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Author SHA1 Message Date
Ettore Di Giacinto
27d7ada8dd feat(l4t): add support for extras images
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2025-02-06 11:53:07 +01:00
890 changed files with 54732 additions and 335194 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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@@ -0,0 +1,23 @@
meta {
name: musicgen
type: http
seq: 1
}
post {
url: {{PROTOCOL}}{{HOST}}:{{PORT}}/v1/sound-generation
body: json
auth: none
}
headers {
Content-Type: application/json
}
body:json {
{
"model_id": "facebook/musicgen-small",
"text": "Exciting 80s Newscast Interstitial",
"duration_seconds": 8
}
}

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@@ -0,0 +1,17 @@
meta {
name: backend monitor
type: http
seq: 4
}
get {
url: {{PROTOCOL}}{{HOST}}:{{PORT}}/backend/monitor
body: json
auth: none
}
body:json {
{
"model": "{{DEFAULT_MODEL}}"
}
}

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@@ -0,0 +1,21 @@
meta {
name: backend-shutdown
type: http
seq: 3
}
post {
url: {{PROTOCOL}}{{HOST}}:{{PORT}}/backend/shutdown
body: json
auth: none
}
headers {
Content-Type: application/json
}
body:json {
{
"model": "{{DEFAULT_MODEL}}"
}
}

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@@ -0,0 +1,5 @@
{
"version": "1",
"name": "LocalAI Test Requests",
"type": "collection"
}

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@@ -0,0 +1,6 @@
vars {
HOST: localhost
PORT: 8080
DEFAULT_MODEL: gpt-3.5-turbo
PROTOCOL: http://
}

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@@ -0,0 +1,11 @@
meta {
name: get models list
type: http
seq: 2
}
get {
url: {{PROTOCOL}}{{HOST}}:{{PORT}}/models
body: none
auth: none
}

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@@ -0,0 +1,25 @@
meta {
name: Generate image
type: http
seq: 1
}
post {
url: {{PROTOCOL}}{{HOST}}:{{PORT}}/v1/images/generations
body: json
auth: none
}
headers {
Content-Type: application/json
}
body:json {
{
"prompt": "<positive prompt>|<negative prompt>",
"model": "model-name",
"step": 51,
"size": "1024x1024",
"image": ""
}
}

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@@ -0,0 +1,24 @@
meta {
name: -completions
type: http
seq: 4
}
post {
url: {{PROTOCOL}}{{HOST}}:{{PORT}}/completions
body: json
auth: none
}
headers {
Content-Type: application/json
}
body:json {
{
"model": "{{DEFAULT_MODEL}}",
"prompt": "function downloadFile(string url, string outputPath) {",
"max_tokens": 256,
"temperature": 0.5
}
}

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@@ -0,0 +1,23 @@
meta {
name: -edits
type: http
seq: 5
}
post {
url: {{PROTOCOL}}{{HOST}}:{{PORT}}/edits
body: json
auth: none
}
headers {
Content-Type: application/json
}
body:json {
{
"model": "{{DEFAULT_MODEL}}",
"input": "What day of the wek is it?",
"instruction": "Fix the spelling mistakes"
}
}

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@@ -0,0 +1,22 @@
meta {
name: -embeddings
type: http
seq: 6
}
post {
url: {{PROTOCOL}}{{HOST}}:{{PORT}}/embeddings
body: json
auth: none
}
headers {
Content-Type: application/json
}
body:json {
{
"model": "{{DEFAULT_MODEL}}",
"input": "A STRANGE GAME.\nTHE ONLY WINNING MOVE IS NOT TO PLAY.\n\nHOW ABOUT A NICE GAME OF CHESS?"
}
}

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@@ -0,0 +1,30 @@
meta {
name: chat completion -simple- 1 message-
type: http
seq: 4
}
post {
url: {{PROTOCOL}}{{HOST}}:{{PORT}}/chat/completions
body: json
auth: none
}
headers {
Content-Type: application/json
}
body:json {
{
"model": "{{DEFAULT_MODEL}}",
"messages": [
{
"role": "user",
"content": "How could one use friction to cook an egg?"
}
],
"max_tokens": 256,
"temperature": 0.2,
"grammar": ""
}
}

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@@ -0,0 +1,29 @@
meta {
name: chat-completions -long-
type: http
seq: 5
}
post {
url: {{PROTOCOL}}{{HOST}}:{{PORT}}/chat/completions
body: json
auth: none
}
headers {
Content-Type: application/json
}
body:json {
{
"model": "{{DEFAULT_MODEL}}",
"messages": [{"role": "system", "content": "You are a helpful, intelligent pirate assistant. Always answer as helpfully as possible, while being a pirate and using pirate language. If a question does not make any sense, or is not factually coherent, explain why instead of answering something not correct. If you don't know the answer to a question, please don't share false information."},
{"role": "user", "content": "How could one use electricity to cook an egg?"},
{"role": "assistant",
"content": "Shiver me timbers! Using electricity to cook an egg? Well, matey, I reckon that be a right curious idea! *adjusts spectacles* Now, I ain't sure if this be possible, but I'll do me best to help ye out.\n\nFirst things first, ye gotta understand that electricity be a powerful force, and it can't just cook an egg on its own. Ye see, electricity be like a mighty wind that can make things happen, but it needs somethin' to work with. So, if ye want to use electricity to cook an egg, ye gotta find a way to harness that power and make it do the cookin'.\n\nNow, I know what ye might be thinkin': \"How do I harness the power of electricity to cook an egg?\" Well, matey, there be a few ways to do it. One way be to use a special device called an \"electric frying pan.\" This be a pan that has a built-in heating element that gets hot when ye plug it into a wall socket. When the element gets hot, ye can crack an egg into the pan and watch as it cook"
},
{"role": "user", "content": "I don't have one of those, just a raw wire and plenty of power! How do we get it done?"}],
"max_tokens": 1024,
"temperature": 0.5
}
}

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@@ -0,0 +1,25 @@
meta {
name: chat-completions -stream-
type: http
seq: 6
}
post {
url: {{PROTOCOL}}{{HOST}}:{{PORT}}/chat/completions
body: json
auth: none
}
headers {
Content-Type: application/json
}
body:json {
{
"model": "{{DEFAULT_MODEL}}",
"messages": [{"role": "user", "content": "Explain how I can set sail on the ocean using only power generated by seagulls?"}],
"max_tokens": 256,
"temperature": 0.9,
"stream": true
}
}

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@@ -0,0 +1,22 @@
meta {
name: add model gallery
type: http
seq: 10
}
post {
url: {{PROTOCOL}}{{HOST}}:{{PORT}}/models/galleries
body: json
auth: none
}
headers {
Content-Type: application/json
}
body:json {
{
"url": "file:///home/dave/projects/model-gallery/huggingface/TheBloke__CodeLlama-7B-Instruct-GGML.yaml",
"name": "test"
}
}

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@@ -0,0 +1,21 @@
meta {
name: delete model gallery
type: http
seq: 11
}
delete {
url: {{PROTOCOL}}{{HOST}}:{{PORT}}/models/galleries
body: json
auth: none
}
headers {
Content-Type: application/json
}
body:json {
{
"name": "test"
}
}

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@@ -0,0 +1,11 @@
meta {
name: list MODELS in galleries
type: http
seq: 7
}
get {
url: {{PROTOCOL}}{{HOST}}:{{PORT}}/models/available
body: none
auth: none
}

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@@ -0,0 +1,11 @@
meta {
name: list model GALLERIES
type: http
seq: 8
}
get {
url: {{PROTOCOL}}{{HOST}}:{{PORT}}/models/galleries
body: none
auth: none
}

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@@ -0,0 +1,11 @@
meta {
name: model delete
type: http
seq: 7
}
post {
url: {{PROTOCOL}}{{HOST}}:{{PORT}}/models/galleries
body: none
auth: none
}

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@@ -0,0 +1,21 @@
meta {
name: model gallery apply -gist-
type: http
seq: 12
}
post {
url: {{PROTOCOL}}{{HOST}}:{{PORT}}/models/apply
body: json
auth: none
}
headers {
Content-Type: application/json
}
body:json {
{
"id": "TheBloke__CodeLlama-7B-Instruct-GGML__codellama-7b-instruct.ggmlv3.Q2_K.bin"
}
}

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@@ -0,0 +1,22 @@
meta {
name: model gallery apply
type: http
seq: 9
}
post {
url: {{PROTOCOL}}{{HOST}}:{{PORT}}/models/apply
body: json
auth: none
}
headers {
Content-Type: application/json
}
body:json {
{
"id": "dave@TheBloke__CodeLlama-7B-Instruct-GGML__codellama-7b-instruct.ggmlv3.Q3_K_S.bin",
"name": "codellama7b"
}
}

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@@ -0,0 +1,16 @@
meta {
name: transcribe
type: http
seq: 1
}
post {
url: {{PROTOCOL}}{{HOST}}:{{PORT}}/v1/audio/transcriptions
body: multipartForm
auth: none
}
body:multipart-form {
file: @file(transcription/gb1.ogg)
model: whisper-1
}

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@@ -0,0 +1,22 @@
meta {
name: -tts
type: http
seq: 2
}
post {
url: {{PROTOCOL}}{{HOST}}:{{PORT}}/tts
body: json
auth: none
}
headers {
Content-Type: application/json
}
body:json {
{
"model": "{{DEFAULT_MODEL}}",
"input": "A STRANGE GAME.\nTHE ONLY WINNING MOVE IS NOT TO PLAY.\n\nHOW ABOUT A NICE GAME OF CHESS?"
}
}

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@@ -0,0 +1,23 @@
meta {
name: musicgen
type: http
seq: 2
}
post {
url: {{PROTOCOL}}{{HOST}}:{{PORT}}/tts
body: json
auth: none
}
headers {
Content-Type: application/json
}
body:json {
{
"backend": "transformers",
"model": "facebook/musicgen-small",
"input": "80s Synths playing Jazz"
}
}

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@@ -2,6 +2,9 @@
cd /workspace
# Grab the pre-stashed backend assets to avoid build issues
cp -r /build/backend-assets /workspace/backend-assets
# Ensures generated source files are present upon load
make prepare

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@@ -4,6 +4,10 @@ services:
context: ..
dockerfile: Dockerfile
target: devcontainer
args:
- FFMPEG=true
- IMAGE_TYPE=extras
- GO_TAGS=p2p tts
env_file:
- ../.env
ports:

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@@ -3,13 +3,7 @@
.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*
@@ -20,4 +14,4 @@ __pycache__
# backend virtual environments
**/venv
backend/python/**/source
backend/python/**/source

19
.env
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@@ -29,8 +29,21 @@
## Enable/Disable single backend (useful if only one GPU is available)
# LOCALAI_SINGLE_ACTIVE_BACKEND=true
# Forces shutdown of the backends if busy (only if LOCALAI_SINGLE_ACTIVE_BACKEND is set)
# LOCALAI_FORCE_BACKEND_SHUTDOWN=true
## Specify a build type. Available: cublas, openblas, clblas.
## cuBLAS: This is a GPU-accelerated version of the complete standard BLAS (Basic Linear Algebra Subprograms) library. It's provided by Nvidia and is part of their CUDA toolkit.
## OpenBLAS: This is an open-source implementation of the BLAS library that aims to provide highly optimized code for various platforms. It includes support for multi-threading and can be compiled to use hardware-specific features for additional performance. OpenBLAS can run on many kinds of hardware, including CPUs from Intel, AMD, and ARM.
## 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: p2p, tts
## p2p: enable distributed inferencing
## tts: enables text-to-speech with go-piper
## (requires REBUILD=true)
#
# GO_TAGS=p2p
## Path where to store generated images
# LOCALAI_IMAGE_PATH=/tmp/generated/images
@@ -60,7 +73,7 @@
### 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
# https://github.com/ggerganov/llama.cpp/blob/master/examples/rpc/README.md
# LLAMACPP_GRPC_SERVERS=""
### Enable to run parallel requests

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@@ -3,20 +3,15 @@ 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?=" $FILE | cut -d'=' -f2)"
CURRENT_COMMIT="$(grep -m1 "^$VAR?=" Makefile | cut -d'=' -f2)"
set -e
sed -i $FILE -e "s/$VAR?=.*/$VAR?=$LAST_COMMIT/"
sed -i Makefile -e "s/$VAR?=.*/$VAR?=$LAST_COMMIT/"
if [ -z "$CURRENT_COMMIT" ]; then
echo "Could not find $VAR in Makefile."

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@@ -29,6 +29,10 @@ updates:
schedule:
# Check for updates to GitHub Actions every weekday
interval: "weekly"
- package-ecosystem: "pip"
directory: "/backend/python/autogptq"
schedule:
interval: "weekly"
- package-ecosystem: "pip"
directory: "/backend/python/bark"
schedule:
@@ -61,6 +65,10 @@ updates:
directory: "/backend/python/openvoice"
schedule:
interval: "weekly"
- package-ecosystem: "pip"
directory: "/backend/python/parler-tts"
schedule:
interval: "weekly"
- package-ecosystem: "pip"
directory: "/backend/python/rerankers"
schedule:

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@@ -1,445 +0,0 @@
package main
import (
"context"
"encoding/json"
"fmt"
"io"
"net/http"
"os"
"regexp"
"slices"
"strings"
"github.com/ghodss/yaml"
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"))
}
type galleryModel struct {
Name string `yaml:"name"`
Urls []string `yaml:"urls"`
}
// 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)
}
var galleryModels []galleryModel
err = yaml.Unmarshal(content, &galleryModels)
if err != nil {
return false, fmt.Errorf("failed to unmarshal %s: %w", indexPath, err)
}
for _, galleryModel := range galleryModels {
if slices.Contains(galleryModel.Urls, modelID) {
return true, nil
}
}
return false, 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) {
if len(searchResult.Models) == 1 {
return searchResult.Models, nil
}
// 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

@@ -1,383 +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)
var models []ProcessedModel
if len(result.Models) > 1 {
fmt.Println("More than one model found (", len(result.Models), "), using AI agent to select the most interesting models")
for _, model := range result.Models {
fmt.Println("Model: ", model.ModelID)
}
// 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
}
} else if len(result.Models) == 1 {
models = result.Models
fmt.Println("Only one model found, using it directly")
}
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 {
fmt.Printf(" Warning: Failed to get real readme: %v\n", err)
}
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"},
},
},
}
}

2
.github/labeler.yml vendored
View File

@@ -1,4 +1,4 @@
enhancement:
enhancements:
- head-branch: ['^feature', 'feature']
dependencies:

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@@ -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

@@ -1,41 +1,39 @@
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: "ggerganov/llama.cpp"
variable: "CPPLLAMA_VERSION"
branch: "master"
file: "backend/cpp/llama-cpp/Makefile"
- repository: "ggml-org/whisper.cpp"
- 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"
branch: "master"
file: "backend/go/stablediffusion-ggml/Makefile"
- repository: "mudler/go-stable-diffusion"
variable: "STABLEDIFFUSION_VERSION"
branch: "master"
- 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 }}
bash .github/bump_deps.sh ${{ matrix.repository }} ${{ matrix.branch }} ${{ matrix.variable }}
{
echo 'message<<EOF'
cat "${{ matrix.variable }}_message.txt"
@@ -49,7 +47,7 @@ jobs:
rm -rfv ${{ matrix.variable }}_message.txt
rm -rfv ${{ matrix.variable }}_commit.txt
- name: Create Pull Request
uses: peter-evans/create-pull-request@v8
uses: peter-evans/create-pull-request@v7
with:
token: ${{ secrets.UPDATE_BOT_TOKEN }}
push-to-fork: ci-forks/LocalAI

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:
@@ -12,12 +12,12 @@ 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@v7
with:
token: ${{ secrets.UPDATE_BOT_TOKEN }}
push-to-fork: ci-forks/LocalAI

View File

@@ -5,7 +5,7 @@ on:
workflow_dispatch:
jobs:
checksum_check:
runs-on: ubuntu-latest
runs-on: arc-runner-set
steps:
- name: Force Install GIT latest
run: |
@@ -15,11 +15,12 @@ jobs:
&& sudo add-apt-repository -y ppa:git-core/ppa \
&& sudo apt-get update \
&& sudo apt-get install -y git
- uses: actions/checkout@v6
- uses: actions/checkout@v4
- name: Install dependencies
run: |
sudo apt-get update
sudo apt-get install -y pip wget
sudo pip install --upgrade pip
pip install huggingface_hub
- name: 'Setup yq'
uses: dcarbone/install-yq-action@v1.3.1
@@ -35,7 +36,7 @@ jobs:
sudo chmod 777 /hf_cache
bash .github/checksum_checker.sh gallery/index.yaml
- name: Create Pull Request
uses: peter-evans/create-pull-request@v8
uses: peter-evans/create-pull-request@v7
with:
token: ${{ secrets.UPDATE_BOT_TOKEN }}
push-to-fork: ci-forks/LocalAI

View File

@@ -14,13 +14,13 @@ jobs:
steps:
- name: Dependabot metadata
id: metadata
uses: dependabot/fetch-metadata@v2.5.0
uses: dependabot/fetch-metadata@v2.3.0
with:
github-token: "${{ secrets.GITHUB_TOKEN }}"
skip-commit-verification: true
- name: Checkout repository
uses: actions/checkout@v6
uses: actions/checkout@v4
- name: Approve a PR if not already approved
run: |

View File

@@ -15,7 +15,7 @@ jobs:
runs-on: ubuntu-latest
steps:
- name: Clone
uses: actions/checkout@v6
uses: actions/checkout@v4
with:
submodules: true
- uses: actions/setup-go@v5
@@ -31,9 +31,9 @@ jobs:
make protogen-go
- name: Build api
run: |
CGO_ENABLED=0 make build
CGO_ENABLED=0 make build-api
- name: rm
uses: appleboy/ssh-action@v1.2.4
uses: appleboy/ssh-action@v1.2.0
with:
host: ${{ secrets.EXPLORER_SSH_HOST }}
username: ${{ secrets.EXPLORER_SSH_USERNAME }}
@@ -42,7 +42,7 @@ jobs:
script: |
sudo rm -rf local-ai/ || true
- name: copy file via ssh
uses: appleboy/scp-action@v1.0.0
uses: appleboy/scp-action@v0.1.7
with:
host: ${{ secrets.EXPLORER_SSH_HOST }}
username: ${{ secrets.EXPLORER_SSH_USERNAME }}
@@ -53,7 +53,7 @@ jobs:
rm: true
target: ./local-ai
- name: restarting
uses: appleboy/ssh-action@v1.2.4
uses: appleboy/ssh-action@v1.2.0
with:
host: ${{ secrets.EXPLORER_SSH_HOST }}
username: ${{ secrets.EXPLORER_SSH_USERNAME }}

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: 'https://huggingface.co/bartowski/Qwen_Qwen3-1.7B-GGUF'
- name: Run gallery agent
env:
#OPENAI_MODEL: ${{ secrets.OPENAI_MODEL }}
OPENAI_MODE: Qwen_Qwen3-1.7B-GGUF
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

@@ -2,10 +2,9 @@ name: 'generate and publish GRPC docker caches'
on:
workflow_dispatch:
schedule:
# daily at midnight
- cron: '0 0 * * *'
push:
branches:
- master
concurrency:
group: grpc-cache-${{ github.head_ref || github.ref }}-${{ github.repository }}
@@ -16,7 +15,7 @@ jobs:
strategy:
matrix:
include:
- grpc-base-image: ubuntu:24.04
- grpc-base-image: ubuntu:22.04
runs-on: 'ubuntu-latest'
platforms: 'linux/amd64,linux/arm64'
runs-on: ${{matrix.runs-on}}
@@ -73,7 +72,7 @@ jobs:
uses: docker/setup-buildx-action@master
- name: Checkout
uses: actions/checkout@v6
uses: actions/checkout@v4
- name: Cache GRPC
uses: docker/build-push-action@v6

View File

@@ -15,8 +15,8 @@ jobs:
strategy:
matrix:
include:
- base-image: intel/oneapi-basekit:2025.3.0-0-devel-ubuntu24.04
runs-on: 'arc-runner-set'
- base-image: intel/oneapi-basekit:2025.0.0-0-devel-ubuntu22.04
runs-on: 'ubuntu-latest'
platforms: 'linux/amd64'
runs-on: ${{matrix.runs-on}}
steps:
@@ -43,7 +43,7 @@ jobs:
uses: docker/setup-buildx-action@master
- name: Checkout
uses: actions/checkout@v6
uses: actions/checkout@v4
- name: Cache Intel images
uses: docker/build-push-action@v6
@@ -53,7 +53,7 @@ jobs:
BASE_IMAGE=${{ matrix.base-image }}
context: .
file: ./Dockerfile
tags: quay.io/go-skynet/intel-oneapi-base:24.04
tags: quay.io/go-skynet/intel-oneapi-base:latest
push: true
target: intel
platforms: ${{ matrix.platforms }}

View File

@@ -1,95 +1,140 @@
---
name: 'build container images tests'
on:
pull_request:
concurrency:
group: ci-${{ github.head_ref || github.ref }}-${{ github.repository }}
cancel-in-progress: true
jobs:
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 }}
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 }}
quayUsername: ${{ secrets.LOCALAI_REGISTRY_USERNAME }}
quayPassword: ${{ secrets.LOCALAI_REGISTRY_PASSWORD }}
strategy:
# Pushing with all jobs in parallel
# eats the bandwidth of all the nodes
max-parallel: ${{ github.event_name != 'pull_request' && 4 || 8 }}
fail-fast: false
matrix:
include:
- build-type: 'cublas'
cuda-major-version: "12"
cuda-minor-version: "9"
platforms: 'linux/amd64'
tag-latest: 'false'
tag-suffix: '-gpu-nvidia-cuda-12'
runs-on: 'ubuntu-latest'
base-image: "ubuntu:24.04"
makeflags: "--jobs=3 --output-sync=target"
ubuntu-version: '2404'
- build-type: 'cublas'
cuda-major-version: "13"
cuda-minor-version: "0"
platforms: 'linux/amd64'
tag-latest: 'false'
tag-suffix: '-gpu-nvidia-cuda-13'
runs-on: 'ubuntu-latest'
base-image: "ubuntu:22.04"
makeflags: "--jobs=3 --output-sync=target"
ubuntu-version: '2404'
- build-type: 'hipblas'
platforms: 'linux/amd64'
tag-latest: 'false'
tag-suffix: '-hipblas'
base-image: "rocm/dev-ubuntu-24.04:6.4.4"
grpc-base-image: "ubuntu:24.04"
runs-on: 'ubuntu-latest'
makeflags: "--jobs=3 --output-sync=target"
ubuntu-version: '2404'
- build-type: 'sycl'
platforms: 'linux/amd64'
tag-latest: 'false'
base-image: "intel/oneapi-basekit:2025.3.0-0-devel-ubuntu24.04"
grpc-base-image: "ubuntu:24.04"
tag-suffix: 'sycl'
runs-on: 'ubuntu-latest'
makeflags: "--jobs=3 --output-sync=target"
ubuntu-version: '2404'
- build-type: 'vulkan'
platforms: 'linux/amd64,linux/arm64'
tag-latest: 'false'
tag-suffix: '-vulkan-core'
runs-on: 'ubuntu-latest'
base-image: "ubuntu:24.04"
makeflags: "--jobs=4 --output-sync=target"
ubuntu-version: '2404'
- build-type: 'cublas'
cuda-major-version: "13"
cuda-minor-version: "0"
platforms: 'linux/arm64'
tag-latest: 'false'
tag-suffix: '-nvidia-l4t-arm64-cuda-13'
base-image: "ubuntu:24.04"
runs-on: 'ubuntu-24.04-arm'
makeflags: "--jobs=4 --output-sync=target"
skip-drivers: 'false'
ubuntu-version: '2404'
name: 'build container images tests'
on:
pull_request:
concurrency:
group: ci-${{ github.head_ref || github.ref }}-${{ github.repository }}
cancel-in-progress: true
jobs:
extras-image-build:
uses: ./.github/workflows/image_build.yml
with:
tag-latest: ${{ matrix.tag-latest }}
tag-suffix: ${{ matrix.tag-suffix }}
ffmpeg: ${{ matrix.ffmpeg }}
image-type: ${{ matrix.image-type }}
build-type: ${{ matrix.build-type }}
cuda-major-version: ${{ matrix.cuda-major-version }}
cuda-minor-version: ${{ matrix.cuda-minor-version }}
platforms: ${{ matrix.platforms }}
runs-on: ${{ matrix.runs-on }}
base-image: ${{ matrix.base-image }}
grpc-base-image: ${{ matrix.grpc-base-image }}
makeflags: ${{ matrix.makeflags }}
secrets:
dockerUsername: ${{ secrets.DOCKERHUB_USERNAME }}
dockerPassword: ${{ secrets.DOCKERHUB_PASSWORD }}
quayUsername: ${{ secrets.LOCALAI_REGISTRY_USERNAME }}
quayPassword: ${{ secrets.LOCALAI_REGISTRY_PASSWORD }}
strategy:
# Pushing with all jobs in parallel
# eats the bandwidth of all the nodes
max-parallel: ${{ github.event_name != 'pull_request' && 4 || 8 }}
matrix:
include:
# This is basically covered by the AIO test
# - build-type: ''
# platforms: 'linux/amd64'
# tag-latest: 'false'
# tag-suffix: '-ffmpeg'
# ffmpeg: 'true'
# image-type: 'extras'
# runs-on: 'arc-runner-set'
# base-image: "ubuntu:22.04"
# makeflags: "--jobs=3 --output-sync=target"
- build-type: 'cublas'
cuda-major-version: "12"
cuda-minor-version: "0"
platforms: 'linux/amd64'
tag-latest: 'false'
tag-suffix: '-cublas-cuda12-ffmpeg'
ffmpeg: 'true'
image-type: 'extras'
runs-on: 'arc-runner-set'
base-image: "ubuntu:22.04"
makeflags: "--jobs=3 --output-sync=target"
# - build-type: 'hipblas'
# platforms: 'linux/amd64'
# tag-latest: 'false'
# tag-suffix: '-hipblas'
# ffmpeg: 'false'
# image-type: 'extras'
# base-image: "rocm/dev-ubuntu-22.04:6.1"
# grpc-base-image: "ubuntu:22.04"
# runs-on: 'arc-runner-set'
# makeflags: "--jobs=3 --output-sync=target"
# - build-type: 'sycl_f16'
# platforms: 'linux/amd64'
# tag-latest: 'false'
# base-image: "quay.io/go-skynet/intel-oneapi-base:latest"
# grpc-base-image: "ubuntu:22.04"
# tag-suffix: 'sycl-f16-ffmpeg'
# ffmpeg: 'true'
# image-type: 'extras'
# runs-on: 'arc-runner-set'
# makeflags: "--jobs=3 --output-sync=target"
# core-image-build:
# uses: ./.github/workflows/image_build.yml
# with:
# tag-latest: ${{ matrix.tag-latest }}
# tag-suffix: ${{ matrix.tag-suffix }}
# ffmpeg: ${{ matrix.ffmpeg }}
# image-type: ${{ matrix.image-type }}
# build-type: ${{ matrix.build-type }}
# cuda-major-version: ${{ matrix.cuda-major-version }}
# cuda-minor-version: ${{ matrix.cuda-minor-version }}
# platforms: ${{ matrix.platforms }}
# runs-on: ${{ matrix.runs-on }}
# base-image: ${{ matrix.base-image }}
# grpc-base-image: ${{ matrix.grpc-base-image }}
# makeflags: ${{ matrix.makeflags }}
# secrets:
# dockerUsername: ${{ secrets.DOCKERHUB_USERNAME }}
# dockerPassword: ${{ secrets.DOCKERHUB_PASSWORD }}
# quayUsername: ${{ secrets.LOCALAI_REGISTRY_USERNAME }}
# quayPassword: ${{ secrets.LOCALAI_REGISTRY_PASSWORD }}
# strategy:
# matrix:
# include:
# - build-type: ''
# platforms: 'linux/amd64'
# tag-latest: 'false'
# tag-suffix: '-ffmpeg-core'
# ffmpeg: 'true'
# image-type: 'core'
# runs-on: 'ubuntu-latest'
# base-image: "ubuntu:22.04"
# makeflags: "--jobs=4 --output-sync=target"
# - build-type: 'sycl_f16'
# platforms: 'linux/amd64'
# tag-latest: 'false'
# base-image: "quay.io/go-skynet/intel-oneapi-base:latest"
# grpc-base-image: "ubuntu:22.04"
# tag-suffix: 'sycl-f16-ffmpeg-core'
# ffmpeg: 'true'
# image-type: 'core'
# runs-on: 'arc-runner-set'
# makeflags: "--jobs=3 --output-sync=target"
# - build-type: 'cublas'
# cuda-major-version: "12"
# cuda-minor-version: "0"
# platforms: 'linux/amd64'
# tag-latest: 'false'
# tag-suffix: '-cublas-cuda12-ffmpeg-core'
# ffmpeg: 'true'
# image-type: 'core'
# runs-on: 'ubuntu-latest'
# base-image: "ubuntu:22.04"
# makeflags: "--jobs=4 --output-sync=target"
# - build-type: 'vulkan'
# platforms: 'linux/amd64'
# tag-latest: 'false'
# tag-suffix: '-vulkan-ffmpeg-core'
# ffmpeg: 'true'
# image-type: 'core'
# runs-on: 'ubuntu-latest'
# base-image: "ubuntu:22.04"
# makeflags: "--jobs=4 --output-sync=target"

View File

@@ -1,187 +1,404 @@
---
name: 'build container images'
on:
push:
branches:
- master
tags:
- '*'
concurrency:
group: ci-${{ github.head_ref || github.ref }}-${{ github.repository }}
cancel-in-progress: true
jobs:
hipblas-jobs:
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 }}
base-image: ${{ matrix.base-image }}
grpc-base-image: ${{ matrix.grpc-base-image }}
aio: ${{ matrix.aio }}
makeflags: ${{ matrix.makeflags }}
ubuntu-version: ${{ matrix.ubuntu-version }}
ubuntu-codename: ${{ matrix.ubuntu-codename }}
secrets:
dockerUsername: ${{ secrets.DOCKERHUB_USERNAME }}
dockerPassword: ${{ secrets.DOCKERHUB_PASSWORD }}
quayUsername: ${{ secrets.LOCALAI_REGISTRY_USERNAME }}
quayPassword: ${{ secrets.LOCALAI_REGISTRY_PASSWORD }}
strategy:
matrix:
include:
- build-type: 'hipblas'
platforms: 'linux/amd64'
tag-latest: 'auto'
tag-suffix: '-gpu-hipblas'
base-image: "rocm/dev-ubuntu-24.04:6.4.4"
grpc-base-image: "ubuntu:24.04"
runs-on: 'ubuntu-latest'
makeflags: "--jobs=3 --output-sync=target"
aio: "-aio-gpu-hipblas"
ubuntu-version: '2404'
ubuntu-codename: 'noble'
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 }}
ubuntu-codename: ${{ matrix.ubuntu-codename }}
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: ''
base-image: "ubuntu:24.04"
runs-on: 'ubuntu-latest'
aio: "-aio-cpu"
makeflags: "--jobs=4 --output-sync=target"
skip-drivers: 'false'
ubuntu-version: '2404'
ubuntu-codename: 'noble'
- build-type: 'cublas'
cuda-major-version: "12"
cuda-minor-version: "9"
platforms: 'linux/amd64'
tag-latest: 'auto'
tag-suffix: '-gpu-nvidia-cuda-12'
runs-on: 'ubuntu-latest'
base-image: "ubuntu:24.04"
skip-drivers: 'false'
makeflags: "--jobs=4 --output-sync=target"
aio: "-aio-gpu-nvidia-cuda-12"
ubuntu-version: '2404'
ubuntu-codename: 'noble'
- 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: '2404'
ubuntu-codename: 'noble'
- build-type: 'vulkan'
platforms: 'linux/amd64,linux/arm64'
tag-latest: 'auto'
tag-suffix: '-gpu-vulkan'
runs-on: 'ubuntu-latest'
base-image: "ubuntu:24.04"
skip-drivers: 'false'
makeflags: "--jobs=4 --output-sync=target"
aio: "-aio-gpu-vulkan"
ubuntu-version: '2404'
ubuntu-codename: 'noble'
- build-type: 'intel'
platforms: 'linux/amd64'
tag-latest: 'auto'
base-image: "intel/oneapi-basekit:2025.3.0-0-devel-ubuntu24.04"
grpc-base-image: "ubuntu:24.04"
tag-suffix: '-gpu-intel'
runs-on: 'ubuntu-latest'
makeflags: "--jobs=3 --output-sync=target"
aio: "-aio-gpu-intel"
ubuntu-version: '2404'
ubuntu-codename: 'noble'
gh-runner:
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 }}
ubuntu-codename: ${{ matrix.ubuntu-codename }}
secrets:
dockerUsername: ${{ secrets.DOCKERHUB_USERNAME }}
dockerPassword: ${{ secrets.DOCKERHUB_PASSWORD }}
quayUsername: ${{ secrets.LOCALAI_REGISTRY_USERNAME }}
quayPassword: ${{ secrets.LOCALAI_REGISTRY_PASSWORD }}
strategy:
matrix:
include:
- build-type: 'cublas'
cuda-major-version: "12"
cuda-minor-version: "0"
platforms: 'linux/arm64'
tag-latest: 'auto'
tag-suffix: '-nvidia-l4t-arm64'
base-image: "nvcr.io/nvidia/l4t-jetpack:r36.4.0"
runs-on: 'ubuntu-24.04-arm'
makeflags: "--jobs=4 --output-sync=target"
skip-drivers: 'true'
ubuntu-version: "2204"
ubuntu-codename: 'jammy'
- build-type: 'cublas'
cuda-major-version: "13"
cuda-minor-version: "0"
platforms: 'linux/arm64'
tag-latest: 'auto'
tag-suffix: '-nvidia-l4t-arm64-cuda-13'
base-image: "ubuntu:24.04"
runs-on: 'ubuntu-24.04-arm'
makeflags: "--jobs=4 --output-sync=target"
skip-drivers: 'false'
ubuntu-version: '2404'
ubuntu-codename: 'noble'
name: 'build container images'
on:
push:
branches:
- master
tags:
- '*'
concurrency:
group: ci-${{ github.head_ref || github.ref }}-${{ github.repository }}
cancel-in-progress: true
jobs:
hipblas-jobs:
uses: ./.github/workflows/image_build.yml
with:
tag-latest: ${{ matrix.tag-latest }}
tag-suffix: ${{ matrix.tag-suffix }}
ffmpeg: ${{ matrix.ffmpeg }}
image-type: ${{ matrix.image-type }}
build-type: ${{ matrix.build-type }}
cuda-major-version: ${{ matrix.cuda-major-version }}
cuda-minor-version: ${{ matrix.cuda-minor-version }}
platforms: ${{ matrix.platforms }}
runs-on: ${{ matrix.runs-on }}
base-image: ${{ matrix.base-image }}
grpc-base-image: ${{ matrix.grpc-base-image }}
aio: ${{ matrix.aio }}
makeflags: ${{ matrix.makeflags }}
latest-image: ${{ matrix.latest-image }}
latest-image-aio: ${{ matrix.latest-image-aio }}
secrets:
dockerUsername: ${{ secrets.DOCKERHUB_USERNAME }}
dockerPassword: ${{ secrets.DOCKERHUB_PASSWORD }}
quayUsername: ${{ secrets.LOCALAI_REGISTRY_USERNAME }}
quayPassword: ${{ secrets.LOCALAI_REGISTRY_PASSWORD }}
strategy:
# Pushing with all jobs in parallel
# eats the bandwidth of all the nodes
max-parallel: 2
matrix:
include:
- build-type: 'hipblas'
platforms: 'linux/amd64'
tag-latest: 'auto'
tag-suffix: '-hipblas-ffmpeg'
ffmpeg: 'true'
image-type: 'extras'
aio: "-aio-gpu-hipblas"
base-image: "rocm/dev-ubuntu-22.04:6.1"
grpc-base-image: "ubuntu:22.04"
latest-image: 'latest-gpu-hipblas'
latest-image-aio: 'latest-aio-gpu-hipblas'
runs-on: 'arc-runner-set'
makeflags: "--jobs=3 --output-sync=target"
- build-type: 'hipblas'
platforms: 'linux/amd64'
tag-latest: 'false'
tag-suffix: '-hipblas'
ffmpeg: 'false'
image-type: 'extras'
base-image: "rocm/dev-ubuntu-22.04:6.1"
grpc-base-image: "ubuntu:22.04"
runs-on: 'arc-runner-set'
makeflags: "--jobs=3 --output-sync=target"
- build-type: 'hipblas'
platforms: 'linux/amd64'
tag-latest: 'false'
tag-suffix: '-hipblas-ffmpeg-core'
ffmpeg: 'true'
image-type: 'core'
base-image: "rocm/dev-ubuntu-22.04:6.1"
grpc-base-image: "ubuntu:22.04"
runs-on: 'arc-runner-set'
makeflags: "--jobs=3 --output-sync=target"
- build-type: 'hipblas'
platforms: 'linux/amd64'
tag-latest: 'false'
tag-suffix: '-hipblas-core'
ffmpeg: 'false'
image-type: 'core'
base-image: "rocm/dev-ubuntu-22.04:6.1"
grpc-base-image: "ubuntu:22.04"
runs-on: 'arc-runner-set'
makeflags: "--jobs=3 --output-sync=target"
self-hosted-jobs:
uses: ./.github/workflows/image_build.yml
with:
tag-latest: ${{ matrix.tag-latest }}
tag-suffix: ${{ matrix.tag-suffix }}
ffmpeg: ${{ matrix.ffmpeg }}
image-type: ${{ matrix.image-type }}
build-type: ${{ matrix.build-type }}
cuda-major-version: ${{ matrix.cuda-major-version }}
cuda-minor-version: ${{ matrix.cuda-minor-version }}
platforms: ${{ matrix.platforms }}
runs-on: ${{ matrix.runs-on }}
base-image: ${{ matrix.base-image }}
grpc-base-image: ${{ matrix.grpc-base-image }}
aio: ${{ matrix.aio }}
makeflags: ${{ matrix.makeflags }}
latest-image: ${{ matrix.latest-image }}
latest-image-aio: ${{ matrix.latest-image-aio }}
secrets:
dockerUsername: ${{ secrets.DOCKERHUB_USERNAME }}
dockerPassword: ${{ secrets.DOCKERHUB_PASSWORD }}
quayUsername: ${{ secrets.LOCALAI_REGISTRY_USERNAME }}
quayPassword: ${{ secrets.LOCALAI_REGISTRY_PASSWORD }}
strategy:
# Pushing with all jobs in parallel
# eats the bandwidth of all the nodes
max-parallel: ${{ github.event_name != 'pull_request' && 5 || 8 }}
matrix:
include:
# Extra images
- build-type: ''
#platforms: 'linux/amd64,linux/arm64'
platforms: 'linux/amd64'
tag-latest: 'auto'
tag-suffix: ''
ffmpeg: ''
image-type: 'extras'
runs-on: 'arc-runner-set'
base-image: "ubuntu:22.04"
makeflags: "--jobs=3 --output-sync=target"
- build-type: ''
platforms: 'linux/amd64'
tag-latest: 'auto'
tag-suffix: '-ffmpeg'
ffmpeg: 'true'
image-type: 'extras'
runs-on: 'arc-runner-set'
base-image: "ubuntu:22.04"
makeflags: "--jobs=3 --output-sync=target"
- build-type: 'cublas'
cuda-major-version: "11"
cuda-minor-version: "7"
platforms: 'linux/amd64'
tag-latest: 'false'
tag-suffix: '-cublas-cuda11'
ffmpeg: ''
image-type: 'extras'
runs-on: 'arc-runner-set'
base-image: "ubuntu:22.04"
makeflags: "--jobs=3 --output-sync=target"
- build-type: 'cublas'
cuda-major-version: "12"
cuda-minor-version: "0"
platforms: 'linux/amd64'
tag-latest: 'false'
tag-suffix: '-cublas-cuda12'
ffmpeg: ''
image-type: 'extras'
runs-on: 'arc-runner-set'
base-image: "ubuntu:22.04"
makeflags: "--jobs=3 --output-sync=target"
- build-type: 'cublas'
cuda-major-version: "11"
cuda-minor-version: "7"
platforms: 'linux/amd64'
tag-latest: 'auto'
tag-suffix: '-cublas-cuda11-ffmpeg'
ffmpeg: 'true'
image-type: 'extras'
runs-on: 'arc-runner-set'
base-image: "ubuntu:22.04"
aio: "-aio-gpu-nvidia-cuda-11"
latest-image: 'latest-gpu-nvidia-cuda-11'
latest-image-aio: 'latest-aio-gpu-nvidia-cuda-11'
makeflags: "--jobs=3 --output-sync=target"
- build-type: 'cublas'
cuda-major-version: "12"
cuda-minor-version: "0"
platforms: 'linux/amd64'
tag-latest: 'auto'
tag-suffix: '-cublas-cuda12-ffmpeg'
ffmpeg: 'true'
image-type: 'extras'
runs-on: 'arc-runner-set'
base-image: "ubuntu:22.04"
aio: "-aio-gpu-nvidia-cuda-12"
latest-image: 'latest-gpu-nvidia-cuda-12'
latest-image-aio: 'latest-aio-gpu-nvidia-cuda-12'
makeflags: "--jobs=3 --output-sync=target"
- build-type: ''
#platforms: 'linux/amd64,linux/arm64'
platforms: 'linux/amd64'
tag-latest: 'auto'
tag-suffix: ''
ffmpeg: ''
image-type: 'extras'
base-image: "ubuntu:22.04"
runs-on: 'arc-runner-set'
makeflags: "--jobs=3 --output-sync=target"
- build-type: 'sycl_f16'
platforms: 'linux/amd64'
tag-latest: 'auto'
base-image: "quay.io/go-skynet/intel-oneapi-base:latest"
grpc-base-image: "ubuntu:22.04"
tag-suffix: '-sycl-f16-ffmpeg'
ffmpeg: 'true'
image-type: 'extras'
runs-on: 'arc-runner-set'
aio: "-aio-gpu-intel-f16"
latest-image: 'latest-gpu-intel-f16'
latest-image-aio: 'latest-aio-gpu-intel-f16'
makeflags: "--jobs=3 --output-sync=target"
- build-type: 'sycl_f32'
platforms: 'linux/amd64'
tag-latest: 'auto'
base-image: "quay.io/go-skynet/intel-oneapi-base:latest"
grpc-base-image: "ubuntu:22.04"
tag-suffix: '-sycl-f32-ffmpeg'
ffmpeg: 'true'
image-type: 'extras'
runs-on: 'arc-runner-set'
aio: "-aio-gpu-intel-f32"
latest-image: 'latest-gpu-intel-f32'
latest-image-aio: 'latest-aio-gpu-intel-f32'
makeflags: "--jobs=3 --output-sync=target"
# Core images
- build-type: 'sycl_f16'
platforms: 'linux/amd64'
tag-latest: 'false'
base-image: "quay.io/go-skynet/intel-oneapi-base:latest"
grpc-base-image: "ubuntu:22.04"
tag-suffix: '-sycl-f16-core'
ffmpeg: 'false'
image-type: 'core'
runs-on: 'arc-runner-set'
makeflags: "--jobs=3 --output-sync=target"
- build-type: 'sycl_f32'
platforms: 'linux/amd64'
tag-latest: 'false'
base-image: "quay.io/go-skynet/intel-oneapi-base:latest"
grpc-base-image: "ubuntu:22.04"
tag-suffix: '-sycl-f32-core'
ffmpeg: 'false'
image-type: 'core'
runs-on: 'arc-runner-set'
makeflags: "--jobs=3 --output-sync=target"
- build-type: 'sycl_f16'
platforms: 'linux/amd64'
tag-latest: 'false'
base-image: "quay.io/go-skynet/intel-oneapi-base:latest"
grpc-base-image: "ubuntu:22.04"
tag-suffix: '-sycl-f16-ffmpeg-core'
ffmpeg: 'true'
image-type: 'core'
runs-on: 'arc-runner-set'
makeflags: "--jobs=3 --output-sync=target"
- build-type: 'sycl_f32'
platforms: 'linux/amd64'
tag-latest: 'false'
base-image: "quay.io/go-skynet/intel-oneapi-base:latest"
grpc-base-image: "ubuntu:22.04"
tag-suffix: '-sycl-f32-ffmpeg-core'
ffmpeg: 'true'
image-type: 'core'
runs-on: 'arc-runner-set'
makeflags: "--jobs=3 --output-sync=target"
core-image-build:
uses: ./.github/workflows/image_build.yml
with:
tag-latest: ${{ matrix.tag-latest }}
tag-suffix: ${{ matrix.tag-suffix }}
ffmpeg: ${{ matrix.ffmpeg }}
image-type: ${{ matrix.image-type }}
build-type: ${{ matrix.build-type }}
cuda-major-version: ${{ matrix.cuda-major-version }}
cuda-minor-version: ${{ matrix.cuda-minor-version }}
platforms: ${{ matrix.platforms }}
runs-on: ${{ matrix.runs-on }}
aio: ${{ matrix.aio }}
base-image: ${{ matrix.base-image }}
grpc-base-image: ${{ matrix.grpc-base-image }}
makeflags: ${{ matrix.makeflags }}
latest-image: ${{ matrix.latest-image }}
latest-image-aio: ${{ matrix.latest-image-aio }}
skip-drivers: ${{ matrix.skip-drivers }}
secrets:
dockerUsername: ${{ secrets.DOCKERHUB_USERNAME }}
dockerPassword: ${{ secrets.DOCKERHUB_PASSWORD }}
quayUsername: ${{ secrets.LOCALAI_REGISTRY_USERNAME }}
quayPassword: ${{ secrets.LOCALAI_REGISTRY_PASSWORD }}
strategy:
max-parallel: ${{ github.event_name != 'pull_request' && 2 || 4 }}
matrix:
include:
- build-type: ''
platforms: 'linux/amd64,linux/arm64'
tag-latest: 'auto'
tag-suffix: '-ffmpeg-core'
ffmpeg: 'true'
image-type: 'core'
base-image: "ubuntu:22.04"
runs-on: 'arc-runner-set'
aio: "-aio-cpu"
latest-image: 'latest-cpu'
latest-image-aio: 'latest-aio-cpu'
makeflags: "--jobs=4 --output-sync=target"
skip-drivers: 'false'
- build-type: 'cublas'
cuda-major-version: "11"
cuda-minor-version: "7"
platforms: 'linux/amd64'
tag-latest: 'false'
tag-suffix: '-cublas-cuda11-core'
ffmpeg: ''
image-type: 'core'
base-image: "ubuntu:22.04"
runs-on: 'arc-runner-set'
makeflags: "--jobs=4 --output-sync=target"
skip-drivers: 'false'
- build-type: 'cublas'
cuda-major-version: "12"
cuda-minor-version: "0"
platforms: 'linux/amd64'
tag-latest: 'false'
tag-suffix: '-cublas-cuda12-core'
ffmpeg: ''
image-type: 'core'
base-image: "ubuntu:22.04"
runs-on: 'arc-runner-set'
makeflags: "--jobs=4 --output-sync=target"
skip-drivers: 'false'
- build-type: 'cublas'
cuda-major-version: "11"
cuda-minor-version: "7"
platforms: 'linux/amd64'
tag-latest: 'false'
tag-suffix: '-cublas-cuda11-ffmpeg-core'
ffmpeg: 'true'
image-type: 'core'
runs-on: 'arc-runner-set'
base-image: "ubuntu:22.04"
makeflags: "--jobs=4 --output-sync=target"
skip-drivers: 'false'
- build-type: 'cublas'
cuda-major-version: "12"
cuda-minor-version: "0"
platforms: 'linux/amd64'
tag-latest: 'false'
tag-suffix: '-cublas-cuda12-ffmpeg-core'
ffmpeg: 'true'
image-type: 'core'
runs-on: 'arc-runner-set'
base-image: "ubuntu:22.04"
skip-drivers: 'false'
makeflags: "--jobs=4 --output-sync=target"
- build-type: 'vulkan'
platforms: 'linux/amd64'
tag-latest: 'false'
tag-suffix: '-vulkan-ffmpeg-core'
latest-image: 'latest-vulkan-ffmpeg-core'
ffmpeg: 'true'
image-type: 'core'
runs-on: 'arc-runner-set'
base-image: "ubuntu:22.04"
skip-drivers: 'false'
makeflags: "--jobs=4 --output-sync=target"
gh-runner:
uses: ./.github/workflows/image_build.yml
with:
tag-latest: ${{ matrix.tag-latest }}
tag-suffix: ${{ matrix.tag-suffix }}
ffmpeg: ${{ matrix.ffmpeg }}
image-type: ${{ matrix.image-type }}
build-type: ${{ matrix.build-type }}
cuda-major-version: ${{ matrix.cuda-major-version }}
cuda-minor-version: ${{ matrix.cuda-minor-version }}
platforms: ${{ matrix.platforms }}
runs-on: ${{ matrix.runs-on }}
aio: ${{ matrix.aio }}
base-image: ${{ matrix.base-image }}
grpc-base-image: ${{ matrix.grpc-base-image }}
makeflags: ${{ matrix.makeflags }}
latest-image: ${{ matrix.latest-image }}
latest-image-aio: ${{ matrix.latest-image-aio }}
skip-drivers: ${{ matrix.skip-drivers }}
secrets:
dockerUsername: ${{ secrets.DOCKERHUB_USERNAME }}
dockerPassword: ${{ secrets.DOCKERHUB_PASSWORD }}
quayUsername: ${{ secrets.LOCALAI_REGISTRY_USERNAME }}
quayPassword: ${{ secrets.LOCALAI_REGISTRY_PASSWORD }}
strategy:
matrix:
include:
- build-type: 'cublas'
cuda-major-version: "12"
cuda-minor-version: "0"
platforms: 'linux/arm64'
tag-latest: 'false'
tag-suffix: '-nvidia-l4t-arm64-core'
latest-image: 'latest-nvidia-l4t-arm64-core'
ffmpeg: 'true'
image-type: 'core'
base-image: "nvcr.io/nvidia/l4t-jetpack:r36.4.0"
runs-on: 'ubuntu-24.04-arm'
makeflags: "--jobs=4 --output-sync=target"
skip-drivers: 'true'

View File

@@ -23,7 +23,7 @@ on:
type: string
cuda-minor-version:
description: 'CUDA minor version'
default: "9"
default: "4"
type: string
platforms:
description: 'Platforms'
@@ -33,14 +33,30 @@ 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
ffmpeg:
description: 'FFMPEG'
default: ''
type: string
skip-drivers:
description: 'Skip drivers by default'
default: 'false'
type: string
image-type:
description: 'Image type'
default: ''
type: string
runs-on:
description: 'Runs on'
required: true
@@ -56,16 +72,6 @@ on:
required: false
default: ''
type: string
ubuntu-version:
description: 'Ubuntu version'
required: false
default: '2204'
type: string
ubuntu-codename:
description: 'Ubuntu codename'
required: false
default: 'noble'
type: string
secrets:
dockerUsername:
required: true
@@ -79,22 +85,6 @@ jobs:
reusable_image-build:
runs-on: ${{ inputs.runs-on }}
steps:
- name: Free Disk Space (Ubuntu)
if: inputs.runs-on == 'ubuntu-latest'
uses: jlumbroso/free-disk-space@main
with:
# this might remove tools that are actually needed,
# if set to "true" but frees about 6 GB
tool-cache: true
# all of these default to true, but feel free to set to
# "false" if necessary for your workflow
android: true
dotnet: true
haskell: true
large-packages: true
docker-images: true
swap-storage: true
- name: Force Install GIT latest
run: |
sudo apt-get update \
@@ -104,7 +94,7 @@ jobs:
&& sudo apt-get update \
&& sudo apt-get install -y git
- name: Checkout
uses: actions/checkout@v6
uses: actions/checkout@v4
- name: Release space from worker
if: inputs.runs-on == 'ubuntu-latest'
@@ -116,8 +106,8 @@ jobs:
df -h
echo
sudo apt-get remove -y '^llvm-.*|^libllvm.*' || true
sudo apt-get remove --auto-remove android-sdk-platform-tools snapd || true
sudo apt-get purge --auto-remove android-sdk-platform-tools snapd || true
sudo apt-get remove --auto-remove android-sdk-platform-tools || true
sudo apt-get purge --auto-remove android-sdk-platform-tools || true
sudo rm -rf /usr/local/lib/android
sudo apt-get remove -y '^dotnet-.*|^aspnetcore-.*' || true
sudo rm -rf /usr/share/dotnet
@@ -162,18 +152,18 @@ jobs:
type=sha
flavor: |
latest=${{ inputs.tag-latest }}
suffix=${{ inputs.tag-suffix }},onlatest=true
suffix=${{ inputs.tag-suffix }}
- name: Docker meta for PR
id: meta_pull_request
if: github.event_name == 'pull_request'
uses: docker/metadata-action@v5
with:
images: |
quay.io/go-skynet/ci-tests
ttl.sh/localai-ci-pr-${{ github.event.number }}
tags: |
type=ref,event=branch,suffix=localai${{ 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 }}-${{ inputs.cuda-minor-version }}
type=ref,event=branch
type=semver,pattern={{raw}}
type=sha
flavor: |
latest=${{ inputs.tag-latest }}
suffix=${{ inputs.tag-suffix }}
@@ -189,7 +179,7 @@ jobs:
type=semver,pattern={{raw}}
flavor: |
latest=${{ inputs.tag-latest }}
suffix=${{ inputs.aio }},onlatest=true
suffix=${{ inputs.aio }}
- name: Docker meta AIO (dockerhub)
if: inputs.aio != ''
@@ -202,8 +192,7 @@ jobs:
type=ref,event=branch
type=semver,pattern={{raw}}
flavor: |
latest=${{ inputs.tag-latest }}
suffix=${{ inputs.aio }},onlatest=true
suffix=${{ inputs.aio }}
- name: Set up QEMU
uses: docker/setup-qemu-action@master
@@ -242,14 +231,14 @@ jobs:
BUILD_TYPE=${{ 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=${{ inputs.ubuntu-version }}
UBUNTU_CODENAME=${{ inputs.ubuntu-codename }}
context: .
file: ./Dockerfile
cache-from: type=gha
@@ -271,21 +260,25 @@ jobs:
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 }}
UBUNTU_CODENAME=${{ inputs.ubuntu-codename }}
context: .
file: ./Dockerfile
cache-from: type=gha
platforms: ${{ inputs.platforms }}
#push: true
push: true
tags: ${{ steps.meta_pull_request.outputs.tags }}
labels: ${{ steps.meta_pull_request.outputs.labels }}
- name: Testing image
if: github.event_name == 'pull_request'
run: |
echo "Image is available at ttl.sh/localai-ci-pr-${{ github.event.number }}:${{ steps.meta_pull_request.outputs.version }}" >> $GITHUB_STEP_SUMMARY
## End testing image
- name: Build and push AIO image
if: inputs.aio != ''
@@ -317,6 +310,27 @@ 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

@@ -6,15 +6,14 @@ 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):') }}
if: ${{ github.actor == 'localai-bot' }}
steps:
- name: Checkout repository
uses: actions/checkout@v6
uses: actions/checkout@v4
- name: Approve a PR if not already approved
run: |

View File

@@ -1,29 +1,24 @@
name: Notifications for new models
on:
pull_request_target:
pull_request:
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
MODEL_NAME: hermes-2-theta-llama-3-8b
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v6
- uses: actions/checkout@v4
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"
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@v2.8.1
- uses: GrantBirki/git-diff-action@v2.8.0
id: git-diff-action
with:
json_diff_file_output: diff.json
@@ -84,7 +79,7 @@ jobs:
args: ${{ steps.summarize.outputs.message }}
- name: Setup tmate session if fails
if: ${{ failure() }}
uses: mxschmitt/action-tmate@v3.23
uses: mxschmitt/action-tmate@v3.19
with:
detached: true
connect-timeout-seconds: 180
@@ -92,20 +87,19 @@ jobs:
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
MODEL_NAME: hermes-2-theta-llama-3-8b
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v6
- uses: actions/checkout@v4
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
docker run -e -ti -d --name local-ai -p 8080:8080 localai/localai:master-ffmpeg-core run --debug $MODEL_NAME
until [ "`docker inspect -f {{.State.Health.Status}} local-ai`" == "healthy" ]; do echo "Waiting for container to be ready"; docker logs --tail 10 local-ai; sleep 2; done
# Check the PR diff using the current branch and the base branch of the PR
- uses: GrantBirki/git-diff-action@v2.8.1
- uses: GrantBirki/git-diff-action@v2.8.0
id: git-diff-action
with:
json_diff_file_output: diff.json
@@ -167,7 +161,7 @@ jobs:
TWITTER_ACCESS_TOKEN_SECRET: ${{ secrets.TWITTER_ACCESS_TOKEN_SECRET }}
- name: Setup tmate session if fails
if: ${{ failure() }}
uses: mxschmitt/action-tmate@v3.23
uses: mxschmitt/action-tmate@v3.19
with:
detached: true
connect-timeout-seconds: 180

View File

@@ -11,11 +11,10 @@ jobs:
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"
model: 'hermes-2-theta-llama-3-8b' # Any from models.localai.io, or from huggingface.com with: "huggingface://<repository>/file"
- name: Summarize
id: summarize
run: |
@@ -61,4 +60,4 @@ jobs:
DISCORD_AVATAR: "https://avatars.githubusercontent.com/u/139863280?v=4"
uses: Ilshidur/action-discord@master
with:
args: ${{ steps.summarize.outputs.message }}
args: ${{ steps.summarize.outputs.message }}

View File

@@ -1,64 +1,324 @@
name: goreleaser
name: Build and Release
on:
push:
branches:
- master
tags:
- 'v*'
pull_request:
env:
GRPC_VERSION: v1.65.0
permissions:
contents: write
concurrency:
group: ci-releases-${{ github.head_ref || github.ref }}-${{ github.repository }}
cancel-in-progress: true
jobs:
goreleaser:
build-linux-arm:
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@v5
with:
go-version: 1.23
- name: Run GoReleaser
uses: goreleaser/goreleaser-action@v6
with:
version: v2.11.0
args: release --clean
env:
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
launcher-build-darwin:
runs-on: macos-latest
steps:
- name: Checkout
uses: actions/checkout@v6
with:
fetch-depth: 0
- name: Set up Go
uses: actions/setup-go@v5
with:
go-version: 1.23
- name: Build launcher for macOS ARM64
run: |
make build-launcher-darwin
- name: Upload DMG to Release
uses: softprops/action-gh-release@v2
with:
files: ./dist/LocalAI.dmg
launcher-build-linux:
runs-on: ubuntu-latest
steps:
- name: Checkout
uses: actions/checkout@v6
with:
fetch-depth: 0
- name: Set up Go
uses: actions/setup-go@v5
with:
go-version: 1.23
- name: Build launcher for Linux
go-version: '1.21.x'
cache: false
- name: Dependencies
run: |
sudo apt-get update
sudo apt-get install golang gcc libgl1-mesa-dev xorg-dev libxkbcommon-dev
make build-launcher-linux
- name: Upload Linux launcher artifacts
uses: softprops/action-gh-release@v2
sudo apt-get install build-essential ffmpeg protobuf-compiler ccache upx-ucl gawk
sudo apt-get install -qy binutils-aarch64-linux-gnu gcc-aarch64-linux-gnu g++-aarch64-linux-gnu libgmock-dev
- name: Install CUDA Dependencies
run: |
curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/cross-linux-aarch64/cuda-keyring_1.1-1_all.deb
sudo dpkg -i cuda-keyring_1.1-1_all.deb
sudo apt-get update
sudo apt-get install -y cuda-cross-aarch64 cuda-nvcc-cross-aarch64-${CUDA_VERSION} libcublas-cross-aarch64-${CUDA_VERSION}
env:
CUDA_VERSION: 12-4
- name: Cache grpc
id: cache-grpc
uses: actions/cache@v4
with:
files: ./local-ai-launcher-linux.tar.xz
path: grpc
key: ${{ runner.os }}-arm-grpc-${{ env.GRPC_VERSION }}
- name: Build grpc
if: steps.cache-grpc.outputs.cache-hit != 'true'
run: |
git clone --recurse-submodules -b ${{ env.GRPC_VERSION }} --depth 1 --shallow-submodules https://github.com/grpc/grpc && \
cd grpc && sed -i "216i\ TESTONLY" "third_party/abseil-cpp/absl/container/CMakeLists.txt" && mkdir -p cmake/build && \
cd cmake/build && cmake -DgRPC_INSTALL=ON \
-DgRPC_BUILD_TESTS=OFF \
../.. && sudo make --jobs 5 --output-sync=target
- name: Install gRPC
run: |
GNU_HOST=aarch64-linux-gnu
C_COMPILER_ARM_LINUX=$GNU_HOST-gcc
CXX_COMPILER_ARM_LINUX=$GNU_HOST-g++
CROSS_TOOLCHAIN=/usr/$GNU_HOST
CROSS_STAGING_PREFIX=$CROSS_TOOLCHAIN/stage
CMAKE_CROSS_TOOLCHAIN=/tmp/arm.toolchain.cmake
# https://cmake.org/cmake/help/v3.13/manual/cmake-toolchains.7.html#cross-compiling-for-linux
echo "set(CMAKE_SYSTEM_NAME Linux)" >> $CMAKE_CROSS_TOOLCHAIN && \
echo "set(CMAKE_SYSTEM_PROCESSOR arm)" >> $CMAKE_CROSS_TOOLCHAIN && \
echo "set(CMAKE_STAGING_PREFIX $CROSS_STAGING_PREFIX)" >> $CMAKE_CROSS_TOOLCHAIN && \
echo "set(CMAKE_SYSROOT ${CROSS_TOOLCHAIN}/sysroot)" >> $CMAKE_CROSS_TOOLCHAIN && \
echo "set(CMAKE_C_COMPILER /usr/bin/$C_COMPILER_ARM_LINUX)" >> $CMAKE_CROSS_TOOLCHAIN && \
echo "set(CMAKE_CXX_COMPILER /usr/bin/$CXX_COMPILER_ARM_LINUX)" >> $CMAKE_CROSS_TOOLCHAIN && \
echo "set(CMAKE_FIND_ROOT_PATH_MODE_PROGRAM NEVER)" >> $CMAKE_CROSS_TOOLCHAIN && \
echo "set(CMAKE_FIND_ROOT_PATH_MODE_LIBRARY ONLY)" >> $CMAKE_CROSS_TOOLCHAIN && \
echo "set(CMAKE_FIND_ROOT_PATH_MODE_INCLUDE ONLY)" >> $CMAKE_CROSS_TOOLCHAIN && \
echo "set(CMAKE_FIND_ROOT_PATH_MODE_PACKAGE ONLY)" >> $CMAKE_CROSS_TOOLCHAIN
GRPC_DIR=$PWD/grpc
cd grpc && cd cmake/build && sudo make --jobs 5 --output-sync=target install && \
GRPC_CROSS_BUILD_DIR=$GRPC_DIR/cmake/cross_build && \
mkdir -p $GRPC_CROSS_BUILD_DIR && \
cd $GRPC_CROSS_BUILD_DIR && \
cmake -DCMAKE_TOOLCHAIN_FILE=$CMAKE_CROSS_TOOLCHAIN \
-DCMAKE_BUILD_TYPE=Release \
-DCMAKE_INSTALL_PREFIX=$CROSS_TOOLCHAIN/grpc_install \
../.. && \
sudo make -j`nproc` install
- name: Build
id: build
run: |
GNU_HOST=aarch64-linux-gnu
C_COMPILER_ARM_LINUX=$GNU_HOST-gcc
CXX_COMPILER_ARM_LINUX=$GNU_HOST-g++
CROSS_TOOLCHAIN=/usr/$GNU_HOST
CROSS_STAGING_PREFIX=$CROSS_TOOLCHAIN/stage
CMAKE_CROSS_TOOLCHAIN=/tmp/arm.toolchain.cmake
go install google.golang.org/grpc/cmd/protoc-gen-go-grpc@1958fcbe2ca8bd93af633f11e97d44e567e945af
go install google.golang.org/protobuf/cmd/protoc-gen-go@v1.34.2
export PATH=$PATH:$GOPATH/bin
export PATH=/usr/local/cuda/bin:$PATH
sudo rm -rf /usr/aarch64-linux-gnu/lib/libstdc++.so.6
sudo cp -rf /usr/aarch64-linux-gnu/lib/libstdc++.so* /usr/aarch64-linux-gnu/lib/libstdc++.so.6
sudo cp /usr/aarch64-linux-gnu/lib/ld-linux-aarch64.so.1 ld.so
BACKEND_LIBS="./grpc/cmake/cross_build/third_party/re2/libre2.a ./grpc/cmake/cross_build/libgrpc.a ./grpc/cmake/cross_build/libgrpc++.a ./grpc/cmake/cross_build/third_party/protobuf/libprotobuf.a /usr/aarch64-linux-gnu/lib/libc.so.6 /usr/aarch64-linux-gnu/lib/libstdc++.so.6 /usr/aarch64-linux-gnu/lib/libgomp.so.1 /usr/aarch64-linux-gnu/lib/libm.so.6 /usr/aarch64-linux-gnu/lib/libgcc_s.so.1 /usr/aarch64-linux-gnu/lib/libdl.so.2 /usr/aarch64-linux-gnu/lib/libpthread.so.0 ./ld.so" \
GOOS=linux \
GOARCH=arm64 \
CMAKE_ARGS="-DProtobuf_INCLUDE_DIRS=$CROSS_STAGING_PREFIX/include -DProtobuf_DIR=$CROSS_STAGING_PREFIX/lib/cmake/protobuf -DgRPC_DIR=$CROSS_STAGING_PREFIX/lib/cmake/grpc -DCMAKE_TOOLCHAIN_FILE=$CMAKE_CROSS_TOOLCHAIN -DCMAKE_C_COMPILER=aarch64-linux-gnu-gcc -DCMAKE_CXX_COMPILER=aarch64-linux-gnu-g++" make dist-cross-linux-arm64
- uses: actions/upload-artifact@v4
with:
name: LocalAI-linux-arm64
path: release/
- name: Release
uses: softprops/action-gh-release@v2
if: startsWith(github.ref, 'refs/tags/')
with:
files: |
release/*
- name: Setup tmate session if tests fail
if: ${{ failure() }}
uses: mxschmitt/action-tmate@v3.19
with:
detached: true
connect-timeout-seconds: 180
limit-access-to-actor: true
build-linux:
runs-on: arc-runner-set
steps:
- name: Force Install GIT latest
run: |
sudo apt-get update \
&& sudo apt-get install -y software-properties-common \
&& sudo apt-get update \
&& sudo add-apt-repository -y ppa:git-core/ppa \
&& sudo apt-get update \
&& sudo apt-get install -y git
- name: Clone
uses: actions/checkout@v4
with:
submodules: true
- uses: actions/setup-go@v5
with:
go-version: '1.21.x'
cache: false
- name: Dependencies
run: |
sudo apt-get update
sudo apt-get install -y wget curl build-essential ffmpeg protobuf-compiler ccache upx-ucl gawk cmake libgmock-dev
- name: Intel Dependencies
run: |
wget -O- https://apt.repos.intel.com/intel-gpg-keys/GPG-PUB-KEY-INTEL-SW-PRODUCTS.PUB | gpg --dearmor | sudo tee /usr/share/keyrings/oneapi-archive-keyring.gpg > /dev/null
echo "deb [signed-by=/usr/share/keyrings/oneapi-archive-keyring.gpg] https://apt.repos.intel.com/oneapi all main" | sudo tee /etc/apt/sources.list.d/oneAPI.list
sudo apt update
sudo apt install -y intel-basekit
- name: Install CUDA Dependencies
run: |
curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64/cuda-keyring_1.1-1_all.deb
sudo dpkg -i cuda-keyring_1.1-1_all.deb
sudo apt-get update
sudo apt-get install -y cuda-nvcc-${CUDA_VERSION} libcublas-dev-${CUDA_VERSION}
env:
CUDA_VERSION: 12-5
- name: "Install Hipblas"
env:
ROCM_VERSION: "6.1"
AMDGPU_VERSION: "6.1"
run: |
set -ex
sudo apt-get update
sudo DEBIAN_FRONTEND=noninteractive apt-get install -y --no-install-recommends ca-certificates curl libnuma-dev gnupg
curl -sL https://repo.radeon.com/rocm/rocm.gpg.key | sudo apt-key add -
printf "deb [arch=amd64] https://repo.radeon.com/rocm/apt/$ROCM_VERSION/ jammy main" | sudo tee /etc/apt/sources.list.d/rocm.list
printf "deb [arch=amd64] https://repo.radeon.com/amdgpu/$AMDGPU_VERSION/ubuntu jammy main" | sudo tee /etc/apt/sources.list.d/amdgpu.list
printf 'Package: *\nPin: release o=repo.radeon.com\nPin-Priority: 600' | sudo tee /etc/apt/preferences.d/rocm-pin-600
sudo apt-get update
sudo DEBIAN_FRONTEND=noninteractive apt-get install -y \
hipblas-dev rocm-dev \
rocblas-dev
sudo apt-get clean
sudo rm -rf /var/lib/apt/lists/*
sudo ldconfig
- name: Cache grpc
id: cache-grpc
uses: actions/cache@v4
with:
path: grpc
key: ${{ runner.os }}-grpc-${{ env.GRPC_VERSION }}
- name: Build grpc
if: steps.cache-grpc.outputs.cache-hit != 'true'
run: |
git clone --recurse-submodules -b ${{ env.GRPC_VERSION }} --depth 1 --shallow-submodules https://github.com/grpc/grpc && \
cd grpc && sed -i "216i\ TESTONLY" "third_party/abseil-cpp/absl/container/CMakeLists.txt" && mkdir -p cmake/build && \
cd cmake/build && cmake -DgRPC_INSTALL=ON \
-DgRPC_BUILD_TESTS=OFF \
../.. && sudo make --jobs 5 --output-sync=target
- name: Install gRPC
run: |
cd grpc && cd cmake/build && sudo make --jobs 5 --output-sync=target install
# BACKEND_LIBS needed for gpu-workload: /opt/intel/oneapi/*/lib/libiomp5.so /opt/intel/oneapi/*/lib/libmkl_core.so /opt/intel/oneapi/*/lib/libmkl_core.so.2 /opt/intel/oneapi/*/lib/libmkl_intel_ilp64.so /opt/intel/oneapi/*/lib/libmkl_intel_ilp64.so.2 /opt/intel/oneapi/*/lib/libmkl_sycl_blas.so /opt/intel/oneapi/*/lib/libmkl_sycl_blas.so.4 /opt/intel/oneapi/*/lib/libmkl_tbb_thread.so /opt/intel/oneapi/*/lib/libmkl_tbb_thread.so.2 /opt/intel/oneapi/*/lib/libsycl.so /opt/intel/oneapi/*/lib/libsycl.so.7 /opt/intel/oneapi/*/lib/libsycl.so.7.1.0 /opt/rocm-*/lib/libamdhip64.so /opt/rocm-*/lib/libamdhip64.so.5 /opt/rocm-*/lib/libamdhip64.so.6 /opt/rocm-*/lib/libamdhip64.so.6.1.60100 /opt/rocm-*/lib/libhipblas.so /opt/rocm-*/lib/libhipblas.so.2 /opt/rocm-*/lib/libhipblas.so.2.1.60100 /opt/rocm-*/lib/librocblas.so /opt/rocm-*/lib/librocblas.so.4 /opt/rocm-*/lib/librocblas.so.4.1.60100 /usr/lib/x86_64-linux-gnu/libstdc++.so.6 /usr/lib/x86_64-linux-gnu/libOpenCL.so.1 /usr/lib/x86_64-linux-gnu/libOpenCL.so.1.0.0 /usr/lib/x86_64-linux-gnu/libm.so.6 /usr/lib/x86_64-linux-gnu/libgcc_s.so.1 /usr/lib/x86_64-linux-gnu/libc.so.6 /usr/lib/x86_64-linux-gnu/librt.so.1 /usr/local/cuda-*/targets/x86_64-linux/lib/libcublas.so /usr/local/cuda-*/targets/x86_64-linux/lib/libcublasLt.so /usr/local/cuda-*/targets/x86_64-linux/lib/libcudart.so /usr/local/cuda-*/targets/x86_64-linux/lib/stubs/libcuda.so
- name: Build
id: build
run: |
go install google.golang.org/grpc/cmd/protoc-gen-go-grpc@1958fcbe2ca8bd93af633f11e97d44e567e945af
go install google.golang.org/protobuf/cmd/protoc-gen-go@v1.34.2
export PATH=$PATH:$GOPATH/bin
export PATH=/usr/local/cuda/bin:$PATH
export PATH=/opt/rocm/bin:$PATH
source /opt/intel/oneapi/setvars.sh
sudo cp /lib64/ld-linux-x86-64.so.2 ld.so
BACKEND_LIBS="./ld.so ./sources/go-piper/piper/build/fi/lib/libfmt.a ./sources/go-piper/piper-phonemize/pi/lib/libonnxruntime.so.1.14.1 ./sources/go-piper/piper-phonemize/pi/src/libespeak-ng/libespeak-ng.so /usr/lib/x86_64-linux-gnu/libdl.so.2 /usr/lib/x86_64-linux-gnu/librt.so.1 /usr/lib/x86_64-linux-gnu/libpthread.so.0 ./sources/go-piper/piper-phonemize/pi/lib/libpiper_phonemize.so.1 ./sources/go-piper/piper/build/si/lib/libspdlog.a ./sources/go-piper/espeak/ei/lib/libucd.so" \
make -j4 dist
- uses: actions/upload-artifact@v4
with:
name: LocalAI-linux
path: release/
- name: Release
uses: softprops/action-gh-release@v2
if: startsWith(github.ref, 'refs/tags/')
with:
files: |
release/*
- name: Setup tmate session if tests fail
if: ${{ failure() }}
uses: mxschmitt/action-tmate@v3.19
with:
detached: true
connect-timeout-seconds: 180
limit-access-to-actor: true
build-macOS-x86_64:
runs-on: macos-13
steps:
- name: Clone
uses: actions/checkout@v4
with:
submodules: true
- uses: actions/setup-go@v5
with:
go-version: '1.21.x'
cache: false
- name: Dependencies
run: |
brew install protobuf grpc
go install google.golang.org/grpc/cmd/protoc-gen-go-grpc@8ba23be9613c672d40ae261d2a1335d639bdd59b
go install google.golang.org/protobuf/cmd/protoc-gen-go@v1.34.0
- name: Build
id: build
run: |
export C_INCLUDE_PATH=/usr/local/include
export CPLUS_INCLUDE_PATH=/usr/local/include
export PATH=$PATH:$GOPATH/bin
export SKIP_GRPC_BACKEND=backend-assets/grpc/whisper
make dist
- uses: actions/upload-artifact@v4
with:
name: LocalAI-MacOS-x86_64
path: release/
- name: Release
uses: softprops/action-gh-release@v2
if: startsWith(github.ref, 'refs/tags/')
with:
files: |
release/*
- name: Setup tmate session if tests fail
if: ${{ failure() }}
uses: mxschmitt/action-tmate@v3.19
with:
detached: true
connect-timeout-seconds: 180
limit-access-to-actor: true
build-macOS-arm64:
runs-on: macos-14
steps:
- name: Clone
uses: actions/checkout@v4
with:
submodules: true
- uses: actions/setup-go@v5
with:
go-version: '1.21.x'
cache: false
- name: Dependencies
run: |
brew install protobuf grpc libomp llvm
go install google.golang.org/grpc/cmd/protoc-gen-go-grpc@1958fcbe2ca8bd93af633f11e97d44e567e945af
go install google.golang.org/protobuf/cmd/protoc-gen-go@v1.34.2
- name: Build
id: build
run: |
export C_INCLUDE_PATH=/usr/local/include
export CPLUS_INCLUDE_PATH=/usr/local/include
export PATH=$PATH:$GOPATH/bin
export CC=/opt/homebrew/opt/llvm/bin/clang
make dist
- uses: actions/upload-artifact@v4
with:
name: LocalAI-MacOS-arm64
path: release/
- name: Release
uses: softprops/action-gh-release@v2
if: startsWith(github.ref, 'refs/tags/')
with:
files: |
release/*
- name: Setup tmate session if tests fail
if: ${{ failure() }}
uses: mxschmitt/action-tmate@v3.19
with:
detached: true
connect-timeout-seconds: 180
limit-access-to-actor: true

View File

@@ -14,17 +14,17 @@ jobs:
GO111MODULE: on
steps:
- name: Checkout Source
uses: actions/checkout@v6
uses: actions/checkout@v4
if: ${{ github.actor != 'dependabot[bot]' }}
- name: Run Gosec Security Scanner
if: ${{ github.actor != 'dependabot[bot]' }}
uses: securego/gosec@v2.22.9
uses: securego/gosec@v2.22.0
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@v3
with:
# Path to SARIF file relative to the root of the repository
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

@@ -14,33 +14,11 @@ 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
uses: actions/checkout@v4
with:
submodules: true
- name: Dependencies
@@ -61,7 +39,7 @@ jobs:
runs-on: ubuntu-latest
steps:
- name: Clone
uses: actions/checkout@v6
uses: actions/checkout@v4
with:
submodules: true
- name: Dependencies
@@ -83,7 +61,7 @@ jobs:
runs-on: ubuntu-latest
steps:
- name: Clone
uses: actions/checkout@v6
uses: actions/checkout@v4
with:
submodules: true
- name: Dependencies
@@ -100,31 +78,11 @@ jobs:
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:
# runs-on: ubuntu-latest
# steps:
# - name: Clone
# uses: actions/checkout@v6
# uses: actions/checkout@v4
# with:
# submodules: true
# - name: Dependencies
@@ -186,7 +144,7 @@ jobs:
# sudo rm -rf "$AGENT_TOOLSDIRECTORY" || true
# df -h
# - name: Clone
# uses: actions/checkout@v6
# uses: actions/checkout@v4
# with:
# submodules: true
# - name: Dependencies
@@ -211,7 +169,7 @@ jobs:
# runs-on: ubuntu-latest
# steps:
# - name: Clone
# uses: actions/checkout@v6
# uses: actions/checkout@v4
# with:
# submodules: true
# - name: Dependencies
@@ -232,7 +190,7 @@ jobs:
runs-on: ubuntu-latest
steps:
- name: Clone
uses: actions/checkout@v6
uses: actions/checkout@v4
with:
submodules: true
- name: Dependencies
@@ -247,22 +205,3 @@ jobs:
run: |
make --jobs=5 --output-sync=target -C backend/python/coqui
make --jobs=5 --output-sync=target -C backend/python/coqui test
tests-moonshine:
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
sudo apt-get install -y ca-certificates cmake curl patch python3-pip
# Install UV
curl -LsSf https://astral.sh/uv/install.sh | sh
pip install --user --no-cache-dir grpcio-tools==1.64.1
- name: Test moonshine
run: |
make --jobs=5 --output-sync=target -C backend/python/moonshine
make --jobs=5 --output-sync=target -C backend/python/moonshine test

View File

@@ -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"
@@ -70,7 +56,7 @@ jobs:
sudo rm -rfv build || true
df -h
- name: Clone
uses: actions/checkout@v6
uses: actions/checkout@v4
with:
submodules: true
- name: Setup Go ${{ matrix.go-version }}
@@ -81,20 +67,18 @@ jobs:
# You can test your matrix by printing the current Go version
- name: Display Go version
run: go version
- name: Proto Dependencies
run: |
# Install protoc
curl -L -s https://github.com/protocolbuffers/protobuf/releases/download/v26.1/protoc-26.1-linux-x86_64.zip -o protoc.zip && \
unzip -j -d /usr/local/bin protoc.zip bin/protoc && \
rm protoc.zip
go install google.golang.org/protobuf/cmd/protoc-gen-go@v1.34.2
go install google.golang.org/grpc/cmd/protoc-gen-go-grpc@1958fcbe2ca8bd93af633f11e97d44e567e945af
PATH="$PATH:$HOME/go/bin" make protogen-go
- name: Dependencies
run: |
sudo apt-get update
sudo apt-get install build-essential ccache upx-ucl curl ffmpeg
sudo apt-get install -y libgmock-dev clang
sudo apt-get install -y libgmock-dev
curl https://repo.anaconda.com/pkgs/misc/gpgkeys/anaconda.asc | gpg --dearmor > conda.gpg && \
sudo install -o root -g root -m 644 conda.gpg /usr/share/keyrings/conda-archive-keyring.gpg && \
gpg --keyring /usr/share/keyrings/conda-archive-keyring.gpg --no-default-keyring --fingerprint 34161F5BF5EB1D4BFBBB8F0A8AEB4F8B29D82806 && \
sudo /bin/bash -c 'echo "deb [arch=amd64 signed-by=/usr/share/keyrings/conda-archive-keyring.gpg] https://repo.anaconda.com/pkgs/misc/debrepo/conda stable main" > /etc/apt/sources.list.d/conda.list' && \
sudo /bin/bash -c 'echo "deb [arch=amd64 signed-by=/usr/share/keyrings/conda-archive-keyring.gpg] https://repo.anaconda.com/pkgs/misc/debrepo/conda stable main" | tee -a /etc/apt/sources.list.d/conda.list' && \
sudo apt-get update && \
sudo apt-get install -y conda
# Install UV
curl -LsSf https://astral.sh/uv/install.sh | sh
sudo apt-get install -y ca-certificates cmake patch python3-pip unzip
@@ -109,17 +93,44 @@ jobs:
sudo apt-get update
sudo apt-get install -y cuda-nvcc-${CUDA_VERSION} libcublas-dev-${CUDA_VERSION}
export CUDACXX=/usr/local/cuda/bin/nvcc
go install google.golang.org/protobuf/cmd/protoc-gen-go@v1.34.2
go install google.golang.org/grpc/cmd/protoc-gen-go-grpc@1958fcbe2ca8bd93af633f11e97d44e567e945af
# The python3-grpc-tools package in 22.04 is too old
pip install --user grpcio-tools
make -C backend/python/transformers
make backends/huggingface backends/llama-cpp backends/local-store backends/silero-vad backends/piper backends/whisper backends/stablediffusion-ggml
# 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/
env:
CUDA_VERSION: 12-4
- name: Cache grpc
id: cache-grpc
uses: actions/cache@v4
with:
path: grpc
key: ${{ runner.os }}-grpc-${{ env.GRPC_VERSION }}
- name: Build grpc
if: steps.cache-grpc.outputs.cache-hit != 'true'
run: |
git clone --recurse-submodules -b ${{ env.GRPC_VERSION }} --depth 1 --jobs 5 --shallow-submodules https://github.com/grpc/grpc && \
cd grpc && sed -i "216i\ TESTONLY" "third_party/abseil-cpp/absl/container/CMakeLists.txt" && mkdir -p cmake/build && cd cmake/build && \
cmake -DgRPC_INSTALL=ON \
-DgRPC_BUILD_TESTS=OFF \
../.. && sudo make --jobs 5
- name: Install gRPC
run: |
cd grpc && cd cmake/build && sudo make --jobs 5 install
- name: Test
run: |
PATH="$PATH:/root/go/bin" GO_TAGS="tts" make --jobs 5 --output-sync=target test
- name: Setup tmate session if tests fail
if: ${{ failure() }}
uses: mxschmitt/action-tmate@v3.23
uses: mxschmitt/action-tmate@v3.19
with:
detached: true
connect-timeout-seconds: 180
@@ -161,7 +172,7 @@ jobs:
sudo rm -rfv build || true
df -h
- name: Clone
uses: actions/checkout@v6
uses: actions/checkout@v4
with:
submodules: true
- name: Dependencies
@@ -173,25 +184,30 @@ jobs:
go install google.golang.org/protobuf/cmd/protoc-gen-go@v1.34.2
go install google.golang.org/grpc/cmd/protoc-gen-go-grpc@1958fcbe2ca8bd93af633f11e97d44e567e945af
PATH="$PATH:$HOME/go/bin" make protogen-go
- name: Build images
run: |
docker build --build-arg FFMPEG=true --build-arg IMAGE_TYPE=extras --build-arg EXTRA_BACKENDS=rerankers --build-arg MAKEFLAGS="--jobs=5 --output-sync=target" -t local-ai:tests -f Dockerfile .
BASE_IMAGE=local-ai:tests DOCKER_AIO_IMAGE=local-ai-aio:test make docker-aio
- name: Test
run: |
PATH="$PATH:$HOME/go/bin" make backends/local-store backends/silero-vad backends/llama-cpp backends/whisper backends/piper backends/stablediffusion-ggml docker-build-aio e2e-aio
PATH="$PATH:$HOME/go/bin" LOCALAI_MODELS_DIR=$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
uses: mxschmitt/action-tmate@v3.19
with:
detached: true
connect-timeout-seconds: 180
limit-access-to-actor: true
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
uses: actions/checkout@v4
with:
submodules: true
- name: Setup Go ${{ matrix.go-version }}
@@ -205,11 +221,7 @@ jobs:
- name: Dependencies
run: |
brew install protobuf grpc make protoc-gen-go protoc-gen-go-grpc libomp llvm
pip install --user --no-cache-dir grpcio-tools grpcio
- name: Build llama-cpp-darwin
run: |
make protogen-go
make backends/llama-cpp-darwin
pip install --user --no-cache-dir grpcio-tools
- name: Test
run: |
export C_INCLUDE_PATH=/usr/local/include
@@ -217,11 +229,10 @@ jobs:
export CC=/opt/homebrew/opt/llvm/bin/clang
# Used to run the newer GNUMake version from brew that supports --output-sync
export PATH="/opt/homebrew/opt/make/libexec/gnubin:$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="-DGGML_F16C=OFF -DGGML_AVX512=OFF -DGGML_AVX2=OFF -DGGML_FMA=OFF" make --jobs 4 --output-sync=target test
- name: Setup tmate session if tests fail
if: ${{ failure() }}
uses: mxschmitt/action-tmate@v3.23
uses: mxschmitt/action-tmate@v3.19
with:
detached: true
connect-timeout-seconds: 180

View File

@@ -9,7 +9,7 @@ jobs:
fail-fast: false
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v6
- uses: actions/checkout@v4
- uses: actions/setup-go@v5
with:
go-version: 'stable'
@@ -25,7 +25,7 @@ jobs:
run: |
make protogen-go swagger
- name: Create Pull Request
uses: peter-evans/create-pull-request@v8
uses: peter-evans/create-pull-request@v7
with:
token: ${{ secrets.UPDATE_BOT_TOKEN }}
push-to-fork: ci-forks/LocalAI

View File

@@ -8,7 +8,7 @@ jobs:
steps:
- name: 'Checkout'
uses: actions/checkout@master
- name: 'Yamllint model gallery'
- name: 'Yamllint'
uses: karancode/yamllint-github-action@master
with:
yamllint_file_or_dir: 'gallery'
@@ -16,11 +16,3 @@ jobs:
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 }}

14
.gitignore vendored
View File

@@ -5,14 +5,9 @@ __pycache__/
*.o
get-sources
prepare-sources
/backend/cpp/llama-cpp/grpc-server
/backend/cpp/llama-cpp/llama.cpp
/backend/cpp/llama/grpc-server
/backend/cpp/llama/llama.cpp
/backend/cpp/llama-*
!backend/cpp/llama-cpp
/backends
/backend-images
/result.yaml
protoc
*.log
@@ -24,8 +19,7 @@ go-bert
# LocalAI build binary
LocalAI
/local-ai
/local-ai-launcher
local-ai
# prevent above rules from omitting the helm chart
!charts/*
# prevent above rules from omitting the api/localai folder
@@ -62,4 +56,4 @@ docs/static/gallery.html
**/venv
# per-developer customization files for the development container
.devcontainer/customization/*
.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

2
.vscode/launch.json vendored
View File

@@ -26,7 +26,7 @@
"LOCALAI_P2P": "true",
"LOCALAI_FEDERATED": "true"
},
"buildFlags": ["-tags", "", "-v"],
"buildFlags": ["-tags", "p2p tts", "-v"],
"envFile": "${workspaceFolder}/.env",
"cwd": "${workspaceRoot}"
}

282
AGENTS.md
View File

@@ -1,282 +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.
## Building a specified backend
Let's say the user wants to build a particular backend for a given platform. For example let's say they want to build bark for ROCM/hipblas
- The Makefile has targets like `docker-build-bark` created with `generate-docker-build-target` at the time of writing. Recently added backends may require a new target.
- At a minimum we need to set the BUILD_TYPE, BASE_IMAGE build-args
- Use .github/workflows/backend.yml as a reference it lists the needed args in the `include` job strategy matrix
- l4t and cublas also requires the CUDA major and minor version
- You can pretty print a command like `DOCKER_MAKEFLAGS=-j$(nproc --ignore=1) BUILD_TYPE=hipblas BASE_IMAGE=rocm/dev-ubuntu-24.04:6.4.4 make docker-build-bark`
- Unless the user specifies that they want you to run the command, then just print it because not all agent frontends handle long running jobs well and the output may overflow your context
- The user may say they want to build AMD or ROCM instead of hipblas, or Intel instead of SYCL or NVIDIA insted of l4t or cublas. Ask for confirmation if there is ambiguity.
- Sometimes the user may need extra parameters to be added to `docker build` (e.g. `--platform` for cross-platform builds or `--progress` to view the full logs), in which case you can generate the `docker build` command directly.
## Adding a New Backend
When adding a new backend to LocalAI, you need to update several files to ensure the backend is properly built, tested, and registered. Here's a step-by-step guide based on the pattern used for adding backends like `moonshine`:
### 1. Create Backend Directory Structure
Create the backend directory under the appropriate location:
- **Python backends**: `backend/python/<backend-name>/`
- **Go backends**: `backend/go/<backend-name>/`
- **C++ backends**: `backend/cpp/<backend-name>/`
For Python backends, you'll typically need:
- `backend.py` - Main gRPC server implementation
- `Makefile` - Build configuration
- `install.sh` - Installation script for dependencies
- `protogen.sh` - Protocol buffer generation script
- `requirements.txt` - Python dependencies
- `run.sh` - Runtime script
- `test.py` / `test.sh` - Test files
### 2. Add Build Configurations to `.github/workflows/backend.yml`
Add build matrix entries for each platform/GPU type you want to support. Look at similar backends (e.g., `chatterbox`, `faster-whisper`) for reference.
**Placement in file:**
- CPU builds: Add after other CPU builds (e.g., after `cpu-chatterbox`)
- CUDA 12 builds: Add after other CUDA 12 builds (e.g., after `gpu-nvidia-cuda-12-chatterbox`)
- CUDA 13 builds: Add after other CUDA 13 builds (e.g., after `gpu-nvidia-cuda-13-chatterbox`)
**Additional build types you may need:**
- ROCm/HIP: Use `build-type: 'hipblas'` with `base-image: "rocm/dev-ubuntu-24.04:6.4.4"`
- Intel/SYCL: Use `build-type: 'intel'` or `build-type: 'sycl_f16'`/`sycl_f32` with `base-image: "intel/oneapi-basekit:2025.3.0-0-devel-ubuntu24.04"`
- L4T (ARM): Use `build-type: 'l4t'` with `platforms: 'linux/arm64'` and `runs-on: 'ubuntu-24.04-arm'`
### 3. Add Backend Metadata to `backend/index.yaml`
**Step 3a: Add Meta Definition**
Add a YAML anchor definition in the `## metas` section (around line 2-300). Look for similar backends to use as a template such as `diffusers` or `chatterbox`
**Step 3b: Add Image Entries**
Add image entries at the end of the file, following the pattern of similar backends such as `diffusers` or `chatterbox`. Include both `latest` (production) and `master` (development) tags.
### 4. Update the Makefile
The Makefile needs to be updated in several places to support building and testing the new backend:
**Step 4a: Add to `.NOTPARALLEL`**
Add `backends/<backend-name>` to the `.NOTPARALLEL` line (around line 2) to prevent parallel execution conflicts:
```makefile
.NOTPARALLEL: ... backends/<backend-name>
```
**Step 4b: Add to `prepare-test-extra`**
Add the backend to the `prepare-test-extra` target (around line 312) to prepare it for testing:
```makefile
prepare-test-extra: protogen-python
...
$(MAKE) -C backend/python/<backend-name>
```
**Step 4c: Add to `test-extra`**
Add the backend to the `test-extra` target (around line 319) to run its tests:
```makefile
test-extra: prepare-test-extra
...
$(MAKE) -C backend/python/<backend-name> test
```
**Step 4d: Add Backend Definition**
Add a backend definition variable in the backend definitions section (around line 428-457). The format depends on the backend type:
**For Python backends with root context** (like `faster-whisper`, `bark`):
```makefile
BACKEND_<BACKEND_NAME> = <backend-name>|python|.|false|true
```
**For Python backends with `./backend` context** (like `chatterbox`, `moonshine`):
```makefile
BACKEND_<BACKEND_NAME> = <backend-name>|python|./backend|false|true
```
**For Go backends**:
```makefile
BACKEND_<BACKEND_NAME> = <backend-name>|golang|.|false|true
```
**Step 4e: Generate Docker Build Target**
Add an eval call to generate the docker-build target (around line 480-501):
```makefile
$(eval $(call generate-docker-build-target,$(BACKEND_<BACKEND_NAME>)))
```
**Step 4f: Add to `docker-build-backends`**
Add `docker-build-<backend-name>` to the `docker-build-backends` target (around line 507):
```makefile
docker-build-backends: ... docker-build-<backend-name>
```
**Determining the Context:**
- If the backend is in `backend/python/<backend-name>/` and uses `./backend` as context in the workflow file, use `./backend` context
- If the backend is in `backend/python/<backend-name>/` but uses `.` as context in the workflow file, use `.` context
- Check similar backends to determine the correct context
### 5. Verification Checklist
After adding a new backend, verify:
- [ ] Backend directory structure is complete with all necessary files
- [ ] Build configurations added to `.github/workflows/backend.yml` for all desired platforms
- [ ] Meta definition added to `backend/index.yaml` in the `## metas` section
- [ ] Image entries added to `backend/index.yaml` for all build variants (latest + development)
- [ ] Tag suffixes match between workflow file and index.yaml
- [ ] Makefile updated with all 6 required changes (`.NOTPARALLEL`, `prepare-test-extra`, `test-extra`, backend definition, docker-build target eval, `docker-build-backends`)
- [ ] No YAML syntax errors (check with linter)
- [ ] No Makefile syntax errors (check with linter)
- [ ] Follows the same pattern as similar backends (e.g., if it's a transcription backend, follow `faster-whisper` pattern)
### 6. Example: Adding a Python Backend
For reference, when `moonshine` was added:
- **Files created**: `backend/python/moonshine/{backend.py, Makefile, install.sh, protogen.sh, requirements.txt, run.sh, test.py, test.sh}`
- **Workflow entries**: 3 build configurations (CPU, CUDA 12, CUDA 13)
- **Index entries**: 1 meta definition + 6 image entries (cpu, cuda12, cuda13 × latest/development)
- **Makefile updates**:
- Added to `.NOTPARALLEL` line
- Added to `prepare-test-extra` and `test-extra` targets
- Added `BACKEND_MOONSHINE = moonshine|python|./backend|false|true`
- Added eval for docker-build target generation
- Added `docker-build-moonshine` to `docker-build-backends`
# 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`
## Tool Call Parsing Maintenance
When working on JSON/XML tool call parsing functionality, always check llama.cpp for reference implementation and updates:
### Checking for XML Parsing Changes
1. **Review XML Format Definitions**: Check `llama.cpp/common/chat-parser-xml-toolcall.h` for `xml_tool_call_format` struct changes
2. **Review Parsing Logic**: Check `llama.cpp/common/chat-parser-xml-toolcall.cpp` for parsing algorithm updates
3. **Review Format Presets**: Check `llama.cpp/common/chat-parser.cpp` for new XML format presets (search for `xml_tool_call_format form`)
4. **Review Model Lists**: Check `llama.cpp/common/chat.h` for `COMMON_CHAT_FORMAT_*` enum values that use XML parsing:
- `COMMON_CHAT_FORMAT_GLM_4_5`
- `COMMON_CHAT_FORMAT_MINIMAX_M2`
- `COMMON_CHAT_FORMAT_KIMI_K2`
- `COMMON_CHAT_FORMAT_QWEN3_CODER_XML`
- `COMMON_CHAT_FORMAT_APRIEL_1_5`
- `COMMON_CHAT_FORMAT_XIAOMI_MIMO`
- Any new formats added
### Model Configuration Options
Always check `llama.cpp` for new model configuration options that should be supported in LocalAI:
1. **Check Server Context**: Review `llama.cpp/tools/server/server-context.cpp` for new parameters
2. **Check Chat Params**: Review `llama.cpp/common/chat.h` for `common_chat_params` struct changes
3. **Check Server Options**: Review `llama.cpp/tools/server/server.cpp` for command-line argument changes
4. **Examples of options to check**:
- `ctx_shift` - Context shifting support
- `parallel_tool_calls` - Parallel tool calling
- `reasoning_format` - Reasoning format options
- Any new flags or parameters
### Implementation Guidelines
1. **Feature Parity**: Always aim for feature parity with llama.cpp's implementation
2. **Test Coverage**: Add tests for new features matching llama.cpp's behavior
3. **Documentation**: Update relevant documentation when adding new formats or options
4. **Backward Compatibility**: Ensure changes don't break existing functionality
### Files to Monitor
- `llama.cpp/common/chat-parser-xml-toolcall.h` - Format definitions
- `llama.cpp/common/chat-parser-xml-toolcall.cpp` - Parsing logic
- `llama.cpp/common/chat-parser.cpp` - Format presets and model-specific handlers
- `llama.cpp/common/chat.h` - Format enums and parameter structures
- `llama.cpp/tools/server/server-context.cpp` - Server configuration options

View File

@@ -30,7 +30,6 @@ Thank you for your interest in contributing to LocalAI! We appreciate your time
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`
## Contributing
@@ -77,21 +76,7 @@ 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
### Gallery YAML Schema
LocalAI provides a JSON Schema for gallery model YAML files at:
`core/schema/gallery-model.schema.json`
This schema mirrors the internal gallery model configuration and can be used by editors (such as VS Code) to enable autocomplete, validation, and inline documentation when creating or modifying gallery files.
To use it with the YAML language server, add the following comment at the top of a gallery YAML file:
```yaml
# yaml-language-server: $schema=../core/schema/gallery-model.schema.json
```
## Community and Communication
- You can reach out via the Github issue tracker.

View File

@@ -1,202 +1,36 @@
ARG BASE_IMAGE=ubuntu:24.04
ARG IMAGE_TYPE=extras
ARG BASE_IMAGE=ubuntu:22.04
ARG GRPC_BASE_IMAGE=${BASE_IMAGE}
ARG INTEL_BASE_IMAGE=${BASE_IMAGE}
ARG UBUNTU_CODENAME=noble
FROM ${BASE_IMAGE} AS requirements
ENV DEBIAN_FRONTEND=noninteractive
RUN apt-get update && \
apt-get install -y --no-install-recommends \
ca-certificates curl wget espeak-ng libgomp1 \
ffmpeg libopenblas0 libopenblas-dev && \
apt-get clean && \
rm -rf /var/lib/apt/lists/*
# The requirements-drivers target is for BUILD_TYPE specific items. If you need to install something specific to CUDA, or specific to ROCM, it goes here.
FROM requirements AS requirements-drivers
ARG BUILD_TYPE
ARG CUDA_MAJOR_VERSION=12
ARG CUDA_MINOR_VERSION=0
ARG SKIP_DRIVERS=false
ARG TARGETARCH
ARG TARGETVARIANT
ENV BUILD_TYPE=${BUILD_TYPE}
ARG UBUNTU_VERSION=2404
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 && \
apt-get install -y libglm-dev cmake libxcb-dri3-0 libxcb-present0 libpciaccess0 \
libpng-dev libxcb-keysyms1-dev libxcb-dri3-dev libx11-dev g++ gcc \
libwayland-dev libxrandr-dev libxcb-randr0-dev libxcb-ewmh-dev \
git python-is-python3 bison libx11-xcb-dev liblz4-dev libzstd-dev \
ocaml-core ninja-build pkg-config libxml2-dev wayland-protocols python3-jsonschema \
clang-format qtbase5-dev qt6-base-dev libxcb-glx0-dev sudo xz-utils mesa-vulkan-drivers
if [ "amd64" = "$TARGETARCH" ]; then
wget "https://sdk.lunarg.com/sdk/download/1.4.328.1/linux/vulkansdk-linux-x86_64-1.4.328.1.tar.xz" && \
tar -xf vulkansdk-linux-x86_64-1.4.328.1.tar.xz && \
rm vulkansdk-linux-x86_64-1.4.328.1.tar.xz && \
mkdir -p /opt/vulkan-sdk && \
mv 1.4.328.1 /opt/vulkan-sdk/ && \
cd /opt/vulkan-sdk/1.4.328.1 && \
./vulkansdk --no-deps --maxjobs \
vulkan-loader \
vulkan-validationlayers \
vulkan-extensionlayer \
vulkan-tools \
shaderc && \
cp -rfv /opt/vulkan-sdk/1.4.328.1/x86_64/bin/* /usr/bin/ && \
cp -rfv /opt/vulkan-sdk/1.4.328.1/x86_64/lib/* /usr/lib/x86_64-linux-gnu/ && \
cp -rfv /opt/vulkan-sdk/1.4.328.1/x86_64/include/* /usr/include/ && \
cp -rfv /opt/vulkan-sdk/1.4.328.1/x86_64/share/* /usr/share/ && \
rm -rf /opt/vulkan-sdk
fi
if [ "arm64" = "$TARGETARCH" ]; then
mkdir vulkan && cd vulkan && \
curl -L -o vulkan-sdk.tar.xz https://github.com/mudler/vulkan-sdk-arm/releases/download/1.4.335.0/vulkansdk-ubuntu-24.04-arm-1.4.335.0.tar.xz && \
tar -xvf vulkan-sdk.tar.xz && \
rm vulkan-sdk.tar.xz && \
cd 1.4.335.0 && \
cp -rfv aarch64/bin/* /usr/bin/ && \
cp -rfv aarch64/lib/* /usr/lib/aarch64-linux-gnu/ && \
cp -rfv aarch64/include/* /usr/include/ && \
cp -rfv aarch64/share/* /usr/share/ && \
cd ../.. && \
rm -rf vulkan
fi
ldconfig && \
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
FROM ${BASE_IMAGE} AS requirements-core
ARG GO_VERSION=1.25.4
ARG CMAKE_VERSION=3.31.10
USER root
ARG GO_VERSION=1.22.6
ARG CMAKE_VERSION=3.26.4
ARG CMAKE_FROM_SOURCE=false
ARG TARGETARCH
ARG TARGETVARIANT
ENV DEBIAN_FRONTEND=noninteractive
ENV EXTERNAL_GRPC_BACKENDS="coqui:/build/backend/python/coqui/run.sh,transformers:/build/backend/python/transformers/run.sh,rerankers:/build/backend/python/rerankers/run.sh,autogptq:/build/backend/python/autogptq/run.sh,bark:/build/backend/python/bark/run.sh,diffusers:/build/backend/python/diffusers/run.sh,faster-whisper:/build/backend/python/faster-whisper/run.sh,kokoro:/build/backend/python/kokoro/run.sh,vllm:/build/backend/python/vllm/run.sh,exllama2:/build/backend/python/exllama2/run.sh"
RUN apt-get update && \
apt-get install -y --no-install-recommends \
build-essential \
ccache \
ca-certificates espeak-ng \
ca-certificates \
curl libssl-dev \
git \
git-lfs \
unzip upx-ucl python3 python-is-python3 && \
unzip upx-ucl && \
apt-get clean && \
rm -rf /var/lib/apt/lists/*
# Install CMake (the version in 22.04 is too old)
RUN <<EOT bash
if [ "${CMAKE_FROM_SOURCE}" = "true" ]; then
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 && \
@@ -225,11 +59,124 @@ RUN test -n "$TARGETARCH" \
RUN echo "Target Architecture: $TARGETARCH"
RUN echo "Target Variant: $TARGETVARIANT"
# Cuda
ENV PATH=/usr/local/cuda/bin:${PATH}
# HipBLAS requirements
ENV PATH=/opt/rocm/bin:${PATH}
# OpenBLAS requirements and stable diffusion
RUN apt-get update && \
apt-get install -y --no-install-recommends \
libopenblas-dev && \
apt-get clean && \
rm -rf /var/lib/apt/lists/*
WORKDIR /build
###################################
###################################
# The requirements-extras target is for any builds with IMAGE_TYPE=extras. It should not be placed in this target unless every IMAGE_TYPE=extras build will use it
FROM requirements-core AS requirements-extras
# Install uv as a system package
RUN curl -LsSf https://astral.sh/uv/install.sh | UV_INSTALL_DIR=/usr/bin sh
ENV PATH="/root/.cargo/bin:${PATH}"
RUN curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh -s -- -y
RUN apt-get update && \
apt-get install -y --no-install-recommends \
espeak-ng \
espeak \
python3-pip \
python-is-python3 \
python3-dev llvm \
python3-venv && \
apt-get clean && \
rm -rf /var/lib/apt/lists/* && \
pip install --upgrade pip
# Install grpcio-tools (the version in 22.04 is too old)
RUN pip install --user grpcio-tools
###################################
###################################
# The requirements-drivers target is for BUILD_TYPE specific items. If you need to install something specific to CUDA, or specific to ROCM, it goes here.
# This target will be built on top of requirements-core or requirements-extras as retermined by the IMAGE_TYPE build-arg
FROM requirements-${IMAGE_TYPE} AS requirements-drivers
ARG BUILD_TYPE
ARG CUDA_MAJOR_VERSION=12
ARG CUDA_MINOR_VERSION=0
ARG SKIP_DRIVERS=false
ENV BUILD_TYPE=${BUILD_TYPE}
# Vulkan requirements
RUN <<EOT bash
if [ "${BUILD_TYPE}" = "vulkan" ] && [ "${SKIP_DRIVERS}" = "false" ]; then
apt-get update && \
apt-get install -y --no-install-recommends \
software-properties-common pciutils wget gpg-agent && \
wget -qO - https://packages.lunarg.com/lunarg-signing-key-pub.asc | apt-key add - && \
wget -qO /etc/apt/sources.list.d/lunarg-vulkan-jammy.list https://packages.lunarg.com/vulkan/lunarg-vulkan-jammy.list && \
apt-get update && \
apt-get install -y \
vulkan-sdk && \
apt-get clean && \
rm -rf /var/lib/apt/lists/*
fi
EOT
# CuBLAS requirements
RUN <<EOT bash
if [ "${BUILD_TYPE}" = "cublas" ] && [ "${SKIP_DRIVERS}" = "false" ]; then
apt-get update && \
apt-get install -y --no-install-recommends \
software-properties-common pciutils
if [ "amd64" = "$TARGETARCH" ]; then
curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64/cuda-keyring_1.1-1_all.deb
fi
if [ "arm64" = "$TARGETARCH" ]; then
curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/arm64/cuda-keyring_1.1-1_all.deb
fi
dpkg -i cuda-keyring_1.1-1_all.deb && \
rm -f cuda-keyring_1.1-1_all.deb && \
apt-get update && \
apt-get install -y --no-install-recommends \
cuda-nvcc-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
libcufft-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
libcurand-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
libcublas-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
libcusparse-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
libcusolver-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} && \
apt-get clean && \
rm -rf /var/lib/apt/lists/*
fi
EOT
# If we are building with clblas support, we need the libraries for the builds
RUN if [ "${BUILD_TYPE}" = "clblas" ] && [ "${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
###################################
###################################
@@ -238,29 +185,72 @@ WORKDIR /build
# 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
ARG UBUNTU_CODENAME=noble
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 ${UBUNTU_CODENAME}/lts/2350 unified" > /etc/apt/sources.list.d/intel-graphics.list
RUN echo "deb [arch=amd64 signed-by=/usr/share/keyrings/intel-graphics.gpg] https://repositories.intel.com/gpu/ubuntu jammy/lts/2350 unified" > /etc/apt/sources.list.d/intel-graphics.list
###################################
###################################
# The grpc target does one thing, it builds and installs GRPC. This is in it's own layer so that it can be effectively cached by CI.
# You probably don't need to change anything here, and if you do, make sure that CI is adjusted so that the cache continues to work.
FROM ${GRPC_BASE_IMAGE} AS grpc
# This is a bit of a hack, but it's required in order to be able to effectively cache this layer in CI
ARG GRPC_MAKEFLAGS="-j4 -Otarget"
ARG GRPC_VERSION=v1.65.0
ARG CMAKE_FROM_SOURCE=false
ARG CMAKE_VERSION=3.26.4
ENV MAKEFLAGS=${GRPC_MAKEFLAGS}
WORKDIR /build
RUN apt-get update && \
apt-get install -y --no-install-recommends \
intel-oneapi-runtime-libs && \
ca-certificates \
build-essential curl libssl-dev \
git && \
apt-get clean && \
rm -rf /var/lib/apt/lists/*
# Install CMake (the version in 22.04 is too old)
RUN <<EOT bash
if [ "${CMAKE_FROM_SOURCE}}" = "true" ]; then
curl -L -s https://github.com/Kitware/CMake/releases/download/v${CMAKE_VERSION}/cmake-${CMAKE_VERSION}.tar.gz -o cmake.tar.gz && tar xvf cmake.tar.gz && cd cmake-${CMAKE_VERSION} && ./configure && make && make install
else
apt-get update && \
apt-get install -y \
cmake && \
apt-get clean && \
rm -rf /var/lib/apt/lists/*
fi
EOT
# We install GRPC to a different prefix here so that we can copy in only the build artifacts later
# saves several hundred MB on the final docker image size vs copying in the entire GRPC source tree
# and running make install in the target container
RUN git clone --recurse-submodules --jobs 4 -b ${GRPC_VERSION} --depth 1 --shallow-submodules https://github.com/grpc/grpc && \
mkdir -p /build/grpc/cmake/build && \
cd /build/grpc/cmake/build && \
sed -i "216i\ TESTONLY" "../../third_party/abseil-cpp/absl/container/CMakeLists.txt" && \
cmake -DgRPC_INSTALL=ON -DgRPC_BUILD_TESTS=OFF -DCMAKE_INSTALL_PREFIX:PATH=/opt/grpc ../.. && \
make && \
make install && \
rm -rf /build
###################################
###################################
# The builder-base target has the arguments, variables, and copies shared between full builder images and the uncompiled devcontainer
FROM build-requirements AS builder-base
FROM requirements-drivers AS builder-base
ARG GO_TAGS=""
ARG GO_TAGS="tts p2p"
ARG GRPC_BACKENDS
ARG MAKEFLAGS
ARG LD_FLAGS="-s -w"
ARG TARGETARCH
ARG TARGETVARIANT
ENV GRPC_BACKENDS=${GRPC_BACKENDS}
ENV GO_TAGS=${GO_TAGS}
ENV MAKEFLAGS=${MAKEFLAGS}
@@ -274,7 +264,9 @@ RUN echo "GO_TAGS: $GO_TAGS" && echo "TARGETARCH: $TARGETARCH"
WORKDIR /build
# We need protoc installed, and the version in 22.04 is too old.
# We need protoc installed, and the version in 22.04 is too old. We will create one as part installing the GRPC build below
# but that will also being in a newer version of absl which stablediffusion cannot compile with. This version of protoc is only
# here so that we can generate the grpc code for the stablediffusion build
RUN <<EOT bash
if [ "amd64" = "$TARGETARCH" ]; then
curl -L -s https://github.com/protocolbuffers/protobuf/releases/download/v27.1/protoc-27.1-linux-x86_64.zip -o protoc.zip && \
@@ -291,39 +283,35 @@ 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
FROM builder-base AS builder
# Install the pre-built GRPC
COPY --from=grpc /opt/grpc /usr/local
# Rebuild with defaults backends
WORKDIR /build
COPY . .
COPY .git .
RUN make prepare
## Build the binary
## If we're on arm64 AND using cublas/hipblas, skip some of the llama-compat backends to save space
## Otherwise just run the normal build
RUN make build
## If it's CUDA or hipblas, we want to skip some of the llama-compat backends to save space
## We only leave the most CPU-optimized variant and the fallback for the cublas/hipblas build
## (both will use CUDA or hipblas for the actual computation)
RUN if [ "${BUILD_TYPE}" = "cublas" ] || [ "${BUILD_TYPE}" = "hipblas" ]; then \
SKIP_GRPC_BACKEND="backend-assets/grpc/llama-cpp-avx512 backend-assets/grpc/llama-cpp-avx backend-assets/grpc/llama-cpp-avx2" make build; \
else \
make build; \
fi
RUN 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
###################################
###################################
@@ -333,11 +321,24 @@ RUN make build
FROM builder-base AS devcontainer
ARG FFMPEG
COPY --from=grpc /opt/grpc /usr/local
COPY .devcontainer-scripts /.devcontainer-scripts
# Add FFmpeg
RUN if [ "${FFMPEG}" = "true" ]; then \
apt-get update && \
apt-get install -y --no-install-recommends \
ffmpeg && \
apt-get clean && \
rm -rf /var/lib/apt/lists/* \
; fi
RUN apt-get update && \
apt-get install -y --no-install-recommends \
ssh less
ssh less wget
# For the devcontainer, leave apt functional in case additional devtools are needed at runtime.
RUN go install github.com/go-delve/delve/cmd/dlv@latest
@@ -351,27 +352,103 @@ RUN go install github.com/mikefarah/yq/v4@latest
# If you cannot find a more suitable place for an addition, this layer is a suitable place for it.
FROM requirements-drivers
ARG FFMPEG
ARG BUILD_TYPE
ARG BUILD_PLATFORM
ARG TARGETARCH
ARG IMAGE_TYPE=extras
ARG EXTRA_BACKENDS
ARG MAKEFLAGS
ENV BUILD_TYPE=${BUILD_TYPE}
ENV BUILD_PLATFORM=${BUILD_PLATFORM}
ENV REBUILD=false
ENV HEALTHCHECK_ENDPOINT=http://localhost:8080/readyz
ENV MAKEFLAGS=${MAKEFLAGS}
ARG CUDA_MAJOR_VERSION=12
ENV NVIDIA_DRIVER_CAPABILITIES=compute,utility
ENV NVIDIA_REQUIRE_CUDA="cuda>=${CUDA_MAJOR_VERSION}.0"
ENV NVIDIA_VISIBLE_DEVICES=all
WORKDIR /
# Add FFmpeg
RUN if [ "${FFMPEG}" = "true" ]; then \
apt-get update && \
apt-get install -y --no-install-recommends \
ffmpeg && \
apt-get clean && \
rm -rf /var/lib/apt/lists/* \
; fi
COPY ./entrypoint.sh .
WORKDIR /build
# we start fresh & re-copy all assets because `make build` does not clean up nicely after itself
# so when `entrypoint.sh` runs `make build` again (which it does by default), the build would fail
# see https://github.com/go-skynet/LocalAI/pull/658#discussion_r1241971626 and
# https://github.com/go-skynet/LocalAI/pull/434
COPY . .
COPY --from=builder /build/sources ./sources/
COPY --from=grpc /opt/grpc /usr/local
RUN make prepare-sources
# Copy the binary
COPY --from=builder /build/local-ai ./
# Copy shared libraries for piper
COPY --from=builder /build/sources/go-piper/piper-phonemize/pi/lib/* /usr/lib/
# Change the shell to bash so we can use [[ tests below
SHELL ["/bin/bash", "-c"]
# We try to strike a balance between individual layer size (as that affects total push time) and total image size
# Splitting the backends into more groups with fewer items results in a larger image, but a smaller size for the largest layer
# Splitting the backends into fewer groups with more items results in a smaller image, but a larger size for the largest layer
RUN if [[ ( "${IMAGE_TYPE}" == "extras ")]]; then \
apt-get -qq -y install espeak-ng \
; fi
RUN if [[ ( "${EXTRA_BACKENDS}" =~ "coqui" || -z "${EXTRA_BACKENDS}" ) && "$IMAGE_TYPE" == "extras" ]]; then \
make -C backend/python/coqui \
; fi && \
if [[ ( "${EXTRA_BACKENDS}" =~ "faster-whisper" || -z "${EXTRA_BACKENDS}" ) && "$IMAGE_TYPE" == "extras" ]]; then \
make -C backend/python/faster-whisper \
; fi && \
if [[ ( "${EXTRA_BACKENDS}" =~ "diffusers" || -z "${EXTRA_BACKENDS}" ) && "$IMAGE_TYPE" == "extras" ]]; then \
make -C backend/python/diffusers \
; fi
RUN if [[ ( "${EXTRA_BACKENDS}" =~ "kokoro" || -z "${EXTRA_BACKENDS}" ) && "$IMAGE_TYPE" == "extras" ]]; then \
make -C backend/python/kokoro \
; fi && \
if [[ ( "${EXTRA_BACKENDS}" =~ "exllama2" || -z "${EXTRA_BACKENDS}" ) && "$IMAGE_TYPE" == "extras" ]]; then \
make -C backend/python/exllama2 \
; fi && \
if [[ ( "${EXTRA_BACKENDS}" =~ "transformers" || -z "${EXTRA_BACKENDS}" ) && "$IMAGE_TYPE" == "extras" ]]; then \
make -C backend/python/transformers \
; fi
RUN if [[ ( "${EXTRA_BACKENDS}" =~ "vllm" || -z "${EXTRA_BACKENDS}" ) && "$IMAGE_TYPE" == "extras" ]]; then \
make -C backend/python/vllm \
; fi && \
if [[ ( "${EXTRA_BACKENDS}" =~ "autogptq" || -z "${EXTRA_BACKENDS}" ) && "$IMAGE_TYPE" == "extras" ]]; then \
make -C backend/python/autogptq \
; fi && \
if [[ ( "${EXTRA_BACKENDS}" =~ "bark" || -z "${EXTRA_BACKENDS}" ) && "$IMAGE_TYPE" == "extras" ]]; then \
make -C backend/python/bark \
; fi && \
if [[ ( "${EXTRA_BACKENDS}" =~ "rerankers" || -z "${EXTRA_BACKENDS}" ) && "$IMAGE_TYPE" == "extras" ]]; then \
make -C backend/python/rerankers \
; fi
# 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
VOLUME /build/models
EXPOSE 8080
ENTRYPOINT [ "/entrypoint.sh" ]
ENTRYPOINT [ "/build/entrypoint.sh" ]

View File

@@ -1,4 +1,4 @@
ARG BASE_IMAGE=ubuntu:24.04
ARG BASE_IMAGE=ubuntu:22.04
FROM ${BASE_IMAGE}

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

969
Makefile
View File

File diff suppressed because it is too large Load Diff

259
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>
@@ -30,10 +31,10 @@
<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>
@@ -43,162 +44,35 @@
> :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/) [🖼️ Models](https://models.localai.io/) [🚀 Roadmap](https://github.com/mudler/LocalAI/issues?q=is%3Aissue+is%3Aopen+label%3Aroadmap) [🥽 Demo](https://demo.localai.io) [🌍 Explorer](https://explorer.localai.io) [🛫 Examples](https://github.com/mudler/LocalAI-examples)
[![tests](https://github.com/go-skynet/LocalAI/actions/workflows/test.yml/badge.svg)](https://github.com/go-skynet/LocalAI/actions/workflows/test.yml)[![Build and Release](https://github.com/go-skynet/LocalAI/actions/workflows/release.yaml/badge.svg)](https://github.com/go-skynet/LocalAI/actions/workflows/release.yaml)[![build container images](https://github.com/go-skynet/LocalAI/actions/workflows/image.yml/badge.svg)](https://github.com/go-skynet/LocalAI/actions/workflows/image.yml)[![Bump dependencies](https://github.com/go-skynet/LocalAI/actions/workflows/bump_deps.yaml/badge.svg)](https://github.com/go-skynet/LocalAI/actions/workflows/bump_deps.yaml)[![Artifact Hub](https://img.shields.io/endpoint?url=https://artifacthub.io/badge/repository/localai)](https://artifacthub.io/packages/search?repo=localai)
**LocalAI** is the free, Open Source OpenAI alternative. LocalAI act as a drop-in replacement REST API that's compatible with OpenAI (Elevenlabs, Anthropic... ) API specifications for local AI inferencing. It allows you to run LLMs, generate images, audio (and not only) locally or on-prem with consumer grade hardware, supporting multiple model families. Does not require GPU. It is created and maintained by [Ettore Di Giacinto](https://github.com/mudler).
**LocalAI** is the free, Open Source OpenAI alternative. LocalAI act as a drop-in replacement REST API thats compatible with OpenAI (Elevenlabs, Anthropic... ) API specifications for local AI inferencing. It allows you to run LLMs, generate images, audio (and not only) locally or on-prem with consumer grade hardware, supporting multiple model families. Does not require GPU. It is created and maintained by [Ettore Di Giacinto](https://github.com/mudler).
## 📚🆕 Local Stack Family
🆕 LocalAI is now part of a comprehensive suite of AI tools designed to work together:
<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>
## Screenshots / Video
### Youtube video
<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>
### 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
![screen](https://github.com/mudler/LocalAI/assets/2420543/20b5ccd2-8393-44f0-aaf6-87a23806381e)
Run the installer script:
```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
```
# CPU only image:
docker run -ti --name local-ai -p 8080:8080 localai/localai:latest-cpu
### NVIDIA GPU Images:
```bash
# CUDA 13.0
docker run -ti --name local-ai -p 8080:8080 --gpus all localai/localai:latest-gpu-nvidia-cuda-13
# CUDA 12.0
# Nvidia GPU:
docker run -ti --name local-ai -p 8080:8080 --gpus all localai/localai:latest-gpu-nvidia-cuda-12
# NVIDIA Jetson (L4T) ARM64
# CUDA 12 (for Nvidia AGX Orin and similar platforms)
docker run -ti --name local-ai -p 8080:8080 --gpus all localai/localai:latest-nvidia-l4t-arm64
# CPU and GPU image (bigger size):
docker run -ti --name local-ai -p 8080:8080 localai/localai:latest
# CUDA 13 (for Nvidia DGX Spark)
docker run -ti --name local-ai -p 8080:8080 --gpus all localai/localai:latest-nvidia-l4t-arm64-cuda-13
```
### 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
# AIO images (it will pre-download a set of models ready for use, see https://localai.io/basics/container/)
docker run -ti --name local-ai -p 8080:8080 localai/localai:latest-aio-cpu
# NVIDIA CUDA 13 version
docker run -ti --name local-ai -p 8080:8080 --gpus all localai/localai:latest-aio-gpu-nvidia-cuda-13
# NVIDIA CUDA 12 version
docker run -ti --name local-ai -p 8080:8080 --gpus all localai/localai:latest-aio-gpu-nvidia-cuda-12
# 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
```
For more information about the AIO images and pre-downloaded models, see [Container Documentation](https://localai.io/basics/container/).
To load models:
```bash
@@ -214,26 +88,10 @@ local-ai run https://gist.githubusercontent.com/.../phi-2.yaml
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)
[💻 Getting started](https://localai.io/basics/getting_started/index.html)
## 📰 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 )
@@ -247,9 +105,21 @@ For more information, see [💻 Getting started](https://localai.io/basics/getti
Roadmap items: [List of issues](https://github.com/mudler/LocalAI/issues?q=is%3Aissue+is%3Aopen+label%3Aroadmap)
## 🔥🔥 Hot topics (looking for help):
- Multimodal with vLLM and Video understanding: https://github.com/mudler/LocalAI/pull/3729
- Realtime API https://github.com/mudler/LocalAI/issues/3714
- WebUI improvements: https://github.com/mudler/LocalAI/issues/2156
- Backends v2: https://github.com/mudler/LocalAI/issues/1126
- Improving UX v2: https://github.com/mudler/LocalAI/issues/1373
- Assistant API: https://github.com/mudler/LocalAI/issues/1273
- Vulkan: https://github.com/mudler/LocalAI/issues/1647
- Anthropic API: https://github.com/mudler/LocalAI/issues/1808
If you want to help and contribute, issues up for grabs: https://github.com/mudler/LocalAI/issues?q=is%3Aissue+is%3Aopen+label%3A%22up+for+grabs%22
## 🚀 [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 to Audio](https://localai.io/features/text-to-audio/)
- 🔈 [Audio to Text](https://localai.io/features/audio-to-text/) (Audio transcription with `whisper.cpp`)
@@ -259,70 +129,14 @@ Roadmap items: [List of issues](https://github.com/mudler/LocalAI/issues?q=is%3A
- ✍️ [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!
## 🧩 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 12/13, ROCm, Intel SYCL, Vulkan, Metal, CPU |
| **vLLM** | Fast LLM inference with PagedAttention | CUDA 12/13, ROCm, Intel |
| **transformers** | HuggingFace transformers framework | CUDA 12/13, ROCm, Intel, CPU |
| **exllama2** | GPTQ inference library | CUDA 12/13 |
| **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 12/13, ROCm, Intel SYCL, Vulkan, CPU |
| **faster-whisper** | Fast Whisper with CTranslate2 | CUDA 12/13, ROCm, Intel, CPU |
| **bark** | Text-to-audio generation | CUDA 12/13, ROCm, Intel |
| **bark-cpp** | C++ implementation of Bark | CUDA, Metal, CPU |
| **coqui** | Advanced TTS with 1100+ languages | CUDA 12/13, ROCm, Intel, CPU |
| **kokoro** | Lightweight TTS model | CUDA 12/13, ROCm, Intel, CPU |
| **chatterbox** | Production-grade TTS | CUDA 12/13, 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 12/13, ROCm, CPU |
| **vibevoice** | Real-time TTS with voice cloning | CUDA 12/13, ROCm, Intel, CPU |
### Image & Video Generation
| Backend | Description | Acceleration Support |
|---------|-------------|---------------------|
| **stablediffusion.cpp** | Stable Diffusion in C/C++ | CUDA 12/13, Intel SYCL, Vulkan, CPU |
| **diffusers** | HuggingFace diffusion models | CUDA 12/13, ROCm, Intel, Metal, CPU |
### Specialized AI Tasks
| Backend | Description | Acceleration Support |
|---------|-------------|---------------------|
| **rfdetr** | Real-time object detection | CUDA 12/13, Intel, CPU |
| **rerankers** | Document reranking API | CUDA 12/13, 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 12** | All CUDA-compatible backends | Nvidia hardware |
| **NVIDIA CUDA 13** | All CUDA-compatible backends | Nvidia hardware |
| **AMD ROCm** | llama.cpp, whisper, vllm, transformers, diffusers, rerankers, coqui, kokoro, bark, neutts, vibevoice | AMD Graphics |
| **Intel oneAPI** | llama.cpp, whisper, stablediffusion, vllm, transformers, diffusers, rfdetr, rerankers, exllama2, coqui, kokoro, bark, vibevoice | 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 (CUDA 12)** | llama.cpp, whisper, stablediffusion, diffusers, rfdetr | ARM64 embedded AI (AGX Orin, etc.) |
| **NVIDIA Jetson (CUDA 13)** | llama.cpp, whisper, stablediffusion, diffusers, rfdetr | ARM64 embedded AI (DGX Spark) |
| **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
@@ -334,18 +148,9 @@ WebUIs:
- 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
@@ -407,17 +212,13 @@ A huge thank you to our generous sponsors who support this project covering CI e
<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">
<img height="200" src="https://github.com/go-skynet/LocalAI/assets/2420543/68a6f3cb-8a65-4a4d-99b5-6417a8905512">
</a>
<a href="https://www.premai.io/" target="blank">
<img height="200" src="https://github.com/mudler/LocalAI/assets/2420543/42e4ca83-661e-4f79-8e46-ae43689683d6"> <br>
</a>
</p>
### Individual sponsors
A special thanks to individual sponsors that contributed to the project, a full list is in [Github](https://github.com/sponsors/mudler) and [buymeacoffee](https://buymeacoffee.com/mudler), a special shout out goes to [drikster80](https://github.com/drikster80) for being generous. Thank you everyone!
## 🌟 Star history
[![LocalAI Star history Chart](https://api.star-history.com/svg?repos=go-skynet/LocalAI&type=Date)](https://star-history.com/#go-skynet/LocalAI&Date)

View File

@@ -1,8 +1,7 @@
embeddings: true
name: text-embedding-ada-002
backend: llama-cpp
embeddings: true
parameters:
model: huggingface://bartowski/granite-embedding-107m-multilingual-GGUF/granite-embedding-107m-multilingual-f16.gguf
model: huggingface://hugging-quants/Llama-3.2-1B-Instruct-Q4_K_M-GGUF/llama-3.2-1b-instruct-q4_k_m.gguf
usage: |
You can test this model with curl like this:

View File

@@ -1,13 +1,7 @@
name: jina-reranker-v1-base-en
reranking: true
f16: true
backend: rerankers
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
model: cross-encoder
usage: |
You can test this model with curl like this:

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

View File

@@ -1,8 +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
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}/rerank.yaml,/aio/${PROFILE}/text-to-speech.yaml,/aio/${PROFILE}/image-gen.yaml,/aio/${PROFILE}/text-to-text.yaml,/aio/${PROFILE}/speech-to-text.yaml,/aio/${PROFILE}/vision.yaml}"
check_vars
echo "===> Starting LocalAI[$PROFILE] with the following models: $MODELS"
exec /entrypoint.sh "$@"
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

@@ -1,13 +1,7 @@
name: jina-reranker-v1-base-en
reranking: true
f16: true
backend: rerankers
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
model: cross-encoder
usage: |
You can test this model with curl like this:

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

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
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

@@ -1,13 +1,7 @@
name: jina-reranker-v1-base-en
reranking: true
f16: true
backend: rerankers
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
model: cross-encoder
usage: |
You can test this model with curl like this:

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 +1,103 @@
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
context_size: 8192
f16: false
parameters:
model: localai-functioncall-qwen2.5-7b-v0.5-q4_k_m.gguf
model: huggingface://NousResearch/Hermes-2-Pro-Llama-3-8B-GGUF/Hermes-2-Pro-Llama-3-8B-Q4_K_M.gguf
stopwords:
- <|im_end|>
- <dummy32000>
- </s>
- "<|im_end|>"
- "<dummy32000>"
- "</tool_call>"
- "<|eot_id|>"
- "<|end_of_text|>"
function:
# disable injecting the "answer" tool
disable_no_action: true
grammar:
# This allows the grammar to also return messages
mixed_mode: true
# Suffix to add to the grammar
#prefix: '<tool_call>\n'
# Force parallel calls in the grammar
# parallel_calls: true
return_name_in_function_response: true
# Without grammar uncomment the lines below
# Warning: this is relying only on the capability of the
# LLM model to generate the correct function call.
json_regex_match:
- "(?s)<tool_call>(.*?)</tool_call>"
- "(?s)<tool_call>(.*?)"
replace_llm_results:
# Drop the scratchpad content from responses
- key: "(?s)<scratchpad>.*</scratchpad>"
value: ""
replace_function_results:
# Replace everything that is not JSON array or object
#
- key: '(?s)^[^{\[]*'
value: ""
- key: '(?s)[^}\]]*$'
value: ""
- key: "'([^']*?)'"
value: "_DQUOTE_${1}_DQUOTE_"
- key: '\\"'
value: "__TEMP_QUOTE__"
- key: "\'"
value: "'"
- key: "_DQUOTE_"
value: '"'
- key: "__TEMP_QUOTE__"
value: '"'
# Drop the scratchpad content from responses
- key: "(?s)<scratchpad>.*</scratchpad>"
value: ""
template:
chat: |
{{.Input -}}
<|im_start|>assistant
chat_message: |
<|im_start|>{{ .RoleName }}
{{ if .FunctionCall -}}
Function call:
{{ else if eq .RoleName "tool" -}}
Function response:
{{ end -}}
{{ if .Content -}}
<|im_start|>{{if eq .RoleName "assistant"}}assistant{{else if eq .RoleName "system"}}system{{else if eq .RoleName "tool"}}tool{{else if eq .RoleName "user"}}user{{end}}
{{- if .FunctionCall }}
<tool_call>
{{- else if eq .RoleName "tool" }}
<tool_response>
{{- end }}
{{- if .Content}}
{{.Content }}
{{ end -}}
{{ if .FunctionCall -}}
{{- end }}
{{- if .FunctionCall}}
{{toJson .FunctionCall}}
{{ end -}}<|im_end|>
{{- end }}
{{- if .FunctionCall }}
</tool_call>
{{- else if eq .RoleName "tool" }}
</tool_response>
{{- end }}<|im_end|>
completion: |
{{.Input}}
function: |
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.
Here are the available tools:
<tools>
{{range .Functions}}
{'type': 'function', 'function': {'name': '{{.Name}}', 'description': '{{.Description}}', 'parameters': {{toJson .Parameters}} }}
{{end}}
<|im_end|>
</tools>
You should call the tools provided to you sequentially
Please use <scratchpad> XML tags to record your reasoning and planning before you call the functions as follows:
<scratchpad>
{step-by-step reasoning and plan in bullet points}
</scratchpad>
For each function call return a json object with function name and arguments within <tool_call> XML tags as follows:
<tool_call>
{"arguments": <args-dict>, "name": <function-name>}
</tool_call><|im_end|>
{{.Input -}}
<|im_start|>assistant
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

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
context_size: 4096
mmap: false
f16: false
name: gpt-4o
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
View File

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

View File

@@ -1,192 +0,0 @@
ARG BASE_IMAGE=ubuntu:24.04
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=1.25.4
ARG UBUNTU_VERSION=2404
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 && \
apt-get install -y libglm-dev cmake libxcb-dri3-0 libxcb-present0 libpciaccess0 \
libpng-dev libxcb-keysyms1-dev libxcb-dri3-dev libx11-dev g++ gcc \
libwayland-dev libxrandr-dev libxcb-randr0-dev libxcb-ewmh-dev \
git python-is-python3 bison libx11-xcb-dev liblz4-dev libzstd-dev \
ocaml-core ninja-build pkg-config libxml2-dev wayland-protocols python3-jsonschema \
clang-format qtbase5-dev qt6-base-dev libxcb-glx0-dev sudo xz-utils
if [ "amd64" = "$TARGETARCH" ]; then
wget "https://sdk.lunarg.com/sdk/download/1.4.328.1/linux/vulkansdk-linux-x86_64-1.4.328.1.tar.xz" && \
tar -xf vulkansdk-linux-x86_64-1.4.328.1.tar.xz && \
rm vulkansdk-linux-x86_64-1.4.328.1.tar.xz && \
mkdir -p /opt/vulkan-sdk && \
mv 1.4.328.1 /opt/vulkan-sdk/ && \
cd /opt/vulkan-sdk/1.4.328.1 && \
./vulkansdk --no-deps --maxjobs \
vulkan-loader \
vulkan-validationlayers \
vulkan-extensionlayer \
vulkan-tools \
shaderc && \
cp -rfv /opt/vulkan-sdk/1.4.328.1/x86_64/bin/* /usr/bin/ && \
cp -rfv /opt/vulkan-sdk/1.4.328.1/x86_64/lib/* /usr/lib/x86_64-linux-gnu/ && \
cp -rfv /opt/vulkan-sdk/1.4.328.1/x86_64/include/* /usr/include/ && \
cp -rfv /opt/vulkan-sdk/1.4.328.1/x86_64/share/* /usr/share/ && \
rm -rf /opt/vulkan-sdk
fi
if [ "arm64" = "$TARGETARCH" ]; then
mkdir vulkan && cd vulkan && \
curl -L -o vulkan-sdk.tar.xz https://github.com/mudler/vulkan-sdk-arm/releases/download/1.4.335.0/vulkansdk-ubuntu-24.04-arm-1.4.335.0.tar.xz && \
tar -xvf vulkan-sdk.tar.xz && \
rm vulkan-sdk.tar.xz && \
cd 1.4.335.0 && \
cp -rfv aarch64/bin/* /usr/bin/ && \
cp -rfv aarch64/lib/* /usr/lib/aarch64-linux-gnu/ && \
cp -rfv aarch64/include/* /usr/include/ && \
cp -rfv aarch64/share/* /usr/share/ && \
cd ../.. && \
rm -rf vulkan
fi
ldconfig && \
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" = "$TARGETARCH" ]; then
curl -L -s https://github.com/protocolbuffers/protobuf/releases/download/v27.1/protoc-27.1-linux-aarch_64.zip -o protoc.zip && \
unzip -j -d /usr/local/bin protoc.zip bin/protoc && \
rm protoc.zip
fi
EOT
COPY . /LocalAI
RUN git config --global --add safe.directory /LocalAI
RUN cd /LocalAI && make protogen-go && make -C /LocalAI/backend/go/${BACKEND} build
FROM scratch
ARG BACKEND=rerankers
COPY --from=builder /LocalAI/backend/go/${BACKEND}/package/. ./

View File

@@ -1,286 +0,0 @@
ARG BASE_IMAGE=ubuntu:24.04
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 ${GRPC_BASE_IMAGE} AS grpc
# This is a bit of a hack, but it's required in order to be able to effectively cache this layer in CI
ARG GRPC_MAKEFLAGS="-j4 -Otarget"
ARG GRPC_VERSION=v1.65.0
ARG CMAKE_FROM_SOURCE=false
# CUDA Toolkit 13.x compatibility: CMake 3.31.9+ fixes toolchain detection/arch table issues
ARG CMAKE_VERSION=3.31.10
ENV MAKEFLAGS=${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 ${BASE_IMAGE} AS builder
ARG CMAKE_FROM_SOURCE=false
ARG CMAKE_VERSION=3.31.10
# We can target specific CUDA ARCHITECTURES like --build-arg CUDA_DOCKER_ARCH='75;86;89;120'
ARG CUDA_DOCKER_ARCH
ENV CUDA_DOCKER_ARCH=${CUDA_DOCKER_ARCH}
ARG CMAKE_ARGS
ENV CMAKE_ARGS=${CMAKE_ARGS}
ARG BACKEND=rerankers
ARG BUILD_TYPE
ENV BUILD_TYPE=${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=1.25.4
ARG UBUNTU_VERSION=2404
RUN apt-get update && \
apt-get install -y --no-install-recommends \
build-essential \
ccache git \
ca-certificates \
make \
pkg-config libcurl4-openssl-dev \
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 && \
apt-get install -y libglm-dev cmake libxcb-dri3-0 libxcb-present0 libpciaccess0 \
libpng-dev libxcb-keysyms1-dev libxcb-dri3-dev libx11-dev g++ gcc \
libwayland-dev libxrandr-dev libxcb-randr0-dev libxcb-ewmh-dev \
git python-is-python3 bison libx11-xcb-dev liblz4-dev libzstd-dev \
ocaml-core ninja-build pkg-config libxml2-dev wayland-protocols python3-jsonschema \
clang-format qtbase5-dev qt6-base-dev libxcb-glx0-dev sudo xz-utils
if [ "amd64" = "$TARGETARCH" ]; then
wget "https://sdk.lunarg.com/sdk/download/1.4.328.1/linux/vulkansdk-linux-x86_64-1.4.328.1.tar.xz" && \
tar -xf vulkansdk-linux-x86_64-1.4.328.1.tar.xz && \
rm vulkansdk-linux-x86_64-1.4.328.1.tar.xz && \
mkdir -p /opt/vulkan-sdk && \
mv 1.4.328.1 /opt/vulkan-sdk/ && \
cd /opt/vulkan-sdk/1.4.328.1 && \
./vulkansdk --no-deps --maxjobs \
vulkan-loader \
vulkan-validationlayers \
vulkan-extensionlayer \
vulkan-tools \
shaderc && \
cp -rfv /opt/vulkan-sdk/1.4.328.1/x86_64/bin/* /usr/bin/ && \
cp -rfv /opt/vulkan-sdk/1.4.328.1/x86_64/lib/* /usr/lib/x86_64-linux-gnu/ && \
cp -rfv /opt/vulkan-sdk/1.4.328.1/x86_64/include/* /usr/include/ && \
cp -rfv /opt/vulkan-sdk/1.4.328.1/x86_64/share/* /usr/share/ && \
rm -rf /opt/vulkan-sdk
fi
if [ "arm64" = "$TARGETARCH" ]; then
mkdir vulkan && cd vulkan && \
curl -L -o vulkan-sdk.tar.xz https://github.com/mudler/vulkan-sdk-arm/releases/download/1.4.335.0/vulkansdk-ubuntu-24.04-arm-1.4.335.0.tar.xz && \
tar -xvf vulkan-sdk.tar.xz && \
rm vulkan-sdk.tar.xz && \
cd 1.4.335.0 && \
cp -rfv aarch64/bin/* /usr/bin/ && \
cp -rfv aarch64/lib/* /usr/lib/aarch64-linux-gnu/ && \
cp -rfv aarch64/include/* /usr/include/ && \
cp -rfv aarch64/share/* /usr/share/ && \
cd ../.. && \
rm -rf vulkan
fi
ldconfig && \
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-${CMAKE_VERSION} && ./configure && make && make install
else
apt-get update && \
apt-get install -y \
cmake && \
apt-get clean && \
rm -rf /var/lib/apt/lists/*
fi
EOT
COPY --from=grpc /opt/grpc /usr/local
COPY . /LocalAI
RUN <<'EOT' bash
set -euxo pipefail
if [[ -n "${CUDA_DOCKER_ARCH:-}" ]]; then
CUDA_ARCH_ESC="${CUDA_DOCKER_ARCH//;/\\;}"
export CMAKE_ARGS="${CMAKE_ARGS:-} -DCMAKE_CUDA_ARCHITECTURES=${CUDA_ARCH_ESC}"
echo "CMAKE_ARGS(env) = ${CMAKE_ARGS}"
rm -rf /LocalAI/backend/cpp/llama-cpp-*-build
fi
if [ "${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

@@ -1,207 +0,0 @@
ARG BASE_IMAGE=ubuntu:24.04
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=2404
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" ] && [ "${SKIP_DRIVERS}" = "false" ]; then
apt-get update && \
apt-get install -y --no-install-recommends \
software-properties-common pciutils wget gpg-agent && \
apt-get install -y libglm-dev cmake libxcb-dri3-0 libxcb-present0 libpciaccess0 \
libpng-dev libxcb-keysyms1-dev libxcb-dri3-dev libx11-dev g++ gcc \
libwayland-dev libxrandr-dev libxcb-randr0-dev libxcb-ewmh-dev \
git python-is-python3 bison libx11-xcb-dev liblz4-dev libzstd-dev \
ocaml-core ninja-build pkg-config libxml2-dev wayland-protocols python3-jsonschema \
clang-format qtbase5-dev qt6-base-dev libxcb-glx0-dev sudo xz-utils
if [ "amd64" = "$TARGETARCH" ]; then
wget "https://sdk.lunarg.com/sdk/download/1.4.328.1/linux/vulkansdk-linux-x86_64-1.4.328.1.tar.xz" && \
tar -xf vulkansdk-linux-x86_64-1.4.328.1.tar.xz && \
rm vulkansdk-linux-x86_64-1.4.328.1.tar.xz && \
mkdir -p /opt/vulkan-sdk && \
mv 1.4.328.1 /opt/vulkan-sdk/ && \
cd /opt/vulkan-sdk/1.4.328.1 && \
./vulkansdk --no-deps --maxjobs \
vulkan-loader \
vulkan-validationlayers \
vulkan-extensionlayer \
vulkan-tools \
shaderc && \
cp -rfv /opt/vulkan-sdk/1.4.328.1/x86_64/bin/* /usr/bin/ && \
cp -rfv /opt/vulkan-sdk/1.4.328.1/x86_64/lib/* /usr/lib/x86_64-linux-gnu/ && \
cp -rfv /opt/vulkan-sdk/1.4.328.1/x86_64/include/* /usr/include/ && \
cp -rfv /opt/vulkan-sdk/1.4.328.1/x86_64/share/* /usr/share/ && \
rm -rf /opt/vulkan-sdk
fi
if [ "arm64" = "$TARGETARCH" ]; then
mkdir vulkan && cd vulkan && \
curl -L -o vulkan-sdk.tar.xz https://github.com/mudler/vulkan-sdk-arm/releases/download/1.4.335.0/vulkansdk-ubuntu-24.04-arm-1.4.335.0.tar.xz && \
tar -xvf vulkan-sdk.tar.xz && \
rm vulkan-sdk.tar.xz && \
cd 1.4.335.0 && \
cp -rfv aarch64/bin/* /usr/bin/ && \
cp -rfv aarch64/lib/* /usr/lib/aarch64-linux-gnu/ && \
cp -rfv aarch64/include/* /usr/include/ && \
cp -rfv aarch64/share/* /usr/share/ && \
cd ../.. && \
rm -rf vulkan
fi
ldconfig && \
apt-get clean && \
rm -rf /var/lib/apt/lists/*
fi
EOT
# CuBLAS requirements
RUN <<EOT bash
if ( [ "${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}"
# Increase timeout for uv installs behind slow networks
ENV UV_HTTP_TIMEOUT=180
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 [ "${UBUNTU_VERSION}" = "2404" ]; then
pip install --break-system-packages --user grpcio-tools==1.71.0 grpcio==1.71.0
else
pip install grpcio-tools==1.71.0 grpcio==1.71.0
fi
EOT
COPY backend/python/${BACKEND} /${BACKEND}
COPY backend/backend.proto /${BACKEND}/backend.proto
COPY backend/python/common/ /${BACKEND}/common
COPY scripts/build/package-gpu-libs.sh /package-gpu-libs.sh
RUN cd /${BACKEND} && PORTABLE_PYTHON=true make
# Package GPU libraries into the backend's lib directory
RUN mkdir -p /${BACKEND}/lib && \
TARGET_LIB_DIR="/${BACKEND}/lib" BUILD_TYPE="${BUILD_TYPE}" CUDA_MAJOR_VERSION="${CUDA_MAJOR_VERSION}" \
bash /package-gpu-libs.sh "/${BACKEND}/lib"
FROM scratch
ARG BACKEND=rerankers
COPY --from=builder /${BACKEND}/ /

View File

@@ -1,212 +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 12.x, 13.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
- **`cublas12`**, **`cublas13`**: CUDA 12.x, 13.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

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