Compare commits

..

2 Commits

Author SHA1 Message Date
Ettore Di Giacinto
c28e8ca697 Merge branch 'master' into ci/static-check 2024-07-18 19:44:59 +02:00
Ettore Di Giacinto
ecaaff8f03 ci: add static-checker
**Description**

This PR adds a static-checker pipeline as part of our workflows

**Notes for Reviewers**
N/A

**[Signed commits](../CONTRIBUTING.md#signing-off-on-commits-developer-certificate-of-origin)**
- [x] Yes, I signed my commits.

Signed-off-by: Ettore Di Giacinto <mudler@users.noreply.github.com>
2024-07-12 10:28:44 +02:00
1280 changed files with 64056 additions and 373235 deletions

View File

@@ -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

View File

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

View File

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

View File

@@ -1,55 +0,0 @@
#!/bin/bash
# This file contains some really simple functions that are useful when building up customization scripts.
# Checks if the git config has a user registered - and sets it up if not.
#
# Param 1: name
# Param 2: email
#
config_user() {
echo "Configuring git for $1 <$2>"
local gcn=$(git config --global user.name)
if [ -z "${gcn}" ]; then
echo "Setting up git user / remote"
git config --global user.name "$1"
git config --global user.email "$2"
fi
}
# Checks if the git remote is configured - and sets it up if not. Fetches either way.
#
# Param 1: remote name
# Param 2: remote url
#
config_remote() {
echo "Adding git remote and fetching $2 as $1"
local gr=$(git remote -v | grep $1)
if [ -z "${gr}" ]; then
git remote add $1 $2
fi
git fetch $1
}
# Setup special .ssh files
# Prints out lines of text to make things pretty
# Param 1: bash array, filenames relative to the customization directory that should be copied to ~/.ssh
setup_ssh() {
echo "starting ~/.ssh directory setup..."
mkdir -p "${HOME}.ssh"
chmod 0700 "${HOME}/.ssh"
echo "-----"
local files=("$@")
for file in "${files[@]}" ; do
local cfile="/devcontainer-customization/${file}"
local hfile="${HOME}/.ssh/${file}"
if [ ! -f "${hfile}" ]; then
echo "copying \"${file}\""
cp "${cfile}" "${hfile}"
chmod 600 "${hfile}"
fi
done
echo "~/.ssh directory setup complete!"
}

View File

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

View File

@@ -1,24 +0,0 @@
{
"$schema": "https://raw.githubusercontent.com/devcontainers/spec/main/schemas/devContainer.schema.json",
"name": "LocalAI",
"workspaceFolder": "/workspace",
"dockerComposeFile": [ "./docker-compose-devcontainer.yml" ],
"service": "api",
"shutdownAction": "stopCompose",
"customizations": {
"vscode": {
"extensions": [
"golang.go",
"ms-vscode.makefile-tools",
"ms-azuretools.vscode-docker",
"ms-python.python",
"ms-python.debugpy",
"wayou.vscode-todo-highlight",
"waderyan.gitblame"
]
}
},
"forwardPorts": [8080, 3000],
"postCreateCommand": "bash /.devcontainer-scripts/postcreate.sh",
"postStartCommand": "bash /.devcontainer-scripts/poststart.sh"
}

View File

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

View File

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

View File

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

View File

@@ -1,15 +1,8 @@
.idea
.github
.vscode
.devcontainer
models
backends
examples/chatbot-ui/models
backend/go/image/stablediffusion-ggml/build/
backend/go/*/build
backend/go/*/.cache
backend/go/*/sources
backend/go/*/package
examples/rwkv/models
examples/**/models
Dockerfile*
@@ -20,4 +13,4 @@ __pycache__
# backend virtual environments
**/venv
backend/python/**/source
backend/python/**/source

31
.env
View File

@@ -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: stablediffusion, tts
## stablediffusion: image generation with stablediffusion
## tts: enables text-to-speech with go-piper
## (requires REBUILD=true)
#
# GO_TAGS=stablediffusion
## Path where to store generated images
# LOCALAI_IMAGE_PATH=/tmp/generated/images
@@ -60,24 +73,12 @@
### 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
# LOCALAI_PARALLEL_REQUESTS=true
# Enable to allow p2p mode
# LOCALAI_P2P=true
# Enable to use federated mode
# LOCALAI_FEDERATED=true
# Enable to start federation server
# FEDERATED_SERVER=true
# Define to use federation token
# TOKEN=""
### Watchdog settings
###
# Enables watchdog to kill backends that are inactive for too much time

1
.gitattributes vendored
View File

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

20
.github/bump_deps.sh vendored
View File

@@ -3,25 +3,7 @@ set -xe
REPO=$1
BRANCH=$2
VAR=$3
FILE=$4
if [ -z "$FILE" ]; then
FILE="Makefile"
fi
LAST_COMMIT=$(curl -s -H "Accept: application/vnd.github.VERSION.sha" "https://api.github.com/repos/$REPO/commits/$BRANCH")
# Read $VAR from Makefile (only first match)
set +e
CURRENT_COMMIT="$(grep -m1 "^$VAR?=" $FILE | cut -d'=' -f2)"
set -e
sed -i $FILE -e "s/$VAR?=.*/$VAR?=$LAST_COMMIT/"
if [ -z "$CURRENT_COMMIT" ]; then
echo "Could not find $VAR in Makefile."
exit 0
fi
echo "Changes: https://github.com/$REPO/compare/${CURRENT_COMMIT}..${LAST_COMMIT}" >> "${VAR}_message.txt"
echo "${LAST_COMMIT}" >> "${VAR}_commit.txt"
sed -i Makefile -e "s/$VAR?=.*/$VAR?=$LAST_COMMIT/"

View File

@@ -29,14 +29,9 @@ def calculate_sha256(file_path):
def manual_safety_check_hf(repo_id):
scanResponse = requests.get('https://huggingface.co/api/models/' + repo_id + "/scan")
scan = scanResponse.json()
# Check if 'hasUnsafeFile' exists in the response
if 'hasUnsafeFile' in scan:
if scan['hasUnsafeFile']:
return scan
else:
return None
else:
return None
if scan['hasUnsafeFile']:
return scan
return None
download_type, repo_id_or_url = parse_uri(uri)

View File

@@ -6,7 +6,6 @@ import (
"io/ioutil"
"os"
"github.com/microcosm-cc/bluemonday"
"gopkg.in/yaml.v3"
)
@@ -280,12 +279,6 @@ func main() {
return
}
// Ensure that all arbitrary text content is sanitized before display
for i, m := range models {
models[i].Name = bluemonday.StrictPolicy().Sanitize(m.Name)
models[i].Description = bluemonday.StrictPolicy().Sanitize(m.Description)
}
// render the template
data := struct {
Models []*GalleryModel

View File

@@ -9,8 +9,6 @@ updates:
directory: "/"
schedule:
interval: "weekly"
ignore:
- dependency-name: "github.com/mudler/LocalAI/pkg/grpc/proto"
- package-ecosystem: "github-actions"
# Workflow files stored in the default location of `.github/workflows`. (You don't need to specify `/.github/workflows` for `directory`. You can use `directory: "/"`.)
directory: "/"
@@ -29,6 +27,10 @@ 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 +63,14 @@ 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/petals"
schedule:
interval: "weekly"
- package-ecosystem: "pip"
directory: "/backend/python/rerankers"
schedule:
@@ -73,6 +83,14 @@ updates:
directory: "/backend/python/transformers"
schedule:
interval: "weekly"
- package-ecosystem: "pip"
directory: "/backend/python/transformers-musicgen"
schedule:
interval: "weekly"
- package-ecosystem: "pip"
directory: "/backend/python/vall-e-x"
schedule:
interval: "weekly"
- package-ecosystem: "pip"
directory: "/backend/python/vllm"
schedule:

View File

@@ -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"},
},
},
}
}

11
.github/labeler.yml vendored
View File

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

View File

File diff suppressed because it is too large Load Diff

View File

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

View File

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

View File

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

View File

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

View File

@@ -1,62 +1,56 @@
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: "go-skynet/go-ggml-transformers.cpp"
variable: "GOGGMLTRANSFORMERS_VERSION"
branch: "master"
- repository: "donomii/go-rwkv.cpp"
variable: "RWKV_VERSION"
branch: "main"
- repository: "ggerganov/whisper.cpp"
variable: "WHISPER_CPP_VERSION"
branch: "master"
file: "backend/go/whisper/Makefile"
- repository: "PABannier/bark.cpp"
variable: "BARKCPP_VERSION"
branch: "main"
file: "Makefile"
- repository: "leejet/stable-diffusion.cpp"
variable: "STABLEDIFFUSION_GGML_VERSION"
- repository: "go-skynet/go-bert.cpp"
variable: "BERT_VERSION"
branch: "master"
- repository: "go-skynet/bloomz.cpp"
variable: "BLOOMZ_VERSION"
branch: "main"
- repository: "mudler/go-ggllm.cpp"
variable: "GOGGLLM_VERSION"
branch: "master"
- repository: "mudler/go-stable-diffusion"
variable: "STABLEDIFFUSION_VERSION"
branch: "master"
file: "backend/go/stablediffusion-ggml/Makefile"
- repository: "mudler/go-piper"
variable: "PIPER_VERSION"
branch: "master"
file: "backend/go/piper/Makefile"
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v6
- uses: actions/checkout@v4
- name: Bump dependencies 🔧
id: bump
run: |
bash .github/bump_deps.sh ${{ matrix.repository }} ${{ matrix.branch }} ${{ matrix.variable }} ${{ matrix.file }}
{
echo 'message<<EOF'
cat "${{ matrix.variable }}_message.txt"
echo EOF
} >> "$GITHUB_OUTPUT"
{
echo 'commit<<EOF'
cat "${{ matrix.variable }}_commit.txt"
echo EOF
} >> "$GITHUB_OUTPUT"
rm -rfv ${{ matrix.variable }}_message.txt
rm -rfv ${{ matrix.variable }}_commit.txt
bash .github/bump_deps.sh ${{ matrix.repository }} ${{ matrix.branch }} ${{ matrix.variable }}
- name: Create Pull Request
uses: peter-evans/create-pull-request@v8
uses: peter-evans/create-pull-request@v6
with:
token: ${{ secrets.UPDATE_BOT_TOKEN }}
push-to-fork: ci-forks/LocalAI
commit-message: ':arrow_up: Update ${{ matrix.repository }}'
title: 'chore: :arrow_up: Update ${{ matrix.repository }} to `${{ steps.bump.outputs.commit }}`'
title: 'chore: :arrow_up: Update ${{ matrix.repository }}'
branch: "update/${{ matrix.variable }}"
body: ${{ steps.bump.outputs.message }}
body: Bump of ${{ matrix.repository }} version
signoff: true

View File

@@ -1,10 +1,10 @@
name: Bump Documentation
name: Bump dependencies
on:
schedule:
- cron: 0 20 * * *
workflow_dispatch:
jobs:
bump-docs:
bump:
strategy:
fail-fast: false
matrix:
@@ -12,12 +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@v6
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: |
@@ -15,14 +15,15 @@ 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
uses: dcarbone/install-yq-action@v1.1.1
with:
version: 'v4.44.2'
download-compressed: true
@@ -35,12 +36,12 @@ jobs:
sudo chmod 777 /hf_cache
bash .github/checksum_checker.sh gallery/index.yaml
- name: Create Pull Request
uses: peter-evans/create-pull-request@v8
uses: peter-evans/create-pull-request@v6
with:
token: ${{ secrets.UPDATE_BOT_TOKEN }}
push-to-fork: ci-forks/LocalAI
commit-message: ':arrow_up: Checksum updates in gallery/index.yaml'
title: 'chore(model-gallery): :arrow_up: update checksum'
title: 'models(gallery): :arrow_up: update checksum'
branch: "update/checksum"
body: Updating checksums in gallery/index.yaml
signoff: true

View File

@@ -12,7 +12,6 @@ jobs:
uses: actions/checkout@v3
with:
ref: "${{ github.event.pull_request.merge_commit_sha }}"
fetch-depth: 0 # needed to checkout all branches for this Action to work
- uses: mudler/localai-github-action@v1
with:
model: 'hermes-2-theta-llama-3-8b' # Any from models.localai.io, or from huggingface.com with: "huggingface://<repository>/file"
@@ -23,7 +22,6 @@ jobs:
json_diff_file_output: diff.json
raw_diff_file_output: diff.txt
file_output_only: "true"
base_branch: ${{ github.event.pull_request.base.sha }}
- name: Show diff
env:
DIFF: ${{ steps.git-diff-action.outputs.raw-diff-path }}

View File

@@ -14,13 +14,13 @@ jobs:
steps:
- name: Dependabot metadata
id: metadata
uses: dependabot/fetch-metadata@v2.5.0
uses: dependabot/fetch-metadata@v2.2.0
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

@@ -1,64 +0,0 @@
name: Explorer deployment
on:
push:
branches:
- master
tags:
- 'v*'
concurrency:
group: ci-deploy-${{ github.head_ref || github.ref }}-${{ github.repository }}
jobs:
build-linux:
runs-on: ubuntu-latest
steps:
- name: Clone
uses: actions/checkout@v6
with:
submodules: true
- uses: actions/setup-go@v5
with:
go-version: '1.21.x'
cache: false
- name: Dependencies
run: |
sudo apt-get update
sudo apt-get install -y wget curl build-essential ffmpeg protobuf-compiler ccache upx-ucl gawk cmake libgmock-dev
go install google.golang.org/grpc/cmd/protoc-gen-go-grpc@1958fcbe2ca8bd93af633f11e97d44e567e945af
go install google.golang.org/protobuf/cmd/protoc-gen-go@v1.34.2
make protogen-go
- name: Build api
run: |
CGO_ENABLED=0 make build
- name: rm
uses: appleboy/ssh-action@v1.2.4
with:
host: ${{ secrets.EXPLORER_SSH_HOST }}
username: ${{ secrets.EXPLORER_SSH_USERNAME }}
key: ${{ secrets.EXPLORER_SSH_KEY }}
port: ${{ secrets.EXPLORER_SSH_PORT }}
script: |
sudo rm -rf local-ai/ || true
- name: copy file via ssh
uses: appleboy/scp-action@v1.0.0
with:
host: ${{ secrets.EXPLORER_SSH_HOST }}
username: ${{ secrets.EXPLORER_SSH_USERNAME }}
key: ${{ secrets.EXPLORER_SSH_KEY }}
port: ${{ secrets.EXPLORER_SSH_PORT }}
source: "local-ai"
overwrite: true
rm: true
target: ./local-ai
- name: restarting
uses: appleboy/ssh-action@v1.2.4
with:
host: ${{ secrets.EXPLORER_SSH_HOST }}
username: ${{ secrets.EXPLORER_SSH_USERNAME }}
key: ${{ secrets.EXPLORER_SSH_KEY }}
port: ${{ secrets.EXPLORER_SSH_PORT }}
script: |
sudo cp -rfv local-ai/local-ai /usr/bin/local-ai
sudo systemctl restart local-ai

View File

@@ -1,132 +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:2024.2.0-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: ${{ github.event_name != 'pull_request' && 4 || 8 }}
fail-fast: false
matrix:
include:
- build-type: 'cublas'
cuda-major-version: "12"
cuda-minor-version: "8"
platforms: 'linux/amd64'
tag-latest: 'false'
tag-suffix: '-gpu-nvidia-cuda-12'
runs-on: 'ubuntu-latest'
base-image: "ubuntu:24.04"
makeflags: "--jobs=3 --output-sync=target"
ubuntu-version: '2404'
- build-type: 'cublas'
cuda-major-version: "13"
cuda-minor-version: "0"
platforms: 'linux/amd64'
tag-latest: 'false'
tag-suffix: '-gpu-nvidia-cuda-13'
runs-on: 'ubuntu-latest'
base-image: "ubuntu:22.04"
makeflags: "--jobs=3 --output-sync=target"
ubuntu-version: '2404'
- build-type: 'hipblas'
platforms: 'linux/amd64'
tag-latest: 'false'
tag-suffix: '-hipblas'
base-image: "rocm/dev-ubuntu-24.04:6.4.4"
grpc-base-image: "ubuntu:24.04"
runs-on: 'ubuntu-latest'
makeflags: "--jobs=3 --output-sync=target"
ubuntu-version: '2404'
- build-type: 'sycl'
platforms: 'linux/amd64'
tag-latest: 'false'
base-image: "intel/oneapi-basekit:2025.3.0-0-devel-ubuntu24.04"
grpc-base-image: "ubuntu:24.04"
tag-suffix: 'sycl'
runs-on: 'ubuntu-latest'
makeflags: "--jobs=3 --output-sync=target"
ubuntu-version: '2404'
- build-type: 'vulkan'
platforms: 'linux/amd64,linux/arm64'
tag-latest: 'false'
tag-suffix: '-vulkan-core'
runs-on: 'ubuntu-latest'
base-image: "ubuntu:24.04"
makeflags: "--jobs=4 --output-sync=target"
ubuntu-version: '2404'
- build-type: 'cublas'
cuda-major-version: "13"
cuda-minor-version: "0"
platforms: 'linux/arm64'
tag-latest: 'false'
tag-suffix: '-nvidia-l4t-arm64-cuda-13'
base-image: "ubuntu:24.04"
runs-on: 'ubuntu-24.04-arm'
makeflags: "--jobs=4 --output-sync=target"
skip-drivers: 'false'
ubuntu-version: '2404'
name: 'build container images tests'
on:
pull_request:
concurrency:
group: ci-${{ 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: "4"
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: "4"
# 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 +1,328 @@
---
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: "8"
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:
self-hosted-jobs:
uses: ./.github/workflows/image_build.yml
with:
tag-latest: ${{ matrix.tag-latest }}
tag-suffix: ${{ matrix.tag-suffix }}
ffmpeg: ${{ matrix.ffmpeg }}
image-type: ${{ matrix.image-type }}
build-type: ${{ matrix.build-type }}
cuda-major-version: ${{ matrix.cuda-major-version }}
cuda-minor-version: ${{ matrix.cuda-minor-version }}
platforms: ${{ matrix.platforms }}
runs-on: ${{ matrix.runs-on }}
base-image: ${{ matrix.base-image }}
grpc-base-image: ${{ matrix.grpc-base-image }}
aio: ${{ matrix.aio }}
makeflags: ${{ matrix.makeflags }}
latest-image: ${{ matrix.latest-image }}
latest-image-aio: ${{ matrix.latest-image-aio }}
secrets:
dockerUsername: ${{ secrets.DOCKERHUB_USERNAME }}
dockerPassword: ${{ secrets.DOCKERHUB_PASSWORD }}
quayUsername: ${{ secrets.LOCALAI_REGISTRY_USERNAME }}
quayPassword: ${{ secrets.LOCALAI_REGISTRY_PASSWORD }}
strategy:
# Pushing with all jobs in parallel
# eats the bandwidth of all the nodes
max-parallel: ${{ github.event_name != 'pull_request' && 6 || 10 }}
matrix:
include:
# Extra images
- build-type: ''
#platforms: 'linux/amd64,linux/arm64'
platforms: 'linux/amd64'
tag-latest: 'auto'
tag-suffix: ''
ffmpeg: ''
image-type: 'extras'
runs-on: 'arc-runner-set'
base-image: "ubuntu:22.04"
makeflags: "--jobs=3 --output-sync=target"
- build-type: ''
platforms: 'linux/amd64'
tag-latest: 'auto'
tag-suffix: '-ffmpeg'
ffmpeg: 'true'
image-type: 'extras'
runs-on: 'arc-runner-set'
base-image: "ubuntu:22.04"
makeflags: "--jobs=3 --output-sync=target"
- build-type: 'cublas'
cuda-major-version: "11"
cuda-minor-version: "7"
platforms: 'linux/amd64'
tag-latest: 'false'
tag-suffix: '-cublas-cuda11'
ffmpeg: ''
image-type: 'extras'
runs-on: 'arc-runner-set'
base-image: "ubuntu:22.04"
makeflags: "--jobs=3 --output-sync=target"
- build-type: 'cublas'
cuda-major-version: "12"
cuda-minor-version: "4"
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: "4"
platforms: 'linux/amd64'
tag-latest: 'auto'
tag-suffix: '-cublas-cuda12-ffmpeg'
ffmpeg: 'true'
image-type: 'extras'
runs-on: 'arc-runner-set'
base-image: "ubuntu:22.04"
aio: "-aio-gpu-nvidia-cuda-12"
latest-image: 'latest-gpu-nvidia-cuda-12'
latest-image-aio: 'latest-aio-gpu-nvidia-cuda-12'
makeflags: "--jobs=3 --output-sync=target"
- build-type: ''
#platforms: 'linux/amd64,linux/arm64'
platforms: 'linux/amd64'
tag-latest: 'auto'
tag-suffix: ''
ffmpeg: ''
image-type: 'extras'
base-image: "ubuntu:22.04"
runs-on: 'arc-runner-set'
makeflags: "--jobs=3 --output-sync=target"
- build-type: 'hipblas'
platforms: 'linux/amd64'
tag-latest: 'auto'
tag-suffix: '-hipblas-ffmpeg'
ffmpeg: 'true'
image-type: 'extras'
aio: "-aio-gpu-hipblas"
base-image: "rocm/dev-ubuntu-22.04:6.1"
grpc-base-image: "ubuntu:22.04"
latest-image: 'latest-gpu-hipblas'
latest-image-aio: 'latest-aio-gpu-hipblas'
runs-on: 'arc-runner-set'
makeflags: "--jobs=3 --output-sync=target"
- build-type: 'hipblas'
platforms: 'linux/amd64'
tag-latest: 'false'
tag-suffix: '-hipblas'
ffmpeg: 'false'
image-type: 'extras'
base-image: "rocm/dev-ubuntu-22.04:6.1"
grpc-base-image: "ubuntu:22.04"
runs-on: 'arc-runner-set'
makeflags: "--jobs=3 --output-sync=target"
- build-type: 'sycl_f16'
platforms: 'linux/amd64'
tag-latest: 'auto'
base-image: "quay.io/go-skynet/intel-oneapi-base:latest"
grpc-base-image: "ubuntu:22.04"
tag-suffix: '-sycl-f16-ffmpeg'
ffmpeg: 'true'
image-type: 'extras'
runs-on: 'arc-runner-set'
aio: "-aio-gpu-intel-f16"
latest-image: 'latest-gpu-intel-f16'
latest-image-aio: 'latest-aio-gpu-intel-f16'
makeflags: "--jobs=3 --output-sync=target"
- build-type: 'sycl_f32'
platforms: 'linux/amd64'
tag-latest: 'auto'
base-image: "quay.io/go-skynet/intel-oneapi-base:latest"
grpc-base-image: "ubuntu:22.04"
tag-suffix: '-sycl-f32-ffmpeg'
ffmpeg: 'true'
image-type: 'extras'
runs-on: 'arc-runner-set'
aio: "-aio-gpu-intel-f32"
latest-image: 'latest-gpu-intel-f32'
latest-image-aio: 'latest-aio-gpu-intel-f32'
makeflags: "--jobs=3 --output-sync=target"
# Core images
- build-type: 'sycl_f16'
platforms: 'linux/amd64'
tag-latest: 'false'
base-image: "quay.io/go-skynet/intel-oneapi-base:latest"
grpc-base-image: "ubuntu:22.04"
tag-suffix: '-sycl-f16-core'
ffmpeg: 'false'
image-type: 'core'
runs-on: 'arc-runner-set'
makeflags: "--jobs=3 --output-sync=target"
- build-type: 'sycl_f32'
platforms: 'linux/amd64'
tag-latest: 'false'
base-image: "quay.io/go-skynet/intel-oneapi-base:latest"
grpc-base-image: "ubuntu:22.04"
tag-suffix: '-sycl-f32-core'
ffmpeg: 'false'
image-type: 'core'
runs-on: 'arc-runner-set'
makeflags: "--jobs=3 --output-sync=target"
- build-type: 'sycl_f16'
platforms: 'linux/amd64'
tag-latest: 'false'
base-image: "quay.io/go-skynet/intel-oneapi-base:latest"
grpc-base-image: "ubuntu:22.04"
tag-suffix: '-sycl-f16-ffmpeg-core'
ffmpeg: 'true'
image-type: 'core'
runs-on: 'arc-runner-set'
makeflags: "--jobs=3 --output-sync=target"
- build-type: 'sycl_f32'
platforms: 'linux/amd64'
tag-latest: 'false'
base-image: "quay.io/go-skynet/intel-oneapi-base:latest"
grpc-base-image: "ubuntu:22.04"
tag-suffix: '-sycl-f32-ffmpeg-core'
ffmpeg: 'true'
image-type: 'core'
runs-on: 'arc-runner-set'
makeflags: "--jobs=3 --output-sync=target"
- build-type: 'hipblas'
platforms: 'linux/amd64'
tag-latest: 'false'
tag-suffix: '-hipblas-ffmpeg-core'
ffmpeg: 'true'
image-type: 'core'
base-image: "rocm/dev-ubuntu-22.04:6.1"
grpc-base-image: "ubuntu:22.04"
runs-on: 'arc-runner-set'
makeflags: "--jobs=3 --output-sync=target"
- build-type: 'hipblas'
platforms: 'linux/amd64'
tag-latest: 'false'
tag-suffix: '-hipblas-core'
ffmpeg: 'false'
image-type: 'core'
base-image: "rocm/dev-ubuntu-22.04:6.1"
grpc-base-image: "ubuntu:22.04"
runs-on: 'arc-runner-set'
makeflags: "--jobs=3 --output-sync=target"
core-image-build:
uses: ./.github/workflows/image_build.yml
with:
tag-latest: ${{ matrix.tag-latest }}
tag-suffix: ${{ matrix.tag-suffix }}
ffmpeg: ${{ matrix.ffmpeg }}
image-type: ${{ matrix.image-type }}
build-type: ${{ matrix.build-type }}
cuda-major-version: ${{ matrix.cuda-major-version }}
cuda-minor-version: ${{ matrix.cuda-minor-version }}
platforms: ${{ matrix.platforms }}
runs-on: ${{ matrix.runs-on }}
aio: ${{ matrix.aio }}
base-image: ${{ matrix.base-image }}
grpc-base-image: ${{ matrix.grpc-base-image }}
makeflags: ${{ matrix.makeflags }}
latest-image: ${{ matrix.latest-image }}
latest-image-aio: ${{ matrix.latest-image-aio }}
secrets:
dockerUsername: ${{ secrets.DOCKERHUB_USERNAME }}
dockerPassword: ${{ secrets.DOCKERHUB_PASSWORD }}
quayUsername: ${{ secrets.LOCALAI_REGISTRY_USERNAME }}
quayPassword: ${{ secrets.LOCALAI_REGISTRY_PASSWORD }}
strategy:
max-parallel: ${{ github.event_name != 'pull_request' && 2 || 4 }}
matrix:
include:
- build-type: ''
platforms: 'linux/amd64,linux/arm64'
tag-latest: 'auto'
tag-suffix: '-ffmpeg-core'
ffmpeg: 'true'
image-type: 'core'
base-image: "ubuntu:22.04"
runs-on: 'arc-runner-set'
aio: "-aio-cpu"
latest-image: 'latest-cpu'
latest-image-aio: 'latest-aio-cpu'
makeflags: "--jobs=4 --output-sync=target"
- build-type: 'cublas'
cuda-major-version: "11"
cuda-minor-version: "7"
platforms: 'linux/amd64'
tag-latest: 'false'
tag-suffix: '-cublas-cuda11-core'
ffmpeg: ''
image-type: 'core'
base-image: "ubuntu:22.04"
runs-on: 'arc-runner-set'
makeflags: "--jobs=4 --output-sync=target"
- build-type: 'cublas'
cuda-major-version: "12"
cuda-minor-version: "4"
platforms: 'linux/amd64'
tag-latest: 'false'
tag-suffix: '-cublas-cuda12-core'
ffmpeg: ''
image-type: 'core'
base-image: "ubuntu:22.04"
runs-on: 'arc-runner-set'
makeflags: "--jobs=4 --output-sync=target"
- build-type: 'cublas'
cuda-major-version: "11"
cuda-minor-version: "7"
platforms: 'linux/amd64'
tag-latest: 'false'
tag-suffix: '-cublas-cuda11-ffmpeg-core'
ffmpeg: 'true'
image-type: 'core'
runs-on: 'arc-runner-set'
base-image: "ubuntu:22.04"
makeflags: "--jobs=4 --output-sync=target"
- build-type: 'cublas'
cuda-major-version: "12"
cuda-minor-version: "4"
platforms: 'linux/amd64'
tag-latest: 'false'
tag-suffix: '-cublas-cuda12-ffmpeg-core'
ffmpeg: 'true'
image-type: 'core'
runs-on: 'arc-runner-set'
base-image: "ubuntu:22.04"
makeflags: "--jobs=4 --output-sync=target"
- build-type: 'vulkan'
platforms: 'linux/amd64'
tag-latest: 'false'
tag-suffix: '-vulkan-ffmpeg-core'
latest-image: 'latest-vulkan-ffmpeg-core'
ffmpeg: 'true'
image-type: 'core'
runs-on: 'arc-runner-set'
base-image: "ubuntu:22.04"
makeflags: "--jobs=4 --output-sync=target"

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'
@@ -33,13 +33,25 @@ on:
description: 'Tag latest'
default: ''
type: string
latest-image:
description: 'Tag latest'
default: ''
type: string
latest-image-aio:
description: 'Tag latest'
default: ''
type: string
tag-suffix:
description: 'Tag suffix'
default: ''
type: string
skip-drivers:
description: 'Skip drivers by default'
default: 'false'
ffmpeg:
description: 'FFMPEG'
default: ''
type: string
image-type:
description: 'Image type'
default: ''
type: string
runs-on:
description: 'Runs on'
@@ -56,16 +68,6 @@ 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 +81,6 @@ jobs:
reusable_image-build:
runs-on: ${{ inputs.runs-on }}
steps:
- name: Free Disk Space (Ubuntu)
if: inputs.runs-on == 'ubuntu-latest'
uses: jlumbroso/free-disk-space@main
with:
# this might remove tools that are actually needed,
# if set to "true" but frees about 6 GB
tool-cache: true
# all of these default to true, but feel free to set to
# "false" if necessary for your workflow
android: true
dotnet: true
haskell: true
large-packages: true
docker-images: true
swap-storage: true
- name: Force Install GIT latest
run: |
sudo apt-get update \
@@ -104,7 +90,7 @@ jobs:
&& sudo apt-get update \
&& sudo apt-get install -y git
- name: Checkout
uses: actions/checkout@v6
uses: actions/checkout@v4
- name: Release space from worker
if: inputs.runs-on == 'ubuntu-latest'
@@ -116,8 +102,8 @@ jobs:
df -h
echo
sudo apt-get remove -y '^llvm-.*|^libllvm.*' || true
sudo apt-get remove --auto-remove android-sdk-platform-tools snapd || true
sudo apt-get purge --auto-remove android-sdk-platform-tools snapd || true
sudo apt-get remove --auto-remove android-sdk-platform-tools || true
sudo apt-get purge --auto-remove android-sdk-platform-tools || true
sudo rm -rf /usr/local/lib/android
sudo apt-get remove -y '^dotnet-.*|^aspnetcore-.*' || true
sudo rm -rf /usr/share/dotnet
@@ -162,18 +148,18 @@ jobs:
type=sha
flavor: |
latest=${{ 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=${{ inputs.tag-suffix }}
@@ -189,7 +175,7 @@ jobs:
type=semver,pattern={{raw}}
flavor: |
latest=${{ inputs.tag-latest }}
suffix=${{ inputs.aio }},onlatest=true
suffix=${{ inputs.aio }}
- name: Docker meta AIO (dockerhub)
if: inputs.aio != ''
@@ -202,8 +188,7 @@ jobs:
type=ref,event=branch
type=semver,pattern={{raw}}
flavor: |
latest=${{ inputs.tag-latest }}
suffix=${{ inputs.aio }},onlatest=true
suffix=${{ inputs.aio }}
- name: Set up QEMU
uses: docker/setup-qemu-action@master
@@ -242,14 +227,13 @@ jobs:
BUILD_TYPE=${{ 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 +255,24 @@ 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 +304,27 @@ 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@v2.7.0
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@v3.18
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@v2.7.0
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@v3.18
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 +1,356 @@
name: goreleaser
name: Build and Release
on:
push:
tags:
- 'v*'
branches:
- master
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: ${{ secrets.GITHUB_TOKEN }}
launcher-build-darwin:
runs-on: macos-latest
steps:
- name: Checkout
uses: actions/checkout@v6
with:
fetch-depth: 0
- name: Set up Go
uses: actions/setup-go@v5
with:
go-version: 1.23
- name: Build launcher for macOS ARM64
run: |
make build-launcher-darwin
- name: Upload DMG to Release
uses: softprops/action-gh-release@v2
with:
files: ./dist/LocalAI.dmg
launcher-build-linux:
runs-on: ubuntu-latest
steps:
- name: Checkout
uses: actions/checkout@v6
with:
fetch-depth: 0
- name: Set up Go
uses: actions/setup-go@v5
with:
go-version: 1.23
- name: Build launcher for Linux
go-version: '1.21.x'
cache: false
- name: Dependencies
run: |
sudo apt-get update
sudo apt-get install golang gcc libgl1-mesa-dev xorg-dev libxkbcommon-dev
make build-launcher-linux
- name: Upload Linux launcher artifacts
uses: softprops/action-gh-release@v2
sudo apt-get install build-essential ffmpeg protobuf-compiler ccache gawk
sudo apt-get install -qy binutils-aarch64-linux-gnu gcc-aarch64-linux-gnu g++-aarch64-linux-gnu libgmock-dev
- name: Install CUDA Dependencies
run: |
curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/cross-linux-aarch64/cuda-keyring_1.1-1_all.deb
sudo dpkg -i cuda-keyring_1.1-1_all.deb
sudo apt-get update
sudo apt-get install -y cuda-cross-aarch64 cuda-nvcc-cross-aarch64-${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: ${{ failure() }}
uses: mxschmitt/action-tmate@v3.18
with:
detached: true
connect-timeout-seconds: 180
limit-access-to-actor: true
build-linux:
runs-on: arc-runner-set
steps:
- name: Force Install GIT latest
run: |
sudo apt-get update \
&& sudo apt-get install -y software-properties-common \
&& sudo apt-get update \
&& sudo add-apt-repository -y ppa:git-core/ppa \
&& sudo apt-get update \
&& sudo apt-get install -y git
- name: Clone
uses: actions/checkout@v4
with:
submodules: true
- uses: actions/setup-go@v5
with:
go-version: '1.21.x'
cache: false
- name: Dependencies
run: |
sudo apt-get update
sudo apt-get install -y wget curl build-essential ffmpeg protobuf-compiler ccache gawk cmake libgmock-dev
- name: Intel Dependencies
run: |
wget -O- https://apt.repos.intel.com/intel-gpg-keys/GPG-PUB-KEY-INTEL-SW-PRODUCTS.PUB | gpg --dearmor | sudo tee /usr/share/keyrings/oneapi-archive-keyring.gpg > /dev/null
echo "deb [signed-by=/usr/share/keyrings/oneapi-archive-keyring.gpg] https://apt.repos.intel.com/oneapi all main" | sudo tee /etc/apt/sources.list.d/oneAPI.list
sudo apt update
sudo apt install -y intel-basekit
- name: Install CUDA Dependencies
run: |
curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64/cuda-keyring_1.1-1_all.deb
sudo dpkg -i cuda-keyring_1.1-1_all.deb
sudo apt-get update
sudo apt-get install -y cuda-nvcc-${CUDA_VERSION} libcublas-dev-${CUDA_VERSION}
env:
CUDA_VERSION: 12-5
- name: "Install Hipblas"
env:
ROCM_VERSION: "6.1"
AMDGPU_VERSION: "6.1"
run: |
set -ex
sudo apt-get update
sudo DEBIAN_FRONTEND=noninteractive apt-get install -y --no-install-recommends ca-certificates curl libnuma-dev gnupg
curl -sL https://repo.radeon.com/rocm/rocm.gpg.key | sudo apt-key add -
printf "deb [arch=amd64] https://repo.radeon.com/rocm/apt/$ROCM_VERSION/ jammy main" | sudo tee /etc/apt/sources.list.d/rocm.list
printf "deb [arch=amd64] https://repo.radeon.com/amdgpu/$AMDGPU_VERSION/ubuntu jammy main" | sudo tee /etc/apt/sources.list.d/amdgpu.list
printf 'Package: *\nPin: release o=repo.radeon.com\nPin-Priority: 600' | sudo tee /etc/apt/preferences.d/rocm-pin-600
sudo apt-get update
sudo DEBIAN_FRONTEND=noninteractive apt-get install -y \
hipblas-dev rocm-dev \
rocblas-dev
sudo apt-get clean
sudo rm -rf /var/lib/apt/lists/*
sudo ldconfig
- name: Cache grpc
id: cache-grpc
uses: actions/cache@v4
with:
path: grpc
key: ${{ runner.os }}-grpc-${{ env.GRPC_VERSION }}
- name: Build grpc
if: steps.cache-grpc.outputs.cache-hit != 'true'
run: |
git clone --recurse-submodules -b ${{ env.GRPC_VERSION }} --depth 1 --shallow-submodules https://github.com/grpc/grpc && \
cd grpc && sed -i "216i\ TESTONLY" "third_party/abseil-cpp/absl/container/CMakeLists.txt" && mkdir -p cmake/build && \
cd cmake/build && cmake -DgRPC_INSTALL=ON \
-DgRPC_BUILD_TESTS=OFF \
../.. && sudo make --jobs 5 --output-sync=target
- name: Install gRPC
run: |
cd grpc && cd cmake/build && sudo make --jobs 5 --output-sync=target install
# BACKEND_LIBS needed for gpu-workload: /opt/intel/oneapi/*/lib/libiomp5.so /opt/intel/oneapi/*/lib/libmkl_core.so /opt/intel/oneapi/*/lib/libmkl_core.so.2 /opt/intel/oneapi/*/lib/libmkl_intel_ilp64.so /opt/intel/oneapi/*/lib/libmkl_intel_ilp64.so.2 /opt/intel/oneapi/*/lib/libmkl_sycl_blas.so /opt/intel/oneapi/*/lib/libmkl_sycl_blas.so.4 /opt/intel/oneapi/*/lib/libmkl_tbb_thread.so /opt/intel/oneapi/*/lib/libmkl_tbb_thread.so.2 /opt/intel/oneapi/*/lib/libsycl.so /opt/intel/oneapi/*/lib/libsycl.so.7 /opt/intel/oneapi/*/lib/libsycl.so.7.1.0 /opt/rocm-*/lib/libamdhip64.so /opt/rocm-*/lib/libamdhip64.so.5 /opt/rocm-*/lib/libamdhip64.so.6 /opt/rocm-*/lib/libamdhip64.so.6.1.60100 /opt/rocm-*/lib/libhipblas.so /opt/rocm-*/lib/libhipblas.so.2 /opt/rocm-*/lib/libhipblas.so.2.1.60100 /opt/rocm-*/lib/librocblas.so /opt/rocm-*/lib/librocblas.so.4 /opt/rocm-*/lib/librocblas.so.4.1.60100 /usr/lib/x86_64-linux-gnu/libstdc++.so.6 /usr/lib/x86_64-linux-gnu/libOpenCL.so.1 /usr/lib/x86_64-linux-gnu/libOpenCL.so.1.0.0 /usr/lib/x86_64-linux-gnu/libm.so.6 /usr/lib/x86_64-linux-gnu/libgcc_s.so.1 /usr/lib/x86_64-linux-gnu/libc.so.6 /usr/lib/x86_64-linux-gnu/librt.so.1 /usr/local/cuda-*/targets/x86_64-linux/lib/libcublas.so /usr/local/cuda-*/targets/x86_64-linux/lib/libcublasLt.so /usr/local/cuda-*/targets/x86_64-linux/lib/libcudart.so /usr/local/cuda-*/targets/x86_64-linux/lib/stubs/libcuda.so
- name: Build
id: build
run: |
go install google.golang.org/grpc/cmd/protoc-gen-go-grpc@1958fcbe2ca8bd93af633f11e97d44e567e945af
go install google.golang.org/protobuf/cmd/protoc-gen-go@v1.34.2
export PATH=$PATH:$GOPATH/bin
export PATH=/usr/local/cuda/bin:$PATH
export PATH=/opt/rocm/bin:$PATH
source /opt/intel/oneapi/setvars.sh
sudo cp /lib64/ld-linux-x86-64.so.2 ld.so
BACKEND_LIBS="./ld.so ./sources/go-piper/piper/build/fi/lib/libfmt.a ./sources/go-piper/piper-phonemize/pi/lib/libonnxruntime.so.1.14.1 ./sources/go-piper/piper-phonemize/pi/src/libespeak-ng/libespeak-ng.so /usr/lib/x86_64-linux-gnu/libdl.so.2 /usr/lib/x86_64-linux-gnu/librt.so.1 /usr/lib/x86_64-linux-gnu/libpthread.so.0 ./sources/go-piper/piper-phonemize/pi/lib/libpiper_phonemize.so.1 ./sources/go-piper/piper/build/si/lib/libspdlog.a ./sources/go-piper/espeak/ei/lib/libucd.so" \
make -j4 dist
- uses: actions/upload-artifact@v4
with:
name: LocalAI-linux
path: release/
- name: Release
uses: softprops/action-gh-release@v2
if: startsWith(github.ref, 'refs/tags/')
with:
files: |
release/*
- name: Setup tmate session if tests fail
if: ${{ failure() }}
uses: mxschmitt/action-tmate@v3.18
with:
detached: true
connect-timeout-seconds: 180
limit-access-to-actor: true
build-stablediffusion:
runs-on: ubuntu-latest
steps:
- name: Clone
uses: actions/checkout@v4
with:
submodules: true
- uses: actions/setup-go@v5
with:
go-version: '1.21.x'
cache: false
- name: Dependencies
run: |
sudo apt-get update
sudo apt-get install -y --no-install-recommends libopencv-dev protobuf-compiler ccache
go install google.golang.org/grpc/cmd/protoc-gen-go-grpc@1958fcbe2ca8bd93af633f11e97d44e567e945af
go install google.golang.org/protobuf/cmd/protoc-gen-go@v1.34.2
- name: Build stablediffusion
run: |
export PATH=$PATH:$GOPATH/bin
make backend-assets/grpc/stablediffusion
mkdir -p release && cp backend-assets/grpc/stablediffusion release
env:
GO_TAGS: stablediffusion
- uses: actions/upload-artifact@v4
with:
name: stablediffusion
path: release/
- name: Release
uses: softprops/action-gh-release@v2
if: startsWith(github.ref, 'refs/tags/')
with:
files: |
release/*
build-macOS-x86_64:
runs-on: macos-13
steps:
- name: Clone
uses: actions/checkout@v4
with:
submodules: true
- uses: actions/setup-go@v5
with:
go-version: '1.21.x'
cache: false
- name: Dependencies
run: |
brew install protobuf grpc
go install google.golang.org/grpc/cmd/protoc-gen-go-grpc@8ba23be9613c672d40ae261d2a1335d639bdd59b
go install google.golang.org/protobuf/cmd/protoc-gen-go@v1.34.0
- name: Build
id: build
run: |
export C_INCLUDE_PATH=/usr/local/include
export CPLUS_INCLUDE_PATH=/usr/local/include
export PATH=$PATH:$GOPATH/bin
make dist
- uses: actions/upload-artifact@v4
with:
name: LocalAI-MacOS-x86_64
path: release/
- name: Release
uses: softprops/action-gh-release@v2
if: startsWith(github.ref, 'refs/tags/')
with:
files: |
release/*
- name: Setup tmate session if tests fail
if: ${{ failure() }}
uses: mxschmitt/action-tmate@v3.18
with:
detached: true
connect-timeout-seconds: 180
limit-access-to-actor: true
build-macOS-arm64:
runs-on: macos-14
steps:
- name: Clone
uses: actions/checkout@v4
with:
submodules: true
- uses: actions/setup-go@v5
with:
go-version: '1.21.x'
cache: false
- name: Dependencies
run: |
brew install protobuf grpc
go install google.golang.org/grpc/cmd/protoc-gen-go-grpc@1958fcbe2ca8bd93af633f11e97d44e567e945af
go install google.golang.org/protobuf/cmd/protoc-gen-go@v1.34.2
- name: Build
id: build
run: |
export C_INCLUDE_PATH=/usr/local/include
export CPLUS_INCLUDE_PATH=/usr/local/include
export PATH=$PATH:$GOPATH/bin
make dist
- uses: actions/upload-artifact@v4
with:
name: LocalAI-MacOS-arm64
path: release/
- name: Release
uses: softprops/action-gh-release@v2
if: startsWith(github.ref, 'refs/tags/')
with:
files: |
release/*
- name: Setup tmate session if tests fail
if: ${{ failure() }}
uses: mxschmitt/action-tmate@v3.18
with:
detached: true
connect-timeout-seconds: 180
limit-access-to-actor: true

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@master
with:
# we let the report trigger content trigger a failure using the GitHub Security features.
args: '-no-fail -fmt sarif -out results.sarif ./...'
- name: Upload SARIF file
if: ${{ github.actor != 'dependabot[bot]' }}
uses: github/codeql-action/upload-sarif@v4
uses: github/codeql-action/upload-sarif@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'

70
.github/workflows/static-check.yml vendored Normal file
View File

@@ -0,0 +1,70 @@
name: static check
on: pull_request
jobs:
imports:
name: Imports
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@master
- name: check
uses: danhunsaker/golang-github-actions@v1.3.0
with:
run: imports
token: ${{ secrets.GITHUB_TOKEN }}
errcheck:
name: Errcheck
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@master
- name: check
uses: danhunsaker/golang-github-actions@v1.3.0
with:
run: errcheck
token: ${{ secrets.GITHUB_TOKEN }}
lint:
name: Lint
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@master
- name: check
uses: danhunsaker/golang-github-actions@v1.3.0
with:
run: lint
token: ${{ secrets.GITHUB_TOKEN }}
shadow:
name: Shadow
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@master
- name: check
uses: danhunsaker/golang-github-actions@v1.3.0
with:
run: shadow
token: ${{ secrets.GITHUB_TOKEN }}
staticcheck:
name: StaticCheck
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@master
- name: check
uses: danhunsaker/golang-github-actions@v1.3.0
with:
run: staticcheck
token: ${{ secrets.GITHUB_TOKEN }}
sec:
name: Sec
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@master
- name: check
uses: danhunsaker/golang-github-actions@v1.3.0
with:
run: sec
token: ${{ secrets.GITHUB_TOKEN }}
flags: "-exclude=G104"

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
@@ -57,11 +35,35 @@ jobs:
run: |
make --jobs=5 --output-sync=target -C backend/python/transformers
make --jobs=5 --output-sync=target -C backend/python/transformers test
tests-sentencetransformers:
runs-on: ubuntu-latest
steps:
- name: Clone
uses: actions/checkout@v4
with:
submodules: true
- name: Dependencies
run: |
sudo apt-get update
sudo apt-get install build-essential ffmpeg
# Install UV
curl -LsSf https://astral.sh/uv/install.sh | sh
sudo apt-get install -y ca-certificates cmake curl patch python3-pip
sudo apt-get install -y libopencv-dev
pip install --user --no-cache-dir grpcio-tools==1.64.1
- name: Test sentencetransformers
run: |
make --jobs=5 --output-sync=target -C backend/python/sentencetransformers
make --jobs=5 --output-sync=target -C backend/python/sentencetransformers test
tests-rerankers:
runs-on: ubuntu-latest
steps:
- name: Clone
uses: actions/checkout@v6
uses: actions/checkout@v4
with:
submodules: true
- name: Dependencies
@@ -83,7 +85,7 @@ jobs:
runs-on: ubuntu-latest
steps:
- name: Clone
uses: actions/checkout@v6
uses: actions/checkout@v4
with:
submodules: true
- name: Dependencies
@@ -100,31 +102,79 @@ 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:
tests-parler-tts:
runs-on: ubuntu-latest
steps:
- name: Clone
uses: actions/checkout@v4
with:
submodules: true
- name: Dependencies
run: |
sudo apt-get update
sudo apt-get install build-essential ffmpeg
# Install UV
curl -LsSf https://astral.sh/uv/install.sh | sh
sudo apt-get install -y ca-certificates cmake curl patch python3-pip
sudo apt-get install -y libopencv-dev
pip install --user --no-cache-dir grpcio-tools==1.64.1
- name: Test parler-tts
run: |
make --jobs=5 --output-sync=target -C backend/python/parler-tts
make --jobs=5 --output-sync=target -C backend/python/parler-tts test
tests-openvoice:
runs-on: ubuntu-latest
steps:
- name: Clone
uses: actions/checkout@v4
with:
submodules: true
- name: Dependencies
run: |
sudo apt-get update
sudo apt-get install build-essential ffmpeg
# Install UV
curl -LsSf https://astral.sh/uv/install.sh | sh
sudo apt-get install -y ca-certificates cmake curl patch python3-pip
sudo apt-get install -y libopencv-dev
pip install --user --no-cache-dir grpcio-tools==1.64.1
- name: Test openvoice
run: |
make --jobs=5 --output-sync=target -C backend/python/openvoice
make --jobs=5 --output-sync=target -C backend/python/openvoice test
tests-transformers-musicgen:
runs-on: ubuntu-latest
steps:
- name: Clone
uses: actions/checkout@v4
with:
submodules: true
- name: Dependencies
run: |
sudo apt-get update
sudo apt-get install build-essential ffmpeg
# Install UV
curl -LsSf https://astral.sh/uv/install.sh | sh
sudo apt-get install -y ca-certificates cmake curl patch python3-pip
sudo apt-get install -y libopencv-dev
pip install --user --no-cache-dir grpcio-tools==1.64.1
- name: Test transformers-musicgen
run: |
make --jobs=5 --output-sync=target -C backend/python/transformers-musicgen
make --jobs=5 --output-sync=target -C backend/python/transformers-musicgen test
# tests-petals:
# runs-on: ubuntu-latest
# steps:
# - name: Clone
# uses: actions/checkout@v6
# uses: actions/checkout@v4
# with:
# submodules: true
# - name: Dependencies
@@ -137,10 +187,12 @@ jobs:
# sudo apt-get install -y libopencv-dev
# pip install --user --no-cache-dir grpcio-tools==1.64.1
# - name: Test transformers-musicgen
# - name: Test petals
# run: |
# make --jobs=5 --output-sync=target -C backend/python/transformers-musicgen
# make --jobs=5 --output-sync=target -C backend/python/transformers-musicgen test
# make --jobs=5 --output-sync=target -C backend/python/petals
# make --jobs=5 --output-sync=target -C backend/python/petals test
# tests-bark:
# runs-on: ubuntu-latest
@@ -186,7 +238,7 @@ 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 +263,7 @@ jobs:
# runs-on: ubuntu-latest
# steps:
# - name: Clone
# uses: actions/checkout@v6
# uses: actions/checkout@v4
# with:
# submodules: true
# - name: Dependencies
@@ -227,18 +279,38 @@ jobs:
# run: |
# make --jobs=5 --output-sync=target -C backend/python/vllm
# make --jobs=5 --output-sync=target -C backend/python/vllm test
tests-coqui:
tests-vallex:
runs-on: ubuntu-latest
steps:
- name: Clone
uses: actions/checkout@v6
uses: actions/checkout@v4
with:
submodules: true
- name: Dependencies
run: |
sudo apt-get update
sudo apt-get install -y build-essential ffmpeg
sudo apt-get install build-essential ffmpeg
# Install UV
curl -LsSf https://astral.sh/uv/install.sh | sh
sudo apt-get install -y ca-certificates cmake curl patch python3-pip
sudo apt-get install -y libopencv-dev
pip install --user --no-cache-dir grpcio-tools==1.64.1
- name: Test vall-e-x
run: |
make --jobs=5 --output-sync=target -C backend/python/vall-e-x
make --jobs=5 --output-sync=target -C backend/python/vall-e-x test
tests-coqui:
runs-on: ubuntu-latest
steps:
- name: Clone
uses: actions/checkout@v4
with:
submodules: true
- name: Dependencies
run: |
sudo apt-get update
sudo apt-get install build-essential ffmpeg
sudo apt-get install -y ca-certificates cmake curl patch espeak espeak-ng python3-pip
# Install UV
curl -LsSf https://astral.sh/uv/install.sh | sh
@@ -247,98 +319,3 @@ 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 -y 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
tests-pocket-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 -y 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 pocket-tts
run: |
make --jobs=5 --output-sync=target -C backend/python/pocket-tts
make --jobs=5 --output-sync=target -C backend/python/pocket-tts test
tests-qwen-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 -y 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 qwen-tts
run: |
make --jobs=5 --output-sync=target -C backend/python/qwen-tts
make --jobs=5 --output-sync=target -C backend/python/qwen-tts test
tests-qwen-asr:
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 sox
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 qwen-asr
run: |
make --jobs=5 --output-sync=target -C backend/python/qwen-asr
make --jobs=5 --output-sync=target -C backend/python/qwen-asr test
tests-voxcpm:
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 voxcpm
run: |
make --jobs=5 --output-sync=target -C backend/python/voxcpm
make --jobs=5 --output-sync=target -C backend/python/voxcpm 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:$HOME/go/bin" make protogen-go
- name: Dependencies
run: |
sudo apt-get update
sudo apt-get install build-essential ccache upx-ucl curl ffmpeg
sudo apt-get install -y libgmock-dev clang
sudo apt-get install build-essential curl ffmpeg
sudo apt-get install -y libgmock-dev
curl https://repo.anaconda.com/pkgs/misc/gpgkeys/anaconda.asc | gpg --dearmor > conda.gpg && \
sudo install -o root -g root -m 644 conda.gpg /usr/share/keyrings/conda-archive-keyring.gpg && \
gpg --keyring /usr/share/keyrings/conda-archive-keyring.gpg --no-default-keyring --fingerprint 34161F5BF5EB1D4BFBBB8F0A8AEB4F8B29D82806 && \
sudo /bin/bash -c 'echo "deb [arch=amd64 signed-by=/usr/share/keyrings/conda-archive-keyring.gpg] https://repo.anaconda.com/pkgs/misc/debrepo/conda stable main" > /etc/apt/sources.list.d/conda.list' && \
sudo /bin/bash -c 'echo "deb [arch=amd64 signed-by=/usr/share/keyrings/conda-archive-keyring.gpg] https://repo.anaconda.com/pkgs/misc/debrepo/conda stable main" | tee -a /etc/apt/sources.list.d/conda.list' && \
sudo apt-get update && \
sudo apt-get install -y conda
# Install UV
curl -LsSf https://astral.sh/uv/install.sh | sh
sudo apt-get install -y ca-certificates cmake patch python3-pip unzip
@@ -109,17 +93,47 @@ jobs:
sudo apt-get update
sudo apt-get install -y cuda-nvcc-${CUDA_VERSION} libcublas-dev-${CUDA_VERSION}
export CUDACXX=/usr/local/cuda/bin/nvcc
make -C backend/python/transformers
make backends/huggingface backends/llama-cpp backends/local-store backends/silero-vad backends/piper backends/whisper backends/stablediffusion-ggml
go install google.golang.org/protobuf/cmd/protoc-gen-go@v1.34.2
go install google.golang.org/grpc/cmd/protoc-gen-go-grpc@1958fcbe2ca8bd93af633f11e97d44e567e945af
# The python3-grpc-tools package in 22.04 is too old
pip install --user grpcio-tools
sudo rm -rfv /usr/bin/conda || true
PATH=$PATH:/opt/conda/bin make -C backend/python/sentencetransformers
# Pre-build piper before we start tests in order to have shared libraries in place
make sources/go-piper && \
GO_TAGS="tts" make -C sources/go-piper piper.o && \
sudo cp -rfv sources/go-piper/piper-phonemize/pi/lib/. /usr/lib/ && \
# Pre-build stable diffusion before we install a newer version of abseil (not compatible with stablediffusion-ncn)
PATH="$PATH:/root/go/bin" GO_TAGS="stablediffusion tts" GRPC_BACKENDS=backend-assets/grpc/stablediffusion make build
env:
CUDA_VERSION: 12-4
- name: Cache grpc
id: cache-grpc
uses: actions/cache@v4
with:
path: grpc
key: ${{ runner.os }}-grpc-${{ env.GRPC_VERSION }}
- name: Build grpc
if: steps.cache-grpc.outputs.cache-hit != 'true'
run: |
git clone --recurse-submodules -b ${{ env.GRPC_VERSION }} --depth 1 --jobs 5 --shallow-submodules https://github.com/grpc/grpc && \
cd grpc && sed -i "216i\ TESTONLY" "third_party/abseil-cpp/absl/container/CMakeLists.txt" && mkdir -p cmake/build && cd cmake/build && \
cmake -DgRPC_INSTALL=ON \
-DgRPC_BUILD_TESTS=OFF \
../.. && sudo make --jobs 5
- name: Install gRPC
run: |
cd grpc && cd cmake/build && sudo make --jobs 5 install
- name: Test
run: |
PATH="$PATH:/root/go/bin" GO_TAGS="tts" make --jobs 5 --output-sync=target test
PATH="$PATH:/root/go/bin" GO_TAGS="stablediffusion tts" make --jobs 5 --output-sync=target test
- name: Setup tmate session if tests fail
if: ${{ failure() }}
uses: mxschmitt/action-tmate@v3.23
uses: mxschmitt/action-tmate@v3.18
with:
detached: true
connect-timeout-seconds: 180
@@ -161,37 +175,33 @@ jobs:
sudo rm -rfv build || true
df -h
- name: Clone
uses: actions/checkout@v6
uses: actions/checkout@v4
with:
submodules: true
- name: Dependencies
- name: Build images
run: |
# Install protoc
curl -L -s https://github.com/protocolbuffers/protobuf/releases/download/v26.1/protoc-26.1-linux-x86_64.zip -o protoc.zip && \
unzip -j -d /usr/local/bin protoc.zip bin/protoc && \
rm protoc.zip
go install google.golang.org/protobuf/cmd/protoc-gen-go@v1.34.2
go install google.golang.org/grpc/cmd/protoc-gen-go-grpc@1958fcbe2ca8bd93af633f11e97d44e567e945af
PATH="$PATH:$HOME/go/bin" make protogen-go
docker build --build-arg FFMPEG=true --build-arg IMAGE_TYPE=extras --build-arg EXTRA_BACKENDS=rerankers --build-arg MAKEFLAGS="--jobs=5 --output-sync=target" -t local-ai:tests -f Dockerfile .
BASE_IMAGE=local-ai:tests DOCKER_AIO_IMAGE=local-ai-aio:test make docker-aio
- name: Test
run: |
PATH="$PATH:$HOME/go/bin" make backends/local-store backends/silero-vad backends/llama-cpp backends/whisper backends/piper backends/stablediffusion-ggml docker-build-aio e2e-aio
LOCALAI_MODELS_DIR=$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@v3.18
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 ${{ matrix.go-version }}
@@ -204,24 +214,18 @@ jobs:
run: go version
- name: Dependencies
run: |
brew install protobuf grpc make protoc-gen-go protoc-gen-go-grpc libomp llvm
pip install --user --no-cache-dir grpcio-tools grpcio
- name: Build llama-cpp-darwin
run: |
make protogen-go
make backends/llama-cpp-darwin
brew install protobuf grpc make protoc-gen-go protoc-gen-go-grpc
pip install --user --no-cache-dir grpcio-tools==1.64.1
- name: Test
run: |
export C_INCLUDE_PATH=/usr/local/include
export CPLUS_INCLUDE_PATH=/usr/local/include
export CC=/opt/homebrew/opt/llvm/bin/clang
# Used to run the newer GNUMake version from brew that supports --output-sync
export PATH="/opt/homebrew/opt/make/libexec/gnubin:$PATH"
PATH="$PATH:$HOME/go/bin" make protogen-go
PATH="$PATH:$HOME/go/bin" BUILD_TYPE="GITHUB_CI_HAS_BROKEN_METAL" CMAKE_ARGS="-DGGML_F16C=OFF -DGGML_AVX512=OFF -DGGML_AVX2=OFF -DGGML_FMA=OFF" make --jobs 4 --output-sync=target test
BUILD_TYPE="GITHUB_CI_HAS_BROKEN_METAL" CMAKE_ARGS="-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@v3.18
with:
detached: true
connect-timeout-seconds: 180

View File

@@ -1,56 +0,0 @@
---
name: 'E2E Backend Tests'
on:
pull_request:
push:
branches:
- master
tags:
- '*'
concurrency:
group: ci-tests-e2e-backend-${{ github.head_ref || github.ref }}-${{ github.repository }}
cancel-in-progress: true
jobs:
tests-e2e-backend:
runs-on: ubuntu-latest
strategy:
matrix:
go-version: ['1.25.x']
steps:
- name: Clone
uses: actions/checkout@v6
with:
submodules: true
- name: Setup Go ${{ matrix.go-version }}
uses: actions/setup-go@v5
with:
go-version: ${{ matrix.go-version }}
cache: false
- name: Display Go version
run: go version
- name: Proto Dependencies
run: |
# Install protoc
curl -L -s https://github.com/protocolbuffers/protobuf/releases/download/v26.1/protoc-26.1-linux-x86_64.zip -o protoc.zip && \
unzip -j -d /usr/local/bin protoc.zip bin/protoc && \
rm protoc.zip
go install google.golang.org/protobuf/cmd/protoc-gen-go@v1.34.2
go install google.golang.org/grpc/cmd/protoc-gen-go-grpc@1958fcbe2ca8bd93af633f11e97d44e567e945af
PATH="$PATH:$HOME/go/bin" make protogen-go
- name: Dependencies
run: |
sudo apt-get update
sudo apt-get install -y build-essential
- name: Test Backend E2E
run: |
PATH="$PATH:$HOME/go/bin" make build-mock-backend test-e2e
- name: Setup tmate session if tests fail
if: ${{ failure() }}
uses: mxschmitt/action-tmate@v3.23
with:
detached: true
connect-timeout-seconds: 180
limit-access-to-actor: true

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@v6
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 }}

19
.gitignore vendored
View File

@@ -2,30 +2,24 @@
/sources/
__pycache__/
*.a
*.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
go-ggml-transformers
go-gpt2
go-rwkv
whisper.cpp
/bloomz
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
@@ -36,8 +30,6 @@ LocalAI
models/*
test-models/
test-dir/
tests/e2e-aio/backends
tests/e2e-aio/models
release/
@@ -62,6 +54,3 @@ docs/static/gallery.html
# backend virtual environments
**/venv
# per-developer customization files for the development container
.devcontainer/customization/*

3
.gitmodules vendored
View File

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

View File

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

21
.vscode/launch.json vendored
View File

@@ -3,12 +3,12 @@
"configurations": [
{
"name": "Python: Current File",
"type": "debugpy",
"type": "python",
"request": "launch",
"program": "${file}",
"console": "integratedTerminal",
"justMyCode": false,
"cwd": "${fileDirname}",
"cwd": "${workspaceFolder}/examples/langchain-chroma",
"env": {
"OPENAI_API_BASE": "http://localhost:8080/v1",
"OPENAI_API_KEY": "abc"
@@ -19,16 +19,15 @@
"type": "go",
"request": "launch",
"mode": "debug",
"program": "${workspaceRoot}",
"args": [],
"program": "${workspaceFolder}/main.go",
"args": [
"api"
],
"env": {
"LOCALAI_LOG_LEVEL": "debug",
"LOCALAI_P2P": "true",
"LOCALAI_FEDERATED": "true"
},
"buildFlags": ["-tags", "", "-v"],
"envFile": "${workspaceFolder}/.env",
"cwd": "${workspaceRoot}"
"C_INCLUDE_PATH": "${workspaceFolder}/go-llama:${workspaceFolder}/go-stable-diffusion/:${workspaceFolder}/gpt4all/gpt4all-bindings/golang/:${workspaceFolder}/go-gpt2:${workspaceFolder}/go-rwkv:${workspaceFolder}/whisper.cpp:${workspaceFolder}/go-bert:${workspaceFolder}/bloomz",
"LIBRARY_PATH": "${workspaceFolder}/go-llama:${workspaceFolder}/go-stable-diffusion/:${workspaceFolder}/gpt4all/gpt4all-bindings/golang/:${workspaceFolder}/go-gpt2:${workspaceFolder}/go-rwkv:${workspaceFolder}/whisper.cpp:${workspaceFolder}/go-bert:${workspaceFolder}/bloomz",
"DEBUG": "true"
}
}
]
}

290
AGENTS.md
View File

@@ -1,290 +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 coqui for ROCM/hipblas
- The Makefile has targets like `docker-build-coqui` 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-coqui`
- 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`, `coqui`):
```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
# Documentation
The project documentation is located in `docs/content`. When adding new features or changing existing functionality, it is crucial to update the documentation to reflect these changes. This helps users understand how to use the new capabilities and ensures the documentation stays relevant.
- **Feature Documentation**: If you add a new feature (like a new backend or API endpoint), create a new markdown file in `docs/content/features/` explaining what it is, how to configure it, and how to use it.
- **Configuration**: If you modify configuration options, update the relevant sections in `docs/content/`.
- **Examples**: providing concrete examples (like YAML configuration blocks) is highly encouraged to help users get started quickly.

View File

@@ -15,6 +15,8 @@ Thank you for your interest in contributing to LocalAI! We appreciate your time
- [Documentation](#documentation)
- [Community and Communication](#community-and-communication)
## Getting Started
### Prerequisites
@@ -30,7 +32,6 @@ 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
@@ -53,7 +54,7 @@ If you find a bug, have a feature request, or encounter any issues, please check
## Coding Guidelines
- No specific coding guidelines at the moment. Please make sure the code can be tested. The most popular lint tools like [`golangci-lint`](https://golangci-lint.run) can help you here.
- No specific coding guidelines at the moment. Please make sure the code can be tested. The most popular lint tools like []`golangci-lint`](https://golangci-lint.run) can help you here.
## Testing
@@ -77,23 +78,11 @@ 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.
- Open a new discussion at [Discussion](https://github.com/go-skynet/LocalAI/discussions)
- Join the Discord channel [Discord](https://discord.gg/uJAeKSAGDy)
---

View File

@@ -1,100 +1,135 @@
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
# The requirements-core target is common to all images. It should not be placed in requirements-core unless every single build will use it.
FROM ${BASE_IMAGE} AS requirements-core
USER root
ARG GO_VERSION=1.22.5
ARG TARGETARCH
ARG TARGETVARIANT
ENV DEBIAN_FRONTEND=noninteractive
ENV EXTERNAL_GRPC_BACKENDS="coqui:/build/backend/python/coqui/run.sh,huggingface-embeddings:/build/backend/python/sentencetransformers/run.sh,petals:/build/backend/python/petals/run.sh,transformers:/build/backend/python/transformers/run.sh,sentencetransformers:/build/backend/python/sentencetransformers/run.sh,rerankers:/build/backend/python/rerankers/run.sh,autogptq:/build/backend/python/autogptq/run.sh,bark:/build/backend/python/bark/run.sh,diffusers:/build/backend/python/diffusers/run.sh,exllama:/build/backend/python/exllama/run.sh,openvoice:/build/backend/python/openvoice/run.sh,vall-e-x:/build/backend/python/vall-e-x/run.sh,vllm:/build/backend/python/vllm/run.sh,mamba:/build/backend/python/mamba/run.sh,exllama2:/build/backend/python/exllama2/run.sh,transformers-musicgen:/build/backend/python/transformers-musicgen/run.sh,parler-tts:/build/backend/python/parler-tts/run.sh"
RUN apt-get update && \
apt-get install -y --no-install-recommends \
ca-certificates curl wget espeak-ng libgomp1 \
ffmpeg libopenblas0 libopenblas-dev sox && \
build-essential \
ccache \
ca-certificates \
cmake \
curl \
git \
unzip && \
apt-get clean && \
rm -rf /var/lib/apt/lists/*
# Install Go
RUN curl -L -s https://go.dev/dl/go${GO_VERSION}.linux-${TARGETARCH}.tar.gz | tar -C /usr/local -xz
ENV PATH $PATH:/root/go/bin:/usr/local/go/bin
# Install grpc compilers
RUN go install google.golang.org/protobuf/cmd/protoc-gen-go@v1.34.2 && \
go install google.golang.org/grpc/cmd/protoc-gen-go-grpc@1958fcbe2ca8bd93af633f11e97d44e567e945af
COPY --chmod=644 custom-ca-certs/* /usr/local/share/ca-certificates/
RUN update-ca-certificates
# Use the variables in subsequent instructions
RUN echo "Target Architecture: $TARGETARCH"
RUN echo "Target Variant: $TARGETVARIANT"
# Cuda
ENV PATH /usr/local/cuda/bin:${PATH}
# HipBLAS requirements
ENV PATH /opt/rocm/bin:${PATH}
# OpenBLAS requirements and stable diffusion
RUN apt-get update && \
apt-get install -y --no-install-recommends \
libopenblas-dev \
libopencv-dev && \
apt-get clean && \
rm -rf /var/lib/apt/lists/*
# Set up OpenCV
RUN ln -s /usr/include/opencv4/opencv2 /usr/include/opencv2
WORKDIR /build
RUN test -n "$TARGETARCH" \
|| (echo 'warn: missing $TARGETARCH, either set this `ARG` manually, or run using `docker buildkit`')
###################################
###################################
# The requirements-extras target is for any builds with IMAGE_TYPE=extras. It should not be placed in this target unless every IMAGE_TYPE=extras build will use it
FROM requirements-core AS requirements-extras
RUN curl -LsSf https://astral.sh/uv/install.sh | sh
ENV PATH="/root/.cargo/bin:${PATH}"
RUN curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh -s -- -y
RUN apt-get update && \
apt-get install -y --no-install-recommends \
espeak-ng \
espeak \
python3-pip \
python-is-python3 \
python3-dev \
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.
FROM requirements AS requirements-drivers
# This target will be built on top of requirements-core or requirements-extras as retermined by the IMAGE_TYPE build-arg
FROM requirements-${IMAGE_TYPE} AS requirements-drivers
ARG BUILD_TYPE
ARG CUDA_MAJOR_VERSION=12
ARG CUDA_MINOR_VERSION=0
ARG SKIP_DRIVERS=false
ARG TARGETARCH
ARG TARGETVARIANT
ENV BUILD_TYPE=${BUILD_TYPE}
ARG UBUNTU_VERSION=2404
ARG CUDA_MINOR_VERSION=4
RUN mkdir -p /run/localai
RUN echo "default" > /run/localai/capability
ENV BUILD_TYPE=${BUILD_TYPE}
# Vulkan requirements
RUN <<EOT bash
if [ "${BUILD_TYPE}" = "vulkan" ] && [ "${SKIP_DRIVERS}" = "false" ]; then
if [ "${BUILD_TYPE}" = "vulkan" ]; 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" = "$TARGETARCH" ]; then
wget "https://sdk.lunarg.com/sdk/download/1.4.335.0/linux/vulkansdk-linux-x86_64-1.4.335.0.tar.xz" && \
tar -xf vulkansdk-linux-x86_64-1.4.335.0.tar.xz && \
rm vulkansdk-linux-x86_64-1.4.335.0.tar.xz && \
mkdir -p /opt/vulkan-sdk && \
mv 1.4.335.0 /opt/vulkan-sdk/ && \
cd /opt/vulkan-sdk/1.4.335.0 && \
./vulkansdk --no-deps --maxjobs \
vulkan-loader \
vulkan-validationlayers \
vulkan-extensionlayer \
vulkan-tools \
shaderc && \
cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/bin/* /usr/bin/ && \
cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/lib/* /usr/lib/x86_64-linux-gnu/ && \
cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/include/* /usr/include/ && \
cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/share/* /usr/share/ && \
rm -rf /opt/vulkan-sdk
fi
if [ "arm64" = "$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 && \
wget -qO - https://packages.lunarg.com/lunarg-signing-key-pub.asc | apt-key add - && \
wget -qO /etc/apt/sources.list.d/lunarg-vulkan-jammy.list https://packages.lunarg.com/vulkan/lunarg-vulkan-jammy.list && \
apt-get update && \
apt-get install -y \
vulkan-sdk && \
apt-get clean && \
rm -rf /var/lib/apt/lists/* && \
echo "vulkan" > /run/localai/capability
rm -rf /var/lib/apt/lists/*
fi
EOT
# CuBLAS requirements
RUN <<EOT bash
if ( [ "${BUILD_TYPE}" = "cublas" ] || [ "${BUILD_TYPE}" = "l4t" ] ) && [ "${SKIP_DRIVERS}" = "false" ]; then
if [ "${BUILD_TYPE}" = "cublas" ]; then
apt-get update && \
apt-get install -y --no-install-recommends \
software-properties-common pciutils
if [ "amd64" = "$TARGETARCH" ]; then
curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu${UBUNTU_VERSION}/x86_64/cuda-keyring_1.1-1_all.deb
curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64/cuda-keyring_1.1-1_all.deb
fi
if [ "arm64" = "$TARGETARCH" ]; then
if [ "${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
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 && \
@@ -105,39 +140,14 @@ RUN <<EOT bash
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}-${CUDA_MINOR_VERSION}
fi
libcusolver-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} && \
apt-get clean && \
rm -rf /var/lib/apt/lists/* && \
echo "nvidia-cuda-${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
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 \
RUN if [ "${BUILD_TYPE}" = "clblas" ]; then \
apt-get update && \
apt-get install -y --no-install-recommends \
libclblast-dev && \
@@ -145,92 +155,18 @@ RUN if [ "${BUILD_TYPE}" = "clblas" ] && [ "${SKIP_DRIVERS}" = "false" ]; then \
rm -rf /var/lib/apt/lists/* \
; fi
RUN if [ "${BUILD_TYPE}" = "hipblas" ] && [ "${SKIP_DRIVERS}" = "false" ]; then \
RUN if [ "${BUILD_TYPE}" = "hipblas" ]; then \
apt-get update && \
apt-get install -y --no-install-recommends \
hipblas-dev \
rocblas-dev && \
apt-get clean && \
rm -rf /var/lib/apt/lists/* && \
echo "amd" > /run/localai/capability && \
# I have no idea why, but the ROCM lib packages don't trigger ldconfig after they install, which results in local-ai and others not being able
# to locate the libraries. We run ldconfig ourselves to work around this packaging deficiency
ldconfig \
; fi
RUN if [ "${BUILD_TYPE}" = "hipblas" ]; then \
ln -s /opt/rocm-**/lib/llvm/lib/libomp.so /usr/lib/libomp.so \
; fi
RUN expr "${BUILD_TYPE}" = intel && echo "intel" > /run/localai/capability || echo "not intel"
# Cuda
ENV PATH=/usr/local/cuda/bin:${PATH}
# HipBLAS requirements
ENV PATH=/opt/rocm/bin:${PATH}
###################################
###################################
# The requirements-core target is common to all images. It should not be placed in requirements-core unless every single build will use it.
FROM requirements-drivers AS build-requirements
ARG GO_VERSION=1.25.4
ARG CMAKE_VERSION=3.31.10
ARG CMAKE_FROM_SOURCE=false
ARG TARGETARCH
ARG TARGETVARIANT
RUN apt-get update && \
apt-get install -y --no-install-recommends \
build-essential \
ccache \
ca-certificates espeak-ng \
curl libssl-dev \
git \
git-lfs \
unzip upx-ucl python3 python-is-python3 && \
apt-get clean && \
rm -rf /var/lib/apt/lists/*
# Install CMake (the version in 22.04 is too old)
RUN <<EOT bash
if [ "${CMAKE_FROM_SOURCE}" = "true" ]; then
curl -L -s https://github.com/Kitware/CMake/releases/download/v${CMAKE_VERSION}/cmake-${CMAKE_VERSION}.tar.gz -o cmake.tar.gz && tar xvf cmake.tar.gz && cd cmake-${CMAKE_VERSION} && ./configure && make && make install
else
apt-get update && \
apt-get install -y \
cmake && \
apt-get clean && \
rm -rf /var/lib/apt/lists/*
fi
EOT
# Install Go
RUN curl -L -s https://go.dev/dl/go${GO_VERSION}.linux-${TARGETARCH}.tar.gz | tar -C /usr/local -xz
ENV PATH=$PATH:/root/go/bin:/usr/local/go/bin
# Install grpc compilers
RUN go install google.golang.org/protobuf/cmd/protoc-gen-go@v1.34.2 && \
go install google.golang.org/grpc/cmd/protoc-gen-go-grpc@1958fcbe2ca8bd93af633f11e97d44e567e945af
COPY --chmod=644 custom-ca-certs/* /usr/local/share/ca-certificates/
RUN update-ca-certificates
RUN test -n "$TARGETARCH" \
|| (echo 'warn: missing $TARGETARCH, either set this `ARG` manually, or run using `docker buildkit`')
# Use the variables in subsequent instructions
RUN echo "Target Architecture: $TARGETARCH"
RUN echo "Target Variant: $TARGETVARIANT"
WORKDIR /build
###################################
###################################
@@ -238,43 +174,75 @@ 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 ${GRPC_BASE_IMAGE} AS grpc
# This is a bit of a hack, but it's required in order to be able to effectively cache this layer in CI
ARG GRPC_MAKEFLAGS="-j4 -Otarget"
ARG GRPC_VERSION=v1.65.0
ENV MAKEFLAGS=${GRPC_MAKEFLAGS}
WORKDIR /build
RUN apt-get update && \
apt-get install -y --no-install-recommends \
intel-oneapi-runtime-libs && \
ca-certificates \
build-essential \
cmake \
git && \
apt-get clean && \
rm -rf /var/lib/apt/lists/*
# We install GRPC to a different prefix here so that we can copy in only the build artifacts later
# saves several hundred MB on the final docker image size vs copying in the entire GRPC source tree
# and running make install in the target container
RUN git clone --recurse-submodules --jobs 4 -b ${GRPC_VERSION} --depth 1 --shallow-submodules https://github.com/grpc/grpc && \
mkdir -p /build/grpc/cmake/build && \
cd /build/grpc/cmake/build && \
sed -i "216i\ TESTONLY" "../../third_party/abseil-cpp/absl/container/CMakeLists.txt" && \
cmake -DgRPC_INSTALL=ON -DgRPC_BUILD_TESTS=OFF -DCMAKE_INSTALL_PREFIX:PATH=/opt/grpc ../.. && \
make && \
make install && \
rm -rf /build
###################################
###################################
# The builder-base target has the arguments, variables, and copies shared between full builder images and the uncompiled devcontainer
# The builder target compiles LocalAI. This target is not the target that will be uploaded to the registry.
# Adjustments to the build process should likely be made here.
FROM requirements-drivers AS builder
FROM build-requirements AS builder-base
ARG GO_TAGS=""
ARG GO_TAGS="stablediffusion tts p2p"
ARG GRPC_BACKENDS
ARG MAKEFLAGS
ARG LD_FLAGS="-s -w"
ARG TARGETARCH
ARG TARGETVARIANT
ENV GRPC_BACKENDS=${GRPC_BACKENDS}
ENV GO_TAGS=${GO_TAGS}
ENV MAKEFLAGS=${MAKEFLAGS}
ENV NVIDIA_DRIVER_CAPABILITIES=compute,utility
ENV NVIDIA_REQUIRE_CUDA="cuda>=${CUDA_MAJOR_VERSION}.0"
ENV NVIDIA_VISIBLE_DEVICES=all
ENV LD_FLAGS=${LD_FLAGS}
RUN echo "GO_TAGS: $GO_TAGS" && echo "TARGETARCH: $TARGETARCH"
WORKDIR /build
COPY . .
COPY .git .
RUN echo "GO_TAGS: $GO_TAGS"
# We need protoc installed, and the version in 22.04 is too old.
RUN make prepare
# We need protoc installed, and the version in 22.04 is too old. We will create one as part installing the GRPC build below
# but that will also being in a newer version of absl which stablediffusion cannot compile with. This version of protoc is only
# here so that we can generate the grpc code for the stablediffusion build
RUN <<EOT bash
if [ "amd64" = "$TARGETARCH" ]; then
curl -L -s https://github.com/protocolbuffers/protobuf/releases/download/v27.1/protoc-27.1-linux-x86_64.zip -o protoc.zip && \
@@ -288,61 +256,22 @@ RUN <<EOT bash
fi
EOT
###################################
###################################
# stablediffusion does not tolerate a newer version of abseil, build it first
RUN GRPC_BACKENDS=backend-assets/grpc/stablediffusion make build
# Compile backends first in a separate stage
FROM builder-base AS builder-backends
ARG TARGETARCH
ARG TARGETVARIANT
# Install the pre-built GRPC
COPY --from=grpc /opt/grpc /usr/local
# Rebuild with defaults backends
WORKDIR /build
COPY ./Makefile .
COPY ./backend ./backend
COPY ./go.mod .
COPY ./go.sum .
COPY ./.git ./.git
# Some of the Go backends use libs from the main src, we could further optimize the caching by building the CPP backends before here
COPY ./pkg/grpc ./pkg/grpc
COPY ./pkg/utils ./pkg/utils
COPY ./pkg/langchain ./pkg/langchain
RUN ls -l ./
RUN make protogen-go
# The builder target compiles LocalAI. This target is not the target that will be uploaded to the registry.
# Adjustments to the build process should likely be made here.
FROM builder-backends AS builder
WORKDIR /build
COPY . .
## 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
###################################
###################################
# The devcontainer target is not used on CI. It is a target for developers to use locally -
# rather than copying files it mounts them locally and leaves building to the developer
FROM builder-base AS devcontainer
COPY .devcontainer-scripts /.devcontainer-scripts
RUN apt-get update && \
apt-get install -y --no-install-recommends \
ssh less
# For the devcontainer, leave apt functional in case additional devtools are needed at runtime.
RUN go install github.com/go-delve/delve/cmd/dlv@latest
RUN go install github.com/mikefarah/yq/v4@latest
RUN if [ ! -d "/build/sources/go-piper/piper-phonemize/pi/lib/" ]; then \
mkdir -p /build/sources/go-piper/piper-phonemize/pi/lib/ \
touch /build/sources/go-piper/piper-phonemize/pi/lib/keep \
; fi
###################################
###################################
@@ -351,27 +280,118 @@ 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 TARGETARCH
ARG IMAGE_TYPE=extras
ARG EXTRA_BACKENDS
ARG MAKEFLAGS
ENV BUILD_TYPE=${BUILD_TYPE}
ENV REBUILD=false
ENV HEALTHCHECK_ENDPOINT=http://localhost:8080/readyz
ENV MAKEFLAGS=${MAKEFLAGS}
ARG CUDA_MAJOR_VERSION=12
ENV NVIDIA_DRIVER_CAPABILITIES=compute,utility
ENV NVIDIA_REQUIRE_CUDA="cuda>=${CUDA_MAJOR_VERSION}.0"
ENV NVIDIA_VISIBLE_DEVICES=all
WORKDIR /
# Add FFmpeg
RUN if [ "${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/
# do not let stablediffusion rebuild (requires an older version of absl)
COPY --from=builder /build/backend-assets/grpc/stablediffusion ./backend-assets/grpc/stablediffusion
# Change the shell to bash so we can use [[ tests below
SHELL ["/bin/bash", "-c"]
# We try to strike a balance between individual layer size (as that affects total push time) and total image size
# Splitting the backends into more groups with fewer items results in a larger image, but a smaller size for the largest layer
# Splitting the backends into fewer groups with more items results in a smaller image, but a larger size for the largest layer
RUN if [[ ( "${EXTRA_BACKENDS}" =~ "coqui" || -z "${EXTRA_BACKENDS}" ) && "$IMAGE_TYPE" == "extras" ]]; then \
make -C backend/python/coqui \
; fi && \
if [[ ( "${EXTRA_BACKENDS}" =~ "parler-tts" || -z "${EXTRA_BACKENDS}" ) && "$IMAGE_TYPE" == "extras" ]]; then \
make -C backend/python/parler-tts \
; fi && \
if [[ ( "${EXTRA_BACKENDS}" =~ "diffusers" || -z "${EXTRA_BACKENDS}" ) && "$IMAGE_TYPE" == "extras" ]]; then \
make -C backend/python/diffusers \
; fi && \
if [[ ( "${EXTRA_BACKENDS}" =~ "transformers-musicgen" || -z "${EXTRA_BACKENDS}" ) && "$IMAGE_TYPE" == "extras" ]]; then \
make -C backend/python/transformers-musicgen \
; fi && \
if [[ ( "${EXTRA_BACKENDS}" =~ "exllama1" || -z "${EXTRA_BACKENDS}" ) && "$IMAGE_TYPE" == "extras" ]]; then \
make -C backend/python/exllama \
; fi
RUN if [[ ( "${EXTRA_BACKENDS}" =~ "vall-e-x" || -z "${EXTRA_BACKENDS}" ) && "$IMAGE_TYPE" == "extras" ]]; then \
make -C backend/python/vall-e-x \
; fi && \
if [[ ( "${EXTRA_BACKENDS}" =~ "openvoice" || -z "${EXTRA_BACKENDS}" ) && "$IMAGE_TYPE" == "extras" ]]; then \
make -C backend/python/openvoice \
; fi && \
if [[ ( "${EXTRA_BACKENDS}" =~ "petals" || -z "${EXTRA_BACKENDS}" ) && "$IMAGE_TYPE" == "extras" ]]; then \
make -C backend/python/petals \
; fi && \
if [[ ( "${EXTRA_BACKENDS}" =~ "sentencetransformers" || -z "${EXTRA_BACKENDS}" ) && "$IMAGE_TYPE" == "extras" ]]; then \
make -C backend/python/sentencetransformers \
; fi && \
if [[ ( "${EXTRA_BACKENDS}" =~ "exllama2" || -z "${EXTRA_BACKENDS}" ) && "$IMAGE_TYPE" == "extras" ]]; then \
make -C backend/python/exllama2 \
; fi && \
if [[ ( "${EXTRA_BACKENDS}" =~ "transformers" || -z "${EXTRA_BACKENDS}" ) && "$IMAGE_TYPE" == "extras" ]]; then \
make -C backend/python/transformers \
; fi
RUN if [[ ( "${EXTRA_BACKENDS}" =~ "vllm" || -z "${EXTRA_BACKENDS}" ) && "$IMAGE_TYPE" == "extras" ]]; then \
make -C backend/python/vllm \
; fi && \
if [[ ( "${EXTRA_BACKENDS}" =~ "autogptq" || -z "${EXTRA_BACKENDS}" ) && "$IMAGE_TYPE" == "extras" ]]; then \
make -C backend/python/autogptq \
; fi && \
if [[ ( "${EXTRA_BACKENDS}" =~ "bark" || -z "${EXTRA_BACKENDS}" ) && "$IMAGE_TYPE" == "extras" ]]; then \
make -C backend/python/bark \
; fi && \
if [[ ( "${EXTRA_BACKENDS}" =~ "rerankers" || -z "${EXTRA_BACKENDS}" ) && "$IMAGE_TYPE" == "extras" ]]; then \
make -C backend/python/rerankers \
; fi && \
if [[ ( "${EXTRA_BACKENDS}" =~ "mamba" || -z "${EXTRA_BACKENDS}" ) && "$IMAGE_TYPE" == "extras" ]]; then \
make -C backend/python/mamba \
; fi
# Make sure the models directory exists
RUN mkdir -p /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

1090
Makefile
View File

File diff suppressed because it is too large Load Diff

298
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>
@@ -30,283 +31,87 @@
<p align="center">
<a href="https://twitter.com/LocalAI_API" target="blank">
<img src="https://img.shields.io/badge/X-%23000000.svg?style=for-the-badge&logo=X&logoColor=white&label=LocalAI_API" alt="Follow LocalAI_API"/>
<img src="https://img.shields.io/twitter/follow/LocalAI_API?label=Follow: LocalAI_API&style=social" alt="Follow LocalAI_API"/>
</a>
<a href="https://discord.gg/uJAeKSAGDy" target="blank">
<img src="https://img.shields.io/badge/dynamic/json?color=blue&label=Discord&style=for-the-badge&query=approximate_member_count&url=https%3A%2F%2Fdiscordapp.com%2Fapi%2Finvites%2FuJAeKSAGDy%3Fwith_counts%3Dtrue&logo=discord" alt="Join LocalAI Discord Community"/>
<img src="https://dcbadge.vercel.app/api/server/uJAeKSAGDy?style=flat-square&theme=default-inverted" alt="Join LocalAI Discord Community"/>
</a>
</p>
<p align="center">
<a href="https://trendshift.io/repositories/5539" target="_blank"><img src="https://trendshift.io/api/badge/repositories/5539" alt="mudler%2FLocalAI | Trendshift" style="width: 250px; height: 55px;" width="250" height="55"/></a>
</p>
> :bulb: Get help - [❓FAQ](https://localai.io/faq/) [💭Discussions](https://github.com/go-skynet/LocalAI/discussions) [:speech_balloon: Discord](https://discord.gg/uJAeKSAGDy) [:book: Documentation website](https://localai.io/)
>
> [💻 Quickstart](https://localai.io/basics/getting_started/) [🖼️ Models](https://models.localai.io/) [🚀 Roadmap](https://github.com/mudler/LocalAI/issues?q=is%3Aissue+is%3Aopen+label%3Aroadmap) [🛫 Examples](https://github.com/mudler/LocalAI-examples) Try on
[![Telegram](https://img.shields.io/badge/Telegram-2CA5E0?style=for-the-badge&logo=telegram&logoColor=white)](https://t.me/localaiofficial_bot)
> [💻 Quickstart](https://localai.io/basics/getting_started/) [📣 News](https://localai.io/basics/news/) [ 🛫 Examples ](https://github.com/go-skynet/LocalAI/tree/master/examples/) [ 🖼️ Models ](https://localai.io/models/) [ 🚀 Roadmap ](https://github.com/mudler/LocalAI/issues?q=is%3Aissue+is%3Aopen+label%3Aroadmap)
[![tests](https://github.com/go-skynet/LocalAI/actions/workflows/test.yml/badge.svg)](https://github.com/go-skynet/LocalAI/actions/workflows/test.yml)[![Build and Release](https://github.com/go-skynet/LocalAI/actions/workflows/release.yaml/badge.svg)](https://github.com/go-skynet/LocalAI/actions/workflows/release.yaml)[![build container images](https://github.com/go-skynet/LocalAI/actions/workflows/image.yml/badge.svg)](https://github.com/go-skynet/LocalAI/actions/workflows/image.yml)[![Bump dependencies](https://github.com/go-skynet/LocalAI/actions/workflows/bump_deps.yaml/badge.svg)](https://github.com/go-skynet/LocalAI/actions/workflows/bump_deps.yaml)[![Artifact Hub](https://img.shields.io/endpoint?url=https://artifacthub.io/badge/repository/localai)](https://artifacthub.io/packages/search?repo=localai)
**LocalAI** is the free, Open Source OpenAI alternative. LocalAI act as a drop-in replacement REST API that's compatible with OpenAI (Elevenlabs, Anthropic... ) API specifications for local AI inferencing. It allows you to run LLMs, generate images, audio (and not only) locally or on-prem with consumer grade hardware, supporting multiple model families. Does not require GPU. It is created and maintained by [Ettore Di Giacinto](https://github.com/mudler).
**LocalAI** is the free, Open Source OpenAI alternative. LocalAI act as a drop-in replacement REST API thats compatible with OpenAI (Elevenlabs, Anthropic... ) API specifications for local AI inferencing. It allows you to run LLMs, generate images, audio (and not only) locally or on-prem with consumer grade hardware, supporting multiple model families. Does not require GPU. It is created and maintained by [Ettore Di Giacinto](https://github.com/mudler).
## Local Stack Family
Liking LocalAI? LocalAI is part of an integrated suite of AI infrastructure tools, you might also like:
- **[LocalAGI](https://github.com/mudler/LocalAGI)** - AI agent orchestration platform with OpenAI Responses API compatibility and advanced agentic capabilities
- **[LocalRecall](https://github.com/mudler/LocalRecall)** - MCP/REST API knowledge base system providing persistent memory and storage for AI agents
- 🆕 **[Cogito](https://github.com/mudler/cogito)** - Go library for building intelligent, co-operative agentic software and LLM-powered workflows, focusing on improving results for small, open source language models that scales to any LLM. Powers LocalAGI and LocalAI MCP/Agentic capabilities
- 🆕 **[Wiz](https://github.com/mudler/wiz)** - Terminal-based AI agent accessible via Ctrl+Space keybinding. Portable, local-LLM friendly shell assistant with TUI/CLI modes, tool execution with approval, MCP protocol support, and multi-shell compatibility (zsh, bash, fish)
- 🆕 **[SkillServer](https://github.com/mudler/skillserver)** - Simple, centralized skills database for AI agents via MCP. Manages skills as Markdown files with MCP server integration, web UI for editing, Git synchronization, and full-text search capabilities
## 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
> ⚠️ **Note:** The `install.sh` script is currently experiencing issues due to the heavy changes currently undergoing in LocalAI and may produce broken or misconfigured installations. Please use Docker installation (see below) or manual binary installation until [issue #8032](https://github.com/mudler/LocalAI/issues/8032) is resolved.
![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
### Containers (Docker, podman, ...)
> **💡 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:
Or run with docker:
```bash
docker run -ti --name local-ai -p 8080:8080 localai/localai:latest
```
#### 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
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
# 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
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
# Alternative images:
# - if you have an Nvidia GPU:
# docker run -ti --name local-ai -p 8080:8080 --gpus all localai/localai:latest-aio-gpu-nvidia-cuda-12
# - without preconfigured models
# docker run -ti --name local-ai -p 8080:8080 localai/localai:latest
# - without preconfigured models for Nvidia GPUs
# docker run -ti --name local-ai -p 8080:8080 --gpus all localai/localai:latest-gpu-nvidia-cuda-12
```
For more information about the AIO images and pre-downloaded models, see [Container Documentation](https://localai.io/basics/container/).
[💻 Getting started](https://localai.io/basics/getting_started/index.html)
To load models:
## 🔥🔥 Hot topics / Roadmap
```bash
# From the model gallery (see available models with `local-ai models list`, in the WebUI from the model tab, or visiting https://models.localai.io)
local-ai run llama-3.2-1b-instruct:q4_k_m
# Start LocalAI with the phi-2 model directly from huggingface
local-ai run huggingface://TheBloke/phi-2-GGUF/phi-2.Q8_0.gguf
# Install and run a model from the Ollama OCI registry
local-ai run ollama://gemma:2b
# Run a model from a configuration file
local-ai run https://gist.githubusercontent.com/.../phi-2.yaml
# Install and run a model from a standard OCI registry (e.g., Docker Hub)
local-ai run oci://localai/phi-2:latest
```
[Roadmap](https://github.com/mudler/LocalAI/issues?q=is%3Aissue+is%3Aopen+label%3Aroadmap)
> ⚡ **Automatic Backend Detection**: When you install models from the gallery or YAML files, LocalAI automatically detects your system's GPU capabilities (NVIDIA, AMD, Intel) and downloads the appropriate backend. For advanced configuration options, see [GPU Acceleration](https://localai.io/features/gpu-acceleration/#automatic-backend-detection).
For more information, see [💻 Getting started](https://localai.io/basics/getting_started/index.html), if you are interested in our roadmap items and future enhancements, you can see the [Issues labeled as Roadmap here](https://github.com/mudler/LocalAI/issues?q=is%3Aissue+is%3Aopen+label%3Aroadmap)
## 📰 Latest project news
- December 2025: [Dynamic Memory Resource reclaimer](https://github.com/mudler/LocalAI/pull/7583), [Automatic fitting of models to multiple GPUS(llama.cpp)](https://github.com/mudler/LocalAI/pull/7584), [Added Vibevoice backend](https://github.com/mudler/LocalAI/pull/7494)
- November 2025: Major improvements to the UX. Among these: [Import models via URL](https://github.com/mudler/LocalAI/pull/7245) and [Multiple chats and history](https://github.com/mudler/LocalAI/pull/7325)
- October 2025: 🔌 [Model Context Protocol (MCP)](https://localai.io/docs/features/mcp/) support added for agentic capabilities with external tools
- September 2025: New Launcher application for MacOS and Linux, extended support to many backends for Mac and Nvidia L4T devices. Models: Added MLX-Audio, WAN 2.2. WebUI improvements and Python-based backends now ships portable python environments.
- August 2025: MLX, MLX-VLM, Diffusers and llama.cpp are now supported on Mac M1/M2/M3+ chips ( with `development` suffix in the gallery ): https://github.com/mudler/LocalAI/pull/6049 https://github.com/mudler/LocalAI/pull/6119 https://github.com/mudler/LocalAI/pull/6121 https://github.com/mudler/LocalAI/pull/6060
- July/August 2025: 🔍 [Object Detection](https://localai.io/features/object-detection/) added to the API featuring [rf-detr](https://github.com/roboflow/rf-detr)
- July 2025: All backends migrated outside of the main binary. LocalAI is now more lightweight, small, and automatically downloads the required backend to run the model. [Read the release notes](https://github.com/mudler/LocalAI/releases/tag/v3.2.0)
- June 2025: [Backend management](https://github.com/mudler/LocalAI/pull/5607) has been added. Attention: extras images are going to be deprecated from the next release! Read [the backend management PR](https://github.com/mudler/LocalAI/pull/5607).
- May 2025: [Audio input](https://github.com/mudler/LocalAI/pull/5466) and [Reranking](https://github.com/mudler/LocalAI/pull/5396) in llama.cpp backend, [Realtime API](https://github.com/mudler/LocalAI/pull/5392), Support to Gemma, SmollVLM, and more multimodal models (available in the gallery).
- May 2025: Important: image name changes [See release](https://github.com/mudler/LocalAI/releases/tag/v2.29.0)
- Apr 2025: Rebrand, WebUI enhancements
- Apr 2025: [LocalAGI](https://github.com/mudler/LocalAGI) and [LocalRecall](https://github.com/mudler/LocalRecall) join the LocalAI family stack.
- Apr 2025: WebUI overhaul, AIO images updates
- Feb 2025: Backend cleanup, Breaking changes, new backends (kokoro, OutelTTS, faster-whisper), Nvidia L4T images
- Jan 2025: LocalAI model release: https://huggingface.co/mudler/LocalAI-functioncall-phi-4-v0.3, SANA support in diffusers: https://github.com/mudler/LocalAI/pull/4603
- Dec 2024: stablediffusion.cpp backend (ggml) added ( https://github.com/mudler/LocalAI/pull/4289 )
- Nov 2024: Bark.cpp backend added ( https://github.com/mudler/LocalAI/pull/4287 )
- Nov 2024: Voice activity detection models (**VAD**) added to the API: https://github.com/mudler/LocalAI/pull/4204
- Oct 2024: examples moved to [LocalAI-examples](https://github.com/mudler/LocalAI-examples)
- Aug 2024: 🆕 FLUX-1, [P2P Explorer](https://explorer.localai.io)
- July 2024: 🔥🔥 🆕 P2P Dashboard, LocalAI Federated mode and AI Swarms: https://github.com/mudler/LocalAI/pull/2723. P2P Global community pools: https://github.com/mudler/LocalAI/issues/3113
- July 2024: 🔥🔥 🆕 P2P Dashboard, LocalAI Federated mode and AI Swarms: https://github.com/mudler/LocalAI/pull/2723
- June 2024: 🆕 You can browse now the model gallery without LocalAI! Check out https://models.localai.io
- June 2024: Support for models from OCI registries: https://github.com/mudler/LocalAI/pull/2628
- May 2024: 🔥🔥 Decentralized P2P llama.cpp: https://github.com/mudler/LocalAI/pull/2343 (peer2peer llama.cpp!) 👉 Docs https://localai.io/features/distribute/
- May 2024: 🔥🔥 Openvoice: https://github.com/mudler/LocalAI/pull/2334
- May 2024: 🆕 Function calls without grammars and mixed mode: https://github.com/mudler/LocalAI/pull/2328
- May 2024: 🔥🔥 Distributed inferencing: https://github.com/mudler/LocalAI/pull/2324
- May 2024: Chat, TTS, and Image generation in the WebUI: https://github.com/mudler/LocalAI/pull/2222
- April 2024: Reranker API: https://github.com/mudler/LocalAI/pull/2121
Roadmap items: [List of issues](https://github.com/mudler/LocalAI/issues?q=is%3Aissue+is%3Aopen+label%3Aroadmap)
Hot topics (looking for contributors):
- WebUI improvements: https://github.com/mudler/LocalAI/issues/2156
- Backends v2: https://github.com/mudler/LocalAI/issues/1126
- Improving UX v2: https://github.com/mudler/LocalAI/issues/1373
- Assistant API: https://github.com/mudler/LocalAI/issues/1273
- Moderation endpoint: https://github.com/mudler/LocalAI/issues/999
- Vulkan: https://github.com/mudler/LocalAI/issues/1647
- Anthropic API: https://github.com/mudler/LocalAI/issues/1808
If you want to help and contribute, issues up for grabs: https://github.com/mudler/LocalAI/issues?q=is%3Aissue+is%3Aopen+label%3A%22up+for+grabs%22
## 🚀 [Features](https://localai.io/features/)
- 🧩 [Backend Gallery](https://localai.io/backends/): Install/remove backends on the fly, powered by OCI images — fully customizable and API-driven.
- 📖 [Text generation with GPTs](https://localai.io/features/text-generation/) (`llama.cpp`, `transformers`, `vllm` ... [:book: and more](https://localai.io/model-compatibility/index.html#model-compatibility-table))
- 📖 [Text generation with GPTs](https://localai.io/features/text-generation/) (`llama.cpp`, `gpt4all.cpp`, ... [:book: and more](https://localai.io/model-compatibility/index.html#model-compatibility-table))
- 🗣 [Text to Audio](https://localai.io/features/text-to-audio/)
- 🔈 [Audio to Text](https://localai.io/features/audio-to-text/) (Audio transcription with `whisper.cpp`)
- 🎨 [Image generation](https://localai.io/features/image-generation)
- 🎨 [Image generation with stable diffusion](https://localai.io/features/image-generation)
- 🔥 [OpenAI-alike tools API](https://localai.io/features/openai-functions/)
- ⚡ [Realtime API](https://localai.io/features/openai-realtime/) (Speech-to-speech)
- 🧠 [Embeddings generation for vector databases](https://localai.io/features/embeddings/)
- ✍️ [Constrained grammars](https://localai.io/features/constrained_grammars/)
- 🖼️ [Download Models directly from Huggingface ](https://localai.io/models/)
- 🥽 [Vision API](https://localai.io/features/gpt-vision/)
- 🔍 [Object Detection](https://localai.io/features/object-detection/)
- 📈 [Reranker API](https://localai.io/features/reranker/)
- 🆕🖧 [P2P Inferencing](https://localai.io/features/distribute/)
- 🆕🔌 [Model Context Protocol (MCP)](https://localai.io/docs/features/mcp/) - Agentic capabilities with external tools and [LocalAGI's Agentic capabilities](https://github.com/mudler/LocalAGI)
- 🔊 Voice activity detection (Silero-VAD support)
- 🌍 Integrated WebUI!
## 🧩 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 |
| **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 |
| **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 |
| **pocket-tts** | Lightweight CPU-based TTS | CUDA 12/13, ROCm, Intel, CPU |
| **qwen-tts** | High-quality TTS with custom voice, voice design, and 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, neutts, vibevoice, pocket-tts, qwen-tts | AMD Graphics |
| **Intel oneAPI** | llama.cpp, whisper, stablediffusion, vllm, transformers, diffusers, rfdetr, rerankers, coqui, kokoro, vibevoice, pocket-tts, qwen-tts | Intel Arc, Intel iGPUs |
| **Apple Metal** | llama.cpp, whisper, diffusers, MLX, MLX-VLM | 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
@@ -318,26 +123,12 @@ 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
OS Assistant:
- https://github.com/mudler/Keygeist - Keygeist is an AI-powered keyboard operator that listens for key combinations and responds with AI-generated text typed directly into your Linux box.
Model galleries
- https://github.com/go-skynet/model-gallery
Voice:
- https://github.com/richiejp/VoxInput
Other:
- Helm chart https://github.com/go-skynet/helm-charts
- VSCode extension https://github.com/badgooooor/localai-vscode-plugin
- Langchain: https://python.langchain.com/docs/integrations/providers/localai/
- Terminal utility https://github.com/djcopley/ShellOracle
- Local Smart assistant https://github.com/mudler/LocalAGI
- Home Assistant https://github.com/sammcj/homeassistant-localai / https://github.com/drndos/hass-openai-custom-conversation / https://github.com/valentinfrlch/ha-gpt4vision
@@ -345,9 +136,6 @@ Other:
- Slack bot https://github.com/mudler/LocalAGI/tree/main/examples/slack
- Shell-Pilot(Interact with LLM using LocalAI models via pure shell scripts on your Linux or MacOS system) https://github.com/reid41/shell-pilot
- Telegram bot https://github.com/mudler/LocalAI/tree/master/examples/telegram-bot
- Another Telegram Bot https://github.com/JackBekket/Hellper
- Auto-documentation https://github.com/JackBekket/Reflexia
- Github bot which answer on issues, with code and documentation as context https://github.com/JackBekket/GitHelper
- Github Actions: https://github.com/marketplace/actions/start-localai
- Examples: https://github.com/mudler/LocalAI/tree/master/examples/
@@ -362,7 +150,6 @@ Other:
## :book: 🎥 [Media, Blogs, Social](https://localai.io/basics/news/#media-blogs-social)
- [Run Visual studio code with LocalAI (SUSE)](https://www.suse.com/c/running-ai-locally/)
- 🆕 [Run LocalAI on Jetson Nano Devkit](https://mudler.pm/posts/local-ai-jetson-nano-devkit/)
- [Run LocalAI on AWS EKS with Pulumi](https://www.pulumi.com/blog/low-code-llm-apps-with-local-ai-flowise-and-pulumi/)
- [Run LocalAI on AWS](https://staleks.hashnode.dev/installing-localai-on-aws-ec2-instance)
@@ -395,17 +182,13 @@ 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)
@@ -426,6 +209,7 @@ LocalAI couldn't have been built without the help of great software already avai
- https://github.com/antimatter15/alpaca.cpp
- https://github.com/EdVince/Stable-Diffusion-NCNN
- https://github.com/ggerganov/whisper.cpp
- https://github.com/saharNooby/rwkv.cpp
- https://github.com/rhasspy/piper
## 🤗 Contributors

View File

@@ -1,8 +1,7 @@
embeddings: true
name: text-embedding-ada-002
backend: llama-cpp
backend: bert-embeddings
parameters:
model: huggingface://bartowski/granite-embedding-107m-multilingual-GGUF/granite-embedding-107m-multilingual-f16.gguf
model: huggingface://mudler/all-MiniLM-L6-v2/ggml-model-q4_0.bin
usage: |
You can test this model with curl like this:

View File

@@ -1,17 +1,56 @@
name: stablediffusion
backend: stablediffusion-ggml
cfg_scale: 4.5
options:
- sampler:euler
backend: stablediffusion
parameters:
model: stable-diffusion-v1-5-pruned-emaonly-Q4_0.gguf
step: 25
model: stablediffusion_assets
license: "BSD-3"
urls:
- https://github.com/EdVince/Stable-Diffusion-NCNN
- https://github.com/EdVince/Stable-Diffusion-NCNN/blob/main/LICENSE
description: |
Stable Diffusion in NCNN with c++, supported txt2img and img2img
download_files:
- filename: "stable-diffusion-v1-5-pruned-emaonly-Q4_0.gguf"
sha256: "b8944e9fe0b69b36ae1b5bb0185b3a7b8ef14347fe0fa9af6c64c4829022261f"
uri: "huggingface://second-state/stable-diffusion-v1-5-GGUF/stable-diffusion-v1-5-pruned-emaonly-Q4_0.gguf"
- filename: "stablediffusion_assets/AutoencoderKL-256-256-fp16-opt.param"
sha256: "18ca4b66685e21406bcf64c484b3b680b4949900415536d599cc876579c85c82"
uri: "https://raw.githubusercontent.com/EdVince/Stable-Diffusion-NCNN/main/x86/linux/assets/AutoencoderKL-256-256-fp16-opt.param"
- filename: "stablediffusion_assets/AutoencoderKL-512-512-fp16-opt.param"
sha256: "cf45f63aacf3dbbab0f59ed92a6f2c14d9a1801314631cd3abe91e3c85639a20"
uri: "https://raw.githubusercontent.com/EdVince/Stable-Diffusion-NCNN/main/x86/linux/assets/AutoencoderKL-512-512-fp16-opt.param"
- filename: "stablediffusion_assets/AutoencoderKL-base-fp16.param"
sha256: "0254a056dce61b0c27dc9ec1b78b53bcf55315c540f55f051eb841aa992701ba"
uri: "https://raw.githubusercontent.com/EdVince/Stable-Diffusion-NCNN/main/x86/linux/assets/AutoencoderKL-base-fp16.param"
- filename: "stablediffusion_assets/AutoencoderKL-encoder-512-512-fp16.bin"
sha256: "ddcb79a9951b9f91e05e087739ed69da2c1c4ae30ba4168cce350b49d617c9fa"
uri: "https://github.com/EdVince/Stable-Diffusion-NCNN/releases/download/naifu/AutoencoderKL-encoder-512-512-fp16.bin"
- filename: "stablediffusion_assets/AutoencoderKL-fp16.bin"
sha256: "f02e71f80e70252734724bbfaed5c4ddd3a8ed7e61bb2175ff5f53099f0e35dd"
uri: "https://github.com/EdVince/Stable-Diffusion-NCNN/releases/download/naifu/AutoencoderKL-fp16.bin"
- filename: "stablediffusion_assets/FrozenCLIPEmbedder-fp16.bin"
sha256: "1c9a12f4e1dd1b295a388045f7f28a2352a4d70c3dc96a542189a3dd7051fdd6"
uri: "https://github.com/EdVince/Stable-Diffusion-NCNN/releases/download/naifu/FrozenCLIPEmbedder-fp16.bin"
- filename: "stablediffusion_assets/FrozenCLIPEmbedder-fp16.param"
sha256: "471afbe678dd1fd3fe764ef9c6eccaccb0a7d7e601f27b462aa926b20eb368c9"
uri: "https://raw.githubusercontent.com/EdVince/Stable-Diffusion-NCNN/main/x86/linux/assets/FrozenCLIPEmbedder-fp16.param"
- filename: "stablediffusion_assets/log_sigmas.bin"
sha256: "a2089f8aa4c61f9c200feaec541ab3f5c94233b28deb6d5e8bcd974fa79b68ac"
uri: "https://github.com/EdVince/Stable-Diffusion-NCNN/raw/main/x86/linux/assets/log_sigmas.bin"
- filename: "stablediffusion_assets/UNetModel-256-256-MHA-fp16-opt.param"
sha256: "a58c380229f09491776df837b7aa7adffc0a87821dc4708b34535da2e36e3da1"
uri: "https://raw.githubusercontent.com/EdVince/Stable-Diffusion-NCNN/main/x86/linux/assets/UNetModel-256-256-MHA-fp16-opt.param"
- filename: "stablediffusion_assets/UNetModel-512-512-MHA-fp16-opt.param"
sha256: "f12034067062827bd7f43d1d21888d1f03905401acf6c6eea22be23c259636fa"
uri: "https://raw.githubusercontent.com/EdVince/Stable-Diffusion-NCNN/main/x86/linux/assets/UNetModel-512-512-MHA-fp16-opt.param"
- filename: "stablediffusion_assets/UNetModel-base-MHA-fp16.param"
sha256: "696f6975de49f4325b53ce32aff81861a6d6c07cd9ce3f0aae2cc405350af38d"
uri: "https://raw.githubusercontent.com/EdVince/Stable-Diffusion-NCNN/main/x86/linux/assets/UNetModel-base-MHA-fp16.param"
- filename: "stablediffusion_assets/UNetModel-MHA-fp16.bin"
sha256: "d618918d011bfc1f644c0f2a33bf84931bd53b28a98492b0a8ed6f3a818852c3"
uri: "https://github.com/EdVince/Stable-Diffusion-NCNN/releases/download/naifu/UNetModel-MHA-fp16.bin"
- filename: "stablediffusion_assets/vocab.txt"
sha256: "e30e57b6f1e47616982ef898d8922be24e535b4fa3d0110477b3a6f02ebbae7d"
uri: "https://raw.githubusercontent.com/EdVince/Stable-Diffusion-NCNN/main/x86/linux/assets/vocab.txt"
usage: |
curl http://localhost:8080/v1/images/generations \

View File

@@ -1,13 +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
name: gpt-4-vision-preview
roles:
user: "USER:"
assistant: "ASSISTANT:"
system: "SYSTEM:"
mmproj: bakllava-mmproj.gguf
parameters:
model: minicpm-v-4_5-Q4_K_M.gguf
stopwords:
- <|im_end|>
- <dummy32000>
- </s>
- <|endoftext|>
model: bakllava.gguf
template:
chat: |
{{.Input -}}
<|im_start|>assistant
chat_message: |
<|im_start|>{{ .RoleName }}
{{ if .FunctionCall -}}
Function call:
{{ else if eq .RoleName "tool" -}}
Function response:
{{ end -}}
{{ if .Content -}}
{{.Content }}
{{ end -}}
{{ if .FunctionCall -}}
{{toJson .FunctionCall}}
{{ end -}}<|im_end|>
completion: |
A chat between a curious human and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the human's questions.
{{.Input}}
function: |
<|im_start|>system
You are a function calling AI model. You are provided with functions to execute. You may call one or more functions to assist with the user query. Don't make assumptions about what values to plug into functions. Here are the available tools:
{{range .Functions}}
{'type': 'function', 'function': {'name': '{{.Name}}', 'description': '{{.Description}}', 'parameters': {{toJson .Parameters}} }}
{{end}}
For each function call return a json object with function name and arguments
<|im_end|>
{{.Input -}}
<|im_start|>assistant
ASSISTANT:
download_files:
- filename: minicpm-v-4_5-Q4_K_M.gguf
sha256: c1c3c33100b15b4caf7319acce4e23c0eb0ce1cbd12f70e8d24f05aa67b7512f
uri: huggingface://openbmb/MiniCPM-V-4_5-gguf/ggml-model-Q4_K_M.gguf
- filename: minicpm-v-4_5-mmproj-f16.gguf
uri: huggingface://openbmb/MiniCPM-V-4_5-gguf/mmproj-model-f16.gguf
sha256: 7a7225a32e8d453aaa3d22d8c579b5bf833c253f784cdb05c99c9a76fd616df8
- filename: bakllava.gguf
uri: huggingface://mys/ggml_bakllava-1/ggml-model-q4_k.gguf
- filename: bakllava-mmproj.gguf
uri: huggingface://mys/ggml_bakllava-1/mmproj-model-f16.gguf
usage: |
curl http://localhost:8080/v1/chat/completions -H "Content-Type: application/json" -d '{
"model": "gpt-4-vision-preview",
"messages": [{"role": "user", "content": [{"type":"text", "text": "What is in the image?"}, {"type": "image_url", "image_url": {"url": "https://upload.wikimedia.org/wikipedia/commons/thumb/d/dd/Gfp-wisconsin-madison-the-nature-boardwalk.jpg/2560px-Gfp-wisconsin-madison-the-nature-boardwalk.jpg" }}], "temperature": 0.9}]}'

View File

@@ -129,10 +129,10 @@ detect_gpu
detect_gpu_size
PROFILE="${PROFILE:-$GPU_SIZE}" # default to cpu
export MODELS="${MODELS:-/aio/${PROFILE}/embeddings.yaml,/aio/${PROFILE}/rerank.yaml,/aio/${PROFILE}/text-to-speech.yaml,/aio/${PROFILE}/image-gen.yaml,/aio/${PROFILE}/text-to-text.yaml,/aio/${PROFILE}/speech-to-text.yaml,/aio/${PROFILE}/vad.yaml,/aio/${PROFILE}/vision.yaml}"
export MODELS="${MODELS:-/aio/${PROFILE}/embeddings.yaml,/aio/${PROFILE}/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
name: gpt-4-vision-preview
roles:
user: "USER:"
assistant: "ASSISTANT:"
system: "SYSTEM:"
mmproj: llava-v1.6-7b-mmproj-f16.gguf
parameters:
model: minicpm-v-4_5-Q4_K_M.gguf
stopwords:
- <|im_end|>
- <dummy32000>
- </s>
- <|endoftext|>
model: llava-v1.6-mistral-7b.Q5_K_M.gguf
temperature: 0.2
top_k: 40
top_p: 0.95
seed: -1
template:
chat: |
{{.Input -}}
<|im_start|>assistant
chat_message: |
<|im_start|>{{ .RoleName }}
{{ if .FunctionCall -}}
Function call:
{{ else if eq .RoleName "tool" -}}
Function response:
{{ end -}}
{{ if .Content -}}
{{.Content }}
{{ end -}}
{{ if .FunctionCall -}}
{{toJson .FunctionCall}}
{{ end -}}<|im_end|>
completion: |
A chat between a curious human and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the human's questions.
{{.Input}}
function: |
<|im_start|>system
You are a function calling AI model. You are provided with functions to execute. You may call one or more functions to assist with the user query. Don't make assumptions about what values to plug into functions. Here are the available tools:
{{range .Functions}}
{'type': 'function', 'function': {'name': '{{.Name}}', 'description': '{{.Description}}', 'parameters': {{toJson .Parameters}} }}
{{end}}
For each function call return a json object with function name and arguments
<|im_end|>
{{.Input -}}
<|im_start|>assistant
ASSISTANT:
download_files:
- filename: minicpm-v-4_5-Q4_K_M.gguf
sha256: c1c3c33100b15b4caf7319acce4e23c0eb0ce1cbd12f70e8d24f05aa67b7512f
uri: huggingface://openbmb/MiniCPM-V-4_5-gguf/ggml-model-Q4_K_M.gguf
- filename: minicpm-v-4_5-mmproj-f16.gguf
uri: huggingface://openbmb/MiniCPM-V-4_5-gguf/mmproj-model-f16.gguf
sha256: 7a7225a32e8d453aaa3d22d8c579b5bf833c253f784cdb05c99c9a76fd616df8
- filename: llava-v1.6-mistral-7b.Q5_K_M.gguf
uri: huggingface://cjpais/llava-1.6-mistral-7b-gguf/llava-v1.6-mistral-7b.Q5_K_M.gguf
- filename: llava-v1.6-7b-mmproj-f16.gguf
uri: huggingface://cjpais/llava-1.6-mistral-7b-gguf/mmproj-model-f16.gguf
usage: |
curl http://localhost:8080/v1/chat/completions -H "Content-Type: application/json" -d '{
"model": "gpt-4-vision-preview",
"messages": [{"role": "user", "content": [{"type":"text", "text": "What is in the image?"}, {"type": "image_url", "image_url": {"url": "https://upload.wikimedia.org/wikipedia/commons/thumb/d/dd/Gfp-wisconsin-madison-the-nature-boardwalk.jpg/2560px-Gfp-wisconsin-madison-the-nature-boardwalk.jpg" }}], "temperature": 0.9}]}'

View File

@@ -1,8 +1,7 @@
embeddings: true
name: text-embedding-ada-002
backend: llama-cpp
backend: sentencetransformers
parameters:
model: huggingface://bartowski/granite-embedding-107m-multilingual-GGUF/granite-embedding-107m-multilingual-f16.gguf
model: all-MiniLM-L6-v2
usage: |
You can test this model with curl like this:

View File

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

View File

@@ -1,13 +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
name: gpt-4o
context_size: 4096
mmap: false
f16: false
name: gpt-4-vision-preview
roles:
user: "USER:"
assistant: "ASSISTANT:"
system: "SYSTEM:"
mmproj: llava-v1.6-7b-mmproj-f16.gguf
parameters:
model: minicpm-v-4_5-Q4_K_M.gguf
stopwords:
- <|im_end|>
- <dummy32000>
- </s>
- <|endoftext|>
model: llava-v1.6-mistral-7b.Q5_K_M.gguf
temperature: 0.2
top_k: 40
top_p: 0.95
seed: -1
template:
chat: |
{{.Input -}}
<|im_start|>assistant
chat_message: |
<|im_start|>{{ .RoleName }}
{{ if .FunctionCall -}}
Function call:
{{ else if eq .RoleName "tool" -}}
Function response:
{{ end -}}
{{ if .Content -}}
{{.Content }}
{{ end -}}
{{ if .FunctionCall -}}
{{toJson .FunctionCall}}
{{ end -}}<|im_end|>
completion: |
A chat between a curious human and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the human's questions.
{{.Input}}
function: |
<|im_start|>system
You are a function calling AI model. You are provided with functions to execute. You may call one or more functions to assist with the user query. Don't make assumptions about what values to plug into functions. Here are the available tools:
{{range .Functions}}
{'type': 'function', 'function': {'name': '{{.Name}}', 'description': '{{.Description}}', 'parameters': {{toJson .Parameters}} }}
{{end}}
For each function call return a json object with function name and arguments
<|im_end|>
{{.Input -}}
<|im_start|>assistant
ASSISTANT:
download_files:
- filename: minicpm-v-4_5-Q4_K_M.gguf
sha256: c1c3c33100b15b4caf7319acce4e23c0eb0ce1cbd12f70e8d24f05aa67b7512f
uri: huggingface://openbmb/MiniCPM-V-4_5-gguf/ggml-model-Q4_K_M.gguf
- filename: minicpm-v-4_5-mmproj-f16.gguf
uri: huggingface://openbmb/MiniCPM-V-4_5-gguf/mmproj-model-f16.gguf
sha256: 7a7225a32e8d453aaa3d22d8c579b5bf833c253f784cdb05c99c9a76fd616df8
- filename: llava-v1.6-mistral-7b.Q5_K_M.gguf
uri: huggingface://cjpais/llava-1.6-mistral-7b-gguf/llava-v1.6-mistral-7b.Q5_K_M.gguf
- filename: llava-v1.6-7b-mmproj-f16.gguf
uri: huggingface://cjpais/llava-1.6-mistral-7b-gguf/mmproj-model-f16.gguf
usage: |
curl http://localhost:8080/v1/chat/completions -H "Content-Type: application/json" -d '{
"model": "gpt-4-vision-preview",
"messages": [{"role": "user", "content": [{"type":"text", "text": "What is in the image?"}, {"type": "image_url", "image_url": {"url": "https://upload.wikimedia.org/wikipedia/commons/thumb/d/dd/Gfp-wisconsin-madison-the-nature-boardwalk.jpg/2560px-Gfp-wisconsin-madison-the-nature-boardwalk.jpg" }}], "temperature": 0.9}]}'

6
assets.go Normal file
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" = "$TARGETARCH" ]; then
wget "https://sdk.lunarg.com/sdk/download/1.4.335.0/linux/vulkansdk-linux-x86_64-1.4.335.0.tar.xz" && \
tar -xf vulkansdk-linux-x86_64-1.4.335.0.tar.xz && \
rm vulkansdk-linux-x86_64-1.4.335.0.tar.xz && \
mkdir -p /opt/vulkan-sdk && \
mv 1.4.335.0 /opt/vulkan-sdk/ && \
cd /opt/vulkan-sdk/1.4.335.0 && \
./vulkansdk --no-deps --maxjobs \
vulkan-loader \
vulkan-validationlayers \
vulkan-extensionlayer \
vulkan-tools \
shaderc && \
cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/bin/* /usr/bin/ && \
cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/lib/* /usr/lib/x86_64-linux-gnu/ && \
cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/include/* /usr/include/ && \
cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/share/* /usr/share/ && \
rm -rf /opt/vulkan-sdk
fi
if [ "arm64" = "$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" = "$TARGETARCH" ]; then
wget "https://sdk.lunarg.com/sdk/download/1.4.335.0/linux/vulkansdk-linux-x86_64-1.4.335.0.tar.xz" && \
tar -xf vulkansdk-linux-x86_64-1.4.335.0.tar.xz && \
rm vulkansdk-linux-x86_64-1.4.335.0.tar.xz && \
mkdir -p /opt/vulkan-sdk && \
mv 1.4.335.0 /opt/vulkan-sdk/ && \
cd /opt/vulkan-sdk/1.4.335.0 && \
./vulkansdk --no-deps --maxjobs \
vulkan-loader \
vulkan-validationlayers \
vulkan-extensionlayer \
vulkan-tools \
shaderc && \
cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/bin/* /usr/bin/ && \
cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/lib/* /usr/lib/x86_64-linux-gnu/ && \
cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/include/* /usr/include/ && \
cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/share/* /usr/share/ && \
rm -rf /opt/vulkan-sdk
fi
if [ "arm64" = "$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/1.4.335.0/linux/vulkansdk-linux-x86_64-1.4.335.0.tar.xz" && \
tar -xf vulkansdk-linux-x86_64-1.4.335.0.tar.xz && \
rm vulkansdk-linux-x86_64-1.4.335.0.tar.xz && \
mkdir -p /opt/vulkan-sdk && \
mv 1.4.335.0 /opt/vulkan-sdk/ && \
cd /opt/vulkan-sdk/1.4.335.0 && \
./vulkansdk --no-deps --maxjobs \
vulkan-loader \
vulkan-validationlayers \
vulkan-extensionlayer \
vulkan-tools \
shaderc && \
cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/bin/* /usr/bin/ && \
cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/lib/* /usr/lib/x86_64-linux-gnu/ && \
cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/include/* /usr/include/ && \
cp -rfv /opt/vulkan-sdk/1.4.335.0/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

@@ -1,211 +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**: 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
- **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

View File

@@ -14,14 +14,10 @@ service Backend {
rpc PredictStream(PredictOptions) returns (stream Reply) {}
rpc Embedding(PredictOptions) returns (EmbeddingResult) {}
rpc GenerateImage(GenerateImageRequest) returns (Result) {}
rpc GenerateVideo(GenerateVideoRequest) returns (Result) {}
rpc AudioTranscription(TranscriptRequest) returns (TranscriptResult) {}
rpc TTS(TTSRequest) returns (Result) {}
rpc TTSStream(TTSRequest) returns (stream Reply) {}
rpc SoundGeneration(SoundGenerationRequest) returns (Result) {}
rpc TokenizeString(PredictOptions) returns (TokenizationResponse) {}
rpc Status(HealthMessage) returns (StatusResponse) {}
rpc Detect(DetectOptions) returns (DetectResponse) {}
rpc StoresSet(StoresSetOptions) returns (Result) {}
rpc StoresDelete(StoresDeleteOptions) returns (Result) {}
@@ -29,23 +25,6 @@ service Backend {
rpc StoresFind(StoresFindOptions) returns (StoresFindResult) {}
rpc Rerank(RerankRequest) returns (RerankResult) {}
rpc GetMetrics(MetricsRequest) returns (MetricsResponse);
rpc VAD(VADRequest) returns (VADResponse) {}
rpc ModelMetadata(ModelOptions) returns (ModelMetadataResponse) {}
}
// Define the empty request
message MetricsRequest {}
message MetricsResponse {
int32 slot_id = 1;
string prompt_json_for_slot = 2; // Stores the prompt as a JSON string.
float tokens_per_second = 3;
int32 tokens_generated = 4;
int32 prompt_tokens_processed = 5;
}
message RerankRequest {
@@ -154,13 +133,6 @@ message PredictOptions {
repeated string Images = 42;
bool UseTokenizerTemplate = 43;
repeated Message Messages = 44;
repeated string Videos = 45;
repeated string Audios = 46;
string CorrelationId = 47;
string Tools = 48; // JSON array of available tools/functions for tool calling
string ToolChoice = 49; // JSON string or object specifying tool choice behavior
int32 Logprobs = 50; // Number of top logprobs to return (maps to OpenAI logprobs parameter)
int32 TopLogprobs = 51; // Number of top logprobs to return per token (maps to OpenAI top_logprobs parameter)
}
// The response message containing the result
@@ -168,14 +140,6 @@ message Reply {
bytes message = 1;
int32 tokens = 2;
int32 prompt_tokens = 3;
double timing_prompt_processing = 4;
double timing_token_generation = 5;
bytes audio = 6;
bytes logprobs = 7; // JSON-encoded logprobs data matching OpenAI format
}
message GrammarTrigger {
string word = 1;
}
message ModelOptions {
@@ -194,13 +158,18 @@ message ModelOptions {
string MainGPU = 13;
string TensorSplit = 14;
int32 Threads = 15;
string LibrarySearchPath = 16;
float RopeFreqBase = 17;
float RopeFreqScale = 18;
float RMSNormEps = 19;
int32 NGQA = 20;
string ModelFile = 21;
// AutoGPTQ
string Device = 22;
bool UseTriton = 23;
string ModelBaseName = 24;
bool UseFastTokenizer = 25;
// Diffusers
string PipelineType = 26;
@@ -233,12 +202,6 @@ message ModelOptions {
int32 SwapSpace = 53;
int32 MaxModelLen = 54;
int32 TensorParallelSize = 55;
string LoadFormat = 58;
bool DisableLogStatus = 66;
string DType = 67;
int32 LimitImagePerPrompt = 68;
int32 LimitVideoPerPrompt = 69;
int32 LimitAudioPerPrompt = 70;
string MMProj = 41;
@@ -250,24 +213,8 @@ message ModelOptions {
string Type = 49;
string FlashAttention = 56;
bool FlashAttention = 56;
bool NoKVOffload = 57;
string ModelPath = 59;
repeated string LoraAdapters = 60;
repeated float LoraScales = 61;
repeated string Options = 62;
string CacheTypeKey = 63;
string CacheTypeValue = 64;
repeated GrammarTrigger GrammarTriggers = 65;
bool Reranking = 71;
repeated string Overrides = 72;
}
message Result {
@@ -284,8 +231,6 @@ message TranscriptRequest {
string language = 3;
uint32 threads = 4;
bool translate = 5;
bool diarize = 6;
string prompt = 7;
}
message TranscriptResult {
@@ -299,12 +244,12 @@ message TranscriptSegment {
int64 end = 3;
string text = 4;
repeated int32 tokens = 5;
string speaker = 6;
}
message GenerateImageRequest {
int32 height = 1;
int32 width = 2;
int32 mode = 3;
int32 step = 4;
int32 seed = 5;
string positive_prompt = 6;
@@ -315,24 +260,6 @@ message GenerateImageRequest {
// Diffusers
string EnableParameters = 10;
int32 CLIPSkip = 11;
// Reference images for models that support them (e.g., Flux Kontext)
repeated string ref_images = 12;
}
message GenerateVideoRequest {
string prompt = 1;
string negative_prompt = 2; // Negative prompt for video generation
string start_image = 3; // Path or base64 encoded image for the start frame
string end_image = 4; // Path or base64 encoded image for the end frame
int32 width = 5;
int32 height = 6;
int32 num_frames = 7; // Number of frames to generate
int32 fps = 8; // Frames per second
int32 seed = 9;
float cfg_scale = 10; // Classifier-free guidance scale
int32 step = 11; // Number of inference steps
string dst = 12; // Output path for the generated video
}
message TTSRequest {
@@ -343,30 +270,6 @@ message TTSRequest {
optional string language = 5;
}
message VADRequest {
repeated float audio = 1;
}
message VADSegment {
float start = 1;
float end = 2;
}
message VADResponse {
repeated VADSegment segments = 1;
}
message SoundGenerationRequest {
string text = 1;
string model = 2;
string dst = 3;
optional float duration = 4;
optional float temperature = 5;
optional bool sample = 6;
optional string src = 7;
optional int32 src_divisor = 8;
}
message TokenizationResponse {
int32 length = 1;
repeated int32 tokens = 2;
@@ -391,31 +294,4 @@ message StatusResponse {
message Message {
string role = 1;
string content = 2;
// Optional fields for OpenAI-compatible message format
string name = 3; // Tool name (for tool messages)
string tool_call_id = 4; // Tool call ID (for tool messages)
string reasoning_content = 5; // Reasoning content (for thinking models)
string tool_calls = 6; // Tool calls as JSON string (for assistant messages with tool calls)
}
message DetectOptions {
string src = 1;
}
message Detection {
float x = 1;
float y = 2;
float width = 3;
float height = 4;
float confidence = 5;
string class_name = 6;
}
message DetectResponse {
repeated Detection Detections = 1;
}
message ModelMetadataResponse {
bool supports_thinking = 1;
string rendered_template = 2; // The rendered chat template with enable_thinking=true (empty if not applicable)
}
}

View File

@@ -1,167 +0,0 @@
LLAMA_VERSION?=2634ed207a17db1a54bd8df0555bd8499a6ab691
LLAMA_REPO?=https://github.com/ggerganov/llama.cpp
CMAKE_ARGS?=
BUILD_TYPE?=
NATIVE?=false
ONEAPI_VARS?=/opt/intel/oneapi/setvars.sh
TARGET?=--target grpc-server
JOBS?=$(shell nproc 2>/dev/null || sysctl -n hw.ncpu 2>/dev/null || echo 1)
ARCH?=$(shell uname -m)
# Disable Shared libs as we are linking on static gRPC and we can't mix shared and static
CMAKE_ARGS+=-DBUILD_SHARED_LIBS=OFF -DLLAMA_CURL=OFF
CURRENT_MAKEFILE_DIR := $(dir $(abspath $(lastword $(MAKEFILE_LIST))))
ifeq ($(NATIVE),false)
CMAKE_ARGS+=-DGGML_NATIVE=OFF -DLLAMA_OPENSSL=OFF
endif
# If build type is cublas, then we set -DGGML_CUDA=ON to CMAKE_ARGS automatically
ifeq ($(BUILD_TYPE),cublas)
CMAKE_ARGS+=-DGGML_CUDA=ON
# If build type is openblas then we set -DGGML_BLAS=ON -DGGML_BLAS_VENDOR=OpenBLAS
# to CMAKE_ARGS automatically
else ifeq ($(BUILD_TYPE),openblas)
CMAKE_ARGS+=-DGGML_BLAS=ON -DGGML_BLAS_VENDOR=OpenBLAS
# If build type is clblas (openCL) we set -DGGML_CLBLAST=ON -DCLBlast_DIR=/some/path
else ifeq ($(BUILD_TYPE),clblas)
CMAKE_ARGS+=-DGGML_CLBLAST=ON -DCLBlast_DIR=/some/path
# If it's hipblas we do have also to set CC=/opt/rocm/llvm/bin/clang CXX=/opt/rocm/llvm/bin/clang++
else ifeq ($(BUILD_TYPE),hipblas)
ROCM_HOME ?= /opt/rocm
ROCM_PATH ?= /opt/rocm
export CXX=$(ROCM_HOME)/llvm/bin/clang++
export CC=$(ROCM_HOME)/llvm/bin/clang
AMDGPU_TARGETS?=gfx803,gfx900,gfx906,gfx908,gfx90a,gfx942,gfx1010,gfx1030,gfx1032,gfx1100,gfx1101,gfx1102,gfx1200,gfx1201
CMAKE_ARGS+=-DGGML_HIP=ON -DAMDGPU_TARGETS=$(AMDGPU_TARGETS)
else ifeq ($(BUILD_TYPE),vulkan)
CMAKE_ARGS+=-DGGML_VULKAN=1
else ifeq ($(OS),Darwin)
ifeq ($(BUILD_TYPE),)
BUILD_TYPE=metal
endif
ifneq ($(BUILD_TYPE),metal)
CMAKE_ARGS+=-DGGML_METAL=OFF
else
CMAKE_ARGS+=-DGGML_METAL=ON
CMAKE_ARGS+=-DGGML_METAL_EMBED_LIBRARY=ON
CMAKE_ARGS+=-DGGML_METAL_USE_BF16=ON
CMAKE_ARGS+=-DGGML_OPENMP=OFF
endif
TARGET+=--target ggml-metal
endif
ifeq ($(BUILD_TYPE),sycl_f16)
CMAKE_ARGS+=-DGGML_SYCL=ON \
-DCMAKE_C_COMPILER=icx \
-DCMAKE_CXX_COMPILER=icpx \
-DCMAKE_CXX_FLAGS="-fsycl" \
-DGGML_SYCL_F16=ON
endif
ifeq ($(BUILD_TYPE),sycl_f32)
CMAKE_ARGS+=-DGGML_SYCL=ON \
-DCMAKE_C_COMPILER=icx \
-DCMAKE_CXX_COMPILER=icpx \
-DCMAKE_CXX_FLAGS="-fsycl"
endif
INSTALLED_PACKAGES=$(CURDIR)/../grpc/installed_packages
INSTALLED_LIB_CMAKE=$(INSTALLED_PACKAGES)/lib/cmake
ADDED_CMAKE_ARGS=-Dabsl_DIR=${INSTALLED_LIB_CMAKE}/absl \
-DProtobuf_DIR=${INSTALLED_LIB_CMAKE}/protobuf \
-Dutf8_range_DIR=${INSTALLED_LIB_CMAKE}/utf8_range \
-DgRPC_DIR=${INSTALLED_LIB_CMAKE}/grpc \
-DCMAKE_CXX_STANDARD_INCLUDE_DIRECTORIES=${INSTALLED_PACKAGES}/include
build-llama-cpp-grpc-server:
# Conditionally build grpc for the llama backend to use if needed
ifdef BUILD_GRPC_FOR_BACKEND_LLAMA
$(MAKE) -C ../../grpc build
_PROTOBUF_PROTOC=${INSTALLED_PACKAGES}/bin/proto \
_GRPC_CPP_PLUGIN_EXECUTABLE=${INSTALLED_PACKAGES}/bin/grpc_cpp_plugin \
PATH="${INSTALLED_PACKAGES}/bin:${PATH}" \
CMAKE_ARGS="${CMAKE_ARGS} ${ADDED_CMAKE_ARGS}" \
LLAMA_VERSION=$(LLAMA_VERSION) \
$(MAKE) -C $(CURRENT_MAKEFILE_DIR)/../$(VARIANT) grpc-server
else
echo "BUILD_GRPC_FOR_BACKEND_LLAMA is not defined."
LLAMA_VERSION=$(LLAMA_VERSION) $(MAKE) -C $(CURRENT_MAKEFILE_DIR)/../$(VARIANT) grpc-server
endif
llama-cpp-avx2: llama.cpp
cp -rf $(CURRENT_MAKEFILE_DIR)/../llama-cpp $(CURRENT_MAKEFILE_DIR)/../llama-cpp-avx2-build
$(MAKE) -C $(CURRENT_MAKEFILE_DIR)/../llama-cpp-avx2-build purge
$(info ${GREEN}I llama-cpp build info:avx2${RESET})
CMAKE_ARGS="$(CMAKE_ARGS) -DGGML_AVX=on -DGGML_AVX2=on -DGGML_AVX512=off -DGGML_FMA=on -DGGML_F16C=on" $(MAKE) VARIANT="llama-cpp-avx2-build" build-llama-cpp-grpc-server
cp -rfv $(CURRENT_MAKEFILE_DIR)/../llama-cpp-avx2-build/grpc-server llama-cpp-avx2
llama-cpp-avx512: llama.cpp
cp -rf $(CURRENT_MAKEFILE_DIR)/../llama-cpp $(CURRENT_MAKEFILE_DIR)/../llama-cpp-avx512-build
$(MAKE) -C $(CURRENT_MAKEFILE_DIR)/../llama-cpp-avx512-build purge
$(info ${GREEN}I llama-cpp build info:avx512${RESET})
CMAKE_ARGS="$(CMAKE_ARGS) -DGGML_AVX=on -DGGML_AVX2=off -DGGML_AVX512=on -DGGML_FMA=on -DGGML_F16C=on" $(MAKE) VARIANT="llama-cpp-avx512-build" build-llama-cpp-grpc-server
cp -rfv $(CURRENT_MAKEFILE_DIR)/../llama-cpp-avx512-build/grpc-server llama-cpp-avx512
llama-cpp-avx: llama.cpp
cp -rf $(CURRENT_MAKEFILE_DIR)/../llama-cpp $(CURRENT_MAKEFILE_DIR)/../llama-cpp-avx-build
$(MAKE) -C $(CURRENT_MAKEFILE_DIR)/../llama-cpp-avx-build purge
$(info ${GREEN}I llama-cpp build info:avx${RESET})
CMAKE_ARGS="$(CMAKE_ARGS) -DGGML_AVX=on -DGGML_AVX2=off -DGGML_AVX512=off -DGGML_FMA=off -DGGML_F16C=off -DGGML_BMI2=off" $(MAKE) VARIANT="llama-cpp-avx-build" build-llama-cpp-grpc-server
cp -rfv $(CURRENT_MAKEFILE_DIR)/../llama-cpp-avx-build/grpc-server llama-cpp-avx
llama-cpp-fallback: llama.cpp
cp -rf $(CURRENT_MAKEFILE_DIR)/../llama-cpp $(CURRENT_MAKEFILE_DIR)/../llama-cpp-fallback-build
$(MAKE) -C $(CURRENT_MAKEFILE_DIR)/../llama-cpp-fallback-build purge
$(info ${GREEN}I llama-cpp build info:fallback${RESET})
CMAKE_ARGS="$(CMAKE_ARGS) -DGGML_AVX=off -DGGML_AVX2=off -DGGML_AVX512=off -DGGML_FMA=off -DGGML_F16C=off -DGGML_BMI2=off" $(MAKE) VARIANT="llama-cpp-fallback-build" build-llama-cpp-grpc-server
cp -rfv $(CURRENT_MAKEFILE_DIR)/../llama-cpp-fallback-build/grpc-server llama-cpp-fallback
llama-cpp-grpc: llama.cpp
cp -rf $(CURRENT_MAKEFILE_DIR)/../llama-cpp $(CURRENT_MAKEFILE_DIR)/../llama-cpp-grpc-build
$(MAKE) -C $(CURRENT_MAKEFILE_DIR)/../llama-cpp-grpc-build purge
$(info ${GREEN}I llama-cpp build info:grpc${RESET})
CMAKE_ARGS="$(CMAKE_ARGS) -DGGML_RPC=ON -DGGML_AVX=off -DGGML_AVX2=off -DGGML_AVX512=off -DGGML_FMA=off -DGGML_F16C=off -DGGML_BMI2=off" TARGET="--target grpc-server --target rpc-server" $(MAKE) VARIANT="llama-cpp-grpc-build" build-llama-cpp-grpc-server
cp -rfv $(CURRENT_MAKEFILE_DIR)/../llama-cpp-grpc-build/grpc-server llama-cpp-grpc
llama-cpp-rpc-server: llama-cpp-grpc
cp -rf $(CURRENT_MAKEFILE_DIR)/../llama-cpp-grpc-build/llama.cpp/build/bin/rpc-server llama-cpp-rpc-server
llama.cpp:
mkdir -p llama.cpp
cd llama.cpp && \
git init && \
git remote add origin $(LLAMA_REPO) && \
git fetch origin && \
git checkout -b build $(LLAMA_VERSION) && \
git submodule update --init --recursive --depth 1 --single-branch
llama.cpp/tools/grpc-server: llama.cpp
mkdir -p llama.cpp/tools/grpc-server
bash prepare.sh
rebuild:
bash prepare.sh
rm -rf grpc-server
$(MAKE) grpc-server
package:
bash package.sh
purge:
rm -rf llama.cpp/build
rm -rf llama.cpp/tools/grpc-server
rm -rf grpc-server
clean: purge
rm -rf llama.cpp
grpc-server: llama.cpp llama.cpp/tools/grpc-server
@echo "Building grpc-server with $(BUILD_TYPE) build type and $(CMAKE_ARGS)"
ifneq (,$(findstring sycl,$(BUILD_TYPE)))
+bash -c "source $(ONEAPI_VARS); \
cd llama.cpp && mkdir -p build && cd build && cmake .. $(CMAKE_ARGS) && cmake --build . --config Release -j $(JOBS) $(TARGET)"
else
+cd llama.cpp && mkdir -p build && cd build && cmake .. $(CMAKE_ARGS) && cmake --build . --config Release -j $(JOBS) $(TARGET)
endif
cp llama.cpp/build/bin/grpc-server .

View File

File diff suppressed because it is too large Load Diff

View File

@@ -1,52 +0,0 @@
#!/bin/bash
# Script to copy the appropriate libraries based on architecture
# This script is used in the final stage of the Dockerfile
set -e
CURDIR=$(dirname "$(realpath $0)")
REPO_ROOT="${CURDIR}/../../.."
# Create lib directory
mkdir -p $CURDIR/package/lib
cp -avrf $CURDIR/llama-cpp-* $CURDIR/package/
cp -rfv $CURDIR/run.sh $CURDIR/package/
# Detect architecture and copy appropriate libraries
if [ -f "/lib64/ld-linux-x86-64.so.2" ]; then
# x86_64 architecture
echo "Detected x86_64 architecture, copying x86_64 libraries..."
cp -arfLv /lib64/ld-linux-x86-64.so.2 $CURDIR/package/lib/ld.so
cp -arfLv /lib/x86_64-linux-gnu/libc.so.6 $CURDIR/package/lib/libc.so.6
cp -arfLv /lib/x86_64-linux-gnu/libgcc_s.so.1 $CURDIR/package/lib/libgcc_s.so.1
cp -arfLv /lib/x86_64-linux-gnu/libstdc++.so.6 $CURDIR/package/lib/libstdc++.so.6
cp -arfLv /lib/x86_64-linux-gnu/libm.so.6 $CURDIR/package/lib/libm.so.6
cp -arfLv /lib/x86_64-linux-gnu/libgomp.so.1 $CURDIR/package/lib/libgomp.so.1
elif [ -f "/lib/ld-linux-aarch64.so.1" ]; then
# ARM64 architecture
echo "Detected ARM64 architecture, copying ARM64 libraries..."
cp -arfLv /lib/ld-linux-aarch64.so.1 $CURDIR/package/lib/ld.so
cp -arfLv /lib/aarch64-linux-gnu/libc.so.6 $CURDIR/package/lib/libc.so.6
cp -arfLv /lib/aarch64-linux-gnu/libgcc_s.so.1 $CURDIR/package/lib/libgcc_s.so.1
cp -arfLv /lib/aarch64-linux-gnu/libstdc++.so.6 $CURDIR/package/lib/libstdc++.so.6
cp -arfLv /lib/aarch64-linux-gnu/libm.so.6 $CURDIR/package/lib/libm.so.6
cp -arfLv /lib/aarch64-linux-gnu/libgomp.so.1 $CURDIR/package/lib/libgomp.so.1
else
echo "Error: Could not detect architecture"
exit 1
fi
# Package GPU libraries based on BUILD_TYPE
# The GPU library packaging script will detect BUILD_TYPE and copy appropriate GPU libraries
GPU_LIB_SCRIPT="${REPO_ROOT}/scripts/build/package-gpu-libs.sh"
if [ -f "$GPU_LIB_SCRIPT" ]; then
echo "Packaging GPU libraries for BUILD_TYPE=${BUILD_TYPE:-cpu}..."
source "$GPU_LIB_SCRIPT" "$CURDIR/package/lib"
package_gpu_libs
fi
echo "Packaging completed successfully"
ls -liah $CURDIR/package/
ls -liah $CURDIR/package/lib/

View File

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

View File

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

View File

@@ -1,3 +1,20 @@
## XXX: In some versions of CMake clip wasn't being built before llama.
## This is an hack for now, but it should be fixed in the future.
set(TARGET myclip)
add_library(${TARGET} clip.cpp clip.h llava.cpp llava.h)
install(TARGETS ${TARGET} LIBRARY)
target_include_directories(myclip PUBLIC .)
target_include_directories(myclip PUBLIC ../..)
target_include_directories(myclip PUBLIC ../../common)
target_link_libraries(${TARGET} PRIVATE common ggml llama ${CMAKE_THREAD_LIBS_INIT})
target_compile_features(${TARGET} PRIVATE cxx_std_11)
if (NOT MSVC)
target_compile_options(${TARGET} PRIVATE -Wno-cast-qual) # stb_image.h
endif()
# END CLIP hack
set(TARGET grpc-server)
set(CMAKE_CXX_STANDARD 17)
cmake_minimum_required(VERSION 3.15)
@@ -57,12 +74,8 @@ add_library(hw_grpc_proto
${hw_proto_srcs}
${hw_proto_hdrs} )
add_executable(${TARGET} grpc-server.cpp json.hpp httplib.h)
target_include_directories(${TARGET} PRIVATE ../llava)
target_include_directories(${TARGET} PRIVATE ${CMAKE_SOURCE_DIR})
target_link_libraries(${TARGET} PRIVATE common llama mtmd ${CMAKE_THREAD_LIBS_INIT} absl::flags hw_grpc_proto
add_executable(${TARGET} grpc-server.cpp utils.hpp json.hpp)
target_link_libraries(${TARGET} PRIVATE common llama myclip ${CMAKE_THREAD_LIBS_INIT} absl::flags hw_grpc_proto
absl::flags_parse
gRPC::${_REFLECTION}
gRPC::${_GRPC_GRPCPP}
@@ -70,4 +83,4 @@ target_link_libraries(${TARGET} PRIVATE common llama mtmd ${CMAKE_THREAD_LIBS_IN
target_compile_features(${TARGET} PRIVATE cxx_std_11)
if(TARGET BUILD_INFO)
add_dependencies(${TARGET} BUILD_INFO)
endif()
endif()

View File

@@ -0,0 +1,82 @@
LLAMA_VERSION?=
LLAMA_REPO?=https://github.com/ggerganov/llama.cpp
CMAKE_ARGS?=
BUILD_TYPE?=
ONEAPI_VARS?=/opt/intel/oneapi/setvars.sh
TARGET?=--target grpc-server
# Disable Shared libs as we are linking on static gRPC and we can't mix shared and static
CMAKE_ARGS+=-DBUILD_SHARED_LIBS=OFF
# If build type is cublas, then we set -DGGML_CUDA=ON to CMAKE_ARGS automatically
ifeq ($(BUILD_TYPE),cublas)
CMAKE_ARGS+=-DGGML_CUDA=ON
# If build type is openblas then we set -DGGML_BLAS=ON -DGGML_BLAS_VENDOR=OpenBLAS
# to CMAKE_ARGS automatically
else ifeq ($(BUILD_TYPE),openblas)
CMAKE_ARGS+=-DGGML_BLAS=ON -DGGML_BLAS_VENDOR=OpenBLAS
# If build type is clblas (openCL) we set -DGGML_CLBLAST=ON -DCLBlast_DIR=/some/path
else ifeq ($(BUILD_TYPE),clblas)
CMAKE_ARGS+=-DGGML_CLBLAST=ON -DCLBlast_DIR=/some/path
# If it's hipblas we do have also to set CC=/opt/rocm/llvm/bin/clang CXX=/opt/rocm/llvm/bin/clang++
else ifeq ($(BUILD_TYPE),hipblas)
CMAKE_ARGS+=-DGGML_HIPBLAS=ON
# If it's OSX, DO NOT embed the metal library - -DGGML_METAL_EMBED_LIBRARY=ON requires further investigation
# But if it's OSX without metal, disable it here
else ifeq ($(OS),Darwin)
ifneq ($(BUILD_TYPE),metal)
CMAKE_ARGS+=-DGGML_METAL=OFF
else
CMAKE_ARGS+=-DGGML_METAL=ON
# Until this is tested properly, we disable embedded metal file
# as we already embed it as part of the LocalAI assets
CMAKE_ARGS+=-DGGML_METAL_EMBED_LIBRARY=OFF
TARGET+=--target ggml-metal
endif
endif
ifeq ($(BUILD_TYPE),sycl_f16)
CMAKE_ARGS+=-DGGML_SYCL=ON -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx -DGGML_SYCL_F16=ON
endif
ifeq ($(BUILD_TYPE),sycl_f32)
CMAKE_ARGS+=-DGGML_SYCL=ON -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx
endif
llama.cpp:
mkdir -p llama.cpp
cd llama.cpp && \
git init && \
git remote add origin $(LLAMA_REPO) && \
git fetch origin && \
git checkout -b build $(LLAMA_VERSION) && \
git submodule update --init --recursive --depth 1 --single-branch
llama.cpp/examples/grpc-server: llama.cpp
mkdir -p llama.cpp/examples/grpc-server
bash prepare.sh
rebuild:
bash prepare.sh
rm -rf grpc-server
$(MAKE) grpc-server
purge:
rm -rf llama.cpp/build
rm -rf llama.cpp/examples/grpc-server
rm -rf grpc-server
clean: purge
rm -rf llama.cpp
grpc-server: llama.cpp llama.cpp/examples/grpc-server
@echo "Building grpc-server with $(BUILD_TYPE) build type and $(CMAKE_ARGS)"
ifneq (,$(findstring sycl,$(BUILD_TYPE)))
+bash -c "source $(ONEAPI_VARS); \
cd llama.cpp && mkdir -p build && cd build && cmake .. $(CMAKE_ARGS) && cmake --build . --config Release $(TARGET)"
else
+cd llama.cpp && mkdir -p build && cd build && cmake .. $(CMAKE_ARGS) && cmake --build . --config Release $(TARGET)
endif
cp llama.cpp/build/bin/grpc-server .

View File

File diff suppressed because it is too large Load Diff

24596
backend/cpp/llama/json.hpp Normal file
View File

File diff suppressed because it is too large Load Diff

Some files were not shown because too many files have changed in this diff Show More