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1 Commits

Author SHA1 Message Date
Ettore Di Giacinto
ac47aeaddd wip: try to let JSON grammar to return strings as well
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2024-05-14 22:58:27 +02:00
828 changed files with 21555 additions and 306224 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

View File

@@ -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

View File

@@ -1,55 +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() {
echo "Configuring git for $1 <$2>"
local gcn=$(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() {
echo "Adding git remote and fetching $2 as $1"
local gr=$(git remote -v | grep $1)
if [ -z "${gr}" ]; then
git remote add $1 $2
fi
git fetch $1
}
# Setup special .ssh files
# Prints out lines of text to make things pretty
# Param 1: bash array, filenames relative to the customization directory that should be copied to ~/.ssh
setup_ssh() {
echo "starting ~/.ssh directory setup..."
mkdir -p "${HOME}.ssh"
chmod 0700 "${HOME}/.ssh"
echo "-----"
local files=("$@")
for file in "${files[@]}" ; do
local cfile="/devcontainer-customization/${file}"
local hfile="${HOME}/.ssh/${file}"
if [ ! -f "${hfile}" ]; then
echo "copying \"${file}\""
cp "${cfile}" "${hfile}"
chmod 600 "${hfile}"
fi
done
echo "~/.ssh directory setup complete!"
}

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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=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

@@ -1,7 +1,6 @@
.idea
.github
.vscode
.devcontainer
models
examples/chatbot-ui/models
examples/rwkv/models

26
.env
View File

@@ -29,9 +29,6 @@
## Enable/Disable single backend (useful if only one GPU is available)
# LOCALAI_SINGLE_ACTIVE_BACKEND=true
# Forces shutdown of the backends if busy (only if LOCALAI_SINGLE_ACTIVE_BACKEND is set)
# LOCALAI_FORCE_BACKEND_SHUTDOWN=true
## Specify a build type. Available: cublas, openblas, clblas.
## cuBLAS: This is a GPU-accelerated version of the complete standard BLAS (Basic Linear Algebra Subprograms) library. It's provided by Nvidia and is part of their CUDA toolkit.
## OpenBLAS: This is an open-source implementation of the BLAS library that aims to provide highly optimized code for various platforms. It includes support for multi-threading and can be compiled to use hardware-specific features for additional performance. OpenBLAS can run on many kinds of hardware, including CPUs from Intel, AMD, and ARM.
@@ -41,12 +38,12 @@
## Uncomment and set to true to enable rebuilding from source
# REBUILD=true
## Enable go tags, available: p2p, tts
## p2p: enable distributed inferencing
## Enable go tags, available: stablediffusion, tts
## stablediffusion: image generation with stablediffusion
## tts: enables text-to-speech with go-piper
## (requires REBUILD=true)
#
# GO_TAGS=p2p
# GO_TAGS=stablediffusion
## Path where to store generated images
# LOCALAI_IMAGE_PATH=/tmp/generated/images
@@ -74,26 +71,9 @@
### 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
# Enable to use federated mode
# LOCALAI_FEDERATED=true
# Enable to start federation server
# FEDERATED_SERVER=true
# Define to use federation token
# TOKEN=""
### Watchdog settings
###
# Enables watchdog to kill backends that are inactive for too much time

1
.gitattributes vendored
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@@ -1,2 +1 @@
*.sh text eol=lf
backend/cpp/llama/*.hpp linguist-vendored

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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@@ -1,85 +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()
# Check if 'hasUnsafeFile' exists in the response
if 'hasUnsafeFile' in scan:
if scan['hasUnsafeFile']:
return scan
else:
return None
else:
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)

View File

@@ -14,14 +14,62 @@ function check_and_update_checksum() {
idx="$5"
# Download the file and calculate new checksum using Python
new_checksum=$(python3 ./.github/check_and_update.py $uri)
result=$?
new_checksum=$(python3 -c "
import hashlib
from huggingface_hub import hf_hub_download
import requests
import sys
import os
if [[ $result -eq 5 ]]; then
echo "Contaminated entry detected, deleting entry for $model_name..."
yq eval -i "del([$idx])" "$input_yaml"
return
fi
uri = '$uri'
file_name = uri.split('/')[-1]
# Function to parse the URI and determine download method
# 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()
download_type, repo_id_or_url = parse_uri(uri)
# Decide download method based on URI type
if download_type == 'huggingface':
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)
print(calculate_sha256(file_path))
# Clean up the downloaded file
os.remove(file_path)
")
if [[ "$new_checksum" == "" ]]; then
echo "Error calculating checksum for $file_name. Skipping..."
@@ -31,7 +79,7 @@ function check_and_update_checksum() {
echo "Checksum for $file_name: $new_checksum"
# Compare and update the YAML file if checksums do not match
result=$?
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"

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@@ -1,304 +0,0 @@
package main
import (
"fmt"
"html/template"
"io/ioutil"
"os"
"github.com/microcosm-cc/bluemonday"
"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
}
// Ensure that all arbitrary text content is sanitized before display
for i, m := range models {
models[i].Name = bluemonday.StrictPolicy().Sanitize(m.Name)
models[i].Description = bluemonday.StrictPolicy().Sanitize(m.Description)
}
// 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
}
}

View File

@@ -1,16 +1,10 @@
# 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"
ignore:
- dependency-name: "github.com/mudler/LocalAI/pkg/grpc/proto"
- 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: "/"
@@ -29,95 +23,3 @@ updates:
schedule:
# Check for updates to GitHub Actions every weekday
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/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"

11
.github/labeler.yml vendored
View File

@@ -1,15 +1,6 @@
enhancement:
enhancements:
- head-branch: ['^feature', 'feature']
dependencies:
- any:
- changed-files:
- any-glob-to-any-file: 'Makefile'
- changed-files:
- any-glob-to-any-file: '*.mod'
- changed-files:
- any-glob-to-any-file: '*.sum'
kind/documentation:
- any:
- changed-files:

3
.github/release.yml vendored
View File

@@ -13,9 +13,6 @@ changelog:
labels:
- bug
- regression
- title: "🖧 P2P area"
labels:
- area/p2p
- title: Exciting New Features 🎉
labels:
- Semver-Minor

View File

@@ -9,17 +9,32 @@ jobs:
fail-fast: false
matrix:
include:
- repository: "ggml-org/llama.cpp"
- repository: "go-skynet/go-llama.cpp"
variable: "GOLLAMA_VERSION"
branch: "master"
- repository: "ggerganov/llama.cpp"
variable: "CPPLLAMA_VERSION"
branch: "master"
- repository: "go-skynet/go-ggml-transformers.cpp"
variable: "GOGGMLTRANSFORMERS_VERSION"
branch: "master"
- repository: "donomii/go-rwkv.cpp"
variable: "RWKV_VERSION"
branch: "main"
- repository: "ggerganov/whisper.cpp"
variable: "WHISPER_CPP_VERSION"
branch: "master"
- repository: "PABannier/bark.cpp"
variable: "BARKCPP_VERSION"
- repository: "go-skynet/go-bert.cpp"
variable: "BERT_VERSION"
branch: "master"
- repository: "go-skynet/bloomz.cpp"
variable: "BLOOMZ_VERSION"
branch: "main"
- repository: "leejet/stable-diffusion.cpp"
variable: "STABLEDIFFUSION_GGML_VERSION"
- repository: "nomic-ai/gpt4all"
variable: "GPT4ALL_VERSION"
branch: "main"
- repository: "mudler/go-ggllm.cpp"
variable: "GOGGLLM_VERSION"
branch: "master"
- repository: "mudler/go-stable-diffusion"
variable: "STABLEDIFFUSION_VERSION"
@@ -31,30 +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@v7
uses: peter-evans/create-pull-request@v6
with:
token: ${{ secrets.UPDATE_BOT_TOKEN }}
push-to-fork: ci-forks/LocalAI
commit-message: ':arrow_up: Update ${{ matrix.repository }}'
title: 'chore: :arrow_up: Update ${{ matrix.repository }} to `${{ steps.bump.outputs.commit }}`'
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@v7
uses: peter-evans/create-pull-request@v6
with:
token: ${{ secrets.UPDATE_BOT_TOKEN }}
push-to-fork: ci-forks/LocalAI
commit-message: ':arrow_up: Update docs version ${{ matrix.repository }}'
title: 'docs: :arrow_up: update docs version ${{ matrix.repository }}'
title: ':arrow_up: Update docs version ${{ matrix.repository }}'
branch: "update/docs"
body: Bump of ${{ matrix.repository }} version inside docs
signoff: true

View File

@@ -20,12 +20,12 @@ jobs:
run: |
sudo apt-get update
sudo apt-get install -y pip wget
sudo pip install --upgrade pip
sudo pip install --upgrade pip
pip install huggingface_hub
- name: 'Setup yq'
uses: dcarbone/install-yq-action@v1.3.1
uses: dcarbone/install-yq-action@v1.1.1
with:
version: 'v4.44.2'
version: 'v4.43.1'
download-compressed: true
force: true
@@ -36,12 +36,12 @@ jobs:
sudo chmod 777 /hf_cache
bash .github/checksum_checker.sh gallery/index.yaml
- name: Create Pull Request
uses: peter-evans/create-pull-request@v7
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'
title: 'models(gallery): :arrow_up: update checksum'
branch: "update/checksum"
body: Updating checksums in gallery/index.yaml
signoff: true

View File

@@ -14,7 +14,7 @@ jobs:
steps:
- name: Dependabot metadata
id: metadata
uses: dependabot/fetch-metadata@v2.3.0
uses: dependabot/fetch-metadata@v2.1.0
with:
github-token: "${{ secrets.GITHUB_TOKEN }}"
skip-commit-verification: true

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@v1.2.2
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@v1.2.2
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

@@ -2,10 +2,9 @@ name: 'generate and publish GRPC docker caches'
on:
workflow_dispatch:
schedule:
# daily at midnight
- cron: '0 0 * * *'
push:
branches:
- master
concurrency:
group: grpc-cache-${{ github.head_ref || github.ref }}-${{ github.repository }}
@@ -17,8 +16,8 @@ jobs:
matrix:
include:
- grpc-base-image: ubuntu:22.04
runs-on: 'arc-runner-set'
platforms: 'linux/amd64,linux/arm64'
runs-on: 'ubuntu-latest'
platforms: 'linux/amd64'
runs-on: ${{matrix.runs-on}}
steps:
- name: Release space from worker
@@ -76,7 +75,7 @@ jobs:
uses: actions/checkout@v4
- name: Cache GRPC
uses: docker/build-push-action@v6
uses: docker/build-push-action@v5
with:
builder: ${{ steps.buildx.outputs.name }}
# The build-args MUST be an EXACT match between the image cache and other workflow steps that want to use that cache.
@@ -85,11 +84,11 @@ jobs:
build-args: |
GRPC_BASE_IMAGE=${{ matrix.grpc-base-image }}
GRPC_MAKEFLAGS=--jobs=4 --output-sync=target
GRPC_VERSION=v1.65.0
GRPC_VERSION=v1.63.0
context: .
file: ./Dockerfile
cache-to: type=gha,ignore-error=true
cache-from: type=gha
target: grpc
platforms: ${{ matrix.platforms }}
push: false
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:2025.1.0-0-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

@@ -32,22 +32,21 @@ 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"
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-ffmpeg'
@@ -56,85 +55,76 @@ jobs:
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-22.04:6.1"
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: "intel/oneapi-basekit:2024.1.0-devel-ubuntu22.04"
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: "intel/oneapi-basekit:2024.1.0-devel-ubuntu22.04"
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: "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"
makeflags: "--jobs=4 --output-sync=target"

View File

@@ -13,79 +13,6 @@ concurrency:
cancel-in-progress: true
jobs:
hipblas-jobs:
uses: ./.github/workflows/image_build.yml
with:
tag-latest: ${{ matrix.tag-latest }}
tag-suffix: ${{ matrix.tag-suffix }}
ffmpeg: ${{ matrix.ffmpeg }}
image-type: ${{ matrix.image-type }}
build-type: ${{ matrix.build-type }}
cuda-major-version: ${{ matrix.cuda-major-version }}
cuda-minor-version: ${{ matrix.cuda-minor-version }}
platforms: ${{ matrix.platforms }}
runs-on: ${{ matrix.runs-on }}
base-image: ${{ matrix.base-image }}
grpc-base-image: ${{ matrix.grpc-base-image }}
aio: ${{ matrix.aio }}
makeflags: ${{ matrix.makeflags }}
latest-image: ${{ matrix.latest-image }}
latest-image-aio: ${{ matrix.latest-image-aio }}
secrets:
dockerUsername: ${{ secrets.DOCKERHUB_USERNAME }}
dockerPassword: ${{ secrets.DOCKERHUB_PASSWORD }}
quayUsername: ${{ secrets.LOCALAI_REGISTRY_USERNAME }}
quayPassword: ${{ secrets.LOCALAI_REGISTRY_PASSWORD }}
strategy:
# Pushing with all jobs in parallel
# eats the bandwidth of all the nodes
max-parallel: 2
matrix:
include:
- build-type: 'hipblas'
platforms: 'linux/amd64'
tag-latest: 'auto'
tag-suffix: '-hipblas-ffmpeg'
ffmpeg: 'true'
image-type: 'extras'
aio: "-aio-gpu-hipblas"
base-image: "rocm/dev-ubuntu-22.04:6.1"
grpc-base-image: "ubuntu:22.04"
latest-image: 'latest-gpu-hipblas'
latest-image-aio: 'latest-aio-gpu-hipblas'
runs-on: 'arc-runner-set'
makeflags: "--jobs=3 --output-sync=target"
- build-type: 'hipblas'
platforms: 'linux/amd64'
tag-latest: 'false'
tag-suffix: '-hipblas'
ffmpeg: 'false'
image-type: 'extras'
base-image: "rocm/dev-ubuntu-22.04:6.1"
grpc-base-image: "ubuntu:22.04"
runs-on: 'arc-runner-set'
makeflags: "--jobs=3 --output-sync=target"
- build-type: 'hipblas'
platforms: 'linux/amd64'
tag-latest: 'false'
tag-suffix: '-hipblas-ffmpeg-core'
ffmpeg: 'true'
image-type: 'core'
base-image: "rocm/dev-ubuntu-22.04:6.1"
grpc-base-image: "ubuntu:22.04"
runs-on: 'arc-runner-set'
makeflags: "--jobs=3 --output-sync=target"
latest-image: 'latest-gpu-hipblas-core'
- build-type: 'hipblas'
platforms: 'linux/amd64'
tag-latest: 'false'
tag-suffix: '-hipblas-core'
ffmpeg: 'false'
image-type: 'core'
base-image: "rocm/dev-ubuntu-22.04:6.1"
grpc-base-image: "ubuntu:22.04"
runs-on: 'arc-runner-set'
makeflags: "--jobs=3 --output-sync=target"
self-hosted-jobs:
uses: ./.github/workflows/image_build.yml
with:
@@ -112,7 +39,7 @@ jobs:
strategy:
# Pushing with all jobs in parallel
# eats the bandwidth of all the nodes
max-parallel: ${{ github.event_name != 'pull_request' && 5 || 8 }}
max-parallel: ${{ github.event_name != 'pull_request' && 2 || 4 }}
matrix:
include:
# Extra images
@@ -148,7 +75,7 @@ jobs:
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'
@@ -173,7 +100,7 @@ jobs:
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-suffix: '-cublas-cuda12-ffmpeg'
@@ -195,10 +122,33 @@ jobs:
base-image: "ubuntu:22.04"
runs-on: 'arc-runner-set'
makeflags: "--jobs=3 --output-sync=target"
- build-type: 'hipblas'
platforms: 'linux/amd64'
tag-latest: 'auto'
tag-suffix: '-hipblas-ffmpeg'
ffmpeg: 'true'
image-type: 'extras'
aio: "-aio-gpu-hipblas"
base-image: "rocm/dev-ubuntu-22.04:6.1"
grpc-base-image: "ubuntu:22.04"
latest-image: 'latest-gpu-hipblas'
latest-image-aio: 'latest-aio-gpu-hipblas'
runs-on: 'arc-runner-set'
makeflags: "--jobs=3 --output-sync=target"
- build-type: 'hipblas'
platforms: 'linux/amd64'
tag-latest: 'false'
tag-suffix: '-hipblas'
ffmpeg: 'false'
image-type: 'extras'
base-image: "rocm/dev-ubuntu-22.04:6.1"
grpc-base-image: "ubuntu:22.04"
runs-on: 'arc-runner-set'
makeflags: "--jobs=3 --output-sync=target"
- build-type: 'sycl_f16'
platforms: 'linux/amd64'
tag-latest: 'auto'
base-image: "quay.io/go-skynet/intel-oneapi-base:latest"
base-image: "intel/oneapi-basekit:2024.1.0-devel-ubuntu22.04"
grpc-base-image: "ubuntu:22.04"
tag-suffix: '-sycl-f16-ffmpeg'
ffmpeg: 'true'
@@ -211,7 +161,7 @@ jobs:
- build-type: 'sycl_f32'
platforms: 'linux/amd64'
tag-latest: 'auto'
base-image: "quay.io/go-skynet/intel-oneapi-base:latest"
base-image: "intel/oneapi-basekit:2024.1.0-devel-ubuntu22.04"
grpc-base-image: "ubuntu:22.04"
tag-suffix: '-sycl-f32-ffmpeg'
ffmpeg: 'true'
@@ -225,7 +175,7 @@ jobs:
- build-type: 'sycl_f16'
platforms: 'linux/amd64'
tag-latest: 'false'
base-image: "quay.io/go-skynet/intel-oneapi-base:latest"
base-image: "intel/oneapi-basekit:2024.1.0-devel-ubuntu22.04"
grpc-base-image: "ubuntu:22.04"
tag-suffix: '-sycl-f16-core'
ffmpeg: 'false'
@@ -235,7 +185,7 @@ jobs:
- build-type: 'sycl_f32'
platforms: 'linux/amd64'
tag-latest: 'false'
base-image: "quay.io/go-skynet/intel-oneapi-base:latest"
base-image: "intel/oneapi-basekit:2024.1.0-devel-ubuntu22.04"
grpc-base-image: "ubuntu:22.04"
tag-suffix: '-sycl-f32-core'
ffmpeg: 'false'
@@ -245,26 +195,44 @@ jobs:
- build-type: 'sycl_f16'
platforms: 'linux/amd64'
tag-latest: 'false'
base-image: "quay.io/go-skynet/intel-oneapi-base:latest"
base-image: "intel/oneapi-basekit:2024.1.0-devel-ubuntu22.04"
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"
latest-image: 'latest-gpu-intel-f16-core'
- build-type: 'sycl_f32'
platforms: 'linux/amd64'
tag-latest: 'false'
base-image: "quay.io/go-skynet/intel-oneapi-base:latest"
base-image: "intel/oneapi-basekit:2024.1.0-devel-ubuntu22.04"
grpc-base-image: "ubuntu:22.04"
tag-suffix: '-sycl-f32-ffmpeg-core'
ffmpeg: 'true'
image-type: 'core'
runs-on: 'arc-runner-set'
makeflags: "--jobs=3 --output-sync=target"
latest-image: 'latest-gpu-intel-f32-core'
- build-type: 'hipblas'
platforms: 'linux/amd64'
tag-latest: 'false'
tag-suffix: '-hipblas-ffmpeg-core'
ffmpeg: 'true'
image-type: 'core'
base-image: "rocm/dev-ubuntu-22.04:6.1"
grpc-base-image: "ubuntu:22.04"
runs-on: 'arc-runner-set'
makeflags: "--jobs=3 --output-sync=target"
- build-type: 'hipblas'
platforms: 'linux/amd64'
tag-latest: 'false'
tag-suffix: '-hipblas-core'
ffmpeg: 'false'
image-type: 'core'
base-image: "rocm/dev-ubuntu-22.04:6.1"
grpc-base-image: "ubuntu:22.04"
runs-on: 'arc-runner-set'
makeflags: "--jobs=3 --output-sync=target"
core-image-build:
uses: ./.github/workflows/image_build.yml
with:
@@ -283,29 +251,26 @@ jobs:
makeflags: ${{ matrix.makeflags }}
latest-image: ${{ matrix.latest-image }}
latest-image-aio: ${{ matrix.latest-image-aio }}
skip-drivers: ${{ matrix.skip-drivers }}
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'
platforms: 'linux/amd64'
tag-latest: 'auto'
tag-suffix: '-ffmpeg-core'
ffmpeg: 'true'
image-type: 'core'
base-image: "ubuntu:22.04"
runs-on: 'arc-runner-set'
runs-on: 'ubuntu-latest'
aio: "-aio-cpu"
latest-image: 'latest-cpu'
latest-image-aio: 'latest-aio-cpu'
makeflags: "--jobs=4 --output-sync=target"
skip-drivers: 'false'
- build-type: 'cublas'
cuda-major-version: "11"
cuda-minor-version: "7"
@@ -315,21 +280,19 @@ jobs:
ffmpeg: ''
image-type: 'core'
base-image: "ubuntu:22.04"
runs-on: 'arc-runner-set'
runs-on: 'ubuntu-latest'
makeflags: "--jobs=4 --output-sync=target"
skip-drivers: 'false'
- 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'
runs-on: 'ubuntu-latest'
makeflags: "--jobs=4 --output-sync=target"
skip-drivers: 'false'
- build-type: 'cublas'
cuda-major-version: "11"
cuda-minor-version: "7"
@@ -338,72 +301,17 @@ 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"
skip-drivers: 'false'
latest-image: 'latest-gpu-nvidia-cuda-12-core'
- 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"
skip-drivers: 'false'
makeflags: "--jobs=4 --output-sync=target"
latest-image: 'latest-gpu-nvidia-cuda-12-core'
- build-type: 'vulkan'
platforms: 'linux/amd64'
tag-latest: 'false'
tag-suffix: '-vulkan-ffmpeg-core'
ffmpeg: 'true'
image-type: 'core'
runs-on: 'arc-runner-set'
base-image: "ubuntu:22.04"
skip-drivers: 'false'
makeflags: "--jobs=4 --output-sync=target"
latest-image: 'latest-gpu-vulkan-core'
gh-runner:
uses: ./.github/workflows/image_build.yml
with:
tag-latest: ${{ matrix.tag-latest }}
tag-suffix: ${{ matrix.tag-suffix }}
ffmpeg: ${{ matrix.ffmpeg }}
image-type: ${{ matrix.image-type }}
build-type: ${{ matrix.build-type }}
cuda-major-version: ${{ matrix.cuda-major-version }}
cuda-minor-version: ${{ matrix.cuda-minor-version }}
platforms: ${{ matrix.platforms }}
runs-on: ${{ matrix.runs-on }}
aio: ${{ matrix.aio }}
base-image: ${{ matrix.base-image }}
grpc-base-image: ${{ matrix.grpc-base-image }}
makeflags: ${{ matrix.makeflags }}
latest-image: ${{ matrix.latest-image }}
latest-image-aio: ${{ matrix.latest-image-aio }}
skip-drivers: ${{ matrix.skip-drivers }}
secrets:
dockerUsername: ${{ secrets.DOCKERHUB_USERNAME }}
dockerPassword: ${{ secrets.DOCKERHUB_PASSWORD }}
quayUsername: ${{ secrets.LOCALAI_REGISTRY_USERNAME }}
quayPassword: ${{ secrets.LOCALAI_REGISTRY_PASSWORD }}
strategy:
matrix:
include:
- build-type: 'cublas'
cuda-major-version: "12"
cuda-minor-version: "0"
platforms: 'linux/arm64'
tag-latest: 'false'
tag-suffix: '-nvidia-l4t-arm64-core'
latest-image: 'latest-nvidia-l4t-arm64-core'
ffmpeg: 'true'
image-type: 'core'
base-image: "nvcr.io/nvidia/l4t-jetpack:r36.4.0"
runs-on: 'ubuntu-24.04-arm'
makeflags: "--jobs=4 --output-sync=target"
skip-drivers: 'true'

View File

@@ -19,11 +19,11 @@ 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'
@@ -49,10 +49,6 @@ on:
description: 'FFMPEG'
default: ''
type: string
skip-drivers:
description: 'Skip drivers by default'
default: 'false'
type: string
image-type:
description: 'Image type'
default: ''
@@ -140,7 +136,6 @@ jobs:
- name: Docker meta
id: meta
if: github.event_name != 'pull_request'
uses: docker/metadata-action@v5
with:
images: |
@@ -153,20 +148,7 @@ 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=${{ inputs.tag-suffix }}
- name: Docker meta AIO (quay.io)
if: inputs.aio != ''
id: meta_aio
@@ -192,6 +174,7 @@ jobs:
type=ref,event=branch
type=semver,pattern={{raw}}
flavor: |
latest=${{ inputs.tag-latest }}
suffix=${{ inputs.aio }}
- name: Set up QEMU
@@ -219,8 +202,7 @@ 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: ${{ steps.buildx.outputs.name }}
# The build-args MUST be an EXACT match between the image cache and other workflow steps that want to use that cache.
@@ -236,9 +218,8 @@ jobs:
BASE_IMAGE=${{ inputs.base-image }}
GRPC_BASE_IMAGE=${{ inputs.grpc-base-image || inputs.base-image }}
GRPC_MAKEFLAGS=--jobs=4 --output-sync=target
GRPC_VERSION=v1.65.0
GRPC_VERSION=v1.63.0
MAKEFLAGS=${{ inputs.makeflags }}
SKIP_DRIVERS=${{ inputs.skip-drivers }}
context: .
file: ./Dockerfile
cache-from: type=gha
@@ -246,43 +227,10 @@ jobs:
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=${{ inputs.makeflags }}
SKIP_DRIVERS=${{ inputs.skip-drivers }}
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
uses: docker/build-push-action@v5
with:
builder: ${{ steps.buildx.outputs.name }}
build-args: |
@@ -297,7 +245,7 @@ jobs:
- name: Build and push AIO image (dockerhub)
if: inputs.aio != ''
uses: docker/build-push-action@v6
uses: docker/build-push-action@v5
with:
builder: ${{ steps.buildx.outputs.name }}
build-args: |
@@ -310,11 +258,6 @@ jobs:
tags: ${{ steps.meta_aio_dockerhub.outputs.tags }}
labels: ${{ steps.meta_aio_dockerhub.outputs.labels }}
- name: Cleanup
run: |
docker builder prune -f
docker system prune --force --volumes --all
- name: Latest tag
# run this on branches, when it is a tag and there is a latest-image defined
if: github.event_name != 'pull_request' && inputs.latest-image != '' && github.ref_type == 'tag'
@@ -335,7 +278,7 @@ jobs:
docker pull quay.io/go-skynet/local-ai:${{ 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

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: gemma-3-12b-it
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: 'gemma-3-12b-it' # 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@v2.8.0
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@v3.19
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: gemma-3-12b-it
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@v2.8.0
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@v3.19
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: ${{ github.event.release.tag_name }}
steps:
- uses: mudler/localai-github-action@v1
with:
model: 'gemma-3-12b-it' # Any from models.localai.io, or from huggingface.com with: "huggingface://<repository>/file"
- name: Summarize
id: summarize
run: |
input="$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 +1,11 @@
name: Build and Release
on:
push:
branches:
- master
tags:
- 'v*'
pull_request:
- push
- pull_request
env:
GRPC_VERSION: v1.65.0
GRPC_VERSION: v1.63.0
permissions:
contents: write
@@ -19,8 +15,7 @@ concurrency:
cancel-in-progress: true
jobs:
build-linux-arm:
build-linux:
runs-on: ubuntu-latest
steps:
- name: Clone
@@ -34,129 +29,7 @@ jobs:
- 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: ${{ failure() }}
uses: mxschmitt/action-tmate@v3.19
with:
detached: true
connect-timeout-seconds: 180
limit-access-to-actor: true
build-linux:
runs-on: arc-runner-set
steps:
- name: Force Install GIT latest
run: |
sudo apt-get update \
&& sudo apt-get install -y software-properties-common \
&& sudo apt-get update \
&& sudo add-apt-repository -y ppa:git-core/ppa \
&& sudo apt-get update \
&& sudo apt-get install -y git
- name: Clone
uses: actions/checkout@v4
with:
submodules: true
- uses: actions/setup-go@v5
with:
go-version: '1.21.x'
cache: false
- name: Dependencies
run: |
sudo apt-get update
sudo apt-get install -y wget curl build-essential ffmpeg protobuf-compiler ccache upx-ucl gawk cmake libgmock-dev
- name: Intel Dependencies
run: |
wget -O- https://apt.repos.intel.com/intel-gpg-keys/GPG-PUB-KEY-INTEL-SW-PRODUCTS.PUB | gpg --dearmor | sudo tee /usr/share/keyrings/oneapi-archive-keyring.gpg > /dev/null
echo "deb [signed-by=/usr/share/keyrings/oneapi-archive-keyring.gpg] https://apt.repos.intel.com/oneapi all main" | sudo tee /etc/apt/sources.list.d/oneAPI.list
sudo apt update
sudo apt install -y intel-basekit
sudo apt-get install build-essential ffmpeg protobuf-compiler
- name: Install CUDA Dependencies
run: |
curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64/cuda-keyring_1.1-1_all.deb
@@ -164,32 +37,7 @@ jobs:
sudo apt-get update
sudo apt-get install -y cuda-nvcc-${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
CUDA_VERSION: 12-3
- name: Cache grpc
id: cache-grpc
uses: actions/cache@v4
@@ -200,26 +48,20 @@ jobs:
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 \
cd grpc && mkdir -p cmake/build && cd cmake/build && cmake -DgRPC_INSTALL=ON \
-DgRPC_BUILD_TESTS=OFF \
../.. && sudo make --jobs 5 --output-sync=target
- name: Install gRPC
run: |
cd grpc && cd cmake/build && sudo make --jobs 5 --output-sync=target install
# BACKEND_LIBS needed for gpu-workload: /opt/intel/oneapi/*/lib/libiomp5.so /opt/intel/oneapi/*/lib/libmkl_core.so /opt/intel/oneapi/*/lib/libmkl_core.so.2 /opt/intel/oneapi/*/lib/libmkl_intel_ilp64.so /opt/intel/oneapi/*/lib/libmkl_intel_ilp64.so.2 /opt/intel/oneapi/*/lib/libmkl_sycl_blas.so /opt/intel/oneapi/*/lib/libmkl_sycl_blas.so.4 /opt/intel/oneapi/*/lib/libmkl_tbb_thread.so /opt/intel/oneapi/*/lib/libmkl_tbb_thread.so.2 /opt/intel/oneapi/*/lib/libsycl.so /opt/intel/oneapi/*/lib/libsycl.so.7 /opt/intel/oneapi/*/lib/libsycl.so.7.1.0 /opt/rocm-*/lib/libamdhip64.so /opt/rocm-*/lib/libamdhip64.so.5 /opt/rocm-*/lib/libamdhip64.so.6 /opt/rocm-*/lib/libamdhip64.so.6.1.60100 /opt/rocm-*/lib/libhipblas.so /opt/rocm-*/lib/libhipblas.so.2 /opt/rocm-*/lib/libhipblas.so.2.1.60100 /opt/rocm-*/lib/librocblas.so /opt/rocm-*/lib/librocblas.so.4 /opt/rocm-*/lib/librocblas.so.4.1.60100 /usr/lib/x86_64-linux-gnu/libstdc++.so.6 /usr/lib/x86_64-linux-gnu/libOpenCL.so.1 /usr/lib/x86_64-linux-gnu/libOpenCL.so.1.0.0 /usr/lib/x86_64-linux-gnu/libm.so.6 /usr/lib/x86_64-linux-gnu/libgcc_s.so.1 /usr/lib/x86_64-linux-gnu/libc.so.6 /usr/lib/x86_64-linux-gnu/librt.so.1 /usr/local/cuda-*/targets/x86_64-linux/lib/libcublas.so /usr/local/cuda-*/targets/x86_64-linux/lib/libcublasLt.so /usr/local/cuda-*/targets/x86_64-linux/lib/libcudart.so /usr/local/cuda-*/targets/x86_64-linux/lib/stubs/libcuda.so
- name: Build
id: build
run: |
go install google.golang.org/grpc/cmd/protoc-gen-go-grpc@1958fcbe2ca8bd93af633f11e97d44e567e945af
go install google.golang.org/protobuf/cmd/protoc-gen-go@v1.34.2
go install google.golang.org/grpc/cmd/protoc-gen-go-grpc@latest
go install google.golang.org/protobuf/cmd/protoc-gen-go@latest
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
make dist
- uses: actions/upload-artifact@v4
with:
name: LocalAI-linux
@@ -230,17 +72,9 @@ jobs:
with:
files: |
release/*
- name: Setup tmate session if tests fail
if: ${{ failure() }}
uses: mxschmitt/action-tmate@v3.19
with:
detached: true
connect-timeout-seconds: 180
limit-access-to-actor: true
build-macOS-x86_64:
runs-on: macos-13
build-stablediffusion:
runs-on: ubuntu-latest
steps:
- name: Clone
uses: actions/checkout@v4
@@ -252,34 +86,18 @@ jobs:
cache: false
- name: Dependencies
run: |
brew install protobuf grpc
go install google.golang.org/grpc/cmd/protoc-gen-go-grpc@8ba23be9613c672d40ae261d2a1335d639bdd59b
go install google.golang.org/protobuf/cmd/protoc-gen-go@v1.34.0
- name: Build
id: build
sudo apt-get install -y --no-install-recommends libopencv-dev protobuf-compiler
go install google.golang.org/grpc/cmd/protoc-gen-go-grpc@latest
go install google.golang.org/protobuf/cmd/protoc-gen-go@latest
- name: Build stablediffusion
run: |
export C_INCLUDE_PATH=/usr/local/include
export CPLUS_INCLUDE_PATH=/usr/local/include
export PATH=$PATH:$GOPATH/bin
export SKIP_GRPC_BACKEND=backend-assets/grpc/whisper
make dist
make backend-assets/grpc/stablediffusion
mkdir -p release && cp backend-assets/grpc/stablediffusion release
- uses: actions/upload-artifact@v4
with:
name: LocalAI-MacOS-x86_64
name: stablediffusion
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: ${{ failure() }}
uses: mxschmitt/action-tmate@v3.19
with:
detached: true
connect-timeout-seconds: 180
limit-access-to-actor: true
build-macOS-arm64:
runs-on: macos-14
@@ -294,16 +112,15 @@ jobs:
cache: false
- name: Dependencies
run: |
brew install protobuf grpc libomp llvm
go install google.golang.org/grpc/cmd/protoc-gen-go-grpc@1958fcbe2ca8bd93af633f11e97d44e567e945af
go install google.golang.org/protobuf/cmd/protoc-gen-go@v1.34.2
brew install protobuf grpc
go install google.golang.org/grpc/cmd/protoc-gen-go-grpc@latest
go install google.golang.org/protobuf/cmd/protoc-gen-go@latest
- name: Build
id: build
run: |
export C_INCLUDE_PATH=/usr/local/include
export CPLUS_INCLUDE_PATH=/usr/local/include
export PATH=$PATH:$GOPATH/bin
export CC=/opt/homebrew/opt/llvm/bin/clang
make dist
- uses: actions/upload-artifact@v4
with:
@@ -315,10 +132,3 @@ jobs:
with:
files: |
release/*
- name: Setup tmate session if tests fail
if: ${{ failure() }}
uses: mxschmitt/action-tmate@v3.19
with:
detached: true
connect-timeout-seconds: 180
limit-access-to-actor: true

View File

@@ -18,7 +18,7 @@ jobs:
if: ${{ github.actor != 'dependabot[bot]' }}
- name: Run Gosec Security Scanner
if: ${{ github.actor != 'dependabot[bot]' }}
uses: securego/gosec@v2.22.3
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 ./...'

View File

@@ -19,7 +19,7 @@ jobs:
steps:
- name: Clone
uses: actions/checkout@v4
with:
with:
submodules: true
- name: Dependencies
run: |
@@ -29,18 +29,42 @@ jobs:
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
pip install --user grpcio-tools==1.63.0
- name: Test transformers
run: |
make --jobs=5 --output-sync=target -C backend/python/transformers
make --jobs=5 --output-sync=target -C backend/python/transformers test
tests-sentencetransformers:
runs-on: ubuntu-latest
steps:
- name: Clone
uses: actions/checkout@v4
with:
submodules: true
- name: Dependencies
run: |
sudo apt-get update
sudo apt-get install build-essential ffmpeg
# Install UV
curl -LsSf https://astral.sh/uv/install.sh | sh
sudo apt-get install -y ca-certificates cmake curl patch python3-pip
sudo apt-get install -y libopencv-dev
pip install --user grpcio-tools==1.63.0
- 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:
with:
submodules: true
- name: Dependencies
run: |
@@ -50,7 +74,7 @@ jobs:
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
pip install --user grpcio-tools==1.63.0
- name: Test rerankers
run: |
@@ -62,7 +86,7 @@ jobs:
steps:
- name: Clone
uses: actions/checkout@v4
with:
with:
submodules: true
- name: Dependencies
run: |
@@ -72,18 +96,64 @@ jobs:
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
pip install --user grpcio-tools==1.63.0
- name: Test diffusers
run: |
make --jobs=5 --output-sync=target -C backend/python/diffusers
make --jobs=5 --output-sync=target -C backend/python/diffusers test
# tests-transformers-musicgen:
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 grpcio-tools==1.63.0
- 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-transformers-musicgen:
runs-on: ubuntu-latest
steps:
- name: Clone
uses: actions/checkout@v4
with:
submodules: true
- name: Dependencies
run: |
sudo apt-get update
sudo apt-get install build-essential ffmpeg
# Install UV
curl -LsSf https://astral.sh/uv/install.sh | sh
sudo apt-get install -y ca-certificates cmake curl patch python3-pip
sudo apt-get install -y libopencv-dev
pip install --user grpcio-tools==1.63.0
- name: Test transformers-musicgen
run: |
make --jobs=5 --output-sync=target -C backend/python/transformers-musicgen
make --jobs=5 --output-sync=target -C backend/python/transformers-musicgen test
# tests-petals:
# runs-on: ubuntu-latest
# steps:
# - name: Clone
# uses: actions/checkout@v4
# with:
# with:
# submodules: true
# - name: Dependencies
# run: |
@@ -93,12 +163,14 @@ jobs:
# 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
# pip install --user grpcio-tools==1.63.0
# - name: Test transformers-musicgen
# - name: Test petals
# run: |
# make --jobs=5 --output-sync=target -C backend/python/transformers-musicgen
# make --jobs=5 --output-sync=target -C backend/python/transformers-musicgen test
# make --jobs=5 --output-sync=target -C backend/python/petals
# make --jobs=5 --output-sync=target -C backend/python/petals test
# tests-bark:
# runs-on: ubuntu-latest
@@ -145,7 +217,7 @@ jobs:
# df -h
# - name: Clone
# uses: actions/checkout@v4
# with:
# with:
# submodules: true
# - name: Dependencies
# run: |
@@ -155,14 +227,14 @@ jobs:
# 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
# pip install --user grpcio-tools==1.63.0
# - name: Test bark
# run: |
# make --jobs=5 --output-sync=target -C backend/python/bark
# make --jobs=5 --output-sync=target -C backend/python/bark test
# Below tests needs GPU. Commented out for now
# TODO: Re-enable as soon as we have GPU nodes
# tests-vllm:
@@ -170,7 +242,7 @@ jobs:
# steps:
# - name: Clone
# uses: actions/checkout@v4
# with:
# with:
# submodules: true
# - name: Dependencies
# run: |
@@ -180,18 +252,38 @@ jobs:
# 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
# pip install --user grpcio-tools==1.63.0
# - name: Test vllm
# run: |
# make --jobs=5 --output-sync=target -C backend/python/vllm
# make --jobs=5 --output-sync=target -C backend/python/vllm test
tests-vallex:
runs-on: ubuntu-latest
steps:
- name: Clone
uses: actions/checkout@v4
with:
submodules: true
- name: Dependencies
run: |
sudo apt-get update
sudo apt-get install build-essential ffmpeg
# Install UV
curl -LsSf https://astral.sh/uv/install.sh | sh
sudo apt-get install -y ca-certificates cmake curl patch python3-pip
sudo apt-get install -y libopencv-dev
pip install --user grpcio-tools==1.63.0
- name: Test vall-e-x
run: |
make --jobs=5 --output-sync=target -C backend/python/vall-e-x
make --jobs=5 --output-sync=target -C backend/python/vall-e-x test
tests-coqui:
runs-on: ubuntu-latest
steps:
- name: Clone
uses: actions/checkout@v4
with:
with:
submodules: true
- name: Dependencies
run: |
@@ -200,8 +292,8 @@ jobs:
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
pip install --user grpcio-tools==1.63.0
- 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
make --jobs=5 --output-sync=target -C backend/python/coqui test

View File

@@ -10,7 +10,7 @@ on:
- '*'
env:
GRPC_VERSION: v1.65.0
GRPC_VERSION: v1.63.0
concurrency:
group: ci-tests-${{ github.head_ref || github.ref }}-${{ github.repository }}
@@ -70,8 +70,7 @@ jobs:
- 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 curl 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 && \
@@ -94,20 +93,23 @@ jobs:
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
go install google.golang.org/protobuf/cmd/protoc-gen-go@latest
go install google.golang.org/grpc/cmd/protoc-gen-go-grpc@latest
# The python3-grpc-tools package in 22.04 is too old
pip install --user grpcio-tools
make -C backend/python/transformers
sudo rm -rfv /usr/bin/conda || true
PATH=$PATH:/opt/conda/bin make -C backend/python/sentencetransformers
# Pre-build piper before we start tests in order to have shared libraries in place
make sources/go-piper && \
GO_TAGS="tts" make -C sources/go-piper piper.o && \
sudo cp -rfv sources/go-piper/piper-phonemize/pi/lib/. /usr/lib/
sudo cp -rfv sources/go-piper/piper-phonemize/pi/lib/. /usr/lib/ && \
# Pre-build stable diffusion before we install a newer version of abseil (not compatible with stablediffusion-ncn)
PATH="$PATH:/root/go/bin" GO_TAGS="stablediffusion tts" GRPC_BACKENDS=backend-assets/grpc/stablediffusion make build
env:
CUDA_VERSION: 12-4
CUDA_VERSION: 12-3
- name: Cache grpc
id: cache-grpc
uses: actions/cache@v4
@@ -118,8 +120,7 @@ jobs:
if: steps.cache-grpc.outputs.cache-hit != 'true'
run: |
git clone --recurse-submodules -b ${{ env.GRPC_VERSION }} --depth 1 --jobs 5 --shallow-submodules https://github.com/grpc/grpc && \
cd grpc && sed -i "216i\ TESTONLY" "third_party/abseil-cpp/absl/container/CMakeLists.txt" && mkdir -p cmake/build && cd cmake/build && \
cmake -DgRPC_INSTALL=ON \
cd grpc && mkdir -p cmake/build && cd cmake/build && cmake -DgRPC_INSTALL=ON \
-DgRPC_BUILD_TESTS=OFF \
../.. && sudo make --jobs 5
- name: Install gRPC
@@ -127,10 +128,10 @@ jobs:
cd grpc && cd cmake/build && sudo make --jobs 5 install
- name: Test
run: |
PATH="$PATH:/root/go/bin" GO_TAGS="tts" make --jobs 5 --output-sync=target test
PATH="$PATH:/root/go/bin" GO_TAGS="stablediffusion tts" make --jobs 5 --output-sync=target test
- name: Setup tmate session if tests fail
if: ${{ failure() }}
uses: mxschmitt/action-tmate@v3.19
uses: mxschmitt/action-tmate@v3.18
with:
detached: true
connect-timeout-seconds: 180
@@ -175,26 +176,17 @@ jobs:
uses: actions/checkout@v4
with:
submodules: true
- name: Dependencies
run: |
# Install protoc
curl -L -s https://github.com/protocolbuffers/protobuf/releases/download/v26.1/protoc-26.1-linux-x86_64.zip -o protoc.zip && \
unzip -j -d /usr/local/bin protoc.zip bin/protoc && \
rm protoc.zip
go install google.golang.org/protobuf/cmd/protoc-gen-go@v1.34.2
go install google.golang.org/grpc/cmd/protoc-gen-go-grpc@1958fcbe2ca8bd93af633f11e97d44e567e945af
PATH="$PATH:$HOME/go/bin" make protogen-go
- name: Build images
run: |
docker build --build-arg FFMPEG=true --build-arg IMAGE_TYPE=extras --build-arg EXTRA_BACKENDS=rerankers --build-arg MAKEFLAGS="--jobs=5 --output-sync=target" -t local-ai:tests -f Dockerfile .
docker build --build-arg FFMPEG=true --build-arg IMAGE_TYPE=core --build-arg MAKEFLAGS="--jobs=5 --output-sync=target" -t local-ai:tests -f Dockerfile .
BASE_IMAGE=local-ai:tests DOCKER_AIO_IMAGE=local-ai-aio:test make docker-aio
- name: Test
run: |
PATH="$PATH:$HOME/go/bin" LOCALAI_MODELS_DIR=$PWD/models LOCALAI_IMAGE_TAG=test LOCALAI_IMAGE=local-ai-aio \
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: ${{ failure() }}
uses: mxschmitt/action-tmate@v3.19
uses: mxschmitt/action-tmate@v3.18
with:
detached: true
connect-timeout-seconds: 180
@@ -220,19 +212,18 @@ jobs:
run: go version
- name: Dependencies
run: |
brew install protobuf grpc make protoc-gen-go protoc-gen-go-grpc libomp llvm
pip install --user --no-cache-dir grpcio-tools
brew install protobuf grpc make protoc-gen-go protoc-gen-go-grpc
pip install --user grpcio-tools==1.63.0
- name: Test
run: |
export C_INCLUDE_PATH=/usr/local/include
export CPLUS_INCLUDE_PATH=/usr/local/include
export CC=/opt/homebrew/opt/llvm/bin/clang
# Used to run the newer GNUMake version from brew that supports --output-sync
export PATH="/opt/homebrew/opt/make/libexec/gnubin:$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
BUILD_TYPE="GITHUB_CI_HAS_BROKEN_METAL" CMAKE_ARGS="-DLLAMA_F16C=OFF -DLLAMA_AVX512=OFF -DLLAMA_AVX2=OFF -DLLAMA_FMA=OFF" make --jobs 4 --output-sync=target test
- name: Setup tmate session if tests fail
if: ${{ failure() }}
uses: mxschmitt/action-tmate@v3.19
uses: mxschmitt/action-tmate@v3.18
with:
detached: true
connect-timeout-seconds: 180

View File

@@ -13,19 +13,13 @@ jobs:
- 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
make swagger
- name: Create Pull Request
uses: peter-evans/create-pull-request@v7
uses: peter-evans/create-pull-request@v6
with:
token: ${{ secrets.UPDATE_BOT_TOKEN }}
push-to-fork: ci-forks/LocalAI

11
.gitignore vendored
View File

@@ -2,17 +2,14 @@
/sources/
__pycache__/
*.a
*.o
get-sources
prepare-sources
/backend/cpp/llama/grpc-server
/backend/cpp/llama/llama.cpp
/backend/cpp/llama-*
*.log
go-ggml-transformers
go-gpt2
go-rwkv
whisper.cpp
/bloomz
go-bert
@@ -42,7 +39,6 @@ backend-assets/*
!backend-assets/.keep
prepare
/ggml-metal.metal
docs/static/gallery.html
# Protobuf generated files
*.pb.go
@@ -53,7 +49,4 @@ docs/static/gallery.html
.scannerwork
# backend virtual environments
**/venv
# per-developer customization files for the development container
.devcontainer/customization/*
**/venv

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": "${workspaceFolder}/main.go",
"args": [
"api"
],
"env": {
"LOCALAI_LOG_LEVEL": "debug",
"LOCALAI_P2P": "true",
"LOCALAI_FEDERATED": "true"
},
"buildFlags": ["-tags", "p2p tts", "-v"],
"envFile": "${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

@@ -15,6 +15,8 @@ Thank you for your interest in contributing to LocalAI! We appreciate your time
- [Documentation](#documentation)
- [Community and Communication](#community-and-communication)
## Getting Started
### Prerequisites
@@ -52,7 +54,7 @@ If you find a bug, have a feature request, or encounter any issues, please check
## Coding Guidelines
- No specific coding guidelines at the moment. Please make sure the code can be tested. The most popular lint tools like [`golangci-lint`](https://golangci-lint.run) can help you here.
- No specific coding guidelines at the moment. Please make sure the code can be tested. The most popular lint tools like []`golangci-lint`](https://golangci-lint.run) can help you here.
## Testing
@@ -82,3 +84,5 @@ We are welcome the contribution of the documents, please open new PR or create a
- 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

@@ -1,88 +1,82 @@
ARG IMAGE_TYPE=extras
ARG BASE_IMAGE=ubuntu:22.04
ARG GRPC_BASE_IMAGE=${BASE_IMAGE}
ARG INTEL_BASE_IMAGE=${BASE_IMAGE}
# The requirements-core target is common to all images. It should not be placed in requirements-core unless every single build will use it.
FROM ${BASE_IMAGE} AS requirements-core
USER root
ARG GO_VERSION=1.22.6
ARG CMAKE_VERSION=3.26.4
ARG CMAKE_FROM_SOURCE=false
ARG GO_VERSION=1.21.7
ARG TARGETARCH
ARG TARGETVARIANT
ENV DEBIAN_FRONTEND=noninteractive
ENV EXTERNAL_GRPC_BACKENDS="coqui:/build/backend/python/coqui/run.sh,transformers:/build/backend/python/transformers/run.sh,rerankers:/build/backend/python/rerankers/run.sh,bark:/build/backend/python/bark/run.sh,diffusers:/build/backend/python/diffusers/run.sh,faster-whisper:/build/backend/python/faster-whisper/run.sh,kokoro:/build/backend/python/kokoro/run.sh,vllm:/build/backend/python/vllm/run.sh,exllama2:/build/backend/python/exllama2/run.sh"
ENV EXTERNAL_GRPC_BACKENDS="coqui:/build/backend/python/coqui/run.sh,huggingface-embeddings:/build/backend/python/sentencetransformers/run.sh,petals:/build/backend/python/petals/run.sh,transformers:/build/backend/python/transformers/run.sh,sentencetransformers:/build/backend/python/sentencetransformers/run.sh,rerankers:/build/backend/python/rerankers/run.sh,autogptq:/build/backend/python/autogptq/run.sh,bark:/build/backend/python/bark/run.sh,diffusers:/build/backend/python/diffusers/run.sh,exllama:/build/backend/python/exllama/run.sh,vall-e-x:/build/backend/python/vall-e-x/run.sh,vllm:/build/backend/python/vllm/run.sh,mamba:/build/backend/python/mamba/run.sh,exllama2:/build/backend/python/exllama2/run.sh,transformers-musicgen:/build/backend/python/transformers-musicgen/run.sh,parler-tts:/build/backend/python/parler-tts/run.sh"
ARG GO_TAGS="stablediffusion tinydream tts"
RUN apt-get update && \
apt-get install -y --no-install-recommends \
build-essential \
ccache \
ca-certificates \
curl libssl-dev \
cmake \
curl \
git \
git-lfs \
unzip upx-ucl && \
python3-pip \
python-is-python3 \
unzip && \
apt-get clean && \
rm -rf /var/lib/apt/lists/*
# Install CMake (the version in 22.04 is too old)
RUN <<EOT bash
if [ "${CMAKE_FROM_SOURCE}}" = "true" ]; then
curl -L -s https://github.com/Kitware/CMake/releases/download/v${CMAKE_VERSION}/cmake-${CMAKE_VERSION}.tar.gz -o cmake.tar.gz && tar xvf cmake.tar.gz && cd cmake-${CMAKE_VERSION} && ./configure && make && make install
else
apt-get update && \
apt-get install -y \
cmake && \
apt-get clean && \
rm -rf /var/lib/apt/lists/*
fi
EOT
rm -rf /var/lib/apt/lists/* && \
pip install --upgrade pip
# Install Go
RUN curl -L -s https://go.dev/dl/go${GO_VERSION}.linux-${TARGETARCH}.tar.gz | tar -C /usr/local -xz
ENV PATH=$PATH:/root/go/bin:/usr/local/go/bin
ENV PATH $PATH:/root/go/bin:/usr/local/go/bin
# Install grpc compilers
RUN go install google.golang.org/protobuf/cmd/protoc-gen-go@v1.34.2 && \
go install google.golang.org/grpc/cmd/protoc-gen-go-grpc@1958fcbe2ca8bd93af633f11e97d44e567e945af
RUN go install google.golang.org/protobuf/cmd/protoc-gen-go@latest && \
go install google.golang.org/grpc/cmd/protoc-gen-go-grpc@latest
# Install grpcio-tools (the version in 22.04 is too old)
RUN pip install --user grpcio-tools
COPY --chmod=644 custom-ca-certs/* /usr/local/share/ca-certificates/
RUN update-ca-certificates
RUN test -n "$TARGETARCH" \
|| (echo 'warn: missing $TARGETARCH, either set this `ARG` manually, or run using `docker buildkit`')
# Use the variables in subsequent instructions
RUN echo "Target Architecture: $TARGETARCH"
RUN echo "Target Variant: $TARGETVARIANT"
# Cuda
ENV PATH=/usr/local/cuda/bin:${PATH}
ENV PATH /usr/local/cuda/bin:${PATH}
# HipBLAS requirements
ENV PATH=/opt/rocm/bin:${PATH}
ENV PATH /opt/rocm/bin:${PATH}
# OpenBLAS requirements and stable diffusion
RUN apt-get update && \
apt-get install -y --no-install-recommends \
libopenblas-dev && \
libopenblas-dev \
libopencv-dev && \
apt-get clean && \
rm -rf /var/lib/apt/lists/*
# Set up OpenCV
RUN ln -s /usr/include/opencv4/opencv2 /usr/include/opencv2
WORKDIR /build
RUN test -n "$TARGETARCH" \
|| (echo 'warn: missing $TARGETARCH, either set this `ARG` manually, or run using `docker buildkit`')
###################################
###################################
# The requirements-extras target is for any builds with IMAGE_TYPE=extras. It should not be placed in this target unless every IMAGE_TYPE=extras build will use it
FROM requirements-core AS requirements-extras
# Install uv as a system package
RUN curl -LsSf https://astral.sh/uv/install.sh | UV_INSTALL_DIR=/usr/bin sh
RUN curl -LsSf https://astral.sh/uv/install.sh | sh
ENV PATH="/root/.cargo/bin:${PATH}"
RUN curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh -s -- -y
@@ -90,16 +84,10 @@ RUN apt-get update && \
apt-get install -y --no-install-recommends \
espeak-ng \
espeak \
python3-pip \
python-is-python3 \
python3-dev llvm \
python3-dev \
python3-venv && \
apt-get clean && \
rm -rf /var/lib/apt/lists/* && \
pip install --upgrade pip
# Install grpcio-tools (the version in 22.04 is too old)
RUN pip install --user grpcio-tools
rm -rf /var/lib/apt/lists/*
###################################
###################################
@@ -109,57 +97,32 @@ RUN pip install --user grpcio-tools
FROM requirements-${IMAGE_TYPE} AS requirements-drivers
ARG BUILD_TYPE
ARG CUDA_MAJOR_VERSION=12
ARG CUDA_MINOR_VERSION=0
ARG SKIP_DRIVERS=false
ARG CUDA_MAJOR_VERSION=11
ARG CUDA_MINOR_VERSION=7
ENV BUILD_TYPE=${BUILD_TYPE}
# Vulkan requirements
RUN <<EOT bash
if [ "${BUILD_TYPE}" = "vulkan" ] && [ "${SKIP_DRIVERS}" = "false" ]; 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 [ "${BUILD_TYPE}" = "cublas" ] && [ "${SKIP_DRIVERS}" = "false" ]; then
RUN 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" = "$TARGETARCH" ]; then
curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/arm64/cuda-keyring_1.1-1_all.deb
fi
software-properties-common && \
curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64/cuda-keyring_1.1-1_all.deb && \
dpkg -i cuda-keyring_1.1-1_all.deb && \
rm -f cuda-keyring_1.1-1_all.deb && \
apt-get update && \
apt-get install -y --no-install-recommends \
cuda-nvcc-${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}-${CUDA_MINOR_VERSION} && \
apt-get clean && \
rm -rf /var/lib/apt/lists/*
fi
EOT
rm -rf /var/lib/apt/lists/* \
; fi
# If we are building with clblas support, we need the libraries for the builds
RUN if [ "${BUILD_TYPE}" = "clblas" ] && [ "${SKIP_DRIVERS}" = "false" ]; then \
RUN if [ "${BUILD_TYPE}" = "clblas" ]; then \
apt-get update && \
apt-get install -y --no-install-recommends \
libclblast-dev && \
@@ -167,7 +130,7 @@ RUN if [ "${BUILD_TYPE}" = "clblas" ] && [ "${SKIP_DRIVERS}" = "false" ]; then \
rm -rf /var/lib/apt/lists/* \
; fi
RUN if [ "${BUILD_TYPE}" = "hipblas" ] && [ "${SKIP_DRIVERS}" = "false" ]; then \
RUN if [ "${BUILD_TYPE}" = "hipblas" ]; then \
apt-get update && \
apt-get install -y --no-install-recommends \
hipblas-dev \
@@ -182,26 +145,13 @@ RUN if [ "${BUILD_TYPE}" = "hipblas" ] && [ "${SKIP_DRIVERS}" = "false" ]; then
###################################
###################################
# Temporary workaround for Intel's repository to work correctly
# https://community.intel.com/t5/Intel-oneAPI-Math-Kernel-Library/APT-Repository-not-working-signatures-invalid/m-p/1599436/highlight/true#M36143
# This is a temporary workaround until Intel fixes their repository
FROM ${INTEL_BASE_IMAGE} AS intel
RUN wget -qO - https://repositories.intel.com/gpu/intel-graphics.key | \
gpg --yes --dearmor --output /usr/share/keyrings/intel-graphics.gpg
RUN echo "deb [arch=amd64 signed-by=/usr/share/keyrings/intel-graphics.gpg] https://repositories.intel.com/gpu/ubuntu jammy/lts/2350 unified" > /etc/apt/sources.list.d/intel-graphics.list
###################################
###################################
# The grpc target does one thing, it builds and installs GRPC. This is in it's own layer so that it can be effectively cached by CI.
# You probably don't need to change anything here, and if you do, make sure that CI is adjusted so that the cache continues to work.
FROM ${GRPC_BASE_IMAGE} AS grpc
# This is a bit of a hack, but it's required in order to be able to effectively cache this layer in CI
ARG GRPC_MAKEFLAGS="-j4 -Otarget"
ARG GRPC_VERSION=v1.65.0
ARG CMAKE_FROM_SOURCE=false
ARG CMAKE_VERSION=3.26.4
ARG GRPC_VERSION=v1.58.0
ENV MAKEFLAGS=${GRPC_MAKEFLAGS}
@@ -210,31 +160,18 @@ WORKDIR /build
RUN apt-get update && \
apt-get install -y --no-install-recommends \
ca-certificates \
build-essential curl libssl-dev \
build-essential \
cmake \
git && \
apt-get clean && \
rm -rf /var/lib/apt/lists/*
# Install CMake (the version in 22.04 is too old)
RUN <<EOT bash
if [ "${CMAKE_FROM_SOURCE}}" = "true" ]; then
curl -L -s https://github.com/Kitware/CMake/releases/download/v${CMAKE_VERSION}/cmake-${CMAKE_VERSION}.tar.gz -o cmake.tar.gz && tar xvf cmake.tar.gz && cd cmake-${CMAKE_VERSION} && ./configure && make && make install
else
apt-get update && \
apt-get install -y \
cmake && \
apt-get clean && \
rm -rf /var/lib/apt/lists/*
fi
EOT
# 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 && \
@@ -243,14 +180,13 @@ RUN git clone --recurse-submodules --jobs 4 -b ${GRPC_VERSION} --depth 1 --shall
###################################
###################################
# The builder-base target has the arguments, variables, and copies shared between full builder images and the uncompiled devcontainer
# The builder target compiles LocalAI. This target is not the target that will be uploaded to the registry.
# Adjustments to the build process should likely be made here.
FROM requirements-drivers AS builder
FROM requirements-drivers AS builder-base
ARG GO_TAGS="tts p2p"
ARG GO_TAGS="stablediffusion tts"
ARG GRPC_BACKENDS
ARG MAKEFLAGS
ARG LD_FLAGS="-s -w"
ENV GRPC_BACKENDS=${GRPC_BACKENDS}
ENV GO_TAGS=${GO_TAGS}
@@ -258,56 +194,31 @@ ENV MAKEFLAGS=${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
COPY . .
COPY .git .
RUN echo "GO_TAGS: $GO_TAGS"
RUN make prepare
# We need protoc installed, and the version in 22.04 is too old. We will create one as part installing the GRPC build below
# but that will also being in a newer version of absl which stablediffusion cannot compile with. This version of protoc is only
# here so that we can generate the grpc code for the stablediffusion build
RUN <<EOT bash
if [ "amd64" = "$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" = "$TARGETARCH" ]; then
curl -L -s https://github.com/protocolbuffers/protobuf/releases/download/v27.1/protoc-27.1-linux-aarch_64.zip -o protoc.zip && \
unzip -j -d /usr/local/bin protoc.zip bin/protoc && \
rm protoc.zip
fi
EOT
RUN curl -L -s https://github.com/protocolbuffers/protobuf/releases/download/v26.1/protoc-26.1-linux-x86_64.zip -o protoc.zip && \
unzip -j -d /usr/local/bin protoc.zip bin/protoc && \
rm protoc.zip
###################################
###################################
# The builder target compiles LocalAI. This target is not the target that will be uploaded to the registry.
# Adjustments to the build process should likely be made here.
FROM builder-base AS builder
# stablediffusion does not tolerate a newer version of abseil, build it first
RUN GRPC_BACKENDS=backend-assets/grpc/stablediffusion make build
# Install the pre-built GRPC
COPY --from=grpc /opt/grpc /usr/local
# Rebuild with defaults backends
WORKDIR /build
COPY . .
COPY .git .
RUN make prepare
## Build the binary
## If it's CUDA or hipblas, we want to skip some of the llama-compat backends to save space
## We only leave the most CPU-optimized variant and the fallback for the cublas/hipblas build
## (both will use CUDA or hipblas for the actual computation)
RUN if [ "${BUILD_TYPE}" = "cublas" ] || [ "${BUILD_TYPE}" = "hipblas" ]; then \
SKIP_GRPC_BACKEND="backend-assets/grpc/llama-cpp-avx512 backend-assets/grpc/llama-cpp-avx backend-assets/grpc/llama-cpp-avx2" make build; \
else \
make build; \
fi
RUN make build
RUN if [ ! -d "/build/sources/go-piper/piper-phonemize/pi/lib/" ]; then \
mkdir -p /build/sources/go-piper/piper-phonemize/pi/lib/ \
@@ -317,38 +228,6 @@ RUN if [ ! -d "/build/sources/go-piper/piper-phonemize/pi/lib/" ]; then \
###################################
###################################
# The devcontainer target is not used on CI. It is a target for developers to use locally -
# rather than copying files it mounts them locally and leaves building to the developer
FROM builder-base AS devcontainer
ARG FFMPEG
COPY --from=grpc /opt/grpc /usr/local
COPY .devcontainer-scripts /.devcontainer-scripts
# Add FFmpeg
RUN if [ "${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 wget
# For the devcontainer, leave apt functional in case additional devtools are needed at runtime.
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
@@ -365,7 +244,7 @@ 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
@@ -398,28 +277,39 @@ COPY --from=builder /build/local-ai ./
# Copy shared libraries for piper
COPY --from=builder /build/sources/go-piper/piper-phonemize/pi/lib/* /usr/lib/
# do not let stablediffusion rebuild (requires an older version of absl)
COPY --from=builder /build/backend-assets/grpc/stablediffusion ./backend-assets/grpc/stablediffusion
# 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 [[ ( "${IMAGE_TYPE}" == "extras ")]]; then \
apt-get -qq -y install espeak-ng \
; fi
RUN if [[ ( "${EXTRA_BACKENDS}" =~ "coqui" || -z "${EXTRA_BACKENDS}" ) && "$IMAGE_TYPE" == "extras" ]]; then \
make -C backend/python/coqui \
; fi && \
if [[ ( "${EXTRA_BACKENDS}" =~ "faster-whisper" || -z "${EXTRA_BACKENDS}" ) && "$IMAGE_TYPE" == "extras" ]]; then \
make -C backend/python/faster-whisper \
if [[ ( "${EXTRA_BACKENDS}" =~ "parler-tts" || -z "${EXTRA_BACKENDS}" ) && "$IMAGE_TYPE" == "extras" ]]; then \
make -C backend/python/parler-tts \
; fi && \
if [[ ( "${EXTRA_BACKENDS}" =~ "diffusers" || -z "${EXTRA_BACKENDS}" ) && "$IMAGE_TYPE" == "extras" ]]; then \
make -C backend/python/diffusers \
; fi && \
if [[ ( "${EXTRA_BACKENDS}" =~ "transformers-musicgen" || -z "${EXTRA_BACKENDS}" ) && "$IMAGE_TYPE" == "extras" ]]; then \
make -C backend/python/transformers-musicgen \
; fi && \
if [[ ( "${EXTRA_BACKENDS}" =~ "exllama1" || -z "${EXTRA_BACKENDS}" ) && "$IMAGE_TYPE" == "extras" ]]; then \
make -C backend/python/exllama \
; fi
RUN if [[ ( "${EXTRA_BACKENDS}" =~ "kokoro" || -z "${EXTRA_BACKENDS}" ) && "$IMAGE_TYPE" == "extras" ]]; then \
make -C backend/python/kokoro \
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}" =~ "petals" || -z "${EXTRA_BACKENDS}" ) && "$IMAGE_TYPE" == "extras" ]]; then \
make -C backend/python/petals \
; 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 \
@@ -431,11 +321,17 @@ RUN if [[ ( "${EXTRA_BACKENDS}" =~ "kokoro" || -z "${EXTRA_BACKENDS}" ) && "$IMA
RUN if [[ ( "${EXTRA_BACKENDS}" =~ "vllm" || -z "${EXTRA_BACKENDS}" ) && "$IMAGE_TYPE" == "extras" ]]; then \
make -C backend/python/vllm \
; fi && \
if [[ ( "${EXTRA_BACKENDS}" =~ "autogptq" || -z "${EXTRA_BACKENDS}" ) && "$IMAGE_TYPE" == "extras" ]]; then \
make -C backend/python/autogptq \
; fi && \
if [[ ( "${EXTRA_BACKENDS}" =~ "bark" || -z "${EXTRA_BACKENDS}" ) && "$IMAGE_TYPE" == "extras" ]]; then \
make -C backend/python/bark \
; fi && \
if [[ ( "${EXTRA_BACKENDS}" =~ "rerankers" || -z "${EXTRA_BACKENDS}" ) && "$IMAGE_TYPE" == "extras" ]]; then \
make -C backend/python/rerankers \
; fi && \
if [[ ( "${EXTRA_BACKENDS}" =~ "mamba" || -z "${EXTRA_BACKENDS}" ) && "$IMAGE_TYPE" == "extras" ]]; then \
make -C backend/python/mamba \
; fi
# Make sure the models directory exists
@@ -444,7 +340,7 @@ RUN mkdir -p /build/models
# Define the health check command
HEALTHCHECK --interval=1m --timeout=10m --retries=10 \
CMD curl -f ${HEALTHCHECK_ENDPOINT} || exit 1
VOLUME /build/models
EXPOSE 8080
ENTRYPOINT [ "/build/entrypoint.sh" ]

View File

@@ -1,6 +1,6 @@
MIT License
Copyright (c) 2023-2025 Ettore Di Giacinto (mudler@localai.io)
Copyright (c) 2023-2024 Ettore Di Giacinto (mudler@localai.io)
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal

592
Makefile
View File

@@ -3,43 +3,42 @@ GOTEST=$(GOCMD) test
GOVET=$(GOCMD) vet
BINARY_NAME=local-ai
DETECT_LIBS?=true
# llama.cpp versions
CPPLLAMA_VERSION?=6408210082cc0a61b992b487be7e2ff2efbb9e36
GOLLAMA_STABLE_VERSION?=2b57a8ae43e4699d3dc5d1496a1ccd42922993be
CPPLLAMA_VERSION?=dc685be46622a8fabfd57cfa804237c8f15679b8
# gpt4all version
GPT4ALL_REPO?=https://github.com/nomic-ai/gpt4all
GPT4ALL_VERSION?=27a8b020c36b0df8f8b82a252d261cda47cf44b8
# go-rwkv version
RWKV_REPO?=https://github.com/donomii/go-rwkv.cpp
RWKV_VERSION?=661e7ae26d442f5cfebd2a0881b44e8c55949ec6
# whisper.cpp version
WHISPER_REPO?=https://github.com/ggerganov/whisper.cpp
WHISPER_CPP_VERSION?=6266a9f9e56a5b925e9892acf650f3eb1245814d
WHISPER_CPP_VERSION?=4ef8d9f44eb402c528ab6d990ab50a9f4f666347
# bert.cpp version
BERT_VERSION?=6abe312cded14042f6b7c3cd8edf082713334a4d
# go-piper version
PIPER_REPO?=https://github.com/mudler/go-piper
PIPER_VERSION?=e10ca041a885d4a8f3871d52924b47792d5e5aa0
PIPER_VERSION?=9d0100873a7dbb0824dfea40e8cec70a1b110759
# bark.cpp
BARKCPP_REPO?=https://github.com/PABannier/bark.cpp.git
BARKCPP_VERSION?=v1.0.0
# stablediffusion version
STABLEDIFFUSION_VERSION?=4a3cd6aeae6f66ee57eae9a0075f8c58c3a6a38f
# stablediffusion.cpp (ggml)
STABLEDIFFUSION_GGML_REPO?=https://github.com/richiejp/stable-diffusion.cpp
STABLEDIFFUSION_GGML_VERSION?=53e3b17eb3d0b5760ced06a1f98320b68b34aaae
ONNX_VERSION?=1.20.0
ONNX_ARCH?=x64
ONNX_OS?=linux
# tinydream version
TINYDREAM_VERSION?=c04fa463ace9d9a6464313aa5f9cd0f953b6c057
export BUILD_TYPE?=
export STABLE_BUILD_TYPE?=$(BUILD_TYPE)
export CMAKE_ARGS?=
export BACKEND_LIBS?=
CGO_LDFLAGS?=
CGO_LDFLAGS_WHISPER?=
CGO_LDFLAGS_WHISPER+=-lggml
CUDA_LIBPATH?=/usr/local/cuda/lib64/
GO_TAGS?=
BUILD_ID?=
NATIVE?=false
TEST_DIR=/tmp/test
@@ -49,13 +48,13 @@ RANDOM := $(shell bash -c 'echo $$RANDOM')
VERSION?=$(shell git describe --always --tags || echo "dev" )
# go tool nm ./local-ai | grep Commit
LD_FLAGS?=-s -w
override LD_FLAGS += -X "github.com/mudler/LocalAI/internal.Version=$(VERSION)"
override LD_FLAGS += -X "github.com/mudler/LocalAI/internal.Commit=$(shell git rev-parse HEAD)"
LD_FLAGS?=
override LD_FLAGS += -X "github.com/go-skynet/LocalAI/internal.Version=$(VERSION)"
override LD_FLAGS += -X "github.com/go-skynet/LocalAI/internal.Commit=$(shell git rev-parse HEAD)"
OPTIONAL_TARGETS?=
export OS := $(shell uname -s)
OS := $(shell uname -s)
ARCH := $(shell uname -m)
GREEN := $(shell tput -Txterm setaf 2)
YELLOW := $(shell tput -Txterm setaf 3)
@@ -63,14 +62,6 @@ WHITE := $(shell tput -Txterm setaf 7)
CYAN := $(shell tput -Txterm setaf 6)
RESET := $(shell tput -Txterm sgr0)
UPX?=
# check if upx exists
ifeq (, $(shell which upx))
UPX=
else
UPX=$(shell which upx)
endif
# Default Docker bridge IP
E2E_BRIDGE_IP?=172.17.0.1
@@ -78,25 +69,7 @@ ifndef UNAME_S
UNAME_S := $(shell uname -s)
endif
# IF native is false, we add -DGGML_NATIVE=OFF to CMAKE_ARGS
ifeq ($(NATIVE),false)
CMAKE_ARGS+=-DGGML_NATIVE=OFF
endif
# Detect if we are running on arm64
ifneq (,$(findstring aarch64,$(shell uname -m)))
ONNX_ARCH=aarch64
endif
ifeq ($(OS),Darwin)
ONNX_OS=osx
ifneq (,$(findstring aarch64,$(shell uname -m)))
ONNX_ARCH=arm64
else ifneq (,$(findstring arm64,$(shell uname -m)))
ONNX_ARCH=arm64
else
ONNX_ARCH=x86_64
endif
ifeq ($(OSX_SIGNING_IDENTITY),)
OSX_SIGNING_IDENTITY := $(shell security find-identity -v -p codesigning | grep '"' | head -n 1 | sed -E 's/.*"(.*)"/\1/')
@@ -107,40 +80,27 @@ ifeq ($(OS),Darwin)
BUILD_TYPE=metal
# disable metal if on Darwin and any other value is explicitly passed.
else ifneq ($(BUILD_TYPE),metal)
CMAKE_ARGS+=-DGGML_METAL=OFF
export GGML_NO_ACCELERATE=1
export GGML_NO_METAL=1
CMAKE_ARGS+=-DLLAMA_METAL=OFF
export LLAMA_NO_ACCELERATE=1
endif
ifeq ($(BUILD_TYPE),metal)
# -lcblas removed: it seems to always be listed as a duplicate flag.
CGO_LDFLAGS += -framework Accelerate
endif
else
CGO_LDFLAGS_WHISPER+=-lgomp
endif
ifeq ($(BUILD_TYPE),openblas)
CGO_LDFLAGS+=-lopenblas
export GGML_OPENBLAS=1
export WHISPER_OPENBLAS=1
endif
ifeq ($(BUILD_TYPE),cublas)
CGO_LDFLAGS+=-lcublas -lcudart -L$(CUDA_LIBPATH)
export GGML_CUDA=1
CGO_LDFLAGS_WHISPER+=-L$(CUDA_LIBPATH)/stubs/ -lcuda -lcufft
endif
ifeq ($(BUILD_TYPE),vulkan)
CMAKE_ARGS+=-DGGML_VULKAN=1
endif
ifneq (,$(findstring sycl,$(BUILD_TYPE)))
export GGML_SYCL=1
endif
ifeq ($(BUILD_TYPE),sycl_f16)
export GGML_SYCL_F16=1
export LLAMA_CUBLAS=1
export WHISPER_CUDA=1
CGO_LDFLAGS_WHISPER+=-L$(CUDA_LIBPATH)/stubs/ -lcuda
endif
ifeq ($(BUILD_TYPE),hipblas)
@@ -149,27 +109,39 @@ ifeq ($(BUILD_TYPE),hipblas)
LD_LIBRARY_PATH ?= /opt/rocm/lib:/opt/rocm/llvm/lib
export CXX=$(ROCM_HOME)/llvm/bin/clang++
export CC=$(ROCM_HOME)/llvm/bin/clang
# llama-ggml has no hipblas support, so override it here.
export STABLE_BUILD_TYPE=
export GGML_HIP=1
GPU_TARGETS ?= gfx900,gfx906,gfx908,gfx940,gfx941,gfx942,gfx90a,gfx1030,gfx1031,gfx1100,gfx1101
export WHISPER_HIPBLAS=1
GPU_TARGETS ?= gfx900,gfx90a,gfx1030,gfx1031,gfx1100
AMDGPU_TARGETS ?= "$(GPU_TARGETS)"
CMAKE_ARGS+=-DGGML_HIP=ON -DAMDGPU_TARGETS="$(AMDGPU_TARGETS)" -DGPU_TARGETS="$(GPU_TARGETS)"
CMAKE_ARGS+=-DLLAMA_HIPBLAS=ON -DAMDGPU_TARGETS="$(AMDGPU_TARGETS)" -DGPU_TARGETS="$(GPU_TARGETS)"
CGO_LDFLAGS += -O3 --rtlib=compiler-rt -unwindlib=libgcc -lhipblas -lrocblas --hip-link -L${ROCM_HOME}/lib/llvm/lib
endif
ifeq ($(BUILD_TYPE),metal)
CGO_LDFLAGS+=-framework Foundation -framework Metal -framework MetalKit -framework MetalPerformanceShaders
export GGML_METAL=1
export LLAMA_METAL=1
export WHISPER_METAL=1
endif
ifeq ($(BUILD_TYPE),clblas)
CGO_LDFLAGS+=-lOpenCL -lclblast
export GGML_OPENBLAS=1
export WHISPER_CLBLAST=1
endif
# glibc-static or glibc-devel-static required
ifeq ($(STATIC),true)
LD_FLAGS+=-linkmode external -extldflags -static
LD_FLAGS=-linkmode external -extldflags -static
endif
ifeq ($(findstring stablediffusion,$(GO_TAGS)),stablediffusion)
# OPTIONAL_TARGETS+=go-stable-diffusion/libstablediffusion.a
OPTIONAL_GRPC+=backend-assets/grpc/stablediffusion
endif
ifeq ($(findstring tinydream,$(GO_TAGS)),tinydream)
# OPTIONAL_TARGETS+=go-tiny-dream/libtinydream.a
OPTIONAL_GRPC+=backend-assets/grpc/tinydream
endif
ifeq ($(findstring tts,$(GO_TAGS)),tts)
@@ -181,26 +153,16 @@ ifeq ($(findstring tts,$(GO_TAGS)),tts)
endif
ALL_GRPC_BACKENDS=backend-assets/grpc/huggingface
ALL_GRPC_BACKENDS+=backend-assets/grpc/bert-embeddings
ALL_GRPC_BACKENDS+=backend-assets/grpc/llama-cpp-avx
ALL_GRPC_BACKENDS+=backend-assets/grpc/llama-cpp-avx2
ALL_GRPC_BACKENDS+=backend-assets/grpc/llama-cpp-avx512
ALL_GRPC_BACKENDS+=backend-assets/grpc/llama-cpp-fallback
ALL_GRPC_BACKENDS+=backend-assets/grpc/llama-cpp-grpc
ALL_GRPC_BACKENDS+=backend-assets/util/llama-cpp-rpc-server
ALL_GRPC_BACKENDS+=backend-assets/grpc/llama-ggml
ALL_GRPC_BACKENDS+=backend-assets/grpc/gpt4all
ALL_GRPC_BACKENDS+=backend-assets/grpc/rwkv
ALL_GRPC_BACKENDS+=backend-assets/grpc/whisper
ifeq ($(ONNX_OS),linux)
ifeq ($(ONNX_ARCH),x64)
ALL_GRPC_BACKENDS+=backend-assets/grpc/bark-cpp
ALL_GRPC_BACKENDS+=backend-assets/grpc/stablediffusion-ggml
endif
endif
ALL_GRPC_BACKENDS+=backend-assets/grpc/local-store
ALL_GRPC_BACKENDS+=backend-assets/grpc/silero-vad
ALL_GRPC_BACKENDS+=$(OPTIONAL_GRPC)
# Use filter-out to remove the specified backends
ALL_GRPC_BACKENDS := $(filter-out $(SKIP_GRPC_BACKEND),$(ALL_GRPC_BACKENDS))
GRPC_BACKENDS?=$(ALL_GRPC_BACKENDS) $(OPTIONAL_GRPC)
TEST_PATHS?=./api/... ./pkg/... ./core/...
@@ -218,88 +180,93 @@ endif
all: help
## bark.cpp
sources/bark.cpp:
git clone --recursive $(BARKCPP_REPO) sources/bark.cpp && \
cd sources/bark.cpp && \
git checkout $(BARKCPP_VERSION) && \
git submodule update --init --recursive --depth 1 --single-branch
## BERT embeddings
sources/go-bert.cpp:
git clone --recurse-submodules https://github.com/go-skynet/go-bert.cpp sources/go-bert.cpp
cd sources/go-bert.cpp && git checkout -b build $(BERT_VERSION) && git submodule update --init --recursive --depth 1
sources/bark.cpp/build/libbark.a: sources/bark.cpp
cd sources/bark.cpp && \
mkdir -p build && \
cd build && \
cmake $(CMAKE_ARGS) .. && \
cmake --build . --config Release
sources/go-bert.cpp/libgobert.a: sources/go-bert.cpp
$(MAKE) -C sources/go-bert.cpp libgobert.a
backend/go/bark/libbark.a: sources/bark.cpp/build/libbark.a
$(MAKE) -C backend/go/bark libbark.a
## go-llama.cpp
sources/go-llama.cpp:
git clone --recurse-submodules https://github.com/go-skynet/go-llama.cpp sources/go-llama.cpp
cd sources/go-llama.cpp && git checkout -b build $(GOLLAMA_STABLE_VERSION) && git submodule update --init --recursive --depth 1
sources/go-llama.cpp/libbinding.a: sources/go-llama.cpp
$(MAKE) -C sources/go-llama.cpp BUILD_TYPE=$(STABLE_BUILD_TYPE) libbinding.a
## go-piper
sources/go-piper:
mkdir -p sources/go-piper
cd sources/go-piper && \
git init && \
git remote add origin $(PIPER_REPO) && \
git fetch origin && \
git checkout $(PIPER_VERSION) && \
git submodule update --init --recursive --depth 1 --single-branch
git clone --recurse-submodules https://github.com/mudler/go-piper sources/go-piper
cd sources/go-piper && git checkout -b build $(PIPER_VERSION) && git submodule update --init --recursive --depth 1
sources/go-piper/libpiper_binding.a: sources/go-piper
$(MAKE) -C sources/go-piper libpiper_binding.a example/main piper.o
## stablediffusion (ggml)
sources/stablediffusion-ggml.cpp:
git clone --recursive $(STABLEDIFFUSION_GGML_REPO) sources/stablediffusion-ggml.cpp && \
cd sources/stablediffusion-ggml.cpp && \
git checkout $(STABLEDIFFUSION_GGML_VERSION) && \
git submodule update --init --recursive --depth 1 --single-branch
## GPT4ALL
sources/gpt4all:
git clone --recurse-submodules $(GPT4ALL_REPO) sources/gpt4all
cd sources/gpt4all && git checkout -b build $(GPT4ALL_VERSION) && git submodule update --init --recursive --depth 1
backend/go/image/stablediffusion-ggml/libsd.a: sources/stablediffusion-ggml.cpp
$(MAKE) -C backend/go/image/stablediffusion-ggml build/libstable-diffusion.a
$(MAKE) -C backend/go/image/stablediffusion-ggml libsd.a
sources/gpt4all/gpt4all-bindings/golang/libgpt4all.a: sources/gpt4all
$(MAKE) -C sources/gpt4all/gpt4all-bindings/golang/ libgpt4all.a
backend-assets/grpc/stablediffusion-ggml: backend/go/image/stablediffusion-ggml/libsd.a backend-assets/grpc
$(MAKE) -C backend/go/image/stablediffusion-ggml CGO_LDFLAGS="$(CGO_LDFLAGS)" stablediffusion-ggml
## RWKV
sources/go-rwkv.cpp:
git clone --recurse-submodules $(RWKV_REPO) sources/go-rwkv.cpp
cd sources/go-rwkv.cpp && git checkout -b build $(RWKV_VERSION) && git submodule update --init --recursive --depth 1
sources/onnxruntime:
mkdir -p sources/onnxruntime
curl -L https://github.com/microsoft/onnxruntime/releases/download/v$(ONNX_VERSION)/onnxruntime-$(ONNX_OS)-$(ONNX_ARCH)-$(ONNX_VERSION).tgz -o sources/onnxruntime/onnxruntime-$(ONNX_OS)-$(ONNX_ARCH)-$(ONNX_VERSION).tgz
cd sources/onnxruntime && tar -xvf onnxruntime-$(ONNX_OS)-$(ONNX_ARCH)-$(ONNX_VERSION).tgz && rm onnxruntime-$(ONNX_OS)-$(ONNX_ARCH)-$(ONNX_VERSION).tgz
cd sources/onnxruntime && mv onnxruntime-$(ONNX_OS)-$(ONNX_ARCH)-$(ONNX_VERSION)/* ./
sources/go-rwkv.cpp/librwkv.a: sources/go-rwkv.cpp
cd sources/go-rwkv.cpp && cd rwkv.cpp && cmake . -DRWKV_BUILD_SHARED_LIBRARY=OFF && cmake --build . && cp librwkv.a ..
backend-assets/lib/libonnxruntime.so.1: backend-assets/lib sources/onnxruntime
cp -rfv sources/onnxruntime/lib/* backend-assets/lib/
ifeq ($(OS),Darwin)
mv backend-assets/lib/libonnxruntime.$(ONNX_VERSION).dylib backend-assets/lib/libonnxruntime.dylib
else
mv backend-assets/lib/libonnxruntime.so.$(ONNX_VERSION) backend-assets/lib/libonnxruntime.so.1
endif
## stable diffusion
sources/go-stable-diffusion:
git clone --recurse-submodules https://github.com/mudler/go-stable-diffusion sources/go-stable-diffusion
cd sources/go-stable-diffusion && git checkout -b build $(STABLEDIFFUSION_VERSION) && git submodule update --init --recursive --depth 1
sources/go-stable-diffusion/libstablediffusion.a: sources/go-stable-diffusion
CPATH="$(CPATH):/usr/include/opencv4" $(MAKE) -C sources/go-stable-diffusion libstablediffusion.a
## tiny-dream
sources/go-tiny-dream:
git clone --recurse-submodules https://github.com/M0Rf30/go-tiny-dream sources/go-tiny-dream
cd sources/go-tiny-dream && git checkout -b build $(TINYDREAM_VERSION) && git submodule update --init --recursive --depth 1
sources/go-tiny-dream/libtinydream.a: sources/go-tiny-dream
$(MAKE) -C sources/go-tiny-dream libtinydream.a
## whisper
sources/whisper.cpp:
mkdir -p sources/whisper.cpp
cd sources/whisper.cpp && \
git init && \
git remote add origin $(WHISPER_REPO) && \
git fetch origin && \
git checkout $(WHISPER_CPP_VERSION) && \
git submodule update --init --recursive --depth 1 --single-branch
git clone https://github.com/ggerganov/whisper.cpp sources/whisper.cpp
cd sources/whisper.cpp && git checkout -b build $(WHISPER_CPP_VERSION) && git submodule update --init --recursive --depth 1
sources/whisper.cpp/libwhisper.a: sources/whisper.cpp
cd sources/whisper.cpp && $(MAKE) libwhisper.a libggml.a
cd sources/whisper.cpp && $(MAKE) libwhisper.a
get-sources: sources/go-piper sources/stablediffusion-ggml.cpp sources/bark.cpp sources/whisper.cpp backend/cpp/llama/llama.cpp
get-sources: sources/go-llama.cpp sources/gpt4all sources/go-piper sources/go-rwkv.cpp sources/whisper.cpp sources/go-bert.cpp sources/go-stable-diffusion sources/go-tiny-dream
replace:
$(GOCMD) mod edit -replace github.com/donomii/go-rwkv.cpp=$(CURDIR)/sources/go-rwkv.cpp
$(GOCMD) mod edit -replace github.com/ggerganov/whisper.cpp=$(CURDIR)/sources/whisper.cpp
$(GOCMD) mod edit -replace github.com/ggerganov/whisper.cpp/bindings/go=$(CURDIR)/sources/whisper.cpp/bindings/go
$(GOCMD) mod edit -replace github.com/go-skynet/go-bert.cpp=$(CURDIR)/sources/go-bert.cpp
$(GOCMD) mod edit -replace github.com/M0Rf30/go-tiny-dream=$(CURDIR)/sources/go-tiny-dream
$(GOCMD) mod edit -replace github.com/mudler/go-piper=$(CURDIR)/sources/go-piper
$(GOCMD) mod edit -replace github.com/mudler/go-stable-diffusion=$(CURDIR)/sources/go-stable-diffusion
$(GOCMD) mod edit -replace github.com/nomic-ai/gpt4all/gpt4all-bindings/golang=$(CURDIR)/sources/gpt4all/gpt4all-bindings/golang
$(GOCMD) mod edit -replace github.com/go-skynet/go-llama.cpp=$(CURDIR)/sources/go-llama.cpp
dropreplace:
$(GOCMD) mod edit -dropreplace github.com/donomii/go-rwkv.cpp
$(GOCMD) mod edit -dropreplace github.com/ggerganov/whisper.cpp
$(GOCMD) mod edit -dropreplace github.com/ggerganov/whisper.cpp/bindings/go
$(GOCMD) mod edit -dropreplace github.com/go-skynet/go-bert.cpp
$(GOCMD) mod edit -dropreplace github.com/M0Rf30/go-tiny-dream
$(GOCMD) mod edit -dropreplace github.com/mudler/go-piper
$(GOCMD) mod edit -dropreplace github.com/mudler/go-stable-diffusion
$(GOCMD) mod edit -dropreplace github.com/nomic-ai/gpt4all/gpt4all-bindings/golang
$(GOCMD) mod edit -dropreplace github.com/go-skynet/go-llama.cpp
prepare-sources: get-sources replace
$(GOCMD) mod download
@@ -307,8 +274,14 @@ prepare-sources: get-sources replace
## GENERIC
rebuild: ## Rebuilds the project
$(GOCMD) clean -cache
$(MAKE) -C sources/go-llama.cpp clean
$(MAKE) -C sources/gpt4all/gpt4all-bindings/golang/ clean
$(MAKE) -C sources/go-rwkv.cpp clean
$(MAKE) -C sources/whisper.cpp clean
$(MAKE) -C sources/go-stable-diffusion clean
$(MAKE) -C sources/go-bert.cpp clean
$(MAKE) -C sources/go-piper clean
$(MAKE) -C sources/go-tiny-dream clean
$(MAKE) build
prepare: prepare-sources $(OPTIONAL_TARGETS)
@@ -321,9 +294,7 @@ clean: ## Remove build related file
rm -rf release/
rm -rf backend-assets/*
$(MAKE) -C backend/cpp/grpc clean
$(MAKE) -C backend/go/bark clean
$(MAKE) -C backend/cpp/llama clean
$(MAKE) -C backend/go/image/stablediffusion-ggml clean
rm -rf backend/cpp/llama-* || true
$(MAKE) dropreplace
$(MAKE) protogen-clean
@@ -334,70 +305,34 @@ clean-tests:
rm -rf test-dir
rm -rf core/http/backend-assets
clean-dc: clean
cp -r /build/backend-assets /workspace/backend-assets
## Build:
build: prepare backend-assets grpcs ## Build the project
$(info ${GREEN}I local-ai build info:${RESET})
$(info ${GREEN}I BUILD_TYPE: ${YELLOW}$(BUILD_TYPE)${RESET})
$(info ${GREEN}I GO_TAGS: ${YELLOW}$(GO_TAGS)${RESET})
$(info ${GREEN}I LD_FLAGS: ${YELLOW}$(LD_FLAGS)${RESET})
$(info ${GREEN}I UPX: ${YELLOW}$(UPX)${RESET})
ifneq ($(BACKEND_LIBS),)
$(MAKE) backend-assets/lib
cp -f $(BACKEND_LIBS) backend-assets/lib/
endif
CGO_LDFLAGS="$(CGO_LDFLAGS)" $(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o $(BINARY_NAME) ./
build-minimal:
BUILD_GRPC_FOR_BACKEND_LLAMA=true GRPC_BACKENDS="backend-assets/grpc/llama-cpp-avx2" GO_TAGS=p2p $(MAKE) build
BUILD_GRPC_FOR_BACKEND_LLAMA=true GRPC_BACKENDS="backend-assets/grpc/llama-cpp" GO_TAGS=none $(MAKE) build
build-api:
BUILD_GRPC_FOR_BACKEND_LLAMA=true BUILD_API_ONLY=true GO_TAGS=p2p $(MAKE) build
backend-assets/lib:
mkdir -p backend-assets/lib
BUILD_GRPC_FOR_BACKEND_LLAMA=true BUILD_API_ONLY=true GO_TAGS=none $(MAKE) build
dist:
$(MAKE) backend-assets/grpc/llama-cpp-avx2
ifeq ($(DETECT_LIBS),true)
scripts/prepare-libs.sh backend-assets/grpc/llama-cpp-avx2
endif
STATIC=true $(MAKE) backend-assets/grpc/llama-cpp-avx2
ifeq ($(OS),Darwin)
BUILD_TYPE=none $(MAKE) backend-assets/grpc/llama-cpp-fallback
$(info ${GREEN}I Skip CUDA build on MacOS${RESET})
else
$(MAKE) backend-assets/grpc/llama-cpp-cuda
$(MAKE) backend-assets/grpc/llama-cpp-hipblas
$(MAKE) backend-assets/grpc/llama-cpp-sycl_f16
$(MAKE) backend-assets/grpc/llama-cpp-sycl_f32
endif
GO_TAGS="tts p2p" $(MAKE) build
ifeq ($(DETECT_LIBS),true)
scripts/prepare-libs.sh backend-assets/grpc/piper
endif
GO_TAGS="tts p2p" STATIC=true $(MAKE) build
$(MAKE) build
mkdir -p release
# if BUILD_ID is empty, then we don't append it to the binary name
ifeq ($(BUILD_ID),)
cp $(BINARY_NAME) release/$(BINARY_NAME)-$(OS)-$(ARCH)
shasum -a 256 release/$(BINARY_NAME)-$(OS)-$(ARCH) > release/$(BINARY_NAME)-$(OS)-$(ARCH).sha256
else
cp $(BINARY_NAME) release/$(BINARY_NAME)-$(BUILD_ID)-$(OS)-$(ARCH)
shasum -a 256 release/$(BINARY_NAME)-$(BUILD_ID)-$(OS)-$(ARCH) > release/$(BINARY_NAME)-$(BUILD_ID)-$(OS)-$(ARCH).sha256
endif
dist-cross-linux-arm64:
CMAKE_ARGS="$(CMAKE_ARGS) -DGGML_NATIVE=off" GRPC_BACKENDS="backend-assets/grpc/llama-cpp-fallback backend-assets/grpc/llama-cpp-grpc backend-assets/util/llama-cpp-rpc-server" GO_TAGS="p2p" \
STATIC=true $(MAKE) build
mkdir -p release
# if BUILD_ID is empty, then we don't append it to the binary name
ifeq ($(BUILD_ID),)
cp $(BINARY_NAME) release/$(BINARY_NAME)-$(OS)-arm64
shasum -a 256 release/$(BINARY_NAME)-$(OS)-arm64 > release/$(BINARY_NAME)-$(OS)-arm64.sha256
else
cp $(BINARY_NAME) release/$(BINARY_NAME)-$(BUILD_ID)-$(OS)-arm64
shasum -a 256 release/$(BINARY_NAME)-$(BUILD_ID)-$(OS)-arm64 > release/$(BINARY_NAME)-$(BUILD_ID)-$(OS)-arm64.sha256
endif
osx-signed: build
@@ -410,10 +345,12 @@ run: prepare ## run local-ai
test-models/testmodel.ggml:
mkdir test-models
mkdir test-dir
wget -q https://huggingface.co/RichardErkhov/Qwen_-_Qwen2-1.5B-Instruct-gguf/resolve/main/Qwen2-1.5B-Instruct.Q2_K.gguf -O test-models/testmodel.ggml
wget -q https://huggingface.co/TheBloke/orca_mini_3B-GGML/resolve/main/orca-mini-3b.ggmlv3.q4_0.bin -O test-models/testmodel.ggml
wget -q https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-base.en.bin -O test-models/whisper-en
wget -q https://huggingface.co/mudler/all-MiniLM-L6-v2/resolve/main/ggml-model-q4_0.bin -O test-models/bert
wget -q https://cdn.openai.com/whisper/draft-20220913a/micro-machines.wav -O test-dir/audio.wav
wget -q https://huggingface.co/mudler/rwkv-4-raven-1.5B-ggml/resolve/main/RWKV-4-Raven-1B5-v11-Eng99%2525-Other1%2525-20230425-ctx4096_Q4_0.bin -O test-models/rwkv
wget -q https://raw.githubusercontent.com/saharNooby/rwkv.cpp/5eb8f09c146ea8124633ab041d9ea0b1f1db4459/rwkv/20B_tokenizer.json -O test-models/rwkv.tokenizer.json
cp tests/models_fixtures/* test-models
prepare-test: grpcs
@@ -422,10 +359,12 @@ prepare-test: grpcs
test: prepare test-models/testmodel.ggml grpcs
@echo 'Running tests'
export GO_TAGS="tts debug"
export GO_TAGS="tts stablediffusion debug"
$(MAKE) prepare-test
HUGGINGFACE_GRPC=$(abspath ./)/backend/python/transformers/run.sh TEST_DIR=$(abspath ./)/test-dir/ FIXTURES=$(abspath ./)/tests/fixtures CONFIG_FILE=$(abspath ./)/test-models/config.yaml MODELS_PATH=$(abspath ./)/test-models \
$(GOCMD) run github.com/onsi/ginkgo/v2/ginkgo --label-filter="!llama-gguf" --flake-attempts $(TEST_FLAKES) --fail-fast -v -r $(TEST_PATHS)
HUGGINGFACE_GRPC=$(abspath ./)/backend/python/sentencetransformers/run.sh TEST_DIR=$(abspath ./)/test-dir/ FIXTURES=$(abspath ./)/tests/fixtures CONFIG_FILE=$(abspath ./)/test-models/config.yaml MODELS_PATH=$(abspath ./)/test-models \
$(GOCMD) run github.com/onsi/ginkgo/v2/ginkgo --label-filter="!gpt4all && !llama && !llama-gguf" --flake-attempts $(TEST_FLAKES) --fail-fast -v -r $(TEST_PATHS)
$(MAKE) test-gpt4all
$(MAKE) test-llama
$(MAKE) test-llama-gguf
$(MAKE) test-tts
$(MAKE) test-stablediffusion
@@ -434,42 +373,50 @@ prepare-e2e:
mkdir -p $(TEST_DIR)
cp -rfv $(abspath ./tests/e2e-fixtures)/gpu.yaml $(TEST_DIR)/gpu.yaml
test -e $(TEST_DIR)/ggllm-test-model.bin || wget -q https://huggingface.co/TheBloke/CodeLlama-7B-Instruct-GGUF/resolve/main/codellama-7b-instruct.Q2_K.gguf -O $(TEST_DIR)/ggllm-test-model.bin
docker build --build-arg GRPC_BACKENDS="$(GRPC_BACKENDS)" --build-arg IMAGE_TYPE=core --build-arg BUILD_TYPE=$(BUILD_TYPE) --build-arg CUDA_MAJOR_VERSION=12 --build-arg CUDA_MINOR_VERSION=0 --build-arg FFMPEG=true -t localai-tests .
docker build --build-arg GRPC_BACKENDS="$(GRPC_BACKENDS)" --build-arg IMAGE_TYPE=core --build-arg BUILD_TYPE=$(BUILD_TYPE) --build-arg CUDA_MAJOR_VERSION=11 --build-arg CUDA_MINOR_VERSION=7 --build-arg FFMPEG=true -t localai-tests .
run-e2e-image:
ls -liah $(abspath ./tests/e2e-fixtures)
docker run -p 5390:8080 -e MODELS_PATH=/models -e THREADS=1 -e DEBUG=true -d --rm -v $(TEST_DIR):/models --gpus all --name e2e-tests-$(RANDOM) localai-tests
run-e2e-aio: protogen-go
run-e2e-aio:
@echo 'Running e2e AIO tests'
$(GOCMD) run github.com/onsi/ginkgo/v2/ginkgo --flake-attempts $(TEST_FLAKES) -v -r ./tests/e2e-aio
$(GOCMD) run github.com/onsi/ginkgo/v2/ginkgo --flake-attempts 5 -v -r ./tests/e2e-aio
test-e2e:
@echo 'Running e2e tests'
BUILD_TYPE=$(BUILD_TYPE) \
LOCALAI_API=http://$(E2E_BRIDGE_IP):5390/v1 \
$(GOCMD) run github.com/onsi/ginkgo/v2/ginkgo --flake-attempts $(TEST_FLAKES) -v -r ./tests/e2e
$(GOCMD) run github.com/onsi/ginkgo/v2/ginkgo --flake-attempts 5 -v -r ./tests/e2e
teardown-e2e:
rm -rf $(TEST_DIR) || true
docker stop $$(docker ps -q --filter ancestor=localai-tests)
test-gpt4all: prepare-test
TEST_DIR=$(abspath ./)/test-dir/ FIXTURES=$(abspath ./)/tests/fixtures CONFIG_FILE=$(abspath ./)/test-models/config.yaml MODELS_PATH=$(abspath ./)/test-models \
$(GOCMD) run github.com/onsi/ginkgo/v2/ginkgo --label-filter="gpt4all" --flake-attempts 5 -v -r $(TEST_PATHS)
test-llama: prepare-test
TEST_DIR=$(abspath ./)/test-dir/ FIXTURES=$(abspath ./)/tests/fixtures CONFIG_FILE=$(abspath ./)/test-models/config.yaml MODELS_PATH=$(abspath ./)/test-models \
$(GOCMD) run github.com/onsi/ginkgo/v2/ginkgo --label-filter="llama" --flake-attempts 5 -v -r $(TEST_PATHS)
test-llama-gguf: prepare-test
TEST_DIR=$(abspath ./)/test-dir/ FIXTURES=$(abspath ./)/tests/fixtures CONFIG_FILE=$(abspath ./)/test-models/config.yaml MODELS_PATH=$(abspath ./)/test-models \
$(GOCMD) run github.com/onsi/ginkgo/v2/ginkgo --label-filter="llama-gguf" --flake-attempts $(TEST_FLAKES) -v -r $(TEST_PATHS)
$(GOCMD) run github.com/onsi/ginkgo/v2/ginkgo --label-filter="llama-gguf" --flake-attempts 5 -v -r $(TEST_PATHS)
test-tts: prepare-test
TEST_DIR=$(abspath ./)/test-dir/ FIXTURES=$(abspath ./)/tests/fixtures CONFIG_FILE=$(abspath ./)/test-models/config.yaml MODELS_PATH=$(abspath ./)/test-models \
$(GOCMD) run github.com/onsi/ginkgo/v2/ginkgo --label-filter="tts" --flake-attempts $(TEST_FLAKES) -v -r $(TEST_PATHS)
$(GOCMD) run github.com/onsi/ginkgo/v2/ginkgo --label-filter="tts" --flake-attempts 1 -v -r $(TEST_PATHS)
test-stablediffusion: prepare-test
TEST_DIR=$(abspath ./)/test-dir/ FIXTURES=$(abspath ./)/tests/fixtures CONFIG_FILE=$(abspath ./)/test-models/config.yaml MODELS_PATH=$(abspath ./)/test-models \
$(GOCMD) run github.com/onsi/ginkgo/v2/ginkgo --label-filter="stablediffusion" --flake-attempts $(TEST_FLAKES) -v -r $(TEST_PATHS)
$(GOCMD) run github.com/onsi/ginkgo/v2/ginkgo --label-filter="stablediffusion" --flake-attempts 1 -v -r $(TEST_PATHS)
test-stores: backend-assets/grpc/local-store
mkdir -p tests/integration/backend-assets/grpc
cp -f backend-assets/grpc/local-store tests/integration/backend-assets/grpc/
$(GOCMD) run github.com/onsi/ginkgo/v2/ginkgo --label-filter="stores" --flake-attempts $(TEST_FLAKES) -v -r tests/integration
$(GOCMD) run github.com/onsi/ginkgo/v2/ginkgo --label-filter="stores" --flake-attempts 1 -v -r tests/integration
test-container:
docker build --target requirements -t local-ai-test-container .
@@ -496,7 +443,7 @@ protogen-clean: protogen-go-clean protogen-python-clean
.PHONY: protogen-go
protogen-go:
mkdir -p pkg/grpc/proto
protoc --experimental_allow_proto3_optional -Ibackend/ --go_out=pkg/grpc/proto/ --go_opt=paths=source_relative --go-grpc_out=pkg/grpc/proto/ --go-grpc_opt=paths=source_relative \
protoc -Ibackend/ --go_out=pkg/grpc/proto/ --go_opt=paths=source_relative --go-grpc_out=pkg/grpc/proto/ --go-grpc_opt=paths=source_relative \
backend/backend.proto
.PHONY: protogen-go-clean
@@ -505,10 +452,18 @@ protogen-go-clean:
$(RM) bin/*
.PHONY: protogen-python
protogen-python: bark-protogen coqui-protogen diffusers-protogen exllama2-protogen rerankers-protogen transformers-protogen kokoro-protogen vllm-protogen faster-whisper-protogen
protogen-python: autogptq-protogen bark-protogen coqui-protogen diffusers-protogen exllama-protogen exllama2-protogen mamba-protogen petals-protogen rerankers-protogen sentencetransformers-protogen transformers-protogen parler-tts-protogen transformers-musicgen-protogen vall-e-x-protogen vllm-protogen
.PHONY: protogen-python-clean
protogen-python-clean: bark-protogen-clean coqui-protogen-clean diffusers-protogen-clean exllama2-protogen-clean rerankers-protogen-clean transformers-protogen-clean kokoro-protogen-clean vllm-protogen-clean faster-whisper-protogen-clean
protogen-python-clean: autogptq-protogen-clean bark-protogen-clean coqui-protogen-clean diffusers-protogen-clean exllama-protogen-clean exllama2-protogen-clean mamba-protogen-clean petals-protogen-clean sentencetransformers-protogen-clean rerankers-protogen-clean transformers-protogen-clean transformers-musicgen-protogen-clean parler-tts-protogen-clean vall-e-x-protogen-clean vllm-protogen-clean
.PHONY: autogptq-protogen
autogptq-protogen:
$(MAKE) -C backend/python/autogptq protogen
.PHONY: autogptq-protogen-clean
autogptq-protogen-clean:
$(MAKE) -C backend/python/autogptq protogen-clean
.PHONY: bark-protogen
bark-protogen:
@@ -534,13 +489,13 @@ diffusers-protogen:
diffusers-protogen-clean:
$(MAKE) -C backend/python/diffusers protogen-clean
.PHONY: faster-whisper-protogen
faster-whisper-protogen:
$(MAKE) -C backend/python/faster-whisper protogen
.PHONY: exllama-protogen
exllama-protogen:
$(MAKE) -C backend/python/exllama protogen
.PHONY: faster-whisper-protogen-clean
faster-whisper-protogen-clean:
$(MAKE) -C backend/python/faster-whisper protogen-clean
.PHONY: exllama-protogen-clean
exllama-protogen-clean:
$(MAKE) -C backend/python/exllama protogen-clean
.PHONY: exllama2-protogen
exllama2-protogen:
@@ -550,6 +505,22 @@ exllama2-protogen:
exllama2-protogen-clean:
$(MAKE) -C backend/python/exllama2 protogen-clean
.PHONY: mamba-protogen
mamba-protogen:
$(MAKE) -C backend/python/mamba protogen
.PHONY: mamba-protogen-clean
mamba-protogen-clean:
$(MAKE) -C backend/python/mamba protogen-clean
.PHONY: petals-protogen
petals-protogen:
$(MAKE) -C backend/python/petals protogen
.PHONY: petals-protogen-clean
petals-protogen-clean:
$(MAKE) -C backend/python/petals protogen-clean
.PHONY: rerankers-protogen
rerankers-protogen:
$(MAKE) -C backend/python/rerankers protogen
@@ -558,6 +529,14 @@ rerankers-protogen:
rerankers-protogen-clean:
$(MAKE) -C backend/python/rerankers protogen-clean
.PHONY: sentencetransformers-protogen
sentencetransformers-protogen:
$(MAKE) -C backend/python/sentencetransformers protogen
.PHONY: sentencetransformers-protogen-clean
sentencetransformers-protogen-clean:
$(MAKE) -C backend/python/sentencetransformers protogen-clean
.PHONY: transformers-protogen
transformers-protogen:
$(MAKE) -C backend/python/transformers protogen
@@ -566,13 +545,29 @@ transformers-protogen:
transformers-protogen-clean:
$(MAKE) -C backend/python/transformers protogen-clean
.PHONY: kokoro-protogen
kokoro-protogen:
$(MAKE) -C backend/python/kokoro protogen
.PHONY: parler-tts-protogen
parler-tts-protogen:
$(MAKE) -C backend/python/parler-tts protogen
.PHONY: kokoro-protogen-clean
kokoro-protogen-clean:
$(MAKE) -C backend/python/kokoro protogen-clean
.PHONY: parler-tts-protogen-clean
parler-tts-protogen-clean:
$(MAKE) -C backend/python/parler-tts protogen-clean
.PHONY: transformers-musicgen-protogen
transformers-musicgen-protogen:
$(MAKE) -C backend/python/transformers-musicgen protogen
.PHONY: transformers-musicgen-protogen-clean
transformers-musicgen-protogen-clean:
$(MAKE) -C backend/python/transformers-musicgen protogen-clean
.PHONY: vall-e-x-protogen
vall-e-x-protogen:
$(MAKE) -C backend/python/vall-e-x protogen
.PHONY: vall-e-x-protogen-clean
vall-e-x-protogen-clean:
$(MAKE) -C backend/python/vall-e-x protogen-clean
.PHONY: vllm-protogen
vllm-protogen:
@@ -585,14 +580,20 @@ vllm-protogen-clean:
## GRPC
# Note: it is duplicated in the Dockerfile
prepare-extra-conda-environments: protogen-python
$(MAKE) -C backend/python/autogptq
$(MAKE) -C backend/python/bark
$(MAKE) -C backend/python/coqui
$(MAKE) -C backend/python/diffusers
$(MAKE) -C backend/python/faster-whisper
$(MAKE) -C backend/python/vllm
$(MAKE) -C backend/python/mamba
$(MAKE) -C backend/python/sentencetransformers
$(MAKE) -C backend/python/rerankers
$(MAKE) -C backend/python/transformers
$(MAKE) -C backend/python/kokoro
$(MAKE) -C backend/python/transformers-musicgen
$(MAKE) -C backend/python/parler-tts
$(MAKE) -C backend/python/vall-e-x
$(MAKE) -C backend/python/exllama
$(MAKE) -C backend/python/petals
$(MAKE) -C backend/python/exllama2
prepare-test-extra: protogen-python
@@ -613,14 +614,25 @@ backend-assets/espeak-ng-data: sources/go-piper sources/go-piper/libpiper_bindin
mkdir -p backend-assets/espeak-ng-data
@cp -rf sources/go-piper/piper-phonemize/pi/share/espeak-ng-data/. backend-assets/espeak-ng-data
backend-assets/gpt4all: sources/gpt4all sources/gpt4all/gpt4all-bindings/golang/libgpt4all.a
mkdir -p backend-assets/gpt4all
@cp sources/gpt4all/gpt4all-bindings/golang/buildllm/*.so backend-assets/gpt4all/ || true
@cp sources/gpt4all/gpt4all-bindings/golang/buildllm/*.dylib backend-assets/gpt4all/ || true
@cp sources/gpt4all/gpt4all-bindings/golang/buildllm/*.dll backend-assets/gpt4all/ || true
backend-assets/grpc: protogen-go replace
mkdir -p backend-assets/grpc
backend-assets/grpc/bert-embeddings: sources/go-bert.cpp sources/go-bert.cpp/libgobert.a backend-assets/grpc
CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(CURDIR)/sources/go-bert.cpp LIBRARY_PATH=$(CURDIR)/sources/go-bert.cpp \
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/bert-embeddings ./backend/go/llm/bert/
backend-assets/grpc/gpt4all: sources/gpt4all sources/gpt4all/gpt4all-bindings/golang/libgpt4all.a backend-assets/gpt4all backend-assets/grpc
CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(CURDIR)/sources/gpt4all/gpt4all-bindings/golang/ LIBRARY_PATH=$(CURDIR)/sources/gpt4all/gpt4all-bindings/golang/ \
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/gpt4all ./backend/go/llm/gpt4all/
backend-assets/grpc/huggingface: backend-assets/grpc
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/huggingface ./backend/go/llm/langchain/
ifneq ($(UPX),)
$(UPX) backend-assets/grpc/huggingface
endif
backend/cpp/llama/llama.cpp:
LLAMA_VERSION=$(CPPLLAMA_VERSION) $(MAKE) -C backend/cpp/llama llama.cpp
@@ -647,114 +659,64 @@ else
LLAMA_VERSION=$(CPPLLAMA_VERSION) $(MAKE) -C backend/cpp/${VARIANT} grpc-server
endif
# This target is for manually building a variant with-auto detected flags
backend-assets/grpc/llama-cpp: backend-assets/grpc backend/cpp/llama/llama.cpp
cp -rf backend/cpp/llama backend/cpp/llama-cpp
$(MAKE) -C backend/cpp/llama-cpp purge
$(info ${GREEN}I llama-cpp build info:avx2${RESET})
$(MAKE) VARIANT="llama-cpp" build-llama-cpp-grpc-server
cp -rfv backend/cpp/llama-cpp/grpc-server backend-assets/grpc/llama-cpp
backend-assets/grpc/llama-cpp-avx2: backend-assets/grpc backend/cpp/llama/llama.cpp
backend-assets/grpc/llama-cpp-avx2: backend-assets/grpc
cp -rf backend/cpp/llama backend/cpp/llama-avx2
$(MAKE) -C backend/cpp/llama-avx2 purge
$(info ${GREEN}I llama-cpp build info:avx2${RESET})
CMAKE_ARGS="$(CMAKE_ARGS) -DGGML_AVX=on -DGGML_AVX2=on -DGGML_AVX512=off -DGGML_FMA=on -DGGML_F16C=on" $(MAKE) VARIANT="llama-avx2" build-llama-cpp-grpc-server
CMAKE_ARGS="$(CMAKE_ARGS) -DLLAMA_AVX=on -DLLAMA_AVX2=on -DLLAMA_AVX512=off -DLLAMA_FMA=on -DLLAMA_F16C=on" $(MAKE) VARIANT="llama-avx2" build-llama-cpp-grpc-server
cp -rfv backend/cpp/llama-avx2/grpc-server backend-assets/grpc/llama-cpp-avx2
backend-assets/grpc/llama-cpp-avx512: backend-assets/grpc backend/cpp/llama/llama.cpp
cp -rf backend/cpp/llama backend/cpp/llama-avx512
$(MAKE) -C backend/cpp/llama-avx512 purge
$(info ${GREEN}I llama-cpp build info:avx512${RESET})
CMAKE_ARGS="$(CMAKE_ARGS) -DGGML_AVX=on -DGGML_AVX2=off -DGGML_AVX512=on -DGGML_FMA=on -DGGML_F16C=on" $(MAKE) VARIANT="llama-avx512" build-llama-cpp-grpc-server
cp -rfv backend/cpp/llama-avx512/grpc-server backend-assets/grpc/llama-cpp-avx512
backend-assets/grpc/llama-cpp-avx: backend-assets/grpc backend/cpp/llama/llama.cpp
backend-assets/grpc/llama-cpp-avx: backend-assets/grpc
cp -rf backend/cpp/llama backend/cpp/llama-avx
$(MAKE) -C backend/cpp/llama-avx purge
$(info ${GREEN}I llama-cpp build info:avx${RESET})
CMAKE_ARGS="$(CMAKE_ARGS) -DGGML_AVX=on -DGGML_AVX2=off -DGGML_AVX512=off -DGGML_FMA=off -DGGML_F16C=off" $(MAKE) VARIANT="llama-avx" build-llama-cpp-grpc-server
CMAKE_ARGS="$(CMAKE_ARGS) -DLLAMA_AVX=on -DLLAMA_AVX2=off -DLLAMA_AVX512=off -DLLAMA_FMA=off -DLLAMA_F16C=off" $(MAKE) VARIANT="llama-avx" build-llama-cpp-grpc-server
cp -rfv backend/cpp/llama-avx/grpc-server backend-assets/grpc/llama-cpp-avx
backend-assets/grpc/llama-cpp-fallback: backend-assets/grpc backend/cpp/llama/llama.cpp
backend-assets/grpc/llama-cpp-fallback: backend-assets/grpc
cp -rf backend/cpp/llama backend/cpp/llama-fallback
$(MAKE) -C backend/cpp/llama-fallback purge
$(info ${GREEN}I llama-cpp build info:fallback${RESET})
CMAKE_ARGS="$(CMAKE_ARGS) -DGGML_AVX=off -DGGML_AVX2=off -DGGML_AVX512=off -DGGML_FMA=off -DGGML_F16C=off" $(MAKE) VARIANT="llama-fallback" build-llama-cpp-grpc-server
CMAKE_ARGS="$(CMAKE_ARGS) -DLLAMA_AVX=off -DLLAMA_AVX2=off -DLLAMA_AVX512=off -DLLAMA_FMA=off -DLLAMA_F16C=off" $(MAKE) VARIANT="llama-fallback" build-llama-cpp-grpc-server
cp -rfv backend/cpp/llama-fallback/grpc-server backend-assets/grpc/llama-cpp-fallback
# TODO: every binary should have its own folder instead, so can have different metal implementations
ifeq ($(BUILD_TYPE),metal)
cp backend/cpp/llama-fallback/llama.cpp/build/bin/default.metallib backend-assets/grpc/
endif
backend-assets/grpc/llama-cpp-cuda: backend-assets/grpc backend/cpp/llama/llama.cpp
backend-assets/grpc/llama-cpp-cuda: backend-assets/grpc
cp -rf backend/cpp/llama backend/cpp/llama-cuda
$(MAKE) -C backend/cpp/llama-cuda purge
$(info ${GREEN}I llama-cpp build info:cuda${RESET})
CMAKE_ARGS="$(CMAKE_ARGS) -DGGML_AVX=on -DGGML_AVX2=off -DGGML_AVX512=off -DGGML_FMA=off -DGGML_F16C=off -DGGML_CUDA=ON" $(MAKE) VARIANT="llama-cuda" build-llama-cpp-grpc-server
CMAKE_ARGS="$(CMAKE_ARGS) -DLLAMA_AVX=on -DLLAMA_AVX2=off -DLLAMA_AVX512=off -DLLAMA_FMA=off -DLLAMA_F16C=off -DLLAMA_CUDA=ON" $(MAKE) VARIANT="llama-cuda" build-llama-cpp-grpc-server
cp -rfv backend/cpp/llama-cuda/grpc-server backend-assets/grpc/llama-cpp-cuda
backend-assets/grpc/llama-cpp-hipblas: backend-assets/grpc backend/cpp/llama/llama.cpp
cp -rf backend/cpp/llama backend/cpp/llama-hipblas
$(MAKE) -C backend/cpp/llama-hipblas purge
$(info ${GREEN}I llama-cpp build info:hipblas${RESET})
CMAKE_ARGS="$(CMAKE_ARGS) -DGGML_AVX=off -DGGML_AVX2=off -DGGML_AVX512=off -DGGML_FMA=off -DGGML_F16C=off" BUILD_TYPE="hipblas" $(MAKE) VARIANT="llama-hipblas" build-llama-cpp-grpc-server
cp -rfv backend/cpp/llama-hipblas/grpc-server backend-assets/grpc/llama-cpp-hipblas
backend-assets/grpc/llama-cpp-sycl_f16: backend-assets/grpc backend/cpp/llama/llama.cpp
cp -rf backend/cpp/llama backend/cpp/llama-sycl_f16
$(MAKE) -C backend/cpp/llama-sycl_f16 purge
$(info ${GREEN}I llama-cpp build info:sycl_f16${RESET})
BUILD_TYPE="sycl_f16" $(MAKE) VARIANT="llama-sycl_f16" build-llama-cpp-grpc-server
cp -rfv backend/cpp/llama-sycl_f16/grpc-server backend-assets/grpc/llama-cpp-sycl_f16
backend-assets/grpc/llama-cpp-sycl_f32: backend-assets/grpc backend/cpp/llama/llama.cpp
cp -rf backend/cpp/llama backend/cpp/llama-sycl_f32
$(MAKE) -C backend/cpp/llama-sycl_f32 purge
$(info ${GREEN}I llama-cpp build info:sycl_f32${RESET})
BUILD_TYPE="sycl_f32" $(MAKE) VARIANT="llama-sycl_f32" build-llama-cpp-grpc-server
cp -rfv backend/cpp/llama-sycl_f32/grpc-server backend-assets/grpc/llama-cpp-sycl_f32
backend-assets/grpc/llama-cpp-grpc: backend-assets/grpc backend/cpp/llama/llama.cpp
cp -rf backend/cpp/llama backend/cpp/llama-grpc
$(MAKE) -C backend/cpp/llama-grpc purge
$(info ${GREEN}I llama-cpp build info:grpc${RESET})
CMAKE_ARGS="$(CMAKE_ARGS) -DGGML_RPC=ON -DGGML_AVX=off -DGGML_AVX2=off -DGGML_AVX512=off -DGGML_FMA=off -DGGML_F16C=off" TARGET="--target grpc-server --target rpc-server" $(MAKE) VARIANT="llama-grpc" build-llama-cpp-grpc-server
cp -rfv backend/cpp/llama-grpc/grpc-server backend-assets/grpc/llama-cpp-grpc
backend-assets/util/llama-cpp-rpc-server: backend-assets/grpc/llama-cpp-grpc
mkdir -p backend-assets/util/
cp -rf backend/cpp/llama-grpc/llama.cpp/build/bin/rpc-server backend-assets/util/llama-cpp-rpc-server
backend-assets/grpc/bark-cpp: backend/go/bark/libbark.a backend-assets/grpc
CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(CURDIR)/backend/go/bark/ LIBRARY_PATH=$(CURDIR)/backend/go/bark/ \
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/bark-cpp ./backend/go/bark/
ifneq ($(UPX),)
$(UPX) backend-assets/grpc/bark-cpp
endif
backend-assets/grpc/llama-ggml: sources/go-llama.cpp sources/go-llama.cpp/libbinding.a backend-assets/grpc
CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(CURDIR)/sources/go-llama.cpp LIBRARY_PATH=$(CURDIR)/sources/go-llama.cpp \
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/llama-ggml ./backend/go/llm/llama-ggml/
backend-assets/grpc/piper: sources/go-piper sources/go-piper/libpiper_binding.a backend-assets/grpc backend-assets/espeak-ng-data
CGO_CXXFLAGS="$(PIPER_CGO_CXXFLAGS)" CGO_LDFLAGS="$(PIPER_CGO_LDFLAGS)" LIBRARY_PATH=$(CURDIR)/sources/go-piper \
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/piper ./backend/go/tts/
ifneq ($(UPX),)
$(UPX) backend-assets/grpc/piper
endif
backend-assets/grpc/silero-vad: backend-assets/grpc backend-assets/lib/libonnxruntime.so.1
CGO_LDFLAGS="$(CGO_LDFLAGS)" CPATH="$(CPATH):$(CURDIR)/sources/onnxruntime/include/" LIBRARY_PATH=$(CURDIR)/backend-assets/lib \
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/silero-vad ./backend/go/vad/silero
ifneq ($(UPX),)
$(UPX) backend-assets/grpc/silero-vad
endif
backend-assets/grpc/rwkv: sources/go-rwkv.cpp sources/go-rwkv.cpp/librwkv.a backend-assets/grpc
CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(CURDIR)/sources/go-rwkv.cpp LIBRARY_PATH=$(CURDIR)/sources/go-rwkv.cpp \
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/rwkv ./backend/go/llm/rwkv
backend-assets/grpc/stablediffusion: sources/go-stable-diffusion sources/go-stable-diffusion/libstablediffusion.a backend-assets/grpc
CGO_LDFLAGS="$(CGO_LDFLAGS)" CPATH="$(CPATH):$(CURDIR)/sources/go-stable-diffusion/:/usr/include/opencv4" LIBRARY_PATH=$(CURDIR)/sources/go-stable-diffusion/ \
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/stablediffusion ./backend/go/image/stablediffusion
backend-assets/grpc/tinydream: sources/go-tiny-dream sources/go-tiny-dream/libtinydream.a backend-assets/grpc
CGO_LDFLAGS="$(CGO_LDFLAGS)" LIBRARY_PATH=$(CURDIR)/go-tiny-dream \
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/tinydream ./backend/go/image/tinydream
backend-assets/grpc/whisper: sources/whisper.cpp sources/whisper.cpp/libwhisper.a backend-assets/grpc
CGO_LDFLAGS="$(CGO_LDFLAGS) $(CGO_LDFLAGS_WHISPER)" C_INCLUDE_PATH="$(CURDIR)/sources/whisper.cpp/include:$(CURDIR)/sources/whisper.cpp/ggml/include" LIBRARY_PATH=$(CURDIR)/sources/whisper.cpp \
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/whisper ./backend/go/transcribe/whisper
ifneq ($(UPX),)
$(UPX) backend-assets/grpc/whisper
endif
CGO_LDFLAGS="$(CGO_LDFLAGS) $(CGO_LDFLAGS_WHISPER)" C_INCLUDE_PATH=$(CURDIR)/sources/whisper.cpp LIBRARY_PATH=$(CURDIR)/sources/whisper.cpp \
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/whisper ./backend/go/transcribe/
backend-assets/grpc/local-store: backend-assets/grpc
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/local-store ./backend/go/stores/
ifneq ($(UPX),)
$(UPX) backend-assets/grpc/local-store
endif
grpcs: prepare $(GRPC_BACKENDS)
@@ -772,17 +734,6 @@ docker:
--build-arg BUILD_TYPE=$(BUILD_TYPE) \
-t $(DOCKER_IMAGE) .
docker-cuda11:
docker build \
--build-arg CUDA_MAJOR_VERSION=11 \
--build-arg CUDA_MINOR_VERSION=8 \
--build-arg BASE_IMAGE=$(BASE_IMAGE) \
--build-arg IMAGE_TYPE=$(IMAGE_TYPE) \
--build-arg GO_TAGS="$(GO_TAGS)" \
--build-arg MAKEFLAGS="$(DOCKER_MAKEFLAGS)" \
--build-arg BUILD_TYPE=$(BUILD_TYPE) \
-t $(DOCKER_IMAGE)-cuda11 .
docker-aio:
@echo "Building AIO image with base $(BASE_IMAGE) as $(DOCKER_AIO_IMAGE)"
docker build \
@@ -796,8 +747,7 @@ docker-aio-all:
docker-image-intel:
docker build \
--progress plain \
--build-arg BASE_IMAGE=intel/oneapi-basekit:2025.1.0-0-devel-ubuntu24.04 \
--build-arg BASE_IMAGE=intel/oneapi-basekit:2024.1.0-devel-ubuntu22.04 \
--build-arg IMAGE_TYPE=$(IMAGE_TYPE) \
--build-arg GO_TAGS="none" \
--build-arg MAKEFLAGS="$(DOCKER_MAKEFLAGS)" \
@@ -805,7 +755,7 @@ docker-image-intel:
docker-image-intel-xpu:
docker build \
--build-arg BASE_IMAGE=intel/oneapi-basekit:2025.1.0-0-devel-ubuntu22.04 \
--build-arg BASE_IMAGE=intel/oneapi-basekit:2024.1.0-devel-ubuntu22.04 \
--build-arg IMAGE_TYPE=$(IMAGE_TYPE) \
--build-arg GO_TAGS="none" \
--build-arg MAKEFLAGS="$(DOCKER_MAKEFLAGS)" \
@@ -814,25 +764,3 @@ docker-image-intel-xpu:
.PHONY: swagger
swagger:
swag init -g core/http/app.go --output swagger
.PHONY: gen-assets
gen-assets:
$(GOCMD) run core/dependencies_manager/manager.go webui_static.yaml core/http/static/assets
## Documentation
docs/layouts/_default:
mkdir -p docs/layouts/_default
docs/static/gallery.html: docs/layouts/_default
$(GOCMD) run ./.github/ci/modelslist.go ./gallery/index.yaml > docs/static/gallery.html
docs/public: docs/layouts/_default docs/static/gallery.html
cd docs && hugo --minify
docs-clean:
rm -rf docs/public
rm -rf docs/static/gallery.html
.PHONY: docs
docs: docs/static/gallery.html
cd docs && hugo serve

182
README.md
View File

@@ -1,6 +1,7 @@
<h1 align="center">
<br>
<img height="300" src="./core/http/static/logo.png"> <br>
<img height="300" src="https://github.com/go-skynet/LocalAI/assets/2420543/0966aa2a-166e-4f99-a3e5-6c915fc997dd"> <br>
LocalAI
<br>
</h1>
@@ -37,146 +38,66 @@
</a>
</p>
<p align="center">
<a href="https://trendshift.io/repositories/5539" target="_blank"><img src="https://trendshift.io/api/badge/repositories/5539" alt="mudler%2FLocalAI | Trendshift" style="width: 250px; height: 55px;" width="250" height="55"/></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/) [🖼️ Models](https://models.localai.io/) [🚀 Roadmap](https://github.com/mudler/LocalAI/issues?q=is%3Aissue+is%3Aopen+label%3Aroadmap) [🥽 Demo](https://demo.localai.io) [🌍 Explorer](https://explorer.localai.io) [🛫 Examples](https://github.com/mudler/LocalAI-examples)
> [💻 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 that's 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).
**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).
## 🔥🔥 Hot topics / Roadmap
## 📚🆕 Local Stack Family
[Roadmap](https://github.com/mudler/LocalAI/issues?q=is%3Aissue+is%3Aopen+label%3Aroadmap)
🆕 LocalAI is now part of a comprehensive suite of AI tools designed to work together:
- Chat, TTS, and Image generation in the WebUI: https://github.com/mudler/LocalAI/pull/2222
- Reranker API: https://github.com/mudler/LocalAI/pull/2121
- Gallery WebUI: https://github.com/mudler/LocalAI/pull/2104
- llama3: https://github.com/mudler/LocalAI/discussions/2076
- Parler-TTS: https://github.com/mudler/LocalAI/pull/2027
- Openvino support: https://github.com/mudler/LocalAI/pull/1892
- Vector store: https://github.com/mudler/LocalAI/pull/1795
- All-in-one container image: https://github.com/mudler/LocalAI/issues/1855
<table>
<tr>
<td width="50%" valign="top">
<a href="https://github.com/mudler/LocalAGI">
<img src="https://raw.githubusercontent.com/mudler/LocalAGI/refs/heads/main/webui/react-ui/public/logo_2.png" width="300" alt="LocalAGI Logo">
</a>
</td>
<td width="50%" valign="top">
<h3><a href="https://github.com/mudler/LocalAGI">LocalAGI</a></h3>
<p>A powerful Local AI agent management platform that serves as a drop-in replacement for OpenAI's Responses API, enhanced with advanced agentic capabilities.</p>
</td>
</tr>
<tr>
<td width="50%" valign="top">
<a href="https://github.com/mudler/LocalRecall">
<img src="https://raw.githubusercontent.com/mudler/LocalRecall/refs/heads/main/static/localrecall_horizontal.png" width="300" alt="LocalRecall Logo">
</a>
</td>
<td width="50%" valign="top">
<h3><a href="https://github.com/mudler/LocalRecall">LocalRecall</a></h3>
<p>A REST-ful API and knowledge base management system that provides persistent memory and storage capabilities for AI agents.</p>
</td>
</tr>
</table>
Hot topics (looking for contributors):
## Screenshots
- 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
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
| Talk Interface | Generate Audio |
| --- | --- |
| ![Screenshot 2025-03-31 at 12-01-36 LocalAI - Talk](./docs/assets/images/screenshots/screenshot_tts.png) | ![Screenshot 2025-03-31 at 12-01-29 LocalAI - Generate audio with voice-en-us-ryan-low](./docs/assets/images/screenshots/screenshot_tts.png) |
## 💻 [Getting started](https://localai.io/basics/getting_started/index.html)
| Models Overview | Generate Images |
| --- | --- |
| ![Screenshot 2025-03-31 at 12-01-20 LocalAI - Models](./docs/assets/images/screenshots/screenshot_gallery.png) | ![Screenshot 2025-03-31 at 12-31-41 LocalAI - Generate images with flux 1-dev](./docs/assets/images/screenshots/screenshot_image.png) |
For a detailed step-by-step introduction, refer to the [Getting Started](https://localai.io/basics/getting_started/index.html) guide.
| Chat Interface | Home |
| --- | --- |
| ![Screenshot 2025-03-31 at 11-57-44 LocalAI - Chat with localai-functioncall-qwen2 5-7b-v0 5](./docs/assets/images/screenshots/screenshot_chat.png) | ![Screenshot 2025-03-31 at 11-57-23 LocalAI API - c2a39e3 (c2a39e3639227cfd94ffffe9f5691239acc275a8)](./docs/assets/images/screenshots/screenshot_home.png) |
For those in a hurry, here's a straightforward one-liner to launch a LocalAI AIO(All-in-one) Image using `docker`:
| Login | Swarm |
| --- | --- |
|![Screenshot 2025-03-31 at 12-09-59 ](./docs/assets/images/screenshots/screenshot_login.png) | ![Screenshot 2025-03-31 at 12-10-39 LocalAI - P2P dashboard](./docs/assets/images/screenshots/screenshot_p2p.png) |
## 💻 Quickstart
Run the installer script:
```bash
curl https://localai.io/install.sh | sh
```
Or run with docker:
### CPU only image:
```bash
docker run -ti --name local-ai -p 8080:8080 localai/localai:latest-cpu
```
### Nvidia GPU:
```bash
docker run -ti --name local-ai -p 8080:8080 --gpus all localai/localai:latest-gpu-nvidia-cuda-12
```
### CPU and GPU image (bigger size):
```bash
docker run -ti --name local-ai -p 8080:8080 localai/localai:latest
```
### AIO images (it will pre-download a set of models ready for use, see https://localai.io/basics/container/)
```bash
docker run -ti --name local-ai -p 8080:8080 localai/localai:latest-aio-cpu
# or, 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
```
To load models:
```bash
# From the model gallery (see available models with `local-ai models list`, in the WebUI from the model tab, or visiting https://models.localai.io)
local-ai run llama-3.2-1b-instruct:q4_k_m
# Start LocalAI with the phi-2 model directly from huggingface
local-ai run huggingface://TheBloke/phi-2-GGUF/phi-2.Q8_0.gguf
# Install and run a model from the Ollama OCI registry
local-ai run ollama://gemma:2b
# Run a model from a configuration file
local-ai run https://gist.githubusercontent.com/.../phi-2.yaml
# Install and run a model from a standard OCI registry (e.g., Docker Hub)
local-ai run oci://localai/phi-2:latest
```
For more information, see [💻 Getting started](https://localai.io/basics/getting_started/index.html)
## 📰 Latest project news
- Apr 2025: [LocalAGI](https://github.com/mudler/LocalAGI) and [LocalRecall](https://github.com/mudler/LocalRecall) join the LocalAI family stack.
- Apr 2025: WebUI overhaul, AIO images updates
- Feb 2025: Backend cleanup, Breaking changes, new backends (kokoro, OutelTTS, faster-whisper), Nvidia L4T images
- Jan 2025: LocalAI model release: https://huggingface.co/mudler/LocalAI-functioncall-phi-4-v0.3, SANA support in diffusers: https://github.com/mudler/LocalAI/pull/4603
- Dec 2024: stablediffusion.cpp backend (ggml) added ( https://github.com/mudler/LocalAI/pull/4289 )
- Nov 2024: Bark.cpp backend added ( https://github.com/mudler/LocalAI/pull/4287 )
- Nov 2024: Voice activity detection models (**VAD**) added to the API: https://github.com/mudler/LocalAI/pull/4204
- Oct 2024: examples moved to [LocalAI-examples](https://github.com/mudler/LocalAI-examples)
- Aug 2024: 🆕 FLUX-1, [P2P Explorer](https://explorer.localai.io)
- July 2024: 🔥🔥 🆕 P2P Dashboard, LocalAI Federated mode and AI Swarms: https://github.com/mudler/LocalAI/pull/2723. P2P Global community pools: https://github.com/mudler/LocalAI/issues/3113
- May 2024: 🔥🔥 Decentralized P2P llama.cpp: https://github.com/mudler/LocalAI/pull/2343 (peer2peer llama.cpp!) 👉 Docs https://localai.io/features/distribute/
- May 2024: 🔥🔥 Distributed inferencing: https://github.com/mudler/LocalAI/pull/2324
- April 2024: Reranker API: https://github.com/mudler/LocalAI/pull/2121
Roadmap items: [List of issues](https://github.com/mudler/LocalAI/issues?q=is%3Aissue+is%3Aopen+label%3Aroadmap)
## 🚀 [Features](https://localai.io/features/)
- 📖 [Text generation with GPTs](https://localai.io/features/text-generation/) (`llama.cpp`, `transformers`, `vllm` ... [:book: and more](https://localai.io/model-compatibility/index.html#model-compatibility-table))
- 📖 [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](https://localai.io/features/image-generation)
- 🔥 [OpenAI-alike tools API](https://localai.io/features/openai-functions/)
- 🎨 [Image generation with stable diffusion](https://localai.io/features/image-generation)
- 🔥 [OpenAI functions](https://localai.io/features/openai-functions/) 🆕
- 🧠 [Embeddings generation for vector databases](https://localai.io/features/embeddings/)
- ✍️ [Constrained grammars](https://localai.io/features/constrained_grammars/)
- 🖼️ [Download Models directly from Huggingface ](https://localai.io/models/)
- 🥽 [Vision API](https://localai.io/features/gpt-vision/)
- 📈 [Reranker API](https://localai.io/features/reranker/)
- 🆕🖧 [P2P Inferencing](https://localai.io/features/distribute/)
- [Agentic capabilities](https://github.com/mudler/LocalAGI)
- 🔊 Voice activity detection (Silero-VAD support)
- 🌍 Integrated WebUI!
- 🆕 [Reranker API](https://localai.io/features/reranker/)
## 💻 Usage
Check out the [Getting started](https://localai.io/basics/getting_started/index.html) section in our documentation.
### 🔗 Community and integrations
@@ -186,7 +107,6 @@ 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
@@ -194,24 +114,18 @@ Model galleries
Other:
- Helm chart https://github.com/go-skynet/helm-charts
- VSCode extension https://github.com/badgooooor/localai-vscode-plugin
- Langchain: https://python.langchain.com/docs/integrations/providers/localai/
- 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
- Another Telegram Bot https://github.com/JackBekket/Hellper
- Auto-documentation https://github.com/JackBekket/Reflexia
- Github bot which answer on issues, with code and documentation as context https://github.com/JackBekket/GitHelper
- 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/)
@@ -219,8 +133,6 @@ 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](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/)
@@ -248,16 +160,17 @@ 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/user-attachments/assets/72eab1dd-8b93-4fc0-9ade-84db49f24962">
</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
@@ -267,7 +180,7 @@ 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
@@ -279,6 +192,7 @@ LocalAI couldn't have been built without the help of great software already avai
- https://github.com/antimatter15/alpaca.cpp
- https://github.com/EdVince/Stable-Diffusion-NCNN
- https://github.com/ggerganov/whisper.cpp
- https://github.com/saharNooby/rwkv.cpp
- https://github.com/rhasspy/piper
## 🤗 Contributors

View File

@@ -1,7 +1,7 @@
embeddings: true
name: text-embedding-ada-002
backend: bert-embeddings
parameters:
model: huggingface://bartowski/granite-embedding-107m-multilingual-GGUF/granite-embedding-107m-multilingual-f16.gguf
model: huggingface://mudler/all-MiniLM-L6-v2/ggml-model-q4_0.bin
usage: |
You can test this model with curl like this:

View File

@@ -1,17 +1,56 @@
name: stablediffusion
backend: stablediffusion-ggml
cfg_scale: 4.5
options:
- sampler:euler
backend: stablediffusion
parameters:
model: stable-diffusion-v1-5-pruned-emaonly-Q4_0.gguf
step: 25
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: "stable-diffusion-v1-5-pruned-emaonly-Q4_0.gguf"
sha256: "b8944e9fe0b69b36ae1b5bb0185b3a7b8ef14347fe0fa9af6c64c4829022261f"
uri: "huggingface://second-state/stable-diffusion-v1-5-GGUF/stable-diffusion-v1-5-pruned-emaonly-Q4_0.gguf"
- 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 \

View File

@@ -1,57 +1,59 @@
context_size: 8192
f16: true
function:
grammar:
no_mixed_free_string: true
schema_type: llama3.1 # or JSON is supported too (json)
response_regex:
- <function=(?P<name>\w+)>(?P<arguments>.*)</function>
mmap: true
name: gpt-4
mmap: true
parameters:
model: Hermes-3-Llama-3.2-3B-Q4_K_M.gguf
model: huggingface://NousResearch/Hermes-2-Pro-Llama-3-8B-GGUF/Hermes-2-Pro-Llama-3-8B-Q4_K_M.gguf
template:
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|>
# https://huggingface.co/NousResearch/Hermes-2-Pro-Mistral-7B-GGUF#prompt-format-for-function-calling
function: |
<|im_start|>system
You are a function calling AI model. You are provided with function signatures within <tools></tools> XML tags. You may call one or more functions to assist with the user query. Don't make assumptions about what values to plug into functions. Here are the available tools:
<tools>
{{range .Functions}}
{'type': 'function', 'function': {'name': '{{.Name}}', 'description': '{{.Description}}', 'parameters': {{toJson .Parameters}} }}
{{end}}
</tools>
Use the following pydantic model json schema for each tool call you will make:
{'title': 'FunctionCall', 'type': 'object', 'properties': {'arguments': {'title': 'Arguments', 'type': 'object'}, 'name': {'title': 'Name', 'type': 'string'}}, 'required': ['arguments', 'name']}
For each function call return a json object with function name and arguments within <tool_call></tool_call> XML tags as follows:
<tool_call>
{'arguments': <args-dict>, 'name': <function-name>}
</tool_call><|im_end|>
{{.Input -}}
<|im_start|>assistant
<tool_call>
chat: |
{{.Input -}}
<|im_start|>assistant
completion: |
{{.Input}}
context_size: 4096
f16: true
stopwords:
- <|im_end|>
- <dummy32000>
- <|eot_id|>
- <|end_of_text|>
template:
chat: |
<|begin_of_text|><|start_header_id|>system<|end_header_id|>
You are a helpful assistant<|eot_id|><|start_header_id|>user<|end_header_id|>
{{.Input }}
<|start_header_id|>assistant<|end_header_id|>
chat_message: |
<|start_header_id|>{{if eq .RoleName "assistant"}}assistant{{else if eq .RoleName "system"}}system{{else if eq .RoleName "tool"}}tool{{else if eq .RoleName "user"}}user{{end}}<|end_header_id|>
{{ if .FunctionCall -}}
{{ else if eq .RoleName "tool" -}}
The Function was executed and the response was:
{{ end -}}
{{ if .Content -}}
{{.Content -}}
{{ else if .FunctionCall -}}
{{ range .FunctionCall }}
[{{.FunctionCall.Name}}({{.FunctionCall.Arguments}})]
{{ end }}
{{ end -}}
<|eot_id|>
completion: |
{{.Input}}
function: |
<|start_header_id|>system<|end_header_id|>
You are an expert in composing functions. You are given a question and a set of possible functions.
Based on the question, you will need to make one or more function/tool calls to achieve the purpose.
If none of the functions can be used, point it out. If the given question lacks the parameters required by the function, also point it out. You should only return the function call in tools call sections.
If you decide to invoke any of the function(s), you MUST put it in the format as follows:
[func_name1(params_name1=params_value1,params_name2=params_value2,...),func_name2(params_name1=params_value1,params_name2=params_value2,...)]
You SHOULD NOT include any other text in the response.
Here is a list of functions in JSON format that you can invoke.
{{toJson .Functions}}
<|eot_id|><|start_header_id|>user<|end_header_id|>
{{.Input}}
<|eot_id|><|start_header_id|>assistant<|end_header_id|>
download_files:
- filename: Hermes-3-Llama-3.2-3B-Q4_K_M.gguf
sha256: 2e220a14ba4328fee38cf36c2c068261560f999fadb5725ce5c6d977cb5126b5
uri: huggingface://bartowski/Hermes-3-Llama-3.2-3B-GGUF/Hermes-3-Llama-3.2-3B-Q4_K_M.gguf
- "\n</tool_call>"
- "\n\n\n"
usage: |
curl http://localhost:8080/v1/chat/completions -H "Content-Type: application/json" -d '{
"model": "gpt-4",
"messages": [{"role": "user", "content": "How are you doing?", "temperature": 0.1}]
}'

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@@ -1,8 +0,0 @@
backend: silero-vad
name: silero-vad
parameters:
model: silero-vad.onnx
download_files:
- filename: silero-vad.onnx
uri: https://huggingface.co/onnx-community/silero-vad/resolve/main/onnx/model.onnx
sha256: a4a068cd6cf1ea8355b84327595838ca748ec29a25bc91fc82e6c299ccdc5808

View File

@@ -1,49 +1,31 @@
backend: llama-cpp
context_size: 4096
f16: true
mmap: true
mmproj: minicpm-v-2_6-mmproj-f16.gguf
name: gpt-4o
name: gpt-4-vision-preview
roles:
user: "USER:"
assistant: "ASSISTANT:"
system: "SYSTEM:"
mmproj: bakllava-mmproj.gguf
parameters:
model: minicpm-v-2_6-Q4_K_M.gguf
stopwords:
- <|im_end|>
- <dummy32000>
- </s>
- <|endoftext|>
model: bakllava.gguf
template:
chat: |
{{.Input -}}
<|im_start|>assistant
chat_message: |
<|im_start|>{{ .RoleName }}
{{ if .FunctionCall -}}
Function call:
{{ else if eq .RoleName "tool" -}}
Function response:
{{ end -}}
{{ if .Content -}}
{{.Content }}
{{ end -}}
{{ if .FunctionCall -}}
{{toJson .FunctionCall}}
{{ end -}}<|im_end|>
completion: |
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}}
function: |
<|im_start|>system
You are a function calling AI model. You are provided with functions to execute. You may call one or more functions to assist with the user query. Don't make assumptions about what values to plug into functions. Here are the available tools:
{{range .Functions}}
{'type': 'function', 'function': {'name': '{{.Name}}', 'description': '{{.Description}}', 'parameters': {{toJson .Parameters}} }}
{{end}}
For each function call return a json object with function name and arguments
<|im_end|>
{{.Input -}}
<|im_start|>assistant
ASSISTANT:
download_files:
- filename: minicpm-v-2_6-Q4_K_M.gguf
sha256: 3a4078d53b46f22989adbf998ce5a3fd090b6541f112d7e936eb4204a04100b1
uri: huggingface://openbmb/MiniCPM-V-2_6-gguf/ggml-model-Q4_K_M.gguf
- filename: minicpm-v-2_6-mmproj-f16.gguf
uri: huggingface://openbmb/MiniCPM-V-2_6-gguf/mmproj-model-f16.gguf
sha256: 4485f68a0f1aa404c391e788ea88ea653c100d8e98fe572698f701e5809711fd
- 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

@@ -129,7 +129,7 @@ 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}/vad.yaml,/aio/${PROFILE}/vision.yaml}"
export MODELS="${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

View File

@@ -1,7 +1,7 @@
embeddings: true
name: text-embedding-ada-002
backend: sentencetransformers
parameters:
model: huggingface://bartowski/granite-embedding-107m-multilingual-GGUF/granite-embedding-107m-multilingual-f16.gguf
model: all-MiniLM-L6-v2
usage: |
You can test this model with curl like this:

View File

@@ -1,53 +1,59 @@
context_size: 4096
f16: true
function:
capture_llm_results:
- (?s)<Thought>(.*?)</Thought>
grammar:
properties_order: name,arguments
json_regex_match:
- (?s)<Output>(.*?)</Output>
replace_llm_results:
- key: (?s)<Thought>(.*?)</Thought>
value: ""
mmap: true
name: gpt-4
mmap: true
parameters:
model: localai-functioncall-qwen2.5-7b-v0.5-q4_k_m.gguf
stopwords:
- <|im_end|>
- <dummy32000>
- </s>
model: huggingface://NousResearch/Hermes-2-Pro-Llama-3-8B-GGUF/Hermes-2-Pro-Llama-3-8B-Q4_K_M.gguf
template:
chat: |
{{.Input -}}
<|im_start|>assistant
chat_message: |
<|im_start|>{{ .RoleName }}
{{ if .FunctionCall -}}
Function call:
{{ else if eq .RoleName "tool" -}}
Function response:
{{ end -}}
{{ if .Content -}}
<|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 -}}
{{- end }}
{{- if .FunctionCall}}
{{toJson .FunctionCall}}
{{ end -}}<|im_end|>
completion: |
{{.Input}}
{{- end }}
{{- if .FunctionCall }}
</tool_call>
{{- else if eq .RoleName "tool" }}
</tool_response>
{{- end }}<|im_end|>
# https://huggingface.co/NousResearch/Hermes-2-Pro-Mistral-7B-GGUF#prompt-format-for-function-calling
function: |
<|im_start|>system
You are an AI assistant that executes function calls, and these are the tools at your disposal:
You are a function calling AI model. You are provided with function signatures within <tools></tools> XML tags. You may call one or more functions to assist with the user query. Don't make assumptions about what values to plug into functions. Here are the available tools:
<tools>
{{range .Functions}}
{'type': 'function', 'function': {'name': '{{.Name}}', 'description': '{{.Description}}', 'parameters': {{toJson .Parameters}} }}
{{end}}
<|im_end|>
</tools>
Use the following pydantic model json schema for each tool call you will make:
{'title': 'FunctionCall', 'type': 'object', 'properties': {'arguments': {'title': 'Arguments', 'type': 'object'}, 'name': {'title': 'Name', 'type': 'string'}}, 'required': ['arguments', 'name']}
For each function call return a json object with function name and arguments within <tool_call></tool_call> XML tags as follows:
<tool_call>
{'arguments': <args-dict>, 'name': <function-name>}
</tool_call><|im_end|>
{{.Input -}}
<|im_start|>assistant
download_files:
- filename: localai-functioncall-phi-4-v0.3-q4_k_m.gguf
sha256: 23fee048ded2a6e2e1a7b6bbefa6cbf83068f194caa9552aecbaa00fec8a16d5
uri: huggingface://mudler/LocalAI-functioncall-phi-4-v0.3-Q4_K_M-GGUF/localai-functioncall-phi-4-v0.3-q4_k_m.gguf
<tool_call>
chat: |
{{.Input -}}
<|im_start|>assistant
completion: |
{{.Input}}
context_size: 4096
f16: true
stopwords:
- <|im_end|>
- <dummy32000>
- "\n</tool_call>"
- "\n\n\n"
usage: |
curl http://localhost:8080/v1/chat/completions -H "Content-Type: application/json" -d '{
"model": "gpt-4",
"messages": [{"role": "user", "content": "How are you doing?", "temperature": 0.1}]
}'

View File

@@ -1,8 +0,0 @@
backend: silero-vad
name: silero-vad
parameters:
model: silero-vad.onnx
download_files:
- filename: silero-vad.onnx
uri: https://huggingface.co/onnx-community/silero-vad/resolve/main/onnx/model.onnx
sha256: a4a068cd6cf1ea8355b84327595838ca748ec29a25bc91fc82e6c299ccdc5808

View File

@@ -1,49 +1,35 @@
backend: llama-cpp
context_size: 4096
f16: true
mmap: true
mmproj: minicpm-v-2_6-mmproj-f16.gguf
name: gpt-4o
name: gpt-4-vision-preview
roles:
user: "USER:"
assistant: "ASSISTANT:"
system: "SYSTEM:"
mmproj: llava-v1.6-7b-mmproj-f16.gguf
parameters:
model: minicpm-v-2_6-Q4_K_M.gguf
stopwords:
- <|im_end|>
- <dummy32000>
- </s>
- <|endoftext|>
model: llava-v1.6-mistral-7b.Q5_K_M.gguf
temperature: 0.2
top_k: 40
top_p: 0.95
seed: -1
template:
chat: |
{{.Input -}}
<|im_start|>assistant
chat_message: |
<|im_start|>{{ .RoleName }}
{{ if .FunctionCall -}}
Function call:
{{ else if eq .RoleName "tool" -}}
Function response:
{{ end -}}
{{ if .Content -}}
{{.Content }}
{{ end -}}
{{ if .FunctionCall -}}
{{toJson .FunctionCall}}
{{ end -}}<|im_end|>
completion: |
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}}
function: |
<|im_start|>system
You are a function calling AI model. You are provided with functions to execute. You may call one or more functions to assist with the user query. Don't make assumptions about what values to plug into functions. Here are the available tools:
{{range .Functions}}
{'type': 'function', 'function': {'name': '{{.Name}}', 'description': '{{.Description}}', 'parameters': {{toJson .Parameters}} }}
{{end}}
For each function call return a json object with function name and arguments
<|im_end|>
{{.Input -}}
<|im_start|>assistant
ASSISTANT:
download_files:
- filename: minicpm-v-2_6-Q4_K_M.gguf
sha256: 3a4078d53b46f22989adbf998ce5a3fd090b6541f112d7e936eb4204a04100b1
uri: huggingface://openbmb/MiniCPM-V-2_6-gguf/ggml-model-Q4_K_M.gguf
- filename: minicpm-v-2_6-mmproj-f16.gguf
uri: huggingface://openbmb/MiniCPM-V-2_6-gguf/mmproj-model-f16.gguf
sha256: 4485f68a0f1aa404c391e788ea88ea653c100d8e98fe572698f701e5809711fd
- 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

@@ -1,7 +1,7 @@
embeddings: true
name: text-embedding-ada-002
backend: sentencetransformers
parameters:
model: huggingface://bartowski/granite-embedding-107m-multilingual-GGUF/granite-embedding-107m-multilingual-f16.gguf
model: all-MiniLM-L6-v2
usage: |
You can test this model with curl like this:

View File

@@ -1,6 +1,6 @@
name: stablediffusion
parameters:
model: Lykon/dreamshaper-8
model: runwayml/stable-diffusion-v1-5
backend: diffusers
step: 25
f16: true

View File

@@ -1,53 +1,59 @@
context_size: 4096
f16: true
function:
capture_llm_results:
- (?s)<Thought>(.*?)</Thought>
grammar:
properties_order: name,arguments
json_regex_match:
- (?s)<Output>(.*?)</Output>
replace_llm_results:
- key: (?s)<Thought>(.*?)</Thought>
value: ""
mmap: true
name: gpt-4
mmap: false
f16: false
parameters:
model: localai-functioncall-qwen2.5-7b-v0.5-q4_k_m.gguf
stopwords:
- <|im_end|>
- <dummy32000>
- </s>
model: huggingface://NousResearch/Hermes-2-Pro-Llama-3-8B-GGUF/Hermes-2-Pro-Llama-3-8B-Q4_K_M.gguf
template:
chat: |
{{.Input -}}
<|im_start|>assistant
chat_message: |
<|im_start|>{{ .RoleName }}
{{ if .FunctionCall -}}
Function call:
{{ else if eq .RoleName "tool" -}}
Function response:
{{ end -}}
{{ if .Content -}}
<|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 -}}
{{- end }}
{{- if .FunctionCall}}
{{toJson .FunctionCall}}
{{ end -}}<|im_end|>
completion: |
{{.Input}}
{{- end }}
{{- if .FunctionCall }}
</tool_call>
{{- else if eq .RoleName "tool" }}
</tool_response>
{{- end }}<|im_end|>
# https://huggingface.co/NousResearch/Hermes-2-Pro-Mistral-7B-GGUF#prompt-format-for-function-calling
function: |
<|im_start|>system
You are an AI assistant that executes function calls, and these are the tools at your disposal:
You are a function calling AI model. You are provided with function signatures within <tools></tools> XML tags. You may call one or more functions to assist with the user query. Don't make assumptions about what values to plug into functions. Here are the available tools:
<tools>
{{range .Functions}}
{'type': 'function', 'function': {'name': '{{.Name}}', 'description': '{{.Description}}', 'parameters': {{toJson .Parameters}} }}
{{end}}
<|im_end|>
</tools>
Use the following pydantic model json schema for each tool call you will make:
{'title': 'FunctionCall', 'type': 'object', 'properties': {'arguments': {'title': 'Arguments', 'type': 'object'}, 'name': {'title': 'Name', 'type': 'string'}}, 'required': ['arguments', 'name']}
For each function call return a json object with function name and arguments within <tool_call></tool_call> XML tags as follows:
<tool_call>
{'arguments': <args-dict>, 'name': <function-name>}
</tool_call><|im_end|>
{{.Input -}}
<|im_start|>assistant
download_files:
- filename: localai-functioncall-phi-4-v0.3-q4_k_m.gguf
sha256: 23fee048ded2a6e2e1a7b6bbefa6cbf83068f194caa9552aecbaa00fec8a16d5
uri: huggingface://mudler/LocalAI-functioncall-phi-4-v0.3-Q4_K_M-GGUF/localai-functioncall-phi-4-v0.3-q4_k_m.gguf
<tool_call>
chat: |
{{.Input -}}
<|im_start|>assistant
completion: |
{{.Input}}
context_size: 4096
stopwords:
- <|im_end|>
- "\n</tool_call>"
- <dummy32000>
- "\n\n\n"
usage: |
curl http://localhost:8080/v1/chat/completions -H "Content-Type: application/json" -d '{
"model": "gpt-4",
"messages": [{"role": "user", "content": "How are you doing?", "temperature": 0.1}]
}'

View File

@@ -1,8 +0,0 @@
backend: silero-vad
name: silero-vad
parameters:
model: silero-vad.onnx
download_files:
- filename: silero-vad.onnx
uri: https://huggingface.co/onnx-community/silero-vad/resolve/main/onnx/model.onnx
sha256: a4a068cd6cf1ea8355b84327595838ca748ec29a25bc91fc82e6c299ccdc5808

View File

@@ -1,50 +1,35 @@
backend: llama-cpp
context_size: 4096
f16: true
mmap: true
mmproj: minicpm-v-2_6-mmproj-f16.gguf
name: gpt-4o
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: minicpm-v-2_6-Q4_K_M.gguf
stopwords:
- <|im_end|>
- <dummy32000>
- </s>
- <|endoftext|>
model: llava-v1.6-mistral-7b.Q5_K_M.gguf
temperature: 0.2
top_k: 40
top_p: 0.95
seed: -1
template:
chat: |
{{.Input -}}
<|im_start|>assistant
chat_message: |
<|im_start|>{{ .RoleName }}
{{ if .FunctionCall -}}
Function call:
{{ else if eq .RoleName "tool" -}}
Function response:
{{ end -}}
{{ if .Content -}}
{{.Content }}
{{ end -}}
{{ if .FunctionCall -}}
{{toJson .FunctionCall}}
{{ end -}}<|im_end|>
completion: |
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}}
function: |
<|im_start|>system
You are a function calling AI model. You are provided with functions to execute. You may call one or more functions to assist with the user query. Don't make assumptions about what values to plug into functions. Here are the available tools:
{{range .Functions}}
{'type': 'function', 'function': {'name': '{{.Name}}', 'description': '{{.Description}}', 'parameters': {{toJson .Parameters}} }}
{{end}}
For each function call return a json object with function name and arguments
<|im_end|>
{{.Input -}}
<|im_start|>assistant
ASSISTANT:
download_files:
- filename: minicpm-v-2_6-Q4_K_M.gguf
sha256: 3a4078d53b46f22989adbf998ce5a3fd090b6541f112d7e936eb4204a04100b1
uri: huggingface://openbmb/MiniCPM-V-2_6-gguf/ggml-model-Q4_K_M.gguf
- filename: minicpm-v-2_6-mmproj-f16.gguf
uri: huggingface://openbmb/MiniCPM-V-2_6-gguf/mmproj-model-f16.gguf
sha256: 4485f68a0f1aa404c391e788ea88ea653c100d8e98fe572698f701e5809711fd
- 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

@@ -16,7 +16,6 @@ service Backend {
rpc GenerateImage(GenerateImageRequest) returns (Result) {}
rpc AudioTranscription(TranscriptRequest) returns (TranscriptResult) {}
rpc TTS(TTSRequest) returns (Result) {}
rpc SoundGeneration(SoundGenerationRequest) returns (Result) {}
rpc TokenizeString(PredictOptions) returns (TokenizationResponse) {}
rpc Status(HealthMessage) returns (StatusResponse) {}
@@ -26,21 +25,6 @@ service Backend {
rpc StoresFind(StoresFindOptions) returns (StoresFindResult) {}
rpc Rerank(RerankRequest) returns (RerankResult) {}
rpc GetMetrics(MetricsRequest) returns (MetricsResponse);
rpc VAD(VADRequest) returns (VADResponse) {}
}
// Define the empty request
message MetricsRequest {}
message MetricsResponse {
int32 slot_id = 1;
string prompt_json_for_slot = 2; // Stores the prompt as a JSON string.
float tokens_per_second = 3;
int32 tokens_generated = 4;
int32 prompt_tokens_processed = 5;
}
message RerankRequest {
@@ -149,9 +133,6 @@ message PredictOptions {
repeated string Images = 42;
bool UseTokenizerTemplate = 43;
repeated Message Messages = 44;
repeated string Videos = 45;
repeated string Audios = 46;
string CorrelationId = 47;
}
// The response message containing the result
@@ -159,12 +140,6 @@ message Reply {
bytes message = 1;
int32 tokens = 2;
int32 prompt_tokens = 3;
double timing_prompt_processing = 4;
double timing_token_generation = 5;
}
message GrammarTrigger {
string word = 1;
}
message ModelOptions {
@@ -190,7 +165,11 @@ message ModelOptions {
int32 NGQA = 20;
string ModelFile = 21;
// AutoGPTQ
string Device = 22;
bool UseTriton = 23;
string ModelBaseName = 24;
bool UseFastTokenizer = 25;
// Diffusers
string PipelineType = 26;
@@ -223,12 +202,6 @@ message ModelOptions {
int32 SwapSpace = 53;
int32 MaxModelLen = 54;
int32 TensorParallelSize = 55;
string LoadFormat = 58;
bool DisableLogStatus = 66;
string DType = 67;
int32 LimitImagePerPrompt = 68;
int32 LimitVideoPerPrompt = 69;
int32 LimitAudioPerPrompt = 70;
string MMProj = 41;
@@ -242,18 +215,6 @@ message ModelOptions {
bool FlashAttention = 56;
bool NoKVOffload = 57;
string ModelPath = 59;
repeated string LoraAdapters = 60;
repeated float LoraScales = 61;
repeated string Options = 62;
string CacheTypeKey = 63;
string CacheTypeValue = 64;
repeated GrammarTrigger GrammarTriggers = 65;
}
message Result {
@@ -269,7 +230,6 @@ message TranscriptRequest {
string dst = 2;
string language = 3;
uint32 threads = 4;
bool translate = 5;
}
message TranscriptResult {
@@ -306,31 +266,6 @@ message TTSRequest {
string model = 2;
string dst = 3;
string voice = 4;
optional string language = 5;
}
message VADRequest {
repeated float audio = 1;
}
message VADSegment {
float start = 1;
float end = 2;
}
message VADResponse {
repeated VADSegment segments = 1;
}
message SoundGenerationRequest {
string text = 1;
string model = 2;
string dst = 3;
optional float duration = 4;
optional float temperature = 5;
optional bool sample = 6;
optional string src = 7;
optional int32 src_divisor = 8;
}
message TokenizationResponse {
@@ -357,4 +292,4 @@ message StatusResponse {
message Message {
string role = 1;
string content = 2;
}
}

View File

@@ -46,14 +46,9 @@ 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 --jobs 2 --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

View File

@@ -2,7 +2,7 @@
## XXX: In some versions of CMake clip wasn't being built before llama.
## This is an hack for now, but it should be fixed in the future.
set(TARGET myclip)
add_library(${TARGET} clip.cpp clip.h clip-impl.h llava.cpp llava.h)
add_library(${TARGET} clip.cpp clip.h llava.cpp llava.h)
install(TARGETS ${TARGET} LIBRARY)
target_include_directories(myclip PUBLIC .)
target_include_directories(myclip PUBLIC ../..)

View File

@@ -1,63 +1,45 @@
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 -DLLAMA_CURL=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_HIP=ON
# If it's OSX, DO NOT embed the metal library - -DGGML_METAL_EMBED_LIBRARY=ON requires further investigation
CMAKE_ARGS+=-DLLAMA_HIPBLAS=ON
# If it's OSX, DO NOT embed the metal library - -DLLAMA_METAL_EMBED_LIBRARY=ON requires further investigation
# But if it's OSX without metal, disable it here
else ifeq ($(OS),Darwin)
else ifeq ($(OS),darwin)
ifneq ($(BUILD_TYPE),metal)
CMAKE_ARGS+=-DGGML_METAL=OFF
else
CMAKE_ARGS+=-DGGML_METAL=ON
CMAKE_ARGS+=-DGGML_METAL_EMBED_LIBRARY=ON
TARGET+=--target ggml-metal
CMAKE_ARGS+=-DLLAMA_METAL=OFF
endif
endif
ifeq ($(BUILD_TYPE),sycl_f16)
CMAKE_ARGS+=-DGGML_SYCL=ON \
-DCMAKE_C_COMPILER=icx \
-DCMAKE_CXX_COMPILER=icpx \
-DCMAKE_CXX_FLAGS="-fsycl" \
-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 \
-DCMAKE_CXX_FLAGS="-fsycl"
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
mkdir -p llama.cpp/examples/grpc-server
@@ -79,9 +61,9 @@ clean: purge
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) && $(MAKE)"
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) && $(MAKE)
endif
cp llama.cpp/build/bin/grpc-server .
cp llama.cpp/build/bin/grpc-server .

View File

File diff suppressed because it is too large Load Diff

View File

@@ -1,13 +0,0 @@
diff --git a/examples/llava/clip.cpp b/examples/llava/clip.cpp
index 3cd0d2fa..6c5e811a 100644
--- a/examples/llava/clip.cpp
+++ b/examples/llava/clip.cpp
@@ -2608,7 +2608,7 @@ bool clip_image_batch_encode(clip_ctx * ctx, const int n_threads, const clip_ima
struct ggml_tensor * patches = ggml_graph_get_tensor(gf, "patches");
int* patches_data = (int*)malloc(ggml_nbytes(patches));
for (int i = 0; i < num_patches; i++) {
- patches_data[i] = i + 1;
+ patches_data[i] = i;
}
ggml_backend_tensor_set(patches, patches_data, 0, ggml_nbytes(patches));
free(patches_data);

View File

@@ -1,12 +1,5 @@
#!/bin/bash
## Patches
## Apply patches from the `patches` directory
for patch in $(ls patches); do
echo "Applying patch $patch"
patch -d llama.cpp/ -p1 < patches/$patch
done
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/
@@ -21,7 +14,6 @@ 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/clip-impl.h llama.cpp/examples/grpc-server/clip-impl.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

View File

@@ -61,7 +61,6 @@ struct task_server {
json data;
bool infill_mode = false;
bool embedding_mode = false;
bool reranking_mode = false;
int multitask_id = -1;
};
@@ -481,4 +480,31 @@ static inline std::vector<uint8_t> base64_decode(const std::string & encoded_str
}
return ret;
}
//
// random string / id
//
static std::string random_string()
{
static const std::string str("0123456789ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz");
std::random_device rd;
std::mt19937 generator(rd());
std::string result(32, ' ');
for (int i = 0; i < 32; ++i) {
result[i] = str[generator() % str.size()];
}
return result;
}
static std::string gen_chatcmplid()
{
std::stringstream chatcmplid;
chatcmplid << "chatcmpl-" << random_string();
return chatcmplid.str();
}

View File

@@ -1,25 +0,0 @@
INCLUDE_PATH := $(abspath ./)
LIBRARY_PATH := $(abspath ./)
AR?=ar
BUILD_TYPE?=
# keep standard at C11 and C++11
CXXFLAGS = -I. -I$(INCLUDE_PATH)/../../../sources/bark.cpp/examples -I$(INCLUDE_PATH)/../../../sources/bark.cpp/spm-headers -I$(INCLUDE_PATH)/../../../sources/bark.cpp -O3 -DNDEBUG -std=c++17 -fPIC
LDFLAGS = -L$(LIBRARY_PATH) -L$(LIBRARY_PATH)/../../../sources/bark.cpp/build/examples -lbark -lstdc++ -lm
# warnings
CXXFLAGS += -Wall -Wextra -Wpedantic -Wcast-qual -Wno-unused-function
gobark.o:
$(CXX) $(CXXFLAGS) gobark.cpp -o gobark.o -c $(LDFLAGS)
libbark.a: gobark.o
cp $(INCLUDE_PATH)/../../../sources/bark.cpp/build/libbark.a ./
$(AR) rcs libbark.a gobark.o
$(AR) rcs libbark.a $(LIBRARY_PATH)/../../../sources/bark.cpp/build/encodec.cpp/ggml/src/CMakeFiles/ggml.dir/ggml.c.o
$(AR) rcs libbark.a $(LIBRARY_PATH)/../../../sources/bark.cpp/build/encodec.cpp/ggml/src/CMakeFiles/ggml.dir/ggml-alloc.c.o
$(AR) rcs libbark.a $(LIBRARY_PATH)/../../../sources/bark.cpp/build/encodec.cpp/ggml/src/CMakeFiles/ggml.dir/ggml-backend.c.o
clean:
rm -f gobark.o libbark.a

View File

@@ -1,85 +0,0 @@
#include <iostream>
#include <tuple>
#include "bark.h"
#include "gobark.h"
#include "common.h"
#include "ggml.h"
struct bark_context *c;
void bark_print_progress_callback(struct bark_context *bctx, enum bark_encoding_step step, int progress, void *user_data) {
if (step == bark_encoding_step::SEMANTIC) {
printf("\rGenerating semantic tokens... %d%%", progress);
} else if (step == bark_encoding_step::COARSE) {
printf("\rGenerating coarse tokens... %d%%", progress);
} else if (step == bark_encoding_step::FINE) {
printf("\rGenerating fine tokens... %d%%", progress);
}
fflush(stdout);
}
int load_model(char *model) {
// initialize bark context
struct bark_context_params ctx_params = bark_context_default_params();
bark_params params;
params.model_path = model;
// ctx_params.verbosity = verbosity;
ctx_params.progress_callback = bark_print_progress_callback;
ctx_params.progress_callback_user_data = nullptr;
struct bark_context *bctx = bark_load_model(params.model_path.c_str(), ctx_params, params.seed);
if (!bctx) {
fprintf(stderr, "%s: Could not load model\n", __func__);
return 1;
}
c = bctx;
return 0;
}
int tts(char *text,int threads, char *dst ) {
ggml_time_init();
const int64_t t_main_start_us = ggml_time_us();
// generate audio
if (!bark_generate_audio(c, text, threads)) {
fprintf(stderr, "%s: An error occured. If the problem persists, feel free to open an issue to report it.\n", __func__);
return 1;
}
const float *audio_data = bark_get_audio_data(c);
if (audio_data == NULL) {
fprintf(stderr, "%s: Could not get audio data\n", __func__);
return 1;
}
const int audio_arr_size = bark_get_audio_data_size(c);
std::vector<float> audio_arr(audio_data, audio_data + audio_arr_size);
write_wav_on_disk(audio_arr, dst);
// report timing
{
const int64_t t_main_end_us = ggml_time_us();
const int64_t t_load_us = bark_get_load_time(c);
const int64_t t_eval_us = bark_get_eval_time(c);
printf("\n\n");
printf("%s: load time = %8.2f ms\n", __func__, t_load_us / 1000.0f);
printf("%s: eval time = %8.2f ms\n", __func__, t_eval_us / 1000.0f);
printf("%s: total time = %8.2f ms\n", __func__, (t_main_end_us - t_main_start_us) / 1000.0f);
}
return 0;
}
int unload() {
bark_free(c);
}

View File

@@ -1,52 +0,0 @@
package main
// #cgo CXXFLAGS: -I${SRCDIR}/../../../sources/bark.cpp/ -I${SRCDIR}/../../../sources/bark.cpp/encodec.cpp -I${SRCDIR}/../../../sources/bark.cpp/examples -I${SRCDIR}/../../../sources/bark.cpp/spm-headers
// #cgo LDFLAGS: -L${SRCDIR}/ -L${SRCDIR}/../../../sources/bark.cpp/build/examples -L${SRCDIR}/../../../sources/bark.cpp/build/encodec.cpp/ -lbark -lencodec -lcommon
// #include <gobark.h>
// #include <stdlib.h>
import "C"
import (
"fmt"
"unsafe"
"github.com/mudler/LocalAI/pkg/grpc/base"
pb "github.com/mudler/LocalAI/pkg/grpc/proto"
)
type Bark struct {
base.SingleThread
threads int
}
func (sd *Bark) Load(opts *pb.ModelOptions) error {
sd.threads = int(opts.Threads)
modelFile := C.CString(opts.ModelFile)
defer C.free(unsafe.Pointer(modelFile))
ret := C.load_model(modelFile)
if ret != 0 {
return fmt.Errorf("inference failed")
}
return nil
}
func (sd *Bark) TTS(opts *pb.TTSRequest) error {
t := C.CString(opts.Text)
defer C.free(unsafe.Pointer(t))
dst := C.CString(opts.Dst)
defer C.free(unsafe.Pointer(dst))
threads := C.int(sd.threads)
ret := C.tts(t, threads, dst)
if ret != 0 {
return fmt.Errorf("inference failed")
}
return nil
}

View File

@@ -1,8 +0,0 @@
#ifdef __cplusplus
extern "C" {
#endif
int load_model(char *model);
int tts(char *text,int threads, char *dst );
#ifdef __cplusplus
}
#endif

View File

@@ -1,135 +0,0 @@
INCLUDE_PATH := $(abspath ./)
LIBRARY_PATH := $(abspath ./)
AR?=ar
CMAKE_ARGS?=
BUILD_TYPE?=
ONEAPI_VARS?=/opt/intel/oneapi/setvars.sh
# keep standard at C11 and C++11
CXXFLAGS = -I. -I$(INCLUDE_PATH)/../../../../sources/stablediffusion-ggml.cpp/thirdparty -I$(INCLUDE_PATH)/../../../../sources/stablediffusion-ggml.cpp/ggml/include -I$(INCLUDE_PATH)/../../../../sources/stablediffusion-ggml.cpp -O3 -DNDEBUG -std=c++17 -fPIC
GOCMD?=go
CGO_LDFLAGS?=
# Avoid parent make file overwriting CGO_LDFLAGS which is needed for hipblas
CGO_LDFLAGS_SYCL=
GO_TAGS?=
LD_FLAGS?=
# 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
ifeq ($(BUILD_TYPE),cublas)
CMAKE_ARGS+=-DGGML_CUDA=ON
# If build type is openblas then we set -DGGML_BLAS=ON -DGGML_BLAS_VENDOR=OpenBLAS
# to CMAKE_ARGS automatically
else ifeq ($(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
else ifeq ($(BUILD_TYPE),clblas)
CMAKE_ARGS+=-DGGML_CLBLAST=ON -DCLBlast_DIR=/some/path
# If it's hipblas we do have also to set CC=/opt/rocm/llvm/bin/clang CXX=/opt/rocm/llvm/bin/clang++
else ifeq ($(BUILD_TYPE),hipblas)
CMAKE_ARGS+=-DGGML_HIP=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
CMAKE_ARGS+=-DGGML_METAL_EMBED_LIBRARY=ON
TARGET+=--target ggml-metal
endif
endif
ifeq ($(BUILD_TYPE),sycl_f16)
CMAKE_ARGS+=-DGGML_SYCL=ON \
-DCMAKE_C_COMPILER=icx \
-DCMAKE_CXX_COMPILER=icpx \
-DSD_SYCL=ON \
-DGGML_SYCL_F16=ON
CC=icx
CXX=icpx
CGO_LDFLAGS_SYCL += -fsycl -L${DNNLROOT}/lib -ldnnl ${MKLROOT}/lib/intel64/libmkl_sycl.a -fiopenmp -fopenmp-targets=spir64 -lOpenCL
CGO_LDFLAGS_SYCL += $(shell pkg-config --libs mkl-static-lp64-gomp)
CGO_CXXFLAGS += -fiopenmp -fopenmp-targets=spir64
CGO_CXXFLAGS += $(shell pkg-config --cflags mkl-static-lp64-gomp )
endif
ifeq ($(BUILD_TYPE),sycl_f32)
CMAKE_ARGS+=-DGGML_SYCL=ON \
-DCMAKE_C_COMPILER=icx \
-DCMAKE_CXX_COMPILER=icpx \
-DSD_SYCL=ON
CC=icx
CXX=icpx
CGO_LDFLAGS_SYCL += -fsycl -L${DNNLROOT}/lib -ldnnl ${MKLROOT}/lib/intel64/libmkl_sycl.a -fiopenmp -fopenmp-targets=spir64 -lOpenCL
CGO_LDFLAGS_SYCL += $(shell pkg-config --libs mkl-static-lp64-gomp)
CGO_CXXFLAGS += -fiopenmp -fopenmp-targets=spir64
CGO_CXXFLAGS += $(shell pkg-config --cflags mkl-static-lp64-gomp )
endif
# warnings
# CXXFLAGS += -Wall -Wextra -Wpedantic -Wcast-qual -Wno-unused-function
# Find all .a archives in ARCHIVE_DIR
# (ggml can have different backends cpu, cuda, etc., each backend generates a .a archive)
GGML_ARCHIVE_DIR := build/ggml/src/
ALL_ARCHIVES := $(shell find $(GGML_ARCHIVE_DIR) -type f -name '*.a')
# Name of the single merged library
COMBINED_LIB := libggmlall.a
# Rule to merge all the .a files into one
$(COMBINED_LIB): $(ALL_ARCHIVES)
@echo "Merging all .a into $(COMBINED_LIB)"
rm -f $@
mkdir -p merge-tmp
for a in $(ALL_ARCHIVES); do \
( cd merge-tmp && ar x ../$$a ); \
done
( cd merge-tmp && ar rcs ../$@ *.o )
# Ensure we have a proper index
ranlib $@
# Clean up
rm -rf merge-tmp
build/libstable-diffusion.a:
@echo "Building SD with $(BUILD_TYPE) build type and $(CMAKE_ARGS)"
ifneq (,$(findstring sycl,$(BUILD_TYPE)))
+bash -c "source $(ONEAPI_VARS); \
mkdir -p build && \
cd build && \
cmake $(CMAKE_ARGS) ../../../../../sources/stablediffusion-ggml.cpp && \
cmake --build . --config Release"
else
mkdir -p build && \
cd build && \
cmake $(CMAKE_ARGS) ../../../../../sources/stablediffusion-ggml.cpp && \
cmake --build . --config Release
endif
$(MAKE) $(COMBINED_LIB)
gosd.o:
ifneq (,$(findstring sycl,$(BUILD_TYPE)))
+bash -c "source $(ONEAPI_VARS); \
$(CXX) $(CXXFLAGS) gosd.cpp -o gosd.o -c"
else
$(CXX) $(CXXFLAGS) gosd.cpp -o gosd.o -c
endif
libsd.a: gosd.o
cp $(INCLUDE_PATH)/build/libstable-diffusion.a ./libsd.a
$(AR) rcs libsd.a gosd.o
stablediffusion-ggml:
CGO_LDFLAGS="$(CGO_LDFLAGS) $(CGO_LDFLAGS_SYCL)" C_INCLUDE_PATH="$(INCLUDE_PATH)" LIBRARY_PATH="$(LIBRARY_PATH)" \
CC="$(CC)" CXX="$(CXX)" CGO_CXXFLAGS="$(CGO_CXXFLAGS)" \
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o ../../../../backend-assets/grpc/stablediffusion-ggml ./
ifneq ($(UPX),)
$(UPX) ../../../../backend-assets/grpc/stablediffusion-ggml
endif
clean:
rm -rf gosd.o libsd.a build $(COMBINED_LIB)

View File

@@ -1,231 +0,0 @@
#include <stdio.h>
#include <string.h>
#include <time.h>
#include <iostream>
#include <random>
#include <string>
#include <vector>
#include "gosd.h"
// #include "preprocessing.hpp"
#include "flux.hpp"
#include "stable-diffusion.h"
#define STB_IMAGE_IMPLEMENTATION
#define STB_IMAGE_STATIC
#include "stb_image.h"
#define STB_IMAGE_WRITE_IMPLEMENTATION
#define STB_IMAGE_WRITE_STATIC
#include "stb_image_write.h"
#define STB_IMAGE_RESIZE_IMPLEMENTATION
#define STB_IMAGE_RESIZE_STATIC
#include "stb_image_resize.h"
// Names of the sampler method, same order as enum sample_method in stable-diffusion.h
const char* sample_method_str[] = {
"euler_a",
"euler",
"heun",
"dpm2",
"dpm++2s_a",
"dpm++2m",
"dpm++2mv2",
"ipndm",
"ipndm_v",
"lcm",
"ddim_trailing",
"tcd",
};
// Names of the sigma schedule overrides, same order as sample_schedule in stable-diffusion.h
const char* schedule_str[] = {
"default",
"discrete",
"karras",
"exponential",
"ays",
"gits",
};
sd_ctx_t* sd_c;
sample_method_t sample_method;
int load_model(char *model, char* options[], int threads, int diff) {
fprintf (stderr, "Loading model!\n");
char *stableDiffusionModel = "";
if (diff == 1 ) {
stableDiffusionModel = model;
model = "";
}
// decode options. Options are in form optname:optvale, or if booleans only optname.
char *clip_l_path = "";
char *clip_g_path = "";
char *t5xxl_path = "";
char *vae_path = "";
char *scheduler = "";
char *sampler = "";
// If options is not NULL, parse options
for (int i = 0; options[i] != NULL; i++) {
char *optname = strtok(options[i], ":");
char *optval = strtok(NULL, ":");
if (optval == NULL) {
optval = "true";
}
if (!strcmp(optname, "clip_l_path")) {
clip_l_path = optval;
}
if (!strcmp(optname, "clip_g_path")) {
clip_g_path = optval;
}
if (!strcmp(optname, "t5xxl_path")) {
t5xxl_path = optval;
}
if (!strcmp(optname, "vae_path")) {
vae_path = optval;
}
if (!strcmp(optname, "scheduler")) {
scheduler = optval;
}
if (!strcmp(optname, "sampler")) {
sampler = optval;
}
}
int sample_method_found = -1;
for (int m = 0; m < N_SAMPLE_METHODS; m++) {
if (!strcmp(sampler, sample_method_str[m])) {
sample_method_found = m;
}
}
if (sample_method_found == -1) {
fprintf(stderr, "Invalid sample method, default to EULER_A!\n");
sample_method_found = EULER_A;
}
sample_method = (sample_method_t)sample_method_found;
int schedule_found = -1;
for (int d = 0; d < N_SCHEDULES; d++) {
if (!strcmp(scheduler, schedule_str[d])) {
schedule_found = d;
fprintf (stderr, "Found scheduler: %s\n", scheduler);
}
}
if (schedule_found == -1) {
fprintf (stderr, "Invalid scheduler! using DEFAULT\n");
schedule_found = DEFAULT;
}
schedule_t schedule = (schedule_t)schedule_found;
fprintf (stderr, "Creating context\n");
sd_ctx_t* sd_ctx = new_sd_ctx(model,
clip_l_path,
clip_g_path,
t5xxl_path,
stableDiffusionModel,
vae_path,
"",
"",
"",
"",
"",
false,
false,
false,
threads,
SD_TYPE_COUNT,
STD_DEFAULT_RNG,
schedule,
false,
false,
false,
false);
if (sd_ctx == NULL) {
fprintf (stderr, "failed loading model (generic error)\n");
return 1;
}
fprintf (stderr, "Created context: OK\n");
sd_c = sd_ctx;
return 0;
}
int gen_image(char *text, char *negativeText, int width, int height, int steps, int seed , char *dst, float cfg_scale) {
sd_image_t* results;
std::vector<int> skip_layers = {7, 8, 9};
fprintf (stderr, "Generating image\n");
results = txt2img(sd_c,
text,
negativeText,
-1, //clip_skip
cfg_scale, // sfg_scale
3.5f,
0, // eta
width,
height,
sample_method,
steps,
seed,
1,
NULL,
0.9f,
20.f,
false,
"",
skip_layers.data(),
skip_layers.size(),
0,
0.01,
0.2);
if (results == NULL) {
fprintf (stderr, "NO results\n");
return 1;
}
if (results[0].data == NULL) {
fprintf (stderr, "Results with no data\n");
return 1;
}
fprintf (stderr, "Writing PNG\n");
fprintf (stderr, "DST: %s\n", dst);
fprintf (stderr, "Width: %d\n", results[0].width);
fprintf (stderr, "Height: %d\n", results[0].height);
fprintf (stderr, "Channel: %d\n", results[0].channel);
fprintf (stderr, "Data: %p\n", results[0].data);
stbi_write_png(dst, results[0].width, results[0].height, results[0].channel,
results[0].data, 0, NULL);
fprintf (stderr, "Saved resulting image to '%s'\n", dst);
// TODO: free results. Why does it crash?
free(results[0].data);
results[0].data = NULL;
free(results);
fprintf (stderr, "gen_image is done", dst);
return 0;
}
int unload() {
free_sd_ctx(sd_c);
}

View File

@@ -1,96 +0,0 @@
package main
// #cgo CXXFLAGS: -I${SRCDIR}/../../../../sources/stablediffusion-ggml.cpp/thirdparty -I${SRCDIR}/../../../../sources/stablediffusion-ggml.cpp -I${SRCDIR}/../../../../sources/stablediffusion-ggml.cpp/ggml/include
// #cgo LDFLAGS: -L${SRCDIR}/ -lsd -lstdc++ -lm -lggmlall -lgomp
// #include <gosd.h>
// #include <stdlib.h>
import "C"
import (
"fmt"
"os"
"path/filepath"
"strings"
"unsafe"
"github.com/mudler/LocalAI/pkg/grpc/base"
pb "github.com/mudler/LocalAI/pkg/grpc/proto"
"github.com/mudler/LocalAI/pkg/utils"
)
type SDGGML struct {
base.SingleThread
threads int
sampleMethod string
cfgScale float32
}
func (sd *SDGGML) Load(opts *pb.ModelOptions) error {
sd.threads = int(opts.Threads)
modelFile := C.CString(opts.ModelFile)
defer C.free(unsafe.Pointer(modelFile))
var options **C.char
// prepare the options array to pass to C
size := C.size_t(unsafe.Sizeof((*C.char)(nil)))
length := C.size_t(len(opts.Options))
options = (**C.char)(C.malloc(length * size))
view := (*[1 << 30]*C.char)(unsafe.Pointer(options))[0:len(opts.Options):len(opts.Options)]
var diffusionModel int
var oo []string
for _, op := range opts.Options {
if op == "diffusion_model" {
diffusionModel = 1
continue
}
// If it's an option path, we resolve absolute path from the model path
if strings.Contains(op, ":") && strings.Contains(op, "path") {
data := strings.Split(op, ":")
data[1] = filepath.Join(opts.ModelPath, data[1])
if err := utils.VerifyPath(data[1], opts.ModelPath); err == nil {
oo = append(oo, strings.Join(data, ":"))
}
} else {
oo = append(oo, op)
}
}
fmt.Fprintf(os.Stderr, "Options: %+v\n", oo)
for i, x := range oo {
view[i] = C.CString(x)
}
sd.cfgScale = opts.CFGScale
ret := C.load_model(modelFile, options, C.int(opts.Threads), C.int(diffusionModel))
if ret != 0 {
return fmt.Errorf("could not load model")
}
return nil
}
func (sd *SDGGML) GenerateImage(opts *pb.GenerateImageRequest) error {
t := C.CString(opts.PositivePrompt)
defer C.free(unsafe.Pointer(t))
dst := C.CString(opts.Dst)
defer C.free(unsafe.Pointer(dst))
negative := C.CString(opts.NegativePrompt)
defer C.free(unsafe.Pointer(negative))
ret := C.gen_image(t, negative, C.int(opts.Width), C.int(opts.Height), C.int(opts.Step), C.int(opts.Seed), dst, C.float(sd.cfgScale))
if ret != 0 {
return fmt.Errorf("inference failed")
}
return nil
}

View File

@@ -1,8 +0,0 @@
#ifdef __cplusplus
extern "C" {
#endif
int load_model(char *model, char* options[], int threads, int diffusionModel);
int gen_image(char *text, char *negativeText, int width, int height, int steps, int seed, char *dst, float cfg_scale);
#ifdef __cplusplus
}
#endif

View File

@@ -1,10 +1,11 @@
package main
// Note: this is started internally by LocalAI and a server is allocated for each model
import (
"flag"
grpc "github.com/mudler/LocalAI/pkg/grpc"
grpc "github.com/go-skynet/LocalAI/pkg/grpc"
)
var (
@@ -14,7 +15,7 @@ var (
func main() {
flag.Parse()
if err := grpc.StartServer(*addr, &Bark{}); err != nil {
if err := grpc.StartServer(*addr, &Image{}); err != nil {
panic(err)
}
}

View File

@@ -0,0 +1,33 @@
package main
// This is a wrapper to statisfy the GRPC service interface
// It is meant to be used by the main executable that is the server for the specific backend type (falcon, gpt3, etc)
import (
"github.com/go-skynet/LocalAI/pkg/grpc/base"
pb "github.com/go-skynet/LocalAI/pkg/grpc/proto"
"github.com/go-skynet/LocalAI/pkg/stablediffusion"
)
type Image struct {
base.SingleThread
stablediffusion *stablediffusion.StableDiffusion
}
func (image *Image) Load(opts *pb.ModelOptions) error {
var err error
// Note: the Model here is a path to a directory containing the model files
image.stablediffusion, err = stablediffusion.New(opts.ModelFile)
return err
}
func (image *Image) GenerateImage(opts *pb.GenerateImageRequest) error {
return image.stablediffusion.GenerateImage(
int(opts.Height),
int(opts.Width),
int(opts.Mode),
int(opts.Step),
int(opts.Seed),
opts.PositivePrompt,
opts.NegativePrompt,
opts.Dst)
}

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, &Image{}); err != nil {
panic(err)
}
}

View File

@@ -0,0 +1,32 @@
package main
// This is a wrapper to statisfy the GRPC service interface
// It is meant to be used by the main executable that is the server for the specific backend type (falcon, gpt3, etc)
import (
"github.com/go-skynet/LocalAI/pkg/grpc/base"
pb "github.com/go-skynet/LocalAI/pkg/grpc/proto"
"github.com/go-skynet/LocalAI/pkg/tinydream"
)
type Image struct {
base.SingleThread
tinydream *tinydream.TinyDream
}
func (image *Image) Load(opts *pb.ModelOptions) error {
var err error
// Note: the Model here is a path to a directory containing the model files
image.tinydream, err = tinydream.New(opts.ModelFile)
return err
}
func (image *Image) GenerateImage(opts *pb.GenerateImageRequest) error {
return image.tinydream.GenerateImage(
int(opts.Height),
int(opts.Width),
int(opts.Step),
int(opts.Seed),
opts.PositivePrompt,
opts.NegativePrompt,
opts.Dst)
}

View File

@@ -0,0 +1,34 @@
package main
// This is a wrapper to statisfy the GRPC service interface
// It is meant to be used by the main executable that is the server for the specific backend type (falcon, gpt3, etc)
import (
bert "github.com/go-skynet/go-bert.cpp"
"github.com/go-skynet/LocalAI/pkg/grpc/base"
pb "github.com/go-skynet/LocalAI/pkg/grpc/proto"
)
type Embeddings struct {
base.SingleThread
bert *bert.Bert
}
func (llm *Embeddings) Load(opts *pb.ModelOptions) error {
model, err := bert.New(opts.ModelFile)
llm.bert = model
return err
}
func (llm *Embeddings) Embeddings(opts *pb.PredictOptions) ([]float32, error) {
if len(opts.EmbeddingTokens) > 0 {
tokens := []int{}
for _, t := range opts.EmbeddingTokens {
tokens = append(tokens, int(t))
}
return llm.bert.TokenEmbeddings(tokens, bert.SetThreads(int(opts.Threads)))
}
return llm.bert.Embeddings(opts.Embeddings, bert.SetThreads(int(opts.Threads)))
}

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, &Embeddings{}); err != nil {
panic(err)
}
}

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

@@ -5,7 +5,7 @@ package main
import (
"flag"
grpc "github.com/mudler/LocalAI/pkg/grpc"
grpc "github.com/go-skynet/LocalAI/pkg/grpc"
)
var (
@@ -15,7 +15,7 @@ var (
func main() {
flag.Parse()
if err := grpc.StartServer(*addr, &VAD{}); err != nil {
if err := grpc.StartServer(*addr, &LLM{}); err != nil {
panic(err)
}
}

View File

@@ -6,9 +6,9 @@ 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 {

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 +1,204 @@
package main
// This is a wrapper to statisfy the GRPC service interface
// It is meant to be used by the main executable that is the server for the specific backend type (falcon, gpt3, etc)
import (
"fmt"
"github.com/go-skynet/LocalAI/pkg/grpc/base"
pb "github.com/go-skynet/LocalAI/pkg/grpc/proto"
"github.com/go-skynet/go-llama.cpp"
)
type LLM struct {
base.SingleThread
llama *llama.LLama
}
func (llm *LLM) Load(opts *pb.ModelOptions) error {
ropeFreqBase := float32(10000)
ropeFreqScale := float32(1)
if opts.RopeFreqBase != 0 {
ropeFreqBase = opts.RopeFreqBase
}
if opts.RopeFreqScale != 0 {
ropeFreqScale = opts.RopeFreqScale
}
llamaOpts := []llama.ModelOption{
llama.WithRopeFreqBase(ropeFreqBase),
llama.WithRopeFreqScale(ropeFreqScale),
}
if opts.NGQA != 0 {
llamaOpts = append(llamaOpts, llama.WithGQA(int(opts.NGQA)))
}
if opts.RMSNormEps != 0 {
llamaOpts = append(llamaOpts, llama.WithRMSNormEPS(opts.RMSNormEps))
}
if opts.ContextSize != 0 {
llamaOpts = append(llamaOpts, llama.SetContext(int(opts.ContextSize)))
}
if opts.F16Memory {
llamaOpts = append(llamaOpts, llama.EnableF16Memory)
}
if opts.Embeddings {
llamaOpts = append(llamaOpts, llama.EnableEmbeddings)
}
if opts.NGPULayers != 0 {
llamaOpts = append(llamaOpts, llama.SetGPULayers(int(opts.NGPULayers)))
}
llamaOpts = append(llamaOpts, llama.SetMMap(opts.MMap))
llamaOpts = append(llamaOpts, llama.SetMainGPU(opts.MainGPU))
llamaOpts = append(llamaOpts, llama.SetTensorSplit(opts.TensorSplit))
if opts.NBatch != 0 {
llamaOpts = append(llamaOpts, llama.SetNBatch(int(opts.NBatch)))
} else {
llamaOpts = append(llamaOpts, llama.SetNBatch(512))
}
if opts.NUMA {
llamaOpts = append(llamaOpts, llama.EnableNUMA)
}
if opts.LowVRAM {
llamaOpts = append(llamaOpts, llama.EnabelLowVRAM)
}
model, err := llama.New(opts.ModelFile, llamaOpts...)
llm.llama = model
return err
}
func buildPredictOptions(opts *pb.PredictOptions) []llama.PredictOption {
ropeFreqBase := float32(10000)
ropeFreqScale := float32(1)
if opts.RopeFreqBase != 0 {
ropeFreqBase = opts.RopeFreqBase
}
if opts.RopeFreqScale != 0 {
ropeFreqScale = opts.RopeFreqScale
}
predictOptions := []llama.PredictOption{
llama.SetTemperature(opts.Temperature),
llama.SetTopP(opts.TopP),
llama.SetTopK(int(opts.TopK)),
llama.SetTokens(int(opts.Tokens)),
llama.SetThreads(int(opts.Threads)),
llama.WithGrammar(opts.Grammar),
llama.SetRopeFreqBase(ropeFreqBase),
llama.SetRopeFreqScale(ropeFreqScale),
llama.SetNegativePromptScale(opts.NegativePromptScale),
llama.SetNegativePrompt(opts.NegativePrompt),
}
if opts.PromptCacheAll {
predictOptions = append(predictOptions, llama.EnablePromptCacheAll)
}
if opts.PromptCacheRO {
predictOptions = append(predictOptions, llama.EnablePromptCacheRO)
}
// Expected absolute path
if opts.PromptCachePath != "" {
predictOptions = append(predictOptions, llama.SetPathPromptCache(opts.PromptCachePath))
}
if opts.Mirostat != 0 {
predictOptions = append(predictOptions, llama.SetMirostat(int(opts.Mirostat)))
}
if opts.MirostatETA != 0 {
predictOptions = append(predictOptions, llama.SetMirostatETA(opts.MirostatETA))
}
if opts.MirostatTAU != 0 {
predictOptions = append(predictOptions, llama.SetMirostatTAU(opts.MirostatTAU))
}
if opts.Debug {
predictOptions = append(predictOptions, llama.Debug)
}
predictOptions = append(predictOptions, llama.SetStopWords(opts.StopPrompts...))
if opts.PresencePenalty != 0 {
predictOptions = append(predictOptions, llama.SetPenalty(opts.PresencePenalty))
}
if opts.NKeep != 0 {
predictOptions = append(predictOptions, llama.SetNKeep(int(opts.NKeep)))
}
if opts.Batch != 0 {
predictOptions = append(predictOptions, llama.SetBatch(int(opts.Batch)))
}
if opts.F16KV {
predictOptions = append(predictOptions, llama.EnableF16KV)
}
if opts.IgnoreEOS {
predictOptions = append(predictOptions, llama.IgnoreEOS)
}
if opts.Seed != 0 {
predictOptions = append(predictOptions, llama.SetSeed(int(opts.Seed)))
}
//predictOptions = append(predictOptions, llama.SetLogitBias(c.Seed))
predictOptions = append(predictOptions, llama.SetFrequencyPenalty(opts.FrequencyPenalty))
predictOptions = append(predictOptions, llama.SetMlock(opts.MLock))
predictOptions = append(predictOptions, llama.SetMemoryMap(opts.MMap))
predictOptions = append(predictOptions, llama.SetPredictionMainGPU(opts.MainGPU))
predictOptions = append(predictOptions, llama.SetPredictionTensorSplit(opts.TensorSplit))
predictOptions = append(predictOptions, llama.SetTailFreeSamplingZ(opts.TailFreeSamplingZ))
predictOptions = append(predictOptions, llama.SetTypicalP(opts.TypicalP))
return predictOptions
}
func (llm *LLM) Predict(opts *pb.PredictOptions) (string, error) {
return llm.llama.Predict(opts.Prompt, buildPredictOptions(opts)...)
}
func (llm *LLM) PredictStream(opts *pb.PredictOptions, results chan string) error {
predictOptions := buildPredictOptions(opts)
predictOptions = append(predictOptions, llama.SetTokenCallback(func(token string) bool {
results <- token
return true
}))
go func() {
_, err := llm.llama.Predict(opts.Prompt, predictOptions...)
if err != nil {
fmt.Println("err: ", err)
}
close(results)
}()
return nil
}
func (llm *LLM) Embeddings(opts *pb.PredictOptions) ([]float32, error) {
predictOptions := buildPredictOptions(opts)
if len(opts.EmbeddingTokens) > 0 {
tokens := []int{}
for _, t := range opts.EmbeddingTokens {
tokens = append(tokens, int(t))
}
return llm.llama.TokenEmbeddings(tokens, predictOptions...)
}
return llm.llama.Embeddings(opts.Embeddings, predictOptions...)
}

View File

@@ -0,0 +1,19 @@
package main
import (
"flag"
grpc "github.com/go-skynet/LocalAI/pkg/grpc"
)
var (
addr = flag.String("addr", "localhost:50051", "the address to connect to")
)
func main() {
flag.Parse()
if err := grpc.StartServer(*addr, &LLM{}); err != nil {
panic(err)
}
}

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

@@ -1,10 +1,11 @@
package main
// Note: this is started internally by LocalAI and a server is allocated for each model
import (
"flag"
grpc "github.com/mudler/LocalAI/pkg/grpc"
grpc "github.com/go-skynet/LocalAI/pkg/grpc"
)
var (
@@ -14,7 +15,7 @@ var (
func main() {
flag.Parse()
if err := grpc.StartServer(*addr, &SDGGML{}); err != nil {
if err := grpc.StartServer(*addr, &LLM{}); err != nil {
panic(err)
}
}

View File

@@ -0,0 +1,95 @@
package main
// This is a wrapper to statisfy the GRPC service interface
// It is meant to be used by the main executable that is the server for the specific backend type (falcon, gpt3, etc)
import (
"fmt"
"path/filepath"
"github.com/donomii/go-rwkv.cpp"
"github.com/go-skynet/LocalAI/pkg/grpc/base"
pb "github.com/go-skynet/LocalAI/pkg/grpc/proto"
)
const tokenizerSuffix = ".tokenizer.json"
type LLM struct {
base.SingleThread
rwkv *rwkv.RwkvState
}
func (llm *LLM) Load(opts *pb.ModelOptions) error {
tokenizerFile := opts.Tokenizer
if tokenizerFile == "" {
modelFile := filepath.Base(opts.ModelFile)
tokenizerFile = modelFile + tokenizerSuffix
}
modelPath := filepath.Dir(opts.ModelFile)
tokenizerPath := filepath.Join(modelPath, tokenizerFile)
model := rwkv.LoadFiles(opts.ModelFile, tokenizerPath, uint32(opts.GetThreads()))
if model == nil {
return fmt.Errorf("could not load model")
}
llm.rwkv = model
return nil
}
func (llm *LLM) Predict(opts *pb.PredictOptions) (string, error) {
stopWord := "\n"
if len(opts.StopPrompts) > 0 {
stopWord = opts.StopPrompts[0]
}
if err := llm.rwkv.ProcessInput(opts.Prompt); err != nil {
return "", err
}
response := llm.rwkv.GenerateResponse(int(opts.Tokens), stopWord, float32(opts.Temperature), float32(opts.TopP), nil)
return response, nil
}
func (llm *LLM) PredictStream(opts *pb.PredictOptions, results chan string) error {
go func() {
stopWord := "\n"
if len(opts.StopPrompts) > 0 {
stopWord = opts.StopPrompts[0]
}
if err := llm.rwkv.ProcessInput(opts.Prompt); err != nil {
fmt.Println("Error processing input: ", err)
return
}
llm.rwkv.GenerateResponse(int(opts.Tokens), stopWord, float32(opts.Temperature), float32(opts.TopP), func(s string) bool {
results <- s
return true
})
close(results)
}()
return nil
}
func (llm *LLM) TokenizeString(opts *pb.PredictOptions) (pb.TokenizationResponse, error) {
tokens, err := llm.rwkv.Tokenizer.Encode(opts.Prompt)
if err != nil {
return pb.TokenizationResponse{}, err
}
l := len(tokens)
i32Tokens := make([]int32, l)
for i, t := range tokens {
i32Tokens[i] = int32(t.ID)
}
return pb.TokenizationResponse{
Length: int32(l),
Tokens: i32Tokens,
}, nil
}

View File

@@ -6,7 +6,7 @@ import (
"flag"
"os"
grpc "github.com/mudler/LocalAI/pkg/grpc"
grpc "github.com/go-skynet/LocalAI/pkg/grpc"
"github.com/rs/zerolog"
"github.com/rs/zerolog/log"
)

View File

@@ -8,8 +8,8 @@ import (
"math"
"slices"
"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"
"github.com/rs/zerolog/log"
)
@@ -311,16 +311,12 @@ func (s *Store) StoresGet(opts *pb.StoresGetOptions) (pb.StoresGetResult, error)
}
func isNormalized(k []float32) bool {
var sum float64
var sum float32
for _, v := range k {
v64 := float64(v)
sum += v64*v64
sum += v
}
s := math.Sqrt(sum)
return s >= 0.99 && s <= 1.01
return sum == 1.0
}
// TODO: This we could replace with handwritten SIMD code
@@ -332,7 +328,7 @@ func normalizedCosineSimilarity(k1, k2 []float32) float32 {
dot += k1[i] * k2[i]
}
assert(dot >= -1.01 && dot <= 1.01, fmt.Sprintf("dot = %f", dot))
assert(dot >= -1 && dot <= 1, fmt.Sprintf("dot = %f", dot))
// 2.0 * (1.0 - dot) would be the Euclidean distance
return dot
@@ -422,7 +418,7 @@ func cosineSimilarity(k1, k2 []float32, mag1 float64) float32 {
sim := float32(dot / (mag1 * math.Sqrt(mag2)))
assert(sim >= -1.01 && sim <= 1.01, fmt.Sprintf("sim = %f", sim))
assert(sim >= -1 && sim <= 1, fmt.Sprintf("sim = %f", sim))
return sim
}

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 +1,100 @@
package main
import (
"fmt"
"os"
"os/exec"
"path/filepath"
"github.com/ggerganov/whisper.cpp/bindings/go/pkg/whisper"
"github.com/go-audio/wav"
"github.com/go-skynet/LocalAI/core/schema"
)
func ffmpegCommand(args []string) (string, error) {
cmd := exec.Command("ffmpeg", args...) // Constrain this to ffmpeg to permit security scanner to see that the command is safe.
cmd.Env = os.Environ()
out, err := cmd.CombinedOutput()
return string(out), err
}
// AudioToWav converts audio to wav for transcribe.
// TODO: use https://github.com/mccoyst/ogg?
func audioToWav(src, dst string) error {
commandArgs := []string{"-i", src, "-format", "s16le", "-ar", "16000", "-ac", "1", "-acodec", "pcm_s16le", dst}
out, err := ffmpegCommand(commandArgs)
if err != nil {
return fmt.Errorf("error: %w out: %s", err, out)
}
return nil
}
func Transcript(model whisper.Model, audiopath, language string, threads uint) (schema.TranscriptionResult, error) {
res := schema.TranscriptionResult{}
dir, err := os.MkdirTemp("", "whisper")
if err != nil {
return res, err
}
defer os.RemoveAll(dir)
convertedPath := filepath.Join(dir, "converted.wav")
if err := audioToWav(audiopath, convertedPath); err != nil {
return res, err
}
// Open samples
fh, err := os.Open(convertedPath)
if err != nil {
return res, err
}
defer fh.Close()
// Read samples
d := wav.NewDecoder(fh)
buf, err := d.FullPCMBuffer()
if err != nil {
return res, err
}
data := buf.AsFloat32Buffer().Data
// Process samples
context, err := model.NewContext()
if err != nil {
return res, err
}
context.SetThreads(threads)
if language != "" {
context.SetLanguage(language)
} else {
context.SetLanguage("auto")
}
if err := context.Process(data, nil, nil); err != nil {
return res, err
}
for {
s, err := context.NextSegment()
if err != nil {
break
}
var tokens []int
for _, t := range s.Tokens {
tokens = append(tokens, t.Id)
}
segment := schema.Segment{Id: s.Num, Text: s.Text, Start: s.Start, End: s.End, Tokens: tokens}
res.Segments = append(res.Segments, segment)
res.Text += s.Text
}
return res, nil
}

View File

@@ -0,0 +1,26 @@
package main
// This is a wrapper to statisfy the GRPC service interface
// It is meant to be used by the main executable that is the server for the specific backend type (falcon, gpt3, etc)
import (
"github.com/ggerganov/whisper.cpp/bindings/go/pkg/whisper"
"github.com/go-skynet/LocalAI/core/schema"
"github.com/go-skynet/LocalAI/pkg/grpc/base"
pb "github.com/go-skynet/LocalAI/pkg/grpc/proto"
)
type Whisper struct {
base.SingleThread
whisper whisper.Model
}
func (sd *Whisper) Load(opts *pb.ModelOptions) error {
// Note: the Model here is a path to a directory containing the model files
w, err := whisper.New(opts.ModelFile)
sd.whisper = w
return err
}
func (sd *Whisper) AudioTranscription(opts *pb.TranscriptRequest) (schema.TranscriptionResult, error) {
return Transcript(sd.whisper, opts.Dst, opts.Language, uint(opts.Threads))
}

View File

@@ -1,105 +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 (
"os"
"path/filepath"
"github.com/ggerganov/whisper.cpp/bindings/go/pkg/whisper"
"github.com/go-audio/wav"
"github.com/mudler/LocalAI/pkg/grpc/base"
pb "github.com/mudler/LocalAI/pkg/grpc/proto"
"github.com/mudler/LocalAI/pkg/utils"
)
type Whisper struct {
base.SingleThread
whisper whisper.Model
}
func (sd *Whisper) Load(opts *pb.ModelOptions) error {
// Note: the Model here is a path to a directory containing the model files
w, err := whisper.New(opts.ModelFile)
sd.whisper = w
return err
}
func (sd *Whisper) AudioTranscription(opts *pb.TranscriptRequest) (pb.TranscriptResult, error) {
dir, err := os.MkdirTemp("", "whisper")
if err != nil {
return pb.TranscriptResult{}, err
}
defer os.RemoveAll(dir)
convertedPath := filepath.Join(dir, "converted.wav")
if err := utils.AudioToWav(opts.Dst, convertedPath); err != nil {
return pb.TranscriptResult{}, err
}
// Open samples
fh, err := os.Open(convertedPath)
if err != nil {
return pb.TranscriptResult{}, err
}
defer fh.Close()
// Read samples
d := wav.NewDecoder(fh)
buf, err := d.FullPCMBuffer()
if err != nil {
return pb.TranscriptResult{}, err
}
data := buf.AsFloat32Buffer().Data
// Process samples
context, err := sd.whisper.NewContext()
if err != nil {
return pb.TranscriptResult{}, err
}
context.SetThreads(uint(opts.Threads))
if opts.Language != "" {
context.SetLanguage(opts.Language)
} else {
context.SetLanguage("auto")
}
if opts.Translate {
context.SetTranslate(true)
}
if err := context.Process(data, nil, nil); err != nil {
return pb.TranscriptResult{}, err
}
segments := []*pb.TranscriptSegment{}
text := ""
for {
s, err := context.NextSegment()
if err != nil {
break
}
var tokens []int32
for _, t := range s.Tokens {
tokens = append(tokens, int32(t.Id))
}
segment := &pb.TranscriptSegment{Id: int32(s.Num), Text: s.Text, Start: int64(s.Start), End: int64(s.End), Tokens: tokens}
segments = append(segments, segment)
text += s.Text
}
return pb.TranscriptResult{
Segments: segments,
Text: text,
}, nil
}

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 (
"os"
"path/filepath"
"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"
piper "github.com/mudler/go-piper"
)

View File

@@ -1,54 +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 (
"fmt"
"github.com/mudler/LocalAI/pkg/grpc/base"
pb "github.com/mudler/LocalAI/pkg/grpc/proto"
"github.com/streamer45/silero-vad-go/speech"
)
type VAD struct {
base.SingleThread
detector *speech.Detector
}
func (vad *VAD) Load(opts *pb.ModelOptions) error {
v, err := speech.NewDetector(speech.DetectorConfig{
ModelPath: opts.ModelFile,
SampleRate: 16000,
//WindowSize: 1024,
Threshold: 0.5,
MinSilenceDurationMs: 0,
SpeechPadMs: 0,
})
if err != nil {
return fmt.Errorf("create silero detector: %w", err)
}
vad.detector = v
return err
}
func (vad *VAD) VAD(req *pb.VADRequest) (pb.VADResponse, error) {
audio := req.Audio
segments, err := vad.detector.Detect(audio)
if err != nil {
return pb.VADResponse{}, fmt.Errorf("detect: %w", err)
}
vadSegments := []*pb.VADSegment{}
for _, s := range segments {
vadSegments = append(vadSegments, &pb.VADSegment{
Start: float32(s.SpeechStartAt),
End: float32(s.SpeechEndAt),
})
}
return pb.VADResponse{
Segments: vadSegments,
}, nil
}

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