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3 Commits

Author SHA1 Message Date
Ettore Di Giacinto
495191a54a fix(llama.cpp): fix eos without cache 2024-03-18 12:14:16 +01:00
Ettore Di Giacinto
b790fca180 fix(whisper.cpp): Add stubs and -lcuda 2024-03-18 12:13:39 +01:00
Ettore Di Giacinto
0663f66205 deps(whisper.cpp): update, fix cublas build 2024-03-16 10:38:57 +01:00
703 changed files with 15650 additions and 62611 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
}

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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"
```

View File

@@ -1,24 +0,0 @@
{
"$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"
}

View File

@@ -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:

View File

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

View File

@@ -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

View File

@@ -1,17 +1,6 @@
.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
Dockerfile

View File

@@ -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

46
.env
View File

@@ -1,33 +1,33 @@
## Set number of threads.
## Note: prefer the number of physical cores. Overbooking the CPU degrades performance notably.
# LOCALAI_THREADS=14
# THREADS=14
## Specify a different bind address (defaults to ":8080")
# LOCALAI_ADDRESS=127.0.0.1:8080
# ADDRESS=127.0.0.1:8080
## Default models context size
# LOCALAI_CONTEXT_SIZE=512
# 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"}]
# GALLERIES=[{"name":"model-gallery", "url":"github:go-skynet/model-gallery/index.yaml"}]
## CORS settings
# LOCALAI_CORS=true
# LOCALAI_CORS_ALLOW_ORIGINS=*
# CORS=true
# CORS_ALLOW_ORIGINS=*
## Default path for models
#
# LOCALAI_MODELS_PATH=/models
# MODELS_PATH=/models
## Enable debug mode
# LOCALAI_LOG_LEVEL=debug
# DEBUG=true
## Disables COMPEL (Diffusers)
# COMPEL=0
## Enable/Disable single backend (useful if only one GPU is available)
# LOCALAI_SINGLE_ACTIVE_BACKEND=true
# 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.
@@ -46,13 +46,13 @@
# GO_TAGS=stablediffusion
## Path where to store generated images
# LOCALAI_IMAGE_PATH=/tmp/generated/images
# IMAGE_PATH=/tmp
## Specify a default upload limit in MB (whisper)
# LOCALAI_UPLOAD_LIMIT=15
# UPLOAD_LIMIT
## 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
# 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 ###
@@ -71,27 +71,19 @@
### 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
# PARALLEL_REQUESTS=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
# WATCHDOG_IDLE=true
#
# Enables watchdog to kill backends that are busy for too much time
# LOCALAI_WATCHDOG_BUSY=true
# WATCHDOG_BUSY=true
#
# Time in duration format (e.g. 1h30m) after which a backend is considered idle
# WATCHDOG_IDLE_TIMEOUT=5m
#
# Time in duration format (e.g. 1h30m) after which a backend is considered busy
# LOCALAI_WATCHDOG_BUSY_TIMEOUT=5m
# WATCHDOG_BUSY_TIMEOUT=5m

13
.github/bump_deps.sh vendored
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@@ -6,17 +6,4 @@ 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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@@ -2,6 +2,6 @@
set -xe
REPO=$1
LATEST_TAG=$(curl -s "https://api.github.com/repos/$REPO/releases/latest" | jq -r '.tag_name')
LATEST_TAG=$(curl -s "https://api.github.com/repos/$REPO/releases/latest" | jq -r '.name')
cat <<< $(jq ".version = \"$LATEST_TAG\"" docs/data/version.json) > docs/data/version.json

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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/*'

15
.github/release.yml vendored
View File

@@ -12,26 +12,13 @@ changelog:
- 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:
- "*"
- "*"

View File

@@ -9,6 +9,9 @@ jobs:
fail-fast: false
matrix:
include:
- repository: "go-skynet/go-llama.cpp"
variable: "GOLLAMA_VERSION"
branch: "master"
- repository: "ggerganov/llama.cpp"
variable: "CPPLLAMA_VERSION"
branch: "master"
@@ -27,6 +30,9 @@ jobs:
- repository: "go-skynet/bloomz.cpp"
variable: "BLOOMZ_VERSION"
branch: "main"
- repository: "nomic-ai/gpt4all"
variable: "GPT4ALL_VERSION"
branch: "main"
- repository: "mudler/go-ggllm.cpp"
variable: "GOGGLLM_VERSION"
branch: "master"
@@ -40,30 +46,17 @@ jobs:
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
uses: peter-evans/create-pull-request@v5
with:
token: ${{ secrets.UPDATE_BOT_TOKEN }}
push-to-fork: ci-forks/LocalAI
commit-message: ':arrow_up: Update ${{ matrix.repository }}'
title: 'chore: :arrow_up: Update ${{ matrix.repository }} to `${{ steps.bump.outputs.commit }}`'
title: ':arrow_up: Update ${{ matrix.repository }}'
branch: "update/${{ matrix.variable }}"
body: ${{ steps.bump.outputs.message }}
body: Bump of ${{ matrix.repository }} version
signoff: true

View File

@@ -17,12 +17,12 @@ jobs:
run: |
bash .github/bump_docs.sh ${{ matrix.repository }}
- name: Create Pull Request
uses: peter-evans/create-pull-request@v6
uses: peter-evans/create-pull-request@v5
with:
token: ${{ secrets.UPDATE_BOT_TOKEN }}
push-to-fork: ci-forks/LocalAI
commit-message: ':arrow_up: Update docs version ${{ matrix.repository }}'
title: 'docs: :arrow_up: update docs version ${{ matrix.repository }}'
title: ':arrow_up: Update docs version ${{ matrix.repository }}'
branch: "update/docs"
body: Bump of ${{ matrix.repository }} version inside docs
signoff: true

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

@@ -1,94 +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

@@ -22,8 +22,6 @@ jobs:
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 }}
@@ -32,22 +30,20 @@ jobs:
strategy:
# Pushing with all jobs in parallel
# eats the bandwidth of all the nodes
max-parallel: ${{ github.event_name != 'pull_request' && 4 || 8 }}
max-parallel: ${{ github.event_name != 'pull_request' && 2 || 4 }}
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: ''
platforms: 'linux/amd64'
tag-latest: 'false'
tag-suffix: '-ffmpeg'
ffmpeg: 'true'
image-type: 'extras'
runs-on: 'arc-runner-set'
base-image: "ubuntu:22.04"
- build-type: 'cublas'
cuda-major-version: "12"
cuda-minor-version: "0"
cuda-minor-version: "1"
platforms: 'linux/amd64'
tag-latest: 'false'
tag-suffix: '-cublas-cuda12-ffmpeg'
@@ -55,86 +51,66 @@ jobs:
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"
- build-type: 'hipblas'
platforms: 'linux/amd64'
tag-latest: 'false'
tag-suffix: '-hipblas'
ffmpeg: 'false'
image-type: 'extras'
base-image: "rocm/dev-ubuntu-22.04:6.0-complete"
runs-on: 'arc-runner-set'
- build-type: 'sycl_f16'
platforms: 'linux/amd64'
tag-latest: 'false'
base-image: "intel/oneapi-basekit:2024.0.1-devel-ubuntu22.04"
tag-suffix: 'sycl-f16-ffmpeg'
ffmpeg: 'true'
image-type: 'extras'
runs-on: 'arc-runner-set'
core-image-build:
uses: ./.github/workflows/image_build.yml
with:
tag-latest: ${{ matrix.tag-latest }}
tag-suffix: ${{ matrix.tag-suffix }}
ffmpeg: ${{ matrix.ffmpeg }}
image-type: ${{ matrix.image-type }}
build-type: ${{ matrix.build-type }}
cuda-major-version: ${{ matrix.cuda-major-version }}
cuda-minor-version: ${{ matrix.cuda-minor-version }}
platforms: ${{ matrix.platforms }}
runs-on: ${{ matrix.runs-on }}
base-image: ${{ matrix.base-image }}
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"
- build-type: 'sycl_f16'
platforms: 'linux/amd64'
tag-latest: 'false'
base-image: "intel/oneapi-basekit:2024.0.1-devel-ubuntu22.04"
tag-suffix: 'sycl-f16-ffmpeg-core'
ffmpeg: 'true'
image-type: 'core'
runs-on: 'arc-runner-set'
- build-type: 'cublas'
cuda-major-version: "12"
cuda-minor-version: "1"
platforms: 'linux/amd64'
tag-latest: 'false'
tag-suffix: '-cublas-cuda12-ffmpeg-core'
ffmpeg: 'true'
image-type: 'core'
runs-on: 'ubuntu-latest'
base-image: "ubuntu:22.04"

View File

@@ -26,11 +26,6 @@ jobs:
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 }}
@@ -39,7 +34,7 @@ jobs:
strategy:
# Pushing with all jobs in parallel
# eats the bandwidth of all the nodes
max-parallel: ${{ github.event_name != 'pull_request' && 6 || 10 }}
max-parallel: ${{ github.event_name != 'pull_request' && 2 || 4 }}
matrix:
include:
# Extra images
@@ -52,16 +47,14 @@ jobs:
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-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: "11"
cuda-minor-version: "7"
@@ -72,10 +65,9 @@ jobs:
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"
cuda-minor-version: "1"
platforms: 'linux/amd64'
tag-latest: 'false'
tag-suffix: '-cublas-cuda12'
@@ -83,35 +75,26 @@ jobs:
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-latest: 'false'
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"
cuda-minor-version: "1"
platforms: 'linux/amd64'
tag-latest: 'auto'
tag-latest: 'false'
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'
@@ -121,118 +104,88 @@ jobs:
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-latest: 'false'
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'
base-image: "rocm/dev-ubuntu-22.04:6.0-complete"
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"
base-image: "rocm/dev-ubuntu-22.04:6.0-complete"
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-latest: 'false'
base-image: "intel/oneapi-basekit:2024.0.1-devel-ubuntu22.04"
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-latest: 'false'
base-image: "intel/oneapi-basekit:2024.0.1-devel-ubuntu22.04"
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"
base-image: "intel/oneapi-basekit:2024.0.1-devel-ubuntu22.04"
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"
base-image: "intel/oneapi-basekit:2024.0.1-devel-ubuntu22.04"
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"
base-image: "intel/oneapi-basekit:2024.0.1-devel-ubuntu22.04"
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"
base-image: "intel/oneapi-basekit:2024.0.1-devel-ubuntu22.04"
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"
base-image: "rocm/dev-ubuntu-22.04:6.0-complete"
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"
base-image: "rocm/dev-ubuntu-22.04:6.0-complete"
runs-on: 'arc-runner-set'
makeflags: "--jobs=3 --output-sync=target"
core-image-build:
uses: ./.github/workflows/image_build.yml
with:
@@ -245,33 +198,23 @@ jobs:
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'
platforms: 'linux/amd64'
tag-latest: 'false'
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"
runs-on: 'ubuntu-latest'
- build-type: 'cublas'
cuda-major-version: "11"
cuda-minor-version: "7"
@@ -281,19 +224,17 @@ jobs:
ffmpeg: ''
image-type: 'core'
base-image: "ubuntu:22.04"
runs-on: 'arc-runner-set'
makeflags: "--jobs=4 --output-sync=target"
runs-on: 'ubuntu-latest'
- build-type: 'cublas'
cuda-major-version: "12"
cuda-minor-version: "0"
cuda-minor-version: "1"
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"
runs-on: 'ubuntu-latest'
- build-type: 'cublas'
cuda-major-version: "11"
cuda-minor-version: "7"
@@ -302,27 +243,15 @@ jobs:
tag-suffix: '-cublas-cuda11-ffmpeg-core'
ffmpeg: 'true'
image-type: 'core'
runs-on: 'arc-runner-set'
runs-on: 'ubuntu-latest'
base-image: "ubuntu:22.04"
makeflags: "--jobs=4 --output-sync=target"
- build-type: 'cublas'
cuda-major-version: "12"
cuda-minor-version: "0"
cuda-minor-version: "1"
platforms: 'linux/amd64'
tag-latest: 'false'
tag-suffix: '-cublas-cuda12-ffmpeg-core'
ffmpeg: 'true'
image-type: 'core'
runs-on: 'arc-runner-set'
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'
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"

View File

@@ -6,10 +6,6 @@ on:
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
@@ -19,11 +15,11 @@ on:
type: string
cuda-major-version:
description: 'CUDA major version'
default: "12"
default: "11"
type: string
cuda-minor-version:
description: 'CUDA minor version'
default: "4"
default: "7"
type: string
platforms:
description: 'Platforms'
@@ -33,14 +29,6 @@ on:
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: ''
@@ -58,16 +46,6 @@ 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
@@ -91,7 +69,6 @@ jobs:
&& sudo apt-get install -y git
- name: Checkout
uses: actions/checkout@v4
- name: Release space from worker
if: inputs.runs-on == 'ubuntu-latest'
run: |
@@ -133,10 +110,8 @@ jobs:
sudo rm -rf "/usr/local/share/boost" || true
sudo rm -rf "$AGENT_TOOLSDIRECTORY" || true
df -h
- name: Docker meta
id: meta
if: github.event_name != 'pull_request'
uses: docker/metadata-action@v5
with:
images: |
@@ -149,46 +124,6 @@ jobs:
flavor: |
latest=${{ 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
@@ -215,14 +150,9 @@ jobs:
password: ${{ secrets.quayPassword }}
- name: Build and push
uses: docker/build-push-action@v6
if: github.event_name != 'pull_request'
uses: docker/build-push-action@v5
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=${{ inputs.cuda-major-version }}
@@ -230,106 +160,12 @@ jobs:
FFMPEG=${{ 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

@@ -1,15 +1,6 @@
name: Build and Release
on:
push:
branches:
- master
tags:
- 'v*'
pull_request:
env:
GRPC_VERSION: v1.65.0
on: push
permissions:
contents: write
@@ -19,224 +10,85 @@ concurrency:
cancel-in-progress: true
jobs:
build-linux-arm:
build-linux:
strategy:
matrix:
include:
- build: 'avx2'
defines: ''
- build: 'avx'
defines: '-DLLAMA_AVX2=OFF'
- build: 'avx512'
defines: '-DLLAMA_AVX512=ON'
- build: 'cuda12'
defines: ''
- build: 'cuda11'
defines: ''
runs-on: ubuntu-latest
steps:
- name: Clone
uses: actions/checkout@v4
with:
submodules: true
- uses: actions/setup-go@v5
- uses: actions/setup-go@v4
with:
go-version: '1.21.x'
cache: false
go-version: '>=1.21.0'
- 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
sudo apt-get install build-essential ffmpeg
- name: Install CUDA Dependencies
if: ${{ matrix.build == 'cuda12' || matrix.build == 'cuda11' }}
run: |
if [ "${{ matrix.build }}" == "cuda12" ]; then
export CUDA_VERSION=12-3
else
export CUDA_VERSION=11-7
fi
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
uses: actions/cache@v3
with:
path: grpc
key: ${{ runner.os }}-grpc-${{ env.GRPC_VERSION }}
key: ${{ runner.os }}-grpc
- 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 \
git clone --recurse-submodules -b v1.58.0 --depth 1 --shallow-submodules https://github.com/grpc/grpc && \
cd grpc && mkdir -p cmake/build && cd cmake/build && cmake -DgRPC_INSTALL=ON \
-DgRPC_BUILD_TESTS=OFF \
../.. && sudo make --jobs 5 --output-sync=target
../.. && sudo make -j12
- 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
cd grpc && cd cmake/build && sudo make -j12 install
- name: Build
id: build
env:
CMAKE_ARGS: "${{ matrix.defines }}"
BUILD_ID: "${{ matrix.build }}"
run: |
go install google.golang.org/grpc/cmd/protoc-gen-go-grpc@1958fcbe2ca8bd93af633f11e97d44e567e945af
go install google.golang.org/protobuf/cmd/protoc-gen-go@v1.34.2
export PATH=$PATH:$GOPATH/bin
export PATH=/usr/local/cuda/bin:$PATH
export PATH=/opt/rocm/bin:$PATH
source /opt/intel/oneapi/setvars.sh
sudo cp /lib64/ld-linux-x86-64.so.2 ld.so
BACKEND_LIBS="./ld.so ./sources/go-piper/piper/build/fi/lib/libfmt.a ./sources/go-piper/piper-phonemize/pi/lib/libonnxruntime.so.1.14.1 ./sources/go-piper/piper-phonemize/pi/src/libespeak-ng/libespeak-ng.so /usr/lib/x86_64-linux-gnu/libdl.so.2 /usr/lib/x86_64-linux-gnu/librt.so.1 /usr/lib/x86_64-linux-gnu/libpthread.so.0 ./sources/go-piper/piper-phonemize/pi/lib/libpiper_phonemize.so.1 ./sources/go-piper/piper/build/si/lib/libspdlog.a ./sources/go-piper/espeak/ei/lib/libucd.so" \
make -j4 dist
- uses: actions/upload-artifact@v4
if [ "${{ matrix.build }}" == "cuda12" ] || [ "${{ matrix.build }}" == "cuda11" ]; then
export BUILD_TYPE=cublas
export PATH=/usr/local/cuda/bin:$PATH
make dist
else
STATIC=true make dist
fi
- uses: actions/upload-artifact@v3
with:
name: LocalAI-linux
name: ${{ matrix.build }}
path: release/
- name: Release
uses: softprops/action-gh-release@v2
uses: softprops/action-gh-release@v1
if: startsWith(github.ref, 'refs/tags/')
with:
files: |
release/*
- name: Setup tmate session if tests fail
if: ${{ failure() }}
uses: mxschmitt/action-tmate@v3.18
with:
detached: true
connect-timeout-seconds: 180
limit-access-to-actor: true
build-stablediffusion:
runs-on: ubuntu-latest
steps:
@@ -244,114 +96,66 @@ jobs:
uses: actions/checkout@v4
with:
submodules: true
- uses: actions/setup-go@v5
- uses: actions/setup-go@v4
with:
go-version: '1.21.x'
cache: false
go-version: '>=1.21.0'
- name: Dependencies
run: |
sudo apt-get update
sudo apt-get install -y --no-install-recommends libopencv-dev protobuf-compiler ccache upx-ucl
go install google.golang.org/grpc/cmd/protoc-gen-go-grpc@1958fcbe2ca8bd93af633f11e97d44e567e945af
go install google.golang.org/protobuf/cmd/protoc-gen-go@v1.34.2
sudo apt-get install -y --no-install-recommends libopencv-dev
sudo ln -s /usr/include/opencv4/opencv2 /usr/include/opencv2
- name: Build stablediffusion
run: |
export PATH=$PATH:$GOPATH/bin
make backend-assets/grpc/stablediffusion
mkdir -p release && cp backend-assets/grpc/stablediffusion release
env:
GO_TAGS: stablediffusion
- uses: actions/upload-artifact@v4
- uses: actions/upload-artifact@v3
with:
name: stablediffusion
path: release/
- name: Release
uses: softprops/action-gh-release@v2
uses: softprops/action-gh-release@v1
if: startsWith(github.ref, 'refs/tags/')
with:
files: |
release/*
build-macOS-x86_64:
runs-on: macos-13
build-macOS:
strategy:
matrix:
include:
- build: 'avx2'
defines: ''
- build: 'avx'
defines: '-DLLAMA_AVX2=OFF'
- build: 'avx512'
defines: '-DLLAMA_AVX512=ON'
runs-on: macOS-latest
steps:
- name: Clone
uses: actions/checkout@v4
with:
submodules: true
- uses: actions/setup-go@v5
- uses: actions/setup-go@v4
with:
go-version: '1.21.x'
cache: false
go-version: '>=1.21.0'
- name: Dependencies
run: |
brew install protobuf grpc
go install google.golang.org/grpc/cmd/protoc-gen-go-grpc@8ba23be9613c672d40ae261d2a1335d639bdd59b
go install google.golang.org/protobuf/cmd/protoc-gen-go@v1.34.0
- name: Build
id: build
env:
CMAKE_ARGS: "${{ matrix.defines }}"
BUILD_ID: "${{ matrix.build }}"
run: |
export C_INCLUDE_PATH=/usr/local/include
export CPLUS_INCLUDE_PATH=/usr/local/include
export PATH=$PATH:$GOPATH/bin
make dist
- uses: actions/upload-artifact@v4
- uses: actions/upload-artifact@v3
with:
name: LocalAI-MacOS-x86_64
name: ${{ matrix.build }}
path: release/
- name: Release
uses: softprops/action-gh-release@v2
uses: softprops/action-gh-release@v1
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

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

@@ -19,154 +19,150 @@ jobs:
steps:
- name: Clone
uses: actions/checkout@v4
with:
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
curl https://repo.anaconda.com/pkgs/misc/gpgkeys/anaconda.asc | gpg --dearmor > conda.gpg && \
sudo install -o root -g root -m 644 conda.gpg /usr/share/keyrings/conda-archive-keyring.gpg && \
gpg --keyring /usr/share/keyrings/conda-archive-keyring.gpg --no-default-keyring --fingerprint 34161F5BF5EB1D4BFBBB8F0A8AEB4F8B29D82806 && \
sudo /bin/bash -c 'echo "deb [arch=amd64 signed-by=/usr/share/keyrings/conda-archive-keyring.gpg] https://repo.anaconda.com/pkgs/misc/debrepo/conda stable main" > /etc/apt/sources.list.d/conda.list' && \
sudo /bin/bash -c 'echo "deb [arch=amd64 signed-by=/usr/share/keyrings/conda-archive-keyring.gpg] https://repo.anaconda.com/pkgs/misc/debrepo/conda stable main" | tee -a /etc/apt/sources.list.d/conda.list' && \
sudo apt-get update && \
sudo apt-get install -y conda
sudo apt-get install -y ca-certificates cmake curl patch
sudo apt-get install -y libopencv-dev && sudo ln -s /usr/include/opencv4/opencv2 /usr/include/opencv2
sudo rm -rfv /usr/bin/conda || true
- name: Test transformers
run: |
make --jobs=5 --output-sync=target -C backend/python/transformers
make --jobs=5 --output-sync=target -C backend/python/transformers test
export PATH=$PATH:/opt/conda/bin
make -C backend/python/transformers
make -C backend/python/transformers test
tests-sentencetransformers:
runs-on: ubuntu-latest
steps:
- name: Clone
uses: actions/checkout@v4
with:
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
curl https://repo.anaconda.com/pkgs/misc/gpgkeys/anaconda.asc | gpg --dearmor > conda.gpg && \
sudo install -o root -g root -m 644 conda.gpg /usr/share/keyrings/conda-archive-keyring.gpg && \
gpg --keyring /usr/share/keyrings/conda-archive-keyring.gpg --no-default-keyring --fingerprint 34161F5BF5EB1D4BFBBB8F0A8AEB4F8B29D82806 && \
sudo /bin/bash -c 'echo "deb [arch=amd64 signed-by=/usr/share/keyrings/conda-archive-keyring.gpg] https://repo.anaconda.com/pkgs/misc/debrepo/conda stable main" > /etc/apt/sources.list.d/conda.list' && \
sudo /bin/bash -c 'echo "deb [arch=amd64 signed-by=/usr/share/keyrings/conda-archive-keyring.gpg] https://repo.anaconda.com/pkgs/misc/debrepo/conda stable main" | tee -a /etc/apt/sources.list.d/conda.list' && \
sudo apt-get update && \
sudo apt-get install -y conda
sudo apt-get install -y ca-certificates cmake curl patch
sudo apt-get install -y libopencv-dev && sudo ln -s /usr/include/opencv4/opencv2 /usr/include/opencv2
sudo rm -rfv /usr/bin/conda || true
- name: Test sentencetransformers
run: |
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
export PATH=$PATH:/opt/conda/bin
make -C backend/python/sentencetransformers
make -C backend/python/sentencetransformers test
tests-diffusers:
runs-on: ubuntu-latest
steps:
- name: Clone
uses: actions/checkout@v4
with:
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
sudo apt-get install build-essential ffmpeg
curl https://repo.anaconda.com/pkgs/misc/gpgkeys/anaconda.asc | gpg --dearmor > conda.gpg && \
sudo install -o root -g root -m 644 conda.gpg /usr/share/keyrings/conda-archive-keyring.gpg && \
gpg --keyring /usr/share/keyrings/conda-archive-keyring.gpg --no-default-keyring --fingerprint 34161F5BF5EB1D4BFBBB8F0A8AEB4F8B29D82806 && \
sudo /bin/bash -c 'echo "deb [arch=amd64 signed-by=/usr/share/keyrings/conda-archive-keyring.gpg] https://repo.anaconda.com/pkgs/misc/debrepo/conda stable main" > /etc/apt/sources.list.d/conda.list' && \
sudo /bin/bash -c 'echo "deb [arch=amd64 signed-by=/usr/share/keyrings/conda-archive-keyring.gpg] https://repo.anaconda.com/pkgs/misc/debrepo/conda stable main" | tee -a /etc/apt/sources.list.d/conda.list' && \
sudo apt-get update && \
sudo apt-get install -y conda
sudo apt-get install -y ca-certificates cmake curl patch
sudo apt-get install -y libopencv-dev && sudo ln -s /usr/include/opencv4/opencv2 /usr/include/opencv2
sudo rm -rfv /usr/bin/conda || true
- name: Test diffusers
run: |
make --jobs=5 --output-sync=target -C backend/python/diffusers
make --jobs=5 --output-sync=target -C backend/python/diffusers test
export PATH=$PATH:/opt/conda/bin
make -C backend/python/diffusers
make -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:
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
curl https://repo.anaconda.com/pkgs/misc/gpgkeys/anaconda.asc | gpg --dearmor > conda.gpg && \
sudo install -o root -g root -m 644 conda.gpg /usr/share/keyrings/conda-archive-keyring.gpg && \
gpg --keyring /usr/share/keyrings/conda-archive-keyring.gpg --no-default-keyring --fingerprint 34161F5BF5EB1D4BFBBB8F0A8AEB4F8B29D82806 && \
sudo /bin/bash -c 'echo "deb [arch=amd64 signed-by=/usr/share/keyrings/conda-archive-keyring.gpg] https://repo.anaconda.com/pkgs/misc/debrepo/conda stable main" > /etc/apt/sources.list.d/conda.list' && \
sudo /bin/bash -c 'echo "deb [arch=amd64 signed-by=/usr/share/keyrings/conda-archive-keyring.gpg] https://repo.anaconda.com/pkgs/misc/debrepo/conda stable main" | tee -a /etc/apt/sources.list.d/conda.list' && \
sudo apt-get update && \
sudo apt-get install -y conda
sudo apt-get install -y ca-certificates cmake curl patch
sudo apt-get install -y libopencv-dev && sudo ln -s /usr/include/opencv4/opencv2 /usr/include/opencv2
sudo rm -rfv /usr/bin/conda || true
- name: Test transformers-musicgen
run: |
make --jobs=5 --output-sync=target -C backend/python/transformers-musicgen
make --jobs=5 --output-sync=target -C backend/python/transformers-musicgen test
export PATH=$PATH:/opt/conda/bin
make -C backend/python/transformers-musicgen
make -C backend/python/transformers-musicgen test
tests-petals:
runs-on: ubuntu-latest
steps:
- name: Clone
uses: actions/checkout@v4
with:
submodules: true
- name: Dependencies
run: |
sudo apt-get update
sudo apt-get install build-essential ffmpeg
curl https://repo.anaconda.com/pkgs/misc/gpgkeys/anaconda.asc | gpg --dearmor > conda.gpg && \
sudo install -o root -g root -m 644 conda.gpg /usr/share/keyrings/conda-archive-keyring.gpg && \
gpg --keyring /usr/share/keyrings/conda-archive-keyring.gpg --no-default-keyring --fingerprint 34161F5BF5EB1D4BFBBB8F0A8AEB4F8B29D82806 && \
sudo /bin/bash -c 'echo "deb [arch=amd64 signed-by=/usr/share/keyrings/conda-archive-keyring.gpg] https://repo.anaconda.com/pkgs/misc/debrepo/conda stable main" > /etc/apt/sources.list.d/conda.list' && \
sudo /bin/bash -c 'echo "deb [arch=amd64 signed-by=/usr/share/keyrings/conda-archive-keyring.gpg] https://repo.anaconda.com/pkgs/misc/debrepo/conda stable main" | tee -a /etc/apt/sources.list.d/conda.list' && \
sudo apt-get update && \
sudo apt-get install -y conda
sudo apt-get install -y ca-certificates cmake curl patch
sudo apt-get install -y libopencv-dev && sudo ln -s /usr/include/opencv4/opencv2 /usr/include/opencv2
sudo rm -rfv /usr/bin/conda || true
- name: Test petals
run: |
export PATH=$PATH:/opt/conda/bin
make -C backend/python/petals
make -C backend/python/petals test
# tests-bark:
# runs-on: ubuntu-latest
@@ -213,24 +209,31 @@ jobs:
# df -h
# - name: Clone
# uses: actions/checkout@v4
# with:
# with:
# submodules: true
# - name: Dependencies
# run: |
# sudo apt-get update
# sudo apt-get install build-essential ffmpeg
# # Install UV
# curl -LsSf https://astral.sh/uv/install.sh | sh
# sudo apt-get install -y ca-certificates cmake curl patch python3-pip
# sudo apt-get install -y libopencv-dev
# pip install --user --no-cache-dir grpcio-tools==1.64.1
# curl https://repo.anaconda.com/pkgs/misc/gpgkeys/anaconda.asc | gpg --dearmor > conda.gpg && \
# sudo install -o root -g root -m 644 conda.gpg /usr/share/keyrings/conda-archive-keyring.gpg && \
# gpg --keyring /usr/share/keyrings/conda-archive-keyring.gpg --no-default-keyring --fingerprint 34161F5BF5EB1D4BFBBB8F0A8AEB4F8B29D82806 && \
# sudo /bin/bash -c 'echo "deb [arch=amd64 signed-by=/usr/share/keyrings/conda-archive-keyring.gpg] https://repo.anaconda.com/pkgs/misc/debrepo/conda stable main" > /etc/apt/sources.list.d/conda.list' && \
# sudo /bin/bash -c 'echo "deb [arch=amd64 signed-by=/usr/share/keyrings/conda-archive-keyring.gpg] https://repo.anaconda.com/pkgs/misc/debrepo/conda stable main" | tee -a /etc/apt/sources.list.d/conda.list' && \
# sudo apt-get update && \
# sudo apt-get install -y conda
# sudo apt-get install -y ca-certificates cmake curl patch
# sudo apt-get install -y libopencv-dev && sudo ln -s /usr/include/opencv4/opencv2 /usr/include/opencv2
# sudo rm -rfv /usr/bin/conda || true
# - name: Test bark
# run: |
# make --jobs=5 --output-sync=target -C backend/python/bark
# make --jobs=5 --output-sync=target -C backend/python/bark test
# export PATH=$PATH:/opt/conda/bin
# make -C backend/python/bark
# make -C backend/python/bark test
# Below tests needs GPU. Commented out for now
# TODO: Re-enable as soon as we have GPU nodes
# tests-vllm:
@@ -238,58 +241,77 @@ jobs:
# steps:
# - name: Clone
# uses: actions/checkout@v4
# with:
# 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
# curl https://repo.anaconda.com/pkgs/misc/gpgkeys/anaconda.asc | gpg --dearmor > conda.gpg && \
# sudo install -o root -g root -m 644 conda.gpg /usr/share/keyrings/conda-archive-keyring.gpg && \
# gpg --keyring /usr/share/keyrings/conda-archive-keyring.gpg --no-default-keyring --fingerprint 34161F5BF5EB1D4BFBBB8F0A8AEB4F8B29D82806 && \
# sudo /bin/bash -c 'echo "deb [arch=amd64 signed-by=/usr/share/keyrings/conda-archive-keyring.gpg] https://repo.anaconda.com/pkgs/misc/debrepo/conda stable main" > /etc/apt/sources.list.d/conda.list' && \
# sudo /bin/bash -c 'echo "deb [arch=amd64 signed-by=/usr/share/keyrings/conda-archive-keyring.gpg] https://repo.anaconda.com/pkgs/misc/debrepo/conda stable main" | tee -a /etc/apt/sources.list.d/conda.list' && \
# sudo apt-get update && \
# sudo apt-get install -y conda
# sudo apt-get install -y ca-certificates cmake curl patch
# sudo apt-get install -y libopencv-dev && sudo ln -s /usr/include/opencv4/opencv2 /usr/include/opencv2
# sudo rm -rfv /usr/bin/conda || true
# - name: Test vllm
# run: |
# make --jobs=5 --output-sync=target -C backend/python/vllm
# make --jobs=5 --output-sync=target -C backend/python/vllm test
# export PATH=$PATH:/opt/conda/bin
# make -C backend/python/vllm
# make -C backend/python/vllm test
tests-vallex:
runs-on: ubuntu-latest
steps:
- name: Clone
uses: actions/checkout@v4
with:
with:
submodules: true
- name: Dependencies
run: |
sudo apt-get update
sudo apt-get install build-essential ffmpeg
# Install UV
curl -LsSf https://astral.sh/uv/install.sh | sh
sudo apt-get install -y ca-certificates cmake curl patch python3-pip
sudo apt-get install -y libopencv-dev
pip install --user --no-cache-dir grpcio-tools==1.64.1
curl https://repo.anaconda.com/pkgs/misc/gpgkeys/anaconda.asc | gpg --dearmor > conda.gpg && \
sudo install -o root -g root -m 644 conda.gpg /usr/share/keyrings/conda-archive-keyring.gpg && \
gpg --keyring /usr/share/keyrings/conda-archive-keyring.gpg --no-default-keyring --fingerprint 34161F5BF5EB1D4BFBBB8F0A8AEB4F8B29D82806 && \
sudo /bin/bash -c 'echo "deb [arch=amd64 signed-by=/usr/share/keyrings/conda-archive-keyring.gpg] https://repo.anaconda.com/pkgs/misc/debrepo/conda stable main" > /etc/apt/sources.list.d/conda.list' && \
sudo /bin/bash -c 'echo "deb [arch=amd64 signed-by=/usr/share/keyrings/conda-archive-keyring.gpg] https://repo.anaconda.com/pkgs/misc/debrepo/conda stable main" | tee -a /etc/apt/sources.list.d/conda.list' && \
sudo apt-get update && \
sudo apt-get install -y conda
sudo apt-get install -y ca-certificates cmake curl patch
sudo apt-get install -y libopencv-dev && sudo ln -s /usr/include/opencv4/opencv2 /usr/include/opencv2
sudo rm -rfv /usr/bin/conda || true
- name: Test vall-e-x
run: |
make --jobs=5 --output-sync=target -C backend/python/vall-e-x
make --jobs=5 --output-sync=target -C backend/python/vall-e-x test
export PATH=$PATH:/opt/conda/bin
make -C backend/python/vall-e-x
make -C backend/python/vall-e-x test
tests-coqui:
runs-on: ubuntu-latest
steps:
- name: Clone
uses: actions/checkout@v4
with:
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
curl https://repo.anaconda.com/pkgs/misc/gpgkeys/anaconda.asc | gpg --dearmor > conda.gpg && \
sudo install -o root -g root -m 644 conda.gpg /usr/share/keyrings/conda-archive-keyring.gpg && \
gpg --keyring /usr/share/keyrings/conda-archive-keyring.gpg --no-default-keyring --fingerprint 34161F5BF5EB1D4BFBBB8F0A8AEB4F8B29D82806 && \
sudo /bin/bash -c 'echo "deb [arch=amd64 signed-by=/usr/share/keyrings/conda-archive-keyring.gpg] https://repo.anaconda.com/pkgs/misc/debrepo/conda stable main" > /etc/apt/sources.list.d/conda.list' && \
sudo /bin/bash -c 'echo "deb [arch=amd64 signed-by=/usr/share/keyrings/conda-archive-keyring.gpg] https://repo.anaconda.com/pkgs/misc/debrepo/conda stable main" | tee -a /etc/apt/sources.list.d/conda.list' && \
sudo apt-get update && \
sudo apt-get install -y conda
sudo apt-get install -y ca-certificates cmake curl patch espeak espeak-ng
sudo rm -rfv /usr/bin/conda || true
- name: Test coqui
run: |
make --jobs=5 --output-sync=target -C backend/python/coqui
make --jobs=5 --output-sync=target -C backend/python/coqui test
export PATH=$PATH:/opt/conda/bin
make -C backend/python/coqui
make -C backend/python/coqui test

View File

@@ -9,9 +9,6 @@ on:
tags:
- '*'
env:
GRPC_VERSION: v1.65.0
concurrency:
group: ci-tests-${{ github.head_ref || github.ref }}-${{ github.repository }}
cancel-in-progress: true
@@ -57,49 +54,29 @@ jobs:
df -h
- name: Clone
uses: actions/checkout@v4
with:
with:
submodules: true
- name: Setup Go ${{ matrix.go-version }}
uses: actions/setup-go@v5
uses: actions/setup-go@v4
with:
go-version: ${{ matrix.go-version }}
cache: false
# You can test your matrix by printing the current Go version
- name: Display Go version
run: go version
- name: Dependencies
run: |
sudo apt-get update
sudo apt-get install build-essential ccache upx-ucl curl ffmpeg
sudo apt-get install -y libgmock-dev
sudo apt-get install build-essential ffmpeg
curl https://repo.anaconda.com/pkgs/misc/gpgkeys/anaconda.asc | gpg --dearmor > conda.gpg && \
sudo install -o root -g root -m 644 conda.gpg /usr/share/keyrings/conda-archive-keyring.gpg && \
gpg --keyring /usr/share/keyrings/conda-archive-keyring.gpg --no-default-keyring --fingerprint 34161F5BF5EB1D4BFBBB8F0A8AEB4F8B29D82806 && \
gpg --keyring /usr/share/keyrings/conda-archive-keyring.gpg --no-default-keyring --fingerprint 34161F5BF5EB1D4BFBBB8F0A8AEB4F8B29D82806 && \
sudo /bin/bash -c 'echo "deb [arch=amd64 signed-by=/usr/share/keyrings/conda-archive-keyring.gpg] https://repo.anaconda.com/pkgs/misc/debrepo/conda stable main" > /etc/apt/sources.list.d/conda.list' && \
sudo /bin/bash -c 'echo "deb [arch=amd64 signed-by=/usr/share/keyrings/conda-archive-keyring.gpg] https://repo.anaconda.com/pkgs/misc/debrepo/conda stable main" | tee -a /etc/apt/sources.list.d/conda.list' && \
sudo apt-get update && \
sudo apt-get install -y conda
# Install UV
curl -LsSf https://astral.sh/uv/install.sh | sh
sudo apt-get install -y ca-certificates cmake patch python3-pip unzip
sudo apt-get install -y libopencv-dev
curl -L -s https://github.com/protocolbuffers/protobuf/releases/download/v26.1/protoc-26.1-linux-x86_64.zip -o protoc.zip && \
unzip -j -d /usr/local/bin protoc.zip bin/protoc && \
rm protoc.zip
curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64/cuda-keyring_1.1-1_all.deb
sudo dpkg -i cuda-keyring_1.1-1_all.deb
sudo apt-get update
sudo apt-get install -y cuda-nvcc-${CUDA_VERSION} libcublas-dev-${CUDA_VERSION}
export CUDACXX=/usr/local/cuda/bin/nvcc
go install google.golang.org/protobuf/cmd/protoc-gen-go@v1.34.2
go install google.golang.org/grpc/cmd/protoc-gen-go-grpc@1958fcbe2ca8bd93af633f11e97d44e567e945af
# The python3-grpc-tools package in 22.04 is too old
pip install --user grpcio-tools
sudo apt-get install -y ca-certificates cmake curl patch
sudo apt-get install -y libopencv-dev && sudo ln -s /usr/include/opencv4/opencv2 /usr/include/opencv2
sudo rm -rfv /usr/bin/conda || true
PATH=$PATH:/opt/conda/bin make -C backend/python/sentencetransformers
@@ -108,125 +85,49 @@ jobs:
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
GO_TAGS="stablediffusion tts" GRPC_BACKENDS=backend-assets/grpc/stablediffusion make build
- name: Cache grpc
id: cache-grpc
uses: actions/cache@v4
uses: actions/cache@v3
with:
path: grpc
key: ${{ runner.os }}-grpc-${{ env.GRPC_VERSION }}
key: ${{ runner.os }}-grpc
- name: Build grpc
if: steps.cache-grpc.outputs.cache-hit != 'true'
run: |
git clone --recurse-submodules -b ${{ env.GRPC_VERSION }} --depth 1 --jobs 5 --shallow-submodules https://github.com/grpc/grpc && \
cd grpc && sed -i "216i\ TESTONLY" "third_party/abseil-cpp/absl/container/CMakeLists.txt" && mkdir -p cmake/build && cd cmake/build && \
cmake -DgRPC_INSTALL=ON \
git clone --recurse-submodules -b v1.58.0 --depth 1 --shallow-submodules https://github.com/grpc/grpc && \
cd grpc && mkdir -p cmake/build && cd cmake/build && cmake -DgRPC_INSTALL=ON \
-DgRPC_BUILD_TESTS=OFF \
../.. && sudo make --jobs 5
../.. && sudo make -j12
- name: Install gRPC
run: |
cd grpc && cd cmake/build && sudo make --jobs 5 install
cd grpc && cd cmake/build && sudo make -j12 install
- name: Test
run: |
PATH="$PATH:/root/go/bin" GO_TAGS="stablediffusion tts" make --jobs 5 --output-sync=target test
- name: Setup tmate session if tests fail
if: ${{ failure() }}
uses: mxschmitt/action-tmate@v3.18
with:
detached: true
connect-timeout-seconds: 180
limit-access-to-actor: true
tests-aio-container:
runs-on: ubuntu-latest
steps:
- name: Release space from worker
run: |
echo "Listing top largest packages"
pkgs=$(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
GO_TAGS="stablediffusion tts" make test
tests-apple:
runs-on: macOS-14
runs-on: macOS-latest
strategy:
matrix:
go-version: ['1.21.x']
steps:
- name: Clone
uses: actions/checkout@v4
with:
with:
submodules: true
- name: Setup Go ${{ matrix.go-version }}
uses: actions/setup-go@v5
uses: actions/setup-go@v4
with:
go-version: ${{ matrix.go-version }}
cache: false
# You can test your matrix by printing the current Go version
- name: Display Go version
run: go version
- name: Dependencies
run: |
brew install protobuf grpc make protoc-gen-go protoc-gen-go-grpc
pip install --user --no-cache-dir grpcio-tools==1.64.1
brew install protobuf grpc
- name: Test
run: |
export C_INCLUDE_PATH=/usr/local/include
export CPLUS_INCLUDE_PATH=/usr/local/include
# Used to run the newer GNUMake version from brew that supports --output-sync
export PATH="/opt/homebrew/opt/make/libexec/gnubin:$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
CMAKE_ARGS="-DLLAMA_F16C=OFF -DLLAMA_AVX512=OFF -DLLAMA_AVX2=OFF -DLLAMA_FMA=OFF" 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 }}

18
.gitignore vendored
View File

@@ -6,9 +6,6 @@ get-sources
prepare-sources
/backend/cpp/llama/grpc-server
/backend/cpp/llama/llama.cpp
/backend/cpp/llama-*
*.log
go-ggml-transformers
go-gpt2
@@ -42,18 +39,3 @@ 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/*

View File

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

21
.vscode/launch.json vendored
View File

@@ -3,12 +3,12 @@
"configurations": [
{
"name": "Python: Current File",
"type": "debugpy",
"type": "python",
"request": "launch",
"program": "${file}",
"console": "integratedTerminal",
"justMyCode": false,
"cwd": "${fileDirname}",
"cwd": "${workspaceFolder}/examples/langchain-chroma",
"env": {
"OPENAI_API_BASE": "http://localhost:8080/v1",
"OPENAI_API_KEY": "abc"
@@ -19,16 +19,15 @@
"type": "go",
"request": "launch",
"mode": "debug",
"program": "${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": "${workspaceRoot}"
"C_INCLUDE_PATH": "${workspaceFolder}/go-llama:${workspaceFolder}/go-stable-diffusion/:${workspaceFolder}/gpt4all/gpt4all-bindings/golang/:${workspaceFolder}/go-gpt2:${workspaceFolder}/go-rwkv:${workspaceFolder}/whisper.cpp:${workspaceFolder}/go-bert:${workspaceFolder}/bloomz",
"LIBRARY_PATH": "${workspaceFolder}/go-llama:${workspaceFolder}/go-stable-diffusion/:${workspaceFolder}/gpt4all/gpt4all-bindings/golang/:${workspaceFolder}/go-gpt2:${workspaceFolder}/go-rwkv:${workspaceFolder}/whisper.cpp:${workspaceFolder}/go-bert:${workspaceFolder}/bloomz",
"DEBUG": "true"
}
}
]
}

View File

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

View File

@@ -1,4 +1,4 @@
# Contributing to LocalAI
# 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.
@@ -29,9 +29,8 @@ Thank you for your interest in contributing to LocalAI! We appreciate your time
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`
3. Install the required dependencies: `make prepare`
4. Run LocalAI: `make run`
## Contributing
@@ -60,29 +59,14 @@ If you find a bug, have a feature request, or encounter any issues, please check
`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
- We are welcome the contribution of the documents, please open new PR in the official document repo [localai-website](https://github.com/go-skynet/localai-website)
## Community and Communication
- You can reach out via the Github issue tracker.
- Open a new discussion at [Discussion](https://github.com/go-skynet/LocalAI/discussions)
- Join the Discord channel [Discord](https://discord.gg/uJAeKSAGDy)
---
---

View File

@@ -1,364 +1,165 @@
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
# extras or core
FROM ${BASE_IMAGE} as requirements-core
USER root
ARG GO_VERSION=1.22.6
ARG GO_VERSION=1.21.7
ARG BUILD_TYPE
ARG CUDA_MAJOR_VERSION=11
ARG CUDA_MINOR_VERSION=7
ARG TARGETARCH
ARG TARGETVARIANT
ENV BUILD_TYPE=${BUILD_TYPE}
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"
ENV EXTERNAL_GRPC_BACKENDS="coqui:/build/backend/python/coqui/run.sh,huggingface-embeddings:/build/backend/python/sentencetransformers/run.sh,petals:/build/backend/python/petals/run.sh,transformers:/build/backend/python/transformers/run.sh,sentencetransformers:/build/backend/python/sentencetransformers/run.sh,autogptq:/build/backend/python/autogptq/run.sh,bark:/build/backend/python/bark/run.sh,diffusers:/build/backend/python/diffusers/run.sh,exllama:/build/backend/python/exllama/run.sh,vall-e-x:/build/backend/python/vall-e-x/run.sh,vllm:/build/backend/python/vllm/run.sh,mamba:/build/backend/python/mamba/run.sh,exllama2:/build/backend/python/exllama2/run.sh,transformers-musicgen:/build/backend/python/transformers-musicgen/run.sh"
ARG GO_TAGS="stablediffusion tinydream tts"
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/*
apt-get install -y ca-certificates curl patch pip cmake git && apt-get clean
# Install Go
RUN curl -L -s https://go.dev/dl/go${GO_VERSION}.linux-${TARGETARCH}.tar.gz | tar -C /usr/local -xz
ENV PATH=$PATH:/root/go/bin:/usr/local/go/bin
# Install grpc compilers
RUN go install google.golang.org/protobuf/cmd/protoc-gen-go@v1.34.2 && \
go install google.golang.org/grpc/cmd/protoc-gen-go-grpc@1958fcbe2ca8bd93af633f11e97d44e567e945af
RUN curl -L -s https://go.dev/dl/go$GO_VERSION.linux-$TARGETARCH.tar.gz | tar -C /usr/local -xz
ENV PATH $PATH:/usr/local/go/bin
COPY --chmod=644 custom-ca-certs/* /usr/local/share/ca-certificates/
RUN update-ca-certificates
RUN test -n "$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: $TARGETVARIANT"
# CuBLAS requirements
RUN if [ "${BUILD_TYPE}" = "cublas" ]; then \
apt-get install -y software-properties-common && \
curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64/cuda-keyring_1.1-1_all.deb && \
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 cuda-nvcc-${CUDA_MAJOR_VERSION}-${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 \
; fi
# Cuda
ENV PATH=/usr/local/cuda/bin:${PATH}
ENV PATH /usr/local/cuda/bin:${PATH}
# HipBLAS requirements
ENV PATH=/opt/rocm/bin:${PATH}
ENV PATH /opt/rocm/bin:${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/*
RUN apt-get install -y \
libopenblas-dev \
libopencv-dev \
&& apt-get clean
# Set up OpenCV
RUN ln -s /usr/include/opencv4/opencv2 /usr/include/opencv2
WORKDIR /build
###################################
###################################
RUN test -n "$TARGETARCH" \
|| (echo 'warn: missing $TARGETARCH, either set this `ARG` manually, or run using `docker buildkit`')
# The requirements-extras target is for any builds with IMAGE_TYPE=extras. It should not be placed in this target unless every IMAGE_TYPE=extras build will use it
FROM requirements-core AS requirements-extras
# Extras requirements
FROM requirements-core as requirements-extras
RUN curl https://repo.anaconda.com/pkgs/misc/gpgkeys/anaconda.asc | gpg --dearmor > conda.gpg && \
install -o root -g root -m 644 conda.gpg /usr/share/keyrings/conda-archive-keyring.gpg && \
gpg --keyring /usr/share/keyrings/conda-archive-keyring.gpg --no-default-keyring --fingerprint 34161F5BF5EB1D4BFBBB8F0A8AEB4F8B29D82806 && \
echo "deb [arch=amd64 signed-by=/usr/share/keyrings/conda-archive-keyring.gpg] https://repo.anaconda.com/pkgs/misc/debrepo/conda stable main" > /etc/apt/sources.list.d/conda.list && \
echo "deb [arch=amd64 signed-by=/usr/share/keyrings/conda-archive-keyring.gpg] https://repo.anaconda.com/pkgs/misc/debrepo/conda stable main" | tee -a /etc/apt/sources.list.d/conda.list && \
apt-get update && \
apt-get install -y conda && apt-get clean
RUN curl -LsSf https://astral.sh/uv/install.sh | sh
ENV PATH="/root/.cargo/bin:${PATH}"
RUN apt-get install -y python3-pip && apt-get clean
RUN pip install --upgrade pip
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
RUN apt-get install -y espeak-ng espeak && apt-get clean
# 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 \
RUN if [ ! -e /usr/bin/python ]; then \
ln -s /usr/bin/python3 /usr/bin/python \
; 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 ${INTEL_BASE_IMAGE} AS intel
RUN wget -qO - https://repositories.intel.com/gpu/intel-graphics.key | \
gpg --yes --dearmor --output /usr/share/keyrings/intel-graphics.gpg
RUN echo "deb [arch=amd64 signed-by=/usr/share/keyrings/intel-graphics.gpg] https://repositories.intel.com/gpu/ubuntu jammy/lts/2350 unified" > /etc/apt/sources.list.d/intel-graphics.list
FROM requirements-${IMAGE_TYPE} as builder
###################################
###################################
# 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 ${GRPC_VERSION} --depth 1 --shallow-submodules https://github.com/grpc/grpc && \
mkdir -p /build/grpc/cmake/build && \
cd /build/grpc/cmake/build && \
sed -i "216i\ TESTONLY" "../../third_party/abseil-cpp/absl/container/CMakeLists.txt" && \
cmake -DgRPC_INSTALL=ON -DgRPC_BUILD_TESTS=OFF -DCMAKE_INSTALL_PREFIX:PATH=/opt/grpc ../.. && \
make && \
make install && \
rm -rf /build
###################################
###################################
# The builder-base target has the arguments, variables, and copies shared between full builder images and the uncompiled devcontainer
FROM requirements-drivers AS builder-base
ARG GO_TAGS="stablediffusion tts p2p"
ARG GO_TAGS="stablediffusion tts"
ARG GRPC_BACKENDS
ARG MAKEFLAGS
ARG LD_FLAGS="-s -w"
ARG BUILD_GRPC=true
ENV GRPC_BACKENDS=${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" = "$TARGETARCH" ]; then
curl -L -s https://github.com/protocolbuffers/protobuf/releases/download/v27.1/protoc-27.1-linux-aarch_64.zip -o protoc.zip && \
unzip -j -d /usr/local/bin protoc.zip bin/protoc && \
rm protoc.zip
fi
EOT
###################################
###################################
# This first portion of builder holds the layers specifically used to build backend-assets/grpc/stablediffusion
# In most cases, builder is the image you should be using - however, this can save build time if one just needs to copy backend-assets/grpc/stablediffusion and nothing else.
FROM builder-base AS builder-sd
COPY . .
COPY .git .
RUN make prepare
# If we are building with clblas support, we need the libraries for the builds
RUN if [ "${BUILD_TYPE}" = "clblas" ]; then \
apt-get update && \
apt-get install -y libclblast-dev && \
apt-get clean \
; fi
# 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
RUN if [ "${BUILD_GRPC}" = "true" ]; then \
git clone --recurse-submodules -b v1.58.0 --depth 1 --shallow-submodules https://github.com/grpc/grpc && \
cd grpc && mkdir -p cmake/build && cd cmake/build && cmake -DgRPC_INSTALL=ON \
-DgRPC_BUILD_TESTS=OFF \
../.. && make -j12 install \
; fi
# Rebuild with defaults backends
WORKDIR /build
## Build the binary
RUN make build
RUN if [ ! -d "/build/sources/go-piper/piper-phonemize/pi/lib/" ]; then \
mkdir -p /build/sources/go-piper/piper-phonemize/pi/lib/ \
touch /build/sources/go-piper/piper-phonemize/pi/lib/keep \
mkdir -p /build/sources/go-piper/piper-phonemize/pi/lib/ \
touch /build/sources/go-piper/piper-phonemize/pi/lib/keep \
; fi
###################################
###################################
# The devcontainer target is not used on CI. It is a target for developers to use locally -
# rather than copying files it mounts them locally and leaves building to the developer
FROM builder-base AS devcontainer
ARG FFMPEG
COPY --from=grpc /opt/grpc /usr/local
COPY --from=builder-sd /build/backend-assets/grpc/stablediffusion /build/backend-assets/grpc/stablediffusion
COPY .devcontainer-scripts /.devcontainer-scripts
# Add FFmpeg
RUN if [ "${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
FROM requirements-${IMAGE_TYPE}
ARG FFMPEG
ARG BUILD_TYPE
ARG TARGETARCH
ARG IMAGE_TYPE=extras
ARG EXTRA_BACKENDS
ARG MAKEFLAGS
ENV BUILD_TYPE=${BUILD_TYPE}
ENV REBUILD=false
ENV HEALTHCHECK_ENDPOINT=http://localhost:8080/readyz
ENV MAKEFLAGS=${MAKEFLAGS}
ARG CUDA_MAJOR_VERSION=12
ARG CUDA_MAJOR_VERSION=11
ENV NVIDIA_DRIVER_CAPABILITIES=compute,utility
ENV NVIDIA_REQUIRE_CUDA="cuda>=${CUDA_MAJOR_VERSION}.0"
ENV NVIDIA_VISIBLE_DEVICES=all
ENV PIP_CACHE_PURGE=true
# Add FFmpeg
RUN if [ "${FFMPEG}" = "true" ]; then \
apt-get update && \
apt-get install -y --no-install-recommends \
ffmpeg && \
apt-get clean && \
rm -rf /var/lib/apt/lists/* \
apt-get install -y ffmpeg && apt-get clean \
; fi
# Add OpenCL
RUN if [ "${BUILD_TYPE}" = "clblas" ]; then \
apt-get update && \
apt-get install -y libclblast1 && \
apt-get clean \
; fi
WORKDIR /build
@@ -370,9 +171,9 @@ WORKDIR /build
COPY . .
COPY --from=builder /build/sources ./sources/
COPY --from=grpc /opt/grpc /usr/local
COPY --from=builder /build/grpc ./grpc/
RUN make prepare-sources
RUN make prepare-sources && cd /build/grpc/cmake/build && make install && rm -rf grpc
# Copy the binary
COPY --from=builder /build/local-ai ./
@@ -381,60 +182,47 @@ COPY --from=builder /build/local-ai ./
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
COPY --from=builder /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}" ) && "$IMAGE_TYPE" == "extras" ]]; then \
make -C backend/python/exllama \
## Duplicated from Makefile to avoid having a big layer that's hard to push
RUN if [ "${IMAGE_TYPE}" = "extras" ]; then \
make -C backend/python/autogptq \
; 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}" ) && "$IMAGE_TYPE" == "extras" ]]; then \
make -C backend/python/transformers \
RUN if [ "${IMAGE_TYPE}" = "extras" ]; then \
make -C backend/python/bark \
; 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}" ) && "$IMAGE_TYPE" == "extras" ]]; then \
make -C backend/python/mamba \
RUN if [ "${IMAGE_TYPE}" = "extras" ]; then \
make -C backend/python/diffusers \
; fi
RUN if [ "${IMAGE_TYPE}" = "extras" ]; then \
make -C backend/python/vllm \
; fi
RUN if [ "${IMAGE_TYPE}" = "extras" ]; then \
make -C backend/python/mamba \
; fi
RUN if [ "${IMAGE_TYPE}" = "extras" ]; then \
make -C backend/python/sentencetransformers \
; fi
RUN if [ "${IMAGE_TYPE}" = "extras" ]; then \
make -C backend/python/transformers \
; fi
RUN if [ "${IMAGE_TYPE}" = "extras" ]; then \
make -C backend/python/vall-e-x \
; fi
RUN if [ "${IMAGE_TYPE}" = "extras" ]; then \
make -C backend/python/exllama \
; fi
RUN if [ "${IMAGE_TYPE}" = "extras" ]; then \
make -C backend/python/exllama2 \
; fi
RUN if [ "${IMAGE_TYPE}" = "extras" ]; then \
make -C backend/python/petals \
; fi
RUN if [ "${IMAGE_TYPE}" = "extras" ]; then \
make -C backend/python/transformers-musicgen \
; fi
RUN if [ "${IMAGE_TYPE}" = "extras" ]; then \
make -C backend/python/coqui \
; fi
# Make sure the models directory exists
@@ -442,8 +230,7 @@ RUN mkdir -p /build/models
# Define the health check command
HEALTHCHECK --interval=1m --timeout=10m --retries=10 \
CMD curl -f ${HEALTHCHECK_ENDPOINT} || exit 1
CMD curl -f $HEALTHCHECK_ENDPOINT || exit 1
VOLUME /build/models
EXPOSE 8080
ENTRYPOINT [ "/build/entrypoint.sh" ]

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" ]

786
Makefile
View File

File diff suppressed because it is too large Load Diff

119
README.md
View File

@@ -20,14 +20,14 @@
</a>
</p>
<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>
[<img src="https://img.shields.io/badge/dockerhub-images-important.svg?logo=Docker">](https://hub.docker.com/r/localai/localai)
[<img src="https://img.shields.io/badge/quay.io-images-important.svg?">](https://quay.io/repository/go-skynet/local-ai?tab=tags&tag=latest)
> :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)
[![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)
<p align="center">
<a href="https://twitter.com/LocalAI_API" target="blank">
@@ -36,79 +36,53 @@
<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>
> :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)
[![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)
**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).
![screen](https://github.com/mudler/LocalAI/assets/2420543/20b5ccd2-8393-44f0-aaf6-87a23806381e)
Run the installer script:
```bash
curl https://localai.io/install.sh | sh
```
Or run with docker:
```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
```
[💻 Getting started](https://localai.io/basics/getting_started/index.html)
**LocalAI** is the free, Open Source OpenAI alternative. LocalAI act as a drop-in replacement REST API thats compatible with OpenAI API specifications for local inferencing. It allows you to run LLMs, generate images, audio (and not only) locally or on-prem with consumer grade hardware, supporting multiple model families. Does not require GPU.
## 🔥🔥 Hot topics / Roadmap
[Roadmap](https://github.com/mudler/LocalAI/issues?q=is%3Aissue+is%3Aopen+label%3Aroadmap)
- 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
- Parallel function calling: https://github.com/mudler/LocalAI/pull/1726
- Upload file API: https://github.com/mudler/LocalAI/pull/1703
- Tools API support: https://github.com/mudler/LocalAI/pull/1715
- LLaVa 1.6: https://github.com/mudler/LocalAI/pull/1714
- ROCm container images: https://github.com/mudler/LocalAI/pull/1595
- Intel GPU support (sycl, transformers, diffusers): https://github.com/mudler/LocalAI/issues/1653
- Deprecation of old backends: https://github.com/mudler/LocalAI/issues/1651
- Mamba support: https://github.com/mudler/LocalAI/pull/1589
- Start and share models with config file: https://github.com/mudler/LocalAI/pull/1522
- 🐸 Coqui: https://github.com/mudler/LocalAI/pull/1489
- Img2vid https://github.com/mudler/LocalAI/pull/1442
Hot topics (looking for contributors):
- 🔥🔥 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
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
## 💻 [Getting started](https://localai.io/basics/getting_started/index.html)
For a detailed step-by-step introduction, refer to the [Getting Started](https://localai.io/basics/getting_started/index.html) guide. For those in a hurry, here's a straightforward one-liner to launch a LocalAI instance with [phi-2](https://huggingface.co/microsoft/phi-2) using `docker`:
```
docker run -ti -p 8080:8080 localai/localai:v2.9.0-ffmpeg-core phi-2
```
## 🚀 [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/)
- 🔥 [OpenAI functions](https://localai.io/features/openai-functions/) 🆕
- 🧠 [Embeddings generation for vector databases](https://localai.io/features/embeddings/)
- ✍️ [Constrained grammars](https://localai.io/features/constrained_grammars/)
- 🖼️ [Download Models directly from Huggingface ](https://localai.io/models/)
- 🥽 [Vision API](https://localai.io/features/gpt-vision/)
- 📈 [Reranker API](https://localai.io/features/reranker/)
- 🆕🖧 [P2P Inferencing](https://localai.io/features/distribute/)
- 🌍 Integrated WebUI!
- 🆕 [Vision API](https://localai.io/features/gpt-vision/)
## 💻 Usage
@@ -122,7 +96,6 @@ Build and deploy custom containers:
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
@@ -130,20 +103,17 @@ Model galleries
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
- Home Assistant https://github.com/sammcj/homeassistant-localai / https://github.com/drndos/hass-openai-custom-conversation
- Discord bot https://github.com/mudler/LocalAGI/tree/main/examples/discord
- Slack bot https://github.com/mudler/LocalAGI/tree/main/examples/slack
- 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/)
- 🆕 New! [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/)
@@ -151,9 +121,7 @@ Other:
## :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 EKS with Pulumi](https://www.pulumi.com/ai/answers/tiZMDoZzZV6TLxgDXNBnFE/deploying-helm-charts-on-aws-eks)
- [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)
@@ -180,16 +148,17 @@ If you utilize this repository, data in a downstream project, please consider ci
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.
A huge thank you to our generous sponsors who support this project covering CI expenses, and our [Sponsor list](https://github.com/sponsors/mudler):
A huge thank you to our generous sponsors who support this project:
<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>
| ![Spectro Cloud logo_600x600px_transparent bg](https://github.com/go-skynet/LocalAI/assets/2420543/68a6f3cb-8a65-4a4d-99b5-6417a8905512) |
|:-----------------------------------------------:|
| [Spectro Cloud](https://www.spectrocloud.com/) |
| Spectro Cloud kindly supports LocalAI by providing GPU and computing resources to run tests on lamdalabs! |
And a huge shout-out to individuals sponsoring the project by donating hardware or backing the project.
- [Sponsor list](https://github.com/sponsors/mudler)
- JDAM00 (donating HW for the CI)
## 🌟 Star history
@@ -199,7 +168,7 @@ A huge thank you to our generous sponsors who support this project covering CI e
LocalAI is a community-driven project created by [Ettore Di Giacinto](https://github.com/mudler/).
MIT - Author Ettore Di Giacinto <mudler@localai.io>
MIT - Author Ettore Di Giacinto
## 🙇 Acknowledgements

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}]}'

View File

@@ -18,72 +18,6 @@ service Backend {
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 {}
@@ -131,15 +65,11 @@ message PredictOptions {
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 {
@@ -191,7 +121,7 @@ message ModelOptions {
bool NoMulMatQ = 37;
string DraftModel = 39;
string AudioPath = 38;
// vllm
@@ -201,7 +131,6 @@ message ModelOptions {
bool EnforceEager = 52;
int32 SwapSpace = 53;
int32 MaxModelLen = 54;
int32 TensorParallelSize = 55;
string MMProj = 41;
@@ -212,9 +141,6 @@ message ModelOptions {
float YarnBetaSlow = 47;
string Type = 49;
bool FlashAttention = 56;
bool NoKVOffload = 57;
}
message Result {
@@ -230,7 +156,6 @@ message TranscriptRequest {
string dst = 2;
string language = 3;
uint32 threads = 4;
bool translate = 5;
}
message TranscriptResult {
@@ -267,7 +192,6 @@ message TTSRequest {
string model = 2;
string dst = 3;
string voice = 4;
optional string language = 5;
}
message TokenizationResponse {
@@ -289,9 +213,4 @@ message StatusResponse {
}
State state = 1;
MemoryUsageData memory = 2;
}
message Message {
string role = 1;
string content = 2;
}

457
backend/backend_grpc.pb.go Normal file
View File

@@ -0,0 +1,457 @@
// Code generated by protoc-gen-go-grpc. DO NOT EDIT.
// versions:
// - protoc-gen-go-grpc v1.2.0
// - protoc v4.23.4
// source: backend/backend.proto
package proto
import (
context "context"
grpc "google.golang.org/grpc"
codes "google.golang.org/grpc/codes"
status "google.golang.org/grpc/status"
)
// This is a compile-time assertion to ensure that this generated file
// is compatible with the grpc package it is being compiled against.
// Requires gRPC-Go v1.32.0 or later.
const _ = grpc.SupportPackageIsVersion7
// BackendClient is the client API for Backend service.
//
// For semantics around ctx use and closing/ending streaming RPCs, please refer to https://pkg.go.dev/google.golang.org/grpc/?tab=doc#ClientConn.NewStream.
type BackendClient interface {
Health(ctx context.Context, in *HealthMessage, opts ...grpc.CallOption) (*Reply, error)
Predict(ctx context.Context, in *PredictOptions, opts ...grpc.CallOption) (*Reply, error)
LoadModel(ctx context.Context, in *ModelOptions, opts ...grpc.CallOption) (*Result, error)
PredictStream(ctx context.Context, in *PredictOptions, opts ...grpc.CallOption) (Backend_PredictStreamClient, error)
Embedding(ctx context.Context, in *PredictOptions, opts ...grpc.CallOption) (*EmbeddingResult, error)
GenerateImage(ctx context.Context, in *GenerateImageRequest, opts ...grpc.CallOption) (*Result, error)
AudioTranscription(ctx context.Context, in *TranscriptRequest, opts ...grpc.CallOption) (*TranscriptResult, error)
TTS(ctx context.Context, in *TTSRequest, opts ...grpc.CallOption) (*Result, error)
TokenizeString(ctx context.Context, in *PredictOptions, opts ...grpc.CallOption) (*TokenizationResponse, error)
Status(ctx context.Context, in *HealthMessage, opts ...grpc.CallOption) (*StatusResponse, error)
}
type backendClient struct {
cc grpc.ClientConnInterface
}
func NewBackendClient(cc grpc.ClientConnInterface) BackendClient {
return &backendClient{cc}
}
func (c *backendClient) Health(ctx context.Context, in *HealthMessage, opts ...grpc.CallOption) (*Reply, error) {
out := new(Reply)
err := c.cc.Invoke(ctx, "/backend.Backend/Health", in, out, opts...)
if err != nil {
return nil, err
}
return out, nil
}
func (c *backendClient) Predict(ctx context.Context, in *PredictOptions, opts ...grpc.CallOption) (*Reply, error) {
out := new(Reply)
err := c.cc.Invoke(ctx, "/backend.Backend/Predict", in, out, opts...)
if err != nil {
return nil, err
}
return out, nil
}
func (c *backendClient) LoadModel(ctx context.Context, in *ModelOptions, opts ...grpc.CallOption) (*Result, error) {
out := new(Result)
err := c.cc.Invoke(ctx, "/backend.Backend/LoadModel", in, out, opts...)
if err != nil {
return nil, err
}
return out, nil
}
func (c *backendClient) PredictStream(ctx context.Context, in *PredictOptions, opts ...grpc.CallOption) (Backend_PredictStreamClient, error) {
stream, err := c.cc.NewStream(ctx, &Backend_ServiceDesc.Streams[0], "/backend.Backend/PredictStream", opts...)
if err != nil {
return nil, err
}
x := &backendPredictStreamClient{stream}
if err := x.ClientStream.SendMsg(in); err != nil {
return nil, err
}
if err := x.ClientStream.CloseSend(); err != nil {
return nil, err
}
return x, nil
}
type Backend_PredictStreamClient interface {
Recv() (*Reply, error)
grpc.ClientStream
}
type backendPredictStreamClient struct {
grpc.ClientStream
}
func (x *backendPredictStreamClient) Recv() (*Reply, error) {
m := new(Reply)
if err := x.ClientStream.RecvMsg(m); err != nil {
return nil, err
}
return m, nil
}
func (c *backendClient) Embedding(ctx context.Context, in *PredictOptions, opts ...grpc.CallOption) (*EmbeddingResult, error) {
out := new(EmbeddingResult)
err := c.cc.Invoke(ctx, "/backend.Backend/Embedding", in, out, opts...)
if err != nil {
return nil, err
}
return out, nil
}
func (c *backendClient) GenerateImage(ctx context.Context, in *GenerateImageRequest, opts ...grpc.CallOption) (*Result, error) {
out := new(Result)
err := c.cc.Invoke(ctx, "/backend.Backend/GenerateImage", in, out, opts...)
if err != nil {
return nil, err
}
return out, nil
}
func (c *backendClient) AudioTranscription(ctx context.Context, in *TranscriptRequest, opts ...grpc.CallOption) (*TranscriptResult, error) {
out := new(TranscriptResult)
err := c.cc.Invoke(ctx, "/backend.Backend/AudioTranscription", in, out, opts...)
if err != nil {
return nil, err
}
return out, nil
}
func (c *backendClient) TTS(ctx context.Context, in *TTSRequest, opts ...grpc.CallOption) (*Result, error) {
out := new(Result)
err := c.cc.Invoke(ctx, "/backend.Backend/TTS", in, out, opts...)
if err != nil {
return nil, err
}
return out, nil
}
func (c *backendClient) TokenizeString(ctx context.Context, in *PredictOptions, opts ...grpc.CallOption) (*TokenizationResponse, error) {
out := new(TokenizationResponse)
err := c.cc.Invoke(ctx, "/backend.Backend/TokenizeString", in, out, opts...)
if err != nil {
return nil, err
}
return out, nil
}
func (c *backendClient) Status(ctx context.Context, in *HealthMessage, opts ...grpc.CallOption) (*StatusResponse, error) {
out := new(StatusResponse)
err := c.cc.Invoke(ctx, "/backend.Backend/Status", in, out, opts...)
if err != nil {
return nil, err
}
return out, nil
}
// BackendServer is the server API for Backend service.
// All implementations must embed UnimplementedBackendServer
// for forward compatibility
type BackendServer interface {
Health(context.Context, *HealthMessage) (*Reply, error)
Predict(context.Context, *PredictOptions) (*Reply, error)
LoadModel(context.Context, *ModelOptions) (*Result, error)
PredictStream(*PredictOptions, Backend_PredictStreamServer) error
Embedding(context.Context, *PredictOptions) (*EmbeddingResult, error)
GenerateImage(context.Context, *GenerateImageRequest) (*Result, error)
AudioTranscription(context.Context, *TranscriptRequest) (*TranscriptResult, error)
TTS(context.Context, *TTSRequest) (*Result, error)
TokenizeString(context.Context, *PredictOptions) (*TokenizationResponse, error)
Status(context.Context, *HealthMessage) (*StatusResponse, error)
mustEmbedUnimplementedBackendServer()
}
// UnimplementedBackendServer must be embedded to have forward compatible implementations.
type UnimplementedBackendServer struct {
}
func (UnimplementedBackendServer) Health(context.Context, *HealthMessage) (*Reply, error) {
return nil, status.Errorf(codes.Unimplemented, "method Health not implemented")
}
func (UnimplementedBackendServer) Predict(context.Context, *PredictOptions) (*Reply, error) {
return nil, status.Errorf(codes.Unimplemented, "method Predict not implemented")
}
func (UnimplementedBackendServer) LoadModel(context.Context, *ModelOptions) (*Result, error) {
return nil, status.Errorf(codes.Unimplemented, "method LoadModel not implemented")
}
func (UnimplementedBackendServer) PredictStream(*PredictOptions, Backend_PredictStreamServer) error {
return status.Errorf(codes.Unimplemented, "method PredictStream not implemented")
}
func (UnimplementedBackendServer) Embedding(context.Context, *PredictOptions) (*EmbeddingResult, error) {
return nil, status.Errorf(codes.Unimplemented, "method Embedding not implemented")
}
func (UnimplementedBackendServer) GenerateImage(context.Context, *GenerateImageRequest) (*Result, error) {
return nil, status.Errorf(codes.Unimplemented, "method GenerateImage not implemented")
}
func (UnimplementedBackendServer) AudioTranscription(context.Context, *TranscriptRequest) (*TranscriptResult, error) {
return nil, status.Errorf(codes.Unimplemented, "method AudioTranscription not implemented")
}
func (UnimplementedBackendServer) TTS(context.Context, *TTSRequest) (*Result, error) {
return nil, status.Errorf(codes.Unimplemented, "method TTS not implemented")
}
func (UnimplementedBackendServer) TokenizeString(context.Context, *PredictOptions) (*TokenizationResponse, error) {
return nil, status.Errorf(codes.Unimplemented, "method TokenizeString not implemented")
}
func (UnimplementedBackendServer) Status(context.Context, *HealthMessage) (*StatusResponse, error) {
return nil, status.Errorf(codes.Unimplemented, "method Status not implemented")
}
func (UnimplementedBackendServer) mustEmbedUnimplementedBackendServer() {}
// UnsafeBackendServer may be embedded to opt out of forward compatibility for this service.
// Use of this interface is not recommended, as added methods to BackendServer will
// result in compilation errors.
type UnsafeBackendServer interface {
mustEmbedUnimplementedBackendServer()
}
func RegisterBackendServer(s grpc.ServiceRegistrar, srv BackendServer) {
s.RegisterService(&Backend_ServiceDesc, srv)
}
func _Backend_Health_Handler(srv interface{}, ctx context.Context, dec func(interface{}) error, interceptor grpc.UnaryServerInterceptor) (interface{}, error) {
in := new(HealthMessage)
if err := dec(in); err != nil {
return nil, err
}
if interceptor == nil {
return srv.(BackendServer).Health(ctx, in)
}
info := &grpc.UnaryServerInfo{
Server: srv,
FullMethod: "/backend.Backend/Health",
}
handler := func(ctx context.Context, req interface{}) (interface{}, error) {
return srv.(BackendServer).Health(ctx, req.(*HealthMessage))
}
return interceptor(ctx, in, info, handler)
}
func _Backend_Predict_Handler(srv interface{}, ctx context.Context, dec func(interface{}) error, interceptor grpc.UnaryServerInterceptor) (interface{}, error) {
in := new(PredictOptions)
if err := dec(in); err != nil {
return nil, err
}
if interceptor == nil {
return srv.(BackendServer).Predict(ctx, in)
}
info := &grpc.UnaryServerInfo{
Server: srv,
FullMethod: "/backend.Backend/Predict",
}
handler := func(ctx context.Context, req interface{}) (interface{}, error) {
return srv.(BackendServer).Predict(ctx, req.(*PredictOptions))
}
return interceptor(ctx, in, info, handler)
}
func _Backend_LoadModel_Handler(srv interface{}, ctx context.Context, dec func(interface{}) error, interceptor grpc.UnaryServerInterceptor) (interface{}, error) {
in := new(ModelOptions)
if err := dec(in); err != nil {
return nil, err
}
if interceptor == nil {
return srv.(BackendServer).LoadModel(ctx, in)
}
info := &grpc.UnaryServerInfo{
Server: srv,
FullMethod: "/backend.Backend/LoadModel",
}
handler := func(ctx context.Context, req interface{}) (interface{}, error) {
return srv.(BackendServer).LoadModel(ctx, req.(*ModelOptions))
}
return interceptor(ctx, in, info, handler)
}
func _Backend_PredictStream_Handler(srv interface{}, stream grpc.ServerStream) error {
m := new(PredictOptions)
if err := stream.RecvMsg(m); err != nil {
return err
}
return srv.(BackendServer).PredictStream(m, &backendPredictStreamServer{stream})
}
type Backend_PredictStreamServer interface {
Send(*Reply) error
grpc.ServerStream
}
type backendPredictStreamServer struct {
grpc.ServerStream
}
func (x *backendPredictStreamServer) Send(m *Reply) error {
return x.ServerStream.SendMsg(m)
}
func _Backend_Embedding_Handler(srv interface{}, ctx context.Context, dec func(interface{}) error, interceptor grpc.UnaryServerInterceptor) (interface{}, error) {
in := new(PredictOptions)
if err := dec(in); err != nil {
return nil, err
}
if interceptor == nil {
return srv.(BackendServer).Embedding(ctx, in)
}
info := &grpc.UnaryServerInfo{
Server: srv,
FullMethod: "/backend.Backend/Embedding",
}
handler := func(ctx context.Context, req interface{}) (interface{}, error) {
return srv.(BackendServer).Embedding(ctx, req.(*PredictOptions))
}
return interceptor(ctx, in, info, handler)
}
func _Backend_GenerateImage_Handler(srv interface{}, ctx context.Context, dec func(interface{}) error, interceptor grpc.UnaryServerInterceptor) (interface{}, error) {
in := new(GenerateImageRequest)
if err := dec(in); err != nil {
return nil, err
}
if interceptor == nil {
return srv.(BackendServer).GenerateImage(ctx, in)
}
info := &grpc.UnaryServerInfo{
Server: srv,
FullMethod: "/backend.Backend/GenerateImage",
}
handler := func(ctx context.Context, req interface{}) (interface{}, error) {
return srv.(BackendServer).GenerateImage(ctx, req.(*GenerateImageRequest))
}
return interceptor(ctx, in, info, handler)
}
func _Backend_AudioTranscription_Handler(srv interface{}, ctx context.Context, dec func(interface{}) error, interceptor grpc.UnaryServerInterceptor) (interface{}, error) {
in := new(TranscriptRequest)
if err := dec(in); err != nil {
return nil, err
}
if interceptor == nil {
return srv.(BackendServer).AudioTranscription(ctx, in)
}
info := &grpc.UnaryServerInfo{
Server: srv,
FullMethod: "/backend.Backend/AudioTranscription",
}
handler := func(ctx context.Context, req interface{}) (interface{}, error) {
return srv.(BackendServer).AudioTranscription(ctx, req.(*TranscriptRequest))
}
return interceptor(ctx, in, info, handler)
}
func _Backend_TTS_Handler(srv interface{}, ctx context.Context, dec func(interface{}) error, interceptor grpc.UnaryServerInterceptor) (interface{}, error) {
in := new(TTSRequest)
if err := dec(in); err != nil {
return nil, err
}
if interceptor == nil {
return srv.(BackendServer).TTS(ctx, in)
}
info := &grpc.UnaryServerInfo{
Server: srv,
FullMethod: "/backend.Backend/TTS",
}
handler := func(ctx context.Context, req interface{}) (interface{}, error) {
return srv.(BackendServer).TTS(ctx, req.(*TTSRequest))
}
return interceptor(ctx, in, info, handler)
}
func _Backend_TokenizeString_Handler(srv interface{}, ctx context.Context, dec func(interface{}) error, interceptor grpc.UnaryServerInterceptor) (interface{}, error) {
in := new(PredictOptions)
if err := dec(in); err != nil {
return nil, err
}
if interceptor == nil {
return srv.(BackendServer).TokenizeString(ctx, in)
}
info := &grpc.UnaryServerInfo{
Server: srv,
FullMethod: "/backend.Backend/TokenizeString",
}
handler := func(ctx context.Context, req interface{}) (interface{}, error) {
return srv.(BackendServer).TokenizeString(ctx, req.(*PredictOptions))
}
return interceptor(ctx, in, info, handler)
}
func _Backend_Status_Handler(srv interface{}, ctx context.Context, dec func(interface{}) error, interceptor grpc.UnaryServerInterceptor) (interface{}, error) {
in := new(HealthMessage)
if err := dec(in); err != nil {
return nil, err
}
if interceptor == nil {
return srv.(BackendServer).Status(ctx, in)
}
info := &grpc.UnaryServerInfo{
Server: srv,
FullMethod: "/backend.Backend/Status",
}
handler := func(ctx context.Context, req interface{}) (interface{}, error) {
return srv.(BackendServer).Status(ctx, req.(*HealthMessage))
}
return interceptor(ctx, in, info, handler)
}
// Backend_ServiceDesc is the grpc.ServiceDesc for Backend service.
// It's only intended for direct use with grpc.RegisterService,
// and not to be introspected or modified (even as a copy)
var Backend_ServiceDesc = grpc.ServiceDesc{
ServiceName: "backend.Backend",
HandlerType: (*BackendServer)(nil),
Methods: []grpc.MethodDesc{
{
MethodName: "Health",
Handler: _Backend_Health_Handler,
},
{
MethodName: "Predict",
Handler: _Backend_Predict_Handler,
},
{
MethodName: "LoadModel",
Handler: _Backend_LoadModel_Handler,
},
{
MethodName: "Embedding",
Handler: _Backend_Embedding_Handler,
},
{
MethodName: "GenerateImage",
Handler: _Backend_GenerateImage_Handler,
},
{
MethodName: "AudioTranscription",
Handler: _Backend_AudioTranscription_Handler,
},
{
MethodName: "TTS",
Handler: _Backend_TTS_Handler,
},
{
MethodName: "TokenizeString",
Handler: _Backend_TokenizeString_Handler,
},
{
MethodName: "Status",
Handler: _Backend_Status_Handler,
},
},
Streams: []grpc.StreamDesc{
{
StreamName: "PredictStream",
Handler: _Backend_PredictStream_Handler,
ServerStreams: true,
},
},
Metadata: "backend/backend.proto",
}

View File

@@ -5,6 +5,7 @@ SYSTEM ?= $(HOST_SYSTEM)
TAG_LIB_GRPC?=v1.59.0
GIT_REPO_LIB_GRPC?=https://github.com/grpc/grpc.git
GIT_CLONE_DEPTH?=1
NUM_BUILD_THREADS?=$(shell nproc --ignore=1)
INSTALLED_PACKAGES=installed_packages
GRPC_REPO=grpc_repo
@@ -46,17 +47,12 @@ 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
git clone --depth $(GIT_CLONE_DEPTH) -b $(TAG_LIB_GRPC) $(GIT_REPO_LIB_GRPC) $(GRPC_REPO)/grpc
cd $(GRPC_REPO)/grpc && git submodule update --init --recursive --depth $(GIT_CLONE_DEPTH)
$(GRPC_BUILD): $(GRPC_REPO)
mkdir -p $(GRPC_BUILD)
cd $(GRPC_BUILD) && cmake $(CMAKE_ARGS) ../$(GRPC_REPO)/grpc && cmake --build . && cmake --build . --target install
cd $(GRPC_BUILD) && cmake $(CMAKE_ARGS) ../$(GRPC_REPO)/grpc && cmake --build . -- -j ${NUM_BUILD_THREADS} && cmake --build . --target install -- -j ${NUM_BUILD_THREADS}
build: $(INSTALLED_PACKAGES)

View File

@@ -1,82 +1,72 @@
LLAMA_VERSION?=
LLAMA_REPO?=https://github.com/ggerganov/llama.cpp
CMAKE_ARGS?=
BUILD_TYPE?=
ONEAPI_VARS?=/opt/intel/oneapi/setvars.sh
TARGET?=--target grpc-server
# Disable Shared libs as we are linking on static gRPC and we can't mix shared and static
CMAKE_ARGS+=-DBUILD_SHARED_LIBS=OFF
# If build type is cublas, then we set -DGGML_CUDA=ON to CMAKE_ARGS automatically
# If build type is cublas, then we set -DLLAMA_CUBLAS=ON to CMAKE_ARGS automatically
ifeq ($(BUILD_TYPE),cublas)
CMAKE_ARGS+=-DGGML_CUDA=ON
# If build type is openblas then we set -DGGML_BLAS=ON -DGGML_BLAS_VENDOR=OpenBLAS
CMAKE_ARGS+=-DLLAMA_CUBLAS=ON
# If build type is openblas then we set -DLLAMA_BLAS=ON -DLLAMA_BLAS_VENDOR=OpenBLAS
# to CMAKE_ARGS automatically
else ifeq ($(BUILD_TYPE),openblas)
CMAKE_ARGS+=-DGGML_BLAS=ON -DGGML_BLAS_VENDOR=OpenBLAS
# If build type is clblas (openCL) we set -DGGML_CLBLAST=ON -DCLBlast_DIR=/some/path
CMAKE_ARGS+=-DLLAMA_BLAS=ON -DLLAMA_BLAS_VENDOR=OpenBLAS
# If build type is clblas (openCL) we set -DLLAMA_CLBLAST=ON -DCLBlast_DIR=/some/path
else ifeq ($(BUILD_TYPE),clblas)
CMAKE_ARGS+=-DGGML_CLBLAST=ON -DCLBlast_DIR=/some/path
CMAKE_ARGS+=-DLLAMA_CLBLAST=ON -DCLBlast_DIR=/some/path
# If it's hipblas we do have also to set CC=/opt/rocm/llvm/bin/clang CXX=/opt/rocm/llvm/bin/clang++
else ifeq ($(BUILD_TYPE),hipblas)
CMAKE_ARGS+=-DGGML_HIPBLAS=ON
# If it's OSX, DO NOT embed the metal library - -DGGML_METAL_EMBED_LIBRARY=ON requires further investigation
# But if it's OSX without metal, disable it here
else ifeq ($(OS),Darwin)
ifneq ($(BUILD_TYPE),metal)
CMAKE_ARGS+=-DGGML_METAL=OFF
else
CMAKE_ARGS+=-DGGML_METAL=ON
# Until this is tested properly, we disable embedded metal file
# as we already embed it as part of the LocalAI assets
CMAKE_ARGS+=-DGGML_METAL_EMBED_LIBRARY=OFF
TARGET+=--target ggml-metal
endif
CMAKE_ARGS+=-DLLAMA_HIPBLAS=ON
# If it's OSX, DO NOT embed the metal library - -DLLAMA_METAL_EMBED_LIBRARY=ON requires further investigation
endif
ifeq ($(BUILD_TYPE),sycl_f16)
CMAKE_ARGS+=-DGGML_SYCL=ON -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx -DGGML_SYCL_F16=ON
CMAKE_ARGS+=-DLLAMA_SYCL=ON -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx -DLLAMA_SYCL_F16=ON
endif
ifeq ($(BUILD_TYPE),sycl_f32)
CMAKE_ARGS+=-DGGML_SYCL=ON -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx
CMAKE_ARGS+=-DLLAMA_SYCL=ON -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx
endif
llama.cpp:
mkdir -p llama.cpp
cd llama.cpp && \
git init && \
git remote add origin $(LLAMA_REPO) && \
git fetch origin && \
git checkout -b build $(LLAMA_VERSION) && \
git submodule update --init --recursive --depth 1 --single-branch
git clone --recurse-submodules https://github.com/ggerganov/llama.cpp llama.cpp
if [ -z "$(LLAMA_VERSION)" ]; then \
exit 1; \
fi
cd llama.cpp && git checkout -b build $(LLAMA_VERSION) && git submodule update --init --recursive --depth 1
llama.cpp/examples/grpc-server: llama.cpp
llama.cpp/examples/grpc-server:
mkdir -p llama.cpp/examples/grpc-server
bash prepare.sh
cp -r $(abspath ./)/CMakeLists.txt llama.cpp/examples/grpc-server/
cp -r $(abspath ./)/grpc-server.cpp llama.cpp/examples/grpc-server/
cp -rfv $(abspath ./)/json.hpp llama.cpp/examples/grpc-server/
cp -rfv $(abspath ./)/utils.hpp llama.cpp/examples/grpc-server/
echo "add_subdirectory(grpc-server)" >> llama.cpp/examples/CMakeLists.txt
## XXX: In some versions of CMake clip wasn't being built before llama.
## This is an hack for now, but it should be fixed in the future.
cp -rfv llama.cpp/examples/llava/clip.h llama.cpp/examples/grpc-server/clip.h
cp -rfv llama.cpp/examples/llava/llava.cpp llama.cpp/examples/grpc-server/llava.cpp
echo '#include "llama.h"' > llama.cpp/examples/grpc-server/llava.h
cat llama.cpp/examples/llava/llava.h >> llama.cpp/examples/grpc-server/llava.h
cp -rfv llama.cpp/examples/llava/clip.cpp llama.cpp/examples/grpc-server/clip.cpp
rebuild:
bash prepare.sh
cp -rfv $(abspath ./)/CMakeLists.txt llama.cpp/examples/grpc-server/
cp -rfv $(abspath ./)/grpc-server.cpp llama.cpp/examples/grpc-server/
cp -rfv $(abspath ./)/json.hpp llama.cpp/examples/grpc-server/
rm -rf grpc-server
$(MAKE) grpc-server
purge:
rm -rf llama.cpp/build
rm -rf llama.cpp/examples/grpc-server
clean:
rm -rf llama.cpp
rm -rf grpc-server
clean: purge
rm -rf llama.cpp
grpc-server: llama.cpp llama.cpp/examples/grpc-server
@echo "Building grpc-server with $(BUILD_TYPE) build type and $(CMAKE_ARGS)"
ifneq (,$(findstring sycl,$(BUILD_TYPE)))
+bash -c "source $(ONEAPI_VARS); \
cd llama.cpp && mkdir -p build && cd build && cmake .. $(CMAKE_ARGS) && cmake --build . --config Release $(TARGET)"
bash -c "source $(ONEAPI_VARS); \
cd llama.cpp && mkdir -p build && cd build && cmake .. $(CMAKE_ARGS) && cmake --build . --config Release"
else
+cd llama.cpp && mkdir -p build && cd build && cmake .. $(CMAKE_ARGS) && cmake --build . --config Release $(TARGET)
cd llama.cpp && mkdir -p build && cd build && cmake .. $(CMAKE_ARGS) && cmake --build . --config Release
endif
cp llama.cpp/build/bin/grpc-server .

View File

@@ -458,9 +458,7 @@ struct llama_server_context
}
}
llama_init_result llama_init = llama_init_from_gpt_params(params);
model = llama_init.model;
ctx = llama_init.context;
std::tie(model, ctx) = llama_init_from_gpt_params(params);
if (model == nullptr)
{
LOG_ERROR("unable to load model", {{"model", params.model}});
@@ -480,7 +478,7 @@ struct llama_server_context
n_ctx = llama_n_ctx(ctx);
add_bos_token = llama_add_bos_token(model);
add_bos_token = llama_should_add_bos_token(model);
return true;
}
@@ -793,7 +791,7 @@ struct llama_server_context
sampler_names.emplace_back(sampler_name);
}
}
slot->sparams.samplers_sequence = llama_sampling_types_from_names(sampler_names, false);
slot->sparams.samplers_sequence = sampler_types_from_names(sampler_names, false);
}
else
{
@@ -888,8 +886,6 @@ struct llama_server_context
{"task_id", slot->task_id},
});
LOG_TEE("sampling: \n%s\n", llama_sampling_print(slot->sparams).c_str());
return true;
}
@@ -1150,7 +1146,7 @@ struct llama_server_context
std::vector<std::string> samplers_sequence;
for (const auto &sampler_type : slot.sparams.samplers_sequence)
{
samplers_sequence.emplace_back(llama_sampling_type_to_str(sampler_type));
samplers_sequence.emplace_back(sampler_type_to_name_string(sampler_type));
}
return json {
@@ -2110,7 +2106,6 @@ json parse_options(bool streaming, const backend::PredictOptions* predict, llama
data["grammar"] = predict->grammar();
data["prompt"] = predict->prompt();
data["ignore_eos"] = predict->ignoreeos();
data["embeddings"] = predict->embeddings();
// for each image in the request, add the image data
//
@@ -2222,12 +2217,6 @@ static void params_parse(const backend::ModelOptions* request,
} else {
params.n_parallel = 1;
}
const char *llama_grpc_servers = std::getenv("LLAMACPP_GRPC_SERVERS");
if (llama_grpc_servers != NULL) {
params.rpc_servers = std::string(llama_grpc_servers);
}
// TODO: Add yarn
if (!request->tensorsplit().empty()) {
@@ -2260,13 +2249,11 @@ static void params_parse(const backend::ModelOptions* request,
}
// get the directory of modelfile
std::string model_dir = params.model.substr(0, params.model.find_last_of("/\\"));
params.lora_adapters.push_back({ model_dir + "/"+request->loraadapter(), scale_factor });
params.lora_adapter.push_back(std::make_tuple(model_dir + "/"+request->loraadapter(), scale_factor));
params.lora_base = model_dir + "/"+request->lorabase();
}
params.use_mlock = request->mlock();
params.use_mmap = request->mmap();
params.flash_attn = request->flashattention();
params.no_kv_offload = request->nokvoffload();
params.embedding = request->embeddings();
if (request->ropescaling() == "none") { params.rope_scaling_type = LLAMA_ROPE_SCALING_TYPE_NONE; }
@@ -2345,10 +2332,6 @@ public:
std::string completion_text = result.result_json.value("content", "");
reply.set_message(completion_text);
int32_t tokens_predicted = result.result_json.value("tokens_predicted", 0);
reply.set_tokens(tokens_predicted);
int32_t tokens_evaluated = result.result_json.value("tokens_evaluated", 0);
reply.set_prompt_tokens(tokens_evaluated);
// Send the reply
writer->Write(reply);
@@ -2374,10 +2357,6 @@ public:
task_result result = llama.queue_results.recv(task_id);
if (!result.error && result.stop) {
completion_text = result.result_json.value("content", "");
int32_t tokens_predicted = result.result_json.value("tokens_predicted", 0);
int32_t tokens_evaluated = result.result_json.value("tokens_evaluated", 0);
reply->set_prompt_tokens(tokens_evaluated);
reply->set_tokens(tokens_predicted);
reply->set_message(completion_text);
}
else
@@ -2387,31 +2366,6 @@ public:
return grpc::Status::OK;
}
/// https://github.com/ggerganov/llama.cpp/blob/aa2341298924ac89778252015efcb792f2df1e20/examples/server/server.cpp#L2969
grpc::Status Embedding(ServerContext* context, const backend::PredictOptions* request, backend::EmbeddingResult* embeddingResult) {
json data = parse_options(false, request, llama);
const int task_id = llama.queue_tasks.get_new_id();
llama.queue_results.add_waiting_task_id(task_id);
llama.request_completion(task_id, { {"prompt", data["embeddings"]}, { "n_predict", 0}, {"image_data", ""} }, false, true, -1);
// get the result
task_result result = llama.queue_results.recv(task_id);
//std::cout << "Embedding result JSON" << result.result_json.dump() << std::endl;
llama.queue_results.remove_waiting_task_id(task_id);
if (!result.error && result.stop) {
std::vector<float> embeddings = result.result_json.value("embedding", std::vector<float>());
// loop the vector and set the embeddings results
for (int i = 0; i < embeddings.size(); i++) {
embeddingResult->add_embeddings(embeddings[i]);
}
}
else
{
return grpc::Status::OK;
}
return grpc::Status::OK;
}
};
void RunServer(const std::string& server_address) {

View File

@@ -1,20 +0,0 @@
#!/bin/bash
cp -r CMakeLists.txt llama.cpp/examples/grpc-server/
cp -r grpc-server.cpp llama.cpp/examples/grpc-server/
cp -rfv json.hpp llama.cpp/examples/grpc-server/
cp -rfv utils.hpp llama.cpp/examples/grpc-server/
if grep -q "grpc-server" llama.cpp/examples/CMakeLists.txt; then
echo "grpc-server already added"
else
echo "add_subdirectory(grpc-server)" >> llama.cpp/examples/CMakeLists.txt
fi
## XXX: In some versions of CMake clip wasn't being built before llama.
## This is an hack for now, but it should be fixed in the future.
cp -rfv llama.cpp/examples/llava/clip.h llama.cpp/examples/grpc-server/clip.h
cp -rfv llama.cpp/examples/llava/llava.cpp llama.cpp/examples/grpc-server/llava.cpp
echo '#include "llama.h"' > llama.cpp/examples/grpc-server/llava.h
cat llama.cpp/examples/llava/llava.h >> llama.cpp/examples/grpc-server/llava.h
cp -rfv llama.cpp/examples/llava/clip.cpp llama.cpp/examples/grpc-server/clip.cpp

View File

@@ -5,7 +5,7 @@ package main
import (
"flag"
grpc "github.com/mudler/LocalAI/pkg/grpc"
grpc "github.com/go-skynet/LocalAI/pkg/grpc"
)
var (

View File

@@ -3,9 +3,9 @@ package main
// This is a wrapper to statisfy the GRPC service interface
// It is meant to be used by the main executable that is the server for the specific backend type (falcon, gpt3, etc)
import (
"github.com/mudler/LocalAI/pkg/grpc/base"
pb "github.com/mudler/LocalAI/pkg/grpc/proto"
"github.com/mudler/LocalAI/pkg/stablediffusion"
"github.com/go-skynet/LocalAI/pkg/grpc/base"
pb "github.com/go-skynet/LocalAI/pkg/grpc/proto"
"github.com/go-skynet/LocalAI/pkg/stablediffusion"
)
type Image struct {

View File

@@ -5,7 +5,7 @@ package main
import (
"flag"
grpc "github.com/mudler/LocalAI/pkg/grpc"
grpc "github.com/go-skynet/LocalAI/pkg/grpc"
)
var (

View File

@@ -3,9 +3,9 @@ package main
// This is a wrapper to statisfy the GRPC service interface
// It is meant to be used by the main executable that is the server for the specific backend type (falcon, gpt3, etc)
import (
"github.com/mudler/LocalAI/pkg/grpc/base"
pb "github.com/mudler/LocalAI/pkg/grpc/proto"
"github.com/mudler/LocalAI/pkg/tinydream"
"github.com/go-skynet/LocalAI/pkg/grpc/base"
pb "github.com/go-skynet/LocalAI/pkg/grpc/proto"
"github.com/go-skynet/LocalAI/pkg/tinydream"
)
type Image struct {

View File

@@ -5,8 +5,8 @@ package main
import (
bert "github.com/go-skynet/go-bert.cpp"
"github.com/mudler/LocalAI/pkg/grpc/base"
pb "github.com/mudler/LocalAI/pkg/grpc/proto"
"github.com/go-skynet/LocalAI/pkg/grpc/base"
pb "github.com/go-skynet/LocalAI/pkg/grpc/proto"
)
type Embeddings struct {

View File

@@ -5,7 +5,7 @@ package main
import (
"flag"
grpc "github.com/mudler/LocalAI/pkg/grpc"
grpc "github.com/go-skynet/LocalAI/pkg/grpc"
)
var (

View File

@@ -0,0 +1,62 @@
package main
// This is a wrapper to statisfy the GRPC service interface
// It is meant to be used by the main executable that is the server for the specific backend type (falcon, gpt3, etc)
import (
"fmt"
"github.com/go-skynet/LocalAI/pkg/grpc/base"
pb "github.com/go-skynet/LocalAI/pkg/grpc/proto"
gpt4all "github.com/nomic-ai/gpt4all/gpt4all-bindings/golang"
)
type LLM struct {
base.SingleThread
gpt4all *gpt4all.Model
}
func (llm *LLM) Load(opts *pb.ModelOptions) error {
model, err := gpt4all.New(opts.ModelFile,
gpt4all.SetThreads(int(opts.Threads)),
gpt4all.SetLibrarySearchPath(opts.LibrarySearchPath))
llm.gpt4all = model
return err
}
func buildPredictOptions(opts *pb.PredictOptions) []gpt4all.PredictOption {
predictOptions := []gpt4all.PredictOption{
gpt4all.SetTemperature(float64(opts.Temperature)),
gpt4all.SetTopP(float64(opts.TopP)),
gpt4all.SetTopK(int(opts.TopK)),
gpt4all.SetTokens(int(opts.Tokens)),
}
if opts.Batch != 0 {
predictOptions = append(predictOptions, gpt4all.SetBatch(int(opts.Batch)))
}
return predictOptions
}
func (llm *LLM) Predict(opts *pb.PredictOptions) (string, error) {
return llm.gpt4all.Predict(opts.Prompt, buildPredictOptions(opts)...)
}
func (llm *LLM) PredictStream(opts *pb.PredictOptions, results chan string) error {
predictOptions := buildPredictOptions(opts)
go func() {
llm.gpt4all.SetTokenCallback(func(token string) bool {
results <- token
return true
})
_, err := llm.gpt4all.Predict(opts.Prompt, predictOptions...)
if err != nil {
fmt.Println("err: ", err)
}
llm.gpt4all.SetTokenCallback(nil)
close(results)
}()
return nil
}

View File

@@ -0,0 +1,21 @@
package main
// Note: this is started internally by LocalAI and a server is allocated for each model
import (
"flag"
grpc "github.com/go-skynet/LocalAI/pkg/grpc"
)
var (
addr = flag.String("addr", "localhost:50051", "the address to connect to")
)
func main() {
flag.Parse()
if err := grpc.StartServer(*addr, &LLM{}); err != nil {
panic(err)
}
}

View File

@@ -4,11 +4,10 @@ package main
// It is meant to be used by the main executable that is the server for the specific backend type (falcon, gpt3, etc)
import (
"fmt"
"os"
"github.com/mudler/LocalAI/pkg/grpc/base"
pb "github.com/mudler/LocalAI/pkg/grpc/proto"
"github.com/mudler/LocalAI/pkg/langchain"
"github.com/go-skynet/LocalAI/pkg/grpc/base"
pb "github.com/go-skynet/LocalAI/pkg/grpc/proto"
"github.com/go-skynet/LocalAI/pkg/langchain"
)
type LLM struct {
@@ -19,14 +18,9 @@ type LLM struct {
}
func (llm *LLM) Load(opts *pb.ModelOptions) error {
var err error
hfToken := os.Getenv("HUGGINGFACEHUB_API_TOKEN")
if hfToken == "" {
return fmt.Errorf("no huggingface token provided")
}
llm.langchain, err = langchain.NewHuggingFace(opts.Model, hfToken)
llm.langchain, _ = langchain.NewHuggingFace(opts.Model)
llm.model = opts.Model
return err
return nil
}
func (llm *LLM) Predict(opts *pb.PredictOptions) (string, error) {

View File

@@ -5,7 +5,7 @@ package main
import (
"flag"
grpc "github.com/mudler/LocalAI/pkg/grpc"
grpc "github.com/go-skynet/LocalAI/pkg/grpc"
)
var (

View File

@@ -5,9 +5,9 @@ package main
import (
"fmt"
"github.com/go-skynet/LocalAI/pkg/grpc/base"
pb "github.com/go-skynet/LocalAI/pkg/grpc/proto"
"github.com/go-skynet/go-llama.cpp"
"github.com/mudler/LocalAI/pkg/grpc/base"
pb "github.com/mudler/LocalAI/pkg/grpc/proto"
)
type LLM struct {

View File

@@ -3,7 +3,7 @@ package main
import (
"flag"
grpc "github.com/mudler/LocalAI/pkg/grpc"
grpc "github.com/go-skynet/LocalAI/pkg/grpc"
)
var (

View File

@@ -6,9 +6,9 @@ import (
"fmt"
"path/filepath"
"github.com/go-skynet/LocalAI/pkg/grpc/base"
pb "github.com/go-skynet/LocalAI/pkg/grpc/proto"
"github.com/go-skynet/go-llama.cpp"
"github.com/mudler/LocalAI/pkg/grpc/base"
pb "github.com/mudler/LocalAI/pkg/grpc/proto"
)
type LLM struct {

View File

@@ -7,7 +7,7 @@ package main
import (
"flag"
grpc "github.com/mudler/LocalAI/pkg/grpc"
grpc "github.com/go-skynet/LocalAI/pkg/grpc"
)
var (

View File

@@ -5,7 +5,7 @@ package main
import (
"flag"
grpc "github.com/mudler/LocalAI/pkg/grpc"
grpc "github.com/go-skynet/LocalAI/pkg/grpc"
)
var (

View File

@@ -7,8 +7,8 @@ import (
"path/filepath"
"github.com/donomii/go-rwkv.cpp"
"github.com/mudler/LocalAI/pkg/grpc/base"
pb "github.com/mudler/LocalAI/pkg/grpc/proto"
"github.com/go-skynet/LocalAI/pkg/grpc/base"
pb "github.com/go-skynet/LocalAI/pkg/grpc/proto"
)
const tokenizerSuffix = ".tokenizer.json"
@@ -31,7 +31,7 @@ func (llm *LLM) Load(opts *pb.ModelOptions) error {
model := rwkv.LoadFiles(opts.ModelFile, tokenizerPath, uint32(opts.GetThreads()))
if model == nil {
return fmt.Errorf("rwkv could not load model")
return fmt.Errorf("could not load model")
}
llm.rwkv = model
return nil

View File

@@ -1,14 +0,0 @@
//go:build debug
// +build debug
package main
import (
"github.com/rs/zerolog/log"
)
func assert(cond bool, msg string) {
if !cond {
log.Fatal().Stack().Msg(msg)
}
}

View File

@@ -1,26 +0,0 @@
package main
// Note: this is started internally by LocalAI and a server is allocated for each store
import (
"flag"
"os"
grpc "github.com/mudler/LocalAI/pkg/grpc"
"github.com/rs/zerolog"
"github.com/rs/zerolog/log"
)
var (
addr = flag.String("addr", "localhost:50051", "the address to connect to")
)
func main() {
log.Logger = log.Output(zerolog.ConsoleWriter{Out: os.Stderr})
flag.Parse()
if err := grpc.StartServer(*addr, NewStore()); err != nil {
panic(err)
}
}

View File

@@ -1,7 +0,0 @@
//go:build !debug
// +build !debug
package main
func assert(cond bool, msg string) {
}

View File

@@ -1,507 +0,0 @@
package main
// This is a wrapper to statisfy the GRPC service interface
// It is meant to be used by the main executable that is the server for the specific backend type (falcon, gpt3, etc)
import (
"container/heap"
"fmt"
"math"
"slices"
"github.com/mudler/LocalAI/pkg/grpc/base"
pb "github.com/mudler/LocalAI/pkg/grpc/proto"
"github.com/rs/zerolog/log"
)
type Store struct {
base.SingleThread
// The sorted keys
keys [][]float32
// The sorted values
values [][]byte
// If for every K it holds that ||k||^2 = 1, then we can use the normalized distance functions
// TODO: Should we normalize incoming keys if they are not instead?
keysAreNormalized bool
// The first key decides the length of the keys
keyLen int
}
// TODO: Only used for sorting using Go's builtin implementation. The interfaces are columnar because
// that's theoretically best for memory layout and cache locality, but this isn't optimized yet.
type Pair struct {
Key []float32
Value []byte
}
func NewStore() *Store {
return &Store{
keys: make([][]float32, 0),
values: make([][]byte, 0),
keysAreNormalized: true,
keyLen: -1,
}
}
func compareSlices(k1, k2 []float32) int {
assert(len(k1) == len(k2), fmt.Sprintf("compareSlices: len(k1) = %d, len(k2) = %d", len(k1), len(k2)))
return slices.Compare(k1, k2)
}
func hasKey(unsortedSlice [][]float32, target []float32) bool {
return slices.ContainsFunc(unsortedSlice, func(k []float32) bool {
return compareSlices(k, target) == 0
})
}
func findInSortedSlice(sortedSlice [][]float32, target []float32) (int, bool) {
return slices.BinarySearchFunc(sortedSlice, target, func(k, t []float32) int {
return compareSlices(k, t)
})
}
func isSortedPairs(kvs []Pair) bool {
for i := 1; i < len(kvs); i++ {
if compareSlices(kvs[i-1].Key, kvs[i].Key) > 0 {
return false
}
}
return true
}
func isSortedKeys(keys [][]float32) bool {
for i := 1; i < len(keys); i++ {
if compareSlices(keys[i-1], keys[i]) > 0 {
return false
}
}
return true
}
func sortIntoKeySlicese(keys []*pb.StoresKey) [][]float32 {
ks := make([][]float32, len(keys))
for i, k := range keys {
ks[i] = k.Floats
}
slices.SortFunc(ks, compareSlices)
assert(len(ks) == len(keys), fmt.Sprintf("len(ks) = %d, len(keys) = %d", len(ks), len(keys)))
assert(isSortedKeys(ks), "keys are not sorted")
return ks
}
func (s *Store) Load(opts *pb.ModelOptions) error {
return nil
}
// Sort the incoming kvs and merge them with the existing sorted kvs
func (s *Store) StoresSet(opts *pb.StoresSetOptions) error {
if len(opts.Keys) == 0 {
return fmt.Errorf("no keys to add")
}
if len(opts.Keys) != len(opts.Values) {
return fmt.Errorf("len(keys) = %d, len(values) = %d", len(opts.Keys), len(opts.Values))
}
if s.keyLen == -1 {
s.keyLen = len(opts.Keys[0].Floats)
} else {
if len(opts.Keys[0].Floats) != s.keyLen {
return fmt.Errorf("Try to add key with length %d when existing length is %d", len(opts.Keys[0].Floats), s.keyLen)
}
}
kvs := make([]Pair, len(opts.Keys))
for i, k := range opts.Keys {
if s.keysAreNormalized && !isNormalized(k.Floats) {
s.keysAreNormalized = false
var sample []float32
if len(s.keys) > 5 {
sample = k.Floats[:5]
} else {
sample = k.Floats
}
log.Debug().Msgf("Key is not normalized: %v", sample)
}
kvs[i] = Pair{
Key: k.Floats,
Value: opts.Values[i].Bytes,
}
}
slices.SortFunc(kvs, func(a, b Pair) int {
return compareSlices(a.Key, b.Key)
})
assert(len(kvs) == len(opts.Keys), fmt.Sprintf("len(kvs) = %d, len(opts.Keys) = %d", len(kvs), len(opts.Keys)))
assert(isSortedPairs(kvs), "keys are not sorted")
l := len(kvs) + len(s.keys)
merge_ks := make([][]float32, 0, l)
merge_vs := make([][]byte, 0, l)
i, j := 0, 0
for {
if i+j >= l {
break
}
if i >= len(kvs) {
merge_ks = append(merge_ks, s.keys[j])
merge_vs = append(merge_vs, s.values[j])
j++
continue
}
if j >= len(s.keys) {
merge_ks = append(merge_ks, kvs[i].Key)
merge_vs = append(merge_vs, kvs[i].Value)
i++
continue
}
c := compareSlices(kvs[i].Key, s.keys[j])
if c < 0 {
merge_ks = append(merge_ks, kvs[i].Key)
merge_vs = append(merge_vs, kvs[i].Value)
i++
} else if c > 0 {
merge_ks = append(merge_ks, s.keys[j])
merge_vs = append(merge_vs, s.values[j])
j++
} else {
merge_ks = append(merge_ks, kvs[i].Key)
merge_vs = append(merge_vs, kvs[i].Value)
i++
j++
}
}
assert(len(merge_ks) == l, fmt.Sprintf("len(merge_ks) = %d, l = %d", len(merge_ks), l))
assert(isSortedKeys(merge_ks), "merge keys are not sorted")
s.keys = merge_ks
s.values = merge_vs
return nil
}
func (s *Store) StoresDelete(opts *pb.StoresDeleteOptions) error {
if len(opts.Keys) == 0 {
return fmt.Errorf("no keys to delete")
}
if len(opts.Keys) == 0 {
return fmt.Errorf("no keys to add")
}
if s.keyLen == -1 {
s.keyLen = len(opts.Keys[0].Floats)
} else {
if len(opts.Keys[0].Floats) != s.keyLen {
return fmt.Errorf("Trying to delete key with length %d when existing length is %d", len(opts.Keys[0].Floats), s.keyLen)
}
}
ks := sortIntoKeySlicese(opts.Keys)
l := len(s.keys) - len(ks)
merge_ks := make([][]float32, 0, l)
merge_vs := make([][]byte, 0, l)
tail_ks := s.keys
tail_vs := s.values
for _, k := range ks {
j, found := findInSortedSlice(tail_ks, k)
if found {
merge_ks = append(merge_ks, tail_ks[:j]...)
merge_vs = append(merge_vs, tail_vs[:j]...)
tail_ks = tail_ks[j+1:]
tail_vs = tail_vs[j+1:]
} else {
assert(!hasKey(s.keys, k), fmt.Sprintf("Key exists, but was not found: t=%d, %v", len(tail_ks), k))
}
log.Debug().Msgf("Delete: found = %v, t = %d, j = %d, len(merge_ks) = %d, len(merge_vs) = %d", found, len(tail_ks), j, len(merge_ks), len(merge_vs))
}
merge_ks = append(merge_ks, tail_ks...)
merge_vs = append(merge_vs, tail_vs...)
assert(len(merge_ks) <= len(s.keys), fmt.Sprintf("len(merge_ks) = %d, len(s.keys) = %d", len(merge_ks), len(s.keys)))
s.keys = merge_ks
s.values = merge_vs
assert(len(s.keys) >= l, fmt.Sprintf("len(s.keys) = %d, l = %d", len(s.keys), l))
assert(isSortedKeys(s.keys), "keys are not sorted")
assert(func() bool {
for _, k := range ks {
if _, found := findInSortedSlice(s.keys, k); found {
return false
}
}
return true
}(), "Keys to delete still present")
if len(s.keys) != l {
log.Debug().Msgf("Delete: Some keys not found: len(s.keys) = %d, l = %d", len(s.keys), l)
}
return nil
}
func (s *Store) StoresGet(opts *pb.StoresGetOptions) (pb.StoresGetResult, error) {
pbKeys := make([]*pb.StoresKey, 0, len(opts.Keys))
pbValues := make([]*pb.StoresValue, 0, len(opts.Keys))
ks := sortIntoKeySlicese(opts.Keys)
if len(s.keys) == 0 {
log.Debug().Msgf("Get: No keys in store")
}
if s.keyLen == -1 {
s.keyLen = len(opts.Keys[0].Floats)
} else {
if len(opts.Keys[0].Floats) != s.keyLen {
return pb.StoresGetResult{}, fmt.Errorf("Try to get a key with length %d when existing length is %d", len(opts.Keys[0].Floats), s.keyLen)
}
}
tail_k := s.keys
tail_v := s.values
for i, k := range ks {
j, found := findInSortedSlice(tail_k, k)
if found {
pbKeys = append(pbKeys, &pb.StoresKey{
Floats: k,
})
pbValues = append(pbValues, &pb.StoresValue{
Bytes: tail_v[j],
})
tail_k = tail_k[j+1:]
tail_v = tail_v[j+1:]
} else {
assert(!hasKey(s.keys, k), fmt.Sprintf("Key exists, but was not found: i=%d, %v", i, k))
}
}
if len(pbKeys) != len(opts.Keys) {
log.Debug().Msgf("Get: Some keys not found: len(pbKeys) = %d, len(opts.Keys) = %d, len(s.Keys) = %d", len(pbKeys), len(opts.Keys), len(s.keys))
}
return pb.StoresGetResult{
Keys: pbKeys,
Values: pbValues,
}, nil
}
func isNormalized(k []float32) bool {
var sum float32
for _, v := range k {
sum += v
}
return sum == 1.0
}
// TODO: This we could replace with handwritten SIMD code
func normalizedCosineSimilarity(k1, k2 []float32) float32 {
assert(len(k1) == len(k2), fmt.Sprintf("normalizedCosineSimilarity: len(k1) = %d, len(k2) = %d", len(k1), len(k2)))
var dot float32
for i := 0; i < len(k1); i++ {
dot += k1[i] * k2[i]
}
assert(dot >= -1 && dot <= 1, fmt.Sprintf("dot = %f", dot))
// 2.0 * (1.0 - dot) would be the Euclidean distance
return dot
}
type PriorityItem struct {
Similarity float32
Key []float32
Value []byte
}
type PriorityQueue []*PriorityItem
func (pq PriorityQueue) Len() int { return len(pq) }
func (pq PriorityQueue) Less(i, j int) bool {
// Inverted because the most similar should be at the top
return pq[i].Similarity < pq[j].Similarity
}
func (pq PriorityQueue) Swap(i, j int) {
pq[i], pq[j] = pq[j], pq[i]
}
func (pq *PriorityQueue) Push(x any) {
item := x.(*PriorityItem)
*pq = append(*pq, item)
}
func (pq *PriorityQueue) Pop() any {
old := *pq
n := len(old)
item := old[n-1]
*pq = old[0 : n-1]
return item
}
func (s *Store) StoresFindNormalized(opts *pb.StoresFindOptions) (pb.StoresFindResult, error) {
tk := opts.Key.Floats
top_ks := make(PriorityQueue, 0, int(opts.TopK))
heap.Init(&top_ks)
for i, k := range s.keys {
sim := normalizedCosineSimilarity(tk, k)
heap.Push(&top_ks, &PriorityItem{
Similarity: sim,
Key: k,
Value: s.values[i],
})
if top_ks.Len() > int(opts.TopK) {
heap.Pop(&top_ks)
}
}
similarities := make([]float32, top_ks.Len())
pbKeys := make([]*pb.StoresKey, top_ks.Len())
pbValues := make([]*pb.StoresValue, top_ks.Len())
for i := top_ks.Len() - 1; i >= 0; i-- {
item := heap.Pop(&top_ks).(*PriorityItem)
similarities[i] = item.Similarity
pbKeys[i] = &pb.StoresKey{
Floats: item.Key,
}
pbValues[i] = &pb.StoresValue{
Bytes: item.Value,
}
}
return pb.StoresFindResult{
Keys: pbKeys,
Values: pbValues,
Similarities: similarities,
}, nil
}
func cosineSimilarity(k1, k2 []float32, mag1 float64) float32 {
assert(len(k1) == len(k2), fmt.Sprintf("cosineSimilarity: len(k1) = %d, len(k2) = %d", len(k1), len(k2)))
var dot, mag2 float64
for i := 0; i < len(k1); i++ {
dot += float64(k1[i] * k2[i])
mag2 += float64(k2[i] * k2[i])
}
sim := float32(dot / (mag1 * math.Sqrt(mag2)))
assert(sim >= -1 && sim <= 1, fmt.Sprintf("sim = %f", sim))
return sim
}
func (s *Store) StoresFindFallback(opts *pb.StoresFindOptions) (pb.StoresFindResult, error) {
tk := opts.Key.Floats
top_ks := make(PriorityQueue, 0, int(opts.TopK))
heap.Init(&top_ks)
var mag1 float64
for _, v := range tk {
mag1 += float64(v * v)
}
mag1 = math.Sqrt(mag1)
for i, k := range s.keys {
dist := cosineSimilarity(tk, k, mag1)
heap.Push(&top_ks, &PriorityItem{
Similarity: dist,
Key: k,
Value: s.values[i],
})
if top_ks.Len() > int(opts.TopK) {
heap.Pop(&top_ks)
}
}
similarities := make([]float32, top_ks.Len())
pbKeys := make([]*pb.StoresKey, top_ks.Len())
pbValues := make([]*pb.StoresValue, top_ks.Len())
for i := top_ks.Len() - 1; i >= 0; i-- {
item := heap.Pop(&top_ks).(*PriorityItem)
similarities[i] = item.Similarity
pbKeys[i] = &pb.StoresKey{
Floats: item.Key,
}
pbValues[i] = &pb.StoresValue{
Bytes: item.Value,
}
}
return pb.StoresFindResult{
Keys: pbKeys,
Values: pbValues,
Similarities: similarities,
}, nil
}
func (s *Store) StoresFind(opts *pb.StoresFindOptions) (pb.StoresFindResult, error) {
tk := opts.Key.Floats
if len(tk) != s.keyLen {
return pb.StoresFindResult{}, fmt.Errorf("Try to find key with length %d when existing length is %d", len(tk), s.keyLen)
}
if opts.TopK < 1 {
return pb.StoresFindResult{}, fmt.Errorf("opts.TopK = %d, must be >= 1", opts.TopK)
}
if s.keyLen == -1 {
s.keyLen = len(opts.Key.Floats)
} else {
if len(opts.Key.Floats) != s.keyLen {
return pb.StoresFindResult{}, fmt.Errorf("Try to add key with length %d when existing length is %d", len(opts.Key.Floats), s.keyLen)
}
}
if s.keysAreNormalized && isNormalized(tk) {
return s.StoresFindNormalized(opts)
} else {
if s.keysAreNormalized {
var sample []float32
if len(s.keys) > 5 {
sample = tk[:5]
} else {
sample = tk
}
log.Debug().Msgf("Trying to compare non-normalized key with normalized keys: %v", sample)
}
return s.StoresFindFallback(opts)
}
}

View File

@@ -5,7 +5,7 @@ package main
import (
"flag"
grpc "github.com/mudler/LocalAI/pkg/grpc"
grpc "github.com/go-skynet/LocalAI/pkg/grpc"
)
var (

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