIDIA_REQUIRE_CUDA="cuda>=${CUDA_MAJOR_VERSION}.0"
ENV NVIDIA_VISIBLE_DEVICES=all
# Add FFmpeg
RUN if [ "${FFMPEG}" = "true" ]; then \
apt-get update && \
apt-get install -y --no-install-recommends \
ffmpeg && \
apt-get clean && \
rm -rf /var/lib/apt/lists/* \
; fi
WORKDIR /build
# we start fresh & re-copy all assets because `make build` does not clean up nicely after itself
# so when `entrypoint.sh` runs `make build` again (which it does by default), the build would fail
# see https://github.com/go-skynet/LocalAI/pull/658#discussion_r1241971626 and
# https://github.com/go-skynet/LocalAI/pull/434
COPY . .
COPY --from=builder /build/sources ./sources/
COPY --from=grpc /opt/grpc /usr/local
RUN make prepare-sources
# Copy the binary
COPY --from=builder /build/local-ai ./
# Copy shared libraries for piper
COPY --from=builder /build/sources/go-piper/piper-phonemize/pi/lib/* /usr/lib/
# do not let stablediffusion rebuild (requires an older version of absl)
COPY --from=builder-sd /build/backend-assets/grpc/stablediffusion ./backend-assets/grpc/stablediffusion
# Change the shell to bash so we can use [[ tests below
SHELL ["/bin/bash", "-c"]
# We try to strike a balance between individual layer size (as that affects total push time) and total image size
# Splitting the backends into more groups with fewer items results in a larger image, but a smaller size for the largest layer
# Splitting the backends into fewer groups with more items results in a smaller image, but a larger size for the largest layer
RUN if [[ ( "${EXTRA_BACKENDS}" =~ "coqui" || -z "${EXTRA_BACKENDS}" ) && "$IMAGE_TYPE" == "extras" ]]; then \
make -C backend/python/coqui \
; fi && \
if [[ ( "${EXTRA_BACKENDS}" =~ "parler-tts" || -z "${EXTRA_BACKENDS}" ) && "$IMAGE_TYPE" == "extras" ]]; then \
make -C backend/python/parler-tts \
; fi && \
if [[ ( "${EXTRA_BACKENDS}" =~ "diffusers" || -z "${EXTRA_BACKENDS}" ) && "$IMAGE_TYPE" == "extras" ]]; then \
make -C backend/python/diffusers \
; fi && \
if [[ ( "${EXTRA_BACKENDS}" =~ "transformers-musicgen" || -z "${EXTRA_BACKENDS}" ) && "$IMAGE_TYPE" == "extras" ]]; then \
make -C backend/python/transformers-musicgen \
; fi && \
if [[ ( "${EXTRA_BACKENDS}" =~ "exllama1" || -z "${EXTRA_BACKENDS}" ) && "$IMAGE_TYPE" == "extras" ]]; then \
make -C backend/python/exllama \
; fi
RUN if [[ ( "${EXTRA_BACKENDS}" =~ "vall-e-x" || -z "${EXTRA_BACKENDS}" ) && "$IMAGE_TYPE" == "extras" ]]; then \
make -C backend/python/vall-e-x \
; fi && \
if [[ ( "${EXTRA_BACKENDS}" =~ "openvoice" || -z "${EXTRA_BACKENDS}" ) && "$IMAGE_TYPE" == "extras" ]]; then \
make -C backend/python/openvoice \
; fi && \
if [[ ( "${EXTRA_BACKENDS}" =~ "sentencetransformers" || -z "${EXTRA_BACKENDS}" ) && "$IMAGE_TYPE" == "extras" ]]; then \
make -C backend/python/sentencetransformers \
; fi && \
if [[ ( "${EXTRA_BACKENDS}" =~ "exllama2" || -z "${EXTRA_BACKENDS}" ) && "$IMAGE_TYPE" == "extras" ]]; then \
make -C backend/python/exllama2 \
; fi && \
if [[ ( "${EXTRA_BACKENDS}" =~ "transformers" || -z "${EXTRA_BACKENDS}" ) && "$IMAGE_TYPE" == "extras" ]]; then \
make -C backend/python/transformers \
; fi
RUN if [[ ( "${EXTRA_BACKENDS}" =~ "vllm" || -z "${EXTRA_BACKENDS}" ) && "$IMAGE_TYPE" == "extras" ]]; then \
make -C backend/python/vllm \
; fi && \
if [[ ( "${EXTRA_BACKENDS}" =~ "autogptq" || -z "${EXTRA_BACKENDS}" ) && "$IMAGE_TYPE" == "extras" ]]; then \
make -C backend/python/autogptq \
; fi && \
if [[ ( "${EXTRA_BACKENDS}" =~ "bark" || -z "${EXTRA_BACKENDS}" ) && "$IMAGE_TYPE" == "extras" ]]; then \
make -C backend/python/bark \
; fi && \
if [[ ( "${EXTRA_BACKENDS}" =~ "rerankers" || -z "${EXTRA_BACKENDS}" ) && "$IMAGE_TYPE" == "extras" ]]; then \
make -C backend/python/rerankers \
; fi && \
if [[ ( "${EXTRA_BACKENDS}" =~ "mamba" || -z "${EXTRA_BACKENDS}" ) && "$IMAGE_TYPE" == "extras" ]]; then \
make -C backend/python/mamba \
; fi
# Make sure the models directory exists
RUN mkdir -p /build/models
# Define the health check command
HEALTHCHECK --interval=1m --timeout=10m --retries=10 \
CMD curl -f ${HEALTHCHECK_ENDPOINT} || exit 1
VOLUME /build/models
EXPOSE 8080
ENTRYPOINT [ "/build/entrypoint.sh" ]
FROM debian:$DEBIAN_VERSION
COPY --from=builder /build/local-ai /usr/bin/local-ai
ENTRYPOINT [ "/usr/bin/local-ai" ]

View File

@@ -1,8 +0,0 @@
ARG BASE_IMAGE=ubuntu:22.04
FROM ${BASE_IMAGE}
RUN apt-get update && apt-get install -y pciutils && apt-get clean
COPY aio/ /aio
ENTRYPOINT [ "/aio/entrypoint.sh" ]

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@@ -1,10 +0,0 @@
<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE plist PUBLIC "-//Apple//DTD PLIST 1.0//EN" "http://www.apple.com/DTDs/PropertyList-1.0.dtd">
<plist version="1.0">
<dict>
<key>com.apple.security.network.client</key>
<true/>
<key>com.apple.security.network.server</key>
<true/>
</dict>
</plist>

View File

@@ -1,6 +1,6 @@
MIT License
Copyright (c) 2023-2024 Ettore Di Giacinto (mudler@localai.io)
Copyright (c) 2023 go-skynet authors
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal

975
Makefile
View File

File diff suppressed because it is too large Load Diff

584
README.md
View File

@@ -1,222 +1,452 @@
<h1 align="center">
<br>
<img height="300" src="https://github.com/go-skynet/LocalAI/assets/2420543/0966aa2a-166e-4f99-a3e5-6c915fc997dd"> <br>
<img height="300" src="https://user-images.githubusercontent.com/2420543/233147843-88697415-6dbf-4368-a862-ab217f9f7342.jpeg"> <br>
LocalAI
<br>
</h1>
<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>
> :warning: This project has been renamed from `llama-cli` to `LocalAI` to reflect the fact that we are focusing on a fast drop-in OpenAI API rather than on the CLI interface. We think that there are already many projects that can be used as a CLI interface already, for instance [llama.cpp](https://github.com/ggerganov/llama.cpp) and [gpt4all](https://github.com/nomic-ai/gpt4all). If you are using `llama-cli` for CLI interactions and want to keep using it, use older versions or please open up an issue - contributions are welcome!
<p align="center">
<a href="https://hub.docker.com/r/localai/localai" target="blank">
<img src="https://img.shields.io/badge/dockerhub-images-important.svg?logo=Docker" alt="LocalAI Docker hub"/>
</a>
<a href="https://quay.io/repository/go-skynet/local-ai?tab=tags&tag=latest" target="blank">
<img src="https://img.shields.io/badge/quay.io-images-important.svg?" alt="LocalAI Quay.io"/>
</a>
</p>
[![tests](https://github.com/go-skynet/LocalAI/actions/workflows/test.yml/badge.svg)](https://github.com/go-skynet/LocalAI/actions/workflows/test.yml) [![build container images](https://github.com/go-skynet/LocalAI/actions/workflows/image.yml/badge.svg)](https://github.com/go-skynet/LocalAI/actions/workflows/image.yml)
<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>
[![](https://dcbadge.vercel.app/api/server/uJAeKSAGDy?style=flat-square&theme=default-inverted)](https://discord.gg/uJAeKSAGDy)
> :bulb: Get help - [❓FAQ](https://localai.io/faq/) [💭Discussions](https://github.com/go-skynet/LocalAI/discussions) [:speech_balloon: Discord](https://discord.gg/uJAeKSAGDy) [:book: Documentation website](https://localai.io/)
>
> [💻 Quickstart](https://localai.io/basics/getting_started/) [📣 News](https://localai.io/basics/news/) [ 🛫 Examples ](https://github.com/go-skynet/LocalAI/tree/master/examples/) [ 🖼️ Models ](https://localai.io/models/) [ 🚀 Roadmap ](https://github.com/mudler/LocalAI/issues?q=is%3Aissue+is%3Aopen+label%3Aroadmap)
**LocalAI** is a straightforward, drop-in replacement API compatible with OpenAI for local CPU inferencing, based on [llama.cpp](https://github.com/ggerganov/llama.cpp), [gpt4all](https://github.com/nomic-ai/gpt4all) and [ggml](https://github.com/ggerganov/ggml), including support GPT4ALL-J which is Apache 2.0 Licensed and can be used for commercial purposes.
[![tests](https://github.com/go-skynet/LocalAI/actions/workflows/test.yml/badge.svg)](https://github.com/go-skynet/LocalAI/actions/workflows/test.yml)[![Build and Release](https://github.com/go-skynet/LocalAI/actions/workflows/release.yaml/badge.svg)](https://github.com/go-skynet/LocalAI/actions/workflows/release.yaml)[![build container images](https://github.com/go-skynet/LocalAI/actions/workflows/image.yml/badge.svg)](https://github.com/go-skynet/LocalAI/actions/workflows/image.yml)[![Bump dependencies](https://github.com/go-skynet/LocalAI/actions/workflows/bump_deps.yaml/badge.svg)](https://github.com/go-skynet/LocalAI/actions/workflows/bump_deps.yaml)[![Artifact Hub](https://img.shields.io/endpoint?url=https://artifacthub.io/badge/repository/localai)](https://artifacthub.io/packages/search?repo=localai)
- OpenAI compatible API
- Supports multiple-models
- Once loaded the first time, it keep models loaded in memory for faster inference
- Support for prompt templates
- Doesn't shell-out, but uses C bindings for a faster inference and better performance. Uses [go-llama.cpp](https://github.com/go-skynet/go-llama.cpp) and [go-gpt4all-j.cpp](https://github.com/go-skynet/go-gpt4all-j.cpp).
**LocalAI** is the free, Open Source OpenAI alternative. LocalAI act as a drop-in replacement REST API thats compatible with OpenAI (Elevenlabs, Anthropic... ) API specifications for local AI inferencing. It allows you to run LLMs, generate images, audio (and not only) locally or on-prem with consumer grade hardware, supporting multiple model families. Does not require GPU. It is created and maintained by [Ettore Di Giacinto](https://github.com/mudler).
Reddit post: https://www.reddit.com/r/selfhosted/comments/12w4p2f/localai_openai_compatible_api_to_run_llm_models/
![screen](https://github.com/mudler/LocalAI/assets/2420543/20b5ccd2-8393-44f0-aaf6-87a23806381e)
LocalAI is a community-driven project, focused on making the AI accessible to anyone. Any contribution, feedback and PR is welcome! It was initially created by [mudler](https://github.com/mudler/) at the [SpectroCloud OSS Office](https://github.com/spectrocloud).
Run the installer script:
## Model compatibility
It is compatible with the models supported by [llama.cpp](https://github.com/ggerganov/llama.cpp) supports also [GPT4ALL-J](https://github.com/nomic-ai/gpt4all) and [cerebras-GPT with ggml](https://huggingface.co/lxe/Cerebras-GPT-2.7B-Alpaca-SP-ggml).
Tested with:
- Vicuna
- Alpaca
- [GPT4ALL](https://github.com/nomic-ai/gpt4all)
- [GPT4ALL-J](https://gpt4all.io/models/ggml-gpt4all-j.bin)
- Koala
- [cerebras-GPT with ggml](https://huggingface.co/lxe/Cerebras-GPT-2.7B-Alpaca-SP-ggml)
It should also be compatible with StableLM and GPTNeoX ggml models (untested)
Note: You might need to convert older models to the new format, see [here](https://github.com/ggerganov/llama.cpp#using-gpt4all) for instance to run `gpt4all`.
## Usage
> `LocalAI` comes by default as a container image. You can check out all the available images with corresponding tags [here](https://quay.io/repository/go-skynet/local-ai?tab=tags&tag=latest).
The easiest way to run LocalAI is by using `docker-compose`:
```bash
curl https://localai.io/install.sh | sh
git clone https://github.com/go-skynet/LocalAI
cd LocalAI
# (optional) Checkout a specific LocalAI tag
# git checkout -b build <TAG>
# copy your models to models/
cp your-model.bin models/
# (optional) Edit the .env file to set things like context size and threads
# vim .env
# start with docker-compose
docker-compose up -d --build
# Now API is accessible at localhost:8080
curl http://localhost:8080/v1/models
# {"object":"list","data":[{"id":"your-model.bin","object":"model"}]}
curl http://localhost:8080/v1/completions -H "Content-Type: application/json" -d '{
"model": "your-model.bin",
"prompt": "A long time ago in a galaxy far, far away",
"temperature": 0.7
}'
```
Or run with docker:
### Example: Use GPT4ALL-J model
<details>
```bash
docker run -ti --name local-ai -p 8080:8080 localai/localai:latest-aio-cpu
# Alternative images:
# - if you have an Nvidia GPU:
# docker run -ti --name local-ai -p 8080:8080 --gpus all localai/localai:latest-aio-gpu-nvidia-cuda-12
# - without preconfigured models
# docker run -ti --name local-ai -p 8080:8080 localai/localai:latest
# - without preconfigured models for Nvidia GPUs
# docker run -ti --name local-ai -p 8080:8080 --gpus all localai/localai:latest-gpu-nvidia-cuda-12
# Clone LocalAI
git clone https://github.com/go-skynet/LocalAI
cd LocalAI
# (optional) Checkout a specific LocalAI tag
# git checkout -b build <TAG>
# Download gpt4all-j to models/
wget https://gpt4all.io/models/ggml-gpt4all-j.bin -O models/ggml-gpt4all-j
# Use a template from the examples
cp -rf prompt-templates/ggml-gpt4all-j.tmpl models/
# (optional) Edit the .env file to set things like context size and threads
# vim .env
# start with docker-compose
docker-compose up -d --build
# Now API is accessible at localhost:8080
curl http://localhost:8080/v1/models
# {"object":"list","data":[{"id":"ggml-gpt4all-j","object":"model"}]}
curl http://localhost:8080/v1/chat/completions -H "Content-Type: application/json" -d '{
"model": "ggml-gpt4all-j",
"messages": [{"role": "user", "content": "How are you?"}],
"temperature": 0.9
}'
# {"model":"ggml-gpt4all-j","choices":[{"message":{"role":"assistant","content":"I'm doing well, thanks. How about you?"}}]}
```
</details>
[💻 Getting started](https://localai.io/basics/getting_started/index.html)
To build locally, run `make build` (see below).
## 🔥🔥 Hot topics / Roadmap
## Other examples
[Roadmap](https://github.com/mudler/LocalAI/issues?q=is%3Aissue+is%3Aopen+label%3Aroadmap)
![Screenshot from 2023-04-26 23-59-55](https://user-images.githubusercontent.com/2420543/234715439-98d12e03-d3ce-4f94-ab54-2b256808e05e.png)
- July 2024: 🔥🔥 🆕 P2P Dashboard, LocalAI Federated mode and AI Swarms: https://github.com/mudler/LocalAI/pull/2723
- June 2024: 🆕 You can browse now the model gallery without LocalAI! Check out https://models.localai.io
- June 2024: Support for models from OCI registries: https://github.com/mudler/LocalAI/pull/2628
- May 2024: 🔥🔥 Decentralized P2P llama.cpp: https://github.com/mudler/LocalAI/pull/2343 (peer2peer llama.cpp!) 👉 Docs https://localai.io/features/distribute/
- May 2024: 🔥🔥 Openvoice: https://github.com/mudler/LocalAI/pull/2334
- May 2024: 🆕 Function calls without grammars and mixed mode: https://github.com/mudler/LocalAI/pull/2328
- May 2024: 🔥🔥 Distributed inferencing: https://github.com/mudler/LocalAI/pull/2324
- May 2024: Chat, TTS, and Image generation in the WebUI: https://github.com/mudler/LocalAI/pull/2222
- April 2024: Reranker API: https://github.com/mudler/LocalAI/pull/2121
To see other examples on how to integrate with other projects for instance chatbot-ui, see: [examples](https://github.com/go-skynet/LocalAI/tree/master/examples/).
Hot topics (looking for contributors):
## Prompt templates
- 🔥🔥 Distributed, P2P Global community pools: https://github.com/mudler/LocalAI/issues/3113
- WebUI improvements: https://github.com/mudler/LocalAI/issues/2156
- Backends v2: https://github.com/mudler/LocalAI/issues/1126
- Improving UX v2: https://github.com/mudler/LocalAI/issues/1373
- Assistant API: https://github.com/mudler/LocalAI/issues/1273
- Moderation endpoint: https://github.com/mudler/LocalAI/issues/999
- Vulkan: https://github.com/mudler/LocalAI/issues/1647
- Anthropic API: https://github.com/mudler/LocalAI/issues/1808
The API doesn't inject a default prompt for talking to the model. You have to use a prompt similar to what's described in the standford-alpaca docs: https://github.com/tatsu-lab/stanford_alpaca#data-release.
If you want to help and contribute, issues up for grabs: https://github.com/mudler/LocalAI/issues?q=is%3Aissue+is%3Aopen+label%3A%22up+for+grabs%22
## 🚀 [Features](https://localai.io/features/)
- 📖 [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-alike tools API](https://localai.io/features/openai-functions/)
- 🧠 [Embeddings generation for vector databases](https://localai.io/features/embeddings/)
- ✍️ [Constrained grammars](https://localai.io/features/constrained_grammars/)
- 🖼️ [Download Models directly from Huggingface ](https://localai.io/models/)
- 🥽 [Vision API](https://localai.io/features/gpt-vision/)
- 📈 [Reranker API](https://localai.io/features/reranker/)
- 🆕🖧 [P2P Inferencing](https://localai.io/features/distribute/)
- 🌍 Integrated WebUI!
## 💻 Usage
Check out the [Getting started](https://localai.io/basics/getting_started/index.html) section in our documentation.
### 🔗 Community and integrations
Build and deploy custom containers:
- https://github.com/sozercan/aikit
WebUIs:
- https://github.com/Jirubizu/localai-admin
- https://github.com/go-skynet/LocalAI-frontend
- QA-Pilot(An interactive chat project that leverages LocalAI LLMs for rapid understanding and navigation of GitHub code repository) https://github.com/reid41/QA-Pilot
Model galleries
- https://github.com/go-skynet/model-gallery
Other:
- Helm chart https://github.com/go-skynet/helm-charts
- VSCode extension https://github.com/badgooooor/localai-vscode-plugin
- Terminal utility https://github.com/djcopley/ShellOracle
- Local Smart assistant https://github.com/mudler/LocalAGI
- Home Assistant https://github.com/sammcj/homeassistant-localai / https://github.com/drndos/hass-openai-custom-conversation / https://github.com/valentinfrlch/ha-gpt4vision
- Discord bot https://github.com/mudler/LocalAGI/tree/main/examples/discord
- Slack bot https://github.com/mudler/LocalAGI/tree/main/examples/slack
- Shell-Pilot(Interact with LLM using LocalAI models via pure shell scripts on your Linux or MacOS system) https://github.com/reid41/shell-pilot
- Telegram bot https://github.com/mudler/LocalAI/tree/master/examples/telegram-bot
- Github Actions: https://github.com/marketplace/actions/start-localai
- Examples: https://github.com/mudler/LocalAI/tree/master/examples/
### 🔗 Resources
- [LLM finetuning guide](https://localai.io/docs/advanced/fine-tuning/)
- [How to build locally](https://localai.io/basics/build/index.html)
- [How to install in Kubernetes](https://localai.io/basics/getting_started/index.html#run-localai-in-kubernetes)
- [Projects integrating LocalAI](https://localai.io/docs/integrations/)
- [How tos section](https://io.midori-ai.xyz/howtos/) (curated by our community)
## :book: 🎥 [Media, Blogs, Social](https://localai.io/basics/news/#media-blogs-social)
- [Run Visual studio code with LocalAI (SUSE)](https://www.suse.com/c/running-ai-locally/)
- 🆕 [Run LocalAI on Jetson Nano Devkit](https://mudler.pm/posts/local-ai-jetson-nano-devkit/)
- [Run LocalAI on AWS EKS with Pulumi](https://www.pulumi.com/blog/low-code-llm-apps-with-local-ai-flowise-and-pulumi/)
- [Run LocalAI on AWS](https://staleks.hashnode.dev/installing-localai-on-aws-ec2-instance)
- [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)
## Citation
If you utilize this repository, data in a downstream project, please consider citing it with:
<details>
You can use a default template for every model present in your model path, by creating a corresponding file with the `.tmpl` suffix next to your model. For instance, if the model is called `foo.bin`, you can create a sibling file, `foo.bin.tmpl` which will be used as a default prompt and can be used with alpaca:
```
@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}},
The below instruction describes a task. Write a response that appropriately completes the request.
### Instruction:
{{.Input}}
### Response:
```
## ❤️ Sponsors
See the [prompt-templates](https://github.com/go-skynet/LocalAI/tree/master/prompt-templates) directory in this repository for templates for some of the most popular models.
> 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.
## Installation
A huge thank you to our generous sponsors who support this project covering CI expenses, and our [Sponsor list](https://github.com/sponsors/mudler):
Currently LocalAI comes as container images and can be used with docker or a containre engine of choice.
<p align="center">
<a href="https://www.spectrocloud.com/" target="blank">
<img height="200" src="https://github.com/go-skynet/LocalAI/assets/2420543/68a6f3cb-8a65-4a4d-99b5-6417a8905512">
</a>
<a href="https://www.premai.io/" target="blank">
<img height="200" src="https://github.com/mudler/LocalAI/assets/2420543/42e4ca83-661e-4f79-8e46-ae43689683d6"> <br>
</a>
</p>
### Run LocalAI in Kubernetes
## 🌟 Star history
LocalAI can be installed inside Kubernetes with helm.
<details>
The local-ai Helm chart supports two options for the LocalAI server's models directory:
1. Basic deployment with no persistent volume. You must manually update the Deployment to configure your own models directory.
Install the chart with `.Values.deployment.volumes.enabled == false` and `.Values.dataVolume.enabled == false`.
2. Advanced, two-phase deployment to provision the models directory using a DataVolume. Requires [Containerized Data Importer CDI](https://github.com/kubevirt/containerized-data-importer) to be pre-installed in your cluster.
First, install the chart with `.Values.deployment.volumes.enabled == false` and `.Values.dataVolume.enabled == true`:
```bash
helm install local-ai charts/local-ai -n local-ai --create-namespace
```
Wait for CDI to create an importer Pod for the DataVolume and for the importer pod to finish provisioning the model archive inside the PV.
Once the PV is provisioned and the importer Pod removed, set `.Values.deployment.volumes.enabled == true` and `.Values.dataVolume.enabled == false` and upgrade the chart:
```bash
helm upgrade local-ai -n local-ai charts/local-ai
```
This will update the local-ai Deployment to mount the PV that was provisioned by the DataVolume.
</details>
## API
`LocalAI` provides an API for running text generation as a service, that follows the OpenAI reference and can be used as a drop-in. The models once loaded the first time will be kept in memory.
<details>
Example of starting the API with `docker`:
```bash
docker run -p 8080:8080 -ti --rm quay.io/go-skynet/local-ai:latest --models-path /path/to/models --context-size 700 --threads 4
```
You should see:
```
┌───────────────────────────────────────────────────┐
│ Fiber v2.42.0 │
│ http://127.0.0.1:8080 │
│ (bound on host 0.0.0.0 and port 8080) │
│ │
│ Handlers ............. 1 Processes ........... 1 │
│ Prefork ....... Disabled PID ................. 1 │
└───────────────────────────────────────────────────┘
```
You can control the API server options with command line arguments:
```
local-api --models-path <model_path> [--address <address>] [--threads <num_threads>]
```
The API takes takes the following parameters:
| Parameter | Environment Variable | Default Value | Description |
| ------------ | -------------------- | ------------- | -------------------------------------- |
| models-path | MODELS_PATH | | The path where you have models (ending with `.bin`). |
| threads | THREADS | Number of Physical cores | The number of threads to use for text generation. |
| address | ADDRESS | :8080 | The address and port to listen on. |
| context-size | CONTEXT_SIZE | 512 | Default token context size. |
| debug | DEBUG | false | Enable debug mode. |
| config-file | CONFIG_FILE | empty | Path to a LocalAI config file. |
Once the server is running, you can start making requests to it using HTTP, using the OpenAI API.
</details>
### Supported OpenAI API endpoints
You can check out the [OpenAI API reference](https://platform.openai.com/docs/api-reference/chat/create).
Following the list of endpoints/parameters supported.
Note:
- You can also specify the model as part of the OpenAI token.
- If only one model is available, the API will use it for all the requests.
#### Chat completions
<details>
For example, to generate a chat completion, you can send a POST request to the `/v1/chat/completions` endpoint with the instruction as the request body:
```
curl http://localhost:8080/v1/chat/completions -H "Content-Type: application/json" -d '{
"model": "ggml-koala-7b-model-q4_0-r2.bin",
"messages": [{"role": "user", "content": "Say this is a test!"}],
"temperature": 0.7
}'
```
Available additional parameters: `top_p`, `top_k`, `max_tokens`
</details>
#### Completions
<details>
To generate a completion, you can send a POST request to the `/v1/completions` endpoint with the instruction as per the request body:
```
curl http://localhost:8080/v1/completions -H "Content-Type: application/json" -d '{
"model": "ggml-koala-7b-model-q4_0-r2.bin",
"prompt": "A long time ago in a galaxy far, far away",
"temperature": 0.7
}'
```
Available additional parameters: `top_p`, `top_k`, `max_tokens`
</details>
#### List models
<details>
You can list all the models available with:
```
curl http://localhost:8080/v1/models
```
</details>
## Advanced configuration
LocalAI can be configured to serve user-defined models with a set of default parameters and templates.
<details>
You can create multiple `yaml` files in the models path or either specify a single YAML configuration file.
For instance, a configuration file (`gpt-3.5-turbo.yaml`) can be declaring the "gpt-3.5-turbo" model but backed by the "testmodel" model file:
```yaml
name: gpt-3.5-turbo
parameters:
model: testmodel
context_size: 512
threads: 10
stopwords:
- "HUMAN:"
- "### Response:"
roles:
user: "HUMAN:"
system: "GPT:"
template:
completion: completion
chat: ggml-gpt4all-j
```
Specifying a `config-file` via CLI allows to declare models in a single file as a list, for instance:
```yaml
- name: list1
parameters:
model: testmodel
context_size: 512
threads: 10
stopwords:
- "HUMAN:"
- "### Response:"
roles:
user: "HUMAN:"
system: "GPT:"
template:
completion: completion
chat: ggml-gpt4all-j
- name: list2
parameters:
model: testmodel
context_size: 512
threads: 10
stopwords:
- "HUMAN:"
- "### Response:"
roles:
user: "HUMAN:"
system: "GPT:"
template:
completion: completion
chat: ggml-gpt4all-j
```
See also [chatbot-ui](https://github.com/go-skynet/LocalAI/tree/master/examples/chatbot-ui) as an example on how to use config files.
</details>
## Blog posts
- https://medium.com/@tyler_97636/k8sgpt-localai-unlock-kubernetes-superpowers-for-free-584790de9b65
## Windows compatibility
It should work, however you need to make sure you give enough resources to the container. See https://github.com/go-skynet/LocalAI/issues/2
## Build locally
Pre-built images might fit well for most of the modern hardware, however you can and might need to build the images manually.
In order to build the `LocalAI` container image locally you can use `docker`:
```
# build the image
docker build -t LocalAI .
docker run LocalAI
```
Or build the binary with `make`:
```
make build
```
## Frequently asked questions
Here are answers to some of the most common questions.
### How do I get models?
<details>
Most ggml-based models should work, but newer models may require additions to the API. If a model doesn't work, please feel free to open up issues. However, be cautious about downloading models from the internet and directly onto your machine, as there may be security vulnerabilities in lama.cpp or ggml that could be maliciously exploited. Some models can be found on Hugging Face: https://huggingface.co/models?search=ggml, or models from gpt4all should also work: https://github.com/nomic-ai/gpt4all.
</details>
### What's the difference with Serge, or XXX?
<details>
LocalAI is a multi-model solution that doesn't focus on a specific model type (e.g., llama.cpp or alpaca.cpp), and it handles all of these internally for faster inference, easy to set up locally and deploy to Kubernetes.
</details>
### Can I use it with a Discord bot, or XXX?
<details>
Yes! If the client uses OpenAI and supports setting a different base URL to send requests to, you can use the LocalAI endpoint. This allows to use this with every application that was supposed to work with OpenAI, but without changing the application!
</details>
### Can this leverage GPUs?
<details>
Not currently, as ggml doesn't support GPUs yet: https://github.com/ggerganov/llama.cpp/discussions/915.
</details>
### Where is the webUI?
<details>
We are working on to have a good out of the box experience - however as LocalAI is an API you can already plug it into existing projects that provides are UI interfaces to OpenAI's APIs. There are several already on github, and should be compatible with LocalAI already (as it mimics the OpenAI API)
</details>
### Does it work with AutoGPT?
<details>
AutoGPT currently doesn't allow to set a different API URL, but there is a PR open for it, so this should be possible soon!
</details>
## Projects already using LocalAI to run local models
Feel free to open up a PR to get your project listed!
- [Kairos](https://github.com/kairos-io/kairos)
- [k8sgpt](https://github.com/k8sgpt-ai/k8sgpt#running-local-models)
## Short-term roadmap
- [x] Mimic OpenAI API (https://github.com/go-skynet/LocalAI/issues/10)
- [ ] Binary releases (https://github.com/go-skynet/LocalAI/issues/6)
- [ ] Upstream our golang bindings to llama.cpp (https://github.com/ggerganov/llama.cpp/issues/351) and [gpt4all](https://github.com/go-skynet/LocalAI/issues/85)
- [x] Multi-model support
- [x] Have a webUI!
- [x] Allow configuration of defaults for models.
- [ ] Enable automatic downloading of models from a curated gallery, with only free-licensed models.
## Star history
[![LocalAI Star history Chart](https://api.star-history.com/svg?repos=go-skynet/LocalAI&type=Date)](https://star-history.com/#go-skynet/LocalAI&Date)
## 📖 License
## License
LocalAI is a community-driven project created by [Ettore Di Giacinto](https://github.com/mudler/).
LocalAI is a community-driven project. It was initially created by [mudler](https://github.com/mudler/) at the [SpectroCloud OSS Office](https://github.com/spectrocloud).
MIT - Author Ettore Di Giacinto <mudler@localai.io>
MIT
## 🙇 Acknowledgements
LocalAI couldn't have been built without the help of great software already available from the community. Thank you!
## Acknowledgements
- [llama.cpp](https://github.com/ggerganov/llama.cpp)
- https://github.com/tatsu-lab/stanford_alpaca
- https://github.com/cornelk/llama-go for the initial ideas
- https://github.com/antimatter15/alpaca.cpp
- https://github.com/EdVince/Stable-Diffusion-NCNN
- https://github.com/ggerganov/whisper.cpp
- https://github.com/saharNooby/rwkv.cpp
- https://github.com/rhasspy/piper
## 🤗 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>
- https://github.com/antimatter15/alpaca.cpp for the light model version (this is compatible and tested only with that checkpoint model!)

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@@ -1,42 +0,0 @@
# Security Policy
## Introduction
At LocalAI, we take the security of our software seriously. We understand the importance of protecting our community from vulnerabilities and are committed to ensuring the safety and security of our users.
## Supported Versions
We provide support and updates for certain versions of our software. The following table outlines which versions are currently supported with security updates:
| Version | Supported |
| ------- | ------------------ |
| > 2.0 | :white_check_mark: |
| < 2.0 | :x: |
Please ensure that you are using a supported version to receive the latest security updates.
## Reporting a Vulnerability
We encourage the responsible disclosure of any security vulnerabilities. If you believe you've found a security issue in our software, we kindly ask you to follow the steps below to report it to us:
1. **Email Us:** Send an email to [security@localai.io](mailto:security@localai.io) with a detailed report. Please do not disclose the vulnerability publicly or to any third parties before it has been addressed by us.
2. **Expect a Response:** We aim to acknowledge receipt of vulnerability reports within 48 hours. Our security team will review your report and work closely with you to understand the impact and ensure a thorough investigation.
3. **Collaboration:** If the vulnerability is accepted, we will work with you and our community to address the issue promptly. We'll keep you informed throughout the resolution process and may request additional information or collaboration.
4. **Disclosure:** Once the vulnerability has been resolved, we encourage a coordinated disclosure. We believe in transparency and will work with you to ensure that our community is informed in a responsible manner.
## Use of Third-Party Platforms
As a Free and Open Source Software (FOSS) organization, we do not offer monetary bounties. However, researchers who wish to report vulnerabilities can also do so via [Huntr](https://huntr.dev/bounties), a platform that recognizes contributions to open source security.
## Contact
For any security-related inquiries beyond vulnerability reporting, please contact us at [security@localai.io](mailto:security@localai.io).
## Acknowledgments
We appreciate the efforts of those who contribute to the security of our project. Your responsible disclosure is invaluable to the safety and integrity of LocalAI.
Thank you for helping us keep LocalAI secure.

View File

@@ -1,5 +0,0 @@
## AIO CPU size
Use this image with CPU-only.
Please keep using only C++ backends so the base image is as small as possible (without CUDA, cuDNN, python, etc).

View File

@@ -1,12 +0,0 @@
name: text-embedding-ada-002
backend: bert-embeddings
parameters:
model: huggingface://mudler/all-MiniLM-L6-v2/ggml-model-q4_0.bin
usage: |
You can test this model with curl like this:
curl http://localhost:8080/embeddings -X POST -H "Content-Type: application/json" -d '{
"input": "Your text string goes here",
"model": "text-embedding-ada-002"
}'

View File

@@ -1,62 +0,0 @@
name: stablediffusion
backend: stablediffusion
parameters:
model: stablediffusion_assets
license: "BSD-3"
urls:
- https://github.com/EdVince/Stable-Diffusion-NCNN
- https://github.com/EdVince/Stable-Diffusion-NCNN/blob/main/LICENSE
description: |
Stable Diffusion in NCNN with c++, supported txt2img and img2img
download_files:
- filename: "stablediffusion_assets/AutoencoderKL-256-256-fp16-opt.param"
sha256: "18ca4b66685e21406bcf64c484b3b680b4949900415536d599cc876579c85c82"
uri: "https://raw.githubusercontent.com/EdVince/Stable-Diffusion-NCNN/main/x86/linux/assets/AutoencoderKL-256-256-fp16-opt.param"
- filename: "stablediffusion_assets/AutoencoderKL-512-512-fp16-opt.param"
sha256: "cf45f63aacf3dbbab0f59ed92a6f2c14d9a1801314631cd3abe91e3c85639a20"
uri: "https://raw.githubusercontent.com/EdVince/Stable-Diffusion-NCNN/main/x86/linux/assets/AutoencoderKL-512-512-fp16-opt.param"
- filename: "stablediffusion_assets/AutoencoderKL-base-fp16.param"
sha256: "0254a056dce61b0c27dc9ec1b78b53bcf55315c540f55f051eb841aa992701ba"
uri: "https://raw.githubusercontent.com/EdVince/Stable-Diffusion-NCNN/main/x86/linux/assets/AutoencoderKL-base-fp16.param"
- filename: "stablediffusion_assets/AutoencoderKL-encoder-512-512-fp16.bin"
sha256: "ddcb79a9951b9f91e05e087739ed69da2c1c4ae30ba4168cce350b49d617c9fa"
uri: "https://github.com/EdVince/Stable-Diffusion-NCNN/releases/download/naifu/AutoencoderKL-encoder-512-512-fp16.bin"
- filename: "stablediffusion_assets/AutoencoderKL-fp16.bin"
sha256: "f02e71f80e70252734724bbfaed5c4ddd3a8ed7e61bb2175ff5f53099f0e35dd"
uri: "https://github.com/EdVince/Stable-Diffusion-NCNN/releases/download/naifu/AutoencoderKL-fp16.bin"
- filename: "stablediffusion_assets/FrozenCLIPEmbedder-fp16.bin"
sha256: "1c9a12f4e1dd1b295a388045f7f28a2352a4d70c3dc96a542189a3dd7051fdd6"
uri: "https://github.com/EdVince/Stable-Diffusion-NCNN/releases/download/naifu/FrozenCLIPEmbedder-fp16.bin"
- filename: "stablediffusion_assets/FrozenCLIPEmbedder-fp16.param"
sha256: "471afbe678dd1fd3fe764ef9c6eccaccb0a7d7e601f27b462aa926b20eb368c9"
uri: "https://raw.githubusercontent.com/EdVince/Stable-Diffusion-NCNN/main/x86/linux/assets/FrozenCLIPEmbedder-fp16.param"
- filename: "stablediffusion_assets/log_sigmas.bin"
sha256: "a2089f8aa4c61f9c200feaec541ab3f5c94233b28deb6d5e8bcd974fa79b68ac"
uri: "https://github.com/EdVince/Stable-Diffusion-NCNN/raw/main/x86/linux/assets/log_sigmas.bin"
- filename: "stablediffusion_assets/UNetModel-256-256-MHA-fp16-opt.param"
sha256: "a58c380229f09491776df837b7aa7adffc0a87821dc4708b34535da2e36e3da1"
uri: "https://raw.githubusercontent.com/EdVince/Stable-Diffusion-NCNN/main/x86/linux/assets/UNetModel-256-256-MHA-fp16-opt.param"
- filename: "stablediffusion_assets/UNetModel-512-512-MHA-fp16-opt.param"
sha256: "f12034067062827bd7f43d1d21888d1f03905401acf6c6eea22be23c259636fa"
uri: "https://raw.githubusercontent.com/EdVince/Stable-Diffusion-NCNN/main/x86/linux/assets/UNetModel-512-512-MHA-fp16-opt.param"
- filename: "stablediffusion_assets/UNetModel-base-MHA-fp16.param"
sha256: "696f6975de49f4325b53ce32aff81861a6d6c07cd9ce3f0aae2cc405350af38d"
uri: "https://raw.githubusercontent.com/EdVince/Stable-Diffusion-NCNN/main/x86/linux/assets/UNetModel-base-MHA-fp16.param"
- filename: "stablediffusion_assets/UNetModel-MHA-fp16.bin"
sha256: "d618918d011bfc1f644c0f2a33bf84931bd53b28a98492b0a8ed6f3a818852c3"
uri: "https://github.com/EdVince/Stable-Diffusion-NCNN/releases/download/naifu/UNetModel-MHA-fp16.bin"
- filename: "stablediffusion_assets/vocab.txt"
sha256: "e30e57b6f1e47616982ef898d8922be24e535b4fa3d0110477b3a6f02ebbae7d"
uri: "https://raw.githubusercontent.com/EdVince/Stable-Diffusion-NCNN/main/x86/linux/assets/vocab.txt"
usage: |
curl http://localhost:8080/v1/images/generations \
-H "Content-Type: application/json" \
-d '{
"prompt": "<positive prompt>|<negative prompt>",
"step": 25,
"size": "512x512"
}'

View File

@@ -1,27 +0,0 @@
name: jina-reranker-v1-base-en
backend: rerankers
parameters:
model: cross-encoder
usage: |
You can test this model with curl like this:
curl http://localhost:8080/v1/rerank \
-H "Content-Type: application/json" \
-d '{
"model": "jina-reranker-v1-base-en",
"query": "Organic skincare products for sensitive skin",
"documents": [
"Eco-friendly kitchenware for modern homes",
"Biodegradable cleaning supplies for eco-conscious consumers",
"Organic cotton baby clothes for sensitive skin",
"Natural organic skincare range for sensitive skin",
"Tech gadgets for smart homes: 2024 edition",
"Sustainable gardening tools and compost solutions",
"Sensitive skin-friendly facial cleansers and toners",
"Organic food wraps and storage solutions",
"All-natural pet food for dogs with allergies",
"Yoga mats made from recycled materials"
],
"top_n": 3
}'

View File

@@ -1,18 +0,0 @@
name: whisper-1
backend: whisper
parameters:
model: ggml-whisper-base.bin
usage: |
## example audio file
wget --quiet --show-progress -O gb1.ogg https://upload.wikimedia.org/wikipedia/commons/1/1f/George_W_Bush_Columbia_FINAL.ogg
## Send the example audio file to the transcriptions endpoint
curl http://localhost:8080/v1/audio/transcriptions \
-H "Content-Type: multipart/form-data" \
-F file="@$PWD/gb1.ogg" -F model="whisper-1"
download_files:
- filename: "ggml-whisper-base.bin"
sha256: "60ed5bc3dd14eea856493d334349b405782ddcaf0028d4b5df4088345fba2efe"
uri: "https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-base.bin"

View File

@@ -1,15 +0,0 @@
name: tts-1
download_files:
- filename: voice-en-us-amy-low.tar.gz
uri: https://github.com/rhasspy/piper/releases/download/v0.0.2/voice-en-us-amy-low.tar.gz
parameters:
model: en-us-amy-low.onnx
usage: |
To test if this model works as expected, you can use the following curl command:
curl http://localhost:8080/tts -H "Content-Type: application/json" -d '{
"model":"voice-en-us-amy-low",
"input": "Hi, this is a test."
}'

View File

@@ -1,101 +0,0 @@
name: gpt-4
mmap: true
parameters:
model: huggingface://NousResearch/Hermes-2-Pro-Llama-3-8B-GGUF/Hermes-2-Pro-Llama-3-8B-Q4_K_M.gguf
context_size: 8192
stopwords:
- "<|im_end|>"
- "<dummy32000>"
- "</tool_call>"
- "<|eot_id|>"
- "<|end_of_text|>"
function:
# disable injecting the "answer" tool
disable_no_action: true
grammar:
# This allows the grammar to also return messages
mixed_mode: true
# Suffix to add to the grammar
#prefix: '<tool_call>\n'
# Force parallel calls in the grammar
# parallel_calls: true
return_name_in_function_response: true
# Without grammar uncomment the lines below
# Warning: this is relying only on the capability of the
# LLM model to generate the correct function call.
json_regex_match:
- "(?s)<tool_call>(.*?)</tool_call>"
- "(?s)<tool_call>(.*?)"
replace_llm_results:
# Drop the scratchpad content from responses
- key: "(?s)<scratchpad>.*</scratchpad>"
value: ""
replace_function_results:
# Replace everything that is not JSON array or object
#
- key: '(?s)^[^{\[]*'
value: ""
- key: '(?s)[^}\]]*$'
value: ""
- key: "'([^']*?)'"
value: "_DQUOTE_${1}_DQUOTE_"
- key: '\\"'
value: "__TEMP_QUOTE__"
- key: "\'"
value: "'"
- key: "_DQUOTE_"
value: '"'
- key: "__TEMP_QUOTE__"
value: '"'
# Drop the scratchpad content from responses
- key: "(?s)<scratchpad>.*</scratchpad>"
value: ""
template:
chat: |
{{.Input -}}
<|im_start|>assistant
chat_message: |
<|im_start|>{{if eq .RoleName "assistant"}}assistant{{else if eq .RoleName "system"}}system{{else if eq .RoleName "tool"}}tool{{else if eq .RoleName "user"}}user{{end}}
{{- if .FunctionCall }}
<tool_call>
{{- else if eq .RoleName "tool" }}
<tool_response>
{{- end }}
{{- if .Content}}
{{.Content }}
{{- end }}
{{- if .FunctionCall}}
{{toJson .FunctionCall}}
{{- end }}
{{- if .FunctionCall }}
</tool_call>
{{- else if eq .RoleName "tool" }}
</tool_response>
{{- end }}<|im_end|>
completion: |
{{.Input}}
function: |-
<|im_start|>system
You are a function calling AI model.
Here are the available tools:
<tools>
{{range .Functions}}
{'type': 'function', 'function': {'name': '{{.Name}}', 'description': '{{.Description}}', 'parameters': {{toJson .Parameters}} }}
{{end}}
</tools>
You should call the tools provided to you sequentially
Please use <scratchpad> XML tags to record your reasoning and planning before you call the functions as follows:
<scratchpad>
{step-by-step reasoning and plan in bullet points}
</scratchpad>
For each function call return a json object with function name and arguments within <tool_call> XML tags as follows:
<tool_call>
{"arguments": <args-dict>, "name": <function-name>}
</tool_call><|im_end|>
{{.Input -}}
<|im_start|>assistant

View File

@@ -1,31 +0,0 @@
backend: llama-cpp
context_size: 4096
f16: true
mmap: true
name: gpt-4-vision-preview
roles:
user: "USER:"
assistant: "ASSISTANT:"
system: "SYSTEM:"
mmproj: bakllava-mmproj.gguf
parameters:
model: bakllava.gguf
template:
chat: |
A chat between a curious human and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the human's questions.
{{.Input}}
ASSISTANT:
download_files:
- filename: bakllava.gguf
uri: huggingface://mys/ggml_bakllava-1/ggml-model-q4_k.gguf
- filename: bakllava-mmproj.gguf
uri: huggingface://mys/ggml_bakllava-1/mmproj-model-f16.gguf
usage: |
curl http://localhost:8080/v1/chat/completions -H "Content-Type: application/json" -d '{
"model": "gpt-4-vision-preview",
"messages": [{"role": "user", "content": [{"type":"text", "text": "What is in the image?"}, {"type": "image_url", "image_url": {"url": "https://upload.wikimedia.org/wikipedia/commons/thumb/d/dd/Gfp-wisconsin-madison-the-nature-boardwalk.jpg/2560px-Gfp-wisconsin-madison-the-nature-boardwalk.jpg" }}], "temperature": 0.9}]}'

View File

@@ -1,138 +0,0 @@
#!/bin/bash
echo "===> LocalAI All-in-One (AIO) container starting..."
GPU_ACCELERATION=false
GPU_VENDOR=""
function check_intel() {
if lspci | grep -E 'VGA|3D' | grep -iq intel; then
echo "Intel GPU detected"
if [ -d /opt/intel ]; then
GPU_ACCELERATION=true
GPU_VENDOR=intel
else
echo "Intel GPU detected, but Intel GPU drivers are not installed. GPU acceleration will not be available."
fi
fi
}
function check_nvidia_wsl() {
if lspci | grep -E 'VGA|3D' | grep -iq "Microsoft Corporation Device 008e"; then
# We make the assumption this WSL2 cars is NVIDIA, then check for nvidia-smi
# Make sure the container was run with `--gpus all` as the only required parameter
echo "NVIDIA GPU detected via WSL2"
# nvidia-smi should be installed in the container
if nvidia-smi; then
GPU_ACCELERATION=true
GPU_VENDOR=nvidia
else
echo "NVIDIA GPU detected via WSL2, but nvidia-smi is not installed. GPU acceleration will not be available."
fi
fi
}
function check_amd() {
if lspci | grep -E 'VGA|3D' | grep -iq amd; then
echo "AMD GPU detected"
# Check if ROCm is installed
if [ -d /opt/rocm ]; then
GPU_ACCELERATION=true
GPU_VENDOR=amd
else
echo "AMD GPU detected, but ROCm is not installed. GPU acceleration will not be available."
fi
fi
}
function check_nvidia() {
if lspci | grep -E 'VGA|3D' | grep -iq nvidia; then
echo "NVIDIA GPU detected"
# nvidia-smi should be installed in the container
if nvidia-smi; then
GPU_ACCELERATION=true
GPU_VENDOR=nvidia
else
echo "NVIDIA GPU detected, but nvidia-smi is not installed. GPU acceleration will not be available."
fi
fi
}
function check_metal() {
if system_profiler SPDisplaysDataType | grep -iq 'Metal'; then
echo "Apple Metal supported GPU detected"
GPU_ACCELERATION=true
GPU_VENDOR=apple
fi
}
function detect_gpu() {
case "$(uname -s)" in
Linux)
check_nvidia
check_amd
check_intel
check_nvidia_wsl
;;
Darwin)
check_metal
;;
esac
}
function detect_gpu_size() {
# Attempting to find GPU memory size for NVIDIA GPUs
if [ "$GPU_ACCELERATION" = true ] && [ "$GPU_VENDOR" = "nvidia" ]; then
echo "NVIDIA GPU detected. Attempting to find memory size..."
# Using head -n 1 to get the total memory of the 1st NVIDIA GPU detected.
# If handling multiple GPUs is required in the future, this is the place to do it
nvidia_sm=$(nvidia-smi --query-gpu=memory.total --format=csv,noheader,nounits | head -n 1)
if [ ! -z "$nvidia_sm" ]; then
echo "Total GPU Memory: $nvidia_sm MiB"
# if bigger than 8GB, use 16GB
#if [ "$nvidia_sm" -gt 8192 ]; then
# GPU_SIZE=gpu-16g
#else
GPU_SIZE=gpu-8g
#fi
else
echo "Unable to determine NVIDIA GPU memory size. Falling back to CPU."
GPU_SIZE=gpu-8g
fi
elif [ "$GPU_ACCELERATION" = true ] && [ "$GPU_VENDOR" = "intel" ]; then
GPU_SIZE=intel
# Default to a generic GPU size until we implement GPU size detection for non NVIDIA GPUs
elif [ "$GPU_ACCELERATION" = true ]; then
echo "Non-NVIDIA GPU detected. Specific GPU memory size detection is not implemented."
GPU_SIZE=gpu-8g
# default to cpu if GPU_SIZE is not set
else
echo "GPU acceleration is not enabled or supported. Defaulting to CPU."
GPU_SIZE=cpu
fi
}
function check_vars() {
if [ -z "$MODELS" ]; then
echo "MODELS environment variable is not set. Please set it to a comma-separated list of model YAML files to load."
exit 1
fi
if [ -z "$PROFILE" ]; then
echo "PROFILE environment variable is not set. Please set it to one of the following: cpu, gpu-8g, gpu-16g, apple"
exit 1
fi
}
detect_gpu
detect_gpu_size
PROFILE="${PROFILE:-$GPU_SIZE}" # default to cpu
export MODELS="${MODELS:-/aio/${PROFILE}/embeddings.yaml,/aio/${PROFILE}/rerank.yaml,/aio/${PROFILE}/text-to-speech.yaml,/aio/${PROFILE}/image-gen.yaml,/aio/${PROFILE}/text-to-text.yaml,/aio/${PROFILE}/speech-to-text.yaml,/aio/${PROFILE}/vision.yaml}"
check_vars
echo "===> Starting LocalAI[$PROFILE] with the following models: $MODELS"
exec /build/entrypoint.sh "$@"

View File

@@ -1,12 +0,0 @@
name: text-embedding-ada-002
backend: sentencetransformers
parameters:
model: all-MiniLM-L6-v2
usage: |
You can test this model with curl like this:
curl http://localhost:8080/embeddings -X POST -H "Content-Type: application/json" -d '{
"input": "Your text string goes here",
"model": "text-embedding-ada-002"
}'

View File

@@ -1,25 +0,0 @@
name: stablediffusion
parameters:
model: DreamShaper_8_pruned.safetensors
backend: diffusers
step: 25
f16: true
diffusers:
pipeline_type: StableDiffusionPipeline
cuda: true
enable_parameters: "negative_prompt,num_inference_steps"
scheduler_type: "k_dpmpp_2m"
download_files:
- filename: DreamShaper_8_pruned.safetensors
uri: huggingface://Lykon/DreamShaper/DreamShaper_8_pruned.safetensors
usage: |
curl http://localhost:8080/v1/images/generations \
-H "Content-Type: application/json" \
-d '{
"prompt": "<positive prompt>|<negative prompt>",
"step": 25,
"size": "512x512"
}'

View File

@@ -1,27 +0,0 @@
name: jina-reranker-v1-base-en
backend: rerankers
parameters:
model: cross-encoder
usage: |
You can test this model with curl like this:
curl http://localhost:8080/v1/rerank \
-H "Content-Type: application/json" \
-d '{
"model": "jina-reranker-v1-base-en",
"query": "Organic skincare products for sensitive skin",
"documents": [
"Eco-friendly kitchenware for modern homes",
"Biodegradable cleaning supplies for eco-conscious consumers",
"Organic cotton baby clothes for sensitive skin",
"Natural organic skincare range for sensitive skin",
"Tech gadgets for smart homes: 2024 edition",
"Sustainable gardening tools and compost solutions",
"Sensitive skin-friendly facial cleansers and toners",
"Organic food wraps and storage solutions",
"All-natural pet food for dogs with allergies",
"Yoga mats made from recycled materials"
],
"top_n": 3
}'

View File

@@ -1,18 +0,0 @@
name: whisper-1
backend: whisper
parameters:
model: ggml-whisper-base.bin
usage: |
## example audio file
wget --quiet --show-progress -O gb1.ogg https://upload.wikimedia.org/wikipedia/commons/1/1f/George_W_Bush_Columbia_FINAL.ogg
## Send the example audio file to the transcriptions endpoint
curl http://localhost:8080/v1/audio/transcriptions \
-H "Content-Type: multipart/form-data" \
-F file="@$PWD/gb1.ogg" -F model="whisper-1"
download_files:
- filename: "ggml-whisper-base.bin"
sha256: "60ed5bc3dd14eea856493d334349b405782ddcaf0028d4b5df4088345fba2efe"
uri: "https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-base.bin"

View File

@@ -1,15 +0,0 @@
name: tts-1
download_files:
- filename: voice-en-us-amy-low.tar.gz
uri: https://github.com/rhasspy/piper/releases/download/v0.0.2/voice-en-us-amy-low.tar.gz
parameters:
model: en-us-amy-low.onnx
usage: |
To test if this model works as expected, you can use the following curl command:
curl http://localhost:8080/tts -H "Content-Type: application/json" -d '{
"model":"tts-1",
"input": "Hi, this is a test."
}'

View File

@@ -1,101 +0,0 @@
name: gpt-4
mmap: true
parameters:
model: huggingface://NousResearch/Hermes-2-Pro-Llama-3-8B-GGUF/Hermes-2-Pro-Llama-3-8B-Q4_K_M.gguf
context_size: 8192
stopwords:
- "<|im_end|>"
- "<dummy32000>"
- "</tool_call>"
- "<|eot_id|>"
- "<|end_of_text|>"
function:
# disable injecting the "answer" tool
disable_no_action: true
grammar:
# This allows the grammar to also return messages
mixed_mode: true
# Suffix to add to the grammar
#prefix: '<tool_call>\n'
# Force parallel calls in the grammar
# parallel_calls: true
return_name_in_function_response: true
# Without grammar uncomment the lines below
# Warning: this is relying only on the capability of the
# LLM model to generate the correct function call.
json_regex_match:
- "(?s)<tool_call>(.*?)</tool_call>"
- "(?s)<tool_call>(.*?)"
replace_llm_results:
# Drop the scratchpad content from responses
- key: "(?s)<scratchpad>.*</scratchpad>"
value: ""
replace_function_results:
# Replace everything that is not JSON array or object
#
- key: '(?s)^[^{\[]*'
value: ""
- key: '(?s)[^}\]]*$'
value: ""
- key: "'([^']*?)'"
value: "_DQUOTE_${1}_DQUOTE_"
- key: '\\"'
value: "__TEMP_QUOTE__"
- key: "\'"
value: "'"
- key: "_DQUOTE_"
value: '"'
- key: "__TEMP_QUOTE__"
value: '"'
# Drop the scratchpad content from responses
- key: "(?s)<scratchpad>.*</scratchpad>"
value: ""
template:
chat: |
{{.Input -}}
<|im_start|>assistant
chat_message: |
<|im_start|>{{if eq .RoleName "assistant"}}assistant{{else if eq .RoleName "system"}}system{{else if eq .RoleName "tool"}}tool{{else if eq .RoleName "user"}}user{{end}}
{{- if .FunctionCall }}
<tool_call>
{{- else if eq .RoleName "tool" }}
<tool_response>
{{- end }}
{{- if .Content}}
{{.Content }}
{{- end }}
{{- if .FunctionCall}}
{{toJson .FunctionCall}}
{{- end }}
{{- if .FunctionCall }}
</tool_call>
{{- else if eq .RoleName "tool" }}
</tool_response>
{{- end }}<|im_end|>
completion: |
{{.Input}}
function: |-
<|im_start|>system
You are a function calling AI model.
Here are the available tools:
<tools>
{{range .Functions}}
{'type': 'function', 'function': {'name': '{{.Name}}', 'description': '{{.Description}}', 'parameters': {{toJson .Parameters}} }}
{{end}}
</tools>
You should call the tools provided to you sequentially
Please use <scratchpad> XML tags to record your reasoning and planning before you call the functions as follows:
<scratchpad>
{step-by-step reasoning and plan in bullet points}
</scratchpad>
For each function call return a json object with function name and arguments within <tool_call> XML tags as follows:
<tool_call>
{"arguments": <args-dict>, "name": <function-name>}
</tool_call><|im_end|>
{{.Input -}}
<|im_start|>assistant

View File

@@ -1,35 +0,0 @@
backend: llama-cpp
context_size: 4096
f16: true
mmap: true
name: gpt-4-vision-preview
roles:
user: "USER:"
assistant: "ASSISTANT:"
system: "SYSTEM:"
mmproj: llava-v1.6-7b-mmproj-f16.gguf
parameters:
model: llava-v1.6-mistral-7b.Q5_K_M.gguf
temperature: 0.2
top_k: 40
top_p: 0.95
seed: -1
template:
chat: |
A chat between a curious human and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the human's questions.
{{.Input}}
ASSISTANT:
download_files:
- filename: llava-v1.6-mistral-7b.Q5_K_M.gguf
uri: huggingface://cjpais/llava-1.6-mistral-7b-gguf/llava-v1.6-mistral-7b.Q5_K_M.gguf
- filename: llava-v1.6-7b-mmproj-f16.gguf
uri: huggingface://cjpais/llava-1.6-mistral-7b-gguf/mmproj-model-f16.gguf
usage: |
curl http://localhost:8080/v1/chat/completions -H "Content-Type: application/json" -d '{
"model": "gpt-4-vision-preview",
"messages": [{"role": "user", "content": [{"type":"text", "text": "What is in the image?"}, {"type": "image_url", "image_url": {"url": "https://upload.wikimedia.org/wikipedia/commons/thumb/d/dd/Gfp-wisconsin-madison-the-nature-boardwalk.jpg/2560px-Gfp-wisconsin-madison-the-nature-boardwalk.jpg" }}], "temperature": 0.9}]}'

View File

@@ -1,12 +0,0 @@
name: text-embedding-ada-002
backend: sentencetransformers
parameters:
model: all-MiniLM-L6-v2
usage: |
You can test this model with curl like this:
curl http://localhost:8080/embeddings -X POST -H "Content-Type: application/json" -d '{
"input": "Your text string goes here",
"model": "text-embedding-ada-002"
}'

View File

@@ -1,20 +0,0 @@
name: stablediffusion
parameters:
model: runwayml/stable-diffusion-v1-5
backend: diffusers
step: 25
f16: true
diffusers:
pipeline_type: StableDiffusionPipeline
cuda: true
enable_parameters: "negative_prompt,num_inference_steps"
scheduler_type: "k_dpmpp_2m"
usage: |
curl http://localhost:8080/v1/images/generations \
-H "Content-Type: application/json" \
-d '{
"prompt": "<positive prompt>|<negative prompt>",
"step": 25,
"size": "512x512"
}'

View File

@@ -1,27 +0,0 @@
name: jina-reranker-v1-base-en
backend: rerankers
parameters:
model: cross-encoder
usage: |
You can test this model with curl like this:
curl http://localhost:8080/v1/rerank \
-H "Content-Type: application/json" \
-d '{
"model": "jina-reranker-v1-base-en",
"query": "Organic skincare products for sensitive skin",
"documents": [
"Eco-friendly kitchenware for modern homes",
"Biodegradable cleaning supplies for eco-conscious consumers",
"Organic cotton baby clothes for sensitive skin",
"Natural organic skincare range for sensitive skin",
"Tech gadgets for smart homes: 2024 edition",
"Sustainable gardening tools and compost solutions",
"Sensitive skin-friendly facial cleansers and toners",
"Organic food wraps and storage solutions",
"All-natural pet food for dogs with allergies",
"Yoga mats made from recycled materials"
],
"top_n": 3
}'

View File

@@ -1,18 +0,0 @@
name: whisper-1
backend: whisper
parameters:
model: ggml-whisper-base.bin
usage: |
## example audio file
wget --quiet --show-progress -O gb1.ogg https://upload.wikimedia.org/wikipedia/commons/1/1f/George_W_Bush_Columbia_FINAL.ogg
## Send the example audio file to the transcriptions endpoint
curl http://localhost:8080/v1/audio/transcriptions \
-H "Content-Type: multipart/form-data" \
-F file="@$PWD/gb1.ogg" -F model="whisper-1"
download_files:
- filename: "ggml-whisper-base.bin"
sha256: "60ed5bc3dd14eea856493d334349b405782ddcaf0028d4b5df4088345fba2efe"
uri: "https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-base.bin"

View File

@@ -1,15 +0,0 @@
name: tts-1
download_files:
- filename: voice-en-us-amy-low.tar.gz
uri: https://github.com/rhasspy/piper/releases/download/v0.0.2/voice-en-us-amy-low.tar.gz
parameters:
model: en-us-amy-low.onnx
usage: |
To test if this model works as expected, you can use the following curl command:
curl http://localhost:8080/tts -H "Content-Type: application/json" -d '{
"model":"tts-1",
"input": "Hi, this is a test."
}'

View File

@@ -1,103 +0,0 @@
name: gpt-4
mmap: false
context_size: 8192
f16: false
parameters:
model: huggingface://NousResearch/Hermes-2-Pro-Llama-3-8B-GGUF/Hermes-2-Pro-Llama-3-8B-Q4_K_M.gguf
stopwords:
- "<|im_end|>"
- "<dummy32000>"
- "</tool_call>"
- "<|eot_id|>"
- "<|end_of_text|>"
function:
# disable injecting the "answer" tool
disable_no_action: true
grammar:
# This allows the grammar to also return messages
mixed_mode: true
# Suffix to add to the grammar
#prefix: '<tool_call>\n'
# Force parallel calls in the grammar
# parallel_calls: true
return_name_in_function_response: true
# Without grammar uncomment the lines below
# Warning: this is relying only on the capability of the
# LLM model to generate the correct function call.
json_regex_match:
- "(?s)<tool_call>(.*?)</tool_call>"
- "(?s)<tool_call>(.*?)"
replace_llm_results:
# Drop the scratchpad content from responses
- key: "(?s)<scratchpad>.*</scratchpad>"
value: ""
replace_function_results:
# Replace everything that is not JSON array or object
#
- key: '(?s)^[^{\[]*'
value: ""
- key: '(?s)[^}\]]*$'
value: ""
- key: "'([^']*?)'"
value: "_DQUOTE_${1}_DQUOTE_"
- key: '\\"'
value: "__TEMP_QUOTE__"
- key: "\'"
value: "'"
- key: "_DQUOTE_"
value: '"'
- key: "__TEMP_QUOTE__"
value: '"'
# Drop the scratchpad content from responses
- key: "(?s)<scratchpad>.*</scratchpad>"
value: ""
template:
chat: |
{{.Input -}}
<|im_start|>assistant
chat_message: |
<|im_start|>{{if eq .RoleName "assistant"}}assistant{{else if eq .RoleName "system"}}system{{else if eq .RoleName "tool"}}tool{{else if eq .RoleName "user"}}user{{end}}
{{- if .FunctionCall }}
<tool_call>
{{- else if eq .RoleName "tool" }}
<tool_response>
{{- end }}
{{- if .Content}}
{{.Content }}
{{- end }}
{{- if .FunctionCall}}
{{toJson .FunctionCall}}
{{- end }}
{{- if .FunctionCall }}
</tool_call>
{{- else if eq .RoleName "tool" }}
</tool_response>
{{- end }}<|im_end|>
completion: |
{{.Input}}
function: |-
<|im_start|>system
You are a function calling AI model.
Here are the available tools:
<tools>
{{range .Functions}}
{'type': 'function', 'function': {'name': '{{.Name}}', 'description': '{{.Description}}', 'parameters': {{toJson .Parameters}} }}
{{end}}
</tools>
You should call the tools provided to you sequentially
Please use <scratchpad> XML tags to record your reasoning and planning before you call the functions as follows:
<scratchpad>
{step-by-step reasoning and plan in bullet points}
</scratchpad>
For each function call return a json object with function name and arguments within <tool_call> XML tags as follows:
<tool_call>
{"arguments": <args-dict>, "name": <function-name>}
</tool_call><|im_end|>
{{.Input -}}
<|im_start|>assistant

View File

@@ -1,35 +0,0 @@
backend: llama-cpp
context_size: 4096
mmap: false
f16: false
name: gpt-4-vision-preview
roles:
user: "USER:"
assistant: "ASSISTANT:"
system: "SYSTEM:"
mmproj: llava-v1.6-7b-mmproj-f16.gguf
parameters:
model: llava-v1.6-mistral-7b.Q5_K_M.gguf
temperature: 0.2
top_k: 40
top_p: 0.95
seed: -1
template:
chat: |
A chat between a curious human and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the human's questions.
{{.Input}}
ASSISTANT:
download_files:
- filename: llava-v1.6-mistral-7b.Q5_K_M.gguf
uri: huggingface://cjpais/llava-1.6-mistral-7b-gguf/llava-v1.6-mistral-7b.Q5_K_M.gguf
- filename: llava-v1.6-7b-mmproj-f16.gguf
uri: huggingface://cjpais/llava-1.6-mistral-7b-gguf/mmproj-model-f16.gguf
usage: |
curl http://localhost:8080/v1/chat/completions -H "Content-Type: application/json" -d '{
"model": "gpt-4-vision-preview",
"messages": [{"role": "user", "content": [{"type":"text", "text": "What is in the image?"}, {"type": "image_url", "image_url": {"url": "https://upload.wikimedia.org/wikipedia/commons/thumb/d/dd/Gfp-wisconsin-madison-the-nature-boardwalk.jpg/2560px-Gfp-wisconsin-madison-the-nature-boardwalk.jpg" }}], "temperature": 0.9}]}'

74
api/api.go Normal file
View File

@@ -0,0 +1,74 @@
package api
import (
"errors"
model "github.com/go-skynet/LocalAI/pkg/model"
"github.com/gofiber/fiber/v2"
"github.com/gofiber/fiber/v2/middleware/cors"
"github.com/gofiber/fiber/v2/middleware/recover"
"github.com/rs/zerolog"
"github.com/rs/zerolog/log"
)
func App(configFile string, loader *model.ModelLoader, threads, ctxSize int, f16 bool, debug, disableMessage bool) *fiber.App {
zerolog.SetGlobalLevel(zerolog.InfoLevel)
if debug {
zerolog.SetGlobalLevel(zerolog.DebugLevel)
}
// Return errors as JSON responses
app := fiber.New(fiber.Config{
DisableStartupMessage: disableMessage,
// Override default error handler
ErrorHandler: func(ctx *fiber.Ctx, err error) error {
// Status code defaults to 500
code := fiber.StatusInternalServerError
// Retrieve the custom status code if it's a *fiber.Error
var e *fiber.Error
if errors.As(err, &e) {
code = e.Code
}
// Send custom error page
return ctx.Status(code).JSON(
ErrorResponse{
Error: &APIError{Message: err.Error(), Code: code},
},
)
},
})
cm := make(ConfigMerger)
if err := cm.LoadConfigs(loader.ModelPath); err != nil {
log.Error().Msgf("error loading config files: %s", err.Error())
}
if configFile != "" {
if err := cm.LoadConfigFile(configFile); err != nil {
log.Error().Msgf("error loading config file: %s", err.Error())
}
}
if debug {
for k, v := range cm {
log.Debug().Msgf("Model: %s (config: %+v)", k, v)
}
}
// Default middleware config
app.Use(recover.New())
app.Use(cors.New())
// openAI compatible API endpoint
app.Post("/v1/chat/completions", openAIEndpoint(cm, true, debug, loader, threads, ctxSize, f16))
app.Post("/chat/completions", openAIEndpoint(cm, true, debug, loader, threads, ctxSize, f16))
app.Post("/v1/completions", openAIEndpoint(cm, false, debug, loader, threads, ctxSize, f16))
app.Post("/completions", openAIEndpoint(cm, false, debug, loader, threads, ctxSize, f16))
app.Get("/v1/models", listModels(loader, cm))
app.Get("/models", listModels(loader, cm))
return app
}

121
api/api_test.go Normal file
View File

@@ -0,0 +1,121 @@
package api_test
import (
"context"
"os"
. "github.com/go-skynet/LocalAI/api"
"github.com/go-skynet/LocalAI/pkg/model"
"github.com/gofiber/fiber/v2"
. "github.com/onsi/ginkgo/v2"
. "github.com/onsi/gomega"
"github.com/sashabaranov/go-openai"
)
var _ = Describe("API test", func() {
var app *fiber.App
var modelLoader *model.ModelLoader
var client *openai.Client
Context("API query", func() {
BeforeEach(func() {
modelLoader = model.NewModelLoader(os.Getenv("MODELS_PATH"))
app = App("", modelLoader, 1, 512, false, true, true)
go app.Listen("127.0.0.1:9090")
defaultConfig := openai.DefaultConfig("")
defaultConfig.BaseURL = "http://127.0.0.1:9090/v1"
// Wait for API to be ready
client = openai.NewClientWithConfig(defaultConfig)
Eventually(func() error {
_, err := client.ListModels(context.TODO())
return err
}, "2m").ShouldNot(HaveOccurred())
})
AfterEach(func() {
app.Shutdown()
})
It("returns the models list", func() {
models, err := client.ListModels(context.TODO())
Expect(err).ToNot(HaveOccurred())
Expect(len(models.Models)).To(Equal(3))
Expect(models.Models[0].ID).To(Equal("testmodel"))
})
It("can generate completions", func() {
resp, err := client.CreateCompletion(context.TODO(), openai.CompletionRequest{Model: "testmodel", Prompt: "abcdedfghikl"})
Expect(err).ToNot(HaveOccurred())
Expect(len(resp.Choices)).To(Equal(1))
Expect(resp.Choices[0].Text).ToNot(BeEmpty())
})
It("can generate chat completions ", func() {
resp, err := client.CreateChatCompletion(context.TODO(), openai.ChatCompletionRequest{Model: "testmodel", Messages: []openai.ChatCompletionMessage{openai.ChatCompletionMessage{Role: "user", Content: "abcdedfghikl"}}})
Expect(err).ToNot(HaveOccurred())
Expect(len(resp.Choices)).To(Equal(1))
Expect(resp.Choices[0].Message.Content).ToNot(BeEmpty())
})
It("can generate completions from model configs", func() {
resp, err := client.CreateCompletion(context.TODO(), openai.CompletionRequest{Model: "gpt4all", Prompt: "abcdedfghikl"})
Expect(err).ToNot(HaveOccurred())
Expect(len(resp.Choices)).To(Equal(1))
Expect(resp.Choices[0].Text).ToNot(BeEmpty())
})
It("can generate chat completions from model configs", func() {
resp, err := client.CreateChatCompletion(context.TODO(), openai.ChatCompletionRequest{Model: "gpt4all-2", Messages: []openai.ChatCompletionMessage{openai.ChatCompletionMessage{Role: "user", Content: "abcdedfghikl"}}})
Expect(err).ToNot(HaveOccurred())
Expect(len(resp.Choices)).To(Equal(1))
Expect(resp.Choices[0].Message.Content).ToNot(BeEmpty())
})
It("returns errors", func() {
_, err := client.CreateCompletion(context.TODO(), openai.CompletionRequest{Model: "foomodel", Prompt: "abcdedfghikl"})
Expect(err).To(HaveOccurred())
Expect(err.Error()).To(ContainSubstring("error, status code: 500, message: llama: model does not exist"))
})
})
Context("Config file", func() {
BeforeEach(func() {
modelLoader = model.NewModelLoader(os.Getenv("MODELS_PATH"))
app = App(os.Getenv("CONFIG_FILE"), modelLoader, 1, 512, false, true, true)
go app.Listen("127.0.0.1:9090")
defaultConfig := openai.DefaultConfig("")
defaultConfig.BaseURL = "http://127.0.0.1:9090/v1"
// Wait for API to be ready
client = openai.NewClientWithConfig(defaultConfig)
Eventually(func() error {
_, err := client.ListModels(context.TODO())
return err
}, "2m").ShouldNot(HaveOccurred())
})
AfterEach(func() {
app.Shutdown()
})
It("can generate chat completions from config file", func() {
models, err := client.ListModels(context.TODO())
Expect(err).ToNot(HaveOccurred())
Expect(len(models.Models)).To(Equal(5))
Expect(models.Models[0].ID).To(Equal("testmodel"))
})
It("can generate chat completions from config file", func() {
resp, err := client.CreateChatCompletion(context.TODO(), openai.ChatCompletionRequest{Model: "list1", Messages: []openai.ChatCompletionMessage{openai.ChatCompletionMessage{Role: "user", Content: "abcdedfghikl"}}})
Expect(err).ToNot(HaveOccurred())
Expect(len(resp.Choices)).To(Equal(1))
Expect(resp.Choices[0].Message.Content).ToNot(BeEmpty())
})
It("can generate chat completions from config file", func() {
resp, err := client.CreateChatCompletion(context.TODO(), openai.ChatCompletionRequest{Model: "list2", Messages: []openai.ChatCompletionMessage{openai.ChatCompletionMessage{Role: "user", Content: "abcdedfghikl"}}})
Expect(err).ToNot(HaveOccurred())
Expect(len(resp.Choices)).To(Equal(1))
Expect(resp.Choices[0].Message.Content).ToNot(BeEmpty())
})
})
})

View File

@@ -1,4 +1,4 @@
package http_test
package api_test
import (
"testing"

100
api/config.go Normal file
View File

@@ -0,0 +1,100 @@
package api
import (
"fmt"
"io/ioutil"
"os"
"path/filepath"
"strings"
"gopkg.in/yaml.v3"
)
type Config struct {
OpenAIRequest `yaml:"parameters"`
Name string `yaml:"name"`
StopWords []string `yaml:"stopwords"`
Cutstrings []string `yaml:"cutstrings"`
TrimSpace []string `yaml:"trimspace"`
ContextSize int `yaml:"context_size"`
F16 bool `yaml:"f16"`
Threads int `yaml:"threads"`
Debug bool `yaml:"debug"`
Roles map[string]string `yaml:"roles"`
TemplateConfig TemplateConfig `yaml:"template"`
}
type TemplateConfig struct {
Completion string `yaml:"completion"`
Chat string `yaml:"chat"`
}
type ConfigMerger map[string]Config
func ReadConfigFile(file string) ([]*Config, error) {
c := &[]*Config{}
f, err := os.ReadFile(file)
if err != nil {
return nil, fmt.Errorf("cannot read config file: %w", err)
}
if err := yaml.Unmarshal(f, c); err != nil {
return nil, fmt.Errorf("cannot unmarshal config file: %w", err)
}
return *c, nil
}
func ReadConfig(file string) (*Config, error) {
c := &Config{}
f, err := os.ReadFile(file)
if err != nil {
return nil, fmt.Errorf("cannot read config file: %w", err)
}
if err := yaml.Unmarshal(f, c); err != nil {
return nil, fmt.Errorf("cannot unmarshal config file: %w", err)
}
return c, nil
}
func (cm ConfigMerger) LoadConfigFile(file string) error {
c, err := ReadConfigFile(file)
if err != nil {
return fmt.Errorf("cannot load config file: %w", err)
}
for _, cc := range c {
cm[cc.Name] = *cc
}
return nil
}
func (cm ConfigMerger) LoadConfig(file string) error {
c, err := ReadConfig(file)
if err != nil {
return fmt.Errorf("cannot read config file: %w", err)
}
cm[c.Name] = *c
return nil
}
func (cm ConfigMerger) LoadConfigs(path string) error {
files, err := ioutil.ReadDir(path)
if err != nil {
return err
}
for _, file := range files {
// Skip templates, YAML and .keep files
if !strings.Contains(file.Name(), ".yaml") {
continue
}
c, err := ReadConfig(filepath.Join(path, file.Name()))
if err == nil {
cm[c.Name] = *c
}
}
return nil
}

396
api/openai.go Normal file
View File

@@ -0,0 +1,396 @@
package api
import (
"bufio"
"encoding/json"
"fmt"
"os"
"path/filepath"
"regexp"
"strings"
"sync"
model "github.com/go-skynet/LocalAI/pkg/model"
"github.com/gofiber/fiber/v2"
"github.com/rs/zerolog/log"
"github.com/valyala/fasthttp"
)
// APIError provides error information returned by the OpenAI API.
type APIError struct {
Code any `json:"code,omitempty"`
Message string `json:"message"`
Param *string `json:"param,omitempty"`
Type string `json:"type"`
}
type ErrorResponse struct {
Error *APIError `json:"error,omitempty"`
}
type 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"`
}
type Choice struct {
Index int `json:"index,omitempty"`
FinishReason string `json:"finish_reason,omitempty"`
Message *Message `json:"message,omitempty"`
Delta *Message `json:"delta,omitempty"`
Text string `json:"text,omitempty"`
}
type Message struct {
Role string `json:"role,omitempty" yaml:"role"`
Content string `json:"content,omitempty" yaml:"content"`
}
type OpenAIModel struct {
ID string `json:"id"`
Object string `json:"object"`
}
type OpenAIRequest struct {
Model string `json:"model" yaml:"model"`
// Prompt is read only by completion API calls
Prompt string `json:"prompt" yaml:"prompt"`
Stop string `json:"stop" yaml:"stop"`
// Messages is read only by chat/completion API calls
Messages []Message `json:"messages" yaml:"messages"`
Stream bool `json:"stream"`
Echo bool `json:"echo"`
// Common options between all the API calls
TopP float64 `json:"top_p" yaml:"top_p"`
TopK int `json:"top_k" yaml:"top_k"`
Temperature float64 `json:"temperature" yaml:"temperature"`
Maxtokens int `json:"max_tokens" yaml:"max_tokens"`
N int `json:"n"`
// Custom parameters - not present in the OpenAI API
Batch int `json:"batch" yaml:"batch"`
F16 bool `json:"f16" yaml:"f16"`
IgnoreEOS bool `json:"ignore_eos" yaml:"ignore_eos"`
RepeatPenalty float64 `json:"repeat_penalty" yaml:"repeat_penalty"`
Keep int `json:"n_keep" yaml:"n_keep"`
Seed int `json:"seed" yaml:"seed"`
}
func defaultRequest(modelFile string) OpenAIRequest {
return OpenAIRequest{
TopP: 0.7,
TopK: 80,
Maxtokens: 512,
Temperature: 0.9,
Model: modelFile,
}
}
func updateConfig(config *Config, input *OpenAIRequest) {
if input.Echo {
config.Echo = input.Echo
}
if input.TopK != 0 {
config.TopK = input.TopK
}
if input.TopP != 0 {
config.TopP = input.TopP
}
if input.Temperature != 0 {
config.Temperature = input.Temperature
}
if input.Maxtokens != 0 {
config.Maxtokens = input.Maxtokens
}
if input.Stop != "" {
config.StopWords = append(config.StopWords, input.Stop)
}
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
}
}
var cutstrings map[string]*regexp.Regexp = make(map[string]*regexp.Regexp)
var mu sync.Mutex = sync.Mutex{}
// https://platform.openai.com/docs/api-reference/completions
func openAIEndpoint(cm ConfigMerger, chat, debug bool, loader *model.ModelLoader, threads, ctx int, f16 bool) func(c *fiber.Ctx) error {
return func(c *fiber.Ctx) error {
input := new(OpenAIRequest)
// Get input data from the request body
if err := c.BodyParser(input); err != nil {
return err
}
if input.Stream {
log.Debug().Msgf("Stream request received")
//c.Response().Header.SetContentType(fiber.MIMETextHTMLCharsetUTF8)
c.Set("Content-Type", "text/event-stream; charset=utf-8")
c.Set("Cache-Control", "no-cache")
c.Set("Connection", "keep-alive")
c.Set("Transfer-Encoding", "chunked")
}
modelFile := input.Model
received, _ := json.Marshal(input)
log.Debug().Msgf("Request received: %s", string(received))
// Set model from bearer token, if available
bearer := strings.TrimLeft(c.Get("authorization"), "Bearer ")
bearerExists := bearer != "" && loader.ExistsInModelPath(bearer)
// If no model was specified, take the first available
if modelFile == "" && !bearerExists {
models, _ := loader.ListModels()
if len(models) > 0 {
modelFile = models[0]
log.Debug().Msgf("No model specified, using: %s", modelFile)
} else {
log.Debug().Msgf("No model specified, returning error")
return fmt.Errorf("no model specified")
}
}
// If a model is found in bearer token takes precedence
if bearerExists {
log.Debug().Msgf("Using model from bearer token: %s", bearer)
modelFile = bearer
}
// Load a config file if present after the model name
modelConfig := filepath.Join(loader.ModelPath, modelFile+".yaml")
if _, err := os.Stat(modelConfig); err == nil {
if err := cm.LoadConfig(modelConfig); err != nil {
return fmt.Errorf("failed loading model config (%s) %s", modelConfig, err.Error())
}
}
var config *Config
cfg, exists := cm[modelFile]
if !exists {
config = &Config{
OpenAIRequest: defaultRequest(modelFile),
}
} else {
config = &cfg
}
// Set the parameters for the language model prediction
updateConfig(config, input)
if threads != 0 {
config.Threads = threads
}
if ctx != 0 {
config.ContextSize = ctx
}
if f16 {
config.F16 = true
}
if debug {
config.Debug = true
}
log.Debug().Msgf("Parameter Config: %+v", config)
predInput := input.Prompt
if chat {
mess := []string{}
for _, i := range input.Messages {
r := config.Roles[i.Role]
if r == "" {
r = i.Role
}
content := fmt.Sprint(r, " ", i.Content)
mess = append(mess, content)
}
predInput = strings.Join(mess, "\n")
}
templateFile := config.Model
if config.TemplateConfig.Chat != "" && chat {
templateFile = config.TemplateConfig.Chat
}
if config.TemplateConfig.Completion != "" && !chat {
templateFile = config.TemplateConfig.Completion
}
// A model can have a "file.bin.tmpl" file associated with a prompt template prefix
templatedInput, err := loader.TemplatePrefix(templateFile, struct {
Input string
}{Input: predInput})
if err == nil {
predInput = templatedInput
log.Debug().Msgf("Template found, input modified to: %s", predInput)
}
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)
if err != nil {
return err
}
finetunePrediction := func(prediction string) string {
if config.Echo {
prediction = predInput + 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
}
for i := 0; i < n; i++ {
prediction, err := predFunc()
if err != nil {
return err
}
prediction = finetunePrediction(prediction)
if chat {
if input.Stream {
result = append(result, Choice{Delta: &Message{Role: "assistant", Content: prediction}})
} else {
result = append(result, Choice{Message: &Message{Role: "assistant", Content: prediction}})
}
} else {
result = append(result, Choice{Text: prediction})
}
}
resp := &OpenAIResponse{
Model: input.Model, // we have to return what the user sent here, due to OpenAI spec.
Choices: result,
}
if input.Stream && chat {
resp.Object = "chat.completion.chunk"
} else if chat {
resp.Object = "chat.completion"
} else {
resp.Object = "text_completion"
}
jsonResult, _ := json.Marshal(resp)
log.Debug().Msgf("Response: %s", jsonResult)
if input.Stream {
log.Debug().Msgf("Handling stream request")
c.Context().SetBodyStreamWriter(fasthttp.StreamWriter(func(w *bufio.Writer) {
fmt.Fprintf(w, "event: data\n")
w.Flush()
fmt.Fprintf(w, "data: %s\n\n", jsonResult)
w.Flush()
fmt.Fprintf(w, "event: data\n")
w.Flush()
resp := &OpenAIResponse{
Model: input.Model, // we have to return what the user sent here, due to OpenAI spec.
Choices: []Choice{Choice{FinishReason: "stop"}},
}
respData, _ := json.Marshal(resp)
fmt.Fprintf(w, "data: %s\n\n", respData)
w.Flush()
// fmt.Fprintf(w, "data: [DONE]\n\n")
// w.Flush()
}))
return nil
} else {
// Return the prediction in the response body
return c.JSON(resp)
}
}
}
func listModels(loader *model.ModelLoader, cm ConfigMerger) func(ctx *fiber.Ctx) error {
return func(c *fiber.Ctx) error {
models, err := loader.ListModels()
if err != nil {
return err
}
var mm map[string]interface{} = map[string]interface{}{}
dataModels := []OpenAIModel{}
for _, m := range models {
mm[m] = nil
dataModels = append(dataModels, OpenAIModel{ID: m, Object: "model"})
}
for k := range cm {
if _, exists := mm[k]; !exists {
dataModels = append(dataModels, OpenAIModel{ID: k, Object: "model"})
}
}
return c.JSON(struct {
Object string `json:"object"`
Data []OpenAIModel `json:"data"`
}{
Object: "list",
Data: dataModels,
})
}
}

188
api/prediction.go Normal file
View File

@@ -0,0 +1,188 @@
package api
import (
"fmt"
"sync"
model "github.com/go-skynet/LocalAI/pkg/model"
gpt2 "github.com/go-skynet/go-gpt2.cpp"
gptj "github.com/go-skynet/go-gpt4all-j.cpp"
llama "github.com/go-skynet/go-llama.cpp"
)
// mutex still needed, see: https://github.com/ggerganov/llama.cpp/discussions/784
var mutexMap sync.Mutex
var mutexes map[string]*sync.Mutex = make(map[string]*sync.Mutex)
func ModelInference(s string, loader *model.ModelLoader, c Config) (func() (string, error), error) {
var model *llama.LLama
var gptModel *gptj.GPTJ
var gpt2Model *gpt2.GPT2
var stableLMModel *gpt2.StableLM
modelFile := c.Model
// Try to load the model
var llamaerr, gpt2err, gptjerr, stableerr error
llamaOpts := []llama.ModelOption{}
if c.ContextSize != 0 {
llamaOpts = append(llamaOpts, llama.SetContext(c.ContextSize))
}
if c.F16 {
llamaOpts = append(llamaOpts, llama.EnableF16Memory)
}
// TODO: this is ugly, better identifying the model somehow! however, it is a good stab for a first implementation..
model, llamaerr = loader.LoadLLaMAModel(modelFile, llamaOpts...)
if llamaerr != nil {
gptModel, gptjerr = loader.LoadGPTJModel(modelFile)
if gptjerr != nil {
gpt2Model, gpt2err = loader.LoadGPT2Model(modelFile)
if gpt2err != nil {
stableLMModel, stableerr = loader.LoadStableLMModel(modelFile)
if stableerr != nil {
return nil, fmt.Errorf("llama: %s gpt: %s gpt2: %s stableLM: %s", llamaerr.Error(), gptjerr.Error(), gpt2err.Error(), stableerr.Error()) // llama failed first, so we want to catch both errors
}
}
}
}
var fn func() (string, error)
switch {
case stableLMModel != nil:
fn = func() (string, error) {
// Generate the prediction using the language model
predictOptions := []gpt2.PredictOption{
gpt2.SetTemperature(c.Temperature),
gpt2.SetTopP(c.TopP),
gpt2.SetTopK(c.TopK),
gpt2.SetTokens(c.Maxtokens),
gpt2.SetThreads(c.Threads),
}
if c.Batch != 0 {
predictOptions = append(predictOptions, gpt2.SetBatch(c.Batch))
}
if c.Seed != 0 {
predictOptions = append(predictOptions, gpt2.SetSeed(c.Seed))
}
return stableLMModel.Predict(
s,
predictOptions...,
)
}
case gpt2Model != nil:
fn = func() (string, error) {
// Generate the prediction using the language model
predictOptions := []gpt2.PredictOption{
gpt2.SetTemperature(c.Temperature),
gpt2.SetTopP(c.TopP),
gpt2.SetTopK(c.TopK),
gpt2.SetTokens(c.Maxtokens),
gpt2.SetThreads(c.Threads),
}
if c.Batch != 0 {
predictOptions = append(predictOptions, gpt2.SetBatch(c.Batch))
}
if c.Seed != 0 {
predictOptions = append(predictOptions, gpt2.SetSeed(c.Seed))
}
return gpt2Model.Predict(
s,
predictOptions...,
)
}
case gptModel != nil:
fn = func() (string, error) {
// Generate the prediction using the language model
predictOptions := []gptj.PredictOption{
gptj.SetTemperature(c.Temperature),
gptj.SetTopP(c.TopP),
gptj.SetTopK(c.TopK),
gptj.SetTokens(c.Maxtokens),
gptj.SetThreads(c.Threads),
}
if c.Batch != 0 {
predictOptions = append(predictOptions, gptj.SetBatch(c.Batch))
}
if c.Seed != 0 {
predictOptions = append(predictOptions, gptj.SetSeed(c.Seed))
}
return gptModel.Predict(
s,
predictOptions...,
)
}
case model != nil:
fn = func() (string, error) {
// Generate the prediction using the language model
predictOptions := []llama.PredictOption{
llama.SetTemperature(c.Temperature),
llama.SetTopP(c.TopP),
llama.SetTopK(c.TopK),
llama.SetTokens(c.Maxtokens),
llama.SetThreads(c.Threads),
}
if c.Debug {
predictOptions = append(predictOptions, llama.Debug)
}
predictOptions = append(predictOptions, llama.SetStopWords(c.StopWords...))
if c.RepeatPenalty != 0 {
predictOptions = append(predictOptions, llama.SetPenalty(c.RepeatPenalty))
}
if c.Keep != 0 {
predictOptions = append(predictOptions, llama.SetNKeep(c.Keep))
}
if c.Batch != 0 {
predictOptions = append(predictOptions, llama.SetBatch(c.Batch))
}
if c.F16 {
predictOptions = append(predictOptions, llama.EnableF16KV)
}
if c.IgnoreEOS {
predictOptions = append(predictOptions, llama.IgnoreEOS)
}
if c.Seed != 0 {
predictOptions = append(predictOptions, llama.SetSeed(c.Seed))
}
return model.Predict(
s,
predictOptions...,
)
}
}
return func() (string, error) {
// This is still needed, see: https://github.com/ggerganov/llama.cpp/discussions/784
mutexMap.Lock()
l, ok := mutexes[modelFile]
if !ok {
m := &sync.Mutex{}
mutexes[modelFile] = m
l = m
}
mutexMap.Unlock()
l.Lock()
defer l.Unlock()
return fn()
}, nil
}

View File

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

View File

@@ -1,297 +0,0 @@
syntax = "proto3";
option go_package = "github.com/go-skynet/LocalAI/pkg/grpc/proto";
option java_multiple_files = true;
option java_package = "io.skynet.localai.backend";
option java_outer_classname = "LocalAIBackend";
package backend;
service Backend {
rpc Health(HealthMessage) returns (Reply) {}
rpc Predict(PredictOptions) returns (Reply) {}
rpc LoadModel(ModelOptions) returns (Result) {}
rpc PredictStream(PredictOptions) returns (stream Reply) {}
rpc Embedding(PredictOptions) returns (EmbeddingResult) {}
rpc GenerateImage(GenerateImageRequest) returns (Result) {}
rpc AudioTranscription(TranscriptRequest) returns (TranscriptResult) {}
rpc TTS(TTSRequest) returns (Result) {}
rpc TokenizeString(PredictOptions) returns (TokenizationResponse) {}
rpc Status(HealthMessage) returns (StatusResponse) {}
rpc StoresSet(StoresSetOptions) returns (Result) {}
rpc StoresDelete(StoresDeleteOptions) returns (Result) {}
rpc StoresGet(StoresGetOptions) returns (StoresGetResult) {}
rpc StoresFind(StoresFindOptions) returns (StoresFindResult) {}
rpc Rerank(RerankRequest) returns (RerankResult) {}
}
message RerankRequest {
string query = 1;
repeated string documents = 2;
int32 top_n = 3;
}
message RerankResult {
Usage usage = 1;
repeated DocumentResult results = 2;
}
message Usage {
int32 total_tokens = 1;
int32 prompt_tokens = 2;
}
message DocumentResult {
int32 index = 1;
string text = 2;
float relevance_score = 3;
}
message StoresKey {
repeated float Floats = 1;
}
message StoresValue {
bytes Bytes = 1;
}
message StoresSetOptions {
repeated StoresKey Keys = 1;
repeated StoresValue Values = 2;
}
message StoresDeleteOptions {
repeated StoresKey Keys = 1;
}
message StoresGetOptions {
repeated StoresKey Keys = 1;
}
message StoresGetResult {
repeated StoresKey Keys = 1;
repeated StoresValue Values = 2;
}
message StoresFindOptions {
StoresKey Key = 1;
int32 TopK = 2;
}
message StoresFindResult {
repeated StoresKey Keys = 1;
repeated StoresValue Values = 2;
repeated float Similarities = 3;
}
message HealthMessage {}
// The request message containing the user's name.
message PredictOptions {
string Prompt = 1;
int32 Seed = 2;
int32 Threads = 3;
int32 Tokens = 4;
int32 TopK = 5;
int32 Repeat = 6;
int32 Batch = 7;
int32 NKeep = 8;
float Temperature = 9;
float Penalty = 10;
bool F16KV = 11;
bool DebugMode = 12;
repeated string StopPrompts = 13;
bool IgnoreEOS = 14;
float TailFreeSamplingZ = 15;
float TypicalP = 16;
float FrequencyPenalty = 17;
float PresencePenalty = 18;
int32 Mirostat = 19;
float MirostatETA = 20;
float MirostatTAU = 21;
bool PenalizeNL = 22;
string LogitBias = 23;
bool MLock = 25;
bool MMap = 26;
bool PromptCacheAll = 27;
bool PromptCacheRO = 28;
string Grammar = 29;
string MainGPU = 30;
string TensorSplit = 31;
float TopP = 32;
string PromptCachePath = 33;
bool Debug = 34;
repeated int32 EmbeddingTokens = 35;
string Embeddings = 36;
float RopeFreqBase = 37;
float RopeFreqScale = 38;
float NegativePromptScale = 39;
string NegativePrompt = 40;
int32 NDraft = 41;
repeated string Images = 42;
bool UseTokenizerTemplate = 43;
repeated Message Messages = 44;
}
// The response message containing the result
message Reply {
bytes message = 1;
int32 tokens = 2;
int32 prompt_tokens = 3;
}
message ModelOptions {
string Model = 1;
int32 ContextSize = 2;
int32 Seed = 3;
int32 NBatch = 4;
bool F16Memory = 5;
bool MLock = 6;
bool MMap = 7;
bool VocabOnly = 8;
bool LowVRAM = 9;
bool Embeddings = 10;
bool NUMA = 11;
int32 NGPULayers = 12;
string MainGPU = 13;
string TensorSplit = 14;
int32 Threads = 15;
string LibrarySearchPath = 16;
float RopeFreqBase = 17;
float RopeFreqScale = 18;
float RMSNormEps = 19;
int32 NGQA = 20;
string ModelFile = 21;
// AutoGPTQ
string Device = 22;
bool UseTriton = 23;
string ModelBaseName = 24;
bool UseFastTokenizer = 25;
// Diffusers
string PipelineType = 26;
string SchedulerType = 27;
bool CUDA = 28;
float CFGScale = 29;
bool IMG2IMG = 30;
string CLIPModel = 31;
string CLIPSubfolder = 32;
int32 CLIPSkip = 33;
string ControlNet = 48;
string Tokenizer = 34;
// LLM (llama.cpp)
string LoraBase = 35;
string LoraAdapter = 36;
float LoraScale = 42;
bool NoMulMatQ = 37;
string DraftModel = 39;
string AudioPath = 38;
// vllm
string Quantization = 40;
float GPUMemoryUtilization = 50;
bool TrustRemoteCode = 51;
bool EnforceEager = 52;
int32 SwapSpace = 53;
int32 MaxModelLen = 54;
int32 TensorParallelSize = 55;
string MMProj = 41;
string RopeScaling = 43;
float YarnExtFactor = 44;
float YarnAttnFactor = 45;
float YarnBetaFast = 46;
float YarnBetaSlow = 47;
string Type = 49;
bool FlashAttention = 56;
bool NoKVOffload = 57;
}
message Result {
string message = 1;
bool success = 2;
}
message EmbeddingResult {
repeated float embeddings = 1;
}
message TranscriptRequest {
string dst = 2;
string language = 3;
uint32 threads = 4;
bool translate = 5;
}
message TranscriptResult {
repeated TranscriptSegment segments = 1;
string text = 2;
}
message TranscriptSegment {
int32 id = 1;
int64 start = 2;
int64 end = 3;
string text = 4;
repeated int32 tokens = 5;
}
message GenerateImageRequest {
int32 height = 1;
int32 width = 2;
int32 mode = 3;
int32 step = 4;
int32 seed = 5;
string positive_prompt = 6;
string negative_prompt = 7;
string dst = 8;
string src = 9;
// Diffusers
string EnableParameters = 10;
int32 CLIPSkip = 11;
}
message TTSRequest {
string text = 1;
string model = 2;
string dst = 3;
string voice = 4;
optional string language = 5;
}
message TokenizationResponse {
int32 length = 1;
repeated int32 tokens = 2;
}
message MemoryUsageData {
uint64 total = 1;
map<string, uint64> breakdown = 2;
}
message StatusResponse {
enum State {
UNINITIALIZED = 0;
BUSY = 1;
READY = 2;
ERROR = -1;
}
State state = 1;
MemoryUsageData memory = 2;
}
message Message {
string role = 1;
string content = 2;
}

View File

@@ -1,3 +0,0 @@
installed_packages/
grpc_build/
grpc_repo/

View File

@@ -1,70 +0,0 @@
# Basic platform detection
HOST_SYSTEM = $(shell uname | cut -f 1 -d_)
SYSTEM ?= $(HOST_SYSTEM)
TAG_LIB_GRPC?=v1.59.0
GIT_REPO_LIB_GRPC?=https://github.com/grpc/grpc.git
GIT_CLONE_DEPTH?=1
INSTALLED_PACKAGES=installed_packages
GRPC_REPO=grpc_repo
GRPC_BUILD=grpc_build
export CMAKE_ARGS?=
CMAKE_ARGS+=-DCMAKE_BUILD_TYPE=Release
CMAKE_ARGS+=-DgRPC_INSTALL=ON
CMAKE_ARGS+=-DEXECUTABLE_OUTPUT_PATH=../$(INSTALLED_PACKAGES)/grpc/bin
CMAKE_ARGS+=-DLIBRARY_OUTPUT_PATH=../$(INSTALLED_PACKAGES)/grpc/lib
CMAKE_ARGS+=-DgRPC_BUILD_TESTS=OFF
CMAKE_ARGS+=-DgRPC_BUILD_CSHARP_EXT=OFF
CMAKE_ARGS+=-DgRPC_BUILD_GRPC_CPP_PLUGIN=ON
CMAKE_ARGS+=-DgRPC_BUILD_GRPC_CSHARP_PLUGIN=OFF
CMAKE_ARGS+=-DgRPC_BUILD_GRPC_NODE_PLUGIN=OFF
CMAKE_ARGS+=-DgRPC_BUILD_GRPC_OBJECTIVE_C_PLUGIN=OFF
CMAKE_ARGS+=-DgRPC_BUILD_GRPC_PHP_PLUGIN=OFF
CMAKE_ARGS+=-DgRPC_BUILD_GRPC_PYTHON_PLUGIN=ON
CMAKE_ARGS+=-DgRPC_BUILD_GRPC_RUBY_PLUGIN=OFF
CMAKE_ARGS+=-Dprotobuf_WITH_ZLIB=ON
CMAKE_ARGS+=-DRE2_BUILD_TESTING=OFF
CMAKE_ARGS+=-DCMAKE_INSTALL_PREFIX=../$(INSTALLED_PACKAGES)
# windows need to set OPENSSL_NO_ASM. Results in slower crypto performance but doesn't build otherwise.
# May be resolvable, but for now its set. More info: https://stackoverflow.com/a/75240504/480673
ifeq ($(SYSTEM),MSYS)
CMAKE_ARGS+=-DOPENSSL_NO_ASM=ON
endif
ifeq ($(SYSTEM),MINGW64)
CMAKE_ARGS+=-DOPENSSL_NO_ASM=ON
endif
ifeq ($(SYSTEM),MINGW32)
CMAKE_ARGS+=-DOPENSSL_NO_ASM=ON
endif
ifeq ($(SYSTEM),CYGWIN)
CMAKE_ARGS+=-DOPENSSL_NO_ASM=ON
endif
$(INSTALLED_PACKAGES): grpc_build
$(GRPC_REPO):
mkdir -p $(GRPC_REPO)/grpc
cd $(GRPC_REPO)/grpc && \
git init && \
git remote add origin $(GIT_REPO_LIB_GRPC) && \
git fetch origin && \
git checkout $(TAG_LIB_GRPC) && \
git submodule update --init --recursive --depth 1 --single-branch
$(GRPC_BUILD): $(GRPC_REPO)
mkdir -p $(GRPC_BUILD)
cd $(GRPC_BUILD) && cmake $(CMAKE_ARGS) ../$(GRPC_REPO)/grpc && cmake --build . && cmake --build . --target install
build: $(INSTALLED_PACKAGES)
rebuild:
rm -rf grpc_build
$(MAKE) grpc_build
clean:
rm -rf grpc_build
rm -rf grpc_repo
rm -rf installed_packages

View File

@@ -1,86 +0,0 @@
## XXX: In some versions of CMake clip wasn't being built before llama.
## This is an hack for now, but it should be fixed in the future.
set(TARGET myclip)
add_library(${TARGET} clip.cpp clip.h llava.cpp llava.h)
install(TARGETS ${TARGET} LIBRARY)
target_include_directories(myclip PUBLIC .)
target_include_directories(myclip PUBLIC ../..)
target_include_directories(myclip PUBLIC ../../common)
target_link_libraries(${TARGET} PRIVATE common ggml llama ${CMAKE_THREAD_LIBS_INIT})
target_compile_features(${TARGET} PRIVATE cxx_std_11)
if (NOT MSVC)
target_compile_options(${TARGET} PRIVATE -Wno-cast-qual) # stb_image.h
endif()
# END CLIP hack
set(TARGET grpc-server)
set(CMAKE_CXX_STANDARD 17)
cmake_minimum_required(VERSION 3.15)
set(TARGET grpc-server)
set(_PROTOBUF_LIBPROTOBUF libprotobuf)
set(_REFLECTION grpc++_reflection)
if (${CMAKE_SYSTEM_NAME} MATCHES "Darwin")
# Set correct Homebrew install folder for Apple Silicon and Intel Macs
if (CMAKE_HOST_SYSTEM_PROCESSOR MATCHES "arm64")
set(HOMEBREW_DEFAULT_PREFIX "/opt/homebrew")
else()
set(HOMEBREW_DEFAULT_PREFIX "/usr/local")
endif()
link_directories("${HOMEBREW_DEFAULT_PREFIX}/lib")
include_directories("${HOMEBREW_DEFAULT_PREFIX}/include")
endif()
find_package(absl CONFIG REQUIRED)
find_package(Protobuf CONFIG REQUIRED)
find_package(gRPC CONFIG REQUIRED)
find_program(_PROTOBUF_PROTOC protoc)
set(_GRPC_GRPCPP grpc++)
find_program(_GRPC_CPP_PLUGIN_EXECUTABLE grpc_cpp_plugin)
include_directories(${CMAKE_CURRENT_BINARY_DIR})
include_directories(${Protobuf_INCLUDE_DIRS})
message(STATUS "Using protobuf version ${Protobuf_VERSION} | Protobuf_INCLUDE_DIRS: ${Protobuf_INCLUDE_DIRS} | CMAKE_CURRENT_BINARY_DIR: ${CMAKE_CURRENT_BINARY_DIR}")
# Proto file
get_filename_component(hw_proto "../../../../../../backend/backend.proto" ABSOLUTE)
get_filename_component(hw_proto_path "${hw_proto}" PATH)
# Generated sources
set(hw_proto_srcs "${CMAKE_CURRENT_BINARY_DIR}/backend.pb.cc")
set(hw_proto_hdrs "${CMAKE_CURRENT_BINARY_DIR}/backend.pb.h")
set(hw_grpc_srcs "${CMAKE_CURRENT_BINARY_DIR}/backend.grpc.pb.cc")
set(hw_grpc_hdrs "${CMAKE_CURRENT_BINARY_DIR}/backend.grpc.pb.h")
add_custom_command(
OUTPUT "${hw_proto_srcs}" "${hw_proto_hdrs}" "${hw_grpc_srcs}" "${hw_grpc_hdrs}"
COMMAND ${_PROTOBUF_PROTOC}
ARGS --grpc_out "${CMAKE_CURRENT_BINARY_DIR}"
--cpp_out "${CMAKE_CURRENT_BINARY_DIR}"
-I "${hw_proto_path}"
--plugin=protoc-gen-grpc="${_GRPC_CPP_PLUGIN_EXECUTABLE}"
"${hw_proto}"
DEPENDS "${hw_proto}")
# hw_grpc_proto
add_library(hw_grpc_proto
${hw_grpc_srcs}
${hw_grpc_hdrs}
${hw_proto_srcs}
${hw_proto_hdrs} )
add_executable(${TARGET} grpc-server.cpp utils.hpp json.hpp)
target_link_libraries(${TARGET} PRIVATE common llama myclip ${CMAKE_THREAD_LIBS_INIT} absl::flags hw_grpc_proto
absl::flags_parse
gRPC::${_REFLECTION}
gRPC::${_GRPC_GRPCPP}
protobuf::${_PROTOBUF_LIBPROTOBUF})
target_compile_features(${TARGET} PRIVATE cxx_std_11)
if(TARGET BUILD_INFO)
add_dependencies(${TARGET} BUILD_INFO)
endif()

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