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Author SHA1 Message Date
Sebastian.W
0004ec8be3 fix(autogptq): do not use_triton with qwen-vl (#1985)
* Enhance autogptq backend to support VL models

* update dependencies for autogptq

* remove redundant auto-gptq dependency

* Convert base64 to image_url for Qwen-VL model

* implemented model inference for qwen-vl

* remove user prompt from generated answer

* fixed write image error

* fixed use_triton issue when loading Qwen-VL model

---------

Co-authored-by: Binghua Wu <bingwu@estee.com>
2024-04-11 12:33:58 +02:00
1249 changed files with 64563 additions and 375907 deletions

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@@ -1,8 +0,0 @@
# .air.toml
[build]
cmd = "make build"
bin = "./local-ai"
args_bin = [ "--debug" ]
include_ext = ["go", "html", "yaml", "toml", "json", "txt", "md"]
exclude_dir = ["pkg/grpc/proto"]
delay = 1000

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

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@@ -1,13 +0,0 @@
#!/bin/bash
cd /workspace
# Ensures generated source files are present upon load
make prepare
echo "Standard Post-Start script completed."
if [ -f "/devcontainer-customization/poststart.sh" ]; then
echo "Launching customization poststart.sh"
bash "/devcontainer-customization/poststart.sh"
fi

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@@ -1,55 +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"
```

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@@ -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"
}

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@@ -1,44 +0,0 @@
services:
api:
build:
context: ..
dockerfile: Dockerfile
target: devcontainer
env_file:
- ../.env
ports:
- 8080:8080
volumes:
- localai_workspace:/workspace
- ../models:/host-models
- ./customization:/devcontainer-customization
command: /bin/sh -c "while sleep 1000; do :; done"
cap_add:
- SYS_PTRACE
security_opt:
- seccomp:unconfined
prometheus:
image: prom/prometheus
container_name: prometheus
command:
- '--config.file=/etc/prometheus/prometheus.yml'
ports:
- 9090:9090
restart: unless-stopped
volumes:
- ./prometheus:/etc/prometheus
- prom_data:/prometheus
grafana:
image: grafana/grafana
container_name: grafana
ports:
- 3000:3000
restart: unless-stopped
environment:
- GF_SECURITY_ADMIN_USER=admin
- GF_SECURITY_ADMIN_PASSWORD=grafana
volumes:
- ./grafana:/etc/grafana/provisioning/datasources
volumes:
prom_data:
localai_workspace:

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

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

View File

@@ -1,23 +1,6 @@
.idea
.github
.vscode
.devcontainer
models
backends
examples/chatbot-ui/models
backend/go/image/stablediffusion-ggml/build/
backend/go/*/build
backend/go/*/.cache
backend/go/*/sources
backend/go/*/package
examples/rwkv/models
examples/**/models
Dockerfile*
__pycache__
# SonarQube
.scannerwork
# backend virtual environments
**/venv
backend/python/**/source
Dockerfile*

72
.env
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@@ -1,45 +1,58 @@
## Set number of threads.
## Note: prefer the number of physical cores. Overbooking the CPU degrades performance notably.
# LOCALAI_THREADS=14
# THREADS=14
## Specify a different bind address (defaults to ":8080")
# LOCALAI_ADDRESS=127.0.0.1:8080
# ADDRESS=127.0.0.1:8080
## Default models context size
# LOCALAI_CONTEXT_SIZE=512
# CONTEXT_SIZE=512
#
## Define galleries.
## models will to install will be visible in `/models/available`
# LOCALAI_GALLERIES=[{"name":"localai", "url":"github:mudler/LocalAI/gallery/index.yaml@master"}]
# GALLERIES=[{"name":"model-gallery", "url":"github:go-skynet/model-gallery/index.yaml"}]
## CORS settings
# LOCALAI_CORS=true
# LOCALAI_CORS_ALLOW_ORIGINS=*
# CORS=true
# CORS_ALLOW_ORIGINS=*
## Default path for models
#
# LOCALAI_MODELS_PATH=/models
# MODELS_PATH=/models
## Enable debug mode
# LOCALAI_LOG_LEVEL=debug
# DEBUG=true
## Disables COMPEL (Diffusers)
# COMPEL=0
## Enable/Disable single backend (useful if only one GPU is available)
# LOCALAI_SINGLE_ACTIVE_BACKEND=true
# SINGLE_ACTIVE_BACKEND=true
# 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.
## clBLAS: This is an open-source implementation of the BLAS library that uses OpenCL, a framework for writing programs that execute across heterogeneous platforms consisting of CPUs, GPUs, and other processors. clBLAS is designed to take advantage of the parallel computing power of GPUs but can also run on any hardware that supports OpenCL. This includes hardware from different vendors like Nvidia, AMD, and Intel.
# BUILD_TYPE=openblas
## Uncomment and set to true to enable rebuilding from source
# REBUILD=true
## Enable go tags, available: stablediffusion, tts
## stablediffusion: image generation with stablediffusion
## tts: enables text-to-speech with go-piper
## (requires REBUILD=true)
#
# GO_TAGS=stablediffusion
## Path where to store generated images
# LOCALAI_IMAGE_PATH=/tmp/generated/images
# IMAGE_PATH=/tmp
## Specify a default upload limit in MB (whisper)
# LOCALAI_UPLOAD_LIMIT=15
# UPLOAD_LIMIT
## List of external GRPC backends (note on the container image this variable is already set to use extra backends available in extra/)
# LOCALAI_EXTERNAL_GRPC_BACKENDS=my-backend:127.0.0.1:9000,my-backend2:/usr/bin/backend.py
# EXTERNAL_GRPC_BACKENDS=my-backend:127.0.0.1:9000,my-backend2:/usr/bin/backend.py
### Advanced settings ###
### Those are not really used by LocalAI, but from components in the stack ###
@@ -58,36 +71,19 @@
### Define the number of parallel LLAMA.cpp workers (Defaults to 1)
# LLAMACPP_PARALLEL=1
### Define a list of GRPC Servers for llama-cpp workers to distribute the load
# https://github.com/ggerganov/llama.cpp/pull/6829
# https://github.com/ggerganov/llama.cpp/blob/master/tools/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=""
# PARALLEL_REQUESTS=true
### Watchdog settings
###
# Enables watchdog to kill backends that are inactive for too much time
# LOCALAI_WATCHDOG_IDLE=true
#
# Time in duration format (e.g. 1h30m) after which a backend is considered idle
# LOCALAI_WATCHDOG_IDLE_TIMEOUT=5m
# WATCHDOG_IDLE=true
#
# Enables watchdog to kill backends that are busy for too much time
# LOCALAI_WATCHDOG_BUSY=true
# WATCHDOG_BUSY=true
#
# Time in duration format (e.g. 1h30m) after which a backend is considered idle
# WATCHDOG_IDLE_TIMEOUT=5m
#
# Time in duration format (e.g. 1h30m) after which a backend is considered busy
# LOCALAI_WATCHDOG_BUSY_TIMEOUT=5m
# WATCHDOG_BUSY_TIMEOUT=5m

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

20
.github/bump_deps.sh vendored
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@@ -3,25 +3,7 @@ set -xe
REPO=$1
BRANCH=$2
VAR=$3
FILE=$4
if [ -z "$FILE" ]; then
FILE="Makefile"
fi
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?=" $FILE | cut -d'=' -f2)"
set -e
sed -i $FILE -e "s/$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}" >> "${VAR}_commit.txt"
sed -i Makefile -e "s/$VAR?=.*/$VAR?=$LAST_COMMIT/"

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

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@@ -1,85 +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)

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

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@@ -1,304 +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
}
}

119
.github/dependabot.yml vendored
View File

@@ -1,119 +0,0 @@
# https://docs.github.com/en/code-security/dependabot/dependabot-version-updates/configuration-options-for-the-dependabot.yml-file
version: 2
updates:
- package-ecosystem: "gitsubmodule"
directory: "/"
schedule:
interval: "weekly"
- package-ecosystem: "gomod"
directory: "/"
schedule:
interval: "weekly"
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: "/"
schedule:
# Check for updates to GitHub Actions every weekday
interval: "weekly"
- package-ecosystem: "pip"
# Workflow files stored in the default location of `.github/workflows`. (You don't need to specify `/.github/workflows` for `directory`. You can use `directory: "/"`.)
directory: "/"
schedule:
# Check for updates to GitHub Actions every weekday
interval: "weekly"
- package-ecosystem: "docker"
# Workflow files stored in the default location of `.github/workflows`. (You don't need to specify `/.github/workflows` for `directory`. You can use `directory: "/"`.)
directory: "/"
schedule:
# Check for updates to GitHub Actions every weekday
interval: "weekly"
- package-ecosystem: "pip"
directory: "/backend/python/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/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"

View File

@@ -1,423 +0,0 @@
package main
import (
"context"
"encoding/json"
"fmt"
"io"
"net/http"
"os"
"regexp"
"slices"
"strings"
hfapi "github.com/mudler/LocalAI/pkg/huggingface-api"
cogito "github.com/mudler/cogito"
"github.com/mudler/cogito/structures"
"github.com/sashabaranov/go-openai/jsonschema"
)
var (
openAIModel = os.Getenv("OPENAI_MODEL")
openAIKey = os.Getenv("OPENAI_KEY")
openAIBaseURL = os.Getenv("OPENAI_BASE_URL")
galleryIndexPath = os.Getenv("GALLERY_INDEX_PATH")
//defaultclient
llm = cogito.NewOpenAILLM(openAIModel, openAIKey, openAIBaseURL)
)
// cleanTextContent removes trailing spaces, tabs, and normalizes line endings
// to prevent YAML linting issues like trailing spaces and multiple empty lines
func cleanTextContent(text string) string {
lines := strings.Split(text, "\n")
var cleanedLines []string
var prevEmpty bool
for _, line := range lines {
// Remove all trailing whitespace (spaces, tabs, etc.)
trimmed := strings.TrimRight(line, " \t\r")
// Avoid multiple consecutive empty lines
if trimmed == "" {
if !prevEmpty {
cleanedLines = append(cleanedLines, "")
}
prevEmpty = true
} else {
cleanedLines = append(cleanedLines, trimmed)
prevEmpty = false
}
}
// Remove trailing empty lines from the result
result := strings.Join(cleanedLines, "\n")
return stripThinkingTags(strings.TrimRight(result, "\n"))
}
// isModelExisting checks if a specific model ID exists in the gallery using text search
func isModelExisting(modelID string) (bool, error) {
indexPath := getGalleryIndexPath()
content, err := os.ReadFile(indexPath)
if err != nil {
return false, fmt.Errorf("failed to read %s: %w", indexPath, err)
}
contentStr := string(content)
// Simple text search - if the model ID appears anywhere in the file, it exists
return strings.Contains(contentStr, modelID), nil
}
// filterExistingModels removes models that already exist in the gallery
func filterExistingModels(models []ProcessedModel) ([]ProcessedModel, error) {
var filteredModels []ProcessedModel
for _, model := range models {
exists, err := isModelExisting(model.ModelID)
if err != nil {
fmt.Printf("Error checking if model %s exists: %v, skipping\n", model.ModelID, err)
continue
}
if !exists {
filteredModels = append(filteredModels, model)
} else {
fmt.Printf("Skipping existing model: %s\n", model.ModelID)
}
}
fmt.Printf("Filtered out %d existing models, %d new models remaining\n",
len(models)-len(filteredModels), len(filteredModels))
return filteredModels, nil
}
// getGalleryIndexPath returns the gallery index file path, with a default fallback
func getGalleryIndexPath() string {
if galleryIndexPath != "" {
return galleryIndexPath
}
return "gallery/index.yaml"
}
func stripThinkingTags(content string) string {
// Remove content between <thinking> and </thinking> (including multi-line)
content = regexp.MustCompile(`(?s)<thinking>.*?</thinking>`).ReplaceAllString(content, "")
// Remove content between <think> and </think> (including multi-line)
content = regexp.MustCompile(`(?s)<think>.*?</think>`).ReplaceAllString(content, "")
// Clean up any extra whitespace
content = strings.TrimSpace(content)
return content
}
func getRealReadme(ctx context.Context, repository string) (string, error) {
// Create a conversation fragment
fragment := cogito.NewEmptyFragment().
AddMessage("user",
`Your task is to get a clear description of a large language model from huggingface by using the provided tool. I will share with you a repository that might be quantized, and as such probably not by the original model author. We need to get the real description of the model, and not the one that might be quantized. You will have to call the tool to get the readme more than once by figuring out from the quantized readme which is the base model readme. This is the repository: `+repository)
// Execute with tools
result, err := cogito.ExecuteTools(llm, fragment,
cogito.WithIterations(3),
cogito.WithMaxAttempts(3),
cogito.WithTools(&HFReadmeTool{client: hfapi.NewClient()}))
if err != nil {
return "", err
}
result = result.AddMessage("user", "Describe the model in a clear and concise way that can be shared in a model gallery.")
// Get a response
newFragment, err := llm.Ask(ctx, result)
if err != nil {
return "", err
}
content := newFragment.LastMessage().Content
return cleanTextContent(content), nil
}
func selectMostInterestingModels(ctx context.Context, searchResult *SearchResult) ([]ProcessedModel, error) {
// Create a conversation fragment
fragment := cogito.NewEmptyFragment().
AddMessage("user",
`Your task is to analyze a list of AI models and select the most interesting ones for a model gallery. You will be given detailed information about multiple models including their metadata, file information, and README content.
Consider the following criteria when selecting models:
1. Model popularity (download count)
2. Model recency (last modified date)
3. Model completeness (has preferred model file, README, etc.)
4. Model uniqueness (not duplicates or very similar models)
5. Model quality (based on README content and description)
6. Model utility (practical applications)
You should select models that would be most valuable for users browsing a model gallery. Prioritize models that are:
- Well-documented with clear READMEs
- Recently updated
- Popular (high download count)
- Have the preferred quantization format available
- Offer unique capabilities or are from reputable authors
Return your analysis and selection reasoning.`)
// Add the search results as context
modelsInfo := fmt.Sprintf("Found %d models matching '%s' with quantization preference '%s':\n\n",
searchResult.TotalModelsFound, searchResult.SearchTerm, searchResult.Quantization)
for i, model := range searchResult.Models {
modelsInfo += fmt.Sprintf("Model %d:\n", i+1)
modelsInfo += fmt.Sprintf(" ID: %s\n", model.ModelID)
modelsInfo += fmt.Sprintf(" Author: %s\n", model.Author)
modelsInfo += fmt.Sprintf(" Downloads: %d\n", model.Downloads)
modelsInfo += fmt.Sprintf(" Last Modified: %s\n", model.LastModified)
modelsInfo += fmt.Sprintf(" Files: %d files\n", len(model.Files))
if model.PreferredModelFile != nil {
modelsInfo += fmt.Sprintf(" Preferred Model File: %s (%d bytes)\n",
model.PreferredModelFile.Path, model.PreferredModelFile.Size)
} else {
modelsInfo += " No preferred model file found\n"
}
if model.ReadmeContent != "" {
modelsInfo += fmt.Sprintf(" README: %s\n", model.ReadmeContent)
}
if model.ProcessingError != "" {
modelsInfo += fmt.Sprintf(" Processing Error: %s\n", model.ProcessingError)
}
modelsInfo += "\n"
}
fragment = fragment.AddMessage("user", modelsInfo)
fragment = fragment.AddMessage("user", "Based on your analysis, select the top 5 most interesting models and provide a brief explanation for each selection. Also, create a filtered SearchResult with only the selected models. Return just a list of repositories IDs, you will later be asked to output it as a JSON array with the json tool.")
// Get a response
newFragment, err := llm.Ask(ctx, fragment)
if err != nil {
return nil, err
}
fmt.Println(newFragment.LastMessage().Content)
repositories := struct {
Repositories []string `json:"repositories"`
}{}
s := structures.Structure{
Schema: jsonschema.Definition{
Type: jsonschema.Object,
AdditionalProperties: false,
Properties: map[string]jsonschema.Definition{
"repositories": {
Type: jsonschema.Array,
Items: &jsonschema.Definition{Type: jsonschema.String},
Description: "The trending repositories IDs",
},
},
Required: []string{"repositories"},
},
Object: &repositories,
}
err = newFragment.ExtractStructure(ctx, llm, s)
if err != nil {
return nil, err
}
filteredModels := []ProcessedModel{}
for _, m := range searchResult.Models {
if slices.Contains(repositories.Repositories, m.ModelID) {
filteredModels = append(filteredModels, m)
}
}
return filteredModels, nil
}
// ModelMetadata represents extracted metadata from a model
type ModelMetadata struct {
Tags []string `json:"tags"`
License string `json:"license"`
}
// extractModelMetadata extracts tags and license from model README and documentation
func extractModelMetadata(ctx context.Context, model ProcessedModel) ([]string, string, error) {
// Create a conversation fragment
fragment := cogito.NewEmptyFragment().
AddMessage("user",
`Your task is to extract metadata from an AI model's README and documentation. You will be provided with:
1. Model information (ID, author, description)
2. README content
You need to extract:
1. **Tags**: An array of relevant tags that describe the model. Use common tags from the gallery such as:
- llm, gguf, gpu, cpu, multimodal, image-to-text, text-to-text, text-to-speech, tts
- thinking, reasoning, chat, instruction-tuned, code, vision
- Model family names (e.g., llama, qwen, mistral, gemma) if applicable
- Any other relevant descriptive tags
Select 3-8 most relevant tags.
2. **License**: The license identifier (e.g., "apache-2.0", "mit", "llama2", "gpl-3.0", "bsd", "cc-by-4.0").
If no license is found, return an empty string.
Return the extracted metadata in a structured format.`)
// Add model information
modelInfo := "Model Information:\n"
modelInfo += fmt.Sprintf(" ID: %s\n", model.ModelID)
modelInfo += fmt.Sprintf(" Author: %s\n", model.Author)
modelInfo += fmt.Sprintf(" Downloads: %d\n", model.Downloads)
if model.ReadmeContent != "" {
modelInfo += fmt.Sprintf(" README Content:\n%s\n", model.ReadmeContent)
} else if model.ReadmeContentPreview != "" {
modelInfo += fmt.Sprintf(" README Preview: %s\n", model.ReadmeContentPreview)
}
fragment = fragment.AddMessage("user", modelInfo)
fragment = fragment.AddMessage("user", "Extract the tags and license from the model information. Return the metadata as a JSON object with 'tags' (array of strings) and 'license' (string).")
// Get a response
newFragment, err := llm.Ask(ctx, fragment)
if err != nil {
return nil, "", err
}
// Extract structured metadata
metadata := ModelMetadata{}
s := structures.Structure{
Schema: jsonschema.Definition{
Type: jsonschema.Object,
AdditionalProperties: false,
Properties: map[string]jsonschema.Definition{
"tags": {
Type: jsonschema.Array,
Items: &jsonschema.Definition{Type: jsonschema.String},
Description: "Array of relevant tags describing the model",
},
"license": {
Type: jsonschema.String,
Description: "License identifier (e.g., apache-2.0, mit, llama2). Empty string if not found.",
},
},
Required: []string{"tags", "license"},
},
Object: &metadata,
}
err = newFragment.ExtractStructure(ctx, llm, s)
if err != nil {
return nil, "", err
}
return metadata.Tags, metadata.License, nil
}
// extractIconFromReadme scans the README content for image URLs and returns the first suitable icon URL found
func extractIconFromReadme(readmeContent string) string {
if readmeContent == "" {
return ""
}
// Regular expressions to match image URLs in various formats (case-insensitive)
// Match markdown image syntax: ![alt](url) - case insensitive extensions
markdownImageRegex := regexp.MustCompile(`(?i)!\[[^\]]*\]\(([^)]+\.(png|jpg|jpeg|svg|webp|gif))\)`)
// Match HTML img tags: <img src="url">
htmlImageRegex := regexp.MustCompile(`(?i)<img[^>]+src=["']([^"']+\.(png|jpg|jpeg|svg|webp|gif))["']`)
// Match plain URLs ending with image extensions
plainImageRegex := regexp.MustCompile(`(?i)https?://[^\s<>"']+\.(png|jpg|jpeg|svg|webp|gif)`)
// Try markdown format first
matches := markdownImageRegex.FindStringSubmatch(readmeContent)
if len(matches) > 1 && matches[1] != "" {
url := strings.TrimSpace(matches[1])
// Prefer HuggingFace CDN URLs or absolute URLs
if strings.HasPrefix(strings.ToLower(url), "http") {
return url
}
}
// Try HTML img tags
matches = htmlImageRegex.FindStringSubmatch(readmeContent)
if len(matches) > 1 && matches[1] != "" {
url := strings.TrimSpace(matches[1])
if strings.HasPrefix(strings.ToLower(url), "http") {
return url
}
}
// Try plain URLs
matches = plainImageRegex.FindStringSubmatch(readmeContent)
if len(matches) > 0 {
url := strings.TrimSpace(matches[0])
if strings.HasPrefix(strings.ToLower(url), "http") {
return url
}
}
return ""
}
// getHuggingFaceAvatarURL attempts to get the HuggingFace avatar URL for a user
func getHuggingFaceAvatarURL(author string) string {
if author == "" {
return ""
}
// Try to fetch user info from HuggingFace API
// HuggingFace API endpoint: https://huggingface.co/api/users/{username}
baseURL := "https://huggingface.co"
userURL := fmt.Sprintf("%s/api/users/%s", baseURL, author)
req, err := http.NewRequest("GET", userURL, nil)
if err != nil {
return ""
}
client := &http.Client{}
resp, err := client.Do(req)
if err != nil {
return ""
}
defer resp.Body.Close()
if resp.StatusCode != http.StatusOK {
return ""
}
// Parse the response to get avatar URL
var userInfo map[string]interface{}
body, err := io.ReadAll(resp.Body)
if err != nil {
return ""
}
if err := json.Unmarshal(body, &userInfo); err != nil {
return ""
}
// Try to extract avatar URL from response
if avatar, ok := userInfo["avatarUrl"].(string); ok && avatar != "" {
return avatar
}
if avatar, ok := userInfo["avatar"].(string); ok && avatar != "" {
return avatar
}
return ""
}
// extractModelIcon extracts icon URL from README or falls back to HuggingFace avatar
func extractModelIcon(model ProcessedModel) string {
// First, try to extract icon from README
if icon := extractIconFromReadme(model.ReadmeContent); icon != "" {
return icon
}
// Fallback: Try to get HuggingFace user avatar
if model.Author != "" {
if avatar := getHuggingFaceAvatarURL(model.Author); avatar != "" {
return avatar
}
}
return ""
}

View File

@@ -1,200 +0,0 @@
package main
import (
"context"
"encoding/json"
"fmt"
"os"
"strings"
"github.com/ghodss/yaml"
"github.com/mudler/LocalAI/core/gallery/importers"
)
func formatTextContent(text string) string {
return formatTextContentWithIndent(text, 4, 6)
}
// formatTextContentWithIndent formats text content with specified base and list item indentation
func formatTextContentWithIndent(text string, baseIndent int, listItemIndent int) string {
var formattedLines []string
lines := strings.Split(text, "\n")
for _, line := range lines {
trimmed := strings.TrimRight(line, " \t\r")
if trimmed == "" {
// Keep empty lines as empty (no indentation)
formattedLines = append(formattedLines, "")
} else {
// Preserve relative indentation from yaml.Marshal output
// Count existing leading spaces to preserve relative structure
leadingSpaces := len(trimmed) - len(strings.TrimLeft(trimmed, " \t"))
trimmedStripped := strings.TrimLeft(trimmed, " \t")
var totalIndent int
if strings.HasPrefix(trimmedStripped, "-") {
// List items: use listItemIndent (ignore existing leading spaces)
totalIndent = listItemIndent
} else {
// Regular lines: use baseIndent + preserve relative indentation
// This handles both top-level keys (leadingSpaces=0) and nested properties (leadingSpaces>0)
totalIndent = baseIndent + leadingSpaces
}
indentStr := strings.Repeat(" ", totalIndent)
formattedLines = append(formattedLines, indentStr+trimmedStripped)
}
}
formattedText := strings.Join(formattedLines, "\n")
// Remove any trailing spaces from the formatted description
formattedText = strings.TrimRight(formattedText, " \t")
return formattedText
}
// generateYAMLEntry generates a YAML entry for a model using the specified anchor
func generateYAMLEntry(model ProcessedModel, quantization string) string {
modelConfig, err := importers.DiscoverModelConfig("https://huggingface.co/"+model.ModelID, json.RawMessage(`{ "quantization": "`+quantization+`"}`))
if err != nil {
panic(err)
}
// Extract model name from ModelID
parts := strings.Split(model.ModelID, "/")
modelName := model.ModelID
if len(parts) > 0 {
modelName = strings.ToLower(parts[len(parts)-1])
}
// Remove common suffixes
modelName = strings.ReplaceAll(modelName, "-gguf", "")
modelName = strings.ReplaceAll(modelName, "-q4_k_m", "")
modelName = strings.ReplaceAll(modelName, "-q4_k_s", "")
modelName = strings.ReplaceAll(modelName, "-q3_k_m", "")
modelName = strings.ReplaceAll(modelName, "-q2_k", "")
description := model.ReadmeContent
if description == "" {
description = fmt.Sprintf("AI model: %s", modelName)
}
// Clean up description to prevent YAML linting issues
description = cleanTextContent(description)
formattedDescription := formatTextContent(description)
configFile := formatTextContent(modelConfig.ConfigFile)
filesYAML, _ := yaml.Marshal(modelConfig.Files)
// Files section: list items need 4 spaces (not 6), since files: is at 2 spaces
files := formatTextContentWithIndent(string(filesYAML), 4, 4)
// Build metadata sections
var metadataSections []string
// Add license if present
if model.License != "" {
metadataSections = append(metadataSections, fmt.Sprintf(` license: "%s"`, model.License))
}
// Add tags if present
if len(model.Tags) > 0 {
tagsYAML, _ := yaml.Marshal(model.Tags)
tagsFormatted := formatTextContentWithIndent(string(tagsYAML), 4, 4)
tagsFormatted = strings.TrimRight(tagsFormatted, "\n")
metadataSections = append(metadataSections, fmt.Sprintf(" tags:\n%s", tagsFormatted))
}
// Add icon if present
if model.Icon != "" {
metadataSections = append(metadataSections, fmt.Sprintf(` icon: %s`, model.Icon))
}
// Build the metadata block
metadataBlock := ""
if len(metadataSections) > 0 {
metadataBlock = strings.Join(metadataSections, "\n") + "\n"
}
yamlTemplate := ""
yamlTemplate = `- name: "%s"
url: "github:mudler/LocalAI/gallery/virtual.yaml@master"
urls:
- https://huggingface.co/%s
description: |
%s%s
overrides:
%s
files:
%s`
// Trim trailing newlines from formatted sections to prevent extra blank lines
formattedDescription = strings.TrimRight(formattedDescription, "\n")
configFile = strings.TrimRight(configFile, "\n")
files = strings.TrimRight(files, "\n")
// Add newline before metadata block if present
if metadataBlock != "" {
metadataBlock = "\n" + strings.TrimRight(metadataBlock, "\n")
}
return fmt.Sprintf(yamlTemplate,
modelName,
model.ModelID,
formattedDescription,
metadataBlock,
configFile,
files,
)
}
// generateYAMLForModels generates YAML entries for selected models and appends to index.yaml
func generateYAMLForModels(ctx context.Context, models []ProcessedModel, quantization string) error {
// Generate YAML entries for each model
var yamlEntries []string
for _, model := range models {
fmt.Printf("Generating YAML entry for model: %s\n", model.ModelID)
// Generate YAML entry
yamlEntry := generateYAMLEntry(model, quantization)
yamlEntries = append(yamlEntries, yamlEntry)
}
// Prepend to index.yaml (write at the top)
if len(yamlEntries) > 0 {
indexPath := getGalleryIndexPath()
fmt.Printf("Prepending YAML entries to %s...\n", indexPath)
// Read current content
content, err := os.ReadFile(indexPath)
if err != nil {
return fmt.Errorf("failed to read %s: %w", indexPath, err)
}
existingContent := string(content)
yamlBlock := strings.Join(yamlEntries, "\n")
// Check if file starts with "---"
var newContent string
if strings.HasPrefix(existingContent, "---\n") {
// File starts with "---", prepend new entries after it
restOfContent := strings.TrimPrefix(existingContent, "---\n")
// Ensure proper spacing: "---\n" + new entries + "\n" + rest of content
newContent = "---\n" + yamlBlock + "\n" + restOfContent
} else if strings.HasPrefix(existingContent, "---") {
// File starts with "---" but no newline after
restOfContent := strings.TrimPrefix(existingContent, "---")
newContent = "---\n" + yamlBlock + "\n" + strings.TrimPrefix(restOfContent, "\n")
} else {
// No "---" at start, prepend new entries at the very beginning
// Trim leading whitespace from existing content
existingContent = strings.TrimLeft(existingContent, " \t\n\r")
newContent = yamlBlock + "\n" + existingContent
}
// Write back to file
err = os.WriteFile(indexPath, []byte(newContent), 0644)
if err != nil {
return fmt.Errorf("failed to write %s: %w", indexPath, err)
}
fmt.Printf("Successfully prepended %d models to %s\n", len(yamlEntries), indexPath)
}
return nil
}

View File

@@ -1,373 +0,0 @@
package main
import (
"context"
"encoding/json"
"fmt"
"os"
"strconv"
"strings"
"time"
hfapi "github.com/mudler/LocalAI/pkg/huggingface-api"
)
// ProcessedModelFile represents a processed model file with additional metadata
type ProcessedModelFile struct {
Path string `json:"path"`
Size int64 `json:"size"`
SHA256 string `json:"sha256"`
IsReadme bool `json:"is_readme"`
FileType string `json:"file_type"` // "model", "readme", "other"
}
// ProcessedModel represents a processed model with all gathered metadata
type ProcessedModel struct {
ModelID string `json:"model_id"`
Author string `json:"author"`
Downloads int `json:"downloads"`
LastModified string `json:"last_modified"`
Files []ProcessedModelFile `json:"files"`
PreferredModelFile *ProcessedModelFile `json:"preferred_model_file,omitempty"`
ReadmeFile *ProcessedModelFile `json:"readme_file,omitempty"`
ReadmeContent string `json:"readme_content,omitempty"`
ReadmeContentPreview string `json:"readme_content_preview,omitempty"`
QuantizationPreferences []string `json:"quantization_preferences"`
ProcessingError string `json:"processing_error,omitempty"`
Tags []string `json:"tags,omitempty"`
License string `json:"license,omitempty"`
Icon string `json:"icon,omitempty"`
}
// SearchResult represents the complete result of searching and processing models
type SearchResult struct {
SearchTerm string `json:"search_term"`
Limit int `json:"limit"`
Quantization string `json:"quantization"`
TotalModelsFound int `json:"total_models_found"`
Models []ProcessedModel `json:"models"`
FormattedOutput string `json:"formatted_output"`
}
// AddedModelSummary represents a summary of models added to the gallery
type AddedModelSummary struct {
SearchTerm string `json:"search_term"`
TotalFound int `json:"total_found"`
ModelsAdded int `json:"models_added"`
AddedModelIDs []string `json:"added_model_ids"`
AddedModelURLs []string `json:"added_model_urls"`
Quantization string `json:"quantization"`
ProcessingTime string `json:"processing_time"`
}
func main() {
startTime := time.Now()
// Check for synthetic mode
syntheticMode := os.Getenv("SYNTHETIC_MODE")
if syntheticMode == "true" || syntheticMode == "1" {
fmt.Println("Running in SYNTHETIC MODE - generating random test data")
err := runSyntheticMode()
if err != nil {
fmt.Fprintf(os.Stderr, "Error in synthetic mode: %v\n", err)
os.Exit(1)
}
return
}
// Get configuration from environment variables
searchTerm := os.Getenv("SEARCH_TERM")
if searchTerm == "" {
searchTerm = "GGUF"
}
limitStr := os.Getenv("LIMIT")
if limitStr == "" {
limitStr = "5"
}
limit, err := strconv.Atoi(limitStr)
if err != nil {
fmt.Fprintf(os.Stderr, "Error parsing LIMIT: %v\n", err)
os.Exit(1)
}
quantization := os.Getenv("QUANTIZATION")
maxModels := os.Getenv("MAX_MODELS")
if maxModels == "" {
maxModels = "1"
}
maxModelsInt, err := strconv.Atoi(maxModels)
if err != nil {
fmt.Fprintf(os.Stderr, "Error parsing MAX_MODELS: %v\n", err)
os.Exit(1)
}
// Print configuration
fmt.Printf("Gallery Agent Configuration:\n")
fmt.Printf(" Search Term: %s\n", searchTerm)
fmt.Printf(" Limit: %d\n", limit)
fmt.Printf(" Quantization: %s\n", quantization)
fmt.Printf(" Max Models to Add: %d\n", maxModelsInt)
fmt.Printf(" Gallery Index Path: %s\n", os.Getenv("GALLERY_INDEX_PATH"))
fmt.Println()
result, err := searchAndProcessModels(searchTerm, limit, quantization)
if err != nil {
fmt.Fprintf(os.Stderr, "Error: %v\n", err)
os.Exit(1)
}
fmt.Println(result.FormattedOutput)
// Use AI agent to select the most interesting models
fmt.Println("Using AI agent to select the most interesting models...")
models, err := selectMostInterestingModels(context.Background(), result)
if err != nil {
fmt.Fprintf(os.Stderr, "Error in model selection: %v\n", err)
// Continue with original result if selection fails
models = result.Models
}
fmt.Print(models)
// Filter out models that already exist in the gallery
fmt.Println("Filtering out existing models...")
models, err = filterExistingModels(models)
if err != nil {
fmt.Fprintf(os.Stderr, "Error filtering existing models: %v\n", err)
os.Exit(1)
}
// Limit to maxModelsInt after filtering
if len(models) > maxModelsInt {
models = models[:maxModelsInt]
}
// Track added models for summary
var addedModelIDs []string
var addedModelURLs []string
// Generate YAML entries and append to gallery/index.yaml
if len(models) > 0 {
for _, model := range models {
addedModelIDs = append(addedModelIDs, model.ModelID)
// Generate Hugging Face URL for the model
modelURL := fmt.Sprintf("https://huggingface.co/%s", model.ModelID)
addedModelURLs = append(addedModelURLs, modelURL)
}
fmt.Println("Generating YAML entries for selected models...")
err = generateYAMLForModels(context.Background(), models, quantization)
if err != nil {
fmt.Fprintf(os.Stderr, "Error generating YAML entries: %v\n", err)
os.Exit(1)
}
} else {
fmt.Println("No new models to add to the gallery.")
}
// Create and write summary
processingTime := time.Since(startTime).String()
summary := AddedModelSummary{
SearchTerm: searchTerm,
TotalFound: result.TotalModelsFound,
ModelsAdded: len(addedModelIDs),
AddedModelIDs: addedModelIDs,
AddedModelURLs: addedModelURLs,
Quantization: quantization,
ProcessingTime: processingTime,
}
// Write summary to file
summaryData, err := json.MarshalIndent(summary, "", " ")
if err != nil {
fmt.Fprintf(os.Stderr, "Error marshaling summary: %v\n", err)
} else {
err = os.WriteFile("gallery-agent-summary.json", summaryData, 0644)
if err != nil {
fmt.Fprintf(os.Stderr, "Error writing summary file: %v\n", err)
} else {
fmt.Printf("Summary written to gallery-agent-summary.json\n")
}
}
}
func searchAndProcessModels(searchTerm string, limit int, quantization string) (*SearchResult, error) {
client := hfapi.NewClient()
var outputBuilder strings.Builder
fmt.Println("Searching for models...")
// Initialize the result struct
result := &SearchResult{
SearchTerm: searchTerm,
Limit: limit,
Quantization: quantization,
Models: []ProcessedModel{},
}
models, err := client.GetLatest(searchTerm, limit)
if err != nil {
return nil, fmt.Errorf("failed to fetch models: %w", err)
}
fmt.Println("Models found:", len(models))
result.TotalModelsFound = len(models)
if len(models) == 0 {
outputBuilder.WriteString("No models found.\n")
result.FormattedOutput = outputBuilder.String()
return result, nil
}
outputBuilder.WriteString(fmt.Sprintf("Found %d models matching '%s':\n\n", len(models), searchTerm))
// Process each model
for i, model := range models {
outputBuilder.WriteString(fmt.Sprintf("%d. Processing Model: %s\n", i+1, model.ModelID))
outputBuilder.WriteString(fmt.Sprintf(" Author: %s\n", model.Author))
outputBuilder.WriteString(fmt.Sprintf(" Downloads: %d\n", model.Downloads))
outputBuilder.WriteString(fmt.Sprintf(" Last Modified: %s\n", model.LastModified))
// Initialize processed model struct
processedModel := ProcessedModel{
ModelID: model.ModelID,
Author: model.Author,
Downloads: model.Downloads,
LastModified: model.LastModified,
QuantizationPreferences: []string{quantization, "Q4_K_M", "Q4_K_S", "Q3_K_M", "Q2_K"},
}
// Get detailed model information
details, err := client.GetModelDetails(model.ModelID)
if err != nil {
errorMsg := fmt.Sprintf(" Error getting model details: %v\n", err)
outputBuilder.WriteString(errorMsg)
processedModel.ProcessingError = err.Error()
result.Models = append(result.Models, processedModel)
continue
}
// Define quantization preferences (in order of preference)
quantizationPreferences := []string{quantization, "Q4_K_M", "Q4_K_S", "Q3_K_M", "Q2_K"}
// Find preferred model file
preferredModelFile := hfapi.FindPreferredModelFile(details.Files, quantizationPreferences)
// Process files
processedFiles := make([]ProcessedModelFile, len(details.Files))
for j, file := range details.Files {
fileType := "other"
if file.IsReadme {
fileType = "readme"
} else if preferredModelFile != nil && file.Path == preferredModelFile.Path {
fileType = "model"
}
processedFiles[j] = ProcessedModelFile{
Path: file.Path,
Size: file.Size,
SHA256: file.SHA256,
IsReadme: file.IsReadme,
FileType: fileType,
}
}
processedModel.Files = processedFiles
// Set preferred model file
if preferredModelFile != nil {
for _, file := range processedFiles {
if file.Path == preferredModelFile.Path {
processedModel.PreferredModelFile = &file
break
}
}
}
// Print file information
outputBuilder.WriteString(fmt.Sprintf(" Files found: %d\n", len(details.Files)))
if preferredModelFile != nil {
outputBuilder.WriteString(fmt.Sprintf(" Preferred Model File: %s (SHA256: %s)\n",
preferredModelFile.Path,
preferredModelFile.SHA256))
} else {
outputBuilder.WriteString(fmt.Sprintf(" No model file found with quantization preferences: %v\n", quantizationPreferences))
}
if details.ReadmeFile != nil {
outputBuilder.WriteString(fmt.Sprintf(" README File: %s\n", details.ReadmeFile.Path))
// Find and set readme file
for _, file := range processedFiles {
if file.IsReadme {
processedModel.ReadmeFile = &file
break
}
}
fmt.Println("Getting real readme for", model.ModelID, "waiting...")
// Use agent to get the real readme and prepare the model description
readmeContent, err := getRealReadme(context.Background(), model.ModelID)
if err == nil {
processedModel.ReadmeContent = readmeContent
processedModel.ReadmeContentPreview = truncateString(readmeContent, 200)
outputBuilder.WriteString(fmt.Sprintf(" README Content Preview: %s\n",
processedModel.ReadmeContentPreview))
} else {
continue
}
fmt.Println("Real readme got", readmeContent)
// Extract metadata (tags, license) from README using LLM
fmt.Println("Extracting metadata for", model.ModelID, "waiting...")
tags, license, err := extractModelMetadata(context.Background(), processedModel)
if err == nil {
processedModel.Tags = tags
processedModel.License = license
outputBuilder.WriteString(fmt.Sprintf(" Tags: %v\n", tags))
outputBuilder.WriteString(fmt.Sprintf(" License: %s\n", license))
} else {
fmt.Printf(" Warning: Failed to extract metadata: %v\n", err)
}
// Extract icon from README or use HuggingFace avatar
icon := extractModelIcon(processedModel)
if icon != "" {
processedModel.Icon = icon
outputBuilder.WriteString(fmt.Sprintf(" Icon: %s\n", icon))
}
// Get README content
// readmeContent, err := client.GetReadmeContent(model.ModelID, details.ReadmeFile.Path)
// if err == nil {
// processedModel.ReadmeContent = readmeContent
// processedModel.ReadmeContentPreview = truncateString(readmeContent, 200)
// outputBuilder.WriteString(fmt.Sprintf(" README Content Preview: %s\n",
// processedModel.ReadmeContentPreview))
// }
}
// Print all files with their checksums
outputBuilder.WriteString(" All Files:\n")
for _, file := range processedFiles {
outputBuilder.WriteString(fmt.Sprintf(" - %s (%s, %d bytes", file.Path, file.FileType, file.Size))
if file.SHA256 != "" {
outputBuilder.WriteString(fmt.Sprintf(", SHA256: %s", file.SHA256))
}
outputBuilder.WriteString(")\n")
}
outputBuilder.WriteString("\n")
result.Models = append(result.Models, processedModel)
}
result.FormattedOutput = outputBuilder.String()
return result, nil
}
func truncateString(s string, maxLen int) string {
if len(s) <= maxLen {
return s
}
return s[:maxLen] + "..."
}

View File

@@ -1,224 +0,0 @@
package main
import (
"context"
"fmt"
"math/rand"
"strings"
"time"
)
// runSyntheticMode generates synthetic test data and appends it to the gallery
func runSyntheticMode() error {
generator := NewSyntheticDataGenerator()
// Generate a random number of synthetic models (1-3)
numModels := generator.rand.Intn(3) + 1
fmt.Printf("Generating %d synthetic models for testing...\n", numModels)
var models []ProcessedModel
for i := 0; i < numModels; i++ {
model := generator.GenerateProcessedModel()
models = append(models, model)
fmt.Printf("Generated synthetic model: %s\n", model.ModelID)
}
// Generate YAML entries and append to gallery/index.yaml
fmt.Println("Generating YAML entries for synthetic models...")
err := generateYAMLForModels(context.Background(), models, "Q4_K_M")
if err != nil {
return fmt.Errorf("error generating YAML entries: %w", err)
}
fmt.Printf("Successfully added %d synthetic models to the gallery for testing!\n", len(models))
return nil
}
// SyntheticDataGenerator provides methods to generate synthetic test data
type SyntheticDataGenerator struct {
rand *rand.Rand
}
// NewSyntheticDataGenerator creates a new synthetic data generator
func NewSyntheticDataGenerator() *SyntheticDataGenerator {
return &SyntheticDataGenerator{
rand: rand.New(rand.NewSource(time.Now().UnixNano())),
}
}
// GenerateProcessedModelFile creates a synthetic ProcessedModelFile
func (g *SyntheticDataGenerator) GenerateProcessedModelFile() ProcessedModelFile {
fileTypes := []string{"model", "readme", "other"}
fileType := fileTypes[g.rand.Intn(len(fileTypes))]
var path string
var isReadme bool
switch fileType {
case "model":
path = fmt.Sprintf("model-%s.gguf", g.randomString(8))
isReadme = false
case "readme":
path = "README.md"
isReadme = true
default:
path = fmt.Sprintf("file-%s.txt", g.randomString(6))
isReadme = false
}
return ProcessedModelFile{
Path: path,
Size: int64(g.rand.Intn(1000000000) + 1000000), // 1MB to 1GB
SHA256: g.randomSHA256(),
IsReadme: isReadme,
FileType: fileType,
}
}
// GenerateProcessedModel creates a synthetic ProcessedModel
func (g *SyntheticDataGenerator) GenerateProcessedModel() ProcessedModel {
authors := []string{"microsoft", "meta", "google", "openai", "anthropic", "mistralai", "huggingface"}
modelNames := []string{"llama", "gpt", "claude", "mistral", "gemma", "phi", "qwen", "codellama"}
author := authors[g.rand.Intn(len(authors))]
modelName := modelNames[g.rand.Intn(len(modelNames))]
modelID := fmt.Sprintf("%s/%s-%s", author, modelName, g.randomString(6))
// Generate files
numFiles := g.rand.Intn(5) + 2 // 2-6 files
files := make([]ProcessedModelFile, numFiles)
// Ensure at least one model file and one readme
hasModelFile := false
hasReadme := false
for i := 0; i < numFiles; i++ {
files[i] = g.GenerateProcessedModelFile()
if files[i].FileType == "model" {
hasModelFile = true
}
if files[i].FileType == "readme" {
hasReadme = true
}
}
// Add required files if missing
if !hasModelFile {
modelFile := g.GenerateProcessedModelFile()
modelFile.FileType = "model"
modelFile.Path = fmt.Sprintf("%s-Q4_K_M.gguf", modelName)
files = append(files, modelFile)
}
if !hasReadme {
readmeFile := g.GenerateProcessedModelFile()
readmeFile.FileType = "readme"
readmeFile.Path = "README.md"
readmeFile.IsReadme = true
files = append(files, readmeFile)
}
// Find preferred model file
var preferredModelFile *ProcessedModelFile
for i := range files {
if files[i].FileType == "model" {
preferredModelFile = &files[i]
break
}
}
// Find readme file
var readmeFile *ProcessedModelFile
for i := range files {
if files[i].FileType == "readme" {
readmeFile = &files[i]
break
}
}
readmeContent := g.generateReadmeContent(modelName, author)
// Generate sample metadata
licenses := []string{"apache-2.0", "mit", "llama2", "gpl-3.0", "bsd", ""}
license := licenses[g.rand.Intn(len(licenses))]
sampleTags := []string{"llm", "gguf", "gpu", "cpu", "text-to-text", "chat", "instruction-tuned"}
numTags := g.rand.Intn(4) + 3 // 3-6 tags
tags := make([]string, numTags)
for i := 0; i < numTags; i++ {
tags[i] = sampleTags[g.rand.Intn(len(sampleTags))]
}
// Remove duplicates
tags = g.removeDuplicates(tags)
// Optionally include icon (50% chance)
icon := ""
if g.rand.Intn(2) == 0 {
icon = fmt.Sprintf("https://cdn-avatars.huggingface.co/v1/production/uploads/%s.png", g.randomString(24))
}
return ProcessedModel{
ModelID: modelID,
Author: author,
Downloads: g.rand.Intn(1000000) + 1000,
LastModified: g.randomDate(),
Files: files,
PreferredModelFile: preferredModelFile,
ReadmeFile: readmeFile,
ReadmeContent: readmeContent,
ReadmeContentPreview: truncateString(readmeContent, 200),
QuantizationPreferences: []string{"Q4_K_M", "Q4_K_S", "Q3_K_M", "Q2_K"},
ProcessingError: "",
Tags: tags,
License: license,
Icon: icon,
}
}
// Helper methods for synthetic data generation
func (g *SyntheticDataGenerator) randomString(length int) string {
const charset = "abcdefghijklmnopqrstuvwxyz0123456789"
b := make([]byte, length)
for i := range b {
b[i] = charset[g.rand.Intn(len(charset))]
}
return string(b)
}
func (g *SyntheticDataGenerator) randomSHA256() string {
const charset = "0123456789abcdef"
b := make([]byte, 64)
for i := range b {
b[i] = charset[g.rand.Intn(len(charset))]
}
return string(b)
}
func (g *SyntheticDataGenerator) randomDate() string {
now := time.Now()
daysAgo := g.rand.Intn(365) // Random date within last year
pastDate := now.AddDate(0, 0, -daysAgo)
return pastDate.Format("2006-01-02T15:04:05.000Z")
}
func (g *SyntheticDataGenerator) removeDuplicates(slice []string) []string {
keys := make(map[string]bool)
result := []string{}
for _, item := range slice {
if !keys[item] {
keys[item] = true
result = append(result, item)
}
}
return result
}
func (g *SyntheticDataGenerator) generateReadmeContent(modelName, author string) string {
templates := []string{
fmt.Sprintf("# %s Model\n\nThis is a %s model developed by %s. It's designed for various natural language processing tasks including text generation, question answering, and conversation.\n\n## Features\n\n- High-quality text generation\n- Efficient inference\n- Multiple quantization options\n- Easy to use with LocalAI\n\n## Usage\n\nUse this model with LocalAI for various AI tasks.", strings.Title(modelName), modelName, author),
fmt.Sprintf("# %s\n\nA powerful language model from %s. This model excels at understanding and generating human-like text across multiple domains.\n\n## Capabilities\n\n- Text completion\n- Code generation\n- Creative writing\n- Technical documentation\n\n## Model Details\n\n- Architecture: Transformer-based\n- Training: Large-scale supervised learning\n- Quantization: Available in multiple formats", strings.Title(modelName), author),
fmt.Sprintf("# %s Language Model\n\nDeveloped by %s, this model represents state-of-the-art performance in natural language understanding and generation.\n\n## Key Features\n\n- Multilingual support\n- Context-aware responses\n- Efficient memory usage\n- Fast inference speed\n\n## Applications\n\n- Chatbots and virtual assistants\n- Content generation\n- Code completion\n- Educational tools", strings.Title(modelName), author),
}
return templates[g.rand.Intn(len(templates))]
}

View File

@@ -1,46 +0,0 @@
package main
import (
"fmt"
hfapi "github.com/mudler/LocalAI/pkg/huggingface-api"
openai "github.com/sashabaranov/go-openai"
jsonschema "github.com/sashabaranov/go-openai/jsonschema"
)
// Get repository README from HF
type HFReadmeTool struct {
client *hfapi.Client
}
func (s *HFReadmeTool) Execute(args map[string]any) (string, error) {
q, ok := args["repository"].(string)
if !ok {
return "", fmt.Errorf("no query")
}
readme, err := s.client.GetReadmeContent(q, "README.md")
if err != nil {
return "", err
}
return readme, nil
}
func (s *HFReadmeTool) Tool() openai.Tool {
return openai.Tool{
Type: openai.ToolTypeFunction,
Function: &openai.FunctionDefinition{
Name: "hf_readme",
Description: "A tool to get the README content of a huggingface repository",
Parameters: jsonschema.Definition{
Type: jsonschema.Object,
Properties: map[string]jsonschema.Definition{
"repository": {
Type: jsonschema.String,
Description: "The huggingface repository to get the README content of",
},
},
Required: []string{"repository"},
},
},
}
}

18
.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:
@@ -17,11 +8,6 @@ kind/documentation:
- changed-files:
- any-glob-to-any-file: '*.md'
area/ai-model:
- any:
- changed-files:
- any-glob-to-any-file: 'gallery/*'
examples:
- any:
- changed-files:
@@ -30,4 +16,4 @@ examples:
ci:
- any:
- changed-files:
- any-glob-to-any-file: '.github/*'
- any-glob-to-any-file: '.github/*'

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

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View File

@@ -1,250 +0,0 @@
---
name: 'build backend container images (reusable)'
on:
workflow_call:
inputs:
base-image:
description: 'Base image'
required: true
type: string
build-type:
description: 'Build type'
default: ''
type: string
cuda-major-version:
description: 'CUDA major version'
default: "12"
type: string
cuda-minor-version:
description: 'CUDA minor version'
default: "1"
type: string
platforms:
description: 'Platforms'
default: ''
type: string
tag-latest:
description: 'Tag latest'
default: ''
type: string
tag-suffix:
description: 'Tag suffix'
default: ''
type: string
runs-on:
description: 'Runs on'
required: true
default: ''
type: string
backend:
description: 'Backend to build'
required: true
type: string
context:
description: 'Build context'
required: true
type: string
dockerfile:
description: 'Build Dockerfile'
required: true
type: string
skip-drivers:
description: 'Skip drivers'
default: 'false'
type: string
ubuntu-version:
description: 'Ubuntu version'
required: false
default: '2204'
type: string
secrets:
dockerUsername:
required: false
dockerPassword:
required: false
quayUsername:
required: true
quayPassword:
required: true
jobs:
backend-build:
runs-on: ${{ inputs.runs-on }}
env:
quay_username: ${{ secrets.quayUsername }}
steps:
- name: Free Disk Space (Ubuntu)
if: inputs.runs-on == 'ubuntu-latest'
uses: jlumbroso/free-disk-space@main
with:
# this might remove tools that are actually needed,
# if set to "true" but frees about 6 GB
tool-cache: true
# all of these default to true, but feel free to set to
# "false" if necessary for your workflow
android: true
dotnet: true
haskell: true
large-packages: true
docker-images: true
swap-storage: true
- name: Force Install GIT latest
run: |
sudo apt-get update \
&& sudo apt-get install -y software-properties-common \
&& sudo apt-get update \
&& sudo add-apt-repository -y ppa:git-core/ppa \
&& sudo apt-get update \
&& sudo apt-get install -y git
- name: Checkout
uses: actions/checkout@v6
- name: Release space from worker
if: inputs.runs-on == 'ubuntu-latest'
run: |
echo "Listing top largest packages"
pkgs=$(dpkg-query -Wf '${Installed-Size}\t${Package}\t${Status}\n' | awk '$NF == "installed"{print $1 "\t" $2}' | sort -nr)
head -n 30 <<< "${pkgs}"
echo
df -h
echo
sudo apt-get remove -y '^llvm-.*|^libllvm.*' || true
sudo apt-get remove --auto-remove android-sdk-platform-tools snapd || true
sudo apt-get purge --auto-remove android-sdk-platform-tools snapd || true
sudo rm -rf /usr/local/lib/android
sudo apt-get remove -y '^dotnet-.*|^aspnetcore-.*' || true
sudo rm -rf /usr/share/dotnet
sudo apt-get remove -y '^mono-.*' || true
sudo apt-get remove -y '^ghc-.*' || true
sudo apt-get remove -y '.*jdk.*|.*jre.*' || true
sudo apt-get remove -y 'php.*' || true
sudo apt-get remove -y hhvm powershell firefox monodoc-manual msbuild || true
sudo apt-get remove -y '^google-.*' || true
sudo apt-get remove -y azure-cli || true
sudo apt-get remove -y '^mongo.*-.*|^postgresql-.*|^mysql-.*|^mssql-.*' || true
sudo apt-get remove -y '^gfortran-.*' || true
sudo apt-get remove -y microsoft-edge-stable || true
sudo apt-get remove -y firefox || true
sudo apt-get remove -y powershell || true
sudo apt-get remove -y r-base-core || true
sudo apt-get autoremove -y
sudo apt-get clean
echo
echo "Listing top largest packages"
pkgs=$(dpkg-query -Wf '${Installed-Size}\t${Package}\t${Status}\n' | awk '$NF == "installed"{print $1 "\t" $2}' | sort -nr)
head -n 30 <<< "${pkgs}"
echo
sudo rm -rfv build || true
sudo rm -rf /usr/share/dotnet || true
sudo rm -rf /opt/ghc || true
sudo rm -rf "/usr/local/share/boost" || true
sudo rm -rf "$AGENT_TOOLSDIRECTORY" || true
df -h
- name: Docker meta
id: meta
if: github.event_name != 'pull_request'
uses: docker/metadata-action@v5
with:
images: |
quay.io/go-skynet/local-ai-backends
localai/localai-backends
tags: |
type=ref,event=branch
type=semver,pattern={{raw}}
type=sha
flavor: |
latest=${{ inputs.tag-latest }}
suffix=${{ inputs.tag-suffix }},onlatest=true
- name: Docker meta for PR
id: meta_pull_request
if: github.event_name == 'pull_request'
uses: docker/metadata-action@v5
with:
images: |
quay.io/go-skynet/ci-tests
tags: |
type=ref,event=branch,suffix=${{ github.event.number }}-${{ inputs.backend }}-${{ inputs.build-type }}-${{ inputs.cuda-major-version }}-${{ inputs.cuda-minor-version }}
type=semver,pattern={{raw}},suffix=${{ github.event.number }}-${{ inputs.backend }}-${{ inputs.build-type }}-${{ inputs.cuda-major-version }}-${{ inputs.cuda-minor-version }}
type=sha,suffix=${{ github.event.number }}-${{ inputs.backend }}-${{ inputs.build-type }}-${{ inputs.cuda-major-version }}-${{ inputs.cuda-minor-version }}
flavor: |
latest=${{ inputs.tag-latest }}
suffix=${{ inputs.tag-suffix }},onlatest=true
## End testing image
- name: Set up QEMU
uses: docker/setup-qemu-action@master
with:
platforms: all
- name: Set up Docker Buildx
id: buildx
uses: docker/setup-buildx-action@master
- name: Login to DockerHub
if: github.event_name != 'pull_request'
uses: docker/login-action@v3
with:
username: ${{ secrets.dockerUsername }}
password: ${{ secrets.dockerPassword }}
- name: Login to Quay.io
if: ${{ env.quay_username != '' }}
uses: docker/login-action@v3
with:
registry: quay.io
username: ${{ secrets.quayUsername }}
password: ${{ secrets.quayPassword }}
- name: Build and push
uses: docker/build-push-action@v6
if: github.event_name != 'pull_request'
with:
builder: ${{ steps.buildx.outputs.name }}
build-args: |
BUILD_TYPE=${{ inputs.build-type }}
SKIP_DRIVERS=${{ inputs.skip-drivers }}
CUDA_MAJOR_VERSION=${{ inputs.cuda-major-version }}
CUDA_MINOR_VERSION=${{ inputs.cuda-minor-version }}
BASE_IMAGE=${{ inputs.base-image }}
BACKEND=${{ inputs.backend }}
UBUNTU_VERSION=${{ inputs.ubuntu-version }}
context: ${{ inputs.context }}
file: ${{ inputs.dockerfile }}
cache-from: type=gha
platforms: ${{ inputs.platforms }}
push: ${{ github.event_name != 'pull_request' }}
tags: ${{ steps.meta.outputs.tags }}
labels: ${{ steps.meta.outputs.labels }}
- name: Build and push (PR)
uses: docker/build-push-action@v6
if: github.event_name == 'pull_request'
with:
builder: ${{ steps.buildx.outputs.name }}
build-args: |
BUILD_TYPE=${{ inputs.build-type }}
SKIP_DRIVERS=${{ inputs.skip-drivers }}
CUDA_MAJOR_VERSION=${{ inputs.cuda-major-version }}
CUDA_MINOR_VERSION=${{ inputs.cuda-minor-version }}
BASE_IMAGE=${{ inputs.base-image }}
BACKEND=${{ inputs.backend }}
UBUNTU_VERSION=${{ inputs.ubuntu-version }}
context: ${{ inputs.context }}
file: ${{ inputs.dockerfile }}
cache-from: type=gha
platforms: ${{ inputs.platforms }}
push: ${{ env.quay_username != '' }}
tags: ${{ steps.meta_pull_request.outputs.tags }}
labels: ${{ steps.meta_pull_request.outputs.labels }}
- name: job summary
run: |
echo "Built image: ${{ steps.meta.outputs.labels }}" >> $GITHUB_STEP_SUMMARY

View File

@@ -1,144 +0,0 @@
---
name: 'build darwin python backend container images (reusable)'
on:
workflow_call:
inputs:
backend:
description: 'Backend to build'
required: true
type: string
build-type:
description: 'Build type (e.g., mps)'
default: ''
type: string
use-pip:
description: 'Use pip to install dependencies'
default: false
type: boolean
lang:
description: 'Programming language (e.g. go)'
default: 'python'
type: string
go-version:
description: 'Go version to use'
default: '1.24.x'
type: string
tag-suffix:
description: 'Tag suffix for the built image'
required: true
type: string
runs-on:
description: 'Runner to use'
default: 'macOS-14'
type: string
secrets:
dockerUsername:
required: false
dockerPassword:
required: false
quayUsername:
required: true
quayPassword:
required: true
jobs:
darwin-backend-build:
runs-on: ${{ inputs.runs-on }}
strategy:
matrix:
go-version: ['${{ inputs.go-version }}']
steps:
- name: Clone
uses: actions/checkout@v6
with:
submodules: true
- name: Setup Go ${{ matrix.go-version }}
uses: actions/setup-go@v5
with:
go-version: ${{ matrix.go-version }}
cache: false
# You can test your matrix by printing the current Go version
- name: Display Go version
run: go version
- name: Dependencies
run: |
brew install protobuf grpc make protoc-gen-go protoc-gen-go-grpc libomp llvm
- name: Build ${{ inputs.backend }}-darwin
run: |
make protogen-go
BACKEND=${{ inputs.backend }} BUILD_TYPE=${{ inputs.build-type }} USE_PIP=${{ inputs.use-pip }} make build-darwin-${{ inputs.lang }}-backend
- name: Upload ${{ inputs.backend }}.tar
uses: actions/upload-artifact@v6
with:
name: ${{ inputs.backend }}-tar
path: backend-images/${{ inputs.backend }}.tar
darwin-backend-publish:
needs: darwin-backend-build
if: github.event_name != 'pull_request'
runs-on: ubuntu-latest
steps:
- name: Download ${{ inputs.backend }}.tar
uses: actions/download-artifact@v7
with:
name: ${{ inputs.backend }}-tar
path: .
- name: Install crane
run: |
curl -L https://github.com/google/go-containerregistry/releases/latest/download/go-containerregistry_Linux_x86_64.tar.gz | tar -xz
sudo mv crane /usr/local/bin/
- name: Log in to DockerHub
run: |
echo "${{ secrets.dockerPassword }}" | crane auth login docker.io -u "${{ secrets.dockerUsername }}" --password-stdin
- name: Log in to quay.io
run: |
echo "${{ secrets.quayPassword }}" | crane auth login quay.io -u "${{ secrets.quayUsername }}" --password-stdin
- name: Docker meta
id: meta
uses: docker/metadata-action@v5
with:
images: |
localai/localai-backends
tags: |
type=ref,event=branch
type=semver,pattern={{raw}}
type=sha
flavor: |
latest=auto
suffix=${{ inputs.tag-suffix }},onlatest=true
- name: Docker meta
id: quaymeta
uses: docker/metadata-action@v5
with:
images: |
quay.io/go-skynet/local-ai-backends
tags: |
type=ref,event=branch
type=semver,pattern={{raw}}
type=sha
flavor: |
latest=auto
suffix=${{ inputs.tag-suffix }},onlatest=true
- name: Push Docker image (DockerHub)
run: |
for tag in $(echo "${{ steps.meta.outputs.tags }}" | tr ',' '\n'); do
crane push ${{ inputs.backend }}.tar $tag
done
- name: Push Docker image (Quay)
run: |
for tag in $(echo "${{ steps.quaymeta.outputs.tags }}" | tr ',' '\n'); do
crane push ${{ inputs.backend }}.tar $tag
done

View File

@@ -1,79 +0,0 @@
name: 'build backend container images (PR-filtered)'
on:
pull_request:
concurrency:
group: ci-backends-pr-${{ github.head_ref || github.ref }}-${{ github.repository }}
cancel-in-progress: true
jobs:
generate-matrix:
runs-on: ubuntu-latest
outputs:
matrix: ${{ steps.set-matrix.outputs.matrix }}
matrix-darwin: ${{ steps.set-matrix.outputs.matrix-darwin }}
has-backends: ${{ steps.set-matrix.outputs.has-backends }}
has-backends-darwin: ${{ steps.set-matrix.outputs.has-backends-darwin }}
steps:
- name: Checkout repository
uses: actions/checkout@v6
- name: Setup Bun
uses: oven-sh/setup-bun@v2
- name: Install dependencies
run: |
bun add js-yaml
bun add @octokit/core
# filters the matrix in backend.yml
- name: Filter matrix for changed backends
id: set-matrix
env:
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
GITHUB_EVENT_PATH: ${{ github.event_path }}
run: bun run scripts/changed-backends.js
backend-jobs:
needs: generate-matrix
uses: ./.github/workflows/backend_build.yml
if: needs.generate-matrix.outputs.has-backends == 'true'
with:
tag-latest: ${{ matrix.tag-latest }}
tag-suffix: ${{ matrix.tag-suffix }}
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 }}
backend: ${{ matrix.backend }}
dockerfile: ${{ matrix.dockerfile }}
skip-drivers: ${{ matrix.skip-drivers }}
context: ${{ matrix.context }}
ubuntu-version: ${{ matrix.ubuntu-version }}
secrets:
quayUsername: ${{ secrets.LOCALAI_REGISTRY_USERNAME }}
quayPassword: ${{ secrets.LOCALAI_REGISTRY_PASSWORD }}
strategy:
fail-fast: true
matrix: ${{ fromJson(needs.generate-matrix.outputs.matrix) }}
backend-jobs-darwin:
needs: generate-matrix
uses: ./.github/workflows/backend_build_darwin.yml
if: needs.generate-matrix.outputs.has-backends-darwin == 'true'
with:
backend: ${{ matrix.backend }}
build-type: ${{ matrix.build-type }}
go-version: "1.24.x"
tag-suffix: ${{ matrix.tag-suffix }}
lang: ${{ matrix.lang || 'python' }}
use-pip: ${{ matrix.backend == 'diffusers' }}
runs-on: "macos-latest"
secrets:
quayUsername: ${{ secrets.LOCALAI_REGISTRY_USERNAME }}
quayPassword: ${{ secrets.LOCALAI_REGISTRY_PASSWORD }}
strategy:
fail-fast: true
matrix: ${{ fromJson(needs.generate-matrix.outputs.matrix-darwin) }}

View File

@@ -1,67 +0,0 @@
name: Build test
on:
push:
branches:
- master
pull_request:
jobs:
build-test:
runs-on: ubuntu-latest
steps:
- name: Checkout
uses: actions/checkout@v6
with:
fetch-depth: 0
- name: Set up Go
uses: actions/setup-go@v5
with:
go-version: 1.25
- name: Run GoReleaser
run: |
make dev-dist
launcher-build-darwin:
runs-on: macos-latest
steps:
- name: Checkout
uses: actions/checkout@v6
with:
fetch-depth: 0
- name: Set up Go
uses: actions/setup-go@v5
with:
go-version: 1.25
- name: Build launcher for macOS ARM64
run: |
make build-launcher-darwin
ls -liah dist
- name: Upload macOS launcher artifacts
uses: actions/upload-artifact@v6
with:
name: launcher-macos
path: dist/
retention-days: 30
launcher-build-linux:
runs-on: ubuntu-latest
steps:
- name: Checkout
uses: actions/checkout@v6
with:
fetch-depth: 0
- name: Set up Go
uses: actions/setup-go@v5
with:
go-version: 1.25
- name: Build launcher for Linux
run: |
sudo apt-get update
sudo apt-get install golang gcc libgl1-mesa-dev xorg-dev libxkbcommon-dev
make build-launcher-linux
- name: Upload Linux launcher artifacts
uses: actions/upload-artifact@v6
with:
name: launcher-linux
path: local-ai-launcher-linux.tar.xz
retention-days: 30

View File

@@ -1,62 +1,62 @@
name: Bump Backend dependencies
name: Bump dependencies
on:
schedule:
- cron: 0 20 * * *
workflow_dispatch:
jobs:
bump-backends:
bump:
strategy:
fail-fast: false
matrix:
include:
- repository: "ggml-org/llama.cpp"
variable: "LLAMA_VERSION"
- repository: "go-skynet/go-llama.cpp"
variable: "GOLLAMA_VERSION"
branch: "master"
file: "backend/cpp/llama-cpp/Makefile"
- repository: "ggml-org/whisper.cpp"
- 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"
file: "backend/go/whisper/Makefile"
- repository: "PABannier/bark.cpp"
variable: "BARKCPP_VERSION"
branch: "main"
file: "Makefile"
- repository: "leejet/stable-diffusion.cpp"
variable: "STABLEDIFFUSION_GGML_VERSION"
- repository: "go-skynet/go-bert.cpp"
variable: "BERT_VERSION"
branch: "master"
- repository: "go-skynet/bloomz.cpp"
variable: "BLOOMZ_VERSION"
branch: "main"
- repository: "nomic-ai/gpt4all"
variable: "GPT4ALL_VERSION"
branch: "main"
- repository: "mudler/go-ggllm.cpp"
variable: "GOGGLLM_VERSION"
branch: "master"
- repository: "mudler/go-stable-diffusion"
variable: "STABLEDIFFUSION_VERSION"
branch: "master"
file: "backend/go/stablediffusion-ggml/Makefile"
- repository: "mudler/go-piper"
variable: "PIPER_VERSION"
branch: "master"
file: "backend/go/piper/Makefile"
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v6
- uses: actions/checkout@v4
- name: Bump dependencies 🔧
id: bump
run: |
bash .github/bump_deps.sh ${{ matrix.repository }} ${{ matrix.branch }} ${{ matrix.variable }} ${{ matrix.file }}
{
echo 'message<<EOF'
cat "${{ 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
bash .github/bump_deps.sh ${{ matrix.repository }} ${{ matrix.branch }} ${{ matrix.variable }}
- name: Create Pull Request
uses: peter-evans/create-pull-request@v8
uses: peter-evans/create-pull-request@v5
with:
token: ${{ secrets.UPDATE_BOT_TOKEN }}
push-to-fork: ci-forks/LocalAI
commit-message: ':arrow_up: Update ${{ matrix.repository }}'
title: 'chore: :arrow_up: Update ${{ matrix.repository }} to `${{ steps.bump.outputs.commit }}`'
title: ':arrow_up: Update ${{ matrix.repository }}'
branch: "update/${{ matrix.variable }}"
body: ${{ steps.bump.outputs.message }}
body: Bump of ${{ matrix.repository }} version
signoff: true

View File

@@ -1,10 +1,10 @@
name: Bump Documentation
name: Bump dependencies
on:
schedule:
- cron: 0 20 * * *
workflow_dispatch:
jobs:
bump-docs:
bump:
strategy:
fail-fast: false
matrix:
@@ -12,17 +12,17 @@ jobs:
- repository: "mudler/LocalAI"
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v6
- uses: actions/checkout@v4
- name: Bump dependencies 🔧
run: |
bash .github/bump_docs.sh ${{ matrix.repository }}
- name: Create Pull Request
uses: peter-evans/create-pull-request@v8
uses: peter-evans/create-pull-request@v5
with:
token: ${{ secrets.UPDATE_BOT_TOKEN }}
push-to-fork: ci-forks/LocalAI
commit-message: ':arrow_up: Update docs version ${{ matrix.repository }}'
title: 'docs: :arrow_up: update docs version ${{ matrix.repository }}'
title: ':arrow_up: Update docs version ${{ matrix.repository }}'
branch: "update/docs"
body: Bump of ${{ matrix.repository }} version inside docs
signoff: true

View File

@@ -1,46 +0,0 @@
name: Check if checksums are up-to-date
on:
schedule:
- cron: 0 20 * * *
workflow_dispatch:
jobs:
checksum_check:
runs-on: ubuntu-latest
steps:
- name: Force Install GIT latest
run: |
sudo apt-get update \
&& sudo apt-get install -y software-properties-common \
&& sudo apt-get update \
&& sudo add-apt-repository -y ppa:git-core/ppa \
&& sudo apt-get update \
&& sudo apt-get install -y git
- uses: actions/checkout@v6
- name: Install dependencies
run: |
sudo apt-get update
sudo apt-get install -y pip wget
pip install huggingface_hub
- name: 'Setup yq'
uses: dcarbone/install-yq-action@v1.3.1
with:
version: 'v4.44.2'
download-compressed: true
force: true
- name: Checksum checker 🔧
run: |
export HF_HOME=/hf_cache
sudo mkdir /hf_cache
sudo chmod 777 /hf_cache
bash .github/checksum_checker.sh gallery/index.yaml
- name: Create Pull Request
uses: peter-evans/create-pull-request@v8
with:
token: ${{ secrets.UPDATE_BOT_TOKEN }}
push-to-fork: ci-forks/LocalAI
commit-message: ':arrow_up: Checksum updates in gallery/index.yaml'
title: 'chore(model-gallery): :arrow_up: update checksum'
branch: "update/checksum"
body: Updating checksums in gallery/index.yaml
signoff: true

View File

@@ -1,43 +0,0 @@
name: Dependabot auto-merge
on:
- pull_request_target
permissions:
contents: write
pull-requests: write
packages: read
jobs:
dependabot:
runs-on: ubuntu-latest
if: ${{ github.actor == 'dependabot[bot]' }}
steps:
- name: Dependabot metadata
id: metadata
uses: dependabot/fetch-metadata@v2.4.0
with:
github-token: "${{ secrets.GITHUB_TOKEN }}"
skip-commit-verification: true
- name: Checkout repository
uses: actions/checkout@v6
- name: Approve a PR if not already approved
run: |
gh pr checkout "$PR_URL"
if [ "$(gh pr status --json reviewDecision -q .currentBranch.reviewDecision)" != "APPROVED" ];
then
gh pr review --approve "$PR_URL"
else
echo "PR already approved.";
fi
env:
PR_URL: ${{github.event.pull_request.html_url}}
GITHUB_TOKEN: ${{secrets.GITHUB_TOKEN}}
- name: Enable auto-merge for Dependabot PRs
if: ${{ contains(github.event.pull_request.title, 'bump')}}
run: gh pr merge --auto --squash "$PR_URL"
env:
PR_URL: ${{github.event.pull_request.html_url}}
GITHUB_TOKEN: ${{secrets.GITHUB_TOKEN}}

View File

@@ -1,64 +0,0 @@
name: Explorer deployment
on:
push:
branches:
- master
tags:
- 'v*'
concurrency:
group: ci-deploy-${{ github.head_ref || github.ref }}-${{ github.repository }}
jobs:
build-linux:
runs-on: ubuntu-latest
steps:
- name: Clone
uses: actions/checkout@v6
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
- name: rm
uses: appleboy/ssh-action@v1.2.4
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@v1.0.0
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@v1.2.4
with:
host: ${{ secrets.EXPLORER_SSH_HOST }}
username: ${{ secrets.EXPLORER_SSH_USERNAME }}
key: ${{ secrets.EXPLORER_SSH_KEY }}
port: ${{ secrets.EXPLORER_SSH_PORT }}
script: |
sudo cp -rfv local-ai/local-ai /usr/bin/local-ai
sudo systemctl restart local-ai

View File

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

View File

@@ -1,132 +0,0 @@
name: Gallery Agent
on:
schedule:
- cron: '0 */3 * * *' # Run every 4 hours
workflow_dispatch:
inputs:
search_term:
description: 'Search term for models'
required: false
default: 'GGUF'
type: string
limit:
description: 'Maximum number of models to process'
required: false
default: '15'
type: string
quantization:
description: 'Preferred quantization format'
required: false
default: 'Q4_K_M'
type: string
max_models:
description: 'Maximum number of models to add to the gallery'
required: false
default: '1'
type: string
jobs:
gallery-agent:
runs-on: ubuntu-latest
steps:
- name: Checkout repository
uses: actions/checkout@v6
with:
token: ${{ secrets.GITHUB_TOKEN }}
- name: Set up Go
uses: actions/setup-go@v5
with:
go-version: '1.21'
- name: Proto Dependencies
run: |
# Install protoc
curl -L -s https://github.com/protocolbuffers/protobuf/releases/download/v26.1/protoc-26.1-linux-x86_64.zip -o protoc.zip && \
unzip -j -d /usr/local/bin protoc.zip bin/protoc && \
rm protoc.zip
go install google.golang.org/protobuf/cmd/protoc-gen-go@v1.34.2
go install google.golang.org/grpc/cmd/protoc-gen-go-grpc@1958fcbe2ca8bd93af633f11e97d44e567e945af
PATH="$PATH:$HOME/go/bin" make protogen-go
- uses: mudler/localai-github-action@v1.1
with:
model: 'qwen3-4b'
- name: Run gallery agent
env:
#OPENAI_MODEL: ${{ secrets.OPENAI_MODEL }}
OPENAI_MODE: qwen3-4b
OPENAI_BASE_URL: "http://localhost:8080"
OPENAI_KEY: ${{ secrets.OPENAI_KEY }}
#OPENAI_BASE_URL: ${{ secrets.OPENAI_BASE_URL }}
SEARCH_TERM: ${{ github.event.inputs.search_term || 'GGUF' }}
LIMIT: ${{ github.event.inputs.limit || '15' }}
QUANTIZATION: ${{ github.event.inputs.quantization || 'Q4_K_M' }}
MAX_MODELS: ${{ github.event.inputs.max_models || '1' }}
run: |
export GALLERY_INDEX_PATH=$PWD/gallery/index.yaml
go run ./.github/gallery-agent
- name: Check for changes
id: check_changes
run: |
if git diff --quiet gallery/index.yaml; then
echo "changes=false" >> $GITHUB_OUTPUT
echo "No changes detected in gallery/index.yaml"
else
echo "changes=true" >> $GITHUB_OUTPUT
echo "Changes detected in gallery/index.yaml"
git diff gallery/index.yaml
fi
- name: Read gallery agent summary
id: read_summary
if: steps.check_changes.outputs.changes == 'true'
run: |
if [ -f "./gallery-agent-summary.json" ]; then
echo "summary_exists=true" >> $GITHUB_OUTPUT
# Extract summary data using jq
echo "search_term=$(jq -r '.search_term' ./gallery-agent-summary.json)" >> $GITHUB_OUTPUT
echo "total_found=$(jq -r '.total_found' ./gallery-agent-summary.json)" >> $GITHUB_OUTPUT
echo "models_added=$(jq -r '.models_added' ./gallery-agent-summary.json)" >> $GITHUB_OUTPUT
echo "quantization=$(jq -r '.quantization' ./gallery-agent-summary.json)" >> $GITHUB_OUTPUT
echo "processing_time=$(jq -r '.processing_time' ./gallery-agent-summary.json)" >> $GITHUB_OUTPUT
# Create a formatted list of added models with URLs
added_models=$(jq -r 'range(0; .added_model_ids | length) as $i | "- [\(.added_model_ids[$i])](\(.added_model_urls[$i]))"' ./gallery-agent-summary.json | tr '\n' '\n')
echo "added_models<<EOF" >> $GITHUB_OUTPUT
echo "$added_models" >> $GITHUB_OUTPUT
echo "EOF" >> $GITHUB_OUTPUT
rm -f ./gallery-agent-summary.json
else
echo "summary_exists=false" >> $GITHUB_OUTPUT
fi
- name: Create Pull Request
if: steps.check_changes.outputs.changes == 'true'
uses: peter-evans/create-pull-request@v8
with:
token: ${{ secrets.UPDATE_BOT_TOKEN }}
push-to-fork: ci-forks/LocalAI
commit-message: 'chore(model gallery): :robot: add new models via gallery agent'
title: 'chore(model gallery): :robot: add ${{ steps.read_summary.outputs.models_added || 0 }} new models via gallery agent'
# Branch has to be unique so PRs are not overriding each other
branch-suffix: timestamp
body: |
This PR was automatically created by the gallery agent workflow.
**Summary:**
- **Search Term:** ${{ steps.read_summary.outputs.search_term || github.event.inputs.search_term || 'GGUF' }}
- **Models Found:** ${{ steps.read_summary.outputs.total_found || 'N/A' }}
- **Models Added:** ${{ steps.read_summary.outputs.models_added || '0' }}
- **Quantization:** ${{ steps.read_summary.outputs.quantization || github.event.inputs.quantization || 'Q4_K_M' }}
- **Processing Time:** ${{ steps.read_summary.outputs.processing_time || 'N/A' }}
**Added Models:**
${{ steps.read_summary.outputs.added_models || '- No models added' }}
**Workflow Details:**
- Triggered by: `${{ github.event_name }}`
- Run ID: `${{ github.run_id }}`
- Commit: `${{ github.sha }}`
signoff: true
delete-branch: true

View File

@@ -1,95 +0,0 @@
name: 'generate and publish GRPC docker caches'
on:
workflow_dispatch:
schedule:
# daily at midnight
- cron: '0 0 * * *'
concurrency:
group: grpc-cache-${{ github.head_ref || github.ref }}-${{ github.repository }}
cancel-in-progress: true
jobs:
generate_caches:
strategy:
matrix:
include:
- grpc-base-image: ubuntu:22.04
runs-on: 'ubuntu-latest'
platforms: 'linux/amd64,linux/arm64'
runs-on: ${{matrix.runs-on}}
steps:
- name: Release space from worker
if: matrix.runs-on == 'ubuntu-latest'
run: |
echo "Listing top largest packages"
pkgs=$(dpkg-query -Wf '${Installed-Size}\t${Package}\t${Status}\n' | awk '$NF == "installed"{print $1 "\t" $2}' | sort -nr)
head -n 30 <<< "${pkgs}"
echo
df -h
echo
sudo apt-get remove -y '^llvm-.*|^libllvm.*' || true
sudo apt-get remove --auto-remove android-sdk-platform-tools || true
sudo apt-get purge --auto-remove android-sdk-platform-tools || true
sudo rm -rf /usr/local/lib/android
sudo apt-get remove -y '^dotnet-.*|^aspnetcore-.*' || true
sudo rm -rf /usr/share/dotnet
sudo apt-get remove -y '^mono-.*' || true
sudo apt-get remove -y '^ghc-.*' || true
sudo apt-get remove -y '.*jdk.*|.*jre.*' || true
sudo apt-get remove -y 'php.*' || true
sudo apt-get remove -y hhvm powershell firefox monodoc-manual msbuild || true
sudo apt-get remove -y '^google-.*' || true
sudo apt-get remove -y azure-cli || true
sudo apt-get remove -y '^mongo.*-.*|^postgresql-.*|^mysql-.*|^mssql-.*' || true
sudo apt-get remove -y '^gfortran-.*' || true
sudo apt-get remove -y microsoft-edge-stable || true
sudo apt-get remove -y firefox || true
sudo apt-get remove -y powershell || true
sudo apt-get remove -y r-base-core || true
sudo apt-get autoremove -y
sudo apt-get clean
echo
echo "Listing top largest packages"
pkgs=$(dpkg-query -Wf '${Installed-Size}\t${Package}\t${Status}\n' | awk '$NF == "installed"{print $1 "\t" $2}' | sort -nr)
head -n 30 <<< "${pkgs}"
echo
sudo rm -rfv build || true
sudo rm -rf /usr/share/dotnet || true
sudo rm -rf /opt/ghc || true
sudo rm -rf "/usr/local/share/boost" || true
sudo rm -rf "$AGENT_TOOLSDIRECTORY" || true
df -h
- name: Set up QEMU
uses: docker/setup-qemu-action@master
with:
platforms: all
- name: Set up Docker Buildx
id: buildx
uses: docker/setup-buildx-action@master
- name: Checkout
uses: actions/checkout@v6
- name: Cache GRPC
uses: docker/build-push-action@v6
with:
builder: ${{ steps.buildx.outputs.name }}
# The build-args MUST be an EXACT match between the image cache and other workflow steps that want to use that cache.
# This means that even the MAKEFLAGS have to be an EXACT match.
# If the build-args are not an EXACT match, it will result in a cache miss, which will require GRPC to be built from scratch.
build-args: |
GRPC_BASE_IMAGE=${{ matrix.grpc-base-image }}
GRPC_MAKEFLAGS=--jobs=4 --output-sync=target
GRPC_VERSION=v1.65.0
context: .
file: ./Dockerfile
cache-to: type=gha,ignore-error=true
cache-from: type=gha
target: grpc
platforms: ${{ matrix.platforms }}
push: false

View File

@@ -1,59 +0,0 @@
name: 'generate and publish intel docker caches'
on:
workflow_dispatch:
push:
branches:
- master
concurrency:
group: intel-cache-${{ github.head_ref || github.ref }}-${{ github.repository }}
cancel-in-progress: true
jobs:
generate_caches:
strategy:
matrix:
include:
- base-image: intel/oneapi-basekit:2025.2.0-0-devel-ubuntu22.04
runs-on: 'arc-runner-set'
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@v6
- 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

@@ -9,20 +9,20 @@ concurrency:
cancel-in-progress: true
jobs:
image-build:
extras-image-build:
uses: ./.github/workflows/image_build.yml
with:
tag-latest: ${{ matrix.tag-latest }}
tag-suffix: ${{ matrix.tag-suffix }}
ffmpeg: ${{ matrix.ffmpeg }}
image-type: ${{ matrix.image-type }}
build-type: ${{ matrix.build-type }}
cuda-major-version: ${{ matrix.cuda-major-version }}
cuda-minor-version: ${{ matrix.cuda-minor-version }}
platforms: ${{ matrix.platforms }}
runs-on: ${{ matrix.runs-on }}
base-image: ${{ matrix.base-image }}
grpc-base-image: ${{ matrix.grpc-base-image }}
makeflags: ${{ matrix.makeflags }}
ubuntu-version: ${{ matrix.ubuntu-version }}
secrets:
dockerUsername: ${{ secrets.DOCKERHUB_USERNAME }}
dockerPassword: ${{ secrets.DOCKERHUB_PASSWORD }}
@@ -31,64 +31,95 @@ jobs:
strategy:
# Pushing with all jobs in parallel
# eats the bandwidth of all the nodes
max-parallel: ${{ github.event_name != 'pull_request' && 4 || 8 }}
fail-fast: false
max-parallel: ${{ github.event_name != 'pull_request' && 2 || 4 }}
matrix:
include:
- 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: '-gpu-nvidia-cuda-12'
runs-on: 'ubuntu-latest'
tag-suffix: '-cublas-cuda12-ffmpeg'
ffmpeg: 'true'
image-type: 'extras'
runs-on: 'arc-runner-set'
base-image: "ubuntu:22.04"
makeflags: "--jobs=3 --output-sync=target"
ubuntu-version: '2204'
- build-type: 'cublas'
cuda-major-version: "13"
cuda-minor-version: "0"
platforms: 'linux/amd64'
tag-latest: 'false'
tag-suffix: '-gpu-nvidia-cuda-13'
runs-on: 'ubuntu-latest'
base-image: "ubuntu:22.04"
makeflags: "--jobs=3 --output-sync=target"
ubuntu-version: '2204'
- build-type: 'hipblas'
platforms: 'linux/amd64'
tag-latest: 'false'
tag-suffix: '-hipblas'
base-image: "rocm/dev-ubuntu-22.04:6.4.3"
grpc-base-image: "ubuntu:22.04"
runs-on: 'ubuntu-latest'
ffmpeg: 'false'
image-type: 'extras'
base-image: "rocm/dev-ubuntu-22.04:6.0-complete"
runs-on: 'arc-runner-set'
makeflags: "--jobs=3 --output-sync=target"
ubuntu-version: '2204'
- build-type: 'sycl'
- 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'
runs-on: 'ubuntu-latest'
base-image: "intel/oneapi-basekit:2024.0.1-devel-ubuntu22.04"
tag-suffix: 'sycl-f16-ffmpeg'
ffmpeg: 'true'
image-type: 'extras'
runs-on: 'arc-runner-set'
makeflags: "--jobs=3 --output-sync=target"
ubuntu-version: '2204'
- build-type: 'vulkan'
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 }}
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: '-vulkan-core'
tag-suffix: '-ffmpeg-core'
ffmpeg: 'true'
image-type: 'core'
runs-on: 'ubuntu-latest'
base-image: "ubuntu:22.04"
makeflags: "--jobs=4 --output-sync=target"
ubuntu-version: '2204'
- build-type: 'cublas'
cuda-major-version: "13"
cuda-minor-version: "0"
platforms: 'linux/arm64'
makeflags: "--jobs=5 --output-sync=target"
- build-type: 'sycl_f16'
platforms: 'linux/amd64'
tag-latest: 'false'
tag-suffix: '-nvidia-l4t-arm64-cuda-13'
base-image: "ubuntu:24.04"
runs-on: 'ubuntu-24.04-arm'
makeflags: "--jobs=4 --output-sync=target"
skip-drivers: 'false'
ubuntu-version: '2404'
base-image: "intel/oneapi-basekit:2024.0.1-devel-ubuntu22.04"
tag-suffix: 'sycl-f16-ffmpeg-core'
ffmpeg: 'true'
image-type: 'core'
runs-on: 'arc-runner-set'
makeflags: "--jobs=3 --output-sync=target"
- build-type: '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=5 --output-sync=target"

View File

@@ -13,137 +13,222 @@ concurrency:
cancel-in-progress: true
jobs:
hipblas-jobs:
self-hosted-jobs:
uses: ./.github/workflows/image_build.yml
with:
tag-latest: ${{ matrix.tag-latest }}
tag-suffix: ${{ matrix.tag-suffix }}
ffmpeg: ${{ matrix.ffmpeg }}
image-type: ${{ matrix.image-type }}
build-type: ${{ matrix.build-type }}
cuda-major-version: ${{ matrix.cuda-major-version }}
cuda-minor-version: ${{ matrix.cuda-minor-version }}
platforms: ${{ matrix.platforms }}
runs-on: ${{ matrix.runs-on }}
base-image: ${{ matrix.base-image }}
grpc-base-image: ${{ matrix.grpc-base-image }}
aio: ${{ matrix.aio }}
makeflags: ${{ matrix.makeflags }}
ubuntu-version: ${{ matrix.ubuntu-version }}
latest-image: ${{ matrix.latest-image }}
latest-image-aio: ${{ matrix.latest-image-aio }}
secrets:
dockerUsername: ${{ secrets.DOCKERHUB_USERNAME }}
dockerPassword: ${{ secrets.DOCKERHUB_PASSWORD }}
quayUsername: ${{ secrets.LOCALAI_REGISTRY_USERNAME }}
quayPassword: ${{ secrets.LOCALAI_REGISTRY_PASSWORD }}
strategy:
# Pushing with all jobs in parallel
# eats the bandwidth of all the nodes
max-parallel: ${{ github.event_name != 'pull_request' && 2 || 4 }}
matrix:
include:
- build-type: 'hipblas'
# Extra images
- build-type: ''
#platforms: 'linux/amd64,linux/arm64'
platforms: 'linux/amd64'
tag-latest: 'auto'
tag-suffix: '-gpu-hipblas'
base-image: "rocm/dev-ubuntu-22.04:6.4.3"
grpc-base-image: "ubuntu:22.04"
runs-on: 'ubuntu-latest'
makeflags: "--jobs=3 --output-sync=target"
aio: "-aio-gpu-hipblas"
ubuntu-version: '2204'
core-image-build:
uses: ./.github/workflows/image_build.yml
with:
tag-latest: ${{ matrix.tag-latest }}
tag-suffix: ${{ matrix.tag-suffix }}
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 }}
skip-drivers: ${{ matrix.skip-drivers }}
ubuntu-version: ${{ matrix.ubuntu-version }}
secrets:
dockerUsername: ${{ secrets.DOCKERHUB_USERNAME }}
dockerPassword: ${{ secrets.DOCKERHUB_PASSWORD }}
quayUsername: ${{ secrets.LOCALAI_REGISTRY_USERNAME }}
quayPassword: ${{ secrets.LOCALAI_REGISTRY_PASSWORD }}
strategy:
#max-parallel: ${{ github.event_name != 'pull_request' && 2 || 4 }}
matrix:
include:
- build-type: ''
platforms: 'linux/amd64,linux/arm64'
tag-latest: 'auto'
tag-suffix: ''
ffmpeg: ''
image-type: 'extras'
runs-on: 'arc-runner-set'
base-image: "ubuntu:22.04"
runs-on: 'ubuntu-latest'
aio: "-aio-cpu"
makeflags: "--jobs=4 --output-sync=target"
skip-drivers: 'false'
ubuntu-version: '2204'
makeflags: "--jobs=3 --output-sync=target"
- build-type: ''
platforms: 'linux/amd64'
tag-latest: 'auto'
tag-suffix: '-ffmpeg'
ffmpeg: 'true'
image-type: 'extras'
runs-on: 'arc-runner-set'
base-image: "ubuntu:22.04"
makeflags: "--jobs=3 --output-sync=target"
- build-type: 'cublas'
cuda-major-version: "11"
cuda-minor-version: "7"
platforms: 'linux/amd64'
tag-latest: 'false'
tag-suffix: '-cublas-cuda11'
ffmpeg: ''
image-type: 'extras'
runs-on: 'arc-runner-set'
base-image: "ubuntu:22.04"
makeflags: "--jobs=3 --output-sync=target"
- build-type: 'cublas'
cuda-major-version: "12"
cuda-minor-version: "1"
platforms: 'linux/amd64'
tag-latest: 'false'
tag-suffix: '-cublas-cuda12'
ffmpeg: ''
image-type: 'extras'
runs-on: 'arc-runner-set'
base-image: "ubuntu:22.04"
makeflags: "--jobs=3 --output-sync=target"
- build-type: 'cublas'
cuda-major-version: "11"
cuda-minor-version: "7"
platforms: 'linux/amd64'
tag-latest: 'auto'
tag-suffix: '-gpu-nvidia-cuda-11'
runs-on: 'ubuntu-latest'
tag-suffix: '-cublas-cuda11-ffmpeg'
ffmpeg: 'true'
image-type: 'extras'
runs-on: 'arc-runner-set'
base-image: "ubuntu:22.04"
makeflags: "--jobs=4 --output-sync=target"
skip-drivers: 'false'
aio: "-aio-gpu-nvidia-cuda-11"
ubuntu-version: '2204'
latest-image: 'latest-gpu-nvidia-cuda-11'
latest-image-aio: 'latest-aio-gpu-nvidia-cuda-11'
makeflags: "--jobs=3 --output-sync=target"
- build-type: 'cublas'
cuda-major-version: "12"
cuda-minor-version: "0"
cuda-minor-version: "1"
platforms: 'linux/amd64'
tag-latest: 'auto'
tag-suffix: '-gpu-nvidia-cuda-12'
runs-on: 'ubuntu-latest'
tag-suffix: '-cublas-cuda12-ffmpeg'
ffmpeg: 'true'
image-type: 'extras'
runs-on: 'arc-runner-set'
base-image: "ubuntu:22.04"
skip-drivers: 'false'
makeflags: "--jobs=4 --output-sync=target"
aio: "-aio-gpu-nvidia-cuda-12"
ubuntu-version: '2204'
- build-type: 'cublas'
cuda-major-version: "13"
cuda-minor-version: "0"
platforms: 'linux/amd64'
tag-latest: 'auto'
tag-suffix: '-gpu-nvidia-cuda-13'
runs-on: 'ubuntu-latest'
base-image: "ubuntu:22.04"
skip-drivers: 'false'
makeflags: "--jobs=4 --output-sync=target"
aio: "-aio-gpu-nvidia-cuda-13"
ubuntu-version: '2204'
- build-type: 'vulkan'
platforms: 'linux/amd64'
tag-latest: 'auto'
tag-suffix: '-gpu-vulkan'
runs-on: 'ubuntu-latest'
base-image: "ubuntu:22.04"
skip-drivers: 'false'
makeflags: "--jobs=4 --output-sync=target"
aio: "-aio-gpu-vulkan"
ubuntu-version: '2204'
- build-type: 'intel'
platforms: 'linux/amd64'
tag-latest: 'auto'
base-image: "quay.io/go-skynet/intel-oneapi-base:latest"
grpc-base-image: "ubuntu:22.04"
tag-suffix: '-gpu-intel'
runs-on: 'ubuntu-latest'
latest-image: 'latest-gpu-nvidia-cuda-12'
latest-image-aio: 'latest-aio-gpu-nvidia-cuda-12'
makeflags: "--jobs=3 --output-sync=target"
aio: "-aio-gpu-intel"
ubuntu-version: '2204'
gh-runner:
- build-type: ''
#platforms: 'linux/amd64,linux/arm64'
platforms: 'linux/amd64'
tag-latest: 'auto'
tag-suffix: ''
ffmpeg: ''
image-type: 'extras'
base-image: "ubuntu:22.04"
runs-on: 'arc-runner-set'
makeflags: "--jobs=3 --output-sync=target"
- build-type: 'hipblas'
platforms: 'linux/amd64'
tag-latest: 'auto'
tag-suffix: '-hipblas-ffmpeg'
ffmpeg: 'true'
image-type: 'extras'
aio: "-aio-gpu-hipblas"
base-image: "rocm/dev-ubuntu-22.04:6.0-complete"
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-22.04:6.0-complete"
runs-on: 'arc-runner-set'
makeflags: "--jobs=3 --output-sync=target"
- build-type: 'sycl_f16'
platforms: 'linux/amd64'
tag-latest: 'auto'
base-image: "intel/oneapi-basekit:2024.0.1-devel-ubuntu22.04"
tag-suffix: '-sycl-f16-ffmpeg'
ffmpeg: 'true'
image-type: 'extras'
runs-on: 'arc-runner-set'
aio: "-aio-gpu-intel-f16"
latest-image: 'latest-gpu-intel-f16'
latest-image-aio: 'latest-aio-gpu-intel-f16'
makeflags: "--jobs=3 --output-sync=target"
- build-type: 'sycl_f32'
platforms: 'linux/amd64'
tag-latest: 'auto'
base-image: "intel/oneapi-basekit:2024.0.1-devel-ubuntu22.04"
tag-suffix: '-sycl-f32-ffmpeg'
ffmpeg: 'true'
image-type: 'extras'
runs-on: 'arc-runner-set'
aio: "-aio-gpu-intel-f32"
latest-image: 'latest-gpu-intel-f32'
latest-image-aio: 'latest-aio-gpu-intel-f32'
makeflags: "--jobs=3 --output-sync=target"
# Core images
- build-type: 'sycl_f16'
platforms: 'linux/amd64'
tag-latest: 'false'
base-image: "intel/oneapi-basekit:2024.0.1-devel-ubuntu22.04"
tag-suffix: '-sycl-f16-core'
ffmpeg: 'false'
image-type: 'core'
runs-on: 'arc-runner-set'
makeflags: "--jobs=3 --output-sync=target"
- build-type: 'sycl_f32'
platforms: 'linux/amd64'
tag-latest: 'false'
base-image: "intel/oneapi-basekit:2024.0.1-devel-ubuntu22.04"
tag-suffix: '-sycl-f32-core'
ffmpeg: 'false'
image-type: 'core'
runs-on: 'arc-runner-set'
makeflags: "--jobs=3 --output-sync=target"
- build-type: 'sycl_f16'
platforms: 'linux/amd64'
tag-latest: 'false'
base-image: "intel/oneapi-basekit:2024.0.1-devel-ubuntu22.04"
tag-suffix: '-sycl-f16-ffmpeg-core'
ffmpeg: 'true'
image-type: 'core'
runs-on: 'arc-runner-set'
makeflags: "--jobs=3 --output-sync=target"
- build-type: 'sycl_f32'
platforms: 'linux/amd64'
tag-latest: 'false'
base-image: "intel/oneapi-basekit:2024.0.1-devel-ubuntu22.04"
tag-suffix: '-sycl-f32-ffmpeg-core'
ffmpeg: 'true'
image-type: 'core'
runs-on: 'arc-runner-set'
makeflags: "--jobs=3 --output-sync=target"
- build-type: 'hipblas'
platforms: 'linux/amd64'
tag-latest: 'false'
tag-suffix: '-hipblas-ffmpeg-core'
ffmpeg: 'true'
image-type: 'core'
base-image: "rocm/dev-ubuntu-22.04:6.0-complete"
runs-on: 'arc-runner-set'
makeflags: "--jobs=3 --output-sync=target"
- build-type: 'hipblas'
platforms: 'linux/amd64'
tag-latest: 'false'
tag-suffix: '-hipblas-core'
ffmpeg: 'false'
image-type: 'core'
base-image: "rocm/dev-ubuntu-22.04:6.0-complete"
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 }}
@@ -151,10 +236,9 @@ jobs:
runs-on: ${{ matrix.runs-on }}
aio: ${{ matrix.aio }}
base-image: ${{ matrix.base-image }}
grpc-base-image: ${{ matrix.grpc-base-image }}
makeflags: ${{ matrix.makeflags }}
skip-drivers: ${{ matrix.skip-drivers }}
ubuntu-version: ${{ matrix.ubuntu-version }}
latest-image: ${{ matrix.latest-image }}
latest-image-aio: ${{ matrix.latest-image-aio }}
secrets:
dockerUsername: ${{ secrets.DOCKERHUB_USERNAME }}
dockerPassword: ${{ secrets.DOCKERHUB_PASSWORD }}
@@ -163,25 +247,59 @@ jobs:
strategy:
matrix:
include:
- build-type: ''
platforms: 'linux/amd64'
tag-latest: 'auto'
tag-suffix: '-ffmpeg-core'
ffmpeg: 'true'
image-type: 'core'
base-image: "ubuntu:22.04"
runs-on: 'ubuntu-latest'
aio: "-aio-cpu"
latest-image: 'latest-cpu'
latest-image-aio: 'latest-aio-cpu'
makeflags: "--jobs=5 --output-sync=target"
- build-type: 'cublas'
cuda-major-version: "11"
cuda-minor-version: "7"
platforms: 'linux/amd64'
tag-latest: 'false'
tag-suffix: '-cublas-cuda11-core'
ffmpeg: ''
image-type: 'core'
base-image: "ubuntu:22.04"
runs-on: 'ubuntu-latest'
makeflags: "--jobs=5 --output-sync=target"
- build-type: 'cublas'
cuda-major-version: "12"
cuda-minor-version: "0"
platforms: 'linux/arm64'
tag-latest: 'auto'
tag-suffix: '-nvidia-l4t-arm64'
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'
ubuntu-version: "2204"
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: 'ubuntu-latest'
makeflags: "--jobs=5 --output-sync=target"
- build-type: 'cublas'
cuda-major-version: "13"
cuda-minor-version: "0"
platforms: 'linux/arm64'
tag-latest: 'auto'
tag-suffix: '-nvidia-l4t-arm64-cuda-13'
base-image: "ubuntu:24.04"
runs-on: 'ubuntu-24.04-arm'
makeflags: "--jobs=4 --output-sync=target"
skip-drivers: 'false'
ubuntu-version: '2404'
cuda-major-version: "11"
cuda-minor-version: "7"
platforms: 'linux/amd64'
tag-latest: 'false'
tag-suffix: '-cublas-cuda11-ffmpeg-core'
ffmpeg: 'true'
image-type: 'core'
runs-on: 'ubuntu-latest'
base-image: "ubuntu:22.04"
makeflags: "--jobs=5 --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=5 --output-sync=target"

View File

@@ -6,10 +6,6 @@ on:
inputs:
base-image:
description: 'Base image'
required: true
type: string
grpc-base-image:
description: 'GRPC Base image, must be a compatible image with base-image'
required: false
default: ''
type: string
@@ -19,11 +15,11 @@ on:
type: string
cuda-major-version:
description: 'CUDA major version'
default: "12"
default: "11"
type: string
cuda-minor-version:
description: 'CUDA minor version'
default: "4"
default: "7"
type: string
platforms:
description: 'Platforms'
@@ -33,13 +29,25 @@ on:
description: 'Tag latest'
default: ''
type: string
latest-image:
description: 'Tag latest'
default: ''
type: string
latest-image-aio:
description: 'Tag latest'
default: ''
type: string
tag-suffix:
description: 'Tag suffix'
default: ''
type: string
skip-drivers:
description: 'Skip drivers by default'
default: 'false'
ffmpeg:
description: 'FFMPEG'
default: ''
type: string
image-type:
description: 'Image type'
default: ''
type: string
runs-on:
description: 'Runs on'
@@ -49,18 +57,13 @@ on:
makeflags:
description: 'Make Flags'
required: false
default: '--jobs=4 --output-sync=target'
default: '--jobs=3 --output-sync=target'
type: string
aio:
description: 'AIO Image Name'
required: false
default: ''
type: string
ubuntu-version:
description: 'Ubuntu version'
required: false
default: '2204'
type: string
secrets:
dockerUsername:
required: true
@@ -74,22 +77,6 @@ jobs:
reusable_image-build:
runs-on: ${{ inputs.runs-on }}
steps:
- name: Free Disk Space (Ubuntu)
if: inputs.runs-on == 'ubuntu-latest'
uses: jlumbroso/free-disk-space@main
with:
# this might remove tools that are actually needed,
# if set to "true" but frees about 6 GB
tool-cache: true
# all of these default to true, but feel free to set to
# "false" if necessary for your workflow
android: true
dotnet: true
haskell: true
large-packages: true
docker-images: true
swap-storage: true
- name: Force Install GIT latest
run: |
sudo apt-get update \
@@ -99,7 +86,7 @@ jobs:
&& sudo apt-get update \
&& sudo apt-get install -y git
- name: Checkout
uses: actions/checkout@v6
uses: actions/checkout@v4
- name: Release space from worker
if: inputs.runs-on == 'ubuntu-latest'
@@ -111,8 +98,8 @@ jobs:
df -h
echo
sudo apt-get remove -y '^llvm-.*|^libllvm.*' || true
sudo apt-get remove --auto-remove android-sdk-platform-tools snapd || true
sudo apt-get purge --auto-remove android-sdk-platform-tools snapd || true
sudo apt-get remove --auto-remove android-sdk-platform-tools || true
sudo apt-get purge --auto-remove android-sdk-platform-tools || true
sudo rm -rf /usr/local/lib/android
sudo apt-get remove -y '^dotnet-.*|^aspnetcore-.*' || true
sudo rm -rf /usr/share/dotnet
@@ -145,7 +132,6 @@ jobs:
- name: Docker meta
id: meta
if: github.event_name != 'pull_request'
uses: docker/metadata-action@v5
with:
images: |
@@ -155,23 +141,10 @@ jobs:
type=ref,event=branch
type=semver,pattern={{raw}}
type=sha
flavor: |
latest=${{ inputs.tag-latest }}
suffix=${{ inputs.tag-suffix }},onlatest=true
- name: Docker meta for PR
id: meta_pull_request
if: github.event_name == 'pull_request'
uses: docker/metadata-action@v5
with:
images: |
quay.io/go-skynet/ci-tests
tags: |
type=ref,event=branch,suffix=localai${{ github.event.number }}-${{ inputs.build-type }}-${{ inputs.cuda-major-version }}-${{ inputs.cuda-minor-version }}
type=semver,pattern={{raw}},suffix=localai${{ github.event.number }}-${{ inputs.build-type }}-${{ inputs.cuda-major-version }}-${{ inputs.cuda-minor-version }}
type=sha,suffix=localai${{ github.event.number }}-${{ inputs.build-type }}-${{ inputs.cuda-major-version }}-${{ inputs.cuda-minor-version }}
flavor: |
latest=${{ inputs.tag-latest }}
suffix=${{ inputs.tag-suffix }}
- name: Docker meta AIO (quay.io)
if: inputs.aio != ''
id: meta_aio
@@ -184,7 +157,7 @@ jobs:
type=semver,pattern={{raw}}
flavor: |
latest=${{ inputs.tag-latest }}
suffix=${{ inputs.aio }},onlatest=true
suffix=${{ inputs.aio }}
- name: Docker meta AIO (dockerhub)
if: inputs.aio != ''
@@ -198,7 +171,7 @@ jobs:
type=semver,pattern={{raw}}
flavor: |
latest=${{ inputs.tag-latest }}
suffix=${{ inputs.aio }},onlatest=true
suffix=${{ inputs.aio }}
- name: Set up QEMU
uses: docker/setup-qemu-action@master
@@ -224,26 +197,37 @@ jobs:
username: ${{ secrets.quayUsername }}
password: ${{ secrets.quayPassword }}
- name: Build and push
uses: docker/build-push-action@v6
if: github.event_name != 'pull_request'
- name: Cache GRPC
uses: docker/build-push-action@v5
with:
builder: ${{ steps.buildx.outputs.name }}
build-args: |
IMAGE_TYPE=${{ inputs.image-type }}
BASE_IMAGE=${{ inputs.base-image }}
MAKEFLAGS=${{ inputs.makeflags }}
GRPC_VERSION=v1.58.0
context: .
file: ./Dockerfile
cache-from: type=gha
cache-to: type=gha,ignore-error=true
target: grpc
platforms: ${{ inputs.platforms }}
push: false
tags: ${{ steps.meta.outputs.tags }}
labels: ${{ steps.meta.outputs.labels }}
- name: Build and push
uses: docker/build-push-action@v5
with:
builder: ${{ steps.buildx.outputs.name }}
# The build-args MUST be an EXACT match between the image cache and other workflow steps that want to use that cache.
# This means that even the MAKEFLAGS have to be an EXACT match.
# If the build-args are not an EXACT match, it will result in a cache miss, which will require GRPC to be built from scratch.
# This is why some build args like GRPC_VERSION and MAKEFLAGS are hardcoded
build-args: |
BUILD_TYPE=${{ inputs.build-type }}
CUDA_MAJOR_VERSION=${{ inputs.cuda-major-version }}
CUDA_MINOR_VERSION=${{ 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 }}
UBUNTU_VERSION=${{ inputs.ubuntu-version }}
context: .
file: ./Dockerfile
cache-from: type=gha
@@ -251,38 +235,18 @@ 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 }}
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 }}
UBUNTU_VERSION=${{ inputs.ubuntu-version }}
context: .
file: ./Dockerfile
cache-from: type=gha
platforms: ${{ inputs.platforms }}
#push: true
tags: ${{ steps.meta_pull_request.outputs.tags }}
labels: ${{ steps.meta_pull_request.outputs.labels }}
## End testing image
- name: Inspect image
if: github.event_name != 'pull_request'
run: |
docker pull localai/localai:${{ steps.meta.outputs.version }}
docker image inspect localai/localai:${{ steps.meta.outputs.version }}
docker pull quay.io/go-skynet/local-ai:${{ steps.meta.outputs.version }}
docker image inspect quay.io/go-skynet/local-ai:${{ steps.meta.outputs.version }}
- 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 +261,7 @@ 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: |
@@ -310,6 +274,27 @@ jobs:
tags: ${{ steps.meta_aio_dockerhub.outputs.tags }}
labels: ${{ steps.meta_aio_dockerhub.outputs.labels }}
- name: Latest tag
# run this on branches, when it is a tag and there is a latest-image defined
if: github.event_name != 'pull_request' && inputs.latest-image != '' && github.ref_type == 'tag'
run: |
docker pull localai/localai:${{ steps.meta.outputs.version }}
docker tag localai/localai:${{ steps.meta.outputs.version }} localai/localai:${{ inputs.latest-image }}
docker push localai/localai:${{ inputs.latest-image }}
docker pull quay.io/go-skynet/local-ai:${{ steps.meta.outputs.version }}
docker tag quay.io/go-skynet/local-ai:${{ steps.meta.outputs.version }} quay.io/go-skynet/local-ai:${{ inputs.latest-image }}
docker push quay.io/go-skynet/local-ai:${{ inputs.latest-image }}
- name: Latest AIO tag
# run this on branches, when it is a tag and there is a latest-image defined
if: github.event_name != 'pull_request' && inputs.latest-image-aio != '' && github.ref_type == 'tag'
run: |
docker pull localai/localai:${{ steps.meta_aio_dockerhub.outputs.version }}
docker tag localai/localai:${{ steps.meta_aio_dockerhub.outputs.version }} localai/localai:${{ inputs.latest-image-aio }}
docker push localai/localai:${{ inputs.latest-image-aio }}
docker pull quay.io/go-skynet/local-ai:${{ steps.meta_aio.outputs.version }}
docker tag quay.io/go-skynet/local-ai:${{ steps.meta_aio.outputs.version }} quay.io/go-skynet/local-ai:${{ inputs.latest-image-aio }}
docker push quay.io/go-skynet/local-ai:${{ inputs.latest-image-aio }}
- name: job summary
run: |
echo "Built image: ${{ steps.meta.outputs.labels }}" >> $GITHUB_STEP_SUMMARY

View File

@@ -9,4 +9,4 @@ jobs:
pull-requests: write
runs-on: ubuntu-latest
steps:
- uses: actions/labeler@v6
- uses: actions/labeler@v5

View File

@@ -1,36 +0,0 @@
name: LocalAI-bot auto-merge
on:
- pull_request_target
permissions:
contents: write
pull-requests: write
packages: read
issues: write # for Homebrew/actions/post-comment
actions: write # to dispatch publish workflow
jobs:
dependabot:
runs-on: ubuntu-latest
if: ${{ github.actor == 'localai-bot' && !contains(github.event.pull_request.title, 'chore(model gallery):') }}
steps:
- name: Checkout repository
uses: actions/checkout@v6
- name: Approve a PR if not already approved
run: |
gh pr checkout "$PR_URL"
if [ "$(gh pr status --json reviewDecision -q .currentBranch.reviewDecision)" != "APPROVED" ];
then
gh pr review --approve "$PR_URL"
else
echo "PR already approved.";
fi
env:
PR_URL: ${{github.event.pull_request.html_url}}
GITHUB_TOKEN: ${{secrets.GITHUB_TOKEN}}
- name: Enable auto-merge for LocalAIBot PRs
run: gh pr merge --auto --squash "$PR_URL"
env:
PR_URL: ${{github.event.pull_request.html_url}}
GITHUB_TOKEN: ${{secrets.GITHUB_TOKEN}}

View File

@@ -1,174 +0,0 @@
name: Notifications for new models
on:
pull_request_target:
types:
- closed
permissions:
contents: read
pull-requests: read
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-qat
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v6
with:
fetch-depth: 0 # needed to checkout all branches for this Action to work
ref: ${{ github.event.pull_request.head.sha }} # Checkout the PR head to get the actual changes
- uses: mudler/localai-github-action@v1
with:
model: 'gemma-3-12b-it-qat' # 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@v2.8.1
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@v3.23
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-qat
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v6
with:
fetch-depth: 0 # needed to checkout all branches for this Action to work
ref: ${{ github.event.pull_request.head.sha }} # Checkout the PR head to get the actual changes
- name: Start LocalAI
run: |
echo "Starting LocalAI..."
docker run -e -ti -d --name local-ai -p 8080:8080 localai/localai:master 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@v2.8.1
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@v3.23
with:
detached: true
connect-timeout-seconds: 180
limit-access-to-actor: true

View File

@@ -1,64 +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: ${{ github.event.release.tag_name }}
MODEL_NAME: gemma-3-12b-it-qat
steps:
- uses: mudler/localai-github-action@v1
with:
model: 'gemma-3-12b-it-qat' # Any from models.localai.io, or from huggingface.com with: "huggingface://<repository>/file"
- name: Summarize
id: summarize
run: |
input="$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

@@ -1,64 +1,166 @@
name: goreleaser
name: Build and Release
on:
push:
tags:
- 'v*'
on: push
env:
GRPC_VERSION: v1.58.0
permissions:
contents: write
concurrency:
group: ci-releases-${{ github.head_ref || github.ref }}-${{ github.repository }}
cancel-in-progress: true
jobs:
goreleaser:
build-linux:
strategy:
matrix:
include:
- build: 'avx2'
defines: ''
- build: 'avx'
defines: '-DLLAMA_AVX2=OFF'
- build: 'avx512'
defines: '-DLLAMA_AVX512=ON'
- build: 'cuda12'
defines: ''
- build: 'cuda11'
defines: ''
runs-on: ubuntu-latest
steps:
- name: Checkout
uses: actions/checkout@v6
- name: Clone
uses: actions/checkout@v4
with:
fetch-depth: 0
- name: Set up Go
uses: actions/setup-go@v5
submodules: true
- uses: actions/setup-go@v4
with:
go-version: 1.23
- name: Run GoReleaser
uses: goreleaser/goreleaser-action@v6
with:
version: v2.11.0
args: release --clean
env:
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
launcher-build-darwin:
runs-on: macos-latest
steps:
- name: Checkout
uses: actions/checkout@v6
with:
fetch-depth: 0
- name: Set up Go
uses: actions/setup-go@v5
with:
go-version: 1.23
- name: Build launcher for macOS ARM64
run: |
make build-launcher-darwin
- name: Upload DMG to Release
uses: softprops/action-gh-release@v2
with:
files: ./dist/LocalAI.dmg
launcher-build-linux:
runs-on: ubuntu-latest
steps:
- name: Checkout
uses: actions/checkout@v6
with:
fetch-depth: 0
- name: Set up Go
uses: actions/setup-go@v5
with:
go-version: 1.23
- name: Build launcher for Linux
go-version: '1.21.x'
cache: false
- name: Dependencies
run: |
sudo apt-get update
sudo apt-get install golang gcc libgl1-mesa-dev xorg-dev libxkbcommon-dev
make build-launcher-linux
- name: Upload Linux launcher artifacts
uses: softprops/action-gh-release@v2
sudo apt-get install build-essential ffmpeg
- name: Install CUDA Dependencies
if: ${{ matrix.build == 'cuda12' || matrix.build == 'cuda11' }}
run: |
if [ "${{ matrix.build }}" == "cuda12" ]; then
export CUDA_VERSION=12-3
else
export CUDA_VERSION=11-7
fi
curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64/cuda-keyring_1.1-1_all.deb
sudo dpkg -i cuda-keyring_1.1-1_all.deb
sudo apt-get update
sudo apt-get install -y cuda-nvcc-${CUDA_VERSION} libcublas-dev-${CUDA_VERSION}
- name: Cache grpc
id: cache-grpc
uses: actions/cache@v3
with:
files: ./local-ai-launcher-linux.tar.xz
path: grpc
key: ${{ runner.os }}-grpc-${{ env.GRPC_VERSION }}
- name: Build grpc
if: steps.cache-grpc.outputs.cache-hit != 'true'
run: |
git clone --recurse-submodules -b ${{ env.GRPC_VERSION }} --depth 1 --shallow-submodules https://github.com/grpc/grpc && \
cd grpc && mkdir -p cmake/build && cd cmake/build && cmake -DgRPC_INSTALL=ON \
-DgRPC_BUILD_TESTS=OFF \
../.. && sudo make --jobs 5 --output-sync=target
- name: Install gRPC
run: |
cd grpc && cd cmake/build && sudo make --jobs 5 --output-sync=target install
- name: Build
id: build
env:
CMAKE_ARGS: "${{ matrix.defines }}"
BUILD_ID: "${{ matrix.build }}"
run: |
if [ "${{ matrix.build }}" == "cuda12" ] || [ "${{ matrix.build }}" == "cuda11" ]; then
export BUILD_TYPE=cublas
export PATH=/usr/local/cuda/bin:$PATH
make dist
else
STATIC=true make dist
fi
- uses: actions/upload-artifact@v3
with:
name: ${{ matrix.build }}
path: release/
- name: Release
uses: softprops/action-gh-release@v1
if: startsWith(github.ref, 'refs/tags/')
with:
files: |
release/*
build-stablediffusion:
runs-on: ubuntu-latest
steps:
- name: Clone
uses: actions/checkout@v4
with:
submodules: true
- uses: actions/setup-go@v4
with:
go-version: '1.21.x'
cache: false
- name: Dependencies
run: |
sudo apt-get install -y --no-install-recommends libopencv-dev
- name: Build stablediffusion
run: |
make backend-assets/grpc/stablediffusion
mkdir -p release && cp backend-assets/grpc/stablediffusion release
- uses: actions/upload-artifact@v3
with:
name: stablediffusion
path: release/
- name: Release
uses: softprops/action-gh-release@v1
if: startsWith(github.ref, 'refs/tags/')
with:
files: |
release/*
build-macOS:
strategy:
matrix:
include:
- build: 'avx2'
defines: ''
- build: 'avx'
defines: '-DLLAMA_AVX2=OFF'
- build: 'avx512'
defines: '-DLLAMA_AVX512=ON'
runs-on: macOS-latest
steps:
- name: Clone
uses: actions/checkout@v4
with:
submodules: true
- uses: actions/setup-go@v4
with:
go-version: '1.21.x'
cache: false
- name: Dependencies
run: |
brew install protobuf grpc
- name: Build
id: build
env:
CMAKE_ARGS: "${{ matrix.defines }}"
BUILD_ID: "${{ matrix.build }}"
run: |
export C_INCLUDE_PATH=/usr/local/include
export CPLUS_INCLUDE_PATH=/usr/local/include
make dist
- uses: actions/upload-artifact@v3
with:
name: ${{ matrix.build }}
path: release/
- name: Release
uses: softprops/action-gh-release@v1
if: startsWith(github.ref, 'refs/tags/')
with:
files: |
release/*

View File

@@ -14,17 +14,14 @@ jobs:
GO111MODULE: on
steps:
- name: Checkout Source
uses: actions/checkout@v6
if: ${{ github.actor != 'dependabot[bot]' }}
uses: actions/checkout@v3
- name: Run Gosec Security Scanner
if: ${{ github.actor != 'dependabot[bot]' }}
uses: securego/gosec@v2.22.9
uses: securego/gosec@master
with:
# we let the report trigger content trigger a failure using the GitHub Security features.
args: '-no-fail -fmt sarif -out results.sarif ./...'
- name: Upload SARIF file
if: ${{ github.actor != 'dependabot[bot]' }}
uses: github/codeql-action/upload-sarif@v4
uses: github/codeql-action/upload-sarif@v2
with:
# Path to SARIF file relative to the root of the repository
sarif_file: results.sarif
sarif_file: results.sarif

View File

@@ -1,24 +0,0 @@
name: 'Close stale issues and PRs'
permissions:
issues: write
pull-requests: write
on:
schedule:
- cron: '30 1 * * *'
jobs:
stale:
runs-on: ubuntu-latest
steps:
- uses: actions/stale@997185467fa4f803885201cee163a9f38240193d # v9
with:
stale-issue-message: 'This issue is stale because it has been open 90 days with no activity. Remove stale label or comment or this will be closed in 5 days.'
stale-pr-message: 'This PR is stale because it has been open 90 days with no activity. Remove stale label or comment or this will be closed in 10 days.'
close-issue-message: 'This issue was closed because it has been stalled for 5 days with no activity.'
close-pr-message: 'This PR was closed because it has been stalled for 10 days with no activity.'
days-before-issue-stale: 90
days-before-pr-stale: 90
days-before-issue-close: 5
days-before-pr-close: 10
exempt-issue-labels: 'roadmap'
exempt-pr-labels: 'roadmap'

View File

@@ -14,133 +14,155 @@ concurrency:
cancel-in-progress: true
jobs:
# Requires CUDA
# tests-chatterbox-tts:
# runs-on: ubuntu-latest
# steps:
# - name: Clone
# uses: actions/checkout@v6
# with:
# submodules: true
# - name: Dependencies
# run: |
# sudo apt-get update
# sudo apt-get install build-essential ffmpeg
# # Install UV
# curl -LsSf https://astral.sh/uv/install.sh | sh
# sudo apt-get install -y ca-certificates cmake curl patch python3-pip
# sudo apt-get install -y libopencv-dev
# pip install --user --no-cache-dir grpcio-tools==1.64.1
# - name: Test chatterbox-tts
# run: |
# make --jobs=5 --output-sync=target -C backend/python/chatterbox
# make --jobs=5 --output-sync=target -C backend/python/chatterbox test
tests-transformers:
runs-on: ubuntu-latest
steps:
- name: Clone
uses: actions/checkout@v6
with:
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
curl https://repo.anaconda.com/pkgs/misc/gpgkeys/anaconda.asc | gpg --dearmor > conda.gpg && \
sudo install -o root -g root -m 644 conda.gpg /usr/share/keyrings/conda-archive-keyring.gpg && \
gpg --keyring /usr/share/keyrings/conda-archive-keyring.gpg --no-default-keyring --fingerprint 34161F5BF5EB1D4BFBBB8F0A8AEB4F8B29D82806 && \
sudo /bin/bash -c 'echo "deb [arch=amd64 signed-by=/usr/share/keyrings/conda-archive-keyring.gpg] https://repo.anaconda.com/pkgs/misc/debrepo/conda stable main" > /etc/apt/sources.list.d/conda.list' && \
sudo /bin/bash -c 'echo "deb [arch=amd64 signed-by=/usr/share/keyrings/conda-archive-keyring.gpg] https://repo.anaconda.com/pkgs/misc/debrepo/conda stable main" | tee -a /etc/apt/sources.list.d/conda.list' && \
sudo apt-get update && \
sudo apt-get install -y conda
sudo apt-get install -y ca-certificates cmake curl patch
sudo apt-get install -y libopencv-dev
pip install --user --no-cache-dir grpcio-tools==1.64.1
sudo rm -rfv /usr/bin/conda || true
- name: Test transformers
run: |
export PATH=$PATH:/opt/conda/bin
make --jobs=5 --output-sync=target -C backend/python/transformers
make --jobs=5 --output-sync=target -C backend/python/transformers test
tests-rerankers:
tests-sentencetransformers:
runs-on: ubuntu-latest
steps:
- name: Clone
uses: actions/checkout@v6
with:
uses: actions/checkout@v4
with:
submodules: true
- name: Dependencies
run: |
sudo apt-get update
sudo apt-get install build-essential ffmpeg
# Install UV
curl -LsSf https://astral.sh/uv/install.sh | sh
sudo apt-get install -y ca-certificates cmake curl patch python3-pip
curl https://repo.anaconda.com/pkgs/misc/gpgkeys/anaconda.asc | gpg --dearmor > conda.gpg && \
sudo install -o root -g root -m 644 conda.gpg /usr/share/keyrings/conda-archive-keyring.gpg && \
gpg --keyring /usr/share/keyrings/conda-archive-keyring.gpg --no-default-keyring --fingerprint 34161F5BF5EB1D4BFBBB8F0A8AEB4F8B29D82806 && \
sudo /bin/bash -c 'echo "deb [arch=amd64 signed-by=/usr/share/keyrings/conda-archive-keyring.gpg] https://repo.anaconda.com/pkgs/misc/debrepo/conda stable main" > /etc/apt/sources.list.d/conda.list' && \
sudo /bin/bash -c 'echo "deb [arch=amd64 signed-by=/usr/share/keyrings/conda-archive-keyring.gpg] https://repo.anaconda.com/pkgs/misc/debrepo/conda stable main" | tee -a /etc/apt/sources.list.d/conda.list' && \
sudo apt-get update && \
sudo apt-get install -y conda
sudo apt-get install -y ca-certificates cmake curl patch
sudo apt-get install -y libopencv-dev
pip install --user --no-cache-dir grpcio-tools==1.64.1
sudo rm -rfv /usr/bin/conda || true
- name: Test rerankers
- name: Test sentencetransformers
run: |
make --jobs=5 --output-sync=target -C backend/python/rerankers
make --jobs=5 --output-sync=target -C backend/python/rerankers test
export PATH=$PATH:/opt/conda/bin
make --jobs=5 --output-sync=target -C backend/python/sentencetransformers
make --jobs=5 --output-sync=target -C backend/python/sentencetransformers test
tests-diffusers:
runs-on: ubuntu-latest
steps:
- name: Clone
uses: actions/checkout@v6
with:
uses: actions/checkout@v4
with:
submodules: true
- name: Dependencies
run: |
sudo apt-get update
sudo apt-get install -y build-essential ffmpeg
sudo apt-get install -y ca-certificates cmake curl patch python3-pip
sudo apt-get install build-essential ffmpeg
curl https://repo.anaconda.com/pkgs/misc/gpgkeys/anaconda.asc | gpg --dearmor > conda.gpg && \
sudo install -o root -g root -m 644 conda.gpg /usr/share/keyrings/conda-archive-keyring.gpg && \
gpg --keyring /usr/share/keyrings/conda-archive-keyring.gpg --no-default-keyring --fingerprint 34161F5BF5EB1D4BFBBB8F0A8AEB4F8B29D82806 && \
sudo /bin/bash -c 'echo "deb [arch=amd64 signed-by=/usr/share/keyrings/conda-archive-keyring.gpg] https://repo.anaconda.com/pkgs/misc/debrepo/conda stable main" > /etc/apt/sources.list.d/conda.list' && \
sudo /bin/bash -c 'echo "deb [arch=amd64 signed-by=/usr/share/keyrings/conda-archive-keyring.gpg] https://repo.anaconda.com/pkgs/misc/debrepo/conda stable main" | tee -a /etc/apt/sources.list.d/conda.list' && \
sudo apt-get update && \
sudo apt-get install -y conda
sudo apt-get install -y ca-certificates cmake curl patch
sudo apt-get install -y libopencv-dev
# Install UV
curl -LsSf https://astral.sh/uv/install.sh | sh
pip install --user --no-cache-dir grpcio-tools==1.64.1
sudo rm -rfv /usr/bin/conda || true
- name: Test diffusers
run: |
make --jobs=5 --output-sync=target -C backend/python/diffusers
make --jobs=5 --output-sync=target -C backend/python/diffusers test
export PATH=$PATH:/opt/conda/bin
make --jobs=5 --output-sync=target -C backend/python/diffusers
make --jobs=5 --output-sync=target -C backend/python/diffusers test
#tests-vllm:
# runs-on: ubuntu-latest
# steps:
# - name: Clone
# uses: actions/checkout@v6
# with:
# submodules: true
# - name: Dependencies
# run: |
# sudo apt-get update
# sudo apt-get install -y build-essential ffmpeg
# sudo apt-get install -y ca-certificates cmake curl patch python3-pip
# sudo apt-get install -y libopencv-dev
# # Install UV
# curl -LsSf https://astral.sh/uv/install.sh | sh
# pip install --user --no-cache-dir grpcio-tools==1.64.1
# - name: Test vllm backend
# run: |
# make --jobs=5 --output-sync=target -C backend/python/vllm
# make --jobs=5 --output-sync=target -C backend/python/vllm test
# tests-transformers-musicgen:
tests-transformers-musicgen:
runs-on: ubuntu-latest
steps:
- name: Clone
uses: actions/checkout@v4
with:
submodules: true
- name: Dependencies
run: |
sudo apt-get update
sudo apt-get install build-essential ffmpeg
curl https://repo.anaconda.com/pkgs/misc/gpgkeys/anaconda.asc | gpg --dearmor > conda.gpg && \
sudo install -o root -g root -m 644 conda.gpg /usr/share/keyrings/conda-archive-keyring.gpg && \
gpg --keyring /usr/share/keyrings/conda-archive-keyring.gpg --no-default-keyring --fingerprint 34161F5BF5EB1D4BFBBB8F0A8AEB4F8B29D82806 && \
sudo /bin/bash -c 'echo "deb [arch=amd64 signed-by=/usr/share/keyrings/conda-archive-keyring.gpg] https://repo.anaconda.com/pkgs/misc/debrepo/conda stable main" > /etc/apt/sources.list.d/conda.list' && \
sudo /bin/bash -c 'echo "deb [arch=amd64 signed-by=/usr/share/keyrings/conda-archive-keyring.gpg] https://repo.anaconda.com/pkgs/misc/debrepo/conda stable main" | tee -a /etc/apt/sources.list.d/conda.list' && \
sudo apt-get update && \
sudo apt-get install -y conda
sudo apt-get install -y ca-certificates cmake curl patch
sudo apt-get install -y libopencv-dev
sudo rm -rfv /usr/bin/conda || true
- name: Test transformers-musicgen
run: |
export PATH=$PATH:/opt/conda/bin
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@v6
# with:
# 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
# curl https://repo.anaconda.com/pkgs/misc/gpgkeys/anaconda.asc | gpg --dearmor > conda.gpg && \
# sudo install -o root -g root -m 644 conda.gpg /usr/share/keyrings/conda-archive-keyring.gpg && \
# gpg --keyring /usr/share/keyrings/conda-archive-keyring.gpg --no-default-keyring --fingerprint 34161F5BF5EB1D4BFBBB8F0A8AEB4F8B29D82806 && \
# sudo /bin/bash -c 'echo "deb [arch=amd64 signed-by=/usr/share/keyrings/conda-archive-keyring.gpg] https://repo.anaconda.com/pkgs/misc/debrepo/conda stable main" > /etc/apt/sources.list.d/conda.list' && \
# sudo /bin/bash -c 'echo "deb [arch=amd64 signed-by=/usr/share/keyrings/conda-archive-keyring.gpg] https://repo.anaconda.com/pkgs/misc/debrepo/conda stable main" | tee -a /etc/apt/sources.list.d/conda.list' && \
# sudo apt-get update && \
# sudo apt-get install -y conda
# sudo apt-get install -y ca-certificates cmake curl patch
# sudo apt-get install -y libopencv-dev
# pip install --user --no-cache-dir grpcio-tools==1.64.1
# sudo rm -rfv /usr/bin/conda || true
# - 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
# export PATH=$PATH:/opt/conda/bin
# make --jobs=5 --output-sync=target -C backend/python/petals
# make --jobs=5 --output-sync=target -C backend/python/petals test
# tests-bark:
# runs-on: ubuntu-latest
@@ -186,64 +208,110 @@ jobs:
# sudo rm -rf "$AGENT_TOOLSDIRECTORY" || true
# df -h
# - name: Clone
# uses: actions/checkout@v6
# with:
# 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
# curl https://repo.anaconda.com/pkgs/misc/gpgkeys/anaconda.asc | gpg --dearmor > conda.gpg && \
# sudo install -o root -g root -m 644 conda.gpg /usr/share/keyrings/conda-archive-keyring.gpg && \
# gpg --keyring /usr/share/keyrings/conda-archive-keyring.gpg --no-default-keyring --fingerprint 34161F5BF5EB1D4BFBBB8F0A8AEB4F8B29D82806 && \
# sudo /bin/bash -c 'echo "deb [arch=amd64 signed-by=/usr/share/keyrings/conda-archive-keyring.gpg] https://repo.anaconda.com/pkgs/misc/debrepo/conda stable main" > /etc/apt/sources.list.d/conda.list' && \
# sudo /bin/bash -c 'echo "deb [arch=amd64 signed-by=/usr/share/keyrings/conda-archive-keyring.gpg] https://repo.anaconda.com/pkgs/misc/debrepo/conda stable main" | tee -a /etc/apt/sources.list.d/conda.list' && \
# sudo apt-get update && \
# sudo apt-get install -y conda
# sudo apt-get install -y ca-certificates cmake curl patch
# sudo apt-get install -y libopencv-dev
# pip install --user --no-cache-dir grpcio-tools==1.64.1
# sudo rm -rfv /usr/bin/conda || true
# - name: Test bark
# run: |
# export PATH=$PATH:/opt/conda/bin
# make --jobs=5 --output-sync=target -C backend/python/bark
# make --jobs=5 --output-sync=target -C backend/python/bark test
# Below tests needs GPU. Commented out for now
# TODO: Re-enable as soon as we have GPU nodes
# tests-vllm:
# runs-on: ubuntu-latest
# steps:
# - name: Clone
# uses: actions/checkout@v6
# with:
# uses: actions/checkout@v4
# with:
# submodules: true
# - name: Dependencies
# run: |
# sudo apt-get update
# sudo apt-get install build-essential ffmpeg
# # Install UV
# curl -LsSf https://astral.sh/uv/install.sh | sh
# sudo apt-get install -y ca-certificates cmake curl patch python3-pip
# curl https://repo.anaconda.com/pkgs/misc/gpgkeys/anaconda.asc | gpg --dearmor > conda.gpg && \
# sudo install -o root -g root -m 644 conda.gpg /usr/share/keyrings/conda-archive-keyring.gpg && \
# gpg --keyring /usr/share/keyrings/conda-archive-keyring.gpg --no-default-keyring --fingerprint 34161F5BF5EB1D4BFBBB8F0A8AEB4F8B29D82806 && \
# sudo /bin/bash -c 'echo "deb [arch=amd64 signed-by=/usr/share/keyrings/conda-archive-keyring.gpg] https://repo.anaconda.com/pkgs/misc/debrepo/conda stable main" > /etc/apt/sources.list.d/conda.list' && \
# sudo /bin/bash -c 'echo "deb [arch=amd64 signed-by=/usr/share/keyrings/conda-archive-keyring.gpg] https://repo.anaconda.com/pkgs/misc/debrepo/conda stable main" | tee -a /etc/apt/sources.list.d/conda.list' && \
# sudo apt-get update && \
# sudo apt-get install -y conda
# sudo apt-get install -y ca-certificates cmake curl patch
# sudo apt-get install -y libopencv-dev
# pip install --user --no-cache-dir grpcio-tools==1.64.1
# sudo rm -rfv /usr/bin/conda || true
# - name: Test vllm
# run: |
# export PATH=$PATH:/opt/conda/bin
# make --jobs=5 --output-sync=target -C backend/python/vllm
# make --jobs=5 --output-sync=target -C backend/python/vllm test
tests-coqui:
tests-vallex:
runs-on: ubuntu-latest
steps:
- name: Clone
uses: actions/checkout@v6
with:
uses: actions/checkout@v4
with:
submodules: true
- name: Dependencies
run: |
sudo apt-get update
sudo apt-get install build-essential ffmpeg
sudo apt-get install -y ca-certificates cmake curl patch espeak espeak-ng python3-pip
# Install UV
curl -LsSf https://astral.sh/uv/install.sh | sh
pip install --user --no-cache-dir grpcio-tools==1.64.1
curl https://repo.anaconda.com/pkgs/misc/gpgkeys/anaconda.asc | gpg --dearmor > conda.gpg && \
sudo install -o root -g root -m 644 conda.gpg /usr/share/keyrings/conda-archive-keyring.gpg && \
gpg --keyring /usr/share/keyrings/conda-archive-keyring.gpg --no-default-keyring --fingerprint 34161F5BF5EB1D4BFBBB8F0A8AEB4F8B29D82806 && \
sudo /bin/bash -c 'echo "deb [arch=amd64 signed-by=/usr/share/keyrings/conda-archive-keyring.gpg] https://repo.anaconda.com/pkgs/misc/debrepo/conda stable main" > /etc/apt/sources.list.d/conda.list' && \
sudo /bin/bash -c 'echo "deb [arch=amd64 signed-by=/usr/share/keyrings/conda-archive-keyring.gpg] https://repo.anaconda.com/pkgs/misc/debrepo/conda stable main" | tee -a /etc/apt/sources.list.d/conda.list' && \
sudo apt-get update && \
sudo apt-get install -y conda
sudo apt-get install -y ca-certificates cmake curl patch
sudo apt-get install -y libopencv-dev
sudo rm -rfv /usr/bin/conda || true
- name: Test vall-e-x
run: |
export PATH=$PATH:/opt/conda/bin
make --jobs=5 --output-sync=target -C backend/python/vall-e-x
make --jobs=5 --output-sync=target -C backend/python/vall-e-x test
tests-coqui:
runs-on: ubuntu-latest
steps:
- name: Clone
uses: actions/checkout@v4
with:
submodules: true
- name: Dependencies
run: |
sudo apt-get update
sudo apt-get install build-essential ffmpeg
curl https://repo.anaconda.com/pkgs/misc/gpgkeys/anaconda.asc | gpg --dearmor > conda.gpg && \
sudo install -o root -g root -m 644 conda.gpg /usr/share/keyrings/conda-archive-keyring.gpg && \
gpg --keyring /usr/share/keyrings/conda-archive-keyring.gpg --no-default-keyring --fingerprint 34161F5BF5EB1D4BFBBB8F0A8AEB4F8B29D82806 && \
sudo /bin/bash -c 'echo "deb [arch=amd64 signed-by=/usr/share/keyrings/conda-archive-keyring.gpg] https://repo.anaconda.com/pkgs/misc/debrepo/conda stable main" > /etc/apt/sources.list.d/conda.list' && \
sudo /bin/bash -c 'echo "deb [arch=amd64 signed-by=/usr/share/keyrings/conda-archive-keyring.gpg] https://repo.anaconda.com/pkgs/misc/debrepo/conda stable main" | tee -a /etc/apt/sources.list.d/conda.list' && \
sudo apt-get update && \
sudo apt-get install -y conda
sudo apt-get install -y ca-certificates cmake curl patch espeak espeak-ng
sudo rm -rfv /usr/bin/conda || true
- name: Test coqui
run: |
make --jobs=5 --output-sync=target -C backend/python/coqui
make --jobs=5 --output-sync=target -C backend/python/coqui test
export PATH=$PATH:/opt/conda/bin
make --jobs=5 --output-sync=target -C backend/python/coqui
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: v1.58.0
concurrency:
group: ci-tests-${{ github.head_ref || github.ref }}-${{ github.repository }}
@@ -21,22 +21,8 @@ jobs:
runs-on: ubuntu-latest
strategy:
matrix:
go-version: ['1.25.x']
go-version: ['1.21.x']
steps:
- name: Free Disk Space (Ubuntu)
uses: jlumbroso/free-disk-space@main
with:
# this might remove tools that are actually needed,
# if set to "true" but frees about 6 GB
tool-cache: true
# all of these default to true, but feel free to set to
# "false" if necessary for your workflow
android: true
dotnet: true
haskell: true
large-packages: true
docker-images: true
swap-storage: true
- name: Release space from worker
run: |
echo "Listing top largest packages"
@@ -70,60 +56,63 @@ jobs:
sudo rm -rfv build || true
df -h
- name: Clone
uses: actions/checkout@v6
with:
uses: actions/checkout@v4
with:
submodules: true
- name: Setup Go ${{ matrix.go-version }}
uses: actions/setup-go@v5
uses: actions/setup-go@v4
with:
go-version: ${{ matrix.go-version }}
cache: false
# You can test your matrix by printing the current Go version
- name: Display Go version
run: go version
- name: Proto Dependencies
run: |
# Install protoc
curl -L -s https://github.com/protocolbuffers/protobuf/releases/download/v26.1/protoc-26.1-linux-x86_64.zip -o protoc.zip && \
unzip -j -d /usr/local/bin protoc.zip bin/protoc && \
rm protoc.zip
go install google.golang.org/protobuf/cmd/protoc-gen-go@v1.34.2
go install google.golang.org/grpc/cmd/protoc-gen-go-grpc@1958fcbe2ca8bd93af633f11e97d44e567e945af
PATH="$PATH:$HOME/go/bin" make protogen-go
- name: Dependencies
run: |
sudo apt-get update
sudo apt-get install build-essential ccache upx-ucl curl ffmpeg
sudo apt-get install -y libgmock-dev clang
# Install UV
curl -LsSf https://astral.sh/uv/install.sh | sh
sudo apt-get install -y ca-certificates cmake patch python3-pip unzip
sudo apt-get install build-essential ffmpeg
curl https://repo.anaconda.com/pkgs/misc/gpgkeys/anaconda.asc | gpg --dearmor > conda.gpg && \
sudo install -o root -g root -m 644 conda.gpg /usr/share/keyrings/conda-archive-keyring.gpg && \
gpg --keyring /usr/share/keyrings/conda-archive-keyring.gpg --no-default-keyring --fingerprint 34161F5BF5EB1D4BFBBB8F0A8AEB4F8B29D82806 && \
sudo /bin/bash -c 'echo "deb [arch=amd64 signed-by=/usr/share/keyrings/conda-archive-keyring.gpg] https://repo.anaconda.com/pkgs/misc/debrepo/conda stable main" > /etc/apt/sources.list.d/conda.list' && \
sudo /bin/bash -c 'echo "deb [arch=amd64 signed-by=/usr/share/keyrings/conda-archive-keyring.gpg] https://repo.anaconda.com/pkgs/misc/debrepo/conda stable main" | tee -a /etc/apt/sources.list.d/conda.list' && \
sudo apt-get update && \
sudo apt-get install -y conda
sudo apt-get install -y ca-certificates cmake curl patch
sudo apt-get install -y libopencv-dev
sudo rm -rfv /usr/bin/conda || true
PATH=$PATH:/opt/conda/bin make -C backend/python/sentencetransformers
curl -L -s https://github.com/protocolbuffers/protobuf/releases/download/v26.1/protoc-26.1-linux-x86_64.zip -o protoc.zip && \
unzip -j -d /usr/local/bin protoc.zip bin/protoc && \
rm protoc.zip
curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64/cuda-keyring_1.1-1_all.deb
sudo dpkg -i cuda-keyring_1.1-1_all.deb
sudo apt-get update
sudo apt-get install -y cuda-nvcc-${CUDA_VERSION} libcublas-dev-${CUDA_VERSION}
export CUDACXX=/usr/local/cuda/bin/nvcc
make -C backend/python/transformers
make backends/huggingface backends/llama-cpp backends/local-store backends/silero-vad backends/piper backends/whisper backends/stablediffusion-ggml
env:
CUDA_VERSION: 12-4
# Pre-build piper before we start tests in order to have shared libraries in place
make sources/go-piper && \
GO_TAGS="tts" make -C sources/go-piper piper.o && \
sudo cp -rfv sources/go-piper/piper-phonemize/pi/lib/. /usr/lib/ && \
# Pre-build stable diffusion before we install a newer version of abseil (not compatible with stablediffusion-ncn)
GO_TAGS="stablediffusion tts" GRPC_BACKENDS=backend-assets/grpc/stablediffusion make build
- name: Cache grpc
id: cache-grpc
uses: actions/cache@v3
with:
path: grpc
key: ${{ runner.os }}-grpc-${{ env.GRPC_VERSION }}
- name: Build grpc
if: steps.cache-grpc.outputs.cache-hit != 'true'
run: |
git clone --recurse-submodules -b ${{ env.GRPC_VERSION }} --depth 1 --jobs 5 --shallow-submodules https://github.com/grpc/grpc && \
cd grpc && mkdir -p cmake/build && cd cmake/build && cmake -DgRPC_INSTALL=ON \
-DgRPC_BUILD_TESTS=OFF \
../.. && sudo make --jobs 5
- name: Install gRPC
run: |
cd grpc && cd cmake/build && sudo make --jobs 5 install
- name: Test
run: |
PATH="$PATH:/root/go/bin" GO_TAGS="tts" make --jobs 5 --output-sync=target test
GO_TAGS="stablediffusion tts" make --jobs 5 --output-sync=target test
- name: Setup tmate session if tests fail
if: ${{ failure() }}
uses: mxschmitt/action-tmate@v3.23
with:
detached: true
connect-timeout-seconds: 180
limit-access-to-actor: true
uses: mxschmitt/action-tmate@v3
timeout-minutes: 5
tests-aio-container:
runs-on: ubuntu-latest
@@ -161,41 +150,34 @@ jobs:
sudo rm -rfv build || true
df -h
- name: Clone
uses: actions/checkout@v6
with:
uses: actions/checkout@v4
with:
submodules: true
- name: Dependencies
- name: Build images
run: |
# Install protoc
curl -L -s https://github.com/protocolbuffers/protobuf/releases/download/v26.1/protoc-26.1-linux-x86_64.zip -o protoc.zip && \
unzip -j -d /usr/local/bin protoc.zip bin/protoc && \
rm protoc.zip
go install google.golang.org/protobuf/cmd/protoc-gen-go@v1.34.2
go install google.golang.org/grpc/cmd/protoc-gen-go-grpc@1958fcbe2ca8bd93af633f11e97d44e567e945af
PATH="$PATH:$HOME/go/bin" make protogen-go
docker build --build-arg FFMPEG=true --build-arg IMAGE_TYPE=core --build-arg MAKEFLAGS="--jobs=5 --output-sync=target" -t local-ai:tests -f Dockerfile .
BASE_IMAGE=local-ai:tests DOCKER_AIO_IMAGE=local-ai-aio:test make docker-aio
- name: Test
run: |
PATH="$PATH:$HOME/go/bin" make backends/local-store backends/silero-vad backends/llama-cpp backends/whisper backends/piper backends/stablediffusion-ggml docker-build-aio e2e-aio
LOCALAI_MODELS_DIR=$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@v3.23
with:
detached: true
connect-timeout-seconds: 180
limit-access-to-actor: true
uses: mxschmitt/action-tmate@v3
timeout-minutes: 5
tests-apple:
runs-on: macos-latest
runs-on: macOS-14
strategy:
matrix:
go-version: ['1.25.x']
go-version: ['1.21.x']
steps:
- name: Clone
uses: actions/checkout@v6
with:
uses: actions/checkout@v4
with:
submodules: true
- name: Setup Go ${{ matrix.go-version }}
uses: actions/setup-go@v5
uses: actions/setup-go@v4
with:
go-version: ${{ matrix.go-version }}
cache: false
@@ -204,25 +186,15 @@ jobs:
run: go version
- name: Dependencies
run: |
brew install protobuf grpc make protoc-gen-go protoc-gen-go-grpc libomp llvm
pip install --user --no-cache-dir grpcio-tools grpcio
- name: Build llama-cpp-darwin
run: |
make protogen-go
make backends/llama-cpp-darwin
brew install protobuf grpc make
- name: Test
run: |
export C_INCLUDE_PATH=/usr/local/include
export CPLUS_INCLUDE_PATH=/usr/local/include
export CC=/opt/homebrew/opt/llvm/bin/clang
# Used to run the newer GNUMake version from brew that supports --output-sync
export PATH="/opt/homebrew/opt/make/libexec/gnubin:$PATH"
PATH="$PATH:$HOME/go/bin" make protogen-go
PATH="$PATH:$HOME/go/bin" 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@v3.23
with:
detached: true
connect-timeout-seconds: 180
limit-access-to-actor: true
uses: mxschmitt/action-tmate@v3
timeout-minutes: 5

View File

@@ -1,37 +0,0 @@
name: Update swagger
on:
schedule:
- cron: 0 20 * * *
workflow_dispatch:
jobs:
swagger:
strategy:
fail-fast: false
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v6
- uses: actions/setup-go@v5
with:
go-version: 'stable'
- name: Dependencies
run: |
sudo apt-get update
sudo apt-get install protobuf-compiler
- run: |
go install github.com/swaggo/swag/cmd/swag@latest
go install google.golang.org/grpc/cmd/protoc-gen-go-grpc@1958fcbe2ca8bd93af633f11e97d44e567e945af
go install google.golang.org/protobuf/cmd/protoc-gen-go@v1.34.2
- name: Bump swagger 🔧
run: |
make protogen-go swagger
- name: Create Pull Request
uses: peter-evans/create-pull-request@v8
with:
token: ${{ secrets.UPDATE_BOT_TOKEN }}
push-to-fork: ci-forks/LocalAI
commit-message: 'feat(swagger): update swagger'
title: 'feat(swagger): update swagger'
branch: "update/swagger"
body: Update swagger
signoff: true

View File

@@ -1,26 +0,0 @@
name: 'Yamllint GitHub Actions'
on:
- pull_request
jobs:
yamllint:
name: 'Yamllint'
runs-on: ubuntu-latest
steps:
- name: 'Checkout'
uses: actions/checkout@master
- name: 'Yamllint model gallery'
uses: karancode/yamllint-github-action@master
with:
yamllint_file_or_dir: 'gallery'
yamllint_strict: false
yamllint_comment: true
env:
GITHUB_ACCESS_TOKEN: ${{ secrets.GITHUB_TOKEN }}
- name: 'Yamllint Backend gallery'
uses: karancode/yamllint-github-action@master
with:
yamllint_file_or_dir: 'backend'
yamllint_strict: false
yamllint_comment: true
env:
GITHUB_ACCESS_TOKEN: ${{ secrets.GITHUB_TOKEN }}

31
.gitignore vendored
View File

@@ -2,29 +2,21 @@
/sources/
__pycache__/
*.a
*.o
get-sources
prepare-sources
/backend/cpp/llama-cpp/grpc-server
/backend/cpp/llama-cpp/llama.cpp
/backend/cpp/llama-*
!backend/cpp/llama-cpp
/backends
/backend-images
/result.yaml
protoc
*.log
/backend/cpp/llama/grpc-server
/backend/cpp/llama/llama.cpp
go-ggml-transformers
go-gpt2
go-rwkv
whisper.cpp
/bloomz
go-bert
# LocalAI build binary
LocalAI
/local-ai
local-ai
# prevent above rules from omitting the helm chart
!charts/*
# prevent above rules from omitting the api/localai folder
@@ -47,18 +39,3 @@ backend-assets/*
!backend-assets/.keep
prepare
/ggml-metal.metal
docs/static/gallery.html
# Protobuf generated files
*.pb.go
*pb2.py
*pb2_grpc.py
# SonarQube
.scannerwork
# backend virtual environments
**/venv
# per-developer customization files for the development container
.devcontainer/customization/*

3
.gitmodules vendored
View File

@@ -1,3 +1,6 @@
[submodule "docs/themes/hugo-theme-relearn"]
path = docs/themes/hugo-theme-relearn
url = https://github.com/McShelby/hugo-theme-relearn.git
[submodule "docs/themes/lotusdocs"]
path = docs/themes/lotusdocs
url = https://github.com/colinwilson/lotusdocs

View File

@@ -1,36 +0,0 @@
version: 2
before:
hooks:
- make protogen-go
- go mod tidy
dist: release
source:
enabled: true
name_template: '{{ .ProjectName }}-{{ .Tag }}-source'
builds:
- main: ./cmd/local-ai
env:
- CGO_ENABLED=0
ldflags:
- -s -w
- -X "github.com/mudler/LocalAI/internal.Version={{ .Tag }}"
- -X "github.com/mudler/LocalAI/internal.Commit={{ .FullCommit }}"
goos:
- linux
- darwin
#- windows
goarch:
- amd64
- arm64
ignore:
- goos: darwin
goarch: amd64
archives:
- formats: [ 'binary' ] # this removes the tar of the archives, leaving the binaries alone
name_template: local-ai-{{ .Tag }}-{{ .Os }}-{{ .Arch }}{{ if .Arm }}v{{ .Arm }}{{ end }}
checksum:
name_template: '{{ .ProjectName }}-{{ .Tag }}-checksums.txt'
snapshot:
version_template: "{{ .Tag }}-next"
changelog:
use: github-native

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

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

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@@ -1,79 +0,0 @@
# Build and testing
Building and testing the project depends on the components involved and the platform where development is taking place. Due to the amount of context required it's usually best not to try building or testing the project unless the user requests it. If you must build the project then inspect the Makefile in the project root and the Makefiles of any backends that are effected by changes you are making. In addition the workflows in .github/workflows can be used as a reference when it is unclear how to build or test a component. The primary Makefile contains targets for building inside or outside Docker, if the user has not previously specified a preference then ask which they would like to use.
# Coding style
- The project has the following .editorconfig
```
root = true
[*]
indent_style = space
indent_size = 2
end_of_line = lf
charset = utf-8
trim_trailing_whitespace = true
insert_final_newline = true
[*.go]
indent_style = tab
[Makefile]
indent_style = tab
[*.proto]
indent_size = 2
[*.py]
indent_size = 4
[*.js]
indent_size = 2
[*.yaml]
indent_size = 2
[*.md]
trim_trailing_whitespace = false
```
- Use comments sparingly to explain why code does something, not what it does. Comments are there to add context that would be difficult to deduce from reading the code.
- Prefer modern Go e.g. use `any` not `interface{}`
# Logging
Use `github.com/mudler/xlog` for logging which has the same API as slog.
# llama.cpp Backend
The llama.cpp backend (`backend/cpp/llama-cpp/grpc-server.cpp`) is a gRPC adaptation of the upstream HTTP server (`llama.cpp/tools/server/server.cpp`). It uses the same underlying server infrastructure from `llama.cpp/tools/server/server-context.cpp`.
## Building and Testing
- Test llama.cpp backend compilation: `make backends/llama-cpp`
- The backend is built as part of the main build process
- Check `backend/cpp/llama-cpp/Makefile` for build configuration
## Architecture
- **grpc-server.cpp**: gRPC server implementation, adapts HTTP server patterns to gRPC
- Uses shared server infrastructure: `server-context.cpp`, `server-task.cpp`, `server-queue.cpp`, `server-common.cpp`
- The gRPC server mirrors the HTTP server's functionality but uses gRPC instead of HTTP
## Common Issues When Updating llama.cpp
When fixing compilation errors after upstream changes:
1. Check how `server.cpp` (HTTP server) handles the same change
2. Look for new public APIs or getter methods
3. Store copies of needed data instead of accessing private members
4. Update function calls to match new signatures
5. Test with `make backends/llama-cpp`
## Key Differences from HTTP Server
- gRPC uses `BackendServiceImpl` class with gRPC service methods
- HTTP server uses `server_routes` with HTTP handlers
- Both use the same `server_context` and task queue infrastructure
- gRPC methods: `LoadModel`, `Predict`, `PredictStream`, `Embedding`, `Rerank`, `TokenizeString`, `GetMetrics`, `Health`

View File

@@ -1,4 +1,4 @@
# Contributing to LocalAI
# Contributing to localAI
Thank you for your interest in contributing to LocalAI! We appreciate your time and effort in helping to improve our project. Before you get started, please take a moment to review these guidelines.
@@ -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
@@ -27,10 +29,8 @@ Thank you for your interest in contributing to LocalAI! We appreciate your time
1. Clone the repository: `git clone https://github.com/go-skynet/LocalAI.git`
2. Navigate to the project directory: `cd LocalAI`
3. Install the required dependencies ( see https://localai.io/basics/build/#build-localai-locally )
4. Build LocalAI: `make build`
5. Run LocalAI: `./local-ai`
6. To Build and live reload: `make build-dev`
3. Install the required dependencies: `make prepare`
4. Run LocalAI: `make run`
## Contributing
@@ -53,33 +53,20 @@ 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
`make test` cannot handle all the model now. Please be sure to add a test case for the new features or the part was changed.
### Running AIO tests
All-In-One images has a set of tests that automatically verifies that most of the endpoints works correctly, a flow can be :
```bash
# Build the LocalAI docker image
make DOCKER_IMAGE=local-ai docker
# Build the corresponding AIO image
BASE_IMAGE=local-ai DOCKER_AIO_IMAGE=local-ai-aio:test make docker-aio
# Run the AIO e2e tests
LOCALAI_IMAGE_TAG=test LOCALAI_IMAGE=local-ai-aio make run-e2e-aio
```
## Documentation
We are welcome the contribution of the documents, please open new PR or create a new issue. The documentation is available under `docs/` https://github.com/mudler/LocalAI/tree/master/docs
- We are welcome the contribution of the documents, please open new PR in the official document repo [localai-website](https://github.com/go-skynet/localai-website)
## Community and Communication
- You can reach out via the Github issue tracker.
- Open a new discussion at [Discussion](https://github.com/go-skynet/LocalAI/discussions)
- Join the Discord channel [Discord](https://discord.gg/uJAeKSAGDy)
---

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@@ -1,342 +1,266 @@
ARG IMAGE_TYPE=extras
ARG BASE_IMAGE=ubuntu:22.04
ARG GRPC_BASE_IMAGE=${BASE_IMAGE}
ARG INTEL_BASE_IMAGE=${BASE_IMAGE}
FROM ${BASE_IMAGE} AS requirements
# extras or core
FROM ${BASE_IMAGE} as requirements-core
ENV DEBIAN_FRONTEND=noninteractive
RUN apt-get update && \
apt-get install -y --no-install-recommends \
ca-certificates curl wget espeak-ng libgomp1 \
ffmpeg && \
apt-get clean && \
rm -rf /var/lib/apt/lists/*
# The requirements-drivers target is for BUILD_TYPE specific items. If you need to install something specific to CUDA, or specific to ROCM, it goes here.
FROM requirements AS requirements-drivers
USER root
ARG GO_VERSION=1.21.7
ARG BUILD_TYPE
ARG CUDA_MAJOR_VERSION=12
ARG CUDA_MINOR_VERSION=0
ARG SKIP_DRIVERS=false
ARG CUDA_MAJOR_VERSION=11
ARG CUDA_MINOR_VERSION=7
ARG TARGETARCH
ARG TARGETVARIANT
ENV BUILD_TYPE=${BUILD_TYPE}
ARG UBUNTU_VERSION=2204
RUN mkdir -p /run/localai
RUN echo "default" > /run/localai/capability
# 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/* && \
echo "vulkan" > /run/localai/capability
fi
EOT
# CuBLAS requirements
RUN <<EOT bash
if ( [ "${BUILD_TYPE}" = "cublas" ] || [ "${BUILD_TYPE}" = "l4t" ] ) && [ "${SKIP_DRIVERS}" = "false" ]; then
apt-get update && \
apt-get install -y --no-install-recommends \
software-properties-common pciutils
if [ "amd64" = "$TARGETARCH" ]; then
curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu${UBUNTU_VERSION}/x86_64/cuda-keyring_1.1-1_all.deb
fi
if [ "arm64" = "$TARGETARCH" ]; then
if [ "${CUDA_MAJOR_VERSION}" = "13" ]; then
curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu${UBUNTU_VERSION}/sbsa/cuda-keyring_1.1-1_all.deb
else
curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu${UBUNTU_VERSION}/arm64/cuda-keyring_1.1-1_all.deb
fi
fi
dpkg -i cuda-keyring_1.1-1_all.deb && \
rm -f cuda-keyring_1.1-1_all.deb && \
apt-get update && \
apt-get install -y --no-install-recommends \
cuda-nvcc-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
libcufft-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
libcurand-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
libcublas-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
libcusparse-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
libcusolver-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION}
if [ "${CUDA_MAJOR_VERSION}" = "13" ] && [ "arm64" = "$TARGETARCH" ]; then
apt-get install -y --no-install-recommends \
libcufile-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} libcudnn9-cuda-${CUDA_MAJOR_VERSION} cuda-cupti-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} libnvjitlink-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION}
fi
apt-get clean && \
rm -rf /var/lib/apt/lists/* && \
echo "nvidia-cuda-${CUDA_MAJOR_VERSION}" > /run/localai/capability
fi
EOT
RUN <<EOT bash
if [ "${BUILD_TYPE}" = "cublas" ] && [ "${TARGETARCH}" = "arm64" ]; then
echo "nvidia-l4t-cuda-${CUDA_MAJOR_VERSION}" > /run/localai/capability
fi
EOT
# https://github.com/NVIDIA/Isaac-GR00T/issues/343
RUN <<EOT bash
if [ "${BUILD_TYPE}" = "cublas" ] && [ "${TARGETARCH}" = "arm64" ]; then
wget https://developer.download.nvidia.com/compute/cudss/0.6.0/local_installers/cudss-local-tegra-repo-ubuntu${UBUNTU_VERSION}-0.6.0_0.6.0-1_arm64.deb && \
dpkg -i cudss-local-tegra-repo-ubuntu${UBUNTU_VERSION}-0.6.0_0.6.0-1_arm64.deb && \
cp /var/cudss-local-tegra-repo-ubuntu${UBUNTU_VERSION}-0.6.0/cudss-*-keyring.gpg /usr/share/keyrings/ && \
apt-get update && apt-get -y install cudss cudss-cuda-${CUDA_MAJOR_VERSION} && \
wget https://developer.download.nvidia.com/compute/nvpl/25.5/local_installers/nvpl-local-repo-ubuntu${UBUNTU_VERSION}-25.5_1.0-1_arm64.deb && \
dpkg -i nvpl-local-repo-ubuntu${UBUNTU_VERSION}-25.5_1.0-1_arm64.deb && \
cp /var/nvpl-local-repo-ubuntu${UBUNTU_VERSION}-25.5/nvpl-*-keyring.gpg /usr/share/keyrings/ && \
apt-get update && apt-get install -y nvpl
fi
EOT
# If we are building with clblas support, we need the libraries for the builds
RUN if [ "${BUILD_TYPE}" = "clblas" ] && [ "${SKIP_DRIVERS}" = "false" ]; then \
apt-get update && \
apt-get install -y --no-install-recommends \
libclblast-dev && \
apt-get clean && \
rm -rf /var/lib/apt/lists/* \
; fi
RUN if [ "${BUILD_TYPE}" = "hipblas" ] && [ "${SKIP_DRIVERS}" = "false" ]; then \
apt-get update && \
apt-get install -y --no-install-recommends \
hipblas-dev \
rocblas-dev && \
apt-get clean && \
rm -rf /var/lib/apt/lists/* && \
echo "amd" > /run/localai/capability && \
# I have no idea why, but the ROCM lib packages don't trigger ldconfig after they install, which results in local-ai and others not being able
# to locate the libraries. We run ldconfig ourselves to work around this packaging deficiency
ldconfig \
; fi
RUN if [ "${BUILD_TYPE}" = "hipblas" ]; then \
ln -s /opt/rocm-**/lib/llvm/lib/libomp.so /usr/lib/libomp.so \
; fi
RUN expr "${BUILD_TYPE}" = intel && echo "intel" > /run/localai/capability || echo "not intel"
# Cuda
ENV PATH=/usr/local/cuda/bin:${PATH}
# HipBLAS requirements
ENV PATH=/opt/rocm/bin:${PATH}
###################################
###################################
# The requirements-core target is common to all images. It should not be placed in requirements-core unless every single build will use it.
FROM requirements-drivers AS build-requirements
ARG GO_VERSION=1.22.6
ARG CMAKE_VERSION=3.26.4
ARG CMAKE_FROM_SOURCE=false
ARG TARGETARCH
ARG TARGETVARIANT
ENV DEBIAN_FRONTEND=noninteractive
ENV EXTERNAL_GRPC_BACKENDS="coqui:/build/backend/python/coqui/run.sh,huggingface-embeddings:/build/backend/python/sentencetransformers/run.sh,petals:/build/backend/python/petals/run.sh,transformers:/build/backend/python/transformers/run.sh,sentencetransformers:/build/backend/python/sentencetransformers/run.sh,autogptq:/build/backend/python/autogptq/run.sh,bark:/build/backend/python/bark/run.sh,diffusers:/build/backend/python/diffusers/run.sh,exllama:/build/backend/python/exllama/run.sh,vall-e-x:/build/backend/python/vall-e-x/run.sh,vllm:/build/backend/python/vllm/run.sh,mamba:/build/backend/python/mamba/run.sh,exllama2:/build/backend/python/exllama2/run.sh,transformers-musicgen:/build/backend/python/transformers-musicgen/run.sh"
ARG GO_TAGS="stablediffusion tinydream tts"
RUN apt-get update && \
apt-get install -y --no-install-recommends \
build-essential \
ccache \
ca-certificates espeak-ng \
curl libssl-dev \
git \
git-lfs \
unzip upx-ucl python3 python-is-python3 && \
apt-get clean && \
rm -rf /var/lib/apt/lists/*
# Install CMake (the version in 22.04 is too old)
RUN <<EOT bash
if [ "${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-${CMAKE_VERSION} && ./configure && make && make install
else
apt-get update && \
apt-get install -y \
cmake && \
apt-get clean && \
rm -rf /var/lib/apt/lists/*
fi
EOT
apt-get install -y ca-certificates curl patch pip cmake git && apt-get clean
# Install Go
RUN curl -L -s https://go.dev/dl/go${GO_VERSION}.linux-${TARGETARCH}.tar.gz | tar -C /usr/local -xz
ENV PATH=$PATH:/root/go/bin:/usr/local/go/bin
# Install grpc compilers
RUN go install google.golang.org/protobuf/cmd/protoc-gen-go@v1.34.2 && \
go install google.golang.org/grpc/cmd/protoc-gen-go-grpc@1958fcbe2ca8bd93af633f11e97d44e567e945af
RUN curl -L -s https://go.dev/dl/go$GO_VERSION.linux-$TARGETARCH.tar.gz | tar -C /usr/local -xz
ENV PATH $PATH:/usr/local/go/bin
COPY --chmod=644 custom-ca-certs/* /usr/local/share/ca-certificates/
RUN update-ca-certificates
RUN test -n "$TARGETARCH" \
|| (echo 'warn: missing $TARGETARCH, either set this `ARG` manually, or run using `docker buildkit`')
# Use the variables in subsequent instructions
RUN echo "Target Architecture: $TARGETARCH"
RUN echo "Target Variant: $TARGETVARIANT"
# CuBLAS requirements
RUN if [ "${BUILD_TYPE}" = "cublas" ]; then \
apt-get install -y software-properties-common && \
curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64/cuda-keyring_1.1-1_all.deb && \
dpkg -i cuda-keyring_1.1-1_all.deb && \
rm -f cuda-keyring_1.1-1_all.deb && \
apt-get update && \
apt-get install -y cuda-nvcc-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} libcurand-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} libcublas-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} libcusparse-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} libcusolver-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} && apt-get clean \
; fi
# Cuda
ENV PATH /usr/local/cuda/bin:${PATH}
# HipBLAS requirements
ENV PATH /opt/rocm/bin:${PATH}
# OpenBLAS requirements and stable diffusion
RUN apt-get install -y \
libopenblas-dev \
libopencv-dev \
&& apt-get clean
# Set up OpenCV
RUN ln -s /usr/include/opencv4/opencv2 /usr/include/opencv2
WORKDIR /build
RUN test -n "$TARGETARCH" \
|| (echo 'warn: missing $TARGETARCH, either set this `ARG` manually, or run using `docker buildkit`')
###################################
###################################
# Temporary workaround for Intel's repository to work correctly
# https://community.intel.com/t5/Intel-oneAPI-Math-Kernel-Library/APT-Repository-not-working-signatures-invalid/m-p/1599436/highlight/true#M36143
# This is a temporary workaround until Intel fixes their repository
FROM ${INTEL_BASE_IMAGE} AS intel
RUN wget -qO - https://repositories.intel.com/gpu/intel-graphics.key | \
gpg --yes --dearmor --output /usr/share/keyrings/intel-graphics.gpg
RUN echo "deb [arch=amd64 signed-by=/usr/share/keyrings/intel-graphics.gpg] https://repositories.intel.com/gpu/ubuntu jammy/lts/2350 unified" > /etc/apt/sources.list.d/intel-graphics.list
FROM requirements-core as requirements-extras
RUN curl https://repo.anaconda.com/pkgs/misc/gpgkeys/anaconda.asc | gpg --dearmor > conda.gpg && \
install -o root -g root -m 644 conda.gpg /usr/share/keyrings/conda-archive-keyring.gpg && \
gpg --keyring /usr/share/keyrings/conda-archive-keyring.gpg --no-default-keyring --fingerprint 34161F5BF5EB1D4BFBBB8F0A8AEB4F8B29D82806 && \
echo "deb [arch=amd64 signed-by=/usr/share/keyrings/conda-archive-keyring.gpg] https://repo.anaconda.com/pkgs/misc/debrepo/conda stable main" > /etc/apt/sources.list.d/conda.list && \
echo "deb [arch=amd64 signed-by=/usr/share/keyrings/conda-archive-keyring.gpg] https://repo.anaconda.com/pkgs/misc/debrepo/conda stable main" | tee -a /etc/apt/sources.list.d/conda.list && \
apt-get update && \
apt-get install -y conda && apt-get clean
ENV PATH="/root/.cargo/bin:${PATH}"
RUN apt-get install -y python3-pip && apt-get clean
RUN pip install --upgrade pip
RUN curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh -s -- -y
RUN apt-get install -y espeak-ng espeak && apt-get clean
RUN if [ ! -e /usr/bin/python ]; then \
ln -s /usr/bin/python3 /usr/bin/python \
; fi
###################################
###################################
FROM ${BASE_IMAGE} as grpc
ARG MAKEFLAGS
ARG GRPC_VERSION=v1.58.0
ENV MAKEFLAGS=${MAKEFLAGS}
WORKDIR /build
RUN apt-get update && \
apt-get install -y --no-install-recommends \
intel-oneapi-runtime-libs && \
apt-get install -y g++ cmake git && \
apt-get clean && \
rm -rf /var/lib/apt/lists/*
RUN git clone --recurse-submodules --jobs 4 -b ${GRPC_VERSION} --depth 1 --shallow-submodules https://github.com/grpc/grpc
RUN cd grpc && \
mkdir -p cmake/build && \
cd cmake/build && \
cmake -DgRPC_INSTALL=ON -DgRPC_BUILD_TESTS=OFF ../.. && \
make
###################################
###################################
# The builder-base target has the arguments, variables, and copies shared between full builder images and the uncompiled devcontainer
FROM requirements-${IMAGE_TYPE} as builder
FROM build-requirements AS builder-base
ARG GO_TAGS=""
ARG GO_TAGS="stablediffusion tts"
ARG GRPC_BACKENDS
ARG MAKEFLAGS
ARG LD_FLAGS="-s -w"
ARG TARGETARCH
ARG TARGETVARIANT
ENV GRPC_BACKENDS=${GRPC_BACKENDS}
ENV GO_TAGS=${GO_TAGS}
ENV MAKEFLAGS=${MAKEFLAGS}
ENV NVIDIA_DRIVER_CAPABILITIES=compute,utility
ENV NVIDIA_REQUIRE_CUDA="cuda>=${CUDA_MAJOR_VERSION}.0"
ENV NVIDIA_VISIBLE_DEVICES=all
ENV LD_FLAGS=${LD_FLAGS}
RUN echo "GO_TAGS: $GO_TAGS" && echo "TARGETARCH: $TARGETARCH"
WORKDIR /build
# We need protoc installed, and the version in 22.04 is too old.
RUN <<EOT bash
if [ "amd64" = "$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
###################################
###################################
# Compile backends first in a separate stage
FROM builder-base AS builder-backends
ARG TARGETARCH
ARG TARGETVARIANT
WORKDIR /build
COPY ./Makefile .
COPY ./backend ./backend
COPY ./go.mod .
COPY ./go.sum .
COPY ./.git ./.git
# Some of the Go backends use libs from the main src, we could further optimize the caching by building the CPP backends before here
COPY ./pkg/grpc ./pkg/grpc
COPY ./pkg/utils ./pkg/utils
COPY ./pkg/langchain ./pkg/langchain
RUN ls -l ./
RUN make protogen-go
# 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-backends AS builder
WORKDIR /build
COPY . .
COPY .git .
RUN echo "GO_TAGS: $GO_TAGS"
RUN make prepare
## Build the binary
## If we're on arm64 AND using cublas/hipblas, skip some of the llama-compat backends to save space
## Otherwise just run the normal build
# If we are building with clblas support, we need the libraries for the builds
RUN if [ "${BUILD_TYPE}" = "clblas" ]; then \
apt-get update && \
apt-get install -y libclblast-dev && \
apt-get clean \
; fi
# stablediffusion does not tolerate a newer version of abseil, build it first
RUN GRPC_BACKENDS=backend-assets/grpc/stablediffusion make build
COPY --from=grpc /build/grpc ./grpc/
RUN cd /build/grpc/cmake/build && make install
# Rebuild with defaults backends
RUN make build
###################################
###################################
# 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
COPY .devcontainer-scripts /.devcontainer-scripts
RUN apt-get update && \
apt-get install -y --no-install-recommends \
ssh less
# 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
RUN if [ ! -d "/build/sources/go-piper/piper-phonemize/pi/lib/" ]; then \
mkdir -p /build/sources/go-piper/piper-phonemize/pi/lib/ \
touch /build/sources/go-piper/piper-phonemize/pi/lib/keep \
; fi
###################################
###################################
# This is the final target. The result of this target will be the image uploaded to the registry.
# If you cannot find a more suitable place for an addition, this layer is a suitable place for it.
FROM requirements-drivers
FROM requirements-${IMAGE_TYPE}
ARG FFMPEG
ARG BUILD_TYPE
ARG TARGETARCH
ARG IMAGE_TYPE=extras
ARG MAKEFLAGS
ENV BUILD_TYPE=${BUILD_TYPE}
ENV REBUILD=false
ENV HEALTHCHECK_ENDPOINT=http://localhost:8080/readyz
ENV MAKEFLAGS=${MAKEFLAGS}
ARG CUDA_MAJOR_VERSION=12
ARG CUDA_MAJOR_VERSION=11
ENV NVIDIA_DRIVER_CAPABILITIES=compute,utility
ENV NVIDIA_REQUIRE_CUDA="cuda>=${CUDA_MAJOR_VERSION}.0"
ENV NVIDIA_VISIBLE_DEVICES=all
ENV PIP_CACHE_PURGE=true
WORKDIR /
# Add FFmpeg
RUN if [ "${FFMPEG}" = "true" ]; then \
apt-get install -y ffmpeg && apt-get clean \
; fi
COPY ./entrypoint.sh .
# Add OpenCL
RUN if [ "${BUILD_TYPE}" = "clblas" ]; then \
apt-get update && \
apt-get install -y libclblast1 && \
apt-get clean \
; fi
WORKDIR /build
# we start fresh & re-copy all assets because `make build` does not clean up nicely after itself
# so when `entrypoint.sh` runs `make build` again (which it does by default), the build would fail
# see https://github.com/go-skynet/LocalAI/pull/658#discussion_r1241971626 and
# https://github.com/go-skynet/LocalAI/pull/434
COPY . .
COPY --from=builder /build/sources ./sources/
COPY --from=grpc /build/grpc ./grpc/
RUN make prepare-sources && cd /build/grpc/cmake/build && make install && rm -rf grpc
# Copy the binary
COPY --from=builder /build/local-ai ./
# Copy shared libraries for piper
COPY --from=builder /build/sources/go-piper/piper-phonemize/pi/lib/* /usr/lib/
# do not let stablediffusion rebuild (requires an older version of absl)
COPY --from=builder /build/backend-assets/grpc/stablediffusion ./backend-assets/grpc/stablediffusion
## Duplicated from Makefile to avoid having a big layer that's hard to push
RUN if [ "${IMAGE_TYPE}" = "extras" ]; then \
make -C backend/python/autogptq \
; fi
RUN if [ "${IMAGE_TYPE}" = "extras" ]; then \
make -C backend/python/bark \
; fi
RUN if [ "${IMAGE_TYPE}" = "extras" ]; then \
make -C backend/python/diffusers \
; fi
RUN if [ "${IMAGE_TYPE}" = "extras" ]; then \
make -C backend/python/vllm \
; fi
RUN if [ "${IMAGE_TYPE}" = "extras" ]; then \
make -C backend/python/mamba \
; fi
RUN if [ "${IMAGE_TYPE}" = "extras" ]; then \
make -C backend/python/sentencetransformers \
; fi
RUN if [ "${IMAGE_TYPE}" = "extras" ]; then \
make -C backend/python/transformers \
; fi
RUN if [ "${IMAGE_TYPE}" = "extras" ]; then \
make -C backend/python/vall-e-x \
; fi
RUN if [ "${IMAGE_TYPE}" = "extras" ]; then \
make -C backend/python/exllama \
; fi
RUN if [ "${IMAGE_TYPE}" = "extras" ]; then \
make -C backend/python/exllama2 \
; fi
RUN if [ "${IMAGE_TYPE}" = "extras" ]; then \
make -C backend/python/petals \
; fi
RUN if [ "${IMAGE_TYPE}" = "extras" ]; then \
make -C backend/python/transformers-musicgen \
; fi
RUN if [ "${IMAGE_TYPE}" = "extras" ]; then \
make -C backend/python/coqui \
; fi
# Make sure the models directory exists
RUN mkdir -p /models /backends
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 /models /backends /configuration
CMD curl -f $HEALTHCHECK_ENDPOINT || exit 1
VOLUME /build/models
EXPOSE 8080
ENTRYPOINT [ "/entrypoint.sh" ]
ENTRYPOINT [ "/build/entrypoint.sh" ]

5
Earthfile Normal file
View File

@@ -0,0 +1,5 @@
VERSION 0.7
build:
FROM DOCKERFILE -f Dockerfile .
SAVE ARTIFACT /usr/bin/local-ai AS LOCAL local-ai

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

830
Makefile
View File

@@ -2,18 +2,43 @@ GOCMD=go
GOTEST=$(GOCMD) test
GOVET=$(GOCMD) vet
BINARY_NAME=local-ai
LAUNCHER_BINARY_NAME=local-ai-launcher
CUDA_MAJOR_VERSION?=13
CUDA_MINOR_VERSION?=0
# llama.cpp versions
GOLLAMA_STABLE_VERSION?=2b57a8ae43e4699d3dc5d1496a1ccd42922993be
CPPLLAMA_VERSION?=1b67731e184e27a465b8c5476061294a4af668ea
GORELEASER?=
# 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_CPP_VERSION?=8f253ef3af1c62c04316ba4afa7145fc4d701a8c
# bert.cpp version
BERT_VERSION?=6abe312cded14042f6b7c3cd8edf082713334a4d
# go-piper version
PIPER_VERSION?=9d0100873a7dbb0824dfea40e8cec70a1b110759
# stablediffusion version
STABLEDIFFUSION_VERSION?=362df9da29f882dbf09ade61972d16a1f53c3485
# tinydream version
TINYDREAM_VERSION?=22a12a4bc0ac5455856f28f3b771331a551a4293
export BUILD_TYPE?=
export STABLE_BUILD_TYPE?=$(BUILD_TYPE)
export CMAKE_ARGS?=
CGO_LDFLAGS?=
CGO_LDFLAGS_WHISPER?=
CUDA_LIBPATH?=/usr/local/cuda/lib64/
GO_TAGS?=
BUILD_ID?=
NATIVE?=false
BUILD_ID?=git
TEST_DIR=/tmp/test
@@ -23,13 +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)
@@ -45,181 +70,340 @@ UNAME_S := $(shell uname -s)
endif
ifeq ($(OS),Darwin)
ifeq ($(OSX_SIGNING_IDENTITY),)
OSX_SIGNING_IDENTITY := $(shell security find-identity -v -p codesigning | grep '"' | head -n 1 | sed -E 's/.*"(.*)"/\1/')
endif
# on OSX, if BUILD_TYPE is blank, we should default to use Metal
ifeq ($(BUILD_TYPE),)
BUILD_TYPE=metal
# disable metal if on Darwin and any other value is explicitly passed.
else ifneq ($(BUILD_TYPE),metal)
CMAKE_ARGS+=-DLLAMA_METAL=OFF
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
endif
# check if goreleaser exists
ifeq (, $(shell which goreleaser))
GORELEASER=curl -sfL https://goreleaser.com/static/run | bash -s --
else
GORELEASER=$(shell which goreleaser)
ifeq ($(BUILD_TYPE),openblas)
CGO_LDFLAGS+=-lopenblas
export WHISPER_OPENBLAS=1
endif
ifeq ($(BUILD_TYPE),cublas)
CGO_LDFLAGS+=-lcublas -lcudart -L$(CUDA_LIBPATH)
export LLAMA_CUBLAS=1
export WHISPER_CUBLAS=1
CGO_LDFLAGS_WHISPER+=-L$(CUDA_LIBPATH)/stubs/ -lcuda
endif
ifeq ($(BUILD_TYPE),hipblas)
ROCM_HOME ?= /opt/rocm
ROCM_PATH ?= /opt/rocm
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 WHISPER_HIPBLAS=1
GPU_TARGETS ?= gfx900,gfx90a,gfx1030,gfx1031,gfx1100
AMDGPU_TARGETS ?= "$(GPU_TARGETS)"
CMAKE_ARGS+=-DLLAMA_HIPBLAS=ON -DAMDGPU_TARGETS="$(AMDGPU_TARGETS)" -DGPU_TARGETS="$(GPU_TARGETS)"
CGO_LDFLAGS += -O3 --rtlib=compiler-rt -unwindlib=libgcc -lhipblas -lrocblas --hip-link -L${ROCM_HOME}/lib/llvm/lib
endif
ifeq ($(BUILD_TYPE),metal)
CGO_LDFLAGS+=-framework Foundation -framework Metal -framework MetalKit -framework MetalPerformanceShaders
export LLAMA_METAL=1
export WHISPER_METAL=1
endif
ifeq ($(BUILD_TYPE),clblas)
CGO_LDFLAGS+=-lOpenCL -lclblast
export WHISPER_CLBLAST=1
endif
# glibc-static or glibc-devel-static required
ifeq ($(STATIC),true)
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)
# OPTIONAL_TARGETS+=go-piper/libpiper_binding.a
# OPTIONAL_TARGETS+=backend-assets/espeak-ng-data
PIPER_CGO_CXXFLAGS+=-I$(CURDIR)/sources/go-piper/piper/src/cpp -I$(CURDIR)/sources/go-piper/piper/build/fi/include -I$(CURDIR)/sources/go-piper/piper/build/pi/include -I$(CURDIR)/sources/go-piper/piper/build/si/include
PIPER_CGO_LDFLAGS+=-L$(CURDIR)/sources/go-piper/piper/build/fi/lib -L$(CURDIR)/sources/go-piper/piper/build/pi/lib -L$(CURDIR)/sources/go-piper/piper/build/si/lib -lfmt -lspdlog -lucd
OPTIONAL_GRPC+=backend-assets/grpc/piper
endif
ALL_GRPC_BACKENDS=backend-assets/grpc/langchain-huggingface
ALL_GRPC_BACKENDS+=backend-assets/grpc/bert-embeddings
ALL_GRPC_BACKENDS+=backend-assets/grpc/llama-cpp
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
ALL_GRPC_BACKENDS+=backend-assets/grpc/local-store
ALL_GRPC_BACKENDS+=$(OPTIONAL_GRPC)
GRPC_BACKENDS?=$(ALL_GRPC_BACKENDS) $(OPTIONAL_GRPC)
TEST_PATHS?=./api/... ./pkg/... ./core/...
# If empty, then we build all
ifeq ($(GRPC_BACKENDS),)
GRPC_BACKENDS=$(ALL_GRPC_BACKENDS)
endif
.PHONY: all test build vendor
ifeq ($(BUILD_API_ONLY),true)
GRPC_BACKENDS=
endif
.PHONY: all test build vendor get-sources prepare-sources prepare
all: help
## BERT embeddings
sources/go-bert:
git clone --recurse-submodules https://github.com/go-skynet/go-bert.cpp sources/go-bert
cd sources/go-bert && git checkout -b build $(BERT_VERSION) && git submodule update --init --recursive --depth 1
sources/go-bert/libgobert.a: sources/go-bert
$(MAKE) -C sources/go-bert libgobert.a
## go-llama-ggml
sources/go-llama-ggml:
git clone --recurse-submodules https://github.com/go-skynet/go-llama.cpp sources/go-llama-ggml
cd sources/go-llama-ggml && git checkout -b build $(GOLLAMA_STABLE_VERSION) && git submodule update --init --recursive --depth 1
sources/go-llama-ggml/libbinding.a: sources/go-llama-ggml
$(MAKE) -C sources/go-llama-ggml BUILD_TYPE=$(STABLE_BUILD_TYPE) libbinding.a
## go-piper
sources/go-piper:
git clone --recurse-submodules https://github.com/mudler/go-piper sources/go-piper
cd sources/go-piper && git checkout -b build $(PIPER_VERSION) && git submodule update --init --recursive --depth 1
sources/go-piper/libpiper_binding.a: sources/go-piper
$(MAKE) -C sources/go-piper libpiper_binding.a example/main piper.o
## 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
sources/gpt4all/gpt4all-bindings/golang/libgpt4all.a: sources/gpt4all
$(MAKE) -C sources/gpt4all/gpt4all-bindings/golang/ libgpt4all.a
## RWKV
sources/go-rwkv:
git clone --recurse-submodules $(RWKV_REPO) sources/go-rwkv
cd sources/go-rwkv && git checkout -b build $(RWKV_VERSION) && git submodule update --init --recursive --depth 1
sources/go-rwkv/librwkv.a: sources/go-rwkv
cd sources/go-rwkv && cd rwkv.cpp && cmake . -DRWKV_BUILD_SHARED_LIBRARY=OFF && cmake --build . && cp librwkv.a ..
## 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:
git clone https://github.com/ggerganov/whisper.cpp.git sources/whisper.cpp
cd sources/whisper.cpp && git checkout -b build $(WHISPER_CPP_VERSION) && git submodule update --init --recursive --depth 1
sources/whisper.cpp/libwhisper.a: sources/whisper.cpp
cd sources/whisper.cpp && make libwhisper.a
get-sources: sources/go-llama-ggml sources/gpt4all sources/go-piper sources/go-rwkv sources/whisper.cpp sources/go-bert sources/go-stable-diffusion sources/go-tiny-dream
replace:
$(GOCMD) mod edit -replace github.com/donomii/go-rwkv.cpp=$(CURDIR)/sources/go-rwkv
$(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
$(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
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
## GENERIC
rebuild: ## Rebuilds the project
$(GOCMD) clean -cache
$(MAKE) -C sources/go-llama-ggml clean
$(MAKE) -C sources/gpt4all/gpt4all-bindings/golang/ clean
$(MAKE) -C sources/go-rwkv clean
$(MAKE) -C sources/whisper.cpp clean
$(MAKE) -C sources/go-stable-diffusion clean
$(MAKE) -C sources/go-bert clean
$(MAKE) -C sources/go-piper clean
$(MAKE) -C sources/go-tiny-dream clean
$(MAKE) build
prepare: prepare-sources $(OPTIONAL_TARGETS)
clean: ## Remove build related file
$(GOCMD) clean -cache
rm -f prepare
rm -rf ./sources
rm -rf $(BINARY_NAME)
rm -rf release/
$(MAKE) protogen-clean
rmdir pkg/grpc/proto || true
rm -rf backend-assets
$(MAKE) -C backend/cpp/grpc clean
$(MAKE) -C backend/cpp/llama clean
$(MAKE) dropreplace
clean-tests:
rm -rf test-models
rm -rf test-dir
## Install Go tools
install-go-tools:
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
rm -rf core/http/backend-assets
## Build:
build: protogen-go install-go-tools ## Build the project
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})
rm -rf $(BINARY_NAME) || true
CGO_LDFLAGS="$(CGO_LDFLAGS)" $(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o $(BINARY_NAME) ./cmd/local-ai
CGO_LDFLAGS="$(CGO_LDFLAGS)" $(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o $(BINARY_NAME) ./
build-launcher: ## Build the launcher application
$(info ${GREEN}I local-ai launcher 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})
rm -rf $(LAUNCHER_BINARY_NAME) || true
CGO_LDFLAGS="$(CGO_LDFLAGS)" $(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o $(LAUNCHER_BINARY_NAME) ./cmd/launcher
build-minimal:
BUILD_GRPC_FOR_BACKEND_LLAMA=true GRPC_BACKENDS=backend-assets/grpc/llama-cpp GO_TAGS=none $(MAKE) build
build-all: build build-launcher ## Build both server and launcher
build-api:
BUILD_GRPC_FOR_BACKEND_LLAMA=true BUILD_API_ONLY=true GO_TAGS=none $(MAKE) build
build-dev: ## Run LocalAI in dev mode with live reload
@command -v air >/dev/null 2>&1 || go install github.com/air-verse/air@latest
air -c .air.toml
dev-dist:
$(GORELEASER) build --snapshot --clean
dist:
$(GORELEASER) build --clean
dist: build
mkdir -p release
cp $(BINARY_NAME) release/$(BINARY_NAME)-$(BUILD_ID)-$(OS)-$(ARCH)
osx-signed: build
codesign --deep --force --sign "$(OSX_SIGNING_IDENTITY)" --entitlements "./Entitlements.plist" "./$(BINARY_NAME)"
## Run
run: ## run local-ai
run: prepare ## run local-ai
CGO_LDFLAGS="$(CGO_LDFLAGS)" $(GOCMD) run ./
test-models/testmodel.ggml:
mkdir -p test-models
mkdir -p test-dir
wget -q https://huggingface.co/mradermacher/gpt2-alpaca-gpt4-GGUF/resolve/main/gpt2-alpaca-gpt4.Q4_K_M.gguf -O test-models/testmodel.ggml
mkdir test-models
mkdir test-dir
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: protogen-go
prepare-test: grpcs
cp -rf backend-assets core/http
cp tests/models_fixtures/* test-models
########################################################
## Tests
########################################################
## Test targets
test: test-models/testmodel.ggml protogen-go
test: prepare test-models/testmodel.ggml grpcs
@echo 'Running tests'
export GO_TAGS="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 BACKENDS_PATH=$(abspath ./)/backends \
$(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
########################################################
## AIO tests
########################################################
docker-build-aio:
docker build --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
e2e-aio:
LOCALAI_BACKEND_DIR=$(abspath ./backends) \
LOCALAI_MODELS_DIR=$(abspath ./models) \
LOCALAI_IMAGE_TAG=test \
LOCALAI_IMAGE=local-ai-aio \
$(MAKE) run-e2e-aio
run-e2e-aio: protogen-go
@echo 'Running e2e AIO tests'
$(GOCMD) run github.com/onsi/ginkgo/v2/ginkgo --flake-attempts $(TEST_FLAKES) -v -r ./tests/e2e-aio
########################################################
## E2E tests
########################################################
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 IMAGE_TYPE=core --build-arg BUILD_TYPE=$(BUILD_TYPE) --build-arg CUDA_MAJOR_VERSION=12 --build-arg CUDA_MINOR_VERSION=0 -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:
@echo 'Running e2e AIO tests'
$(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)
########################################################
## Integration and unit 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=$(abspath ./)/test-models BACKENDS_PATH=$(abspath ./)/backends \
$(GOCMD) run github.com/onsi/ginkgo/v2/ginkgo --label-filter="llama-gguf" --flake-attempts $(TEST_FLAKES) -v -r $(TEST_PATHS)
TEST_DIR=$(abspath ./)/test-dir/ FIXTURES=$(abspath ./)/tests/fixtures CONFIG_FILE=$(abspath ./)/test-models/config.yaml MODELS_PATH=$(abspath ./)/test-models \
$(GOCMD) run github.com/onsi/ginkgo/v2/ginkgo --label-filter="llama-gguf" --flake-attempts 5 -v -r $(TEST_PATHS)
test-tts: prepare-test
TEST_DIR=$(abspath ./)/test-dir/ FIXTURES=$(abspath ./)/tests/fixtures CONFIG_FILE=$(abspath ./)/test-models/config.yaml MODELS_PATH=$(abspath ./)/test-models BACKENDS_PATH=$(abspath ./)/backends \
$(GOCMD) run github.com/onsi/ginkgo/v2/ginkgo --label-filter="tts" --flake-attempts $(TEST_FLAKES) -v -r $(TEST_PATHS)
TEST_DIR=$(abspath ./)/test-dir/ FIXTURES=$(abspath ./)/tests/fixtures CONFIG_FILE=$(abspath ./)/test-models/config.yaml MODELS_PATH=$(abspath ./)/test-models \
$(GOCMD) run github.com/onsi/ginkgo/v2/ginkgo --label-filter="tts" --flake-attempts 1 -v -r $(TEST_PATHS)
test-stablediffusion: prepare-test
TEST_DIR=$(abspath ./)/test-dir/ FIXTURES=$(abspath ./)/tests/fixtures CONFIG_FILE=$(abspath ./)/test-models/config.yaml MODELS_PATH=$(abspath ./)/test-models BACKENDS_PATH=$(abspath ./)/backends \
$(GOCMD) run github.com/onsi/ginkgo/v2/ginkgo --label-filter="stablediffusion" --flake-attempts $(TEST_FLAKES) -v -r $(TEST_PATHS)
TEST_DIR=$(abspath ./)/test-dir/ FIXTURES=$(abspath ./)/tests/fixtures CONFIG_FILE=$(abspath ./)/test-models/config.yaml MODELS_PATH=$(abspath ./)/test-models \
$(GOCMD) run github.com/onsi/ginkgo/v2/ginkgo --label-filter="stablediffusion" --flake-attempts 1 -v -r $(TEST_PATHS)
test-stores:
$(GOCMD) run github.com/onsi/ginkgo/v2/ginkgo --label-filter="stores" --flake-attempts $(TEST_FLAKES) -v -r tests/integration
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 1 -v -r tests/integration
test-container:
docker build --target requirements -t local-ai-test-container .
docker run -ti --rm --entrypoint /bin/bash -ti -v $(abspath ./):/build local-ai-test-container
########################################################
## Help
########################################################
## Help:
help: ## Show this help.
@echo ''
@@ -232,69 +416,143 @@ help: ## Show this help.
else if (/^## .*$$/) {printf " ${CYAN}%s${RESET}\n", substr($$1,4)} \
}' $(MAKEFILE_LIST)
########################################################
## Backends
########################################################
protogen: protogen-go protogen-python
.PHONY: protogen
protogen: protogen-go
protoc:
@OS_NAME=$$(uname -s | tr '[:upper:]' '[:lower:]'); \
ARCH_NAME=$$(uname -m); \
if [ "$$OS_NAME" = "darwin" ]; then \
if [ "$$ARCH_NAME" = "arm64" ]; then \
FILE=protoc-31.1-osx-aarch_64.zip; \
elif [ "$$ARCH_NAME" = "x86_64" ]; then \
FILE=protoc-31.1-osx-x86_64.zip; \
else \
echo "Unsupported macOS architecture: $$ARCH_NAME"; exit 1; \
fi; \
elif [ "$$OS_NAME" = "linux" ]; then \
if [ "$$ARCH_NAME" = "x86_64" ]; then \
FILE=protoc-31.1-linux-x86_64.zip; \
elif [ "$$ARCH_NAME" = "aarch64" ] || [ "$$ARCH_NAME" = "arm64" ]; then \
FILE=protoc-31.1-linux-aarch_64.zip; \
elif [ "$$ARCH_NAME" = "ppc64le" ]; then \
FILE=protoc-31.1-linux-ppcle_64.zip; \
elif [ "$$ARCH_NAME" = "s390x" ]; then \
FILE=protoc-31.1-linux-s390_64.zip; \
elif [ "$$ARCH_NAME" = "i386" ] || [ "$$ARCH_NAME" = "x86" ]; then \
FILE=protoc-31.1-linux-x86_32.zip; \
else \
echo "Unsupported Linux architecture: $$ARCH_NAME"; exit 1; \
fi; \
else \
echo "Unsupported OS: $$OS_NAME"; exit 1; \
fi; \
URL=https://github.com/protocolbuffers/protobuf/releases/download/v31.1/$$FILE; \
curl -L $$URL -o protoc.zip && \
unzip -j -d $(CURDIR) protoc.zip bin/protoc && rm protoc.zip
.PHONY: protogen-go
protogen-go: protoc install-go-tools
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 \
protogen-go:
protoc -Ibackend/ --go_out=pkg/grpc/proto/ --go_opt=paths=source_relative --go-grpc_out=pkg/grpc/proto/ --go-grpc_opt=paths=source_relative \
backend/backend.proto
.PHONY: protogen-go-clean
protogen-go-clean:
$(RM) pkg/grpc/proto/backend.pb.go pkg/grpc/proto/backend_grpc.pb.go
$(RM) bin/*
protogen-python:
python3 -m grpc_tools.protoc -Ibackend/ --python_out=backend/python/sentencetransformers/ --grpc_python_out=backend/python/sentencetransformers/ backend/backend.proto
python3 -m grpc_tools.protoc -Ibackend/ --python_out=backend/python/transformers/ --grpc_python_out=backend/python/transformers/ backend/backend.proto
python3 -m grpc_tools.protoc -Ibackend/ --python_out=backend/python/transformers-musicgen/ --grpc_python_out=backend/python/transformers-musicgen/ backend/backend.proto
python3 -m grpc_tools.protoc -Ibackend/ --python_out=backend/python/autogptq/ --grpc_python_out=backend/python/autogptq/ backend/backend.proto
python3 -m grpc_tools.protoc -Ibackend/ --python_out=backend/python/exllama/ --grpc_python_out=backend/python/exllama/ backend/backend.proto
python3 -m grpc_tools.protoc -Ibackend/ --python_out=backend/python/bark/ --grpc_python_out=backend/python/bark/ backend/backend.proto
python3 -m grpc_tools.protoc -Ibackend/ --python_out=backend/python/diffusers/ --grpc_python_out=backend/python/diffusers/ backend/backend.proto
python3 -m grpc_tools.protoc -Ibackend/ --python_out=backend/python/coqui/ --grpc_python_out=backend/python/coqui/ backend/backend.proto
python3 -m grpc_tools.protoc -Ibackend/ --python_out=backend/python/vall-e-x/ --grpc_python_out=backend/python/vall-e-x/ backend/backend.proto
python3 -m grpc_tools.protoc -Ibackend/ --python_out=backend/python/vllm/ --grpc_python_out=backend/python/vllm/ backend/backend.proto
python3 -m grpc_tools.protoc -Ibackend/ --python_out=backend/python/petals/ --grpc_python_out=backend/python/petals/ backend/backend.proto
python3 -m grpc_tools.protoc -Ibackend/ --python_out=backend/python/mamba/ --grpc_python_out=backend/python/mamba/ backend/backend.proto
python3 -m grpc_tools.protoc -Ibackend/ --python_out=backend/python/exllama2/ --grpc_python_out=backend/python/exllama2/ backend/backend.proto
prepare-test-extra: protogen-python
## GRPC
# Note: it is duplicated in the Dockerfile
prepare-extra-conda-environments:
$(MAKE) -C backend/python/autogptq
$(MAKE) -C backend/python/bark
$(MAKE) -C backend/python/coqui
$(MAKE) -C backend/python/diffusers
$(MAKE) -C backend/python/vllm
$(MAKE) -C backend/python/mamba
$(MAKE) -C backend/python/sentencetransformers
$(MAKE) -C backend/python/transformers
$(MAKE) -C backend/python/transformers-musicgen
$(MAKE) -C backend/python/vall-e-x
$(MAKE) -C backend/python/exllama
$(MAKE) -C backend/python/petals
$(MAKE) -C backend/python/exllama2
prepare-test-extra:
$(MAKE) -C backend/python/transformers
$(MAKE) -C backend/python/diffusers
$(MAKE) -C backend/python/chatterbox
$(MAKE) -C backend/python/vllm
$(MAKE) -C backend/python/vibevoice
test-extra: prepare-test-extra
$(MAKE) -C backend/python/transformers test
$(MAKE) -C backend/python/diffusers test
$(MAKE) -C backend/python/chatterbox test
$(MAKE) -C backend/python/vllm test
$(MAKE) -C backend/python/vibevoice test
backend-assets:
mkdir -p backend-assets
ifeq ($(BUILD_API_ONLY),true)
touch backend-assets/keep
endif
backend-assets/espeak-ng-data: sources/go-piper sources/go-piper/libpiper_binding.a
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: replace
mkdir -p backend-assets/grpc
backend-assets/grpc/bert-embeddings: sources/go-bert sources/go-bert/libgobert.a backend-assets/grpc
CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(CURDIR)/sources/go-bert LIBRARY_PATH=$(CURDIR)/sources/go-bert \
$(GOCMD) build -ldflags "$(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/langchain-huggingface: backend-assets/grpc
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/langchain-huggingface ./backend/go/llm/langchain/
backend/cpp/llama/llama.cpp:
LLAMA_VERSION=$(CPPLLAMA_VERSION) $(MAKE) -C backend/cpp/llama llama.cpp
INSTALLED_PACKAGES=$(CURDIR)/backend/cpp/grpc/installed_packages
INSTALLED_LIB_CMAKE=$(INSTALLED_PACKAGES)/lib/cmake
ADDED_CMAKE_ARGS=-Dabsl_DIR=${INSTALLED_LIB_CMAKE}/absl \
-DProtobuf_DIR=${INSTALLED_LIB_CMAKE}/protobuf \
-Dutf8_range_DIR=${INSTALLED_LIB_CMAKE}/utf8_range \
-DgRPC_DIR=${INSTALLED_LIB_CMAKE}/grpc \
-DCMAKE_CXX_STANDARD_INCLUDE_DIRECTORIES=${INSTALLED_PACKAGES}/include
backend/cpp/llama/grpc-server:
# Conditionally build grpc for the llama backend to use if needed
ifdef BUILD_GRPC_FOR_BACKEND_LLAMA
$(MAKE) -C backend/cpp/grpc build
_PROTOBUF_PROTOC=${INSTALLED_PACKAGES}/bin/proto \
_GRPC_CPP_PLUGIN_EXECUTABLE=${INSTALLED_PACKAGES}/bin/grpc_cpp_plugin \
PATH="${INSTALLED_PACKAGES}/bin:${PATH}" \
CMAKE_ARGS="${CMAKE_ARGS} ${ADDED_CMAKE_ARGS}" \
LLAMA_VERSION=$(CPPLLAMA_VERSION) \
$(MAKE) -C backend/cpp/llama grpc-server
else
echo "BUILD_GRPC_FOR_BACKEND_LLAMA is not defined."
LLAMA_VERSION=$(CPPLLAMA_VERSION) $(MAKE) -C backend/cpp/llama grpc-server
endif
backend-assets/grpc/llama-cpp: backend-assets/grpc backend/cpp/llama/grpc-server
cp -rfv backend/cpp/llama/grpc-server backend-assets/grpc/llama-cpp
# TODO: every binary should have its own folder instead, so can have different metal implementations
ifeq ($(BUILD_TYPE),metal)
cp backend/cpp/llama/llama.cpp/build/bin/default.metallib backend-assets/grpc/
endif
backend-assets/grpc/llama-ggml: sources/go-llama-ggml sources/go-llama-ggml/libbinding.a backend-assets/grpc
$(GOCMD) mod edit -replace github.com/go-skynet/go-llama.cpp=$(CURDIR)/sources/go-llama-ggml
CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(CURDIR)/sources/go-llama-ggml LIBRARY_PATH=$(CURDIR)/sources/go-llama-ggml \
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/llama-ggml ./backend/go/llm/llama-ggml/
backend-assets/grpc/piper: sources/go-piper sources/go-piper/libpiper_binding.a backend-assets/grpc backend-assets/espeak-ng-data
CGO_CXXFLAGS="$(PIPER_CGO_CXXFLAGS)" CGO_LDFLAGS="$(PIPER_CGO_LDFLAGS)" LIBRARY_PATH=$(CURDIR)/sources/go-piper \
$(GOCMD) build -ldflags "$(LD_FLAGS)" -tags "$(GO_TAGS)" -o backend-assets/grpc/piper ./backend/go/tts/
backend-assets/grpc/rwkv: sources/go-rwkv sources/go-rwkv/librwkv.a backend-assets/grpc
CGO_LDFLAGS="$(CGO_LDFLAGS)" C_INCLUDE_PATH=$(CURDIR)/sources/go-rwkv LIBRARY_PATH=$(CURDIR)/sources/go-rwkv \
$(GOCMD) build -ldflags "$(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 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/
grpcs: prepare $(GRPC_BACKENDS)
DOCKER_IMAGE?=local-ai
DOCKER_AIO_IMAGE?=local-ai-aio
@@ -309,18 +567,7 @@ docker:
--build-arg MAKEFLAGS="$(DOCKER_MAKEFLAGS)" \
--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)-cuda-11 .
docker-aio:
@echo "Building AIO image with base $(BASE_IMAGE) as $(DOCKER_AIO_IMAGE)"
docker build \
@@ -334,253 +581,20 @@ docker-aio-all:
docker-image-intel:
docker build \
--build-arg BASE_IMAGE=quay.io/go-skynet/intel-oneapi-base:latest \
--build-arg BASE_IMAGE=intel/oneapi-basekit:2024.0.1-devel-ubuntu22.04 \
--build-arg IMAGE_TYPE=$(IMAGE_TYPE) \
--build-arg GO_TAGS="$(GO_TAGS)" \
--build-arg GO_TAGS="none" \
--build-arg MAKEFLAGS="$(DOCKER_MAKEFLAGS)" \
--build-arg BUILD_TYPE=intel -t $(DOCKER_IMAGE) .
########################################################
## Backends
########################################################
backends/diffusers: docker-build-diffusers docker-save-diffusers build
./local-ai backends install "ocifile://$(abspath ./backend-images/diffusers.tar)"
backends/llama-cpp: docker-build-llama-cpp docker-save-llama-cpp build
./local-ai backends install "ocifile://$(abspath ./backend-images/llama-cpp.tar)"
backends/piper: docker-build-piper docker-save-piper build
./local-ai backends install "ocifile://$(abspath ./backend-images/piper.tar)"
backends/stablediffusion-ggml: docker-build-stablediffusion-ggml docker-save-stablediffusion-ggml build
./local-ai backends install "ocifile://$(abspath ./backend-images/stablediffusion-ggml.tar)"
backends/whisper: docker-build-whisper docker-save-whisper build
./local-ai backends install "ocifile://$(abspath ./backend-images/whisper.tar)"
backends/silero-vad: docker-build-silero-vad docker-save-silero-vad build
./local-ai backends install "ocifile://$(abspath ./backend-images/silero-vad.tar)"
backends/local-store: docker-build-local-store docker-save-local-store build
./local-ai backends install "ocifile://$(abspath ./backend-images/local-store.tar)"
backends/huggingface: docker-build-huggingface docker-save-huggingface build
./local-ai backends install "ocifile://$(abspath ./backend-images/huggingface.tar)"
backends/rfdetr: docker-build-rfdetr docker-save-rfdetr build
./local-ai backends install "ocifile://$(abspath ./backend-images/rfdetr.tar)"
backends/kitten-tts: docker-build-kitten-tts docker-save-kitten-tts build
./local-ai backends install "ocifile://$(abspath ./backend-images/kitten-tts.tar)"
backends/kokoro: docker-build-kokoro docker-save-kokoro build
./local-ai backends install "ocifile://$(abspath ./backend-images/kokoro.tar)"
backends/chatterbox: docker-build-chatterbox docker-save-chatterbox build
./local-ai backends install "ocifile://$(abspath ./backend-images/chatterbox.tar)"
backends/llama-cpp-darwin: build
bash ./scripts/build/llama-cpp-darwin.sh
./local-ai backends install "ocifile://$(abspath ./backend-images/llama-cpp.tar)"
backends/neutts: docker-build-neutts docker-save-neutts build
./local-ai backends install "ocifile://$(abspath ./backend-images/neutts.tar)"
backends/vllm: docker-build-vllm docker-save-vllm build
./local-ai backends install "ocifile://$(abspath ./backend-images/vllm.tar)"
backends/vibevoice: docker-build-vibevoice docker-save-vibevoice build
./local-ai backends install "ocifile://$(abspath ./backend-images/vibevoice.tar)"
build-darwin-python-backend: build
bash ./scripts/build/python-darwin.sh
build-darwin-go-backend: build
bash ./scripts/build/golang-darwin.sh
backends/mlx:
BACKEND=mlx $(MAKE) build-darwin-python-backend
./local-ai backends install "ocifile://$(abspath ./backend-images/mlx.tar)"
backends/diffuser-darwin:
BACKEND=diffusers $(MAKE) build-darwin-python-backend
./local-ai backends install "ocifile://$(abspath ./backend-images/diffusers.tar)"
backends/mlx-vlm:
BACKEND=mlx-vlm $(MAKE) build-darwin-python-backend
./local-ai backends install "ocifile://$(abspath ./backend-images/mlx-vlm.tar)"
backends/mlx-audio:
BACKEND=mlx-audio $(MAKE) build-darwin-python-backend
./local-ai backends install "ocifile://$(abspath ./backend-images/mlx-audio.tar)"
backends/stablediffusion-ggml-darwin:
BACKEND=stablediffusion-ggml BUILD_TYPE=metal $(MAKE) build-darwin-go-backend
./local-ai backends install "ocifile://$(abspath ./backend-images/stablediffusion-ggml.tar)"
backend-images:
mkdir -p backend-images
docker-build-llama-cpp:
docker build --build-arg BUILD_TYPE=$(BUILD_TYPE) --build-arg BASE_IMAGE=$(BASE_IMAGE) -t local-ai-backend:llama-cpp -f backend/Dockerfile.llama-cpp .
docker-build-bark-cpp:
docker build --build-arg BUILD_TYPE=$(BUILD_TYPE) --build-arg BASE_IMAGE=$(BASE_IMAGE) -t local-ai-backend:bark-cpp -f backend/Dockerfile.golang --build-arg BACKEND=bark-cpp .
docker-build-piper:
docker build --build-arg BUILD_TYPE=$(BUILD_TYPE) --build-arg BASE_IMAGE=$(BASE_IMAGE) -t local-ai-backend:piper -f backend/Dockerfile.golang --build-arg BACKEND=piper .
docker-build-local-store:
docker build --build-arg BUILD_TYPE=$(BUILD_TYPE) --build-arg BASE_IMAGE=$(BASE_IMAGE) -t local-ai-backend:local-store -f backend/Dockerfile.golang --build-arg BACKEND=local-store .
docker-build-huggingface:
docker build --build-arg BUILD_TYPE=$(BUILD_TYPE) --build-arg BASE_IMAGE=$(BASE_IMAGE) -t local-ai-backend:huggingface -f backend/Dockerfile.golang --build-arg BACKEND=huggingface .
docker-build-rfdetr:
docker build --build-arg BUILD_TYPE=$(BUILD_TYPE) --build-arg BASE_IMAGE=$(BASE_IMAGE) -t local-ai-backend:rfdetr -f backend/Dockerfile.python --build-arg BACKEND=rfdetr ./backend
docker-build-kitten-tts:
docker build --build-arg BUILD_TYPE=$(BUILD_TYPE) --build-arg BASE_IMAGE=$(BASE_IMAGE) -t local-ai-backend:kitten-tts -f backend/Dockerfile.python --build-arg BACKEND=kitten-tts ./backend
docker-save-kitten-tts: backend-images
docker save local-ai-backend:kitten-tts -o backend-images/kitten-tts.tar
docker-save-chatterbox: backend-images
docker save local-ai-backend:chatterbox -o backend-images/chatterbox.tar
docker-save-vibevoice: backend-images
docker save local-ai-backend:vibevoice -o backend-images/vibevoice.tar
docker-build-neutts:
docker build --build-arg BUILD_TYPE=$(BUILD_TYPE) --build-arg BASE_IMAGE=$(BASE_IMAGE) -t local-ai-backend:neutts -f backend/Dockerfile.python --build-arg BACKEND=neutts ./backend
docker-save-neutts: backend-images
docker save local-ai-backend:neutts -o backend-images/neutts.tar
docker-build-kokoro:
docker build --build-arg BUILD_TYPE=$(BUILD_TYPE) --build-arg BASE_IMAGE=$(BASE_IMAGE) -t local-ai-backend:kokoro -f backend/Dockerfile.python --build-arg BACKEND=kokoro ./backend
docker-build-vllm:
docker build --build-arg CUDA_MAJOR_VERSION=$(CUDA_MAJOR_VERSION) --build-arg CUDA_MINOR_VERSION=$(CUDA_MINOR_VERSION) --build-arg BUILD_TYPE=$(BUILD_TYPE) --build-arg BASE_IMAGE=$(BASE_IMAGE) -t local-ai-backend:vllm -f backend/Dockerfile.python --build-arg BACKEND=vllm ./backend
docker-save-vllm: backend-images
docker save local-ai-backend:vllm -o backend-images/vllm.tar
docker-save-kokoro: backend-images
docker save local-ai-backend:kokoro -o backend-images/kokoro.tar
docker-save-rfdetr: backend-images
docker save local-ai-backend:rfdetr -o backend-images/rfdetr.tar
docker-save-huggingface: backend-images
docker save local-ai-backend:huggingface -o backend-images/huggingface.tar
docker-save-local-store: backend-images
docker save local-ai-backend:local-store -o backend-images/local-store.tar
docker-build-silero-vad:
docker build --build-arg BUILD_TYPE=$(BUILD_TYPE) --build-arg BASE_IMAGE=$(BASE_IMAGE) -t local-ai-backend:silero-vad -f backend/Dockerfile.golang --build-arg BACKEND=silero-vad .
docker-save-silero-vad: backend-images
docker save local-ai-backend:silero-vad -o backend-images/silero-vad.tar
docker-save-piper: backend-images
docker save local-ai-backend:piper -o backend-images/piper.tar
docker-save-llama-cpp: backend-images
docker save local-ai-backend:llama-cpp -o backend-images/llama-cpp.tar
docker-save-bark-cpp: backend-images
docker save local-ai-backend:bark-cpp -o backend-images/bark-cpp.tar
docker-build-stablediffusion-ggml:
docker build --progress=plain --build-arg BUILD_TYPE=$(BUILD_TYPE) --build-arg BASE_IMAGE=$(BASE_IMAGE) --build-arg CUDA_MAJOR_VERSION=$(CUDA_MAJOR_VERSION) --build-arg CUDA_MINOR_VERSION=$(CUDA_MINOR_VERSION) -t local-ai-backend:stablediffusion-ggml -f backend/Dockerfile.golang --build-arg BACKEND=stablediffusion-ggml .
docker-save-stablediffusion-ggml: backend-images
docker save local-ai-backend:stablediffusion-ggml -o backend-images/stablediffusion-ggml.tar
docker-build-rerankers:
docker build --build-arg BUILD_TYPE=$(BUILD_TYPE) --build-arg BASE_IMAGE=$(BASE_IMAGE) -t local-ai-backend:rerankers -f backend/Dockerfile.python --build-arg BACKEND=rerankers .
docker-build-transformers:
docker build --build-arg BUILD_TYPE=$(BUILD_TYPE) --build-arg BASE_IMAGE=$(BASE_IMAGE) -t local-ai-backend:transformers -f backend/Dockerfile.python --build-arg BACKEND=transformers .
docker-build-diffusers:
docker build --progress=plain --build-arg BUILD_TYPE=$(BUILD_TYPE) --build-arg BASE_IMAGE=$(BASE_IMAGE) -t local-ai-backend:diffusers -f backend/Dockerfile.python --build-arg BACKEND=diffusers ./backend
docker-save-diffusers: backend-images
docker save local-ai-backend:diffusers -o backend-images/diffusers.tar
docker-build-whisper:
docker build --build-arg BUILD_TYPE=$(BUILD_TYPE) --build-arg BASE_IMAGE=$(BASE_IMAGE) --build-arg CUDA_MAJOR_VERSION=$(CUDA_MAJOR_VERSION) --build-arg CUDA_MINOR_VERSION=$(CUDA_MINOR_VERSION) -t local-ai-backend:whisper -f backend/Dockerfile.golang --build-arg BACKEND=whisper .
docker-save-whisper: backend-images
docker save local-ai-backend:whisper -o backend-images/whisper.tar
docker-build-faster-whisper:
docker build --build-arg BUILD_TYPE=$(BUILD_TYPE) --build-arg BASE_IMAGE=$(BASE_IMAGE) -t local-ai-backend:faster-whisper -f backend/Dockerfile.python --build-arg BACKEND=faster-whisper .
docker-build-coqui:
docker build --build-arg BUILD_TYPE=$(BUILD_TYPE) --build-arg BASE_IMAGE=$(BASE_IMAGE) -t local-ai-backend:coqui -f backend/Dockerfile.python --build-arg BACKEND=coqui .
docker-build-bark:
docker build --build-arg BUILD_TYPE=$(BUILD_TYPE) --build-arg BASE_IMAGE=$(BASE_IMAGE) -t local-ai-backend:bark -f backend/Dockerfile.python --build-arg BACKEND=bark .
docker-build-chatterbox:
docker build --build-arg BUILD_TYPE=$(BUILD_TYPE) --build-arg BASE_IMAGE=$(BASE_IMAGE) -t local-ai-backend:chatterbox -f backend/Dockerfile.python --build-arg BACKEND=chatterbox ./backend
docker-build-vibevoice:
docker build --progress=plain --build-arg BUILD_TYPE=$(BUILD_TYPE) --build-arg BASE_IMAGE=$(BASE_IMAGE) -t local-ai-backend:vibevoice -f backend/Dockerfile.python --build-arg BACKEND=vibevoice ./backend
docker-build-exllama2:
docker build --build-arg BUILD_TYPE=$(BUILD_TYPE) --build-arg BASE_IMAGE=$(BASE_IMAGE) -t local-ai-backend:exllama2 -f backend/Dockerfile.python --build-arg BACKEND=exllama2 .
docker-build-backends: docker-build-llama-cpp docker-build-rerankers docker-build-vllm docker-build-transformers docker-build-diffusers docker-build-kokoro docker-build-faster-whisper docker-build-coqui docker-build-bark docker-build-chatterbox docker-build-vibevoice docker-build-exllama2
########################################################
### END Backends
########################################################
--build-arg BUILD_TYPE=sycl_f32 -t $(DOCKER_IMAGE) .
docker-image-intel-xpu:
docker build \
--build-arg BASE_IMAGE=intel/oneapi-basekit:2024.0.1-devel-ubuntu22.04 \
--build-arg IMAGE_TYPE=$(IMAGE_TYPE) \
--build-arg GO_TAGS="none" \
--build-arg MAKEFLAGS="$(DOCKER_MAKEFLAGS)" \
--build-arg BUILD_TYPE=sycl_f32 -t $(DOCKER_IMAGE) .
.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
$(GOCMD) run ./.github/ci/modelslist.go ./gallery/index.yaml > docs/static/gallery.html
docs/public: docs/layouts/_default docs/static/gallery.html
cd docs && hugo --minify
docs-clean:
rm -rf docs/public
rm -rf docs/static/gallery.html
.PHONY: docs
docs: docs/static/gallery.html
cd docs && hugo serve
########################################################
## Platform-specific builds
########################################################
## fyne cross-platform build
build-launcher-darwin: build-launcher
go run github.com/tiagomelo/macos-dmg-creator/cmd/createdmg@latest \
--appName "LocalAI" \
--appBinaryPath "$(LAUNCHER_BINARY_NAME)" \
--bundleIdentifier "com.localai.launcher" \
--iconPath "core/http/static/logo.png" \
--outputDir "dist/"
build-launcher-linux:
cd cmd/launcher && go run fyne.io/tools/cmd/fyne@latest package -os linux -icon ../../core/http/static/logo.png --executable $(LAUNCHER_BINARY_NAME)-linux && mv launcher.tar.xz ../../$(LAUNCHER_BINARY_NAME)-linux.tar.xz
swag init -g core/http/api.go --output swagger

340
README.md
View File

@@ -1,6 +1,7 @@
<h1 align="center">
<br>
<img width="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>
@@ -30,293 +31,73 @@
<p align="center">
<a href="https://twitter.com/LocalAI_API" target="blank">
<img src="https://img.shields.io/badge/X-%23000000.svg?style=for-the-badge&logo=X&logoColor=white&label=LocalAI_API" alt="Follow LocalAI_API"/>
<img src="https://img.shields.io/twitter/follow/LocalAI_API?label=Follow: LocalAI_API&style=social" alt="Follow LocalAI_API"/>
</a>
<a href="https://discord.gg/uJAeKSAGDy" target="blank">
<img src="https://img.shields.io/badge/dynamic/json?color=blue&label=Discord&style=for-the-badge&query=approximate_member_count&url=https%3A%2F%2Fdiscordapp.com%2Fapi%2Finvites%2FuJAeKSAGDy%3Fwith_counts%3Dtrue&logo=discord" alt="Join LocalAI Discord Community"/>
<img src="https://dcbadge.vercel.app/api/server/uJAeKSAGDy?style=flat-square&theme=default-inverted" alt="Join LocalAI Discord Community"/>
</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) [🛫 Examples](https://github.com/mudler/LocalAI-examples) Try on
[![Telegram](https://img.shields.io/badge/Telegram-2CA5E0?style=for-the-badge&logo=telegram&logoColor=white)](https://t.me/localaiofficial_bot)
> [💻 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.
## 🔥🔥 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:
- Landing page: https://github.com/mudler/LocalAI/pull/1922
- 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
- Parallel function calling: https://github.com/mudler/LocalAI/pull/1726 / Tools API support: https://github.com/mudler/LocalAI/pull/1715
- Upload file API: https://github.com/mudler/LocalAI/pull/1703
- ROCm container images: https://github.com/mudler/LocalAI/pull/1595 / Intel GPU support (sycl, transformers, diffusers): https://github.com/mudler/LocalAI/issues/1653
- Mamba support: https://github.com/mudler/LocalAI/pull/1589
- Start and share models with config file: https://github.com/mudler/LocalAI/pull/1522
- 🐸 Coqui: https://github.com/mudler/LocalAI/pull/1489
- Img2vid https://github.com/mudler/LocalAI/pull/1442
<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):
- 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
## Screenshots / Video
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
### Youtube video
## 💻 [Getting started](https://localai.io/basics/getting_started/index.html)
<h1 align="center">
<br>
<a href="https://www.youtube.com/watch?v=PDqYhB9nNHA" target="_blank"> <img width="300" src="https://img.youtube.com/vi/PDqYhB9nNHA/0.jpg"> </a><br>
<br>
</h1>
For a detailed step-by-step introduction, refer to the [Getting Started](https://localai.io/basics/getting_started/index.html) guide.
### Screenshots
| 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) |
| 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) |
| 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) |
| 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:
For those in a hurry, here's a straightforward one-liner to launch a LocalAI AIO(All-in-one) Image using `docker`:
```bash
# Basic installation
curl https://localai.io/install.sh | sh
```
For more installation options, see [Installer Options](https://localai.io/installation/).
### macOS Download:
<a href="https://github.com/mudler/LocalAI/releases/latest/download/LocalAI.dmg">
<img src="https://img.shields.io/badge/Download-macOS-blue?style=for-the-badge&logo=apple&logoColor=white" alt="Download LocalAI for macOS"/>
</a>
> Note: the DMGs are not signed by Apple as quarantined. See https://github.com/mudler/LocalAI/issues/6268 for a workaround, fix is tracked here: https://github.com/mudler/LocalAI/issues/6244
Or run with docker:
> **💡 Docker Run vs Docker Start**
>
> - `docker run` creates and starts a new container. If a container with the same name already exists, this command will fail.
> - `docker start` starts an existing container that was previously created with `docker run`.
>
> If you've already run LocalAI before and want to start it again, use: `docker start -i local-ai`
### CPU only image:
```bash
docker run -ti --name local-ai -p 8080:8080 localai/localai:latest
```
### NVIDIA GPU Images:
```bash
# CUDA 12.0
docker run -ti --name local-ai -p 8080:8080 --gpus all localai/localai:latest-gpu-nvidia-cuda-12
# CUDA 11.7
docker run -ti --name local-ai -p 8080:8080 --gpus all localai/localai:latest-gpu-nvidia-cuda-11
# NVIDIA Jetson (L4T) ARM64
docker run -ti --name local-ai -p 8080:8080 --gpus all localai/localai:latest-nvidia-l4t-arm64
```
### AMD GPU Images (ROCm):
```bash
docker run -ti --name local-ai -p 8080:8080 --device=/dev/kfd --device=/dev/dri --group-add=video localai/localai:latest-gpu-hipblas
```
### Intel GPU Images (oneAPI):
```bash
docker run -ti --name local-ai -p 8080:8080 --device=/dev/dri/card1 --device=/dev/dri/renderD128 localai/localai:latest-gpu-intel
```
### Vulkan GPU Images:
```bash
docker run -ti --name local-ai -p 8080:8080 localai/localai:latest-gpu-vulkan
```
### AIO Images (pre-downloaded models):
```bash
# CPU version
docker run -ti --name local-ai -p 8080:8080 localai/localai:latest-aio-cpu
# NVIDIA CUDA 12 version
docker run -ti --name local-ai -p 8080:8080 --gpus all localai/localai:latest-aio-gpu-nvidia-cuda-12
# NVIDIA CUDA 11 version
docker run -ti --name local-ai -p 8080:8080 --gpus all localai/localai:latest-aio-gpu-nvidia-cuda-11
# Intel GPU version
docker run -ti --name local-ai -p 8080:8080 localai/localai:latest-aio-gpu-intel
# AMD GPU version
docker run -ti --name local-ai -p 8080:8080 --device=/dev/kfd --device=/dev/dri --group-add=video localai/localai:latest-aio-gpu-hipblas
# 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
```
For more information about the AIO images and pre-downloaded models, see [Container Documentation](https://localai.io/basics/container/).
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
```
> ⚡ **Automatic Backend Detection**: When you install models from the gallery or YAML files, LocalAI automatically detects your system's GPU capabilities (NVIDIA, AMD, Intel) and downloads the appropriate backend. For advanced configuration options, see [GPU Acceleration](https://localai.io/features/gpu-acceleration/#automatic-backend-detection).
For more information, see [💻 Getting started](https://localai.io/basics/getting_started/index.html), if you are interested in our roadmap items and future enhancements, you can see the [Issues labeled as Roadmap here](https://github.com/mudler/LocalAI/issues?q=is%3Aissue+is%3Aopen+label%3Aroadmap)
## 📰 Latest project news
- December 2025: [Dynamic Memory Resource reclaimer](https://github.com/mudler/LocalAI/pull/7583), [Automatic fitting of models to multiple GPUS(llama.cpp)](https://github.com/mudler/LocalAI/pull/7584), [Added Vibevoice backend](https://github.com/mudler/LocalAI/pull/7494)
- November 2025: Major improvements to the UX. Among these: [Import models via URL](https://github.com/mudler/LocalAI/pull/7245) and [Multiple chats and history](https://github.com/mudler/LocalAI/pull/7325)
- October 2025: 🔌 [Model Context Protocol (MCP)](https://localai.io/docs/features/mcp/) support added for agentic capabilities with external tools
- September 2025: New Launcher application for MacOS and Linux, extended support to many backends for Mac and Nvidia L4T devices. Models: Added MLX-Audio, WAN 2.2. WebUI improvements and Python-based backends now ships portable python environments.
- August 2025: MLX, MLX-VLM, Diffusers and llama.cpp are now supported on Mac M1/M2/M3+ chips ( with `development` suffix in the gallery ): https://github.com/mudler/LocalAI/pull/6049 https://github.com/mudler/LocalAI/pull/6119 https://github.com/mudler/LocalAI/pull/6121 https://github.com/mudler/LocalAI/pull/6060
- July/August 2025: 🔍 [Object Detection](https://localai.io/features/object-detection/) added to the API featuring [rf-detr](https://github.com/roboflow/rf-detr)
- July 2025: All backends migrated outside of the main binary. LocalAI is now more lightweight, small, and automatically downloads the required backend to run the model. [Read the release notes](https://github.com/mudler/LocalAI/releases/tag/v3.2.0)
- June 2025: [Backend management](https://github.com/mudler/LocalAI/pull/5607) has been added. Attention: extras images are going to be deprecated from the next release! Read [the backend management PR](https://github.com/mudler/LocalAI/pull/5607).
- May 2025: [Audio input](https://github.com/mudler/LocalAI/pull/5466) and [Reranking](https://github.com/mudler/LocalAI/pull/5396) in llama.cpp backend, [Realtime API](https://github.com/mudler/LocalAI/pull/5392), Support to Gemma, SmollVLM, and more multimodal models (available in the gallery).
- May 2025: Important: image name changes [See release](https://github.com/mudler/LocalAI/releases/tag/v2.29.0)
- Apr 2025: Rebrand, WebUI enhancements
- 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/)
- 🧩 [Backend Gallery](https://localai.io/backends/): Install/remove backends on the fly, powered by OCI images — fully customizable and API-driven.
- 📖 [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/)
- 🔍 [Object Detection](https://localai.io/features/object-detection/)
- 📈 [Reranker API](https://localai.io/features/reranker/)
- 🆕🖧 [P2P Inferencing](https://localai.io/features/distribute/)
- 🆕🔌 [Model Context Protocol (MCP)](https://localai.io/docs/features/mcp/) - Agentic capabilities with external tools and [LocalAGI's Agentic capabilities](https://github.com/mudler/LocalAGI)
- 🔊 Voice activity detection (Silero-VAD support)
- 🌍 Integrated WebUI!
- 🆕 [Vision API](https://localai.io/features/gpt-vision/)
## 🧩 Supported Backends & Acceleration
## 💻 Usage
LocalAI supports a comprehensive range of AI backends with multiple acceleration options:
### Text Generation & Language Models
| Backend | Description | Acceleration Support |
|---------|-------------|---------------------|
| **llama.cpp** | LLM inference in C/C++ | CUDA 11/12, ROCm, Intel SYCL, Vulkan, Metal, CPU |
| **vLLM** | Fast LLM inference with PagedAttention | CUDA 12, ROCm, Intel |
| **transformers** | HuggingFace transformers framework | CUDA 11/12, ROCm, Intel, CPU |
| **exllama2** | GPTQ inference library | CUDA 12 |
| **MLX** | Apple Silicon LLM inference | Metal (M1/M2/M3+) |
| **MLX-VLM** | Apple Silicon Vision-Language Models | Metal (M1/M2/M3+) |
### Audio & Speech Processing
| Backend | Description | Acceleration Support |
|---------|-------------|---------------------|
| **whisper.cpp** | OpenAI Whisper in C/C++ | CUDA 12, ROCm, Intel SYCL, Vulkan, CPU |
| **faster-whisper** | Fast Whisper with CTranslate2 | CUDA 12, ROCm, Intel, CPU |
| **bark** | Text-to-audio generation | CUDA 12, ROCm, Intel |
| **bark-cpp** | C++ implementation of Bark | CUDA, Metal, CPU |
| **coqui** | Advanced TTS with 1100+ languages | CUDA 12, ROCm, Intel, CPU |
| **kokoro** | Lightweight TTS model | CUDA 12, ROCm, Intel, CPU |
| **chatterbox** | Production-grade TTS | CUDA 11/12, CPU |
| **piper** | Fast neural TTS system | CPU |
| **kitten-tts** | Kitten TTS models | CPU |
| **silero-vad** | Voice Activity Detection | CPU |
| **neutts** | Text-to-speech with voice cloning | CUDA 12, ROCm, CPU |
### Image & Video Generation
| Backend | Description | Acceleration Support |
|---------|-------------|---------------------|
| **stablediffusion.cpp** | Stable Diffusion in C/C++ | CUDA 12, Intel SYCL, Vulkan, CPU |
| **diffusers** | HuggingFace diffusion models | CUDA 11/12, ROCm, Intel, Metal, CPU |
### Specialized AI Tasks
| Backend | Description | Acceleration Support |
|---------|-------------|---------------------|
| **rfdetr** | Real-time object detection | CUDA 12, Intel, CPU |
| **rerankers** | Document reranking API | CUDA 11/12, ROCm, Intel, CPU |
| **local-store** | Vector database | CPU |
| **huggingface** | HuggingFace API integration | API-based |
### Hardware Acceleration Matrix
| Acceleration Type | Supported Backends | Hardware Support |
|-------------------|-------------------|------------------|
| **NVIDIA CUDA 11** | llama.cpp, whisper, stablediffusion, diffusers, rerankers, bark, chatterbox | Nvidia hardware |
| **NVIDIA CUDA 12** | All CUDA-compatible backends | Nvidia hardware |
| **AMD ROCm** | llama.cpp, whisper, vllm, transformers, diffusers, rerankers, coqui, kokoro, bark, neutts | AMD Graphics |
| **Intel oneAPI** | llama.cpp, whisper, stablediffusion, vllm, transformers, diffusers, rfdetr, rerankers, exllama2, coqui, kokoro, bark | Intel Arc, Intel iGPUs |
| **Apple Metal** | llama.cpp, whisper, diffusers, MLX, MLX-VLM, bark-cpp | Apple M1/M2/M3+ |
| **Vulkan** | llama.cpp, whisper, stablediffusion | Cross-platform GPUs |
| **NVIDIA Jetson** | llama.cpp, whisper, stablediffusion, diffusers, rfdetr | ARM64 embedded AI |
| **CPU Optimized** | All backends | AVX/AVX2/AVX512, quantization support |
Check out the [Getting started](https://localai.io/basics/getting_started/index.html) section in our documentation.
### 🔗 Community and integrations
@@ -326,41 +107,24 @@ 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
Agentic Libraries:
- https://github.com/mudler/cogito
MCPs:
- https://github.com/mudler/MCPs
Model galleries
- https://github.com/go-skynet/model-gallery
Voice:
- https://github.com/richiejp/VoxInput
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/)
@@ -368,9 +132,7 @@ Other:
## :book: 🎥 [Media, Blogs, Social](https://localai.io/basics/news/#media-blogs-social)
- [Run Visual studio code with LocalAI (SUSE)](https://www.suse.com/c/running-ai-locally/)
- 🆕 [Run LocalAI on Jetson Nano Devkit](https://mudler.pm/posts/local-ai-jetson-nano-devkit/)
- [Run LocalAI on AWS EKS with Pulumi](https://www.pulumi.com/blog/low-code-llm-apps-with-local-ai-flowise-and-pulumi/)
- [Run LocalAI on AWS EKS with Pulumi](https://www.pulumi.com/ai/answers/tiZMDoZzZV6TLxgDXNBnFE/deploying-helm-charts-on-aws-eks)
- [Run LocalAI on AWS](https://staleks.hashnode.dev/installing-localai-on-aws-ec2-instance)
- [Create a slackbot for teams and OSS projects that answer to documentation](https://mudler.pm/posts/smart-slackbot-for-teams/)
- [LocalAI meets k8sgpt](https://www.youtube.com/watch?v=PKrDNuJ_dfE)
@@ -397,16 +159,17 @@ 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
@@ -416,7 +179,7 @@ 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
@@ -428,6 +191,7 @@ 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

@@ -1,8 +1,7 @@
embeddings: true
name: text-embedding-ada-002
backend: llama-cpp
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

@@ -1,33 +0,0 @@
name: jina-reranker-v1-base-en
reranking: true
f16: true
parameters:
model: jina-reranker-v1-tiny-en.f16.gguf
backend: llama-cpp
download_files:
- filename: jina-reranker-v1-tiny-en.f16.gguf
sha256: 5f696cf0d0f3d347c4a279eee8270e5918554cdac0ed1f632f2619e4e8341407
uri: huggingface://mradermacher/jina-reranker-v1-tiny-en-GGUF/jina-reranker-v1-tiny-en.f16.gguf
usage: |
You can test this model with curl like this:
curl http://localhost:8080/v1/rerank \
-H "Content-Type: application/json" \
-d '{
"model": "jina-reranker-v1-base-en",
"query": "Organic skincare products for sensitive skin",
"documents": [
"Eco-friendly kitchenware for modern homes",
"Biodegradable cleaning supplies for eco-conscious consumers",
"Organic cotton baby clothes for sensitive skin",
"Natural organic skincare range for sensitive skin",
"Tech gadgets for smart homes: 2024 edition",
"Sustainable gardening tools and compost solutions",
"Sensitive skin-friendly facial cleansers and toners",
"Organic food wraps and storage solutions",
"All-natural pet food for dogs with allergies",
"Yoga mats made from recycled materials"
],
"top_n": 3
}'

View File

@@ -2,7 +2,7 @@ name: tts-1
download_files:
- filename: voice-en-us-amy-low.tar.gz
uri: https://github.com/rhasspy/piper/releases/download/v0.0.2/voice-en-us-amy-low.tar.gz
backend: piper
parameters:
model: en-us-amy-low.onnx

View File

@@ -1,58 +1,53 @@
context_size: 8192
f16: true
backend: llama-cpp
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-Mistral-7B-GGUF/Hermes-2-Pro-Mistral-7B.Q2_K.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>{{end}}
{{- if eq .RoleName "tool" }}<tool_result>{{end }}
{{- if .Content}}
{{.Content}}
{{- end }}
{{- if .FunctionCall}}{{toJson .FunctionCall}}{{end }}
{{- if .FunctionCall }}</tool_call>{{end }}
{{- if eq .RoleName "tool" }}</tool_result>{{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}]
}'

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 +1,31 @@
backend: llama-cpp
context_size: 4096
f16: true
backend: llama-cpp
mmap: true
mmproj: minicpm-v-4_5-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-4_5-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-4_5-Q4_K_M.gguf
sha256: c1c3c33100b15b4caf7319acce4e23c0eb0ce1cbd12f70e8d24f05aa67b7512f
uri: huggingface://openbmb/MiniCPM-V-4_5-gguf/ggml-model-Q4_K_M.gguf
- filename: minicpm-v-4_5-mmproj-f16.gguf
uri: huggingface://openbmb/MiniCPM-V-4_5-gguf/mmproj-model-f16.gguf
sha256: 7a7225a32e8d453aaa3d22d8c579b5bf833c253f784cdb05c99c9a76fd616df8
- 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

@@ -129,10 +129,10 @@ 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}/text-to-speech.yaml,/aio/${PROFILE}/image-gen.yaml,/aio/${PROFILE}/text-to-text.yaml,/aio/${PROFILE}/speech-to-text.yaml,/aio/${PROFILE}/vision.yaml}"
check_vars
echo "===> Starting LocalAI[$PROFILE] with the following models: $MODELS"
exec /entrypoint.sh "$@"
exec /build/entrypoint.sh "$@"

View File

@@ -1,8 +1,7 @@
embeddings: true
name: text-embedding-ada-002
backend: llama-cpp
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

@@ -1,33 +0,0 @@
name: jina-reranker-v1-base-en
reranking: true
f16: true
parameters:
model: jina-reranker-v1-tiny-en.f16.gguf
backend: llama-cpp
download_files:
- filename: jina-reranker-v1-tiny-en.f16.gguf
sha256: 5f696cf0d0f3d347c4a279eee8270e5918554cdac0ed1f632f2619e4e8341407
uri: huggingface://mradermacher/jina-reranker-v1-tiny-en-GGUF/jina-reranker-v1-tiny-en.f16.gguf
usage: |
You can test this model with curl like this:
curl http://localhost:8080/v1/rerank \
-H "Content-Type: application/json" \
-d '{
"model": "jina-reranker-v1-base-en",
"query": "Organic skincare products for sensitive skin",
"documents": [
"Eco-friendly kitchenware for modern homes",
"Biodegradable cleaning supplies for eco-conscious consumers",
"Organic cotton baby clothes for sensitive skin",
"Natural organic skincare range for sensitive skin",
"Tech gadgets for smart homes: 2024 edition",
"Sustainable gardening tools and compost solutions",
"Sensitive skin-friendly facial cleansers and toners",
"Organic food wraps and storage solutions",
"All-natural pet food for dogs with allergies",
"Yoga mats made from recycled materials"
],
"top_n": 3
}'

View File

@@ -2,7 +2,7 @@ name: tts-1
download_files:
- filename: voice-en-us-amy-low.tar.gz
uri: https://github.com/rhasspy/piper/releases/download/v0.0.2/voice-en-us-amy-low.tar.gz
backend: piper
parameters:
model: en-us-amy-low.onnx

View File

@@ -1,54 +1,53 @@
context_size: 4096
f16: true
backend: llama-cpp
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-Mistral-7B-GGUF/Hermes-2-Pro-Mistral-7B.Q6_K.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: |
{{.Input}}
<|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>{{end}}
{{- if eq .RoleName "tool" }}<tool_result>{{end }}
{{- if .Content}}
{{.Content}}
{{- end }}
{{- if .FunctionCall}}{{toJson .FunctionCall}}{{end }}
{{- if .FunctionCall }}</tool_call>{{end }}
{{- if eq .RoleName "tool" }}</tool_result>{{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}}
</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-qwen2.5-7b-v0.5-q4_k_m.gguf
sha256: 4e7b7fe1d54b881f1ef90799219dc6cc285d29db24f559c8998d1addb35713d4
uri: huggingface://mudler/LocalAI-functioncall-qwen2.5-7b-v0.5-Q4_K_M-GGUF/localai-functioncall-qwen2.5-7b-v0.5-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

@@ -1,50 +1,35 @@
context_size: 4096
backend: llama-cpp
context_size: 4096
f16: true
mmap: true
mmproj: minicpm-v-4_5-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-4_5-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-4_5-Q4_K_M.gguf
sha256: c1c3c33100b15b4caf7319acce4e23c0eb0ce1cbd12f70e8d24f05aa67b7512f
uri: huggingface://openbmb/MiniCPM-V-4_5-gguf/ggml-model-Q4_K_M.gguf
- filename: minicpm-v-4_5-mmproj-f16.gguf
uri: huggingface://openbmb/MiniCPM-V-4_5-gguf/mmproj-model-f16.gguf
sha256: 7a7225a32e8d453aaa3d22d8c579b5bf833c253f784cdb05c99c9a76fd616df8
- 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

@@ -1,8 +1,7 @@
embeddings: true
name: text-embedding-ada-002
backend: llama-cpp
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

@@ -1,33 +0,0 @@
name: jina-reranker-v1-base-en
reranking: true
f16: true
parameters:
model: jina-reranker-v1-tiny-en.f16.gguf
backend: llama-cpp
download_files:
- filename: jina-reranker-v1-tiny-en.f16.gguf
sha256: 5f696cf0d0f3d347c4a279eee8270e5918554cdac0ed1f632f2619e4e8341407
uri: huggingface://mradermacher/jina-reranker-v1-tiny-en-GGUF/jina-reranker-v1-tiny-en.f16.gguf
usage: |
You can test this model with curl like this:
curl http://localhost:8080/v1/rerank \
-H "Content-Type: application/json" \
-d '{
"model": "jina-reranker-v1-base-en",
"query": "Organic skincare products for sensitive skin",
"documents": [
"Eco-friendly kitchenware for modern homes",
"Biodegradable cleaning supplies for eco-conscious consumers",
"Organic cotton baby clothes for sensitive skin",
"Natural organic skincare range for sensitive skin",
"Tech gadgets for smart homes: 2024 edition",
"Sustainable gardening tools and compost solutions",
"Sensitive skin-friendly facial cleansers and toners",
"Organic food wraps and storage solutions",
"All-natural pet food for dogs with allergies",
"Yoga mats made from recycled materials"
],
"top_n": 3
}'

View File

@@ -2,7 +2,7 @@ name: tts-1
download_files:
- filename: voice-en-us-amy-low.tar.gz
uri: https://github.com/rhasspy/piper/releases/download/v0.0.2/voice-en-us-amy-low.tar.gz
backend: piper
parameters:
model: en-us-amy-low.onnx

View File

@@ -1,54 +1,53 @@
context_size: 4096
f16: true
backend: llama-cpp
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-Mistral-7B-GGUF/Hermes-2-Pro-Mistral-7B.Q6_K.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: |
{{.Input}}
<|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>{{end}}
{{- if eq .RoleName "tool" }}<tool_result>{{end }}
{{- if .Content}}
{{.Content}}
{{- end }}
{{- if .FunctionCall}}{{toJson .FunctionCall}}{{end }}
{{- if .FunctionCall }}</tool_call>{{end }}
{{- if eq .RoleName "tool" }}</tool_result>{{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}}
</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

@@ -1,51 +1,35 @@
context_size: 4096
backend: llama-cpp
f16: true
mmap: true
mmproj: minicpm-v-4_5-mmproj-f16.gguf
name: gpt-4o
context_size: 4096
mmap: false
f16: false
name: gpt-4-vision-preview
roles:
user: "USER:"
assistant: "ASSISTANT:"
system: "SYSTEM:"
mmproj: llava-v1.6-7b-mmproj-f16.gguf
parameters:
model: minicpm-v-4_5-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-4_5-Q4_K_M.gguf
sha256: c1c3c33100b15b4caf7319acce4e23c0eb0ce1cbd12f70e8d24f05aa67b7512f
uri: huggingface://openbmb/MiniCPM-V-4_5-gguf/ggml-model-Q4_K_M.gguf
- filename: minicpm-v-4_5-mmproj-f16.gguf
uri: huggingface://openbmb/MiniCPM-V-4_5-gguf/mmproj-model-f16.gguf
sha256: 7a7225a32e8d453aaa3d22d8c579b5bf833c253f784cdb05c99c9a76fd616df8
- 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}]}'

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

View File

@@ -1,156 +0,0 @@
ARG BASE_IMAGE=ubuntu:22.04
FROM ${BASE_IMAGE} AS builder
ARG BACKEND=rerankers
ARG BUILD_TYPE
ENV BUILD_TYPE=${BUILD_TYPE}
ARG CUDA_MAJOR_VERSION
ARG CUDA_MINOR_VERSION
ARG SKIP_DRIVERS=false
ENV CUDA_MAJOR_VERSION=${CUDA_MAJOR_VERSION}
ENV CUDA_MINOR_VERSION=${CUDA_MINOR_VERSION}
ENV DEBIAN_FRONTEND=noninteractive
ARG TARGETARCH
ARG TARGETVARIANT
ARG GO_VERSION=1.22.6
ARG UBUNTU_VERSION=2204
RUN apt-get update && \
apt-get install -y --no-install-recommends \
build-essential \
git ccache \
ca-certificates \
make cmake wget \
curl unzip \
libssl-dev && \
apt-get clean && \
rm -rf /var/lib/apt/lists/*
# Cuda
ENV PATH=/usr/local/cuda/bin:${PATH}
# HipBLAS requirements
ENV PATH=/opt/rocm/bin:${PATH}
# 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 ( [ "${BUILD_TYPE}" = "cublas" ] || [ "${BUILD_TYPE}" = "l4t" ] ) && [ "${SKIP_DRIVERS}" = "false" ]; then
apt-get update && \
apt-get install -y --no-install-recommends \
software-properties-common pciutils
if [ "amd64" = "$TARGETARCH" ]; then
curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu${UBUNTU_VERSION}/x86_64/cuda-keyring_1.1-1_all.deb
fi
if [ "arm64" = "$TARGETARCH" ]; then
if [ "${CUDA_MAJOR_VERSION}" = "13" ]; then
curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu${UBUNTU_VERSION}/sbsa/cuda-keyring_1.1-1_all.deb
else
curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu${UBUNTU_VERSION}/arm64/cuda-keyring_1.1-1_all.deb
fi
fi
dpkg -i cuda-keyring_1.1-1_all.deb && \
rm -f cuda-keyring_1.1-1_all.deb && \
apt-get update && \
apt-get install -y --no-install-recommends \
cuda-nvcc-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
libcufft-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
libcurand-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
libcublas-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
libcusparse-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
libcusolver-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION}
if [ "${CUDA_MAJOR_VERSION}" = "13" ] && [ "arm64" = "$TARGETARCH" ]; then
apt-get install -y --no-install-recommends \
libcufile-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} libcudnn9-cuda-${CUDA_MAJOR_VERSION} cuda-cupti-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} libnvjitlink-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION}
fi
apt-get clean && \
rm -rf /var/lib/apt/lists/*
fi
EOT
# https://github.com/NVIDIA/Isaac-GR00T/issues/343
RUN <<EOT bash
if [ "${BUILD_TYPE}" = "cublas" ] && [ "${TARGETARCH}" = "arm64" ]; then
wget https://developer.download.nvidia.com/compute/cudss/0.6.0/local_installers/cudss-local-tegra-repo-ubuntu${UBUNTU_VERSION}-0.6.0_0.6.0-1_arm64.deb && \
dpkg -i cudss-local-tegra-repo-ubuntu${UBUNTU_VERSION}-0.6.0_0.6.0-1_arm64.deb && \
cp /var/cudss-local-tegra-repo-ubuntu${UBUNTU_VERSION}-0.6.0/cudss-*-keyring.gpg /usr/share/keyrings/ && \
apt-get update && apt-get -y install cudss cudss-cuda-${CUDA_MAJOR_VERSION} && \
wget https://developer.download.nvidia.com/compute/nvpl/25.5/local_installers/nvpl-local-repo-ubuntu${UBUNTU_VERSION}-25.5_1.0-1_arm64.deb && \
dpkg -i nvpl-local-repo-ubuntu${UBUNTU_VERSION}-25.5_1.0-1_arm64.deb && \
cp /var/nvpl-local-repo-ubuntu${UBUNTU_VERSION}-25.5/nvpl-*-keyring.gpg /usr/share/keyrings/ && \
apt-get update && apt-get install -y nvpl
fi
EOT
# If we are building with clblas support, we need the libraries for the builds
RUN if [ "${BUILD_TYPE}" = "clblas" ] && [ "${SKIP_DRIVERS}" = "false" ]; then \
apt-get update && \
apt-get install -y --no-install-recommends \
libclblast-dev && \
apt-get clean && \
rm -rf /var/lib/apt/lists/* \
; fi
RUN if [ "${BUILD_TYPE}" = "hipblas" ] && [ "${SKIP_DRIVERS}" = "false" ]; then \
apt-get update && \
apt-get install -y --no-install-recommends \
hipblas-dev \
rocblas-dev && \
apt-get clean && \
rm -rf /var/lib/apt/lists/* && \
# I have no idea why, but the ROCM lib packages don't trigger ldconfig after they install, which results in local-ai and others not being able
# to locate the libraries. We run ldconfig ourselves to work around this packaging deficiency
ldconfig \
; fi
# Install Go
RUN curl -L -s https://go.dev/dl/go${GO_VERSION}.linux-${TARGETARCH}.tar.gz | tar -C /usr/local -xz
ENV PATH=$PATH:/root/go/bin:/usr/local/go/bin:/usr/local/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 echo "TARGETARCH: $TARGETARCH"
# We need protoc installed, and the version in 22.04 is too old. We will create one as part installing the GRPC build below
# but that will also being in a newer version of absl which stablediffusion cannot compile with. This version of protoc is only
# here so that we can generate the grpc code for the stablediffusion build
RUN <<EOT bash
if [ "amd64" = "$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" = "$TARGETARCH" ]; then
curl -L -s https://github.com/protocolbuffers/protobuf/releases/download/v27.1/protoc-27.1-linux-aarch_64.zip -o protoc.zip && \
unzip -j -d /usr/local/bin protoc.zip bin/protoc && \
rm protoc.zip
fi
EOT
COPY . /LocalAI
RUN cd /LocalAI && make protogen-go && make -C /LocalAI/backend/go/${BACKEND} build
FROM scratch
ARG BACKEND=rerankers
COPY --from=builder /LocalAI/backend/go/${BACKEND}/package/. ./

View File

@@ -1,232 +0,0 @@
ARG BASE_IMAGE=ubuntu:22.04
ARG GRPC_BASE_IMAGE=${BASE_IMAGE}
# 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 ${GRPC_BASE_IMAGE} AS grpc
# This is a bit of a hack, but it's required in order to be able to effectively cache this layer in CI
ARG GRPC_MAKEFLAGS="-j4 -Otarget"
ARG GRPC_VERSION=v1.65.0
ARG CMAKE_FROM_SOURCE=false
ARG CMAKE_VERSION=3.26.4
ENV MAKEFLAGS=${GRPC_MAKEFLAGS}
WORKDIR /build
RUN apt-get update && \
apt-get install -y --no-install-recommends \
ca-certificates \
build-essential curl libssl-dev \
git wget && \
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 && \
rm -rf /build
FROM ${BASE_IMAGE} AS builder
ARG BACKEND=rerankers
ARG BUILD_TYPE
ENV BUILD_TYPE=${BUILD_TYPE}
ARG CUDA_MAJOR_VERSION
ARG CUDA_MINOR_VERSION
ARG SKIP_DRIVERS=false
ENV CUDA_MAJOR_VERSION=${CUDA_MAJOR_VERSION}
ENV CUDA_MINOR_VERSION=${CUDA_MINOR_VERSION}
ENV DEBIAN_FRONTEND=noninteractive
ARG TARGETARCH
ARG TARGETVARIANT
ARG GO_VERSION=1.22.6
ARG UBUNTU_VERSION=2204
RUN apt-get update && \
apt-get install -y --no-install-recommends \
build-essential \
ccache git \
ca-certificates \
make \
curl unzip \
libssl-dev wget && \
apt-get clean && \
rm -rf /var/lib/apt/lists/*
# Cuda
ENV PATH=/usr/local/cuda/bin:${PATH}
# HipBLAS requirements
ENV PATH=/opt/rocm/bin:${PATH}
# 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 ( [ "${BUILD_TYPE}" = "cublas" ] || [ "${BUILD_TYPE}" = "l4t" ] ) && [ "${SKIP_DRIVERS}" = "false" ]; then
apt-get update && \
apt-get install -y --no-install-recommends \
software-properties-common pciutils
if [ "amd64" = "$TARGETARCH" ]; then
curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu${UBUNTU_VERSION}/x86_64/cuda-keyring_1.1-1_all.deb
fi
if [ "arm64" = "$TARGETARCH" ]; then
if [ "${CUDA_MAJOR_VERSION}" = "13" ]; then
curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu${UBUNTU_VERSION}/sbsa/cuda-keyring_1.1-1_all.deb
else
curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu${UBUNTU_VERSION}/arm64/cuda-keyring_1.1-1_all.deb
fi
fi
dpkg -i cuda-keyring_1.1-1_all.deb && \
rm -f cuda-keyring_1.1-1_all.deb && \
apt-get update && \
apt-get install -y --no-install-recommends \
cuda-nvcc-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
libcufft-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
libcurand-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
libcublas-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
libcusparse-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
libcusolver-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION}
if [ "${CUDA_MAJOR_VERSION}" = "13" ] && [ "arm64" = "$TARGETARCH" ]; then
apt-get install -y --no-install-recommends \
libcufile-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} libcudnn9-cuda-${CUDA_MAJOR_VERSION} cuda-cupti-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} libnvjitlink-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION}
fi
apt-get clean && \
rm -rf /var/lib/apt/lists/*
fi
EOT
# https://github.com/NVIDIA/Isaac-GR00T/issues/343
RUN <<EOT bash
if [ "${BUILD_TYPE}" = "cublas" ] && [ "${TARGETARCH}" = "arm64" ]; then
wget https://developer.download.nvidia.com/compute/cudss/0.6.0/local_installers/cudss-local-tegra-repo-ubuntu${UBUNTU_VERSION}-0.6.0_0.6.0-1_arm64.deb && \
dpkg -i cudss-local-tegra-repo-ubuntu${UBUNTU_VERSION}-0.6.0_0.6.0-1_arm64.deb && \
cp /var/cudss-local-tegra-repo-ubuntu${UBUNTU_VERSION}-0.6.0/cudss-*-keyring.gpg /usr/share/keyrings/ && \
apt-get update && apt-get -y install cudss cudss-cuda-${CUDA_MAJOR_VERSION} && \
wget https://developer.download.nvidia.com/compute/nvpl/25.5/local_installers/nvpl-local-repo-ubuntu${UBUNTU_VERSION}-25.5_1.0-1_arm64.deb && \
dpkg -i nvpl-local-repo-ubuntu${UBUNTU_VERSION}-25.5_1.0-1_arm64.deb && \
cp /var/nvpl-local-repo-ubuntu${UBUNTU_VERSION}-25.5/nvpl-*-keyring.gpg /usr/share/keyrings/ && \
apt-get update && apt-get install -y nvpl
fi
EOT
# If we are building with clblas support, we need the libraries for the builds
RUN if [ "${BUILD_TYPE}" = "clblas" ] && [ "${SKIP_DRIVERS}" = "false" ]; then \
apt-get update && \
apt-get install -y --no-install-recommends \
libclblast-dev && \
apt-get clean && \
rm -rf /var/lib/apt/lists/* \
; fi
RUN if [ "${BUILD_TYPE}" = "hipblas" ] && [ "${SKIP_DRIVERS}" = "false" ]; then \
apt-get update && \
apt-get install -y --no-install-recommends \
hipblas-dev \
rocblas-dev && \
apt-get clean && \
rm -rf /var/lib/apt/lists/* && \
# I have no idea why, but the ROCM lib packages don't trigger ldconfig after they install, which results in local-ai and others not being able
# to locate the libraries. We run ldconfig ourselves to work around this packaging deficiency
ldconfig \
; fi
RUN echo "TARGETARCH: $TARGETARCH"
# We need protoc installed, and the version in 22.04 is too old. We will create one as part installing the GRPC build below
# but that will also being in a newer version of absl which stablediffusion cannot compile with. This version of protoc is only
# here so that we can generate the grpc code for the stablediffusion build
RUN <<EOT bash
if [ "amd64" = "$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" = "$TARGETARCH" ]; then
curl -L -s https://github.com/protocolbuffers/protobuf/releases/download/v27.1/protoc-27.1-linux-aarch_64.zip -o protoc.zip && \
unzip -j -d /usr/local/bin protoc.zip bin/protoc && \
rm protoc.zip
fi
EOT
# Install CMake (the version in 22.04 is too old)
RUN <<EOT bash
if [ "${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-${CMAKE_VERSION} && ./configure && make && make install
else
apt-get update && \
apt-get install -y \
cmake && \
apt-get clean && \
rm -rf /var/lib/apt/lists/*
fi
EOT
COPY --from=grpc /opt/grpc /usr/local
COPY . /LocalAI
## Otherwise just run the normal build
RUN <<EOT bash
if [ "${TARGETARCH}" = "arm64" ] || [ "${BUILD_TYPE}" = "hipblas" ]; then \
cd /LocalAI/backend/cpp/llama-cpp && make llama-cpp-fallback && \
make llama-cpp-grpc && make llama-cpp-rpc-server; \
else \
cd /LocalAI/backend/cpp/llama-cpp && make llama-cpp-avx && \
make llama-cpp-avx2 && \
make llama-cpp-avx512 && \
make llama-cpp-fallback && \
make llama-cpp-grpc && \
make llama-cpp-rpc-server; \
fi
EOT
# Copy libraries using a script to handle architecture differences
RUN make -BC /LocalAI/backend/cpp/llama-cpp package
FROM scratch
# Copy all available binaries (the build process only creates the appropriate ones for the target architecture)
COPY --from=builder /LocalAI/backend/cpp/llama-cpp/package/. ./

View File

@@ -1,166 +0,0 @@
ARG BASE_IMAGE=ubuntu:22.04
FROM ${BASE_IMAGE} AS builder
ARG BACKEND=rerankers
ARG BUILD_TYPE
ENV BUILD_TYPE=${BUILD_TYPE}
ARG CUDA_MAJOR_VERSION
ARG CUDA_MINOR_VERSION
ARG SKIP_DRIVERS=false
ENV CUDA_MAJOR_VERSION=${CUDA_MAJOR_VERSION}
ENV CUDA_MINOR_VERSION=${CUDA_MINOR_VERSION}
ENV DEBIAN_FRONTEND=noninteractive
ARG TARGETARCH
ARG TARGETVARIANT
ARG UBUNTU_VERSION=2204
RUN apt-get update && \
apt-get install -y --no-install-recommends \
build-essential \
ccache \
ca-certificates \
espeak-ng \
curl \
libssl-dev \
git wget \
git-lfs \
unzip clang \
upx-ucl \
curl python3-pip \
python-is-python3 \
python3-dev llvm \
python3-venv make cmake && \
apt-get clean && \
rm -rf /var/lib/apt/lists/*
RUN <<EOT bash
if [ "${UBUNTU_VERSION}" = "2404" ]; then
pip install --break-system-packages --user --upgrade pip
else
pip install --upgrade pip
fi
EOT
# Cuda
ENV PATH=/usr/local/cuda/bin:${PATH}
# HipBLAS requirements
ENV PATH=/opt/rocm/bin:${PATH}
# Vulkan requirements
RUN <<EOT bash
if [ "${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" ] || [ "${BUILD_TYPE}" = "l4t" ] ) && [ "${SKIP_DRIVERS}" = "false" ]; then
apt-get update && \
apt-get install -y --no-install-recommends \
software-properties-common pciutils
if [ "amd64" = "$TARGETARCH" ]; then
curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu${UBUNTU_VERSION}/x86_64/cuda-keyring_1.1-1_all.deb
fi
if [ "arm64" = "$TARGETARCH" ]; then
if [ "${CUDA_MAJOR_VERSION}" = "13" ]; then
curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu${UBUNTU_VERSION}/sbsa/cuda-keyring_1.1-1_all.deb
else
curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu${UBUNTU_VERSION}/arm64/cuda-keyring_1.1-1_all.deb
fi
fi
dpkg -i cuda-keyring_1.1-1_all.deb && \
rm -f cuda-keyring_1.1-1_all.deb && \
apt-get update && \
apt-get install -y --no-install-recommends \
cuda-nvcc-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
libcufft-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
libcurand-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
libcublas-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
libcusparse-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
libcusolver-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION}
if [ "${CUDA_MAJOR_VERSION}" = "13" ] && [ "arm64" = "$TARGETARCH" ]; then
apt-get install -y --no-install-recommends \
libcufile-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} libcudnn9-cuda-${CUDA_MAJOR_VERSION} cuda-cupti-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} libnvjitlink-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION}
fi
apt-get clean && \
rm -rf /var/lib/apt/lists/*
fi
EOT
# https://github.com/NVIDIA/Isaac-GR00T/issues/343
RUN <<EOT bash
if [ "${BUILD_TYPE}" = "cublas" ] && [ "${TARGETARCH}" = "arm64" ]; then
wget https://developer.download.nvidia.com/compute/cudss/0.6.0/local_installers/cudss-local-tegra-repo-ubuntu${UBUNTU_VERSION}-0.6.0_0.6.0-1_arm64.deb && \
dpkg -i cudss-local-tegra-repo-ubuntu${UBUNTU_VERSION}-0.6.0_0.6.0-1_arm64.deb && \
cp /var/cudss-local-tegra-repo-ubuntu${UBUNTU_VERSION}-0.6.0/cudss-*-keyring.gpg /usr/share/keyrings/ && \
apt-get update && apt-get -y install cudss cudss-cuda-${CUDA_MAJOR_VERSION} && \
wget https://developer.download.nvidia.com/compute/nvpl/25.5/local_installers/nvpl-local-repo-ubuntu${UBUNTU_VERSION}-25.5_1.0-1_arm64.deb && \
dpkg -i nvpl-local-repo-ubuntu${UBUNTU_VERSION}-25.5_1.0-1_arm64.deb && \
cp /var/nvpl-local-repo-ubuntu${UBUNTU_VERSION}-25.5/nvpl-*-keyring.gpg /usr/share/keyrings/ && \
apt-get update && apt-get install -y nvpl
fi
EOT
# If we are building with clblas support, we need the libraries for the builds
RUN if [ "${BUILD_TYPE}" = "clblas" ] && [ "${SKIP_DRIVERS}" = "false" ]; then \
apt-get update && \
apt-get install -y --no-install-recommends \
libclblast-dev && \
apt-get clean && \
rm -rf /var/lib/apt/lists/* \
; fi
RUN if [ "${BUILD_TYPE}" = "hipblas" ] && [ "${SKIP_DRIVERS}" = "false" ]; then \
apt-get update && \
apt-get install -y --no-install-recommends \
hipblas-dev \
rocblas-dev && \
apt-get clean && \
rm -rf /var/lib/apt/lists/* && \
# I have no idea why, but the ROCM lib packages don't trigger ldconfig after they install, which results in local-ai and others not being able
# to locate the libraries. We run ldconfig ourselves to work around this packaging deficiency
ldconfig \
; fi
RUN if [ "${BUILD_TYPE}" = "hipblas" ]; then \
ln -s /opt/rocm-**/lib/llvm/lib/libomp.so /usr/lib/libomp.so \
; fi
# Install uv as a system package
RUN curl -LsSf https://astral.sh/uv/install.sh | UV_INSTALL_DIR=/usr/bin sh
ENV PATH="/root/.cargo/bin:${PATH}"
RUN curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh -s -- -y
# Install grpcio-tools (the version in 22.04 is too old)
RUN <<EOT bash
if [ "${UBUNTU_VERSION}" = "2404" ]; then
pip install --break-system-packages --user grpcio-tools==1.71.0 grpcio==1.71.0
else
pip install grpcio-tools==1.71.0 grpcio==1.71.0
fi
EOT
COPY python/${BACKEND} /${BACKEND}
COPY backend.proto /${BACKEND}/backend.proto
COPY python/common/ /${BACKEND}/common
RUN cd /${BACKEND} && PORTABLE_PYTHON=true make
FROM scratch
ARG BACKEND=rerankers
COPY --from=builder /${BACKEND}/ /

View File

@@ -1,213 +0,0 @@
# LocalAI Backend Architecture
This directory contains the core backend infrastructure for LocalAI, including the gRPC protocol definition, multi-language Dockerfiles, and language-specific backend implementations.
## Overview
LocalAI uses a unified gRPC-based architecture that allows different programming languages to implement AI backends while maintaining consistent interfaces and capabilities. The backend system supports multiple hardware acceleration targets and provides a standardized way to integrate various AI models and frameworks.
## Architecture Components
### 1. Protocol Definition (`backend.proto`)
The `backend.proto` file defines the gRPC service interface that all backends must implement. This ensures consistency across different language implementations and provides a contract for communication between LocalAI core and backend services.
#### Core Services
- **Text Generation**: `Predict`, `PredictStream` for LLM inference
- **Embeddings**: `Embedding` for text vectorization
- **Image Generation**: `GenerateImage` for stable diffusion and image models
- **Audio Processing**: `AudioTranscription`, `TTS`, `SoundGeneration`
- **Video Generation**: `GenerateVideo` for video synthesis
- **Object Detection**: `Detect` for computer vision tasks
- **Vector Storage**: `StoresSet`, `StoresGet`, `StoresFind` for RAG operations
- **Reranking**: `Rerank` for document relevance scoring
- **Voice Activity Detection**: `VAD` for audio segmentation
#### Key Message Types
- **`PredictOptions`**: Comprehensive configuration for text generation
- **`ModelOptions`**: Model loading and configuration parameters
- **`Result`**: Standardized response format
- **`StatusResponse`**: Backend health and memory usage information
### 2. Multi-Language Dockerfiles
The backend system provides language-specific Dockerfiles that handle the build environment and dependencies for different programming languages:
- `Dockerfile.python`
- `Dockerfile.golang`
- `Dockerfile.llama-cpp`
### 3. Language-Specific Implementations
#### Python Backends (`python/`)
- **transformers**: Hugging Face Transformers framework
- **vllm**: High-performance LLM inference
- **mlx**: Apple Silicon optimization
- **diffusers**: Stable Diffusion models
- **Audio**: bark, coqui, faster-whisper, kitten-tts
- **Vision**: mlx-vlm, rfdetr
- **Specialized**: rerankers, chatterbox, kokoro
#### Go Backends (`go/`)
- **whisper**: OpenAI Whisper speech recognition in Go with GGML cpp backend (whisper.cpp)
- **stablediffusion-ggml**: Stable Diffusion in Go with GGML Cpp backend
- **huggingface**: Hugging Face model integration
- **piper**: Text-to-speech synthesis Golang with C bindings using rhaspy/piper
- **bark-cpp**: Bark TTS models Golang with Cpp bindings
- **local-store**: Vector storage backend
#### C++ Backends (`cpp/`)
- **llama-cpp**: Llama.cpp integration
- **grpc**: GRPC utilities and helpers
## Hardware Acceleration Support
### CUDA (NVIDIA)
- **Versions**: CUDA 11.x, 12.x
- **Features**: cuBLAS, cuDNN, TensorRT optimization
- **Targets**: x86_64, ARM64 (Jetson)
### ROCm (AMD)
- **Features**: HIP, rocBLAS, MIOpen
- **Targets**: AMD GPUs with ROCm support
### Intel
- **Features**: oneAPI, Intel Extension for PyTorch
- **Targets**: Intel GPUs, XPUs, CPUs
### Vulkan
- **Features**: Cross-platform GPU acceleration
- **Targets**: Windows, Linux, Android, macOS
### Apple Silicon
- **Features**: MLX framework, Metal Performance Shaders
- **Targets**: M1/M2/M3 Macs
## Backend Registry (`index.yaml`)
The `index.yaml` file serves as a central registry for all available backends, providing:
- **Metadata**: Name, description, license, icons
- **Capabilities**: Hardware targets and optimization profiles
- **Tags**: Categorization for discovery
- **URLs**: Source code and documentation links
## Building Backends
### Prerequisites
- Docker with multi-architecture support
- Appropriate hardware drivers (CUDA, ROCm, etc.)
- Build tools (make, cmake, compilers)
### Build Commands
Example of build commands with Docker
```bash
# Build Python backend
docker build -f backend/Dockerfile.python \
--build-arg BACKEND=transformers \
--build-arg BUILD_TYPE=cublas12 \
--build-arg CUDA_MAJOR_VERSION=12 \
--build-arg CUDA_MINOR_VERSION=0 \
-t localai-backend-transformers .
# Build Go backend
docker build -f backend/Dockerfile.golang \
--build-arg BACKEND=whisper \
--build-arg BUILD_TYPE=cpu \
-t localai-backend-whisper .
# Build C++ backend
docker build -f backend/Dockerfile.llama-cpp \
--build-arg BACKEND=llama-cpp \
--build-arg BUILD_TYPE=cublas12 \
-t localai-backend-llama-cpp .
```
For ARM64/Mac builds, docker can't be used, and the makefile in the respective backend has to be used.
### Build Types
- **`cpu`**: CPU-only optimization
- **`cublas11`**: CUDA 11.x with cuBLAS
- **`cublas12`**: CUDA 12.x with cuBLAS
- **`hipblas`**: ROCm with rocBLAS
- **`intel`**: Intel oneAPI optimization
- **`vulkan`**: Vulkan-based acceleration
- **`metal`**: Apple Metal optimization
## Backend Development
### Creating a New Backend
1. **Choose Language**: Select Python, Go, or C++ based on requirements
2. **Implement Interface**: Implement the gRPC service defined in `backend.proto`
3. **Add Dependencies**: Create appropriate requirements files
4. **Configure Build**: Set up Dockerfile and build scripts
5. **Register Backend**: Add entry to `index.yaml`
6. **Test Integration**: Verify gRPC communication and functionality
### Backend Structure
```
backend-name/
├── backend.py/go/cpp # Main implementation
├── requirements.txt # Dependencies
├── Dockerfile # Build configuration
├── install.sh # Installation script
├── run.sh # Execution script
├── test.sh # Test script
└── README.md # Backend documentation
```
### Required gRPC Methods
At minimum, backends must implement:
- `Health()` - Service health check
- `LoadModel()` - Model loading and initialization
- `Predict()` - Main inference endpoint
- `Status()` - Backend status and metrics
## Integration with LocalAI Core
Backends communicate with LocalAI core through gRPC:
1. **Service Discovery**: Core discovers available backends
2. **Model Loading**: Core requests model loading via `LoadModel`
3. **Inference**: Core sends requests via `Predict` or specialized endpoints
4. **Streaming**: Core handles streaming responses for real-time generation
5. **Monitoring**: Core tracks backend health and performance
## Performance Optimization
### Memory Management
- **Model Caching**: Efficient model loading and caching
- **Batch Processing**: Optimize for multiple concurrent requests
- **Memory Pinning**: GPU memory optimization for CUDA/ROCm
### Hardware Utilization
- **Multi-GPU**: Support for tensor parallelism
- **Mixed Precision**: FP16/BF16 for memory efficiency
- **Kernel Fusion**: Optimized CUDA/ROCm kernels
## Troubleshooting
### Common Issues
1. **GRPC Connection**: Verify backend service is running and accessible
2. **Model Loading**: Check model paths and dependencies
3. **Hardware Detection**: Ensure appropriate drivers and libraries
4. **Memory Issues**: Monitor GPU memory usage and model sizes
## Contributing
When contributing to the backend system:
1. **Follow Protocol**: Implement the exact gRPC interface
2. **Add Tests**: Include comprehensive test coverage
3. **Document**: Provide clear usage examples
4. **Optimize**: Consider performance and resource usage
5. **Validate**: Test across different hardware targets

View File

@@ -14,57 +14,15 @@ service Backend {
rpc PredictStream(PredictOptions) returns (stream Reply) {}
rpc Embedding(PredictOptions) returns (EmbeddingResult) {}
rpc GenerateImage(GenerateImageRequest) returns (Result) {}
rpc GenerateVideo(GenerateVideoRequest) 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) {}
rpc Detect(DetectOptions) returns (DetectResponse) {}
rpc StoresSet(StoresSetOptions) returns (Result) {}
rpc StoresDelete(StoresDeleteOptions) returns (Result) {}
rpc StoresGet(StoresGetOptions) returns (StoresGetResult) {}
rpc StoresFind(StoresFindOptions) returns (StoresFindResult) {}
rpc Rerank(RerankRequest) returns (RerankResult) {}
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 {
string query = 1;
repeated string documents = 2;
int32 top_n = 3;
}
message RerankResult {
Usage usage = 1;
repeated DocumentResult results = 2;
}
message Usage {
int32 total_tokens = 1;
int32 prompt_tokens = 2;
}
message DocumentResult {
int32 index = 1;
string text = 2;
float relevance_score = 3;
}
message StoresKey {
@@ -149,30 +107,11 @@ message PredictOptions {
string NegativePrompt = 40;
int32 NDraft = 41;
repeated string Images = 42;
bool UseTokenizerTemplate = 43;
repeated Message Messages = 44;
repeated string Videos = 45;
repeated string Audios = 46;
string CorrelationId = 47;
string Tools = 48; // JSON array of available tools/functions for tool calling
string ToolChoice = 49; // JSON string or object specifying tool choice behavior
int32 Logprobs = 50; // Number of top logprobs to return (maps to OpenAI logprobs parameter)
int32 TopLogprobs = 51; // Number of top logprobs to return per token (maps to OpenAI top_logprobs parameter)
}
// The response message containing the result
message Reply {
bytes message = 1;
int32 tokens = 2;
int32 prompt_tokens = 3;
double timing_prompt_processing = 4;
double timing_token_generation = 5;
bytes audio = 6;
bytes logprobs = 7; // JSON-encoded logprobs data matching OpenAI format
}
message GrammarTrigger {
string word = 1;
}
message ModelOptions {
@@ -191,13 +130,18 @@ message ModelOptions {
string MainGPU = 13;
string TensorSplit = 14;
int32 Threads = 15;
string LibrarySearchPath = 16;
float RopeFreqBase = 17;
float RopeFreqScale = 18;
float RMSNormEps = 19;
int32 NGQA = 20;
string ModelFile = 21;
// AutoGPTQ
string Device = 22;
bool UseTriton = 23;
string ModelBaseName = 24;
bool UseFastTokenizer = 25;
// Diffusers
string PipelineType = 26;
@@ -229,13 +173,6 @@ message ModelOptions {
bool EnforceEager = 52;
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;
@@ -246,25 +183,6 @@ message ModelOptions {
float YarnBetaSlow = 47;
string Type = 49;
string 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;
bool Reranking = 71;
repeated string Overrides = 72;
}
message Result {
@@ -280,9 +198,6 @@ message TranscriptRequest {
string dst = 2;
string language = 3;
uint32 threads = 4;
bool translate = 5;
bool diarize = 6;
string prompt = 7;
}
message TranscriptResult {
@@ -312,24 +227,6 @@ message GenerateImageRequest {
// Diffusers
string EnableParameters = 10;
int32 CLIPSkip = 11;
// Reference images for models that support them (e.g., Flux Kontext)
repeated string ref_images = 12;
}
message GenerateVideoRequest {
string prompt = 1;
string negative_prompt = 2; // Negative prompt for video generation
string start_image = 3; // Path or base64 encoded image for the start frame
string end_image = 4; // Path or base64 encoded image for the end frame
int32 width = 5;
int32 height = 6;
int32 num_frames = 7; // Number of frames to generate
int32 fps = 8; // Frames per second
int32 seed = 9;
float cfg_scale = 10; // Classifier-free guidance scale
int32 step = 11; // Number of inference steps
string dst = 12; // Output path for the generated video
}
message TTSRequest {
@@ -337,31 +234,6 @@ 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 {
@@ -384,30 +256,3 @@ message StatusResponse {
State state = 1;
MemoryUsageData memory = 2;
}
message Message {
string role = 1;
string content = 2;
// Optional fields for OpenAI-compatible message format
string name = 3; // Tool name (for tool messages)
string tool_call_id = 4; // Tool call ID (for tool messages)
string reasoning_content = 5; // Reasoning content (for thinking models)
string tool_calls = 6; // Tool calls as JSON string (for assistant messages with tool calls)
}
message DetectOptions {
string src = 1;
}
message Detection {
float x = 1;
float y = 2;
float width = 3;
float height = 4;
float confidence = 5;
string class_name = 6;
}
message DetectResponse {
repeated Detection Detections = 1;
}

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

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

View File

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

View File

@@ -1,166 +0,0 @@
LLAMA_VERSION?=5b6c9bc0f3c8f55598b9999b65aff7ce4119bc15
LLAMA_REPO?=https://github.com/ggerganov/llama.cpp
CMAKE_ARGS?=
BUILD_TYPE?=
NATIVE?=false
ONEAPI_VARS?=/opt/intel/oneapi/setvars.sh
TARGET?=--target grpc-server
JOBS?=$(shell nproc)
# 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
CURRENT_MAKEFILE_DIR := $(dir $(abspath $(lastword $(MAKEFILE_LIST))))
ifeq ($(NATIVE),false)
CMAKE_ARGS+=-DGGML_NATIVE=OFF -DLLAMA_OPENSSL=OFF
endif
# 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)
ROCM_HOME ?= /opt/rocm
ROCM_PATH ?= /opt/rocm
export CXX=$(ROCM_HOME)/llvm/bin/clang++
export CC=$(ROCM_HOME)/llvm/bin/clang
AMDGPU_TARGETS?=gfx803,gfx900,gfx906,gfx908,gfx90a,gfx942,gfx1010,gfx1030,gfx1032,gfx1100,gfx1101,gfx1102,gfx1200,gfx1201
CMAKE_ARGS+=-DGGML_HIP=ON -DAMDGPU_TARGETS=$(AMDGPU_TARGETS)
else ifeq ($(BUILD_TYPE),vulkan)
CMAKE_ARGS+=-DGGML_VULKAN=1
else ifeq ($(OS),Darwin)
ifeq ($(BUILD_TYPE),)
BUILD_TYPE=metal
endif
ifneq ($(BUILD_TYPE),metal)
CMAKE_ARGS+=-DGGML_METAL=OFF
else
CMAKE_ARGS+=-DGGML_METAL=ON
CMAKE_ARGS+=-DGGML_METAL_EMBED_LIBRARY=ON
CMAKE_ARGS+=-DGGML_METAL_USE_BF16=ON
CMAKE_ARGS+=-DGGML_OPENMP=OFF
endif
TARGET+=--target ggml-metal
endif
ifeq ($(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
endif
ifeq ($(BUILD_TYPE),sycl_f32)
CMAKE_ARGS+=-DGGML_SYCL=ON \
-DCMAKE_C_COMPILER=icx \
-DCMAKE_CXX_COMPILER=icpx \
-DCMAKE_CXX_FLAGS="-fsycl"
endif
INSTALLED_PACKAGES=$(CURDIR)/../grpc/installed_packages
INSTALLED_LIB_CMAKE=$(INSTALLED_PACKAGES)/lib/cmake
ADDED_CMAKE_ARGS=-Dabsl_DIR=${INSTALLED_LIB_CMAKE}/absl \
-DProtobuf_DIR=${INSTALLED_LIB_CMAKE}/protobuf \
-Dutf8_range_DIR=${INSTALLED_LIB_CMAKE}/utf8_range \
-DgRPC_DIR=${INSTALLED_LIB_CMAKE}/grpc \
-DCMAKE_CXX_STANDARD_INCLUDE_DIRECTORIES=${INSTALLED_PACKAGES}/include
build-llama-cpp-grpc-server:
# Conditionally build grpc for the llama backend to use if needed
ifdef BUILD_GRPC_FOR_BACKEND_LLAMA
$(MAKE) -C ../../grpc build
_PROTOBUF_PROTOC=${INSTALLED_PACKAGES}/bin/proto \
_GRPC_CPP_PLUGIN_EXECUTABLE=${INSTALLED_PACKAGES}/bin/grpc_cpp_plugin \
PATH="${INSTALLED_PACKAGES}/bin:${PATH}" \
CMAKE_ARGS="${CMAKE_ARGS} ${ADDED_CMAKE_ARGS}" \
LLAMA_VERSION=$(LLAMA_VERSION) \
$(MAKE) -C $(CURRENT_MAKEFILE_DIR)/../$(VARIANT) grpc-server
else
echo "BUILD_GRPC_FOR_BACKEND_LLAMA is not defined."
LLAMA_VERSION=$(LLAMA_VERSION) $(MAKE) -C $(CURRENT_MAKEFILE_DIR)/../$(VARIANT) grpc-server
endif
llama-cpp-avx2: llama.cpp
cp -rf $(CURRENT_MAKEFILE_DIR)/../llama-cpp $(CURRENT_MAKEFILE_DIR)/../llama-cpp-avx2-build
$(MAKE) -C $(CURRENT_MAKEFILE_DIR)/../llama-cpp-avx2-build 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-cpp-avx2-build" build-llama-cpp-grpc-server
cp -rfv $(CURRENT_MAKEFILE_DIR)/../llama-cpp-avx2-build/grpc-server llama-cpp-avx2
llama-cpp-avx512: llama.cpp
cp -rf $(CURRENT_MAKEFILE_DIR)/../llama-cpp $(CURRENT_MAKEFILE_DIR)/../llama-cpp-avx512-build
$(MAKE) -C $(CURRENT_MAKEFILE_DIR)/../llama-cpp-avx512-build 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-cpp-avx512-build" build-llama-cpp-grpc-server
cp -rfv $(CURRENT_MAKEFILE_DIR)/../llama-cpp-avx512-build/grpc-server llama-cpp-avx512
llama-cpp-avx: llama.cpp
cp -rf $(CURRENT_MAKEFILE_DIR)/../llama-cpp $(CURRENT_MAKEFILE_DIR)/../llama-cpp-avx-build
$(MAKE) -C $(CURRENT_MAKEFILE_DIR)/../llama-cpp-avx-build 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-cpp-avx-build" build-llama-cpp-grpc-server
cp -rfv $(CURRENT_MAKEFILE_DIR)/../llama-cpp-avx-build/grpc-server llama-cpp-avx
llama-cpp-fallback: llama.cpp
cp -rf $(CURRENT_MAKEFILE_DIR)/../llama-cpp $(CURRENT_MAKEFILE_DIR)/../llama-cpp-fallback-build
$(MAKE) -C $(CURRENT_MAKEFILE_DIR)/../llama-cpp-fallback-build 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-cpp-fallback-build" build-llama-cpp-grpc-server
cp -rfv $(CURRENT_MAKEFILE_DIR)/../llama-cpp-fallback-build/grpc-server llama-cpp-fallback
llama-cpp-grpc: llama.cpp
cp -rf $(CURRENT_MAKEFILE_DIR)/../llama-cpp $(CURRENT_MAKEFILE_DIR)/../llama-cpp-grpc-build
$(MAKE) -C $(CURRENT_MAKEFILE_DIR)/../llama-cpp-grpc-build 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-cpp-grpc-build" build-llama-cpp-grpc-server
cp -rfv $(CURRENT_MAKEFILE_DIR)/../llama-cpp-grpc-build/grpc-server llama-cpp-grpc
llama-cpp-rpc-server: llama-cpp-grpc
cp -rf $(CURRENT_MAKEFILE_DIR)/../llama-cpp-grpc-build/llama.cpp/build/bin/rpc-server llama-cpp-rpc-server
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
llama.cpp/tools/grpc-server: llama.cpp
mkdir -p llama.cpp/tools/grpc-server
bash prepare.sh
rebuild:
bash prepare.sh
rm -rf grpc-server
$(MAKE) grpc-server
package:
bash package.sh
purge:
rm -rf llama.cpp/build
rm -rf llama.cpp/tools/grpc-server
rm -rf grpc-server
clean: purge
rm -rf llama.cpp
grpc-server: llama.cpp llama.cpp/tools/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 -j $(JOBS) $(TARGET)"
else
+cd llama.cpp && mkdir -p build && cd build && cmake .. $(CMAKE_ARGS) && cmake --build . --config Release -j $(JOBS) $(TARGET)
endif
cp llama.cpp/build/bin/grpc-server .

View File

File diff suppressed because it is too large Load Diff

View File

@@ -1,42 +0,0 @@
#!/bin/bash
# Script to copy the appropriate libraries based on architecture
# This script is used in the final stage of the Dockerfile
set -e
CURDIR=$(dirname "$(realpath $0)")
# Create lib directory
mkdir -p $CURDIR/package/lib
cp -avrf $CURDIR/llama-cpp-* $CURDIR/package/
cp -rfv $CURDIR/run.sh $CURDIR/package/
# Detect architecture and copy appropriate libraries
if [ -f "/lib64/ld-linux-x86-64.so.2" ]; then
# x86_64 architecture
echo "Detected x86_64 architecture, copying x86_64 libraries..."
cp -arfLv /lib64/ld-linux-x86-64.so.2 $CURDIR/package/lib/ld.so
cp -arfLv /lib/x86_64-linux-gnu/libc.so.6 $CURDIR/package/lib/libc.so.6
cp -arfLv /lib/x86_64-linux-gnu/libgcc_s.so.1 $CURDIR/package/lib/libgcc_s.so.1
cp -arfLv /lib/x86_64-linux-gnu/libstdc++.so.6 $CURDIR/package/lib/libstdc++.so.6
cp -arfLv /lib/x86_64-linux-gnu/libm.so.6 $CURDIR/package/lib/libm.so.6
cp -arfLv /lib/x86_64-linux-gnu/libgomp.so.1 $CURDIR/package/lib/libgomp.so.1
elif [ -f "/lib/ld-linux-aarch64.so.1" ]; then
# ARM64 architecture
echo "Detected ARM64 architecture, copying ARM64 libraries..."
cp -arfLv /lib/ld-linux-aarch64.so.1 $CURDIR/package/lib/ld.so
cp -arfLv /lib/aarch64-linux-gnu/libc.so.6 $CURDIR/package/lib/libc.so.6
cp -arfLv /lib/aarch64-linux-gnu/libgcc_s.so.1 $CURDIR/package/lib/libgcc_s.so.1
cp -arfLv /lib/aarch64-linux-gnu/libstdc++.so.6 $CURDIR/package/lib/libstdc++.so.6
cp -arfLv /lib/aarch64-linux-gnu/libm.so.6 $CURDIR/package/lib/libm.so.6
cp -arfLv /lib/aarch64-linux-gnu/libgomp.so.1 $CURDIR/package/lib/libgomp.so.1
else
echo "Error: Could not detect architecture"
exit 1
fi
echo "Packaging completed successfully"
ls -liah $CURDIR/package/
ls -liah $CURDIR/package/lib/

View File

@@ -1,31 +0,0 @@
#!/bin/bash
## Patches
## Apply patches from the `patches` directory
if [ -d "patches" ]; then
for patch in $(ls patches); do
echo "Applying patch $patch"
patch -d llama.cpp/ -p1 < patches/$patch
done
fi
set -e
for file in $(ls llama.cpp/tools/server/); do
cp -rfv llama.cpp/tools/server/$file llama.cpp/tools/grpc-server/
done
cp -r CMakeLists.txt llama.cpp/tools/grpc-server/
cp -r grpc-server.cpp llama.cpp/tools/grpc-server/
cp -rfv llama.cpp/vendor/nlohmann/json.hpp llama.cpp/tools/grpc-server/
cp -rfv llama.cpp/vendor/cpp-httplib/httplib.h llama.cpp/tools/grpc-server/
set +e
if grep -q "grpc-server" llama.cpp/tools/CMakeLists.txt; then
echo "grpc-server already added"
else
echo "add_subdirectory(grpc-server)" >> llama.cpp/tools/CMakeLists.txt
fi
set -e

View File

@@ -1,62 +0,0 @@
#!/bin/bash
set -ex
# Get the absolute current dir where the script is located
CURDIR=$(dirname "$(realpath $0)")
cd /
echo "CPU info:"
grep -e "model\sname" /proc/cpuinfo | head -1
grep -e "flags" /proc/cpuinfo | head -1
BINARY=llama-cpp-fallback
if grep -q -e "\savx\s" /proc/cpuinfo ; then
echo "CPU: AVX found OK"
if [ -e $CURDIR/llama-cpp-avx ]; then
BINARY=llama-cpp-avx
fi
fi
if grep -q -e "\savx2\s" /proc/cpuinfo ; then
echo "CPU: AVX2 found OK"
if [ -e $CURDIR/llama-cpp-avx2 ]; then
BINARY=llama-cpp-avx2
fi
fi
# Check avx 512
if grep -q -e "\savx512f\s" /proc/cpuinfo ; then
echo "CPU: AVX512F found OK"
if [ -e $CURDIR/llama-cpp-avx512 ]; then
BINARY=llama-cpp-avx512
fi
fi
if [ -n "$LLAMACPP_GRPC_SERVERS" ]; then
if [ -e $CURDIR/llama-cpp-grpc ]; then
BINARY=llama-cpp-grpc
fi
fi
# Extend ld library path with the dir where this script is located/lib
if [ "$(uname)" == "Darwin" ]; then
export DYLD_LIBRARY_PATH=$CURDIR/lib:$DYLD_LIBRARY_PATH
#export DYLD_FALLBACK_LIBRARY_PATH=$CURDIR/lib:$DYLD_FALLBACK_LIBRARY_PATH
else
export LD_LIBRARY_PATH=$CURDIR/lib:$LD_LIBRARY_PATH
fi
# If there is a lib/ld.so, use it
if [ -f $CURDIR/lib/ld.so ]; then
echo "Using lib/ld.so"
echo "Using binary: $BINARY"
exec $CURDIR/lib/ld.so $CURDIR/$BINARY "$@"
fi
echo "Using binary: $BINARY"
exec $CURDIR/$BINARY "$@"
# We should never reach this point, however just in case we do, run fallback
exec $CURDIR/llama-cpp-fallback "$@"

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